The manifestations of climate change are increasing with the days: sudden rains and floods, lakes that evaporate, rivers that experience unprecedentedly low water levels, and successive droughts such as the Tigris, Euphrates, Rhine, and Lape rivers. At the same time, energy consumption is increasing, and there is no way to stop the warming of the Earth's atmosphere despite the many conferences and growing interest in environmental problems. An aspect that has not received sufficient attention is the tremendous heat produced by human activities. This work links four elements in the built environment that are known for their high energy consumption (houses, supermarkets, greenhouses, and asphalt roads) according t

Luminescent solar concentrator (LSC) are used to enhance       photoresponsivity of solar cell. The Quantumdots luminescent solar concentrator (QDLSC) consists of CdSe/CdS core/shell nanoparticles embedded in polyacrylamide polymer matrix positioned on the top surface of the silicon solar cell. This procedure improves the conversion efficiency of the bare silicon solar cell. The conversion efficiency of the solar cell has increased from 7.3% to 10.3%.  this improvement is referred to the widening of the response spectral region window  of the a- Si. Solar cell.

In the present work, Response Surface Methodology (RSM) was utilized to optimize process variables and find the best circumstances for indirect electrochemical oxidation of mimicked wastewater to remove phenol contaminants using prepared ternary composite electrode. The electrodeposition process is used for the synthesis of a ternary composite electrode of Mn, Co, and Ni oxides. The selected concentrations of metal salts of these elements were 0.05, 0.1, and 1.5 M, with constant molar ratio, current density, and electrolysis time of 1:1:1, 25 mA/cm2, and 2 h. Interestedly, the gathered Mn-Co-Ni oxides were deposited at both the anode and cathode. X-ray diffraction (XRD) and scanning electron microscopy (SEM) facilitated the qualitative char

A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

Kinetics and mechanism studies of oxidation of some α-amino acids (Proline, Arginine, Alanine) (AA) by N-Bromosuccinimide (NBS) by using conductivity method was carried out. The kinetic study showed that the reaction was first order with respect to NBS and AA. The effect of addition of HClO4 to the reaction was negative on the rate of reaction. The reaction was carried out at different temperatures in which  * * *   , S , G were calculated. The rate of reaction of AA was as follows: Proline > Arginine > Alanine

Abstract: E2F6 is a member of the E2F family of transcription factors involved in regulation of a wide variety of genes through both activation and repression. E2F6 has been reported as overexpressed in breast cancers but whether or not this is important for tumor development is unclear. We first checked E2F6 expression in tumor cDNAs and the protein level in a range of breast cancer cell lines. RNA interference-mediated depletion was then used to assess the importance of E2F6 expression in cell lines with regard to cell cycle profile using fluorescence-activated cell sorting and a cell survival assay using (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The overexpression of E2F6 was confirmed in breast tumor cDNA samp

PV connected systems are worldwide installed because it allows consumer to reduce energy consumption from the electricity grid. This paper presents the results obtained from monitoring a 1.1 kWp. The system was monitored for nine months and all the electricity generated was fed to the fifth floor for physics and renewable energy building   220 V, 50 Hz. Monthly, and daily performance parameters of the PV system are evaluated which include: average generated of system Ah per day, average system efficiency, solar irradiation around these months. The average generated kWh per day was 8 kWh/day, the average solar irradiation per day was 5.6 kWh/m²/day, the average inverter efficiency was 95%, the average modules efficien

This research paper studies the use of an environmentally and not expensive method to degrade Orange G dye (OG) from the aqueous solution, where the extract of ficus leaves has been used to fabricate the green bimetallic iron/copper nanoparticles (G-Fe/Cu-NPs). The fabricated G‑Fe/Cu-NPs were characterized utilizing scanning electron microscopy, BET, atomic force microscopy, energy dispersive spectroscopy, Fourier-transform infrared spectroscopy and zeta potential. The rounded and shaped as like spherical nanoparticles were found for G-Fe/Cu‑NPs with the size ranged 32-59 nm and the surface area was 4.452 m²/g. Then the resultant nanoparticles were utilized as a Fenton-like oxidation catalyst. The degradation efficiency of

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de