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Enhanced termination of zinc and cadmium ions from wastewater employing plain and chitosan-modified mxenes: synthesis, characterization,and adsorption performance

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Green Chemical Engineering 2024年第3期5卷 339-347页

作者： Njood R.Azeez suhaib s.salih mohammed Kadhom Harith N.mohammed Tushar K.Ghosh Department of Chemical Engineering College of Engineering University of Tikrit Department of Environmental science College of Energy and Environmental Science Al-Karkh University of Science Department of Nuclear science & Engineering Institute University of Missouri-Columbia

Zinc and cadmium pollutants cause a significant environmental effect that cannot be ignored. Due to their considerable amount in an aqueous environment, industries are seeking suitable adsorbents that are environmentally friendly and inexpensive for removing metals from wastewater before disposing of them in surface waters. This research employed original MXene(MX) and chitosan-modified MXene(CsMX) to extract zinc(Zn(Ⅱ)) and cadmium(Cd(Ⅱ)) metal ions from water-based solutions. The composite material produced was analyzed using techniques such as X-ray Diffraction(XRD), scanning Electron Microscopy(sEM), Fourier Transform Infrared spectroscopy(FTIR), and Brunauer-Emmett-Teller(BET). The effects of contact duration, p H of the solution, and initial concentration of metal ions on the adsorption process of Zn(Ⅱ) and Cd(Ⅱ) onto both MX and CsMX composites were investigated. MX and prepared CsMX composite presented a high adsorption capacity for both studied heavy metals, which were 91.55 and 73.82 mg/g for Zn(Ⅱ) and Cd(Ⅱ) onto MX, 106.84 and 93.07 mg/g for Cd(Ⅱ) and Zn(Ⅱ) onto CsMX composite, respectively. Furthermore, the maximum competitive adsorption capacities for Zn(Ⅱ) onto MX and CsMX composites are 77.29 and 93.47 mg/g, and for are Cd(Ⅱ)60.30 and 79.66 mg/g, respectively. Hence, the removal capacities for both single and competitive metal ions were superior to CsMX composite. However, the adsorption capacities after five successive regeneration sequences were only dropped by 13.2% for Zn(Ⅱ) and 17.4% for Cd(Ⅱ) onto the CsMX composite compared to the first cycle. These results confirm that both metals could be efficiently terminated from wastewater, which makes the prepared CsMX composite a favorable candidate adsorbent in practical applications.

关键词： Adsorption Chitosan MXene Zn(II) Cd(II) Wastewater

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A hydrodynamic modelling of wave-activated bodies for wavelet marine regions

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Clean Energy 2024年第2期8卷 35-47页

作者： J.s.Peh mohammed W.Muhieldeen N.H.shuaib Mechanical Engineering Department Faculty of EngineeringTechnology&Built EnvironmentUCSI UniversityKuala Lumpur56000Malaysia MTC Engineer sdn.Bhd Shah AlamSelangorMalaysia

Recently,most wave energy research has targeted sea areas with high power density under extreme wave conditions for *** trend often leads to higher energy costs for wave power ***,many marine areas with low power density,characterized by wavelet conditions and less destructive forces than extreme wave conditions,remain ***,this study aimed to propose a wave-activated body model for sea regions with wavelet *** wave-activated body design process encompassed site selection,parameter determination,geometry design,comparison and performance evaluation using the ANsYs®AQWA *** results indicated that the proposed device achieved the desired heave motion,with an amplitude range of 1.2 to-2.5 m,validating its potential for deployment in marine regions with wavelet ***,while the proposed design is optimized for wavelet conditions,it was found to have potential limitations in extreme wave *** observation emphasizes the challenge of formulating a generalized design suitable for both ***,it is pivotal for wave-activated body designs to be customized based on the specific ocean conditions they target,underscoring the need for specialized designs of wave energy converters that consider the unique wave characteristics of their deployment sites.

关键词： wave energy converter south China sea renewable and sustainable energy wavelet ANsYs AQWA hydrodynamic wave-activated bodies

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Nodule Detection Using Local Binary Pattern Features to Enhance Diagnostic Decisions

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Computers, Materials & Continua 2024年第3期78卷 3377-3390页

作者： Umar Rashid Arfan Jaffar Muhammad Rashid mohammed s.Alshuhri sheeraz Akram Faculty of Computer science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54600Pakistan Department of Computer science National University of TechnologyIslamabad45000Pakistan Department of Radiological sciences and Medical Imaging College of AppliedMedical SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Information systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia

Pulmonary nodules are small, round, or oval-shaped growths on the lungs. They can be benign (noncancerous) or malignant (cancerous). The size of a nodule can range from a few millimeters to a few centimeters in diameter. Nodules may be found during a chest X-ray or other imaging test for an unrelated health problem. In the proposed methodology pulmonary nodules can be classified into three stages. Firstly, a 2D histogram thresholding technique is used to identify volume segmentation. An ant colony optimization algorithm is used to determine the optimal threshold value. secondly, geometrical features such as lines, arcs, extended arcs, and ellipses are used to detect oval shapes. Thirdly, Histogram Oriented surface Normal Vector (HOsNV) feature descriptors can be used to identify nodules of different sizes and shapes by using a scaled and rotation-invariant texture description. smart nodule classification was performed with the XGBoost classifier. The results are tested and validated using the Lung Image Consortium Database (LICD). The proposed method has a sensitivity of 98.49% for nodules sized 3–30 mm.

关键词： Pulmonary nodules segmentation histogram thresholding

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synthetic polymers:A review of applications in drilling fluids

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Petroleum science 2024年第1期21卷 475-518页

作者： shadfar Davoodi mohammed Al-shargabi David A.Wood Valeriy s.Rukavishnikov Konstantin M.Minaev school of Earth sciences&Engineering Tomsk Polytechnic UniversityLenin AvenueTomskRussia DWA Energy Limited LincolnUnited Kingdom

With the growth of deep drilling and the complexity of the well profile,the requirements for a more complete and efficient exploitation of productive formations increase,which increases the risk of various ***,reagents based on modified natural polymers(which are naturally occurring compounds)and synthetic polymers(sPs)which are polymeric compounds created industrially,are widely used to prevent emerging complications in the drilling ***,compared to modified natural polymers,sPs form a family of high-molecular-weight compounds that are fully synthesized by undergoing chemical polymerization *** provide substantial flexibility in their ***,their size and chemical composition can be adjusted to provide properties for nearly all the functional objectives of drilling *** can be classified based on chemical ingredients,type of reaction,and their responses to ***,some of sPs,due to their structural characteristics,have a high cost,a poor temperature and salt resistance in drilling fluids,and degradation begins when the temperature reaches 130℃.These drawbacks prevent sP use in some medium and deep ***,this review addresses the historical development,the characteristics,manufacturing methods,classification,and the applications of sPs in drilling *** contributions of sPs as additives to drilling fluids to enhance rheology,filtrate generation,carrying of cuttings,fluid lubricity,and clay/shale stability are explained in *** mechanisms,impacts,and advances achieved when sPs are added to drilling fluids are also *** typical challenges encountered by sPs when deployed in drilling fluids and their advantages and drawbacks are also *** issues also impact the applications of sPs in drilling ***,the cost of the most relevant sPs,and the monomers used in their synthesis,are *** impacts of sPs when deployed in drilling fluids,and t

关键词： synthetic versus.natural polymers nanopolymers Drilling fluid additives Lubricity Clay swelling Hole cleaning

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Predicting potential invasion risks of Leucaena leucocephala(Lam.)de Wit in the arid area of saudi Arabia

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Journal of Arid Land 2024年第7期16卷 983-999页

作者： Haq s MARIFATUL Darwish mohammed Waheed MUHAMMAD Kumar MANOJ siddiqui H MANZER Bussmann W RAINER Department of Ethnobotany Institute of BotanyIlia State UniversityTbilisi 0162Georgia The Centre of Excellence on sustainable Land Management(CoE-sLM) Indian Council of Forestry Research and EducationDehradun 248006India Department of Botany and Microbiology College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of Botany State Museum for Natural HistoryKarlsruhe 76133Germany

The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is *** study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in saudi Arabia under present and future climate change *** the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive *** conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological *** focused on the important influence of temperature seas.nality,temperature annual range,and precipitation *** distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate *** complex interaction that influenced the invasion of *** was highlighted by the environmental parameters using Jackknife ***,the actual geographic area where *** was found in saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand *** MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC *** and temperature were the primary factors influencing the potential distribution of ***,an estimated area of 216,342 km^(2)in saudi Arabia was at a high probability of invasion by *** investigated the potential for increased invasion hazards in the future due to climate change scenarios(shared socioeconomic Pathways(ssPs)245 and 585).The analysis of key climatic variables,including temperature seas.nality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substanti

关键词： area under the curve invasive species invasion risks climate change MaxEnt model

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Bayesian and Non-Bayesian Analysis for the sine Generalized Linear Exponential Model under Progressively Censored Data

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Computer Modeling in Engineering & sciences 2024年第9期140卷 2795-2823页

作者： naif Alotaibi A.s.Al-Moisheer Ibrahim Elbatal mohammed Elgarhy Ehab M.Almetwally Department of Mathematics and statistics Faculty of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Mathematics College of ScienceJouf UniversityP.O.Box 848Sakaka72351Saudi Arabia Mathematics and Computer science Department Faculty of ScienceBeni-Suef UniversityBeni-Suef62521Egypt Department of Basic sciences Higher Institute of Administrative SciencesBelbeisEgypt Faculty of Business Administration Delta University for Science and TechnologyGamasa11152Egypt

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(sGLE)*** sGLE distribution utilizes the sine transformation to enhance its *** updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability *** suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique *** model includes many well-known lifespan distributions as separate *** suggested model is accompanied with a range of statistical *** model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored *** order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing *** relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

关键词： sine G family generalized linear failure rate progressively censored data moments maximum likelihood estimation Bayesian estimation simulation

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Network security Enhanced with Deep Neural Network-Based Intrusion Detection system

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma s.Alrayes mohammed Zakariah syed Umar Amin Zafar Iqbal Khan Jehad saad Alqurni Information systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDs)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDs is trained and validated by the model using the NsL-KDD dataset,a popular benchmark for IDs *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDs in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NsL-KDD Dataset

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Proteome profiling to advance management of metabolic dysfunction-associated fatty liver disease

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Hepatobiliary surgery and Nutrition 2024年第1期13卷 147-149页

作者： mohammed Eslam nahum Méndez-sánchez Ming-Hua Zheng storr Liver Centre Westmead Institute for Medical ResearchWestmead Hospital and University of SydneySydneyNSWAustralia Liver Research Unit Medica Sur Clinic FoundationMexico CityMexico MAFLD Research Center Department of HepatologyThe First Affiliated Hospital of Wenzhou Medical UniversityWenzhouChina Institute of Hepatology Wenzhou Medical UniversityWenzhouChina Key Laboratory of Diagnosis and Treatment for The Development of Chronic Liver Disease in Zhejiang Province WenzhouChina

Metabolic dysfunction-associated fatty liver disease(MAFLD)is a complex,heterogenous and progressive disease that is characterised by substantial phenotypic variability,which results in disparate clinical presentations and outcomes(1-4).Notably,only a proportion of patients with MAFLD progress to the more advanced stages of the ***,the identification of the subgroups that have a high risk of disease progression is of paramount importance for clinical care,as well as drug development and clinical trials(5).

关键词： Metabolic dysfunction-associated fatty liver disease(MAFLD) fatty liver disease(FLD) fibrosis proteome biomarkers

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Impact of metal polluted sewage water on soil nematode assemblages in agricultural settings of Aligarh,India

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soil Ecology Letters 2024年第1期6卷 61-75页

作者： mohammed F.s.A.Ghanem shahid Afzal Humira Nesar Zarrin Imran Wasim Ahmad Nematode Biodiversity Research Lab Department of ZoologyAligarh Muslim UniversityAligarh 202002India

sewage water in agriculture threatens human health and soil ecosystems through metal *** show promise as bioindicators of soil health due to their abundance and position in soil food ***-polluted water decreased abundance of certain nematode groups and sigma Maturity *** pollution positively affected nematode groups with r-selected life *** water has been inappropriately used in agriculture,posing possible threats to human health and the soil ecosystems by its constituent pollutants,especially heavy *** evaluation of its influences on soil biomes needs to consider the response of soil *** soil organisms,nematodes are seen as the best promising candidates for bioindicators of soil *** in,we collected soil samples from fresh water irrigated field from three sites(s1,s2 and s3)and sewage water irrigated distance gradient(5 m-40 m),to assess the influence of metal(Cu,Zn,Cd,Mn,Pb)polluted water on various characteristics of nematode *** results indicated that the heavy metals decreased the abundance of C-p3 nematodes,herbivores,and predatory nematodes as well as sigma maturity index,whereas,C-p1,C-p2,bacterivore and fungivore nematodes abundance and diversity positively responded to the metal ***,nematode genera with r-selected life cycle were positively affected and those with K-selected life cycle were negatively affected by metal *** nematode community has potential to be used as indicator of pollution stress in agricultural soils to check soil health and sustainability.

关键词： heavy metals sewage irigation agriculture nematodes bioindicators

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CNN Channel Attention Intrusion Detection systemUsing NsL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

Intrusion detection systems(IDs)are essential in the field of cybersecurity because they protect networks from a wide range of online *** goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection systems(NIDs)that can identify *** NsL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection ***,maintaining operating efficiency while improving detection accuracy is the primary goal of this ***,typical NIDs examines both risky and typical behavior using a variety of *** the NsL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel *** to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection ***,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this *** efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDs) NsL-KDD dataset deep-learning machine-learning CNN channel Attention network security

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