9 resultados para Automatic Animal Call Recognition

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

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During the past 20 years or so, more has become known about the properties of khat, its pharmacology, physiological and psychological effects on humans. However, at the same time its reputation of social and recreational use in traditional contexts has hindered the dissemination of knowledge about its detrimental effects in terms of mortality. This paper focuses on this particular deficit and adds to the knowledge-base by reviewing the scant literature that does exist on mortality associated with the trade and use of khat. We sought all peer-reviewed papers relating to deaths associated with khat. From an initial list of 111, we identified 15 items meeting our selection criteria. Examination of these revealed 61 further relevant items. These were supplemented with published reports, newspaper and other media reports. A conceptual framework was then developed for classifying mortality associated with each stage of the plant's journey from its cultivation, transportation, consumption, to its effects on the human body. The model is demonstrated with concrete examples drawn from the above sources. These highlight a number of issues for which more substantive statistical data are needed, including population-based studies of the physiological and psychological determinants of khat-related fatalities. Khat-consuming communities, and health professionals charged with their care should be more aware of the physiological and psychological effects of khat, together with the risks for morbidity and mortality associated with its use. There is also a need for information to be collected at international and national levels on other causes of death associated with khat cultivation, transportation, and trade. Both these dimensions need to be understood.

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Chemicals can elicit T-cell-mediated diseases such as allergic contact dermatitis and adverse drug reactions. Therefore, testing of chemicals, drugs and protein allergens for hazard identification and risk assessment is essential in regulatory toxicology. The seventh amendment of the EU Cosmetics Directive now prohibits the testing of cosmetic ingredients in mice, guinea pigs and other animal species to assess their sensitizing potential. In addition, the EU Chemicals Directive REACh requires the retesting of more than 30,000 chemicals for different toxicological endpoints, including sensitization, requiring vast numbers of animals. Therefore, alternative methods are urgently needed to eventually replace animal testing. Here, we summarize the outcome of an expert meeting in Rome on 7 November 2009 on the development of T-cell-based in vitro assays as tools in immunotoxicology to identify hazardous chemicals and drugs. In addition, we provide an overview of the development of the field over the last two decades.

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Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are syndromes of acute diffuse damage to the pulmonary parenchyma by a variety of local or systemic insults. Increased alveolar capillary membrane permeability was recognized as the common end organ injury and a central feature in all forms of ALI/ARDS. Although great strides have been made in understanding the pathogenesis of ALI/ARDS and in intensive care medicine, the treatment approach to ARDS is still relying on ventilatory and cardiovascular support based on the recognition of the clinical picture. In the course of evaluating novel treatment approaches to ARDS, 3 models of ALI induced in different species, i.e. the surfactant washout lavage model, the oleic acid intravenous injection model and the endotoxin injection model, were widely used. This review gives an overview of the pathological characteristics of these models from studies in pigs, dogs or sheep. We believe that a good morphological description of these models, both spatially and temporally, will help us gain a better understanding of the real pathophysiological picture and apply these models more accurately and liberally in evaluating novel treatment approaches to ARDS.

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A large number of studies utilize animal models to investigate therapeutic angiogenesis. However, the lack of a standardized experimental model leaves the comparison of different studies problematic. To establish a reference model of prolonged moderate tissue ischemia, we created unilateral hind limb ischemia in athymic rnu-rats by surgical excision of the femoral vessels. Blood flow of the limb was monitored for 60 days by laser Doppler imaging. Following a short postoperative period of substantially depressed perfusion, the animals showed a status of moderate hind limb ischemia from day 14 onwards. Thereafter, the perfusion remained at a constant level (55.5% of normal value) until the end of the observation period. Histopathological assessment of the ischemic musculature on postoperative days 28 and 60 showed essentially no inflammatory cell infiltrate or fibrosis. However, the mitochondrial activity and capillary-to-fiber ratio of the muscular tissue was reduced to 52.7% of normal, presenting with a significant weakness of the ischemic limb evidenced by a progressive decline in performance. Intramuscular injection of culture-expanded human endothelial progenitor cells (EPC) resulted in a significant increase in blood flow (82.0+/-3.5% of normal), capillary density (1.60+/-0.08/muscle fiber) and smooth muscle covered arterioles (8.0+/-0.6/high power field) in the ischemic hind limb as compared to controls (55.0+/-3.1%; 0.99+/-0.03; 5.0+/-0.2). In conclusion, chronic, moderate hind limb ischemia with consistently reduced perfusion levels persisting over a prolonged period can be established reliably in rnu athymic nude rats and is responsive to pro-angiogenic treatments such as EPC transplantation. This study provides a detailed protocol of a highly reproducible reference model to test novel therapeutic options for limb ischemia.

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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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Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

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The scientific literature of laboratory animal research is replete with papers reporting poor reproducibility of results as well as failure to translate results to clinical trials in humans. This may stem in part from poor experimental design and conduct of animal experiments. Despite widespread recognition of these problems and implementation of guidelines to attenuate them, a review of the literature suggests that experimental design and conduct of laboratory animal research are still in need of refinement. This paper will review and discuss possible sources of biases, highlight advantages and limitations of strategies proposed to alleviate them, and provide a conceptual framework for improving the reproducibility of laboratory animal research.