899 resultados para Singapore retail


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BACKGROUND: Detection of pre-neoplastic gastric mucosal changes and early gastric cancer (EGC) by white-light endoscopy (WLE) is often difficult. In this study we investigated whether combined autofluorescence imaging (AFI) and narrow band imaging (NBI) can improve detection of pre-neoplastic lesions and early gastric cancer in high-risk patients.

PATIENTS AND METHODS: Chinese patients who were 50-years-old or above with dyspepsia were examined by both high-resolution WLE and combined AFI followed by NBI (AFI-NBI), consecutively in a prospective randomized cross-over setting, by two experienced endoscopists. The primary outcome was diagnostic ability of the two methods for patients with pre-neoplastic lesions such as intestinal metaplasia (IM) and mucosal atrophy.

RESULTS: Sixty-five patients were recruited. One patient with large advanced gastric cancer was found and excluded from the analysis. Among the remaining 64 patients, 38 (59%) had IM; of these, 26 (68%) were correctly identified by AFI-NBI (sensitivity 68%, specificity 23%) and only 13 (34%) by WLE (sensitivity 34%, specificity 65%). AFI-NBI detected more patients with IM than did WLE (p=0.011). Thirty-one patients (48%) had mucosal atrophy. Ten patients (32%) were identified by AFI-NBI (sensitivity 32%, specificity 79%) and four patients (13%) by WLE (sensitivity 13%, specificity 88%) (p=0.100). No dysplasia or EGC was found.

CONCLUSION: AFI-NBI identified significantly more patients with IM than did WLE. Our result warrants further studies to define the role of combined AFI-NBI endoscopy for detection of precancerous conditions.

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Relatório de estágio de mestrado, Ciências da Educação (Formação de Adultos), Universidade de Lisboa, Instituto de Educação, 2013

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This paper discusses the literature on the established determinants of productivity in the retail sector. It also draws attention to some neglected strands of research which provide useful insights into strategies that could allow productivity enhancements in this area of the economy. To date, very few attempts have been made to integrate different specialisms in order to explain what drives productivity in retail. Here this paper rectifies this omission by putting together studies from economics, geography, knowledge management and employment studies. It is the authors' view that quantitative studies of retail productivity should focus on total factor productivity in retailing as the result of competition/composition effects, planning regulations, information and communications technology, the multinational operation element and workforce skills. Further, the fact that retail firms possess advantages that are transferable between locations suggests that investment in strategies enhancing the transfer of explicit and tacit knowledge between and within businesses are crucial to achieve productivity gains.

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Studies on microbial characterization of cold-smoked salmon and salmon trout during cold storage were performed on samples available in the Portuguese market. Samples were also classified microbiologically according to guidelines for ready-to-eat (RTE) products. Further investigations on sample variability and microbial abilities to produce tyramine and histamine were also performed. The coefficient of variation for viable counts of different groups of microorganisms of samples collected at retail market point was high in the first 2 wk of storage, mainly in the Enterobacteriaceae group and aerobic plate count (APC), suggesting that microbiological characteristics of samples were different in numbers, even within the same batch from the same producer. This variation seemed to be decreased when storage and temperature were controlled under lab conditions. The numbers of Enterobacteriaceae were influenced by storage temperature, as indicated by low microbial numbers in samples from controlled refrigeration. Lactic acid bacteria (LAB) and Enterobacteriaceae were predominant in commercial products, a significant percentage of which were tyramine and less histamine producers. These results might be influenced by (1) the technological processes in the early stages of production, (2) contamination during the smoking process, and (3) conditions and temperature fluctuations during cold storage at retail market point of sale.

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Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Double degree. A Work Project presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA- School of Business and Economics and Warsaw School of Economics

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This work project (WP) is a study about a clustering strategy for Sport Zone. The general cluster study’s objective is to create groups such that within each group the individuals are similar to each other, but should be different among groups. The clusters creation is a mix of common sense, trial and error and some statistical supporting techniques. Our particular objective is to support category managers to better define the product type to be displayed in the stores’ shelves by doing store clusters. This research was carried out for Sport Zone, and comprises an objective definition, a literature review, the clustering activity itself, some factor analysis and a discriminant analysis to better frame our work. Together with this quantitative part, a survey addressed to category managers to better understand their key drivers, for choosing the type of product of each store, was carried out. Based in a non-random sample of 65 stores with data referring to 2013, the final result was the choice of 6 store clusters (Figure 1) which were individually characterized as the main outcome of this work. In what relates to our selected variables, all were important for the distinction between clusters, which proves the adequacy of their choice. The interpretation of the results gives category managers a tool to understand which products best fit the clustered stores. Furthermore, as a side finding thanks to the clusterization, a STP (Segmentation, Targeting and Positioning) was initiated, being this WP the first steps of a continuous process.