Genetic Diversity of Boleophthalmus Boddarti and Other Malaysian Gobies

Mudskippers (Family Gobiidae: Subfamily Oxudercinae) are residents of tidal mudflat shores, tidal muddy zone of estuaries, rivers, and mangrove swamps. The aims of this study were to describe the morphological and genetic variations among populations of Boleophthalmus boddarti, phylogenetic of Malaysian Oxudercine gobies, and the exposure of PAHs on Boleophthalmus boddarti. The samples of B. boddarti were collected from six locations, namely Pulau Pinang, Selangor (Kuala Selangor), Negeri Sembilan (Pasir Panjang), Melaka, Johor and Pahang (Cherating). Conventional and Truss morphometrics analyses were carried out on 300 individuals belonging to 7 species, namely B. boddarti, Periophthalmus chrysospilos, Periophthalmus grasilos, Periophthalmus novemoradiatus, Periophthalmodon schlosseri, Pseudapocryptes elangatus and Scartlaos histophoris. Using the Discriminate Function Analysis (DFA), the conventional morphometric discriminate the populations of B. boddarti into 2 groups while Truss morphometrics into 3 groups, whereby geographically closer populations were grouped together. Of the 29 Randomly Amplified Polymorphic DNA (RAPD) primers tested, only 12 primers gave clear bands and showed polymorphisms. Eleven bands were identified as RAPD markers in the six populations (N=155) of B. boddarti. The dendrogram from RAPD data revealed three major groups of B. boddarti, in which the first group consisted of the central population (Selangor, Negeri Sembilan and Melaka populations), the second group made up the southern (Johor) and eastern (Pahang) populations, and the third group was the northern populations (P. Pinang), which was distinctly separated from the rest of the population, with a genetic distance of 0.698. The mitochondrial cytochrome b (cytb) sequences in 6 populations of B. boddarti revealed a total of 26 haplotypes. Based on haplotype analyses, the populations were grouped into two clades, I and II. Clade I was divided into two subclades consisting of the northern (P. Pinang) and the central (Selangor) populations as subclade IA, and the central population (N. Sembilan and Melaka) as subclade IB. Clade II consisted of the southern (Johor) and the eastern (Pahang) populations of B. boddarti. Both cytb (345bp) and 16S rDNA (550bp) gene sequences were carried out for phylogenetic studies on 11 species of the subfamily Oxudercinae. Four phylogenetic trees were constructed using maximum parsimony (MP) and neighbor-joining (NJ) methods, using Kimura-2-Parameter (K2P) and Jukes and Cantor models. Based on parsimony analysis, Oxudercinae subfamily was divided into two main clades consisting of Oxuderces in one clade and the rest were in another clade. The distributions of polycyclic aromatic hydrocarbons (PAHs) in both sediments and porewaters (N=8) in the Klang River and its estuaries were higher than those in the Kuala Muda River. Hepatic EROD activities were carried out on B. boddarti (N=62) collected from the Klang River and its estuaries as polluted and Kuala Muda River as less polluted rivers. Hepatic EROD activities showed significantly (p<0.05) higher induction of EROD in fish from the Klang River and its estuaries (mean=24.55 pmol min-1 mg protein-1) than those in the Kuala Muda River (mean=6.84 pmol min-1 mg protein-1). There were close relationships between the log EROD activities in B. boddarti and the total PAHs concentration in sediments (r2= 0.68) and porewaters (r2= 0.66), implying that this fish can be used as an early signal of PAHs exposure in estuarine areas. In conclusions, morphological and molecular markers using both RAPD mtDNA were able to discriminate the populations of B. boddarti in Peninsular Malaysia. MtDNA sequences (cytb and 16S rDNA) were found to be useful tools for phylogenetic studies of the subfamily Oxudercinae. For future endeavour, the use of the other molecular markers is recommended to study the population structure of mudskippers in Malaysia

Development of calcium phosphate bioceramics with different architectures: Achievements by gelcasting and robocasting technologies

L'abstract è presente nell'allegato / the abstract is in the attachmen

Contextual Bag-Of-Visual-Words and ECOC-Rank for Retrieval and Multi-class Object Recognition

Projecte Final de Màster UPC realitzat en col.laboració amb Dept. Matemàtica Aplicada i Anàlisi, Universitat de BarcelonaMulti-class object categorization is an important line of research in Computer Vision and Pattern Recognition fields. An artificial intelligent system is able to interact with its environment if it is able to distinguish among a set of cases, instances, situations, objects, etc. The World is inherently multi-class, and thus, the eficiency of a system can be determined by its accuracy discriminating among a set of cases. A recently applied procedure in the literature is the Bag-Of-Visual-Words (BOVW). This methodology is based on the natural language processing theory, where a set of sentences are defined based on word frequencies. Analogy, in the pattern recognition domain, an object is described based on the frequency of its parts appearance. However, a general drawback of this method is that the dictionary construction does not take into account geometrical information about object parts. In order to include parts relations in the BOVW model, we propose the Contextual BOVW (C-BOVW), where the dictionary construction is guided by a geometricaly-based merging procedure. As a result, objects are described as sentences where geometrical information is implicitly considered. In order to extend the proposed system to the multi-class case, we used the Error-Correcting Output Codes framework (ECOC). State-of-the-art multi-class techniques are frequently defined as an ensemble of binary classifiers. In this sense, the ECOC framework, based on error-correcting principles, showed to be a powerful tool, being able to classify a huge number of classes at the same time that corrects classification errors produced by the individual learners. In our case, the C-BOVW sentences are learnt by means of an ECOC configuration, obtaining high discriminative power. Moreover, we used the ECOC outputs obtained by the new methodology to rank classes. In some situations, more than one label is required to work with multiple hypothesis and find similar cases, such as in the well-known retrieval problems. In this sense, we also included contextual and semantic information to modify the ECOC outputs and defined an ECOC-rank methodology. Altering the ECOC output values by means of the adjacency of classes based on features and classes relations based on ontologies, we also reporteda significant improvement in class-retrieval problems

Nonlinear Vibration Analysis of Axially Functionally Graded Microbeams Based on Nonlinear Elastic Foundation Using Modified Couple Stress Theory

In this study, a non-classical approach was developed to analyze nonlinear free and forced vibration of an Axially Functionally Graded (AFG) microbeam by means of modified couple stress theory. The beam is considered as Euler-Bernoulli type supported on a three-layered elastic foundation with Von-Karman geometric nonlinearity. Small size effects included in the analysis by considering the length scale parameter. It is assumed that the mass density and elasticity modulus varies continuously in the axial direction according to the power law form. Hamilton's principle was implemented to derive the nonlinear governing partial differential equation concerning associated boundary conditions. The nonlinear partial differential equation was reduced to some nonlinear ordinary differential equations via Galerkin's discretization technique. He's Variational iteration methods were implemented to obtain approximate analytical expressions for the frequency response as well as the forced vibration response of the microbeam with doubly-clamped end conditions. In this study, some factors influencing the forced vibration response were investigated. Specifically, the influence of the length scale parameter, the length of the microbeam, the power index, the Winkler parameter, the Pasternak parameter, and the&nbsp;nonlinear parameter on the nonlinear natural frequency as well as the amplitude of forced response have been investigated

Management of electronic learning (e-learning) and knowledge: A tool to promote higher education

Knowledge as a mental capital is the only strategic resource, and compared to the traditional capital, it is highly mobile and versatile. The purpose of this paper was to introduce management of e-learning and knowledge and study their role in the development of higher education. The results indicate that the development of e-learning and virtual discussion environment produces significant opportunities for transferring and sharing of tacit and explicit knowledge, knowledge organization, and organizing information, and it is also a great base to create beneficial and destructive challenges for higher education

Management of electronic learning (e-learning) and knowledge: A tool to promote higher education

Knowledge as a mental capital is the only strategic resource, and compared to the traditional capital, it is highly mobile and versatile. The purpose of this paper was to introduce management of e-learning and knowledge and study their role in the development of higher education. The results indicate that the development of e-learning and virtual discussion environment produces significant opportunities for transferring and sharing of tacit and explicit knowledge, knowledge organization, and organizing information, and it is also a great base to create beneficial and destructive challenges for higher education

A Divide and Conquer Approximation Algorithm for Partitioning Rectangles

Given a rectangle $R$ with area $A$ and a set of areas $L=\{A_1,...,A_n\}$ with $\sum_{i=1}^n A_i = A$, we consider the problem of partitioning $R$ into $n$ sub-regions $R_1,...,R_n$ with areas $A_1,...,A_n$ in a way that the total perimeter of all sub-regions is minimized. The goal is to create square-like sub-regions, which are often more desired. We propose an efficient $1.203$--approximation algorithm for this problem based on a divide and conquer scheme that runs in $\mathcal{O}(n^2)$ time. For the special case when the aspect ratios of all rectangles are bounded from above by 3, the approximation factor is $2/\sqrt{3} \leq 1.1548$. We also present a modified version of out algorithm as a heuristic that achieves better average and best run times