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The resolution sensitivity of the Kain–Fritsch (KF) convection scheme and the role of interactions between the physics and dynamics within the gray zone (<10 km) were investigated using the Separate Physics and Dynamics Experiment (SPADE) framework. Two groups of experiments were conducted using the Weather Research and Forecasting (WRF) model via traditional (Tradition) runs and SPADE runs with resolutions of 1, 2, 4, and 8 km during the wet period of the Tropical Warm Pool–International Cloud Experiment (TWP‐ICE). Results show that the KF scheme simulates the weakened convective processes well as the resolution increases in both groups, and the changes in the convective variables with resolution in SPADE are smaller than in the Tradition group. This indicates the important effects of interactions between model components on convection parameterizations as the resolution changes. Additionally, the microphysics variables remain nearly unchanged with resolution in SPADE and weaken slightly in Tradition as the resolution decreases, suggesting the relatively weaker influences of model interactions for the resolved‐cloud parameterization. Therefore, the scale‐aware behavior of KF scheme is further strengthened in Tradition runs, primarily through inhibiting the strength of stratiform processes through physics–dynamics interactions and physical components. Plain Language Summary The resolution sensitivity of Convective Parameterization Schemes (CPS) is a critical and challenging issue in the Earth's weather and climate system, particularly within the gray‐zone scale (1–10 km). This paper analyzes the resolution sensitivity of the KF convection scheme and isolates the effects of other model components (mainly the dynamics) on the CPS through designing two groups of experiments under the backgrounds with and without the physics‐dynamics feedbacks using the WRF model with resolutions of 1, 2, 4, and 8 km. The results demonstrate that the KF scheme shows scale‐aware performance in simulating convection under the strong tropical rainfall condition. Furthermore, the scale‐awareness of the KF scheme could be strengthen with the interactions from other model components. This paper provides a new perspective for evaluating the scale‐aware CPS and understanding the effects of physics‐dynamics interactions on the simulations. Key Points The resolution sensitivity of the Kain–Fritsch scheme was analyzed using the SPADE framework The KF scheme shows the scale adaptability across the gray zone during the wet period of TWP‐ICE The scale‐dependence of the KF scheme is strengthened by physics–dynamics interactions across the gray zone

In this article, the computational methodology of the catenary–train–track system vibration analysis is presented and used to estimate the influence of vehicle body vibrations on the pantograph–catenary dynamic interaction. This issue is rarely referred in the literature, although any perturbations appearing at the pantograph–catenary interface are of great importance for high-speed railways. Vehicle body vibrations considered in this article are induced by the passage of train through the track stiffness discontinuity, being a frequent cause of significant dynamic effects. First, the most important assumptions of the computational model are presented, including the general idea of decomposing catenary–train–track dynamic system into two main subsystems and the concept of one-way coupling between them. Then, the pantograph base vibrations calculated for two train speeds (60 m/s, 100 m/s) and two cases of track discontinuity (a sudden increase and a sudden decrease in the stiffness of track substrate) are analyzed. Two cases of the railway vehicle suspension are considered – a typical two-stage suspension and a primary suspension alone. To evaluate catenary–pantograph dynamic interaction, the dynamic uplift of the contact wire at steady arm and the pantograph contact force is computed. It is demonstrated that an efficiency of the two-stage suspension grows with the train speed; hence, such vehicle suspension effectively suppresses strong sudden shocks of vehicle body, appearing while the train passes through the track stiffness discontinuity at a high speed. In a hypothetical case when the one-stage vehicle suspension is used, the pantograph base vibrations may increase the number of contact loss events at the catenary–pantograph interface.

Bacterial growth dynamics, typically represented by growth curves, are fundamental yet complex features of living populations. Traditional analyses focusing on specific parameters often overlook the full temporal patterns of growth. Here, we systematically investigated how genomic and environmental factors shape bacterial growth dynamics by analyzing 870 growth curves from five Escherichia coli strains with varying genome sizes cultured in 29 chemically defined media. Using dynamic time warping, clustering, and gradient boosting decision trees, we found that environmental components, especially glucose, primarily determine overall growth curve patterns, while genome size governs detailed growth parameters such as lag time, growth rate, and carrying capacity. Notably, finer clustering revealed increased genomic influence and decreased environmental impact, suggesting a hierarchical interaction where the environment modulates broad growth behavior and the genome fine-tunes specific growth responses. These findings provide insights into the coordinated roles of genome and environment in bacterial population dynamics, advancing our understanding of microbial growth regulation.

CD44 ligand-receptor interactions are known to be involved in regulating cell migration and tumor cell metastasis. High expression levels of CD44 correlate with a poor prognosis of melanoma patients. In order to understand not only the mechanistic basis for dacarbazine (DTIC)-based melanoma treatment but also the reason for the poor prognosis of melanoma patients treated with DTIC, dynamic force spectroscopy was used to structurally map single native CD44-coupled receptors on the surface of melanoma cells. The effect of DTIC treatment was quantified by the dynamic binding strength and the ligand-binding free-energy landscape. The results demonstrated no obvious effect of DTIC on the unbinding force between CD44 ligand and its receptor, even when the CD44 nanodomains were reduced significantly. However, DTIC did perturb the kinetic and thermodynamic interactions of the CD44 ligand-receptor, with a resultant greater dissociation rate, lower affinity, lower binding free energy, and a narrower energy valley for the free-energy landscape. For cells treated with 25 and 75 μg/mL DTIC for 24 hours, the dissociation constant for CD44 increased 9- and 70-fold, respectively. The CD44 ligand binding free energy decreased from 9.94 for untreated cells to 8.65 and 7.39 kcal/mol for DTIC-treated cells, which indicated that the CD44 ligand-receptor complexes on DTIC-treated melanoma cells were less stable than on untreated cells. However, affinity remained in the micromolar range, rather than the millimolar range associated with nonaffinity ligands. Hence, the CD44 receptor could still be activated, resulting in intracellular signaling that could trigger a cellular response. These results demonstrate DTIC perturbs, but not completely inhibits, the binding of CD44 ligand to membrane receptors, suggesting a basis for the poor prognosis associated with DTIC treatment of melanoma. Overall, atomic force microscopy-based nanoscopic methods offer thermodynamic and kinetic insight into the effect of DTIC on the CD44 ligand-binding process.

We advance interactionist perspectives on how organizational structures emerge in new issue domains. Our study is grounded in field data collected over 18 months at a large biomedical company that sought to become more sustainable. Over that period, some sustainability-related issues became firmly embedded in formal structures and procedures, while others faltered. We identify the quality of situational interactions among organizational members as the engine behind the structuring of organizational sustainability efforts. Successful interactions generated traces of attention, motivation, knowledge, relationships, and resources that linked fleeting interactions to emergent organizational structures. Our findings point to the importance of internal advocates and distributed processes at middle and lower levels for developing organizational structures, and we show that advocates’ interests, commitments, and identities are altered in the course of repeated interactions, as are the political resources available to them. Paying attention to situation-level interactions thus results in a more dynamic view of the emergence of formal structures through political processes. We develop a process model that informs structuration perspectives on organizational change by showing how social interaction dynamics can account for divergent levels of structuring within the same domain. The model also advances political perspectives on organizational change by unpacking the situational underpinnings of advocacy efforts and collective mobilization around issues.

The overlapping displacement fields among closely spaced piles termed as pile-to-pile interactions, increase the overall settlement of pile groups. Resultantly, under static loading, these interactions invariably decrease the group stiffness of piles than the collective stiffnesses of corresponding single piles. Whereas under dynamic loading, the group stiffness may increase or decrease than the cumulative stiffnesses of single piles depending on the loading frequency. As soil exhibits nonlinear behaviour under strong motions, in addition to the consideration for soil nonlinearity to obtain the response of piles, nonlinearity generated at the interface between the soil and pile needs to be appropriately considered as it can significantly change the response of piles. To assess the influence of mentioned nonlinearities on the vertical pile-to-pile interaction factors, a scale model test on closely spaced piles is carried out under 1 g conditions. At very low loading amplitudes wherein soil exhibits close-to-elastic behaviour, the experimental interactions are drastically smaller than those obtained from closed-form solutions assuming soil as an elastic material, highlighting the influence of soil-pile interface nonlinearity. Under higher loading amplitudes, results indicate that the increased nonlinearities strengthen the amplitude dependency of interactions. To minutely assess the effects of soil-pile interface nonlinearity on the response, three-dimensional nonlinear finite element modelling (FEM) is carried out. Results obtained from FEM considering soil and soil-pile interface nonlinearities validate the experimental results well. Whereas, assuming soil as an elastic material leads to a noticeable reduction in interactions due to stiffnesses of neighbouring piles; interactions get further reduced when the number of adjacent piles increases.

The method of inputting the seismic wave determines the accuracy of the simulation of soil-structure dynamic interaction. The wave method is a commonly used approach for seismic wave input, which converts the incident wave into equivalent loads on the cutoff boundaries. The wave method has high precision, but the implementation is complicated, especially for three-dimensional models. By deducing another form of equivalent input seismic loads in the finite element model, a new seismic wave input method is proposed. In the new method, by imposing the displacements of the free wave field on the nodes of the substructure composed of elements that contain artificial boundaries, the equivalent input seismic loads are obtained through dynamic analysis of the substructure. Subsequently, the equivalent input seismic loads are imposed on the artificial boundary nodes to complete the seismic wave input and perform seismic analysis of the soil-structure dynamic interaction model. Compared with the wave method, the new method is simplified by avoiding the complex processes of calculating the equivalent input seismic loads. The validity of the new method is verified by the dynamic analysis numerical examples of the homogeneous and layered half space under vertical and oblique incident seismic waves.

This paper presents a general procedure for dynamic modeling and simulation of planar multibody systems considering multiple revolute clearance joints. The normal contact force is evaluated by a hybrid continuous contact force model, established on the base of the Lankarani–Nikravesh (L–N) model and the elastic foundation model. The LuGre friction law is employed to describe the tangential effect. The effectiveness of the presented methodology is demonstrated through the comparisons with the MSC ADAMS software simulation results of a slider–crank mechanism with clearance joints. Then, the system behavior affected by dynamic interaction of three revolute clearance joints is analyzed and some kinds of 27 combination modes are presented. Additionally, a comprehensive analysis of the system responses in a wide range of dynamic simulation parameters is conducted to find out some inner rules existed in the mechanical system with revolute clearance joints. Results show that there exists a strong dynamic interaction between different clearance joints, indicating that all joints should be modeled as imperfect to achieve a further understanding of multibody system behavior. Also, the clearance joint nearer to the input link is found to suffer more serious contact effects, require more input torque and cost longer computational time. Furthermore, the system dynamics relies on many factors, even a small change of which may lead to different system responses, changing from periodic to chaotic and the other way around. In addition, several characteristic values have been captured from the simulation results, which need to be paid more attention in use.

We propose an extension of the stochastic block model for recurrent interaction events in continuous time, where every individual belongs to a latent group and conditional interactions between two individuals follow an inhomogeneous Poisson process with intensity driven by the individuals’ latent groups. We show that the model is identifiable and estimate it with a semiparametric variational expectation-maximization algorithm. We develop two versions of the method, one using a nonparametric histogram approach with an adaptive choice of the partition size, and the other using kernel intensity estimators. We select the number of latent groups by an integrated classification likelihood criterion. We demonstrate the performance of our procedure on synthetic experiments, analyse two datasets to illustrate the utility of our approach, and comment on competing methods.