Recension des écrits sur l'impact des contacts sexuels précoces sur les hommes.

A review of the literature on the impact of sexual contacts between adults and boys reveals the existence of two principal outcomes: 1) some participants develop various disorders once in adulthood, such as behavioural problems, sexual disorders, or personality problems; 2) some participants do not present with any major disorders in the long run. These different outcomes may be associated with several moderating variables related to the sexual contacts, such as the level of coercion at the time of these contacts, the bond between the child and the adult, or the context of the sexual relation. However, the conclusions relating to the relations between early sexual contacts with adults and subsequent problems of adaptation in adulthood are difficult to determine. This is because of various methodological problems associated with relevant studies (i.e., definition of these contacts, nature of the sample, method evaluation, statistical analyses). In this article, we propose certain avenues of research that may help clarify this problem. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An integrated fuzzy regression-data envelopment analysis algorithm for optimum oil consumption estimation with ambiguous data

This study introduces an integrated fuzzy regression (FR) data envelopment analysis (DEA) algorithm for oil consumption estimation and optimization with uncertain and ambiguous data. This is quite important as oil consumption estimations deals with several uncertainties due to social, economic factors. Furthermore, DEA is integrated with FR because there is no clear cut as to which FR approach is superior for oil consumption estimation. The standard indicators used in this paper are population, cost of crude oil, gross domestic production (GDP) and annual oil production. Fifteen popular and most cited FR models are considered in the algorithm. Each FR model has different approach and advantages. The input data is divided into train and test data. The FR models have been tuned for all their parameters according to the train data, and the best coefficients are identified. Center of Average Method for defuzzification output process is applied. For determining the rate of error of FR models estimations, the rate of defuzzified output of each model is compared with its actual rate consumption in test data. The efficiency of 15 FR models is examined by the output-oriented Data Envelopment Analysis (DEA) model without inputs by considering three types of relative error: RMSE, MAE and MAPE. The applicability and superiority of the proposed algorithm is shown for monthly oil consumption of Canada, United States, Japan and Australia from 1990 to 2005.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

A novel algorithm for layout optimization of injection process with random demands and sequence dependent setup times

Injection molding is an ideal manufacturing process for producing high volumes of products from both thermoplastic and thermo setting materials. Nevertheless, in some cases, this type of manufacturing process decelerates the production rate as a bottleneck. Thus, layout optimization plays a crucial role in this type of problem in terms of increasing the efficiency of the production line. In this regard, a novel computer simulation–stochastic data envelopment analysis (CS-SDEA) algorithm is proposed in this paper to deal with a single row job-shop layout problem in an injection molding process. First, the system is modeled with discrete-event-simulation as a powerful tool for analyzing complex stochastic systems. Then, due to lack of information about some operational parameters, theory of uncertainty is imported to the simulation model. Finally, an output-oriented stochastic DEA model is used for ranking the outputs of simulation model. The proposed CS-SDEA algorithm is capable of modeling and optimizing non-linear, stochastic, and uncertain injection process problems. The solution quality is illustrated by an actual case study in a refrigerator manufacturing company.     

Surface modification of ultra‐high‐molecular‐weight polyethylene. II. Effect on the physicomechanical and tribological properties of ultra‐high‐molecular‐weight polyethylene/poly(ethylene terephthalate) composites

We performed surface modification of ultra‐high‐molecular‐weight polyethylene (UHMWPE) through chromic acid etching, with the aim of improving the performance of its composites with poly(ethylene terephthalate) (PET) fibers. In this article, we report on the morphology and physicomechanical and tribological properties of modified UHMWPE/PET composites. Composites containing chemically modified UHMWPE had higher impact properties than those based on unmodified UHMWPE because of improved interfacial bonding between the polymer matrix and the fibers and better dispersion of the fibers within the modified UHMWPE matrix. Chemical modification of UHMWPE before the introduction of PET fibers resulted in composites exhibiting improved wear resistance compared to the base material and compared to unmodified UHMWPE/PET composites. On the basis of the morphological studies of worn samples, microploughing and fatigue failure associated with microcracking were identified as the principle wear mechanisms. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns

Identifying the presence of anti-nuclear antibody (ANA) in human epithelial type 2 (HEp-2) cells via the indirect immunofluorescence (IIF) protocol is commonly used to diagnose various connective tissue diseases in clinical pathology tests. As it is a labour and time intensive diagnostic process, several computer aided diagnostic (CAD) systems have been proposed. However, the existing CAD systems suffer from numerous shortcomings due to the selection of features, which is commonly based on expert experience. Such a choice of features may not work well when the CAD systems are retasked to another dataset. To address this, in our previous work, we proposed a novel approach that learns a set of filters from HEp-2 cell images. It is inspired by the receptive fields in the mammalian's vision system, since the receptive fields can be thought as a set of filters for similar shapes. We obtain robust filters for HEp-2 cell classification by employing the independent component analysis (ICA) framework. Although, this approach may be held back due to one particular problem; ICA learning requires a sufficiently large volume of training data which is not always available. In this paper, we demonstrate a biologically inspired solution to address this issue via the use of spontaneous activity patterns (SAP). The spontaneous activity patterns, which are related to the spontaneous neural activities initialised by the chemical release in the brain, are found as the typical stimuli for the visual cell development of newborn animals. In the classification system for HEp-2 cells, we propose to model SAP as a set of small image patches containing randomly positioned Gaussian spots. The SAP image patches are generated and mixed with the training images in order to learn filters via the ICA framework. The obtained filters are adopted to extract the set of responses from a HEp-2 cell image. We then employ regions from this set of responses and stack them into “cubic regions”, and apply a classification based on the correlation information of the features. We show that applying the additional SAP leads to a better classification performance on HEp-2 cell images compared to using only the existing patterns for training ICA filters. The improvement on classification is particularly significant when there are not enough specimen images available in the training set, as SAP adds more variations to the existing data that makes the learned ICA model more robust. We show that the proposed approach consistently outperforms three recently proposed CAD systems on two publicly available datasets: ICPR HEp-2 contest and SNPHEp-2.     

Mechanical properties of composites from sawdust and recycled plastics

Mechanical properties of wood plastic composites (WPCs) manufactured from sawdust and virgin and/or recycled plastics, namely high density polyethylene (HDPE) and polypropylene (PP), were studied. Sawdust was prepared from beech industrial sawdust by screening to the desired particle size and was mixed with different virgin or recycled plastics at 50% by weight fiber loading. The mixed materials were then compression molded into panels. Flexural and tensile properties and impact strength of the manufactured WPCs were determined according to the relevant standard specifications. Although composites containing PP (virgin and recycled) exhibited higher stiffness and strength than those made from HDPE (virgin and recycled), they had lower unnotched impact strengths. Mechanical properties of specimens containing recycled plastics (HDPE and PP) were statistically similar and comparable to those of composites made from virgin plastics. This was considered as a possibility to expand the use of recycled plastics in the manufacture of WPCs. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 3641–3645, 2006     

Maintenance Scheduling Optimization in a Multiple Production Line Considering Human Error

An analytical multiobjective maintenance planning model that maximizes reliability while minimizing cost and human error is proposed. In order to incorporate human error, the model minimizes the maximum human error over the planning horizon. Human Error Assessment and Reduction Technique (HEART) is used to quantify the human error. Maintenance activities include adjustment and replacement activities, in which each of them consumes a certain amount of human resource, spare parts, and budget and brings about a specified level of reliability and human error. Economic dependence is also considered, in which grouping maintenance activities reduces total cost. However, this may increase human error probability due to operator fatigue or time pressure. The main purpose is to investigate the relationship between human factors and maintenance activities to find the preferred maintenance plan. A multiple production line is considered as a case study. A sensitivity analysis is performed, and the effects of grouping and human factors on the preferred maintenance plan are discussed. It is shown how human proficiency may affect reliability and cost.