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Chinese Physics B 2022年第11期31卷 244-255页

作者：胡永兵杨晓敏丁大为杨宗立 School of Electronics and Information engineering Anhui UniversityHefei 230601China national engineering research center for agro-ecological big data analysis&application Anhui UniversityHefei 230601China

Multi-link networks are universal in the real world such as relationship networks,transportation networks,and communication *** is significant to investigate the synchronization of the network with *** this paper,considering the complex network with uncertain parameters,new adaptive controller and update laws are proposed to ensure that complex-valued multilink network realizes finite-time complex projective synchronization(FTCPS).In addition,based on fractional-order Lyapunov functional method and finite-time stability theory,the criteria of FTCPS are derived and synchronization time is given which is associated with fractional order and control ***,numerical example is given to verify the validity of proposed finite-time complex projection strategy and analyze the relationship between synchronization time and fractional order and control ***,the network is applied to image encryption,and the security analysis is carried out to verify the correctness of this method.

关键词： multi-links network fractional order complex-valued network finite-time complex projective synchronization image encryption

Phosphotungstic acid ionic liquid for efficient photocatalytic desulfurization:Synthesis,application and mechanism

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Chinese Journal of Chemical engineering 2024年第5期69卷 101-111页

作者： Chenchao Hu Suhang Xun Desheng Liu Junjie Zhang Minqiang He Wei Jiang Huaming Li Wenshuai Zhu Institute of Environmental Health and ecological Security School of Environment and Safety EngineeringJiangsu UniversityZhenjiang 212013China School of Chemistry and Chemical engineering Institute for Energy ResearchJiangsu UniversityZhenjiang 212013China Jiangsu Collaborative Innovation center of Technology and Material of Water Treatment Suzhou University of Science and TechnologySuzhou 215009China

An efficient mass transfer process is a critical factor for regulating catalytic activity in a photocatalytic desulfurization ***,a phosphotungstic acid(HPW)active center is successfully composited with a quaternary ammonium phosphotungstate-based hexadecyltrimethylammonium chloride ionic liquid(CTAC-HPW)by the ion exchange method for the photocatalytic oxidative desulfurization of dibenzothiophene *** keggin structure of HPW and highly mass transfer performance of organic cations synergistically enhanced the photocatalytic activity towards the effective convertion of dibenzothiophene(DBT)with the excitation of visible *** deep desulfurization(analysis confirmed that h^(+)and,COOH played critical roles in the oxidation *** work offers a practicable strategy for efficiently converting DBT to DBTO_(2) with added value.

关键词： Photocatalytic desulfurization Extraction Ionic liquid CTAC-HPW

Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

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Journal of Mountain Science 2024年第2期21卷 511-525页

作者： ZHAO Kaixin LI Xuemei ZHANG Zhengrong LIU Xinyu Faculty of Geomatics Lanzhou Jiaotong UniversityLanzhou 730070China national-Local Joint engineering research center of Technologies and applications for national Geographic State Monitoring Lanzhou 730070China Gansu Provincial engineering Laboratory for national Geographic State Monitoring Lanzhou 730070China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate *** relationship between changes in vegetation growth and climate remains *** this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to ***,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation ***,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly *** SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other *** EOS in MDW and GSD were concentrated between late August and April and early September and early January,*** phenology exhibits distinct responses to seasonal temperature and precipitation *** advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,*** advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,*** the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect *** indirec

关键词： Vegetation phenology Time series decomposition Path analysis Climate change

Estimating wheat spike-leaf composite indicator(SLI)dynamics by coupling spectral indices and machine learning

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The Crop Journal 2024年第3期12卷 927-937页

作者： Haiyu Tao Ruiheng Zhou Yining Tang Wanyu Li Xia Yao Tao Cheng Yan Zhu Weixing Cao Yongchao Tian national engineering and Technology center for Information Agriculture Key Laboratory of Crop System Analysis and Decision MakingMinistry of Agriculture and Rural AffairsJiangsu Key Laboratory for Information AgricultureNanjing Agricultural UniversityNanjing 210095JiangsuChina

The contribution of spike photosynthesis to grain yield(GY)has been overlooked in the accurate spectral prediction of ***,it’s essential to construct and estimate a yield-related phenotypic trait considering spike *** on field and spectral reflectance data from 19 wheat cultivars under two nitrogen fertilization conditions in two years,our objectives were to(i)construct a yield-related phenotypic trait(spike–leaf composite indicator,SLI)accounting for the contribution of the spike to photosynthesis,(ii)develop a novel spectral index(enhanced triangle vegetation index,ETVI3)sensitive to SLI,and(iii)establish and evaluate SLI estimation models by integrating spectral indices and machine learning *** results showed that SLI was sensitive to nitrogen fertilizer and wheat cultivar variation as well as a better predictor of yield than the leaf area ***3 maintained a strong correlation with SLI throughout the growth stage,whereas the correlations of other spectral indices with SLI were poor after spike *** spectral indices and machine learning algorithms improved the estimation accuracy of SLI,with the most accurate estimates of SLI showing coefficient of determination,root mean square error(RMSE),and relative RMSE values of 0.71,0.047,and 26.93%,*** results provide new insights into the role of fruiting organs for the accurate spectral prediction of *** high-throughput SLI estimation approach can be applied for wheat yield prediction at whole growth stages and may be assisted with agronomical practices and variety selection.

关键词： Wheat spike photosynthesis Yield-related phenotypic trait Spectral indices Machine learning Estimation

Regulating^(*)COOH intermediate via amino alkylation engineering for exceptionally effective photocatalytic CO_(2) reduction

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Journal of Energy Chemistry 2024年第5期92卷 282-291页

作者： Chengcheng Chen Qiaoyu Zhang Fangting Liu Zhengguo Zhang Qiong Liu Xiaoming Fang Key Laboratory of Enhanced Heat Transfer and Energy Conservation The Ministry of EducationSchool of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510640GuangdongChina Guangdong Provincial Key Laboratory of Chemical Measurement and Emergency Test Technology(China) Institute of AnalysisGuangdong Academy of Sciences(China National Analytical CenterGuangzhou)Guangzhou 510070GuangdongChina Guangdong engineering Technology research center of Efficient Heat Storage and application South China University of TechnologyGuangzhou 510640GuangdongChina Guangdong Provincial Key Laboratory of Fuel Cell Technology South China University of TechnologyGuangzhou 510640GuangdongChina

Photocatalytic reduction of CO_(2) into fuel represents a promising approach for achieving carbon neutrality,while realizing high selectivity in this process is challenging due to uncontrollable reaction intermediate and retarded desorption of target *** the interface microenvironment of catalysts has been proposed as a strategy to exert a significant influence on reaction outcomes,yet it remains a significant *** this study,amino alkylation was successfully integrated into the melem unit of polymeric carbon nitrides(PCN),which could efficiently drive the photocatalytic CO_(2) *** characterization and theoretical calculations revealed that the introduction of amino alkylation lowers the energy barrier for CO_(2) reduction into^(*)COOH intermediate,transforming the adsorption of^(*)COOH intermediate from the endothermic to an exothermic ***,the as-prepared materials demonstrated outstanding performance in photocatalytic CO_(2) reduction,yielding CO_(2)at a rate of 152.8μmol h^(-1) with a high selectivity of 95.4%and a quantum efficiency of 6.6%.

关键词： Polymeric carbonnitride Regulate intermediate Photocatalytic CO_(2)reduction Amino alkylation ^(*)COOH adsorption

New Record Ocean Temperatures and Related Climate Indicators in 2023

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Advances in Atmospheric Sciences 2024年第6期41卷 1068-1082页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH Tim BOYER Michael EMANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Viktor GOURETSKI Gengxin CHEN Alexey MISHONOV Jim REAGAN Karina VON SCHUCKMANN Yuying PAN Zhetao TAN Yujing ZHU Wangxu WEI Guancheng LI Qiuping REN Lijuan CAO Yayang LU International center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of St.Thomas School of EngineeringMinnesota 55105USA NSF national center for Atmospheric research BoulderColorado 80307USA University of Auckland Auckland 1010New Zealand national Oceanic and Atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA Department of Earth and Environmental Science University of PennsylvaniaPhiladelphiaPennsylvania 19104USA Institute of Oceanology Chinese Academy of SciencesQingdao 266071China national Marine Environmental Forecasting center Ministry of Natural Resources of ChinaBeijing 100081China Oceanographic data center Chinese Academy of SciencesQingdao 266071China College of Oceanography Hohai UniversityNanjing 210098China national Marine data and Information Service Tianjin 300171China Italian national Agency for New Technologies Energy and Sustainable Economic DevelopmentS.Teresa Research CenterLerici 19032Italy Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South China Sea Institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMD20740USA Mercator Ocean International Toulouse 31400France Eco-Environmental Monitoring and research center Pearl River Valley and South China Sea Ecology and Environment AdministrationMinistry of Ecology and EnvironmentPRCGuangzhou 510611China national Meteorological Information center China Meteorological AdministrationBeijing 100081China International research center of big data for Sustainable Development Goals Beijing 100094China

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human *** 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record *** 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the *** with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of *** density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

关键词： ocean heat content salinity stratification global warming climate

Deep learning-based semantic segmentation of human features in bath scrubbing robots

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Biomimetic Intelligence & Robotics 2024年第1期4卷 70-79页

作者： Chao Zhuang Tianyi Ma Bokai Xuan Cheng Chang Baichuan An Minghuan Yin Hao Sun School of Artificial Intelligence and data Science Hebei University of TechnologyTianjin 300401China engineering research center of Intelligent Rehabilitation Device and Detection Technology Ministry of EducationTianjin 300401China

With the rise in the aging population,an increase in the number of semidisabled elderly individuals has been noted,leading to notable challenges in medical and healthcare,exacerbated by a shortage of nursing *** study aims to enhance the human feature recognition capabilities of bath scrubbing robots operating in a water fog *** investigation focuses on semantic segmentation of human features using deep learning ***,3D point cloud data of human bodies with varying sizes are gathered through light detection and ranging to establish human ***,a hybrid filtering algorithm was employed to address the impact of the water fog environment on the modeling and extraction of human ***,the network is refined by integrating the spatial feature extraction module and the channel attention module based on *** results indicate that the algorithm adeptly identifies feature information for 3D human models of diverse body sizes,achieving an overall accuracy of 95.7%.This represents a 4.5%improvement compared with the PointNet network and a 2.5%enhancement over mean intersection over *** conclusion,this study substantially augments the human feature segmentation capabilities,facilitating effective collaboration with bath scrubbing robots for caregiving tasks,thereby possessing significant engineering application value.

关键词： 3D point cloud Human model LiDAR Semantic segmentation

An Innovative K-Anonymity Privacy-Preserving Algorithm to Improve data Availability in the Context of big data

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Computers, Materials & Continua 2024年第4期79卷 1561-1579页

作者： Linlin Yuan Tiantian Zhang Yuling Chen Yuxiang Yang Huang Li State Key Laboratory of Public big data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China College of Information engineering Guizhou Open UniversityGuiyang550025China Guizhou Academy of Tobacco Science Guiyang550025China

The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more *** K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big ***,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data *** addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be *** on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data ***,we construct a new information loss function based on the information quantity *** that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss *** addition,to reduce information loss,we improve K-anonymity in two ***,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering *** addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of ***,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information ***,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.

关键词： Blockchain big data K-anonymity 2-means clustering greedy algorithm mean-center method

ThyroidNet:A Deep Learning Network for Localization and Classification of Thyroid Nodules

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Computer Modeling in engineering & Sciences 2024年第4期139卷 361-382页

作者： Lu Chen Huaqiang Chen Zhikai Pan Sheng Xu Guangsheng Lai Shuwen Chen Shuihua Wang Xiaodong Gu Yudong Zhang Ultrasonic Department Zhongda Hospital Affiliated to Southeast UniversityNanjing210009China School of Physics and Information engineering Jiangsu Second Normal UniversityNanjing211200China School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia State Key Laboratory of MillimeterWaves Southeast UniversityNanjing210096China Jiangsu Province engineering research center of Basic Education big data application Jiangsu Second Normal UniversityNanjing211200China School of Software engineering Quanzhou Normal UniversityQuanzhou362000China Department of Biological Sciences Xi’an Jiaotong-Liverpool UniversitySuzhou215123China

Aim:This study aims to establish an artificial intelligence model,ThyroidNet,to diagnose thyroid nodules using deep learning techniques ***:A novel method,ThyroidNet,is introduced and evaluated based on deep learning for the localization and classification of thyroid ***,we propose the multitask TransUnet,which combines the TransUnet encoder and decoder with multitask ***,we propose the DualLoss function,tailored to the thyroid nodule localization and classification *** balances the learning of the localization and classification tasks to help improve the model’s generalization ***,we introduce strategies for augmenting the ***,we submit a novel deep learning model,ThyroidNet,to accurately detect thyroid ***:ThyroidNet was evaluated on private datasets and was comparable to other existing methods,including U-Net and *** results show that ThyroidNet outperformed these methods in localizing and classifying thyroid *** achieved improved accuracy of 3.9%and 1.5%,***:ThyroidNet significantly improves the clinical diagnosis of thyroid nodules and supports medical image analysis *** research directions include optimization of the model structure,expansion of the dataset size,reduction of computational complexity and memory requirements,and exploration of additional applications of ThyroidNet in medical image analysis.

关键词： ThyroidNet deep learning TransUnet multitask learning medical image analysis

Identification and Expression Profile of a Neuropeptide LFRFamide-Like Gene During Different Stages of Gonadal Development in the Cephalopod Sepia pharaonis

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Journal of Ocean University of China 2024年第2期23卷 499-508页

作者： QIU Jiayin SUN Lianlian LI Shuang ZHOU Xu CHI Changfeng ZHENG Libing national and Provincial Joint engineering research center for Marine Germplasm Resources Exploration and Utilization School of Marine Science and TechnologyZhejiang Ocean UniversityZhoushan 316022China

Neuropeptides are widely distributed in vertebrates and invertebrates,regulating a variety of physiological activities in the organisms,such as metabolism,feeding and *** this study,to explore the function of neuropeptide LFRFamide in Sepia pharaonis,the full-length cDNA of LFRFamide-like gene(named SpLFRFL,MG869822.1)was identified with rapid amplification of cDNA ends(RACE)*** sequence of SpLFRFL was 860 bp in length and encoded 188 amino acids containing 4 different mature peptides:1 copy of PHTPFRFamide,NSLFRFamide,TIFRFamide,and 3 copies of *** alignment and phylogenetic analysis results showed that SpLFRFL shared high identity with LFRFamides of Sepia officinalis and Sepiella japonica and had the closest relationship with *** quantitative Real-time PCR(qRT-PCR),it was found that the SpLFRFL gene was highly expressed in the optic lobe and brain at three different stages during gonad development in both ***,the four mature peptides at a concentration of 0.01μmol L^(−1) could inhibit the protein synthesis in the Chinese hamster ovary cell strain-K1(CHOK1)induced by *** data suggest that SpLFRFL might be involved in the development and reproduction of *** results can contribute to future studies on neuropeptide evolution and function and benefit the cuttlefish farming.

关键词： neuropeptide LFRFamide-like cephalopod cuttlefish Sepia pharaonis development reproduction