479,078 results on '"Vieira WAS"'
Search Results
2. Parabola or Second-Degree Polynomial Function Exploration in Initial Teacher Training: Integrating Intuition and Didactic Situations
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Renata Teófilo de Sousa, Francisco Régis Vieira Alves, and Helena Maria Barros de Campos
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This work is the result of a master's investigation in Brazil, which discusses the teaching of the parabola in the initial training of mathematics teachers. Our theoretical framework addresses the relationship between intuition and the dialectics of the theory of didactic situations, which supports the analysis of the results of this study Its objective was to identify and register categories of intuitive reasoning manifested by the subjects when solving a didactic situation involving the parabola with GeoGebra software contribution. The methodology adopted was didactic engineering, experimented with eight students in initial training at a Brazilian public university, among 6th and 9th undergraduate semesters. The posterior analysis and validation allowed us to verify the need to discuss the parabola, articulating its geometric, algebraic, and analytical views, as well as to reinforce the importance of its teaching with the use of technology.
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- 2024
3. Understanding Engagement in Intensive Learning: From Fuzzy Chaotic Indigestion to Eupeptic Clarity
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Reilly A. Dempsey Willis and Paulo Vieira Braga
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This paper is framed by Nick Zepke's, Vicki Trowler's, and Paul Trowler's concept of student engagement being "chaotic", suffering from "indigestion" and "fuzziness". This study was conducted at a UK higher education institution that recently moved to a "block and blend" delivery approach. We investigated what students and staff think engagement looks like in an intensive block and blend learning context. Data were gathered from students and staff via an online survey, which consisted of both scaled and open-ended questions. Findings are synthesised in an elemental map, providing a comparison of students and staff perceptions of engagement. Specifically, students and staff thought engagement in an intensive block and blend context entailed participation and active learning; a mindset that included enthusiasm, interest, focus, and enjoyment; timely completion of assessments; relationships with peers and tutors; doing more than required, such as completing extra readings; and accessing help and support. Participants also identified attendance as an indicator of student engagement and determined that the university has a responsibility to create learning environments to foster student engagement. Overall, the study findings point to elements of student engagement that may be designed into intensive block and blend learning environments. These approaches are also relevant to other similar intensive learning contexts.
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- 2024
4. Student and Faculty Perceptions of Summative Assessment Methods in a Block and Blend Mode of Delivery
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Paulo Ricardo Vieira Braga, Carmen Maria Ortiz Granero, and Ellen Buck
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The recent increase in the number of higher education institutions adopting block teaching has prompted questions about the appropriateness of assessment methods that were commonly used in a semesterised delivery model. This paper explores student and faculty perceptions of summative assessment methods in a block and blend mode of delivery at a higher education institution in the United Kingdom. In this study, we used a convergent mixed methods approach to explore student and faculty perceptions of different assessment methods as accurate evaluations of learning using surveys, combining Likert-type and open-ended questions. The findings highlight how traditional, single assessment methods occurring at the end of a block were perceived as less accurate in evaluating learning when compared to multiple smaller assessments that occur throughout a block. The thematic analysis revealed the latter was perceived as allowing for a broader range of skills to be evaluated while simultaneously facilitating effective workload management and timely feedback. These outcomes indicate the need for assessment redesign that considers the characteristics of a block and blend mode of delivery and illuminates the shared perception of students and faculty that multiple smaller assessments are more accurate evaluations of learning. Further research with larger, more diverse samples, accommodating for different fields of study, could further our understanding of effective assessment methods and inform our practice in a block and blend mode of delivery.
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- 2024
5. Hadronic scattering effects on $\psi(2S)$ suppression in relativistic heavy-ion collisions
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Abreu, L. M., Navarra, F. S., and Vieira, H. P. L.
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High Energy Physics - Phenomenology - Abstract
In this work we estimate the $N_{\psi(2S)} / N_{J/\psi}$ yield ratio in heavy-ion collisions, considering the interactions of the $\psi (2S) $ and $J/\psi$ states with light mesons in the hadron gas formed at the late stages of these collisions. Starting from the appropriate effective Lagrangians, we first compute the thermally-averaged cross sections for the production and absorption of the mentioned states, and then use them as input in the rate equations to determine the time evolution of $N_{\psi(2S)}$, $N_{J/\psi}$ and $N_{\psi(2S)} / N_{J/\psi}$. The main conclusion of our study is that the $\psi (2S) $ and $J/\psi$ multiplicities do not change much in the hadron gas phase and that the $\psi (2S)$ is more absorbed than the $J/\psi$. The obtained final ratio is in qualitative agreement with experimental data., Comment: 8 pages, 6 figures
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- 2024
6. VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
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Zibaeirad, Arastoo and Vieira, Marco
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Computer Science - Software Engineering ,Computer Science - Artificial Intelligence - Abstract
Large Language Models (LLMs) have shown promise in tasks like code translation, prompting interest in their potential for automating software vulnerability detection (SVD) and patching (SVP). To further research in this area, establishing a benchmark is essential for evaluating the strengths and limitations of LLMs in these tasks. Despite their capabilities, questions remain regarding whether LLMs can accurately analyze complex vulnerabilities and generate appropriate patches. This paper introduces VulnLLMEval, a framework designed to assess the performance of LLMs in identifying and patching vulnerabilities in C code. Our study includes 307 real-world vulnerabilities extracted from the Linux kernel, creating a well-curated dataset that includes both vulnerable and patched code. This dataset, based on real-world code, provides a diverse and representative testbed for evaluating LLM performance in SVD and SVP tasks, offering a robust foundation for rigorous assessment. Our results reveal that LLMs often struggle with distinguishing between vulnerable and patched code. Furthermore, in SVP tasks, these models tend to oversimplify the code, producing solutions that may not be directly usable without further refinement.
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- 2024
7. Improving parameters estimation in Gaussian channels using quantum coherence
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Santos, Jonas F. G., Vieira, Carlos H. S., and Cardoso, Wilder R.
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Quantum Physics - Abstract
Gaussian quantum channels are relevant operations in continuous variable systems. In general, given an arbitrary state, the action on it is well-known provided that the quantum channels are completely characterized. In this work, we consider the inverse problem, i.e., the estimation of channel parameters employing probes in which quantum coherence is used as a resource. Two paradigmatic bosonic Gaussian channels are treated, the thermal attenuator and the thermal amplifier. We also consider the degradation of the coherence due to a Markovian bath. The quantum Fisher information for each relevant parameter is computed and we observed that the rate of change of coherence concerning the channel parameter, rather than the amount of coherence, can produce a parameter estimation gain. Finally, we obtain a direct relation between the quantum Fisher information and the relative entropy or coherence, allowing in principle an experimental implementation based on the measurement of the covariance matrix of the probe system.
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- 2024
8. Thermal Conductivity of Metastable Ionic Liquid [$C_{2}mim$][$CH_{3}SO_{3}$]
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Lozano-Martín, Daniel, Vieira, Salomé Inês Cardoso, Paredes, Xavier, Lourenço, Maria José Vitoriano, de Castro, Carlos A. Nieto, Sengers, Jan V., and Massonne, Klemens
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Physics - Chemical Physics - Abstract
Ionic liquids have been suggested as new engineering fluids, namely in the area of heat transfer, as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and dimethyl polysiloxane oils, which degrade above 200 {\deg}C and pose some environmental problems. Recently, we have proposed 1-ethyl-3-methylimidazolium methanesulfonate, [$C_{2}mim$][$CH_{3}SO_{3}$], as a new heat transfer fluid, because of its thermophysical and toxicological properties. However, there are some interesting points raised in this work, namely the possibility of the existence of liquid metastability below the melting point (303 K) or second order-disorder transitions ($\lambda$-type) before reaching the calorimetric freezing point. This paper analyses in more detail this zone of the phase diagram of the pure fluid, by reporting accurate thermal-conductivity measurements between 278 and 355 K with an estimated uncertainty of 2% at a 95% confidence level. A new value of the melting temperature is also reported, $T_{melt}$ = 307.8 $\pm$ 1 K. Results obtained support liquid metastability behaviour in the solid-phase region and permit the use of this ionic liquid at a heat transfer fluid at temperatures below its melting point. Thermal conductivity models based on Bridgman theory and estimation formulas were also used in this work, failing to predict the experimental data within its uncertainty.
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- 2024
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9. Extended symmetry of higher Painlev\'e equations of even periodicity and their rational solutions
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Aratyn, Henrik, Gomes, José Francisco, Lobo, Gabriel Vieira, and Zimerman, Abraham Hirsz
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Nonlinear Sciences - Exactly Solvable and Integrable Systems - Abstract
The structure of extended affine Weyl symmetry group of higher Painlev\'e equations of $N$ periodicity depends on whether $N$ is even or odd. We find that for even $N$, the symmetry group ${\widehat A}^{(1)}_{N-1}$ contains the conventional B\"acklund transformations $s_j, j=1,{\ldots},N$, the group of automorphisms consisting of cycling permutations but also reflections on a periodic circle of $N$ points, which is a novel feature uncovered in this paper. The presence of reflection automorphisms is connected to existence of degenerated solutions and for $N=4$ we explicitly show how the reflection automorphisms around even points cause degeneracy of a class of rational solutions obtained on the orbit of translation operators of ${\widehat A}^{(1)}_{3}$. We obtain the closed expressions for solutions and their degenerated counterparts in terms of determinants of Kummer polynomials., Comment: 26 pages
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- 2024
10. How Much Data is Enough Data? Fine-Tuning Large Language Models for In-House Translation: Performance Evaluation Across Multiple Dataset Sizes
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Vieira, Inacio, Allred, Will, Lankford, Séamus, Castilho, Sheila, and Way, Andy
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Decoder-only LLMs have shown impressive performance in MT due to their ability to learn from extensive datasets and generate high-quality translations. However, LLMs often struggle with the nuances and style required for organisation-specific translation. In this study, we explore the effectiveness of fine-tuning Large Language Models (LLMs), particularly Llama 3 8B Instruct, leveraging translation memories (TMs), as a valuable resource to enhance accuracy and efficiency. We investigate the impact of fine-tuning the Llama 3 model using TMs from a specific organisation in the software sector. Our experiments cover five translation directions across languages of varying resource levels (English to Brazilian Portuguese, Czech, German, Finnish, and Korean). We analyse diverse sizes of training datasets (1k to 207k segments) to evaluate their influence on translation quality. We fine-tune separate models for each training set and evaluate their performance based on automatic metrics, BLEU, chrF++, TER, and COMET. Our findings reveal improvement in translation performance with larger datasets across all metrics. On average, BLEU and COMET scores increase by 13 and 25 points, respectively, on the largest training set against the baseline model. Notably, there is a performance deterioration in comparison with the baseline model when fine-tuning on only 1k and 2k examples; however, we observe a substantial improvement as the training dataset size increases. The study highlights the potential of integrating TMs with LLMs to create bespoke translation models tailored to the specific needs of businesses, thus enhancing translation quality and reducing turn-around times. This approach offers a valuable insight for organisations seeking to leverage TMs and LLMs for optimal translation outcomes, especially in narrower domains.
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- 2024
11. Light-Ray Wave Functions and Integrability
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Homrich, Alexandre, Simmons-Duffin, David, and Vieira, Pedro
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High Energy Physics - Theory - Abstract
Using integrability, we construct (to leading order in perturbation theory) the explicit form of twist-three light-ray operators in planar $\mathcal{N}=4$ SYM. This construction allows us to directly compute analytically continued CFT data at complex spin. We derive analytically the "magic'' decoupling zeroes previously observed numerically. Using the Baxter equation, we also show that certain Regge trajectories merge together into a single unifying Riemann surface. Perhaps more surprisingly, we find that this unification of Regge trajectories is not unique. If we organize twist-three operators differently into what we call "cousin trajectories'' we find infinitely more possible continuations. We speculate about which of these remarkable features of twist-three operators might generalize to other operators, other regimes and other theories., Comment: 52 pages, 15 figures
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- 2024
12. Enhancing Gaussian quantum metrology with position-momentum correlations
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Porto, João C. P., Marinho, Lucas S., Dieguez, Pedro R., da Paz, Irismar G., and Vieira, Carlos H. S.
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Quantum Physics - Abstract
Quantum metrology offers significant improvements in several quantum technologies. In this work, we propose a Gaussian quantum metrology protocol assisted by initial position-momentum correlations (PM). We employ a correlated Gaussian wave packet as a probe to examine the dynamics of Quantum Fisher Information (QFI) and purity based on PM correlations to demonstrate how to estimate the PM correlations and, more importantly, to unlock its potential applications such as a resource to enhance quantum thermometry. In the low-temperature regime, we find an improvement in the thermometry of the surrounding environment when the original system exhibits a non-null initial correlation (correlated Gaussian state). In addition, we explore the connection between the loss of purity and the gain in QFI during the process of estimating the effective environment coupling and its effective temperature.
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- 2024
13. DUNE Phase II: Scientific Opportunities, Detector Concepts, Technological Solutions
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D. M., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Barham~Alzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cortez, A. F. V., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Fernández-Posada, D., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., M~Gago, A., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, F. Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hart, A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C. M., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Hellmuth, P., Henry, S., Hernández-García, J., Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., Kim, M. J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kuźniak, M., Kvasnicka, J., Labree, T., Lackey, T., Lalău, I., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Laycock, P., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., -Y~Li, J., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Mameli, S., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Micallef, J., Miccoli, A., Michna, G., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, P., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, A., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Gann, G. D. Orebi, Osbiston, M., Vélez, J. A. Osorio, O'Sullivan, L., Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pincha, S., Pinchault, J., Pitts, K., Plows, K., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Paix{ã}o, L. G. Porto, Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Queen, J., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Raffaelli, F., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Diego~Restrepo, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ruiz, G., Russell, B., Ruterbories, D., Rybnikov, A., Sacerdoti, S., Saha, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sánchez-Castillo, A., Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senadheera, D., Senise, C. R., Sensenig, J., Seo, S. H., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Poudel, S. Sharma, Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, J., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turnberg, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Hernandez, A. P. Vizcaya, Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Westerdale, S., Wetstein, M., Whalen, K., White, A., Whitehead, L. H., Whittington, D., Wilhlemi, J., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, J., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
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Physics - Instrumentation and Detectors ,High Energy Physics - Experiment - Abstract
The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a "Module of Opportunity", aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.
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- 2024
14. Report on the Advanced Linear Collider Study Group (ALEGRO) Workshop 2024
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Vieira, J., Cros, B., Muggli, P., Andriyash, I. A., Apsimon, O., Backhouse, M., Benedetti, C., Bulanov, S. S., Caldwell, A., Chen, Min, Cilento, V., Corde, S., D'Arcy, R., Diederichs, S., Ericson, E., Esarey, E., Farmer, J., Fedeli, L., Formenti, A., Foster, B., Garten, M., Geddes, C. G. R., Grismayer, T., Hogan, M. J., Hooker, S., Huebl, A., Jalas, S., Kirchen, M., Lehe, R., Leemans, W., Li, Boyuan, Lindström, C. A., Losito, R., Mitchell, C. E., Mori, W. B., Piot, P., Terzani, D., Thévenet, M., Turner, M., Vay, J. -L., Völker, D., Zhang, Jie, and Zhang, W.
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Physics - Accelerator Physics - Abstract
The workshop focused on the application of ANAs to particle physics keeping in mind the ultimate goal of a collider at the energy frontier (10\,TeV, e$^+$/e$^-$, e$^-$/e$^-$, or $\gamma\gamma$). The development of ANAs is conducted at universities and national laboratories worldwide. The community is thematically broad and diverse, in particular since lasers suitable for ANA research (multi-hundred-terawatt peak power, a few tens of femtosecond-long pulses) and acceleration of electrons to hundreds of mega electron volts to multi giga electron volts became commercially available. The community spans several continents (Europe, America, Asia), including more than 62 laboratories in more than 20 countries. It is among the missions of the ICFA-ANA panel to feature the amazing progress made with ANAs, to provide international coordination and to foster international collaborations towards a future HEP collider. The scope of this edition of the workshop was to discuss the recent progress and necessary steps towards realizing a linear collider for particle physics based on novel-accelerator technologies (laser or beam driven in plasma or structures). Updates on the relevant aspects of the European Strategy for Particle Physics (ESPP) Roadmap Process as well as of the P5 (in the US) were presented, and ample time was dedicated to discussions. The major outcome of the workshop is the decision for ALEGRO to coordinate efforts in Europe, in the US, and in Asia towards a pre-CDR for an ANA-based, 10\,TeV CM collider. This goal of this coordination is to lead to a funding proposal to be submitted to both EU and EU/US funding agencies. This document presents a summary of the workshop, as seen by the co-chairs, as well as short 'one-pagers' written by the presenters at the workshop., Comment: 72 pages
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- 2024
15. First Measurement of the Total Inelastic Cross-Section of Positively-Charged Kaons on Argon at Energies Between 5.0 and 7.5 GeV
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Barham~Alzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., M~Gago, A., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. 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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and 7 GeV/$c$ beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam momentum setting was measured to be 380$\pm$26 mbarns for the 6 GeV/$c$ setting and 379$\pm$35 mbarns for the 7 GeV/$c$ setting.
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- 2024
16. Peer-to-Peer (P2P) Electricity Markets for Low Voltage Networks
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Fernandes, Diana Vieira, Christin, Nicolas, and Kar, Soummya
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Mathematics - Optimization and Control ,49 ,I.2.8 - Abstract
We develop a clearance and settlement model for Peer-to-Peer (P2P) energy trading in low-voltage networks. The model enables direct transactions between parties within an open and distributed system and integrates unused capacity while respecting network constraints. We evaluate the model through simulations of different scenarios (normal operating conditions and extreme conditions) for 24-hour time blocks. Our simulations highlight the benefits of our model in a decentralized energy system, notably its ability to deal with high-trade volumes., Comment: To appear in IEEE SmartGridComm'24 - 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
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- 2024
17. Constraints on the $\gamma$-parameter for the vacuum solution of Cotton gravity with geodesics and shadows
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Junior, Ednaldo L. B., Junior, José Tarciso S. S., Lobo, Francisco S. N., Rodrigues, Manuel E., Rubiera-Garcia, Diego, da Silva, Luís F. Dias, and Vieira, Henrique A.
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General Relativity and Quantum Cosmology ,Astrophysics - High Energy Astrophysical Phenomena ,High Energy Physics - Theory - Abstract
We consider a recently introduced extension of General Relativity dubbed as Cotton gravity (CG), based on the use of the Cotton tensor, to estimate the size of a new constant $\gamma$ appearing within a spherically symmetric, vacuum solution of the theory. Taking into account its non-asymptotically flat character, we use the inferred size of the central brightness depression of the supermassive object at the heart of the Milky Way galaxy (Sgr A*) by the Event Horizon Telescope to constrain at $2\sigma$ the CG parameter as $\gamma M \approx 3.5 \times 10^{-12}$. We study the potential observational consequences from the smallness of such a value using exact and numerical expressions for the deflection angle, optical images from optically and geometrically thin accretion disks, isoradials, and instability scales (Lyapunov index) of nearly bound geodesics associated to photon rings. Our results point towards the impossibility to distinguish between these two geometries using current and foreseeable techniques in the field of interferometric detection of optical sources., Comment: 13 pages, 8 figures
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- 2024
18. Black bounces in Cotton gravity
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Junior, Ednaldo L. B., Junior, José Tarciso S. S., Lobo, Francisco S. N., Rodrigues, Manuel E., Rubiera-Garcia, Diego, da Silva, Luís F. Dias, and Vieira, Henrique A.
- Subjects
General Relativity and Quantum Cosmology ,High Energy Physics - Theory - Abstract
Recently, J. Harada proposed a theory relating gravity to the Cotton tensor, dubbed as ''Cotton gravity'' (CG). This is an extension of General Relativity such that every solution of the latter turns out to be a solution of the former (but the converse is not true) and, furthermore, it is possible to derive the cosmological constant as an integration constant within it. In this work we investigate CG by coupling it to both non-linear electrodynamics (NLED) and scalar fields. We study static and spherically symmetric solutions implementing a bouncing behaviour in the radial function so as to avoid the development of singularities, inspired by the Simpson-Visser black bounce and the Bardeen model, both interpreted as magnetic monopoles. We identify the NLED Lagrangian density and the scalar field potential generating such solutions, and investigate the corresponding gravitational configurations in terms of horizons, behaviour of the metric functions, and regularity of the Kretchsman curvature scalar. Our analysis extends the class of non-singular geometries found in the literature and paves the ground for further analysis of black holes in CG., Comment: 14 pages, 6 figures
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- 2024
19. A certain sequence on pure $\kappa-$sparse gapsets
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Brito, Gilberto and Vieira, Stéfani
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Mathematics - Combinatorics ,20M14 (Primary), 05A15, 05A19 (Secondary) - Abstract
In this paper, we study the pure $\kappa-$sparse gapsets and our focus on getting information about the sequence observed in Table 3 at [1], this sequence is listed in OEIS as A374773. We verify that the cardinality of the set of gapsets with genus $3n+1$ such that the maximum distance between two consecutive elements is $2n$ is equal to the cardinality of the set of gapsets with genus $3n+2$ such that the maximum distance between two consecutive elements is $2n+1$, for all $n\in \mathbb{N}$. In particular, we compute the cardinality of the symmetric and pseudo-symmetric gapsets in these cases., Comment: arXiv admin note: text overlap with arXiv:2106.13296
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- 2024
20. Measurement and Modeling of Polarized Atmosphere at the South Pole with SPT-3G
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Coerver, A., Zebrowski, J. A., Takakura, S., Holzapfel, W. L., Ade, P. A. R., Anderson, A. J., Ahmed, Z., Ansarinejad, B., Archipley, M., Balkenhol, L., Barron, D., Benabed, K., Bender, A. N., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Camphuis, E., Carlstrom, J. E., Cecil, T. W., Chang, C. L., Chaubal, P., Chichura, P. M., Chokshi, A., Chou, T. -L., Crawford, T. M., Cukierman, A., Daley, C., de Haan, T., Dibert, K. R., Dobbs, M. A., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Foster, A., Galli, S., Gambrel, A. E., Gardner, R. W., Ge, F., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Hood, J. C., Hryciuk, A., Huang, N., Keruzore, F., Khalife, A. R., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Lee, A. T., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Martsen, E. S., Menanteau, F., Millea, M., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Novosad, V., Omori, Y., Padin, S., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Quan, W., Rahimi, M., Rahlin, A., Reichardt, C. L., Rouble, M., Ruhl, J. E., Schiappucci, E., Smecher, G., Sobrin, J. A., Stark, A. A., Stephen, J., Suzuki, A., Tandoi, C., Thompson, K. L., Thorne, B., Trendafilova, C., Tucker, C., Umilta, C., Vieira, J. D., Vitrier, A., Wan, Y., Wang, G., Whitehorn, N., Wu, W. L. K., Yefremenko, V., and Young, M. R.
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present the detection and characterization of fluctuations in linearly polarized emission from the atmosphere above the South Pole. These measurements make use of Austral winter survey data from the SPT-3G receiver on the South Pole Telescope in three frequency bands centered at 95, 150, and 220 GHz. We use the cross-correlation between detectors to produce an unbiased estimate of the power in Stokes I, Q, and U parameters on large angular scales. Our results are consistent with the polarized signal being produced by the combination of Rayleigh scattering of thermal radiation from the ground and thermal emission from a population of horizontally aligned ice crystals with an anisotropic distribution described by Kolmogorov turbulence. The signal is most significant at large angular scales, high observing frequency, and low elevation angle. Polarized atmospheric emission has the potential to significantly impact observations on the large angular scales being targeted by searches for inflationary B-mode CMB polarization. We present the distribution of measured angular power spectrum amplitudes in Stokes Q and I for 4 years of winter observations, which can be used to simulate the impact of atmospheric polarization and intensity fluctuations at the South Pole on a specified experiment and observation strategy. For the SPT-3G data, downweighting the small fraction of significantly contaminated observations is an effective mitigation strategy. In addition, we present a strategy for further improving sensitivity on large angular scales where maps made in the 220 GHz band are used to measure and subtract the polarized atmosphere signal from the 150 GHz band maps. In observations with the SPT-3G instrument at the South Pole, the polarized atmospheric signal is a well-understood and sub-dominant contribution to the measured noise after implementing the mitigation strategies described here., Comment: 32 pages, 28 figures
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- 2024
21. Bayesian optimization of laser wakefield acceleration in the self-modulated regime (SM-LWFA) aiming to produce molybdenum-99 via photonuclear reactions
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Nunes, B. S., Santos, S. P., Nunes, R. P., Bonţoiu, C., Alva-Sánchez, M. S., Samad, R. E., Vieira Jr., N. D., Xia, G., Resta-López, J., and Bonatto, A.
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Physics - Accelerator Physics ,Physics - Plasma Physics - Abstract
While laser wakefield acceleration (LWFA) in the bubble regime demands ultra-short, high-peak-power laser pulses, operation in the self-modulated regime (SM-LWFA) works with more relaxed pulse conditions, albeit at the cost of lower beam quality. Modern laser systems can deliver pulses with durations of a few tens of femtoseconds and peak powers on the order of a few terawatts, at kHz repetition rates. These systems are well-suited for developing SM-LWFA applications where high average energy and charge are prioritized over beam quality. Such beams could be used to generate high-energy bremsstrahlung photons, capable of triggering photonuclear reactions to produce radioisotopes like molybdenum-99. This isotope decays into technetium-99m, the most widely used medical radioisotope, with over 30 million applications worldwide per year. This work explores the use of Bayesian optimization to maximize the energy and charge of electron beams accelerated via SM-LWFA. Particle-in-cell (PIC) simulations model a 5 TW, 15 fs-long Gaussian laser pulse, propagating through tailored hydrogen gas-density profiles. In these simulations, over multiple iterations, the algorithm optimizes a set of input parameters characterizing the gas-density profile and the laser focal position. Three distinct profiles, with total lengths ranging from 200 to 400 micrometers and combining ramps and plateaus, were investigated. Optimal configurations were found to produce electron beams with median energies ranging from 14 to 17 MeV and charges of 600 to 1300 pC, considering electrons with energies above 8 MeV. Preliminary estimates of the molybdenum-99 yields for the optimal beams were obtained by employing their phase spaces, retrieved from PIC simulations, as radiation source inputs in Monte Carlo simulations irradiating a combined tantalum and molybdenum target., Comment: 19 pages, 19 figures
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- 2024
22. Utilizing Generative Adversarial Networks for Image Data Augmentation and Classification of Semiconductor Wafer Dicing Induced Defects
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Hu, Zhining, Schlosser, Tobias, Friedrich, Michael, Silva, André Luiz Vieira e, Beuth, Frederik, and Kowerko, Danny
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
In semiconductor manufacturing, the wafer dicing process is central yet vulnerable to defects that significantly impair yield - the proportion of defect-free chips. Deep neural networks are the current state of the art in (semi-)automated visual inspection. However, they are notoriously known to require a particularly large amount of data for model training. To address these challenges, we explore the application of generative adversarial networks (GAN) for image data augmentation and classification of semiconductor wafer dicing induced defects to enhance the variety and balance of training data for visual inspection systems. With this approach, synthetic yet realistic images are generated that mimic real-world dicing defects. We employ three different GAN variants for high-resolution image synthesis: Deep Convolutional GAN (DCGAN), CycleGAN, and StyleGAN3. Our work-in-progress results demonstrate that improved classification accuracies can be obtained, showing an average improvement of up to 23.1 % from 65.1 % (baseline experiment) to 88.2 % (DCGAN experiment) in balanced accuracy, which may enable yield optimization in production., Comment: Accepted for: 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)
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- 2024
23. Cosmic ray susceptibility of the Terahertz Intensity Mapper detector arrays
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Liu, Lun-Jun, Janssen, Reinier M. J., Bumble, Bruce, Kane, Elijah, Foote, Logan M., Bradford, Charles M., Hailey-Dunsheath, Steven, Agrawal, Shubh, Aguirre, James E., Athreya, Hrushi, Bracks, Justin S., Brendal, Brockton S., Corso, Anthony J., Filippini, Jeffrey P., Fu, Jianyang, Groppi, Christopher E., Joralmon, Dylan, Keenan, Ryan P., Kowalik, Mikolaj, Lowe, Ian N., Manduca, Alex, Marrone, Daniel P., Mauskopf, Philip D., Mayer, Evan C., Nie, Rong, Razavimaleki, Vesal, Saeid, Talia, Trumper, Isaac, and Vieira, Joaquin D.
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Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Applied Physics ,Physics - Instrumentation and Detectors - Abstract
We report on the effects of cosmic ray interactions with the Kinetic Inductance Detector (KID) based focal plane array for the Terahertz Intensity Mapper (TIM). TIM is a NASA-funded balloon-borne experiment designed to probe the peak of the star formation in the Universe. It employs two spectroscopic bands, each equipped with a focal plane of four $\sim\,$900-pixel, KID-based array chips. Measurements of an 864-pixel TIM array shows 791 resonators in a 0.5$\,$GHz bandwidth. We discuss challenges with resonator calibration caused by this high multiplexing density. We robustly identify the physical positions of 788 (99.6$\,$%) detectors using a custom LED-based identification scheme. Using this information we show that cosmic ray events occur at a rate of 2.1$\,\mathrm{events/min/cm^2}$ in our array. 66$\,$% of the events affect a single pixel, and another 33$\,$% affect $<\,$5 KIDs per event spread over a 0.66$\,\mathrm{cm^2}$ region (2 pixel pitches in radius). We observe a total cosmic ray dead fraction of 0.0011$\,$%, and predict that the maximum possible in-flight dead fraction is $\sim\,$0.165$\,$%, which demonstrates our design will be robust against these high-energy events., Comment: 14 pages, 5 figures. Accepted for the publication in Journal of Low Temperature Physics (2024)
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- 2024
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24. A new visual quality metric for Evaluating the performance of multidimensional projections
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Ibrahim, Maniru and Vieira, Thales
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Graphics - Abstract
Multidimensional projections (MP) are among the most essential approaches in the visual analysis of multidimensional data. It transforms multidimensional data into two-dimensional representations that may be shown as scatter plots while preserving their similarity with the original data. Human visual perception is frequently used to evaluate the quality of MP. In this work, we propose to study and improve on a well-known map called Local Affine Multidimensional Projection (LAMP), which takes a multidimensional instance and embeds it in Cartesian space via moving least squares deformation. We propose a new visual quality metric based on human perception. The new metric combines three previously used metrics: silhouette coefficient, neighborhood preservation, and silhouette ratio. We show that the proposed metric produces more precise results in analyzing the quality of MP than other previously used metrics. Finally, we describe an algorithm that attempts to overcome a limitation of the LAMP method which requires a similar scale for control points and their counterparts in the Cartesian space., Comment: 19 pages, 10 figures
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- 2024
25. The Foundations of Tokenization: Statistical and Computational Concerns
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Gastaldi, Juan Luis, Terilla, John, Malagutti, Luca, DuSell, Brian, Vieira, Tim, and Cotterell, Ryan
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Tokenization - the practice of converting strings of characters over an alphabet into sequences of tokens over a vocabulary - is a critical yet under-theorized step in the NLP pipeline. Notably, it remains the only major step not fully integrated into widely used end-to-end neural models. This paper aims to address this theoretical gap by laying the foundations of tokenization from a formal perspective. By articulating and extending basic properties about the category of stochastic maps, we propose a unified framework for representing and analyzing tokenizer models. This framework allows us to establish general conditions for the use of tokenizers. In particular, we formally establish the necessary and sufficient conditions for a tokenizer model to preserve the consistency of statistical estimators. Additionally, we discuss statistical and computational concerns crucial for the design and implementation of tokenizer models. The framework and results advanced in this paper represent a step toward a robust theoretical foundation for neural language modeling.
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- 2024
26. Intelligent Urban Traffic Management via Semantic Interoperability across Multiple Heterogeneous Mobility Data Sources
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Scrocca, Mario, Grassi, Marco, Comerio, Marco, Carriero, Valentina Anita, Dias, Tiago Delgado, Da Silva, Ana Vieira, and Celino, Irene
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Computer Science - Databases - Abstract
The integrated exploitation of data sources in the mobility domain is key to providing added-value services to passengers, transport companies and authorities. Indeed, multiple stakeholders operate and maintain different kinds of data but several interoperability issues limit their effective usage. In this paper, we present an architecture enabled by Semantic Web technologies to overcome such issues and facilitate the development of an integrated solution for mobility stakeholders. The proposed solution is composed of different components that address challenges for enabling data interoperability, from the findability of data sources to their integrated consumption adopting standardised data formats. We report on the implementation and validation in four European cities of the TANGENT solution enabling data-driven tools for the dynamic management of multimodal traffic. Finally, we discuss the feedback received by users testing the solution and the lessons learnt during its development., Comment: In Use paper accepted for publication at the 23rd International Semantic Web Conference (ISWC) 2024. This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution will be published in the conference proceedings
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- 2024
27. Supernova Pointing Capabilities of DUNE
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M, Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Fernández, D. José, Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kumar, J., Kumar, P., Kumaran, S., Kunze, P., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, J., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Miccoli, A., Michna, G., Mikola, V., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Mote, M., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pinchault, J., Pitts, K., Plows, K., Plunkett, R., Pollack, C., Pollman, T., Polo-Toledo, D., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Queen, J., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, Diego, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Roeth, A. J., Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thiebault, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
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High Energy Physics - Experiment ,Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Solar and Stellar Astrophysics ,Nuclear Experiment ,Physics - Instrumentation and Detectors - Abstract
The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on $^{40}$Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage., Comment: 25 pages, 16 figures
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- 2024
28. Gradient Einstein-type warped products: rigidity, existence and nonexistence results via a nonlinear PDE
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Gomes, José Nazareno Vieira and Tokura, Willian Isao
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Mathematics - Differential Geometry - Abstract
We establish the necessary and sufficient conditions for constructing gradient Einstein-type warped metrics. One of these conditions leads us to a general Lichnerowicz equation with analytic and geometric coefficients for this class of metrics on the space of warping functions. In this way, we prove gradient estimates for positive solutions of a nonlinear elliptic differential equation on a complete Riemannian manifold with associated Bakry-\'Emery Ricci tensor bounded from below. As an application, we provide nonexistence and rigidity results for a large class of gradient Einstein-type warped metrics. Furthermore, we show how to construct gradient Einstein-type warped metrics, and then we give explicit examples which are not only meaningful in their own right, but also help to justify our results., Comment: 28 pages. Suggestions and comments are welcome
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- 2024
29. Exploring Galactic open clusters with Gaia I. An examination in the first kiloparsec
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Alfonso, Jeison, García-Varela, Alejandro, and Vieira, Katherine
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Astrophysics - Astrophysics of Galaxies - Abstract
Context. Since the first publication of the Gaia catalogue a new view of our Galaxy has arrived. Its astrometric and photometric information has improved the precision of the physical parameters of open star clusters obtained from them. Aims. Using the Gaia DR3 catalogue, we aim to find physical stellar members including faint stars for 370 Galactic open clusters located within 1 kpc. We also estimate the age, metallicity, distance modulus and extinction of these clusters. Methods. We employ the HDBSCAN algorithm on both astrometric and photometric data to identify members in the open clusters. Subsequently, we refine the samples by eliminating outliers through the application of the Mahalanobis metric utilizing the chi-square distribution at a confidence level of 95%. Furthermore, we characterize the stellar parameters with the PARSEC isochrones. Results. We obtain reliable star members for 370 open clusters with an average parallax error of 0.16 mas. We identify about 40% more stars in these clusters compared to previous work using the Gaia DR2 catalogue, including faint stars as new members with G > 17. Before the clustering application we correct the parallax zero-point bias to avoid spatial distribution stretching that may affect clustering results. Our membership lists include merging stars identified by HDBSCAN with astrometry and photometry. We note that the use of photometry in clustering can recover up to 10% more stars in the fainter limit than clustering based on astrometry only, this combined with the selection of stars filtering them out by quality cuts significantly reduces the number of stars with huge parallax error. After clustering, we estimate age, Z, and AV from the photometry of the membership lists., Comment: Submitted to A&A. 11 pages, 10 figures
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- 2024
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30. Slab tilings, flips and the triple twist
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Alencar, George L. D., Saldanha, Nicolau C., and Vieira, Arthur M. M.
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Mathematics - Combinatorics ,05B45, 52C20, 52C22, 05C70 - Abstract
A domino is a $2\times 1\times 1$ parallelepiped formed by the union of two unit cubes and a slab is a $2\times 2\times 1$ parallelepiped formed by the union of four unit cubes. We are interested in tiling regions formed by the finite union of unit cubes. We investigate domino tilings, slab tilings and mixed tilings (vertical dominoes and horizontal slabs). A flip is a local move: in a slab (resp. domino) tiling, two neighboring parallel slabs (resp. dominoes) are removed and placed back in a different position. We may interpret a three dimensional region as being made of floors. A slab or domino which crosses two floors is vertical, and horizontal otherwise. We can also define a flip in a mixed tiling, we replace four vertical dominoes in a $2\times 2\times 2$ box by two horizontal slabs and vice-versa. Inspired by the twist for domino tilings we construct a flip invariant for mixed tilings. Based on this, we then construct the triple twist for slab tilings: an invariant under flips assuming values in $\mathbb{Z}^3$. We show that if the region is a large box then the triple twist assumes a large number of possible values, at least proportional to the fourth power of the volume. We also give examples of smaller regions for which the triple twist assumes only one value and the set of tilings is connected under flips., Comment: 21 pages, 30 figures
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- 2024
31. Variational Best-of-N Alignment
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Amini, Afra, Vieira, Tim, and Cotterell, Ryan
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Best-of-N (BoN) is a popular and effective algorithm for aligning language models to human preferences. The algorithm works as follows: at inference time, N samples are drawn from the language model, and the sample with the highest reward, as judged by a reward model, is returned as the output. Despite its effectiveness, BoN is computationally expensive; it reduces sampling throughput by a factor of N. To make BoN more efficient at inference time, one strategy is to fine-tune the language model to mimic what BoN does during inference. To achieve this, we derive the distribution induced by the BoN algorithm. We then propose to fine-tune the language model to minimize backward KL divergence to the BoN distribution. Our approach is analogous to mean-field variational inference and, thus, we term it variational BoN (vBoN). To the extent this fine-tuning is successful and we end up with a good approximation, we have reduced the inference cost by a factor of N. Our experiments on a controlled generation task suggest that while variational BoN is not as effective as BoN in aligning language models, it is close to BoN performance as vBoN appears more often on the Pareto frontier of reward and KL divergence compared to models trained with KL-constrained RL objective.
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- 2024
32. Pr\'avention und Beseitigung von Fehlerursachen im Kontext von unbemannten Fahrzeugen
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Schnakenbeck, Aron, Sieber, Christoph, da Silva, Luis Miguel Vieira, Gehlhoff, Felix, and Fay, Alexander
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Computer Science - Robotics ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Mobile robots, becoming increasingly autonomous, are capable of operating in diverse and unknown environments. This flexibility allows them to fulfill goals independently and adapting their actions dynamically without rigidly predefined control codes. However, their autonomous behavior complicates guaranteeing safety and reliability due to the limited influence of a human operator to accurately supervise and verify each robot's actions. To ensure autonomous mobile robot's safety and reliability, which are aspects of dependability, methods are needed both in the planning and execution of missions for autonomous mobile robots. In this article, a twofold approach is presented that ensures fault removal in the context of mission planning and fault prevention during mission execution for autonomous mobile robots. First, the approach consists of a concept based on formal verification applied during the planning phase of missions. Second, the approach consists of a rule-based concept applied during mission execution. A use case applying the approach is presented, discussing how the two concepts complement each other and what contribution they make to certain aspects of dependability. Unbemannte Fahrzeuge sind durch zunehmende Autonomie in der Lage in unterschiedlichen unbekannten Umgebungen zu operieren. Diese Flexibilit\"at erm\"oglicht es ihnen Ziele eigenst\"andig zu erf\"ullen und ihre Handlungen dynamisch anzupassen ohne starr vorgegebenen Steuerungscode. Allerdings erschwert ihr autonomes Verhalten die Gew\"ahrleistung von Sicherheit und Zuverl\"assigkeit, bzw. der Verl\"asslichkeit, da der Einfluss eines menschlichen Bedieners zur genauen \"Uberwachung und Verifizierung der Aktionen jedes Roboters begrenzt ist. Daher werden Methoden sowohl in der Planung als auch in der Ausf\"uhrung von Missionen f\"ur unbemannte Fahrzeuge ben\"otigt, um die Sicherheit und Zuverl\"assigkeit dieser Fahrzeuge zu gew\"ahrleisten. In diesem Artikel wird ein zweistufiger Ansatz vorgestellt, der eine Fehlerbeseitigung w\"ahrend der Missionsplanung und eine Fehlerpr\"avention w\"ahrend der Missionsausf\"uhrung f\"ur unbemannte Fahrzeuge sicherstellt. Die Fehlerbeseitigung basiert auf formaler Verifikation, die w\"ahrend der Planungsphase der Missionen angewendet wird. Die Fehlerpr\"avention basiert auf einem regelbasierten Konzept, das w\"ahrend der Missionsausf\"uhrung angewendet wird. Der Ansatz wird an einem Beispiel angewendet und es wird diskutiert, wie die beiden Konzepte sich erg\"anzen und welchen Beitrag sie zu verschiedenen Aspekten der Verl\"asslichkeit leisten., Comment: Language: German. Dieser Beitrag wird eingereicht in: "dtec.bw-Beitr\"age der Helmut-Schmidt-Universit\"at/Universit\"at der Bundeswehr Hamburg: Forschungsaktivit\"aten im Zentrum f\"ur Digitalisierungs- und Technologieforschung der Bundeswehr dtec.bw"
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- 2024
33. Revealing the Electronic Structure of NiPS$_3$ through Synchrotron-Based ARPES and Alkali Metal Dosing
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Cao, Yifeng, Tan, Qishuo, Guo, Yucheng, Vieira, Clóvis Guerim, Mazzon, Mário S. C., Laverock, Jude, Russo, Nicholas, Gao, Hongze, Jozwiak, Chris, Bostwick, Aaron, Rotenberg, Eli, Guo, Jinghua, Yi, Ming, Matos, Matheus J. S., Ling, Xi, and Smith, Kevin E.
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Condensed Matter - Materials Science ,Condensed Matter - Strongly Correlated Electrons - Abstract
This study presents a comprehensive analysis of the band structure in NiPS$_3$, a van der Waals layered antiferromagnet, utilizing high-resolution synchrotron-based angle-resolved photoemission spectroscopy (ARPES) and corroborative density functional theory (DFT) calculations. By tuning the parameters of the light source, we obtained a very clear and wide energy range band structure of NiPS$_3$. Comparison with DFT calculations allows for the identification of the orbital character of the observed bands. Our DFT calculations perfectly match the experimental results, and no adaptations were made to the calculations based on the experimental outcomes. The appearance of novel electronic structure upon alkali metal dosing (AMD) were also obtained in this ARPES study. Above valence band maximum, structure of conduction bands and bands from defect states were firstly observed in NiPS$_3$. We provide the direct determination of the band gap of NiPS$_3$ as 1.3 eV from the band structure by AMD. In addition, detailed temperature dependent ARPES spectra were obtained across a range that spans both below and above the N\'eel transition temperature of NiPS$_3$. We found that the paramagnetic and antiferromagnetic states have almost identical spectra, indicating the highly localized nature of Ni $d$ states., Comment: 4 figures
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- 2024
34. Knowledge gaps and educational opportunities in congenital toxoplasmosis: A narrative review of Brazilian and global perspectives
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Coelho, David Richer Araujo, da Luz, Rogerio Oliveira, Melegario, Catiucia Soares, Vieira, Willians Fernando, and Bahia-Oliveira, Lilian Maria Garcia
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- 2024
35. Infectious diseases and secondary antibody deficiency in patients from a mesoregion of Sao Paulo State, Brazil
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Prestes-Carneiro, Luiz Euribel, Carrilho, Paula Andreia Martins, de Barros Torelli, Danielle Francisco Honorato, Bressa, Jose Antonio Nascimento, Parizi, Ana Carolina Gomes, Vieira, Pedro Henrique Meireles, Caliani Sa, Fernanda Miranda, and Ferreira, Mauricio Domingues
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- 2024
36. Value Generation from Academic Activities in a Public Higher Education: A Lean Perspective
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Leander Luiz Klein, Kelmara Mendes Vieira, Eric Charles Henri Dorion, Luana Brondani Costa, and Patricia Kruel Froner Moreira
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The concept of value, in a context of higher education institutions (HEIs), simply refers to meeting or exceeding customer requirements and expectations. HEIs have a fundamental role in the dissemination of knowledge, in addition to developing new skills and awareness for future professionals, in relation to local, regional and national issues. The aim of this research is to analyse the academic activities and outcomes influence on value generation perception in a public university students' perspective. A survey, built from a structured questionnaire, was carried out in a Brazilian HEI, the Federal University of Santa Maria, with students who are in their course final stage. Data collection came out with a valid sample of 389 respondents. It was analysed using descriptive statistics, exploratory factor and regression analyses. The findings suggest that among the services and resources that the university may offer to its students, the ones that present the most impact refer to cognitive and social abilities emerging from specific teaching practices and strategies from the professors. This research presents useful insights and applicable elements from which public managers can utilize to enhance engagement, create value and build a more rigorous and relevant practice.
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- 2024
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- View/download PDF
37. Mealtime Conversations between Parents and Their 2-Year-Old Children in Five Cultural Contexts
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Manuel Bohn, Wilson Filipe da Silva Vieira, Marta Giner Torréns, Joscha Kärtner, Shoji Itakura, Lília Cavalcante, Daniel Haun, Moritz Köster, and Patricia Kanngiesser
- Abstract
Children all over the world learn language, yet the contexts in which they do so vary substantially. This variation needs to be systematically quantified to build robust and generalizable theories of language acquisition. We compared communicative interactions between parents and their 2-year-old children (N = 99 families) during mealtime across five cultural settings (Brazil, Ecuador, Argentina, Germany, and Japan) and coded the amount of talk and gestures as well as their conversational embedding (interlocutors, function, and themes). We found a comparable pattern of communicative interactions across cultural settings, which were modified in ways that are consistent with local norms and values. These results suggest that children encounter similarly structured communicative environments across diverse cultural contexts and will inform theories of language learning.
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- 2024
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38. Mitogenomic analysis of a late Pleistocene jaguar from North America
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Srigyan, Megha, Schubert, Blaine W, Bushell, Matthew, Santos, Sarah HD, Figueiró, Henrique Vieira, Sacco, Samuel, Eizirik, Eduardo, and Shapiro, Beth
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Biological Sciences ,Evolutionary Biology ,Genetics ,Human Genome ,Animals ,Panthera ,Genome ,Mitochondrial ,Phylogeny ,Fossils ,Sequence Analysis ,DNA ,DNA ,Mitochondrial ,North America ,Georgia ,Evolution ,Molecular ,Genetic Variation ,ancient DNA ,jaguar ,mitochondrial DNA ,Pleistocene ,Evolutionary biology - Abstract
The jaguar (Panthera onca) is the largest living cat species native to the Americas and one of few large American carnivorans to have survived into the Holocene. However, the extent to which jaguar diversity declined during the end-Pleistocene extinction event remains unclear. For example, Pleistocene jaguar fossils from North America are notably larger than the average extant jaguar, leading to hypotheses that jaguars from this continent represent a now-extinct subspecies (Panthera onca augusta) or species (Panthera augusta). Here, we used a hybridization capture approach to recover an ancient mitochondrial genome from a large, late Pleistocene jaguar from Kingston Saltpeter Cave, Georgia, United States, which we sequenced to 26-fold coverage. We then estimated the evolutionary relationship between the ancient jaguar mitogenome and those from other extinct and living large felids, including multiple jaguars sampled across the species' current range. The ancient mitogenome falls within the diversity of living jaguars. All sampled jaguar mitogenomes share a common mitochondrial ancestor ~400 thousand years ago, indicating that the lineage represented by the ancient specimen dispersed into North America from the south at least once during the late Pleistocene. While genomic data from additional and older specimens will continue to improve understanding of Pleistocene jaguar diversity in the Americas, our results suggest that this specimen falls within the variation of extant jaguars despite the relatively larger size and geographic location and does not represent a distinct taxon.
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- 2024
39. Chaos in undamped, forced oscillators via stroboscopic maps
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Vieira, Ronaldo S. S., Daniel, Luiz H. R., and de Aguiar, Marcus A. M.
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Physics - Classical Physics - Abstract
Non-linear dynamics is not a usually covered topic in undergraduate physics courses. However, its importance within classical mechanics and the general theory of dynamical systems is unquestionable. In this work we show that this subject can be included in the schedule of an introductory classical mechanics course without the need to develop a robust theory of chaotic dynamics. To do this, we take as examples conservative non-linear oscillators subject to time-dependent periodic forces. By introducing the concept of stroboscopic maps we show that it is possible to visualize the appearance of chaos in these systems. We also address the example of the forced simple pendulum applying the same treatment. Finally, we briefly comment on the more general theory of chaos in conservative Hamiltonian systems., Comment: 14 pages, 16 figures. Accepted for publication in "Revista Brasileira de Ensino de F\'isica". Written in Portuguese
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- 2024
- Full Text
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40. Automatic Prediction of Amyotrophic Lateral Sclerosis Progression using Longitudinal Speech Transformer
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Wang, Liming, Gong, Yuan, Dawalatabad, Nauman, Vilela, Marco, Placek, Katerina, Tracey, Brian, Gong, Yishu, Premasiri, Alan, Vieira, Fernando, and Glass, James
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Computer Science - Sound ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a more efficient and objective alternative than manual approaches. We propose ALS longitudinal speech transformer (ALST), a neural network-based automatic predictor of ALS disease progression from longitudinal speech recordings of ALS patients. By taking advantage of high-quality pretrained speech features and longitudinal information in the recordings, our best model achieves 91.0\% AUC, improving upon the previous best model by 5.6\% relative on the ALS TDI dataset. Careful analysis reveals that ALST is capable of fine-grained and interpretable predictions of ALS progression, especially for distinguishing between rarer and more severe cases. Code is publicly available.
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- 2024
41. Semi-supervised classification of dental conditions in panoramic radiographs using large language model and instance segmentation: A real-world dataset evaluation
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Silva, Bernardo, Fontinele, Jefferson, Vieira, Carolina Letícia Zilli, Tavares, João Manuel R. S., Cury, Patricia Ramos, and Oliveira, Luciano
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Dental panoramic radiographs offer vast diagnostic opportunities, but training supervised deep learning networks for automatic analysis of those radiology images is hampered by a shortage of labeled data. Here, a different perspective on this problem is introduced. A semi-supervised learning framework is proposed to classify thirteen dental conditions on panoramic radiographs, with a particular emphasis on teeth. Large language models were explored to annotate the most common dental conditions based on dental reports. Additionally, a masked autoencoder was employed to pre-train the classification neural network, and a Vision Transformer was used to leverage the unlabeled data. The analyses were validated using two of the most extensive datasets in the literature, comprising 8,795 panoramic radiographs and 8,029 paired reports and images. Encouragingly, the results consistently met or surpassed the baseline metrics for the Matthews correlation coefficient. A comparison of the proposed solution with human practitioners, supported by statistical analysis, highlighted its effectiveness and performance limitations; based on the degree of agreement among specialists, the solution demonstrated an accuracy level comparable to that of a junior specialist., Comment: 43 pages, 12 figures, 9 tables
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- 2024
42. Independent [k]-Roman Domination on Graphs
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Luiz, Atílio Gomes and Vieira, Francisco Anderson Silva
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Mathematics - Combinatorics ,05C69, 05C99 - Abstract
Given a function $f\colon V(G) \to \mathbb{Z}_{\geq 0}$ on a graph $G$, $AN(v)$ denotes the set of neighbors of $v \in V(G)$ that have positive labels under $f$. In 2021, Ahangar et al.~introduced the notion of $[k]$-Roman Dominating Function ([$k$]-RDF) of a graph $G$, which is a function $f\colon V(G) \to \{0,1,\ldots,k+1\}$ such that $\sum_{u \in N[v]}f(u) \geq k + |AN(v)|$ for all $v \in V(G)$ with $f(v)
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- 2024
43. Toward a Method to Generate Capability Ontologies from Natural Language Descriptions
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da Silva, Luis Miguel Vieira, Köcher, Aljosha, Gehlhoff, Felix, and Fay, Alexander
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
To achieve a flexible and adaptable system, capability ontologies are increasingly leveraged to describe functions in a machine-interpretable way. However, modeling such complex ontological descriptions is still a manual and error-prone task that requires a significant amount of effort and ontology expertise. This contribution presents an innovative method to automate capability ontology modeling using Large Language Models (LLMs), which have proven to be well suited for such tasks. Our approach requires only a natural language description of a capability, which is then automatically inserted into a predefined prompt using a few-shot prompting technique. After prompting an LLM, the resulting capability ontology is automatically verified through various steps in a loop with the LLM to check the overall correctness of the capability ontology. First, a syntax check is performed, then a check for contradictions, and finally a check for hallucinations and missing ontology elements. Our method greatly reduces manual effort, as only the initial natural language description and a final human review and possible correction are necessary, thereby streamlining the capability ontology generation process.
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- 2024
44. Gap theorems in Yang-Mills theory for complete four-dimensional manifolds with positive Yamabe constant
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Vieira, Matheus
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Mathematics - Differential Geometry - Abstract
In this paper we prove gap theorems in Yang-Mills theory for complete four-dimensional manifolds with positive Yamabe constant. We extend the results of Gursky-Kelleher-Streets to complete manifolds. We also describe the equality in the gap theorem in terms of the basic instanton, which is interesting even for compact manifolds., Comment: 13 pages
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- 2024
45. SDS++: Online Situation-Aware Drivable Space Estimation for Automated Driving
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Sánchez, Manuel Muñoz, Trots, Gijs, Smit, Robin, Oliveira, Pedro Vieira, Silvas, Emilia, Elfring, Jos, and van de Molengraft, René
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Computer Science - Robotics - Abstract
Autonomous Vehicles (AVs) need an accurate and up-to-date representation of the environment for safe navigation. Traditional methods, which often rely on detailed environmental representations constructed offline, struggle in dynamically changing environments or when dealing with outdated maps. Consequently, there is a pressing need for real-time solutions that can integrate diverse data sources and adapt to the current situation. An existing framework that addresses these challenges is SDS (situation-aware drivable space). However, SDS faces several limitations, including its use of a non-standard output representation, its choice of encoding objects as points, restricting representation of more complex geometries like road lanes, and the fact that its methodology has been validated only with simulated or heavily post-processed data. This work builds upon SDS and introduces SDS++, designed to overcome SDS's shortcomings while preserving its benefits. SDS++ has been rigorously validated not only in simulations but also with unrefined vehicle data, and it is integrated with a model predictive control (MPC)-based planner to verify its advantages for the planning task. The results demonstrate that SDS++ significantly enhances trajectory planning capabilities, providing increased robustness against localization noise, and enabling the planning of trajectories that adapt to the current driving context.
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- 2024
46. Feedback in Emerging Extragalactic Star Clusters (JWST--FEAST): Calibration of Star Formation Rates in the Mid-Infrared with NGC 628
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Calzetti, Daniela, Adamo, Angela, Linden, Sean T., Gregg, Benjamin, Krumholz, Mark R., Bajaj, Varun, Bik, Arjan, Cignoni, Michele, Correnti, Matteo, Elmegreen, Bruce, Vieira, Helena Faustino, Gallagher, John S., Grasha, Kathryn, Gutermuth, Robert A., Johnson, Kelsey E., Messa, Matteo, Melinder, Jens, Ostlin, Goran, Pedrini, Alex, Sabbi, Elena, Smith, Linda J., and Tosi, Monica
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
New JWST near-infrared imaging of the nearby galaxy NGC 628 from the Cycle 1 program JWST-FEAST is combined with archival JWST mid-infrared imaging to calibrate the 21 $\mu$m emission as a star formation rate indicator (SFR) at $\sim$120 pc scales. The Pa$\alpha$ ($\lambda$1.8756 $\mu$m) hydrogen recombination emission line targeted by FEAST provides a reference SFR indicator that is relatively insensitive to dust attenuation, as demonstrated by combining this tracer with the HST H$\alpha$ imaging. Our analysis is restricted to regions that appear compact in nebular line emission and are sufficiently bright to mitigate effects of both age and stochastic sampling of the stellar initial mass function. We find that the 21 $\mu$m emission closely correlates with the nebular line emission, with a power-law with exponent=1.07$\pm$0.01, in agreement with past results. We calibrate a hybrid SFR indicator using a combination of H$\alpha$ and 24 $\mu$m (extrapolated from 21 $\mu$m) tracers and derive the proportionality constant between the two tracers $b=0.095\pm0.007$, which is $\sim$ 3-5 times larger than previous derivations using large regions/entire galaxies. We model these discrepancies as an increasing contribution to the dust heating by progressively older stellar populations for increasing spatial scales, in agreement with earlier findings that star formation is hierarchically distributed in galaxies. Thus, use of hybrid SFR indicators requires prior knowledge of the mean age of the stellar populations dominating the dust heating, which makes their application uncertain. Conversely, non-linear calibrations of SFRs from L(24) alone are more robust, with a factor $\lesssim$2.5 variation across the entire range of L(24) luminosities from HII regions to galaxies., Comment: 28 pages, 9 figures. Accepted for publication on the Astrophysical Journal
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- 2024
47. Huge BPS Operators and Fluid Dynamics in $\mathcal{N}=4$ SYM
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Kazakov, Vladimir, Murali, Harish, and Vieira, Pedro
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High Energy Physics - Theory - Abstract
In the bulk dual of holography, huge operators correspond to sources so heavy that they fully backreact on the space-time geometry. Here we study the correlation function of three such huge operators when they are given by $1/2$ BPS operators in $\mathcal{N}=4$ SYM theory, dual to IIB Strings in $AdS_5 \times S^5$. We unveil simple matrix model representations for these correlators which we can sometimes solve analytically. For general huge operators, we translate these matrix model expressions into a $1+1$ dimensional hydrodynamical fluid problem. This fluid is integrable thus unveiling a novel integrable sector of the $AdS/CFT$ duality in a full fledged gravitational regime, very far from the usual free string planar regime where integrability reigns supreme. We explain how an adiabatic deformation method can be developed to yield the solution to an integrable discrete formulation of these fluids -- the rational Calogero-Moser Model -- so we can access the general three point correlation functions of generic huge $1/2$-BPS operators. Everything will be done on the gauge theory side of the duality. It would be fascinating to find the holographic dual of these matrix models and fluids., Comment: 68 pages, 25 figures
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- 2024
48. Feedback in Emerging extragAlactic Star clusTers, FEAST: JWST spots PAH destruction in NGC 628 during the emerging phase of star formation
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Pedrini, Alex, Adamo, Angela, Calzetti, Daniela, Bik, Arjan, Gregg, Benjamin, Linden, Sean T., Bajaj, Varun, Ryon, Jenna E., Ali, Ahmad A., Bortolini, Giacomo, Correnti, Matteo, Elmegreen, Bruce G., Elmegreen, Debra Meloy, Gallagher, John S., Grasha, Kathryn, Gutermuth, Robert A., Johnson, Kelsey E., Melinder, Jens, Messa, Matteo, Östlin, Göran, Sabbi, Elena, Smith, Linda J., Tosi, Monica, and Vieira, Helena Faustino
- Subjects
Astrophysics - Astrophysics of Galaxies - Abstract
We investigate the emergence phase of young star clusters in the nearby spiral galaxy NGC 628. We use JWST NIRCam and MIRI observations to create spatially resolved maps of the Pa$\alpha$-1.87 $\mu$m and Br$\alpha$-4.05 $\mu$m hydrogen recombination lines, as well as the 3.3 $\mu$m and 7.7 $\mu$m emission from polycyclic aromatic hydrocarbons (PAHs). We extract 953 compact HII regions and analyze the PAH emission and morphology at $\sim$10 pc scales in the associated photo-dissociation regions (PDRs). While HII regions remain compact, radial profiles help us to define three PAH morphological classes: compact ($\sim$ 42%), extended ($\sim$ 34%) and open ($\sim$ 24%). The majority of compact and extended PAH morphologies are associated with very young star clusters ($<$5 Myr), while open PAH morphologies are mainly associated with star clusters older than 3 Myr. We observe a general decrease in the 3.3 $\mu$m and 7.7 $\mu$m PAH band emission as a function of cluster age, while their ratio remains constant with age out to 10 Myr and morphological class. The recovered PAH$_{3.3 \mu{\rm m}}$/PAH$_{7.7 \mu{\rm m}}$ ratio is lower than values reported in the literature for reference models that consider neutral and ionized PAH populations and analyses conducted at galactic scales. The 3.3 $\mu$m and 7.7 $\mu$m bands are typically associated to neutral and ionised PAHs, respectively. While we expected neutral PAHs to be suppressed in proximity of the ionizing source, the constant PAH$_{3.3 \mu{\rm m}}$/PAH$_{7.7 \mu{\rm m}}$ ratio would indicate that both families of molecules disrupt at similar rates in proximity of the HII regions., Comment: 25 pages, 14 figures, 3 tables. Accepted for publication in ApJ V2: Minor changes to Figures 7, 8, and 9, and to the text
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- 2024
49. Towards an ontology of portions of matter to support multi-scale analysis and provenance tracking
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Vieira, Lucas Valadares, Abel, Mara, Rodrigues, Fabricio Henrique, Sales, Tiago Prince, and Fonseca, Claudenir M.
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Computer Science - Artificial Intelligence ,I.2.4 - Abstract
This paper presents an ontology of portions of matter with practical implications across scientific and industrial domains. The ontology is developed under the Unified Foundational Ontology (UFO), which uses the concept of quantity to represent topologically maximally self-connected portions of matter. The proposed ontology introduces the granuleOf parthood relation, holding between objects and portions of matter. It also discusses the constitution of quantities by collections of granules, the representation of sub-portions of matter, and the tracking of matter provenance between quantities using historical relations. Lastly, a case study is presented to demonstrate the use of the portion of matter ontology in the geology domain for an Oil & Gas industry application. In the case study, we model how to represent the historical relation between an original portion of rock and the sub-portions created during the industrial process. Lastly, future research directions are outlined, including investigating granularity levels and defining a taxonomy of events.
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- 2024
50. Achieving Distributed MIMO Performance with Repeater-Assisted Cellular Massive MIMO
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Willhammar, Sara, Iimori, Hiroki, Vieira, Joao, Sundström, Lars, Tufvesson, Fredrik, and Larsson, Erik G.
- Subjects
Electrical Engineering and Systems Science - Signal Processing - Abstract
5G systems are being deployed all over the world and one key enabler of these systems is massive multiple-input multiple-output (MIMO). This technology has brought large performance gains in terms of serving many users. Despite the possibility to further exploit the spatial domain, there are situations where it is not possible to offer more than a single, or a few, data streams per user and where cell-edge coverage is an issue due to the lack of enough efficient channel scatterers. Looking ahead, distributed MIMO systems, where the antennas are spread over a larger area, are investigated for next generation systems. However, distributed MIMO comes with many practical deployment issues, making it a big challenge to adopt. As another way forward, we envision repeater-assisted cellular massive MIMO, where repeaters are deployed to act as channel scatterers to increase the rank of the channel and provide macro diversity for improved coverage and reliability. After elaborating on the requirements and hardware aspects of repeaters that enable this vision, we demonstrate through simulations the potential of repeater-assisted cellular massive MIMO to achieve distributed MIMO performance. Following this, we discuss open questions and future research directions., Comment: Submitted to IEEE Communications Magazine
- Published
- 2024
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