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Journal of Earth Science 2024年第5期35卷 1426-1446页

作者： Jintao Kong Zhongjie Xu Rihui Cheng Duo Wan College of Earth Sciences Jilin UniversityChangchun 130061China Key Laboratory of Mineral Resources Evaluation in northeast asia Ministry of Natural and ResourcesChangchun 130061China

During the Late Paleozoic-Early Mesozoic Era,the sediment transport system and tectonic regime in the southeastern margin of the South China Block(SESCB)all changed,significantly affected by the Paleo-pacific ***,controversy exists about the Paleo-pacific subduction's initiation *** study uses detrital zircon U-Pb ages to discuss the Late Triassic source-tosink system in the *** provides some references for the Paleo-pacific subduction process based on crucial age information and zircons'trace *** paleogeography and similarity of detrital zircon age distribution indicate that three sinks were found in the SESCB during the Late Triassic:*** Yangchun-Kaiping-Gaoming area,comprising major age ranges of 260-220,460-400,and 1200-800 Ma,which might be sourced from the Yunkai terrane;*** Jiexi-Kanshi-Nanjing area,characterized by the significant age component of 2000-1800 Ma,which corresponded to the Wuyi terrane;*** Xinan area,consisting of significant age groups of 290-250 and 380-320 Ma,which might be sourced from the magmatic rocks formed by the Huinan Movement and Paleo-pacific *** that 290-250 Ma zircons were widely distributed in the Upper Triassic strata,and their trace elements suggested the existence of a magmatic arc near the SESCB during the 290-250 ***,we propose that the Paleo-pacific subduction might have begun in the Early Permian.

关键词： detrital zircon geochronology South China Block Paleo-pacific Block provenance analysis geochronology geochemistry

Characteristics of Multi-Objective Linear Programming Problem and Multi-Objective Linear Fractional Programming Problem Taking Maximum Value of Multi-Objective Functions

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Applied Mathematics 2024年第1期15卷 22-32页

作者： Samsun Nahar Md. Asadujjaman Khadiza Begum Mahede-Ul-Hassan Md. Abdul Alim Department of Basic Sciences and Humanities University of Asia Pacific Dhaka Bangladesh Department of Mathematics University of Dhaka Dhaka Bangladesh Computer Science and Engineering Department Prime University Dhaka Bangladesh Department of Mathematics and Statistics Bangladesh University of Business and Technology Dhaka Bangladesh Department of Mathematics Bangladesh University of Engineering and Technology Dhaka Bangladesh

In this paper, a new statistical averaging technique is proposed for finding an optimal solution to a multi-objective linear fractional programming problem (MOLFPP) and multi-objective linear programming problem (MOLPP) by using new arithmetic averaging method and new geometric averaging method. It is significantly noticeable same characteristics among all the technique while taking maximum or minimum among all optimized values for multi-objective functions using simplex algorithm. The characteristics provided from the problems are verified by the numerical examples.

关键词： MOLPP MOLFPP New Arithmetic Averaging Method New Geometric Averaging Method

New PAMA Technology Helps Tackle the New Challenges of China Automotive Sector

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润滑油 2010年第1期25卷 31-38页

作者： Alex Tsay Evonik RohMax asia pacific pte.ltd

Polyalkylmethacrylate (PAMA) based viscosity index improver (VII) and pour point depressant (PPD), with the versatile chemistry and unique performance characteristics, are widely used in advanced formulations, enabling fluids to meet rheological requirement of modern specifications. This paper will be dedicated to the application of PAMA in helping China automotive lubricant formulators tackle the challenges of improving fuel economics from using lower viscosity fluids, of better protection strengthten in transmission performance and meeting new global specifications for low temperature performance.

关键词： polyalkylmethacrylate viscosity index improver pour point depressant automatic transmission fluid gear oil ROBO test

Advancing space-based gravitational wave astronomy: Rapid parameter estimation via normalizing flows

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Science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 20-33页

作者： Minghui Du Bo Liang He Wang Peng Xu Ziren Luo Yueliang Wu Center for Gravitational Wave Experiment National Microgravity LaboratoryInstitute of MechanicsChinese Academy of SciencesBeijing 100190China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of SciencesShanghai 201800China International Centre for Theoretical Physics asia-pacific University of Chinese Academy of SciencesBeijing 100049China Taiji Laboratory for Gravitational Wave Universe(Beijing/Hangzhou) University of Chinese Academy of SciencesBeijing 100049China Lanzhou Center of Theoretical Physics Lanzhou UniversityLanzhou 730000China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310024China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China

Gravitational wave(GW) astronomy is witnessing a transformative shift from terrestrial to space-based detection, with missions like Taiji at the forefront. While the transition brings unprecedented opportunities for exploring massive black hole binaries(MBHBs), it also imposes complex challenges in data analysis, particularly in parameter estimation amidst confusion *** this gap, we utilize scalable normalizing flow models to achieve rapid and accurate inference within the Taiji environment. Innovatively, our approach simplifies the data's complexity, employs a transformation mapping to overcome the year-period time-dependent response function, and unveils additional multimodality in the arrival time parameter. Our method estimates MBHBs several orders of magnitude faster than conventional techniques, maintaining high accuracy even in complex backgrounds. These findings significantly enhance the efficiency of GW data analysis, paving the way for rapid detection and alerting systems and enriching our ability to explore the universe through space-based GW observation.

关键词： Taiji program gravitational wave detection parameter estimation machine learning

String Cosmological Models in Five-Dimensional Spacetimes

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Chinese Physics Letters 2009年第1期26卷 40-42页

作者： Sanjay Oli Department of Applied Mathematics Asia-Pacific Institute of Information Technology Panipat India

We present some classes of solutions for dust matter coupled to the string cloud in five-dimensional Kaluza-Klein spacetimes. The solutions have one or two distinct singularities depending upon the sign of the constant of integration. Some of the classes of models exhibit inflation in the initial stage. The behaviour of associated parameters has been discussed in detail.

关键词： field emission molybdenum dioxide enhancement factor

2023: Weather and Climate Extremes Hitting the Globe with Emerging Features

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Advances in Atmospheric Sciences 2024年第6期41卷 1001-1016页

作者： Wenxia ZHANG Robin CLARK Tianjun ZHOU Laurent LI Chao LI Juan RIVERA Lixia ZHANG Kexin GUI Tingyu ZHANG Lan LI Rongyun PAN Yongjun CHEN Shijie TANG Xin HUANG Shuai HU State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Met Office Hadley Centre Exeter EX13PBUK University of Chinese Academy of Sciences Beijing 100049China Laboratoire de Météorologie Dynamique CNRSSorbonne UniversitéEcole Normale SupérieureEcole PolytechniqueParis 75230France Max Planck Institute for Meteorology Hamburg 20146Germany Instituto Argentino de Nivología Glaciología Y Ciencias Ambientales(IANIGLA)CCT CONICETMendoza CP 5500Argentina Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030China asia-pacific Typhoon Collaborative Research Center Shanghai 201306China

Globally,2023 was the warmest observed year on record since at least 1850 and,according to proxy evidence,possibly of the past 100000 *** in recent years,the record warmth has again been accompanied with yet more extreme weather and climate events throughout the ***,we provide an overview of those of 2023,with details and key background causes to help build upon our understanding of the roles of internal climate variability and anthropogenic climate *** also highlight emerging features associated with some of these extreme *** extremes are occurring earlier in the year,and increasingly simultaneously in differing parts of the world(e.g.,the concurrent hot extremes in the northern Hemisphere in July 2023).Intense cyclones are exacerbating precipitation extremes(e.g.,the north China flooding in July and the Libya flooding in September).Droughts in some regions(e.g.,California and the Horn of Africa)have transitioned into flood *** extremes also show increasing interactions with ecosystems via wildfires(e.g.,those in Hawaii in August and in Canada from spring to autumn 2023)and sandstorms(e.g.,those in Mongolia in April 2023).Finally,we also consider the challenges to research that these emerging characteristics present for the strategy and practice of adaptation.

关键词： weather and climate extremes temperature extremes extreme precipitation drought wildfires

Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

Experimental Investigations of Various Methods of Sludge Measurements in Storage Oil Tanks

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Advances in Remote Sensing 2015年第2期4卷 119-137页

作者： Manuel Monteiro Victor Svet Donald Sandilands Sergey Tsysar International Tank Services (asia pacific) pte ltd. Singapore Singapore

This article describes the results of experimental studies into various methods of measuring sludge volume and its 3D spatial distribution using a base of data received from the inspection of more than 30 storage tanks of different types: external floating roof, internal floating roof and fixed roof. The advantages and disadvantages of making measurements with existing methods are discussed, including the problem of accuracy. Numerous examples of tank survey results are presented.

关键词： Storage Tanks Sludge Volume of Sludge Acoustic Bathymetry Thermography

Tailor-Made PAMA VII to Optimize Automatic Transmission Fluid Rheological Requirements

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润滑油 2008年第2期23卷 27-32页

作者： Alex Tsay Bernard Kinker Evonik RohMax asia-pacific pte.ltd. Evonik RohMax USA

There are three predominant aspects of the rheological requirements: maximum possible high temperature thickening,minimum possible low-temperature thickening,and high shear stability for automatic transmission *** temperature thickening by VI improvers is largely a function of molecular size and high solubility to give extended polymer coil *** the other hand,the desirable characteristic of minimum low-temperature thickening is a function of somewhat the opposite characteristic;namely relatively poor solubility leading to minimal polymer coil size and thus low viscosity *** addition to not thickening fluids at cold temperatures VI improvers should also provide control of wax-gelation which,if unfettered,can lead to congealed *** the third property of high shear stability is in direct conflict with the desirable characteristic of large molecular size for effective high temperature *** this paper we shall attempt to sort out these conflicting properties and provide some insight into how we approach design of VI improvers for the highly demanding world of automatic transmission fluid rheology.

关键词：自动传动液润滑剂稳定性低温流最优化流变学特制

The Peculiarities of Acoustical Monitoring of Moving Objects in Shallow Water Areas

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Open Journal of Acoustics 2014年第3期4卷 145-154页

作者： Manel Monteiro Victor Svet Donald Sandilands International Tank Services (asia pacific) pte ltd. Singapore City Singapore

The article considers peculiarities of underwater monitoring of moving objects in the shallow water areas, particularly seaports. These areas are characterized by a multitude of factors influencing the efficiency of detection. Nonstationarity conditions of sound propagation and specific interference caused by shipping are the major factors. The various algorithms for the space-time signal processing have been tested and some experimental results are presented. It has been shown that the use of clipped mode in conjunction with the correlation processing of wideband signals and subsequent speckle tracking allow realizing high efficiency of monitoring.

关键词： Acoustical Underwater Monitoring Shallow Water Areas Multi-Ray Propagation Correlation Processing Speckle-Tracking