cssi/SciSciGPT-SciSciNet huggingface dataset:
ViGGO: A Video Game Corpus for Data-To-Text Generation in Open-Domain Conversation.

The uptake of deep learning in natural language generation (NLG) led to the release of both small and relatively large parallel corpora for training neural models. The existing data-to-text datasets are, however, aimed at task-oriented dialogue systems, and often thus limited in diversity and versatility. They are typically crowdsourced, with much of the noise left in them. Moreover, current neural NLG models do not take full advantage of large training data, and due to their strong generalizing properties produce sentences that look template-like regardless. We therefore present a new corpus of 7K samples, which (1) is clean despite being crowdsourced, (2) has utterances of 9 generalizable and conversational dialogue act types, making it more suitable for open-domain dialogue systems, and (3) explores the domain of video games, which is new to dialogue systems despite having excellent potential for supporting rich conversations.
A clinical review of first seizures in adult patients

First seizures in adult patients are a common problem in clinical practice and their management represents a challenge for physicians The aim of this review is to develop a systematic clinical approach for the classification diagnosis and treatment of patients who have experienced a first seizure This could help clinicians to recognize and treat this condition appropriately Because these seizures can arise from several etiologies it is essential to know if the event was a provoked acute symptomatic or unprovoked seizure Thus an adequate classification is important to establish the length of the diagnosis approach the necessary treatment and every individual prognosis We found that patients diagnosed with a single unprovoked seizure require electroencephalography and magnetic resonance imaging This will allow an assessment of the risk of recurrence and the identification of patients that follow the diagnosis criteria for epilepsy We recommend individualized pharmacological therapy to reduce early seizure recurrence le years even if it can produce some adverse effects Finally we determine that there are still certain areas of uncertainty to promote future research in this topic
Exact parameterization of fermionic wave functions via unitary coupled cluster theory.

A formal analysis is conducted on the exactness of various forms of unitary coupled cluster (UCC) theory based on particle-hole excitation and de-excitation operators. Both the conventional single exponential UCC parameterization and a factorized (referred to here as “disentangled”) version are considered. We formulate a differential cluster analysis to determine the UCC amplitudes corresponding to a general quantum state. The exactness of conventional UCC (ability to represent any state) is explored numerically, and it is formally shown to be determined by the structure of the critical points of the UCC exponential mapping. A family of disentangled UCC wave functions is proven to exactly parameterize any state, thus showing how to construct Trotter-error-free parameterizations of UCC for applications in quantum computing. From these results, we construct an exact disentangled UCC parameterization that employs an infinite sequence of particle-hole or general one- and two-body substitution operators.
Enhanced Scenario Analysis

Investors have long relied on scenario analysis as an alternative to mean–variance analysis to help them construct portfolios. Even though mean–variance analysis accounts for all potential scenarios, many investors find it difficult to implement because it requires them to specify statistical features of asset classes that are often unintuitive and difficult to estimate. Scenario analysis, by contrast, requires only that investors specify a small set of potential outcomes as projections of economic variables and assign probabilities to their occurrence. It is, therefore, more intuitive than mean–variance analysis, but it is highly subjective. In this article, the authors propose to replace the subjective elements of scenario analysis with a robust statistical process. They use a multivariate measure of statistical distance to estimate probabilities of prospective scenarios. Next, they construct portfolios that maximize utility for investors with different risk preferences. Lastly, the authors introduce a procedure for minimally modifying scenarios to render them consistent with prespecified views about their probabilities of occurrence. TOPICS:Portfolio management/multi-asset allocation, risk management, quantitative methods Key Findings • The authors use a multivariate measure of statistical distance to estimate probabilities of prospective scenarios. • They construct portfolios that maximize utility for investors with different risk preferences. • The authors introduce a procedure for minimally modifying scenarios to render them consistent with one’s prespecified views about their probabilities of occurrence.
In Praise of Confidence Intervals

Most empirical papers in economics focus on two aspects of their results: whether the estimates are statistically significantly different from zero and the interpretation of the point estimates. This focus obscures important information about the implications of the results for economically interesting hypotheses about values of the parameters other than zero, and in some cases, about the strength of the evidence against values of zero. This limitation can be overcome by reporting confidence intervals for papers' main estimates and discussing their economic interpretation.
A cryo-tomography-based volumetric model of the actin core of mouse vestibular hair cell stereocilia lacking plastin 1.

Abstract Electron cryo-tomography allows for high-resolution imaging of stereocilia in their native state. Because their actin filaments have a higher degree of order, we imaged stereocilia from mice lacking the actin crosslinker plastin 1 (PLS1). We found that while stereocilia actin filaments run 13 nm apart in parallel for long distances, there were gaps of significant size that were stochastically distributed throughout the actin core. Actin crosslinkers were distributed through the stereocilium, but did not occupy all possible binding sites. At stereocilia tips, protein density extended beyond actin filaments, especially on the side of the tip where a tip link is expected to anchor. Along the shaft, repeating density was observed that corresponds to actin-to-membrane connectors. In the taper region, most actin filaments terminated near the plasma membrane. The remaining filaments twisted together to make a tighter bundle than was present in the shaft region; the spacing between them decreased from 13 nm to 9 nm, and the apparent filament diameter decreased from 6.4 to 4.8 nm. Our models illustrate detailed features of distinct structural domains that are present within the stereocilium.
Understanding the healthcare experiences and needs of African immigrants in the United States: a scoping review.

Africans immigrants in the United States are the least-studied immigrant group, despite the research and policy efforts to address health disparities within immigrant communities. Although their healthcare experiences and needs are unique, they are often included in the “black” category, along with other phenotypically-similar groups. This process makes utilizing research data to make critical healthcare decisions specifically targeting African immigrants, difficult. The purpose of this Scoping Review was to examine extant information about African immigrant health in the U.S., in order to develop lines of inquiry using the identified knowledge-gaps. Literature published in the English language between 1980 and 2016 were reviewed in five stages: (1) identification of the question and (b) relevant studies, (c) screening, (d) data extraction and synthesis, and (e) results. Databases used included EBSCO, ProQuest, PubMed, and Google Scholar (hand-search). The articles were reviewed according to title and abstract, and studies deemed relevant were reviewed as full-text articles. Data was extracted from the selected articles using the inductive approach, which was based on the comprehensive reading and interpretive analysis of the organically emerging themes. Finally, the results from the selected articles were presented in a narrative format. Culture, religion, and spirituality were identified as intertwined key contributors to the healthcare experiences of African immigrants. In addition, lack of culturally-competent healthcare, distrust, and complexity, of the U.S. health system, and the exorbitant cost of care, were identified as major healthcare access barriers. Knowledge about African immigrant health in the U.S. is scarce, with available literature mainly focusing on databases, which make it difficult to identify African immigrants. To our knowledge, this is the first Scoping Review pertaining to the healthcare experiences and needs of African immigrants in the U.S.
Mathematical Models of Protease-Based Enzymatic Biosensors.

An important goal of synthetic biology is to build biosensors and circuits with well-defined input–output relationships that operate at speeds found in natural biological systems. However, for molecular computation, most commonly used genetic circuit elements typically involve several steps from input detection to output signal production: transcription, translation, and post-translational modifications. These multiple steps together require up to several hours to respond to a single stimulus, and this limits the overall speed and complexity of genetic circuits. To address this gap, molecular frameworks that rely exclusively on post-translational steps to realize reaction networks that can process inputs at a time scale of seconds to minutes have been proposed. Here, we build mathematical models of fast biosensors capable of producing Boolean logic functionality. We employ protease-based chemical and light-induced switches, investigate their operation, and provide selection guidelines for their use as on–...
Whole genome analysis identifies the association of TP53 genomic deletions with lower survival in Stage III colorectal cancer

DNA copy number aberrations (CNA) are frequently observed in colorectal cancers (CRC). There is an urgent need for CNA-based biomarkers in clinics,. n For Stage III CRC, if combined with imaging or pathologic evidence, these markers promise more precise care. We conducted this Stage III specific biomarker discovery with a cohort of 134 CRCs, and with a newly developed high-efficiency CNA profiling protocol. Specifically, we developed the profiling protocol for tumor-normal matched tissue samples based on low-coverage clinical whole-genome sequencing (WGS). We demonstrated the protocol’s accuracy and robustness by a systematic benchmark with microarray, high-coverage whole-exome and -genome approaches, where the low-coverage WGS-derived CNA segments were highly accordant (PCC >0.95) with those derived from microarray, and they were substantially less variable if compared to exome-derived segments. A lasso-based model and multivariate cox regression analysis identified a chromosome 17p loss, containing the TP53 tumor suppressor gene, that was significantly associated with reduced survival (P = 0.0139, HR = 1.688, 95% CI = [1.112–2.562]), which was validated by an independent cohort of 187 Stage III CRCs. In summary, this low-coverage WGS protocol has high sensitivity, high resolution and low cost and the identified 17p-loss is an effective poor prognosis marker for Stage III patients.
Robust Barrier Functions for a Fully Autonomous, Remotely Accessible Swarm-Robotics Testbed

The Robotarium, a remotely accessible swarm-robotics testbed, has provided free, open access to robotics and controls research for hundreds of users in thousands of experiments. This high level of usage requires autonomy in the system, which mainly corresponds to constraint satisfaction in the context of users’ submissions. In other words, in case that the users’ inputs to the robots may lead to collisions, these inputs must be altered to avoid these collisions automatically. However, these alterations must be minimal so as to preserve the users’ objective in the experiment. Toward this end, the system has utilized barrier functions, which admit a minimally invasive controller-synthesis procedure. However, barrier functions are yet to be robustified with respect to unmodeled disturbances (e.g., wheel slip or packet loss) in a manner conducive to real-time synthesis. As such, this paper formulates robust barrier functions for a general class of disturbed control-affine systems that, in turn, is key for the Robotarium to operate fully autonomously (i.e., without human supervision). Experimental results showcase the effectiveness of this robust formulation in a long-term experiment in the Robotarium.
Cross-linker control of vitrimer flow

Vitrimers are a class of covalent adaptable networks (CANs) that undergo topology reconfiguration via associative exchange reactions, enabling reprocessing at elevated temperatures. Here, we show that cross-linker reactivity represents an additional design parameter to tune stress relaxation rates in vitrimers. Guided by calculated activation barriers, we prepared a series of cross-linkers with varying reactivity for the conjugate addition—elimination of thiols in a PDMS vitrimer. Surprisingly, despite a wide range of stress relaxation rates, we observe that the flow activation energy of the bulk material is independent of the cross-linker structure. Superposition of storage and loss moduli from frequency sweeps can be performed for different cross-linkers, indicating the same exchange mechanism. We show that we can mix different cross-linkers in a single material in order to further modulate the stress relaxation behavior.
Binary X-ray pulsars

Progress made over the last decade in the understanding of the binary X-ray pulsars is reviewed. The characteristics of the pulse profiles of the known binary X-ray pulsars are discussed, and observed variations in pulse period corresponding to the spin-up of the neutron star are considered. Determinations of the orbits and binary system parameters of the binary X-ray pulsars from measurements of pulse arrival times are then examined. Attention is also given to current problems in binary X-ray pulsars, including the apsidal motion test, which allows the determination of the mass distribution within a star, the X-ray source 4U 1626-67, which is believed to be a highly compact binary X-ray source, and the observation of very faint X-ray pulsars with the Einstein Observatory.
And Now for Something Completely Different: The Versatility of Conceptual Innovators

Art critics and scholars have puzzled over the behavior of Pablo Picasso, Gerhard Richter, and Sigmar Polke, three important modern painters who have made frequent and abrupt changes of style. In each case, assuming this behavior to be idiosyncratic, the experts consequently failed to recognize its common basis. But stylistic versatility is in fact often a characteristic of conceptual innovators whose ability to solve specific problems can free them to pursue new goals. This contrasts sharply with the practice of experimental artists, whose inability to achieve their goals often ties them to a single style for an entire career. The phenomenon of the conceptual innovator who produces diverse innovations is an important and new feature of twentieth-century art; Picasso was the prototype, and he has been followed by a series of others, from Marcel Duchamp and Francis Picabia to Bruce Nauman and Damien Hirst. Versatility has furthermore been a characteristic not only of modern painters but also of conceptual ...
Social Interaction Models

Social interaction is modeled in behavior genetics as the influence of one individual's phenotype on another. The consequences of this for phenotypic variances and covariances among relatives of different degrees of relationship can be predicted from an extension to the usual path models. Social cooperation (or imitation) and social competition (or contrast) result in different patterns of variation and resemblance that depend on the prior similarity of the interacting pair. Although of considerable theoretical interest, the behavior genetics literature does not offer many convincing examples of the empirical effects of such social interactions. Keywords: social interaction; path models; cooperation; imitation; competition; contrast; variance; covariance; family resemblance; sibling resemblance
Knowledge of endometrial cancer risk factors in a general gynecologic population

Abstract Objectives To determine knowledge regarding endometrial cancer (EC) risk factors in a general gynecologic patient population. Study design A questionnaire survey regarding health behaviors and knowledge of risk factors of EC was administered to patients presenting for routine gynecologic care at two general gynecologic practices affiliated with a tertiary-care center between August and October 2014. Patient demographics, lifestyle information, and knowledge regarding EC risk factors were assessed. Data were analyzed using univariable and bivariable analyses, Χ2 tests, Fischer's exact tests, and t-tests. Results 231 women responded. Median age was 56 years old (IQR 25–64), and 87% were Caucasian. Median BMI was 24.9 (IQR 22.3–29.2). 24.7% were overweight and 24.3% obese. The majority (69.4%) of patients received a college or graduate degree. Over half of the women (52.1%) did not know that obesity was associated with increased risk of EC. When dichotomized based on obese vs non obese, there was no difference in patients' knowledge of the association between obesity and EC (47% vs 48%, respectively, p = .93). 91% of all respondents reported that their gynecologist or primary care physician had never discussed the risks of EC with them. Conclusions Regardless of education level, age or obesity status, the majority of women did not know the common risks of EC. Increased efforts towards educating women regarding obesity and other risk factors of EC are necessary in order to reduce the rising incidence of EC, a predominantly obesity-driven disease. Interventions must include general obstetrician-gynecologists and primary care providers.
ON TWO OF ERDÖS’S OPEN PROBLEMS

This short note presents some remarks and conjectures on two open problems proposed by P. Erdos.
An Unlucky Feeling: Overconfidence and Noisy Feedback

Abstract How do individuals’ beliefs respond to ego-relevant information? After receiving noisy, but unbiased performance feedback, participants in an experiment overestimate their own scores on a quiz and believe their feedback to be ‘unlucky’, estimating that it under-represents their score by 13%. However, they exhibit no such overconfidence in non-ego-relevant beliefs—in this case, estimates of others’ scores. Comparing subjects’ belief-updating to the Bayesian benchmark, we find that this ‘unlucky feeling’ is largely due to overconfident priors, with biased updating driving overconfidence only among the participants with the worst-calibrated beliefs. This suggests that social comparisons contribute to the biased response to feedback on relative performance observed in other studies. While feedback improves performance estimates, this learning does not translate into improved estimates of subsequent performances. This suggests that beliefs about ability are updated differently than beliefs about a particular performance, contributing to the persistence of overconfidence.
The abundance and distribution of water vapor in Jupiter's atmosphere

The atmospheric transmission window between 1800 and 2250/cm in Jupiter's atmosphere was observed from the Kuiper Airborne Observatory and by the IR spectrometer (IRIS) on Voyager. The vertical distribution of H2O was derived for the 1-6 bar portion of Jupiter's troposphere. The spatial variation of H2O was measured using IRIS spectra of the Hot Spots in the North and South Equatorial Belts (NEB, SEB) and the Equatorial Zone and for an average of the North and South Tropical Zones. The H2O column abundance above the 4 bar level is the same in the zones as in the SEB Hot Spots, about 20 cm amagats. The NEB Hot Spots are desiccated by a factor of 3 with respect to the rest of Jupiter. For an average between -40 and +40 deg latitude, the H2O mole fraction, qH2O, is saturated for P less than 2 bars, qH2O = 4 millionths in the 2-4 bar range, and it increases to 3/100,000 at 6 bars. A similar vertical profile applies to the spatially resolved zone and belt spectra, except that H2O falls off more rapidly at P less than 4 bars in the NEB Hot Spots. A massive H2O cloud at 5 bars, T = 273 K is inconsistent with the observations. Instead, a thin H2O ice cloud would form at 2 bars, T = 200 K. The O/H ratio in Jupiter, inferred from H2O measurements in both belts and zones at 6 bars, is depleted by a factor of 50 with respect to the sun.
On enumerators of smirnov words by descents and cyclic descents

A Smirnov word is a word over the positive integers in which adjacent letters must be different. A symmetric function enumerating these words by descent number arose in the work of Shareshian and the second named author on $q$-Eulerian polynomials, where a $t$-analog of a formula of Carlitz, Scoville, and Vaughan for enumerating Smirnov words is proved. A symmetric function enumerating a circular version of these words by cyclic descent number arose in the work of the first named author on chromatic quasisymmetric functions of directed graphs, where a $t$-analog of a formula of Stanley for enumerating circular Smirnov words is proved. In this paper we obtain new $t$-analogs of the Carlitz-Scoville-Vaughan formula and the Stanley formula in which the roles of descent number and cyclic descent number are switched. These formulas show that the Smirnov word enumerators are polynomials in $t$ whose coefficients are e-positive symmetric functions. We also obtain expansions in the power sum basis and the fundamental quasisymmetric function basis, complementing earlier results of Shareshian and the authors. Our work relies on studying refinements of the Smirnov word enumerators that count certain restricted classes of Smirnov words by descent number. Applications to variations of $q$-Eulerian polynomials and to the chromatic quasisymmetric functions introduced by Shareshian and the second named author are also presented.
Acute normovolemic hemodilution.

Background The inherent risks of blood transfusion have led to concerted efforts to find alternatives to allogeneic blood transfusion. Among these alternatives are supplementation with iron and treatment with erythropoietin, autologous pre-donation before major elective surgery, intraoperative blood salvage (particularly for emergency cases or when major blood loss is unanticipated), acute normovolemic hemodilution, and artificial blood substitutes. Methods Review of pertinent English-language literature. Results Autologous pre-donation of the patient's own blood, even if supplemented with iron and erythropoietin, is increasingly out of favor for several reasons. Autologous pre-donation is an added out-of-pocket expense for the patient. The major cause of incompatible blood transfusion, namely clerical error, is not eliminated. Moreover, autologous pre-donated blood is not released to the general blood supply; therefore, autologous blood that is not returned to the patient by infusion is wasted. Acute normovolemic hemodilution is a safe alternative that eliminates the risk of mistransfusion, minimizes the shed red cell mass when bleeding occurs, and reduces the risk of perioperative transfusion as shown in patients undergoing radical prostatectomy. Conclusions Acute normovolemic hemodilution achieves equivalent outcomes at lower cost compared with autologous pre-donation. Patient safety is increased, and if pharmacologic strategies are combined with acute normovolemic hemodilution, allogeneic blood transfusion may be eliminated entirely.
Sense and Sensibility: Characterizing Social Media Users Regarding the Use of Controversial Terms for COVID-19

With the world-wide development of 2019 novel coronavirus, although WHO has officially announced the disease as COVID-19, one controversial term - "Chinese Virus" is still being used by a great number of people. In the meantime, global online media coverage about COVID-19-related racial attacks increases steadily, most of which are anti-Chinese or anti-Asian. As this pandemic becomes increasingly severe, more people start to talk about it on social media platforms such as Twitter. When they refer to COVID-19, there are mainly two ways: using controversial terms like "Chinese Virus", or using non-controversial terms like "Coronavirus". We attempt to characterize the Twitter users who use controversial terms and those who use non-controversial terms. We use the Tweepy API to retrieve 17 million related tweets and the information of their authors. We find significant differences between these two groups of Twitter users across their demographics, user-level features like the number of followers, political following status, as well as geo-locations. We apply classification models to predict Twitter users who are more likely to use controversial terms. To our best knowledge, this is the first large-scale social media-based study to characterize users with respect to their usage of controversial terms during a major crisis.
Unbiased Identification of trans Regulators of ADAR and A-to-I RNA Editing

Adenosine-to-inosine RNA editing is catalyzed by adenosine deaminase acting on RNA (ADAR) enzymes that deaminate adenosine to inosine. Although many RNA editing sites are known, few trans regulators have been identified. We perform BioID followed by mass spectrometry to identify trans regulators of ADAR1 and ADAR2 in HeLa and M17 neuroblastoma cells. We identify known and novel ADAR-interacting proteins. Using ENCODE data, we validate and characterize a subset of the novel interactors as global or site-specific RNA editing regulators. Our set of novel trans regulators includes all four members of the DZF-domain-containing family of proteins: ILF3, ILF2, STRBP, and ZFR. We show that these proteins interact with each ADAR and modulate RNA editing levels. We find ILF3 is a broadly influential negative regulator of editing. This work demonstrates the broad roles that RNA binding proteins play in regulating editing levels, and establishes DZF-domain-containing proteins as a group of highly influential RNA editing regulators.
Gaze-Net: appearance-based gaze estimation using capsule networks

Recent studies on appearance based gaze estimation indicate the ability of Neural Networks to decode gaze information from facial images encompassing pose information. In this paper, we propose Gaze-Net: A capsule network capable of decoding, representing, and estimating gaze information from ocular region images. We evaluate our proposed system using two publicly available datasets, MPIIGaze (200,000+ images in the wild) and Columbia Gaze (5000+ images of users with 21 gaze directions observed at 5 camera angles/positions). Our model achieves a Mean Absolute Error (MAE) of 2.84° for Combined angle error estimate within dataset for MPI-IGaze dataset. Further, model achieves a MAE of 10.04° for across dataset gaze estimation error for Columbia gaze dataset. Through transfer learning, the error is reduced to 5.9°. The results show this approach is promising with implications towards using commodity webcams to develop low-cost multi-user gaze tracking systems.
A Blockchain-Encryption-Based Approach to Protect Fog Federations from Rogue Nodes

People have used cloud computing approach to store their data remotely. As auspicious as this approach is, it brings forth many challenges: from data security to time latency issues with data computation as well as delivery to end users. Fog computing has emerged as an extension for cloud computing to bring data processing and storage close to end-users; however, it minimizes the time latency issue but still suffers from data security challenges. For instance, when a fog node providing services to end users is compromised, the users’ data security can be violated. Thus, this paper proposes a secure and fine-grained data access control scheme by integrating the Ciphertext Policy Attribute-Based Encryption (CP-ABE) algorithm and blockchain concept to prevent fog nodes from violating end users’ data security in a situation where a compromised fog node is being ousted. We also classify the fog nodes into fog federations, based on their attributes such as services and locations, to minimize the time latency and communication overhead between fog nodes and cloud server. Further, the exploitation and integration of the blockchain concept and the CP-ABE algorithm enables fog nodes in the same fog federation to perform the authorization process in a distributed manner. In addition, to solve time latency and communication overhead problems, we equip every fog node with an off-chain database to store most frequently accessed data files for specific time, and with an on-chain access control policies table (On-chain Files Tracking Table) which must be protected from being tampered by malicious (rogue) fog nodes. Therefore, blockchain plays a vital role here as it is tamper-proof by nature. We demonstrate our scheme’s efficiency and feasibility by designing algorithms and conducting a security analysis. The provided analysis shows that the proposed scheme is efficient and feasible in ousting malicious (rogue) fog nodes.
Combinatorial quorum sensing in Pseudomonas aeruginosa allows for novel cheating strategies.

In the opportunistic pathogen Pseudomonas aeruginosa, quorum sensing (QS) is a social trait that is exploitable by non-cooperating cheats. Previously it has been shown that by linking QS to the production of both public and private goods, cheats can be prevented from invading populations of cooperators and this was described by Dandekar et al. (Science 2012;338:264–266) as ‘a metabolic incentive to cooperate’. We hypothesized that P. aeruginosa could evolve novel cheating strategies to circumvent private goods metabolism by rewiring its combinatorial response to two QS signals (3O-C12-HSL and C4-HSL). We performed a selection experiment that cycled P. aeruginosa between public and private goods growth media and evolved an isolate that rewired its control of cooperative protease expression from a synergistic (AND-gate) response to dual-signal input to a 3O-C12-HSL-only response. We show that this isolate circumvents metabolic incentives to cooperate and acts as a combinatorial signalling cheat, with higher fitness in competition with its ancestor. Our results show three important principles: first, combinatorial QS allows for diverse social strategies to emerge; second, restrictions levied by private goods are not sufficient to explain the maintenance of cooperation in natural populations; and third, modifying combinatorial QS responses could result in important physiological outcomes in bacterial populations.
PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofing

Face anti-spoofing has become an increasingly important and critical security feature for authentication systems, due to rampant and easily launchable presentation attacks. Addressing the shortage of multi-modal face dataset, CASIA recently released the largest up-to-date CASIA-SURF Cross-ethnicity Face Anti-spoofing(CeFA) dataset, covering 3 ethnicities, 3 modalities, 1607 subjects, and 2D plus 3D attack types in four protocols, and focusing on the challenge of improving the generalization capability of face anti-spoofing in cross-ethnicity and multi-modal continuous data. In this paper, we propose a novel pipeline-based multi-stream CNN architecture called PipeNet for multimodal face anti-spoofing. Unlike previous works, Selective Modal Pipeline (SMP) is designed to enable a customized pipeline for each data modality to take full advantage of multi-modal data. Limited Frame Vote (LFV) is designed to ensure stable and accurate prediction for video classification. The proposed method wins the third place in the final ranking of Chalearn Multi-modal Cross-ethnicity Face Anti-spoofing Recognition Challenge@CVPR2020. Our final submission achieves the Average Classification Error Rate (ACER) of 2.21 ± 1.26 on the test set.
Four-dimensional dominance range reporting in linear space

In this paper we study the four-dimensional dominance range reporting problem and present data structures with linear or almost-linear space usage. Our results can be also used to answer four-dimensional queries that are bounded on five sides. The first data structure presented in this paper uses linear space and answers queries in O(log^{1+e} n + k log^e n) time, where k is the number of reported points, n is the number of points in the data structure, and e is an arbitrarily small positive constant. Our second data structure uses O(n log^e n) space and answers queries in O(log n+k) time. These are the first data structures for this problem that use linear (resp. O(n log^e n)) space and answer queries in poly-logarithmic time. For comparison the fastest previously known linear-space or O(n log^e n)-space data structure supports queries in O(n^e + k) time (Bentley and Mauer, 1980). Our results can be generalized to d ≥ 4 dimensions. For example, we can answer d-dimensional dominance range reporting queries in O(log log n (log n/log log n)^{d-3} + k) time using O(n log^{d-4+e} n) space. Compared to the fastest previously known result (Chan, 2013), our data structure reduces the space usage by O(log n) without increasing the query time.
Upper bounds on the coarsening rate of discrete, ill-posed nonlinear diffusion equations

We prove a weak upper bound on the coarsening rate of the discrete-in-space version of an ill-posed, nonlinear diffusion equation. The continuum version of the equation violates parabolicity and lacks a complete well-posedness theory. In particular, numerical simulations indicate very sensitive dependence on initial data. Nevertheless, models based on its discrete-in-space version, which we study, are widely used in a number of applications, including population dynamics (chemotactic movement of bacteria), granular flow (formation of shear bands), and computer vision (image denoising and segmentation). Our bounds have implications for all three applications. © 2008 Wiley Periodicals, Inc.
The Structure of Rubber Networks with Multifunctional Junctions

Abstract A number of statistical relationships have been derived for calculating the structure of rubber networks with multifunctional junctions. Some of these quantities appear as parameters in the molecular theory of elastic energy in phantom networks. Others relate to Langley's trapping factor for the entanglement contribution to the modulus, to the maximum extensibility, and to the viscoelastic properties of networks.
Presidential antagonism and central bank credibility

This paper uses an online survey experiment to study how President Trump's criticism of the Federal Reserve may affect consumers' long‐run inflation expectations, confidence in the Fed, and responsiveness to information about inflation. A random subset of respondents view one of President Trump's critical tweets about the Fed, or the tweet plus a Washington Post article discussing the President as a threat to the Fed's independence. All respondents provide long‐run inflation forecasts, before and after receiving information about past inflation and the Fed's inflation target. Finally, respondents rate their confidence in the President and the Fed. Respondents who view the tweet or tweet plus article have final long‐run inflation forecasts that are farther from the Fed's target after exposure to information about the Fed's target and recent inflation. Exposure to the tweet plus news article has a polarizing effect on confidence, increasing the share of respondents with high confidence in either the Fed or the President.
A Theory of Entanglement

This article presents the basis of a theory of entanglement. We begin with a classical theory of entangled discrete measures. Then, we treat quantum mechanics and discuss the statistics of bounded operators on a Hilbert space in terms of context coefficients. Finally, we combine both topics to develop a general theory of entanglement for quantum states. A measure of entanglement called the entanglement number is introduced. Although this number is related to entanglement robustness, its motivation is not the same and there are some differences. The present article only involves bipartite systems and we leave the study of multipartite systems for later work. Quanta 2020; 9: 7–15.
Structure-Based Design with Tag-Based Purification and In-Process Biotinylation Enable Streamlined Development of SARS-CoV-2 Spike Molecular Probes

Biotin-labeled molecular probes, comprising specific regions of the SARS-CoV-2 spike, would be helpful in the isolation and characterization of antibodies targeting this recently emerged pathogen. To develop such probes, we designed constructs incorporating an N-terminal purification tag, a site-specific protease-cleavage site, the probe region of interest, and a C-terminal sequence targeted by biotin ligase. Probe regions included full-length spike ectodomain as well as various subregions, and we also designed mutants to eliminate recognition of the ACE2 receptor. Yields of biotin-labeled probes from transient transfection ranged from ~0.5 mg/L for the complete ectodomain to >5 mg/L for several subregions. Probes were characterized for antigenicity and ACE2 recognition, and the structure of the spike ectodomain probe was determined by cryo-electron microscopy. We also characterized antibody-binding specificities and cell-sorting capabilities of the biotinylated probes. Altogether, structure-based design coupled to efficient purification and biotinylation processes can thus enable streamlined development of SARS-CoV-2 spike-ectodomain probes. Funding: Support for this work was provided by the Intramural Research Program of the Vaccine Research Center, National Institute of Allergy and Infectious Diseases (NIAID). Support for this work was also provided by COVID-19 Fast Grants, the Jack Ma Foundation, the Self Graduate Fellowship Program, and NIH grants DP5OD023118, R21AI143407, and R21AI144408. Some of this work was performed at the Columbia University Cryo-EM Center at the Zuckerman Institute, and some at the Simons Electron Microscopy Center (SEMC) and National Center for Cryo-EM Access and Training (NCCAT) located at the New York Structural Biology Center, supported by grants from the Simons Foundation (SF349247), NYSTAR, and the NIH National Institute of General Medical Sciences (GM103310). Conflict of Interest: The authors declare that they have no conflict of interest. Ethical Approval: Peripheral blood mononuclear cells (PBMCs) for B cell sorting were obtained from a convalescent SARS-CoV-2 patient (collected 75 days post symptom onset under an IRB approved clinical trial protocol, VRC 200 - ClinicalTrials.gov Identifier: NCT00067054) and a healthy control donor from the NIH blood bank pre-SARS-CoV-2 pandemic.
High-cadence Dispersed Spectral Analysis of Supernova Remnant 1987A

We present an analysis of the dispersed spectral data from 11 epochs (March 2011 to September 2018) of supernova remnant (SNR) 1987A observations performed with Chandra. These observations were performed with the High Energy Transmission Grating (HETG) as part of our ongoing Chandra monitoring campaign of SNR 1987A, whose 1st-order dispersed spectrum provides a significantly greater energy resolution than the previously-published 0th-order spectrum. Our data sets with moderate exposure times of ~50-70ks per epoch cover the time period between deep Chandra HETG observations (with individual exposures >200ks) taken in March 2011 and March 2018. These data have a much higher cadence than the widely-spaced deep high-resolution spectra, at the expense of total exposure time. While statistical uncertainties are large due to low photon count statistics in the observed 1st-order spectra, we find that spectral model parameters are generally in line with the shock wave propagating into the medium beyond the dense inner ring, as suggested by Frank et al. 2016. As the reverse shock begins ionizing the heavier elements of the supernova ejecta interior to the equatorial ring, spectral fit parameters are expected to change as the chemical makeup and physical properties of the shocked gas evolve. Based on our broadband spectral model fits, we find that abundance values appear to be constant in this time period. While our results are somewhat limited due to photon statistics, we demonstrate the utility of the dispersed HETG spectral analysis that can be performed with our regular Chandra monitoring observations of SNR 1987A.
Ultraviolet Spectroscopy of Comets

Results of observations of comets in the ultraviolet are reviewed in relation to their significance for the chemistry and physics of the cometary coma and the composition of the cometary ice. Ultraviolet cometary observations began in 1970, when a hydrogen envelope was discovered extending millions of kilometers from the nucleus of comet Bennett, and continued with the discovery of oxygen and carbon in comet Kohoutek and the acquisition of comprehensive UV spectra from comets West (1976 VI), Seargent (1978 XV) and Bradfield (1979 X). The available cometary spectra are remarkably similar, indicative of a common composition and origin for comets and the insignificance of chemical reactions in the inner coma to species abundances. Ultraviolet spectroscopy has also allowed the determination of gas production rates from either the surface brightness or the total luminosity in a given spectral line. IUE observations of comet Bradfield reveal the water production rate to vary as the -3.7 power of heliocentric distance from 0.71 to 1.55 AU, incompatible with solar energy input as the controlling influence on water vaporization.
How to Count Triangles, without Seeing the Whole Graph

Triangle counting is a fundamental problem in the analysis of large graphs. There is a rich body of work on this problem, in varying streaming and distributed models, yet all these algorithms require reading the whole input graph. In many scenarios, we do not have access to the whole graph, and can only sample a small portion of the graph (typically through crawling). In such a setting, how can we accurately estimate the triangle count of the graph? We formally study triangle counting in the random walk access model introduced by Dasgupta et al (WWW '14) and Chierichetti et al (WWW '16). We have access to an arbitrary seed vertex of the graph, and can only perform random walks. This model is restrictive in access and captures the challenges of collecting real-world graphs. Even sampling a uniform random vertex is a hard task in this model. Despite these challenges, we design a provable and practical algorithm, TETRIS, for triangle counting in this model. TETRIS is the first provably sublinear algorithm (for most natural parameter settings) that approximates the triangle count in the random walk model, for graphs with low mixing time. Our result builds on recent advances in the theory of sublinear algorithms. The final sample built by TETRIS is a careful mix of random walks and degree-biased sampling of neighborhoods. Empirically, TETRIS accurately counts triangles on a variety of large graphs, getting estimates within 5% relative error by looking at 3% of the number of edges.
Extracting Information Overlap in Simultaneous OH-PLIF and PIV Fields with Neural Networks

Abstract Simultaneous measurements, such as the combination of particle image velocimetry (PIV) for velocity fields with planar laser induced fluorescence (PLIF) for species fields, are widely used in experimental turbulent combustion applications for the analysis of a plethora of complex physical processes. Such physical analyses are driven by the interpretation of spatial correlations between these fields by the experimenter. However, these correlations also imply some amount of intrinsic redundancy; the simultaneous fields carry overlapping information content. The goal of this work lies in the quantitative extraction of this overlap in simultaneous field measurements. Specifically, the amount of PIV information contained in simultaneously measured OH-PLIF fields in the domain of a swirl-stabilized combustor is sought. This task is accomplished using machine learning techniques based on artificial neural networks designed to optimize PLIF-to-PIV mappings. It was found that most of the velocity information content could be retrieved when considering linear combinations of neighborhoods of OH-PLIF signal spanning roughly two integral lengthscales (half of the considered domain), and that PLIF signal interactions residing in smaller, local regions (less than half of the domain) captured no PIV information. Further, by visualizing the coherent structures within the neural network parameters, the role of multi-scale interactions related to velocity field retrieval from the OH-PLIF signal became more apparent. Overall, this study reveals a useful pathway (in the form of overlapping information content extraction) to develop diagnostic tools that capture more information using the same experimental resources by minimizing redundancy.
Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19) pandemic, has infected millions of people and caused hundreds of thousands of deaths. While COVID-19 has overwhelmed healthcare resources (e.g., healthcare personnel, testing resources, hospital beds, and ventilators) in a number of countries, limited research has been conducted to understand spatial accessibility of such resources. This study fills this gap by rapidly measuring the spatial accessibility of COVID-19 healthcare resources with a particular focus on Illinois, USA. The rapid measurement is achieved by resolving computational intensity of an enhanced two-step floating catchment area (E2SFCA) method through a parallel computing strategy based on cyberGIS (cyber geographic information science and systems). The E2SFCA has two major steps. First, it calculates a bed-to-population ratio for each hospital location. Second, it sums these ratios for residential locations where hospital locations overlap. The comparison of the spatial accessibility measures for COVID-19 patients to those of population at risk identifies which geographic areas need additional healthcare resources to improve access. The results also help delineate the areas that may face a COVID-19-induced shortage of healthcare resources. The Chicagoland, particularly the southern Chicago, shows an additional need for resources. This study also identified vulnerable population residing in the areas with low spatial accessibility in Chicago. Rapidly measuring spatial accessibility of healthcare resources provides an improved understanding of how well the healthcare infrastructure is equipped to save people’s lives during the COVID-19 pandemic. The findings are relevant for policymakers and public health practitioners to allocate existing healthcare resources or distribute new resources for maximum access to health services.