Recent Developments in Predicting Impact and Shock Sensitivities of Energetic Materials （英）

Empirical, quantum mechanical and artificial neural network methods are three usual methods in recent years that were used to predict sensitivity of different classes of high explosives. Some recent developments in predicting sensitivity by various methods are reviewed and discussed for various classes of energetic materials.     

Evaluation of alumina reinforced oil fly ash composites prepared by spark plasma sintering

The thermomechanical behavior of micro/nano-alumina (Al₂O₃) ceramics reinforced with 1-5 wt.% of acid-treated oil fly ash (OFA) was investigated. Composites were sintered using spark plasma sintering (SPS) technique at a temperature of 1400°C by applying a constant uniaxial pressure of 50 MPa. It was evaluated that the fracture toughness of micro- and nanosized composites improved in contrast with the monolithic alumina. Highest fracture toughness value of 4.85 MPam^1/2 was measured for the nanosized composite reinforced with 5 wt.% OFA. The thermal conductivity of the composites (nano-/microsized) decreased with the increase in temperature. However, the addition of OFA (1-5 wt.%) in nanosized alumina enhanced the thermal conductivity at an evaluated temperature. Furthermore, a minimum thermal expansion value of 6.17 ppm*K⁻¹ was measured for nanosized Al₂O₃/5 wt.% OFA composite. Microstructural characterization of Al₂O₃-OFA composites was done by x-ray diffraction and Raman spectroscopy. Oil fly ash particles were seen to be well dispersed within the alumina matrix. Moreover, the comparative analysis of the nano-/microsized Al₂O₃/OFA composites shows that the mechanical and thermal properties were improved in nanosized alumina composites.     

Synthesis of Architectural-Cubic Porous Silicon by Electroless Stain Etching in V2O5 and HF Solution

Silicon - Porous silicon (PSi) samples were prepared via electroless stain etching of silicon substrates in HF using V2O5 as an oxidant and ethanol as a surfactant for different etching times. The...     

A Modified Method for the Determination of N‐Nitrosodiethanolamine in Coconut Diethanolamide Using HPLC with Dual‐Wavelength UV–Vis Detector

A simple and novel method based on high‐performance liquid chromatography with dual‐wavelength ultraviolet detection at 234 and 254 nm has been developed for the determination of underivatized N‐nitrosodiethanolamine in coconut diethanolamide. The correlation coefficient obtained shows that the method is correct.     

Correct Prediction of the Vibration Behavior of a High Power Ultrasonic Transducer by FEM Simulation

This paper presents a study on three types of finite element analyses of high power ultrasonic transducer by using the finite element commercial software called ANSYS. The transducer geometry was treated as a 2D axi- symmetric model, 3D quart and full 3D model. For all of the simulations the modeled transducer was used in modal analysis and harmonic solutions to understand its mechanical behavior and its natural frequency. A comparison was made between each type of modeling and experimental results. This comparison allows the parameters of FEM models to be iteratively adjusted and optimized and also leads to selection of the best modeling type. The achieved FEM results exhibited a remarkably high predictive potential of ANSYS in modeling and simulation and allowed control on the design and on the vibration behavior of the high power ultrasonic transducer.     

Multi-reservoir Operation Rules: Multi-swarm PSO-based Optimization Approach

Reservoir operation rules are intended to help an operator so that water releases and storage capacities are in the best interests of the system objectives. In multi-reservoir systems, a large number of feasible operation policies may exist. System engineering and optimization techniques can assist in identifying the most desirable of those feasible operation policies. This paper presents and tests a set of operation rules for a multi-reservoir system, employing a multi-swarm version of particle swarm optimization (MSPSO) in connection with the well-known HEC-ResPRM simulation model in a parameterization–simulation–optimization (parameterization SO) approach. To improve the performance of the standard particle swarm optimization algorithm, this paper incorporates a new strategic mechanism called multi-swarm into the algorithm. Parameters of the rule are estimated by employing a parameterization–simulation–optimization approach, in which a full-scale simulation model evaluates the objective function value for each trial set of parameter values proposed with an efficient version of the particle swarm optimization algorithm. The usefulness of the MSPSO in developing reservoir operation policies is examined by using the existing three-reservoir system of Mica, Libby, and Grand Coulee as part of the Columbia River Basin development. Results of the rule-based reservoir operation are compared with those of HEC-ResPRM. It is shown that the real-time operation of the three reservoir system with the proposed approach may significantly outperform the common implicit stochastic optimization approach.     

Generalized thermoelastic diffusion in a nanoscale beam using eigenvalue approach

In this paper, the effect of mass diffusion in a thermoelastic nanoscale beam in context Lord and Shulman theory is studied. The analytical solution in the Laplace domain is obtained for lateral deflection, temperature, displacement, concentration, stress and chemical potential. The both ends of the nanoscale beam are simply supported. The basic equations have been written in the form of a vector-matrix differential equation in the Laplace transform domain, which is then solved by an eigenvalue approach. The results obtained are presented graphically for the effect of time and mass diffusion to display the phenomena physical meaning.     

Green synthesised zinc oxide nanostructures through Periploca aphylla extract shows tremendous antibacterial potential against multidrug resistant pathogens

To grapple with multidrug resistant bacterial infections, implementations of antibacterial nanomedicines have gained prime attention of the researchers across the globe. Nowadays, zinc oxide (ZnO) at nano‐scale has emerged as a promising antibacterial therapeutic agent. Keeping this in view, ZnO nanostructures (ZnO‐NS) have been synthesised through reduction by P. aphylla aqueous extract without the utilisation of any acid or base. Structural examinations via scanning electron microscopy (SEM) and X‐ray diffraction have revealed pure phase morphology with highly homogenised average particle size of 18 nm. SEM findings were further supplemented by transmission electron microscopy examinations. The characteristic Zn–O peak has been observed around 363 nm using ultra‐violet–visible spectroscopy. Fourier‐transform infrared spectroscopy examination has also confirmed the formation of ZnO‐NS through detection of Zn–O bond vibration frequencies. To check the superior antibacterial activity of ZnO‐NS, the authors'' team has performed disc diffusion assay and colony forming unit testing against multidrug resistant E. coli, S. marcescens and E. cloacae. Furthermore, protein kinase inhibition assay and cytotoxicity examinations have revealed that green fabricated ZnO‐NS are non‐hazardous, economical, environmental friendly and possess tremendous potential to treat lethal infections caused by multidrug resistant pathogens.Inspec keywords: nanomedicine, zinc compounds, II‐VI semiconductors, wide band gap semiconductors, nanoparticles, scanning electron microscopy, X‐ray diffraction, antibacterial activity, transmission electron microscopy, particle size, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, enzymes, biochemistry, molecular biophysics, microorganisms, drugs, toxicology, bonds (chemical), semiconductor growth, nanofabrication, vibrational modesOther keywords: green synthesised zinc oxide nanostructures, Periploca aphylla extract, antibacterial potential, multidrug resistant pathogens, multidrug resistant bacterial infections, antibacterial nanomedicines, P. aphylla aqueous extract, structural examinations, scanning electron microscopy, X‐ray diffraction, pure phase morphology, homogenised average particle size, SEM, transmission electron microscopy, Fourier‐transform infrared spectroscopy, bond vibration frequency, antibacterial activity, disc diffusion assay, colony forming unit testing, S. marcescens, E. cloacae, E. coli, ultraviolet‐visible spectroscopy, protein kinase inhibition assay, cytotoxicity, lethal infections, ZnO     

Enhancement of in vitro antitumour activity of epirubicin in HER2+ breast cancer cells using immunoliposome formulation

Epirubicin (EPI) is one of the potent breast cancer (BC) chemotherapeutic agents, but its adverse effects limit its efficacy. Herein, EPI was selected to be loaded in liposomal carrier, which has been targeted by a monoclonal antibody, Herceptin. The preparation process of liposomes was a modified ethanol injection method followed by Herceptin conjugation. The in vitro cell toxicity and cellular uptake of optimum formulation against HER2+ and HER2− cancer cell lines were evaluated. The results showed that the drug loading (DL%) and encapsulation efficiency (EE%) of liposome preparation method yielded 30.62% ± 0.49% and 62.39% ± 8.75%, respectively. The average size of naked liposomes (EPI‐Lipo) and immunoliposomes (EPI‐Lipo‐mAb) was 234 ± 9.86 and 257.26 ± 6.25 nm, with a relatively monodisperse distribution, which was confirmed by SEM micrographs. The release kinetic followed Higuchi model for both naked and immunoliposomes. In vitro cytotoxicity study on three different BC cell lines including BT‐20, MDA‐MB‐453 and MCF‐7 demonstrated higher toxicity of EPI in the Herceptin conjugated form (EPI‐Lipo‐mAb) in comparison with the free EPI and EPI‐Lipo in HER2 overexpressing cell line. In addition, the cellular uptake study showed a higher uptake of immunoliposomes by MCF‐7 cells in comparison with naked liposomes. In conclusion, these data show that the targeted delivery of EPI to breast cancer cells can be achieved by EPI‐Lipo‐mAb in vitro, and this strategy could be used for breast cancer therapy with further studies.     

Transfer Learning-based Computer-aided Diagnosis System for Predicting Grades of Diabetic Retinopathy

Diabetic retinopathy (DR) diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features. This task is very difficult for ophthalmologists and time-consuming. Therefore, many computer-aided diagnosis (CAD) systems were developed to automate this screening process of DR. In this paper, a CAD-DR system is proposed based on preprocessing and a pre-train transfer learning-based convolutional neural network (PCNN) to recognize the five stages of DR through retinal fundus images. To develop this CAD-DR system, a preprocessing step is performed in a perceptual-oriented color space to enhance the DR-related lesions and then a standard pre-train PCNN model is improved to get high classification results. The architecture of the PCNN model is based on three main phases. Firstly, the training process of the proposed PCNN is accomplished by using the expected gradient length (EGL) to decrease the image labeling efforts during the training of the CNN model. Secondly, the most informative patches and images were automatically selected using a few pieces of training labeled samples. Thirdly, the PCNN method generated useful masks for prognostication and identified regions of interest. Fourthly, the DR-related lesions involved in the classification task such as micro-aneurysms, hemorrhages, and exudates were detected and then used for recognition of DR. The PCNN model is pre-trained using a high-end graphical processor unit (GPU) on the publicly available Kaggle benchmark. The obtained results demonstrate that the CAD-DR system outperforms compared to other state-of-the-art in terms of sensitivity (SE), specificity (SP), and accuracy (ACC). On the test set of 30,000 images, the CAD-DR system achieved an average SE of 93.20%, SP of 96.10%, and ACC of 98%. This result indicates that the proposed CAD-DR system is appropriate for the screening of the severity-level of DR.