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Co-transformation of HMs-PAHs in rhizosphere soils and adaptive responses of rhizobacteria during whole growth period of rice(Oryza sativa L.)

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Journal of Environmental sciences 2023年第10期132卷 71-82页

作者： Shengwei Yi Feng Li ChenWu Fei Ge Chuang Feng Ming Zhang Yun Liu Hainan Lu College of Environment Science and Resources Xiangtan UniversityXiangtan 411105China Hunan Engineering Laboratory for High-Efficiency Purification Technology and its Application in Complex Heavy Metal Wastewater Treatment Xiangtan 411105China Scientific Research Innovation Platform of Environmental Behavior and Control Principle about New Pollutants in Hunan Provincial Universities Xiangtan 411105China Department of Environmental Engineering China Jiliang UniversityHangzhou 310018China Shanghai Academy of Environmental Sciences Shanghai 200233China

This study investigated the transformations of heavy metals(HMs) and polycyclic aromatic hydrocarbons(PAHs) in rhizosphere soils and adaptive responses of rhizobacterial community under the real field conditions during four growth stages(e.g., greening, tillering, heading, and maturity) of early rice(Zhongjiazao 17) and late rice(Zhongyou 9918) in Jiangshe village(JSV) and Yangji village(YJV). Results showed that rhizosphere soils of YJV were mildly polluted by Cd and PAHs compared to that of JSV. The relative abundance of bioavailable Cd(bio-Cd) and bioavailable As(bio-As) in rhizosphere soil increased before the heading stage but decreased at the subsequent growth stage, but the content of ΣPAHs in rhizosphere soil decreased gradually during whole growth period. The dominant rhizobacteria genera at YJV(e.g., Bacillus, Massilia, Sphingomonas, and Geobacter) increased at an abundance level from the tillering to heading stage. Rhizobacteria interacted with the above co-pollutant more intensely at the tillering and heading stage, where genes involved in HM-resistance and PAH-degradation appeared to have a significant enhancement. The contents of bioCd and bio-As in rhizosphere soil of early rice were higher than that of late rice at each growth stage, especially at the heading stage. Bio-Cd, ΣPAHs, and organic matter were key factors influencing the community structure of rhizobacteria. Results of this study provide valuable insights about the interactions between HM-PAH co-pollutant and rhizobacterial community under real field conditions and thus develop in-situ rhizosphere remediation techniques for contaminated paddy fields.

关键词： Heavy metals(HMs) PAHs Co-pollutants Rhizobacterial community Paddy field

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Synthesis of multifunctional additives for solid propellants:Structure,properties and mechanism

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Defence technology（防务技术） 2024年第3期33卷 308-316页

作者： Pingan Zhang Lina Sun Jianmin Yuan Jianru Deng College of Chemistry and Chemical Engineering Hunan UniversityChangsha 410082PR China College of Material Science and Engineering Hunan UniversityChangsha 410082PR China Hu Bei Sanjiang Aerospace Jianghe Chemical Technology Co. LtdYichang 444200PR China

To simplify the composite propellant formulation and address the current issue of the single-functionality present in existing additives,the multi-cyano,amine-based polybutadiene(AEHTPB-CN)was prepared based on AEHTPB by adopting appropriate synthesis *** replacing 10% of HTPB binder in the propellant formulation,it can effectively enhance the interfacial bond strength between the propellant binder matrix and solid fillers(AP(ammonium perchlorate)and RDX(cyclotrimethylene-trinitramine)),the mechanical properties of the HTPB/AP/RDX/Al propellant were superior to blank control propellant with an improvement of 35.4% in tensile strength,62.0% enhancement in elongation at break,and reduce the propellant burn rate by 10.7% with any energy *** function mechanism of AEHTPB-CN was systematically elucidated through experiments and computer simulation *** results show that the tertiary amine group in AEHTPB-CN can react with AP to form ammonium ionic bonds,and the hydroxyl and cyano groups can form hydrogen bonding interactions with AP,which enables AEHTPB-CN to be firmly adsorbed on the AP surface through chemical and physical *** RDX,the interfacial bonding effect of AEHTPB-CN is attributed to their ability to form C-H···N≡C weak hydrogen bonding interaction between the cyano group and RDX methylene group.

关键词： Hydroxyl-terminated polybutadiene(HTPB) HTPB propellant Chemical modification Bonding agent Mechanism

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Valorization of Camellia oleifera oil processing byproducts to value-added chemicals and biobased materials: A critical review

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Green Energy & Environment 2024年第1期9卷 28-53页

作者： Xudong Liu Yiying Wu Yang Gao Zhicheng Jiang Zicheng Zhao Wenquan Zeng Mingyu Xie Sisi Liu Rukuan Liu Yan Chao Suli Nie Aihua Zhang Changzhu Li Zhihong Xiao State Key Laboratory of Utilization of Woody Oil Resource Hunan Academy of ForestryChangsha410004China Key Laboratory of State Forestry and Grassland Administration on Utilization Science for Southern Woody Oil Resource Hunan Academy of ForestryChangsha410004China Hunan Provincial Key Laboratory of Oils and Fats Molecular Structure and Function Changsha410004China State Key Laboratory of Separation Membranes and Membrane Processes College of ChemistryTiangong UniversityTianjin300387China College of Biomass Science and Engineering Sichuan UniversityChengdu610065China College of Mechanical Engineering and Mechanics Xiangtan UniversityXiangtan411105China

The *** oil processing industry generates large amounts of solid wastes,including *** shell(COS)and *** cake(COC).Distinct from generally acknowledged lignocellulosic biomass(corn stover,bamboo,birch,etc.),Camellia wastes contain diverse bioactive substances in addition to the abundant lignocellulosic components,and thus,the bioreﬁnery utilization of *** processing byproducts involves complicated processing *** reviewﬁrst summarizes various technologies for extracting and converting the main components in *** oil processing byproducts into value-added chemicals and biobased materials,as well as their potential ***,ultrasound,and Soxhlet extractions are compared for the extraction of functional bioactive components(tannin,ﬂavonoid,saponin,etc.),while solvothermal conversion and pyrolysis are discussed for the conversion of lignocellulosic components into value-added *** application areas of these chemicals according to their properties are introduced in detail,including utilizing antioxidant and anti-in-ﬂammatory properties of the bioactive substances for the speciﬁc application,as well as drop-in chemicals for the substitution of unrenewable fossil fuel-derived *** addition to chemical production,biochar fabricated from COS and its applications in theﬁelds of adsorption,supercapacitor,soil remediation and wood composites are comprehensively reviewed and ***,based on the compositions and structural characteristics of *** byproducts,the development of full-component valorization strategies and the expansion of the appli-cationﬁelds are proposed.

关键词： Camellia oleifera shell Camellia oleifera cake Value-added chemicals Bioactive components Biobased materials

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Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

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In-Memory Computing Accelerator for Iterative Linear Algebra Solvers

IEEE Computer Architecture Letters

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IEEE computer Architecture Letters 2025年第1期24卷 161-164页

作者： Liu, Rui Li, Zerun Zhang, Xiaoyu Chen, Xiaoming Han, Yinhe Tang, Minghua Xiangtan University School of Materials Science and Engineering Hunan China Chinese Academy of Sciences Institute of Computing Technology Beijing China University of Chinese Academy of Sciences Beijing100190 China

Iterative linear solvers are a crucial kernel in many numerical analysis problems. The performance and energy efficiency of iterative solvers based on traditional architectures are severely constrained by the memory wall bottleneck. Computing-in-memory (CIM) has the potential to enhance solving efficiency. Existing CIM architectures are mostly customized for specific algorithms and primarily focus on handling fixed-point operations, which makes them difficult to meet the demands of diverse and high-precision applications. In this work, we propose a CIM architecture that natively supports various iterative linear solvers based on floating-point operations. We develop a new instruction set for the accelerator, which can be flexibly combined to implement various iterative solvers. The evaluation results show that, compared with the GPU implementation, our accelerator achieves more than 10.1× speedup and 6.8× energy savings when executing different iterative solvers. © 2002-2011 IEEE.

关键词： Fixed point arithmetic

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On Mixed Model for Improvement in Stock Price Forecasting

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computer Systems science & engineering 2022年第5期41卷 795-809页

作者： Qunhui Zhang Mengzhe Lu Liang Dai Hunan Vocational College of Science and Technology ChangshaChina Hunan University of Finance and Economics ChangshaChina Xiangtan University XiangtanChina University Malaysia Sabah Kota KinabaluMalaysia

Stock market trading is an activity in which investors need fast and accurate information to make effective *** the fact is that forecasting stock prices by using various models has been suffering from low accuracy,slow convergence,and complex *** study aims to employ a mixed model to improve the accuracy of stock price *** present how to use a random walk based on jump-diffusion,to obtain stock predictions with a good-fitting degree by adjusting different *** at getting better parameters and then using the time series model to predict the data,we employed the time series model to smooth the sequence utilizing logarithm and difference,which successfully resulted in drawing the auto-correlation figure and partial the auto-correlation *** to the comparative analysis,which focuses on checking the mean absolute error,including root mean square error and R square evaluation index,we have drawn a clear conclusion that our mixed model prediction effect is relatively *** the context of Chinese stocks,the hybrid random walk model is very suitable for predicting *** can“interpret”the randomness of stocks very well,and it also has an unparalleled prediction effect compared with other *** on the time series model’s application in this paper,the abovementioned series is more suitable for predicting trends.

关键词： Random walk model time series model stock forecasting

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Interpretable multi-view attention network for drug-drug interaction prediction

Interpretable multi-view attention network for drug-drug int...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Lin, Xuan Wen, Qi Yang, Sijie Yu, Zu-Guo Long, Yahui Zeng, Xiangxiang Xiangtan University College of Computer Science China Xiangtan University Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education China Singapore Hunan University College of Information Science and Engineering China

ISBN: (纸本)9798350337488

Drug-drug interaction (DDI) plays an increasingly crucial role in drug discovery. Predicting potential DDI is also essential for clinical research. Given the high cost and risk of wet-lab experiments, in-silico DDI prediction is an alternative choice. Recently, deep learning methods have been developed for DDI prediction. However, most of existing methods focus on feature extraction from either molecular SMILES sequences or drug interactive networks, ignoring the valuable complementary information that can be derived from these two views. In this paper, we propose a novel interpretable Multi-View Attention network (MVA-DDI) for DDI prediction. MVA-DDI can effectively extracts drug representations from different perspectives to improve DDI prediction. Specifically, for a given drug, we design a transformer-based encoder and a graph convolutional networkbased encoder to learn sequence and graph representations from SMILES sequence and molecular graph, respectively. To fully exploit the complementary information between the sequence and molecular views, an attention mechanism is further adopted to adaptively aggregate the sequence and graph representations by taking the importance of different views into accounts, generating the final drug representations. Comparison experiments demonstrated that our MVA-DDI1 model achieved superior performance to state-of-the-art models on DDI prediction. © 2023 IEEE.

关键词： Contrastive learning Drug-drug interaction prediction Interpretable attention network Multi-view learning

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A Web Service Recommendation Method Based on Adaptive Gate Network and xDeepFM 1

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22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Tao, Zhi Cao, Buqing Ye, Hongfan Kang, Guosheng Peng, Zhenlian Wen, Yiping School of Computer Science and Engineering and Hunan Key Laboratory of Service Computing and New Software Service Technology Hunan University of Science and Technology Hunan Xiangtan China School of Computer and Artificial Intelligence Huaihua University Huaihua China

ISBN: (数字)9783031226779

ISBN: (纸本)9783031226762

With the rapid development of service computing technology, more and more companies and organizations are encapsulating and publishing their operational data or resources to the Internet in the form of Web services, resulting in an exponential increase in the number of Web services. To automatically generate or recommend a group of Web services according to the user's natural language requirements description, to build a Mashup application to meet the user's requirement is a hot topic in service computing. Some researchers enhance the quality of Web service recommendation by using auxiliary information into the recommendation system. However, they mainly focus on adding external information (e.g., pre-training of external corpora) to enhance semantic features, while some internal statistical features of the corpus such as word distribution on labels and frequency are not fully exploited. Compared to other exterior knowledge, statistical features are naturally compatible with Web service recommendation tasks. To fully exploit the statistical features, this paper proposes a Web service recommendation method based on adaptive gate network and xDeepFM model. In this method, firstly, the description document of Web services is taken as the basic corpus, the semantic and statistical information in the corpus are mined by utilizing the adaptive gate network, and the statistical features are encoded by a variational encoder. Secondly, the similarity between Web services is derived from the semantic features, at the same time the popularity and co-occurrence of Web services are calculated. Thirdly, the xDeepFM model is used to mine the explicit and implicit higher-order interactions in the sparse matrix which consists of the above information to recommend Web services for Mashup application. Finally, a multiple sets of experiments based on the dataset crawled from the ProgrammableWeb have been conducted to evaluate the proposed method and the experimental result shows that t

关键词： Web services

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VmPTP: Precise Time Protocol for Inter-VM Communication in Embedded Virtualized Systems

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年第3期44卷 897-910页

作者： Zhao, Sirong Xie, Guoqi Ma, Wenhong Ren, Wei Li, Kenli Hunan University Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan Changsha410082 China Huawei Technology Co. Ltd. Central Software Institute Guangdong Shenzhen518129 China

System virtualization techniques are gradually applied to embedded systems with the performance improvement of embedded devices;however, there is a large time offset (i.e., deviation) of hundreds of ms between virtual machines (VMs) due to the drift of the virtualization abstraction layer and the jitter phenomenon. It is urgent to significantly reduce this offset by time synchronization techniques. Unfortunately, the current mainstream time synchronization software (e.g., Chrony and LinuxPTP) cannot be used in the embedded virtualized system connected by the fieldbus, such as controller area network (CAN);meanwhile, drift correction-based time synchronization techniques dedicated to CAN bus cannot be utilized for virtualized systems. In this study, we design a general vmPTP, which is a precise time protocol (PTP) for inter-VM communication in embedded virtualized systems based on Linux kernel-based VM (KVM). This is the first time synchronization work focused on embedded virtualized systems. We implement two vmPTP versions based on VirtIO and inter-VM shared memory (IVSHMEM) according to the four message (i.e., packet) exchanges of PTP. We propose an asymmetry compensation strategy to solve the problem of asymmetric rate of I/O operations in the message exchange process, which optimizes the offset computation. We further produce a convergence stopping approach which can continuously converge the offset until the offset is within the given bound and stop. We conduct experimental evaluations on both X86-64 and ARM64 architectures. For two versions of vmPTP, the experimental results show that: 1) the offsets are always within 1μ s on two architectures;2) the offsets are less than that of LinuxPTP and Chrony;and 3) the vmPTP's CPU and memory utilization on the X86-64 architecture are merely 0.3% and 0.1%, respectively, whereas those on the ARM64 architecture are 3.8% and 0.1%, respectively. We experiment with vmPTP in real-time application and the result demonstrates th

关键词： Linux

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A lightweight deep learning model with knowledge distillation for pulmonary diseases detection in chest X-rays

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Multimedia Tools and Applications 2025年第15期84卷 14885-14913页

作者： Asham, Mohammed A. Al-Shargabi, Asma A. Al-Sabri, Raeed Meftah, Ibrahim School of Computer Science and Engineering Central South University Hunan Changsha410083 China Department of Information Technology Collage of Computer Qassim University Buraydah51452 Saudi Arabia College of Mechanical and Electrical Engineering Central South University Changsha410017 China

Accurate and timely diagnosis of pulmonary diseases is critical in the field of medical imaging. While deep learning models have shown promise in this regard, the current methods for developing such models often require extensive computing resources and complex procedures, rendering them impractical. This study focuses on the development of a lightweight deep-learning model for the detection of pulmonary diseases. Leveraging the benefits of knowledge distillation (KD) and the integration of the ConvMixer block, we propose a novel lightweight student model based on the MobileNet architecture. The methodology begins with training multiple teacher model candidates to identify the most suitable teacher model. Subsequently, KD is employed, utilizing the insights of this robust teacher model to enhance the performance of the student model. The objective is to reduce the student model's parameter size and computational complexity while preserving its diagnostic accuracy. We perform an in-depth analysis of our proposed model's performance compared to various well-established pre-trained student models, including MobileNetV2, ResNet50, InceptionV3, Xception, and NasNetMobile. Through extensive experimentation and evaluation across diverse datasets, including chest X-rays of different pulmonary diseases such as pneumonia, COVID-19, tuberculosis, and pneumothorax, we demonstrate the robustness and effectiveness of our proposed model in diagnosing various chest infections. Our model showcases superior performance, achieving an impressive classification accuracy of 97.92%. We emphasize the significant reduction in model complexity, with 0.63 million parameters, allowing for efficient inference and rapid prediction times, rendering it ideal for resource-constrained environments. Outperforming various pre-trained student models in terms of overall performance and computation cost, our findings underscore the effectiveness of the proposed KD strategy and the integration of the Conv

关键词： Diagnosis

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