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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 University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL Department of Mechanical Engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University Department of Civil Engineering College of EngineeringKing Saud University

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 Al2O3nanoparticles 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） of2.85% 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 NOxemissions 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） Al2O3nanoparticle-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,CO2,NOx,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 CO2emission results.

关键词： Al2O3 concentration Ci engine Dairy Scum Methyl Ester biodiesel

Arctic sea-ice extent: No record minimum in 2023 or recent years

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 52-55页

作者： Ola M.Johannessen Tor i.Olaussen Nansen Scientific Society BergenNorway Nansen Environmental and Remote Sensing Center BergenNorway

Arctic sea-ice extent reaches its minimum each year in September. On 11 September 2023 the minimum was 4.969 million square kilometers(***^(2)). This was not a record low, which occurred in 2012, when the minimum was 4.175 ***^(2), 0.794 ***^(2) less than the minimum in 2023. However, the ice extent had decreased by 0.432 ***^(2) compared with 2022. Nevertheless, the summer melting in 2023 was remarkably less than expected when considering the strong heat waves in the atmosphere and ocean, with record temperatures set around the world. in general, there is a high correlation between the long-term decrease in sea-ice extent and the increasing CO_(2) in the atmosphere, where the increase of CO_(2) in recent decades explains about 80% of the decrease in sea ice in September, while the remainder is caused by natural variability.

关键词： Sea ice Arctic Minimum ice Climate

intrumer:A Multi Module Distributed Explainable iDS/iPS for Securing Cloud Environment

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Computers, Materials & Continua 2025年第1期82卷 579-607页

作者： Nazreen banu A S.K.b.Sangeetha Department of Computer Science and Engineering SRM Institute of Science and TechnologyVadapalani CampusChennai600026Tamil NaduIndia

The increasing use of cloud-based devices has reached the critical point of cybersecurity and unwanted network *** environments pose significant challenges in maintaining privacy and *** approaches,such as iDS,have been developed to tackle these ***,most conventional intrusion Detection System(iDS)models struggle with unseen cyberattacks and complex high-dimensional *** fact,this paper introduces the idea of a novel distributed explainable and heterogeneous transformer-based intrusion detection system,named iNTRUMER,which offers balanced accuracy,reliability,and security in cloud settings bymultiplemodulesworking together within *** traffic captured from cloud devices is first passed to the TC&TM module in which the Falcon Optimization Algorithm optimizes the feature selection process,and Naie bayes algorithm performs the classification of *** selected features are classified further and are forwarded to the Heterogeneous Attention Transformer(HAT)*** this module,the contextual interactions of the network traffic are taken into account to classify them as normal or malicious *** classified results are further analyzed by the Explainable Prevention Module(XPM)to ensure trustworthiness by providing interpretable *** the explanations fromthe classifier,emergency alarms are transmitted to nearby iDSmodules,servers,and underlying cloud devices for the enhancement of preventive *** experiments on benchmark iDS datasets CiCiDS 2017,Honeypots,and NSL-KDD were conducted to demonstrate the efficiency of the iNTRUMER model in detecting network trafficwith high accuracy for different *** outperforms state-of-the-art approaches,obtaining better performance metrics:98.7%accuracy,97.5%precision,96.3%recall,and 97.8%*** results validate the robustness and effectiveness of iNTRUMER in securing diverse cloud environments against sophisticated cyber threats.

关键词： Cloud computing intrusion detection system transformers and explainable artificial intelligence(XAi)

Neuroinflammation revisited through the microglial lens

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Neural Regeneration Research 2025年第7期20卷 1989-1990页

作者： Renato Socodato João b.Relvas institute of Research and innovation in Health(i3S)and institute for Molecular and Cell biology(ibMC) University of PortoPortoPortugal Department of biomedicine Faculty of Medicine of the University of Porto(FMUP)PortoPortugal

Neuroimmunology is emerging as a pivotal field,shedding light on the intricate dialogues between the central nervous system(CNS)and the immune *** exploration is particularly significant in understanding microglia,the CNS’s innate immune cells,beyond the conventional conflation of“neuroinflammation”and“microglial activation.”This conflation has clouded the true complexity of these processes,potentially stalling scientific progress and the development of new *** challenge the long-standing perspectives that have oversimplified these interactions,advocating for a deeper exploration of the dynamic relationship between neuroinflammation and microglial *** dissecting specific molecular pathways,we aim to illuminate their elaborate roles in neuroinflammatory responses,especially in the context of Alzheimer’s disease(AD).Here,neuroinflammation is not merely a passive observer or a direct antagonist but a complex agent in the disease’s *** article calls for a significant paradigm shift towards an integrative,multi-omics approach to *** such a comprehensive framework is crucial for advancing our understanding of neuroinflammatory conditions and paving the way for targeted therapeutic strategies for brain diseases.

关键词： inflammation simplified activation

Coarse to Fine: The Role of Severe Plastic Deformation in Advancing Titanium-based Medical implants - A Comprehensive Review

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 295-306页

作者： Dragana R Mihajlović bojan i Međo ivana Lj Cvijović-Alagić Veljko R Djokić Faculty of Technology and Metallurgy University of BelgradeKarnegijeva 411120 BelgradeSerbia Vinča institute of Nuclear Sci-ences-National institute of the Republic of Serbia University of Belgrade11001BeogradSerbia innovation Centre of the Faculty of Technology and Metallurgy Karnegijeva 411120 BelgradeSerbia

This paper describes severe plastic deformation(SPD)procedures,which are utilized to form an ultrafine-grained structure in metallic *** the SPD process,a solid material sample is subjected to very high loads without a significant change in sample *** the present work,the high-pressure torsion(HPT)process,as one of the SPD techniques,which achieves a high degree of deformation and ensures refinement of the microstructure,will be discussed in more *** that grain size control is accepted as a method to obtain materials with desired characteristics,an overview of the properties of ultrafine-grained titanium-based biomaterials to be used in medicine is ***,particular attention is dedicated to the influences of HPT process parameters,primarily hydrostatic pressure,and number of revolutions during torsion,on the grain size and physical and mechanical characteristics(modulus of elasticity,microhardness,and tensile properties),corrosion resistance,and biocompatibility of the titanium-based biomaterials.A review of the literature indicates that titanium-based materials obtained by the SPD process show improved mechanical and physical properties without losing biocompatibility and corrosion resistance,which suggests that these methods of obtaining implants are something that should be further developed in the future.

关键词： high-pressure torsion process ultrafine-grained titanium-based materials electrochemical anodization physical properties mechanical properties

Federated Learning’s Role in Next-Gen TV Ad Optimization

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Computers, Materials & Continua 2025年第1期82卷 675-712页

作者： Gabriela Dobrita Simona-Vasilica Oprea Adela bâra Department of Economic informatics and Cybernetics Bucharest University of Economic StudiesBucharest010374Romania

in the rapidly evolving landscape of television advertising,optimizing ad schedules to maximize viewer engagement and revenue has become *** methods often operate in silos,limiting the potential insights gained from broader data analysis due to concerns over privacy and data *** article introduces a novel approach that leverages Federated Learning(FL)to enhance TV ad schedule optimization,combining the strengths of local optimization techniques with the power of global Machine Learning(ML)models to uncover actionable insights without compromising data *** combines linear programming for initial ads scheduling optimization with ML—specifically,a K-Nearest Neighbors(KNN)model—for predicting ad spot *** into account the diversity and the difficulty of the ad-scheduling problem,we propose a prescriptivepredictive approach in which first the position of the ads is optimized(using Google’s OR-Tools CP-SAT)and then the scheduled position of all ads will be the result of the optimization ***,this output becomes the target of a predictive task that predicts the position of new entries based on their characteristics ensuring the implementation of the scheduling at large scale(using KNN,Light Gradient boosting Machine and Random Forest).Furthermore,we explore the integration of FL to enhance predictive accuracy and strategic insight across different broadcasting networks while preserving data *** FL approach resulted in 8750 ads being precisely matched to their optimal category placements,showcasing an alignment with the intended diversity ***,there was a minimal deviation observed,with 1133 ads positioned within a one-category variance from their ideal placement in the original dataset.

关键词： Ad scheduling prescriptive-predictive approach federated learning KNN

Multisensory mechanisms of gait and balance in Parkinson’s disease:an integrative review

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Neural Regeneration Research 2025年第1期20卷 82-92页

作者： Stiven Roytman Rebecca Paalanen Giulia Carli Uros Marusic Prabesh Kanel Teus van Laar Nico i.bohnen Department of Radiology University of MichiganAnn ArborMIUSA Department of Neurology University of MichiganAnn ArborMIUSA Morris K.Udall Center of Excellence for Parkinson’s Disease Research University of MichiganAnn ArborMIUSA institute for Kinesiology Research Science and Research Centre KoperKoperSlovenia Department of Health Sciences Alma Mater Europaea–ECMMariborSlovenia Parkinson’s Foundation Research Center of Excellence University of MichiganAnn ArborMIUSA Department of Neurology University of GroningenUniversity Medical Center GroningenGroningenThe Netherlands Neurology Service and GRECC VA Ann Arbor Healthcare SystemAnn ArborMIUSA

Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging *** and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous *** effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory *** mechanisms which underpin the integration of these multisensory signals are the principal topic of the present *** multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older *** emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and *** the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s *** also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older ***,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.

关键词： aging balance encephalography functional magnetic resonance imaging gait multisensory integration Parkinson’s disease positron emission tomography somatosensory vestibular visual

Apolipoprotein A-i binding protein-mediated neuroprotection in glaucomatous neuroinflammation and neurodegeneration

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Neural Regeneration Research 2025年第5期20卷 1414-1415页

作者： Sinwoo Hwang Seunghwan Choi Soo-Ho Choi Keun-Young Kim Yury i.Miller Won-Kyu Ju Hamilton Glaucoma Center and Shiley Eye institute The Viterbi Family Department of OphthalmologyUniversity of California San DiegoLa JollaCAUSA Department of Medicine University of California San DiegoLa JollaCAUSA National Center for Microscopy and imaging Research Department of NeurosciencesUniversity of California San DiegoLa JollaCAUSA

Glaucoma is a multifactorial eye disorder that can cause vision loss and irreversible blindness,affecting individ uals aged 40 to 80 yea rs *** to the aging population,it is expected that the number of people affected by glaucoma will surpass 111 million by 2040 as the disease becomes more *** primarily contributes to optic nerve axon loss and the progressive degeneration of retinal ganglion cells (RGCs),subsequently leading to vision impairment.

关键词： irreversible pass primarily

Prediction of the Resonance Characteristics of Combustion Chambers on the basis of Large-Eddy Simulation

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Journal of Thermal Science 2005年第2期14卷 156-161页

作者： Franco MAGAGNATO balázs PRiTZ horst bCHNER Martin GAbi Department of Fluid Machinery University of Karlsruhe GermanyDepartment of Fluid Machinery University of KarlsruheGermanyEngler-Bunte-Institute/Division for Combustion Technology University of KarlsruheGermanyDepartment of Fluid Machinery University of KarlsruheGermany

in the last few years intensive experimental investigations were performed at the University of Karlsruhe to develop an analytical model for the Helmholtz resonator-type combustion system. in the present work the resonance characteristics of a Helmholtz resonator-type combustion chamber were investigated using large-eddy simulations (LES), to understand better the flow effects in the chamber and to localize the dissipation. in this paper the results of the LES are presented, which show good agreement with the experiments. The comparison of the LES study with the experiments sheds light on the significant role of the wall roughness in the exhaust gas pipe.

关键词： compressible large-eddy simulation combustion instabilities oscillating flow damping ratio.