Reciprocal Associations Between Adolescent Sexual Activity and Quality of Youth-Parent Interactions.

The authors examined differences in adolescents' relationships with their parents before and after adolescent first sexual activity. Participants were 13,570 members of the core sample of the National Longitudinal Survey of Adolescent Health (Add Health) Waves 1 and 2. Path analyses examined changes in parent-adolescent closeness, shared activities, and problem-focused interactions associated with changes in sexual activity separately for sons and daughters and for mothers and fathers. Race, religion, age, urbanicity, and parents' education were controls. Results confirm that increased problem-focused interactions and decreased parental closeness and shared activities both precede and follow adolescent sexual activity. Maintaining positive parental relations after adolescent first sexual activity is discussed as a means to reduce risks associated with sex. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Testing a Self-Determination Theory Process Model for Promoting Glycemic Control Through Diabetes Self-Management.

A longitudinal study tested the self-determination theory (SDT) process model of health behavior change for glycemic control within a randomized trial of patient activation versus passive education. Glycosylated hemoglobin for patients with Type 2 diabetes (n=159) was assessed at baseline, 6 months, and 12 months. Autonomous motivation and perceived competence were assessed at baseline and 6 months, and the autonomy supportiveness of clinical practitioners was assessed at 3 months. Perceptions of autonomy and competence were promoted by perceived autonomy support, and changes in perceptions of autonomy and competence, in turn, predicted change in glycemic control. Self-management behaviors mediated the relation between change in perceived competence and change in glycemic control. The self-determination process model fit the data well. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

NJTxtr—A Computer Program Based on LASER to Monitor Asphalt Segregation

Abstract: This paper describes the research funded by the New Jersey Department of Transportation to develop an automated technology to monitor segregation during construction of hot-mix asphalt concrete pavements. A Laser-based system was used to measure surface texture and to detect segregation. Two segregated test sections and a control test section were tested to evaluate the applicability of Laser texture method to detect and quantify segregation. Laser texture data were gathered from all three sections. Ratios of texture in segregated areas to that in nonsegregated areas were set as the basis for detection of different levels of segregation. By combining the level of segregation and extent of segregation, an AREA index was developed to determine the acceptability of a pavement section. Based on AREA index, pay adjustment factors were proposed to reduce the payment to account for loss of pavement life due to segregation. Further remedial actions were proposed to correct segregated pavement sections with acceptable AREA index. Based on the above concepts, Windows-based computer program NJTxtr was developed to detect and quantify segregation. This computer program uses the Laser-equipment-collected pavement texture data and determines whether the pavement section is acceptable or unacceptable based on the level of segregation within a pavement section, and provides bonus or penalties to the contractor. The paper describes a novel technology using laser and associated software for construction quality control of asphalt concrete pavements. The proposed methodology was applied to detect segregation in an interstate highway section in New Jersey, and this section was repaved based on visual observation and recommendation from this study.     

A dynamic analysis of chalcopyrite bioleaching in continuous flow reactor systems

A dynamic analysis of chalcopyrite bioleaching was performed in continuous flow systems. In contrast to a previous batch analysis¹ in which the influence of particle surface area on reaction rate was not accounted for, the unsteady‐state change in particle surface area was integrated into the dynamic analysis by application of the modified PBM.² The current study extends the analysis to include the influence of convective flow on the system. It is demonstrated that the analysis can be used to determine feasible control strategies for operating near the steady‐state maximum rate that is stable. Two strategies were evaluated for the purpose of increasing the leaching rates, showing that an increased rate of 56% is feasible. Analysis on experimental data showed that increased rates can be achieved by controlling the biomass concentration and ferric:ferrous ion ratio at an optimum by increasing the solids loading [m/v] in the reactor. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2428–2440, 2012     

Mechanical properties of continuous bamboo fiber-reinforced biobased polyamide 11 composites

This study is devoted to the analysis of the properties of continuous bamboo fiber (BF)-reinforced polyamide 11 (PA 11) composites. The SEM observations highlighted continuity between BFs and the polymeric matrix showing a high density of hydrogen bonds. The comparative calorimetric study of the matrix and its composites showed that the crystallinity of PA 11 was not modified by the presence of bamboo fibers. The physical aging observed in PA 11 is no more observed in composites due to physical interactions between PA 11 and BFs. The mechanical properties were investigated by tensile strength and dynamic mechanical analysis. The introduction of BFs enhanced Young's modulus of the matrix by a factor of 10. The presence of BFs also improved the storage shear modulus G′ over the whole temperature range. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47623.     

Preface

<正>Every three years the world's leaders in solvent extraction get together at the International Solvent Extraction Conference and in2014 it was held in Wurzburg in Germany.The following are 9 papers that were picked out that show an overview of the work presented and provide an update on some of the research being undertaken in solvent extraction today.For me the trend to environmentally sustainable bio derived solvents is a key for     

Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification

Averaged n-Dependence Estimators (AnDE) is an approach to probabilistic classification learning that learns by extrapolation from marginal to full-multivariate probability distributions. It utilizes a single parameter that transforms the approach between a low-variance high-bias learner (Naive Bayes) and a high-variance low-bias learner with Bayes optimal asymptotic error. It extends the underlying strategy of Averaged One-Dependence Estimators (AODE), which relaxes the Naive Bayes independence assumption while retaining many of Naive Bayes’ desirable computational and theoretical properties. AnDE further relaxes the independence assumption by generalizing AODE to higher-levels of dependence. Extensive experimental evaluation shows that the bias-variance trade-off for Averaged 2-Dependence Estimators results in strong predictive accuracy over a wide range of data sets. It has training time linear with respect to the number of examples, learns in a single pass through the training data, supports incremental learning, handles directly missing values, and is robust in the face of noise. Beyond the practical utility of its lower-dimensional variants, AnDE is of interest in that it demonstrates that it is possible to create low-bias high-variance generative learners and suggests strategies for developing even more powerful classifiers.