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To date there is little publicly available scientific data on Unidentified Aerial Phenomena (UAP) whose properties and kinematics purportedly reside outside the performance envelope of known phenomena. To address this deficiency, the Galileo Project is designing, building, and commissioning a multi-modal ground-based observatory to continuously monitor the sky and conduct a rigorous long-term aerial census of all aerial phenomena, including natural and human-made. One of the key instruments is an all-sky infrared camera array using eight uncooled long-wave infrared FLIR Boson 640 cameras. Their calibration includes a novel extrinsic calibration method using airplane positions from Automatic Dependent Surveillance-Broadcast (ADS-B) data. We establish a first baseline for the system performance over five months of field operation, using a real-world dataset derived from ADS-B data, synthetic 3-D trajectories, and a hand-labelled real-world dataset. We report acceptance rates (e.g. viewable airplanes that are recorded) and detection efficiencies (e.g. recorded airplanes which are successfully detected) for a variety of weather conditions, range and aircraft size. We reconstruct $\sim$500,000 trajectories of aerial objects from this commissioning period. A toy outlier search focused on large sinuosity of the 2-D reconstructed trajectories flags about 16% of trajectories as outliers. After manual review, 144 trajectories remain ambiguous: they are likely mundane objects but cannot be elucidated at this stage of development without distance and kinematics estimation or other sensor modalities. Our observed count of ambiguous outliers combined with systematic uncertainties yields an upper limit of 18,271 outliers count for the five-month interval at a 95% confidence level. This likelihood-based method to evaluate significance is applicable to all of our future outlier searches.

Summarization is one of the most common tasks performed by large language models (LLMs), especially in applications like Retrieval-Augmented Generation (RAG). However, existing evaluations of hallucinations in LLM-generated summaries, and evaluations of hallucination detection models both suffer from a lack of diversity and recency in the LLM and LLM families considered. This paper introduces FaithBench, a summarization hallucination benchmark comprising challenging hallucinations made by 10 modern LLMs from 8 different families, with ground truth annotations by human experts. ``Challenging'' here means summaries on which popular, state-of-the-art hallucination detection models, including GPT-4o-as-a-judge, disagreed on. Our results show GPT-4o and GPT-3.5-Turbo produce the least hallucinations. However, even the best hallucination detection models have near 50\% accuracies on FaithBench, indicating lots of room for future improvement. The repo is https://github.com/vectara/FaithBench

Recent advances in Retrieval-Augmented Generation (RAG) systems have popularized semantic chunking, which aims to improve retrieval performance by dividing documents into semantically coherent segments. Despite its growing adoption, the actual benefits over simpler fixed-size chunking, where documents are split into consecutive, fixed-size segments, remain unclear. This study systematically evaluates the effectiveness of semantic chunking using three common retrieval-related tasks: document retrieval, evidence retrieval, and retrieval-based answer generation. The results show that the computational costs associated with semantic chunking are not justified by consistent performance gains. These findings challenge the previous assumptions about semantic chunking and highlight the need for more efficient chunking strategies in RAG systems.

The research builds and evaluates the adversarial potential to introduce copied code or hallucinated AI recommendations for malicious code in popular code repositories. While foundational large language models (LLMs) from OpenAI, Google, and Anthropic guard against both harmful behaviors and toxic strings, previous work on math solutions that embed harmful prompts demonstrate that the guardrails may differ between expert contexts. These loopholes would appear in mixture of expert's models when the context of the question changes and may offer fewer malicious training examples to filter toxic comments or recommended offensive actions. The present work demonstrates that foundational models may refuse to propose destructive actions correctly when prompted overtly but may unfortunately drop their guard when presented with a sudden change of context, like solving a computer programming challenge. We show empirical examples with trojan-hosting repositories like GitHub, NPM, NuGet, and popular content delivery networks (CDN) like jsDelivr which amplify the attack surface. In the LLM's directives to be helpful, example recommendations propose application programming interface (API) endpoints which a determined domain-squatter could acquire and setup attack mobile infrastructure that triggers from the naively copied code. We compare this attack to previous work on context-shifting and contrast the attack surface as a novel version of "living off the land" attacks in the malware literature. In the latter case, foundational language models can hijack otherwise innocent user prompts to recommend actions that violate their owners' safety policies when posed directly without the accompanying coding support request.

The Charting Cluster Construction with VUDS and ORELSE (C3VO) survey is an ongoing imaging and spectroscopic campaign aiming to map out the growth of structure up to $z\sim5$ and was born from the combination of the VIMOS Ultra Deep Survey (VUDS) and the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) survey. As we previously accomplished with the ORELSE survey, we apply our technique known as Voronoi tessellation Monte-Carlo (VMC) mapping to search for serendipitous galaxy overdensities at $2 14$. In the C3VO fields, we were able to recover many of the previously known structures in the literature as well as find hundreds of new overdensity candidates, once again demonstrating the powerful capabilities of VMC mapping when applied to wide-field optical and infrared galaxy evolution surveys at ever higher redshifts., Comment: 36 pages, 16 figures, 5 tables, submitted to ApJ

We present MM1.5, a new family of multimodal large language models (MLLMs) designed to enhance capabilities in text-rich image understanding, visual referring and grounding, and multi-image reasoning. Building upon the MM1 architecture, MM1.5 adopts a data-centric approach to model training, systematically exploring the impact of diverse data mixtures across the entire model training lifecycle. This includes high-quality OCR data and synthetic captions for continual pre-training, as well as an optimized visual instruction-tuning data mixture for supervised fine-tuning. Our models range from 1B to 30B parameters, encompassing both dense and mixture-of-experts (MoE) variants, and demonstrate that careful data curation and training strategies can yield strong performance even at small scales (1B and 3B). Additionally, we introduce two specialized variants: MM1.5-Video, designed for video understanding, and MM1.5-UI, tailored for mobile UI understanding. Through extensive empirical studies and ablations, we provide detailed insights into the training processes and decisions that inform our final designs, offering valuable guidance for future research in MLLM development.

We conduct a study on the relationship between galaxy environments and their active galactic nuclei (AGN) activity at high redshifts ($2.010^{12.8}M_\odot$) overdense ($\sigma_\delta>5.0$) peak, normalized with respect to the size of the peak. These findings indicate that the prevalence of AGN activity is highly dependent on the environment in which a host galaxy resides, even at early times in the formation history of the Universe., Comment: 15 pages, 11 figures, submitted to A&A, comments welcome

Students who perform well at school academically are more likely to complete Year 12 and experience smoother transitions from education to employment. However, disentangling the effects of prior academic achievement on later performance from other confounding factors, such as socioeconomic status, has proved difficult. This study uses data from the Longitudinal Surveys of Australian Youth (LSAY), in conjunction with data from the National Assessment Program -- Literacy and Numeracy (NAPLAN) and MySchool, to consider the contextual factors that affect a student's academic trajectory. Using measures of students' academic achievement, demographic factors, information about the school they attended and subsequent outcomes, the study explores the association between students' academic performance at school and their schooling outcomes, as evidenced by their Australian Tertiary Admissions Rank (ATAR). It investigates whether Year 9 NAPLAN scores can be used to predict students' likelihood of obtaining an ATAR upon completing Year 12, and the likelihood of obtaining a high ATAR, controlling for several demographic characteristics.

Apprenticeships remain an important source of skilled workers in Australia; however, commencements have not kept pace with the skills demand projected in the previous decade. During that same decade, undergraduate university enrolments grew considerably. In investigating whether young people who would previously have chosen an apprenticeship have instead entered university, this study uses data from the Longitudinal Surveys of Youth (LSAY) to compare the characteristics of apprenticeship-bound young people with those who are university-bound and to determine whether the characteristics have changed between 2007 and 2019.

This paper studies the pricing of contingent claims of American style, using indifference pricing by fully dynamic convex risk measures. We provide a general definition of risk-indifference prices for buyers and sellers in continuous time, in a setting where buyer and seller have potentially different information, and show that these definitions are consistent with no-arbitrage principles. Specifying to stochastic volatility models, we characterize indifference prices via solutions of Backward Stochastic Differential Equations reflected at Backward Stochastic Differential Equations and show that this characterization provides a basis for the implementation of numerical methods using deep learning., Comment: 18 pages, 3 figures

How do complex adaptive systems, such as life, emerge from simple constituent parts? In the 1990s Walter Fontana and Leo Buss proposed a novel modeling approach to this question, based on a formal model of computation known as $\lambda$ calculus. The model demonstrated how simple rules, embedded in a combinatorially large space of possibilities, could yield complex, dynamically stable organizations, reminiscent of biochemical reaction networks. Here, we revisit this classic model, called AlChemy, which has been understudied over the past thirty years. We reproduce the original results and study the robustness of those results using the greater computing resources available today. Our analysis reveals several unanticipated features of the system, demonstrating a surprising mix of dynamical robustness and fragility. Specifically, we find that complex, stable organizations emerge more frequently than previously expected, that these organizations are robust against collapse into trivial fixed-points, but that these stable organizations cannot be easily combined into higher order entities. We also study the role played by the random generators used in the model, characterizing the initial distribution of objects produced by two random expression generators, and their consequences on the results. Finally, we provide a constructive proof that shows how an extension of the model, based on typed $\lambda$ calculus, could simulate transitions between arbitrary states in any possible chemical reaction network, thus indicating a concrete connection between AlChemy and chemical reaction networks. We conclude with a discussion of possible applications of AlChemy to self-organization in modern programming languages and quantitative approaches to the origin of life.

We report on the rejuvenation of thin films of polystyrene (PS) as they are heated from stable glassy states - prepared either through vapour deposition or physical aging. For films with thickness $h \gtrsim 200$ nm, the rejuvenation of vapour deposited stable PS glass films follow behaviour well-documented for other stable glasses. For films with thickness $h \lesssim 160$nm the behaviour of the vapour deposited films becomes more complicated. This behaviour is characterized for different film thicknesses. The results are compared with vapour deposited films that are aged after rejuvenation or spincast and aged. Collectively, the results of these studies strongly suggest two distinct mechanisms that can result in rejuvenation, and hence two distinct relaxation processes that can couple to the material density. The two physical mechanisms can provide insight into poorly understood or apparently contradictory aspects of $T_g$ measurements in thin PS films.

The rapid growth in natural language processing (NLP) over the last couple years has generated student interest and excitement in learning more about the field. In this paper, we present two types of students that NLP courses might want to train. First, an "NLP engineer" who is able to flexibly design, build and apply new technologies in NLP for a wide range of tasks. Second, an "NLP scholar" who is able to pose, refine and answer questions in NLP and how it relates to the society, while also learning to effectively communicate these answers to a broader audience. While these two types of skills are not mutually exclusive -- NLP engineers should be able to think critically, and NLP scholars should be able to build systems -- we think that courses can differ in the balance of these skills. As educators at Small Liberal Arts Colleges, the strengths of our students and our institution favors an approach that is better suited to train NLP scholars. In this paper we articulate what kinds of skills an NLP scholar should have, and then adopt a backwards design to propose course components that can aid the acquisition of these skills., Comment: 9 pages, Presented at 6th Workshop on Teaching NLP

We developed several combinatorial notions about these laminations some with clear implications for parameter space. We introduce a simplified class of laminations called finite dynamical laminations (FDL). In order to count FDL, we introduce sibling portraits, of which we provide a comprehensive counting theorem. We introduce the pullback tree, and show that all FDL have a child in it. This gives a characterization of which periodic polygons appear in invariant laminations. The base of the pullback tree is a set of laminations, and we show that those laminations have very nice properties. We define the generational FDL graph, and it provides a summary of the combinatorial information we provide about polynomial parameter space., Comment: 18 pages, 9 figures

In the interplanetary space solar wind plasma, whistler waves are observed in a wide range of heliocentric distance (from ~20 solar radii (RS) to Jupiter's orbit). They are known to interact with solar wind suprathermal electrons (strahl and halo) and to regulate the solar wind heat flux through scattering the strahl electrons. We present the results of applying the technique to determine the whistler wave propagation direction to the spectral data continuously collected by the FIELDS instruments aboard Parker Solar Probe (PSP). The technique was validated based on the results obtained from burst mode magnetic and electric field waveform data collected during Encounter 1. We estimated the effective length of the PSP electric field antennas (EFI) for a variety of solar wind conditions in the whistler wave frequency range and utilized these estimates for determining the whistler wave properties during PSP Encounters 1-11. Our findings show that (1) the enhancement of the whistler wave occurrence rate and wave amplitudes observed between 25-35 RS is predominantly due to the sunward propagating whistler waves population associated with the switchback-related magnetic dips; (2) the anti-sunward or counter-propagating cases are observed at 30-40 RS; (3) between 40-50 RS, sunward and anti-sunward whistlers are observed with comparable occurrence rates; and (4) almost no sunward or counter-propagating whistlers were observed at heliocentric distances above 50 RS., Comment: Accepted for publication in ApJ

We investigate closed knight's tours on M\"obius strip and Klein bottle chess boards. In particular, we characterize the board dimensions that admit tours that are nullhomotopic and the board dimensions that admit tours that realize generators of the fundamental groups of each of the surfaces., Comment: 33 pages, 23 figures

Filaments of cold gas ($T\leq 10^{4}$ K) are found in the inner regions of many cool-core clusters. These structures are thought to play a major role in the regulation of feedback from active galactic nuclei (AGN). We study the morphology of the filaments, their formation, and their impact on the propagation of the outflowing AGN jets. We present a set of GPU-accelerated 3D (magneto)hydrodynamical simulations of an idealized Perseus-like cluster using the performance portable code AthenaPK. We include radiative cooling, and a self-regulated AGN feedback model that redistributes accreted material through kinetic, thermal and magnetic feedback. We confirm that magnetic fields play an important role in both the formation and evolution of the cold material. These suppress the formation of massive cold disks and favor magnetically supported filaments over clumpy structures. Achieving resolutions of $25-50$ pc, we find that filaments are not monolithic as they contain numerous and complex magnetically--supported substructures. We find that the mass distribution of these clumps follows a power law for all investigated filaments, consistent with previous cloud-crushing simulations of individual clumps. Studying the evolution of individual filaments, we find that their formation pathways can be diverse. We find examples of filaments forming through a combination of cold gas uplifting and condensation, as well as systems of purely infalling clumps condensing out of the intracluster medium. The density contrast between the cold gas and the outflowing hot material leads to recurring deflections of the jets, favoring inflation of bubbles., Comment: 19 pages, 19 figures, submitted to Astronomy & Astrophysics

We present an analysis of the number density of galaxies as a function of stellar mass (i.e., the stellar mass function, SMF) in the COSMOS field at z~3.3, making a comparison between the SMF in overdense environments and the SMF in the coeval field. In particular, this region contains the Elent\'ari proto-supercluster, a system of 6 extended overdensities spanning ~70 cMpc on a side. A clear difference is seen in the high-mass slope of these SMFs, with overdense regions showing an increase in the ratio of high-mass galaxies to low-mass galaxies relative to the field, indicating a more rapid build-up of stellar mass in overdense environments. This result qualitatively agrees with analyses of clusters at z~1, though the differences between protocluster and field SMFs at z~3.3 are smaller. While this is consistent with overdensities enhancing the evolution of their member galaxies, potentially through increased merger rates, whether this enhancement begins in protocluster environments or even earlier in group environments is still unclear. Though the measured fractions of quiescent galaxies between the field and overdense environments do not vary significantly, implying that this stellar mass enhancement is ongoing and any starbursts triggered by merger activity have not yet quenched, we note that spectroscopic observations are biased towards star-forming populations, particularly for low-mass galaxies. If mergers are indeed responsible, high resolution imaging of Elent\'ari and similar structures at these early epochs should then reveal increased merger rates relative to the field. Larger samples of well-characterized overdensities are necessary to draw broader conclusions in these areas., Comment: 15 pages, 8 figures, plus references and appendices. Submitted to ApJ, posted after responding to referee comments. Further comments welcome

Layout design generation has recently gained significant attention due to its potential applications in various fields, including UI, graphic, and floor plan design. However, existing models face two main challenges that limits their adoption in practice. Firstly, the limited expressiveness of individual condition types used in previous works restricts designers' ability to convey complex design intentions and constraints. Secondly, most existing models focus on generating labels and coordinates, while real layouts contain a range of style properties. To address these limitations, we propose a novel framework, CoLay, that integrates multiple condition types and generates complex layouts with diverse style properties. Our approach outperforms prior works in terms of generation quality and condition satisfaction while empowering users to express their design intents using a flexible combination of modalities, including natural language prompts, layout guidelines, element types, and partially completed designs.

Learning from human feedback has shown success in aligning large, pretrained models with human values. Prior works have mostly focused on learning from high-level labels, such as preferences between pairs of model outputs. On the other hand, many domains could benefit from more involved, detailed feedback, such as revisions, explanations, and reasoning of human users. Our work proposes using nuanced feedback through the form of human revisions for stronger alignment. In this paper, we ask expert designers to fix layouts generated from a generative layout model that is pretrained on a large-scale dataset of mobile screens. Then, we train a reward model based on how human designers revise these generated layouts. With the learned reward model, we optimize our model with reinforcement learning from human feedback (RLHF). Our method, Revision-Aware Reward Models ($\method$), allows a generative text-to-layout model to produce more modern, designer-aligned layouts, showing the potential for utilizing human revisions and stronger forms of feedback in improving generative models.

Machine learning (ML) now pervades the field of Automated Program Repair (APR). Algorithms deploy neural machine translation and large language models (LLMs) to generate software patches, among other tasks. But, there are important differences between these applications of ML and earlier work. Evaluations and comparisons must take care to ensure that results are valid and likely to generalize. A challenge is that the most popular APR evaluation benchmarks were not designed with ML techniques in mind. This is especially true for LLMs, whose large and often poorly-disclosed training datasets may include problems on which they are evaluated., Comment: 16 pages, 1 table, submitted to ACM Computing Surveys

The nature of the first galaxies that reionized the universe during the Epoch of Reionization (EoR) remains unclear. Attempts to directly determine spectral properties of these early galaxies are affected by both limited photometric constraints across the spectrum and by the opacity of the intergalactic medium (IGM) to the Lyman Continuum (LyC) at high redshift. We approach this by analysing properties of analogous extreme emission line galaxies (EELGs, [OIII]+Hbeta EW $>400$ Angstrom) at $2.55.5$ observed with the James Webb Space Telesope (JWST) with self-consistent spectral energy distribution fitting methodology. This work focuses on the comparison of their UV slopes ($\beta_P$), ionizing photon production efficiencies $\xi_{ion}$, star formation rates and dust properties to determine the effectiveness of this analogue selection technique. We report the median ionizing photon production efficiencies as log$_{10}(\xi_{ion}/(Hz\ {\rm erg}^{-1}))=$$25.14^{+0.06}_{-0.04}$,$25.16^{+0.06}_{-0.05}$,$25.16^{+0.04}_{-0.05}$,$25.18^{+0.06}_{-0.07}$ for our ZFOURGE control, ZFOURGE EELG, JADES and CEERS samples respectively. ZFOURGE EELGs are 0.57 dex lower in stellar mass and have half the dust extinction, compared to their ZFOURGE control counterparts. They also have a similar specific star formation rates and $\beta_P$ to the $z>5.5$ samples. We find that EELGs at low redshift ($2.5

With dynamic pricing on the rise, firms are using sophisticated algorithms for price determination. These algorithms are often non-interpretable and there has been a recent interest in their seemingly emergent ability to tacitly collude with each other without any prior communication whatsoever. Most of the previous works investigate algorithmic collusion on simple reinforcement learning (RL) based algorithms operating on a basic market model. Instead, we explore the collusive tendencies of Proximal Policy Optimization (PPO), a state-of-the-art continuous state/action space RL algorithm, on a complex double-sided hierarchical market model of rideshare. For this purpose, we extend a mathematical program network (MPN) based rideshare model to a temporal multi origin-destination setting and use PPO to solve for a repeated duopoly game. Our results indicate that PPO can either converge to a competitive or a collusive equilibrium depending upon the underlying market characteristics, even when the hyper-parameters are held constant., Comment: 8 pages, 6 figures

We report on our experiences replicating 7.3 petabytes (PB) of Earth System Grid Federation (ESGF) climate simulation data from Lawrence Livermore National Laboratory (LLNL) in California to Argonne National Laboratory (ANL) in Illinois and Oak Ridge National Laboratory (ORNL) in Tennessee. This movement of some 29 million files, twice, undertaken in order to establish new ESGF nodes at ANL and ORNL, was performed largely automatically by a simple replication tool, a script that invoked Globus to transfer large bundles of files while tracking progress in a database. Under the covers, Globus organized transfers to make efficient use of the high-speed Energy Sciences network (ESnet) and the data transfer nodes deployed at participating sites, and also addressed security, integrity checking, and recovery from a variety of transient failures. This success demonstrates the considerable benefits that can accrue from the adoption of performant data replication infrastructure.

We present rest-frame optical spectra from Keck/MOSFIRE and Keck/NIRES of 16 candidate ultramassive galaxies targeted as part of the Massive Ancient Galaxies at $z>3$ Near-Infrared (MAGAZ3NE) Survey. These candidates were selected to have photometric redshifts $3\lesssim z_{\rm phot}<4$, photometric stellar masses log($M$/M$_\odot$)$>11.7$, and well-sampled photometric spectral energy distributions (SEDs) from the UltraVISTA and VIDEO surveys. In contrast to previous spectroscopic observations of blue star-forming and post-starburst ultramassive galaxies, candidates in this sample have very red SEDs implying significant dust attenuation, old stellar ages, and/or active galactic nuclei (AGN). Of these galaxies, eight are revealed to be heavily dust-obscured $2.03$, one is a $z\sim1.2$ dusty galaxy, and four galaxies do not have a confirmed spectroscopic redshift. In fact, none of the sample has |$z_{\rm spec}-z_{\rm phot}$|$<0.5$, suggesting difficulties for photometric redshift programs in fitting similarly red SEDs. The prevalence of these red interloper galaxies suggests that the number densities of high-mass galaxies are overestimated at $z\gtrsim3$ in large photometric surveys, helping to resolve the `impossibly early galaxy problem' and leading to much better agreement with cosmological galaxy simulations. A more complete spectroscopic survey of ultramassive galaxies is required to pin down the uncertainties on their number densities in the early universe., Comment: Accepted for publication in ApJ

We present spectroscopic confirmation of an ultra-massive galaxy (UMG) with $\log(M_\star/M_\odot) = 10.98 \pm 0.07$ at $z_\mathrm{spec} = 4.8947$ in the Extended Groth Strip (EGS), based on deep observations of Ly$\alpha$ emission with Keck/DEIMOS. The ultra-massive galaxy (UMG-28740) is the most massive member in one of the most significant overdensities in the EGS, with four additional photometric members with $\log(M_\star/M_\odot) > 10.5$ within $R_\mathrm{proj} \sim 1$ cMpc. The Ly$\alpha$ profile is highly asymmetric ($A_f = 3.56$), suggesting the presence of neutral gas within the interstellar medium, circumgalactic medium, or via AGN-driven outflows. Spectral energy distribution (SED) fitting using a large suite of star formation histories and two sets of high-quality photometry from ground- and space-based facilities consistently estimates the stellar mass of UMG-28740 to be $\log(M_\star/M_\odot) \sim 11$ with a small standard deviation between measurements ($\sigma = 0.07$). While the best-fit SED models agree on stellar mass, we find discrepancies in the estimated star formation rate for UMG-28740, resulting in either a star-forming or quiescent system. JWST/NIRCam photometry of UMG-28740 strongly favors a quiescent scenario, demonstrating the need for high-quality mid-IR observations. Assuming the galaxy to be quiescent, UMG-28740 formed the bulk of its stars at $z > 10$ and is quenching at $z \sim 8$, resulting in a high star formation efficiency at high redshift ($\epsilon \sim 0.2$ at $z \sim 5$ and $\epsilon \gtrsim 1$ at $z \gtrsim 8$). As the most massive galaxy in its protocluster environment, UMG-28740 is a unique example of the impossibly early galaxy problem., Comment: 11 pages, 6 figures, 2 tables, Accepted to OJA

Introduction: Chronic pain patients are at increased risk of opioid-misuse. Less is known about the unique risk conferred by each pain-management treatment, as treatments are typically implemented together, confounding their independent effects. We estimated the extent to which pain-management strategies were associated with risk of incident opioid use disorder (OUD) for those with chronic pain, controlling for baseline demographic and clinical confounding variables and holding other pain-management treatments at their observed levels. Methods: We used data from two chronic pain subgroups within a cohort of non-pregnant Medicaid patients aged 35-64 years, 2016-2019, from 25 states: 1) those with a chronic pain condition co-morbid with physical disability (N=6,133) or 2) those with chronic pain without disability (N=67,438). We considered 9 pain-management treatments: prescription opioid i) dose and ii) duration; iii) number of opioid prescribers; opioid co-prescription with iv) benzodiazepines, v) muscle relaxants, and vi) gabapentinoids; vii) non-opioid pain prescription, viii) physical therapy, and ix) other pain treatment modality. Our outcome was incident OUD. Results: Having an opioid and gabapentin co-prescription or an opioid and benzodiazepine co-prescription was statistically significantly associated with a 16-46% increased risk of OUD. Opioid dose and duration also were significantly associated with increased risk of OUD. Physical therapy was significantly associated with an 11% decreased risk of OUD in the subgroup with chronic pain but no disability. Conclusions: Co-prescription of opioids with either gabapentin or benzodiazepines may substantially increase risk of OUD. More positively, physical therapy may be a relatively accessible and safe pain-management strategy.

Gig economy consists of two market groups connected via an intermediary. Popular examples are rideshares where passengers and drivers are mediated via platforms such as Uber and Lyft. In a duopoly market, the platforms must compete to attract not only the passengers by providing a lower rate but also the drivers by providing better wages. While this should indicate better driver payout, as platforms compete to attract the driver pool, real world statistics does not indicate such. This goes completely against the intuition that the worker side of a gig economy, given their importance, should always earn better. We attempt to answer the low wages of drivers in the gig economy by modeling the ridesharing game between duopoly platforms, drivers, and passengers using Mathematical Program Networks. Our model is parsimonious, expressive, models the same-side and cross-side externalities of the economy, and has interpretations under both single-homing and multi-homing regimes. We derive the conditions for the existence of a profitable duopoly and show that it can only happen if the platforms collude together to pay the bare minimum to the drivers. This not only answers why drivers are paid less but also provides strong managerial insights to any interested policy maker.

The widespread adoption of voice-activated systems has modified routine human-machine interaction but has also introduced new vulnerabilities. This paper investigates the susceptibility of automatic speech recognition (ASR) algorithms in these systems to interference from near-ultrasonic noise. Building upon prior research that demonstrated the ability of near-ultrasonic frequencies (16 kHz - 22 kHz) to exploit the inherent properties of microelectromechanical systems (MEMS) microphones, our study explores alternative privacy enforcement means using this interference phenomenon. We expose a critical vulnerability in the most common microphones used in modern voice-activated devices, which inadvertently demodulate near-ultrasonic frequencies into the audible spectrum, disrupting the ASR process. Through a systematic analysis of the impact of near-ultrasonic noise on various ASR systems, we demonstrate that this vulnerability is consistent across different devices and under varying conditions, such as broadcast distance and specific phoneme structures. Our findings highlight the need to develop robust countermeasures to protect voice-activated systems from malicious exploitation of this vulnerability. Furthermore, we explore the potential applications of this phenomenon in enhancing privacy by disrupting unauthorized audio recording or eavesdropping. This research underscores the importance of a comprehensive approach to securing voice-activated systems, combining technological innovation, responsible development practices, and informed policy decisions to ensure the privacy and security of users in an increasingly connected world.

Mathematical Program Networks (MPNs) are introduced in this work. An MPN is a collection of interdependent Mathematical Programs (MPs) which are to be solved simultaneously, while respecting the connectivity pattern of the network defining their relationships. The network structure of an MPN impacts which decision variables each constituent mathematical program can influence, either directly or indirectly via solution graph constraints representing optimal decisions for their decedents. Many existing problem formulations can be formulated as MPNs, including Nash Equilibrium problems, multilevel optimization problems, and Equilibrium Programs with Equilibrium Constraints (EPECs), among others. The equilibrium points of an MPN correspond with the equilibrium points or solutions of these other problems. By thinking of a collection of decision problems as an MPN, a common definition of equilibrium can be used regardless of relationship between problems, and the same algorithms can be used to compute solutions. The presented framework facilitates modeling flexibility and analysis of various equilibrium points in problems involving multiple mathematical programs.

We present the discovery of a unique Lyman-continuum (LyC) emitter at z=3.088. The LyC emission were detected using the Hubble Space Telescope (HST) WFC3/UVIS F336W filter, covering a rest-frame wavelength range of 760-900 Angstrom. The peak signal-to-noise ratio (SNR) of LyC emission is 3.9 in a r=0.24'' aperture and is spatially offset by 0.29''+/-0.04'' (~ 2.2+/-0.3 kpc) from the rest-UV emission peak (F606W). By combining imaging and spectroscopic data from the James Webb Space Telescope (JWST) JADES, FRESCO and JEMS surveys, along with VLT/MUSE data from the MXDF survey, we estimate that the probability of random alignment with an interloper galaxy causing the LyC emission is less than 6x10^-5. The interstellar medium (ISM) conditions in the galaxy are similar to other LyC emitters at high redshift (12+log(O/H)=7.79+/-0.06, logU =-3.27+/-0.14, O32 = 3.65+/-0.22), although the single-peaked Lyman-alpha profile and lack of rest-UV emission lines suggest an optically thick ISM. We think that LyC photons are leaking through a narrow cone of optically thin neutral ISM, most likely created by a past merger (as evidenced by medium-band F210M and F182M images). Using the escape fraction constraints from individual leakers and a simple model, we estimate that the opening half-angle of ionization cones can be as low as 16^deg (2% ionised fraction) to reproduce some of the theoretical constraints on the average escape fraction for galaxies. The narrow opening angle required can explain the low number density of confirmed LyC leakers., Comment: 12 pages, 8 figures, and 1 table. Submitted to The Astrophysical Journal

Technical Debt, considered by many to be the 'silent killer' of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or inadvertently. We understand Technical Debt is not all derogatory, often serving the purpose of expediency. But, it is associated with a clear risk, especially for large and complex systems with extended service life: if we do not properly manage Technical Debt, it threatens to "bankrupt" those systems. Software engineers and organizations that develop software-intensive systems are facing an increasingly more dire future state of those systems if they do not start incorporating Technical Debt management into their day to day practice. But how? What have the wins and losses of the past decade of research and practice in managing Technical Debt taught us and where should we focus next? In this paper, we examine the state of the art in both industry and research communities in managing Technical Debt; we subsequently distill the gaps in industrial practice and the research shortcomings, and synthesize them to define and articulate a vision for what Technical Debt management looks like five years hence., Comment: 16 pages

$\textit{AIMS.}$ To investigate processes associated with generation of type-III radiation. $\textit{METHODS.}$ Measure the amplitudes and phase velocities of Parker Solar Probe observed electric fields, magnetic fields, and plasma density fluctuations. $\textit{RESULTS.}$ (1) There are slow electrostatic waves near the Langmuir frequency and at as many as six harmonics, the number of which increases with the amplitude of the Langmuir wave. Their electrostatic nature is shown by measurement of the plasma density fluctuations. From these density fluctuations and the electric field magnitude, the k-value of the Langmuir wave is estimated to be 0.14 and $k \lambda_d$ = 0.4. Even with a large uncertainty in this quantity (more than a factor of two) the phase velocity of the Langmuir wave was <10,000 km/sec. (2) There is an electromagnetic wave near the Langmuir frequency having a phase velocity <50,000 km/sec. (3) Whether there are electromagnetic waves at the harmonics of the Langmuir frequency cannot be determined because, if they existed, their magnetic field components would be below the noise level of the measurement. (4) The rapid (less than one msec) amplitude variations typical of the Langmuir wave and its harmonics are artifacts resulting from addition of two waves, one of which has small frequency variations that arise from traveling through density irregularities. None of these results are expected in or consistent with the conventional model of the three-wave interaction of two counter-streaming Langmuir waves that coalesce to produce the type-III wave. They are consistent with a new model in which electrostatic antenna waves are produced at the harmonics by radiation of the Langmuir wave, after which at least the first harmonic wave evolved through density irregularities such that its wave number decreased and it became the type-III radiation.

Let $\mathfrak{g}$ be a symmetrizable Kac--Moody algebra. Given a root $\alpha$ and a real root $\beta$ of $\mathfrak{g}$, it is known that the $\beta$-string through $\alpha$, denoted $R_\alpha(\beta)$, is finite. Given an imaginary root $\beta$, we show that $R_\alpha(\beta)=\{\beta\}$ or $R_\alpha(\beta)$ is infinite. If $(\beta,\beta)<0$, we also show that the multiplicity of the root ${\alpha+n\beta}$ grows at least exponentially as $n\to\infty$. If $(\beta,\beta)=(\alpha, \beta) = 0$, we show that $R_\alpha(\beta)$ is bi-infinite and the multiplicities of $\alpha+n\beta$ are bounded. If $(\beta,\beta)=0$ and $(\alpha, \beta) \neq 0$, we show that $R_\alpha(\beta)$ is semi-infinite and the muliplicity of $\alpha+n\beta$ or $\alpha-n\beta$ grows faster than every polynomial as $n\to\infty$. We also prove that $\dim \mathfrak{g}_{\alpha+\beta} \geq \dim \mathfrak{g}_\alpha + \dim \mathfrak{g}_\beta -1$ whenever $\alpha \neq \beta$ with $(\alpha, \beta)<0$.