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Host-Induced Gene Silencing of Effector AGLIP1 Enhanced Resistance of Rice to Rhizoctonia solani AG1-IA

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Rice science 2024年第4期31卷 463-474,I0031-I0034页

作者： ZHAO Mei LIU Xiaoxue WAN jun zhou Erxun SHU Canwei Pesticide State Key Laboratory of Green Pesticide Guangdong Province Key Laboratory of Microbial Signals and Disease ControlCollege of Plant ProtectionSouth China Agricultural UniversityGuangzhou 510642China College of Life Science and Engineering Henan University of Urban ConstructionPingdingshan 467036China

Rice sheath blight, caused by Rhizoctonia solani AG1-IA, is a major disease in rice-growing areas worldwide. Effectors of phytopathogenic fungi play important roles during the infection process of fungal pathogens onto their host plants. However, the molecular mechanisms by which R. solani effectors regulate rice immunity are not well understood. Through prediction, 78 candidate effector molecules were identified. Using the tobacco rattle virus-host induced gene silencing(TRV-HIGS) system, 45 RNAi constructs of effector genes were infiltrated into Nicotiana benthamiana leaves. The results revealed that eight of these constructs resulted in a significant reduction in necrosis caused by infection with the AG1-IA strain GD-118. Additionally, stable rice transformants carrying the double-stranded RNA construct for one of the effector genes, AGLIP1, were generated to further verify the function of this gene. The suppression of the AGLIP1 gene increased the resistance of both N. benthamiana and rice against GD-118, and also affected the growth rate of GD-118, indicating that AGLIP1 is a key pathogenic factor. Small RNA sequencing showed that the HIGS vectors were processed into si RNAs within the plants and then translocated to the fungi, leading to the silencing of the target genes. As a result, AGLIP1 might be an excellent candidate for HIGS, thereby enhancing crop resistance against the pathogen and contributing to the control of R. solani infection.

关键词： Rhizoctonia solani host-induced gene silencing lipase tobacco rattle virus

Spatial and Temporal Differences of Climate Suitability of Ice and Snow Sports in Major Ski Tourism Destinations in China

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Chinese Geographical Science 2024年第5期34卷 967-982页

作者： XIE Xia PANG Zhengjin ZHU Haiqiang GAO jun zhou Qiaoya Key Laboratory of the Sustainable Development of Xinjiang’s Historical and Cultural Tourism Xinjiang UniversityUrumqi 830046China College of Tourism Xinjiang UniversityUrumqi 830046China School of Tourism Management Sun Yat-sen UniversityZhuhai 519000China

Ice and snow tourism in China has grown significantly since the country successfully hosted the Beijing Winter *** conditions profoundly impact the development of ice and snow tourism;however,most studies have focused on constructing different climate suitability indicators for ice and snow tourism to evaluate individual regions,lacking horizontal comparative studies across multiple *** study aims to enrich the connotation of climate suitability for ice and snow sports,establish an evaluation model based on snowfall amount,temperature,and wind speed,and use daily meteorological data from 1991 to 2021 to horizontally compare the climate suitability for ice and snow sports in major ski tourism destinations in *** study boasts four major findings:1)the average ice and snow sports climate index of each region decreases over time,and the overall suitability of the climate for ice and snow sports is reducing;2)northern Xinjiang exhibits the most evident regional differentiation from‘very suitable’to‘generally suitable’;3)the spatial zoning of climate suitability for ice and snow sports exhibits heterogeneity,as northern Xinjiang is divided into two‘suitable and above’zones with rotating empirical orthogonal function(REOF).Correspondingly,the four provinces of Hebei,Heilongjiang,Jilin,and Liaoning are divided into three‘generally suitable and above’zones;4)snowfall amount is the main factor affecting the climate suitability of ice and snow sports in the major ski tourist destinations in China.

关键词： ice and snow tourism climate suitability rotating empirical orthogonal function(REOF) spatial division China

Efficacy and safety of Chinese herbal medicine as adjunctive therapy in sepsis patients with bloodstream infection:a propensity-matched analysis

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Journal of Traditional Chinese Medicine 2024年第1期44卷 197-204页

作者： zhou Xianshi ZHONG Minlin XI Xiaotu LI jun TANG Guanghua the Second Clinical College of Guangzhou University of Chinese Medicine Guangzhou 510120China Emergency Department Guangdong Provincial Hospital of Chinese MedicineGuangzhou 510120China Guangdong Provincial Key Laboratory of Research on Emergency in TCM Guangzhou 510120China Guangzhou Key Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Emerging Infectious Diseases Guangzhou 510120China Administration Department the First Hospital of Guangzhou University of Chinese MedicineGuangzhou 510405China

OBJECTIVE:To investigate the efficacy and safety of Chinese herbal medicine in treating sepsis patients with bloodstream ***:A 6-year retrospective study was carried out at a university hospital in *** sepsis patients with bloodstream infection were *** primary outcome was 28-day mortality after *** score method was used to adjust for possible confounding.28-day mortality was estimated by KaplanMeier analysis and compared using the log-rank *** regression analysis was carried out to identify factors impacting in-hospital mortality ***:Following the application of the propensity score method,a total of 176 patients were *** all-cause 28-day mortality in the control group and Chinese herbal medicine group was 21.6%and 14.8%,***-Meier survival analysis showed that Chinese herbal medicine was associated with a lower hazard ratio(HR)in all-cause 28-day death compared with the control group[HR=0.44,95%CI(0.22,0.90),P0.05).Blood-activating and stasis-eliminating herb administration was associated with reduced inhospital mortality among sepsis patients with bloodstream infection[HR=0.54,95%CI(0.34,0.94),P<0.05].CONCLUSIONS:Chinese herbal medicine,especially the blood-activating and stasis-eliminating herb,might have certain efficacy and safety in treating sepsis patients with bloodstream *** should prescribe blood-activating and stasis-eliminating herb in treating these two coalescent critical diseases as long as no contraindications ***,further studies are needed to validate our results.

关键词： bacteremia medicine Chinese traditional herbal medicine sepsis propensity-matched analysis

Electrocatalytic Multicomponent Cascade Cross-Coupling for the Synthesis of Chalcogenosulfonates

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Chinese Journal of Chemistry 2024年第17期42卷 2049-2055页

作者： Zhiheng Zhao Hongyan Yan Yaqin zhou Wei xue Lijun Gu Shengyong Zhang State Key Laboratoryof Green Pesticide Key Laboratoryof Green Pesticide and Agricultural BioengineeringMinistry of EducationCenter for R&D of Fine Chemicals of Guizhou UniversityGuiyangGuizhou 550025China Schoolof Pharmacy Air Force Medical UniversityShaanxiXi'anShaanxi 710032China

An electrocatalytic multicomponent cascade cross-coupling for the synthesis of chalcogenosulfonates has been *** approach does not require the use of transition metals,acids,and external *** gentle conditions and tole... 详细信息

关键词： Electrochemical catalysis Synthetic methods Radical Multi-component reaction Chalcogenosulfonates Tellurium

Sensing Matrix Optimization for Random Stepped-Frequency Signal Based on Two-Dimensional Ambiguity Function

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Chinese Journal of Electronics 2024年第1期33卷 161-174页

作者： Mingjiu LYU Hao CHEN jun YANG Xia WU Ming zhou Xiaoyan MA Radar NCO School Air Force Early Warning Academy Department of Early Warning Technology Air Force Early Warning Academy

Compressive sensing technique has been widely applied to achieve range-Doppler reconstruction of high frequency radar by utilizing sparse random stepped-frequency(SRSF) signal, which can suppress the complex electromagnetic interference and greatly reduce the coherent processing interval. An important way to improve the performance of sparse signal reconstruction is to optimize the sensing matrix(SM). However, the existing research on the SM optimization needs to design a measurement matrix with superior performance, which needs a large amount of computation and does not consider the influence of the waveform parameters design. In order to improve the superior reconstruction performance, a novel SM optimization approach for SRSF signal is proposed by using two-dimensional ambiguity function(TDAF) in this paper. Firstly, based on the two-dimensional sparse reconstruction model of the SRSFs, the internal relationship between the waveform parameters and the SM was derived. Secondly, the SM optimization problem was directly transformed into the waveform design of SRSFs. Furthermore, on the basis of analyzing the relationship between the mutual coherence matrix of SM and the TDAF matrix of SRSFs, the purpose of optimizing the SM can be achieved by designing the TDAF of the SRSFs. Based on this analysis, a sparse waveform optimization method with joint constraints of maximum and mean sidelobes of the TDAF by using the genetic algorithm was derived. Compared with the traditional SM optimization method, our method not only avoids generating a new measurement matrix, but also further reduces the complexity of the waveform optimization. Simulation experiments verified the effectiveness of the proposed method.

关键词： Correlation Computational modeling Electromagnetic interference Optimization methods Signal reconstruction High frequency radar Sensors

A New Method for the Aging Evaluation of Oil-Paper Insulation Using η-Butanol and Methanol

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 717-726页

作者： Jianyi Wang Yuanxiang zhou jun Liu Zhaowei Wang Song Bai Jiayu Lu Department of High Voltage China Electric Power Research InstituteBeijing 100192China State Key Laboratory of Power Grid Environmental Protection Beijing 100192China Electrical Engineering Department Tsinghua UniversityBeijing 100084China Solar Storage Division of State Key Lab of Power System and Generation Equipment School of Electrical EngineeringXinjiang UniversityUrumqi 830047China State Grid Wuwei Electric Power Supply Company Wuwei 733000China

To improve the accuracy and efficiency of the aging life prediction and assessment of transformer oil-paper insulation,and to make up for the deficiencies of traditional characterizers,such as 2-furfural,carbon monoxide,and carbon dioxide,a method for the simultaneous determination of methanol,ethanol,n−propanol,and η-butanol in oil with a single injection is established by headspace-gas chromatography-mass *** measured results show that the determination limits of the four alcohol characterizers can be controlled to 10μg/kg *** on this method,the change patterns of the above four alcohols with thermal aging time and degree of polymerization are obtained through thermal aging experimental ***,η-propanol,and η-butanol in oil indicate nearly linear correlations with thermal aging time and degree of polymerization,similar to that of *** analyzing 52 sets of measured data of 500 kV EHV transformers in operation,η-butanol is found to have excellent performance,and a new method to evaluate the aging state of oil-paper insulation employing η-butanol and methanol is proposed along with the aging attention value *** measured data of 500 kV EHV transformers in operation indicate that the combination of η-butanol and methanol as the preferred characterizers can effectively compensate for the shortcoming of traditional characterizers in the early stages of aging,and the feasibility of the method is *** possible pathways for the generation of η-butanol by cellulose cleavage during the aging of oil-paper are proposed from the chemical structure of cellulose.

关键词： Aging characterization determination method methanol η-butanol oil-paper insulation 500 kV transformers

Understanding adversarial attacks on observations in deep reinforcement learning

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Science China(Information Sciences) 2024年第5期67卷 69-83页

作者： You QIAOBEN Chengyang YING Xinning zhou Hang SU jun ZHU Bo ZHANG Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua-Bosch Joint Center for Machine Learning Institute for Artificial Intelligence Tsinghua University Peng Cheng Laboratory

Deep reinforcement learning models are vulnerable to adversarial attacks that can decrease the cumulative expected reward of a victim by manipulating its observations. Despite the efficiency of previous optimization-based methods for generating adversarial noise in supervised learning, such methods might not achieve the lowest cumulative reward since they do not generally explore the environmental ***, a framework is provided to better understand the existing methods by reformulating the problem of adversarial attacks on reinforcement learning in the function space. The reformulation approach adopted herein generates an optimal adversary in the function space of targeted attacks, repelling them via a generic two-stage framework. In the first stage, a deceptive policy is trained by hacking the environment and discovering a set of trajectories routing to the lowest reward or the worst-case performance. Next, the adversary misleads the victim to imitate the deceptive policy by perturbing the observations. Compared to existing approaches, it is theoretically shown that our adversary is strong under an appropriate noise level. Extensive experiments demonstrate the superiority of the proposed method in terms of efficiency and effectiveness, achieving state-of-the-art performance in both Atari and MuJoCo environments.

关键词： deep learning reinforcement learning adversarial robustness adversarial attack

Advances of Electrochemical and Electrochemiluminescent Sensors Based on Covalent Organic Frameworks

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Nano-Micro Letters 2024年第2期16卷 395-422页

作者： Yue Cao Ru Wu Yan‑Yan Gao Yang zhou jun‑Jie Zhu Key Laboratory for Organic Electronics and Information Displays(KLOEID)and Institute of Advanced Materials(IAM) Nanjing University of Posts and Telecommunications(NJUPT)Nanjing 210023People’s Republic of China State Key Laboratory of Analytical Chemistry for Life Science School of Chemistry and Chemical EngineeringNanjing UniversityNanjing 210023People’s Republic of China

Covalent organic frameworks(COFs),a rapidly developing category of crystalline conjugated organic polymers,possess highly ordered structures,large specific surface areas,stable chemical properties,and tunable pore *** the first report of boroxine/boronate ester-linked COFs in 2005,COFs have rapidly gained popularity,showing important application prospects in various fields,such as sensing,catalysis,separation,and energy *** them,COFs-based electrochemical(EC)sensors with upgraded analytical performance are arousing extensive *** this review,therefore,we summarize the basic properties and the general synthesis methods of COFs used in the field of electroanalytical chemistry,with special emphasis on their usages in the fabrication of chemical sensors,ions sensors,immunosensors,and ***,the emerged COFs in the electrochemiluminescence(ECL)realm are thoroughly covered along with their preliminary ***,final conclusions on state-of-the-art COFs are provided in terms of EC and ECL sensors,as well as challenges and prospects for extending and improving the research and applications of COFs in electroanalytical chemistry.

关键词： Covalent organic frameworks Electrochemistry Electrochemiluminescence Sensors

Adversarial Defense Technology for Small Infrared Targets

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Computers, Materials and Continua 2024年第1期81卷 1235-1250页

作者： Yu, Tongan xue, Yali He, Yiming Cui, Shan Hong, jun College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210000 China Shanghai Electro-Mechanical Engineering Institute Shanghai 201109 China

With the rapid development of deep learning-based detection algorithms, deep learning is widely used in the field of infrared small target detection. However, well-designed adversarial samples can fool human visual perception, directly causing a serious decline in the detection quality of the recognition model. In this paper, an adversarial defense technology for small infrared targets is proposed to improve model robustness. The adversarial samples with strong migration can not only improve the generalization of defense technology, but also save the training cost. Therefore, this study adopts the concept of maximizing multidimensional feature distortion, applying noise to clean samples to serve as subsequent training samples. On this basis, this study proposes an inverse perturbation eliminationmethod based onGenerativeAdversarialNetworks (GAN)to realize the adversarial defense, and design the generator and discriminator for infrared small targets, aiming to make both of them compete with each other to continuously improve the performance of the model, find out the commonalities and differences between the adversarial samples and the original samples. Through experimental verification, our defense algorithmis not only able to cope with multiple attacks but also performs well on different recognition models compared to commonly used defense algorithms, making it a plug-and-play efficient adversarial defense technique. © 2024 The Authors. Published by Tech Science Press.

关键词： Adversarial machine learning