875 resultados para ENVIRONMENT DATA


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Abstract Cloud computing service emerged as an essential component of the Enterprise {IT} infrastructure. Migration towards a full range and large-scale convergence of Cloud and network services has become the current trend for addressing requirements of the Cloud environment. Our approach takes the infrastructure as a service paradigm to build converged virtual infrastructures, which allow offering tailored performance and enable multi-tenancy over a common physical infrastructure. Thanks to virtualization, new exploitation activities of the physical infrastructures may arise for both transport network and Data Centres services. This approach makes network and Data Centres’ resources dedicated to Cloud Computing to converge on the same flexible and scalable level. The work presented here is based on the automation of the virtual infrastructure provisioning service. On top of the virtual infrastructures, a coordinated operation and control of the different resources is performed with the objective of automatically tailoring connectivity services to the Cloud service dynamics. Furthermore, in order to support elasticity of the Cloud services through the optical network, dynamic re-planning features have been provided to the virtual infrastructure service, which allows scaling up or down existing virtual infrastructures to optimize resource utilisation and dynamically adapt to users’ demands. Thus, the dynamic re-planning of the service becomes key component for the coordination of Cloud and optical network resource in an optimal way in terms of resource utilisation. The presented work is complemented with a use case of the virtual infrastructure service being adopted in a distributed Enterprise Information System, that scales up and down as a function of the application requests.

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Objective We evaluated whether regional differences in physical activity (PA) and sedentary behaviour (SB) existed along language boundaries within Switzerland and whether potential differences would be explained by socio-demographics or environmental characteristics. Methods We combined data of 611 children aged 4 to 7 years from four regional studies. PA and SB were assessed by accelerometers. Information about the socio-demographic background was obtained by questionnaires. Objective neighbourhood attributes could be linked to home addresses. Multivariate regression models were used to test associations between PA and SB and socio-demographic characteristics and neighbourhood attributes. Results Children from the German compared to the French-speaking region were more physically active and less sedentary (by 10–15 %, p < 0.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences p < 0.001), these characteristics did not explain the differences in PA behaviour between French and German speaking. Conclusions Factors related to the language region, which might be culturally rooted were among the strongest correlates of PA and SB among Swiss children, independent of individual, social and environmental factors.

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PRINCIPALS Throughout the world, falls are a major public health problem and a socioeconomic burden. Nevertheless there is little knowledge about how the injury types may be related to the aetiology and setting of the fall, especially in the elderly. We have therefore analysed all patients presenting with a fall to our Emergency Department (ED) over the past five years. METHODS Our retrospective data analysis comprised adult patients admitted to our Emergency Department between January 1, 2006, and December 31, 2010, in relation to a fall. RESULTS Of a total of 6357 patients 78% (n = 4957) patients were younger than 75 years. The main setting for falls was patients home (n = 2239, 35.3%). In contrast to the younger patients, the older population was predominantly female (56.3% versus 38.6%; P < 0.0001). Older patients were more likely to fall at home and suffer from medical conditions (all P < 0.0001). Injuries to the head (P < 0.0001) and to the lower extremity (P < 0.019) occurred predominantly in the older population. Age was the sole predictor for recurrent falls (OR 1.2, P < 0.0001). CONCLUSION Falls at home are the main class of falls for all age groups, particularly in the elderly. Fall prevention strategies must therefore target activities of daily living. Even though falls related to sports mostly take place in the younger cohort, a significant percentage of elderly patients present with falls related to sporting activity. Falls due to medical conditions were most likely to result in mild traumatic brain injury.

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This report presents a basic analyis of the data collected on agroclimatology, erosion, and soil and water conservation at Afdeyu Station in the central highlands of Eritrea between 1984 and 2007. Datasets and graphs include rainfall, air and soil surface temperatures, soil loss, surface runoff, river discharge, and land use including cropping patterns of the measured catchment.

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The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

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In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use–poverty–environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local—highly contextual—development potentials is key to shaping outcomes of the land use–poverty–environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.

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Report on the project activities 2003.

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Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

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BACKGROUND Living at higher altitude was dose-dependently associated with lower risk of ischaemic heart disease (IHD). Higher altitudes have different climatic, topographic and built environment properties than lowland regions. It is unclear whether these environmental factors mediate/confound the association between altitude and IHD. We examined how much of the altitude-IHD association is explained by variations in exposure at place of residence to sunshine, temperature, precipitation, aspect, slope and distance to main road. METHODS We included 4.2 million individuals aged 40-84 at baseline living in Switzerland at altitudes 195-2971 m above sea level (ie, full range of residence), providing 77 127 IHD deaths. Mortality data 2000-2008, sociodemographic/economic information and coordinates of residence were obtained from the Swiss National Cohort, a longitudinal, census-based record linkage study. Environment information was modelled to residence level using Weibull regression models. RESULTS In the model not adjusted for other environmental factors, IHD mortality linearly decreased with increasing altitude resulting in a lower risk (HR, 95% CI 0.67, 0.60 to 0.74) for those living >1500 m (vs<600 m). This association remained after adjustment for all other environmental factors 0.74 (0.66 to 0.82). CONCLUSIONS The benefit of living at higher altitude was only partially confounded by variations in climate, topography and built environment. Rather, physical environment factors appear to have an independent effect and may impact on cardiovascular health in a cumulative way. Inclusion of additional modifiable factors as well as individual information on traditional IHD risk factors in our combined environmental model could help to identify strategies for the reduction of inequalities in IHD mortality.

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Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

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Interactions between pesticides and parasites are believed to be responsible for increased mortality of honey bee (Apis mellifera) colonies in the northern hemisphere. Previous efforts have employed experimental approaches using small groups under laboratory conditions to investigate influence of these stressors on honey bee physiology and behaviour, although both the colony level and field conditions play a key role for eusocial honey bees. Here, we challenged honey bee workers under in vivo colony conditions with sublethal doses of the neonicotinoid thiacloprid, the miticide tau-fluvalinate and the endoparasite Nosema ceranae, to investigate potential effects on longevity and behaviour using observation hives. In contrast to previous laboratory studies, our results do not suggest interactions among stressors, but rather lone effects of pesticides and the parasite on mortality and behaviour, respectively. These effects appear to be weak due to different outcomes at the two study sites, thereby suggesting that the role of thiacloprid, tau-fluvalinate and N. ceranae and interactions among them may have been overemphasized. In the future, investigations into the effects of honey bee stressors should prioritize the use of colonies maintained under a variety of environmental conditions in order to obtain more biologically relevant data.

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Using the directional distance function we study a cross section of 110 countries to examine the efficiency of management of the tradeoffs between pollution and income. The DEA model is reformulated to permit 'reverse disposability' of the bad output. Further, we interpret the optimal solution of the multiplier form of the DEA model as an iso-inefficiency line. This permits us to measure the shadow cost of the bad output for a country that is in the interior, rather than on the frontier of the production possibilities set. We also compare the relative environmental performance of countries in terms of emission intensity adjusted for technical efficiency. Only 10% of the countries are found to be on the frontier. Also, there is considerable inter-country variation in the imputed opportunity cost of CO2 reduction. Further, differences in technical efficiency contribute substantially to differences in the observed levels of CO2 intensity.

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Digital terrain models (DTM) typically contain large numbers of postings, from hundreds of thousands to billions. Many algorithms that run on DTMs require topological knowledge of the postings, such as finding nearest neighbors, finding the posting closest to a chosen location, etc. If the postings are arranged irregu- larly, topological information is costly to compute and to store. This paper offers a practical approach to organizing and searching irregularly-space data sets by presenting a collection of efficient algorithms (O(N),O(lgN)) that compute important topological relationships with only a simple supporting data structure. These relationships include finding the postings within a window, locating the posting nearest a point of interest, finding the neighborhood of postings nearest a point of interest, and ordering the neighborhood counter-clockwise. These algorithms depend only on two sorted arrays of two-element tuples, holding a planimetric coordinate and an integer identification number indicating which posting the coordinate belongs to. There is one array for each planimetric coordinate (eastings and northings). These two arrays cost minimal overhead to create and store but permit the data to remain arranged irregularly.