cssi/SciSciGPT-SciSciNet huggingface dataset:
Bounds on Velocity-dependent Dark Matter-Proton Scattering from Milky Way Satellite Abundance

We use the latest measurements of the Milky Way satellite population from the Dark Energy Survey and Pan-STARRS1 to infer the most stringent astrophysical bound to date on velocity-dependent interactions between dark matter particles and protons. We model the momentum-transfer cross section as a power law of the relative particle velocity $v$ with a free normalizing amplitude, $\sigma_\text{MT}=\sigma_0 v^n$, to broadly capture the interactions arising within the non-relativistic effective theory of dark matter-proton scattering. The scattering leads to a momentum and heat transfer between the baryon and dark matter fluids in the early Universe, ultimately erasing structure on small physical scales and reducing the abundance of low-mass halos that host dwarf galaxies today. From the consistency of observations with the cold collisionless dark matter paradigm, using a new method that relies on the most robust predictions of the linear perturbation theory, we infer an upper limit on $\sigma_0$ of $1.4\times10^{-23}$, $2.1\times10^{-19}$, and $1.0\times10^{-12}\ \mathrm{cm}^2$, for interaction models with $n=2,4,6$, respectively, for a dark matter particle mass of $10\ \mathrm{MeV}$. These results improve observational limits on dark matter--proton scattering by orders of magnitude and thus provide an important guide for viable sub-GeV dark matter candidates.
Urban violence and police privatization in Brazil: blended invisibility

AT THE TURN OF THE SECOND MILLENNIUM, VISIBLE STATE-SPONSORED ATROCITIES in Brazil may seem to be only a pale reflection of the ethnic and political cleansing and other large-scale, often genocidal, violence in places such as Guatemala, East Timor, Rwanda, the Sudan, Bosnia, Kosovo, and Chechnya. The extent and scope of violence in these countries ? with its raw brutality, military context, and state and overt paramilitary state-sponsored murder and mistreatment of civilians ? make contemporary peacetime violence in Brazil, or even during its 21-year military dictatorship (1964 to 1985), appear to be much less noteworthy and significant. Yet, that assumption suggests the questionable moral thesis that smaller numbers or a lower percentage of victims out of the total Brazilian population reduce the significance of this and similar situations of state permitted or encouraged violence. Whether defensible or not, the validity of such a proposition cannot be considered without examining the extent and nature of violence in Brazil, where interpersonal violence is prevalent and dramatic, although disguised because it is ethnically and class selective as well as geographi? cally focused. To indicate the extent of violence in Brazil, in Sao Paulo alone (the largest city in South America), between 1984 and 1996 there were 69,700 homicides ? over 10,000 more deaths than known U.S. casualties during the entire Vietnam War. Between 1979 and 1997, the homicide rate in Brazil increased from 11.5 murders per one hundred thousand population to 25.4. This 18-year period spans the six years before the military left power through the 12 years after formal democratic government had returned. Between 1979 and 1997, Brazil's population increased
The use of adjusted earnings in performance evaluation

We document widespread adoption of adjustments to earnings for performance evaluation; 84% of our sample of S&P 1500 firms use adjusted earnings for bonus compensation. We find that the transactions removed from adjusted earnings vary widely and include both transitory and nontransitory items. We examine the determinants of using adjusted earnings and find some evidence that boards are more likely to contract using adjusted earnings when firms have high levels of intangible assets, more volatile earnings, CEOs with shorter tenures, CEOs who also act as board chairperson, or larger compensation committees or are reporting losses. We find that firms with an independent chairperson or lead director are less likely to contract using adjusted earnings. We examine the compensation consequences of the use of adjusted earnings and find that CEOs compensated on adjusted earnings are less likely to miss minimum bonus thresholds, are less likely to meet maximum bonus thresholds, and have higher overall bonus compensation, controlling for firm performance. Taken together, our analyses suggest that both managerial power and efficient contracting concerns explain the use of adjusted earnings in CEO compensation contracts.
Stabilizing a System With an Unbounded Random Gain Using Only Finitely Many Bits

We study the stabilization of a linear control system with an unbounded random system gain where the controller must act based on a rate-limited observation of the state. More precisely, we consider the system $X_{n+1}=A_{n}X_{n}+W_{n}-U_{n}$ , where the $A_{n}$ ’s are drawn independently at random at each time $n$ from a known distribution with unbounded support, and where the controller receives at most $R$ bits about the system state at each time from an encoder. We provide a time-varying achievable strategy to stabilize the system in a second-moment sense with fixed, finite $R$ . While our previous result provided a strategy to stabilize this system using a variable-rate code, this work provides an achievable strategy using a fixed-rate code. The strategy we employ to achieve this is time-varying and takes different actions depending on the value of the state. It proceeds in two modes: a normal mode (or zoom-in), where the realization of $A_{n}$ is typical, and an emergency mode (or zoom-out), where the realization of $A_{n}$ is exceptionally large. To analyze the performance of the scheme we construct an auxiliary sequence that bounds the state $X_{n}$ , and then bound auxiliary sequence in both the zoom-in and zoom-out modes.
Sparse Longitudinal Representations of Electronic Health Record Data for the Early Detection of Chronic Kidney Disease in Diabetic Patients

Chronic kidney disease (CKD) is a gradual loss of renal function over time, and it increases the risk of mortality, decreased quality of life, as well as serious complications. The prevalence of CKD has been increasing in the last couple of decades, which is partly due to the increased prevalence of diabetes and hypertension. To accurately detect CKD in diabetic patients, we propose a novel framework to learn sparse longitudinal representations of patients’ medical records. The proposed method is also compared with widely used baselines such as Aggregated Frequency Vector and Bag-of-Pattern in Sequences on real EHR data, and the experimental results indicate that the proposed model achieves higher predictive performance. Additionally, the learned representations are interpreted and visualized to bring clinical insights.
Why Did Public Banks Lend More During the Global Financial Crisis

During the Global Financial Crisis (GFC), state-owned or public banks lent relativelymore than domestic private banks in many countries. However, data limitations havehindered a thorough assessment of what led public banks to better maintain lendingduring the GFC. Using a novel bank-level dataset covering 25 emerging marketeconomies, we show that public banks lent relatively more during the GFC becausethey pursued an objective of helping to stabilize the economy, rather than because theyhad superior fundamentals or access to public or depositors' funding. Nonetheless,their countercyclical behavior seems unique to the GFC rather than a regularcharacteristic of public banks before and after the GFC.
Inspection-on-the-fly using Hybrid Physical Interaction Control for Aerial Manipulators

Inspection for structural properties (surface stiffness and coefficient of restitution) is crucial for understanding and performing aerial manipulations in unknown environments, with little to no prior knowledge on their state. Inspection-on-the-fly is the uncanny ability of humans to infer states during manipulation, reducing the necessity to perform inspection and manipulation separately. This paper presents an infrastructure for inspection-on-the-fly method for aerial manipulators using hybrid physical interaction control. With the proposed method, structural properties (surface stiffness and coefficient of restitution) can be estimated during physical interactions. A three-stage hybrid physical interaction control paradigm is presented to robustly approach, acquire and impart a desired force signature onto a surface. This is achieved by combining a hybrid force/motion controller with a model-based feed-forward impact control as intermediate phase. The proposed controller ensures a steady transition from unconstrained motion control to constrained force control, while reducing the lag associated with the force control phase. And an underlying Operational Space dynamic configuration manager permits complex, redundant vehicle/arm combinations. Experiments were carried out in a mock-up of a Dept. of Energy exhaust shaft, to show the effectiveness of the inspection-on-the-fly method to determine the structural properties of the target surface and the performance of the hybrid physical interaction controller in reducing the lag associated with force control phase.
Whole genome genetic variation and linkage disequilibrium in a diverse collection of Listeria monocytogenes isolates

We performed whole-genome multi-locus sequence typing for 2554 genes in a large and heterogenous panel of 180 Listeria monocytogenes strains having diverse geographical and temporal origins. The subtyping data was used for characterizing genetic variation and evaluating patterns of linkage disequilibrium in the pan-genome of L. monocytogenes. Our analysis revealed the presence of strong linkage disequilibrium in L. monocytogenes, with ~99% of genes showing significant non-random associations with a large majority of other genes in the genome. Twenty-seven loci having lower levels of association with other genes were considered to be potential "hot spots" for horizontal gene transfer (i.e., recombination via conjugation, transduction, and/or transformation). The patterns of linkage disequilibrium in L. monocytogenes suggest limited exchange of foreign genetic material in the genome and can be used as a tool for identifying new recombinant strains. This can help understand processes contributing to the diversification and evolution of this pathogenic bacteria, thereby facilitating development of effective control measures.
Hyperbolic geometry of gene expression.

Abstract Patterns of gene expressions play a key role in determining cell state. Although correlations in gene expressions have been well documented, most of the current methods treat them as independent variables. One way to take into account gene correlations is to find a low-dimensional curved geometry that describes variation in the data. Here we develop such a method and find that gene expression across multiple cell types exhibit a low dimensional hyperbolic structure. When more genes are taken into account, hyperbolic effects become stronger but representation remains low-dimensional. The size of the hyperbolic map, which indicates the hierarchical depth of the data, was the largest for human cells, the smallest for mouse embryonic cells and intermediate in differentiated cells from different mouse organs. We also describe how hyperbolic metric can be incorporated into the t-SNE method to lead to improved visualizations compared to leading methods.
Do link polynomials detect causality in globally hyperbolic spacetimes

Let X be a (2 + 1)-dimensional globally hyperbolic spacetime with a Cauchy surface Σ whose universal cover is homeomorphic to R2. We provide empirical evidence suggesting that the Jones polynomial detects causality in X. We introduce a new invariant of certain tangles related to the Conway polynomial and prove that the Conway polynomial does not detect the connected sum of two Hopf links among relevant three-component links, which suggests that the Conway polynomial does not detect causality in the scenario described.
Increased platelet glycoprotein IIb/IIIa activation precedes continuous-flow left ventricular assist device pump thrombosis events.

Purpose Continuous-flow left ventricular assist devices (CFLVAD) in management of end-stage heart failure continues to expand. Adverse events however remain high. Better understanding of platelet activation in the context of CFLVAD therapy may help reduce bleeding and pump thrombosis (PT) risks to patients. Methods Whole blood was collected 15 days post CFLVAD implant. Blood samples were stimulated, stained with anti- CD61, gpIIb/IIIa complex (PAC-1), CD62P, fixed, and analyzed by flow cytometry. Unstimulated blood +/- RDGS were prepared as controls. Platelets were gated as CD61+ and CD62P and PAC-1 signal determined activation. Adverse events (PT/bleeding) were determined through INTERMACS. Results Median age was 62 years, 21% female, 17 implanted with centrifugal and 2axial flow pumps. Groups consisted of those without an adverse event (No event, n=11), PT (w or w/o bleed, n=3), and Bleeding event only (n=5). Healthy volunteers (n=5) were recruited to serve as controls. CFLVAD implantation alone did not increase PAC-1 platelet activation in patients 15 days post implant. In addition, CFLVAD implantation did not prevent platelets from becoming activated following stimulation. In patients with PT, PAC-1 was higher in unstimulated blood (9.9%) when compared to No event (2.22% p=0.023) and healthy controls (0.66% p=0.028). This elevation of PAC-1 was detected before the clinical manifestation of pump thrombosis (8, 139, 274 days). In addition, following stimulation, PAC-1 was increased significantly in PT patients (89.6%) compared to both No event (54.8% p Conclusion Platelet gpIIb/IIIa activation from PT patients was evident prior to thrombus development. PT patients even had the largest response to stimulation. This increase in platelet activation could serve as a predictor of device-related thrombosis events and may have important implications in targeted therapy to reduce PT in CFLVAD patients
In vivo quantitative analysis of anterior chamber white blood cell mixture composition using spectroscopic optical coherence tomography

Anterior uveitis is the most common form of intraocular inflammation, and one of its main signs is the presence of white blood cells (WBCs) in the anterior chamber (AC). Clinically, the true composition of cells can currently only be obtained using AC paracentesis, an invasive procedure to obtain AC fluid requiring needle insertion into the AC. We previously developed a spectroscopic optical coherence tomography (SOCT) analysis method to differentiate between populations of RBCs and subtypes of WBCs, including granulocytes, lymphocytes and monocytes, both in vitro and in ACs of excised porcine eyes. We have shown that different types of WBCs have distinct characteristic size distributions, extracted from the backscattered reflectance spectrum of individual cells using Mie theory. Here, we further develop our method to estimate the composition of blood cell mixtures, both in vitro and in vivo. To do so, we estimate the size distribution of unknown cell mixtures by fitting the distribution observed using SOCT with a weighted combination of reference size distributions of each WBC type calculated using kernel density estimation. We validate the accuracy of our estimation in an in vitro study, by comparing our results for a given WBC sample mixture with the cellular concentrations measured by a hemocytometer and SOCT images before mixing. We also conducted a small in vivo quantitative cell mixture validation pilot study which demonstrates congruence between our method and AC paracentesis in two patients with uveitis. The SOCT based method appears promising to provide quantitative diagnostic information of cellular responses in the ACs of patients with uveitis.
Schizosaccharomyces pombe KAT5 contributes to resection and repair of a DNA double-strand break.

Chromatin remodeling is essential for effective repair of a DNA double strand break. KAT5 (S. pombe Mst1, human TIP60) is a MYST family histone acetyltransferase conserved from yeast to humans that coordinates various DNA damage response activities at a DNA double strand break (DSB), including histone remodeling and activation of the DNA damage checkpoint. In S. pombe, mutations in mst1+ causes sensitivity to DNA damaging drugs. Here we show that Mst1 is recruited to DSBs. Mutation of mst1+ disrupts recruitment of repair proteins and delays resection. These defects are partially rescued by deletion of pku70, which has been previously shown to antagonize repair by homologous recombination. These phenotypes of mst1 are similar to pht1-4KR, a non-acetylatable form of histone variant H2A.Z, which has been proposed to affect resection. Our data suggest that Mst1 functions to direct repair of DSBs towards homologous recombination pathways by modulating resection at the double strand break.
Computing the Writhing Number of a Polygonal Knot

The writhing number measures the global geometry of a closed space curve or knot. We show that this measure is related to the average winding number of its Gauss map. Using this relationship, we give an algorithm for computing the writhing number for a polygonal knot with n edges in time roughly proportional to n1.6. We also implement a different, simple algorithm and provide experimental evidence for its practical efficiency.
CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings

Recent advances in training deep learning models have demonstrated the potential to provide accurate chest X-ray interpretation and increase access to radiology expertise. However, poor generalization due to data distribution shifts in clinical settings is a key barrier to implementation. In this study, we measured the diagnostic performance for 8 different chest X-ray models when applied to (1) smartphone photos of chest X-rays and (2) external datasets without any finetuning. All models were developed by different groups and submitted to the CheXpert challenge, and re-applied to test datasets without further tuning. We found that (1) on photos of chest X-rays, all 8 models experienced a statistically significant drop in task performance, but only 3 performed significantly worse than radiologists on average, and (2) on the external set, none of the models performed statistically significantly worse than radiologists, and five models performed statistically significantly better than radiologists. Our results demonstrate that some chest X-ray models, under clinically relevant distribution shifts, were comparable to radiologists while other models were not. Future work should investigate aspects of model training procedures and dataset collection that influence generalization in the presence of data distribution shifts.
A Study in Frequency-dependent Effects on Precision Pulsar Timing Parameters with the Pulsar Signal Simulator

In this paper we introduce a new Python package, the Pulsar Signal Simulator, or PsrSigSim, which is designed to simulate a pulsar signal from emission at the pulsar, through the interstellar medium, to observation by a radio telescope, and digitization in a standard data format. We use the PsrSigSim to simulate observations of three millisecond pulsars, PSRs J1744--1134, B1855+09, and B1953+29, to explore the covariances between frequency-dependent parameters, such as variations in the dispersion measure (DM), pulse profile evolution with frequency, and pulse scatter broadening. We show that the PsrSigSim can produce realistic simulated data and can accurately recover the parameters injected into the data. We also find that while there are covariances when fitting DM variations and frequency-dependent parameters, they have little effect on timing precision. Our simulations also show that time-variable scattering delays decrease the accuracy and increase the variability of the recovered DM and frequency-dependent parameters. Despite this, our simulations also show that the time-variable scattering delays have little impact on the root mean square of the timing residuals. This suggests that the variability seen in recovered DM, when time-variable scattering delays are present, is due to a covariance between the two parameters, with the DM modeling out the additional scattering delays.
PKIND: A parallel k-induction based model checker

PKIND is a novel parallel k-induction-based model checker of invariant properties for finite- or infinite-state Lustre programs. Its architecture, which is strictly message-based, is designed to minimize synchronization delays and easily accommodate the incorporation of incremental invariant generators to enhance basic k-induction. We describe PKIND’s functionality and main features, and present experimental evidence that PKIND significantly speeds up the verification of safety properties and, due to incremental invariant generation, also considerably increases the number of provable ones.
The Empowering and Competition Effects of the Platform-Based Sharing Economy on the Supply and Demand Sides of the Labor Market

The sharing economy has fundamentally changed the way many individuals work. In this paper, we study the impact of the entry of a major ridesharing platform into U.S. Metropolitan Statistical Areas...
Rates of convergence for the planar discrete Green’s function in Pacman domains

We obtain upper bounds for the rates of convergence for the simple random walk Green’s function in the domains Dα=Dα(n)={rei&#120579;∈C:0<&#120579;<2π−α,0<r<2n}−z0, where z0∈Z2 is a point closest to nei(π−α∕2). The rate depends on the angle of the wedge and is what was suggested by the sharpest available results in the extreme cases α=0 and α=π. Our proof uses the KMT coupling between random walk and Brownian motion.
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering

We consider an online model for recommendation systems, with each user being recommended an item at each time-step and providing ‘like’ or ‘dislike’ feedback. Each user may be recommended a given item at most once. A latent variable model specifies the user preferences: both users and items are clustered into types . All users of a given type have identical preferences for the items, and similarly, items of a given type are either all liked or all disliked by a given user. We assume that the matrix encoding the preferences of each user type for each item type is randomly generated; in this way, the model captures structure in both the item and user spaces, the amount of structure depending on the number of each of the types. The measure of performance of the recommendation system is the expected number of disliked recommendations per user, defined as expected regret. We propose two algorithms inspired by user-user and item-item collaborative filtering (CF), modified to explicitly make exploratory recommendations, and prove performance guarantees in terms of their expected regret. For two regimes of model parameters, with structure only in item space or only in user space, we prove information-theoretic lower bounds on regret that match our upper bounds up to logarithmic factors. Our analysis elucidates system operating regimes in which existing CF algorithms are nearly optimal.
Reproducible validation and replication studies in nanoscale physics.

Credibility building activities in computational research include verification and validation, reproducibility and replication, and uncertainty quantification. Though orthogonal to each other, they...
RTL2RTL Formal Equivalence: Boosting the Design Confidence

Increasing design complexity driven by feature and performance requirements and the Time to Market (TTM) constraints force a faster design and validation closure. This in turn enforces novel ways of identifying and debugging behavioral inconsistencies early in the design cycle. Addition of incremental features and timing fixes may alter the legacy design behavior and would inadvertently result in undesirable bugs. The most common method of verifying the correctness of the changed design is to run a dynamic regression test suite before and after the intended changes and compare the results, a method which is not exhaustive. Modern Formal Verification (FV) techniques involving new methods of proving Sequential Hardware Equivalence enabled a new set of solutions for the given problem, with complete coverage guarantee. Formal Equivalence can be applied for proving functional integrity after design changes resulting from a wide variety of reasons, ranging from simple pipeline optimizations to complex logic redistributions. We present here our experience of successfully applying the RTL to RTL (RTL2RTL) Formal Verification across a wide spectrum of problems on a Graphics design. The RTL2RTL FV enabled checking the design sanity in a very short time, thus enabling faster and safer design churn. The techniques presented in this paper are applicable to any complex hardware design.
Bottomonium suppression and elliptic flow using Heavy Quarkonium Quantum Dynamics

We introduce a framework called Heavy Quarkonium Quantum Dynamics (HQQD) which can be used to compute the dynamical suppression of heavy quarkonia propagating in the quark-gluon plasma using real-time in-medium quantum evolution. Using HQQD we compute large sets of real-time solutions to the Schrodinger equation using a realistic in-medium complex-valued potential. We sample 2 million quarkonia wave packet trajectories and evolve them through the QGP using HQQD to obtain their survival probabilities. The computation is performed using three different HQQD model parameter sets in order to estimate our systematic uncertainty. After taking into account final state feed down we compare our results to existing experimental data for the suppression and elliptic flow of bottomonium states and find that HQQD predictions are good agreement with available data for RAA as a function of Npart and pT collected at $$ \sqrt{s_{\mathrm{NN}}} $$ = 5.02 TeV. In the case of v2 for the various states, we find that the path-length dependence of ϒ(1s) suppression results in quite small v2 for ϒ(1s). Our prediction for the integrated elliptic flow for ϒ(1s) in the 10−90% centrality class, which now includes an estimate of the systematic error, is v2[ϒ(1s)] = 0.003 ± 0.0007 ± $$ {}_{0.0013}^{0.0006} $$ . We also find that, due to their increased suppression, excited bottomonium states have a larger elliptic flow. Based on this observation we make predictions for v2[ϒ(2s)] and v2[ϒ(3s)] as a function of centrality and transverse momentum.
Endoscopic polypectomy devices

Video 1Use of submucosal injection prior to en-bloc endoscopic mucosal resection.Video 2Use of a detachable loop ligating device prior to hot snare resection of a pedunculated polyp.
Detection and removal of pacing artifacts prior to automated analysis of 12-lead ECG

Abstract Background Pacing artifacts must be excluded from the analysis of paced ECG waveform. This study aimed to develop and validate an algorithm to identify and remove the pacing artifacts on ECG and vectorcardiogram (VCG). Methods We developed a semi-automatic algorithm that identifies the onset and offset of a pacing artifact based on the VCG signal slope steepness and designed a graphical user interface that permits quality control and fine-tuning the constraining threshold values. We used 1054 ECGs from the retrospective, multicenter cohort study “Global Electrical Heterogeneity and Clinical Outcomes,” including 3825 atrial and 10,031 ventricular pacing artifacts for the algorithm development and 22 ECGs including 108 atrial and 241 ventricular pacing artifacts for validation. Validation was performed per digital sample. We used the kappa-statistic of interrater agreement between manually labeled sample (ground-truth) and automated detection. Results The constraining parameter values were for onset threshold 13.06 ± 6.21 μV/ms, offset threshold 34.77 ± 17.80 μV/ms, and maximum window size 27.23 ± 3.53 ms. The automated algorithm detected a digital sample belonging to pacing artifact with a sensitivity of 74.5% and specificity of 99.6% and classified correctly 98.8% of digital samples (ROC AUC 0.871; 95%CI 0.853–0.878). The kappa-statistic was 0.785, indicating substantial agreement. The agreement was on 98.81% digital samples, significantly (P Conclusions The semi-automated algorithm can detect and remove ECG pacing artifacts with high accuracy and provide a user-friendly interface for quality control.
Canonical fragments of the strong reflection principle

For an arbitrary forcing class Γ, the Γ-fragment of Todorcevic’s strong reflection principle SRP is isolated in such a way that (1) the forcing axiom for Γ implies the Γ-fragment of SRP, (2) the st...
Fair for All: Best-effort Fairness Guarantees for Classification.

Standard approaches to group-based notions of fairness, such as \emph{parity} and \emph{equalized odds}, try to equalize absolute measures of performance across known groups (based on race, gender, etc.). Consequently, a group that is inherently harder to classify may hold back the performance on other groups; and no guarantees can be provided for unforeseen groups. Instead, we propose a fairness notion whose guarantee, on each group $g$ in a class $\mathcal{G}$, is relative to the performance of the best classifier on $g$. We apply this notion to broad classes of groups, in particular, where (a) $\mathcal{G}$ consists of all possible groups (subsets) in the data, and (b) $\mathcal{G}$ is more streamlined. For the first setting, which is akin to groups being completely unknown, we devise the {\sc PF} (Proportional Fairness) classifier, which guarantees, on any possible group $g$, an accuracy that is proportional to that of the optimal classifier for $g$, scaled by the relative size of $g$ in the data set. Due to including all possible groups, some of which could be too complex to be relevant, the worst-case theoretical guarantees here have to be proportionally weaker for smaller subsets. For the second setting, we devise the {\sc BeFair} (Best-effort Fair) framework which seeks an accuracy, on every $g \in \mathcal{G}$, which approximates that of the optimal classifier on $g$, independent of the size of $g$. Aiming for such a guarantee results in a non-convex problem, and we design novel techniques to get around this difficulty when $\mathcal{G}$ is the set of linear hypotheses. We test our algorithms on real-world data sets, and present interesting comparative insights on their performance.
MicroGrad: A Centralized Framework for Workload Cloning and Stress Testing

We present MicroGrad, a centralized automated framework that is able to efficiently analyze the capabilities, limits and sensitivities of complex modern processors in the face of constantly evolving application domains. MicroGrad uses Microprobe, a flexible code generation framework as its back-end and a Gradient Descent based tuning mechanism to efficiently enable the evolution of the test cases to suit tasks such as Workload Cloning and Stress Testing. MicroGrad can interface with a variety of execution infrastructure such as performance/power simulators as well as native hardware. Further, the modular “abstract workload model” approach to building MicroGrad allows it to be easily extended for further use - enabling more novel usecases, diverse platforms or robust tuning algorithms. In this paper, we evaluate MicroGrad over different use cases and architectures and showcase that MicroGrad can achieve greater than 95% accuracy across different tasks within few tuning epochs and low resource requirements. We also observe that MicroGrad's accuracy is 25-30% higher than competing techniques. At the same time, MicroGrad is able to reach tuning goals 4-5x faster compared to alternate mechanisms. Overall, MicroGrad's fast, resource efficient and accurate test case generation capability allows it to perform rapid evaluation of complex processors.
LUCIDGames: Online Unscented Inverse Dynamic Games for Adaptive Trajectory Prediction and Planning

Existing game-theoretic planning methods assume that the robot knows the objective functions of the other agents a priori while, in practical scenarios, this is rarely the case. This letter introduces LUCIDGames, an inverse optimal control algorithm that is able to estimate the other agents’ objective functions in real time, and incorporate those estimates online into a receding-horizon game-theoretic planner. LUCIDGames solves the inverse optimal control problem by recasting it in a recursive parameter-estimation framework. LUCIDGames uses an unscented Kalman filter (UKF) to iteratively update a Bayesian estimate of the other agents’ cost function parameters, improving that estimate online as more data is gathered from the other agents’ observed trajectories. The planner then takes account of the uncertainty in the Bayesian parameter estimates of other agents by planning a trajectory for the robot subject to uncertainty ellipse constraints. The algorithm assumes no explicit communication or coordination between the robot and the other agents in the environment. An MPC implementation of LUCIDGames demonstrates real-time performance on complex autonomous driving scenarios with an update frequency of 40 Hz. Empirical results demonstrate that LUCIDGames improves the robot's performance over existing game-theoretic and traditional MPC planning approaches. Our implementation of LUCIDGames is available at https://github.com/RoboticExplorationLab/LUCIDGames.jl .
MGATRx: Discovering Drug Repositioning Candidates Using Multi-view Graph Attention.

In-silico drug repositioning or predicting new indications for approved or late-stage clinical trial drugs is a resourceful and time-ecient strategy in drug discovery. However, inferring novel candidate drugs for a disease is challenging, given the heterogeneity and sparseness of the underlying biological entities and their relationships (e.g., disease/drug annotations). By integrating drug-centric and disease-centric annotations as multiviews, we propose a multi-view graph attention network for indication discovery (MGATRx). Unlike most current similaritybased methods, we employ graph attention network on the heterogeneous drug and disease data to learn the representation of nodes and identify associations. MGATRx outperformed four other state-of-art methods used for computational drug repositioning. Further, several of our predicted novel indications are either currently investigated or are supported by literature evidence, demonstrating the overall translational utility of MGATRx.
An Adaptive Video Acquisition Scheme for Object Tracking and Its Performance Optimization

We present a novel adaptive host-chip modular architecture for video acquisition to optimize an overall objective task constrained under a given bit rate. The chip is a high resolution imaging sensor such as gigapixel focal plane array (FPA) with low computational power deployed on the field remotely, while the host is a server with high computational power. The communication channel data bandwidth between the chip and host is constrained to accommodate transfer of all captured data from the chip. The host performs objective task specific computations and also intelligently guides the chip to optimize (compress) the data sent to host. This proposed system is modular and highly versatile in terms of flexibility in re-orienting the objective task. In this work, object tracking is the objective task. While our architecture supports any form of compression/distortion, in this paper we use quadtree (QT)-segmented video frames. We use Viterbi (Dynamic Programming) algorithm to minimize the area normalized weighted rate-distortion allocation of resources. The host receives only these degraded frames for analysis. An object detector is used to detect objects, and a Kalman Filter based tracker is used to track those objects. Evaluation of system performance is done in terms of Multiple Object Tracking Accuracy (MOTA) metric. In this proposed novel architecture, performance gains in MOTA is obtained by twice training the object detector with different system generated distortions as a novel 2-step process. Additionally, object detector is assisted by tracker to upscore the region proposals in the detector to further improve the performance.
Discrete quantitative Helly-type theorems with boxes

Abstract Research on Helly-type theorems in combinatorial convex geometry has produced volumetric versions of Helly's theorem using witness sets and quantitative extensions of Doignon's theorem. This paper combines these philosophies and presents quantitative Helly-type theorems for the integer lattice with axis-parallel boxes as witness sets. Our main result shows that, while quantitative Helly numbers for the integer lattice grow polynomially in each fixed dimension, their variants with boxes as witness sets are uniformly bounded. We prove several colorful and fractional variations on this theorem. We also prove that the Helly number for A × A ⊆ R 2 need not be finite even when A ⊆ Z is a syndetic set.
Generalized impurity pinch in partially magnetized multi-ion plasma

In a two-ion-species plasma with disparate ion masses, heavy ions tend to concentrate in the low-temperature region of collisionally magnetized plasma and in the high-temperature region of collisionally unmagnetized plasma, respectively. Moreover, collisional magnetization can be determined as the ratio of the light ion gyrofrequency to the collision frequency of light and heavy ion species, and the behavior of this effect in the intermediate regime of partially magnetized plasma is predominantly dependent on this Hall parameter. Multi-ion cross-field transport has been described before in the collisionally magnetized plasma regime, and generalized pinch relations, which describe densities of ion species in equilibrium in that plasma, are found in the literature. In this paper, the role of collisional magnetization and Larmor magnetization in multi-ion collisional transport is clarified, and generalized pinch relations are extended to the partially magnetized regime in which the ion Hall parameter may be small, as long as electrons remain collisionally magnetized. Equilibrium ion density profiles have the same dependence on external forces and on each other regardless of collisional magnetization of ions. The expansion of the range of validity of multi-ion collisional transport models makes them applicable to a wider range of laboratory plasma conditions. In particular, ion density profiles evolve sufficiently fast for radial impurity transport to be observable around stagnation on MagLIF, leading to expulsion of heavy ion impurities from the hotspot as long as plasma becomes sufficiently collisionally magnetized during the implosion.
Adiabatic analysis of the rotating BTZ black hole

In this paper we analyze some interesting features of the thermodynamics of the rotating BTZ black hole from the Caratheodory axiomatic postulate, for which, we exploit the appropriate Pfaffian form. The allowed adiabatic transformations are then obtained by solving the corresponding Cauchy problem, and are studied accordingly. Furthermore, we discuss the implications of our approach, regarding the second and third laws of black hole thermodynamics. In particular, the merging of two extremal black holes is studied in detail.
Implementation and Comparison of Model Co-Simulation Methods in a Turbofan Model

The process of developing, parameterizing, validating, and maintaining models occurs within a wide variety of tools, and requires significant time and resources. To maximize model utilization, models are often shared between various toolsets and experts. Model integration is typically divided into two categories: model exchange and model co-simulation. Of these two categories, model co-simulation is typically regarded as the more complex and difficult to implement. Co-Simulation provides the ability to integrate models between different toolsets or incompatible versions of the same software. Additionally, it provides the capabilities for real-time simulations and hardware-in-the-Ioop test scenarios. This paper reviews some of the common co-simulation data communication methods including pipes and file input/output. The differences between serial and parallel, aka synchronous and asynchronous, communication patterns are also discussed. A simple turbofan model was developed to demonstrate the aforementioned methods. The turbofan model was developed in a legacy version of Numerical Propulsion System Simulation (NPSS), and this legacy model was integrated with a high-fidelity turbine model developed in a newer version of the NPSS software. The integration of the legacy turbojet model with the high-fidelity turbine is used to demonstrate how to integrate two models between incompatible software versions. This application can readily be extended to other co-simulation scenarios, such as real-time simulation. Integration of the two models was implemented using the aforementioned communication methods, synchronization mechanisms, and communication patterns. Relevant implementation details for the turbojet/turbine application are described, and a detailed discussion of the results and comparisons between different methods is provided.
Acoustic Directivity of the DGEN Aero-propulsion Research Turbofan at Multiple Farfield Array Locations

The NASA Glenn Research Center's DGEN Aero-propulsion Research Turbofan (DART) is based on the Price Induction DGEN380 a small, ~500-lbf thrust class, high-bypass, geared-turbofan engine with a separate flow nozzle. The general characteristics of the DART make it an ideal candidate for utilization as a test bed for engine aeroacoustic research in a relevant performance environment. To provide a baseline acoustic profile for the DART, the system was tested in the NASA Glenn Research Center's Aero-Acoustic Propulsion Laboratory. Acoustic measurements from multiple external arrays locations were acquired over the nominal fan operating range of 50-95%. The acoustic data are evaluated and reported in terms of overall, broadband, and tonal components. The existence of interaction tones (a result of the physics of the dual-spool interactions) are noted and presented. The symmetry of the acoustic directivity was measured in preparation for potential testing in other facilities.
When the Nontrivial, Small Divisors of a Natural Number are in Arithmetic Progression

Iannucci considered the positive divisors of a natural number $n$ that do not exceed $\sqrt{n}$ and found all forms of numbers whose such divisors are in arithmetic progression. In this paper, we generalize Iannucci's result by excluding the trivial divisors $1$ and $\sqrt{n}$ (when $n$ is a square). Surprisingly, the length of our arithmetic progression cannot exceed $5$.
Bottleneck Transformers for Visual Recognition

We present BoTNet, a conceptually simple yet powerful backbone architecture that incorporates self-attention for multiple computer vision tasks including image classification, object detection and instance segmentation. By just replacing the spatial convolutions with global self-attention in the final three bottleneck blocks of a ResNet and no other changes, our approach improves upon the baselines significantly on instance segmentation and object detection while also reducing the parameters, with minimal overhead in latency. Through the design of BoTNet, we also point out how ResNet bottleneck blocks with self-attention can be viewed as Transformer blocks. Without any bells and whistles, BoTNet achieves 44.4% Mask AP and 49.7% Box AP on the COCO Instance Segmentation benchmark using the Mask R-CNN framework; surpassing the previous best published single model and single scale results of ResNeSt [67] evaluated on the COCO validation set. Finally, we present a simple adaptation of the BoTNet design for image classification, resulting in models that achieve a strong performance of 84.7% top-1 accuracy on the ImageNet benchmark while being up to 1.64x faster in "compute"1 time than the popular EfficientNet models on TPU-v3 hardware. We hope our simple and effective approach will serve as a strong baseline for future research in self-attention models for vision.2
SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification

A common classification task situation is where one has a large amount of data available for training, but only a small portion is annotated with class labels. The goal of semi-supervised training, in this context, is to improve classification accuracy by leverage information not only from labeled data but also from a large amount of unlabeled data. Recent works [2], [1], [26] have developed significant improvements by exploring the consistency constrain between differently augmented labeled and unlabeled data. Following this path, we propose a novel unsupervised objective that focuses on the less studied relationship between the high confidence unlabeled data that are similar to each other. The new proposed Pair Loss minimizes the statistical distance between high confidence pseudo labels with similarity above a certain threshold. Combining the Pair Loss with the techniques developed by the MixMatch family [2], [1], [26], our proposed SimPLE algorithm shows significant performance gains over previous algorithms on CIFAR-100 and Mini-ImageNet [31], and is on par with the state-of-the-art methods on CIFAR-10 and SVHN. Furthermore, SimPLE also outperforms the state-of-the-art methods in the transfer learning setting, where models are initialized by the weights pre-trained on ImageNet[15] or DomainNet-Real[23]. The code is available at github.com/zijian-hu/SimPLE.
Decentralized Fictitious Play in Near-Potential Games With Time-Varying Communication Networks

We study the convergence properties of decentralized fictitious play (DFP) for the class of near-potential games where the incentives of agents are nearly aligned with a potential function. In DFP, agents share information only with their current neighbors in a sequence of time-varying networks, keep estimates of other agents’ empirical frequencies, and take actions to maximize their expected utility functions computed with respect to the estimated empirical frequencies. We show that empirical frequencies of actions converge to a set of strategies with potential function values that are larger than the potential function values obtained by approximate Nash equilibria of the potential game. This result establishes that DFP has identical convergence guarantees in near-potential games as the standard fictitious play in which agents observe the past actions of all the other agents.
Piloted simulation of an onboard trajectory optimization algorithm

This paper will describe a real time piloted simulation of algorithms designed for on-board computation of time-optimal intercept trajectories for an F-8 aircraft. The algorithms, which were derived using singular perturbation theory, generate commands that are displayed to the pilot on flight director needles on the 8-ball. By flying the airplane so as to zero the horizontal and vertical needles, the pilot flies an approximation to a time-optimal intercept trajectory. The various display and computation modes that are available will be described and results will be presented illustrating the performance of the algorithms with a pilot in the loop.
Fair Allocation of Vaccines, Ventilators and Antiviral Treatments: Leaving No Ethical Value Behind in Health Care Rationing

COVID-19 has revealed limitations of existing mechanisms for rationing medical resources under emergency scenarios. Many argue that these mechanisms abandon various ethical values such as equity by discriminating against disadvantaged communities. Illustrating that these limitations are aggravated by a restrictive choice of mechanism, we formulate pandemic rationing of medical resources as a new application of market design and propose a reserve system as a resolution. We develop a general theory of reserve design, introduce new concepts such as cutoff equilibria and smart reserves, extend the analysis of previously-known ones such as sequential reserve matching, relate these concepts to current debates, and present preliminary policy impact.