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Association between serum estradiol level and appendicular lean mass index in middle-aged postmenopausal women

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World Journal of Orthopedics 2024年第1期15卷 45-51页

作者： Fang Jin yan-Fei Wang Zhong-Xin zhu Department of Osteoporosis Care and Control Xiaoshan Affiliated Hospital of Wenzhou Medical UniversityHangzhou 311200Zhejiang ProvinceChina

BACKGROUND Previous studies investigating the association between loss of estrogen at menopause and skeletal muscle mass came to contradictory conclusions.AIM To evaluate the association between serum estradiol level and appendicular lean mass index in middle-aged postmenopausal women using population-based data.METHODS This study included 673 postmenopausal women,aged 40-59 years,from the National Health and Nutrition Examination Survey between 2013 and 2016.Weighted multivariable linear regression models were used to evaluate the association between serum E2 Level and appendicular lean mass index(ALMI).When non-linear associations were found by using weighted generalized additive model and smooth curve fitting,two-piecewise linear regression models were further applied to examine the threshold effects.RESULTS There was a positive association between serum E2 level and ALMI.Compared to individuals in quartile 1 group,those in other quartiles had higher ALMI levels.An inverted U-shaped curve relationship between serum E2 Level and ALMI was found on performing weighted generalized additive model and smooth curve fitting,and the inflection point was identified as a serum E2 level of 85 pg/mL.CONCLUSION Our results demonstrated an inverted U-shaped curve relationship between serum E2 levels and ALMI in middle-aged postmenopausal women,suggesting that low serum E2 levels play an important in the loss of muscle mass in middleaged postmenopausal women.

关键词： Estradiol Skeletal muscle Menopause Health The National Health and Nutrition Examination Survey

Poly(3-hexylthio) thiophene Field-effect Transistor Device Performance: Impact of the Content of Hexylthio Side Chain on Backbone

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Chinese Journal of Polymer Science 2024年第1期42卷 14-23,I0005页

作者： Hao-Yu Liu Lian-He Han Ling-Wei Kong Li-ping zhu Xiao-Lan Qiao Mei-Fang zhu State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Regioregular poly(3-hexylthio)thiopene(P3HTT) has emerged tremendous potential in organic electronic applications due to the strong noncovalent interactions from the sulfur atom linked to thiophene. However, P3HTT generally exhibits low charge mobility mostly due to poor solution processability attributed to dense arrangement of hexylthio side chain in polymer, which led to strong noncovalent interactions among sulfur atoms. To balance the nonvalent interaction and aggregation for P3HTT, herein, we systematically study the effect of hexylthio side chain content in polymer backbone on the structure and properties. A series of regioregular P3HTT-based homopolymers(P3HTT, P3HTT-50,P3HTT-33 and P3HTT-25) were prepared via Kumada catalyst transfer polycondensation method from a set of mono-, bi-, ter-and quarterthiophenes containing different contents of hexylthio side chain. The DFT calculation shows the planarity of polymers backbone could be improved through reducing the density of hexylthio side chain in polymer mainchain. And significant changes in their crystallinity, aggregation and optical properties were observed with the content of hexylthio side chain reducing. The P3HTT-33 displayed the highest field-effect transistor hole mobility of 2.83×10^(-2) cm^(2)·V^(-1)·s^(-1) resulting from a balance between the crystallinity and planarity. This study demonstrates modulating the content of hexylthio side chain in P3HTT is an effective strategy to optimize the opto-electronic properties of polymer obtaining excellent semiconductor device performance.

关键词： Conjugated polymer Polythiophene Noncovalent interaction Molecular aggregation Organic field-effect transistor

Crystallization characteristics of iron-rich glass ceramics prepared from nickel slag and blast furnace slag

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International Journal of Minerals,Metallurgy and Materials 2011年第4期18卷 455-459页

作者： Zhong-jie Wang Wen Ni Ke-qing Li Xiao-yan Huang Li-ping zhu School of Civil and Environmental Engineering University of Science and Technology Beijing Beijing 100083 China

The crystallization process of iron-rich glass-ceramics prepared from the mixture of nickel slag（NS） and blast furnace slag（BFS） with a small amount of quartz sand was investigated.A modified melting method which was more energy-saving than the traditional methods was used to control the crystallization process.The results show that the iron-rich system has much lower melting temperature,glass transition temperature（Tg）,and glass crystallization temperature（Tc）,which can result in a further energy-saving process.The results also show that the system has a quick but controllable crystallization process with its peak crystallization temperature at 918°C.The crystallization of augite crystals begins from the edge of the sample and invades into the whole sample.The crystallization process can be completed in a few minutes.A distinct boundary between the crystallized part and the non-crystallized part exists during the process.In the non-crystallized part showing a black colour,some sphere-shaped augite crystals already exist in the glass matrix before samples are heated to Tc.In the crystallized part showing a khaki colour,a compact structure is formed by augite crystals.

关键词： glass ceramics grain growth crystallization slag

Solving the subset sum problem by the quantum Ising model with variational quantum optimization based on conditional values at risk

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Science China(Physics,Mechanics & Astronomy) 2024年第8期Mechanics & Astronomy) .卷 47-59页

作者： Qilin Zheng Miaomiao Yu pingyu zhu yan Wang Weihong Luo ping Xu Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense Technology Hefei National Laboratory

The subset sum problem is a combinatorial optimization problem, and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete) class. This problem is widely used in encryption, planning or scheduling, and integer partitions.An accurate search algorithm with polynomial time complexity has not been found, which makes it challenging to be solved on classical computers. To effectively solve this problem, we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at risk. The proposed model needs only n qubits to encode 2ndimensional search space, which can effectively save the encoding quantum resources. The model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise, and it is convenient to be deployed in the Noisy Intermediate Scale Quantum era. We investigate the effects of the scalability, the variational ansatz type, the variational depth, and noise on the model. Moreover, we also discuss the performance of the model under different conditional values at risk. Through computer simulation, the scale can reach more than nine qubits. By selecting the noise type,we construct simulators with different QVs and study the performance of the model with them. In addition, we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum problem. This model provides a new perspective for solving the subset sum problem.

关键词： subset sum problem quantum Ising model conditional values at risk variational quantum optimization

Reconfigurable memlogic long wave infrared sensing with superconductors

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Light(Science & Applications) 2024年第5期13卷 908-920页

作者： Bingxin Chen Huanyi Xue Hong Pan Liping zhu Xiaomi yan Jingzhe Wang yanru Song Zhenghua An State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Department of PhysicsFudan UniversityShanghai 200438China. ShanghaiTech Quantum Device Lab ShanghaiTech UniversityShanghai 201210China. Shanghai Qi Zhi Institute 41th FloorAI TowerNo.701 Yunjin RoadXuhui DistrictShanghai 200232China. Yiwu Research Institute of Fudan University Chengbei RoadYiwu City 322000 ZhejiangChina. Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China

Optical sensors with in-cell logic and memory capabilities offer new horizons in realizing machine vision beyond von Neumann architectures and have been attempted with two-dimensional materials,memristive oxides,phasechanging materials etc.Noting the unparalleled performance of superconductors with both quantum-limited optical sensitivities and ultra-wide spectrum coverage,here we report a superconducting memlogic long-wave infrared sensor based on the bistability in hysteretic superconductor-normal phase transition.Driven cooperatively by electrical and optical pulses,the device offers deterministic in-sensor switching between resistive and superconducting(hence dissipationless)states with persistence>105 s.This results in a resilient reconfigurable memlogic system applicable for,e.g.,encrypted communications.Besides,a high infrared sensitivity at 12.2μm is achieved through its in-situ metamaterial perfect absorber design.Our work opens the avenue to realize all-in-one superconducting memlogic sensors,surpassing biological retina capabilities in both sensitivity and wavelength,and presents a groundbreaking opportunity to integrate visional perception capabilities into superconductor-based intelligent quantum machines.

关键词： wave superconductor quantum

Machine learning assisted adsorption performance evaluation of biochar on heavy metal

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 29-42页

作者： Qiannan Duan Pengwei yan Yichen Feng Qianru Wan Xiaoli zhu Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity College of Urban and Environmental SciencesNorthwest UniversityXi’an710127China Department of Environment Science Shaanxi Normal UniversityXi’an710062China

Heavy metals(HMs)represent pervasive and highly toxic environmental pollutants,known for their long latency periods and high toxicity levels,which pose significant challenges for their removal and degradation.Therefore,the removal of heavy metals from the environment is crucial to ensure the water safety.Biochar materials,known for their intricate pore structures and abundant oxygen-containing functional groups,are frequently harnessed for their effectiveness in mitigating heavy metal contamination.However,conventional tests for optimizing biochar synthesis and assessing their heavy metal adsorption capabilities can be both costly and tedious.To address this challenge,this paper proposes a data-driven machine learning(ML)approach to identify the optimal biochar preparation and adsorption reaction conditions,with the ultimate goal of maximizing their adsorption capacity.By utilizing a data set comprising 476 instances of heavy metal absorption by biochar,seven classical integrated models and one stacking model were trained to rapidly predict the efficiency of heavy metal adsorption by biochar.These predictions were based on diverse physicochemical properties of biochar and the specific adsorption reaction conditions.The results demonstrate that the stacking model,which integrates multiple algorithms,allows for training with fewer samples to achieve higher prediction accuracy and improved generalization ability.

关键词： Machine learning Biochar Heavy metal Adsorption efficiency

Generation and regulation of electromagnetic pulses generated by femtosecond lasers interacting with multitargets

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Nuclear Science and Techniques 2024年第1期35卷 96-107页

作者： Ya-Dong Xia De-Feng Kong Qiang-You He Zhen Guo Dong-Jun Zhang Tong yang Hao Cheng Yu-Ze Li yang yan Xiao Liang ping zhu Xing-Long Xie Jian-Qiang zhu Ting-Shuai Li Chen Lin Wen-Jun Ma Xue-Qing yan State Key Laboratory of Nuclear Physics and Technology and Key Laboratory of HEDP of the Ministry of EducationCAPTPeking UniversityBeijing 100871China Beijing Laser Acceleration Innovation Center Beijing 101407China Institute of Guangdong Laser Plasma Technology Guangzhou 510540China National Laboratory on High Power Laser and Physics Shanghai Institute of Optics and FineChinese Academy of SciencesShanghai 201800China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 611731China

Ultrashort and powerful laser interactions with a target generate intense wideband electromagnetic pulses(EMPs).In this study,we report EMPs generated by the interactions between petawatt(30 fs,1.4×10^(20) W/cm^(2))femtosecond(fs)lasers with metal flat,plastic flat,and plastic nanowire-array(NWA)targets.Detailed analyses are conducted on the EMPs in terms of their spatial distribution,time and frequency domains,radiation energy,and protection.The results indicate that EMPs from metal targets exhibit larger amplitudes at varying angles than those generated by other types of targets and are enhanced significantly for NWA targets.Using a plastic target holder and increasing the laser focal spot can significantly decrease the radiation energy of the EMPs.Moreover,the composite shielding materials indicate an effective shielding effect against EMPs.The simulation results show that the NWA targets exert a collimating effect on thermal electrons,which directly affects the distribution of EMPs.This study provides guidance for regulating EMPs by controlling the laser focal spot,target parameters,and target rod material and is beneficial for electromagnetic-shielding design.

关键词： Electromagnetic pulses Laser plasma interaction Electromagnetic shielding Electron distribution

A Disulfide-Based Poly(ether-b-amide)Copolymer with Rapid Self-healing Ability under Moderate

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Chinese Journal of Chemistry 2024年第9期42卷 943-950页

作者： Weijan Lu ping zhu Ying Zhao Dujin Wang Xia Dong Institute of Chemistry Chinese Academy of SciencesBeijing 100190China Schoolof Chemical Sciences University of Chinese Academy of SciencesBejing 100049China

Comprehensive Summary A disulfide-based poly(ether-b-amide)copolymer with rapid self-healing capability under moderate conditions was synthesized from 4,4’-dithiodibutyric acid(DTDBA),isophorondiamine(IPDA)and poly(tetramethylene oxide)(PTMO)based on a two-step method.The incorporation of IPDA with asymmetric structure and substantial steric hindrance not only effectively decreased the number of regular H-bonds,but also inhibited the crystallization of polyamide segments,imparting the synthesized poly(ether-b-amide)copolymer with an amorphous structural feature.Based on the coordination of segmental diffusion and recombination of disulfide bonds and hydrogen bonds,the scratches and damaged mechanical properties of PEBADS-I611 could be completely self-healed after healing at 40°C for only 11 min and 3 h,respectively.

关键词： Poly(ether-b-amide)copolymer Disulfide bonds Hydrogen bonds Polycondensation Smart polymers Self-healing

Estimating the optimal vegetation coverage for the dominant tree and shrub species over China's northwest drylands

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Science China Earth Sciences 2024年第5期67卷 1500-1517页

作者： Zhongdian ZHANG Xiaoxu JIA ping zhu Mingbin HUANG Lidong REN Ming’an SHAO School of Geographic Sciences Xinyang Normal UniversityXinyang 464000China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100190China Yellow River Delta Modern Agricultural Engineering Laboratory Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water ConservationNorthwest A&F UniversityYangling 712100China

Anthropogenic revegetation is an effective way to control soil erosion and restore degraded ecosystems in China's northwest drylands(NWD).However,excessive vegetation cover expansion has long been known to increase evapotranspiration,leading to reduced local water availability,which can in turn threaten the health and services of restored ecosystems.Determining the optimal vegetation coverage(OVC)is critical for balancing the trade-off between plant growth and water consumption in water-stressed areas,yet quantitative assessments over the entire NWD are still lacking.In this study,a modified Biome BioGeochemical Cycles(Biome-BGC)model was used to simulate the long-term(1961–2020)dynamics of actual evapotranspiration(ET_(a)),net primary productivity(NPP),and leaf area index(LAI)for the dominant non-native tree(R.pseudoacacia and P.sylvestris)and shrub(C.korshinkii and H.rhamnoides)species at 246 meteorological sites over NWD.The modified model incorporated the Richards equation to simulate transient unsaturated water flow in a multilayer soil module,and both soil and eco-physiological parameters required by the model were validated using field-observed ETadata for each species.Spatial distributions of OVC(given by the mean maximum LAI,LAI_(max))for the dominant species were determined within three hydrogeomorphic sub-areas(i.e.,the loess hilly-gully sub-area,the windy and sandy sub-area,and the desert sub-area).The modified Biome-BGC model performed well in terms of simulating ET_(a) dynamics for the four plant species.Spatial distributions of mean ET_a,NPP,and LAI_(max)generally exhibited patterns similar to mean annual precipitation(MAP).In the loess hilly-gully sub-area(MAP:210 to 710 mm),the OVC respectively ranged from 1.7 to 2.9 and 0.8 to 2.9 for R.pseudoacacia and H.rhamnoides.In the windy and sandy sub-area(MAP:135 to 500 mm),the OVC ranged from 0.3 to 3.3,0.5 to 2.6 and 0.6 to 2.1for P.sylvestris,C.korshinkii and H.rhamnoides,respectively.In the desert sub-area(MAP:90 to 500 mm),the OVC ranged from 0.4 t

关键词： Optimal vegetation coverage Water balance Leaf area index Biome-BGC model Dryland