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Gas Chromatographic Analysis of the Methanogenic Potential of Lignocellulosic Biomass Consisting of Banana Residues in Tambacounda, Senegal

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Open Journal of Applied Sciences 2025年第1期15卷 187-201页

作者： Haroun Ali Adannou hamza Aziber Ousman Ndiaye Mouhamadou Lamine Department of Physics and Chemistry Higher Normal School of NDjamena NDjamena Chad African Laboratory for Sustainable Development Research NDjamena Chad Department of Life and Earth Sciences Ecole Normale Suprieure de NDjamena NDjamena Chad Sustainable Business for AllSB2-4All Dakar Senegal

The residual biomass composed of pseudo trunks and banana leaves is very important and poorly valued. There is very little quantified data on the deposits of residual biomass from banana plantations in Senegal and in particular in the Tambacounda region. In this work, we seek to evaluate the methanogenic potential and to valorize this biomass in biogas and biofertilizer. The laboratory experiment lasted approximately 35 days. During this time, the methanogenic microorganisms degrade the organic residue provided, which results in the production of biogas. At the end of the reactions, the rate of biogas production drops, indicating the end of the biodegradation of organic matter. Biogas production is measured over time and the composition of the biogas produced is analyzed by gas chromatography (GC) or by an infrared analyzer. The methane potential of each sample is determined from the cumulative quantity of methane produced in each flask representing a digestion system. The measurement can be expressed in m3 of CH4 per tonne of dry matter or per tonne of raw material. The first challenge of this study therefore lies in the acquisition of reliable and usable data to quantify the methanizable biomass. This study will allow us not only to evaluate the quantities of pseudo trunks and banana leaves available in a plot after harvest but also to test the biogas and methane production potential (BMP test) of this substrate and therefore determine the expected biogas production of this biomass.

关键词： Residual Biomass Banana Tambacounda Laboratory Organic Matter Infrared Analyzer

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An Efficient Mechanism for Product Data Extraction from E-Commerce Websites

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Computers, Materials & Continua 2020年第12期65卷 2639-2663页

作者： Malik Javed Akhtar Zahur Ahmad Rashid Amin Sultan H.Almotiri Mohammed A.Al Ghamdi hamza.aldabbas University of Engineering and Technology TaxilaPakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia Al-Balqa Applied University Al-SaltJordan

A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular *** are designed for human understanding and not for ***,to make data machine-readable,it requires techniques to grab data from web *** have addressed the problem using two approaches,i.e.,knowledge engineering and machine *** of the art knowledge engineering approaches use the structure of documents,visual cues,clustering of attributes of data records and text processing techniques to identify data records on a web *** learning approaches use annotated pages to learn *** rules are used to extract data from unseen web *** structure of web documents is continuously ***,new techniques are needed to handle the emerging requirements of web data *** this paper,we have presented a novel,simple and efficient technique to extract data from web pages using visual styles and structure of *** proposed technique detects Rich Data Region(RDR)using query and correlative words of the *** is then divided into data records using style *** elements are removed using a Common Tag Sequence(CTS)and formatting *** system is implemented using JAVA and runs on the dataset of real-world working *** effectiveness of results is evaluated using precision,recall,and F-measure and compared with five existing systems.A comparison of the proposed technique to existing systems has shown encouraging results.

关键词： Document object model rich data region common tag sequence web data extraction deep web mining

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Human Aspects of Smart Technologies'Security:The Role of Human Failure

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Journal of Electronic Science and Technology 2016年第4期14卷 311-318页

作者： Mohammad aldabbas Bemd Teufel International Institute of Management in Technology University of FribourgFribourg 1700Switzerland

Security of smart technologies like smart grids and crowd energy systems cannot rely only on technical solutions, humans play a significant role in failure, security culture, information security, cyber security, trust and sharing, and perceptions and concern. This paper investigates security issues in smart technologies and the related role of human failure, whether it is intentional or *** that help reducing this failure are discussed. A human oriented framework for failure reduction is presented in order to enhance security.

关键词： Crowd energy human role intentional failure security smart grids unintentional failure.

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Acute Bronchiolitis about 535 Cases at Zinder National Hospital, Niger

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Open Journal of Pediatrics 2025年第1期15卷 130-140页

作者： Georges Thomas Ibrahim Doutchi Mahamadou Hassane Maman Laoul hamza Mahaman Nafissa Garba Moumouni Samaila Aboubacar Kamaye Moumouni Clinical Research and Health System Laboratory Faculty of Health Sciences Andr Salifou University Zinder Niger Zinder National Hospital Zinder Niger Faculty of Health Sciences Abdou Moumouni University Niamey Niger Amirou Boubacar Diallo National Hospital Niamey Niger Niamey National Hospital Niger

Introduction: Lower respiratory infections in general, and acute bronchiolitis in particular, represent a major cause of morbidity in children in Niger. The aim of this study was to investigate the epidemiological, diagnostic and therapeutic features of acute bronchiolitis in infants in the Pediatrics A department of the National Hospital in Zinder. Patients and Methods: This was a descriptive, cross-sectional study with prospective data collection conducted from April 1 to May 31, 2024. All infants aged 0 to 24 months hospitalized with acute bronchiolitis in the pediatric ward A of Zinder National Hospital were included in the study. Epidemiological, diagnostic and therapeutic aspects were the characteristics studied. Data analysis was performed using Epi info 7 software. Results: During the study period, acute bronchiolitis accounted for 51% of hospitalizations, and infants aged 3 - 11 months were the most affected (52.90%). The sex ratio was 1.6. The average age of patients was 10.40 ± 6.91 months, with extremes of 1 and 24 months. 98.50% of patients came from urban areas, and the socioeconomic level of families was average in 47.49% of cases. Mixed breastfeeding was practiced in 59.63% of cases. Average hospital admission time was 4.22 days. The main clinical signs were cough (43.18%), rhinorrhea (70.85%), ronchi (35.33%), crepitating rales (26.54%), sibilant rales (24.11%), signs of struggle (14.02%) and polypnea (70.85%). Paraclinical findings included chest distension, hyperleukocytosis and anemia, with 47.48%, 55.14% and 78.31% respectively. Therapeutically, nebulization was used in 93.08% of cases, respiratory physiotherapy (41.34%), corticosteroid therapy (34.08%), antibiotic therapy (21.50%), oxygen therapy (20.11%) and antipyretics (4.68%) were prescribed. Progression was favorable in 93.08% of patients, with a case-fatality rate of 1.12%. Conclusion: With its high frequency, acute bronchiolitis is a public health problem. Boys were the most affected by

关键词： Acute Bronchiolitis Infant Zinder Niger

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Innovative genome editing in plants: a transposase and CRISPR combination approach

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Science China Life Sciences 2025年第03期 893-894页

作者： hamza Sohail Iqra Noor Xuehao Chen Xiaodong Yang School of Horticulture and Landscape Architecture Yangzhou University

Transgenic plants are extensively utilized in research, enabling scientists to explore gene functions in controlled environments, leading to crops with higher productivity and greater resistance to biotic and abiotic stressors (Oyebamiji et al., 2024). Traditional transgene integration techniques, such as particle bombardment and Agrobacterium T-DNA integration, often lead to unintended mutations and unpredictable insertion sites, emphasizing the necessity for developing targeted transgene integration(Ahuja and Fladung, 2014).

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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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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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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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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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