Geographic isolation and physiological mechanisms underpinning species distributions at the range limit hotspot of South Georgia

In order to allocate quotas for sustainable harvests, that account for climate warming, it is important to incorporate species vulnerabilities that will underlie likely changes in population dynamics. Hotspots, regions with rapidly changing climate, are important locations for rapid advances in mechanistic understanding of the factors driving these changes, particularly if they coincide with regions with a high incidence of range limits, such as the sub-Antarctic Island of South Georgia. This archipelago is at the Northern limit of the Southern Ocean and therefore the northern distribution limit for many Southern Ocean shallow water marine species, which are amongst the most sensitive fauna to increasing temperature. At range limits species may either be living close to their physiological limits, or they may have more resistant phenotypes. In case studies, the northern range limit population of the gastropod limpet, Nacella concinna, has greater physiological plasticity at South Georgia than those from further south, allowing them to cope better with the warmer and more variable seasonal temperatures. Bivalve species, however, alter their depth distributions at South Georgia, to avoid the warmer water masses, indicating that they may not be able to cope with the warmer temperatures. Mackerel icefish, Champsocephalus gunnari, has a unique Antarctic trait, the loss of haemoglobin. A combination of temperature driven change in food web structure, and this extreme physiological cold adaptation, may explain why rapid warming at its northern range limit of South Georgia, has prevented stocks fully recovering from over fishing in the 1980s, despite highly conservative management strategies

Using blink rate to detect deception: A study to validate an automatic blink detector and a new dataset of videos from liars and truth-tellers

Eye-blink is a sensitive index of cognitive load and some studies have reported that it can be a useful cue for detecting deception. However, it is difficult to apply in the real forensic scenario as very complex techniques to record eye blinking are usually needed (e.g., electrooculography, eye tracker technology). In this paper, we propose a new approach to automatically detect eye blinking based on a computer vision algorithm, which does not require any expensive technology to record data. Results demonstrated that the automatic blink detector reached an accuracy similar to the electrooculogram in detecting the blink rate. Moreover, the automatic blink detector was applied to 68 videos of people who were lying or telling the truth about a past holiday, testing the difference between the two groups in terms of blink rate and response timing. Training machine learning classification models on these features, an accuracy up to 70% in identifying liars and truth-tellers was obtained

Estado nutricional e fatores associados em escolares domiciliados na área rural e urbana Nutritional status and associated factors in schoolchildren living in rural and urban areas

Objetivo Verificar o estado nutricional de escolares domiciliados nas áreas urbana e rural da Região Sul do Brasil e analisar sua associação com fatores demográficos e nível de atividade física. Métodos Participaram do estudo 1.415 escolares (720 rapazes e 695 moças), sendo 878 da área urbana e 537 da área rural. Foram pesquisadas informações demográficas (sexo, idade, área de domicílio), antropométricas (massa corporal, estatura) e do nível de atividade física. O estado nutricional - desnutrição e excesso de peso - foi determinado pelo índice de massa corporal a partir dos critérios propostos pela International Obesity Task Force. O nível de atividade física foi classificado em duas categorias: mais ativo ou menos ativo. Resultados A prevalência de desnutrição foi de 11,4% (IC95%=9,85-13,16) e excesso de peso de 11,2% (IC95%=9,66-12,95). A prevalência de excesso de peso foi superior nos escolares domiciliados na área urbana (14,0%; IC95%=12,29-15,91) em relação aos da área rural (6,7%; IC95%=5,51-8,12). Foi verificado, nos rapazes, que os menos ativos fisicamente (OR=1,74; IC95%=1,03-2,94) apresentaram chance maior de ter desnutrição. Além disso, os adolescentes da área urbana (OR=3,40; IC95%=1,88-6,17) e os menos ativos fisicamente (OR=1,88; IC95%=1,07-3,33) apresentaram maiores chances de excesso de peso. As moças de 10 a 13 anos apresentaram maior chance de desnutrição (OR=1,95; IC95%=1,17-3,24) e aquelas residentes na área urbana (OR=1,75; IC95%=1,03-2,99), mais chance de excesso de peso. Conclusão A prevalência de desnutrição encontrada ainda é elevada em escolares. O excesso de peso assemelha-se ao que tem sido observado nas regiões Sul e Sudeste do Brasil. Rapazes com baixo nível de atividade física e moças de 10 a 13 anos apresentam maior exposição à desnutrição. Moças e rapazes domiciliados na área urbana e rapazes com baixo nível de atividade física apresentam maior exposição aos riscos decorrentes do excesso de peso corporal.<br>Objective The objectives of this study were to assess the nutritional status of schoolchildren living in urban and rural areas in the southern region of Brazil, and investigate a possible association between nutritional status and demographic factors and level of physical activity. Methods A total of 1,415 schoolchildren (720 boys and 695 girls) participated in the study; of these, 878 lived in rural areas and 537 lived in urban areas. Demographic (gender, age, residence location) and anthropometric (body weight and height) data were collected and level of physical activity investigated. Nutritional status (malnutrition and excess weight) was classified according to body mass index following the International Obesity Task Force criteria. The level of physical activity was classified into two categories (more or less active). Results The prevalence of malnutrition was 11.4% (CI95%=9.85-13.16) and the prevalence of excess weight was 11.2% (CI95%=9.66-12.95). The prevalence of excess weight was higher among adolescents living in urban areas (14.0%; CI95%=12.29-15.91) than among those living in rural areas (6.7%; CI95%=5.51-8.12). Boys with lower levels of physical activity (OR=1.74; CI95%=1.03-2.94) were more likely to be malnourished. On the other hand, adolescents living in urban areas (OR=3.40; CI95%=1.88-6.17) and less physically active (OR=1.88; CI95%=1.07-3.33) were more likely to be overweight or obese. Girls aged 10 to 13 years were more likely to be malnourished (OR=1.95; CI95%=1.17-3.24) and those living in urban areas (OR=1.75; CI95%=1.03-2.99) were more likely to be overweight or obese. Conclusion The prevalence of malnourished schoolchildren is still high. In contrast, the prevalence of excess weight was similar to that observed in South and Southeast Brazil. Boys with low levels of physical activity and girls aged 10 to 13 years are more exposed to malnutrition. Boys and girls living in urban areas and boys with low levels of physical activity are more exposed to the risk of becoming overweight or obese