cssi/SciSciGPT-SciSciNet huggingface dataset:
Genetic contributions to variation in human stature in prehistoric Europe

The relative contributions of genetics and environment to temporal and geographic variation in human height remain largely unknown. Ancient DNA has identified changes in genetic ancestry over time, but it is not clear whether those changes in ancestry are associated with changes in height. Here, we directly test whether changes over the past 38,000 y in European height predicted using DNA from 1,071 ancient individuals are consistent with changes observed in 1,159 skeletal remains from comparable populations. We show that the observed decrease in height between the Early Upper Paleolithic and the Mesolithic is qualitatively predicted by genetics. Similarly, both skeletal and genetic height remained constant between the Mesolithic and Neolithic and increased between the Neolithic and Bronze Age. Sitting height changes much less than standing height-consistent with genetic predictions-although genetics predicts a small post-Neolithic increase that is not observed in skeletal remains. Geographic variation in stature is also qualitatively consistent with genetic predictions, particularly with respect to latitude. Finally, we hypothesize that an observed decrease in genetic heel bone mineral density in the Neolithic reflects adaptation to the decreased mobility indicated by decreased femoral bending strength. This study provides a model for interpreting phenotypic changes predicted from ancient DNA and demonstrates how they can be combined with phenotypic measurements to understand the relative contribution of genetic and developmentally plastic responses to environmental change.
X-ray phase contrast imaging of Vitis spp. buds shows freezing pattern and correlation between volume and cold hardiness

Grapevine (Vitis spp.) buds must survive winter temperatures in order to resume growth when suitable conditions return in spring. They do so by developing cold hardiness through deep supercooling, but the mechanistic process of supercooling in buds remains largely unknown. Here we use synchrotron X-ray phase contrast imaging to study cold hardiness-related characteristics of V. amurensis, V. riparia, and V. vinifera buds: time-resolved 2D imaging was used to visualize freezing; and microtomography was used to evaluate morphological changes during deacclimation. Bud cold hardiness was determined (low temperature exotherms; LTEs) using needle thermocouples during 2D imaging as buds were cooled with a N2 gas cryostream. Resolution in 2D imaging did not allow for ice crystal identification, but freezing was assessed by movement of tissues coinciding with LTE values. Freezing was observed to propagate from the center of the bud toward the outer bud scales. The freezing events observed lasted several minutes. Additionally, loss of supercooling ability appears to be correlated with increases in bud tissue volume during the process of deacclimation, but major increases in volume occur after most of the supercooling ability is lost, suggesting growth resumption processes are limited by deacclimation state.
Stochastic multiscale flux basis for Stokes-Darcy flows

Abstract Three algorithms are developed for uncertainty quantification in modeling coupled Stokes and Darcy flows. The porous media may consist of multiple regions with different properties. The permeability is modeled as a non-stationary stochastic variable, with its log represented as a sum of local Karhunen-Loeve (KL) expansions. The problem is approximated by stochastic collocation on either tensor-product or sparse grids, coupled with a multiscale mortar mixed finite element method for the spatial discretization. A non-overlapping domain decomposition algorithm reduces the global problem to a coarse scale mortar interface problem, which is solved by an iterative solver, for each stochastic realization. In the traditional domain decomposition implementation, each subdomain solves a local Dirichlet or Neumann problem in every interface iteration. To reduce this cost, two additional algorithms based on deterministic or stochastic multiscale flux basis are introduced. The basis consists of the local flux (or velocity trace) responses from each mortar degree of freedom. It is computed for each subdomain independently before the interface iteration begins. The use of the multiscale flux basis avoids the need for subdomain solves on each iteration. The deterministic basis is computed at each stochastic collocation and used only at this realization. The stochastic basis is formed by further looping over all local realizations of a subdomain's KL region before the stochastic collocation begins. It is reused over multiple realizations. Numerical tests are presented to illustrate the performance of the three algorithms, with the stochastic multiscale flux basis showing significant savings in computational cost compared to the other two algorithms.
Predicting mid-life capital formation with pre-school delay of gratification and life-course measures of self-regulation

How well do pre-school delay of gratification and life-course measures of self-regulation predict mid-life capital formation? We surveyed 113 participants of the 1967-1973 Bing pre-school studies on delay of gratification when they were in their late 40's. They reported 11 mid-life capital formation outcomes, including net worth, permanent income, absence of high-interest debt, forward-looking behaviors, and educational attainment. To address multiple hypothesis testing and our small sample, we pre-registered an analysis plan of well-powered tests. As predicted, a newly constructed and pre-registered measure derived from preschool delay of gratification does not predict the 11 capital formation variables (i.e., the sign-adjusted average correlation was 0.02). A pre-registered composite self-regulation index, combining preschool delay of gratification with survey measures of self-regulation collected at ages 17, 27, and 37, does predict 10 of the 11 capital formation variables in the expected direction, with an average correlation of 0.19. The inclusion of the preschool delay of gratification measure in this composite index does not affect the index's predictive power. We tested several hypothesized reasons that preschool delay of gratification does not have predictive power for our mid-life capital formation variables.
Gli3 regulates vomeronasal neurogenesis, olfactory ensheathing cell formation and GnRH-1 neuronal migration

During mammalian development, gonadotropin-releasing-hormone-1 neurons (GnRH-1ns) migrate from the developing vomeronasal organ (VNO) into the brain asserting control of pubertal onset and fertility. Recent data suggest that correct development of the olfactory ensheathing cells (OEC) is imperative for normal GnRH-1 neuronal migration. However, the full ensemble of molecular pathways that regulate OEC development remains to be fully deciphered. Loss-of-function of the transcription factor Gli3 is known to disrupt olfactory development, however, if Gli3 plays a role in GnRH-1 neuronal development is unclear. By analyzing Gli3 extra-toe mutants (Gli3Xt/Xt), we found that Gli3 loss-of-function compromises the onset of achaete-scute family bHLH transcription factor 1 (Ascl-1)+ vomeronasal progenitors and the formation of OEC in the nasal mucosa. Surprisingly, GnRH-1 neurogenesis was intact in Gli3Xt/Xt mice but they displayed significant defects in GnRH-1 neuronal migration. In contrast, Ascl-1null mutants showed reduced neurogenesis for both vomeronasal and GnRH-1ns but less severe defects in OEC development. These observations suggest that Gli3 is critical for OEC development in the nasal mucosa and subsequent GnRH-1 neuronal migration. However, the nonoverlapping phenotypes between Ascl-1 and Gli3 mutants indicate that Ascl-1, while crucial for GnRH-1 neurogenesis, is not required for normal OEC development. Because Kallmann syndrome (KS) is characterized by abnormal GnRH-1ns migration, we examined whole-exome sequencing data from KS subjects. We identified and validated a GLI3 loss-of-function variant in a KS individual. These findings provide new insights into GnRH-1 and OECs development and demonstrate that human GLI3 mutations contribute to KS etiology.SIGNIFICANCE STATEMENT The transcription factor Gli3 is necessary for correct development of the olfactory system. However, if Gli3 plays a role in controlling GnRH-1 neuronal development has not been addressed. We found that Gli3 loss-of-function compromises the onset of Ascl-1+ vomeronasal progenitors, formation of olfactory ensheathing cells in the nasal mucosa, and impairs GnRH-1 neuronal migration to the brain. By analyzing Ascl-1null mutants we dissociated the neurogenic defects observed in Gli3 mutants from lack of olfactory ensheathing cells in the nasal mucosa, moreover, we discovered that Ascl-1 is necessary for GnRH-1 ontogeny. Analyzing human whole-exome sequencing data, we identified a GLI3 loss-of-function variant in a KS individual. Our data suggest that GLI3 is a candidate gene contributing to KS etiology.
A speech envelope landmark for syllable encoding in human superior temporal gyrus

The most salient acoustic features in speech are the modulations in its intensity, captured by the amplitude envelope. Perceptually, the envelope is necessary for speech comprehension. Yet, the neural computations that represent the envelope and their linguistic implications are heavily debated. We used high-density intracranial recordings, while participants listened to speech, to determine how the envelope is represented in human speech cortical areas on the superior temporal gyrus (STG). We found that a well-defined zone in middle STG detects acoustic onset edges (local maxima in the envelope rate of change). Acoustic analyses demonstrated that timing of acoustic onset edges cues syllabic nucleus onsets, while their slope cues syllabic stress. Synthesized amplitude-modulated tone stimuli showed that steeper slopes elicited greater responses, confirming cortical encoding of amplitude change, not absolute amplitude. Overall, STG encoding of the timing and magnitude of acoustic onset edges underlies the perception of speech temporal structure.
I'm Sure! Automatic Detection of Metacognition in Online Course Discussion Forums

Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the forums of two online, university-level science courses, which revealed common patterns of phrases that we used for automatic metacognition detection. The algorithm we developed exhibited high accuracy on expert-labeled metacognitive phrases (Spearman's rho = 0.878 and Cohen's kappa = 0.792), and provides a reliable, fast method for automatically annotating text corpora that are too large for manual annotation. We applied this algorithm to analyze relationships between students' metacognitive language and their academic performance, finding small correlations with course grade and medium-sized differences in metacognition across courses. We discuss how our algorithm can be used to advance metacognitive studies and online educational systems.
Structure of the Vesicular Stomatitis Virus L Protein in Complex with Its Phosphoprotein Cofactor

Summary The large (L) proteins of non-segmented, negative-strand RNA viruses are multifunctional enzymes that produce capped, methylated, and polyadenylated mRNA and replicate the viral genome. A phosphoprotein (P), required for efficient RNA-dependent RNA polymerization from the viral ribonucleoprotein (RNP) template, regulates the function and conformation of the L protein. We report the structure of vesicular stomatitis virus L in complex with its P cofactor determined by electron cryomicroscopy at 3.0 A resolution, enabling us to visualize bound segments of P. The contacts of three P segments with multiple L domains show how P induces a closed, compact, initiation-competent conformation. Binding of P to L positions its N-terminal domain adjacent to a putative RNA exit channel for efficient encapsidation of newly synthesized genomes with the nucleoprotein and orients its C-terminal domain to interact with an RNP template. The model shows that a conserved tryptophan in the priming loop can support the initiating 5′ nucleotide.
Pricing Analytics for Rotable Spare Parts

The authors developed a comprehensive approach to pricing analytics for rotable spare parts (i.e., parts that can be repaired and resold repeatedly). They describe a large-scale implementation of t...
Performance of FRAX in Predicting Fractures in US Postmenopausal Women with Varied Race and Genetic Profiles.

Background: Whether the Fracture Risk Assessment Tool (FRAX) performed differently in estimating the 10-year fracture probability in women of different genetic profiling and race remained unclear. Methods: The genomic data in the Women’s Health Initiative (WHI) study was analyzed (n = 23,981). The genetic risk score (GRS) was calculated from 14 fracture-associated single nucleotide polymorphisms (SNPs) for each participant. FRAX without bone mineral density (BMD) was used to estimate fracture probability. Results: FRAX significantly overestimated the risk of major osteoporotic fracture (MOF) in the WHI study. The most significant overestimation was observed in women with low GRS (predicted/observed ratio (POR): 1.61, 95% CI: 1.45–1.79) specifically Asian women (POR: 3.5, 95% CI 2.48–4.81) and in African American women (POR: 2.59, 95% CI: 2.33–2.87). Compared to the low GRS group, the 10-year probability of MOF adjusted for the FRAX score was 21% and 30% higher in the median GRS group and high GRS group, respectively. Asian, African American, and Hispanic women respectively had a 78%, 76%, and 56% lower hazard than Caucasian women after the FRAX score was adjusted. The results were similar for hip fractures. Conclusions: Our study suggested the FRAX performance varies significantly by both genetic profile and race in postmenopausal women.
Semiparametric regression and risk prediction with competing risks data under missing cause of failure

The cause of failure in cohort studies that involve competing risks is frequently incompletely observed. To address this, several methods have been proposed for the semiparametric proportional cause-specific hazards model under a missing at random assumption. However, these proposals provide inference for the regression coefficients only, and do not consider the infinite dimensional parameters, such as the covariate-specific cumulative incidence function. Nevertheless, the latter quantity is essential for risk prediction in modern medicine. In this paper we propose a unified framework for inference about both the regression coefficients of the proportional cause-specific hazards model and the covariate-specific cumulative incidence functions under missing at random cause of failure. Our approach is based on a novel computationally efficient maximum pseudo-partial-likelihood estimation method for the semiparametric proportional cause-specific hazards model. Using modern empirical process theory we derive the asymptotic properties of the proposed estimators for the regression coefficients and the covariate-specific cumulative incidence functions, and provide methodology for constructing simultaneous confidence bands for the latter. Simulation studies show that our estimators perform well even in the presence of a large fraction of missing cause of failures, and that the regression coefficient estimator can be substantially more efficient compared to the previously proposed augmented inverse probability weighting estimator. The method is applied using data from an HIV cohort study and a bladder cancer clinical trial.
CK2-Dependent Phosphorylation of the Brg1 Chromatin Remodeling Enzyme Occurs during Mitosis

Brg1 (Brahma-related gene 1) is one of two mutually exclusive ATPases that can act as the catalytic subunit of mammalian SWI/SNF (mSWI/SfigureNF) chromatin remodeling enzymes that facilitate utilization of the DNA in eukaryotic cells. Brg1 is a phospho-protein, and its activity is regulated by specific kinases and phosphatases. Previously, we showed that Brg1 interacts with and is phosphorylated by casein kinase 2 (CK2) in a manner that regulates myoblast proliferation. Here, we use biochemical and cell and molecular biology approaches to demonstrate that the Brg1-CK2 interaction occurred during mitosis in embryonic mouse somites and in primary myoblasts derived from satellite cells isolated from mouse skeletal muscle tissue. The interaction of CK2 with Brg1 and the incorporation of a number of other subunits into the mSWI/SNF enzyme complex were independent of CK2 enzymatic activity. CK2-mediated hyperphosphorylation of Brg1 was observed in mitotic cells derived from multiple cell types and organisms, suggesting functional conservation across tissues and species. The mitotically hyperphosphorylated form of Brg1 was localized with soluble chromatin, demonstrating that CK2-mediated phosphorylation of Brg1 is associated with specific partitioning of Brg1 within subcellular compartments. Thus, CK2 acts as a mitotic kinase that regulates Brg1 phosphorylation and subcellular localization.
Improved Linear Programs for Discrete Barycenters

Discrete barycenters are the optimal solutions to mass transport problems for a set of discrete measures. Such transport problems arise in many applications of operations research and statistics. T...
Group actions, divisors, and plane curves

After a general discussion of group actions, orbifolds, and "weak orbifolds" this note will provide elementary introductions to two basic moduli spaces over the real or complex numbers: First the moduli space of effective divisors with finite stabilizer on the projective space ${\mathbb P}^1$ modulo the group ${\rm PGL}_2$ of projective transformations of ${\mathbb P}^1$; and then the moduli space of effective 1-cycles with finite stabilizer on ${\mathbb P}^2$ modulo the group ${\rm PGL}_3$ of projective transformations of ${\mathbb P}^2$.
A toolkit for solving models with a lower bound on interest rates of stochastic duration

Abstract This paper presents a toolkit to solve for equilibrium in a computationally efficient way in economies facing the effective lower bound on the nominal interest rate under a special assumption about the underlying shock process, a two-state Markov process with an absorbing state. We illustrate the algorithm in the canonical New Keynesian model by replicating the optimal monetary policy in Eggertsson and Woodford (2003) , and we show how the toolkit can be used to analyse the medium-scale dynamic stochastic general equilibrium model developed by the Federal Reserve Bank of New York. As an application, we show how various policy rules perform relative to the optimal commitment equilibrium. A key conclusion is that previously suggested strategies – such as price level targeting and nominal GDP targeting – do not perform well when there is a small drop in the price level, as observed during the Great Recession, because they do not imply a sufficiently strong commitment to low future interest rates (“make-up strategy”). We propose two new policy rules – the cumulative nominal GDP targeting rule and the symmetric dual-objective targeting rule – that are more robust. Had these policies been in place in 2008, they would have reduced the output contraction by approximately 80 percent. If the Federal Reserve had followed average inflation targeting – which arguably approximates the policy framework announced in August 2020 – the output contraction would have been roughly 25 percent smaller.
Constraints in Random Effects Age-Period-Cohort Models

Random effects (RE) models have been widely used to study the contextual effects of structures such as neighborhoods or schools. The RE approach has recently been applied to age-period-cohort (APC)...
Wall-to-wall optimal transport in two dimensions

Gradient ascent methods are developed to compute incompressible flows that maximize heat transport between two isothermal no-slip parallel walls. Parameterizing the magnitude of the velocity fields by a Peclet number similar to the computationally achieved scaling. Implications for heat transfer in buoyancy-driven Rayleigh–Benard convection are discussed.
Limited Evidence for Selection at the FADS Locus in Native American Populations

The FADS locus contains the genes FADS1 and FADS2 that encode enzymes involved in the synthesis of long-chain polyunsaturated fatty acids. This locus appears to have been a repeated target of selection in human evolution, likely because dietary input of long-chain polyunsaturated fatty acids varied over time depending on environment and subsistence strategy. Several recent studies have identified selection at the FADS locus in Native American populations, interpreted as evidence for adaptation during or subsequent to the passage through Beringia. Here, we show that these signals are confounded by independent selection-postdating the split from Native Americans-in the European and, possibly, the East Asian populations used in the population branch statistic test. This is supported by direct evidence from ancient DNA that one of the putatively selected haplotypes was already common in Northern Eurasia at the time of the separation of Native American ancestors. An explanation for the present-day distribution of the haplotype that is more consistent with the data is that Native Americans retain the ancestral state of Paleolithic Eurasians. Another haplotype at the locus may reflect a secondary selection signal, although its functional impact is unknown.
Stochastic Bregman Parallel Direction Method of Multipliers for Distributed Optimization

Bregman parallel direction method of multipliers (BPDMM) efficiently solves distributed optimization over a network, which arises in a wide spectrum of collaborative multi-agent learning applications. In this paper, we generalize BPDMM to stochastic BPDMM, where each iteration only solves local optimization on a randomly selected subset of nodes rather than all the nodes in the network. Such generalization reduce the need for computational resources and allows applications to larger scale networks. We establish both the global convergence and the O(1/T) iteration complexity of stochastic BPDMM. We demonstrate our results via numerical examples.
Accurate and complete genomes from metagenomes

Genomes are an integral component of the biological information about an organism; thus, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures, and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs); but gaps, local assembly errors, chimeras, and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and, in some cases, achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of about 7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. The analysis of cumulative GC skew identified potential misassemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.
Definition of Naturally Processed Peptides Reveals Convergent Presentation of Autoantigenic Topoisomerase I Epitopes in Scleroderma

Author(s): Tiniakou, Eleni; Fava, Andrea; McMahan, Zsuzsanna H; Guhr, Tara; O'Meally, Robert N; Shah, Ami A; Wigley, Fredrick M; Cole, Robert N; Boin, Francesco; Darrah, Erika | Abstract: ObjectiveAutoimmune responses to DNA topoisomerase I (topo I) are found in a subset of scleroderma patients who are at high risk for interstitial lung disease (ILD) and mortality. Anti-topo I antibodies (ATAs) are associated with specific HLA-DRB1 alleles, and the frequency of HLA-DR-restricted topo I-specific CD4+ T cells is associated with the presence, severity, and progression of ILD. Although this strongly implicates the presentation of topo I peptides by HLA-DR in scleroderma pathogenesis, the processing and presentation of topo I has not been studied.MethodsWe developed a natural antigen processing assay (NAPA) to identify putative CD4+ T cell epitopes of topo I presented by monocyte-derived dendritic cells (mo-DCs) from 6 ATA-positive patients with scleroderma. Mo-DCs were pulsed with topo I protein, HLA-DR-peptide complexes were isolated, and eluted peptides were analyzed by mass spectrometry. We then examined the ability of these naturally presented peptides to induce CD4+ T cell activation in 11 ATA-positive and 11 ATA-negative scleroderma patients.ResultsWe found that a common set of 10 topo I epitopes was presented by Mo-DCs from scleroderma patients with diverse HLA-DR variants. Sequence analysis revealed shared peptide-binding motifs within the HLA-DRβ chains of ATA-positive patients and a subset of topo I epitopes with distinct sets of anchor residues capable of binding to multiple different HLA-DR variants. The NAPA-derived epitopes elicited robust CD4+ T cell responses in 73% of ATA-positive patients (8 of 11), and the number of epitopes recognized correlated with ILD severity (P = 0.025).ConclusionThese findings mechanistically implicate the presentation of a convergent set of topo I epitopes in the development of scleroderma.
12 – Sequences and Series

Publisher Summary A sequence is a function whose domain is the set of positive integers. The general term is used to define the other terms of the sequence. That is, if the formula for the general term, “an” is given, one can find any other term in the sequence. The sum of a number of terms in a sequence is called a series. A sequence can be finite or infinite depending on whether the sequence ends at the nth term. An arithmetic progression is a sequence of numbers in which each term is obtained from the preceding term by adding the same amount each time. A sequence of numbers in which each term is obtained from the previous term by multiplying by the same amount each time is called a geometric progression. This chapter focuses on the classification of sequences, called geometric progressions.
Commutative semigroup cohomology

Triple cohomology for commutative semigroups is described in concrete terms and related to commutative group coextensions.
Where modern macroeconomics went wrong

This paper provides a critique of the DSGE models that have come to dominate macroeconomics during the past quarter-century. It argues that at the heart of the failure were the wrong microfoundations, which failed to incorporate key aspects of economic behaviour, e.g. incorporating insights from information economics and behavioural economics. Inadequate modelling of the financial sector meant they were ill-suited for predicting or responding to a financial crisis; and a reliance on representative agent models meant they were ill-suited for analysing either the role of distribution in fluctuations and crises or the consequences of fluctuations on inequality. The paper proposes alternative benchmark models that may be more useful both in understanding deep downturns and responding to them.
Economic Analysis and the Design of Constitutional Courts

Though nominally exercised on behalf of private citizens, constitutional judicial review does perform an insurance function for politicians who expect to lose power in future elections. This paper discusses the various dimensions of institutional design of constitutional courts and argues that the extent and power of judicial review can be expected to increase relative to the degree of political uncertainty at the time of constitutional design. The paper then develops a simple empirical test of this hypothesis using data from Eastern Europe, regressing measures for various aspects of court design on the strength of the largest party in the legislature. The paper shows that the design of constitutional courts reflects the interests of the dominant political parties and that independent and powerful courts are associated with situations of divided or deadlocked politics.
Oxygen supply capacity in animals evolves to meet maximum demand at the current oxygen partial pressure regardless of size or temperature

The capacity to extract oxygen from the environment and transport it to respiring tissues in support of metabolic demand reportedly has implications for species’ thermal tolerance, body-size, diversity and biogeography. Here we derive a quantifiable linkage between maximum and basal metabolic rate and their oxygen, temperature and size dependencies. We show that, regardless of size or temperature, the physiological capacity for oxygen supply precisely matches the maximum evolved demand at the highest persistently available oxygen pressure and this is the critical PO2 for the maximum metabolic rate. For most terrestrial and shallow-living marine species, this “Pcrit-max” is the current atmospheric pressure, 21 kPa. Any reduction in oxygen partial pressure from current values will result in a calculable decrement in maximum metabolic performance. However, oxygen supply capacity has evolved to match demand across temperatures and body sizes and so does not constrain thermal tolerance or cause the well-known reduction in mass-specific metabolic rate with increasing body mass. The critical oxygen pressure for resting metabolic rate, typically viewed as an indicator of hypoxia tolerance, is, instead, simply a rate-specific reflection of the oxygen supply capacity. A compensatory reduction in maintenance metabolic costs in warm-adapted species constrains factorial aerobic scope and the critical PO2 to a similar range, between ∼2 and 6, across each species’ natural temperature range. The simple new relationship described here redefines many important physiological concepts and alters their ecological interpretation.
IS TRADE GOOD OR BAD FOR THE ENVIRONMENT? SORTING OUT THE CAUSALITY

We seek to contribute to the debate over globalization and the environment by asking: What is the effect of trade on a country's environment, for a given level of GDP? We take specific account of the endogeneity of trade, using exogenous geographic determinants of trade as instrumental variables. We find that trade tends to reduce three measures of air pollution. Statistical significance is high for concentrations of SO2, moderate for NO2, and lacking for particulate matter. Although results for other environmental measures are not as encouraging, there is little evidence that trade has a detrimental effect on the environment.
Algol, Beta Lyrae, and W Serpentis: Some new results for three well studied eclipsing binaries

The properties of the eclipsing binaries Algol, Beta Lyrae, and W Serpentis are discussed and new results are presented. The physical properties of the components of Algol are now well determined. High resolution spectroscopy of the H-alpha feature by Richards et al. and by Gillet et al. and spectroscopy of the ultraviolet resonance lines with the International Ultraviolet Explorer satellite reveal hot gas around the BBV primary. Gas flows also have been detected apparently originating from the low mass, cooler secondary component and flowing toward the hotter star through the Lagrangian L1 point. Analysis of 6 years of multi-bandpass photoelectric photometry of Beta Lyrae indicates that systematic changes in light curves occur with a characteristic period of -275 ± 25 days. These changes may arise from pulsations of the B8II star or from changes in the geometry of the disk component. Hitherto unpublished u, v, b, y, and H-alpha index light curves of W Ser are presented and discussed. W Ser is a very complex binary system that undergoes complicated, large changes in its light curves. The physical properties of W Ser are only poorly known, but it probably contains one component at its Roche surface, rapidly transfering matter to a component which is embedded in a thick, opaque disk. In several respects, W Ser resembles an upscale version of a cataclysmic variable binary system.
Data Monitoring Committees

Randomized clinical trials are the standard by which new interventions are evaluated for benefit or harm. Federal guidelines in the United States now recommend that all trials have a monitoring plan for early evidence of harm. For trials that have serious irreversible outcomes such as death, heart attack, stroke, or cancer recurrence, an external independent committee called a Data Monitoring Committee (DMCs) is recommended to evaluate the accumulating interim data. Trials for which interim data are convincing for benefit or harm may be terminated early. DMCs began in the early 1970s by trials sponsored by the National Institutes of Health and more recently by the pharmaceutical industry. DMCs review not only the primary outcome data and the serious adverse events but also the recruitment progress, patient compliance to the intervention, other secondary outcome variables, and high risk subgroups of patients if such exist. Because of the complexity of such monitoring, DMCs have a composition with biological, clinical, and biostatistical expertise. Keywords: Data Monitoring Committee; early termination
The Political Economy of Debt and Entitlements

This article presents a dynamic political-economic model of total government obligations. Its focus is on the interplay between debt and entitlements. In our model, both are tools by which temporarily powerful groups can extract resources from groups that will be powerful in the future: debt transfers resources across periods; entitlements directly target the future allocation of resources. We prove the following results. First, the presence of endogenous entitlements dampens the incentives of politically powerful groups to accumulate debt, but it leads to an increase in total government obligations. Second, fiscal rules can have perverse effects: if entitlements are unconstrained, and there are capital market frictions, debt limits lead to an increase in total government obligations and to worse outcomes for all groups. Analogous results hold for entitlement limits. Third, our model sheds some lights on the influence of capital market frictions on the incentives of governments to adopt fiscal rules, and implement entitlement programs. Finally, we identify preference polarization as a possible explanation for the joint growth of debt and entitlements.
A machine learning efficient frontier

Abstract We propose a simple approach to bridge between portfolio theory and machine learning. The outcome is an out-of-sample machine learning efficient frontier based on two assets, high risk and low risk. By rotating between the two assets, we show that the proposed frontier dominates the mean–variance efficient frontier out-of-sample. Our results, therefore, shed important light on the appeal of machine learning into portfolio selection under estimation risk.
Lectures on Inflationary Cosmology

The standard big bang theory asserts that the Universe was born at some moment t, = 0 about 15 billion years ago, in a state of infinitely large density and temperature. With the rapid expansion of the Universe the average energy of particles, given by the temperature, decreased rapidly, and the Universe became cold. This theory became especially popular after the discovery of the microwave background radiation. However, by the end of the 70’s it was understood that this theory is hardly compatible with the present theory of elementary particles (primordial monopole problem, Polonyi fields problem, gravitino problem, domain wall problem) and it has many internal difficulties (flatness problem, horizon problem, homogeneity and isotropy problems, etc.).
Swimming sheet in a viscosity-stratified fluid

In this work, we theoretically investigate the motion of a Taylor swimming sheet immersed in a viscosity-stratified fluid. The propulsion of the swimmer disturbs the surrounding fluid, which influences the transport of the stratifying agent described by the advection–diffusion equation. We employ a regular perturbation scheme to solve the coupled differential equations of motion up to the second order with the small parameter given by the ratio of the wave amplitude and the wavelength. The expression for the swimming velocity is linear in the magnitude of the viscosity gradient, while depending on the Peclet number in a non-monotonic way. Interestingly, we find that the Peclet number governs the propensity of the sheet to propel towards regions of favourable viscosities. In particular, for small Peclet numbers (), the swimmer prefers regions of high viscosity. Our analysis shows that purely hydrodynamic effects might be responsible for the experimentally observed accumulation of swimmers near favourable viscosity regions. We find that viscosity gradients influence other motility characteristics of the swimmer, such as power expenditure and hydrodynamic efficiency, and provide analytical expressions for both.
Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges

Magnetic Resonance Imaging (MRI) suffers from several artifacts, the most common of which are motion artifacts. These artifacts often yield images that are of non-diagnostic quality. To detect such artifacts, images are prospectively evaluated by experts for their diagnostic quality, which necessitates patient-revisits and rescans whenever non-diagnostic quality scans are encountered. This motivates the need to develop an automated framework capable of accessing medical image quality and detecting diagnostic and non-diagnostic images. In this paper, we explore several convolutional neural network-based frameworks for medical image quality assessment and investigate several challenges therein.
node2bits: Compact Time- and Attribute-Aware Node Representations for User Stitching

Identity stitching, the task of identifying and matching various online references (e.g., sessions over different devices and timespans) to the same user in real-world web services, is crucial for personalization and recommendations. However, traditional user stitching approaches, such as grouping or blocking, require pairwise comparisons between a massive number of user activities, thus posing both computational and storage challenges. Recent works, which are often application-specific, heuristically seek to reduce the amount of comparisons, but they suffer from low precision and recall. To solve the problem in an application-independent way, we take a heterogeneous network-based approach in which users (nodes) interact with content (e.g., sessions, websites), and may have attributes (e.g., location). We propose node2bits, an efficient framework that represents multi-dimensional features of node contexts with binary hashcodes. node2bits leverages feature-based temporal walks to encapsulate short- and long-term interactions between nodes in heterogeneous web networks, and adopts SimHash to obtain compact, binary representations and avoid the quadratic complexity for similarity search. Extensive experiments on large-scale real networks show that node2bits outperforms traditional techniques and existing works that generate real-valued embeddings by up to \(5.16\%\) in F1 score on user stitching, while taking only up to \(1.56\%\) as much storage.
A Ribosome Interaction Surface Sensitive to mRNA GCN Periodicity

A longstanding challenge is to understand how ribosomes parse mRNA open reading frames (ORFs). Significantly, GCN codons are over-represented in the initial codons of ORFs of prokaryote and eukaryote mRNAs. We describe a ribosome rRNA-protein surface that interacts with an mRNA GCN codon when next in line for the ribosome A-site. The interaction surface is comprised of the edges of two stacked rRNA bases: the Watson–Crick edge of 16S/18S rRNA C1054 and the adjacent Hoogsteen edge of A1196 (Escherichia coli 16S rRNA numbering). Also part of the interaction surface, the planar guanidinium group of a conserved Arginine (R146 of yeast ribosomal protein Rps3) is stacked adjacent to A1196. On its other side, the interaction surface is anchored to the ribosome A-site through base stacking of C1054 with the wobble anticodon base of the A-site tRNA. Using molecular dynamics simulations of a 495-residue subsystem of translocating ribosomes, we observed base pairing of C1054 to nucleotide G at position 1 of the next-in-line codon, consistent with previous cryo-EM observations, and hydrogen bonding of A1196 and R146 to C at position 2. Hydrogen bonding to both of these codon positions is significantly weakened when C at position 2 is changed to G, A or U. These sequence-sensitive mRNA-ribosome interactions at the C1054-A1196-R146 (CAR) surface potentially contribute to the GCN-mediated regulation of protein translation.
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

Although graph neural networks (GNNs) have made great progress recently on learning from graph-structured data in practice, their theoretical guarantee on generalizability remains elusive in the literature. In this paper, we provide a theoretically-grounded generalizability analysis of GNNs with one hidden layer for both regression and binary classification problems. Under the assumption that there exists a ground-truth GNN model (with zero generalization error), the objective of GNN learning is to estimate the ground-truth GNN parameters from the training data. To achieve this objective, we propose a learning algorithm that is built on tensor initialization and accelerated gradient descent. We then show that the proposed learning algorithm converges to the ground-truth GNN model for the regression problem, and to a model sufficiently close to the ground-truth for the binary classification problem. Moreover, for both cases, the convergence rate of the proposed learning algorithm is proven to be linear and faster than the vanilla gradient descent algorithm. We further explore the relationship between the sample complexity of GNNs and their underlying graph properties. Lastly, we provide numerical experiments to demonstrate the validity of our analysis and the effectiveness of the proposed learning algorithm for GNNs.
On Efficient Constructions of Checkpoints

Efficient construction of checkpoints/snapshots is a critical tool for training and diagnosing deep learning models. In this paper, we propose a lossy compression scheme for checkpoint constructions (called LC-Checkpoint). LC-Checkpoint simultaneously maximizes the compression rate and optimizes the recovery speed, under the assumption that SGD is used to train the model. LC-Checkpointuses quantization and priority promotion to store the most crucial information for SGD to recover, and then uses a Huffman coding to leverage the non-uniform distribution of the gradient scales. Our extensive experiments show that LC-Checkpoint achieves a compression rate up to $28\times$ and recovery speedup up to $5.77\times$ over a state-of-the-art algorithm (SCAR).
The quaternion-based spatial-coordinate and orientation-frame alignment problems.

The general problem of finding a global rotation that transforms a given set of spatial coordinates and/or orientation frames (the `test' data) into the best possible alignment with a corresponding set (the `reference' data) is reviewed. For 3D point data, this `orthogonal Procrustes problem' is often phrased in terms of minimizing a root-mean-square deviation (RMSD) corresponding to a Euclidean distance measure relating the two sets of matched coordinates. This article focuses on quaternion eigensystem methods that have been exploited to solve this problem for at least five decades in several different bodies of scientific literature, where they were discovered independently. While numerical methods for the eigenvalue solutions dominate much of this literature, it has long been realized that the quaternion-based RMSD optimization problem can also be solved using exact algebraic expressions based on the form of the quartic equation solution published by Cardano in 1545; focusing on these exact solutions exposes the structure of the entire eigensystem for the traditional 3D spatial-alignment problem. The structure of the less-studied orientation-data context is then explored, investigating how quaternion methods can be extended to solve the corresponding 3D quaternion orientation-frame alignment (QFA) problem, noting the interesting equivalence of this problem to the rotation-averaging problem, which also has been the subject of independent literature threads. The article concludes with a brief discussion of the combined 3D translation–orientation data alignment problem. Appendices are devoted to a tutorial on quaternion frames, a related quaternion technique for extracting quaternions from rotation matrices and a review of quaternion rotation-averaging methods relevant to the orientation-frame alignment problem. The supporting information covers novel extensions of quaternion methods to the 4D Euclidean spatial-coordinate alignment and 4D orientation-frame alignment problems, some miscellaneous topics, and additional details of the quartic algebraic eigenvalue problem.
Legislating in the time of a pandemic: window of opportunity or invitation for recklessness?

The COVID-19 epidemic has been exacerbated by failures in diagnostic testing for the virus in the United States. In response to these problems, two bills have been introduced in Congress to not only reform emergency use of diagnostic tests, but to fundamentally reform diagnostics regulation in non-emergencies. There has been a long-standing recognition that current U.S. regulation of diagnostics is outdated and problematic, and the history of public health legislation is that emergencies and crises have been the primary motivating factor to break Congressional inertia and to implement new legislation. Thus, the COVID-19 may create a useful “window of opportunity” to pass much-needed legislative reform of diagnostic regulation in both emergency and non-emergency contexts. At the same time, rushing radical legislative changes, especially if they have not been subject to careful stakeholder engagement and Congressional deliberation in advance, is precarious and could result in reckless and disruptive changes. We review and apply the historical lessons of legislating in response to a crisis and conclude the one but not both of the pending legislative proposals may satisfy the criteria for an appropriate opportunistic change for diagnostics regulation.