The growing push in nonprofit studies toward panel data necessitates a methodological guide tailored for nonprofit scholars and practitioners. Panel data analysis can be a robust tool in advancing the understanding of causal and/or more nuanced inferences that many nonprofit scholars seek. This study provides a walk-through of the assumptions and common modeling approaches in panel data analysis, as well as an empirical illustration of the models using data from the nonprofit housing sector. In addition, the paper compiles applications of panel data analysis by scholars in leading nonprofit journals for further reference.

In this paper, a novel series–parallel stable platform is proposed, and its kinematic and dynamic models are established. The relationship between the length, speed, and acceleration of rolling and pitching electric push rods is analyzed. The workspace of the series–parallel stable platform is determined, and the singularity and interference are analyzed. The state-machine-based control system of the stable platform is designed. An experimental environment of the principle of the real-time control system based on dSPACE was built. A position–speed double closed-loop experiment, simulating mounting carrier of the random signal tracking, and system comprehensive performance experiment were conducted to verify the accuracy of the kinematics and dynamics model of the series–parallel stable platform and the rationality and stability of the control system.

The study presents a novel cable-driven serial robot based on flexible joints and tensegrity structures, which features a rapid response capability in complex dynamic environments. This makes it particularly suitable for human–robot interaction scenarios. Compared to traditional rigid serial robots, the design’s compliance demonstrates significant advantages in addressing complex demands. The study delves into kinematic and dynamic modeling methods and verifies their effectiveness through simulations. The kinematic model transforms the local coordinate system to the global one using general kinematic equations. First, the static and dynamic model of the robot is derived based on the torque balance equation, and then the dynamic model of the robot is constructed. By simplifying the robot model, the relationship between tension values from driving cables and the robot’s workspace is analyzed under the constraints of tensegrity structures and flexible joints. Additionally, trajectory simulations validate the kinematic and dynamic models. The kinetic energy variation curves based on the trajectories confirm the accuracy of the theoretical analysis. This method demonstrates broad applicability and can be applied to other serial robots with flexible structures, offering effective solutions for use in complex dynamic environments.

Human–machine compatibility and collaborative control for stroke patients utilizing lower limb rehabilitation robots have attracted considerable research attention. As a highly human–machine-coupled system, ensuring adequate compliance and safety is fundamental to efficient and comfortable rehabilitation. Therefore, this paper first quantifies human–machine contact interactions, proposes a human–machine coupling dynamics modeling method, and identifies the robot’s dynamic inertia parameters and human lower limb parameters. Second, a dual closed-loop controller for the rehabilitation robot is designed. Based on the bottom position control, an adaptive admittance control algorithm is proposed that employs the root-mean-square propagation (RMSprop) algorithm to tune the adaptive gain. In rehabilitation training, the controller can adaptively adjust the admittance parameters according to the human–machine interaction force to achieve responsiveness to the dynamic changes of the human–machine system. The experimental results of the control system show that the human–machine cooperative control performance is significantly improved, the maximum joint angle error is reduced by more than 40.9%, and the maximum human–machine interaction force is reduced by more than 19.4%.

This article provides a Construction Grammar (CxG) analysis of the Complex Modifier Construction (CMC) in English and an investigation of its productivity in World Englishes with a particular focus on African and South-East Asian Englishes. By examining data from the Corpus of Global Web-based English (GloWbE), we seek to establish whether the productivity of the construction correlates with the developmental phase of the variety of English in Schneider’s Dynamic Model of Postcolonial Englishes, or whether language contact, and particularly the typological profiles of the local substrate languages (head-initial versus head-final syntax), affects productivity. We find that evolutionary progress is indeed a relevant factor insofar as the most advanced ‘Inner Circle’ varieties are concerned, but we also observe substantially lower productivity in the African varieties of English when compared to the South-East Asian Englishes represented in the corpus. As the main substrate languages in the African countries under study have head-initial syntax and those in the South-East Asian countries head-final syntax, we conclude that the productivity of complex premodifiers is affected by the multilingual situation in these regions and propose that language contact should be considered more closely as an explanatory factor in future studies of constructional productivity in World Englishes.

With numerous applications of coilable masts in high-precision space application scenarios, there are also greater demands on the accuracy of their dynamic modelling and analysis. The modelling of hinges is a critical issue in the dynamic modelling of coilable masts, which significantly affects the accuracy of the dynamic response analysis. For coilable masts, the rotational effect is the most important problem in hinge modelling. However, few studies have focused on this topic. To address this problem, the concept of hinge equivalent rotational stiffness is proposed in this paper to describe the rotational effect of the coilable mast hinges. After that, a new coilable mast dynamic model containing the undetermined hinge equivalent rotational stiffness is introduced, and an identification method for the hinge equivalent rotational stiffness based on the hammer test is proposed. Finally, the dynamic modelling method is validated through an actual coilable mast example, and the analysis and test results show that the accuracy of the dynamic model established by the proposed method in this paper is greater than that of the traditional model.

This study aims to uncover the dynamics of the evolution of English in Rwanda, using Schneider's (2007) Dynamic Model. Even though Rwanda has had no history of British colonial rule or that of any other Anglophone country, it currently presents a situation of a non-postcolonial environment where English plays a preponderant role on a par with many dimensions of the status of English in Outer Circle counties such as Uganda or Ghana. Despite the fact that the Dynamic Model was primarily meant to account for the evolution of English in postcolonial environments, its applicability (with a few caveats) to the current linguistic situation in Rwanda provides a robust articulation of the trajectorial development of English in this country.

Accurate dynamic model is essential for the model-based control of robotic systems. However, on the one hand, the nonlinearity of the friction is seldom treated in robot dynamics. On the other hand, few of the previous studies reasonably balance the calculation time-consuming and the quality for the excitation trajectory optimization. To address these challenges, this article gives a Lie-theory-based dynamic modeling scheme of multi-degree-of-freedom (DoF) serial robots involving nonlinear friction and excitation trajectory optimization. First, we introduce two coefficients to describe the Stribeck characteristics of Coulomb and static friction and consider the dependency of friction on load torque, so as to propose an improved Stribeck friction model. Whereafter, the improved friction model is simplified in a no-load scenario, a novel nonlinear dynamic model is linearized to capture the features of viscous friction across the entire velocity range. Additionally, a new optimization algorithm of excitation trajectories is presented considering the benefits of three different optimization criteria to design the optimal excitation trajectory. On the basis of the above, we retrieve a feasible dynamic parameter set of serial robots through the hybrid least square algorithm. Finally, our research is supported by simulation and experimental analyses of different combinations on the seven-DoF Franka Emika robot. The results show that the proposed friction has better accuracy performance, and the modified optimization algorithm can reduce the overall time required for the optimization process while maintaining the quality of the identification results.

Evolution has shown that legged locomotion is most adequate for tasks requiring versatile movement on land, allowing animals to traverse a wide variety of environments ranging from natural terrain to artificial, man-made landscapes with great ease. By employing well-designed control schemes, this ability could be replicated for legged robots, enabling them to be used in critical situations that still pose great danger to human integrity, such as search and rescue missions, inspection of hazardous areas, and even space exploration. This work characterizes the quadruped robot and contact dynamics that will compose our in-house simulator to be used for prototyping locomotion control schemes applied to quadruped robots. The proposed simulator computes the robot dynamics using the Recursive Newton-Euler and Composite-Rigid-Body algorithms with a few modifications to make certain aspects relevant for contact detection and control more easily accessible; furthermore, a compliant contact force method alongside stick-slip friction modeled the contact dynamics. To allow the robot to move, a simple PD-independent joint controller was implemented to track a desired leg trajectory. With the same robot and controller implemented using the MuJoCo simulation software, this work evaluates the proposed simulator by comparing characteristic locomotion signals such as the trunk pose and the ground reaction forces. Results showed similar behavior for both simulators, especially with regard to the contact detection, despite the significantly different contact models. Lastly, final remarks to enhance our simulator’s performance are suggested to be explored in future works.

The present article analyzes the use of preposition stranding (the world which we live in) and pied-piping (the world in which we live) in finite WH-relative clauses in twelve varieties of English. In the light of previous studies, it assumes that the strength of processing constraints and formality effects that drive speakers’ constructional choices should correlate with Dynamic Model stages (Schneider 2007). However, drawing on data from the International Corpus of English (ICE) and using mixed-effects logistic regression analysis, the study shows that processing factors affect speakers of all Dynamic Model stages in a very similar way. At the same time, clear differences between variety stages are observed with respect to formality and topic, which strongly affect Phases IV and V but not Phase III. These results are interpreted from a Usage-based Construction Grammar perspective.

A walking robot consisting of double Stewarts parallel legs was designed by our research team in the past time, which was mainly used for the transportation of the wounded after the disaster. In order to promote stability of control locomotion and ensure invariably horizontal state of the robot platform in the process of motion, the central pattern generator (CPG) based on particle swarm optimization (PSO) is presented to optimize the kinematic model. The purpose of optimization is to solve the hysteresis problem of displacement variation among the electric cylinders. Moreover, the dynamic model of the robot is established, which can provide mechanical basis for the feedback of control signal and make the robot move stably. The simulation results show that the displacement hysteresis problem of the electric cylinders is solved well. Meanwhile, compared with simulation results based on GA-CPG method, it is demonstrated that the robot motion planned using PSO-CPG method has better motion stability and can avoid the impact of legs landing during the transition phase of the motion cycle. The experimental results show that the platform on the robot can maintain an invariably horizontal state, and the locomotion is more stable. It verifies the feasibility of PSO-CPG model and the correctness of the dynamic model of the parallel mobile rescue robot.

We use a dynamic model of the U.S. apple industry separated into organic and conventional production to better measure the impacts of pest or disease outbreaks on producers and consumers, along with an equilibrium displacement model to simulate welfare effects from various shocks compared to a baseline. Our results show that the impacts of the outbreaks differ between organic and conventional production methods. Growers’ and consumers’ responses to shocks differ widely across the industry. Farmers and policy makers should use these findings to appropriately respond to different shocks and production methods.

Spherical robots (SRs) have the characteristics of nonholonomic constraints, underactuation, nonchain, and strong coupling, which increase the difficulty of modeling and motion control compared with traditional robots. In this study, we develop an adaptive motion control scheme for a nonholonomic SR, in which an omnidirectional dynamic model is carried out by using the Euler–Lagrange method to describe the omnidirectional motion of the SR more accurately. Furthermore, to facilitate the design of the motion controller, the dynamic model is simplified to obtain the state space expression of the SR. Aiming at the problem of poor control effect caused by the change of system model parameters which are influenced by dynamic model reduction, an adaptive motion control law of SR is designed based on MRAC. And the coefficient adjustment of the controller is obtained by the Lyapunov method, with the guaranteed stability of the closed-loop system. Finally, the controller designed in this thesis is compared with four controllers including linear quadratic regulator, Fuzzy PID, PSO-ADRC, and hierarchical SMC. The experimental comparison proves that the control scheme proposed in this study still has good control ability when the motion parameters are disturbed.

The principal objective of the paper is to show the importance of the Hamiltonian in control theory. Instead of using the Lagrangian formulation of electromechanical or robotic systems, our work is focused on robot dynamics by its Hamiltonian. Using the iterative Newton–Euler, we generate the local Hamiltonians and the derivative of the moments at each joint of the robot manipulator. Thus, we can apply decentralized controllers at each joint. We compare and discuss the efficiency of the controllers. We show that the performance of the sliding modes controller is more robust than that of the PD or Bang–Bang controllers.

This article presents a methodology to reduce the energy consumption of an industrial robot. We propose a design for a 3R serial manipulator of general geometry. We show an analytical model aiming to analyze the search space of architectures based on the torsion angles of the robot to determine the optimal architecture that allows the efficient use of energy. The analytical model provides a theoretical estimation of the energy consumption and is validated by monitoring the experimental robot. The numerical calculations obtained with a particular case reduced the energy consumption by approximately 7.5%.

Family feasting during the Spring Festival is a Chinese tradition. However, close contact during this period is likely to promote the spread of coronavirus disease 2019 (COVID-19). This study developed a dynamic infectious disease model in which the feast gatherings of families were considered the sole mode of transmission. The model simulates COVID-19 transmission via family feast gatherings through a social contact network. First, a kinship-based, virtual social contact network was constructed, with nodes representing families and connections representing kinships. Families in kinship with each other comprised of the largest globally coupled network, also known as a clique, in which a feast gathering was generated by randomly selecting two or more families willing to gather. The social contact network in the model comprised of 215 cliques formed among 608 families with 1517 family members. The modelling results indicated that when there is only one patient on day 0, the number of new infections will reach a peak on day 29, and almost all families and their members in the social contact network will be infected by day 60. This study demonstrated that COVID-19 can spread rapidly through continuous feast gatherings through social contact networks and that the disease will run rampant throughout the network.

The traditional identification methods of industrial robots are based on Inverse Dynamic Identification Model (IDIM). Based on the model, input torque, motor-side and link-side motion data are necessary when joint flexibilities are considered. However, it is often unavailable or expensive to general robots which are not equipped with link-side sensors. To solve the problem, a novel dynamic parameter identification method, which only employ input torque and motor-side motion data, is proposed in this report. Based on motor-side dynamics, link-side dynamics are modified as high-order nonlinear functions of input torque and motor-side motion. Then, through different trajectory-load groups and high-order observers, the nonlinear equations can be solved, and dynamic parameters can be estimated with short operation time. The selection rules of the trajectory-load groups are then discussed based on simulation results, so as to promote estimation results. Finally, experiments are conducted to verify the proposed method and exhibit the selection rules of observer gains. As shown in the report, except viscous friction parameters, identification difference between the IDM-based methods and the proposed one is less than 9%.