890 resultados para Conservation Area Networks


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El següent projecte consisteix en analitzar com funciona un sistema SAN, per tal de veure comes pot obtenir un millor rendiment. L’objectiu principal es saber com es comportarà la nostra SAN muntada amb iSCSI a través de la xarxa, volem veure quines són les operacions, les dades i els resultats que comporta crear una RAID a través de discos no locals d’un ordinador i a través d’una xarxa LAN

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The genetic diversity displayed by Plasmodium falciparum, the most deadly Plasmodium species, is a significant obstacle for effective malaria vaccine development. In this study, we identified genetic polymorphisms in P. falciparum glutamate-rich protein (GLURP), which is currently being tested in clinical trials as a malaria vaccine candidate, from isolates found circulating in the Brazilian Amazon at variable transmission levels. The study was performed using samples collected in 1993 and 2008 from rural villages situated near Porto Velho, in the state of Rondônia. DNA was extracted from 126 P. falciparum-positive thick blood smears using the phenol-chloroform method and subjected to a nested polymerase chain reaction protocol with specific primers against two immunodominant regions of GLURP, R0 and R2. Only one R0 fragment and four variants of the R2 fragment were detected. No differences were observed between the two time points with regard to the frequencies of the fragment variants. Mixed infections were uncommon. Our results demonstrate conservation of GLURP-R0 and limited polymorphic variation of GLURP-R2 in P. falciparum isolates from individuals living in Porto Velho. This is an important finding, as genetic polymorphisms in B and T-cell epitopes could have implications for the immunological properties of the antigen.

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The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.

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Habitat loss and fragmentation due to land use changes are major threats to biodiversity in forest ecosystems, and they are expected to have important impacts on many taxa and at various spatial scales. Species richness and area relationships (SARs) have been used to assess species diversity patterns and drivers, and thereby in the establishment of conservation and management strategies. Here we propose a hierarchical approach to achieve deeper insights on SARs in small forest islets in intensive farmland and to address the impacts of decreasing naturalness on such relationships. In the intensive dairy landscapes of Northwest Portugal, where small forest stands (dominated by pines, eucalypts or both) represent semi-natural habitat islands, 50 small forest stands were selected and surveyed for vascular plant diversity. A hierarchical analytical framework was devised to determine species richness and inter- and intra-patch SARs for the whole set of forest patches (general patterns) and for each type of forest (specific patterns). Differences in SARs for distinct groups were also tested by considering subsets of species (native, alien, woody, and herbaceous). Overall, values for species richness were confirmed to be different between forest patches exhibiting different levels of naturalness. Whereas higher values of plant diversity were found in pine stands, higher values for alien species were observed in eucalypt stands. Total area of forest (inter-patch SAR) was found not to have a significant impact on species richness for any of the targeted groups of species. However, significant intra-patch SARs were obtained for all groups of species and forest types. A hierarchical approach was successfully applied to scrutinise SARs along a gradient of forest naturalness in intensively managed landscapes. Dominant canopy tree and management intensity were found to reflect differently on distinct species groups as well as to compensate for increasing stand area, buffering SARs among patches, but not within patches. Thus, the maintenance of small semi-natural patches dominated by pines, under extensive practices of forest management, will promote native plant diversity while at the same time contributing to limit the expansion of problematic alien invasive species.

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Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise. Structural brain adaptations in musicians have been repeatedly demonstrated in areas involved in auditory perception and motor skills. However, musical activities are not confined to auditory perception and motor performance, but are entangled with higher-order cognitive processes. In consequence, neuronal systems involved in such higher-order processing may also be shaped by experience-driven plasticity. We modelled expertise as a three-level regressor to study possible linear relationships of expertise with grey matter density. The key finding of this study resides in a functional dissimilarity between areas exhibiting increase versus decrease of grey matter as a function of musical expertise. Grey matter density increased with expertise in areas known for their involvement in higher-order cognitive processing: right fusiform gyrus (visual pattern recognition), right mid orbital gyrus (tonal sensitivity), left inferior frontal gyrus (syntactic processing, executive function, working memory), left intraparietal sulcus (visuo-motor coordination) and bilateral posterior cerebellar Crus II (executive function, working memory) and in auditory processing: left Heschl's gyrus. Conversely, grey matter density decreased with expertise in bilateral perirolandic and striatal areas that are related to sensorimotor function, possibly reflecting high automation of motor skills. Moreover, a multiple regression analysis evidenced that grey matter density in the right mid orbital area and the inferior frontal gyrus predicted accuracy in detecting fine-grained incongruities in tonal music.

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We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.

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Melipona bicolor schencki occurs in southern Brazil and at high elevations in southeastern Brazil. It has potential for use in meliponiculture but this stingless bee species is vulnerable to extinction and we have little knowledge about its ecology. In order to gather essential information for species conservation and management, we made a study of seasonal flight activities in its natural environment. We sampled bees entering the nests with pollen, nectar/water and resin/mud, in five colonies during each season. In parallel, we analyzed the influence of hour of the day and meteorological factors on flight activity. Flights were most intense during spring and summer, with daily mean estimates of 2,100 and 2,333 flights respectively, while in fall and winter the daily flight estimate was reduced to 612 and 1,104 flights, respectively. Nectar and water were the most frequently-collected resources, followed by pollen and building materials. This preference occurred in all seasons, but with variations in intensity. During spring, daily flight activity lasted over 14 hours; this period was reduced in the other seasons, reaching eight hours in winter. Meteorological factors were associated with 40.2% of the variation in flight and resource collection activity. Apparently, other factors that we did not measure, such as colony needs and availability of floral resources, also strongly influence the intensity of resource collection.

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We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

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ABSTRACT Stichelia pelotensis (Lepidoptera, Riodinidae) is an endemic and threatened butterfly from the Pampa biome in southern Brazil, and has not been recorded in its type locality in the last 56 years. Recently, a population was found in two sites from extreme south Brazil, Pelotas, Rio Grande do Sul state. These records are an important find given the conservation status of S. pelotensis, since all the information gathered is new and involve the natural history of this species. The information obtained is useful for the management, monitoring and conservation priorities of this species and its associated habitats, since its known distribution is restricted to a narrow area in the Rio Grande do Sul Coastal Plain inside this threatened biome in southern Brazil.

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Because protected areas are a major means of conservation, the extent to which ecosystems are represented under different protection regimes needs to be ascertained. A gap analysis approach was used to assess the representativeness of Chile's terrestrial ecosystems in differing kinds of protected areas. Terrestrial ecosystems were described in terms of potential vegetation, employing three protection scenarios. Scenario 1 was based exclusively on the Chilean National System of Protected Wild Areas (SNASPE). Scenario 2 included all types of public protected areas, namely SNASPE, nature sanctuaries and Ministry of National Heritage lands. Scenario 3 included all items in Scenario 2, but also included private protected areas and biodiversity priority sites. There is insufficient protection of terrestrial ecosystems under the Scenario 2. In addition to the low level of ecosystem protection provided by state protected areas (only 42 of the 127 terrestrial ecosystems had >10% of their area protected), 23 terrestrial ecosystems were identified as having no protection at the national level. Gaps in protection were concentrated in the North (both coastal and inland desertic scrub), Central (thorny scrub, thorny forests, sclerophyllous forests and deciduous coastal forests) and Austral (steppe ecosystems) regions of Chile. These gaps include ecosystems that are of global conservation importance.

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The first breeding records of the Bee-eater in canton de Vaud was recorded in a temporarily disused gravel-pit in the Venoge valley (W Switzerland). In 1996 the reproduction of a single pair failed after the eclosion of the chicks during a long period of uninterrupted rain. In 1997, probably the same pair returned and raised 3 fledglings. In 1998, 4 pairs bred raising 20 feldglings. The site is particularly rich with insects and birds: 12 bird species of the red data list breed in the site and surrounding area. However, it is threatened by state project: the gravel-pit is planned to be filled in the coming years. Its future management in relation to the preservation of the Bee-eater and the other bird species on the red data list is presented and discussed.

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In recent decades, recognition of both cultural and natural heritage has grown in the Alps. This tendency illustrates a collective identity building (local, national, alpine), but it also highlights, in the current context of global change, a renewed reflection of man's relationship with the environment. Thus, a fundamental and scientific intrinsic value (as a part of wilderness) tends to be recognized in the natural heritage as a whole. However, geoheritage (and geodiversity) is still often perceived as a secondary natural component, compared with bioheritage (and biodiversity). In this context, we study the geomorphological heritage (landforms and the processes that shape them) of Les Contamines-Montjoie Natural Reserve. Indeed, despite the high geomorphological richness (especially glacial) of the reserve, which covers more than 4000 ha of the Mont-Blanc Massif, local recognition of this heritage is still limited. In order to recognize and protect it, and starting with a scientific study, this research identifies the main local richness and assesses the geotourist and educational potentials. Finally, several tools to educate and promote geoheritage (educational paths and website) are proposed.

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Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

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Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

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ABSTRACT Water erosion is one of the main factors driving soil degradation, which has large economic and environmental impacts. Agricultural production systems that are able to provide soil and water conservation are of crucial importance in achieving more sustainable use of natural resources, such as soil and water. The aim of this study was to evaluate soil and water losses in different integrated production systems under natural rainfall. Experimental plots under six different land use and cover systems were established in an experimental field of Embrapa Agrossilvipastoril in Sinop, state of Mato Grosso, Brazil, in a Latossolo Vermelho-Amarelo Distrófico (Udox) with clayey texture. The treatments consisted of perennial pasture (PAS), crop-forest integration (CFI), eucalyptus plantation (EUC), soybean and corn crop succession (CRP), no ground cover (NGC), and forest (FRS). Soil losses in the treatments studied were below the soil loss limits (11.1 Mg ha-1 yr-1), with the exception of the plot under bare soil (NGC), which exhibited soil losses 30 % over the tolerance limit. Water losses on NGC, EUC, CRP, PAS, CFI and FRS were 33.8, 2.9, 2.4, 1.7, 2.4, and 0.5 % of the total rainfall during the period of study, respectively.