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Hard carbon derived from coconut shells,walnut shells,and corn silk biomass waste exhibiting high capacity for Na-ion batteries

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Journal of Energy Chemistry 2021年第7期30卷 207-218页

作者： Cristina Nita Biao Zhang Joseph Dentzer camélia matei Ghimbeu Universitéde Haute-Alsace Institut de Science des Matériaux de Mulhouse(IS2M)CNRS UMR 7361F-68100 MulhouseFrance Universitéde Strasbourg F-67081 StrasbourgFrance Center for Advanced Laser Technologies(CETAL) National Institute for LasersPlasma and Radiation PhysicsAtomistilor 409 bisRO-77125 MagureleRomania Department of Applied Physics The Hong Kong Polytechnic UniversityKowloonHong KongChina Réseau sur le Stockage Electrochimique de l’Energie(RS2E) CNRS FR345933 Rue Saint Leu80039 Amiens CedexFrance

In recent years,hard carbon materials have gained significant interest as anode materials for Na-ion *** waste is considered one of the most interesting,renewable,available,and cost-effective precursor to obtain hard carbon(HC);however,HC properties must be finely tuned to achieve performance comparable to those provided by Li-ion *** this work,three biomass wastes(coconut shells,walnut shells,and corn silk) were evaluated as potential precursors for HC preparation involving a pyrolysis process and subsequent acid washing to remove the inorganic *** obtained materials exhibited low and similar specific surface areas(m^(2)·g^(-1)), but they presented different structures and surface *** walnut shell HC possessed a lower amount of inorganic impurities and oxygen-based functional groups compared to the coconut shell and corn silk HCs,leading to higher initial coulombic efficiency(iCE).The structural organization was higher in the case of the walnut shell HC,while the corn silk HC revealed a heterogeneous structure combining both highly disordered carbon and localized graphitized *** HCs delivered high initial reversible capacities between 293 and 315 mAh g^(-1) at 50 mA g^(-1) current rate,which remained rather stable during long-term *** best capacity(293 mAh g^(-1) after 100 charge/discharge cycles) and highest capacity retention(93%) was achieved in walnut HCs in half-cells,which could be associated with its higher sp2 C content,better organized structure,and fewer *** "adsorption-insertion" Na storage mechanism is suggested based on several *** walnut HCs exhibited an attractive energy density of 279 Wh/kg when tested in full cells.

关键词： Biomass Pyrolysis Hard carbon Anode Na-ion batteries Energy storage

Utilizing neural networks to supplant chemical kinetics tabulation through mass conservation and weighting of species depletion

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Energy and AI 2024年第2期16卷 101-110页

作者： Franz m.Rohrhofer Stefan Posch Clemens Gößnitzer Josém.García-Oliver Bernhard C.Geiger Know-Center GmbH Sandgasse 36Graz8010StyriaAustria LEC GmbH Inffeldgasse 19Graz8010StyriaAustria Universitat Politècnica de València Camíde VeraValència46022ValènciaSpain

Artificial Neural Networks(ANNs)have emerged as a powerful tool in combustion simulations to replace memory-intensive tabulation of integrated chemical *** reaction mechanisms,however,present a challenge for standard ANN approaches as modeling multiple species typically suffers from inaccurate predictions on minor *** paper presents a novel ANN approach which can be applied on complex reaction mechanisms in tabular data form,and only involves training a single ANN for a complete reaction *** approach incorporates a network architecture that automatically conserves mass and employs a particular loss weighting based on species *** modifications are used to improve the overall ANN performance and individual prediction accuracies,especially for minor species mass *** validate its effectiveness,the approach is compared to standard ANNs in terms of performance and ANN *** distinct reaction mechanisms(H_(2),C_(7)H_(16),C_(12)H_(26),OmE_(34))are used as a test cases,and results demonstrate that considerable improvements can be achieved by applying both modifications.

关键词： Neural network approach Chemical kinetics Flamelet tabulation mass conservation Species loss weighting

GliomaCNN: An Effective Lightweight CNN model in Assessment of Classifying Brain Tumor from magnetic Resonance Images Using Explainable AI

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Computer modeling in Engineering & Sciences 2024年第9期140卷 2425-2448页

作者： md.Atiqur Rahman mustavi Ibne masum Khan md Hasib m.F.mridha Sultan Alfarhood mejdl Safran Dunren Che Department of Computer Science and Engineering Ahsanullah University of Science and TechnologyDhaka1208Bangladesh Department of Computer Science and Software Engineering The University of Western AustraliaPerthWA 6009Australia Department of Computer Science American International University-BangladeshDhaka1229Bangladesh Department of Computer Science College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia School of Computing Southern Illinois UniversityCarbondale62901USA

Brain tumors pose a significant threat to human lives and have gained increasing attention as the tenth leading cause of global *** study addresses the pressing issue of brain tumor classification using magnetic resonance imaging(mRI).It focuses on distinguishing between Low-Grade Gliomas(LGG)and High-Grade Gliomas(HGG).LGGs are benign and typically manageable with surgical resection,while HGGs are malignant and more *** research introduces an innovative custom convolutional neural network(CNN)model,*** stands out as a lightweight CNN model compared to its *** research utilized the BraTS 2020 dataset for its *** with the gradient-boosting algorithm,GliomaCNN has achieved an impressive accuracy of 99.1569%.The model’s interpretability is ensured through SHapley Additive exPlanations(SHAP)and Gradient-weighted Class Activation mapping(Grad-cam++).They provide insights into critical decision-making regions for classification *** challenges in identifying tumors in images without visible signs,the model demonstrates remarkable performance in this critical medical application,offering a promising tool for accurate brain tumor diagnosis which paves the way for enhanced early detection and treatment of brain tumors.

关键词： Deep learning magnetic resonance imaging convolutional neural networks explainable AI boosting algorithm ablation

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超精密数控机床B旋转轴的可量化对刀方法

清华大学学报（自然科学版） 2014年第11期54卷 1466-1470页

作者： Duong cam Vinh 李朝将李勇高兴清华大学机械工程系精密超精密制造装备及控制北京市重点实验室摩擦学国家重点实验室北京100084

为了提高超精密数控机床旋转B轴的对刀精度和效率,基于3点坐标确定圆心的原理,提出了一种可量化的B旋转轴对刀方法。采用一种非接触式图像识别方式进行精确对刀,可避免对刀过程中金刚石刀具的破损,同时解决刀尖视场与机床坐标不一致的... 详细信息

为了提高超精密数控机床旋转B轴的对刀精度和效率,基于3点坐标确定圆心的原理,提出了一种可量化的B旋转轴对刀方法。采用一种非接触式图像识别方式进行精确对刀,可避免对刀过程中金刚石刀具的破损,同时解决刀尖视场与机床坐标不一致的问题。利用Fresnel透镜模具加工实验验证了对刀精度,并通过激光显微镜检测沟槽里尖角的圆弧半径来确定对刀误差。实验结果表明:该可量化对刀方法的对刀误差为0.8μm,该误差在预先计算的理论误差1μm范围里。该对刀方法适用于超精密切削加工,且对刀的精度可以预测和控制。

关键词：超精密机床 B旋转轴对刀可量化对刀

Biofabrication of nanocomposite-based scaffolds containing human bone extracellularmatrix for the differentiation of skeletal stem and progenitor cells

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Bio-Design and manufacturing 2024年第2期7卷 121-136页

作者： Yang-Hee Kim Janos m.Kanczler Stuart Lanham Andrew Rawlings marta Roldo Gianluca Tozzi Jonathan I.Dawson Gianluca Cidonio Richard O.C.Oreffo Faculty of medicine Bone and Joint Research GroupCentre for Human DevelopmentStem Cells and RegenerationInstitute of Developmental SciencesUniversity of SouthamptonSouthampton SO166YDUK School of Pharmacy and Biomedical Science University of PortsmouthPortsmouth PO12DTUK School of Engineering Faculty of Engineering and ScienceUniversity of GreenwichGreenwich ME44TBUK Center for Life Nano-and Neuro-Science(CLN2S) Italian Institute of Technology00161 RomeItaly

Autograft or metal implants are routinely used in skeletal ***,they fail to provide long-term clinical resolution,necessitating a functional biomimetic tissue engineering *** use of native human bone tissue for synthesizing a biomimeticmaterial inkfor three-dimensional(3D)bioprintingof skeletal tissueis anattractivestrategyfor ***,human bone extracellular matrix(bone-ECm)offers an exciting potential for the development of an appropriate microenvironment for human bone marrow stromal cells(HBmSCs)to proliferate and differentiate along the osteogenic *** this study,we engineered a novel material ink(LAB)by blending human bone-ECm(B)with nanoclay(L,Laponite®)and alginate(A)polymers using extrusion-based *** inclusion of the nanoﬁller and polymeric material increased the rheology,printability,and drug retention properties and,critically,the preservation of HBmSCs viability upon *** composite of human bone-ECm-based 3D constructs containing vascular endothelial growth factor(VEGF)enhanced vascularization after implantation in an ex vivo chick chorioallantoic membrane(cam)*** inclusion of bone morphogenetic protein-2(BmP-2)with the HBmSCs further enhanced vascularization and mineralization after only seven *** study demonstrates the synergistic combination of nanoclay with biomimetic materials(alginate and bone-ECm)to support the formation of osteogenic tissue both in vitro and ex vivo and offers a promising novel 3D bioprinting approach to personalized skeletal tissue repair.

关键词： Extracellular matrix Nanoclay Bone 3D bioprinting

Structural-Adaptation Features of Assimilation Organs of the Species Salsola incanescens cam. in Conditions of Kyzylkum

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American Journal of Plant Sciences 2024年第7期15卷 589-602页

作者： Guli A. Ibrokhimova Guljan m. Duschanova Department of Botany and Plant Physiology National University of Uzbekistan named after Mirzo Ulugbek Tashkent Uzbekistan Department of Botany and Ecology Tashkent State Pedagogical University named after Nizami Tashkent Uzbekistan

The article presents the results of the morpho-anatomical structure of the assimilation organs of the species Salsola leptoclada Gand, which is widespread in the Kyzylkum desert region of Uzbekistan, and reveals the structural, diagnostic and adaptive features. In the assimilation organs, Kranz type of mesophyll was found: in the cotyledons of the Kranz-spherical (Atriplicoid) type, and in the leaf—mesophylls of the Kranz-centric (Salsoloid) and Kranz-ventrodorsal type. These revealed diagnostic features of the assimilating organs of this species in arid conditions noted C4-type photosynthesis. Based on the comparative biometric analysis of quantitative indices of the anatomical features of the assimilating organs, xero-halomorphic features predominate. Halomorphic features are in the cotyledons—thin outer walls of the epidermal cells;few stomata of the anomocytic and paracytic type;few rows of spongy cells (3 - 4 rows);few vascular bundles of the collateral type and xylem, in the leaf—large and thin outer walls of the epidermal cells;succulence of the leaf mesophyll, the presence of aquiferous cells;large palisade, keratin and aquiferous cells. Xeromorphic features in the cotyledons—small and numerous epidermal cells and hemiparacytic type stomata also deep immersion;small palisade cells and a high palisade index, small spongy, hypodermal and keratin cells;small diameter of the xylem in vascular bundles;in the leaf numerous epidermal cells and stomata also deeply immersed;presence and numerous multicellular nodular, dentate trichomes;multi-row water-bearing cells;high palisade index;small and numerous xylem;numerous peripheral vascular bundles of the collateral type. These identified specific diagnostic features showing adaptation to arid conditions can also serve in the identification of plant materials.

关键词： morphology Anatomy Cotyledon Leaf Salsola incanescens South-West Kyzylkum

Personalized nutrition to mitigate inflammation in genetically predisposed individuals: a secondary analysis of the Danish PREVENTOmICS intervention

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Food Science and Human Wellness 2024年

作者： Sebastià Galmés Andreu Palou-march Kristina Pigsborg mona Adnan Aldubayan Sophia m.O.Gormsen Alberto Calleja Joan Trabal Vanesa martínez Biotza Gutiérrez Josep m.Del Bas Faidon magkos Francisca Serra Eurecat， Centre tecnològic de Catalunya， Biotechnology Area Avd Universitat 1 Laboratory of molecular Biology， Nutrition and Biotechnology (Nutrigenomics， Biomarkers and Risk Evaluation-NuBE)， University of the Balearic Islands Health Research Institute of the Balearic Islands (IdISBa) CIBER of Physiopathology of Obesity and Nutrition (CIBEROBN)， Carlos III Health Institute (ISCIII) Alimentómica S.L.， camí de na Pontons.s/n (Pol.11，Parc 3) Department of Nutrition， Exercise and Sports， Faculty of Science， University of Copenhagen Department of Clinical Nutrition， College of Applied medical Sciences， King Saud bin Abdulaziz University for Health Sciences R&D， Food & Culinary Department Simple Feast Leitat Technological Center C/Innovació 2 Creaciones Aromáticas Industriales SA， Cuatrecasas i Arumí， Sant Quirze del Valles

Deep phenotyping and genetic characterization of individuals are fundamental to assessing the metabolic status and determining nutrition-specific requirements. This study aimed to ascertain the utmost effectiveness of personalized interventions by aligning dietary adjustments with both the genotype and metabolotype of individuals. Therefore， we assessed here the usefulness of a polygenic score (PGS) characterizing a potential pro-inflammatory profile (PGSi) as a nutrigenetic tool to discern individuals from the Danish PREVENTOmICS cohort that could better respond to precision nutrition (PN) plans， specifically targeted at counteracting the low-grade inflammatory profile typically found in obesity. The cohort followed a PN plan to counteract the pro-inflammatory profile (PNi group) or generic dietary recommendations (Control) for 10 weeks. PGSi was applied for genetic stratification (Low/High). The effects of the intervention on anthropometrics and biomarkers related to inflammatory profile and carbohydrate metabolism were assessed. Around 30% of subjects had a high genetic predisposition to pro-inflammatory status (high-PGSi). These individuals demonstrated the most effective response to the dietary plan， experiencing improved body composition， with significant decreases in body weight (△: -4.84%; p=0.039) and body fat (△: -4.86%; p=0.007)， and beneficial changes in pro- and anti-inflammatory biomarkers， with significant increases in IL-10 (△: 71.3%; p=0.025) and decreases in TNF-α (△: -3.0%; p=0.048)， CRP (△: -31.1%)， Icam1 (△: -5.8%)， and mCP1 (△: -4.2%) circulating levels， compared to low-PGSi individuals. Both phenotypic and genetic stratification contributed to a better understanding of metabolic heterogeneity in response to diet. This approach allows for refinement of the prediction of individual requirements and potentially for better management of obesity.

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Fabrication and Characterization of Pulp/Chitosan Composite membranes Crosslinked with 3-methylglutaric Anhydride for Pervaporation of Ethanol/Water mixture

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Engineering（科研） 2011年第2期3卷 110-118页

作者： Truong Thi cam Trang Nguyen Thi Nhung Takaomi Kobayashi 不详

Chitosan/Cellulose (CTS/CL) composite membranes were prepared by cross-linking reaction with 3-methy- lglutaric anhydride (3mGA). The cross-linked membranes with CTS/CL were obtained at different CTS con- tents in variations from 50 to 100 wt%, and these membranes were applied in the dehydration of ethanol/wa- ter mixtures. Especially, it was observed that in the case of a composite membrane containing chitosan 80% (CTS/CL-80/20) showed a performance with a separation factor of α = 17.1 and a total permeation flux of J = 326 g/(m2h). It was observed that the total permeation flux decreased when the cross-linking increased and the increase in the ethanol content in the feed solution showed an increase in the separation factor. The CTS/ CL-80/20 showed excellent performance with good mechanical strength and dehydration performance in the ethanol/water mixture separation.

关键词： Pervaporation Chitosan Cellulose Contact Angle Ethanol Composite membrane

Leveraging Robust Artificial Intelligence for mechatronic Product Development—A Literature Review

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International Journal of Intelligence Science 2024年第1期14卷 1-21页

作者： Alexander Nüßgen René Degen marcus Irmer Fabian Richter Cecilia Boström margot Ruschitzka CAD cam Center Cologne Institute of Automotive Engineering Cologne (IFK) Faculty of Automotive Systems and Production Cologne University of Applied Science Cologne Germany Division of Electricity Department of Electrical Engineering Uppsala University Uppsala Sweden

mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.

关键词： Artificial Intelligence mechatronic Product Development Knowledge management Data Analysis Optimization Human Experts Decision-making Processes V-Cycle