Author: "Poon AS" - Searchworks@Jio Institute Digital Library Search Results

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76,604 results on '"Poon AS"'

1. Exploring the Relationship between Test-Optional Admissions and Selectivity and Enrollment Outcomes during the Pandemic. EdWorkingPaper No. 24-982

Author: Annenberg Institute for School Reform at Brown University, Kelly Rosinger, Dominique J. Baker, Joseph Sturm, Wan Yu, Julie J. Park, OiYan Poon, Brian Heseung Kim, and Stephanie Breen
Abstract: Most selective colleges implemented test-optional admissions during the pandemic, making college entrance exam scores optional for applicants. We draw on descriptive, two-way fixed effects, and event study methods to examine variation in test-optional implementation during the pandemic and how implementation relates to selectivity and enrollment. For "test-optional" colleges during the pandemic, we found substantial variation in policy type (e.g., test optional, test free) and whether the policy extended to all applicants and scholarship consideration. Findings suggest test-optional implementation related to increases in Black student enrollment, mostly at moderately selective colleges and when policies extended to all applicants and scholarships. At highly selective colleges, findings suggest test-optional implementation related to an increase in applications but not consistent gains in enrollment.
Published: 2024

2. Building networks of shared research interests by embedding words into a representation space

Author: Poon, Art
Subjects: Computer Science - Social and Information Networks
Abstract: Departments within a university are not only administrative units, but also an effort to gather investigators around common fields of academic study. A pervasive challenge is connecting members with shared research interests both within and between departments. Here I describe a workflow that adapts methods from natural language processing to generate a network connecting $n=79$ members of a university department, or multiple departments within a faculty ($n=278$), based on common topics in their research publications. After extracting and processing terms from $n=16,901$ abstracts in the PubMed database, the co-occurrence of terms is encoded in a sparse document-term matrix. Based on the angular distances between the presence-absence vectors for every pair of terms, I use the uniform manifold approximation and projection (UMAP) method to embed the terms into a representational space such that terms that tend to appear in the same documents are closer together. Each author's corpus defines a probability distribution over terms in this space. Using the Wasserstein distance to quantify the similarity between these distributions, I generate a distance matrix among authors that can be analyzed and visualized as a graph. I demonstrate that this nonparametric method produces clusters with distinct themes that are consistent with some academic divisions, while identifying untapped connections among members. A documented workflow comprising Python and R scripts is available under the MIT license at https://github.com/PoonLab/tragula.
Published: 2025

3. Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale

Author: Wong, Cliff, Preston, Sam, Liu, Qianchu, Gero, Zelalem, Bagga, Jass, Zhang, Sheng, Jain, Shrey, Zhao, Theodore, Gu, Yu, Xu, Yanbo, Kiblawi, Sid, Weerasinghe, Roshanthi, Leidner, Rom, Young, Kristina, Piening, Brian, Bifulco, Carlo, Naumann, Tristan, Wei, Mu, and Poon, Hoifung
Subjects: Computer Science - Computation and Language
Abstract: The vast majority of real-world patient information resides in unstructured clinical text, and the process of medical abstraction seeks to extract and normalize structured information from this unstructured input. However, traditional medical abstraction methods can require significant manual efforts that can include crafting rules or annotating training labels, limiting scalability. In this paper, we propose UniMedAbstractor (UMA), a zero-shot medical abstraction framework leveraging Large Language Models (LLMs) through a modular and customizable prompt template. We refer to our approach as universal abstraction as it can quickly scale to new attributes through its universal prompt template without curating attribute-specific training labels or rules. We evaluate UMA for oncology applications, focusing on fifteen key attributes representing the cancer patient journey, from short-context attributes (e.g., performance status, treatment) to complex long-context attributes requiring longitudinal reasoning (e.g., tumor site, histology, TNM staging). Experiments on real-world data show UMA's strong performance and generalizability. Compared to supervised and heuristic baselines, UMA with GPT-4o achieves on average an absolute 2-point F1/accuracy improvement for both short-context and long-context attribute abstraction. For pathologic T staging, UMA even outperforms the supervised model by 20 points in accuracy.
Published: 2025

4. Optimizing Global Genomic Surveillance for Early Detection of Emerging SARS-CoV-2 Variants

Author: Gu, Haogao, Li, Jifan, Sun, Wanying, Li, Mengting, Leung, Kathy, Wu, Joseph T., Yuan, Hsiang-Yu, Wang, Maggie H., Yang, Bingyi, McKay, Matthew R., Ning, Ning, and Poon, Leo L. M.
Subjects: Quantitative Biology - Populations and Evolution, Quantitative Biology - Quantitative Methods
Abstract: Background: Global viral threats underscore the need for effective genomic surveillance, but high costs and uneven resource distribution hamper its implementation. Targeting surveillance to international travelers in major travel hubs may offer a more efficient strategy for the early detection of SARS-CoV-2 variants. Methods: We developed and calibrated a multiple-strain metapopulation model of global SARS-CoV-2 transmission using extensive epidemiological, phylogenetic, and high-resolution air travel data. We then compared baseline surveillance with various resource-allocation approaches that prioritize travelers, focusing on Omicron BA.1/BA.2 retrospectively and on hypothetical future variants under different emergence, transmission and vaccine effectiveness scenarios. Findings: Focusing existing surveillance resources on travelers at key global hubs significantly shortened detection delays without increasing total surveillance efforts. In retrospective analyses of Omicron BA.1/BA.2, traveler-targeted approaches consistently outperformed baseline strategies, even when overall resources were reduced. Simulations indicate that focusing surveillance on key travel hubs outperform baseline practices in detecting future variants, across different possible origins, even with reduced resources. This approach also remains effective in future pandemic scenarios with varying reproductive numbers and vaccine effectiveness. Interpretation: These findings provide a quantitative, cost-effective framework for strengthening global genomic surveillance. By reallocating resources toward international travelers in select travel hubs, early detection of emerging variants can be enhanced, informing rapid public health interventions and bolstering preparedness for future pandemics.
Published: 2025

5. Do neonates hear what we measure? Assessing neonatal ward soundscapes at the neonates ears

Author: Lam, Bhan, Fan, Peijin Esther Monica, Tay, Yih Yann, Poon, Woei Bing, Ong, Zhen-Ting, Ooi, Kenneth, Gan, Woon-Seng, and Ang, Shin Yuh
Subjects: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
Abstract: Acoustic guidelines for neonatal intensive care units (NICUs) aim to protect vulnerable neonates from noise-induced physiological harm. However, the lack of recognised international standards for measuring neonatal soundscapes has led to inconsistencies in instrumentation and microphone placement in existing literature, raising concerns about the relevance and effectiveness of these guidelines. This study addresses these gaps through long-term acoustic measurements in an operational NICU and a high-dependency ward. We investigate the influence of microphone positioning, bed placement, and ward layout on the assessment of NICU soundscapes. Beyond traditional A-weighted decibel metrics, this study evaluates C-weighted metrics for low-frequency noise, the occurrence of tonal sounds (e.g., alarms), and transient loud events known to disrupt neonates' sleep. Using linear mixed-effects models with aligned ranks transformation ANOVA (LME-ART-ANOVA), our results reveal significant differences in measured noise levels based on microphone placement, highlighting the importance of capturing sound as perceived directly at the neonate's ears. Additionally, bed position and ward layout significantly impact noise exposure, with a NICU bed position consistently exhibiting the highest sound levels across all (psycho)acoustic metrics. These findings support the adoption of binaural measurements along with the integration of additional (psycho)acoustic metrics, such as tonality and transient event occurrence rates, to reliably characterise the neonatal auditory experience., Comment: Accepted manuscript submitted to Building and Environment
Published: 2025

6. Reinforcement Learning for Quantum Circuit Design: Using Matrix Representations

Author: Wang, Zhiyuan, Feng, Chunlin, Poon, Christopher, Huang, Lijian, Zhao, Xingjian, Ma, Yao, Fu, Tianfan, and Liu, Xiao-Yang
Subjects: Quantum Physics, Computer Science - Artificial Intelligence
Abstract: Quantum computing promises advantages over classical computing. The manufacturing of quantum hardware is in the infancy stage, called the Noisy Intermediate-Scale Quantum (NISQ) era. A major challenge is automated quantum circuit design that map a quantum circuit to gates in a universal gate set. In this paper, we present a generic MDP modeling and employ Q-learning and DQN algorithms for quantum circuit design. By leveraging the power of deep reinforcement learning, we aim to provide an automatic and scalable approach over traditional hand-crafted heuristic methods.
Published: 2025

7. The MAJORANA DEMONSTRATOR experiment's construction, commissioning, and performance

Author: Abgrall, N., Aguayo, E., Arnquist, I. J., Avignone III, F. T., Barabash, A. S., Barton, C. J., Barton, P. J., Bertrand, F. E., Blalock, E., Bos, B., Boswell, M., Bradley, A. W., Brudanin, V., Burritt, T. H., Busch, M., Buuck, M., Byram, D., Caldwell, A. S., Caldwell, T. S., Chan, Y. -D., Christofferson, C. D., Chu, P. -H., Clark, M. L., Combs, D. C., Cuesta, C., Detwiler, J. A., Efremenko, Yu., Ejiri, H., Elliott, S. R., Fast, J. E., Finnerty, P., Fraenkle, F. M., Fuad, N., Fuller, E., Gilliss, T., Giovanetti, G. K., Goett, J., Green, M. P., Gruszko, J., Guinn, I. S., Guiseppe, V. E., Harper, G. C., Haufe, C. R., Henning, R., Aguilar, D. Hervas, Hoppe, E. W., Hostiuc, A., Howe, M. A., Jasinski, B. R., Keeter, K. J., Kidd, M. F., Kim, I., Kouzes, R. T., LaFerriere, B. D., Lannen V, T. E., Li, A., Loach, J. C., Lopez, A. M., Lopez-Castano, J. M., MacMullin, J., MacMullin, S., Martin, E. L., Martin, R. D., Massarczyk, R., Meijer, S. J., Merriman, J. H., Mertens, S., Miley, H. S., Myslik, J., Oli, T. K., Orrell, J. L., O'Shaughnessy, C., Othman, G., Overman, N. R., Peterson, D., Pettus, W., Poon, A. W. P., Radford, D. C., Rager, J., Reine, A. L., Rielage, K., Robertson, R. G. H., Rodriguez, L., Ruof, N. W., Salazar, H., Schaper, D. C., Schleich, S. J., Shanks, B., Shirchenko, M., Snavely, K. J., Snyder, N., Soin, A., Steele, D., Suriano, A. M., Swift, G., Trimble, D. Tedeschi J. E., Turqueti, M., Van Wechel, T. D., Varner, R. L., Vasilyev, S., Vorren, K., Watkins, S. L., White, B. R., Wilkerson, J. F., Wiseman, C., Xu, W., Yaver, H., Yu, C. -H., Yumatov, V. I., Zhitnikov, I., and Zhu, B. X.
Subjects: Physics - Instrumentation and Detectors, Nuclear Experiment
Abstract: Background: The MAJORANA DEMONSTRATOR , a modular array of isotopically enriched high-purity germanium (HPGe) detectors, was constructed to demonstrate backgrounds low enough to justify building a tonne-scale experiment to search for the neutrinoless double-beta decay ($\beta\beta(0\nu)$) of $^{76}\mathrm{Ge}$. Purpose: This paper presents a description of the instrument, its commissioning, and operations. It covers the electroforming, underground infrastructure, enrichment, detector fabrication, low-background and construction techniques, electronics, data acquisition, databases, and data processing of the MAJORANA DEMONSTRATOR. Method: The MAJORANA DEMONSTRATOR operated inside an ultra-low radioactivity passive shield at the 4850-foot~level of the Sanford Underground Research Facility (SURF) from 2015-2021. Results and Conclusions: The MAJORANA DEMONSTRATOR achieved the best energy resolution and second-best background level of any $\beta\beta(0\nu)$ search. This enabled it to achieve an ultimate half-life limit on $\beta\beta(0\nu)$ in $^{76}\mathrm{Ge}$ of $8.3\times 10^{25}$~yr (90\% C.L.) and perform a rich set of searches for other physics beyond the Standard Model., Comment: 72 pages
Published: 2025

8. Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. 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L., Pearlman, A. B., Romero, G. E., Shannon, R. M., Shaw, B., Stairs, I. H., Stappers, B. W., Tan, C. M., Theureau, G., Thompson, M., Weltevrede, P., and Zubieta, E.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables
Published: 2025

9. Emoji Retrieval from Gibberish or Garbled Social Media Text: A Novel Methodology and A Case Study

Author: Cui, Shuqi, Thakur, Nirmalya, and Poon, Audrey
Subjects: Computer Science - Social and Information Networks, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Machine Learning, I.2.7, I.2.8, I.5.4, K.4.2, H.2.8, I.2.6
Abstract: Emojis are widely used across social media platforms but are often lost in noisy or garbled text, posing challenges for data analysis and machine learning. Conventional preprocessing approaches recommend removing such text, risking the loss of emojis and their contextual meaning. This paper proposes a three-step reverse-engineering methodology to retrieve emojis from garbled text in social media posts. The methodology also identifies reasons for the generation of such text during social media data mining. To evaluate its effectiveness, the approach was applied to 509,248 Tweets about the Mpox outbreak, a dataset referenced in about 30 prior works that failed to retrieve emojis from garbled text. Our method retrieved 157,748 emojis from 76,914 Tweets. Improvements in text readability and coherence were demonstrated through metrics such as Flesch Reading Ease, Flesch-Kincaid Grade Level, Coleman-Liau Index, Automated Readability Index, Dale-Chall Readability Score, Text Standard, and Reading Time. Additionally, the frequency of individual emojis and their patterns of usage in these Tweets were analyzed, and the results are presented.
Published: 2024

10. Quantifying Public Response to COVID-19 Events: Introducing the Community Sentiment and Engagement Index

Author: Thakur, Nirmalya, Patel, Kesha A., Poon, Audrey, Cui, Shuqi, Azizi, Nazif, Shah, Rishika, and Shah, Riyan
Subjects: Computer Science - Social and Information Networks, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Machine Learning, I.2.7, I.2.8, I.5.4, K.4.2, H.2.8, I.2.6
Abstract: This study introduces the Community Sentiment and Engagement Index (CSEI), developed to capture nuanced public sentiment and engagement variations on social media, particularly in response to major events related to COVID-19. Constructed with diverse sentiment indicators, CSEI integrates features like engagement, daily post count, compound sentiment, fine-grain sentiments (fear, surprise, joy, sadness, anger, disgust, and neutral), readability, offensiveness, and domain diversity. Each component is systematically weighted through a multi-step Principal Component Analysis (PCA)-based framework, prioritizing features according to their variance contributions across temporal sentiment shifts. This approach dynamically adjusts component importance, enabling CSEI to precisely capture high-sensitivity shifts in public sentiment. The development of CSEI showed statistically significant correlations with its constituent features, underscoring internal consistency and sensitivity to specific sentiment dimensions. CSEI's responsiveness was validated using a dataset of 4,510,178 Reddit posts about COVID-19. The analysis focused on 15 major events, including the WHO's declaration of COVID-19 as a pandemic, the first reported cases of COVID-19 across different countries, national lockdowns, vaccine developments, and crucial public health measures. Cumulative changes in CSEI revealed prominent peaks and valleys aligned with these events, indicating significant patterns in public sentiment across different phases of the pandemic. Pearson correlation analysis further confirmed a statistically significant relationship between CSEI daily fluctuations and these events (p = 0.0428), highlighting the capacity of CSEI to infer and interpret shifts in public sentiment and engagement in response to major events related to COVID-19.
Published: 2024

11. Rare multi-nucleon decays with the full data sets of the Majorana Demonstrator

Author: Arnquist, I. J., Avignone III, F. T., Barabash, A. S., Blalock, E., Bos, B., Busch, M., Chan, Y. -D., Chapman, J. R., Christofferson, C. D., Chu, P. -H., Cuesta, C., Detwiler, J. A., Efremenko, Yu., Ejiri, H., Elliott, S. R., Fuad, N., Giovanetti, G. K., Green, M. P., Gruszko, J., Guinn, I. S., Guiseppe, V. E., Henning, R., Hoppe, E. W., Kouzes, R. T., Li, A., Massarczyk, R., Meijer, S. J., Paudel, L. S., Pettus, W., Poon, A. W. P., Radford, D. C., Reine, A. L., Rielage, K., Schaper, D. C., Schleich, S. J., Tedeschi, D., Varner, R. L., Vasilyev, S., Watkins, S. L., Wilkerson, J. F., Wiseman, C., and Yu, C. -H.
Subjects: Nuclear Experiment
Abstract: The Majorana Demonstrator was an ultra-low-background experiment designed for neutrinoless double-beta decay ($0\nu\beta\beta$) investigation in $^{76}$Ge. Located at the Sanford Underground Research Facility in Lead, South Dakota, the Demonstrator utilized modular high-purity Ge detector arrays within shielded vacuum cryostats, operating deep underground. The arrays, with a capacity of up to 40.4 kg (27.2 kg enriched to $\sim 88\%$ in $^{76}$Ge), have accumulated the full data set, totaling 64.5 kg yr of enriched active exposure and 27.4 kg yr of exposure for natural detectors. Our updated search improves previously explored three-nucleon decay modes in Ge isotopes, setting new half-life limits of $1.27\times10^{26}$ years (90\% confidence level) for $^{76}$Ge($ppp$) $\rightarrow$ $^{73}$Cu e$^+\pi^+\pi^+$ and $^{76}$Ge($ppn$) $\rightarrow$ $^{73}$Zn e$^+\pi^+$. The half-life limit for the invisible tri-proton decay mode of $^{76}$Ge is found to be $1.4\times10^{25}$ yr. Furthermore, we have updated limits for corresponding multi-nucleon decays.
Published: 2024

12. Multilabel Classification for Lung Disease Detection: Integrating Deep Learning and Natural Language Processing

Author: Efimovich, Maria, Lim, Jayden, Mehta, Vedant, and Poon, Ethan
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: Classifying chest radiographs is a time-consuming and challenging task, even for experienced radiologists. This provides an area for improvement due to the difficulty in precisely distinguishing between conditions such as pleural effusion, pneumothorax, and pneumonia. We propose a novel transfer learning model for multi-label lung disease classification, utilizing the CheXpert dataset with over 12,617 images of frontal radiographs being analyzed. By integrating RadGraph parsing for efficient annotation extraction, we enhance the model's ability to accurately classify multiple lung diseases from complex medical images. The proposed model achieved an F1 score of 0.69 and an AUROC of 0.86, demonstrating its potential for clinical applications. Also explored was the use of Natural Language Processing (NLP) to parse report metadata and address uncertainties in disease classification. By comparing uncertain reports with more certain cases, the NLP-enhanced model improves its ability to conclusively classify conditions. This research highlights the connection between deep learning and NLP, underscoring their potential to enhance radiological diagnostics and aid in the efficient analysis of chest radiographs., Comment: All authors contributed equally
Published: 2024

13. A potential exomoon from the predicted planet obliquity of $\beta$ Pictoris b

Author: Poon, Michael, Rein, Hanno, and Pham, Dang
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: Planet obliquity is the alignment or misalignment of a planet spin axis relative to its orbit normal. In a multiplanet system, this obliquity is a valuable signature of planet formation and evolutionary history. The young $\beta$ Pictoris system hosts two coplanar super-Jupiters and upcoming JWST observations of this system will constrain the obliquity of the outer planet, $\beta$ Pictoris b. This will be the first planet obliquity measurement in an extrasolar, multiplanet system. First, we show that this new planet obliquity is likely misaligned by using a wide range of simulated observations in combination with published measurements of the system. Motivated by current explanations for the tilted planet obliquities in the Solar System, we consider collisions and secular spin-orbit resonances. While collisions are unlikely to occur, secular spin-orbit resonance modified by the presence of an exomoon around the outer planet can excite a large obliquity. The largest induced obliquities ($\sim 60^\circ$) occur for moons with at least a Neptune-mass and a semimajor axis of $0.03-0.05~\mathrm{au}$ ($40-70$ planet radii). For certain orbital alignments, such a moon may observably transit the planet (transit depth of $3-7\%$, orbital period of $3-7$ weeks). Thus, a nonzero obliquity detection of $\beta$ Pictoris b implies that it may host a large exomoon. Although we focus on the $\beta$ Pictoris system, the idea that the presence of exomoons can excite high obliquities is very general and applicable to other exoplanetary systems., Comment: 10 pages, 8 figures, accepted for publication in The Open Journal of Astrophysics
Published: 2024
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14. DMP_AI: An AI-Aided K-12 System for Teaching and Learning in Diverse Schools

Author: Yang, Zhen-Qun, Cao, Jiannong, Li, Xiaoyin, Wang, Kaile, Zheng, Xinzhe, Poon, Kai Cheung Franky, and Lai, Daniel
Subjects: Computer Science - Computers and Society
Abstract: The use of Artificial Intelligence (AI) has gained momentum in education. However, the use of AI in K-12 education is still in its nascent stages, and further research and development is needed to realize its potential. Moreover, the creation of a comprehensive and cohesive system that effectively harnesses AI to support teaching and learning across a diverse range of primary and secondary schools presents substantial challenges that need to be addressed. To fill these gaps, especially in countries like China, we designed and implemented the DMP_AI (Data Management Platform_Artificial Intelligence) system, an innovative AI-aided educational system specifically designed for K-12 education. The system utilizes data mining, natural language processing, and machine learning, along with learning analytics, to offer a wide range of features, including student academic performance and behavior prediction, early warning system, analytics of Individualized Education Plan, talented students prediction and identification, and cross-school personalized electives recommendation. The development of this system has been meticulously carried out while prioritizing user privacy and addressing the challenges posed by data heterogeneity. We successfully implemented the DMP_AI system in real-world primary and secondary schools, allowing us to gain valuable insights into the potential and challenges of integrating AI into K-12 education in the real world. This system will serve as a valuable resource for supporting educators in providing effective and inclusive K-12 education., Comment: 15 pages
Published: 2024

15. Inequity and College Applications: Assessing Differences and Disparities in Letters of Recommendation from School Counselors with Natural Language Processing. EdWorkingPaper No. 24-953

Author: Annenberg Institute for School Reform at Brown University, Brian Heseung Kim, Julie J. Park, Pearl Lo, Dominique Baker, Nancy Wong, Stephanie Breen, Huong Truong, Jia Zheng, Kelly Rosinger, and OiYan A. Poon
Abstract: Letters of recommendation from school counselors are required to apply to many selective colleges and universities. Still, relatively little is known about how this non-standardized component may affect equity in admissions. We use cutting-edge natural language processing techniques to algorithmically analyze a national dataset of over 600,000 student applications and counselor recommendation letters submitted via the Common App platform. We examine how the length and topical content of letters (e.g., sentences about Personal Qualities, Athletics, Intellectual Promise, etc.) relate to student self-identified race/ethnicity, sex, and proxies for socioeconomic status. Paired with regression analyses, we explore whether demographic differences in letter characteristics persist when accounting for additional student, school, and counselor characteristics, as well as among letters written by the same counselor and among students with comparably competitive standardized test scores. We ultimately find large and noteworthy naïve differences in letter length and content across nearly all demographic groups, many in alignment with known inequities (e.g., many more sentences about Athletics among White and higher-SES students, longer letters and more sentences on Personal Qualities for private school students). However, these differences vary drastically based on the exact controls and comparison groups included -- demonstrating that the ultimate implications of these letter differences for equity hinges on exactly how and when letters are used in admissions processes (e.g., among which groups of students are they used to "break ties"?). Findings do not point to a clear recommendation whether institutions should keep or discard letter requirements, but reflect the importance of reading letters and overall applications in the context of structural opportunity. We discuss additional implications and possible recommendations for college access and admissions policy/practice.
Published: 2024

16. Comparing the Effectiveness of Physical Exercise Intervention and Melatonin Supplement in Improving Sleep Quality in Children with ASD

Author: Andy C. Y. Tse, Paul H. Lee, Cindy H. P. Sit, Eric Tsz-chun Poon, F. Sun, Chi-Ling Pang, and James C. H. Cheng
Abstract: Purpose: Previous studies have demonstrated that physical exercise can modulate the endogenous melatonin level in children with autism spectrum disorder (ASD) and improve their sleep quality. However, it remains unclear whether physical exercise or melatonin supplement, or a combination of both, is more effective in improving sleep quality in this population. The purpose of this study is to answer this research question by comparing the effectiveness of three types of interventions (physical exercise vs. melatonin supplement or a combination of both) in improving sleep quality in children with ASD. Methods: Sixty-two (62) children diagnosed with ASD were randomly assigned to one of four groups--cycling (n = 18), melatonin supplement (n = 14), a combination of both (n = 12), and placebo control group (n = 18). Four (4) sleep parameters (sleep efficiency, sleep onset latency, sleep duration, and wake after sleep onset) were assessed. Results: The results revealed a significant improvement in sleep efficiency, sleep onset latency, and sleep duration in all of the interventions, but not in the placebo control group. However, no significant group differences were found among the interventions (ps > 0.05). Conclusion: Our findings suggest similar effectiveness of physical exercise and melatonin supplementation in improving sleep quality in children with ASD.
Published: 2024
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17. A Sociotechnical Typology of Scientific Software

Author: Paine, Drew, Cohoon, Johanna, Poon, Sarah, Deshmukh, Rajshree, O'Donnell, Cody, Gunter, Daniel, and Ramakrishnan, Lavanya
Subjects: scientific software development, sociotechnical, software sustainability, STRUDEL, typology, user experience
Published: 2024

18. Measurement-induced entanglement entropy of gravitational wave detections

Author: Jones, Preston, Bailey, Quentin G., Gretarsson, Andri, and Poon, Edward
Subjects: General Relativity and Quantum Cosmology
Abstract: Research on the projective measurement of gravitons increasingly supports Dysons conclusions that the detection of single gravitons is not physically possible. It is therefore prudent to consider alternative signatures of non-classicality in gravitational wave detections to determine if gravity is quantized. Coincident multiple detector operations make it possible to consider the bipartite measurement-induced entanglement, in the detection process, as a signature of non-classicality. By developing a model of measurement-induced entanglement, based on a fixed number of gravitons for the bipartite system, we demonstrate that the entanglement entropy is on the order of a few percent of the mean number of gravitons interacting with the detectors. The bipartite measurement-induced entanglement is part of the detection process, which avoids the challenges associated with developing signatures of production-induced entanglement, due to the extremely low gravitational wave detector efficiencies. The calculation of normalized measurement-induced entanglement entropy demonstrates the potential of developing physically meaningful signatures of non-classicality based on bipartite detections of gravitational radiation. This result is in stark contrast to the discouraging calculations based on single-point detections., Comment: 12 pages and 2 figures
Published: 2024

19. A FinTech Clustering Framework: Technology, Model, and Stakeholder Perspectives

Author: Poon, Pak-Lok, Wibowo, Santoso, and Tang, Sau-Fun
Subjects: Quantitative Finance - General Finance, Computer Science - Emerging Technologies
Abstract: Nowadays, the global booming of FinTech can be seen everywhere. FinTech has created innovative disruptions to traditional, long-established financial institutions (e.g., banks and insurance companies) in financial services markets. Despite of its popularity, there are many different definitions of FinTech. This problem occurs because many existing studies only focus on a particular aspect of FinTech without a comprehensive and in-depth analysis. This problem will hinder further development and industrial application of FinTech. In view of this problem, we perform a narrative review involving over 100 relevant studies or reports, with a view to developing a FinTech clustering framework for providing a more comprehensive and holistic view of FinTech. Furthermore, we use an Indian FinTech firm to illustrate how to apply our clustering framework for analysis.
Published: 2024

20. Hadamard Langevin dynamics for sampling the l1-prior

Author: Cheltsov, Ivan, Cornalba, Federico, Poon, Clarice, and Shardlow, Tony
Subjects: Mathematics - Numerical Analysis, 65C40, 68U10, 65K10, 65C30
Abstract: Priors with non-smooth log densities have been widely used in Bayesian inverse problems, particularly in imaging, due to their sparsity inducing properties. To date, the majority of algorithms for handling such densities are based on proximal Langevin dynamics where one replaces the non-smooth part by a smooth approximation known as the Moreau envelope. In this work, we introduce a novel approach for sampling densities with $\ell_1$-priors based on a Hadamard product parameterization. This builds upon the idea that the Laplace prior has a Gaussian mixture representation and our method can be seen as a form of overparametrization: by increasing the number of variables, we construct a density from which one can directly recover the original density. This is fundamentally different from proximal-type approaches since our resolution is exact, while proximal-based methods introduce additional bias due to the Moreau-envelope smoothing. For our new density, we present its Langevin dynamics in continuous time and establish well-posedness and geometric ergodicity. We also present a discretization scheme for the continuous dynamics and prove convergence as the time-step diminishes.
Published: 2024

21. TriG-NER: Triplet-Grid Framework for Discontinuous Named Entity Recognition

Author: Cabral, Rina Carines, Han, Soyeon Caren, Alhassan, Areej, Batista-Navarro, Riza, Nenadic, Goran, and Poon, Josiah
Subjects: Computer Science - Computation and Language
Abstract: Discontinuous Named Entity Recognition (DNER) presents a challenging problem where entities may be scattered across multiple non-adjacent tokens, making traditional sequence labelling approaches inadequate. Existing methods predominantly rely on custom tagging schemes to handle these discontinuous entities, resulting in models tightly coupled to specific tagging strategies and lacking generalisability across diverse datasets. To address these challenges, we propose TriG-NER, a novel Triplet-Grid Framework that introduces a generalisable approach to learning robust token-level representations for discontinuous entity extraction. Our framework applies triplet loss at the token level, where similarity is defined by word pairs existing within the same entity, effectively pulling together similar and pushing apart dissimilar ones. This approach enhances entity boundary detection and reduces the dependency on specific tagging schemes by focusing on word-pair relationships within a flexible grid structure. We evaluate TriG-NER on three benchmark DNER datasets and demonstrate significant improvements over existing grid-based architectures. These results underscore our framework's effectiveness in capturing complex entity structures and its adaptability to various tagging schemes, setting a new benchmark for discontinuous entity extraction., Comment: Accepted at WWW 2025. Code will be made available at https://github.com/adlnlp/trig_ner
Published: 2024

22. A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges

Author: Wang, Zifeng, Wang, Hanyin, Danek, Benjamin, Li, Ying, Mack, Christina, Poon, Hoifung, Wang, Yajuan, Rajpurkar, Pranav, and Sun, Jimeng
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: The integration of Large Language Models (LLMs) into medical applications has sparked widespread interest across the healthcare industry, from drug discovery and development to clinical decision support, assisting telemedicine, medical devices, and healthcare insurance applications. This perspective paper aims to discuss the inner workings of building LLM-powered medical AI applications and introduces a comprehensive framework for their development. We review existing literature and outline the unique challenges of applying LLMs in specialized medical contexts. Additionally, we introduce a three-step framework to organize medical LLM research activities: 1) Modeling: breaking down complex medical workflows into manageable steps for developing medical-specific models; 2) Optimization: optimizing the model performance with crafted prompts and integrating external knowledge and tools, and 3) System engineering: decomposing complex tasks into subtasks and leveraging human expertise for building medical AI applications. Furthermore, we offer a detailed use case playbook that describes various LLM-powered medical AI applications, such as optimizing clinical trial design, enhancing clinical decision support, and advancing medical imaging analysis. Finally, we discuss various challenges and considerations for building medical AI applications with LLMs, such as handling hallucination issues, data ownership and compliance, privacy, intellectual property considerations, compute cost, sustainability issues, and responsible AI requirements.
Published: 2024

23. Search for gravitational waves emitted from SN 2023ixf

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. 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L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table
Published: 2024

24. Quantum Phase Transition as a Promising Route to Enhance the Critical Current in Kagome Superconductor CsV$_{3}$Sb$_{5}$

Author: Wang, Wenyan, Wang, Lingfei, Liu, Xinyou, Tsang, Chun Wai, Wang, Zheyu, Poon, Tsz Fung, Wang, Shanmin, Lai, Kwing To, Zhang, Wei, Tallon, Jeffery L., and Goh, Swee K.
Subjects: Condensed Matter - Superconductivity, Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract: Developing strategies to systematically increase the critical current, the threshold current below which the superconductivity exists, is an important goal of materials science. Here, the concept of quantum phase transition is employed to enhance the critical current of a kagome superconductor CsV$_3$Sb$_5$, which exhibits a charge density wave (CDW) and superconductivity that are both affected by hydrostatic pressure. As the CDW phase is rapidly suppressed under pressure, a large enhancement in the self-field critical current ($I_{\rm c,sf}$) is recorded. The observation of a peak-like enhancement of $I_{\rm c,sf}$ at the zero-temperature limit ($I_{\rm c,sf}(0)$) centred at $p^*\approx 20$~kbar, the same pressure where the CDW phase transition vanishes, further provides strong evidence of a zero-temperature quantum anomaly in this class of pressure-tuned superconductor. Such a peak in $I_{\rm c,sf}(0)$ resembles the findings in other well-established quantum-critical superconductors, hinting at the presence of enhanced quantum fluctuations associated with the CDW phase in CsV$_3$Sb$_5$., Comment: 8 pages, 4 figures. Advanced Science (2024)
Published: 2024
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25. A Novel Twisted-Winching String Actuator for Robotic Applications: Design and Validation

Author: Poon, Ryan, Padia, Vineet, and Hunter, Ian W.
Subjects: Computer Science - Robotics
Abstract: This paper presents a novel actuator system combining a twisted string actuator (TSA) with a winch mechanism. Relative to traditional hydraulic and pneumatic systems in robotics, TSAs are compact and lightweight but face limitations in stroke length and force-transmission ratios. Our integrated TSA-winch system overcomes these constraints by providing variable transmission ratios through dynamic adjustment. It increases actuator stroke by winching instead of overtwisting, and it improves force output by twisting. The design features a rotating turret that houses a winch, which is mounted on a bevel gear assembly driven by a through-hole drive shaft. Mathematical models are developed for the combined displacement and velocity control of this system. Experimental validation demonstrates the actuator's ability to achieve a wide range of transmission ratios and precise movement control. We present performance data on movement precision and generated forces, discussing the results in the context of existing literature. This research contributes to the development of more versatile and efficient actuation systems for advanced robotic applications and improved automation solutions., Comment: 7 pages 11 figures, submitted to 2025 IEEE International Conference on Robotics & Automation
Published: 2024

26. First constraints on general neutrino interactions based on KATRIN data

Author: Aker, M., Batzler, D., Beglarian, A., Beisenkötter, J., Biassoni, M., Bieringer, B., Biondi, Y., Block, F., Bornschein, B., Bornschein, L., Böttcher, M., Carminati, M., Chatrabhuti, A., Chilingaryan, S., Daniel, B. A., Descher, M., Barrero, D. Díaz, Doe, P. J., Dragoun, O., Drexlin, G., Edzards, F., Eitel, K., Ellinger, E., Engel, R., Enomoto, S., Felden, A., Fengler, C., Fiorini, C., Formaggio, J. A., Forstner, C., Fränkle, F. M., Gagliardi, G., Gauda, K., Gavin, A. S., Gil, W., Glück, F., Grössle, R., Gutknecht, N., Hannen, V., Hasselmann, L., Helbing, K., Henke, H., Heyns, S., Hiller, R., Hillesheimer, D., Hinz, D., Höhn, T., Huber, A., Jansen, A., Khosonthongkee, K., Köhler, C., Köllenberger, L., Kopmann, A., Kovač, N., La Cascio, L., Lasserre, T., Lauer, J., Le, T. L., Lebeda, O., Lehnert, B., Li, G., Lokhov, A., Machatschek, M., Mark, M., Marsteller, A., McMichael, K., Melzer, C., Mertens, S., Mohanty, S., Mostafa, J., Müller, K., Nava, A., Neumann, H., Niemes, S., Onillon, A., Parno, D. S., Pavan, M., Pinsook, U., Poon, A. W. P., Poyato, J. M. L., Priester, F., Ráliš, J., Ramachandran, S., Robertson, R. G. H., Rodenbeck, C., Röllig, M., Sack, R., Saenz, A., Salomon, R., Schäfer, P., Schlösser, K., Schlösser, M., Schlüter, L., Schneidewind, S., Schrank, M., Schürmann, J., Schütz, A. K., Schwemmer, A., Schwenck, A., Seeyangnok, J., Šefčík, M., Siegmann, D., Simon, F., Songwadhana, J., Spanier, F., Spreng, D., Sreethawong, W., Steidl, M., Štorek, J., Stribl, X., Sturm, M., Suwonjandee, N., Jerome, N. Tan, Telle, H. H., Thorne, L. A., Thümmler, T., Titov, N., Tkachev, I., Urban, K., Valerius, K., Vénos, D., Weinheimer, C., Welte, S., Wendel, J., Wetter, M., Wiesinger, C., Wilkerson, J. F., Wolf, J., Wüstling, S., Wydra, J., Xu, W., Zadorozhny, S., and Zeller, G.
Subjects: Nuclear Experiment, High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: The precision measurement of the tritium $\beta$-decay spectrum performed by the KATRIN experiment provides a unique way to search for general neutrino interactions (GNI). All theoretical allowed GNI terms involving neutrinos are incorporated into a low-energy effective field theory, and can be identified by specific signatures in the measured tritium $\beta$-spectrum. In this paper an effective description of the impact of GNI on the $\beta$-spectrum is formulated and the first constraints on the effective GNI parameters are derived based on the 4 million electrons collected in the second measurement campaign of KATRIN in 2019. In addition, constraints on selected types of interactions are investigated, thereby exploring the potential of KATRIN to search for more specific new physics cases, including a right-handed W boson, a charged Higgs or leptoquarks.
Published: 2024

27. GEM-VPC: A dual Graph-Enhanced Multimodal integration for Video Paragraph Captioning

Author: Wang, Eileen, Han, Caren, and Poon, Josiah
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Video Paragraph Captioning (VPC) aims to generate paragraph captions that summarises key events within a video. Despite recent advancements, challenges persist, notably in effectively utilising multimodal signals inherent in videos and addressing the long-tail distribution of words. The paper introduces a novel multimodal integrated caption generation framework for VPC that leverages information from various modalities and external knowledge bases. Our framework constructs two graphs: a 'video-specific' temporal graph capturing major events and interactions between multimodal information and commonsense knowledge, and a 'theme graph' representing correlations between words of a specific theme. These graphs serve as input for a transformer network with a shared encoder-decoder architecture. We also introduce a node selection module to enhance decoding efficiency by selecting the most relevant nodes from the graphs. Our results demonstrate superior performance across benchmark datasets.
Published: 2024

28. A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Azrad, D., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R. ., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghonge, S., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables
Published: 2024

29. Characterizing Quantum Codes via the Coefficients in Knill-Laflamme Conditions

Author: Du, Mengxin, Zhang, Chao, Poon, Yiu-Tung, and Zeng, Bei
Subjects: Quantum Physics
Abstract: Quantum error correction (QEC) is essential for protecting quantum information against noise, yet understanding the structure of the Knill-Laflamme (KL) coefficients $\lambda_{ij}$ from the condition $PE_i^\dagger E_j P = \lambda_{ij} P$ remains challenging, particularly for nonadditive codes. In this work, we introduce the signature vector $\vec{\lambda}(P)$, composed of the off-diagonal KL coefficients $\lambda_{ij}$, where each coefficient corresponds to equivalence classes of errors counted only once. We define its Euclidean norm $\lambda^*(P)$ as a scalar measure representing the total strength of error correlations within the code subspace defined by the projector $P$. We parameterize $P$ on a Stiefel manifold and formulate an optimization problem based on the KL conditions to systematically explore possible values of $\lambda^*$. Moreover, we show that, for $((n,K,d))$ codes, $\lambda^*$ is invariant under local unitary transformations. Applying our approach to the $((6, 2, 3))$ quantum code, we find that $\lambda^*_{\text{min}} = \sqrt{0.6}$ and $\lambda^*_{\text{max}} = 1$, with $\lambda^* = 1$ corresponding to a known degenerate stabilizer code. We construct continuous families of new nonadditive codes parameterized by vectors in $\mathbb{R}^5$, with $\lambda^*$ varying over the interval $[\sqrt{0.6}, 1]$. For the $((7, 2, 3))$ code, we identify $\lambda^*_{\text{min}} = 0$ (corresponding to the non-degenerate Steane code) and $\lambda^*_{\text{max}} = \sqrt{7}$ (corresponding to the permutation-invariant code by Pollatsek and Ruskai), and we demonstrate continuous paths connecting these extremes via cyclic codes characterized solely by $\lambda^*$. Our findings provide new insights into the structure of quantum codes, advance the theoretical foundations of QEC, and open new avenues for investigating intricate relationships between code subspaces and error correlations., Comment: 18 pages, 2 figures
Published: 2024

30. MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging

Author: Codella, Noel C. F., Jin, Ying, Jain, Shrey, Gu, Yu, Lee, Ho Hin, Abacha, Asma Ben, Santamaria-Pang, Alberto, Guyman, Will, Sangani, Naiteek, Zhang, Sheng, Poon, Hoifung, Hyland, Stephanie, Bannur, Shruthi, Alvarez-Valle, Javier, Li, Xue, Garrett, John, McMillan, Alan, Rajguru, Gaurav, Maddi, Madhu, Vijayrania, Nilesh, Bhimai, Rehaan, Mecklenburg, Nick, Jain, Rupal, Holstein, Daniel, Gaur, Naveen, Aski, Vijay, Hwang, Jenq-Neng, Lin, Thomas, Tarapov, Ivan, Lungren, Matthew, and Wei, Mu
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: In this work, we present MedImageInsight, an open-source medical imaging embedding model. MedImageInsight is trained on medical images with associated text and labels across a diverse collection of domains, including X-Ray, CT, MRI, dermoscopy, OCT, fundus photography, ultrasound, histopathology, and mammography. Rigorous evaluations demonstrate MedImageInsight's ability to achieve state-of-the-art (SOTA) or human expert level performance across classification, image-image search, and fine-tuning tasks. Specifically, on public datasets, MedImageInsight achieves SOTA in CT 3D medical image retrieval, as well as SOTA in disease classification and search for chest X-ray, dermatology, and OCT imaging. Furthermore, MedImageInsight achieves human expert performance in bone age estimation (on both public and partner data), as well as AUC above 0.9 in most other domains. When paired with a text decoder, MedImageInsight achieves near SOTA level single image report findings generation with less than 10\% the parameters of other models. Compared to fine-tuning GPT-4o with only MIMIC-CXR data for the same task, MedImageInsight outperforms in clinical metrics, but underperforms on lexical metrics where GPT-4o sets a new SOTA. Importantly for regulatory purposes, MedImageInsight can generate ROC curves, adjust sensitivity and specificity based on clinical need, and provide evidence-based decision support through image-image search (which can also enable retrieval augmented generation). In an independent clinical evaluation of image-image search in chest X-ray, MedImageInsight outperformed every other publicly available foundation model evaluated by large margins (over 6 points AUC), and significantly outperformed other models in terms of AI fairness (across age and gender). We hope releasing MedImageInsight will help enhance collective progress in medical imaging AI research and development.
Published: 2024

31. Multimodal Large Language Models and Tunings: Vision, Language, Sensors, Audio, and Beyond

Author: Han, Soyeon Caren, Cao, Feiqi, Poon, Josiah, and Navigli, Roberto
Subjects: Computer Science - Computation and Language
Abstract: This tutorial explores recent advancements in multimodal pretrained and large models, capable of integrating and processing diverse data forms such as text, images, audio, and video. Participants will gain an understanding of the foundational concepts of multimodality, the evolution of multimodal research, and the key technical challenges addressed by these models. We will cover the latest multimodal datasets and pretrained models, including those beyond vision and language. Additionally, the tutorial will delve into the intricacies of multimodal large models and instruction tuning strategies to optimise performance for specific tasks. Hands-on laboratories will offer practical experience with state-of-the-art multimodal models, demonstrating real-world applications like visual storytelling and visual question answering. This tutorial aims to equip researchers, practitioners, and newcomers with the knowledge and skills to leverage multimodal AI. ACM Multimedia 2024 is the ideal venue for this tutorial, aligning perfectly with our goal of understanding multimodal pretrained and large language models, and their tuning mechanisms., Comment: Accepted at ACM-MM 2024
Published: 2024

32. Final Results of the MAJORANA DEMONSTRATOR's Search for Double-Beta Decay of $^{76}$Ge to Excited States of $^{76}$Se

Author: Arnquist, I. J., Avignone III, F. T., Barabash, A. S., Blalock, E., Bos, B., Busch, M., Chan, Y. -D., Chapman, J. R., Christofferson, C. D., Chu, P. -H., Cuesta, C., Detwiler, J. A., Efremenko, Yu., Ejiri, H., Elliott, S. R., Fuad, N., Giovanetti, G. K., Green, M. P., Gruszko, J., Guinn, I. S., Guiseppe, V. E., Haufe, C. R., Henning, R., Aguilar, D. Hervas, Hoppe, E. W., Kim, I., Kouzes, R. T., Lannen V, T. E., Li, A., Massarczyk, R., Meijer, S. J., Oli, T. K., Paudel, L. S., Pettus, W., Poon, A. W. P., Radford, D. C., Reine, A. L., Rielage, K., Schaper, D. C., Schleich, S. J., Tedeschi, D., Varner, R. L., Vasilyev, S., Watkins, S. L., Wilkerson, J. F., Wiseman, C., Yu, C. -H., and Zhu, B. X.
Subjects: Nuclear Experiment
Abstract: $^{76}$Ge can $\beta\beta$ decay into three possible excited states of $^{76}$Se, with the emission of two or, if the neutrino is Majorana, zero neutrinos. None of these six transitions have yet been observed. The MAJORANA DEMONSTRATOR was designed to study $\beta\beta$ decay of $^{76}$Ge using a low background array of high purity germanium detectors. With 98.2 kg-y of isotopic exposure, the DEMONSTRATOR sets the strongest half-life limits to date for all six transition modes. For $2\nu\beta\beta$ to the $0^+_1$ state of $^{76}$Se, this search has begun to probe for the first time half-life values predicted using modern many-body nuclear theory techniques, setting a limit of $T_{1/2}>1.5\times10^{24}$ y (90% CL)., Comment: 8 pages, 3 figures
Published: 2024

33. RESuM: Rare Event Surrogate Model for Physics Detector Design

Author: Schuetz, Ann-Kathrin, Poon, Alan W. P., and Li, Aobo
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment
Abstract: The experimental discovery of neutrinoless double-beta decay (NLDBD) would answer one of the most important questions in physics: Why is there more matter than antimatter in our universe? To maximize the chances of detection, NLDBD experiments must optimize their detector designs to minimize the probability of background events contaminating the detector. Given that this probability is inherently low, design optimization either requires extremely costly simulations to generate sufficient background counts or contending with significant variance. In this work, we formalize this dilemma as a Rare Event Design (RED) problem: identifying optimal design parameters when the design metric to be minimized is inherently small. We then designed the Rare Event Surrogate Model (RESuM) for physics detector design optimization under RED conditions. RESuM uses a pretrained Conditional Neural Process (CNP) model to incorporate additional prior knowledges into a Multi-Fidelity Gaussian Process model. We applied RESuM to optimize neutron moderator designs for the LEGEND NLDBD experiment, identifying an optimal design that reduces neutron background by ($66.5\pm3.5$)% while using only 3.3% of the computational resources compared to traditional methods. Given the prevalence of RED problems in other fields of physical sciences, the RESuM algorithm has broad potential for simulation-intensive applications.
Published: 2024

34. Leaning Sideways: VHS 1256-1257 b is a Super-Jupiter with a Uranus-like Obliquity

Author: Poon, Michael, Bryan, Marta L., Rein, Hanno, Morley, Caroline V., Mace, Gregory, Zhou, Yifan, and Bowler, Brendan P.
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: We constrain the angular momentum architecture of VHS J125601.92-125723.9, a 140 $\pm$ 20 Myr old hierarchical triple system composed of a low-mass binary and a widely-separated planetary-mass companion VHS 1256 b. VHS 1256 b has been a prime target for multiple characterization efforts, revealing the highest measured substellar photometric variability to date and the presence of silicate clouds and disequilibrium chemistry. Here we add a key piece to the characterization of this super-Jupiter on a Tatooine-like orbit; we measure its spin-axis tilt relative to its orbit, i.e. the obliquity of VHS 1256 b. We accomplish this by combining three measurements. We find a projected rotation rate $v \sin{i_p} = 8.7 \pm 0.1 \,\mathrm{km~s^{-1}}$ for VHS 1256 b using near-IR high-resolution spectra from Gemini/IGRINS. Combining this with a published photometric rotation period indicates that the companion is viewed edge-on, with a line-of-sight spin axis inclination of $i_{\rm p} = 90^\circ \pm 18^\circ$. We refit available astrometry measurements to confirm an orbital inclination of $i_{\rm o} = 23 \substack{+10 \\ -13}^\circ$. Taken together, VHS 1256 b has a large planetary obliquity of $\psi = 90^\circ \pm 25^\circ$. In total, we have three measured angular momentum vectors for the system: the binary orbit normal, companion orbit normal, and companion spin axis. All three are misaligned with respect to each other. Although VHS 1256 b is tilted like Uranus, their origins are distinct. We rule out planet-like scenarios including collisions and spin-orbit resonances, and suggest that top-down formation via core/filament fragmentation is promising., Comment: accepted to AJ. 16 pages, 9 figures
Published: 2024
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35. The application of GPT-4 in grading design university students' assignment and providing feedback: An exploratory study

Author: Huang, Qian, Willems, Thijs, and Poon, King Wang
Subjects: Computer Science - Artificial Intelligence, 1.2.6
Abstract: This study aims to investigate whether GPT-4 can effectively grade assignments for design university students and provide useful feedback. In design education, assignments do not have a single correct answer and often involve solving an open-ended design problem. This subjective nature of design projects often leads to grading problems,as grades can vary between different raters,for instance instructor from engineering background or architecture background. This study employs an iterative research approach in developing a Custom GPT with the aim of achieving more reliable results and testing whether it can provide design students with constructive feedback. The findings include: First,through several rounds of iterations the inter-reliability between GPT and human raters reached a level that is generally accepted by educators. This indicates that by providing accurate prompts to GPT,and continuously iterating to build a Custom GPT, it can be used to effectively grade students' design assignments, serving as a reliable complement to human raters. Second, the intra-reliability of GPT's scoring at different times is between 0.65 and 0.78. This indicates that, with adequate instructions, a Custom GPT gives consistent results which is a precondition for grading students. As consistency and comparability are the two main rules to ensure the reliability of educational assessment, this study has looked at whether a Custom GPT can be developed that adheres to these two rules. We finish the paper by testing whether Custom GPT can provide students with useful feedback and reflecting on how educators can develop and iterate a Custom GPT to serve as a complementary rater., Comment: 25 pages, 5 figures
Published: 2024

36. Noncommutative distances on graphs: An explicit approach via Birkhoff-James orthogonality

Author: Clare, Pierre, Li, Chi-Kwong, Poon, Edward, and Swartz, Eric
Subjects: Mathematics - Operator Algebras, Mathematics - Combinatorics, 58B34, 46B20, 05C12, 05C50, 15A60
Abstract: We study the problem of calculating noncommutative distances on graphs, using techniques from linear algebra, specifically, Birkhoff-James orthogonality. A complete characterization of the solutions is obtained in the case when the underlying graph is a path., Comment: 26 pages, 1 figure
Published: 2024

37. Investigating Fintech Education and Training in Australian Universities

Author: Pak-Lok Poon, Santoso Wibowo, Srimannarayana Grandhi, and Sau-Fun Tang
Abstract: For more than a decade, the Financial Technology (FinTech) industry has been growing, and it has reshaped how payments were made and brought new financial service products to the market. FinTech has created innovative disruptions to traditional, long-established financial institutions (e.g., banks and investment firms) in financial services markets. The worldwide blooming of FinTech has caused universities around the globe to teach their students (particularly those in the IT and finance disciplines) about practical and contemporary knowledge on FinTech. This paper discusses our recent survey study to investigate the status quo of offering FinTech education and training by Australian universities. Our study involved two rounds of online data collection (one in November 2021 and the other one in June 2022) from 41 sample universities in Australia. Among our various findings, we observed that, although Australian universities are increasingly aware of the importance of and the demand for FinTech studies, FinTech has still not yet become a mainstream study discipline. This observation indicates that, in Australia, FinTech studies have generally gone through the inception stage and entered the growth stage.
Published: 2024

38. Multi-turn Natural Language Understanding

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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39. Challenges, Conclusion, and Future Direction

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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40. Applications and Case Studies in Natural Language Understanding

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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41. Evaluating Natural Language Understanding

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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42. Single-Turn Natural Language Understanding

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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43. Introduction to Natural Language Understanding

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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44. Prerequisites and Glossary for Natural Language Understanding

Author: Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, Poon, Josiah, Han, Soyeon Caren, Weld, Henry, Li, Yan, Lee, Jean, and Poon, Josiah
Published: 2025
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45. Selective Transfection of a Transferrin Receptor-Expressing Cell Line with DNA-Lipid Nanoparticles.

Author: Vinales, Irodiel, Silva-Espinoza, Juan, Medina, Bryan, Urbay, Juan, Beltran, Miguel, Salinas, Dante, Ramirez-Ramos, Marco, Maldonado, Rosa, Poon, Wilson, Penichet, Manuel, Almeida, Igor, and Michael, Katja
Abstract: Despite considerable progress in using lipid nanoparticle (LNP) vehicles for gene delivery, achieving selective transfection of specific cell types remains a significant challenge, hindering the advancement of new gene or gene-editing therapies. Although LNPs have been equipped with ligands aimed at targeting specific cellular receptors, achieving complete selectivity continues to be elusive. The exact reasons for this limited selectivity are not fully understood, as cell targeting involves a complex interplay of various cellular factors. Assessing how much ligand/receptor binding contributes to selectivity is challenging due to these additional influencing factors. Nonetheless, such data are important for developing new nanocarriers and setting realistic expectations for selectivity. Here, we have quantified the selective, targeted transfection using two uniquely engineered cell lines that eliminate unpredictable and interfering cellular influences. We have compared the targeted transfection of Chinese ovary hamster (CHO) cells engineered to express the human transferrin receptor 1 (hTfR1), CHO-TRVb-hTfR1, with CHO cells that completely lack any transferrin receptor, CHO-TRVb-neo cells (negative control). Thus, the two cell lines differ only in the presence/absence of hTfR1. The transfection was performed with pDNA-encapsulating LNPs equipped with the DT7 peptide ligand that specifically binds to hTfR1 and enables targeted transfection. The LNPs pDNA encoded for the monomeric GreenLantern (mGL) reporter protein, whose fluorescence was used to quantify transfection. We report a novel LNP composition designed to achieve an optimal particle size and ζ-potential, efficient pDNA encapsulation, hTfR1-targeting capability, and sufficient polyethylene glycol sheltering to minimize random cell targeting. The transfection efficiency was quantified in both cell lines separately through flow cytometry based on the expression of the fluorescent gene product. Our results demonstrated an LNP dose-dependent mGL expression, with a 5-fold preference for the CHO-TRVb-hTfR1 when compared to CHO-TRVb-neo. In another experiment, when both cell lines were mixed at a 1:1 ratio, the DT7-decorated LNP achieved a 3-fold higher transfection of the CHO-TRVb-hTfR1 over the CHO-TRVb-neo cells. Based on the low-level transfection of the CHO-TRVb-neo cells in both experiments, our results suggest that 17-25% of the transfection occurred in a nonspecific manner. The observed transfection selectivity for the CHO-TRVb-hTfR1 cells was based entirely on the hTfR1/DT7 interaction. This work showed that the platform of two engineered cell lines which differ only in the hTfR1 can greatly facilitate the development of LNPs with hTfR1-targeting ligands.
Published: 2024

46. The Proteogenomics of Prostate Cancer Radioresistance

Author: Haas, Roni, Frame, Gavin, Khan, Shahbaz, Neilsen, Beth K, Hong, Boon Hao, Yeo, Celestia PX, Yamaguchi, Takafumi N, Ong, Enya HW, Zhao, Wenyan, Carlin, Benjamin, Yeo, Eugenia LL, Tan, Kah Min, Bugh, Yuan Zhe, Zhu, Chenghao, Hugh-White, Rupert, Livingstone, Julie, Poon, Dennis JJ, Chu, Pek Lim, Patel, Yash, Tao, Shu, Ignatchenko, Vladimir, Kurganovs, Natalie J, Higgins, Geoff S, Downes, Michelle R, Loblaw, Andrew, Vesprini, Danny, Kishan, Amar U, Chua, Melvin LK, Kislinger, Thomas, Boutros, Paul C, and Liu, Stanley K
Subjects: Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Human Genome, Cancer Genomics, Urologic Diseases, Prostate Cancer, Biotechnology, Precision Medicine, Cancer, Aging, Genetics, Radiation Oncology, Male, Humans, Prostatic Neoplasms, Radiation Tolerance, Proteogenomics, Cell Line, Tumor, DNA Polymerase theta, Genomic Instability, DNA Mismatch Repair, Gene Expression Regulation, Neoplastic, DNA-Directed DNA Polymerase, Radiation Dose Hypofractionation
Abstract: Prostate cancer is frequently treated with radiotherapy. Unfortunately, aggressive radioresistant relapses can arise, and the molecular underpinnings of radioresistance are unknown. Modern clinical radiotherapy is evolving to deliver higher doses of radiation in fewer fractions (hypofractionation). We therefore analyzed genomic, transcriptomic, and proteomic data to characterize prostate cancer radioresistance in cells treated with both conventionally fractionated and hypofractionated radiotherapy. Independent of fractionation schedule, resistance to radiotherapy involved massive genomic instability and abrogation of DNA mismatch repair. Specific prostate cancer driver genes were modulated at the RNA and protein levels, with distinct protein subcellular responses to radiotherapy. Conventional fractionation led to a far more aggressive biomolecular response than hypofractionation. Testing preclinical candidates identified in cell lines, we revealed POLQ (DNA Polymerase Theta) as a radiosensitizer. POLQ-modulated radioresistance in model systems and was predictive of it in large patient cohorts. The molecular response to radiation is highly multimodal and sheds light on prostate cancer lethality.SignificanceRadiation is standard of care in prostate cancer. Yet, we have little understanding of its failure. We demonstrate a new paradigm that radioresistance is fractionation specific and identified POLQ as a radioresistance modulator.
Published: 2024

47. Linear preservers of parallel matrix pairs with respect to the $k$-numerical radius

Author: Kuzma, Bojan, Li, Chi-Kwong, Poon, Edward, and Singla, Sushil
Subjects: Mathematics - Functional Analysis, 15A60, 15A86, 47A12
Abstract: Let $1 \leq k < n$ be integers. Two $n \times n$ matrices $A$ and $B$ form a parallel pair with respect to the $k$-numerical radius $w_k$ if $w_k(A + \mu B) = w_k(A) + w_k(B)$ for some scalar $\mu$ with $|\mu| = 1$; they form a TEA (triangle equality attaining) pair if the preceding equation holds for $\mu = 1$. We classify linear bijections on $\mathbb M_n$ and on $\mathbb H_n$ which preserve parallel pairs or TEA pairs. Such preservers are scalar multiples of $w_k$-isometries, except for some exceptional maps on $\mathbb H_n$ when $n=2k$.
Published: 2024

48. Revisiting the Borde-Traub focal plane wavefront estimation technique for exoplanet direct imaging

Author: Potier, Axel, Riggs, A J Eldorado, Ruane, Garreth, Poon, Phillip K., Noyes, Matthew, Allan, Greg W., Walter, Alexander B., Prada, Camilo Mejia, Galicher, Raphael, Mazoyer, Johan, and Baudoz, Pierre
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: Direct imaging of exoplanets relies on complex wavefront sensing and control architectures. In addition to fast adaptive optics systems, most of the future high-contrast imaging instruments will soon be equipped with focal plane wavefront sensing algorithms. These techniques use the science detector to estimate the static and quasi-static aberrations induced by optical manufacturing defects and system thermal variations. Pair-wise probing (PWP) has been the most widely used, especially for space-based application and will be tested at contrast levels of ~1e-9 on-sky along with the future coronagraph instrument onboarding the Roman Space Telescope. This algorithm leans on phase diversities applied on the deformable mirror that are recorded in pairs. A minimum of two pairs of probes are required per bandwidth. An additional unprobed image is also recorded to verify the convergence rate of the correction. Before PWP, Borde & Traub proposed a similar algorithm that takes advantage of the unprobed image in the estimation process to get rid of the pair diversity requirement. In this work, we theoretically show that this latter technique should be more efficient than PWP when the convergence time is not limited by photon noise. We then present its performance and practical limitations on coronagraphic testbeds at JPL and exhibit a first on-sky control of non-common path aberrations with such method on VLT/SPHERE., Comment: Proceedings of SPIE Astronomical Telescopes + Instrumentation, Tokyo (2024)
Published: 2024

49. An assay-based background projection for the MAJORANA DEMONSTRATOR using Monte Carlo Uncertainty Propagation

Author: Arnquist, I. J., Avignone III, F. T., Barabash, A. S., Barton, C. J., Bhimani, K. H., Blalock, E., Bos, B., Busch, M., Caldwell, T. S., Chan, Y. -D., Christofferson, C. D., Chu, P. -H., Clark, M. L., Cuesta, C., Detwiler, J. A., Efremenko, Yu., Ejiri, H., Elliott, S. R., Fuad, N., Giovanetti, G. K., Green, M. P., Gruszko, J., Guinn, I. S., Guiseppe, V. E., Haufe, C. R., Henning, R., Aguilar, D. Hervas, Hoppe, E. W., Hostiuc, A., Kidd, M. F., Kim, I., Kouzes, R. T., Lannen V, T. E., Li, A., López-Castaño, J. M., Martin, R. D., Massarczyk, R., Meijer, S. J., Oli, T. K., Paudel, L. S., Pettus, W., Poon, A. W. P., Radford, D. C., Reine, A. L., Rielage, K., Ruof, N. W., Schaper, D. C., Schleich, S. J., Tedeschi, D., Varner, R. L., Vasilyev, S., Watkins, S. L., Wilkerson, J. F., Wiseman, C., Xu, W., and Yu, C. -H.
Subjects: Nuclear Experiment, Physics - Instrumentation and Detectors
Abstract: The background index is an important quantity which is used in projecting and calculating the half-life sensitivity of neutrinoless double-beta decay ($0\nu\beta\beta$) experiments. A novel analysis framework is presented to calculate the background index using the specific activities, masses and simulated efficiencies of an experiment's components as distributions. This Bayesian framework includes a unified approach to combine specific activities from assay. Monte Carlo uncertainty propagation is used to build a background index distribution from the specific activity, mass and efficiency distributions. This analysis method is applied to the MAJORANA DEMONSTRATOR, which deployed arrays of high-purity Ge detectors enriched in $^{76}$Ge to search for $0\nu\beta\beta$. The framework projects a mean background index of $\left[8.95 \pm 0.36\right] \times 10^{-4}$cts/(keV kg yr) from $^{232}$Th and $^{238}$U in the DEMONSTRATOR's components., Comment: 9 pages, 3 figures
Published: 2024

50. Measurement of the electric potential and the magnetic field in the shifted analysing plane of the KATRIN experiment

Author: Aker, M., Batzler, D., Beglarian, A., Behrens, J., Beisenkötter, J., Biassoni, M., Bieringer, B., Biondi, Y., Block, F., Bobien, S., Böttcher, M., Bornschein, B., Bornschein, L., Caldwell, T. S., Carminati, M., Chatrabhuti, A., Chilingaryan, S., Daniel, B. A., Debowski, K., Descher, M., Barrero, D. Díaz, Doe, P. J., Dragoun, O., Drexlin, G., Edzards, F., Eitel, K., Ellinger, E., Engel, R., Enomoto, S., Felden, A., Fengler, C., Fiorini, C., Formaggio, J. A., Forstner, C., Fränkle, F. M., Gauda, K., Gavin, A. S., Gil, W., Glück, F., Grössle, R., Gumbsheimer, R., Hannen, V., Hasselmann, L., Haußmann, N., Helbing, K., Heyns, S., Hickford, S., Hiller, R., Hillesheimer, D., Hinz, D., Höhn, T., Huber, A., Jansen, A., Karl, C., Kellerer, J., Khosonthongkee, K., Köhler, C., Köllenberger, L., Kopmann, A., Kovač, N., Krause, H., La Cascio, L., Lasserre, T., Lauer, J., Le, T. L., Lebeda, O., Lehnert, B., Li, G., Lokhov, A., Machatschek, M., Mark, M., Marsteller, A., Martin, E. L., McMichael, K., Melzer, C., Mertens, S., Mohanty, S., Mostafa, J., Müller, K., Nava, A., Neumann, H., Niemes, S., Parno, D. S., Pavan, M., Pinsook, U., Poon, A. W. P., Poyato, J. M. L., Pozzi, S., Priester, F., Ráliš, J., Ramachandran, S., Robertson, R. G. H., Rodenbeck, C., Röllig, M., Sack, R., Saenz, A., Salomon, R., Schäfer, P., Schlösser, M., Schlösser, K., Schlüter, L., Schneidewind, S., Schrank, M., Schürmann, J., Schütz, A. K., Schwemmer, A., Schwenck, A., Šefčík, M., Siegmann, D., Simon, F., Spanier, F., Spreng, D., Sreethawong, W., Steidl, M., Štorek, J., Stribl, X., Sturm, M., Suwonjandee, N., Jerome, N. Tan, Telle, H. H., Thorne, L. A., Thümmler, T., Titov, N., Tkachev, I., Urban, K., Valerius, K., Vénos, D., Weinheimer, C., Welte, S., Wendel, J., Wiesinger, C., Wilkerson, J. F., Wolf, J., Wüstling, S., Wydra, J., Xu, W., Zadorozhny, S., and Zeller, G.
Subjects: Physics - Instrumentation and Detectors
Abstract: The projected sensitivity of the effective electron neutrino-mass measurement with the KATRIN experiment is below 0.3 eV (90 % CL) after five years of data acquisition. The sensitivity is affected by the increased rate of the background electrons from KATRIN's main spectrometer. A special shifted-analysing-plane (SAP) configuration was developed to reduce this background by a factor of two. The complex layout of electromagnetic fields in the SAP configuration requires a robust method of estimating these fields. We present in this paper a dedicated calibration measurement of the fields using conversion electrons of gaseous $^\mathrm{83m}$Kr, which enables the neutrino-mass measurements in the SAP configuration., Comment: 19 pages, 11 figures
Published: 2024

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