Sensitivity of Viscosity on Molten Ti Infusion into a B4C-Packed Bed at the Microscale

Metallurgical and Materials Transactions B - The effect of the surface tension–viscosity dissipation driving liquid Ti flow into a B4C packed bed was analyzed at 1941 K and 2573 K. The model...     

Social class, education, and smoking cessation: Long-term follow-up of patients treated at a smoking cessation unit.

Our objective was to examine social class and educational differences in long-term smoking cessation success among a cohort of smokers attending a specialized smoking clinic. We studied sustained abstinence after cessation among 1,516 smokers (895 men and 621 women) treated for smoking cessation between 1995 and 2001 at a university teaching hospital in the metropolitan area of Barcelona, Spain. We calculated 1-year and long-term (up to 8-year) abstinence probabilities by means of Kaplan-Meier curves and the hazard ratio of relapse by means of Cox regression, after adjusting for other predictors of relapse. Overall abstinence probability was .277 (95% CI = .254-.301). Men and women in social classes IV-V had significant hazard ratios of relapse after long-term follow-up (men: 1.36, 95% CI = 1.07-1.72; women: 1.60, 95% CI = 1.24-2.06), as compared with patients in social classes I-II. The same independent effect was observed for education: Men and women with primary or less than primary studies had higher hazard ratios of relapse (men: 1.75, 95% CI = 1.35-2.25; women: 1.92, 95% CI = 1.51-2.46), as compared with patients with a university degree. Similar estimates were obtained after adjustment for stage of change, Fagerstr?m score for nicotine dependence, and type of treatment. Patients of lower socioeconomic status are at higher risk of relapse, and this association is independent of other well-known predictors of relapse. Social differences have to be taken into account in the clinical setting when tailoring specific actions to treat smoking dependence.     

The ocular albinism type 1 gene product is a membrane glycoprotein localized to melanosomes

Ocular albinism type 1 (OA1) is an inherited disorder characterized by severe reduction of visual acuity, photophobia, and retinal hypopigmentation. Ultrastructural examination of skin melanocytes and of the retinal pigment epithelium reveals the presence of macromelanosomes, suggesting a defect in melanosome biogenesis. The gene responsible for OA1 is exclusively expressed in pigment cells and encodes a predicted protein of 404 aa displaying several putative transmembrane domains and sharing no similarities with previously identified molecules. Using polyclonal antibodies we have identified the endogenous OA1 protein in retinal pigment epithelial cells, in normal human melanocytes and in various melanoma cell lines. Two forms of the OA1 protein were identified by Western analysis, a 60-kDa glycoprotein and a doublet of 48 and 45 kDa probably corresponding to unglycosylated precursor polypeptides. Upon subcellular fractionation and phase separation with the nonionic detergent Triton X-114, the OA1 protein segregated into the melanosome-rich fraction and behaved as an authentic integral membrane protein. Immunofluorescence and immunogold analyses on normal human melanocytes confirmed the melanosomal membrane localization of the endogenous OA1 protein, consistent with its possible involvement in melanosome biogenesis. The identification of a novel melanosomal membrane protein involved in a human disease will provide insights into the mechanisms that control the cell-specific pathways of subcellular morphogenesis.     

Some methods for the numerical solution of variational inequalities with two obstacles

In this paper the problem \(\mathop {\min }\limits_{u \in K} \int\limits_\Omega {\left| {u_x } \right|^z dx} \) is studied. HereK≡{u∈W ₀ ¹ (Ω):ψ _i≤u≤ψ ₂}, whereψ ₁ andψ ₂ are given functions. The finite-dimensional discretization has been carried out both by the classical finite-difference method and by a «dnal» method whose corresponding finite-dimensional problem is solved by some new method in quadratic programming.     

Numerical solution of a turning point problem in elasticity

Summary The axially symmetric equilibria of a stress-free thin elastic spherical cap are studied in dependence of a “thickness” parameter. The attention is focused on the turning points of the corresponding bifurcation diagram. The numerical method is based on an approximation of the osculating parabola in the turning point. The rate of convergence is related to the Fibonacci numbers.     

An enhanced Bayesian model to detect students' learning styles in Web-based courses

Abstract   Students acquire and process information in different ways depending on their learning styles. To be effective, Web-based courses should guarantee that all the students learn despite their different learning styles. To achieve this goal, we have to detect how students learn: reflecting or acting; steadily or in fits and starts; intuitively or sensitively. In a previous work, we have presented an approach that uses Bayesian networks to detect a student's learning style in Web-based courses. In this work, we present an enhanced Bayesian model designed after the analysis of the results obtained when evaluating the approach in the context of an Artificial Intelligence course. We evaluated the precision of our Bayesian approach to infer students' learning styles from the observation of their actions with a Web-based education system during three semesters. We show how the results from one semester enabled us to adjust our initial model and helped teachers improve the content of the course for the following semester, enhancing in this way students' learning process. We obtained higher precision values when inferring the learning styles with the enhanced model.     

eTeacher: Providing personalized assistance to e-learning students

In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student’s behavior while he/she is taking online courses and automatically builds the student’s profile. This profile comprises the student’s learning style and information about the student’s performance, such as exercises done, topics studied, exam results. In our approach, a student’s learning style is automatically detected from the student’s actions in an e-learning system using Bayesian networks. Then, eTeacher uses the information contained in the student profile to proactively assist the student by suggesting him/her personalized courses of action that will help him/her during the learning process. eTeacher has been evaluated when assisting System Engineering students and the results obtained thus far are promising.     

Entertainment recommender systems for group of users

Recommender systems are used to recommend potentially interesting items to users in different domains. Nowadays, there is a wide range of domains in which there is a need to offer recommendations to group of users instead of individual users. As a consequence, there is also a need to address the preferences of individual members of a group of users so as to provide suggestions for groups as a whole. Group recommender systems present a whole set of new challenges within the field of recommender systems. In this article, we present two expert recommender systems that suggest entertainment to groups of users. These systems, jMusicGroupRecommender and jMoviesGroupRecommender, suggest music and movies and utilize different methods for the generation of group recommendations: merging recommendations made for individuals, aggregation of individuals’ ratings, and construction of group preference models. We also describe the results obtained when comparing different group recommendation techniques in both domains.