cssi/SciSciGPT-SciSciNet huggingface dataset:
Radially symmetric connections over round spheres

We classify the radially symmetric connections in vector bundles over round spheres by proving that they are all parallel.
LABOR LAWS AND CORPORATE INVESTMENT

Using corporate social responsibility (CSR) scores, we examine the effect of unionization on non-shareholding stakeholders and the value of CSR for unionized firms. We show that unionization leads to lower CSR. The negative relation between unionization and CSR is stronger for financially constrained firms. We address endogeneity issues by controlling for firm characteristics including firm fixed effects, examining a quasi-natural experiment, and using regression discontinuity design examining union certification elections. Lower CSR is associated with higher market values of unionized firms and is more common when CEO and shareholder interests are aligned through compensation contracts.
Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.
Data-driven computing in dynamics

We formulate extensions to Data Driven Computing for both distance minimizing and entropy maximizing schemes to incorporate time integration. Previous works focused on formulating both types of solvers in the presence of static equilibrium constraints. Here formulations assign data points a variable relevance depending on distance to the solution and on maximum-entropy weighting, with distance minimizing schemes discussed as a special case. The resulting schemes consist of the minimization of a suitably-defined free energy over phase space subject to compatibility and a time-discretized momentum conservation constraint. We present selected numerical tests that establish the convergence properties of both types of Data Driven solvers and solutions.
Fast quantum dot single photon source triggered at telecommunications wavelength

We demonstrate a 100 MHz quantum dot single photon source at 900 nm triggered by a telecommunications wavelength laser. The quantum dot is excited by on-chip-generated second harmonic radiation, resonantly enhanced by a photonic nanocavity.
Percutaneous Angiographic Embolization: A Procedure of Increasing Usefulness. Review of a Decade of Experience

Summary During the past decade percutaneous therapeutic vascular occlusion was performed on 152 occasions in 124 patients. The primary indication for vaso-occlusive therapy was acute or recurrent bleeding. Upper gastrointestinal bleeding from arterial sources was controlled in 92 percent of patients and acute variceal bleeding in 83 percent. Renal embolization was performed for palliation of severe pain and hematuria from unresectable renal primary or secondary malignancies, to decrease blood loss and facilitate surgery in operable renal tumors, and for ablation of renal function to control chronic protein loss or severe hypertension. Our encouraging experience convinces us that transcatheter embolization is a useful, safe and effective procedure in selected patients. It seems certain that the technique of therapeutic embolization will be improved, its indications extended and its application become commonplace whenever angiographic skills and facilities exist.
Renal Cell Carcinoma With Vena Cava Extension: Diagnostic and Surgical Features of 41 Cases

Vena cava extension of renal cell carcinoma was diagnosed in 33 men and 8 women, 29 of whom had right-sided and 12 left-sided tumours. Angiography was performed in all and cavography in most patients. Computed tomography was available in 16 cases. The tumour thrombus did not reach the diaphragm in 32 patients, and extended above it in 9 cases. Macroscopically, complete cavathrombectomy was performed in 33 patients. All tumours except one were of high grade type (grades III and IV). Serum creatinine and liver enzymes were normal at the first postoperative check-up. The 5-year-survival rate in patients subjected to complete cavathrombectomy was 24%. The 5-year-survival was 33% in patients whose tumours extended to below the diaphragm, 0% in patients whose tumours extended above the diaphragm (NS), 33% in grade III tumours and 0% in grade IV tumours (NS), 33% in patients without evidence of metastases and 0% in patients with preoperative metastases (NS).
The Role of Analgesic Blocking in the Management of Cancer Pain: Current Trends. A Review Article

The significant role of reversible and neurolytic analgesic blocking in the management of cancer pain in general is presented. It is pointed out that this modality of therapy may play a very significant role in the management of many such patients. It is pointed out that blocks of the peripheral as well as the central nervous system should be considered early rather than late in these disease syndromes in order to prevent central fixation. It is obvious that these procedures should be employed much more extensively than is generally the case at the present time. The opinions expressed are based upon over 30 years of clinical experience and a review of the current literature dealing with the management of pain.
Venography of the Undescended Testis

SUMMARY The data obtained in our study and from the literature suggest the following: (1) A gonadal vein with a pampiniform-like plexus almost always indicates that a testis is present. (2) A blind-ending vein on a technically satisfactory venogram is usually associated with absence of a testis. (3) A gonadal vein or vas deferens may be present without a testis. (4) A testis probably cannot be present without a gonadal vein. (5) A testis cannot be present at a site separate from the termination of a gonadal vein. (6) A blind-ending vas deferens does not necessarily indicate the absence of a testis. (7) A blind-ending vas deferens found in a patient in whom a blind-ending gonadal vein is localized to the same region indicates absence of a testis. Whether gonadal venography is used preoperatively or is reserved for those patients in whom exploration fails to identify a testis, we believe that the presence of a pampiniform-like plexus demonstrated by venography at the peripheral portion of a gonadal vein requires exploration, but that exploration can be limited to the location of the pampiniform-like plexus. Absence of a testicular vein or the presence of a blind-ending vein in the absence of a competent valve may obviate the need for surgical exploration, especially in teenage children or adults. However, the experience of the individual performing the venogram should be considered in deciding how much weight to place on the venographic finding of an absent gonadal vein. Incomplete opacification of a gonadal vein because of a competent valve or any other technical problem cannot be considered in any way predictive of the presence or absence of a testis. Surgical exploration is required, and the only value of the venogram is to indicate that surgical exploration need not be carried out above the level of the opacified portion of the vein. In such a case, if a testis is present, it must be present at the end of the unopacified segment of the vein.
A Critical Review of Immunotherapy of Disseminated Renal Adenocarcinoma

Sixty patients with renal adenocarcinoma have been treated with five different immunotherapy trials consisting of 1) Transfer Factor (TF), 2) TF and Bacillus Calmette-Guerin (BCG), 3) TF, BCG, Chloroethyl-cyclohexy-nitrosurea (CCNU) and megestrol acetate (Megase), 4) BCG, CCNU, and Megase, or 5) BCG. Using strict response criterea for measurable disease, objective responses were seen in 14–22% of cases. While this nonspecific immunotherapy of renal adenocarcinoma has been associated with documented regression of metastases, response rates are similar to that obtained with hormonal therapy alone. Objective responses support the concept of further trials in this disease with more sophisticated immunotherapy.
The transformation function, technical efficiency, and the CCR ratio

Abstract Charnes, Cooper, and Rhodes define the ratio of the virtual output to the virtual input as a measure of the technical efficiency of a multiple output multiple input firm. The aggregation weights used in construction the virtual output and the virtual input may be arbitrarily chosen so long as the weights are non-negative and using these weights no firm's input-output bundle shows efficiency exceeding 100%. In production economics, the ratio of aggregate output to aggregate input is a measure of total factor productivity and a direct link of the Charnes, Cooper, and Rhodes ratio to technical efficiency is not obvious. Usually the ratio measure is rationalized as efficiency by showing its equivalence to the Farrell efficiency measure. This paper offers a direct derivation of the ratio measure of efficiency from a transformation function. We also show how Banker, Charnes, and Cooper measure under variable returns to scale can be derived from the transformation function.
How causal analysis can reveal autonomy in models of biological systems.

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system—whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause–effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause–effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast ( Schizosaccharomyces pombe ) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue ‘Reconceptualizing the origins of life’.
Household Informedness and Long‐Run Inflation Expectations: Experimental Evidence

This article uses an experiment embedded in a survey to analyze the response of consumers' long‐run inflation expectations to information about the Federal Reserve's inflation target and past inflation. On average, respondents revise forecasts toward the 2% target with either information treatment. Forecast uncertainty and heterogeneity decline with the treatments, but remain substantial. Since the information in the treatments is publicly available, these findings are consistent with models of imperfect information in which agents do not fully and continually update their information sets or incorporate all available information into their expectations. Response to treatments varies with prior informedness and with demographic characteristics.
Worse than Baumol's disease: The implications of labor productivity, contracting out, and unionization on transit operation costs

Abstract Unit costs measured as bus operating costs per vehicle mile have increased considerably above the inflation rate in recent decades in most transit agencies in the United States. This paper examines the impact of (lack of) productivity growth, union bargaining power, and contracting out on cost escalation. We draw from a 17-year (1997–2014) and a 415-bus transit agency panel with 5780 observations by type of operation (directly operated by the agency or contracted out). We have three main findings: first, the unit cost increase in the transit sector is far worse than what economic theory predicts for industries with low productivity growth. Second, contracting out tends to reduce unit costs, and the results suggest that the costs savings from private operations can be only partly explained by lower wages in the private sector. Interestingly, we find that the cost savings from contracting out are larger when the transit agency also directly operates part of the total transit service. However, while overall unit costs are lower in contracted services, cost growth in large private bus operators is no different than cost growth in large public transit operators. Third, unique transit labor laws that lead to union bargaining power are a likely driver of the unit cost growth above inflation. Overall, these factors reflect inherent characteristics of the bus transit sector, such as the nature of low productivity growth and union legislative power related to the need for public subsidy. They drive increases in both transit fares and public subsidy at rates higher than inflation, and play an important role in the deterioration of transit agencies’ financial sustainability.
A generalized count model on customers' purchases in O2O market

Abstract In the Online-to-Offline (O2O) ecommerce model, one challenge facing the online business is to predict customers' future purchases towards each product or subcategory of products, and consequently, coordinate the large amount of offline businesses involved. The main obstacle in doing that originates from the highly diversified services and thus the customer base which offline businesses bring in. The heterogeneity of customers, geographic or demographic, needs to be accurately accounted for. However, although the previous transactions for each customer are well documented, his/her demographic data is difficult or costly to acquire. Traditional wisdom relies on fitting customers into some specific statistical distribution to arrive at a satisfactory stochastic model, which may be accurate, to some extent, at a higher level. This is the case for the classic Beta-Binomial/Negative Binomial Distribution (BB/NBD) model on customers' repeat purchasing in offline context. Nevertheless, to deal with the complex level in customers' heterogeneity at an O2O business, using specific distribution is inadequate, let alone the mathematical challenges. We propose a new model to deal with the diversity of customers. Using BB/NBD as a starting point, we relax the Beta assumption in the model to include a generalized distribution. The generalization is made possible through using the Gaussian quadrature. The results retain the elegance of stochastic model while at the same time it captures customers' heterogeneity at a better, granular level. We use a dataset from Ctrip.com , a leading O2O provider in China, to show that the proposed method outperforms the BB/NBD model in both in-sample and out-of-sample predictive performance. Our approach provides a practical solution for O2O practitioners to forecast their future demands.
Supply Disruptions and Optimal Network Structures

This paper studies multitier supply chain networks in the presence of disruption risk. Firms decide how much to source from their upstream suppliers so as to maximize their expected profits, and pr...
Joint energy-bandwidth allocation for multi-user channels with cooperating hybrid energy nodes

In this paper, we consider the energy-bandwidth allocation for a network of multiple users, where the transmitters each powered by both an energy harvester and conventional grid, access the network orthogonally on the assigned frequency band. The tradeoff among the weighted sum throughput, the use of grid energy, and the amount of energy cooperation is studied through an optimization objective which is a linear combination of these quantities. To solve the problem efficiently, an iterative algorithm is proposed using the Proximal Jacobian ADMM. We show that this algorithm converges to the optimal solution with an overall complexity of O(N2K2). Numerical results show that the proposed algorithms can make efficient use of the harvested energy, grid energy, energy cooperation, and the available bandwidth.
Potential role of a ventral nerve cord central pattern generator in forward and backward locomotion in Caenorhabditis elegans

C. elegans locomotes in an undulatory fashion, generating thrust by propagating dorsoventral bends along its body. Although central pattern generators (CPGs) are typically involved in animal locomotion, their presence in C. elegans has been questioned, mainly because there has been no evident circuit that supports intrinsic network oscillations. With a fully reconstructed connectome, the question of whether it is possible to have a CPG in the ventral nerve cord (VNC) of C. elegans can be answered through computational models. We modeled a repeating neural unit based on segmentation analysis of the connectome. We then used an evolutionary algorithm to determine the unknown physiological parameters of each neuron so as to match the features of the neural traces of the worm during forward and backward locomotion. We performed 1,000 evolutionary runs and consistently found configurations of the neural circuit that produced oscillations matching the main characteristic observed in experimental recordings. In addition to providing an existence proof for the possibility of a CPG in the VNC, we suggest a series of testable hypotheses about its operation. More generally, we show the feasibility and fruitfulness of a methodology to study behavior based on a connectome, in the absence of complete neurophysiological details.
Finding almost squares VI

In this paper, we continue the study of almost squares and extend the result of the author’s fourth paper in the series to almost squares with closer factors. We prove that almost all intervals [x,...
Cross‐national variations in industry regulation: A factor analytic approach with an application to telecommunications

This study applies factor analytic techniques to 131 telecommunications regulatory agencies in 80 countries to develop a comparative framework for better understanding the cross-national institutional variation in industrial regulation. While some of these measures are specific to the telecom industry (i.e. World Trade Organization Basic Telecom Agreement participation), most of these regulatory variables can be applied to other regulated industries. After analyzing 30 variables, these techniques identify and quantify six distinct dimensions of industry regulation, namely, the competitive market structure rules, industry standards rules, entry barrier rules, institutional stability, political appointment process, and the regulatory governance structure. Despite the conventional wisdom that suggests the “rules of the game” are key to industry regulation, this study finds that the single largest source of cross-national variation is the level of regulatory institutional stability (accounting for 16 percent of the total variation in cross-national industry regulation). This suggests that more focus and attention should be given to the role formal institutions play in industry regulation. This study also finds differences in industry regulation between developed, developing, and least developed nations. Developed countries on average have significantly higher regulation, with the US being the highest. This suggests that regulation is a critical component of industrial regimes and the competitiveness of developed economies.
A Typological Study of the Recent Development and Landscape of Foundations in China

Foundations in China’s nonprofit sector have been increasing in both number and importance. However, scholarly research and nonacademic reports have left a question in the literature waiting to be answered: What led to the recent development and landscape of foundations in China? To answer this question within the framework of “manufactured civil society,” the typological method was used, in which 3342 foundations founded before 2014 were divided into seven types with regard to their founders and policy-related issues, namely government-created, corporate, school, family, religious, community, and independent. The results show that, to a large degree, (1) the government has been one of the major drivers behind the foundations’ development and (2) the government’s attitude and policy toward foundations have shaped and will continue to shape the foundation landscape in China.
Microscale ecology regulates particulate organic matter turnover in model marine microbial communities.

The degradation of particulate organic matter in the ocean is a central process in the global carbon cycle, the mode and tempo of which is determined by the bacterial communities that assemble on particle surfaces. Here, we find that the capacity of communities to degrade particles is highly dependent on community composition using a collection of marine bacteria cultured from different stages of succession on chitin microparticles. Different particle degrading taxa display characteristic particle half-lives that differ by ~170 h, comparable to the residence time of particles in the ocean’s mixed layer. Particle half-lives are in general longer in multispecies communities, where the growth of obligate cross-feeders hinders the ability of degraders to colonize and consume particles in a dose dependent manner. Our results suggest that the microscale community ecology of bacteria on particle surfaces can impact the rates of carbon turnover in the ocean. Particle-attached bacteria play a key ecosystem role by degrading complex organic materials in the ocean. Here, the authors use model marine microbial communities to show that community composition and interspecies interactions can significantly slowdown the rates of particle turnover in the environment.
Post-crisis regulatory reform in banking: Address insolvency risk, not illiquidity!

Abstract An extensive review of the evidence related to the 2007–09 crisis reveals that it was an insolvency risk crisis, not a liquidity crisis. The appropriate post-crisis regulatory reform should therefore focus on increasing capital requirements. The Basel III liquidity requirements do not serve a useful economic purpose in dealing with the root causes of the stresses that led to the 2007–09 crisis, and unnecessarily constrain the asset transformation and liquidity creation roles of banks to the detriment of economic growth.
Cross-feeding modulates antibiotic tolerance in bacterial communities.

Microbes frequently rely on metabolites excreted by other bacterial species, but little is known about how this cross-feeding influences the effect of antibiotics. We hypothesized that when species rely on each other for essential metabolites, the minimum inhibitory concentration (MIC) for all species will drop to that of the “weakest link”—the species least resistant in monoculture. We tested this hypothesis in an obligate cross-feeding system that was engineered between Escherichia coli, Salmonella enterica, and Methylobacterium extorquens. The effect of tetracycline and ampicillin were tested on both liquid and solid media. In all cases, resistant species were inhibited at significantly lower antibiotic concentrations in the cross-feeding community than in monoculture or a competitive community. However, deviation from the “weakest link” hypothesis was also observed in cross-feeding communities apparently as result of changes in the timing of growth and cross-protection. Comparable results were also observed in a clinically relevant system involving facultative cross-feeding between Pseudomonas aeruginosa and an anaerobic consortium found in the lungs of cystic fibrosis patients. P. aeruginosa was inhibited by lower concentrations of ampicillin when cross-feeding than when grown in isolation. These results suggest that cross-feeding significantly alters tolerance to antibiotics in a variety of systems.
Examination of Signatures of Recent Positive Selection on Genes Involved in Human Sialic Acid Biology

Sialic acids are nine carbon sugars ubiquitously found on the surfaces of vertebrate cells and are involved in various immune response-related processes. In humans, at least 58 genes spanning diverse functions, from biosynthesis and activation to recycling and degradation, are involved in sialic acid biology. Because of their role in immunity, sialic acid biology genes have been hypothesized to exhibit elevated rates of evolutionary change. Consistent with this hypothesis, several genes involved in sialic acid biology have experienced higher rates of non-synonymous substitutions in the human lineage than their counterparts in other great apes, perhaps in response to ancient pathogens that infected hominins millions of years ago (paleopathogens). To test whether sialic acid biology genes have also experienced more recent positive selection during the evolution of the modern human lineage, reflecting adaptation to contemporary cosmopolitan or geographically-restricted pathogens, we examined whether their protein-coding regions showed evidence of recent hard and soft selective sweeps. This examination involved the calculation of four measures that quantify changes in allele frequency spectra, extent of population differentiation, and haplotype homozygosity caused by recent hard and soft selective sweeps for 55 sialic acid biology genes using publicly available whole genome sequencing data from 1,668 humans from three ethnic groups. To disentangle evidence for selection from confounding demographic effects, we compared the observed patterns in sialic acid biology genes to simulated sequences of the same length under a model of neutral evolution that takes into account human demographic history. We found that the patterns of genetic variation of most sialic acid biology genes did not significantly deviate from neutral expectations and were not significantly different among genes belonging to different functional categories. Those few sialic acid biology genes that significantly deviated from neutrality either experienced soft sweeps or population-specific hard sweeps. Interestingly, while most hard sweeps occurred on genes involved in sialic acid recognition, most soft sweeps involved genes associated with recycling, degradation and activation, transport, and transfer functions. We propose that the lack of signatures of recent positive selection for the majority of the sialic acid biology genes is consistent with the view that these genes regulate immune responses against ancient rather than contemporary cosmopolitan or geographically restricted pathogens.
Computable performance guarantees for compressed sensing matrices

The null space condition for l1 minimization in compressed sensing is a necessary and sufficient condition on the sensing matrices under which a sparse signal can be uniquely recovered from the observation data via l1 minimization. However, verifying the null space condition is known to be computationally challenging. Most of the existing methods can provide only upper and lower bounds on the proportion parameter that characterizes the null space condition. In this paper, we propose new polynomial-time algorithms to establish upper bounds of the proportion parameter. We leverage on these techniques to find upper bounds and further develop a new procedure—tree search algorithm—that is able to precisely and quickly verify the null space condition. Numerical experiments show that the execution speed and accuracy of the results obtained from our methods far exceed those of the previous methods which rely on linear programming (LP) relaxation and semidefinite programming (SDP).
Synaptogenesis Is Modulated by Heparan Sulfate in Caenorhabditis elegans

The nervous system regulates complex behaviors through a network of neurons interconnected by synapses. How specific synaptic connections are genetically determined is still unclear. Male mating is the most complex behavior in Caenorhabditis elegans It is composed of sequential steps that are governed by > 3000 chemical connections. Here, we show that heparan sulfates (HS) play a role in the formation and function of the male neural network. HS, sulfated in position 3 by the HS modification enzyme HST-3.1/HS 3-O-sulfotransferase and attached to the HS proteoglycan glypicans LON-2/glypican and GPN-1/glypican, functions cell-autonomously and nonautonomously for response to hermaphrodite contact during mating. Loss of 3-O sulfation resulted in the presynaptic accumulation of RAB-3, a molecule that localizes to synaptic vesicles, and disrupted the formation of synapses in a component of the mating circuits. We also show that the neural cell adhesion protein NRX-1/neurexin promotes and the neural cell adhesion protein NLG-1/neuroligin inhibits the formation of the same set of synapses in a parallel pathway. Thus, neural cell adhesion proteins and extracellular matrix components act together in the formation of synaptic connections.
Knowledge of Zika and perception of risk among sexually-active adults in the United States of America: results from a nationally representative sample.

ABSTRACT Objective To examine knowledge of Zika transmission and risk perception and to assess variability by condom use in a probability sample of sexually-active adults in the United States. Methods Data for this study came from the 2016 wave of the National Survey of Sexual Health and Behavior, a nationally representative probability sample of adults in the United States. Data were collected in November 2016 via a cross-sectional Internet-based survey administered to members of a Knowledge Panel, an address-based random sample service managed by GfK. A weighted subsample (n = 1 713) of sexually active adults, 18 – 50 years of age, was included in analyses. Results More than 90% of men and women reported low or no perceived risk of Zika. Most participants identified mosquito bite as a route of transmission, while significantly fewer identified sexual intercourse (≈ 40%) and vertical (29% men, 41% women) transmission routes. Conclusion Sexually-active adults in the United States, especially young men, lack awareness of sexual and vertical transmission of Zika Virus. Given the likely endemic nature of Zika, this low-risk perception is an important prevention challenge. Zika prevention messaging should address lesser known transmission routes, emphasize male education, and promote correct and consistent condom use.
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks Using Stochastic Computing

Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success in many machine learning applications. Nevertheless, the deep structure has brought significant increases in computation complexity. Largescale deep learning systems mainly operate in high-performance server clusters, thus restricting the application extensions to personal or mobile devices. Previous works on GPU and/or FPGA acceleration for DCNNs show increasing speedup, but ignore other constraints, such as area, power, and energy. Stochastic Computing (SC), as a unique data representation and processing technique, has the potential to enable the design of fully parallel and scalable hardware implementations of large-scale deep learning systems. This paper proposed an automatic design allocation algorithm driven by budget requirement considering overall accuracy performance. This systematic method enables the automatic design of a DCNN where all design parameters are jointly optimized. Experimental results demonstrate that proposed algorithm can achieve a joint optimization of all design parameters given the comprehensive budget of a DCNN.
Cone synapses in mammalian retinal rod bipolar cells.

Some mammalian rod bipolar cells (RBCs) can receive excitatory chemical synaptic inputs from both rods and cones (DBCR2 ), but anatomical evidence for mammalian cone-RBC contacts has been sparse. We examined anatomical cone-RBC contacts using neurobiotin (NB) to visualize individual mouse cones and standard immuno-markers to identify RBCs, cone pedicles and synapses in mouse and baboon retinas. Peanut agglutinin (PNA) stained the basal membrane of all cone pedicles, and mouse cones were positive for red/green (R/G)-opsin, whereas baboon cones were positive for calbindin D-28k. All synapses in the outer plexiform layer were labeled for synaptic vesicle protein 2 (SV2) and PSD (postsynaptic density)-95, and those that coincided with PNA resided closest to bipolar cell somas. Cone-RBC synaptic contacts were identified by: (a) RBC dendrites deeply invaginating into the center of cone pedicles (invaginating synapses), (b) RBC dendritic spines intruding into the surface of cone pedicles (superficial synapses), and (c) PKCα immunoreactivity coinciding with synaptic marker SV2, PSD-95, mGluR6, G protein beta 5 or PNA at cone pedicles. One RBC could form 0-1 invaginating and 1-3 superficial contacts with cones. 20.7% and 38.9% of mouse RBCs contacted cones in the peripheral and central retina (p .05). In baboon retinas (n = 4 samples), cone-RBC contacts involved 12.2% of RBCs (n = 416 cells) and 22.5% of cones (n = 225 cells). This suggests that rod and cone signals in the ON pathway are integrated in some RBCs before reaching AII amacrine cells.
What Can Machines Learn, and What Does It Mean for Occupations and the Economy?

Advances in machine learning (ML) are poised to transform numerous occupations and industries. This raises the question of which tasks will be most affected by ML. We apply the rubric evaluating task potential for ML in Brynjolfsson and Mitchell (2017) to build measures of "Suitability for Machine Learning" (SML) and apply it to 18,156 tasks in O*NET. We find that (i) ML affects different occupations than earlier automation waves; (ii) most occupations include at least some SML tasks; (iii) few occupations are fully automatable using ML; and (iv) realizing the potential of ML usually requires redesign of job task content.
Learning Hope and Optimism: Classmate Experiences and Adolescent Development

This article explores individual and contextual factors related to the development of hopeful attitudes during adolescence using a nationally representative study. A key focus is on the experiences...
Removing contaminants from databases of draft genomes

Metagenomic sequencing of patient samples is a very promising method for the diagnosis of human infections. Sequencing has the ability to capture all the DNA or RNA from pathogenic organisms in a human sample. However, complete and accurate characterization of the sequence, including identification of any pathogens, depends on the availability and quality of genomes for comparison. Thousands of genomes are now available, and as these numbers grow, the power of metagenomic sequencing for diagnosis should increase. However, recent studies have exposed the presence of contamination in published genomes, which when used for diagnosis increases the risk of falsely identifying the wrong pathogen. To address this problem, we have developed a bioinformatics system for eliminating contamination as well as low-complexity genomic sequences in the draft genomes of eukaryotic pathogens. We applied this software to identify and remove human, bacterial, archaeal, and viral sequences present in a comprehensive database of all sequenced eukaryotic pathogen genomes. We also removed low-complexity genomic sequences, another source of false positives. Using this pipeline, we have produced a database of "clean" eukaryotic pathogen genomes for use with bioinformatics classification and analysis tools. We demonstrate that when attempting to find eukaryotic pathogens in metagenomic samples, the new database provides better sensitivity than one using the original genomes while offering a dramatic reduction in false positives.
The ecological impact of transportation infrastructure

There is a long-standing debate over whether new roads unavoidably lead to environmental damage, especially forest loss, but causal identification has been elusive. Using multiple causal identification strategies, this paper studies the construction of new rural roads to over 100,000 villages and the upgrading of 10,000 kilometers of national highways in India. The new rural roads had precise zero effects on local deforestation. In contrast, the highway upgrades caused substantial forest loss, which appears to be driven by increased timber demand along the transportation corridors. In terms of forests, last mile connectivity had a negligible environmental cost, while expansion of major corridors had important environmental impacts.
Falling rates of marijuana dependence among heavy users.

Introduction Marijuana use has become increasingly popular in the United States since the turn of the century, and typical use patterns among current marijuana users have intensified, raising concerns for an increase in cannabis use disorders (CUDs). Yet the population prevalence of CUDs has mostly remained flat. We analyzed trends in DSM-IV marijuana dependence among Daily/Near-Daily (DND) users, both overall and by age and gender, and considered potential explanations. Methods Using data assembled from the National Survey on Drug Use and Health (2002-2016), rates of self-reported dependence and constituent symptoms are calculated for DND marijuana users; logistic regressions with pre- and post- periods (2002-2004, 2014-2016) are applied to describe temporal changes. Results Dependence among DND users fell by 39% (26.5%-16.1%; p<0.001). No significant change is detected at the population level. Sub-group analysis shows a steep gradient for age but not for gender. Declines are robust to sub-group analysis, except for users over 50 years old. Among dependence symptoms, most showed significant declines: giving up important activities (p<0.001); continued use despite emotional, mental, or physical problems (p<0.001); failing attempts to reduce use (p<0.001); spending lots of time getting, using, or getting over marijuana (p<0.01); and failing to keep limits set on use (p<.05). Reported tolerance showed no significant change. Conclusions Though it is unclear why, the risk of dependence formation among heavy marijuana users appear to have declined substantially since 2002. Further research is warranted to search for explanations related to state marijuana policies, product forms, or social context.
What Are We Talking about When We Talk about Digital Protectionism

For almost a decade, executives, scholars, and trade diplomats have argued that filtering, censorship, localization requirements, and domestic regulations are distorting the cross-border information flows that underpin the internet. Herein I use process tracing to examine the state and implications of digital protectionism. I make five points: First, I note that digital protectionism differs from protectionism of goods and other services. Information is intangible, highly tradable, and some information is a public good. Secondly, I argue that it will not be easy to set international rules to limit digital protectionism without shared norms and definitions. Thirdly, the US, EU, and Canada have labeled other countries policies’ protectionist, yet their arguments and actions sometimes appear hypocritical. Fourth, I discuss the challenge of Chinese failure to follow key internet governance norms. China allegedly has used a wide range of cyber strategies, including distributed denial of service (DDoS) attacks (bombarding a web site with service requests) to censor information flows and impede online market access beyond its borders. WTO members have yet to discuss this issue and the threat it poses to trade norms and rules. Finally, I note that digital protectionism may be self-defeating. I then draw conclusions and make policy recommendations.
Disagreement, Anti-Realism about Reasons, and Inference to the Best Explanation

I defend an inference to the best explanation (IBE) argument for anti-realism about reasons for acting based on the history of intractable disagreement in moral philosophy. The four key premises of the argument are: 1. If there were objective reasons for action, epistemically-well-situated observers would eventually converge upon them after two thousand years; 2. Contemporary philosophers, as the beneficiaries of two thousand years of philosophy, are epistemically well-situated observers; 3. Contemporary philosophers have not converged upon reasons for action; 4. Conclusion: there are no objective reasons for action (IBE from the first three premises). The key premises of the IBE are (1) sentimentalism; (2) non-cognitivism about basic affects; and (3) philosophical arguments for what our reasons for action are always involve arguments that depend on a basic intuitive moral judgment (that can be explained in terms of a basic non-cognitive affect). All these premises are explored in detail, and various objections addressed.
Evidence of the Relationship between PCAOB Inspection Outcomes and the Use of Structured Audit Technologies

SUMMARY We investigate the relationship between Public Company Accounting Oversight Board (PCAOB) inspection outcomes and auditors' use of structured audit technologies (SATs) by conducting intervi...
Remarks on joint commitment and its relation to moral thinking

Tomasello contends that the emergence of joint commitment is a decisive step in the development of human moral thinking. I delineate the nature and normativity of joint commitment as I understand i...
A Non-Docking Intraoperative Electron Beam Applicator System

A non-docking intraoperative radiation therapy electron beam applicator system for a linear accelerator has been designed to minimize the mechanical, electrical, and tumor visualization problems associated with a docking system. A number of technical innovations have been used in the design of this system. These include: (a) a new intraoperative radiation therapy cone design that gives a better dose uniformity in the treatment volume at all depths; (b) a collimation system which reduces the leakage radiation dose to tissues outside the intraoperative radiation therapy cone; (c) a non-docking system with a translational accuracy of 2 mm and a rotational accuracy of 0.5 degrees; and (d) a rigid clamping system for the cones. A comprehensive set of dosimetric characteristics of the intraoperative radiation therapy applicator system is presented.
Distorting an Adversary's View in Cyber-Physical Systems

In Cyber- Physical Systems (CPSs), inference based on communicated data is of critical significance as it can be used to manipulate or damage the control operations by adversaries. This calls for efficient mechanisms for secure transmission of data since control systems are becoming increasingly distributed over larger geographical areas. Distortion based security, recently proposed as one candidate for CPSs security, is not only more appropriate for these applications but also quite frugal in terms of prior requirements on shared keys. In this paper, we propose distortion-based metrics to protect CPSs communication and show that it is possible to confuse adversaries with just a few bits of pre-shared keys.
dynamicMF: A Matrix Factorization Approach to Monitor Resource Usage in High Performance Computing Systems

High performance computing (HPC) facilities consist of a large number of interconnected computing units (or nodes) that execute highly complex scientific simulations to support scientific research. Monitoring such facilities, in real-time, is essential to ensure that the system operates at peak efficiency. Such systems are typically monitored using a variety of measurements and log data which capture the state of the various components within the system at regular intervals of time. As modern HPC systems grow in capacity and complexity, the data produced by current resource monitoring tools at a scale that is no longer feasible to be visually monitored by analysts. We propose a method that transforms the multidimensional output of resource monitoring tools to a low dimensional representation that facilitates the understanding of the behavior of a High Performance Computing (HPC) system. The proposed method automatically extracts the low-dimensional signal in the data which can be used to track the system efficiency and identify performance anomalies. The method models the resource usage data as a three dimensional tensor (capturing resource usage of all compute nodes for different resources over time). A dynamic matrix factorization algorithm, called dynamicMF, is proposed to extract a low-dimensional temporal signal for each node, which is subsequently fed into an anomaly detector. Results on resource usage data show anomalies identified which are correlated with anomalous events identified over the syslog messages.
A New Model of Human Needs as the Foundation for Innovation Management

A basic synergy requirement is for the participants to jointly perceive sufficient values in their respective investments. Specifically, it is a balance between the perceived direct expected values generated by their investments and the perceived expected risks of losing the investments. Value arises from human need fulfillment and risks relates to the probability of not fulfilling these needs. Thus, understanding of human needs provides a foundation for effective innovation management, as it helps determine motivations for participation and perceiving synergistic values and risks in the innovation implementation process by these major participants.
A Chebyshev-Accelerated Primal-Dual Method for Distributed Optimization

We consider a distributed optimization problem over a network of agents aiming to minimize a global objective function that is the sum of local convex and composite cost functions. To this end, we propose a distributed Chebyshev-accelerated primal-dual algorithm to achieve faster ergodic convergence rates. In standard distributed primal-dual algorithms, the speed of convergence towards a global optimum (i.e., a saddle point in the corresponding Lagrangian function) is directly influenced by the eigenvalues of the Laplacian matrix representing the communication graph. In this paper, we use Chebyshev matrix polynomials to generate gossip matrices whose spectral properties result in faster convergence speeds, while allowing for a fully distributed implementation. As a result, the proposed algorithm requires fewer gradient updates at the cost of additional rounds of communications between agents. We illustrate the performance of the proposed algorithm in a distributed signal recovery problem. Our simulations show how the use of Chebyshev matrix polynomials can be used to improve the convergence speed of a primal-dual algorithm over communication networks, especially in networks with poor spectral properties, by trading local computation by communication rounds.