cssi/SciSciGPT-SciSciNet huggingface dataset:
Healthedge: Task Scheduling for Edge Computing with Health Emergency and Human Behavior Consideration in Smart Homes

Nowadays, a large amount of services are deployed on the edge of the network from the cloud since processing data at the edge can reduce response time and lower bandwidth cost for applications such as healthcare in smart homes. Resource management is very important in the edge computing since it is able to increase the system efficiency and improve the quality of service. A common approach for resource management in edge computing is to assign tasks to the remote cloud or edge devices just according to several factors such as energy, bandwidth consumption, and latency. However, the approach is insufficiently efficient and falls short in meeting the requirements of handling health emergency when being applied in smart homes for healthcare. Possible health emergency needs immediate attention and different health tasks have different priorities to be processed. In this paper, we propose a task scheduling approach called HealthEdge that sets different processing priorities for different tasks based on the collected data on human health status and determines whether a task should run in a local device or a remote cloud in order to reduce its total processing time as much as possible. Based on a real trace from five patients, we conduct a trace-driven experiment to evaluate the performance of HealthEdge in comparison with other methods. The results show that HealthEdge can optimally assign tasks between the network edge and cloud, which can reduce the task processing time, reduce bandwidth consumption and increase local edge workstation utilization.
Evaluation of Several Molybdenum and Ruthenium Catalysts for the Metathesis Homocoupling of 3-Methyl-1-Butene

We synthesized Mo(NC6F5)(CHCMe2Ph)(TPPO)(PPhMe2)Cl (TPPO = 2,3,5,6-tetraphenylphenoxide), Mo(NC6F5)(CHCMe2Ph)(TTBTO)(PPhMe2)Cl (TTBTO = 2,6-di(3’,5’-di-tert-butylphenyl)phenoxide), and Mo(NC6F5)(CHCMe2Ph)(TPPO)(PPhMe2)(CF3Pyr) (CF3Pyr = 3,4-bistrifluoromethylpyrrolide), in order to evaluate them as catalysts for the homocoupling of 3-methyl-1-butene. They were compared with Mo(NC6F5)(CHCMe2Ph)(HMTO)(PPhMe2)Cl (HMTO = 2,6-dimesitylphenoxide), Mo(NC6F5)(CHCMe2Ph)(HIPTO)(PPhMe2)Cl (HIPTO = 2,6-di(2’,4’,6’-triisopropylphenyl)phenoxide), and several other Mo and Ru catalysts. In the best cases turnover numbers (TONs) of 400-700 were observed for the homocoupling of 3-methyl-1-butene in a closed vessel (ethylene not removed). This article is protected by copyright. All rights reserved.
Recurrent glioma clinical trial, CheckMate-143: the game is not over yet

// Anna C. Filley 1 , Mario Henriquez 1 and Mahua Dey 1 1 Department of Neurosurgery, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, USA Correspondence to: Mahua Dey, email: mdey@iu.edu Keywords: gliolastoma, checkpoint inhibitor, PD-1/PD-L1, malignant glioma, immunotherapy Received: July 13, 2017 Accepted: September 08, 2017 Published: October 06, 2017 ABSTRACT Glioblastoma (GBM) is the most common, and aggressive, primary brain tumor in adults. With a median patient survival of less than two years, GBM represents one of the biggest therapeutic challenges of the modern era. Even with the best available treatment, recurrence rates are nearly 100% and therapeutic options at the time of relapse are extremely limited. Nivolumab, an anti-programmed cell death-1 (PD-1) monoclonal antibody, has provided significant clinical benefits in the treatment of various advanced cancers and represented a promising therapy for primary and recurrent GBM. CheckMate 143 (NCT 02017717) was the first large randomized clinical trial of PD pathway inhibition in the setting of GBM, including a comparison of nivolumab and the anti-VEGF antibody, bevacizumab, in the treatment of recurrent disease. However, preliminary results, recently announced in a WFNOS 2017 abstract, demonstrated a failure of nivolumab to prolong overall survival of patients with recurrent GBM, and this arm of the trial was prematurely closed. In this review, we discuss the basic concepts underlying the rational to target PD pathway in GBM, address implications of using immune checkpoint inhibitors in central nervous system malignancies, provide a rationale for possible reasons contributing to the failure of nivolumab to prolong survival in patients with recurrent disease, and analyze the future role of immune checkpoint inhibitors in the treatment of GBM.
Tiered Cloud Storage via Two-Stage, Latency-Aware Bidding

In cloud storage, the digital data is stored in logical storage pools, backed by heterogeneous physical storage media and computing infrastructure that are managed by a cloud service provider (CSP). One of the key advantages of cloud storage is its elastic pricing mechanism, in which the users need only pay for the resources/services they actually use, e.g., depending on the storage capacity consumed, the number of file accesses per month, and the negotiated service level agreement. To balance the tradeoff between service performance and cost, CSPs often employ different storage tiers, for instance, cold storage and hot storage. Storing data in hot storage incurs high storage cost yet delivers low access latency, whereas cold storage is able to inexpensively store massive amounts of data and thus provides lower cost with higher latency. In this paper, we address a major challenge confronting the CSPs utilizing such tiered storage architecture—how to maximize their overall profit over a variety of storage tiers that offer distinct characteristics, as well as file placement and access request scheduling policies. To this end, we propose a scheme where the CSP offers a two-stage auction process for: 1) requesting storage capacity and 2) requesting accesses with latency requirements. Our two-stage bidding scheme provides a hybrid storage and access optimization framework with the objective of maximizing the CSP’s total net profit over four dimensions: file acceptance decision, placement of accepted files, file access decision and access request scheduling policy. The proposed optimization is a mixed-integer nonlinear program that is hard to solve. We propose an efficient heuristic to relax the integer optimization and to solve the resulting nonlinear stochastic programs. The algorithm is evaluated under different scenarios and with different storage system parameters, and insightful numerical results are reported by comparing the proposed approach with other profit-maximization models. We see a profit increase of over 60% of our proposed method compared to other baseline algorithms in certain simulation scenarios.
Economic Sanctions and Public Opinion: Survey Experiments From Russia:

Do economic sanctions turn the public against the target government or cause it to rally around the flag? How do sanctions affect attitudes toward the sanctioner? How does bad economic performance ...
Candidate lethal haplotypes and causal mutations in Angus cattle.

If unmanaged, high rates of inbreeding in livestock populations adversely impact their reproductive fitness. In beef cattle, historical selection strategies have increased the frequency of several segregating fatal autosomal recessive polymorphisms. Selective breeding has also decreased the extent of haplotypic diversity genome-wide. By identifying haplotypes for which homozygotes are not observed but would be expected based on their frequency, candidates for developmentally lethal recessive loci can be localized. This analysis comes without the need for observation of the loss-associated phenotype (e.g., failure to implant, first trimester abortion, deformity at birth). In this study, haplotypes were estimated for 3961 registered Angus individuals using 52,545 SNP loci using findhap v2, which exploited the complex pedigree among the individuals in this population. Seven loci were detected to possess haplotypes that were not observed in homozygous form despite a sufficiently high frequency and pedigree-based expectation of homozygote occurrence. These haplotypes were identified as candidates for harboring autosomal recessive lethal alleles. Of the genotyped individuals, 109 were resequenced to an average 27X depth of coverage to identify putative loss-of-function alleles genome-wide and had variants called using a custom in-house developed pipeline. For the candidate lethal-harboring haplotypes present in these bulls, sequence-called genotypes were used to identify concordant variants. In addition, whole-genome sequence imputation of variants was performed into the set of 3961 genotyped animals using the 109 resequenced animals to identify candidate lethal recessive variants at the seven loci. Following the imputation, no variants were identified that were fully concordant with the marker-based diplotypes. Selective breeding programs could utilize the predicted lethal haplotypes associated with SNP genotypes. Sequencing and other methods for identifying the causal variants underlying these haplotypes can allow for more efficient methods of management such as gene editing. These two methods in total will reduce the negative impacts of inbreeding on fertility and maximize overall genetic gains.
Interactions Between Diet and the Intestinal Microbiota Alter Intestinal Permeability and Colitis Severity in Mice

Abstract Background & Aims It is not clear how the complex interactions between diet and the intestinal microbiota affect development of mucosal inflammation or inflammatory bowel disease. We investigated interactions between dietary ingredients, nutrients, and the microbiota in specific pathogen-free (SPF) and germ-free (GF) mice given more than 40 unique diets; we quantified individual and synergistic effects of dietary macronutrients and the microbiota on intestinal health and development of colitis. Methods C56BL/6J SPF and GF mice were placed on custom diets containing different concentrations and sources of protein, fat, digestible carbohydrates, and indigestible carbohydrates (fiber). After 1 week, SPF and germ-free mice were given dextran sulfate sodium (DSS) to induce colitis. Disease severity was determined based on the percent weight change from baseline, and modeled as a function of the concentration of each macronutrient in the diet. In unchallenged mice, we measured intestinal permeability by feeding mice labeled dextran and measuring levels in blood. Feces were collected and microbiota were analyzed by 16S rDNA sequencing. We collected colons from mice and performed transcriptome analyses. Results Fecal microbiota varied with diet; the concentration of protein and fiber had the strongest effect on colitis development. Among 9 fiber sources tested, psyllium, pectin, and cellulose fiber reduced the severity of colitis in SPF mice, whereas methylcellulose increased severity. Increasing dietary protein increased the density of the fecal microbiota and the severity of colitis in SPF mice, but not in GF mice or mice given antibiotics. Psyllium fiber reduced the severity of colitis through microbiota-dependent and microbiota-independent mechanisms. Combinatorial perturbations to dietary casein protein and psyllium fiber in parallel accounted for most variation in gut microbial density and intestinal permeability in unchallenged mice, as well as the severity of DSS-induced colitis; changes in 1 ingredient could be offset by changes in another. Conclusions In an analysis of the effects of different dietary components and the gut microbiota on mice with and without DSS-induced colitis, we found complex mixtures of nutrients affect intestinal permeability, gut microbial density, and development of intestinal inflammation.
DISCOVERY AND INTERPRETATION OF AN X-RAY PERIOD IN THE GALACTIC CENTER SOURCE CXOGC J174536.1-285638

We present X-ray and infrared observations of the X-ray source CXOGC J174536.1–285638. Previous observations suggest that this source may be an accreting binary with a high-mass donor (HMXB) or a colliding wind binary (CWB). Based on the Chandra and XMM-Newton light curve, we have found an apparent 189 ± 6 day periodicity with better than 99.997% confidence. We discuss several possible causes of this periodicity, including both orbital and superorbital interpretations. We explore in detail the possibility that the X-ray modulation is related to an orbital period and discuss the implications for two scenarios; one in which the variability is caused by obscuration of the X-ray source by a stellar wind, and the other in which it is caused by an eclipse of the X-ray source. We find that in the first case, CXOGC J174536.1–285638 is consistent with both CWB and HMXB interpretations, but in the second, CXOGC J174536.1–285638 is more likely a HMXB.
Behavioral Efficient Markets

Discussions about market efficiency in finance are unfocused when they fail to distinguish between the price-equals-value market hypothesis and the hard-to-beat market hypothesis. And discussions are further lacking when they fail to explain why so many investors believe that markets are easy to beat when, in truth, they are hard to beat. The author explains how behavioral finance contributes positively to these discussions by making the distinction between the price-equals-value market hypothesis and the hard-to-beat market hypothesis and by explaining why so many investors believe that markets are easy to beat when that is actually hard to do. Behavioral finance concludes that markets are not price-equals-value markets but they are rather hard-to-beat for investors lacking exclusively or narrowly-available information. And behavioral finance elucidates the cognitive and emotional errors that mislead investors with nothing but widely-available information into the belief that markets are easy to beat.
Crystallographic observation of nonenzymatic RNA primer extension.

Enzymes speed up chemical reactions that are essential to life. Most enzymes are proteins, but some are molecules of ribonucleic acid or RNA. Like DNA, RNA is made from a chain of building blocks called nucleotides. In modern organisms, protein-based enzymes build RNAs by linking nucleotides together, while the building blocks of proteins are linked by an RNA-based enzyme at the heart of a structure called a ribosome. The earliest life on Earth most likely relied only on RNA-based enzymes, but during the emergence of life, scientists believe that RNA molecules must have replicated spontaneously before dedicated RNA-based enzymes had evolved. How RNA could replicate without enzymes has been a puzzle for decades. Recently, scientists discovered a previously unsuspected chemical intermediate that forms during the process, and hypothesized that this molecule’s special structure is what enables the chemical reaction that adds new nucleotides to a growing strand of RNA. To test this hypothesis, Zhang et al. diffused free RNA nucleotides into a crystalized complex containing template strands of RNA attached to short pieces of RNA called primers, which kick-start replication. Then, the crystals were frozen at various intervals and viewed using X-rays. This allowed Zhang et al. to observe the structural changes that occurred over time as the compounds reacted. The approach first revealed that the free nucleotides had paired with complementary nucleotides on the RNA template strands. Then, pairs of free nucleotides reacted with each other to form the intermediate. Finally, the intermediate reacted with the primer, forming a new bond that connects the RNA primer to one of the nucleotides of the intermediate, while the other nucleotide of the intermediate was released as a free nucleotide. This experiment confirms that the specific structure of the intermediate molecule promotes RNA replication without help from enzymes. These findings will benefit chemists and biologists who study how RNA evolves and replicates. Future research building upon this work will deepen scientific understanding of the environmental conditions that were required for life to appear on Earth.
Exchange Rate Targeting and Gold Demand by Central Banks: Modeling International Reserves Composition

ABSTRACTThis article explores the composition of international reserves under a central bank’s exchange rate policy target. The model allows for numerical estimation of a shadow price of the target...
Managerial flexibility in levelized cost measures: A framework for incorporating uncertainty in energy investment decisions

Abstract Many irreversible long-run capital investments entail opportunities for managers to respond flexibly to changes in the economic environment. However, common levelized cost measures used to guide decision-making, such as the levelized cost of electricity, implicitly assume that the values of random economic variables are known with certainty when investment decisions are made. This assumption implies, often incorrectly, that managerial flexibility carries zero value. This paper improves levelized cost measures by deriving an expansion that accounts for both uncertainties in relevant variables and the value of managerial flexibility in responding to them. This method is applied to quantify the value of flexibility in two example decision problems. In one, an operator of a natural gas electricity generation facility evaluates whether to invest in carbon capture capabilities. Another considers retirement decisions for U.S. nuclear plants. These examples illustrate that simplified cost metrics can inaccurately guide decision-making by inflating cost estimates relative to the proposed levelized cost measure that accounts for uncertainty and flexibility.
Synthetic and Other Drug Use among High School Students: The Role of Perceived Prevalence, Access, and Harms.

Background: Synthetic and other drugs have become available to teens, yet little is known about risk factors of use. Objective: To examine adolescent use of one class of synthetic drugs and its ass...
Effect of mobility and convection-dominated flow on evaluation of reservoir dynamic performance by fast marching method

The determination of optimum well locations and number of wells needed during green field development always comes with unprecedented challenges because of the geological uncertainty, and the non-linear relationship between the input and output variables associated with real reservoirs. These variables are key sources affecting the viability and validity of the results. Reservoir simulation is one of the least uncertain and most reliable prediction tools for dynamic performance of any reservoir. As field development progresses, more information becomes available, enabling us to continually update and, if needed, correct the reservoir description. The simulator can then be used to perform a variety of exercises or scenarios, with the goal of optimizing field development and operation strategies. Optimizing well numbers or locations under such geological uncertainty is achieved by using a reservoir simulator under several geological realizations, and these require multiple reservoir simulations to estimate the field performance for a given well configuration at a given location. Using reservoir simulation becomes impractical when dealing with real field cases incorporating multi-million cells because of the associated CPU demand constraints (Bouzarkouna et al. 2011). For instance, to determine the optimum well locations in a giant field that will result in the most efficient production rate scenario, one requires a large number of simulation runs for different realizations and well configurations. A large amount of runs is technically difficult to achieve even if we have access to super computers. The fast marching method (FMM), which is based on a solution of Eikonal equation, can be used to find the optimum well locations in a green oil field by tracking the pressure distribution in the reservoir. The FMM will enable us to calculate the radius of investigation or pressure front as a function of time without running any simulation and with a high degree of accuracy under primary depletion conditions. The main purpose of this paper is to study the effect of mobility on FMM and extend the investigation of its validity to include two-phase flow and convection-dominated flow and evaluate the ability of the methodology to predict the dynamic performance of the reservoir during pseudo-steady-state flow regime.
Mutual Information, Relative Entropy and Estimation Error in Semi-Martingale Channels

Fundamental relations between information and estimation have been established in the literature for the continuous time Gaussian and Poisson channels. In this paper, we demonstrate that such relations hold for a much larger family of continuous-time channels. We introduce the family of semi-martingale channels where the channel output is a semi-martingale stochastic process, and the channel input modulates the characteristics of the semi-martingale. For these channels, which includes as a special case the continuous time Gaussian and Poisson models, we establish new representations relating the mutual information between the channel input and output to an optimal causal filtering loss, thereby unifying and considerably extending results from the Gaussian and Poisson settings. Extensions to the setting of mismatched estimation are also presented where the relative entropy between the laws governing the output of the channel under two different input distributions is equal to the cumulative difference between the estimation loss incurred by using the mismatched and optimal causal filters, respectively. The main tool underlying these results is the Doob–Meyer decomposition of a class of sub-martingales. The results in this paper can be viewed as the continuous-time analogues of recent generalizations for relations between information and estimation for discrete-time Levy channels.
Organizational Constructs: An Approach to Understanding Organizations

Outlines the essence of an approach for understanding the functioning of formal organizations. Nature of organizational constructs; Problems in studying constructs; Description of the study of an o...
Energy Conservation via Hydrogen Cycling in the Methanogenic Archaeon Methanosarcina barkeri.

ABSTRACT Energy conservation via hydrogen cycling, which generates proton motive force by intracellular H2 production coupled to extracellular consumption, has been controversial since it was first proposed in 1981. It was hypothesized that the methanogenic archaeon Methanosarcina barkeri is capable of energy conservation via H2 cycling, based on genetic data that suggest that H2 is a preferred, but nonessential, intermediate in the electron transport chain of this organism. Here, we characterize a series of hydrogenase mutants to provide direct evidence of H2 cycling. M. barkeri produces H2 during growth on methanol, a phenotype that is lost upon mutation of the cytoplasmic hydrogenase encoded by frhADGB, although low levels of H2, attributable to the Ech hydrogenase, accumulate during stationary phase. In contrast, mutations that conditionally inactivate the extracellular Vht hydrogenase are lethal when expression of the vhtGACD operon is repressed. Under these conditions, H2 accumulates, with concomitant cessation of methane production and subsequent cell lysis, suggesting that the inability to recapture extracellular H2 is responsible for the lethal phenotype. Consistent with this interpretation, double mutants that lack both Vht and Frh are viable. Thus, when intracellular hydrogen production is abrogated, loss of extracellular H2 consumption is no longer lethal. The common occurrence of both intracellular and extracellular hydrogenases in anaerobic microorganisms suggests that this unusual mechanism of energy conservation may be widespread in nature. IMPORTANCE ATP is required by all living organisms to facilitate essential endergonic reactions required for growth and maintenance. Although synthesis of ATP by substrate-level phosphorylation is widespread and significant, most ATP is made via the enzyme ATP synthase, which is energized by transmembrane chemiosmotic gradients. Therefore, establishing this gradient across the membrane is of central importance to sustaining life. Experimental validation of H2 cycling adds to a short list of mechanisms for generating a transmembrane electrochemical gradient that is likely to be widespread, especially among anaerobic microorganisms.
Temporal Viral Genome-Protein Interactions Define Distinct Stages of Productive Herpesviral Infection.

ABSTRACT Herpesviruses utilize multiple mechanisms to redirect host proteins for use in viral processes and to avoid recognition and repression by the host. To investigate dynamic interactions between herpes simplex virus type 1 (HSV-1) DNA and viral and host proteins throughout infection, we developed an approach to identify proteins that associate with the infecting viral genome from nuclear entry through packaging. To accomplish this, virus stocks were prepared in the presence of ethynyl-modified nucleotides to enable covalent tagging of viral genomes after infection for analysis of viral genome-protein interactions by imaging or affinity purification. Affinity purification was combined with stable isotope labeling of amino acids in cell culture (SILAC) mass spectrometry to enable the distinction between proteins that were brought into the cell by the virus or expressed within the infected cell before or during infection. We found that input viral DNA progressed within 6 h through four temporal stages where the genomes sequentially (i) interacted with intrinsic antiviral and DNA damage response proteins, (ii) underwent a robust transcriptional switch mediated largely by ICP4, (iii) engaged in replication, repair, and continued transcription, and then (iv) transitioned to a more transcriptionally inert state engaging de novo -synthesized viral structural components while maintaining interactions with replication proteins. Using a combination of genetic, imaging, and proteomic approaches, we provide a new and temporally compressed view of the HSV-1 life cycle based on input genome-proteome dynamics. IMPORTANCE Herpesviruses are highly prevalent and ubiquitous human pathogens. Studies of herpesviruses and other viruses have previously been limited by the ability to directly study events that occur on the viral DNA throughout infection. We present a new powerful approach, which allows for the temporal investigation of viral genome-protein interactions at all phases of infection. This work has integrated many results from previous studies with the discovery of novel factors potentially involved in viral infection that may represent new antiviral targets. In addition, the study provides a new view of the HSV-1 life cycle based on genome-proteome dynamics.
Assumption Lean Regression

It is well known that with observational data, models used in conventional regression analyses are commonly misspecified. Yet in practice, one tends to proceed with interpretations and inferences t...
Simultaneously high electron and hole mobilities in cubic boron-V compounds: BP, BAs, and BSb

Through first-principles calculations, the phonon-limited transport properties of cubic boron-V compounds (BP, BAs, and BSb) are studied. We find that the high optical phonon frequency in these compounds leads to the substantial suppression of polar scattering and the reduction of intervalley transition mediated by large-wave-vector optical phonons, both of which significantly facilitate charge transport. We also discover that BAs simultaneously has a high hole mobility ($2110\phantom{\rule{0.16em}{0ex}}\mathrm{c}{\mathrm{m}}^{2}/\mathrm{V}\phantom{\rule{0.16em}{0ex}}\mathrm{s}$) and electron mobility ($1400\phantom{\rule{0.16em}{0ex}}\mathrm{c}{\mathrm{m}}^{2}/\mathrm{V}\phantom{\rule{0.16em}{0ex}}\mathrm{s}$) at room temperature, which is rare in semiconductors. Our findings present insight into searching high mobility polar semiconductors, and point to BAs as a promising material for electronic and photovoltaic devices in addition to its predicted high thermal conductivity.
A Generalized Power System Architecture Sizing and Analysis Framework

The aeronautics industry has been challenged to increase efficiency, reduce noise and emissions, and decrease dependency on carbon-based fuels. To address these needs, NASA has identified and begun to pursue electrified aircraft as a possible solution. The power system for an electric aircraft can exist in many different forms, however; at the early design stage the engineer(s) must identify whether a hybrid- or turbo- electric solution may be best, whether the power transmission system is to be AC or DC, and to ultimately answer the question: does the electric solution provide a net system benefit compared to the fully mechanical solution? This paper describes a generalized power system architecture sizing and analysis framework to provide a mechanism to answering these questions, along with an example based on the STARC-ABL Architecture.
A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging

Author(s): Kim, Tyson N; Myers, Frank; Reber, Clay; Loury, PJ; Loumou, Panagiota; Webster, Doug; Echanique, Chris; Li, Patrick; Davila, Jose R; Maamari, Robi N; Switz, Neil A; Keenan, Jeremy; Woodward, Maria A; Paulus, Yannis M; Margolis, Todd; Fletcher, Daniel A | Abstract: Purpose:High-quality, wide-field retinal imaging is a valuable method for screening preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging. Methods:The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. Results:The system automatically generated 100° retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for diabetic retinopathy (DR) screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%. Conclusions:Automation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening. Translational Relevance:Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening.
ST-Hadoop: a MapReduce framework for spatio-temporal data

This paper presents ST-Hadoop; the first full-fledged open-source MapReduce framework with a native support for spatio-temporal data. ST-Hadoop is a comprehensive extension to Hadoop and SpatialHadoop that injects spatio-temporal data awareness inside each of their layers, mainly, language, indexing, and operations layers. In the language layer, ST-Hadoop provides built in spatio-temporal data types and operations. In the indexing layer, ST-Hadoop spatiotemporally loads and divides data across computation nodes in Hadoop Distributed File System in a way that mimics spatio-temporal index structures, which result in achieving orders of magnitude better performance than Hadoop and SpatialHadoop when dealing with spatio-temporal data and queries. In the operations layer, ST-Hadoop shipped with support for three fundamental spatio-temporal queries, namely, spatio-temporal range, top-k nearest neighbor, and join queries. Extensibility of ST-Hadoop allows others to extend features and operations easily using similar approaches described in the paper. Extensive experiments conducted on large-scale dataset of size 10 TB that contains over 1 Billion spatio-temporal records, to show that ST-Hadoop achieves orders of magnitude better performance than Hadoop and SpaitalHadoop when dealing with spatio-temporal data and operations. The key idea behind the performance gained in ST-Hadoop is its ability in indexing spatio-temporal data within Hadoop Distributed File System.
The supply chain for seed in Uganda: Where does it all go wrong?

Abstract Improving agricultural output and food security is a major concern in sub-Saharan Africa, but many efforts to help farmers improve yields have failed. Recent research has shown that farm inputs are often of very low quality, which may explain suboptimal yields and low adoption of inputs. Researchers and policy makers have focused on two main explanations for this low quality: sellers purposefully faking or adulterating inputs, and seed deterioration along the supply chain. We present the results of testing seeds along the maize supply chain in Uganda for seed performance and genetic and physical purity. We obtain two main results. First, we find no evidence that the average quality of seeds deteriorates along the supply chain. In fact, we find generally good levels of quality on average, though variation in outcomes increases further down the supply chain. Second, we do not find evidence of serious seed faking or adulteration. Instead, the results are more consistent with mishandling and poor storage of seeds. These results have potentially significant implications for agricultural policy and programming in sub-Saharan Africa, which has tended recently to focus on certification to reduce the possibility of adulteration rather than improve the handling of inputs.
Unbounded derivations in Bunce–Deddens–Toeplitz algebras

Abstract In this paper we study decompositions and classification problems for unbounded derivations in Bunce–Deddens–Toeplitz and Bunce–Deddens algebras. We also look at implementations of these derivations on associated GNS Hilbert spaces.
Deep Randomized Ensembles for Metric Learning

Learning embedding functions, which map semantically related inputs to nearby locations in a feature space supports a variety of classification and information retrieval tasks. In this work, we propose a novel, generalizable and fast method to define a family of embedding functions that can be used as an ensemble to give improved results. Each embedding function is learned by randomly bagging the training labels into small subsets. We show experimentally that these embedding ensembles create effective embedding functions. The ensemble output defines a metric space that improves state of the art performance for image retrieval on CUB-200-2011, Cars-196, In-Shop Clothes Retrieval and VehicleID.
Regulating Landlords: Unintended Consequences for Poor Tenants

This paper explores “hidden” ways by which cities may inadvertently undermine access to decent, stable, affordable housing—especially for vulnerable renter households—through regulations that sanct...
Pharmacogenetics of Warfarin Dosing in Patients of African and European Ancestry

Despite the introduction of direct acting oral anticoagulants, warfarin remains the most commonly prescribed oral anticoagulant. However, warfarin therapy is plagued by the large inter- and intrapatient variability. The variability in dosing fueled research to identify clinical and genetic predictors and develop more accurate dosing algorithms. Observational studies have demonstrated the significant impact of single nucleotide polymorphisms in CYP2C9 and VKORC1 on warfarin dose in patients of European ancestry and African-Americans. This evidence supported the design and conduct of clinical trials to assess whether genotype-guided dosing results in improved anticoagulation control and outcomes. The trial results have shown discordance by race, with pharmacogenetic algorithms improving dose and anticoagulation control among European ancestry patients compared with African-American patients. Herein, we review the evidence from observational and interventional studies, highlight the need for inclusion of minority race groups and propose the need to develop race specific dosing algorithms.
Number of implants placed for complete‐arch fixed prostheses: A systematic review and meta‐analysis

OBJECTIVES The main purpose of this systematic review was to evaluate outcomes related to the number of implants utilized to support complete-arch fixed prostheses, both for the maxilla and the mandible. MATERIALS AND METHODS This review followed the reporting guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A focused question using the PICO format was developed, questioning whether "In patients with an implant supported fixed complete dental prosthesis, do implant and prosthetic survival outcomes differ between five or more compared to fewer than five supporting implants?". A comprehensive search of the literature was formulated and performed electronically and by hand search. Two independent reviewers selected the papers and tabulated results. Primary outcomes analyzed were implant and prosthesis survival. Implant distribution, loading, and type of retention were observed as secondary outcomes, as they relate to the number of implants. A meta-analysis was performed to compare results for studies by number of implants. RESULTS The search strategy identified 1,579 abstracts for initial review. Based on evaluation of the abstracts, 359 articles were identified for full-text evaluation. From these, 93 were selected and included in this review, being nine RCTs, 42 prospective and 42 retrospective. Of the 93 selected studies, 28 reported number of implants for the maxilla, 46 for the mandible, and 19 for both maxilla and mandible. The most reported number of implants for the "fewer than five" group is 4 for the maxilla, and 3 and 4 for the mandible, whereas for the "five or more" implants group, the most reported number of implants was 6 for the maxilla and 5 for the mandible. No significant differences in the primary outcomes analyzed were identified when fewer than five implants per arch were compared with five or more implants per arch (p > 0.05), in a follow-up time ranging from 1 to 15 years (median of 8 years). CONCLUSIONS Evidence from this systematic review and meta-analysis suggests that the use of fewer than five implants per arch, when compared to five or more implants per arch, to support a fixed prosthesis of the completely edentulous maxilla or mandible, present similar survival rates, with no statistical significant difference at a p < 0.05 and a confidence interval of 95%.
Two Metrics Describing the Causes of Seasonal and Spatial Changes in Subglacial Aqueous Chemistry

Seasonal change in surface melt input and spatial controls on the distribution of subglacial water can cause considerable variability in the aqueous chemistry of subglacial waters. Much of this variability has been interpreted in terms of a single variable: water residence time, with slow flow assumed to correlate with greater mineral dissolution and oxidative weathering. We synthesize data from a range of glacier and ice sheet settings to show that this approach does not adequately describe presently available data. Instead, we propose that two independent variables control spatial and seasonal changes in aqueous chemistry in subglacial settings: atmospheric gas abundance and sediment supply abundance. Where atmospheric gases are abundant, carbonation weathering is responsible for most of the subglacial chemical activity; where they become limited, oxidation weathering becomes more dominant. Where freshly comminuted sediment is abundant, easily dissolved minerals, especially calcite, have proportionally more influence on subglacial hydrochemistry; where sediment supply is limited, silicate minerals and less reactive carbonate minerals will increase in relative influence. In most settings, simple metrics of the abundance of SO42- and Ca2+ in the subglacial waters can characterize these two variables. In the data we synthesize, neither variable consistently correlates to the inferred water residence time, nor do the variables consistently correlate with each other. Spatial data show that point locations and small catchments on the glacial bed differ substantially from the integrated composition found at glacial outlets. The varied response in the subglacial aqueous chemistry to changing water residence times suggests complex control by a broad range of glaciological factors that affect water routing and subglacial sediment generation.
A graph-convolutional neural network model for the prediction of chemical reactivity

We present a supervised learning approach to predict the products of organic reactions given their reactants, reagents, and solvent(s). The prediction task is factored into two stages comparable to manual expert approaches: considering possible sites of reactivity and evaluating their relative likelihoods. By training on hundreds of thousands of reaction precedents covering a broad range of reaction types from the patent literature, the neural model makes informed predictions of chemical reactivity. The model predicts the major product correctly over 85% of the time requiring around 100 ms per example, a significantly higher accuracy than achieved by previous machine learning approaches, and performs on par with expert chemists with years of formal training. We gain additional insight into predictions via the design of the neural model, revealing an understanding of chemistry qualitatively consistent with manual approaches.
Conformational dynamics of the HIV Vif protein complex

Abstract Human immunodeficiency virus-1 viral infectivity factor (Vif) is an intrinsically disordered protein responsible for the ubiquitination of the APOBEC3 (A3) antiviral proteins. Vif folds when it binds Cullin-RING E3 ligase 5 and the transcription cofactor CBF-β. A five-protein complex containing the substrate receptor (Vif, CBF-β, Elongin-B, Elongin-C (VCBC)) and Cullin5 (CUL5) has a published crystal structure, but dynamics of this VCBC-CUL5 complex have not been characterized. Here, we use molecular dynamics (MD) simulations and NMR to characterize the dynamics of the VCBC complex with and without CUL5 and an A3 protein bound. Our simulations show that the VCBC complex undergoes global dynamics involving twisting and clamshell opening of the complex, whereas VCBC-CUL5 maintains a more static conformation, similar to the crystal structure. This observation from MD is supported by methyl-transverse relaxation-optimized spectroscopy NMR data, which indicates that the VCBC complex without CUL5 is dynamic on the μs-ms timescale. Our NMR data also show that the VCBC complex is more conformationally restricted when bound to the antiviral APOBEC3F (one of the A3 proteins), consistent with our MD simulations. Vif contains a flexible linker region located at the hinge of the VCBC complex, which changes conformation in conjunction with the global dynamics of the complex. Like other substrate receptors, VCBC can exist alone or in complex with CUL5 and other proteins in cells. Accordingly, the VCBC complex could be a good target for therapeutics that would inhibit full assembly of the ubiquitination complex by stabilizing an alternate VCBC conformation.
Nrf1-mediated transcriptional regulation of the proteasome requires a functional TIP60 complex

Inhibition of the proteasome leads to proteotoxic stress, which is characterized by the buildup of ubiquitinated proteins that cannot be degraded properly. The transcription factor Nrf1 (also called NFE2L1) counteracts proteotoxic stress by inducing transcription of proteasome subunit genes, resulting in the restoration of proteasome activity. Further understanding of the Nrf1 pathway is therefore of interest in both neurodegeneration, where proteasome activity could be enhanced, and cancer, where suppression of this pathway could potentiate the cell-killing effect mediated by proteasome inhibitor drugs. Here, to identify novel regulators of Nrf1, we performed an RNAi screen in an engineered cell line, reporting on Nrf1 transcriptional activity. In addition to validating known regulators, we discovered that the AAA+ ATPase RUVBL1 is necessary for Nrf1's transcriptional activity. Given that RUVBL1 is part of different multisubunit complexes that play key roles in transcription, we dissected this phenomenon further and found that the TIP60 chromatin-regulatory complex is essential for Nrf1-dependent transcription of proteasome genes. Consistent with these observations, Nrf1, RUVBL1, and TIP60 proteins were co-recruited to the promoter regions of proteasome genes after proteasome inhibitor treatments. More importantly, depletion of RUVBL1 or TIP60 in various cancer cells sensitized them to cell death induced by proteasome inhibition. Overall, our study provides a framework for manipulating the TIP60–Nrf1 axis to alter proteasome function in various human diseases, including cancer.
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization

Stochastic Gradient Descent (SGD) has played a central role in machine learning. However, it requires a carefully hand-picked stepsize for fast convergence, which is notoriously tedious and time-consuming to tune. Over the last several years, a plethora of adaptive gradient-based algorithms have emerged to ameliorate this problem. They have proved efficient in reducing the labor of tuning in practice, but many of them lack theoretic guarantees even in the convex setting. In this paper, we propose new surrogate losses to cast the problem of learning the optimal stepsizes for the stochastic optimization of a non-convex smooth objective function onto an online convex optimization problem. This allows the use of no-regret online algorithms to compute optimal stepsizes on the fly. In turn, this results in a SGD algorithm with self-tuned stepsizes that guarantees convergence rates that are automatically adaptive to the level of noise.
Approximation Techniques for Stochastic Analysis of Biological Systems

There has been an increasing demand for formal methods in the design process of safety-critical synthetic genetic circuits. Probabilistic model checking techniques have demonstrated significant potential in analyzing the intrinsic probabilistic behaviors of complex genetic circuit designs. However, its inability to scale limits its applicability in practice. This chapter addresses the scalability problem by presenting a state-space approximation method to remove unlikely states resulting in a reduced, finite state representation of the infinite-state continuous-time Markov chain that is amenable to probabilistic model checking. The proposed method is evaluated on a design of a genetic toggle switch. Comparisons with another state-of-the-art tool demonstrate both accuracy and efficiency of the presented method.