cssi/SciSciGPT-SciSciNet huggingface dataset:
Implications for law of a unified behavioral science

The argument for unifying behavioral sciences can be enhanced by highlighting concrete, vivid, and useful benefits that coherent behavioral models could provide. Shifting sets of behavioral assumptions underlie every legal system's efforts to modify behaviors by changing incentives in the legal environment. Consequently, where those assumptions are flawed, improved behavioral models could improve law's effectiveness and efficiency in regulating behavior.
Rationality, coordination, and convention

Philosophers using game-theoretical models of human interactions have, I argue, often overestimated what sheer rationality can achieve. (References are made to David Gauthier, David Lewis, and others.) In particular I argue that in coordination problems rational agents will not necessarily reach a unique outcome that is most preferred by all, nor a unique 'coordination equilibrium' (Lewis), nor a unique Nash equilibrium. Nor are things helped by the addition of a successful precedent, or by common knowledge of generally accepted personal principles. Commitments like those generated by agreements may be necessary for rational expectations to arise. Social conventions, construed as group principles (following the analysis in my book On Social Facts), would suffice for this task.
An Application of the Scholes and Wolfson Model to Examine the Relation Between Implicit and Explicit Taxes and Firm Market Structure

A firm can take advantage of preferential tax provisions to lower its explicit tax burden. In the absence of market frictions, this differential tax treatment gives rise to differences in pre‐tax returns across investments, defined as an implicit tax (Scholes and Wolfson 1992). Market structures that are other than perfectly competitive can impede the realization of implicit taxes (which represent lower pre‐tax returns) by allowing firms to earn extra‐normal after‐tax returns (Wilkie 1992). This study estimates implicit tax rates and investigates the relation between a firm's implicit tax rate and two factors: (1) the pre‐tax rate of return, and, (2) the potential market power of the firm, which could provide the opportunity to shift implicit (and explicit) tax burdens from the firm to consumers or labor. The results indicate that implicit taxes are significantly negatively related to the pre‐tax rate of return and firm market structure characteristics. The interaction of pre‐tax returns and firm market s...
Utah's Fine Particulate Air Pollution Problem

For those living along Utah’s Wasatch Front, the air quality problem is visibly obvious. The air pollution, especially in the winter when inversions trap pollutants between the surrounding mountains, is hazardous to people’s health. Several counties along the Wasatch Front violate the Clean Air Act’s air quality standard for particulate matter and are currently designated as “nonattainment” areas. The Environmental Protection Agency requires that affected areas take action to reduce the levels of pollution. This Article will discuss the Clean Air Act and the state’s role in ensuring compliance. This Article then examines some of the reasons for the Wasatch Front’s poor air quality. Finally, this Article proposes solutions and identifies issues that demand further study in order to combat the area’s air pollution problem.
Banking in North America: The Triumph of Public Choice Over Public Policy

This Article examines the state of cross-border banking in the NAFTA countries and the question of whether member country banks should be permitted to branch freely throughout North America. Under present law, the United States permits foreign banks to branch into its territory subject to extensive restrictions, Canada has indicated that it plans to eliminate many restrictions on foreign branching, and Mexico continues to permit access to its banking markets only by investment in or establishment of an institution chartered in Mexico. Article 1403(3) of the NAFTA left the issue of cross-border branching open to subsequent negotiation. If the decision to organize the North American banking market were made by a hypothetical disinterested "expert" the legal regime would permit banking organizations to branch freely across borders, or, alternatively, to establish either a branch or a subsidiary in their own discretion. Of course, the decision will not be made by an impartial expert, but rather will be the result of international bargaining. One way to explain the bargaining would be to say that the member countries will do everything in their control to maximize their respective "national interests." A more realistic way to examine the process, however, is through the lens of public choice theory. Industry groups and regulators will compete for government action to maximize the value of their respective enterprises. The member countries may each find that the existing banking structure provides their banks with certain non-tariff barriers to trade that they may be reluctant to surrender. Finally, the regulators in each of the countries will be reluctant to give up regulatory authority without getting something in return.
Adult Rights as the Achilles’ Heel of the Best Interests Standard: Lessons in Family Law from Across the Pond

And the king said, “Bring me a sword.” So a sword was brought before the king. And the king said, “Divide the living child in two, and give half to the one and half to the other.” Then the woman whose son was alive said to the king, because her heart yearned for her son, “Oh, my lord, give her the living child, and by no means put him to death.” But the other said, “He shall be neither mine nor yours; divide him.” Then the king answered and said, “Give the living child to the first woman, and by no means put him to death; she is his mother.” — 1 Kings 3:24–27
Inflation dynamics in Asia: Causes, changes, and spillovers from China

Abstract The perception that Asia's inflation dynamics are driven by idiosyncratic supply shocks implies, as a corollary, a limited scope for policy responses to inflationary pressures. However, Asia's fast growth and integration with the global economy in the last couple of decades suggest that the drivers of inflation may have changed. This paper presents a quantitative analysis of inflation dynamics in Asia using a Global VAR (GVAR) model, which explicitly incorporates trade and financial linkages among economies, as well as the role of regional and global inflationary spillovers. Our results suggest that over the past two decades, the main drivers of inflation in Asia have been monetary and supply shocks; but that, in recent years, the contribution of these shocks to the region's inflation has fallen. Domestic demand pressures, however, have played a larger role in driving inflation in Asia over the last decade. Moreover, economies in the region are exposed to notable inflation spillovers from China, both directly from higher imported goods prices and indirectly through higher commodity prices.
Sanctions for Frivolous Civil Appeals in Louisiana

The Louisiana Code of Civil Procedure was adopted in 1961, and four years later the Louisiana Supreme Court handed down the first case setting the standard for awarding sanctions for frivolous civil appeals under article 2164. The court adopted an extremely liberal subjective standard, i.e., sanctions could be awarded only if the appeal was taken solely for delay or if appellant’s counsel was obviously insincere. Louisiana courts have followed this standard for the past fifty years. Frivolous appeals waste the courts’ time and diminish the resources available for consideration of serious appeals. Although sanctions could deter frivolous appeals, Louisiana courts rarely award them; when they do, the sanctions are paltry. The author examined the 884 Louisiana cases seeking frivolous-appeal sanctions between 1985 and 2015 and discovered that Louisiana courts awarded sanctions in less than ten percent of the cases in which they were sought — fewer than three awards per year, on average.The fault for the low number of sanctions rests partly with the attorneys who fail to follow proper procedure. The author found procedural deficiencies accounted for sixteen percent of the denials (128 of 801) in that same thirty-year period. The most common deficiency was failing to answer the appeal or file a cross appeal.This article examines the standard applied by Louisiana courts, the circumstances under which frivolous-appeal sanctions will be awarded, the procedural issues attorneys encounter, the types of sanctions awarded, the treatment of pro se litigants, and the ethical issues that arise. It concludes with suggestions for the court and legislature — that the courts apply a more objective standard and award greater sanctions and that the legislature amend the Code of Civil Procedure to extend the period to request sanctions and to allow sanctions when appeals are dismissed as abandoned.
The Insensitivity of Consumption to News About Income

Abstract This paper uses a variance bounds test to see whether consumption is too sensitive to news about income to be consistent with a standard permanent income model, under the maintained hypothesis that income has a unit root. It is found that, if anything, consumption is less sensitive than the model would predict. This implication is robust to the representative consumer having private information about his future income that the econometrician does not have, to wealth shocks, and to transitory consumption. This suggests the importance in future research on the model of allowing for factors that tend to make consumption smooth.
Do hospitals without physicians on the board deliver lower quality of care

This study examines whether hospitals without physician participation on their boards of directors deliver lower quality of care. Using data from California nonprofit hospitals from 2004 to 2008, the authors document that the absence of physicians on the board is associated with a decrease of 3 to 5 percentage points in 3 of 4 measures of care quality. This result was obtained using regression analysis, which controls for various hospital characteristics. The authors also identify factors that influence quality of care in hospitals. Specifically, hospital size, church affiliation, urban location, and system affiliation are positively associated with quality of care; proportion of Medicaid patient revenue and poverty level of the county in which the hospital is located are negatively associated with quality of care. These results highlight the importance of physician participation in hospital governance and indicate areas for hospitals and policy makers to focus on to enhance medical quality management.
THE ORIGINS OF AN INDEPENDENT JUDICIARY IN NEW YORK, 1621–1777

Article III of the U.S. Constitution establishes an independent federal judiciary: federal courts constitute a separate branch of the national government, federal judges enjoy tenure during good behavior, and their salaries cannot be diminished while they hold office. The framers who drafted Article III in 1787 were not working from whole cloth. Rather, they were familiar with the preceding colonial and state practices, including those from New York. This essay provides a case study of New York's judicial history: the Dutch period, 1621-1664; the Ducal proprietary period, 1664-1685; the Royal period, 1685-1776; and the early state period. As will be seen, New York—among the most significant of the original thirteen states—was a state groping towards a new ideal of judicial independence: an ideal that became a reality a decade after its own constitution was enacted in 1777 and at a different level of government. Significantly, the uncertain status of New York's judiciary had profound consequences for the ultimate expression of judicial independence, judicial review.
Online Review Systems: How emotional language drives sales

How does emotional expression in online reviews affect sales? To answer this question, a model is constructed based on theories of sentiment. This model is tested experimentally. Controlling for online review valence online review emotionality affects product sales. The impact is moderated by product type, but not by product price. Specifically, online review language that expresses intense positive or negative emotions increases sales for hedonic products, but it doesn’t affect sales for utilitarian products. This result has implications for the design of online review display algorithms.
Corruption and the ownership composition of the multinational firm at the time of entry: Evidence from Turkey

This paper presents an empirical assessment of the relationship between corruption and the ownership structure of foreign direct investment receipts by Turkey. Two forms of ownership structures are considered: joint venture and wholly owned subsidiary. The results indicate a strong negative impact of corruption on joint ventures, particularly for the ones originating from developed countries. As the degree of dissimilarity between corruption levels in the source country and Turkey diverges, the share of foreign ownership declines. This lends support to the transaction cost approach which emphasizes the expected increase in costs of sharing ownership in corrupt environments.
Corporate Aiding and Abetting of Human Rights Violations: Confusion in the Courts

This article explores whether transnational corporations or their executives can be held criminally or civilly liable for aiding and abetting human rights violations committed by governments, militaries or other actors in foreign countries where they do business. The article particularly examines the mens rea element under international law: whether the aider or abettor must knowingly - or instead purposefully - assist the principal to commit a crime. At present, the principal concern of major corporations about liability for aiding and abetting is the risk of being held liable in U.S. courts under the Alien Tort Statute. But whatever happens with ongoing ATS litigation, the issue of aiding and abetting may become more important in the future in other contexts - including the International Criminal Court, national courts in the home countries of major corporations, and national courts in developing countries where large companies do business. If the standards were clarified for aiding and abetting, and especially for the mens rea element, the resulting legal certainty would be fairer for both corporate managers and victims of human rights violations, while avoiding needless sources of friction among states. As aiding and abetting liability evolves for corporate actors, several principles of international law should be borne in mind. First, even if corporations per se cannot be prosecuted before international criminal tribunals, corporate executives have long been subject to international criminal jurisdiction. Second, international criminal law has long recognized criminal responsibility for aiding and abetting. Third, international law recognizes that civil liability of corporations is widely accepted by national justice systems. Fourth, international law increasingly encourages states to hold corporations criminally responsible for aiding and abetting violations of international law. Combining these principles, whatever may have been the status of corporate aiding and abetting liability in the apartheid era, international norms against corporate aiding and abetting of violations of international criminal law are now widely accepted internationally.
Regulating Student Speech: Suppression Versus Punishment

INTRODUCTION 1113 I. THE SUPREME COURT’S STUDENT-SPEECH FRAMEWORK 1114 II. A DISTINCTION WITH A DIFFERENCE 1120 A. THE THEORETICAL JUSTIFICATIONS FOR THE CURRENT STUDENT-SPEECH FRAMEWORK 1120 B. ENCROACHMENT ON FIRST AMENDMENT RIGHTS 1124 C. DUE PROCESS CONCERNS 1131 III. THE NECESSARY ADDITIONAL PROTECTIONS: NOTICE AND REASONABLENESS 1136 A. ADEQUATE PRIOR NOTICE 1136 B. REASONABLENESS OF THE PUNISHMENT 1141 CONCLUSION 1146
BioMETA: A multiple specification parameter estimation system for stochastic biochemical models

The inherent behavioral variability exhibited by stochastic biochemical systems makes it a challenging task for human experts to manually analyze them. Computational modeling of stochastic biochemical systems helps in predicting the behaviors of the underlying biochemical processes but at the same time introduces the presence of several unknown parameters. A key challenge faced in this scenario is to determine the values of these unknown parameters against known behavioral specifications. We present a new method, BioMETA, to address this problem such that a single set of parameter values causes a parameterized stochastic biochemical model to satisfy all the given probabilistic temporal logic behavioral specifications simultaneously. Our method is based on combining a multiple hypothesis testing based statistical model checking technique with simulated annealing search to look for a single set of parameter values so that the given parameterized model satisfies multiple probabilistic behavioral specifications. Wes tudy two stochastic rule-based models of biochemical receptors, namely, Fc $\epsilon$RI and T-cell as our benchmarks to evaluate the usefulness of the presented method. Our experimental results successfully estimate 26 parameters of Fc $\epsilon$RI and 29 parameters of Tcell receptor model against three probabilistic temporal logic behavioral specifications each.
Basic Column Strength

A summary is presented of a theoretical and experimental investigation of the strength of centrally loaded columns as influenced by residual stresses and variations in the yield-stress level. It is...
How Much Does It Hurt: A Deep Learning Framework for Chronic Pain Score Assessment

Chronic pain is defined as pain that lasts or recurs for more than 3 to 6 months, often long after the injury or illness that initially caused the pain has healed. The “gold standard” for chronic pain assessment remains self report and clinical assessment via a biopsychosocial interview, since there has been no device that can measure it. A device to measure pain would be useful not only for clinical assessment, but potentially also as a biofeedback device leading to pain reduction. In this paper we propose an end-to-end deep learning framework for chronic pain score assessment. Our deep learning framework splits the long time-course data samples into shorter sequences, and uses Consensus Prediction to classify the results. We evaluate the performance of our framework on two chronic pain score datasets collected from two iterations of prototype Pain Meters that we have developed to help chronic pain subjects better understand their health condition.
SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness

In this paper, we cast fair machine learning as invariant machine learning. We first formulate a version of individual fairness that enforces invariance on certain sensitive sets. We then design a transport-based regularizer that enforces this version of individual fairness and develop an algorithm to minimize the regularizer efficiently. Our theoretical results guarantee the proposed approach trains certifiably fair ML models. Finally, in the experimental studies we demonstrate improved fairness metrics in comparison to several recent fair training procedures on three ML tasks that are susceptible to algorithmic bias.
Forecasting River Runoff by Coastal Flow Index

Index method for forecasting Apr through Sept runoff for Columbia River at Dalles, Ore, is presented, based on relationship between winter runoff in coastal drainage areas and spring snowmelt runoff of Columbia River; reliability of forecasts is comparable with those based on precipitation and snowcourse data.
How do populations aggregate

Author(s): Feehan, Dennis M; Wrigley-Field, Elizabeth | Abstract: BackgroundUnderstanding the relationship between populations at different scales plays an important role in many demographic analyses.ObjectiveWe show that when a population can be partitioned into subgroups, the death rate for the entire population can be written as the weighted harmonic mean of the death rates in each subgroup, where the weights are given by the numbers of deaths in each subgroup. This decomposition can be generalized to other types of occurrence-exposure rate. Using different weights, the death rate for the entire population can also be expressed as an arithmetic mean of the death rates in each subgroup.ContributionWe use these relationships as a starting point for investigating how demographers can correctly aggregate rates across non-overlapping subgroups. Our analysis reveals conceptual links between classic demographic models and length-biased sampling. To illustrate how the harmonic mean can suggest new interpretations of demographic relationships, we present as an application a new expression for the frailty of the dying, given a standard demographic frailty model.
Improve global glomerulosclerosis classification with imbalanced data using CircleMix augmentation

The classification of glomerular lesions is a routine and essential task in renal pathology. Recently, machine learning approaches, especially deep learning algorithms, have been used to perform computer-aided lesion characterization of glomeruli. However, one major challenge of developing such methods is the naturally imbalanced distribution of different lesions. In this paper, we propose CircleMix, a novel data augmentation technique, to improve the accuracy of classifying globally sclerotic glomeruli with a hierarchical learning strategy. Different from the recently proposed CutMix method, the CircleMix augmentation is optimized for the ball-shaped biomedical objects, such as glomeruli. 6,861 glomeruli with five classes (normal, periglomerular fibrosis, obsolescent glomerulosclerosis, solidified glomerulosclerosis, and disappearing glomerulosclerosis) were employed to develop and evaluate the proposed methods. From five-fold cross-validation, the proposed CircleMix augmentation achieved superior performance (Balanced Accuracy=73.0%) compared with the EfficientNet-B0 baseline (Balanced Accuracy=69.4%)
Intersective polynomials arising from sums of powers

Given a natural number n≥2, an integer k and for a judiciously chosen l=l(n) we give necessary and sufficient conditions for the polynomial fn,k=(∑i=1lxin)−k to have roots modulo every positive int...
Shift-type SMEFT effects in dileptons at the LHC

We explore the constraints which can be derived on Wilson coefficients in the Standard Model Effective Field Theory from dilepton production, notably including the constraints on operators which do not lead to cross sections growing with energy relative to the Standard Model rate, i.e. shifts. We incorporate essential theory error estimates from higher EFT orders in the analysis in order to provide robust bounds. We find that constraints on four-fermion operator contributions which do grow with energy are not materially weakened by the inclusion of these shifts, and that a constraint on the shifts can also be derived, with a characteristic strength comparable to, and a directionality in parameter space complementary to, those from LEP data. This completes the study of hadronically-quiet dilepton production in the SMEFT, and provides two new constraints which are linearly independent from others arising at the LHC and also rotated in Wilson coefficient space relative to, though not completely independent from, the LEP bounds.
Delaying surgery for clinical T1b-T2bN0M0 renal cell carcinoma: Oncologic implications in the COVID-19 era and beyond

283Background: During COVID-19, many operating rooms were reserved exclusively for emergent cases. As a result, many elective surgeries for renal cell carcinoma (RCC) were deferred, with an unknown...
Fukaya $A_\infty$-structures associated to Lefschetz fibrations. III

Floer cohomology groups are usually defined over a field of formal functions (a Novikov field). Under certain assumptions, one can equip them with connections, which means operations of differentiation with respect to the Novikov variable. This allows one to write differential equations for Floer cohomology classes. Here, we apply that idea to symplectic cohomology groups associated to Lefschetz fibrations, and establish a relation with enumerative geometry.
The Impact of Facility Layout on Service Worker Behavior: An Empirical Study of Nurses in the Emergency Department

Problem definition: We study the impact of service facility layout on how service workers organize their tasks. We focus on the hospital emergency department (ED) as a service setting in which nurs...
Generating Extended Resolution Proofs with a BDD-Based SAT Solver

In 2006, Biere, Jussila, and Sinz made the key observation that the underlying logic behind algorithms for constructing Reduced, Ordered Binary Decision Diagrams (BDDs) can be encoded as steps in a proof in the extended resolution logical framework. Through this, a BDD-based Boolean satisfiability (SAT) solver can generate a checkable proof of unsatisfiability. Such proofs indicate that the formula is truly unsatisfiable without requiring the user to trust the BDD package or the SAT solver built on top of it.
Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges

Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to high complexity, interaction, parallelism and continuous change of roles and organisation between agents. In this paper we record our research experience on formal modelling of MAS. We review our research throughout the last decade, by describing the problems we have encountered and the decisions we have made towards resolving them and providing solutions. Much of this work involved membrane computing and classes of P Systems, such as Tissue and Population P Systems, targeted to the modelling of MAS whose dynamic structure is a prominent characteristic. More particularly, social insects (such as colonies of ants, bees, etc.), biology inspired swarms and systems with emergent behaviour are indicative examples for which we developed formal MAS models. Here, we aim to review our work and disseminate our findings to fellow researchers who might face similar challenges and, furthermore, to discuss important issues for advancing research on the application of membrane computing in MAS modelling.
Courting Genocide: The Unintended Effects of Humanitarian Intervention

“Never Again.” This pithy and evocative phrase, which conjures up horrific images of the Holocaust and other German atrocities committed during World War II, has long been the rallying call for those advocating a more robust international legal regime to combat humanitarian atrocities. Today, the belief that perpetrators of atrocities should no longer be able to hide behind the shield of state sovereignty has gained widespread currency. Indeed, the
Comprehensive and Efficient Workload Compression.

This work studies the problem of constructing a representative workload from a given input analytical query workload where the former serves as an approximation with guarantees of the latter. We discuss our work in the context of workload analysis and monitoring. As an example, evolving system usage patterns in a database system can cause load imbalance and performance regressions which can be controlled by monitoring system usage patterns, i.e.,~a representative workload, over time. To construct such a workload in a principled manner, we formalize the notions of workload {\em representativity} and {\em coverage}. These metrics capture the intuition that the distribution of features in a compressed workload should match a target distribution, increasing representativity, and include common queries as well as outliers, increasing coverage. We show that solving this problem optimally is NP-hard and present a novel greedy algorithm that provides approximation guarantees. We compare our techniques to established algorithms in this problem space such as sampling and clustering, and demonstrate advantages and key trade-offs of our techniques.
Sparse-Hamiltonian approach to the time-evolution of molecules on quantum computers

Quantum chemistry has been viewed as one of the potential early applications of quantum computing. Two techniques have been proposed for electronic structure calculations: (1) the variational quantum eigensolver and (2) the phase-estimation algorithm. In both cases, the complexity of the problem increases for basis sets where either the Hamiltonian is not sparse, or it is sparse, but many orbitals are required to accurately describe the molecule of interest. In this work, we explore the possibility of mapping the molecular problem onto a sparse Hubbard-like Hamiltonian, which allows a Green’s-function-based approach to electronic structure via a hybrid quantum-classical algorithm. We illustrate the time-evolution aspect of this methodology with a simple four-site hydrogen ring.
On the Importance of 3D Surface Information for Remote Sensing Classification Tasks

There has been a surge in remote sensing machine learning applications that operate on data from active or passive sensors as well as multi-sensor combinations (Ma et al. (2019)). Despite this surge, however, there has been relatively little study on the comparative value of 3D surface information for machine learning classification tasks. Adding 3D surface information to RGB imagery can provide crucial geometric information for semantic classes such as buildings, and can thus improve out-of-sample predictive performance. In this paper, we examine in-sample and out-of-sample classification performance of Fully Convolutional Neural Networks (FCNNs) and Support Vector Machines (SVMs) trained with and without 3D normalized digital surface model (nDSM) information. We assess classification performance using multispectral imagery from the International Society for Photogrammetry and Remote Sensing (ISPRS) 2D Semantic Labeling contest and the United States Special Operations Command (USSOCOM) Urban 3D Challenge. We find that providing RGB classifiers with additional 3D nDSM information results in little increase in in-sample classification performance, suggesting that spectral information alone may be sufficient for the given classification tasks. However, we observe that providing these RGB classifiers with additional nDSM information leads to significant gains in out-of-sample predictive performance. Specifically, we observe an average improvement in out-of-sample all-class accuracy of 14.4% on the ISPRS dataset and an average improvement in out-of-sample F1 score of 8.6% on the USSOCOM dataset. In addition, the experiments establish that nDSM information is critical in machine learning and classification settings that face training sample scarcity.
Telgársky’s conjecture may fail

Telgarsky’s conjecture states that for each k ∈ ℕ, there is a topological space Xk such that in the Banach-Mazur game on Xk, the player nonempty has a winning (k + 1)-tactic but no winning k-tactic. We prove that this statement is consistently false. More specifically, we prove, assuming GCH+□, that if nonempty has a winning strategy for the Banach-Mazur game on a T3 space X, then she has a winning 2-tactic. The proof uses a coding argument due to Galvin, whereby if X has a π-base with certain nice properties, then nonempty is able to encode, in each consecutive pair of her opponent’s moves, all essential information about the play of the game before the current move. Our proof shows that under GCH + □, every T3 space has a sufficiently nice π-base that enables this coding strategy. Translated into the language of partially ordered sets, what we really show is that GCH + □ implies the following statement, which is equivalent to the existence of the “nice” π-bases mentioned above: ∇: Every separative poset ℙ with the κ-cc contains a dense sub-poset $$\mathbb{D}$$ such that $$\left| {\left\{ {q \in \mathbb{D} :p\;{\rm{extends}}\;q} \right\}} \right| < \kappa $$ for every p ∈ ℙ. We prove that this statement is independent of ZFC: while it holds under GCH + □, it is false even for ccc posets if $$\mathfrak{b} > {\aleph _1}$$ . We also show that if $$\left|\mathbb{P} \right| < {\aleph _\omega }$$ , then ∇-for-ℙ is a consequence of GCH holding below ∣ℙ∣.
Estimation of the number of spiked eigenvalues in a covariance matrix by bulk eigenvalue matching analysis

The spiked covariance model has gained increasing popularity in high-dimensional data analysis. A fundamental problem is determination of the number of spiked eigenvalues, K. For estimation of K, m...
Optimization schemes for unitary tensor-network circuit

This work assesses the variational optimization schemes for quantum tensor-network circuits with different structures.
Moonshine: An Online Randomness Distiller for Zero-Involvement Authentication

Context-based authentication is a method for transparently validating another device's legitimacy to join a network based on location. Devices can pair with one another by continuously harvesting environmental noise to generate a random key with no user involvement. However, there are gaps in our understanding of the theoretical limitations of environmental noise harvesting, making it difficult for researchers to build efficient algorithms for sampling environmental noise and distilling keys from that noise. This work explores the information-theoretic capacity of context-based authentication mechanisms to generate random bit strings from environmental noise sources with known properties. Using only mild assumptions about the source process's characteristics, we demonstrate that commonly-used bit extraction algorithms extract only about 10% of the available randomness from a source noise process. We present an efficient algorithm to improve the quality of keys generated by context-based methods and evaluate it on real key extraction hardware. MOONSHINE is a randomness distiller which is more efficient at extracting bits from an environmental entropy source than existing methods. Our techniques nearly double the quality of keys as measured by the NIST test suite, producing keys that can be used in real-world authentication scenarios.
How to Identify Exoplanet Surfaces Using Atmospheric Trace Species in Hydrogen-dominated Atmospheres

Sub-Neptunes (Rp~1.25-4 REarth) remain the most commonly detected exoplanets to date. However, it remains difficult for observations to tell whether these intermediate-sized exoplanets have surfaces and where their surfaces are located. Here we propose that the abundances of trace species in the visible atmospheres of these sub-Neptunes can be used as proxies for determining the existence of surfaces and approximate surface conditions. As an example, we used a state-of-the-art photochemical model to simulate the atmospheric evolution of K2-18b and investigate its final steady-state composition with surfaces located at different pressures levels (Psurf). We find the surface location has a significant impact on the atmospheric abundances of trace species, making them deviate significantly from their thermochemical equilibrium and "no-surface" conditions. This result arises primarily because the pressure-temperature conditions at the surface determine whether photochemically-produced species can be recycled back to their favored thermochemical-equilibrium forms and transported back to the upper atmosphere. For an assumed H2-rich atmosphere for K2-18b, we identify seven chemical species that are most sensitive to the existence of surfaces: ammonia (NH3), methane (CH4), hydrogen cyanide (HCN), acetylene (C2H2), ethane (C2H6), carbon monoxide (CO), and carbon dioxide (CO2). The ratio between the observed and the no-surface abundances of these species, can help distinguish the existence of a shallow surface (Psurf 100 bar). This framework can be applied together with future observations to other sub-Neptunes of interest.
Bounded remainder sets for rotations on higher-dimensional adelic tori

In this paper we give a simple, explicit construction of polytopal bounded remainder sets of all possible volumes, for any irrational rotation on the $d$ dimensional adelic torus $\mathbb{A}^d/\mathbb{Q}^d$. Our construction involves ideas from dynamical systems and harmonic analysis on the adeles, as well as a geometric argument that reduces the existence argument to the case of an irrational rotation on the torus $\mathbb{R}^d/\mathbb{Q}^d$.
HetSeq: Distributed GPU Training on Heterogeneous Infrastructure.

Modern deep learning systems like PyTorch and Tensorflow are able to train enormous models with billions (or trillions) of parameters on a distributed infrastructure. These systems require that the internal nodes have the same memory capacity and compute performance. Unfortunately, most organizations, especially universities, have a piecemeal approach to purchasing computer systems resulting in a heterogeneous infrastructure, which cannot be used to compute large models. The present work describes HetSeq, a software package adapted from the popular PyTorch package that provides the capability to train large neural network models on heterogeneous infrastructure. Experiments with language translation, text and image classification shows that HetSeq scales over heterogeneous systems. Additional information, support documents, source code are publicly available at https://github.com/yifding/hetseq.
An End-to-End Differentiable Framework for Contact-Aware Robot Design

The current dominant paradigm for robotic manipulation involves two separate stages: manipulator design and control. Because the robot’s morphology and how it can be controlled are intimately linked, joint optimization of design and control can significantly improve performance. Existing methods for co-optimization are limited and fail to explore a rich space of designs. The primary reason is the trade-off between the complexity of designs that is necessary for contact-rich tasks against the practical constraints of manufacturing, optimization, contact handling, etc. We overcome several of these challenges by building an end-to-end differentiable framework for contact-aware robot design. The two key components of this framework are: a novel deformation-based parameterization that allows for the design of articulated rigid robots with arbitrary, complex geometry, and a differentiable rigid body simulator that can handle contact-rich scenarios and computes analytical gradients for a full spectrum of kinematic and dynamic parameters. On multiple manipulation tasks, our framework outperforms existing methods that either only optimize for control or for design using alternate representations or co-optimize using gradient-free methods.
Measuring Trans Fats in Native American Adolescents

Obesity is becoming increasingly prevalent among US adolescents due to various factors such as food preference, availability, and social condition: however, rates of obesity in Native American adolescents are comparatively much higher than their counterparts as differences of as much as 7.2% have been reported between Native American and white adolescents. Given extensive study highlighting the highly harmful effects to overall health that consuming trans fats has been linked to, this study investigated the dietary intake levels of trans fats by Native American adolescents and explored the implications in regard to their health in terms of BMI. This was done by collecting macronutrient intake levels of adolescents aged 14-18 at Sherman Indian High School. This information was collected from participants using the Harvard School of Public Health Adolescent Questionnaire (HSPH YAQ) for an eight-week period, the data then sorted participants into appropriate dietary groups using statistical software from Cal Baptist University (CBU). The results of the analysis indicated that there was a statistically significant difference in mean trans fats intake between no risk groups (normal and underweight) and at-risk groups (overweight and obese) (p≤0.05) in male adolescents, however statistically significant findings for Native American female adolescents were not observed. This suggests that trans fats intake could be contributing to the high levels of obesity among Native American adolescents. Furthermore, it is of note that this study shows that production and consumption of trans fats are still happening on a day-to-day basis, and a continued effort must be made to eliminate all foods with trans fats from being manufactured and distributed.
NASA's Space Launch System: Launch Capability for Lunar Exploration and Transformative Science

Excitement is building for the first launch of NASA's Space Launch System (SLS), a unique exploration asset for the agency's Artemis lunar program as well as for a new generation of science missions. SLS is designed for an array of missions beyond Earth's orbit. The flexible system, which can be configured for Orion, cargo or Orion with co-manifested payload missions, offers high escape velocities to send more mass to deep space destinations. When configured with an 8.4 m-diameter fairing, SLS offers unmatched payload volume for human exploration and science missions. The initial Block 1 variant will insert at least 26 metric tons (t) to translunar injection (TLI) and the more powerful Block 1B vehicle will launch 34–37 t to TLI using a new-development upper stage. Much of the initial SLS Block 1 vehicle is complete, including the upper stage and payload section, the core stage, engines and the solid rocket boosters. The first mission, Artemis I, launching from modernized and upgraded facilities at Kennedy Space Center (KSC), will be an uncrewed test flight of SLS, Orion and ground processing, with a primary objective of testing Orion's heat shield at lunar re-entry velocity. Artemis I will have accommodations for 13 6U CubeSat payloads. These CubeSat missions will be deployed along the upper stage disposal trajectory after Orion separates from the vehicle. A rare opportunity for CubeSats to be deployed beyond low Earth orbit (LEO), Artemis I CubeSat missions range from searching for hydrogen and other volatiles on the lunar South Pole to studying the acceleration mechanisms of solar and interplanetary particles from a heliocentric trajectory. With manufacturing of the initial vehicle complete, fabrication and procurement is progressing for the second flight of SLS and Orion, Artemis II. Also an SLS Block 1 and Orion flight launching from KSC, Artemis II will mark the return of American astronauts to deep space with a lunar flyby-free return trajectory mission. With the Artemis III flight, NASA has the goal to land the first woman and the next man on the Moon. Infrastructure beyond SLS will be required for this effort, including elements of the lunar Gateway as well as lunar rovers, landers and additional commercially supplied launch services. SLS, as the only vehicle with the capability to lift 26 t of mass to TLI in its initial Block 1 variant, will remain a key component of this new-era exploration program. Future variants - Block 1B and Block 2 - will lift 34–45 t to TLI. This paper will discuss the status of testing and integration for the Artemis I vehicle, manufacturing progress for the second vehicle and the manifest outlook for primary, co-manifested and secondary payloads in the current deep space exploration environment.
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets

Deep, heavily overparameterized language models such as BERT, XLNet and T5 have achieved impressive success in many NLP tasks. However, their high model complexity requires enormous computation resources and extremely long training time for both pre-training and fine-tuning. Many works have studied model compression on large NLP models, but only focus on reducing inference cost/time, while still requiring expensive training process. Other works use extremely large batch sizes to shorten the pre-training time at the expense of high demand for computation resources. In this paper, inspired by the Early-Bird Lottery Tickets studied for computer vision tasks, we propose EarlyBERT, a general computationally-efficient training algorithm applicable to both pre-training and fine-tuning of large-scale language models. We are the first to identify structured winning tickets in the early stage of BERT training, and use them for efficient training. Comprehensive pre-training and fine-tuning experiments on GLUE and SQuAD downstream tasks show that EarlyBERT easily achieves comparable performance to standard BERT with 35~45% less training time.
Comprehension and Knowledge.

The ability of an agent to comprehend a sentence is tightly connected to the agent's prior experiences and background knowledge. The paper suggests to interpret comprehension as a modality and proposes a complete bimodal logical system that describes an interplay between comprehension and knowledge modalities.
Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Bias

It is widely accepted that reasoning about object shape is important for object recognition. However, the most powerful object recognition methods today do not explicitly make use of object shape during learning. In this work, motivated by recent developments in low-shot learning, findings in developmental psychology, and the increased use of synthetic data in computer vision research, we investigate how reasoning about 3D shape can be used to improve low-shot learning methods’ generalization performance. We propose a new way to improve existing low-shot learning approaches by learning a discriminative embedding space using 3D object shape, and using this embedding by learning how to map images into it. Our new approach improves the performance of image-only low-shot learning approaches on multiple datasets. We also introduce Toys4K, a 3D object dataset with the largest number of object categories currently available, which supports low-shot learning.1
Model-Parallel Model Selection for Deep Learning Systems

As deep learning becomes more expensive, both in terms of time and compute, inefficiencies in machine learning training prevent practical usage of state-of-the-art models for most users. The newest model architectures are simply too large to be fit onto a single processor. To address the issue, many ML practitioners have turned to model parallelism as a method of distributing the computational requirements across several devices. Unfortunately, the sequential nature of neural networks causes very low efficiency and device utilization in model parallel training jobs. We propose a new form of "shard parallelism" combining task parallelism and model parallelism, and package it into a framework we name Hydra. Hydra recasts the problem of model parallelism in the multi-model context to produce a fine-grained parallel workload of independent model shards, rather than independent models. This new parallel design promises dramatic speedups relative to the traditional model parallelism paradigm.