980 resultados para RESOURCES ALLOCATION


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The purpose of this policy is to introduce a transparent approach to making best use of resources in plastic surgery and related specialties. It was finalised after a formal Public Consultation that included distribution of the Consultation Document to a range of organisations and individuals, meetings with Board representatives as requested and press releases in local and regional media outlets. All responses to the Consultation were considered carefully in developing this final policy. åÊ åÊ

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Strategic Resources Framework

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Allocating Resources to HSS Boards: Proposed Changes to the Weighted Capitation Formula - Final Consultation Summary

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Water resources management, as also water service provision projects in developing countries have difficulties to take adequate decisions due to scarce reliable information, and a lack of proper information managing. Some appropriate tools need to be developed in order to improve decision making to improve water management and access of the poorest, through the design of Decision Support Systems (DSS). On the one side, a DSS for developing co-operation projects on water access improvement has been developed. Such a tool has specific context constrains (structure of the system, software requirements) and needs (Logical Framework Approach monitoring, organizational-learning, accountability and evaluation) that shall be considered for its design. Key aspects for its successful implementation have appeared to be a participatory design of the system and support of the managerial positions at the inception phase. A case study in Tanzania was conducted, together with the Spanish NGO ONGAWA – Ingeniería para el Desarrollo. On the other side, DSS are required also to improve decision making on water management resources in order to achieve a sustainable development that not only improves the living conditions of the population in developing countries, but that also does not hinder opportunities of the poorest on those context. A DSS made to fulfil these requirements shall be using information from water resources modelling, as also on the environment and the social context. Through the research, a case study has been conducted in the Central Rift Valley of Ethiopia, an endhorreic basin 160 km south of Addis Ababa. There, water has been modelled using ArcSWAT, a physically based model which can assess the impact of land management practices on large complex watersheds with varying soils, land use and management conditions over long periods of time. Moreover, governance on water and environment as also the socioeconomic context have been studied.

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Sex allocation data in eusocial Hymenoptera (ants, bees and wasps) provide an excellent opportunity to assess the effectiveness of kin selection, because queens and workers differ in their relatedness to females and males. The first studies on sex allocation in eusocial Hymenoptera compared population sex investment ratios across species. Female-biased investment in monogyne (= with single-queen colonies) populations of ants suggested that workers manipulate sex allocation according to their higher relatedness to females than males (relatedness asymmetry). However, several factors may confound these comparisons across species. First, variation in relatedness asymmetry is typically associated with major changes in breeding system and life history that may also affect sex allocation. Secondly, the relative cost of females and males is difficult to estimate across sexually dimorphic taxa, such as ants. Thirdly, each species in the comparison may not represent an independent data point, because of phylogenetic relationships among species. Recently, stronger evidence that workers control sex allocation has been provided by intraspecific studies of sex ratio variation across colonies. In several species of eusocial Hymenoptera, colonies with high relatedness asymmetry produced mostly females, in contrast to colonies with low relatedness asymmetry which produced mostly males. Additional signs of worker control were found by investigating proximate mechanisms of sex ratio manipulation in ants and wasps. However, worker control is not always effective, and further manipulative experiments will be needed to disentangle the multiple evolutionary factors and processes affecting sex allocation in eusocial Hymenoptera.

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The evolution of eusociality, here defined as the emergence of societies with reproductive division of labour and cooperative brood care, was first seen as a challenge to Darwin's theory of evolution by natural selection. Why should individuals permanently forgo direct reproduction to help other individuals to reproduce? Kin selection, the indirect transmission of genes through relatives, is the key process explaining the evolution of permanently nonreproductive helpers. However, in some taxa helpers delay reproduction until a breeding opportunity becomes available. Overall, eusociality evolved when ecological conditions promote stable associations of related individuals that benefit from jointly exploiting and defending common resources. High levels of cooperation and robust mechanisms of division of labour are found in many animal societies. However, conflicts among individuals are still frequent when group members that are not genetically identical compete over reproduction or resource allocation.

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A Third Report from the Capitation Formula Review Group

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Syrian dry areas have been for several millennia a place of interaction between human populations and the environment. If environmental constraints and heterogeneity condition the human occupation and exploitation of resources, socio-political, economic and historical elements play a fundamental role. Since the late 1980s, Syrian dry areas are viewed as suffering a serious water crisis, due to groundwater overdraft. The Syrian administration and international development agencies believe that groundwater overexploitation is also leading to a decline of agricultural activities and to poverty increase. Action is thus required to address these problems.However, the overexploitation diagnosis needs to be reviewed. The overexploitation discourse appears in the context of Syria's opening to international organizations and to the market economy. It echoes the international discourse of "global water crisis". The diagnosis is based on national indicators recycling old Soviet data that has not been updated. In the post-Soviet era, the Syrian national water policy seems to abandon large surface water irrigation projects in favor of a strategy of water use rationalization and groundwater conservation in crisis regions, especially in the district of Salamieh.This groundwater conservation policy has a number of inconsistencies. It is justified for the administration and also probably for international donors, since it responds to an indisputable environmental emergency. However, efforts to conserve water are anecdotal or even counterproductive. The water conservation policy appears a posteriori as an extension of the national policy of food self-sufficiency. The dominant interpretation of overexploitation, and more generally of the water crisis, prevents any controversary approach of the status of resources and of the agricultural system in general and thus destroys any attempt to discuss alternatives with respect to groundwater management, allocation, and their inclusion in development programs.A revisited diagnosis of the situation needs to take into account spatial and temporal dimensions of the groundwater exploitation and to analyze the co-evolution of hydrogeological and agricultural systems. It should highlight the adjustments adopted to cope with environmental and economic variability, changes of water availability and regulatory measures enforcements. These elements play an important role for water availability and for the spatial, temporal, sectoral allocation of water resource. The groundwater exploitation in the last century has obviously had an impact on the environment, but the changes are not necessarily catastrophic.The current groundwater use in central Syria increases the uncertainty by reducing the ability of aquifers to buffer climatic changes. However, the climatic factor is not the only source of uncertainty. The high volatility of commodity prices, fuel, land and water, depending on the market but also on the will (and capacity) of the Syrian State to preserve social peace is a strong source of uncertainty. The research should consider the whole range of possibilities and propose alternatives that take into consideration the risks they imply for the water users, the political will to support or not the local access to water - thus involving a redefinition of the economic and social objectives - and finally the ability of international organizations to reconsider pre-established diagnoses.

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Triatoma rubrovaria has become the most frequently captured triatomine species after the control of T. infestans in the State of Rio Grande do Sul (RS), Brazil. Isoenzymatic and chromatic studies indicate the existence of, at least, two distinct phenotypic patterns of T. rubrovaria in RS. The geographic variation noted through molecular tools may also result in distinct profiles of vectorial potentiality. In order to enhance our understanding of the bionomic knowledge of T. rubrovaria separate batches of the species were collected from different municipalities of RS distant from 72 to 332 km: Santana do Livramento (natural ecotope), Santana do Livramento (artificial ecotope), Santiago (natural ecotope), Canguçu (peridomicile) and Encruzilhada do Sul (natural ecotope). A total of 285 specimens were collected, 85 specimens kept sufficient fecal material in their guts for the precipitin analysis. The results indicated the food eclecticism for this species and the anti-rodent serum showed the highest positivity in most localities. From the total of analyzed samples, only 1.3% of unique positivity for human blood was registered, all of them for Santiago population. This reactivity to human blood may be associated to pastures activities in the field.

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  Report of the Expert Group on Resource Allocation and Financing in the Health Sector Download this document (PDF 4.77mb) Alternatively, there is a lower resolution version available (PDF 2.31mb) Related Documents Resource Allocation, Financing and Sustainability in Health Care Evidence for the Expert Group on Resource Allocation and Financing in the Health Sector (Volume I) – PDF, 4.25mbAlternatively, a Lower Resolution version is available – PDF, 2.23mb Resource Allocation, Financing and Sustainability in Health Care Evidence for the Expert Group on Resource Allocation and Financing in the Health Sector (Volume II) – PDF 4.87mbAlternatively, a Lower Resolution version is available – PDF, 2.65mb Presentation by Professor, Frances Ruane Director , ESRI and Chair of the Expert Group. PDF 235KB Presentation by Professor Charles Normand, a member of the Expert Group. PDF 32KB

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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.