cssi/SciSciGPT-SciSciNet huggingface dataset:
Shock-front broadening in polycrystalline materials

We analyze a model for the evolution of shock fronts in polycrystalline materials. This model is based on the idea of Meyers and Carvalho [Mater. Sci. Eng. 24, 131 (1976)] that the shock velocity anisotropy within the polycrystal is the most important factor in shock front broadening. Our analysis predicts that the shock front width increases as the $1∕2$ power of the front penetration distance into the crystal. Our theoretical prediction is in plausible agreement with previous experimental results for the elastic precursor rise time, and it should therefore provide a useful shock width estimate. Furthermore, our theoretical framework is also applicable to other problems involving front propagation in heterogeneous media.
Forceplates Data Reliability Tested on Children with Neuromuscular Disabilities

The âgait cycleâ is considered the fundamental repetitive element of locomotion and is often used in comparative analyses between pathological and normal gait. One device that is used to measure ground reaction forces in the gait laboratory is a six degrees of freedom force transducer (âForce Plateâ). Gait labs use two or more force plates to measure forces during one or two complete strides. Often, the walker âaimsâ to step sequentially on the force plates. This aiming may cause significant distortion of the personâs gait pattern. To validate the measured result as representative of the individualâs gait, a âGait Consistency Testâ was developed by Seliktar et.al with a group of adult individuals. The present study employed the consistency test to the ground reaction force records of two groups of children; typically developing children and children with cerebral palsy. The childrenâs gait consistency study yielded even better results than the adult study; the results showed that the consistency test is useful for screening childrenâs gait data and should be used to ensure higher fidelity of the measured data. The test applied equally to normally developing children and to children with gait pathologies.
Threats to North American forests from southern pine beetle with warming winters

In coming decades, warmer winters are likely to ease range constraints on many cold-limited forest insects1-5. Recent unprecedented expansion of the southern pine beetle (SPB, Dendroctonus frontalis) into New Jersey, New York, and Connecticut in concert with warming annual temperature minima highlights the risk that this insect pest poses to the pine forests of the northern United States and Canada under continued climate change6. Here we present projections of northward expansion in SPB-suitable climates using a statistical bioclimatic range modeling approach and current-generation general circulation model (GCM) output under the Representative Concentration Pathway (RCP) 4.5 and 8.5 emissions scenarios. Our results show that by the middle of the 21st century, the climate is likely to be suitable for SPB expansion into vast areas of previously unaffected forests throughout the northeastern United States and into southeastern Canada. This scenario would pose a significant economic and ecological risk to the affected regions, including disruption of local ecosystem services7, shifts in forest structure8, and threats to native biodiversity9.
La Narración en CARTUCHO. Relatos de la Lucha en el Norte (Nellie Campobello)

Nellie Campobello es la unica escritora de la primera etapa de la novela de la Revolucion Mexicana. En una sociedad tan tradicional como la mexicana, ?cual seria la experiencia de una mujer en esta Revolucion? Es muy importante tener en cuenta su vision porque ella la vivio de nina, y en su obra va a contar sus experiencias, pero desde una perspectiva diferente a los demas escritores que desarrollaron el conflicto. Muchas de las imagenes muestran sentimientos irreconciliables, como la crudeza y la ternura, que solo la mente de una nina es capaz de mezclar.
Making Immigrants into Criminals: Legal Processes of Criminalization in the Post-IIRIRA Era

During a post-election TV interview that aired mid-November 2016, then President-Elect Donald Trump claimed that there are millions of so-called “criminal aliens” living in the United States: “What...
A Failure to Communicate: Are University Websites Readable?

The readability of university-authored websites is an area wholly unexplored by higher education research and constitutes a crucial gap in the literature. The purpose of this study was to examine the readability of university-sponsored webpages of 30 four-year public American universities (n = 300), comprising three of the largest university systems in the country. The results suggest that the vast majority of university-authored webpages are unreadable by prospective postsecondary students, and institutions in the same university system wildly vary the readability of their documents. Implications for policy, practice, and future research are addressed.
Nonwork Trips Associated with Transit-Oriented Development

An analysis of factors associated with nonwork trips was conducted. The key variable of interest was proximity to transit-oriented development areas around train stations in New Jersey. The data were derived from a questionnaire of households around eight train stations and stratified by distance from a station. The focus was on the mode used for trips to restaurants–coffee shops and grocery–food stores, two of the most common and frequent nonwork trips. The analysis focused on the choice of walking versus driving for these trips by using an instrumental variable probit model aimed at controlling for the endogeneity associated with self-selection bias (i.e., people who prefer not to drive choose more walkable neighborhoods). Results showed strong associations between proximity to transit-oriented development areas and walking trips, and these results hold when endogeneity is controlled for. Local street density and per capita vehicle ownership also had the expected effects on walking trips.
A Survey of the Connected Vehicle Landscape—Architectures, Enabling Technologies, Applications, and Development Areas

This paper summarizes the state of the art in connected vehicles—from the need for vehicle data and applications thereof, to enabling technologies, challenges, and identified opportunities. Connectivity is increasing around the world and its expansion to vehicles is no exception. With improvements in connectivity, sensing, and computation, the future will see vehicles used as development platforms capable of generating rich data, acting based on inference, and effecting great change in transportation, the human-vehicle dynamic, the environment, and the economy. Connected vehicle technologies have already been used to improve fleet safety and efficiency, with emerging technologies additionally allowing data to be used to inform aspects of vehicle design, ownership, and use. While the demand for connected vehicles and its enabling technology has progressed significantly in recent years, there remain challenges to connected and collaborative vehicle application deployment before the full potential of connected cars may be realized. From extensibility and scalability to privacy and security, this paper informs the reader about key enabling technologies, opportunities, and challenges in the connected vehicle landscape.
Estimated Costs of Contact in College and High School Male Sports

Injury rates in 12 U.S. men’s college sports and 5 U.S. boys’ high school sports are examined in this article. The sports are categorized as “contact” or “noncontact,” and differences in injury rat...
Endogenous Alpha-Synuclein Protein Analysis from Human Brain Tissues Using Single-Molecule Pull-Down Assay.

Alpha-synuclein (α-SYN) is a central molecule in Parkinson’s disease pathogenesis. Despite several studies, the molecular nature of endogenous α-SYN especially in human brain samples is still not well understood due to the lack of reliable methods and the limited amount of biospecimens. Here, we introduce α-SYN single-molecule pull-down (α-SYN SiMPull) assay combined with in vivo protein crosslinking to count individual α-SYN protein and assess its native oligomerization states from biological samples including human postmortem brains. This powerful single-molecule assay can be highly useful in diagnostic applications using various specimens for neurodegenerative diseases including Alzheimer’s disease and Parkinson’s disease.
Infection via mosquito bite alters Zika virus tissue tropism and replication kinetics in rhesus macaques

Mouse and nonhuman primate models now serve as useful platforms to study Zika virus (ZIKV) pathogenesis, candidate therapies, and vaccines, but they rely on needle inoculation of virus: the effects of mosquito-borne infection on disease outcome have not been explored in these models. Here we show that infection via mosquito bite delays ZIKV replication to peak viral loads in rhesus macaques. Importantly, in mosquito-infected animals ZIKV tissue distribution was limited to hemolymphatic tissues, female reproductive tract tissues, kidney, and liver, potentially emulating key features of human ZIKV infections, most of which are characterized by mild or asymptomatic disease. Furthermore, deep sequencing analysis reveals that ZIKV populations in mosquito-infected monkeys show greater sequence heterogeneity and lower overall diversity than in needle-inoculated animals. This newly developed system will be valuable for studying ZIKV disease because it more closely mimics human infection by mosquito bite than needle-based inoculations.
Collisionless kinetic theory of oblique tearing instabilities

The linear dispersion relation for collisionless kinetic tearing instabilities is calculated for the Harris equilibrium. In contrast to the conventional 2D geometry, which considers only modes at the center of the current sheet, modes can span the current sheet in 3D. Modes at each resonant surface have a unique angle with respect to the guide field direction. Both kinetic simulations and numerical eigenmode solutions of the linearized Vlasov-Maxwell equations have recently revealed that standard analytic theories vastly overestimate the growth rate of oblique modes. We find that this stabilization is associated with the density-gradient-driven diamagnetic drift. The analytic theories miss this drift stabilization because the inner tearing layer broadens at oblique angles sufficiently far that the assumption of scale separation between the inner and outer regions of boundary-layer theory breaks down. The dispersion relation obtained by numerically solving a single second order differential equation is fou...
Elp3 and RlmN: A tale of two mitochondrial tail-anchored radical SAM enzymes in Toxoplasma gondii.

Radical S-adenosylmethionine (rSAM) enzymes use a 5’-deoxyadensyl 5’-radical to methylate a wide array of diverse substrates including proteins, lipids and nucleic acids. One such enzyme, Elongator protein-3 (TgElp3), is an essential protein in Toxoplasma gondii, a protozoan parasite that can cause life-threatening opportunistic disease. Unlike Elp3 homologues which are present in all domains of life, TgElp3 localizes to the outer mitochondrial membrane (OMM) via a tail-anchored trafficking mechanism in Toxoplasma. Intriguingly, we identified a second tail-anchored rSAM domain containing protein (TgRlmN) that also localizes to the OMM. The transmembrane domain (TMD) on Toxoplasma Elp3 and RlmN homologues is required for OMM localization and has not been seen beyond the chromalveolates. Both TgElp3 and TgRlmN contain the canonical rSAM amino acid sequence motif (CxxxCxxC) necessary to form the 4Fe-4S cluster required for tRNA modifications. In E. coli, RlmN is responsible for the 2-methlyadenosine (m2A) synthesis at purine 37 in tRNA while in S. cerevisiae, Elp3 is necessary for the formation of 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U) at the wobble tRNA position. To investigate why these two rSAM enzymes localize to the mitochondrion in Toxoplasma, and whether or not TgRlmN and TgElp3 possess tRNA methyltransferase activity, a series of mutational and biochemical studies were performed. Overexpression of either TgElp3 or TgRlmN resulted in a significant parasite replication defect, but overexpression was tolerated if either the TMD or rSAM domain was mutated. Furthermore, we show the first evidence that Toxoplasma tRNAGlu contains the mcm5s2U modification, which is the putative downstream product generated by TgElp3 activity.
Four-phonon scattering reduces intrinsic thermal conductivity of graphene and the contributions from flexural phonons

We have developed a formalism of the exact solution to linearized phonon Boltzmann transport equation (BTE) for thermal conductivity calculation including three- and four-phonon scattering. We find strikingly high four-phonon scattering rates in single-layer graphene (SLG) based on the optimized Tersoff potential. The reflection symmetry in graphene, which forbids the three-ZA (out-of-plane acoustic) scattering, allows the four-ZA processes $\mathrm{ZA}+\mathrm{ZA}\ensuremath{\rightleftharpoons}\mathrm{ZA}+\mathrm{ZA}$ and $\mathrm{ZA}\ensuremath{\rightleftharpoons}\mathrm{ZA}+\mathrm{ZA}$ + ZA. As a result, the large phonon population of the low-energy ZA branch originated from the quadratic phonon dispersion leads to high four-phonon scattering rates, even much higher than the three-phonon scattering rates at room temperature. These four-phonon processes are dominated by the normal processes, which lead to a failure of the single mode relaxation time approximation. Therefore, we have solved the exact phonon BTE using an iterative scheme and then calculated the length- and temperature-dependent thermal conductivities. We find that the predicted thermal conductivity of SLG is lower than the previously predicted value from the three-phonon scattering only. The relative contribution of the ZA branch is reduced from 70% to 30% when four-phonon scattering is included. Furthermore, we have demonstrated that the four-phonon scattering in multilayer graphene and graphite is not strong due to the ZA splitting by interlayer van der Waals interaction. We also demonstrate that the five-phonon process in SLG is not strong due to the restriction of reflection symmetry.
Surviving Firms of the Syrian Arab Republic : A Rapid Assessment

This paper details the results from the first comprehensive survey of private firms across major urban areas in the Syrian Arab Republic -- including Aleppo, Homs, Hama, Latakia, and Damascus -- since the conflict began in 2011. This builds on the World Bank's Enterprise Survey from 2009 and attempts to survey each of the 508 firms from 2009 again. The survey highlights the major challenges facing firms in Syria today, such as access to electricity, fuel, and water. Yet, loss of workers, managers, and supply chain relationships are also notably severe. Rebuilding the social and human capital of Syria may be even more difficult than the bricks and mortar. The paper also identifies the ways firms have been affected in their prices, sales, supply chains, taxation, and costs as well as how they have adapted in financing and employment. These constraints and impacts are also analyzed at the subnational level and across sectors. Firms in Aleppo stand out for their uniquely difficult challenges and responses that are sometimes at odds with the rest of the country. Finally, the paper analyzes firm exit from 2009 to 2017 and finds that higher productivity firms from 2009 were more likely to survive, except in Aleppo where the reverse holds. The paper hypothesizes that productive firms facing the particularly severe destruction in Aleppo may have made a different calculation compared with productive firms elsewhere: to use their capabilities to leave rather than to use their capabilities to weather the storm.
In vitro synthesis of gene-length single-stranded DNA

Single-stranded DNA (ssDNA) increases the likelihood of homology directed repair with reduced cellular toxicity. However, ssDNA synthesis strategies are limited by the maximum length attainable, ranging from a few hundred nucleotides for chemical synthesis to a few thousand nucleotides for enzymatic synthesis, as well as limited control over nucleotide composition. Here, we apply purely enzymatic synthesis to generate ssDNA greater than 15 kilobases (kb) using asymmetric PCR, and illustrate the incorporation of diverse modified nucleotides for therapeutic and theranostic applications.
The Impact of New Drug Launches on Life-Years Lost in 2015 from 19 Types of Cancer in 36 Countries

This study employs a two-way fixed effects research design to measure the mortality impact and cost-effectiveness of cancer drugs: It analyzes the correlation across 36 countries between the relative mortality from 19 types of cancer in 2015 and the relative number of drugs previously launched in that country to treat that type of cancer, controlling for relative incidence. The sample size (both in terms of number of observations and population covered) of this study is considerably larger than the sample sizes of previous studies; a new and improved method of analyzing the lag structure of the relationship between drug launches and life-years lost is used; and a larger set of measures of the burden of cancer is analyzed. The number of DALYs and life-years lost are unrelated to drug launches 0–4 years earlier. This is not surprising, since utilization of a drug tends to be quite low during the first few post-launch years. Moreover, there is likely to be a lag of several years between utilization of a drug and its impact on mortality. However, mortality is significantly inversely related to the number of drug launches at least 5 years earlier, especially to drug launches 5–9 years earlier. One additional drug for a cancer site launched during 2006–2010 is estimated to have reduced the number of 2015 DALYs due to cancer at that site by 5.8%;; one additional drug launched during 1982–2005 is estimated to have reduced the number of 2015 DALYs by about 2.6%. Lower quality (or effectiveness) of earlier vintage drugs may account for their smaller estimated effect. We estimate that drugs launched during the entire 1982–2010 period reduced the number of cancer DALYs in 2015 by about 23.0%, and that, in the absence of new drug launches during 1982–2010, there would have been 26.3 million additional DALYs in 2015. Also, the nine countries with the largest number of drug launches during 1982–2010 are estimated to have had 14% fewer cancer DALYs (controlling for incidence) in 2015 than the nine countries with the smallest number of drug launches during 1982–2010. Estimates of the cost per life-year gained in 2015 from drugs launched during 2006–2010 range between 2,820 (life-years gained before age 65). These estimates are similar to those obtained in previous country-specific studies of Belgium, Canada, and Mexico, and are well below the estimate obtained in one study of Switzerland. Mortality in 2015 is strongly inversely related to the number of drug launches in 2006–2010. If the relationship between mortality in 2020 and the number of drug launches in 2011–2015 is similar, drug launches 5–9 years earlier will reduce mortality even more (by 9.9%) between 2015 and 2020 than they did (by 8.4%) between 2010 and 2015.
Using satellite imagery to revolutionize creation of tax maps and local revenue collection

The technical complexity of ensuring that tax rolls are complete and valuations current is often perceived as a major barrier to bringing in more property tax revenues in developing countries. This paper shows how high-resolution satellite imagery makes it possible to assess the completeness of existing tax maps by estimating built-up areas based on building heights and footprints. Together with information on sales prices from the land registry, targeted surveys, and routine statistical data, this makes it possible to use mass valuation procedures to generate tax maps. The example of Kigali illustrates the reliability of the method and the potentially far-reaching revenue impacts. Estimates show that heightened compliance and a move to a 1 percent ad valorem tax would yield a tenfold increase in revenue from public land.
Invariant Manifolds for a Class of Degenerate Evolution Equations and Structure of Kinetic Shock Layers

We describe recent results with A. Pogan developing dynamical systems tools for a class of degenerate evolution equations arising in kinetic theory, including the steady Boltzmann and BGK equations. These yield information on structure of large- and small-amplitude kinetic shocks, the first steps in a larger program toward time-evolutionary stability and asymptotic behavior.
A model-based embedding technique for segmenting customers

We consider the problem of segmenting a large population of customers into nonoverlapping groups with similar preferences, using diverse preference observations such as purchases, ratings, clicks, ...
TESTOTOXICOSIS WITH AN EPISODIC COURSE: AN UNUSUAL CASE WITHIN A SERIES

ABSTRACT Objective: To describe an unusual case of familial male precocious puberty (FMPP) characterized by periodic remission compared to a series of boys with typical testotoxicosis. Methods: Med...
Diffusion scattering transforms on graphs

Stability is a key aspect of data analysis. In many applications, the natural notion of stability is geometric, as illustrated for example in computer vision. Scattering transforms construct deep convolutional representations which are certified stable to input deformations. This stability to deformations can be interpreted as stability with respect to changes in the metric structure of the domain. In this work, we show that scattering transforms can be generalized to non-Euclidean domains using diffusion wavelets, while preserving a notion of stability with respect to metric changes in the domain, measured with diffusion maps. The resulting representation is stable to metric perturbations of the domain while being able to capture "high-frequency" information, akin to the Euclidean Scattering.
The effect of moral foundations in prosocial crowdfunding

Prosocial crowdfunding is a new business phenomenon which is transforming the microfinance sector, as more microloans are posted online for fundraising. Research suggests that prosocial lenders reg...
Optimal auctions vs. anonymous pricing

Abstract For selling a single item to agents with independent but non-identically distributed values, the revenue optimal auction is complex. With respect to it, Hartline and Roughgarden (2009) showed that the approximation factor of the second-price auction with an anonymous reserve is between two and four. We consider the more demanding problem of approximating the revenue of the ex ante relaxation of the auction problem by posting an anonymous price and derive a formula for their worst-case ratio, denoted ρ, that numerically evaluates to e. As a corollary, the upper-bound of anonymous pricing or anonymous reserves versus the optimal auction improves from four to ρ ≈ e . We conclude that, up to the factor ρ, discrimination and simultaneity are unimportant for driving revenue in single-item auctions.
Did Chuck Berry Have a Co-Writer?

On New Year’s Eve 1952, Johnnie Johnson hired Chuck Berry. In the year 2000, he sued him. What happened in between became legend: the creation of songs so wildly influential that John Lennon sugges...
Proximity and Economic Activity: An Analysis of Vendor‐University Transactions

This paper using transaction based data to provide new insights into the link between the geographic proximity of businesses and associated economic activity. It contributes to the literature by developing both two new measures of distance and a set of stylized facts on the distances between observed transactions between vendors and customers for a research intensive sector - universities. We show that spending on research inputs is more likely to be expended at businesses physically closer to universities than those farther away. That relationship is stronger for High Tech and R&D performing businesses than businesses in general, which is consistent with theories emphasizing the role of tacit knowledge. We find that firms behave in a way that is consistent with the notion that propinquity is good for business: if a firm supplies a project at a university in a given year, it is more likely to open an establishment near that university in subsequent years than other firms. We also investigate the link between transactional distance and economic activity and show that when a vendor has been a supplier to a project at least one time, that vendor is subsequently more likely to be a vendor on the same or related project.
Practical challenge-response for DNS

Authoritative DNS servers are susceptible to being leveraged in denial of service attacks in which the attacker sends DNS queries while masquerading as a victim---and hence causing the DNS server to send the responses to the victim. This reflection off innocent DNS servers hides the attackers identity and often allows the attackers to amplify their traffic by employing small requests to elicit large responses. Several challenge-response techniques have been proposed to establish a requester's identity before sending a full answer. However, none of these are practical in that they do not work in the face of "resolver pools"---or groups of DNS resolvers that work in concert to lookup records in the DNS. In these cases a challenge transmitted to some resolver R1 may be handled by a resolver R2, hence leaving an authoritative DNS server wondering whether R2 is in fact another resolver in the pool or a victim. We offer a practical challenge-response mechanism that uses challenge chains to establish identity in the face of resolver pools. We illustrate that the practical cost of our scheme in terms of added delay is small.
Bounded-Loss Private Prediction Markets

Prior work has investigated variations of prediction markets that preserve participants' (differential) privacy, which formed the basis of useful mechanisms for purchasing data for machine learning objectives. Such markets required potentially unlimited financial subsidy, however, making them impractical. In this work, we design an adaptively-growing prediction market with a bounded financial subsidy, while achieving privacy, incentives to produce accurate predictions, and precision in the sense that market prices are not heavily impacted by the added privacy-preserving noise. We briefly discuss how our mechanism can extend to the data-purchasing setting, and its relationship to traditional learning algorithms.
Improved Pathogenic Variant Localization via a Hierarchical Model of Sub-regional Intolerance

Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease-associated mutations, which often cluster in particular regions of disease-associated genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease-associated genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease-associated genes for epileptic encephalopathy.
Improved Return Level Estimation via a Weighted Likelihood, Latent Spatial Extremes Model

Uncertainty in return level estimates for rare events, like the intensity of large rainfall events, makes it difficult to develop strategies to mitigate related hazards, like flooding. Latent spatial extremes models reduce the uncertainty by exploiting spatial dependence in statistical characteristics of extreme events to borrow strength across locations. However, these estimates can have poor properties due to model misspecification: Many latent spatial extremes models do not account for extremal dependence, which is spatial dependence in the extreme events themselves. We improve estimates from latent spatial extremes models that make conditional independence assumptions by proposing a weighted likelihood that uses the extremal coefficient to incorporate information about extremal dependence during estimation. This approach differs from, and is simpler than, directly modeling the spatial extremal dependence; for example, by fitting a max-stable process, which is challenging to fit to real, large datasets. We adopt a hierarchical Bayesian framework for inference, use simulation to show the weighted model provides improved estimates of high quantiles, and apply our model to improve return level estimates for Colorado rainfall events with 1% annual exceedance probability. Supplementary materials accompanying this paper appear online.
Blind Joint MIMO Channel Estimation and Decoding

We propose a method for multiple-input multiple-output (MIMO) decoding when channel-state information (CSI) is unknown to both the transmitter and receiver. The proposed method requires some structure in the transmitted signal for the decoding to be effective, in particular that the underlying sources are drawn from a hypercubic space. Our proposed technique fits a minimum volume parallelepiped to the received samples. This problem can be expressed as a non-convex optimization problem that can be solved with high probability by gradient descent. Our blind decoding algorithm can be used when communicating over unknown MIMO wireless channels using either binary phase-shift keying or MPAM modulation. We apply our technique to jointly estimate MIMO-channel gain matrices and decode the underlying transmissions with only knowledge of the transmitted constellation and without the use of pilot symbols. Our results provide theoretical guarantees that the proposed algorithm is correct when applied to MIMO systems with four or fewer transmit antennas. Empirical results show small sample size requirements, making this algorithm suitable for block-fading channels with coherence times typically seen in practice. Our approach has a loss of less than 3 dB compared to zero forcing with perfect CSI, imposing a similar performance penalty as space-time coding techniques without the loss of rate incurred by those techniques.
Identifying Protein Features Responsible for Improved Drug Repurposing Accuracies Using the CANDO Platform: Implications for Drug Design.

Drug repurposing is a valuable tool for combating the slowing rates of novel therapeutic discovery. The Computational Analysis of Novel Drug Opportunities (CANDO) platform performs shotgun repurposing of 2030 indications/diseases using 3733 drugs/compounds to predict interactions with 46,784 proteins and relating them via proteomic interaction signatures. The accuracy is calculated by comparing interaction similarities of drugs approved for the same indications. We performed a unique subset analysis by breaking down the full protein library into smaller subsets and then recombining the best performing subsets into larger supersets. Up to 14% improvement in accuracy is seen upon benchmarking the supersets, representing a 100–1000-fold reduction in the number of proteins considered relative to the full library. Further analysis revealed that libraries comprised of proteins with more equitably diverse ligand interactions are important for describing compound behavior. Using one of these libraries to generate putative drug candidates against malaria, tuberculosis, and large cell carcinoma results in more drugs that could be validated in the biomedical literature compared to using those suggested by the full protein library. Our work elucidates the role of particular protein subsets and corresponding ligand interactions that play a role in drug repurposing, with implications for drug design and machine learning approaches to improve the CANDO platform.
Sensitivity analysis for publication bias in meta-analyses

We propose sensitivity analyses for publication bias in meta-analyses. We consider a publication process such that 'statistically significant' results are more likely to be published than negative or "non-significant" results by an unknown ratio, η. Our proposed methods also accommodate some plausible forms of selection based on a study's standard error. Using inverse probability weighting and robust estimation that accommodates non-normal population effects, small meta-analyses, and clustering, we develop sensitivity analyses that enable statements such as 'For publication bias to shift the observed point estimate to the null, "significant" results would need to be at least 30 fold more likely to be published than negative or "non-significant" results'. Comparable statements can be made regarding shifting to a chosen non-null value or shifting the confidence interval. To aid interpretation, we describe empirical benchmarks for plausible values of η across disciplines. We show that a worst-case meta-analytic point estimate for maximal publication bias under the selection model can be obtained simply by conducting a standard meta-analysis of only the negative and 'non-significant' studies; this method sometimes indicates that no amount of such publication bias could 'explain away' the results. We illustrate the proposed methods by using real meta-analyses and provide an R package: PublicationBias.
Safety and Tolerability of Sonic Hedgehog Pathway Inhibitors in Cancer

The hedgehog pathway, for which sonic hedgehog (Shh) is the most prominent ligand, is highly conserved and is tightly associated with embryonic development in a number of species. This pathway is also tightly associated with the development of several types of cancer, including basal cell carcinoma (BCC) and acute promyelocytic leukemia, among many others. Inactivating mutations in Patched-1 (PTCH1), leading to ligand-independent pathway activation, are frequent in several cancer types, but most prominent in BCC. This has led to the development of several compounds targeting this pathway as a cancer therapeutic. These compounds target the inducers of this pathway in Smoothened (SMO) and the GLI transcription factors, although targeting SMO has had the most success. Despite the many attempts at targeting this pathway, only three US FDA-approved drugs for cancers affect the Shh pathway. Two of these compounds, vismodegib and sonidegib, target SMO to suppress signaling from either PTCH1 or SMO mutations that lead to upregulation of the pathway. The other approved compound is arsenic trioxide, which can suppress this pathway at the level of the GLI proteins, although current evidence suggests it also has other targets. This review focuses on the safety and tolerability of these clinically approved drugs targeting the Shh pathway, along with a discussion on other Shh pathway inhibitors being developed.
Popularity-Aware Caching Increases the Capacity of Wireless Networks

In wireless ad hoc networks, due to the interference between concurrent transmissions, the per-node capacity generally decreases with the increasing number of nodes in the network. Caching can help improve the network capacity, as it shortens the content transmission distance and reduces the communication interference. However, current researches on the capacity of wireless ad hoc networks with caching generally assume that content popularity follows a uniform distribution. They ignore the fact that contents in reality have skewed popularity, which may lead to totally different capacity results. In this paper, we evaluate how the distribution of the content popularity affects the per-node capacity, and derive different capacity scaling laws based on the skewness of the content popularity. Our results suggest that for wireless networks with caching, when contents have skewed popularity, increasing the number of nodes monotonically increases the per-node capacity.
Hop: Heterogeneity-aware Decentralized Training

Recent work has shown that decentralized algorithms can deliver superior performance over centralized ones in the context of machine learning. The two approaches, with the main difference residing in their distinct communication patterns, are both susceptible to performance degradation in heterogeneous environments. Although vigorous efforts have been devoted to supporting centralized algorithms against heterogeneity, little has been explored in decentralized algorithms regarding this problem. This paper proposes Hop, the first heterogeneity-aware decentralized training protocol. Based on a unique characteristic of decentralized training that we have identified, the iteration gap, we propose a queue-based synchronization mechanism that can efficiently implement backup workers and bounded staleness in the decentralized setting. To cope with deterministic slowdown, we propose skipping iterations so that the effect of slower workers is further mitigated. We build a prototype implementation of Hop on TensorFlow. The experiment results on CNN and SVM show significant speedup over standard decentralized training in heterogeneous settings.
Computational epidemiology

As recent pandemics such as SARS and the Swine Flu outbreak have shown, diseases spread very fast in today's interconnected world, making public health an important research area. Some of the basic questions are: How can an outbreak be contained before it becomes an epidemic, and what disease surveillance strategies should be implemented? These problems have been studied traditionally using differential equation methods, which are amenable to analysis and closed form solutions. However, these models are based on complete mixing assumptions, which do not hold for realistic populations, thereby limiting their utility.In this tutorial, we focus on an approach based on diffusion processes on complex networks. This captures more realistic populations, but leads to novel mathematical and computational challenges. The structure of the underlying networks has a significant impact on the dynamical properties, motivating the need for improved network models, and efficient algorithms for computing network and dynamical properties that scale to large networks. We provide an overview of the state of the art in computational epidemiology, which is a multi-disciplinary research area, that overlaps different areas in computer science, including data mining, machine learning, high performance computing and theoretical computer science, as well as mathematics, economics and statistics. Specifically, we will discuss mathematical and computational models, problems of inference, forecasting and state assessment, and epidemic containment.
Is Fasting Necessary for Individuals With Nonalcoholic Fatty Liver Disease to Undergo Vibration-Controlled Transient Elastography?

OBJECTIVES:To investigate the effect of meal intake on liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) in patients with biopsy-proven nonalcoholic fatty liver disease undergoing vibration-controlled transient elastography.METHODS:LSM and CAP were assessed at baseline and
How incentive framing can harness the power of social norms

Abstract Incentives are an increasingly common tool used by organizations, managers, and policymakers to change behavior. We propose that more than just motivating behavior for monetary reasons, incentives also have an important, undiscovered consequence: they leak information about social norms. Four experiments reveal that framing an incentive as a surcharge, as compared to a discount, signals that the incentivized behavior is both more socially approved and more common. These implied norms lead individuals to experience emotions consistent with a desire to conform, motivating them to perform the incentivized behavior. Moreover, by shifting social norms, we find that incentives can influence behavior not only in the moment, but also downstream when there is no longer an active incentive. Further, merely being exposed to a surcharge (vs. discount) incentive—even without being financially affected by it—can increase performance of the behavior. These findings offer a novel perspective on the consequences of different incentive frames, while contributing to both organizational policy and practice by expanding the social norms messaging toolkit.
Honoring Innocent Until Proven Guilty: Switching the Default Rule from Pretrial Detention to Pretrial Release in Texas's Bail System

Texas’s current prison population consists of far more pretrial detainees than convicted criminals. Despite United States and Texas constitutional protections, the default rule in many jurisdictions, including Texas, detains misdemeanor and non-violent felony defendants unless they can post a monetary bond or get a surety to post the bond for them (“bail bond”) to obtain their release. Most pretrial detainees remain detained due not to their alleged dangerousness, but rather because they simply cannot afford to post bail (or get someone to post it for them). As a result, many pretrial detainees find themselves choosing between hamstringing their financial future or remaining in detention until trial. If Americans are serious about “honoring the presumption of innocence,” we must reform the way that misdemeanor and non-violent felony defendants are treated while awaiting trial. Rather than treat them as guilty and keep them in jail unless they can pay for their release, the standard should be to release them unless there is a very good reason for not doing so. By changing the default option from pretrial detention to pretrial release, many Texas judges will be more pre-disposed to release misdemeanor and non-violent felony defendants on conditions other than the posting of monetary bail. This switch will result in fewer people being detained simply because they cannot afford to be released—which will prevent adverse economic consequences to already disadvantaged citizens. Proposed reform has been discussed for decades. Reforming the bail system in Texas is a current, critical need. This criminal justice issue undermines the public’s faith in our system of justice and detrimentally affects the economic and social status of countless citizens who will ultimately be found not guilty. Doing nothing weakens our overall rule-of-law system and ultimately erodes the foundation upon which our society is built.
Rider-to-rider discriminatory attitudes and ridesharing behavior

Abstract Using online survey data from N = 2041 Uber and Lyft users in the United States collected in 2016 and 2018, this paper establishes the validity, reliability, and invariance of a measure of rider-to-rider race and social class discrimination. This measure is then incorporated into three structural models that investigate associations between rider-to-rider discriminatory attitudes and four aspects of ridesharing behavior. We find no significant relationship between rider-to-rider discriminatory attitudes and whether a TNC user has ever used a ridesharing service (such as uberPOOL or Lyft Line). However, among those who have used ridesharing services before, rider-to-rider discriminatory attitudes are strongly negatively predictive of an individual's level of satisfaction with the sharing option, and marginally negatively predictive of an individual's percentage of shared TNC trips. Furthermore, among those who have not yet used ridesharing services, rider-to-rider discriminatory attitudes are strongly negatively predictive of willingness to consider using uberPOOL or Lyft Line in the future. Together, these findings suggest that rider-to-rider discriminatory attitudes may discourage sustained and frequent use of ridesharing services among TNC users. Further research is required to identify strategies for addressing discriminatory attitudes in the ridesharing context and overcoming reluctance to sharing.
Prickle1 is required for EMT and migration of zebrafish cranial neural crest.

Abstract The neural crest—a key innovation of the vertebrates—gives rise to diverse cell types including melanocytes, neurons and glia of the peripheral nervous system, and chondrocytes of the jaw and skull. Proper development of the cephalic region is dependent on the tightly-regulated specification and migration of cranial neural crest cells (NCCs). The core PCP proteins Frizzled and Disheveled have previously been implicated in NCC migration. Here we investigate the functions of the core PCP proteins Prickle1a and Prickle1b in zebrafish cranial NCC development. Using analysis of pk1a and pk1b mutant embryos, we uncover similar roles for both genes in facilitating cranial NCC migration. Disruption of either gene causes pre-migratory NCCs to cluster together at the dorsal aspect of the neural tube, where they adopt aberrant polarity and movement. Critically, in investigating Pk1-deficient cells that fail to migrate ventrolaterally, we have also uncovered roles for pk1a and pk1b in the epithelial-to-mesenchymal transition (EMT) of pre-migratory NCCs that precedes their collective migration to the periphery. Normally, during EMT, pre-migratory NCCs transition from a neuroepithelial to a bleb-based and subsequently, mesenchymal morphology capable of directed migration. When either Pk1a or Pk1b is disrupted, NCCs continue to perform blebbing behaviors characteristic of pre-migratory cells over extended time periods, indicating a block in a key transition during EMT. Although some Pk1-deficient NCCs transition successfully to mesenchymal, migratory morphologies, they fail to separate from neighboring NCCs. Additionally, Pk1b-deficient NCCs show elevated levels of E-Cadherin and reduced levels of N-Cadherin, suggesting that Prickle1 molecules regulate Cadherin levels to ensure the completion of EMT and the commencement of cranial NCC migration. We conclude that Pk1 plays crucial roles in cranial NCCs both during EMT and migration. These roles are dependent on the regulation of E-Cad and N-Cad.
Measuring Norms and Normative Contestation: The Case of International Criminal Law

One way to tell if an international norm is robust is to assess the breadth of its support from a wide variety of important actors. We argue that to assess norm robustness, we should look at the general beliefs, rhetorical support, and actions of both primary and secondary norm addressees (states and non-state actors) at various levels: international, regional, domestic and local. By way of example, we evaluate the robustness of international criminal law (ICL) norms by looking at the rhetoric and actions of a diverse set of international actors, including not only states and intergovernmental organizations but also ordinary publics, rebel groups, and non-governmental organizations. Assessing evidence of norms beyond states leads us to conclude that the core ICL norms are robust but their practical and institutional applicability are still contested. Contestation over applicability is important and there are hints that it is growing, at least among some key actors, suggesting the possibility of ICL norm decay.