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Experimental investigation on high heat flux plasma parameters of HIT-PSI device in argon discharges

Plasma science and technology 2025年第1期27卷 118-127页

作者： Tao HUANG Qiuyue NIE Cheng CHEN Lin NIE Wei ZHAO Tao JIANG Yang LIU Xu ZHAO Feng LI Xiaogang WANG School of Physics Harbin Institute of TechnologyHarbin 150001People’s Republic of China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001People’s Republic of China Laboratory for Space Environment and Physical Science Harbin Institute of TechnologyHarbin 150001People’s Republic of China Southwestern Institute of Physics Chengdu 610041People’s Republic of China

Researches on plasma-facing materials/components(PFMs/PFCs)have become a focus in magnetic confinement fusion studies,particularly for advanced tokamak operation ***,spacecraft surface materials must maintain stable performance under relatively high temperatures and other harsh plasma conditions,making studies of their thermal and ablation resistance ***,a low-cost,low-energy-storage for superconducting magnets,and compact linear device,HIT-PSI,has been designed and constructed at harbin institute of technology(HIT)to investigate the interaction between stable high heat flux plasma and PFMs/PFCs in scrape-off-layer(SOL)and divertor regions,as well as spacecraft surface *** parameters of the argon plasma beam of HIT-PSI are diagnosed using a water-cooled planar Langmuir probe and emission *** magnetic field rises to 2 T,the argon plasma beam generated by a cascaded arc source achieves high density exceeding 1.2×10^(21)m^(-3)at a distance of 25 cm from the source with electron temperature surpassing 4 eV,where the particle flux reaches 10^(24)m^(-2)s^(-1),and the heat flux loaded on the graphite target measured by infrared camera reaches 4 MW/m^(2).Combined with probe and emission spectroscopy data,the transport characteristics of the argon plasma beam are analyzed.

关键词： linear plasma device plasma-material interaction high heat flux high particle flux

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Microstructure and magnetocaloric properties of melt-extracted SmGdDyCoAl high-entropy amorphous microwires

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Rare Metals 2024年第3期43卷 1234-1242页

作者： Shi-Jie Wei Hong-Xian Shen Lun-Yong Zhang Lin Luo Xin-Xing Tang Jian-Fei Sun Xiao-Qing Li School of Materials Science and Engineering Harbin Institute of TechnologyHarbin150001China Applied Materials Physics Department of Materials Science and EngineeringKTH-Royal Institute of Technology10044StockholmSweden

This paper presents a systematic investigation of the microstructure and magnetocaloric properties of melt-extracted Sm_(20)Gd_(20)Dy_(20)Co_(20)Al_(20)high-entropy *** fabricated wires exhibited an amorphous structure,and the temperature interval of the undercooled liquid AT was 45 *** microwires underwent a second-order magnetic transition from a ferromagnetic to a paramagnetic state near the Curie temperature(T_(C)=52 K),The maximum magnetic entropy change(-ΔS_M^(max)),the relative cooling power and the refrigeration capacity reached 6.34 J·kg^(-1)·K^(-1).422.09 J·kg^(-1)and 332.94 J·kg^(-1),respectively,under a magnetic field change of 5 *** addition,the temperature-averaged entropy changes with two temperature lifts(3 and 10 K)were 6.32 and 6.27 J·kg^(-1)·K^(-1),*** good magnetocalorie performance highlights the significant potential for the Sm_(20)Gd_(20)Dy_(20)Co_(20)Al_(20)microwires to be used as magnetic refrigerant materials in low-temperature region *** work will serve as a valuable reference for future investigations on low-temperature high-entropy magnetocaloric materials.

关键词： Melt-extraction High-entropy amorphous microwires Magnetocaloric effect Magnetic refrigeration

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LucIE: Language-guided local image editing for fashion images

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Computational Visual Media 2025年第1期11卷 179-194页

作者： Huanglu Wen Shaodi You Ying Fu School of Computer Science and Technology Beijing Institute of TechnologyBeijingChina Computer Vision Research Group in the Institute of Informatics University of AmsterdamAmsterdamthe Netherlands

Language-guided fashion image editing is challenging,as fashion image editing is local and requires high precision,while natural language cannot provide precise visual information for *** this paper,we propose LucIE,a novel unsupervised language-guided local image editing method for fashion *** adopts and modifies recent text-to-image synthesis network,DF-GAN,as its ***,the synthesis backbone often changes the global structure of the input image,making local image editing *** increase structural consistency between input and edited images,we propose Content-Preserving Fusion Module(CPFM).Different from existing fusion modules,CPFM prevents iterative refinement on visual feature maps and accumulates additive modifications on RGB *** achieves local image editing explicitly with language-guided image segmentation and maskguided image blending while only using image and text *** on the DeepFashion dataset shows that LucIE achieves state-of-the-art *** with previous methods,images generated by LucIE also exhibit fewer *** provide visualizations and perform ablation studies to validate LucIE and the *** also demonstrate and analyze limitations of LucIE,to provide a better understanding of LucIE.

关键词： deep learning language-guided image editing local image editing content preservation fashion images

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Fiber-tip optic sensor based on a three-beam interferometer for simultaneous measurement of flow rate and temperature

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Optics Express 2025年第6期33卷 12509-12518页

作者： Li, Wenxue Li, Jinjian Ye, Jingfu Xu, Weijiang Liu, Yi Qu, Shiliang School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin541004 China School of Science Harbin Institute of Technology Weihai264209 China School of Physics Harbin Institute of Technology Harbin150001 China

Precise monitoring of the microfluidic flow rate is a key factor in microfluidic chips. However, the temperature of the microfluidics often affects the measuring results of the optical flow rate sensor. Here, we present a fiber-tip optical sensor based on a three-beam interferometer that can measure microfluidic flow rate and temperature simultaneously. The optical fiber sensor is composed of UV adhesive at the bottom of the microcavity sealed by liquid paraffin, and a section of air is reserved in the hollow core fiber (HCF). The flow of microfluidics will affect the pressure of the air cavity formed by UV adhesive and the paraffin. Microfluidics with different flow rates in the channel of the microfluidic chip have different effects on the position of the liquid paraffin in the cavity. Because of the small viscous force between the paraffin and the inner wall of the HCF, the length of the air cavity changed greatly as the flow rate changed resulting in a high flow rate sensitivity. The UV adhesive as a temperature measuring part has a high thermo-optical coefficient (TOC), as a temperature measuring part, utilized to measure the temperature of the microfluidics. The length variation of air cavity and refractive index (RI) of UV adhesive will cause the shifting of the dips in the interference spectrum. The rate sensitivity can reach −22.51 nm/(mm/s) in the range of 0.17 mm/s to 1.17 mm/s. In addition, the sensor has a stable temperature sensitivity of 13.513 nm/℃. This work provides a low-cost sensing platform for measuring various physical parameters in microfluidic chips, which is of great significance for on-chip biochemical reactions. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Temperature measurement

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Research on stock trend prediction method based on optimized random forest

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CAAI Transactions on Intelligence technology 2023年第1期8卷 274-284页

作者： Lili Yin Benling Li Peng Li Rubo Zhang School of Computer and Science and Technology Harbin University of Science and TechnologyHarbinChina Department of Computer Science and Engineering Dalian Nationalities UniversityDalianChina

As a complex hot problem in the financial field,stock trend forecasting uses a large amount of data and many related indicators;hence it is difficult to obtain sustainable and effective results only by relying on empirical *** in the field of machine learning have proved that random forest can form better judgements on this kind of problem,and it has an auxiliary role in the prediction of stock *** study uses historical trading data of four listed companies in the USA stock market,and the purpose of this study is to improve the performance of random forest model in medium-and long-term stock trend *** study applies the exponential smoothing method to process the initial data,calculates the relevant technical indicators as the characteristics to be selected,and proposes the D-RF-RS method to optimize random *** the random forest is an ensemble learning model and is closely related to decision tree,D-RF-RS method uses a decision tree to screen the importance of features,and obtains the effective strong feature set of the model as ***,the parameter combination of the model is optimized through random parameter *** experimental results show that the average accuracy of random forest is increased by 0.17 after the above process optimization,which is 0.18 higher than the average accuracy of light gradient boosting machine *** with the performance of the ROC curve and Precision–Recall curve,the stability of the model is also guaranteed,which further demonstrates the advantages of random forest in medium-and long-term trend prediction of the stock market.

关键词： ensemble learning finance random forest random search technical indicator

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Fast Memory Disaggregation with SwiftSwap 20th

Fast Memory Disaggregation with SwiftSwap

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20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Zhang, Xiangwei Wang, Desheng Zhang, Weizhe Yu, Zhiji Hao, Meng School of Computer Science and Technology Harbin Institute of Technology Guangdong Shenzhen518055 China School of Cyberspace Science Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9789819628292

With the continuous evolution of cloud computing technology, the memory requirements of cloud servers are increasing. Insufficient memory has become the performance bottleneck of many applications. Memory disaggregation has been proposed to solve this problem, which enables computing nodes to utilize the memory of remote memory nodes, thus not only effectively extending the capacity of logical memory, but also significantly improving the resource utilization and elasticity of the whole cluster, providing a more flexible resource allocation scheme for large-scale parallel computing and data processing. However, most of the existing memory disaggregation systems require modification of hardware, operating systems or applications, which are difficult to use. This paper proposes a high-performance memory disaggregation system SwiftSwap, which can directly access remote memory without any modification of hardware, operating system, or application. We design and implement a high performance cache, cache lookup algorithm LDA and cache elimination strategy RM_AwareLRU on the computing node to improve the performance of the system. Through comprehensive evaluation, SwiftSwap has up to 5.1× performance advantage in throughput, 4.8× performance advantage in tail delay, and 6.4× performance advantage against applications running in containers. © IFIP International Federation for Information Processing 2025.

关键词： Resource allocation

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The iron-based biochar activating chlorite(ClO_(2)^(−))driven by mechanochemical ultrasonic:piecewise kinetics,biomimetic catalytic-mechanism,and novel advanced redox process

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Frontiers of Environmental science & Engineering 2025年第2期19卷 151-168页

作者： Qihui Xu Qianhui Yang Yuming Xie Lin Hu Zhenghao Fei Hong You School of Chemical and Environmental Engineering Yancheng Teachers UniversityYancheng 224007China State Key Laboratory of Urban Water Resources and Environment Harbin Institute of TechnologyHarbin 150090China School of Marine Science and Technology Harbin Institute of Technology at WeihaiWeihai 264209China

Chlorite(ClO_(2)^(−)or COI)is used to establish the advanced reduction and oxidation process(AROP).The iron/biochar-based particles(iron-based hydrothermal carbon with hinge-like structure,FebHCs,20 mg/L)can be utilized to activate COI(2 mmol/L)to present selective oxidation in removing triphenylmethane derivatives(15 min,90%).The protonation(H+at~102μmol/L level)played a huge role(k-2nd=0.136c-H+−0.014(R^(2)-adj=0.986),and rapp=−0.0876/c-H++1.017(R^(2)-adj=0.996))to boost the generation of the active species(e.g.,high-valent iron oxidizing species(HVI=O)and chlorine dioxide(ClO_(2))).The protonation-coupled electron transfer promoted Fe-substances in Feb/HCs activating COI(the calculated kobs ranging from 0.066−0.285 min^(−1)).The form of ClO_(2) mainly attributed to proton-coupled electron transfer(1e/1H+).The HVI=O was generated from the electron transfer within the coordination ***,carbon particles in FebHCs serve as the bridge for electron *** above roles contribute to the fracture and formation of coordination-induced bonds between Lx-FeII/III and ClO_(2)^(−)at phase interface to form *** ultrasonic(US)cavitation enhanced the mass transfer of active species in bulk solution,and the HVI=O and ClO_(2) attack unsaturated central carbon atoms of triphenylmethane derivatives to initiate selective ***,the scale-up experiment with continuous flow(k values of approximately 0.2 min^(−1),COD removal efficiency of approximately 80%)and the reactor with COMSOL simulation have also proved the applicability of the *** study offers a novel AROP and new insights into correspondingly heterogeneous interface activation mechanisms.

关键词： Chlorite Iron-based biochar Ultrasonic Chlorine dioxide High-valent iron oxidizing species

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Robust video question answering via contrastive cross-modality representation learning

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science China(Information sciences) 2024年第10期67卷 211-226页

作者： Xun YANG Jianming ZENG Dan GUO Shanshan WANG Jianfeng DONG Meng WANG School of Information Science and Technology University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center School of Computer Science and Information Engineering Hefei University of Technology Institutes of Physical Science and Information Technology Anhui University School of Computer Science and Technology Zhejiang Gongshang University

Video question answering(VideoQA) is a challenging yet important task that requires a joint understanding of low-level video content and high-level textual semantics. Despite the promising progress of existing efforts, recent studies revealed that current VideoQA models mostly tend to over-rely on the superficial correlations rooted in the dataset bias while overlooking the key video content, thus leading to unreliable results. Effectively understanding and modeling the temporal and semantic characteristics of a given video for robust VideoQA is crucial but, to our knowledge, has not been well investigated. To fill the research gap, we propose a robust VideoQA framework that can effectively model the cross-modality fusion and enforce the model to focus on the temporal and global content of videos when making a QA decision instead of exploiting the shortcuts in datasets. Specifically, we design a self-supervised contrastive learning objective to contrast the positive and negative pairs of multimodal input, where the fused representation of the original multimodal input is enforced to be closer to that of the intervened input based on video perturbation. We expect the fused representation to focus more on the global context of videos rather than some static keyframes. Moreover, we introduce an effective temporal order regularization to enforce the inherent sequential structure of videos for video representation. We also design a Kullback-Leibler divergence-based perturbation invariance regularization of the predicted answer distribution to improve the robustness of the model against temporal content perturbation of videos. Our method is model-agnostic and can be easily compatible with various VideoQA backbones. Extensive experimental results and analyses on several public datasets show the advantage of our method over the state-of-the-art methods in terms of both accuracy and robustness.

关键词： video question answering cross-modality fusion contrastive learning cross-media reasoning

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Low thermal conductivity of dense(TiZrHfVNbTa)C_(x) high-entropy carbides by tailoring carbon stoichiometry

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Journal of Advanced Ceramics 2023年第1期12卷 49-58页

作者： Lei CHEN Wen ZHANG Wenyu LU Boxin WEI Sijia HUO Yujin WANG Yu ZHOU Institute for Advanced Ceramics School of Materials Science and EngineeringHarbin Institute of TechnologyHarbin 150001China Key Laboratory of Advanced Structural–Functional Integration Materials&Green Manufacturing Technology Harbin Institute of TechnologyHarbin 150001China School of Materials Science and Chemical Engineering Harbin University of Science and TechnologyHarbin 150001China

Transition metal carbides are promising candidates for thermal protection materials due to their high melting points and excellent mechanical ***,the relatively high thermal conductivity is still a major obstacle to its application in an ultra-high-temperature insulation *** this work,the low thermal conductivity of dense(TiZrHfVNbTa)Cx(x=0.6-1)high-entropy carbides has been realized by adjusting the carbon *** thermal conductivity gradually decreases from 10.6 W·m^(−1)·K^(−1) at room temperature to 6.4 W·m^(−1)·K^(−1) with carbon vacancies *** to enhanced scattering of phonons and electrons by the carbon vacancies,nearly full-dense(97.9%)(TiZrHfVNbTa)C_(0.6) possesses low thermal conductivity of 6.4 W·m^(−1)·K^(−1),thermal diffusivity of 2.3 mm^(2)·s^(−1),as well as electrical resistivity of 165.5μΩ·*** thermal conductivity of(TiZrHfVNbTa)C_(0.6) is lower than that of other quaternary and quinary high-entropy carbide ceramics,even if taking the difference of porosity into account in some cases,which is mainly attributed to compositional complexity and carbon *** provides a promising route to reduce the thermal conductivity of high-entropy carbides by increasing the number of metallic elements and carbon vacancies.

关键词： high-entropy carbides thermal conductivity compositional complexity carbon vacancies

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Efficient Semi-External SCC Computation (Extended Abstract) 40

Efficient Semi-External SCC Computation (Extended Abstract)

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40th IEEE International Conference on Data Engineering, ICDE 2024

作者： Wan, Xiaolong Wang, Hongzhi School of Computer Science and Technology Harbin Institute of Technology China

Computing strongly connected components (SCC) is a key operation for many applications on directed graphs. Specifically, a SCC of a directed graph G is one of its maximal subgraphs, in which any two nodes are reachabl... 详细信息

ISBN: (纸本)9798350317152

关键词： Directed graphs

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