Effect of cooling rate during solidification on the hard phases of M23C6-type of cast CoCrMo alloy

Microstructural morphology of CoCrMo alloy by control of the cooling rate during the solidification was investigated. Samples were obtained using both an induction furnace for slow cooling rate and electric arc furnace for fast cooling rate. Microstructural characterizations were performed with metallographic techniques. It was found that the difference between the formation temperature of hard secondary phases of M23C6-type carbides determine the reduction of carbide size by increasing the cooling rate

Analysis of self--averaging properties in the transport of particles through random media

We investigate self-averaging properties in the transport of particles through random media. We show rigorously that in the subdiffusive anomalous regime transport coefficients are not self--averaging quantities. These quantities are exactly calculated in the case of directed random walks. In the case of general symmetric random walks a perturbative analysis around the Effective Medium Approximation (EMA) is performed.Comment: 4 pages, RevTeX , No figures, submitted to Physical Review E (Rapid Communication

Learning to classify software defects from crowds: a novel approach

In software engineering, associating each reported defect with a cate- gory allows, among many other things, for the appropriate allocation of resources. Although this classification task can be automated using stan- dard machine learning techniques, the categorization of defects for model training requires expert knowledge, which is not always available. To cir- cumvent this dependency, we propose to apply the learning from crowds paradigm, where training categories are obtained from multiple non-expert annotators (and so may be incomplete, noisy or erroneous) and, dealing with this subjective class information, classifiers are efficiently learnt. To illustrate our proposal, we present two real applications of the IBM’s or- thogonal defect classification working on the issue tracking systems from two different real domains. Bayesian network classifiers learnt using two state-of-the-art methodologies from data labeled by a crowd of annotators are used to predict the category (impact) of reported software defects. The considered methodologies show enhanced performance regarding the straightforward solution (majority voting) according to different metrics. This shows the possibilities of using non-expert knowledge aggregation techniques when expert knowledge is unavailable

Protocolo unificado de grupo para el tratamiento de la ansiedad y la depresión en la infancia

Childhood anxiety and mood disorders are common and are associated with high levels ofimpairment. These disorders share a common etiology and risk factors, and are often experiencedconcurrently. While evidence-based interventions for youth anxiety and depressive disorders do exist,children experiencing this common comorbidity tend to experience weaker treatment outcomes inanxiety or depression focused treatments as compared to youth suffering from either disorder alone.Researchers are now investigating transdiagnostic interventions, which have potential to target commonvulnerability factors and address a wider range of concerns. The Unified Protocol for the Treatmentof Emotional Disorders in Children: Emotion Detectives (UP-C: ED) is a transdiagnostictreatment that implements a set of core principles to address common factors underlying youth anxietyand depressive disorders in a group setting. Theoretical underpinnings of the UP-C: ED are discussedalong with an in-depth presentation of treatment content. A case study is also presented detailinginitial intake, treatment conceptualization, treatment, and treatment outcomes using this modality.Los trastornos de ansiedad y del estado de ánimo son comunes y están asociados a niveleselevados de perturbación. Estos trastornos comparten etiología y factores de riesgo comunes,y frecuentemente son experimentados al mismo tiempo. Aunque existen intervenciones basadas enla evidencia para el tratamiento de los trastornos de ansiedad y del estado de ánimo en jóvenes, losniños que experimentan esta comorbilidad obtienen peores resultados terapéuticos, a través de lostratamientos focalizados en la ansiedad o en la depresión, que los niños que sólo sufren de uno deestos trastornos. Recientemente se han investigado los tratamientos transdiagnósticos, los cualestienen la capacidad de centrarse en los factores de vulnerabilidad comunes y abordar un conjuntoamplio de problemas. El Unified Protocol for Children: Emotion Detectives (UP-C: ED) es untratamiento transdiagnóstico de grupo, que implementa un conjunto de principios básicos, pensadopara abordar los factores comunes que subyacen a los trastornos de ansiedad y depresión infantojuveniles.Se discute la estructura teórica del UP-C: ED junto con una presentación exhaustiva delcontenido del tratamiento. También se presenta un estudio de caso detallando la evaluación inicial,la conceptualización del tratamiento, el tratamiento y los resultados obtenidos

Fast k-NN classifier for documents based on a graph structure

In this paper, a fast k nearest neighbors (k-NN) classifier for documents is presented. Documents are usually represented in a high-dimensional feature space, where terms appeared on it are treated as features and the weight of each term reflects its importance in the document. There are many approaches to find the vicinity of an object, but their performance drastically decreases as the number of dimensions grows. This problem prevents its application for documents. The proposed method is based on a graph index structure with a fast search algorithm. It’s high selectivity permits to obtain a similar classification quality than exhaustive classifier, with a few number of computed distances. Our experimental results show that it is feasible the use of the proposed method in problems of very high dimensionality, such as Text Mining

Laboratory Analysis of the System for Catchment, Pre-treatment and Treatment (SCPT) of Runoff from Impervious Pavements

This article reports the development and construction of a 1:1 scale laboratory prototype of a System for Catchment, Pre-treatment and Treatment (SCPT) of runoff polluted by contaminants washed from impervious pavements. The concept of the SCPT is an online system with an up-flow filter. The filter is composed geotextile layers and limestone. Laboratory tests carried out were focused on determining the SCPT prototype behaviour under different working conditions. The variables studied were: inflow, pollutant loads and filtration system configuration. The results show that the designed system has a high capacity for total solids and oil treatment, with an average efficiency of 85% and 97% respectively. Moreover, the regression equations of the treatment efficiency have been determined for each of the studied pollutants, for different inflow conditions and pollution loads

Long-term analysis of clogging and oil bio-degradation in a System of Catchment, Pre-treatment and Treatment (SCPT)

Runoff contamination has motivated the development of different systems for its treatment in order to decrease the pollutant load that is discharged into natural water bodies. In the long term, these systems may undergo operational problems. This paper presents the results obtained in a laboratory study with a 1:1 scale prototype of a System of Catchment, Pre-treatment and Treatment (SCPT) of runoff waters. The analysis aims to establish the operational behaviour of the SCPT in the long term with respect to oil degradation and hydraulic conductivity in the geotextile filter. It is concluded that bio-degradation processes take place inside the SCPT and that hydraulic conductivity of the geotextile filtration system decreases slowly with successive simulated runoff events