Physical and chemical characteristics,major fatty acids,antimicrobial activity and toxicity analysis of red shrimp (Metapenaeus brevicornis) brain lipid

Physical and chemical characteristics of red shrimp (Metapenaeus brevicornis) brain lipid have been determined by standard methods. Through GLC analysis, caprylic, myristic, palmitic, stearic and oleic acids have been found as the five major fatty acid components of M. brevicornis brain lipid. The lipid has found active against disease causing bacteria Shigella dysenterial, Salmonella typhi and Staphylococcuss aureus, and fungal pathogens Macrophomina phascolma, Alternaria alternate and Curvularia lunata. By applying on predatory fishes, Heteropneustes fossilis and Anabas testudineus, different extracts of M. brevicornis brain lipid have showed a minimal toxic effect.     

Algorithms for generalized vertex-rankings of partial k-trees

A c-vertex-ranking of a graph G for a positive integer c is a labeling of the vertices of G with integers such that, for any label i, deletion of all vertices with labels >i leaves connected components, each having at most c vertices with label i. A c-vertex-ranking is optimal if the number of labels used is as small as possible. We present sequential and parallel algorithms to find an optimal c-vertex-ranking of a partial k-tree, that is, a graph of treewidth bounded by a fixed integer k. The sequential algorithm takes polynomial-time for any positive integer c. The parallel algorithm takes O(log n) parallel time using a polynomial number of processors on the common CRCW PRAM, where n is the number of vertices in G.     

Learning Sequences of Compatible Actions Among Agents

Action coordination in multiagent systemsis a difficult task especially in dynamicenvironments. If the environment possessescooperation, least communication,incompatibility and local informationconstraints, the task becomes even moredifficult. Learning compatible action sequencesto achieve a designated goal under theseconstraints is studied in this work. Two newmultiagent learning algorithms called QACE andNoCommQACE are developed. To improve theperformance of the QACE and NoCommQACEalgorithms four heuristics, stateiteration, means-ends analysis, decreasing reward and do-nothing, aredeveloped. The proposed algorithms are testedon the blocks world domain and the performanceresults are reported.     

Evaluation of solid-state bioconversion of domestic wastewater sludge as a promising environmental-friendly disposal technique

Natural and environmental-friendly disposal of wastewater sludge is a great concern. Recently, biological treatment has played prominent roles in bioremediation of complex hydrocarbon- rich contaminants. Composting is quite an old biological-based process that is being practiced but it could not create a great impact in the minds of concerned researchers. The present study was conducted to evaluate the feasibility of the solid-state bioconversion (SSB) processes in the biodegradation of wastewater sludge by exploiting this promising technique to rejuvenate the conventional process. The Indah Water Konsortium (IWK) domestic wastewater treatment plant (DWTP) sludge was considered for evaluation of SSB by monitoring the microbial growth and its subsequent roles in biodegradation under two conditions: (i) flask (F) and (ii) composting bin (CB) cultures. Sterile and semi-sterile environments were allowed in the F and the CB, respectively, using two mixed fungal cultures, Trichoderma harzianum with Phanerochaete chrysosporium 2094 (T/P) and T. harzianum with Mucor hiemalis (T/M) and two bulking materials, sawdust (SD) and rice straw (RS). The significant growth and multiplication of both the mixed fungal cultures were reflected in soluble protein, glucosamine and color intensity measurement of the water extract. The color intensity and pH of the water extract significantly increased and supported the higher growth of microbes and bioconversion. The most encouraging results of microbial growth and subsequent bioconversion were exhibited in the RS than the SD. A comparatively higher decrease of organic matter (OM) % and C/N ratio were attained in the CB than the F, which implied a higher bioconversion. But the measurement of soluble protein, glucosamine and color intensity exhibited higher values in the F than the CB. The final pH drop was higher in the CB than the F, which implied that a higher nitrification occurred in the CB associated with a higher release of H+ ions. Both the mixed cultures performed almost equal roles in all cases except the changes in moisture content.     

Synthesis and electrochemical characterization of La0.75Sr0.25Mn0.5Cr0.5−xAlxO3, for IT- and HT-SOFCs

The main emphasis of this work is to create a new perovskite material with three different compositions (La_0.75Sr_0.25Mn_0.5Cr_0.5−xAlxO₃, x = 0.1, 0.2, 0.3) applied in both Intermediate- and High-temperature Solid Oxide Fuel Cells (IT- and HT-SOFCs). Perovskite-type polycrystalline La_0.75Sr_0.25Mn_0.5Cr_0.5−xAl_xO_3−δ (x = 0.1, 0.2, 0.3) powders were synthesized and formed in a single phase structure by a dry chemistry route (standard solid-state reaction method). The effect of Al doping on physicochemical and surface properties has been discovered. The compounds were crystallized in single phase rhombohedral symmetry (R-3C Space. Group). Total conductivity of Al doping in wet 5% H₂ was higher than both dry 5% H₂ and air. The obtained results enhance the electro-catalytic performance and the material conductivity as well, which will be good for anode materials in IT- and HT-SOFCs and the optimum doping is 10%.     

Evaluation of Mechanical and Thermal Performance of Polyethylene Terephthalate Recycled Ribbon and Carbon-Reinforced Compatibilized Polypropylene

Polypropylene (PP) and polyethylene terephthalate (PET) are the two most widely used plastics, which are not compatible with recycling as a blend. In this research work, two different compositions of recycled PP/PET ribbon 65/35 (v/v %) and 78/22 (v/v%) along with 5% (wt%) of polypropylene-grafted maleic anhydride (PP-g-MAH) as compatibilizer were blended, 2– 5 wt% of carbon fiber (CF) was further added for reinforcement. The compositions of these materials are mechanically mixed and extruded by a twin-screw extruder to make pellets. These pellets are then used to produce standard samples by injection molding for evaluation. The molded samples were tested under tensile, flexural and impact loads to evaluate mechanical properties. Scanning electron microscopy (SEM) was conducted on the fracture surface of the impact-tested samples to understand polymer blend morphology. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) also carried out to check the thermal properties, mainly transition temperatures (T_g) and heat flow. These test results compared, which show substantial improvement in mechanical properties by adding CF and compatibilizer, without much change in transition temperatures. POLYM. ENG. SCI., 60:575–580, 2020. © 2019 Society of Plastics Engineers     

Design and development of ceramic-based composites with tailored properties for cutting tool inserts

A successful approach to the development of tailored cutting tool materials requires the development of innovative concepts at each step of manufacturing, from the material design, synthesis of composite powders, to their processing and sintering. In this paper, a computational design approach is applied in the development of reinforced ceramic-based cutting tool inserts with tailored structural and thermal properties. Several potential filler materials are considered at the material design stage for the improvement of structural and thermal properties of a selected matrix material. Properties, such as an improved thermal conductivity and reduced coefficient of thermal expansion are essential for an effective cutting tool insert to absorb thermal shock at varying temperatures. In addition, structural properties such as elastic modulus have to be maintained within a moderate range. A mean-field homogenization theory and effective medium approximation using an in-house code are applied for predicting potential optimum structural and thermal properties for the required application. This is done by considering the effect of inclusions as a function of volume fraction and particle size in the ceramic base matrix. Single inclusion composites such as alumina-silicon (Al₂O₃-SiC) and alumina-cubic boron nitride (Al₂O₃-cBN) as well as hybrid composite such as alumina-silicon-cubic boron nitride (Al₂O₃-SiC-cBN) are developed using the Spark Plasma Sintering (SPS) process in line with the designed range of filler size and volume fraction to validate the computational results. It is found that the computational material design approach is precise enough in predicting the target properties of a designed hybrid composite material for cutting tool inserts.