cssi/SciSciGPT-SciSciNet huggingface dataset:
shinyheatmap: Ultra fast low memory heatmap web interface for big data genomics.

Background Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets, especially across single-cell sequencing studies. Visualizing such big data has posed technical challenges in biology, both in terms of available computational resources as well as programming acumen. Since heatmaps are used to depict high-dimensional numerical data as a colored grid of cells, efficiency and speed have often proven to be critical considerations in the process of successfully converting data into graphics. For example, rendering interactive heatmaps from large input datasets (e.g., 100k+ rows) has been computationally infeasible on both desktop computers and web browsers. In addition to memory requirements, programming skills and knowledge have frequently been barriers-to-entry for creating highly customizable heatmaps. Results We propose shinyheatmap: an advanced user-friendly heatmap software suite capable of efficiently creating highly customizable static and interactive biological heatmaps in a web browser. shinyheatmap is a low memory footprint program, making it particularly well-suited for the interactive visualization of extremely large datasets that cannot typically be computed in-memory due to size restrictions. Also, shinyheatmap features a built-in high performance web plug-in, fastheatmap, for rapidly plotting interactive heatmaps of datasets as large as 105—107 rows within seconds, effectively shattering previous performance benchmarks of heatmap rendering speed. Conclusions shinyheatmap is hosted online as a freely available web server with an intuitive graphical user interface: http://shinyheatmap.com. The methods are implemented in R, and are available as part of the shinyheatmap project at: https://github.com/Bohdan-Khomtchouk/shinyheatmap. Users can access fastheatmap directly from within the shinyheatmap web interface, and all source code has been made publicly available on Github: https://github.com/Bohdan-Khomtchouk/fastheatmap.
Next-generation HVAC: Prospects for and limitations of desiccant and membrane-based dehumidification and cooling

Abstract Recently, next-generation HVAC technologies have gained attention as potential alternatives to the conventional vapor-compression system (VCS) for dehumidification and cooling. Previous studies have primarily focused on analyzing a specific technology or its application to a particular climate. A comparison of these technologies is necessary to elucidate the reasons and conditions under which one technology might outperform the rest. In this study, we apply a uniform framework based on fundamental thermodynamic principles to assess and compare different HVAC technologies from an energy conversion standpoint. The thermodynamic least work of dehumidification and cooling is formally defined as a thermodynamic benchmark, while VCS performance is chosen as the industry benchmark against which other technologies, namely desiccant-based cooling system (DCS) and membrane-based cooling system (MCS), are compared. The effect of outdoor temperature and humidity on device performance is investigated, and key insights underlying the dehumidification and cooling process are elucidated. In spite of the great potential of DCS and MCS technologies, our results underscore the need for improved system-level design and integration if DCS or MCS are to compete with VCS. Our findings have significant implications for the design and operation of next-generation HVAC technologies and shed light on potential avenues to achieve higher efficiencies in dehumidification and cooling applications.
An Observational Diagnostic for Distinguishing between Clouds and Haze in Hot Exoplanet Atmospheres

Research Corporation for Science Advancement; Grinnell College's Harris Faculty Fellowship; NASA through STScI [GO-13665, GO-14792, 14793]; David and Lucile Packard Foundation; NASA Exoplanet Science Institute
Crossovers : female entrepreneurs who enter male sectors -- evidence from Ethiopia

Occupational sector selection is an important determinant of returns for female entrepreneurs. If sectors that are traditionally male owned could provide an opportunity to earn higher returns, then what factors could encourage women to cross over into these sectors or prevent them from doing so? To examine this question, this paper uses data from Ethiopia to compare the firm performance and characteristics of women in male-dominated sectors (crossovers) with women who are in female-concentrated sectors (noncrossovers). The findings show that female-owned enterprises in male-dominated sectors perform better on average than those in female-concentrated sectors, with firms achieving higher profits and having more employees. The descriptive results show that crossovers do not necessarily have more education or greater skills than noncrossovers. Rather, women’s relationships and networks, especially those provided through male relatives, and being opportunity-driven entrepreneurs appear to influence the likelihood of entering a more-profitable, male-dominated sector. The study explores the implications and challenges of encouraging female entrepreneurs to enter male-dominated sectors, in an effort to provide new insight into how the earning gap between male and female entrepreneurs can be closed.
A Novel Approach For Event-By-Event Early Gluon Fields

Abstract We report on efforts to construct an event generator that calculates the classical gluon field generated at early times in high energy nuclear collisions. Existing approaches utilize numerical solutions of the Yang-Mills equations after the collision. In contrast we employ the analytically known recursion relation in the forward light cone. The few lowest orders are expected to lead to reliable results for times of up to the inverse saturation scale, τ 0 ∼ 1 / Q s . In these proceedings we sketch some calculational details, and show some preliminary results.
Autonomic healing of low-velocity impact damage in fiber-reinforced composites

In this study autonomic self-healing of impact damage in composite materials is shown using a microencapsulated healing agent. The components for self-healing, urea‐formaldehyde microcapsules containing dicyclopentadiene (DCPD) liquid healing agent and paraffin wax microspheres containing 10 wt% Grubbs’ catalyst, have been successfully incorporated in a woven S2-glass-reinforced epoxy composite. Lowvelocity impact tests reveal that the self-healing composite panels are able to autonomically repair impact damage. Fluorescent labeling of damage combined with image processing shows that total crack length per imaged cross-section is reduced by 51% after self-healing. A testing protocol based on compression after impact reveals significant recovery of residual compressive strength (RCS) in self-healing panels. Self-healing panels show a higher threshold impact energy before RCS reduction, and as impact energy increases, RCS recovery decreases. Qualitative inspection shows that crack separation increases with increasing impact energy, indicating that self-healing performance depends on the ability to adequately fill damage volume.
Attitude and the Normativity of Law

Though legal positivism remains popular, HLA Hart’s version has fallen somewhat by the wayside. This is because, according to many, the central task of a theory of law is to explain the so-called ‘normativity of law’. Hart’s theory, it is thought, is not up to the task. Some have suggested modifying the theory accordingly. This paper argues that both Hart’s theory and the normativity of law have been misunderstood. First, a popular modification of Hart’s theory is considered and rejected. It stems from a misunderstanding of Hart and his project. Second, a new understanding of the mysterious but often-mentioned ‘normativity of law’ is presented. Once we have dispelled some misunderstandings of Hart’s view and clarified the sense in which law is supposed to be normative, we see that Hart’s view, unmodified, is well suited to the task of explaining law’s normativity.
Resetting the Yeast Epigenome with Human Nucleosomes.

Summary Humans and yeast are separated by a billion years of evolution, yet their conserved histones retain central roles in gene regulation. Here, we "reset" yeast to use core human nucleosomes in lieu of their own (a rare event taking 20 days), which initially only worked with variant H3.1. The cells adapt by acquiring suppressor mutations in cell-division genes or by acquiring certain aneuploid states. Converting five histone residues to their yeast counterparts restored robust growth. We reveal that humanized nucleosomes are positioned according to endogenous yeast DNA sequence and chromatin-remodeling network, as judged by a yeast-like nucleosome repeat length. However, human nucleosomes have higher DNA occupancy, globally reduce RNA content, and slow adaptation to new conditions by delaying chromatin remodeling. These humanized yeasts (including H3.3) pose fundamental new questions about how chromatin is linked to many cell processes and provide a platform to study histone variants via yeast epigenome reprogramming.
Fatiguing STDP: Learning from spike-timing codes in the presence of rate codes

Spiking neural networks (SNNs) could play a key role in unsupervised machine learning applications, by virtue of strengths related to learning from the fine temporal structure of event-based signals. However, some spike-timing-related strengths of SNNs are hindered by the sensitivity of spike-timing-dependent plasticity (STDP) rules to input spike rates, as fine temporal correlations may be obstructed by coarser correlations between firing rates. In this article, we propose a spike-timing-dependent learning rule that allows a neuron to learn from the temporally-coded information despite the presence of rate codes. Our long-term plasticity rule makes use of short-term synaptic fatigue dynamics. We show analytically that, in contrast to conventional STDP rules, our fatiguing STDP (FSTDP) helps learn the temporal code, and we derive the necessary conditions to optimize the learning process. We showcase the effectiveness of FSTDP in learning spike-timing correlations among processes of different rates in synthetic data. Finally, we use FSTDP to detect correlations in real-world weather data from the United States in an experimental realization of the algorithm that uses a neuro-morphic hardware platform comprising phase-change memristive devices. Taken together, our analyses and demonstrations suggest that FSTDP paves the way for the exploitation of the spike-based strengths of SNNs in real-world applications.
Anomalous Android Application Detection with Latent Semantic Indexing.

Android applications are widely used by millions of users to perform many different activities. However, many applications have been reported to do anomalous activities not matching with their expected behaviors such as reading of contact information, sending SMS message to premium numbers, and other consequences. The existing relevant approaches that identify these applications (malware detection technique) suffer from performance issues with high false positive and negative rate. This paper provides a concept of applying Latent Semantic Indexing (LSI) to find if a suspected application is relevant to malware application.
Histopathology of BCG and Thiotepa Treated Bladders

In an effort to characterize the pathophysiological differences between the modes of action of BCG and thiotepa in the treatment of superficial bladder cancer, normal female rats received weekly intravesical instillations of both agents. The animals were sacrificed and their bladders were examined pathologically to determine if there were histological differences between the cellular infiltrates found in the BCG and thiotepa treated bladders. Monomuclear cells, particularly T-cells, predominated in the BCG treated bladders whereas polymorphonucleated cells predominated in the thiotepa treated bladders suggesting that there may be an immune aspect to the former therapy. The presence of T-cells following BCG therapy suggests a T-cell mediated immune response.
Mechanism of Inhibition of Human Testicular Steroidogenesis by Oral Ketoconazole

To determine the antisteroidogenic effect of ketoconazole (KTZ) in the human testis, we measured the plasma Δ5-pregnenolone, Δ5-17α-hydroxypregnenolone, dehydroepiandrosterone (DHEA), progesterone, 17α-hydroxyprogesterone, androstenedione (A), and testosterone (T) concentrations in three men with previously untreated metastatic prostate cancer at various time intervals for 24 h before and 48 h after the administration of 200 mg oral KTZ every 8 h. The adrenal glands of these three patients were suppressed (as measured by the plasma cortisol levels) by the administration of 1.0 mg dexamethasone daily for 7 days before and during the study. After six doses of KTZ, bilateral orchiectomy was performed, and the intratesticular concentration of the aforementioned seven steroids and the intratesticular activities of the 17α-hydroxylase, 17,20-desmolase, and 17β-hydroxysteroid dehydrogehase enzymes in the Δ4-steroidogenic pathway were determined. These seven intratesticular steroids and three intratesticular enzy...
Histories and Trajectories of Socio-Ecological Landscapes in the Lesser Antilles: Implications of Colonial Period Zooarchaeological Research

The plantation era in the Caribbean was characterised by significant ecological degradation and change through the shift to sugar monoculture, and the introduction of exotic taxa to the island, leading to the extensive depletion of native flora and fauna. During European colonial rule in this region, marginalised and enslaved communities developed informal domestic economies such as artisanal fishing, small-scale animal husbandry and agriculture to survive within this oppressive structure. Zooarchaeology from this period offers insight into the variability of historical human eco-dynamics, and how these pasts impact modern social, economic and ecological systems. This study presents archaeological case studies from three plantation sites in the Lesser Antilles, from the islands of Martinique, Barbados and Dominica, to illustrate the potential contributions of historical archaeology to understanding long-term human–environment interaction, and explore the ecological consequences of colonialism in t...
Early Number Skills Gains and Mathematics Achievement: Intervening to Establish Successful Early Mathematics Trajectories.

Early number skills, comprised of both informal and formal skills, are associated with later mathematics achievement. Thus, the development of foundational early number skills is an important aspec...
The development and validation of EpiComet‐Chip, a modified high‐throughput comet assay for the assessment of DNA methylation status

DNA damage and alterations in global DNA methylation status are associated with multiple human diseases and are frequently correlated with clinically relevant information. Therefore, assessing DNA damage and epigenetic modifications, including DNA methylation, is critical for predicting human exposure risk of pharmacological and biological agents. We previously developed a higher-throughput platform for the single cell gel electrophoresis (comet) assay, CometChip, to assess DNA damage and genotoxic potential. Here, we utilized the methylation-dependent endonuclease, McrBC, to develop a modified alkaline comet assay, "EpiComet," which allows single platform evaluation of genotoxicity and global DNA methylation [5-methylcytosine (5-mC)] status of single-cell populations under user-defined conditions. Further, we leveraged the CometChip platform to create an EpiComet-Chip system capable of performing quantification across simultaneous exposure protocols to enable unprecedented speed and simplicity. This system detected global methylation alterations in response to exposures which included chemotherapeutic and environmental agents. Using EpiComet-Chip on 63 matched samples, we correctly identified single-sample hypermethylation (≥1.5-fold) at 87% (20/23), hypomethylation (≥1.25-fold) at 100% (9/9), with a 4% (2/54) false-negative rate (FNR), and 10% (4/40) false-positive rate (FPR). Using a more stringent threshold to define hypermethylation (≥1.75-fold) allowed us to correctly identify 94% of hypermethylation (17/18), but increased our FPR to 16% (7/45). The successful application of this novel technology will aid hazard identification and risk characterization of FDA-regulated products, while providing utility for investigating epigenetic modes of action of agents in target organs, as the assay is amenable to cultured cells or nucleated cells from any tissue. Environ. Mol. Mutagen. 58:508-521, 2017. © 2017 Wiley Periodicals, Inc.
Minimal Frames and Transparent Frames for Risk, Time, and Uncertainty

Behavior differs between transparent and nontransparent presentations of decisions, but “transparent presentation” has not been precisely defined. We formally define “transparent frames” for risk a...
Unified empirical likelihood ratio tests for functional concurrent linear models and the phase transition from sparse to dense functional data

Summary We consider the problem of testing functional constraints in a class of functional concurrent linear models where both the predictors and the response are functional data measured at discrete time points. We propose test procedures based on the empirical likelihood with bias-corrected estimating equations to conduct both pointwise and simultaneous inferences. The asymptotic distributions of the test statistics are derived under the null and local alternative hypotheses, where sparse and dense functional data are considered in a unified framework. We find a phase transition in the asymptotic null distributions and the orders of detectable alternatives from sparse to dense functional data. Specifically, the tests proposed can detect alternatives of √n-order when the number of repeated measurements per curve is of an order larger than nη0 with n being the number of curves. The transition points η0 for pointwise and simultaneous tests are different and both are smaller than the transition point in the estimation problem. Simulation studies and real data analyses are conducted to demonstrate the methods proposed.
A Comparison of Parallel Graph Processing Implementations

The rapidly growing number of large network analysis problems has led to the emergence of many parallel and distributed graph processing systems—one survey in 2014 identified over 80. Determining the best approach for a given problem is infeasible for most developers. We present an approach and associated software for analyzing the performance and scalability of parallel, open-source graph libraries. We demonstrate our approach on five graph processing packages: GraphMat, Graph500, Graph Algorithm Platform Benchmark Suite, GraphBIG, and PowerGraph using synthetic and real-world datasets. We examine previously overlooked aspects of parallel graph processing performance such as phases of execution and energy usage for three algorithms: breadth first search, single source shortest paths, and PageRank.
Putting pieces together: Combining FrameNet, VerbNet and WordNet for robust semantic parsing

This paper describes our work in integrating three different lexical resources: FrameNet, VerbNet, and WordNet, into a unified, richer knowledge-base, to the end of enabling more robust semantic parsing. The construction of each of these lexical resources has required many years of laborious human effort, and they all have their strengths and shortcomings. By linking them together, we build an improved resource in which (1) the coverage of FrameNet is extended, (2) the VerbNet lexicon is augmented with frame semantics, and (3) selectional restrictions are implemented using WordNet semantic classes. The synergistic exploitation of various lexical resources is crucial for many complex language processing applications, and we prove it once again effective in building a robust semantic parser.
Is Your Lawyer a Lemon? Incentives and Selection in the Public Provision of Criminal Defense

Governments in the U.S. must offer free legal services to low-income people accused of crimes. To provide these services, many jurisdictions rely on assigned counsel systems, where private attorney...
Anticipated pain as a predictor of discomfort with intrauterine device placement.

Background Intrauterine devices have been gaining popularity for the past 2 decades. Current data report that >10% of women who use contraception are using an intrauterine device. With Objectives The objective of this analysis was to estimate the association between anticipated pain with intrauterine device placement and experienced pain. We also assessed other factors associated with increased discomfort during intrauterine device placement. We hypothesized that patients with higher levels of anticipated pain would report a higher level of discomfort during placement. Study Design We performed a secondary analysis of the Contraceptive CHOICE Project. There were 9256 patients enrolled in Contraceptive CHOICE Project from the St. Louis region from 2007–2011; data for 1149 subjects who came for their first placement of either the original 52-mg levonorgestrel intrauterine system or the copper intrauterine device were analyzed in this study. Patients were asked to report their anticipated pain before intrauterine device placement and experienced pain during placement on a 10-point visual analog scale. We assessed the association of anticipated pain, patient demographics, reproductive characteristics, and intrauterine device type with experienced pain with intrauterine device placement. Results The mean age of Contraceptive CHOICE Project participants in this subanalysis was 26 years. Of these 1149 study subjects, 44% were black, and 53% were of low socioeconomic status. The median expected pain score was 5 for both the levonorgestrel intrauterine system and the copper intrauterine device; the median experienced pain score was 5 for the levonorgestrel intrauterine system and 4 for the copper intrauterine device. After we controlled for parity, history of dysmenorrhea, and type of intrauterine device, higher anticipated pain was associated with increased experienced pain (adjusted relative risk for 1 unit increase in anticipated pain, 1.19; 95% confidence interval, 1.14–1.25). Nulliparity, history of dysmenorrhea, and the hormonal intrauterine device (compared with copper) also were associated with increased pain with intrauterine device placement. Conclusion High levels of anticipated pain correlated with high levels of experienced pain during intrauterine device placement. Nulliparity and a history of dysmenorrhea were also associated with greater discomfort during placement. This information may help guide and treat patients as they consider intrauterine device placement. Future research should focus on interventions to reduce preprocedural anxiety and anticipated pain to potentially decrease discomfort with intrauterine device placement.
MSRC: multimodal spatial regression with semantic context for phrase grounding

Given a textual description of an image, phrase grounding localizes objects in the image referred by query phrases in the description. State-of-the-art methods treat phrase grounding as a ranking problem and address it by retrieving a set of proposals according to the query’s semantics, which are limited by the performance of independent proposal generation systems and ignore useful cues from context in the description. In this paper, we propose a novel multimodal spatial regression with semantic context (MSRC) system which not only predicts the location of ground truth based on proposal bounding boxes, but also refines prediction results by penalizing similarities of different queries coming from same sentences. There are two advantages of MSRC: First, it sidesteps the performance upper bound from independent proposal generation systems by adopting regression mechanism. Second, MSRC not only encodes the semantics of a query phrase, but also considers its relation with context (i.e., other queries from the same sentence) via a context refinement network. Experiments show MSRC system achieves a significant improvement in accuracy on two popular datasets: Flickr30K Entities and Refer-it Game, with 6.64 and 5.28% increase over the state of the arts, respectively.
Comparative life cycle assessment (LCA) of bio-modified binder and conventional asphalt binder

This study is a life cycle assessment (LCA) of conventional asphalt binder versus bio-modified binder that is produced by mixing asphalt binder with bio-binder obtained from swine manure. Both processes were evaluated and compared in terms of their contribution to global warming, using a global warming potential index and energy consumption. This LCA study uses a cradle-to-gate approach for the binder and includes a comparison between the environmental impacts of swine manure in lagoons and the production of bio-binder. The results show the energy consumption and global warming potential improvements after using bio-binder as a sustainable additive.
Symmetric, Hankel-symmetric, and Centrosymmetric Doubly Stochastic Matrices

We investigate convex polytopes of doubly stochastic matrices having special structures: symmetric, Hankel-symmetric, centrosymmetric, and both symmetric and Hankel-symmetric. We determine dimensions of these polytopes and classify their extreme points. We also determine a basis of the real vector spaces generated by permutation matrices with these special structures.
Revisiting MITL to Fix Decision Procedures

Metric Interval Temporal Logic ( MITL ) is a well studied real-time, temporal logic that has decidable satisfiability and model checking problems. The decision procedures for MITLrely on the automata theoretic approach, where logic formulas are translated into equivalent timed automata. Since timed automata are not closed under complementation, decision procedures for MITLfirst convert a formula into negated normal form before translating to a timed automaton. We show that, unfortunately, these 20-year-old procedures are incorrect, because they rely on an incorrect semantics of the \(\mathcal {R}\) operator. We present the right semantics of \(\mathcal {R}\) and give new, correct decision procedures for MITL. We show that both satisfiability and model checking for MITLare Open image in new window , as was previously claimed. We also identify a fragment of MITLthat we call MITL WIthat is richer than \(\texttt {MITL}_{0,\!\infty }\), for which we show that both satisfiability and model checking are Open image in new window . Many of our results have been formally proved in PVS
Nanostructured GaN transistors

This paper describes how the use of nanostructures can significantly increase the performance of GaN transistors. 100–400 nm fins have been defined underneath the gate electrode of AlGaN/GaN transistors to increase the gate modulation efficiency of these devices and to allow for the tuning of the threshold voltage. The proper design of these fins allows not only an improvement in the DC performance of the device, but also a significant enhancement of the rf linearity of the transistors. The excellent electron transport in these nanostructures, combined with the wide bandgap of GaN, its large effective mass and its moderate electric permittivity, also allows the potential scaling of GaN transistors below 5 nm channel length. The theoretical performance of these ultra-scaled devices is benchmarked with respect to other competing technologies.
Revenge: John Sherman, Russell Alger and the origins of the Sherman Act

This paper argues that Senator John Sherman of Ohio was motivated to introduce an antitrust bill in late 1889 partly as a way of enacting revenge on his political rival, General and former Governor Russell Alger of Michigan, because Sherman believed that Alger personally had cost him the presidential nomination at the 1888 Republican national convention. When discussing his bill on the Senate floor and elsewhere, Sherman repeatedly brought up Alger’s relationship, which in reality was rather tenuous, with the well-known Diamond Match Company. The point of mentioning Alger was to hurt Alger’s future political career and his presidential aspirations in 1892. Sherman was able to pursue his revenge motive by combining it with the broader Republican goals of preserving high tariffs and attacking the trusts. As a result, this paper reinforces previous public choice literature arguing that the 1890 Sherman Act was not passed in the public interest, but instead advanced private interests.
The risks of old capital age: Asset pricing implications of technology adoption

Abstract A dynamic model featuring a stochastic technology frontier shows significant impact of technology adoption for asset prices. In equilibrium, firms operating with old capital are riskier because costly technology adoption restricts their flexibility in upgrading to the latest technology, making them more exposed to technology frontier shocks. Consistent with the model predictions, a long-short portfolio sorted on firm-level capital age earns an average value-weighted return of 9% per year among U.S. public companies. A proxy for technology frontier shocks captures the variation of the capital age portfolios with a positive risk price, corroborating the model mechanism.
Limits on inferring the past.

Here we define and study the properties of retrodictive inference. We derive equations relating retrodiction entropy and thermodynamic entropy, and as a special case, show that under equilibrium conditions, the two are identical. We demonstrate relations involving the Kullback-Leibler divergence and retrodiction probability, and bound the time rate of change of retrodiction entropy. As a specific case, we invert various Langevin processes, inferring the initial condition of $N$ particles given their final positions at some later time. We evaluate the retrodiction entropy for Langevin dynamics exactly for special cases, and find that one's ability to infer the initial state of a system can exhibit two possible qualitative behaviors depending on the potential energy landscape, either decreasing indefinitely, or asymptotically approaching a fixed value. We also study how well we can retrodict points that evolve based on the logistic map. We find singular changes in the retrodictivity near bifurcations. Counterintuitively, the transition to chaos is accompanied by maximal retrodictability.
miRNAs in platelet-poor blood plasma and purified RNA are highly stable: a confirmatory study.

We wished to re-assess the relative stability of microRNAs (miRNAs) as compared with other RNA molecules, which has been confirmed in many contexts. When bound to Argonaute proteins, miRNAs are protected from degradation, even when released into the extracellular space in ribonucleoprotein complexes, and with or without the protection of membranes in extracellular vesicles. Purified miRNAs also appear to present less of a target for degradation than other RNAs. Although miRNAs are by no means immune to degradation, biological samples subjected to prolonged incubation at room temperature, multiple freeze/thaws, or collection in the presence of inhibitors like heparin, can typically be remediated or used directly for miRNA measurements. Here, we provide additional confirmation of early, well validated findings on miRNA stability and detectability. Our data also suggest that inadequate depletion of platelets from plasma may explain the occasional report that freeze–thaw cycles can adversely affect plasma miRNA levels. Overall, the repeated observation of miRNA stability is again confirmed.
Whole Genome Transcriptome Analysis of the Association between Obesity and Triple-Negative Breast Cancer in Caucasian Women.

Background: Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer, with poor outcomes. The molecular basis of TNBC remains poorly understood. The objective of this exploratory study was to investigate the association between obesity and TNBC in premenopausal and postmenopausal Caucasian women using transcription profiling. Methods: We compared gene expression levels of tumor samples drawn from normal weight, overweight, and obese pre and postmenopausal women diagnosed with TNBC. We performed hierarchical clustering to assess similarity in patterns of gene expression profiles, and conducted network and pathway analysis to identify molecular networks and biological pathways. Results: We discovered gene signatures distinguishing normal weight from obese, normal weight from overweight, and overweight from obese individuals in both premenopausal and postmenopausal women. The analysis revealed molecular networks and biological pathways associating obesity with TNBC. The discovered pathways included the unfolded protein response, endoplasmic reticulum stress, B cell receptor, and autophagy signaling pathways in obese premenopausal women; and the integrin, axonal guidance, ERK/MAPK (extracellular-signal-regulated kinase/mitogen activated protein kinase) and glutathione biosynthesis signaling pathways in obese postmenopausal women. Conclusions: The results suggest that both overweight and obese status are associated with TNBC, highlighting the need for conformation of these results in independent studies.
Technology, Incentives, or Both? Factors Related to Level of Hospital Health Information Exchange

Objective To assess whether the level of health information exchange (HIE) in U.S. hospitals is related to technology capabilities, incentives to exchange, or both. Study Setting A total of 1,812 hospitals attesting to stage 2 of Medicare's Meaningful Use Incentive Program through April 2016. Study Design Hospital-level, multivariate OLS regression with state fixed effects was used to analyze the relationship between technology capability and incentives measures, and percent of care transitions with summary of care records (SCRs) sent electronically to subsequent providers. Principal Findings Stage 2 hospitals reported sending SCRs electronically for an average of 41 percent (median = 33 percent) of transitions. HIE level is related to four capability measures, one incentive measure, and one measure that is related to both capability and incentive. Percent of transitions with SCRs sent electronically was 3 percentage points higher (95 percent CI: 0.1–5.1) for hospitals with a third-party HIE vendor, 3 percentage points higher (95 percent CI: 0.5–5.4) for hospitals with an EHR vendor as their HIE vendor, and 3 percentage points higher (95 percent CI: 0.4–5.4) for hospitals that automatically alert primary care providers. The direction and statistical significance of the relationships between specific EHR vendor and electronic SCR transmission level varied by vendor. Nonprofits and government hospitals performed 5 percentage points higher (95 percent CI: 1.5–9.1) and 8 percentage points higher (95 percent CI: 3.4–12.3) than for-profits. Hospitals in systems performed 3 percentage points higher (95 percent CI: 0.8–6.1). Conclusion The overall level of HIE is low, with hospitals sending an SCR electronically for less than half of patient transitions. Specific hospital characteristics related to both technology capabilities and incentives were associated with higher levels of HIE.
Beyond fight or flight: The need for conflict management training in medical education

This article reviewed the literature on conflict management training in medicine, proposed a set of competencies that health professionals need to learn in order to effectively deal with conflict in health care settings, and described a pilot project designed to teach many of these competencies at Dartmouth. Our review of the evidence, discussions with experts, and pilot findings highlight the potential value of incorporating comprehensive conflict management training in medical education. Further research is needed to evaluate the optimal timing and most effective ways to teach these skills in medical school, residency, and beyond.
Statistical Power of the Multiple Domain Latent Growth Model for Detecting Group Differences

The latent growth model (LGM) in structural equation modeling (SEM) may be extended to allow for the modeling of associations among multiple latent growth trajectories, resulting in a multiple doma...
Make It or Break It? Assessing Credit Booms in Developing Countries

In this paper, we argue that the assessment of systemic risk associated with rapid credit growth should be conducted with different tools at different stages of financial development. In particular, using a signal detection framework, we show that, when the level of financial development is low, the most used leading indicator of banking crisis, namely the credit-to-GDP gap, has poor predictive performance, as it is unable to disentangle episodes of financial deepening from bubble-like credit booms. On the contrary, a new class of indicators, comparing credit levels to structural benchmarks, has good capacity to correctly predict financial crises in economies in the early stages of financial development.
Timely double-strand break repair and pathway choice in pericentromeric heterochromatin depend on the histone demethylase dKDM4A

Repair of DNA double-strand breaks (DSBs) must be orchestrated properly within diverse chromatin domains in order to maintain genetic stability. Euchromatin and heterochromatin domains display major differences in histone modifications, biophysical properties, and spatiotemporal dynamics of DSB repair. However, it is unclear whether differential histone-modifying activities are required for DSB repair in these distinct domains. We showed previously that the Drosophila melanogaster KDM4A (dKDM4A) histone demethylase is required for heterochromatic DSB mobility. Here we used locus-specific DSB induction in Drosophila animal tissues and cultured cells to more deeply interrogate the impact of dKDM4A on chromatin changes, temporal progression, and pathway utilization during DSB repair. We found that dKDM4A promotes the demethylation of heterochromatin-associated histone marks at DSBs in heterochromatin but not euchromatin. Most importantly, we demonstrate that dKDM4A is required to complete DSB repair in a timely manner and regulate the relative utilization of homologous recombination (HR) and nonhomologous end-joining (NHEJ) repair pathways but exclusively for heterochromatic DSBs. We conclude that the temporal kinetics and pathway utilization during heterochromatic DSB repair depend on dKDM4A-dependent demethylation of heterochromatic histone marks. Thus, distinct pre-existing chromatin states require specialized epigenetic alterations to ensure proper DSB repair.
Distinct Sampling on Streaming Data with Near-Duplicates

In this paper we study how to perform distinct sampling in the streaming model where data contain near-duplicates. The goal of distinct sampling is to return a distinct element uniformly at random from the universe of elements, given that all the near-duplicates are treated as the same element. We also extend the result to the sliding window cases in which we are only interested in the most recent items. We present algorithms with provable theoretical guarantees for datasets in the Euclidean space, and also verify their effectiveness via an extensive set of experiments.
Structural Basis for the RNA-Guided Ribonuclease Activity of CRISPR-Cas13d.

CRISPR-Cas endonucleases directed against foreign nucleic acids mediate prokaryotic adaptive immunity and have been tailored for broad genetic engineering applications. Type VI-D CRISPR systems contain the smallest known family of single effector Cas enzymes, and their signature Cas13d ribonuclease employs guide RNAs to cleave matching target RNAs. To understand the molecular basis for Cas13d function and explain its compact molecular architecture, we resolved cryoelectron microscopy structures of Cas13d-guide RNA binary complex and Cas13d-guide-target RNA ternary complex to 3.4 and 3.3 A resolution, respectively. Furthermore, a 6.5 A reconstruction of apo Cas13d combined with hydrogen-deuterium exchange revealed conformational dynamics that have implications for RNA scanning. These structures, together with biochemical and cellular characterization, provide insights into its RNA-guided, RNA-targeting mechanism and delineate a blueprint for the rational design of improved transcriptome engineering technologies.
Measuring disorganized speech in schizophrenia: automated analysis explains variance in cognitive deficits beyond clinician-rated scales.

Background Conveying information cohesively is an essential element of communication that is disrupted in schizophrenia. These disruptions are typically expressed through disorganized symptoms, which have been linked to neurocognitive, social cognitive, and metacognitive deficits. Automated analysis can objectively assess disorganization within sentences, between sentences, and across paragraphs by comparing explicit communication to a large text corpus. Method Little work in schizophrenia has tested: (1) links between disorganized symptoms measured via automated analysis and neurocognition, social cognition, or metacognition; and (2) if automated analysis explains incremental variance in cognitive processes beyond clinician-rated scales. Disorganization was measured in schizophrenia (n = 81) with Coh-Metrix 3.0, an automated program that calculates basic and complex language indices. Trained staff also assessed neurocognition, social cognition, metacognition, and clinician-rated disorganization. Results Findings showed that all three cognitive processes were significantly associated with at least one automated index of disorganization. When automated analysis was compared with a clinician-rated scale, it accounted for significant variance in neurocognition and metacognition beyond the clinician-rated measure. When combined, these two methods explained 28-31% of the variance in neurocognition, social cognition, and metacognition. Conclusions This study illustrated how automated analysis can highlight the specific role of disorganization in neurocognition, social cognition, and metacognition. Generally, those with poor cognition also displayed more disorganization in their speech-making it difficult for listeners to process essential information needed to tie the speaker's ideas together. Our findings showcase how implementing a mixed-methods approach in schizophrenia can explain substantial variance in cognitive processes.
Human Factors Considerations for Enabling Functional Use of Exosystems in Operational Environments

The domain of human factors considers how to improve system design by considering the human within the design process, rather than designing a system and then considering the effects on the human after the design is completed. There have been decades of work in the domain of human factors and human–system integration in applications for complex systems to understand concepts within the physical domain (e.g., system sizing and injury risk) and cognitive domain (e.g., workload, situation awareness, and automation mode confusion). Exosystem technologies are reaching the point where the transition to an operational environment is within reach. This paper presents human factors principles related to the cognitive domain. We present examples of these concepts in the context of exosystem design for operational environments and to aid the development of system evaluation standards. We also review current exosystem evaluation methods and present how performance metrics and tasks can be expanded to better describe system function in the context of known human factors complexities.
Generalized parity–time symmetry condition for enhanced sensor telemetry

Wireless sensors based on micromachined tunable resonators are important in a variety of applications, ranging from medical diagnosis to industrial and environmental monitoring. The sensitivity of these devices is, however, often limited by their low quality (Q) factor. Here, we introduce the concept of isospectral party–time–reciprocal scaling (PTX) symmetry and show that it can be used to build a new family of radiofrequency wireless microsensors exhibiting ultrasensitive responses and ultrahigh resolution, which are well beyond the limitations of conventional passive sensors. We show theoretically, and demonstrate experimentally using microelectromechanical-based wireless pressure sensors, that PTX-symmetric electronic systems share the same eigenfrequencies as their parity–time (PT)-symmetric counterparts, but crucially have different circuit profiles and eigenmodes. This simplifies the electronic circuit design and enables further enhancements to the extrinsic Q-factor of the sensors.
Francis Hutcheson and John Clarke on Desire and Self-Interest

Among the most animating debates in eighteenth-century British ethics was the debate over psychological egoism, the view that our most basic desires are self-interested. An important episode in tha...
Just above Chance: Is It Harder to Decode Information from Prefrontal Cortex Hemodynamic Activity Patterns?

The prefrontal cortex (PFC) is central to flexible, goal-directed cognition, and understanding its representational code is an important problem in cognitive neuroscience. In humans, multivariate p...
MERIT reveals the impact of genomic context on sequencing error rate in ultra-deep applications

Rapid progress in high-throughput sequencing (HTS) and the development of novel library preparation methods have improved the sensitivity of detecting mutations in heterogeneous samples, specifically in high-depth (> 500×) clinical applications. However, HTS methods are bounded by their technical and theoretical limitations and sequencing errors cannot be completely eliminated. Comprehensive quantification of the background noise can highlight both the efficiency and the limitations of any HTS methodology, and help differentiate true mutations at low abundance from artifacts. We introduce MERIT (Mutation Error Rate Inference Toolkit), designed for in-depth quantification of erroneous substitutions and small insertions and deletions. MERIT incorporates an all-inclusive variant caller and considers genomic context, including the nucleotides immediately at 5 ′and 3 ′, thereby establishing error rates for 96 possible substitutions as well as four single-base and 16 double-base indels. We applied MERIT to ultra-deep sequencing data (1,300,000 ×) obtained from the amplification of multiple clinically relevant loci, and showed a significant relationship between error rates and genomic contexts. In addition to observing significant difference between transversion and transition rates, we identified variations of more than 100-fold within each error type at high sequencing depths. For instance, T >G transversions in trinucleotide GTCs occurred 133.5 ± 65.9 more often than those in ATAs. Similarly, C >T transitions in GCGs were observed at 73.8 ± 10.5 higher rate than those in TCTs. We also devised an in silico approach to determine the optimal sequencing depth, where errors occur at rates similar to those of expected true mutations. Our analyses showed that increasing sequencing depth might improve sensitivity for detecting some mutations based on their genomic context. For example, T >G rate of error in GTCs did not change when sequenced beyond 10,000 ×; in contrast, T >G rate in TTAs consistently improved even at above 500,000 ×. Our results demonstrate significant variation in nucleotide misincorporation rates, and suggest that genomic context should be considered for comprehensive profiling of specimen-specific and sequencing artifacts in high-depth assays. This data provide strong evidence against assigning a single allele frequency threshold to call mutations, for it can result in substantial false positive as well as false negative variants, with important clinical consequences.