cssi/SciSciGPT-SciSciNet huggingface dataset:
Content Validation of Direct Behavior Rating Multi-Item Scales for Assessing Problem Behaviors:

Direct Behavior Rating (DBR) is an efficient method for monitoring changes in student behavior in response to intervention. Emerging research on DBR Multi-Item Scales (DBR-MIS) indicates that DBR-M...
A yeast optogenetic toolkit (yOTK) for gene expression control in Saccharomyces cerevisiae.

Optogenetic tools for controlling gene expression are ideal for tuning synthetic biological networks due to the exquisite spatiotemporal control available with light. Here we develop an optogenetic system for gene expression control integrated with an existing yeast toolkit allowing for rapid, modular assembly of light-controlled circuits in the important chassis organism Saccharomyces cerevisiae. We reconstitute activity of a split synthetic zinc-finger transcription factor (TF) using light-induced dimerization mediated by the proteins CRY2 and CIB1. We optimize function of this split TF and demonstrate the utility of the toolkit workflow by assembling cassettes expressing the TF activation domain and DNA-binding domain at different levels. Utilizing this TF and a synthetic promoter we demonstrate that light-intensity and duty-cycle can be used to modulate gene expression over the range currently available from natural yeast promoters. This work allows for rapid generation and prototyping of optogenetic circuits to control gene expression in Saccharomyces cerevisiae.
Coproducts of proximity spaces

In this paper, we introduce coproducts of proximity spaces. After exploring several of their basic properties, we show that given a collection of proximity spaces, the coproduct of their Smirnov compactifications proximally and densely embeds in the Smirnov compactification of the coproduct of the original proximity spaces. We also show that the dense proximity embedding is a proximity isomorphism if and only if the index set is finite. After constructing a number of examples of coproducts and their Smirnov compactifications, we explore several properties of the Smirnov compactification of the coproduct, including its metrizability, connectedness of the boundary, dimension, and its relation to the Stone–Cech compactification. In particular, we show that the Smirnov compactification of the infinite coproduct is never metrizable and that its boundary is highly disconnected. We also show that the proximity dimension of the Smirnov compactification of the coproduct equals the supremum of the covering dimensions of the individual Smirnov compactifications and that the Smirnov compactification of the coproduct is homeomorphic to the Stone–Cech compactification if and only if each individual proximity space is equipped with the Stone–Cech proximity. We finish with an example of a coproduct with the covering dimension 0 but the proximity dimension $$\infty $$ .
Constructing a Time Scale of Biotic Recovery Across the Cretaceous–Paleogene Boundary, Corral Bluffs, Denver Basin, Colorado, U.S.A.

ABSTRACT The Cretaceous–Paleogene (K–Pg) boundary interval represents one of the most significant mass extinctions and ensuing biotic recoveries in Earth history. Earliest Paleocene fossil mammal faunas corresponding to the Puercan North American Land Mammal Age (NALMA) are thought to be highly endemic and potentially diachronous, necessitating precise chronostratigraphic controls at key fossil localities to constrain recovery dynamics in continental biotas following the K–Pg mass extinction. The Laramide synorgenic sedimentary deposits within the Denver Basin preserve one of the most continuous and fossiliferous records of the K–Pg boundary interval in North America. However, poor exposure in much of the Denver Basin makes it difficult to correlate between outcrops. In order to constrain fossil localities across the basin, previous studies have relied upon chronostratigraphic methods such as magnetostratigraphy. Here we present a new high-resolution magnetostratigraphy of 10 lithostratigraphic sections spanning the K–Pg boundary interval at Corral Bluffs located east of Colorado Springs in the southern part of the Denver Basin. Fossil localities from Corral Bluffs have yielded limited dinosaur remains, mammal fossils assigned to the Puercan NALMA, and numerous fossil leaf localities. Palynological analysis identifying the K–Pg boundary in three sections and two independent but nearly identical 206Pb/238U age estimates for the same volcanic ash, provide key temporal calibration points. Our paleomagnetic analysis has identified clear polarity reversal boundaries from Chron C30n to Chron C28r across the sections. It is now possible to place the fossil localities at Corral Bluffs within the broader basin-wide chronostratigraphic framework and evaluate them in the context of K–Pg boundary extinction and recovery.
On the Positive Effect of Delay on the Rate of Convergence of a Class of Linear Time-Delayed Systems

This article is a comprehensive study of a long-observed phenomenon of increase in the stability margin and so the rate of convergence of a class of linear systems due to time delay. We use the Lambert $W$ function to determine: 1) in what systems the delay can lead to increase in the rate of convergence; 2) the exact range of time delay, for which the rate of convergence is greater than that of the delay-free system; and 3) an estimate on the value of the delay that leads to the maximum rate of convergence. For the special case when the system matrix eigenvalues are all negative real numbers, we expand our results to show that the rate of convergence in the presence of delay depends only on the eigenvalues with minimum and maximum real parts. Moreover, we determine the exact value of the maximum rate of convergence and the corresponding maximizing time delay. We demonstrate our results through a numerical example on the practical application in accelerating an agreement algorithm for networked systems by using a delayed feedback.
Disruption of the HIV-1 Envelope allosteric network blocks CD4-induced rearrangements.

The trimeric HIV-1 Envelope protein (Env) mediates viral-host cell fusion via a network of conformational transitions, with allosteric elements in each protomer orchestrating host receptor-induced exposure of the co-receptor binding site and fusion elements. To understand the molecular details of this allostery, here, we introduce Env mutations aimed to prevent CD4-induced rearrangements in the HIV-1 BG505 Env trimer. Binding analysis and single-molecule Forster Resonance Energy Transfer confirm that these mutations prevent CD4-induced transitions of the HIV-1 Env. Structural analysis by single-particle cryo-electron microscopy performed on the BG505 SOSIP mutant Env proteins shows rearrangements in the gp120 topological layer contacts with gp41. Displacement of a conserved tryptophan (W571) from its typical pocket in these Env mutants renders the Env insensitive to CD4 binding. These results reveal the critical function of W571 as a conformational switch in Env allostery and receptor-mediated viral entry and provide insights on Env conformation that are relevant for vaccine design.
An inverse function theorem converse

Abstract We establish the following converse of the well-known inverse function theorem. Let g : U → V and f : V → U be inverse homeomorphisms between open subsets of Banach spaces. If g is differentiable of class C p and f is locally Lipschitz, then the Frechet derivative of g at each point of U is invertible and f must be differentiable of class C p .
Factors Related to User Ratings and User Downloads of Mobile Apps for Maternal and Infant Health: Cross-Sectional Study.

Background: Mobile health apps related to maternal and infant health (MIH) are prevalent and frequently used. Some of these apps are extremely popular and have been downloaded over 5 million times. However, the understanding of user behavior and user adoption of these apps based on consumer preferences for different app features and categories is limited. Objective: This study aimed to examine the relationship between MIH app characteristics and users’ perceived satisfaction and intent to use. Methods: The associations between app characteristics, ratings, and downloads were assessed in a sample of MIH apps designed to provide health education or decision-making support to pregnant women or parents and caregivers of infants. Multivariable linear regression was used to assess the relationship between app characteristics and user ratings, and ordinal logistic regression was used to assess the relationship between app characteristics and user downloads. Results: The analyses of user ratings and downloads included 421 and 213 apps, respectively. The average user rating was 3.79 out of 5. Compared with the Apple App Store, the Google Play Store was associated with high user ratings (beta=.33; P=.005). Apps with higher standardized user ratings (beta=.80; P<.001), in-app purchases (beta=1.12; P=.002), and in-app advertisements (beta=.64; P=.02) were more frequently downloaded. Having a health care organization developer as part of the development team was neither associated with user ratings (beta=−.20; P=.06) nor downloads (beta=−.14; P=.63). Conclusions: A majority of MIH apps are developed by non–health care organizations, which could raise concern about the accuracy and trustworthiness of in-app information. These findings could benefit app developers in designing better apps and could help inform marketing and development strategies. Further work is needed to evaluate the clinical accuracy of information provided within the apps.
Rate-Memory Trade-Off for Caching and Delivery of Correlated Sources

This paper studies the fundamental limits of content delivery in a cache-aided broadcast network for correlated content generated by a discrete memoryless source with arbitrary joint distribution. Each receiver is equipped with a cache of equal capacity, and the requested files are delivered over a shared error-free broadcast link. A class of achievable correlation-aware schemes based on a two-step source coding approach is proposed. Library files are first compressed, and then cached and delivered using a combination of multiple-request caching schemes that are agnostic to the content correlations. The first step uses Gray-Wyner source coding to represent the library via private descriptions and descriptions that are common to more than one file. The second step then becomes a multiple-request caching problem, where the demand structure is dictated by the configuration of the compressed library, and it is interesting in its own right. The performance of the proposed two-step scheme is evaluated by comparing its achievable rate with a lower bound on the optimal peak and average rate-memory trade-offs in a two-file multiple-receiver network, and in a three-file two-receiver network. Specifically, in a network with two files and two receivers, the achievable rate matches the lower bound for a significant memory regime and it is within half of the conditional entropy of files for all other memory values. In the three-file two-receiver network, the two-step strategy achieves the lower bound for large cache capacities, and it is within half of the joint entropy of two of the sources conditioned on the third one for all other cache sizes.
Optoelectronic Impacts of Particle Size in Water-Dispersible Plasmonic Copper Selenide Nanoparticles

There is significant interest in earth-abundant plasmonic materials, but whether or not their performance can match or even surpass their noble metal counterparts remains to be established. An impo...
The physics of tossing fried rice

Fried rice is a 1500-year-old dish that is prepared using wok tossing, a technique that enables food to undergo temperatures of 1200°C without burning. Tossing of the heavy wok at high speed may be...
A comparison of some conformal quantile regression methods

We compare two recently proposed methods that combine ideas from conformal inference and quantile regression to produce locally adaptive and marginally valid prediction intervals under sample exchangeability (Romano et al., 2019; Kivaranovic et al., 2019). First, we prove that these two approaches are asymptotically efficient in large samples, under some additional assumptions. Then we compare them empirically on simulated and real data. Our results demonstrate that the method in Romano et al. (2019) typically yields tighter prediction intervals in finite samples. Finally, we discuss how to tune these procedures by fixing the relative proportions of observations used for training and conformalization.
Constructing and Forgetting Temporal Context in the Human Cerebral Cortex.

Summary How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error.
Interest rate trends in a global context

Abstract Long-term interest rates have been falling globally since the early 1980s and have reached historically low levels. Past forecasts largely missed this secular decline. This paper reviews methodologies for making long-term interest rate projections. We synthesize results from studies that use long historical series and cross-country data to estimate the trend and decompose it into components. We then construct a set of economic indicators that are potentially useful in interest rate forecasting. We add international forward-looking economic indicators as explanatory variables in a standard macro-finance forecasting model. We find that the model with international variables can outperform the other models by better tracking the falling trajectory of U.S. interest rates in the post-2008 period, a trend that is missed by domestic variables.
Analysis of adaptive short-time Fourier transform-based synchrosqueezing transform

Recently, the study of modeling a non-stationary signal as a superposition of amplitude and frequency-modulated Fourier-like oscillatory modes has been a very active research area. The synchrosquee...
Speaker Independence of Neural Vocoders and Their Effect on Parametric Resynthesis Speech Enhancement

Traditional speech enhancement systems produce speech with compromised quality. Here we propose to use the high quality speech generation capability of neural vocoders for better quality speech enhancement. We term this parametric resynthesis (PR). In previous work, we showed that PR systems generate high quality speech for a single speaker using two neural vocoders, WaveNet and WaveGlow. Both these vocoders are traditionally speaker dependent. Here we first show that when trained on data from enough speakers, these vocoders can generate speech from unseen speakers, both male and female, with similar quality as seen speakers in training. Next using these two vocoders and a new vocoder LPCNet, we evaluate the noise reduction quality of PR on unseen speakers and show that objective signal and overall quality is higher than the state-of-the-art speech enhancement systems Wave-U-Net, Wavenet-denoise, and SEGAN. Moreover, in subjective quality, multiple-speaker PR out-performs the oracle Wiener mask.
Advancing PICO element detection in biomedical text via deep neural networks.

Motivation In evidence-based medicine, defining a clinical question in terms of the specific patient problem aids the physicians to efficiently identify appropriate resources and search for the best available evidence for medical treatment. In order to formulate a well-defined, focused clinical question, a framework called PICO is widely used, which identifies the sentences in a given medical text that belong to the four components typically reported in clinical trials: Participants/Problem (P), Intervention (I), Comparison (C) and Outcome (O). In this work, we propose a novel deep learning model for recognizing PICO elements in biomedical abstracts. Based on the previous state-of-the-art bidirectional long-short-term memory (bi-LSTM) plus conditional random field architecture, we add another layer of bi-LSTM upon the sentence representation vectors so that the contextual information from surrounding sentences can be gathered to help infer the interpretation of the current one. In addition, we propose two methods to further generalize and improve the model: adversarial training and unsupervised pre-training over large corpora. Results We tested our proposed approach over two benchmark datasets. One is the PubMed-PICO dataset, where our best results outperform the previous best by 5.5%, 7.9% and 5.8% for P, I and O elements in terms of F1 score, respectively. And for the other dataset named NICTA-PIBOSO, the improvements for P/I/O elements are 3.9%, 15.6% and 1.3% in F1 score, respectively. Overall, our proposed deep learning model can obtain unprecedented PICO element detection accuracy while avoiding the need for any manual feature selection. Availability and implementation Code is available at https://github.com/jind11/Deep-PICO-Detection.
To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic

Face mask use by the general public for limiting the spread of the COVID-19 pandemic is controversial, though increasingly recommended, and the potential of this intervention is not well understood. We develop a compartmental model for assessing the community-wide impact of mask use by the general, asymptomatic public, a portion of which may be asymptomatically infectious. Model simulations, using data relevant to COVID-19 dynamics in the US states of New York and Washington, suggest that broad adoption of even relatively ineffective face masks may meaningfully reduce community transmission of COVID-19 and decrease peak hospitalizations and deaths. Moreover, mask use decreases the effective transmission rate in nearly linear proportion to the product of mask effectiveness (as a fraction of potentially infectious contacts blocked) and coverage rate (as a fraction of the general population), while the impact on epidemiologic outcomes (death, hospitalizations) is highly nonlinear, indicating masks could synergize with other non-pharmaceutical measures. Notably, masks are found to be useful with respect to both preventing illness in healthy persons and preventing asymptomatic transmission. Hypothetical mask adoption scenarios, for Washington and New York state, suggest that immediate near universal (80%) adoption of moderately (50%) effective masks could prevent on the order of 17–45% of projected deaths over two months in New York, while decreasing the peak daily death rate by 34–58%, absent other changes in epidemic dynamics. Even very weak masks (20% effective) can still be useful if the underlying transmission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24–65% (and peak deaths 15–69%), compared to 2–9% mortality reduction in New York (peak death reduction 9–18%). Our results suggest use of face masks by the general public is potentially of high value in curtailing community transmission and the burden of the pandemic. The community-wide benefits are likely to be greatest when face masks are used in conjunction with other non-pharmaceutical practices (such as social-distancing), and when adoption is nearly universal (nation-wide) and compliance is high.
Singularities in the classical Rayleigh-Taylor flow: formation and subsequent motion

This paper is concerned with the creation and subsequent motion of singularities of solution to classical Rayleigh-Taylor flow (two-dimensional inviscid, incompressible fluid over a vacuum). For a specific set of initial conditions, we give analytical evidence to suggest the instantaneous formation of one or more singularity(ies) at specific point(s) in the unphysical plane, whose locations depend sensitively to small changes in initial conditions in the physical domain. One-half power singularities are created in accordance with an earlier conjecture; however, depending on initial conditions, other forms of singularities are also possible. For a specific initial condition, we follow a numerical procedure in the unphysical plane to compute the motion of a one-half singularity. This computation confirms our previous conjecture that the approach of a one-half singularity towards the physical domain corresponds to the development of a spike at the physical interface. Under some assumptions that appear to be consistent with numerical calculations, we present analytical evidence to suggest that a singularity of the one-half type cannot impinge the physical domain in finite time.
A Learning Program for the Integration of Systems of Ordinary Differential Equations

In our previous work [1, 2], an effort was made to determine which of the many methods and orders available for the numerical integration of ordinary differential equations was best. While it was possible to show that, under certain circumstances, some methods and orders outperformed others, no one method was clearly superior under all circumstances.
The effects of industry structure on economic exposure

Abstract A firm is subject to “economic exposure” if changes in exchange rates affect the firm's value, as measured by the present value of its future cash flows. This paper shows that in many forms of competition, including the most commonly studied case of monopoly, the economic exposure of an exporting firm is simply proportional to the firm's net revenues based in foreign currency. This simple result breaks down under some, but not all, forms of competition between the exporting firm and foreign firms. In that case, the exporting firm needs to know about the price elasticity of its product demand and its marginal cost in order to assess its exposure to exchange rates. The key determinant of economic exposure, therefore, is the competitive structure of the industry in which a firm operates.
Diffraction of a Shock Wave by a Compression Corner: I. Regular Reflection

The unsteady, two-dimensional flowfield resulting from the interaction of a moving planar shock wave with a compression corner is determined using a second-order, discontinuity-fitting, finite-difference approach. The time-dependent Euler equations are transformed to normalize the distance between the body and peripheral shock and to include the existing self-similar property of the flow. The resulting set of partial differential equations in conservation-law form is then solved in a time-dependent fashion using MacCormack's scheme. The vortical singularity, which lies on the body surface, and the single reflected shock are both treated as discontinuities in the numerical procedure. The results of the numerical simulation compare quite favorably with existing experimental interferograms and yield better flowfield resolution than previous first-order, shock-capturing, numerical solutions.
Risk Management of Construction Defects

Risk management of construction defects involves the collection and analysis of data to ascertain the empirical basis for alleged defects and to assess the producer's or consumer's risk regarding possible actions. In the context of a dispute between two or more parties, risk managers also make decisions concerning alternative options for resolution. Defects are usually identified through quality inspections and tests during construction or sometimes through the manifestation of problems after the completion of construction. Statistical sampling and estimation are used to characterize the prevalence of defects. Important considerations include the selection of a suitable sampling design, determination of an adequate sample size, and control of potential sources of bias. Defects attributable to design, materials, and method of construction may require qualitatively different approaches compared to the sampling plans implemented for defects attributable to workmanship. Repair options often vary in scope and unit cost, with implications for the associated financial risks. Keywords: alternative dispute resolution; random sampling; stratification; sample size; nonresponse bias; substitution; visual inspection; destructive testing; preponderance of evidence
Chapter 9 – Programming Languages

Publisher Summary Each computer can only understand the programs that are written in its own machine language. Machine languages are machine dependent because they are so closely related to the structure of a particular machine. Most programs are written in assembly languages or high-level languages. Assembler programs translate assembly language programs into machine language programs. Assembly language programs can be written faster, have fewer bugs, and are easier to understand and modify than machine language programs. Macro instructions are single statements that an assembler expands into several assembly language statements. High-level languages use English phrases and common mathematical notations. They can convey in one statement what might take many statements in machine and assembly languages. High-level languages are easier to learn than assembly languages. High-level languages are categorized as either procedure oriented or problem oriented. In program development environments, “quick-and-dirty” compilers are used. These translate programs quickly, although the resulting machine language programs might not run as efficiently as possible.
Virus Removal from Plants

Viruses will cause a steady decline in plant vigor, quality, and subsequent loss of yield. The lack of inexpensive and reliable curative agents for the elimination of viruses from plants that are growing in the field, orchard, or landscape has resulted in the development of methods for producing virus-free plant materials to replace material that is chronically infected or to assure that newly planted material or plant material exchanged between locations is free of virus. Therapy may include heat treatment alone or in combination, culture of totipotent cell clusters such as meristems, and use of compounds that affect virus replication. Though plant material may emerge virus-free, it is not virus-resistant. Hence, a vigorous approach to monitor for viruses must be considered when the plant material is used. Keywords: virus elimination; thermotherapy; heat treatment; heat therapy virus detection; tissue culture; chemotherapy; meristem culture; certification; virus-free; virus control; plant disease; disease control
The Geology of the Terrestrial Planets

The geologic history of the terrestrial planets is outlined in light of recent exploration and the revolution in geologic thinking. Among the topics considered are planet formation; planetary craters, basins, and general surface characteristics; tectonics; planetary atmospheres; and volcanism.
UNION ORGANIZING DECISIONS IN A DETERIORATING ENVIRONMENT: THE COMPOSITION OF REPRESENTATION ELECTIONS AND THE DECLINE IN TURNOUT

It is well known that the organizing environment for labor unions in the United States has deteriorated dramatically over a long period of time, a situation that has contributed to the sharp declin...
Kaposi's Sarcoma-Associated Herpesvirus Fine-Tunes the Temporal Expression of Late Genes by Manipulating a Host RNA Quality Control Pathway.

Kaposi's sarcoma-associated herpesvirus (KSHV) is a human oncogenic nuclear DNA virus that expresses its genes using the host cell transcription and RNA processing machinery. As a result, KSHV transcripts are subject to degradation by at least two host-mediated nuclear RNA decay pathways, the PABPN1- and poly(A) polymerase α/γ (PAPα/γ)-mediated RNA decay (PPD) pathway and an ARS2-dependent decay pathway. Here, we present global analyses of viral transcript levels to further understand the roles of these decay pathways in KSHV gene expression. Consistent with our recent report that the KSHV ORF57 protein increases viral transcript stability by impeding ARS2-dependent decay, ARS2 knockdown has only modest effects on viral gene expression 24 h after lytic reactivation of wild-type virus. In contrast, inactivation of PPD has more widespread effects, including premature accumulation of late transcripts. The upregulation of late transcripts does not require the primary late-gene-specific viral transactivation factor, suggesting that cryptic transcription produces the transcripts that then succumb to PPD. Remarkably, PPD inactivation has no effect on late transcripts at their proper time of expression. We show that this time-dependent PPD evasion by late transcripts requires the host factor n uclear R NAi- de fective 2 (NRDE2), which has previously been reported to protect cellular RNAs by sequestering decay factors. From these studies, we conclude that KSHV uses PPD to fine-tune the temporal expression of its genes by preventing their premature accumulation.IMPORTANCE Kaposi's sarcoma-associated herpesvirus (KSHV) is an oncogenic gammaherpesvirus that causes Kaposi's sarcoma and other lymphoproliferative disorders. Nuclear expression of KSHV genes results in exposure to at least two host-mediated nuclear RNA decay pathways, the PABPN1- and PAPα/γ-mediated RNA decay (PPD) pathway and an ARS2-mediated decay pathway. Perhaps unsurprisingly, we previously found that KSHV uses specific mechanisms to protect its transcripts from ARS2-mediated decay. In contrast, here we show that PPD is required to dampen the expression of viral late transcripts that are prematurely transcribed, presumably due to cryptic transcription early in infection. At the proper time for their expression, KSHV late transcripts evade PPD through the activity of the host factor NRDE2. We conclude that KSHV fine-tunes the temporal expression of its genes by modulating PPD activity. Thus, the virus both protects from and exploits the host nuclear RNA decay machinery for proper expression of its genes.
The Tradeoff between Mortgage Prepayments and Tax-Deferred Retirement Savings

Abstract Many households face the tradeoff between paying an extra dollar off the remaining mortgage on their house and saving that extra dollar in tax-deferred accounts (TDAs) used for retirement. We show that, under certain conditions, it becomes a tax arbitrage to reduce mortgage prepayments and to increase TDA contributions because of the tax deductibility of mortgage interest and tax-exemption of qualified retirement savings. Using data from the Survey of Consumer Finances, we document that a significant number of households that are accelerating their mortgage payments instead of saving in TDAs forgo a profitable tax arbitrage opportunity. Finally, we show empirically that this inefficient behavior is unlikely to be driven by liquidity or other financial constraints. Rather, the observed behavior can be attributed to a certain extent to the reluctance of many households to participate in financial markets as either lenders or borrowers.
Testing and Being Tested in Pandemic Times

The coronavirus pandemic is witness to a great proliferation of two types of tests. The first type is testing – new medical diagnostic tests as well as epidemiological models that simulate and project the course of the virus. In the second type, actors, organizations, and institutions are being tested in this moment of social and political crisis. This essay analyzes the similarities and differences between these two major types of tests in order to understand their entanglements in the crisis. In the process, we find a great diversity of tests operating in multiple registers, themselves not clearly demarcated, often combining and sometimes conflating, for example, scientific and public discourse. The study opens by identifying three aspects of testing , drawn from the sociology of testing. First, tests are frequently proxies (or projections) that stand for something. Second, a test is a critical moment that stands out – whether because it is a moment deliberately separated out or because it is a puzzling or troublesome “situation” that disrupts the flow of social life. Third, when someone or something is put to the test , of interest is whether it stands up to the challenge. These insights serve as the building blocks for addressing three major issues – representation , selection , and accountability – regarding testing in the time of the coronavirus crisis.
Optimal targeted lockdowns in a multi-group sir model

We study targeted lockdowns in a multi-group SIR model where infection, hospitalization and fatality rates vary between groups—in particular between the “young”, “the middle-aged” and the “old”. Our model enables a tractable quantitative analysis of optimal policy. For baseline parameter values for the COVID-19 pandemic applied to the US, we find that optimal policies differentially targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter lockdown policies on the oldest group. Intuitively, a strict and long lockdown for the most vulnerable group both reduces infections and enables less strict lockdowns for the lower-risk groups. We also study the impacts of group distancing, testing and contract tracing, the matching technology and the expected arrival time of a vaccine on optimal policies. Overall, targeted policies that are combined with measures that reduce interactions between groups and increase testing and isolation of the infected can minimize both economic losses and deaths in our model.
Non-parametric and semi-parametric support estimation using SEquential RESampling random walks on biomolecular sequences

Non-parametric and semi-parametric resampling procedures are widely used to perform support estimation in computational biology and bioinformatics. Among the most widely used methods in this class is the standard bootstrap method, which consists of random sampling with replacement. While not requiring assumptions about any particular parametric model for resampling purposes, the bootstrap and related techniques assume that sites are independent and identically distributed (i.i.d.). The i.i.d. assumption can be an over-simplification for many problems in computational biology and bioinformatics. In particular, sequential dependence within biomolecular sequences is often an essential biological feature due to biochemical function, evolutionary processes such as recombination, and other factors. To relax the simplifying i.i.d. assumption, we propose a new non-parametric/semi-parametric sequential resampling technique that generalizes “Heads-or-Tails” mirrored inputs, a simple but clever technique due to Landan and Graur. The generalized procedure takes the form of random walks along either aligned or unaligned biomolecular sequences. We refer to our new method as the SERES (or “SEquential RESampling”) method. To demonstrate the performance of the new technique, we apply SERES to estimate support for the multiple sequence alignment problem. Using simulated and empirical data, we show that SERES-based support estimation yields comparable or typically better performance compared to state-of-the-art methods.
Learning a Neural-network-based Representation for Open Set Recognition.

Open set recognition problems exist in many domains. For example in security, new malware classes emerge regularly; therefore malware classification systems need to identify instances from unknown classes in addition to discriminating between known classes. In this paper we present a neural network based representation for addressing the open set recognition problem. In this representation instances from the same class are close to each other while instances from different classes are further apart, resulting in statistically significant improvement when compared to other approaches on three datasets from two different domains.
Dynamic Origin–Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter:

Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of prediction of dynamic or...
Expanding the Chemical Space of Synthetic Cyclic Peptides Using a Promiscuous Macrocyclase from Prenylagaramide Biosynthesis

Cyclic peptides are ubiquitous drug candidates, placing macrocyclization reactions at the apex of drug development. PatG and related dual-action proteases from cyanobactin biosynthesis are responsi...
Representations, Metrics and Statistics for Shape Analysis of Elastic Graphs

Past approaches for statistical shape analysis of objects have focused mainly on objects within the same topological classes, e.g., scalar functions, Euclidean curves, or surfaces, etc. For objects that differ in more complex ways, the current literature offers only topological methods. This paper introduces a far-reaching geometric approach for analyzing shapes of graphical objects, such as road networks, blood vessels, brain fiber tracts, etc. It represents such objects, exhibiting differences in both geometries and topologies, as graphs made of curves with arbitrary shapes (edges) and connected at arbitrary junctions (nodes). To perform statistical analyses, one needs mathematical representations, metrics and other geometrical tools, such as geodesics, means, and covariances. This paper utilizes a quotient structure to develop efficient algorithms for computing these quantities, leading to useful statistical tools, including principal component analysis and analytical statistical testing and modeling of graphical shapes. The efficacy of this framework is demonstrated using various simulated as well as the real data from neurons and brain arterial networks.
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory

Particle-optimization-based sampling (POS) is a recently developed effective sampling technique that interactively updates a set of particles. A representative algorithm is the Stein variational gradient descent (SVGD). We prove, under certain conditions, SVGD experiences a theoretical pitfall, {\it i.e.}, particles tend to collapse. As a remedy, we generalize POS to a stochastic setting by injecting random noise into particle updates, thus yielding particle-optimization sampling (SPOS). Notably, for the first time, we develop {\em non-asymptotic convergence theory} for the SPOS framework (related to SVGD), characterizing algorithm convergence in terms of the 1-Wasserstein distance w.r.t.\! the numbers of particles and iterations. Somewhat surprisingly, with the same number of updates (not too large) for each particle, our theory suggests adopting more particles does not necessarily lead to a better approximation of a target distribution, due to limited computational budget and numerical errors. This phenomenon is also observed in SVGD and verified via an experiment on synthetic data. Extensive experimental results verify our theory and demonstrate the effectiveness of our proposed framework.
Enumeration and Analysis of DC–DC Converter Implementations Based on Piezoelectric Resonators

Demand for power electronics with smaller volume, lighter weight, and lower cost will eventually require new converter energy storage technologies with fundamentally higher power density and efficiency limits. This motivates investigation into piezoelectric resonators (PRs), which offer very high power density and efficiency capabilities and significantly improved scaling properties compared to magnetics. PRs have been used in power conversion previously, but the realm of possible converter implementations using only PRs for energy storage has seen little exploration. In this work, we enumerate and evaluate dc–dc converter topologies and switching sequences that best utilize a PR as the only energy storage component, and that enable low-loss resonant “soft charging” of the PR's input capacitance with voltage regulation capability. To compare these implementations, we present analysis techniques for their operation and periodic steady-state solutions considering practical constraints. In addition, we provide useful techniques for estimating PR utilization and efficiency, which we validate experimentally in a 200–100-V, 25-W rated prototype. This prototype exhibits peak efficiency $>$ 99% as well as high efficiency ( $\geq$ 96%) across a wide range of operating conditions, illustrating the promise of PR-based converters for high voltage, low power applications. This article is accompanied by an instructional video for selecting and analyzing PR-based dc–dc converter implementations.
A remark about the anomalies of cyclic holomorphic permutation orbifolds

Using a result of Longo and Xu, we show that the anomaly arising from a cyclic permutation orbifold of order 3 of a holomorphic conformal net &#x1d49c; with central charge c = 8k depends on the “gravitatio...
Archival Evidence on the Audit Process: Determinants and Consequences of Interim Effort*

Using proprietary data from a global accounting firm, we investigate the determinants of auditors’ interim effort as well as the impact of interim effort on audit quality, client disclosure timeliness, audit hours, and audit fees. Public statements from accounting firms and regulators suggest various benefits from accelerating auditor effort, but these claims remain largely untested. We find that interim effort is higher for large, complex clients that require integrated audits of both financial statements and internal control over financial reporting. With respect to consequences, we find that allocating relatively more work to the interim period is associated with a reduced likelihood of late 10-K filings, decreased total audit hours, and higher fees. Although increasing interim period effort is not, on average, associated with a reduced likelihood of misstatement, we do find that current period material weaknesses are less likely with greater interim work. Thus, greater interim effort appears to facilitate the remediation of internal control deficiencies before year-end. We also show that the benefits of increased interim period effort allocation are much stronger – including improved audit quality – when manager and partner interim involvement is high. Overall, our study provides important new insights on audit production and highlights benefits of reduced hours for auditors, earlier identification of control deficiencies for clients, and more timely financial reports for investors.
Non-commutative integrability of the Grassmann pentagram map

Abstract The pentagram map is a discrete dynamical system first introduced by Schwartz in 1992. It was proved to be integrable by Schwartz, Ovsienko, and Tabachnikov in 2010. Gekhtman, Shapiro, and Vainshtein studied Poisson geometry associated to certain networks embedded in a disc or annulus, and its relation to cluster algebras. Later, Gekhtman et al. and Tabachnikov reinterpreted the pentagram map in terms of these networks, and used the associated Poisson structures to give a new proof of integrability. In 2011, Mari Beffa and Felipe introduced a generalization of the pentagram map to certain Grassmannians, and proved it had a Lax representation. We reinterpret this Grassmann pentagram map in terms of noncommutative algebra, in particular the double brackets of Van den Bergh, and generalize the approach of Gekhtman et al. to establish a noncommutative version of integrability.
How the Mechanical Properties and Thickness of Glass Affect TPaD Performance

One well-known class of surface haptic devices that we have called Tactile Pattern Displays (TPaDs) uses ultrasonic transverse vibrations of a touch surface to modulate fingertip friction. This article addresses the power consumption of glass TPaDs, which is an important consideration in the context of mobile touchscreens. In particular, based on existing ultrasonic friction reduction models, we consider how the mechanical properties (density and Young's modulus) and thickness of commonly-used glass formulations affect TPaD performance, namely the relation between its friction reduction ability and its real power consumption. Experiments performed with eight types of TPaDs and an electromechanical model for the fingertip-TPaD system indicate: 1) TPaD performance decreases as glass thickness increases; 2) TPaD performance increases as the Young's modulus and density of glass decrease; and 3) real power consumption of a TPaD decreases as the contact force increases. Proper applications of these results can lead to significant increases in TPaD performance.
Monitoring Recessions: A Bayesian Sequential Quickest Detection Method.

Abstract Monitoring business cycles faces two potentially conflicting objectives: accuracy and timeliness. To strike a balance between these dual objectives, we propose a Bayesian sequential quickest detection method to identify turning points in real time with a sequential stopping time as a solution. Using four monthly indexes of real economic activity in the United States, we evaluated the method’s real-time ability to date the past five recessions. The proposed method identified similar turning-point dates as the National Bureau of Economic Research (NBER), with no false alarms, but on average, it dated peaks four months faster and troughs 10 months faster relative to the NBER announcement. The timeliness of our method is also notable compared to the dynamic factor Markov-switching model: the average lead time was about five months when dating peaks and two months when dating troughs.
SARS-CoV-2 growth, furin-cleavage-site adaptation and neutralization using serum from acutely infected hospitalized COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), emerged at the end of 2019 and by mid-June 2020 the virus had spread to at least 215 countries, caused more than 8 000 000 confirmed infections and over 450 000 deaths, and overwhelmed healthcare systems worldwide. Like severe acute respiratory syndrome coronavirus (SARS-CoV), which emerged in 2002 and caused a similar disease, SARS-CoV-2 is a betacoronavirus. Both viruses use human angiotensin-converting enzyme 2 (hACE2) as a receptor to enter cells. However, the SARS-CoV-2 spike (S) glycoprotein has a novel insertion that generates a putative furin cleavage signal and this has been postulated to expand the host range. Two low-passage (P) strains of SARS-CoV-2 (Wash1 : P4 and Munich : P1) were cultured twice in Vero E6 cells and characterized virologically. Sanger and MinION sequencing demonstrated significant deletions in the furin cleavage signal of Wash1 : P6 and minor variants in the Munich : P3 strain. Cleavage of the S glycoprotein in SARS-CoV-2-infected Vero E6 cell lysates was inefficient even when an intact furin cleavage signal was present. Indirect immunofluorescence demonstrated that the S glycoprotein reached the cell surface. Since the S protein is a major antigenic target for the development of neutralizing antibodies, we investigated the development of neutralizing antibody titres in serial serum samples obtained from COVID-19 human patients. These were comparable regardless of the presence of an intact or deleted furin cleavage signal. These studies illustrate the need to characterize virus stocks meticulously prior to performing either in vitro or in vivo pathogenesis studies.