Microwave diversity imaging and automated target identificationbased on models of neural networks

Radar targets can be identified by either forming images with sufficient resolution to be recognized by the human observer or by forming signatures or representations of the target for automated machine recognition. Tomographic microwave diversity imaging techniques that combine angular (aspect), spectral, and polarization degrees of freedom have been shown, as summarized in the first part of this paper, to be capable of producing images of the scattering centers of a target with near optical resolution. In the second part of the paper the author shows that collective nonlinear signal processing based on models of neural networks combined with the use of suitable target signatures (here sinogram representations) offer the promise of robust super-resolved target identification from partial information. Results presented are of numerical simulations for a neuromorphic processor where the neural net performs simultaneously the functions of data storage, processing, and recognition by automatically generating an identifying object label, and fast optoelectronic architectures and hardware implementations are briefly mentioned. Practical considerations and extensions to real systems are briefly discussed     

Age-Related Differences in the use of Hypertext: Experiment and Design Guidelines

Hypertext systems can be targeted for many different user populations, yet little experimental research has been done to provide design guidelines on how to match the system to the user. An experiment tested whether age relates to the dimensions of performance, navigation strategies and perceptions in use of a hypertext library card catalog. While adults were superior to children in speed and accuracy, there were no indications that the children were qualitatively different than the adults in navigation patterns or perceptions of the system. Some children exhibited more exploratory problem-solving behaviors that the adults. A number of design guidelines are offered, based on the empirical results.     

Suppressing the coalescence in the multi-component lattice Boltzmann method

This article discusses a novel phenomenological approach for suppressing the coalescence in the Gunstensen multi-component lattice Boltzmann method (LBM). The suppression of coalescence is achieved by perturbing the terminal nodes of the ambient fluid’s thin layer trapped between the approaching droplets. This additional perturbation creates a local high pressure fluid layer which eventually leads to suppressing the coalescence of the neighboring droplets while maintaining a suitable qualitative force balance representative of the physical intermolecular forces which act between them.     

Insight into crystal growth and upconversion luminescence property of tetragonal Ba3Sc2F12 nanocrystals

Sc-based nanomaterials have attracted consid-erable attention due to their unique optical properties dif-ferent from those of Ln/Y-based nanomaterials.However,s...     

Tomographic microwave diversity image reconstruction employingunitary compression

Data compression through a unitary transform is utilized in tomographic microwave diversity image reconstruction in order to reduce the dimensionality and to extract the features in the data space. The unitary compression is derived by minimizing the mean-square error (MSE) and the unitary transform is made of eigenvectors of the data's covariance, regarded as a Karhunen-Loeve transform. Tomographic microwave frequency-swept imaging was developed using a unique target-derived reference technique to access the three dimensional Fourier space of the scatterer and an image reconstruction algorithm based on the projection slice theorem. It is shown that centimeter resolution of a complex object can be preserved even when half of the data set is compressed and that the reconstructed image remains identifiable by a human observer even when 2/3 of the data set is compressed     

A Novel Sprague-Dawley Rat Model Presents Improved NASH/NAFLD Symptoms with PEG Coated Vitexin Liposomes

Chronic liver disease (CLD) is a global threat to the human population, with manifestations resulting from alcohol-related liver disease (ALD) and non-alcohol fatty liver disease (NAFLD). NAFLD, if not treated, may progress to non-alcoholic steatohepatitis (NASH). Furthermore, inflammation leads to liver fibrosis, cirrhosis, and hepatocellular carcinoma. Vitexin, a natural flavonoid, has been recently reported for inhibiting NAFLD. It is a lipogenesis inhibitor and activates lipolysis and fatty acid oxidation. In addition, owing to its antioxidant properties, it appeared as a hepatoprotective candidate. However, it exhibits low bioavailability and low efficacy due to its hydrophobic nature. A novel rat model for liver cirrhosis was developed by CCL4/Urethane co-administration. Vitexin encapsulated liposomes were synthesized by the ‘thin-film hydration’ method. Polyethylene glycol (PEG) was coated on liposomes to enhance stability and stealth effect. The diseased rats were then treated with vitexin and PEGylated vitexin liposomes, administered intravenously and orally. Results ascertained the liposomal encapsulation of vitexin and subsequent PEG coating to be a substantial strategy for treating liver cirrhosis through oral drug delivery.     

DRYING KINETICS AND CHARACTERISTIC DRYING CURVE OF LIGHTLY SALTED SARDINE (SARDINELLA AURITA)

Drying of lightly salted sardine (Sardinella aurita) was accomplished using three air temperatures (35°C, 40°C, 50°C) and three air velocities (0.5 m/s, 1.5 m/s, 2 m/s); the effects of drying conditions on drying kinetics were studied. As for all biological products, air temperature is the main factor influencing the drying kinetics. However, over a given temperature which seems to correspond to protein modification (50°C), and at a high air flow rate (2 m/s and 2.5 m/s) a crust formation on the surface of the fish, due to the combined effect of heat and salt was observed. This phenomenon inhibited the drying rate. From the drying curves, two falling rate periods were observed. The dimensionless drying rate versus a dimensionless moisture content data were regressed by the Marquardt Levenberg non-linear optimization method to obtain an empirical equation describing the salted sardine characteristic drying curve.     

Antimicrobial materials based on poly(ethylene-co-vinyl alcohol) and silver acetate produced by reactive extrusion

The use of silver as an antimicrobial agent has exhibited great interest in recent years. In this research, poly(ethylene-co-vinyl alcohol) (EVOH)–silver acetate-based antimicrobial materials were prepared at high temperature by reactive extrusion. Silver acetates were used without pretreatment. The thermal reaction of silver acetates in the material and their effect on the thermal and mechanical properties of the polymer were investigated as a function of their concentration. The dispersed silver acetate salts within the EVOH matrix have displayed a significant thermal reaction. This reaction of metallic salts was partial when the extrusion temperature was fixed at 190 °C and completed at 230 °C. The antimicrobial agents also had significant effects on the properties of the matrix. Reductions of glass temperature and storage modulus were observed by the analyses. All the variations were dependent on both the concentration of silver acetate and the extrusion parameters. The antimicrobial activity was studied and demonstrated a promising potential to create an antimicrobial material in a one-step solvent free extrusion method. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47799.     

A Novel Hybrid Method for River Discharge Prediction

Accurate prediction of river discharge is essential for the planning and management of water resources. This study proposes a novel hybrid method named HD-SKA by integrating two decomposition techniques (termed as HD) with support vector regression (SVR), K-nearest neighbor (KNN) and ARIMA models (combined as SKA) respectively. Firstly, the proposed method utilizes local mean decomposition (LMD) to decompose the original river discharge series into sub-series. Next, ensemble empirical mode decomposition (EEMD) is employed to further decompose the LMD-based sub-series into intrinsic mode functions. Further, the EEMD decomposed components are used as inputs in three data-driven models to predict river discharge respectively. The prediction of all components is then aggregated to obtain the results of HD-SVR, HD-KNN and HD-ARIMA models. The final prediction is obtained by taking the average prediction of these models. The proposed method is illustrated using five rivers in Indus Basin System. In five case studies, six models were built to compare the performance of the proposed HD-SKA model. The data analysis results show that the HD-SKA model performs better than all other considered models. The Diebold-Mariano test confirms the superiority of the proposed HD-SKA model over ARIMA, SVR, KNN, EEMD-ARIMA, EEMD-KNN, and EEMD-SVR models.

     

Depollution of atmospheric emissions of wood pyrolysis furnaces

The wood carbonization in Tunisia consists essentially of traditional activity using charcoaling stacks and pits characterized by high atmospheric pollution and poor energy conversion. Indeed, 70% of the initial mass of anhydrous wood are found in the vapor as aerosols, polluting and toxic gases and complex condensable organic compounds that can cause a substantial pollution of air, ground and water. Several processes of treatment and energy valorization of such effluents were proposed, but the incineration remains at present the most promising technique of depollution. The results show that the incineration, at about 1000°C, of wood carbonization smokes allows the destruction of 99% of the mass of pollutants except CO₂ and the reduction of polluting gas emission. The possible valorization of the smoke’s energy in the exit of the incinerator enhances the thermal efficiency of the process.