16 research outputs found
COVID-19 and Digital Resilience: Evidence from Uber Eats
We analyze how digital platforms can increase the survival rate of firms
during a crisis by providing continuity in access to customers. Using
order-level data from Uber Technologies, we study how the COVID-19 pandemic and
the ensuing shutdown of businesses in the United States affected independent,
small business restaurant supply and demand on the Uber Eats platform. We find
evidence that small restaurants experience significant increases in total
activity, orders per day, and orders per hour following the closure of the
dine-in channel, and that these increases may be due to both demand-side and
supply-side shocks. We document an increase in the intensity of competitive
effects following the shock, showing that growth in the number of providers on
a platform induces both market expansion and heightened inter-provider
competition. Our findings underscore the critical role that digital will play
in creating business resilience in the post-COVID economy, and provide new
managerial insight into how supply-side and demand-side factors shape business
performance on a platform.Comment: 26 pages, 9 figure
Stress and buckling analysis of multilayered composite plates with different cut - outs using finite element method
This study is a numerical analysis where multiple layers of plates with different orientations were combined to form a composite plate. Within this study, the concept of in-plane tensile loading and buckling upon an orthotropic multi-layered plate with different cut-outs is discussed. The finite element method is used to conduct modeling and analysis of the composite plate where the plate has different geometric shape cut-outs to test for parameters such as deflection, stress-strain distribution, buckling, and other effects of cut-outs on the cross-section of the plate
A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer's disease
A genome-wide survival analysis of 14,406 Alzheimer's disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. The minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, showed association with delayed AD onset and lower expression of SPI1 in monocytes and macrophages. SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability was enriched within the PU.1 cistrome, implicating a myeloid PU.1 target gene network in AD. Finally, experimentally altered PU.1 levels affected the expression of mouse orthologs of many AD risk genes and the phagocytic activity of mouse microglial cells. Our results suggest that lower SPI1 expression reduces AD risk by regulating myeloid gene expression and cell function
Primer on artificial intelligence and robotics
This article provides an introduction to artificial intelligence, robotics, and research streams that examine the economic and organizational consequences of these and related technologies. We describe the nascent research on artificial intelligence and robotics in the economics and management literature and summarize the dominant approaches taken by scholars in this area. We discuss the implications of artificial intelligence, robotics, and automation for organizational design and firm strategy, argue for greater engagement with these topics by organizational and strategy researchers, and outline directions for future research
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A Method to Link Advances in Artificial Intelligence to Occupational Abilities
Prior episodes of automation have led to economic growth and also to many changes in the workplace. We expect the same from artificial intelligence (AI). The link between AI and labor is complex, however. To assist researchers and policymakers, we provide a method that links advances in AI to occupational abilities, and then aggregates from these abilities to the occupation level. We demonstrate the method by estimating which occupational descriptions have changed the most due to advances in AI between 2010 and 2015, and check our estimates using the Bureau of Labor Statistics scheduled update to occupational descriptions in 2016
Vacuum-processed metal halide perovskite light-emitting diodes: prospects and challenges
In less than a decade, organic-inorganic metal halide perovskites (MHPs) have shown tremendous progress in the field of light-emitting applications. Perovskite light-emitting diodes (PeLEDs) have reached external quantum efficiencies (EQE) exceeding 20 % and they have been recognized as a potential contender of the commercial display technologies. However, perovskite thin films in PeLEDs are generally deposited via a spin-coating process, which is not favourable for large area device fabrication. Despite the great success of solution-processed PeLEDs, very few articles have been reported on vacuum processed PeLEDs and the improvements in their optoelctronic performances are also progressing slowly. On the other hand, vacuum processing techniques are mostly used in organic LED technology as they can guarantee (i) the absence of solvent during thin-film growth, (ii) process scalability over large area substrates, and (iii) precise thin-film thickness control. This thin-film growth process is suitable for application in the advancement of a large variety of display technologies. In this Review, we present an overview of current research advances in the field of perovskite thin films grown via vacuum techniques, a study of their photophysical properties, and integration in PeLEDs for the generation of different colors. We also highlight the current challenges and future prospects for the further development of vacuum processed PeLEDs
Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism
Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank's alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence
Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism
Abstract Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank’s alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence
Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria.
Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (eg, ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWAS of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7418 (1121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3175 (585 families) African-American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (P = 4.16E-11) and Desire to cut drinking (P = 1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, P = 6.72E-09); rs1912461 (chromosome 15, Time spent drinking, P = 1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, P = 8.42E-11); rs7597960 (chromosome 2, Time spent drinking, P = 1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (P < .01; 0.61%-1.82% of variance). Identified novel variants (ie, rs1912461, rs61826952) were associated with differential central evoked theta power (loss - gain; P = .0037) and reward-related ventral striatum reactivity (P = .008), respectively. This study suggests that studying individual criteria may unveil new insights into the genetic etiology of AD liability