Cosys-AirSim: A Real-Time Simulation Framework Expanded for Complex Industrial Applications

Within academia and industry, there has been a need for expansive simulation frameworks that include model-based simulation of sensors, mobile vehicles, and the environment around them. To this end, the modular, real-time, and open-source AirSim framework has been a popular community-built system that fulfills some of those needs. However, the framework required adding systems to serve some complex industrial applications, including designing and testing new sensor modalities, Simultaneous Localization And Mapping (SLAM), autonomous navigation algorithms, and transfer learning with machine learning models. In this work, we discuss the modification and additions to our open-source version of the AirSim simulation framework, including new sensor modalities, vehicle types, and methods to generate realistic environments with changeable objects procedurally. Furthermore, we show the various applications and use cases the framework can serve.Comment: Accepted at Annual Modeling and Simulation Conference, ANNSIM 202

Empowering society by reusing privately held data for official statistics - A European approach

The High-Level Expert Group on facilitating the use of new data sources for official statistics has been created in the context of the data and digital strategy of the European Commission (EC). The task of the Expert Group is to provide recommendations aimed at enhancing data sharing between businesses and government (B2G) for the purpose of producing official statistics (B2G4S). The Expert Group consists of high-level experts with various backgrounds that are particularly relevant to B2G4S. Businesses generate and use data primarily for business-related purposes. The motivation for B2G4S stems from the high societal value that such privately held data can potentially generate when transformed into reliable, relevant and timely official statistics that are made available to everybody, for free. Transforming data into statistical information requires cooperation between private data holders and statistical authorities. On a voluntary basis there have been many collaborative efforts by businesses and statistical authorities to produce statistics based on privately held data, but for various reasons the use of such data for official statistics is still far below the level required to provide society with the high-quality and timely official statistics it needs in the increasingly data-driven world

Clinical categories of patients and encounter rates in primary health care – a three-year study in defined populations

BACKGROUND: The objective was to estimate the proportion of inhabitants with a diagnosis-registered encounter with a general practitioner, and to elucidate annual variations of clinical categories of patients in terms of their individual comorbidity. METHODS: A three-year retrospective study of encounter data from electronic patient records, with an annual-based application of the Johns Hopkins Adjusted Clinical Groups (ACG) system. Data were retrieved from every patient with a diagnosis-registered encounter with a GP during the period 2001–2003 at 13 publicly managed primary health care centres in Blekinge county, southeastern Sweden, with about 150000 inhabitants. Main outcome measures: Proportions of inhabitants with a diagnosis-registered encounter, and ranges of the annual proportions of categories of patients according to ACGs. RESULTS: The proportion of inhabitants with a diagnosis-registered encounter ranged from about 64.0% to 90.6% for the primary health care centres, and averaged about 76.5% for all inhabitants. In a three-year perspective the average range of categories of patients was about 0.4% on the county level, and about 0.9% on the primary health care centre level. About one third of the patients each year had a constellation of two or more types of morbidity. CONCLUSION: About three fourths of all inhabitants had one or more diagnosis-registered encounters with a general practitioner during the three-year period. The annual variation of categories of patients according to ACGs was small on both the county and the primary health care centre level. The ACG system seems useful for demonstrating and predicting various aspects of clinical categories of patients in Swedish primary health care

Leptin Affects Life History Decisions in a Passerine Bird: A Field Experiment

BACKGROUND: Organisms face trade-offs regarding their life-history strategies, such as decisions of single or multiple broods within a year. In passerines displaying facultative multiple breeding, the probability of laying a second clutch is influenced by several life-history factors. However, information about the mechanistic background of these trade-offs is largely lacking. Leptin is a protein hormone produced by white fat cells, and acts as a signal between peripheral energy depots and the central nervous system. In addition, leptin affects cells at all levels of the reproductive axis and plays a critical role in regulating the allocation of metabolic energy to reproduction. As such, it is possible that leptin levels influence the decision of whether or not to invest time and energy into a second clutch. Accordingly, we expect a treatment with exogenous leptin to result in an increased number of second broods. METHODOLOGY/PRINCIPAL FINDINGS: At a later stage during the first brood, female great tits were treated either with long-term leptin-filled cholesterol pellets (the experimental birds) or with pellets containing only cholesterol (the control birds). We found that leptin-treated females were significantly more likely to have a second brood and that the earlier females were more likely to lay a second clutch than the late females. CONCLUSIONS/SIGNIFICANCE: As both timing of first brood and treatment with leptin were important in the decision of having multiple broods, the trade-offs involved in the breeding strategy most likely depend on multiple factors. Presumably leptin has evolved as a signal of energy supply status to regulate the release of reproductive hormones so that reproduction is coordinated with periods of sufficient nutrients. This study investigated the role of leptin as a mediator between energy resources and reproductive output, providing a fundamentally new insight into how trade-offs work on a functional basis

Low but contrasting neutral genetic differentiation shaped by winter temperature in European great tits

Gene flow is usually thought to reduce genetic divergence and impede local adaptation by homogenising gene pools between populations. However, evidence for local adaptation and phenotypic differentiation in highly mobile species, experiencing high levels of gene flow, is emerging. Assessing population genetic structure at different spatial scales is thus a crucial step towards understanding mechanisms underlying intraspecific differentiation and diversification. Here, we studied the population genetic structure of a highly mobile species – the great tit Parus major – at different spatial scales. We analysed 884 individuals from 30 sites across Europe including 10 close-by sites (< 50 km), using 22 microsatellite markers. Overall we found a low but significant genetic differentiation among sites (FST = 0.008). Genetic differentiation was higher, and genetic diversity lower, in south-western Europe. These regional differences were statistically best explained by winter temperature. Overall, our results suggest that great tits form a single patchy metapopulation across Europe, in which genetic differentiation is independent of geographical distance and gene flow may be regulated by environmental factors via movements related to winter severity. This might have important implications for the evolutionary trajectories of sub-populations, especially in the context of climate change, and calls for future investigations of local differences in costs and benefits of philopatry at large scales

Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases

Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises

Genetic association study of childhood aggression across raters, instruments, and age

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association metaanalysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis AGGoverall was 3.31% (SE= 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P= 1.6E-06), PCDH7 (P= 2.0E-06), and IPO13 (P= 2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations rg among rater-specific assessment of AGG ranged from rg= 0.46 between self- and teacher-assessment to rg= 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg|: 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg=∼-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg| : 0.46-0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.</p