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Preliminary results of lithological and palynological study of svobodny,ancient man’s parking relic in Amur region,Russia

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Global Geology 2024年第3期27卷 121-131页

作者： Kovalenko s.V. Kezina T.V. Kryuchko e.I. Mironov M.A. Center for the Preservation of Historical and Cultural Heritage of the Amur Region Blagoveshchensk 675000Russia Amur state University Blagoveshchensk 675027Russia

A single-layer monument svobodny,ancient man's parking lot-1,discovered in 2021 as part of archaeological work to study the zone of economic development of the Amur region was investigated lithologically and *** on the results of geomorphological analysis of the territory,the study of artifacts,palynological data,as well as analogy with previously identified and sufficiently studied relics in the region,the existence of the Osinoozersk late Neolithic culture in this territory is *** time of its expansion in the Amur region is determined within the framework of the second half of theⅣmillennium BC to the first half of theⅡmillennium *** preliminary results of palynological analysis suggest the existence of a temperate climate here,was close to the modern one,which does not contradict the reconstructed paleoclimate and environments of the region during the Holocene period.

关键词： Osinoozersk culture palynological spectra Zeya River paleoclimate

Accuracy comparison and improvement for state of health estimation of lithium-ion battery based on random partial recharges and feature engineering

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Journal of energy Chemistry 2024年第5期92卷 591-604页

作者： Xingjun Li Dan Yu søren Byg Vilsen Daniel Ioan stroe Department of energy Aalborg UniversityAalborg 9220Denmark Department of Mathematical sciences Aalborg UniversityAalborg 9220Denmark Walker Department of Mechanical engineering The University of Texas at AustinAustinTX 78712USA

state of health(sOH)estimation of e-mobilities operated in real and dynamic conditions is essential and *** of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real *** work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based sOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is *** features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding ***,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset *** linear regression(MLR),Gaussian process regression(GPR),and support vector regression(sVR)were applied to estimate sOH,and root mean square error(RMse)was used to evaluate and compare the estimation *** results showed that the feature selection pipeline can improve sOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and sVR *** was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher *** work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on sOH estimation performance and tries to fill the gap of effective sOH estimation between theoretical study and real dynamic application.

关键词： Feature engineering Dynamic forklift aging profile state of health comparison Machine learning Lithium-ion batteries

Thermo-kinetic characteristics on stabilizing hetero-phase interface of metal matrix composites by crystal plasticity finite element method

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Journal of Materials science & Technology 2024年第2期169卷 53-67页

作者： Y.B.Zhang s.J.song F.Liu state Key Laboratory of solidification Processing Northwestern Polytechnical UniversityXi’an 710072China Analytical&Testing Center Northwestern Polytechnical UniversityXi’an 710072China

Using dislocation-based constitutive modeling in three-dimension crystal plasticity finite element(3D CPFe)simulations,co-deformation and instability of hetero-phase interface in different material systems were herein studied for polycrystalline metal matrix composites(MMCs).Local stress and strain fields in two types of 3layer MMCs such as fcc/fcc Cu-Ag and fcc/bcc Cu-Nb have been predicted under simple compressive ***,more severe strain-induced interface instability can be observed in the fcc/bcc systems than in the fcc/fcc systems upon refining to metallic nanolayered composites(MNCs).By detailed analysis of stress and strain localization,it has been demonstrated that the interface instability is always accompanied by high-stress concentration,i.e.,thermodynamic characteristics,or high strain prevention i.e.,kinetic characteristics,at the hetero-phase *** then follows that the thermodynamic driving forceG and the kinetic energy barrier Q during dislocation and shear banding can be adopted to classify the deformation modes,following the so-called thermo-kinetic *** by inserting a high density of high-energy interfaces into the Cu-Nb composites,such thermo-kinetic integration at the hetero-phase interface allows a successful establishment of MMCs with the high△G-high Q deformation mode,which ensures high hardening and uniform strain distri-bution,thus efficiently suppressing the shear band,stabilizing the hetero-phase interface,and obtaining an exceptional combination in strength and *** hetero-phase interface chosen by a couple of thermodynamics and kinetics can be defined as breaking the thermo-kinetic correlation and has been proposed for artificially designing MNCs.

关键词： Thermodynamics and kinetics Physics-based constitutive modeling Hetero-phase interface Crystal plasticity finite element

Orbit Weighting scheme in the Context of Vector space Information Retrieval

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Computers, Materials & Continua 2024年第7期80卷 1347-1379页

作者： Ahmad Ababneh Yousef sanjalawe salam Fraihat salam Al-e’mari Hamzah Alqudah Department of Computer science Faculty of Information TechnologyAmerican University of MadabaAmman11821Jordan Department of Cybersecurity Faculty of Information TechnologyAmerican University of MadabaAmman11821Jordan Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityP.O.Box 346Ajman13306United Arab Emirates Information security Department Faculty of Information TechnologyUniversity of PetraAmman11196Jordan Department of Data science and Artificial Intelligence Faculty of Information TechnologyAmerican University of MadabaAmman11821Jordan

This study introduces the Orbit Weighting scheme(OWs),a novel approach aimed at enhancing the precision and efficiency of Vector space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and *** conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size *** proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing *** research focuses on evaluating OWs’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWs’s effectiveness in reducing the inverted index size,crucial for model *** compare OWs-based retrieval models against others using different schemes,including tf-idf variations and *** reveal OWs’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index *** highlights OWs’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWs’s capabilities in information retrieval methodologies.

关键词： Information retrieval orbit weighting scheme semantic text analysis Tf-Idf weighting scheme vector space model

Towards efficient strain engineering of 2D materials:A four-points bending approach for compressive strain

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Nano Research 2024年第6期17卷 5317-5325页

作者： Hao Li Félix Carrascoso Ana Borrás Gloria P.Moreno Francisco J.Aparicio Ángel Barranco Andrés Castellanos Gómez Campus de Cantoblanco Instituto de Ciencia de Materiales de MadridC.Sor Juana Inés de la Cruz328049 MadridSpain Nanotechnology on surfaces and Plasma Lab Instituto de Ciencia de Materiales de Sevilla(CSIC-Universidad de Sevilla).C/Americo Vespucio 49E-41092 SevilleSpain Departamento de Física Aplicada I Escuela Politécnica SuperiorUniversidad de Sevillac/Virgen deÁfrica 7E-41011 SevilleSpain

strain engineering,as a powerful strategy to tune the optical and electrical properties of two-dimensional(2D)materials by deforming their crystal lattice,has attracted significant interest in recent years.2D materials can sustain ultra-high strains,even up to 10%,due to the lack of dangling bonds on their surface,making them ideal brittle *** remarkable mechanical resilience,together with a strong strain-tunable band structure,endows 2D materials with a broad optical and electrical response upon ***,strain engineering based on 2D materials is restricted by their nanoscale and strain quantification *** this study,we have modified a homebuilt three-points bending apparatus to transform it into a four-points bending apparatus that allows for the application of both compressive and tensile strains on 2D *** approach allows for the efficient and reproducible construction of a strain system and minimizes the buckling effect caused by the van der Waals interaction by adamantane encapsulation *** results demonstrate the feasibility of introducing compressive strain on 2D materials and the potential for tuning their optical and physical properties through this approach.

关键词： uniaxial compressive strain polymer encapsulation differential reflectance spectroscopy exciton tunability

evolution, divergence, and convergence in the mandibles of opossums (Didelphidae, Didelphimorphia)

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Current Zoology 2024年第4期70卷 488-504页

作者： Franciscodas Chagas silva-Neto silvia e.Pavan Diego Astua Laboratorio de Mastozoologia Departamento de ZoologiaUniversidade Federal de Pernambuco.Av.Prof.Moraes Regos.n.Cidade Universitaria.50670-901RecifePEBrazil Department of Biological sciences California State Polytechnic UniversityHumboldt1Harpst StreetArcataCA95521USA

Didelphid marsupials are considered a morphologically unspecialized group with a generalist diet that includes vertebrates,invertebrates,and plant *** cranium and scapula variation has alreadybeen examined within Didelphidae,variation inmandible shape,usually associated with diet or phylogeny in other mammalian groups,has not yet been properly assessed in the *** evaluated the variation in mandible shape and size of didelphids(2470 specimens belonging to 94 species)using 2D geometric *** classified the diet of the didel-phids into four broad categories to assess whether morphospace ordination relates to dietary *** also provided the most comprehensive phylogeny for the family(i23 out of the 126 living species)using 10 nuclear and mitochondrial *** then mapped mandible size and shape onto that phylogeny for 93 selected taxa and ancestral size and shapes were reconstructed by *** found phylogenetically structured variation in mandible morphology between didelphid groups,and our results indicate that they have a significant phylogenetic *** main axis of shape variation is poorly related to size,but the second is strongly allometric,indicating that allometry is not the main factor in shaping morphological diversity on their *** results indicate that the shape and size of the ancestral mandible of didelphids would be similar to that of the current species of the genus Marmosa.

关键词： mandible Didelphimorphia morphological evolution allometry phylogeny diet.

Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields

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Petroleum 2024年第1期10卷 150-164页

作者： Leonardo Goliatt C.M.saporetti L.C.Oliveira e.Pereira Department of Computational and Applied Mechanics Federal University of Juiz de ForaJuiz de ForaBrazil Department of Computational Modeling Polytechnic InstituteRio de Janeiro State UniversityNova FriburgoBrazil Petrobras Rio de JaneiroBrazil Department of stratigraphy and Paleontology Rio de Janeiro State UniversityRio de JaneiroBrazil

Rock samples'TOC content is the best indicator of the organic matter in source *** origin rock samples’analysis is used to calculate it manually by *** method requires time and resources because it relies on samples from many well intervals in source ***,research has been done to aid this *** learning algorithms can estimate total organic carbon instead of well logs and stratigraphic *** light of these efforts,the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and *** algorithms,differential evolution,particle swarm optimization,grey wolf optimization,artificial bee colony,and evolution strategies were used to improve machine learning models to predict *** six metaheuristics were integrated into four machine learning methods:extreme learning machine,elastic net linear model,linear support vector regression,and multivariate adaptive regression *** samples from the YuDong-Nan shale gas field,located in the sichuan basin,were used to evaluate the hybrid *** findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict *** results show that,independent of the metaheuristic used to guide the model selection,optimized extreme learning machines attained the best performance scores according to six *** hybrid models can be used in exploratory geological research,particularly for unconventional oil and gas resources.

关键词： Total organic carbon Hybrid models Automated machine learning evolutionary algorithms Geology

Descriptors-based machine-learning prediction of cetane number using quantitative structure–property relationship

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energy and AI 2024年第3期17卷 168-178页

作者： Rodolfo s.M.Freitas Xi Jiang school of engineering and Materials science Queen Mary University of LondonMile End RoadLondonE14NSUK

The physicochemical properties of liquid alternative fuels are important but difficult to measure/predict, especially when complex surrogate fuels are concerned. In the present work, machine learning is used to develop quantitative structure–property relationship models. The fuel chemical structure is represented by molecular descriptors, allowing the linking of important features of the fuel composition and key properties of fuel utilization. Feature selection is employed to select the most relevant features that describe the chemical structure of the fuel and several machine learning algorithms are tested to construct interpretable models. The effectiveness of the methodology is demonstrated through the development of accurate and interpretable predictive models for cetane numbers, with a focus on understanding the link between molecular structure and fuel properties. In this context, matrix-based descriptors and descriptors related to the number of atoms in the molecule are directly linked with the cetane number of hydrocarbons. Furthermore, the results showed that molecular connectivity indices play a role in the cetane number for aromatic molecules. Also, the methodology is extended to predict the cetane number of ester and ether molecules, leveraging the design of alternative fuels towards fully sustainable fuel utilization.

关键词： Chemical descriptors Quantitative structure-property relationship Machine learning Cetane number Fuel design

Modern treatment of gastric gastrointestinal stromal tumors

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World Journal of Gastroenterology 2012年第46期18卷 6720-6728页

作者： Kevin K Roggin Mitchell C posner Department of surgery Pritzker School of Medicine University of Chicago

Gastrointestinal stromal tumors (GIsT) are rare mesenchymal smooth muscle sarcomas that can arise anywhere within the gastrointestinal tract. sporadic mutations within the tyrosine kinase receptors of the interstitial cells of Cajal have been identified as the key molecular step in GIsT carcinogenesis. Although many patients are asymptomatic, the most common associated symptoms include: abdominal pain, dyspepsia, gastric outlet obstruction, and anorexia. Rarely, GIsT can perforate causing life-threatening hemoperitoneum. Most are ultimately diagnosed on cross-sectional imaging studies (i.e., computed tomography and/or magnetic resonance imaging in combination with upper endoscopy. endoscopic ultrasonographic localization of these tumors within the smooth muscle layer and acquisition of neoplastic spindle cells harboring mutations in the c-KIT gene is pathognomonic. Curative treatment requires a complete gross resection of the tumor. Both open and minimally invasive operations have been shown to reduce recurrence rates and improve long-term survival. While there is considerable debate over whether GIsT can be benign neoplasms, we believe that all GIsT have malignant potential, but vary in their propensity to recur after resection and metastasize to distant organ sites. Prognostic factors include location, size (i.e., > 5 cm), grade (> 5-10 mitoses per 50 high power fields and specific mutational events that are still being defined. Adjuvant therapy with tyrosine kinase inhibitors, such as imatinib mesylate, has been shown to reduce the risk of recurrence after one year of therapy. Treatment of locally-advanced or borderline resectable gastric GIsT with neoadjuvant imatinib has been shown to induce regression in a minority of patients and stabilization in the majority of cases. This treatment strategy potentially reduces the need for more extensive surgical resections and increases the number of patients eligible for curative therapy. The modern surgical treatment of

关键词： Gastrointestinal stromal tumors Laparoscopic resections of gastrointestinal stromal tumors Imatinib mesylate Gastrectomy