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Prospects on mangrove knowledge services in the smart era: From plant atlas to knowledge graphs

science China Earth sciences 2025年第1期68卷 111-127页

作者： Zhi-Wei HOU Wenlong JING Cheng-Zhi QIN Ji YANG Qing XIA Xiaoling YIN Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangdong Academy of Sciences Southern Marine science and Engineering Guangdong Laboratory (Guangzhou) State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences College of Resources and Environment University of Chinese Academy of Sciences School of Traffic & Transportation Engineering Changsha University of Science and Technology

Mangroves are crucial to the ecological security of the Earth and human well-being. Their management, conservation, and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplinary knowledge such as biology and ecology. Traditional knowledge services such as plant atlas provide illustrated textual knowledge of mangroves. However, this kind of service is oriented to information retrieval and is incapable of effectively mining and utilizing fragmented knowledge from multi-source heterogeneous data, facing the problem of “massive data, rare knowledge”. Knowledge graphs are capable of extracting, organizing, and fusing the knowledge contained in massive data into semantic networks that can be understood and computed by computers. They provide a solution for the realization of intelligent knowledge services. Focusing on the urgent need for mangrove knowledge acquisition, formal representation, and intelligent services, this paper proposes a research prospect on mangrove knowledge graphs and knowledge services. We first analyze the similarities and differences between various domain-specific concepts of Tupu. On this basis, we define the mangrove knowledge graph as a large-scale knowledge base that integrates multi-disciplinary knowledge and spatio-temporal information with mangrove ecosystems as the core. Then, we propose a research framework for mangrove knowledge services that can realize the transformation from multi-modal data to intelligent knowledge services, including multiple research levels such as ubiquitous data sensing and aggregation, knowledge organization and graph construction, and intelligent mangrove knowledge services. Subsequently, the methods and workflow for constructing mangrove knowledge graphs are introduced. Finally, we discuss the challenges and possible future directions of mangrove knowledge services in the smart era, including the construction of a mangrove knowledge system that integra

关键词： Mangrove Tupu Knowledge graph Multi-modal Knowledge service

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Targets capture by distributed active swarms via bio-inspired reinforcement learning

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science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University institute of Nuclear and New Energy technology Tsinghua University Shanghai Aerospace Control technology institute Shanghai Key Laboratory of Aerospace Intelligent Control technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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Inexact proximal gradient algorithm with random reshuffling for nonsmooth optimization

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science China(Information sciences) 2025年第1期68卷 219-237页

作者： Xia JIANG Yanyan FANG Xianlin ZENG Jian SUN Jie CHEN National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of Technology Beijing institute of technology Chongqing Innovation Center School of Electronic and Information Engineering Tongji University

Proximal gradient algorithms are popularly implemented to achieve convex optimization with nonsmooth regularization. Obtaining the exact solution of the proximal operator for nonsmooth regularization is challenging because errors exist in the computation of the gradient; consequently, the design and application of inexact proximal gradient algorithms have attracted considerable attention from researchers. This paper proposes computationally efficient basic and inexact proximal gradient descent algorithms with random reshuffling. The proposed stochastic algorithms take randomly reshuffled data to perform successive gradient descents and implement only one proximal operator after all data pass through. We prove the convergence results of the proposed proximal gradient algorithms under the sampling-without-replacement reshuffling *** computational errors exist in gradients and proximal operations, the proposed inexact proximal gradient algorithms can converge to an optimal solution neighborhood. Finally, we apply the proposed algorithms to compressed sensing and compare their efficiency with some popular algorithms.

关键词： proximal operator random reshuffling inexact computation compressed sensing nonsmooth optimization

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Multicomponent polymerization of elemental sulfur,difluoromethylene phosphobetaine and aryl silyl ethers toward aromatic poly(O,O′-monothiocarbonate)s

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science China Chemistry 2025年

作者： Yongjiang Yu Rongrong Hu Ben Zhong Tang State Key Laboratory of Luminescent Materials and Devices Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates South China University of Technology School of science and Engineering Shenzhen Institute of Aggregate Science and Technology The Chinese University of Hong Kong AIE institute

Polythiocarbonates with similar structures to polycarbonates, have emerged as a group of promising sulfur-containing polymers with a range of practical applications, taking advantages of their excellent optical properties, good thermal stability and filmforming ability, and so on. However, the synthesis of polythiocarbonates generally suffered from mixed isomeric structures of repeating units, and hazardous sulfur-containing reagents. In this work, an efficient multicomponent reaction of elemental sulfur,difluoromethylene phosphobetaine（PDFA）, and aryl silyl ethers was designed with the assistance of organic base 7-methyl-1,5,7-triazabicyclo[4.4.0]dec-5-ene（MTBD） to produce 12 kinds of O,O′-monothiocarbonate compounds in up to 93% yields,taking advantages of the unique chemical property of difluorocarbene, and the deprotection of silyl group by F-generated from PDFA. Most importantly, the MTBD-assisted multicomponent polymerization of bis（aryl silyl ether）s, elemental sulfur, and PDFA was developed, affording 12 kinds of poly（O,O′-monothiocarbonate）s with well-defined structures, high Mws of up to16900 g/mol and high yields（up to 99%）. These poly（O,O′-monothiocarbonate）s possessed good film-forming properties and thermal stability, high light refractive indices and transmittance. The facile synthesis of these polymonothiocarbonates might pave the way for the development of promising sulfur-containing polymer materials.

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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

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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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Robust interface and excellent as-built mechanical properties of Ti–6Al–4V fabricated through laser-aided additive manufacturing with powder and wire

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 154-168页

作者： Fei Weng Guijun Bi Youxiang Chew Shang Sui Chaolin Tan Zhenglin Du Jinlong Su Fern Lan Ng Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials Ministry of EducationShandong Engineering&Technology Research Center for Superhard MaterialSchool of Materials Science and EngineeringShandong UniversityJinan 250061China institute of Intelligent Manufacturing Guangdong Academy of SciencesGuangzhou 510095China Singapore institute of Manufacturing technology 5 Cleantech Loop636732Singapore

The feasibility of manufacturing Ti-6Al-4V samples through a combination of laser-aided additive manufacturing with powder(LAAM_(p))and wire(LAAM_(w))was explored.A process study was first conducted to successfully circumvent defects in Ti-6Al-4V deposits for LAAM_(p) and LAAM_(w),*** the optimized process parameters,robust interfaces were achieved between powder/wire deposits and the forged substrate,as well as between powder and wire *** characterization results revealed the epitaxial prior β grains in the deposited Ti-6Al-4V,wherein the powder deposit was dominated by a finerα′microstructure and the wire deposit was characterized by lamellar α *** mechanisms of microstructure formation and correlation with mechanical behavior were analyzed and *** mechanical properties of the interfacial samples can meet the requirements of the relevant Aerospace Material Specifications(AMS 6932)even without post heat *** fracture occurred within the interfacial area,further suggesting the robust *** findings of this study highlighted the feasibility of combining LAAM_(p) and LAAM_(w) in the direct manufacturing of Ti-6Al-4V parts in accordance with the required dimensional resolution and deposition rate,together with sound strength and ductility balance in the as-built condition.

关键词： laser-aided additive manufacturing powder deposition wire deposition interfacial characteristic mechanical behavior

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Accurate quantification of the algebraic,multiplicative algebraic,and simultaneous iterative reconstruction techniques in ionosphere rebuilding based on the TIEGCM assessment

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Earth and Planetary Physics 2025年第1期9卷 117-126页

作者： Ao Qi HaiBing Ruan institute of Space Weather Nanjing University of Information Science and TechnologyNanjing 210044China Key Laboratory of Geospace Environment University of Science&Technology of ChinaChinese Academy of SciencesHefei 230026China

The algebraic reconstruction technique(ART),multiplicative algebraic reconstruction technique(MART),and simultaneous iterative reconstruction technique(SIRT)are computational methodologies extensively utilized within the field of computerized ionospheric tomography(CIT)to facilitate three-dimensional reconstruction of the ionospheric ***,reconstruction accuracy elicits recurrent disputes over its practical application,and people usually attribute this issue to incomplete and uneven coverage of the *** Thermosphere Ionosphere Electrodynamics General Circulation Model(TIEGCM)offers a reasonable physics-based ionospheric background and is widely utilized in ionospheric *** use the TIEGCM simulations as the targeted ionosphere because the current measurements are far from able to realistically reproduce the ionosphere in *** designations of satellite measurements are conducted to investigate the limiting performance of CIT methods in ionospheric *** to common practice,electron density distributions from outputs of the International Reference Ionosphere(IRI)model are used as the iterative initial value in CIT *** outcomes suggest that despite data coverage,iterative initial conditions also play an essential role in ionospheric *** particular,in the longitudinal sectors where the iterative initial height of the F2-layer peak electron density(hmF2)differs substantially from the background densities,none of the three CIT methods can reproduce the exact background *** hmF2 is close but the ionospheric F2-layer peak density(NmF2)is different between the targeted background and initial conditions,the MART performs better than the ART and SIRT,as evidenced by the correlation coefficients of MART being above 0.97 and those of ART and SIRT being below *** summary,this investigation reveals the potential uncertainties in traditional CIT reconstruction,particularly when reali

关键词： computerized ionospheric tomography International Reference Ionosphere model Thermosphere Ionosphere Electrodynamics General Circulation model ionosphere

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Aerodynamic Optimization and Flow Mechanism for a Compressor Cascade at Low Reynolds Number

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Journal of Thermal science 2025年第1期34卷 92-109页

作者： LI Lin ZHANG Jianshe CHEN Caiyan TAN Wei ZHANG Yanfeng Key Laboratory of Light-Duty Gas-Turbine Institute of Engineering ThermophysicsChinese Academy of Sciences University of Chinese Academy of sciences National Key Laboratory of science and technology on Advanced Light-duty Gas-turbine

Low-Reynolds-number effect is an important factor affecting the performance of compressors and other main components of high-altitude long-endurance unmanned aerial *** improve the flow condition and reduce flow loss under the condition of high altitude and low Reynolds number(Re),this paper proposes an optimization process based on a surrogate model,which combines the class-shape transformation method(CST),the Latin hypercube sampling(LHS) method,the light gradient-boosting machine algorithm(LightGBM),and a genetic algorithm(GA) to optimize a high-subsonic compressor *** surrogate model is verified to be accurate and can be used in the optimization *** accuracy of the GA is higher than the other algorithms under common test *** optimization results are verified by numerical simulation,and the flow differences before and after optimization are compared,especially the flow within the boundary *** changing the blade shape,the optimization process adjusts the loading distribution to delay the transition of the optimized blade on the suction surface,which changes the turbulent reattachment in the laminar separation bubble(LSB) into laminar ***,the mixing loss induced by the turbulent reattachment of the LSB and the wake loss of turbulent separation at the trailing edge are significantly reduced,and the performance of the compressor profile is finally *** addition,turbulent separation of the optimized profile is delayed reducing the range of the wake region on the suction *** this optimization process,the reduction of total pressure loss coefficient at Re of 2.5×10～5,3.5×10～5,and 4.5×10～5 are 16.32%,20.76%,and 22.16%,respectively.

关键词： Reynolds number

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Optimizing Fine-Tuning in Quantized Language Models:An In-Depth Analysis of Key Variables

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Computers, Materials & Continua 2025年第1期82卷 307-325页

作者： Ao Shen Zhiquan Lai Dongsheng Li Xiaoyu Hu National Key Laboratory of Parallel and Distributed Computing National University of Defense TechnologyChangsha410073China Strategic Assessments and Consultation institute Academy of Military ScienceBeijing100091China

Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning *** this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader ***-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational *** these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA *** these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains *** study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM *** investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do *** insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized ***,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller *** study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM

关键词： Large-scale Language Model Parameter-Efficient Fine-Tuning parameter quantization key variable trainable parameters experimental analysis

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