cssi/SciSciGPT-SciSciNet huggingface dataset:
Comparative Analysis of Peculiar Type Ia 1991bg-like Supernovae Spectra

Spectroscopic analyses of Type Ia supernovae have shown that there exist four spectroscopic groups—cool, broad line, shallow silicon, and core normal—defined by the widths of the Si II features λ5972 and λ6355. The 1991bg-like SNe Ia are classified as "cool." Cool SNe Ia are dim, undergo a rapid decline in luminosity, and produce significantly less 56Ni than normal Type Ia supernovae. They also have an unusually deep and wide trough in their spectra at around 4200 A and a relatively strong Si II absorption attributed to λ5972. We examine the spectra of supernova (SN) 1991bg and the cool SN 1997cn, SN 1999by, and SN 2005bl using the highly parameterized synthetic spectrum code SYNOW, and we find general agreement with similar spectroscopic studies. Our analysis reveals that this group of supernovae is fairly homogeneous, with many of the blue spectral features well fit by Fe II. The nature of the spectroscopic commonalities and the variations in the class are discussed. Finally, we examine intermediates such as SN 2004eo and discuss the spectroscopic subgroup distribution of Type Ia supernovae.
Subjectivity in developing and validating causal explanations in positivist accounting research

Eliminating alternative causal explanations plays an important role in establishing causality. We analyze two strategies researchers use to eliminate alternatives to their preferred causal explanations: providing persuasive evidence against other plausible explanations and developing a preferred explanation in such a way as to limit the number of alternatives against which evidence needs to be provided. Although positivist accounting research aims at objectivity in the use of these strategies, we argue that subjectivity plays an important role as well. We identify and discuss relatively more objective and more subjective components of these strategies for validating and developing causal explanations.
A note on constant proportion trading strategies

We consider constant proportion (CP) trading strategies when there are multiple underlying securities and use a recently derived expression for the terminal wealth of a CP strategy to address two issues. First, we characterize the performance of a CP strategy relative to the performance of the corresponding buy-and-hold strategy. We then explain the performance of leveraged ETFs which have been criticized for not performing as expected, particularly during the financial crisis of 2008.
An Act for All Contexts: Incorporating the Pregnancy Discrimination Act Into Title IX to Help Pregnant Students Gain and Retain Access to Education

Few would agree that pregnancy discrimination is a tolerable by-product of a modern society. Yet there is at least one segment of society where pregnancy discrimination can thrive - federally funded schools. Even though Title IX was passed in 1972 to bar discrimination in school based on sex, it is quite possible for schools to discriminate based on pregnancy with little impunity. Worse, those who suffer the discrimination cannot sue for the harms they suffered in federal court, nor can they seek monetary redress, even if they were financially harmed by the discrimination. The status of Supreme Court precedent, coupled with the inadequacy of Title IX, makes it difficult for pregnant students to protect themselves from pregnancy discrimination or discourage schools from engaging in the practice. A proactive approach to stemming pregnancy discrimination is crucial for pregnant students, just as it was for working women when Congress passed the Pregnancy Discrimination Act in 1978. Congress should make ending pregnancy discrimination in school a clearly defined goal that is efficient and effective by passing an amendment to Title IX that expressly includes pregnancy discrimination in its prohibition of discrimination based on sex. This article discusses how Supreme Court precedent has coalesced to allow pregnancy discrimination in school to slip through the cracks in Title IX and argues for an amendment similar to the Pregnancy Discrimination Act in Title VII to rectify the problem.
Pay for Banker Performance: Structuring Executive Compensation for Risk Regulation

INTRODUCTION 1206 I. THE BANK CONFIDENCE GAME 1210 A. Bank Runs 1210 B. Deposit Insurance and Banker Moral Hazard 1211 C. Bank Risk Regulation 1214 II. PAY FOR PERFORMANCE AND THE FINANCIAL CRISIS 1216 A. Pay for Performance for Shareholders 1216 B. The Evolution of Incentive Pay for Bankers 1218 C. Banker Pay Preceding the Crisis 1222 D. Post-Crisis Pay Constraints 1224 III. PAYING FOR LESS RISKY PERFORMANCE 1226 A. Inside Debt Compensation 1227 B. Market Discipline through Public Subordinated Debt 1229 C. Features 1232 D. Bank-Level Debt to Counter Corporate Structure Effects 1234 IV. COMPARING OTHER APPROACHES 1241 A. Bhagat and Romano: Long-Term Restricted Stock 1241 B. Bebchuk and Spamann: Paying by the Slice 1244 C. Comparing 1245 V. IMPLEMENTATION 1247 A. Setting Debt–Equity Targets 1248 B. Implementation Incentives 1249 CONCLUSION 1251
Loan Originations and Defaults in the Mortgage Crisis: The Role of the Middle Class

This paper highlights the importance of middle-class and high-FICO borrowers for the mortgage crisis. Contrary to popular belief, which focuses on subprime and poor borrowers, we show that mortgage originations increased for borrowers across all income levels and FICO scores. The relation between mortgage growth and income growth at the individual level remained positive throughout the pre-2007 period. Finally, middle-income, high-income, and prime borrowers all sharply increased their share of delinquencies in the crisis. These results are consistent with a demand-side view, where homebuyers and lenders bought into increasing house values and borrowers defaulted after prices dropped.
REGULATORY FOCUS AND EXECUTIVES' INTENTIONS TO COMMIT THEIR FIRMS TO ENTREPRENEURIAL ACTION

Higgins (1997) suggests that strategic actions are influenced by an individual’s regulatory focus, which consists of two distinct strategic orientations: promotion focus and prevention focus. Using survey data from senior executives of 275 telecommunications firms, we find that entrepreneurial intent is positively correlated with both the promotion focus and the prevention focus of the firm and that the positive correlation between promotion focus and entrepreneurial intent becomes even stronger at higher levels of environmental hostility. In contrast, we find that the positive correlation between prevention focus and entrepreneurial intent weakens and eventually reverses at higher levels of environmental hostility.
Geometrically finite amalgamations of hyperbolic 3-manifold groups are not LERF

We prove that, for any two finite volume hyperbolic $3$-manifolds, the amalgamation of their fundamental groups along any nontrivial geometrically finite subgroup is not LERF. This generalizes the author's previous work on nonLERFness of amalgamations of hyperbolic $3$-manifold groups along abelian subgroups. A consequence of this result is that closed arithmetic hyperbolic $4$-manifolds have nonLERF fundamental groups. Along with the author's previous work, we get that, for any arithmetic hyperbolic manifold with dimension at least $4$, with possible exceptions in $7$-dimensional manifolds defined by the octonion, its fundamental group is not LERF.
Accounting conservatism and board of director characteristics: An empirical analysis

Abstract Using three different measures of conservatism, we document that (i) the percentage of inside directors is negatively related to conservatism, and (ii) the percentage of outside directors’ shareholdings is positively related to conservatism. Our results hold after controlling for industry, firm size, leverage, growth opportunities, institutional ownership, inside director ownership, and unobservable firm characteristics that are stable over time. Overall, the evidence is consistent with accounting conservatism assisting directors in reducing agency costs of firms.
Enforceable Accounting Rules and Income Measurement by Early 20th Century Railroads

We investigate the extent to which income measurement by major early 20th-century U.S. railroads shows evidence of lower income smoothness and increased conservatism following new fixed asset accounting rules issued by the Interstate Commerce Commission (ICC) in 1907 and 1908 and concurrent rate regulation regime shifts. Accounting rules promulgated by the ICC after the Hepburn Act of 1906 are the first accounting rules in U.S. history in which regulators could enforce such rules under federal law to increase compliance. Our samplewide results are more consistent with increased conservatism than with income smoothing. Additional tests indicate these effects are more pronounced for firms subject to more intense rate regulation by the ICC, which suggests that the tie-in between accounting regulation and product/service market regulation influences how managers respond to new accounting rules.
Corporate governance and disclosure: purpose, scope, and limitations

Corporate governance has been the subject of dozens, if not hundreds, of books and articles in legal, accounting, finance, and economic literature since at least 1932. Disclosure has also been the subject of dozens, if not hundreds, of books and articles in legal, accounting, finance, and economic literature, but interest in the subject is a more recent phenomenon. It is important therefore to understand the purpose, scope, limitations, and meaning of corporate governance. It is equally important to understand the purpose, scope, and limitations of the effective transparency of information, i.e., disclosure, for publicly listed companies, including what information is disclosed, how it is disclosed, and why it is disclosed. Therefore, this paper examines the purpose, scope, and limitations of corporate governance and disclosure including what, how, and why information about publicly listed companies is disclosed with the intent of providing a better understanding of corporate governance and disclosure and directions for future research.
A theory of tensor products for module categories for a vertex operator algebra, I

This is the first part in a series of papers developing a tensor product theory for modules for a vertex operator algebra. The goal of this theory is to construct a “vertex tensor category” structure on the category of modules for a suitable vertex operator algebra. The notion of vertex tensor category is essentially a “complex analogue” of the notion of symmetric tensor category, and in fact a vertex tensor category produces a braided tensor category in a natural way. The theory applies in particular to many familiar “rational” vertex operator algebras, including those associated with WZNW models, minimal models and the moonshine module. In this paper (Part I), we introduce the notions ofP(z)- andQ(z)-tensor product, whereP(z) andQ(z) are two special elements of the moduli space of spheres with punctures and local coordinates, and we present the fundamental properties and constructions ofQ(z)-tensor products.
Policy Rules and Economic Performance

Abstract Debates about the conduct of monetary policy have evolved over time from “rules versus discretion” to “policy rules versus constrained discretion.” We propose a metric to evaluate monetary policy rules that are consistent with constrained discretion by calculating quadratic loss ratios, the (inflation plus unemployment) loss in high deviations periods divided by the loss in low deviations periods, with policy rules with higher loss ratios preferred to rules with lower loss ratios. The central results of the paper are (1) economic performance is better in periods of low deviations from policy rule prescriptions than in periods of high deviations from policy rule prescriptions for the vast majority of rules, and (2) rules with larger coefficients on the inflation gap than on the output gap are preferred to rules with larger coefficients on the output gap than on the inflation gap. These results are robust to policy lags between one and two years, different weights on inflation loss than on unemployment loss, various definitions of high and low deviations periods, fixed and time varying neutral real interest rates, fixed and time-varying inflation targets, and measuring economic slack by either the output gap or the unemployment gap. We conclude that (1) the Fed should “constrain” constrained discretion by following a rule that responds more strongly to inflation gaps than to output gaps and (2) this type of rule should be added to the Fed's semi-annual Monetary Policy Report.
Group actions, power mean orbit size, and musical scales

We provide an application of the theory of group actions to the study of musical scales. For any group G, finite G-set S, and real number t, we define the t-power diameter diamt(G,S) to be the size...
In vivo CRISPR Screening Identifies Fli1 as a Transcriptional Safeguard that Restrains Effector CD8 T Cell Differentiation During Infection and Cancer

Improving effector activity of antigen specific T cells is a major goal in cancer immunotherapy. Despite the identification of several effector T cell (TEFF)-driving transcription factors (TF), the transcriptional coordination of TEFF biology remains poorly understood. We developed an in vivo T cell CRISPR screening platform and identified a novel mechanism restraining TEFF biology through the ETS family TF, Fli1. Genetic deletion of Fli1 enhanced TEFF responses without compromising memory or exhaustion precursors. Fli1 restrained TEFF lineage differentiation by binding to cis-regulatory elements of effector-associated genes. Loss of Fli1 increased chromatin accessibility at ETS:RUNX motifs allowing more efficient Runx3-driven TEFF biology. CD8 T cells lacking Fli1 provided substantially better protection against multiple infections and tumors. These data indicate that Fli1 safeguards the developing CD8 T cell transcriptional landscape from excessive ETS:RUNX-driven TEFF cell differentiation. Moreover, genetic deletion of Fli1 improves TEFF differentiation and protective immunity in infections and cancer.
A spatial-temporal graph based hybrid infectious disease model with application to COVID-19

As the COVID-19 pandemic evolves, reliable prediction plays an important role in policymaking The classical infectious disease model SEIR (susceptible-exposed-infectious-recovered) is a compact yet simplistic temporal model The data-driven machine learning models such as RNN (recurrent neural networks) can suffer in case of limited time series data such as COVID-19 In this paper, we combine SEIR and RNN on a graph structure to develop a hybrid spatio-temporal model to achieve both accuracy and efficiency in training and forecasting We introduce two features on the graph structure: node feature (local temporal infection trend) and edge feature (geographic neighbor effect) For node feature, we derive a discrete recursion (called I-equation) from SEIR so that gradient descend method applies readily to its optimization For edge feature, we design an RNN model to capture the neighboring effect and regularize the landscape of loss function so that local minima are effective and robust for prediction The resulting hybrid model (called IeRNN) improves the prediction accuracy on state-level COVID-19 new case data from the US, out-performing standard temporal models (RNN, SEIR, and ARIMA) in 1-day and 7-day ahead forecasting Our model accommodates various degrees of reopening and provides potential outcomes for policymakers © 2021 by SCITEPRESS - Science and Technology Publications, Lda All rights reserved
The Contribution of Environmental Enrichment to Phenotypic Variation in Mice and Rats

The reproducibility and translation of neuroscience research is assumed to be undermined by introducing environmental complexity and heterogeneity. Rearing laboratory animals with minimal (if any) environmental stimulation is thought to control for biological variability but may not adequately test the robustness of our animal models. Standard laboratory housing is associated with reduced demonstrations of species typical behaviors and changes in neurophysiology that may impact the translation of research results. Modest increases in environmental enrichment (EE) mitigate against insults used to induce animal models of disease, directly calling into question the translatability of our work. This may in part underlie the disconnect between preclinical and clinical research findings. Enhancing environmental stimulation for our model organisms promotes ethological natural behaviors but may simultaneously increase phenotypic trait variability. To test this assumption, we conducted a systematic review and evaluated coefficients of variation (CVs) between EE and standard housed mice and rats. Given findings of suboptimal reporting of animal laboratory housing conditions, we also developed a methodological reporting table for enrichment use in neuroscience research. Our data show that animals housed in EE were not more variable than those in standard housing. Therefore, environmental heterogeneity introduced into the laboratory, in the form of enrichment, does not compromise data integrity. Overall, human life is complicated, and by embracing such nuanced complexity into our laboratories, we may paradoxically improve on the rigor and reproducibility of our research.
Bayesian Particles on Cyclic Graphs

We consider the problem of designing synthetic cells to achieve a complex goal (e.g., mimicking the immune system by seeking invaders) in a complex environment (e.g., the circulatory system), where they might have to change their control policy, communicate with each other, and deal with stochasticity including false positives and negatives—all with minimal capabilities and only a few bits of memory.We simulate the immune response in cyclic, maze-like environments and use targets at unknown locations to represent invading cells. Using only a few bits of memory, the synthetic cells are programmed to perform a physically-feasible algorithm with which they update their control policy based on randomized encounters with other cells. As the synthetic cells work together to find the target, their interactions as an ensemble function as a physical implementation of a Bayesian update. That is, the particles act as a particle filter.This result provides formal properties about the behavior of the synthetic cell ensemble that can be used to ensure robustness and safety. This method of self-organization is evaluated in simulations, and applied to an actual model of the human circulatory system.
Characterization of heat index experienced by individuals residing in urban and rural settings.

Heatwave warning systems rely on forecasts made for fixed-point weather stations (WS), which do not reflect variation in temperature and humidity experienced by individuals moving through indoor and outdoor locations. We examined whether neighborhood measurement improved the prediction of individually experienced heat index in addition to nearest WS in an urban and rural location. Participants (residents of Birmingham, Alabama [N = 89] and Wilcox County, Alabama [N = 88]) wore thermometers clipped to their shoe for 7 days. Shielded thermometers/hygrometers were placed outdoors within participant’s neighborhoods (N = 43). Nearest WS and neighborhood thermometers were matched to participant’s home address. Heat index (HI) was estimated from participant thermometer temperature and WS humidity per person-hour (HI[individual]), or WS temperature and humidity, or neighborhood temperature and humidity. We found that neighborhood HI improved the prediction of individually experienced HI in addition to WS HI in the rural location, and neighborhood heat index alone served as a better predictor in the urban location, after accounting for individual-level factors. Overall, a 1 °C increase in HI[neighborhood] was associated with 0.20 °C [95% CI (0.19, 0.21)] increase in HI[individual]. After adjusting for ambient condition differences, we found higher HI[individual] in the rural location, and increased HI[individual] during non-rest time (5 a.m. to midnight) and on weekdays.
Efficient implementation of the single-reference algebraic diagrammatic construction theory for charged excitations: Applications to the TEMPO radical and DNA base pairs.

We present an efficient implementation of the second- and third-order single-reference algebraic diagrammatic construction (ADC) theory for electron attachment and ionization energies and spectra [EA/IP-ADC(n), n = 2, 3]. Our new EA/IP-ADC program features spin adaptation for closed-shell systems, density fitting for efficient handling of the two-electron integral tensors, and vectorized and parallel implementation of tensor contractions. We demonstrate capabilities of our efficient implementation by applying the EA/IP-ADC(n) (n = 2, 3) methods to compute the photoelectron spectrum of the (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) radical, as well as the vertical and adiabatic electron affinities of TEMPO and two DNA base pairs (guanine–cytosine and adenine–thymine). The spectra and electron affinities computed using large diffuse basis sets with up to 1028 molecular orbitals are found to be in good agreement with the best available results from the experiment and theoretical simulations.
The Colonial Origins of the State in Southern Belize

Recent research in Belizean historiography has improved our understanding of twentieth-century colonial state relations and the transition to the post-colonial authoritarian democratic state. Following a concise review of these works, I draw on archival documents to examine the origins of the British state in southern Belize. This analysis provides two principal findings. First, the earliest state institutions were founded at the behest of colonists from the defeated Confederate States to facilitate labor discipline over their workers. Once established, local state officials sought to learn about and gain influence over Indigenous communities. Second, the nascent colonial state was relatively authoritarian and inattentive to local accumulation and social needs. Thus from its inception, the state was organized around race and class relations.
Practical optimal control of a wave-energy converter in regular wave environments

Abstract A generic formulation for the optimal control of a single reacting two-body point absorber type wave-energy converter (WEC) is proposed. The formulation involves hard and soft constraints on the motion of the WEC to promote reduced damage with the aim of increasing the service life of the device. Most of the WEC control literature ignores the cost of the control and could therefore result in extracting less energy than expected, or even negative energy. Therefore, to ensure actual energy gains in practice, we incorporate a penalty term in the objective function to approximate the cost of applying the control force. Based on our derivations, the cost of the control force can be approximated as a quadratic function of the input force. We also incorporate another cost term to ensure smoothness of the control force. A discretization of the resulting optimal control problem, maximizing the net energy extraction, is a quadratic optimization problem that can be solved efficiently using state-of-the-art solvers. Using hydrodynamic coefficients estimated by simulations made in WEC-Sim, numerical illustrations are provided of the trade-off between careful operation of the device and energy absorbed. Finally, a demonstration of the real-time use of the approach is provided.
Optimization under Uncertainty of a Chain of Nonlinear Resonators using a Field Representation

Abstract Chains of resonators are known to exhibit interesting dynamic phenomena. For instance, band gaps are frequency ranges within which waves do not propagate or are strongly attenuated. Through the introduction of nonlinearities, other interesting behaviors can be achieved to manipulate waves and optimize the dynamic behavior of a chain. This study proposes the design optimization under uncertainty of such a chain of resonators for the purpose of vibration mitigation. The stochastic optimization accounts for the presence of design uncertainties (e.g., nonlinear stiffness properties) as well as aleatory uncertainties (e.g., loading conditions). The algorithm is tailored to account for discontinuities in the chain’s response due to nonlinearities. In addition, a field formulation is used to define the properties of the resonators along the chain and reduce the dimensionality of the optimization problem. It is shown that the combination of the stochastic optimization algorithm and the field representation leads to robust designs that could not be achieved with optimal properties constant over the chain.
Maximally Recoverable LRCs: A Field Size Lower Bound and Constructions for Few Heavy Parities

The explosion in the volumes of data being stored online has resulted in distributed storage ‘s transitioning to erasure coding based schemes. Local Reconstruction Codes (LRCs) have emerged as the codes of choice for these applications. These codes can correct a small number of erasures (which is the typical case) by accessing only a small number of remaining coordinates. An $(n,r,h,a,q)$ -LRC is a linear code over $\mathbb {F}_{q}$ of length $n$ , whose codeword symbols are partitioned into $g=n/r$ local groups each of size $r$ . Each local group has $a$ local parity checks that allow recovery of up to $a$ erasures within the group by reading the unerased symbols in the group. There are a further $h$ “heavy” parity checks to provide fault tolerance from more global erasure patterns. Such an LRC is Maximally Recoverable (MR), if it corrects all erasure patterns which are information-theoretically correctable under the stipulated structure of local and global parity checks, namely patterns with up to $a$ erasures in each local group and an additional $h$ (or fewer) erasures anywhere in the codeword. The existing constructions require fields of size $n^{\Omega (h)}$ while no superlinear lower bounds were known for any setting of parameters. Is it possible to get linear field size similar to the related MDS codes (e.g., Reed-Solomon codes)? In this work, we answer this question by showing superlinear lower bounds on the field size of MR-LRCs. When $a,h$ are constant and the number of local groups $g \geqslant h$ , while $r$ may grow with $n$ , our lower bound simplifies to $q \geqslant \Omega _{a,h}\left ({n\cdot r^{\min \{a,h-2\}}}\right)$ . MR-LRCs deployed in practice have a small number of global parities, typically $h=2,3$ . We complement our lower bounds by giving constructions with small field size for $h \leqslant 3$ . When $h=2$ , we give a linear field size construction, whereas previous constructions required quadratic field size in some parameter ranges. Note that our lower bound is superlinear only if $h \geqslant 3$ . When $h=3$ , we give a construction with $O(n^{3})$ field size, whereas previous constructions needed $n^{\Theta (a)}$ field size. This makes the choices $r=3, a=1, h=3$ the next simplest non-trivial setting to investigate regarding the existence of MR-LRCs over fields of near-linear size. We answer this question in the positive via a novel approach based on elliptic curves and arithmetic progression free sets.
On the last fall degree of Weil descent polynomial systems

Abstract Given a polynomial system F over a finite field k which is not necessarily of dimension zero, we consider the Weil descent F ′ of F over a subfield k ′ . We prove a theorem which relates the last fall degrees of F 1 and F 1 ′ , where the zero set of F 1 corresponds bijectively to the set of k-rational points of F , and the zero set of F 1 ′ is the set of k ′ -rational points of the Weil descent F ′ . As an application we derive upper bounds on the last fall degree of F 1 ′ in the case where F is a set of linearized polynomials.
Turbulence characteristics of the noise producing region of an excited round jet. II - Large scale structure characteristics

A conditional sampling of digital hot wire records obtained at several radial positions of an axisymmetric jet indicates the existence of regions within the mixing layer which are more orderly than a fully chaotic turbulent flow. A Fourier decomposition of the flow has shown that most of the turbulent energy is contained in the fundamental frequency of the excitation and the first harmonic.
Equality, Quasi-Implicit Products, and Large Eliminations

This paper presents a type theory with a form of equality reflection: provable equalities can be used to coerce the type of a term. Coercions and other annotations, including implicit arguments, are dropped during reduction of terms. We develop the metatheory for an undecidable version of the system with unannotated terms. We then devise a decidable system with annotated terms, justified in terms of the unannotated system. Finally, we show how the approach can be extended to account for large eliminations, using what we call quasi-implicit products.
Obtaining Prevalence Estimates of COVID-19: A Model to Inform Decision-making.

We evaluate whether randomly sampling and testing a set number of individuals for coronavirus disease 2019 (COVID-19) while adjusting for misclassification error captures the true prevalence. We also quantify the impact of misclassification error bias on publicly reported case data in Maryland. Using a stratified random sampling approach, 50,000 individuals were selected from a simulated Maryland population to estimate the prevalence of COVID-19. We examined the situation when the true prevalence is low (0.07%-2%), medium (2%-5%) and high (6%-10%). Bayesian models informed by published validity estimates were used to account for misclassification error when estimating COVID-19 prevalence. Adjustment for misclassification error captured the true prevalence 100% of the time, irrespective of the true prevalence level. When adjustment for misclassification error was not done, the results highly varied depending on the population's underlying true prevalence and the type of diagnostic test used. Generally, the prevalence estimates without adjustment for misclassification error worsened as the true prevalence level increased. Adjustment for misclassification error for publicly reported Maryland data led to a minimal but not significant increase in the estimated average daily cases. Random sampling and testing of COVID-19 are needed with adjustment for misclassification error to improve COVID-19 prevalence estimates.
Causation or covariation: An empirical re-examination of the link between TQM and financial performance

Total Quality Management (TQM) is an integrated management system designed to focus an organization’s resources on increasing the quality of a firm’s products/services, satisfying customer needs and improving the efficiency of the processes that produce the firm’s products/services. Advocates of TQM have suggested that there should be a positive relationship between implementing TQM practices and financial performance measures. The empirical evidence supporting this assertion, however, is limited at best. Most of the research has been limited to surveys of managers’ perceptions of the effect of TQM on financial performance. A few empirical studies using financial performance measures have been done, and have shown that TQM firms have better financial performance than other firms. However, better performing companies may be more likely to adopt TQM, so that rather than being a path to improved financial success (causation), TQM merely “comes along for the ride” (covariation). This study examined the relationship between TQM and financial performance, using a sample of Baldrige Award winners and replicated with a second sample of state quality award winning companies, and three different sets of financial performance measures. Both Baldrige and state quality award winners generally had better financial performance than their peers after winning a quality award, and before. © 2004 Elsevier B.V. All rights reserved.
Network of Tensor Time Series

Co-evolving time series appears in a multitude of applications such as environmental monitoring, financial analysis, and smart transportation. This paper aims to address the following challenges, including (C1) how to incorporate explicit relationship networks of the time series; (C2) how to model the implicit relationship of the temporal dynamics. We propose a novel model called Network of Tensor Time Series (NeT3), which is comprised of two modules, including Tensor Graph Convolutional Network (TGCN) and Tensor Recurrent Neural Network (TRNN). TGCN tackles the first challenge by generalizing Graph Convolutional Network (GCN) for flat graphs to tensor graphs, which captures the synergy between multiple graphs associated with the tensors. TRNN leverages tensor decomposition to model the implicit relationships among co-evolving time series. The experimental results on five real-world datasets demonstrate the efficacy of the proposed method.
Non-equilibrium effective field theory and second sound

We investigate the phenomenon of second sound in various states of matter from the perspective of non-equilibrium effective field theory (EFT). In particular, for each state of matter considered, we find that at least two (though sometimes multiple) qualitatively different EFTs exist at finite temperature such that there is always at least one EFT with a propagating second-sound wave and at least one with no such second-sound wave. To aid in the construction of these EFTs, we use the method of cosets developed for non-equilibrium systems. It turns out that the difference between the EFTs with and without second-sound modes can be understood as arising from different choices of a new kind of inverse Higgs constraint. Finally, we demonstrate that it is possible to bypass the need for new inverse Higgs constraints by formulating EFTs on a new kind of manifold that is like the usual fluid worldvolume, but with reduced gauge symmetries.
The Bactrian effect: multiple resonances and light Dirac dark matter

The possibility of light dark matter (DM) annihilating through a dark photon (DP) which kinetically mixes (KM) with the Standard Model (SM) hypercharge field is a very attractive scenario. For DM in the interesting mass range below ∼ 1 GeV, it is well known that bounds from the CMB provide a very strong model building constraint forcing the DM annihilation cross section to be roughly 3 orders of magnitude below that needed to reproduce the observed relic density. Under most circumstances this removes the possibility of an s-wave annihilation process for DM in this mass range as would be the case, e.g., if the DM were a Dirac fermion. In an extra-dimensional setup explored previously, it was found that the s-channel exchange of multiple gauge bosons could simultaneously encompass a suppressed annihilation cross section during the CMB era while also producing a sufficiently large annihilation rate during freeze-out to recover the DM relic density. In this paper, we analyze more globally the necessary requirements for this mechanism to work successfully and then realize them within the context of a simple model with two ‘dark’ gauge bosons having masses of a similar magnitude and whose contributions to the annihilation amplitude destructively interfere. We show that if the DM mass threshold lies appropriately in the saddle region of this destructive interference between the two resonance humps it then becomes possible to satisfy these requirements simultaneously provided several ancillary conditions are met. The multiple constraints on the parameter space of this setup are then explored in detail to identify the phenomenologically successful regions.
SARS-CoV-2 Sequence Characteristics of COVID-19 Persistence and Reinfection.

BACKGROUND: Both SARS-CoV-2 reinfection and persistent infection have been reported, but sequence characteristics in these scenarios have not been described. We assessed published cases of SARS-CoV-2 reinfection and persistence, characterizing the hallmarks of reinfecting sequences and the rate of viral evolution in persistent infection. METHODS: A systematic review of PubMed was conducted to identify cases of SARS-CoV-2 reinfection and persistence with available sequences. Nucleotide and amino acid changes in the reinfecting sequence were compared to both the initial and contemporaneous community variants. Time-measured phylogenetic reconstruction was performed to compare intra-host viral evolution in persistent SARS-CoV-2 to community-driven evolution. RESULTS: Twenty reinfection and nine persistent infection cases were identified. Reports of reinfection cases spanned a broad distribution of ages, baseline health status, reinfection severity, and occurred as early as 1.5 months or >8 months after the initial infection. The reinfecting viral sequences had a median of 17.5 nucleotide changes with enrichment in the ORF8 and N genes. The number of changes did not differ by the severity of reinfection and reinfecting variants were similar to the contemporaneous sequences circulating in the community. Patients with persistent COVID-19 demonstrated more rapid accumulation of sequence changes than seen with community-driven evolution with continued evolution during convalescent plasma or monoclonal antibody treatment. CONCLUSIONS: Reinfecting SARS-CoV-2 viral genomes largely mirror contemporaneous circulating sequences in that geographic region, while persistent COVID-19 has been largely described in immunosuppressed individuals and is associated with accelerated viral evolution.
HVSRweb: An Open-Source, Web-Based Application for Horizontal-to-Vertical Spectral Ratio Processing

The horizontal-to-vertical spectral ratio (HVSR) method has become an increasingly popular tool for developing a quick and reliable estimate of a site's fundamental natural frequency ($f_0$). This paper presents HVSRweb, an open-source, web-based application for performing HVSR calculations in a convenient, reliable, and statistically-consistent manner. HVSRweb allows the user to upload three-component ambient noise records and perform the HVSR calculation in the cloud, with no installation required. The HVSR calculation can be performed using a single combined horizontal component (e.g., geometric-mean, squared-average) or multiple rotated horizontal components to investigate azimuthal variability. HVSRweb can reject spurious time windows using an automated frequency-domain window-rejection algorithm, removing the need for subjective and time-consuming user interaction. It also facilitates the use of lognormal statistics for $f_0$, allowing for a consistent statistical framework capable of quantifying measurement uncertainty in terms of either frequency or its reciprocal, period. In addition, HVSRweb presents the opportunity to rapidly incorporate new developments in processing and quantification of uncertainty as they emerge, and encourages standardization of HVSR processing across users while avoiding the challenges associated with traditional approaches that require the user to perform regular updates to keep pace with new developments.
Optimization of Ride Sharing Systems Using Event-driven Receding Horizon Control

Abstract We develop an event-driven Receding Horizon Control (RHC) scheme for a Ride Sharing System (RSS) where vehicles are shared to pick up and drop off passengers so as to minimize a weighted sum of passenger waiting and traveling times. The RSS is modeled as a discrete event system and the event-driven nature of the controller significantly reduces the complexity of the vehicle assignment problem, thus enabling its real-time implementation. Simulation results using actual city maps and real traffic data illustrate the effectiveness of the RH controller in terms of online implementation and performance relative to known heuristics.
Limit law for the cover time of a random walk on a binary tree

Let Tn denote the binary tree of depth n augmented by an extra edge connected to its root. Let Cn denote the cover time of Tn by simple random walk. We prove that the sequence of random variables Cn 2−(n+1)−mn, where mn is an explicit constant, converges in distribution as n→∞, and identify the limit.
Offset Curves Loss for Imbalanced Problem in Medical Segmentation

Medical image segmentation has played an important role in medical analysis and widely developed for many clinical applications. Deep learning-based approaches have achieved high performance in semantic segmentation but they are limited to pixel-wise setting and imbalanced classes data problem. In this paper, we tackle those limitations by developing a new deep learning-based model which takes into account both higher feature level i.e. region inside contour, intermediate feature level i.e. offset curves around the contour and lower feature level i.e. contour. Our proposed Offset Curves (OsC) loss consists of three main fitting terms. The first fitting term focuses on pixel-wise level segmentation whereas the second fitting term acts as attention model which pays attention to the area around the boundaries (offset curves). The third terms plays a role as regularization term which takes the length of boundaries into account. We evaluate our proposed OsC loss on both 2D network and 3D network. Two common medical datasets, i.e. retina DRIVE and brain tumor BRATS 2018 datasets are used to benchmark our proposed loss performance. The experiments have shown that our proposed OsC loss function outperforms other mainstream loss functions such as Cross-Entropy, Dice, Focal on the most common segmentation networks Unet, FCN.
Foreign investment of US multinationals: The effect of tax policy and agency conflicts.

Abstract We estimate a dynamic model, featuring agency conflicts and a stochastic tax reform arrival, to evaluate how the change from a worldwide to territorial tax system, enacted under the Tax Cuts and Jobs Act (TCJA), affects foreign investment. Although a worldwide system imposes a higher tax liability on foreign income, we show it encourages excess foreign investment by depressing the opportunity cost of capital. In our estimated model, the TCJA reduces foreign investment by 15.6% on average, with larger declines for services firms and firms with lesser agency conflicts. The reform probability, which we estimate in the model, significantly affects firms’ investment and cash holdings.
Scaling Laws of Dense Multi-Antenna Cellular Networks

We study the scaling laws of the signal-to-interference-plus-noise ratio (SINR) and the area spectral efficiency (ASE) in multi-antenna cellular networks, where the number of antennas scales with the base station (BS) spatial density λ, under the assumption of independent and identically distributed (i.i.d.) channels. We start with the MISO case with N t (λ) transmit antennas and a single receive antenna and prove that the average SINR scales as ${N_{t(\lambda ){/_\lambda }}}$ and the average ASE scales as $\lambda \log \left( {1 + {N_{t(\lambda ){/_\lambda }}}} \right)$. For the MIMO case with singlestream eigenbeamforming and N r (λ) ≤N t (λ) receive antennas, we prove that the scaling laws of the conditional SINR and ASE are agnostic to N r (λ) and scale exactly the same as the MISO case. Hence, deploying multi-antenna BSs can help maintain nonzero per-user throughput and a corresponding linear increase in the ASE in dense cellular networks.
TuringAdvice: A Generative and Dynamic Evaluation of Language Use

We propose TuringAdvice, a new challenge task and dataset for language understanding models. Given a written situation that a real person is currently facing, a model must generate helpful advice in natural language. Our evaluation framework tests a fundamental aspect of human language understanding: our ability to use language to resolve open-ended situations by communicating with each other. Empirical results show that today’s models struggle at TuringAdvice, even multibillion parameter models finetuned on 600k in-domain training examples. The best model, T5, writes advice that is at least as helpful as human-written advice in only 14% of cases; a much larger non-finetunable GPT3 model does even worse at 4%. This low performance reveals language understanding errors that are hard to spot outside of a generative setting, showing much room for progress.
Stable pairs with a twist and gluing morphisms for moduli of surfaces

We propose an alternative definition for families of stable pairs (X, D) over an arbitrary (possibly non-reduced) base in the case in which D is reduced, by replacing (X, D) with an appropriate orbifold pair (X,D). This definition of a stable family ends up being equivalent to previous ones, but has the advantage of being more amenable to the tools of deformation theory. Adjunction for (X,D) holds on the nose; there is no correction term coming from the different. This leads to the existence of functorial gluing morphisms for families of stable surfaces and functorial morphisms from (n+1) dimensional stable pairs to n dimensional polarized orbispaces. As an application, we study the deformation theory of some surface pairs.
Factors leading to sustainable social impact on the affected communities of engineering service learning projects

Abstract University engineering programs across the USA engage in service learning projects. These projects involve student teams designing and implementing products or solutions for communities in need, often in developing nations. There has been much research done relating to pedagogy and the impact of these programs on student learning. However, less research has been done on measuring the impact of these programs on the affected communities. This paper examines factors that practitioners believe are related to successfully delivering a desirable and transferable solution to affected communities. The authors identified 49 distinct factors from the literature that implicitly or explicitly are suggested to contribute to successful project outcomes. Formed as postulates in this paper, these 49 factors have been separated into 5 categories to assist understanding and implementing these factors into service learning programs. Lastly, different methods of analyzing and measuring project success and impact are discussed. Future methods for proving the viability of the 49 postulates are discussed as well.
Around quantum ergodicity

We discuss Shnirelman’s Quantum Ergodicity Theorem, giving an outline of a proof and an overview of some of the recent developments in mathematical Quantum Chaos.
Fast, Conservative Algorithm for Solving the Transonic Full-Potential Equation

A fast, fully implicit approximate factorization algorithm designed to solve the conservative, transonic, full-potential equation in either two or three dimensions is described. The algorithm uses an upwind bias of the density coefficient for stability in supersonic regions. This provides an effective upwind difference of the streamwise terms for any orientation of the velocity vector (i.e., rotated differencing), thereby greatly enhancing the reliability of the present algorithm. A numerical transformation is used to establish an arbitrary body-fitted, finite-difference mesh. Computed results for both airfoils and simplified wings demonstrate substantial improvement in convergence speed for the new algorithm relative to standard successive-line over-relaxation algorithms.
Mars in Situ Resource Utilization Technology Evaluation

We have examined the technologies required to enable Mars In-Situ Resource Utilization (ISRU) because our understanding of Mars resources has changed significantly in the last five years as a result of recent robotic missions to the red planet. Two major developments, (1) confirmation of the presence of near-surface water in the form of ice in very large amounts at high latitudes by the Phoenix Lander and (2) the likely existence of water at lower latitudes in the form of hydrates or ice in the top one meter of the regolith, have the potential to change ISRU technology selection. A brief technology assessment was performed for the most promising Mars atmospheric gas processing techniques: Reverse Water Gas Shift (RWGS) and Methanation (aka Sabatier), as well as an overview of soil processing technology to extract water from Martian soil.