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Multi-exponential model to describe pressure-dependent P-and S-wave velocities and its use to estimate the crack aspect ratio

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第2期14卷 385-395页

作者： mihály dobróka Norbert Péter Szabó Tünde Edit dobróka Mátyás Krisztián Baracza Department of Geophysics University of MiskolcMiskolc-Egyetemváros3515Hungary MTA-ME Geoengineering Research Group University of MiskolcMiskolc-Egyetemváros3515Hungary Research Institute of Applied Earth Sciences University of MiskolcMiskolc-Egyetemváros3515Hungary

We present new quantitative model describing the pressure dependence of acoustic P-and S-wave velocities.Assuming that a variety of individual mechanisms or defects(such as cracks,pore collapse and grain crushing)can contribute to the pressure-dependent change of the wave velocity,we order a characteristic pressure to all of them and allow a series of exponential terms in the description of the(Pand S-waves)velocity-pressure function.We estimate the parameters of the multi-exponential rock physical model in inversion procedures using laboratory measured P-and S-wave velocity data.As is known,the conventional damped least squares method gives acceptable results only when one or two individual mechanisms are assumed.Increasing the number of exponential terms leads to highly nonlinear ill-posed inverse problem.Due to this reason,we develop the spectral inversion method(SIM)in which the velocity amplitudes(the spectral lines in the characteristic pressure spectrum)are only considered as unknowns.The characteristic pressures(belonging to the velocity amplitudes)are excluded from the set of inversion unknowns,instead,they are defined in a set of fixed positions equidistantly distributed in the actual interval of the independent variable(pressure).Through this novel linear inversion method,we estimate the parameters of the multi-exponential rock physical model using laboratory measured P-and S-wave velocity data.The characteristic pressures are related to the closing pressures of cracks which are described by well-known rock mechanical relationships depending on the aspect ratio of elliptical cracks.This gives the possibility to estimate the aspect ratios in terms of the characteristic pressures.

关键词： Multi-exponential rock physical model Spectral inversion method(SIM) Crack aspect ratio Characteristic pressures

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On the Generalization of Seismic Tomography Algorithms

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American Journal of Computational Mathematics 2014年第1期4卷 37-46页

作者： mihály dobróka Hajnalka Szegedi Department of Geophysics University of Miskolc Miskolc Hungary MTA-ME Applied Geosciences Research Group Miskolc Hungary

The seismic tomography problem often leads to underdetermined and inconsistent system of equations. Solving these problems, care must be taken to keep the propagation of data errors under control. Especially, the non-Gaussian nature of the noise distribution (for example outliers in the data sets) can cause appreciable distortions in the tomographic imaging. In order to reduce the sensitivity to outlier, some generalized tomography algorithms are proposed in the paper. The weighted version of the Conjugate Gradient method is combined with the Iteratively Reweighted Least Squares (IRLS) procedure leading to a robust tomography method (W-CGRAD). The generalized version of the SIRT method is introduced in which the (Cauchy-Steiner) weighted average of the ART corrections is used. The proposed tomography algorithms are tested for a small sized tomography example by using synthetic traveltime data. It is proved that—compared to their traditional versions—the outlier sensitivities of the generalized tomography methods are sufficiently reduced.

关键词： Robust Tomography Conjugated Gradients SIRT Cauchy-Steiner Weights

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Cluster Analysis Assisted Float-Encoded Genetic Algorithm for a More Automated Characterization of Hydrocarbon Reservoirs

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Intelligent Control and Automation 2013年第4期4卷 362-370页

作者： Norbert Péter Szabó mihály dobróka Réka kavanda Department of Geophysics University of Miskolc Miskolc Hungary kavreka@***

A genetic algorithm-based joint inversion method is presented for evaluating hydrocarbon-bearing geological formations. Conventional inversion procedures routinely used in the oil industry perform the inversion processing of borehole geophysical data locally. As having barely more types of data than unknowns in a depth, a set of marginally over-determined inverse problems has to be solved along a borehole, which is a rather noise sensitive procedure. For the reduction of noise effect, the amount of overdetermination must be increased. To fulfill this requirement, we suggest the use of our interval inversion method, which inverts simultaneously all data from a greater depth interval to estimate petrophysical parameters of reservoirs to the same interval. A series expansion based discretization scheme ensures much more data against unknowns that significantly reduces the estimation error of model parameters. The knowledge of reservoir boundaries is also required for reserve calculation. Well logs contain information about layer-thicknesses, but they cannot be extracted by the local inversion approach. We showed earlier that the depth coordinates of layerboundaries can be determined within the interval inversion procedure. The weakness of method is that the output of inversion is highly influenced by arbitrary assumptions made for layer-thicknesses when creating a starting model (i.e. number of layers, search domain of thicknesses). In this study, we apply an automated procedure for the determination of rock interfaces. We perform multidimensional hierarchical cluster analysis on well-logging data before inversion that separates the measuring points of different layers on a lithological basis. As a result, the vertical distribution of clusters furnishes the coordinates of layer-boundaries, which are then used as initial model parameters for the interval inversion procedure. The improved inversion method gives a fast, automatic and objective estimation to layer-boundaries and petrophysical parameters, which is demons

关键词： Hierarchical Cluster Analysis Genetic Algorithm Well-Logging Interval Inversion

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Restimate:Recovery Estimation Tool for Resilience Planning

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Journal of Safety Science and Resilience 2024年第1期5卷 47-63页

作者： Scott Miles Megan ly Nick Terry Youngjun Choe Department of Human Centered Design&Engineering Campus Box 352315University of WashingtonSeattleWA 98195United States of America Department of Industrial&Systems Engineering Box 352650University of WashingtonSeattleWA 98195United States of America

The U.S.National Institute of Standards and Technology(NIST)published the Community Resilience Planning Guide in 2016.The NIST Guide advocates for a participatory process for developing a performance measurement framework for the jurisdiction’s resilience against a scenario hazard.The framework centers around tables of expected and desired recovery times for selected community assets,such as electricity,water,and natural gas infrastructures.The NIST Guide does not provide a method for estimating the expected recovery times.However,building high-fidelity computer models for such estimations requires substantial resources that even larger ju-risdictions cannot cost-justify.The most promising approach to recovery time estimation is to systematically use data elicited from people to tap into the wisdom of the(knowledgeable)crowd.This paper describes a novel research-through-design project to enable the computer-supported elicitation of recovery time series data.This work is the first in the literature to examine people’s ability to estimate recovery curves and how design in-fluences such estimations.Its main contribution to resilience planning is three-fold:development of a new elicitation tool called Restimate,understanding its potential user base,and providing insights into how it can facilitate resilience planning.Restimate is the first tool to enable evidence-based expert elicitation in any community with limited resources for resilience planning.Beyond resilience planning,those who facilitate high-stakes planning activities under large uncertainties(e.g.,mission-critical system design and planning)will benefit from a similar research-through-design process.

关键词： expert elicitation disaster natural hazard infrastructure community resilience restoration user-centered design computer-supported cooperative work

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High-resolution multi-scale air pollution system:Evaluation of modelling performance and emission control strategies

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Journal of Environmental Sciences 2024年第3期137卷 65-81页

作者： Diogo Lopes Joana Ferreira Sandra Rafael ka In Hoi Xin Li Yuan Liu ka-Veng Yuen kai Meng Mok Ana Isabel Miranda Department of Environment and Planning&CESAM University of AveiroAveiroPortugal Department of Civil&Environmental Engineering Faculty of Science and TechnologyUniversity of MacaoMacao SARChina

A high percentage of the world's population lives in areas where air pollutant concentrations exceed the World Health Organization guidelines.This work aims to develop and test,a high-resolution multi-scale air pollution modelling system by integrating a set of adequate tools.This system is able to provide detailed air pollutant concentrations in urban areas and support air quality management strategies through a better identification of different atmospheric processes.It also allows furthering the design and assessment of air pollution control measures for a specific area.To evaluate its performance and suitability,the system was applied to the Macao Special Administrative Region(SAR),China,one of the most densely populated areas on earth,during a winter period when this area is affected by high levels of Particulate Matter(PM).Although the developed system tends to underestimate the PM concentrations,it revealed a good performance in reproducing the temporal and spatial air pollution patterns.Several exceedances of the Chinese air quality standards were calculated and high population exposure to PM pollution was estimated.The tested urban atmospheric emission reduction scenarios have shown air quality improvements,indicating that emission reduction measures at urban level should focus on the domestic sector.However,it is crucial to implement joint pollution prevention strategies with neighbouring regions to improve the air quality in Macao SAR.The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas.

关键词： Urban areas High-resolution emission inventory Particulate matter Population exposure

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and Civil Engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong ly Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Faculty of Civil Engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam Department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of Engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming loop.The surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement devices.The proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential scenarios.To achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training process.The approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical examples.The study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured data.Overall,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally intensive.This approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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Self-assembly of tau fragments as a key pathologic event in tauopathies

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Neural Regeneration Research 2024年第12期19卷 2565-2566页

作者： ly Thi Huong Luu Le Jung Hoon Lee Min Jae Lee Department of Biochemistry and Molecular Biology Seoul National University College of MedicineSeoulKorea

Tau protein is encoded by the microtubuleassociated protein tau(MAPT)gene and stabilizes microtubules in the neurons.Tau has unique biophysical properties that make it both highly water-soluble and positively charged.Although tau is an intrinsically disordered protein lacking defined secondary structures,it can acquire highly organized-sheet structures and stack into a filamentous inclusion such as a paired helical filament(PHF).

关键词： tau pathologic assembly

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Hyper spectral resolution stimulated Raman spectroscopy with amplified fs pulse bursts

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Light(Science & Applications) 2024年第3期13卷 566-576页

作者： Hongtao Hu Tobias Flöry Vinzenz Stummer Audrius Pugzlys Markus Zeiler Xinhua Xie Aleksei Zheltikov Andrius Baltuška Photonics Institute Technische Universität WienGußhausstraße 27-29Vienna A-1040Austria SwissFEL Paul Scherrer InstituteVilligen PSI 5232Switzerland Institute for Quantum Science and Engineering Department of Physics and AstronomyTexas A&M UniversityCollege StationTX 77843USA

We present a novel approach for Stimulated Raman Scattering(SRS)spectroscopy in which a hyper spectral resolution and high-speed spectral acquisition are achieved by employing amplified offset-phase controlled fs-pulse bursts.We investigate the method by solving the coupled non-linear Schrödinger equations and validate it by numerically characterizing SRS in molecular nitrogen as a model compound.The spectral resolution of the method is found to be determined by the inverse product of the number of pulses in the burst and the intraburst pulse separation.The SRS spectrum is obtained through a motion-free scanning of the offset phase that results in a sweep of the Raman-shift frequency.Due to high spectral resolution and fast motion-free scanning the technique is beneficial for a number SRS-based applications such as gas sensing and chemical analysis.

关键词： compound spectral resolution

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Modulation doping of p-type Cu_(12)Sb_(4)S_(13)toward improving thermoelectric performance

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Journal of Materials Science & Technology 2024年第4期171卷 71-79页

作者： Khak Ho Lim Mingquan Li Yu Zhang Yue Wu Qimin Zhou Qingyue Wang Xuan Yang Pingwei Liu Wen-Jun Wang ka Wai Wong ka Ming Ng Yu Liu Andreu Cabot Institute of Zhejiang University-Quzhou Quzhou 324000China College of Chemical and Biological Engineering Zhejiang UniversityHangzhou 310007China School of Chemistry and Chemical Engineering Hefei University of TechnologyHefei 230009China Materials Research Institute The Pennsylvania State UniversityUniversity ParkPA 16802USA Ostia Technologies Limited United Kingdom Department of Chemical and Biological Engineering The Hong Kong University of Science and TechnologyClear Water BayHong KongChina ICREA Pg.Lluis Companys 23Barcelona 08010Spain Catalonia Energy Research Institute-IREC Sant Adria del BesosBarcelona 08930Spain

The commercial viability of thermoelectric(TE)devices relies heavily on two factors:cost reduction and efficiency enhancement.In this study,we first produce p-type Cu_(12)Sb_(4)S_(16-x)(x=0,3,4)using a low-temperature bottom-up approach and demonstrate Cu_(12)Sb_(4)S_(13)to show the best TE performance among the three tested compositions.Subsequently,the TE energy conversion efficiency of Cu_(12)Sb_(4)S_(13)is further enhanced by optimizing its electronic band structure through the incorporation of small amounts of tel-lurium.At an optimal Te content of 5 mol%,more than a twofold increase in the TE figure of merit(zT)is obtained.To gain insight into the mechanism of improvement on the transport properties of the mate-rial,we compare the interphase transport mechanism by incorporating nanodomains of different metals(Ag and Cu)into the Cu_(12)Sb_(4)S_(13)matrix.The improved electrical conductivity obtained with Cu_(12)Sb_(4)S_(13)-Te nanocomposites is attributed to a charge flooding of the Cu_(12)Sb_(4)S_(13)surface.In contrast,excessive down-ward band-bending at the interphases of Ag/Cu metal-semiconductor drastically reduces the electrical conductivity.Besides,a weighted mobility(μw)analysis shows a dominant thermal activation of carri-ers in Cu_(12)Sb_(4)S_(13)-Te nanocomposites.In this material,a strong decrease in lattice thermal conductivity is also found,which is associated with a phonon-carrier scattering mechanism.Our work shows the impor-tance of proper band-engineering in TE nanocomposites to decouple electrical and thermal transport to enhance TE performance,and the efficacy ofμw for electrical and thermal transport analysis.

关键词： Modulation doping Thermoelectric Interphase transport Charge flooding Phonon-carrier scattering

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Functionalized selenium nanoparticles ameliorated acetaminophen-induced hepatotoxicity through synergistically triggering PKCδ/Nrf2 signaling pathway and inhibiting CYP 2E1

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Food Science and Human Wellness 2024年第2期13卷 932-945页

作者： Si Zou Yetao Gong Xiujie Li Yanbin Wu Jinzhong Wu Jianguo Wu ka-Hing Wong College of Pharmacy Fujian University of Traditional Chinese MedicineFuzhou 350122China Research Institute for Future Food The Hong Kong Polytechnic UniversityHong Kong 999077China Department of Food Science and Nutrition The Hong Kong Polytechnic UniversityHong Kong 999077China

Selenium nanoparticles(SeNPs)have been demonstrated potential for use in diseases associated with oxidative stress.Functionalized SeNPs with lower toxicity and higher biocompatibility could bring better therapeutic activity and clinical application value.Herein,this work was conducted to investigate the protective effect of Pleurotus tuber-regium polysaccharide-protein complex funtionnalized SeNPs(PTR-SeNPs)against acetaminophen(APAP)-induced oxidative injure in HepG2 cells and C57BL/6J mouse liver.Further elucidation of the underlying molecular mechanism,in particular their modulation of Nrf2 signaling pathway was also performed.The results showed that PTR-SeNPs could significantly ameliorate APAP-induced oxidative injury as evidenced by a range of biochemical analysis,histopathological examination and immunoblotting study.PTR-SeNPs could hosphorylate and activate PKCδ,depress Keap1,and increase nuclear accumulation of Nrf2,resulting in upregulation of GCLC,GCLM,HO-1 and NQO-1 expression.Besides,PTR-SeNPs suppressed the biotransformation of APAP to generate intracellular ROS through CYP 2E1 inhibition,restoring the mitochondrial morphology.Furthermore,the protective effect of PTR-SeNPs against APAP induced hepatotoxicity was weakened as Nrf2 was depleted in vivo,indicating the pivotal role of Nrf2 signaling pathway in PTR-SeNPs mediated hepatoprotective efficacy.Being a potential hepatic protectant,PTR-SeNPs could serve as a new source of selenium supplement for health-promoting and biomedical applications.

关键词： PTR-SeNPs(polysaccharide-proteincomplex functionalized selenium nanoparticles) Acetaminophen-induced hepatotoxicity Nuclear factor erythroid 2-related factor 2 Cytochrome P450 enzyme 2E1 Mitochondria

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