cssi/SciSciGPT-SciSciNet huggingface dataset:
Serum albumin concentration as an independent prognostic indicator in patients with pulmonary arterial hypertension

BACKGROUND Serum albumin is a strong prognostic indicator for many disease processes, yet limited data exist regarding its prognostic relationship in pulmonary arterial hypertension (PAH). Our study aims to assess the relationship of hypoalbuminemia with disease severity and mortality in this population. HYPOTHESIS Serum albumin concentrations are a predictor of outcomes in PAH. METHODS A retrospective review of all patients with World Health Organization group 1 PAH evaluated between March 2001 and August 2008 was performed. Patients were stratified into groups based on serum albumin concentration ≤3.3 g/dL (hypoalbuminemia) vs >3.3 g/dL. Clinical, hemodynamic, and survival comparisons were compared between groups using Student t test and χ2 test, followed by univariate analysis and multivariate logistic regression. RESULTS A total of 163/273 (59.7%) patients had a documented serum albumin concentration. Hypoalbuminemia was present in 41 (25.2%) patients and serum albumin ≤3.3 g/dL represented the lowest quartile of serum albumin. Patients with hypoalbuminemia had higher rates of renal dysfunction (26.8% vs 9.8%, P =0.0069) and hepatic dysfunction (29.3% vs 6.6%, P <0.001), and lower hemoglobin levels (11.6 vs 13.4 g/dL, P < 0.001). Hemodynamic and functional capacity assessments were comparable between groups. Independent predictors of mortality included low albumin levels (hazard ratio [HR]: 0.485, P = 0.008), high right atrial systolic area (HR: 1.062, P = 0.003), low Fick-derived cardiac index (HR: 1.465, P = 0.016), and high New York Heart Association functional class (HR: 1.767, P = 0.042). Patients with hypoalbuminemia demonstrated a significantly lower survival rate at latest follow-up (P = 0.01). CONCLUSIONS Lower serum albumin concentrations in patients with PAH are associated with higher mortality and can serve as a marker of disease severity in this patient population.
Neural Cross-Lingual Coreference Resolution And Its Application To Entity Linking

We propose an entity-centric neural crosslingual coreference model that builds on multi-lingual embeddings and language independent features. We perform both intrinsic and extrinsic evaluations of our model. In the intrinsic evaluation, we show that our model, when trained on English and tested on Chinese and Spanish, achieves competitive results to the models trained directly on Chinese and Spanish respectively. In the extrinsic evaluation, we show that our English model helps achieve superior entity linking accuracy on Chinese and Spanish test sets than the top 2015 TAC system without using any annotated data from Chinese or Spanish.
Detection of multi-dimensional co-exclusion patterns in microbial communities.

Motivation Identification of complex relationships among members of microbial communities is key to understand and control the microbiota. Co-exclusion is arguably one of the most important patterns reflecting micro-organisms' intolerance to each other's presence. Knowing these relations opens an opportunity to manipulate microbiotas, personalize anti-microbial and probiotic treatments as well as guide microbiota transplantation. The co-exclusion pattern however, cannot be appropriately described by a linear function nor its strength be estimated using covariance or (negative) Pearson and Spearman correlation coefficients. This manuscript proposes a way to quantify the strength and evaluate the statistical significance of co-exclusion patterns between two, three or more variables describing a microbiota and allows one to extend analysis beyond micro-organism abundance by including other microbiome associated measurements such as, pH, temperature etc., as well as estimate the expected numbers of false positive co-exclusion patterns in a co-exclusion network. Results The implemented computational pipeline (CoEx) tested against 2380 microbial profiles (samples) from The Human Microbiome Project resulted in body-site specific pairwise co-exclusion patterns. Availability and implementation C++ source code for calculation of the score and P-value for two, three and four dimensional co-exclusion patterns as well as source code and executable files for the CoEx pipeline are available at https://scsb.utmb.edu/labgroups/fofanov/co-exclusion_in_microbial_communities.asp. Supplementary information Supplementary data are available at Bioinformatics online.
Are matching funds for smallholder irrigation money well spent

Abstract Groundwater irrigation can dramatically affect agricultural production and productivity. Despite its potential as an agricultural development tool, little credible evidence exists for the impacts of groundwater development on smallholder agriculture. We add to the evidence on the benefits of irrigation investments for small producers by evaluating the Rural Business Development (RBD) program of the Millennium Challenge Corporation in Nicaragua for small plantain producers. The RBD program offered matching funds covering up to 30% of the cost of two years of inputs, extension services, and diesel-powered micro-sprinkler irrigation for individual farms. In order to estimate the average impact of the RBD program on its beneficiaries, we combine model selection via the LASSO with doubly robust treatment effect estimation as applied to two years of panel data for 146 producers. We find that the program had substantial impacts on plantain revenue and production, while achieving nearly complete irrigation coverage of plantain land among beneficiaries. We find no discernible impact on household expenditure.
Compressible Simulation of Rotor-Stator Interaction in Pump-Turbines

This work investigates the influence of water compressibility on pressure pulsations induced by rotor-stator interaction (RSI) in hydraulic machinery, using the commercial CFD solver ANSYS-CFX. A pipe flow example with harmonic velocity excitation at the inlet plane is simulated using different grid densities and time step sizes. Results are compared with a validated code for hydraulic networks (SIMSEN). Subsequently, the solution procedure is applied to a simplified 2.5-dimensional pump-turbine configuration in prototype with different speeds of sound as well as in model scale with an adapted speed of sound. Pressure fluctuations are compared with numerical and experimental data based on prototype scale. The good agreement indicates that the scaling of acoustic effects with an adapted speed of sound works well. With respect to pressure fluctuation amplitudes along the centerline of runner channels, incompressible solutions exhibit a linear decrease while compressible solutions exhibit sinusoidal distributions with maximum values at half the channel length, coinciding with analytical solutions of one-dimensional acoustics. Furthermore, in compressible simulation the amplification of pressure fluctuations is observed from the inlet of stay vane channels to the spiral case wall. Finally, the procedure is applied to a three-dimensional pump configuration in model scale with adapted speed of sound. Normalized Pressure fluctuations are compared with results from prototype measurements. Compared to incompressible computations, compressible simulations provide similar pressure fluctuations in vaneless space, but pressure fluctuations in spiral case and penstock may be much higher.
The intra-industry effects of proxy contests

In this study, we examine the intra-industry effect of proxy contests. Proxy contests convey the information of common industrial risks or expected competitive relationship change. We find significant negative abnormal returns in the group of competitors of target firms with negative abnormal returns, and such negative abnormal returns become larger for similar-size competitors. In contrast, there are no significant abnormal returns for competitors of target firms with positive abnormal returns. These findings are consistent with the information-based theory but not the competitive theory.
Fetal MRI in management of complicated meconium ileus: Prenatal and surgical imaging

Objective To review fetal MRI cases surgically proven to have meconium ileus (MI) and obstruction, describe the common fetal MRI findings that distinguish cases of complicated MI, and to compare these findings with surgical images and perinatal outcomes. Method We performed a retrospective review of all fetal MRI examinations and the corresponding medical record from our tertiary care children's hospital over an 18-month period. Postnatal management and outcomes were reviewed for these patients, and those patients with surgical or postmortem diagnosis of complicated MI were included in the study. Results Our analysis revealed 7 cases. In this cohort, 3 imaging features of the fetal bowel were repeatedly seen: gradient appearance of intraluminal bowel contents, abnormally localized meconium signal, and collapsed appearance of the colon on MRI. Surgical diagnoses confirmed MI. All live-born infants underwent surgical repair. Conclusion Fetal MRI should be included in the diagnostic algorithm of any pregnancy where fetal bowel obstruction is suspected to better risk stratify patients.
The N-cadherin interactome in primary cardiomyocytes as defined using quantitative proximity proteomics.

ABSTRACT The junctional complexes that couple cardiomyocytes must transmit the mechanical forces of contraction while maintaining adhesive homeostasis. The adherens junction (AJ) connects the actomyosin networks of neighboring cardiomyocytes and is required for proper heart function. Yet little is known about the molecular composition of the cardiomyocyte AJ or how it is organized to function under mechanical load. Here, we define the architecture, dynamics and proteome of the cardiomyocyte AJ. Mouse neonatal cardiomyocytes assemble stable AJs along intercellular contacts with organizational and structural hallmarks similar to mature contacts. We combine quantitative mass spectrometry with proximity labeling to identify the N-cadherin (CDH2) interactome. We define over 350 proteins in this interactome, nearly 200 of which are unique to CDH2 and not part of the E-cadherin (CDH1) interactome. CDH2-specific interactors comprise primarily adaptor and adhesion proteins that promote junction specialization. Our results provide novel insight into the cardiomyocyte AJ and offer a proteomic atlas for defining the molecular complexes that regulate cardiomyocyte intercellular adhesion. This article has an associated First Person interview with the first authors of the paper.
Phenotypic landscape of schizophrenia-associated genes defines candidates and their shared functions

Genomic studies have identified hundreds of candidate genes near loci associated with risk for schizophrenia. To define candidates and their functions, we mutated zebrafish orthologues of 132 human schizophrenia-associated genes and created a phenotype atlas consisting of whole-brain activity maps, brain structural differences, and profiles of behavioral abnormalities. Phenotypes were diverse but specific, including altered forebrain development and decreased prepulse inhibition. Exploration of these datasets identified promising candidates in more than 10 gene-rich regions, including the magnesium transporter cnnm2 and the translational repressor gigyf2, and revealed shared anatomical sites of activity differences, including the pallium, hypothalamus or tectum. Single-cell RNA sequencing uncovered an essential role for the understudied transcription factor znf536 in the development of forebrain neurons implicated in social behavior and stress. This phenotypic landscape of schizophrenia-associated genes prioritizes more than 30 candidates for further study and provides hypotheses to bridge the divide between genetic association and biological mechanism.
Understanding End-to-End Effects of Channel Dynamics in Millimeter Wave 5G New Radio

A critical challenge for wireless communications in the millimeter wave (mmWave) bands is blockage. MmWave signals suffer significant penetration losses from many common materials and objects, and small changes in the position of obstacles in the environment can cause large variations in the channel quality. This paper provides a measurement-based study of the effects of human blockage on an end-to-end application over a mmWave cellular link. A phased array system is used to measure the channel in multiple directions almost simultaneously in a realistic indoor scenario. The measurements are integrated into a detailed ns-3 simulation that models both the latest 3GPP New Radio beam search procedure as well as the internet protocol stack. The measurement-based simulation illustrates how recovery from blockage depends on the path diversity and beam search.
A Third Way: The Politics of School District Takeover and Turnaround in Lawrence, Massachusetts:

Purpose: School district superintendents say politics is the number one factor limiting their performance, yet research provides limited guidance on navigating the political dynamics of district im...
StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction

This paper presents StereoNet, the first end-to-end deep architecture for real-time stereo matching that runs at 60fps on an NVidia Titan X, producing high-quality, edge-preserved, quantization-free disparity maps. A key insight of this paper is that the network achieves a sub-pixel matching precision than is a magnitude higher than those of traditional stereo matching approaches. This allows us to achieve real-time performance by using a very low resolution cost volume that encodes all the information needed to achieve high disparity precision. Spatial precision is achieved by employing a learned edge-aware upsampling function. Our model uses a Siamese network to extract features from the left and right image. A first estimate of the disparity is computed in a very low resolution cost volume, then hierarchically the model re-introduces high-frequency details through a learned upsampling function that uses compact pixel-to-pixel refinement networks. Leveraging color input as a guide, this function is capable of producing high-quality edge-aware output. We achieve compelling results on multiple benchmarks, showing how the proposed method offers extreme flexibility at an acceptable computational budget.
Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment

Biomimicry, adapting and implementing nature's designs provides an adequate first-order solution to achieving superior mechanical properties. However, the design space is too vast even using biomimetic designs as prototypes for optimization. Here, we propose a new approach to design hierarchical materials using machine learning, trained with a database of hundreds of thousands of structures from finite element analysis, together with a self-learning algorithm for discovering high-performing materials where inferior designs are phased out for superior candidates. Results show that our approach can create microstructural patterns that lead to tougher and stronger materials, which are validated through additive manufacturing and testing. We further show that machine learning can be used as an alternative method of coarse-graining – analyzing and designing materials without the use of full microstructural data. This novel paradigm of smart additive manufacturing can aid in the discovery and fabrication of new material designs boasting orders of magnitude increase in computational efficacy over conventional methods.
Orientation information in encoding facial expressions.

Abstract Previous research showed that we use different regions of a face to categorize different facial expressions, e.g. mouth region for identifying happy faces; eyebrows, eyes and upper part of nose for identifying angry faces. These findings imply that the spatial information along or close to the horizontal orientation might be more useful than others for facial expression recognition. In this study, we examined how the performance for recognizing facial expression depends on the spatial information along different orientations, and whether the pixel-level differences in the face images could account for subjects’ performance. Four facial expressions—angry, fearful, happy and sad—were tested. An orientation filter (bandwidth = 23°) was applied to restrict information within the face images, with the center of the filter ranged from 0° (horizontal) to 150° in steps of 30°. Accuracy for recognizing facial expression was measured for an unfiltered and the six filtered conditions. For all four facial expressions, recognition performance (normalized d′) was virtually identical for filter orientations of −30°, horizontal and 30°, and declined systematically as the filter orientation approached vertical. The information contained in mouth and eye regions is a significant predictor for subject’s response (based on the confusion patterns). We conclude that young adults with normal vision categorizes facial expression most effectively based on the spatial information around the horizontal orientation which captures primary changes of facial features across expressions. Across all spatial orientations, the information contained in mouth and eye regions contributes significantly to facial expression categorization.
Robust manipulation of the behavior of Drosophila melanogaster by a fungal pathogen in the laboratory

We are surrounded by billions of microbes, many of which live on or even inside us. With some of these tiny creatures we share a mutually beneficial relationship, and they help to protect and nourish us in return for food and shelter. But some microbes have taken this relationship a step further and evolved the ability to manipulate the behavior of their host animals to their advantage. For example, certain fungi can hijack the nervous systems of ants, turning them into ‘zombies’ that are forced to climb to the precise height of a plant with the right conditions for the fungus to grow. Another fungus, called Entomophthora muscae, induces a similar behavior in flies. Like with the ants, this fungus forces the flies to climb to a high location and to attach themselves to the plant with their mouthparts, so providing a basis for the fungus to grow. Due to the lack of knowledge and tools that allow us to study the genes and cells of many of these host species, it remains unclear how these microbes can manipulate other animals and change their behavior. Now, Elya et al. wanted to find out whether this process can be examined in a well-known ‘model organism’, the fruit fly. The fruit flies were infected with E. muscae obtained from the wild and activity patterns in the genes of both organisms were tracked. One day after infection with the fungus, the flies developed a strong immune response to the invader, and many genes involved in the immune system were overactive. After two days, the fungus started to adopt the shape that eventually kills the flies and began to invade the nervous system. By the third day, the fungus had spread throughout the body and most flies died around four to five days following infection. Two to three hours after the flies had died, the digestive and reproductive systems had been consumed by the fungus and the nervous system was in the process of being degraded. Contrary to other infected organisms, the fungus got inside the fly’s nervous system during the early stages of infection. This could be an important clue as to how the fungus changes the fly’s behavior, but more research is needed to confirm this. The techniques developed in the study of Elya et al. can now be used to study how exactly microbes affect their hosts. A better knowledge of the relationship between these organisms will provide new insight into how animal behaviors are encoded and generated.
Hardness of RNA folding problem with four symbols

Abstract An RNA sequence is a string composed of four types of nucleotides, A , C , G , and U. The goal of the RNA folding problem is to find a maximum cardinality set of crossing-free pairs of the form { A , U } or { C , G } in a given RNA sequence. The problem is central in bioinformatics and has received much attention over the years. Abboud, Backurs, and Williams (FOCS 2015) demonstrated a conditional lower bound for a generalized version of the RNA folding problem based on a conjectured hardness of the k-clique problem. Their lower bound requires the RNA sequence to have at least 36 types of symbols, making the result not applicable to the RNA folding problem in real life (i.e., alphabet size 4). In this paper, we present an improved lower bound that works for the alphabet size 4 case. We also investigate the Dyck edit distance problem, which is a string problem closely related to RNA folding. We demonstrate a reduction from RNA folding to Dyck edit distance with alphabet size 10. This leads to a much simpler proof of the conditional lower bound for Dyck edit distance problem given by Abboud, Backurs, and Williams (FOCS 2015), and lowers the alphabet size requirement.
Detecting Violations of Differential Privacy

The widespread acceptance of differential privacy has led to the publication of many sophisticated algorithms for protecting privacy. However, due to the subtle nature of this privacy definition, many such algorithms have bugs that make them violate their claimed privacy. In this paper, we consider the problem of producing counterexamples for such incorrect algorithms. The counterexamples are designed to be short and human-understandable so that the counterexample generator can be used in the development process -- a developer could quickly explore variations of an algorithm and investigate where they break down. Our approach is statistical in nature. It runs a candidate algorithm many times and uses statistical tests to try to detect violations of differential privacy. An evaluation on a variety of incorrect published algorithms validates the usefulness of our approach: it correctly rejects incorrect algorithms and provides counterexamples for them within a few seconds.
Greedy Algorithms for the Shortest Common Superstring That Are Asymptotically Optimal

There has recently been a resurgence of interest in the shortest common superstring problem due to its important applications in molecular biology (e.g., recombination of DNA) and data compression. The problem is NP-hard, but it has been known for some time that greedy algorithms work well for this problem. More precisely, it was proved in a recent sequence of papers that in the worst case a greedy algorithm produces a superstring that is at most β times (2≤β≤ 4 ) worse than optimal. We analyze the problem in a probabilistic framework, and consider the optimal total overlap O n opt and the overlap O n rg produced by various greedy algorithms. These turn out to be asymptotically equivalent. We show that with high probability $\lim_{n\to \infty} O_n^{\rm opt}/(n\log n) =\lim_{n\to \infty} O_n^{\rm rg}/(n\log n) =1/H$ , where n is the number of original strings and H is the entropy of the underlying alphabet. Our results hold under a condition that the lengths of all strings are not too short.
Fast Fault Diagnosis of a Lithium-Ion Battery for Hybrid Electric Aircraft

A well-designed battery management system along with a set of voltage and current sensors is required to properly measure and control the battery cell operational variables for Hybrid Electric Aircrafts (HEAs). Some critical functions of the battery including State-Of-Charge (SOC) and State-Of-Health (SOH) estimations, over-current, and over-/under-voltage protections are mainly related to current and voltage sensor measurements. Therefore, in case of battery faults occur in HEA, designing a reliable and robust diagnostic procedure is essential. In this study, for Li-ion batteries, a new and fast fault diagnosis technique via collecting data is proposed. Finally, the effectiveness of the proposed diagnostic method is validated, and the results show how over-charge, over-discharge and sensor faults can be accurately detected.
Defending Elections against Malicious Spread of Misinformation.

The integrity of democratic elections depends on voters’ access to accurate information. However, modern media environments, which are dominated by social media, provide malicious actors with unprecedented ability to manipulate elections via misinformation, such as fake news. We study a zerosum game between an attacker, who attempts to subvert an election by propagating a fake new story or other misinformation over a set of advertising channels, and a defender who attempts to limit the attacker’s impact. Computing an equilibrium in this game is challenging as even the pure strategy sets of players are exponential. Nevertheless, we give provable polynomial-time approximation algorithms for computing the defender’s minimax optimal strategy across a range of settings, encompassing different population structures as well as models of the information available to each player. Experimental results confirm that our algorithms provide nearoptimal defender strategies and showcase variations in the difficulty of defending elections depending on the resources and knowledge available to the defender.
Fundamental Limits of Covert Bit Insertion in Packets

Covert communication is necessary when revealing the mere existence of a message leaks sensitive information to an attacker. Consider a network link where an authorized transmitter Jack sends packets to an authorized receiver Steve, and the packets visit Alice, Willie, and Bob, respectively, before they reach Steve. Covert transmitter Alice wishes to alter the packet stream in some way to send information to covert receiver Bob without watchful and capable adversary Willie being able to detect the presence of the message. In our previous works, we addressed two techniques for such covert transmission from Alice to Bob: packet insertion and packet timing. In this paper, we consider covert communication via bit insertion in packets with available space (e.g., with size less than the maximum transmission unit). We consider three scenarios: 1) packet sizes are independent and identically distributed (i.i.d.) with a probability mass function (pmf) whose support is a set of one bit spaced values; 2) packet sizes are i.i.d. with a pmf whose support is arbitrary; 3) packet sizes may be dependent. For the first and second assumptions, we show that Alice can covertly insert $O(\sqrt{n})$ bits of information in a flow of n packets; conversely, if she inserts $\omega(\sqrt{n})$ bits of information, Willie can detect her with arbitrarily small error probability. For the third assumption, we prove Alice can covertly insert on average $O(c(n)/\sqrt{n})$ bits in a sequence of n packets, where $c(n)$ is the average number of conditional pmf of packet sizes given the history, with a support of at least size two.
Who creates new firms when local opportunities arise

Abstract We examine the characteristics of the individuals who become entrepreneurs when local opportunities arise. We identify local demand shocks by linking fluctuations in global commodity prices to municipality-level agricultural endowments in Brazil. We find that the firm creation response is mostly driven by young and skilled individuals. The characteristics of these responsive entrepreneurs are significantly different from those of average entrepreneurs in the economy. By structurally estimating a novel two-sector model of a local economy, we highlight how the demographic composition of the local population can significantly affect the entrepreneurial responsiveness of the economy.
Why We Do Not Evolve Software? Analysis of Evolutionary Algorithms.

In this article, we review the state-of-the-art results in evolutionary computation and observe that we do not evolve nontrivial software from scratch and with no human intervention. A number of po...
mRNAs and lncRNAs intrinsically form secondary structures with short end-to-end distances.

The 5′ and 3′ termini of RNA play important roles in many cellular processes. Using Forster resonance energy transfer (FRET), we show that mRNAs and lncRNAs have an intrinsic propensity to fold in the absence of proteins into structures in which the 5′ end and 3′ end are ≤7 nm apart irrespective of mRNA length. Computational estimates suggest that the inherent proximity of the ends is a universal property of most mRNA and lncRNA sequences. Only guanosine-depleted RNA sequences with low sequence complexity are unstructured and exhibit end-to-end distances expected for the random coil conformation of RNA. While the biological implications remain to be explored, short end-to-end distances could facilitate the binding of protein factors that regulate translation initiation by bridging mRNA 5′ and 3′ ends. Furthermore, our studies provide the basis for measuring, computing and manipulating end-to-end distances and secondary structure in RNA in research and biotechnology. It was previously suggested that formation of RNA secondary structure tends to bring the 5′ and 3′ ends of RNA into close proximity. Here the authors use experimental and computational approaches to show that mRNAs and lncRNAs have an intrinsic propensity to fold into structures in which the 5′ end and 3′ end are ≤7 nm apart irrespective of length.
Computational geometry and the U.S. Supreme Court

Abstract We use the United States Supreme Court as an illuminative context in which to discuss three different spatial voting preference models: an instance of the widely used single-peaked preferences, and two models that are more novel in which vote outcomes have a strength in addition to a location. We introduce each model from a formal axiomatic perspective, briefly discuss practical motivation for each in terms of judicial behavior, prove mathematical relationships among the voting coalitions compatible with each model, and then study the two-dimensional setting by presenting computational tools for working with the models and by exploring these with judicial voting data from the Supreme Court.
Firm Responses to Mass Outrage: Technology, Blame, and Employment

When an employee’s off-duty conduct generates mass social media outrage, managers commonly respond by firing the employee. This, I argue, can be a mistake. The thesis I defend is the following: the fact that a firing would occur in a mass social media outrage context brought about by the employee’s off-duty conduct generates a strong ethical reason weighing against the act. In particular, it contributes to the firing constituting an inappropriate act of blame. Scholars who caution against firing an employee for off-duty conduct have thus far focused primarily on due process related issues or legal concerns pertaining to free speech, lifestyle discrimination, and employment at-will. However, these concerns amount to only a partial, and contingent, diagnosis of what is at issue. I argue that even when due process considerations are met, firings in these contexts can be unjustified. Moreover, even if a business is not concerned with the unethical conduct per se, but is rather strictly concerned with PR, the argument I advance nevertheless provides one important ethical reason that counts against firings in mass social media outrage contexts. Given that managers are often under significant pressure to respond swiftly in cases where an employee is at the center of mass social media outrage, it is especially important that scholars begin to clarify the normative issues. This article builds on the burgeoning philosophical literature on the ethics of blame and provides a novel account of a distinctive ethical concern that arises with firings in mass social media outrage contexts.
The Impact of Permanent Residency Delays for STEM PhDs: Who leaves and Why

Abstract This paper assesses whether delays in obtaining permanent residency status can explain recent declines in the share of Chinese and Indian PhD graduates from US STEM programs who remain in the US after their studies. We find that newly-binding limits on permanent visas for those from China and India with advanced degrees are significantly associated with declines in stay rates. The stay rate of Chinese graduates declines by 2.1 percentage points for each year of delay, while Indian graduates facing delays of at least 5½ years have a stay rate that is 10.6 percentage points lower. The per-country permanent visa cap affects a large share of STEM PhDs who are disproportionately found in fields of study that have been crucial in stimulating US economic growth yet enroll relatively few natives. Finally, results suggest that the growth of science in countries of origin has an important influence on stay rates, while macroeconomic factors such as GDP per capita affect stay rates only via their impact on science funding. We conclude that per-country limits play a significant role in constraining the supply of highly skilled STEM workers in the US economy.
Dynamics of the Kuramoto-Sakaguchi oscillator network with asymmetric order parameter.

We study the dynamics of a generalized version of the famous Kuramoto-Sakaguchi coupled oscillator model. In the classic version of this system, all oscillators are governed by the same ordinary differential equation (ODE), which depends on the order parameter of the oscillator configuration. The order parameter is the arithmetic mean of the configuration of complex oscillator phases, multiplied by some constant complex coupling factor. In the generalized model, we consider that all oscillators are still governed by the same ODE, but the order parameter is allowed to be any complex linear combination of the complex oscillator phases, so the oscillators are no longer necessarily weighted identically in the order parameter. This asymmetric version of the K-S model exhibits a much richer variety of steady-state dynamical behavior than the classic symmetric version; in addition to stable synchronized states, the system may possess multiple stable ( N − 1 , 1 ) states, in which all but one of the oscillators are synchronized, as well as multiple families of neutrally stable states or closed orbits, in which no two oscillators are synchronized. We present an exhaustive description of the possible steady state dynamical behaviors; our classification depends on the complex coefficients that determine the order parameter. We use techniques from group theory and hyperbolic geometry to reduce the dynamic analysis to a 2D flow on the unit disc, which has geometric significance relative to the hyperbolic metric. The geometric-analytic techniques we develop can in turn be applied to study even more general versions of Kuramoto oscillator networks.
A novel streamlined trauma response team training improves imaging efficiency for pediatric blunt abdominal trauma patients.

Abstract Background/purpose The morbidity and mortality of children with traumatic injuries are directly related to the time to definitive management of their injuries. Imaging studies are used in the trauma evaluation to determine the injury type and severity. The goal of this project is to determine if a formal streamlined trauma response improves efficiency in pediatric blunt trauma by evaluating time to acquisition of imaging studies and definitive management. Methods This study is a chart review of patients Results Time from arrival to CT acquisition decreased from 37 (SD 23) to 28 (SD27) min (p Conclusion The implementation of a streamlined trauma team approach is associated with both decreased time to CT, FAST, OR, and an increased proportion of FAST scans in the pediatric trauma evaluation. This could result in the rapid identification of injuries, faster disposition from the ED, and potentially improve outcomes in bluntly injured children. Type of study Therapeutic Level of evidence Level III
User interface

A user interface is that portion of an interactive computer system that communicates with the user. Design of the user interface includes any aspect of the system that is visible to the user. Once, all computer users were specialists in computing, and interfaces consisted of jumper wires in patch boards, punched cards (q.v.) prepared offline, and batch printouts. Today a wide range of nonspecialists use computers, and keyboards, mice, and graphical displays are the most common interface hardware. The user interface is becoming a larger and larger portion of the software in a computer system--and a more important portion, as broader groups of people use computers. As computers become more powerful, the critical bottleneck in applying computer-based systems to solve problems is more often in the user interface rather than in the computer hardware or software.
Graphical Methods Pre-20th Century†

Despite their utility for analyzing and presenting data, the use of graphs in science is a relatively late development and their emergence through history has been uneven and contested. Modern statistical graphics date largely to the pioneering work of William Playfair in the late eighteenth century. The gradual spread of graphical methods in the early nineteenth century was slowed by various antigraph prejudices, but eventually culminated in their enthusiastic reception during the second half of that century. During the Golden Age of graphics, graphs were used extensively in fields ranging from demography to laboratory physiology. Hailed as the universal language of science, graphs underwent a proliferation of novel formats, and they figured crucially in a number of scientific discoveries. The behavioral scientists of that period – including many of psychology's founding figures – made sophisticated applications of graphical methods, but such methods would be eclipsed by the rise of inferential statistics in the behavioral sciences after 1900. Keywords: Playfair; Karl Pearson; Galton; line graphs; histograms; ogives
Interpretable Almost-Exact Matching for Causal Inference

Matching methods are heavily used in the social and health sciences due to their interpretability. We aim to create the highest possible quality of treatment-control matches for categorical data in the potential outcomes framework. The method proposed in this work aims to match units on a weighted Hamming distance, taking into account the relative importance of the covariates; the algorithm aims to match units on as many relevant variables as possible. To do this, the algorithm creates a hierarchy of covariate combinations on which to match (similar to downward closure), in the process solving an optimization problem for each unit in order to construct the optimal matches. The algorithm uses a single dynamic program to solve all of the units' optimization problems simultaneously. Notable advantages of our method over existing matching procedures are its high-quality interpretable matches, versatility in handling different data distributions that may have irrelevant variables, and ability to handle missing data by matching on as many available covariates as possible.
E-Commerce Participation and Household Income Growth in Taobao Villages

E-commerce has developed rapidly in China, and Taobao Villages, which are villages significantly engaged in e-commerce, are prospering in rural areas. E-commerce is fostering entrepreneurship and creating flexible and inclusive employment opportunities, including for women and youth. This paper examines the role of e-commerce participation in household income growth, drawing from a survey of representative Taobao Villages in 2017. The paper presents three main findings. First, e-commerce participation is not random: participation is higher among the households with younger household heads, with secondary education, particularly those with technical and vocational education, urban work experience, and knowledge of e-commerce. Second, e-commerce participation is associated with higher household income, with some indications that participation has a strong positive effect on household incomes. Third, e-commerce appears to yield benefits that are broadly shared among participants in an equitable way in Taobao Villages.
Preparing for planetary surface exploration by measuring habitat dust intrusion with filter tests during an analogue Mars mission

Abstract As humans venture deeper into space more issues related to operations will become apparent. While the perils of dust particles may not be widely recognized, it is one of the major issues astronauts will face on the surface of the Moon and Mars. Dust particles present a problem for both astronaut health and equipment as revealed during the Apollo era lunar surface missions. Dust particles cling to spacesuits and field gear, which upon ingress would begin circulating throughout the spacecraft or habitat. An astronaut's health is compromised by the dust particle's potential to embed in the lungs and cause respiratory illnesses. The extreme abrasiveness and granularity of the particles make it near impossible to completely shield a spacecraft or habitat from dust related damage. NASA's Glenn Research Center (GRC) collaborated with Crew 188 at the Mars Desert Research Station (MDRS) in Utah to measure how much dust entered the habitat during a series of extravehicular activities (EVAs), or surface excursions. A NASA GRC developed multistage filter system, coined the Scroll Filter System, was tested, for its effectiveness in removing dust that entered the airlock and habitat after the EVAs. An optical particle counter measured the ambient airlock particulates five times including: before the start of operations; after the crew left for EVA; in the middle of the EVA with the settled air; before the crew entered the airlock after EVA; and finally, after the crew simulated re-pressurization and suit brushing off in the airlock. Data was also collected in several of the working environment locations around MDRS and outside the habitat in the wind. Data collected from this research will help establish filter equipment for life support systems and prescribed operations for astronaut transition from a planetary surface into a desired clean habitat. Measurements may aid in updating a baseline expected dust load for a surface habitat and further facilitate the mitigation of astronaut's exposure to dust particles on the surface of celestial bodies.
Stability of uncertain linear systems with time delay

The control of systems with uncertain dynamics and unpredictable disturbances has raised some challenging problems. This is particularly important when high system performance is to be guaranteed at all times. Recently, Time Delay Control has been suggested as an alternative control scheme. The proposed control system does not require an explicit plant model nor does it depend on the estimation of specific plant parameters. Rather, it combines adaptation with past observations to directly estimate the effect of the plant dynamics. This paper outlines the Time Delay Control law for a class of linear dynamic systems and then presents a sufficient condition for stability of linear uncertain systems with time delay. The ideas of Nyquist and Kharitonov are used in the development of a sufficient condition, which does not resort to using approximations for time delay. Like Nyquist, the condition depends on maps of the Nyquist path and, like Kharitonov, stability depends on four functions each yielding a stable system. In this paper we combine these ideas to determine the stability of systems where the Time Delay Controller is applied to single input single output, linear time-invariant plants whose coefficients are known to vary within certain defined intervals. The development is carried out in the context of Time Delay Control but it can be applied in more general cases. Two examples will illustrate the approach and the usefulness of the technique.
Bank Risk Dynamics and Distance to Default

We adapt structural models of default risk to take into account the special nature of bank assets. The usual assumption of log-normally distributed asset values is not appropriate for banks. Typical bank assets are risky debt claims, which implies that they embed a short put option on the borrowers’ assets, leading to a concave payoff. This has important consequences for banks’ risk dynamics and distance to default estimation. Due to the payoff non-linearity, bank asset volatility rises following negative shocks to borrower asset values. As a result, standard structural models in which the asset volatility is assumed to be constant can severely understate banks’ default risk in good times when asset values are high. Bank equity payoffs resemble a mezzanine claim rather than a call option. Bank equity return volatility is therefore much more sensitive to big negative shocks to asset values than in standard structural models.
The Evolution of Corporate Cash

We study time-series and cross-firm variation in corporate cash holdings from 1920 to 2014. The recent increase in cash is not unique in magnitude. However, the recent divergence between average and aggregate cash is new and entirely driven by a shift in cash policies of newly public firms, whereas within-firm changes have been negative or flat since the 1940s. Cross-sectional relations between cash holdings and firm characteristics are stable throughout the century, though characteristics explain little of the trends in aggregate cash. Macroeconomic conditions, corporate profitability and investment, and (since 2000) repatriation taxes explain aggregate cash over the last century.Received August 23, 2017; editorial decision April 28, 2018 by Editor Andrew Karolyi.
Data Analytics Supports Decentralized Innovation

Data-analytics technology can accelerate the innovation process by enabling existing knowledge to be identified, accessed, combined, and deployed to address new problem domains. However, like prior...
BOCS: DNA k-mer content and scoring for rapid genetic biomarker identification at low coverage.

Abstract A single, inexpensive diagnostic test capable of rapidly identifying a wide range of genetic biomarkers would prove invaluable in precision medicine. Previous work has demonstrated the potential for high-throughput, label-free detection of A-G-C-T content in DNA k-mers, providing an alternative to single-letter sequencing while also having inherent lossy data compression and massively parallel data acquisition. Here, we apply a new bioinformatics algorithm – block optical content scoring (BOCS) – capable of using the high-throughput content k-mers for rapid, broad-spectrum identification of genetic biomarkers. BOCS uses content-based sequence alignment for probabilistic mapping of k-mer contents to gene sequences within a biomarker database, resulting in a probability ranking of genes on a content score. Simulations of the BOCS algorithm reveal high accuracy for identification of single antibiotic resistance genes, even in the presence of significant sequencing errors (100% accuracy for no sequencing errors, and >90% accuracy for sequencing errors at 20%), and at well below full coverage of the genes. Simulations for detecting multiple resistance genes within a methicillin-resistant Staphylococcus aureus (MRSA) strain showed 100% accuracy at an average gene coverage of merely 0.515, when the k-mer lengths were variable and with 4% sequencing error within the k-mer blocks. Extension of BOCS to cancer and other genetic diseases met or exceeded the results for resistance genes. Combined with a high-throughput content-based sequencing technique, the BOCS algorithm potentiates a test capable of rapid diagnosis and profiling of genetic biomarkers ranging from antibiotic resistance to cancer and other genetic diseases.
SCARI: a strategic caching and reservation protocol for ICN

The point-to-point resource reservation solutions over IP networks are often end-to-end, and data flowing through these reserved tunnels are not reusable. As a result, the in-network resources are not optimally utilized. Information Centric Networking (ICN) has several properties that can more intelligently facilitate resource reservations. In this paper, we present Strategic Caching And Reservation in ICN (SCARI) for reserving resources on ICN networks. Preliminary simulation results indicate that SCARI can reduce bandwidth consumption and free up network resources by aggregating reservation requests and strategically caching content in the network.