Mediation Effect of Resilience on The Relationship Between Self-Efficacy and Competitiveness Among University Students

This study aims to evaluate the mediation role of resilience on the link between self-efficacy and competitiveness among university students in Malaysia. One hundred and thirty-six participants from several universities in Malaysia were recruited to respond to an online form consisted of the following scales: adapted versions of brief resilience scale from Smith et al, self-efficacy scale from Biemann, Kearney and Marggraf, and Personal Development Competitive Attitude Scale  from Ryckman, Hammer, Kaczor and Gold. Data was analyzed by using SPSS with PROCESS Macro and full mediation has been observed. Bias-corrected bootstrap confidence interval test indicated that the indirect effect of self-efficacy on competitiveness was significant and the Sobel test had confirmed the significance of the mediation. Further discussion, limitation and suggestion are discussed in the end of the paper

The use of rapid prototyping in the design of a customised ankle brace structure for ACL injury risk reduction.

Rapid prototyping, or additive manufacturing, is becoming more useful in creating functional prototypes, especially when customisation is required. This paper explores the use of three-dimensional (3D) printing in designing a customised ankle brace structure for anterior cruciate ligament (ACL) injury risk reduction. A new process is proposed to obtain ankle flexion angles and the corresponding foot surface strain associated with high ACL injury risks through motion analysis. This data is used in the design of the customised ankle brace structure and printed using rapid prototyping. One customised ankle brace structure was printed and tested to demonstrate this proposed framework. The ankle flexion range of motion (ROM) was significantly reduced in the high-risk ankle positions with the ankle brace structure. Rapid prototyping could thus be used to design customised ankle brace structures and this is useful in reducing fabrication time and complexity of customisation. © 2013 Taylor & Francis

Genomic insights into rapid speciation within the world’s largest tree genus Syzygium

Species radiations, despite immense phenotypic variation, can be difficult to resolve phylogenetically when genetic change poorly matches the rapidity of diversification. Genomic potential furnished by palaeopolyploidy, and relative roles for adaptation, random drift and hybridisation in the apportionment of genetic variation, remain poorly understood factors. Here, we study these aspects in a model radiation, Syzygium, the most species-rich tree genus worldwide. Genomes of 182 distinct species and 58 unidentified taxa are compared against a chromosome-level reference genome of the sea apple, Syzygium grande. We show that while Syzygium shares an ancient genome doubling event with other Myrtales, little evidence exists for recent polyploidy events. Phylogenomics confirms that Syzygium originated in Australia-New Guinea and diversified in multiple migrations, eastward to the Pacific and westward to India and Africa, in bursts of speciation visible as poorly resolved branches on phylogenies. Furthermore, some sublineages demonstrate genomic clines that recapitulate cladogenetic events, suggesting that stepwise geographic speciation, a neutral process, has been important in Syzygium diversification

A Merge-Decoupling Dead End Elimination algorithm for protein side-chain conformation

10.1504/IJDMB.2007.012966International Journal of Data Mining and Bioinformatics14372-38

De novo peptide sequencing for mass spectra based on multi-charge strong tags

Series on Advances in Bioinformatics and Computational Biology5287-29

A database search algorithm for identification of peptides with multiple charges using tandem mass spectrometry

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)3916 LNBI2-1

Nonlinear Dynamical System Modeling Via Recurrent Neural Networks and A Weighted State Space Search Algorithm

Given a task of tracking a trajectory, a recurrent neural network may be considered as a black-box nonlinear regression model for tracking unknown dynamic systems. An error function is used to measure the difference between the system outputs and the desired trajectory that formulates a nonlinear least square problem with dynamical constraints. With the dynamical constraints, classical gradient type methods are difficult and time consuming due to the involving of the computation of the partial derivatives along the trajectory. We develop an alternative learning algorithm, namely the weighted state space search algorithm, which searches the neighborhood of the target trajectory in the state space instead of the parameter space. Since there is no computation of partial derivatives involved, our algorithm is simple and fast. We demonstrate our approach by modeling the short-term foreign exchange rates. The empirical results show that the weighted state space search method is very promising and effective in solving least square problems with dynamical constraints. Numerical costs between the gradient method and our the proposed method are provided

Nonlinear Dynamical System Modeling Via Recurrent Neural Networks and A Weighted State Space Search Algorithm

Given a task of tracking a trajectory, a recurrent neural network may be considered as a black-box nonlinear regression model for tracking unknown dynamic systems. An error function is used to measure the difference between the system outputs and the desired trajectory that formulates a nonlinear least square problem with dynamical constraints. With the dynamical constraints, classical gradient type methods are difficult and time consuming due to the involving of the computation of the partial derivatives along the trajectory. We develop an alternative learning algorithm, namely the weighted state space search algorithm, which searches the neighborhood of the target trajectory in the state space instead of the parameter space. Since there is no computation of partial derivatives involved, our algorithm is simple and fast. We demonstrate our approach by modeling the short-term foreign exchange rates. The empirical results show that the weighted state space search method is very promising and effective in solving least square problems with dynamical constraints. Numerical costs between the gradient method and our the proposed method are provided