Linking PHYTOCHROME-INTERACTING FACTOR to Histone Modification in Plant Shade Avoidance

Shade avoidance syndrome (SAS) allows a plant grown in a densely populated environment to maximize opportunities to access to sunlight. Although it is well established that SAS is accompanied by gene expression changes, the underlying molecular mechanism needs to be elucidated. Here, we identify the H3K4me3/H3K36me3-binding proteins, Morf Related Gene (MRG) group proteins MRG1 and MRG2, as positive regulators of shade-induced hypocotyl elongation in Arabidopsis (Arabidopsis thaliana). MRG2 binds PHYTOCHROME-INTERACTING FACTOR7 (PIF7) and regulates the expression of several common downstream target genes, including YUCCA8 and IAA19 involved in the auxin biosynthesis or response pathway and PRE1 involved in brassinosteroid regulation of cell elongation. In response to shade, PIF7 and MRG2 are enriched at the promoter and gene-body regions and are necessary for increase of histone H4 and H3 acetylation to promote target gene expression. Our study uncovers a mechanism in which the shade-responsive factor PIF7 recruits MRG1/MRG2 that binds H3K4me3/H3K36me3 and brings histone-acetylases to induce histone acetylations to promote expression of shade responsive genes, providing thus a molecular mechanistic link coupling the environmental light to epigenetic modification in regulation of hypocotyl elongation in plant SAS

Establishing thresholds of handgrip strength based on mortality using machine learning in a prospective cohort of Chinese population

BackgroundThe relative prognostic importance of handgrip strength (HGS) in comparison with other risk factors for mortality remains to be further clarified, and thresholds used for best identify high-risk individuals in health screening are not yet established. Using machine learning and nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), the study aimed to investigate the prognostic importance of HGS and establish sex-specific thresholds for health screening.MethodsA total of 6,762 participants from CHARLS were enrolled. A random forest model was built using 30 variables with all-cause mortality as outcome. SHapley Additive exPlanation values were applied to explain the model. Cox proportional hazard models and Harrell’s C index change were used to validate the clinical importance of the thresholds.ResultsAmong the participants, 3,102 (45.9%) were men, and 622 (9.1%) case of death were documented follow-up period of 6.78 years. The random forest model identified HGS as the fifth important prognostic variable, with thresholds for identifying high-risk individuals were < 32 kg in men and < 19 kg in women. Low HGS were associated with all-cause mortality [HR (95% CI): 1.77 (1.49–2.11), p < 0.001]. The addition of HGS thresholds improved the predictive ability of an established office-based risk score (C-index change: 0.022, p < 0.001).ConclusionOn the basis of our thresholds, low HGS predicted all-cause mortality better than other risk factors and improved prediction of a traditional office-based risk score. These results reinforced the clinical utility of measurement of HGS in health screening

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Deep exploration of street view features for identifying urban vitality: A case study of Qingdao city

Urban vitality has significant practical implications for urban management and planning. In this study, we propose a comprehensive research framework that combines street scene images, point of interest (POI) data, road network data, and residential land data, and employs deep learning algorithms to explore the characteristics and influencing factors of urban vitality from a social perception perspective. By designing multi-scale semantic segmentation models, emotion perception models, and street perception models, we deeply explore the street features of the city. At the block level, we use weighted calculation methods to quantify urban vitality by combining POI data and residential land data, accurately characterizing the city. Finally, we analyze the driving factors of urban vitality using random forest and SHAP methods. The research results show that Chengyang District and Laoshan District have advantages in visual perception, while Shibei District and Shinan District exhibit advantages in urban vitality. The overall urban vitality in the main urban area of Qingdao City is low, with high scores in emotion perception and visual perception, but low scores in transportation accessibility and facility convenience. Visual perception factors play a significant role in urban vitality, highlighting the importance of urban street beautification and humanized design in economic development and environmental construction. The analytical results of this study contribute to optimizing urban spatial features and provide references for urban planning and construction

Tenue des structures en fatigue multiaxiale : prise en compte des variations de chargement en temps et en espace

The aim of this work is to propose a multi-scale approach to energy-based fatigue, which can estimate lifetimes associated with variable multidimensional loading. The foundation of the approach is to assume that the energy dissipated on a small scale governs the fatigue behavior. Each material point is associated to a stochastic distribution of weak points that are likely to plasticize and contribute to the dissipation of energy without affecting global macroscopic stresses. This amounts to adopting Dang Van's paradigm of high cycle fatigue. The structure is supposed to be elastic (or adapted) on a macroscopic scale. In addition, we adopt on the mesoscopic scale an elastoplastic behavior with a dependence of the plastic load function not only of the deviatoric part of the stresses, but also of the hydrostatic part. Linear kinematic hardening is also considered under the assumption of an associated plasticity. Instead of using the number of cycles as an incremental variable, the concept of temporal evolution of the load is adopted for a precise follow-up of the history of the actual loading. The effect of mean stress is taken into account in the mesoscopic yield function; a law of nonlinear accumulation of damage is also considered in the model. Fatigue life is then determined using a phenomenological law based on mesoscopic energy dissipation from the plastic accommodative cycle. The first part of the work focused on a proposal for a fatigue model with a simpler implementation gradient than the previous models.L'objet de ce travail est de proposer une approche multi-échelle de la fatigue fondée sur l'énergie, et susceptible d'estimer les durées de vie associées à des chargements multidimensionnels variables. Le fondement de la démarche consiste à supposer que l'énergie dissipée à petite échelle régit le comportement à la fatigue. À chaque point matériel, est associée une distribution stochastique de points faibles qui sont susceptibles de plastifier et de contribuer à la dissipation d'énergie sans affecter des contraintes macroscopiques globales. Ceci revient à adopter le paradigme de Dang Van en fatigue polycyclique. La structure est supposée élastique (ou adaptée) à l'échelle macroscopique. De plus, on adopte à l'échelle mésoscopique un comportement élastoplastique avec une dépendance de la fonction de charge plastique non seulement de la partie déviatorique des contraintes, mais aussi de la partie hydrostatique. On considère également un écrouissage cinématique linéaire sous l'hypothèse d'une plasticité associée. Au lieu d'utiliser le nombre de cycles comme variable incrémentale, le concept d'évolution temporelle du chargement est adopté pour un suivi précis de l'historique du chargement réel. L'effet de la contrainte moyenne est pris en compte dans la fonction de charge mésoscopique ; une loi de cumul non linéaire de dommage est également considérée dans le modèle. La durée de vie à la fatigue est ensuite déterminée à l'aide d'une loi de phénoménologique fondée sur la dissipation d'énergie mésoscopique issue du cycle d'accommodation plastique. La première partie du travail a porté sur une proposition d'un modèle de fatigie à gradient de mise en oeuvre plus simple que les précédents modèles

Ability of Constitutive Models to Characterize the Temperature Dependence of Rubber Hyperelasticity and to Predict the Stress-Strain Behavior of Filled Rubber under Different Defor Mation States

In this paper, some representative hyperelastic constitutive models of rubber materials were reviewed from the perspectives of molecular chain network statistical mechanics and continuum mechanics. Based on the advantages of existing models, an improved constitutive model was developed, and the stress–strain relationship was derived. Uniaxial tensile tests were performed on two types of filled tire compounds at different temperatures. The physical phenomena related to rubber deformation were analyzed, and the temperature dependence of the mechanical behavior of filled rubber in a larger deformation range (150% strain) was revealed from multiple angles. Based on the experimental data, the ability of several models to describe the stress–strain mechanical response of carbon black filled compound was studied, and the application limitations of some constitutive models were revealed. Combined with the experimental data, the ability of Yeoh model, Ogden model (n = 3), and improved eight-chain model to characterize the temperature dependence was studied, and the laws of temperature dependence of their parameters were revealed. By fitting the uniaxial tensile test data and comparing it with the Yeoh model, the improved eight-chain model was proved to have a better ability to predict the hyperelastic behavior of rubber materials under different deformation states. Finally, the improved eight-chain model was successfully applied to finite element analysis (FEA) and compared with the experimental data. It was found that the improved eight-chain model can accurately describe the stress–strain characteristics of filled rubber

An energy-based strategy for fatigue analysis in presence of general multi-axial time varying loadings

International audienceThe purpose of this paper is to propose an energy based multi-scale fatigue approach which handles multidimensional time varying loading histories.Our fundamental thought is to assume that the energy dissipated at small scales governs fatigue at failure in a nonlinear additive way. We follow the Dang Van paradigm at macro scale. The structure is elastic at the macroscopic scale. At each material point, there is a stochastic distribution of weak points which will undergo strong plastic yielding, which contribute to energy dissipation without affecting the overall macroscopic stress. A kinematic hardening under the assumption of associative plasticity is also considered.Instead of using the number of cycles, we use the concept of multi-scale damage accumulation during the considered load history. A concise non-linear damage accumulation law is also proposed in our model. Fatigue will then be determined from the plastic shakedown cycle and from a phenomenological fatigue law linking lifetime and accumulated mesoscopic plastic dissipation

Multi-axial Fatigue Criteria with Length Scale and Gradient Effects

International audienceThe objective of the work is first to extend some classic high cycle fatigue (HCF) criteria (as Crossland, Dang Van, Papadopoulos, ...) to take into account a sensitivity of the criteria to stress spatial variations occurring at length scale lg, and second to compare the performances of the extensions through numerical simulations of experimental fatigue tests. After an introduction of the basic criteria and their gradient based extensions proposed by Luu et al., we focus on the Crossland criterion to propose a more practical and simple expression taking into account the gradient of the stress amplitude and the maximum hydrostatic stress. The proposition is then tested and applied to different simple situations: 4-point bending and cantilever rotative bending. The relative errors between the exact solutions and the numerical simulations are estimated. Biaxial bending-torsion tests are also simulated to demonstrate the capabilities of the approach. The generalization of the approach to other multiaxial fatigue criteria is briefly shown through the case of Papadopoulos 2001 proposal. Finally, the present study develops a simple formulation of gradient multi-axial fatigue criteria extending the classical HCF criteria. In this work only stress gradient with a beneficial effect on fatigue have been considered

An analysis on the spatiotemporal behavior of inbound tourists in Jiaodong Peninsula based on Flickr geotagged photos

Exploring the spatiotemporal behavior characteristics of inbound tourists is of great practical significance to the management and planning of attractions. Based on Flickr geotagged photos and metadata, the research analyzes the spatiotemporal behavior characteristics of inbound tourists in Jiaodong Peninsula from the perspective of tourist flow network. We decompose the time series characteristics of tourists with STL decomposition algorithm, and predict the inbound tourism trend through the time series model. We propose the Hot Status Index (HSI) based on network centrality, extract and analyze the distribution pattern of inbound tourism hotspots with the structural hole method. The k-core decomposition algorithm is introduced to analyze the hierarchical characteristics of the tourist flow network. And Fast Unfolding algorithm is adopted to analyze the characteristics of community aggregation under different scales, dividing the scenic area into four communities. The results show that the time series model can accurately estimate the trend of the number of tourists. And there is a “competition” effect among attractions in Jiaodong Peninsula. The attractions show a hierarchy effect, of which the core layer has obvious small-world characteristics, with a clustering coefficient of 0.768. The inter-city tourist flow in Jiaodong Peninsula reveals a closed “multi-triangle” distribution pattern, mainly in the marginal coastal cities. Qingdao old town presents community stability, and other urban communities have a scale effect, mainly comprising two tourism circles

Temperature-Dependence of Rubber Hyperelasticity Based on the Eight-Chain Model

Rubber-based materials are widely used in a variety of industrial applications. In these applications, rubber components withstand various loading conditions over a range of temperatures. It is of great significance to study the mechanical behavior of vulcanized rubber at different temperatures, especially in a range of high temperatures. The temperature dependence of the constitutive behavior of filled rubber is important for the performance of the rubber. However, only a few constitutive models have been reported that investigate the stress–temperature relationship. In this paper, based on an analysis of experimental data, the effects of temperature on the hyperelastic behaviors of both natural rubber and filled rubber, with different mass fractions of carbon black, were studied. The regulation of stress and strain of natural rubber and filled rubber with temperature was revealed. In addition, an eight-chain model that can reasonably characterize the experimental data at different temperatures was proved. An explicit temperature-dependent constitutive model was developed based on the Arruda-Boyce model to describe the stress–strain response of filled rubber in a relatively large temperature range. Meanwhile, it was proved that the model can predict the effect of temperature on the hyperelastic behavior of filled rubber. Finally, the improved Arruda-Boyce model was used to obtain the material parameters and was then successfully applied to finite element analysis (FEA), which showed that the model has high application value. In addition, the model had a simple form and could be conveniently applied in related performance test of actual production or finite element analysis