850 resultados para Organizational case studies


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Abstract: Cryptosporidiosis is a very prominent disease in the field of public health, and usually causes diarrhea. We describe two immunocompetent patients who presented with chronic diarrhea that was ultimately found to be caused by continuous exposure to well water contaminated with the microbial cysts (oocysts) of the Cryptosporidium spp parasite. We describe the patients' histories and possible explanations for their prolonged symptoms.

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The main purpose of the research is to present a proposal for a methodology to support the rehabilitation project of renders of old buildings. To achieve the objective it was considered essential to define the main types of participants and aspects to integrate the proposal. The research methodology consists in an inquiry presented to several professional participants in rehabilitation, a market study of materials and products available in Portugal, the design of a methodology proposal and its application to a case study. The inquiry sample totals 24 answers from the targeted professionals. A sequence of relevant supporting procedures consists in the proposal, which aims to provide a supporting methodology to decide and project in this context and also to be tested with its application to the building. This proposal was applied to an old building with load-bearing stone masonry walls and air-lime based renders. It was concluded that the assessment of the building and external renderings’ condition, its diagnosis and of the supporting walls, the definition of intervention, the specification of materials to be used and performance requirements to comply, and also plans for conservation and periodic maintenance, are crucial. From the inquiry, compatibility between materials and complementary roles and points of view of different types of participants in rehabilitation must be highlighted. A proposal for a methodology to support the project could provide useful guidance particularly for architects and construction engineers, and improve the understanding of direct participants on site, therefore contributing for the correct implementation of the intervention.

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Export activities are a major source of economic growth and are considered important both at the national level and for individual businesses. Moreover, in the case of SMEs, they gain particular relevance, exporting being the most common foreign market entry mode for these firms. The decision maker’s role in the export activity is crucial, particularly in the case of SMEs. However, the extant literature on internationalization is characterized by a lack of consensus among scholars as to what constitutes the managerial factor in determining exporting. Therefore, this study focuses on the following issue: Which are the decision maker’s characteristics and perceptions that may influence the export behaviour of Catalan SMEs? To address this question a multiple case study method is applied across four Catalan exporting SMEs. The methodology chosen for analysing the empirical data is relying on the proposition testing approach while the investigation is conducted including both within and cross-case analysis. The findings show that high educational level, language skills, high risk tolerance, innovativeness as well as strongly perceived export stimuli as compared to low and easy to overcome export barriers positively influence the export involvement and development of SMEs. The study provides further insights into the research topic by jointly studying managerial characteristics and perceptions. Additionally, the majority of research on exporting topics has been carried out in the USA, so there is a clear need of investigation in the field in other countries, moreover in Spain where the exporting activities have not been as widely studied.

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In legal medicine, the post mortem interval (PMI) of interest covers the last 50 years. When only human skeletal remains are found, determining the PMI currently relies mostly on the experience of the forensic anthropologist, with few techniques available to help. Recently, several radiometric methods have been proposed to reveal PMI. For instance, (14)C and (90)Sr bomb pulse dating covers the last 60 years and give reliable PMI when teeth or bones are available. (232)Th series dating has also been proposed but requires a large amount of bones. In addition, (210)Pb dating is promising but is submitted to diagenesis and individual habits like smoking that must be handled carefully. Here we determine PMI on 29 cases of forensic interest using (90)Sr bomb pulse. In 12 cases, (210)Pb dating was added to narrow the PMI interval. In addition, anthropological investigations were carried out on 15 cases to confront anthropological expertise to the radiometric method. Results show that 10 of the 29 cases can be discarded as having no forensic interest (PMI>50 years) based only on the (90)Sr bomb pulse dating. For 10 other cases, the additional (210)Pb dating restricts the PMI uncertainty to a few years. In 15 cases, anthropological investigations corroborate the radiometric PMI. This study also shows that diagenesis and inter-individual difference in radionuclide uptake represent the main sources of uncertainty in the PMI determination using radiometric methods.

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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.

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Every year, debris flows cause huge damage in mountainous areas. Due to population pressure in hazardous zones, the socio-economic impact is much higher than in the past. Therefore, the development of indicative susceptibility hazard maps is of primary importance, particularly in developing countries. However, the complexity of the phenomenon and the variability of local controlling factors limit the use of processbased models for a first assessment. A debris flow model has been developed for regional susceptibility assessments using digital elevation model (DEM) with a GIS-based approach.. The automatic identification of source areas and the estimation of debris flow spreading, based on GIS tools, provide a substantial basis for a preliminary susceptibility assessment at a regional scale. One of the main advantages of this model is its workability. In fact, everything is open to the user, from the data choice to the selection of the algorithms and their parameters. The Flow-R model was tested in three different contexts: two in Switzerland and one in Pakistan, for indicative susceptibility hazard mapping. It was shown that the quality of the DEM is the most important parameter to obtain reliable results for propagation, but also to identify the potential debris flows sources.

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The understanding of sedimentary evolution is intimately related to the knowledge of the exact ages of the sediments. When working on carbonate sediments, age dating is commonly based on paleontological observations and established biozonations, which may prove to be relatively imprecise. Dating by means of strontium isotope ratios in marine bioclasts is the probably best method in order to precisely date carbonate successions, provided that the sample reflects original marine geochemical characteristics. This requires a precise study of the samples including its petrography, SEM and cathodoluminescence observations, stable carbon and oxygen isotope geochemistry and finally the strontium isotope measurement itself. On the Nicoya Peninsula (Northwestern Costa Rica) sediments from the Piedras Blancas Formation, Nambi Formation and Quebrada Pavas Formation were dated by the means of strontium isotope ratios measured in Upper Cretaceous Inoceramus shell fragments. Results have shown average 87Sr/86Sr values of 0.707654 (middle late Campanian) for the Piedras Blancas Formation, 0.707322 (Turonian-Coniacian) for the Nambi Formation and 0.707721 (late Campanian-Maastrichtian) for the Quebrada Pavas Formation. Abundant detrital components in the studied formations constitute a difficulty to strontium isotope dating. In fact, the fossil bearing sediments can easily contaminate the target fossil with strontium mobilized form basalts during diagenesis and thus the obtained strontium isotope ratios may be influenced significantly and so will the obtained ages. The new and more precise age assignments allow for more precision in the chronostratigraphic chart of the sedimentary and tectonic evolution of the Nicoya Peninsula, providing a better insight on the evolution of this region. Meteor Cruise M81 dredged shallow water carbonates from the Hess Rise and Hess Escarpment during March 2010. Several of these shallow water carbonates contain abundant Larger Foraminifera that indicates an Eocene-Oligocene age. In this study the strontium isotope values ranging from 0.707847 to 0.708238 can be interpreted as a Rupelian to Chattian age of these sediments. These platform sediments are placed on seamounts, now located at depths reaching 1600 m. Observation of sedimentologic characteristics of these sediments has helped to resolve apparent discrepancies between fossil and strontium isotope ages. Hence, it is possible to show that the subsidence was active during early Miocene times. On La Désirade (Guadeloupe France), the Neogene to Quaternary carbonate cover has been dated by microfossils and some U/Th-ages. Disagreements subsisted in the paleontological ages of the formations. Strontium isotope ratios ranging from 0.709047 to 0.709076 showed the Limestone Table of La Désirade to range from an Early Pliocene to Late Pliocene/early Pleistocene age. A very late Miocene age (87Sr/86Sr =0.709013) can be determined to the Detrital Offshore Limestone. The flat volcanic basement had to be eroded by wave-action during a long-term stable relative sea-level. Sediments of the Table Limestone on La Désirade show both low-stand and high-stand facies that encroach on the igneous basement, implying deposition during a major phase of subsidence creating accommodation space. Subsidence is followed by tectonic uplift documented by fringing reefs and beach rocks that young from the top of the Table Limestone (180 m) towards the present coastline. Strontium isotope ratios from two different fringing reefs (0.707172 and 0.709145) and from a beach rock (0.709163) allow tentative dating, (125ky, ~ 400ky, 945ky) and indicate an uplift rate of about 5cm/ky for this time period of La Désirade Island. The documented subsidence and uplift history calls for a new model of tectonic evolution of the area.

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Secular variations of the seawater carbon isotopic composition provide evidence for paleoceanographic and paleoclimatic changes and may serve for chemiostratigraphic correlations. The present study aimed to improve the current knowledge on the Upper Permian and Triassic segment of the Phanerozoic marine carbon isotope curve, whose Triassic part was poorly constrained by previous studies. Profiles of inorganic carbon isotopes are provided for sections from Himalaya (Salt Range, Kashmir, Spiti and Nepal), Oman and North Dobrogea (Romania) on the basis of whole-rock carbonate analysis. The data acquired, together with a literature compilation confirmed that most of the Upper Permian is characterized by high δ13C values (averaging +40/00) but failed to detect a positive excursion as suggested by recent compilations. In the light of these observations, the large drop in δ13C values associated with the end-Permian mass extinction appears to be driven by a sudden transfer of previously stocked 13C depleted carbon, rather than by the overturn of a Late Permian stratified ocean. The Triassic data-set outlines significant secular variations. The best documented is a carbon isotope positive excursion just across the Lower-Middle Triassic boundary, globally developed since it was detected in various paleogeographic settings. It is interpreted to reflect variations in surface ocean chemistry, possibly related to increased primary productivity, at times when the biotic recovery after the end-Permian mass-extinction began to accelerate significantly and when a sharp rise in seawater δ34S values occurred globally. Strontium isotope data obtained from well preserved biogenic phosphates allow a refinement of the Middle Triassic segment of the seawater strontium isotope curve and show a major inflexion point of the seawater strontium isotope curve also near the Lower Triassic - Middle Triassic boundary. These facts suggest that the transition from the Early to the Middle Triassic was a time of revolutionary global change which represented an important step in the evolution of Mesozoic marine environments. A tentative carbon isotope curve for the Upper Permian to Upper Triassic time interval is proposed. Its major features are: ? high but constant δ13C values during the Late Permian ? a sharp drop in δ13C values in the latest Permian ? subsequent recovery of δ13C values ? a short-lived positive excursion across the Early-Middle Triassic boundary ? a gradual rise in δ13C values starting in the Late Ladinian or in the Early Carnian It is foreseen that these fluctuations of the carbon isotope curve may serve as chronostratigraphic markers and further assist in the correlation of Permian and Triassic carbonate deposits.

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The disintegration of the USSR brought the emergence of a new geo-energy space in Central Asia. This space arose in the context of a global energy transition, which began in the late 1970s. Therefore, this new space in a changing energy world requires both new conceptual frameworks of analysis and the creation of new analytical tools. Taking into account this fact, our paper attempts to apply the theoretical framework of the Global Commodity Chain (GCC) to the case of natural resources in Central Asia. The aim of the paper is to check if there could be any Central Asia’s geo-energy space, assuming that this space would exist if natural resources were managed with regional criteria. The paper is divided into four sections. First an introduction that describes the new global energy context within natural resources of Central Asia would be integrated. Secondly, the paper justifies why the GCC methodology is suitable for the study of the value chains of energy products. Thirdly, we build up three cases studies (oil and uranium from Kazakhstan and gas from Turkmenistan) which reveal a high degree of uncertainty over the direction these chains will take. Finally, we present the conclusions of this study that state that the most plausible scenario would be the integration of energy resources of these countries in GCC where the core of the decision-making process will be far away from the region of Central Asia. Key words: Energy transition, geo-energy space, Global Commodity Chains, Central Asia