The presence of heavy metals in the environment is major concern due to their toxicity. In the present study a strong acid cation exchange resin, Amberlite IR 120 was used for the removal of lead, zinc and copper from simulated wastewater. The optimum conditions were determined in a batch system of concentration 100 mg/L, pH range between 1 and 8, contact time between 5 and 120 minutes, and amount of adsorbent was from 0.05 to 0.45 g/100 ml. A constant stirring speed, 180 rpm, was chosen during all of the experiments. The optimum conditions were found to be pH of 4 for copper and lead and pH 6 for zinc, contact time of 60 min and 0.35 g of adsorbent. Three different temperatures (25, 40 and 60°C) were selected to investigate the effect

The finite element method has been used in this paper to investigate the behavior of precast reinforced concrete dapped-ends beams (DEBs) numerically. A parametric investigation was performed on an experimental specimen tested by a previous researcher to show the effect of numerous parameters on the strength and behavior of RC dapped-end beams. Reinforcement details and steel arrangement, the influence of concrete compressive strength, the effect of inclined load, and the effect of support settlement on the strength of dapped-ends beams are examples of such parameters. The results revealed that the dapped-end reinforcement arrangement greatly affects the behavior of dapped end beam. The failure load decreases by 25% when

Common walnut (Juglans regia L.) has a long cultivation history, given its highly valuable wood and rich nutritious nuts. The Iranian Plateau has been considered as one of the last glaciation refugia and a centre of origin and domestication for the common walnut. However, a prerequisite to conserve or utilize the genetic resources of J. regia in the plateau is a comprehensive evaluation of the genetic diversity that is conspicuously lacking. In this regard, we used 31 polymorphic simple sequence repeat (SSR) markers to delineate the genetic variation and population stru

  Anthropogenic activities cause soil pollution with different serious pollutants, such as polycyclic aromatic hydrocarbon (PAHs) compounds. This study assessed the contamination of PAHs in soil samples collected from 30 sites divided into eight groups (residential areas, oil areas, agricultural areas, roads, petrol stations, power plants, public parks and electrical generators) in Basrah city-Iraq during 2019-2020. The soil characteristics including (moisture, pH, EC and TOC) were measured. Results showed the following ranges (soil moisture (0.03-0.18%),pH (6.90-8.16), EC (2.48-104.80) mS/cm and TOC (9.90-20.50%)). Gas Chromatography (GC) was used to measure PAHs in extracted soil samples. The total PAH range (499.96 - 5864.86) ng/g dr

Foreign direct investment (FDI) is one of the most practical types of foreign investment. FDI contributes to job creation, foreign exchange earnings and national income escalation, improving semi-skill and skilled labor. Based on our knowledge, this paper is the first study attempting to investigate the effect of political stability on the FDI in Turkey using an econometric approach. Achieving this objective, a co-integration analysis was conducted between the FDI and its determinants in the short-run and long-run including “macroeconomic indicators” and “Political Stability (PS)” in Turkey. Using annual data from 1974 to 2017 via Auto-Regressive Distributed Lag (ARDL) model. The results confirm the positive correlation betwe

The removal of cadmium ions from simulated groundwater by zeolite permeable reactive barrier was investigated. Batch tests have been performed to characterize the equilibrium sorption properties of the zeolite in cadmium-containing aqueous solutions. Many operating parameters such as contact time, initial pH of solution, initial concentration, resin dosage and agitation speed were investigated. The best values of these parameters that will achieved removal efficiency of cadmium (=99.5%) were 60 min, 6.5, 50 mg/L, 0.25 g/100 ml and 270 rpm respectively. A 1D explicit finite difference model has been developed to describe pollutant transport within a groundwater taking the pollutant sorption on the permeable reactive barrier (PRB), which i

The research aims to use a new technology for industrial water concentrating that contains poisonous metals and recovery quantities from pure water. Therefore, the technology investigated is the forward osmosis process (FO). It is a new process that use membranes available commercial and this process distinguishes by its low cost compared to other process. Sodium chloride (NaCl) was used as draw solution to extract water from poisonous metals solution. The driving force in the FO process is provided by a different in osmotic pressure (concentration) across the membrane between the draw and poisonous metals solution sides. Experimental work was divided into three parts. The first part includes operating the forward osmosis process using T

This study investigates the influence of fear, refuge, and migration in a predator–prey model, where the interactions between the species follow an asymmetric function response. In contrast to some other findings, we propose that prey develop an anti-predator response in response to a concentration of predators, which in turn increases the fear factor of the predators. The conditions under which all ecologically meaningful equilibrium points exist are discussed in detail. The local and global dynamics of the model are determined at all equilibrium points. The model admits several interesting results by changing the rate of fear of predators and predator aggregate sensitivity. Numerical simulations have been performed to verify our theoret

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