cssi/SciSciGPT-SciSciNet huggingface dataset:
Kinesin's Light Chains Inhibit the Head- and Microtubule-Binding Activity of its Tail

Kinesin-1 comprises two heavy chains (KHCs) and two light chains (KLCs). The KHC tail inhibits ATPase activity by interacting directly with the enzymatic KHC heads, and the inhibitory segment of the tail also binds to microtubules. We have discovered a novel role for the KLCs in regulating the head- and microtubule-binding activities of the kinesin-1 tail. We show that KLCs reduce the affinity of the head-tail interaction over ten-fold. Functional assays confirm that the KLCs attenuate tail-mediated inhibition of kinesin-1 activity. We also show that KLCs block tail-microtubule binding. Inhibition of head-tail binding requires both steric and electrostatic factors. Inhibition of tail-microtubule binding is largely electrostatic and is more pronounced at physiological pH (pH 7.4) than under acidic conditions (pH 6.6). Full inhibition requires a negatively-charged linker region in the KLCs, between its KHC-interacting and cargo-binding domains. Our data support a model wherein KLCs promote activation of kinesin-1 for cargo transport by suppressing both the head-tail and tail-microtubule interactions. Additionally, KLC-mediated inhibition of tail-microtubule binding may influence kinesin-1's emerging role in microtubule sliding and cross-linking.
Dynamics of laminar and transitional flows over slip surfaces: effects on the laminar─turbulent separatrix

The effect of slip surfaces on the laminar–turbulent separatrix of plane Poiseuille flow is studied by direct numerical simulation. In laminar flows, the inclusion of the slip surfaces results in a drag reduction of over 10 %, which is in good agreement with previous studies and the theory of laminar slip flows. Turbulence lifetimes, the likelihood that turbulence is sustained, is investigated for transitional flows with various slip lengths. We show that slip surfaces decrease the likelihood of sustained turbulence compared to the no-slip case, and the likelihood is further decreased as slip length is increased. A more deterministic analysis of the effects of slip surfaces on a transition to turbulence is performed by using nonlinear travelling-wave solutions to the Navier–Stokes equations, also known as exact coherent solutions. Two solution families, dubbed P3 and P4, are used since their lower-branch solutions are embedded on the boundary of the basin of attraction of laminar and turbulent flows (Park & Graham, J. Fluid Mech. , vol. 782, 2015, pp. 430–454). Additionally, they exhibit distinct flow structures – the P3 and P4 are denoted as core mode and critical-layer mode, respectively. Distinct effects of slip surfaces on the solutions are observed by the skin-friction evolution, linear growth rate and phase-space projection of transitional trajectories. The slip surface appears to modify the transition dynamics very little for the core mode, but quite considerably for the critical-layer mode. Most importantly, the slip surface promotes different transition dynamics – an early and bypass-like transition for the core mode and a delayed and H- or K-type-like transition for the critical-layer mode. We explain these distinct transition dynamics based on spatio-temporal and quadrant analyses. It is found that slip surfaces promote the prevalence of strong wall-toward motions (sweep-like events) near vortex cores close to the channel centre, inducing an early transition, while long sustained ejection events are present in the region of the $\unicode[STIX]{x1D6EC}$ -shaped vortex cores close to the critical layer, resulting in a delayed transition. This should motivate flow control strategies to fully exploit these distinct transition dynamics for transition to turbulence.
New experimental results in proton radioactivity

A review of experimental data obtained recently on proton-radioactive nuclei is presented. The highlights include the observation of fine structure in proton emission, for the decays of 131Eu, 145Tm and 146Tm, and the studies of the excited states in proton-emitting nuclei. The observation limits are extended to few nanobarns cross-sections ( 140Ho, 164Ir and 130Eu) and few microsecond half-lives (e.g., 145Tm). Measured decay properties for thirty-nine proton-emitting ground and isomeric states contributed to the understanding of nuclear masses and evolution of single-particle states at and beyond the proton drip line. Experimental results have stimulated new theoretical approaches to proton emission and the structure of unbound narrow resonance states.
Atom Motion in Solids Following Nuclear Transmutation

Following nuclear decay, a daughter atom in a solid will "stay in place" if the recoil energy is less than the threshold for displacement. At high temperature, it may subsequently undergo long-range diffusion or some other kind of atomic motion. In this paper, motion of 111Cd tracer probe atoms is reconsidered following electron-capture decay of 111In in the series of In3R phases (R= rare-earth). The motion produces nuclear relaxation that was measured using the method of perturbed angular correlation. Previous measurements along the entire series of In3R phases appeared to show a crossover between two diffusional regimes. While relaxation for R= Lu-Tb is consistent with a simple vacancy diffusion mechanism, relaxation for R= Nd-La is not. More recent measurements in Pd3R phases demonstrate that the site-preference of the parent In-probe changes along the series and suggests that the same behavior occurs for daughter Cd-probes. The anomalous motion observed for R= Nd-La is attributed to "lanthanide expansion" occurring towards La end-member phases. For In3La, the Cd-tracer is found to jump away from its original location on the In-sublattice in an extremely short time, of order 0.5 ns at 1000 K and 1.2 ms at room temperature, a residence time too short to be consistent with defect-mediated diffusion. Several scenarios that can explain the relaxation are presented based on the hypothesis that daughter Cd-probes first jump to neighboring interstitial sites and then are either trapped and immobilized, undergo long-range diffusion, or persist in a localized motion in a cage.
Phosphorylation of STIM1 Underlies Suppression of Store-Operated Calcium Entry During Mitosis

When endoplasmic reticulum (ER) Ca2+ stores are depleted, Ca2+ influx via plasma membrane (PM) Ca2+ channels is activated by store-operated Ca2+ entry (SOCE). SOCE involves Orai1 Ca2+ influx channels and STIM1 ER Ca2+ sensors. ER Ca2+ depletion induces rearrangement of STIM1 from a diffuse localization throughout the ER membrane into punctate structures near the PM, where it activates Orai1 channels. Interestingly, SOCE is strongly suppressed during mitosis, the only known physiological situation in which SOCE is negatively regulated; however, the mechanisms that underlie SOCE suppression during mitosis are unknown. We found that both endogenous STIM1 and expressed eYFP-tagged STIM1 (eYFP-STIM1) immunoprecipitated from mitotic but not interphase HeLa and HEK293 cells were recognized by the phosphospecific MPM-2 antibody, suggesting mitosis-specific phosphorylation of STIM1. We also found that rearrangement of eYFP-STIM1 into near-PM puncta in response to ER Ca2+ depletion was suppressed during mitosis. We therefore hypothesized that STIM1 phosphorylation underlies prevention of STIM1 puncta formation and suppression of SOCE during mitosis. MPM-2 recognizes phospho-serine or threonine followed by proline, and human STIM1 contains 10 occurrences of S/T-P, all downstream of amino acid 482. eYFP-STIM1 truncated at amino acid 482 (482STOP) was not recognized by MPM-2 when immunoprecipitated from mitotic cells, suggesting lack of phosphorylation. In support of our hypothesis, non-phosphorylatable 482STOP co-expressed with Orai1 rearranged into near-PM puncta in response to ER Ca2+ depletion in mitotic cells, and also significantly rescued mitotic SOCE. A combination of mass spectrometry and site-directed mutagenesis identified S486 and S668 as mitosis-specific phosphorylated residues, and mutation of both to alanine also resulted in partial but significant rescue of SOCE in mitotic cells. Therefore, our data suggest that phosphorylation of S486 and S668 underlies suppression of SOCE during mitosis, although additional phosphorylation sites are likely involved.
Work Incentives in the Social Security Disability Benefit Formula

We examine the connection between taxes paid and benefits accrued under the Social Security Disability Insurance (SSDI) program on both the intensive and extensive margins. We perform these calculations for stylized workers given the existing benefit structure and disability hazard rates. On the intensive margin, we examine the effect of an additional dollar of earnings on the marginal payroll taxes contributed and future benefits earned. We find that the present discounted value of disability benefits received from an additional dollar of earnings, net of the SSDI payroll tax, generally declines with age, becoming negative around age 40 and reaching almost zero at age 63. On the extensive margin, we determine the effect of working an additional year on the additional payroll taxes and future benefits as a percentage of income. The return to working an additional year at an income level just large enough to earn Social Security credits for the year is large and positive through age 60. However, the return to working an additional full year is substantially smaller and becomes negative at approximately age 57. Thus, older workers face strong incentives to earn enough to obtain creditable coverage through age 60, but they face disincentives for additional earnings. In addition, workers aged 61 and older face work disincentives at any level of earnings. We repeat this analysis for stylized workers at different levels of earnings and find that, while the program transfers resources from high earners to low earners, the workers experience similar patterns in the returns to working.
Separating Measured Genetic and Environmental Effects: Evidence Linking Parental Genotype and Adopted Child Outcomes.

There has been widespread adoption of genome wide summary scores (polygenic scores) as tools for studying the importance of genetics and associated life course mechanisms across a range of demographic and socioeconomic outcomes. However, an often unacknowledged issue with these studies is that parental genetics impact both child environments and child genetics, leaving the effects of polygenic scores difficult to interpret. This paper uses multi-generational data containing polygenic scores for parents (n = 7193) and educational outcomes for adopted (n = 855) and biological (n = 20,939) children, many raised in the same families, which allows us to separate the influence of parental polygenic scores on children outcomes between environmental (adopted children) and environmental and genetic (biological children) effects. Our results complement recent work on “genetic nurture” by showing associations of parental polygenic scores with adopted children’s schooling, providing additional evidence that polygenic scores combine genetic and environmental influences and that research designs are needed to separate these estimated impacts.
Does March Madness lead to irrational exuberance in the NBA draft? High-value employee selection decisions and decision-making bias

Abstract We use detailed, personally-assembled data on the performance of collegiate and professional basketball players over the 1997–2010 period, to look at the impact of performance in the NCAA “March Madness” college basketball tournament on NBA teams’ draft decisions and players’ ultimate success in the NBA. We find that unexpected March Madness (MM) performance, in terms of team wins and player scoring, affects draft decisions, and NBA personnel who are making these draft decisions are not irrationally overweighting this MM information. If anything, the unexpected performance in the March Madness tournament deserves more weight than it gets in the draft decisions.
Properties of the X-Ray Emitting Gas in Early-Type Galaxies

The properties of the X-ray emitting gas in a sample of 81 E and S0 galaxies observed with the Einstein Observatory are studied. Measured fluxes for 55 of the galaxies and upper limits for 26 of them are reported. An attempt is made to use consistent optical parameters for the galaxies, including a correction to the velocities for the Virgocentric flow. The sample is then used to explore the contribution from discrete sources, the global physical properties of the hot gas, and the implications for heating by supernovae and gravity. Finally, the question of the presence of heavy halos is addressed. 72 references.
Overview and design of the sPHENIX TPC

The proposed sPHENIX detector at RHIC is being designed to study with unprecedented precision the nature of the Quark Gluon Plasma, or QGP, at RHIC through measurement of jets, jet correlations, and Y particles. To reach the goal of producing a high mass-resolution reconstruction of the Y(nS) states, a compact TPC covering pseudorapidities < |1.1| is under construction to provide sPHENIX with the necessary invariant mass resolution. Similar to the ALICE-TPC upgrade, the sPHENIX TPC design presently utilizes quadruple-GEM detectors. As an alternative solution, a double-GEM-Micromega hybrid arrangement is currently being tested. Utilizing novel zigzag patterned readout pads, a modified SAMPA readout chip, and an optimized Ne-CF4 gas mixture immersed in a 1.4 T magnetic field to reduce ion backflow, sPHENIX will have a unique lens into the QGP. The motivation behind the design and innovations of the TPC will be presented, along with the current status of the project.
Universal Decompositional Semantic Parsing.

We introduce a transductive model for parsing into Universal Decompositional Semantics (UDS) representations, which jointly learns to map natural language utterances into UDS graph structures and annotate the graph with decompositional semantic attribute scores. We also introduce a strong pipeline model for parsing into the UDS graph structure, and show that our transductive parser performs comparably while additionally performing attribute prediction. By analyzing the attribute prediction errors, we find the model captures natural relationships between attribute groups.
"None of the Above":Measure Uncertainty in Dialog Response Retrieval

This paper discusses the importance of uncovering uncertainty in end-to-end dialog tasks and presents our experimental results on uncertainty classification on the processed Ubuntu Dialog Corpus. We show that instead of retraining models for this specific purpose, we can capture the original retrieval model’s underlying confidence concerning the best prediction using trivial additional computation.
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features

Despite their success, kernel methods suffer from a massive computational cost in practice. In this paper, in lieu of commonly used kernel expansion with respect to $N$ inputs, we develop a novel optimal design maximizing the entropy among kernel features. This procedure results in a kernel expansion with respect to entropic optimal features (EOF), improving the data representation dramatically due to features dissimilarity. Under mild technical assumptions, our generalization bound shows that with only $O(N^{\frac{1}{4}})$ features (disregarding logarithmic factors), we can achieve the optimal statistical accuracy (i.e., $O(1/\sqrt{N})$). The salient feature of our design is its sparsity that significantly reduces the time and space cost. Our numerical experiments on benchmark datasets verify the superiority of EOF over the state-of-the-art in kernel approximation.
Quantized Decentralized Stochastic Learning over Directed Graphs

We consider a decentralized stochastic learning problem where data points are distributed among computing nodes communicating over a directed graph. As the model size gets large, decentralized learning faces a major bottleneck that is the heavy communication load due to each node transmitting large messages (model updates) to its neighbors. To tackle this bottleneck, we propose the quantized decentralized stochastic learning algorithm over directed graphs that is based on the push-sum algorithm in decentralized consensus optimization. More importantly, we prove that our algorithm achieves the same convergence rates of the decentralized stochastic learning algorithm with exact-communication for both convex and non-convex losses. Numerical evaluations corroborate our main theoretical results and illustrate significant speed-up compared to the exact-communication methods.
Germline mutation rates in young adults predict longevity and reproductive lifespan

Ageing may be due to mutation accumulation across the lifespan, leading to tissue dysfunction, disease, and death. We tested whether germline autosomal mutation rates in young adults predict their remaining survival, and, for women, their reproductive lifespans. Age-adjusted mutation rates (AAMRs) in 61 women and 61 men from the Utah CEPH (Centre d’Etude du Polymorphisme Humain) families were determined. Age at death, cause of death, all-site cancer incidence, and reproductive histories were provided by the Utah Population Database, Utah Cancer Registry, and Utah Genetic Reference Project. Higher AAMRs were significantly associated with higher all-cause mortality in both sexes combined. Subjects in the top quartile of AAMRs experienced more than twice the mortality of bottom quartile subjects (hazard ratio [HR], 2.07; 95% confidence interval [CI], 1.21–3.56; p = 0.008; median survival difference = 4.7 years). Fertility analyses were restricted to women whose age at last birth (ALB) was ≥ 30 years, the age when fertility begins to decline. Women with higher AAMRs had significantly fewer live births and a younger ALB. Adult germline mutation accumulation rates are established in adolescence, and later menarche in women is associated with delayed mutation accumulation. We conclude that germline mutation rates in healthy young adults may provide a measure of both reproductive and systemic ageing. Puberty may induce the establishment of adult mutation accumulation rates, just when DNA repair systems begin their lifelong decline.
Global stabilization of the oscillating eccentric rotor

The oscillating eccentric rotor has been widely studied to model resonance capture phenomena occurring in dual-spin spacecraft and rotating machinery. This phenomenon arises during spin-up as a resonance condition is encountered. We consider the related problem of rotor despin. Specifically, we determine nonlinear feedback control laws that not only despin the rotor but also bring its translational motion to rest. These globally asymptotically stabilizing control laws are derived using partial feedback linearization and integrator backstepping schemes. For the case in which the oscillating eccentric rotor is excited by a translational sinusoidal forcing function, the control law is shown to attenuate the amplitude of the translational oscillation.
Spotr: GPS spoofing detection via device fingerprinting

As the world's predominant navigation system, GPS is critical to modern life, finding applications in diverse areas like information security, healthcare, marketing, and power and water grid management. Unfortunately this diversification has only served to underscore the insecurity of GPS and the critical need to harden this system against manipulation and exploitation. A wide variety of attacks against GPS have already been documented, both in academia and industry. Several defenses have been proposed to combat these attacks, but they are ultimately insufficient due to scope, expense, complexity, or robustness. With this in mind, we present our own solution: fingerprinting of GPS satellites. We assert that it is possible to create signatures, or fingerprints, of the satellites (more specifically their transmissions) that allow one to determine nearly instantly whether a received GPS transmission is authentic or not. Furthermore, in this paper we demonstrate that this solution detects all known spoofing attacks, that it does so while being fast, cheap, and simpler than previous solutions, and that it is highly robust with respect to environmental factors.
Trends in prescriptions of lithium and other medications for patients with bipolar disorder in office-based practices in the United States: 1996–2015

Abstract Background Studies have shown that rates of lithium use for bipolar disorder in the United States declined through the 1990s as other mood stabilizing anticonvulsants and second-generation antipsychotics (SGAs) became more popular. We examined trends of medications for bipolar disorder from 1996 to 2015. Methods Twenty years of data from the National Ambulatory Medical Care Survey (NAMCS) were used. Weighted percentages of reported use of lithium, anticonvulsants, SGAs and antidepressants were calculated over two-year intervals. Logistic regression was used to examine factors related to polytherapy. Results Reported use of lithium declined from 38.1% (95%CI: 29.8% - 46.3%) in 1996–97 to 14.3% (95%CI: 10.6% - 18.1%) in 2006–07 and has remained stable since. During this time, reports of SGAs more than doubled. SGAs and/or anticonvulsants were reported in 75.4% (95%CI: 69.5% - 81.3%) of visits with bipolar diagnoses in 2014–15. Polytherapy increased by approximately 3% every two years and in 2014–15 occurred in over 30% of visits. Antidepressants were reported in 40–50% of visits, but their reported use without other mood stabilizers decreased from 18.2% (95%CI: 11.7% - 24.8%) in 1998–99 to 7.5% (95%CI: 4.2% - 10.9%) in 2014–15. Limitations The sample had limited power to study the effect of individual medications or the potential for differing effects in certain sub-groups of patients. Conclusions This study further documents the declining use of lithium for bipolar disorder, and corresponding increase in use of anticonvulsants and SGAs, despite the fact that lithium is typically recommended as a first line therapy for bipolar disorder.
Improper Learning for Non-Stochastic Control

We consider the problem of controlling a possibly unknown linear dynamical system with adversarial perturbations, adversarially chosen convex loss functions, and partially observed states, known as non-stochastic control. We introduce a controller parametrization based on the denoised observations, and prove that applying online gradient descent to this parametrization yields a new controller which attains sublinear regret vs. a large class of closed-loop policies. In the fully-adversarial setting, our controller attains an optimal regret bound of $\sqrt{T}$-when the system is known, and, when combined with an initial stage of least-squares estimation, $T^{2/3}$ when the system is unknown; both yield the first sublinear regret for the partially observed setting. Our bounds are the first in the non-stochastic control setting that compete with \emph{all} stabilizing linear dynamical controllers, not just state feedback. Moreover, in the presence of semi-adversarial noise containing both stochastic and adversarial components, our controller attains the optimal regret bounds of $\mathrm{poly}(\log T)$ when the system is known, and $\sqrt{T}$ when unknown. To our knowledge, this gives the first end-to-end $\sqrt{T}$ regret for online Linear Quadratic Gaussian controller, and applies in a more general setting with adversarial losses and semi-adversarial noise.
Accessible Computer Science for K-12 Students with Hearing Impairments

An inclusive science, technology, engineering and mathematics (STEM) workforce is needed to maintain America’s leadership in the scientific enterprise. Increasing the participation of underrepresented groups in STEM, including persons with disabilities, requires national attention to fully engage the nation’s citizens in transforming its STEM enterprise. To address this need, a number of initiatives, such as AccessCSforALL, Bootstrap, and CSforAll, are making efforts to make Computer Science inclusive to the 7.4 million K-12 students with disabilities in the U.S. Of special interest to our project are those K-12 students with hearing impairments. American Sign Language (ASL) is the primary means of communication for an estimated 500,000 people in the United States, yet there are limited online resources providing Computer Science instruction in ASL. This paper introduces a new project designed to support Deaf/Hard of Hearing (D/HH) K-12 students and sign interpreters in acquiring knowledge of complex Computer Science concepts. We discuss the motivation for the project and an early design of the accessible block-based Computer Science curriculum to engage D/HH students in hands-on computing education.
Cyclotron harmonic maser

Recent experiments will be discussed in which coherent power has been extracted from a gyrotron-like device up to the ninth cyclotron harmonic, and at wavelengths (in a single device) ranging from 8 mm to below 1 mm. The device employs a solid-beam 20 kV Pierce gun, a magnetostatic kicker, and a combination of two confocal Fabry-Perot resonators. Evidence supports the interpretation that high harmonic oscillations occur because coupling occurs at the beam boundary allowing short-wavelength Bernstein modes to be excited on the beam.2 Implications of these results will be drawn for the design of compact tunable mm-wave and sub-mm wave sources, and/or for mm-wave devices not requiring superconducting magnets.
EllipTrack: A Global-Local Cell-Tracking Pipeline for 2D Fluorescence Time-Lapse Microscopy

Time-lapse microscopy provides an unprecedented opportunity to monitor single-cell dynamics. However, tracking cells for long periods remains a technical challenge, especially for multi-day, large-scale movies with rapid cell migration, high cell density, and drug treatments that alter cell morphology/behavior. Here, we present EllipTrack, a global-local cell-tracking pipeline optimized for tracking such movies. EllipTrack first implements a global track-linking algorithm to construct tracks that maximize the probability of cell lineages. Tracking mistakes are then corrected with a local track-correction module in which tracks generated by the global algorithm are systematically examined and amended if a more probable alternative can be found. Through benchmarking, we show that EllipTrack outperforms state-of-the-art cell trackers and generates nearly error-free cell lineages for multiple large-scale movies. In addition, EllipTrack can adapt to time- and cell-density-dependent changes in cell migration speeds and requires minimal training datasets. EllipTrack is available at https://github.com/tianchengzhe/EllipTrack.
Simulating Anisoplanatic Turbulence by Sampling Inter-modal and Spatially Correlated Zernike Coefficients

Simulating atmospheric turbulence is an essential task for evaluating turbulence mitigation algorithms and training learning-based methods. Advanced numerical simulators for atmospheric turbulence are available, but they require evaluating wave propagation, which is computationally expensive. We present a propagation-free method for simulating imaging through turbulence with applications in ground-to-ground imaging. The key idea behind our work is a method to draw intermodal and spatially correlated Zernike coefficients. By establishing the equivalence of the angle-of-arrival correlation by Basu, McCrae, and Fiorino (2015) with the multiaperture correlation by Chanan (1992), we show that the Zernike coefficients can be drawn according to a covariance matrix defining the correlations. We propose fast and scalable sampling strategies to draw these samples. The method allows us to compress the wave propagation problem into a sampling problem, hence making the simulator significantly faster than existing ones. Experimental results show that the simulator has an excellent match with the theory and real turbulence data. We anticipate the simulator, which balances speed and accuracy, will be a useful tool for various computational imaging applications.
Birth hospital and racial and ethnic differences in severe maternal morbidity in the state of California.

Background Birth hospital has recently emerged as a potential key contributor to disparities in severe maternal morbidity, but investigations on its contribution to racial and ethnic differences remain limited. Objective We leveraged statewide data from California to examine whether birth hospital explained racial and ethnic differences in severe maternal morbidity. Study Design This cohort study used data on all births at ≥20 weeks gestation in California (2007–2012). Severe maternal morbidity during birth hospitalization was measured using the Centers for Disease Control and Prevention index of having at least 1 of the 21 diagnoses and procedures (eg, eclampsia, blood transfusion, hysterectomy). Mixed-effects logistic regression models (ie, women nested within hospitals) were used to compare racial and ethnic differences in severe maternal morbidity before and after adjustment for maternal sociodemographic and pregnancy-related factors, comorbidities, and hospital characteristics. We also estimated the risk-standardized severe maternal morbidity rates for each hospital (N=245) and the percentage reduction in severe maternal morbidity if each group of racially and ethnically minoritized women gave birth at the same distribution of hospitals as non-Hispanic white women. Results Of the 3,020,525 women who gave birth, 39,192 (1.3%) had severe maternal morbidity (2.1% Black; 1.3% US-born Hispanic; 1.3% foreign-born Hispanic; 1.3% Asian and Pacific Islander; 1.1% white; 1.6% American Indian and Alaska Native, and Mixed-race referred to as Other). Risk-standardized rates of severe maternal morbidity ranged from 0.3 to 4.0 per 100 births across hospitals. After adjusting for covariates, the odds of severe maternal morbidity were greater among nonwhite women than white women in a given hospital (Black: odds ratio, 1.25; 95% confidence interval, 1.19–1.31); US-born Hispanic: odds ratio, 1.25; 95% confidence interval, 1.20–1.29; foreign-born Hispanic: odds ratio, 1.17; 95% confidence interval, 1.11–1.24; Asian and Pacific Islander: odds ratio, 1.26; 95% confidence interval, 1.21–1.32; Other: odds ratio, 1.31; 95% confidence interval, 1.15–1.50). Among the studied hospital factors, only teaching status was associated with severe maternal morbidity in fully adjusted models. Although 33% of white women delivered in hospitals with the highest tertile of severe maternal morbidity rates compared with 53% of Black women, birth hospital only accounted for 7.8% of the differences in severe maternal morbidity comparing Black and white women and accounted for 16.1% to 24.2% of the differences for all other racial and ethnic groups. Conclusion In California, excess odds of severe maternal morbidity among racially and ethnically minoritized women were not fully explained by birth hospital. Structural causes of racial and ethnic disparities in severe maternal morbidity may vary by region, which warrants further examination to inform effective policies.
Heat kernel analysis on diamond fractals

Abstract This paper presents a detailed analysis of the heat kernel on an ( N × N ) -parameter family of compact metric measure spaces which do not satisfy the volume doubling property. In particular, uniform bounds of the heat kernel, its Lipschitz continuity and the continuity of the corresponding heat semigroup are studied; a specific example is presented revealing a logarithmic correction. The estimates are applied to derive functional inequalities of interest in describing the convergence to equilibrium of the diffusion process.
Urine as a high-quality source of host genomic DNA from wild populations

The ability to generate genomic data from wild animal populations has the potential to give unprecedented insight into the population history and dynamics of species in their natural habitats. However, for many species, it is impossible legally, ethically or logistically to obtain tissue samples of quality sufficient for genomic analyses. In this study we evaluate the success of multiple sources of genetic material (faeces, urine, dentin and dental calculus) and several capture methods (shotgun, whole-genome, exome) in generating genome-scale data in wild eastern chimpanzees (Pan troglodytes schweinfurthii) from Gombe National Park, Tanzania. We found that urine harbours significantly more host DNA than other sources, leading to broader and deeper coverage across the genome. Urine also exhibited a lower rate of allelic dropout. We found exome sequencing to be far more successful than both shotgun sequencing and whole-genome capture at generating usable data from low-quality samples such as faeces and dental calculus. These results highlight urine as a promising and untapped source of DNA that can be noninvasively collected from wild populations of many species.
Efficient random graph matching via degree profiles

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erdős-Renyi graphs $$G(n,\frac{d}{n})$$ . This can be viewed as an average-case and noisy version of the graph isomorphism problem. Under this model, the maximum likelihood estimator is equivalent to solving the intractable quadratic assignment problem. This work develops an $${\widetilde{O}}(n d^2+n^2)$$ -time algorithm which perfectly recovers the true vertex correspondence with high probability, provided that the average degree is at least $$d = \varOmega (\log ^2 n)$$ and the two graphs differ by at most $$\delta = O( \log ^{-2}(n) )$$ fraction of edges. For dense graphs and sparse graphs, this can be improved to $$\delta = O( \log ^{-2/3}(n) )$$ and $$\delta = O( \log ^{-2}(d) )$$ respectively, both in polynomial time. The methodology is based on appropriately chosen distance statistics of the degree profiles (empirical distribution of the degrees of neighbors). Before this work, the best known result achieves $$\delta =O(1)$$ and $$n^{o(1)} \le d \le n^c$$ for some constant c with an $$n^{O(\log n)}$$ -time algorithm and $$\delta ={{\widetilde{O}}}((d/n)^4)$$ and $$d = {\widetilde{\varOmega }}(n^{4/5})$$ with a polynomial-time algorithm.
Limits of Conformal Immersions Under a Bound on a Fractional Normal Curvature Quantity

We consider limits of weakly converging W1,2-maps Φk from a ball $B \subset \mathbb {R}^{2}$ into $\mathbb {R}^{3}$ which are conformal immersions. Under the assumption that a normal curvature term is small, namely if for the normal map u we have for some $s \in (\frac {1}{2},1)$ $$ {\int}_{B} {\int}_{B} \left|\frac{u_{k}(x) \wedge u_{k}(y)}{|x-y|^{s}}\right|^{\frac{2}{s}} \frac{dx dy}{|x-y|^{2}} < \varepsilon $$ then we show that we can either pass to the limit and obtain an almost everywhere immersion Φ or Φ collapses and is constant. This is in the spirit of the results by T. Toro, and S. Muller and V. Sverak, and F. Helein, who obtained similar statements under the stronger assumptions that the second fundamental form is bounded (but also a stronger result: a locally bi-Lipschitz parametrization). The fractional normal curvature assumption is vaguely reminiscent of curvature energies such as the scaling-invariant limits of tangent-point energies for surfaces as considered by Strzelecki, von der Mosel et al. and we hope that eventually the analysis in this work can be used to define weak immersions with these kind of energy bounds.
Vehicular LTE connectivity analysis in urban and rural environments using USRP measurements

Abstract The intelligent transportation system (ITS) offers a wide range of applications related to traffic management, which often require high data rate and low latency. The ubiquitous coverage and advancements of the Long Term Evolution (LTE) technology have made it possible to achieve these requirements and to enable broadband applications for vehicular users. In this paper, we perform field trial measurements in various different commercial LTE networks using software defined radios (SDRs) and report our findings. First, we provide a detailed tutorial overview on how to post-process SDR measurements for decoding broadcast channels and reference signal measurements from LTE networks. We subsequently describe the details of our measurement campaigns in urban, sub-urban, and rural environments. Based on these measurements, we report joint distributions of base station density, cellular coverage, link strength, disconnected vehicle duration, and vehicle velocity in these environments, and compare the LTE coverage in different settings. Our experimental results quantify the stronger coverage, shorter link distances, and shorter duration of disconnectivity in urban environments when compared to sub-urban and rural settings.
Tactile Dexterity: Manipulation Primitives with Tactile Feedback

This paper develops closed-loop tactile controllers for dexterous robotic manipulation with a dual-palm robotic system. Tactile dexterity is an approach to dexterous manipulation that plans for robot/object interactions that render interpretable tactile information for control. We divide the role of tactile control into two goals: 1) control the contact state between the end-effector and the object (contact/no-contact, stick/slip) by regulating the stability of planned contact configurations and monitoring undesired slip events; and 2) control the object state by tactile-based tracking and iterative replanning of the object and robot trajectories.Key to this formulation is the decomposition of manipulation plans into sequences of manipulation primitives with simple mechanics and efficient planners. We consider the scenario of manipulating an object from an initial pose to a target pose on a flat surface while correcting for external perturbations and uncertainty in the initial pose of the object. We experimentally validate the approach with an ABB YuMi dual-arm robot and demonstrate the ability of the tactile controller to react to external perturbations.
Games with Unawareness

We provide a tool to model and solve strategic situations where players' perceptions are limited, in the sense that they may only be aware of, or model, some of the aspects of the strategic situations at hand, as well as situations where players realize that other players' perceptions may be limited. We define normal, repeated, incomplete information and dynamic (extensive) form games with unawareness using a unified methodology. A game with unawareness is defined as a collection of standard games (of the corresponding form). The collection specifies how each player views the game, how she views the other players' perceptions of the game and so on. The modeler's description of perceptions, the players' description of other players' reasoning, etc. are shown to have consistent representations. We extend solution concepts such as rationalizability and Nash equilibrium to these games and study their properties. It is shown that while unawareness in normal form games can be mapped to incomplete information games, the extended Nash equilibrium solution is not mapped to a known solution concept in the equivalent incomplete information games, implying that games with unawareness generate novel types of behavior.
Statistical Analysis of Multi-Relational Network Recovery

In this paper, we develop asymptotic theories for a class of latent variable models for large-scale multi-relational networks. In particular, we establish consistency results and asymptotic error bounds for the (penalized) maximum likelihood estimators when the size of the network tends to infinity. The basic technique is to develop a non-asymptotic error bound for the maximum likelihood estimators through large deviations analysis of random fields. We also show that these estimators are nearly optimal in terms of minimax risk.
In-The-Wild Interference Characterization and Modelling for Electro-Quasistatic-HBC with Miniaturized Wearables

The emergence of Human Body Communication (HBC) as an alternative to wireless body area networks (WBAN) has led to the development of small sized, energy efficient and more secure wearable and implantable devices forming a network in and around the body. Previous studies claim that though HBC is comparatively more secure than WBAN, nevertheless, the electromagnetic (EM) radiative nature of HBC in >10MHz region makes the information susceptible to eavesdropping. Furthermore, interferences may be picked up by the body due to the human body antenna effect in the 40-400MHz range. Alternatively, electro-quasistatic (EQS) mode of HBC forms an attractive way for covert data transmission in the sub 10MHz region by allowing the signal to be contained within the body. However, there is a gap in the knowledge about the mechanism and sources of interference in this region (crucial in allowing for proper choice of data transmission band). In this paper, the interference coupling modality in the EQS region is explained along with its possible sources. Interferences seen by the wearable in the actual scenario is a non-trivial problem and a suitable measurement EQS HBC setup is designed to recreate it by employing a wearable sized measurement setup having a small ground plane. For the first time, a human biophysical interference pickup model is proposed and interference measurement results using a wearable device are presented up to 250kHz in different environmental settings.
Quantum dynamical bounds for ergodic potentials with underlying dynamics of zero topological entropy

We show that positive Lyapunov exponents imply upper quantum dynamical bounds for Schrodinger operators H f , θ u ( n ) = u ( n + 1 ) + u ( n − 1 ) + ϕ ( f n θ ) u ( n ) , where ϕ : ℳ → ℝ is a piecewise Holder function on a compact Riemannian manifold ℳ , and f : ℳ → ℳ is a uniquely ergodic volume-preserving map with zero topological entropy. As corollaries we also obtain localization-type statements for shifts and skew-shifts on higher-dimensional tori with arithmetic conditions on the parameters. These are the first localization-type results with precise arithmetic conditions for multifrequency quasiperiodic and skew-shift potentials.
Strangeness Physics with Clas

A brief overview of strangeness physics with the CLAS detector at JLab is given, mainly covering the domain of nucleon resonances. Several excited states predicted by the symmetric constituent quark model may have significant couplings to the KΛ or KΣ channels. We will discuss data that are relevant in the search for such states in the strangeness channel, and give an outlook on the future prospects of the N* program at JLab with electromagnetic probes.
Some algebraic symmetries of (2,2) supersymmetric systems

The Hilbert spaces of supersymmetric systems admit symmetries which are often related to the topology and geometry of the (target) field-space. Here, we study certain (2, 2)-supersymmetric systems in two-dimensional space–time which are closely related to superstring models. They all turn out to possess some hitherto unexploited and geometrically and topologically unobstructed symmetries, providing new tools for studying the topology and geometry of superstring target space–times, and so the dynamics of the effective field theory in these.
Dual-mixed finite element methods for the Navier-Stokes equations

A mixed finite element method for the Navier–Stokes equations is introduced in which the stress is a primary variable. The variational formulation retains the mathematical structure of the Navier–Stokes equations and the classical theory extends naturally to this setting. Finite element spaces satisfying the associated inf–sup conditions are developed.
Geodesics and nodal sets of Laplace eigenfunctions on hyperbolic manifolds

Let X be a manifold equipped with a complete Riemannian metric of constant negative curvature and finite volume. We demonstrate the finiteness of the collection of totally geodesic immersed hypersurfaces in X that lie in the zero-level set of some Laplace eigenfunction. For surfaces, we show that the number can be bounded just in terms of the area of the surface. We also provide constructions of geodesics in hyperbolic surfaces that lie in a nodal set but that do not lie in the fixed point set of a reflection symmetry.
Monte Carlo errors with less errors

Abstract We explain in detail how to estimate mean values and assess statistical errors for arbitrary functions of elementary observables in Monte Carlo simulations. The method is to estimate and sum the relevant autocorrelation functions, which is argued to produce more certain error estimates than binning techniques and hence to help toward a better exploitation of expensive simulations. An effective integrated autocorrelation time is computed which is suitable to benchmark efficiencies of simulation algorithms with regard to specific observables of interest. A Matlab code is offered for download that implements the method. It can also combine independent runs (replica) allowing to judge their consistency.
A trivial tail homology for non-A–adequate links

We prove a conjecture of Rozansky’s concerning his categorification of the tail of the colored Jones polynomial for an A–adequate link. We show that the tail homology groups he constructs are trivial for non-A–adequate links.
The Bartnik–Bray Outer Mass of Small Metric Spheres in Time-Symmetric 3-Slices

Given a sphere with Bartnik data close to that of a round sphere in Euclidean 3-space, we compute its Bartnik–Bray outer mass to first order in the data’s deviation from the standard sphere. The Hawking mass gives a well-known lower bound, and an upper bound is obtained by estimating the mass of a static vacuum extension. As an application we confirm that in a time-symmetric slice concentric geodesic balls shrinking to a point have mass-to-volume ratio converging to the energy density at their center, in accord with physical expectation and the behavior of other quasilocal masses. For balls shrinking to a point where the Riemann curvature tensor vanishes we can also compute the outer mass to fifth order in the radius—the term is proportional to the Laplacian of the scalar curvature at the center—but our estimate is not refined enough to identify this term in general at a point where merely the scalar curvature vanishes. In particular, it cannot discern gravitational contributions to the mass.
Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks

Deep neural networks (DNNs) have become a widely deployed model for numerous machine learning applications. However, their fixed architecture, substantial training cost, and significant model redundancy make it difficult to efficiently update them to accommodate previously unseen data. To solve these problems, we propose an incremental learning framework based on a grow-and-prune neural network synthesis paradigm. When new data arrive, the neural network first grows new connections based on the gradients to increase the network capacity to accommodate new data. Then, the framework iteratively prunes away connections based on the magnitude of weights to enhance network compactness, and hence recover efficiency. Finally, the model rests at a lightweight DNN that is both ready for inference and suitable for future grow-and-prune updates. The proposed framework improves accuracy, shrinks network size, and significantly reduces the additional training cost for incoming data compared to conventional approaches, such as training from scratch and network fine-tuning. For the LeNet-300-100 (LeNet-5) neural network architectures derived for the MNIST dataset, the framework reduces training cost by up to 64% (67%), 63% (63%), and 69% (73%) compared to training from scratch, network fine-tuning, and grow-and-prune from scratch, respectively. For the ResNet-18 architecture derived for the ImageNet dataset (DeepSpeech2 for the AN4 dataset), the corresponding training cost reductions against training from scratch, network fine-tunning, and grow-and-prune from scratch are 64% (67%), 60% (62%), and 72% (71%), respectively. Our derived models contain fewer network parameters but achieve higher accuracy relative to conventional baselines.