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Turning teawaste particles into magnetic bio-sorbents particles for arsenic removal from wastewater:Isotherm and kinetic studies

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Particuology 2024年第4期87卷 179-193页

作者： Mary McGeogh hamza annath Chirangano Mangwandi School of Chemistry and Chemical Engineering Queen's University BelfastDavid Kier BuildingBT95AGUnited Kingdorm Department of Chermnistry Lancaster UniversityBailrigsLancasterLA14YBUnited Kingdom

The primary objective of this research was to assess the potential of magnetic bleached biochar(MBBC)as a cost-effective adsorbent for arsenic *** achieve this,locally collected tea wastes underwent meticulous cleaning,bleaching,and modifications via thermal and chemical *** non-magnetic and magnetic biochar adsorbents were thoroughly characterized using Fourier transform-infrared spectroscopy(FT-IR)and thermo-gravimetric analysis(TGA).Subsequently,the adsorptive performance of MBBC in removing arsenic from wastewater samples was investigated,considering various crucial parameters such as adsorbent-adsorbate contact time,concentration of As,temperature,adsorbent dosage,and the regeneration-ability of the *** experimental data for the adsorption process were best represented by the Langmuir isotherm,indicating its suitability for the MBBC ***,the MBBC demonstrated a maximum Langmuir adsorption capacity of approximately 714 mg/g at room temperature,highlighting its efficiency as an arsenic ***,the Lagergren's Pseudo-second order kinetic model proved to be the most suitable for describing the adsorption kinetics,confirming the chemisorption nature of the *** results also indicated that the adsorption process is endothermic and feasible,suggesting its viability for practical *** all findings into account,the comprehensive analysis strongly supports the potential use of MBBC as a highly promising and cost-effective adsorbent for efficiently removing arsenic from aqueous *** research contributes valuable insights to the field of wastewater treatment and offers a sustainable and environmentally friendly solution for tackling arsenic contamination in water sources.

关键词： Arsenics Wastewater Adsorption Magnetic bio-char Teawaste

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Upcycling tea waste particles into magnetic adsorbent materials for removal of Cr(Ⅵ) from aqueous solutions

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Particuology 2023年第9期80卷 115-126页

作者： Jiahong Wu hamza annath Haili Chen Chirangano Mangwandi School of Chemistry and Chemical Engineering Queen’s University BelfastDavid Kier BuildingBT95AGUnited Kingdom Department of Chemistry University of LancasterBailriggLancasterLA 4YBUnite Kingdomc College of Chemistry and Materials Engineering Zhejiang Agriculture&Forestry UniversityHangzhou311300China

In this work,locally available tea wastes were used as precursors for the development of cost-effectivebio-sorbent materials for heavy metal removal from *** and thermal treatments toprepare magnetic/non-magnetic tea waste-based adsorbents were discussed and correlated theirproperties with corresponding Cr(Ⅵ)adsorption *** bio-sorbents were thoroughly characterized by FT-IR,PXRD,N2 adsorption-desorption surface area techniques and Cr adsorption performancewas investigated in batch reactor under different conditions such as adsorbent dosage,initial Cr concentration,solution pH and contact *** bleaching steps,incorporation of magnetic ironnanoparticles and judicious temperature treatments of tea wastes resulted in high performing biosorbents with a complete removal of Cr at a dosage of 0.25 g/mL of the *** adsorption on thesetea waste-based bio-sorbents were found to be fitting to a pseudo 2nd order kinetics.

关键词： Bleached-tea waste Magnetic-tea waste Biosorption Chromium Adsorption kinetics Pyrolysis

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Coronavirus Detection Using Two Step-AS Clustering and Ensemble Neural Network Model

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Computers, Materials & Continua 2022年第6期71卷 6307-6331页

作者： Ahmed hamza Osman Department of Information System Faculty of Computing and Information Technology King Abdulaziz University RabighSaudi Arabia

This study presents a model of computer-aided intelligence capable of automatically detecting positive COVID-19 instances for use in regular medical *** proposed model is based on an Ensemble boosting Neural Network architecture and can automatically detect discriminatory features on chestX-ray images through Two Step-As clustering algorithm with rich filter families,abstraction and weight-sharing *** contrast to the generally used transformational learning approach,the proposed model was trained before and after *** compilation procedure divides the datasets samples and categories into numerous sub-samples and subcategories and then assigns new group labels to each new group,with each subject group displayed as a distinct *** retrieved characteristics discriminant cases were used to feed the Multiple Neural Network method,which was then utilised to classify the *** Two Step-AS clustering method has been modified by pre-aggregating the dataset before applying Multiple Neural Network algorithm to detect COVID-19 cases from chest X-ray *** forMultiple Neural Network and Two Step-As clustering algorithms were optimised by utilising Ensemble Bootstrap Aggregating algorithm to reduce the number of hyper parameters they *** testswere carried out using theCOVID-19 public radiology database,and a cross-validationmethod ensured *** proposed classifier with an accuracy of 98.02%percent was found to provide the most efficient outcomes *** result is a lowcost,quick and reliable intelligence tool for detecting COVID-19 infection.

关键词： Two step-AS clustering ensemble learning bootstrap aggregating multiple neural network covid-19 X-ray images

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Conjugate-Gradient Progressive-Iterative Approximation for Loop and Catmull-Clark Subdivision Surface Interpolation

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Journal of Computer Science & Technology 2022年第2期37卷 487-504页

作者： Yusuf Fatihu hamza Hong-Wei Lin School of Mathematical Science Zhejiang UniversityHangzhou 310027China State Key Laboratory of CAD Sz CG Zhejiang UniversityHangzhou 310058China

Loop and Catmull-Clark are the most famous approximation subdivision schemes,but their limit surfaces do not interpolate the vertices of the given ***-iterative approximation(PIA)is an efficient method for data interpolation and has a wide range of applications in many fields such as subdivision surface fitting,parametric curve and surface fitting among ***,the convergence rate of classical PIA is *** this paper,we present a new and fast PIA format for constructing interpolation subdivision surface that interpolates the vertices of a mesh with arbitrary *** proposed method,named Conjugate-Gradient Progressive-Iterative Approximation(CG-PIA),is based on the Conjugate-Gradient Iterative algorithm and the Progressive Iterative Approximation(PIA)*** method is presented using Loop and Catmull-Clark subdivision ***-PIA preserves the features of the classical PIA method,such as the advantages of both the local and global scheme and resemblance with the given ***,CG-PIA has the following features.1)It has a faster convergence rate compared with the classical PIA and W-PIA.2)CG-PIA avoids the selection of weights compared with W-PIA.3)CG-PIA does not need to modify the subdivision schemes compared with other methods with fairness *** examples for Loop and Catmull-Clark subdivision surfaces are provided in this paper to demonstrate the efficiency and effectiveness of CG-PIA.

关键词： progressive-iterative approximation Loop subdivision Catmull-Clark subdivision conjugate-gradient method

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Enhanced catalytic activity of monodispersed AgPd alloy nanoparticles assembled on mesoporous graphitic carbon nitride for the hydrolytic dehydrogenation of ammonia borane under sunlight

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Nano Research 2017年第5期10卷 1627-1640页

作者： hamza Kahri Melike Sevim Onder Metin Department of Chemistry Faculty of Science Ataturk University 25240 Erzurum Turkey Laboratoire de Synthese Organique Asymetrique et Catalyse Homogene (UR11ES56) Faculte des Sciences de Monastir Universite de Monastir Bd. de I'Environnement 5019 Monastir Tunisia East Anatolian High Technology Research and Application Center (DAYTAM) Ataturk University 25240 Erzurum Turkey

We address the composition-controlled synthesis of monodispersed AgPd alloy nanoparticles （NPs）, their assembly for the first time on mesoporous graphitic carbon nitride （mpg-C3N4）, and the unprecedented catalysis of mpg-CgN4@AgPd in the hydrolytic dehydrogenation of ammonia borane （AB） at room temperature. Monodispersed AgPd alloy NPs were synthesized using a high-temperature organic-phase surfactant-assisted protocol comprising the co-reduction of silver（I） acetate and palladium（II） acetylacetonate in the presence of oleylamine, oleic acid, and 1-0ctadecene. This protocol allowed the synthesis of four different compositions of AgPd alloy NPs. The AgPd alloy NPs were then assembled on mpg-C3N4, reduced graphene oxide, and Ketjenblack using a liquid-phase self-assembly method. Among the three supports tested, the mpg-CBN4@AgPd catalysts provided the best activity because of the Mott-Schottky effect, which was driven by the favorable work function difference between mpg-CBN4 and the metal NPs. Moreover, the activity of the mpg-CBN4@AgPd catalyst was further enhanced by an acetic acid treatment （AAt）, and a record initial turnover frequency of 94.1 mOl（hydrogen）＇mOl（catalyst）-l-min-1 was obtained. Furthermore, the mpg-CBN4@Ag42Pdss-AAt catalyst also showed moderate durability for the hydrolysis of AB. This study also includes a wealth of kinetic data for the mpg-CBN4@AgPd-catalyzed hydrolysis of AB.

关键词： silver palladium alloy nanoparticles graphitic carbon nitride ammonia borane dehydrogenation

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Effects of Roselle and Ginger on cisplatin-induced reproductive toxicity in rats

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Asian Journal of Andrology 2006年第5期8卷 607-612页

作者： AmrAmin AlaaEldinA.hamza Department of Biology United Arab Emirates University Al-Ain 17551United Arab Emirates

Aim： To evaluate the protective effects of Hibiscus sabdariffa （Roselle） and Zingiber officinale （Ginger） against cisplatin-induced reproductive toxicity in rats and to study the mechanisms underlying these effects. Methods： Ethanol extracts of H. sabdariffa or Z. officinale [1 g/（kg·day）] were given p.o. to male albino rats for 26 days, which began 21 days before a single cisplatin i.p. injection （10 mg/kg body weight）. Results： Extracts of H. sabdariffa and Z. offcinale reduced the extent of cisplatin-induced sperm abnormality and enhanced sperm motility. Both extracts restored the control level of malondialdehyde （MDA）（lipid peroxidation marker） in the cisplatin-treated testis. The cisplatin injection induced decline in the levels of superoxide dismutase （SOD）, reduced glutathione （GSH） and catalase （CAT） were significantly reversed to control levels in groups where cisplatin was preceded by the administration of either H. sabdariffa or Z. officinale. Conclusion： Both H. sabdariffa and Z. officinale treatment increased the activities of testicular antioxidant enzymes and restored sperm motility of cisplatin-treated rats. The protective effects of tested plants are, therefore, suggested to be mediated by their potent antioxidant activities.

关键词： cisplatin testicular toxicity Hibiscus sabdariffa Zingiber officinale herb sperm motility reproductive toxicity

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Hyperparameter Tuned Deep Hybrid Denoising Autoencoder Breast Cancer Classification on Digital Mammograms

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Intelligent Automation & Soft Computing 2023年第6期36卷 2879-2895页

作者： Manar Ahmed hamza Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Breast Cancer(BC)is considered the most commonly scrutinized can-cer in women worldwide,affecting one in eight women in a ***-phy screening becomes one such standard method that is helpful in identifying suspicious masses’malignancy of BC at an initial ***,the prior iden-tification of masses in mammograms was still challenging for extremely dense and dense breast categories and needs an effective and automatic mechanisms for helping radiotherapists in *** learning(DL)techniques were broadly utilized for medical imaging applications,particularly breast mass *** advancements in the DL field paved the way for highly intellectual and self-reliant computer-aided diagnosis(CAD)systems since the learning cap-ability of Machine Learning(ML)techniques was constantly *** paper presents a new Hyperparameter Tuned Deep Hybrid Denoising Autoenco-der Breast Cancer Classification(HTDHDAE-BCC)on Digital *** presented HTDHDAE-BCC model examines the mammogram images for the identification of *** the HTDHDAE-BCC model,the initial stage of image preprocessing is carried out using an average median *** addition,the deep convolutional neural network-based Inception v4 model is employed to generate feature *** parameter tuning process uses the binary spider monkey opti-mization(BSMO)*** HTDHDAE-BCC model exploits chameleon swarm optimization(CSO)with the DHDAE model for BC *** experimental analysis of the HTDHDAE-BCC model is performed using the MIAS *** experimental outcomes demonstrate the betterments of the HTDHDAE-BCC model over other recent approaches.

关键词： Digital mammograms breast cancer classification computer-aided diagnosis deep learning metaheuristics

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Tracking control of redundant manipulator under active remote center-of-motion constraints: an RNN-based metaheuristic approach

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Science China(Information Sciences) 2021年第3期64卷 149-166页

作者： Ameer hamza KHAN Shuai LI Xinwei CAO Department of Computing Hong Kong Polytechnic University Department of Electronics and Electrical Engineering Swansea University School of Management Shanghai University

In this paper, we propose a recurrent neural network(RNN) for the tracking control of surgical robots while satisfying remote center-of-motion(RCM) constraints. RCM constraints enforce rules suggesting that the surgical tip should not go beyond the region of incision while tracking the commands of the *** of RCM constraints can result in serious injury to the patient. We unify the RCM constraints with the tracing control by formulating a single constrained optimization problem using a penalty-term *** penalty-term actively rewards the optimizer for satisfying the RCM constraints. We then propose an RNN-based metaheuristic optimization algorithm called "Beetle Antennae Olfactory Recurrent Neural Network(BAORNN)" for solving the formulated optimization problem in real time. The proposed control framework can track the surgeon’s commands and satisfy the RCM constraints simultaneously. Theoretical analysis is performed to demonstrate the stability and convergence of the BAORNN algorithm. Simulations using LBR IIWA14, a 7-degree-of-freedom robotic arm, are performed to analyze the performance of the proposed framework.

关键词： tracking control surgical robots RCM constraints metaheuristic optimization recurrent neural network RNN redundant manipulator

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Partial pre-image attack on Proof-of-Work based blockchains

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Blockchain(Research and Applications) 2024年第3期5卷 1-10页

作者： hamza Baniata Attila Kertesz Department of Software Engineering University of SzegedH-6720 SzegedHungary

Blockchain is a type of distributed ledger technology that consists of a growing list of records,called blocks,that are securely linked together using *** blockchain-based solution deploys a specific consensus algorithm that guarantees the consistency of the ledger over *** most famous,and yet claimed to be the most secure,is the Proof-of-Work(PoW)consensus *** this paper,we revisit the fundamental calculations and assumptions of this algorithm,originally presented in the Bitcoin white *** break down its claimed calculations in order to better understand the underlying assumptions of the *** also propose a novel formalization model of the PoW mining problem using the Birthday *** utilize this model to formalize and analyze partial pre-image attacks on PoW-based blockchains,with formal analysis that confirms the experimental results and the previously proposed *** build on those analyses and propose new concepts for benchmarking the security of PoW-based systems,including Critical Difficulty and Critical Difficulty per given *** calculations result in several important findings,including the profitability of launching partial pre-image attacks on PoW-based blockchains,once the mining puzzle difficulty reaches a given ***,for any compromised portion of the network(q<0.5;honest majority assumption still holds),the attack is formally proven profitable once the PoW mining puzzle difficulty reaches 56 leading zeros.

关键词： Blockchain Proof-of-Work Security Partial pre-image attack Hash functions

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Enhanced Chimp Optimization Algorithm Using Attack Defense Strategy and Golden Update Mechanism for Robust COVID-19 Medical Image Segmentation

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Journal of Bionic Engineering 2024年第4期21卷 2086-2109页

作者： Amir hamza Morad Grimes Abdelkrim Boukabou Samira Dib Non Testing Destructive Laboratory Faculty of TechnologyUniversity of Jijel18000JijelAlgeria Laboratory of Renewable Energy Faculty of TechnologyUniversity of Jijel18000JijelAlgeria

Medical image segmentation is a powerful and evolving technology in medical *** fact,it has been identified as a very effective tool to support and accompany doctors in their fight against the spread of the coronavirus(COVID-19).Various techniques have been utilized for COVID-19 image segmentation,including Multilevel Thresholding(MLT)-based meta-heuristics,which are considered crucial in addressing this ***,despite their importance,meta-heuristics have significant ***,the imbalance between exploration and exploitation,as well as premature convergence,can cause the optimization process to become stuck in local optima,resulting in unsatisfactory segmentation *** this paper,an enhanced War Strategy Chimp Optimization Algorithm(WSChOA)is proposed to address MLT *** strategies are incorporated into the traditional Chimp Optimization *** update mechanism that provides diversity in the ***,the attack and defense strategies are incorporated to improve the search space leading to avoiding local *** experimental results were conducted by comparing WSChoA with recent and well-known algorithms using various evaluation metrics such as Feature Similarity Index(FSIM),Structural Similarity Index(SSIM),Peak signal-to-Noise Ratio(PSNR),Standard deviation(STD),Freidman Test(FT),and Wilcoxon Sign Rank Test(WSRT).The results obtained by WSChoA surpassed those of other optimization techniques in terms of robustness and accuracy,indicating that it is a powerful tool for image segmentation.

关键词： Image processing Segmentation Optimization Chimp Golden update mechanism Attack-defense strategy COVID-19

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