cssi/SciSciGPT-SciSciNet huggingface dataset:
Residual Urine Volumes in Patients with Spinal Cord Injury: Measurement with a Portable Ultrasound Instrument

Spinal cord injured (SCI) patients are often placed on an intermittent catheterization (IC) program during their initial rehabilitation in an effort to establish a catheter-free state. A noninvasive method to quantitatively determine residual urine volumes would decrease unnecessary catheterizations and be useful in the management of an IC program. This study was undertaken to determine if bladder volumes could be accurately determined in a group of SCI patients using a portable ultrasound scanner. Fifteen SCI patients underwent a total of 224 ultrasonic bladder volume determinations and 57 urethral catheterizations. Immediately prior to catheterization, two investigators alternately performed a total of four ultrasound readings on each patient using a hand-held portable instrument, the BVI 2000. The first ultrasound volume determination was comparable to the average ultrasound volume (r2 = 0.956). For catheterized volumes versus the initial ultrasound volume determination, r2 = 0.80. The average error was 18% for catheterized volumes within the range 50-700ml. Our results compare favorably with both real-time scanning using standard equipment and other portable instruments. The noninvasive nature, negligible risks, and reasonable estimates of volume warrant consideration of portable ultrasound scanning for the determination of bladder volumes in SCI patients.
HELPING ASSURE COMPONENT ALIGNMENT: INTRA-OPERATIVE DIGITAL RADIOGRAPHY

Two critical steps in achieving optimal results and minimizing complications (dislocation, lengthening, and intra-operative fracture) are careful pre-operative planning and more recently, the option of intra-operative imaging in order to optimise accurate and reproducible total hip replacement. The important issues to ascertain are relative limb length, offset and center of rotation. It is important to start the case knowing the patient9s perception of their limb length. Patient perception is equally important, if not more important, than the radiographic assessment. On the acetabular side, the teardrop should be identified and the amount of reaming necessary to place the inferior margin of the acetabular component adjacent to the tear drop should be noted. Superiorly the amount of exposed metal that is expected to be seen during surgery should be measured in millimeters. Once the key issues of limb length, offset, center of rotation, and acetabular component position relative to the native acetabulum have been confirmed along with the expected sizing of the acetabular and femoral components, it is critical that the operative plan is reproduced at the time of surgery and this can best be consistently performed with the use of intra-operative imaging. Advances in digital imaging now make efficient, cost-effective assessment of hip replacement possible. Embedded software allows accurate confirmation of the pre-operative plan intra-operatively when correction of potential errors is easily possible. Such technology is now mature after years of clinical use and studies have confirmed its success in avoiding outliers and achieving optimal results.
Exercise training prevents skeletal muscle plasma membrane cholesterol accumulation, cortical actin filament loss, and insulin resistance in C57BL/6J mice fed a western-style high-fat diet.

Abstract Insulin action and glucose disposal are enhanced by exercise, yet the mechanisms involved remain imperfectly understood. While the causes of skeletal muscle insulin resistance also remain poorly understood, new evidence suggest excess plasma membrane (PM) cholesterol may contribute by damaging the cortical filamentous actin (F‐actin) structure essential for GLUT4 glucose transporter redistribution to the PM upon insulin stimulation. Here, we investigated whether PM cholesterol toxicity was mitigated by exercise. Male C57BL/6J mice were placed on low‐fat (LF, 10% kCal) or high‐fat (HF, 45% kCal) diets for a total of 8 weeks. During the last 3 weeks of this LF/HF diet intervention, all mice were familiarized with a treadmill for 1 week and then either sham‐exercised (0 m/min, 10% grade, 50 min) or exercised (13.5 m/min, 10% grade, 50 min) daily for 2 weeks. HF‐feeding induced a significant gain in body mass by 3 weeks. Sham or chronic exercise did not affect food consumption, water intake, or body mass gain. Prior to sham and chronic exercise, “pre‐intervention” glucose tolerance tests were performed on all animals and demonstrated that HF‐fed mice were glucose intolerant. While sham exercise did not affect glucose tolerance in the LF or HF mice, exercised mice showed an improvement in glucose tolerance. Muscle from sham‐exercised HF‐fed mice showed a significant increase in PM cholesterol, loss of cortical F‐actin, and decrease in insulin‐stimulated glucose transport compared to sham‐exercised LF‐fed mice. These HF‐fed skeletal muscle membrane/cytoskeletal abnormalities and insulin resistance were improved in exercised mice. These data reveal a new therapeutic aspect of exercise being regulation of skeletal muscle PM cholesterol homeostasis. Further studies on this mechanism of insulin resistance and the benefits of exercise on its prevention are needed.
How Conservative is Frozen-time Interpolation?

It is shown in this note that for SISO system under l2 disturbances, when data commute approximately with the shift the optimal interpolation (over all linear time-varying interpolants) can be approximated by the supreme of the frozen-time Hankel norms. This confirms the intuition that the frozen-time constructed optimal or suboptimal interpolants are in fact nearly optimal when data vary slowly.
Hippocampal and Cortical Pyramidal Neurons Swell in Parallel with Astrocytes during Acute Hypoosmolar Stress.

Normal nervous system function is critically dependent on the balance of water and ions in the extracellular space. Pathological reduction in brain interstitial osmolarity results in osmotically-driven flux of water into cells, causing cellular edema which reduces the extracellular space and increases neuronal excitability and risk of seizures. Astrocytes are widely considered to be particularly susceptible to cellular edema due to selective expression of the water channel aquaporin-4 (AQP4). The apparent resistance of pyramidal neurons to osmotic swelling has been attributed to lack of functional water channels. In this study we report rapid volume changes in CA1 pyramidal cells in hypoosmolar ACSF (hACSF) that are equivalent to volume changes in astrocytes across a variety of conditions. Astrocyte and neuronal swelling was significant within 1 minute of exposure to 17 or 40% hACSF, was rapidly reversible upon return to normosmolar ACSF, and repeatable upon re-exposure to hACSF. Neuronal swelling was not an artifact of patch clamp, occurred deep in tissue, was similar at physiological vs. room temperature, and occurred in both juvenile and adult hippocampal slices. Neuronal swelling was neither inhibited by TTX, nor by antagonists of NMDA or AMPA receptors, suggesting that it was not occurring as a result of excitotoxicity. Surprisingly, genetic deletion of AQP4 did not inhibit, but rather augmented, astrocyte swelling in severe hypoosmolar conditions. Taken together, our results indicate that neurons are not osmoresistant as previously reported, and that osmotic swelling is driven by an AQP4-independent mechanism.
Ultrafast Comparison of Personal Genomes via Precomputed Genome Fingerprints.

We present an ultrafast method for comparing personal genomes. We transform the standard genome representation (lists of variants relative to a reference) into 'genome fingerprints' via locality sensitive hashing. The resulting genome fingerprints can be meaningfully compared even when the input data were obtained using different sequencing technologies, processed using different pipelines, represented in different data formats and relative to different reference versions. Furthermore, genome fingerprints are robust to up to 30% missing data. Because of their reduced size, computation on the genome fingerprints is fast and requires little memory. For example, we could compute all-against-all pairwise comparisons among the 2504 genomes in the 1000 Genomes data set in 67 seconds at high quality (21 microseconds per comparison, on a single processor), and achieved a lower quality approximation in just 11 seconds. Efficient computation enables scaling up a variety of important genome analyses, including quantifying relatedness, recognizing duplicative sequenced genomes in a set, population reconstruction, and many others. The original genome representation cannot be reconstructed from its fingerprint, effectively decoupling genome comparison from genome interpretation; the method thus has significant implications for privacy-preserving genome analytics.
Costly circuits, submodular schedules and approximate Carathéodory Theorems

Hybrid switching--in which a high bandwidth circuit switch (optical or wireless) is used in conjunction with a low bandwidth packet switch--is a promising alternative to interconnect servers in today's large-scale data centers. Circuit switches offer a very high link rate, but incur a non-trivial reconfiguration delay which makes their scheduling challenging. In this paper, we demonstrate a lightweight, simple and nearly optimal scheduling algorithm that trades off reconfiguration costs with the benefits of reconfiguration that match the traffic demands. Seen alternatively, the algorithm provides a fast and approximate solution toward a constructive version of Caratheodory's Theorem for the Birkhoff polytope. The algorithm also has strong connections to submodular optimization, achieves a performance at least half that of the optimal schedule and strictly outperforms the state of the art in a variety of traffic demand settings. These ideas naturally generalize: we see that indirect routing leads to exponential connectivity; this is another phenomenon of the power of multi-hop routing, distinct from the well-known load balancing effects.
Dental Manifestations of Pediatric Bone Disorders.

Purpose of review Several bone disorders affecting the skeleton often are manifest in the maxillofacial region. This review presents the most common bone disorders in children and their dental-oral manifestations: fibrous dysplasia, Paget's disease, osteogenesis imperfecta, renal osteodystrophy, hypophosphatasia, and osteoporosis. The specific intraoral characteristics will reviewed in detail. Recent findings Recent studies confirmed the close relationship between the mandible and the maxilla with the most prevalent systemic bone disorders in children. This review will help practitioners to integrate the oral health into the systemic health and improve the multidisciplinary approach of pediatric patients between medicine and dentistry.
Weaving Together Theory, Research, Practice, and Teaching: A Four‐dimensional Approach to Negotiation and Conflict Management Work

In this article, we suggest a new paradigm for writing on negotiation and conflict management that integrates theory, research, practice, and teaching. While there might be an implicit understanding that such integration is key to advancing the field, we make this explicit. Highlighting the critical aspects of this relationship, we call for a four-dimensional approach to writing in the negotiation and conflict management field. We suggest that adopting such systematic and intentional exploration of all four dimensions should be the default approach to writing on negotiation and conflict management topics. We provide brief summaries of the articles presented in the special issue and discuss the essence, origins, and weighting of the four dimensions in each paper. Finally, we suggest that this four-dimensional approach might have ramifications for the field's work, in areas other than writing.
Advertised Incentives for Participation in Daily Fantasy Sports Contests in 2015 and 2016: Legal Classification and Consumer Implications

During the summer of 2015, daily fantasy sports (DFS) advertising in the United States became ubiquitous, with DraftKings and FanDuel embarking on an aggressive advertising campaign. One year later, those commercials all but disappeared from television and radio. In the United States, DFS operators and the industry trade association have argued that fantasy games are legally distinct from prohibited forms of sports gambling; however, several state legislators have concluded differently. In this empirical examination, we examined the advertised incentives across the first two weeks of the National Football League (NFL) season in 2015 and 2016. In order to assess whether the arguments made by industry groups that DFS is distinct from gambling is conveyed in the messages being sent to consumers by the two major DFS companies, we conducted a qualitative directed content analysis. We observed that the 2015 commercials focused on the ease of play, and DFS players’ ability to win money; whereas the 2016 commercials placed a greater emphasis on intrinsic themes. The implications of this study are meaningful because they suggest that as the regulatory framework surrounding DFS in the United States has become more certain, the major DFS companies have made a change in their advertising messaging while not fundamentally altering their most played products.
Why did the equity home bias fall during the financial panic of 2008

Investors tend to put most of their wealth in local stocks; theories of portfolio choice and uncertainty aversion jointly predict that this home bias should increase during a financial crisis. Yet, using a sample of 45 countries, I document that the equity home bias fell during the financial panic of 2008. Exploiting bilateral stock holdings, I find that investors actively increased their home bias, but large valuation changes subsumed these trades. Across countries, the change in home bias is consistent with partial portfolio rebalancing and increased information asymmetries during the crisis.
Subcellular Trafficking of the Papillomavirus Genome during Initial Infection: The Remarkable Abilities of Minor Capsid Protein L2

Since 2012, our understanding of human papillomavirus (HPV) subcellular trafficking has undergone a drastic paradigm shift. Work from multiple laboratories has revealed that HPV has evolved a unique means to deliver its viral genome (vDNA) to the cell nucleus, relying on myriad host cell proteins and processes. The major breakthrough finding from these recent endeavors has been the realization of L2-dependent utilization of cellular sorting factors for the retrograde transport of vDNA away from degradative endo/lysosomal compartments to the Golgi, prior to mitosis-dependent nuclear accumulation of L2/vDNA. An overview of current models of HPV entry, subcellular trafficking, and the role of L2 during initial infection is provided below, highlighting unresolved questions and gaps in knowledge.
Predicting Response to Treatment in a Tier 2 Supplemental Vocabulary Intervention.

Purpose To effectively implement a response to intervention approach, there is a need for timely and specific information about student learning in response to treatment to ensure that treatment de...
A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease

The health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination. We performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden. CalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PM2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs. This study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease.
Multiple injections per injection episode: High-risk injection practice among people who injected pills during the 2015 HIV outbreak in Indiana

Abstract Background Misuse of prescription opioid analgesics (POA) has increased dramatically in the US, particularly in non-urban areas. We examined injection practices among persons who inject POA in a rural area that experienced a large HIV outbreak in 2015. Methods Between August-September 2015, 25 persons who injected drugs within the past 12 months were recruited in Scott County, Indiana for a qualitative study. Data from in-depth, semi-structured interviews were analyzed. Results All 25 participants were non-Hispanic white and the median age was 33 years (range: 19–57). All had ever injected extended-release oxymorphone (Opana ® ER) and most (n=20) described preparing Opana ® ER for multiple injections per injection episode (MIPIE). MIPIE comprised 2–4 injections during an injection episode resulting from needing >1mL water to prepare Opana ® ER solution using 1mL syringes and the frequent use of "rinse shots." MIPIE occurred up to 10 times/day (totaling 35 injections/day), often in the context of sharing drug and injection equipment. Conclusions We describe a high-risk injection practice that may have contributed to the rapid spread of HIV in this community. Efforts to prevent bloodborne infections among people who inject POA need to assess for MIPIE so that provision of sterile injection equipment and safer injection education addresses the MIPIE risk environment.
Designer Spatial Control of Interactions in Ultracold Gases.

Designer optical control of interactions in ultracold atomic gases has wide applications, from creating new quantum phases to modeling the physics of black holes. We demonstrate wide tunability and spatial control of interactions in a two-component cloud of $^{6}\mathrm{Li}$ fermions, using electromagnetically induced transparency. With two control fields detuned $\ensuremath{\simeq}1.5\text{ }\text{ }\mathrm{THz}$ from atomic resonance, megahertz changes in the frequency of one optical beam tune the measured scattering length over the full range achieved by magnetic control, with negligible (${10}^{\ensuremath{-}6}$) effect on the net optical confining potential. A 1D ``sandwich'' of resonantly and weakly interacting regions is imprinted on the trapped cloud and broadly manipulated with sub-MHz frequency changes. All of the data are in excellent agreement with our continuum-dressed state theoretical model of optical control, which includes both the spatial and momentum dependence of the scattering amplitude.
Analysis of Global and Site-Specific Radiation Damage in Cryo-EM.

Micro-crystal electron diffraction (MicroED) combines the efficiency of electron scattering with diffraction to allow structure determination from nano-sized crystalline samples in cryoelectron microscopy (cryo-EM). It has been used to solve structures of a diverse set of biomolecules and materials, in some cases to sub-atomic resolution. However, little is known about the damaging effects of the electron beam on samples during such measurements. We assess global and site-specific damage from electron radiation on nanocrystals of proteinase K and of a prion hepta-peptide and find that the dynamics of electron-induced damage follow well-established trends observed in X-ray crystallography. Metal ions are perturbed, disulfide bonds are broken, and acidic side chains are decarboxylated while the diffracted intensities decay exponentially with increasing exposure. A better understanding of radiation damage in MicroED improves our assessment and processing of all types of cryo-EM data.
Investigation of model stacking for drug sensitivity prediction

A significant problem in precision medicine is the prediction of drug sensitivity for individual cancer cell lines. Predictive models such as Random Forests have shown promising performance while predicting from individual genomic features such as gene expressions. However, accessibility of various other forms of data types including information on multiple tested drugs necessitates the examination of designing predictive models incorporating the various data types. We explore the predictive performance of model stacking and the effect of stacking on the predictive bias and squared error. In addition we discuss the analytical underpinnings supporting the advantages of stacking in reducing squared error and inherent bias of random forests in prediction of outliers. The framework is tested on a setup including gene expression, drug target, physical properties and drug response information for a set of drugs and cell lines. The performance of individual and stacked models are compared. We note that stacking models built on two heterogeneous datasets provide superior performance to stacking different models built on the same dataset. It is also noted that stacking provides a noticeable reduction in the bias of our predictors when the dominant eigenvalue of the principle axis of variation in the residuals is significantly higher than the remaining eigenvalues.
Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time Series

This article proposes a Bayesian nonparametric method for forecasting, imputation, and clustering in sparsely observed, multivariate time series data. The method is appropriate for jointly modeling hundreds of time series with widely varying, non-stationary dynamics. Given a collection of $N$ time series, the Bayesian model first partitions them into independent clusters using a Chinese restaurant process prior. Within a cluster, all time series are modeled jointly using a novel "temporally-reweighted" extension of the Chinese restaurant process mixture. Markov chain Monte Carlo techniques are used to obtain samples from the posterior distribution, which are then used to form predictive inferences. We apply the technique to challenging forecasting and imputation tasks using seasonal flu data from the US Center for Disease Control and Prevention, demonstrating superior forecasting accuracy and competitive imputation accuracy as compared to multiple widely used baselines. We further show that the model discovers interpretable clusters in datasets with hundreds of time series, using macroeconomic data from the Gapminder Foundation.
A Critique of Life Cycle Assessment; Where Are the People?

Abstract In this article, we provide a framework and examples to illustrate how human behavior can disrupt the expected environmental outcomes suggested by Life Cycle Assessment (LCA). The biggest problems are when LCA results are scaled up to make claims about possible future outcomes within a narrowly crafted scenario that ignores real human behavior. There are however, many examples at smaller scales too, where (often) engineers using LCA appear to ignore the behavior of other engineers involved in the development scenario. We argue for the inclusion of more social science in the development of environmental LCA, and the use of a wider array of scenarios (grounded in real behaviors) to portray the possible future development of a product or service at large scale. Ultimately people, not products, need to be at the center of this discussion.
Statistical selection of biological models for genome-wide association analyses

Genome-wide association studies have discovered many biologically important associations of genes with phenotypes. Typically, genome-wide association analyses formally test the association of each genetic feature (SNP, CNV, etc) with the phenotype of interest and summarize the results with multiplicity-adjusted p-values. However, very small p-values only provide evidence against the null hypothesis of no association without indicating which biological model best explains the observed data. Correctly identifying a specific biological model may improve the scientific interpretation and can be used to more effectively select and design a follow-up validation study. Thus, statistical methodology to identify the correct biological model for a particular genotype-phenotype association can be very useful to investigators. Here, we propose a general statistical method to summarize how accurately each of five biological models (null, additive, dominant, recessive, co-dominant) represents the data observed for each variant in a GWAS study. We show that the new method stringently controls the false discovery rate and asymptotically selects the correct biological model. Simulations of two-stage discovery-validation studies show that the new method has these properties and that its validation power is similar to or exceeds that of simple methods that use the same statistical model for all SNPs. Example analyses of three data sets also highlight these advantages of the new method. An R package is freely available at www.stjuderesearch.org/site/depts/biostats/maew.
Quantum optics in Maxwell's fish eye lens with single atoms and photons

The imaging properties of a lens that may perfectly focus electromagnetic waves is investigated at the quantum level. The lens is shown to be diffraction limited, and its role in entangling operations based on dipole-dipole interactions is discussed.
Admissible Abstractions for Near-optimal Task and Motion Planning

We define an admissibility condition for abstractions expressed using angelic semantics and show that these conditions allow us to accelerate planning while preserving the ability to find the optimal motion plan. We then derive admissible abstractions for two motion planning domains with continuous state. We extract upper and lower bounds on the cost of concrete motion plans using local metric and topological properties of the problem domain. These bounds guide the search for a plan while maintaining performance guarantees. We show that abstraction can dramatically reduce the complexity of search relative to a direct motion planner. Using our abstractions, we find near-optimal motion plans in planning problems involving $10^{13}$ states without using a separate task planner.
Intervention strategies for preventing excessive gestational weight gain: systematic review and meta-analysis.

Background Interventions relevant to energy intake to prevent excessive gestational weight gain in pregnant overweight and obese women are important but scarce. This review synthesized healthy eating and physical activity strategies and their effects on excessive gestational weight gain prevention. Methods Twenty-three randomized controlled trials that included healthy eating and/or physical activity as an intervention in healthy pregnant overweight or obese adult women and gestational weight gain as a primary or secondary outcome were reviewed. Findings Heathy eating and/or physical activity (21 studies, n = 6,920 subjects) demonstrated 1.81 kg (95% CI: -3.47, -0.16) of gestational weight gain reduction favouring intervention. Healthy eating (-5.77 kg, 95% CI: -9.34, -2.21, p = 0.02) had a larger effect size than combined healthy eating/physical activity (-0.82 kg, 95% CI: -1.28, -0.36, p = 0.0005) in limiting gestational weight gain. Physical activity did not show a significant pooled effect. Healthy eating with prescribed daily calorie and macronutrient goals significantly limited gestational weight gain by 4.28 kg and 4.23 kg, respectively. Conclusion Healthy eating and/or physical activity are effective in gestational weight gain control. Healthy eating with calorie and macronutrient goals are especially effective in limiting excessive gestational weight gain among pregnant overweight and obese women.
Learning by Contributing: Gaining Competitive Advantage Through Contribution to Crowdsourced Public Goods

As the economy becomes more information based, firms are increasingly using crowdsourced public goods as inputs for innovation and production. Counterintuitively, some firms pay their employees to ...
Simultaneous Segmentation and Classification of Bone Surfaces from Ultrasound Using a Multi-feature Guided CNN

Various imaging artifacts, low signal-to-noise ratio, and bone surfaces appearing several millimeters in thickness have hindered the success of ultrasound (US) guided computer assisted orthopedic surgery procedures. In this work, a multi-feature guided convolutional neural network (CNN) architecture is proposed for simultaneous enhancement, segmentation, and classification of bone surfaces from US data. The proposed CNN consists of two main parts: a pre-enhancing net, that takes the concatenation of B-mode US scan and three filtered image features for the enhancement of bone surfaces, and a modified U-net with a classification layer. The proposed method was validated on 650 in vivo US scans collected using two US machines, by scanning knee, femur, distal radius and tibia bones. Validation, against expert annotation, achieved statistically significant improvements in segmentation of bone surfaces compared to state-of-the-art.
Sarcoidosis from Head to Toe: What the Radiologist Needs to Know

Sarcoidosis is a multisystem granulomatous disorder characterized by development of noncaseating granulomas in various organs. Although the etiology of this condition is unclear, environmental and genetic factors may be substantial in its pathogenesis. Clinical features are often nonspecific, and imaging is essential to diagnosis. Abnormalities may be seen on chest radiographs in more than 90% of patients with thoracic sarcoidosis. Symmetric hilar and mediastinal adenopathy and pulmonary micronodules in a perilymphatic distribution are characteristic features of sarcoidosis. Irreversible pulmonary fibrosis may be seen in 25% of patients with the disease. Although sarcoidosis commonly involves the lungs, it can affect virtually any organ in the body. Computed tomography (CT), magnetic resonance imaging, and positron emission tomography/CT are useful in the diagnosis of extrapulmonary sarcoidosis, but imaging features may overlap with those of other conditions. Familiarity with the spectrum of multimodality imaging findings of sarcoidosis can help to suggest the diagnosis and guide appropriate management. ©RSNA, 2018.
Low-Complexity Reconfigurable MIMO for Millimeter Wave Communications

The performance of millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems is limited by the sparse nature of propagation channels and the restricted number of radio frequency chains at transceivers. The introduction of reconfigurable antennas offers an additional degree of freedom on designing mmWave MIMO systems. This paper provides a theoretical framework for studying the mmWave MIMO with reconfigurable antennas. Based on the virtual channel model, we present an architecture of reconfigurable mmWave MIMO with beamspace hybrid analog–digital beamformers and reconfigurable antennas at both the transmitter and the receiver. We show that employing reconfigurable antennas can provide throughput gain for the mmWave MIMO. We derive the expression for the average throughput gain of using reconfigurable antennas in the system, and further derive the expression for the outage throughput gain for the scenarios where the channels are (quasi) static. Moreover, we propose a low-complexity algorithm for reconfiguration state selection and beam selection. Our numerical results verify the derived expressions for the throughput gains and demonstrate the near-optimal throughput performance of the proposed low-complexity algorithm.
Automatically Designing CNN Architectures for Medical Image Segmentation

Deep neural network architectures have traditionally been designed and explored with human expertise in a long-lasting trial-and-error process. This process requires huge amount of time, expertise, and resources. To address this tedious problem, we propose a novel algorithm to optimally find hyperparameters of a deep network architecture automatically. We specifically focus on designing neural architectures for medical image segmentation task. Our proposed method is based on a policy gradient reinforcement learning for which the reward function is assigned a segmentation evaluation utility (i.e., dice index). We show the efficacy of the proposed method with its low computational cost in comparison with the state-of-the-art medical image segmentation networks. We also present a new architecture design, a densely connected encoder-decoder CNN, as a strong baseline architecture to apply the proposed hyperparameter search algorithm. We apply the proposed algorithm to each layer of the baseline architectures. As an application, we train the proposed system on cine cardiac MR images from Automated Cardiac Diagnosis Challenge (ACDC) MICCAI 2017. Starting from a baseline segmentation architecture, the resulting network architecture obtains the state-of-the-art results in accuracy without performing any trial-and-error based architecture design approaches or close supervision of the hyperparameters changes.
Reliable determination of contact angle from the height and volume of sessile drops

Contact angle is an important parameter in characterizing the wetting properties of fluids. For this reason, accurate measurement of the contact angle at liquid-solid interfaces is of great importance in industrial and scientific applications. The most common method for measuring the contact angle is to obtain it directly from the profile of a sessile drop. Though convenient, this method suffers from certain inherent drawbacks. Here, we describe an alternative method that uses the height and volume of a sessile drop as constraints to construct its profile by numerical integration of two parametric differential equations. The integration yields, self consistently, the average value of the contact angle along the entire contact line as well as the footprint radius of the drop and its crown radius of curvature. As a test case, the new method is used to obtain the contact angle of pure water on two different substrates, Teflon and Lucite. For each substrate, four drops ranging in volume from 10. to 40 μ l are used. The computed contact angles are consistent across the four different drop sizes for each substrate and are in good agreement with the literature values.
Harvest Hope Food Bank Optimizes Its Promotional Strategy to Raise Donations Using Integer Programming

Harvest Hope Food Bank (HHFB), based in South Carolina, serves primarily donated food to people in need in 20 counties across the state. It distributed 28 million pounds of food and fed over two mi...
Evolution of threats in the global risk network

With a steadily growing population and rapid advancements in technology, the global economy is increasing in size and complexity. This growth exacerbates global vulnerabilities and may lead to unforeseen consequences such as global pandemics fueled by air travel, cyberspace attacks, and cascading failures caused by the weakest link in a supply chain. Hence, a quantitative understanding of the mechanisms driving global network vulnerabilities is urgently needed. Developing methods for efficiently monitoring evolution of the global economy is essential to such understanding. Each year the World Economic Forum publishes an authoritative report on the state of the global economy and identifies risks that are likely to be active, impactful or contagious. Using a Cascading Alternating Renewal Process approach to model the dynamics of the global risk network, we are able to answer critical questions regarding the evolution of this network. To fully trace the evolution of the network we analyze the asymptotic state of risks (risk levels which would be reached in the long term if the risks were left unabated) given a snapshot in time; this elucidates the various challenges faced by the world community at each point in time. We also investigate the influence exerted by each risk on others. Results presented here are obtained through either quantitative analysis or computational simulations.
Weaving Transnational Activist Networks: Balancing International and Bottom-up Capacity-building Strategies for Nonviolent Action in Latin America

Latin America has been a laboratory for innovative strategic nonviolent action to confront oppression, corruption, human rights violations, and authoritarianism. One of the most salient explanations for why some movements achieve greater scale and effectiveness in meeting their objectives is the skills of movement organizers in unifying the population, planning strategic moves, and maintaining nonviolent discipline. The training and education to improve these skills often requires resources, transnational networks, and information sharing from external actors to complement the contextual knowledge, local legitimacy, and embedded institutional networks of local insiders. This essay proposes a model for international support of nonviolent action training and education that avoids the pitfalls of imposed liberal peacebuilding and colonizing hierarchies that could undermine movement legitimacy and expose activists to greater scrutiny and repression. In order to illustrate how the model works in practice, the essay examines the case of the Regional Institute for the Study and Practice of Strategic Nonviolent Action in the Americas.
Electron-Impact Ionization of Atomic Nitrogen

New electron-impact ionization (EII) data are presented for neutral atomic nitrogen. The atom is treated as a 67-state system, incorporating Rydberg values up to n=20. State-specific cross sections...
Examining Racial and Ethnic Variations in Reasons for Leaving a Youth Gang

One underrepresented area of research within the developmental and life course framework is how criminal careers vary across racial and ethnic lines. Similarly, little is known about how the processes surrounding leaving a youth gang differ based on the experiences of racial and ethnic minorities. This manuscript will help fill this gap in both bodies of literature by examining differences in push and pull motivations for gang desistance across black, Hispanic, and white youth who reside in seven different cities across the USA. The mixed-method analysis relies on grounded theory techniques to identify themes in the qualitative interviews as well as provides a quantitative comparison of gang desistance motivations. Black youth were least likely to report pulls associated with prosocial attachments and were also least likely to report being disillusioned with intragang relationships. Hispanic youth most commonly reported pulls associated with parental encouragement and experiencing official sanctions and pushes centered on direct and vicarious violent experiences. White youth most commonly reported pulls associated with having a significant other and pushes including feelings of disillusionment with intragang relationships. While there is evidence that street socialization and social isolation uniquely impact the gang desistance decisions of black gang youth, these differences might not be enough to justify race-specific intervention programs.
C 3 LES: Codes for Coded Computation that Leverage Stragglers

In distributed computing systems, it is well recognized that worker nodes that are slow (called stragglers) tend to dominate the overall job execution time. Coded computation utilizes concepts from erasure coding to mitigate the effect of stragglers by running “coded” copies of tasks comprising a job. Stragglers are typically treated as erasures in this process. While this is useful, there are issues with applying, e.g., MDS codes in a straightforward manner. Specifically, several applications such as matrix-vector products deal with sparse matrices. MDS codes typically require dense linear combinations of submatrices of the original matrix which destroy their inherent sparsity. This is problematic as it results in significantly higher processing times for computing the submatrix-vector products in coded computation. Furthermore, it also ignores partial computations at stragglers. In this work, we propose a fine-grained model that quantifies the level of non-trivial coding needed to obtain the benefits of coding in matrix-vector computation. Simultaneously, it allows us to leverage partial computations performed by the straggler nodes. For this model, we propose and evaluate several code designs and discuss their properties.
Beyond Representation of Women in I-O to Producing Gender-Inclusive Knowledge

Gardner, Ryan, and Snoeyink (2018) provided an excellent and much-needed analysis of the status of women in industrial and organizational (I-O) psychology. Although others have produced overall assessments of the status of women in psychology (Eagly & Riger, 2014; Kite et al., 2001), these are not sufficient to identify conditions within the subfields of psychology. As shown by statistics on the divisions of the American Psychological Association (http://www.apa.org/about/division/officers/services/profiles.aspx), the subfields differ greatly in their gender balance, with some being male dominated (e.g., experimental and cognitive science), others female dominated (e.g., developmental psychology), and still others representing women and men more equally (e.g., social and personality psychology). I-O psychology is among the more gender-balanced fields, with an increasing proportion of women over time. It would seem that I-O's gradual inclusion of more women should have changed aspects of research and discourse in this field. In this comment, we argue that these women have produced impressive changes.
Fragile superconductivity in the presence of weakly disordered charge density waves

When superconducting (SC) and charge-density-wave (CDW) orders compete, novel low-temperature behaviors can result. From an analysis of the Landau-Ginzburg-Wilson theory of competing orders, we demonstrate the generic occurrence of a ``fragile'' SC phase at low temperatures and high fields in the presence of weak disorder. Here, the SC order is largely concentrated in the vicinity of dilute dislocations in the CDW order, leading to transition temperatures and critical currents that are parametrically smaller than those characterizing the zero-field SC phase. This may provide the outline of an explanation of the recently discovered ``resilient'' superconducting phase at high fields in underdoped ${\mathrm{YBa}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{6+\ensuremath{\delta}}$.
Jesner v. Arab Bank

The exclusion of transnational human rights litigation from U.S. federal courts is, for most practical purposes, now complete. On April 24, 2018, the U.S. Supreme Court delivered a 5–4 ruling in Jesner v. Arab Bank, deciding that foreign corporations cannot be sued under the Alien Tort Statute (ATS).
Charging of a Single InAs QD with Electrically-Injected Holes using a Lateral Electric Field

We design and fabricate a 3-electrode device that applies 2-D electric fields to a single InAs QD. We observe electrical injection of holes into a QD due to the lateral electric field component.
Applying the Mahalanobis–Taguchi System to Vehicle Handling

The Mahalanobis–Taguchi system (MTS) is a diagnosis and forecasting method using multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and patterns that can be identified and analyzed with respect to a base or reference group. The MTS is of interest because of its reported accuracy in forecasting using small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This article presents the application of the MTS, its applicability in identifying a reduced set of useful variables in multidimensional systems, and a comparison of results with those obtained from a standard statistical approach to the problem.
IMPLEMENTING THE MOLST (MEDICAL ORDERS FOR LIFE-SUSTAINING TREATMENTS): CHALLENGES FACED BY NURSING HOME STAFF

This study examined how the Medical Orders for Life-sustaining Treatment (MOLST) is implemented in two nursing homes in Massachusetts; one had primarily long-term care residents and high hospice utilization, the other had low hospice utilization and a high proportion of post-acute care residents. Qualitative in-person interviews with 21 staff members who had a role implementing the MOLST explored their experiences using the form in their daily work routines. Staff at both nursing homes described benefits of the MOLST such as providing guidance for staff and family. Yet, they also gave detailed accounts of challenges they face in implementing the form. They reported problems with the form itself such as confusing language and conflicting categories as well as a set of procedural challenges that undermined the timely completion of the form. The nursing home with more post-acute care residents faced more challenges with transferability of the MOLST to and from hospitals.
On zigzag maps and the path category of an inverse semigroup

We study the path category of an inverse semigroup admitting unique maximal idempotents and give an abstract characterization of the inverse semigroups arising from zigzag maps on a left cancellative category. As applications we show that every inverse semigroup is Morita equivalent to an inverse semigroup of zigzag maps and hence the class of Cuntz–Krieger $$C^*$$-algebras of singly aligned categories include the tight $$C^*$$-algebras of all countable inverse semigroups, up to Morita equivalence.
Doubly robust difference-in-differences estimators

Abstract This article proposes doubly robust estimators for the average treatment effect on the treated (ATT) in difference-in-differences (DID) research designs. In contrast to alternative DID estimators, the proposed estimators are consistent if either (but not necessarily both) a propensity score or outcome regression working models are correctly specified. We also derive the semiparametric efficiency bound for the ATT in DID designs when either panel or repeated cross-section data are available, and show that our proposed estimators attain the semiparametric efficiency bound when the working models are correctly specified. Furthermore, we quantify the potential efficiency gains of having access to panel data instead of repeated cross-section data. Finally, by paying particular attention to the estimation method used to estimate the nuisance parameters, we show that one can sometimes construct doubly robust DID estimators for the ATT that are also doubly robust for inference. Simulation studies and an empirical application illustrate the desirable finite-sample performance of the proposed estimators. Open-source software for implementing the proposed policy evaluation tools is available.