cssi/SciSciGPT-SciSciNet huggingface dataset:
The Structure of Unjust Enrichment Law: Is Restitution a Right or a Remedy

This essay provides a model for distinguishing between court orders that directly enforce primary duties (e.g., to not trespass) and court orders that require defendants to repair the harm caused by failing to perform a primary duty (e.g., to pay compensatory damages), and then applies the model to the case of restitutionary orders (e.g., a court order that the recipient of a mistaken payment pay an equivalent sum to the payor). Drawing upon, on the one hand, theoretical arguments about the nature of law and the moral foundations of duties to repair, and, on the other hand, the nature of restitutionary orders, Professor Smith concludes that restitutionary orders can be either direct enforcement orders or orders to repair – sometimes they are the former, sometimes the latter.
THE WELFARE COST OF INFLATION IN OECD COUNTRIES

The welfare cost of anticipated inflation is quantified in a matching model of money calibrated to 23 different OECD countries for several sample periods. In most economies, in the common period 1978–1998, a representative agent would give up only a fraction of 1% of consumption to avoid 10% inflation. The welfare cost of inflation varies across countries, from a fraction of 0.1% in Japan, to more than 2% in Australia, reaching 6% with bargaining. The model fits money demand data of several countries poorly, however. The fit generally improves with longer sample periods. The results are fairly robust to variations in choice of calibrated parameters and calibration targets.
Financial Statement Comparability and the Efficiency of Acquisition Decisions

This study examines whether acquirers make better acquisition decisions when target firms’ financial statements exhibit greater comparability with industry peer firms. We predict and find that acquirers make more profitable acquisition decisions when target firms’ financial statements are more comparable—as evidenced by higher merger announcement returns, higher acquisition synergies, and better future operating performance. We also find that post-acquisition goodwill impairments and post-acquisition divestitures are less likely when target firms’ financial statements are more comparable. Finally, we find that acquirers benefit most from comparability when acquirers’ ex ante information asymmetry is higher, acquirers operate in volatile operating environments, and management knows relatively less about the target. In total, our evidence suggests targets’ financial statement comparability helps acquirers make better acquisition-investment decisions and fosters more efficient capital allocation.
Insider Trading after Repurchase Tender Offer Announcements: Timing versus Informed Trading

Abnormally high net insider selling is commonly observed after repurchase tender offer (RTO) announcements although, on average, firms experience positive abnormal returns in the years after the repurchases. We explore two potential explanations: liquidity trade timing and informed trading. Consistent with the notion that fixed price RTOs are more likely than Dutch-auction RTOs to signal undervaluation, the results suggest that insider selling after fixed price RTO announcements are driven largely by insiders who time their trades with the repurchase announcements. In contrast, selling after Dutch-auction RTOs seems to be driven primarily by informed traders who exploit mispricing associated with the repurchase announcements.
Money, It's a Crime, Share It Fairly, But Don't Take a Slice of My Pie: The Legislative Case for the Progressive Income Tax

The progressive tax and its soundness as the best tax structure has been the subject of extensive economic and political debate. A critical void, however, exists in the scholarship examining proposals in support of or against the progressive tax. The legislative and political rationales behind the progressive income tax have not been examined, including the reasons it was enacted and how (and whether) it has survived through so many administrations and political persuasions. Policymakers and analysts of the progressive tax cannot appropriately evaluate the consequences ofa proposal regarding the progressive income tax without this analysis. The purpose of this article is to identify the rationales for and against the progressive income tax, both at the time of its enactment and during subsequent challenges to and affirmations of the progressive income tax. This paper analyzes six fundamental reasons behind the enactment of the progressive income tax and their relevancy today. The American public is still supportive of a progressive income tax and, as a result, when opponents to the progressive income tax make alternative proposals these opponents often label the proposal or an aspect of the proposal as progressive to garner public support. The progressive tax does not exist merely for economic reasons; there are more economically efficient systems. No matter how economically sound a proposal is, unless the proposal fulfills the rationales served by a progressive income tax, it will not be an appropriate replacement. Each of the six reasons, which have been consistently addressed in legislative history, need to be evaluated before any discussion surrounding the progressive income tax can take place. (1) The ability to pay theory provides that those with higher-incomes should have a higher tax rate and burden because they have extra income (surplus) to fund the government. Today, however, lower-income taxpayers often pay a greater tax * Pink Floyd, "Money" from the Dark Side of the Moon (Harvest/Capital Records) (1973). ** Professor of Law Suffolk University of Law School, JD Rutgers Camden, LLM Taxation NYU Law School. Thank you to Annette Donahue, Justin DeAngelis, Mary Flaherty, Christopher Tedone, Kristen Ward, Evan Zaremba, and Christopher Zaremba for their wonderful and supportive research and editing assistance. A writer could not ask for a better team.
Trading system capability

High-frequency trading (HFT) systems come in different shapes and sizes. They include stock and option market making systems, as well as other algorithm-driven strategies such as index arbitrage an...
The Shifting Meaning of Happiness

An examination of emotions reported on 12 million personal blogs along with a series of surveys and laboratory experiments shows that the meaning of happiness is not fixed; instead, it systematical...
New Pleading, New Discovery

Pleading in federal court has a new narrative. The old narrative was one of notice, with the goal of broad access to the civil justice system. New Pleading, after the landmark Supreme Court cases of Twombly and Iqbal, is focused on factual sufficiency, with the purpose of screening out meritless cases that otherwise might impose discovery costs on defendants. The problem with New Pleading is that factual sufficiency often is a poor proxy for meritlessness. Some plaintiffs lack sufficient factual knowledge of the elements of their claims not because the claims lack merit but because the information they need is in the hands of defendants. New Pleading thus screens out these claims even though they may have merit. This article offers a solution to New Pleading's problems of information asymmetry: New Discovery. New Discovery recognizes the need for limited presuit or pre-dismissal discovery to provide plaintiffs the opportunity to gather the facts necessary to comply with New Pleading's strictures. The article presents a normative defense of New Discovery, offers some guiding principles and tools for controlling its scope and cost, and explores how New Discovery might work both under the current discovery scheme and in the context of needed discovery reforms.
Fatal Subtraction: Statistical MIAs on the Industrial Battlefield

In social or natural science investigations it is or should be methodologically self-explanatory that before any phenomenon can be counted, it must be conceptualized and defined. To be sure, certain tricky definitional issues do exist that require clarification before industrial injury fatalities can be counted, but they have largely been resolved or at least disposed of. For many decades, however, the more urgent issue has been for the state to implement adequate injury surveillance in order to conduct an accurate count; the resulting data could then be used for epidemiological studies on the basis of which the state could intervene in employers’ operations to impose safer working conditions. This article analyzes the history of the failure to perform such an enumeration and its consequences for the health and safety of workers in the United States. In order to provide a more finely textured sense of the issues, throughout illustrative material is taken from construction, one of the most dangerous industries. The article begins with an account of the statistical chaos and confusion engendered by the murderous pace of production at the beginning of the twentieth century. Following a survey of flawed private and government efforts to count the dead at work since the 1920s, the focus shifts to the statistical and enforcement defects of OSHA. After analyzing the fatality trends uncovered by the new Census of Fatal Occupational Injuries and a renewed tendency to divert attention from the antagonism between safety and profits, the article concludes with a critique of one important use to which occupational fatality data have been put — economic and legal theories that assert that workers in especially dangerous occupations are compensated for the risks to which they are exposed.
Nonrational actors and financial market behavior

The insights of descriptive decision theorists and psychologists, we believe, have much to contribute to our understanding of financial market macrophenomena. We propose an analytic agenda that distinguishes those individual idiosyncrasies that prove consequential at the macro-level from those that are neutralized by market processes such as poaching. We discuss five behavioral traits — barn-door closing, expert/reliance effects, status quo bias, framing, and herding — that we employ in explaining financial flows. Patterns in flows to mutual funds, to new equities, across national boundaries, as well as movements in debt-equity ratios are shown to be consistent with deviations from rationality.
Health Care Providers Meet ERISA: Are Provider Claims for Misrepresentation of Coverage Preempted

This article explores whether ERISA should preempt state law claims (such as misrepresentation or promissory estoppel) that health care providers have misrepresented coverage. It concludes that ERISA should not preempt such claims.
Uniqueness in Random-Proposer Multilateral Bargaining

Solution uniqueness is an important property for a bargaining model. Rubinstein's (1982) seminal 2-person alternating-offer bargaining game has a unique Subgame Perfect Equilibrium outcome. Is it possible to obtain uniqueness results in the much enlarged setting of multilateral bargaining with a characteristic function? This paper investigates a random-proposer model first studied in Okada (1993) in which each period players have equal probabilities of being selected to make a proposal and bargaining ends after one coalition forms. Focusing on transferable utility environments and Stationary Subgame Perfect Equilibria (SSPE), we find ex ante SSPE payoff uniqueness for symmetric and convex characteristic functions, considerably expanding the conditions under which this model is known to exhibit SSPE payoff uniqueness. Our model includes as a special case a variant of the legislative bargaining model in Baron and Ferejohn (1989), and our results imply (unrestricted) SSPE payoff uniqueness in this case.
Which leadership roles matter to whom? an examination of rater effects on perceptions of effectiveness

Abstract Using a 360-degree feedback approach, we examined the extent to which raters vary in the leadership roles they associate with effectiveness, as well as the extent to which self-ratings reflect those of other raters. Using data from 252 managers and their subordinates, peers, and superiors from the public utility industry, we found that, depending on the rater-ratee relationship, different leadership roles are associated with effectiveness. The managers themselves resembled their superiors the most in terms of the leadership roles they associated with effectiveness. These results lend support for the importance of 360-degree feedback for both practitioners and researchers. Organizational researchers, then, should not only examine levels of rater agreement, but also try to better understand what different raters consider critical leadership roles. This article is a step in that direction.
A Reexamination of Purchasing Power Parity: A Multicountry and Multiperiod Study

Abstract This paper re-examines the purchasing power parity (PPP) theory, in a multiple exchange rate world. Owing to a lack of precision in estimating the parameters, many authors concluded that PPP did not hold very well in the 1970s. Using a time series-cross sectional estimation procedure we are unable to reject the hypothesis that PPP holds in several currencies simultaneously. In addition, the parameters are precisely estimated. This result follows from the estimation procedure which allows us to exploit the cross-sectional variation in the data and the contemporaneous correlation in the deviations from PPP.
The Right to Travel: Breaking Down the Thousand Petty Fortresses of State Self-Deportation Laws

An examination of the use of the Right to Travel as a barrier to State Self-Deportation Laws.The mass exodus from Albertville, Alabama was not the result of a natural disaster or fears of an invasion by hostile forces. Instead, the residents of Albertville fled Alabama exactly in the manner the state legislators intended when Alabama passed H.B. 56. Alabama’s H.B. 56 is part of a legislative strategy known as “self-deportation” - a term first used to satirize an early ancestor of H.B. 56 that was passed in California as a public referendum titled, Proposition 187. The satirical term transformed into public policy for states that were frustrated by a perceived lack of federal enforcement of immigration laws. The policy got national attention when Mitt Romney adopted self-deportation as part of his platform during the 2012 Presidential election campaign. Despite a national discussion on immigration generally, often self-deportation legislation remains a local or state based issue. In June of 2013, the town of Fremont, Nebraska successfully defended in the Eighth Circuit Court of Appeals a set of ordinances written to prevent undocumented immigrants from living in the city.
Activist hedge funds and firm disclosure

This study examines whether firms' disclosure decisions are affected by the presence of activist hedge funds. Using a large sample of firms that experienced increases in ownership by activist hedge funds, we find that firms are more likely to cease providing financial guidance or reduce the information in the guidance in the quarter subsequent to new investment by activist hedge funds. These results hold even for firms that experienced good quarters and consistently provided guidance in previous quarters. Since guidance has been shown to be beneficial to capital market participants in many ways, reduced guidance has meaningful market implications. Our findings highlight a negative and possible unintended consequence of activist hedge funds' investment in firms, which provides some counterbalance to the numerous positive consequences documented in the prior literature on hedge fund activism.
The Bond Coupon’s Impact on Liquidity

Corporate bond investors are compensated for liquidity and counterparty risk in the yield received in excess of the credit premium and risk-free rate. This article shows that the liquidity premium as a hedge against uncertain future states is determined by the ratio of excess coupon payments after paying for credit protection to the capital gain realized after hedging interest rate risk. The liquidity premium increases with the time that investors must wait for compensation. The results suggest that the way in which investors receive compensation for liquidity risk is a more significant determinant of the liquidity premium than turnover.
Coase and Bertrand on lighthouses

Coase (Journal of Low and Economics 17(2):185–213, 1974) failed to appreciate that the construction and maintenance of nineteenth-century lighthouses were in part financed by British taxpayers. Bertrand (Cambridge Journal of Economics 30:389–402, 2006) rightly calls him to account. While agreeing with Bertrand’s conclusion, we dispute her reasoning and argue that lighthouses nevertheless could have been supplied by the private sector.
Revising A Voluntary Disclosure Decision

Public information that becomes available after a manager’s initial voluntary disclosure decision creates incentives for her to reconsider and possibly change that decision. We show that if she has private information that is value relevant or that impacts the firms ability to compete in its product market, the option to revise an initial disclosure decision in the face of a public release of information alters both the initial decision and the overall frequency of disclosure. These effects are amplified if she believes that public information arrival is more likely or if the firms value is more sensitive to it. We also show that an increase in the initial disclosure cost reduces the probability of an initial disclosure and increases the probability of a subsequent disclosure. These effects are reversed if the cost of a subsequent disclosure increases.
Swimming Motility and Chemotaxis Control the Spatial Organization, Persistence, and Inflammatory Activity of a Model Intestinal Pathobiont

Understanding the processes that spatially restrict resident gut bacteria and the mechanisms by which disease-causing pathobionts escape this control will open new avenues for microbiome-based therapies. Using live imaging and genetically engineered bacteria, we discovered that flagella-based swimming motility and chemotaxis enable a model Vibrio pathobiont to govern its own spatial organization within the larval zebrafish gut and to persist in the face of the disruptive forces of intestinal flow. Bacterial mutants lacking motility traits became aggregated and lumenally confined, making them susceptible to periodic expulsion from the host. Consequently, non-motile and non-chemotactic mutants experienced large fluctuations in absolute abundance and impaired interbacterial competition. Further, we found that motile bacterial cells induce expression of the proinflammatory cytokine TNFα in gut-associated macrophages and the liver. Using inducible genetic switches, we demonstrate that swimming motility can be manipulated in situ to modulate the spatial organization, persistence, and inflammatory activity of gut bacteria.
FASiM: A Framework for Automatic Formal Analysis of Simulink Models of Linear Analog Circuits

Simulink is a graphical environment that is widely adapted for the modeling and the Laplace transform based analysis of linear analog circuits used in signal processing architectures. However, due to the involvement of the numerical algorithms of MATLAB in the analysis process, the analysis results cannot be termed as complete and accurate. Higher-order-logic theorem proving is a formal verification method that has been recently proposed to overcome these limitations for the modeling and the Laplace transform based analysis of linear analog circuits. However, the formal modeling of a system is not a straightforward task due to the lack of formal methods background for engineers working in the industry. Moreover, due to the undecidable nature of higher-order logic, the analysis generally requires a significant amount of user guidance in the manual proof process. In order to facilitate industrial engineers to formally analyze the linear analog circuits based on the Laplace transform, we propose a framework, FASiM, which allows automatically conducting the formal analysis of the Simulink models of linear analog circuits using the HOL Light theorem prover. For illustration, we use FASiM to formally analyze Simulink models of some commonly used linear analog filters, such as Sallen-key filters.
Approximately strategyproof tournament rules in the probabilistic setting

We consider the manipulability of tournament rules which map the results of $\binom{n}{2}$ pairwise matches and select a winner. Prior work designs simple tournament rules such that no pair of teams can manipulate the outcome of their match to improve their probability of winning by more than $1/3$, and this is the best possible among any Condorcet-consistent tournament rule (which selects an undefeated team whenever one exists) [Schneider et al., 2017, Schvartzman et al., 2020]. These lower bounds require the manipulators to know precisely the outcome of all future matches. We take a beyond worst-case view and instead consider tournaments which are "close to uniform": the outcome of all matches are independent, and no team is believed to win any match with probability exceeding $1/2+\varepsilon$. We show that Randomized Single Elimination Bracket [Schneider et al., 2017] and a new tournament rule we term Randomized Death Match have the property that no pair of teams can manipulate the outcome of their match to improve their probability of winning by more than $\varepsilon/3 + 2\varepsilon^2/3$, for all $\varepsilon$, and this is the best possible among any Condorcet-consistent tournament rule. Our main technical contribution is a recursive framework to analyze the manipulability of certain forms of tournament rules. In addition to our main results, this view helps streamline previous analysis of Randomized Single Elimination Bracket, and may be of independent interest.
Instantons and Bar-Natan homology

A spectral sequence is established, whose $E_{2}$ page is Bar-Natan's variant of Khovanov homology and which abuts to a deformation of instanton homology for knots and links. This spectral sequence arises as a specialization of a spectral sequence whose $E_{2}$ page is a characteristic-2 version of $F_{5}$ homology, in Khovanov's classification.
Meiotic sister chromatid exchanges are rare in C. elegans.

Summary Sexual reproduction shuffles the parental genomes to generate new genetic combinations. To achieve that, the genome is subjected to numerous double-strand breaks, the repair of which involves two crucial decisions: repair pathway and repair template. 1 Use of crossover pathways with the homologous chromosome as template exchanges genetic information and directs chromosome segregation. Crossover repair, however, can compromise the integrity of the repair template and is therefore tightly regulated. The extent to which crossover pathways are used during sister-directed repair is unclear because the identical sister chromatids are difficult to distinguish. Nonetheless, indirect assays have led to the suggestion that inter-sister crossovers, or sister chromatid exchanges (SCEs), are quite common. 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 Here we devised a technique to directly score physiological SCEs in the C. elegans germline using selective sister chromatid labeling with the thymidine analog 5-ethynyl-2’-deoxyuridine (EdU). Surprisingly, we find SCEs to be rare in meiosis, accounting for 12 , 13 —promotes SCEs when localized between the sisters. Our data suggest that crossover pathways in C. elegans are only used to generate the single necessary link between the homologous chromosomes. Noncrossover pathways repair almost all other breaks, regardless of the repair template.
PTP: Parallelized Tracking and Prediction With Graph Neural Networks and Diversity Sampling

Multi-object tracking (MOT) and trajectory prediction are two critical components in modern 3D perception systems that require accurate modeling of multi-agent interaction. We hypothesize that it is beneficial to unify both tasks under one framework in order to learn a shared feature representation of agent interaction. Furthermore, instead of performing tracking and prediction sequentially which can propagate errors from tracking to prediction, we propose a parallelized framework to mitigate the issue. Also, our parallel track-forecast framework incorporates two additional novel computational units. First, we use a feature interaction technique by introducing Graph Neural Networks (GNNs) to capture the way in which agents interact with one another. The GNN is able to improve discriminative feature learning for MOT association and provide socially-aware contexts for trajectory prediction. Second, we use a diversity sampling function to improve the quality and diversity of our forecasted trajectories. The learned sampling function is trained to efficiently extract a variety of outcomes from a generative trajectory distribution and helps avoid the problem of generating duplicate trajectory samples. We evaluate on KITTI and nuScenes datasets showing that our method with socially-aware feature learning and diversity sampling achieves new state-of-the-art performance on 3D MOT and trajectory prediction. Project website is: http://www.xinshuoweng.com/projects/PTP .
Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach

Online peer-to-peer support platforms enable conversations between millions of people who seek and provide mental health support. If successful, web-based mental health conversations could improve access to treatment and reduce the global disease burden. Psychologists have repeatedly demonstrated that empathy, the ability to understand and feel the emotions and experiences of others, is a key component leading to positive outcomes in supportive conversations. However, recent studies have shown that highly empathic conversations are rare in online mental health platforms. In this paper, we work towards improving empathy in online mental health support conversations. We introduce a new task of empathic rewriting which aims to transform low-empathy conversational posts to higher empathy. Learning such transformations is challenging and requires a deep understanding of empathy while maintaining conversation quality through text fluency and specificity to the conversational context. Here we propose Partner, a deep reinforcement learning (RL) agent that learns to make sentence-level edits to posts in order to increase the expressed level of empathy while maintaining conversation quality. Our RL agent leverages a policy network, based on a transformer language model adapted from GPT-2, which performs the dual task of generating candidate empathic sentences and adding those sentences at appropriate positions. During training, we reward transformations that increase empathy in posts while maintaining text fluency, context specificity, and diversity. Through a combination of automatic and human evaluation, we demonstrate that Partner successfully generates more empathic, specific, and diverse responses and outperforms NLP methods from related tasks such as style transfer and empathic dialogue generation. This work has direct implications for facilitating empathic conversations on web-based platforms.
Data-driven Energy Management Strategy for Plug-in Hybrid Electric Vehicles with Real-World Trip Information

Abstract This paper presents a data-driven supervisory energy management strategy (EMS) for plug-in hybrid electric vehicles which leverages Vehicle-to-Cloud connectivity to increase energy efficiency by learning control policies from completed trips. The proposed EMS consists of two layers, a cloud layer and an on-board layer. The cloud layer has two main tasks: the first task is to learn EMS policy parameters from historical trip data, and the second task is to provide the policy parameters along a certain route requested from the vehicle. The onboard layer receives the learned policy parameters from the cloud layer and computes a real-time solution to the powertrain energy management problem, using a model predictive control scheme. The proposed EMS is evaluated on more than 3000 miles (48 independent driving cycles) of real-world trip data, collected along three commuting routes in California. For the routes, the proposed algorithm shows 3.3%, 7.3%, and 6.5% improvement in average MPGe when compared to a baseline EMS.
The Challenges of Conducting Intrastate Policy Surveillance: A Methods Note on County and City Laws in Indiana.

Policy surveillance is critical in examining the ways law functions as a structural and social determinant of health. To date, little policy surveillance research has focused on examining intrastat...
Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering

Commonly used information retrieval methods such as TF-IDF in open-domain question answering (QA) systems are insufficient to capture deep semantic matching that goes beyond lexical overlaps. Some recent studies consider the retrieval process as maximum inner product search (MIPS) using dense question and paragraph representations, achieving promising results on several information-seeking QA datasets. However, the pretraining of the dense vector representations is highly resource-demanding, e.g., requires a very large batch size and lots of training steps. In this work, we propose a sample-efficient method to pretrain the paragraph encoder. First, instead of using heuristically created pseudo question-paragraph pairs for pretraining, we use an existing pretrained sequence-to-sequence model to build a strong question generator that creates high-quality pretraining data. Second, we propose a simple progressive pretraining algorithm to ensure the existence of effective negative samples in each batch. Across three open-domain QA datasets, our method consistently outperforms a strong dense retrieval baseline that uses 6 times more computation for training. On two of the datasets, our method achieves more than 4-point absolute improvement in terms of answer exact match.
Active participation of membrane lipids in inhibition of multidrug transporter P-glycoprotein

P-glycoprotein (Pgp) is a major efflux pump in humans, overexpressed in a variety of cancers and associated with the development of multi-drug resistance. Allosteric modulation by various ligands (e.g., transport substrates, inhibitors, and ATP) has been biochemically shown to directly influence structural dynamics, and thereby, the function of Pgp. However, the molecular details of such effects, particularly with respect to the role and involvement of the surrounding lipids, are not well established. Here, we employ all-atom molecular dynamics (MD) simulations to study the conformational landscape of Pgp in the presence of a high-affinity, third-generation inhibitor, tariquidar, in comparison to the nucleotide-free (APO) and the ATP-bound states, in order to characterize the mechanical effects of the inhibitor that might be of relevance to its blocking mechanism of Pgp. Simulations in a multi-component lipid bilayer show a dynamic equilibrium between open(er) and more closed inward-facing (IF) conformations in the APO state, with binding of ATP shifting the equilibrium towards conformations more prone to ATP hydrolysis and subsequent events in the transport cycle. In the presence of the inhibitor bound to the drug-binding pocket within the transmembrane domain (TMD), Pgp samples more open IF conformations, and the nucleotide binding domains (NBDs) become highly dynamic. Interestingly, and reproduced in multiple independent simulations, the inhibitor is observed to facilitate recruitment of lipid molecules into the Pgp lumen through the two proposed drug-entry portals, where the lipid head groups from the cytoplasmic leaflet penetrate into and, in some cases, translocate inside the TMD, while the lipid tails remain extended into the bulk lipid environment. These "wedge" lipids likely enhance the inhibitor-induced conformational restriction of the TMD leading to the differential modulation of coupling pathways observed with the NBDs downstream. We suggest a novel inhibitory mechanism for tariquidar, and potentially for related third-generation Pgp inhibitors, where lipids are seen to enhance the inhibitory role in the catalytic cycle of membrane transporters.
Finance and the supply of housing quality

Abstract I show how financial intermediaries affect rental housing quality and affordability by supplying real estate investors with financing for quality improvement projects (i.e., renovations). First, I document a historic surge in improvement activity since the Great Recession. Then, using exogenous variation generated by a 2015 change in regulatory capital requirements, I find that a reallocation of bank credit toward improvement projects accounts for 24% of quality improvements since 2015. The shock increases the supply of high-quality apartments and lowers their rent. However, it raises the average apartment’s rent and accounts for 32% of historically high rent growth over 2015–16.
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models

Bayesian experimental design (BED) is to answer the question that how to choose designs that maximize the information gathering. For implicit models, where the likelihood is intractable but sampling is possible, conventional BED methods have difficulties in efficiently estimating the posterior distribution and maximizing the mutual information (MI) between data and parameters. Recent work proposed the use of gradient ascent to maximize a lower bound on MI to deal with these issues. However, the approach requires a sampling path to compute the pathwise gradient of the MI lower bound with respect to the design variables, and such a pathwise gradient is usually inaccessible for implicit models. In this paper, we propose a novel approach that leverages recent advances in stochastic approximate gradient ascent incorporated with a smoothed variational MI estimator for efficient and robust BED. Without the necessity of pathwise gradients, our approach allows the design process to be achieved through a unified procedure with an approximate gradient for implicit models. Several experiments show that our approach outperforms baseline methods, and significantly improves the scalability of BED in high-dimensional problems.
Dissipation scaling and structural order in turbulent channel flows

Scaling and structural evolutions are contemplated in a new perspective for turbulent channel flows. The total integrated turbulence kinetic energy and the total dissipation can be viewed as global constraints on the turbulence structure, leading to predictable, ordered scaling for u′2 and v′2 through its first and second gradients, respectively. This self-similarity allows for profile reconstructions at any Reynolds numbers based on a common template through simple multiplicative operations. Using these scaled variables in the Lagrangian transport equation derives the Reynolds shear stress, which in turn computes the mean velocity profile through the Reynolds-averaged Navier–Stokes equation. The dissipation scaling along with the transport equations renders succinct views of the turbulence dynamics and its structural characteristics. In this way, variable profiles can be analytically reconstructed, which bears potential implications toward solvability and computability of turbulent flows in canonical and other geometries.
Electrical synaptic transmission requires a postsynaptic scaffolding protein.

Neurons ‘talk’ with each another at junctions called synapses, which can either be chemical or electrical. Communication across a chemical synapse involves a ‘sending’ neuron releasing chemicals that diffuse between the cells and subsequently bind to specialized receptors on the receiving neuron. These complex junctions involve a large number of well-studied molecular actors. Electrical synapses, on the other hand, are believed to be simpler. There, neurons are physically connected via channels formed of ‘connexin’ proteins, which allow electrically charged ions to flow between the cells. However, it is likely that other proteins help to create these structures. In particular, recent evidence shows that without a structurally supporting ‘scaffolding’ protein called ZO1, electrical synapses cannot form in the brain of a tiny freshwater fish known as zebrafish. As their name implies, scaffolding proteins help cells organize their internal structure, for example by anchoring other molecules to the cell membrane. By studying electrical synapses in zebrafish, Lasseigne, Echeverry, Ijaz, Michel et al. now show that these structures are more complex than previously assumed. In particular, the experiments reveal that ZO1 proteins are only present on one side of electrical synapses; despite their deceptively symmetrical anatomical organization, these junctions can be asymmetric, like their chemical cousins. The results also show that ZO1 must be present for connexins to gather at electrical synapses, whereas the converse is not true. This suggests that when a new electrical synapse forms, ZO1 moves into position first: it then recruits or stabilizes connexins to form the channels connecting the two cells. In many animals with a spine, electrical synapses account for about 20% of all neural junctions. Understanding how these structures form and work could help to find new treatments for disorders linked to impaired electrical synapses, such as epilepsy.
Working from home: small business performance and the COVID-19 pandemic

During the COVID-19 pandemic, many firms began operating in a working-from-home environment (WFH). This study focuses on the relationship between WFH and small business performance during the pandemic. We built a theoretical framework based on firm profit maximization, compiled an up-to-date (March through November) real-time daily and weekly multifaceted data set, and empirically estimated fixed-effect panel data, fractional logit, and multilevel mixed effects models to test our hypotheses. We find that in states with higher WFH rates, small businesses performed better overall with industry variations, controlling for the local pandemic, economic, demographic, and policy factors. We also find that WFH rates increased even after stay-at-home orders (SHOs) were rescinded. With the ready technology and practice of WFH in the pandemic, our robust empirics confirm our theory and hypotheses and demonstrate WFH as a potential force that may expedite “creative destruction” instance and permanently impact industrial structure and peoples’ work lives. The Rise of Working from Home (WFH) as a Silver Lining and “Creative Destruction” in the Pandemic: WFH Helps Small Businesses Perform Better with Industry Variations and Continues to Shine after Stay-at-Home Orders Ended. This study focuses on the role of working from home (WFH) for small business performance during the COVID-19 pandemic. We built a theoretical framework based on firm profit maximization and identified WFH as a rational business choice. We then compiled a real-time multifaceted data set, estimated panel fixed-effect, fractional logit, and multilevel mixed effects models, and find that (1) small businesses in states with higher WFH rates performed better with industry variations, controlling for local pandemic and socioeconomic factors; and (2) WFH rates increased after stay-at-home orders were rescinded. Our study demonstrates WFH as a potential “creative destruction” force that may expedite our technologically ready WFH adoption and permanently impact industrial structure and peoples’ work lives.
Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

A land surface hydrology parameterization for use in atmospheric GCMs is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large scale parameterizations: water balance calculations are performed for a number of intervals of the topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well at the dynamics of land surface-atmosphere interactions.
Is there any incremental benefit to conducting neuroimaging and neurocognitive assessments in the diagnosis of ADHD in young children? A machine learning investigation.

Abstract Given the negative trajectories of early behavior problems associated with ADHD, early diagnosis is considered critical to enable intervention and treatment. To this end, the current investigation employed machine learning to evaluate the relative predictive value of parent/teacher ratings, behavioral and neural measures of executive function (EF) in predicting ADHD in a sample consisting of 162 young children (ages 4–7, mean age 5.55, 82.6 % Hispanic/Latino). Among the target measures, teacher ratings of EF were the most predictive of ADHD. While a more extensive evaluation of neural measures, such as diffusion-weighted imaging, may provide more information as they relate to the underlying cognitive deficits associated with ADHD, the current study indicates that measures of cortical anatomy obtained in research studies, as well cognitive measures of EF often obtained in routine assessments, have little incremental value in differentiating typically developing children from those diagnosed with ADHD. It is important to note that the overlap between some of the EF questions in the BRIEF, and the ADHD symptoms could be enhancing this effect. Thus, future research evaluating the importance of such measures in predicting children’s functional impairment in academic and social areas would provide additional insight into their contributing role in ADHD.
Aerothermodynamic Characteristics of Boundary Layer Transition and Trip Effectiveness of the HIFiRE Flight 5 Vehicle

An experimental wind tunnel test was conducted in the NASA Langley Research Center s 20-Inch Mach 6 Tunnel in support of the Hypersonic International Flight Research Experimentation Program. The information in this report is focused on the Flight 5 configuration, one in a series of flight experiments. This report documents experimental measurements made over a range of Reynolds numbers and angles of attack on several scaled ceramic heat transfer models of the Flight 5 vehicle. The heat transfer rate was measured using global phosphor thermography and the resulting images and heat transfer rate distributions were used to infer the state of the boundary layer on the windside, leeside and side surfaces. Boundary layer trips were used to force the boundary layer turbulent, and a study was conducted to determine the effectiveness of the trips with various heights. The experimental data highlighted in this test report were used determine the allowable roughness height for both the windside and side surfaces of the vehicle as well as provide for future tunnel-to-tunnel comparisons.
Quantum-Enhanced Data Classification with a Variational Entangled Sensor Network

Quantum machine-learning techniques speed up the task of classifying data delivered by a small network of quantum sensors.
Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case

We make significant progress toward the stochastic shortest path problem with adversarial costs and unknown transition. Specifically, we develop algorithms that achieve $\widetilde{O}(\sqrt{S^2ADT_\star K})$ regret for the full-information setting and $\widetilde{O}(\sqrt{S^3A^2DT_\star K})$ regret for the bandit feedback setting, where $D$ is the diameter, $T_\star$ is the expected hitting time of the optimal policy, $S$ is the number of states, $A$ is the number of actions, and $K$ is the number of episodes. Our work strictly improves (Rosenberg and Mansour, 2020) in the full information setting, extends (Chen et al., 2020) from known transition to unknown transition, and is also the first to consider the most challenging combination: bandit feedback with adversarial costs and unknown transition. To remedy the gap between our upper bounds and the current best lower bounds constructed via a stochastically oblivious adversary, we also propose algorithms with near-optimal regret for this special case.
Prior Image-Constrained Reconstruction using Style-Based Generative Models

Obtaining a useful estimate of an object from highly incomplete imaging measurements remains a holy grail of imaging science. Deep learning methods have shown promise in learning object priors or constraints to improve the conditioning of an ill-posed imaging inverse problem. In this study, a framework for estimating an object of interest that is semantically related to a known prior image, is proposed. An optimization problem is formulated in the disentangled latent space of a style-based generative model, and semantically meaningful constraints are imposed using the disentangled latent representation of the prior image. Stable recovery from incomplete measurements with the help of a prior image is theoretically analyzed. Numerical experiments demonstrating the superior performance of our approach as compared to related methods are presented.
An Analysis of the Optimal Control Modification Method Applied to Flutter Suppression

Unlike basic Model Reference Adaptive Control (MRAC)l, Optimal Control Modification (OCM) has been shown to be a promising MRAC modification with robustness and analytical properties not present in other adaptive control methods. This paper presents an analysis of the OCM method, and how the asymptotic property of OCM is useful for analyzing and tuning the controller. We begin with a Lyapunov stability proof of an OCM controller having two adaptive gain terms, then the less conservative and easily analyzed OCM asymptotic property is presented. Two numerical examples are used to show how this property can accurately predict steady state stability and quantitative robustness in the presence of time delay, and relative to linear plant perturbations, and nominal Loop Transfer Recovery (LTR) tuning. The asymptotic property of the OCM controller is then used as an aid in tuning the controller applied to a large scale aeroservoelastic longitudinal aircraft model for flutter suppression. Control with OCM adaptive augmentation is shown to improve performance over that of the nominal non-adaptive controller when significant disparities exist between the controller/observer model and the true plant model.
Dot-Projection Photogrammetry and Videogrammetry of Gossamer Space Structures

The technique of using hundreds or thousands of projected dots of light as targets for photogrammetry and videogrammetry of gossamer space structures is documented. Photogrammetry calculates the three-dimensional coordinates of each target on the structure, and videogrammetry tracks the coordinates vs time. Gossamer structures characteristically contain large areas of delicate, thin-film membranes. Examples include solar sails, large antennas, inflatable solar arrays, solar-power concentrators and transmitters, sun shields, and planetary balloons and habitats. Using projected-dot targets avoids the unwanted mass, stiffness, and installation costs of traditional retroreflective adhesive targets. Four laboratory applications are covered that demonstrate the practical effectiveness of white-light dot projection for both static-shape and dynamic measurement of reflective and diffuse surfaces, respectively. Comparisons are made between dot-projection videogrammetry and traditional laser vibrometry for membrane vibration measurements. A promising extension of existing techniques using a novel laser-induced fluorescence approach is introduced.