cssi/SciSciGPT-SciSciNet huggingface dataset:
Harmless Interpolation of Noisy Data in Regression

A continuing mystery in understanding the empirical success of deep neural networks is their ability to achieve zero training error and generalize well, even when the training data is noisy and there are more parameters than data points. We investigate this overparameterized regime in linear regression, where all solutions that minimize training error interpolate the data, including noise. We lower-bound the fundamental generalization (mean-squared) error of any interpolating solution in the presence of noise, and show that this bound decays to zero with the number of features. Thus, overparameterization can be beneficial in ensuring harmless interpolation of noise. We discuss two root causes for poor generalization that are complementary in nature – signal “bleeding” into a large number of alias features, and overfitting of noise by parsimonious feature selectors. For the sparse linear model with noise, we provide a hybrid interpolating scheme that mitigates both these issues and achieves order-optimal MSE over all possible interpolating solutions.
Spatial decomposition analysis of NO2 and PM2.5 air pollution in the United States

Abstract Length scales for spatial variability of air pollution concentrations depend on the pollutant and the location. In this paper, we develop a readily scalable algorithm based on “spatial-increment”, to decompose the air pollution concentration into four spatial components: long-range, mid-range, neighborhood, and near-source. We apply the algorithm to annual-average concentrations of outdoor nitrogen dioxide (NO2) and fine particulate matter (PM2.5) for all census blocks in the contiguous US. For NO2, “neighborhood” and “mid-range” components dominate both within-city and between-city concentration differences (both components are ~5-fold larger in large urbanized areas than rural areas). For PM2.5, the “long-range” component dominates; this component varies by region (e.g., is three times greater in the Midwest [7 μg/m3] than in the West [2.3 μg/m3]), whereas variation by urban area size is relatively minor. Our study provides the first nation-level fine-scale decomposed pollution surfaces to date; this dataset is publicly available. Results can be used to estimate, at least to a zeroth order, the contribution of sources at different distances from the receptor to the annual average pollution in a location of interest.
Efficient and accurate inference of microbial trajectories from longitudinal count data

The human body is home to trillions of microbial cells that play an essential role in health and disease [2]. The gut microbiome, for instance, is responsible for a variety of normal physiological processes such as the regulation of immune response and breakdown of xenobiotics [3]. Disturbances in gut communities have been associated with several diseases, notably obesity [7] and colitis [8]. Moreover, changes to the vaginal microbiome during pregnancy are associated with risk of preterm birth [4]. Consequently, investigating the human microbiome can provide insight into biological processes and the etiology of disease.
Effect of agrochemical exposure on Schistosoma mansoni cercariae survival and activity

Singular use of activity assays or staining dyes to assess pathogen agrochemical tolerance can underestimate tolerance if pesticides cause sublethal effects. We exposed Schistosoma mansoni cercariae, the aquatic life stage of this trematode that infects humans, to 4 insecticides at 5 concentrations using a 24-h time-to-death assay. We used Trypan blue dye, which stains dead tissue, and activity assays simultaneously to discriminate dead from live but paralyzed individuals. Whereas cypermethrin, deltamethrin, and dimethoate exposure did not affect cercariae at any ecologically relevant concentrations, methamidophos exposure increased survival of cercariae compared with those in the controls. This was because methamidophos-induced paralysis reduced cercarial activity and thus energy expenditures, extending the lifespan of this short-lived parasite that causes human schistosomiasis. These findings highlight that sublethal effects should be considered when pesticide effects on disease are under investigation. Environ Toxicol Chem 2020;39:1421-1428. © 2020 SETAC.
Adversarial machine learning for cybersecurity and computer vision: Current developments and challenges

We provide a comprehensive overview of adversarial machine learning focusing on two application domains, i.e., cybersecurity and computer vision. Research in adversarial machine learning addresses a significant threat to the wide application of machine learning techniques -- they are vulnerable to carefully crafted attacks from malicious adversaries. For example, deep neural networks fail to correctly classify adversarial images, which are generated by adding imperceptible perturbations to clean images.We first discuss three main categories of attacks against machine learning techniques -- poisoning attacks, evasion attacks, and privacy attacks. Then the corresponding defense approaches are introduced along with the weakness and limitations of the existing defense approaches. We notice adversarial samples in cybersecurity and computer vision are fundamentally different. While adversarial samples in cybersecurity often have different properties/distributions compared with training data, adversarial images in computer vision are created with minor input perturbations. This further complicates the development of robust learning techniques, because a robust learning technique must withstand different types of attacks.
A Common Model for Cytokine Receptor Activation: Combined Scissor-Like Rotation and Self-Rotation of Receptor Dimer Induced by Class I Cytokine

The precise mechanism by which the binding of a class I cytokine to the extracellular domain of its corresponding receptor transmits a signal through the cell membrane remains unclear. Receptor activation involves a cytokine-receptor complex with a 1:2 stoichiometry. Previously we used our transient-complex theory to calculate the rate constant of the initial cytokine-receptor binding to form a 1:1 complex. Here we computed the binding pathway leading to the 1:2 activation complex. Three cytokine systems (growth hormone, erythropoietin, and prolactin) were studied, and the focus was on the binding of the extracellular domain of the second receptor molecule after forming the 1:1 complex. According to the transient-complex theory, translational and rotation diffusion of the binding entities bring them together to form a transient complex, which has near-native relative separation and orientation but not the short-range specific native interactions. Subsequently conformational rearrangement leads to the formation of the native complex. We found that the changes in relative orientations between the two receptor molecules from the transient complex to the 1:2 native complex are similar for the three cytokine-receptor systems. We thus propose a common model for receptor activation by class I cytokines, involving combined scissor-like rotation and self-rotation of the two receptor molecules. Both types of rotations seem essential: the scissor-like rotation separates the intracellular domains of the two receptor molecules to make room for the associated Janus kinase molecules, while the self-rotation allows them to orient properly for transphosphorylation. This activation model explains a number of experimental observations. The transient-complex based approach presented here may provide a strategy for designing antagonists and be useful for elucidating activation mechanisms of other receptors.
Electrical Characterization of Al-AlN(PSMBE Grown)-Si MIS Structures

AIN films were grown by plasma source Molecular Beam Epitaxy (PSMBE) on n-type Si(111) substrates under various growth parameters. I-V and C-V-f dependencies of AI-AIN-Si(111) MIS structures were measured. Electrical characterization of MIS structures with PSMBE grown textured AIN thin films as insulator shows that low current leakage can be achieved, although some samples have rectifying I-V dependencies. C-V-f characteristics reveal evidence of the presence of different types of traps. Additional investigations are needed in order to determine the nature of these traps.
“More than Meets the Eye”: A Guide to Interpreting the Descriptive Statistics and Correlation Matrices Reported in Management Research

The author of this essay wonders whether in teaching our students the latest analytic techniques we have neglected to emphasize the importance of understanding the most basic aspects of a study’s primary data. In response, he provides a 12-part answer to a fundamental question: “What information can be derived from reviewing the descriptive statistics and correlation matrix that appear in virtually every empirically based, nonexperimental paper published in the management discipline?” The seeming ubiquity of strained responses, to what many at first consider to be a vexed question about a mundane topic, leads the author to suggest that students at all levels, seasoned scholars, manuscript referees, and general consumers of management research may be unaware that the standard Table 1 in a traditional Results section reveals “more than meets the eye!”
The connectome of the Caenorhabditis elegans pharynx

Detailed anatomical maps of individual organs and entire animals have served as invaluable entry points for ensuing dissection of their evolution, development, and function. The pharynx of the nematode Caenorhabditis elegans is a simple neuromuscular organ with a self-contained, autonomously acting nervous system, composed of 20 neurons that fall into 14 anatomically distinct types. Using serial electron micrograph (EM) reconstruction, we re-evaluate here the connectome of the pharyngeal nervous system, providing a novel and more detailed view of its structure and predicted function. Contrasting the previous classification of pharyngeal neurons into distinct inter- and motor neuron classes, we provide evidence that most pharyngeal neurons are also likely sensory neurons and most, if not all, pharyngeal neurons also classify as motor neurons. Together with the extensive cross-connectivity among pharyngeal neurons, which is more widespread than previously realized, the sensory-motor characteristics of most neurons define a shallow network architecture of the pharyngeal connectome. Network analysis reveals that the patterns of neuronal connections are organized into putative computational modules that reflect the known functional domains of the pharynx. Compared with the somatic nervous system, pharyngeal neurons both physically associate with a larger fraction of their neighbors and create synapses with a greater proportion of their neighbors. We speculate that the overall architecture of the pharyngeal nervous system may be reminiscent of the architecture of ancestral, primitive nervous systems.
Systemic risk and the refinancing ratchet effect

Abstract The combination of rising home prices, declining interest rates, and near-frictionless refinancing opportunities can create unintentional synchronization of homeowner leverage, leading to a “ratchet” effect on leverage because homes are indivisible and owner-occupants cannot raise equity to reduce leverage when home prices fall. Our simulation of the U.S. housing market yields potential losses of $1.7 trillion from June 2006 to December 2008 with cash-out refinancing vs. only $330 billion in the absence of cash-out refinancing. The refinancing ratchet effect is a new type of systemic risk in the financial system and does not rely on any dysfunctional behaviors.
The Chemopreventive Role of Selenium in Carcinogenesis

This review discusses the effect of selenium intake on chemical carcinogenesis in animal models. Specifically, the available information in the following areas is summarized: (1) the dose response of selenium intake ranging from deficiency to supranutritional levels of supplementation, (2) the stage specificity of selenium-mediated inhibition of chemical carcinogenesis, (3) the effect of selenium on carcinogen metabolism and DNA adduct formation, and (4) dietary factors (vitamins A, C, and E) that influence the anticarcinogenic efficacy of selenium.
Cloud temperatures from ammonia observations

In association with an ammonia survey of the southern Galaxy (Peters et al., 1986), a search was made for improved analytical formulas to expedite the data analysis. Semi-empirical formulas are presented which relate the kinetic temperature of a molecular cloud to the kinetic temperature used in full statistical equilibrium calculations. The formulas can be used in a simple way to improve the estimate of the kinetic temperature obtained from ammonia observations.
Chapter 7 – Treatment Planning

Publisher Summary This chapter is dedicated to an important play therapy activities, i.e., treatment planning. Treatment planning has four components. First, the play therapist must develop accurate and comprehensive treatment goals that are consistent with the case formulation and the theoretical model being used. Second, the play therapist must find a way to work with both the child client and his or her caregivers to develop a treatment contract. This contract is designed to address each party's needs in a way that will keep them actively engaged in the treatment process over time. Third, the play therapist must organize the treatment goals and the treatment contracts into a realistic and sequential treatment plan. Finally, the play therapist must devise both experiential and cognitive/verbal interventions that will move the client toward the treatment goals. The chapter addresses the first three components of this process. It presents a strategy for developing and organizing specific treatment goals. It then combines the case conceptualization with the organized treatment goals to develop certain things. It develops a treatment contract that addresses the needs of the child and the significant others in the child's life. It also creates a global play therapy treatment and a detailed session-by-session play therapy treatment plan.
Birth Defect Registries

Birth defects registries can be used to determine the prevalence of birth defects in newborns and can serve as a source of cases for etiologic investigations. We discuss the types of information in population-based and nonpopulation-based birth defects registries. We describe some prevention policies that were based on studies of registered cases and population controls. Keywords: birth defect; spina bifida; prevalence of birth defects; birth defect registry
Dynamic stability and reform of political institutions

When are political institutions stable? When do they tend toward reform? This paper examines a model of dynamic, endogenous institutional change. We introduce the class of dynamic political games (DPGs), dynamic games in which the political aggregation rules used at date t+1 are chosen by the rules at date t, and the resulting institutional choices do not aect payos or technology directly. A political rule is stable if it selects itself for use in the following period. A reform occurs when an alternative rule is selected. Absent an essential private sector, it is shown that institutional reform occurs if and only if the current political rule is dynamically inconsistent. Roughly, a rule is dynamically consistent if it is rationalized by a time separable, state invariant social welfare criterion. Simple majority rules are usually dynamically consistent. However, wealth-weighted voting rules are not. More generally, we identify sucient conditions for stability and reform in terms of recursive self-selection constraints that treat the rules themselves as “players” who can strategically delegate future policymaking authority to dierent institutional types. These ideas are illustrated in a parametric model of dynamic public goods provision.
AUTONOMY, TAKING ONE'S CHOICES TO BE GOOD, AND PRACTICAL LAW: REPLIES TO CRITICS

Philosophical Books Vol. 49 No. 2 April 2008 pp. 125 –137 AUTONOMY, TAKING ONE’S CHOICES TO BE GOOD, AND PRACTICAL LAW: REPLIES TO CRITICS andrews reath The University of California, Riverside I Several essays in my book try to understand what Kant means by autonomy and how that concept figures in his foundational project. Since political and juridical terminology runs through much of Kant’s moral theory, I suggest that he models autonomy on a notion of sovereignty. I interpret autonomy not as a motivational capacity, but as the sovereignty of the will over itself: the rational will is not bound to any outside authority and it has the capacity to give universal law. I shall begin with an overview of some of these themes. Since Samuel Kerstein asks whether I am interpreting or defending Kant, let me first say something about my approach. My guiding aim is to reconstruct the underlying ideas and arguments so as to make them philosophically success- ful, where ‘reconstruction’ permits pushing an idea farther in a certain direc- tion than Kant did. My approach is interpretive, since I accept the constraint that the ideas that I develop should have a firm basis in the texts and the underlying arguments. Without claiming that there is a uniquely right reading, I want to get at the deep structure of concepts and arguments that animate the movements of thought in Kant’s texts. But I am also engaged in defending Kant, in that I am trying, as far as I can, to make the arguments work out. Thus a second constraint is that the ideas and arguments attributed to Kant turn out to be philosophically successful. These two constraints are not always compatible, and that is one reason why Kant is hard work (and sometimes frustrating). II To provide background for my responses, I begin with some remarks about the role of autonomy in the overall trajectory of the Groundwork that may clarify the senses in which Kant thinks that moral requirements are laws that the will gives to itself. (Here I am more concerned to lay out an overall picture of what goes on in the Groundwork than to defend it.) Kant thinks that it is part of common moral thought that moral requirements apply with absolute necessity and that we take them to be categorical imperatives. Once this feature of common moral thought is brought to our attention, the question that sets the problematic of the Groundwork naturally arises: how could there be normative requirements with this kind of necessity? Groundwork III attempts to ground the authority of moral requirements in a dual necessity. Greatly simplified, it argues that the Categorical Imperative [CI] is the constitutive or internal principle of a necessary self-conception. First, the CI is the constitutive principle of free Philosophical 2008 The Books Author. Vol. Journal 49 No. 2 compilation © 2008 Blackwell Publishing Ltd. © 2008 The Author. Journal compilation © 2008 Blackwell Publishing Ltd., 9600 Garsington Road, Oxford, OX4 2DQ , UK and 350 Main Street, Malden, MA 02148, USA
Screening Benefit, Evaluation of

Screening is the testing of apparently healthy individuals from a population for the purpose of separating them into groups with high and low probabilities of having a given disease such as cancer. This article examines various issues encountered in assessing the benefit of screening. The use of observational studies and possible involvement of selection bias is included, together with a discussion of lead time and length bias. Appropriate study endpoints are discussed. Various possibilities for randomized control trials are reviewed, and the use of observational designs to compare cancer incidence and mortality in a population before and after the introduction of a screening program is mentioned. The entry also lists important information requirements for the evaluation of screening programs. Keywords: study design; observational studies; clinical trials; bias; data requirements
Do Demographic Changes Affect Risk Premiums? Evidence from International Data*

We examine the link between equity risk premiums and demographic changes using a long sample for the United States, Japan, United Kingdom, Germany, and France and a shorter sample for 15 countries. We find demographic variables significantly predict excess returns internationally. However, the demographic predictability previously found in the United States for the average population age does not extend to other countries. Pooling international data, we find, on average, faster growth in the fraction of retired persons significantly decreases risk premiums. This demographic predictability of premiums is strongest in countries with well‐developed social security systems and lesser‐developed financial markets.
Liberalizing versus Facilitating Mode 4 Trade in Services

The growing importance of services trade for countries across the world is well-documented in the services and trade literatures. At the same time, regulatory and administrative barriers to the movement of service suppliers to deliver services internationally have resulted in very low shares of"Mode 4"trade in total services trade. Against this background, this paper conceptualizes an agenda for trade facilitation in services as it would apply to the movement of natural persons. It also provides descriptive statistical evidence from the Organisation for Economic Co-operation and Development's Services Trade Restrictiveness Index database. The paper differentiates between regulatory measures that may improve transparency or facilitate access for service providers and those measures that impede Mode 4 trade as well as the administrative, financial, and economic costs of compliance with such measures.
Complement regulation during pregnancy.

Complement has an important role in innate immunity and inflammation. Complement also has the capacity to attack self tissues. Cells are protected from the deleterious effects of complement. The Crry protein belongs to a family of molecules that regulates complement activation, protecting tissues from complement-mediated damage. To investigate the role of these molecules in vivo, Crry −/− mice were generated. Crry −/− mice did not survive pregnancy owing to abnormal complement deposition in the placenta through the alternative pathway. Tissue damage related to C5 (production of C5a and C5b-9) was not required. Removal of inflammatory cells did not affect the phenotype. This suggests new noninflammatory mechanisms of pregnancy failure that are dependent solely on C3. The major abnormality was a failure of blood vessel formation in the placenta, revealing an unsuspected C3 effect in the vascular development of this organ.
When Selling Becomes Viral: Disruptions in Debt Markets in the COVID-19 Crisis and the Fed’s Response

We study disruptions in debt markets during the COVID-19 crisis. The safer end of the credit spectrum experienced significant losses that are hard to fully reconcile with standard default or risk premium channels. Corporate bonds traded at a large discount to their corresponding CDS, and this basis widened most for safer bonds. Liquid bond ETFs traded at a large discount to their NAV, more so for Treasuries, municipal bonds, and investment-grade corporate than high-yield corporate. These facts suggest investors tried to sell safer, more liquid securities to raise cash. These disruptions disappeared nearly as fast as they appeared. We trace this recovery back to the unprecedented actions the Fed took to purchase corporate bonds rather than its interventions in extending credit. The March 23rd announcement to buy investment-grade debt boosted prices and lowered bond spreads (particularly at shorter maturities and the safer end of investment-grade) while having virtually no effect on high-yield debt. April 9th, in contrast, had a large effect on both investment-grade and high-yield, even for the riskier end of high yield which would only indirectly benefit from the policy. These facts highlight the importance of financial frictions early on in the crisis, but also challenge existing theories of these frictions.
Edwin Borchard’s Innocence Project: The Origin and Legacy of His Wrongful Conviction Scholarship

The article recognizes the life and work of Edwin Montefiore Borchard, the founder of US innocence scholarship, as fitting for the Wrongful Conviction Law Review’s inaugural issue. The sources of his scholarship are located in his life and times in the early twentieth century US Progressive movement. The links between Borchard's other legal scholarship and his wrongful conviction writings are explained. Borchard's writings and advocacy leading to his main work, Convicting the Innocent, and passage of the federal exoneree compensation law are described. The article concludes that Borchard's lasting legacy is to refute innocence denial, a deeply held belief that wrongful convictions never occur or are vanishingly rare.
Language-Independent Tokenisation Rivals Language-Specific Tokenisation for Word Similarity Prediction.

Language-independent tokenisation (LIT) methods that do not require labelled language resources or lexicons have recently gained popularity because of their applicability in resource-poor languages. Moreover, they compactly represent a language using a fixed size vocabulary and can efficiently handle unseen or rare words. On the other hand, language-specific tokenisation (LST) methods have a long and established history, and are developed using carefully created lexicons and training resources. Unlike subtokens produced by LIT methods, LST methods produce valid morphological subwords. Despite the contrasting trade-offs between LIT vs. LST methods, their performance on downstream NLP tasks remain unclear. In this paper, we empirically compare the two approaches using semantic similarity measurement as an evaluation task across a diverse set of languages. Our experimental results covering eight languages show that LST consistently outperforms LIT when the vocabulary size is large, but LIT can produce comparable or better results than LST in many languages with comparatively smaller (i.e. less than 100K words) vocabulary sizes, encouraging the use of LIT when language-specific resources are unavailable, incomplete or a smaller model is required. Moreover, we find that smoothed inverse frequency (SIF) to be an accurate method to create word embeddings from subword embeddings for multilingual semantic similarity prediction tasks. Further analysis of the nearest neighbours of tokens show that semantically and syntactically related tokens are closely embedded in subword embedding spaces.
Distilling Knowledge Learned in BERT for Text Generation

Large-scale pre-trained language model such as BERT has achieved great success in language understanding tasks. However, it remains an open question how to utilize BERT for language generation. In this paper, we present a novel approach, Conditional Masked Language Modeling (C-MLM), to enable the finetuning of BERT on target generation tasks. The finetuned BERT (teacher) is exploited as extra supervision to improve conventional Seq2Seq models (student) for better text generation performance. By leveraging BERT’s idiosyncratic bidirectional nature, distilling knowledge learned in BERT can encourage auto-regressive Seq2Seq models to plan ahead, imposing global sequence-level supervision for coherent text generation. Experiments show that the proposed approach significantly outperforms strong Transformer baselines on multiple language generation tasks such as machine translation and text summarization. Our proposed model also achieves new state of the art on IWSLT German-English and English-Vietnamese MT datasets.
Gaussian Sketching yields a J-L Lemma in RKHS

The main contribution of the paper is to show that Gaussian sketching of a kernel-Gram matrix $\boldsymbol K$ yields an operator whose counterpart in an RKHS $\mathcal H$, is a \emph{random projection} operator---in the spirit of Johnson-Lindenstrauss (J-L) lemma. To be precise, given a random matrix $Z$ with i.i.d. Gaussian entries, we show that a sketch $Z\boldsymbol{K}$ corresponds to a particular random operator in (infinite-dimensional) Hilbert space $\mathcal H$ that maps functions $f \in \mathcal H$ to a low-dimensional space $\mathbb R^d$, while preserving a weighted RKHS inner-product of the form $\langle f, g \rangle_{\Sigma} \doteq \langle f, \Sigma^3 g \rangle_{\mathcal H}$, where $\Sigma$ is the \emph{covariance} operator induced by the data distribution. In particular, under similar assumptions as in kernel PCA (KPCA), or kernel $k$-means (K-$k$-means), well-separated subsets of feature-space $\{K(\cdot, x): x \in \cal X\}$ remain well-separated after such operation, which suggests similar benefits as in KPCA and/or K-$k$-means, albeit at the much cheaper cost of a random projection. In particular, our convergence rates suggest that, given a large dataset $\{X_i\}_{i=1}^N$ of size $N$, we can build the Gram matrix $\boldsymbol K$ on a much smaller subsample of size $n\ll N$, so that the sketch $Z\boldsymbol K$ is very cheap to obtain and subsequently apply as a projection operator on the original data $\{X_i\}_{i=1}^N$. We verify these insights empirically on synthetic data, and on real-world clustering applications.
Laboratory culture of the California Sea Firefly Vargula tsujii (Ostracoda: Cypridinidae): Developing a model system for the evolution of marine bioluminescence.

Bioluminescence, or the production of light by living organisms via chemical reaction, is widespread across Metazoa. Laboratory culture of bioluminescent organisms from diverse taxonomic groups is important for determining the biosynthetic pathways of bioluminescent substrates, which may lead to new tools for biotechnology and biomedicine. Some bioluminescent groups may be cultured, including some cnidarians, ctenophores, and brittle stars, but those use luminescent substrates (luciferins) obtained from their diets, and therefore are not informative for determination of the biosynthetic pathways of the luciferins. Other groups, including terrestrial fireflies, do synthesize their own luciferin, but culturing them is difficult and the biosynthetic pathway for firefly luciferin remains unclear. An additional independent origin of endogenous bioluminescence is found within ostracods from the family Cypridinidae, which use their luminescence for defense and, in Caribbean species, for courtship displays. Here, we report the first complete life cycle of a luminous ostracod (Vargula tsujii Kornicker & Baker, 1977, the California Sea Firefly) in the laboratory. We also describe the late-stage embryogenesis of Vargula tsujii and discuss the size classes of instar development. We find embryogenesis in V. tsujii ranges from 25–38 days, and this species appears to have five instar stages, consistent with ontogeny in other cypridinid lineages. We estimate a complete life cycle at 3–4 months. We also present the first complete mitochondrial genome for Vargula tsujii. Bringing a luminous ostracod into laboratory culture sets the stage for many potential avenues of study, including learning the biosynthetic pathway of cypridinid luciferin and genomic manipulation of an autogenic bioluminescent system.
Ridge regression and the Lasso: how do they do as finders of significant regressors and their multipliers?

A simulation study is done to compare Ridge Regression (RR) and the Lasso, under the assumption of a linear model, by calculating four metrics: the squared distance, from the true coefficients, of ...
A hierarchical Bayesian mixture model for inferring the expression state of genes in transcriptomes

Transcriptomes are key to understanding the relationship between genotype and phenotype. The ability to infer the expression state (active or inactive) of genes in the transcriptome offers unique benefits for addressing this issue. For example, qualitative changes in gene expression may underly the origin of novel phenotypes, and expression states are readily comparable between tissues and species. However, inferring the expression state of genes is a surprisingly difficult problem, owing to the complex biological and technical processes that give rise to observed transcriptomic datasets. Here, we develop a hierarchical Bayesian mixture model that describes this complex process and allows us to infer expression state of genes from replicate transcriptomic libraries. We explore the statistical behavior of this method with analyses of simulated datasets—where we demonstrate its ability to correctly infer true (known) expression states—and empirical-benchmark datasets, where we demonstrate that the expression states inferred from RNA-sequencing (RNA-seq) datasets using our method are consistent with those based on independent evidence. The power of our method to correctly infer expression states is generally high and remarkably, approaches the maximum possible power for this inference problem. We present an empirical analysis of primate-brain transcriptomes, which identifies genes that have a unique expression state in humans. Our method is implemented in the freely available R package zigzag.
Artificial Intelligence (AI) and IT identity: Antecedents Identifying with AI Applications.

In the age of Artificial Intelligence and automation, machines have taken over many key managerial tasks. Replacing managers with AI systems may have a negative impact on workers outcomes. It is unclear if workers receive the same benefits from their relationships with AI systems, raising the question: What degree does the relationship between AI systems and workers impact worker outcomes? We draw on IT identity to understand the influence of identification with AI systems on job performance. From this theoretical perspective, we propose a research model and conduct a survey of 97 MTurk workers to test the model. The findings reveal that work role identity and organizational identity are key determinants of identification with AI systems. Furthermore, the findings show that identification with AI systems does increase job performance.
CONVINCE: Collaborative Cross-Camera Video Analytics at the Edge

Today, video cameras are deployed in dense for monitoring physical places e.g., city, industrial, or agricultural sites. In the current systems, each camera node sends its feed to a cloud server individually. However, this approach suffers from several hurdles including higher computation cost, large bandwidth requirement for analyzing the enormous data, and privacy concerns. In dense deployment, video nodes typically demonstrate a significant spatio-temporal correlation. To overcome these obstacles in current approaches, this paper introduces CONVINCE, a new approach to look at the network cameras as a collective entity that enables collaborative video analytics pipeline among cameras. CONVINCE aims at 1) reducing the computation cost and bandwidth requirements by leveraging spatiotemporal correlations among cameras in eliminating redundant frames intelligently, and ii) improving vision algorithms' accuracy by enabling collaborative knowledge sharing among relevant cameras. Our results demonstrate that CONVINCE achieves an object identification accuracy of ~91%, by transmitting only about ~25% of all the recorded frames.
Quantum Hall Liquid Crystals

The stripe phase of a two-dimensional electron system in a weak magnetic field bears a close analogy to liquid crystals. However, reduced dimensionality and unusual dynamics give rise to important differences. At finite temperature they cause divergent fluctuations and nonperturbative renormalization of hydrodynamic parameters. Such effects can be verified in microwave experiments. At low temperatures the physics is dominated by quantum fluctuations. When they are large, the transition to a novel quantum nematic phase may occur, driven by quantum proliferation of dislocations. It will be signaled by an additional low-frequency resonance in the microwave response.
The Quest for a European Safe Asset—A Comparative Legal Analysis of Sovereign Bond-Backed Securities, E-Bonds, Purple Bonds, and Coronabonds

The European sovereign debt crisis and, more recently, the COVID-19 pandemic have revealed the European Economic and Monetary Union’s fragility, which essentially emanates from the inherent tension between a single monetary policy and decentralized fiscal policies To cushion economic and financial shocks and sever the sovereign-bank doom loop, different proposals to create a common public debt security have been put forward, although none of them has so far seen the light of day Building on pertinent economic and finance scholarship, this article reviews four promising safe asset proposals from a legal perspective: Sovereign bond-backed securities (SBBS), E-bonds, Purple bonds, and Coronabonds Rather than focusing on their feasibility under EU law or national constitutional law, this article compares the proposals from an investor perspective against the backdrop of the following formal and functional legal characteristics that render assets ‘safe’: governing law, dispute settlement forum, investor protection, and investor representation in sovereign debt restructurings Against this backdrop, targeted recommendations on critical design elements of safe assets, with the aim of reconciling the economic policy objectives with the pertinent legal constraints, are advanced
Ecological processes underlying the emergence of novel enzootic cycles: Arboviruses in the neotropics as a case study

Pathogens originating from wildlife (zoonoses) pose a significant public health burden, comprising the majority of emerging infectious diseases. Efforts to control and prevent zoonotic disease have traditionally focused on animal-to-human transmission, or “spillover.” However, in the modern era, increasing international mobility and commerce facilitate the spread of infected humans, nonhuman animals (hereafter animals), and their products worldwide, thereby increasing the risk that zoonoses will be introduced to new geographic areas. Imported zoonoses can potentially “spill back” to infect local wildlife—a danger magnified by urbanization and other anthropogenic pressures that increase contacts between human and wildlife populations. In this way, humans can function as vectors, dispersing zoonoses from their ancestral enzootic systems to establish reservoirs elsewhere in novel animal host populations. Once established, these enzootic cycles are largely unassailable by standard control measures and have the potential to feed human epidemics. Understanding when and why translocated zoonoses establish novel enzootic cycles requires disentangling ecologically complex and stochastic interactions between the zoonosis, the human population, and the natural ecosystem. In this Review, we address this challenge by delineating potential ecological mechanisms affecting each stage of enzootic establishment—wildlife exposure, enzootic infection, and persistence—applying existing ecological concepts from epidemiology, invasion biology, and population ecology. We ground our discussion in the neotropics, where four arthropod-borne viruses (arboviruses) of zoonotic origin—yellow fever, dengue, chikungunya, and Zika viruses—have separately been introduced into the human population. This paper is a step towards developing a framework for predicting and preventing novel enzootic cycles in the face of zoonotic translocations.
Monetary Policy Cooperation/Coordination and Global Financial Crises in Historical Perspective

The COVID-19 pandemic spawned a global liquidity crisis in March 2020. The global liquidity crisis was alleviated by the Federal Reserve and other advanced country central banks cooperating by extending the swap lines they developed in the Global Financial Crisis 2007-2008. Central bank cooperation in 2020 evolved from a two-century history across several monetary regimes that is surveyed in this paper. I find that in monetary regimes which are rules-based cooperation was most successful. International currency swaps developed to manage exchange rates during the Bretton Woods era have evolved into the leading tool to manage international liquidity crises. The swap network can be viewed as a step in the direction of a global financial safety net.
Dynamics and stability of sessile drops with contact points

Abstract In an effort to study the stability of contact lines in fluids, we consider the dynamics of a drop of incompressible viscous Stokes fluid evolving above a one-dimensional flat surface under the influence of gravity. This is a free boundary problem: the interface between the fluid on the surface and the air above (modeled by a trivial fluid) is free to move and experiences capillary forces. The three-phase interface where the fluid, air, and solid vessel wall meet is known as a contact point, and the angle formed between the free interface and the flat surface is called the contact angle. We consider a model of this problem that allows for fully dynamic contact points and angles. We develop a scheme of a priori estimates for the model, which then allows us to show that for initial data sufficiently close to equilibrium, the model admits global solutions that decay to a shifted equilibrium exponentially fast.
PCB126 Exposure Revealed Alterations in m6A RNA Modifications in Transcripts Associated With AHR Activation.

Chemical modifications of proteins, DNA and RNA moieties play critical roles in regulating gene expression. Emerging evidence suggests the RNA modifications (epitranscriptomics) have substantive roles in basic biological processes. One of the most common modifications in mRNA and noncoding RNAs is N6-methyladenosine (m6A). In a subset of mRNAs, m6A sites are preferentially enriched near stop codons, in 3' UTRs, and within exons, suggesting an important role in the regulation of mRNA processing and function including alternative splicing and gene expression. Very little is known about the effect of environmental chemical exposure on m6A modifications. As many of the commonly occurring environmental contaminants alter gene expression profiles and have detrimental effects on physiological processes, it is important to understand the effects of exposure on this important layer of gene regulation. Hence, the objective of this study was to characterize the acute effects of developmental exposure to PCB126, an environmentally relevant dioxin-like PCB, on m6A methylation patterns. We exposed zebrafish embryos to PCB126 for 6 hours starting from 72 hours post-fertilization and profiled m6A RNA using methylated RNA immunoprecipitation followed by sequencing (MeRIP-seq). Our analysis revealed 117 and 217 m6A peaks in the DMSO and PCB126 samples (FDR 5%), respectively. The majority of the peaks were preferentially located around the 3'UTR and stop codons. Statistical analysis revealed 15 m6A marked transcripts to be differentially methylated by PCB126 exposure. These include transcripts that are known to be activated by AHR agonists (e.g., ahrra, tiparp, nfe2l2b) as well as others that are important for normal development (vgf, cebpd, sned1). These results suggest that environmental chemicals such as dioxin-like PCBs could affect developmental gene expression patterns by altering m6A levels. Further studies are necessary to understand the functional consequences of exposure-associated alterations in m6A levels.
p-Diamond, Si, GaN, and InGaAs TeraFETs

p-Diamond field-effect transistors (FETs) featuring large effective mass, long momentum relaxation time, and high carrier mobility are a superb candidate for plasmonic terahertz (THz) applications. Previous studies have shown that p-diamond plasmonic THz FETs (TeraFETs) could operate in plasmonic resonant mode at a low-frequency window of 200 to ~600 GHz, thus showing promising potential for beyond 5G sub-THz applications. In this work, we explore the advantages of p-diamond transistors over n-diamond, Si, GaN, and InGaAs TeraFETs and estimate the minimum mobility required for the resonant plasmons. Our numerical simulation shows that the p-diamond TeraFET has a relatively low minimum resonant mobility, and thus could enable resonant detection. The diamond response characteristics can be adjusted by changing operating temperature. A decrease of temperature from 300 to 77 K improves the detection performance of TeraFETs. At both room temperature and 77 K, the p-diamond TeraFET presents a high detection sensitivity in a large dynamic range. When the channel length is reduced to 20 nm, the p-diamond TeraFET exhibits the highest dc response among all types of TeraFETs in a large frequency window.
The “black box” at work:

An oversized reliance on big data-driven algorithmic decision-making systems, coupled with a lack of critical inquiry regarding such systems, combine to create the paradoxical “black box” at work. ...
AN ALGORITHMIC APPROACH TO QUANTUM FIELD THEORY

The lattice formulation provides a way to regularize, define and compute the Path Integral in a Quantum Field Theory. In this paper, we review the theoretical foundations and the most basic algorithms required to implement a typical lattice computation, including the Metropolis, the Gibbs sampling, the Minimal Residual, and the Stabilized Biconjugate inverters. The main emphasis is on gauge theories with fermions such as QCD. We also provide examples of typical results from lattice QCD computations for quantities of phenomenological interest.
A Warm Molecular Hydrogen Tail due to Ram-pressure Stripping of a Cluster Galaxy

We have discovered a remarkable warm (130-160 K) molecular hydrogen tail with a H2 mass of approximately 4 × 107 M ☉ extending 20 kpc from a cluster spiral galaxy, ESO 137-001, in Abell 3627. At least half of this gas is lost permanently to the intracluster medium, as the tail extends beyond the tidal radius of the galaxy. We also detect a hot (400-550 K) component in the tail that is approximately 1% of the mass. The large H2 line to IR continuum luminosity ratio in the tail indicates that star formation is not a major excitation source and that the gas is possibly shock-heated. This discovery confirms that the galaxy is currently undergoing ram-pressure stripping, as also indicated by its previously discovered X-ray and Hα tails. We estimate that the galaxy is losing its warm H2 gas at a rate of ~2-3 M ☉ yr–1. The true mass-loss rate is likely higher if we account for cold molecular gas and atomic gas. We predict that the galaxy will lose most of its gas in a single pass through the core and place a strong upper limit on the ram-pressure timescale of 1 Gyr. We also study the star-forming properties of the galaxy and its tail. We identify most of the previously discovered external Hα sources within the tail in our 8 μm data but not in our 3.6 μm data; IRS spectroscopy of the region containing these Hα sources also reveals aromatic features typically associated with star formation. From the positions of these H II regions, it appears that star formation is not occurring throughout the molecular hydrogen tail but only immediately downstream of the galaxy. Some of these H II regions lie outside the tidal radius of the galaxy, indicating that ram-pressure stripping can be a source of intracluster stars.
Ricci flow for homogeneous compact models of the universe

Using quaternions, we give a concise derivation of the Ricci tensor for homogeneous spaces with topology of the 3-dimensional sphere. We derive explicit and numerical solutions for the Ricci flow PDE and discuss their properties. In the collapse (or expansion) of these models, the interplay of the various components of the Ricci tensor are studied.