Comparative study of conventional and micro WEDM based on machining of meso/micro Sized Spur Gear

This paper discusses the comparison of micro machining process using conventional and micro wire electrical discharge machining (WEDM) for fabrication of miniaturized components. Seventeen toothed miniaturized spur gear of 3.5 and 1.2 mm outside diameter were fabricated by conventional and micro WEDM respectively. The process parameters for both conventional and micro WEDM were optimized by preliminary experiments and analysis. The gears were investigated for the quality of surface finish and dimensional accuracy which were used as the criteria for the process evaluation. An average surface roughness (R_a) of 50 nm and dimensional accuracy of 0.1–1 μm were achieved in micro WEDM. Whenever applied conventional WEDM for meso/micro fabrication, a R_a surface roughness of 1.8 μm and dimensional accuracy of 2–3 μm were achieved. However, this level of surface roughness and dimensional accuracy are acceptable in many applications of micro engineering. A window of conventional WEDM consisting of low energy discharge parameters is identified for micromachining.     

Increased In Vitro and In Vivo Digestibility of Soy Proteins by Chemical Modification of Disulfide Bonds

To improve protein digestibility of aqueously extracted soy proteins, an effective chemical treatment under mild conditions is needed. Soy proteins, including storage protein glycinin and antinutritional factors such as trypsin inhibitors, are rich in disulfide bonds. Reduction of these disulfide bonds by incubating soy proteins with sodium sulfite and sodium metabisulfite at 55 °C showed no net increase of free sulfhydryl groups after dialysis to remove the residual reducing agent. However, the in vitro digestibility measured by trypsin hydrolysis using the pH-Stat method was significantly increased. Sodium metabisulfite (SMBS) was more effective in increasing in vitro digestibility than sodium sulfite at the same molar concentration. The digestibility of soy protein treated by 0.5 mmol SMBS/g soy flour at 55 °C was more than doubled compared to that of the control without reduction treatment. Large-scale testing of soy proteins treated with SMBS for an in vivo animal feeding study showed similar in vitro digestibility by trypsin, e.g., the degree of hydrolysis of the treated sample was 8.5% compared to 1.6% of the control. These soy proteins were further evaluated using a chick growth model. The protein efficiency ratio (PER) increased by 57% when the chicks fed SMBS-treated soy were compared to the chicks fed raw soy flour. SMBS-fed chicks did not display any pancreatic hypertrophy compared to those fed with raw soy control. These results indicate that there is great potential to use safe chemicals and mild temperature to inactivate the antinutritional factors in soybeans and thus improve digestibility of soy proteins that are extracted with low-temperature aqueous process.     

Compatibilization of low‐density polyethylene/plasticized starch blends by reactive compounds and electron beam irradiation

Blends based on various compositions of low‐density polyethylene (LDPE) and plasticized starch (PLST) were prepared by melt extrusion and molding in the form of sheets under hot press. The rheology properties during mixing were studied in terms of torque and temperature against mixing time. The structural properties of LDPE/PLST blends before and after electron beam irradiation was characterized by IR spectroscopy, tensile mechanical testing, and scanning electron microscopy (SEM). The torque‐time curves during the mixing process showed that the values of torque in the first region of mixing for pure LDPE or LDPE/PLST blends are higher in the presence of the compatibilizer PEMA than that in the presence of EVA. In addition, the stability of mixing was attained after a short time in the presence of PEMA. The IR spectroscopy suggests that the compatibilization by EVA and PEMA compounds proceeds through the formation of hydrogen bonding during mixing and this compatibility was improved after electron beam irradiation. The stress–strain curves of pure LDPE and its blends with PLST showed the behavior of tough polymers with yielding properties. The SEM micrographs of the fracture surfaces give supports to the effect of EVA and PEMA as compatibilizers and the effect of electron beam irradiation. POLYM. COMPOS., 2008. © 2008 Society of Plastics Engineers     

Ratio of oxygen and nitrogen Raman cross sections in the ultraviolet

We report measurements of the ratio of oxygen and nitrogen Raman cross sections for excitation wavelengths between 220 and 290 nm. These measurements confirm strong enhancement of the oxygen Raman cross section in this region.     

Highly Efficient and Water‐Insensitive Self‐Healing Elastomer for Wet and Underwater Electronics

Integrating self‐healing capabilities into soft electronic devices increases their durability and long‐term reliability. Although some advances have been made, the use of self‐healing electronics in wet and/or (under)water environments has proven to be quite challenging, and has not yet been fully realized. Herein, a new highly water insensitive self‐healing elastomer with high stretchability and mechanical strength that can reach 1100% and ≈6.5 MPa, respectively, is reported. The elastomer exhibits a high (>80%) self‐healing efficiency (after ≈ 24 h) in high humidity and/or different (under)water conditions without the assistance of an external physical and/or chemical triggers. Soft electronic devices made from this elastomer are shown to be highly robust and able to recover their electrical properties after damages in both ambient and aqueous conditions. Moreover, once operated in extreme wet or underwater conditions (e.g., salty sea water), the self‐healing capability leads to the elimination of significant electrical leakage that would be caused by structural damages. This highly efficient self‐healing elastomer can help extend the use of soft electronics outside of the laboratory and allow a wide variety of wet and submarine applications.     

Training radial basis function networks using biogeography-based optimizer

Training artificial neural networks is considered as one of the most challenging machine learning problems. This is mainly due to the presence of a large number of solutions and changes in the search space for different datasets. Conventional training techniques mostly suffer from local optima stagnation and degraded convergence, which make them impractical for datasets with many features. The literature shows that stochastic population-based optimization techniques suit this problem better and are reliably alternative because of high local optima avoidance and flexibility. For the first time, this work proposes a new learning mechanism for radial basis function networks based on biogeography-based optimizer as one of the most well-regarded optimizers in the literature. To prove the efficacy of the proposed methodology, it is employed to solve 12 well-known datasets and compared to 11 current training algorithms including gradient-based and stochastic approaches. The paper considers changing the number of neurons and investigating the performance of algorithms on radial basis function networks with different number of parameters as well. A statistical test is also conducted to judge about the significance of the results. The results show that the biogeography-based optimizer trainer is able to substantially outperform the current training algorithms on all datasets in terms of classification accuracy, speed of convergence, and entrapment in local optima. In addition, the comparison of trainers on radial basis function networks with different neurons size reveal that the biogeography-based optimizer trainer is able to train radial basis function networks with different number of structural parameters effectively.

     

Early detection of Alzheimer’s disease based on the state-of-the-art deep learning approach: a comprehensive survey

Multimedia Tools and Applications - Alzheimer’s disease (AD) is a form of brain disorder that causes functions’ loss in a person’s daily activity. Due to the tremendous progress...     

Evaluating sustainable energy harvesting systems for human implantable sensors

Achieving most appropriate energy-harvesting technique for human implantable sensors is still challenging for the industry where keen decisions have to be performed. Moreover, the available polymeric-based composite materials are offering plentiful renewable applications that can help sustainable development as being useful for the energy-harvesting systems such as photovoltaic, piezoelectric, thermoelectric devices as well as other energy storage systems. This work presents an expert-based model capable of better evaluating and examining various available renewable energy-harvesting techniques in urban surroundings subject to various technical and economic, often conflicting, criteria. Wide evaluation criteria have been adopted in the proposed model after examining their suitability as well as ensuring the expediency and reliability of the model by worldwide experts’ feedback. The model includes establishing an analytic hierarchy structure with simultaneous 12 conflicting factors to establish a systematic road map for designers to better assess such techniques for human implantable medical sensors. The energy-harvesting techniques considered were limited to Wireless, Thermoelectric, Infrared Radiator, Piezoelectric, Magnetic Induction and Electrostatic Energy Harvesters. Results have demonstrated that the best decision was in favour of wireless-harvesting technology for the medical sensors as it is preferable by most of the considered evaluation criteria in the model.