What defense doesSchouwia purpurea (Cruciferae) have against the desert locust?

A field study of the food eaten by solitary desert locusts was carried out in a winter breeding area in Mauritania. The food eaten, determined by the plant epidermis found in fecal pellets, was compared to the plant's availability in the habitat.Schouwia purpurea, well represented in the diets, was dominant at the study site. Adults had a preference forTribulus terrester. Growth and feeding on these two plants were compared. The high water content ofS. purpurea leaves limited the dry matter eaten and slowed down growth. Glucosinolates were separated and quantified by gas chromatography. There are 132mol/g dry matter in green leaves. In multiple choice tests, with paper disks, glucosinolate extracts were phagostimulant at a low concentration (21mol/g dry matter) and repulsive at a higher one (214mol/ g dry matter). Biting behavior onS. purpurea was recorded and analyzed on video. The importance ofSchouwia purpurea in desert locust habitats and its defenses is discussed.     

The pseudo-single-phase,base-catalyzed transmethylation of soybean oil

The base-catalyzed transmethylation of soybean oil has been studied under conditions whereby the reaction starts as a single phase, but later becomes two phases as glycerol separates. Methanol/oil molar ratios of 6∶1 were used at 23°C. The catalysts were sodium hydroxide (0.5, 1.0, and 2.0 wt%), potassium hydroxide (1.0 and 1.4 wt%), and sodium methoxide (0.5, 1.0, and 1.35 wt%), all concentrations being with respect to the oil. Oxolane (tetrahydrofuran) was used to form a single reaction phase. The reactions deviated from homogeneous kinetics as glycerol separated, taking with it most of the catalyst. When 1.0 wt% sodium hydroxide was used, the methyl ester content reached 97.5 wt% after 4 h, compared with 85–90 wt% in the two-phase reaction. Sodium hydroxide (1.0 wt%), sodium methoxide (1.35 wt%), and potassium hydroxide (1.4 wt%) gave similar results, presumably because the same number of moles was used. The ASTM biodiesel specification for chemically bound glycerol was achieved after only 3 min when 2.0 wt% sodium hydroxide was used. However, the standard was not achieved after 4 h when 1.0 wt% sodium hydroxide was used, the MG content being 1.1–1.6 wt%. The use of 2.0 wt% catalyst is commercially impractical.     

Physicochemical properties of irradiated and loaded LDPE films with polyfunctional monomers

Polyfunctional monomers (PFMs), namely, trimethylol propane trimethacrylate (TMPTMA), trimethylol propane triacrylate, ethylene glycol dimethacrylate, and diethylene glycol diacrylate were blended with low‐density polyethylene (LDPE) and exposed to different doses of EB irradiation. Fourier transform infrared and ultraviolet and UV–vis spectroscopy of the unirradiated, irradiated, unloaded, and PFMs‐loaded LDPE films were studied under various irradiation doses up to 300 kGy. The degree of crosslinking and oxidative degradation, as measured by the spectroscopic parameters, were dependent on both the irradiation dose and the type of loaded PFMs. For all of the loaded monomers, the extent of crosslinking increased at different rates as a function of irradiation dose. TMPTMA monomer was the most efficient in enhancing the crosslinking of LDPE films compared to the other loaded monomers. However, the unloaded LDPE film showed the least extent of crosslinking. In addition, the EB‐radiation‐induced changes, such as trans‐vinylene formation, a decrease in vinyl and vinylidene unsaturation; and carbonyl double‐bond formation and change in crystallinity were correlated. The importance of these results on the prediction of the role of polyfunctional monomers in the production of crosslinked polymers is discussed. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2025–2035, 2003     

Effects of dietary casein and soy protein on metabolism of radiolabelled low density apolipoprotein B in rabbits

Rabbits fed semipurified diets containing casein have elevated plasma cholesterol levels compared to those fed soy protein. As part of continuing studies on the mechanism of casein-induced hypercholesterolemia, two groups of six rabbits were fed these diets for 14 to 16 weeks. Animals fed the casein diet were found to have significantly higher plasma concentrations of protein, cholesterol, triacylglycerol, phospholipid and apolipoprotein B (apo B) associated with low density lipoprotein (LDL) than those fed the soy protein diet. Kinetic studies showed that the fractional catabolic rate of LDL-apo B was significantly lower in animals fed casein than in those fed soy protein regardless of whether the tracer LDL was obtained from donors fed casein or soy protein. The production rate of LDL-apo B was higher in casein-fed animals but this was not statistically significant. These results show that the efficiency of removal of LDL is significantly reduced in animals fed casein compared to those fed soy protein, and that the source of LDL did not affect the efficiency of its subsequent removal. The acumulation of LDL in casein-fed animals is consistent with down-regulation of the LDL receptor.     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.

     

Simulink behavioral modeling of a 10-bit pipelined ADC

The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specific data converter simulation environment has been developed which allows designers to perform time-domain behavioral simulations of pipelined analog to digital converters (ADCs). All the necessary blocks of this specific simulation environment have been implemented using the popular Matlab simulink environment. The purpose of this paper is to present the behavioral models of these blocks taking into account most of the pipelined ADC non-idealities, such as sampling jitter, noise, and operational amplifier parameters (white noise, finite DC gain, finite bandwidth, slew rate, and saturation voltages). Simulations, using a 10-bit pipelined ADC as a design example, show that in addition to the limits analysis and the electrical features extraction, designers can determine the specifications of the basic blocks in order to meet the given data converter requirements.     

An effective DeepWINet CNN model for off-line text-independent writer identification

Pattern Analysis and Applications - Writer identification based on handwriting recognition is considered one of the most common research areas in pattern recognition and biometrics. It has...     

An efficient approach for damage identification based on improved machine learning using PSO-SVM

Engineering with Computers - Structural health monitoring (SHM) and Non-destructive Damage Identification (NDI) using responses of structures under dynamic excitation have an imperative role in the...     

The reference temperature dependence of Young’s modulus of two-temperature thermoelastic damping of gold nano-beam

This work is concerning with the study of the thermoelastic damping of a nanobeam resonator in the context of the two-temperature generalized thermoelasticity theory. An explicit formula of thermoelastic damping has been derived when Young’s modulus is a function of the reference temperature. Influences of the beam height and Young’s modulus have been studied with some comparisons between the Biot model and the Lord–Shulman model (L–S) for one- and two-temperature types. Numerical results show that the values of the thermal relaxation parameter and the two-temperature parameter have a strong influence on thermoelastic damping at nanoscales.     

A new contact model for the discrete element method simulation of $$\hbox {TiO}_2$$ nanoparticle films under mechanical load

We develop a novel coarse-grained contact model for Discrete Element Method simulations of \(\hbox {TiO}_2\) nanoparticle films subjected to mechanical stress. All model elements and parameters are derived in a self-consistent and physically sound way from all-atom Molecular Dynamics simulations of interacting particles and surfaces. In particular, the nature of atomic-scale friction and dissipation effects is taken into account by explicit modelling of the surface features and water adsorbate layers that strongly mediate the particle-particle interactions. The quantitative accuracy of the coarse-grained model is validated against all-atom simulations of \(\hbox {TiO}_2\) nanoparticle agglomerates under tensile stress. Moreover, its predictive power is demonstrated with calculations of force-displacement curves of entire nanoparticle films probed with force spectroscopy. The simulation results are compared with Atomic Force Microscopy and Transmission Electron Microscopy experiments.