ABSTRACT: This study aimed to characterize the average seasonal pattern of the vegetation in southern grassland in Brazil, and the variability found in the time series of vegetation indices. It also sought to identify similarities in the seasonal pattern of different grassland typologies. Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images from Feb to Dec, 2000 to 2014 were analyzed for ten regions. The grassland typologies studied showed EVI and NDVI profiles consistent with the seasonal dynamics of grassland vegetation under the influence of a subtropical climate, with highest values in the indices during the warm seasons of the year (spring and summer) and lowest in the colder seasons (autumn and winter). Considering the values of EVI and NDVI, grassland typologies were allocated to four groups with similar temporal profiles. Among the groups formed from the EVI index it is possible to identify differences between grassland typologies during the autumn and winter, while the NDVI showed differences only in winter as compared to the other seasons.
Publisher: University of Southern California Digital Library (USC.DL)
Unbalanced resource distribution has been an essential problem for decades. The problem exists in all kinds of domains and causes many negative effects. For example, the widening gap between the rich and the poor is the root of many social problems in our society. For modular robots, scarcity of resource is especially apparent in environments like space, desert, or ocean, where the resource or power is limited and difficult to acquire. In order to improve the performance or lifespan of the task, each modular robot needs to utilize the power within its own system in order to extend the system operation time or have improved performance. ��� However, figuring out how the systems share resource with one another in order to improve the performance of the collective behavior is a challenging task. This is because resource allocation and sharing encompass the status of each agent as well as the environmental condition. The constraints within the environment might limit the resource sharing task or alter resource distribution. ��� In this dissertation, we initiate our research on power sharing for self-reconfigurable modular robots, which can be easily applied to other applications related to unbalanced resource distribution. ��� We start the research by proposing a distributed near-optimal power sharing mechanism for self-reconfigurable modular robots. The goal is to successfully extend the operation time of sets of connected modular robots and also provide a framework of optimal case through distributed computation. This can serve as the foundation for research works that follow. ��� On this basis, we first study the optimality of system lifespan (T��) with the limited supply rate of each robot under consideration. We then propose a centralized and distributed T�� algorithm, which can help the system to efficiently estimate the optimal lifespan of the robotic network. ��� Unavoidably, each link between the robots in the robotic network usually contains loss that is unknown at the beginning. To solve this essential problem, we propose EM-based algorithm to be implemented in both centralized and distributed manner. This way each robot is able to discover such link loss and readjust the resource (power) sharing policy for the purpose of optimally estimate the system operation data concerning resource sharing amount, resource sharing cost, and resource flow. ��� Furthermore, typically, the physical structure of network and its associated maximum system operation time is typically fixed. However, through reconfiguration, the robotic network can possibly reduce the path loss in changing the network configuration physically. By incorporating Minimum Mean Cost Cycle and the setting of Embedded Cost, we are able to suggest a new configuration with improved system operation time. ��� Nevertheless, most resource sharing tasks in the real world are not able to be accomplished instantly due to the constraints of limited resource supply rate of each robot or the limited link capacity. We propose a generalized approach to solving traditional resource allocation and sharing problems. This is called Reward-Driven Minimum Cost Flow, which is to prioritize each sink node and revise the power sharing policy even when the total resource sharing amount is larger than the total link capacity or maximum flow amount. ��� For each topic, various simulations with different settings of agent and network condition are verified under the environment of Unity game engine. The experiment results demonstrate that our scalable algorithms are capable of allocating the resource by estimating its associated amount and providing an intelligent power sharing policy which can optimally extend the system operation time of the robotic networks. ��� In retrospect, the five main contributions of our research can be summarized as the following: The first contribution is a distributed computation framework that can effectively extend the system operation time to an optimal or near-optimal state. The second contribution is to estimate the optimal robotic system operation time and the associated resource sharing amount. This can be done in both centralized and distributed manners with the consideration of source supply rate. The third contribution is to interactively determine an optimal power sharing policy for the lossy robotic networks. The fourth contribution is to suggest a new configuration with the improvement of the robotic system operation time. The fifth contribution is to provide a generalized time-division resource sharing framework to optimally extend the system operation time for the robotic networks. This goal is achievable even when the resource sharing amount exceeds the maximum flow amount of the network.
Agriculture and Agri-Food Canada | Agriculture et Agroalimentaire Canada;
Agriculture and Agri-Food Canada | Agriculture et Agroalimentaire Canada;
Publisher: Open Data Canada
En 2019, l'équipe d'observation de la Terre de la Direction générale des sciences et de la technologie (DGST) d'Agriculture et Agroalimentaire Canada (AAC) a répété le processus visant à produire des cartes numériques de l'inventaire annuel des cultures à l'aide d'images satellitaires pour l'ensemble du Canada, afin de soutenir la réalisation d'un inventaire national des cultures. Une méthodologie par arbre de décision a été utilisée à l'aide d'images satellitaires optiques (Landsat-8, Sentinel-2) et radar (RADARSAT-2), avec une résolution spatiale finale de 30 m. En même temps que les acquisitions par satellite, des données de réalité de terrain ont été fournies par des sociétés d'assurance-récolte provinciales (Alberta, Saskatchewan, Manitoba et Québec), tandis que des observations ponctuelles provenaient du Ministère d'Environnement, Eau et Changement climatique de l'Île-du-Prince-Édouard. L'acquisition de données a aussi été supportée par les centres régionaux de recherches et développement d'AAC à Saint-Jean de Terre-Neuve, Kentville, Charlottetown, Fredericton, et Guelph. In 2019, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Sentinel-2) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Charlottetown, Fredericton, and Guelph.
Abstract The objective of this research was to obtain, for the Brazilian family farming, a measure of the use of the main technologies. Initially, for each meso-region, 59 indicators of the use of various technologies were obtained. Through factor analysis, these indicators were synthesized in four factors, whose values were the basis for the estimative of an index of technology use. It was observed, from these indexes, large regional differences regarding the use of technology in family farming. It was found that the highest levels of technology use are concentrated in the South, but also in the Southeast of Brazil, especially in São Paulo state. In the Central-West, except for the Federal District, average levels prevail. However, in the North and Northeast, in most cases, low or very low levels of technology are predominant.
ABSTRACT: Genome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS are based on random regression or dimensionality reduction methods. In this study a new non-parametric method, called Delta-p was proposed, which was then compared to the Genomic Best Linear Unbiased Predictor (G-BLUP) method. Furthermore, a new selection index combining the genetic values obtained by the G-BLUP and Delta-p, named Delta-p/G-BLUP methods, was proposed. The efficiency of the proposed methods was evaluated through both simulation and real studies. The simulated data consisted of eight scenarios comprising a combination of two levels of heritability, two genetic architectures and two dominance status (absence and complete dominance). Each scenario was simulated ten times. All methods were applied to a real dataset of Asian rice (Oryza sativa) aiming to increase the efficiency of a current breeding program. The methods were compared as regards accuracy of prediction (simulation data) or predictive ability (real dataset), bias and recovery of the true genomic heritability. The results indicated that the proposed Delta-p/G-BLUP index outperformed the other methods in both prediction accuracy and predictive ability.
Publisher: National Folklore Collection, University College Dublin
Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016. Story collected by Eileen Mc Nicholas, a student at Trian na gCléireach school (Treannagleragh, Co. Mayo) from informant Mrs Mc Nicholas. Collected as part of the Schools' Folklore scheme, 1937-1938, under the supervision of teacher Liam Breathnach.
Publisher: Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC)
The Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), 2002-2016, is a global gridded data set at a spatial resolution of 0.5 degrees that presents trends (rate of change measured in centimeters per year) in freshwater availability based on data obtained from 2002 to 2016 by NASA GRACE. Terrestrial water availability storage is the sum of groundwater, soil moisture, snow and ice, surface waters, and wet biomass, expressed as an equivalent height of water. GRACE measures changes in the terrestrial water cycle by assessing small changes in Earth’s gravity field. This observation-based assessment of how the world’s water cycle is responding to human impacts and climate variations provides an important tool for evaluating and predicting emerging threats to water and food security.
Ce produit permet d'améliorer les renseignements détaillés sur le secteur de l'agriculture et de la fabrication agroalimentaire dans le cadre de comptabilité nationale. Ces renseignements détaillés permettent aux utilisateurs d'analyser les ressources en produits et les emplois des produits pour une gamme plus vaste d'activités de l'agriculture et de la transformation, ainsi que de faciliter la comparaison des relations et des effets économiques pour un plus grand nombre d'industries que ne le permettent les tableaux des ressources et des emplois de base. This product enhances the industrial detail available for the agricultural and agri-food manufacturing sector within the national accounting framework. This detail allows users to analyze the supply and use of products across a broader range of farming and processing activities as well as facilitate the comparison of economic relationships and impacts across more industries than is possible in the core Supply and use tables.
This dataset allows to assess the full outcomes of LIPA (Local Indicator of Phylogenetic Association) computed for the foliar spectral profile (wavelengths: 400-2450 nm) among regenerating plants in Neotropical Forest Gaps in the Southern region of Brazil.
ABSTRACT: Foodborne diseases are often related to consumption of contaminated food or water. Viral agents are important sources of contamination and frequently reported in food of animal origin. The goal of this study was to detect emerging enteric viruses in samples of industrialized foods of animal origin collected in establishments from southern of Brazil. In the analyzed samples, no Hepatitis E virus (HEV) genome was detected. However, 21.8% (21/96) of the samples were positive for Rotavirus (RVA) and 61.4% (59/96) for Adenovirus (AdV), including Human adenovirus-C (HAdV-C), Porcine adenovirus-3 (PAdV-3) and new type of porcine adenovirus PAdV-SVN1. In the present research, PAdV-SVN1 was detected in foods for the first time. The presence of these viruses may be related to poor hygiene in sites of food preparation, production or during handling.
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