cssi/SciSciGPT-SciSciNet huggingface dataset:
Liability for Unconscious Discrimination? A Thought Experiment in the Theory of Employment Discrimination Law

Recent scholarship in employment discrimination law has wrestled with the problem of unconscious bias and its implications for antidiscrimination law. This Article addresses what some might regard as a naive question: Should actions influenced by unconscious bias be regarded as discrimination under Title VII? The question might be considered naive because any proposal for liability based on unconscious bias would surely be unripe for present implementation, and because there is no accepted method either for detecting such bias in individual cases, or for determining whether such bias actually influenced a person’s decisionmaking. But these practical considerations provide no answer to the fundamental issue that underlies the question. Does unconsciously biased action fall within the legal concept of actionable discrimination? To reach that important issue, I devise a thought experiment that brackets practical problems of proof and squarely raises what I regard as the hard question for theorizing about unconscious discrimination. Should an employment action give rise to liability when that action was provably affected by the actor’s unconscious bias with respect to a statutorily protected classification, even when the actor consciously acted only on legitimate, nondiscriminatory reasons? The payoff of the thought experiment is not only a clearer picture of the theoretical commitments entailed by liability based on unconscious bias, but also a keener understanding of our currently prevailing notions of actionable discrimination.
Bank Capital Regulation and Structured Finance

We construct a model in which bank capital regulation and financial innovation interact. Innovation takes the form of pooling and tranching of assets and the creation of separate structures with different seniority, different risk, and different capital charges, a process that captures some stylized features of structured finance. Regulation is motivated by the divergence of private and social interests in future profits. Capital regulation lowers bank profits and may induce banks to innovate in order to evade the regulation itself. We show that structured finance can improve welfare in some cases. However, innovation may also be adopted to avoid regulation, even in cases where it decreases welfare.
Optimization of Convex Risk Functions

We consider optimization problems involving convex risk functions. By employing techniques of convex analysis and optimization theory in vector spaces of measurable functions, we develop new representation theorems for risk models, and optimality and duality theory for problems with convex risk functions.
Program Evaluation as a Decision Problem

I argue for thinking of program evaluation as a decision problem. There are two steps. First, a counselor determines which program (treatment or control) each individual joins, based for example on maximizing the probability of employment or expected earnings. Second, the policymaker decides whether: to assign all individuals to treatment or to control, or to allow the counselor to choose. This framework has two advantages. Individualized assignment rules (known as profiling) can raise the average impact, improving cost effectiveness by exploiting treatment-impact heterogeneity. Second, it accounts systematically for inequality and uncertainty, and the policymaker's attitude toward these, in the evaluation.
Investment frictions and leverage dynamics

Abstract The paper examines the effect of investment frictions on leverage dynamics, using a model of a firm whose investment projects are (1) indivisible and lumpy, and (2) subject to time-to-build. Regressions on the model-simulated data demonstrate that investment frictions can provide alternative interpretations of the observed leverages shown in the empirical literature. Cross-sectional analysis of firms in the oil and gas extraction industries, as well as analysis across all industries, reveals the evidence that small firms have more volatile investments and longer time-to-build, which may explain the observed differences in leverage dynamics across small and large firms.
The instantiation thesis and Raz's critique of inclusive positivism

Inclusive positivists subscribe to the Incorporation Thesis, according to which it is conceptually possible for a legal system to have a rule of recognition that incorporates moral norms. Joseph Raz counters that inclusive positivism is inconsistent with the nature of authority. This influential critique depends on a number of controversial theses about the nature of authority and legal systems. Most conspicuous among these are the Authority Thesis, which asserts that every conceptually possible legal system claims authority, and the Preemption Thesis, which asserts that authority figures (or ought to figure) into practical deliberations by replacing the subject's evaluation of the balance of reasons. In this essay, I challenge an underlying assumption of the Razian critique also depends on a thesis that has gone largely unchallenged in the literature: according to the Instantiation Thesis, law cannot sincerely claim authority unless it is capable of instantiating authority. I argue that this seemingly plausible thesis is false, in part, because there is widespread disagreement among legal officials about what authority is.
The International Criminal Court’s Gravity Jurisprudence at Ten

This Essay, prepared for a symposium on “The International Criminal Court at Ten,” analyzes the ICC’s early jurisprudence on the gravity threshold for admissibility in Article 17 of the Rome Statute. It argues that the threshold, while useful in garnering support for ratification of the Rome Statute, now seems destined to play a minor role in determining the ICC’s reach. While there are multiple possible explanations for this development, an important doctrinal cause identified in the jurisprudence is that the gravity threshold for admissibility is in tension with the Rome Statute’s provisions regarding jurisdiction. At least with regard to the admissibility of cases (as opposed to “situations”), the judges have concluded that interpreting the gravity threshold to exclude certain types of defendants or crimes from the Court’s reach would amount to an impermissible revision of the Court’s jurisdiction. To avoid this outcome, the judges have developed a flexible multi-factor approach to the gravity threshold that enables them to justify admitting virtually any case within the Court’s jurisdiction. The Essay concludes by arguing that, in light of the tension between admissibility and jurisdiction, the judges are right to relegate the gravity threshold to a minor role in determining the cases the Court adjudicates. To the extent the judges seek to limit the ICC’s reach, they should do so by interpreting the Court’s jurisdictional provisions directly rather than through the back door of admissibility.
Failure to Launch: Housing, Debt Overhang, and the Inflation Option During the Great Recession

Can inflating away nominal mortgage liabilities cure debt overhang and combat a severe housing bust? With a focus on the Great Recession, I address this question using a structural macroeconomic model of illiquid housing, endogenous credit supply, and equilibrium default. First, I show that the model successfully replicates and provides insight into the dynamics of the U.S. economy since 2006. Second, I show that temporarily raising the inflation target would have cut foreclosures by over 60% and led to a more robust recovery in real economic variables. Price-level targeting that promises to offset this temporary inflation with future disinflation has more modest positive effects. In short, forward guidance matters. Higher inflation loses its potency in the counterfactual where all homeowners have adjustable rate mortgages, which highlights the importance of nominal rigidities for the e?ectiveness of these policies. Lastly, inflation proves effective even if wages exhibit substantial nominal stickiness.
Abuse of Power and Corruption in Kenya: Will the New Constitution Enhance Government Accountability

This article suggests that corruption in the Kenyan government is largely an institutional problem, rather than a cultural one. It attributes such corruption to the predominance of arbitrary power, especially in the statutory (as opposed to constitutional) order. The statutory order grants executive, legislative, and judicial actors broad powers without establishing effective procedural mechanisms to circumscribe their exercise. In the absence of effective regulation, law often aids the abuse of power and corruption. Although the new constitution establishes principles and mechanisms that may enhance government accountability, the statutory order must be aligned with the values and principles of this new constitution if abuse of power and corruption are to be curbed.
Breakthrough Inventions and Migrating Clusters of Innovation

Abstract We investigate the speed at which clusters of invention for a technology migrate spatially following breakthrough inventions. We identify breakthrough inventions as the top 1% of US inventions for a technology during 1975–1984 in terms of subsequent citations. Patenting growth is significantly higher in cities and technologies where breakthrough inventions occur after 1984 relative to peer locations that do not experience breakthrough inventions. This growth differential in turn depends on the mobility of the technology’s labor force, which we model through the extent that technologies depend upon immigrant scientists and engineers. Spatial adjustments are faster for technologies that depend heavily on immigrant inventors. The results qualitatively confirm the mechanism of industry migration proposed in models like Duranton [Duranton, G., 2007. Urban evolutions: The fast, the slow, and the still. American Economic Review 97, 197–221].
Historical Accounting and the Endogenous Credibility of Current Disclosures

This paper examines how historical financial reporting can serve as an ex post check on more timely voluntary disclosures, and shows that such a check can be sufficient to ensure that the voluntary disclosures are credible most of the time. The model describes an adverse selection setting where an informed seller communicates with an uninformed buyer over time, but there is no exogenous means of making the seller's communication credible. The addition of an ex post report enables the buyer to assess the accuracy of the seller's prior communications and gives the buyer a means to punish a seller who has disclosed falsely in the past. Under certain conditions, this threat of punishment keeps the seller honest in the present most of the time. The model provides a formal means of evaluating the Lundholm (1999) proposal that accounting regulation should turn its attention to supporting credible voluntary disclosures by reporting on the accuracy of past estimates.
The twist for positroid varieties

The purpose of this document is to connect two maps related to certain graphs embedded in the disc. The first is Postnikov's boundary measurement map, which combines partition functions of matchings in the graph into a map from an algebraic torus to an open positroid variety in a Grassmannian. The second is a rational map from the open positroid variety to an algebraic torus, given by certain Plucker coordinates which are expected to be a cluster in a cluster structure. This paper clarifies the relationship between these two maps, which has been ambiguous since they were introduced by Postnikov in 2001. The missing ingredient supplied by this paper is a twist automorphism of the open positroid variety, which takes the target of the boundary measurement map to the domain of the (conjectural) cluster. Among other applications, this provides an inverse to the boundary measurement map, as well as Laurent formulas for twists of Plucker coordinates.
Gartner's hype cycle and information system research issues ☆

Abstract This paper uses Gartner Group's hype cycle as a basis to analyze research issues and opportunities in information systems. The findings including, “where” we find a technology in the hype cycle can influence the kinds of research questions we can ask, the information available about that technology and the research methods that can be employed on the technology at that stage.
Explaining Corporate Capital Structure: Product Markets, Leases, and Asset Similarity

Better measurement of the output produced and capital employed by firms substantially improves the ability to explain capital structure variation in the cross section. For every firm, we construct the set of other firms producing the same output using the set of product market competitors listed in the firm's public Securities and Exchange Commission filings. In addition, we improve measurement of capital structure by explicitly accounting for leased capital. These two steps increase the explanatory power of the average capital structure of other firms producing similar output on a firm's capital structure by 50% compared to using only the average unadjusted debt ratio of other firms in the same three-digit Standard Industrial Classification (SIC) code. We provide evidence that the large explanatory power of the capital structure of other firms producing similar output is related to the assets used in the production process. Our findings suggest that what a firm produces and the assets used in production are the most important determinants of capital structure in the cross section. Copyright 2011, Oxford University Press.
The Role of Taxes in the Disconnect Between Corporate Performance and Economic Growth

We investigate the relation between corporate performance and overall economic growth in the United States. In particular, we focus on the impact of the U.S. corporate tax regime on this relation. ...
A random matching theory

We develop theoretical underpinnings of pairwise random matching processes. We formalize the mechanics of matching, and study the links between properties of the different processes and trade frictions. A particular emphasis is placed on providing a mapping between matching technologies and informational constraints.
Bringing It Home: A Study of the Incentives Surrounding the Repatriation of Foreign Earnings Under the American Jobs Creation Act of 2004

The American Jobs Creation Act of 2004 (the Act) creates a temporary tax holiday that effectively reduces the U.S. tax rate on repatriations from foreign subsidiaries from 35% to 5.25%. Firms receive the reduced tax rate by electing to take an 85% dividends received deduction on repatriations in 2004 or 2005. This paper investigates the characteristics of firms that repatriate under the Act and how they use the repatriated funds. We find that firms that repatriate under the Act have lower investment opportunities and higher free cash flows than nonrepatriating firms. Further, we find that repatriating firms increase share repurchases during 2005 by approximately $60 billion more than nonrepatriating firms, an amount that cannot be explained by differences in earnings between the two groups of firms. This increase represents about 20% of the $291.6 billion repatriated by our sample firms under the Act.
Signal vs. Noise: Some Comments on Professor Stein's Theory of Evidential Efficiency

In this Essay, I examine Professor Stein's intriguing new theory of evidential efficiency, which posits that judges should admit evidence whenever it has a sufficiently high "signal-to-noise ratio." I explore a slightly different definition of the concepts of "signal" and "noise" than Stein, based upon likelihood ratio values rather than the underlying probabilities of events, and I explain why these altered concepts may be analytically superior. Additionally, I call into question the strength of the connection between the signal-to-noise ratio of a piece of evidence and the costs of admitting it at trial. Nevertheless, Stein's project is worthy of great praise because it focuses our attention on the fact that evidentiary rules have many costs beyond their direct contributions to outcome accuracy. Failing to consider these costs does great harm to individual litigants, the justice system, and society at large. ABSTRACT 471 47
Mutual funds as monitors: Evidence from mutual fund voting

Abstract We address how mutual funds vote on shareholder proposals and identify factors that help determine support of wealth-increasing shareholder proposals. We examine 213,579 voting decisions made by 1799 mutual funds from 94 fund families for 1047 shareholder proposals voted on between July 2003 and June 2005. In an analysis of voting across funds within the same fund family, we find significant divergence in voting within families, emphasizing the importance of focusing on voting by individual funds. We also find that, in general, mutual funds vote more affirmatively for potentially wealth-increasing proposals and funds' voting approval rates for these beneficial resolutions are significantly higher than those of other investors. Our results suggest that funds tend to support proposals targeting firms with weaker governance. We also find that funds with lower turnover ratios and social funds are more likely to support shareholder proposals. Finally, fund voting approval rates significantly impact whether a proposal passes and whether one is implemented.
Catch 7(A): The Plaintiff's Burden under the Freedom of Information Act

The Freedom of Information Act (FOIA) mandates full agency disclosure of government records unless they fall within nine specific statutory exemptions. In enacting the FOIA, Congress recognized that agency compliance with its mandate depended upon the availability and effectiveness of external monitoring and enforcement. The FOIA is therefore structured in a manner that affords plaintiffs speedy and proximate access to judicial review of agency decisions against disclosure. Prompt judicial scrutiny has been facilitated by liberal venue provisions, a 30 day answering period for responding to a complaint, and docketing priority for FOIA cases. In addition, litigation to obtain disclosure of records is encouraged by provisions allowing a court to assess costs and attorney's fees against the United States.
Dirty Hands or Deterrence? An Experimental Examination of the Exclusionary Rule

Historically, the Supreme Court has offered two justifications for the exclusionary rule: (1) it protects the integrity of the judicial system from “dirty” evidence and (2) it deters illegal searches by the police. The former justification has mostly fallen out of favor. Today, decisions turn on whether the rule would, in fact, deter illegal searches in a given class of cases. As such, most empirical studies about the rule have focused on whether or not the rule leads to fewer police searches (illegal or otherwise), or to fewer criminal convictions. This study takes a completely different approach, assessing support for the two competing justifications for the rule. Two experiments show support for the integrity justification for the rule, but not for the deterrence justification. Specifically, when deciding whether to exclude evidence found during a search conducted without probable cause, participants are sensitive to a police officer's motive (clean vs. dirty), but not to alternative means of punishing those officers (civil suit, citizen-police review board). A third experiment examines the integrity rationale in more detail. Participants who were obligated to use dirty evidence at trial disproportionately selected a bottle of Purell over a pen as a thank-you gift versus participants who were able to exclude that evidence. In other words, the exclusionary rule seems to protect the courts from being metaphorically tainted. These findings are important given that the rule is not constitutionally mandated. The Supreme Court has held that the rule can be ignored to the extent that it (1) does not achieve its goals and (2) undermines the perceived legitimacy of the courts by the public. Given this, the Court needs to be right about what those goals are, and whether or not its current deterrence-based jurisprudence enhances legitimacy. These experiments suggest the possibility that reinvigorating the integrity justification would serve the ends of the rule better than current doctrine does.
Convex analysis in financial mathematics

Abstract Using the language of convex analysis, we describe key results in several important areas of finance: portfolio theory, financial derivative trading and pricing and consumption based asset pricing theory. We hope to emphasize the importance of convex analysis in financial mathematics and also draw the attention of researchers in convex analysis to interesting issues in financial applications.
Premise-based versus outcome-based information aggregation

Abstract A group of rational individuals with common interest need to select one of two outcomes. The optimal decision depends on whether certain premises or pieces of evidence are established as being true, and each member receives a noisy signal of the truth value of the relevant premises. Should the group reach a decision by voting whether each premise is true or false, or should they simply vote on the outcome? We show that for any finite number of individuals, the premise-based voting rule is more efficient in aggregating information than the outcome-based rule. However, generically, the gain from using the premise-based over the outcome-based rule can only be marginal when numerous individuals express independent opinions. Indeed, the outcome-based game is almost always asymptotically efficient.
An Economical Business-Cycle Model

In recent decades, advanced economies have experienced low and stable inflation and long periods of liquidity trap. We construct an alternative business-cycle model capturing these two features by adding two assumptions to a money-in-the-utility-function model: the labor market is subject to matching frictions, and real wealth enters the utility function. These assumptions modify the two core equations of the standard New Keynesian model. With matching frictions, we can analyze equilibria in which inflation is fixed and not determined by a forward-looking Phillips curve. With wealth in the utility, the Euler equation is modified and we can obtain steady-state equilibria with a liquidity trap, positive inflation, and labor market slack. The model is simple enough to inspect the mechanisms behind cyclical fluctuations and to study the effects of conventional and unconventional monetary and fiscal policies. As a byproduct, the model provides microfoundations for the classical IS-LM model. Finally, we show how directed search can be combined with costly price adjustments to generate a forward-looking Phillips curve and recover some insights from the New Keynesian model.
Do Incumbents Improve Service Quality in Response to Entry? Evidence from Airlines' On-Time Performance

We examine if and how incumbent firms respond to entry and entry threats using nonprice modes of competition. Our analysis focuses on airline service quality. We find that incumbent on-time performance OTP actually worsens in response to entry, and even entry threats, by Southwest Airlines. Since Southwest is both a top-performing airline in OTP and a low-cost carrier LCC, we conjecture that this response by incumbents may be due to a cost-cutting strategy that allows for intense postentry price competition along with preentry deterrence, or it may be due to a postentry differentiation strategy along with preentry accommodation. Further analysis of entry and entry threats by other airlines is inconclusive, providing evidence that is partially consistent with both hypotheses. Nonetheless, the phenomenon of worsening OTP can only be observed when the potential entrant is a LCC Southwest, Jet Blue, and AirTran. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1918 . This paper was accepted by by Bruno Cassiman, business strategy.
Revisiting external validity: Concerns about trolley problems and other sacrificial dilemmas in moral psychology.

Sacrificial dilemmas, especially trolley problems, have rapidly become the most recognizable scientific exemplars of moral situations; they are now a familiar part of the psychological literature and are featured prominently in textbooks and the popular press. We are concerned that studies of sacrificial dilemmas may lack experimental, mundane, and psychological realism and therefore suffer from low external validity. Our apprehensions stem from three observations about trolley problems and other similar sacrificial dilemmas: (i) they are amusing rather than sobering, (ii) they are unrealistic and unrepresentative of the moral situations people encounter in the real world, and (iii) they do not elicit the same psychological processes as other moral situations. We believe it would be prudent to use more externally valid stimuli when testing descriptive theories that aim to provide comprehensive accounts of moral judgment and behavior.
Identifying Conditional Conservatism in Financial Accounting Data: Theory and Evidence

ABSTRACT: Using a financial reporting and valuation model, we investigate the construct validity of Basu's (1997) asymmetric timeliness (AT) regression coefficient as a measure of conditional conse...
Foreign Currency Exposure of Multinational Firms: Accounting Measures and Market Valuation*

Abstract. The accounting method in Statement of Financial Accounting Standards (SFAS) No. 8 for restatement of a foreign operation's financial statements denominated in a foreign currency into the parent's currency equivalents for inclusion in the parent company's financial statements was severely criticized by market participants and managers. Its replacement, SFAS No. 52, represented an attempt to improve on the methods of SFAS No. 8. This study examines two questions: did SFAS No. 8 produce relevant information for valuing US multinational firms, and are the results reported under SFAS No. 52 more valuation relevant than those reported under SFAS No. 8? Valuation relevance is studied because the Financial Accounting Standards Board (FASB) has stated that relevance is an important criterion for choosing among alternative accounting methods. Considered collectively, the results suggest that the rules in SFAS No. 8 produced a poor accounting measure for valuing US multinational firms, and that the introduction of SFAS No. 52 has resulted in a significant improvement in the valuation relevance of the accounting numbers associated with the restatement of a foreign operation's financial statements. However, this improvement applies only to the subset of firms that designated a foreign currency as their functional currency (i.e., switched to the current-rate method) and not to firms that designated the dollar as their functional currency (i.e., as if they still reported under SFAS No. 8).
When do central bank interventions influence intra-daily and longer-term exchange rate movements?

This paper examines dollar interventions by the G3 since 1989, and the reasons that trader reactions to these interventions might differ over time and across central banks. Market microstructure theory provides a framework for understanding the process by which sterilized central bank interventions are observed and interpreted by traders, and how this process, in turn, might influence exchange rates. Using intra-daily and daily exchange rate and intervention data, the paper analyzes the influence of interventions on exchange rate volatility, finding evidence of both within day and daily impact effects, but little evidence that interventions influence longer-term volatility.
Mesothelial Cell-Derived Antigen-Presenting Cancer-Associated Fibroblasts Induce Expansion of Regulatory T Cells in Pancreatic Cancer

Multiple recent single cell RNA sequencing (scRNA-seq) studies have identified a unique cancer-associated fibroblast (CAF) population in pancreatic ductal adenocarcinoma (PDA) called antigen-presenting CAFs (apCAFs). apCAFs are characterized by the expression of MHC II molecules, suggesting a function in regulating tumor immunity. Here we integrated multiple scRNA-seq studies and found that apCAFs are derived from mesothelial cells. Our data show that during PDA progression, mesothelial cells form apCAFs by down-regulating mesothelial features and gaining the fibroblastic features, a process induced by IL-1 and TGFβ. Moreover, apCAFs directly ligate and induce naive CD4+ T cells into regulatory T cells (Tregs) in an antigen-specific manner. Our study elucidates an important but neglected cell type in the regulation of PDA immunity and may lead to targeted therapeutic strategies that can overcome immune evasion in PDA.
Intensity-Based Feature Selection for Near Real-Time Damage Diagnosis of Building Structures

Near real-time damage diagnosis of building structures after extreme events (e.g., earthquakes) is of great importance in structural health monitoring. Unlike conventional methods that are usually time-consuming and require human expertise, pattern recognition algorithms have the potential to interpret sensor recordings as soon as this information is available. This paper proposes a robust framework to build a damage prediction model for building structures. Support vector machines are used to predict the existence as well as the probable location of the damage. The model is designed to consider probabilistic approaches in determining hazard intensity given the existing attenuation models in performance-based earthquake engineering. Performance of the model regarding accurate and safe predictions is enhanced using Bayesian optimization. The proposed framework is evaluated on a reinforced concrete moment frame. Targeting a selected large earthquake scenario, 6,240 nonlinear time history analyses are performed using OpenSees. Simulation results are engineered to extract low-dimensional intensity-based features that can be used as damage indicators. For the given case study, the proposed model achieves a promising accuracy of 83.1% to identify damage location, demonstrating the great potential of model capabilities.
Suppression of electroconvective and morphological instabilities by an imposed cross flow of the electrolyte

The interaction between the electrohydrodynamic instability and an imposed flow is studied. The imposed flow distorts the concentration field causing a sheltering effect which hinders the ion transport from low to high concentration regions, and therefore suppresses the electroconvective instability below a certain wavenumber. The removal of the morphological modes resulting from the hydrodynamic instability can change the wavenumber of the unstable electrodeposition.
Cox regression model under dependent truncation.

Truncation is a statistical phenomenon that occurs in many time-to-event studies. For example, autopsy-confirmed studies of neurodegenerative diseases are subject to an inherent left and right truncation, also known as double truncation. When the goal is to study the effect of risk factors on survival, the standard Cox regression model cannot be used when the survival time is subject to truncation. Existing methods that adjust for both left and right truncation in the Cox regression model require independence between the survival times and truncation times, which may not be a reasonable assumption in practice. We propose an expectation-maximization algorithm to relax the independence assumption in the Cox regression model under left, right, or double truncation to an assumption of conditional independence on the observed covariates. The resulting regression coefficient estimators are consistent and asymptotically normal. We demonstrate through extensive simulations that the proposed estimator has little bias and has a similar or lower mean-squared error compared to existing estimators. We implement our approach to assess the effect of occupation on survival in subjects with autopsy-confirmed Alzheimer's disease.
Doubling the Near-Infrared Photocurrent in a Solar Cell via Omni-Resonant Coherent Perfect Absorption

Minimizing the material usage in thin-film solar cells can reduce manufacturing costs and enable mechanically flexible implementations, but concomitantly diminishes optical absorption. Coherent optical effects can help alleviate this inevitable drawback at discrete frequencies. For example, coherent perfect absorption guarantees that light is fully absorbed in a thin layer regardless of material or thickness but only on resonance. Here we show that omni resonance delivers such coherent enhancement over a broad bandwidth by structuring the optical field to nullify the angular dispersion intrinsic to resonant structures. After embedding an amorphous-silicon thin film photovoltaic cell in a planar cavity, pre conditioning the incident light using an alignment free optical arrangement severs the link between the resonant bandwidth and the cavity photon lifetime, thereby rendering the cavity omni resonant. Coherently enhanced near infrared absorption doubles the photocurrent over the targeted spectral range 660 to 740 nm where every wavelength resonates. These results may pave the way to transparent solar cells that optimally harvest near infrared light.
Searching for gauge theories with the conformal bootstrap

Infrared fixed points of gauge theories provide intriguing targets for the modern conformal bootstrap program. In this work we provide some preliminary evidence that a family of gauged fermionic CFTs saturate bootstrap bounds and can potentially be solved with the conformal bootstrap. We start by considering the bootstrap for SO(N) vector 4-point functions in general dimension D. In the large N limit, upper bounds on the scaling dimensions of the lowest SO(N) singlet and traceless symmetric scalars interpolate between two solutions at ∆ = D/2 − 1 and ∆ = D − 1 via generalized free field theory. In 3D the critical O(N) vector models are known to saturate the bootstrap bounds and correspond to the kinks approaching ∆ = 1/2 at large N. We show that the bootstrap bounds also admit another infinite family of kinks $$ {\mathcal{T}}_D $$ , which at large N approach solutions containing free fermion bilinears at ∆ = D − 1 from below. The kinks $$ {\mathcal{T}}_D $$ appear in general dimensions with a D-dependent critical N* below which the kink disappears. We also study relations between the bounds obtained from the bootstrap with SO(N) vectors, SU(N) fundamentals, and SU(N) × SU(N) bi-fundamentals. We provide a proof for the coincidence between bootstrap bounds with different global symmetries. We show evidence that the proper symmetries of the underlying theories of $$ {\mathcal{T}}_D $$ are subgroups of SO(N), and we speculate that the kinks $$ {\mathcal{T}}_D $$ relate to the fixed points of gauge theories coupled to fermions.
First results from p-Pb collisions at the LHC

Proton–lead (p–Pb) collisions are an integral part of the nuclear program at the Large Hadron Collider (LHC). Their study provides the reference for the Pb–Pb data to disentangle initial from final state effects, as well as the potential to address the partonic structure of matter at low parton fractional momenta (small-x) [1]. The experimental results reported in these proceedings are obtained in a short low-luminosity run performed in September 2012 (with about 1/μb recorded by each experiment), and a longer high-luminosity run in January/February 2013 (with about 30/nb recorded by ATLAS and CMS, about 10/nb by ALICE and about 2/nb by LHCb). The setup of the beams, which is constrained by the two-in-one magnet design of the LHC imposing the same magnetic rigidity of the beams, consisted of protons at 4 TeV energy and of 208 82 Pb ions at 82 × 4 TeV energy. This configuration produced collisions at √ sNN = 5.02 TeV in the nucleon–nucleon centre-of-mass system, shifted in rapidity relative to the laboratory system by ∆yNN = 0.465 in the direction of the proton beam. For clarity, the rapidity (y) as well as the pseudorapidity (η) are sometimes denoted as as ylab and ycms, as well as ηlab and ηcms. To investigate the role of nuclear effects in p–Pb collisions it is desirable to study experimental observables as a function of centrality of the collision. In nucleus– nucleus (A–A) collisions this is typically achieved by relating intervals of measured multiplicity (or energy) distributions (that correspond to certain fractions of the inelastic cross-section) to an average number of nucleon– nucleon collisions (〈Ncoll〉) via a Glauber model [4]. In p–Pb collisions, however, the correlation between multiplicity and collision geometry is less strong than in A–A collisions, and more importantly dynamical biases introduced by the multiplicity estimation can strongly affect the observables under study. Therefore, so far, the experimental results are either reported for minimum-bias collisions (where 〈Ncoll〉 = 208σpp/σpPb = 7.0 ± 0.6, with σpp = 70 ± 5mb [2] and σpPb = 2.09 ± 0.12b [5]), or as a
The obnoxious facilities planar p-median problem

In this paper, we propose the planar obnoxious facilities p-median problem. In the p-median problem the objective is to find p locations for facilities that minimize the weighted sum of distances between communities and their closest facility. In the obnoxious version, we add constraints that each facility must be located at least a certain distance from a partial set of communities because they generate nuisance affecting these communities. The resulting problem is extremely non-convex and traditional nonlinear solvers such as SNOPT are not efficient. An efficient solution method based on Voronoi diagrams is proposed and tested. We also constructed the efficient frontiers of the test problems, showing the trade-off between the required distance and the p-median objective, to assist the planers in making location decisions.
Passage Retrieval for Outside-Knowledge Visual Question Answering

In this work, we address multi-modal information needs that contain text questions and images by focusing on passage retrieval for outside-knowledge visual question answering. This task requires access to outside knowledge, which in our case we define to be a large unstructured passage collection. We first conduct sparse retrieval with BM25 and study expanding the question with object names and image captions. We verify that visual clues play an important role and captions tend to be more informative than object names in sparse retrieval. We then construct a dual-encoder dense retriever, with the query encoder being LXMERT, a multi-modal pre-trained transformer. We further show that dense retrieval significantly outperforms sparse retrieval that uses object expansion. Moreover, dense retrieval matches the performance of sparse retrieval that leverages human-generated captions.
Supervised Prediction of Aging-Related Genes from a Context-Specific Protein Interaction Subnetwork.

Human aging is linked to many prevalent diseases. The aging process is highly influenced by genetic factors. Hence, it is important to identify human aging-related genes. We focus on supervised prediction of such genes. Gene expression-based methods for this purpose study genes in isolation from each other. While protein-protein interaction (PPI) network-based methods for this purpose account for interactions between genes' protein products, current PPI network data are context-unspecific, spanning different biological conditions. Instead, here, we focus on an aging-specific subnetwork of the entire PPI network, obtained by integrating aging-specific gene expression data and PPI network data. The potential of such data integration \emph{has} been recognized but mostly in the context of cancer. So, we are the first to propose a supervised learning framework for predicting aging-related genes from an aging-specific PPI subnetwork. In a systematic and comprehensive evaluation, we find that in many of the evaluation tests: (i) using an aging-specific subnetwork indeed yields more accurate aging-related gene predictions than using the entire network, and (ii) predictive methods from our framework that have not previously been used for supervised prediction of aging-related genes outperform existing prominent methods for the same purpose. These results justify the need for our framework.
Optimal query complexity for private sequential learning against eavesdropping

We study the query complexity of a learner-private sequential learning problem, motivated by the privacy and security concerns due to eavesdropping that arise in practical applications such as pricing and Federated Learning. A learner tries to estimate an unknown scalar value, by sequentially querying an external database and receiving binary responses; meanwhile, a third-party adversary observes the learner's queries but not the responses. The learner's goal is to design a querying strategy with the minimum number of queries (optimal query complexity) so that she can accurately estimate the true value, while the eavesdropping adversary even with the complete knowledge of her querying strategy cannot. We develop new querying strategies and analytical techniques and use them to prove tight upper and lower bounds on the optimal query complexity. The bounds almost match across the entire parameter range, substantially improving upon existing results. We thus obtain a complete picture of the optimal query complexity as a function of the estimation accuracy and the desired levels of privacy. We also extend the results to sequential learning models in higher dimensions, and where the binary responses are noisy. Our analysis leverages a crucial insight into the nature of private learning problem, which suggests that the query trajectory of an optimal learner can be divided into distinct phases that focus on pure learning versus learning and obfuscation, respectively.
TSTNN: Two-Stage Transformer Based Neural Network for Speech Enhancement in the Time Domain

In this paper, we propose a transformer-based architecture, called two-stage transformer neural network (TSTNN) for end-to-end speech denoising in the time domain. The proposed model is composed of an encoder, a two-stage transformer module (TSTM), a masking module and a decoder. The encoder maps input noisy speech into feature representation. The TSTM exploits four stacked two-stage transformer blocks to efficiently extract local and global information from the encoder output stage by stage. The masking module creates a mask which will be multiplied with the encoder output. Finally, the decoder uses the masked encoder feature to reconstruct the enhanced speech. Experimental results on the benchmark dataset show that the TSTNN outperforms most state-of-the-art models in time or frequency domain while having significantly lower model complexity.
Distributed Scheduling Using Graph Neural Networks

A fundamental problem in the design of wireless networks is to efficiently schedule transmission in a distributed manner. The main challenge stems from the fact that optimal link scheduling involves solving a maximum weighted independent set (MWIS) problem, which is NP-hard. For practical link scheduling schemes, distributed greedy approaches are commonly used to approximate the solution of the MWIS problem. However, these greedy schemes mostly ignore important topological information of the wireless networks. To overcome this limitation, we propose a distributed MWIS solver based on graph convolutional networks (GCNs). In a nutshell, a trainable GCN module learns topology-aware node embeddings that are combined with the network weights before calling a greedy solver. In small- to middle-sized wireless networks with tens of links, even a shallow GCN-based MWIS scheduler can leverage the topological information of the graph to reduce in half the suboptimality gap of the distributed greedy solver with good generalizability across graphs and minimal increase in complexity.
Building Computationally Efficient and Well-Generalizing Person Re-Identification Models with Metric Learning

This work considers the problem of domain shift in person re-identification. Being trained on one dataset, a reidentification model usually performs much worse on unseen data. Partially this gap is caused by the relatively small scale of person re-identification datasets (compared to face recognition ones, for instance), but it is also related to training objectives. We propose to use the metric learning objective, namely AM-Softmax loss, and some additional training practices to build well-generalizing, yet, computationally efficient models. We use recently proposed Omni-Scale Network (OSNet) architecture combined with several training tricks and architecture adjustments to obtain state-of-the art results in cross-domain generalization problem on a large-scale MSMT17 dataset in three setups: MSMT17-all→DukeMTMC, MSMT17-train→Market1501 and MSMT17-all→Market1501. Training code and the models are available online in the GitHub repository11https://github.com/openvinotoolkit/training_extensions/tree/develop/pytorch_toolkit/object_reidentitication/person_reidentitication.
Uncertainty quantification and software risk analysis for digital twins in the nearly autonomous management and control systems: A review

Abstract A nearly autonomous management and control (NAMAC) system is designed to furnish recommendations to operators for achieving particular goals based on NAMAC’s knowledge base. As a critical component in a NAMAC system, digital twins (DTs) are used to extract information from the knowledge base to support decision-making in reactor control and management during all modes of plant operations. With the advancement of artificial intelligence and data-driven methods, machine learning algorithms are used to build DTs of various functions in the NAMAC system. To evaluate the uncertainty of DTs and its impacts on the reactor digital instrumentation and control systems, uncertainty quantification (UQ) and software risk analysis is needed. As a comprehensive overview of prior research and a starting point for new investigations, this study selects and reviews relevant UQ techniques and software hazard and software risk analysis methods that may be suitable for DTs in the NAMAC system.
On the Power of Static Assignment Policies for Robust Facility Location Problems.

We consider a two-stage robust facility location problem on a metric under an uncertain demand. The decision-maker needs to decide on the (integral) units of supply for each facility in the first stage to satisfy an uncertain second-stage demand, such that the sum of first stage supply cost and the worst-case cost of satisfying the second-stage demand over all scenarios is minimized. The second-stage decisions are only assignment decisions without the possibility of adding recourse supply capacity. This makes our model different from existing work on two-stage robust facility location and set covering problems. We consider an implicit model of uncertainty with an exponential number of demand scenarios specified by an upper bound k on the number of second-stage clients. In an optimal solution, the second-stage assignment decisions depend on the scenario; surprisingly, we show that restricting to a fixed (static) fractional assignment for each potential client irrespective of the scenario gives us an \(O(\log k/\log \log k)\)-approximation for the problem. Moreover, the best such static assignment can be computed efficiently giving us the desired guarantee.