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The results of the dynamic simulation of organic matter stocks in forest soils are discussed from the point of a predictive assessment of carbon sink depending on forest site types and forest management regimes. The biological cycle in the "soil–forest stand" system was simulated with FORRUS-S, Romul_Hum, and SCLISS simulation models. Computational experiments were carried out for three forest enterprises and a nature reserve located in the Republic of Karelia and in Nizhni Novgorod, Moscow, and Bryansk oblasts, which corresponds to a gradient of zonal conditions from the middle taiga to the broadleaved forest subzone. Forest survey data available for all study objects were used to simulate the long-term (100 years) forest dynamics. Calculations of soil Corg pools were carried out separately for each forest taxation area using the corresponding characteristics of the forest stand (mean height, diameter, basal area, growing stock) and soil (Corg and Ntot contents in the forest floor and mineral soil) as initial data, which made it possible to take into account the spatial variability of forest conditions and successional change of species in the resulting area-based estimates of soil carbon sink. Under the nature reserve regime, the mean increase in soil stock of organic matter by 35–80 t C/ha compared to the initial values is predicted for all territories over 100 years. Felling practices of varying intensity reduce the possible Corg sink into forest soils by an average of 30–50 t/ha compared to the reserve regime. Regional features of the dynamics of organic matter are manifested in different ratios of carbon accumulation in organic and organomineral soil horizons. [ABSTRACT FROM AUTHOR]

Summary: In wireless power transfer (WPT) systems, extended transmission distances significantly impede efficiency, posing a major challenge to their practical application. This paper presents a novel ortho‐octagonal double‐helix metamaterial that can effectively enhance the transmission efficiency of WPT systems. It has theoretically derived and experimentally verified the enhancement of evanescent wave transmission by this metamaterial dielectric plate. A WPT simulation system operating at 10.78 MHz is constructed by HFSS software, and the effects of adding passive relay coils and different shapes of metamaterials on the transmission efficiency are comparatively investigated. Simulated data converge to indicate that integrating variously shaped metamaterials at the transceiver's end distinctly elevates the WPT system's transmission efficiency. When the transceiver coil spacing of the WPT system is greater than 22 cm, the effect of metamaterials on the system transmission efficiency enhancement shows an increasing and then decreasing trend as the distance increases. The positive octagonal metamaterial improves 12% over the circular metamaterial in the mid‐range transmission distance due to its better magnetic coupling effect. When the transceiver coil spacing is 22 cm, the open‐circuit voltage of the receiving coil after loading the metamaterial is stabilized to be enhanced by nearly five times, and it has the best effect at 30 cm, and the transmission efficiency is enhanced from 30% to 60%, which verifies the effective enhancement of the metamaterial on the transmission efficiency of the WPT system. [ABSTRACT FROM AUTHOR]

Background and Aims Design Setting Participants Measurements Findings Conclusions During the COVID‐19 pandemic, there was a surge in opioid overdose deaths (OODs) in Massachusetts, USA, particularly among Black and Hispanic/Latinx populations. Despite the increasing racial and ethnic disparities in OODs, there was no compensatory increase in naloxone distributed to these groups. We aimed to evaluate two community‐based naloxone expansion strategies, with the objective of identifying approaches that could mitigate mortality and racial and ethnic disparities in OODs.Individual‐based simulation model. We measured naloxone availability using naloxone kits per OOD and evaluated scenarios of achieving higher benchmarks for naloxone availability (i.e. 40, 60 and 80 kits per OOD) from 2022 levels (overall: 26.0, White: 28.8, Black: 17.3, Hispanic/Latinx: 18.9). We compared two naloxone distribution strategies: (1) proportional distribution: achieving the benchmark ratio at the overall population level while distributing additional kits proportional to the 2022 level for each racial/ethnic group (at 40 kits per OOD benchmark: overall: 40, White: 44.3, Black: 26.6, Hispanic/Latinx: 29.1), and (2) equity‐focused distribution: achieving the benchmark ratio among each racial/ethnic group (at 40 kits per OOD benchmark: 40 for all groups).Massachusetts, United States.People at risk of OOD.Annual number and rate of OODs, total healthcare costs of increasing naloxone availability.Both naloxone distribution strategies yielded comparable predicted reductions in total OODs in 2025 and incurred similar incremental costs. However, the relative reduction in the rate of OODs differed across groups. For achieving an 80 kits per OOD benchmark, proportional distribution resulted in a projected 6.7%, 6.5% and 7.1% reduction in annual OODs in 2025 among White, Black and Hispanic/Latinx populations, respectively. In contrast, equity‐focused distribution achieved a reduction of 5.7%, 11.3% and 10.2% in the respective groups. In all scenarios, the cost per OOD averted was lower than the generally accepted thresholds for cost per life saved.An equity‐focused naloxone distribution strategy designed to reduce racial and ethnic disparities in naloxone availability could improve health equity among racial and ethnic groups while potentially improving overall population health at lower healthcare costs per opioid overdose death averted than a proportional distribution strategy. [ABSTRACT FROM AUTHOR]

This research employs numerical simulations and scenario analysis to assess a supply chain model's economic and environmental performance operating under stochastic market demand, with inventory levels managed by a periodic review (R, s, S) inventory system. The inventory model in this research is designed to determine the minimal inventory levels required to achieve predefined fill rates across various operational constraints. The supply chain's inventory model simulates optimal responses to normally distributed market demand within 365-day periods characterized by mean and two levels of demand variability through two fill rate levels, two workweek schedules, 15 review periods, and 16 lead times. By conducting an extensive analysis of the 192000 simulation experiments of the supply chain under periodic review (R, s, S) inventory system, complex influences between system variables and economic outcomes of supply chain operation measured by ordering, transportation, holding, penalty, and total costs along with greenhouse gas emissions arising from inventory-related transportation according to the ISO 14083 standard are analyzed. The insights from this research have significant practical implications, providing valuable guidance for supply chain managers, researchers, and freight companies offering guidance for improving economic and environmental performance. [ABSTRACT FROM AUTHOR]

Sustainable development of islands cannot be achieved without the use of renewable energy to address energy and freshwater supply issues. Utilizing the widely distributed tidal current energy in island regions can enhance local energy and water supply security. To achieve economic and operational efficiency, it is crucial to fully account for the unique periodicity and intermittency of tidal current energy. In this study, a tidal current-powered freshwater and energy supply system is proposed. The marine current turbine adopts a direct-drive configuration and will be able to directly transfer the power of the turbine rotation to the seawater pump to improve the energy efficiency. Additionally, the system incorporates batteries for short-term energy storage, aimed at increasing the capacity factor of the electrolyzer. A simulation is conducted using measured inflow velocity data from a full 12 h tidal cycle. The results show that the turbine's average power coefficient reaches 0.434, the electrolyzer's average energy efficiency is 60.9%, the capacity factor is 70.1%, and the desalination system's average specific energy consumption is 6.175 kWh/m3. The feasibility of the system design has been validated. [ABSTRACT FROM AUTHOR]

Research by scientists dealing with sustainable development issues in the aviation industry security focuses on finding solutions that constitute the so-called 'golden mean' between appropriate efficiency and high levels of system safety and reliability (including human reliability). The features mentioned above have been repeatedly investigated in various studies, but always individually—to date, no one has proposed a solution indicating the balance point of all the abovementioned features. Here we propose a solution to this research gap: a model for assessing the configuration of airport security control systems. The model allows for the optimal configuration of airport security control systems. The multi-level model validation presented in the article was performed, among others, based on one of the airports in Poland, and showed that the correct configuration of the system can bring energy savings of 913,500 kWh/year in the case of large international airports. Additionally, the article discusses all solutions and modern technologies equipped with devices supporting the passenger and baggage screening process. [ABSTRACT FROM AUTHOR]

As the proportion of renewable energy infiltrating the power grid increases, suppressing its randomness and volatility, reducing its impact on the safe operation of the power grid, and improving the level of new energy consumption are increasingly important. For these purposes, energy storage stations (ESS) are receiving increasing attention. This article discusses the structure, working principle, and control methods of grid-following and grid-forming energy-storage converters, which are currently commonly used. A simulation analysis was conducted to investigate their dynamic response characteristics. The advantages and disadvantages of two types of energy storage power stations are discussed, and a configuration strategy for hybrid ESS is proposed. This paper presents research on and a simulation analysis of gridforming and grid-following hybrid energy storage systems considering two types of energy storage according to different capacity scenarios. Finally, a comparative analysis between the systems is presented. A simulation model was established using PSD-BPA (Power System Department-Bonneville Power Administration) to analyze the impact of the capacity ratio of grid-following and grid-forming ESS on their dynamic response characteristics in a hybrid ESS. In addition, a development direction for future ESSs is indicated. [ABSTRACT FROM AUTHOR]

Every day, health centers receive a significant number of patients seeking care and hospitalization, leading to long waiting times. Simulation modeling techniques are considered an effective solution to this issue. However, some research efforts had limited success mainly due to the neglect of systematic and straightforward approaches to identify and eliminate time waste in the healthcare system. To address this limitation, this study developed an LSS approach by collecting arriving patients and staff in a health center and using it as a case study. Then, a simulation model of the current system was created using the SIMPROCESS software. Finally, alternative solutions to shorten the queue time were proposed and supported by statistical graphs and tables. This is expected to improve overall health outcomes and enhance the delivery of healthcare services. A scenario is presented to evaluate the impact of the proposed improvements, which includes adding a general practitioner, a pediatrician, a dentist, and another pharmacy counter. This scenario improves system performance by up to 21%, reduces patient waiting times by approximately 50%, and ensures a fair distribution of workload among staff. [ABSTRACT FROM AUTHOR]

The application of computational techniques to the study of zoology has greatly improved our knowledge of animal behaviour and species conservation. This study offers a thorough analysis of the ways that computational methods, such as data mining, simulation modelling, machine learning and geographic information systems (GIS) are revolutionising research in both applied and pure zoology. This review illustrates how these techniques can improve species distribution modelling, habitat suitability analysis, wildlife monitoring and behavioural investigations by looking at current case studies. More accurate forecasts have been produced by machine learning approaches, especially in the areas of species distribution and habitat suitability, which has improved the knowledge base for conservation initiatives. Through the extraction of significant patterns from large, complicated datasets, data mining has made it possible to get new insights into the vocalisations, social relationships and movement of animals. Because GIS provides precise habitat maps, landscape connectivity assessments, and spatial models of species distributions, it has proven to be an invaluable tool in ecological research. Important projections regarding the long-term effects of conservation initiatives have been made possible via simulation modelling, including individualbased models and population viability studies. The study does, however, also address the drawbacks of these computational methods, including data quality, model complexity, resource requirements and integrating disparate data sources. Notwithstanding these obstacles, zoological research seems to have a bright future because computational techniques provide effective instruments for addressing urgent ecological problems. In order to fully realise the potential of computational approaches in promoting species conservation and behavioural studies, this review emphasises the significance of ongoing innovation and multidisciplinary collaboration. [ABSTRACT FROM AUTHOR]

This paper adopts a systems firm-centered perspective on the environmental assessment of recyclable glass and PET soft drink containers. We employ LCA and discrete-event simulation modeling for the environmental assessment of the two soft drinks packaging alternatives in operational terms over the entire supply chain over a period of three years. The assessment is based on real data collected from a large soft drink producer and its suppliers. The research and practice contribution of the paper is twofold: first, it introduces a methodological framework for environmental assessment of companies' packaging environmental impact under different product and operations strategies; and secondly, it provides a holistic environmental assessment of the two packaging materials (PET and glass) taking into account specific operational issues, such as product mix and recycling and reuse options, as well as activity interdependences and stochasticity. The results of the simulation experiments confirm at the operations system level, for glass, the importance for sustainability, to increase the number of reuse cycles (for the particular case, for significant improvement, seven reuses) and the percentage of used bottles collected for refilling (80% recovery rate), whereas for PET, to increase the percentage of recycled PET in new bottles (towards 30%). [ABSTRACT FROM AUTHOR]

Aiming at the complex structure, numerous equipment, intricate control and protection logic, as well as the existence of numerous unmodeled dynamics and black-box device models in photovoltaic (PV) grid-connected systems, a modeling method based on Particle Swarm Optimization Neural Network (PSO-NN) is proposed to address the inability of pure mechanism models to accurately simulate their operational dynamics. Utilizing the differences in active power response waveforms under Voltage-Frequency (Vf) control, Power-Reactive Power (PQ) control, and Droop control as criteria for control strategy identification, a PSO-NN model is constructed for PV grid-connected systems, with inputs comprising temperature, humidity, light intensity, voltage, and frequency disturbances, and outputs being active and reactive power. To validate the model's effectiveness, a PV grid-connected system model is built in a self-developed simulation software and connected to an IEEE 14-bus distribution network for simulation verification. The results demonstrate that the proposed PV grid-connected model can effectively identify the types of Vf control, PQ control, and Droop control strategies, and accurately reflect the dynamic response characteristics of active and reactive power under various voltage and frequency disturbances. [ABSTRACT FROM AUTHOR]

To explore the best mixing working fluid of the two-stage evaporation series organic Rankine cycle system under specific working conditions, three groups of mixing working fluids with different characteristics of R21/R113, R1234ze/R141b and R227ea/R245fa were selected. According to thermodynamic performance, economic index and environmental index, the non-dominated sorting genetic algorithm was used for the multi-objective optimization. By solving Pareto boundary, three decision methods were used to select the optimal solution for each working fluid group. The optimal decision method was selected according to the offset. The results show that when the heat source temperature is 150 C with the cold source temperature of 15 C, the exergy efficiency of the optimal solution of the mixing working fluid of R1234ze/R141b is relatively high with relatively low levelized cost of energy (LCOE) and equivalent carbon emission (ECE), and the heat source temperature is also suitable, which illuminates that R1234ze/R141b is relatively suitable mixing working fluid in this working condition. [ABSTRACT FROM AUTHOR]

Simulation modeling is crucial in support of probabilistic risk assessment (PRA) for nuclear power plants (NPPs). There is a challenge, however, associated with simulation modeling that relates to the time and resources required for collecting data to determine the values of the input parameters. To alleviate this challenge, this article develops a formalized methodology to generate surrogate values of input parameters grounded on the decomposition of phenomenological nondimensional parameters (PNPs) while avoiding detailed data collection. While the fundamental principles of the proposed methodology can be applicable to various hazards, the developments in this article focus on fire PRA as an example application area for which resource intensiveness is recognized as a practical challenge. This article also develops a computational platform to automate the PNP decomposition and seamlessly integrates it with state-of-practice fire scenario analysis. The applicability of the computational platform is demonstrated through a multi-compartment fire case study at an NPP. The computational platform, with its embedded PNP decomposition methodology, can substantially reduce the effort required for input data collection and extraction, thereby facilitating the efficient use of simulation modeling in PRA and enhancing the fire scenario screening analysis. [ABSTRACT FROM AUTHOR]

The paper examines issues concerning the further development of intelligent technology for constructing dynamic integrated expert systems with an emphasis on methods and tools of constructing simulation models of the external environment as an integral stage in the development of dynamic integrated expert systems based on problem-oriented methodology and the AT-TECHNOLOGY workbench. The on-board software complex of the spacecraft is used as an experimental problem domain for prototyping a dynamic integrated expert system. [ABSTRACT FROM AUTHOR]

The development of various machines and equipment containing parts or assemblies made of hyperelastic materials (e.g., rubber, silicone) is difficult because of the intricacies involved in the description of their mechanical properties. This is especially seen in calculations using simulation modeling. The behavior of hyperelastic materials is described by utilizing the results of research conducted with specialized equipment. This allows for the most accurate determination of their mechanical properties. Hyperelastic materials are widely used across diverse industries, encompassing mechanical engineering, the chemical and petrochemical sectors, cement production, and beyond. To determine the mechanical characteristics of SKR-788 silicone, batches of test samples were prepared, varying solely in the ratio of the base to the catalyst. Laboratory testing of silicone samples was performed on an Instron 4500 device, and data such as loads, displacements, and deformations were obtained. In order to verify the results of the tests against the results of simulation modeling in Ansys software, a model of the experimental sample was built. The obtained results of uniaxial tensile testing of the experimental sample were taken into account during the description of the material in the Mooney-Rivlin model. The calculation scheme for the test sample during simulation modeling is similar to the one used during its laboratory testing. Applying the load to the test sample during the simulation proceeded incrementally based on time. As a result of the work, the constants of the SKR-788 silicone material for the three-parameter Mooney-Rivlin model were defined (C10 = -0.10335 MPa, C01 = 0.57534 MPa, and C11 = 0.093309 MPa). As a result of simulation modeling of the experimental silicone sample, the values of its displacements and stresses were obtained. Upon comparing the stress values derived from the results of laboratory testing on the Instron 4500 equipment with those obtained from simulation modeling, a discrepancy of up to 7% was identified. For the first time, the characteristics of the SKR-788 silicone material have been established and verified. This will facilitate the design and research of various equipment and machine components made from hyperelastic materials. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to explore the optimization of support structures for horizontal pressure vessels using simulation modeling. The research aims to reduce the mass of the support while ensuring structural integrity and identifying opportunities for future improvements in materials and design. Design/methodology/approach: The research was conducted by creating a three-dimensional support model in SolidWorks, compliant with GOST standards. The stress-strain behavior and optimization of the support structure were analyzed using SolidWorks’ Simulation module, which employs the finite element method (FEM). Non-uniform load distributions, such as sinusoidal and parabolic loads, were applied during the loading process to enhance the accuracy of the simulation without incorporating the vessel body itself. Findings: The simulation results showed that optimizing the support structure led to a 15% reduction in its mass. Even though this also resulted in a 23% increase in equivalent stresses in critical areas, the support structure remains safe to operate, with a strength reserve factor under static loads exceeding 2. Research limitations/implications: Further research should include simulations that account for the type and properties of connections between elements, particularly weld calculations. Additionally, future studies could explore the use of higher-grade steels than the tested 09G2C steel to achieve further mass reductions, provided the cost is justifiable. Practical implications: This study is particularly relevant for the design of pressure vessel supports used in vehicles, trailers, and semi-trailers transporting liquids or liquefied hydrocarbon gases. Reducing the mass of support structures can increase payload capacity, offering significant commercial benefits in transportation efficiency. Social implications: A lighter, optimized support structure can contribute to more fuel-efficient transportation of liquid and gas materials, thereby reducing the environmental impact of logistics operations. Originality/value: The originality of this study lies in the combined use of topological and parametric optimization techniques for modeling horizontal pressure vessel supports. The paper provides valuable insights into how simulation-based optimization can lead to significant mass reductions while maintaining structural safety. This research is particularly useful to engineers and designers working on pressure vessel supports for transportation applications. [ABSTRACT FROM AUTHOR]

In this study, the pore structure and gas permeability of river sand concrete and manufactured sand concrete (mixed with various stone powders) are examined under dry and wet conditions. First, the pore structure of concrete was tested using the mercury-in-pressure (MIP), hydrostatic balance (HB), and nuclear magnetic resonance (NMR) methods. Second, the gas permeability of concrete was measured using the quasi-stationary flow method. Finally, a numerical model was developed based on the relationship between the pore structure and gas permeability. The results indicated that the gas permeability of dry concrete has a quadratic linear relationship with the porosity and volumetric characteristic pore size. The pore structure of partially water-saturated concrete can be corrected using a correction factor and the relaxation rate of the dry material. Finally, a random hierarchical bundle model using the HB–NMR method is proposed. The maximum relative deviation between the predicted and experimental values is 48.28%. [ABSTRACT FROM AUTHOR]

In this study, a steady-state thermodynamic equilibrium evaluation of CO2 methanation was conducted. Calculations were performed by solving the material balance equations using the equilibrium constants of CO2 methanation and reverse water–gas shift reactions. Results obtained from an analytical method developed with the aid of the Microsoft Excel platform were compared to simulations conducted using the commercially available free software COCO and DWSIM. The effects of temperature, pressure, and H2/CO2 ratio on CH4 yield, carbon oxide formation, and heat balance were investigated. The results indicate that the methanation process is highly favored by low temperatures and higher pressures with a stoichiometric H2/CO2 ratio. Under these conditions, CH4 output increases, and carbon formation is reduced, resulting in better performance. Simulations from all three models are in agreement, with minor differences noted in the DWSIM software. [ABSTRACT FROM AUTHOR]

Improving the performance at signalized intersections can be achieved through different management styles or sensor technologies. It is crucial that we measure the real-time impact of these variables on intersection performance. This study introduces a Bluetooth-based real-time performance measurement system applicable to all signalized intersections. Additionally, the developed method serves as a feedback tool for adaptive intersection management systems, providing valuable data input for performance optimization. The method developed in the study is applied at the Refik Cesur Intersection in the Polatlı district of Ankara where delay values are calculated based on traffic flows and data from Bluetooth sensors positioned at strategic locations. Initially, the intersection operated under a fixed-time signaling system, followed by a fully adaptive signaling system the next day. The performance of these two systems is compared using the Bluetooth-based application. The results show that the average delay per vehicle per day is 58.1 seconds/vehicle for the fixed-time system and 45.3 seconds/vehicle for the adaptive system. To validate the Bluetooth-based performance measurement system, the intersection is modeled and simulated using Aimsun Simulation Software Next 20.0.4. The simulation results confirm the findings of the Bluetooth-based analysis, demonstrating the effectiveness of the adaptive signaling system in reducing delays. [ABSTRACT FROM AUTHOR]

The traditional text based system engineering method has some problems in the development of high complexity satellite Internet simulation platform, such as poor system design coordination and insufficient early simulation verification. The model-based systems engineering (MBSE) method was proposed to model the architecture of satellite Internet simulation platform. Firstly, a DV-MBSE and an integration verification architecture with external software were proposed. Secondly, based on MBSE methodology, the requirements analysis, functional decomposition and interaction structure modeling of the top architecture of the satellite Internet simulation platform were carried out. Finally, the validity of the model was verified by running logic verification and external model integration verification, thus supporting the design of satellite Internet. [ABSTRACT FROM AUTHOR]

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Introduction. The article presents a comparison of simulation models for financing an inpatient emergency department and a therapeutic department using the example of an emergency therapeutic flow of patients.The objective was to analyze the economic aspects in an inpatient emergency department for the treatment of emergency therapeutic conditions such as hypertension.Methods and materials. Based on a retrospective analysis of the flow of incoming patients for emergency and urgent indications, a simulation model of the load and economic calculations of the work of the inpatient emergency department was developed.Results. According to the results of the study, it was revealed that with a three-fold increase in the flow of patients entering the department, the inpatient emergency department copes with this flow more effectively in comparison with the therapeutic one. Despite this funding, the medical institution receives significantly less.Conclusion. Based on the study, the need to create a special tariff plan for the work of such units as the inpatient emergency department was identified, because the capacity in this department is many times greater.

The goal of this work is to analyze the dynamics of soil organic matter (SOM) in arable soils of Yamal using computational experiments with the ROMUL model. Soil temperature and moisture dynamics were simulated using the SCLISS model. The Yamal experimental station was organized in 1932. The soil is Plaggic Podzol. The thickness of humus horizon (PY) is 30 cm. Pools, kg/m2: SOM – 9.32 and 13.75; N – 0.46 and 0.66 for 0–20 and 0–30 cm respectively. Background: soddy-green-moss tundra near Salekhard. Soil: Folic Podzol: litter (O, 2 cm) and humus-accumulative (AY, 4 cm) and illuvial ferruginous (BF, 6 cm) horizons. Pools, kg/m2: SOM – 1.38 and 2.69, N – 0.03 and 0.18 for 0–2 and 2–6 cm respectively. The quantity and quality of background fall was estimated according to literature data. Clarification of the amount of fall was carried out by the method of inverse problem solving (spin-up). Peat application was simulated: starting application in the dose of 12 kg/m2 and maintenance (every 6 years) in doses 4, 8 and 12 kg/m2, N 1%. Application of mineral fertilizers, 2 variants: a) N 4 g/m2 (40 kg/ha) in peatting years and b) application of the same dose of nitrogen every year. The duration of computational experiments is 30 and 90 years. Computational experiments showed that after the starting peatting of Folic Podzol at the rate of 12 kg/m2 after 30 years, only 15% of the applied detritus remained. Maintenance peatting of 8–12 kg/m2 leads to an increase in SOM pool to 20–30 kg/m2 and excessive accumulation of detritus. Application of 4 kg/m2 of peat once every 6 years for 90 years shows the dynamics of SOM pools from Folic Podzol to Plaggic Podzol which is confirmed by field survey data. Application of mineral nitrogen (4 g/m2) once every 6 years does not affect SOM pools. Annual application of mineral N (4 g/m2) increases SOM pools due to intensified humification. This fact requires experimental verification.

The issues of process approach implementation in enterprise financial flows management system have been highlighted. The stages of financial flows management within the framework of business processes model have been defined. The advantages of the balanced scorecard have been revealed. The approach to financial flows management based on business process models and their optimization methods has been proposed. The approach to enterprise process management is based on the Deming-Shewhart cycle. The strategic map has been considered as tools for process management and metrics control. The composition of balanced scorecard has been proposed, reflecting the dependence of profit, accounts receivable, and equity turnover rate on the key indicators of cost, fragmentation. and time of fulfilling tasks of the AS-IS and TO-BE business process models. The cause-and-effect relationships between the business processes tasks and a company’s financial performance have been considered. The paper presents the results of the analysis and visualization of the dynamics of change in indicators depending on business process model transformation. In order to reduce risks and increase the efficiency of implementing process optimization results, a number of simulation experiments have been conducted for a company actively developing online sales channels. Practical recommendations have been developed and changes in the key business process management system justified. The system effect from simulation modeling results implementation has been obtained.

Abstract Aiming at the complex structure, numerous equipment, intricate control and protection logic, as well as the existence of numerous unmodeled dynamics and black-box device models in photovoltaic (PV) grid-connected systems, a modeling method based on Particle Swarm Optimization Neural Network (PSO-NN) is proposed to address the inability of pure mechanism models to accurately simulate their operational dynamics. Utilizing the differences in active power response waveforms under Voltage-Frequency (Vf) control, Power-Reactive Power (PQ) control, and Droop control as criteria for control strategy identification, a PSO-NN model is constructed for PV grid-connected systems, with inputs comprising temperature, humidity, light intensity, voltage, and frequency disturbances, and outputs being active and reactive power. To validate the model's effectiveness, a PV grid-connected system model is built in a self-developed simulation software and connected to an IEEE 14-bus distribution network for simulation verification. The results demonstrate that the proposed PV grid-connected model can effectively identify the types of Vf control, PQ control, and Droop control strategies, and accurately reflect the dynamic response characteristics of active and reactive power under various voltage and frequency disturbances.

The upstart is commonly used on bars in artistic gymnastics following a release and regrasp skill, where the gymnast will perform a flighted element before catching the bar. The variability of the flighted element leads to varying initial conditions prior to the upstart. The aim of the study was to understand how technique can be manipulated in order to ensure success at the task despite this variability. More specifically, the study aimed to quantify the ranges of initial angular velocity a gymnast could cope with in an upstart using (a) a fixed timing technique, (b) with one additional parameter to modify timings as a function of initial angular velocity, and (c) a further additional parameter to extend the range. Relationships were established, using computer simulation modeling, between the movement pattern parameters, which defined the technique, and the initial angular velocity of the upstart. A two-parameter relationship outperformed both the one-parameter relationship and the fixed timing solution in terms of the range of initial angular velocities the model could cope with. One of the two parameters governed the time by which the initiation of the shoulder extension should be reduced as a function of increased initial angular velocity, and the other parameter performed the same function for the remaining timing parameters at the hip and shoulder. The present study suggests that gymnasts, and, therefore, humans, may be able to modify movement patterns to cope with uncertain initial conditions using a relatively small number of parameters. [ABSTRACT FROM AUTHOR]

The focus of the current research is the multi-criteria task of decision-making support for the effective management of ready-mix concrete production and its delivery to construction sites, taking all possible risk factors into account. The development of a simulation model for the network of production facilities and the distribution chain of ready-made concrete mixtures is a key element of the project to create a digital twin in the production and logistics of a concrete plant. The relevance of this study is supported by the fact that post-war restoration of the destroyed housing stock, reconstruction of damaged infrastructure and industrial buildings, and the resumption of work at all construction sites in the country will lead to a sharp increase in the demand for concrete, which will obviously exceed the existing production capacity. Therefore, one of the top priorities for Ukrainian concrete plants today should be the implementation of a strategy and relevant development projects aimed at increasing productivity without losing quality. This research aims to create a simulation model of the production and delivery of ready-mixed concrete in a network of manufacturing plants and construction sites, as part of a project to create a digital double for making effective risk management decisions in real-time for the early detection of suboptimal activity in the production of high-quality concrete mix and its effective logistics. Thus, the objectives of the study are as follows: to analyze the problems and features of creating digital duplicates in the production and logistics of concrete plants; to develop a simulation model of analyzing production processes and logistics of ready-mixed concrete mixtures; to provide an illustrated example of modeling production and logistics processes in a network of concrete factories and construction sites; to conduct optimization experiments to determine the modes of system operation. After all necessary work had been done, the following results have been obtained. A simulation model of the analyzing production processes and logistics of ready-mixed concrete mixtures has been developed, with the help of which it is possible to solve several tasks, including the evaluation of the rationality and efficiency in the organization of production and delivery of ready-mixed concrete, the identification of bottlenecks in production and logistics processes, forecasting of indicators activities of concrete plants, taking into account changes in production conditions, and forming data for decision-making on reducing plant and customer downtime, among others. Conclusions. The academic novelty of the study is related to the solution of the actual problem related to the preparation and planning of logistical actions for the delivery of ready-mixed concrete in the network of plants and construction sites bycreating a complex of optimization and simulation models, that contributes to the effectiveness of decision-making on risk management for the early detection of suboptimal activities in the production of commercial concrete mixtures and logistics. The effectiveness of the proposed approach is illustrated by an example of concrete delivery in a network of concrete factories in the Kharkiv region.

Abstract Introduction Energy system simulation modeling plays an important role in understanding, analyzing, optimizing, and guiding the change to sustainable energy systems. Objectives This review aims to examine energy system simulation modeling, emphasizing its role in analyzing and optimizing energy systems for sustainable development. Methods The paper explores four key simulation methodologies; Agent-Based Modeling (ABM), System Dynamics (SD), Discrete-Event Simulation (DES), and Integrated Energy Models (IEMs). Practical applications of these methodologies are illustrated through specific case studies. Results The analysis covers key components of energy systems, including generation, transmission, distribution, consumption, storage, and renewable integration. ABM models consumer behavior in renewable energy adoption, SD assesses long-term policy impacts, DES optimizes energy scheduling, and IEMs provide comprehensive sector integration. Case studies demonstrate the practical relevance and effectiveness of these models in addressing challenges such as data quality, model complexity, and validation processes. Conclusions Simulation modeling is essential for addressing energy challenges, driving innovation, and informing policy. The review identifies critical areas for improvement, including enhancing data quality, refining modeling techniques, and strengthening validation processes. Future directions emphasize the continued importance of simulation modeling in achieving sustainable energy systems.

To carry out artificial reforestation, it is necessary to use mechanized means – tree-planting machines. The lack of domestic tree-planting machines is one of the problems of artificial reforestation in Russia. The purpose of the study is to substantiate the design parameters of a tree-planting machine with a disk operating device. To achieve this goal, the use of modern software environments is required with the possibility of full consideration of all factors affecting the machine. In the course of this research, a solid model of a tree-planting machine has been developed by means of a computer-aided design system. The “Universal Mechanism 9.1” software package, designed for modeling the dynamics and kinematics of mechanical systems, has been chosen as a computational environment studying the parameters of the model. Only the input values for the simulation model have been introduced into the software package, since the mathematical apparatus is embedded in the core of the program. Using the software package, a simulation model of a tree-planting machine has been created, taking into account both the interaction of the machine links and the discrete contact interaction of the seedling with the machine and the soil. A computational experiment has been carries out and the kinematic and dynamic parameters of the tree-planting machine have been established, in which the feeder would not interfere with the free fallout of the briquette with the seedling. The geometric parameters of the mechanism have been determined to match the cam profile with its movement along with the disk and the operation of the roller tappet so that the grippers install the briquette with the seedling into the soil in a timely manner. The trajectory of movement of the briquette with the seedling has been found. With the help of FDM 3D-printing, a full-size model of a disk planting apparatus has been made, and a laboratory experiment has been conducted to establish the required torque on the hub of the planting apparatus disk and the shaft of the drum. The results of the experiment have confirmed the adequacy of the developed simulation model.

In this study, a steady-state thermodynamic equilibrium evaluation of CO2 methanation was conducted. Calculations were performed by solving the material balance equations using the equilibrium constants of CO2 methanation and reverse water–gas shift reactions. Results obtained from an analytical method developed with the aid of the Microsoft Excel platform were compared to simulations conducted using the commercially available free software COCO and DWSIM. The effects of temperature, pressure, and H2/CO2 ratio on CH4 yield, carbon oxide formation, and heat balance were investigated. The results indicate that the methanation process is highly favored by low temperatures and higher pressures with a stoichiometric H2/CO2 ratio. Under these conditions, CH4 output increases, and carbon formation is reduced, resulting in better performance. Simulations from all three models are in agreement, with minor differences noted in the DWSIM software.

Simulation modeling is crucial in support of probabilistic risk assessment (PRA) for nuclear power plants (NPPs). There is a challenge, however, associated with simulation modeling that relates to the time and resources required for collecting data to determine the values of the input parameters. To alleviate this challenge, this article develops a formalized methodology to generate surrogate values of input parameters grounded on the decomposition of phenomenological nondimensional parameters (PNPs) while avoiding detailed data collection. While the fundamental principles of the proposed methodology can be applicable to various hazards, the developments in this article focus on fire PRA as an example application area for which resource intensiveness is recognized as a practical challenge. This article also develops a computational platform to automate the PNP decomposition and seamlessly integrates it with state-of-practice fire scenario analysis. The applicability of the computational platform is demonstrated through a multi-compartment fire case study at an NPP. The computational platform, with its embedded PNP decomposition methodology, can substantially reduce the effort required for input data collection and extraction, thereby facilitating the efficient use of simulation modeling in PRA and enhancing the fire scenario screening analysis.

Abstract Background Evaluating sugar-sweetened beverage (SSB) taxation often relies on simulation models. We assess how assumptions about the response to SSB taxation affect the projected body weight change and subsequent health and economic impacts related to type 2 diabetes mellitus (T2DM) using Germany as an example. Methods In the main analysis, we estimated changes in energy intake by age and sex under a 20% value-added tax on SSBs in Germany using marginal price elasticities (PE) and applied an energy equilibrium model to predict body weight changes. We then quantified the impact of several assumption modifications: SSB own-PE adjusted for consumption (M1)/based on alternative meta-analysis (M2); SSB consumption adjusted for underreporting (M3); substitution via marginal (M4a) or adjusted (M4b) cross-PE/as % of calorie change (M4c). We also assessed scenarios with alternative tax rates of 10% (S1) or 30% (S2) and including fruit juice (S3). We calculated overweight and obesity rates per modification and scenario. We simulated the impact on T2DM, associated healthcare costs, and disability-adjusted life years (DALYs) over the lifetime of the 2011 German adult population with a Markov model. Data included official demographics, national surveys, and meta-analyses. Results A 20% value-added tax in Germany could reduce the number of men and women with obesity by 210,800 [138,800; 294,100] and 80,800 [45,100; 123,300], respectively. Over the population’s lifetime, this would lead to modest T2DM-related health and economic impacts (76,700 DALYs [42,500; 120,600] averted; €2.37 billion [1.33; 3.71] costs saved). Policy impacts varied highly across modifications (all in DALYs averted): (M1) 94,800 [51,500; 150,700]; (M2) 164,200 [99,500; 243,500]; (M3) 52,600 [22,500; 91,100]; (M4a) -18,100 [-111,500; 68,300]; (M4b) 25,800 [-31,400; 81,500]; (M4c) 46,700 [25,300; 77,200]. The variability in policy impact related to modifications was similar to the variability between alternative policy scenarios (all in DALYs averted): (S1) 26,400 [9,300; 47,600]; (S2) 126,200 [73,600; 194,500]; (S3) 342,200 [234,200; 430,400]. Conclusions Predicted body weight reductions under SSB taxation are sensitive to assumptions by researchers often needed due to data limitations. Because this variability propagates to estimates of health and economic impacts, the resulting structural uncertainty should be considered when using results in decision-making.

Quadrupole mass spectrometer is currently one of the most widely used small-scale mass spectrometry instruments. Studying the ions trajectory in a quadrupole field is very important for a deeper understanding of the behavior of ions in quadrupole field, which not only helps to propose new scientific and technological issues in mass spectrometry, but also has practical guidance for the development of instruments. The digital simulation of ions trajectory is an efficient mean for studying the motion of ions in quadrupole field. In this paper, a digital simulation model of quadrupole field, namely Sim-Quaq-COM-V1.0, was established based on COMSOL Multiphysics. The simulation results of the model are in good agreement with the theoretical calculation results, and it can be used as an accurate digital model to study the behavior of ions in quadrupole fields. On this basis, the motion behavior of ions in the hyperbolic quadrupole and the cylindrical quadrupole were compared, and the number of m/z 69 ions passing through the hyperbolic quadrupole field is about 4 times that of the cylindrical quadrupole field under the same conditions. The model has three advantages. Firstly, the self-designed general geometric model and grid were adopted as the built-in model, which can be used to simulate the cylindrical quadrupole field and hyperbolic quadrupole field of various geometric sizes. The modular design is simple and clear. Users only need to modify the geometric parameters and mesh parameters to generate the corresponding geometric model and high-precision mesh. Secondly, the parameters of the model could be configured uniformly in a text file, and the model parameters could be adjusted in batches by modifying the text file. Lastly, the function of multi-core and cluster in COMSOL were utilized to achieve large-scale parallel computing through multi-CPU server and quickly process a large number of ions at the same time. Compared with other models like the default COMSOL model for cylindrical quadrupole field, the simulation speed and accuracy of this model are improved. Through the simulation calculation model, the time of geometric design and modeling is saved, the global parameters can be quickly configured, and the difficulty of calculation is reduced. The model supports parallel computing technology. It is greatly improved in terms of calculation speed and calculation amount, thus can process a large number of ions at the same time, shorten the research cycle, and help the digital development of mass spectrometer design and research technology.

Abstract In order to address the issue of suppressing thermal runaway (TR) in power battery, a thermal generation model for power batteries was established and then modified based on experimental data. On the basis of simulation calculations, a scheme was designed to suppress thermal runaway of the battery module and battery pack, and samples were produced for testing. The results of the test and simulation calculations were very consistent, confirming the accuracy of the simulation calculation model. The results of thermal runaway test also demonstrate that the measures designed to suppress thermal runaway are effective and meet the design requirements.

The object of this research is an approach to simulating the combat operation of artillery in computer games based on Markov processes. In modern computer games, an important role is played by the realism and plausibility of combat simulation. One of the most difficult and at the same time most interesting tasks is the modeling of artillery operations, where it is necessary to take into account numerous factors affecting the effectiveness of combat work. The research was aimed at improving the methods and models of controlling the combat work of artillery under the conditions for the firing position change and the presence of external disturbances. The use of stochastic models allows more accurate modeling of the behavior of artillery units, taking into account the random nature of many parameters, such as projectile speed, reload time, and the probability of detection by enemy forces. The proposed approach includes the development of a simulation model that allows determining optimal strategies to achieve maximum effectiveness of combat work. The model is based on Markov processes, which allows taking into account possible system states and probable transitions between them. This allows not only to simulate combat operations, but also to predict the results depending on different scenarios. The results of the study show that the use of Markov processes in the simulation of combat operations can significantly increase the realism and efficiency of artillery operations in computer games. This opens up new opportunities for game developers to create more immersive and authentic gaming experiences. The proposed model can be used as a basis for further research and improvement of combat simulation methods in computer games. It can also be used in military simulators and simulators where realistic combat conditions must be taken into account. [ABSTRACT FROM AUTHOR]

Introduction: Energy system simulation modeling plays an important role in understanding, analyzing, optimizing, and guiding the change to sustainable energy systems. Objectives: This review aims to examine energy system simulation modeling, emphasizing its role in analyzing and optimizing energy systems for sustainable development. Methods: The paper explores four key simulation methodologies; Agent-Based Modeling (ABM), System Dynamics (SD), Discrete-Event Simulation (DES), and Integrated Energy Models (IEMs). Practical applications of these methodologies are illustrated through specific case studies. Results: The analysis covers key components of energy systems, including generation, transmission, distribution, consumption, storage, and renewable integration. ABM models consumer behavior in renewable energy adoption, SD assesses long-term policy impacts, DES optimizes energy scheduling, and IEMs provide comprehensive sector integration. Case studies demonstrate the practical relevance and effectiveness of these models in addressing challenges such as data quality, model complexity, and validation processes. Conclusions: Simulation modeling is essential for addressing energy challenges, driving innovation, and informing policy. The review identifies critical areas for improvement, including enhancing data quality, refining modeling techniques, and strengthening validation processes. Future directions emphasize the continued importance of simulation modeling in achieving sustainable energy systems. [ABSTRACT FROM AUTHOR]

The study is devoted to the development of software and information support for business analysis procedures for technological systems of aerospace manufacturing. A technique for constructing simulation models that describe the technological processes of formation of working surfaces of precision aerospace parts based on the concept of technological inheritance is proposed. Evaluation criteria and approaches to managing the stability of technological systems in terms of ensuring functional qualities of the product are proposed. [ABSTRACT FROM AUTHOR]

The paper proposes to use the method of dividing massive conductors into elementary cells to determine the distribution of the characteristics of the primary electric field at the boundaries of a liquid metal object processed by passing an electric current. Simulation modeling of the characteristics of the electric field in the melt during its treatment with a direct current by one current source or simultaneously by two using two-electrode and four-electrode systems, respectively, was carried out. It is shown that the distribution of potentials and currents at the boundaries of the container with the melt, depending on the type of the electrode system, has qualitative and quantitative differences, which determines their multivariance and makes it possible to find favorable conditions for the thermal force load of the processing object. [ABSTRACT FROM AUTHOR]

Background: Evaluating sugar-sweetened beverage (SSB) taxation often relies on simulation models. We assess how assumptions about the response to SSB taxation affect the projected body weight change and subsequent health and economic impacts related to type 2 diabetes mellitus (T2DM) using Germany as an example. Methods: In the main analysis, we estimated changes in energy intake by age and sex under a 20% value-added tax on SSBs in Germany using marginal price elasticities (PE) and applied an energy equilibrium model to predict body weight changes. We then quantified the impact of several assumption modifications: SSB own-PE adjusted for consumption (M1)/based on alternative meta-analysis (M2); SSB consumption adjusted for underreporting (M3); substitution via marginal (M4a) or adjusted (M4b) cross-PE/as % of calorie change (M4c). We also assessed scenarios with alternative tax rates of 10% (S1) or 30% (S2) and including fruit juice (S3). We calculated overweight and obesity rates per modification and scenario. We simulated the impact on T2DM, associated healthcare costs, and disability-adjusted life years (DALYs) over the lifetime of the 2011 German adult population with a Markov model. Data included official demographics, national surveys, and meta-analyses. Results: A 20% value-added tax in Germany could reduce the number of men and women with obesity by 210,800 [138,800; 294,100] and 80,800 [45,100; 123,300], respectively. Over the population's lifetime, this would lead to modest T2DM-related health and economic impacts (76,700 DALYs [42,500; 120,600] averted; €2.37 billion [1.33; 3.71] costs saved). Policy impacts varied highly across modifications (all in DALYs averted): (M1) 94,800 [51,500; 150,700]; (M2) 164,200 [99,500; 243,500]; (M3) 52,600 [22,500; 91,100]; (M4a) -18,100 [-111,500; 68,300]; (M4b) 25,800 [-31,400; 81,500]; (M4c) 46,700 [25,300; 77,200]. The variability in policy impact related to modifications was similar to the variability between alternative policy scenarios (all in DALYs averted): (S1) 26,400 [9,300; 47,600]; (S2) 126,200 [73,600; 194,500]; (S3) 342,200 [234,200; 430,400]. Conclusions: Predicted body weight reductions under SSB taxation are sensitive to assumptions by researchers often needed due to data limitations. Because this variability propagates to estimates of health and economic impacts, the resulting structural uncertainty should be considered when using results in decision-making. [ABSTRACT FROM AUTHOR]

The key to promoting high-quality economic development (HQED) is to identify the influencing factors and the complex relationships among them. Under the guidance of China's new development concept, we systematically analyze the factors influencing the HQED based on the DPSIR (Driver-Pressure-State-Impact-Response) model. We also establish a system dynamics model and adopt Vensim PLE x64 software to simulate the impact of dynamic changes on HQED, which include innovation, coordination, green, openness, sharing systems, and their combinations. The results show that increasing green investment is the most effective, followed by enhancing regional coordination, enhancing foreign trade, and improving human capital. Among the studied factors, improving livelihood is the weakest. For multiple policy scenarios, the balanced scenario is the most efficient, followed by the environment-oriented, and the weakest is the openness-oriented scenario. Interestingly, combined policies are also more effective than single policies, which does not always apply. Furthermore, the effect of the policy combination is more obvious with the strengthening of the implementation intensity, which is important for policymakers. [ABSTRACT FROM AUTHOR]

This study examines the issue of traffic organization on sections of city streets, in which there are public transport stop zones of different configurations (with a drive-in pocket and along a traffic lane). Accordingly, the object of research is the parameters of traffic flows; the subject is the regularities in their change on such specific sections of the street-road network, taking into account the configuration of stops, the number of traffic lanes, and priority conditions for the movement of public transport. The task addressed in this work was the quantitative assessment of the efficiency of traffic management in public transport stop zones. It was also important to compare different configurations of street segments in terms of their impact on delays of private and public transport. As a result of the research, the speed and time characteristics of the traffic flow and their dependence on its composition and intensity for different number and specialization of traffic lanes, as well as the location of the public transport stop, were determined. The resulting quantitative indicators of delays of all types of transport for each modeling option made it possible to determine the best of them according to the criterion of minimal time loss. This applies to both private and public transport, as the values of delays may differ from each other by 10–50 %. An applied aspect related to using the scientific result is the possibility of justifying the number of traffic lanes, or their allocation for public transport, as well as determining the appropriate configuration of stops. This constitutes the prerequisites for the transfer of the scientific results to the relevant interested structures in the field of transport, which are responsible for the organization and safety of traffic under urban conditions. [ABSTRACT FROM AUTHOR]

This paper considers the optimization of parameters for a railroad transport system. The maximum level of technological reliability and the average time spent by trains on the route are used as optimization criteria. The purpose of the study is to establish the optimal parameters for the operational process of railroad transport systems according to the criterion of the maximum level of technological reliability and the minimum time of trains on the route. Methods of technological reliability research have been proposed. Taking into account that the entire technological process is a sequential set of technological elements, a simulation model of the technological process of the transit transport-technological line along a route direction has been built. A population of agents that simulates the operation of railroad sections of the rotation of train locomotives and is a key subsystem of the simulation model has been developed and configured. The simulation model makes it possible to optimize the parameters of multi-section railroad lines. This approach is provided owing to the agent approach. As a result of the experiments, the optimal parameters of the functioning of railroad lines were established when organizing the passage of transit trains. The coefficient of utilization of the locomotive fleet fluctuates within the optimal range (0.55–0.65), which indicates the sufficiency of traction resources in the railroad system. The optimal parameters of the railroad transport system were established experimentally using the example of a train flow of 85 pairs of trains on a two-track route with five sections. The problem of "abandoned trains" has a solution but, to this end, it is necessary to increase the fleet of train locomotives by 150–200 % relative to existing standards. At the same time, even with an unlimited fleet of train locomotives, there is a fairly high probability (up to 30–50 %) of technological failures. [ABSTRACT FROM AUTHOR]

Energy distribution networks represent crucial infrastructures for modern society, and various simulation tools have been widely used by energy suppliers to manage these intricate networks. However, simulation calculations include a large number of fluid control equations, and computational overhead limits the performance of simulation software. This paper proposes a universal parallel simulation framework for energy pipeline networks that takes advantages of data parallelism and computational independence between network elements. A non-pipe model of an energy supply network is optimized, and the input and output of the network model in the proposed framework are modified, which can reduce the development burden during the numerical computations of the pipeline network and weaken the computational correlation between different simulated components. In addition, independent computations can be performed concurrently through periodic data exchange procedures between component instances, improving the parallelism and efficiency of simulation computations. Further, a parallel water pipelines network simulation computing paradigm based on a heterogeneous computer hardware architecture is used to evaluate the proposed framework's performance. A series of tests are conducted to verify the accuracy of the proposed framework, and simulation errors of less than 5% are achieved. The results of multi-threaded simulation experiments have demonstrated the feasibility of the proposed framework in a parallel computing approach. Moreover, an Advanced Micro Devices (AMD) Deep Computing Unit (DCU)-parallel program is implemented into a water supply network simulation system; the computational efficiency of this system is compared with that of its serial counterpart. The experimental results show that the proposed framework is appropriate for high-performance computer architectures, and the 18x speed-up ratio demonstrates that the parallel program based on the proposed universal framework outperforms the serial program. That provides the basis for the application of pipe network simulation on high-performance computers. [ABSTRACT FROM AUTHOR]

The quartz tuning fork (QTF) is a promising instrument for biosensor applications due to its advanced properties such as high sensitivity to physical quantities, cost-effectiveness, frequency stability, and high-quality factor. Nevertheless, the fork's small size and difficulty in modifying the prongs' surfaces limit its wide use in experimental research. Our study presents the development of a QTF immunosensor composed of three active layers: biocompatible natural melanin nanoparticles (MNPs), glutaraldehyde (GLU), and anti-IgG layers, for the detection of immunoglobulin G (IgG). Frequency shifts of QTFs after MNP functionalization, GLU activation, and anti-IgG immobilization were measured with an Asensis QTF F-master device. Using QTF immunosensors that had been modified under optimum conditions, the performance of QTF immunosensors for IgG detection was evaluated. Accordingly, a finite element method (FEM)-based model was produced using the COMSOL Multiphysics software program (COMSOL License No. 2102058) to simulate the effect of deposited layers on the QTF resonance frequency. The experimental results, which demonstrated shifts in frequency with each layer during QTF surface functionalization, corroborated the simulation model predictions. A modelling error of 0.05% was observed for the MNP-functionalized QTF biosensor compared to experimental findings. This study validated a simulation model that demonstrates the advantages of a simulation-based approach to optimize QTF biosensors, thereby reducing the need for extensive laboratory work. [ABSTRACT FROM AUTHOR]

Quadrupole mass spectrometer is currently one of the most widely used small-scale mass spectrometry instruments. Studying the ions trajectory in a quadrupole field is very important for a deeper understanding of the behavior of ions in quadrupole field, which not only helps to propose new scientific and technological issues in mass spectrometry, but also has practical guidance for the development of instruments. The digital simulation of ions trajectory is an efficient mean for studying the motion of ions in quadrupole field. In this paper, a digital simulation model of quadrupole field, namely Sim-Quaq-COM-V1.0, was established based on COMSOL Multiphysics. The simulation results of the model are in good agreement with the theoretical calculation results, and it can be used as an accurate digital model to study the behavior of ions in quadrupole fields. On this basis, the motion behavior of ions in the hyperbolic quadrupole and the cylindrical quadrupole were compared, and the number of m/z 69 ions passing through the hyperbolic quadrupole field is about 4 times that of the cylindrical quadrupole field under the same conditions. The model has three advantages. Firstly, the self-designed general geometric model and grid were adopted as the built-in model, which can be used to simulate the cylindrical quadrupole field and hyperbolic quadrupole field of various geometric sizes. The modular design is simple and clear. Users only need to modify the geometric parameters and mesh parameters to generate the corresponding geometric model and high-precision mesh. Secondly, the parameters of the model could be configured uniformly in a text file, and the model parameters could be adjusted in batches by modifying the text file. Lastly, the function of multi-core and cluster in COMSOL were utilized to achieve large-scale parallel computing through multi-CPU server and quickly process a large number of ions at the same time. Compared with other models like the default COMSOL model for cylindrical quadrupole field, the simulation speed and accuracy of this model are improved. Through the simulation calculation model, the time of geometric design and modeling is saved, the global parameters can be quickly configured, and the difficulty of calculation is reduced. The model supports parallel computing technology. It is greatly improved in terms of calculation speed and calculation amount, thus can process a large number of ions at the same time, shorten the research cycle, and help the digital development of mass spectrometer design and research technology. [ABSTRACT FROM AUTHOR]

Understanding the factors influencing species range limits is increasingly crucial in anticipating migrations due to human‐caused climate change. In the boreal biome, ongoing climate change and the associated increases in the rate, size, and severity of disturbances may alter the distributions of boreal tree species. Notably, Interior Alaska lacks native pine, a biogeographical anomaly that carries implications for ecosystem structure and function. The current range of lodgepole pine (Pinus contorta var. latifolia) in the adjacent Yukon Territory may expand into Interior Alaska, particularly with human assistance. Evaluating the potential for pine expansion in Alaska requires testing constraints on range limits such as dispersal limitations, environmental tolerance limits, and positive or negative biotic interactions. In this study, we used field experiments with pine seeds and transplanted seedlings, complemented by model simulations, to assess the abiotic and biotic factors influencing lodgepole pine seedling establishment and growth after fire in Interior Alaska. We found that pine could successfully recruit, survive, grow, and reproduce across our broadly distributed network of experimental sites. Our results show that both mammalian herbivory and competition from native tree species are unlikely to constrain pine growth and that environmental conditions commonly found in Interior Alaska fall well within the tolerance limits for pine. If dispersal constraints are released, lodgepole pine could have a geographically expansive range in Alaska, and once established, its growth is sufficient to support pine‐dominated stands. Given the impacts of lodgepole pine on ecosystem processes such as increases in timber production, carbon sequestration, landscape flammability, and reduced forage quality, natural or human‐assisted migration of this species is likely to substantially alter responses of Alaskan forest ecosystems to climate change. [ABSTRACT FROM AUTHOR]

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