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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期34卷 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad ABDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of Engineering and Technology ChikodiVisvesvaraya Technological UniversityBelagavi 590018KarnatakaIndia Nitte(Deemed to be University) NMAM Institute of Technology(NMAMIT)Department of Mechanical EngineeringNitte 574110India Aircraft Research and Design Centre HALBangalore 560037KarnatakaIndia Department of Mechanical Engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological UniversityBelagaviIndia Management and Science University Selangor Darul EhsanMalaysia Department of Civil Engineering College of EngineeringKing Saud UniversityRiyadh-11421Saudi Arabia

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al_(2)O_(3)nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest(RF)and CatBoost)was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption(BSFC)of 2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%(in volume),DSMEB20),57.14%less CO,40.8% less hydrocarbon,and increased NO_(x)emissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency(BTE)of 26.29% in 3×10^(-5)(in volume)Al_(2)O_(3)nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures(BTE,BSFC),and emissions(CO,CO_(2),NO_(x),Smoke)are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO_(2)emission results.

关键词： Dairy Scum Methyl Ester Biodiesel CI engine Al_(2)O_(3)concentration

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Rosa moschata ameliorates haloperidol-induced Parkinson's disease via reduction of neurodegeneration and oxidative stress

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Asian Pacific Journal of Tropical Biomedicine 2025年第1期15卷 24-33,I0013-I0015页

作者： Badriyah S.Alotaibi Uzma Saleem Maryam Farrukh Zunera Chaudhary Nabia Anwar Ifat Alsharif Abdullah R.Alanzi Tasahil S.Albishi Fatima A.Jaber Wedad Saeed Al-Qahtani Muhammad Ajmal Shah Department of Pharmaceutical Sciences College of PharmacyPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Punjab University College of Pharmacy University of the PunjabLahore-54000Pakistan Department of Pharmacology Faculty of Pharmaceutical SciencesGovt.College UniversityFaisalabad-38000Pakistan Department of Biology Jamoum University CollegeUmm Al-Qura University-21955 MakkahSaudi Arabia Department of Pharmacognosy College of PharmacyKing Saud UniversityRiyadh-11451Saudi Arabia Department of Biology College of SciencesUmm Al-Qura UniversityMakkahSaudi Arabia Department of Biological Sciences College of ScienceUniversity of JeddahJeddah 21589Saudi Arabia Department of Forensic Sciences College of Criminal JusticeNaif Arab University for Security SciencesP.O.Box 6830Riyadh 11452Saudi Arabia Department of Pharmacy Hazara UniversityMansehra-21300Pakistan

Objective:To investigate the effect of Rosa moschata(***)extract on haloperidol-induced Parkinson’s disease(PD)in ***:Haloperidol(1 mg/kg)was given to rats intraperitoneally for 3 weeks for induction of *** extract(150,300 and 600 mg/kg)was administered orally for 21 *** neuroprotective role of *** leaf extract in PD was explored by performing neurobehavioral tests and RT-PCR analysis and measuring neurotransmitters and oxidative stress ***:An improvement in motor functions and muscle strength was observed in PD rats treated with *** *** levels of dopamine,serotonin,noradrenaline,superoxide dismutase,catalase,glutathione,and superoxide dismutase were significantly increased(P<0.001),whereas acetylcholinesterase and malondialdehyde levels were markedly decreased by treatment with *** extract(P<0.001).The extract also markedly downregulated the mRNA expressions of IL-1β,α-synuclein,IL-1α,and TNF-αin brain ***,histopathological analysis indicated that neurofibrillary tangles and plaques were noticeably decreased in a dose-dependent manner in PD rats treated with *** ***:*** extract alleviates haloperidol-induced PD in rats by reducing oxidative stress and *** may be used for management and treatment of *** additional studies are required to confirm its efficacy and molecular mechanisms.

关键词： Parkinson’s disease Rosa moschata Neurotransmitter,α-Synuclein Haloperidol Neurodegeneration

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Unstable regions of anisotropic relativistic spheres in higher dimensions

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Communications in Theoretical Physics 2025年第3期77卷 112-129页

作者： M Yousaf Bander Almutairi M Z Bhatti Z Yousaf A S Khan Department of Mathematics University of Management and TechnologyJohar Town CampusLahore 54782Pakistan Department of Mathematics College of ScienceKing Saud UniversityPO Box 2455 Riyadh 11451Saudi Arabia Department of Mathematics University of the PunjabQuaid-i-Azam CampusLahore 54590Pakistan Institute of Advanced Study Shenzhen UniversityShenzhen 518060GuangdongChina

In this work,we consider the collapse of a D-dimensional sphere in the framework of a higher-dimensional spherically symmetric space-time in which the gravitational action chosen is claimed to be somehow linked to the D-dimensional modified *** work investigates the criteria for the dynamical instability of anisotropic relativistic sphere systems with D-dimensional modified *** certain conditions are applied that lead to the collapse equation and their effects on adiabatic indexΓin both Newtonian(N)and Post-Newtonian(PN)regimes by using a perturbation *** study explores that theΓplays a crucial role in determining the degree of dynamical *** index characterizes the fluid's stiffness and has a significant impact on defining the ranges of *** systematic investigation demonstrates the influence of various material properties such as anisotropic pressure,kinematic quantities,mass function,D-dimensional modified gravity parameters,and the radial profile of energy density on the instability of considered structures during their *** work also displays the dynamical behavior of spherically symmetric fluid configuration via graphical approaches.

关键词： gravitation dynamical instability mathematical and relativistic aspects of cosmology mathematical physics

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Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 531-553页

作者： Tmader Alballa Muhammad Ihsan Atiqe Ur Rahman Noorah Ayed Alsorayea Hamiden Abd El-Wahed Khalifa Department of Mathematics College of SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia 2 Department of Mathematics University of Management and TechnologyLahore54000Pakistan Department of Mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia

The dramatic rise in the number of people living in cities has made many environmental and social problems *** search for a productive method for disposing of solid waste is the most notable of these *** scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated *** goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site *** characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these *** tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s *** this,an intelligent algorithm is *** steps of the suggested algorithm are explained with an example that explains *** compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their *** study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,*** uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior *** is simpler for the decisionmakers to look at each option separately because the decision is *** the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

关键词： Hypersoft expert set Sanchez’s method decision making optimization solid waste management possibility grade fuzzy parameterization

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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

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Smart Grid Security Framework for Data Transmissions with Adaptive Practices Using Machine Learning Algorithm

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Computers, Materials & Continua 2025年第3期82卷 4339-4369页

作者： Shitharth Selvarajan Hariprasath Manoharan Taher Al-Shehari Hussain Alsalman Taha Alfakih School of Built Environment Engineering and ComputingLeeds Beckett UniversityLeedsLS13HEUK Department of Computer Science and Engineering Chennai Institute of TechnologyChennai602109India Centre for Research Impact & Outcome Chitkara UniversityChandigarh140401India Department of Electronics and Communication Engineering Panimalar Engineering CollegeChennai600123India Department of Self-Development Skill Common First Year DeanshipKing Saud UniversityRiyadh11362Saudi Arabia Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

This research presents an analysis of smart grid units to enhance connected units’security during data *** major advantage of the proposed method is that the system model encompasses multiple aspects such as network flow monitoring,data expansion,control association,throughput,and *** addition,all the above-mentioned aspects are carried out with neural networks and adaptive optimizations to enhance the operation of smart grid ***,the quantitative analysis of the optimization algorithm is discussed concerning two case studies,thereby achieving early convergence at reduced *** suggested method ensures that each communication unit has its own distinct channels,maximizing the possibility of accurate *** results in the provision of only the original data values,hence enhancing *** power and line values are individually observed to establish control in smart grid-connected channels,even in the presence of adaptive settings.A comparison analysis is conducted to showcase the results,using simulation studies involving four scenarios and two case *** proposed method exhibits reduced complexity,resulting in a throughput gain of over 90%.

关键词： Machine learning power systems security smart grid

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Novel Feature Extractor Framework in Conjunction with Supervised Three Class-XGBoost Algorithm for Osteosarcoma Detection from Whole Slide Medical Histopathology Images

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Computers, Materials & Continua 2025年第2期82卷 3337-3353页

作者： Tanzila Saba Muhammad Mujahid Shaha Al-Otaibi Noor Ayesha Amjad Rehman Khan Artificial Intelligence&Data Analytics Lab College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Center of Excellence in Cyber Security(CYBEX) Prince Sultan UniversityRiyadh11586Saudi Arabia

Osteosarcomas are malignant neoplasms derived from undifferentiated osteogenic mesenchymal cells. It causes severe and permanent damage to human tissue and has a high mortality rate. The condition has the capacity to occur in any bone;however, it often impacts long bones like the arms and legs. Prompt identification and prompt intervention are essential for augmenting patient longevity. However, the intricate composition and erratic placement of osteosarcoma provide difficulties for clinicians in accurately determining the scope of the afflicted area. There is a pressing requirement for developing an algorithm that can automatically detect bone tumors with tremendous accuracy. Therefore, in this study, we proposed a novel feature extractor framework associated with a supervised three-class XGBoost algorithm for the detection of osteosarcoma in whole slide histopathology images. This method allows for quicker and more effective data analysis. The first step involves preprocessing the imbalanced histopathology dataset, followed by augmentation and balancing utilizing two techniques: SMOTE and ADASYN. Next, a unique feature extraction framework is used to extract features, which are then inputted into the supervised three-class XGBoost algorithm for classification into three categories: non-tumor, viable tumor, and non-viable tumor. The experimental findings indicate that the proposed model exhibits superior efficiency, accuracy, and a more lightweight design in comparison to other current models for osteosarcoma detection.

关键词： Medical image processing deep learning healthcare image classification histopathology

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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Ultrahigh-resolution atomic localization via superposition of standing waves

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Communications in Theoretical Physics 2025年第3期77卷 57-65页

作者： Muhammad Idrees Ahmed S Hendy Zareen A Khan Institute of Nonlinear Physics and Department of Physics Zhejiang Normal UniversityJinhua 321004China Zhejiang Institute of Photoelectronics and Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua 321004China Department of Computational Mathematics and Computer Science Institute of Natural Sciences and MathematicsUral Federal University19 Mira St.Yekaterinburg 620002Russia Department of Mechanics and Mathematics Western Caspian UniversityBaku 1001Azerbaijan Department of Mathematical Sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityPO Box 84428Riyadh 11671Saudi Arabia

In this study we theoretically demonstrate ultrahigh-resolution two-dimensional atomic localization within a three-levelλ-type atomic medium via superposition of asymmetric and symmetric standing wave *** analysis provides an understanding of the precise spatial localization of atomic positions at the atomic level,utilizing advanced theoretical approaches and principles of quantum *** dynamical behavior of a three-level atomic system is thoroughly analyzed using the density matrix formalism within the realm of quantum mechanics.A theoretical approach is constructed to describe the interaction between the system and external fields,specifically a control field and a probe *** absorption spectrum of the probe field is thoroughly examined to clarify the spatial localization of the atom within the proposed configuration.A theoretical investigation found that symmetric and asymmetric superposition phenomena significantly influence the localized peaks within a two-dimensional spatial ***,the emergence of one and two sharp localized peaks was observed within a one-wavelength *** observed notable influences of the intensity of the control field,probe field detuning and decay rates on atomic ***,we have achieved an unprecedented level of ultrahigh resolution and precision in localizing an atom within an area smaller thanλ/35×λ/*** findings hold promise for potential applications in fields such as Bose-Einstein condensation,nanolithography,laser cooling,trapping of neutral atoms and the measurement of center-of-mass wave functions.

关键词： ultrahigh resolution atom localization symmetric and asymmetric superposition probe absorption standing wave fields

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An Improved Hybrid Deep Learning Approach for Security Requirements Classification

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Computers, Materials & Continua 2025年第3期82卷 4041-4067页

作者： Shoaib Hassan QianmuLi Muhammad Zubair Rakan AAlsowail Muhammad Umair School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing210094China Faculty of Information Technology and Computer Science University of Central PunjabLahore5400Pakistan Computer Skills Self-Development Skills DevelopmentDeanship of Common First YearKing Saud UniversityRiyadh11362Saudia Arabia

As the trend to use the latestmachine learning models to automate requirements engineering processes continues,security requirements classification is tuning into the most researched field in the software engineering *** literature studies have proposed numerousmodels for the classification of security ***,adopting those models is constrained due to the lack of essential datasets permitting the repetition and generalization of studies employing more advanced machine learning ***,most of the researchers focus only on the classification of requirements with security *** did not consider other nonfunctional requirements(NFR)directly or indirectly related to *** has been identified as a significant research gap in security requirements *** major objective of this study is to propose a security requirements classification model that categorizes security and other relevant security *** use PROMISE_exp and DOSSPRE,the two most commonly used datasets in the software engineering *** proposed methodology consists of two *** the first step,we analyze all the nonfunctional requirements and their relation with security *** found 10 NFRs that have a strong relationship with security *** the second step,we categorize those NFRs in the security requirements *** proposedmethodology is a hybridmodel based on the ConvolutionalNeural Network(CNN)and Extreme Gradient Boosting(XGBoost)***,we evaluate the model by updating the requirement type column with a binary classification column in the dataset to classify the requirements into security and non-security *** performance is evaluated using four metrics:recall,precision,accuracy,and F1 Score with 20 and 28 epochs number and batch size of 32 for PROMISE_exp and DOSSPRE datasets and achieved 87.3%and 85.3%accuracy,*** proposed study shows an enhancement in metrics

关键词： Requirements engineering security requirements deep learning CNN XGBoost classification

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