Oestrogenic Regulation of Mitochondrial Dynamics

Biological sex influences disease development and progression. The steroid hormone 17β-oestradiol (E2), along with its receptors, is expected to play a major role in the manifestation of sex differences. E2 exerts pleiotropic effects in a system-specific manner. Mitochondria are one of the central targets of E2, and their biogenesis and respiration are known to be modulated by E2. More recently, it has become apparent that E2 also regulates mitochondrial fusion–fission dynamics, thereby affecting cellular metabolism. The aim of this article is to discuss the regulatory pathways by which E2 orchestrates the activity of several components of mitochondrial dynamics in the cardiovascular and nervous systems in health and disease. We conclude that E2 regulates mitochondrial dynamics to maintain the mitochondrial network promoting mitochondrial fusion and attenuating mitochondrial fission in both the cardiovascular and nervous systems.     

智能水矿化度及离子组成对碳酸盐岩储集层矿物结垢的影响

利用碳酸盐岩岩心开展岩心驱替实验,研究了在智能水驱过程中由于矿物结垢沉淀而引起的储集层伤害风险以及注入水矿化度和离子组成对矿物结垢沉淀的影响.设计了一种新的室内岩心驱替实验程序以模拟注入水和地层水在储集层中的流动条件,考虑了注入水和地层水的原位接触时间对矿物结垢沉淀的影响.在确定了最佳接触时间之后,通过改变注入海水的矿...     

Game theoretic spectrum allocation for competing wireless access technologies to maximize the social welfare

Wireless Networks - Due to its scarce nature, the limited frequency spectrum must be effectively allocated to competing wireless access technologies. A promising approach is to consider frequency...     

Evaluating modes I,II, and mixed mode I-II fracture toughnesses of crystalline rocks using discrete element method

Several cracked chevron-notched Brazilian disk (CCNBD) and hollow center cracked disk (HCCD) samples of crystalline building stones naming Maroon, Baghat, and Neiriz in Iran, bearing the same calcite mineralogy and different grain size distributions were numerically modeled using three-dimensional particle flow code, with the respective microscopic mechanical properties measured through calibration technique. The simulation of CCNBD and HCCD samples highlights higher toughness compared to laboratory measurements. The values regarding HCCD samples are in a better agreement with experimental results than those regarding the CCNBD samples. The principal objective was to evaluate the reliability of numerical simulations in estimating fracture toughness and to recognize the mechanism and the mode of failure, of which laboratory tests are incapable. At microscales, failures occurring due to tensile or shear loadings may not be subsumed within any category as such at macroscales with failure modes I and II. Experimental and numerical results show that the K_IC values determined from both CCNBD and HCCD samples have a negative correlation with the grain size distributions of the marbles. However, no specific trend as such was identified for K_IIC.     

A Hybrid GDM-SERVQUAL-QFD Approach for Service Quality Assessment in Hospitals

Quality is one of the most critical factors in health systems. To improve service quality in hospitals, we propose a hybrid approach incorporating Group decision-making (GDM), Service Quality measurement (SERVQUAL), and Quality function deployment (QFD). QFD is used to translate patient needs into quality characteristics (derived from SERVQUAL), while taking into account interrelationships between design requirements and quality characteristics. One of the most important steps in the QFD process is to prioritize quality characteristics from the patients’ viewpoint, which is inherently affected by two types of uncertainties: human mental perception and patient heterogeneity. In this research, a novel two-stage GDM approach is employed to cope with these uncertainties in an integrated manner. Furthermore, the proposed methodology is applied in a public hospital to effectively enhance quality characteristics, which will be considered in the QFD. Accordingly, the proposed methodology provides a framework for engineering professionals and managers in hospitals to assess and manage quality characteristics.     

Time-dependent behaviour of hardened cement paste under isotropic loading

The experimental results of isotropic compression tests performed at 20 °C and 90 °C on a class G hardened cement paste hydrated at 90 °C (Ghabezloo et al., 2008, Cem. Conc. Res. 38, 1424–1437) have been revisited considering time-dependent response. Within the frame of a viscoplastic model, the non-linear responses of the volumetric strains as observed in drained and undrained tests and of the pore pressure in undrained tests are analysed. The calibration of model parameters based on experimental data allows to study the effect of the test temperature on the viscous response of hardened cement paste showing that the creep is more pronounced for a higher test temperature. The effect of the hydration temperature on the time dependent behaviour is also studied by evaluating the model parameters for a cement paste hydrated at 60 °C. The time-dependent deformations are more pronounced for hydration at a higher temperature.     

Optimization of biological synthesis of silver nanoparticles using Lactobacillus casei subsp. casei

BACKGROUND: The objectives of this study were optimization of silver nanoparticle synthesis using biotransformations by Lactobacillus casei subsp. casei, and studying the location of nanoparticles synthesis in this microorganism. RESULTS: The presence of AgNO₃ (0.1 mmol L^?1) in the culture as the enzyme inducer, and glucose (56 mmol L^?1) as the electron donor in the reaction mixture had positive effects on nanoparticle production. By gradually increasing the concentration of AgNO₃ (as the substrate) to 6 mmol L^?1, nanoparticle production was increased. By increasing biomass, nanoparticles production was also increased. Biosynthesized silver nanoparticles were almost spherical, single (25–50 nm) or in aggregates (100 nm), attached to the surface of biomass or were inside and outside of the cells. CONCLUSION: The present study demonstrated the bioreductive synthesis of silver nanoparticles using L. casei subsp. casei at room temperature. In this research, and due to experience in optimization of biotransformation reactions, the reaction conditions were successfully optimized to increase the yield of nanoparticles production and productivity of this biosynthetic approach. Copyright © 2012 Society of Chemical Industry     

Fabrication and modification of acrylonitrile–butadiene–styrene‐based heterogeneous ion‐exchange membranes by plasma treatment: Investigation of the nanolayer deposition rate and temperature effects

Our target in this study was the preparation of electrodialysis ion‐exchange membranes with appropriate properties for applications in water recovery and treatment. Composite mixed‐matrix, anion‐exchange membranes were prepared by a solution casting technique with acrylonitrile–butadiene–styrene as a base binder, resin powder as a functional group agent, activated carbon as an adsorptive filler, and an Ag nanolayer as a surface modifier. The Ag nanolayer was used with a magnetron sputtering method. The effect of the nanolayer deposition rate (R_q) and substrate and annealing temperatures on the physicochemical characteristics of the membranes were studied. The X‐ray diffraction results show that average grain size of the nanolayer and membrane crystallinity were improved with increasing R_q. The atomic force microscopy and scanning electron microscopy results show that the membrane roughness was enhanced with increasing R_q. The height distribution results also show the best height distribution for the modified membrane at low R_q. The selectivity and flux decreased with increasing nanolayer R_q in the membranes. The selectivity was also decreased initially with increases in the substrate and annealing temperatures from 300 to 325 K in the membranes and then showed an increasing trend. An opposite trend was found for flux with variations in the temperature. The modified membrane containing a 20‐nm Ag nanolayer at low R_q showed better performance compared to the other modified membranes and the pristine one. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2014 , 131, 40025.     

Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network

A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000 mg/L), various organic loading rates (OLRs) (0.281, 0.563, 1.124, 2.248, and 3.372 kg COD/(m³ day)) and cyclic time (12, 24, and 48 h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O&G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44 kg COD/(m³ day), TDS of 78,000 mg/L and reaction time (RT) of 40 h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100 mg/L and met the discharge limits.     

Assessment quality of a nonuniform suspended sediment transport model under unsteady flow condition (case study: Aras River)

This study presents a one‐dimensional, fully coupled numerical model for nonequilibrium suspended sediment transport that can be applied to channels and alluvial rivers. The accuracy of calculations was enhanced using a nonuniform size distribution, and evaluating probability of hiding and exposure effect of particles. This model is also capable of calculating the flocculation and temperature effect on sediment transport. In addition, the BOD and its influence on suspended sediment transport have been discussed. The study was conducted on the Aras River, Iran's third major river with a relatively high sediment concentration. To verify the model, water depth and sediment concentration of measured field data are compared with simulated data. Comparisons show a regression coefficient of more than 95% and mean computational error is less than 5%. The agreement of the data shows that the model is capable of predicting flow and suspended sediment transport with a correlation coefficient higher than 98%.