cssi/SciSciGPT-SciSciNet huggingface dataset:
Skewness, short interest and the efficiency of stock prices

ABSTRACTWe examine the association between return skewness, short interest and the efficiency of stock prices. Since preferences for skewness have been shown to impact asset prices, we examine how skewness relates to market efficiency. We find that stocks with positive skewness are less efficient, which might be explained by investor preferences for positive skewness. Next, we document that short interest reduces both total skewness and idiosyncratic skewness. Finally, while research has shown that short selling can improve the efficiency of markets generally, we show that short interest’s ability to improve market efficiency is strongest in stocks with the highest skewness.
Pervasive Computing: Embedding the Public Sphere

Pervasive Computing (PerC) is what happens when the Internet gets ubiquitous, embedded, and animated. Ubiquitous access to the Internet through mobile, wireless devices is imminent. More important and less understood, the Internet will soon invade real space as networked computing elements become embedded into physical objects and environments. Through this implantation, the physical world will gain digital qualities, such as computer addressability through unique identification codes. Since these elements can also be animated, the environment will be able to respond directly to what it senses. PerC will profoundly alter the construction and experience of the public sphere. As a case study, we (one of us from law, the other architecture) focus on what it might do to the shopping mall. After examining two possible scenarios, called smooth and friction malls, we tease out four basic design principles of privacy, transparency, open access, and publicity. Our recommendation is to embed these public sphere qualities into PerC as PerC is being embedded into the public sphere.
Bread for the Poor: Access to Justice and the Rights of the Needy in India

†India is rightly acclaimed for achieving a flourishing constitutional order, presided over by an inventive and activist judiciary, aided by a proficient bar, supported by the state and cherished by the public. At the same time, the courts and tribunals where ordinary Indians might go for remedy and protection are beset with massive problems of delay, cost, and ineffectiveness. Potential users avoid the courts; in spite of a longstanding reputation for litigiousness, existing evidence suggests that Indians avail themselves of the courts at a low rate and the rate seems to be falling. 1 Still, the courts remain gridlocked. 2
A Rejoinder To The Rejoinder To On The Theory Class's Theories of Asbestos Litigation

This short essay is a partial response to an essay by Professor Charles Silver contesting assertions I set forth in an article titled, "On The Theory Class's Theories of Asbestos Litigation: The Disconnect Between Scholarship and Reality", 31 Pepp. L. Rev. 33 (2003-04), in which I responded to several personal attacks against me by Professor Silver. Since Professor Silver was permitted to substantially add to his essay after I submitted my Rejoinder and I was not provided with these extensive additions, my response is necessarily incomplete. Professor Silver's essay is titled, "A Rejoinder to Lester Brickman", 32 Pepp. L. Rev. 765 (2005). In this exchange on the academic field of battle, bluster meets fact in a head-on-clash. This mictuating match has two redeeming features. One is a discussion of the obligation of an academic, in relation to scholarship, to disclose any personal interest such as a retained advocacy relationship. I favor such disclosure; Professor Silver did not. In addition, there is a brief discussion of the role of the law professor within the legal profession. Professor Silver advances the view that law professors' self-interest should lead them to hold pro-lawyer views and they should therefore not criticize the legal profession because that contributes to the low public esteem in which the bar is held. I demur. In my view, that low esteem is not due to criticisms of various practices of lawyers and the bar but rather to the failure of the bar to curb abuses and to thus enforce its own standard set forth in the Preamble to the Model Rules of Professional Conduct that the bar should act "in the public interest and not in furtherance of [its] parochial self-interested concerns. . . ."
Fairness, Reciprocity, and Wage Rigidity

This paper contains a review of work on wage rigidity. The work includes field studies, and economic experiments, and psychological surveys. Economists have done the field studies and experiments, and management scientists and experimental psychologists have done the surveys.
The effect of management team characteristics on risk-taking and style extremity of mutual fund portfolios

Abstract This paper investigates the effect of management team-level characteristics on portfolio risk and style extremity using a unique dataset of 1678 mutual fund managers. Results show that teams with more members, longer tenure, and more members with graduate business training hold less risky portfolios. The opposite is true for teams whose members engage in side-by-side management; that is, they manage multiple funds simultaneously. Member diversity is related to less extreme style decisions. These findings have important implications for fund management companies as they make decisions about the composition of management teams as well as for individual investors’ investment allocation decisions.
Quantum Field Theory as Manifestation of Self-Organized Criticality

Self-organized criticality (SOC) reflects the ability of many complex dynamical systems to self-sustain critical behavior outside equilibrium. Here we provide analytic evidence that quantum field propagators and the probability distribution of SOC share a common foundation. In particular, we find that the formal structure of quantum propagators replicates the finite scaling ansatz (FSS) of SOC, which is a generic paradigm for the emergence of complexity in Nature.
Fusing a Bayesian Case Velocity Model with Random Forest for Predicting COVID-19 in the U.S.

Background: Predictions of COVID-19 case growth and mortality are critical to the decisions of political leaders, businesses, and individuals grappling with the pandemic. This predictive task is challenging due to the novelty of the virus, limited data, and dynamic political and societal responses. Methods: We embed a Bayesian nonlinear mixed model and a random forest algorithm within an epidemiological compartmental model for empirically grounded COVID-19 predictions. The Bayesian case model fits a location-specific curve to the velocity (first derivative) of the transformed cumulative case count, borrowing strength across geographic locations and incorporating prior information to obtain a posterior distribution for case trajectory. The compartmental model uses this distribution and predicts deaths using a random forest algorithm trained on COVID-19 data and population-level characteristics, yielding daily projections and interval estimates for infections and deaths in U.S. states. We evaluate forecasting accuracy on a two-week holdout set. Findings: The model predicts COVID-19 cases and deaths well, with a mean absolute scaled error of 0.40 for cases and 0.32 for deaths throughout the two-week evaluation period. The substantial variation in predicted trajectories and associated uncertainty between states is illustrated by comparing three unique locations: New York, Ohio, and Mississippi. Interpretation: The sophistication and accuracy of this COVID-19 model offer reliable predictions and uncertainty estimates for the current trajectory of the pandemic in the U.S. and provide a platform for future predictions as shifting political and societal responses alter its course. Funding Statement: Research partially supported by unrestricted grants from Private Health Management. Declaration of Interests: GLW, JAZ, PS, TB, and MAS report personal fees from Private Health Management during the conduct of the study. CMR reports grants and personal fees from Private Health Management. MAS also reports grants from US National Institutes of Health, grants from IQVIA, and personal fees from Janssen Research and Development. All other authors declare no competing interests.
The Cash-Flow Permanence and Information Content of Dividend Increases Versus Repurchases

Abstract We hypothesize that firms choose dividend increases to distribute relatively permanent cash-flow shocks and repurchases to distribute more transient shocks. As predicted, we find that post-shock cash flows of dividend increasing firms exhibit less reversion to pre-shock levels compared with repurchasing firms. We also examine whether the stock market uses the announcement of the payout method to update its beliefs about the permanence of cash-flow shocks. Controlling for payout size and the market's expectation about the permanence of the cash-flow shock, the stock price reaction to dividend increases is more positive than the reaction to repurchases.
Seasonality, Cost Shocks, and the Production Smoothing Model of Inventories

A great deal of research on the empirical behavior of inventories examines some variant of the production smoothing model of finished goods inventories. The overall assessment of this model that exists in the literature is quite negative: there is little evidence that manufacturers hold inventories of finished goods in order to smooth production patterns.
Trust, risk and betrayal

Abstract Using experiments, we examine whether the decision to trust a stranger in a one-shot interaction is equivalent to taking a risky bet, or if a trust decision entails an additional risk premium to balance the costs of trust betrayal. We compare a binary-choice Trust game with a structurally identical, binary-choice Risky Dictator game offering a good or a bad outcome. We elicit individuals’ minimum acceptable probabilities (MAPs) of getting the good outcome such that they would prefer the gamble to the sure payoff. First movers state higher MAPs in the Trust game than in situations where nature determines the outcome.
Stop Federalism Before It Kills Again: Reflections on Hurricane Katrina

Hurricane Katrina operated like a CT or MRI scan on governance in the United States and the results were not pretty. It is widely agreed that our separated system of federal, state, and local jurisdictions did not work together and did not work well. In this short article, I first survey the harm done by our federal system, then offer some historical perspective on what went wrong, and finally try to analyze what, if anything, we can learn from this experience.
Pseudo-Linear Time-Invariant Magnetless Circulators Based on Differential Spatiotemporal Modulation of Resonant Junctions

In this paper, we present voltage-mode and current-mode differential magnetless nonreciprocal devices obtained by pairing two single-ended (SE) circulators, each consisting of three first-order bandpass or bandstop LC filters, connected in either a wye or a delta topology. The resonant poles of each SE circulator are modulated in time with 120° phase-shifted periodic signals, resulting in synthetic angular-momentum biasing achieved through spatiotemporal modulation (STM). We tailor the two SE circulators to exhibit a constant 180° phase difference between their STM biases. Unlike conventional differential time-variant circuits, for which only the even or odd spurs are rejected, we show that the proposed configuration cancels out all intermodulation products, thus making them operate alike linear time-invariant (LTI) circuits for an external observer. In turn, this property enhances all metrics of the resulting circulator, overcoming the limitations of SE architectures, and improving insertion loss, impedance matching, bandwidth, and noise figure. We show that this differential architecture also significantly relaxes the required modulation parameters, both in frequency and amplitude. We develop a rigorous small-signal model to guide the design of the proposed circuits and to get insights into their pseudo-LTI characteristics. Then, we validate the theory with simulations and measurements showing remarkable performance compared to the current state-of-the-art of magnetless nonreciprocal devices.
ENVISIONING uHEALTH - An Ontological Framework

Ubiquitous health care (uHealth) is becoming feasible today, more so than ever before, due to rapid advances in information technology. We can glimpse its possibilities in the care of the wounded in war and the diagnosis and treatment of diseases from a distance. However, the visions of uHealth are many and partial, ill-defined and unclear. We present a set of four ontologies to envision uHealth systemically. The ontologies deconstruct uHealth into spatial, temporal, and semiotic ubiquity. Each aspect of ubiquity is further deconstructed into three components. These ontologies can be used to construct a comprehensive natural-language narrative of uHealth. They can also be used to (a) map the states-of-the-potential, -art, and -practice of uHealth, and (b) systematically design the trajectory for the transformation to uHealth.
Nonlinear price evolution

The neoclassical price adjustment equation stipulates that prices move toward equilibrium at a rate that is proportional to the excess demand, i.e., the difference between the demand and supply divided by the demand (at that price). However, the demand and supply are generally nonlinear functions of price. We show that the information on this nonlinear variation of demand and supply leads to a more accurate description of price evolution toward equilibrium. With this additional information the optimal forecast for the price of the good or asset is given by a nonlinear equation. This yields an advantage to traders utilizing all of the available information on supply and demand functions, rather than simply the value at the current price.
Were Ancestral Proteins Less Specific

Some have hypothesized that ancestral proteins were, on average, less specific than their descendants. If true, this would provide a universal axis along which to organize protein evolution and suggests that reconstructed ancestral proteins may be uniquely powerful tools for protein engineering. Ancestral sequence reconstruction studies are one line of evidence used to support this hypothesis. Previously, we performed such a study, investigating the evolution of peptide binding specificity for the paralogs S100A5 and S100A6. The modern proteins appeared more specific than their last common ancestor (ancA5/A6), as each paralog bound a subset of the peptides bound by ancA5/A6. In the current study, we revisit this transition, using quantitative phage display to measure the interactions of 30,533 random peptides with human S100A5, S100A6, and ancA5/A6. This unbiased screen reveals a different picture. While S100A5 and S100A6 do indeed bind to a subset of the peptides recognized by ancA5/A6, they also acquired new peptide partners outside of the set recognized by ancA5/A6. Our previous work showed that ancA5/A6 had lower specificity than its descendants when measured against biological targets; our new work shows that ancA5/A6 has similar specificity to the modern proteins when measured against a random set of peptide targets. This demonstrates that altered biological specificity does not necessarily indicate altered intrinsic specificity, and sounds a cautionary note for using ancestral reconstruction studies with biological targets as a means to infer global evolutionary trends in specificity.
Reference Dependent Prices in Bargaining: An Experimental Examination of Precise First Offers

Abstract Evidence from psychology and marketing suggests that those who make a “precise” first offer in bargaining get a better deal than those who make a “round” first offer. We report on a series of experiments designed to test for and improve our understanding of the “precise first offer” (PFO) effect in bargaining and whether it likely reflects rational optimizing or equilibrium behavior. Our experiment varies whether decisions are incentivized and whether the PFO effect can emerge as an equilibrium of a cheap-talk signaling game. We find evidence of a PFO effect when subjects read a vignette and make unincentivized individual decisions. When monetary incentives are added to the vignette, we still find the PFO effect, but it is not robust. In a bilateral bargaining situation with a cheap-talk equilibrium, we can not find the PFO effect, which is inconsistent with the equilibrium predictions. Moreover, the PFO effect reemerges in a setting in which initial offers are generated by a random device and thus provides a strong refutation of the signaling model. Our evidence suggests that optimizing and equilibrium accounts of the PFO effect are inadequate. Understanding initial offers as reference points, which subtly change perceptions about the kinds of acceptable counteroffers, provides a plausible account of a new finding on which prior explanations are silent: precise offers induce more precise counteroffers.
Federated Bandit: A Gossiping Approach

In this paper, we study Federated Bandit, a decentralized Multi-Armed Bandit problem with a set of N agents, who can only communicate their local data with neighbors described by a connected graph G. Each agent makes a sequence of decisions on selecting an arm from M candidates, yet they only have access to local and potentially biased feedback/evaluation of the true reward for each action taken. Learning only locally will lead agents to sub-optimal actions while converging to a no-regret strategy requires a collection of distributed data. Motivated by the proposal of federated learning, we aim for a solution with which agents will never share their local observations with a central entity, and will be allowed to only share a private copy of his/her own information with their neighbors. We first propose a decentralized bandit algorithm \textttGossip\_UCB, which is a coupling of variants of both the classical gossiping algorithm and the celebrated Upper Confidence Bound (UCB) bandit algorithm. We show that \textttGossip\_UCB successfully adapts local bandit learning into a global gossiping process for sharing information among connected agents, and achieves guaranteed regret at the order of O(\max\ \textttpoly (N,M) log T, \textttpoly (N,M)log_lambda_2^-1 N\ ) for all N agents, where lambda_2\in(0,1) is the second largest eigenvalue of the expected gossip matrix, which is a function of G. We then propose \textttFed\_UCB, a differentially private version of \textttGossip\_UCB, in which the agents preserve e-differential privacy of their local data while achieving O(\max \\frac\textttpoly (N,M) e log^2.5 T, \textttpoly (N,M) (log_lambda_2^-1 N + log T) \ ) regret.
A note on congruences for weakly holomorphic modular forms

Let $O_L$ be the ring of integers of a number field $L$. Write $q = e^{2 \pi i z}$, and suppose that $$f(z) = \sum_{n \gg - \infty}^{\infty} a_f(n) q^n \in M_{k}^{!}(\operatorname{SL}_2(\mathbb{Z})) \cap O_L[[q]]$$ is a weakly holomorphic modular form of even weight $k \leq 2$. We answer a question of Ono by showing that if $p \geq 5$ is prime and $ 2-k = r(p-1) + 2 p^t$ for some $r \geq 0$ and $t > 0$, then $a_f(p^t) \equiv 0 \pmod p$. For $p = 2,3,$ we show the same result, under the condition that $2 - k - 2 p^t$ is even and at least $4$. This represents the "missing case" of a theorem proved by Jin, Ma, and Ono.
Flavor-Dependent Radiative Corrections in Coherent Elastic Neutrino-Nucleus Scattering

We calculate coherent elastic neutrino-nucleus scattering cross sections on spin-0 nuclei (e.g. 40Ar and 28Si) at energies below 100 MeV within the Standard Model and account for all effects of permille size. We provide a complete error budget including uncertainties at nuclear, nucleon, hadronic, and quark levels separately as well as perturbative error. Our calculation starts from the four-fermion effective field theory to explicitly separate heavy-particle mediated corrections (which are absorbed by Wilson coefficients) from light-particle contributions. Electrons and muons running in loops introduce a non- trivial dependence on the momentum transfer due to their relatively light masses. These same loops, and those mediated by tau leptons, break the flavor universality because of mass-dependent electromagnetic radiative corrections. Nuclear physics uncertainties significantly cancel in flavor asymmetries resulting in subpercent relative errors. We find that for low neutrino energies, the cross section can be predicted with a relative precision that is competitive with neutrino-electron scattering. We highlight potentially useful applications of such a precise cross section prediction ranging from precision tests of the Standard Model, to searches for new physics and to the monitoring of nuclear reactors.
Delay-induced uncertainty for a paradigmatic glucose-insulin model.

Medical practice in the intensive care unit is based on the assumption that physiological systems such as the human glucose–insulin system are predictable. We demonstrate that delay within the glucose–insulin system can induce sustained temporal chaos, rendering the system unpredictable. Specifically, we exhibit such chaos for the ultradian glucose–insulin model. This well-validated, finite-dimensional model represents feedback delay as a three-stage filter. Using the theory of rank one maps from smooth dynamical systems, we precisely explain the nature of the resulting delay-induced uncertainty (DIU). We develop a framework one may use to diagnose DIU in a general oscillatory dynamical system. For infinite-dimensional delay systems, no analog of the theory of rank one maps exists. Nevertheless, we show that the geometric principles encoded in our DIU framework apply to such systems by exhibiting sustained temporal chaos for a linear shear flow. Our results are potentially broadly applicable because delay is ubiquitous throughout mathematical physiology.
Factors driving availability of COVID-19 convalescent plasma: Insights from a demand, production, and supply model.

Background COVID-19 Convalescent Plasma (CCP) is a promising treatment for COVID-19. Blood collectors have rapidly scaled up collection and distribution programs. Methods We developed a detailed simulation model of CCP donor recruitment, collection, production, and distribution processes. We ran our model using varying epidemic trajectories from 11 U.S. states and with key input parameters drawn from wide ranges of plausible values to identify key drivers of ability to scale collections capacity and meet demand for CCP. Results Utilization of available CCP collections capacity followed increases in COVID-19 hospital discharges with a lag. Utilization never exceeded 75% of available capacity in most simulations. Demand was met for most of the simulation period in most simulations, but a substantial portion of demand went unmet during early, sharp increases in hospitalizations. For epidemic trajectories that included multiple epidemic peaks, second wave demand could generally be met due to stockpiles established during the decline from an earlier peak. Apheresis machine capacity (number of machines) and probability that COVID-19 recovered individuals are willing to donate were the most important supply-side drivers of ability to meet demand. Recruitment capacity was important in states with early peaks. Conclusions Epidemic trajectory was the most important determinant of ability to meet demand for CCP, although our simulations revealed several contributing operational drivers of CCP program success.
Dynamical Combinatorics and Torsion Classes

Abstract For finite semidistributive lattices the map κ gives a bijection between the sets of completely join-irreducible elements and completely meet-irreducible elements. Here we study the κ-map in the context of torsion classes. It is well-known that the lattice of torsion classes for an artin algebra is semidistributive, but in general it is far from finite. We show the κ-map is well-defined on the set of completely join-irreducible elements, even when the lattice of torsion classes is infinite. We then extend κ to a map on torsion classes which have canonical join representations given by the special torsion classes associated to the minimal extending modules introduced by the first and third authors and A. Carroll in 2019. For hereditary algebras, we show that the extended κ-map on torsion classes is essentially the same as Ringel's ϵ-map on wide subcategories. Also in the hereditary case, we relate the square of κ to the Auslander-Reiten translation.
An initial exploration of Bayesian model calibration for estimating the composition of rocks and soils on Mars

The Mars Curiosity rover carries an instrument, ChemCam, designed to measure the composition of surface rocks and soil using laser-induced breakdown spectroscopy (LIBS). The measured spectra from this instrument must be analyzed to identify the component elements in the target sample, as well as their relative proportions. This process, which we call disaggregation, is complicated by so-called matrix effects, which describe nonlinear changes in the relative heights of emission lines as an unknown function of composition due to atomic interactions within the LIBS plasma. In this work we explore the use of the plasma physics code ATOMIC, developed at Los Alamos National Laboratory, for the disaggregation task. ATOMIC has recently been used to model LIBS spectra and can robustly reproduce matrix effects from first principles. The ability of ATOMIC to predict LIBS spectra presents an exciting opportunity to perform disaggregation in a manner not yet tried in the LIBS community, namely via Bayesian model calibration. However, using it directly to solve our inverse problem is computationally intractable due to the large parameter space and the computation time required to produce a single output. Therefore we also explore the use of emulators as a fast solution for this analysis. We discuss a proof of concept Gaussian process emulator for disaggregating two-element compounds of sodium and copper. The training and test datasets were simulated with ATOMIC using a Latin hypercube design. After testing the performance of the emulator, we successfully recover the composition of 25 test spectra with Bayesian model calibration.
Mechanics informed fluoroscopy of esophageal transport

Fluoroscopy is a radiographic procedure for evaluating esophageal disorders such as achalasia, dysphasia and gastroesophageal reflux disease. It performs dynamic imaging of the swallowing process and provides anatomical detail and a qualitative idea of how well swallowed fluid is transported through the esophagus. In this work, we present a method called mechanics informed fluoroscopy (FluoroMech) that derives patient-specific quantitative information about esophageal function. FluoroMech uses a convolutional neural network to perform segmentation of image sequences generated from the fluoroscopy, and the segmented images become input to a one-dimensional model that predicts the flow rate and pressure distribution in fluid transported through the esophagus. We have extended this model to identify and estimate potential physiomarkers such as esophageal wall stiffness and active relaxation ahead of the peristaltic wave in the esophageal musculature. FluoroMech requires minimal computational time and hence can potentially be applied clinically in the diagnosis of esophageal disorders.
On Coding Over Sliced Information

The interest in channel models in which the data is sent as an unordered set of binary strings has increased lately, due to emerging applications in DNA storage, among others. In this paper we analyze the minimal redundancy of binary codes for this channel under substitution errors, and provide several constructions, some of which are shown to be asymptotically optimal up to constants. The surprising result in this paper is that while the information vector is sliced into a set of unordered strings, the amount of redundant bits that are required to correct errors is order-wise equivalent to the amount required in the classical error correcting paradigm.
The Aggravating Duty of Non-Aggravation

International law's duty of non-aggravation requires states to avoid actions that might inflame an international dispute, both to maintain international peace and to preserve the effectiveness of judicial or arbitral proceedings. Yet parties on the receiving end of calls for non-aggravation --whether from the Security Council or at ribunal -- have little idea of what conduct they are expected to avoid. This state of affairs is most unfortunate in light of the centrality of this norm to the peaceful resolution of disputes and, in particular, examples of seemingly provocative and aggravating acts in recent years. This article attempts to give some meaning to this important, but frustratingly vague, norm of international law. After reviewing current understandings of the duty by political and judicial bodies, it justifies the need for a more specific understanding of non-aggravation. It then develops a set of criteria to distinguish aggravating from non-aggravating acts, a process informed by both existing expectations and the underlying purposes of the norm. Based on these criteria, the article offers a coding scheme of presumptively aggravating and non-aggravating acts. Beyond its relevance for decision makers, the article seeks to encourage theoretical inquiry into the advantages and disadvantages of vague (or underspecified) norms in the international legal order.
Simultaneous robust subspace recovery and semi-stability of quiver representations

Abstract We consider the problem of simultaneously finding lower-dimensional subspace structures in a given m-tuple ( X 1 , … , X m ) of possibly corrupted, high-dimensional data sets all of the same size. We refer to this problem as simultaneous robust subspace recovery (SRSR) and provide a quiver invariant theoretic approach to it. We show that SRSR is a particular case of the more general problem of effectively deciding whether a quiver representation is semi-stable (in the sense of Geometric Invariant Theory) and, in case it is not, finding a subrepresentation certifying in an optimal way that the representation is not semi-stable. In this paper, we show that SRSR and the more general quiver semi-stability problem can be solved effectively.
Ice, glass, and solid phases in artificial spin systems with quenched disorder

We present a numerical study on a disordered artificial spin-ice system, which interpolates between the long-range ordered square ice and the fully degenerate shakti ice. Starting from the square-ice geometry, disorder is implemented by adding vertical/horizontal magnetic islands to the center of some randomly chosen square plaquettes of the array at different densities. When no island is added, we have ordered square ice. When all square plaquettes have been modified, we obtain shakti ice, which is disordered yet in a topological phase corresponding to the Rys F-model. In between, geometrical frustration due to these additional center spins disrupts the long-range Ising order of square ice, giving rise to a spin-glass regime at low temperatures. The artificial spin system proposed in our work provides an experimental platform to study the interplay between quenched disorder and geometrical frustration.
Am I on Track? Evaluating Patient-Specific Weight Loss After Bariatric Surgery Using an Outcomes Calculator

Individual weight loss outcomes after bariatric surgery can vary considerably. As a result, identifying and assisting patients who are not on track to reach their weight loss goals can be challenging. Using a bariatric surgery outcomes calculator, which was formulated using a state-wide bariatric-specific data registry, predicted weight loss at 1 year after surgery was calculated on 658 patients who underwent bariatric surgery at 35 different bariatric surgery programs between 2015 and 2017. Patient characteristics, postoperative complications, and weight loss trajectories were compared between patients who met or exceeded their predicted weight loss calculation to those who did not based on observed to expected weight loss ratio (O:E) at 1 year after surgery. Patients who did not meet their predicted weight loss at 1 year (n = 237, 36%) had a mean O:E of 0.71, while patients who met or exceeded their prediction (n = 421, 63%) had a mean O:E = 1.14. At 6 months, there was a significant difference in the percent of the total amount of predicted weight loss between the groups (88% of total predicted weight loss for those that met their 1-year prediction vs 66% for those who did not, p < 0.0001). Age, gender, procedure type, and risk-adjusted complication rates were similar between groups. Using a bariatric outcomes calculator can help set appropriate weight-loss expectations after surgery and also identify patients who may benefit from additional therapy prior to reaching their weight loss nadir.
QWIRE Practice: Formal Verification of Quantum Circuits in Coq

We describe an embedding of the QWIRE quantum circuit language in the Coq proof assistant. This allows programmers to write quantum circuits using high-level abstractions and to prove properties of those circuits using Coq's theorem proving features. The implementation uses higher-order abstract syntax to represent variable binding and provides a type-checking algorithm for linear wire types, ensuring that quantum circuits are well-formed. We formalize a denotational semantics that interprets QWIRE circuits as superoperators on density matrices, and prove the correctness of some simple quantum programs.
LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

Image-based fiducial markers are useful in problems such as object tracking in cluttered or textureless environments, camera (and multi-sensor) calibration tasks, and vision-based simultaneous localization and mapping (SLAM). The state-of-the-art fiducial marker detection algorithms rely on the consistency of the ambient lighting. This article introduces LiDARTag, a novel fiducial tag design and detection algorithm suitable for light detection and ranging (LiDAR) point clouds. The proposed method runs in real-time and can process data at 100 Hz, which is faster than the currently available LiDAR sensor frequencies. Because of the LiDAR sensors’ nature, rapidly changing ambient lighting will not affect the detection of a LiDARTag; hence, the proposed fiducial marker can operate in a completely dark environment. In addition, the LiDARTag nicely complements and is compatible with existing visual fiducial markers, such as AprilTags, allowing for efficient multi-sensor fusion and calibration tasks. We further propose a concept of minimizing a fitting error between a point cloud and the marker's template to estimate the marker's pose. The proposed method achieves millimeter error in translation and a few degrees in rotation. Due to LiDAR returns’ sparsity, the point cloud is lifted to a continuous function in a reproducing kernel Hilbert space where the inner product can be used to determine a marker's ID. The experimental results, verified by a motion capture system, confirm that the proposed method can reliably provide a tag's pose and unique ID code. The rejection of false positives is validated on the Google Cartographer indoor dataset and the Honda H3D outdoor dataset. All implementations are coded in C++ and are available at https://github.com/UMich-BipedLab/LiDARTag .
alms1 mutant zebrafish do not show hair cell phenotypes seen in other cilia mutants

Multiple cilia-associated genes have been shown to affect hair cells in zebrafish (Danio rerio), including the human deafness gene dcdc2, the radial spoke gene rsph9, and multiple intraflagellar transport (IFT) and transition zone genes. Recently a zebrafish alms1 mutant was generated. The ALMS1 gene is the gene mutated in the ciliopathy Alstrom Syndrome a disease that causes hearing loss among other symptoms. The hearing loss seen in Alstrom Syndrome may be due in part to hair cell defects as Alms1 mutant mice show stereocilia polarity defects and a loss of hair cells. Hair cell loss is also seen in postmortem analysis of Alstrom patients. The zebrafish alms1 mutant has metabolic defects similar to those seen in Alstrom syndrome and Alms1 mutant mice. We wished to investigate if it also had hair cell defects. We, however, failed to find any hair cell related phenotypes in alms1 mutant zebrafish. They had normal lateral line hair cell numbers as both larvae and adults and normal kinocilia formation. They also showed grossly normal swimming behavior, response to vibrational stimuli, and FM1-43 loading. Mutants also showed a normal degree of sensitivity to both short-term neomycin and long-term gentamicin treatment. These results indicate that cilia-associated genes differentially affect different hair cell types.
Weinberg’s Proposal of 1990: A Very Personal View

My personal encounter with Weinberg’s proposal of 1990 was a really entertaining one: My collaborator David Entem and I had embarked to show that Weinberg’s idea, though smart and beautiful, was essentially useless in practice (like so many of those genius ideas of the 1980s where people claimed to have “derived the nuclear force from QCD”). However, in trying to do so, we showed the opposite; namely, we showed that Weinberg’s idea worked better than allowed by any reasonable means.
Sexually divergent cortical control of affective-autonomic integration.

Abstract Depression and cardiovascular disease reduce quality of life and increase mortality risk. These conditions commonly co-occur with sex-based differences in incidence and severity. However, the biological mechanisms linking the disorders are poorly understood. In the current study, we hypothesized that the infralimbic (IL) prefrontal cortex integrates mood-related behaviors with the cardiovascular burden of chronic stress. In a rodent model, we utilized optogenetics during behavior and in vivo physiological monitoring to examine how the IL regulates affect, social motivation, neuroendocrine-autonomic stress reactivity, and the cardiac consequences of chronic stress. Our results indicate that IL glutamate neurons increase socio-motivational behaviors specifically in males. IL activation also reduced endocrine and cardiovascular stress responses in males, while increasing reactivity in females. Moreover, prior IL stimulation protected males from subsequent chronic stress-induced sympatho-vagal imbalance and cardiac hypertrophy. Our findings suggest that cortical regulation of behavior, physiological stress responses, and cardiovascular outcomes fundamentally differ between sexes.
Zilch: A Framework for Deploying Transparent Zero-Knowledge Proofs

As cloud computing becomes more popular, research has focused on usable solutions to the problem of verifiable computation (VC), where a computationally weak device (Verifier) outsources a program execution to a powerful server (Prover) and receives guarantees that the execution was performed faithfully. A Prover can further demonstrate knowledge of a secret input that causes the Verifier’s program to satisfy certain assertions, without ever revealing which input was used. State-of-the-art Zero-Knowledge Proofs of Knowledge (ZKPK) methods encode a computation using arithmetic circuits and preserve the privacy of Prover’s inputs while attesting the integrity of program execution. Nevertheless, developing, debugging, and optimizing programs as circuits remains a daunting task, as most users are unfamiliar with this programming paradigm. In this work, we present Zilch, a framework that accelerates and simplifies the deployment of VC and ZKPK for any application transparently , i.e., without the need of trusted setup. Zilch uses traditional instruction sequences rather than static arithmetic circuits that would need to be regenerated for each different computation. Towards that end, we have implemented Z MIPS: a MIPS-like processor model that allows verifying each instruction independently and compose a proof for the execution of the target application. To foster usability, Zilch incorporates a novel cross-compiler from an object-oriented Java-like language tailored to ZKPK and optimized our Z MIPS model, as well as a powerful API that enables integration of ZKPK within existing C/C++ programs. In our experiments, we demonstrate the flexibility of Zilch using two real-life applications, and evaluate Prover and Verifier performance on a variety of benchmarks.
General Control Functions for Causal Effect Estimation from Instrumental Variables.

Causal effect estimation relies on separating the variation in the outcome into parts due to the treatment and due to the confounders. To achieve this separation, practitioners often use external sources of randomness that only influence the treatment called instrumental variables (IVs). We study variables constructed from treatment and IV that help estimate effects, called control functions. We characterize general control functions for effect estimation in a meta-identification result. Then, we show that structural assumptions on the treatment process allow the construction of general control functions, thereby guaranteeing identification. To construct general control functions and estimate effects, we develop the general control function method (GCFN). GCFN’s first stage called variational decoupling (VDE) constructs general control functions by recovering the residual variation in the treatment given the IV. Using VDE’s control function, GCFN’s second stage estimates effects via regression. Further, we develop semi-supervised GCFN to construct general control functions using subsets of data that have both IV and confounders observed as supervision; this needs no structural treatment process assumptions. We evaluate GCFN on low and high dimensional simulated data and on recovering the causal effect of slave export on modern community trust [30].
On Ramanujan sums of a real variable and a new Ramanujan expansion for the divisor function

We show that the absolute convergence of a Ramanujan expansion does not guarantee the convergence of its real variable generalization, which is obtained by replacing the integer argument in the Ramanujan sums with a real number. We also construct a new Ramanujan expansion for the divisor function. While our expansion is amenable to a continuous and absolutely convergent real variable generalization, it only interpolates the divisor function locally on $${\mathbb {R}}$$ .
Non-Resident Holdings of Domestic Debt in Nigeria: Internal or External Driven?

Foreign holdings of domestic debt instruments in Nigeria have been increasing. Using data over 2007M1-2019M1, we show that, on average, global factors (global interest rates, oil prices) seem to carry more weight than domestic factors (treasury bills rate and domestic risk) in foreign portfolio invetsors' decisions in Nigeria. Specifically, we show that foreign participation is, in the long run, positively correlated with oil prices and profitable rates of return on local-currency instruments, but negatively correlated with exchange rate depreciation pressures. In the short run, oil prices, opportunity cost of funds and perception of Nigeria-specific risks also play a role. These results highlight the volatile short-term nature of such flows and call for a package of policy reforms to attract longer term direct investments.
An Inquisitive Code Editor for Addressing Novice Programmers' Misconceptions of Program Behavior

Novice programmers face numerous barriers while attempting to learn how to code that may deter them from pursuing a computer science degree or career in software development. In this work, we propose a tool concept to address the particularly challenging barrier of novice programmers holding misconceptions about how their code behaves. Specifically, the concept involves an inquisitive code editor that: (1) identifies misconceptions by periodically prompting the novice programmer with questions about their program's behavior, (2) corrects the misconceptions by generating explanations based on the program's actual behavior, and (3) prevents further misconceptions by inserting test code and utilizing other educational resources. We have implemented portions of the concept as plugins for the Atom code editor and conducted informal surveys with students and instructors. Next steps include deploying the tool prototype to students enrolled in introductory programming courses.
On Convergence of the Cavity and Bolthausen’s TAP Iterations to the Local Magnetization

The cavity and TAP equations are high-dimensional systems of nonlinear equations of the local magnetization in the Sherrington–Kirkpatrick model. In the seminal work, Bolthausen (Commun Math Phys 325(1):333–366, 2014) introduced an iterative scheme that produces an asymptotic solution to the TAP equations if the model lies inside the Almeida–Thouless transition line. However, it was unclear if this asymptotic solution coincides with the local magnetization. In this work, motivated by the cavity equations, we introduce a new iterative scheme and establish a weak law of large numbers. We show that our new scheme is asymptotically the same as the so-called approximate message passing algorithm, a generalization of Bolthausen’s iteration, that has been popularly adapted in compressed sensing, Bayesian inferences, etc. Based on this, we confirm that our cavity iteration and Bolthausen’s scheme both converge to the local magnetization as long as the overlap is locally uniformly concentrated.
Perceptual Loss Based Speech Denoising with an Ensemble of Audio Pattern Recognition and Self-Supervised Models

Deep learning based speech denoising still suffers from the challenge of improving perceptual quality of enhanced signals. We introduce a generalized framework called Perceptual Ensemble Regularization Loss (PERL) built on the idea of perceptual losses. Perceptual loss discourages distortion to certain speech properties and we analyze it using six large-scale pre-trained models: speaker classification, acoustic model, speaker embedding, emotion classification, and two self-supervised speech encoders (PASE+, wav2vec 2.0). We first build a strong baseline (w/o PERL) using Conformer Transformer Networks on the popular enhancement benchmark called VCTK-DEMAND. Using auxiliary models one at a time, we find acoustic event and self-supervised model PASE+ to be most effective. Our best model (PERL-AE) only uses acoustic event model (utilizing AudioSet) to outperform state-of-the-art methods on major perceptual metrics. To explore if denoising can leverage full framework, we use all networks but find that our seven-loss formulation suffers from the challenges of Multi-Task Learning. Finally, we report a critical observation that state-of-the-art Multi-Task weight learning methods cannot outperform hand tuning, perhaps due to challenges of domain mismatch and weak complementarity of losses.