cssi/SciSciGPT-SciSciNet huggingface dataset:
WHEN ARE WE RIGHTFULLY AGGRIEVED?: A Comment on Postema

Joel Feinberg's four volume work The Moral Limits of the Criminal Law can, I believe, be accurately characterized as a normative treatise on what criminal law theorists call the “special part” of the criminal law. The “general part” deals with the basic elements of all criminal offenses—whatever is prohibited. Thus general part theorists analyze the notions of actus reus and mens rea , the conditions that negate voluntariness in acting, the distinction between acts and omissions, the nature of causation, joint participation in crime such as complicity and conspiracy, and the various defenses labeled justifications and excuses. Feinberg has little to say about these matters. His concern is with what conduct may be forbidden and punished—the specific substance rather than the general form of the criminal law.
Paternalism, Unconscionability Doctrine, and Accommodation

L'A. defend la doctrine juridique du deraisonnable, qui consiste a refuser l'application d'un contrat injuste, contre l'objection parternaliste qui lui est opposee. Face aux normes sociales qui garantissent l'autonomie de l'action, l'A. montre que la doctrine du deraisonnable pose probleme a la theorie liberale du compromis, ainsi qu'a la theorie politique du bien-etre et a la theorie constitutionnelle du droit.
The economic determinants of interest rate option smiles

We address three questions relating to the interest rate options market: What is the shape of the smile? What are the economic determinants of the shape of the smile? Do these determinants have predictive power for the future shape of the smile and vice versa? We investigate these issues using daily bid and ask prices of euro (€) interest rate caps/floors. We find a clear smile pattern in interest rate options. The shape of the smile varies over time and is affected in a dynamic manner by yield curve variables and the future uncertainty in the interest rate markets; it also has information about future aggregate default risk. Our findings are useful for the pricing, hedging and risk management of these derivatives.
The market for shareholder voting rights around mergers and acquisitions: Evidence from institutional daily trading and voting☆

Abstract This paper explores the market for voting rights and shareholder voting around 350 mergers and acquisitions between 1999 and 2005 by examining institutional-investor trading and voting outcomes. Our results show institutions in aggregate buy shares and hence voting rights before merger record dates. This trading is not related to proxies for merger arbitrage or trading around merger announcements, and thus is not simply a continuation of the latter. Trading and buying before record dates are positively related to voting turnout and negatively related to shareholder support of merger proposals. We explore several possible interpretations of these results.
Debt Markets in Emerging Economies: Major Trends

This paper documents the major trends in debt (bank and bond) markets in emerging economies since the early 1990s, when these markets started expanding. The paper shows that banks have increased in size in most emerging economies though from low bases. But bond markets have expanded even more, gaining importance relative to banks. The nature of financing has also changed. Local currency bond financing has expanded, the extent of dollarization of loans and bonds has declined, and the maturity of public and private sector bonds has typically increased. However, not all regions have moved in the same direction. Eastern Europe for instance increased its foreign currency debt before the global financial crisis. Relative to developed countries, emerging countries’ financial systems still remain in many aspects underdeveloped. Except in a few cases, liquidity in secondary bond markets has been declining. And the public sector captures a significant share of bond markets.
A Biblical Value in the Constitution: Mercy, Clemency, Faith and History

The United States Constitution is a strikingly secular document, and claims that the United States was founded as a “Christian Nation” find little support there. However, the majority of Americans are Christian, and it should not be surprising that many of them look for a reflection of their faith’s values in the government that is structured by that secular Constitution.This article urges that those who seek Christian values in the government processes allowed by the secular Constitution pay greater attention to the neglected pardon clause. The exercise of mercy is a fundamental Christian imperative, and the idea of pardon is an important and compelling theme in the gospels themselves: Jesus was nearly granted clemency by Pilate, and Jesus himself grants a pardon to the woman who is about to be executed in John 8. To the serious scholar who believes in both the imperatives of Christ and the secular limitations of the Constitution, the pardon power provides a rare instance of those roads running together.
Volume, volatility, and leverage: A dynamic analysis

Abstract This paper uses dynamic impulse response analysis to investigate the interrelationships among stock price volatility, trading volume, and the leverage effect. Dynamic impulse response analysis is a technique for analyzing the multi-step-ahead characteristics of a nonparametric estimate of the one-step conditional density of a strictly stationary process. The technique is the generalization to a nonlinear process of Sims-style impulse response analysis for linear models. In this paper, we define the technique and apply it to a long panel of daily observations on the price and trading volume of four stocks actively traded on the NYSE: Boeing, Coca-Cola, IBM, and MMM.
Parenthood by pure intention: assisted reproduction and the functional approach to parentage.

In this Article, Professor Storrow articulates a theoretical foundation for extending the privilege of intentional parenthood to all individuals, regardless of their marital status. Noting the failure of traditional methods of defining parentage to resolve the parentage issues arising from the use of assisted reproduction, Storrow turns to recently enacted and proposed statutory provisions that clearly define intentional parenthood but reserve the status to married couples alone. Taking issue with the exclusionary criteria of these provisions, Storrow's analysis aligns the emerging doctrine of functional parenthood with current theories in support of intentional parenthood to demonstrate that planning and preparing for the birth of a child--not marriage--are the essential criteria in determining who is--and is not--an intentional parent.
A No‐Arbitrage Structural Vector Autoregressive Model of the UK Yield Curve

This article combines a Structural Vector Autoregression with a no-arbitrage approach to build a multifactor Affine Term Structure Model (ATSM). The resulting No-Arbitrage Structural Vector Autoregressive (NASVAR) model implies that expected excess returns are driven by structural macroeconomic shocks. This is in contrast with a standard ATSM, in which agents are concerned with non-structural risks. As a simple application, we study the effects of supply, demand and monetary policy shocks on the UK yield curve. We show that all structural shocks affect the slope of the yield curve, with demand and supply shocks accounting for a large part of the time variation in bond yields.
More on Marriage, Fertility, and the Distribution of Income*

According to Pareto (1896), the distribution of income depends on “the nature of the people comprising a society, on the organization of the latter, and, also, in part, on chance.” In the model developed here the “nature of the people” is captured by attitudes toward marriage, divorce, fertility, and children. Singles search for mates in a marriage market. Married agents bargain about work, and the quantity and quality of children. They can divorce. Social policies, such as child support requirements, reflect the “organization of the (society).” Finally, “chance” is modeled by randomness in income, marriage opportunities, and marital bliss.
Information Technology and the Future of Cities

Abstract Will improvements in information technology eliminate face-to-face interactions and make cities obsolete? In this paper, we present a model where people make contacts and choose a mode of interaction: meeting face-to-face or communicating electronically. Cities are a means of reducing the fixed travel costs involved in face-to-face interactions. When telecommunications technology improves, there will be two opposing effects on cities and face-to-face interactions. First, some relationships that would have been face-to-face will be conducted electronically. Second, the increase in frequency of contact between individuals caused by improvements in telecommunications technology may result in more face-to-face interactions. If the second effect dominates, telecommunications improvements will complement both face-to-face interactions and cities. Our empirical work suggests that telecommunications may be a complement to, or at least not a strong substitute for, cities and face-to-face interactions.
Southern Solutions for Wisconsin Woes

Since 2011, a number of states have amended their collective bargaining laws covering state and local government employees. Debate rages about whether the goal of the proponents of change was to address budget shortfalls or weaken labor unions. Regardless of motive, legislatures in several states accomplished the goal of severely limiting or eliminating collective bargaining for some or all employees. The question facing unions, employers and employees in those states is “what now?” An answer may lie in looking to southern states like Virginia and North Carolina that have historically prohibited or severely restricted bargaining. This article explores the lessons that that might lie in the labor relations climates there for parties in states facing new and unfamiliar landscapes. The article first discusses labor relations in the southern states, with a primary emphasis on Virginia, and analyzes the factors that contribute to successful union-management relations where they exist. Then, the article considers how these factors might apply in states with newly enacted changes to their collective bargaining laws, focusing specifically on those states that eliminated or virtually eliminated bargaining rights. The article concludes that while labor relations might change in those states, unionization will survive as employees continue to seek a voice in the workplace.
goSLP: globally optimized superword level parallelism framework

Modern microprocessors are equipped with single instruction multiple data (SIMD) or vector instruction sets which allow compilers to exploit superword level parallelism (SLP), a type of fine-grained parallelism. Current SLP auto-vectorization techniques use heuristics to discover vectorization opportunities in high-level language code. These heuristics are fragile, local and typically only present one vectorization strategy that is either accepted or rejected by a cost model. We present goSLP, a novel SLP auto-vectorization framework which solves the statement packing problem in a pairwise optimal manner. Using an integer linear programming (ILP) solver, goSLP searches the entire space of statement packing opportunities for a whole function at a time, while limiting total compilation time to a few minutes. Furthermore, goSLP optimally solves the vector permutation selection problem using dynamic programming. We implemented goSLP in the LLVM compiler infrastructure, achieving a geometric mean speedup of 7.58% on SPEC2017fp, 2.42% on SPEC2006fp and 4.07% on NAS benchmarks compared to LLVM’s existing SLP auto-vectorizer.
The value of flexible backup suppliers and disruption risk information: newsvendor analysis with recourse

This article develops a model and analysis to provide insight into two effective remedies to increase supply chain resilience: (i) contracting with a secondary flexible backup supplier; and (ii) monitoring primary suppliers to obtain disruption risk information. To investigate the true value of these strategies, an analysis is performed under imperfect information concerning the disruption risks and considering a two-stage setting with recourse. In this setting, the firm first monitors its suppliers and then utilizes a recourse option subject to the limited quantity of a capacity reserved a priori via a contract with a flexible backup supplier. The firm’s jointly optimal behavior is analytically characterized (utilizing only the information available to the firm) regarding two interconnected decisions: (i) the advance capacity investment/reservation level with a flexible backup supplier; and (ii) the inventory ordering policy of the underlying products from both primary and backup suppliers. The presented...
Benchmarking Money Manager Performance: Issues and Evidence

Academic and practitioner research evaluates portfolio performance using size and value/growth attributes or factors. We assess the merits of popular evaluation procedures based on matched-characteristic benchmark portfolios or time-series return regressions by applying them to a sample of active money managers and passive indexes. Estimated abnormal returns display large variation across approaches. The benchmarks typically used in academic research--attribute-matched portfolios from independent sorts, the three-factor time-series model, and cross-sectional regressions of returns on stock characteristics--track returns poorly. Some simple alterations improve the performance of these methods. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.
Affordable Housing and Civic Participation: Two Sides of the Same Coin

Over the past several decades, America's inner cities have deteriorated socially, economically, and politically. Simultaneously, civic engagement, almost by any measure, has been on the decline: Americans vote less and volunteer less, go out to dinner with friends less and attend PTA meetings less. In this Article, I argue that the two phenomena are linked, at least from the perspective of remedies. Specifically, by rebuilding our inner cities to promote mixed-use, mixed-income development, we can revitalize some of the most impoverished neighborhoods in our country while simultaneously engendering the mechanisms to foster increased civic engagement in our participatory democracy.
Patents, Biopolitics, and Feminisms: Locating Patent Law Struggles over Breast Cancer Genes and the Hoodia Plant

This article suggests three critical inquiries for formulating a feminist analysis of patent law. The first questions how patent law functions as a strategy within neoliberal, biopolitics. The second examines how patent law is structured through biopolitical techniques of governance by examining two conceptions of the public domain I call open public domain and protective public domain. The third inquiry, drawing upon feminist science studies, asks how women's reproductive and intellectual labor are valued and devalued in various different ways through new patent law technologies. In addition, two recent patent law are struggles are examined. These include an American Civil Liberties Union case against the patenting of breast cancer gene sequences and Southern African San struggles against patents related to the Hoodia gordonii plant. In conclusion, I argue that patent law functions within gendered and ethno-racialized forms of neoliberal, biopolitics involving the patenting of women's reproductive and intellectual labor within new bioeconomics.
Where did economics go wrong? Modern economics as a flight from reality

Abstract F. A. Hayek's realistic economic theory has been replaced by the formalistic use of equlibrium models that bear little resemblance to reality. These models are as serviceable to the right as to the left: they allow the economist either to condemn capitalism for failing to measure up to the model of perfect competition, or to praise capitalism as a utopia of perfect knowledge and rational expectations. Hayek, by contrast, used equilibrium to show that while capitalism is not perfect, it contains error‐correcting institutions that bring it closer to perfection than is intuitively apparent.
Retaliation in the EEO Office

This Article examines a new and as-yet unexplored development in retaliation law under Title VII and other anti-discrimination statutes: the denial of protection from retaliation to the class of employees charged with enforcing their employers’ internal anti-discrimination policies and complaint procedures. Through distinctive applications of traditional retaliation doctrine and newer rules formulated specifically for this class of employees, these workers are increasingly vulnerable to unchecked retaliation by their employers. This troubling trend has important implications for workplace retaliation law and for employment discrimination law more broadly. This Article makes two contributions to legal scholarship. First, it traces the legal doctrines that are leaving employees who have internal EEO responsibilities without meaningful protection from retaliation. Despite increased focus on retaliation law by legal scholars, these developments have not been explored in the legal literature and are significant in their own right for their virtual exclusion of an expanding class of workers from the law’s protection from retaliation. Second, the Article contextualizes these developments within the past two decades’ shift toward an internal governance model of employment discrimination law. As courts have come to embrace internal EEO policies as a measure of substantive compliance with the external law, retaliation law has become increasingly out of synch with the employer autonomy that this model preserves. The problems created by retaliation law’s treatment of EEO employees are part of a broader rift between retaliation law and discrimination law that this Article brings to light.
WRONGFUL LIFE, PROCREATIVE RESPONSIBILITY, AND THE SIGNIFICANCE OF HARM

A wrongful life suit is an unusual civil suit brought by a child (typically a congenitally disabled child)1 who seeks damages for burdens he suffers that result from his creation. Typically, the child charges that he has been born into an unwanted or miserable life.2 These suits offer the prospect of financial relief for some disabled or neglected children and have some theoretical advantages over alternative causes of action.3 But they have had only mixed, mostly negative, success.4 They have, however, spurred considerable philosophical interest.5 This attention, though, has been primarily focused on issues about the coherence of complaining about one’s existence or its essential conditions. These suits also raise important, but less well-probed, philosophical questions about the morality of procreation and, more generally, about the moral significance of imposed, but not consented to, conditions that deliver both significant harms and benefits.
BioSamplr: An open source, low cost automated sampling system for bioreactors

Abstract Autosampling from bioreactors reduces error, increases reproducibility and offers improved aseptic handling when compared to manual sampling. Additionally, autosampling greatly decreases the hands-on time required for a bioreactor experiment and enables sampling 24 h a day. We have designed, built and tested a low cost, open source, automated bioreactor sampling system, the BioSamplr. The BioSamplr can take up to ten samples from a bioreactor at a desired sample interval and cools them to a desired temperature. The device, assembled from low cost and 3D printed components, is controlled wirelessly by a Raspberry Pi, and records all sampling data to a log file. The cost and accessibility of the BioSamplr make it useful for laboratories without access to more expensive and complex autosampling systems.
First Investigation into the Use of Deep Learning for Continuous Assessment of Neonatal Postoperative Pain

This paper presents the first investigation into the use of fully automated deep learning framework for assessing neonatal postoperative pain. It specifically investigates the use of Bilinear Convolutional Neural Network (B-CNN) to extract facial features during different levels of postoperative pain followed by modeling the temporal pattern using Recurrent Neural Network (RNN). Although acute and postoperative pain have some common characteristics (e.g., visual action units), postoperative pain has a different dynamic, and it evolves in a unique pattern over time. Our experimental results indicate a clear difference between the pattern of acute and postoperative pain. They also suggest the efficiency of using a combination of bilinear CNN with RNN model for the continuous assessment of postoperative pain intensity.
Isotropy and Log-Concave Polynomials: Accelerated Sampling and High-Precision Counting of Matroid Bases

We define a notion of isotropy for discrete set distributions. If $\mu$ is a distribution over subsets $\mathcal{S}$ of a ground set [ $n$ ], we say that $\mu$ is in isotropic position if $\mathbb{P}_{\mathcal{S}\sim\mu}[e\in \mathcal{S}]$ is the same for all $e\in[n]$ . We design a new approximate sampling algorithm that leverages isotropy for the class of distributions $\mu$ that have a log-concave generating polynomial; this class includes determinantal point processes, strongly Rayleigh distributions, and uniform distributions over matroid bases. We show that when $\mu$ is in approximately isotropic position, the running time of our algorithm depends polynomially on the size of the set $\mathcal{S}$ , and only logarithmically on $n$ . When $n$ is much larger than the size of $\mathcal{S}$ , this is significantly faster than prior algorithms, and can even be sublinear in $n$ . We then show how to transform a non-isotropic $\mu$ into an equivalent approximately isotropic form with a polynomial-time pre-processing step, accelerating subsequent sampling times. The main new ingredient enabling our algorithms is a class of negative dependence inequalities that may be of independent interest. As an application of our results, we show how to approximately count bases of a matroid of rank $k$ over a ground set of $n$ elements to within a factor of $1+\epsilon$ in time $O((n+1/\epsilon^{2}) \cdot \text{poly}(k,\log n))$ . This is the first algorithm that runs in nearly linear time for fixed rank $k$ , and achieves an inverse polynomially low approximation error. The full version of this paper is available at: https://arxiv.org/abs/2004.09079
Modalities, Challenges, and Possibilities: An Introduction to the Pharmaceutical Innovation Symposium

On October 25, 2019, the Texas A&M Journal of Property Law and the Center for Law and Intellectual Property at Texas A&M University School of Law jointly organized the "Pharmaceutical Innovation, Patent Protection and Regulatory Exclusivities" Symposium. Although none of the organizers and participants could predict what was to come in the next few months, there was a wide consensus that the rapid changes in the pharmaceutical landscape and our continuous struggle to strike a proper balance between proprietary protection and public access in the public health arena deserves scholarly, policy and regulatory attention. To inform readers about the inspirations and motivations behind the Symposium, this introductory article begins by exploring the different modalities of protection, in particular the role of patents and regulatory exclusivities in providing the needed incentives to pharmaceutical developers. It then identifies three sets of challenges that affect the future of pharmaceutical innovation at both the domestic and international levels. The article concludes by utilizing a very recent event—the COVID-19 pandemic—to illustrate the wide array of policy options and possibilities both within and outside the intellectual property system. It makes salient the nexus between the domestic and international debates on pharmaceutical innovation.
Docs with their eyes on the clock? The effect of time pressures on primary care productivity.

Abstract This paper examines how time pressure, an important constraint faced by medical care providers, affects productivity in primary care. We generate empirical predictions by incorporating time pressure into a model of physician behavior by Tai-Seale and McGuire (2012) . We use data from the electronic health records of a large integrated delivery system and leverage unexpected schedule changes as variation in time pressure. We find that greater time pressure reduces the number of diagnoses recorded during a visit and increases both scheduled and unscheduled follow-up care. We also find some evidence of increased low-value care, decreased preventive care, and decreased opioid prescribing.
On a conjecture of Agashe

Let $E/\mathbb{Q}$ be an optimal elliptic curve, $-D$ be a negative fundamental discriminant coprime to the conductor $N$ of $E/\mathbb{Q}$ and let $E^{-D}/\mathbb{Q}$ be the twist of $E/\mathbb{Q}$ by $-D$. A conjecture of Agashe predicts that if $E^{-D}/\mathbb{Q}$ has analytic rank $0$, then the square of the order of the torsion subgroup of $E^{-D}/\mathbb{Q}$ divides the product of the order of the Shafarevich-Tate group of $E^{-D}/\mathbb{Q}$ and the orders of the arithmetic component groups of $E^{-D}/\mathbb{Q}$, up to a power of $2$. This conjecture can be viewed as evidence for the second part of the Birch and Swinnerton-Dyer conjecture for elliptic curves of analytic rank zero. We provide a proof of a slightly more general statement without using the optimality hypothesis.
A C. elegans genome-wide RNAi screen for altered levamisole sensitivity identifies genes required for muscle function.

At the neuromuscular junction (NMJ), postsynaptic ionotropic acetylcholine receptors (AChRs) transduce a chemical signal released from a cholinergic motor neuron into an electrical signal to induce muscle contraction. To identify regulators of postsynaptic function, we conducted a genome-wide RNAi screen for genes required for proper response to levamisole, a pharmacological agonist of ionotropic L-AChRs at the Caenorhabditis elegans NMJ. A total of 117 gene knockdowns were found to cause levamisole hypersensitivity, while 18 resulted in levamisole resistance. Our screen identified conserved genes important for muscle function including some that are mutated in congenital myasthenic syndrome, congenital muscular dystrophy, congenital myopathy, myotonic dystrophy, and mitochondrial myopathy. Of the genes found in the screen, we further investigated those predicted to play a role in endocytosis of cell surface receptors. Loss of the Epsin homolog epn-1 caused levamisole hypersensitivity and had opposing effects on the levels of postsynaptic L-AChRs and GABAA receptors, resulting in increased and decreased abundance, respectively. We also examined other genes that resulted in a levamisole hypersensitive phenotype when knocked down including gas-1, which functions in Complex I of the mitochondrial electron transport chain. Consistent with altered ATP synthesis impacting levamisole response, treatment of wild-type animals with levamisole resulted in L-AChR dependent depletion of ATP levels. These results suggest that the paralytic effects of levamisole ultimately lead to metabolic exhaustion.
A Technical Overview of AV1

The AV1 video compression format is developed by the Alliance for Open Media consortium. It achieves more than a 30% reduction in bit rate compared to its predecessor VP9 for the same decoded video quality. This article provides a technical overview of the AV1 codec design that enables the compression performance gains with considerations for hardware feasibility.
Optimizing embedding-related quantum annealing parameters for reducing hardware bias

Quantum annealers have been designed to propose near-optimal solutions to NP-hard optimization problems. However, the accuracy of current annealers such as the ones of D-Wave Systems, Inc., is limited by environmental noise and hardware biases. One way to deal with these imperfections and to improve the quality of the annealing results is to apply a variety of pre-processing techniques such as spin reversal (SR), anneal offsets (AO), or chain weights (CW). Maximizing the effectiveness of these techniques involves performing optimizations over a large number of parameters, which would be too costly if needed to be done for each new problem instance. In this work, we show that the aforementioned parameter optimization can be done for an entire class of problems, given each instance uses a previously chosen fixed embedding. Specifically, in the training phase, we fix an embedding E of a complete graph onto the hardware of the annealer, and then run an optimization algorithm to tune the following set of parameter values: the set of bits to be flipped for SR, the specific qubit offsets for AO, and the distribution of chain weights, optimized over a set of training graphs randomly chosen from that class, where the graphs are embedded onto the hardware using E. In the testing phase, we estimate how well the parameters computed during the training phase work on a random selection of other graphs from that class. We investigate graph instances of varying densities for the Maximum Clique, Maximum Cut, and Graph Partitioning problems. Our results indicate that, compared to their default behavior, substantial improvements of the annealing results can be achieved by using the optimized parameters for SR, AO, and CW.
Dimensional reduction of higher-point conformal blocks

Recently, with the help of Parisi-Sourlas supersymmetry an intriguing relation was found expressing the four-point scalar conformal block of a (d − 2)-dimensional CFT in terms of a five-term linear combination of blocks of a d-dimensional CFT, with constant coefficients. We extend this dimensional reduction relation to all higher-point scalar conformal blocks of arbitrary topology restricted to scalar exchanges. We show that the constant coefficients appearing in the finite term higher-point dimensional reduction obey an interesting factorization property allowing them to be determined in terms of certain graphical Feynman-like rules and the associated finite set of vertex and edge factors. Notably, these rules can be fully determined by considering the explicit power-series representation of just three particular conformal blocks: the four-point block, the five-point block and the six-point block of the so-called OPE/snowflake topology. In principle, this method can be applied to obtain the arbitrary-point dimensional reduction of conformal blocks with spinning exchanges as well. We also show how to systematically extend the dimensional reduction relation of conformal partial waves to higher-points.
Sparse covariance estimation in logit mixture models

This paper introduces a new data-driven methodology for estimating sparse covariance matrices of the random coefficients in logit mixture models. Researchers typically specify covariance matrices in logit mixture models under one of two extreme assumptions: either an unrestricted full covariance matrix (allowing correlations between all random coefficients), or a restricted diagonal matrix (allowing no correlations at all). Our objective is to find optimal subsets of correlated coefficients for which we estimate covariances. We propose a new estimator, called MISC, that uses a mixed-integer optimization (MIO) program to find an optimal block diagonal structure specification for the covariance matrix, corresponding to subsets of correlated coefficients, for any desired sparsity level using Markov Chain Monte Carlo (MCMC) posterior draws from the unrestricted full covariance matrix. The optimal sparsity level of the covariance matrix is determined using out-of-sample validation. We demonstrate the ability of MISC to correctly recover the true covariance structure from synthetic data. In an empirical illustration using a stated preference survey on modes of transportation, we use MISC to obtain a sparse covariance matrix indicating how preferences for attributes are related to one another.
A Systematic Review of the Efforts and Hindrances of Modeling and Simulation of CAR T-cell Therapy

Chimeric antigen receptor (CAR) T-cell therapy is an immunotherapy that has recently become highly instrumental in the fight against life-threatening diseases. A variety of modeling and computational simulation efforts have addressed different aspects of CAR T-cell therapy, including T-cell activation, T- and malignant cell population dynamics, therapeutic cost-effectiveness strategies, and patient survival. In this article, we present a systematic review of those efforts, including mathematical, statistical, and stochastic models employing a wide range of algorithms, from differential equations to machine learning. To the best of our knowledge, this is the first review of all such models studying CAR T-cell therapy. In this review, we provide a detailed summary of the strengths, limitations, methodology, data used, and data gap in currently published models. This information may help in designing and building better models for enhanced prediction and assessment of the benefit-risk balance associated with novel CAR T-cell therapies, as well as with the data need for building such models.
Students’ Perspectives of Factors Related to Delayed Completion of Online RN-BSN Programs

There are multiple educational programs for individuals to become registered nurses (RNs), and the transition from an associate degree or diploma to a Bachelor of Science in Nursing (BSN) degree is vital to healthcare. This study examined the factors contributing to delayed completion or withdrawal from online RN-BSN nursing programs from students’ perspectives. Thematic content analyses were conducted on qualitative data obtained from semi-structured interviews (N = 26). Complex factors contributed to delayed completion of online RN-BSN programs, including student-, institutional-, and faculty-related factors. This study validated and extends previous studies without delineating students in fully online programs from hybrid and face-to-face programs. Students, faculty, and institutions all have a role to play in facilitating on-time program completion. Recognizing and mitigating the barriers that delay on-time program completion is required to foster nurses to obtain a BSN degree.
Achievable rates for the general Gaussian multiple access wire-tap channel with collective secrecy

We consider the General Gaussian Multiple Access Wire-Tap Channel (GGMAC-WT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed eavesdropper who is as capable as the intended receiver, but has different channel parameters. We aim to provide perfect secrecy for the transmitters in this multi-access environment. Using Gaussian codebooks, an achievable secrecy region is determined and the power allocation that maximizes the achievable sum-rate is found. Numerical results showing the new rate region are presented. It is shown that the multiple-access nature of the channel may be utilized to allow users with zero single-user secrecy capacity to be able to transmit in perfect secrecy. In addition, a new collaborative scheme is shown that may increase the achievable sum-rate. In this scheme, a user who would not transmit to maximize the sum rate can help another user who (i) has positive secrecy capacity to increase its rate, or (ii) has zero secrecy capacity to achieve a positive secrecy capacity.
Single-cell transcriptomics identifies gene expression networks driving differentiation and tumorigenesis in the human fallopian tube.

Summary The human fallopian tube harbors the cell of origin for the majority of high-grade serous “ovarian” cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We perform single-cell transcriptomic profiling of around 53,000 individual cells from 12 primary fallopian specimens to map their major cell types. We identify 10 epithelial subpopulations with diverse transcriptional programs. Based on transcriptional signatures, we reconstruct a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3high intermediate. Computational deconvolution of advanced HGSCs identifies the “early secretory” population as a likely precursor state for the majority of HGSCs. Its signature comprises both epithelial and mesenchymal features and is enriched in mesenchymal-type HGSCs (p = 6.7 × 10−27), a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia.
eDNA metabarcoding outperforms traditional fisheries sampling and reveals fine-scale heterogeneity in a temperate freshwater lake

Understanding biodiversity in aquatic systems is critical to ecological research and conservation efforts, but accurately measuring species richness using traditional methods can be challenging. Environmental DNA (eDNA) metabarcoding, which uses high-throughput sequencing and universal primers to amplify DNA from multiple species present in an environmental sample, has shown great promise for augmenting results from traditional sampling to characterize fish communities in aquatic systems. Few studies, however, have compared exhaustive traditional sampling with eDNA metabarcoding of corresponding water samples at a small spatial scale. We intensively sampled Boardman Lake (137 ha) in Michigan, USA from May to June in 2019 using gill and fyke nets and paired each net set with lake water samples collected in triplicate. We analyzed water samples using eDNA metabarcoding with 12S and 16S fish-specific primers and compared estimates of fish diversity among methods. In total, we set 60 nets and analyzed 180 1 L lake water samples. We captured a total of 12 fish species in our traditional gear and detected 40 taxa in the eDNA water samples, which included all the species observed in nets. The 12S and 16S assays detected a comparable number of taxa, but taxonomic resolution varied between the two genes. In our traditional gear, there was a clear difference in the species selectivity between the two net types, and there were several species commonly detected in the eDNA samples that were not captured in nets. Finally, we detected spatial heterogeneity in fish community composition across relatively small scales in Boardman Lake with eDNA metabarcoding, but not with traditional sampling. Our results demonstrated that eDNA metabarcoding was substantially more efficient than traditional gear for estimating community composition, highlighting the utility of eDNA metabarcoding for assessing species diversity and informing management and conservation.
Phase-field model for a weakly compressible soft layered material: morphological transitions on smectic–isotropic interfaces

A coupled phase-field and hydrodynamic model is introduced to describe a two-phase, weakly compressible smectic (layered phase) in contact with an isotropic fluid of different density. A non-conserved smectic order parameter is coupled to a conserved mass density in order to accommodate non-solenoidal flows near the smectic–isotropic boundary arising from density contrast between the two phases. The model aims to describe morphological transitions in smectic thin films under heat treatment, in which arrays of focal conic defects evolve into conical pyramids and concentric rings through curvature dependent evaporation of smectic layers. The model leads to an extended thermodynamic relation at a curved surface that includes its Gaussian curvature, non-classical stresses at the boundary and flows arising from density gradients. The temporal evolution given by the model conserves the overall mass of the liquid crystal while still allowing for the modulated smectic structure to grow or shrink. A numerical solution of the governing equations reveals that pyramidal domains are sculpted at the center of focal conics upon a temperature increase, which display tangential flows at their surface. Other cases investigated include the possible coalescence of two cylindrical stacks of smectic layers, formation of droplets, and the interactions between focal conic domains through flow.
Bumpless pipe dreams and alternating sign matrices

Abstract In their work on the infinite flag variety, Lam, Lee, and Shimozono [30] introduced objects called bumpless pipe dreams and used them to give a formula for double Schubert polynomials. We extend this formula to the setting of K-theory, giving an expression for double Grothendieck polynomials as a sum over a larger class of bumpless pipe dreams. Our proof relies on techniques found in an unpublished manuscript of Lascoux [27] . Lascoux showed how to write double Grothendieck polynomials as a sum over alternating sign matrices. We explain how to view the Lam-Lee-Shimozono formula as a disguised special case of Lascoux's alternating sign matrix formula. Knutson, Miller, and Yong [21] gave a tableau formula for vexillary Grothendieck polynomials. We recover this formula by showing vexillary marked bumpless pipe dreams and flagged set-valued tableaux are in weight preserving bijection. Finally, we give a bijection between Hecke bumpless pipe dreams and decreasing tableaux. The restriction of this bijection to Edelman-Greene bumpless pipe dreams solves a problem of Lam, Lee, and Shimozono.
Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis.

Lineage tracing is a powerful tool in developmental biology to interrogate the evolution of tissue formation, but the dense, three-dimensional nature of tissue limits the assembly of individual cell trajectories into complete reconstructions of development. Human induced pluripotent stem cells (hiPSCs) can recapitulate aspects of developmental processes, providing an in vitro platform to assess the dynamic collective behaviors directing tissue morphogenesis. Here, we trained an ensemble of neural networks to track individual hiPSCs in time-lapse microscopy, generating longitudinal measures of cell and cellular neighborhood properties on timescales from minutes to days. Our analysis reveals that, while individual cell parameters are not strongly affected by pluripotency maintenance conditions or morphogenic cues, regional changes in cell behavior predict cell fate and colony organization. By generating complete multicellular reconstructions of hiPSC behavior, our tracking pipeline enables fine-grained understanding of morphogenesis by elucidating the role of regional behavior in early tissue formation.
User-oriented Fairness in Recommendation

As a highly data-driven application, recommender systems could be affected by data bias, resulting in unfair results for different data groups, which could be a reason that affects the system performance. Therefore, it is important to identify and solve the unfairness issues in recommendation scenarios. In this paper, we address the unfairness problem in recommender systems from the user perspective. We group users into advantaged and disadvantaged groups according to their level of activity, and conduct experiments to show that current recommender systems will behave unfairly between two groups of users. Specifically, the advantaged users (active) who only account for a small proportion in data enjoy much higher recommendation quality than those disadvantaged users (inactive). Such bias can also affect the overall performance since the disadvantaged users are the majority. To solve this problem, we provide a re-ranking approach to mitigate this unfairness problem by adding constraints over evaluation metrics. The experiments we conducted on several real-world datasets with various recommendation algorithms show that our approach can not only improve group fairness of users in recommender systems, but also achieve better overall recommendation performance.
Mutation-specific SARS-CoV-2 PCR Screen: Rapid and Accurate Detection of Variants of Concern and the Identification of a Newly Emerging Variant with Spike L452R Mutation.

The emergence of more transmissible and/or more virulent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) has triggered intensive genomic surveillance, which is costly and difficult to sustain operationally over the long term. To address this problem, we developed a set of four multiplex mutation-specific PCR-based assays with same-day reporting that can detect five VOC and three variants of interest (VOI), as defined in the March 2021 guidelines from the U.S. Centers for Disease Control and Prevention (https://www.cdc.gov/coronavirus/2019-ncov/). The screening results were compared to the whole-genome sequencing (WGS) and showed 100% concordance for strain typing for B.1.1.7 (n = 25) and P.1 (n = 5) variants using spike (S) mutation S-N501Y, S-E484K, and S-H69-V70del assays. The S-L450R assay, designed to detect the B.1.427/429 VOC, also identified multiple isolates of a newly emerging multiply mutated B.1.526.1 variant that is now rapidly increasing in the eastern United States. PCR approaches can be easily adopted in clinical laboratories, providing rapid screening methods to allow early detection of newly emergent variants and to efficiently triage cases for full genomic sequencing.
Digital quantum simulation of molecular dynamics and control

The authors present a framework that uses quantum and classical computers in tandem to design optimal fields for controlling the dynamics of molecular systems.
IPO peer effects

Abstract This study investigates whether a private firm’s decision to go public affects the IPO decisions of its competitors. Using detailed data from the drug development industry, we identify a private firm’s direct competitors at a precise level through a novel approach using similarity in drug development projects based on disease targets. The analysis shows that a private firm is significantly more likely to go public after observing the recent IPO of a direct competitor, and this effect is distinct from “hot” market effects or other common shocks. Furthermore, our effects are centered on firms that operate in more competitive areas. We additionally explore peer effects in private firm funding propensities more broadly, such as through venture capital or being acquired, and find results consistent with a competitive channel.
Unveiling Anomalous Edges and Nominal Connectivity of Attributed Networks

Uncovering anomalies in attributed networks has recently gained popularity due to its importance in unveiling outliers and flagging adversarial behavior in a gamut of data and network science applications including the Internet of Things (IoT), finance, security, to list a few. The present work deals with uncovering anomalous edges in attributed graphs using two distinct formulations with complementary strengths, which can be easily distributed, and hence efficient. The first relies on decomposing the graph data matrix into low rank plus sparse components to markedly improve performance. The second broadens the scope of the first by performing robust recovery of the unperturbed graph, which enhances the anomaly identification performance. The novel methods not only capture anomalous edges linking nodes of different communities, but also spurious connections between any two nodes with different features. Experiments conducted on real and synthetic data corroborate the effectiveness of both methods in the anomaly identification task.