The cost of microalgae harvesting constitutes a heavy burden on the commercialization of biofuel production. The present study addressed this problem through economic and parametric comparison of electrochemical harvesting using a sacrificial electrode (aluminum) and a nonsacrificial electrode (graphite). The harvesting efficiency, power consumption, and operation cost were collected as objective variables as a function of applied current and initial pH of the solution. The results indicated that high harvesting efficiency obtained by using aluminum anode is achieved in short electrolysis time. That harvesting efficiency can be enhanced by increasing the applied current or the electrolysis time for both electrode materials, where 98

A Mini-TEA CO2 laser system was designed and operated to obtain a pulse at 10.6 μm. Output energy of 30 mJ, with preionization pins, and pulse duration of 100ns were obtained. While an output energy of 6mJ and pulse duration of 100 ns in absence of pre-ionization were obtained. The system was operated with Ernest profile main-discharge electrodes. Dependencies of supply voltage and output laser energy on the pressure inside laser cavity were investigated as well as dependencies of supply voltage and output energy on the main capacitor(8CO2 : 8N2 : 82He :2CO). Efficiency of was calculated to be 4.4%.

In this work, (ZnO)1-x(MnO2)x compounds were synthesized with composition (x=0, 0.1, 0.2, 0.3, 0.4, and 0.5) of manganese oxide content using solid state reaction. Thin films were prepared from these compounds on glass substrates at room temperature using pulsed laser deposition method. The structure of the prepared compounds and thin films were analyzed using x-ray diffraction while the optical properties was measured using UV-visible spectrophotometry. It was found that the synthesized composites declared many peaks in the diffraction pattern which indicate polycrystalline structure with hexagonal wurtzite hexagonal structure of ZnO, and MnO2 and Mn2O3 secondary phases. A narrowing in the optical e

The friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel pr

This Study aimed To know The relation between Types of blood and health problems which human Suffered from , and the effect of food intake on health.
Samples of study contained 269 person aged between 30 – 70 years which choiced randomly for sex , we are take all in formation about samples of study by form paper contian sex , age, type of blood , weight (kg) , height (cm) , smoking or.not , sporting or not, problems in digestive tract , sensitivity for foods , heart problems , ratio of cholesterol in blood , Sinusitis , Asthma , diabetic meliuts , arritable bowel syndrome , diaherra , problems in kidney and urination , hypertension , anemia , alternation in liver function , arthritis with form record in daily food intake and its ade

This research is a study of the difficulties of learning the Arabic language that faces Arabic language learners in the Kurdistan Region, by revealing its types and forms, which can be classified into two categories:

The first type has difficulties related to the educational system, the source of which is the Arabic language itself, the Arabic teacher or the learner studying the Arabic language or the educational curriculum, i.e. educational materials, or the educational process, i.e. the method used in teaching.

The second type: general difficulties related to the political aspect, the source of which is the policy of the Kurdistan Regional Government in marginalizing the Arabic language and replacing the forefront of th

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi