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Introduction: Antimicrobial resistance (AMR) is a growing threat to the efficacy of antimicrobials in humans and animals, including those used to control bovine respiratory disease (BRD) in high-risk calves entering western Canadian feedlots. Successful mitigation strategies require an improved understanding of the epidemiology of AMR. Specifically, the relative contributions of antimicrobial use (AMU) and contagious transmission to AMR emergence in animal populations are unknown. Materials and methods: A stochastic, continuous-time agent-based model (ABM) was developed to explore the dynamics of population-level AMR in Mannheimia haemolytica in pens of high-risk cattle on a typical western Canadian feedlot. The model was directly informed and parameterized with proprietary data from partner veterinary practices and AMU/AMR surveillance data where possible. Hypotheses about how AMR emerges in the feedlot environment were represented by model configurations in which detectable AMR was impacted by (1) only selection arising from AMU; (2) only transmission between animals in the same pen; and (3) both AMU-linked selection and transmission. Automated calibration experiments were used to estimate unknown parameters of interest for select antimicrobial classes. Calibrated parameter values were used in a series of Monte Carlo experiments to generate simulated outputs at both the pen and feedlot levels. Key model outputs included the prevalence of AMR by class at multiple time points across the feeding period. This study compared the relative performances of these model configurations with respect to reproducing empirical AMR data. Results: Across all antimicrobial classes of interest, model configurations which included the potential for contagious acquisition of AMR offered stronger fits to the empirical data. Notably, sensitivity analyses demonstrated that model outputs were more robust to changes in the assumptions underscoring AMU than to those affecting the likelihood of transmission. Discussion: This study establishes a feedlot simulation tool that can be used to explore questions related to antimicrobial stewardship in the context of BRD management. The ABM stands out for its unique hierarchical depiction of AMR in a commercial feedlot and its grounding in robust epidemiological data. Future experiments will allow for both AMU-linked selection and transmission of AMR and can accommodate parameter modifications as required. [ABSTRACT FROM AUTHOR]

Background: Undernutrition remains a global crisis and is a focus of Sustainable Development Goals. While there are multiple known, effective interventions, complex interactions between prevention and treatment and resource constraints can lead to difficulties in allocating funding. Simulation studies that use in silico simulation can help illuminate the interactions between interventions and provide insight into the cost-effectiveness of alternative packages of options. Methods: We developed an individual-based microsimulation model based on the Global Burden of Disease (GBD) 2021 study data to test a range of nutrition interventions, including antenatal interventions (iron and folic acid, multiple micronutrients, and balanced energy protein supplementation) and child interventions (treatment for severe acute malnutrition, treatment for moderate acute malnutrition, and wasting prevention with small-quantity lipid-based nutrient supplements). We also developed an analytic approach to process the results of the microsimulation and identify the optimal intervention funding allocation for a given budget size. We use Ethiopia as an example in this paper. Results: In our illustrative example of Ethiopia, the reallocation of the baseline budget to minimize disability-adjusted life years (DALYs) resulted in first funding the antenatal multiple micronutrients to their maximum coverage and then funding treatment for severe child acute malnutrition. Relative to the baseline allocation, the reallocation optimized to minimizing DALYs resulted in 592,000 fewer annual DALYs, constituting an 8.3% reduction in total DALYs in Ethiopia. For budgets larger than the baseline, our model recommended funding first targeted moderate acute malnutrition treatment, second universal moderate acute malnutrition treatment, third wasting prevention with small-quantity lipid-based nutrient supplements, and fourth balanced energy protein supplementation. Conclusions: Our simulation is a novel model for estimating optimal allocation of spending on antenatal and child health nutrition interventions which accounts for the interaction between preventive and therapeutic approaches. Our illustrative results show that an optimized reallocation of current spending can substantially improve pregnancy-related and child health without additional funding. We hope this model can add validity and confidence to prior results to aid stakeholders in funding decisions. [ABSTRACT FROM AUTHOR]

Highly fecund invaders and size‐selective suppression efforts often limit the effectiveness of invasive species control programs, as compensatory processes can allow suppressed populations to recover. While population models have long explored how demographic characteristics impact management feasibility, there is a growing need to evaluate how the selectivity of suppression efforts might impact the long‐term feasibility of control. We use a simulation framework that integrates age‐based selectivity to evaluate the effect of increasing the range of ages selected for during harvest‐based invasive species control. We applied this approach to common carp in Utah Lake, the location of one of the world's largest freshwater vertebrate species control programs, to assess how selectivity impacts the level of control effort necessary to achieve management targets. Model simulations suggest that increasing the range of ages effectively targeted by removal gears has the potential to significantly reduce the amount of effort required to reach control targets. We found that increasing selectivity on younger, but mature, age classes allowed the control program to maintain the carp population below the 75% biomass reduction target with only 2.5 times the maximum historic effort level, while further increasing juvenile selectivity conferred minimal benefit. Furthermore, we evaluated historic levels of harvest effort against both previously set management targets and theoretical sustainable harvest targets (MSY). The historic level of suppression effort was less than that required to produce MSY regardless of the selectivity scenario explored, suggesting the control program would be harvesting at a sustainable rate even if it increases the range of ages effectively targeted by removal gears. Synthesis and applications. Controlling highly fecund invasive species becomes much more feasible if managers can identify an approach that targets all adult age classes. Explicitly considering sustainable harvest metrics provides a framework for evaluating a harvest control program's ability to overcome density‐dependent processes and achieve management objectives. [ABSTRACT FROM AUTHOR]

Response to animal disease has importance for domestic supply and demand, trade implications, and other economic factors. Stamping out is effective at eradicating disease but requires resource investments that may be prohibitive in large-scale animal production systems. Alternative management strategies in a 50,000-head cattle feedlot are examined. Sample feedlot and epidemiological data are utilized for a discrete programming model. We analyze 14 scenarios across five management strategies under stochastic cattle prices and static disease management costs. Results show that targeted depopulation is a preferred method for the overall feedlot. [ABSTRACT FROM AUTHOR]

The housed environment for dairy cattle is of critical importance to their health, wellbeing, and productivity. Lack of space is an important factor for housing quality assessment due to links with increased likelihood of disease. A recently published randomized controlled trial identified that greater living space provision increased lying time, milk volume production, and also increased time to conception. However, despite probable improvements in cow welfare, the question remains as to whether offering increased living space is a cost-effective option for farmers. The costs associated with financing new housing facilities are escalating, and the industry urgently requires an evidence base for ensuring these investments are financially sustainable. This research used stochastic simulation modeling to explore theoretical net returns on infrastructure investment differences between two living space scenarios (3 m2 vs. 6.5 m2). A cow entered a simulation at the point of first calving, and milk production, reproductive performance, and points of exit were stochastically determined over the cow's lifetime simultaneously based on living space scenario. This allowed for direct financial comparison over specified sets of parameter inputs. Where cows exited the herd within their second to fourth lactation, the median difference in financial return was observed to be +£87.61 per cow per year (mean + £86.74). The estimated return on investment to provide extra living space access varied dependent on provision method, interest rates, and loan repayment duration. Under the circumstances and contexts investigated, the results suggest that building for increased living space would be cost-effective. When building a new shed with a high living space versus control at a 4.00% interest rate, a median net return on infrastructure investment of +£23.00 per cow per year was identified (range –£25.91 to +£64.16 for 10th to 90th percentile). Since decreased living space is likely to lead to poorer welfare, it can be considered a negative production externality associated with current production systems, the cost of which should also be accounted for when analyzing the economics of housing. Further research is essential to gain a complete understanding of the cost-effectiveness of providing increased living space per cow under different management scenarios. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) printing technology presents a promising avenue for the development of affordable neurosurgical simulation models, addressing many challenges related to the use of cadavers, animal models, and direct patient engagement. The aim of this study is to introduce and evaluate a new high-fidelity neurosurgical simulation model targeted for both burr hole and craniotomy procedures. 12 different 3D-printed skull models were manufactured using 5 different materials (polyether ether ketone, White Resin, Rigid 10K, BoneSTN, and SkullSTN) from 3 different 3D print processes (fused filament fabrication, stereolithography [SLA], and material jetting). Six consultant neurosurgeons conducted burr holes and craniotomies on each sample while blinded to these manufacturing details. Participants completed a survey based on the qualities of the models, including mechanical performance, visual appearance, interior feeling, exterior feeling, sound, overall quality, and recommendations for training purposes based on their prior experience completing these procedures on human skulls. This study found that the multimaterial SLA-printed models consisting of White Resin for the outer table and Rigid 10K for the diploe and inner table were successful in replicating a human skull for burr hole and craniotomy simulation. This was followed by the porous General BoneSTN preset material on a Stratasys J750 Digital Anatomy Printer. The findings indicate that widely accessible and economical desktop SLA 3D printers can provide an effective solution in neurosurgical training, thus promoting their integration in hospitals. [ABSTRACT FROM AUTHOR]

To explore the effect of greenhouse microclimate on the growth of protected tomatoes, two models were established: one for simulating the transverse diameter and another for the single fruit weight. These models incorporated accumulated radiation-heat and the rice clock model, utilizing data on the transverse diameter and single fruit weight of protected tomatoes, as well as concurrent meteorological data including illumination, temperature, and humidity from the greenhouse at Hefei Agricultural Meteorological Experiment Station for the years 2022 and 2023. The accuracy of both was verified using experimental data from 2022. Results indicated that both models effectively simulated the transverse diameter and single fruit weight of protected tomatoes, respectively. The transverse diameter model achieved a root mean square error (RMSE) of 1.03mm, a mean absolute error (MAE) of 0.84mm, and a mean relative error (MRE) of 7.5%. The single fruit weight model achieved an RMSE of 692.59mg, an MAE of 395.44mg, and MRE of 8.2%. Decision coefficients exceeded 0.98 for both models, suggesting they possess practical value and can provide a theoretical foundation for environmental regulation in protected tomato cultivation. [ABSTRACT FROM AUTHOR]

The study established that the application of graph theory enables the creation of a model of a country's power system structure in the form of a tiered graph. This allows complex structural elements of the system, such as generating units, electrical substations, and power transmission lines, to be represented as nodes and edges in simulation models that can be used for analysis, dispatch control, and optimization of system operation. A simulation model of the unified power system has been developed to analyze operational efficiency and performance under various planned disturbance scenarios. To solve the given task, it is necessary to develop a model of the power system in the form of a tiered graph, where the nodes are generating equipment stations, transmission system substations with voltages from 330 kV to 750 kV, and distribution system substations with voltages from 110 kV to 220 kV, and the edges are power transmission lines with voltages from 110 kV to 750 kV. The model takes into account the generated and transmitted power, the nominal capacity and the number of transformers at the substations, the cross-section and maximum throughput of the power transmission lines, which made it possible to determine complex interconnections between its nodes and integrate the equipment into a unified power system for efficiency and performance analysis. [ABSTRACT FROM AUTHOR]

The optimization management of complex production processes is the key to enhancing the competitiveness of enterprises in modern manufacturing. Traditional optimization methods often struggle to manage the dynamic and intricate nature of production environments, highlighting the need for more intelligent and efficient approaches. As an advanced technique in artificial intelligence, Deep Reinforcement Learning (DRL) has demonstrated significant potential in addressing high-dimensional, nonlinear dynamic system optimization through interactive learning with the environment. However, current research approaches face limitations in handling the diversity and dynamism inherent in complex production workflows. In this study, a simulation model was constructed to accurately represent realworld production processes, which was subsequently employed as the basis for DRL-driven optimization. Results indicate that this method effectively enhances the overall performance and adaptability of production systems, providing robust support for advancements in smart manufacturing and Industry 4.0. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Henan Agricultural Sciences is the property of Editorial Board of Journal of Henan Agricultural Sciences 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.)

This paper introduces a control method tailored for the speed regulation of monorail cranes in coal mines. Initially, an analysis of the structure and load conditions of the monorail crane drive components is conducted to calculate the traction force, clamping force, and target travel speed across varying operational scenarios. Subsequently, the hydraulic system schematic of the monorail crane is analyzed to develop a mathematical model for speed control, enabling the assessment of system stability using transfer functions. A simulation model of the monorail crane speed control loop is then created in AMESim, where fuzzy adaptive PID controllers and MPC controllers are optimized in a collaborative simulation with Simulink. Experimental findings reveal that in a single acceleration condition, both controllers demonstrate superior dynamic response compared to a traditional PID controller, with the MPC controller exhibiting an overshoot of merely 8.9%. In speed variation conditions, the MPC controller achieved a settling time in the range of 0.26–0.3 s. Notably, the MPC controller displays a maximum overshoot of 11%, substantially enhancing the dynamic response performance of speed regulation in monorail cranes. [ABSTRACT FROM AUTHOR]

This paper examines how the unidirectional alignment of a selected street affects traffic load at nearby signal-controlled intersections. Using the Aimsun 8 simulation model, the intersections in the city of Topoľčany were evaluated. A simulation model was created based on a traffic survey conducted by video detection at selected signal-controlled intersections. Both the negative and positive impacts of this modification were analyzed. This study shows a significant deterioration in the traffic situation. This paper further investigates the improvement achieved through corrective measures such as implementing an actuated control plan, modifying signal plans, and coordinating traffic flows. The results show the effectiveness of these measures in reducing congestion and improving traffic flow. They also serve as a foundation for optimizing traffic systems and implementing measures to improve urban mobility. [ABSTRACT FROM AUTHOR]

This study focuses on optimizing traffic flow at uncontrolled intersections by comparing the effectiveness of different intersection types: roundabouts, signal-controlled intersections, and turbo-roundabouts. The purpose is to determine which type offers the best solution for enhancing traffic efficiency, reducing delays, and improving safety. The research employs simulation-based modeling to analyze traffic performance under varying traffic conditions. Critical parameters such as vehicle flow rate, average delay time, and capacity are used to assess the performance of each intersection type. The results indicate that turbo-roundabouts outperform conventional roundabouts and signal-controlled intersections in terms of both capacity and reduction in delays. The findings suggest that implementing turbo-roundabouts at high-traffic intersections can significantly improve traffic flow and reduce congestion. However, the effectiveness of each solution is context-dependent, with signal-controlled intersections still being advantageous under specific conditions, particularly in highly urbanized areas. This study provides valuable insights for transportation planners and engineers, highlighting the importance of intersection design in traffic optimization. [ABSTRACT FROM AUTHOR]

Microwave energy utilization undergoes two stages via absorption and conversion inside ready-to-eat rice (RER) under microwave reheating. The reasonable utilization of microwave energy inside the processed material may enhance the uniformity of the temperature distribution. To analyze the uniformity changes inside RER, the effects of microwave reflection, refraction, and absorption by a metal aluminum film were studied through the thermodynamic properties. A simulation model was developed using the co-simulation method of COMSOL Multiphysics with MATLAB programming to analyze the mechanism of material properties and electromagnetic distribution on temperature distribution uniformity, as well as the formation mechanism of the temperature distribution uniformity of microwave-reheated RER. Based on models of the designed package boxes covering the metal film, the optimal structure was developed to include a metal aluminum film with a width of 5 mm and a thickness of 0.30 mm, which was sprayed on the edges and corners of a rectangular packaging box. The packaging boxes covering the metal films may reduce the average temperature of the upper and lower layers in RER by 8.03 °C and 7.42 °C, respectively, while the temperature distribution uniformity increased by 35.71% and 72.22%. The introduction of a metalized package significantly enhances the temperature uniformity inside RER under microwave reheating. [ABSTRACT FROM AUTHOR]

The presence of ethanol in the water solution during irradiation by ionizing radiation decreases the number of OH and H radicals. Since the living cell is mainly composed of water, this causes less damage to the DNA molecule irradiated by low-LET ionizing radiation where an indirect effect prevails. Ethanol thus acts as a radioprotective substance, scavenging radicals H and OH. This fact can be used in various practical applications in which living cells are irradiated by ionizing radiation to protect them. We used hybrid Petri nets to simulate all dynamic processes, including chemical reactions and the simultaneous diffusion of radical clusters. The mathematical simulating model enables us to simulate the damage to the DNA molecule by the radical cluster arising at various distances from this molecule. [ABSTRACT FROM AUTHOR]

[Objective] The dual-bus and dual-interruptible power supply (UPS) architecture in rail transit signaling system power supply enhances the system redundancy but does not effectively reduce component failure rates. To improve the safety and reliability of the rail transit signaling system, it is necessary to develop an intelligent health management system for signal power supply, enabling real-time monitoring, fault diagnosis, and predictive maintenance of signaling system power supply and equipment. [Method] The design requirements, architecture, module composition, and functions of the intelligent health management system for rail transit signaling system power supply are elaborated in detail. The system is based on real-time monitoring of the operational status for the signaling system power supply or equipment. By understanding the structure and operating principles of the signaling system power supply, the precise simulation and life prediction models are constructed. Functions such as data acquisition, health status analysis, fault diagnosis, and fault prediction are used to implement health management for the signaling system power supply throughout its lifecycle. [Result ＆ Conclusion] The intelligent health management system for rail transit signaling system power supply utilizes big data processing and mining, applies the AHP (analytic hierarchy process) method and simulation models, aiming to achieve intelligent lifecycle health management of the signaling system power supply, improving reliability and safety while reducing maintenance costs. [ABSTRACT FROM AUTHOR]

Objectives: Fluoroscopic guided procedures are a mainstay for interventional radiology (IR) procedures. Practice is needed for the novice to interpret fluoroscopic images and simultaneously perform the procedure hands-on as well as control the foot pedal to screen. We describe the development of a training simulation model which simulates the human kidney, ureter, and bladder. Methods: Stereolithography (SLA) 3D print technology using SLA resin and Anycubic SLA printer were employed. A plastic tubing was used to connect the 3D printed kidney and bladder as the ureter. This simulation model permits fluoroscopic guided filling of "pelvicalyceal system" with contrast as well as ureteric stenting, guidewire, and drainage catheter manipulation. Effectiveness of the model to attain skills for nephrostomy exchange and ureteric stenting was obtained via questionnaire from trainees prior to and after utilizing the model. Results: The 3D printing simulation model of the kidney, ureter, and bladder system enables trainees to perform nephrostomy exchange, nephrostogram, and antegrade stenting. Participants felt more confident to perform the procedures as they were more familiar with the procedure. Besides that, participants felt their wire and catheter manipulation skills have improved after using the simulation model. Conclusions: Neph-ex simulation model is safe and effective for hands-on training in improving proficiency of fluoroscopy-guided nephrostomy exchange and antegrade ureteric stenting. Advances in knowledge: As of our knowledge, there are no commercially available simulation models for fluoroscopic guided nephrostomy exchange and ureteric stent deployment. No article on nephrostomy exchange simulation model has been published before. [ABSTRACT FROM AUTHOR]

Profitability is a complex notion, intertwined with theoretical, socio-economic, and modern economic considerations. While traditionally linked to monopoly advantages, contemporary views broaden this to include shareholder value creation. In agriculture, profitability faces impediments such as rising input costs, market volatility, and economic disparities, emphasizing technological innovation, market conditions, and policy as crucial determinants. This study presents an econometric simulation model to analyze and forecast wheat production profitability in Poland from 2023 to 2027, providing insights into production efficiencies, market dynamics, and policy impacts. Using a system of recursive equations, the model forecasts profitability, integrating econometric techniques with expert insights. It examines variables like resource use, production levels, and price changes, validated through FADN data. The findings reveal that price relations and production efficiencies are the key to profitability. The model highlights market volatility, particularly through "price scissors", as the main factor influencing profitability. Favorable price conditions significantly boost profitability and incentivize production. The model is a critical tool for analyzing wheat profitability, highlighting the influence of market and policy changes. Future work could extend the model's use to other regions or crops, incorporating advanced technologies to improve accuracy. This study offers valuable insights for agricultural economics, aiding stakeholders in strategic decision-making. [ABSTRACT FROM AUTHOR]

Copyright of China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department 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 China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department 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.)

Since many ecosystem services involve spatial scales beyond farm size, their preservation and management in agricultural systems depend on the interaction of the landowners. For the analysis of such interactive land use a generic dynamic land‐use model is developed that considers different payoff structures in a systematic manner and relates land‐use dynamics to these payoff structures. A landowner's own payoff depends on the land use on neighboring land parcels. The landowners' payoffs are interpreted in a game‐theoretic manner which allows for a game‐theoretic classification of the different land‐use dynamics generated by the model. The model is analyzed to determine the proportion, spatial aggregation and temporal turnover of land‐use measures. The model results are applied to a number of cases from literature in which the management of ecosystem services involves a regional scale, including pollinator conservation, pest control, and coordination incentives for the conservation of species in fragmented landscapes. Four main domains of model behavior are identified and related to the payoff structures (type of game), characterized by the proportions and temporal turnover of land‐use measures, and by whether the system has one or two stable equilibria. An important determinant of the land‐use dynamics is the spatial heterogeneity of the landowners' payoffs which. It affects the domain and the location in the domain by which the land‐use dynamics are characterized. [ABSTRACT FROM AUTHOR]

The control process of technological facilities with resource interaction in a decentralized system requires coordination of local systems for control of the state of objects. For the implementation of coordination methods, learning systems have an advantage since they can flexibly adapt to the specifics of each facility control. However, the coordinators’ training process is complicated by the lack of labelled datasets for technological facilities. In decentralized control systems, the problem is complicated by the need to train all coordinators, with the outcome depending on the coordinator’s position within the structure of the distributed control system. This article explores the prospects of model-based learning for solving the problem of missing datasets used for coordinators’ training. An approach to determining the optimal statistics of the training dataset for the coordination control of nonlinear technological facilities with resource interaction is proposed. A combined three-stage process of coordinator training for the decentralized system is proposed. In the first stage, one coordinator is trained on the basis of a distributed system simulation. In the second stage, the settings of the trained coordinator are applied to other coordinators, which are retrained in parallel on the basis of simulation models of local control systems of the relevant parts of the technological facilities. In the third stage, coordinators are fine-tuned to real conditions using Bayesian random search. Conducted experimental studies of the proposed method of training neural network coordinators, implemented on Python TensorFlow, showed greater effectiveness of Collaborative Federated Learning compared to independent training of coordinators or direct transfer of learning outcomes between coordinators.

[Objective] In order to better understand the fault characteristics of offshore wind power access system, the impact analysis of AC fault characteristics of offshore wind power access system is carried out. [Method] The topology analysis of grid-connected transmission system of offshore wind power and the work control principle analysis of offshore wind power electrical structure were presented, including the work control principle analysis of PMSG, the topology and principle analysis of flexible and direct transmission system, the work control principle analysis of offshore converter station, the work control principle analysis of onshore converter station, and the work control principle analysis of offshore converter station. The fault characteristics and mechanism of offshore wind power access system were analyzed from two aspects: asymmetric fault and symmetric fault. [Result] The simulation model of PSCAD-based offshore wind power transmission through flexible direct transmission is established and verified. The correctness and universal applicability of the proposed mechanism analysis are verified through the simulation analysis of single-phase grounding fault and three-phase grounding fault. [Conclusion] The simulation results verify the correctness of the fault characteristic mechanism analysis. The symmetric component method can be satisfied with the fault analysis in the system with power electronic equipment access. In the case of asymmetric fault, the in-phase short-circuit current on both sides has a certain phase Angle difference, the negative sequence current on the soft straight side is the largest, and the short-circuit current on the wind side is generally small. There is only positive sequence current in the soft direct side and wind field side, and the phase of in-phase short-circuit current on both sides is almost the same, showing amplitude limitation.

This paper examines how the unidirectional alignment of a selected street affects traffic load at nearby signal-controlled intersections. Using the Aimsun 8 simulation model, the intersections in the city of Topoľčany were evaluated. A simulation model was created based on a traffic survey conducted by video detection at selected signal-controlled intersections. Both the negative and positive impacts of this modification were analyzed. This study shows a significant deterioration in the traffic situation. This paper further investigates the improvement achieved through corrective measures such as implementing an actuated control plan, modifying signal plans, and coordinating traffic flows. The results show the effectiveness of these measures in reducing congestion and improving traffic flow. They also serve as a foundation for optimizing traffic systems and implementing measures to improve urban mobility.

Objective The dual-bus and dual-interruptible power supply (UPS) architecture in rail transit signaling system power supply enhances the system redundancy but does not effectively reduce component failure rates. To improve the safety and reliability of the rail transit signaling system, it is necessary to develop an intelligent health management system for signal power supply, enabling real-time monitoring, fault diagnosis, and predictive maintenance of signaling system power supply and equipment. Method The design requirements, architecture, module composition, and functions of the intelligent health management system for rail transit signaling system power supply are elaborated in detail. The system is based on real-time monitoring of the operational status for the signaling system power supply or equipment. By understanding the structure and operating principles of the signaling system power supply, the precise simulation and life prediction models are constructed. Functions such as data acquisition, health status analysis, fault diagnosis, and fault prediction are used to implement health management for the signaling system power supply throughout its lifecycle. Result & Conclusion The intelligent health management system for rail transit signaling system power supply utilizes big data processing and mining, applies the AHP (analytic hierarchy process) method and simulation models, aiming to achieve intelligent lifecycle health management of the signaling system power supply, improving reliability and safety while reducing maintenance costs.

Abstract Background Secondary schools are important settings for promoting varied physical activity (PA) opportunities for adolescents to promote PA throughout life. However, research on the effect of secondary school-based interventions on future PA is limited. This study examined the potential impact of secondary school-based interventions on the determinants of future PA participation of Aotearoa New Zealand (NZ) adolescents using simulated modelling. Methods We used data from a nationally representative sample of secondary school students (n = 5035) aged 12–17 between 2017 and 2020 in NZ. We modelled four secondary school-based interventions and their projected impact on five determinants of future PA. Modelled interventions were the technological augmentation of physical education (TAPE), a peer-led PA mentoring programme (PL), physically active learning (PAL) and the inclusion of a natural environment play area (NE). Results Total weekly PA increased the most from the NE intervention (+ 0.2 h/week), followed by TAPE (+ 0.08 h/week), PAL (+ 0.05 h/week) and PL (-0.06 h/week). Current number of PA settings increased the most in NE (+ 1.75 settings/week), followed by TAPE (+ 1.29 settings/week), PAL (+ 1.21 settings/week) and PL (+ 0.73 settings/week). Current number of PA types increased the most in NE (+ 1.57 types/week), followed by PL (+ 1.05 types/week), TAPE (+ 0.34 types/week) and PAL (+ 0.15 types/week). Physical literacy scores increased the most from PL (+ 3.6%), followed by PAL (+ 3.3%), TAPE (+ 0.43%) and NE (+ 0.12%). Social support scores increased the most from PAL (+ 5%), followed by PL (+ 1.9%), TAPE (+ 1.46%) and NE (+ 0.57%). Conclusions On average, all interventions benefitted determinants of future PA participation to a small degree. Results show differing magnitudes of the intervention effect by determinant, indicating the complexities surrounding the promotion of PA adherence. Future interventions could be improved through detailed consultation alongside, and involving, adolescents and stakeholders within schools. Researchers should also prioritise the collection of longitudinal PA data and explore its connection with sociodemographic differences between adolescents.

ABSTRACT: An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella Dublin (S. Dublin), which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-yr period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for noninfected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and postmovement measures within a 1-mo time window may help reduce S. Dublin spread.

As the realization of carbon neutrality has been a main assignment for coping with the global climate change, it became necessary to analyze upcoming changes in electricity mix with economic and technical viewpoints. This paper presents a newly-developed simulation model that reflects the daily intermittency of renewable energy by applying daily average power supply-demand patterns for each season. Also, the paper provides an economic analysis in the viewpoint of investment cost, annual cost and power generation cost by utilizing the calculations from the simulation model. Four scenarios are selected for the analyses, one based on the Korean Government's 2050 Carbon Neutrality Scenario and three Nuclear Power Build-up scenarios, which are newly suggested by the authors. The simulation results show that the increase of nuclear energy from 5.7% of Government's Scenario to 37.7% of the proposed Nuclear Power Build-up Scenario leads to the decrease of about 704 billion US$ in investment cost and about 181 billion US$ in annual cost; with reduction in the increase of 2050 expected generation cost from 3.1 to 1.6 times compared with the referenced 2021 average cost. Further, this study has significance in performing the economic analysis with the expected daily power supply-demand patterns in 2050.

Abstract In order to improve the measurement accuracy of mutual inductance parameters of transmission lines in the environment of double circuit power lines without power outage, this paper establishes simulation models for measuring mutual inductance parameters of transmission lines using the different frequency method in two modes: equal and unequal zero sequence self‐parameters of two circuit lines, using a parallel zero sequence coupling model of double circuit power lines. In the article, simulation analysis is conducted on the line parameters with a coupling coefficient between 0.4 and 0.6 and a line length of 20–50 km. In order to further verify the correctness of the simulation model and measurement methods, a test bench was established based on the principle of line mutual inductance parameter testing in a laboratory dual circuit line without a power outage environment for experimental testing. By comparing the test values under experimental conditions with the standard values, it has been proven that the model and method can meet the actual measurement requirements of engineering.

Abstract Introduction Cost-effectiveness analyses typically ignore healthcare system resource constraints. Ophthalmology is affected by resource constraints because of increasing disease prevalence and the use of resource-intensive treatments. This study evaluated the impact of resource constraints on the cost-effectiveness of faricimab 6 mg, compared with aflibercept 2 mg and ranibizumab biosimilar 0.5 mg, for treating wet age-related macular degeneration (wAMD) or diabetic macular oedema (DMO) over a 5-year horizon. Methods A microsimulation model estimated the impact of resource constraints on patients visits, delays, costs and quality-adjusted life-year (QALY) losses due to treatment delays at a typical UK National Health Service eye hospital treating 1500 patients with wAMD and 500 patients with DMO. Patient characteristics, treatment regimens and treatment intervals were informed using published literature and expert opinion. Resource constraint was represented by limiting the number of available intravitreal injection appointments per week, with growing demand caused by rising disease prevalence. The model compared outcomes across three scenarios; each scenario involved treating all patients with one of the three treatments. Results Over 5 years, in a resource-constrained hospital, compared with aflibercept, faricimab use resulted in the avoidance of 12,596 delays, saved GBP/£15,108,609 in cost and avoided the loss of 60.06 QALYs. Compared with ranibizumab biosimilar, faricimab use resulted in the avoidance of 18,910 delays, incurred £2,069,088 extra cost and avoided the loss of 105.70 QALYs, resulting in an incremental cost-effectiveness ratio of £19,574/QALY. Conclusions Accounting for resource constraints in health economic evaluation is crucial. Emerging therapies that are more durable and require less frequent clinic visits can reduce treatment delays, leading to improved QALY outcomes and reduced burden on healthcare systems. Faricimab reduced the number of delayed injections, leading to improved QALY outcomes for patients in a healthcare system with resource constraints. Faricimab is cost-saving when compared with aflibercept and cost-effective when compared with ranibizumab biosimilar. Graphical Abstract

This paper explores how investments in research and development (R&D) and government policies impact the growth of renewable energy in Brazil, Chile, and Colombia up to 2040. The study presents four scenarios to understand how different levels of R&D investment and the presence or absence of supportive policies affect the spread of renewable technologies such as solar and wind energy. The scenarios range from an optimistic one with high R&D funding and strong policy support to a worst-case scenario with low R&D efforts and weak policies. The findings emphasize the importance of solid government backing and strategic R&D investments in promoting renewable energy and increasing the number of green patents. On the other hand, scenarios with limited policy support and R&D funding show much slower growth, highlighting the challenges posed by economic constraints and tough market conditions. The study shows that strong renewable energy policies could boost renewable energy adoption by 100% to 200%. Overall, this research adds to the discussion on sustainable energy policies and provides useful insights for policymakers and stakeholders to develop strategies that maximize the potential of renewable energy in the region.

Background: Secondary schools are important settings for promoting varied physical activity (PA) opportunities for adolescents to promote PA throughout life. However, research on the effect of secondary school-based interventions on future PA is limited. This study examined the potential impact of secondary school-based interventions on the determinants of future PA participation of Aotearoa New Zealand (NZ) adolescents using simulated modelling. Methods: We used data from a nationally representative sample of secondary school students (n = 5035) aged 12–17 between 2017 and 2020 in NZ. We modelled four secondary school-based interventions and their projected impact on five determinants of future PA. Modelled interventions were the technological augmentation of physical education (TAPE), a peer-led PA mentoring programme (PL), physically active learning (PAL) and the inclusion of a natural environment play area (NE). Results: Total weekly PA increased the most from the NE intervention (+ 0.2 h/week), followed by TAPE (+ 0.08 h/week), PAL (+ 0.05 h/week) and PL (-0.06 h/week). Current number of PA settings increased the most in NE (+ 1.75 settings/week), followed by TAPE (+ 1.29 settings/week), PAL (+ 1.21 settings/week) and PL (+ 0.73 settings/week). Current number of PA types increased the most in NE (+ 1.57 types/week), followed by PL (+ 1.05 types/week), TAPE (+ 0.34 types/week) and PAL (+ 0.15 types/week). Physical literacy scores increased the most from PL (+ 3.6%), followed by PAL (+ 3.3%), TAPE (+ 0.43%) and NE (+ 0.12%). Social support scores increased the most from PAL (+ 5%), followed by PL (+ 1.9%), TAPE (+ 1.46%) and NE (+ 0.57%). Conclusions: On average, all interventions benefitted determinants of future PA participation to a small degree. Results show differing magnitudes of the intervention effect by determinant, indicating the complexities surrounding the promotion of PA adherence. Future interventions could be improved through detailed consultation alongside, and involving, adolescents and stakeholders within schools. Researchers should also prioritise the collection of longitudinal PA data and explore its connection with sociodemographic differences between adolescents. [ABSTRACT FROM AUTHOR]

The automated material handling system (AMHS) plays a central role in realising smart manufacturing by providing manufacturing facilities with flexible, fast, and precise controls. This paper investigates a new type of AMHS known as the in-line stocker, which not only moves unit loads in manufacturing facilities under processing, similar to the automated-guided vehicle but also stores them on shelves, similar to the automated storage and retrieval system, which can reduce material handling space requirements. However, the traffic rate is very high inside an in-line stocker, and two robots are used along the single lane, which is the dual-robot in-line stocker (DRIS). This paper develops an analytical model to estimate the capacity of the DRIS based on a combined simulation and scheduling method. The simulation analysis shows that the model can be used not only to estimate the precise capacity of a DRIS but also to optimise its operating parameters. [ABSTRACT FROM AUTHOR]

Air pollution in megacities worldwide has been a severe public health and environmental problem; it contributes to climate change and threatens life. Among all services, the transport sector accounts for most of these pollutants. However, despite the strategies implemented to reduce these pollutants, mitigate their effects, and promote prosperity and sustainability, emission reduction targets remain unmet, causing the average global temperatures to keep increasing. In this study, the air pollution in the Mexico City Metropolitan Area (MCMA) is estimated through the design of an environmental simulation model using system dynamics, which constitutes a possibility for authorities to foresee the evolution of air quality in MCMA by assessing the emissions from the transport sector from a holistic perspective, based on the region DESTEP analysis factors. Simulation results estimate a more significant reduction than predicted by the local government's current forecast; this emission reduction would be up to 106% lower for PM10, 176% for PM2.5, 34% for NOx, and 17% for VOC. The conclusion demonstrated that one of the main factors with the most significant impact on the control and reduction of emissions is the use and promotion of public transportation, along with the improvement of its road infrastructure. [ABSTRACT FROM AUTHOR]

Introduction: Cost-effectiveness analyses typically ignore healthcare system resource constraints. Ophthalmology is affected by resource constraints because of increasing disease prevalence and the use of resource-intensive treatments. This study evaluated the impact of resource constraints on the cost-effectiveness of faricimab 6 mg, compared with aflibercept 2 mg and ranibizumab biosimilar 0.5 mg, for treating wet age-related macular degeneration (wAMD) or diabetic macular oedema (DMO) over a 5-year horizon. Methods: A microsimulation model estimated the impact of resource constraints on patients visits, delays, costs and quality-adjusted life-year (QALY) losses due to treatment delays at a typical UK National Health Service eye hospital treating 1500 patients with wAMD and 500 patients with DMO. Patient characteristics, treatment regimens and treatment intervals were informed using published literature and expert opinion. Resource constraint was represented by limiting the number of available intravitreal injection appointments per week, with growing demand caused by rising disease prevalence. The model compared outcomes across three scenarios; each scenario involved treating all patients with one of the three treatments. Results: Over 5 years, in a resource-constrained hospital, compared with aflibercept, faricimab use resulted in the avoidance of 12,596 delays, saved GBP/£15,108,609 in cost and avoided the loss of 60.06 QALYs. Compared with ranibizumab biosimilar, faricimab use resulted in the avoidance of 18,910 delays, incurred £2,069,088 extra cost and avoided the loss of 105.70 QALYs, resulting in an incremental cost-effectiveness ratio of £19,574/QALY. Conclusions: Accounting for resource constraints in health economic evaluation is crucial. Emerging therapies that are more durable and require less frequent clinic visits can reduce treatment delays, leading to improved QALY outcomes and reduced burden on healthcare systems. Faricimab reduced the number of delayed injections, leading to improved QALY outcomes for patients in a healthcare system with resource constraints. Faricimab is cost-saving when compared with aflibercept and cost-effective when compared with ranibizumab biosimilar. [ABSTRACT FROM AUTHOR]

The heating system is an essential component of the glass molding process. It is responsible for heating the glass to an appropriate temperature, allowing it to soften and be easily molded. However, the energy consumption of the heating system becomes particularly significant in large-scale production. This study utilized G-11 glass for the simulation analysis and developed a finite element model for the thermal conduction of a 3D ultra-thin glass molding system, as well as a thermal bending model for smartwatches. Using finite element software, the heat transfer between the mold and the glass was modeled, and the temperature distribution and thermal stress under various processing conditions were predicted. The findings of the simulation, when subjected to a numerical analysis, showed that heating rate techniques significantly affect energy consumption. This study devised a total of four heating strategies. Upon comparison, optimizing with heating strategy 4, which applies an initial heating rate of 35 mJ/(mm2·s) during the initial phase (0 to 60 s) and subsequently escalates to 45 mJ/(mm2·s) during the second phase (60 to 160 s), resulted in a reduction of 4.396% in the system's thermal output and a notable decrease of 7.875% in the heating duration, respectively. Furthermore, a single-factor research method was employed to study the forming process parameters. By comparing the numerical simulation results, it was found that within the temperature range of 615–625 °C, a molding pressure of 25–35 MPa, a heating rate of 1.5–2.5 °C/s, a cooling rate of 0.5–1 °C/s, and a pulse pressure of 45–55 Hz, the influence on residual stress and shape deviation in the glass was minimal. The relative error range was within the 20% acceptable limit, according to the experimental validation, which offered crucial direction and ideas for process development. [ABSTRACT FROM AUTHOR]

The utilization of carbon fiber-reinforced polymer/plastic (CFRP) components is primarily limited due to the lack of high-quality and least damage-based hole constructing technology. In this study, the delamination defect is investigated at the exit of CFRP drilling by a novel three-dimensional simulation model considering heat accumulation effect. The validity of the model is confirmed through experimental data of CFRP boreholes: surface temperature distribution at the borehole outlet, drilling axial force, and delamination factor at the outlet. The model exhibited high accuracy in theoretical analysis of CFRP 3D drilling with/without temperature. Additionally, the variation in temperature field and corresponding delamination damage is analyzed through simulation of CFRP drilling process at the exit plane of a hole. Results indicate that delamination damage occurs during unsupported dry drilling when half of the length of the main cutting edge impale the workpiece after reaching its exit plane. The changes in axial force caused delamination under different processing parameters, and a quantitative relationship is established through multiple regression analysis. The appropriate processing parameters can effectively reduce delamination during CFRP drilling. Specifically, accurate measures can ensure sufficient heat conduction and minimize heat accumulation during the formation stages of exit-related delamination. [ABSTRACT FROM AUTHOR]

Introduction: Chemical mass casualty incidents (MCIs) pose a substantial threat to public health and safety, with the capacity to overwhelm healthcare infrastructure and create societal disorder. Computer simulation systems are becoming an established mechanism to validate these plans due to their versatility, cost-effectiveness and lower susceptibility to ethical problems. Methods: We created a computer simulation model of an urban subway sarin attack analogous to the 1995 Tokyo sarin incident. We created and combined evacuation, dispersion and victim models with the SIMEDIS computer simulator. We analyzed the effect of several possible approaches such as evacuation policy ('Scoop and Run' vs. 'Stay and Play'), three strategies (on-site decontamination and stabilization, off-site decontamination and stabilization, and on-site stabilization with off-site decontamination), preliminary triage, victim distribution methods, transport supervision skill level, and the effect of search and rescue capacity. Results: Only evacuation policy, strategy and preliminary triage show significant effects on mortality. The total average mortality ranges from 14.7 deaths in the combination of off-site decontamination and Scoop and Run policy with pretriage, to 24 in the combination of onsite decontamination with the Stay and Play and no pretriage. Conclusion: Our findings suggest that in a simulated urban chemical MCI, a Stay and Play approach with on-site decontamination will lead to worse outcomes than a Scoop and Run approach with hospital-based decontamination. Quick transport of victims in combination with on-site antidote administration has the potential to save the most lives, due to faster hospital arrival for definitive care. [ABSTRACT FROM AUTHOR]

With global economic integration and rapid IT advancements, enterprises face complex market environments and intense competition. Efficient management and coordination of supply chains and manufacturing are critical. This study explores optimization strategies for integrated supply chain and manufacturing management using system dynamics. Initially, it investigates the contractual collaboration model based on system dynamics, analysing dynamic behaviours and optimization strategies. Subsequently, a system dynamics simulation model of the integrated system is constructed. Simulation analysis reveals the interactive relationships and dynamic patterns within the system. While many studies focus on static analysis, they often overlook dynamic changes and complex interactions. This study enriches the theoretical framework and provides solutions for enhancing management efficiency and competitiveness in a volatile market. [ABSTRACT FROM AUTHOR]

This paper explores how investments in research and development (R&D) and government policies impact the growth of renewable energy in Brazil, Chile, and Colombia up to 2040. The study presents four scenarios to understand how different levels of R&D investment and the presence or absence of supportive policies affect the spread of renewable technologies such as solar and wind energy. The scenarios range from an optimistic one with high R&D funding and strong policy support to a worst-case scenario with low R&D efforts and weak policies. The findings emphasize the importance of solid government backing and strategic R&D investments in promoting renewable energy and increasing the number of green patents. On the other hand, scenarios with limited policy support and R&D funding show much slower growth, highlighting the challenges posed by economic constraints and tough market conditions. The study shows that strong renewable energy policies could boost renewable energy adoption by 100% to 200%. Overall, this research adds to the discussion on sustainable energy policies and provides useful insights for policymakers and stakeholders to develop strategies that maximize the potential of renewable energy in the region. [ABSTRACT FROM AUTHOR]