The effect of reform-based science teaching on SES-associated achievement gap on Pisa 2006 : a comparative study of the United States and Taiwan

The goal of this study is to examine how reform-based science teaching has been implemented and whether reform-based science teaching has promoted education equity through being available and beneficial for students from different socioeconomic status (SES) family backgrounds in the U.S. and Taiwan. No existing study used large-scale assessment to investigate the implementation and outcomes of the science reform movement in the U.S. and Taiwan. This study was developed to fill this gap using the Program of International Student Assessment (PISA) 2006 data including 5,611 students in the United States and 5995 students in Taiwan. A Latent Profile Analysis (LPA) was used to classify students into different science learning subgroups to understand how broadly reform-based science learning has been implemented in classrooms. The results showed that students in the U.S. had more opportunity to learn science through the reform-based learning activities than students in Taiwan. Latent Class Regression (LCR) and Structural Equation Modeling (SEM) were used for examining the availability of reform-based science teaching in both countries. The results showed that in the U.S., higher SES students had more opportunity to learn science reform-based learning activities. On the other hand, students' SES had no association with reform-based science learning in Taiwan. Regression Mixture Modeling and SEM were used to examine whether there was an association between reform-based science teaching and SES-associated achievement gaps. The results found no evidence to support the claim that reform-based science teaching helps to minimize SES-associated achievement gaps in both countries

Rice seed quality as influenced by storage duration and package type in Cameroon

The study aimed at evaluating the changes in rice seed quality as a function of storage duration and package type through characterization of seed quality determinants. Two rice varieties NERICA8 and NERICAL56) were measured into four package types (nylon bag, polyethylene bag, jute bag, and paper bag) and stored in a storage room of average relative humidity and temperature of 80% and 26 °C respectively. Standard methods of evaluating seed quality applicable to paddy were used. The quality parameters showed variability across the package types and storage duration. Remarkable changes were observed in the germination rate and insect damaged grains with slight changes in the number of colored grains, moisture content, and grain weight during the sampling intervals. The quantity of insect damage grains increased while germination rate decreased continuously during the entire experimental period. At three months of storage, the quantity of insect damage grains increased in all the bags for NERICA8 (0.1 g - 3.73 g) and was so for NERICAL56 only in the jute (0.15 g - 3.43 g) and paper (0.1 g - 3.13 g) bags at p<0.05 level of significance. Germination rate had reduced in all the bags below the minimum seed certification standard (MSCS) of 85%, reaching values of 53% and 51% for NERICA8 and NERICAL56 respectively in the polyethylene bag. Insect damage was least in the polyethylene bag (1.73 g) and highest in the jute (3.73 g) and paper (3.43 g) bags. NERICA8 was more pruned to insect damage as high values were observed at one month of storage but observed for NERICAL56 only at two months of storage. In addition, the number of colored grains was higher in the polyethylene and nylon bags compared to the jute and paper bags. From these results, a huge decrease in the quality of rice seeds occurred in the nylon and polyethylene bags. The observed high germination rate associated with insect infestation in the jute and paper bags suggest that if seeds in these bags are treated with insecticides, germination rate could improve to values around the MSCS even after three months of storage.Keywords: Seed quality, NERICA, germination, insect damage

Statistical Properties of Multiple Optical Emission Components in Gamma-Ray Bursts and Implications

Well-sampled optical lightcurves of 146 gamma-ray bursts (GRBs) are complied from the literature. Multiple optical emission components are extracted with power-law function fits to these lightcurves. We present a systematical analysis for statistical properties and their relations to prompt gamma-ray emission and X-ray afterglow for each component. We show that peak luminosity in the prompt and late flares are correlated and the evolution of the peak luminosity may signal the evolution of the accretion rate. No tight correlation between the shallow decay phase/plateau and prompt gamma-ray emission is found. Assuming that they are due to a long-lasting wind injected by a compact object, we show that the injected behavior favors the scenarios of a long-lasting wind after the main burst episode. The peak luminosity of the afterglow onset is tightly correlated with Eiso, and it is dimmer as peaking later. Assuming that the onset bump is due to the fireball deceleration by the external medium, we examine the Gamma_0-Eiso relation and find that it is confirmed with the current sample. Optical re-brightening is observed in 30 GRBs in our sample. It shares the same relation between the width and the peak time as found in the onset bump, but no clear correlation between the peak luminosity and Eiso as observed in the onset bumps is found. Although its peak luminosity also decays with time, the slope is much shallower than that of the onset peak. We get L t^{-1}_{p}$, being consistent with off-axis observations to an expanding external fireball in a wind-like circum medium. The late re-brightening may signal another jet component. Mixing of different emission components may be the reason for the observed chromatic breaks in different energy bands.Comment: 10 pages, 5 figures, to be published by IJMPD (Proceedings of "The Third Galileo - Xu Guangqi meeting", Beijing, October 11-15, 2011

Higher education, high-impact research, and world university rankings: A case of India and comparison with China

AbstractTo date, this paper is probably the first to compare Indian and Chinese universities on educational performance metrics such as high-impact research and world university rankings. The study, therefore, examines the current state of higher education, high-impact research metrics, and world university rankings in an emerging market of India. First, we present an overview of the higher education system, government schemes for academic research, and related educational statistics. Second, we compare India and China on various academic-research metrics (citable documents, number of citations, cites per document, and H-index in three categories), and world university rankings. Special attention is devoted to revealing the progress of management research metrics, business school accreditations and rankings, and abstracting and indexing of publishing journals. Last, we discuss several challenges in university education and recommend policy guidelines pertaining to research funding, collaborative research projects, and research assessment council for imparting quality academic practices and standards in a higher education environment. Our exploratory analysis indicates that for citable documents in the ‘all subjects’ category, the United States is ranked first, followed by China in second, the United Kingdom in third, and India in ninth. Overall, world university rankings and research metrics of Indian universities are found to be far behind those of Chinese universities

The role of the small GTPase Rab31 in cancer

10.1111/jcmm.12403Journal of Cellular and Molecular Medicine1911-1

Neural Network Preference Learning Approaches For Improving Agent-Based Meeting Scheduling Problems

Meeting scheduling is a distributed, tedious and time-consuming task in an organization which involves several individual in different location. The preferences and calendar availability of each individual are vary and treated as private information that unlikely to share with other individuals. Application of software agent is one of the solutions to automate this tedious task. Agent-Based Meeting Scheduling (ABMS) consists of several autonomous Secretary Agent (SA) that perform meeting scheduling task on behalf of their respective user through negotiation among them. Searching strategy is the negotiation technique that performed by SA in searching a suitable meeting timeslot. This study is interested in investigating the efficiency of searching strategy in term of communication cost, optimality of solution found and proposal successful rate during negotiation. Preliminary study of searching strategy use relaxation process to allow agents negotiate by relaxes their preference when conflicts arise. This strategy was extended with “preference estimation” technique to optimize the user preference level of negotiation outcome. However, this will increase the cost of searching process. As the result, an improvement of relaxation searching strategy by adapting artificial neural network (ANN) learning mechanism into SA is proposed in this study. ANN is used in this study because of its popularity in predicting. Unfortunately, ANN has never been used to improve the searching strategy in meeting scheduling. The back-propagation neural network (BPNN) is applied in this research to intelligently predict of participants’ preferences and guide the host in selecting proposals that are more likely to get accepted by participants. Hence, increase the accuracy of negotiation outcome and reduce the communication cost. A computer simulation is conducted to compare the proposed searching strategy with the two existing strategies namely “relaxation”, and “relaxation with preference estimation”. It is carried out by performing scheduling tasks on a set of meeting in difference calendar density. Some measurement such as, the average preference level for committed meeting, optimality of the solution, the communication cost, and rate of successful proposals are defined to evaluate the performance of these three strategies. Finally, the result of the simulation shows the ability of proposed searching strategy to find the timeslot that close to optimal solution and achieves higher average preference level. Besides, proposed searching strategy requires less communication cost to achieve optimal solution. In conclusion, the use of ANN in relaxation searching strategy successfully improves the performance of timeslot searching process in ABMS. In future works, the existing system may be extended to deal with more complex and dynamic scheduling situation such as synchronize scheduling, meeting rescheduling and user preference elicitation technique

S-allylcysteine Improves Blood Flow Recovery and Prevents Ischemic Injury by Augmenting Neovasculogenesis.

Studies suggest that a low level of circulating human endothelial progenitor cells (EPCs) is a risk factor for ischemic injury and coronary artery disease (CAD). Consumption of S-allylcysteine (SAC) is known to prevent CAD. However, the protective effects of SAC on the ischemic injury are not yet clear. In this study, we examined whether SAC could improve blood flow recovery in ischemic tissues through EPC-mediated neovasculogenesis. The results demonstrate that SAC significantly enhances the neovasculogenesis of EPCs in vitro. The molecular mechanisms for SAC enhancement of neovasculogenesis include the activation of Akt/endothelial nitric oxide synthase signaling cascades. SAC increased the expression of c-kit, β-catenin, cyclin D1, and Cyclin-dependent kinase 4 (CDK4) proteins in EPCs. Daily intake of SAC at dosages of 0.2 and 2 mg/kg body weight significantly enhanced c-kit protein levels in vivo. We conclude that dietary consumption of SAC improves blood flow recovery and prevents ischemic injury by inducing neovasculogenesis in experimental models