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The relationship between professional skills and higher education programs is modeled as a non-directed bipartite network with binary entries representing the links between 28 skills (as captured by the occupational information network, O*NET) and 258 graduate program summaries (as captured by commercial brochures of graduate programs in marketing with accreditation standards of the Association to Advance Collegiate Schools of Business). While descriptive analysis for skills suggests a qualitative lack of alignment between the job demands captured by O*NET, inferential analyses based on exponential random graph model estimates show that skills' popularity and homophily coexist with a systematic yet weak alignment to job demands for marketing managers., Comment: 14 pages, 4 figures, 4 tables

We calculate the quark self-energy correction in light-cone gauge motivated by distribution amplitudes whose definition implies a Wilson line. The latter serves to preserve the gauge invariance of the hadronic amplitudes and becomes trivial in light-cone gauge. Therefore, the calculation of the distribution amplitudes simplifies significantly provided that wave functions and propagators are obtained in that gauge. In here, we explore the corresponding Dyson-Schwinger equation in its leading truncation and with a dressed vertex derived from a Ward identity in light-cone gauge. The quark's mass and wave renormalization functions, as well as a third complex-valued amplitude, are found to depend on the relative orientation of the quark momentum and a light-like four-vector, which expresses a geometric gauge dependence of the propagator., Comment: 9 pages, 6 figures

The apportionment problem constitutes a fundamental problem in democratic societies: How to distribute a fixed number of seats among a set of states in proportion to the states' populations? This--seemingly simple--task has led to a rich literature and has become well known in the context of the US House of Representatives. In this paper, we connect the design of monotone apportionment methods to classic problems from discrete geometry and combinatorial optimization and explore the extent to which randomization can enhance proportionality. We first focus on the well-studied family of stationary divisor methods, which satisfy the strong population monotonicity property, and show that this family produces only a slightly superlinear number of different outputs as a function of the number of states. While our upper and lower bounds leave a small gap, we show that--surprisingly--closing this gap would solve a long-standing open problem from discrete geometry, known as the complexity of $k$-levels in line arrangements. The main downside of divisor methods is their violation of the quota axiom, i.e., every state should receive $\lfloor q_i\rfloor$ or $\lceil q_i\rceil$ seats, where $q_i$ is the proportional share of the state. As we show that randomizing over divisor methods can only partially overcome this issue, we propose a relaxed version of divisor methods in which the total number of seats may slightly deviate from the house size. By randomizing over them, we can simultaneously satisfy population monotonicity, quota, and ex-ante proportionality. Finally, we turn our attention to quota-compliant methods that are house-monotone, i.e., no state may lose a seat when the house size is increased. We provide a polyhedral characterization based on network flows, which implies a simple description of all ex-ante proportional randomized methods that are house-monotone and quota-compliant.

Objective: Scientific publications play a crucial role in uncovering insights, testing novel drugs, and shaping healthcare policies. Accessing the quality of publications requires evaluating their Risk of Bias (RoB), a process typically conducted by human reviewers. In this study, we introduce a new dataset for machine reading comprehension and RoB assessment and present RoBIn (Risk of Bias Inference), an innovative model crafted to automate such evaluation. The model employs a dual-task approach, extracting evidence from a given context and assessing the RoB based on the gathered evidence. Methods: We use data from the Cochrane Database of Systematic Reviews (CDSR) as ground truth to label open-access clinical trial publications from PubMed. This process enabled us to develop training and test datasets specifically for machine reading comprehension and RoB inference. Additionally, we created extractive (RoBInExt) and generative (RoBInGen) Transformer-based approaches to extract relevant evidence and classify the RoB effectively. Results: RoBIn is evaluated across various settings and benchmarked against state-of-the-art methods for RoB inference, including large language models in multiple scenarios. In most cases, the best-performing RoBIn variant surpasses traditional machine learning and LLM-based approaches, achieving an ROC AUC of 0.83. Conclusion: Based on the evidence extracted from clinical trial reports, RoBIn performs a binary classification to decide whether the trial is at a low RoB or a high/unclear RoB. We found that both RoBInGen and RoBInExt are robust and have the best results in many settings.

Dengue is a climate-sensitive mosquito-borne disease with a complex transmission dynamic. Data related to climate, environmental and sociodemographic characteristics of the target population are important for project scenarios. Different datasets and methodologies have been applied to build complex models for dengue forecast, stressing the need to evaluate these models and their relative accuracy grounded on a reproducible methodology. The goal of this work is to describe and present Mosqlimate, a web-based platform composed by a dashboard, a data store, model and rediction registries and support for a community of practice in arbovirus forecasting. Multiple API endpoints give access to data for development, open registration of predictive models from different approaches and sharing of predictive models for arboviruses incidence, facilitating interaction between modellers and allowing for proper comparison of the performance of different registered models, by means of probabilistic scores. Epidemiological, entomological, climatic and sociodemographic datasets related to arboviruses in Brazil, are freely available for download, alongside full documentation., Comment: 10 pages, 2 figures, 6 tables

Acute kidney injury (AKI) is a serious clinical condition that affects up to 20% of hospitalised patients. AKI is associated with short term unplanned hospital readmission and post-discharge mortality risk. Patient risk and healthcare expenditures can be minimised by followup planning grounded on predictive models and machine learning. Since AKI is multi-factorial, predictive models specialised in different categories of patients can increase accuracy of predictions. In the present article we present some results following this approach.

In this work, we have developed and characterized a position-sensitive CLYC detector that acts as the neutron imaging layer and $\gamma$-ray Compton scatterer of the novel dual \g-ray and neutron imaging system GN-Vision, which aims at simultaneously obtaining information about the spatial origin of \g-ray and neutron sources. We first investigated the performance of large 50$\times$50~mm$^{2}$ monolithic CLYC crystals coupled to a pixelated SiPM in terms of energy resolution and neutron-gamma discrimination. The response of two different 95\% $^{6}$Li-enriched CLYC detectors coupled to an array of 8$\times$8 SiPMs was studied in comparison to the results of a conventional photo-multiplier tube. Energy resolution ranging from 6-8\% for the $^{137}$Cs peak and a figure of merit of 3-4 for the neutron-gamma discrimination have been obtained. The spatial response of the CLYC-SiPM detector to $\gamma$-rays and neutrons has also been characterized using charge modulation-based multiplexing techniques based on a diode-coupled charge division circuit. Average resolutions close to 5~mm FWHM with good linearity are obtained in the transverse crystal plane. Last, this work presents the first proof-of-concept experiments of the neutron imaging capability using a neutron pinhole collimator attached to the developed position sensitive CLYC detector., Comment: 14 pages, 15 Figures, submitted to NIM-A

A fundamental economic question is that of designing revenue-maximizing mechanisms in dynamic environments. This paper considers a simple yet compelling market model to tackle this question, where forward-looking buyers arrive at the market over discrete time periods, and a monopolistic seller is endowed with a limited supply of a single good. In the case of i.i.d. and regular valuations for the buyers, Board and Skrzypacz (2016) characterized the optimal mechanism and proved the optimality of posted prices in the continuous-time limit. Our main result considers the limit case of a continuum of buyers, establishing that for arbitrary independent buyers' valuations, posted prices and capacity rationing can implement the optimal anonymous mechanism. Our result departs from the literature in three ways: It does not make any regularity assumptions, it considers the case of general, not necessarily i.i.d., arrivals, and finally, not only posted prices but also capacity rationing takes part in the optimal mechanism. Additionally, if supply is unlimited, we show that the rationing effect vanishes, and the optimal mechanism can be implemented using posted prices only, \`a la Board (2008)., Comment: none

A minor change in the Barcelos-Wotzasek (BW) symplectic algorithm for constrained systems is proposed. The change addresses some criticism that formalism has received, placing it on the same footing as Dirac's algorithm., Comment: A final version article is available at Brazilian Journal of Physics

Halide perovskites is a new class of semiconductors with exceptional optoelectronic properties. Among many advantages offered by halide perovskites, the bandgap energy can be tuned in a much broader range than what was possible in conventional semiconductors. This was commonly achieved in previous research by mixing different species of halides into solid solutions. The tuned bandgap using this method, however, often underwent an energy shift under optical or electrical stimuli due to halide segregation. In this work, we discovered an alternative approach to achieve super-bandgap electroluminescence from CsPbBr3. The peak energy of the light emission can be 0.7 eV higher than the reported bandgap energy. Evidence pointed to the radiative recombination at the perovskite-PEDOT:PSS interface being responsible for the unexpected blueshift of electroluminescence. We speculated that perovskite nanocrystals were formed therein and produced higher-energy photons due to quantum confinement. The results suggested an alternative strategy to manipulate and stabilize the color of electroluminescence and achieve particularly blue emission in perovskite-based LEDs.

Network Slicing (NS) has transformed the landscape of resource sharing in networks, offering flexibility to support services and applications with highly variable requirements in areas such as the next-generation 5G/6G mobile networks (NGMN), vehicular networks, industrial Internet of Things (IoT), and verticals. Although significant research and experimentation have driven the development of network slicing, existing architectures often fall short in intrinsic architectural intelligent security capabilities. This paper proposes an architecture-intelligent security mechanism to improve the NS solutions. We idealized a security-native architecture that deploys intelligent microservices as federated agents based on machine learning, providing intra-slice and architectural operation security for the Slicing Future Internet Infrastructures (SFI2) reference architecture. It is noteworthy that federated learning approaches match the highly distributed modern microservice-based architectures, thus providing a unifying and scalable design choice for NS platforms addressing both service and security. Using ML-Agents and Security Agents, our approach identified Distributed Denial-of-Service (DDoS) and intrusion attacks within the slice using generic and non-intrusive telemetry records, achieving an average accuracy of approximately $95.60\%$ in the network slicing architecture and $99.99\%$ for the deployed slice -- intra-slice. This result demonstrates the potential for leveraging architectural operational security and introduces a promising new research direction for network slicing architectures., Comment: 18 pages, 12 figures, Future Generation Computer Systems (FGCS)

Let $\mathcal{F}$ be a one-dimensional holomorphic foliation on $\mathbb{P}^n$ such that $\mathbf{W} \subset \text{Sing}(\mathcal{F})$, where $\mathbf{W}$ is a smooth complete intersection variety. We determine and compute the variation of the Milnor number $\mu(\mathcal{F}, \mathbf{W})$ under blowups, which depends on the vanishing order of the pullback foliation along the exceptional divisor, as well as on numerical and topological invariants of $\mathbf{W}$. This represents a higher-dimensional version of Van den Essen's formula for projective foliations. As an application, in $\mathbb{P}^3$, we provide a Seidenberg-type theorem for non-isolated singularities, without assuming that they are absolutely isolated. That is, the foliation has a birational model on a smooth manifold which is generically log canonical., Comment: 36 pages; In memory of Celso dos Santos Viana

How to elect the representatives in legislative bodies is a question that every modern democracy has to answer. This design task has to consider various elements so as to fulfill the citizens' expectations and contribute to the maintenance of a healthy democracy. The notion of proportionality, in that the support of a given idea in the house should be nearly proportional to its support in the general public, lies at the core of this design task. In the last decades, demographic aspects beyond political support have been incorporated by requiring that they are also fairly represented in the body, giving rise to a multidimensional version of the apportionment problem. In this work, we provide an axiomatic justification for a recently proposed notion of multidimensional proportionality and extend it to encompass two relevant constraints often used in electoral systems: a threshold on the number of votes that a list needs in order to be eligible and the election of the most-voted candidate in each district. We then build upon these results to design methods based on multidimensional proportionality. We use the Chilean Constitutional Convention election (May 15-16, 2021) results as a testing ground -- where the dimensions are given by political lists, districts, and genders -- and compare the apportionment obtained under each method according to three criteria: proportionality, representativeness, and voting power. While local and global methods exhibit a natural trade-off between local and global proportionality, including the election of most-voted candidates on top of methods based on 3-dimensional proportionality allows us to incorporate both notions while ensuring higher levels of representativeness and a balanced voting power.

Achieving simultaneous lasing of photons and phonons in optomechanical setups has great potential for applications in quantum information processing, high precision sensing and the design of hybrid photonic-phononic devices. Here, we explore this possibility with an optomechanical system driven by a two-tone field. Whenever the difference between the driving frequencies matches the associated mechanical frequency, the photon and phonon populations are found to achieve steady-state coherent oscillations, demonstrating a dual lasing phenomenon. Such drive-tone resonance condition can synchronize the phases of the photon and phonon fields, which facilitates a robust simultaneous lasing. Here, we provide analytical insights into the joint amplification of the optical and mechanical modes, and further confirm the dual lasing phenomenon by numerically calculating the relevant correlation functions and the power spectrum. Our setup, consisting of a single optomechanical cavity, is simpler than previous realizations of dual lasing and provides a clean picture of the underlying mechanisms. Our work thus paves the way for the development of novel strategies for the optimisation of optomechanical interactions through tailored driving schemes., Comment: 10 pages, 6 figures, SM in form of appendices. Feedback is invaluable in guiding us to enhance and refine our work

We study correlators of insertions along 1/2 BPS line defects in the holographic dual to type IIB string theory in $AdS_3 \times S^3 \times T^4$ with mixed Ramond-Ramond and Neveu Schwarz-Neveu Schwarz three-form flux. These defects break the symmetries of the bulk CFT$_2$ as $PSU(1,1|2)^2\times SO(4) \rightarrow PSU(1,1|2)\times SU(2)$, defining displacement and tilt supermultiplets. We focus on the two-, three- and four-point functions of these supermultiplets, which we compute using analytic conformal bootstrap up to next-to-leading order in their strong coupling expansion. We obtain a bootstrap result that only depends on two OPE coefficients. We perform a Witten diagram check of the bootstrap result, obtaining an holographic interpretation of the two OPE coefficients that are not constrained by the bootstrap procedure., Comment: 39 pages, 3 figures

This paper deals with the regularization of the sum of functions defined on a locally convex spaces through their closed-convex hulls in the bidual space. Different conditions guaranteeing that the closed-convex hull of the sum is the sum of the corresponding closed-convex hulls are provided. These conditions are expressed in terms of some epsilon-subdifferential calculus rules for the sum. The case of convex functions is also studied, and exact calculus rules are given under additional continuity/qualifications conditions. As an illustration, a variant of the proof of the classical Rockafellar theorem on convex integration is proposed.

An exciting recent development for deep-tissue imaging with cellular resolution is three-photon fluorescence microscopy (3PM) with excitation at long wavelengths (1300 and 1700 nm). In the last few years, long-wavelength 3PM has driven rapid progress in deep-tissue imaging beyond the depth limit of two-photon microscopy, with impacts in neuroscience, immunology, and cancer biology. However, wide adoption of 3PM faces challenges. Three-photon excitation (3PE) is naturally weaker than two-photon excitation, which places a premium on ultrashort pulses with high peak power. The inefficiency, complexity, and cost of current sources of these pulses present major barriers to the use of 3PM in typical biomedical research labs. Here, we describe a fiber-based source of femtosecond pulses with multi-megawatt peak power, tunable from 850 nm to 1700 nm. Compressed pulses from a fiber amplifier at 1030~nm are launched into an antiresonant hollow-core fiber filled with argon. By varying only the gas pressure, pulses with hundreds of nanojoules of energy and sub-100 fs duration are obtained at wavelengths between 850 and 1700 nm. This approach is a new route to an efficient, robust, and potentially low-cost source for multiphoton deep-tissue imaging. In particular, 960-nJ and 50-fs pulses are generated at 1300 nm with a conversion efficiency of 10\%. The nearly 20-MW peak power is an order of magnitude higher than the previous best from femtosecond fiber source at 1300~nm. As an example of the capabilities of the source, these pulses are used to image structure and neuronal activity in mouse brain as deep as 1.1 mm below the dura., Comment: Supplement appended at end

In this work, we propose to study noncommutative geometry using the language of categories of sheaves of algebras with polynomial identities and their properties, introducing new (graded) noncommutative geometries, which include, for example, the following algebras: superalgebras, $\mathbb{Z}_2^n$-graded superalgebras, Azumaya algebras, Clifford and quaternion algebras, the algebra of upper triangular matrices, quantum groups at roots of unity, and also some NC-schemes. More precisely, fix a group $G$, a $G$-graded associative algebra $A$ over a field $F$ of characteristic 0 and a topological space $X$; we construct a locally $G$-graded ringed space structure on $X$, where the sheaf structure belongs to the $G$-graded variety $\text{G-var}(A)$ of algebras generated by $A$, which classify all geometric spaces that belong to $\text{G-var}(A)$. We study conditions to compare two geometries in a (graded) Morita context, as well as their corresponding differential calculi.

We consider the Carrollian limit of ModMax electrodynamics, namely the limit of vanishing speed of light, for the most general, four-dimensional, duality and conformal invariant electromagnetism. The theory is parameterized by a unique real constant $\gamma$, which remains playing a non-trivial role in the magnetic Carrollian case, while it can be removed in the electric Carrollian contraction, and we therefore focus in the former. Applying the technique of Lie point symmetries, we obtain that the magnetic limit is invariant under the Carrollian group, as well as under the local translation in Carrollian time $x^{0}\rightarrow x^{0\prime}=x^{0}+f\left(x^{i}\right) $ and $x^{i}\rightarrow x^{i\prime}=x^{i}$, with $f$ being an arbitrary function. A diagonal part of the symmetries span the Conformal Carroll algebra of level $2$, $\mathfrak{ccarr}_2$ in four dimensions. Two additional internal symmetries remain in the Carrollian limit of ModMax standing for the conformal invariance of the theory, as well as the invariance under duality transformations., Comment: 14 pages, 4 figures

Nodes that play strategic roles in networks are called critical or influential nodes. For example, in an epidemic, we can control the infection spread by isolating critical nodes; in marketing, we can use certain nodes as the initial spreaders aiming to reach the largest part of the network, or they can be selected for removal in targeted attacks to maximise the fragmentation of the network. In this study, we focus on critical node detection in temporal networks. We propose three new measures to identify the critical nodes in temporal networks: the temporal supracycle ratio, temporal semi-local integration, and temporal semi-local centrality. We analyse the performance of these measures based on their effect on the SIR epidemic model in three scenarios: isolating the influential nodes when an epidemic happens, using the influential nodes as seeds of the epidemic, or removing them to analyse the robustness of the network. We compare the results with existing centrality measures, particularly temporal betweenness, temporal centrality, and temporal degree deviation. The results show that the introduced measures help identify influential nodes more accurately. The proposed methods can be used to detect nodes that need to be isolated to reduce the spread of an epidemic or as initial nodes to speedup dissemination of information., Comment: Comments and criticisms are welcomed

Many real-world tasks are intuitive for a human to perform, but difficult to encode algorithmically when utilizing a robot to perform the tasks. In these scenarios, robotic systems can benefit from expert demonstrations to learn how to perform each task. In many settings, it may be difficult or unsafe to use a physical robot to provide these demonstrations, for example, considering cooking tasks such as slicing with a knife. Extended reality provides a natural setting for demonstrating robotic trajectories while bypassing safety concerns and providing a broader range of interaction modalities. We propose the Robot Action Demonstration in Extended Reality (RADER) system, a generic extended reality interface for learning from demonstration. We additionally present its application to an existing state-of-the-art learning from demonstration approach and show comparable results between demonstrations given on a physical robot and those given using our extended reality system., Comment: In submission

This paper explores the adaptation and application of i-TED Compton imagers for real-time dosimetry in Boron Neutron Capture Therapy (BNCT). The i-TED array, previously utilized in nuclear astrophysics experiments at CERN, is being optimized for detecting and imaging 478 keV gamma-rays, critical for accurate BNCT dosimetry. Detailed Monte Carlo simulations were used to optimize the i-TED detector configuration and enhance its performance in the challenging radiation environment typical of BNCT. Additionally, advanced 3D image reconstruction algorithms, including a combination of back-projection and List-Mode Maximum Likelihood Expectation Maximization (LM-MLEM), are implemented and validated through simulations. Preliminary experimental tests at the Institut Laue-Langevin (ILL) demonstrate the potential of i-TED in a clinical setting, with ongoing experiments focusing on improving imaging capabilities in realistic BNCT conditions., Comment: 9 pages, 7 figures, submitted to the Special Issue of Applied Radiation and Isotopes associated to the 20th International Congress on Neutron Capture Therapy (20th ICNCT)

Photonic lanterns are waveguide devices enabling high throughput single mode spectroscopy and high angular resolution. We aim to present the first on-sky demonstration of a photonic lantern (PL) operating in visible light, to measure its throughput and assess its potential for high-resolution spectroscopy of compact objects. We used the SCExAO instrument (a double stage extreme AO system installed at the Subaru telescope) and FIRST mid-resolution spectrograph (R 3000) to test the visible capabilities of the PL on internal source and on-sky observations. The best averaged coupling efficiency over the PL field of view was measured at 51% +/- 10% with a peak at 80%. We also investigate the relationship between coupling efficiency and the Strehl ratio for a PL, comparing them with those of a single-mode fiber (SMF). Findings show that in the AO regime, a PL offers better coupling efficiency performance than a SMF, especially in the presence of low spatial frequency aberrations. We observed Ikiiki (alpha Leo - mR = 1.37) and `Aua (alpha Ori - mR = -1.17) at a frame rate of 200 Hz. Under median seeing conditions (about 1 arcsec measured in H band) and large tip/tilt residuals (over 20 mas), we estimated an average light coupling efficiency of 14.5% +/- 7.4%, with a maximum of 42.8% at 680 nm. We were able to reconstruct both star's spectra, containing various absorption lines. The successful demonstration of this device opens new possibilities in terms of high throughput single-mode fiber-fed spectroscopy in the Visible. The demonstrated on-sky coupling efficiency performance would not have been achievable with a single SMF injection setup under similar conditions, partly because the residual tip/tilt alone exceeded the field of view of a visible SMF (18 mas at 700 nm). Thus emphasizing the enhanced resilience of PL technology to such atmospheric disturbances. The additional, Comment: Accepted in Astronomy and Astrophysics journal on 9/11/2024

Dosimetry in BNCT poses significant challenges due to the indirect effect of neutrons interacting with elements within the body and uncertainties associated with the uptake of boron compounds used in clinical practice. Current treatment planning relies on unconventional estimates of boron tumor uptake derived from prior PET scans and thus, an online boron-uptake monitor would be highly convenient. This work presents the first pilot experiments carried out at ILL-Grenoble with the high-efficiency Compton camera i-TED, hereby aiming at demonstrating its applicability for BNCT dosimetry by introducing real-time measurement of the boron concentration and imaging capabilities of spatial dose distribution. In this experiment, we measured the $^{10}$B uptake of different cancer cells of tongue squamous cell carcinoma, malignant melanoma and glioblastoma treated with BPA (80~ppm of $^{10}$B). The samples were irradiated with the thermal neutron spectrum of ILL-Grenoble and the 478keV $\gamma$-rays from the $^{7}$Li de-excitation after the neutron-boron reaction were registered both with the Compton imager and the high-sensitivity FIPPS HPGe array. These series of measurements allowed us to demonstrate the imaging capabilities of the Compton imaging device for this type of application, as well as to assess its sensitivity, which was found to be below 1 $\mu$g of $^{10}$B., Comment: 10 pages, 12 figures, submitted to the Special Issue of Applied Radiation and Isotopes associated to the 20th International Congress on Neutron Capture Therapy (20th ICNCT)

Organ transplantation serves as the primary therapeutic strategy for end-stage organ failures. However, allograft rejection is a common complication of organ transplantation. Histological assessment is essential for the timely detection and diagnosis of transplant rejection and remains the gold standard. Nevertheless, the traditional histochemical staining process is time-consuming, costly, and labor-intensive. Here, we present a panel of virtual staining neural networks for lung and heart transplant biopsies, which digitally convert autofluorescence microscopic images of label-free tissue sections into their brightfield histologically stained counterparts, bypassing the traditional histochemical staining process. Specifically, we virtually generated Hematoxylin and Eosin (H&E), Masson's Trichrome (MT), and Elastic Verhoeff-Van Gieson (EVG) stains for label-free transplant lung tissue, along with H&E and MT stains for label-free transplant heart tissue. Subsequent blind evaluations conducted by three board-certified pathologists have confirmed that the virtual staining networks consistently produce high-quality histology images with high color uniformity, closely resembling their well-stained histochemical counterparts across various tissue features. The use of virtually stained images for the evaluation of transplant biopsies achieved comparable diagnostic outcomes to those obtained via traditional histochemical staining, with a concordance rate of 82.4% for lung samples and 91.7% for heart samples. Moreover, virtual staining models create multiple stains from the same autofluorescence input, eliminating structural mismatches observed between adjacent sections stained in the traditional workflow, while also saving tissue, expert time, and staining costs., Comment: 21 Pages, 5 Figures

This is an index of the contributions by the Giant Radio Array for Neutrino Detection (GRAND) Collaboration to the 10th International Workshop on Acoustic and Radio EeV Neutrino Detection Activities (ARENA 2024, University of Chicago, June 11-14, 2024). The contributions include an overview of GRAND in its present and future incarnations, methods of radio-detection that are being developed for them, and ongoing joint work between the GRAND and BEACON experiments., Comment: Note: To access the list of contributions, please follow the "HTML" link that can be found on the arXiv page

Neutrinos at ultrahigh energies can originate both from interactions of cosmic rays at their acceleration sites and through cosmic-ray interactions as they propagate through the universe. These neutrinos are expected to have a low flux which drives the need for instruments with large effective areas. Radio observations of the inclined air showers induced by tau neutrino interactions in rock can achieve this, because radio waves can propagate essentially unattenuated through the hundreds of kilometers of atmosphere. Proposed arrays for radio detection of tau neutrinos focus on either arrays of inexpensive receivers distributed over a large area, the GRAND concept, or compact phased arrays on elevated mountains, the BEACON concept, to build up a large detector area with a low trigger threshold. We present a concept that combines the advantages of these two approaches with a trigger driven by phased arrays at a moderate altitude (1 km) and sparse, high-gain outrigger receivers for reconstruction and background rejection. We show that this design has enhanced sensitivity at 100 PeV over the two prior designs with fewer required antennas and discuss the need for optimized antenna designs., Comment: ARENA2024 Conference Proceeding PoS(ARENA2024)058

One of the major challenges for the radio detection of extensive air showers, as encountered by the Giant Radio Array for Neutrino Detection (GRAND), is the requirement of an autonomous radio self-trigger. This work presents the current development of self-triggering techniques at the detection-unit level -- the so-called first-level trigger (FLT) -- in the context of the NUTRIG project. A second-level trigger (SLT) at the array level is described in a separate contribution. Two FLT methods are described, based on a template-fitting algorithm and a convolutional neural network (CNN). In this work, we compare the preliminary offline performance of both FLT methods in terms of signal selection efficiency and background rejection efficiency. We find that for both methods, ${\gtrsim}40\%$ of the background can be rejected if a signal selection efficiency of 90\% is required at the $5\sigma$ level., Comment: Presented at the 10th International Workshop on Acoustic and Radio EeV Neutrino Activities (ARENA2024). 8 pages, 4 figures

In the study of properties within one-dimensional dynamics, the assumption of a negative Schwarzian derivative has been shown to be very useful. However, this condition may appear somewhat arbitrary, as it is not a dynamical condition in any sense other than that it is preserved for its iterates. In this brief work, we show that the assumption of a negative Schwarzian derivative it is not entirely arbitrary but rather strictly related to the fulfillment of the Minimum Principle for the derivative of the map and its iterates, which is the key point in the proof of Singer's Theorem.

Large-scale cosmic-ray detectors like the Giant Radio Array for Neutrino Detection (GRAND) are pushing the boundaries of our ability to identify air shower events. Existing trigger schemes rely solely on the timing of signals detected by individual antennas, which brings many challenges in distinguishing true air shower signals from background. This work explores novel event-level radio trigger methods specifically designed for GRAND, but also applicable to other systems, such as the Radio Detector (RD) of the Pierre Auger Observatory. In addition to an upgraded plane wave front reconstruction technique, we introduce orthogonal and complementary approaches that analyze the radio-emission footprint, the spatial distribution of signal strength across triggered antennas, to refine event selection. We test our methods on mock data sets constructed with simulated showers and real background noise measured with the GRAND prototype, to assess the performance potential in terms of sensitivity and background rejection in GRAND. Our preliminary results are a first step to identifying the most discriminating radio signal features at event-level, and optimizing the techniques for future implementation on experimental data., Comment: 8 pages, 5 figures, 10th International Workshop on Acoustic and Radio EeV Neutrino Detection Activities - ARENA2024

This whitepaper offers normative and practical guidance for developers of artificial intelligence (AI) systems to achieve "Trustworthy AI". In it, we present overall ethical requirements and six ethical principles with value-specific recommendations for tools to implement these principles into technology. Our value-specific recommendations address the principles of fairness, privacy and data protection, safety and robustness, sustainability, transparency and explainability and truthfulness. For each principle, we also present examples of criteria for risk assessment and categorization of AI systems and applications in line with the categories of the European Union (EU) AI Act. Our work is aimed at stakeholders who can take it as a potential blueprint to fulfill minimum ethical requirements for trustworthy AI and AI Certification., Comment: Whitepaper - deliverable from the KI.NRW flagship-project "Zertifizierte KI"

Recently [PRA 108, L051501 (2023)], it has been shown that in a centrosymmetric cubic system, two-photons from a broadband intense laser field can be converted into a pair of Stokes and anti-Stokes entangled photons. Here we properly explain, demonstrate, quantify (for diamond) and explore the possibilities offered by such system, designing an entanglement map based on changes in the light-matter system. In particular, we show how the broadband polarization entanglement, that emerges from the interference between electronic and phononic degrees of freedom in the four-wave mixing process, depends on parameters such as Stokes-anti-Stokes Raman shift, scattering geometry and laser bandwidth, opening the avenue of exploration of such phenomenon in information processing., Comment: 12 pages, 2 figures

The operation of upcoming ultra-high-energy cosmic-ray, gamma-ray, and neutrino radio-detection experiments, like the Giant Radio Array for Neutrino Detection (GRAND), poses significant computational challenges involving the production of numerous simulations of particle showers and their detection, and a high data throughput. GRANDlib is an open-source software tool designed to meet these challenges. Its primary goal is to perform end-to-end simulations of the detector operation, from the interaction of ultra-high-energy particles, through -- by interfacing with external air-shower simulations -- the ensuing particle shower development and its radio emission, to its detection by antenna arrays and its processing by data-acquisition systems. Additionally, GRANDlib manages the visualization, storage, and retrieval of experimental and simulated data. We present an overview of GRANDlib to serve as the basis of future GRAND analyses., Comment: 11 pages, 9 figures, plus appendices

The widespread application of Artificial Intelligence (AI) techniques has significantly influenced the development of new therapeutic agents. These computational methods can be used to design and predict the properties of generated molecules. Multi-target Drug Discovery (MTDD) is an emerging paradigm for discovering drugs against complex disorders that do not respond well to more traditional target-specific treatments, such as central nervous system, immune system, and cardiovascular diseases. Still, there is yet to be an established benchmark suite for assessing the effectiveness of AI tools for designing multi-target compounds. Standardized benchmarks allow for comparing existing techniques and promote rapid research progress. Hence, this work proposes an evaluation framework for molecule generation techniques in MTDD scenarios, considering brain diseases as a case study. Our methodology involves using large language models to select the appropriate molecular targets, gathering and preprocessing the bioassay datasets, training quantitative structure-activity relationship models to predict target modulation, and assessing other essential drug-likeness properties for implementing the benchmarks. Additionally, this work will assess the performance of four deep generative models and evolutionary algorithms over our benchmark suite. In our findings, both evolutionary algorithms and generative models can achieve competitive results across the proposed benchmarks., Comment: 8 pages, 1 figure, published in 2024 IEEE Congress on Evolutionary Computation (CEC)

We obtain an infinite-dimensional cone of singular twisted Hilbert spaces $Z(\varphi)$ which are isomorphic to their duals but not to their conjugate duals. We do that by showing that the subset of all bi-Lipschitz maps from $[0, \infty)$ to $\mathbb{R}$ is coneable. We also provide a characterization of the Kalton-Peck space among all twisted Hilbert spaces of the form $Z(\varphi)$, which gives a partial answer to a conjecture of F. Cabello S\'anchez and J. Castillo.

First principles real-time time dependent density functional theory (rt-TDDFT) calculations reveal the existence of ballistic photocurrents generated by Coulomb scattering, a form of photocurrent that has not previously been considered as a mechanism for the bulk photovoltaic effect. With monolayer GeS as an example, it is predicted that ballistic currents can exceed shift currents under experimentally accessible conditions. Moreover, these simulations reveal recombination pathways that work to modify shift current magnitudes beyond perturbation theory predictions.

The classification of IoT traffic is important to improve the efficiency and security of IoT-based networks. As the state-of-the-art classification methods are based on Deep Learning, most of the current results require a large amount of data to be trained. Thereby, in real-life situations, where there is a scarce amount of IoT traffic data, the models would not perform so well. Consequently, these models underperform outside their initial training conditions and fail to capture the complex characteristics of network traffic, rendering them inefficient and unreliable in real-world applications. In this paper, we propose IoT Traffic Classification Transformer (ITCT), a novel approach that utilizes the state-of-the-art transformer-based model named TabTransformer. ITCT, which is pre-trained on a large labeled MQTT-based IoT traffic dataset and may be fine-tuned with a small set of labeled data, showed promising results in various traffic classification tasks. Our experiments demonstrated that the ITCT model significantly outperforms existing models, achieving an overall accuracy of 82%. To support reproducibility and collaborative development, all associated code has been made publicly available., Comment: Updated version of: B. Bazaluk, M. Hamdan, M. Ghaleb, M. S. M. Gismalla, F. S. Correa da Silva and D. M. Batista, "Towards a Transformer-Based Pre-trained Model for IoT Traffic Classification," NOMS 2024-2024 IEEE Network Operations and Management Symposium, Seoul, Korea, Republic of, 2024, pp. 1-7, doi: 10.1109/NOMS59830.2024.10575448

The majority of stars in today's Universe reside within spheroids, which are bulges of spiral galaxies and elliptical galaxies. Their formation is still an unsolved problem. Infrared/submm-bright galaxies at high redshifts have long been suspected to be related to spheroids formation. Proving this connection has been hampered so far by heavy dust obscuration when focusing on their stellar emission or by methodologies and limited signal-to-noise ratios when looking at submm wavelengths. Here we show that spheroids are directly generated by star formation within the cores of highly luminous starburst galaxies in the distant Universe. This follows from the ALMA submillimeter surface brightness profiles which deviate significantly from those of exponential disks, and from the skewed-high axis-ratio distribution. The majority of these galaxies are fully triaxial rather than flat disks: the ratio of the shortest to the longest of their three axes is half, on average, and increases with spatial compactness. These observations, supported by simulations, reveal a cosmologically relevant pathway for in-situ spheroid formation through starbursts likely preferentially triggered by interactions (and mergers) acting on galaxies fed by non-co-planar gas accretion streams., Comment: Nature in press

A Photonic Lantern (PL) is a novel device that efficiently converts a multi-mode fiber into several single-mode fibers. When coupled with an extreme adaptive optics (ExAO) system and a spectrograph, PLs enable high throughput spectroscopy at high angular resolution. The Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system of the Subaru Telescope recently acquired a PL that converts its multi-mode input into 19 single-mode outputs. The single mode outputs feed a R~4,000 spectrograph optimized for the 600 to 760 nm wavelength range. We present here the integration of the PL on SCExAO, and study the device performance in terms of throughput, field of view, and spectral reconstruction. We also present the first on-sky demonstration of a Visible PL coupled with an ExAO system, showing a significant improvement of x12 in throughput compared to the use of a sole single-mode fiber. This work paves the way towards future high throughput photonics instrumentation at small angular resolution., Comment: Proceeding published in SPIE Astronomical Telescopes + Instrumentation (2024) - Paper number 13096-25

We consider the dynamics of a population spatially structured in colonies that are vulnerable to catastrophic events occurring at random times, which randomly reduce their population size and compel survivors to disperse to neighboring areas. The dispersion behavior of survivors is critically significant for the survival of the entire species. In this paper, we consider an uniform dispersion scheme, where all possible survivor groupings are equally probable. The aim of the survivors is to establish new colonies, with individuals who settle in empty sites potentially initiating a new colony by themselves. However, all other individuals succumb to the catastrophe. We consider the number of dispersal options for surviving individuals in the aftermath of a catastrophe to be a fixed value $d$ within the neighborhood. In this context, we conceptualize the evolution of population dynamics occurring over a homogeneous tree. We investigate the conditions necessary for these populations to survive, presenting pertinent bounds for survival probability, the number of colonized vertices, the extent of dispersion within the population, and the mean time to extinction for the entire population., Comment: 22 pages

We obtain a quantitative star formation history (SFH) of a shell-like structure ('shell') located in the northeastern part of the Small Magellanic Cloud (SMC). We use the Survey of the MAgellanic Stellar History (SMASH) to derive colour-magnitude diagrams (CMDs), reaching below the oldest main-sequence turnoff, from which we compute the SFHs with CMD fitting techniques. We present, for the first time, a novel technique that uses red clump (RC) stars from the CMDs to assess and account for the SMC's line-of-sight depth effect present during the SFH derivation. We find that accounting for this effect recovers a more accurate SFH. We quantify a 7 kpc line-of-sight depth present in the CMDs, in good agreement with depth estimates from RC stars in the northeastern SMC. By isolating the stellar content of the northeastern shell and incorporating the line-of-sight depth into our calculations, we obtain an unprecedentedly detailed SFH. We find that the northeastern shell is primarily composed of stars younger than 500 Myrs, with significant star formation enhancements around 250 Myr and 450 Myr. These young stars are the main contributors to the shell's structure. We show synchronicity between the northeastern shell's SFH with the Large Magellanic Cloud's (LMC) northern arm, which we attribute to the interaction history of the SMC with the LMC and the Milky Way (MW) over the past 500 Myr. Our results highlight the complex interplay of ram pressure stripping and the influence of the MW's circumgalactic medium in shaping the SMC's northeastern shell., Comment: 17 pages, 13 figures. Accepted to MNRAS for publication

Euler-Poisson equations belong to the class of first-order differential equations for determining the integral lines of a given vector field. The general solution to these equations can be written as a power series of the evolution parameter. We calculated the sum of these series for the case of a free symmetric body, obtaining its rotation matrix through the elementary functions., Comment: 14 pages

Starlight suppression techniques for High-Contrast Imaging (HCI) are crucial to achieving the demanding contrast ratios and inner working angles required for detecting and characterizing exoplanets with a wide range of masses and separations. The advent of photonic technologies provides new opportunities to control the amplitude and phase characteristics of light, with the potential to enhance and control starlight suppression. Here, we present a focal plane optical-fiber-based nulling interferometer working with commercially available components for amplitude and phase modulation. The instrument implements single-mode fiber-coupled elements: a MEMS variable optical attenuator (VOA) matches the on-axis and off-axis starlight amplitude, while a piezoelectric-driven fiber stretcher modifies the optical path difference between the channels to achieve the $\pi$ phase shift condition for destructive interference. We show preliminary lab results using a narrowband light source working at 632 nm and discuss future opportunities for testing on-sky with the Astrophotonics Advancement Platform at Lick Observatory (APALO) at the Shane 3-m Telescope., Comment: submitted to SPIE Astronomical Telescopes and Instrumentation 2024, paper number 13095-95

In this work we analyze the $\bar KN$ interaction in the framework of a constituent quark model. The near-threshold elastic and charge exchange cross sections are evaluated, finding a good agreement with the experimental data. Furthermore, the possible existence of $\bar KN$ bound states are explored, finding two poles in the isoscalar $J^P=\frac{1}{2}^-$ sector that can be interpreted as the experimental $\Lambda(1405)$ state., Comment: 7 pages, 2 figures, 3 tables

In this paper, combining the Rashevsky-Chow-Sussmann (orbit) theorem with the Ambrose-Singer theorem, we introduce the notion of controllable principal connections on principal $G$-bundles. Using this concept, under a mild assumption of compactness, we estimate the Gromov-Hausdorff distance between principal $G$-bundles and certain reductive homogeneous $G$-spaces. In addition, we prove that every reduction of the structure group $G$ to a closed connected subgroup gives rise to a sequence of Riemannian metrics on the total space for which the underlying sequence of metric spaces converges, in the Gromov-Housdorff topology, to a normal reductive homogeneous $G$-space. This last finding allows one to detect the presence of certain reductive homogeneous $G$-spaces in the Gromov-Housdorff closure of the moduli space of Riemannian metrics of the total space of the bundle through topological invariants provided by obstruction theory., Comment: 13 pages, Comments are welcome