8,236 results on '"Zhang Xiaohui"'
Search Results
2. Effects of Combined Addition of Modified Starch and Non-Muscle Protein on Gel Properties and Protein Conformation of Squid Surimi Products
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ZHANG Xiaohui, GUO Quanyou, ZHENG Yao, BAO Hairong, WEI Banghong, ZHUANG Xiaomei, YANG Xu
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squid surimi ,modified corn starch ,non-muscle proteins ,gel properties ,protein conformation ,Food processing and manufacture ,TP368-456 - Abstract
To improve the gel properties of squid surimi products, we optimized the addition of modified corn starch acetylated distarch phosphate (ADSP) and the non-muscle proteins egg white protein (EWP) and soy protein isolate (SPI), and we evaluated the effects of the addition of ADSP, EWP and SPI on the texture, intermolecular force, protein secondary structure and microstructure of squid surimi products. Furthermore, we explored the mechanism by which modified starch and non-muscle protein improve the gel quality of squid surimi products. The results showed that the gel properties of squid surimi products with 10% ADSP, 7% EWP and 6% SPI were the best. Compared with the control group, the addition of modified starch or non-muscle protein decrease the relative contents of random coil and α-helix in proteins, and increased the contents of β-sheet and β-turn. Their combined addition was beneficial for the retention of β-sheet and β-turn structures during the gelation process, and promoted the hydrophobic interaction between proteins, resulting in the formation of a denser gel network structure, which in turn improved the gel strength and water holding capacity of squid surimi products. Correlation analysis showed that the gel strength and water holding capacity, hydrophobic interaction, and relative contents of β-turn and immobilized water of squid surimi products were significantly positively correlated with each other (P < 0.01), and significantly negatively correlated with the contents of free water and random coil (P < 0.01). Therefore, the addition of 10% ADSP, 7% EWP and 6% SPI improved the gel quality of squid surimi products by affecting protein secondary structure and water distribution.
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- 2023
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3. Diagnostic value of magnetic resonance imaging for patients with periprosthetic joint infection: a systematic review
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Chang Shufen, Liu Jinmin, Zhang Xiaohui, and Geng Bin
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Magnetic resonance imaging ,Periprosthetic Joint infection ,Diagnosis ,Total joint arthroplasty ,Diseases of the musculoskeletal system ,RC925-935 - Abstract
Abstract Purpose The purpose of this study was to provide a critical systematic review of the role of magnetic resonance imaging (MRI) as a noninvasive method to assess periprosthetic joint infections (PJIs). Methods The electronic databases PubMed and EMBASE were searched, since their inception up to March 27, 2022. The included studies evaluated the reproducibility and accuracy of MRI features to diagnose PJIs. The article quality assessment was conducted by the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Results Among 1909 studies identified in the initial search, 8 studies were eligible for final systematic review. The included studies evaluated the reproducibility and accuracy of MRI features to diagnose PJIs. Seven of 8 studies showed good to excellent reliability, but only one article among them in which accuracy was evaluated had a low risk of bias. The intraclass correlation coefficient (ICC) and Cohen coefficient (κ) varied between 0.44 and 1.00. The accuracy varied between 63.9% and 94.4%. Potential MRI features, such as lamellated hyperintense synovitis, edema, fluid collection, or lymphadenopathy, might be valuable for diagnosing PJIs. Conclusion The quality of the evidence regarding the role of MRI for PJIs diagnosis was low. There is preliminary evidence that MRI has a noteworthy value of distinguishing suspected periprosthetic joint infection in patients with total knee arthroplasty or total hip arthroplasty, but the definition of specific MRI features related to PJIs diagnosis lacks consensus and standardization. Large-scale studies with robust quality were required to help make better clinical decisions in the future.
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- 2023
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4. A new record of Pittosporum brevicalyx (Oliv.) Gagnep. from Shaanxi Province, China
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TIAN Mo and ZHANG Xiaohui
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pittosporaceae ,pittosporum ,pittosporum brevicalyx (oliv.) gagnep. ,new record ,shaanxi province ,Biology (General) ,QH301-705.5 ,Botany ,QK1-989 - Abstract
Abstract [Objective] Investigating the distribution of the genus Pittosporum in the Bashan area of Shaanxi Province. [Methods and Results] Based on the investigation, collection, and study of Pittosporum sp. from Youhao village, Baihe County, new geographic distribution of Pittosporum brevicalyx (Oliv.) Gagnep. was discovered in Shaanxi Province. [Conclusion] Pittosporum sp. is mainly distributed in the subtropical areas of the south of the Qinling Mountains in China. This report expands the distribution of this species from northeast to the Daba Mountains of Shaanxi Province, which enriches the distribution records of plants in Qinling-Daba Mountains, as well as provides basis for the study of species diversity in the Daba Mountains.
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- 2024
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5. Effective application of multimodal discourse analysis in Russian translation
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Wu Yanan, Zhang Xiaohui, and Zhang Duo
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multimodal discourse ,visual grammar ,self-attention ,wait-k strategy ,multi30k training set ,97p10 ,Mathematics ,QA1-939 - Abstract
Based on ELAN multimodal discourse analysis software, this paper constructs a multimodal Russian translation model based on the machine translation model with visual grammar and multimodal discourse analysis as the theoretical basis. To address the issue of missing semantics caused by insufficient input information at the source of real-time translation, the model uses images as auxiliary modalities. The real-time Russian translation model is constructed using the wait-k strategy and the concept of multimodal self-attention. Experiments and analysis are carried out on the Multi30k training set, and the generalization ability and translation effect of the model are finally evaluated with the test set. The results show that by applying multimodal discourse analysis to Russian translation, the three translation evaluation indexes of BLEU, METEOR, and TER are improved by 1.3, 1.0, and 1.4 percentage points, respectively, and the phenomenon of phantom translation is effectively reduced.
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- 2024
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6. Modular design of smart home under the concept of whole-house customization integration
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Zhang Xiaohui
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kano model ,fuzzy qfd ,modular design ,smart home ,05b05 ,Mathematics ,QA1-939 - Abstract
Digital empowerment of home product design and manufacturing integration, to achieve the whole process of personalized customization of home products innovative design. Using big data for user analysis, we obtained functional demand data for smart home modules, and 28.5% of user demand is reflected in cell phone interconnection. Using the KANO model, user customization demands can be calculated to form basic and excitement type demand expectations represented by A and M. Then based on the fuzzy QFD method for demand raw data conversion, to get the initial weights and weighted weights of each demand item, taking A14 home space utilization efficiency as an example, the initial weights and weighted weights of A14 are 0.66 and 0.10, respectively, and the importance of demand sorted seventh. Combined with the specific application of modular design in smart homes, the modular design of smart homes is verified. Further adjustments should be made to enhance the innovation degree of smart homes.
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- 2024
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7. An Innovative Model of Higher Mathematics Curriculum Education Incorporating Artificial Intelligence Technology
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Zhang Xiaohui
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artificial intelligence technology ,subject knowledge mapping ,ant colony optimization algorithm ,learning path ,higher mathematics course ,00a35 ,Mathematics ,QA1-939 - Abstract
This paper first proposes the direction of constructing a higher mathematics teaching mode supported by intelligent technology and then models the learner portrait of the learning outcome data according to the subject knowledge graph. An improved ant colony optimization algorithm is used to search for the optimal learning path, which is then combined with an improved convolutional neural network to generate a personalized learning path. The Trans R method is used to quantify the relationship between learners and learning resources and a semi-supervised learning conditional random field method based on K-NN is proposed to label learning resources and generate learning accurate evaluation for smart teaching. The smart teaching model of advanced mathematics courses is applied and analyzed in terms of students’ advanced mathematics pre and post-test scores, students’ satisfaction, teachers’ teaching methods and teaching resources in four directions. The analysis obtained that the posttest scores of the learners in the experimental group were 75.631, and the posttest scores of the learners in the control group were 66.314, with a difference of 9.317. The significance level of the variance chi-square test was 0.000
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- 2024
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8. Efficient excitation of nuclear isomer 152mEu using a bremsstrahlung radiation source generated by laser plasma
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LUO Kaijun, FAN Wenru, YUAN Yun, QI Wei, ZHANG Jingli, ZHANG Xiaohui, DENG Zhigang, and LUO Wen
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isomer 152meu ,bremsstrahlung source ,laser plasma ,(γ, n) reaction ,peak excitation efficiency ,Nuclear engineering. Atomic power ,TK9001-9401 - Abstract
BackgroundNuclear isomers are crucial in cosmic element synthesis and have potential applications in controlling nuclear energy release. Specifically, Europium (Eu) is significant in fundamental studies. For instance, 152Eu is used as a reference source for radioactive experiments, and its isomeric state 152m1Eu has a probability of 73% to produce cosmological p-nuclei 152Gd with β- decay. Therefore, 152m1Eu is a crucial nuclide in the nuclearsynthesis of p-nuclei 152Gd.PurposeThis study aims to realize the efficient excitation of 152m1Eu with a bremsstrahlung source generated by laser plasma.MethodsFirstly, the laser-plasma bremsstrahlung source was utilized to achieve the efficient excitation of 152m1Eu (45.6 keV, T1/2=9.31 h) in the experiment with yields of 8×104 particles/shot by this isotope. Then, numerical simulations of the yield of 152m1, m2Eu were performed using the Geant4-GENBOD program to get generation time, and peak excitation efficiency evolution with electron temperature.ResultsThe results demonstrate that when the electron temperature reaches 15 MeV, the yield of 152m1, m2Eu approaches saturation. When the incident electron charge is 17.6 nC, the yield of 152m1Eu is approximately 8×106 particles/shot, and that of 152m2Eu is approximately 2×105 particles/shot. The generation time of 152m1, m2Eu in the target is approximately 32 ps. When the electron temperature reaches 15 MeV, the peak excitation efficiency of 152m1Eu is expected to be ~1017 particles/s, and that of 152m2Eu is expected to be ~1016 particles/s.ConclusionsThe ultrashort ultrahigh intensity laser technology can significantly enhance the excitation efficiency of isotopes of the same nucleus, and this will provide an important research avenue for the study of cosmic element synthesis and nuclear energy release control applications.
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- 2024
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9. Surgical interventions for symptomatic knee osteoarthritis: a network meta-analysis of randomized control trials
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Geng Bin, Liu Jinmin, Tian Cong, Tang Yuchen, Zhang Xiaohui, and Xia Yayi
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Total knee arthroplasty ,Unicompartmental knee arthroplasty ,High tibial osteotomy ,Bicompartmental knee arthroplasty ,Bi-unicompartmental knee arthroplasty ,Knee joint distraction ,Diseases of the musculoskeletal system ,RC925-935 - Abstract
Abstract Background Multiple surgical interventions exist for the treatment of symptomatic knee osteoarthritis, but the surgeon and patient may often have difficulty deciding which interventions are the best option. Methods We conducted a systematic review to identify randomized clinical trials (RCTs) that compared complications, revisions, reoperations, and functional outcomes among TKA (total knee arthroplasty), UKA (unicompartmental knee arthroplasty), HTO (high tibial osteotomy), BCA (bicompartmental knee arthroplasty), BIU (bi-unicompartmental knee arthroplasty), and KJD (knee joint distraction). The PubMed, Embase, and Cochrane databases were reviewed for all studies comparing two or more surgical interventions. Direct-comparison meta-analysis and network meta-analysis (NMA) were performed to combine direct and indirect evidence. The risk of bias was assessed using the revised Cochrane risk of bias tool for RCTs. Results This NMA and systematic review included 21 studies (17 RCTs), with a total of 1749 patients. The overall risk-of-bias assessment of the RCTs revealed that 7 studies had low risk, 5 had some concerns, and 9 had high risk. SUCRA (the surface under the cumulative ranking curve) rankings revealed that KJD had the greatest risk of appearing postoperative complications, revisions, and reoperations, and UKA or TKA had the lowest risk. The majority of comparisons among various treatments showed no difference for functional outcomes. Conclusion Each surgical intervention is noninferior to other treatments in functional outcomes, but UKA and TKA are better options to treat OA according to SUCRA rankings by comparing complications, revisions, and reoperations. KJD is an imperfect option for treating OA. Other treatments should be carefully considered for each patient in accordance with their actual conditions. However, this conclusion is limited by the selection of reviewed publications and individual variation of surgical indications for patients. Trial registration This study was registered with Research Registry (reviewregistry1395).
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- 2023
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10. Multimedia sensor image detection based on constrained underdetermined equation
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Xu Peng, Zhang Xiaohui, and Soltan Mohamed Abdeldayem
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under determined equation ,multi-media ,sensors ,image detection ,war page test ,03c05 ,Mathematics ,QA1-939 - Abstract
In order to study the image detection of multimedia sensor based on constrained under determined equation, this paper proposes the improvement of image sensor quality detection method based on image recognition algorithm. Firstly, the principle and steps of the under determined method are explained, and the complexity of the algorithm is analyzed. The image sensor is the most important part of the mobile camera, which determines the performance of the mobile camera, and its assembly quality largely determines the quality of the whole mobile camera. The case studied in this paper is model h mobile phone camera, and the first pass rate of good products is only 80%. In order to meet the 95% pass rate of good products required by customers, it is necessary to comprehensively improve the processes that have a great impact on product quality, so as to improve the first pass rate of products, achieve quality objectives and reduce manufacturing failure costs. In order to find out the threshold value of the height information measured by the improved method, to determine whether the product is good, and to find out the process that has a great impact on the surface flatness of the image sensor, the product measurement experiment is specially set. The improved war page test method was used to measure the products of each experimental group. Among them, No. 22, No. 39 and No. 40 products are poor due to changes in physical properties in subsequent production, and cannot flow to the next process for production. Therefore, the data of No. 22, No. 39 and No. 40 are missing in the test data. A total of 133 groups of experimental data were obtained in this experimental test. The results showed that the standard deviations of group 1, group 2, group 3 and group 4 were 0.172, 0.125 and 0.304 respectively. That is, after the same product is treated by false hardening, heating hardening and base installation processes, the false hardening and heating hardening processes have relatively little impact on the surface flatness of the image sensor. After the base opening and installation process, the surface flatness of the image sensor begins to change. The standard deviations of the measurement results of group 1 and groups 4, 5, 6 and 7 were 0.304, 0.381, 0.391 and 0.514 respectively. That is, after the base installation, calibration, bonding, soldering and testing of the product, the surface flatness of the image sensor and the initial surface flatness have changed greatly. Therefore, production technicians can focus on the process that starts to change, that is, the base installation process. The improved method has the advantages of automatic operation, low error, low error rate and so on.
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- 2023
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11. TanshinoneⅡA protects acute lung injury in septic mice by regulating neutrophil extracellular traps
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ZHANG Xiaohui, CHEN Congmin, DING Xinyun, DONG Xupeng, and MA Yuqing
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sepsis ,acute lung injury ,tanshinoneⅱa ,neutrophils extracellular traps ,pi3k/akt ,Medicine (General) ,R5-920 - Abstract
Objective To observe the effect of tanshinoneⅡA (TanⅡA) on acute lung injury (ALI) in septic mice, and to explore its effect on neutrophil extracellular traps (NETs) and its possible mechanism. Methods A mouse model of sepsis was established by intraperitoneal injection of lipopolysaccharide (LPS) at a dose of 10 mg/kg. Thirty male C57BL/6 mice aged 6~8 weeks were randomly divided into 5 groups (n=6): Normal group (Nor group), LPS group, LPS+TanⅡA group (30 mg/kg TanⅡA was injected intraperitoneally 30 min before LPS injection), LPS+LY294002 group (pre-injection of 30 mg/kg LY294002), and LPS+DMSO group (pre-injection of the same amount of DMSO). At 12 h after modeling, the lung tissues were collected, lung coefficients were calculated, and pathological changes of lung tissue were observed with HE staining. ELISA was used to detect the levels of inflammatory factors IL-1β and IL-10 and NETs markers MPO-DNA complex and citrolinated histone H3 (Cit H3) in lung tissue. Western blotting was applied to detect the phosphorylation of the PI3K/AKT signaling pathway. Results Compared with the Nor group, the LPS group had an increased lung coefficient, significantly damaged lung tissue, increased levels of IL-1β (P < 0.05) and decreased level of IL-10 (P < 0.05), and elevated MPO-DNA complex and Cit H3 levels (P < 0.05) as well as the levels of p-PI3K and p-AKT (P < 0.05). While, the above conditions were much better in the LPS+TanⅡA group and the LPS+LY294002 group than the LPS group, with decreased lung coefficient, alleviated lung injury by HE staining and Smith scores, increased level of IL-1β and decreased IL-10 level in the lung tissue (P < 0.05), reduced levels of MPO-DNA complex and Cit H3 (P < 0.05) and p-PI3K and p-AKT (P < 0.05). Conclusion TanⅡA can alleviate sepsis-induced ALI, and its mechanism may be through inhibiting PI3K/AKT signaling pathway, regulating the level of NETs, and thus reducing the inflammatory response.
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- 2023
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12. Characterization of Yellow-Green Hetian Jade in Qiemo—Ruoqiang, Xinjiang
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ZHANG Xiaohui, FENG Yuhuan, ZHANG Yong, and MAITUOHUTI Abuduwayiti
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hetian jade ,zircon u-pb dating ,electron probe microanalysis ,x-ray fluorescence spectrometry ,high resolution inductively coupled plasma-mass spectrometry ,qiemo—ruoqiang area ,Geology ,QE1-996.5 ,Ecology ,QH540-549.5 - Abstract
BACKGROUND The Hetian nephrite belt in Xinjiang is the largest nephrite ore belt in the world, with a length of about 1300km. In addition to white, gray, black and brown nephrite, the Qiemo—Ruoqiang zone, Xinjiang also produces a yellow-green nephrite. There are few studies on the color origin and characterization of this kind of Hetian nephrite, which affects the understanding of the color and genesis of this kind of Hetian nephrite. OBJECTIVES To understand the color genesis, genetic types and formation age of the yellow-green nephrite in Qiemo—Ruoqiang deposit. METHODS Electron probe microanalysis (EPMA), backscattered electron (BSE) image, X-ray fluorescencespectrometry (XRF), and high resolution inductively coupled plasma-mass spectrometry (HR-ICP-MS) were used to investigate mineral and chemical composition. The FeO content was determined by titration method to explore its color origin and genetic type, and the zircon U-Pb isotope dating by sensitive high-resolution ion microprobe (SHRIMP) was used to constrain its mineralization age. RESULTS Yellow-green nephrite in Qiemo—Ruoqiang was predominately composed of apatite, calcite, dolomite, diopside, epidote, sphene and zircon. The yellow-green nephrite whole rock had low total REE (∑REE=2.61-19.1μg/g) with obvious Eu negative anomaly (δEu < 0.05), LREE right dipping, and HREE flat pattern. According to the distribution pattern of rare earth and the content of Cr and Ni, it was inferred that it was a magnesia skarn type Hetian nephrite. Compared with other nephrite in the world, the average value of Fe3+/Fe2+ of the yellow-green nephrite in Qiemo—Ruoqiang (average=0.16) overlapped with nephrite in other regions. The ratio is slightly higher (0.07-0.26), while the content of Fe3+ and Fe2+ was not significantly different between the yellow-green nephrite and other color nephrite. The SHRIMP U-Pb dating of zircon in the yellow-green nephrite yielded ages of 461.7±6.1Ma (MSWD=1.6) and 498.1±4.6Ma (MSWD=1.16). CONCLUSIONS The color genesis of the yellow-green nephrite in Qiemo is probably related to the ratio of Fe3+/Fe2+, but not to the content of Fe3+ and Fe2+. The SHRIMP U-Pb dating results of zircon in yellow-green nephrite represent the formation age of the yellow-green nephrite. These new data provide geochronological constraints for the magmatism of Hetian nephrite belt and the tectonic evolution of the West Kunlun orogenic belt.
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- 2022
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13. Investigation of different nanoparticles properties on the thermal conductivity and viscosity of nanofluids by molecular dynamics simulation
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Zhang Ruihao, Qing Shan, Zhang Xiaohui, Luo Zhumei, and Liu Yiqing
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molecular dynamics simulation ,different nanoparticles ,interfacial nanolayer ,Technology ,Chemical technology ,TP1-1185 ,Physical and theoretical chemistry ,QD450-801 - Abstract
The mechanisms of thermal conductivity enhancement and the factors influencing viscosity are of great interest in the study of nanofluids, while molecular dynamics (MD) simulations considering nanofluids provide more accurate predictions of microscopic properties than conventional experimental studies. MD simulations of non-equilibrium molecular dynamics and reversing perturbation non-equilibrium molecular dynamics methods were used to study thermal conductivity and viscosity, taking into account a variety of influencing factors, as well as nanoparticle material and volume fraction. Through the analysis of the number density distribution, radial distribution function (RDF), and mean square displacement (MSD), the influences of different nanoparticles (Ag, Cu, Au, and Fe) were described and investigated: Ag particles contribute to 47.0% increase in thermal conductivity of 2.5 vol% nanofluids; Au particles improved the viscosity of 2.5 vol% nanofluids by 20.2%; the number density distribution showed positive linear relationship with the atomic mass; the results of MSD and RDF (mean square displacement and radial distribution function) in combination indicated a positive effect of interfacial nanolayer. The results of this research provide important perspectives for comprehending the impacts of multiple nanoparticles on the micro-thermal properties of nanofluids and also highlight the simulation potential of Au–Ar nanofluids.
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- 2023
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14. Data processing error accumulation of accelerator alignment control network
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WANG Xiaolong, KANG Ling, DONG Lan, LI Bo, MEN Lingling, LUO Tao, WANG Tong, LIANG Jing, HE Zhenqiang, KE Zhiyong, MA Na, LU Shang, HAN Yuanying, YAN Luping, ZHANG Luyan, LIU Xiaoyang, YAN Haoyue, LI Chunhua, WU Lei, SHEN Jianxin, and ZHANG Xiaohui
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three dimensional adjustment ,accelerator alignment control network ,laser tracker ,error accumulation ,move station measurement ,Nuclear engineering. Atomic power ,TK9001-9401 - Abstract
BackgroundCompared with 2D+1D adjustment, three dimensional adjustment has a more rigorous theoretical basis. However, when the unconstrained three dimensional adjustment is applied to the observation values processing of the accelerator alignment control network, serious error accumulation will occur and resulting in obvious distortion of the results.PurposeThis study aims to expound the ways and characteristics of three dimensional adjustment error accumulation for accelerator alignment control network.MethodsFirstly, based on the layout of accelerator alignment control network and the moving station measurement method of laser tracker, the three dimensional adjustment mathematical model was analyzed, and the least-squares collocation theory was used to clearly explain the error propagation. Secondly, the characters of laser tracker measurement accuracy, station positioning and orientation accuracy and single station measurement error propagation were studied by analyzing the laser tracker 3D coordinate measurement model, measurement point error model and simulation measurement experiments. Finally, adjustment calculation of the linac control network was verified by simulation measurement, and two error accumulation suppression methods were tested.ResultsThe source and propagation mode of error accumulation are explained theoretically, and verified by simulation calculation, so are the serious error accumulation of elevation and lateral errors in three dimensional adjustment of control network in accelerator.ConclusionsProviding high-precision point coordinate constraint for three dimensional adjustment can effectively suppress error accumulation, and providing high-precision orientation constraint for station coordinate system can also achieve the effect of suppressing error accumulation.
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- 2021
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15. An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio
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Zeng, Siding, Yi, Jiangyan, Tao, Jianhua, Chen, Yujie, Liang, Shan, Ren, Yong, and Zhang, Xiaohui
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Computer Science - Sound ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
When the task of locating manipulation regions in partially-fake audio (PFA) involves cross-domain datasets, the performance of deep learning models drops significantly due to the shift between the source and target domains. To address this issue, existing approaches often employ data augmentation before training. However, they overlook the characteristics in target domain that are absent in source domain. Inspired by the mixture-of-experts model, we propose an unsupervised method named Samples mining with Diversity and Entropy (SDE). Our method first learns from a collection of diverse experts that achieve great performance from different perspectives in the source domain, but with ambiguity on target samples. We leverage these diverse experts to select the most informative samples by calculating their entropy. Furthermore, we introduced a label generation method tailored for these selected samples that are incorporated in the training process in source domain integrating the target domain information. We applied our method to a cross-domain partially fake audio detection dataset, ADD2023Track2. By introducing 10% of unknown samples from the target domain, we achieved an F1 score of 43.84%, which represents a relative increase of 77.2% compared to the second-best method.
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- 2024
16. Efficient Neural Common Neighbor for Temporal Graph Link Prediction
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Zhang, Xiaohui, Wang, Yanbo, Wang, Xiyuan, and Zhang, Muhan
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Social and Information Networks - Abstract
Temporal graphs are ubiquitous in real-world scenarios, such as social network, trade and transportation. Predicting dynamic links between nodes in a temporal graph is of vital importance. Traditional methods usually leverage the temporal neighborhood of interaction history to generate node embeddings first and then aggregate the source and target node embeddings to predict the link. However, such methods focus on learning individual node representations, but overlook the pairwise representation learning nature of link prediction and fail to capture the important pairwise features of links such as common neighbors (CN). Motivated by the success of Neural Common Neighbor (NCN) for static graph link prediction, we propose TNCN, a temporal version of NCN for link prediction in temporal graphs. TNCN dynamically updates a temporal neighbor dictionary for each node, and utilizes multi-hop common neighbors between the source and target node to learn a more effective pairwise representation. We validate our model on five large-scale real-world datasets from the Temporal Graph Benchmark (TGB), and find that it achieves new state-of-the-art performance on three of them. Additionally, TNCN demonstrates excellent scalability on large datasets, outperforming popular GNN baselines by up to 6.4 times in speed. Our code is available at https: //github.com/GraphPKU/TNCN.
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- 2024
17. RawBMamba: End-to-End Bidirectional State Space Model for Audio Deepfake Detection
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Chen, Yujie, Yi, Jiangyan, Xue, Jun, Wang, Chenglong, Zhang, Xiaohui, Dong, Shunbo, Zeng, Siding, Tao, Jianhua, Zhao, Lv, and Fan, Cunhang
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Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Fake artefacts for discriminating between bonafide and fake audio can exist in both short- and long-range segments. Therefore, combining local and global feature information can effectively discriminate between bonafide and fake audio. This paper proposes an end-to-end bidirectional state space model, named RawBMamba, to capture both short- and long-range discriminative information for audio deepfake detection. Specifically, we use sinc Layer and multiple convolutional layers to capture short-range features, and then design a bidirectional Mamba to address Mamba's unidirectional modelling problem and further capture long-range feature information. Moreover, we develop a bidirectional fusion module to integrate embeddings, enhancing audio context representation and combining short- and long-range information. The results show that our proposed RawBMamba achieves a 34.1\% improvement over Rawformer on ASVspoof2021 LA dataset, and demonstrates competitive performance on other datasets., Comment: Accepted by Interspeech 2024
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- 2024
18. Identifying Functional Brain Networks of Spatiotemporal Wide-Field Calcium Imaging Data via a Long Short-Term Memory Autoencoder
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Zhang, Xiaohui, Landsness, Eric C, Brier, Lindsey M, Chen, Wei, Tang, Michelle J., Miao, Hanyang, Lee, Jin-Moo, Anastasio, Mark A., and Culver, Joseph P.
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Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Wide-field calcium imaging (WFCI) that records neural calcium dynamics allows for identification of functional brain networks (FBNs) in mice that express genetically encoded calcium indicators. Estimating FBNs from WFCI data is commonly achieved by use of seed-based correlation (SBC) analysis and independent component analysis (ICA). These two methods are conceptually distinct and each possesses limitations. Recent success of unsupervised representation learning in neuroimage analysis motivates the investigation of such methods to identify FBNs. In this work, a novel approach referred as LSTM-AER, is proposed in which a long short-term memory (LSTM) autoencoder (AE) is employed to learn spatial-temporal latent embeddings from WFCI data, followed by an ordinary least square regression (R) to estimate FBNs. The goal of this study is to elucidate and illustrate, qualitatively and quantitatively, the FBNs identified by use of the LSTM-AER method and compare them to those from traditional SBC and ICA. It was observed that spatial FBN maps produced from LSTM-AER resembled those derived by SBC and ICA while better accounting for intra-subject variation, data from a single hemisphere, shorter epoch lengths and tunable number of latent components. The results demonstrate the potential of unsupervised deep learning-based approaches to identifying and mapping FBNs.
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- 2024
19. Dynamical behavior and optimal control of a stochastic SAIRS epidemic model with two saturated incidences
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Zhang, Xiaohui, Li, Zhiming, Chen, Shenglong, and Yang, Jikai
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Mathematics - Probability ,Mathematics - Optimization and Control ,Physics - Physics and Society - Abstract
Stochastic models are widely used to investigate the spread of epidemics in a complex environment. This paper extends a deterministic SAIRS epidemic model to a stochastic case with limited patient capacity and exposure. We first study the dynamical properties of the model under certain conditions, including persistence, extinction, and ergodic. Then, we introduce vaccination and isolation into the model as control variables. The optimal control strategies are obtained based on the Pontryagin minimum principle. Finally, numerical simulations are given to illustrate our theoretical results., Comment: 18 pages, 5 figures
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- 2024
20. EVDA: Evolving Deepfake Audio Detection Continual Learning Benchmark
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Zhang, Xiaohui, Yi, Jiangyan, and Tao, Jianhua
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Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
The rise of advanced large language models such as GPT-4, GPT-4o, and the Claude family has made fake audio detection increasingly challenging. Traditional fine-tuning methods struggle to keep pace with the evolving landscape of synthetic speech, necessitating continual learning approaches that can adapt to new audio while retaining the ability to detect older types. Continual learning, which acts as an effective tool for detecting newly emerged deepfake audio while maintaining performance on older types, lacks a well-constructed and user-friendly evaluation framework. To address this gap, we introduce EVDA, a benchmark for evaluating continual learning methods in deepfake audio detection. EVDA includes classic datasets from the Anti-Spoofing Voice series, Chinese fake audio detection series, and newly generated deepfake audio from models like GPT-4 and GPT-4o. It supports various continual learning techniques, such as Elastic Weight Consolidation (EWC), Learning without Forgetting (LwF), and recent methods like Regularized Adaptive Weight Modification (RAWM) and Radian Weight Modification (RWM). Additionally, EVDA facilitates the development of robust algorithms by providing an open interface for integrating new continual learning methods, Comment: This paper need more modification
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- 2024
21. Decentralized Economic Dispatching of Multi-Micro Grid Considering Wind Power and Photovoltaic Output Uncertainty
- Author
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Zhang Xiaohui, Gao Wenbo, and Zhong Jiaqing
- Subjects
Alternating direction method of multipliers (ADMM) ,decentralized economic scheduling ,multi-micro grid ,wind power generation ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
In this paper, the decentralized economic scheduling problem of multi-micro grid is studied on the basis of considering the uncertainty of wind power and photovoltaic output. Firstly, in order to meet the independent and autonomous requirements of decentralized scheduling, the decoupling method of public connection points, which is more suitable for the multi-micro grid structure, is adopted to partition the multi-micro grid regions. Then, considering the uncertainty of wind-wind output, a decentralized economic dispatching model of multi-micro grid with robust optimization participation is proposed to minimize the economic cost. Finally, the improved Alternating direction method of multipliers is used to solve the decentralized economic scheduling problem of multi-micro grid. The feasibility and superiority of the improved algorithm are verified by simulation test and comparative analysis. The decentralized autonomy of multi-micro grid scheduling can be realized, and the random uncertainty of landscape can be effectively dealt with.
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- 2021
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22. Less Peaky and More Accurate CTC Forced Alignment by Label Priors
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Huang, Ruizhe, Zhang, Xiaohui, Ni, Zhaoheng, Sun, Li, Hira, Moto, Hwang, Jeff, Manohar, Vimal, Pratap, Vineel, Wiesner, Matthew, Watanabe, Shinji, Povey, Daniel, and Khudanpur, Sanjeev
- Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Machine Learning - Abstract
Connectionist temporal classification (CTC) models are known to have peaky output distributions. Such behavior is not a problem for automatic speech recognition (ASR), but it can cause inaccurate forced alignments (FA), especially at finer granularity, e.g., phoneme level. This paper aims at alleviating the peaky behavior for CTC and improve its suitability for forced alignment generation, by leveraging label priors, so that the scores of alignment paths containing fewer blanks are boosted and maximized during training. As a result, our CTC model produces less peaky posteriors and is able to more accurately predict the offset of the tokens besides their onset. It outperforms the standard CTC model and a heuristics-based approach for obtaining CTC's token offset timestamps by 12-40% in phoneme and word boundary errors (PBE and WBE) measured on the Buckeye and TIMIT data. Compared with the most widely used FA toolkit Montreal Forced Aligner (MFA), our method performs similarly on PBE/WBE on Buckeye, yet falls behind MFA on TIMIT. Nevertheless, our method has a much simpler training pipeline and better runtime efficiency. Our training recipe and pretrained model are released in TorchAudio., Comment: Accepted by ICASSP 2024. Github repo: https://github.com/huangruizhe/audio/tree/aligner_label_priors
- Published
- 2024
23. Soft-Weighted CrossEntropy Loss for Continous Alzheimer's Disease Detection
- Author
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Zhang, Xiaohui, Fu, Wenjie, and Liang, Mangui
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing ,Quantitative Biology - Neurons and Cognition - Abstract
Alzheimer's disease is a common cognitive disorder in the elderly. Early and accurate diagnosis of Alzheimer's disease (AD) has a major impact on the progress of research on dementia. At present, researchers have used machine learning methods to detect Alzheimer's disease from the speech of participants. However, the recognition accuracy of current methods is unsatisfactory, and most of them focus on using low-dimensional handcrafted features to extract relevant information from audios. This paper proposes an Alzheimer's disease detection system based on the pre-trained framework Wav2vec 2.0 (Wav2vec2). In addition, by replacing the loss function with the Soft-Weighted CrossEntropy loss function, we achieved 85.45\% recognition accuracy on the same test dataset.
- Published
- 2024
24. Multimodal Emotion Recognition from Raw Audio with Sinc-convolution
- Author
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Zhang, Xiaohui, Fu, Wenjie, and Liang, Mangui
- Subjects
Computer Science - Sound ,Computer Science - Multimedia ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Speech Emotion Recognition (SER) is still a complex task for computers with average recall rates usually about 70% on the most realistic datasets. Most SER systems use hand-crafted features extracted from audio signal such as energy, zero crossing rate, spectral information, prosodic, mel frequency cepstral coefficient (MFCC), and so on. More recently, using raw waveform for training neural network is becoming an emerging trend. This approach is advantageous as it eliminates the feature extraction pipeline. Learning from time-domain signal has shown good results for tasks such as speech recognition, speaker verification etc. In this paper, we utilize Sinc-convolution layer, which is an efficient architecture for preprocessing raw speech waveform for emotion recognition, to extract acoustic features from raw audio signals followed by a long short-term memory (LSTM). We also incorporate linguistic features and append a dialogical emotion decoding (DED) strategy. Our approach achieves a weighted accuracy of 85.1\% in four class emotion on the Interactive Emotional Dyadic Motion Capture (IEMOCAP) dataset.
- Published
- 2024
25. A Bionic Data-driven Approach for Long-distance Underwater Navigation with Anomaly Resistance
- Author
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Yang, Songnan, Zhang, Xiaohui, Zhang, Shiliang, Ma, Xuehui, Bai, Wenqi, Li, Yushuai, and Huang, Tingwen
- Subjects
Computer Science - Robotics ,Computer Science - Artificial Intelligence - Abstract
Various animals exhibit accurate navigation using environment cues. The Earth's magnetic field has been proved a reliable information source in long-distance fauna migration. Inspired by animal navigation, this work proposes a bionic and data-driven approach for long-distance underwater navigation. The proposed approach uses measured geomagnetic data for the navigation, and requires no GPS systems or geographical maps. Particularly, we construct and train a Temporal Attention-based Long Short-Term Memory (TA-LSTM) network to predict the heading angle during the navigation. To mitigate the impact of geomagnetic anomalies, we develop the mechanism to detect and quantify the anomalies based on Maximum Likelihood Estimation. We integrate the developed mechanism with the TA-LSTM, and calibrate the predicted heading angles to gain resistance against geomagnetic anomalies. Using the retrieved data from the WMM model, we conduct numerical simulations with diversified navigation conditions to test our approach. The simulation results demonstrate a resilience navigation against geomagnetic anomalies by our approach, along with precision and stability of the underwater navigation in single and multiple destination missions.
- Published
- 2024
26. Dysbiosis characteristics of gut microbiota in cerebral infarction patients
- Author
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Li Hao, Zhang Xiaohui, Pan Dengdeng, Liu Yongqiang, Yan Xuebing, Tang Yihan, Tao Mingyang, Gong Li, Zhang Ting, Woods Christian Rutan, Du Yong, Gao Renyuan, and Qin Huanlong
- Subjects
cerebral infarction ,gut microbiota ,dysbiosis ,nihss ,diagnosis ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
The aim of this study is to investigate the dysbiosis characteristics of gut microbiota in patients with cerebral infarction (CI) and its clinical implications.
- Published
- 2020
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- View/download PDF
27. On split involutive regular BiHom-Lie superalgebras
- Author
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Guo Shuangjian, Zhang Xiaohui, and Wang Shengxiang
- Subjects
involutive ,bihom-lie superalgebra ,root space ,structure theory ,17b05 ,17b20 ,17b65 ,Mathematics ,QA1-939 - Abstract
The goal of this paper is to examine the structure of split involutive regular BiHom-Lie superalgebras, which can be viewed as the natural generalization of split involutive regular Hom-Lie algebras and split regular BiHom-Lie superalgebras. By developing techniques of connections of roots for this kind of algebras, we show that such a split involutive regular BiHom-Lie superalgebra L{\mathfrak{L}} is of the form L=U+∑αIα{\mathfrak{L}}=U+{\sum }_{\alpha }{I}_{\alpha } with U a subspace of a maximal abelian subalgebra H and any I α, a well-described ideal of L{\mathfrak{L}}, satisfying [I α, I β] = 0 if [α] ≠ [β]. In the case of L{\mathfrak{L}} being of maximal length, the simplicity of L{\mathfrak{L}} is also characterized in terms of connections of roots.
- Published
- 2020
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28. Review of nano-phase effects in high strength and conductivity copper alloys
- Author
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Zhang Xiaohui, Zhang Yi, Tian Baohong, Song Kexing, Liu Ping, Jia Yanlin, Chen Xiaohong, An Junchao, Zhao Zhuan, Liu Yong, Volinsky Alex A., Li Xu, and Yin Ting
- Subjects
Technology ,Chemical technology ,TP1-1185 ,Physical and theoretical chemistry ,QD450-801 - Abstract
Copper alloys and copper matrix composites have been attracting a lot of attention lately. Their composition design, preparation, and processing directly affect the final performance. In this review, several typical copper alloys, such as Cu-Fe-P, Cu-Ni-Si, and Cu-Cr-Zr are analyzed. The deformation mechanisms, microstructure evolution, and dynamic recrystallization behavior are summarized. In addition, dispersion strengthened copper matrix composites and graphene reinforced copper matrix composites are reviewed.
- Published
- 2019
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- View/download PDF
29. Cr effects on the electrical contact properties of the Al2O3-Cu/15W composites
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Zhang Xiaohui, Zhang Yi, Tian Baohong, Jia Yanlin, Liu Yong, Song Kexing, Volinsky Alex. A., and Xue Huihui
- Subjects
electrical contact ,al2o3 nanoparticles ,orientation relationship ,mass transfer mechanism ,Technology ,Chemical technology ,TP1-1185 ,Physical and theoretical chemistry ,QD450-801 - Abstract
In order to investigate the effects of chromium on the electrical contact properties of the Al2O3-Cu/15W composites, vacuum hot-pressing sintering and internal oxidation methods were employed to fabricate the Al2O3-Cu/15W and Al2O3-Cu/15W5Cr composites. The microstructure was analyzed by scanning and transmission electron microscopy. The electrical contacts testing was performed using the JF04C testing machine at 30 V DC with 10-30 A current. The effects of Cr on the comprehensive properties, arc erosion morphology and welding force of the electrical contacts were investigated. The mass transfer mechanism was discussed. It was demonstrated that the Al2O3 nanoparticles pinned dislocations. The diffraction spots of the Cu matrix and the γ-Al2O3 disclose an orientation relationship of Cu//γ−Al2O3,{020}Cu//{040}γ−Al2O3. A typical arc erosion morphology, such as needle-like and coral structures was formed, which provides significantly enhanced arc erosion resistance of the contact material. Compared with the Al2O3-Cu/15W composite, the Al2O3-Cu/15W5Cr composite has a lower welding force. The two composites present two distinct mass transfer trends before and after 25 A. The final mass transfer direction of the composites is from the cathode to the anode. The Al2O3-Cu/15W5Cr contacts have less mass change under all testing conditions.
- Published
- 2019
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30. What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection
- Author
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Zhang, Xiaohui, Yi, Jiangyan, Wang, Chenglong, Zhang, Chuyuan, Zeng, Siding, and Tao, Jianhua
- Subjects
Computer Science - Sound ,Computer Science - Cryptography and Security ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
The rapid evolution of speech synthesis and voice conversion has raised substantial concerns due to the potential misuse of such technology, prompting a pressing need for effective audio deepfake detection mechanisms. Existing detection models have shown remarkable success in discriminating known deepfake audio, but struggle when encountering new attack types. To address this challenge, one of the emergent effective approaches is continual learning. In this paper, we propose a continual learning approach called Radian Weight Modification (RWM) for audio deepfake detection. The fundamental concept underlying RWM involves categorizing all classes into two groups: those with compact feature distributions across tasks, such as genuine audio, and those with more spread-out distributions, like various types of fake audio. These distinctions are quantified by means of the in-class cosine distance, which subsequently serves as the basis for RWM to introduce a trainable gradient modification direction for distinct data types. Experimental evaluations against mainstream continual learning methods reveal the superiority of RWM in terms of knowledge acquisition and mitigating forgetting in audio deepfake detection. Furthermore, RWM's applicability extends beyond audio deepfake detection, demonstrating its potential significance in diverse machine learning domains such as image recognition., Comment: Accepted by the main track The 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)
- Published
- 2023
31. Multimodal Representation Learning by Alternating Unimodal Adaptation
- Author
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Zhang, Xiaohui, Yoon, Jaehong, Bansal, Mohit, and Yao, Huaxiu
- Subjects
Computer Science - Machine Learning ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Multimodal learning, which integrates data from diverse sensory modes, plays a pivotal role in artificial intelligence. However, existing multimodal learning methods often struggle with challenges where some modalities appear more dominant than others during multimodal learning, resulting in suboptimal performance. To address this challenge, we propose MLA (Multimodal Learning with Alternating Unimodal Adaptation). MLA reframes the conventional joint multimodal learning process by transforming it into an alternating unimodal learning process, thereby minimizing interference between modalities. Simultaneously, it captures cross-modal interactions through a shared head, which undergoes continuous optimization across different modalities. This optimization process is controlled by a gradient modification mechanism to prevent the shared head from losing previously acquired information. During the inference phase, MLA utilizes a test-time uncertainty-based model fusion mechanism to integrate multimodal information. Extensive experiments are conducted on five diverse datasets, encompassing scenarios with complete modalities and scenarios with missing modalities. These experiments demonstrate the superiority of MLA over competing prior approaches. Our code is available at https://github.com/Cecile-hi/Multimodal-Learning-with-Alternating-Unimodal-Adaptation., Comment: Accepted by CVPR 2024
- Published
- 2023
32. Single-cell immune landscape of measurable residual disease in acute myeloid leukemia
- Author
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Mo, Xiaodong, Zhang, Weilong, Fu, Guomei, Chang, Yingjun, Zhang, Xiaohui, Xu, Lanping, Wang, Yu, Yan, Chenhua, Shen, Mengzhu, Wei, Qiuxia, Yan, Changjian, and Huang, Xiaojun
- Published
- 2024
- Full Text
- View/download PDF
33. Lipschitz constants for a hyperbolic type metric under Möbius transformations
- Author
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Wu, Yinping, Wang, Gendi, Jia, Gaili, and Zhang, Xiaohui
- Published
- 2024
- Full Text
- View/download PDF
34. The clinical significance and prognostic value of serum beta-2 microglobulin in adult lymphoma-associated hemophagocytic lymphohistiocytosis: a multicenter analysis of 326 patients
- Author
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Jin, Ze, Miao, Yi, Zhang, Jie, Zhang, Jing, Wang, Chunling, Lu, Xuzhang, Miao, Yuqing, Sun, Miao, Zhang, Yunping, Zhuang, Yun, Ni, Haiwen, Xu, Jingyan, Zhuang, Wanchuan, Zhao, Min, Zhu, Jianfeng, Xu, Min, Lin, Guoqiang, Hua, Haiying, Xie, Xiaoyan, Xu, Maozhong, Jia, Tao, Zhai, Lijia, Gu, Weiying, Shan, Qiurong, Wang, Zhi, Shen, Qiudan, Zhang, Xiaohui, Li, Jianyong, and Shi, Wenyu
- Published
- 2024
- Full Text
- View/download PDF
35. RaBFT: an improved Byzantine fault tolerance consensus algorithm based on raft
- Author
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Bai, Fenhua, Li, Fushuang, Shen, Tao, Zeng, Kai, Zhang, Xiaohui, and Zhang, Chi
- Published
- 2024
- Full Text
- View/download PDF
36. CD56bright NK cell expansion correlated with EBV reactivation control post allogeneic hematopoietic stem cell transplantation
- Author
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Juan, Xie, Fan, Zeying, Cao, Xunhong, Ding, Yi-yang, Liu, Huixin, Shang, Qian-nan, Zhao, Xiaosu, Chang, Yingjun, Wang, Yu, Xu, Lanping, Zhang, Xiaohui, Huang, Xiaojun, and Zhao, Xiangyu
- Published
- 2024
- Full Text
- View/download PDF
37. Outcomes and prognosis of haploidentical haematopoietic stem cell transplantation in children with FLT3-ITD mutated acute myeloid leukaemia
- Author
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Shang, Qianwen, Bai, Lu, Cheng, Yifei, Suo, Pan, Hu, Guanhua, Yan, Chenhua, Wang, Yu, Zhang, Xiaohui, Xu, Lanping, Liu, Kaiyan, and Huang, Xiaojun
- Published
- 2024
- Full Text
- View/download PDF
38. Biochemical risk factors and outcomes of acute promyelocytic leukemia patients with thrombotic events: a matched pair analysis
- Author
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Song, Xiaojing, Chi, Cheng, Gao, Weibo, Sun, Wei, Liu, Yang, Zhang, Xiaohui, Huang, Xiaojun, Zhu, Jihong, and Wang, Yu
- Published
- 2024
- Full Text
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39. Clinical efficacy of percutaneous vertebroplasty versus percutaneous kyphoplasty treating osteoporotic vertebral compression fractures with kyphosis
- Author
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Liang, Dawei, Pei, Jia, Pei, Ruoyan, Zhou, Xianwei, and Zhang, Xiaohui
- Published
- 2024
- Full Text
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40. The evolution of preexisting primary immune thrombocytopenia after COVID-19 onset: A nationally representative, prospective, multicentre, observational study
- Author
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Fu, Haixia, Cai, Xuan, Cui, Lijuan, Nong, Weixia, Li, Wenqian, Mei, Heng, Yang, Tonghua, Yue, Han, Huang, Qiusha, An, Zhuoyu, Wu, Yejun, Huang, Xiaojun, and Zhang, Xiaohui
- Published
- 2024
- Full Text
- View/download PDF
41. Comparative efficacy and safety of anti-vascular endothelial growth factor regimens for neovascular age-related macular degeneration: systematic review and Bayesian network meta-analysis
- Author
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Lu Ye, Zhao Jiaqi, Wang Jianchao, Feng Zhaohui, Yao Liang, and Zhang Xiaohui
- Subjects
Therapeutics. Pharmacology ,RM1-950 - Abstract
Background: As a debilitating neurodegenerative disease, neovascular age-related macular degeneration (nAMD) accounts for more than 90% of severe visual loss or legal blindness among AMD patients. Anti-vascular endothelial growth factor (VEGF) had been applied widely in nAMD treatment. To date, debate regarding efficacy and safety still exists among different anti-VEGF regimens as management of nAMD. To provide substantial evidence for clinical nAMD treatment, this study ranks the priority of anti-VEGF regimens via Bayesian network meta-analysis (NMA), comparing data collected from randomized controlled trials (RCTs). Methods: We searched PubMed Central, MEDLINE Ovid, Embase Ovid, ISRCTN, ICTRP and ClinicalTrials. gov from a database established until 1 April 2019 systematically for anti-VEGF regimens. Bayesian NMA with random-effect was conducted to compare efficacy and safety and rank priority of anti-VEGF regimens. The primary efficacy and safety outcomes were the proportion of patients gaining 15 or more letters, and the incidence of arterial thromboembolic (ATC) events. The effect measure is the standard mean difference (SMD), or the odds ratio (OR) with their 95% confidence interval (CI). The study protocol is registered with PROSPERO, number CRD42019132243. Results: We obtained 6467 citations and identified 29 RCTs including 13,596 participants; 86% of these trials were low risk or of uncertain risk bias. In NMA, ORs compared with sham injection for the proportion of patients gaining 15 or more letters (12,699 participants from 23 trials) ranged from 4.05 [95% Bayesian credible interval (CrI) 1.62–10.11] for ranibizumab quarterly regimen to 8.57 (95% CrI 4.66–15.73) for a ranibizumab treat-and-extend regimen. No difference was found between sham injection and anti-VEGF regimens for ATC events (11,500 participants from 18 trials). Results for the primary outcome did not substantially change in sensitivity analyses after removing studies at high risk of bias and small sample size ( n
- Published
- 2020
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42. Optofluidic laser based on a hollow-core negative-curvature fiber
- Author
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Yu Jie, Liu Yange, Wang Yingying, Wang Zhi, Zhang Xiaohui, Liu Xiaoqi, Gao Shoufei, Wang Xiaocong, and Wang Pu
- Subjects
optofluidic dye laser ,hollow-core photonic crystal fiber ,microring resonator ,low threshold ,Physics ,QC1-999 - Abstract
An optofluidic laser based on a hollow-core negative-curvature fiber (HC-NCF) is proposed and demonstrated. The submicron-thick circular capillary tubes embedded in the cladding of the HC-NCF act as antiresonant elements and are used as both a resonator and dye microfluidic channels. A stable optofluidic dye laser with a low threshold of 15.14 nJ/mm2 is achieved. The laser is compact and robust and exhibits directional output.
- Published
- 2018
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43. Enhanced bovine genome annotation through integration of transcriptomics and epi-transcriptomics datasets facilitates genomic biology
- Author
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Beiki, Hamid, Murdoch, Brenda M, Park, Carissa A, Kern, Chandlar, Kontechy, Denise, Becker, Gabrielle, Rincon, Gonzalo, Jiang, Honglin, Zhou, Huaijun, Thorne, Jacob, Koltes, James E, Michal, Jennifer J, Davenport, Kimberly, Rijnkels, Monique, Ross, Pablo J, Hu, Rui, Corum, Sarah, McKay, Stephanie, Smith, Timothy PL, Liu, Wansheng, Ma, Wenzhi, Zhang, Xiaohui, Xu, Xiaoqing, Han, Xuelei, Jiang, Zhihua, Hu, Zhi-Liang, and Reecy, James M
- Subjects
Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Human Genome ,Biotechnology ,Underpinning research ,1.1 Normal biological development and functioning ,Generic health relevance ,Cattle ,Animals ,Gene Expression Profiling ,Genomics ,Sequence Analysis ,RNA ,Transcriptome ,Quantitative Trait Loci ,RNA ,Protein Isoforms ,Molecular Sequence Annotation ,QTL ,epi-genetics ,functional genomics ,multi-omics integration ,trait-similarity network ,transcriptomics - Abstract
BackgroundThe accurate identification of the functional elements in the bovine genome is a fundamental requirement for high-quality analysis of data informing both genome biology and genomic selection. Functional annotation of the bovine genome was performed to identify a more complete catalog of transcript isoforms across bovine tissues.ResultsA total of 160,820 unique transcripts (50% protein coding) representing 34,882 unique genes (60% protein coding) were identified across tissues. Among them, 118,563 transcripts (73% of the total) were structurally validated by independent datasets (PacBio isoform sequencing data, Oxford Nanopore Technologies sequencing data, de novo assembled transcripts from RNA sequencing data) and comparison with Ensembl and NCBI gene sets. In addition, all transcripts were supported by extensive data from different technologies such as whole transcriptome termini site sequencing, RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression, chromatin immunoprecipitation sequencing, and assay for transposase-accessible chromatin using sequencing. A large proportion of identified transcripts (69%) were unannotated, of which 86% were produced by annotated genes and 14% by unannotated genes. A median of two 5' untranslated regions were expressed per gene. Around 50% of protein-coding genes in each tissue were bifunctional and transcribed both coding and noncoding isoforms. Furthermore, we identified 3,744 genes that functioned as noncoding genes in fetal tissues but as protein-coding genes in adult tissues. Our new bovine genome annotation extended more than 11,000 annotated gene borders compared to Ensembl or NCBI annotations. The resulting bovine transcriptome was integrated with publicly available quantitative trait loci data to study tissue-tissue interconnection involved in different traits and construct the first bovine trait similarity network.ConclusionsThese validated results show significant improvement over current bovine genome annotations.
- Published
- 2024
44. TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch
- Author
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Hwang, Jeff, Hira, Moto, Chen, Caroline, Zhang, Xiaohui, Ni, Zhaoheng, Sun, Guangzhi, Ma, Pingchuan, Huang, Ruizhe, Pratap, Vineel, Zhang, Yuekai, Kumar, Anurag, Yu, Chin-Yun, Zhu, Chuang, Liu, Chunxi, Kahn, Jacob, Ravanelli, Mirco, Sun, Peng, Watanabe, Shinji, Shi, Yangyang, Tao, Yumeng, Scheibler, Robin, Cornell, Samuele, Kim, Sean, and Petridis, Stavros
- Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Sound - Abstract
TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research and development of audio and speech technologies by providing well-designed, easy-to-use, and performant PyTorch components. Its contributors routinely engage with users to understand their needs and fulfill them by developing impactful features. Here, we survey TorchAudio's development principles and contents and highlight key features we include in its latest version (2.1): self-supervised learning pre-trained pipelines and training recipes, high-performance CTC decoders, speech recognition models and training recipes, advanced media I/O capabilities, and tools for performing forced alignment, multi-channel speech enhancement, and reference-less speech assessment. For a selection of these features, through empirical studies, we demonstrate their efficacy and show that they achieve competitive or state-of-the-art performance.
- Published
- 2023
45. Deep learning-based image super-resolution of a novel end-expandable optical fiber probe for application in esophageal cancer diagnostics
- Author
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Zhang, Xiaohui, Tan, Mimi, Nabil, Mansour, Shukla, Richa, Vasavada, Shaleen, Anandasabapathy, Sharmila, Anastasio, Mark A., and Petrova, Elena
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Significance: Endoscopic screening for esophageal cancer may enable early cancer diagnosis and treatment. While optical microendoscopic technology has shown promise in improving specificity, the limited field of view (<1 mm) significantly reduces the ability to survey large areas efficiently in esophageal cancer screening. Aim: To improve the efficiency of endoscopic screening, we proposed a novel end-expandable endoscopic optical fiber probe for larger field of visualization and employed a deep learning-based image super-resolution (DL-SR) method to overcome the issue of limited sampling capability. Approach: To demonstrate feasibility of the end-expandable optical fiber probe, DL-SR was applied on simulated low-resolution (LR) microendoscopic images to generate super-resolved (SR) ones. Varying the degradation model of image data acquisition, we identified the optimal parameters for optical fiber probe prototyping. The proposed screening method was validated with a human pathology reading study. Results: For various degradation parameters considered, the DL-SR method demonstrated different levels of improvement of traditional measures of image quality. The endoscopist interpretations of the SR images were comparable to those performed on the high-resolution ones. Conclusions: This work suggests avenues for development of DL-SR-enabled end-expandable optical fiber probes to improve high-yield esophageal cancer screening.
- Published
- 2023
46. Exploring Speech Enhancement for Low-resource Speech Synthesis
- Author
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Ni, Zhaoheng, Popuri, Sravya, Dong, Ning, Saijo, Kohei, Zhang, Xiaohui, Lan, Gael Le, Shi, Yangyang, Chandra, Vikas, and Wang, Changhan
- Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
High-quality and intelligible speech is essential to text-to-speech (TTS) model training, however, obtaining high-quality data for low-resource languages is challenging and expensive. Applying speech enhancement on Automatic Speech Recognition (ASR) corpus mitigates the issue by augmenting the training data, while how the nonlinear speech distortion brought by speech enhancement models affects TTS training still needs to be investigated. In this paper, we train a TF-GridNet speech enhancement model and apply it to low-resource datasets that were collected for the ASR task, then train a discrete unit based TTS model on the enhanced speech. We use Arabic datasets as an example and show that the proposed pipeline significantly improves the low-resource TTS system compared with other baseline methods in terms of ASR WER metric. We also run empirical analysis on the correlation between speech enhancement and TTS performances., Comment: Submitted to ICASSP 2024
- Published
- 2023
47. Lipschitz constants for a hyperbolic type metric under M\'obius transformations
- Author
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Wu, Yinping, Wang, Gendi, Jia, Gaili, and Zhang, Xiaohui
- Subjects
Mathematics - Metric Geometry ,51M10, 30C65 - Abstract
Let $D$ be a nonempty open set in a metric space $(X,d)$ with $\partial D\neq \emptyset$. Define \begin{equation*} h_{D,c}(x,y)=\log\left(1+c\frac{d(x,y)}{\sqrt{d_D(x)d_D(y)}}\right), \end{equation*} where $d_D(x)=d(x,\partial D)$ is the distance from $x$ to the boundary of $D$. For every $c\geq 2$, $h_{D,c}$ is a metric. In this paper, we study the sharp Lipschitz constants for the metric $h_{D,c}$ under M\"obius transformations of the unit ball, the upper half space, and the punctured unit ball., Comment: 18 pages
- Published
- 2023
48. Audio Deepfake Detection: A Survey
- Author
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Yi, Jiangyan, Wang, Chenglong, Tao, Jianhua, Zhang, Xiaohui, Zhang, Chu Yuan, and Zhao, Yan
- Subjects
Computer Science - Sound ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Audio deepfake detection is an emerging active topic. A growing number of literatures have aimed to study deepfake detection algorithms and achieved effective performance, the problem of which is far from being solved. Although there are some review literatures, there has been no comprehensive survey that provides researchers with a systematic overview of these developments with a unified evaluation. Accordingly, in this survey paper, we first highlight the key differences across various types of deepfake audio, then outline and analyse competitions, datasets, features, classifications, and evaluation of state-of-the-art approaches. For each aspect, the basic techniques, advanced developments and major challenges are discussed. In addition, we perform a unified comparison of representative features and classifiers on ASVspoof 2021, ADD 2023 and In-the-Wild datasets for audio deepfake detection, respectively. The survey shows that future research should address the lack of large scale datasets in the wild, poor generalization of existing detection methods to unknown fake attacks, as well as interpretability of detection results.
- Published
- 2023
49. Do You Remember? Overcoming Catastrophic Forgetting for Fake Audio Detection
- Author
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Zhang, Xiaohui, Yi, Jiangyan, Tao, Jianhua, Wang, Chenglong, and Zhang, Chuyuan
- Subjects
Computer Science - Sound ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Audio and Speech Processing - Abstract
Current fake audio detection algorithms have achieved promising performances on most datasets. However, their performance may be significantly degraded when dealing with audio of a different dataset. The orthogonal weight modification to overcome catastrophic forgetting does not consider the similarity of genuine audio across different datasets. To overcome this limitation, we propose a continual learning algorithm for fake audio detection to overcome catastrophic forgetting, called Regularized Adaptive Weight Modification (RAWM). When fine-tuning a detection network, our approach adaptively computes the direction of weight modification according to the ratio of genuine utterances and fake utterances. The adaptive modification direction ensures the network can effectively detect fake audio on the new dataset while preserving its knowledge of old model, thus mitigating catastrophic forgetting. In addition, genuine audio collected from quite different acoustic conditions may skew their feature distribution, so we introduce a regularization constraint to force the network to remember the old distribution in this regard. Our method can easily be generalized to related fields, like speech emotion recognition. We also evaluate our approach across multiple datasets and obtain a significant performance improvement on cross-dataset experiments., Comment: 40th Internation Conference on Machine Learning (ICML 2023)
- Published
- 2023
50. A survey on social network’s anomalous behavior detection
- Author
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Xing, Ling, Li, Shiyu, Zhang, Qi, Wu, Honghai, Ma, Huahong, and Zhang, Xiaohui
- Published
- 2024
- Full Text
- View/download PDF
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