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Designing salt stress-resilient crops:Current progress and future challenges

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Journal of Integrative Plant Biology 2024年第3期66卷 303-329页

作者： Xiaoyan Liang jianfang Li Yongqing Yang Caifu Jiang Yan Guo State Key Laboratory of Plant Environmental Resilience College of Biological SciencesChina Agricultural UniversityBeijing 100094China State Key Laboratory of Nutrient Use and Management College of Resources and Environmental SciencesChina Agricultural UniversityBeijing 100194China Center for Crop Functional Genomics and Molecular Breeding China Agricultural UniversityBeijing 100094China Frontiers Science Center for Molecular Design Breeding China Agricultural UniversityBeijing 100193China

Excess soil salinity affects large regions of land and is a major hindrance to crop production worldwide.Therefore,understanding the molecular mechanisms of plant salt tolerance has scientific importance and practical significance.In recent decades,studies have characterized hundreds of genes associated with plant responses to salt stress in different plant species.These studies have substantially advanced our molecular and genetic understanding of salt tolerance in plants and have introduced an era of molecular design breeding of salt-tolerant crops.This review summarizes our current knowledge of plant salt tolerance,emphasizing advances in elucidating the molecular mechanisms of osmotic stress tolerance,salt-ion transport and compartmentalization,oxidative stress tolerance,alkaline stress tolerance,and the trade-off between growth and salt tolerance.We also examine recent advances in understanding natural variation in the salt tolerance of crops and discuss possible strategies and challenges for designing salt stress-resilient crops.We focus on the model plant Arabidopsis(Arabidopsis thaliana)and the four most-studied crops:rice(Oryza sativa),wheat(Triticum aestivum),maize(Zea mays),and soybean(Glycine max).

关键词： molecular design breeding salt stress-resilient crop salt tolerance

Potassium isotopic signatures of modern offshore detrital sediments from different climatic regimes and the implications

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Science China Earth Sciences 2024年第2期67卷 405-419页

作者： Jun MU Tianyu CHEN Qian YU Shichao AN jianfang CHEN Xuefa SHI Weiqiang LI State Key Laboratory for Mineral Deposits Research School of Earth Sciences and EngineeringNanjing UniversityNanjing210023China Ministry of Education Key Laboratory for Coast and Island Development School of Geography and Ocean ScienceNanjing UniversityNanjing210023China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou310012China Key Laboratory of Marine Geology and Metallogeny First Institute of OceanographyMinistry of Natural ResourcesQingdao266061China

Potassium isotopes are a novel tracer for continental weathering.Previous K isotope studies on chemical weathering generally targeted weathering profiles under a particular climate region,yet the effects of chemical weathering on K isotopes under different climatic backgrounds remain unclear.Moreover,little is known about the K isotope signatures of modern unconsolidated detrital sediments.Here,we report K isotopic data of surficial seafloor sediments from continental shelves along the east coast of China(ECC),as well as those around the tropical Hainan island in the northern South China Sea.The ECC sediments have a relatively narrow distribution ofδ^(41)K(with reference to NIST3141a)values,which range from(-0.40±0.01)‰to(-0.57±0.04)‰,with an average of(-0.51±0.09)‰.By contrast,δ^(41)K values of Hainan offshore sediments display a larger variation,ranging from(-0.28±0.07)‰to(-0.67±0.02)‰.Theδ^(41)K values of Hainan offshore sediments exhibit negative correlations with the chemical index of alteration(CIA),Al/K,Ti/K,and total iron(FeT),which underlines the control of chemical weathering on K isotopic signatures of detritus inputs into oceans.We also measured Mg isotope compositions for the same samples;interestingly,the variability inδ^(26)Mg of the samples is small(~0.24‰)for all ECC and Hainan offshore sediments,andδ^(26)Mg values do not show clear correlations with indexes of chemical weathering.Our study demonstrates the link between K isotopic variability of detrital sediments and climatic conditions including rainfall intensity,which indicates that K isotopes of the detrital component of marine sediments could be applied to study Earth’s climate in deep time.Theδ^(41)K values of the offshore detrital sediments are significantly less variable than those of pelagic marine sediments,highlighting the importance of distinguishing the effects of diagenesis and neoformation of clay minerals from continental weathering in attempts to study deep-time climate-weathering link by K isotopes in detrital sedimentary recor

关键词： Potassium isotopes Magnesium isotopes Chemical weathering Detrital sediments Climatic regimes Mean annual precipitation

Graphitic carbon nitride nanosheets mitigate cadmium toxicity in Glycine max L.by promoting cadmium retention in root and improving photosynthetic performance

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Journal of Environmental Sciences 2024年第5期139卷 543-555页

作者： Kai Xu Yunyu Guo Chenghua Xing Ronglong Fu Bin Zou Rongchuan Liu Luyi Cai jianfang Yan Xi-Lin Wu Miaozhen Cai College of Geography and Environmental Sciences Zhejiang Normal UniversityJinhua 321004China College of Agriculture Jinhua PolytechnicJinhua 321007China

Cadmium(Cd)pollution poses a serious threat to plant growth and yield.Nanomaterials have shown great application potential for alleviation of Cd toxicity to plants.In this study,we applied graphitic carbon nitride nanosheets(g-C_(3)N_(4)NSs)for alleviation of Cd-toxicity to soybean(Glycine max L.).The g-C_(3)N_(4)NSs supplementation significantly improved plant growth and reduced oxidative damage in the Cd-toxicated soybean seedlings through hydroponic culture.Particularly,the g-C_(3)N_(4)NSs dynamically regulated the root cell wall(RCW)components by increasing pectin content and modifying its demethylation via enhancing pectin methylesterase(PME)activity,therefore greatly enhanced stronger RCW-Cd retention(up to 82.8%)and reduced Cd migration to the shoot.Additionally,the g-C_(3)N_(4)NSs reversed the Cd-induced chlorosis,increased photosynthetic efficiency because of enhancement in F_v/F_mration,Y(Ⅱ)and sugars content.These results provide new insights into the alleviation of Cd toxicity to plants by g-C_(3)N_(4)NSs,and shed light on the application of low-cost and environmental-friendly carbon-based NMs for alleviating heavy metal toxicity to plants.

关键词： Cadmium Carbon nitride nanosheets Cell wall Pectin Pectin methylesterase Soybean

FusionNN:A Semantic Feature Fusion Model Based on Multimodal for Web Anomaly Detection

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Computers, Materials & Continua 2024年第5期79卷 2991-3006页

作者： Li Wang Mingshan Xia Hao Hu jianfang Li Fengyao Hou Gang Chen Institute of High Energy Physics Chinese Academy of SciencesBeijing100049China Spallation Neutron Source Science Center(SNSSC) Dongguan523803China School of Nuclear Technology University of Chinese Academy of SciencesBeijing100049Chin

With the rapid development of the mobile communication and the Internet,the previous web anomaly detectionand identificationmodels were built relying on security experts’empirical knowledge and attack features.Althoughthis approach can achieve higher detection performance,it requires huge human labor and resources to maintainthe feature library.In contrast,semantic feature engineering can dynamically discover new semantic featuresand optimize feature selection by automatically analyzing the semantic information contained in the data itself,thus reducing dependence on prior knowledge.However,current semantic features still have the problem ofsemantic expression singularity,as they are extracted from a single semantic mode such as word segmentation,character segmentation,or arbitrary semantic feature extraction.This paper extracts features of web requestsfrom dual semantic granularity,and proposes a semantic feature fusion method to solve the above problems.Themethod first preprocesses web requests,and extracts word-level and character-level semantic features of URLs viaconvolutional neural network(CNN),respectively.By constructing three loss functions to reduce losses betweenfeatures,labels and categories.Experiments on the HTTP CSIC 2010,Malicious URLs and HttpParams datasetsverify the proposedmethod.Results show that compared withmachine learning,deep learningmethods and BERTmodel,the proposed method has better detection performance.And it achieved the best detection rate of 99.16%in the dataset HttpParams.

关键词： Feature fusion web anomaly detection multimodal convolutional neural network(CNN) semantic feature extraction

Combining machine and deep transfer learning for mediastinal lymph node evaluation in patients with lung cancer

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虚拟现实与智能硬件（中英文） 2024年第3期6卷 226-238页

作者： Hui XIE jianfang ZHANG Lijuan DING Tao TAN Qing LI Department of Radiation Oncology Affiliated Hospital(Clinical College)of Xiangnan UniversityChenzhou 423000China Faulty of Applied Sciences Macao Polytechnic UniversityMacao 999078China Department of Physical examination Beihu Centers for Disease Control and PreventionChenzhou 423000China Department of Radiation Oncology the Third People's Hospital of Chenzhou CityChenzhou 423000China School of Medical Imaging Laboratory Science and RehabilitationXiangnan UniversityChenzhou 423000China

Background The prognosis and survival of patients with lung cancer are likely to deteriorate with metastasis.Using deep-learning in the detection of lymph node metastasis can facilitate the noninvasive calculation of the likelihood of such metastasis,thereby providing clinicians with crucial information to enhance diagnostic precision and ultimately improve patient survival and prognosis.Methods In total,623 eligible patients were recruited from two medical institutions.Seven deep learning models,namely Alex,GoogLeNet,Resnet18,Resnet101,Vgg16,Vgg19,and MobileNetv3(small),were utilized to extract deep image histological features.The dimensionality of the extracted features was then reduced using the Spearman correlation coefficient(r≥0.9)and Least Absolute Shrinkage and Selection Operator.Eleven machine learning methods,namely Support Vector Machine,K-nearest neighbor,Random Forest,Extra Trees,XGBoost,LightGBM,Naive Bayes,AdaBoost,Gradient Boosting Decision Tree,Linear Regression,and Multilayer Perceptron,were employed to construct classification prediction models for the filtered final features.The diagnostic performances of the models were assessed using various metrics,including accuracy,area under the receiver operating characteristic curve,sensitivity,specificity,positive predictive value,and negative predictive value.Calibration and decision-curve analyses were also performed.Results The present study demonstrated that using deep radiomic features extracted from Vgg16,in conjunction with a prediction model constructed via a linear regression algorithm,effectively distinguished the status of mediastinal lymph nodes in patients with lung cancer.The performance of the model was evaluated based on various metrics,including accuracy,area under the receiver operating characteristic curve,sensitivity,specificity,positive predictive value,and negative predictive value,which yielded values of 0.808,0.834,0.851,0.745,0.829,and 0.776,respectively.The validation set of the model was assessed using clinical decision curv

关键词： Machine learning Deep transfer learning Evaluation Mediastinal lymph node lung cancer patie

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

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工程与科学中的计算机建模(英文) 2024年第1期138卷 429-458页

作者： Rongrong Ren Luyang Su Xinyu Meng jianfang Wang Meng Zhao School of Business Administration Northeastern UniversityShenyang110819China School of Management Northeastern University at QinhuangdaoQinhuangdao066004China School of Modern Logistics Shanxi Vocational University of Engineering Science and TechnologyTaiyuan030031China Business School Sichuan UniversityChengdu610064China

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

关键词： Large-scale group decision making social network updating trust relationship group consensus feedback mechanism

Biogeochemistry of sedimentary organic matter in the Yongjiang River estuary in the southern part of Hangzhou Bay,China,since the Late Pleistocene

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Journal of Oceanology and Limnology 2024年第3期42卷 772-786页

作者： Dongqin HUANG Xiaolong LI Zilong LI Pei Sun LOH Jianxiong HU jianfang CHEN Yuan-Pin CHANG Chin-Wen YANG Qin GAO Institute of Marine Geology and Resources Ocean CollegeZhejiang UniversityZhoushan 316021China Ministry of Water Resources of the People’s Republic of China Beijing 100054China Key Laboratory of Marine Ecosystem Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Department of Oceanography Sun Yat-sen UniversityKaohsiung 80424China

A sediment core(YJK19-02)collected from the southern outlet of Hangzhou Bay near the Yongjiang River estuary in East China was analyzed for grain size,lignin,bulk elemental composition,stable carbon isotope,and rare earth elements(REEs)to determine the sources and diagenesis of sedimentary organic matter(OM)of the estuary and adjacent areas since the Late Pleistocene.δ^(13)C values(-24.80‰–-23.60‰),total organic carbon/total nitrogen(TOC/TN)molar ratios(8.00–12.14),and light rare earth element/heavy rare earth element ratios(LREE/HREE=8.34–8.91)revealed the predominance of terrestrial sources of OM,mainly from the Changjiang(Yangtze)River.The lignin parameters of syringyl/vanillyl(S/V=0.20–0.73)and cinnamyl/vanillyl(C/V=0.03–0.19)ratios indicate the predominance of nonwoody angiosperms,and the vanillic acid/vanillin ratios[(Ad/Al)_(V)=0.32–1.57]indicate medium to high degrees of lignin degradation.An increasing trend ofΛ(total lignin in mg/100-mg OC)values from ca.14500 a BP to ca.11000 a BP reflected the increase in temperature during the Late Pleistocene.However,a time lag effect of temperature on vegetation abundance was also revealed.The relatively higher and stableΛvalues correspond to the higher temperature during the mid-Holocene from ca.8500 a BP to ca.4500 a BP.Λvalues decreased from ca.4000 a BP to the present,corresponding to historical temperature fluctuations during this time.Our results show that the vegetation abundance in the Yongjiang River Basin since the Late Pleistocene was related to the temperature fluctuation duo to climate change.

关键词： Yongjiang River estuary sedimentary organic matter lignin environmental change Late Pleistocene

Saline-alkali soil reclamation and utilization in China:progress and prospects

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Frontiers of Agricultural Science and Engineering 2024年第2期11卷 216-228页

作者： Guangzhou WANG Gang NI Gu FENG Haley M.BURRILL jianfang LI Junling ZHANG Fusuo ZHANG State Key Laboratory of Nutrient Use and Management (SKLNUM) College of Resources and Environmental SciencesNational Academy of Agriculture Green Development China Agricultural University The Institute of Ecology and Evolution University of Oregon

Soil salinity is a global threat to the productivity of arable land. With the impact of population growth and development of social economy in China, the area of arable land has been shrinking in recent decades and is approaching a critical threshold of 120 Mha, the minimum area for maintaining the national food security. Saline-alkaline land, as important backup reserve, has been receiving increased attention as an opportunity to expand land resources. This review first summarizes the general principles and technologies of saline soil reclamation to support plant growth, including leaching salts or blocking the rise of salts, and soil fertility enhancement to improve the buffering capacity.Then the progress in this area in China is described including the customization of technologies and practices used in different saline-alkali regions. Following the soil management strategies, the concept of selecting crops for saline soil is proposed. This encompasses halophyte planting, salt-tolerant crop breeding and the application of saline-adapted functional microorganisms to improve the adaptation of crops. Finally, the current problems and challenges are evaluate, and future research directions and prospects proposed for managing this major soil constraint.

关键词： Food security land reserve reclamation saline-alkali soil utilization

Development and optimized pairing of mouse monoclonal antibodies for detecting hemagglutinin in novel H7 subtype influenza viruses

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Science China(Life Sciences) 2020年第2期63卷 279-289页

作者： Huijuan Wang jianfang zhou Dayan Wang Baoying Huang Wenjie Tan NHC Key Laboratory of Biosafety National Institute for Viral Disease Control&PreventionChinese Center for Disease Control and PreventionChina CDCBeijing 102206China

The H7 subtype avian influenza threatens public health with respect to poultry and humans.Thus,a specific and sensitive diagnostic test is essential for the management of H7 subtype influenza infections.In this study,five mouse monoclonal antibodies(mAbs)against hemagglutinin(HA)of influenza A/Anhui/1/2013(H7N9)were produced and characterized by the Western blot,immunofluorescence,and hemagglutination inhibition assays.All five specific mAbs reacted with the HA protein of H7N9 but not with that of H1 N1,H3 N2,or H5 N1.With the combination arrays of capture and detection antibodies,the matched pair m Abs(1 C4-coated and 2 D7-labeled)were selected and employed in a double-antibody sandwich ELISA(DASELISA).Detection limits of the sandwich ELISA were 0.45 ng mL^–1 for the HA protein derived from A/Anhui/1/2013(H7N9);or 1 and 2 HA units/50μL for A/Anhui/1/2013(H7N9)and A/GD/17 SF003/2016(H7N9),respectively.These anti-HA mAbs against subtype H7 and the novel DAS-ELISA provide a valuable approach for specific detection of the H7 subtype influenza virus and quantification of its HA protein,especially for the novel epidemic H7N9.

关键词： influenza A H7 subtype hemagglutinin monoclonal antibodies sandwich ELISA