cssi/SciSciGPT-SciSciNet huggingface dataset:
Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction

Abstract Many recent modeling advances in finance topics ranging from the pricing of volatility-based derivative products to asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in forecasting volatility. Key papers in this area include Andersen et al. (2003), Corsi (2004), Andersen et al. (2007), Corsi et al. (2008), Barndorff et al. (2010), Patton and Shephard (2011), and the references cited therein. In this paper, we review the extant literature and then present new empirical evidence on the predictive content of realized measures of jump power variations (including upside and downside risk, jump asymmetry, and truncated jump variables), constructed using instantaneous returns, i.e., | r t | q , 0 ≤ q ≤ 6 in the spirit of Ding et al. (1993) and Ding and Granger (1996). We also present new empirical evidence on the predictive content of realized measures of truncated large jump variations, constructed using truncated squared instantaneous return, i.e., r t 2 × I | r t | > γ , where γ is the threshold jump size. Our prediction experiments use high frequency price returns constructed using S&P500 futures data as well as stocks in the Dow 30, and our empirical implementation involves estimating linear and nonlinear heterogeneous autoregressive realized volatility (HAR-RV) type models. We find that past “large” jump power variations help less in the prediction of future realized volatility, than past “small” jump power variations. Additionally, we find evidence that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility, and that past downside jump variations matter in prediction. Finally, incorporation of downside and upside jump power variations does improve predictability, albeit to a limited extent.
Do local and international venture capitalists play well together? The complementarity of local and international venture capitalists

Abstract We find that entrepreneurial firms in emerging nations backed by syndicates composed of international and local venture capitalists have more successful exits and higher post-IPO operating performance than those backed by syndicates of purely international or purely local venture capitalists. We control for the potential endogenous participation and syndication by international VCs using instrumental variables analyses and a natural experiment and find a causal effect of international VC participation on successful outcomes. International VCs face disadvantages in their investments due to the lack of proximity to the entrepreneurial firm. Using air service agreements between countries as an exogenous change in effective proximity, we find that entrepreneurial firms backed by international VCs are more successful when travel becomes easier between the two countries. Overall, our results indicate that the greater venture capital expertise of international venture capitalists and the superior local knowledge and lower monitoring costs of local venture capitalists are both important in obtaining successful investment outcomes.
The Rehnquist Court and the Groundwork for Greater First Amendment Scrutiny of Intellectual Property

This contribution to the Washington University School of Law conference on the Rehnquist Court and the First Amendment addresses the Rehnquist Court's view of the role of the First Amendment in intellectual property cases. It argues that, while the Rehnquist Court was not eager to find a conflict between intellectual property laws and the First Amendment, there is reason to believe that it set the stage for greater First Amendment scrutiny of intellectual property protections. At the very least, the Court left that road open to future courts, which might be inclined to view intellectual property more skeptically.
Does distance still matter? The information revolution in small business lending

The distance between small firms and their lenders is increasing, and they are communicating in more impersonal ways. After documenting these systematic changes, we demonstrate they do not arise from small firms locating differently, consolidation in the banking industry, or biases in the sample. Instead, improvements in lender productivity appear to explain our findings. We also find distant firms no longer have to be the highest quality credits, indicating they have greater access to credit. The evidence indicates there has been substantial development of the financial sector, even in areas such as small business lending.
Intellectual Property, Asian Philosophy and the Yin- Yang School

Written for a special issue on intellectual property philosophy, this article begins by providing a brief discussion of the many different schools of Asian philosophy, including those in China and India. Although Confucianism has garnered considerable attention in intellectual property literature, the nexus between Asian philosophy and the notion of intellectual property rights remains largely understudied. Thus, instead of revisiting the debate on intellectual property and Confucianism, this article aims to introduce to the Western audience Yin-Yang, one of the six dominant ancient schools of Chinese philosophy. It argues that this school’s focus on contexts, relationships and adaptiveness and its high tolerance for contradictions have made it particularly well-equipped to address the ongoing intellectual property challenges concerning both emerging economies and the digital environment.
The Determinants and Impact of Private Tutoring Classes in Vietnam.

Private tutoring is a widespread phenomenon in many developing countries, including Vietnam. Using the Vietnam Living Standards Surveys 1997–1998 and 1992–1993 for analysis, this paper finds evidence that private tutoring in Vietnam is a necessity in the household budget for both primary students and lower secondary students, and the trend to attend private tutoring is stronger at higher education levels. There is no evidence of gender discrimination in expenditure on private tutoring. Ethnic minority students spend less on private tutoring at the primary level but not at the lower secondary level, as do students living in rural areas. However, spending on private tutoring would fall significantly if the qualifications of primary school teachers are increased. Private tutoring is found to have significant impact on a student's academic performance, but the influence is larger for lower secondary students. This paper contributes to the available estimation techniques by extending the simultaneous Tobit model of Amemiya [(1974). Multivariate regression and simultaneous equation models when the dependent variables are truncated normal. Econometrica, 42(6), 999–1012] to a joint Tobit-ordered probit econometric model to address the possible endogeneity of household spending on private tutoring.
Cool Data on a Hot Issue: Empirical Evidence that a Law School Bar Support Program Enhances Bar Performance

Te bar exam is a hot and controversial topic for academics, lawyers, bar examiners, graduates, and students. Criticism of the exam abounds. Does the bar exam correctly decide who should be admitted to practice law? Does the bar exam unfairly exclude minorities from the profession? Regardless of the accuracy of these criticisms, the bar exam is a reality that law schools and their graduates must face. Many law schools are now offer programs specifically designed to improve their graduates' performance on the bar exam. But none has engaged in a statistically verifiable analysis of whether the programs materially affect a student's chance of passing the bar on a first attempt. This article fills the gap. It presents statistical analyses supporting the conclusion that a bar support program can significantly improve bar passage rates.
Law, medicine, and wealth: does concierge medicine promote health care choice, or is it a barrier to access?

Many primary care physicians are unhappy with patient panels in excess of 3000, increased administrative requirements, reduced reimbursement rates, and other earmarks of managed care. Concierge medicine is a new form of medical practice that allows physicians to reduce their patient load to perhaps 300 or less, in order to spend more time with each patient and increase their incomes at the same time. In one model, the physician accomplishes this by charging patients a monthly fee that varies from a few hundred to over a thousand dollars, for which the patient is allowed to access the medical services of the physician. The fee covers special attention from the physician and a list of amenities not usually covered by insurance, while the patients remain responsible for their medical bills. The dark side of concierge medicine is that thousands of patients unable to pay the fee no longer have access to their physician, and must find a new physician in a market with increasingly fewer primary care physicians available. Because wealthier patients are often healthier, concierge medicine may also require those physicians remaining within the system to absorb the sicker patients. Medicare patients in particular may be disproportionately affected. This presentation briefly reviews state and federal laws that may impede this new practice form, as well as its ethical implications. More importantly, this presentation focuses on the potential negative effects of concierge medicine on access to health care. It concludes that, although physicians may provide, and wealthy persons may receive, medical care as they wish (or as the market will bear), private insurers should exclude concierge physicians from their networks and physicians should be prohibited from charging Medicare patients access fees.
Why Judicial Takings are Unripe

In Stop the Beach Renourishment v. Florida Department of Environmental Protection, the Supreme Court considered without resolving whether a judicial decision reinterpreting property law could violate the Takings Clause of the Fifth Amendment. This Note focuses on ripeness and other procedural implications of the judicial takings concept because they present both practical and doctrinal problems. First, ripeness is important on a practical level because it presents a threshold justiciability hurdle for judicial taking claims. Second, the judicial takings concept seems fundamentally at odds with the judicial federalism underpinnings of the Court’s special ripeness rules for takings claims. The Court has essentially forced all federal takings claims into state courts on the premise that they offered an adequate forum, but now the judicial takings theory would prop back open the federal courthouse doors to check purported state court abuses. This Note concludes that, until the Supreme Court reconsiders its special ripeness rules from Williamson County Regional Planning Commission v. Hamilton Bank, lower courts should strictly apply the state litigation requirement and limit judicial takings claims to state courts with the possibility of certiorari review when parties properly raise those claims below. This approach would achieve the desired outcomes of a judicial takings doctrine - forcing state courts to recognize the risk of altering property rules and improve the quality of their decisions - while remaining faithful to the practical requirements and policy rationales of the Court’s current ripeness jurisprudence.
Two Dualities: Markov and Schur–Weyl

We show that quantum Schur-Weyl duality leads to Markov duality for a variety of asymmetric interacting particle systems. In particular, we consider three cases: (1) Using a Schur-Weyl duality between a two-parameter quantum group and a two-parameter Hecke algebra from arXiv:math/0108038, we recover the Markov self-duality of multi-species ASEP previously discovered in arXiv:1605.00691 and arXiv:1606.04587. (2) From a Schur-Weyl duality between a co-ideal subalgebra of a quantum group and a Hecke algebra of type B arXiv:1609.01766, we find a Markov duality for a multi-species open ASEP on the semi-infinite line. The duality functional has not previously appeared in the literature. (3) A "fused" Hecke algebra from arXiv:2001.11372 leads to a new process, which we call braided ASEP. In braided ASEP, up to m particles may occupy a site and up to m particles may jump at a time. The Schur-Weyl duality between this Hecke algebra and a quantum group lead to a Markov duality. The duality function had previously appeared as the duality function of the multi-species ASEP(q,m/2) arXiv:1605.00691 and the stochastic multi-species higher spin vertex model arXiv:1701.04468.
DRPnet: automated particle picking in cryo-electron micrographs using deep regression

Identification and selection of protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based particle picking network to automatically detect particle centers from cryoEM micrographs. This is a challenging task due to the nature of cryoEM data, having low signal-to-noise ratios with variable particle sizes, shapes, distributions, grayscale variations as well as other undesirable artifacts. We propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. This approach, entitled Deep Regression Picker Network or “DRPnet”, is simple but very effective in recognizing different particle sizes, shapes, distributions and grayscale patterns corresponding to 2D views of 3D particles. Particles are detected by the first network, a fully convolutional regression network (FCRN), which maps the particle image to a continuous distance map that acts like a probability density function of particle centers. Particles identified by FCRN are further refined to reduce false particle detections by the second classification CNN. DRPnet’s first CNN pretrained with only a single cryoEM dataset can be used to detect particles from different datasets without retraining. Compared to RELION template-based autopicking, DRPnet results in better particle picking performance with drastically reduced user interactions and processing time. DRPnet also outperforms the state-of-the-art particle picking networks in terms of the supervised detection evaluation metrics recall, precision, and F-measure. To further highlight quality of the picked particle sets, we compute and present additional performance metrics assessing the resulting 3D reconstructions such as number of 2D class averages, efficiency/angular coverage, Rosenthal-Henderson plots and local/global 3D reconstruction resolution. DRPnet shows greatly improved time-savings to generate an initial particle dataset compared to manual picking, followed by template-based autopicking. Compared to other networks, DRPnet has equivalent or better performance. DRPnet excels on cryoEM datasets that have low contrast or clumped particles. Evaluating other performance metrics, DRPnet is useful for higher resolution 3D reconstructions with decreased particle numbers or unknown symmetry, detecting particles with better angular orientation coverage.
Chemokine CCL5 promotes robust optic nerve regeneration and mediates many of the effects of CNTF gene therapy

Ciliary neurotrophic factor (CNTF) is a leading therapeutic candidate for several ocular diseases and induces optic nerve regeneration in animal models. Paradoxically, however, although CNTF gene therapy promotes extensive regeneration, recombinant CNTF (rCNTF) has little effect. Because intraocular viral vectors induce inflammation, and because CNTF is an immune modulator, we investigated whether CNTF gene therapy acts indirectly through other immune mediators. The beneficial effects of CNTF gene therapy remained unchanged after deleting CNTF receptor alpha (CNTFRα) in retinal ganglion cells (RGCs), the projection neurons of the retina, but were diminished by depleting neutrophils or by genetically suppressing monocyte infiltration. CNTF gene therapy increased expression of C-C motif chemokine ligand 5 (CCL5) in immune cells and retinal glia, and recombinant CCL5 induced extensive axon regeneration. Conversely, CRISPR-mediated knockdown of the cognate receptor (CCR5) in RGCs or treating wild-type mice with a CCR5 antagonist repressed the effects of CNTF gene therapy. Thus, CCL5 is a previously unrecognized, potent activator of optic nerve regeneration and mediates many of the effects of CNTF gene therapy.
Highly volatile element (H, C, F, Cl, S) abundances and H isotopic compositions in chondrules from carbonaceous and ordinary chondrites

Abstract The partial pressures and isotopic compositions of volatiles present during chondrule formation can be constrained by the highly volatile element or HVE (H, C, F, Cl, and S) abundances and isotopic compositions in chondrules. Here we present the results of high spatial resolution and low background secondary ion mass spectroscopy (SIMS) analyses of the HVE concentrations and H isotopic compositions in type I and II chondrules in primitive ordinary chondrites Semarkona (LL3.00) and Queen Alexandra Range (QUE) 97008 (L3.05), and the primitive carbonaceous chondrite Dominion Range (DOM) 08006 (CO3.00). The HVEs in the chondrules primarily reside in the mesostases, in which the HVE contents and H isotopic compositions vary significantly (H2O: 8–10,200 ppm, CO2: 2.4–1170 ppm, F: 0.3–30 ppm, Cl: 0.07–175 ppm, S: 0.38–4400 ppm, δD: 77–15,000‰). To dissolve such HVE contents in a silicate melt requires significantly higher total pressures (up to 1900 bars), and in some cases requires anomalous gas compositions (CO dominated), compared to those expected from canonical conditions of chondrule formation (∼10−3 bars, H2 + H2O dominated). Rather, the enrichments of H2O, CO2, Cl, and F in the mesostases at the edges of some chondrules suggest that there were secondary influxes of HVEs into the chondrule mesostases from the surrounding matrix during parent body processes. Consistent with this, melt inclusions sealed in olivine phenocrysts have significantly lower HVE contents than the mesostases in contact with the surrounding matrix material. Further, the calculated diffusion distances of H2O in silicate glasses under the relevant conditions are comparable to the radii of the chondrules. The high δD values in the mesostases could have been generated through isotopic Rayleigh fractionation as a result of the loss of very D-poor H2 generated from Fe metal oxidation by H2O in the parent bodies. Based on these results, we hypothesize that the bulk of the HVEs in the chondrules are secondary in origin. However, a small portion of the HVEs in chondrules could be primary, as there are low but measurable amounts of HVEs in the melt inclusions that are sealed in phenocrysts. Further, measured S contents in some chondrule mesostases agree with those predicted in a sulfide saturated silicate melt based on an experimentally calibrated thermodynamic model. We constrain the upper limits of primary HVEs in the chondrules based on the lowest measured HVE contents to minimize the effects of the secondary influx of HVEs (type I H2O: 7–11 ppm, CO2: 0.3–0.6 ppm, F: 0.1–0.2 ppm, Cl: 0.01–0.03 ppm, S: 0.3–60 ppm, and type II H2O: 50–85 ppm, CO2: 0.4–3 ppm, F: 0.04–2 ppm, Cl: 0.04–2 ppm, S: 190–260 ppm).
Models of Greedy Algorithms for Graph Problems

Borodin et al. (Algorithmica 37(4):295–326, 2003) gave a model of greedy-like algorithms for scheduling problems and Angelopoulos and Borodin (Algorithmica 40(4):271–291, 2004) extended their work to facility location and set cover problems. We generalize their model to include other optimization problems, and apply the generalized framework to graph problems. Our goal is to define an abstract model that captures the intrinsic power and limitations of greedy algorithms for various graph optimization problems, as Borodin et al. (Algorithmica 37(4):295–326, 2003) did for scheduling. We prove bounds on the approximation ratio achievable by such algorithms for basic graph problems such as shortest path, weighted vertex cover, Steiner tree, and independent set. For example, we show that, for the shortest path problem, no algorithm in the FIXED priority model can achieve any approximation ratio (even one dependent on the graph size), but the well-known Dijkstra’s algorithm is an optimal ADAPTIVE priority algorithm. We also prove that the approximation ratio for weighted vertex cover achievable by ADAPTIVE priority algorithms is exactly 2. Here, a new lower bound matches the known upper bounds (Johnson in J. Comput. Syst. Sci. 9(3):256–278, 1974). We give a number of other lower bounds for priority algorithms, as well as a new approximation algorithm for minimum Steiner tree problem with weights in the interval [1,2].
A Statistical Perspective on the Challenges in Molecular Microbial Biology

High throughput sequencing (HTS)-based technology enables identifying and quantifying non-culturable microbial organisms in all environments. Microbial sequences have enhanced our understanding of the human microbiome, the soil and plant environment, and the marine environment. All molecular microbial data pose statistical challenges due to contamination sequences from reagents, batch effects, unequal sampling, and undetected taxa. Technical biases and heteroscedasticity have the strongest effects, but different strains across subjects and environments also make direct differential abundance testing unwieldy. We provide an introduction to a few statistical tools that can overcome some of these difficulties and demonstrate those tools on an example. We show how standard statistical methods, such as simple hierarchical mixture and topic models, can facilitate inferences on latent microbial communities. We also review some nonparametric Bayesian approaches that combine visualization and uncertainty quantification. The intersection of molecular microbial biology and statistics is an exciting new venue. Finally, we list some of the important open problems that would benefit from more careful statistical method development.
Experience-dependent contextual codes in the hippocampus

The hippocampus contains neural representations capable of supporting declarative memory. Hippocampal place cells are one such representation, firing in one or few locations in a given environment. Between environments, place cell firing fields remap (turning on/off or moving to a new location) to provide a population-wide code for distinct contexts. However, the manner by which contextual features combine to drive hippocampal remapping remains a matter of debate. Using large-scale in vivo two-photon intracellular calcium recordings in mice during virtual navigation, we show that remapping in the hippocampal region CA1 is driven by prior experience regarding the frequency of certain contexts and that remapping approximates an optimal estimate of the identity of the current context. A simple associative-learning mechanism reproduces these results. Together, our findings demonstrate that place cell remapping allows an animal to simultaneously identify its physical location and optimally estimate the identity of the environment.
Perturbative calculations of entanglement entropy

This paper is an attempt to extend the recent understanding of the Page curve for evaporating black holes to more general systems coupled to a heat bath. Although calculating the von Neumann entropy by the replica trick is usually a challenge, we have identified two solvable cases. For the initial section of the Page curve, we sum up the perturbation series in the system-bath coupling κ; the most interesting contribution is of order 2s, where s is the number of replicas. For the saturated regime, we consider the effect of an external impulse on the entropy at a later time and relate it to OTOCs. A significant simplification occurs in the maximal chaos case such that the effect may be interpreted in terms of an intermediate object, analogous to the branching surface of a replica wormhole.
U.S. and Canadian College Students’ Fear of Crime: A Comparative Investigation of Fear of Crime and Its Correlates:

Being fearful of crime is, unfortunately, a common experience. Research shows that many factors influence a person's fear of crime, demonstrating that certain groups are generally more fearful than others. Even though they are typically young, college students express being fearful of crime on and off campus. What has yet to be investigated is whether college students who attend school in the United States are fearful at similar levels to their Canadian counterparts. Further, the correlates of fear of crime may also be different. To explore these issues, data from the American College Health Association's National College Health Assessment II survey of U.S. and Canadian college students are used. Results show that Canadian college students generally perceive their safety as being higher than U.S. college students, even though they face elevated victimization risks. Further, some correlates of fear of crime differ for U.S. and Canadian college students. These findings suggest the need for additional cross-national comparative work to see if patterns generalize across contexts.
Modeling of Emotional Influence in Multiagent System.

Emotions are an integral part of human personality. That is why it is necessary to take them into account when modeling human behavior and to implement them appropriately with respect to the given objective. For simulation models, a so-called computational approach based on the emotional appraisal of the stimuli the individual is exposed to is usually used. The selection of criteria for this appraisal is not strictly given, just as the transformation of their values into the emotional space. It depends primarily on the purpose of the model and the environment in which the model exists. This paper describes a specific emotional appraisal setting for the modeling of social structures based on communication between individuals in a multi-agent environment. The experiments present simulations of several scenarios showing the development of selected model parameters over time, as well as the effect of the possible involvement of the emotional appraisal in the simulation of the authentic behavior of individuals in the network.
Generalized Bayes Quantification Learning under Dataset Shift

Quantification learning is the task of prevalence estimation for a test population using predictions from a classifier trained on a different population. Quantification methods assume that the sens...
Imaging approach to COVID-19 Associated Pulmonary Embolism.

The novel coronavirus disease-2019 (COVID-19) illness and deaths, caused by the severe acute respiratory syndrome coronavirus-2, continue to increase. Multiple reports highlight the thromboembolic complications, such as pulmonary embolism (PE), in COVID-19. Imaging plays an essential role in the diagnosis and management of COVID-19 patients with PE. There continues to be a rapid evolution of knowledge related to COVID-19 associated PE. This review summarises the current understanding of prevalence, pathophysiology, role of diagnostic imaging modalities, and management, including catheter-directed therapy for COVID-19 associated PE. It also describes infection control considerations for the radiology department while providing care for patients with COVID-19 associated PE.
SCENTinel 1.0: development of a rapid test to screen for smell loss.

Commercially available smell tests are primarily used in research or in-depth clinical evaluations and are too costly and time-consuming for population surveillance in health emergencies like COVID-19. To address this need, we developed the SCENTinel 1.0 test, which rapidly evaluates three olfactory functions: detection, intensity, and identification. We tested whether self-administering the SCENTinel 1.0 test discriminates between individuals with self-reported smell loss and those with average smell ability (normosmic individuals) and provides performance comparable to the validated and standardized NIH Toolbox ® Odor Identification Test in normosmic individuals. Using Bayesian linear models and prognostic classification algorithms, we compared the SCENTinel 1.0 performance of a group of self-reported anosmic individuals (N=111, 47±13yo, F=71%) and normosmic individuals (N=154, 47±14yo, F=74%), as well as individuals reporting other smell disorders (such as hyposmia or parosmia; N=42, 55±10yo, F=67%). Ninety-four percent of normosmic individuals met our SCENTinel 1.0 accuracy criteria, compared to only 10% of anosmic individuals and 64% of individuals with other smell disorders. Overall performance on SCENTinel 1.0 predicted belonging to the normosmic group better than identification or detection alone (vs anosmic: AUC=0.95,specificity=0.94). Odor intensity provided the best single-feature predictor to classify normosmic individuals. Among normosmic individuals, 92% met the accuracy criteria at both SCENTinel 1.0 and the NIH Toolbox ® Odor Identification Test. SCENTinel 1.0 is a practical test able to discriminate individuals with smell loss and will likely be useful in many clinical situations, including COVID-19 symptom screening.
Distance Education: Better, Worse, Or As Good As Traditional Education?

This study examined pre-test and post-test scores, homework grades, research paper grades, final exam scores, final course grades, learning styles, and ages of distance education and traditional students enrolled in a business communications class to determine if distance education is better, worse, or as good as traditional education. Significant differences were found for post-test scores, final exam scores, and age. There were no significant differences in pre-test scores, homework grades, research paper grades, and final course grades. Both groups preferred clearly organized coursework and performing at an above-average level--ranking in the top 25 to 33% of their class. Recommendations for research include investigating student social interaction and increasing the number of classes studied to compare results.
Common Denominator for Value and Expectation No-go Theorems: Extended Abstract

Hidden-variable (HV) theories allege that a quantum state describes an ensemble of systems distinguished by the values of hidden variables. No-go theorems assert that HV theories cannot match the predictions of quantum theory. The present work started with repairing flaws in the literature on no-go theorems asserting that HV theories cannot predict the expectation values of measurements. That literature gives one an impression that expectation no-go theorems subsume the time-honored no-go theorems asserting that HV theories cannot predict the possible values of measurements. But the two approaches speak about different kinds of measurement. This hinders comparing them to each other. Only projection measurements are common to both. Here, we sharpen the results of both approaches so that only projection measurements are used. This allows us to clarify the similarities and differences between the two approaches. Neither one dominates the other.
Sentencing the Why of White Collar Crime

“So why did Mr. Gupta do it?” That question was at the heart of Judge Jed Rakoff’s recent sentencing of Rajat Gupta, a former Wall Street titan and the most high-profile insider-trading defendant of the past thirty years. The answer, which the court actively sought by inquiring into Gupta’s psychological motivations, resulted in a two-year sentence, eight years less than the government requested. What was it that Judge Rakoff found in Gupta that warranted such a lenient sentence? While it was ultimately unclear to the court exactly what motivated Gupta to commit such a “terrible breach of trust,” it is exceedingly clear that Judge Rakoff’s search for those motivations impacted the sentence imposed. This search by judges sentencing white collar defendants—the search to understand the “why” motivating defendants’ actions—is what this Article explores. When judges inquire into defendants’ motivations, they necessarily delve into the psychological mechanisms defendants employ to free themselves from the social norms they previously followed, thereby allowing themselves to engage in criminality. These “techniques of neutralization” are precursors to white collar crime, and they impact courts’ sentencing decisions. Yet the role of neutralizations in sentencing has been largely unexamined. This Article rectifies that absence by drawing on established criminological theory and applying it to three recent high-profile white collar cases. Ultimately, this Article concludes that judges’ search for the “why” of white collar crime, which occurs primarily through the exploration of offender neutralizations, is legally and normatively justified. While there are significant potential drawbacks to judges conducting these inquiries, they are outweighed by the benefits of increased individualized sentencing and opportunities to disrupt the mechanisms that make white collar crime possible.
Surface defects in holographic 5d SCFTs

We use holography to study codimension-2 surface defects in 5d SCFTs engineered by (p, q) 5-brane webs. The three-dimensional defects are realized by D3-branes ending on the brane web. We identify the holographic representation of the defects in Type IIB AdS6 solutions as probe D3-branes, and study conformal and non-conformal defects which, respectively, preserve one half and one quarter of the supersymmetry. For a sample of 5d SCFTs, including the TN theories, we provide explicit solutions for conformal and non-conformal defects. For the conformal defects we obtain their contribution to the free energy on S5.
Structural variation affecting DNA backbone interactions underlies adaptation of B3 DNA binding domains to constraints imposed by protein architecture

Functional and architectural diversification of transcription factor families has played a central role in the independent evolution of complex development in plants and animals. Here, we investigate the role of architectural constraints on evolution of B3 DNA binding domains that regulate plant embryogenesis. B3 domains of ABI3, FUS3, LEC2 and VAL1 proteins recognize the same cis-element. Complex architectures of ABI3 and VAL1 integrate cis-element recognition with other signals, whereas LEC2 and FUS3 have reduced architectures conducive to roles as pioneer activators. In yeast and plant in vivo assays, B3 domain functions correlate with architectural complexity of the parent transcription factor rather than phylogenetic relatedness. In a complex architecture, attenuated ABI3-B3 and VAL1-B3 activities enable integration of cis-element recognition with hormone signaling, whereas hyper-active LEC2-B3 and FUS3-B3 over-ride hormonal control. Three clade-specific amino acid substitutions (β4-triad) implicated in interactions with the DNA backbone account for divergence of LEC2-B3 and ABI3-B3. We find a striking correlation between differences in in vitro DNA binding affinity and in vivo activities of B3 domains in plants and yeast. Our results highlight the role of DNA backbone interactions that preserve DNA sequence specificity in adaptation of B3 domains to functional constraints associated with domain architecture.
Investigating the Relationship between Freeway Rear-end Crash Rates and Macroscopically Modelled Reaction Time

This study tests the hypothesis that an analytically estimated driver reaction time required for asymptotic stability, based on the macroscopic Gazis-Herman-Rothery (GHR) model, serves as an indica...
De Morgan clones and four-valued logics

We study clones on a four-element set related to the clone $${\mathsf {DMA}}$$ of all term functions of the subdirectly irreducible four-element De Morgan algebra $${\mathbf {DM}}_{{{\mathbf {4}}}}$$ . We find generating sets for the clones of all functions preserving the subalgebras of $${\mathbf {DM}}_{{{\mathbf {4}}}}$$ , the automorphisms of $${\mathbf {DM}}_{{{\mathbf {4}}}}$$ , the truth order and the information order on $${\mathbf {DM}}_{{{\mathbf {4}}}}$$ , as well as clones defined by conjunctions of these conditions. We identify the covers of $${\mathsf {DMA}}$$ in the lattice of four-valued clones and describe the lattice of clones above $${\mathsf {DMA}}$$ which contain the discriminator function. Finally, observing that each clone above $${\mathsf {DMA}}$$ defines an expansion of the four-valued Belnap–Dunn logic, we classify these clones by their metalogical properties, specifically by their position within the Leibniz and Frege hierarchies of abstract algebraic logic.
Parallel Software to Offset the Cost of Higher Precision

Hardware double precision is often insufficient to solve large scientific problems accurately. Computing in higher precision defined by software causes significant computational overhead. The application of parallel algorithms compensates for this overhead. Newton's method to develop power series expansions of algebraic space curves is the use case for this application.
Rosette Harmonic Mappings

A harmonic mapping is a univalent harmonic function of one complex variable. We define a family of harmonic mappings on the unit disk whose images are rotationally symmetric “rosettes” with n cusps or n nodes, $$n\ge 3$$ . These mappings are analogous to the n-cusped hypocycloid, but are modified by Gauss hypergeometric factors, both in the analytic and co-analytic parts. Relative rotations by an angle $$\beta $$ of the analytic and anti-analytic parts lead to graphs that have cyclic, and in some cases dihedral symmetry of order n. While the graphs for different $$\beta $$ can be dissimilar, the cusps are aligned along axes that are independent of $$\beta $$ . For certain isolated values of $$\beta $$ , the boundary function is continuous with arcs of constancy, and has nodes of interior angle $$\pi /2-\pi /n$$ instead of cusps.
Population and comparative genetics of thermotolerance divergence between yeast species.

Many familiar traits in the natural world-from lions' manes to the longevity of bristlecone pine trees-arose in the distant past, and have long since fixed in their respective species. A key challenge in evolutionary genetics is to figure out how and why species-defining traits have come to be. We used the thermotolerance growth advantage of the yeast Saccharomyces cerevisiae over its sister species Saccharomyces paradoxus as a model for addressing these questions. Analyzing loci at which the S. cerevisiae allele promotes thermotolerance, we detected robust evidence for positive selection, including amino acid divergence between the species and conservation within S. cerevisiae populations. Since such signatures were particularly strong at the chromosome segregation gene ESP1, we used this locus as a case study for focused mechanistic follow-up. Experiments revealed that, in culture at high temperature, the S. paradoxus ESP1 allele conferred a qualitative defect in biomass accumulation and cell division relative to the S. cerevisiae allele. Only genetic divergence in the ESP1 coding region mattered phenotypically, with no functional impact detectable from the promoter. Together, these data support a model in which an ancient ancestor of S. cerevisiae, under selection to boost viability at high temperature, acquired amino acid variants at ESP1 and many other loci, which have been constrained since then. Complex adaptations of this type hold promise as a paradigm for interspecies genetics, especially in deeply diverged traits that may have taken millions of years to evolve.
“Seemingly‐Beneficial” Interventions

Organizations routinely introduce hitherto‐unexplored interventions to improve their supply chains. Consider a principal (e.g., a firm) that implements a “seemingly helpful” intervention: For any fixed actions of the principal and the agents (e.g., consumers), the principal's payoff is higher in the presence of the intervention than in its absence. While one would expect such well‐intentioned interventions to benefit the principal, several papers within the operations management (OM) literature show that the principal's equilibrium payoff can be hurt, even ignoring the intervention's implementation cost. While this conclusion is often based on analyzing a single‐shot, simultaneous‐move game, repeated interactions can also serve as an appropriate environment in many cases. A fundamental question arises: Does this conclusion hold even under repeated interactions? We study this question using the framework of infinitely repeated games and the notion of a precommitment equilibrium from the literature on reputation in repeated games. We identify two key characteristics that determine whether a seemingly beneficial intervention helps, or can possibly hurt the firm: (i) nature of the intervention (ceteris paribus, does it induce agents to react in a manner favorable to the principal?), and (ii) extent of interaction (single shot at one extreme and infinitely repeated at the other). Interestingly, we demonstrate the following two possibilities using settings analyzed in the recent OM literature: seemingly beneficial interventions can (a) hurt the firm in a single‐shot analysis but benefit under repeated interactions, and (b) continue to hurt the firm under repeated interactions. We also obtain easy‐to‐interpret conditions under which the benefit of such interventions is guaranteed under repeated interactions.
High-dimensional regimes of non-stationary Gaussian correlated Wishart matrices

We study the high-dimensional asymptotic regimes of correlated Wishart matrices d−1&#x1d4b4;&#x1d4b4;T, where &#x1d4b4; is a n × d Gaussian random matrix with correlated and non-stationary entries. We prove that under dif...
Investor Taxes and Option Prices

We examine whether tax-sensitive investors play a significant role in options markets by examining whether option prices reflect investor taxes. Existing empirical option pricing literature ignores taxes. We exploit a unique setting where “index” options on the S&P 500 Index (SPX) and nearly identical “non-index” options on the exchange traded fund (ETF) tracking the S&P 500 Index (SPY) face different tax treatments. We find that higher investor taxes reduce option prices, indicating tax capitalization in options. We find consistent results when analyzing options around the investor tax changes enacted by the American Taxpayer Relief Act (ATRA) of 2012, and for options on stock indices other than the S&P 500 (e.g., Russell 2000). Altogether, our findings provide new evidence of an additional item – investor taxes – influencing option prices, suggesting that tax-sensitive investors play a non-trivial role in options markets and that taxes warrant consideration in broader options research.
The randomized communication complexity of randomized auctions

We study the communication complexity of incentive compatible auction-protocols between a monopolist seller and a single buyer with a combinatorial valuation function over n items. Motivated by the fact that revenue-optimal auctions are randomized (as well as by an open problem of Babaioff, Gonczarowski, and Nisan), we focus on the randomized communication complexity of this problem (in contrast to most prior work on deterministic communication). We design simple, incentive compatible, and revenue-optimal auction-protocols whose expected communication complexity is much (in fact infinitely) more efficient than their deterministic counterparts. We also give nearly matching lower bounds on the expected communication complexity of approximately-revenue-optimal auctions. These results follow from a simple characterization of incentive compatible auction-protocols that allows us to prove lower bounds against randomized auction-protocols. In particular, our lower bounds give the first approximation-resistant, exponential separation between communication complexity of incentivizing vs implementing a Bayesian incentive compatible social choice rule, settling an open question of Fadel and Segal.
Modular Networks for Compositional Instruction Following.

Standard architectures used in instruction following often struggle on novel compositions of subgoals (e.g. navigating to landmarks or picking up objects) observed during training. We propose a modular architecture for following natural language instructions that describe sequences of diverse subgoals. In our approach, subgoal modules each carry out natural language instructions for a specific subgoal type. A sequence of modules to execute is chosen by learning to segment the instructions and predicting a subgoal type for each segment. When compared to standard, non-modular sequence-to-sequence approaches on ALFRED, a challenging instruction following benchmark, we find that modularization improves generalization to novel subgoal compositions, as well as to environments unseen in training.
Validation of HD 183579b Using Archival Radial Velocities: A Warm Neptune Orbiting a Bright Solar Analog

As exoplanetary science matures into its third decade, we are increasingly offered the possibility of pre existing, archival observations for newly detected candidates. This is particularly poignant for the TESS mission, whose survey spans bright, nearby dwarf stars in both hemispheres, which are precisely the types of sources targeted by previous radial velocity (RV) surveys. On this basis, we investigated whether any of the TESS Objects of Interest (TOIs) coincided with such observations, from which we find 18 single planet candidate systems. Of these, one exhibits an RV signature that has the correct period and phase matching the transiting planetary candidate with a false alarm probability of less than 1 percent. After further checks, we exploit this fact to validate HD 183579b (TOI-1055b). This planet is less than 4 Earth Radii and has better than 33 percent planetary mass measurements, thus advancing the TESS primary objective of finding 50 such worlds. We find that this planet is amongst the most accessible small transiting planets for atmospheric characterization. Our work highlights that the efforts to confirm and even precisely measure the masses of new transiting planet candidates need not always depend on acquiring new observations - that in some instances these tasks can be completed with existing data.
Information Projection on Banach Spaces with Applications to State Independent KL-Weighted Optimal Control

This paper studies constrained information projections on Banach spaces with respect to a Gaussian reference measure. Specifically our interest lies in characterizing projections of the reference measure, with respect to the KL-divergence, onto sets of measures corresponding to changes in the mean (or shift measures). As our main result, we give a portmanteau theorem that characterizes the relationship among several different formulations of this problem. In the general setting of Gaussian measures on a Banach space, we show that this information projection problem is equivalent to minimization of a certain Onsager–Machlup (OM) function with respect to an associated stochastic process. We then construct several reformulations in the more specific setting of classical Wiener space. First, we show that KL-weighted optimization over shift measures can also be expressed in terms of an OM function for an associated stochastic process that we are able to characterize. Next, we show how to encode the feasible set of shift measures through an explicit functional constraint by constructing an appropriate penalty function. Finally, we express our information projection problem as a calculus of variations problem, which suggests a solution procedure via the Euler–Lagrange equation. We work out the details of these reformulations for several specific examples.