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A Quantitative Process-Based Inventory Study on Material Embodied Carbon Emissions of Residential, Office, and Commercial Buildings in China

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Journal of Thermal Science 2019年第6期28卷 1236-1251页

作者： LUO Zhixing cang Yujie zhang Nan YANG Liu LIU Jiaping State Key Laboratory of Green Building in Western China Xi'an University of Architecture and TechnologyShaanxi 710055China College of Architecture Xi'an University of Architecture and TechnologyShaanxi 710055China

Studies on building carbon emissions focus mainly on the materialization phase of life cycle, as carbon emissions in this stage is intensive and high. This paper proposes a simplified model to calculate embodied carbon emissions in building design stage by conducting a process-based inventory analysis of carbon emissions from materials used in 129 residential buildings, 41 office buildings, and 21 commercial buildings during materialization phase. The results indicate that average carbon emissions per unit area from building materials used in residential buildings, office buildings, and commercial buildings are 514.66 kgCO2 e/m2, 533.69 kg CO2 e/m2 and 494.19 kgCO2 e/m2, respectively. Besides, ten kinds of building materials(namely, steel, commercial concrete, wall building materials, mortar, copper core cables, architectural ceramics, PVC pipes, thermal insulation materials, doors and windows, and water paint) constitute 99% of total carbon emissions in all three types of buildings. These materials are major carbon emissions sources in materialization phase. Thus, embodied carbon emissions can be significantly reduced by limiting the amount of these materials in architectural design as well as by using environmental friendly materials.

关键词： embodied carbon emissions life cycle analysis materialization phase building material

Highly conductive and stable iodine doped argyrodite electrolyte for all-solid-state lithium batteries

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Journal of Energy Chemistry 2025年第1期100卷 50-58页

作者： Gaozhan Liu Jing zhang Jing Yang Jinghui Chen Xingyue Xiao Xiayin Yao Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences

Lithium argyrodites with high ionic conductivity and low cost are considered as one of the most prospective solid electrolytes for all-solid-state lithium ***,the poor chemical stability and compatibility with lithium metal limit their ***,Li5.4PS4.4Cl1.4I0.2solid electrolyte with high ionic conductivity of 11.49 m S cm-1and improved chemical stability is synthesized by iodine *** ultra-thin Li5.4PS4.4Cl1.4I0.2membrane with thickness of 10μm can be obtained by wet coating process,exhibiting a high ionic conductivity of 2.09 mS cm-1and low areal resistance of 1.17Ω***,iodine doping could in-situ form LiI at the lithium/electrolyte interface and improve the critical current density of Li5.4PS4.4Cl1.6from 0.8 to 1.35 mA *** resultant LiCoO2/Li5.4PS4.4Cl1.4I0.2/Li battery shows excellent cycling stability at 1 C,with a reversible specific capacity of 110.1 mA h g-1and a retention of 80.5% after 1000 *** addition,the assembled LiCoO2/Li5.4PS4.4Cl1.4I0.2membrane/Li pouch cell delivers an initial discharge capacity of 110.4 mA h g-1and 80.5% capacity retention after 100 cycles.

关键词： Solid-State Batteries

Novel models for simulating maize growth based on thermal time and photothermal units: Applications under various mulching practices

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Journal of Integrative Agriculture 2023年第5期22卷 1381-1395页

作者： LIAO Zhen-qi ZHENG Jing FAN Jun-liang PEI Sheng-zhao DAI Yu-long zhang fu-cang LI Zhi-jun Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas Ministry of EducationNorthwest A&F UniversityYangling 712100P.R.China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041P.R.China

Maize (Zea mays L.) is one of the three major food crops and an important source of carbohydrates for maintaining food security around the *** height (H),stem diameter (SD),leaf area index (LAI) and dry matter (DM) are important growth parameters that influence maize ***,the combined effect of temperature and light on maize growth is rarely considered in crop growth *** maize growth models based on the modified logistic growth equation (Mlog) and the Mitscherlich growth equation (Mit) were proposed to simulate the H,SD,LAI and DM of maize under different mulching practices based on experimental data from 2015–*** the accumulative growing degree-days (AGDD),helio thermal units (HTU),photothermal units (PTU) or photoperiod thermal units (PPTU,first proposed here) was used as a single driving factor in the models;or AGDD was combined with either accumulative actual solar hours (ASS),accumulative photoperiod response (APR,first proposed here) or accumulative maximum possible sunshine hours (ADL) as the dual driving factors in the *** model performances were evaluated using seven statistical indicators and a global performance *** results showed that the three mulching practices significantly increased the maize growth rates and the maximum values of the growth curves compared with *** the four single factor-driven models,the overall performance of the Mlog_(PTU)Model was the best,followed by the Mlog_(AGDD)*** Mlog_(PPTU)Model was better than the Mlog_(AGDD)Model in simulating SD and *** the 10 models,the overall performance of the Mlog_(AGDD–APR)Model was the best,followed by the Mlog_(AGDD–ASS)***,the Mlog_(AGDD–APR)Model performed the best in simulating H and LAI,while the Mlog_(AGDD–ADL)and Mlog_(AGDD–ASS)models performed the best in simulating SD and DM,*** conclusion,the modified logistic growth equations with AGDD and either APR,ASS or ADL as the dual driving

关键词： thermal time accumulative growing degree-days helio thermal units photothermal units growth model

Wafer‑Scale Ag_(2)S‑Based Memristive Crossbar Arrays with Ultra‑Low Switching‑Energies Reaching Biological Synapses

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Nano-Micro Letters 2025年第3期17卷 328-339页

作者： Yuan Zhu Tomas Nyberg Leif Nyholm Daniel Primetzhofer Xun Shi Zhen zhang Division of Solid‑State Electronics Department of Electrical EngineeringUppsala University75121 UppsalaSweden Department of Chemistry Uppsala UniversityUppsalaSweden Department of Physics and Astronomy Uppsala UniversityUppsalaSweden State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050People’s Republic of China

Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic ***,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMOS)technology still suffer from substantially larger energy consumption than biological synapses,due to the slow kinetics of forming conductive paths inside the memristive *** we report wafer-scale Ag_(2)S-based MCAs realized using CMOS-compatible processes at temperatures below 160℃.Ag_(2)S electrolytes supply highly mobile Ag+ions,and provide the Ag/Ag_(2)S interface with low silver nucleation barrier to form silver filaments at low energy *** further enhancing Ag+migration in Ag_(2)S electrolytes via microstructure modulation,the integrated memristors exhibit a record low threshold of approximately−0.1 V,and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological *** low-temperature process also enables MCA integration on polyimide substrates for applications in flexible ***,the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training *** impressive accuracy of 92.6%in image recognition simulations is demonstrated with the MCAs after the *** demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.

关键词： Wafer-scale Ag_(2)S films Reactive sputter Silver nucleation Ag^(+)migration Energy-efficient neuromorphic computing

Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

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Structural Durability & Health Monitoring 2025年第1期19卷 25-54页

作者： Chao zhang Shang-Xi Lai Hua-Ping Wang School of Civil Engineering and Mechanics Lanzhou UniversityLanzhou730000China Key Laboratory of Special functional Materials and Structural Design Ministry of EducationLanzhou UniversityLanzhou730000China

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the ***,it is particularly signiﬁcant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientiﬁc basis for structural damage identiﬁcation and dynamic model modiﬁ*** view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and brieﬂy describes how to identify structural damages based on the derived modal *** paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),brieﬂy describes damage identiﬁcation methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artiﬁcial intelligence(AI)methods in the direction of modal parameter recognition and damage identiﬁcation is further *** on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identiﬁcation methods are given to provide scientiﬁc references for the optimized design and functional upgrading of SHM systems.

关键词： Structural health monitoring data information modal parameters damage identiﬁcation AI method

DecMamba:Mamba Utilizing Series Decomposition for Multivariate Time Series Forecasting

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Computers, Materials & Continua 2025年第1期82卷 1049-1068页

作者： Jianxin Feng Jianhao zhang Ge Cao Zhiguo Liu Yuanming Ding Communication and Network Key Laboratory Dalian UniversityDalian116622China

Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy *** decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time ***,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between *** problems make it difficult to analyze the intricate temporal variations of real-world time *** this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between *** backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend *** with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.

关键词： Data prediction time series Mamba series decomposition

In situ Investigation on Layer-by-Layer Deposition of Polyelectrolytes by Quartz Crystal Microbalance

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Chinese Journal of Chemical Physics 2008年第3期21卷 291-294页

作者： Yun-fengYan Guang-ming Liu Ye-cang Tang Guang-zhao zhang Department of Chemical Physics University of Science and Technology of China Hefei 230025 China

The effect of salt concentration on layer-by-layer deposition of poly（sodium 4-styrene sulfonate）（PSSS）/poly（vinylbenzyl trimethylammonium chloride）（PVTC） was investigated by use of quartz crystal microbalance with dissipation （QCM-D）. The changes in frequency and dissipation demonstrate that the addition of NaC1 leads the thickness of PSSS/PVTC multilayer to increase. The deposition of PSSS/PVTC is dominated by surface charge overcompensation level at lower salt concentrations. However, it is mainly determined by the interpenetration of polyelectrolytes at a higher salt concentration, as reflected in the oscillation of dissipation change.

关键词： Polyelectrolyte Layer-by-layer deposition Quartz crystal microbalance

Unraveling brain aging through the lens of oral microbiota

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Neural Regeneration Research 2025年第7期20卷 1930-1943页

作者： Qinchao Hu Si Wang Weiqi zhang Jing Qu Guang-Hui Liu State Key Laboratory of Membrane Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Hospital of Stomatology Guanghua School of StomatologyGuangdong Provincial Key Laboratory of StomatologySun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders Xuanwu HospitalCapital Medical UniversityBeijingChina Aging Translational Medicine Center International Center for Aging and CancerBeijing Municipal Geriatric Medical Research CenterXuanwu HospitalCapital Medical UniversityBeijingChina CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijingChina University of Chinese Academy of Sciences BeijingChina Institute for Stem Cell and Regeneration Chinese Academy of SciencesBeijingChina Aging Biomarker Consortium BeijingChina State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Beijing Institute for Stem Cell and Regenerative Medicine BeijingChina

The oral cavity is a complex physiological community encompassing a wide range of *** of oral microbiota can lead to various oral infectious diseases,such as periodontitis and tooth decay,and even affect systemic health,including brain aging and neurodegenerative *** studies have highlighted how oral microbes might be involved in brain aging and neurodegeneration,indicating potential avenues for intervention *** this review,we summarize clinical evidence demonstrating a link between oral microbes/oral infectious diseases and brain aging/neurodegenerative diseases,and dissect potential mechanisms by which oral microbes contribute to brain aging and *** also highlight advances in therapeutic development grounded in the realm of oral microbes,with the goal of advancing brain health and promoting healthy aging.

关键词： Alzheimer's disease brain aging multiple sclerosis neurodegeneration neurodegenerative diseases oral microbiota Parkinson's disease periodontitis bacteria Porphyromonas gingivalis

Early identification of stroke through deep learning with multi-modal human speech and movement data

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Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao Wang Bin zhang Haobang Liang Bei Hu Longlong Ren Yanjuan Liu Yuhu zhang Chengbo Dai Hejun Wu Weifeng Li Xin Li School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke