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Quantitative and Qualitative Responses of Hydroponic Tomato Production to Different Levels of Salinity

Phyton-International Journal of Experimental Botany 2024年第6期93卷 1311-1323页

作者： khalid A.al-Gaadi Ahmed M.Zeyada ElKamil Tola Abdullah M.alhamdan khalid A.M.Ahmed Rangaswamy Madugundu Mohamed K.Edrris Department of Agricultural Engineering College of Food and Agriculture SciencesKing Saud UniversityRiyadh11451Saudi Arabia Precision Agriculture Research Chair Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Chair of Dates Industry&Technology Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Agricultural Research Centre Agricultural Engineering Research Institute(AEnRI)Giza12619Egypt

From economic and nutritional points of view,tomato is,historically,considered one of the most important crops.Without signiﬁcant yield reduction,most commercial cultivars of tomato crops are sensitive to moderate levels of salinity.However,high levels of salt stress can negatively affect the yield and quality of tomato fruits.Therefore,this study was conducted to evaluate the yield and fruit quality of three tomato cultivars(Forester,Ghandowra-F1,and Feisty-Red)cultivated hydroponically,under three different levels of nutrient solution salinity.Evaluation of tomato fruits was performed based on quantity(number and weight of fruits,and total fruit yield),physical quality(color andﬁrmness),and chemical quality(refractometric index“Brix”,pH,EC,K^(+),Na^(+),and NO_(3)-).Experiments were conducted using three salinity levels of the nutrient solution with electrical conductivity values(dSm^(-1))of 2.5(control),6.0,and 9.5.Results showed that the studied tomato cultivars were signiﬁcantly inﬂuenced by high salinity(9.5 dSm^(-1))in comparison to the low(2.5 dSm^(-1))and medium(6.0 dSm^(-1))levels of salinity.On average,the highest fruit weight per plant of 1944.84 g and total fruit yield of 4.42 kgm^(-2) were observed at the low salinity level;however,no signiﬁcant differences were obtained in the two yield factors(single fruit weight and total fruit yield)for the low and medium salinity levels.On the other hand,a signiﬁcant reduction in tomato yield(31%)was associated with the high salinity level compared to the yield at low and medium salinity levels.Results of physical quality parameters showed highly signiﬁcant differences among all salinity levels.On average,the maximum value of color change(1.72)was associated with the medium salinity level,and the maximum value ofﬁrmness(9.61 Ncm^(-1))was recorded at the high salinity level.Salinity levels and tomato cultivars introduced signiﬁcant differences in chemical quality parameters;however,no signiﬁcant differences in these parameters were attributed to the low and mediu

关键词： Quality cultivars yield color ﬁrmness brix

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Hydrometallurgy two stage process for preparation of (Nd,La,Ce)_(2)O_(3) from end-of-life NiMH batteries

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Journal of Rare Earths 2024年第2期42卷 415-423,I0007页

作者： Karim Tanji khalid Ouzaouit Mohamed Belghiti Isam Lamsayety Hakim Faqir Intissar Benzakour Centre de recherche REMINEX-Groupe MANAGEM MarrakechMorocco

The present work aims to investigate the recovery of light rare earth elements(LREEs) oxides from end-oflife NiMH batteries using a hydro metallurgical process followed by effective precipitation.The operational leaching parameters such as phosphoric acid concentration,temperature,and the solid-liquid ratio were first optimized by Box-Behnken design.The results reveal that under optimum conditions([H_(3)PO_(4)]=2 mol/L,T=80℃,and S/L=1:10 g/mL) the leaching efficiencies of Ni,Co reach 98.1% and99.3%.While La,Ce,and Nd elements remain in the leaching residue as(La,Ce,Nd)PO_(4) with yields of 98.2%,98.6%,and 99.6% for La,Ce,and Nd,respectively.Afterward,the(La,Ce,Nd)PO_(4) is leached with HCl acid,then the rare earth oxalate was precipitated using oxalic acid at a pH of 1.8 and then the product was calcined at 800℃ for 2 h in order to synthesize the(Nd,La,Ce)_(2)O_(3).The analysis using scanning electron microscopy(SEM) coupled with energy dispersive X-ray spectroscopy(EDX) confirms the homogeneity of(Nd,La,Ce)_(2)O_(3) particles that have two morphologies,i.e.,flower and sticks with a particle size between 3and 6 μm.The unit cell parameters of(Nd,La,Ce)_(2)O_(3) were calculated after Rietveld refinement of the XRD patterns,in the space group of Fm-3m are a=b=c=0.57921 nm and the volume equal to 0.194322 nm^(3).

关键词： NiMH batteries Hydrometallurgical process Leaching Phosphoric acid Box-Behnken Light rare earth oxides

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MicroRNAs in hepatocellular carcinoma treatment:Charting the path forward

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World Journal of Gastroenterology 2024年第11期30卷 1470-1474页

作者： Hong T Lin Antonio F alvarez Castaneda Somashekar G Krishna khalid Mumtaz Division of Gastroenterology Hepatology and NutritionDepartment of MedicineThe Ohio State University Wexner Medical CenterColumbusOH 43210United States

MicroRNAs(miRNAs)are recognized for their involvement in the regulation of gene expression and exhibit significant potential in both the prognostic assessment and treatment of hepatocellular carcinoma(HCC).HCC,like other tumors,seldom occurs in isolation;instead,it evolves within a microenvironment featuring oncogenic and tumor-suppressive elements.When combined with suitable delivery vehicles,miRNA technology provides the capability to directly engage with these elements,thereby hindering tumor formation and progression.Ongoing research in this domain holds the promise of enabling a more efficacious and multi-modal treatment approach for HCC in the near future.

关键词： Hepatocellular carcinoma Tumor microenvironment MicroRNA Mesenchymal stem cell Exosome

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Diagnostic and therapeutic role of endoscopic ultrasound in liver diseases:A systematic review and meta-analysis

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World Journal of Gastroenterology 2024年第7期30卷 742-758页

作者： Eyad Gadour Abeer Awad Zeinab Hassan khalid Jebril Shrwani Bogdan Miutescu Hussein Hassan Okasha Department of Gastroenterology and Hepatology King Abdulaziz Hospital-National GuardAhsa 31982Saudi Arabia Department of Internal Medicine Faculty of MedicineZamzam University CollegeKhartoum 11113Sudan Department of Hepatogastroenterology Kasar Alainy HospitalFaculty of MedicineCairo UniversityCairo 11451Egypt Department of Internal Medicine Stockport Hospitals NHS Foundation TrustManchester SK27JEUnited Kingdom Public Health Authority Saudi Center for Disease Prevention and ControlJazan 45142Saudi Arabia Department of Clinical Infection Microbiology and ImmunologyInstitute of Infection and Global HealthSchool of Medicine and Life SciencesUniversity of LiverpoolLiverpoolUnited Kingdom Department of Gastroenterology and Hepatology Victor Babes University of Medicine and PharmacyTimisoara 300041Romania Advanced Regional Research Center in Gastroenterology and Hepatology Victor Babes University of Medicine and PharmacyTimisoara 30041Romania Department of Internal Medicine Division of Gastroenterology and HepatologyKasr Al-Aini School of MedicineCairo UniversityCairo 11562Egypt

BACKGROUND In hepatology,the clinical use of endoscopic ultrasound(EUS)has experienced a notable increase in recent times.These applications range from the diagnosis to the treatment of various liver diseases.Therefore,this systematic review summarizes the evidence for the diagnostic and therapeutic roles of EUS in liver diseases.AIM To examine and summarize the current available evidence of the possible roles of the EUS in making a suitable diagnosis in liver diseases as well as the therapeutic accuracy and efficacy.METHODS PubMed,Medline,Cochrane Library,Web of Science,and Google Scholar databases were extensively searched until October 2023.The methodological quality of the eligible articles was assessed using the Newcastle-Ottawa scale or Cochrane Risk of Bias tool.In addition,statistical analyses were performed using the Comprehensive Meta-Analysis software.RESULTS Overall,45 articles on EUS were included(28 on diagnostic role and 17 on therapeutic role).Pooled analysis demonstrated that EUS diagnostic tests had an accuracy of 92.4%for focal liver lesions(FLL)and 96.6%for parenchymal liver diseases.EUS-guided liver biopsies with either fine needle aspiration or fine needle biopsy had low complication rates when sampling FLL and parenchymal liver diseases(3.1%and 8.7%,respectively).Analysis of data from four studies showed that EUS-guided liver abscess had high clinical(90.7%)and technical success(90.7%)without significant complications.Similarly,EUS-guided interventions for the treatment of gastric varices(GV)have high technical success(98%)and GV obliteration rate(84%)with few complications(15%)and rebleeding events(17%).CONCLUSION EUS in liver diseases is a promising technique with the potential to be considered a first-line therapeutic and diagnostic option in selected cases.

关键词： Focal liver lesion Liver abscess drainage Fine needle aspiration Gastric varices Endoscopic ultrasound

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Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection

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Computers, Materials & Continua 2024年第2期78卷 2441-2468页

作者： Vaishnawi Priyadarshni Sanjay Kumar Sharma Mohammad khalid Imam Rahmani Baijnath Kaushik Rania almajalid Department of Computer Science Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia School of Computer Science Shri Vaishno Devi UniversityKatraIndia

Breast cancer(BC)is one of the leading causes of death among women worldwide,as it has emerged as the most commonly diagnosed malignancy in women.Early detection and effective treatment of BC can help save women’s lives.Developing an efficient technology-based detection system can lead to non-destructive and preliminary cancer detection techniques.This paper proposes a comprehensive framework that can effectively diagnose cancerous cells from benign cells using the Curated Breast Imaging Subset of the Digital Database for Screening Mammography(CBIS-DDSM)data set.The novelty of the proposed framework lies in the integration of various techniques,where the fusion of deep learning(DL),traditional machine learning(ML)techniques,and enhanced classification models have been deployed using the curated dataset.The analysis outcome proves that the proposed enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models for BC detection outperformed most of the existing models with impressive results.

关键词： Autoencoder breast cancer deep neural network convolutional neural network image processing machine learning deep learning

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Model Agnostic Meta-Learning(MAML)-Based Ensemble Model for Accurate Detection of Wheat Diseases Using Vision Transformer and Graph Neural Networks

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Computers, Materials & Continua 2024年第5期79卷 2795-2811页

作者： Yasir Maqsood Syed Muhammad Usman Musaed alhussein Khursheed Aurangzeb Shehzad khalid Muhammad Zubair Department of Creative Technologies Faculty of Computing and Artificial IntelligenceAir UniversityIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Engineering Bahria School of Engineering and Applied SciencesBahria UniversityIslamabad44000Pakistan Laboratory for Neuro&Psychophysiology KU LeuvenLeuven3000Belgium

Wheat is a critical crop,extensively consumed worldwide,and its production enhancement is essential to meet escalating demand.The presence of diseases like stem rust,leaf rust,yellow rust,and tan spot significantly diminishes wheat yield,making the early and precise identification of these diseases vital for effective disease management.With advancements in deep learning algorithms,researchers have proposed many methods for the automated detection of disease pathogens;however,accurately detectingmultiple disease pathogens simultaneously remains a challenge.This challenge arises due to the scarcity of RGB images for multiple diseases,class imbalance in existing public datasets,and the difficulty in extracting features that discriminate between multiple classes of disease pathogens.In this research,a novel method is proposed based on Transfer Generative Adversarial Networks for augmenting existing data,thereby overcoming the problems of class imbalance and data scarcity.This study proposes a customized architecture of Vision Transformers(ViT),where the feature vector is obtained by concatenating features extracted from the custom ViT and Graph Neural Networks.This paper also proposes a Model AgnosticMeta Learning(MAML)based ensemble classifier for accurate classification.The proposedmodel,validated on public datasets for wheat disease pathogen classification,achieved a test accuracy of 99.20%and an F1-score of 97.95%.Compared with existing state-of-the-art methods,this proposed model outperforms in terms of accuracy,F1-score,and the number of disease pathogens detection.In future,more diseases can be included for detection along with some other modalities like pests and weed.

关键词： Wheat disease detection deep learning vision transformer graph neural network model agnostic meta learning

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Deep Learning Approach for Hand Gesture Recognition:Applications in Deaf Communication and Healthcare

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Computers, Materials & Continua 2024年第1期78卷 127-144页

作者： Khursheed Aurangzeb khalid Javeed Musaed alhussein Imad Rida Syed Irtaza Haider Anubha Parashar Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Kingdom of Saudi Arabia Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Laboratory Biomechanics and Bioengineering University of Technology of CompiegneCompiegne60200France Department of Computer Science and Engineering Manipal University JaipurJaipur303007India

Hand gestures have been used as a significant mode of communication since the advent of human civilization.By facilitating human-computer interaction(HCI),hand gesture recognition(HGRoc)technology is crucial for seamless and error-free HCI.HGRoc technology is pivotal in healthcare and communication for the deaf community.Despite significant advancements in computer vision-based gesture recognition for language understanding,two considerable challenges persist in this field:(a)limited and common gestures are considered,(b)processing multiple channels of information across a network takes huge computational time during discriminative feature extraction.Therefore,a novel hand vision-based convolutional neural network(CNN)model named(HVCNNM)offers several benefits,notably enhanced accuracy,robustness to variations,real-time performance,reduced channels,and scalability.Additionally,these models can be optimized for real-time performance,learn from large amounts of data,and are scalable to handle complex recognition tasks for efficient human-computer interaction.The proposed model was evaluated on two challenging datasets,namely the Massey University Dataset(MUD)and the American Sign Language(ASL)alphabet Dataset(ASLAD).On the MUD and ASLAD datasets,HVCNNM achieved a score of 99.23% and 99.00%,respectively.These results demonstrate the effectiveness of CNN as a promising HGRoc approach.The findings suggest that the proposed model have potential roles in applications such as sign language recognition,human-computer interaction,and robotics.

关键词： Computer vision deep learning gait recognition sign language recognition machine learning

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Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 633-659页

作者： Nadeem Ahmed khalid Mohammadani ali Kashif Bashir Marwan Omar Angel Jones Fayaz Hassan School of Electronic Science Beijing University of Post and TelecommunicationBeijing100086China Department of Computer Science Huanggang Normal UniversityHuanggangChina Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabad502345India Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Information Technology and Management Illinois Institute of TechnologyChicagoUSA College of Computing Capital Technology UniversityLaurelUSA

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes altogether.Recognizing the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against BHA.An additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network behaviors.Rigorous testing of our solution has revealed its remarkable ability to enhance communication in VANETs.Specifically,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and security.These results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

关键词： Black hole attack IoV vehicular ad hoc network AODV routing protocol

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The role of green industrial transformation in mitigating carbon emissions:Exploring the channels of technological innovation and environmental regulation

Energy and Built Environment

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Energy and Built Environment 2024年第3期5卷 464-479页

作者： Saima Mehmood khalid Zaman Shiraz Khan Zohaib ali Haroon ur Rashid Khan Department of Economics The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Management Sciences The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Energy and Process Engineering(EPT) Norwegian University of Science and TechnologyHøgskoleringen 1Trondheim 7034Norway Faculty of Business The University of Wollongong in DubaiDubai 20183United Arab Emirates

The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic concerns.The purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and 2020.Carbon emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible mediators.The association between variables is assessed using the robust least-squares approach.Green industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon emissions.The findings support the pollution haven hypothesis in a country.The causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental standards.According to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 forward.Additionally,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over time.Green industrial transitions are projected to result in a ten-year reduction in carbon emissions.The variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over time.Pakistan’s economy should foster a green industrial revolution to avoid pollution and increase environmental sustainability to meet its environmental g

关键词： Carbon intensity Industrial green transformation Environmental regulations Technological innovations Robust least squares regression

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Video Summarization Approach Based on Binary Robust Invariant Scalable Keypoints and Bisecting K-Means

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Computers, Materials & Continua 2024年第3期78卷 3565-3583页

作者： Sameh Zarif Eman Morad khalid Amin Abdullah alharbi Wail S.Elkilani Shouze Tang Department of Information Technology Faculty of Computers and InformationMenoufia UniversityMenoufia32511Egypt Department of Artificial Intelligence Faculty of Artificial IntelligenceEgyptian Russian UniversityBader11829Egypt Department of Computer Science Community CollegeKing Saud UniversityRiyadh11362Saudi Arabia College of Applied Computer Science King Saud UniversityAl-Muzahmiya19676Saudi Arabia School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

Due to the exponential growth of video data,aided by rapid advancements in multimedia technologies.It became difficult for the user to obtain information from a large video series.The process of providing an abstract of the entire video that includes the most representative frames is known as static video summarization.This method resulted in rapid exploration,indexing,and retrieval of massive video libraries.We propose a framework for static video summary based on a Binary Robust Invariant Scalable Keypoint(BRISK)and bisecting K-means clustering algorithm.The current method effectively recognizes relevant frames using BRISK by extracting keypoints and the descriptors from video sequences.The video frames’BRISK features are clustered using a bisecting K-means,and the keyframe is determined by selecting the frame that is most near the cluster center.Without applying any clustering parameters,the appropriate clusters number is determined using the silhouette coefficient.Experiments were carried out on a publicly available open video project(OVP)dataset that contained videos of different genres.The proposed method’s effectiveness is compared to existing methods using a variety of evaluation metrics,and the proposed method achieves a trade-off between computational cost and quality.

关键词： BRISK bisecting K-mean video summarization keyframe extraction shot detection

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