Review of FEWS NET Biophysical Monitoring Requirements

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users: it focused upon operational requirements to determine additional useful remote sensing data and; subsequently, beneficial FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world, enabling a robust set of professional perspectives to be gathered and analyzed rapidly. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard: that high resolution remote sensing products continue to be in demand, and that rainfall and vegetation products were valued as data that provide actionable food security information

GCIP water and energy budget synthesis (WEBS)

As part of the World Climate Research Program\u27s (WCRPs) Global Energy and Water-Cycle Experiment (GEWEX) Continental-scale International Project (GCIP), a preliminary water and energy budget synthesis (WEBS) was developed for the period 1996–1999 from the “best available” observations and models. Besides this summary paper, a companion CD-ROM with more extensive discussion, figures, tables, and raw data is available to the interested researcher from the GEWEX project office, the GAPP project office, or the first author. An updated online version of the CD-ROM is also available at http://ecpc.ucsd.edu/gcip/webs.htm/. Observations cannot adequately characterize or “close” budgets since too many fundamental processes are missing. Models that properly represent the many complicated atmospheric and near-surface interactions are also required. This preliminary synthesis therefore included a representative global general circulation model, regional climate model, and a macroscale hydrologic model as well as a global reanalysis and a regional analysis. By the qualitative agreement among the models and available observations, it did appear that we now qualitatively understand water and energy budgets of the Mississippi River Basin. However, there is still much quantitative uncertainty. In that regard, there did appear to be a clear advantage to using a regional analysis over a global analysis or a regional simulation over a global simulation to describe the Mississippi River Basin water and energy budgets. There also appeared to be some advantage to using a macroscale hydrologic model for at least the surface water budgets

Deficiency of the lipid synthesis enzyme, DGAT1, extends longevity in mice

Calorie restriction results in leanness, which is linked to metabolic conditions that favor longevity. We show here that deficiency of the triglyceride synthesis enzyme acyl CoA:diacylglycerol acyltransferase 1 (DGAT1), which promotes leanness, also extends longevity without limiting food intake. Female DGAT1-deficient mice were protected from age-related increases in body fat, tissue triglycerides, and inflammation in white adipose tissue. This protection was accompanied by increased mean and maximal life spans of ~25% and ~10%, respectively. Middle-aged Dgat1−/− mice exhibited several features associated with longevity, including decreased levels of circulating insulin growth factor 1 (IGF1) and reduced fecundity. Thus, deletion of DGAT1 in mice provides a model of leanness and extended lifespan that is independent of calorie restriction

Generation and conceptualization of cognitive styles of learning of enterprise negotiators for adaptation of tutorial teaching in the web

A presente pesquisa foi desenvolvida no cerne do projeto multidisciplinar e multinstitucional "Tapejara" - Sistemas Inteligentes de Ensino na Internet-. O artigo apresenta os Estilos Cognitivos de Aprendizagem gerados a partir dos resultados da aplicação do Teste Ross e da Bateria de Provas de Raciocínio BPR-5 numa amostra de funcionários da população-alvo do Curso de Negociação Empresarial a ser ministrado pela empresa parceira de telecomunicações. Os resultados da testagem cognitiva foram submetidos a análises fatoriais e, a seguir, a uma análise de cluster que, com seus respectivos dendogramas, possibilitaram o agrupamento da população em cinco grandes grupos a saber: Analógico-analítico, Concreto-genérico, Dedutivo-avaliativo, Relacional-sintético e Sintético-avaliativo. Os Estilos Cognitivos de Aprendizagem permitirão a Modelagem Cognitiva do Agente-Aprendiz que possibilitará um ensino tutorial adaptado às necessidades próprias de cada estilo cognitivo, e que assista eficazmente o aprendizado de forma assíncrona e individualizada.This article presents a research developed in the core of a multidisciplinary Project 'Tapejara' - Intelligent Systems of Instruction in the Internet -. The article presents, mainly, the Cognitive Styles of Learning generated from the results of Test Ross and BPR-5 Test applications in the employee's partner Company. The results from the cognitive assessment were submitted to a Cluster Analysis. The dendogramms allowed grouping the target population in five groups: Analogue-analytical, Concrete-generic, Evaluative-deductive, Relational-synthetic and Synthetic-evaluative. In the Project 'Tapejara', the Cognitive Styles of Learning will make possible to build the Student Model of the Pedagogical Agent, consequently will allow a tutorial adapted to the individual learning differences

Geração de estilos cognitivos de aprendizagem de negociadores empresariais para adaptação de ensino tutorializado na web

This article presents a research developed in the core of a multidisciplinary Project 'Tapejara' - Intelligent Systems of Instruction in the Internet -. The article presents, mainly, the Cognitive Styles of Learning generated from the results of Test Ross and BPR-5 Test applications in the employee's partner Company. The results from the cognitive assessment were submitted to a Cluster Analysis. The dendogramms allowed grouping the target population in five groups: Analogue-analytical, Concrete-generic, Evaluative-deductive, Relational-synthetic and Synthetic-evaluative. In the Project 'Tapejara', the Cognitive Styles of Learning will make possible to build the Student Model of the Pedagogical Agent, consequently will allow a tutorial adapted to the individual learning differences.A presente pesquisa foi desenvolvida no cerne do projeto multidisciplinar e multinstitucional "Tapejara" - Sistemas Inteligentes de Ensino na Internet-. O artigo apresenta os Estilos Cognitivos de Aprendizagem gerados a partir dos resultados da aplicação do Teste Ross e da Bateria de Provas de Raciocínio BPR-5 numa amostra de funcionários da população-alvo do Curso de Negociação Empresarial a ser ministrado pela empresa parceira de telecomunicações. Os resultados da testagem cognitiva foram submetidos a análises fatoriais e, a seguir, a uma análise de cluster que, com seus respectivos dendogramas, possibilitaram o agrupamento da população em cinco grandes grupos a saber: Analógico-analítico, Concreto-genérico, Dedutivo-avaliativo, Relacional-sintético e Sintético-avaliativo. Os Estilos Cognitivos de Aprendizagem permitirão a Modelagem Cognitiva do Agente-Aprendiz que possibilitará um ensino tutorial adaptado às necessidades próprias de cada estilo cognitivo, e que assista eficazmente o aprendizado de forma assíncrona e individualizada

NASAs Seasonal Hydrological Forecast System for Improved Food Insecurity Early Warning in Africa

To develop a seasonal scale drought forecasting system to strengthen FEWS NET's progressive early warning efforts in Africa and the Middle East. This presentation provides an overview of the implementation, validation, and ongoing operational applications of this system

Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle

Histone deacetylases as new therapy targets for platinum-resistant epithelial ovarian cancer

Introduction: In developed countries, ovarian cancer is the fourth most common cancer in women. Due to the nonspecific symptomatology associated with the disease many patients with ovarian cancer are diagnosed late, which leads to significantly poorer prognosis. Apart from surgery and radiotherapy, a substantial number of ovarian cancer patients will undergo chemotherapy and platinum based agents are the mainstream first-line therapy for this disease. Despite the initial efficacy of these therapies, many women relapse; therefore, strategies for second-line therapies are required. Regulation of DNA transcription is crucial for tumour progression, metastasis and chemoresistance which offers potential for novel drug targets. Methods: We have reviewed the existing literature on the role of histone deacetylases, nuclear enzymes regulating gene transcription. Results and conclusion: Analysis of available data suggests that a signifant proportion of drug resistance stems from abberant gene expression, therefore HDAC inhibitors are amongst the most promising therapeutic targets for cancer treatment. Together with genetic testing, they may have a potential to serve as base for patient-adapted therapies