25,806 results on '"Zhao Ming"'
Search Results
2. Prediction of mutation-induced protein stability changes based on the geometric representations learned by a self-supervised method
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Shan Shan Li, Zhao Ming Liu, Jiao Li, Yi Bo Ma, Ze Yuan Dong, Jun Wei Hou, Fu Jie Shen, Wei Bu Wang, Qi Ming Li, and Ji Guo Su
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Protein stability changes ,Mutation ,Graph attention network ,Self-supervised learning ,EXtreme Gradient Boosting model ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Thermostability is a fundamental property of proteins to maintain their biological functions. Predicting protein stability changes upon mutation is important for our understanding protein structure–function relationship, and is also of great interest in protein engineering and pharmaceutical design. Results Here we present mutDDG-SSM, a deep learning-based framework that uses the geometric representations encoded in protein structure to predict the mutation-induced protein stability changes. mutDDG-SSM consists of two parts: a graph attention network-based protein structural feature extractor that is trained with a self-supervised learning scheme using large-scale high-resolution protein structures, and an eXtreme Gradient Boosting model-based stability change predictor with an advantage of alleviating overfitting problem. The performance of mutDDG-SSM was tested on several widely-used independent datasets. Then, myoglobin and p53 were used as case studies to illustrate the effectiveness of the model in predicting protein stability changes upon mutations. Our results show that mutDDG-SSM achieved high performance in estimating the effects of mutations on protein stability. In addition, mutDDG-SSM exhibited good unbiasedness, where the prediction accuracy on the inverse mutations is as well as that on the direct mutations. Conclusion Meaningful features can be extracted from our pre-trained model to build downstream tasks and our model may serve as a valuable tool for protein engineering and drug design.
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- 2024
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3. Aberration-corrected hybrid metalens for longwave infrared thermal imaging
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Hu Tie, Wen Liqing, Li Haowei, Wang Shengqi, Xia Rui, Mei Zihan, Yang Zhenyu, and Zhao Ming
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hybrid metalens ,aberration-corrected ,thermal imaging ,longwave infrared ,Physics ,QC1-999 - Abstract
Wide-angle metalenses in the longwave infrared have shown great advantages over the traditional refractive doublets or triplets, due to light weight, CMOS compatibility, and low cost. However, previous endeavors have been plagued by challenges including a narrow waveband, large F-number, distortion, and spherical aberration. To address these problems, this study introduces two dispersive metasurfaces, placed near the front focal plane and upon the rear plane of a plano-convex lens, to correct optical aberrations. Utilizing this methodology, we propose and experimentally demonstrate an aberration-corrected hybrid metalens for thermal imaging in the 8–12 μm waveband, featuring an FOV of 24°, F-number of 1.2, and diameter of 12.2 mm. The developed hybrid metalens rigorously evaluated, exhibits Modulation Transfer Function (MTF) values exceeding 0.2 at 20 Lp/mm across the full FOV, and features an average transmission of 48.7 %, a relative focusing efficiencies of up to 42.1 %, polarization insensitivity and broadband imaging capacity. These results emphasize the potential applications of our system in diverse fields, such as camera lenses, autonomous driving, healthcare, and environmental monitoring.
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- 2024
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4. Effect of bone window closure on moderate to severe traumatic brain injury models in mice
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ZHAO Ming-yu, YANG Chen, LIU Yu-heng, LI Jing, YU Ming-sheng, and WANG Zeng-guang
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brain injuries, traumatic ,decompressive craniectomy ,intracranial pressure ,brain edema ,morris water maze test ,nissl bodies ,disease models, animal ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Objective To investigate the effect of bone window closure on moderate to severe traumatic brain injury (TBI) in mice by controlled cortical impact (CCI). Methods A total of 200 healthy male mice were divided into 2 groups for moderate and severe TBI. Fifty were randomly selected from each group for bone window closed, and the remaining 50 were not closed. The intracranial pressure (ICP) was monitored, the water content of brain tissue and the volume of cerebral edema were measured, the degree of neurological impairment was assessed by modified Neurological Severity Score (mNSS), and the spatial learning ability and memory were evaluated by Morris water maze test. Nissl staining assessed the degree of neuronal damage in the cerebral cortex and CA1 region of the hippocampus. Results For ICP, there were differences in ICP between the bone window closed group and the unclosed group in both the moderate and severe TBI (P = 0.007, 0.000). There were also significant differences in ICP at different observation time points after modeling (P = 0.000, 0.000). The ICP on 1 d of the moderate bone window closed group was higher than that in the moderate bone window unclosed group (P = 0.009), 1 d (P = 0.000) and 3 d (P = 0.038) of the severe bone window closed group was higher than that of the severe bone window unclosed group. On 7 d, the ICP in the moderate bone window closed group (P = 0.000, 0.000) and the severe bone window closed group (P = 0.000, 0.008) was lower than that on 1 and 3 d, and the ICP on 3 d was also lower than that on 1 d (P = 0.000, 0.000). The ICP in the moderate bone window unclosed group on 7 d was lower than that on 1 d (P = 0.031). The water content of brain tissue was lower on 1 d (P = 0.028), 3 d (P = 0.023) and 7 d (P = 0.023) in severe bone window closed group than that of severe bone window unclosed group. The volume of brain edema in the bone window closed group was smaller than that in the bone window unclosed group (P = 0.021, 0.037). In the evaluation of the degree of neurological impairment, there were differences in mNSS scores at different observation time points between the bone window closed group and the bone window unclosed group (P = 0.000, 0.001). On 7 d, the mNSS scores of the moderate bone window closed group (P = 0.002), the moderate bone window unclosed group (P = 0.013) and the severe bone window closed group (P = 0.009) were all lower than those on 1 d. The mNSS scores of the severe bone window closed group (P = 0.006) and the severe bone window unclosed group (P = 0.002) were all lower than those of 3 d. Morris water maze test showed that the platform latency of mice in the severe bone window closed group was longer than that in the severe bone window unclosed group (P = 0.045), and the target quadrant residence time was shorter than that in the severe bone window unclosed group (P = 0.025). Nissl staining showed compared with the moderate bone window unclosed group, the density of Nissl bodies in cerebral cortex neurons was decreased, the staining was lighter, and the density of Nissl bodies in cerebral cortex neurons of CA1 region of hippocampus was decreased, the Nissl staining was lighter and the shape was blurred in the moderate bone window closed group. In severe TBI model mice, compared with the bone window unclosed group, the density of Nissl bodies in cerebral cortex and hippocampal CA1 region of the bone window closed group was decreased, the staining was blurred, and more metachromic particles appeared, hippocampal CA1 region body edema, the Nissl staining blurred. Conclusions In moderate TBI model mice, bone window closure increases ICP in the acute stage, but has no significant effect on the degree of cerebral edema, neurological function and cognitive function. In severe TBI model mice, bone window closure can lead to increased ICP and decreased spatial learning ability and memory, but it can reduce the degree of brain edema and improve neurological function. It is suggested that bone window closure should be selected according to the purpose of the study.
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- 2024
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5. Low voltage ride-through control of virtual synchronous generator based on phase and amplitude compensation
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CHEN Zhiyong, DONG Xinwei, LI Chuanhui, WANG Zhichao, ZHAO Ming, and DU Xiuwen
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virtual synchronous generator (vsg) ,low voltage ride-through ,phase and amplitude jump ,phase and amplitude compensation ,overcurrent suppression ,output power stabilization ,reactive power compensation ,Applications of electric power ,TK4001-4102 - Abstract
Virtual synchronous generator (VSG) enhances the stability of distributed power sources during grid connection by simulating the operating principle of a synchronous generator and introducing the virtual inertia and damping coefficient. However the traditional VSG control strategy struggles to address abrupt changes in grid voltage phase and amplitude when the voltage drops in the grid. Therefore, a low voltage ride-through control method for VSG based on phase and amplitude compensation is proposed. Firstly, the different effects of voltage drops and recovery on the power grid are analyzed. Secondly, during voltage drops, the purposes of overcurrent suppression, rapid stabilization of output power, and reactive power compensation are achieved by controlling the phase and amplitude difference between VSG output voltage and grid voltage within the allowable range. Then, during voltage recovery, rapid compensation eliminates the phase difference and amplitude difference between VSG output voltage and grid voltage to suppress overcurrent and other problems caused by grid voltage jumps. Finally, the effectiveness of the proposed control strategy is verified by MATLAB/Simulink simulation. The simulation results show that it can effectively suppress the overcurrent and realize reactive power compensation.
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- 2024
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6. Proposing a Seven-parameter Polynomial Equation to Fit the Moisture Sorption Isotherms of Helium Cold Plasma-treated Wheat Flours
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WANG Meng-ya, ZHAO Ming-hui, GAO Guang-biao, WU Jian-zhang, LI Xing-jun, and WANG Wan-gui
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polynomial equilibrium moisture equation ,flour ,helium-cold plasma ,hysteresis loop ,extended pressure ,Food processing and manufacture ,TP368-456 ,Nutrition. Foods and food supply ,TX341-641 - Abstract
For seeking the cause of the increase in dough water absorption rate after cold plasma treatment, this study adopted low-pressure, radiofrequency 120 W helium cold plasma (CP) to treat wheat flours from 0 s to 180 s. Results showed that water absorption rate, conductivity, values of water and sucrose solvent retention capacity (SRC), and paste breakdown value in wheat flours increased significantly with increasing CP treatment time. To further explore the change causes in these physiochemical indexes, we developed a seven- parameter polynomial , (M was equilibrium moisture (%), ERH was equilibrium relative humidity (decimal), t was temperature (℃), and A~G were parameters. This polynomial could fit moisture sorption isotherms (20-35 ℃ and ERH 10%-90%) of helium CP treated flours, and the goodness-of-fit indexes were superior to those of modified Chung-Pfost (commonly used) and four-parameter polynomial (without temperature term) equations. The seven-parameter polynomial equation clearly showed the hysteresis loops between moisture adsorption and desorption isotherms of flour samples, which shifted downward with increasing temperature. The hysteresis degree showed a parabolic shape curve with increasing ERH, and the vertex of the parabola was at the range of 40-50% ERH. CP treatment shifted the monolayer adsorption sites to multi-molecular adsorption sites ahead of schedule, from ERH 50% to 40%. Further analysis using Dent model showed that the helium CP treatment was able to reduce the mono-layer moisture content and spreading pressure in wheat flour, and increase the elasticity of a capillary wall. The ability of water molecules was increased to form hydrogen bonds with the chemical components, which promoted the uniform distribution and permeation of water molecules into flour particles. Infrared spectral scanning showed that the degree of short-range order at the surface of starch granules and the interaction between protein and starch tended to increase with increasing CP time. Helium cold plasma technology has potential application in improving flour processing quality.
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- 2024
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7. Temporal and Spatial Evolution Characteristics of Carbon Storage in Hefei Ecosystem Based on PLUS and InVEST Models
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ZHI Fei, ZHOU Zhenhong, ZHAO Ming, and WANG Shiqi
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invest model ,plus model ,carbon stocks ,composite index of land use ,Environmental sciences ,GE1-350 ,Agriculture - Abstract
[Objective] To seek a new urban development plan of Hefei under the guidance of “double carbon” goal. [Methods] Based on the land use data of Hefei City in the 5th period from 2000 to 2020, under the guidance of territorial spatial Planning of Hefei City, the spatio-temporal evolution law of land use in 2035 was simulated by the PLUS model, and the spatio-temporal change characteristics of carbon storage in Hefei City under multiple scenarios were explored by coupling the InVEST model. And further explore the effect of the comprehensive land use on the carbon storage. [Results] (1) The main characteristics of land use change in Hefei City from 2000 to 2020 were the decrease of cultivated land and forest land, among which cultivated land was the main source of construction land expansion. The law of land change in the natural development and farmland resource protection scenarios was roughly the same, mainly represented by the reduction of cultivated land, forest land and water body. In the green urban development scenario, the area of forest land changed from decreasing to increasing compared with the other two scenarios. (2) Carbon storage in Hefei City decreased year by year from 2000 to 2020, and the carbon loss was the most 2005 to 2010. By 2035, the carbon reserves of natural development scenario, farmland resource protection scenario and green urban development scenario were 138.96×106 t, 140.13×106 t, and 139.81×106 t, respectively. Under the farmland resource protection scenario, the area with the lowest increase of carbon storage significantly slowed down the expansion of the construction land. under the scenario of urban development, forest land changes from carbon loss to carbon sequestration, which was the most potential trend of carbon sequestration. (3) The land utilization rate of green urban development scenario was the highest, which can effectively reduce the threat of comprehensive land use degree to carbon storage loss. [Conclusion] Both farmland resource protection scenario and green accumulation urban development scenario were conducive to urban carbon sequestration development. Implementing parallel policies of ecological protection and urban development, and adjusting comprehensive land use mode were conducive to improving urban carbon loss.
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- 2024
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8. Study on the Characteristics of Monolayer Water and Bound Water of Wheat Flour after Cold Plasma Treatment
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ZHAO Ming-hui, LI Xing-jun, WU Jian-zhang, JIE Yu, WANG Meng-ya, and JIANG Yu-shan
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wheat shorts ,modified caurie equation ,the density of adsorbed water ,monolayer water content ,the number of sorbed water layers ,cold plasma ,Food processing and manufacture ,TP368-456 ,Nutrition. Foods and food supply ,TX341-641 - Abstract
To understand the cause for the increasing water absorption rate of wheat shorts after cold plasma treatment, a dynamic moisture adsorption instrument was used to measure the moisture sorption isotherms of samples treated with 120 W low-pressure strong radio frequency helium or oxygen CP for different times. The result was that the Caurie equation can fit an isotherm, and its coefficient C0 gived the density of water adsorbed by the sample. For adsorbed or desorbed samples, as the helium or oxygen CP treatment time at the same power increased, there was no difference in the density of adsorbed water, and the coefficient M0 gived the adsorbed water content of the monomolecular layer of the sample. For adsorbed or desorbed samples, as the helium CP treatment time at the same power increased, the water content of the monomolecular layer increased significantly. For samples treated with oxygen plasma, the content of the adsorbed monomolecular layer water first decreased and then increased as the treatment time increased, while the desorbed single-molecule water content showed a decreasing trend with the increased time. In order to improve the fitting of the Caurie equation, M0 was corrected to A+Bt (t was the temperature, A and B were constants). Analysis of the coefficients of the modified Caurie equation showed that as the 120 W helium CP treatment time (0~180 s) increased, the monomolecular layer of water, the number of adsorbed water molecule layers, the bound water content, and the water adsorption surface area all showed a continuous increase trend. For oxygen CP, these indicators showed an increasing trend in the first 60 s of processing, and then showed a decreasing trend if the processing time was extended. The results showed that compared with oxygen-cold plasma, high-energy helium-cold plasma improved the hydrophilicity of wheat shorts proteins and polysaccharides. As the treatment time increased, the surface area and number of layers of water adsorbed by these macromolecules and the monomolecular layer, and the bound water content steadily continued to increase.
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- 2024
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9. Design of hepadnavirus core protein-based chimeric virus-like particles carrying epitopes from respiratory syncytial virus
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Shuai Shao, Xue Feng Zhang, Jun Wei Hou, Sen Sen Yang, Zi Bo Han, Hai Lan Wu, Fang Tang, Xin Yu Li, Ze Hua Lei, Zi Xin Zhao, Shu Xiang Li, Zhao Ming Liu, Pu Shan, Yu Qin Jin, Ji Guo Su, Yu Liang, Jing Zhang, and Qi Ming Li
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Immunologic diseases. Allergy ,RC581-607 ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Respiratory syncytial virus (RSV) is one of the most important pathogens causing respiratory tract infection in humans, especially in infants and the elderly. The identification and structural resolution of the potent neutralizing epitopes on RSV fusion (F) protein enable an “epitope-focused” vaccine design. However, the display of RSV F epitope II on the surface of the widely-used human hepatitis B virus core antigen (HBcAg) has failed to induce neutralizing antibody response in mice. Here, we used the hepadnavirus core protein (HcAg) from different mammalian hosts as scaffolds to construct chimeric virus-like particles (VLPs) presenting the RSV F epitope II. Mouse immunization showed that different HcAg-based chimeric VLPs elicited significantly different neutralizing antibody responses, among which the HcAg derived from roundleaf bat (RBHcAg) is the most immunogenic. Furthermore, RBHcAg was used as the scaffold platform to present multiple RSV F epitopes, and the immunogenicity was further improved in comparison to that displaying a single epitope II. The designed RBHcAg-based multiple-epitope-presenting VLP formulated with MF59-like adjuvant elicited a potent and balanced Th1/Th2 immune response, and offered substantial protection in mice against the challenge of live RSV A2 virus. The designed chimeric VLPs may serve as the potential starting point for developing epitope-focused vaccines against RSV. Our study also demonstrated that RBHcAg is an effective VLP carrier for presenting foreign epitopes, providing a promising platform for epitope-focused vaccine design.
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- 2024
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10. Effect of Helium Cold Plasma on the Moisture Sorption Isotherms of Milled Rice
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CAO Zi-yi, LI Xing-jun, SONG Hong-dong, and ZHAO Ming-hui
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cold plasma ,helium ,milled rice ,hygroscopic property ,safe storage moisture ,water contract angle ,Food processing and manufacture ,TP368-456 ,Nutrition. Foods and food supply ,TX341-641 - Abstract
The low-pressure radio-frequency (RF) cold plasma equipment has been developing in China for over 20 years. This equipment can significantly shorten rice cooking time and increase the solid solubility in the porridge. The safety evaluation of cold plasma technology in food industry is being carried out during the recent five years. This study measured the moisture desorption/adsorption isotherms of milled rice treated zero to four times by 120 W-20 s helium cold plasma (CP, 140 Pa, 13.56 MHz, the distance from plasma resource to the samples is 3 cm, 300 g samples were treated each time). In the range of 5 to 45 ℃ and 10% to 90% RH, in contrast to the untreated samples, CP repeat treatments did not change the hygroscopic properties such as monolayer and multilayer moisture properties and the moisture content of safe storage, but they increased hydrophilicity and water absorption rate of milled rice with a significant decrease in water contract angle. This study gives basic data for the safe storage of CP-treated milled rice.
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- 2023
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11. EBV-Positive Classic Hodgkin Lymphoma and Primary Nodal T-Cell/NK-Cell Lymphoma Arising in the Background of Follicular Lymphoma
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Suravi Raychaudhuri, Zhao Ming Dong, Scott Knowles, and Solomon Graf
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Diseases of the blood and blood-forming organs ,RC633-647.5 - Abstract
EBV-positive primary nodal T-cell/NK cell lymphoma (TNKL) is a rare diagnosis with a poor prognosis. No relationship with follicular lymphoma (FL), classic Hodgkin lymphoma (cHL), or other non-Hodgkin lymphomas is established. We describe a case of Epstein–Barr virus (EBV)-positive cHL and EBV-positive primary nodal TNKL in the background of an antecedent FL, with all 3 subtypes identified in a single lymph node biopsy from an immunocompetent patient. Intensive frontline therapy achieved only a temporary response, with subsequent rapid progression associated with hemophagocytic lymphohistiocytosis (HLH). We discuss the relationship of the three lymphoma subtypes and the potential roles of EBV and immune dysregulation as contributing factors to this previously undescribed composite lymphoma.
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- 2024
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12. Energy consumption calculation of campus buildings based on the law of personnel flow
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Zhao Ming‐ming and Lv Zi‐qiang
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campus building complex ,carbon emission ,energy consumption simulation ,people mobility ,Technology ,Science - Abstract
Abstract For a certain functional building group, the coupling relationship between the load of a single unit and entire building groups lies in the spatial and temporal patterns personnel distribution. Using the DeST (Designer's Simulation Toolkit) method, the personnel flow trajectory in a university campus in Shanghai was analyzed and the established energy consumption calculation model based on personnel flow trajectory of university buildings. It is proposed that personnel mobility should be included in the application of DeST to predict the total load of building groups. The results show that after the people flow trajectory was included, the total annual accumulated load decreased from 27.01 to 19.39 GWh, reducing by 28.20%; the hourly load fluctuation became more stable, the daily peak load decreased by 22.57%, and the daily peak valley difference decreased by 43.74%. The results suggest that the prediction for the air conditioning load of building complexes would be better when the trajectory of human flow is considered, minimizing unnecessary system scale and investments. Under the “double carbon” policy, the personnel flow trajectory model can effectively reduce waste in air conditioning energy consumption in campus buildings.
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- 2023
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13. Key grouting technology and engineering demonstration for green mines
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Du Jinlong, Pan Shuren, Liu Changyou, Wei Yunxun, Lu Yan, Pan Haiyang, Qi Kuan, Zhao Ming, Liu Housong, Yao Hongxin, Zhou Yao, Yan Jia, Li Shinian, Zhang Biao, and Zhang Sinuo
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green mine ,multivariate coupling ,intellectualization ,key grouting technology ,engineering demonstration ,Engineering geology. Rock mechanics. Soil mechanics. Underground construction ,TA703-712 ,Mining engineering. Metallurgy ,TN1-997 - Abstract
This study proposed the multi-coupling grouting system with the aim to tackle green mine problems such as surface collapse, water resources destruction and coal based solid waste accumulation.Successfully applied, this system yielded the following major achievements: this study (1) probed into the patterns of development and evolution in mining separation space and primary fracture space, and conducted the intelligent identification of grouting space by means of theoretical analysis, physical and numerical simulation and field detection.(2) prepared multi-source inorganic high-performance grouting materials for different scenarios by using coal-based solid wastes (coal gangue, fly ash), and developed a new KEP grouting material with underwater dispersion resistance, high volume coefficient and high plastic strength.(3) applied cluster well and feather well to grouting hole drilling and and developed an all-weather, high pump pressure and large flow intelligent grouting system; The reinforcement grouting technology is applied for the first time to strengthen the effect of grouting to reduce settlement.(4)put forward the technology system of grouting effect monitoring and detection, and emphatically expounded the borehole detection method of combining drilling core and well logging.(5)formed an intelligent technology system based on the methods of separation space grouting to reduce settlement and treat waste, caving zone grouting to treat waste, goaf grouting to strengthen foundation bearing capacity and treat waste, and roof fissure grouting to control water gushing as the core.Engineering demonstrations of this system have been carried out in Xiadian coal mine, Xinpu phosphate mine, Caojiatan coal mine, Gaojiabao coal mine and other places, which yielded good results.
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- 2023
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14. Safety and immunogenicity of a mosaic vaccine booster against Omicron and other SARS-CoV-2 variants: a randomized phase 2 trial
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Nawal Al Kaabi, Yun Kai Yang, Yu Liang, Ke Xu, Xue Feng Zhang, Yun Kang, Yu Qin Jin, Jun Wei Hou, Jing Zhang, Tian Yang, Salah Hussein, Mohamed Saif ElDein, Ze Hua Lei, Hao Zhang, Shuai Shao, Zhao Ming Liu, Ning Liu, Xiang Zheng, Ji Guo Su, Sen Sen Yang, Xiangfeng Cong, Yao Tan, Wenwen Lei, Xue Jun Gao, Zhiwei Jiang, Hui Wang, Meng Li, Hanadi Mekki Mekki, Walid Zaher, Sally Mahmoud, Xue Zhang, Chang Qu, Dan Ying Liu, Mengjie Yang, Islam Eltantawy, Peng Xiao, Fu Jie Shen, Jin Juan Wu, Zi Bo Han, Li Fang Du, Fang Tang, Shi Chen, Zhi Jing Ma, Fan Zheng, Ya Nan Hou, Xin Yu Li, Xin Li, Zhao Nian Wang, Jin Liang Yin, Xiao Yan Mao, Jin Zhang, Liang Qu, Yun Tao Zhang, Xiao Ming Yang, Guizhen Wu, and Qi Ming Li
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Medicine ,Biology (General) ,QH301-705.5 - Abstract
Abstract An ongoing randomized, double-blind, controlled phase 2 trial was conducted to evaluate the safety and immunogenicity of a mosaic-type recombinant vaccine candidate, named NVSI-06-09, as a booster dose in subjects aged 18 years and older from the United Arab Emirates (UAE), who had administered two or three doses of inactivated vaccine BBIBP-CorV at least 6 months prior to enrollment. The participants were randomly assigned with 1:1 to receive a booster dose of NVSI-06-09 or BBIBP-CorV. The primary outcomes were immunogenicity and safety against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant, and the exploratory outcome was cross-immunogenicity against other circulating strains. Between May 25 and 30, 2022, 516 adults received booster vaccination with 260 in NVSI-06-09 group and 256 in BBIBP-CorV group. Interim results showed a similar safety profile between two booster groups, with low incidence of adverse reactions of grade 1 or 2. For immunogenicity, by day 14 post-booster, the fold rises in neutralizing antibody geometric mean titers (GMTs) from baseline elicited by NVSI-06-09 were remarkably higher than those by BBIBP-CorV against the prototype strain (19.67 vs 4.47-fold), Omicron BA.1.1 (42.35 vs 3.78-fold), BA.2 (25.09 vs 2.91-fold), BA.4 (22.42 vs 2.69-fold), and BA.5 variants (27.06 vs 4.73-fold). Similarly, the neutralizing GMTs boosted by NVSI-06-09 against Beta and Delta variants were also 6.60-fold and 7.17-fold higher than those by BBIBP-CorV. Our findings indicated that a booster dose of NVSI-06-09 was well-tolerated and elicited broad-spectrum neutralizing responses against divergent SARS-CoV-2 variants, including Omicron and its sub-lineages.
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- 2023
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15. Epidemiological characteristics of norovirus infection in Lin’an District of Hangzhou City from 2012 to 2020
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SHI Shuiliang, LYU Lei, DUAN Tianxiao, ZHAO Ming, YE Yajun, YUAN Busheng, and LI Xuan
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norovirus ,epidemiology ,characteristics ,hangzhou ,Medicine - Abstract
ObjectiveTo determine the epidemiological characteristics of norovirus infections in Lin’an District, Hangzhou City from 2012 to 2020, and provide scientific evidence for improving preventive and control measures.MethodsDescriptive epidemiological methods were used to characterize the epidemic and conduct statistical analysis to determine related factors.ResultsA total of 37 clustered outbreaks of norovirus infection were reported in Lin’an District of Hangzhou from 2012 to 2020, including 8 outbreaks in kindergartens, 15 ones in elementary schools, 8 ones in middle and high schools, 2 ones in universities, and 4 other ones. The total number of cases with norovirus infection was 1 194, with the average attack rate of 3.76%. The incidence of norovirus was higher in winter and spring. It was also higher in urban areas, followed by suburban and mountainous areas neighbored to traffic lines. Moreover, attack rates differed significantly by transmission routes, including mixed contact and aerosol transmission, contact transmission, food-borne transmission, and water-borne transmission (χ2=186.91,P
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- 2022
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16. Comparison of oral sodium phosphate tablets and polyethylene glycol lavage solution for colonoscopy preparation: a systematic review and meta-analysis of randomized clinical trials
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Li Yao-dong, Wang Yi-ping, Mai Gang, Han Yang-yun, Zhu Ling-ling, Deng Hong, Deng Jia-zheng, Xiang Rong-chao, Li You-wei, Zhao Ming, Ding Shun-bin, Ling Jing, Shen Yang, Dong Jia-qi, Deng Lei, Song Xiong-feng, Zhang You-jian, and Zhou Zuo-qiong
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colonoscopy ,bowel preparation ,sodium phosphate ,polyethylene glycol electrolyte lavage solution ,meta-analysis ,systematic review ,Medicine (General) ,R5-920 - Abstract
ObjectiveTo systematically compare the bowel cleaning ability, patient tolerance and safety of oral sodium phosphate tablets (NaPTab) and oral polyethylene glycol electrolyte lavage solution (PEGL) to inform clinical decision making.MethodsPubMed, Embase, CBM, WanFang Data, CNKI, and VIP databases were searched for studies that used randomized controlled trials (RCTs) to compare the roles of NaPTab and PEGL in bowel preparation before colonoscopy. Two reviewers independently screened the studies, extracted data, and assessed the risk of bias in the included papers. A meta-analysis was performed using RevMan 5.3 software.ResultsA total of 13 RCTs were eligible for inclusion, including 2,773 patients (1,378 and 1,395 cases in the NaPTab and PEGL groups, respectively). Meta-analysis revealed no significant difference in the cleansing quality of the NaPTab and PEGL groups [RR 1.02, 95% CI (0.96–1.08), P = 0.46]. The incidence of nausea was lower in the NaPTab group than in the PEGL group [RR 0.67, 95% CI (0.58–0.76), p < 0.00001]. Patients rated the taste of NaPTab higher than PEGL [RR 1.33, 95% CI (1.26–1.40), P < 0.00001]. Willingness to repeat the treatment was also higher in the NaPTab group than in the PEGL group [RR 1.52, 95% CI (1.28–1.80), P < 0.00001]. Both serum potassium and serum calcium decreased in both groups after the preparation; however, meta-analysis revealed that both minerals decreased more in the NaPTab group than in the PEGL group [MD = 0.38, 95% CI (0.13–0.62), P = 0.006 for serum potassium and MD = 0.41, 95% CI (0.04–0.77), P = 0.03 for serum calcium]. Meanwhile, serum phosphorus increased in both groups after the preparation; however, levels increased more in the NaPTab group than in the PEGL group [MD 4.51, (95% CI 2.9–6.11), P < 0.00001].ConclusionsWhile NaP tablets and PEGL were shown to have a similar cleaning effect before colonoscopy, NaP tablets had improved patient tolerance. However, NaP tablets had a strong effect on serum potassium, calcium, and phosphorus levels. For patients with low potassium, low calcium, and renal insufficiency, NaP tablets should be prescribed with caution. For those at high-risk for acute phosphate nephropathy, NaP tablets should be avoided. Given the low number and quality of included studies, these conclusions will require additional verification by large high-quality studies.Systematic review registration10.37766/inplasy2023.5.0013, identifier: NPLASY202350013.
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- 2023
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17. Conception, experience and enlightenment of Japan's basic law of food education
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YANG Jin-yu, LI Xu, and ZHAO Ming-yang
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basic law of food education ,food education ,children ,diet ,japan ,Food processing and manufacture ,TP368-456 - Abstract
The research focuses on the conception and experience of the Basic Law of Food Education in Japan, analyzes its conception, and draws the experience of the implementation of "food education" in Japan: Focusing on giving justice and responsibility by means of law; Building a multi-subject cooperation system under the leadership of the government; Implementing an all-round "food education" promotion path and emphasizing the dynamic nature of the "food education promotion basic plan" are the practical experience of "food education" of the law. In order to give play to the educational value of "food breeding" in improving the diet of Chinese children, we can learn from the following aspects: Pay attention to the matching of "food breeding" laws; Establish and improve government management systems and mechanisms; Establish a trinity of family, school and society education model and carry out a long-term follow-up survey of children's dietary status.
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- 2023
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18. Metabolomics of Mice Serum Analysis to Assess the Effects of Saikosaponin D on Breast Cancer
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ZHAO Ming-yue, HOU Yu-zhu, LIU Xin, WANG Yang, SUN Kai-ju, PANG Bo, LIU Shu-ying, LI Dan, and SU Rui1
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ultra-high performance liquid chromatography tandem orbitrap mass spectrometry (uplc-orbitrap ms) ,saikosaponin d (ssd) ,breast cancer ,mice serum ,metabolite ions ,Chemistry ,QD1-999 - Abstract
The implementation of targeted therapies for breast cancer has been a challenge. Saikosaponin D (SsD), a triterpene saponin derived from Bupleurum, exhibits potential therapeutic properties for cancer therapy. Here, the role of SsD in broad antiproliferation effects in breast cancer was investigated, and the SsD pharmaceutical efficacy was evaluated by metabolomics analysis. Low (0.4 mg/kg) and high (2.0 mg/kg) concentrations of SsDs were used to treat breast cancer tumors in mice by intraperitoneal injection. Blood samples of mice were collected and the serum samples were extracted after SsD administration for different days. Subsequently, the serum samples were analyzed by ultra-high performance liquid chromatography tandem Orbitrap mass spectrometry (UPLC-Orbitrap MS). According to the “80% rule”, UPLC-Orbitrap MS data were processed and proper ions were screened out for further analysis. Statistical methods including one-way analysis of variance (One-way ANOVA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to cross validate the reasonable and accuracy of the models. Representational metabolite ions present significant differences acquired by comparison within/between control group, SsD low concentration group and SsD high concentration group. The results of animal survival experiments demonstrated that SsD had obvious therapeutic effect on tumor. Mice treated with low and high concentrations of SsD showed 60% and 80% survival rate, respectively, with a significant increase in survival compared to untreated control mice. Metabonomic results showed that 12 target metabolite ions including pipecolic acid, N-acryloylglycine, 3-methyleneindolenine, L-kynurenine, phenylethylamine, DL-2-aminooctanoic acid, N (6)-methyllysine, indoleacetaldehyde, 3-methylhistamine, hexanoylglycine, hypoxanthine and hexanoylcarnitine were obtained by intra-group (in control group) screening. The signal intensities of these 12 ions changed significantly in the process of tumor growth, which provided theoretical basis for the study of tumor development and evolution. Meanwhile, 7 important metabolite ions including 3-methylene-indolenine, phenylethylamine, pipecolic acid, L-kynurenine, indoleacetaldehyde, 5-acetylamino-6-formylamino-3-methyluracil and proline betaine were obtained by analyzing inter-group data (compared among three groups), and the first 5 metabolite ions were overlapped with the ions in the list of intra-group screening. Moreover, the biological significances of the selected ions with significant difference were investigated, and two highly correlated manifested metabolic pathways including amino acid metabolism and nucleotide metabolism were discussed. Overall, the results derived from intra-group metabolomic analysis were highly correlated with the inter-group results, and the metabolites along the relevant pathways deserve further attention. This study provides a practical strategy for targeting metabolic analysis using natural product to improve the survival of patients with breast cancer.
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- 2022
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19. Study on related risk factors of pain in de novo Parkinson's disease patients
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GUO Zhi⁃ying, LIU Wei⁃guo, SUN Yu, ZHENG Hui⁃fen, YANG Yu⁃xuan, and ZHAO Ming⁃ming
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parkinson disease ,pain ,risk factors ,logistic models ,Neurology. Diseases of the nervous system ,RC346-429 - Abstract
Objective To explore the risk factors of pain in de novo Parkinson's disease (PD) patients. Methods A total of 129 de novo PD patients collected from The Affiliated Brain Hospital of Nanjing Medical University from October 2018 to September 2021 were included. According to the Item ⁃17 of the Unified Parkinson's Disease Rating Scale Ⅱ (UPDRSⅡ⁃17th), patients were classified as PD patients without pain (UPDRSⅡ⁃17th was 0, n = 88) and PD patients with pain (UPDRSⅡ⁃17th ≥ 2, n = 41). Mini⁃ Mental State Examination (MMSE) and corrected Montreal Cognitive Assessment (corrected MoCA) were used to assess cognitive function. Meanwhile, Hamilton Depression Rating Scale ⁃24 Items (HAMD ⁃24) was used to assess the depression status and the UPDRSⅢ was used to assess the motor function. The modified version of Hoehn ⁃Yahr staging was used to assess disease severity. The related risk factors of pain in PD patients were analyzed by univariate and multivariate forward Logistic regression. Results The in of pain in PD patients was 31.78% (41/129). Compared with PD without pain group, PD with pain group had lower scores in MMSE (Z = ﹣2.389, P = 0.017) and corrected MoCA (Z = ﹣2.166, P = 0.030), but higher scores in HAMD-24 (Z = ﹣4.024, P = 0.000), UPDRS Ⅲ (Z = ﹣3.639, P = 0.000)and Hoehn-Yahr staging grading (Z = ﹣2.232, P = 0.026). Further analysis of the differences between 2 groups in 7 domains of HAMD-24 showed PD with pain group had higher scores of the anxiety/somatization (Z = ﹣3.707, P = 0.000), mental disorder (Z = ﹣2.519, P = 0.012), retardation symptom (Z = ﹣2.048, P = 0.041), sleep disturbances (Z = ﹣3.484, P = 0.000) and despair symptom (Z = ﹣3.069, P = 0.002) than PD without pain group. Logistic regression analysis showed long duration (OR = 1.354, 95%CI: 1.013-1.809; P = 0.041), high HAMD-24 score (OR = 1.095, 95%CI: 1.033-1.162; P = 0.002) and high UPDRS Ⅲ score (OR = 1.040, 95%CI: 1.001- 1.082; P = 0.046) were risk factors of pain in PD patients. Conclusions Pain in PD has a high incidence in de novo PD patients. Long duration, a depressed state and severe motor symptoms are main risk factors for the development of pain in PD patients.
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- 2022
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20. Detection rates of mental disorders in pregnant women with subjective depressive symptoms
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ZHAO Ming-zhe, WEI Jing, DUAN Yan-ping, ZHAO Yue, MA Liang-kun
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pregnant women ,mental disorders ,incidence ,Medicine - Abstract
Objective To analyze the detection rates of mental disorders in women with subjective depressive symptoms during pregnancy and the postnatal period. Methods From March 1st 2020 to February 28th 2021, Patient Health Questionnaire-9 items (PHQ-9) and Edinburgh Postnatal Depression Scale (EPDS) were used to screen pregnant women and mothers who were established in a third-grade hospital. The women with PHQ-9≥5 or EPDS≥9 were followed up. Mini-International Neuropsychiatric Interview (MINI) was used to confirm the detection rates of mental disorders. Results Of the 342 women who were followed up, 24 (7.0%) were diagnosed with depressive episodes. There were 17 cases had depression in the past. Among them 3 women had a history of depression before pregnancy, and 14 had the first episode after pregnancy. The detection rate of depression in the second trimester is higher than that in the first and third trimester; 9 (2.6%)with (hypo)manic episodes; 6 (1.8%) with panic disorder; 13(3.8%) with agoraphobia; 3(0.9%) with social phobia; 15(4.4%) with generalized anxiety disorder; 6 (1.8%)with obsessive-compulsive disorder. Eighteen women suffered from two or more mental disorders, accounting for 29.0% of the total number of diagnosed mental disorders. Conclusions A variety of mental disorders occur in women with subjective depressive symptoms during pregnancy and the postnatal period, and comorbidity is a common finding. Pregnant women with depression may have several episodes during this period. So it is necessary to evaluate their mental status professionally.
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- 2022
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21. Design of a mutation-integrated trimeric RBD with broad protection against SARS-CoV-2
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Yu Liang, Jing Zhang, Run Yu Yuan, Mei Yu Wang, Peng He, Ji Guo Su, Zi Bo Han, Yu Qin Jin, Jun Wei Hou, Hao Zhang, Xue Feng Zhang, Shuai Shao, Ya Nan Hou, Zhao Ming Liu, Li Fang Du, Fu Jie Shen, Wei Min Zhou, Ke Xu, Ru Qin Gao, Fang Tang, Ze Hua Lei, Shuo Liu, Wei Zhen, Jin Juan Wu, Xiang Zheng, Ning Liu, Shi Chen, Zhi Jing Ma, Fan Zheng, Si Yu Ren, Zhong Yu Hu, Wei Jin Huang, Gui Zhen Wu, Chang Wen Ke, and Qi Ming Li
- Subjects
Cytology ,QH573-671 - Abstract
Abstract The continuous emergence of SARS-CoV-2 variants highlights the need of developing vaccines with broad protection. Here, according to the immune-escape capability and evolutionary convergence, the representative SARS-CoV-2 strains carrying the hotspot mutations were selected. Then, guided by structural and computational analyses, we present a mutation-integrated trimeric form of spike receptor-binding domain (mutI-tri-RBD) as a broadly protective vaccine candidate, which combined heterologous RBDs from different representative strains into a hybrid immunogen and integrated immune-escape hotspots into a single antigen. When compared with a homo-tri-RBD vaccine candidate in the stage of phase II trial, of which all three RBDs are derived from the SARS-CoV-2 prototype strain, mutI-tri-RBD induced significantly higher neutralizing antibody titers against the Delta and Beta variants, and maintained a similar immune response against the prototype strain. Pseudo-virus neutralization assay demonstrated that mutI-tri-RBD also induced broadly strong neutralizing activities against all tested 23 SARS-CoV-2 variants. The in vivo protective capability of mutI-tri-RBD was further validated in hACE2-transgenic mice challenged by the live virus, and the results showed that mutI-tri-RBD provided potent protection not only against the SARS-CoV-2 prototype strain but also against the Delta and Beta variants.
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- 2022
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22. Numerical analysis on dynamic response characteristics of geosynthetic reinforced embankment under moving load
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ZHANG Ling, OU Qiang, ZHAO Ming-hua, DING Xuan-ming, and LIU Jian-fei
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moving load ,geosynthetics ,reinforced embankment ,finite element ,dynamic response ,Engineering geology. Rock mechanics. Soil mechanics. Underground construction ,TA703-712 - Abstract
The dynamic response of geosynthetic reinforced embankment under traffic moving load has attracted increasing attentions in the engineering field. A 3D model of geosynthetic reinforced embankment was established by using the ABAQUS finite element software in this paper, which was used to analyze the dynamic stress and deformation of geosynthetic reinforced embankment under moving load. The traffic load was simulated by two moving rectangular plane loads. Fortran subroutine was developed to control the amplitude, range, and speed of the moving load. The equivalent linear viscoelastic model was developed to simulate embankment fill to reflect the viscoelasticity of embankment fill. The geogrid was simulated by T3D2 truss element. The infinite element was used to reduce the boundary effect caused by model size. The numerical model of geosynthetic reinforced embankment under moving load was established without considering drainage consolidation. Based on the results of the existing literature and the results of this paper, the cross-section deformations of the geosynthetic reinforced embankment and the stress at the embankment top surface were compared and verified. The dynamic stress distribution in the longitudinal section and transverse section and the vertical dynamic stress distribution characteristics of the geosynthetic reinforced embankment under moving load were also analyzed. The results showed that the dynamic stress and deformation decayed rapidly within the range of 1.0 m on the embankment top surface and gradually transitioned to an equivalent uniform load with small amplitude. At the same depth, the attenuation coefficient of dynamic stress under the wheel load was the smallest, followed by that at the center of double wheel loads, and the attenuation coefficient at the outer edge of the wheel load was the largest.
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- 2021
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23. An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Large-Scale Recommender Systems
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Liu, Peng, Zhu, Jiawei, Xu, Cong, Zhao, Ming, and Wang, Bin
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Computer Science - Information Retrieval ,Computer Science - Machine Learning - Abstract
As the last key stage of Recommender Systems (RSs), Multi-Task Fusion (MTF) is in charge of combining multiple scores predicted by Multi-Task Learning (MTL) into a final score to maximize user satisfaction, which decides the ultimate recommendation results. In recent years, to maximize long-term user satisfaction within a recommendation session, Reinforcement Learning (RL) is widely used for MTF in large-scale RSs. However, limited by their modeling pattern, all the current RL-MTF methods can only utilize user features as the state to generate actions for each user, but unable to make use of item features and other valuable features, which leads to suboptimal results. Addressing this problem is a challenge that requires breaking through the current modeling pattern of RL-MTF. To solve this problem, we propose a novel method called Enhanced-State RL for MTF in RSs. Unlike the existing methods mentioned above, our method first defines user features, item features, and other valuable features collectively as the enhanced state; then proposes a novel actor and critic learning process to utilize the enhanced state to make much better action for each user-item pair. To the best of our knowledge, this novel modeling pattern is being proposed for the first time in the field of RL-MTF. We conduct extensive offline and online experiments in a large-scale RS. The results demonstrate that our model outperforms other models significantly. Enhanced-State RL has been fully deployed in our RS more than half a year, improving +3.84% user valid consumption and +0.58% user duration time compared to baseline., Comment: arXiv admin note: substantial text overlap with arXiv:2404.17589
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- 2024
24. Diagnosing the pattern effect in the atmosphere-ocean coupled system through linear response theory
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Falasca, Fabrizio, Basinski-Ferris, Aurora, Zanna, Laure, and Zhao, Ming
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Physics - Atmospheric and Oceanic Physics ,Condensed Matter - Statistical Mechanics ,Nonlinear Sciences - Chaotic Dynamics - Abstract
The energy surplus resulting from radiative forcing causes warming of the Earth system. This initial warming drives a myriad of changes including in sea surface temperatures (SSTs), leading to different radiative feedbacks. The relationship between the radiative feedbacks and the pattern of SST changes is referred to as the "pattern effect". The current approach to study the pattern effect relies on diagnosing the response of atmosphere-only models to perturbations in the SST boundary condition. Here, we argue that the fluctuation-dissipation relation (FDR), together with coarse-graining procedures, is a computationally cheap and theoretically grounded alternative to model experiments. We introduce a protocol to study the pattern effect and present its application in a state-of-the-art coupled climate model. By focusing on the coupled dynamics, we unveil the role of the slow ocean component in setting the pattern effect. We present a new "sensitivity map", representing a first, qualitative prediction of the response of the average top-of-the-atmosphere (TOA) radiative flux to perturbations in the SST field. We find negative sensitivity throughout the tropics, in contrast to the current understanding of a positive-negative dipole of sensitivity in the tropical Pacific. Considering only the shortest time scales, the response is dominated by the fast atmospheric variability and we recover results in qualitative agreement with the literature. Therefore, the difference between our results and previous studies, largely comes from including the atmosphere-ocean coupling. The framework offers a conceptually novel perspective on the pattern effect: feedbacks in the coupled system are encoded in a temporally and spatially dependent response operator, rather than time-independent maps as for previous studies.
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- 2024
25. The quantum uncertainty relations of quantum channels
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Kong, Shi-Yun, Zhao, Ming-Jing, Wang, Zhi-Xi, and Fei, Shao-Ming
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Quantum Physics - Abstract
The uncertainty relation reveals the intrinsic difference between the classical world and the quantum world. We investigate the quantum uncertainty relation of quantum channel in qubit systems. Under two general measurement bases, we first derive the quantum uncertainty relation for quantum channels with respect to the relative entropy of coherence. Then we obtain the quantum uncertainty relation for unitary channels with respect to the $l_1$ norm of coherence. Some examples are given in detail.
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- 2024
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26. KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment
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Wu, Zongzong, Tang, Fengxiao, Zhao, Ming, and Li, Yufeng
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Computer Science - Cryptography and Security ,Computer Science - Information Retrieval - Abstract
Cyber threat intelligence is a critical tool that many organizations and individuals use to protect themselves from sophisticated, organized, persistent, and weaponized cyber attacks. However, few studies have focused on the quality assessment of threat intelligence provided by intelligence platforms, and this work still requires manual analysis by cybersecurity experts. In this paper, we propose a knowledge graph-based verifier, a novel Cyber Threat Intelligence (CTI) quality assessment framework that combines knowledge graphs and Large Language Models (LLMs). Our approach introduces LLMs to automatically extract OSCTI key claims to be verified and utilizes a knowledge graph consisting of paragraphs for fact-checking. This method differs from the traditional way of constructing complex knowledge graphs with entities as nodes. By constructing knowledge graphs with paragraphs as nodes and semantic similarity as edges, it effectively enhances the semantic understanding ability of the model and simplifies labeling requirements. Additionally, to fill the gap in the research field, we created and made public the first dataset for threat intelligence assessment from heterogeneous sources. To the best of our knowledge, this work is the first to create a dataset on threat intelligence reliability verification, providing a reference for future research. Experimental results show that KGV (Knowledge Graph Verifier) significantly improves the performance of LLMs in intelligence quality assessment. Compared with traditional methods, we reduce a large amount of data annotation while the model still exhibits strong reasoning capabilities. Finally, our method can achieve XXX accuracy in network threat assessment.
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- 2024
27. Federated Hypergraph Learning with Hyperedge Completion
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Luo, Linfeng, Tang, Fengxiao, Liu, Xiyu, Guo, Zhiqi, Qiu, Zihao, and Zhao, Ming
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Computer Science - Machine Learning - Abstract
Hypergraph neural networks enhance conventional graph neural networks by capturing high-order relationships among nodes, which proves vital in data-rich environments where interactions are not merely pairwise. As data complexity and interconnectivity grow, it is common for graph-structured data to be split and stored in a distributed manner, underscoring the necessity of federated learning on subgraphs. In this work, we propose FedHGN, a novel algorithm for federated hypergraph learning. Our algorithm utilizes subgraphs of a hypergraph stored on distributed devices to train local HGNN models in a federated manner:by collaboratively developing an effective global HGNN model through sharing model parameters while preserving client privacy. Additionally, considering that hyperedges may span multiple clients, a pre-training step is employed before the training process in which cross-client hyperedge feature gathering is performed at the central server. In this way, the missing cross-client information can be supplemented from the central server during the node feature aggregation phase. Experimental results on seven real-world datasets confirm the effectiveness of our approach and demonstrate its performance advantages over traditional federated graph learning methods.
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- 2024
28. Arbitrary quantum states preparation aided by deep reinforcement learning
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Wang, Zhao-Wei and Wang, Zhao-Ming
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Quantum Physics - Abstract
The preparation of quantum states is essential in the realm of quantum information processing, and the development of efficient methodologies can significantly alleviate the strain on quantum resources. Within the framework of deep reinforcement learning (DRL), we integrate the initial and the target state information within the state preparation task together, so as to realize the control trajectory design between two arbitrary quantum states. Utilizing a semiconductor double quantum dots (DQDs) model, our results demonstrate that the resulting control trajectories can effectively achieve arbitrary quantum state preparation (AQSP) for both single-qubit and two-qubit systems, with average fidelities of 0.9868 and 0.9556 for the test sets, respectively. Furthermore, we consider the noise around the system and the control trajectories exhibit commendable robustness against charge and nuclear noise. Our study not only substantiates the efficacy of DRL in QSP, but also provides a new solution for quantum control tasks of multi-initial and multi-objective states, and is expected to be extended to a wider range of quantum control problems.
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- 2024
29. Non-Markovian environment induced anomaly in steady state quantum coherence
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Ablimit, Arapat, Wang, Zhao-Ming, Ren, Feng-Hua, Brumer, Paul, and Wu, Lian-Ao
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Quantum Physics - Abstract
Environment induced steady state quantum coherence (SSQC) is a captivating phenomenon that challenges conventional understandings of decoherence. In this letter, we delve into the foundational aspects of environment-induced SSQC, shedding light on its emergence within the framework of system-bath interactions. Starting from a microscopic system-bath coupled model, we investigate the dependence of SSQC on environmental memory effects, bath temperature, system-bath coupling strength, and squeezing parameters. Our findings reveal that the environment not only acts as a generator but also as a disruptor of SSQC. A peak will exist for a non-Markovian bath, which is a result of competition between these two mechanisms. Interestingly, the peak disappears in Markovian case. Additionally, we observe that the generated SSQC can be further amplified through environment squeezing., Comment: 8 pages, 3 figures
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- 2024
30. A mosaic-type trimeric RBD-based COVID-19 vaccine candidate induces potent neutralization against Omicron and other SARS-CoV-2 variants
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Jing Zhang, Zi Bo Han, Yu Liang, Xue Feng Zhang, Yu Qin Jin, Li Fang Du, Shuai Shao, Hui Wang, Jun Wei Hou, Ke Xu, Wenwen Lei, Ze Hua Lei, Zhao Ming Liu, Jin Zhang, Ya Nan Hou, Ning Liu, Fu Jie Shen, Jin Juan Wu, Xiang Zheng, Xin Yu Li, Xin Li, Wei Jin Huang, Gui Zhen Wu, Ji Guo Su, and Qi Ming Li
- Subjects
SARS-CoV-2 ,COVID-19 ,omicron variant ,vaccine ,broad-spectrum ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Large-scale populations in the world have been vaccinated with COVID-19 vaccines, however, breakthrough infections of SARS-CoV-2 are still growing rapidly due to the emergence of immune-evasive variants, especially Omicron. It is urgent to develop effective broad-spectrum vaccines to better control the pandemic of these variants. Here, we present a mosaic-type trimeric form of spike receptor-binding domain (mos-tri-RBD) as a broad-spectrum vaccine candidate, which carries the key mutations from Omicron and other circulating variants. Tests in rats showed that the designed mos-tri-RBD, whether used alone or as a booster shot, elicited potent cross-neutralizing antibodies against not only Omicron but also other immune-evasive variants. Neutralizing antibody ID50 titers induced by mos-tri-RBD were substantially higher than those elicited by homo-tri-RBD (containing homologous RBDs from prototype strain) or the BIBP inactivated COVID-19 vaccine (BBIBP-CorV). Our study indicates that mos-tri-RBD is highly immunogenic, which may serve as a broad-spectrum vaccine candidate in combating SARS-CoV-2 variants including Omicron.
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- 2022
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31. The influence of closed/open conditions on the flavoring compounds produced from tyrosine-based Maillard reaction
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YIN Xiao-qing, LI Rui, PEI Qi, LU Zi-qi, and ZHAO Ming-qin
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closed system ,open system ,maillard reaction ,tyrosine ,Food processing and manufacture ,TP368-456 - Abstract
Objective: This article is aimed to explore the influence of closed/open conditions on the flavor compounds of Maillard reaction. Methods: The species and amounts of flavor compounds produced from Tyrosine-based Maillard reactions under closed/open conditions in different solvents and reaction temperatures were determined by GC-MS. Results: The results showed that the species and contents of flavor products are quite different under closed and open conditions. The amounts of alcohol flavor compounds were higher in closed system, while the amount of esters and ketones were higher inopensystem. Conclusion: The amounts of active oxygen and intermediates produced during the reactions likely result in the difference between closed and opensystems from the proposed mechanisms.
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- 2022
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32. Combined prediction model of truck multi-section travel time in open-pit mine based on velocity field
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TIAN Fengliang, WANG Zhongxin, SUN Xiaoyu, XIN Fengyang, SONG Bo, WANG Jinjin, ZENG Xiangyu, ZHOU Hao, and ZHAO Ming
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open-pit mine ,truck optimal dispatching ,truck travel time ,combined prediction ,velocity field ,random forest algorithm ,Mining engineering. Metallurgy ,TN1-997 - Abstract
Due to the complexity of road in open-pit mine, the existing truck travel time prediction methods are difficult in the actual deployment. This leads to the truck optimal scheduling system only realizing scheduling instead of optimization. A combined prediction model of truck multi-section travel time in open pit mine based on velocity field is proposed. The open-pit mine road is divided into multiple road sections. the random forest algorithm is used to construct the unit prediction model to predict the travel time of the truck in each section. Then the predicted values of the unit prediction models are accumulated to obtain the travel time predicted value of the truck on in the composite road section. In order to improve the prediction precision, the average velocity of the truck is taken as an influence factor of the travel time. The velocity field is constructed according to the collected velocity information of the truck. The average value of the truck velocity at all points on a road section is calculated, which is approximate to the average velocity of the truck on the road section, and the average velocity is input into the unit prediction model. Based on the data of truck schedule information in truck dispatching system of Yimin Open-pit Mine, the combined prediction model is trained, and the prediction precision and real-time performance of the model are tested. The results show that the combined prediction model of truck travel time in multiple sections of open-pit mine based on velocity field has high prediction precision for truck travel time in composite road sections. The average absolute error percentage is 4.81%, which is more than 2% lower than the single prediction model based on random forest algorithm. The operation time of the combined prediction model is less than 1 s, which can realize the real-time prediction of truck travel time.
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- 2022
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33. Effect of cyclic heat treatment on carbide evolution and impact toughness of 1Cr-0.5Mo steel
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CHEN Guang-xing, ZHANG Yong-wei, XU Xiao-chang, XU Chen, LI Hong-ying, and ZHAO Ming-chun
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1cr-0.5mo steel ,cyclic heat treatment ,pearlite ,carbide ,m23c6 ,Materials of engineering and construction. Mechanics of materials ,TA401-492 - Abstract
The effects of the evolution behavior of carbide on impact toughness of 1Cr-0.5Mo steel during cyclic heat treatment were investigated by quantitative metallographic method and electrolytic extraction method with SEM,XRD,EPMA and low temperature impact test. The results show that with the increasing number of cyclic heat treatment, the lamellar carbides in the pearlite structure dissolve and spheroidize gradually, and the type of carbide also changes: M3C→M23C6. Increasing the number of cyclic heat treatments promotes the precipitation and connection of M23C6 along the grain boundaries, significantly deteriorates the impact toughness of 1Cr-0.5Mo steel.When the number of cyclic heat treatments reaches 4,the M23C6 grows to chain-like at the grain boundary and the impact toughness of 1Cr-0.5Mo steel can no longer meet the requirements. During the cyclic heat treatment, the average equivalent circle diameter of the overall carbide in 1Cr-0.5Mo steel shows a trend of decrease first and then increase because of the dissolution of lamellar carbides and the Ostwald ripening of carbides.
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- 2020
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34. Another treatment option for locally advanced hepatocellular carcinoma: Interventional arterial infusion of FOLFOX chemotherapy from the FOHAIC-1 study
- Author
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Lyu Ning and Zhao Ming
- Subjects
folfox ,arterial chemotherapy ,advanced hepatocellular carcinoma ,Medicine - Abstract
Advanced stage primary hepatocellular carcinoma (HCC) accounts for more than half of all cases worldwide. Poor prognosis is mainly attributed to intrahepatic tumor burden caused by high-risk factors, including Vp4-portal vein tumor thrombosis or tumor occupancy of >50% of the liver. In 2020, the combination of a VEGF/PD-L1 blocker was superior to a single tyrosine kinase inhibitor and associated with a median overall survival of 19.2 months. However, overall survival dramatically declined from 19.2 months to 7.6 months for patients with high-risk factors. In this present study, the FOHAIC-1 trial, interventional hepatic arterial infusion chemotherapy of FOLFOX (HAIC-FO) showed favorable survival outcomes in patients with high-risk advanced HCC. Compared with a tyrosine kinase inhibitor, in the high-risk subgroup, HAIC-FO achieved an overall survival of 10.8 months (vs. 5.7 months, hazard ratio 0.343, 95% confidence interval, 0.219–0.538). This study also observed disease downstaging in 16 (16/130) patients who received HAIC-FO; 15 (93.8%) patients received curative or regional treatments afterward. Therefore, for advanced HCC with localized high-risk factors, the clinical efficacy of HAIC-FO is significant and may be a better option than systemic therapies.
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- 2022
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35. Large Language Model(LLM) assisted End-to-End Network Health Management based on Multi-Scale Semanticization
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Tang, Fengxiao, Wang, Xiaonan, Yuan, Xun, Luo, Linfeng, Zhao, Ming, and Kato, Nei
- Subjects
Computer Science - Networking and Internet Architecture ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Network device and system health management is the foundation of modern network operations and maintenance. Traditional health management methods, relying on expert identification or simple rule-based algorithms, struggle to cope with the dynamic heterogeneous networks (DHNs) environment. Moreover, current state-of-the-art distributed anomaly detection methods, which utilize specific machine learning techniques, lack multi-scale adaptivity for heterogeneous device information, resulting in unsatisfactory diagnostic accuracy for DHNs. In this paper, we develop an LLM-assisted end-to-end intelligent network health management framework. The framework first proposes a Multi-Scale Semanticized Anomaly Detection Model (MSADM), incorporating semantic rule trees with an attention mechanism to address the multi-scale anomaly detection problem in DHNs. Secondly, a chain-of-thought-based large language model is embedded in downstream to adaptively analyze the fault detection results and produce an analysis report with detailed fault information and optimization strategies. Experimental results show that the accuracy of our proposed MSADM for heterogeneous network entity anomaly detection is as high as 91.31\%.
- Published
- 2024
36. The uncertainty of quantum states with respect to the projective measurement
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Zhao, Ming-Jing and Tao, Yuanhong
- Subjects
Quantum Physics - Abstract
The uncertainty relation is a distinctive characteristic of quantum theory. The uncertainty is essentially rooted in quantum states. In this work we regard the uncertainty as an intrinsic property of quantum state and characterize it systematically with respect to given projective measurement. Some basic concepts about uncertainty are reformulated in this context. We prove and get the form of the uncertainty preserving operations. The quantum states with maximal uncertainty are characterized. A universal decomposition of uncertainty into classical uncertainty and quantum uncertainty is provided. Furthermore, a unified and general relation among uncertainty, coherence and coherence of assistance is established. These results are independent of any explicit uncertainty measure. At last, we propose a new uncertainty measure called the geometric uncertainty based on the fidelity and link it with the geometric coherence., Comment: 15 pages
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- 2024
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37. Joint Node Selection and Resource Allocation Optimization for Cooperative Sensing with a Shared Wireless Backhaul
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Chen, Mingxin, Zhao, Ming-Min, Liu, An, Li, Min, and Shi, Qingjiang
- Subjects
Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
In this paper, we consider a cooperative sensing framework in the context of future multi-functional network with both communication and sensing ability, where one base station (BS) serves as a sensing transmitter and several nearby BSs serve as sensing receivers. Each receiver receives the sensing signal reflected by the target and communicates with the fusion center (FC) through a wireless multiple access channel (MAC) for cooperative target localization. To improve the localization performance, we present a hybrid information-signal domain cooperative sensing (HISDCS) design, where each sensing receiver transmits both the estimated time delay/effective reflecting coefficient and the received sensing signal sampled around the estimated time delay to the FC. Then, we propose to minimize the number of channel uses by utilizing an efficient Karhunen-Lo\'eve transformation (KLT) encoding scheme for signal quantization and proper node selection, under the Cram\'er-Rao lower bound (CRLB) constraint and the capacity limits of MAC. A novel matrix-inequality constrained successive convex approximation (MCSCA) algorithm is proposed to optimize the wireless backhaul resource allocation, together with a greedy strategy for node selection. Despite the high non-convexness of the considered problem, we prove that the proposed MCSCA algorithm is able to converge to the set of Karush-Kuhn-Tucker (KKT) solutions of a relaxed problem obtained by relaxing the discrete variables. Besides, a low-complexity quantization bit reallocation algorithm is designed, which does not perform explicit node selection, and is able to harvest most of the performance gain brought by HISDCS. Finally, numerical simulations are presented to show that the proposed HISDCS design is able to significantly outperform the baseline schemes., Comment: 13 pages, 10 figures
- Published
- 2024
38. Enhancing User Interest based on Stream Clustering and Memory Networks in Large-Scale Recommender Systems
- Author
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Liu, Peng, Wang, Nian, Xu, Cong, Zhao, Ming, Wang, Bin, and Ren, Yi
- Subjects
Computer Science - Information Retrieval ,Computer Science - Machine Learning - Abstract
Recommender Systems (RSs) provide personalized recommendation service based on user interest, which are widely used in various platforms. However, there are lots of users with sparse interest due to lacking consumption behaviors, which leads to poor recommendation results for them. This problem is widespread in large-scale RSs and is particularly difficult to address. To solve this problem, we propose a novel solution named User Interest Enhancement (UIE) which enhances user interest including user profile and user history behavior sequences using the enhancement vectors and personalized enhancement vector generated based on stream clustering and memory networks from different perspectives. UIE not only remarkably improves model performance on the users with sparse interest but also significantly enhance model performance on other users. UIE is an end-to-end solution which is easy to be implemented based on ranking model. Moreover, we expand our solution and apply similar methods to long-tail items, which also achieves excellent improvement. Furthermore, we conduct extensive offline and online experiments in a large-scale industrial RS. The results demonstrate that our model outperforms other models remarkably, especially for the users with sparse interest. Until now, UIE has been fully deployed in multiple large-scale RSs and achieved remarkable improvements.
- Published
- 2024
39. A characterization of entangled two-qubit states via partial-transpose-moments
- Author
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Zhang, Lin, Zhao, Ming-Jing, Chen, Lin, Xiang, Hua, and Shen, Yi
- Subjects
Quantum Physics ,Mathematical Physics ,Mathematics - Optimization and Control - Abstract
Although quantum entanglement is an important resource, its characterization is quite challenging. The partial transposition is a common method to detect bipartite entanglement. In this paper, the authors study the partial-transpose(PT)-moments of two-qubit states,and completely describe the whole region, composed of the second and third PT-moments, for all two-qubit states. Furthermore, they determine the accurate region corresponding to all entangled two-qubit states. The states corresponding to those boundary points of the whole region, and to the border lines between separable and entangled states are analyzed. As an application, they characterize the entangled region of PT-moments for the two families of Werner states and Bell-diagonal states. The relations between entanglement and the pairs of PT-moments are revealed from these typical examples. They also numerically plot the whole region of possible PT-moments for all two-qubit X-states, and find that this region is almost the same as the whole region of PT-moments for all two-qubit states. Moreover, they extend their results to detect the entanglement of multiqubit states. By utilizing the PT-moment-based method to characterize the entanglement of the multiqubit states mixed by the GHZ and W states, they propose an operational way of verifying the genuine entanglement in such states., Comment: 31 pages, LaTeX, 9 figures
- Published
- 2024
- Full Text
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40. Uncertainty relation and the constrained quadratic programming
- Author
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Zhang, Lin, Wu, Dade, Zhao, Ming-Jing, and Nan, Hua
- Subjects
Quantum Physics ,Mathematical Physics ,Mathematics - Optimization and Control - Abstract
The uncertainty relation is a fundamental concept in quantum theory, plays a pivotal role in various quantum information processing tasks. In this study, we explore the additive uncertainty relation pertaining to two or more observables, in terms of their variance,by utilizing the generalized Gell-Mann representation in qudit systems. We find that the tight state-independent lower bound of the variance sum can be characterized as a quadratic programming problem with nonlinear constraints in optimization theory. As illustrative examples, we derive analytical solutions for these quadratic programming problems in lower-dimensional systems, which align with the state-independent lower bounds. Additionally, we introduce a numerical algorithm tailored for solving these quadratic programming instances, highlighting its efficiency and accuracy. The advantage of our approach lies in its potential ability to simultaneously achieve the optimal value of the quadratic programming problem with nonlinear constraints but also precisely identify the extremal state where this optimal value is attained. This enables us to establish a tight state-independent lower bound for the sum of variances, and further identify the extremal state at which this lower bound is realized., Comment: 35 pages, LaTeX
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- 2024
- Full Text
- View/download PDF
41. 6G comprehensive intelligence: network operations and optimization based on Large Language Models
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Long, Sifan, Tang, Fengxiao, Li, Yangfan, Tan, Tiao, Jin, Zhengjie, Zhao, Ming, and Kato, Nei
- Subjects
Computer Science - Networking and Internet Architecture - Abstract
The sixth generation mobile communication standard (6G) can promote the development of Industrial Internet and Internet of Things (IoT). To achieve comprehensive intelligent development of the network and provide customers with higher quality personalized services. This paper proposes a network performance optimization and intelligent operation network architecture based on Large Language Model (LLM), aiming to build a comprehensive intelligent 6G network system. The Large Language Model, with more parameters and stronger learning ability, can more accurately capture patterns and features in data, which can achieve more accurate content output and high intelligence and provide strong support for related research such as network data security, privacy protection, and health assessment. This paper also presents the design framework of a network health assessment system based on LLM and focuses on its potential application value, through the case of network health management system, it is fully demonstrated that the 6G intelligent network system based on LLM has important practical significance for the comprehensive realization of intelligence., Comment: 8 pages, 5 figures, 15 preferences
- Published
- 2024
42. An Off-Policy Reinforcement Learning Algorithm Customized for Multi-Task Fusion in Large-Scale Recommender Systems
- Author
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Liu, Peng, Xu, Cong, Zhao, Ming, Zhu, Jiawei, Wang, Bin, and Ren, Yi
- Subjects
Computer Science - Information Retrieval ,Computer Science - Machine Learning - Abstract
As the last critical stage of RSs, Multi-Task Fusion (MTF) is responsible for combining multiple scores outputted by Multi-Task Learning (MTL) into a final score to maximize user satisfaction, which determines the ultimate recommendation results. Recently, to optimize long-term user satisfaction within a recommendation session, Reinforcement Learning (RL) is used for MTF in the industry. However, the off-policy RL algorithms used for MTF so far have the following severe problems: 1) to avoid out-of-distribution (OOD) problem, their constraints are overly strict, which seriously damage their performance; 2) they are unaware of the exploration policy used for producing training data and never interact with real environment, so only suboptimal policy can be learned; 3) the traditional exploration policies are inefficient and hurt user experience. To solve the above problems, we propose a novel method named IntegratedRL-MTF customized for MTF in large-scale RSs. IntegratedRL-MTF integrates off-policy RL model with our online exploration policy to relax overstrict and complicated constraints, which significantly improves its performance. We also design an extremely efficient exploration policy, which eliminates low-value exploration space and focuses on exploring potential high-value state-action pairs. Moreover, we adopt progressive training mode to further enhance our model's performance with the help of our exploration policy. We conduct extensive offline and online experiments in the short video channel of Tencent News. The results demonstrate that our model outperforms other models remarkably. IntegratedRL-MTF has been fully deployed in our RS and other large-scale RSs in Tencent, which have achieved significant improvements.
- Published
- 2024
43. AlN/Si interface engineering to mitigate RF losses in MOCVD grown GaN-on-Si substrates
- Author
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Cardinael, Pieter, Yadav, Sachin, Hahn, Herwig, Zhao, Ming, Banerjee, Sourish, Esfeh, Babak Kazemi, Mauder, Christof, Sullivan, Barry O, Peralagu, Uthayasankaran, Vohra, Anurag, Langer, Robert, Collaert, Nadine, Parvais, Bertrand, and Raskin, Jean-Pierre
- Subjects
Physics - Applied Physics - Abstract
Fabrication of low-RF loss GaN-on-Si HEMT stacks is critical to enable competitive front-end-modules for 5G and 6G applications. The main contribution to RF losses is the interface between the III-N layer and the HR Si wafer, more specifically the AlN/Si interface. At this interface, a parasitic surface conduction layer exists in Si, which decreases the substrate effective resistivity sensed by overlying circuitry below the nominal Si resistivity. However, a clear understanding of this interface with control of the parasitic channel is lacking. In this letter, a detailed physical and electrical description of MOCVD-grown AlN/Si structures is presented. The presence of a $\text{SiC}_\text{x}\text{N}_\text{y}$ interfacial layer is revealed and its importance for RF losses is shown. Through C-V and I-V characterisation, an increase in the C concentration of this interfacial layer is linked to the formation of negative charge at the AlN/Si interface, which counteracts the positive charge present in the 0-predose limit. The variation of TMAl predose is shown to allow precise tuning of the C composition and, consequently, the resulting interface charge. Notably, a linear relationship between predose and net interface charge is observed and confirmed by the fabrication of an AlN/Si sample with close to zero net charge. In addition, a higher $D_{it}$ ($\sim 2\times 10^{12}$ cm$^\text{-2}$) for such compensated samples is observed and can contribute to low RF loss. An exceptionally high effective resistivity of above 8 k$\Omega\cdot$cm is achieved, corresponding to an RF loss below 0.3 dB/mm at 10 GHz., Comment: The following article has been accepted for publication in Applied Physics Letters. After it is published, it will be found at https://pubs.aip.org/aip/apl
- Published
- 2024
44. Towards Practical Requirement Analysis and Verification: A Case Study on Software IP Components in Aerospace Embedded Systems
- Author
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Ma, Zhi, Wen, Cheng, Su, Jie, Zhao, Ming, Yu, Bin, Lu, Xu, and Tian, Cong
- Subjects
Computer Science - Software Engineering - Abstract
IP-based software design is a crucial research field that aims to improve efficiency and reliability by reusing complex software components known as intellectual property (IP) components. To ensure the reusability of these components, particularly in security-sensitive software systems, it is necessary to analyze the requirements and perform formal verification for each IP component. However, converting the requirements of IP components from natural language descriptions to temporal logic and subsequently conducting formal verification demands domain expertise and non-trivial manpower. This paper presents a case study on software IP components derived from aerospace embedded systems, with the objective of automating the requirement analysis and verification process. The study begins by employing Large Language Models to convert unstructured natural language into formal specifications. Subsequently, three distinct verification techniques are employed to ascertain whether the source code meets the extracted temporal logic properties. By doing so, five real-world IP components from the China Academy of Space Technology (CAST) have been successfully verified.
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- 2024
45. Self-Supervised Quantization-Aware Knowledge Distillation
- Author
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Zhao, Kaiqi and Zhao, Ming
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Quantization-aware training (QAT) and Knowledge Distillation (KD) are combined to achieve competitive performance in creating low-bit deep learning models. However, existing works applying KD to QAT require tedious hyper-parameter tuning to balance the weights of different loss terms, assume the availability of labeled training data, and require complex, computationally intensive training procedures for good performance. To address these limitations, this paper proposes a novel Self-Supervised Quantization-Aware Knowledge Distillation (SQAKD) framework. SQAKD first unifies the forward and backward dynamics of various quantization functions, making it flexible for incorporating various QAT works. Then it formulates QAT as a co-optimization problem that simultaneously minimizes the KL-Loss between the full-precision and low-bit models for KD and the discretization error for quantization, without supervision from labels. A comprehensive evaluation shows that SQAKD substantially outperforms the state-of-the-art QAT and KD works for a variety of model architectures. Our code is at: https://github.com/kaiqi123/SQAKD.git.
- Published
- 2024
46. CSI Transfer From Sub-6G to mmWave: Reduced-Overhead Multi-User Hybrid Beamforming
- Author
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Deng, Weicao, Li, Min, Zhao, Ming-Min, Zhao, Min-Jian, and Simeone, Osvaldo
- Subjects
Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Hybrid beamforming is vital in modern wireless systems, especially for massive MIMO and millimeter-wave deployments, offering efficient directional transmission with reduced hardware complexity. However, effective beamforming in multi-user scenarios relies heavily on accurate channel state information, the acquisition of which often incurs excessive pilot overhead, degrading system performance. To address this and inspired by the spatial congruence between sub-6GHz (sub-6G) and mmWave channels, we propose a Sub-6G information Aided Multi-User Hybrid Beamforming (SA-MUHBF) framework, avoiding excessive use of pilots. SA-MUHBF employs a convolutional neural network to predict mmWave beamspace from sub-6G channel estimate, followed by a novel multi-layer graph neural network for analog beam selection and a linear minimum mean-square error algorithm for digital beamforming. Numerical results demonstrate that SA-MUHBF efficiently predicts the mmWave beamspace representation and achieves superior spectrum efficiency over state-of-the-art benchmarks. Moreover, SA-MUHBF demonstrates robust performance across varied sub-6G system configurations and exhibits strong generalization to unseen scenarios., Comment: 13 pages, 12 figures, submitted
- Published
- 2024
47. Semi-Passive Intelligent Reflecting Surface Enabled Sensing Systems
- Author
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Peng, Qiaoyan, Wu, Qingqing, Chen, Wen, Ma, Shaodan, Zhao, Ming-Min, and Dobre, Octavia A.
- Subjects
Electrical Engineering and Systems Science - Signal Processing - Abstract
Intelligent reflecting surface (IRS) has garnered growing interest and attention due to its potential for facilitating and supporting wireless communications and sensing. This paper studies a semi-passive IRS-enabled sensing system, where an IRS consists of both passive reflecting elements and active sensors. Our goal is to minimize the Cram\'{e}r-Rao bound (CRB) for parameter estimation under both point and extended target cases. Towards this goal, we begin by deriving the CRB for the direction-of-arrival (DoA) estimation in closed-form and then theoretically analyze the IRS reflecting elements and sensors allocation design based on the CRB under the point target case with a single-antenna base station (BS). To efficiently solve the corresponding optimization problem for the case with a multi-antenna BS, we propose an efficient algorithm by jointly optimizing the IRS phase shifts and the BS beamformers. Under the extended target case, the CRB for the target response matrix (TRM) estimation is minimized via the optimization of the BS transmit beamformers. Moreover, we explore the influence of various system parameters on the CRB and compare these effects to those observed under the point target case. Simulation results show the effectiveness of the semi-passive IRS and our proposed beamforming design for improving the performance of the sensing system.
- Published
- 2024
48. Time series prediction of open quantum system dynamics
- Author
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Wang, Zhao-Wei and Wang, Zhao-Ming
- Subjects
Quantum Physics - Abstract
Time series prediction (TSP) has been widely used in various fields, such as life sciences and finance, to forecast future trends based on historical data. However, to date, there has been relatively little research conducted on the TSP for quantum physics. In this paper, we explore the potential application of TSP in forecasting the dynamical evolution of open quantum systems. We employ deep learning techniques to train a TSP model and evaluate its performance by comparison with exact solution. We use the ratio of the prediction step length and the sequence length to define short and long-term forecasting. Our results show that the trained model has the ability to effectively capture the inherent characteristics of time series for both short-term and long-term forecasting. Accurate predictions for different coupling intensities and initial states are obtained. Furthermore, we use our method to train another model and find that it can successfully predict the steady state of the system. These findings suggests that TSP is a valuable tool for the prediction of the dynamics in open quantum systems.
- Published
- 2024
49. Mixed-permutation channel with its application to estimate quantum coherence
- Author
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Zhang, Lin and Zhao, Ming-Jing
- Subjects
Quantum Physics - Abstract
Quantum channel, as the information transmitter, is an indispensable tool in quantum information theory. In this paper, we study a class of special quantum channels named the mixed-permutation channels. The properties of these channels are characterized. The mixedpermutation channels can be applied to give a lower bound of quantum coherence with respect to any coherence measure. In particular, the analytical lower bounds for l1-norm coherence and the relative entropy of coherence are shown respectively. The extension to bipartite systems is presented for the actions of the mixed-permutation channels., Comment: 19 pages
- Published
- 2024
- Full Text
- View/download PDF
50. In Vivo and In Vitro Approaches to Modeling Hypoplastic Left Heart Syndrome
- Author
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Alonzo, Matthew, Contreras, Javier, Bering, Jakob, and Zhao, Ming-Tao
- Published
- 2024
- Full Text
- View/download PDF
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