cssi/SciSciGPT-SciSciNet huggingface dataset:
Automatic Prediction of Suicidal Risk in Military Couples Using Multimodal Interaction Cues from Couples Conversations

Suicide is a major societal challenge globally, with a wide range of risk factors, from individual health, psychological and behavioral elements to socio-economic aspects. Military personnel, in particular, are at especially high risk. Crisis resources, while helpful, are often constrained by access to clinical visits or therapist availability, especially when needed in a timely manner. There have hence been efforts on identifying whether communication patterns between couples at home can provide preliminary information about potential suicidal behaviors, prior to intervention. In this work, we investigate whether acoustic, lexical, behavior and turn-taking cues from military couples’ conversations can provide meaningful markers of suicidal risk. We test their effectiveness in real-world noisy conditions by extracting these cues through an automatic diarization and speech recognition front-end. Evaluation is performed by classifying 3 degrees of suicidal risk: none, ideation, attempt. Our automatic system performs significantly better than chance in all classification scenarios and we find that behavior and turn-taking cues are the most informative ones. We also observe that conditioning on factors such as speaker gender and topic of discussion tends to improve classification performance.
A Cotlar type maximal function associated with Fourier multipliers

Abstract We prove the L p boundedness of a maximal operator associated with a dyadic frequency decomposition of a Fourier multiplier, under a weak regularity assumption.
Design Philosophy for an Interactive Keyboard Terminal

The basic version of the Klerer--May programming system has been in operation at Columbia University's Hudson Laboratories for nearly four years in an off-line mode and for two years in an on-line mode. This system [1--3] permits programming using normal two-dimensional mathematical expressions and flexible language forms. In the area of scientific applications, such a language approach permits faster total throughput, i.e., less time spent in programming or debugging a specific problem compared to conventional FORTRAN-like languages. It also offers a basic framework for extension into other areas such as the manipulation and editing of two-dimensional mathematical input for automatic typesetting of mathematical text [4]. A typical program segment in this language is illustrated in Fig. 1. More visually complex forms, such as multiple integrals, sums, products, and "IF" conditions are also recognized and compiled.
Chapter 3 – Receptors

Chapter 3 discusses concepts of macromolecular receptors as drug targets. Attention is directed at the molecular forces that drive the interactions of a drug with its target receptor. The concepts of receptor agonism, partial agonism, inverse agonism, and antagonism are discussed, and theories of how small molecules exert their effects on receptors, and consequently on the cells and tissues that express them, are described. In addition, the important concepts of topography and stereochemistry, as related to drug-receptor interactions, are introduced, and various molecules with stereochemical features, such as enantiomers, diastereomers, conformational isomers, atropisomers, and ring compounds, are discussed in detail. Two receptor-related case histories, one driven by receptor binding and the other driven by pharmacokinetics, are presented.
Electromagnetic Field Measurement

Various electromagnetic field sensors for measuring radiofrequency (RF) electric and magnetic fields are discussed. Throughout the discussion, the interplay between measured quantities and predicted (modeled) quantities is emphasized. The ability of measurements and the restrictions imposed by rigorous theoretical analysis of given models are discussed for the frequencies from 10 kHz to 40GHz and upward. Keywords: electromagnetic field; radiofrequency; electric field sensor; magnetic field sensor; photonic
Separated flowfield on a slender wing undergoing transient pitching motions

An experimental investigation on the flowfield surrounding a delta wing undergoing a transient pitching motion was conducted. The leading-edge vortices were marked with smoke, and the model and vortex motions were recorded using high-speed motion picture photography. These film records were then analyzed to yield information on the vortex location and trajectory as functions of both angle of attack and time. Hysteresis effects on the vortex dynamics were apparent for both the pitch-up and pitch-down motions
Conjectures on non-local effects in string black holes.

Abstract We consider the modifications to general relativity by the non-local (classical and quantum) string effects for the case of a D -dimensional Schwarzschild black hole. The classical non-local effects do not alter the spacetime topology (the horizon remains unshifted, at least perturbatively). We suggest a simple analytic continuation of the perturbative result into the non-perturbative domain, which eliminates the black hole singularity at the origin and yields an ultraviolet-finite theory of quantum gravity. We investigate the quantum non-local effects (including massive modes) and argue that the inclusion of these back reactions resolves the problem of the thermal spectrum in the semiclassical approach of field quantization in a black hole background, through the bootstrap condition. The density of states for both the quantum and thermal interpretation of the WKB formula are finally shown to differ quantitatively when including the non-local effects.
Characterizing activity-dependent processes with a piecewise exponential model

Abstract The response of some biological processes is dependent on the frequency of stimulation. With first-order processes, the response is driven exponentially to an equilibrium determined by the value of the driving function. When the stimulus or driving function is viewed witching between constant values the resulting response is piecewise exponential. With periodic excitation, the time course of a point fixed in time relative to the initiation time of each stimulus is shown to be exponential with a rate and steady state that are linearly dependent on the rates and equilibria associated with each component exponential. This linearity can be exploited and leads to a simple estimation procedure for the apparent state-dependent rates.
Distributed Cognition in the Management of Design Requirements

In this position statement, we outline a new theoretical framework of the distribution of design requirements processes. Building upon the Theory of Distributed Cognition, we characterize contemporary requirements efforts as distributed cognitive systems in which elements of a design vision are distributed socially, structurally, and temporally. We discuss the various forms of distribution observed in real-world systems development projects and the processes by which representational states are propagated through the system. We conclude with a brief discussion of the implications of the framework for requirements research and practice.
Chapter 13 – Quality Control

Publisher Summary This chapter considers quality control and a key statistical technique in manufacturing and production processes. A variety of control charts, including not only the Shewhart control charts but also more sophisticated ones, based on moving averages and cumulative sums, are considered. The determination of whether a process is in or out of control is greatly facilitated by the use of control charts, which are determined by two numbers—the upper and lower control limits. To employ such a chart, the data generated by the manufacturing process are further divided into subgroups and subgroup statistics. The successive items produced have measurable characteristics, whose mean and variance are fixed when the process is in control. The chapter also shows how to construct control charts based on subgroup averages and on subgroup standard deviations. These control charts can be used to indicate a change in the quality of the items produced and are considered in situations where each item produced has a random number of defects. Three different control charts are also presented that do not consider each subgroup value in isolation—moving average, exponential weighted moving average, and cumulative sum control charts.
The Effects of Regional Insolation Differences upon Advanced Solar Thermal Electric Power Plant Performance and Energy Costs

This paper presents the performance and cost of four 10-MWe advanced solar thermal electric power plants sited in various regions of the continental United States. Each region has different insolation characteristics which result in varying collector field areas, plant performance, capital costs, and energy costs. The paraboloidal dish, central receiver, cylindrical parabolic trough, and compound parabolic concentrator (CPC) comprise the advanced concepts studied. This paper contains a discussion of the regional insolation data base, a description of the solar systems' performances and costs, and a presentation of a range for the forecast cost of conventional electricity by region and nationally over the next several decades.
Determinants of neonatal mortality rates in the U.S. A reduced form model.

The aim of this paper is to contribute to an understanding of the determinants of differences in race-specific neonatal mortality rates among large counties of the U.S. in 1977. After estimating cross-sectional regressions, we apply their coefficients to national trends in the exogenous variables to 'explain' the rapid decline in neonatal mortality since 1964. The regressions and the extrapolations point to the importance of abortion availability, neonatal intensive care availability, females' schooling levels, Medicaid, and to a lesser extent Bureau of Community Health Services projects, poverty, maternal nutrition programs and organized family planning in trends in black neonatal mortality between 1964 and 1977. They also underscore the importance of schooling, neonatal intensive care, poverty, Medicaid, maternal nutrition programs, abortion, and organized family planning clinics in trends in white neonatal mortality in those years.
THE-HILL SACHS LESION IS BEST TREATED WITH A SURFACE REPLACEMENT – AFFIRMS

The classic Hill-Sachs lesion is a compression or impression fracture of the humeral head in occurrence with anterior glenohumeral instability. The true incidence is unknown but clearly increases with recurrent instability episodes. Recent peer-reviewed literature has highlighted the importance of addressing “significant” humeral and glenoid bone defects in the management of glenohumeral instability. Quantification of the “significance” of a Hill-Sachs lesion with regard to location, size, and depth in relation to the glenoid has helped guide indications for surgical management. Options for managing Hill-Sachs lesions include both humeral-sided techniques (soft tissue, bone, and/or prosthetic techniques) and also glenoid-sided techniques (bone transfers to increase glenoid width). The majority of significant acute or chronic Hill-Sachs lesions can be effectively managed without prosthetic replacement. Is a prosthetic surface replacement ever indicated for the management of Hill-Sachs lesions? The peer-reviewed literature is sparse with the outcomes of this treatment, and significant consideration must be given to both the age of the patient and the need for such management when other effective non-prosthetic options exist. In a patient with more than half of the humeral head involved after instability episodes (perhaps seizure or polytrauma patients), metallic surface replacement arthroplasty may be an option that could require less involved post-operative care while restoring range of motion and stability.
The effects of clinically-derived parametric data uncertainty in patient-specific coronary simulations with deformable walls

Cardiovascular simulations are increasingly used for noninvasive diagnosis of cardiovascular disease, to guide treatment decisions, and in the design of medical devices. Quantitative assessment of the variability of simulation outputs due to input uncertainty is a key step toward further integration of cardiovascular simulations in the clinical workflow. In this study, we present uncertainty quantification in computational models of the coronary circulation to investigate the effect of uncertain parameters, including coronary pressure waveform, intramyocardial pressure, morphometry exponent, and the vascular wall Young's modulus. We employ a left coronary artery model with deformable vessel walls, simulated via an Arbitrary-Lagrangian-Eulerian framework for fluid-structure interaction, with a prescribed inlet pressure and open-loop lumped parameter network outlet boundary conditions. Stochastic modeling of the uncertain inputs is determined from intra-coronary catheterization data or gathered from the literature. Uncertainty propagation is performed using several approaches including Monte Carlo, Quasi Monte Carlo sampling, stochastic collocation, and multi-wavelet stochastic expansion. Variabilities in the quantities of interest, including branch pressure, flow, wall shear stress, and wall deformation are assessed. We find that uncertainty in inlet pressures and intramyocardial pressures significantly affect all resulting QoIs, while uncertainty in elastic modulus only affects the mechanical response of the vascular wall. Variability in the morphometry exponent used to distribute the total downstream vascular resistance to the single outlets, has little effect on coronary hemodynamics or wall mechanics. Finally, we compare convergence behaviors of statistics of QoIs using several uncertainty propagation methods on three model benchmark problems and the left coronary simulations. From the simulation results, we conclude that the multi-wavelet stochastic expansion shows superior accuracy and performance against Quasi Monte Carlo and stochastic collocation methods.
An eye on the dog as the scientist's best friend for translational research in ophthalmology: Focus on the ocular surface.

Preclinical animal studies provide valuable opportunities to better understand human diseases and contribute to major advances in medicine. This review provides a comprehensive overview of ocular parameters in humans and selected animals, with a focus on the ocular surface, detailing species differences in ocular surface anatomy, physiology, tear film dynamics and tear film composition. We describe major pitfalls that tremendously limit the translational potential of traditional laboratory animals (i.e., rabbits, mice, and rats) in ophthalmic research, and highlight the benefits of integrating companion dogs with clinical analogues to human diseases into preclinical pharmacology studies. This One Health approach can help accelerate and improve the framework in which ophthalmic research is translated to the human clinic. Studies can be conducted in canine subjects with naturally occurring or noninvasively induced ocular surface disorders (e.g., dry eye disease, conjunctivitis), reviewed herein, and tear fluid can be easily retrieved from canine eyes for various bioanalytical purposes. In this review, we discuss common tear collection methods, including capillary tubes and Schirmer tear strips, and provide guidelines for tear sampling and extraction to improve the reliability of analyte quantification (drugs, proteins, others).
The Grothendieck group of unipotent representations: A new basis

Let G(F_q) be the group of rational points of a simple algebraic group defined and split over a finite field F_q. In this paper we define a new basis for the Grothendieck group of unipotent representations of G(F_q).
Regularity estimates for nonlocal space-time master equations in bounded domains

We obtain sharp parabolic interior and global Schauder estimates for solutions to nonlocal space-time master equations $$(\partial _t +L)^su = f$$ in $$\mathbb {R}\times \Omega $$ , where L is an elliptic operator in divergence form, subject to homogeneous Dirichlet and Neumann boundary conditions. In particular, we establish the precise behavior of solutions near the boundary. Along the way, we prove a characterization of the correct intermediate parabolic Holder spaces in the spirit of Sergio Campanato.
Real-time Flexibility Feedback for Closed-loop Aggregator and System Operator Coordination

Consider a system operator that wishes to optimize its objectives over time subject to operational constraints as well as private constraints of controllable loads managed by an aggregator. In this paper, we design a real-time feedback signal for the aggregator to quantify and communicate its available flexibility to the system operator. The proposed feedback signal at each time is the conditional probability of future feasible trajectories that will be enabled by the operator's decision. We show that it is the unique distribution that maximizes a system capacity for flexibility. It allows the system operator to maintain feasibility and enhance future flexibility while optimizing its objectives. We illustrate how the design can be used by the system operator to perform online cost minimization and real-time capacity estimation, while provably satisfying the private constraints of the loads.
Vacancy diffusion in multi-principal element alloys: The role of chemical disorder in the ordered lattice

Abstract Many of the purported virtues of Multi-Principal Element Alloys (MPEAs), such as corrosion, high-temperature oxidation and irradiation resistance, are highly sensitive to vacancy diffusivity. Similarly, solute interdiffusion is governed by vacancy diffusion. It is also often unclear whether MPEAs are truly stable or effectively stabilized by slow interdiffusion. The considerable composition space afforded to these alloys makes optimizing for desired properties a daunting task; theoretical and computational tools are necessary to guide alloy development. For diffusion, such tools depend on both a knowledge of the vacancy migration barriers within a given alloy and an understanding of how these barriers influence vacancy diffusivity. We present a generalized theory of vacancy diffusion in rugged energy landscapes, paired with Kinetic Monte Carlo simulations of MPEA vacancy diffusion. The barrier energy statistics are informed by nudged elastic band calculations in the equiatomic CoNiCrFeMn alloy. Theory and simulations show that vacancy diffusion in solid-solution MPEAs is not necessarily sluggish, but can potentially be tuned, and that trap models are an insufficient explanation for sluggish diffusion in the CoNiCrFeMn HEA. These results also show that any model that endeavors to faithfully represent diffusion-related phenomena must account for the full nature of the energy landscape, not just the migration barriers.
Sublinear Algorithms and Lower Bounds for Metric TSP Cost Estimation.

We consider the problem of designing sublinear time algorithms for estimating the cost of minimum metric traveling salesman (TSP) tour. Specifically, given access to a n × n distance matrix D that specifies pairwise distances between n points, the goal is to estimate the TSP cost by performing only sublinear (in the size of D) queries. For the closely related problem of estimating the weight of a metric minimum spanning tree (MST), it is known that for any e > 0, there exists an O(n/e^O(1)) time algorithm that returns a (1 + e)-approximate estimate of the MST cost. This result immediately implies an O(n/e^O(1)) time algorithm to estimate the TSP cost to within a (2 + e) factor for any e > 0. However, no o(n²) time algorithms are known to approximate metric TSP to a factor that is strictly better than 2. On the other hand, there were also no known barriers that rule out existence of (1 + e)-approximate estimation algorithms for metric TSP with O(n) time for any fixed e > 0. In this paper, we make progress on both algorithms and lower bounds for estimating metric TSP cost. On the algorithmic side, we first consider the graphic TSP problem where the metric D corresponds to shortest path distances in a connected unweighted undirected graph. We show that there exists an O(n) time algorithm that estimates the cost of graphic TSP to within a factor of (2-e₀) for some e₀ > 0. This is the first sublinear cost estimation algorithm for graphic TSP that achieves an approximation factor less than 2. We also consider another well-studied special case of metric TSP, namely, (1,2)-TSP where all distances are either 1 or 2, and give an O(n^1.5) time algorithm to estimate optimal cost to within a factor of 1.625. Our estimation algorithms for graphic TSP as well as for (1,2)-TSP naturally lend themselves to O(n) space streaming algorithms that give an 11/6-approximation for graphic TSP and a 1.625-approximation for (1,2)-TSP. These results motivate the natural question if analogously to metric MST, for any e > 0, (1 + e)-approximate estimates can be obtained for graphic TSP and (1,2)-TSP using O(n) queries. We answer this question in the negative - there exists an e₀ > 0, such that any algorithm that estimates the cost of graphic TSP ((1,2)-TSP) to within a (1 + e₀)-factor, necessarily requires Ω(n²) queries. This lower bound result highlights a sharp separation between the metric MST and metric TSP problems. Similarly to many classical approximation algorithms for TSP, our sublinear time estimation algorithms utilize subroutines for estimating the size of a maximum matching in the underlying graph. We show that this is not merely an artifact of our approach, and that for any e > 0, any algorithm that estimates the cost of graphic TSP or (1,2)-TSP to within a (1 + e)-factor, can also be used to estimate the size of a maximum matching in a bipartite graph to within an e n additive error. This connection allows us to translate known lower bounds for matching size estimation in various models to similar lower bounds for metric TSP cost estimation.
Scheduling Flows on a Switch to Optimize Response Times

We study the scheduling of flows on a switch with the goal of optimizing metrics related to the response time of the flows. The input is a sequence of flow requests on a switch, where the switch is represented by a bipartite graph with a capacity on each vertex (port), and a flow request is an edge with associated demand. In each round, a subset of edges can be scheduled under the constraint that the total demand of the scheduled edges incident on any vertex is at most the capacity of the vertex. This class of scheduling problems has applications in datacenter networks, and has been extensively studied. Previous work has essentially settled the complexity of metrics based on completion time. The objective of average or maximum response time, however, is more challenging. To the best of our knowledge, there are no prior approximation algorithms results for these metrics in the context of flow scheduling. We present the first approximation algorithms for flow scheduling over a switch to optimize response time based metrics. For the average response time metric, whose NP-hardness follows directly from past work, we present an offline O(1 + O(log(n))/c) approximation algorithm for unit flows, assuming that the port capacities of the switch can be increased by a factor of 1 + c, for any given positive integer c. For the maximum response time metric, we first establish that it is NP-hard to achieve an approximation factor of better than 4/3 without augmenting capacity. We then present an offline algorithm that achieves optimal maximum response time, assuming the capacity of each port is increased by at most 2 dmax - 1, where dmax is the maximum demand of any flow. Both algorithms are based on linear programming relaxations. We also study the online version of flow scheduling using the lens of competitive analysis, and present preliminary results along with experiments that evaluate the performance of fast online heuristics.
Conjugated activation of myocardial-specific transcription of Gja5 by a pair of Nkx2-5-Shox2 co-responsive elements

The sinoatrial node (SAN) is the primary pacemaker in the heart. During cardiogenesis, Shox2 and Nkx2-5 are co-expressed in the junction domain of the SAN and regulate pacemaker cell fate through a Shox2-Nkx2-5 antagonism. Cx40 is a marker of working myocardium and an Nkx2-5 transcriptional output antagonized by Shox2, but the underlying regulatory mechanisms remain elusive. Here we characterized a bona fide myocardial-specific Gja5 (coding gene of Cx40) distal enhancer consisting of a pair of Nkx2-5 and Shox2 co-bound elements in the regulatory region of Gja5. Transgenic reporter assays revealed that neither element alone, but the conjugation of both elements together, drives myocardial-specific transcription. Genetic analyses confirmed that the activation of this enhancer depends on Nkx2-5 but is inhibited by Shox2 in vivo, and its presence is essential for Gja5 expression in the myocardium but not the endothelial cells of the heart. Furthermore, chromatin conformation analysis showed an Nkx2-5-dependent loop formation between these two elements and the Gja5 promoter in vivo, indicating that Nkx2-5 bridges the conjugated activation of this enhancer by pairing the two elements to the Gja5 promoter.
An Integrated Microfluidic Probe for Mass Spectrometry Imaging of Biological Samples

Ambient ionization based on liquid extraction is widely used in mass spectrometry imaging (MSI) of molecules in biological samples. The development of nanospray desorption electrospray ionization (nano-DESI) has enabled the robust imaging of tissue sections with high spatial resolution. However, the fabrication of the nano-DESI probe is challenging, which limits its dissemination to the broader scientific community. Herein, we describe the design and performance of an integrated microfluidic probe (iMFP) for nano-DESI MSI. The glass iMFP, fabricated using photolithography, wet etching, and polishing, shows comparable performance to the capillary-based nano-DESI MSI in terms of stability and sensitivity; a spatial resolution of better than 25 μm was obtained in these first proof-of-principle experiments. The iMFP is easy to operate and align in front of a mass spectrometer, which will facilitate broader use of liquid-extraction-based MSI in biological research, drug discovery, and clinical studies.
Bone geometry and microarchitecture deficits in children with Alagille syndrome.

Abstract Alagille syndrome (ALGS) is an autosomal dominant disorder attributed to mutations in the Notch signaling pathway. Children with ALGS are at increased risk for fragility fracture of unknown etiology. Our objective was to characterize bone mass, geometry, and microarchitecture in children with ALGS. This was a cross-sectional study of 10 children (9 females), ages 8–18 years, with a clinical diagnosis of ALGS. Bone density was assessed via DXA (Hologic Discovery A) at several skeletal regions. Tibia trabecular and cortical bone was assessed via pQCT (Stratec XCT 2000) at the distal 3% and 38% sites, respectively. Tibia bone microarchitecture was assessed via HR-pQCT (Scanco XtremeCT II) at an ultradistal site located at 4% of tibia length and a cortical site at 30% of tibia length. Z-scores were calculated for DXA and pQCT measures. In the absence of XtremeCT II HR-pQCT reference data, these outcome measures were descriptively compared to a sample of healthy children ages 5–20 years (n = 247). Anthropometrics and labs were also collected. Based on one-sample t-tests, mean Z-scores for height and weight (both p
Multi-Opponent James Functions

The James function, also known as the "log5 method," assigns a probability to the result of a competition between two teams based on their respective winning percentages. This paper, which builds on earlier work of the authors and Steven J. Miller, explores the analogous situation where a single team or player competes simultaneously against multiple opponents.
Increased Indoor Exposure to Commonly Used Disinfectants during the COVID-19 Pandemic

Quaternary ammonium compounds (QACs or “quats”) make up a class of chemicals used as disinfectants in cleaning and other consumer products. While disinfection is recommended for maintaining a safe environment during the COVID-19 pandemic, the increased use of QACs is concerning as exposure to these compounds has been associated with adverse effects on reproductive and respiratory systems. We have determined the occurrence of 19 QACs in residential dust collected before and during the COVID-19 pandemic. QACs were detected in >90% of the samples collected during the pandemic at concentrations ranging from 1.95 to 531 μg/g (n = 40; median of 58.9 μg/g). The total QAC concentrations in these samples were significantly higher than in samples collected before the COVID-19 pandemic (p < 0.05; n = 21; median of 36.3 μg/g). Higher QAC concentrations were found in households that generally disinfected more frequently (p < 0.05). Disinfecting products commonly used in these homes were analyzed, and the QAC profiles in dust and in products were similar, suggesting that these products can be a significant source of QACs. Our findings indicate that indoor exposure to QACs is widespread and has increased during the pandemic.
The Case for Algebraic Biology: from Research to Education

Though it goes without saying that linear algebra is fundamental to mathematical biology, polynomial algebra is less visible. In this article, we will give a brief tour of four diverse biological problems where multivariate polynomials play a central role-a subfield that is sometimes called algebraic biology. Namely, these topics include biochemical reaction networks, Boolean models of gene regulatory networks, algebraic statistics and genomics, and place fields in neuroscience. After that, we will summarize the history of discrete and algebraic structures in mathematical biology, from their early appearances in the late 1960s to the current day. Finally, we will discuss the role of algebraic biology in the modern classroom and curriculum, including resources in the literature and relevant software. Our goal is to make this article widely accessible, reaching the mathematical biologist who knows no algebra, the algebraist who knows no biology, and especially the interested student who is curious about the synergy between these two seemingly unrelated fields.
Implicit Attitudes and U.S. Tax Professionals' Reliance on Offshore Tax Professionals' Recommendations

Large accounting firms offshore a significant amount of tax work to professionals in India. Prior research suggests that individuals can have negative implicit attitudes toward people from different nationalities and that negative implicit attitudes can have undesired consequences. In this study, we measure a sample of U.S. tax professionals’ implicit attitudes toward Indian persons using an implicit association test (IAT) and assess whether the U.S. tax professionals respond differently to work produced by Indian versus U.S. tax professionals and whether implicit attitudes affect the U.S. professionals’ assessments of Indian tax professionals’ work product. We document that participants in our study have strong negative implicit attitudes toward Indian persons relative to U.S. persons. Conversely, we find similar reliance on and evaluation of U.S. and Indian work products, suggesting that the negative implicit attitudes observed have no relation to any of the variable measures we collect. Participants appear able to rise above their negative implicit attitudes and perform their tax work without bias in our experiment. However, it is important to acknowledge that negative implicit attitudes may result in biased behavior towards others in contexts outside of our experiment.
Does self-efficacy affect entrepreneurial investment?

We empirically examine the effect of self-efficacy on entrepreneurial investment choices. We identify various attributes of entrepreneurial investment and argue that higher self-efficacy is associated with more aggressive entrepreneurial investment decisions. We show that self-efficacy increases the likelihood of being a nascent entrepreneur and creating an operating business. Self-efficacy also increases the proportion of personal wealth invested in the venture and the amount of hours per week the entrepreneur devotes to the venture. These results are significant even when controlling for other known characteristics associated with entrepreneurial investment. Copyright © 2009 Strategic Management Society.
Identification of a Core Module for Bone Mineral Density through the Integration of a Co-expression Network and GWAS Data.

Summary The “omnigenic” model of the genetic architecture of complex traits proposed two categories of causal genes: core and peripheral. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. Using a cell-type- and time-point-specific gene co-expression network for mineralizing osteoblasts, we identify a co-expression module enriched for genes implicated by bone mineral density (BMD) genome-wide association studies (GWASs), correlated with in vitro osteoblast mineralization and associated with skeletal phenotypes in human monogenic disease and mouse knockouts. Four genes from this module (B4GALNT3, CADM1, DOCK9, and GPR133) are located within the BMD GWAS loci with colocalizing expression quantitative trait loci (eQTL) and exhibit altered BMD in mouse knockouts, suggesting that they are causal genetic drivers of BMD in humans. Our network-based approach identifies a “core” module for BMD and provides a resource for expanding our understanding of the genetics of bone mass.
Integrating runtime verification into an automated UAS traffic management system

Unmanned Aerial Systems (UAS) are quickly integrating into the National Air Space (NAS). With the number of registered small (under 55 pounds) UAS in the USA alone at over 1.5 million, and projected to expand rapidly, according to the Federal Aviation Administration (FAA), safety is a pressing consideration. Safe UAS integration into the NAS requires an intelligent, automated system for UAS Traffic Management (UTM). Even more than for manned aircraft, UTM must integrate runtime checks to ensure system safety, at the very least to make up for the lack of humans on board to employ the common-sense safety checks ingrained into the culture of human aviation.
Practical Route to Entanglement-Enhanced Communication over Noisy Bosonic Channels

We report structured encoding and decoding schemes for entanglement-assisted classical communication in a lossy and noisy scenario. Phase encoding on the entangled two-mode squeezed vacuum is shown to be optimal and practical receivers are analyzed.
Experimental methodologies can affect pathogenicity of Batrachochytrium salamandrivorans infections

Controlled experiments are one approach to understanding the pathogenicity of etiologic agents to susceptible hosts. The recently discovered fungal pathogen, Batrachochytrium salamandrivorans (Bsal), has resulted in a surge of experimental investigations because of its potential to impact global salamander biodiversity. However, variation in experimental methodologies could thwart knowledge advancement by introducing confounding factors that make comparisons difficult among studies. Thus, our objective was to evaluate if variation in experimental methods changed inferences made on the pathogenicity of Bsal. We tested whether passage duration of Bsal culture, exposure method of the host to Bsal (water bath vs. skin inoculation), Bsal culturing method (liquid vs. plated), host husbandry conditions (aquatic vs. terrestrial), and skin swabbing frequency influenced diseased-induced mortality in a susceptible host species, the eastern newt (Notophthalmus viridescens). We found that disease-induced mortality was faster for eastern newts when exposed to a low passage isolate, when newts were housed in terrestrial environments, and if exposure to zoospores occurred via water bath. We did not detect differences in disease-induced mortality between culturing methods or swabbing frequencies. Our results illustrate the need to standardize methods among Bsal experiments. We provide suggestions for future Bsal experiments in the context of hypothesis testing and discuss the ecological implications of our results.
Dignity Rights for a pandemic

The concept of human dignity means, quite simply, that every person has inherent equal worth. This incontrovertible but profound concept is derived from the body of dignity law that has developed s...
High-Scalability CMOS Quantum Magnetometer With Spin-State Excitation and Detection of Diamond Color Centers

Magnetometers based on quantum mechanical processes enable high sensitivity and long-term stability without the need for re-calibration, but their integration into fieldable devices remains challenging. This article presents a CMOS quantum vector-field magnetometer that miniaturizes the conventional quantum sensing platforms using nitrogen-vacancy (NV) centers in diamond. By integrating key components for spin control and readout, the chip performs magnetometry through optically detected magnetic resonance (ODMR) through a diamond slab attached to a custom CMOS chip. The ODMR control is highly uniform across the NV centers in the diamond, which is enabled by a CMOS-generated ~2.87 GHz magnetic field with $\times $ 80 $\mu \text{m}^{2}$ diamond slab. NV fluorescence is measured by CMOS-integrated photodetectors. This ON-chip measurement is enabled by efficient rejection of the green pump light from the red fluorescence through a CMOS-integrated spectral filter based on a combination of spectrally dependent plasmonic losses and diffractive filtering in the CMOS back-end-of-line (BEOL). This filter achieves a measured ~25 dB of green light rejection. We measure a sensitivity of 245 nT/Hz1/2, marking a 130 $\times $ improvement over a previous CMOS-NV sensor prototype, largely thanks to the better spectral filtering and homogeneous microwave generation over larger area.
Study on Patterns and Effect of Task Diversity in Software Crowdsourcing

Context: The success of software crowdsourcing depends on steady pools of task demand and active workers supply. Existing analysis reveals an average task failure ratio of 15.7% in software crowdsourcing market.Goal: The objective of this study is to empirically investigate patterns and effect of task diversity in software crowdsourcing platform in order to improve the success and efficiency of software crowdsourcing.Method: We first propose a conceptual task diversity model, and develop an approach to measuring and analyzing task diversity. More specifically, task diversity is characterized based on semantic similarity, dynamic competition level, and the analysis includes identifying the dominant attributes distinguishing the competition levels, and measuring the impact of task diversity on task success and worker performance in crowdsourcing platform. The empirical study is conducted on more than one year's real-world data from TopCoder, one of the leading software crowdsourcing platforms.Results: We identified that monetary prize and task complexity are the dominant attributes that differentiate among different competition levels. Based on these dominant attributes, we concluded three task diversity patterns (configurations) from workers behavior perspective: responsive-to-prize, responsive-to-prize-and-complexity and over-responsive-to-prize. This study supports that the second pattern, i.e. responsive-to-prize-and-complexity configuration, associates with the lowest task failure ratio.Conclusions: These findings are helpful for task requesters to plan for and improve task success in a more effective and efficient manner in software crowdsourcing platform.
Inequality and Growth: A Semiparametric Investigation

The impact of income inequality on subsequent growth is examined using a model designed to capture the effects of both capital-skill complementarities and political economy bargaining processes. Methodologically, the model is estimated using a fixed-effects semiparametric dynamic panel procedure. The results support the theory that the relationship is nonlinear, and influenced by capital-skill complementarities. It is found that poorer nations benefit more from (or are less harmed by) higher inequality than wealthier nations. Additionally, the empirical results provide limited support for the existence of a political economy bargaining process in nations with high levels of inequality. In highly unequal nations, additional inequality reduces subsequent economic growth. However, in more egalitarian nations, additional inequality raises subsequent economic growth.
FastDTW is approximate and Generally Slower than the Algorithm it Approximates

Many time series data mining problems can be solved with repeated use of distance measure. Examples of such tasks include similarity search, clustering, classification, anomaly detection and segmentation. For over two decades it has been known that the Dynamic Time Warping (DTW) distance measure is the best measure to use for most tasks, in most domains. Because the classic DTW algorithm has quadratic time complexity, many ideas have been introduced to reduce its amortized time, or to quickly approximate it. One of the most cited approximate approaches is FastDTW. The FastDTW algorithm has well over a thousand citations and has been explicitly used in several hundred research efforts. In this work, we make a surprising claim. In any realistic data mining application, the approximate FastDTW is much slower than the exact DTW. This fact clearly has implications for the community that uses this algorithm: allowing it to address much larger datasets, get exact results, and do so in less time.
Additivity of Higher Rho Invariants and Nonrigidity of Topological Manifolds

Let $X$ be a closed oriented connected topological manifold of dimension $n\geq 5$. The structure group of $X$ is the abelian group of equivalence classes of all pairs $(f, M)$ such that $M$ is a closed oriented manifold and $f\colon M \to X$ is an orientation-preserving homotopy equivalence. The main purpose of this article is to prove that a higher rho invariant defines a group homomorphism from the topological structure group of $X$ to the $C^*$-algebraic structure group of $X$. In fact, we introduce a higher rho invariant map on the homology manifold structure group of a closed oriented connected $\textit{topological}$ manifold, and prove its additivity. This higher rho invariant map restricts to the higher rho invariant map on the topological structure group. More generally, the same techniques developed in this paper can be applied to define a higher rho invariant map on the homology manifold structure group of a closed oriented connected $\textit{homology}$ manifold. As an application, we use the additivity of the higher rho invariant map to study non-rigidity of topological manifolds. More precisely, we give a lower bound for the free rank of the $\textit{algebraically reduced}$ structure group of $X$ by the number of torsion elements in $\pi_1 X$. Here the algebraic reduced structure group of $X$ is the quotient of the topological structure group of $X$ modulo a certain action of self-homotopy equivalences of $X$. We also introduce a notion of homological higher rho invariant, which can be used to detect many elements in the structure group of a closed oriented topological manifold, even when the fundamental group of the manifold is torsion free. In particular, we apply this homological higher rho invariant to show that the structure group is not finitely generated for a class of manifolds.
Periodic TASEP with general initial conditions

We consider the one-dimensional totally asymmetric simple exclusion process with an arbitrary initial condition in a spatially periodic domain, and obtain explicit formulas for the multi-point distributions in the space-time plane. The formulas are given in terms of an integral involving a Fredholm determinant. We then evaluate the large-time, large-period limit in the relaxation time scale, which is the scale such that the system size starts to affect the height fluctuations. The limit is obtained assuming certain conditions on the initial condition, which we show that the step, flat, and step-flat initial conditions satisfy. Hence, we obtain the limit theorem for these three initial conditions in the periodic model, extending the previous work on the step initial condition. We also consider uniform random and uniform-step random initial conditions.
Nonlinear ISA with Auxiliary Variables for Learning Speech Representations.

This paper extends recent work on nonlinear Independent Component Analysis (ICA) by introducing a theoretical framework for nonlinear Independent Subspace Analysis (ISA) in the presence of auxiliary variables. Observed high dimensional acoustic features like log Mel spectrograms can be considered as surface level manifestations of nonlinear transformations over individual multivariate sources of information like speaker characteristics, phonological content etc. Under assumptions of energy based models we use the theory of nonlinear ISA to propose an algorithm that learns unsupervised speech representations whose subspaces are independent and potentially highly correlated with the original non-stationary multivariate sources. We show how nonlinear ICA with auxiliary variables can be extended to a generic identifiable model for subspaces as well while also providing sufficient conditions for the identifiability of these high dimensional subspaces. Our proposed methodology is generic and can be integrated with standard unsupervised approaches to learn speech representations with subspaces that can theoretically capture independent higher order speech signals. We evaluate the gains of our algorithm when integrated with the Autoregressive Predictive Decoding (APC) model by showing empirical results on the speaker verification and phoneme recognition tasks.
Numerical solution of two-dimensional ablation problems using the finite control volume method with unstructured grids

This paper presents the solution of two-dimensional axisymmetric ablation problems with unstructured grids. The energy equation is fmulated and solved using the Finite Control Volume Method. The exterior shape of the ablating body is determined from a surf= e m g y balance with the interior mesh displaced in response to the surface ablat i o ~ as if the body was a linear elastic solid. Boundary condition matrices are formulated for both heat of ablation and generalized thermochemical ablation boundary conditions. Computed recession rates are. compared to an analytical solution to demonstrate the accuracy and convergence of this approach. Additionally, the practical application of this approach to the ablation of a reentry vehicle nase tip is presented. Nomenclature 4" e Q' r r S
The equation of state of neutron matter, symmetry energy, and neutron star structure

We review the calculation of the equation of state of pure neutron matter using quantum Monte Carlo (QMC) methods. QMC algorithms permit the study of many-body nuclear systems using realistic two- and three-body forces in a non-perturbative framework. We present the results for the equation of state of neutron matter, and focus on the role of three-neutron forces at supranuclear density. We discuss the correlation between the symmetry energy, the neutron star radius and the symmetry energy. We also combine QMC and theoretical models of the three-nucleon interactions, and recent neutron star observations to constrain the value of the symmetry energy and its density dependence.