3,683 results on '"Song, Zhao"'
Search Results
152. An empirical study of the performance of the sixth generation ports model with smart ports with reference to major container ports in mainland China
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Song, Zhao-Yu, Lin, Cheng-Wei, Feng, Xuehao, and Lee, Paul Tae-Woo
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- 2024
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153. Surgical Treatment of Brucellar Cervical Epidural Abscess
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Li-Di, Liu, Song, Zhao, Yang, Liu, Zhen-Shan, Lv, Yuan-Zhe, Jin, and Shao-Kun, Zhang
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- 2024
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154. An integrated strategy for reducing anastomotic leakage in patients undergoing McKeown esophagectomy
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Yan Zhang, Junya Wang, Shuang Ren, Jia Jiao, Zheng Ding, Hang Yang, Dabo Pan, Jindong Li, Guoqing Zhang, Xiangnan Li, and Song Zhao
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Esophagectomy ,Anastomotic leakage ,Blood supply ,Reconstruction route ,Gastric tube dilation ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Objective: To describe our experience of reducing anastomotic leakage, a problem that has not been properly solved. Methods: Starting in January 2020, we began implementing our integrated strategy (application of an esophageal diameter-approximated slender gastric tube, preservation of the fibrous tissue around the residual esophagus and thyroid inferior pole anastomosis) in consecutive patients undergoing esophagectomy without a nasogastric tube or a nasal-jejunum feeding tube. Additionally, the blood supply at the site of the anastomosis was evaluated with a near-infrared fluorescence thoracoscope after the completion of esophagogastric anastomosis in the integrated strategy group. Results: Of 570 patients who were reviewed, 119 (20.9%) underwent the integrated strategy, and 451 (79.1%) underwent the conventional strategy. The rate of anastomotic leakage was 2.5% in the integrated strategy group and 10.2% in the conventional strategy group (p = 0.008). In the integrated strategy group, the site of most of the anastomotic blood supply was the residual esophagus dominant (82.4%), followed by the gastroesophageal dual-dominant (12.6%) and the gastric tube dominant (5.0%). The reconstruction route was more likely to be orthotopic in the integrated strategy group than in the conventional strategy group (89.9% vs. 38.6%, p = 0.004). Gastric dilation was identified in 3.4% of the patients in the integrated strategy group and in 21.1% in the conventional strategy group. Conclusions: Patients who underwent our proposed integrated strategy (Zhengzhou Strategy) during McKeown esophagectomy without a nasogastric tube or a nasal-jejunum feeding tube had a strikingly lower rate of anastomotic leakage and a relatively lower rate of postoperative complications, such as gastric tube dilation and delayed gastric emptying.
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- 2024
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155. Polyploid giant cancer cells induced by Docetaxel exhibit a senescence phenotype with the expression of stem cell markers in ovarian cancer cells.
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Song Zhao, Lili Wang, Mingyue Ouyang, Sining Xing, Shuo Liu, Lingyan Sun, and Huiying Yu
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Medicine ,Science - Abstract
Docetaxel (Doc) plays a crucial role in clinical antineoplastic practice. However, it is continuously documented that tumors frequently develop chemoresistance and relapse, which may be related to polyploid giant cancer cells (PGCCs). The aim of this study was investigate the formation mechanism and biological behavior of PGCCs induced by Doc. Ovarian cancer cells were treated with Doc, and then the effect of Doc on cellular viability was evaluated by MTT assay and microscopic imaging analysis. The biological properties of PGCCs were further evaluated by Hoechst 33342 staining, cell cycle and DNA content assay, DNA damage response (DDR) signaling detection, β-galactosidase staining, mitochondrial membrane potential detection, and reverse transcription-quantitative polymerase chain reaction. The results indicated that Doc reduced cellular viability; however, many cells were still alive, and were giant and polyploid. Doc increased the proportion of cells stayed in the G2/M phase and reduced the number of cells. In addition, the expression of γ-H2A.X was constantly increased after Doc treatment. PGCCs showed senescence-associated β-galactosidase activity and an increase in the monomeric form of JC-1. The mRNA level of octamer-binding transcription factor 4 (OCT4) and krüppel-like factor 4 (KLF4) was significantly increased in PGCCs. Taken together, our results suggest that Doc induces G2/M cell cycle arrest, inhibits the proliferation and activates persistent DDR signaling to promote the formation of PGCCs. Importantly, PGCCs exhibit a senescence phenotype and express stem cell markers.
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- 2024
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156. Effect of temperature and water conditioning on noise and skid resistance of dense-graded, open-graded and gap-graded asphalt mixes
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Song Zhao, Haitao Zhang, Yuping Feng, Zhichao Guo, Hongsheng Yang, and Yiming Li
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Permeable asphalt mixture ,Water-temperature coupling ,Meso structure ,Functional characteristics ,Influence mechanism ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
With the rapid development of the transportation industry, permeable asphalt pavement has become widely used in the construction of expressways and urban roads due to its safety, comfort, and environmental protection characteristics. However, water-temperature coupling can damage the mechanical properties of permeable asphalt mixtures. The use of high-viscosity modified asphalt can improve the water damage resistance of the mixture to a certain extent, resulting in better mechanical properties. This paper focuses on the preparation of PAC-13 mixture specimens using high-viscosity modified asphalt and the study of its noise reduction and anti-skidding properties under water-temperature coupling. SMA-13 and AC-13 are used for comparative research. The influence of water-temperature coupling on the functional characteristics of permeable asphalt mixture is analyzed through standing wave tube test and pendulum test. The results show that PAC-13 exhibits better noise reduction and anti-skidding characteristics than SMA-13 and AC-13. As the temperature increases, the skid resistance of asphalt mixtures weakens, but the noise reduction properties are less affected. Furthermore, the noise reduction and anti-skidding properties of the three mixtures are significantly damaged by the action of water, with PAC-13 being the most affected. Nevertheless, PAC-13 still exhibits the best noise reduction and anti-skidding properties.
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- 2024
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157. Sublinear Least-Squares Value Iteration via Locality Sensitive Hashing
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Shrivastava, Anshumali, Song, Zhao, and Xu, Zhaozhuo
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Computer Science - Data Structures and Algorithms ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
We present the first provable Least-Squares Value Iteration (LSVI) algorithms that have runtime complexity sublinear in the number of actions. We formulate the value function estimation procedure in value iteration as an approximate maximum inner product search problem and propose a locality sensitive hashing (LSH) [Indyk and Motwani STOC'98, Andoni and Razenshteyn STOC'15, Andoni, Laarhoven, Razenshteyn and Waingarten SODA'17] type data structure to solve this problem with sublinear time complexity. Moreover, we build the connections between the theory of approximate maximum inner product search and the regret analysis of reinforcement learning. We prove that, with our choice of approximation factor, our Sublinear LSVI algorithms maintain the same regret as the original LSVI algorithms while reducing the runtime complexity to sublinear in the number of actions. To the best of our knowledge, this is the first work that combines LSH with reinforcement learning resulting in provable improvements. We hope that our novel way of combining data-structures and iterative algorithm will open the door for further study into cost reduction in optimization.
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- 2021
158. FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Convergence Analysis
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Huang, Baihe, Li, Xiaoxiao, Song, Zhao, and Yang, Xin
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Computer Science - Machine Learning ,Computer Science - Distributed, Parallel, and Cluster Computing ,Statistics - Machine Learning - Abstract
Federated Learning (FL) is an emerging learning scheme that allows different distributed clients to train deep neural networks together without data sharing. Neural networks have become popular due to their unprecedented success. To the best of our knowledge, the theoretical guarantees of FL concerning neural networks with explicit forms and multi-step updates are unexplored. Nevertheless, training analysis of neural networks in FL is non-trivial for two reasons: first, the objective loss function we are optimizing is non-smooth and non-convex, and second, we are even not updating in the gradient direction. Existing convergence results for gradient descent-based methods heavily rely on the fact that the gradient direction is used for updating. This paper presents a new class of convergence analysis for FL, Federated Learning Neural Tangent Kernel (FL-NTK), which corresponds to overparamterized ReLU neural networks trained by gradient descent in FL and is inspired by the analysis in Neural Tangent Kernel (NTK). Theoretically, FL-NTK converges to a global-optimal solution at a linear rate with properly tuned learning parameters. Furthermore, with proper distributional assumptions, FL-NTK can also achieve good generalization., Comment: ICML 2021
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- 2021
159. The dissociation of semantically congruent and incongruent cross-modal effects on the visual attentional blink
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Song Zhao, Yuxin Zhou, Fangfang Ma, Jimei Xie, Chengzhi Feng, and Wenfeng Feng
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attentional blink ,cross-modal integration ,audiovisual semantic congruency ,congruent sound ,ERPs ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
IntroductionRecent studies have found that the sound-induced alleviation of visual attentional blink, a well-known phenomenon exemplifying the beneficial influence of multisensory integration on time-based attention, was larger when that sound was semantically congruent relative to incongruent with the second visual target (T2). Although such an audiovisual congruency effect has been attributed mainly to the semantic conflict carried by the incongruent sound restraining that sound from facilitating T2 processing, it is still unclear whether the integrated semantic information carried by the congruent sound benefits T2 processing.MethodsTo dissociate the congruence-induced benefit and incongruence-induced reduction in the alleviation of visual attentional blink at the behavioral and neural levels, the present study combined behavioral measures and event-related potential (ERP) recordings in a visual attentional blink task wherein the T2-accompanying sound, when delivered, could be semantically neutral in addition to congruent or incongruent with respect to T2.ResultsThe behavioral data clearly showed that compared to the neutral sound, the congruent sound improved T2 discrimination during the blink to a higher degree while the incongruent sound improved it to a lesser degree. The T2-locked ERP data revealed that the early occipital cross-modal N195 component (192–228 ms after T2 onset) was uniquely larger in the congruent-sound condition than in the neutral-sound and incongruent-sound conditions, whereas the late parietal cross-modal N440 component (400–500 ms) was prominent only in the incongruent-sound condition.DiscussionThese findings provide strong evidence that the modulating effect of audiovisual semantic congruency on the sound-induced alleviation of visual attentional blink contains not only a late incongruence-induced cost but also an early congruence-induced benefit, thereby demonstrating for the first time an unequivocal congruent-sound-induced benefit in alleviating the limitation of time-based visual attention.
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- 2023
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160. The consensus guideline of perioperative antiviral therapy for AIDS patients in China based on clinical practice
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Rui Ma, Qiang Zhang, Chang song Zhao, Rugang Zhao, Yao Zhang, Yao shen Zhang, Yong Hai, Guo Wei, Yu Pu, Li qiang Hu, Yanzheng Song, Yu Zhang, Bo yong Hu, and Shijie Xin
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human immunodeficiency virus ,perioperative period ,antiretroviral therapy regimen ,viral load ,expert consensus ,Medicine (General) ,R5-920 - Abstract
The prevalence of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) has emerged as a major public health concern in China. When patients with HIV infection undergo surgical treatment, there are two main challenges. Firstly, medical staff face a high risk of HIV infection due to occupational exposure. Secondly, the patient’s immune function is impaired, increasing the risk of opportunistic infections and postoperative complications. The surgical treatment of such patients is unique, and the risk of occupational exposure during the operation primarily depends upon the viral load of HIV/AIDS patients. Therefore, perioperative antiretroviral therapy is of paramount importance in order to standardize the perioperative antiretroviral therapy (ART) for HIV/AIDS patients. The Surgery Group of the Chinese Association of STD and AIDS Prevention and Control, in collaboration with the Treatment Association, and Surgery Group of the Chinese Medical Association of Tropical Diseases and Parasitology, has developed an expert consensus on perioperative antiretroviral therapy for HIV/AIDS patients. This consensus encompasses various aspects, including surgical risk assessment, selection of perioperative antiretroviral therapy regimens, prevention of opportunistic infections, and the crucial focus on rapid preoperative viral load reduction and immune function reconstruction for HIV/AIDS patients.
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- 2023
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161. Development and performance of recombinase-aided amplification (RAA) assay for detecting Schistosoma haematobium DNA in urine samples
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Song Zhao, Qiaoqiao Zhang, Xinyao Wang, Wei Li, Saleh Juma, Robert Berquist, Jianfeng Zhang, and Kun Yang
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Schistosoma haematobium ,Field diagnosis ,Recombinase-aided amplification (RAA) ,Cytochrome c oxidase subunit 1 (cox1) ,Urine ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Rapid diagnosis of urogenital schistosomiasis caused by Schistosoma haematobium requires an accurate and timely assay, especially for low-intensity S. haematobium infection cases and in non-endemic areas. The mitochondrial cytochrome c oxidase 1 (cox1) gene fragment of S. haematobium was selected as detection target as this short fragment, which can be rapidly sequenced and yet possess good diagnostic resolution. A pair of primers and a fluorescent probe were designed according to the principle of recombinase-aided amplification (RAA), which was subsequently optimized and applied as an S. haematobium-specific RAA assay. Its diagnostic performance was validated for sensitivity and specificity in comparison to microscopy-based egg counting after urine filtration. The RAA assay could detect as little as 10 copies/μL of S. haematobium recombinant plasmid, and no cross-reactions were observed with S. mansoni, S. japonicum, Ancylostoma duodenale, Clonorchis sinensis, Echinococcus granulosus, or Ascaris lumbricoides. This test can be conducted at 39 °C and the whole RAA reaction can be completed within 20 min. The validation of the RAA assay showed that it had 100 % consistency with urine-egg microscopy, as it does not require an elaborate reading tool, is simple to use, and should be useful for field diagnostics and point-of-care applications.
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- 2023
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162. Enhancing low-temperature electrochemical kinetics and high-temperature cycling stability by decreasing ionic packing factor
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Changpeng Lv, Chunfu Lin, and Xiu Song Zhao
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Ionic packing factor ,Low-temperature electrochemical kinetics ,High-temperature cycling stability ,Wadsley–Roth niobate ,Substitution ,In situ characterization ,Mechanical engineering and machinery ,TJ1-1570 ,Electronics ,TK7800-8360 - Abstract
Present-day Li+ storage materials generally suffer from sluggish low-temperature electrochemical kinetics and poor high-temperature cycling stability. Herein, based on a Ca2+ substituted Mg2Nb34O87 anode material, we demonstrate that decreasing the ionic packing factor is a two-fold strategy to enhance the low-temperature electrochemical kinetics and high-temperature cyclic stability. The resulting Mg1.5Ca0.5Nb34O87 shows the smallest ionic packing factor among Wadsley–Roth niobate materials. Compared with Mg2Nb34O87, Mg1.5Ca0.5Nb34O87 delivers a 1.6 times faster Li+ diffusivity at −20 °C, leading to 56% larger reversible capacity and 1.5 times higher rate capability. Furthermore, Mg1.5Ca0.5Nb34O87 exhibits an 11% smaller maximum unit-cell volume expansion upon lithiation at 60 °C, resulting in better cyclic stability; at 10C after 500 cycles, it has a 7.1% higher capacity retention, and its reversible capacity at 10C is 57% larger. Therefore, Mg1.5Ca0.5Nb34O87 is an all-climate anode material capable of working at harsh temperatures, even when its particle sizes are in the order of micrometers.
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- 2023
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163. Surfactants effects on the self-healing properties of asphalt mixtures in a water environment
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Qianhui Zhang, Liming Wang, Meiyi Gao, and Song Zhao
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Asphalt self-healing ,Surfactants ,Molecular simulation ,Interface energy ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
Under a certain temperature, cracks in asphalt mixtures can heal themselves, but water in the cracks will reduce the self-healing performance of the asphalt mixture. In this study, surfactants were added to asphalt mixtures. In the presence of water, the characteristics of amphiphilic surfactants are used to promote the adsorption between asphalt and aggregates; In this paper, the ability of surfactants to promote the formation of adsorption of asphalt on the crystal surface is verified using a combination of molecular simulations and macroscopic experiments. Molecular simulation results show that the adsorption energies of asphalt and surfactants, surfactants and silica, and asphalt and silica are all negative. Adsorption can occur between the three interfaces, and the surfactants effectively pulls the asphalt molecules onto the silica molecules, achieving adsorption similar to that between asphalt organic polymers and crystals. Macroscopic experiments show that in asphalt mixtures with active agents added, the active agent can be adsorbed on the surface of the aggregate, part of the asphalt is adsorbed on the surface of the active agent, and part is directly adsorbed on the gravel. Some asphalt is also adsorbed on the aggregate under the action of pure water, but the total adsorption capacity is lower than that of asphalt mixtures containing surfactants.
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- 2023
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164. Research on Adaptive Modulation Coding Technique in VDE-TER Multi-link Mode.
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Chen Song Zhao, Shuaiheng Huai, Yu Chen Wang, and Qing Hu 0001
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- 2023
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165. Research on the Influence of Voltage Platform on the Performance of Electric Drive System
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Zhang, Wenhui, Song, Zhao, Wei, Changhe, Qin, Zhidong, Liu, Jihong, Qi, Ruzhi, China Society of Automotive Engineers, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, and Zhang, Junjie James, Series Editor
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- 2023
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166. IL-1β is involved in docetaxel chemoresistance by regulating the formation of polyploid giant cancer cells in non-small cell lung cancer
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Song Zhao, Sining Xing, Lili Wang, Mingyue Ouyang, Shuo Liu, Lingyan Sun, and Huiying Yu
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Medicine ,Science - Abstract
Abstract Docetaxel (Doc) is a cornerstone of chemotherapy; however, treatment with Doc often and inevitably leads to drug resistance and the formation of polyploid giant cancer cells (PGCCs). In this study, we investigated the effect of Doc on non-small cell lung cancer to explore the role of PGCCs in drug resistance and the molecular mechanisms that regulate this resistance. We found that Doc induced G2/M cell cycle arrest and cell death in A549 and NCI-H1299 cells. However, many cells remained alive and became PGCCs by decreasing the expression of key regulatory proteins related to the cell cycle and proliferation. Notably, the PGCCs showed typical features of senescence, especially upregulation of p21 and p-histone H2A.X expression. Moreover, the mRNA level of IL-1β in the senescence-associated secretory phenotype was increased significantly with the development of PGCCs. Inhibition of IL-1β reduced the expression of p-histone H2A.X and promoted polyploidy to enhance the proapoptotic effect of Doc. Taken together, our results suggested that IL-1β was involved in the formation of PGCCs and regulated the senescence of PGCCs, which contributed to drug resistance to Doc. Therefore, targeting IL-1β in PGCCs may be a novel approach to overcome drug resistance.
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- 2023
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167. CTHP: Selection for adoption of open‐source bioinformatics software based on a customised ISO 25010 quality model, three‐way decision and Delphi hierarchy process
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Yuqi Li, Yixin Bian, Ziheng Zhang, Song Zhao, and Yiqi Liu
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software engineering ,software maintenance ,software metrics ,software quality ,Computer software ,QA76.75-76.765 - Abstract
Abstract The ever‐growing open‐source software tools in different domains increase the difficulty of software selection from the end‐users perspective. The process of evaluating, comparing, and selecting open‐source solutions is far from trivial. Especially, when additional requirements need to be considered, the existing methodologies will fail to adapt to the new tasks. The objective of this study is to present a solution for dealing with this issue. A novel approach, CTHP, is presented for the evaluation and selection of open‐source software in the Bioinformatics domain. First, the ISO 25010 quality model is chosen as the basis. This model is customised according to the special characteristics of the Bioinformatics applications. The customisation is done by extracting the quality factors from the Bioinformatics applications, weighting these factors from the viewpoints of both developers and end‐users, and adding them to the model. After that, Three‐way Decision and Delphi Hierarchy Process are integrated to assist in the selection for adoption. Finally, as a case study, the proposed approach is applied to assist the decision‐making process of two popular natural language processing frameworks in the Bioinformatics area. Our study is a valuable contribution since it provides a systematic way to document the decision‐making process and help the researchers and practitioners of Bioinformatics to make better decisions among the alternatives.
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- 2023
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168. ER Ca2+ overload activates the IRE1α signaling and promotes cell survival
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Song Zhao, Haiping Feng, Dongfang Jiang, Keyan Yang, Si-Tong Wang, Yu-Xin Zhang, Yun Wang, Hongmei Liu, Caixia Guo, and Tie-Shan Tang
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ER Ca2+ overload ,TMCO1 ,ER stress ,IRE1α ,Biotechnology ,TP248.13-248.65 ,Biology (General) ,QH301-705.5 ,Biochemistry ,QD415-436 - Abstract
Abstract Background Maintaining homeostasis of Ca2+ stores in the endoplasmic reticulum (ER) is crucial for proper Ca2+ signaling and key cellular functions. Although Ca2+ depletion has been known to cause ER stress which in turn activates the unfolded protein response (UPR), how UPR sensors/transducers respond to excess Ca2+ when ER stores are overloaded remain largely unclear. Results Here, we report for the first time that overloading of ER Ca2+ can directly sensitize the IRE1α-XBP1 axis. The overloaded ER Ca2+ in TMCO1-deficient cells can cause BiP dissociation from IRE1α, promote the dimerization and stability of the IRE1α protein, and boost IRE1α activation. Intriguingly, attenuation of the over-activated IRE1α-XBP1s signaling by a IRE1α inhibitor can cause a significant cell death in TMCO1-deficient cells. Conclusions Our data establish a causal link between excess Ca2+ in ER stores and the selective activation of IRE1α-XBP1 axis, underscoring an unexpected role of overload of ER Ca2+ in IRE1α activation and in preventing cell death.
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- 2023
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169. Adaptive navigation assistance based on eye movement features in virtual reality
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Song Zhao and Shiwei Cheng
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Eye movement ,Navigation ,Human-computer interaction ,Virtual reality ,Eye tracking ,Computer engineering. Computer hardware ,TK7885-7895 - Abstract
Background: Navigation assistance is very important for users when roaming in virtual reality scenes, however, the traditional navigation method requires users to manually request a map for viewing, which leads to low immersion and poor user experience. Methods: To address this issue, first, we collected data when users need navigation assistance in a virtual reality environment, including various eye movement features such as gaze fixation, pupil size, and gaze angle, etc. After that, we used the Boostingbased XGBoost algorithm to train a prediction model, and finally used it to predict whether users need navigation assistance in a roaming task. Results: After evaluating the performance of the model, the accuracy, precision, recall, and F1-score of our model reached about 95%. In addition, by applying the model to a virtual reality scene, an adaptive navigation assistance system based on the user’s real-time eye movement data was implemented. Conclusions: Compared with traditional navigation assistance methods, our new adaptive navigation assistance could enable the user to be more immersive and effective during roaming in VR environment.
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- 2023
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170. ANKRD29, as a new prognostic and immunological biomarker of non–small cell lung cancer, inhibits cell growth and migration by regulating MAPK signaling pathway
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Hanqing Zhao, Yanbo Wang, Yaomei He, Peng Zhang, Cheng Zeng, Tongxuan Du, Qiushuo Shen, and Song Zhao
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ANKRD29 ,Non–small cell lung cancer ,Cell growth and migration ,Immune therapy response ,Biomarker ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background The predominant cancer-related deaths worldwide are caused by lung cancer, particularly non-small cell lung cancer (NSCLC), despite the fact that numerous therapeutic initiatives have been devised to improve the outcomes. Ankyrin repeat domain (ANKRD) is one of the widespread protein structural motifs in eukaryotes but the functions of ANKRD proteins in NSCLC progression remains unclear. Methods We performed integrative bioinformatical analysis to determine the dysregulated expression of ANKRDs in multiple tumors and the association between ANKRD29 expression and the NSCLC tumor environment. Quantitative real-time PCR (qRT-PCR), western blot, immunohistochemistry (IHC), and tissue microarray (TMA) assays were used to investigate the expression of ANKRD29 in NSCLC cell lines. The role of ANKRD29 in NSCLC cell proliferation and migration in vitro was deteceted by 5-bromodeoxyuridine (BrdU) incorporation, colony formation, flow cytometry, would-healing, trans-well, and western blot experiment. RNA-seq technology was applied to deciper the molecular mechanism regulated by ANKRD29 in NSCLC. Results We constructed a valuable risk-score system for predicting the overall survival outcomes of NSCLC patients based on the expression of five hub ANKRD genes. And we found that the hub gene ANKRD29 was remarkedly decreased in NSCLC tissues and cell lines due to the promoter hypermethylation, and revealed that high ANKRD29 expression obviously correlated with patients’ better clinical outcome. Overexpression of ANKRD29 significantly inhibited cell proliferation and migration, promoted the cancerous cells’ sensitivity to carboplatin and enhanced the killing ability of T cells in NSCLC cells. Interestingly, ANKRD29 can be served as a biomarker to predict the response to immunotherapy in NSCLC. Mechanically, RNA-seq results showed that ANKRD29 could regulate MAPK signaling pathway. Moreover, we screened two potential agonists for ANKRD29. Conclusions ANKRD29 functions as a new tumor suppressor in NSCLC tumorigenesis and could be developed as a biomarker for prognostic prediction, immunotherapy response, and drug susceptibility evaluation of NSCLC in the future.
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- 2023
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171. Caseinate vs bovine serum albumin on stabilizing zein nanoparticles for co-entrapping quercetin and curcumin
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Chen, Xiao, Wang, Zi-Xuan, Zhang, Yi, Liu, Wei, Hao-Song, Zhao, Wu, Yan-Chao, and Li, Hui-Jing
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- 2024
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172. Nitrous oxide production from biological and chemodenitrification by Fe(II) in estuarine and coastal sediments
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Qi, Mengting, Gao, Dengzhou, Dong, Hongpo, Liang, Xia, Song, Zhao, Liu, Min, Hou, Lijun, and Li, Xiaofei
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- 2024
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173. Mechanistic insights into the efficient activation of peracetic acid by ZIF-67 for bisphenol A degradation
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Tan, Zhongxuan, Wang, Zhen, Song, Zhao, Liu, Xiaoxia, Tang, Shiyi, Ren, Nanqi, Ma, Xing, and Chen, Yidi
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- 2024
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174. Near-Optimal Two-Pass Streaming Algorithm for Sampling Random Walks over Directed Graphs
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Chen, Lijie, Kol, Gillat, Paramonov, Dmitry, Saxena, Raghuvansh, Song, Zhao, and Yu, Huacheng
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Computer Science - Data Structures and Algorithms ,Computer Science - Computational Complexity - Abstract
For a directed graph $G$ with $n$ vertices and a start vertex $u_{\sf start}$, we wish to (approximately) sample an $L$-step random walk over $G$ starting from $u_{\sf start}$ with minimum space using an algorithm that only makes few passes over the edges of the graph. This problem found many applications, for instance, in approximating the PageRank of a webpage. If only a single pass is allowed, the space complexity of this problem was shown to be $\tilde{\Theta}(n \cdot L)$. Prior to our work, a better space complexity was only known with $\tilde{O}(\sqrt{L})$ passes. We settle the space complexity of this random walk simulation problem for two-pass streaming algorithms, showing that it is $\tilde{\Theta}(n \cdot \sqrt{L})$, by giving almost matching upper and lower bounds. Our lower bound argument extends to every constant number of passes $p$, and shows that any $p$-pass algorithm for this problem uses $\tilde{\Omega}(n \cdot L^{1/p})$ space. In addition, we show a similar $\tilde{\Theta}(n \cdot \sqrt{L})$ bound on the space complexity of any algorithm (with any number of passes) for the related problem of sampling an $L$-step random walk from every vertex in the graph.
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- 2021
175. Symmetric Sparse Boolean Matrix Factorization and Applications
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Chen, Sitan, Song, Zhao, Tao, Runzhou, and Zhang, Ruizhe
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Data Structures and Algorithms ,Statistics - Machine Learning - Abstract
In this work, we study a variant of nonnegative matrix factorization where we wish to find a symmetric factorization of a given input matrix into a sparse, Boolean matrix. Formally speaking, given $\mathbf{M}\in\mathbb{Z}^{m\times m}$, we want to find $\mathbf{W}\in\{0,1\}^{m\times r}$ such that $\| \mathbf{M} - \mathbf{W}\mathbf{W}^\top \|_0$ is minimized among all $\mathbf{W}$ for which each row is $k$-sparse. This question turns out to be closely related to a number of questions like recovering a hypergraph from its line graph, as well as reconstruction attacks for private neural network training. As this problem is hard in the worst-case, we study a natural average-case variant that arises in the context of these reconstruction attacks: $\mathbf{M} = \mathbf{W}\mathbf{W}^{\top}$ for $\mathbf{W}$ a random Boolean matrix with $k$-sparse rows, and the goal is to recover $\mathbf{W}$ up to column permutation. Equivalently, this can be thought of as recovering a uniformly random $k$-uniform hypergraph from its line graph. Our main result is a polynomial-time algorithm for this problem based on bootstrapping higher-order information about $\mathbf{W}$ and then decomposing an appropriate tensor. The key ingredient in our analysis, which may be of independent interest, is to show that such a matrix $\mathbf{W}$ has full column rank with high probability as soon as $m = \widetilde{\Omega}(r)$, which we do using tools from Littlewood-Offord theory and estimates for binary Krawtchouk polynomials., Comment: 33 pages, to appear in Innovations in Theoretical Computer Science (ITCS 2022), v2: updated refs
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- 2021
176. Solving SDP Faster: A Robust IPM Framework and Efficient Implementation
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Huang, Baihe, Jiang, Shunhua, Song, Zhao, Tao, Runzhou, and Zhang, Ruizhe
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Mathematics - Optimization and Control ,Computer Science - Data Structures and Algorithms - Abstract
This paper introduces a new robust interior point method analysis for semidefinite programming (SDP). This new robust analysis can be combined with either logarithmic barrier or hybrid barrier. Under this new framework, we can improve the running time of semidefinite programming (SDP) with variable size $n \times n$ and $m$ constraints up to $\epsilon$ accuracy. We show that for the case $m = \Omega(n^2)$, we can solve SDPs in $m^{\omega}$ time. This suggests solving SDP is nearly as fast as solving the linear system with equal number of variables and constraints. This is the first result that tall dense SDP can be solved in the nearly-optimal running time, and it also improves the state-of-the-art SDP solver [Jiang, Kathuria, Lee, Padmanabhan and Song, FOCS 2020]. In addition to our new IPM analysis, we also propose a number of techniques that might be of further interest, such as, maintaining the inverse of a Kronecker product using lazy updates, a general amortization scheme for positive semidefinite matrices.
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- 2021
177. Back-n White Neutron Source at CSNS and its Applications
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Collaboration, The CSNS Back-n, Tang, Jing-Yu, An, Qi, Bai, Jiang-Bo, Bao, Jie, Bao, Yu, Cao, Ping, Chen, Hao-Lei, Chen, Qi-Ping, Chen, Yong-Hao, Chen, Zhen, Cui, Zeng-Qi, Fan, Rui-Rui, Feng, Chang-Qing, Gao, Ke-Qing, Gao, Xiao-Long, Gu, Min-Hao, Han, Chang-Cai, Han, Zi-Jie, He, Guo-Zhu, He, Yong-Cheng, Hong, Yang, Hu, Yi-Wei, Huang, Han-Xiong, Huang, Xi-Ru, Jiang, Hao-Yu, Jiang, Wei, Jiang, Zhi-Jie, Jing, Han-Tao, Kang, Ling, Li, Bo, Li, Chao, Li, Jia-Wen, Li, Qiang, Li, Xiao, Li, Yang, Liu, Jie, Liu, Rong, Liu, Shu-Bin, Liu, Xing-Yan, Long, Ze, Luan, Guang-Yuan, Ning, Chang-Jun, Niu, Meng-Chen, Qi, Bin-Bin, Ren, Jie, Ren, Zhi-Zhou, Ruan, Xi-Chao, Song, Zhao-Hui, Sun, Kang, Sun, Zhi-Jia, Tan, Zhi-Xin, Tang, Xin-Yi, Tian, Bin-Bin, Wang, Li-Jiao, Wang, Peng-Cheng, Wang, Zhao-Hui, Wen, Zhong-Wei, Wu, Xiao-Guang, Wu, Xuan, Xie, Li-Kun, Yang, Xiao-Yun, Yang, Yi-Wei, Yi, Han, Yu, Li, Yu, Tao, Yu, Yong-Ji, Zhang, Guo-Hui, Zhang, Lin-Hao, Zhang, Qi-Wei, Zhang, Xian-Peng, Zhang, Yu-Liang, Zhang, Zhi-Yong, Zhou, Lu-Ping, Zhou, Zhi-Hao, and Zhu, Ke-Jun
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Physics - Accelerator Physics - Abstract
Back-streaming neutrons from the spallation target of the China Spallation Neutron Source (CSNS) that emit through the incoming proton channel were exploited to build a white neutron beam facility (the so-called Back-n white neutron source), which was completed in March 2018. The Back-n neutron beam is very intense, at approximately 2*10^7 n/cm^2/s at 55 m from the target, and has a nominal proton beam with a power of 100 kW in the CSNS-I phase and a kinetic energy of 1.6 GeV and a thick tungsten target in multiple slices with modest moderation from the cooling water through the slices. In addition, the excellent energy spectrum spanning from 0.5 eV to 200 MeV, and a good time resolution related to the time-of-flight measurements make it a typical white neutron source for nuclear data measurements; its overall performance is among that of the best white neutron sources in the world. Equipped with advanced spectrometers, detectors, and application utilities, the Back-n facility can serve wide applications, with a focus on neutron-induced cross-section measurements. This article presents an overview of the neutron beam characteristics, the experimental setups, and the ongoing applications at Back-n., Comment: 11 pages, 9 figures
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- 2021
178. Minimum Cost Flows, MDPs, and $\ell_1$-Regression in Nearly Linear Time for Dense Instances
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Brand, Jan van den, Lee, Yin Tat, Liu, Yang P., Saranurak, Thatchaphol, Sidford, Aaron, Song, Zhao, and Wang, Di
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Computer Science - Data Structures and Algorithms ,Mathematics - Optimization and Control - Abstract
In this paper we provide new randomized algorithms with improved runtimes for solving linear programs with two-sided constraints. In the special case of the minimum cost flow problem on $n$-vertex $m$-edge graphs with integer polynomially-bounded costs and capacities we obtain a randomized method which solves the problem in $\tilde{O}(m+n^{1.5})$ time. This improves upon the previous best runtime of $\tilde{O}(m\sqrt{n})$ (Lee-Sidford 2014) and, in the special case of unit-capacity maximum flow, improves upon the previous best runtimes of $m^{4/3+o(1)}$ (Liu-Sidford 2020, Kathuria 2020) and $\tilde{O}(m\sqrt{n})$ (Lee-Sidford 2014) for sufficiently dense graphs. For $\ell_1$-regression in a matrix with $n$-columns and $m$-rows we obtain a randomized method which computes an $\epsilon$-approximate solution in $\tilde{O}(mn+n^{2.5})$ time. This yields a randomized method which computes an $\epsilon$-optimal policy of a discounted Markov Decision Process with $S$ states and $A$ actions per state in time $\tilde{O}(S^2A+S^{2.5})$. These methods improve upon the previous best runtimes of methods which depend polylogarithmically on problem parameters, which were $\tilde{O}(mn^{1.5})$ (Lee-Sidford 2015) and $\tilde{O}(S^{2.5}A)$ (Lee-Sidford 2014, Sidford-Wang-Wu-Ye 2018). To obtain this result we introduce two new algorithmic tools of independent interest. First, we design a new general interior point method for solving linear programs with two sided constraints which combines techniques from (Lee-Song-Zhang 2019, Brand et al. 2020) to obtain a robust stochastic method with iteration count nearly the square root of the smaller dimension. Second, to implement this method we provide dynamic data structures for efficiently maintaining approximations to variants of Lewis-weights, a fundamental importance measure for matrices which generalize leverage scores and effective resistances.
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- 2021
179. Vasculopathy Augments Cardiovascular Risk in Community-Dwelling Elderly with Left Ventricular Hypertrophy
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Rusitanmujiang Maimaitiaili, Song Zhao, Jiadela Teliewubai, Shikai Yu, Weilun Meng, Yifan Zhao, Yawei Xu, and Yi Zhang
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vasculopathies ,left ventricular hypertrophy ,cardiovascular risk ,elderly ,Medicine - Abstract
This study aimed to investigate the impact of various vasculopathies alongside left ventricular hypertrophy (LVH) on cardiovascular risk in the elderly. This prospective cohort study included 3339 older adults from the Northern Shanghai Study, classified into four mutually exclusive left ventricular (LV) geometry groups based on echocardiographic data: normal geometry, concentric remodeling, eccentric hypertrophy, and concentric hypertrophy. Vasculopathy was categorized into three primary types: arteriosclerosis, atherosclerosis, and renal senescence. Major adverse cardiovascular events (MACEs) were defined as non-fatal acute myocardial infarction, non-fatal stroke, and cardiovascular deaths according to ICD-10 codes. Over a median follow-up period of 5.7 years, 221 incident cases of MACEs were identified. Concentric hypertrophy exhibited the highest prevalence of hypertension, the most significant increase in vascular stiffness, and the highest rate of MACEs. The adjusted Cox regression analysis showed that eccentric hypertrophy is associated with an increased risk of MACEs (HR: 1.638 [95% CI: 1.151–2.331], p = 0.006), while concentric hypertrophy shows an even higher risk (HR: 1.751 [95% CI: 1.127–2.721], p = 0.013). Conversely, concentric remodeling was not significantly associated with an increased risk of MACEs. Renal senescence presents a moderate but significant risk for MACEs, with an HR of 1.361 (95% CI: 1.019–1.819; p = 0.037) when adjusted for LVH. The Kaplan–Meier analysis showed that patients with LVH and multiple vasculopathies experience the most significant decrease in survival probability (log-rank p < 0.001). The subgroup analysis revealed that LVH significantly raises the risk of MACEs, especially in older males with hypertension, diabetes, or vasculopathy. This study reinforces the importance of LVH as a predictor of adverse cardiovascular outcomes and underscores the compounded risk associated with the presence of multiple vasculopathies. Additionally, it highlights renal senescence as a distinct and independent risk factor for MACEs, separate from LVH.
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- 2024
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180. Analysis of Underwater Melting Process and Leakage Plugging Performance of Phase-Change Materials
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Shenghang Zhang, Lei Tang, Fei Li, Po Li, Yao Sima, and Song Zhao
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leakage ,self-priming plugging technology ,phase-change material ,plugging effect ,melting process ,Technology ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Microscopy ,QH201-278.5 ,Descriptive and experimental mechanics ,QC120-168.85 - Abstract
Leakage is a high-incidence disease of embankment dams, and efficiently addressing this disease guarantees the safe operation of dams. Underwater leakage self-priming plugging technology is a new technology that utilizes the melting and solidifying characteristics of phase-change materials and the negative pressure in the leakage entry area to accurately plug the leakage. However, little is yet known about the underwater melting process of phase-change materials and how their characteristics influence the plugging effect. In this study, three kinds of phase-change materials, namely, paraffin, rosin, and stearic acid, were used to conduct underwater leakage self-priming plugging tests, observe and analyze the underwater melting process, and compare the plugging effects. The results showed that the underwater melting process of phase-change materials exhibited different plugging window periods depending on their melting points, specific heat capacities, and mobilities, which were the main factors affecting their plugging effects. In the final plugging stage, paraffin had the best plugging effect, but the material strength was low; rosin had good plugging compactness, but the fluidity performance was poor, and the material effective utilization was low; stearic acid had a low melting point but dispersed easily. Therefore, a blocking material with a suitable blocking window period can be produced by adjusting the material properties accordingly for an improved blocking effect.
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- 2024
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181. Study on the Compatibility of SBR and Asphalt Base Based on Molecular Simulation
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Xiaolei Jiao, Dandan Huang, Song Zhao, and Jian Ouyang
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molecular dynamics ,compatibility ,solubility parameters ,modified asphalt ,Technology ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Microscopy ,QH201-278.5 ,Descriptive and experimental mechanics ,QC120-168.85 - Abstract
In the field of highway construction, the application of styrene–butadiene rubber (SBR)-modified asphalt has gained popularity across different levels of road surfaces. A crucial aspect in ensuring the efficacy of this modification lies in the compatibility between SBR and the matrix asphalt. To address this, the current study utilizes molecular dynamics simulation as a technique. By establishing a model for the SBR-modified asphalt mixture, the research quantifies the compatibility level between the SBR modifier and the asphalt. The aim is to uncover the underlying mechanisms of compatibility between the SBR modifier and the base asphalt, ultimately contributing to the improvement of the storage stability of SBR-modified asphalt, which holds significant importance. The investigation began with the creation of models for both the base asphalt and the SBR modifier. A model for the SBR-modified asphalt blending system was then formulated based on these initial models. After undergoing geometry optimization and annealing procedures, the model attained its lowest energy state, providing a reliable basis for examining the performance of SBR-modified asphalt. The study proceeded to calculate solubility parameters and interaction energies of the system to evaluate the compatibility between the SBR modifier and the base asphalt at various temperatures. The analysis of these parameters shed light on the compatibility mechanism between the two components. Notably, it was found that at a temperature of 160 ℃, the compatibility was significantly enhanced. The findings were further corroborated through scanning electron microscope and rheological tests. The outcomes of this research offer theoretical guidance for the application of SBR-modified asphalt.
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- 2024
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182. Recent advances in the fixed-electrode capacitive deionization (CDI): Innovations in electrode materials and applications
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Song, Zhao, Chen, Yidi, Ren, Nanqi, and Duan, Xiaoguang
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- 2023
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183. InstaHide's Sample Complexity When Mixing Two Private Images
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Huang, Baihe, Song, Zhao, Tao, Runzhou, Yin, Junze, Zhang, Ruizhe, and Zhuo, Danyang
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Computer Science - Machine Learning ,Computer Science - Computational Complexity ,Computer Science - Cryptography and Security ,Computer Science - Data Structures and Algorithms ,Statistics - Machine Learning - Abstract
Training neural networks usually require large numbers of sensitive training data, and how to protect the privacy of training data has thus become a critical topic in deep learning research. InstaHide is a state-of-the-art scheme to protect training data privacy with only minor effects on test accuracy, and its security has become a salient question. In this paper, we systematically study recent attacks on InstaHide and present a unified framework to understand and analyze these attacks. We find that existing attacks either do not have a provable guarantee or can only recover a single private image. On the current InstaHide challenge setup, where each InstaHide image is a mixture of two private images, we present a new algorithm to recover all the private images with a provable guarantee and optimal sample complexity. In addition, we also provide a computational hardness result on retrieving all InstaHide images. Our results demonstrate that InstaHide is not information-theoretically secure but computationally secure in the worst case, even when mixing two private images.
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- 2020
184. Metric Transforms and Low Rank Matrices via Representation Theory of the Real Hyperrectangle
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Alman, Josh, Chu, Timothy, Miller, Gary, Narayanan, Shyam, Sellke, Mark, and Song, Zhao
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Computer Science - Computational Geometry ,Computer Science - Machine Learning ,Mathematics - Metric Geometry - Abstract
In this paper, we develop a new technique which we call representation theory of the real hyperrectangle, which describes how to compute the eigenvectors and eigenvalues of certain matrices arising from hyperrectangles. We show that these matrices arise naturally when analyzing a number of different algorithmic tasks such as kernel methods, neural network training, natural language processing, and the design of algorithms using the polynomial method. We then use our new technique along with these connections to prove several new structural results in these areas, including: $\bullet$ A function is a positive definite Manhattan kernel if and only if it is a completely monotone function. These kernels are widely used across machine learning; one example is the Laplace kernel which is widely used in machine learning for chemistry. $\bullet$ A function transforms Manhattan distances to Manhattan distances if and only if it is a Bernstein function. This completes the theory of Manhattan to Manhattan metric transforms initiated by Assouad in 1980. $\bullet$ A function applied entry-wise to any square matrix of rank $r$ always results in a matrix of rank $< 2^{r-1}$ if and only if it is a polynomial of sufficiently low degree. This gives a converse to a key lemma used by the polynomial method in algorithm design. Our work includes a sophisticated combination of techniques from different fields, including metric embeddings, the polynomial method, and group representation theory.
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- 2020
185. On InstaHide, Phase Retrieval, and Sparse Matrix Factorization
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Chen, Sitan, Li, Xiaoxiao, Song, Zhao, and Zhuo, Danyang
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Data Structures and Algorithms ,Statistics - Machine Learning - Abstract
In this work, we examine the security of InstaHide, a scheme recently proposed by [Huang, Song, Li and Arora, ICML'20] for preserving the security of private datasets in the context of distributed learning. To generate a synthetic training example to be shared among the distributed learners, InstaHide takes a convex combination of private feature vectors and randomly flips the sign of each entry of the resulting vector with probability 1/2. A salient question is whether this scheme is secure in any provable sense, perhaps under a plausible hardness assumption and assuming the distributions generating the public and private data satisfy certain properties. We show that the answer to this appears to be quite subtle and closely related to the average-case complexity of a new multi-task, missing-data version of the classic problem of phase retrieval. Motivated by this connection, we design a provable algorithm that can recover private vectors using only the public vectors and synthetic vectors generated by InstaHide, under the assumption that the private and public vectors are isotropic Gaussian., Comment: 30 pages, to appear in ICLR 2021, v2: updated discussion of follow-up work
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- 2020
186. Algorithms and Hardness for Linear Algebra on Geometric Graphs
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Alman, Josh, Chu, Timothy, Schild, Aaron, and Song, Zhao
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Computer Science - Data Structures and Algorithms ,Computer Science - Computational Complexity ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
For a function $\mathsf{K} : \mathbb{R}^{d} \times \mathbb{R}^{d} \to \mathbb{R}_{\geq 0}$, and a set $P = \{ x_1, \ldots, x_n\} \subset \mathbb{R}^d$ of $n$ points, the $\mathsf{K}$ graph $G_P$ of $P$ is the complete graph on $n$ nodes where the weight between nodes $i$ and $j$ is given by $\mathsf{K}(x_i, x_j)$. In this paper, we initiate the study of when efficient spectral graph theory is possible on these graphs. We investigate whether or not it is possible to solve the following problems in $n^{1+o(1)}$ time for a $\mathsf{K}$-graph $G_P$ when $d < n^{o(1)}$: $\bullet$ Multiply a given vector by the adjacency matrix or Laplacian matrix of $G_P$ $\bullet$ Find a spectral sparsifier of $G_P$ $\bullet$ Solve a Laplacian system in $G_P$'s Laplacian matrix For each of these problems, we consider all functions of the form $\mathsf{K}(u,v) = f(\|u-v\|_2^2)$ for a function $f:\mathbb{R} \rightarrow \mathbb{R}$. We provide algorithms and comparable hardness results for many such $\mathsf{K}$, including the Gaussian kernel, Neural tangent kernels, and more. For example, in dimension $d = \Omega(\log n)$, we show that there is a parameter associated with the function $f$ for which low parameter values imply $n^{1+o(1)}$ time algorithms for all three of these problems and high parameter values imply the nonexistence of subquadratic time algorithms assuming Strong Exponential Time Hypothesis ($\mathsf{SETH}$), given natural assumptions on $f$. As part of our results, we also show that the exponential dependence on the dimension $d$ in the celebrated fast multipole method of Greengard and Rokhlin cannot be improved, assuming $\mathsf{SETH}$, for a broad class of functions $f$. To the best of our knowledge, this is the first formal limitation proven about fast multipole methods., Comment: FOCS 2020
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- 2020
187. MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery
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Li, Xiaoxiao, Huang, Yangsibo, Peng, Binghui, Song, Zhao, and Li, Kai
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security - Abstract
To address the issue that deep neural networks (DNNs) are vulnerable to model inversion attacks, we design an objective function, which adjusts the separability of the hidden data representations, as a way to control the trade-off between data utility and vulnerability to inversion attacks. Our method is motivated by the theoretical insights of data separability in neural networking training and results on the hardness of model inversion. Empirically, by adjusting the separability of data representation, we show that there exist sweet-spots for data separability such that it is difficult to recover data during inference while maintaining data utility.
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- 2020
188. TextHide: Tackling Data Privacy in Language Understanding Tasks
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Huang, Yangsibo, Song, Zhao, Chen, Danqi, Li, Kai, and Arora, Sanjeev
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Computer Science - Computation and Language ,Computer Science - Cryptography and Security ,Computer Science - Data Structures and Algorithms ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
An unsolved challenge in distributed or federated learning is to effectively mitigate privacy risks without slowing down training or reducing accuracy. In this paper, we propose TextHide aiming at addressing this challenge for natural language understanding tasks. It requires all participants to add a simple encryption step to prevent an eavesdropping attacker from recovering private text data. Such an encryption step is efficient and only affects the task performance slightly. In addition, TextHide fits well with the popular framework of fine-tuning pre-trained language models (e.g., BERT) for any sentence or sentence-pair task. We evaluate TextHide on the GLUE benchmark, and our experiments show that TextHide can effectively defend attacks on shared gradients or representations and the averaged accuracy reduction is only $1.9\%$. We also present an analysis of the security of TextHide using a conjecture about the computational intractability of a mathematical problem. Our code is available at https://github.com/Hazelsuko07/TextHide, Comment: Findings of EMNLP 2020
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- 2020
189. InstaHide: Instance-hiding Schemes for Private Distributed Learning
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Huang, Yangsibo, Song, Zhao, Li, Kai, and Arora, Sanjeev
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Computer Science - Cryptography and Security ,Computer Science - Computational Complexity ,Computer Science - Data Structures and Algorithms ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
How can multiple distributed entities collaboratively train a shared deep net on their private data while preserving privacy? This paper introduces InstaHide, a simple encryption of training images, which can be plugged into existing distributed deep learning pipelines. The encryption is efficient and applying it during training has minor effect on test accuracy. InstaHide encrypts each training image with a "one-time secret key" which consists of mixing a number of randomly chosen images and applying a random pixel-wise mask. Other contributions of this paper include: (a) Using a large public dataset (e.g. ImageNet) for mixing during its encryption, which improves security. (b) Experimental results to show effectiveness in preserving privacy against known attacks with only minor effects on accuracy. (c) Theoretical analysis showing that successfully attacking privacy requires attackers to solve a difficult computational problem. (d) Demonstrating that use of the pixel-wise mask is important for security, since Mixup alone is shown to be insecure to some some efficient attacks. (e) Release of a challenge dataset https://github.com/Hazelsuko07/InstaHide_Challenge Our code is available at https://github.com/Hazelsuko07/InstaHide, Comment: ICML 2020
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- 2020
190. A Faster Interior Point Method for Semidefinite Programming
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Jiang, Haotian, Kathuria, Tarun, Lee, Yin Tat, Padmanabhan, Swati, and Song, Zhao
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Computer Science - Data Structures and Algorithms ,Mathematics - Optimization and Control - Abstract
Semidefinite programs (SDPs) are a fundamental class of optimization problems with important recent applications in approximation algorithms, quantum complexity, robust learning, algorithmic rounding, and adversarial deep learning. This paper presents a faster interior point method to solve generic SDPs with variable size $n \times n$ and $m$ constraints in time \begin{align*} \widetilde{O}(\sqrt{n}( mn^2 + m^\omega + n^\omega) \log(1 / \epsilon) ), \end{align*} where $\omega$ is the exponent of matrix multiplication and $\epsilon$ is the relative accuracy. In the predominant case of $m \geq n$, our runtime outperforms that of the previous fastest SDP solver, which is based on the cutting plane method of Jiang, Lee, Song, and Wong [JLSW20]. Our algorithm's runtime can be naturally interpreted as follows: $\widetilde{O}(\sqrt{n} \log (1/\epsilon))$ is the number of iterations needed for our interior point method, $mn^2$ is the input size, and $m^\omega + n^\omega$ is the time to invert the Hessian and slack matrix in each iteration. These constitute natural barriers to further improving the runtime of interior point methods for solving generic SDPs., Comment: FOCS 2020
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- 2020
191. Generalized Leverage Score Sampling for Neural Networks
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Lee, Jason D., Shen, Ruoqi, Song, Zhao, Wang, Mengdi, and Yu, Zheng
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Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
Leverage score sampling is a powerful technique that originates from theoretical computer science, which can be used to speed up a large number of fundamental questions, e.g. linear regression, linear programming, semi-definite programming, cutting plane method, graph sparsification, maximum matching and max-flow. Recently, it has been shown that leverage score sampling helps to accelerate kernel methods [Avron, Kapralov, Musco, Musco, Velingker and Zandieh 17]. In this work, we generalize the results in [Avron, Kapralov, Musco, Musco, Velingker and Zandieh 17] to a broader class of kernels. We further bring the leverage score sampling into the field of deep learning theory. $\bullet$ We show the connection between the initialization for neural network training and approximating the neural tangent kernel with random features. $\bullet$ We prove the equivalence between regularized neural network and neural tangent kernel ridge regression under the initialization of both classical random Gaussian and leverage score sampling.
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- 2020
192. An improved quantum-inspired algorithm for linear regression
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Gilyén, András, Song, Zhao, and Tang, Ewin
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Computer Science - Data Structures and Algorithms ,Quantum Physics - Abstract
We give a classical algorithm for linear regression analogous to the quantum matrix inversion algorithm [Harrow, Hassidim, and Lloyd, Physical Review Letters'09, arXiv:0811.3171] for low-rank matrices [Wossnig, Zhao, and Prakash, Physical Review Letters'18, arXiv:1704.06174], when the input matrix $A$ is stored in a data structure applicable for QRAM-based state preparation. Namely, suppose we are given an $A \in \mathbb{C}^{m\times n}$ with minimum non-zero singular value $\sigma$ which supports certain efficient $\ell_2$-norm importance sampling queries, along with a $b \in \mathbb{C}^m$. Then, for some $x \in \mathbb{C}^n$ satisfying $\|x - A^+b\| \leq \varepsilon\|A^+b\|$, we can output a measurement of $|x\rangle$ in the computational basis and output an entry of $x$ with classical algorithms that run in $\tilde{\mathcal{O}}\big(\frac{\|A\|_{\mathrm{F}}^6\|A\|^6}{\sigma^{12}\varepsilon^4}\big)$ and $\tilde{\mathcal{O}}\big(\frac{\|A\|_{\mathrm{F}}^6\|A\|^2}{\sigma^8\varepsilon^4}\big)$ time, respectively. This improves on previous "quantum-inspired" algorithms in this line of research by at least a factor of $\frac{\|A\|^{16}}{\sigma^{16}\varepsilon^2}$ [Chia, Gily\'en, Li, Lin, Tang, and Wang, STOC'20, arXiv:1910.06151]. As a consequence, we show that quantum computers can achieve at most a factor-of-12 speedup for linear regression in this QRAM data structure setting and related settings. Our work applies techniques from sketching algorithms and optimization to the quantum-inspired literature. Unlike earlier works, this is a promising avenue that could lead to feasible implementations of classical regression in a quantum-inspired settings, for comparison against future quantum computers., Comment: 21 pages, v4 journal version, v2 bug fixed
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- 2020
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193. Space-Efficient Interior Point Method, with applications to Linear Programming and Maximum Weight Bipartite Matching
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Liu, S. Cliff, Song, Zhao, Zhang, Hengjie, Zhang, Lichen, and Zhou, Tianyi
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Computer Science - Data Structures and Algorithms - Abstract
We study the problem of solving linear program in the streaming model. Given a constraint matrix $A\in \mathbb{R}^{m\times n}$ and vectors $b\in \mathbb{R}^m, c\in \mathbb{R}^n$, we develop a space-efficient interior point method that optimizes solely on the dual program. To this end, we obtain efficient algorithms for various different problems: * For general linear programs, we can solve them in $\widetilde O(\sqrt n\log(1/\epsilon))$ passes and $\widetilde O(n^2)$ space for an $\epsilon$-approximate solution. To the best of our knowledge, this is the most efficient LP solver in streaming with no polynomial dependence on $m$ for both space and passes. * For bipartite graphs, we can solve the minimum vertex cover and maximum weight matching problem in $\widetilde O(\sqrt{m})$ passes and $\widetilde O(n)$ space. In addition to our space-efficient IPM, we also give algorithms for solving SDD systems and isolation lemma in $\widetilde O(n)$ spaces, which are the cornerstones for our graph results., Comment: 72 pages, full version
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- 2020
194. Bipartite Matching in Nearly-linear Time on Moderately Dense Graphs
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Brand, Jan van den, Lee, Yin-Tat, Nanongkai, Danupon, Peng, Richard, Saranurak, Thatchaphol, Sidford, Aaron, Song, Zhao, and Wang, Di
- Subjects
Computer Science - Data Structures and Algorithms ,Mathematics - Optimization and Control - Abstract
We present an $\tilde O(m+n^{1.5})$-time randomized algorithm for maximum cardinality bipartite matching and related problems (e.g. transshipment, negative-weight shortest paths, and optimal transport) on $m$-edge, $n$-node graphs. For maximum cardinality bipartite matching on moderately dense graphs, i.e. $m = \Omega(n^{1.5})$, our algorithm runs in time nearly linear in the input size and constitutes the first improvement over the classic $O(m\sqrt{n})$-time [Dinic 1970; Hopcroft-Karp 1971; Karzanov 1973] and $\tilde O(n^\omega)$-time algorithms [Ibarra-Moran 1981; Mucha-Sankowski 2004] (where currently $\omega\approx 2.373$). On sparser graphs, i.e. when $m = n^{9/8 + \delta}$ for any constant $\delta>0$, our result improves upon the recent advances of [Madry 2013] and [Liu-Sidford 2020b, 2020a] which achieve an $\tilde O(m^{4/3+o(1)})$ runtime. We obtain these results by combining and advancing recent lines of research in interior point methods (IPMs) and dynamic graph algorithms. First, we simplify and improve the IPM of [v.d.Brand-Lee-Sidford-Song 2020], providing a general primal-dual IPM framework and new sampling-based techniques for handling infeasibility induced by approximate linear system solvers. Second, we provide a simple sublinear-time algorithm for detecting and sampling high-energy edges in electric flows on expanders and show that when combined with recent advances in dynamic expander decompositions, this yields efficient data structures for maintaining the iterates of both [v.d.Brand et al.] and our new IPMs. Combining this general machinery yields a simpler $\tilde O(n \sqrt{m})$ time algorithm for matching based on the logarithmic barrier function, and our state-of-the-art $\tilde O(m+n^{1.5})$ time algorithm for matching based on the [Lee-Sidford 2014] barrier (as regularized in [v.d.Brand et al.]).
- Published
- 2020
195. Greatly enhanced mechanical properties of thermoelectric SnSe through microstructure engineering
- Author
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Chen Chen, Bin-Hao Wang, Hai-Dong Zhao, Bin Zhang, Dan Wang, Tao Shen, Peng-Hui Li, Song Zhao, Dong-Li Yu, Yong-Jun Tian, and Bo Xu
- Subjects
thermoelectric materials ,snse ,mechanical properties ,hardness ,Clay industries. Ceramics. Glass ,TP785-869 - Abstract
The outstanding thermoelectric material, SnSe, is also known for its inferior mechanical properties, which bring great inconvenience for its application in thermoelectric devices. In this work, SnSe bulks were prepared via a sequential procedure of high-pressure synthesis (HPS), ball milling, and spark plasma sintering (SPS). The produced polycrystalline samples with a unique microstructure of tightly-bound quasi-equiaxed grains exhibited excellent mechanical properties. The Vickers hardness (HV), compressive strength (σc), and bending strength (σb) reached 1.1 GPa, 300 MPa, and 90 MPa, respectively, all of which are far superior to those of ordinary polycrystalline SnSe. Furthermore, the microstructures did not deteriorate thermoelectric performance. This work demonstrated an effective procedure to prepare polycrystalline microstructure-engineered SnSe materials, which not only show advantages in device applications but also shed light on property enhancement for other layer-structured thermoelectric materials.
- Published
- 2023
- Full Text
- View/download PDF
196. Study on Tribological Properties of Duplex Coating Formed on Magnesium Alloy Using Micro-Arc Oxidation and Magnetron Sputtering under Different Power
- Author
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AN Ling-yun, CHANG Cheng-gong, YUE Zheng, WANG Zhao, KANG Di-song, ZHAO Ying-jie, MENG Lei-chao
- Subjects
magnesium alloy ,micro-arc oxidation ,magnetron sputtering ,carbon film ,sputtering power ,tribological property ,Materials of engineering and construction. Mechanics of materials ,TA401-492 ,Technology - Abstract
For further improving the tribological properties of magnesium alloy micro-arc oxidation (MAO) coating,a carbon film was deposited on such coating by magnetron sputtering (MS) technology under different sputtering power to prepare duplex MAO/MS coating with different carbon contents.The carbon structure in the coating was tested by Raman spectrometer.Scanning electron microscope (SEM) and energy spectrum (EDS) were employed to analyze the micro morphology and the elemental composition,distribution and content of coatings before and after friction and wear test.Additionally,the tribological properties of the coatings were studied by the ball-on-disk friction tester.Results showed that the carbon film deposited on the surface of the magnesium alloy MAO coating by MS technology partly sealed the micropores of MAO coating,and reduced the size and number of micro-pores as well as the coating’s surface roughness.During the friction and wear process,the duplex coatings exhibited a low friction coefficient,narrow and shallow wear scars,and a small wear rate,indicating that they possessed excellent tribological properties.Moreover,sputtering power had a significant effect on the duplex MAO/MS coatings.The duplex coating prepared under high sputtering power possessed better tribological properties due to lower friction coefficient,narrower and shallower wear scars as well as smaller wear rate,which were attributed to a smoother surface and a larger quantity of C with self-lubricating characteristic.The as-prepared coating could provide a better protection on the substrate especially under high load.
- Published
- 2023
- Full Text
- View/download PDF
197. Hyperbolic Concentration, Anti-concentration, and Discrepancy
- Author
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Song, Zhao and Zhang, Ruizhe
- Subjects
Mathematics - Probability ,Computer Science - Discrete Mathematics - Abstract
Chernoff bound is a fundamental tool in theoretical computer science. It has been extensively used in randomized algorithm design and stochastic type analysis. Discrepancy theory, which deals with finding a bi-coloring of a set system such that the coloring of each set is balanced, has a huge number of applications in approximation algorithms design. Chernoff bound [Che52] implies that a random bi-coloring of any set system with $n$ sets and $n$ elements will have discrepancy $O(\sqrt{n \log n})$ with high probability, while the famous result by Spencer [Spe85] shows that there exists an $O(\sqrt{n})$ discrepancy solution. The study of hyperbolic polynomials dates back to the early 20th century when used to solve PDEs by G{\aa}rding [G{\aa}r59]. In recent years, more applications are found in control theory, optimization, real algebraic geometry, and so on. In particular, the breakthrough result by Marcus, Spielman, and Srivastava [MSS15] uses the theory of hyperbolic polynomials to prove the Kadison-Singer conjecture [KS59], which is closely related to discrepancy theory. In this paper, we present a list of new results for hyperbolic polynomials: * We show two nearly optimal hyperbolic Chernoff bounds: one for Rademacher sum of arbitrary vectors and another for random vectors in the hyperbolic cone. * We show a hyperbolic anti-concentration bound. * We generalize the hyperbolic Kadison-Singer theorem [Br\"a18] for vectors in sub-isotropic position, and prove a hyperbolic Spencer theorem for any constant hyperbolic rank vectors. The classical matrix Chernoff and discrepancy results are based on determinant polynomial. To the best of our knowledge, this paper is the first work that shows either concentration or anti-concentration results for hyperbolic polynomials. We hope our findings provide more insights into hyperbolic and discrepancy theories.
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- 2020
198. Training (Overparametrized) Neural Networks in Near-Linear Time
- Author
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Brand, Jan van den, Peng, Binghui, Song, Zhao, and Weinstein, Omri
- Subjects
Computer Science - Machine Learning ,Computer Science - Data Structures and Algorithms ,Statistics - Machine Learning - Abstract
The slow convergence rate and pathological curvature issues of first-order gradient methods for training deep neural networks, initiated an ongoing effort for developing faster $\mathit{second}$-$\mathit{order}$ optimization algorithms beyond SGD, without compromising the generalization error. Despite their remarkable convergence rate ($\mathit{independent}$ of the training batch size $n$), second-order algorithms incur a daunting slowdown in the $\mathit{cost}$ $\mathit{per}$ $\mathit{iteration}$ (inverting the Hessian matrix of the loss function), which renders them impractical. Very recently, this computational overhead was mitigated by the works of [ZMG19,CGH+19}, yielding an $O(mn^2)$-time second-order algorithm for training two-layer overparametrized neural networks of polynomial width $m$. We show how to speed up the algorithm of [CGH+19], achieving an $\tilde{O}(mn)$-time backpropagation algorithm for training (mildly overparametrized) ReLU networks, which is near-linear in the dimension ($mn$) of the full gradient (Jacobian) matrix. The centerpiece of our algorithm is to reformulate the Gauss-Newton iteration as an $\ell_2$-regression problem, and then use a Fast-JL type dimension reduction to $\mathit{precondition}$ the underlying Gram matrix in time independent of $M$, allowing to find a sufficiently good approximate solution via $\mathit{first}$-$\mathit{order}$ conjugate gradient. Our result provides a proof-of-concept that advanced machinery from randomized linear algebra -- which led to recent breakthroughs in $\mathit{convex}$ $\mathit{optimization}$ (ERM, LPs, Regression) -- can be carried over to the realm of deep learning as well.
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- 2020
199. When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?
- Author
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Du, Simon S., Hu, Wei, Li, Zhiyuan, Shen, Ruoqi, Song, Zhao, and Wu, Jiajun
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Computer Science - Machine Learning ,Mathematics - Optimization and Control ,Statistics - Machine Learning - Abstract
Particle filtering is a popular method for inferring latent states in stochastic dynamical systems, whose theoretical properties have been well studied in machine learning and statistics communities. In many control problems, e.g., partially observed linear dynamical systems (POLDS), oftentimes the inferred latent state is further used for planning at each step. This paper initiates a rigorous study on the efficiency of particle filtering for sequential planning, and gives the first particle complexity bounds. Though errors in past actions may affect the future, we are able to bound the number of particles needed so that the long-run reward of the policy based on particle filtering is close to that based on exact inference. In particular, we show that, in stable systems, polynomially many particles suffice. Key in our proof is a coupling of the ideal sequence based on the exact planning and the sequence generated by approximate planning based on particle filtering. We believe this technique can be useful in other sequential decision-making problems.
- Published
- 2020
200. Super-resolution and Robust Sparse Continuous Fourier Transform in Any Constant Dimension: Nearly Linear Time and Sample Complexity
- Author
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Jin, Yaonan, Liu, Daogao, and Song, Zhao
- Subjects
Computer Science - Data Structures and Algorithms - Abstract
The ability to resolve detail in the object that is being imaged, named by resolution, is the core parameter of an imaging system. Super-resolution is a class of techniques that can enhance the resolution of an imaging system and even transcend the diffraction limit of systems. Despite huge success in the application, super-resolution is not well understood on the theoretical side, especially for any dimension $d \geq 2$. In particular, in order to recover a $k$-sparse signal, all previous results suffer from either/both poly$(k)$ samples or running time. We design robust algorithms for any (constant) dimension under a strong noise model based on developing some new techniques in Sparse Fourier transform (Sparse FT), such as inverting a robust linear system, "eggshell" sampling schemes, and partition and voting methods in high dimension. These algorithms are the first to achieve running time and sample complexity (nearly) linear in the number of source points and logarithmic in bandwidth for any constant dimension, and we believe the techniques developed in the work can find their further applications on the Super-resolution and Sparse FT problem., Comment: SODA 2023
- Published
- 2020
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