Configuration Model Research Articles

Measurement Invariance and Psychometric Evaluation of the Tendency to Avoid Physical Activity and Sport Scale (TAPAS) Among Mainland Chinese University Students.

Preventative factors in young people's physical inactivity require further understanding, including related psychosocial factors (eg, body image and weight stigma). The Tendency to Avoid Physical Activity and Sport Scale (TAPAS) is a recently developed instrument to address this issue and the present study examined its psychometric properties among Chinese university students particularly in relation to patterns across sex, physical activity (PA) level, and weight status. Using a convenience sample of 3142 students (mean age = 19.8 years; 56% female) in mainland China, data were collected using an online survey between August and October 2022. Psychometric instruments including the Weight Bias Internalization Scale, 21-item Depression, Anxiety and Stress Scale, and International Physical Activity Questionnaire Short Form were administered along with the TAPAS to assess convergent and discriminant validity. Multi-group confirmatory factor analysis (CFA) assessed the measurement invariance across specific groups. The unidimensional structure of the scale was confirmed through CFA (CFI=0.995; RMSEA=0.046). All configural, metric and scalar models of invariance indicated that the scale was invariant across sex, PA level, and weight status. Acceptable convergent and discriminant validity for the scale were found. The TAPAS is a suitable instrument to assess body image and weight stigma concerns for avoiding physical activity and sport among Chinese university students.

Modal Theory and Approach for Accurate Characterization of Common-Mode Chokes

This work presents a method for characterization of common mode chokes, aimed at constructing accurate virtual prototypes of electromagnetic interference filters. This method is based on a general modal analysis that identifies the natural modes of a symmetric four-ports network in a power line. Natural modes excited in the setups defined in the CISPR-17 norm to characterize filtering devices are determined. From this analysis, two simple measurement setups particularly suitable for characterizing common mode chokes are identified, and a decision-making algorithm is presented to determine the parameters of a configurable circuit model of the common mode choke. This circuit model is especially devised so that each one of its different circuit blocks can be associated with a single modal response of the common mode choke. This, along with the use of physical criteria to define the basic schematic of each circuit block, ensures the simplicity, accuracy, and generality of the final circuit model. Characterization of many commercial common mode chokes with different core materials and winding configurations has been carried out to demonstrate that this circuit model is able to accurately account for the actual response of different types of common mode chokes in a wide frequency range.

Electronic and optical characteristics of Silicane/GeAs van der Waals heterostructures: Effects of external electric field and biaxial strain: A first-principles study

The van der Waals heterostructure offers unusual physical properties to design novel structures for efficient optoelectronic applications. To enhance the low mobility of monolayer SiH and broaden the light absorption coefficient and range of monolayer SiH, a lattice-matched SiH/GeAs vdWh has been constructed. At the same time, the basic electronic and optical properties were investigated by first-principles calculations. The SiH/GeAs vdWh with six different structural configurations were compared, and the most stable configuration model H2 has a type-II band alignment with an indirect bandgap semiconductor value of 1.54 eV. It is associated with a strong charge transfer. Moreover, SiH/GeAs vdWh possesses anisotropic transport properties with high electron mobility along the y-direction. Interestingly, both external electric field and biaxial strain can adjust band offsets and bandgaps values. After applying vertical electric fields, The SiH/GeAs vdWh has a mutual transformation from type-I (symmetric) to type-II(staggered) to type-III(broken) band alignment, and metal-semiconductor phase transitions occurred at −0.35 and 0.15 V/Å. Besides, it's found that band alignment transition from type-II to type-I emerged under the in-plane biaxial strain of 2% and transformed indirect into direct bandgap. More importantly, tensile biaxial strain can enhance the visible-light absorption while sustaining type-II band alignment, which is favorable for photocatalysis of visible light. Our results indicate that the SiH/GeAs vdWh's moderate bandgap, excellent transport properties and optical performance may have potential applications in the field of nanoelectronic and optoelectronic devices.

Distributed Photovoltaic Optimization Configuration Based on Marine Predators Algorithm in Low Voltage Transformer Area

This article proposes a method for determining the scale and location of Distributed Photovoltaic (DPV)under the operational constraints of low-voltage transformer areas. Firstly, a low-voltage transformer areas operation model and a DPV output model were established. Determine the access nodes and rated capacity of the DPV using the indicators of minimizing voltage fluctuations and minimizing line loss rate in the optimized configuration model; Then, the maximum capacity of DPV that can be installed in the transformer area is determined with the goal of maximizing the photovoltaic penetration rate in DPV accessible nodes; Use Marine Predators Algorithm(MPA) to solve nonlinear problems in the model. Finally, simulation analysis was conducted using an actual low-voltage transformer area as an example to demonstrate the effectiveness of the proposed model and method, ensuring the safe and stable operation of the low-voltage transformer area when connected to a high proportion of photovoltaic energy.

Optimal Dispatching of Energy Hub for New Energy Consumption

In recent years, with the continuous increase of wind power installed capacity, due to insufficient flexibility of the system, there has been a serious problem of wind power abandonment. In response to this phenomenon, this article improves the flexibility of the regional energy system by adding various flexible devices. Based on the concept of an energy hub, an energy hub model including wind power, CHP, heat pumps, heat storage, and other equipment is established. On this basis, considering system operating costs, wind abandonment penalty costs, and electricity purchase costs, a multi-objective regional energy system flexibility configuration model based on energy hubs was established to explore the feasibility of this model in improving wind power consumption. Finally, specific examples were combined in two different cases for analysis. The results indicate that the model has a very good effect on improving system flexibility and improving wind power consumption rate.

Refined modeling and co-optimization of electric-hydrogen-thermal-gas integrated energy system with hybrid energy storage

To further explore the multi-energy complementary potential on multi-time scales under variable operating conditions, a refined modeling and collaborative configuration method for Electric-Hydrogen-Thermal-Gas Integrated Energy Systems (EHTG-IES) with hybrid energy storage system (HESS) is proposed in this paper. To commence with, an advanced operation model for the EHTG energy conversion equipment is formulated by incorporating their nonlinear operating characteristics under variable operating conditions. Next, the distinct features of HESS with different energy medium are accurately depicted with various effective linear-reduction and relaxation strategies. Then, the coupling design day method and the intra-day and inter-day state superposition strategy are combined to efficiently model the time horizon. Lastly, a co-optimal configuration model of the EHTG-IES is devised, with the aim of minimizing total annual cost. The case study validates that the refined modeling of coupled components leads to a 3.18% reduction in cost and 5.05% reduction in carbon emissions significantly. This paper also assessments the synergy and substitution benefits of multiple low-carbon technologies and finds that diurnal and seasonal hydrogen storage have a large part of overlapping roles, and hydrogen-based system contributes a deeper utilization of seasonal thermal storage. The sensitivity analysis indicates that the current carbon tax policy has a negligible impact on the carbon emissions, equivalent to about 1% of the gas price, but appropriately increasing attention on low carbon allows for an emission decrease of 28.62% at a cost increase of 4.38%.

What Kind of Market Is Conducive to the Development of High-Tech Industry? Configuration Analysis Based on Market Field Theory

The high-tech industry is important in supporting China’s construction of a high-quality modern economic system. The high-tech industry markets are spaces for the supply and transaction of high-tech products. The existing research lacks in-depth discussions on the constituent factors and shaping mechanisms of the high-tech industry market. This paper constructs the market field configuration model of the high-tech industry and studies the impact of the market field configuration of the high-tech industry in 30 provinces of China on the innovation performance of the high-tech industry using the fuzzy-set qualitative comparative analysis method. The findings are as follows: (1) The three structural variables of network, institution, and cognition cannot individually constitute the necessary conditions for explaining the high or low innovation performance of high-tech industries; (2) Three high-tech industry market field configurations can lead to high innovation performance, and the condition combination among different configurations has a substitution effect; (3) Four high-tech industry market field configurations will lead to low innovation performance, in which the lack of multiple conditions in the network, system, and cognition is the main reason for the market failure. The research conclusions of this study highlight the cognitive role of market construction and the configuration characteristics of effective high-tech industry market fields, which provides practical enlightenment for China to improve the innovation performance of high-tech industries.

Configurable soft computing-based generative model: The search for catalytic peptides

Configurable soft computing-based generative model: The search for catalytic peptides

Performance Improving of Wind Power Generation Systems Through Parameter Optimization and Dynamic Analysis of the Speed-Regulating Differential Transmission

Abstract Hybrid drive wind power generation systems (WPGSs) equipped with speed-regulating differential mechanisms (SRDMs) have emerged as a promising solution for integrating large-scale wind energy into the power grid without the need for partially or fully rated converters. This article presents a comprehensive study on the dynamic analysis and parameter optimization of the SRDM-based transmission, with the aim of providing a sound foundation for the design and performance improvement of hybrid drive WPGSs. This study first formulates the kinematics, power flow, and mechanical efficiency of the SRDM and then proposes an effective parameter configuration model for optimizing the speed ratios of the key link units. The objective function is set as the minimum peak power required for speed regulation by the SRDM. Furthermore, to deal with the unique mechanical features such as dual power inputs, continuously variable transmission, and time-varying steering mechanism, an appropriate nonlinear dynamic modeling method of the SRDM transmission is developed. The torsion–translation vibration equations are derived and solved using the Runge–Kutta numerical integral method, considering randomly changing wind speed inputs and time-varying internal/external excitations. Results reveal that the sun gear experiences severe vibrations with the maximal and average vibration displacements of 0.563 mm and 0.112 mm, respectively, in the circumferential direction, while the planet gear exhibits complex frequency responses. Finally, specialized case studies are demonstrated to verify the proposed approaches, showing the satisfactory on-grid operating performance of the proposed SRDM-based WPGSs.

Configurable dual rotor wind turbine model based on BEM method: Co-rotating and counter-rotating comparison

This article proposes a Blade Element Momentum (BEM) theory based model applied to dual rotors wind turbines. Dual rotor wind turbines studied consist of two rotors mounted coaxially to recover the flow from the first rotor. These rotors can turn in the same (co-rotating) or in opposite directions (counter-rotating). The aim of the model is to be fast, accurate and configurable in order to be used as design tool or for optimization purposes. The model considers axial and tangential induction influences of the first rotor on the second one and the influence of the distance between them. The model has been validated by comparison with experimental data from the literature and shows that the counter-rotating configuration has a power coefficient 4.6% higher than the co-rotating for the same turbine geometrical setting. Besides, in our case study, the counter-rotating power coefficient can be in average on different wind speeds 10.6% higher compare to the single rotor.

Optimal Capacity Configuration of Wind–Solar Hydrogen Storage Microgrid Based on IDW-PSO

Because the new energy is intermittent and uncertain, it has an influence on the system’s output power stability. A hydrogen energy storage system is added to the system to create a wind, light, and hydrogen integrated energy system, which increases the utilization rate of renewable energy while encouraging the consumption of renewable energy and lowering the rate of abandoning wind and light. Considering the system’s comprehensive operation cost economy, power fluctuation, and power shortage as the goal, considering the relationship between power generation and load, assigning charging and discharging commands to storage batteries and hydrogen energy storage, and constructing a model for optimal capacity allocation of wind–hydrogen microgrid system. The optimal configuration model of the wind, solar, and hydrogen microgrid system capacity is constructed. A particle swarm optimization with dynamic adjustment of inertial weight (IDW-PSO) is proposed to solve the optimal allocation scheme of the model in order to achieve the optimal allocation of energy storage capacity in a wind–hydrogen storage microgrid. Finally, a microgrid system in Beijing is taken as an example for simulation and solution, and the results demonstrate that the proposed approach has the characteristics to optimize the economy and improve the capacity of renewable energy consumption, realize the inhibition of the fluctuations of power, reduce system power shortage, and accelerate the convergence speed.

Dense multigraphon-valued stochastic processes and edge-changing dynamics in the configuration model

Dense multigraphon-valued stochastic processes and edge-changing dynamics in the configuration model

Necessary and sufficient conditions for exact closures of epidemic equations on configuration model networks

We prove that it is possible to obtain the exact closure of SIR pairwise epidemic equations on a configuration model network if and only if the degree distribution follows a Poisson, binomial, or negative binomial distribution. The proof relies on establishing the equivalence, for these specific degree distributions, between the closed pairwise model and a dynamical survival analysis (DSA) model that was previously shown to be exact. Specifically, we demonstrate that the DSA model is equivalent to the well-known edge-based Volz model. Using this result, we also provide reductions of the closed pairwise and Volz models to a single equation that involves only susceptibles. This equation has a useful statistical interpretation in terms of times to infection. We provide some numerical examples to illustrate our results.

A conditionally constrained compound sub‐gradient method for distributed energy coordination

AbstractA conditionally constrained compound (CCC) sub‐gradient method typically involves solutions by multi‐agents, which have important applications in distributed energy resources (DER). The proposed DER system structure model uses operating state switching to analyze the characteristics of the model transformation. The work proposes that energy storage (ES) transformation is the main factor that influences the transformation in the DER model. For solving this optimization problem, this study uses a compound sub‐gradient method that is distributed among the agents. Compared with the conventional analysis methods, a system configuration and equivalent model of distributed power is obtained using the sub‐gradient method, and the power distribution characteristics of the DER in the off‐grid state are further given. Using a time‐based representation, this method can be applied to complex distributed new energy access applications and uses an iterative compound step ladder algorithm with a specific step size for switching. The compound distributed gradient algorithm further determines the selected range of algorithm parameters. Finally, the results of the convergence rate explicitly characterize the effectiveness of the method.

Learning spatially variant degradation for unsupervised blind photoacoustic tomography image restoration

Photoacoustic tomography (PAT) images contain inherent distortions due to the imaging system and heterogeneous tissue properties. Improving image quality requires the removal of these system distortions. While model-based approaches and data-driven techniques have been proposed for PAT image restoration, achieving accurate and robust image recovery remains challenging. Recently, deep-learning-based image deconvolution approaches have shown promise for image recovery. However, PAT imaging presents unique challenges, including spatially varying resolution and the absence of ground truth data. Consequently, there is a pressing need for a novel learning strategy specifically tailored for PAT imaging. Herein, we propose a configurable network model named Deep hybrid Image-PSF Prior (DIPP) that builds upon the physical image degradation model of PAT. DIPP is an unsupervised and deeply learned network model that aims to extract the ideal PAT image from complex system degradation. Our DIPP framework captures the degraded information solely from the acquired PAT image, without relying on ground truth or labeled data for network training. Additionally, we can incorporate the experimentally measured Point Spread Functions (PSFs) of the specific PAT system as a reference to further enhance performance. To evaluate the algorithm’s effectiveness in addressing multiple degradations in PAT, we conduct extensive experiments using simulation images, publicly available datasets, phantom images, and in vivo small animal imaging data. Comparative analyses with classical analytical methods and state-of-the-art deep learning models demonstrate that our DIPP approach achieves significantly improved restoration results in terms of image details and contrast.

Service Innovation Model in Boarding School Programs for New Students at Islamic Higher Education

This research seeks a service innovation model at Ma'had Al-Jami'ah, a unit at an Islamic religious university in Indonesia, both during the Covid-19 pandemic and its sustainability after the pandemic subsided. This research is based on field studies using a mix-method with a sequential exploratory design. Observations, documentation, interviews, and questionnaires with a sample of 172 students are used to gather the data. As for analysis techniques: preparing data to be analyzed, exploring data, conducting post-exploration data analysis, selecting data that represents the results of the analysis, displaying the interpretation of the results, and validating the data and results. The results show that service innovation is carried out using a configuration model through the application of CLER (configuration, linkage, environment, resources) based on the use of technology to deal with existing situations and the application of five innovation characteristics. The implementation of service innovation is directed at information and registration, learning, and evaluation services. Based on the existing sample, the percentage of students participating in the Islamic boarding school program in the BTA-PPI competency test reached 78%.

MaxEnt modeling for predicting the potential distribution of Lebrunia bushaie Staner (Clusiaceae) under different climate change scenarios in Democratic Republic of Congo

Lebrunia bushaie Staner is an endangered medicinal plant that is endemic in the Democratic Republic of Congo (DRC). In this study, its current and future suitable distribution habitats were assessed using two Global Circulation Models (GCMs) HadGEM3-GC3.1-LL” (Third Hadley Centre Global Environment Model in the Global Coupled Configuration 3.1) and MIROC6 (Model for Interdisciplinary Research on Climate) under twoShared Socioeconomic Pathways (ssp) scenarios, ssp126 and ssp245 at the horizon 2050. Potential habitat predictions for L. bushaie were performed using MaxEnt software. The area under the curve (AUC˃ 0.90) revealed a high level of prediction for the current and future scenarios. Seasonal Temperature (Bio4), and isothermality (Bio3) were the variables with the greatest influence on the distribution of L. bushaie. The current distribution that is highly suitable for this plant corresponds to the habitat in which this species was inventoried. Furthermore, the projected future suitable area of L. bushaie based HadGEM3-GC3.1-LL and MIROC6 is expected to increase under the ssp126 and ssp245 scenarios by 2050.

Configurational model for the process of alignment in technology implementations

Configurational model for the process of alignment in technology implementations

A New Product Configuration Model for Low Product Cost and Carbon-Neutral Expenditure

In the background of global carbon-neutral requirements, enterprises need to control carbon emissions in the process of product lifecycles in order to gain market competitive advantages. Previous product configuration studies, mostly focused on minimizing carbon dioxide emissions, have ignored the issue of carbon-neutral costs. This study quantifies the product costs borne by enterprises and the carbon-neutral cost borne by the government, respectively. A carbon-neutral cost model for suppliers, enterprises, customers, and recycling plants in the whole life cycle of products was constructed. The whole life cycle carbon emissions and the unit carbon removal costs were taken into account in the carbon-neutral cost model. By minimizing product and carbon-neutral costs, a bi-objective integer programming model was constructed. The NSGA-II algorithm was introduced to solve the Pareto front of the model. The feasibility and effectiveness of this method were then illustrated through a case study and results comparison. It showed that, compared with the scheme of carbon emissions reduction, the optimization scheme with carbon-neutral costs as the object had a significant change. Integrating carbon-neutral costs into product development activities was effective in reducing the enterprise’s product cost and the government’s financial expenditure on carbon removal simultaneously. The proposed model could provide a win–win product configuration scheme for the government and enterprises.

Simulation of Native Oxide‐Passivated CsSn0.5Ge0.5I3 Highly Stable Lead‐Free Inorganic Perovskite Solar Cell

The search for a lead‐free, nontoxic, highly stable perovskite phase could end at the native oxide‐passivated composition of CsSn0.5Ge0.5I3. Mainly its remarkable stability is due to a thin native oxide layer (Sn‐doped GeO2) formation over CsSn0.5Ge0.5I3, which suppresses the Sn2+ oxidation to Sn+4. Herein, the performance of this mixed Sn–Ge perovskite and the role of native oxide is analyzed. The experimental device with 7% efficiency is numerically replicated, utilizing reasonable device configuration, material parameters, and defect model. The low efficiency of CsSn0.5Ge0.5I3 is due to high bulk defects. The simulation result shows that Sn oxidation suppressing the native oxide layer imparts stability but does not significantly impact device efficiency. The optimization provides passivated design for absorbers with high bulk defects. Low thickness at high defect density is preferable, and higher thickness at lower defect density is optimal for device design. The final optimized device achieves an efficiency of 21%. The results summarized here can provide a guideline for high‐efficiency, lead‐free, nontoxic stable perovskite solar cells.