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Elite Dung Beetle Optimization Algorithm for Multi-UAV Cooperative Search in Mountainous Environments

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Journal of Bionic engineering 2024年第4期21卷 1677-1694页

作者： Xiaoyong Zhang Wei Yue The college of marine Electrical engineering Dalian Maritime UniversityDalian116026China

This paper aims to address the problem of multi-UAV cooperative search for multiple targets in a mountainous environment,considering the constraints of UAV dynamics and prior environmental ***,using the target probability distribution map,two strategies of information fusion and information diffusion are employed to solve the problem of environmental information inconsistency caused by different UAVs searching different areas,thereby improving the coordination of UAV ***,the task region is decomposed into several high-value sub-regions by using data clustering *** on this,a hierarchical search strategy is proposed,which allows precise or rough search in different probability areas by adjusting the altitude of the aircraft,thereby improving the search ***,the Elite Dung Beetle Optimization Algorithm(EDBOA)is proposed based on bionics by accurately simulating the social behavior of dung beetles to plan paths that satisfy the UAV dynamics constraints and adapt to the mountainous terrain,where the mountain is considered as an obstacle to be ***,the objective function for path optimization is formulated by considering factors such as coverage within the task region,smoothness of the search path,and path *** effectiveness and superiority of the proposed schemes are verified by the simulation.

关键词： Mountainous environment Multi-UAV cooperative search Environment information consistency Elite dung beetle optimization algorithm(EDBOA) Path planning

Facet effects on bimetallic ZnSn hydroxide microcrystals for selective electrochemical CO2 reduction

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Green Energy & Environment 2024年第8期9卷 1314-1320页

作者： Liu Han Cheng-wei Wang Shan-shan Luo Ying-tang Zhou Bing Li Ming Liu School of Chemistry and Chemical engineering Harbin Institute of Technology National engineering Research Center for marine Aquaculture Marine Science and Technology CollegeZhejiang Ocean University

Employing crystal facets to regulate the catalytic properties in electrocatalytic carbon dioxide reduction reaction（eCO2RR） has been well demonstrated on electrocatalysts containing single metals but rarely explored for bimetallic systems. Here, we synthesize Zn Sn（OH）6（ZSO）microcrystals（MCs） with distinct facets and investigate the facet effects in eCO2RR. Electrochemical studies and in situ Fourier Transform Infrared Spectroscopy（in situ-FTIR） reveal that ZSO MCs produce mainly C1 products of HCOOH and CO. The {111} facet of the ZSO MCS exhibits higher selectivity and faradaic efficiency（FE） than that of the {100} facet over a wide range of potentials（-0.9 V ～-1.3 V versus RHE）. Density Functional Theory（DFT） calculations elucidate that the {111} facet is favorable to the adsorption/activation of CO2molecules,the formation of intermediate in the rate-determining step, and the desorption of C1 products of CO and HCOOH molecules.

关键词： ZnSn(OH) 6 Crystal facets Electrochemical carbon dioxide reduction C1 product Density functional theory

Advances in Biomedical Applications of Hydrogels from Seaweed-Derived Sulfated Polysaccharides:

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Journal of Ocean University of China 2024年第5期23卷 1329-1346页

作者： CUI Zhiyong JIANG Fei LI Luxi CHI Zhe LIU Chenguang college of marine Life sciences Ocean University of China

Sulfated polysaccharides extracted from seaweeds, including Carrageenan, Fucoidan and Ulvan, are crucial bioactive compounds known for their diverse beneficial properties, such as anti-inflammatory, antitumor, immunomodulatory, antiviral, and anticoagulant effects. These polysaccharides form hydrogels hold immense promise in biomedicine, particularly in tissue engineering, drug delivery systems and wound healing. This review comprehensively explores the sources and structural characteristics of the three important sulfated polysaccharides extracted from different algae species. It elucidates the gelation mechanisms of these polysaccharides into hydrogels. Furthermore, the biomedical applications of these three sulfated polysaccharide hydrogels in wound healing, drug delivery, and tissue engineering are discussed, highlighting their potential in the biomedicine.

关键词： biomaterials in medical applications hydrogels seaweed sulfated polysaccharides

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-Qiang Yang Nian-Tian Lin Kai Zhang Yan Cui Chao Fu Dong Zhang college of Earth sciences and engineering Shandong University of Science and Technology Laboratory for marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

Lipase and photodecarboxylase coexpression: A potential strategy for alkane-based biodiesel production from natural triglycerides

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Chinese Journal of Chemical engineering 2024年第3期67卷 238-246页

作者： Yong-Yi Zeng Xin-Yi Xu Jin-Xuan Xie Wen-Li Chen Lan Liu Xin-Jian Yin Bi-Shuang Chen School of marine sciences Sun Yat-Sen UniversityZhuhai 519080China Southern marine Science and engineering Guangdong Laboratory(Zhuhai) Zhuhai 519080China

Alkane-based biodiesel is considered the next generation of biodiesel owing to its potential environmental benefits and the fact that it exhibits much higher specific caloric values than traditional ***,the formidable obstacle impeding the commercialization of this cutting-edge fuel alternative lies in the cost associated with its *** this study,an engineered strain Escherichia coli(***)showcasing harmonized coexpression of a lipase(from Thermomyces lanuginosus lipase,TLL)and a fatty acid photodecarboxylase(from Chlorella variabilis,CvFAP)was first constructed to transform triglycerides into *** potential of *** BL21(DE3)/pRSFDuet-1-TLL-CvFAP for alkane synthesis was evaluated with tripalmitin as a model substrate under various process *** a comprehensive examination of the reaction parameters,the scope of the biotransformation was expanded to‘real’substrates(vegetable oils).The results showed that bioderived oils can be transformed into alkanes with high yields(0.80-10.20 mmol·L^(-1))under mild conditions(35℃,pH 8.0,and 36 h)and blue light *** selected processes were performed on an increased lab scale(up to 100 ml)with up to 24.77 mmol·L^(-1) tripalmitin,leading to a yield of 18.89 mmol·L^(-1) *** the employment of a method for efficiently producing alkanes under mild conditions and a simple procedure to isolate alkanes from the reaction system,the utilization of sustainable biomass as a fundamental feedstock emerges as the primary solution to lower the cost of alkane-based ***,this study proposes a readily implementable and highly effective approach for alkane-based biodiesel production.

关键词： Alkane-based biodiesel Renewable biomass Co-overexpression Lipase Photodecarboxylase

Heteroatom tuning in agarose derived carbon aerogel for enhanced potassium ion multiple energy storage

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Carbon Energy 2024年第3期6卷 239-254页

作者： Kaijun Xie Xin Liu Haolin Li Long Fang Kai Xia Dongjiang Yang Yihui Zou Xiaodong Zhang State Key Laboratory of Bio-fibers and Eco-textiles Shandong Collaborative Innovation Center of Marine Biobased Fibers and Ecological TextilesInstitute of Marine Biobased MaterialsCollege of Chemistry and Chemical EngineeringCollege of Environmental Science and EngineeringQingdao UniversityQingdaoChina

The incorporation of heteroatoms into carbon aerogels(CAs)can lead to structural distortions and changes in active sites due to their smaller size and electronegativity compared to pure ***,the evolution of the electronic structure from single-atom doping to heteroatom codoping in CAs has not yet been thoroughly investigated,and the impact of codoping on potassium ion(K+)storage and diffusion pathways as electrode material remains *** this study,experimental and theoretical simulations were conducted to demonstrate that heteroatom codoping,composed of multiple heteroatoms(O/N/B)with different properties,has the potential to improve the electrical properties and stability of CAs compared to single-atom *** states near the Fermi level have revealed that doping with O/N/B generates a greater number of active centers on adjacent carbon atoms than doping with O and O/N *** a result of synergy with enhanced wetting ability(contact angle of 9.26°)derived from amino groups and hierarchical porous structure,ON-CA has the most optimized adsorption capacity(−1.62 eV)and diffusion barrier(0.12 eV)of K^(+).The optimal pathway of K^(+)in ON-CA is along the carbon ring with N or O *** K^(+)storage material for supercapacitors and ion batteries,it shows an outstanding specific capacity and capacitance,electrochemical stability,and rate ***,the assembled symmetrical K^(+)supercapacitor demonstrates an energy density of 51.8 Wh kg^(−1),an ultrahigh power density of 443Wkg^(−1),and outstanding cycling stability(maintaining 83.3%after 10,000 cycles in 1M KPF6 organic electrolyte).This research provides valuable insights into the design of highperformance potassium ion storage materials.

关键词： agarose carbon aerogels O/N/B codoping potassium-ion battery potassium-ion supercapacitor

Smart beam via electrically addressing the dye-doped and polymer-stabilized cholesteric liquid crystals

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Chinese Optics Letters 2024年第5期22卷 111-116页

作者：彭程徐春庭胡伟 college of engineering and Applied sciences Nanjing UniversityNanjing 210023China

Smart beams play a vital role in modern intelligent vehicles and have recently attracted significant attention.A spatial light modulator with high optical efficiency,low cost,and compact size is crucial for designing smart ***,we mix cholesteric liquid crystals with dichroic black dye and a *** UV polymerization,the sample exhibits a low driving voltage of 26 V,a high transmittance of over 70%,and an On-off ratio over 280,thanks to the joint contribution of both the absorption and the scattering effect.A smart beam device is demonstrated by electrically addressing the dye-doped and polymer-stabilized cholesteric liquid crystal with pixelated *** patterns with arbitrary designs are projected *** switching time reaches several tens of *** strategy brings new designs to intelligent vehicles and may also inspire applications in public information displays,advertising,and even AR/VR displays.

关键词： cholesteric liquid crystal spatial light modulation smart beam dye guest-host effect

Constructing porous ZnFC-PA/PSF composite spheres for highly efficient Cs^(+) removal

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Journal of Environmental sciences 2024年第9期143卷 126-137页

作者： Senjian Han Chao Gao Wenfeng Yan Yafei Guo Shiqiang Wang Tianlong Deng college of marine and Environmental sciences Tianjin University of Science and TechnologyTianjin 300457China Key Laboratory of marine Resource Chemistry and Food Technology Ministry of EducationTianjin 300457China

Radioisotope leaking from nuclear waste has become an intractable problem due to its gamma radiation and strong water *** this work,a novel porous ZnFC-PA/PSF composite sphere was fabricated by immobilization of ferrocyanides modified zinc phytate into polysulfone(PSF)substrate for the treatment of Cs-contaminated *** maximum adsorption capacity of ZnFC-PA/PSF was 305.38 mg/g,and the removal efficiency of Cs+was reached 94.27%within 2 *** ZnFC-PA/PSF presented favorable stability with negligible dissolution loss of Zn^(2+)and Fe^(2+)(<2%).The ZnFC-PA/PSF achieved high-selectivity towards Cs+(K_(d)=2.24×10^(4)mL/g)even in actual geothermal *** adsorption mechanism was inferred to be the ion-exchange between Cs^(+)and K^(+).What’s more,ZnFC-PA/PSF worked well in the fixed-bed adsorption(E=91.92%),indicating the application potential for the hazardous Cs^(+)removal from wastewater.

关键词： Adsorption Cesium Metal ferrocyanide Composite adsorbent

A physics-informed neural network for simulation of finite deformation in hyperelastic-magnetic coupling problems

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Applied Mathematics and Mechanics(English Edition) 2024年第10期45卷 1717-1732页

作者： Lei WANG Zikun LUO Mengkai LU Minghai TANG Department of engineering Mechanics College of Mechanics and Engineering SciencesHohai University School of Mechanical engineering and Mechanics Ningbo University

Recently, numerous studies have demonstrated that the physics-informed neural network(PINN) can effectively and accurately resolve hyperelastic finite deformation problems. In this paper, a PINN framework for tackling hyperelastic-magnetic coupling problems is proposed. Since the solution space consists of two-phase domains,two separate networks are constructed to independently predict the solution for each phase region. In addition, a conscious point allocation strategy is incorporated to enhance the prediction precision of the PINN in regions characterized by sharp *** the developed framework, the magnetic fields and deformation fields of magnetorheological elastomers(MREs) are solved under the control of hyperelastic-magnetic coupling equations. Illustrative examples are provided and contrasted with the reference results to validate the predictive accuracy of the proposed framework. Moreover, the advantages of the proposed framework in solving hyperelastic-magnetic coupling problems are validated, particularly in handling small data sets, as well as its ability in swiftly and precisely forecasting magnetostrictive motion.

关键词： 74B20 74F15 deep learning finite deformation hyperelasticmagnetic coupling O343.5 physics-informed neural network (PINN) small data set