957 resultados para Ensemble nodal
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BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package
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Comprend : De guerre, paix ; Pyramide+ renversee sur la mort de Gaspar de Coligny ; Au :Roy: +Roi+ ; Ce que Dieu touche ard
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Species' geographic ranges are usually considered as basic units in macroecology and biogeography, yet it is still difficult to measure them accurately for many reasons. About 20 years ago, researchers started using local data on species' occurrences to estimate broad scale ranges, thereby establishing the niche modeling approach. However, there are still many problems in model evaluation and application, and one of the solutions is to find a consensus solution among models derived from different mathematical and statistical models for niche modeling, climatic projections and variable combination, all of which are sources of uncertainty during niche modeling. In this paper, we discuss this approach of ensemble forecasting and propose that it can be divided into three phases with increasing levels of complexity. Phase I is the simple combination of maps to achieve a consensual and hopefully conservative solution. In Phase II, differences among the maps used are described by multivariate analyses, and Phase III consists of the quantitative evaluation of the relative magnitude of uncertainties from different sources and their mapping. To illustrate these developments, we analyzed the occurrence data of the tiger moth, Utetheisa ornatrix (Lepidoptera, Arctiidae), a Neotropical moth species, and modeled its geographic range in current and future climates.
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Comprend : Brief discours et histoire d'un voyage de quelques François en Floride : & du massacre autant injustement que barbarement executé sur eux, par les Hespagnols, l'an mil cinq cens soixante cinq
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Titre original : Lehrbuch der Institutionen der römischen Rechtex
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To assess the value of sampling lymph nodes located far sidelong colorectal cancer specimens, we analyzed retrospectively surgical specimens from 345 colorectal cancer patients. The mesocolic and perirectal fat was divided into 2 fractions: close to (<5 cm) and distant from (>5 cm) the tumor. Tumors were located in the cecum (n = 61), ascending colon (n = 29), transverse colon (n = 31), descending colon (n = 27), sigmoid colon (n = 108), and rectum (n = 89). The median number of lymph nodes sampled was 17 in both fractions (range, 4-66), 12 (range, 0-46) in the close fraction, and 3 (range, 0-33) in the distant fraction. There were 169 pN0, 104 pN1, and 72 pN2 cases. The pN staging was accurate in all cases except 10 based on the close fraction alone; of these, 6 were upstaged from pN0 to pN1 and 4 from pN1 to pN2 when the distant fraction was considered. Among pN1-upstaged cases, 5 were rectal (3/5 with neoadjuvant radiotherapy) and 1 colonic. In the colon, we found that lymph node location is more important than lymph node number because metastatic lymph nodes were present mostly in the peritumoral area. This suggests that lymph nodes should be initially recovered from the pericolic fat close to the tumor. If there are less than 4 positive lymph nodes and less than 12 lymph nodes examined in total, additional lymph nodes should be retrieved from the distal fraction for potential upstaging. In the rectum, systematic sampling of close and distant lymph nodes is mandatory because in rare cases, metastases are detected only in distant lymph nodes, particularly in patients who have undergone neoadjuvant radiotherapy.
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The extended Gaussian ensemble (EGE) is introduced as a generalization of the canonical ensemble. This ensemble is a further extension of the Gaussian ensemble introduced by Hetherington [J. Low Temp. Phys. 66, 145 (1987)]. The statistical mechanical formalism is derived both from the analysis of the system attached to a finite reservoir and from the maximum statistical entropy principle. The probability of each microstate depends on two parameters ß and ¿ which allow one to fix, independently, the mean energy of the system and the energy fluctuations, respectively. We establish the Legendre transform structure for the generalized thermodynamic potential and propose a stability criterion. We also compare the EGE probability distribution with the q-exponential distribution. As an example, an application to a system with few independent spins is presented.