Showing papers by "University of Connecticut published in 2018"

Industrial Internet of Things: Challenges, Opportunities, and Directions

Abstract: Internet of Things (IoT) is an emerging domain that promises ubiquitous connection to the Internet, turning common objects into connected devices. The IoT paradigm is changing the way people interact with things around them. It paves the way for creating pervasively connected infrastructures to support innovative services and promises better flexibility and efficiency. Such advantages are attractive not only for consumer applications, but also for the industrial domain. Over the last few years, we have been witnessing the IoT paradigm making its way into the industry marketplace with purposely designed solutions. In this paper, we clarify the concepts of IoT, Industrial IoT, and Industry 4.0. We highlight the opportunities brought in by this paradigm shift as well as the challenges for its realization. In particular, we focus on the challenges associated with the need of energy efficiency, real-time performance, coexistence, interoperability, and security and privacy. We also provide a systematic overview of the state-of-the-art research efforts and potential research directions to solve Industrial IoT challenges.

Senolytics improve physical function and increase lifespan in old age

Abstract: Physical function declines in old age, portending disability, increased health expenditures, and mortality. Cellular senescence, leading to tissue dysfunction, may contribute to these consequences of aging, but whether senescence can directly drive age-related pathology and be therapeutically targeted is still unclear. Here we demonstrate that transplanting relatively small numbers of senescent cells into young mice is sufficient to cause persistent physical dysfunction, as well as to spread cellular senescence to host tissues. Transplanting even fewer senescent cells had the same effect in older recipients and was accompanied by reduced survival, indicating the potency of senescent cells in shortening health- and lifespan. The senolytic cocktail, dasatinib plus quercetin, which causes selective elimination of senescent cells, decreased the number of naturally occurring senescent cells and their secretion of frailty-related proinflammatory cytokines in explants of human adipose tissue. Moreover, intermittent oral administration of senolytics to both senescent cell–transplanted young mice and naturally aged mice alleviated physical dysfunction and increased post-treatment survival by 36% while reducing mortality hazard to 65%. Our study provides proof-of-concept evidence that senescent cells can cause physical dysfunction and decreased survival even in young mice, while senolytics can enhance remaining health- and lifespan in old mice.

Cardiovascular Safety of Febuxostat or Allopurinol in Patients with Gout

Abstract: Background Cardiovascular risk is increased in patients with gout. We compared cardiovascular outcomes associated with febuxostat, a nonpurine xanthine oxidase inhibitor, with those associated with allopurinol, a purine base analogue xanthine oxidase inhibitor, in patients with gout and cardiovascular disease. Methods We conducted a multicenter, double-blind, noninferiority trial involving patients with gout and cardiovascular disease; patients were randomly assigned to receive febuxostat or allopurinol and were stratified according to kidney function. The trial had a prespecified noninferiority margin of 1.3 for the hazard ratio for the primary end point (a composite of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or unstable angina with urgent revascularization). Results In total, 6190 patients underwent randomization, received febuxostat or allopurinol, and were followed for a median of 32 months (maximum, 85 months). The trial regimen was discontinued in 56.6% of pat...

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Abstract: Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Ouroboros Praos: An Adaptively-Secure, Semi-synchronous Proof-of-Stake Blockchain

Abstract: We present “Ouroboros Praos”, a proof-of-stake blockchain protocol that, for the first time, provides security against fully-adaptive corruption in the semi-synchronous setting: Specifically, the adversary can corrupt any participant of a dynamically evolving population of stakeholders at any moment as long the stakeholder distribution maintains an honest majority of stake; furthermore, the protocol tolerates an adversarially-controlled message delivery delay unknown to protocol participants.

Calculation of the hadronic vacuum polarization contribution to the muon anomalous magnetic moment

Abstract: We present a first-principles lattice QCD+QED calculation at physical pion mass of the leading-order hadronic vacuum polarization contribution to the muon anomalous magnetic moment. The total contribution of up, down, strange, and charm quarks including QED and strong isospin breaking effects is aμHVP LO=715.4(18.7)×10-10. By supplementing lattice data for very short and long distances with R-ratio data, we significantly improve the precision to aμHVP LO=692.5(2.7)×10-10. This is the currently most precise determination of aμHVP LO.

3D printed polyamide membranes for desalination

Abstract: Polyamide thickness and roughness have been identified as critical properties that affect thin-film composite membrane performance for reverse osmosis. Conventional formation methodologies lack the ability to control these properties independently with high resolution or precision. An additive approach is presented that uses electrospraying to deposit monomers directly onto a substrate, where they react to form polyamide. The small droplet size coupled with low monomer concentrations result in polyamide films that are smoother and thinner than conventional polyamides, while the additive nature of the approach allows for control of thickness and roughness. Polyamide films are formed with a thickness that is controllable down to 4-nanometer increments and a roughness as low as 2 nanometers while still exhibiting good permselectivity relative to a commercial benchmarking membrane.

Path ORAM: An Extremely Simple Oblivious RAM Protocol

Abstract: We present Path ORAM, an extremely simple Oblivious RAM protocol with a small amount of client storage. Partly due to its simplicity, Path ORAM is the most practical ORAM scheme known to date with small client storage. We formally prove that Path ORAM has a O(log N) bandwidth cost for blocks of size B = Ω (log2N) bits. For such block sizes, Path ORAM is asymptotically better than the best-known ORAM schemes with small client storage. Due to its practicality, Path ORAM has been adopted in the design of secure processors since its proposal.

Justify your alpha

Abstract: In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.

Single cell transcriptome profiling of retinal ganglion cells identifies cellular subtypes.

Abstract: Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes. Retinal ganglion cells (RGCs) are diverse in cellular function and physiology. This study demonstrates additional RGC heterogeneity using single cell transcriptomic analyses to classify 40 classes of RGCs in early postnatal mice before eye opening.

Weight bias internalization and health: a systematic review

Abstract: A robust literature has documented the negative health effects of being the target of weight bias. Weight bias internalization (WBI) occurs when individuals apply negative weight stereotypes to themselves and self-derogate because of their body weight. Compared with experiences of weight bias, less is known about the relationship between WBI and mental and physical health, although more literature on this topic has emerged in recent years. The current systematic review identified 74 studies assessing the relationship between WBI and health and interventions designed to reduce WBI and improve health. Over half of identified studies were published from 2016 to 2017. Results showed strong, negative relationships between WBI and mental health outcomes. Fewer studies have examined the relationship between WBI and physical health, and results were less consistent. Key directions for future research are highlighted, including the need for prospective and experimental studies with greater sample diversity.

Preprocessing-Free Gear Fault Diagnosis Using Small Datasets With Deep Convolutional Neural Network-Based Transfer Learning

Abstract: Early diagnosis of gear transmission has been a significant challenge, because gear faults occur primarily at microstructure or even material level but their effects can only be observed indirectly at a system level. The performance of a gear fault diagnosis system depends significantly on the features extracted and the classifier subsequently applied. Traditionally, fault-related features are extracted and identified based on domain expertise through data preprocessing which are system-specific and may not be easily generalized. On the other hand, although recently the deep neural networks based approaches featuring adaptive feature extractions and inherent classifications have attracted attention, they usually require a substantial set of training data. Aiming at tackling these issues, this paper presents a deep convolutional neural network-based transfer learning approach. The proposed transfer learning architecture consists of two parts; the first part is constructed with a pre-trained deep neural network that serves to extract the features automatically from the input, and the second part is a fully connected stage to classify the features that needs to be trained using gear fault experimental data. Case analyses using experimental data from a benchmark gear system indicate that the proposed approach not only entertains preprocessing free adaptive feature extractions, but also requires only a small set of training data.

DNA Damage, Mutagenesis and Cancer

Abstract: A large number of chemicals and several physical agents, such as UV light and γ-radiation, have been associated with the etiology of human cancer. Generation of DNA damage (also known as DNA adducts or lesions) induced by these agents is an important first step in the process of carcinogenesis. Evolutionary processes gave rise to DNA repair tools that are efficient in repairing damaged DNA; yet replication of damaged DNA may take place prior to repair, particularly when they are induced at a high frequency. Damaged DNA replication may lead to gene mutations, which in turn may give rise to altered proteins. Mutations in an oncogene, a tumor-suppressor gene, or a gene that controls the cell cycle can generate a clonal cell population with a distinct advantage in proliferation. Many such events, broadly divided into the stages of initiation, promotion, and progression, which may occur over a long period of time and transpire in the context of chronic exposure to carcinogens, can lead to the induction of human cancer. This is exemplified in the long-term use of tobacco being responsible for an increased risk of lung cancer. This mini-review attempts to summarize this wide area that centers on DNA damage as it relates to the development of human cancer.

Strengths and limitations of Nitrogen rate recommendations for corn and opportunities for improvement

Abstract: 1 The goal of an N recommendation system is to accurately estimate the gap between the N provided by the soil and the N required by the plant. Accurately estimating this gap depends on the ability of the recommendation system to accurately estimate fi eld or subfi eld specifi c economically optimal nitrogen rates (EONR). Current recommendation systems are not as accurate as needed to provide consistently reliable estimates of N needs across years at the fi eld or subfi eld scale. Uncontrollable factors like temperature, rainfall timing, intensity and amount, and interactions of temperature and rainfall with factors such as N source, timing and placement, plant genetics, and soil characteristics combine to make N rate recommendations for an individual fi eld or rates for subfi elds a process guided as much by science as by the best professional judgement of farmers and farm advisors. Substantial evidence has accumulated that EONRs can vary widely across fi elds, within fi elds and over years in the same fi eld for a wide range of crops and geographies. Examples Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

Polymer Genome: A Data-Powered Polymer Informatics Platform for Property Predictions

Abstract: The recent successes of the Materials Genome Initiative have opened up new opportunities for data-centric informatics approaches in several subfields of materials research, including in polymer science and engineering. Polymers, being inexpensive and possessing a broad range of tunable properties, are widespread in many technological applications. The vast chemical and morphological complexity of polymers though gives rise to challenges in the rational discovery of new materials for specific applications. The nascent field of polymer informatics seeks to provide tools and pathways for accelerated property prediction (and materials design) via surrogate machine learning models built on reliable past data. We have carefully accumulated a data set of organic polymers whose properties were obtained either computationally (bandgap, dielectric constant, refractive index, and atomization energy) or experimentally (glass transition temperature, solubility parameter, and density). A fingerprinting scheme that capt...

Age-related changes in the gut microbiota influence systemic inflammation and stroke outcome.

Abstract: OBJECTIVE Chronic systemic inflammation contributes to the pathogenesis of many age-related diseases. Although not well understood, alterations in the gut microbiota, or dysbiosis, may be responsible for age-related inflammation. METHODS Using stroke as a disease model, we tested the hypothesis that a youthful microbiota, when established in aged mice, produces positive outcomes following ischemic stroke. Conversely, an aged microbiota, when established in young mice, produces negative outcomes after stroke. Young and aged male mice had either a young or an aged microbiota established by fecal transplant gavage (FTG). Mice were subjected to ischemic stroke (middle cerebral artery occlusion; MCAO) or sham surgery. During the subsequent weeks, mice underwent behavioral testing and fecal samples were collected for 16S ribosomal RNA analysis of bacterial content. RESULTS We found that the microbiota is altered after experimental stroke in young mice and resembles the biome of uninjured aged mice. In aged mice, the ratio of Firmicutes to Bacteroidetes (F:B), two main bacterial phyla in gut microbiota, increased ∼9-fold (p < 0.001) compared to young. This increased F:B ratio in aged mice is indicative of dysbiosis. Altering the microbiota in young by fecal gavage to resemble that of aged mice (∼6-fold increase in F:B ratio, p < 0.001) increased mortality following MCAO, decreased performance in behavioral testing, and increased cytokine levels. Conversely, altering the microbiota in aged to resemble that of young (∼9-fold decrease in F:B ratio, p < 0.001) increased survival and improved recovery following MCAO. INTERPRETATION Aged biome increased the levels of systemic proinflammatory cytokines. We conclude that the gut microbiota can be modified to positively impact outcomes from age-related diseases. Ann Neurol 2018;83:23-36.

Epacadostat Plus Pembrolizumab in Patients With Advanced Solid Tumors: Phase I Results From a Multicenter, Open-Label Phase I/II Trial (ECHO-202/KEYNOTE-037)

Abstract: PurposeTumors may evade immunosurveillance through upregulation of the indoleamine 2,3-dioxygenase 1 (IDO1) enzyme. Epacadostat is a potent and highly selective IDO1 enzyme inhibitor. The open-label phase I/II ECHO-202/KEYNOTE-037 trial evaluated epacadostat plus pembrolizumab, a programmed death protein 1 inhibitor, in patients with advanced solid tumors. Phase I results on maximum tolerated dose, safety, tolerability, preliminary antitumor activity, and pharmacokinetics are reported.Patients and MethodsPatients received escalating doses of oral epacadostat (25, 50, 100, or 300 mg) twice per day plus intravenous pembrolizumab 2 mg/kg or 200 mg every 3 weeks. During the safety expansion, patients received epacadostat (50, 100, or 300 mg) twice per day plus pembrolizumab 200 mg every 3 weeks.ResultsSixty-two patients were enrolled and received one or more doses of study treatment. The maximum tolerated dose of epacadostat in combination with pembrolizumab was not reached. Fifty-two patients (84%) experienc...

Biogeographic patterns of abundant and rare bacterioplankton in three subtropical bays resulting from selective and neutral processes.

Abstract: Unraveling the relative importance of ecological processes regulating microbial community structure is a central goal in microbial ecology. Here, we used high-throughput sequencing to examine the relative contribution of selective and neutral processes in the assembly of abundant and rare subcommunities from three subtropical bays of China. We found that abundant and rare bacterial taxa were distinctly different in diversity, despite the similar biogeographic patterns and strong distance-decay relationships, but the dispersal of rare bacterial taxa was more limited than that of abundant taxa. Furthermore, the environmental (selective processes) and spatial (neutral processes) factors seemed to govern the assembly and biogeography of abundant and rare bacterial subcommunities, although both factors explained only a small fraction of variation within the rare subcommunity. More importantly, variation partitioning (based on adjusted R2 in redundancy analysis) showed that spatial factors exhibited a slightly greater influence on both abundant and rare subcommunities compared to environmental selection; however, the abundant subcommunity had a much stronger response to spatial factors (17.3% of pure variance was explained) than that shown by the rare bacteria (3.5%). These results demonstrate that environmental selection and neutral processes explained the similar biogeographic patterns of abundant and rare subcommunities, but a large proportion of unexplained variation in the rare taxa (91.1%) implies that more complex assembly mechanisms may exist to shape the rare bacterial assemblages in the three subtropical bays.

BioTIME: A database of biodiversity time series for the Anthropocene

Abstract: Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)).Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

Deep Learning of Aftershock Patterns Following Large Earthquakes

Abstract: Aftershocks are a response to changes in stress generated by large earthquakes and represent the most common observations of the triggering of earthquakes. The maximum magnitude of aftershocks and their temporal decay are well described by empirical laws (such as Bath’s law1 and Omori’s law2), but explaining and forecasting the spatial distribution of aftershocks is more difficult. Coulomb failure stress change3 is perhaps the most widely used criterion to explain the spatial distributions of aftershocks4–8, but its applicability has been disputed9–11. Here we use a deep-learning approach to identify a static-stress-based criterion that forecasts aftershock locations without prior assumptions about fault orientation. We show that a neural network trained on more than 131,000 mainshock–aftershock pairs can predict the locations of aftershocks in an independent test dataset of more than 30,000 mainshock–aftershock pairs more accurately (area under curve of 0.849) than can classic Coulomb failure stress change (area under curve of 0.583). We find that the learned aftershock pattern is physically interpretable: the maximum change in shear stress, the von Mises yield criterion (a scaled version of the second invariant of the deviatoric stress-change tensor) and the sum of the absolute values of the independent components of the stress-change tensor each explain more than 98 per cent of the variance in the neural-network prediction. This machine-learning-driven insight provides improved forecasts of aftershock locations and identifies physical quantities that may control earthquake triggering during the most active part of the seismic cycle. Neural networks trained on data from about 130,000 aftershocks from around 100 large earthquakes improve predictions of the spatial distribution of aftershocks and suggest physical quantities that may control earthquake triggering.

Predicting global killer whale population collapse from PCB pollution

Abstract: Killer whales (Orcinus orca) are among the most highly polychlorinated biphenyl (PCB)-contaminated mammals in the world, raising concern about the health consequences of current PCB exposures. Using an individual-based model framework and globally available data on PCB concentrations in killer whale tissues, we show that PCB-mediated effects on reproduction and immune function threaten the long-term viability of >50% of the world's killer whale populations. PCB-mediated effects over the coming 100 years predicted that killer whale populations near industrialized regions, and those feeding at high trophic levels regardless of location, are at high risk of population collapse. Despite a near-global ban of PCBs more than 30 years ago, the world's killer whales illustrate the troubling persistence of this chemical class.

Fundamentals of 3D imaging and displays: a tutorial on integral imaging, light-field, and plenoptic systems

Abstract: There has been great interest in researching and implementing effective technologies for the capture, processing, and display of 3D images. This broad interest is evidenced by widespread international research and activities on 3D technologies. There is a large number of journal and conference papers on 3D systems, as well as research and development efforts in government, industry, and academia on this topic for broad applications including entertainment, manufacturing, security and defense, and biomedical applications. Among these technologies, integral imaging is a promising approach for its ability to work with polychromatic scenes and under incoherent or ambient light for scenarios from macroscales to microscales. Integral imaging systems and their variations, also known as plenoptics or light-field systems, are applicable in many fields, and they have been reported in many applications, such as entertainment (TV, video, movies), industrial inspection, security and defense, and biomedical imaging and displays. This tutorial is addressed to the students and researchers in different disciplines who are interested to learn about integral imaging and light-field systems and who may or may not have a strong background in optics. Our aim is to provide the readers with a tutorial that teaches fundamental principles as well as more advanced concepts to understand, analyze, and implement integral imaging and light-field-type capture and display systems. The tutorial is organized to begin with reviewing the fundamentals of imaging, and then it progresses to more advanced topics in 3D imaging and displays. More specifically, this tutorial begins by covering the fundamentals of geometrical optics and wave optics tools for understanding and analyzing optical imaging systems. Then, we proceed to use these tools to describe integral imaging, light-field, or plenoptics systems, the methods for implementing the 3D capture procedures and monitors, their properties, resolution, field of view, performance, and metrics to assess them. We have illustrated with simple laboratory setups and experiments the principles of integral imaging capture and display systems. Also, we have discussed 3D biomedical applications, such as integral microscopy.

Forces inside hadrons: pressure, surface tension, mechanical radius, and all that

Abstract: The physics related to the form factors of the energy–momentum tensor spans a wide spectrum of problems, and includes gravitational physics, hard-exclusive reactions, hadronic decays of heavy quark...

Beyond catalysis and membranes: visualizing and solving the challenge of electrode water accumulation and flooding in AEMFCs

Abstract: A majority of anion exchange membrane fuel cells (AEMFCs) reported in the literature have been unable to achieve high current or power A recently proposed theory is that the achievable current is largely limited by poorly balanced water during cell operation In this work, we present convincing experimental results – coupling operando electrochemical measurements and neutron imaging – supporting this theory and allowing the amount and distribution of water, and its impact on AEMFC performance, to be quantified for the first time We also create new electrode compositions by systematically manipulating the ionomer and carbon content in the anode catalyst layer, which allowed us to alleviate the mass transport behavior limitations of H2/O2 AEMFCs and achieve a new record-setting peak power density of 19 W cm−2 – a step-change to existing literature Our efforts cast a new light on the design and optimization of AEMFCs – potentially changing the way that AEMFCs are constructed and operated

Photocatalytic degradation of organic pollutants coupled with simultaneous photocatalytic H2 evolution over graphene quantum dots/Mn-N-TiO2/g-C3N4 composite catalysts: Performance and mechanism

Abstract: Graphene quantum dots/Mn-N-TiO2/g-C3N4 (GQDs/TCN) composite photocatalysts have been designed, synthesized and characterized by XRD, SEM, TEM, Raman, BET, and XPS. The photodegradation of organic pollutants (p-nitrophenol, diethyl phthalate and ciprofloxacin, called as 4-NP, CIP and DEP, respectively) coupled with simultaneous photocatalytic production of hydrogen was successfully achieved using the GQDs/TCN catalysts. The 5%GQDs/TCN-0.4 sample shows the best photocatalytic hydrogen production and organic pollutant degradation rate under simulated solar irradiation in the simultaneous photocatalytic oxidation and reduction system. Furthermore, the photocatalytic H2 evolution rates in the solution of 4-NP, CIP and DEP are all larger than that in pure water system over the 5%GQDs/TCN-0.4 catalyst. And the H2 evolution rate in the solution of 4-NP is smaller than that in the solutions of CIP and DEP. Accordingly, the photodegradation rate of 4-NP is larger than that of CIP and DEP. The analyses of density functional theory and liquid chromatography mass spectrometry indicate that some photogenerated electrons were used in the photodegradation process of 4-NP but not in that of CIP and DEP. And it leads to the photocatalytic rate of H2 evolution in the 4-NP solution smaller than that in the solution of CIP and DEP. For the first time, the present work illuminates the photocatalytic enhancement of the GQDs/TCN-0.4 catalyst and the mechanism of the effect of different organic pollutants on photocatalytic H2 evolution.