Personality factors and orientation to organizational strategy.

Dept. of Psychology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1983 .K473. Source: Masters Abstracts International, Volume: 40-07, page: . Thesis (M.A.)--University of Windsor (Canada), 1983

Task characteristics and individual differences in task design for computer-based clerical work.

It was proposed that the principal effects of computerization on job content in clerical work can be described in terms of increasing or decreasing task complexity and job decision latitude. The purpose of the study was as follows: (a) to investigate, in computer-based clerical tasks, the effects of variations in task complexity and job decision latitude on performance, subjective workload, and perceptual and affective responses to the work; and (b) to assess the effects of individual differences in abilities, personal control beliefs, and work preferences on reactions to task characteristics. One hundred and thirty-four female undergraduate students performed proofreading, text entry, and data entry tasks on a micro-computer. The subjects performed the tasks under one of four combinations of work conditions: low or high task complexity, and low or high job decision latitude. As hypothesized, subjects performed better when task complexity was low rather than high. The subjects reported lower workload when job decision latitude was high rather than low. With regard to perceptual and affective responses to the work, subjects in the high job decision latitude condition perceived their work to be lower in complexity than subjects in the low job decision latitude condition. Predicted relationships between abilities, locus of control, and work aspect preferences were not observed. Contrary to predictions, neither ability or locus of control moderated perceptual and affective responses to the work. Consistent with predictions from theories of job enrichment, strong associations were observed between perceptions of high task complexity, meaningfulness, and skill-utilization, and intrinsic task satisfaction. Implications of these findings for the psychologically-based design of computerized clerical work are discussed. Source: Dissertation Abstracts International, Volume: 50-08, Section: B, page: 3738. Thesis (Ph.D.)--University of Windsor (Canada), 1989

Clinical sequencing identifies potential actionable alterations in a high rate of urachal and primary bladder adenocarcinomas.

OBJECTIVE Administration of targeted therapies provides a promising treatment strategy for urachal adenocarcinoma (UrC) or primary bladder adenocarcinoma (PBAC); however, the selection of appropriate drugs remains difficult. Here, we aimed to establish a routine compatible methodological pipeline for the identification of the most important therapeutic targets and potentially effective drugs for UrC and PBAC. METHODS Next-generation sequencing, using a 161 cancer driver gene panel, was performed on 41 UrC and 13 PBAC samples. Clinically relevant alterations were filtered, and therapeutic interpretation was performed by in silico evaluation of drug-gene interactions. RESULTS After data processing, 45/54 samples passed the quality control. Sequencing analysis revealed 191 pathogenic mutations in 68 genes. The most frequent gain-of-function mutations in UrC were found in KRAS (33%), and MYC (15%), while in PBAC KRAS (25%), MYC (25%), FLT3 (17%) and TERT (17%) were recurrently affected. The most frequently affected pathways were the cell cycle regulation, and the DNA damage control pathway. Actionable mutations with at least one available approved drug were identified in 31/33 (94%) UrC and 8/12 (67%) PBAC patients. CONCLUSIONS In this study, we developed a data-processing pipeline for the detection and therapeutic interpretation of genetic alterations in two rare cancers. Our analyses revealed actionable mutations in a high rate of cases, suggesting that this approach is a potentially feasible strategy for both UrC and PBAC treatments

What do hospital decision-makers in Ontario, Canada, have to say about the fairness of priority setting in their institutions?

BACKGROUND: Priority setting, also known as rationing or resource allocation, occurs at all levels of every health care system. Daniels and Sabin have proposed a framework for priority setting in health care institutions called 'accountability for reasonableness', which links priority setting to theories of democratic deliberation. Fairness is a key goal of priority setting. According to 'accountability for reasonableness', health care institutions engaged in priority setting have a claim to fairness if they satisfy four conditions of relevance, publicity, appeals/revision, and enforcement. This is the first study which has surveyed the views of hospital decision makers throughout an entire health system about the fairness of priority setting in their institutions. The purpose of this study is to elicit hospital decision-makers' self-report of the fairness of priority setting in their hospitals using an explicit conceptual framework, 'accountability for reasonableness'. METHODS: 160 Ontario hospital Chief Executive Officers, or their designates, were asked to complete a survey questionnaire concerning priority setting in their publicly funded institutions. Eight-six Ontario hospitals completed this survey, for a response rate of 54%. Six close-ended rating scale questions (e.g. Overall, how fair is priority setting at your hospital?), and 3 open-ended questions (e.g. What do you see as the goal(s) of priority setting in your hospital?) were used. RESULTS: Overall, 60.7% of respondents indicated their hospitals' priority setting was fair. With respect to the 'accountability for reasonableness' conditions, respondents indicated their hospitals performed best for the relevance (75.0%) condition, followed by appeals/revision (56.6%), publicity (56.0%), and enforcement (39.5%). CONCLUSIONS: For the first time hospital Chief Executive Officers within an entire health system were surveyed about the fairness of priority setting practices in their institutions using the conceptual framework 'accountability for reasonableness'. Although many hospital CEOs felt that their priority setting was fair, ample room for improvement was noted, especially for the enforcement condition

Comparison of SIFT Encoded and Deep Learning Features for the Classification and Detection of Esca Disease in Bordeaux Vineyards

Grapevine wood fungal diseases such as esca are among the biggest threats in vineyards nowadays. The lack of very efficient preventive (best results using commercial products report 20% efficiency) and curative means induces huge economic losses. The study presented in this paper is centered around the in-field detection of foliar esca symptoms during summer, exhibiting a typical “striped„ pattern. Indeed, in-field disease detection has shown great potential for commercial applications and has been successfully used for other agricultural needs such as yield estimation. Differentiation with foliar symptoms caused by other diseases or abiotic stresses was also considered. Two vineyards from the Bordeaux region (France, Aquitaine) were chosen as the basis for the experiment. Pictures of diseased and healthy vine plants were acquired during summer 2017 and labeled at the leaf scale, resulting in a patch database of around 6000 images (224 × 224 pixels) divided into red cultivar and white cultivar samples. Then, we tackled the classification part of the problem comparing state-of-the-art SIFT encoding and pre-trained deep learning feature extractors for the classification of database patches. In the best case, 91% overall accuracy was obtained using deep features extracted from MobileNet network trained on ImageNet database, demonstrating the efficiency of simple transfer learning approaches without the need to design an ad-hoc specific feature extractor. The third part aimed at disease detection (using bounding boxes) within full plant images. For this purpose, we integrated the deep learning base network within a “one-step„ detection network (RetinaNet), allowing us to perform detection queries in real time (approximately six frames per second on GPU). Recall/Precision (RP) and Average Precision (AP) metrics then allowed us to evaluate the performance of the network on a 91-image (plants) validation database. Overall, 90% precision for a 40% recall was obtained while best esca AP was about 70%. Good correlation between annotated and detected symptomatic surface per plant was also obtained, meaning slightly symptomatic plants can be efficiently separated from severely attacked plants

Spatial pattern analysis of flavescence dorée repartition in vineyards from the Bordeaux region

The devastating incidence of flavesence dorée on vineyards throughout the world motivates for a better comprehension of this epidemic disease. In this study, we highlight the characteristic spatial non-random distribution of flavescence dorée diseased plants on a set of 7 vineyards from the Bordeaux region plot. In a first time, we propose a simple statistical framework using Monte-Carlo simulations in order to assess the randomness of the disease repartition. Several statistics are considered such as the mean distance to the nearest diseased neighbor or divergence (using Kullback-Leibler dissimilarity symmetric variant) of the distance histogram to the average distance histogram of random simulations. The performance of these statistics is first evaluated on a set of generated repartitions at different randomness levels using ROC curves as a visual representation of the risks associated with the test. Histogram comparison was found to be more effective and robust for the detection of non-random configurations. The proposed algorithm is then used on real data, showing significant aggregations patterns and edge effect on some of the plots for flavesence dorée diseased plants but also uprooted plants

Internet of food and farming

National audienceLe projet IOF vise à développer le concept de l’agriculture de précision en le fusionnant avec le concept de Internet of Things. Le smart farming and alimentation se base sur un réseau de capteurs connectées à bas coût, capable de suivre du près la chaîne de production. Le système est coordonnée par un gateway IOT et soutenu par une base de données, un logiciel de gestion et une système de décision

In Field Detection of Downy Mildew Symptoms with Proximal Colour Imaging

This paper proposes to study the potentialities of on-board colour imaging for the in-field detection of a textbook case disease: the grapevine downy mildew. It introduces an algorithmic strategy for the detection of various forms of foliar symptoms on proximal high-resolution images. The proposed strategy is based on structure–colour representations and probabilistic models of grapevine tissues. It operates in three steps: (i) Formulating descriptors to extract the characteristic and discriminating properties of each class. They combine the Local Structure Tensors (LST) with colorimetric statistics calculated in pixel’s neighbourhood. (ii) Modelling the statistical distributions of these descriptors in each class. To account for the specific nature of LSTs, the descriptors are mapped in the Log-Euclidean space. In this space, the classes of interest can be modelled with mixtures of multivariate Gaussian distributions. (iii) Assigning each pixel to one of the classes according to its suitability to their models. The decision method is based on a “seed growth segmentation” process. This step exploits statistical criteria derived from the probabilistic model. The resulting processing chain reliably detects downy mildew symptoms and estimates the area of the affected tissues. A leave-one-out cross-validation is conducted on a dataset constituted of a hundred independent images of grapevines affected only by downy mildew and/or abiotic stresses. The proposed method achieves an extensive and accurate recovery of foliar symptoms, with on average, a 83% pixel-wise precision and a 76% pixel-wise recall

What do hospital decision-makers in Ontario, Canada, have to say about the fairness of priority setting in their institutions?

Abstract Background Priority setting, also known as rationing or resource allocation, occurs at all levels of every health care system. Daniels and Sabin have proposed a framework for priority setting in health care institutions called 'accountability for reasonableness', which links priority setting to theories of democratic deliberation. Fairness is a key goal of priority setting. According to 'accountability for reasonableness', health care institutions engaged in priority setting have a claim to fairness if they satisfy four conditions of relevance, publicity, appeals/revision, and enforcement. This is the first study which has surveyed the views of hospital decision makers throughout an entire health system about the fairness of priority setting in their institutions. The purpose of this study is to elicit hospital decision-makers' self-report of the fairness of priority setting in their hospitals using an explicit conceptual framework, 'accountability for reasonableness'. Methods 160 Ontario hospital Chief Executive Officers, or their designates, were asked to complete a survey questionnaire concerning priority setting in their publicly funded institutions. Eight-six Ontario hospitals completed this survey, for a response rate of 54%. Six close-ended rating scale questions (e.g. Overall, how fair is priority setting at your hospital?), and 3 open-ended questions (e.g. What do you see as the goal(s) of priority setting in your hospital?) were used. Results Overall, 60.7% of respondents indicated their hospitals' priority setting was fair. With respect to the 'accountability for reasonableness' conditions, respondents indicated their hospitals performed best for the relevance (75.0%) condition, followed by appeals/revision (56.6%), publicity (56.0%), and enforcement (39.5%). Conclusions For the first time hospital Chief Executive Officers within an entire health system were surveyed about the fairness of priority setting practices in their institutions using the conceptual framework 'accountability for reasonableness'. Although many hospital CEOs felt that their priority setting was fair, ample room for improvement was noted, especially for the enforcement condition.</p