868 resultados para Multi-scale place recognition
Resumo:
Decadal-to-century scale trends for a range of marine environmental variables in the upper mesopelagic layer (UML, 100–600 m) are investigated using results from seven Earth System Models forced by a high greenhouse gas emission scenario. The models as a class represent the observation-based distribution of oxygen (O2) and carbon dioxide (CO2), albeit major mismatches between observation-based and simulated values remain for individual models. By year 2100 all models project an increase in SST between 2 °C and 3 °C, and a decrease in the pH and in the saturation state of water with respect to calcium carbonate minerals in the UML. A decrease in the total ocean inventory of dissolved oxygen by 2% to 4% is projected by the range of models. Projected O2 changes in the UML show a complex pattern with both increasing and decreasing trends reflecting the subtle balance of different competing factors such as circulation, production, remineralization, and temperature changes. Projected changes in the total volume of hypoxic and suboxic waters remain relatively small in all models. A widespread increase of CO2 in the UML is projected. The median of the CO2 distribution between 100 and 600m shifts from 0.1–0.2 mol m−3 in year 1990 to 0.2–0.4 mol m−3 in year 2100, primarily as a result of the invasion of anthropogenic carbon from the atmosphere. The co-occurrence of changes in a range of environmental variables indicates the need to further investigate their synergistic impacts on marine ecosystems and Earth System feedbacks.
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The responses of carbon dioxide (CO2) and other climate variables to an emission pulse of CO2 into the atmosphere are often used to compute the Global Warming Potential (GWP) and Global Temperature change Potential (GTP), to characterize the response timescales of Earth System models, and to build reduced-form models. In this carbon cycle-climate model intercomparison project, which spans the full model hierarchy, we quantify responses to emission pulses of different magnitudes injected under different conditions. The CO2 response shows the known rapid decline in the first few decades followed by a millennium-scale tail. For a 100 Gt-C emission pulse added to a constant CO2 concentration of 389 ppm, 25 ± 9% is still found in the atmosphere after 1000 yr; the ocean has absorbed 59 ± 12% and the land the remainder (16 ± 14%). The response in global mean surface air temperature is an increase by 0.20 ± 0.12 °C within the first twenty years; thereafter and until year 1000, temperature decreases only slightly, whereas ocean heat content and sea level continue to rise. Our best estimate for the Absolute Global Warming Potential, given by the time-integrated response in CO2 at year 100 multiplied by its radiative efficiency, is 92.5 × 10−15 yr W m−2 per kg-CO2. This value very likely (5 to 95% confidence) lies within the range of (68 to 117) × 10−15 yr W m−2 per kg-CO2. Estimates for time-integrated response in CO2 published in the IPCC First, Second, and Fourth Assessment and our multi-model best estimate all agree within 15% during the first 100 yr. The integrated CO2 response, normalized by the pulse size, is lower for pre-industrial conditions, compared to present day, and lower for smaller pulses than larger pulses. In contrast, the response in temperature, sea level and ocean heat content is less sensitive to these choices. Although, choices in pulse size, background concentration, and model lead to uncertainties, the most important and subjective choice to determine AGWP of CO2 and GWP is the time horizon.
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An accurate and coherent chronological framework is essential for the interpretation of climatic and environmental records obtained from deep polar ice cores. Until now, one common ice core age scale had been developed based on an inverse dating method (Datice), combining glaciological modelling with absolute and stratigraphic markers between 4 ice cores covering the last 50 ka (thousands of years before present) (Lemieux-Dudon et al., 2010). In this paper, together with the companion paper of Veres et al. (2013), we present an extension of this work back to 800 ka for the NGRIP, TALDICE, EDML, Vostok and EDC ice cores using an improved version of the Datice tool. The AICC2012 (Antarctic Ice Core Chronology 2012) chronology includes numerous new gas and ice stratigraphic links as well as improved evaluation of background and associated variance scenarios. This paper concentrates on the long timescales between 120–800 ka. In this framework, new measurements of δ18Oatm over Marine Isotope Stage (MIS) 11–12 on EDC and a complete δ18Oatm record of the TALDICE ice cores permit us to derive additional orbital gas age constraints. The coherency of the different orbitally deduced ages (from δ18Oatm, δO2/N2 and air content) has been verified before implementation in AICC2012. The new chronology is now independent of other archives and shows only small differences, most of the time within the original uncertainty range calculated by Datice, when compared with the previous ice core reference age scale EDC3, the Dome F chronology, or using a comparison between speleothems and methane. For instance, the largest deviation between AICC2012 and EDC3 (5.4 ka) is obtained around MIS 12. Despite significant modifications of the chronological constraints around MIS 5, now independent of speleothem records in AICC2012, the date of Termination II is very close to the EDC3 one.
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An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.
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In several regions of the world, climate change is expected to have severe impacts on agricultural systems. Changes in land management are one way to adapt to future climatic conditions, including land-use changes and local adjustments of agricultural practices. In previous studies, options for adaptation have mostly been explored by testing alternative scenarios. Systematic explorations of land management possibilities using optimization approaches were so far mainly restricted to studies of land and resource management under constant climatic conditions. In this study, we bridge this gap and exploit the benefits of multi-objective regional optimization for identifying optimum land management adaptations to climate change. We design a multi-objective optimization routine that integrates a generic crop model and considers two climate scenarios for 2050 in a meso-scale catchment on the Swiss Central Plateau with already limited water resources. The results indicate that adaptation will be necessary in the study area to cope with a decrease in productivity by 0–10 %, an increase in soil loss by 25–35 %, and an increase in N-leaching by 30–45 %. Adaptation options identified here exhibit conflicts between productivity and environmental goals, but compromises are possible. Necessary management changes include (i) adjustments of crop shares, i.e. increasing the proportion of early harvested winter cereals at the expense of irrigated spring crops, (ii) widespread use of reduced tillage, (iii) allocation of irrigated areas to soils with low water-retention capacity at lower elevations, and (iv) conversion of some pre-alpine grasslands to croplands.
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Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.
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This study presents the first consolidation of palaeoclimate proxy records from multiple archives to develop statistical rainfall reconstructions for southern Africa covering the last two centuries. State-of-the-art ensemble reconstructions reveal multi-decadal rainfall variability in the summer and winter rainfall zones. A decrease in precipitation amount over time is identified in the summer rainfall zone. No significant change in precipitation amount occurred in the winter rainfall zone, but rainfall variability has increased over time. Generally synchronous rainfall fluctuations between the two zones are identified on decadal scales, with common wet (dry) periods reconstructed around 1890 (1930). A strong relationship between seasonal rainfall and sea surface temperatures (SSTs) in the surrounding oceans is confirmed. Coherence among decadal-scale fluctuations of southern African rainfall, regional SST, SSTs in the Pacific Ocean and rainfall in south-eastern Australia suggest SST-rainfall teleconnections across the southern hemisphere. Temporal breakdowns of the SST-rainfall relationship in the southern African regions and the connection between the two rainfall zones are observed, for example during the 1950s. Our results confirm the complex interplay between large-scale teleconnections, regional SSTs and local effects in modulating multi-decadal southern African rainfall variability over long timescales.
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Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.
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OBJECTIVES Cognitive fluctuation (CF) is a common feature of dementia and a core diagnostic symptom for dementia with Lewy bodies (DLB). CF remains difficult to accurately and reliably detect clinically. This study aimed to develop a psychometric test that could be used by clinicians to facilitate the identification of CF and improve the recognition and diagnosis of DLB and Parkinson disease, and to improve differential diagnosis of other dementias. METHODS We compiled a 17-item psychometric test for identifying CF and applied this measure in a cross-sectional design. Participants were recruited from the North East of England, and assessments were made in individuals' homes. We recruited people with four subtypes of dementia and a healthy comparison group, and all subjects were administered this pilot scale together with other standard ratings. The psychometric properties of the scale were examined with exploratory factor analysis. We also examined the ability of individual items to identify CF to discriminate between dementia subtypes. The sensitivity and specificity of discriminating items were explored along with validity and reliability analyses. RESULTS Participants comprised 32 comparison subjects, 30 people with Alzheimer disease, 30 with vascular dementia, 29 with DLB, and 32 with dementia associated with Parkinson disease. Four items significantly discriminated between dementia groups and showed good levels of sensitivity (range: 78.6%-80.3%) and specificity (range: 73.9%-79.3%). The scale had very good levels of test-retest (Cronbach's alpha: 0.82) and interrater (0.81) reliabilities. The four items loaded onto three different factors. These items were: 1) marked differences in functioning during the daytime; 2) daytime somnolence; 3) daytime drowsiness; and 4) altered levels of consciousness during the day. CONCLUSIONS We identified four items that provide valid, sensitive, and specific questions for reliably identifying CF and distinguishing the Lewy body dementias from other major causes of dementia (Alzheimer disease and vascular dementia).
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Increasing commercial pressures on land are provoking fundamental and far-reaching changes in the relationships between people and land. Much knowledge on land-oriented investments projects currently comes from the media. Although this provides a good starting point, lack of transparency and rapidly changing contexts mean that this is often unreliable. The International Land Coalition, in partnership with Oxfam Novib, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), University of Pretoria, Centre for Development and Environment of the University of Bern (CDE), and GIZ, started to compile an inventory of land-related investments. This project aims to better understand the extent, trends and impacts of land-related investments by supporting an ongoing and systematic stocktaking exercise of the various investment projects currently taking place worldwide. It involves a large number of organizations and individuals working in areas where land transactions are being made, and able to provide details of such investments. The project monitors land transactions in rural areas that imply a transformation of land use rights from communities and smallholders to commercial use, and are made both by domestic and foreign investors (private actors, governments, government-back private investors). The focus is on investments for food or agrofuel production, timber extraction, carbon trading, mineral extraction, conservation and tourism. A novel way of using ITC to document land acquisitions in a spatially explicit way and by using an approach called “crowdsourcing” is being developed. This approach will allow actors to share information and knowledge directly and at any time on a public platform, where it will be scrutinized in terms of reliability and cross checked with other sources. Up to now, over 1200 deals have been recorded across 96 countries. Details of such transactions have been classified in a matrix and distributed to over 350 contacts worldwide for verification. The verified information has been geo-referenced and represented in two global maps. This is an open database enabling a continued monitoring exercise and the improvement of data accuracy. More information will be released over time. The opportunities arise from overcoming constraints by incomplete information by proposing a new way of collecting, enhancing and sharing information and knowledge in a more democratic and transparent manner. The intention is to develop interactive knowledge platform where any interested person can share and access information on land deals, their link to involved stakeholders, and their embedding into a geographical context. By making use of new ICT technologies that are more and more in the reach of local stakeholders, as well as open access and web-based spatial information systems, it will become possible to create a dynamic database containing spatial explicit data. Feeding in data by a large number of stakeholders, increasingly also by means of new mobile ITC technologies, will open up new opportunities to analyse, monitor and assess highly dynamic trends of land acquisition and rural transformation.
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This article develops an integrative framework of the concept of perceived brand authenticity (PBA) and sheds light on PBA’s (1) measurement, (2) drivers, (3) consequences, as well as (4) an underlying process of its effects and (5) boundary conditions. A multi-phase scale development process resulted in a 15-item PBA scale to measure its four dimensions of credibility, integrity, symbolism, and continuity. PBA is influenced by indexical, existential, and iconic cues, whereby the latter’s influence is moderated by consumers’ level of marketing skepticism. Results also suggest that PBA drives brand choice likelihood through self-congruence for consumers high in self-authenticity.
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Although brand authenticity is gaining increasing interest in consumer behavior research and managerial practice, literature on its measurement and contribution to branding theory is still limited. This article develops an integrative framework of the concept of brand authenticity and reports the development and validation of a scale measuring consumers' perceived brand authenticity (PBA). A multi-phase scale development process resulted in a 15-item PBA scale measuring four dimensions: credibility, integrity, symbolism, and continuity. This scale is reliable across different brands and cultural contexts. We find that brand authenticity perceptions are influenced by indexical, existential, and iconic cues, whereby some of the latters' influence is moderated by consumers' level of marketing skepticism. Results also suggest that PBA increases emotional brand attachment and word-of-mouth, and that it drives brand choice likelihood through self-congruence for consumers high in self-authenticity.
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The north-eastern escarpment of Madagascar harbours the island’s last remaining large-scale humid forest massifs surrounded by a small-scale agricultural mosaic. There is high deforestation, commonly thought to be caused by shifting cultivation practiced by local land users to produce upland rice. However, little is known about the dynamics between forest and shifting cultivation systems at a regional level. Our study presents a first attempt to quantify changes in the extent of forest and different agricultural land cover classes, and to identify the main dynamics of land cover change for two intervals, 1995–2005 and 2005–2011. Over the 16-year study period, the speed of forest loss increased, the total area of upland rice production remained almost stable, and the area of irrigated rice fields slightly increased. While our findings seem to confirm a general trend of land use intensification, deforestation through shifting cultivation is still on the rise. Deforestation mostly affects the small forest fragments interspersed in the agricultural mosaic and is slowly leading to a homogenization of the landscape. These findings have important implications for future interventions to slow forest loss in the region, as the processes of agricultural expansion through shifting cultivation versus intensified land use cannot per se be considered mutually exclusive.
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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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The value of wildlife has long been ignored or under-rated. However, growing concerns about biodiversity loss and emerging diseases of wildlife origin have enhanced debates about the importance of wildlife. Wildlife-related diseases are viewed through these debates as a potential threat to wildlife conservation and domestic animal and human health. This article provides an overview of the values we place on wildlife (positive: socio-cultural, nutritional, economic, ecological; and negative: damages, health issues) and of the significance of diseases for biodiversity conservation. It shows that the values of wildlife, the emergence of wildlife diseases and biodiversity conservation are closely linked. The article also illustrates why investigations into wildlife diseases are now recognized as an integral part of global health issues. The modern One Health concept requires multi-disciplinary research groups including veterinarians, human physicians, ecologists and other scientists collaborating towards a common goal: prevention of disease emergence and preservation of ecosystems, both of which are essential to protect human life and well-being.