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Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Bone research 2024年第1期12卷 1-19页

作者： Xiwei Fan Antonia rujia Sun reuben S.e.Young Isaac O.Afara Brett r.Hamilton Louis Jun Ye Ong ross Crawford Indira Prasadam Centre for Biomedical Technologies Queensland University of TechnologyBrisbaneQLDAustralia School of Mechanical Medical&Process EngineeringQueensland University of TechnologyBrisbaneQLDAustralia Central Analytical research Facility Queensland University of TechnologyBrisbaneQLDAustralia Molecular Horizons University of WollongongWollongongNSWAustralia Department of Technical Physics University of Eastern FinlandKuopioFinland School of electrical engineering and Computer Science Faculty of EngineeringArchitecture and Information TechnologyUniversity of QueenslandBrisbaneQLDAustralia Centre for Microscopy and Microanalysis University of QueenslandBrisbaneQLDAustralia The Prince Charles Hospital BrisbaneQLDAustralia

Osteoarthritis(OA)is a debilitating degenerative disease affecting multiple joint tissues,including cartilage,bone,synovium,and adipose *** presents diverse clinical phenotypes and distinct molecular endotypes,including inflammatory,metabolic,mechanical,genetic,and synovial ***,innovative technologies are needed to support the development of effective diagnostic and precision therapeutic *** analysis of bulk OA tissue extracts has limitations due to technical constraints,causing challenges in the differentiation between various physiological and pathological phenotypes in joint *** issue has led to standardization difficulties and hindered the success of clinical *** insights into the spatial variations of the cellular and molecular structures in OA tissues,encompassing DNA,rNA,metabolites,and proteins,as well as their chemical properties,elemental composition,and mechanical attributes,can contribute to a more comprehensive understanding of the disease *** resolved biology enables biologists to investigate cells within the context of their tissue microenvironment,providing a more holistic view of cellular *** advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various-omics lenses,such as genomics,transcriptomics,proteomics,and metabolomics,with spatial *** fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial ***,advanced imaging techniques,including high-resolution microscopy,hyperspectral imaging,and mass spectrometry imaging,enable the visualization and analysis of the spatial distribution of biomolecules,cells,and *** these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease *** review summarizes the rec

关键词： insight Spatial enable

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effect of biochar on the metabolome of soybean seedlings

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Oil Crop Science 2024年第1期9卷 60-68页

作者： Nathalia e.Silva Mariana G.Aguilar Osania e.Ferreira Gleicia M.Paulino Jaqueline C.L.Carvalho Lúcia P.S.Pimenta Alan r.T.Machado Programa de Pos-graduaçao em Ciencias Ambientais Universidade do Estado de Minas GeraisFrutalMinas Gerais38202-436Brazil Departamento de Química Universidade Federal de Minas GeraisMinas GeraisBelo Horizonte31270-901Brazil Departamento de engenharia Aplicada e Tecnologias Ambientais Universidade do Estado de Minas GeraisJoao MonlevadeMinas Gerais35930-314Brazil Departamento de Ciencias exatas Universidade do Estado de Minas GeraisJoao MonlevadeMinas Gerais35930-314Brazil

The use of biochar can have several effects on plant germination,depending on raw material,preparation method and application ***,the molecular mechanisms that lead to those results have yet to be *** aim of this research was to improve the understanding of these mechanisms by characterizing the metabolic effects of sugarcane bagasse biochar on soybean *** types of biochars were prepared by pyrolysis at 300℃(SCB300),400℃(SCB400)and 600℃(SCB600).Then,each one was mixed into sand at 1%,3%,5%(w/w)dose,*** experiment was performed in 8 days of incubation,when the number of germinated seeds and the average radicle length were *** evaluate the metabolome,the dry biomass(DB)was subjected to extraction with a mixture of methanol-d4 and D2O(1:1 v/v).The extracts were submitted to metabolomics analysis by Proton Nuclear Magnetic *** relative Germination,relative Average radicle Growth and Germination Index increased in all treatments compared to *** the other hand,the DB increased in all treatments,except for SCB300,at doses of 1%and 3%w/*** metabolites(alanine,asparagine,acetic acid,citric acid,glycerol,fatty acids and sucrose)were identified and quantified in DB extracts as the most influential finding for the separation of *** together,these results strongly suggested that biochars accelerated the catabolism of triacylglycerols to sucrose and induced a slight osmotic stress.

关键词： Germination Metabolomics 1H NMr Pyrolysis Sugarcane bagasse

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Quantitative Mapping of Transient Thermodynamic States in Ultrafast Laser Nanostructuring of Quartz

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Ultrafast Science 2024年第2期4卷 9-18页

作者： H.D.Nguyen A.Tsaturyan S.Sao Joao r.Dwivedi A.Melkonyan C.D’Amico e.Kachan J.P.Colombier G.Kermouche r.Stoian Laboratoire Hubert Curien UMR 5516 CNRSUniversite Jean Monnet42000 Saint EtienneFrance Laboratoire George Friedel UMR 5307 CNRSEcole des Mines de Saint Etienne42000 Saint EtienneFrance

Understanding material structural reaction to light is of utmost importance to advance processing resolution in ultrafast laser volume structuring into the *** thermodynamic pathways are required to quench energy transport in the most rapid manner and to confine the process to nanometer lengths,bypassing optical *** material dynamics under confinement,with in situ access to transient local temperature and density parameters,thus becomes key in understanding the *** report in situ reconstruction of thermodynamic states over the entire matter relaxation path in bulkα-quartz irradiated by ultrafast nondiffractive laser beams using time-resolved qualitative and quantitative optical phase *** dynamics indicate rapid spatially confined crystalline-to-amorphous transition to a hot dense fused silica *** exceeds 20%and the matrix temperature rises to more than 2,000 K in the first *** structural state relaxes in hundreds of *** dispersion and time design of the optical beam to picosecond durations increases the spatial confinement and triggers an extreme nanostructuring process based on nanocavitation that occurs within the amorphizing material,where the low-viscosity phase lowers the mechanical requirements for the *** feature scales of less than a tenth of the optical wavelength are obtained in the *** allows for structural and morphological nanoscale material features under 3D confinement that can engineer optical materials.

关键词： Quartz hundreds qualitative

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A brief history of the Compendium of Physical Activities

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Journal of Sport and Health Science 2024年第1期13卷 3-5页

作者： Barbara e.Ainsworth Stephen D.Herrmann David r.Jacobs Jr. Melicia C.Whitt-Glover Catrine Tudor-Locke School of exercise and Health Shanghai University of SportShanghai 200438China College of Health Solutions Arizona State UniversityPhoenixAZ 85003USA Kansas Center for Metabolism and Obesity research University of Kansas Medical CenterKansas CityKS 66160USA Division of epidemiology and Community Health University of MinnesotaMinneapolisMN 55455USA Gramercy research Group KnightdaleNC 27545USA College of Health and Human Services University of North Carolina at CharlotteCharlotteNC 28223USA

The Compendium of Physical Activities(Compendium)was developed to address consistent assignment of physical activity(PA)intensity values used in PA epidemiology research of the association between PA and health outcomes.1The known protective effects of PA on incident health outcomes traces to the mid-1900s,with over 50 studies examining coronary heart disease(CHD)as the outcome of interest.

关键词： epidemiology Activities protective

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Self-Triggered Set Stabilization of Boolean Control Networks and Its Applications

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Ieee/CAA Journal of Automatica Sinica 2024年第7期11卷 1631-1642页

作者： rong Zhao Jun-e Feng Dawei Zhang the School of Mathematics Shandong UniversityShandong UniversityJinan 250100China

Set stabilization is one of the essential problems in engineering systems, and self-triggered control(STC) can save the storage space for interactive information, and can be successfully applied in networked control systems with limited communication resources. In this study, the set stabilization problem and STC design of Boolean control networks are investigated via the semi-tensor product technique. On the one hand, the largest control invariant subset is calculated in terms of the strongly connected components of the state transition graph, by which a graph-theoretical condition for set stabilization is derived. On the other hand, a characteristic function is exploited to determine the triggering mechanism and feasible controls. Based on this, the minimum-time and minimum-triggering open-loop, state-feedback and output-feedback STCs for set stabilization are designed,respectively. As classic applications of self-triggered set stabilization, self-triggered synchronization, self-triggered output tracking and self-triggered output regulation are discussed as well. Additionally, several practical examples are given to illustrate the effectiveness of theoretical results.

关键词： Boolean control networks(BCNs) output regulation self-triggered control semi-tensor product of matrices set stabilization synchronization

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Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

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Applied Mathematics and Mechanics(english edition) 2024年第4期45卷 633-648页

作者： e.GHAVANLOO S.eL-BOrGI School of Mechanical engineering Shiraz UniversityShiraz 71963-16548Iran Mechanical engineering Program Texas A&M University at QatarDoha 23874Qatar

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed *** developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a *** inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed ***,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed *** discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization *** subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed *** novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed ***,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum *** parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

关键词： nonlinear mass-spring chain discrete model continuum model LindstedtPoincare method(LPM) method of multiple scales(MMS) dispersion phase velocity

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Annual variation of adult survival of a south-temperate House Wren population in Argentina

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Avian research 2024年第2期15卷 229-237页

作者： Gustavo J.Fernandez Mariana e.Carro Paulo e.Llambías Grupo de Investigacion en ecofisiología de Fauna Silvestre INIBIOMA-CONICETAsentamiento Universitario San Martín de los Andes(AUSMA)Universidad Nacional Del ComahuePasaje de la Paz 235(8370)San Martín de los AndesNeuquenArgentina Grupo de Investigacion de Biología de Aves IADIZA CCT-MendozaUniversidad Nacional de CuyoAvenida RuizLeal s/n Parque General San Martin5500MendozaArgentina

Identifying factors affecting the survival of individuals is essential for understanding the evolution of life-history traits and population *** numerous studies on this subject in north-temperate environments,there is a lack of equivalent studies at similar latitudes in the ***,we used a 14-year dataset of capture,banding,and resighting to estimate the annual variation in the apparent adult survival probability of a south-temperate population of House Wrens(Troglodytes aedon bonariae).We evaluated temporal variation in sur-vival and the effect of environmental(climatic)and demographic variables(adult abundance,total number of fledglings produced during each breeding season)on survival *** found that the probability of adult survival decreased as the abundance of breeding adults *** density-dependent effect could be related to the resident lifestyle of southern House Wrens,which could determine an intense competition for territories and resources that ultimately would affect their survival.

关键词： Annual variation CJS Density-dependence Survival Troglodytes aedon bonariae

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An efficient Long Short-TermMemory and Gated recurrent Unit Based Smart Vessel Trajectory Prediction Using Automatic Identification System Data

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Computers, Materials and Continua 2024年第1期81卷 1789-1808页

作者： Zaman U. Khan J. Lee e. Hussain S. Balobaid A.S. Aburasain r.Y. Kim K. Department of Computer engineering Chungnam National University Daejeon 34134 South Korea Department of environmental IT engineering Chungnam National University Daejeon 34134 South Korea Autonomous Ship research Center Samsung Heavy Industries Daejeon 34051 South Korea ICArOS Center (PrISMA Lab) University of Naples Federico II Naples 80131 Italy Department of Computer Science College of Computer Science and Information Technology Jazan University Jazan 45142 Saudi Arabia

Maritime transportation, a cornerstone of global trade, faces increasing safety challenges due to growing sea traffic volumes. This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System (AIS) data and advanced deep learning models, including Long Short-Term Memory (LSTM), Gated recurrent Unit (GrU), Bidirectional LSTM (DBLSTM), Simple recurrent Neural Network (SimplerNN), and Kalman Filtering. The research implemented rigorous AIS data preprocessing, encompassing record deduplication, noise elimination, stationary simplification, and removal of insignificant trajectories. Models were trained using key navigational parameters: latitude, longitude, speed, and heading. Spatiotemporal aware processing through trajectory segmentation and topological data analysis (TDA)was employed to capture dynamic *** using a three-month AIS dataset demonstrated significant improvements in prediction accuracy. The GrU model exhibited superior performance, achieving training losses of 0.0020 (Mean Squared error, MSe) and 0.0334 (Mean Absolute error, MAe), with validation losses of 0.0708 (MSe) and 0.1720 (MAe). The LSTM model showed comparable efficacy, with training losses of 0.0011 (MSe) and 0.0258 (MAe), and validation losses of 0.2290 (MSe) and 0.2652 (MAe). Both models demonstrated reductions in training and validation losses, measured by MAe, MSe, Average Displacement error (ADe), and Final Displacement error (FDe). This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions, contributing significantly to the development of robust, intelligent navigation systems for the maritime industry. © 2024 The Authors. Published by Tech Science Press.

关键词： AIS data deep learning GrU LSTM smart vessel Trajectory prediction

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Graphene-calcium carbonate coating to improve the degradation resistance and mechanical integrity of a biodegradable implant

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Journal of Magnesium and Alloys 2024年第1期12卷 394-404页

作者： Lokesh Choudhary Parama Chakraborty Banerjee r.K.Singh raman Derrek e.Lobo Christopher D.easton Mainak Majumder Frank Witte Jörg F.Löffler Department of Mechanical and Aerospace engineering Monash UniversityClayton CampusMelbourneVIC 3800Australia Department of Chemical and Biological engineering Monash UniversityClayton CampusMelbourneVIC 3800Australia Nanoscale Science and engineering Laboratory(NSeL) Bldg 37Monash UniversityClayton CampusMelbourneVIC 3800Australia CSIrO Materials Science and engineering Bayview AvenueClaytonVIC 3168Australia Julius Wolff Institute and Berlin Brandenburg Center for regenerative Therapies Charité–Universitätsmedizin BerlinAugustenburger Platz 113353 BerlinGermany Laboratory of Metal Physics and Technology Department of MaterialsETH Zurich8093 ZurichSwitzerland

Biodegradable implants are critical for regenerative orthopaedic procedures,but they may suffer from too fast corrosion in human-body *** necessitates the synthesis of a suitable coating that may improve the corrosion resistance of these implants without compromising their mechanical *** this study,an AZ91 magnesium alloy,as a representative for a biodegradable Mg implant material,was modified with a thin reduced graphene oxide(rGO)-calcium carbonate(CaCO_(3))composite *** analytical and in-vitro electrochemical characterization reveals that this coating significantly improves the corrosion resistance and mechanical integrity,and thus has the potential to greatly extend the related application field.

关键词： Graphene coating Biodegradable implant Hydroxyapatite Corrosion Magnesium alloy

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.e.Al-Atroush A.e.Aboelela ezz el-Din Hemdan Civil and environmental engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and Materials research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(rVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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