Differences in therapeutic alliance when working with an interpreter: a preliminary study

This preliminary study aims to analyze the therapeutic alliance in a crosscultural triadic setting, where there is a therapist and a client who speak a different language but are able to interact thanks to an interpreter/cultural mediator. The participants' (therapists, clients, interpreters) representations associated with the notion of therapeutic alliance, and the level of alliance between each group was obtained and compared. Clients (N = 9) were all from Albanese origin. The results show that the three groups of participants give particular meanings to the alliance and tend to evaluate their alliance level differently. The interpreter's mediating role in the construction of the therapeutic alliance is discussed.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Chronic obstructive pulmonary disease in never-smoking animal farmers working inside confinement buildings

BACKGROUND: In animal farming, respiratory disease has been associated with indoor air contaminants and an excess in FEV1 decline. Our aim was to determine the characteristics and risk factors for chronic obstructive pulmonary disease (COPD) in never-smoking European farmers working inside animal confinement buildings. METHODS: A sample of participants in the European Farmers' Study was selected for a cross-sectional study assessing lung function and air contaminants. Dose-response relationships were assessed using logistic regression models. RESULTS: COPD was found in 18 of 105 farmers (45.1 SD 11.7 years) (17.1%); 8 cases (7.6%) with moderate and 3 cases (2.9%) with severe disease. Dust and endotoxin showed a dose-response relationship with COPD, with the highest prevalence of COPD in subjects with high dust (low=7.9%/high=31.6%) and endotoxin exposure (low=10.5%/high=20.0%). This association was statistically significant for dust in the multivariate analysis (OR 6.60, 95% CI 1.10-39.54). CONCLUSION: COPD in never-smoking animal farmers working inside confinement buildings is related to indoor dust exposure and may become severe. [Authors]

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Alleviating Working Poverty in Postindustrial Economies

In order to identify the main social policy tools that can efficiently combat working poverty, it is essential to identify its main driving factors. More importantly, this work shows that all poverty factors identified in the literature have a direct bearing on working households through three mechanisms, namely being badly paid, having a below-average workforce participation, and high needs. One of the main purposes of this work is to assess whether the policies put forward in the specialist literature as potentially efficient really work. This is done in two ways. A first empirical prong provides an evaluation of the employment and antipoverty effects of these instruments, based on a meta-analysis of four instruments: minimum wages, tax credits for working households, family cash benefits and childcare policies. The second prong relies on a broader framework based on welfare regimes. This work contributes to the identification of a typology of welfare regimes that is suitable for the analysis of working poverty, and four countries are chosen to exemplify each regime: the US, Sweden, Germany, and Spain. It then moves on to show that the weight of the three working poverty mechanisms varies widely from one welfare regime to the other. This second empirical contribution clearly shows that there is no "one-size-fits-all" approach to the fight against working poverty. But none of this is possible without having properly defined the phenomenon. Most of the literature is characterized by a "definitional chaos" that probably does more harm than good to social policy efforts. Hence, this book provides a conceptual reflection pleading for the use of a very encompassing definition of being in work. It shows that "the working poor" is too broad a category to be used for meaningful academic or policy discussion, and that a distinction must be operated between different categories of the working poor. Failing to acknowledge this prevents the design of an efficient policy mix.

Fusion of protoplasts with irradiated microprotoplasts as a tool for radiation hybrid panel in citrus

The objective of this work was to combine asymmetric somatic hybridization (donor-recipient fusion or gamma fusion) to microprotoplast-mediated chromosome transfer, as a tool to be used for chromosome mapping in Citrus. Swinglea glutinosa microprotoplasts were irradiated either with 50, 70, 100 or 200 gamma rays and fused to cv. Ruby Red grapefruit or Murcott tangor protoplasts. Cell colonies were successfully formed and AFLP analyses confirmed presence of S. glutinosa in both 'Murcott' tangor and 'Ruby Red' grapefruit genomes.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Genomic behavior of hybrid combinations between elephant grass and pearl millet

The objective of this work was to evaluate the genomic behavior of hybrid combinations between elephant grass (Pennisetum purpureum) and pearl millet (P. glaucum). Tetraploid (AAA'B) and pentaploid (AA'A'BB) chromosome races resulting from the backcross of the hexaploid hybrid to its parents elephant grass (A'A'BB) and pearl millet (AA) were analyzed as to chromosome number and DNA content. Genotypes of elephant grass, millet, and triploid and hexaploid induced hybrids were compared. Pentaploid and tetraploid genomic combinations showed high level of mixoploidy, in discordance with the expected somatic chromosome set. The pentaploid chromosome number ranged from 20 to 34, and the tetraploid chromosome number from 16 to 28. Chromosome number variation was higher in pentaploid genomic combinations than in tetraploid, and mixoploidy was observed among hexaploids. Genomic combinations 4x and 5x are mixoploid, and the variation of chromosome number within chromosomal race 5x is greater than in 4x.

Detection and mapping of a lethal locus in a eucalyptus hybrid population

The objective of this work was to verify the existence of a lethal locus in a eucalyptus hybrid population, and to quantify the segregation distortion in the linkage group 3 of the Eucalyptus genome. A E. grandis x E. urophylla hybrid population, which segregates for rust resistance, was genotyped with 19 microsatellite markers belonging to linkage group 3 of the Eucalyptus genome. To quantify the segregation distortion, maximum likelihood (ML) models, specific to outbreeding populations, were used. These models consider the observed marker genotypes and the lethal locus viability as parameters. The ML solutions were obtained using the expectation‑maximization algorithm. A lethal locus in the linkage group 3 was verified and mapped, with high confidence, between the microssatellites EMBRA 189 e EMBRA 122. This lethal locus causes an intense gametic selection from the male side. Its map position is 25 cM from the locus which controls the rust resistance in this population.

Learning in the working place: the educational potential of a multihead microscope in pathology postgraduate training.

Training future pathologists is an important mission of many hospital anatomic pathology departments. Apprenticeship-a process in which learning and teaching tightly intertwine with daily work, is one of the main educational methods in use in postgraduate medical training. However, patient care, including pathological diagnosis, often comes first, diagnostic priorities prevailing over educational ones. Recognition of the unique educational opportunities is a prerequisite for enhancing the postgraduate learning experience. The aim of this paper is to draw attention of senior pathologists with a role as supervisor in postgraduate training on the potential educational value of a multihead microscope, a common setting in pathology departments. After reporting on an informal observation of senior and junior pathologists' meetings around the multihead microscope in our department, we review the literature on current theories of learning to provide support to the high potential educational value of these meetings for postgraduate training in pathology. We also draw from the literature on learner-centered teaching some recommendations to better support learning in this particular context. Finally, we propose clues for further studies and effective instruction during meetings around a multihead microscope.

Interventions hybrides et malformations cardiaques congénitales [Hybrid procedures in congenital heart disease]

La complexité croissante de la prise en charge des malformations cardiaques congénitales impose des interventions chirurgicales et des cathétérismes cardiaques interventionnels fréquents. Chacune de ces techniques a ces limitations propres. Les interventions hybrides associent les avantages de la chirurgie cardiaque et du cathétérisme interventionnel. Dans notre expérience, les thérapies hybrides permettent de diminuer le temps de circulation extracorporelle, de diminuer la morbidité des interventions chirurgicales, de raccourcir le séjour du patient aux soins intensifs. Pour certaines malformations cardiaques congénitales complexes pour lesquelles il n'existe pas de chirurgie ou de thérapie interventionnelle idéale, les interventions hybrides sont en train de s'imposer comme la prise en charge incontournable. Increasing complexity in management of congenital heart disease imposes more frequent surgeries and interventions. Each technique has its own limitations, which could impair the anticipated result. Hybrid procedures join the advantages of cardiac surgery and interventions, creating a synergy in the management of these patients with cardiac anomalies. In our experience, hybrid procedures shorten cardiopulmonary bypass, reduce morbidity of surgery and reduce duration of stay in the intensive care unit. For some complex congenital heart diseases for which there are no ideal surgical or interventional options, hybrid procedures are becoming increasingly important in their management. Finally hybrid procedures allow surgeons and cardiologist to achieve complex procedures that could not be possible in another way