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Generative AI (genAI) tools, such as ChatGPT or Copilot, are advertised to improve developer productivity and are being integrated into software development. However, misaligned trust, skepticism, and usability concerns can impede the adoption of such tools. Research also indicates that AI can be exclusionary, failing to support diverse users adequately. One such aspect of diversity is cognitive diversity -- variations in users' cognitive styles -- that leads to divergence in perspectives and interaction styles. When an individual's cognitive style is unsupported, it creates barriers to technology adoption. Therefore, to understand how to effectively integrate genAI tools into software development, it is first important to model what factors affect developers' trust and intentions to adopt genAI tools in practice? We developed a theoretical model to (1) identify factors that influence developers' trust in genAI tools and (2) examine the relationship between developers' trust, cognitive styles, and their intentions to use these tools. We surveyed software developers (N=238) at two major global tech organizations and employed Partial Least Squares-Structural Equation Modeling (PLS-SEM) to evaluate our model. Our findings reveal that genAI's system/output quality, functional value, and goal maintenance significantly influence developers' trust in these tools. Furthermore, developers' trust and cognitive styles influence their intentions to use these tools. We offer practical suggestions for designing genAI tools for effective use and inclusive user experience.

The demand for cognitive load assessment with low-cost easy-to-use equipment is increasing, with applications ranging from safety-critical industries to entertainment. Though pupillometry is an attractive solution for cognitive load estimation in such applications, its sensitivity to light makes it less robust under varying lighting conditions. Multimodal data acquisition provides a viable alternative, where pupillometry is combined with electrocardiography (ECG) or electroencephalography (EEG). In this work, we study the sensitivity of pupillometry-based cognitive load estimation to light. By collecting heart rate variability (HRV) data during the same experimental sessions, we analyze how the multimodal data reduces this sensitivity and increases robustness to light conditions. In addition to this, we compared the performance in multimodal settings using the HRV data obtained from low-cost fitness-grade equipment to that from clinical-grade equipment by synchronously collecting data from both devices for all task conditions. Our results indicate that multimodal data improves the robustness of cognitive load estimation under changes in light conditions and improves the accuracy by more than 20% points over assessment based on pupillometry alone. In addition to that, the fitness grade device is observed to be a potential alternative to the clinical grade one, even in controlled laboratory settings., Comment: 9 pages

Background. Clinical data warehouses (CDWs) are essential in the reuse of hospital data in observational studies or predictive modeling. However, state of-the-art CDW systems present two drawbacks. First, they do not support the management of large data files, what is critical in medical genomics, radiology, digital pathology, and other domains where such files are generated. Second, they do not provide provenance management or means to represent longitudinal relationships between patient events. Indeed, a disease diagnosis and its follow-up rely on multiple analyses. In these cases no relationship between the data (e.g., a large file) and its associated analysis and decision can be documented.Method. We introduce gitOmmix, an approach that overcomes these limitations, and illustrate its usefulness in the management of medical omics data. gitOmmix relies on (i) a file versioning system: git, (ii) an extension that handles large files: git-annex, (iii) a provenance knowledge graph: PROV-O, and (iv) an alignment between the git versioning information and the provenance knowledge graph.Results. Capabilities inherited from git and git-annex enable retracing the history of a clinical interpretation back to the patient sample, through supporting data and analyses. In addition, the provenance knowledge graph, aligned with the git versioning information, enables querying and browsing provenance relationships between these elements.Conclusion. gitOmmix adds a provenance layer to CDWs, while scaling to large files and being agnostic of the CDW system. For these reasons, we think that it is a viable and generalizable solution for omics clinical studies.

Quantum optimization has emerged as a promising frontier of quantum computing, providing novel numerical approaches to mathematical optimization problems. The main goal of this paper is to facilitate interdisciplinary research between the Operations Research (OR) and Quantum Computing communities by providing an OR scientist's perspective on selected quantum-powered methods for discrete optimization. To this end, we consider three quantum-powered optimization approaches that make use of different types of quantum hardware available on the market. To illustrate these approaches, we solve three classical optimization problems: the Traveling Salesperson Problem, Weighted Maximum Cut, and Maximum Independent Set. With a general OR audience in mind, we attempt to provide an intuition behind each approach along with key references, describe the corresponding high-level workflow, and highlight crucial practical considerations. In particular, we emphasize the importance of problem formulations and device-specific configurations, and their impact on the amount of resources required for computation (where we focus on the number of qubits). These points are illustrated with a series of experiments on three types of quantum computers: a neutral atom machine from QuEra, a quantum annealer from D-Wave, and a gate-based device from IBM., Comment: 43 pages, 18 figures, 7 tables. Technical supplement: https://alex-bochkarev.github.io/qopt-overview . Source code, problem instances, and other raw data: https://github.com/alex-bochkarev/qopt-overview

In the paper we study the Boltzmann equation in the diffusive limit in a channel domain $\mathbb{T}^2\times (-1,1)$ for the 3D kinetic Couette flow. Our results demonstrate that the first-order approximation of the solutions is governed by the perturbed incompressible Navier-Stokes-Fourier system around the fluid Couette flow. Moverover, in the absence of external forces, the 3D kinetic Couette flow asymptotically converges over time to the 1D steady planar kinetic Couette flow. Our proof relies on (i) the Fourier transform on $\mathbb{T}^2$ to essentially reduce the 3D problem to a one-dimensional one, (ii) anisotropic Chemin-Lerner type function spaces, incorporating the Wiener algebra, to control nonlinear terms and address the singularity associated with a small Knudsen number in the diffusive limit, and (iii) Caflisch's decomposition, combined with the $L^2\cap L^\infty$ interplay technique, to manage the growth of large velocities., Comment: 67 pages

Asymmetric 3D structures are observed in the outflows of evolved low- and intermediate-mass stars, and are believed to be shaped through the interaction of companions that are hidden within the dense wind. We investigate how triple systems can shape the outflow of AGB stars. We focus on coplanar systems in a hierarchical, stable orbit, consisting of an AGB star with one relatively close companion, and one at large orbital separation. We model a grid of hierarchical triple systems including a wind-launching AGB star, with the smoothed-particle-hydrodynamic Phantom code. We vary the outer companion mass, the AGB wind velocity and the orbital eccentricities to study the impact of these parameters on the wind morphology. Further, we investigate if the outflow of the AGB star R Aql could be shaped by a triple system, by post-processing one of our triple models with a radiative transfer routine, and comparing this to data of the ALMA ATOMIUM programme. The characteristic wind structures resulting from a hierarchical triple system are the following. A large two-edged spiral wake results behind the outer companion star. This structure lies on top of the spiral structure formed by the close binary, which is affected by the orbital motion around the system centre-of-mass. This dense inner spiral pattern interacts with, and strongly impacts, the spiral wake of the outer companion, resulting in a waved-pattern on the outer edge of this spiral wake. From the comparison of our models to the observations of R Aql, we conclude that this circumstellar environment might be shaped by a similar system as the ones modelled in this work, but an elaborate study of the observational data is needed to determine better the orbital parameters and characteristics of the central system., Comment: 20 pages, 19 figures

The problem of conditioning a continuous-state branching process with quadratic competition (logistic CB process) on non-extinction is investigated. We first establish that non-extinction is equivalent to the total progeny of the population being infinite. The conditioning we propose is then designed by requiring the total progeny to exceed arbitrarily large exponential random variables. This is related to a Doob's $h$-transform with an explicit excessive function $h$. The $h$-transformed process, i.e. the conditioned process, is shown to have a finite lifetime almost surely (it is either killed or it explodes continuously). When starting from positive values, the conditioned process is furthermore characterized, up to its lifetime, as the solution to a certain stochastic equation with jumps. The latter superposes the dynamics of the initial logistic CB process with an additional density-dependent immigration term. Last, it is established that the conditioned process can be starting from zero. Key tools employed are a representation of the logistic CB process through a time-changed generalized Ornstein-Uhlenbeck process, as well as Laplace and Siegmund duality relationships with auxiliary diffusion processes.

A $(v,k;r)$ Heffter space is a resolvable $(v_r,b_k)$ configuration whose points form a half-set of an abelian group $G$ and whose blocks are all zero-sum in $G$. It was recently proved that there are infinitely many orders $v$ for which, given any pair $(k,r)$ with $k\geq3$ odd, a $(v,k;r)$ Heffter space exists. This was obtained by imposing a point-regular automorphism group. Here we relax this request by asking for a point-semiregular automorphism group. In this way the above result is extended also to the case $k$ even., Comment: 8 pages

The usage of commercial Micro Aerial Vehicles (MAVs) has increased drastically during the last decade. While the added value of MAVs to society is apparent, their growing use is also coming with increasing risks like violating public airspace at airports or committing privacy violations. To mitigate these issues it is becoming critical to develop solutions that incorporate the detection and tracking of MAVs with autonomous systems. This work presents a method for the detection and tracking of MAVs using a novel, low-cost rosette scanning LiDAR on a pan-tilt turret. Once the static background is captured, a particle filter is utilized to detect a possible target and track its position with a physical, programmable pan-tilt system. The tracking makes it possible to keep the MAV in the center, maximizing the density of 3D points measured on the target by the LiDAR sensor. The developed algorithm was evaluated within the indoor MIcro aerial vehicle and MOtion capture (MIMO) arena and has state-of-the-art tracking accuracy, stability, and fast re-detection time in case of tracking loss. Based on the outdoor tests, it was possible to significantly increase the detection distance and number of returned points compared to other similar methods using LiDAR.

Artificial intelligence (AI) is increasingly used in every stage of drug development. One challenge facing drug discovery AI is that drug pharmacokinetic (PK) datasets are often collected independently from each other, often with limited overlap, creating data overlap sparsity. Data sparsity makes data curation difficult for researchers looking to answer research questions in poly-pharmacy, drug combination research, and high-throughput screening. We propose Imagand, a novel SMILES-to-Pharmacokinetic (S2PK) diffusion model capable of generating an array of PK target properties conditioned on SMILES inputs. We show that Imagand-generated synthetic PK data closely resembles real data univariate and bivariate distributions, and improves performance for downstream tasks. Imagand is a promising solution for data overlap sparsity and allows researchers to efficiently generate ligand PK data for drug discovery research. Code is available at \url{https://github.com/bing1100/Imagand}., Comment: 13 pages, 5 figures, 4 tables

Ge two-dimensional hole gases in strained modulation-doped quantum-wells represent a promising material platform for future spintronic applications due to their excellent spin transport properties and the theoretical possibility of efficient spin manipulation. Due to the continuous development of epitaxial growth recipes extreme high hole mobilities and low effective masses can be achieved, promising an efficient spin transport. Furthermore, the Ge two-dimensional hole gas (2DHG) can be integrated in the well-established industrial complementary metal-oxide-semiconductor (CMOS) devices technology. However, efficient electrical spin injection into a Ge 2DHG - a prerequisite for the realization of spintronic devices - has not yet been demonstrated. In this work, we report the fabrication and low-temperature magnetoresistance measurements of a laterally structured Mn5Ge3/Ge 2DHG/ Mn5Ge3 device. The ferromagnetic Mn5Ge3 contacts are grown directly into the Ge quantum well by means of an interdiffusion process with a spacing of approximately 130 nm. We observe a magnetoresistance signal for temperatures below 13 K possibly arising from successful spin injection. The results represent a step forward toward the realization of CMOS compatible spintronic devices based on a 2DHG., Comment: 6 figures

The problem of adopting quantum-resistant cryptographic network protocols or post-quantum cryptography (PQC) is critically important to democratizing quantum computing. The problem is urgent because practical quantum computers will break classical encryption in the next few decades. Past encrypted data has already been collected and can be decrypted in the near future. The main challenges of adopting post-quantum cryptography lie in algorithmic complexity and hardware/software/network implementation. The grand question of how existing cyberinfrastructure will support post-quantum cryptography remains unanswered. This paper describes: i) the design of a novel Post-Quantum Cryptography (PQC) network instrument placed at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign and a part of the FABRIC testbed; ii) the latest results on PQC adoption rate across a wide spectrum of network protocols (Secure Shell -- SSH, Transport Layer Security -- TLS, etc.); iii) the current state of PQC implementation in key scientific applications (e.g., OpenSSH or SciTokens); iv) the challenges of being quantum-resistant; and v) discussion of potential novel attacks. This is the first large-scale measurement of PQC adoption at national-scale supercomputing centers and FABRIC testbeds. Our results show that only OpenSSH and Google Chrome have successfully implemented PQC and achieved an initial adoption rate of 0.029% (6,044 out of 20,556,816) for OpenSSH connections at NCSA coming from major Internet Service Providers or Autonomous Systems (ASes) such as OARNET, GTT, Google Fiber Webpass (U.S.) and Uppsala Lans Landsting (Sweden), with an overall increasing adoption rate year-over-year for 2023-2024. Our analyses identify pathways to migrate current applications to be quantum-resistant., Comment: Accepted at IEEE QCE 2024

In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To address these challenges, our research explores the power of robust multi-objective optimization. Since portfolio managers frequently measure their solutions against benchmarks, we enhance the multi-objective min-regret robustness concept by incorporating these benchmark comparisons. This approach bridges the gap between theoretical models and real-world investment scenarios, offering portfolio managers more reliable and adaptable strategies for navigating market uncertainties. Our framework provides a more nuanced and practical approach to portfolio optimization under real-world conditions.

Iterative Bleaching Extends multipleXity (IBEX) is a versatile method for highly multiplexed imaging of diverse tissues. Based on open science principles, we created the IBEX Knowledge-Base, a resource for reagents, protocols and more, to empower innovation., Comment: 8 pages, 1 figure, 9 references

Volumetric neuroimaging examinations like structural Magnetic Resonance Imaging (sMRI) are routinely applied to support the clinical diagnosis of dementia like Alzheimer's Disease (AD). Neuroradiologists examine 3D sMRI to detect and monitor abnormalities in brain morphology due to AD, like global and/or local brain atrophy and shape alteration of characteristic structures. There is a strong research interest in developing diagnostic systems based on Deep Learning (DL) models to analyse sMRI for AD. However, anatomical information extracted from an sMRI examination needs to be interpreted together with patient's age to distinguish AD patterns from the regular alteration due to a normal ageing process. In this context, part-prototype neural networks integrate the computational advantages of DL in an interpretable-by-design architecture and showed promising results in medical imaging applications. We present PIMPNet, the first interpretable multimodal model for 3D images and demographics applied to the binary classification of AD from 3D sMRI and patient's age. Despite age prototypes do not improve predictive performance compared to the single modality model, this lays the foundation for future work in the direction of the model's design and multimodal prototype training process, Comment: Accepted "late-breaking work" at XAI-2024

The integrated exploitation of data sources in the mobility domain is key to providing added-value services to passengers, transport companies and authorities. Indeed, multiple stakeholders operate and maintain different kinds of data but several interoperability issues limit their effective usage. In this paper, we present an architecture enabled by Semantic Web technologies to overcome such issues and facilitate the development of an integrated solution for mobility stakeholders. The proposed solution is composed of different components that address challenges for enabling data interoperability, from the findability of data sources to their integrated consumption adopting standardised data formats. We report on the implementation and validation in four European cities of the TANGENT solution enabling data-driven tools for the dynamic management of multimodal traffic. Finally, we discuss the feedback received by users testing the solution and the lessons learnt during its development., Comment: In Use paper accepted for publication at the 23rd International Semantic Web Conference (ISWC) 2024. This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution will be published in the conference proceedings

The highest scientific return, for adaptive optics (AO) observations, is achieved with a reliable reconstruction of the PSF. This is especially true for MICADO@ELT. In this presentation, we will focus on extending the MICADO PSF reconstruction (PSF-R) method to the off-axis case. Specifically, a novel approach based on temporal-based tomography of AO telemetry data has been recently implemented. Results from the PSF-R of both simulated and real data show that, at half isoplanatic angle distances, a precision of about 10-15% is achievable in both Strehl ratio and full-width at half maximum, paving the way to extend the MICADO PSF-R tool also to the multi-conjugated AO case., Comment: 8 pages, 4 figures. Proceeding of SPIE Astronomical Telescopes + Instrumentation 2024, Adaptive Optics Systems IX

MICADO is the first-light camera of the ESO ELT, allowing NIR imaging and long-slit spectroscopy assisted by adaptive optics. MICADO is now entering its construction phase, and the software for data reduction is reaching an adequate maturity level. The PSF Reconstruction (PSF-R) of MICADO is a software tool for the blind derivation of the PSF, only using adaptive optics telemetry data. An update of the status of the PSF-R service is provided here. The PSF-R prototype has been tested on ERIS@VLT data in order to check the reconstruction of on- and off-axis PSFs. The on-axis PSF-R is accurate at a few percent level on Strehl, FWHM, Encircled Energy, and half light radius, while for the off-axis case the match is within 10-15 percent at a distance of half isoplanatic angle. The first version of the workflow for the PSF-R pipeline has been developed and verified using the latest release of the ESO data processing system. A set of simulations has been implemented on the morphological analysis of distant galaxies, showing that the accuracy of the PSF-R matches the goals needed to study their morphology. In summary, the PSF-R team is on the right track towards the ELT first light., Comment: 5 pages, 3 figures, Proceedings for the SPIE Astronomical Telescopes and Instrumentation 2024, Adaptive Optics Systems IX, Paper No.13097-234

This study comprehensively investigates the gamma-ray dim population of Fanaroff-Riley Type 0 (FR0) radio galaxies as potentially significant sources of ultra-high-energy cosmic rays (UHECRs, E $>$ 10$^{18}$ eV) detected on Earth. While individual FR0 luminosities are relatively low compared to the more powerful Fanaroff-Riley Type 1 and Type 2 galaxies, FR0s are substantially more prevalent in the local universe, outnumbering the more energetic galaxies by a factor of $\sim$5 within a redshift of z $\leq$ 0.05. Employing CRPropa3 simulations, we estimate the mass composition and energy spectra of UHECRs originating from FR0 galaxies for energies above 10$^{18.6}$ eV. This estimation fits data from the Pierre Auger Observatory (Auger) using three extensive air shower models; both constant and energy-dependent observed elemental fractions are considered. The simulation integrates an isotropic distribution of FR0 galaxies, extrapolated from observed characteristics, with UHECR propagation in the intergalactic medium, incorporating various plausible configurations of extragalactic magnetic fields, both random and structured. We then compare the resulting emission spectral indices, rigidity cutoffs, and elemental fractions with recent Auger results. In total, 25 combined energy spectrum and mass composition fits are considered. Beyond the cosmic ray fluxes emitted by FR0 galaxies, this study predicts the secondary photon and neutrino fluxes from UHECR interactions with intergalactic cosmic photon backgrounds. The multi-messenger approach, encompassing observational data and theoretical models, helps elucidate the contribution of low luminosity FR0 radio galaxies to the total cosmic ray energy density., Comment: To be submitted to The Astrophysical Journal. 22 pages, 16 figures, 6 tables

We introduce generalizations of the COGARCH model of Kl\"uppelberg et al. from 2004 and the volatility and price model of Barndorff-Nielsen and Shephard from 2001 to a Markov-switching environment. These generalizations allow for exogeneous jumps of the volatility at times of a regime switch. Both models are studied within the framework of Markov-modulated generalized Ornstein-Uhlenbeck processes which allows to derive conditions for stationarity, formulas for moments, as well as the autocovariance structure of volatility and price process. It turns out that both models inherit various properties of the original models and therefore are able to capture basic stylized facts of financial time-series such as uncorrelated log-returns, correlated squared log-returns and non-existence of higher moments in the COGARCH case., Comment: 2 figures

Submillimeter and millimeter wavelengths provide a unique view of the Universe, from the gas and dust that fills and surrounds galaxies to the chromosphere of our own Sun. Current single-dish facilities have presented a tantalising view of the brightest (sub-)mm sources, and interferometers have provided the exquisite resolution necessary to analyse the details in small fields, but there are still many open questions that cannot be answered with current facilities. In this report we summarise the science that is guiding the design of the Atacama Large Aperture Submillimeter Telescope (AtLAST). We demonstrate how tranformational advances in topics including star formation in high redshift galaxies, the diffuse circumgalactic medium, Galactic ecology, cometary compositions and solar flares motivate the need for a 50m, single-dish telescope with a 1-2 degree field of view and a new generation of highly multiplexed continuum and spectral cameras. AtLAST will have the resolution to drastically lower the confusion limit compared to current single-dish facilities, whilst also being able to rapidly map large areas of the sky and detect extended, diffuse structures. Its high sensitivity and large field of view will open up the field of submillimeter transient science by increasing the probability of serendipitous detections. Finally, the science cases listed here motivate the need for a highly flexible operations model capable of short observations of individual targets, large surveys, monitoring programmes, target of opportunity observations and coordinated observations with other observatories. AtLAST aims to be a sustainable, upgradeable, multipurpose facility that will deliver orders of magnitude increases in sensitivity and mapping speeds over current and planned submillimeter observatories., Comment: 47 pages, 12 figures. For further details on AtLAST see https://atlast.uio.no

We report a study on the dynamics of absorbing asymmetric carbon clusters trapped by a loosely focused Gaussian beam using photophoretic force. At high laser powers, all the trapped clusters display rotation coupled with oscillation along the axial direction, with a majority spinning about a body fixed axis, while the rest display dual spin as well as orbital motion about a fixed point in space. The spinning and orbiting frequency is inversely proportional to the amplitude of the axial oscillation - with one growing at the expense of the other. Further, the frequencies of these rotations are not proportional to the laser power, but to the trap stiffnesses inferred from the corresponding natural frequencies. The clusters also stop rotating below a certain laser power, and execute random thermal fluctuations. Our work suggests that the dynamics of clusters trapped with photophoretic force are largely dependent on the cluster size and morphology, which could, in principle, be tuned to obtain various motional responses, and help in the design of rotating micromachines in air.

We investigate a two-parameter extension of the $\Lambda_{\rm s}$CDM model by allowing variations in the effective number of neutrino species $N_{\rm eff}$ and their total mass $\sum m_\nu$. Our motivation is twofold: (i) to examine whether $\Lambda_{\rm s}$CDM retains its success in fitting the data and addressing major cosmological tensions, without suggesting a need for a deviation from the standard model of particle physics, and (ii) to determine whether the data indicate new physics that could potentially address cosmological tensions, either in the post-recombination universe through the late-time mirror AdS-dS transition, or in the pre-recombination universe through modifications in the standard values of $N_{\rm eff}$ and $\sum m_\nu$, or both. Within the extended $\Lambda_{\rm s}$CDM model, referred to as $\Lambda_{\rm s}$CDM+$N_{\rm eff}$+$\sum m_{\rm \nu}$, we find no significant tension when considering the Planck-alone analysis. We observe that incorporating BAO data limits the further success of the $\Lambda_{\rm s}$CDM extension. However, the weakly model-dependent BAOtr data, along with Planck and Planck+PP\&SH0ES, favor $H_0\sim 73\,{\rm km\, s^{-1}\, Mpc^{-1}}$. In cases where BAOtr dataset is used, the mirror AdS-dS transition is very effective in providing enhanced $H_0$ values, and thus the model requires no significant deviation from the standard value of $N_{\rm eff} = 3.044$. Both the $H_0$ and $S_8$ tensions are effectively addressed, with some compromise in the case of the Planck+BAO dataset. Finally, the upper bounds obtained on $\sum m_\nu \lesssim 0.5$~eV are fully compatible with neutrino oscillation experiments. Our findings provide evidence that late-time physics beyond $\Lambda$CDM, such as $\Lambda_{\rm s}$CDM, without altering the standard pre-recombination universe, can suffice to alleviate the major cosmological tensions., Comment: 20 pages, 6 figures, 3 tables

Understanding the impact of digital platforms on user behavior presents foundational challenges, including issues related to polarization, misinformation dynamics, and variation in news consumption. Comparative analyses across platforms and over different years can provide critical insights into these phenomena. This study investigates the linguistic characteristics of user comments over 34 years, focusing on their complexity and temporal shifts. Utilizing a dataset of approximately 300 million English comments from eight diverse platforms and topics, we examine the vocabulary size and linguistic richness of user communications and their evolution over time. Our findings reveal consistent patterns of complexity across social media platforms and topics, characterized by a nearly universal reduction in text length, diminished lexical richness, but decreased repetitiveness. Despite these trends, users consistently introduce new words into their comments at a nearly constant rate. This analysis underscores that platforms only partially influence the complexity of user comments. Instead, it reflects a broader, universal pattern of human behaviour, suggesting intrinsic linguistic tendencies of users when interacting online.

Controlling light propagation through complex media plays a significant role in a wide range of applications ranging from astronomical observations to microscopy. Although, several advances have been made based on adaptive optics, optical phase conjugation and wavefront shaping, but many of these involve challenges. Recently, controlling light propagation in complex media by simply structuring light has shown promising capabilities. We present experimental and numerical investigations of abruptly autofocusing of circular Airy derivative beams (CADBs) in complex media. We find that up to a relatively high turbulence strength, CADB possesses relatively good abrupt autofocusing, however, efficiency and autofocusing position vary with the strength of turbulence. Further, the spatial distortions in CADB caused by turbulence are quantified by an overlap integral, which shows that CADB possesses reasonably good resilience against the turbulence. The diffraction efficiency of CADB changes by a factor of ~ 1.7 with increasing strength of turbulence from zero to high, indicating good confinement of intensity at autofocusing. The focused beam spot size grows gradually with increasing the strength of turbulence, specifically, it grows by a factor of ~ 2 for a strong turbulence, indicating reasonably good focusing abilities. The results of CADB are compared with a Gaussian beam, and find that CADB possesses superior focusing abilities in turbulent media. We have carried out a detailed analysis of these observations based on Zernike polynomials, which reveals that different kinds of aberrations present in turbulent media leads to distortions in the spatial structure as well as other properties of CADBs. Our results can be used for various applications, such as in biomedical treatment, seismology, optical tweezers and material processing., Comment: 20 pages, 23 figures

The idea of a rapid sign-switching cosmological constant (mirror AdS-dS transition) in the late universe at $z\sim1.7$, known as the $\Lambda_{\rm s}$CDM model, has significantly improved the fit to observational data and provides a promising scenario for alleviating major cosmological tensions, such as the $H_0$ and $S_8$ tensions. However, in the absence of a fully predictive model, implementing this fit required conjecturing that the dynamics of the linear perturbations are governed by general relativity. Recent work embedding the $\Lambda_{\rm s}$CDM model with the Lagrangian of a type-II minimally modified gravity known as VCDM has propelled $\Lambda_{\rm s}$CDM to a fully predictive model, removing the uncertainty related to the aforementioned assumption; we call this new model $\Lambda_{\rm s}$VCDM. In this work, we demonstrate that not only does $\Lambda_{\rm s}$CDM fit the data better than the standard $\Lambda$CDM model, but the new model, $\Lambda_{\rm s}$VCDM, performs even better in alleviating cosmological tensions while also providing a better fit to the data, including CMB, BAO, SNe Ia, and Cosmic Shear measurements. Our findings highlight the $\Lambda_{\rm s}$CDM framework, particularly the $\Lambda_{\rm s}$VCDM model, as a compelling alternative to the standard $\Lambda$CDM model, especially by successfully alleviating the $H_0$ tension. Additionally, these models predict higher values for $\sigma_8$, indicating enhanced structuring, albeit with lower present-day matter density parameter values and consequently reduced $S_8$ values, alleviating the $S_8$ tension as well. This demonstrates that the data are well fit by a combination of background and linear perturbations, both having dynamics differing from those of $\Lambda$CDM. This paves the way for further exploration of new ways for embedding the sign-switching cosmological constant into other models., Comment: 15 pages, 5 figures, 2 tables

The dimer (monomer-dimer) model deals with weighted enumeration of perfect matchings (matchings). The monopole-dimer model is a signed variant of the monomer-dimer model whose partition function is a determinant. In 1999, Lu and Wu evaluated the partition function of the dimer model on two-dimensional grids embedded on a M\"obius strip and a Klein bottle. While the partition function of the dimer model has been known for the two-dimensional grids with different boundary conditions, we present a similar product formula for the partition function of the monopole-dimer model on higher dimensional cylindrical and toroidal grid graphs. We also evaluate the same for the three-dimensional M\"obius and Klein grid graphs and show that the formula does not generalise for the higher dimensions. Further, we present a relation between the product formula for the three-dimensional cylindrical and M\"obius grid., Comment: 25 pages, 9 figures

Science, Technology, Engineering, and Mathematics classes are mainly taught using visual supports. However, the advancement of technology and the increasing eforts to equip schools with digital instrumentation have opened up the possibility of exploring new teaching avenues, such as sonifcation. We explored the efcacy of sonifcation in education using a novel interactive tool, Edukoi, in the context of astronomy, which is predominantly disseminated through spectacular images, animations, and visuals. Edukoi is a motion-sensing sonifcation tool that converts images to sound in real-time for educational applications. Our study, conducted with nearly 150 middle-school students, included a preliminary questionnaire investigating the perception, engagement, and motivation of students towards science; two sessions dedicated to testing Edukoi and assessing the potentiality of the software for the recognition of the colour and the shape of real and sketchy images; and a fnal second administration of the questionnaire to capture a possible benefcial efect of the use of the tool in the engagement towards science. Results showed the efectiveness of Edukoi in colour recognition and reasonable efcacy in shape identifcation. Although the questionnaire did not reveal an increment in science engagement over the time of the study, oral feedback from the students was positive. Edukoi presents a possible alternative teaching aid, potentially benefting diverse learners, including the visually impaired. Further developments of the software are needed to enhance its efectiveness in conveying more complex features such as composite colours or shapes.

We explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$., Comment: 28 pages, 7 figures, 4 tables

As a result of rapidly accelerating AI capabilities, over the past year, national governments and multinational bodies have announced efforts to address safety, security and ethics issues related to AI models. One high priority among these efforts is the mitigation of misuse of AI models. Many biologists have for decades sought to reduce the risks of scientific research that could lead, through accident or misuse, to high-consequence disease outbreaks. Scientists have carefully considered what types of life sciences research have the potential for both benefit and risk (dual-use), especially as scientific advances have accelerated our ability to engineer organisms and create novel variants of pathogens. Here we describe how previous experience and study by scientists and policy professionals of dual-use capabilities in the life sciences can inform risk evaluations of AI models with biological capabilities. We argue that AI model evaluations should prioritize addressing high-consequence risks (those that could cause large-scale harm to the public, such as pandemics), and that these risks should be evaluated prior to model deployment so as to allow potential biosafety and/or biosecurity measures. Scientists' experience with identifying and mitigating dual-use biological risks can help inform new approaches to evaluating biological AI models. Identifying which AI capabilities post the greatest biosecurity and biosafety concerns is necessary in order to establish targeted AI safety evaluation methods, secure these tools against accident and misuse, and avoid impeding immense potential benefits., Comment: 9 pages, 1 figure, 3 tables, 1 box