DVCC-Based Non-linear Feedback Neural Circuit for?Solving System of Linear Equations

A neural circuit to solve a system of simultaneous linear equations is presented. The circuit employs non-linear feedback to achieve a transcendental energy function that ensures fast convergence to the exact solution while enjoying reduction in hardware complexity over existing schemes. A new building block for analog signal processing, the digitally controlled differential voltage current conveyor (DC-DVCC) is introduced and is utilized for the non-linear synaptic interconnections between neurons. The proof of the energy function has been given and it is shown that the gradient network converges exactly to the solution of the system of equations. PSPICE simulation results are presented for linear systems of equations of various sizes and are found to be in close agreement with the algebraic solution. The use of CMOS DC-DVCCs and operational amplifiers facilitates monolithic integration.     

Stochastic multiscale fracture analysis of three-dimensional functionally graded composites

A new moment-modified polynomial dimensional decomposition (PDD) method is presented for stochastic multiscale fracture analysis of three-dimensional, particle-matrix, functionally graded materials (FGMs) subject to arbitrary boundary conditions. The method involves Fourier-polynomial expansions of component functions by orthonormal polynomial bases, an additive control variate in conjunction with Monte Carlo simulation for calculating the expansion coefficients, and a moment-modified random output to account for the effects of particle locations and geometry. A numerical verification conducted on a two-dimensional FGM reveals that the new method, notably the univariate PDD method, produces the same crude Monte Carlo results with a five-fold reduction in the computational effort. The numerical results from a three-dimensional, edge-cracked, FGM specimen under a mixed-mode deformation demonstrate that the statistical moments or probability distributions of crack-driving forces and the conditional probability of fracture initiation can be efficiently generated by the univariate PDD method. There exist significant variations in the probabilistic characteristics of the stress-intensity factors and fracture-initiation probability along the crack front. Furthermore, the results are insensitive to the subdomain size from concurrent multiscale analysis, which, if selected judiciously, leads to computationally efficient estimates of the probabilistic solutions.     

Effect of phosphoric acid on the performance of low antimony grid of Pb‐acid cell under constant current charging and discharging

Effect of phosphoric acid on the performance of Pb‐1.7%Sb grid of lead‐acid cell is studied in 5 M H₂SO₄ by cyclic galvanostatic polarization and impedance spectroscopy. An increase in capacitance to a maximum is recorded during the initial stages of the electro‐reduction of PbO₂ into Pb(II) compounds and attributed to concurrent compositional and dimensional changes. These changes include removal of O₂ bubbles, insertion of large amounts of H₂SO₄ and H₂O. Efficiency of PbO₂ formation decreases, while its rate of self‐discharge increases with increasing the charging current and in the presence of H₃PO₄. The charge capacity increases with increasing the discharging current due to the decrease in the self‐discharge. The charge capacity is lower in the presence of H₃PO₄. On increasing the cycle number, the corrodibility of the grid increases, because more layers of the surface Pb are involved in the self‐discharge. H₃PO₄ significantly retards the effect of cycle number.     

Accuracy of Numerical Methods in Determination of Residual Stresses Due to Cold Expansion in Metallic Materials

Today more than ever, it was tried to reach the optimum usage of materials by applying various methods of manufacturing processes. Increasing the fatigue life of components is one of important aims. All parts of a machine must be connected together for incoming to service. Nonpermanent connections like bolt and nut joints must have hole on both components. Fatigue life was increased if these holes were reinforced by various methods. One of the ways is producing compressive residual stress in near fields of hole by cold expansion (CE) method. In this study the CE process was applied to plate was made from elastic–perfectly plastic material. Residual stresses distributions were obtained by analytical and numerical methods (using finite elements analysis). Results of these methods were compared together for determination the accuracy of numerical methods. In the next step, residual stress distribution due to the CE in real material (aluminum) was determined numerically. Three numerical methods were used: really simulation method (3D plate with punch), 2D and 3D model with internal pressure (using try and error, the amount of pressure that was needed to introduce the same CE ratio was determined) and finally, 2D and 3D model with radial displacement in internal surface of the hole. It was determined that the first and second methods have good agreement with experimental results so can be used for simulation of the CE process.     

Optimization of biohydrogen production by Clostridium butyricum EB6 from palm oil mill effluent using response surface methodology

Clostridium butyricum EB6 successfully produced hydrogen gas from palm oil mill effluent (POME). In this study, central composite design and response surface methodology were applied to determine the optimum conditions for hydrogen production (P_c) and maximum hydrogen production rate (R_max) from POME. Experimental results showed that the pH, temperature and chemical oxygen demand (COD) of POME affected both the hydrogen production and production rate, both individually and interactively. The optimum conditions for hydrogen production (P_c) were pH 5.69, 36 °C, and 92 g COD/l; with an estimated P_c value of 306 ml H₂/g carbohydrate. The optimum conditions for maximum hydrogen production rate (R_max) were pH 6.52, 41 °C and 60 g COD/l; with an estimated R_max value of 914 ml H₂/h. An overlay study was performed to obtain an overall model optimization. The optimized conditions for the overall model were pH 6.05, 36 °C and 94 g COD/l. The hydrogen content in the biogas produced ranged from 60% to 75%.     

Integration of GIS and multicriteria decision analysis for urban aquaculture development in Bangladesh

Site selection is a key factor in any aquaculture operation, affecting both success and sustainability as well as solving land or water use conflicts. This study was conducted to identify suitable sites for carp farming development in urban water bodies (UWBs) of Chittagong, Bangladesh using Geographical Information Systems (GIS) based MultiCriteria Evaluation (MCE) of water, soil and infrastructure database. ASTER imagery and 14 thematic layers were analyzed with ENVI and GIS capabilities, and developed a series of GIS models to identify and prioritize the appropriate UWBs for carp farming. The study identified 487 UWBs occupying 362 ha and revealed 280 ha (77%) is the most suitable, 36 ha (10%) is moderately suitable and 46 ha (13%) is not suitable which was consistent with field verification. The results are encouraging for extension of carp culture and diversify the economic activities of the urban dwellers.     

The structure and photocatalytic performances of mechanically synthesized poly(3′,4′‐ethylenedioxy‐2,2′:5′,2″‐Terthiophene)/Zno composites

Poly(3′,4′‐ethylenedioxy‐2,2′:5′,2″‐terthiophene)/ZnO(poly(TET)/ZnO) composites with the ratio of poly(TET) and nano‐ZnO from 3:1 to 1:3 were synthesized by hand grinding and ball milling methods, respectively. The photocatalytic activities of the composites were examined through the degradation processes of methylene blue (MB) solution under UV light irradiation, and the possible mechanism for the photocatalytic activity enhancement by synergetic effects between nano‐ZnO and poly(TET) was proposed. The results showed that the strong interactions between the poly(TET) and nano‐ZnO occurred in the case of ball milling method. The results also proved that the crystallinity of ZnO was not disturbed in both of methods, and the nano‐ZnO was uniformly distributed in polymer matrix in the case of ball milling method. The comparative studies showed that the addition of the nano‐ZnO could enhance the photocatalytic activities of the composites. The highest degradation efficiency (100%) at 3 h under UV light irradiation occurred in the case of poly(TET)/ZnO(1:1) synthesized by ball milling method. Furthermore, the nanocompsosite displayed higher photocatalytic activity than nano‐ZnO, which was due to the holes (h⁺) transferring from the valence band of ZnO to the polymer backbone and the adsorption of MB molecules in polymer matrix via π–π conjugation between MB and aromatic regions of the poly(TET). POLYM. COMPOS., 36:1597–1605, 2015. © 2014 Society of Plastics Engineers     

Effect of processing on the composition and oxidative stability of coconut oil

The effect of various processing procedures on the composition and oxidative stability of coconut oil has been studied. The crude oil is relatively stable but major reductions in oxidative stability occur during the bleaching of oil degummed with phosphoric acid; during alkali refining; during the deodorization of oil degummed with citric acid and bleached; and during the deodorization of oil processed with a combined phosphoric acid degumming and bleaching operation. The reasons for the loss of oxidative stability during processing are discussed with reference to changes in the composition of the oil. Residual traces of citric acid or phosphoric acid play an important role in stabilizing processed oils. The tocopherol content is also important, although no additional stabilization of the oil occurs on adding levels of tocopherol above those present naturally in the crude oil. A combined phosphoric acid degumming and bleaching process leads to smaller losses of tocopherols than sequential treatments.     

Molecular Pathogenesis of Glioblastoma in Adults and Future Perspectives: A Systematic Review

Glioblastoma (GBM) is the most common and malignant tumour of the central nervous system. Recent appreciation of the heterogeneity amongst these tumours not only changed the WHO classification approach, but also created the need for developing novel and personalised therapies. This systematic review aims to highlight recent advancements in understanding the molecular pathogenesis of the GBM and discuss related novel treatment targets. A systematic search of the literature in the PubMed library was performed following the PRISMA guidelines for molecular pathogenesis and therapeutic advances. Original and meta-analyses studies from the last ten years were reviewed using pre-determined search terms. The results included articles relevant to GBM development focusing on the aberrancy in cell signaling pathways and intracellular events. Theragnostic targets and vaccination to treat GBM were also explored. The molecular pathophysiology of GBM is complex. Our systematic review suggests targeting therapy at the stemness, p53 mediated pathways and immune modulation. Exciting novel immune therapy involving dendritic cell vaccines, B-cell vaccines and viral vectors may be the future of treating GBM.     

Nanomedicine-Based Delivery Strategies for Breast Cancer Treatment and Management

Breast cancer is one of the most common types of cancer among women globally. It is caused by mutations in the estrogen/progesterone receptors and conventional treatment methods are commonly utilized. About 70–80 percent of individuals with the early-stage non-metastatic disease may be cured. Conventional treatment is far less than the optimal ratio, as demonstrated through the high mortality rate of women with this cancer. However, conventional treatment methods like surgery, radiotherapy, and chemotherapy are not as effective as expected and lead to concerns about low bioavailability, low cellular uptake, emerging resistance, and adverse toxicities. A nanomedicine-based approach is a promising alternative for breast cancer treatment. The present era is witnessing rapid advancements in nanomedicine as a platform for investigating novel therapeutic applications and modern intelligent healthcare management strategies. This paper focuses on nanomedicine-based therapeutic interventions that are becoming more widely accepted for improving treatment effectiveness and reducing undesired side effects in breast cancer patients. By evaluating the state-of-the-art tools and taking the challenges involved into consideration, various aspects of the proposed nano-enabled therapeutic approaches have been discussed in this review.