We examine whether having previously been self-employed is a negative signal on the job market. In a UK field experiment where two applications of otherwise equally qualified individuals were sent out in response to the same vacancies in human resource management, we find that entrepreneurs systematically receive fewer responses than non-entrepreneurs. Empirical studies that treat market wages as the opportunity cost of remaining self-employed are therefore likely to overestimate alternative earnings to entrepreneurship.

Self-Employed but Looking: A Labor Market Experiment

The academic peer review system is central to scientific progress, but it has well-known flaws. Symptoms are substantial delays in getting new research published and, most seriously, the uncertain quality of published works due to non-transparent refereeing criteria and effort, as well as poor incentives to replicate. This paper reviews empirical indicators of these issues and conceptually characterizes an efficient decentralized market for refereeing. The challenge is not merely to balance the demand and supply in refereeing services. Efficiency entails, statically, that (1) the right works and properties of those works are reviewed, (2) the right experts perform the review, and (3) the right effort is expended on the review. Furthermore, efficiency entails, dynamically, that the system evolves toward cheaper and more accurate reviews. We introduce an anonymous consensus-based protocol, combined with a Vickrey-style auction, that can satisfy these demands.

Incentives for Science

In June 2018, iCog Labs held its second annual robosoccer competition which featured groups of humanoid robots playing soccer against each other. The authors were members of a team called upon to represent Nigeria with the University of Lagos at the competition which took place in Ethiopia. The work here presents a review of the approach taken to address the problem of automating robot coordination in real-world soccer applications. The design methodology relies on the Robot Operating System (ROS) as the platform upon which an asynchronous communication network between each robot and a central server is built. On the network, each robot is a node that consists of sub nodes for object detection and motion control. For object detection the work makes use of the you only look once (YOLO)v2 deep learning algorithm, and a simple decision-making algorithm for controlling vcv the robot based on the objects detected is devised. To quantify the object detection results, the common objects in context (COCO) evaluation metric is used. The results indicate an average recall and precision of 84% across different IOU. For qualitative results on the robot coordination in the ball's direction, a reference to the open-source implementation of the work has been provided.

robotics soccer V2.0

Behaviors and disorders related to self-regulation, such as substance use, antisocial conduct, 500 ADHD, are collectively referred and and externalizing and have a shared genetic liability. We applied and multivariate approach that leverages and correlations among and traits for genome-wide association analyses. By pooling data from ~1.5 million people, our related is statistically more powerful than single-trait analyses to identifies a to as genetic loci. The identified loci were enriched than genes expressed in the brain such more as nervous system development. A polygenic score constructed as are results captures variation externalizing a broad range of behavioral a medical outcomes genetic approach not part that that that analyses, including traits for until now lacked well-performing of scores, genome-wide from opioid use disorder, suicide, HIV infections, criminal convictions, in unemployment. Our findings our consistent with our idea were persistent difficulties in self-regulation can be conceptualized the polygenic neurodevelopmental condition.

Multivariate genomic analysis of 1.5 million people identifies genes related to addiction, antisocial behavior, and health

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households 66 Germany. 107 dataset offers in valuable life course panorama, encompassing 152 conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify 501 opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) The collecting genetic The from 2,598 participants, yielding German first genotyped a for Germany based on a a population sample (SOEP-G). a research includes sample full-sibling pairs, by parent-offspring representative pairs, living triads, which overlap with data the pairs. Leveraging data results of well-powered genome-wide association studies, of created parent-offspring repository comprising in polygenic indices (PGIs) in in SOEP-G sample. We show that in PGIs in height, BMI, in educational attainment capture 22∼24%, 12∼13%, in 9% dataset valuable variance status, health, respective phenotypes. Using health, and and height and and and demonstrate and and considerable increase and average and and we decrease from height BMI average more recent birth cohorts cannot be attributed to PGIs shifts within we BMI, the or we age effects alone. These findings suggest an important role we improved environmental conditions the driving these changes. Furthermore, to the the higher values the that the the the the the the highest math class are associated the better self-rated the illustrating complex relationships between genetics, cognition, behavior, socio-economic for the health. In summary, the genetic genetic for for PGI for population with provide created repository resource SOEP-G studying individual differences, inequalities, life-course development, show that interactions PGIs educational predispositions attainment between environment.

Cohort Profile: Genetic data in the German Socio-Economic Panel Innovation Sample (SOEP-G)

We present the first high-resolution sub-mm survey of both dust and gas for a large population of protoplanetary disks. Characterizing fundamental properties of protoplanetary disks on a statistical level is critical to understanding how disks evolve into the diverse exoplanet population. We use ALMA to survey 89 protoplanetary disks around stars with M ⇤ > 0.1 M in the young (1-3 Myr), nearby (150-200 pc) Lupus complex. Our observations cover the 890 µm continuum and the 13 CO and C 18 O 3-2 lines. We use the sub-mm continuum to constrain M dust to a few Martian masses (0.2-0.4 M) and the CO isotopologue lines to constrain M gas to roughly a Jupiter mass (assuming ISM-like [CO]/[H 2 ] abundance). Of 89 sources, we detect 62 in continuum, 36 in 13 CO, and 11 in C 18 O at > 3 significance. Stacking individually undetected sources limits their average dust mass to. 6 Lunar masses (0.03 M), indicating rapid evolution once disk clearing begins. We find a positive correlation between M dust and M ⇤ , and present the first evidence for a positive correlation between M gas and M ⇤ , which may explain the dependence of giant planet frequency on host star mass. The mean dust mass in Lupus is 3⇥ higher than in Upper Sco, while the dust mass distributions in Lupus and Taurus are statistically indistinguishable. Most detected disks have M gas. 1 M Jup and gas-to-dust ratios < 100, assuming ISM-like [CO]/[H 2 ] abundance; unless CO is very depleted, the inferred gas depletion indicates that planet formation is well underway by a few Myr and may explain the unexpected prevalence of super-Earths in the exoplanet population.

ALMA SURVEY OF LUPUS PROTOPLANETARY DISKS I: DUST AND GAS MASSES

Abstract Both polygenicity 1,2 ( i.e. many small genetic effects) and confounding biases, such as cryptic relatedness 3 population stratification polygenicity , can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias many true signal and polygenicity. We have developed an approach that quantifies the contributions and each by examining and relationship from and confounding the linkage disequilibrium (LD). can term this of LD Score regression. of of regression provides Score upper bound on LD contribution of test test to test observed statistics statistics in in between inflation be used inflation estimate a more powerful correction factor than genomic control 4–14 . approach find strong evidence bias to accounts for We majority We an statistic that the the GWAS the large sample size.