52 resultados para Semi dwarf
Resumo:
Famines are often linked to drought in semi-arid areas of Sub-Saharan Africa where not only pastoralists, but also increasingly agro-pastoralists are affected. This study addresses the interplay between drought and famine in the rural semi-arid areas of Makueni district, Kenya, by examining whether, and how crop production conditions and agro-pastoral strategies predispose smallholder households to drought-triggered food insecurity. If this hypothesis holds, then approaches to deal with drought and famine have to target factors causing household food insecurity during non-drought periods. Data from a longitudinal survey of 127 households, interviews, workshops, and daily rainfall records (1961–2003) were analysed using quantitative and qualitative methods. This integrated approach confirms the above hypothesis and reveals that factors other than rainfall, like asset and labour constraints, inadequate policy enforcement, as well as the poverty-driven inability to adopt risk-averse production systems play a key role. When linking these factors to the high rainfall variability, farmer-relevant definitions and forecasts of drought have to be applied.
Resumo:
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.
Resumo:
Changes in agricultural practices of semi-natural mountain grasslands are expected to modify plant community structure and shift dominance patterns. Using vegetation surveys of 11 sites in semi-natural grasslands of the Swiss Jura and Swiss and French Alps, we determined the relative contribution of dominant, subordinate and transient plant species in grazed and abandoned communities and observed their changes along a gradient of productivity and in response to abandonment of pasturing. The results confirm the humpbacked diversity–productivity relationship in semi-natural grassland, which is due to the increase of subordinate species number at intermediate productivity levels. Grazed communities, at the lower or higher end of the species diversity gradient, suffered higher species loss after grazing abandonment. Species loss after abandonment of pasturing was mainly due to a higher reduction in the number of subordinate species, as a consequence of the increasing proportion of dominant species. When plant biodiversity maintenance is the aim, our results have direct implications for the way grasslands should be managed. Indeed, while intensification and abandonment have been accelerated since few decades, our findings in this multi-site analysis confirm the importance of maintaining intermediate levels of pasturing to preserve biodiversity.
Resumo:
Context. Planet formation models have been developed during the past years to try to reproduce what has been observed of both the solar system and the extrasolar planets. Some of these models have partially succeeded, but they focus on massive planets and, for the sake of simplicity, exclude planets belonging to planetary systems. However, more and more planets are now found in planetary systems. This tendency, which is a result of radial velocity, transit, and direct imaging surveys, seems to be even more pronounced for low-mass planets. These new observations require improving planet formation models, including new physics, and considering the formation of systems. Aims: In a recent series of papers, we have presented some improvements in the physics of our models, focussing in particular on the internal structure of forming planets, and on the computation of the excitation state of planetesimals and their resulting accretion rate. In this paper, we focus on the concurrent effect of the formation of more than one planet in the same protoplanetary disc and show the effect, in terms of architecture and composition of this multiplicity. Methods: We used an N-body calculation including collision detection to compute the orbital evolution of a planetary system. Moreover, we describe the effect of competition for accretion of gas and solids, as well as the effect of gravitational interactions between planets. Results: We show that the masses and semi-major axes of planets are modified by both the effect of competition and gravitational interactions. We also present the effect of the assumed number of forming planets in the same system (a free parameter of the model), as well as the effect of the inclination and eccentricity damping. We find that the fraction of ejected planets increases from nearly 0 to 8% as we change the number of embryos we seed the system with from 2 to 20 planetary embryos. Moreover, our calculations show that, when considering planets more massive than ~5 M⊕, simulations with 10 or 20 planetary embryos statistically give the same results in terms of mass function and period distribution.
Resumo:
Access to sufficient quantities of safe drinking water is a human right. Moreover, access to clean water is of public health relevance, particularly in semi-arid and Sahelian cities due to the risks of water contamination and transmission of water-borne diseases. We conducted a study in Nouakchott, the capital of Mauritania, to deepen the understanding of diarrhoeal incidence in space and time. We used an integrated geographical approach, combining socio-environmental, microbiological and epidemiological data from various sources, including spatially explicit surveys, laboratory analysis of water samples and reported diarrhoeal episodes. A geospatial technique was applied to determine the environmental and microbiological risk factors that govern diarrhoeal transmission. Statistical and cartographic analyses revealed concentration of unimproved sources of drinking water in the most densely populated areas of the city, coupled with a daily water allocation below the recommended standard of 20 l per person. Bacteriological analysis indicated that 93% of the non-piped water sources supplied at water points were contaminated with 10-80 coliform bacteria per 100 ml. Diarrhoea was the second most important disease reported at health centres, accounting for 12.8% of health care service consultations on average. Diarrhoeal episodes were concentrated in municipalities with the largest number of contaminated water sources. Environmental factors (e.g. lack of improved water sources) and bacteriological aspects (e.g. water contamination with coliform bacteria) are the main drivers explaining the spatio-temporal distribution of diarrhoea. We conclude that integrating environmental, microbiological and epidemiological variables with statistical regression models facilitates risk profiling of diarrhoeal diseases. Modes of water supply and water contamination were the main drivers of diarrhoea in this semi-arid urban context of Nouakchott, and hence require a strategy to improve water quality at the various levels of the supply chain.
Resumo:
Identifying drivers of species diversity is a major challenge in understanding and predicting the dynamics of species-rich semi-natural grasslands. In particular in temperate grasslands changes in land use and its consequences, i.e. increasing fragmentation, the on-going loss of habitat and the declining importance of regional processes such as seed dispersal by livestock, are considered key drivers of the diversity loss witnessed within the last decades. It is a largely unresolved question to what degree current temperate grassland communities already reflect a decline of regional processes such as longer distance seed dispersal. Answering this question is challenging since it requires both a mechanistic approach to community dynamics and a sufficient data basis that allows identifying general patterns. Here, we present results of a local individual- and trait-based community model that was initialized with plant functional types (PFTs) derived from an extensive empirical data set of species-rich grasslands within the `Biodiversity Exploratories' in Germany. Driving model processes included above- and belowground competition, dynamic resource allocation to shoots and roots, clonal growth, grazing, and local seed dispersal. To test for the impact of regional processes we also simulated seed input from a regional species pool. Model output, with and without regional seed input, was compared with empirical community response patterns along a grazing gradient. Simulated response patterns of changes in PFT richness, Shannon diversity, and biomass production matched observed grazing response patterns surprisingly well if only local processes were considered. Already low levels of additional regional seed input led to stronger deviations from empirical community pattern. While these findings cannot rule out that regional processes other than those considered in the modeling study potentially play a role in shaping the local grassland communities, our comparison indicates that European grasslands are largely isolated, i.e. local mechanisms explain observed community patterns to a large extent.
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In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.
Resumo:
BACKGROUND AND PURPOSE Precise mechanisms underlying the effectiveness of the stroke unit (SU) are not fully established. Studies that compare monitored stroke units (semi-intensive type, SI-SU) versus an intensive care unit (ICU)-based mobile stroke team (MST-ICU) are lacking. Although inequalities in access to stroke unit care are globally improving, acute stroke patients may be admitted to Intensive Care Units for monitoring and followed by a mobile stroke team in hospital's lacking an SU with continuous cardiovascular monitoring. We aimed at comparing the stroke outcome between SI-SU and MST-ICU and hypothesized that the benefits of SI-SU are driven by additional elements other than cardiovascular monitoring, which is equally offered in both care systems. METHODS In a single-center setting, we compared the unfavorable outcomes (dependency and mortality) at 3 months in consecutive patients with ischemic stroke or spontaneous intracerebral hemorrhage admitted to a stroke unit with semi-intensive monitoring (SI-SU) to a cohort of stroke patients hospitalized in an ICU and followed by a mobile stroke team (MST-ICU) during an equal observation period of 27 months. Secondary objectives included comparing mortality and the proportion of patients with excellent outcomes (modified Rankin Score (mRS) 0-1). Equal cardiovascular monitoring was offered in patients admitted in both SI-SU and MST-ICU. RESULTS 458 patients were treated in the SI-SU and compared to the MST-ICU (n = 370) cohort. The proportion of death and dependency after 3 months was significantly improved for patients in the SI-SU compared to MST-ICU (p < 0.001; aOR = 0.45; 95% CI: 0.31-0.65). The shift analysis of the mRS distribution showed significant shift to the lower mRS in the SI-SU group, p < 0.001. The proportion of mortality in patients after 3 months also differed between the MST-ICU and the SI-SU (p < 0.05), but after adjusting for confounders this association was not significant (aOR = 0.59; 95% CI: 0.31-1.13). The proportion of patients with excellent outcome was higher in the SI-SU (59.4 vs. 44.9%, p < 0.001) but the relationship was no more significant after adjustment (aOR = 1.17; 95% CI: 0.87-1.5). CONCLUSIONS Our study shows that moving from a stroke team in a monitored setting (ICU) to an organized stroke unit leads to a significant reduction in the 3 months unfavorable outcome in patients with an acute ischemic or hemorrhagic stroke. Cardiovascular monitoring is indispensable, but benefits of a semi-intensive Stroke Unit are driven by additional elements beyond intensive cardiovascular monitoring. This observation supports the ongoing development of Stroke Centers for efficient stroke care. © 2015 S. Karger AG, Basel.
Resumo:
While most events related to the International Year of Deserts and Desertification 2006 took mainly a problem-oriented perspective and approach, the Bern Symposium held in May 2006 tried to adopt a more positive attitude by attempting to take stock of experience as well as best and worst practices in the past, both in development practice and in research. Through this deliberate focus on potentials, positive experiences, solutions and pathways, predominant passive and reactive attitudes and hopelessness might be better overcome. The Symposium was organized by CDE, NCCR North-South and Forum SLM.
Resumo:
The growth rate of atmospheric carbondioxide(CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO 2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.