Ameliorating Effects of Exogenously Applied Proline on Seed Composition,Seed Oil Quality and Oil Antioxidant Activity of Maize (Zea mays L.) under Drought Stress

This study was carried out to appraise whether or not the exogenous application of a potential osmoprotectant, proline, could ameliorate the adverse effects of drought stress on maize seed and seed oil composition, as well as oil antioxidant activity. Water stress reduced the kernel sugar, oil, protein and moisture contents and most of the seed macro- and micro-elements analyzed in both maize cultivars but it increased the contents of seed fiber and ash. Water stress increased the oil oleic acid content with a subsequent decrease in the amount of linoleic acid, resulting in an increased oil oleic/linoleic ratio for both maize cultivars. However, no variation was observed in oil stearic and palmitic acids content due to water stress. A considerable drought induced an increase in seed oil α-, γ-, δ- and total tocopherols and flavonoids were observed in both maize cultivars. However, oil phenolic and carotenoid content as well as 1,1-diphenyl-2-picryl-hydrazyl (DPPH) free radical scavenging activity decreased. Foliar-applied proline significantly increased the content of seed sugar, oil, protein, moisture, fiber and ash in both maize cultivars under well irrigated and water deficit conditions. Furthermore, exogenous application of proline increased the oil oleic and linoleic acid contents. The concentrations of antioxidant compounds namely phenolics, carotenoids, flavonoids and tocopherols estimated in the seed oil increased due to foliar-applied proline under water deficit conditions that was positively correlated with the enhanced oil DPPH free radical scavenging activity. Moreover, the increase in the contents of these antioxidant compounds and oil antioxidant activity due to the foliar application of proline was noted to be more pronounced under water deficit conditions.     

Prevalence and characterization of Salmonella enterica serovar Weltevreden from imported seafood

During 2001-2005, 210 Salmonella enterica strains were isolated from seafood samples imported into US. Strains of S. enterica serovar Weltevreden were the most predominantly found among the 64 different serovars isolated. A total of 37 Salmonella Weltevreden isolates were characterized by pulsed-field gel electrophoresis (PFGE), plasmid profiles and antibiotic susceptibility to assess genetic diversity. Our results showed a low frequency of antibiotic resistance; 35 of the 37 isolates were sensitive to ampicillin, tetracycline, chloramphenicol, gentamicin, sulfisoxazole, streptomycin and kanamycin. Only two isolates, from samples originating in the Philippines and India, showed resistance to ampicillin and tetracycline and to streptomycin, sulfisoxazole and tetracycline, respectively. Of the 37 isolates, two isolates did not carry any plasmid and 35 isolates harbored several small and mega-plasmids. These isolates were differentiated into 10 distinct types based on plasmid profiles. Four different PFGE clusters were obtained with a genetic similarity of 66-76%. Four groups of isolates (formed by two or three isolates each) showed 100% similarity in the PFGE profiles. One of these groups included strains isolated in Vietnam in 2003, 2004 and 2005 from fish and shrimp. The other groups included strains isolated in Vietnam, Indonesia and Thailand in 2000, 2004 and 2005 from snail, shrimp and fish. Our findings show genetic diversity and temporal persistence of S. enterica serovar Weltevreden in recently monitored seafood imports.     

Exploring the fitness landscape and the run-time behaviour of an iterated local search algorithm for cost-based abduction

Cost-based abduction (CBA) is an important problem in reasoning under uncertainty, and can be considered a generalization of belief revision. CBA is known to be NP-hard and has been a subject of considerable research over the past decade. In this paper, we investigate the fitness landscape for CBA, by looking at fitness–distance correlation for local minima and at landscape ruggedness. Our results indicate that stochastic local search techniques would be promising on this problem. We go on to present an iterated local search algorithm based on hill-climbing, tabu search, and simulated annealing. We compare the performance of our algorithm to simulated annealing, and to Santos' integer linear programming method for CBA.     

A visual tool for computer supported learning: The robot motion planning example

We introduce an effective computer aided learning visual tool (CALVT) to teach graph-based applications. We present the robot motion planning problem as an example of such applications. The proposed tool can be used to simulate and/or further to implement practical systems in different areas of computer science such as graphics, computational geometry, robotics and networking. In the robot motion planning example, CALVT enables users to setup the working environment by creating obstacles and a robot of different shapes, specifying starting and goal positions, and setting other path or environment parameters from a user-friendly interface. The path planning system involves several phases. Each of these modules is complex and therefore we provide the possibility of visualizing graphically the output of each phase. Based on our experience, this tool has been an effective one in classroom teaching. It not only cuts down, significantly, on the instructor’s time and effort but also motivates senior/graduate students to pursue work in this specific area of research.     

Synthesis of nitrogen incorporated diamond-like carbon thin films using microwave surface-wave plasma CVD

Nitrogenated diamond-like (DLC:N) carbon thin films have been deposited by microwave surface wave plasma chemical vapor deposition on silicon and quartz substrates, using argon gas, camphor dissolved in ethyl alcohol composition and nitrogen as plasma source. The deposited DLC:N films were characterized for their chemical, optical, structural and electrical properties through X-ray photoelectron spectroscopy, UV/VIS/NIR spectroscopy, Raman spectroscopy, atomic force microscope and current–voltage characteristics. Optical band gap decreased (2.7 to 2.4 eV) with increasing Ar gas flow rate. The photovoltaic measurements of DLC:N / p-Si structure show that the open-circuit voltage (V_oc) of 168.8 mV and a short-circuit current density (J_sc) of 8.4 μA/cm² under light illumination (AM 1.5 100 mW/cm²). The energy conversion efficiency and fill factor were found to be 3.4 × 10^{− 4}% and 0.238 respectively.     

Gateway Placement for Throughput Optimization in Wireless Mesh Networks

In this paper, we address the problem of gateway placement for throughput optimization in multi-hop wireless mesh networks. Assume that each mesh node in the mesh network has a traffic demand. Given the number of gateways to be deployed (denoted by k) and the interference model in the network, we study where to place exactly k gateways in the mesh network such that the total throughput is maximized while it also ensures a certain fairness among all mesh nodes. We propose a novel grid-based gateway deployment method using a cross-layer throughput optimization, and prove that the achieved throughput by our method is a constant times of the optimal. Simulation results demonstrate that our method can effectively exploit the available resources and perform much better than random and fixed deployment methods. In addition, the proposed method can also be extended to work with multi-channel and multi-radio mesh networks under different interference models.     

Reservoir Inflow Prediction by Ensembling Wavelet and Bootstrap Techniques to Multiple Linear Regression Model

In this study, a new hybrid model, bootstrap multiple linear regression (BMLR) is suggested to investigate the potential of bootstrap resampling technique for daily reservoir inflow prediction. The proposed model compares with three other models: Multiple linear regression (MLR), wavelet multiple linear regression (WMLR) and wavelet bootstrap multiple linear regression (WBMLR). River stage data of monsoon season (1st July 2010 to 30 September 2010) from three gauging stations of Chenab river basin are used. In wavelet transformation, input vectors are decomposed using discrete wavelet transformation (DWT) into discrete wavelet components (DWCs). Then suitable DWCs are used to provide input to MLR model to develop WMLR model. Bootstrap technique coupled with MLR model to build up BMLR model. While WBMLR model is the conjunction of suitable DWCs and bootstrap technique to MLR model. Performance indices namely root mean square error (RMSE), mean absolute error (MAE), Nash-Sutcliffe coefficient of efficiency (NSC), and persistence index (CP) are used in study to evaluate the performance of model. Results showed that hybrid model BMLR produce significantly better results on performance indices than other models MLR, WMLR and WBMLR.