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Multifaceted Aquatic Environmental Differences between Nanoplastics and Microplastics:Behavior and Fate

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Environment & Health 2024年第10期2卷 688-701页

作者： Sheng Wang noor Sulaiman AL-Hasni Zhaoli Liu Airong Liu State Key Laboratory for Pollution Control School of Environmental Science and EngineeringTongji UniversityShanghai 200092China

Microplastics and nanoplastics are emerging pollutants of concern in the aquatic environment that are causing increasing global environmental and human health *** there has been extensive research on microplastics and nanoplastics,little has been said about the differences in their behavior in the aquatic environment,and many studies have considered them as the same class of hazardous materials;but in fact,microplastics and nanoplastics should be considered as two different types of environmentally hazardous *** this review,we propose that microplastics and nanoplastics behave in the aquatic environment in a size-dependent manner and should be *** we systematically analyzed the differences in the behavior of microplastics and nanoplastics in the aquatic environment in terms of five aspects:1)distribution behavior;2)adsorption behavior;3)reaction with natural colloids;4)aging and leaching behavior;5)interaction with *** paper has been written to draw academic attention to the different behaviors of microplastics and nanoplastics in the aquatic environment in order to distinguish between their effects on humans and the environment.

关键词： Microplastics Nanoplastics Aquatic environmental behavior Differences

DeepSVDNet:A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

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Computer Systems Science & Engineering 2024年第2期48卷 511-528页

作者： Anas Bilal Azhar Imran Talha Imtiaz baig Xiaowen Liu Haixia Long Abdulkareem Alzahrani Muhammad Shafiq College of Information Science and Technology Hainan Normal UniversityHaikou571158China Department of Creative Technologies Air UniversityIslamabadPakistan School of Life Science and Technology University of Electronic Science and Technology of China UESTCChengduChina School of Science and Technology University of Management and Technology UMTLahorePunjabPakistan Faculty of Computer Science&Information Technology Al Baha UniversityAl BahaSaudi Arabia School of Information Engineering Qujing Normal UniversityQujingChina

Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness ***,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to *** paper proposes a novel VTDR detection and classification model that combines different models through majority *** proposed methodology involves preprocessing,data augmentation,feature extraction,and classification *** use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for *** tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,*** proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.

关键词： Diabetic retinopathy(DR) fundus images(FIs) support vector machine(SVM) medical image analysis convolutional neural networks(CNN) singular value decomposition(SVD) classification

Novel energy recovery from an integrated municipal solid waste and leachate treatment system

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Waste Disposal and Sustainable Energy 2024年第1期6卷 53-61页

作者： Siti Salwa Khamis Hadi Purwanto Hamzah Mohd Salleh Alya Naili Rozhan Mohamed Abdur Rahman Mahammadsalman Warimani noor Alam Faculty of Engineering International Islamic University MalaysiaJalan Gombak53100Kuala LumpurMalaysia Department of Engineering Management Universitas Internasional Semen IndonesiaGresikIndonesia Halalan Thayyiban Research Centre Sultan Sharif Ali Islamic UniversityBandar Seri BegawanBrunei Department of Mechanical Engineering P.A.College of EngineeringMangaloreKarnataka574153India Department of Mechanical Engineering Malaysia-Japan International Institute of TechnologyUniversity of Technology Malaysia54100Kuala LumpurMalaysia

Population growth,waste generation,and massive waste mismanagement have led to environmental *** of municipal solid waste(MSW)requires an efficient and sustainable integrated *** integrated thermal processing of MSW is one of the best waste management *** this study,energy analysis of MSW is carried out based on the material and energy balance of 2000 kg wet MSW,which contains 50%*** the leachate is removed,the dry MSW is sent for carbon content enhancement in carbonization to produce MSW-based ***,the combustion of MSW-based char provided high heat and syngas to be used in a hydrothermal process for MSW leachate *** result shows that the char fuel of MSW produces a sufficient amount of energy,13501.29 MJ(84.55%),in the form of synthetic gas by-product,which has a big potential as an energy *** novelty of the proposed integrated thermal system is to produce 84.55%synthetic gas by-product,which is used for electricity production,cooking,food,and heat energy for industrial *** proposed applications of this paper offer insightful information for policymaking regarding novel MSW techniques,which are economical,energy-efficient,and environmentally ***,it increases the effectiveness of MSW utilization.

关键词： Energy Carbonization Hydrothermal Municipal solid waste Integrated system

Diabetic Retinopathy Detection: A Hybrid Intelligent Approach

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Computers, Materials & Continua 2024年第9期80卷 4561-4576页

作者： Atta Rahman Mustafa Youldash Ghaida Alshammari Abrar Sebiany Joury Alzayat Manar Alsayed Mona Alqahtani noor Aljishi Department of Computer Science(CS) College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of Computer Engineering(CE) College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia

Diabetes is a serious health condition that can cause several issues in human body organs such as the heart and kidney as well as a serious eye disease called diabetic retinopathy(DR).Early detection and treatment are crucial to prevent complete blindness or partial vision *** detection methods,which involve ophthalmologists examining retinal fundus images,are subjective,expensive,and ***,this study employs artificial intelligence(AI)technology to perform faster and more accurate binary classifications and determine the presence of *** this regard,we employed three promising machine learning models namely,support vector machine(SVM),k-nearest neighbors(KNN),and Histogram Gradient Boosting(HGB),after carefully selecting features using transfer learning on the fundus images of the Asia Pacific Tele-Ophthalmology Society(APTOS)(a standard dataset),which includes 3662 images and originally categorized DR into five levels,now simplified to a binary format:No DR and DR(Classes 1-4).The results demonstrate that the SVM model outperformed the other approaches in the literature with the same dataset,achieving an excellent accuracy of 96.9%,compared to 95.6%for both the KNN and HGB *** approach is evaluated by medical health professionals and offers a valuable pathway for the early detection of DR and can be successfully employed as a clinical decision support system.

关键词： Diabetic retinopathy transfer learning machine learning fundus images binary classification APTOS

Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul Haq Fahim Arif Khursheed Aurangzeb noor ul Ain Javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

Application of Polygonum minus Extract in Enhancing Drought Tolerance in Maize by Regulating Osmotic and Antioxidant System

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Phyton-International Journal of Experimental Botany 2024年第2期93卷 213-226页

作者： Mingzhao Han Susilawati Kasim Zhongming Yang Xi Deng Md Kamal Uddin noor Baity Saidi Effyanti Mohd Shuib Department of Land Management Faculty of AgricultureUniversiti Putra MalaysiaSerdang43400Malaysia Natural Medicines and Products Research Laboratory Institute of BioscienceUniversiti Putra MalaysiaSerdang43400Malaysia Department of Cell and Molecular Biology Faculty of Biotechnology and Biomolecular SciencesUniversiti Putra MalaysiaSerdang43400Malaysia

Drought stress is a major factor affecting plant growth and crop yield *** extracts as natural biostimulants hold great potential to strengthen plants to overcome drought *** explore the effect of Polygonum minus extract(PME)in enhancing drought tolerance in plants,a study was set up in a glasshouse environment using 10 different treatment *** foliar application were designed in CRD and effects were closely observed related to the growth,physiology,and antioxidant system changes in maize(Zea mays L.)under well-watered and drought *** seaweed extract(SWE)was used as a *** subjected to drought stress exhibited a significant reduction in fresh weight,dry weight,relative water content(RWC),and soluble sugar,but they stimulated the phenolic,flavonoid,proline,glutathione(GSH),malondialdehyde(MDA)and antioxidant enzyme(catalase,CAT;peroxidase,POD;superoxide dismutase,SOD)*** application of PME improved fresh and dry weight(FW:33.1%~41.4%;DW:48.0%~43.1%),chlorophyll content(Chl b:87.9%~100.76%),soluble sugar(23.6%~49.3%),and soluble protein(48.6%~56.9%)as well as antioxidant enzyme activities(CAT and POD)compared to CK under drought *** decreasing the level of ***,the mitigating effect of PME application with high concentration was more effective than those of *** study reveals that PME could alleviate drought stress by regulating osmoprotectant content and antioxidant defense system and can be used as an economical and environmentally friendly biostimulants for promoting maize growth under drought stress.

关键词： Drought biostimulants photosynthesis osmoprotectants antioxidants maize

Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char:A statistical neural network approach

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Journal of Road Engineering 2024年第3期4卷 318-333页

作者： Nura Shehu Aliyu Yaro Muslich Hartadi Sutanto noor Zainab Habib Aliyu Usman Abiola Adebanjo Surajo Abubakar Wada Ahmad Hussaini Jagaba Department of Civil and Environmental Engineering Universiti Teknologi PETRONASSeri Iskandar 32610Malaysia Department of Civil Engineering Ahmadu Bello UniversityZaria 810107Nigeria Institute of Infrastructure and Environment Heriot-Watt UniversityDubai 294345United Arab Emirates School of Civil Engineering Central South UniversityChangsha 410075China Interdisciplinary Research Centre for Membranes and Water Security King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia

The goals of this study are to assess the viability of waste tire-derived char(WTDC)as a sustainable,low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network(SCNN)model for predicting volumetric and Marshall properties of asphalt mixtures modified with *** study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDCmodified asphalt mixtures(WTDC-MAM).The input variables comprised waste tire char content and asphalt binder *** output variables comprised mixture unit weight,total voids,voids filled with asphalt,Marshall stability,and *** coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt *** predictive modeling,the SCNN model is employed,incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and *** optimal network architecture,using the collected dataset,was a 2:6:5 structure,and the neural network was trained with 60%of the data,whereas the other 20%was used for cross-validation and testing *** network employed a hyperbolic tangent(tanh)activation function and a feed-forward *** to the results,the network model could accurately predict the volumetric and Marshall *** predicted accuracy of SCNN was found to be as high value>98%and low prediction errors for both volumetric and Marshall *** study demonstrates WTDC's potential as a low-cost,sustainable aggregate *** SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices.

关键词： Waste tire Neural network Sustainable practices Asphalt mixtures Predictive model

Optimized protoplast isolation and transfection with a breakpoint:accelerating Cas9/sgRNA cleavage efficiency validation in monocot and dicot

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aBIOTECH 2024年第2期5卷 151-168页

作者： Debasmita Panda Subhasis Karmakar Manaswini Dash Swagat Kumar Tripathy Priya Das Sagar Banerjee Yiping Qi Sanghamitra Samantaray Pradipta Kumar Mohapatra Mirza J.baig Kutubuddin A.Molla ICAR National Rice Research Institute CuttackOdisha 753006India Department of Botany Ravenshaw UniversityCuttackOdisha 753003India Department of Plant Science and Landscape Architecture University of MarylandCollege ParkMD 20742USA

The CRISPR-Cas genome editing tools are revolutionizing agriculture and basic biology with their simplicity and precision ability to modify target genomic ***-predicted guide RNAs(gRNAs)often fail to induce efficient cleavage at target *** target loci are inaccessible due to complex chromatin ***,there is no suitable tool available to predict the architecture of genomic target sites and their ***,significant time and resources are spent on performing editing experiments with inefficient *** in vitro-cleavage assay could provide a rough assessment of gRNA efficiency,it largely excludes the interference of native genomic *** in-vivo testing gives a proper assessment of the cleavage ability of editing reagents in a native genomic ***,we developed a modified protocol that offers highly efficient protoplast isolation from rice,Arabidopsis,and chickpea,using a sucrose gradient,transfection using PEG(polyethylene glycol),and validation of single guide RNAs(sgRNAs)cleavage efficiency of *** have optimized various parameters for PEG-mediated protoplast transfection and achieved high transfection efficiency using our protocol in both monocots and *** introduced plasmid vectors containing Cas9 and sgRNAs targeting genes in rice,Arabidopsis,and chickpea *** dual sgRNAs,our CRISPRdeletion strategy offers straightforward detection of genome editing success by simple agarose gel *** sequencing of PCR products confirmed the editing efficiency of specific ***,we demonstrated that isolated protoplasts can be stored for up to 24/48 h with little loss of viability,allowing a pause between isolation and *** high-efficiency protocol for protoplast isolation and transfection enables rapid(less than 7 days)validation of sgRNA cleavage efficiency before proceeding with stable *** isolation and transfection method can als

关键词： Protoplast Genome editing Transgene-free edited plants Rice Chickpea

Scoliocorrector Fatma-UI for correction of adolescent idiopathic scoliosis: Development, effectivity, safety and functional outcome

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World Journal of Orthopedics 2024年第1期15卷 61-72页

作者： Phedy Phedy Ismail Hadisoebroto Dilogo Wresti Indriatmi Sugeng Supriadi Marcel Prasetyo Fitri Octaviana Zairin noor Doctoral Program in Medical Sciences Faculty of Medicine University of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Department of Orthopaedic and Traumatology Universitas IndonesiaJakarta 10430DKI JakartaIndonesia Department of Dermatology and Venereology Faculty of MedicineUniversity of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Faculty of Mechanical Engineering University of IndonesiaDepok 16424Jawa BaratIndonesia Department of Radiology University of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Department of Neurology Faculty of MedicineUniversity of IndonesiaJakarta Pusat 10430DKI JakartaIndonesia Research Center for Osteoporosis Department of Orthopaedic and TraumatologyLambung Mangkurat UniversityBanjarmasin 70123Kalimantan SelatanIndonesia

BACKGROUND Adolescent idiopathic scoliosis remains a major problem due to its high incidence,high risk,and high *** of the aims of the management in scoliosis is to correct the *** techniques are available to correct scoliosis deformity;however,they are all far from ideal to achieve three-dimensional correction in *** To develop a set of tools named Scoliocorrector Fatma-UI(SCFUI)to aid threedimensional correction and to evaluate the efficacy,safety,and functional *** This study consists of two *** the first stage,we developed the SCFUI and tested it in finite element and biomechanical *** second stage was a single-blinded randomized clinical trial to evaluate the SCFUI compared to direct vertebral rotation(DVR).Forty-four subjects with adolescent idiopathic scoliosis were randomly allocated into the DVR group(n=23)and SCFUI group(n=21).Radiological,neurological,and functional outcome was compared between the *** Finite element revealed the maximum stress of the SCFUI components to be between 31.2-252 *** analysis revealed the modulus elasticity of SCFUI was 9561324±633277 *** groups showed improvement in Cobb angle and sagittal profile,however the rotation angle was lower in the SCFUI group(11.59±7.46 vs 18.23±6.39,P=0.001).Neurological and functional outcome were comparable in both *** We concluded that SCFUI developed in this study resulted in similar coronal and sagittal but better rotational correction compared to *** safety and functional outcomes were also similar to DVR.

关键词： Adolescent idiopathic scoliosis Scoliocorrector Fatma-UI Scoliosis surgery Posteromedial translation Direct vertebral rotation