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Ammonia-induced CuO/13X for H_(2)S removal from simulated blast furnace gas at low temperature

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Green Energy & Environment 2025年第1期10卷 139-149页

作者： Erping Cao yuhua Zheng Hao zhang Jianshan Wang yuran li Tingyu Zhu zhan-guo zhang Guangwen Xu Yanbin Cui State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing100190China State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization PanGang Group Research Institute Co.Ltd.Panzhihua Sichuan617000China Shenyang University of Chemical Technology Shenyang110142China University of Chinese Academy of Sciences Beijing 100049China

Blast furnace gas(BFG)is an important by-product energy for the iron and steel industry and has been widely used for heating or electricity ***,the undesirable contaminants in BFG(especially H_(2)S)generate harmful environmental *** desulfurization of BFG is urgent for integrated steel plants due to the stringent ultra-low emission *** with other desulfurization materials,zeolite-based adsorbents represent a viable option with low costs and long service *** this study,an ammonia-induced CuO modified 13X adsorbent(NH3–CuO/13X)was prepared for H_(2)S removal from simulated BFG at low *** XRD,H_(2)-TPR and TEM analysis proved that smaller CuO particles were formed and the dispersion of Cu on the surface of 13X zeolite was improved via the induction of *** on H_(2)S adsorption performance of the adsorbent was carried out using simulated BFG,and the results showed that NH3–CuO/13X-3 has better breakthrough sulfur capacity,which was more than twice the sulfur capacity of CuO/*** is proposed that the enhanced desulfurization performance of NH3–CuO/13X is attributed to an abundant pore of 13X,and combined action of 13X and *** work provided an effective way to improve the sulfur capacity of zeolite-based adsorbents via impregnation method by ammonia induction.

关键词： Blast furnace gas Desulfurization Ammonia-induced CuO 13X zeolite

An embedded electron current layer observed at the edge of the plasma sheet in the Earth’s magnetotail

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Earth and Planetary Physics 2025年第1期9卷 148-158页

作者： ChenChen zhan RongSheng Wang QuanMing Lu San Lu xinMin li Deep Space Exploration Laboratory/School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China Chinese Academy of Sciences(CAS)Center for Excellence in Comparative Planetology/CAS Key Laboratory of Geospace Environment/Anhui Mengcheng National Geophysical Observatory University of Science and Technology of ChinaHefei 230026China Collaborative Innovation Center of Astronautical Science and Technology Harbin 150001China

The formation of an embedded electron current sheet within the magnetotail plasma sheet has been poorly *** this article,we present an electron current layer detected at the edge of the magnetotail plasma *** ions were demagnetized inside the electron current layer,but the electrons were still frozen in with the magnetic field ***,this decoupling of ions and electrons gave rise to a strong Hall electric field,which could be the reason for the formation of the embedded thin current *** magnetized electrons,the absence of the nongyrotropic electron distribution,and negligible energy dissipation in the layer indicate that magnetic reconnection had not been triggered within the embedded thin current *** highly asymmetric plasma on the two sides of the current layer and low magnetic shear across it could suppress magnetic *** observations indicate that the embedded electric current layer,probably generated by the Hall electric field,even down to electron scale,is not a sufficient condition for magnetic reconnection.

关键词： magnetotail plasma sheet magnetic reconnection

Utilization-Aware Data Variable Allocation on NVM- Based SPM in Real-Time Embedded Systems

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Journal of Electronic Science and Technology 2021年第2期19卷 163-172页

作者： jin-yu zhan.yi-xin li Wei Jiang Jun-Huan Yang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054 State Key Lab of Mathematical Engineering and Advanced Computing Wuxi 214000

With the development of the nonvolatile memory(NVM),using NVM in the design of the cache and scratchpad memory(SPM)has been *** paper presents a data variable allocation(DVA)algorithm based on the genetic algorithm for NVM-based SPM to prolong the *** lifetime can be formulated indirectly as the write counts on each SPM *** the differences between global variables and stack variables,our optimization model has three *** constraints of the central processing unit(CPU)utilization and size are used for all variables,while no-overlay constraint is only used for stack *** satisfy the constraints of the optimization model,we use the greedy strategy to generate the initial population which can determine whether data variables are allocated to SPM and distribute them evenly on SPM ***,we use the Mälardalen worst case executive time(WCET)benchmark to evaluate our *** experimental results show that the DVA algorithm can not only obtain close-to-optimal solutions,but also prolong the lifetime by 9.17% on average compared with SRAM-based SPM.

关键词： Data variables allocation genetic algorithm nonvolatile momory(NVM) scratchpad memory(SPM)

Power-Aware Data Management Based on Hybrid RAM-NVM Memory for Smart Bracelet

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Journal of Electronic Science and Technology 2017年第4期15卷 385-390页

作者： jin-yu zhan Jun-Huan Yang Wei Jiang yi-xin li yi-Ming zhang School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054 China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi 214000China

Wearable devices become popular because they can help people observe health *** battery life is the critical problem for wearable devices. The non-volatile memory(NVM) attracts attention in recent years because of its fast reading and writing speed, high density, persistence, and especially low idle power. With its low idle power consumption,NVM can be applied in wearable devices to prolong the battery lifetime such as smart bracelet. However, NVM has higher write power consumption than dynamic random access memory(DRAM). In this paper, we assume to use hybrid random access memory(RAM)and NVM architecture for the smart bracelet *** paper presents a data management algorithm named bracelet power-aware data management(BPADM) based on the architecture. The BPADM can estimate the power consumption according to the memory access, such as sampling rate of data, and then determine the data should be stored in NVM or DRAM in order to satisfy low power. The experimental results show BPADM can reduce power consumption effectively for bracelet in normal and sleeping modes.

关键词： Hybrid memory non-volatile memory(NVM) power-aware smart bracelet

Self-Triggered Impulsive Control for Nonlinear Stochastic Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期 264-266页

作者： Tao zhan.yi Ji Yabin Gao Hongyi li yuanqing Xia the School of Mathematics and Statistics Southwest University the School of Astronautics Harbin Institute of Technology IEEE the College of Electronic and Information Engineering Southwest University Zhongyuan University of Technology the School of Automation Beijing Institute of Technology

Dear Editor,This letter deals with the stabilization problem of nonlinear stochastic systems via self-triggered impulsive control(STIC), where the timing of impulsive control actions is not dependent on continuous state monitoring. In contrast to the existing self-triggered control method, novel self-triggered mechanism(STM) is proposed by incorporating a waiting time for stabilizing impulses. This allows for direct prediction of the next impulsive instant.

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A blind watermarking algorithm for 3D mesh models based on vertex curvature

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Journal of Zhejiang University-Science C(Computers and Electronics) 2014年第5期15卷 351-362页

作者： Yong-zhao zhan Yan-ting li xin-yu WANG yi QIAN School of Computer Science and Communication Engineering Jiangsu University

We propose a robust blind watermarking algorithm for three-dimensional(3D)mesh models based on vertex curvature to maintain good robustness and improve visual masking in 3D mesh *** the embedding process,by using the local window of vertex,the root mean square curvature is calculated for every vertex of the 3D mesh model and an ordered set of fluctuation values is *** to the ordered fluctuation values,the vertices are separated into *** each bin the fluctuation values are ***,the mean of the root mean square curvature fluctuation values of the vertices in each bin is modulated to embed watermark *** watermark detection,the algorithm uses a blind watermark extraction technique to extract the watermark *** experimental results show that the algorithm has a very good performance for visual masking of the embedded model and that it can resist a variety of common attacks such as vertex rearrangement,rotation,translating,uniform scaling,noise,smoothing,quantization,and simplification.

关键词： Three-dimensional mesh model Visual masking Root mean square curvature Blind watermarking Attack resisting

MDCFS: few-shot object detection with multilevel decoupled classifiers

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Optoelectronics Letters 2025年

作者： li Chuanhui ZHOU Mian FENG Zhikun SUI Zezhou GAO zhan School of Computer Science and Engineering， Tianjin University of Technology

Few-shot object detection poses unique challenges as it requires effectively learning novel classes with limited labeled data. Current approaches often suffer from biases towards base classes during fine-tuning， leading to suboptimal performance on detecting novel classes. Additionally， in complex scenes， the confusion between foreground and background objects further affects the accuracy and robustness of the model. To address these issues， we propose the Multilevel Decoupling Classification Few-Shot Algorithm (MDCFS). we decouple the standard classifier into a parallel foreground classifier and a background classifier in the Few-Shot Object Detection (FSOD) setting. This decoupling enables the independent separation of positive samples from noisy negative samples， alleviating the foreground-background confusion problem commonly encountered in few-shot detectors. For Generalized Few-Shot Object Detection (G-FSOD)， where the few-shot dataset contains base classes， we further decouple the foreground classification head into a base class classification head and a novel class classification head. To ensure balance， we assign more weight to the novel class classification head， effectively addressing the bias towards base classes. Furthermore， we optimize the initial weights of the few-shot fine-tuning stage， significantly reducing training time and mitigating catastrophic forgetting in G-FSOD. Additionally， we incorporate metric learning into our model with minimal cost. Experimental results demonstrate the effectiveness of our approach. Compared to state-of-the-art few-shot object detection methods based on fine-tuning， MDCFS achieves performance improvements of up to 6.3% on the PASCAL VOC dataset and 1.5% on the COCO dataset.

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Deep multiple instance selection

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Science China(Information Sciences) 2021年第3期64卷 18-32页

作者： xin-Chun li De-Chuan zhan Jia-Qi YANG yi SHI State Key Laboratory for Novel Software Technology Nanjing University

Multiple instance learning(MIL) assigns a single class label to a bag of instances tailored for some real-world applications such as drug activity prediction. Classical MIL methods focus on figuring out interested instances, that is, region of interests(ROIs). However, owing to the non-differentiable selection process, these methods are not feasible in deep learning. Thus, we focus on fusing ROIs identification with deep MILs in this paper. We propose a novel deep MIL framework based on hard selection, that is, deep multiple instance selection(DMIS), which can automatically figure ROIs out in an end-to-end *** be specific, we propose DMIS-GS for instance selection via gumbel softmax or gumbel top-k, and then make predictions for this bag without the interference of redundant instances. For balancing exploration and exploitation of key instances, we apply a cooling down approach to the temperature in DMIS-GS, and propose a variance normalization method to make this hyper-parameter tuning process much easier. Generally, we give a theoretical analysis of our framework. The empirical investigations reveal the proposed frameworks' superiorities against classical MIL methods on generalization ability, positioning ROIs, and comprehensibility on both synthetic and real-world datasets.

关键词： multiple instance learning instance selection gumbel softmax variance normalization hard attention

Preparation of urea-formaldehyde paraffin microcapsules modified by carboxymethyl cellulose as a potential phase change material

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Journal of Forestry Research 2015年第1期26卷 253-260页

作者： zhan-hua Huang xin yu Wei li Shou-xin liu Key Laboratory of Bio-based Material Science and Technology Ministry of EducationNortheast Forestry University

We prepared spherical microcapsules modified by carboxymethyl cellulose（CMC） with urea-formaldehyde（UF） resin as a shell material with a two-step process by in situ polymerization, and characterized the microcosmic features, chemical structure, and thermal performance of the microcapsules by SEM, FTIR, DSC, and TGA. We studied the effects of different experimental parameters of curing p H, the amounts of the emulsifier and emulsion speed. The CMC-UF microcapsules had good heat resistance and stability. The enthalpy of CMC-UF microcapsules reached 50.33 J g-1. Therefore, CMC-UF resin can be used as a potential wall material of phase change materials.

关键词： Spherical microcapsules Carboxymethyl cellulose Energy storage