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This paper examines a 115 cm long profile section of lacustrine-swamp sediments from the Langou I Bay (eastern part of Primorsky Krai; 44°25′10.16″ N, 135°54′26.08″ E). According to the produced age model, the sediments are 3900 years old. A multiproxy study involving geochemical, chironomid, diatom, and palynological analysis indicates that the climatic and environmental conditions on the seacoast in the eastern part of Primorsky Krai developed in many respects synchronously with known climatic phases of the Late Holocene. The period from ca. 4200 to 2600 cal years BP corresponds to the first and second warm stages of the Jōmon period and the late Jōmon transgression in Japan. The peak of summer temperatures in the vicinity of the Langou I Bay occurred between 2900 and 2600 cal years BP. The cooling that began after 2600 cal years BP was not as severe in the study area as in Japan (cold Jōmon and Kofun stages): the reconstructed temperatures were 1°C lower than now; in Japan, they were 2–3°C below the current level. The Medieval Climate Optimum (Nara–Heian–Kamakura stage in Japan) reconstructed for the eastern part of Primorsky Krai in the period from 1250 to 750 cal years BP featured a humid climate with summer temperatures ca. 1.5°C higher than at present. The period between 750 and 250 cal years BP correlates with the Little Ice Age: summer temperatures had dropped to 1.5–2°C below the modern one. In the last 200 years, the lake has been shallowing and has nearly dried out. This period is marked by temperature fluctuations amid the trend of climate warming. [ABSTRACT FROM AUTHOR]

Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weather, topographical and demographical datasets. We introduce weighted frequent item mining for the analysis of the data. In this way, we capture temporal and environmental situations that frequently associate with different running performances. The results show that specific temporal and environmental situations (hour in a day, day in a week, temperature, distance to residential areas, and population density) influence the running performance of users more than other situational features. Hierarchical agglomerative clustering on the running data is used to split runners in two clusters (with sustained and less sustained running behavior). We compared the two groups of runners and found that runners with less sustained behavior are more sensitive to the environmental situations (especially several weather and location related features, such as temperature, weather type, distance to the nearest park) than regular runners. Further analysis focused on the situational features for the less sustained runners. Results show that specific feature values correspond to a better or worse running distance. Not only the influence of individual features was examined but also the interplay between features. Our findings provide important empirical evidence that the role of external situations in the running behavior of individuals can be derived from analysis of the combined historical datasets. This opens up a large potential to take those situations specifically into consideration when supporting individuals which show less sustained behavior.

Real-time systems are usually well-defined and operate based on a specific task model defined during system design. However, the system can interact with different objects from its environment at runtime and needs to guarantee its operational as well as timing behavior even in adverse environmental situations. Uncertainties in the system environment impose challenges on assuring the runtime behavior during system design. The system needs to adapt to different environmental situations which require the task model to consider the execution of adaptive tasks which can be activated in response to environmental events. We present an operational environment model that characterizes environmental situations of the real-time system and identifies the adaptive tasks needed to be activated at runtime. The adaptive tasks can be included and executed using a number of existing task models which allow non-deterministic task activation patterns. We present a situation-aware task model which efficiently maps the environmental events to (reduced) adaptive tasks. To demonstrate the applicability and usability of the proposed situation-aware task model, we perform the experimental analysis using two case studies: an automotive situation-aware task model, and an unmanned aerial vehicle situation-aware task model. The experimental results of our work show that the constructed situation-aware task model contains a maximum of nine vertices and 68 edges, provides an improvement in terms of scheduling overhead and in adaptation time (with respect to the considered existing task models). [ABSTRACT FROM AUTHOR]

The objective of this study was to examine the influence of environmental challenges on tic expression by subjective and objective measures. The study group consisted of 41 children aged 6–18 years (M=10.15, SD=2.73) with a primary diagnosis of Tourette syndrome. Subjective measures included the Functional Assessment Interview developed for this study and three standard validated instruments. The objective measure was a video-recording of the patients in five daily-life situations: watching television, doing homework, being alone, receiving attention when ticcing, and talking to a stranger. In addition, the effect of premonitory urges on assessment of tic expression was evaluated. The associations between the subjective and objective measures of tic expression were moderate to low. A significantly higher number of tics were observed in the television situation, and a significantly lower number in the alone situation, compared to the other situations. Higher levels of premonitory urge were associated with greater awareness of objectively measured tic expression. In conclusion, tic expression is significantly influenced by the environment. Subjective measures of tic expression may be misleading. These results have implications for refining the clinical assessment of tics, improving research methodology, and developing new therapeutic strategies. [ABSTRACT FROM AUTHOR]

The different models of driver behaviour can be categorized as 'Descriptive' models that focus on what the driver does and 'Functional' models that focus on why the driver behaves the way he does and from that to predict drivers' performance in different situations: demanding situations that elicit peak performance capabilities and routine situations that elicit typical behaviour. The optimal approach might be a hybrid that extracts the most useful features of each. Recently, a variety of driver support and information management systems have been designed and implemented to improve safety and performance. To predict the impact of these systems on driver behaviour, we need predictive models of driver-vehicle-environment interactions. The aim of the European ITERATE project is to develop and validate a unified driver-vehicle-environment (DVE) model. A critical review of existing models led to the identification of the most relevant parameters and variables that need to be included in such models. The selected driver characteristics (and variables used to measure them) are culture (country), attitudes/personality (sensation seeking), experience (hazard perception skills), driver state (fatigue), and task demand (workload). The proposed model includes selected environmental parameters that are simulated in the different test phases, such as road, traffic and visibility. The model will consider driving behaviour and performance from the point of view of how drivers perceive and attend to environmental situations, make choices, and respond to those situations. Performance will be measured in terms of errors and reaction times. Though this paper focuses on cars, the ITERATE project covers trains and ships as well. [ABSTRACT FROM AUTHOR]

Abstract: The Cyprinus carpio fingerlings on exposure to lethal (1mg/L) and sub lethal concentrations (0.066mg/L) of sodium cyanide showed inhibition in the activity of catalase. The disruption of catalase activity in freshwater fish, C. carpio is demonstrated in the present study using UV–visible spectrophotometer at 240nm using hydrogen peroxide as a substrate. It suggests toxic effects of sodium cyanide and consequent accumulation of hydrogen peroxide in the functionally different tissues namely, liver, gill, muscle and brain. This might lead to cellular damages, and create widespread physiological disturbance. The results suggest that catalase activity can be a good diagnostic tool for sodium cyanide toxicity in biomonitoring programme. [Copyright &y& Elsevier]