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An accurate model is developed for predicting the energy efficiency of a single-slope solar still equipped with thermoelectric modules. Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) enhanced by Particle Swarm Optimization (PSO) are employed. Cu2O nanoparticles are utilized in the solar still basin, and the energy efficiency is modeled as a function of the time, glass temperature, fan power, solar radiation, ambient temperature, water temperature, basin temperature as well as the nanoparticle volume fraction. The experimental data are utilized for training the artificial intelligence methods. The ANN with three hidden neurons and the ANFIS with nine clusters present the best predictions. Applying the PSO profoundly enhances the prediction performance. The comparison between the performances of PSO-based ensemble models reveals superiority of the PSO-ANFIS compared with the PSO-ANN. The R2 values for the PSO-ANFIS model are 0.9884 and 0.9906 for the training and test sets, respectively.

In the present study, a combination of the modified sine and cosine algorithm (MSCA) and teaching–learning-based optimization (TLBO) algorithm is integrated with the neuro-fuzzy system to obtain three hybrid models. The proposed model predicts the effects of design parameters including the bottom galvanized protective edge of the cooking plate, top insulator cap of the cooking plate, position of the cooking plate, time duration of bread cooking and weather conditions on the dependent parameter which is the required temperature of a solar bread cooker equipped with a concentrator. For this purpose, the networks are trained on the basis of the experimentally measured data. The goal is to assess the ability of the hybrid networks for modeling cooking plate required based on the input variables. The quality of the bread produced by the solar cooker is evaluated by proper selection of the design parameters. The results show twelve breads per hour each with 200 g weight of dough can be produced by the cooker for at least six hours in every sunny day in eight months of the year, and also, the best hybrid network predicts the results with a low error which guarantees the performance of the applied hybrid model.

This experimental and theoretical study presents the performance of copper oxide (Cu2O) nanofluid in a single slope solar still fitted with an external thermoelectric condensing channel. Four thermoelectric cooling modules (TEC) are installed around the walls of the external channel in order to make a cool place in the vapor flow, and also the Cu2O–water nanofluid with different volume concentrations is employed. The temperatures of glass cover, basin water, absorber plate as well as distillated water productivity, and daily energy and exergy efficiencies of the modified solar still are presented during July in Razi university of Kermanshah (Iran). Moreover, the cost of distilled water for different cases is calculated. The results disclose that the productivity, energy and exergy efficiencies of solar still equipped with the external thermoelectric condensing channel enhance by about 38.5%, 38.9% and 31.2%, respectively. In this case, by adding 0.08% volume fraction of the Cu2O nanoparticles in basin water, the productivity, energy and exergy efficiencies are enhanced about 82.4%, 81.5% and 92.6%, respectively. The cost analysis designates that in optimum mode, the cost of distillated water per liter is 0.021 $/L/m2 for this modified solar still.

Cisplatin is a broadly prescribed anti-tumor agent for the treatment of diverse cancers. Therapy with cisplatin, however, is associated with various adverse effects including nephrotoxicity and ototoxicity. AMP kinase (AMPK), an evolutionarily conserved enzyme, functions as the fundamental regulator of energy homeostasis. While AMPK activation protects normal tissues against cisplatin-induced toxicities, its impact in cancer is context-dependent and there is no single, uniform role for AMPK. On one hand, some report that AMPK activation augments cisplatin-induced apoptosis in cancer, while on the other hand, few reports indicate that AMPK activation rescues cancer cells from the cytotoxicity induced by cisplatin. Here we review the most salient signaling pathways regulated by AMPK with an emphasis on their relation to cisplatin toxicity and yet discuss context-dependent functions of AMPK in cancer.

This experimental study elucidates the performance of copper oxide (Cu2O) nanofluid in a single slope solar still integrated with external thermoelectric glass cover cooling channel. Four thermoelectric cooling modules (TEC) are mounted on the walls of the galvanized external channel in order to create the cool air to flow over the glass cover. Moreover, copper oxide nanoparticles with different volume concentrations are utilized. The results including difference in temperature between the water basin and glass cover, productivity of fresh water, energy efficiency and exergy efficiency of modified solar still are compared with those of a conventional solar still. The results reveal that the productivity, energy efficiency and exergy efficiency of the modified solar still are enhanced in comparison with the conventional solar still. Additionally, with adding the copper oxide nanoparticles to the basin brackish water, the productivity, energy and exergy efficiencies increase significantly with respect to the modified solar still without using the nanofluid. By adding 0.08% volume fraction of the Cu2O nanoparticles to the basin water of modified solar still with thermoelectric cooling channel, the maximum enhancement values for productivity, energy and exergy efficiencies are about 81%, 80.6% and 112.5%, respectively. In addition, the cost analysis shows that the optimum cost per liter and payback period time in the modified solar still are 0.0218 ($/L/m2) and 13.8 months, respectively.

Receptor for advanced glycation end-products (RAGE) is involved in the pathogenesis of diabetic nephropathy. FPS-ZM1, a selective RAGE inhibitor, in combination with valsartan were investigated for their protective potentials on the renal markers of tubular injury in streptozotocin-induced diabetic rats. Rats were assigned into groups of receiving FPS-ZM1 (1 mg/kg/day), valsartan (100 mg/kg/day), and FPS-ZM1 plus valsartan (1 mg/kg/day and 100 mg/kg/day, respectively) for one month. Kidney histology, renal inflammation and oxidative stress, and renal and urinary markers of tubular injury were investigated. FPS-ZM1 and valsartan in combination more significantly attenuated renal expressions of tumor necrosis factor-alpha and interleukin-6 genes and reduced urinary levels of interleukin-6. Moreover, the combination elevated renal NAD+/NADH ratios and Sirt1 activities, and mitigated nuclear acetylated NF-κB p65 levels. In addition to alleviating indices of oxidative stress i.e. malondialdehyde, superoxide dismutase and glutathione peroxidase, the combination of FPS-ZM1 and valsartan more effectively upregulated the renal levels of master antioxidant proteins Nrf2, heme oxygenase-1, and NAD(P)H:quinone oxidoreductase-1. Additionally, this dual therapy ameliorated more efficiently the indices of renal tubular injuries as indicated by decreased renal kidney injury molecule-1 levels as well as reduced urinary levels of cystatin C, retinol binding protein, and beta-2-microglobulin. While FPS-ZM1 alone had no appreciable effects on the renal fibrosis, the combination treatment ameliorated fibrosis better than valsartan in the kidneys. Collectively, these findings underline the extra benefits of FPS-ZM1 and valsartan dual administrations in obviating the renal tubular cell injury in streptozotocin-induced diabetic rats partly by suppressing renal inflammation and oxidative stress.

Post-transplant ischemic acute kidney injury (AKI), secondary to ischemia reperfusion injury (IRI), is a major problem influencing on the short and long term graft and patient survival. Many molecular and cellular modifications are observed during IRI, for example, tissue damage result production of reactive oxygen species (ROS), cytokines, chemokines, and leukocytes recruitment which are activated by NF-κB (nuclear factor kappa B) signaling pathway. Therefore, inhibiting these processes can significantly protect renal parenchyma from tissue damage. Klotho protein, mainly produced in distal convoluted tubules (DCT), is an anti-senescence protein. There is increasing evidence to confirm a relationship between Klotho levels and renal allograft function. Many studies have also demonstrated that expression of the Klotho gene would be down regulated with IRI, so it will be used as an early biomarker for acute kidney injury after renal transplantation. Other studies suggest that Klotho may have a renoprotective effect for attenuating of kidney injury. In this review, we will discuss pathophysiology of IRI-induced acute kidney injury and its relation with klotho level in renal transplantation procedure.

Some graphene-based adsorbents such as mesoporous graphene oxide/TiO 2 nanocomposite, thermally treated graphene nanosheets, holey graphene frameworks and 3-D graphene-based porous adsorbent have recently been introduced as promising adsorbents for post-combustion CO 2 capture while, their CO 2 adsorption kinetics and mechanisms have not sufficiently been reported by the scholars. To begin, in this study, CO 2 capture kinetics of these adsorbents are investigated by different adsorption kinetic models including pseudo-first order model, pseudo-second order model, Avrami model, and the fractal-like exponential kinetic model. Subsequently, the Eyring and Arrhenius equations are used to determine the activation parameters related to the CO 2 adsorption on these adsorbents. Furthermore, a mechanism is proposed to describe the negative activation energy assessed for CO 2 adsorption on the studied adsorbents. Eventually, the rate-limiting kinetic models including interparticle diffusion model, intraparticle diffusion model and Boyd’s film diffusion model are applied to determine CO 2 capture mechanisms on the mentioned graphene-based adsorbents.

In the present study, the modified evacuated tube solar collector (METSC) with a bypass pipe utilizing copper oxide/distilled water (Cu2O/DW) nanofluid is experimented. Then, the performance of METSC was predicted through Artificial Neural Networks (ANNs) techniques. The input variables were different volumes of the storage tank from 5 to 8 l, various diameters of the bypass pipe from 6 to 10 mm, and various volumetric concentration of the nanofluid from 0 to 0.04. Also, the output variables were the temperature difference of fluid in 1-h period and the energetic efficiency of METSC. The results demonstrated that the METSC performance was mostly impacted by the tank volume alteration. Moreover, the optimum bypass tube diameter value was obtained, and it was denoted that using the Cu2O/DW nanofluid enhances the daily energy efficiency of METSC up to 4%. Furthermore, it was shown that both MLP and RBF techniques are two reliable algorithms to predict the thermal characteristics of an METSC. The maximum amounts of mean relative percentage error for MLP and RBF algorithms were reported as 0.576 and 0.907, respectively. Hence, two mathematical models were reported for formulating the output variables in terms of the input variables using the MLP technique.

The present research aims to investigate the concept of J-shaped blade in a straight–bladed Darrieus type VAWT in terms of output torque and power by employing high-fidelity 3D numerical simulations. Theoretically, since the J-shaped blades can benefit from the lift and drag forces simultaneously, this combined forces help the turbine possess faster operation at low wind speeds, thereby resulting in the termination of self-starting problem and improving power coefficients, especially at low and moderate tip speed ratios. In this study, NACA0015 is served as the base airfoil and has been modified to generate the desired J-shape profile. The attained results indicate improvements on torque and power coefficients, more specifically in the first half of revolution namely 0°

In this research, the proper models are developed to simultaneously predict the energy efficiency, exergy efficiency, and water productivity of a single-slope solar still via an Artificial Neural Network (ANN) and a neural network optimized by Imperialist Competition Algorithm (ICA). The outputs are modeled as a function of the time, ambient temperature, solar radiation, glass temperature, basin temperature, and water temperature. The empirical data are utilized to train both the ANN and ICA-enhanced ANN. The neural network with five hidden neurons demonstrates the best performance. The results reveal that implementing the ICA significantly improves the performance of the ANN in predicting all the three outputs. Thereby, as a result of employing the ICA in the ANN, Mean Absolute Error (MAE) experiences 54.30%, 40.11%, and 53.35% reductions in prediction of the water productivity, energy efficiency, and exergy efficiency, respectively, based on the testing date set. Moreover, based on the test data, the ANN-ICA predicts the water productivity, energy efficiency, and exergy efficiency with root mean square error (RMSE) values of about 15.77, 1.37, and 0.29, respectively. In addition, the developed mathematical correlations are finally presented as a function of the inputs.

In this study, a thermodynamic model is developed for a natural gas pressure reduction station, which uses solar energy as an auxiliary energy source for preheating the natural gas. To increase the duration of solar energy usage per day and the consequent decrease in the fuel consumption of the heater, a novel design is presented in which preheating the gas to lower temperatures becomes possible through the use of multi-stage preheating and pressure reduction. Through this novel design, it becomes possible to utilize a single heater to preheat all stages, which reduces the costs dramatically. To investigate the effectiveness of the proposed design in different climate conditions, a comprehensive economic analysis is conducted based on fuel saving and carbon dioxide emission reduction. The results show that the return of capital is within 1–10 years considering different parameters, including: 1- daily time duration of solar energy usage by the station before implementation of the new design, 2- additional daily time duration of solar energy usage after implementation of the new design, and 3- number of preheating and pressure reduction stages. Finally, the effects of different parameters on the return of capital are discussed.

The experimental investigations are carried out on a circular nanofluid jet impingement for cooling an aluminum disk with constant heat flux. The study is performed to understand the effects of different factors such as Reynolds number and nanoparticle concentration on the fluid flow and characteristics of heat transfer. The target surface has a circular shape and is kept at constant heat flux with the value of 1414.71 W/m2. The copper oxide-nanoparticle concentrations are changed from 0.03 to 0.07 wt%. The experimental results show that the Cu2O nanofluid increases the heat transfer efficiency of the impinging jet cooling system. Compared to the case of using the base fluid, the nanofluid increases the convective heat transfer by 45% at 0.07 wt% concentration at Reynolds number of 7330. The center of the target surface, i.e. the stagnation zone, has the highest turbulence intensity because of impinging of the fluid flow on the surface center, while the endpoint of the target surface has the minimum turbulence intensity. Indeed, the turbulence intensity decreases along the radial direction, which augments the effect of employing the nanofluid because the heat transfer due to the turbulence diminishes and merit of using the nanofluid enhances.

In this paper, the improvement of the thermal characteristics of an evacuated tube solar collector for different volumetric flow rates of the fluid (10, 30 and 50 L/h) was experimentally enhanced by using copper oxide/water (Cu2O/W) nanofluid, and a parabolic concentrator. Moreover, the effect of different volume fractions of the utilized nanofluid on the energy and exergy efficiencies, convective heat transfer coefficient, Nusselt number, and useful heat gain of the solar collector was experimented. Finally, the accuracy of the experimentations was verified via Artificial Neural Networks (ANNs). The Multi-layer Perceptron (MLP) and Radial Basis Function (RBF) models were investigated to predict the performance of the constructed tubular collector, and their results were compared to one another. The results demonstrated that the MLP method can make a more accurate prediction of the collector performance than the RBF one. The highest error rate for the MLP model was less than that of the RBF model. It was also concluded that the increase in both the flow rate and concentration of the nanofluid leads to an increase in the thermal performance of the solar collector.

One of the important factors in the occurrence of acute kidney injury (AKI) among renal transplant patients (RTPs) is ischemia reperfusion injury (IRI). The current study aimed at determining the anti-inflammatory and anti-oxidative effects of melatonin on the complications of IRI and the level of Klotho expression in these patients.A total of 40 renal transplant candidates were randomly assigned into placebo or melatonin group receiving the same dose of 3 mg/day. In order to measure serum melatonin levels, inflammatory and oxidative stress factors, renal function biomarkers, and Klotho gene/protein expression, venous blood samples were taken from patients over two different time points, i e, 24 h before the transplantation and at discharge from hospital.Melatonin was associated with improvement in renal transplantation, since the serum level of neutrophil gelatinase-associated lipocalin, as a renal functional marker, significantly decreased (P .001). The effect of melatonin as a suppressor of inflammation and oxidative stress was also evident in the melatonin group due to a significant reduction in the serum levels of MDA, CP, 8-OHdG, and TNF-α markers (P .001).Reduction in serum levels of renal function and oxidative stress/inflammatory markers in the melatonin group indicates that melatonin can inhibit IRI outcomes in RTPs through its anti-oxidant and anti-inflammatory properties. However, these properties do not appear as a result of influence on the level of Klotho gene/protein expression.

The possibility of applying headspace microextraction into a single drop for the determination of amines in aqueous solutions is demonstrated. A 1mul drop of benzyl alcohol containing 2-butanone as an internal standard was suspended from the tip of a micro syringe needle over the headspace of stirred sample solutions for extraction. The drop was then injected directly into a GC. The total chromatographic determination was less than 10min. Optimization of experimental conditions (sampling time, sampling temperature, stirring rate, ionic strength of the solution, concentration of reagents, time of extraction and organic drop volume) with respect to the extraction efficiency were investigated and the linear range and the precision were also examined. Calibration curves yielded good linearity and concentrations down to 2.5ngml(-1) were detectable with R.S.D. values ranging from 6.0 to 12.0%. Finally, the method was successfully applied to the extraction and determination of amines in tap and river water samples. This system represents an inexpensive, fast, simple and precise sample cleanup and preconcentration method for the determination of volatile organic compounds at trace levels.