882 resultados para VEGETATION CLASSIFICATION SYSTEM


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BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

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In the Bolivian Amazon several paleochannel generations are preserved. Their wide spectrum of morphologies clearly provides crucial information on the type and magnitude of geomorphic and hydrological changes within the drainage network of the Andean foreland. Therefore, in this study we mapped geomorphological characteristics of paleochannels, and applied radiocarbon and optically stimulated luminescence dating. Seven paleochannel generations are identified. Significant changes in sinuosity, channel widths and river pattern are observed for the successive paleochannel generations. Our results clearly reflect at least three different geomorphic and hydrological periods in the evolution of the fluvial system since the late Pleistocene. Changes in discharge and sediment load may be controlled by combinations of two interrelated mechanisms: (i) spatial changes and re-organizations of the drainage network in the upper catchment, and/or (ii) climate changes with their associated local to catchment-scale modifications in vegetation cover, and changes in discharge, inundation frequencies and magnitudes, which have likely affected the evolution of the fluvial system in the Llanos de Moxos. In summary, our study has revealed the enormous potential which geomorphic mapping and analysis combined with luminescence based chronologies hold for the reconstruction of the late Pleistocene to recent fluvial system in a large portion of Amazonia.

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The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named 'Immunoscore' has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

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AIMS Information on tumour border configuration (TBC) in colorectal cancer (CRC) is currently not included in most pathology reports, owing to lack of reproducibility and/or established evaluation systems. The aim of this study was to investigate whether an alternative scoring system based on the percentage of the infiltrating component may represent a reliable method for assessing TBC. METHODS AND RESULTS Two hundred and fifteen CRCs with complete clinicopathological data were evaluated by two independent observers, both 'traditionally' by assigning the tumours into pushing/infiltrating/mixed categories, and alternatively by scoring the percentage of infiltrating margin. With the pushing/infiltrating/mixed pattern method, interobserver agreement (IOA) was moderate (κ = 0.58), whereas with the percentage of infiltrating margins method, IOA was excellent (intraclass correlation coefficient of 0.86). A higher percentage of infiltrating margin correlated with adverse features such as higher grade (P = 0.0025), higher pT (P = 0.0007), pN (P = 0.0001) and pM classification (P = 0.0063), high-grade tumour budding (P < 0.0001), lymphatic invasion (P < 0.0001), vascular invasion (P = 0.0032), and shorter survival (P = 0.0008), and was significantly associated with an increased probability of lymph node metastasis (P < 0.001). CONCLUSIONS Information on TBC gives additional prognostic value to pathology reports on CRC. The novel proposed scoring system, by using the percentage of infiltrating margin, outperforms the 'traditional' way of reporting TBC. Additionally, it is reproducible and simple to apply, and can therefore be easily integrated into daily diagnostic practice.

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Information on how species distributions and ecosystem services are impacted by anthropogenic climate change is important for adaptation planning. Palaeo data suggest that Abies alba formed forests under significantly warmer-than-present conditions in Europe and might be a native substitute for widespread drought-sensitive temperate and boreal tree species such as beech (Fagus sylvatica) and spruce (Picea abies) under future global warming conditions. Here, we combine pollen and macrofossil data, modern observations, and results from transient simulations with the LPX-Bern dynamic global vegetation model to assess past and future distributions of A. alba in Europe. LPX-Bern is forced with climate anomalies from a run over the past 21 000 years with the Community Earth System Model, modern climatology, and with 21st-century multimodel ensemble results for the high-emission RCP8.5 and the stringent mitigation RCP2.6 pathway. The simulated distribution for present climate encompasses the modern range of A. alba, with the model exceeding the present distribution in north-western and southern Europe. Mid-Holocene pollen data and model results agree for southern Europe, suggesting that at present, human impacts suppress the distribution in southern Europe. Pollen and model results both show range expansion starting during the Bølling–Allerød warm period, interrupted by the Younger Dryas cold, and resuming during the Holocene. The distribution of A. alba expands to the north-east in all future scenarios, whereas the potential (currently unrealized) range would be substantially reduced in southern Europe under RCP8.5. A. alba maintains its current range in central Europe despite competition by other thermophilous tree species. Our combined palaeoecological and model evidence suggest that A. alba may ensure important ecosystem services including stand and slope stability, infrastructure protection, and carbon sequestration under significantly warmer-than-present conditions in central Europe.

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Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. In this paper, we propose and evaluate a convolutional neural network (CNN), designed for the classification of ILD patterns. The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by average pooling with size equal to the size of the final feature maps and three dense layers. The last dense layer has 7 outputs, equivalent to the classes considered: healthy, ground glass opacity (GGO), micronodules, consolidation, reticulation, honeycombing and a combination of GGO/reticulation. To train and evaluate the CNN, we used a dataset of 14696 image patches, derived by 120 CT scans from different scanners and hospitals. To the best of our knowledge, this is the first deep CNN designed for the specific problem. A comparative analysis proved the effectiveness of the proposed CNN against previous methods in a challenging dataset. The classification performance (~85.5%) demonstrated the potential of CNNs in analyzing lung patterns. Future work includes, extending the CNN to three-dimensional data provided by CT volume scans and integrating the proposed method into a CAD system that aims to provide differential diagnosis for ILDs as a supportive tool for radiologists.

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For a hundred years semi-natural species-rich meadow vegetation has been described from various areas of Switzerland. The first description dates from 1892 by Stebler and Schröter. In the present study, relevés of 65 semi-natural mesophilous meadow associations and communities reported by 26 authors, which were collected throughout the century, are summarized. An increasing number of descriptions dating from the 1980s and 1990s is included. A numerical classification of these 65 types resulted in four main groups of meadow-types. When compared with the existing literature of alliances a high correlation is found with the Polygono-Trisetion Br.-Bl. et R. Tx. ex Marshall 1947, the Arrhenatherion W. Koch 1926, the Agrostio-Festucion Puscaru et al. 1956, the Mesobromion Br.-Bl. et Moor 1938 em. Oberdorfer 1957, and with the Chrysopogonetum W. Koch 1943. The Agrostio-Festucion is characteristic for the montane belt in southern Switzerland and was until recently poorly known. This alliance is discussed in detail. Some classifications of meadow types by the original authors had to be rearranged for the present purpose. The present classification coincides well with the one Stebler and Schröter gave in 1892. Today, after a century of intensive changes in land use, their four main types are still valid.

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The Carrabassett Valley Sanitary District in Carrabassett Valley, Maine has utilized both a forest spray irrigation system and a Snowfluent™ system for the treatment of their wastewater effluent. This study was designed to evaluate potential changes in soil properties after approximately 20 years of treatment in the forested spray irrigation site and three years of treatment in the field Snowfluent™ site. In addition, grass yield and composition were evaluated on the field study sites. After treatment with effluent or Snowfluent™, soils showed an increase in soil exchangeable Ca, Mg, Na, and K, base saturation, and pH. While most constituents were higher in treated soils, available P was lower in treated soils compared to the controls. This difference was attributed to higher rates of P mineralization from soil organic matter due to an irrigation effect of the treatment, depleting available P pools despite the P addition with the treatment. Most of the differences due to treatment were greatest at the surface and diminished with depth. Depth patterns in soil properties mostly reflected the decreasing influence of organic matter and its decomposition products with depth as evidenced by significantly higher total C in the surface compared to lower horizons. There were decreasing concentrations of total N, and exchangeable or extractable Ca, Mg, Na, K, Mn, Zn, and P with depth. In addition, there was decreasing BS with depth, driven primarily by declining exchangeable Ca and Mg. Imgation with Snowfluent™ altered the chemical composition of the grass on the site. All element concentrations were significantly higher in the grass foliage except for Ca. The differences were attributed to the additional nutrients and moisture derived from the Snowfluent™. The use of forest spray imgation and Snowfluent™ as a wastewater treatment strategy appears to work well. The soil and vegetation were able to retain most of the applied nutrients, and do not appear to be moving toward saturation. Vegetation management may be a key tool for managing nutrient accumulation on the grass sites as the system ages.

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Economic historians have recently emphasized the importance of integrating economic and historical approaches in studying institutions. The literature on the Ottoman system of taxation, however, has continued to adopt a primarily historical approach, using ad hoc categories of classification and explaining the system through its continuities with the historical precedent. This paper integrates economic and historical approaches to examine the structure, efficiency, and regional diversity of the tax system. The structure of the system made it possible for the Ottomans to economize on the transaction cost of measuring the tax base. Regional variations resulted from both efficient adaptations and institutional rigidities.

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von Richard Neumann

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Test

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von C. A. Weber