Efficacy of iron fortification compared to iron supplementation among Vietnamese schoolchildren

Background  

Parents of six children are facing a trial on charges of aggravated manslaughter in the care a 5 1/2 month old infant who died suddenly and neglect of their four older children for causing them to be malnourished by feeding them all an exclusively raw foods vegan diet. Both parents declined plea bargains and plan to defend themselves in court.     

Effects of molasses grass,Melinis minutiflora volatiles on the foraging behavior of the cereal stemborer parasitoid,Cotesia sesamiae

Olfactory responses of the cereal stemborer parasitoid Cotesia sesamiae to volatiles emitted by gramineous host and nonhost plants of the stemborers were studied in a Y-tube olfactometer. The host plants were maize (Zea mays) and sorghum ( Sorghum bicolor), while the nonhost plant was molasses grass (Melinis minutiflora). In single-choice tests, females of C. sesamiae chose volatiles from infested and uninfested host plants and molasses grass over volatiles from the control (soil). In dual-choice tests, the wasp preferred volatiles from infested host plants to those from uninfested host plants. There was no discrimination between molasses grass volatiles and those of uninfested maize, uninfested sorghum, or infested maize. The wasp preferred sorghum volatiles over maize. Combining uninfested maize or sorghum with molasses grass did not make volatiles from the combination more attractive as compared to only uninfested host plants. Infested maize alone was as attractive as when combined with molasses grass. Infested sorghum was preferred over its combination with molasses grass. Local growth conditions of the molasses grasses influenced attractiveness to the parasitoids. Volatiles from Thika molasses grass were attractive, while those from Mbita molasses grass were not. Growing the Thika molasses grass in Mbita rendered it unattractive and vice versa with the Mbita molasses grass. This is a case of the same genotype expressing different phenotypes due to environmental factors.     

PCA-DTT 2D-DHCES based attack resilient imperceptible image watermarking

Most schemes exhibit low robustness due to LSB’s (Least Significant Bit) and MSB’s (Most Significant Bit) based information hiding in the cover image. However, most of these IW schemes have low imperceptibility as the cover image distortion reveals to the attacker due to information hiding in MSB’s. In this paper, a hybrid image watermarking scheme is proposed based on integrating Robust Principal Component Analysis (R-PCA), Discrete Tchebichef Transform (DTT), and Singular Value Decomposition (SVD). A grayscale watermark image is twisted/scrambled using a 2D Discrete Hyper-chaotic Encryption System (2D-DHCES) to boost up the robustness/heftiness and security. The original cover image is crumbled into sparse components using R-PCA and using DTT the substantial component is additionally decomposed and the watermark will be embedded in the cover image using SVD processing. In DTT, scarcer coefficients hold the utmost energy, also provide an optimum sparse depiction of the substantial image edges and features that supports proficient retrieval of the watermark image even after unadorned image distortion based channel attacks. The imperceptibility and robustness of the proposed method are corroborated against a variety of signal processing channel attacks (salt and pepper noise, multi-directional shearing, cropping, and frequency filtering, etc.). The visual and quantifiable outcomes reveal that the proposed image watermarking scheme is much effective and delivers high forbearance against several image processing and geometric attacks.

     

Sensor Fault Diagnosis and Unknown Disturbances Estimation of High Switching Frequency Single-phase PWM Rectifier

International Journal of Control, Automation and Systems - The fault and disturbances estimation has an important role in the modern traction railway system. This paper proposes a unique method for...     

Fabrication of co-PVDF/modacrylic/SiO2 nanofibrous membrane: Composite separator for safe and high performance lithium-ion batteries

Highly porous free-standing co-poly(vinylidene fluoride)/modacrylic/SiO₂ nanofibrous membrane was developed using electrically-assisted solution blow spinning method. The performance and the potential of the membrane as a lithium-ion battery separator were investigated. The addition of modacrylic enhanced the solution spinnability that resulted in defect-free membranes. Moreover, the presence of modacrylic enhanced the dimensional and thermal stabilities, while the addition of hydrophilic SiO₂ nanoparticle enhanced both mechanical property and ionic conductivity. Combustion test results illustrated that the presence of modacrylic provide flame retarding property over a set of different polymeric-based membranes. Electrochemical performance results showed that the developed membrane can increase the battery capacity compared with the commercial separator.     

Performance tuning of glass fiber/epoxy composites through interfacial modification upon integrating with dendrimer functionalized graphene oxide

In this study, glass fiber/epoxy composites were interfacially tailored by introducing polyamidoamine (PAM) dendrimer functionalized graphene oxide (GO) into epoxy matrix. Two different composites each containing varying loading fraction (0.5, 1.0, and 1.5 wt%) of GO and GO-PAM were fabricated via hot press processing. Composites were evaluated for interlaminar shear strength (ILSS), dynamic mechanical properties and thermal conductivity. The inclusion of 1.5 wt% GO-PAM resulted ~57.3%, ~42.7%, and ~54% enhancement in ILSS, storage modulus and thermal conductivity, respectively. Almost, ~71% reduction in coefficient of thermal expansion was also observed at same GO-PAM loading. Moreover, higher glass transition temperature was observed with GO-PAM addition. GO-PAM substantially improved fiber/matrix interfacial adhesion, which was witnessed through scanning electron microscopy. The enhanced thermo-mechanical performance was attributed to interfacial covalent interactions engendered by ring opening reaction between epoxy and amine moieties of PAM dendrimers. These multiscale composites with extraordinary functional properties can outperform conventional counterparts with improved reliability and performance.     

Adaptive interpolation scheme for NURBS curves with the integration of machining dynamics

This paper develops a comprehensive interpolation scheme for non-uniform rational B-spline (NURBS) curves, which does not only simultaneously meet the requirements of both constant feedrate and chord accuracy, but also real-time integrates machining dynamics in the interpolation stage. Although the existing work in this regard has realized the importance to simultaneously consider chord error and machining dynamics, none has really incorporated these in one complete interpolation scheme. In this paper, machining dynamics is considered for three aspects: sharp corners or feedrate sensitive corners on the curves, components with high frequencies or frequencies matching machine natural ones and high jerks. A look-ahead module was developed for detecting and adaptively adjusting the feedrate at the sharp corners. By Fast Fourier Transform (FFT) analysis with a moving window in the interpolation stage identified were some special frequency components such as those containing high frequencies or with frequencies matching machine natural ones. Then, the notch filtering or time spacing method was used to eliminate these components. To more completely reduce feedrate and acceleration fluctuations, the jerk-limited algorithm was also developed. Finally, the interpolated feedrate was further smoothened with B-spline fitting method and the NURBS curves were re-interpolated with the smoothened feedrate. During the interpolation, the chord error was repeatedly checked and confined in the prescribed tolerance. Two NURBS curves were used as examples to test the feasibility of the developed interpolation scheme.     

Molybdenum and tungsten coatings for x- ray targets obtained through the low-pressure plasma spraying process

Low-pressure plasma spraying under an argon atmosphere was employed to deposit molybdenum and tungsten coatings on different metallic, ceramic, and composite substrates. Molybdenum coatings ob-tained through this technique presented a homogeneous structure with an average porosity of about 17 %. These coatings exhibited adhesion greater than 40 MPa on molybdenum and grey cast iron (FT25) substrates. No adhesion was observed on an A1N surface regardless of the preheating temperature and/or surface preparation. Adhesion on AIN-Mo (AM25) composite substrate, containing 25 % dispersed metal-lic phase by volume, showed intermediate results. Tungsten coatings exhibited porosity between 10 to 12% and a typical lamellar structure. The adhesion of tungsten coatings on molybdenum and FT25 sub-strates was around 40 MPa.     

Implementation and performance evaluation of a scheduling algorithm for divisible load parallel applications in a cloud computing environment

Cloud computing is an emerging technology in which information technology resources are virtualized to users in a set of computing resources on a pay‐per‐use basis. It is seen as an effective infrastructure for high performance applications. Divisible load applications occur in many scientific and engineering applications. However, dividing an application and deploying it in a cloud computing environment face challenges to obtain an optimal performance due to the overheads introduced by the cloud virtualization and the supporting cloud middleware. Therefore, we provide results of series of extensive experiments in scheduling divisible load application in a Cloud environment to decrease the overall application execution time considering the cloud networking and computing capacities presented to the application's user. We experiment with real applications within the Amazon cloud computing environment. Our extensive experiments analyze the reasons of the discrepancies between a theoretical model and the reality and propose adequate solutions. These discrepancies are due to three factors: the network behavior, the application behavior and the cloud computing virtualization. Our results show that applying the algorithm result in a maximum ratio of 1.41 of the measured normalized makespan versus the ideal makespan for application in which the communication to computation ratio is big. They show that the algorithm is effective for those applications in a heterogeneous setting reaching a ratio of 1.28 for large data sets. For application following the ensemble clustering model in which the computation to communication ratio is big and variable, we obtained a maximum ratio of 4.7 for large data set and a ratio of 2.11 for small data set. Applying the algorithm also results in an important speedup. These results are revealing for the type of applications we consider under experiments. The experiments also reveal the impact of the choice of the platforms provided by Amazon on the performance of the applications under study. Considering the emergence of cloud computing for high performance applications, the results in this paper can be widely adopted by cloud computing developers. Copyright © 2014 John Wiley & Sons, Ltd.     

Using model transformation to refactor use case models based on antipatterns

Use Case modeling is a popular technique for documenting functional requirements of software systems. Refactoring is the process of enhancing the structure of a software artifact without changing its intended behavior. Refactoring, which was first introduced for source code, has been extended for use case models. Antipatterns are low quality solutions to commonly occurring design problems. The presence of antipatterns in a use case model is likely to propagate defects to other software artifacts. Therefore, detection and refactoring of antipatterns in use case models is crucial for ensuring the overall quality of a software system. Model transformation can greatly ease several software development activities including model refactoring. In this paper, a model transformation approach is proposed for improving the quality of use case models. Model transformations which can detect antipattern instances in a given use case model, and refactor them appropriately are defined and implemented. The practicability of the approach is demonstrated by applying it on a case study that pertains to biodiversity database system. The results show that model transformations can efficiently improve quality of use case models by saving time and effort.