Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutants and environmental conditions remains uncharted. Future research must expand EME's applicability, assess its environmental impact versus other methods, and boost scalability, cost-effectiveness, and energy efficiency in industry. Advances in novel liquid membrane materials can enhance extraction efficiency and selectivity, aiming to provide efficient, sustainable industrial pollutant treatment. This research provides a review of the existing practices in the field of liquid membranes when coupled with the application of an electric field.
Circular data (circular sightings) are periodic data and are measured on the unit's circle by radian or grades. They are fundamentally different from those linear data compatible with the mathematical representation of the usual linear regression model due to their cyclical nature. Circular data originate in a wide variety of fields of scientific, medical, economic and social life. One of the most important statistical methods that represents this data, and there are several methods of estimating angular regression, including teachers and non-educationalists, so the letter included the use of three models of angular regression, two of which are teaching models and one of which is a model of educators. ) (DM) (MLE) and circular shrinkage mod
... Show MoreThe study showed that there are (28) plant families present in Al-Razzaza Lake. The families are (Amaranthaceae, Amaryllidaceae, Aizoaceae, Apiaceae, Apocynaceae, Asteraceae, Brassicaceae, Boraginaceae, Capparaceae, Caryophyllaceae, Cistaceae, Colchicaceae, Convolvulaceae, Cynomoriaceae, Fabaceae, Frankeniaceae, Lamiaceae, Liliaceae, Malvaceae, Orobanchaceae, Plantaginaceae, Poaceae, Polygonaceae, Ranunculaceae, Solanaceae, Tamaricaceae,Typhaceae, Zygophyllaceae). Asteraceae family is the largest number of species found in abundance in this lake, followed by the Fabaceae family.
This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
... Show MoreThe objective of this article is to delve into the intricate dynamics of marriage relationships, exploring the impact of emotions such as fear, love, financial considerations and likability. In our investigation, we adopt a perspective that acknowledges the nonlinear nature of interactions among individuals. Diverging from certain prior studies, we propose that the fear element within the context of marriage is not a singular, isolated factor but rather a manifestation resulting from the amalgamation of numerous social issues. This, in turn, contributes to the emergence of strained and unsuccessful relationships. Unlike conventional approaches, we extensively examine the conditions essential for the existence of all socially signifi
... Show MoreKeys to four genera and twelve species of the subfamily Phlaeothripinae (Phlaeothripidae) were constructed, these are: Haplothrips; Karnyothrips; Phlaeothrips; and Dolicholepta ,and the species are: Haplothrips cerealis Priesner; Haplothrips tritici kurdjumov, Haplothrips hukkineni Priesner; Haplothrips subtilissimus (Haliday) ؛ Haplothrips reuteri Karny; Haplothrips jasonis Priesner; Haplothrips sallloumensis Priesner ; Haplothrips pharao Priesner ; Phlaeothrips sycomri Priesner ; Karnyothrips flavipus (Jones); Karnyothrips melaleucus (Bagnall) ; Dolicholepta micrurus (Bagnall). These were collected from Baghdad
... Show MoreSimple, cheap, sensitive, and accurate kinetic- spectrophotometric method has been developed for the determination of naringenin in pure and supplements formulations. The method is based on the formation of Prussian blue. The product dye exhibits a maximum absorbance at 707 nm. The calibration graph of naringenin was linear over the range 0.3 to 10 µg ml-1 for the fixed time method (at 15 min) with a correlation coefficient (r) and percentage linearity (r2%) were of 0.9995 and 99.90 %, respectively, while the limit of detection LOD was 0.041 µg ml-1. The method was successfully applied for the determination of naringenin in supplements with satisfac
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.