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The aim of this paper is the development of a mathematical model to compute the optimal inventory mix to face stochastic demand at minimum cost in a two-level supply chain. The paper addresses a multi-product dynamic lot-sizing problem under stochastic demand subject to capacity and service level constraints. This model is executed to compare a Make To Order (MTO) strategy to a Vendor Managed Inventory (VMI) partnership between the supplier and their customers. Both strategies provide the demand order to be produced. A schedule of production orders is determined over the planning horizon in order to minimize the inventory holding costs of the supply chain, taking into consideration that the supplier is also responsible of initiating the replenishment orders and deliveries of their customers according to the VMI partnership. The simulation model is illustrated empirically using a real case study: a paper manufacturing company that pursues to improve customer service level and supply chain inventory costs through a proper production planning of their paper machines and a suitable VMI order replenishment schedule. [ABSTRACT FROM AUTHOR]

• Combined effects of extruded brick compositions with paper sludge and expanded perlite were characterized. • The use of additives in bricks has significantly affected their thermo-physical and mechanical properties. • The effects of process parameters on brick properties were investigated with a new mathematical modeling approach. • Fired brick samples showed good thermal insulation performance. • Produced exruded bricks have good potential for energy saving. Lightweight bricks produced with addition of different additive materials such as expanded perlite (EP) and recycling paper sludge (RPS) waste have been accomplished by a pug mill. Porous fired bricks were produced by using organic and inorganic additives such as paper waste and expanded perlite as pore-makers. In the experimental study, the seventeen mixture sets were prepared with Box-Behnken experimental design procedure of two additive ratios and firing temperatures. The brick samples were produced with shaping by extrusion method and firing at 850, 950 and 1050 °C for two hours after drying. Physical characteristics such as bulk density, apparent porosity and water absorption, and also, compressive strength, thermal conductivity and microstructural properties of brick samples were studied. Influences of process parameters on brick properties were investigated with a detailed neuro-regression analysis. In conclusion, the best brick composition (10 % EP + 10 %RPS by weight) in terms of thermal conductivity corresponding to acceptable mechanical properties was optimized. Accordingly, the compressive strength values of all samples are around 10 to 27 MPa. Also, the samples with high additive content (especially 10 %RPS + 5 %EP sample) exhibited the lowest thermal conductivity value (0.432 W/mK) due to the low firing temperature. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that students who are engaged in learning tasks and make errors before receiving instruction on how to complete them, achieve better learning outcomes than students who first receive instruction and then complete the learning activities with the aim of avoiding errors. Although simulation literature often refers to errors as learning opportunities, to date, there is limited understanding of how pedagogical approaches that promote learning from errors can guide the design of simulation-based learning in healthcare education. To (a) present the Learning from Errors conceptual model; and (b) provide an example of how educators can use this model. The Learning from Errors model is drawn from critical elements of two pedagogical approaches, productive failure and error management training and pedagogical features of high-quality healthcare simulations. We describe the Learning from Errors model, which emphasises the need for adopting pedagogical methods that explicitly use errors as learning opportunities and ultimately inform simulation design. We then illustrate the application of this model to a simulation example. The model includes the following elements: i) normalisation of errors, ii) challenging simulation scenarios, iii) self-directed learning, iv) collaborative teamwork and v) comparison with best practice. This discussion paper presents the Learning from Errors conceptual model, an evidence-based approach that can assist educators in the design of simulations that embrace errors as a catalyst for learning. [ABSTRACT FROM AUTHOR]

Stochastic cellular automata for rock-paper-scissors games are related to Lotka-Volterra model. Simulations are usually performed by two methods local and global interactions. It is well known that the population dynamics with local interaction is stable, where all species coexist. In contrast, global interaction leads to extinction. So far, theories such as mean-field theory and pair approximation have been presented, but they never explained the stable dynamics in local simulation. In the present article, we apply effective medium approximation (EMA) which has been developed in Physics. The effective medium is determined in a self-consistent way. The EMA theory well predicts the stability of population dynamics. Moreover, it fairly explains the aggregation of each species observed in the stationary state. [ABSTRACT FROM AUTHOR]

Significant dimensional variations may occur in paper-based materials when subjected to changes in moisture content. Moisture induced deformations are governed by the swelling of individual fibres, which is transferred through inter-fibre bonds to the entire fibrous network. Complex interactions between mechanical and hygro-expansive properties take place in the bonding areas, affecting the overall material response. In most network models, the role of these inter-fibre bonds is not explicitly incorporated. This work presents a periodic meso-structural model for the discrete fibrous network, which considers the free-standing fibre segments and inter-fibre bonds. Despite its simplicity, the reference unit-cell enables the incorporation of relevant micro- and meso-structural features such as network structure, fibres and bond geometry and hygro-elastic properties. The proposed model is solved analytically through a proper homogenization strategy, allowing to recover the paper’s anisotropic hygro-mechanical response in terms of effective elastic constants and effective hygro-expansive coefficients, exploiting the coupling at the meso-structural level between hygroscopic and mechanical behavior. A comparison with experimental results obtained from the literature shows that the presented approach is quite accurate in predicting the overall paper response, thereby revealing the influence of several meso-scale parameters (e.g. fibre orientation, dimensions, mechanical strength). [ABSTRACT FROM AUTHOR]

This discussion is based on the paper by Farshidianfar and Soheili [1] . In this paper, the authors consider Soil–Structure Interaction effects (SSI) and optimize parameters of Tuned Mass Dampers (TMD) to decrease the earthquake vibrations of tall buildings. They also develop a mathematical model based on the time domain analysis. In this discussion we show that the offered model is not accurate enough and we rectify the model. [ABSTRACT FROM AUTHOR]

We propose a new concept which is a generalization of fuzzy soft subset and fuzzy soft equal. Using such notions, we will be able to consider the distributive law of fuzzy soft sets. Using the distributive law of fuzzy soft sets, we point out that the distributive law of trapezoidal fuzzy soft sets as proposed by Xiao et al. (2012) is not true. The correction will further improve further extensions of the results of Xiao et al. (2012). We will also establish the generalized distributive law of trapezoidal fuzzy soft sets along with illustrative examples. [ABSTRACT FROM AUTHOR]

The present comment concerns some doubtful results included in the above papers. [ABSTRACT FROM AUTHOR]

Motivated by the art of curved crease origami we study mathematical models for folding ideal paper along curved creases. We approach the problem of finding mathematical descriptions in terms of developable surfaces of those shapes which can be folded from real paper but where its rigorous description is very often unknown. For that we investigate a particular one-parameter family of surfaces isometric to a given planar surface patch. For each such surface we parametrize the crease curves which fold those surfaces into cylinders and cones. We apply our methods to explore curved crease origami designs, such as tessellations of the plane and cylinders. • We compute explicit isometric deformations of developable surfaces that are guided by sliding on planes. • We give explicit parametrizations of crease curves between developable surfaces and cylinders and cones. • We illustrate our methods on examples such as curved crease tessellations of cylinders and planes. [ABSTRACT FROM AUTHOR]

We used the random forest classifier to predict Gross Motor Function Classification System (GMFCS) levels I-IV from patient reported abilities recorded on the Gillette Functional Assessment Questionnaire (FAQ). The classifier exhibited outstanding accuracy across GMFCS levels I-IV, with 83%-91% true positive rate (TPR), area under the receiver operation characteristic (ROC) curve greater than 0.96 for all levels, and misclassification by more than one level only occurring 1.2% of the time. This new approach to GMFCS level assignment overcomes several difficulties with the current method: (i) it is based on a broad spectrum of functional abilities, (ii) it resolves functional ability profiles that conflict with existing GMFCS level definitions, (iii) it is based entirely on self-reported abilities, and (iv) it removes complex age dependence. Further work is needed to examine inter-center differences in classifier performance-which would most likely reflect interpretive differences in GMFCS level definitions between centers. [ABSTRACT FROM AUTHOR]

The last-mile delivery challenges and complexity are increasing simultaneously with the e-commerce growth, the e-commerce growth constitutes a threat to urban transport, especially for big cities and developing countries. This paper examines the economic impact of crowd-shipping based on public transport collaborated with the automated parcel locker and the impact of traditional delivery, as two different methods of last-mile delivery under the same circumstances. This paper aims to assess crowd-shipping as an alternative solution for last-mile delivery compared to traditional delivery. Data has been simulated based on Cairo reality, one of the largest cities in the world. The mathematical models were formulated for the problem, where the first model objective function minimizes the costs of vehicle possession and vehicle kilometers traveled, while the second model objective function minimizes the costs of establishing lockers, vehicle possession, and vehicle kilometers traveled. A genetic algorithm has been used due to the complexity of the problem. The results show that the economic impact of the crowd-shipping delivery system is better than the traditional delivery system under the conditions of large-sized and medium-sized demand, while the economic impact of traditional delivery is better than the crowd-shipping delivery system under the conditions of small-sized demand. [ABSTRACT FROM AUTHOR]

Safe operation of orbital platforms relies heavily on stability of fluid flows in microgravity, which are strongly affected by capillary forces. The paper considers multiphase fluid seepage through a porous medium. Questions of instability of the interface between liquids are discussed. The effect of capillary instability is shown, which was revealed during the processing of experimental data on the imbibition of a porous structure in microgravity conditions during parabolic flights. A mathematical model is proposed to describe the process of multiple imbibition of a porous medium under conditions of variable gravity. The model takes into account hysteresis, various models of capillary pressure are used during imbibition and drainage. The paper also considers a method for modeling the instability by transforming the constitutive equations. The method allows modeling additional blurring of the imbibition front. The results of modeling based on this method for capillary imbibition of a porous medium under microgravity conditions, as well as for the case when chemical interactions occur between flowing fluids, are considered. • The instability of the phase boundary during seepage is considered. • Flows are studied controlling safe operation of spacecraft fluid supply systems. • A new mathematical model for describing the multiple imbibition is proposed • The seepage with chemical interactions between the phases is considered. [ABSTRACT FROM AUTHOR]

Center winding is one of the most suitable and universal schemes in the winding mechanism. In general, the quality of wound rolls is significantly degraded by axial slip. In this paper, an advanced winding tension method is proposed to overcome axial slip. Firstly, the axial slip mechanism is analyzed by means of the mutual mechanical relationship between the layers of the center-wound roll. Secondly, a mathematical model for overcoming axial slip was developed based on the correlation between axial slip and winding tension. Then, based on the mathematical model, a special neural network structure with back propagation training is developed so that the winding tension is dynamically updated with the winding radius. Finally, a roll-to-roll slitting system for lithium-ion battery pole pieces is proposed and used to verify the performance of the proposed method. The experiments show that there is no quality problem of axial slip in the center-wound rolls wound by the winding tension control method proposed in this paper. It shows that the winding tension control method proposed in this paper is effective in preventing axial slip. • The mechanism of axial slip of the center-wound roll is described systematically. • A special neural network structure is used to solve the winding tension. • It is of great significance to improve the winding process of flexible materials. [ABSTRACT FROM AUTHOR]

• A chamber model considering pressure distributions of compressors is proposed. • An exhaustive mathematical model and an efficient solution method are provided. • More geometry features and compression mechanisms can be investigated. • Parametric studies are performed using the new model with good trends. Further efficiency improvements of screw compressors rely on computer modeling and mathematical analysis at the design stage. As speed and capacity increase, the uniformity assumption used in the conventional chamber model for twin-screw compressors is no longer suitable. At the same time, CFD simulations are complicated and time-consuming for design optimization. Therefore, in this paper, a chamber model considering pressure distribution is proposed, which is fast enough and more applicable. Each working unit of a screw compressor is considered a one-dimensional compressible transient flow with two moving pistons, which allow the passage of fluid. Numerical methods of the model are verified by a shock wave test. A twin-screw compressor was also simulated and the results of the chamber model were compared with the CFD results. Pressure fluctuations like those in previous experimental studies can be captured in the simulated indicator diagram. General trends with different speeds, suction ports, and wrap angles could also be recognized in the simulation results. The compression process and the influence of structural parameters on the compressor's functioning are revealed intuitively. By combining existing chamber models, the applicability of the new model can be further extended, and it is expected to be a helpful tool for compressor design. [ABSTRACT FROM AUTHOR]

In this paper, we develop and study a new mathematical model to describe the good functioning of the biodenitrification process, combining both the biological and the mechanical aspects, and taking into account the chemotaxis-phenomenon. The model is governed by a non-linear reaction-diffusion-advection system for the bacterial activity and the Darcy flow for the porous medium. We prove the existence and uniqueness of the solution and we carry out the numerical approximation of the model within a variational framework. We propose a full discrete system based on a finite element method and we perform numerical simulations both in 2D and 3D. [ABSTRACT FROM AUTHOR]

This paper proposes a model to predict the tensile characteristics of metal fused filament fabricated (MFFF) components. The proposed model consists of mathematical, experimental, and finite element (FE) models. The mathematical model was constructed based on the composite laminate theory and was combined with experiments for basic layup of 0° and 90° raster angle to describe the behavior of MFFF parts. The FE model was built to simulate the behavior of MFFF parts in a virtual environment and its validity was verified using independent experiments for a more common layup of +45°/−45°. • Predicts the mechanical properties of a MFFF specimen printed with antisymmetric layup. • Models the anisotropic material behavior of MFFF parts using classic laminate theory. • Introduces the procedure for fabricating defect free metal FFF sample. • Investigates the effect of FFF process parameters on the quality of metal parts. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model in the biofilm phase and in the gas phase that has been successfully applied to investigate various aspects of the biofiltration process. The mixtures of volatile organic compounds (VOCs) are emitted from a wide range of industries, such as chemical, petrochemical, pharmaceutical, pulp paper mills, printing and paint workshops, etc. The objective of the present study is, presence of high n-propanol loading negatively affected the toluene removal; however, n-propanol removal was not affected by the presence of toluene and was effectively removed in the biofilter despite high toluene loadings. A model for toluene and n-propanol biofiltration could predict the cross-inhibition effect of n-propanol on toluene removal. Further, we studied the effects of many physical and biological parameters on model prediction. The mathematical equations (2.12)-(2.16) which are non-linear partial differential equations are solved by using the homotopy perturbation technique. Also, we derived the semi-analytical results for toluene and n -propanol concentrations for saturated and unsaturated kinetics. It is verified that the proposed solution is validated by comparing it with numerical solutions. • Here mathematical modelling is developed for bio-filtration in the biofilm phase. • The adopted model investigate various aspects of the bio-filtration process. • Analytical results is obtained via Homotopy Perturbation Technique. • The obtained solutions is verified for accuracy with existing literature. [ABSTRACT FROM AUTHOR]

Two-phase flows under microgravity conditions play a crucial role in Space technology and science. Studying the behavior of dispersed droplets suspended in a gas flow and their influence on the characteristics of the carrier flow is the main task of computational modeling of turbulent two-phase flows. To understand the features and predict the behavior of such flows, along with experimental studies, it is necessary to develop mathematical models, which adequately describe all the basic physical and chemical processes in a gas-droplet environment at different scales. In this paper we obtain solutions for the problem of two droplets collision, using solutions for cumulative jets, and propose droplet collision outcome criterion. This research will focus on the process of two interacting droplets coalescence into one and coalescence with subsequent separation into two or more droplets. A semi-analytical method has been developed for application of the solution of the cumulative jet problem to the problem of droplet collision. A differential equation has been obtained that describes the following possible outcomes of droplet collision: coalescence and coalescence with subsequent separation. A criterion for determining the outcome of on-head droplet collision has been obtained. In accordance with the developed criterion, the number and size of formed droplets are obtained. The effect of collision on moving droplet evaporation in a heated atmosphere was regarded. • Solutions for the problem of two droplets collision and fragmentation are obtained. • A differential equation has been obtained that describes droplet coalescence or atomization. • A criterion for droplet fragmentation has been obtained. • The effect of collision on moving droplet evaporation in a heated atmosphere was regarded. [ABSTRACT FROM AUTHOR]

• A modified evaporative condenser model with 4 characteristic parameters is proposed. • Data screening and supplementation methods are developed for on-site applications. • The average relative errors of the training and test sets are 2.10 % and 2.87 %. • Air–water mass transfer is the major factor in enhancing thermodynamic performance. Evaporative condensers (ECs) have been widely adopted in the fields of refrigeration, petrochemicals, etc. owing to the advantages of low water and energy consumption. However, due to the lack of a reliable mathematical model, the energy-saving potential of ECs remains unexplored. To realize thermodynamic performance predictions under on-site conditions, a generic model with 4 characteristic parameters, that could be identified specifically for different ECs, is innovatively proposed in this paper. Taking the refrigeration system of a food factory as a case study, a well-organized data processing method including filtering, screening, and supplementation is established. The processed real-operating data is used for characteristic parameters identification and model validation. Simulations indicate satisfactory transferability and a good agreement between the test and simulated results, with average relative errors of 2.10 % and 2.87 % for the training and test sets, respectively. Based on the proposed model, the overall performance and the working fluids' thermodynamic state of the EC during operation are investigated carefully. It could be concluded that the air–water mass transfer is the dominating factor in enhancing EC's thermodynamic performance, and air flow shows greater significance than water in improving heat exchange capacity. The heat exchange intensity of the superheating and two-phase zones is similar, while that of the subcooling zone is the lowest, averaging only 37.9 %. [ABSTRACT FROM AUTHOR]

The mealybug (Paracoccus marginatus) is one of the most important pests of papaya (Carica papaya L.). The high potential damage of this pest threatens papaya production. The objective of this paper is to explore the impact of biocontrol and temperature variations on the population dynamics of Paracoccus marginatus (P. marginatus). We first propose and study a mathematical model for the dynamics of P. marginatus within a papaya field. This model consists of a time-delayed non-autonomous system of differential equations that takes into account the egg incubation period, temperature variations, plant compensation and predators that are natural enemies of the papaya pest. We provide the basic properties of the model, compute the basic offspring number N 0 and show that there exists two threshold parameters N _ 0 and ξ 0 such that N _ 0 ≤ N 0 ≤ ξ 0 ≤ 1 and N 0 ≥ N _ 0 > 1 provide conditions for the extinction and persistence of the pest within the papaya field, respectively. After, we investigate the impact of biocontrol on the pest population. We found that the use of a control strategy based on constant releases of predators could reduce the pest population by 35.62 percent and increase the biomass by 77.50 percent, while the use of impulsive releases of predators result in a decrease of 96.31 percent of the pest population and an increases of 55.74 percent of the biomass. We also combine the use of continuous predator releases and bio-pesticides and discovered that a spray applied 90 days after germination could completely eliminate the pest population and boost the biomass by 81.58 percent. • The population dynamics of Paracoccus marginatus , papaya pest is modeled. • The model includes the egg incubation period, temperature variations and biocontrol. • The warm temperatures are favorable to the development and survival of the pest. • The use of impulsive releases of predators can reduce the pest by 96.31%. • The use of continuous releases of predators and bio-pesticides can eradicate the pest. [ABSTRACT FROM AUTHOR]

Earth observation satellite (EOS) scheduling is critical for improving the performance of Earth observation system. Most of the existing studies on satellite observation scheduling problems focus on static tasks and real-time dynamic tasks also known as emergency tasks while few attempts have been made for common dynamic tasks yet. The common dynamic tasks are characterized by uncertain arrival times and delayable observations while the emergency tasks require immediate observations. The number of common dynamic tasks is rapidly increasing with the expansion of satellite observation applications, which poses great challenges to EOS observation scheduling. To address this issue, this paper investigates the satellite observation scheduling problem with common dynamic tasks. Firstly, a centralized onboard dynamic scheduling framework based on a periodic-triggered rolling horizontal optimization (RHO) strategy is proposed and a novel two-stage mathematical model is established for the periodic rescheduling problem. Secondly, we propose a low-complexity onboard periodic rescheduling algorithm (OPR), which consists of a greedy-based task allocation algorithm, a pointer network (Ptr-network) based task scheduling algorithm and an iterative local search algorithm. In the greedy-based task allocation algorithm, we define a Task-EOS Fitness Indicator (TEFI) and each task is greedily allocated to the EOS with maximum TEFI. In the Ptr-network based task scheduling algorithm, the allocated task sets of all EOSs are fed into the Ptr-network in parallel to generate the observation scheduling result. Afterward, an iterative local search algorithm is proposed to further improve the quality of the observation scheduling result. Finally, extensive experiments are conducted to demonstrate the superiority of the OPR algorithm for the satellite observation scheduling problem with common dynamic tasks. [ABSTRACT FROM AUTHOR]

Energy efficient permutation flowshop scheduling problem (PFSP) is widely studied to reduce the energy consumption in manufacturing systems. Most traditional studies make the premise that setup time is a component of processing time. However, this assumption does not satisfy the small batches, more varieties manufacturing models criterion. Therefore, energy efficient PFSP with setup times thus becomes a pressing problem that needs to be resolved. The contribution of this paper includes: (1) a permutation flowshop scheduling problem (PFSP) mathematical model by considering energy consumed and setup time by each machine in the system; (2) a grey-wolf algorithm optimization with variable neighborhood search (VNS) method (GWO_VNS) is proposed for the multi-objective PFSP model; (3) solved 9 benchmarks problems of Taillard (1993) [8] for the minimization of flowtime (FT) and energy consumption (EC). The performance of the proposed GWO_VNS algorithm is evaluated on the benchmark problems selected from the published literature [15]. It is noted that the proposed algorithm performed better on both the objectives i.e., FT and EC minimization. Overall, the proposed algorithm achieved 33.25% and 30.56% average improvement in FT and EC minimization respectively on benchmark problems. [ABSTRACT FROM AUTHOR]

• Reviews the mathematics of the EOQ/EPQ-based reverse logistics models. • It provides a condensed review of the works that stemmed from the work of Schrady (1967). • It identifies significant research gaps and provides future research directions. This paper reviews the mathematics of the economic order/production quantity (EOQ/EPQ)-based models in the reverse logistics (RL) literature. It starts with the seminal work of Schrady (A deterministic inventory model for reparable items. Naval Research Logistics Quarterly, 14(3), 1967, 391–398) up until December 31, 2022. It provides researchers with a road map of how the mathematics has evolved since the work of Schrady and saves them time and effort by avoiding the need to review the entire RL literature. As it unifies the notations for all reviewed models, it also provides some research pointers for promising topics to be pursued. [ABSTRACT FROM AUTHOR]

The red palm weevil is one of the most dangerous pests affecting date palm trees in the Gulf region and the Middle East. This paper investigates the control of the red palm weevil (RPW) in date palms using several techniques, namely stem injection, sex pheromone traps, and the Sterile Insect Technique. A mathematical model describing the spread of the red palm weevil is presented, and the boundedness of the solution for the RPW system is studied. The conditions for local stability, forward bifurcation, and Hopf bifurcation are also obtained. Additionally, this research highlights the significance of optimal control in managing RPW and simulates the model using the Forward-Backward Sweep numerical method. It is observed that the parameters of the sterile insect technique, the pheromone trap, and the mechanical injection play important roles in controlling the RPW. Mechanical Injection may be more effective in controlling the palm weevil compared to the other two methods. [ABSTRACT FROM AUTHOR]

In-band network telemetry is a powerful framework for network monitoring. It allows the collection of telemetry data in real-time and provides network-wide visibility. However, depending on the routing of network flows and which telemetry data are collected, the network-wide visibility and the performance of monitoring applications may decrease. In this paper, we present the in-band network telemetry problem and extend the existing mathematical optimization models of the problem by proposing a new model that computes the routing of network flows. Results show that the new model outperforms existing models in term of network coverage and monitoring applications performance. The results of this work can be useful for network managers and enterprises to gain real-time insights into network performance. [ABSTRACT FROM AUTHOR]

• A new design of an oil-free rotary-vane compressor with a mechanical efficiency exceeding 0.9 has been proposed. • A mathematical model for calculating power losses due to friction for the new design of an oil-free rotary-vane compressor has been developed, with a calculation error not exceeding 10 %. • The power losses due to friction in the working chamber of the new oil-free rotary-vane compressor in the range of rotor speeds from 1000 to 3700 rpm are 4 to 20 times lower than those for the traditional design. Additionally, the frictional power losses in the rotor slot are 20–30 % lower, and on the stator, they are 16–20 times lower. This paper presents the design of an oil-free rotor vane stage with a new tribological scheme. The new scheme differs from existing ones in that the sealing vane contain protrusions that rest on rolling unloading bearings located in the end covers of the cylinder. Experimental results on friction power losses in the new and traditional stages are provided, demonstrating that the implementation of the new stage design allows for an average reduction in friction power losses by a factor of 10. A mathematical model for calculating friction power losses in the rotor vane type compressor stage, implementing the new tribological scheme, has been developed. The analysis based on the mathematical model confirms the possibility of achieving mechanical efficiency values higher than 0.9 in oil-free rotor vane stages with a pressure ratio of 3 and a rotor speed of 3000 rpm, through the use of the new tribological scheme. It has been found that there is a redistribution of the importance and values of the main design parameters recommended for the design of oil-free rotor vane stages with the new tribological scheme, which determine its structural configuration, compared to its traditional design. [ABSTRACT FROM AUTHOR]

Identification of a multi-input/single-output system enables the creation of a mathematical model that as accurately as possible represents the input-output relation induced by a physical system. When there is little information about the physical laws related to the system or when the system is too complex, methods such as parametric identification are used to define the system model. In that case, preliminary assumptions can be made about the system leading to a parametric aggregation function based model. This parametric model may be learned by estimating the parameters of this aggregation function from a representative set of inputs/outputs. A major difficulty is to design a model that is relatively simple yet precise enough to meet the user's needs. Linear models are commonly used because they meet these two contradictory constraints. However, use of a linear model is often at the expense of the accuracy of input-output relationship description. In a recent paper, a new modeling approach was proposed, under the name of macsum modeling [31] , which aims at replacing the linear model concept by a set of linear models. The obtained aggregation function leads to an interval-valued output. This represents the lack of accuracy of the model to predict the system output when the inputs are known. An interesting feature of this model is that it is ruled by a single precise parametric vector whereas the output is imprecise. Moreover, the vector dimension is equal to that of the input space. In this paper, we propose a method to learn such a model so that it best reflects the input-output relationship of the considered system. This method is based, as in the case of linear modeling, on a regression method. This is particularly new approach because the macsum aggregation is based on a Choquet integral and very few authors have proposed learning of an aggregation function based on the Choquet integral. [ABSTRACT FROM AUTHOR]

The quest for a theory of cities that could offer a quantitative and systematic approach to managing cities represents a top priority. If such a theory is feasible, then its formulation must be in a mathematical way. As a contribution to organizing the mathematical ideas that deal with such a systematic way of understanding urban phenomena, we review the main theoretical models present in the literature that aim at explaining the origin and emergence of urban scaling. We intend to present the models, identify similarities and connections between them, and find situations in which different models lead to the same output. In addition, we report situations where some ideas initially introduced in a particular model can also be introduced in another one, generating more diversification and increasing the scope of the original works. The models treated in this paper explain urban scaling from different premises, i.e. from gravity ideas, densification and cites' geometry to a hierarchical organization and social network properties. We also investigate scenarios in which these different fundamental ideas could be interpreted as similar — where the similarity is likely but not obvious. Furthermore, concerning the gravity model, we propose a general framework that includes all analyzed models as particular cases. We conclude the paper by discussing perspectives of this field and how future research designs and schools of thought can build on the ideas treated here. • We review the mathematical models which explain the emergence of urban scaling. • We identify similarities and connections between these models. • Models consider different premises, e.g. gravity ideas, cities' geometry, and network properties. • Regarding the gravity idea, we propose a general framework [ABSTRACT FROM AUTHOR]

The traveling salesman problem (TSP) is one of the classic research topics in the field of operations research, graph theory and computer science. In this paper, we propose a generalized model of traveling salesman problem, denoted by generalized traveling salesman path problem. Let G = (V , E , c) be a weighted complete graph, in which c is a nonnegative metric cost function on edge set E , i.e., c : E → R +. The traveling salesman path problem aims to find a Hamiltonian path in G with minimum cost. Compared to the traveling salesman path problem, we are given extra vertex subset V ′ and edge subset E ′ in the problem proposed in this paper; its goal is to construct a path which traverses all the edges in E ′ while only needs to visit each vertex in V ′ exactly once. Based on integer programming, we give a mathematical model of the problem, and design a 1 + 5 2 -approximation algorithm for the problem by combining linear programming rounding strategy and a special graph structure. • In this paper, we consider a generalized model of traveling salesman problem. • Based on integer programming, we give a mathematical model of the problem. • Combining linear programming rounding strategy and a special graph structure, we propose a 1 + 5 2 -approximation algorithm. [ABSTRACT FROM AUTHOR]

The reliable incorporation of hydrogen as a clean energy source necessitates an in-depth comprehension of the dynamics of flammable clouds resulting from potential leakage incidents. This research introduces an innovative model rooted in the principles of the kinetic theory of gases to determine the dimensions of flammable hydrogen clouds during leaks. The model integrates critical variables such as leak rate, leak direction, wind speed, and wind direction, in addition to surrounding atmospheric conditions, offering a precise forecast of hydrogen dispersion and behaviour during leakage scenarios. This modelling approach relies on two dimensionless groups derived through dimensional analysis, and the correlation between these groups has been established. Furthermore, the model incorporates three constants accounting for hydrogen buoyancy, gas dilution, and mixing, which are fine-tuned through a minimal number of Computational Fluid Dynamics (CFD) simulations. This indispensable information is crucial for the formulation of effective safety protocols, evacuation plans, and risk assessment strategies. Validation of the model against simulated data attests to its accuracy and reliability, underscoring its potential as a valuable tool for steering the secure integration of hydrogen technologies. This research significantly contributes to the advancement of safety measures in the utilisation of hydrogen as a clean energy source, providing a robust foundation for the design and implementation of precautionary measures in real-world applications. • A method for predicting hydrogen flammable cloud size based on dimensional analysis and CFD is proposed. • This method allows an improvement in the calculation efficiency while ensuring its accuracy. • A detailed comparative analysis of three prediction methods was presented in this paper. • This method is suitable for explosion risk analysis during the preliminary design phase. [ABSTRACT FROM AUTHOR]

The paper considers a process of a controlled attitude motion of a dual-spin nanosatellite. The main goal of control is to achieve a gravitationally stabilized position in a circular orbit in the shortest possible time. The dual-spin nanosatellite contains a gravitational damper and an internal rotor inside a movable unit. The movable unit can fulfill small controlled inclination relative to the main body of the nanosatellite. The mathematical model of the attitude dynamics of the nanosatellite is built and appropriate control laws are developed. Simulation results confirm the performance of the gravitational damper and efficiency of the control algorithm. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of optimizing energy efficiency in production shop scheduling problem, focusing specifically on the constraint of sequence-dependent setup times (FSSP SDST). This study is conducted in the context of promoting green industrial practices. The main objective is to minimize total energy consumption (TEC) in the manufacturing process. We introduce a mathematical model of this problem. To solve this problem, we use the Artificial Bee Colony algorithm (ABC). In addition, the Migrating Birds Optimization (MBO) algorithm will be presented. The effectiveness of the proposed algorithms will be subjected to rigorous evaluation through detailed tests on different instances. This methodical approach will enable us to carry out an in-depth and detailed comparative analysis, highlighting the relative strengths and weaknesses of the algorithms presented in this study. [ABSTRACT FROM AUTHOR]

Southeastern Turkey perished by the M w 7.8, Kahramanmaras earthquake on February 6, 2023, at 01:17 UT (04:17 LT). The Kahramanmaras-centered event, hit by the break of the East Anatolian Fault Line, is felt in Syria, Egypt, Lebanon, Iraq, and Cyprus on the border of Turkey. Together with Syria, it causes loss of lives and severe damage in 10 cities. This work is dedicated to the people of the region. The study discusses the causality of anomalies by conducting ionospheric anomaly research via the interpolated TEC map obtained from the CODE according to the coordinates of the epicenter of the earthquake (latitude, longitude). The TEC amplitudes are observed by evolving the time-domain TEC map into the frequency-domain with the Fourier transform. The peaks of the amplitudes allow preliminary information for the anomaly days. For the anomaly, the TEC (TECU) boundaries are drawn by the statistical specification. The TEC map outside these boundaries is marked as an anomaly. The causality of abnormalities is tried to be read through the triad of the geomagnetic storm(s) , solar activity , and the earthquake effect. One can find seven anomaly days in the paper. January 30, February 2, 3, 11, 15, 16, and 21 are the anomaly days. The essay probably detects the anomaly before 3 days related to the Southeastern earthquake. • Reads the causality of the earthquake in southeast Turkey (Mw 7.8), through the ionosphere-earth crust relationship. • Notices potential anomalies by presenting the time-domain TEC atlas in the frequency domain with Fourier spectral analysis. • Considering all possible TEC anomaly essentials detect the precursors of the earthquake 3 days before the event day. [ABSTRACT FROM AUTHOR]

Emerging Industry 5.0 pushes advanced automation towards resilient solutions with enhanced human role. Resilience as an ability to sustain processes in the face of disruptions and adversarial attacks requires careful modelling and simulation. Cellular automata are efficient mathematical models used to simulate the behavior of complex systems, which change their state based on a set of predefined rules. In this paper, we suggest several updates to cellular automata (particularly Conway's "Game of Life") to address resilience. These include "Life and Creation", "War and Peace", and their hybrid "War and Creation" capable of addressing the important components of resilience, such as controllable creativity and adversarial interactions. Inherited in these updates and known advantages of cellular automata, such as simplicity, emergent behavior, parallelism, and adaptability, makes it a powerful simulation tool for a wide range of Industry 5.0 systems that involve humans, smart infrastructure, their complex and adversarial interactions, safety, and resilience. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of model fidelity and parameter uncertainty on the performance of a hybrid model-based feedback-feedforward control scheme for attitude tracking of a satellite with flexible appendages. The feedforward component is an inverse model-based term produced through a computational approach known as inverse simulation (InvSim), which works by iteratively solving a discretised reference trajectory. The hybrid controller's feedback is proportional-derivative (PD) based, using body attitude and rate feedback to provide stability and robustness. Furthermore, to ensure that the flexible modes do not trigger instability, the PD control gains are tuned to give a closed-loop response that is significantly slower than the flexible modes. Additionally, excitation of the flexible modes is reduced by minimising jerk through polynomial rest-to-rest manoeuvres, following the shortest quaternion path using spherical–linear-interpolation (SLERP). The effects of the appendage flexing on attitude tracking are then compensated through the feedforward element of the hybrid controller, with performance being compared to a traditional PD tracking law. The effect of the model fidelity on the performance of the hybrid controller is investigated through the use of both rigid body and multiple-fidelity finite-element mathematical models. Additionally, the effect of uncertainties in the model parameters is investigated to determine the accuracy of the model required to obtain significant improvement in attitude tracking. It is found that in the absence of any model parameter uncertainty, the hybrid controller outperforms the PD tracking control law by at least one order of magnitude when the finite-element model is used. Increasing the number of finite elements was found to provide no significant improvement in performance, with one element being sufficient and favourable with its lower computational overhead. It was also found that to ensure good performance compared to the PD tracking controller, the uncertainty in the inertia tensor should be < 1%. Similarly, uncertainty in the first flexible modal frequency should be < 0.5 rad/s. • Inverse simulation (InvSim) used to produce model-based feedforward control. • Combined with PD feedback to improve attitude tracking. • Effects of model uncertainty and fidelity on model-based control investigated. [ABSTRACT FROM AUTHOR]

Physics-informed neural networks (PINN) architectures have been recently explored to accelerate hemodynamics simulations by leveraging mathematical models for blood flow and empirical data. In this paper, a variable separated physics-informed neural networks based on adaptive weighted loss functions (AW-vsPINN) is developed for blood flow model in arteries. In particular, sub-neural networks are proposed to separately predict the unknown scalar state variables by sharing the same input layer. The AW-vsPINN adaptively adjusts the weights of loss terms by the minmax algorithm, which will be updated synchronously along with the network parameters and can balance the contributions of different loss terms during training. The two-stage optimization is implemented to train the neural networks. Specifically, the Adam optimizer is iterated for initial steps with the learning rate generated by the inverse time decay scheduler, and then the L-BFGS optimizer continues to train until the loss converges. Numerical results illustrate that the AW-vsPINN can remarkably improve prediction accuracy and enhance the ability of generalization compared to the conventional PINN. The proposed AW-vsPINN framework has high potential in predicting the blood flow information in cardiovascular disease. [ABSTRACT FROM AUTHOR]

Exploring special multi-scroll chaotic systems is meaningful work. This paper studies an expanded multi-scroll chaotic system consisting of eight terms with one nonlinearity. It is generated by modifying the nonlinear term of the newly constructed chaotic system by a polynomial function. The unique mathematical model makes the unstable index-2 equilibria increase in four dimensions, which contributes to the number of scrolls expanding in each phase plane unidirectionally. Dynamic analysis finds that the system can yield complex nested multi-scroll attractors and has single-parameter-based synchronization control of amplitude and offset boosting behavior. Moreover, circuit implementation verifies the physical existence of the proposed system. Also, an image encryption algorithm for remote sensing images is established. Permutation and diffusion operations are performed using new pixel coordinates derived from the data of the chaotic matrix, which comes from the same position as the pixel matrix. Relevant tests suggest that the algorithm is secure and able to resist undesirable interference. • Simple multiscroll chaotic system with various signal control features is proposed. • Complex dynamics, circuit implementation of the proposed system is studied. • New chaos-based image encryption algorithm with high security is designed. [ABSTRACT FROM AUTHOR]

This research paper focuses on the development of advanced mathematical models for disease diagnosis and prediction, and the subsequent creation of automated systems based on these models. These systems leverage a range of mathematical models and incorporate cutting-edge information technology achievements to provide medical professionals with valuable decision-making support. By amalgamating mathematical rigor and technological innovation, this research endeavors to enhance the accuracy and efficiency of medical diagnoses, thereby improving patient care and healthcare outcomes. This study delves into the persistent need for contemporary information systems, where information plays a crucial role in decision-making. It aims to provide an objective approach to addressing pressing medical challenges, particularly in disease diagnosis and prediction, enhancing the effectiveness of these critical tasks. Automated medical information systems, built on advanced mathematical models, significantly empower physicians. Machine diagnostics, relying on deterministic logic, the phase interval method, and information-probabilistic logic, bolster diagnostic capabilities. Functional entropy enables individuals to handle vague information, aiding decision-making. Assessing imprecision and uncertainty computationally diminishes subjectivity, while employing fuzzy set theory enhances diagnostic modeling. Mathematical models assess diagnostic indicators, and linguistic variables quantify resemblance. The diagnostic model for primary biliary cirrhosis and active hepatitis utilizes a diagnostic table and gradient projection. This comprehensive study advances medical diagnostics through mathematical models and automated systems, addressing critical healthcare challenges. [ABSTRACT FROM AUTHOR]

This manuscript discusses the positional systems used in intelligent robots. One of the characteristic problems that arise in such systems is associated with friction, including sticking during the process. Friction greatly affects the positioning accuracy of the actuators of controlled robots, especially if a pneumatic actuator is used as a motor. The work is devoted to the study and solution of this problem. Since it is impossible to completely eliminate the effect of friction, ways to minimize this effect are being investigated using a targeted choice of system parameters. For this purpose, the method of multicriteria optimization of a detailed mathematical model is applied on the example of a pneumatic positional system, as the most sensitive to friction. The paper considers the first stage of optimization associated with visualization and preliminary analysis of the process in order to prepare it for performing a system procedure. The dynamics equations of an intelligent positional system are written out, both in full-size and dimensionless one. The most convenient mathematical model of friction is presented terms of its use in the process of optimizing the entire control system. A procedure for visualizing the optimization process in the form of a graphical interface has been developed. The first stage of the intelligent drive system optimization procedure has been carried out. The paper presents at which parameters of the control system the "stick-slip" effect has less influence on the positioning process. [ABSTRACT FROM AUTHOR]

In this paper, we solve a non-linear reaction–diffusion system with Dirichlet–Neumann mixed boundary conditions using a finite difference method (FDM) in space and the implicit midpoint method in time. This type of system appears, e.g., in the mathematical modeling of light-controlled drug delivery. One of the key results of this paper is the proof that the method has superconvergence second-order in space in a discrete H 1 -norm and optimal second-order convergence in time in a discrete L 2 -norm. Our result relies on the direct analysis of a suitable error equation, avoiding the classic construction of consistency plus stability implies convergence. One advantage of such an analysis technique is the establishment of the method's non-linear stability in an elegant way. Numerical examples support the theoretical convergence result. [ABSTRACT FROM AUTHOR]

Linear projects are a special type of repetitive projects. Major disadvantages have been shown when using the critical path method (CPM) for linear project problems. So, to overcome these shortcomings linear scheduling method (LSM) was used to analyze linear projects. There are different types of activities in linear projects. However, existing mathematical models for LSM cannot represent all types of linear project activities. Therefore, this paper presents a mathematical model that can represent all types of activities using matrices. Moreover, the mathematical model is then used to create an optimization model that minimizes the project duration and cost using non-dominated sorting genetic algorithm II (NSGA-II). The two models can help project managers in scheduling real-life linear projects and find optimum linear project schedules. This paper introduces an optimization model for linear projects that utilizes matrices, offering a different approach in the field of linear project optimization. • Different types of activities in linear schedule method (LSM) are identified • New mathematical formation for (LSM) is developed using matrices • Mathematical formation helps in representing all types activities • Mathematical formation was used to build an optimization model • Optimization model solves time cost tradeoff problem for linear project [ABSTRACT FROM AUTHOR]

Due to the rise of the nurse practitioner (NP) role in long-term care settings, it is important to understand the underlying structures and processes that influence NP and physician care models. This scoping review aims to answer the question, "What are the structures, processes, and outcomes of care models involving NPs and physicians in long-term care (LTC) homes?" A secondary aim was to describe the structural enablers and barriers across care models. Seven databases were searched. Studies that described NPs and physicians working in LTC were identified and included in the review. We stratified the findings by care model and synthesized using the Donabedian model, which evaluates health care quality based on 3 dimensions: structure, process, and outcome. We then categorized macro, meso, and micro structural enablers and barriers. Sixty papers were included in the review. The main structural influencers within 5 care models included policies on scope of practice, clarity of role description, and workload. A limited number of papers referred to the process of enabling the development of a working relationship. Thirty-five (49%) studies described resident, staff, and health system outcomes. Although structural characteristics of NP and physician care models are described in-depth, there is less detail on the processes that occur within the NP and physician care models. We highlight structural barriers and enablers within the care models, allowing for recognition of the importance of organizational influence on the NP and physician relationship. Future work should focus on the processes of the relationships in the models by identifying the drivers and initiators of collaboration between NPs and physicians and how these relationships influence outcomes. [ABSTRACT FROM AUTHOR]

Interactive teaching is very popular in the field of education, especially in college preschool education teaching. In this study, the experimental performance of the evaluation system based on scientific emotion construction is analyzed by the machine learning algorithm. The experimental results show that the classification model realized by the machine learning algorithm is feasible and effective for the construction of an interactive design teaching evaluation system of preschool education in colleges and universities. The main research content of this experiment is for the teaching evaluation text, this paper intends to use NB, KNN, LR, and SVM algorithms as the meta-learning algorithm in the framework, the classification effect of the meta-classifier is ranked as SVM > LR > KNN > NB. From the above data comparison, the SVM meta-classifier in the algorithm in this paper has achieved the best classification effect. The SVM meta-classifier based on the algorithm in this paper performs well, and the classification accuracy rate reaches 92.1%. This shows that this model is very suitable for studying the. And the classification accuracy rate reaches 92.1%. This shows that this model is very suitable for studying the construction of interactive teaching evaluation systems under emotional education. • The experimental results show that the classification model realized by machine learning algorithm. • This shows that this model is very suitable for studying the construction of interactive teaching. • The main research content of this experiment is for the teaching evaluation text. • This paper intends to use NB, KNN, LR and SVM algorithms as the meta-learning algorithm. [ABSTRACT FROM AUTHOR]

• A child and youth participatory model was developed, drawing on current best practice and evidence, to support the co-design of child and youth led service initiatives. • The model was trialled with young people who experienced marginalisation to understand their experiences of service engagement, support the development and testing of their ideas, and to support them as advocates for youth led initiatives. • The model also requires addressing issues of knowledge, capacity and culture within service organisations to increase responsiveness to child and youth engagement in service design and decision making. • The strengths and challenges of model implementation are discussed. The ReSPECT Project (Reconceptualising Services from the Perspectives of Children and Teens) was conducted in a disadvantaged urban community in Australia, with young people who experience marginalisation and who were involved with multiple service agencies across a range of service sectors. Its purpose was to work closely with young people to understand their experiences of service engagement, their perspectives on the service priorities for young people in their area, and to support them in the development, trial and implementation of a youth led service initiative. This paper describes the methodology employed with the young people, its theoretical underpinnings, and the challenges that needed to be overcome in the conduct of this research. Critical to the ReSPECT approach is relationship building and capacity development with local service providers. This aspect of our work is also briefly described in this paper. The ReSPECT approach makes a significant contribution to the participatory methodological literature. It is distinctive from existing approaches because (1) it gives equal attention to the sustained engagement and scaffolding of young people in the development of ideas, and to the capacity building of service providers addressing organisational culture and constraints; (2) it follows the process of service change from the conceptualisation of youth-led ideas, through to development, partnership, implementation and evaluation; and (3) it is designed for engagement with marginalised young people with diverse service experiences, whose voices are so often absent from participatory projects. [ABSTRACT FROM AUTHOR]

Risks are uncertain events that can affect criteria such as project cost, quality, and completion time and ultimately lead to project failure. That is why the project risk management process, which is one of the most fundamental parts of project management, must be done properly. In this paper, a new multi-objective fuzzy model is proposed to respond appropriately to the primary and secondary project risks. The contributions, such as risk interdependency, considering the project with multi-mode activities, resource considerations, as well as attention to interval-valued fuzzy uncertainties are regarded simultaneously for the first time. The purpose of the proposed multi-objective mathematical model is to minimize cost, quality reduction, and project completion time. Then, a new two-stage uncertain solution approach is introduced in this paper. In this solution approach, using an equivalent method in the first step and then using an extended multi-choice goal programming method in the second step, for both lower and upper limits of the membership functions for interval-valued fuzzy numbers, the computational processes are performed. To show the application and effectiveness of the proposed model, a case study adapted from the literature is given. Finally, sensitivity analysis is conducted to analyze the behavior of the developed mixed-integer programming model. The analysis of obtained results indicates that the utilization of the proposed model leads to better and more appropriate solutions. • Presenting a new multi-objective programming model for project risk responses. • Proposing multi-mode activity and resource considerations in project risk modeling. • Introducing a new interval-valued fuzzy solution approach to handle uncertainty. • Focusing on primary and secondary risks along with project risk interdependency. • Implementing the proposed model in a case study for electricity industry projects. [ABSTRACT FROM AUTHOR]

This paper deals with the degree of approximation by an operator based on the partial sum of the Fourier series of a function of class L p , p ≥ 1. We use modulus of continuity of the function satisfying weaker conditions than those used by Deǧer and Bayindir [On the degree of approximation by the Woronoi-Nörlund and Riesz type means in the GHM, Azerb. J. Math., 8 (2018), 122-141]. The results of our paper also improve those of Singh and Sonker [Degree of approximation of function in H p w in generalized Hölder metric by matrix means, Mathematical modelling and scientific computation, 1-10, Commun. Comput. Inf. Sci., 283, Springer, Heidelberg, 2012]. [ABSTRACT FROM AUTHOR]

• Childcare policy responses towards Covid-19 differed in European welfare states. • Policy responses cause informalization of childcare to different degrees. • Informalization of childcare is mainly connected with social risks for women. • Cultural and institutional differences help to understand varying policy responses. The closure of extra-familial childcare facilities by European governments in 2020 was an important part of interventions against the spread of the COVID-19 pandemic. One consequence was that childcare was provided by parents at home, mainly by women. As a result, women mainly experienced financial and employment risks related to this "informalization" of childcare. The childcare policies of European welfare states differ in the extent to which they include measures to reduce the social risks related to informalization. Against this backdrop, this paper asks: How should one understand cross-national differences in childcare policies during the pandemic? We are also particularly interested in the effects of childcare policies on the social risks connected with the informalization of childcare and what these mean for the gendered division of paid work and care. Differences in childcare policies during the pandemic are commonly explained in terms of the path dependence of such policies. Using the theoretical approach of "care arrangement," this article introduces a broader theoretical framework that considers the role of cultural and institutional factors for understanding the cross-national differences in childcare policies during the pandemic. We introduce the findings of a comparative empirical study of childcare policies in three European welfare states—Denmark, Germany and England—that represent different types of care arrangements. This paper uses policy and media documents, quantitative data on childcare and women's employment, cultural ideas and secondary analysis of empirical studies. We find that governments did not per se respond to the pandemic based on institutional path dependence regarding childcare policies, while the integration of culture into the theoretical framework allows for a more comprehensive understanding. [ABSTRACT FROM AUTHOR]

This paper describes an accurate model of the Electrical Power Subsystem (EPS) of the Thermal Analysis Support and Environment Characterization Laboratory (TASEC-Lab), a university experiment developed for using in high-altitude balloon missions to measure and analyze the convection heat transfer. A Li-ion battery and two high efficient DC–DC converters have been characterized through laboratory tests and fitting to the experimental results. The developed mathematical models described in this paper are used to carry out accurate EPS simulations and are validated by comparison with the experimental data. • Design and modeling of the electrical power subsystem of a stratospheric balloon experiment. • New Li-lion battery discharging model that describes the three main parts: initial decay, linear, and exponential decay. • Formulation of a new DC/DC converter efficiency model. • Simulation and model validation of the electrical power subsystem. [ABSTRACT FROM AUTHOR]