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In this article, we briefly clarify several points regarding immunopsychiatry. In particular, we argue that higher density data and a greater focus on temporal dynamics are both important, and that studies incorporating these features have the potential to greatly advance the field. We also respond to recent comments made on our original article on this topic (Moriarity and Slavich, 2023), including the contention that our perspective on immunopsychiatry is reductionistic. To the contrary, we believe that strong immunopsychiatry studies are highly integrative and include data from multiple major levels of analysis to form a more complete picture of how processes that are relevant for mental health and behavior emerge and dynamically change over time in relation to one another.

Romantic relationships are defined by emotion dynamics, or how the emotions of one partner at a single timepoint can affect their own emotions and the emotions of their partner at the next timepoint. Previous research has shown that the level of these emotion dynamics plays a role in determining the state and quality of the relationship. However, this research has not examined whether the estimated emotion dynamics change over time, and how the change in these dynamics might relate to relationship outcomes, despite changes in dynamics being likely to occur. We examined whether the magnitude of variation in emotion dynamics over time was associated with relationship outcomes in a sample of 148 couples. Time-varying vector autoregressive models were used to estimate the emotion dynamics for each couple, and the average and standard deviation of the dynamics over time was related to relationship quality and relationship dissolution 1-2 years later. Our results demonstrate that certain autoregressive and cross-lagged parameters do show significant variation over time, and that this variation is associated with relationship outcomes. Overall, this study demonstrates the importance of accounting for change in emotion dynamics over time, and the relevance of this change to the prediction of future outcomes.

• 3D recursive kinematics is introduced for the dynamic modeling of the multi-flexible-link space manipulators. • The general expressions of the dynamic boundary conditions are derived based on 3D recursive kinematics. • The difference between the results of the time-varying modes and time-invariant modes is investigated. This paper presents a dynamic modeling method for the multi-flexible-link space manipulators under time-varying dynamic boundary conditions. This method is based on 3D recursive kinematics and is applicable to the space manipulators with an arbitrary number of flexible links. The elastic deflection of the flexible links is described by using the Assumed Mode Method (AMM). The general expressions of the dynamic boundary conditions are derived by combining the Newton-Euler equation with 3D recursive kinematics. Based on 3D recursive kinematics, the dynamic model suitable for space manipulators with an arbitrary number of flexible links is established. For the multi-flexible-link manipulator systems, the movement of the links will alter the mass distribution of the system, resulting in the time-varying modes of the links. The difference between the results of the time-varying modes and time-invariant modes are investigated. Numerical simulations are performed to verify the adaptability of the proposed dynamic modeling method to different manipulators. Simulation results shows that the results of time-varying modes are in good agreement with those of time-invariant modes, and the simulation calculation time of time-invariant modes is less than that of time-varying modes. For the above reasons, the time-invariant modes are sufficient and it is unnecessary to update the modes. [ABSTRACT FROM AUTHOR]

The development of telescopes with large apertures is driven by the increasing demand for higher imaging resolution and coverage. Large membrane diffraction space telescopes are particularly attractive due to their lightweight nature, ease of folding and unfolding, and high-precision imaging capabilities. However, their substantial size and flexibility make them susceptible to long-duration, low-frequency vibrations during attitude maneuvers, which degrade attitude and imaging accuracy and risk instrument damage. Consequently, an urgent need exists for a high-precision integrated control scheme. In this paper, the integrated control of vibration and attitude in a large space telescope is studied using cable actuators and control moment gyroscopes (CMGs). Since cables can only withstand limited tension, the unilateral and constrained characteristics of the control input are taken into account during the control design process. Firstly, a rigid-flexible coupling dynamic model of the space telescope is established using the velocity variation principle with hybrid coordinates. Additionally, a two-body astrodynamic model is developed to assess the impact of gravity gradient torque. Next, combining the computational torque method and H∞ control theory, an integrated control scheme is proposed, which achieves vibration and attitude control during maneuvers. Then, this paper optimizes the cable actuator positions via the discrete particle swarm optimization (PSO) algorithm and plans various attitude maneuver paths. Finally, numerical simulations are adopted to demonstrate the effectiveness of the control scheme. The results show that this integrated control scheme swiftly suppresses structural vibrations during attitude maneuvers, enabling high-precision attitude control of the space telescope. • A vibration-attitude integrated control for a novel large membrane diffraction space telescope is studied • 3 types of attitude maneuver paths are planned for the two requirements of time optimal and minimum vibration excitation. [ABSTRACT FROM AUTHOR]

The idea of switching costs and how they affect agricultural technology adoption has received little attention in the literature. We employ a dynamic switching model to show that switching costs generally discourage the adoption of new technologies by farmers, but the extent of the effect depends on the level of switching costs, as well as farmer perceptions and foresight. We provide an empirical strategy to identify switching costs and estimate their effects on adoption under different farmers’ perceptions about adoption uncertainty. An application to hybrid seed adoption in Kenya confirms the existence of switching costs. The correlated‐random‐effects probit results suggest there is heterogeneity in dominant farmer types across agro‐ecological zones in Kenya. Area‐specific policies are suggested to promote technology adoption in different environments. [ABSTRACT FROM AUTHOR]

To improve the precision of the dynamic modeling of bolted joints, a novel method is presented to model the dynamics by using a radially segmented annular virtual material equivalent bolted joints considering the thickness in this work. Firstly, on the basis of obtaining the contact pressure distribution at bolted joints, the division criterion of the virtual material layer along the radial segments is proposed, and the finite element (FE) model of the equivalent bolted joints of the radially segmented annular virtual material considering the thickness is established. Secondly, the characteristic parameters (elastic modulus, poisson's ratio, density, and thickness) of the radially segmented annular virtual material are used as inputs to calculate the natural frequencies of the bolted joints system, and the deep neural network (DNN) model is constructed and trained on this data sample. Finally, the cuckoo search (CS) algorithm is used to optimally identify the characteristic parameters of radially segmented annular virtual material. The bolted joints of the self-designed solid model of the bolted joints system are studied and analyzed as an example, and the maximum relative error of the first six orders natural frequencies lowers than 1.5 %. [ABSTRACT FROM AUTHOR]

Automatic transdiagnostic risk calculators can improve the detection of individuals at risk of psychosis. However, they rely on assessment at a single point in time and can be refined with dynamic modeling techniques that account for changes in risk over time. We included 158,139 patients (5007 events) who received a first index diagnosis of a nonorganic and nonpsychotic mental disorder within electronic health records from the South London and Maudsley National Health Service Foundation Trust between January 1, 2008, and October 8, 2021. A dynamic Cox landmark model was developed to estimate the 2-year risk of developing psychosis according to the TRIPOD (Transparent Reporting of a multivariate prediction model for Individual Prognosis or Diagnosis) statement. The dynamic model included 24 predictors extracted at 9 landmark points (baseline, 0, 6, 12, 24, 30, 36, 42, and 48 months): 3 demographic, 1 clinical, and 20 natural language processing–based symptom and substance use predictors. Performance was compared with a static Cox regression model with all predictors assessed at baseline only and indexed via discrimination (C-index), calibration (calibration plots), and potential clinical utility (decision curves) in internal-external validation. The dynamic model improved discrimination performance from baseline compared with the static model (dynamic: C-index = 0.9; static: C-index = 0.87) and the final landmark point (dynamic: C-index = 0.79; static: C-index = 0.76). The dynamic model was also significantly better calibrated (calibration slope = 0.97–1.1) than the static model at later landmark points (≥24 months). Net benefit was higher for the dynamic than for the static model at later landmark points (≥24 months). These findings suggest that dynamic prediction models can improve the detection of individuals at risk for psychosis in secondary mental health care settings. [ABSTRACT FROM AUTHOR]

Advanced Driving Assistance Systems (ADAS), such as collision avoidance systems and adaptive cruise control, are important features of autonomous driving and are gaining importance day by day in terms of increasing road safety. To increase the reliability of the system, virtual simulation environments are used during the design and development stages. This study examines the effect of ADAS features on energy parameters during the driving cycle in a virtual simulation environment. The discussion focuses on the simulation of an electric vehicle and the relationship between energy use and ADAS functions. For ADAS modeling and simulation, a dynamic model was developed in MATLAB and examined throughout the NEDC drive cycle. [ABSTRACT FROM AUTHOR]

For building projects, the manager is responsible for coordinating the work of subcontractors at the construction site. This includes operations, material flows, and storage. In summary, one of their main roles is to ensure smooth team rotation, maintain fluid circulation, and avoid congestion or relaxation on the site. However, traditional tools lack the ability to consider the planning and management of worksite spaces when calculating the execution schedule and critical path. Consequently, three-week planning is usually carried out separately on independent plans, often using spreadsheets. In addition, a construction site is highly dynamic and mobile in nature, and the positioning of resources and workers can change daily. This makes the management of available space even more complex, and effective space management becomes an imperative. To address this challenge, this paper develops visual dynamic artifacts that present different operation types. The methodology and the conceptual framework facilitate the calculation of the Occupancy Rate (OR) that enables construction project managers to create simple yet dynamic spatiotemporal models of the construction schedule. By incorporating factors such as crew turnover and occupancy evolution, managers can simplify the calculation process and effectively optimize construction work by utilizing site occupancy rates. In summary, this paper presents the Dynamic Model of the Occupancy Rate Schedule (DMORS), a methodology developed through design science. This model utilizes created artifacts representing various operation types to ensure accurate calculations of dynamic occupancy by floor and sector in a site. Consequently, it enables the construction of a more realistic schedule based on critical space ideologies. The DMORS enables managers to use the OR for different floors and sectors of a site, allowing for better space management. A proof of concept demonstrates that this tool can enhance the efficiency and productivity of construction projects by optimizing crew schedules and resource allocation based on site OR. [ABSTRACT FROM AUTHOR]

Rotating machinery is an important component of mechanical equipment, and misaligned rotor systems are a key factor leading to equipment failures. If there is a misalignment fault during operation, it may have various adverse effects on the stable operation of mechanical equipment, such as causing dynamic and static friction between the rotor and stator, bearing friction damage, shaft bending deformation, oil film oscillation, vibration, etc., all of which may seriously interfere with the stable operation of mechanical equipment. Studying the mechanism and vibration characteristics of misalignment faults in rotor systems is particularly crucial for accurately judging and mastering the operating conditions of the rotor system. This article focuses on the parallel misalignment fault of the rotor system of a hydroelectric generator set and the collision friction coupling fault between the rotor system of the generator set. Based on nonlinear rotor dynamics theory and the motion mechanism of parallel misalignment faults, a nonlinear dynamic model of the rotor system of a hydroelectric generator set is constructed, which considers the influence of parallel misalignment and collision friction coupling faults. The model explores the nonlinear dynamic performance of the generator rotor system under multiple parameter changes such as unit speed, eccentricity, and parallel misalignment. [ABSTRACT FROM AUTHOR]

This study presents the design and a thorough analysis of a six-bar crank-driven leg mechanism integrated with a skew pantograph, developed for walking robots. The mechanism's dimensions were optimized using a rigorous dimensional synthesis process in GIM software (version 2024). Subsequently, a detailed kinematic analysis was performed in GIM to simulate the leg's motion trajectory, velocity, and acceleration. In parallel, kinematic equations were formulated using the vector loop method, implemented in MATLAB (version R2013-b), and compared with the GIM results for validation, demonstrating the strong agreement between both tools. These results confirm the mechanism's ability to generate a compact, high-lift foot trajectory while maintaining system stability and energy efficiency. An inverse dynamic analysis was carried out to determine the actuator's driving torque, ensuring efficient operation under expected load conditions. Furthermore, topology optimization conducted in SOLIDWORKS (version 2021) significantly reduced the weight of the ground-contacting link while preserving its structural integrity. A subsequent stress analysis validated the mechanical viability of the optimized design, supporting its feasibility for real-world implementation. This research provides a robust foundation for the development of a functional prototype. Its potential applications include mobile robots for sectors such as agriculture and all-terrain vehicles, where efficient, reliable, and adaptive locomotion is crucial. The proposed mechanism strikes an optimal balance between mechanical simplicity, cost-effectiveness, and high performance, making it well-suited for challenging operational environments. [ABSTRACT FROM AUTHOR]

AbstractAs an important component of rotating machinery, the rotor system (RSM) has a decisive effect on the system dynamics. Most previous works established the RSM dynamic model without the bearing slip, ball dynamics, and cage dynamics. This work proposes a flexible rotor system (FRSM) dynamic model with the bearing slip, ball dynamics, and cage dynamics. The effect of the bearing slip on the FRSM dynamic is analyzed. The FRSM consists of the rotor, rigid disk, and ball bearings. The rotor is modeled using the Timoshenko beam elements. The dynamic models of the rigid disk and ball bearing are established by using the lumped parameter method. The bearing clearance and installation method effects are considered. An experimental verification is developed to demonstrate the validity of the proposed dynamic model. The results obtained by the proposed model and the previous model without the bearing slip are compared. Moreover, the effects of the rotor rotational speed and rigid disk unbalance eccentric distance on the FRSM dynamics and bearing slip are analyzed. The results shows that rotor rotation frequency (fs) is not obvious for health FRSM and the amplitudes of fs and nfs increase with rotation speed and unbalance eccentric distance, which can provide guidance for fault diagnosis. [ABSTRACT FROM AUTHOR]

AbstractOver the past three decades, Trust in Automation (TiA) has been the subject of extensive research. However, a large portion of the research takes a “static” approach to modeling trust and views trust as a linear unidirectional phenomenon. This view fails to recognize that trust is a dynamic construct that changes over time as an outcome of prolonged interaction with automation. The present study aims to address this gap and explore the nonlinear dynamic nature of trust by developing a simulation model of Trust in Automation (TiA) that can demonstrate trust evolution, deterioration, and recovery within the context of supervisory control of Maritime Autonomous Surface Ships (MASS). Employing System Dynamics (SD) approach, the model captures trust’s non-linear and reciprocal nature through dynamic feedback loops, producing behavioral patterns consistent with empirical observations of trust. The simulation results showcase the crucial role of initial trust conditions and the alignment of expectations with system performance in fostering trust and effective automation use. The study also explores the timing of system malfunctions, revealing that early faults have a greater negative impact on trust compared to later faults of the same magnitude. We tested a segment of the proposed model in an experimental study involving 30 human participants to investigate the effects of automation malfunctions on operators’ trust and behavioral responses during the supervisory control of MASS. Results not only validated the proposed model but demonstrated a significant decline in perceived reliability and trust in automation as well as the monitoring strategy after the automation malfunction. [ABSTRACT FROM AUTHOR]

This article discusses an identification and modeling approach of a reluctance synchronous motor (RSM) based on the running rotor technique. The applied flux linkage approximation functions reflect the self-saturation and cross-saturation effects, and the applied mathematical model is continuous and differentiable. The proper design of the experiment is discussed, and relevant recommendations are made to ensure the mitigation of procedural mistakes in the experiments. A detailed analysis of the impact of configuration faults on the obtained experimental data is provided, considering distortions in the obtained flux linkage and inductance surfaces. Considering the achieved model accuracy, a novel model evaluation considering the achieved model accuracy technique based on transient current response is proposed. [ABSTRACT FROM AUTHOR]

In response to the uncertainties and time-varying disturbances in the dynamic model of the 6-PSS parallel motion simulator, a robust control strategy based on sliding mode variable structure was proposed. Firstly, the dynamic model of the mechanism was established using the principle of virtual work. The dynamic model indicated that the 6-PSS parallel mechanism was a multivariable system with nonlinear and strongly coupled characteristics. The dynamic model was processed offline to reflect the actual dynamic characteristics of the mechanism and meet the real-time computational requirements of the device. Then, based on the simplified dynamic model, a global fast terminal sliding mode controller (GFTSMC) was designed. The Lyapunov function was employed to analyze the control law, demonstrating the stability of the controller. Finally, the control strategy was applied to the trajectory tracking control of the 6-PSS parallel motion simulator and compared with PD feedforward control and traditional sliding mode control (SMC) through experimental comparison. The research results indicate that, comparing to PD and SMC, GFTSMC reduces the average error by 82. 92% and 18. 88% respectively, and the standard deviation by 80. 03% and 41. 73% respectively. Moreover, it is capable of suppressing oscillations, making it an effective and practical robust control scheme for the 6-PSS parallel motion simulator. The research results can provide a theoretical basis for the control and engineering application of the 6-PSS parallel motion simulator. [ABSTRACT FROM AUTHOR]

Timing risk refers to a situation in which the timing of an economically important event is unknown (risky) from the perspective of an economic decision maker. While this special class of dynamic stochastic control problems has many applications in economics, the methods used to solve them are not easily accessible within a single, comprehensive survey. We provide a survey of dynamic optimization methods under comprehensive assumptions about the nature of timing risk. We also relax the assumption of full information and summarize optimization with limited information, ambiguity, imperfect hedging, and dynamic inconsistency. Our goal is to provide a concise user guide for specialists and nonspecialists alike. [ABSTRACT FROM AUTHOR]

Space robots are inseparable components of many space missions. However, capabilities of space robots with rigid manipulators are restricted in confronting with unknown and confined environments and situations require high safety. To overcome these defects, the potential of bio-inspired soft robots for space applications has recently been addressed in the literature. Dynamic modeling and control of soft manipulators are challenging due to their infinite degrees of freedom. In this paper, a general comprehensive three-dimensional dynamic modeling framework is developed for a floating soft manipulator-spacecraft system employing the Euler-Lagrange method. This framework derives the coupled equations of motion adapting the generalized Jacobian approach. Consequently, the opportunity of exploiting model-based control methods will be provided. In addition, the proposed model avoids numerical singularities once the bending angles are near zero. Furthermore, the generalized Jacobian matrix is defined for any arbitrary point of the soft manipulator essential for the contact dynamics. Eventually, to verify the proposed dynamic modeling procedure, the dynamic response of a floating soft manipulator-spacecraft system released from an initial configuration is investigated. Then, a sliding mode controller is designed for the floating soft manipulator to track the desired shape and compared to the proportional-derivative control scheme. The obtained results follow the physical principles and fulfill the control objective. • To overcome defects of usual rigid manipulators, soft space robots are concentrated. • A thorough 3D modeling frame is presented for soft manipulator-spacecraft systems. • Thorough dynamic modeling process is established using the Euler-Lagrange approach. • The generalized Jacobian matrix is derived for any optional point of the soft arm. • Application of the sliding mode control is proven for the soft space manipulator. [ABSTRACT FROM AUTHOR]

The tool-workpiece vibration in the precision milling process plays a pivotal role in influencing the surface quality. To solve the machining problem coming with the process vibration, the active vibration control model as well as the corresponding platform are developed, and the active vibration control algorithms are applied to reduce the relative vibrations and improve the surface quality. Firstly, the milling vibration reduction and surface quality improvement are modeled based on the active control algorithms and the system dynamic characteristics. Then, applying the different algorithm control strategies, such as PID, Fuzzy PID, BP neural network, and BP neural network PID control, the control effect is simulated and analyzed. Finally, an experimental platform is established to validate the system's reliability. The efficiency of various active control methods is compared in terms of frequency vibration control and surface finish roughness improvement. The results indicate that under different milling parameters, the four algorithm control strategies exhibit optimal effects of 13.5%, 30.4%, 28.8%, and 40.1% respectively. These findings provide valuable insights into selecting the optimal vibration control method for precision milling. [ABSTRACT FROM AUTHOR]

Purpose: The interest in applying and modeling dynamic MRS has recently grown. Two‐dimensional modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to one‐dimensional (1D) modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches. Methods: Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multitransient linear‐combination modeling (LCM) with 1D‐LCM of the average. A total of 2,500 data sets per condition with different noise representations of a 64‐transient MRS experiment at six signal‐to‐noise levels for two separate spin systems (scyllo‐inositol and gamma‐aminobutyric acid) were analyzed. Additional data sets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by SDs and Cramér‐Rao lower bounds (CRLBs). Results: Amplitude estimates for 1D‐ and 2D‐LCM agreed well and showed a similar level of bias compared with the ground truth. Estimated CRLBs agreed well between both models and with ground‐truth CRLBs. For correlated noise, the estimated CRLBs increased with the correlation strength for the 1D‐LCM but remained stable for the 2D‐LCM. Conclusion: Our results indicate that the model performance of 2D multitransient LCM is similar to averaged 1D‐LCM. This validation on a simplified scenario serves as a necessary basis for further applications of 2D modeling. [ABSTRACT FROM AUTHOR]

This study aimed to explore the challenges posed by air pollution near cement industry and the potential health impacts on residents. To address health risk associated with air pollution, a unique blend of environmental strategies was introduced by implementing measures such as increasing stack heights, planting trees known for particulate absorption, and promoting the use of protective masks. These interventions were strategically guided by dynamic modeling system implemented through STELLA software. The model predicted that the most efficient combination of treatments would take approximately 240 months to significantly reduce metal concentrations and associated carcinogenic risk for the nearest population. In scenarios where stack heights were increased by 60 m and 90 m, the effectiveness in lowering average metal concentration was 5.38% and 24.07%, respectively. Similarly, when 2550 and 3900 were trees planted, the effectiveness in reducing average metal concentration was 2.33% and 24.12%, respectively. The use of cloth masks led to a reduction in carcinogenic risk of 36.90% for adults and 36.93% for children. Meanwhile, the use of disposable masks led to a significant reduction of 96.30% for adults and 78.93% for children. The most effective approach for reducing airborne metal exposure was found to be the use of a multi-sectoral method that applied a combined optimistic scenario. The results provided valuable information on the understanding of the local-scale prediction of health hazards associated with metal exposure in ambient air. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) and photovoltaics (PVs) are expected to be broadly adopted in future power systems. However, the temporal variability of EV load and PV production presents challenges for integrating them into the power grid. This study evaluates and assesses the synergies between EVs and PV systems to maximize solar energy utilization for EV load coverage. The configurations studied include EV charging via the national grid as a reference case (Case 1) and two solar energy harvesting options: EVs powered directly by vehicle-mounted PVs (Case 2) and EV chargers connected to residential PV installations (Case 3). These cases are evaluated across different urban environments with large EV fleets and dissimilar weather conditions: Berlin and Los Angeles. A customized operation profile based on the worldwide harmonized light-duty test cycle (WLTC) and a charge-right-away (CRA) strategy is used. Energy performance analysis is conducted through dynamic simulations using the Modelica language, with environmental and economic indices derived. Key findings highlight the superior performance of residential PV systems in both cities compared to current solar EV technologies, with both solutions offering significant benefits over the reference case. Cases 2 and 3 result in a 44% and 59% reduction in annual energy consumption, greenhouse gas emissions, and charging costs in Berlin, while in Los Angeles, the reductions are 67% and 98%. The average daily solar driving range reaches 20.3% in Berlin and 30.4% in Los Angeles. [ABSTRACT FROM AUTHOR]

In 2022, global poliovirus modeling suggested that coordinated cessation of bivalent oral poliovirus vaccine (bOPV, containing Sabin-strain types 1 and 3) in 2027 would likely increase the risks of outbreaks and expected paralytic cases caused by circulating vaccine-derived polioviruses (cVDPVs), particularly type 1. The analysis did not include the implementation of planned, preventive supplemental immunization activities (pSIAs) with bOPV to achieve and maintain higher population immunity for types 1 and 3 prior to bOPV cessation. We reviewed prior published OPV cessation modeling studies to support bOPV cessation planning. We applied an integrated global poliovirus transmission and OPV evolution model after updating assumptions to reflect the epidemiology, immunization, and polio eradication plans through the end of 2023. We explored the effects of bOPV cessation in 2027 with and without additional bOPV pSIAs prior to 2027. Increasing population immunity for types 1 and 3 with bOPV pSIAs (i.e., intensification) could substantially reduce the expected global risks of experiencing cVDPV outbreaks and the number of expected polio cases both before and after bOPV cessation. We identified the need for substantial increases in overall bOPV coverage prior to bOPV cessation to achieve a high probability of successful bOPV cessation. [ABSTRACT FROM AUTHOR]

Background Despite multiple revisions of targets and timelines in polio eradication plans since 1988, including changes in supplemental immunization activities (SIAs) that increase immunity above routine immunization (RI) coverage, poliovirus transmission continues as of 2024.Methods We reviewed polio eradication plans and Global Polio Eradication Initiative (GPEI) annual reports and budgets to characterize key phases of polio eradication, the evolution of poliovirus vaccines, and the role of SIAs. We used polio epidemiology to provide context for successes and failures and updated prior modeling to show the contribution of SIAs in achieving and maintaining low polio incidence compared to expected incidence for the counterfactual of RI only.Results We identified multiple phases of polio eradication that included shifts in targets and timelines and the introduction of different poliovirus vaccines, which influenced polio epidemiology. Notable shifts occurred in GPEI investments in SIAs since 2001, particularly since 2016. Modeling results suggest that SIAs play(ed) a key role in increasing (and maintaining) high population immunity to levels required to eradicate poliovirus transmission globally.Conclusions Shifts in polio eradication strategy and poliovirus vaccine usage in SIAs provide important context for understanding polio epidemiology, delayed achievement of polio eradication milestones, and complexity of the polio endgame.

ABSTRACTBackground New York State (NYS) reported a polio case (June 2022) and outbreak of imported type 2 circulating vaccine-derived poliovirus (cVDPV2) (last positive wastewater detection in February 2023), for which uncertainty remains about potential ongoing undetected transmission.Research Design and Methods Extending a prior deterministic model, we apply an established stochastic modeling approach to characterize the confidence about no circulation (CNC) of cVDPV2 as a function of time since the last detected signal of transmission (i.e. poliovirus positive acute flaccid myelitis case or wastewater sample).Results With the surveillance coverage for the NYS population majority and its focus on outbreak counties, modeling suggests a high CNC (95%) within 3–10 months of the last positive surveillance signal, depending on surveillance sensitivity and population mixing patterns. Uncertainty about surveillance sensitivity implies longer durations required to achieve higher CNC.Conclusions In populations that maintain high overall immunization coverage with inactivated poliovirus vaccine (IPV), rare polio cases may occur in un(der)-vaccinated individuals. Modeling demonstrates the unlikeliness of type 2 outbreaks reestablishing endemic transmission or resulting in large absolute numbers of paralytic cases. Achieving and maintaining high immunization coverage with IPV remains the most effective measure to prevent outbreaks and shorten the duration of imported poliovirus transmission.

This paper presents an analysis of the operating characteristics of a chemisorption heat pump. 1-D transient model of a chemisorption heat pump was developed, for which an analysis of four alternating modes of operation was performed. The performance was analyzed with respect to the operating time of the adsorption and desorption operation modes during alternating operations, and the results showed that the cooling capacity has an optimum point depending on the operating times. It was also confirmed that the coefficient of performance increases as the operating time increases. The system performance was also analyzed according to the flow rates of the secondary fluids supplied to the main components. As the flow rates of the secondary fluids supplied to the main components increased, the cooling capacity improved, and the coefficient of performance was found to be compounded by the secondary flow conditions and the operating times of the adsorption and desorption operation modes. Based on the results, it was found that the cooling capacity, coefficient of performance, and specific cooling power of the chemisorption heat pump can be operated in a large range from 876.7 to 3070.0 W, 0.13 to 0.32, and 39.3 to 137.7 W/kg, respectively, depending on the operating conditions. [ABSTRACT FROM AUTHOR]

Abstract A dual-arm nursing robot can gently lift patients and transfer them between a bed and a wheelchair. With its lightweight design, high load-bearing capacity, and smooth surface, the coupled-drive joint is particularly well suited for these robots. However, the coupled nature of the joint disrupts the direct linear relationship between the input and output torques, posing challenges for dynamic modeling and practical applications. This study investigated the transmission mechanism of this joint and employed the Lagrangian method to construct a dynamic model of its internal dynamics. Building on this foundation, the Newton-Euler method was used to develop a dynamic model for the entire robotic arm. A continuously differentiable friction model was incorporated to reduce the vibrations caused by speed transitions to zero. An experimental method was designed to compensate for gravity, inertia, and modeling errors to identify the parameters of the friction model. This method establishes a mapping relationship between the friction force and motor current. In addition, a Fourier series-based excitation trajectory was developed to facilitate the identification of the dynamic model parameters of the robotic arm. Trajectory tracking experiments were conducted during the experimental validation phase, demonstrating the high accuracy of the dynamic model and the parameter identification method for the robotic arm. This study presents a dynamic modeling and parameter identification method for coupled-drive joint robotic arms, thereby establishing a foundation for motion control in humanoid nursing robots.

This study investigates a novel approach for assessing the health status of rotating machinery transmission systems by analyzing the dynamic degradation of bearings. The proposed method generates multi-dimensional data by creating virtual states and constructs a multi-dimensional model using virtual state-space in conjunction with mechanism model analysis. Innovatively, the Hammerstein–Wiener (HW) modeling technique from control theory is applied to identify these dynamic multi-dimensional models. The modeling experiments are performed, focusing on the model's input and output types, the selection of nonlinear module estimators, the configuration of linear module transfer functions, and condition transfer. Dynamic degradation response signals are generated, and the method is validated using four widely recognized databases consisting of accurate measurement signals collected by vibration sensors. Experimental results demonstrated that the model achieved a modeling accuracy of 99% for multiple bearings under various conditions. The effectiveness of this dynamic modeling method is further confirmed through comparative experimental data and signal images. This approach offers a novel reference for evaluating the health status of transmission systems. [ABSTRACT FROM AUTHOR]

A dynamic numerical model is developed considering in-plane and out-of-plane behaviour and their interaction for the novel energy dissipating hysteretic infill and conventional brick infill system. The response of three-story infilled buildings under earthquake excitations shows a significant performance improvement in the energy dissipating hysteretic infilled building. The novel infill system resists the formation of the soft-story mechanism with enhanced overall structural performance, and a reduced number of infill failures compared with the conventional infilled buildings. This is mainly due to its low stiffening effect, better post-peak response in the in-plane direction and improved out-of-plane deformation capacity and bi-axial stability. [ABSTRACT FROM AUTHOR]

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The interaction between the double pendulum and nonlinear sloshing in two cranes transporting a liquid tank corrupts the efficiency and safety of the cooperative transportation. Although significant work has been directed at the double-pendulum dynamics of industrial cranes and the liquid-sloshing dynamics in the moving tank, less effort has been focused on the interaction between the double pendulum and nonlinear sloshing. An analytical model of two cranes carrying a liquid tank has been derived in this article. The interaction between the double pendulum and nonlinear sloshing has been captured by the model. Furthermore, a new method has been developed to control coupled oscillations caused by the interaction. Simulated and experimental data obtained from a testbench of two cranes carrying a liquid tank validated the effectiveness of the dynamic modeling and vibration control methods. [ABSTRACT FROM AUTHOR]

A dual-arm nursing robot can gently lift patients and transfer them between a bed and a wheelchair. With its lightweight design, high load-bearing capacity, and smooth surface, the coupled-drive joint is particularly well suited for these robots. However, the coupled nature of the joint disrupts the direct linear relationship between the input and output torques, posing challenges for dynamic modeling and practical applications. This study investigated the transmission mechanism of this joint and employed the Lagrangian method to construct a dynamic model of its internal dynamics. Building on this foundation, the Newton-Euler method was used to develop a dynamic model for the entire robotic arm. A continuously differentiable friction model was incorporated to reduce the vibrations caused by speed transitions to zero. An experimental method was designed to compensate for gravity, inertia, and modeling errors to identify the parameters of the friction model. This method establishes a mapping relationship between the friction force and motor current. In addition, a Fourier series-based excitation trajectory was developed to facilitate the identification of the dynamic model parameters of the robotic arm. Trajectory tracking experiments were conducted during the experimental validation phase, demonstrating the high accuracy of the dynamic model and the parameter identification method for the robotic arm. This study presents a dynamic modeling and parameter identification method for coupled-drive joint robotic arms, thereby establishing a foundation for motion control in humanoid nursing robots. [ABSTRACT FROM AUTHOR]

Collaborative robotics is a field of growing industrial interest, within which understanding the energetic behavior of manipulators is essential. In this work, we present the electro-mechanical modeling of the UR5 e-series robot through the identification of its dynamics and electrical parameters. By means of the identified robot model, it is then possible to compute and optimize the energy consumption of the robot during prescribed trajectories. The proposed model is derived from data acquired from the robot controller during bespoke experimental tests, using model identification procedures and datasheet provided by manipulator, motors, and gearbox manufacturers. The entire procedure does not require the use of any additional sensor, so it can be easily replicated with an off-the-shelf manipulator, and applied to other robots of the same family. [ABSTRACT FROM AUTHOR]

Dynamic models that consider multiple nonlinear factors including the two-dimensional deformation and higher-order modes are too computationally complex to be suitable for real-time control of the rotating Euler-Bernoulli beam. This article proposes a new dynamic modeling method according to the assumed mode method. The new modeling method not only has high modeling accuracy but also has a brief mathematical expression. In addition, based on the new modeling method, a neural network sliding mode control strategy using the saturation function is designed to improve the rotational accuracy of the Euler-Bernoulli beam. In the control law design, the saturation function is proposed instead of the unit step function to reduce the chattering phenomenon. Simulation and control experiments describe that the new dynamic modeling method has higher modeling accuracy than the modeling method based on the one-dimensional deformation; the proposed strategy can effectively decrease the rotation angle tracking error of the rotating Euler-Bernoulli beam and improve the control accuracy. [ABSTRACT FROM AUTHOR]

This study delves into the factors that affect the reliability of satellite antenna deployment mechanisms. It employs the Kolmogorov–Smirnov (K‐S) test to quantify uncertainty characteristics, leading to the acquisition of pertinent stochastic parameters. Subsequently, three‐dimensional models and finite element models of the satellite antenna deployment mechanism are established using SOLIDWORKS and ANSYS software. Modal distribution, harmonic response analysis, random vibration analysis, and deployment process simulation are conducted. Parameterized modeling of the deployment mechanism's dynamics simulation process is performed, taking into consideration parameter uncertainty. Finally, a Kriging surrogate model is utilized to formulate an approximate expression between the factors influencing the reliability of the antenna deployment mechanism and its dynamic response. Based on the general stress‐strength interference theory, a reliability analysis model is constructed. Combined with active learning algorithms, this approach achieves efficient and precise calculations of the reliability of the satellite antenna deployment mechanism. [ABSTRACT FROM AUTHOR]

Space robots have proven their ability to accomplish many space missions impossible or dangerous for the human. However, the conventional space robots suffer from the low adaptability, heavy structures, and the low safety. In this regard, the bio-inspired soft robots, composed of the soft material, have been emerged to overcome these shortcomings and to expand the space missions' diversity. The potential of soft robots for space applications has recently been investigated in the literature. Although the dynamic modeling and control of soft robotic arms are complicated due to their infinite degrees of freedom, soft manipulators are anticipated to provide the adaptive capture of targets, confined space operations, and the long-distance handling of space facilities. In this regard, a general novel dynamic modeling algorithm is presented here for soft space robotic manipulators (SSRM) in a specified orientation based on the generalized Jacobian method. The proposed algorithm could be employed for different numbers of soft manipulator constant-curvature elements and avoids numerical singularities using the Taylor expansion as well. In addition, the generalized Jacobian matrix is defined to compute the velocity of any arbitrary point on the soft manipulator for contact dynamics objectives. Accuracy of the proposed dynamic model has been verified via comparison to the simulation results of the existing fixed-base soft manipulators. Moreover, performance of the proposed model has been more investigated through two numerical simulation case studies. The first case verifies that the dynamic responses of the floating SSRM follows the physical principles. While the second one addresses the configuration tracking problem of the floating SSRM exposing a computed torque control scheme. The obtained results indicate the effectiveness of the presented dynamic modeling algorithm and the proposed control scheme. [ABSTRACT FROM AUTHOR]

Bearing deflection has a direct impact on the mesh condition of gear systems via the center distance of the gear pair and corner contact. These factors need to be considered to accurately model the time-varying mesh stiffness and dynamic responses of gears. To address this issue, a spatial coordinate conversion is used to obtain the instantaneous spatial position of the gear pair under the bearing deflection. The tooth pair separation distance is derived through the geometric relationship analysis to model the corner contact effect. A dynamic model is established which employs a step-to-step time integration algorithm that considers the coupling effect between bearing deflection and time-varying mesh stiffness to obtain the dynamic response of the spur gear system. The simulation results of the proposed model show good agreement with the experimental results which demonstrate that the proposed model enables a proper analysis of the influence of bearing deflection on gear mesh behavior. This study provides an original dynamic model for analyzing the dynamic performance of the gear system considering the influence of bearing deflection. [ABSTRACT FROM AUTHOR]

At present, reusable launch vehicle technology (RLV) has become a research hotspot in the aerospace field and one of the major development trends in this industry. With reference to the aircraft carrier's arresting cable technology, this paper puts forward a novel cable-net buffer device for recovering the first stage of launch vehicle. The device can transfer load through a cable-pulley mechanism, and then complete the first stage recovery by losing the kinetic energy and gravitational potential energy of the first stage through hydraulic dampers and preloaded counterweights. In order to analyze the performance of this cable-net buffer device, the finite element software ABAQUS is adopted to establish a rigid-flexible coupling dynamic model. In this model, the cable-pulley mechanism is simulated by connector and shell elements, the damping force of the hydraulic dampers by VUAMP subroutine, and the preloaded counterweights by mass point. And then, performance evaluation indexes of this buffer device are proposed in this paper. Meanwhile, the dynamic simulation, using the established dynamic model, is carried out under different device design parameters and working condition parameters. On the one hand, the simulation results show that the tower span and damping force have remarkable effects on the buffer performance. On the other hand, among all working condition parameters, only the fall point deviation has a significant effect on the buffer performance, but this effect is less than that of the design parameters. Finally, combing the dynamic model and the surrogate model technique, this paper obtains feasible boundaries of design parameters of the device for the subsequent detailed design of it. Researches in this paper will provide new ideas for the development of RLV. [ABSTRACT FROM AUTHOR]

Connecting the chemical industry with the academic environment has created a unique opportunity to apply experiential learning in many areas of teaching. A new approach of using the existing operator training simulator, which is basically a digital twin of a new dicyclopentadiene plant, was used to educate and train students from technical universities. Using this simulator, students can gain adequate knowledge for control, process optimization, and problem solving under nonstandard operating conditions. Simulating a dynamic process in the Aspen HYSYS interface along with elements of a real industrial control system and control interface, and especially the online visualization of the results, helps students understand the physicochemical principles through their own intervention and experience of the consequences. The training simulator's ability to accurately reflect ongoing processes can be verified by students during a guided tour of a production plant. The experience with student learning so far shows that this is a very attractive and, above all, effective tool for extending the teaching of chemical engineering, control, and automation of chemical processes. [ABSTRACT FROM AUTHOR]

Training studies typically investigate the cumulative rather than the analytically challenging immediate effect of exercise on cognitive outcomes. We investigated the dynamic interplay between single‐session exercise intensity and time‐locked recognition speed‐accuracy scores in older adults with Alzheimer's dementia (N = 17) undergoing a 24‐week dual‐task regime. We specified a state‐of‐the‐art hierarchical Bayesian continuous‐time dynamic model with fully connected state variables to analyze the bi‐directional effects between physical and recognition scores over time. Higher physical performance was dynamically linked to improved recognition (−1.335, SD = 0.201, 95% Bayesian credible interval [BCI] [−1.725, −0.954]). The effect was short‐term, lasting up to 5 days (−0.368, SD = 0.05, 95% BCI [−0.479, −0.266]). Clinical scores supported the validity of the model and observed temporal dynamics. Higher physical performance predicted improved recognition speed accuracy in a day‐by‐day manner, providing a proof‐of‐concept for the feasibility of linking exercise training and recognition in patients with Alzheimer's dementia. Highlights: Hierarchical Bayesian continuous‐time dynamic modeling approachA total of 72 repeated physical exercise (PP) and integrated recognition speed‐accuracy (IRSA) measurementsPP is dynamically linked to session‐to‐session variability of IRSAHigher PP improved IRSA in subsequent sessions in subjects with Alzheimer's dementiaShort‐term effect: lasting up to 4 days after training session [ABSTRACT FROM AUTHOR]

This paper envisages studying the features of a conventional inductive ignition system along with its MOSFET and IGBT-based transistorized modifications. The influence of mechanical contact breaker dynamics and ignition coil characteristics on the current and voltage waveforms of the primary and secondary circuits of these studied ignition systems are mathematically and experimentally exposed. The investigation is considered necessary prior to attempting subsequent modeling and diagnostics procedures on the current-voltage performance characteristics of conventional and transistorized ignition systems. The work has demanded the development of an experimental setup based on a basic modifiable ignition system mockup and an instrumentation system to measure and analyze the voltage-current parameters of inductive ignition systems. The paper describes the design details of such instrumentation system, presents mechanical and electrical models for contact breaker and ignition circuits, then simulated to obtain base free-run response waveforms and electrical continuity behavior of the contact. A test of frequency response of the ignition coil provided additional input to the model. An experimental test of continuity of the contact, in agreement with its model, shed light on the actual excitation of the primary coil. The work comments on a sample of the registered current and voltage waveforms in primary and secondary coil windings of the ignition system at atmospheric conditions. Comparisons of waveforms and energy for mechanical contact, MOSFET and IGBT switches are made to establish them as a reference for future tests. [ABSTRACT FROM AUTHOR]

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Voronoi diagram on the Earth's surface is a significant data model, characterized by natural proximity and dynamic stability, which has emerged as one of the most promising solutions for global spatial dynamic management and analysis. However, traditional algorithms for generating spherical raster Voronoi diagrams find it challenging to dynamically adjust the Voronoi diagram while maintaining precision and efficiency. The efficient and accurate construction of the spherical Voronoi diagram has become one of the bottleneck issues limiting its further large-scale application. To this end, this paper proposes a dynamic construction scheme for the spherical Voronoi diagram based on the QTM (Quaternary Triangular Mesh) system, with the aim of enabling efficient generation, local updates, and multi-scale visualization of the spherical Voronoi diagrams. In this paper, canonical ordering is introduced. Tailored for the properties of the spherical triangular grid, it constructs a unified and standardized sorting strategy for the dilation of the spherical grids. The construction and updating of the spherical Voronoi diagram are achieved through the ordered dilation of sites. Furthermore, the multi-scale visualization of the spherical Voronoi diagram is realized through the hierarchical structure of the QTM. The paper presents our algorithm intuitively through pseudocode, conducts comparative experiments on the feasibility and efficiency, and designs an experiment for the dynamic navigation and management of ocean-going vessels based on the global multi-resolution Voronoi diagram. The experimental results demonstrate that our algorithm effectively controls the error of the generation of the raster Voronoi diagram and has a significant efficiency advantage when processing dynamic environments. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The long-term value of immunopsychiatry will be based on its ability to translate basic science into effective clinical interventions. In this article, we discuss a key obstacle to achieving this important translational goal-namely, the preponderance of studies that are cross-sectional, or that have months-to-years long follow-up periods. Immunopsychiatric processes such as stress, inflammation, and depression symptoms are inherently dynamic and fluctuate over hours, days, and weeks. This fact suggests that higher-density data collection with only days between measurements is necessary to capture-with adequate resolution-the actual dynamics of these systems, determine optimal time lags with which to observe associations between variables of interest, and maximize the translational potential of these data. To illustrate these points, we use pilot data from our own intensive longitudinal immunopsychiatric study. We then conclude by making several recommendations for future research. By learning how to better use existing data for dynamically informative studies as well as collecting intensive longitudinal data, we believe immunopsychiatry will be much better positioned to advance our causal understanding of the interplay between the immune system and health.

The study presents an innovative solar-assisted dual-tank direct contact membrane distillation (DCMD) system designed to enhance the operational stability and efficiency of solar-powered desalination. The proposed system integrates a dual thermal storage tank configuration, allowing for continuous operation by alternating between two tanks that store pre-heated water, thereby mitigating the impact of solar energy fluctuations. The dynamic modeling approach used in this study predicts the system's performance under varying solar conditions, focusing on key parameters such as permeate flux, evaporation efficiency, and specific thermal energy consumption. The simulation results show that the system achieves an average permeate flux of 14.4 L/h m² and a thermal efficiency of 53.3 % at a hot water temperature of 60 °C, with a corresponding average specific thermal energy consumption of 1567 kWh/m³. These findings highlight a substantial improvement in both thermal efficiency and water production compared to conventional single-tank systems.The dual-tank DCMD system is particularly suited for deployment in remote or arid regions where stable and efficient freshwater production is critical. This research provides a comprehensive analysis of a novel solar-assisted desalination technology, contributing to the advancement of sustainable water resources management by providing a reliable and scalable solution that can maintain high operational efficiency even in remote areas with variable solar conditions.

A two-component system for control and monitoring of solar power towers with molten salt receivers is proposed. The control component consists of a model predictive control application (MPC) with a flexible objective function and on-line tunable weights, which runs on a Industrial PC and uses a reduced order dynamic model of the receiver’s thermal and flow dynamics. The second component consists of a service-life monitoring unit, which estimates the service-life consumption of the absorber tubes depending on the current mode of operation based on thermal stresses and creep fatigue in the high temperature regime. The calculation of stresses is done based on a detailed finite element study, in which a digital twin of the receiver was developed. By parallelising the model solver, the estimation of service-life consumption became capable of real-time operation. The system has been implemented at a test facility in Jülich, Germany, and awaits field experiments. In this paper, the modeling and architecture are presented along simulation results, which were validated on a hardware-in-the-loop test bench. The MPC showed good disturbance rejection while respecting process variable constraints during the simulation studies.