Using Variable-Rate Alerting to Counter Boredom in Human Supervisory Control

A low task load, long duration experiment was conducted to evaluate the impact of cyclical attention switching strategies on operator performance in supervisory domains. The impetus for such a study stems from the lack of prior work to improve human-system performance in low task load supervisory domains through the use of design interventions. In this study, a design intervention in the form of auditory alerts is introduced and the effects of the alerts are examined. The test bed consists of a video game-like simulation environment, which allows a single operator the ability to supervise multiple unmanned vehicles. Each participant in the study completed two different four hour sessions, with and without the alerts. The results suggest that the alerts can be useful for operators who are distracted for a considerable amount of time, but that the alerts may not be appropriate for operators who are able to sustain directed attention for prolonged periods.United States. Office of Naval Researc

Deep diversification of an AAV capsid protein by machine learning.

Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12-29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics

Goal setting and self-efficacy among delinquent, at-risk and not at-risk adolescents

Setting clear achievable goals that enhance self-efficacy and reputational status directs the energies of adolescents into socially conforming or non-conforming activities. This present study investigates the characteristics and relationships between goal setting and self-efficacy among a matched sample of 88 delinquent (18 % female), 97 at-risk (20 % female), and 95 not at-risk adolescents (20 % female). Four hypotheses related to this were tested. Findings revealed that delinquent adolescents reported fewest goals, set fewer challenging goals, had a lower commitment to their goals, and reported lower levels of academic and self-regulatory efficacy than those in the at-risk and not at-risk groups. Discriminant function analysis indicated that adolescents who reported high delinquency goals and low educational and interpersonal goals were likely to belong to the delinquent group, while adolescents who reported high educational and interpersonal goals and low delinquency goals were likely to belong to the not at-risk group. The at-risk and not at-risk groups could not be differentiated. A multinomial logistic regression also revealed that adolescents were more likely to belong to the delinquent group if they reported lower self-regulatory efficacy and lower goal commitment. These findings have important implications for the development of prevention and intervention programs, particularly for those on a trajectory to delinquency. Specifically, programs should focus on assisting adolescents to develop clear self-set achievable goals and support them through the process of attaining them, particularly if the trajectory towards delinquency is to be addressed

Investigating the Effect of Conflicting Goals and Transparency on Trust and Collaboration in Multi-Team Systems

In Air Traffic Management (ATM) multiple teams have to collaborate to achieve efficient and safe operation. Multiple-team operations rely on communication and information sharing between the team members. In this field, multi-team systems (MTSs) are the most common form of organization. The interface between the organizations involved (e.g. air traffic control, cockpit crews, airports) is of central importance. Apart from a common goal, different stakeholders may pursue individual goals governed by their own company culture or policies. Therefore, simply sharing all available information may not be enough to ensure safe and efficient operation. As part of the project ITC (Inter-Team Collaboration), an experimental study with 48 teams of three (n=144) has just started to investigate the impact that conflicting goals have on communication and collaboration. Additionally, it examines whether and how transparency in roles, processes, and goals can affect performance, communication, and trust in multi-team systems. In the synthetic task environment (STE) ConCenT (Control Center Task Environment), teams of three have to collaborate to detect system failures in time, determine their causes, and decide on a solution in order to ensure successful production processes. Measurements of performance, perceived trust, communication, and gaze data will be analyzed to examine and compare different coordination and communication patterns on a group level. Results of the study will identify factors that may facilitate or hinder collaborative work processes in an MTS, thus enabling the validation of an approach to improve collaboration through transparency and mutual trust

Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015:a systematic analysis for the Global Burden of Disease Study 2015

Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015.Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores.Findings We generated 9.3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17.2 billion, 95% uncertainty interval [UI] 15.4-19.2 billion) and diarrhoeal diseases (2.39 billion, 2.30-2.50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2.36 billion (2.35-2.37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20-30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo.Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Copyright (C) The Author(s). Published by Elsevier Ltd.</p

Five insights from the Global Burden of Disease Study 2019

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3.5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.Peer reviewe