A combined support vector regression with a firefly algorithm for prediction of energy consumption in wastewater treatment plants.

Wastewater treatment plants (WWTPs) comprise energy-intensive processes, serving as primary contributors to overall WWTP costs. This research study proposes a novel approach that integrates support vector regression (SVR) with the firefly algorithm (FFA) for the prediction of energy consumption in a WWTP in Chlef City, Algeria. The database comprises a comprehensive set of 1,653 samples, capturing diverse information categories.

In-vitro antibacterial and antibiofilm activities and in-silico analysis of a potent cyclic peptide from a novel Streptomyces sp. strain RG-5 against antibiotic-resistant and biofilm-forming pathogenic bacteria.

The proliferation of multidrug-resistant and biofilm-forming pathogenic bacteria poses a serious threat to public health. The limited effectiveness of current antibiotics motivates the search for new antibacterial compounds. In this study, a novel strain, RG-5, was isolated from desert soil.

Exploring NRB Biofilm Adhesion and Biocorrosion in Oil/Water Recovery Operations Within Pipelines.

Microbially influenced corrosion represents a critical challenge to the integrity and durability of carbon steel infrastructure, particularly in environments conducive to biofilm formation by nitrate-reducing bacteria (NRB). This study investigated the impact of NRB biofilms on biocorrosion processes within oil/water recovery operations in Algerian pipelines. A comprehensive suite of experimental and analytical techniques, including microbial analysis, gravimetric methods, and surface characterization, were employed to elucidate the mechanisms of microbially influenced corrosion (MIC).

Investigation of structural, elastic, electronic, and optical properties of lead-free double perovskites CsXBeBr (X = Ge, Sn): a first-principles DFT study.

Context: In this study, the structural, elastic, electronic, and optical properties of CsGeBeBr and CsSnBeBr halide double perovskites (HDPs) were investigated using density functional theory (DFT) calculations. Notably, the Tran-Blaha modified Becke-Johnson (TB-mBJ) method was employed to predict indirect band gaps of 2.434 eV for CsGeBeBr and 2.

Enhancing deep learning-based slope stability classification using a novel metaheuristic optimization algorithm for feature selection.

The evaluation of slope stability is of crucial importance in geotechnical engineering and has significant implications for infrastructure safety, natural hazard mitigation, and environmental protection. This study aimed to identify the most influential factors affecting slope stability and evaluate the performance of various machine learning models for classifying slope stability. Through correlation analysis and feature importance evaluation using a random forest regressor, cohesion, unit weight, slope height, and friction angle were identified as the most critical parameters influencing slope stability.

Hybrid attention-based deep neural networks for short-term wind power forecasting using meteorological data in desert regions.

This study introduces an optimized hybrid deep learning approach that leverages meteorological data to improve short-term wind energy forecasting in desert regions. Over a year, various machine learning and deep learning models have been tested across different wind speed categories, with multiple performance metrics used for evaluation. Hyperparameter optimization for the LSTM and Conv-Dual Attention Long Short-Term Memory (Conv-DA-LSTM) architectures was performed.

Psychometric characteristics of the Narcissistic Admiration and Rivalry Questionnaire (NARQ): Arabic version.

Narcissists are characterized by confidence, fragility, a desire for social approval without showing interest in others, charm, self-assurance, arrogance, and aggression. This study assesses the psychometric properties of the Arabic version of the Narcissistic Admiration and Rivalry Questionnaire (NARQ) among Algerian students ( = 714). Confirmatory factor and Rasch analyses were used.

Fine-tuning inflow prediction models: integrating optimization algorithms and TRMM data for enhanced accuracy.

This research explores machine learning algorithms for reservoir inflow prediction, including long short-term memory (LSTM), random forest (RF), and metaheuristic-optimized models. The impact of feature engineering techniques such as discrete wavelet transform (DWT) and XGBoost feature selection is investigated. LSTM shows promise, with LSTM-XGBoost exhibiting strong generalization from 179.

Psychometric properties of the Benign and Malicious Envy Scale: A cross-cultural study in the Arab Maghreb countries.

Background: The Benign and Malicious Envy Scale (BeMaS) is designed to assess the trait of envy and evaluate individual differences in people's tendency to experience benign or malicious envy towards superior comparison standards.

Objective: This study aimed to examine the factor structure of the BeMaS in Arab culture through exploratory and confirmatory factor analysis and to ensure the measurement equivalence of the benign and malicious envy scale across three countries in the Arab Maghreb region (Algeria, Tunisia, and Morocco).

Methods: The study was conducted on a sample of 1047 students from various universities across three countries, Algeria (n = 401), Tunisia (n = 289), and Morocco (n = 357), and implemented a cross-sectional study design.

Assessing the viability of hydrogen-based perovskites for optoelectronic and thermoelectric applications via first principle modeling.

Context: In this study, we delve into the physical characteristics of six hydride perovskites of ABH-type materials (CsCaH, CsSrH, KMgH, LiBaH, NaBeH, and RbCaH). Our investigation primarily focuses on assessing their structural stability by determining the enthalpy of formation and examining the dispersion of phonons. Using band structure calculations, we discern the characteristics of semiconductors, observing a direct bandgap in all four perovskites except NaBeH and KMgH, which exhibit indirect gaps.

Antibacterial and antibiofilm properties of two cyclic dipeptides produced by a new desert Streptomyces sp. HG-17 strain against multidrug-resistant pathogenic bacteria.

Introduction: The emergence of multidrug-resistant bacteria and biofilms requires discovering new antimicrobial agents from unexplored environments.

Objectives: This study aims to isolate and characterize a new actinobacterial strain from the Hoggar Mountains in southern Algeria and evaluate its ability to produce bioactive molecules with potential antibacterial and antibiofilm activities.

Methods: A novel halotolerant actinobacterial strain, designated HG-17, was isolated from the Hoggar Mountains, and identified based on phenotypic characterizations, 16S rDNA sequence analysis, and phylogenetic analysis.

Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran).

The estimation of groundwater levels is crucial and an important step in ensuring sustainable management of water resources. In this paper, selected piezometers of the Hamedan-Bahar plain located in west of Iran. The main objective of this study is to compare effect of various pre-processing methods on input data for different artificial intelligence (AI) models to predict groundwater levels (GWLs).

Nonlinear optical properties of azo sulfonamide derivatives.

Context: The present work deals with the linear and nonlinear optical properties such as the dipole moment, polarizability, total hyperpolarizability, electric field-induced second harmonic generation, and hyper-Rayleigh scattering first hyperpolarizability of four heterocyclic azo compounds containing the sulfonamide group considered promise in nonlinear optic. The obtained polarizability and hyperpolarizability were supported by the frontier molecular orbital analysis. The properties have been effectively estimated and thoroughly examined to shed light on the nonlinear optical activity based on the density functional theory.

Structural, elastic, electronic, and optical properties of lead-free halide double perovskites CsBꞌBꞌꞌBr (BꞌBꞌꞌ: BeMg, CdBe, CdGe, GeMg, GeZn, MgZn): Ab initio calculations.

Context: In our study, we theoretically investigated the structural, elastic, electronic, and optical characteristics of halide double perovskites (DPs) CsB'B''Br (B'B'': BeMg, CdBe, CdGe, GeMg, GeZn, MgZn). Structural stabilities were assessed based on the enthalpy of formation, tolerance factor, and elastic constants. Ductile and brittle behavior was examined using Poisson and Pugh's ratios.

Shannon entropy of performance metrics to choose the best novel hybrid algorithm to predict groundwater level (case study: Tabriz plain, Iran).

Predicting groundwater level (GWL) fluctuations, which act as a reserve water reservoir, particularly in arid and semi-arid climates, is vital in water resources management and planning. Within the scope of current research, a novel hybrid algorithm is proposed for estimating GWL values in the Tabriz plain of Iran by combining the artificial neural network (ANN) algorithm with newly developed nature-inspired Coot and Honey Badger metaheuristic optimization algorithms. Various combinations of meteorological data such as temperature, evaporation, and precipitation, previous GWL values, and the month and year values of the data were used to evaluate the algorithm's success.

In situ Fourier transform infrared-attenuated total reflection spectroscopy and modeling investigation of protein adsorption: Case of expanded bovine serum albumin on titanium dioxide anatase.

The purpose of this experimental and modeling research is to study the pH effect and to determine the surface coverage plus the adsorption constant (Ka) of bovine serum albumin (BSA) protein adsorbed on TiO2 anatase surface, respectively. In situ Fourier transform infrared-attenuated total reflection spectroscopy in a flow-through cell was used to study the BSA adsorption on porous TiO2 anatase films. The experiments were performed in water solution, under different pH values, at a concentration of 10-6 mol/l.

Family Communication as a Mediator between Family Resilience and Family Functioning under the Quarantine and COVID-19 Pandemic in Arabic Countries.

The coronavirus pandemic has become an unprecedented world crisis in which we have struggled against the most potent threat of the twenty-first century. This pandemic has had a profound impact on individuals and families. Therefore, the study aimed to examine family communication as a mediator of the relationship between family resilience and family functioning under the quarantine and coronavirus pandemic in Algeria and Iraq.

Characteristics of new pyrrolic derivatives and their oligomers using DFT and TD-DFT calculations.

Context: This article is based on the study of pyrrolic derivatives and their oligomers. Knowing that, pyrrolic derivatives are widely studied on an industrial scale. The aim of this work is to find pyrrolic derivatives having the same physicochemical characteristics such as the pyrrolic edifice.

Psychometric Properties of the Perceived Collective Family Efficacy Scale in Algeria.

The Perceived Collective Family Efficacy Scale is a tool utilized to assess the effectiveness of a family as a functioning system. The scale has a single-factor structure with good validity and reliability. However, there is a shortage of psychometric evidence of the scale in an Arab context.

Psychological Toll of the COVID-19 Pandemic: An In-Depth Exploration of Anxiety, Depression, and Insomnia and the Influence of Quarantine Measures on Daily Life.

The COVID-19 pandemic, on a global scale, has prompted multifaceted challenges, including a notable psychological toll on the general population. This study uses mixed-method approach for a nuanced exploration of these experiences. Using a phenomenological strategy, qualitative responses from 999 participants were analyzed regarding their pandemic-induced anxiety and the influence of quarantine measures on their lives.

Study of mechanical, optical, and thermoelectric characteristics of Ba XMoO (X = Zn, Cd) double perovskite for energy harvesting.

The double perovskites are become the emerging aspirant to fulfill the demand of energy. Therefore, the optoelectronic, elastic and transport characteristics of Ba XMoO (X = Zn, Cd) are addressed systemically. The elastic constants show the mechanical stability.

Theoretical insight of stabilities and optoelectronic properties of double perovskite CsCuIrF: Ab-initio calculations.

Context: In this study, we predict the stability, elastic, electronic and optical properties of double perovskite (DP) CsCuIrF. The detailed investigation of electronic structure and optical properties to find the suitability of DP CsCuIrF for device applications. From the structural optimization results, the stability of DP (CsCuIrF) is in cubic order and belongs to the Fm-3 m space group (#225) with a nonmagnetic (NM) state.

A theoretical investigation of the lead-free double perovskites halides Rb XCl (X = Se, Ti) for optoelectronic and thermoelectric applications.

In this study, structural, electronic, optical, thermoelectric, and thermodynamics properties of vacancy-ordered double perovskites Rb XCl (X = Se, Ti) were explored theoretically. The results revealed that Rb2SeCl6 and Rb TiCl are indirect band gap (E ) semiconductors with E values of 2.95 eV, and 2.

The Effect of Ramadan Fasting on the Coping Strategies Used by Male Footballers Affiliated with the Tunisian First Professional League.

This study aimed to discover coping strategies among professional male Tunisian footballers during the Ramadan 2021 fast. One hundred and eighty footballers who belong to twelve Tunisian professional clubs (age: 25.54 ± 4.

First-principles calculations to investigate physical properties of orthorhombic perovskite YBO (B = Ti & Fe) for high energy applications.

Orthorhombic oxide perovskite compounds are very promising materials for the applications of optoelectronics and thermal barrier coating. This work represents a numerical simulation of YBO compounds through the first-principles approach. The electronic and magnetic properties are investigated employing the general gradient approximation (GGA) coupled to the integration of the Hubbard U-term which is the GGA + U.