920 resultados para Uncertainty avoidance
Resumo:
Within corporate contexts, senior leaders must construct credible leadership identities if they are to demonstrate effectiveness in achieving business goals. This is a particular challenge for women, who have struggled historically to gain senior leadership positions. This chapter explores the identity struggles experienced by Karen, a woman Human Resources director within a management meeting as she delivers bad news about ‘company restructuring’ to her colleagues. Using Feminist Poststructuralist Discourse Analysis (FPDA), I show how this leader struggles to maintain a professionally competent identity as she negotiates the bad news. The analysis reveals that despite the demands of her role, Karen demonstrates extraordinary linguistic competence in managing her team within a turbulent business world that continues to remain inhospitable to female leaders.
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The purpose of this thesis is to investigate and understand the effect of a servicescape’s ambient and social conditions on consumers’ service encounter experience and their approach/avoidance behavior in a retail context. In three papers, with a total sample of over 1600 participants (including 550 actual consumers) and seven experiments, the author investigates the effect of music (ambient stimuli), employees’ self-disclosure (verbal social stimuli) and employees’ gazing behavior (nonverbal social stimuli) on consumers’ service encounter experience and approach/avoidance behavior in a retail store. Paper I comprised two experiments, and the aim was to investigate the influence of music on emotions, approach/avoidance behavior. Paper II comprised two experiments, and the aim was to investigate the effect of frontline employees’ personal self-disclosure on consumers’ reciprocal behavior. Paper III comprised three experiments, and the aim was to investigate the influence of employee’s direct eye gaze/ averted eye gaze on consumer emotions, social impression of the frontline employee and encounter satisfaction in different purchase situations. The results in this thesis show that music affects consumers in both positive and negative ways (Paper I). Self-disclosure affects consumers negatively, in such a way that it decreases encounter satisfaction (Paper II) and, finally, eye gaze affects consumers by regulating both positively – and in some cases also negatively – consumers’ social impression of the frontline employee and their encounter satisfaction (Paper III). The conclusions of this thesis are that both ambient and social stimuli in a servicescape affect consumers’ internal responses, which in turn affect their behavior. Depending on the purchase situation, type of retail, and stimuli, the internal and behavioral responses are different.
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The main purpose of this study is to assess the relationship between four bioclimatic indices for cattle (environmental stress, heat load, modified heat load, and respiratory rate predictor indices) and three main milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when the cows use the natural pasture. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty information in the confidence intervals. The main results identify an interesting relationship between the milk compounds and climate indices under all climate conditions. During spring, there are reasonably high correlations between the fat and protein concentrations vs. the climate indices, whereas there are insignificant dependencies between the milk yield and climate indices. During summer, the correlation between the fat and protein concentrations with the climate indices decreased in comparison with the spring results, whereas the correlation for the milk yield increased. This methodology is suggested for studies investigating the impacts of climate variability/change on food and agriculture using short term data considering uncertainty.
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In sexually reproducing organisms, the specific combinations of parental alleles can have important consequences on offspring viability and fitness. Accordingly, genetic relationship between mates can be used as a criterion for mate choice. Here, we used microsatellite genetic markers to estimate the genetic relationship between mating pairs in the wild boar, Sus scrofa. Males, females and foetuses proceeding from Portugal, Spain and Hungary were genotyped using 14 microsatellite markers. The genetic relationship between mates was estimated using different measures of foetus heterozygosity. We found that the observed heterozygosity of foetuses was lower than that expected under random mating. This result occurred mainly when Sd2 (relatedness of parental genomes) was used as the heterozygosity measure. After simulations, we concluded that the observed low heterozygosity was possibly due to outbreeding avoidance. Outbreeding avoidance based on genetically different genomes might play an important role in species evolution and its genetic conservation.
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The paper discusses the evaluation of the uncertainty of a multivariate quantity using the Law of Propagation of Uncertainty defined in the Guide to the Expression of Uncertainty in Measurement (GUM) and a Monte Carlo method according to the GUM’s Supplement 2. The quantity analysed is the electrical impedance, which is not a scalar but a complex quantity. The used measuring method allows the evaluation of the impedance and of its uncertainty in different ways and the corresponding results are presented, compared and discussed. For comparison purposes, results of the impedance uncertainty obtained using the NIST Uncertainty Machine are also presented.
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In the framework of a global transition to a low-carbon energy mix, the interest in advanced nuclear Small Modular Reactors (SMRs) has been growing at the international level. Due to the high level of maturity reached by Severe Accident Codes for currently operating rectors, their applicability to advanced SMRs is starting to be studied. Within the present work of thesis and in the framework of a collaboration between ENEA, UNIBO and IRSN, an ASTEC code model of a generic IRIS reactor has been developed. The simulation of a DBA sequence involving the operation of all the passive safety systems of the generic IRIS has been carried out to investigate the code model capability in the prediction of the thermal-hydraulics characterizing an integral SMR adopting a passive mitigation strategy. The following simulation of 4 BDBAs sequences explores the applicability of Severe Accident Codes to advance SMRs in beyond-design and core-degradation conditions. The uncertainty affecting a code simulation can be estimated by using the method of Input Uncertainty Propagation, whose application has been realized through the RAVEN-ASTEC coupling and implementation on an HPC platform. This probabilistic methodology has been employed in a study of the uncertainty affecting the passive safety system operation in the DBA simulation of ASTEC, providing a further characterization of the thermal-hydraulics of this sequence. The application of the Uncertainty Quantification method to early core-melt phenomena has been investigated in the framework of a BEPU analysis of the ASTEC simulation of the QUENCH test-6 experiment. A possible solution to the encountered challenges has been proposed through the application of a Limit Surface search algorithm.
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Depth represents a crucial piece of information in many practical applications, such as obstacle avoidance and environment mapping. This information can be provided either by active sensors, such as LiDARs, or by passive devices like cameras. A popular passive device is the binocular rig, which allows triangulating the depth of the scene through two synchronized and aligned cameras. However, many devices that are already available in several infrastructures are monocular passive sensors, such as most of the surveillance cameras. The intrinsic ambiguity of the problem makes monocular depth estimation a challenging task. Nevertheless, the recent progress of deep learning strategies is paving the way towards a new class of algorithms able to handle this complexity. This work addresses many relevant topics related to the monocular depth estimation problem. It presents networks capable of predicting accurate depth values even on embedded devices and without the need of expensive ground-truth labels at training time. Moreover, it introduces strategies to estimate the uncertainty of these models, and it shows that monocular networks can easily generate training labels for different tasks at scale. Finally, it evaluates off-the-shelf monocular depth predictors for the relevant use case of social distance monitoring, and shows how this technology allows to overcome already existing strategies limitations.
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The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.
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The aim of this work is to present a general overview of state-of-the-art related to design for uncertainty with a focus on aerospace structures. In particular, a simulation on a FCCZ lattice cell and on the profile shape of a nozzle will be performed. Optimization under uncertainty is characterized by the need to make decisions without complete knowledge of the problem data. When dealing with a complex problem, non-linearity, or optimization, two main issues are raised: the uncertainty of the feasibility of the solution and the uncertainty of the objective value of the function. In the first part, the Design Of Experiments (DOE) methodologies, Uncertainty Quantification (UQ), and then Uncertainty optimization will be deepened. The second part will show an application of the previous theories on through a commercial software. Nowadays multiobjective optimization on high non-linear problem can be a powerful tool to approach new concept solutions or to develop cutting-edge design. In this thesis an effective improvement have been reached on a rocket nozzle. Future work could include the introduction of multi scale modelling, multiphysics approach and every strategy useful to simulate as much possible real operative condition of the studied design.
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In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.
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In recent years, global supply chains have increasingly suffered from reliability issues due to various external and difficult to-manage events. The following paper aims to build an integrated approach for the design of a Supply Chain under the risk of disruption and demand fluctuation. The study is divided in two parts: a mathematical optimization model, to identify the optimal design and assignments customer-facility, and a discrete-events simulation of the resulting network. The first one describes a model in which plant location decisions are influenced by variables such as distance to customers, investments needed to open plants and centralization phenomena that help contain the risk of demand variability (Risk Pooling). The entire model has been built with a proactive approach to manage the risk of disruptions assigning to each customer two types of open facilities: one that will serve it under normal conditions and a back-up facility, which comes into operation when the main facility has failed. The study is conducted on a relatively small number of instances due to the computational complexity, a matheuristic approach can be found in part A of the paper to evaluate the problem with a larger set of players. Once the network is built, a discrete events Supply Chain simulation (SCS) has been implemented to analyze the stock flow within the facilities warehouses, the actual impact of disruptions and the role of the back-up facilities which suffer a great stress on their inventory due to a large increase in demand caused by the disruptions. Therefore, simulation follows a reactive approach, in which customers are redistributed among facilities according to the interruptions that may occur in the system and to the assignments deriving from the design model. Lastly, the most important results of the study will be reported, analyzing the role of lead time in a reactive approach for the occurrence of disruptions and comparing the two models in terms of costs.
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Previous research has shown that crotamine, a toxin isolated from the venom of Crotalus durissus terrificus, induces the release of acetylcholine and dopamine in the central nervous system of rats. Particularly, these neurotransmitters are important modulators of memory processes. Therefore, in this study we investigated the effects of crotamine infusion on persistence of memory in rats. We verified that the intrahippocampal infusion of crotamine (1 μg/μl; 1 μl/side) improved the persistence of object recognition and aversive memory. By other side, the intrahippocampal infusion of the toxin did not alter locomotor and exploratory activities, anxiety or pain threshold. These results demonstrate a future prospect of using crotamine as potential pharmacological tool to treat diseases involving memory impairment, although it is still necessary more researches to better elucidate the crotamine effects on hippocampus and memory.
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This work assessed the environmental impacts of the production and use of 1 MJ of hydrous ethanol (E100) in Brazil in prospective scenarios (2020-2030), considering the deployment of technologies currently under development and better agricultural practices. The life cycle assessment technique was employed using the CML method for the life cycle impact assessment and the Monte Carlo method for the uncertainty analysis. Abiotic depletion, global warming, human toxicity, ecotoxicity, photochemical oxidation, acidification, and eutrophication were the environmental impacts categories analyzed. Results indicate that the proposed improvements (especially no-til farming-scenarios s2 and s4) would lead to environmental benefits in prospective scenarios compared to the current ethanol production (scenario s0). Combined first and second generation ethanol production (scenarios s3 and s4) would require less agricultural land but would not perform better than the projected first generation ethanol, although the uncertainties are relatively high. The best use of 1 ha of sugar cane was also assessed, considering the displacement of the conventional products by ethanol and electricity. No-til practices combined with the production of first generation ethanol and electricity (scenario s2) would lead to the largest mitigation effects for global warming and abiotic depletion. For the remaining categories, emissions would not be mitigated with the utilization of the sugar cane products. However, this conclusion is sensitive to the displaced electricity sources.
Resumo:
The consumption of dietary supplements is highest among athletes and it can represent potential a health risk for consumers. The aim of this study was to determine the prevalence of consumption of dietary supplements by road runners. We interviewed 817 volunteers from four road races in the Brazilian running calendar. The sample consisted of 671 male and 146 female runners with a mean age of 37.9 ± 12.4 years. Of the sample, 28.33% reported having used some type of dietary supplement. The main motivation for this consumption is to increase in stamina and improve performance. The probability of consuming dietary supplements increased 4.67 times when the runners were guided by coaches. The consumption of supplements was strongly correlated (r = 0.97) with weekly running distance, and also highly correlated (r = 0.86) with the number of years the sport had been practiced. The longer the runner had practiced the sport, the higher the training volume and the greater the intake of supplements. The five most frequently cited reasons for consumption were: energy enhancement (29.5%), performance improvement (17.1%), increased level of endurance (10.3%), nutrient replacement (11.1%), and avoidance of fatigue (10.3%). About 30% of the consumers declared more than one reason for taking dietary supplements. The most consumed supplements were: carbohydrates (52.17%), vitamins (28.70%), and proteins (13.48%). Supplement consumption by road runners in Brazil appeared to be guided by the energy boosting properties of the supplement, the influence of coaches, and the experience of the user. The amount of supplement intake seemed to be lower among road runners than for athletes of other sports. We recommend that coaches and nutritionists emphasise that a balanced diet can meet the needs of physically active people.
A Feasibility Study Of Fricke Dosimetry As An Absorbed Dose To Water Standard For 192ir Hdr Sources.
Resumo:
High dose rate brachytherapy (HDR) using 192Ir sources is well accepted as an important treatment option and thus requires an accurate dosimetry standard. However, a dosimetry standard for the direct measurement of the absolute dose to water for this particular source type is currently not available. An improved standard for the absorbed dose to water based on Fricke dosimetry of HDR 192Ir brachytherapy sources is presented in this study. The main goal of this paper is to demonstrate the potential usefulness of the Fricke dosimetry technique for the standardization of the quantity absorbed dose to water for 192Ir sources. A molded, double-walled, spherical vessel for water containing the Fricke solution was constructed based on the Fricke system. The authors measured the absorbed dose to water and compared it with the doses calculated using the AAPM TG-43 report. The overall combined uncertainty associated with the measurements using Fricke dosimetry was 1.4% for k = 1, which is better than the uncertainties reported in previous studies. These results are promising; hence, the use of Fricke dosimetry to measure the absorbed dose to water as a standard for HDR 192Ir may be possible in the future.