cssi/SciSciGPT-SciSciNet huggingface dataset:
Computer simulation of crystal structures

It is impossible to calculate from first principles the details of crystal structures. However, it is possible to rely on information which is certain, namely on interatomic distances, and calculate the details of a crystal structure based on these. Individual distances between atoms can be predicted accurately if one considers the coordination numbers of anions and cations, the extended electrostatic valence rule, and the effects of shared edges between different coordination polyhedra. The predicted interatomic distances are used as observations in a distance least squares refinement in which the positional parameters and the cell edges are adjusted until the calculated interatomic distances correspond as closely as possible to the predicted distances. The topology of the simulated structure has to be known or assumed. Appropriate weighting can facilitate proper modelling. Applications include: a) solution of pseudosymmetric structures; b) preliminary refinement of trial structures; c) geometric refinement without X-ray intensities; d) comparison of hypothetical structures with observed polymorphs of the same compositions; e) simulation of temperature dependence of structures; f) simulation of pressure dependence; g) calculation of structures isomorphous to known structures; h) calculation of thermal ellipsoids; i) calculation of local environments deviating from the overall symmetry of a structure; j) testing of hypotheses about the behavior of structures at varying conditions.
Opioid use prior to knee arthroplasty in patients who catastrophize about their pain: preoperative data from a multisite randomized clinical trial

Background Opioid use rates prior to knee arthroplasty (KA) among people who catastrophize about their pain are unknown. We determined prevalence of opioid use and compared patterns of preoperative opioid use and oral morphine equivalent (OME), a measure of daily opioid dose, across varied geographic sites. We also determined which baseline variables were associated with opioid use and OME. Patients and methods Preoperative opioid use data described type of opioid, dosage, and frequency among 397 patients scheduled for KA. Demographic, knee-related pain, and psychological distress dimensions were examined to identify variables associated with opioid use and opioid dose (OME). Opioid use prevalence and OME were compared across the four sites. A three-level censored regression determined variables associated with opioid use and OME. Results The overall opioid use prevalence was 31.7% (95% confidence interval [CI] = 27.0, 36.3) and varied across sites from 15.9% (95% CI = 9.0, 22.8) to 51.2% (95% CI = 40.5, 61.9). After adjustment, patients using opioids were more likely to be younger, African American, and have higher self-efficacy and comorbidity scores (P < 0.05). The only variable independently associated with OME was lower depressive symptoms (P < 0.05). Conclusion People who catastrophized prior to KA did not demonstrate increased preoperative opioid use based on current evidence, but variation in the prevalence of opioid use across study sites was substantial. Variables associated with opioid use were non-modifiable demographic and comorbidity variables.
Cost Functions for Robot Motion Style

We focus on autonomously generating robot motion for day to day physical tasks that is expressive of a certain style or emotion. Because we seek generalization across task instances and task types, we propose to capture style via cost functions that the robot can use to augment its nominal task cost and task constraints in a trajectory optimization process. We compare two approaches to representing such cost functions: a weighted linear combination of hand-designed features, and a neural network parameterization operating on raw trajectory input. For each cost type, we learn weights for each style from user feedback. We contrast these approaches to a nominal motion across different tasks and for different styles in a user study, and find that they both perform on par with each other, and significantly outperform the baseline. Each approach has its advantages: featurized costs require learning fewer parameters and can perform better on some styles, but neural network representations do not require expert knowledge to design features and could even learn more complex, nuanced costs than an expert can easily design.
Agro-Climate Projections for a Warming Alaska

AbstractClimate warming is expected to disproportionately affect crop yields in the southern United States due to excessive heat stress, while presenting new farming opportunities through a longer ...
A Proximal Zeroth-Order Algorithm for Nonconvex Nonsmooth Problems

In this paper, we focus on solving an important class of nonconvex optimization problems which includes many problems for example signal processing over a networked multi-agent system and distributed learning over networks. Motivated by many applications in which the local objective function is the sum of smooth but possibly nonconvex part, and non-smooth but convex part subject to a linear equality constraint, this paper proposes a proximal zeroth-order primal dual algorithm (PZO-PDA) that accounts for the information structure of the problem. This algorithm only utilize the zeroth-order information (i.e., the functional values) of smooth functions, yet the flexibility is achieved for applications that only noisy information of the objective function is accessible, where classical methods cannot be applied. We prove convergence and rate of convergence for PZO-PDA. Numerical experiments are provided to validate the theoretical results.
Chilled Water VAV System Optimization and Modeling Using Artificial Neural Networks

in 2016, It was estimated that about 40% of total U.S. energy consumption was consumed by the residential and commercial sectors. According to EIA, in 2009, the energy consumption in U.S. homes was 48% which was down from 58% in 1993 Residential Energy Consumption Survey (RECS). The development of building energy savings methods and models becomes apparently more necessary for a sustainable future. The cooling coil is an essential component of HVAC systems. The accurate prediction of a cooling coil performance is important in many energy solution applications. This paper discusses the modeling methodologies of a chilled water cooling system using artificial neural networks. The objective of this research paper is to properly develop the model to predict the cooling coil performance accurately. This study utilized data from an existing building located in North Carolina, USA. Data such as chilled water supply temperature, airflow rate, mixture and supply air temperatures and humidity ratios, etc., are collected over the course of three months for developing and testing the model. Multiple neural network structures are tested along with multiple input and output delays to determine the one yielding the optimal results. Moreover, an optimization technique is developed to select premier model that can predict results accurately validated by the actual data. The observations from this research validates the use of artificial neural network model as an accurate tool for predicting the performance of a chilled water air handling unit.
Go with the Flow: Compositional Abstractions for Concurrent Data Structures

Concurrent separation logics have helped to significantly simplify correctness proofs for concurrent data structures. However, a recurring problem in such proofs is that data structure abstractions that work well in the sequential setting are much harder to reason about in a concurrent setting due to complex sharing and overlays. To solve this problem, we propose a novel approach to abstracting regions in the heap by encoding the data structure invariant into a local condition on each individual node. This condition may depend on a quantity associated with the node that is computed as a fixpoint over the entire heap graph. We refer to this quantity as a \emph{flow}. Flows can encode both structural properties of the heap (e.g. the reachable nodes from the root form a tree) as well as data invariants (e.g. sortedness). We then introduce the notion of a \emph{flow interface}, which expresses the relies and guarantees that a heap region imposes on its context to maintain the local flow invariant with respect to the global heap. Our main technical result is that this notion leads to a new semantic model of separation logic. In this model, flow interfaces provide a general abstraction mechanism for describing complex data structures. This abstraction mechanism admits proof rules that generalize over a wide variety of data structures. To demonstrate the versatility of our approach, we show how to extend the logic RGSep with flow interfaces. We have used this new logic to prove linearizability and memory safety of nontrivial concurrent data structures. In particular, we obtain parametric linearizability proofs for concurrent dictionary algorithms that abstract from the details of the underlying data structure representation. These proofs cannot be easily expressed using the abstraction mechanisms provided by existing separation logics.
A proof of the Krylov–Safonov theorem without localization

AbstractThe Krylov–Safonov theorem says that solutions to non-divergence uniformly elliptic equations with rough coefficients are Holder continuous. The proof combines a basic measure estimate with...
Video killed the writing assignment

We move pretty fast in the introductory astronomy class at Albion College (Albion, MI)—13.7 billion years of astronomy in about 15 weeks (one semester). Thus, it is virtually impossible to talk about all of the really interesting things that are happening in our solar system, our galaxy, and the universe, or about the really cool people and instruments that make our observations possible. This may or may not be a problem because students take this course for different reasons—to satisfy a graduation requirement, because it fits in their schedule, and/or because they are interested in astronomy in general.
Walled Cities and Urban Density in China

Throughout the imperial era, defensive walls surrounded Chinese cities. Although most city walls have vanished, the cities have survived. We analyze a sample of nearly 300 prefectural-level cities in China, among which about half historically had city walls. We document that cities that had walls in late imperial China have higher population and employment density today, despite the fact that their walls have long gone. Using data from various sources, we test several possible explanations of this fact, including (1) walled cities have a well-defined historical core that helps hold economic activity close to the city center today; (2) walled cities today tend to have different industry compositions that are less conducive to decentralization; (3) walled cities are situated in regions where the local geographies make it less desirable to build out; (4) walled cities have more compact shapes that facilitate high density development; and (5) walled cities are located in regions where rural land is more valuable today and discourages urban sprawl. We find that historically walled cities still have higher density after taking into account all of these factors, which we interpret as evidence of economic persistence.
On the Volume of Redistribution: Across Income Levels and Across Groups

The optimal income taxation literature focuses on the tradeoff between the equity gains of higher progressivity versus its greater incentive costs at the individual level. This paper highlights a neglected aspect of redistribution—greater progressivity requires a higher volume of gross redistributive flows, across income levels. If these flows are costly to manage, administratively, or politically, then progressivity will be lower. Moreover, if redistribution across income levels implies redistribution across sociopolitically salient groups because of the way in which these groups line up relative to the income distribution, this can be an added cost in the objective function and progressivity is further disadvantaged. The paper develops a simple framework in which these questions can be addressed. Among the many interesting results is that when the capacity for the volume of redistributive flows, across income levels or across sociopolitical groups, is reached, an increase in market inequality can lead to a fall in progressivity in the tax-transfer regime without any change in the government’s preferences for equity. A focus on the volume of redistribution thus opens up an important set of theoretical and empirical questions for analysis and for policy.
Collective ethnic-racial identity and health outcomes among African American youth: Examination of promotive and protective effects.

Objectives Racial discrimination is associated with numerous negative health outcomes, including increased risk for depression and anxiety symptoms and substance use. Positive affect toward of one's ethnic or racial group (i.e., ethnic-racial identity affirmation) has been shown to buffer the negative effects of racial discrimination on health outcomes. The extent to which one believes his or her group is valued by others (i.e., positive collective ethnic-racial identity) has also been proposed to be protective. However, to date a limited body of research has examined the moderating effect of collective ethnic-racial identity on health, and among available studies, findings are mixed. Method African American youth (N = 612; 58.2% female, M grade = 8) completed measures on experiences of discrimination, mood symptoms, substance use, ethnic-racial identity affirmation, and collective ethnic-racial identity (assessed using the Collective Self-Esteem Scale). Results Controlling for demographic variables and affirmation, a significant main effect was found for collective ethnic-racial identity, such that believing that others viewed your group positively was associated with better health outcomes among African American youth. However, collective ethnic-racial identity was not found to buffer the effects of discrimination on health outcomes. Conclusions These findings highlight the importance of examining collective ethnic-racial identity and the promotive effect it can have on health outcomes for African Americans. More research is needed to better understand if there are health outcomes in which collective ethnic-racial identity may also mitigate risk as a consequence of racial discrimination. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Transmission mode is associated with environment type and taxa across bacteria-eukaryote symbioses: a systematic review and meta-analysis

Symbiotic associations between bacteria and eukaryotes exhibit a range of transmission strategies. The rates and distributions of transmission modes have not been thoroughly investigated across associations, despite their consequences on symbiont and host evolution. To address this empirically, I compiled data from the literature on bacteria-multicellular eukaryote associations for which transmission mode data was available. Of the total 528 analyzed symbioses, 21.2% were strictly horizontally transmitted, 36.0% exhibited some form of mixed mode transmission and 42.8% were strictly vertically transmitted. Controlling for phylogenetically independent symbiosis events revealed modes were approximately equally distributed among the 113 independent associations, at 32.1%+/-0.57% horizontal, 37.8%+/-1.4% mixed mode and 31.1%+/-1.3% vertical transmission. Binning symbioses by environment revealed an abundance of vertical transmission on land and a lack of it in aquatic environments. The naturally occurring uneven distribution of taxa among environments prevented controlling for host/symbiont phylogeny. However, the results were robust over a large number of independently evolved associations, suggesting that many vertically transmitted bacteria are capable of mixed mode transmission and barriers exist that reduce the rate of horizontal transmission events. Thus, both the environment type and host/symbiont taxa influence symbiont transmission mode evolution.
Intracranial arachnoid cysts: Pediatric neurosurgery update.

Background With the greater worldwide availability of neuroimaging, more intracranial arachnoid cysts (IACs) are being found in all age groups. A subset of these lesions become symptomatic and requires neurosurgical management. The clinical presentations of IACs vary from asymptomatic to extremely symptomatic. Here, we reviewed the clinical presentation and treatment considerations for pediatric IACs. Case description Here, we presented three cases of IAC, focusing on different clinical and treatment considerations. Conclusion IACs can be challenging to manage. There is no Class I Evidence to guide how these should be treated. We suggest clinical decision-making framework as to how to treat IACs based on our understanding of the natural history, risks/benefits of treatments, and outcomes in the future, require better patient selection for the surgical management of IACs will be warranted.
Nudging persistence after failure through emergency reserves

Abstract Along the path of struggling to reach their personal and organizational long-term goals, the experience of an initial subgoal failure can lead individuals to feel less committed to their overall goal and even to give up entirely on reaching it. In one field study and four lab studies, we examine the ability of a cost-free nudge to decrease the detrimental impact of subgoal failure on goal attainment. More specifically, we demonstrate that framing goals with emergency reserves, a type of slack, can motivate individuals to persist after subgoal failures, leading to better performance on long-term goals, compared to objectively equivalent goals without slack. After failing to reach a subgoal, we found that individuals with goals framed with emergency reserves felt a greater sense of perceived progress, causing them to feel more committed to their goal, and thus increasing their likelihood of persisting at their goals.
White Lies

In this paper we distinguish between two types of white lies: those that help others at the expense of the person telling the lie, which we term altruistic white lies, and those that help both others and the liar, which we term Pareto white lies. We find that a large fraction of participants are reluctant to tell even a Pareto white lie, demonstrating a pure lie aversion independent of any social preferences for outcomes. In contrast, a nonnegligible fraction of participants are willing to tell an altruistic white lie that hurts them a bit but significantly helps others. Comparing white lies to those where lying increases the liar's payoff at the expense of another reveals important insights into the interaction of incentives, lying aversion, and preferences for payoff distributions. Finally, in line with previous findings, women are less likely to lie when it is costly to the other side. Interestingly though, we find that women are more likely to tell an altruistic lie. This paper was accepted by Teck Ho, decision analysis.
Approximable Sets

Much structural work on NP-complete sets has exploited SAT?s d-self-reducibility. In this paper, we exploit the additional fact that SAT is a d-cylinder to show that NP-complete sets are p-superterse unless P = NP. In fact, every set that is NP-hard under polynomial-time no(1)-tt reductions is p-superterse unless P = NP. In particular, no p-selective set is NP-hard under polynomial-time no(1)-tt reductions unless P = NP. In addition, no easily countable set is NP-hard under Turing reductions unless P = NP. Self-reducibility does not seem to suffice far our main result: in a relativized world, we construct a d-self-reducible set in NP ? P that is polynomial-time 2-tt reducible to a p-selective set.
3D simulation of a viscous flow past a compliant model of arteriovenous-graft annastomosis

Abstract Hemodialysis is a common treatment for end-stage renal-disease patients to manage their renal failure while awaiting kidney transplant. Arteriovenous graft (AVG) is a major vascular access for hemodialysis but often fails due to the thrombosis near the vein-graft anastomosis. Almost all of the existing computational studies involving AVG assume that the vein and graft are rigid. As a first step to include vein/graft flexibility, we consider an ideal vein-AVG anastomosis model and apply the lattice Boltzmann-immersed boundary (LB-IB) framework for fluid-structure-interaction. The framework is extended to the case of non-uniform Lagrangian mesh for complex structure. After verification and validation of the numerical method and its implementation, many simulations are performed to simulate a viscous incompressible flow past the anastomosis model under pulsatile flow condition using various levels of vein elasticity. Our simulation results indicate that vein compliance may lessen flow disturbance and a more compliant vein experiences less wall shear stress (WSS).
Two new functions in the WormBase Enrichment Suite

Genome-wide experiments routinely generate large amounts of data that can be hard to interpret biologically. A common approach to interpreting these results is to employ enrichment analyses of controlled languages, known as ontologies, that describe various biological parameters such as gene molecular or biological function. In C. elegans, three distinct ontologies, the Gene Ontology (GO), Anatomy Ontology (AO), and the Worm Phenotype Ontology (WPO) are used to annotate gene function, expression and phenotype, respectively (Ashburner et al. 2000; Lee and Sternberg, 2003; Schindelman et al. 2011). Previously, we developed software to test datasets for enrichment of anatomical terms, called the Tissue Enrichment Analysis (TEA) tool (Angeles-Albores and Sternberg, 2016). Using the same hypergeometric statistical method, we extend enrichment testing to include WPO and GO, offering a unified approach to enrichment testing in C. elegans. The WormBase Enrichment Suite can be accessed via a user-friendly interface at http://www.wormbase.org/tools/enrichment/tea/tea.cgi. To validate the tools, we analyzed a previously published extracellular vesicle (EV)-releasing neuron (EVN) signature gene set derived from dissociated ciliated EV neurons (Wang et al. 2015) using WormBase Enrichment Suite based on the WS262 WormBase release. TEA correctly identified the CEM, hook sensillum and IL2 neuron as enriched tissues. The top phenotype associated with the EVN signature was chemosensory behavior. Gene Ontology enrichment analysis showed that cell projection and cell body were the most enriched cellular components in this gene set, followed by the biological processes neuropeptide signaling pathway and vesicle localization further down. The tutorial script used to generate the figure above can be viewed at: https://github.com/dangeles/TissueEnrichmentAnalysis/blob/master/tutorial/Tutorial.ipynb The addition of Gene Enrichment Analysis (GEA) and Phenotype Enrichment Analysis (PEA) to WormBase marks an important step towards a unified set of analyses that can help researchers to understand genomic datasets. These enrichment analyses will allow the community to fully benefit from the data curation ongoing at WormBase.
Gradient-induced droplet motion over soft solids

Fluid droplets can be induced to move over rigid or flexible surfaces under external or body forces. We describe the effect of variations in material properties of a flexible substrate as a mechanism for motion. In this paper, we consider a droplet placed on a substrate with either a stiffness or surface energy gradient, and consider its potential for motion via coupling to elastic deformations of the substrate. In order to clarify the role of contact angles and to obtain a tractable model, we consider a two-dimensional droplet. The gradients in substrate material properties give rise to asymmetric solid deformation and to unequal contact angles, thereby producing a force on the droplet. We then use a dynamic viscoelastic model to predict the resulting dynamics of droplets. Numerical results quantifying the effect of the gradients establish that it is more feasible to induce droplet motion with a gradient in surface energy. The results show that the magnitude of elastic modulus gradient needed to induce droplet motion exceeds experimentally feasible limits in the production of soft solids and is therefore unlikely as a passive mechanism for cell motion. In both cases, of surface energy or elastic modulus, the threshold to initiate motion is achieved at lower mean values of the material properties.
OpenHealth: Open-Source Platform for Wearable Health Monitoring

Editor’s note: This article presents an open-source platform for wearable health monitoring. It aims to design a standard set of hardware/software and wearable devices that can enable autonomous collection of clinically relevant data. It provides reference implementations of human activity and gesture recognition applications within this platform. –Jana, Doppa, Washington State University
Building peace through systemic compassion

More than an individual emotion experienced by conflict resolution practitioners, compassion constitutes a primary norm of the field of peacebuilding. Three domains of peacebuilding practice are showcased: first, the human rights agenda of the United Nations, second, the practices of everyday peace, and third, the strategies among professionals of interactive conflict resolution. Motivated by the compassion‐related programs in these domains, we propose that peacebuilders develop strategies that are intended to foster compassion among the conflict parties. The notion of systemic compassion is introduced and illustrated with examples within current practice.
Examining spillover effect of US monetary policy to European stock markets: A Markov-Switching approach

espanolEste trabajo evalua el efecto rebalse de la politica monetaria de Estados Unidos en diecinueve economias europeas, utilizando modelos de cambios markovianos. Modelos univariados validan la presencia de dos regimenes, tanto para la politica monetaria de Estados Unidos como de los mercados accionarios. Encontramos una relacion positiva entre la tasa de Estados Unidos y los mercados accionarios de economias desarrolladas (con la excepcion de Finlandia, Suiza, Suecia y Reino Unido) y mercados accionarios de paises en desarrollo (excepto por Eslovenia y Ucrania). A su vez, la naturaleza de este efecto varia en periodos de crisis. El trabajo tambien compara el efecto rebalse entre economias asiaticas y europeas, demostrando que los efectos son distintos entre mercados. Sin embargo, la influencia de la tasa de interes de Estados Unidos es mayor en mercados desarrollados. EnglishThis study empirically examines the spillover effect from US monetary policy to nineteen European economies using Markov-switching models. The results of the univariate Markov-switching models validate the presence of two distinct regimes for both US monetary policy and the stock markets. We find mixed results when applying the multivariate Markov-switching models. The results report a positive relationship between the US interest rate and developed stock markets except for the Finish, Swiss, Swedish and UK stock markets whereas our findings confirm a positive relationship with the developing stock markets except for the Slovenian and Ukraine stock markets. Importantly, the nature of this effect varies during the economic crisis period. This study also compares the spillover effect between Asian and European stock markets and concludes that the effect of US monetary policy varies from market to market, however, changes in US monetary policy have greater effects on developed markets.
Two resolutions of the margin loan pricing puzzle

Abstract This paper supplies two possible resolutions of Fortune’s (2000) margin-loan pricing puzzle. Fortune (2000) noted that the margin loan interest rates charged by stock brokers are very high in relation to the actual (low) credit risk and the cost of funds. If we live in the Black–Scholes world, the brokers are presumably making arbitrage profits by shorting dynamically precise amounts of their clients’ portfolios. First, we extend Fortune’s (2000) application of Merton’s (1974) no-arbitrage approach to allow for brokers that can only revise their hedges finitely many times during the term of the loan. We show that extremely small differences in the revision frequency can easily explain the observed variation in margin loan pricing. In fact, four additional revisions per three-day period serve to explain all of the currently observed heterogeneity. Second, we study monopolistic (or oligopolistic) margin loan pricing by brokers whose clients are continuous-time Kelly gamblers. The broker solves a general stochastic control problem that yields simple and pleasant formulas for the optimal interest rate and the net interest margin. If the author owned a brokerage, he would charge an interest rate of ( r + ν ) / 2 − σ 2 / 4 , where r is the cost of funds, ν is the compound-annual growth rate of the S&P 500 index, and σ is the volatility.
An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search

Globally normalized neural sequence models are considered superior to their locally normalized equivalents because they may ameliorate the effects of label bias. However, when considering high-capacity neural parametrizations that condition on the whole input sequence, both model classes are theoretically equivalent in terms of the distributions they are capable of representing. Thus, the practical advantage of global normalization in the context of modern neural methods remains unclear. In this paper, we attempt to shed light on this problem through an empirical study. We extend an approach for search-aware training via a continuous relaxation of beam search (Goyal et al., 2017b) in order to enable training of globally normalized recurrent sequence models through simple backpropagation. We then use this technique to conduct an empirical study of the interaction between global normalization, high-capacity encoders, and search-aware optimization. We observe that in the context of inexact search, globally normalized neural models are still more effective than their locally normalized counterparts. Further, since our training approach is sensitive to warm-starting with pre-trained models, we also propose a novel initialization strategy based on self-normalization for pre-training globally normalized models. We perform analysis of our approach on two tasks: CCG supertagging and Machine Translation, and demonstrate the importance of global normalization under different conditions while using search-aware training.
A comparison of hyperelastic constitutive models applicable to Shear Wave Elastography (SWE) data in tissue-mimicking materials

Shear wave elastography (SWE) techniques have received substantial attention in recent years. Strong experimental data in SWE suggest that shear wave speed changes significantly due to the known acoustoelastic effect (AE). This presents both challenges and opportunities toward the in vivo characterization of biological soft tissues. In this work, under the framework of continuum mechanics, we model a tissue-mimicking material as a homogeneous, isotropic, incompressible, hyperelastic material. Our primary objective is to quantitatively and qualitatively compare experimentally measured acoustoelastic data with model-predicted outcomes using multiple strain energy functions. Our analysis indicated that the classic neo-Hookean and Mooney-Rivlin models are inadequate for modeling the AE in tissue-mimicking materials. However, a subclass of strain energy functions containing both high-order/exponential term(s) and second-order invariant dependence showed good agreement with experimental data. Based on data investigated, we also found that discrepancies may exist between parameters inversely estimated from uniaxial compression, and SWE data though Mooney plots were consistent between the uniaxial compression and AE results. Overall, our findings may improve our understanding of the clinical SWE results.
Fault Detection Effectiveness of Metamorphic Relations Developed for Testing Supervised Classifiers

In machine learning, supervised classifiers are used to obtain predictions for unlabeled data by inferring prediction functions using labeled data. Supervised classifiers are widely applied in domains such as computational biology, computational physics and healthcare to make critical decisions. However, it is often hard to test supervised classifiers since the expected answers are unknown. This is commonly known as the oracle problem and metamorphic testing (MT) has been used to test such programs. In MT, metamorphic relations (MRs) are developed from intrinsic characteristics of the software under test (SUT). These MRs are used to generate test data and to verify the correctness of the test results without the presence of a test oracle. Effectiveness of MT heavily depends on the MRs used for testing. In this paper we have conducted an extensive empirical study to evaluate the fault detection effectiveness of MRs that have been used in multiple previous studies to test supervised classifiers. Our study uses a total of 709 reachable mutants generated by multiple mutation engines and uses data sets with varying characteristics to test the SUT. Our results reveal that only 14.8% of these mutants are detected using the MRs and that the fault detection effectiveness of these MRs do not scale with the increased number of mutants when compared to what was reported in previous studies.
Insurance status impacts treatment for hepatocellular carcinoma.

Abstract Introduction and aim Previous studies have identified treatment disparities in the treatment of hepatocellular carcinoma (HCC) based on insurance status and provider. Recent studies have shown more Americans have healthcare insurance; therefore we aim to determine if treatment disparities based on insurance providers continue to exist. Materials and methods A retrospective database analysis using the NIS was performed between 2010 and 2013 including adult patients with a primary diagnosis of HCC determined by ICD-9 codes. Multivariable logistic regressions were performed to analyze differences in treatment, mortality, features of decompensation, and metastatic disease based on the patient's primary payer. Results This study included 62,368 patients. Medicare represented 44% of the total patients followed by private insurance (27%), Medicaid (19%), and other payers (10%). Patients with Medicare, Medicaid, and other payer were less likely to undergo liver transplantation [(OR 0.63, 95% CI 0.47–0.84), (OR 0.23, 95% CI 0.15–0.33), (OR 0.26, 95% CI 0.15–0.45)] and surgical resection [(OR 0.74, 95% CI 0.63–0.87), (OR 0.40, 95% CI 0.32–0.51), (OR 0.42, 95% CI 0.32–0.54)] than patients with private insurance. Medicaid patients were less likely to undergo ablation then patients with private insurance (OR 0.52, 95% CI 0.40–0.68). Patients with other forms of insurance were less likely to undergo transarterial chemoembolization (TACE) compared to private insurance (OR 0.64, 95% CI 0.43–0.96). Conclusion Insurance status impacts treatment for HCC. Patients with private insurance are more likely to undergo curative therapies of liver transplantation and surgical resection compared to patients with government funded insurance.
Does transvaginal ultrasound at 13-15 weeks improve anatomic survey completion rates in obese gravidas?

Objective: Obesity increases the difficulty of completing the fetal anatomic survey. This is of added concern in obese gravidas who are at higher risk of congenital fetal anomalies. We hypothesized...
Characterization of upregulated adhesion GPCRs in acute myeloid leukemia.

The role of adhesion G protein-coupled receptors (aGPCRs) in cancer has become increasingly evident in recent years. Yet, data supporting the contribution of this family of genes to hematological malignancies, particularly acute myeloid leukemia (AML) are limited. Here, we use publicly available genomic data to characterize the expression of the 33 aGPCRs in patients with AML and examine whether upregulation of these genes is associated with the clinical and molecular characteristics of patients. Upregulation in one or more of eight aGPCR genes (ADGRB1, ADGRC2, ADGRD1, ADGRE1, ADGRE2, ADGRE5, ADGRG1, and/or ADGRG3) was significantly associated with shorter overall survival (OS) (median OS: 11.8 vs 55.4 months; P
Measuring the Full Extent of Fiscal Losses and Gains

Current measures of fiscal impoverishment and gains are not consistent with the law of diminishing returns. This paper proposes new measures of fiscal impoverishment and gains that are consistent with the law of diminishing returns, based on a methodology that gives more significance to greater income gaps, and more importance to the experience of the poorest individuals within the fiscal system. The new indicators are decomposable and cover the incidence, intensity, and severity of fiscal impoverishment and gains. An empirical illustration using the 2014 household consumption data reveals that, overall, in Niger the fiscal system is improving the welfare of the population: only 33.2 percent of the population has become poorer due to the fiscal system, while the remaining 66.8 percent has become richer because of it. Moreover, the mean relative fiscal loss (0.014), is 11 percent lower than the mean relative fiscal gain (0.126).
Is It Actionable? An Evaluation of the Rapid PCR-Based Blood Culture Identification Panel on the Management of Gram-Positive and Gram-Negative Blood Stream Infections.

Background There is growing interest in the use of rapid blood culture identification (BCID) in antimicrobial stewardship programs (ASPs). Although many studies have looked at its clinical and economic utility, its comparative utility in gram-positive and gram-negative blood stream infections (BSIs) has not been as well characterized. Methods The study was a quasi-experimental retrospective study at the Mayo Clinic in Phoenix, Arizona. All adult patients with positive blood cultures before BCID implementation (June 2015 to December 2015) and after BCID implementation (June 2016 to December 2016) were included. The outcomes of interest included time to first appropriate antibiotic escalation, time to first appropriate antibiotic de-escalation, time to organism identification, length of stay, infectious diseases consultation, discharge disposition, and in-hospital mortality. Results In total, 203 patients were included in this study. There was a significant difference in the time to organism identification between the pre- and post-BCID cohorts (27.1 hours vs 3.3 hours, P < .0001). BCID did not significantly reduce the time to first appropriate antimicrobial escalation or de-escalation for either gram-positive BSIs (GP-BSIs) or gram-negative BSIs (GN-BSIs). Providers were more likely to escalate antimicrobial therapy in GP-BSIs after gram stain and more likely to de-escalate therapy in GN-BSIs after susceptibilities. Although there were no significant differences in changes in antimicrobial therapy for organism identification by BCID vs traditional methods, more than one-quarter of providers (28.1%) made changes after organism identification. There were no differences in hospital length of stay or in-hospital mortality comparing pre- vs post-BCID. Conclusions Although BCID significantly reduced the time to identification for both GP-BSIs and GN-BSIs, BCID did not reduce the time to first appropriate antimicrobial escalation and de-escalation.
Synthesis and characterization of Ba3Bi6.67Se13 and its filled variants Ba3Bi6PbSe13 and Ba3Bi6SnSe13

The three title compounds were synthesized at 710 °C and their structure type is isotypic to Sr4Bi6Se13 and β-K2Bi8Se13. The compounds crystallize in P21/m (Z = 2) with a = 17.2228(6) A, b = 4.2729(1) A, c = 18.4659(6) A, β = 90.720(0)° for Ba3Bi6.67Se13; a = 17.2427(4) A, b = 4.2736(1) A, c = 18.4560(4) A, β = 90.861(1)° for Ba3Bi6PbSe13; and a = 17.2498(5) A, b = 4.2912(1) A, c = 18.4590(5) A, and β = 90.679(1)° for Ba3Bi6SnSe13. The coordination environments of Bi/Pb/Sn are distorted Se octahedra, while the coordination spheres of Ba are bi- or tricapped trigonal prisms. Transport measurements indicate that Ba3Bi6.67Se13 and Ba3Bi6PbSe13 are semiconducting.
The D 2k R 4 Invariants of N = 8 Supergravity

The existence of a linearized SUSY invariant for N = 8 supergravity whose gravitational components are usually called R 4 was established long ago by on-shell superspace arguments. Superspace and string theory methods have also established analogous higher dimensional D 2k R 4 invariants. However, very little is known about the SUSY completions of these operators which involve other fields of the theory. In this paper we find the detailed component expansion of the linearized R 4 invariant starting from the corresponding superamplitude which generates all component matrix elements of the operator. It is then quite straightforward to extend results to the entire set of D 2k R 4 operators.
Venlafaxine stimulates PNN proteolysis and MMP-9-dependent enhancement of gamma power; relevance to antidepressant efficacy.

Drugs that target monoaminergic transmission represent a first-line treatment for major depression. Though a full understanding of the mechanisms that underlie antidepressant efficacy is lacking, evidence supports a role for enhanced excitatory transmission. This can occur through two non-mutually exclusive mechanisms. The first involves increased function of excitatory neurons through relatively direct mechanisms such as enhanced dendritic arborization. Another mechanism involves reduced inhibitory function, which occurs with the rapid antidepressant ketamine. Consistent with this, GABAergic interneuron-mediated cortical inhibition is linked to reduced gamma oscillatory power, a rhythm also diminished in depression. Remission of depressive symptoms correlates with restoration of gamma power. As a result of strong excitatory input, reliable GABA release, and fast firing, PV-expressing neurons (PV neurons) represent critical pacemakers for synchronous oscillations. PV neurons also represent the predominant GABAergic population enveloped by perineuronal nets (PNNs), lattice-like structures that localize glutamatergic input. Disruption of PNNs reduces PV excitability and enhances gamma activity. Studies suggest that monoamine reuptake inhibitors reduce integrity of the PNN. Mechanisms by which these inhibitors reduce PNN integrity, however, remain largely unexplored. A better understanding of these issues might encourage development of therapeutics that best up-regulate PNN-modulating proteases. We observe that the serotonin/norepinephrine reuptake inhibitor venlafaxine increases hippocampal matrix metalloproteinase (MMP)-9 levels as determined by ELISA and concomitantly reduces PNN integrity in murine hippocampus as determined by analysis of sections following their staining with a fluorescent PNN-binding lectin. Moreover, venlafaxine-treated mice (30 mg/kg/day) show an increase in carbachol-induced gamma power in ex vivo hippocampal slices as determined by local field potential recording and Matlab analyses. Studies with mice deficient in matrix metalloproteinase 9 (MMP-9), a protease linked to PNN disruption in other settings, suggest that MMP-9 contributes to venlafaxine-enhanced gamma power. In conclusion, our results support the possibility that MMP-9 activity contributes to antidepressant efficacy through effects on the PNN that may in turn enhance neuronal population dynamics involved in mood and/or memory. Cover Image for this issue: doi: 10.1111/jnc.14498.
Products of the gas-phase reaction of methyl tert-butyl ether with the OH radical in the presence of NOx

The products of the reaction of the hydroxyl (OH) radical with methyl tert-butyl ether (MTBE) in NOx-air systems were identified and measured by Fourier transform infrared absorption spectroscopy and gas chromatography. The products observed, and their yields, were as follows: t-butyl formate, 76 ± 7%; formaldehyde, 37%; methyl acetate, 17 ± 2%, and acetone, 2.1 ± 0.9%, where the stated error limits represent both random (two standard deviations) and estimated systematic uncertainties. These products account for ca. 95% of the MTBE carbon reacted. Infrared absorption bands which may be due to small amounts of organic nitrate formation were observed, but organic nitrate yields could not be quantified. These data allow a chemical mechanism for the reaction of MTBE with the OH radical in the presence of NOx to be formulated.
Where is the quantum critical point in the cuprate superconductors

Transport measurements in the hole-doped cuprates show a "strange metal" normal state with an electrical resistance which varies linearly with temperature. This strange metal phase is often identified with the quantum critical region of a zero temperature quantum critical point (QCP) at hole density x = x m , near optimal doping. A long-standing problem with this picture is that low temperature experiments within the superconducting phase have not shown convincing signatures of such an optimal doping QCP (except in some cuprates with small superconducting critical temperatures). I review theoretical work which proposes a simple resolution of this enigma. The crossovers in the normal state are argued to be controlled by a QCP at x m linked to the onset of spin density wave (SDW) order in a "large" Fermi surface metal, leading to small Fermi pockets for x < x m . A key effect is that the onset of superconductivity at low temperatures disrupts the simplest canonical quantum critical crossover phase diagram. In particular, the competition between superconductivity and SDW order shifts the actual QCP to a lower doping x s < x m in the underdoped regime, so that SDW order is only present for x < x s . I review the phase transitions and crossovers associated with the QCPs at x m and x s : the resulting phase diagram as a function of x, temperature, and applied magnetic field consistently explains a number of recent experiments.