Competitive Model Research Articles

Economic and environmental evaluation of different collection models for spent power batteries

The efficient collection of spent batteries is important for the recycling of power batteries and the sustainable advancement of electric vehicles (EVs). This study introduces and evaluates 14 power battery collection models, encompassing single-channel, dual-channel, and triple-channel scenarios, which encapsulate the dynamics of competition, cooperation, and co-opetition among key stakeholders. Employing Stackelberg game theory and simulation analysis, this study assesses the economic and environmental benefits of these models, with particular attention to the impact of consumer environmental awareness and competition intensity. Findings indicate that the collaborative collection model involving battery manufacturers, EV companies, and third-party recyclers (Model MVTP) delivers superior economic outcomes, with benefits ranging from 20.3 to 20.31 billion RMB. Meanwhile, the competitive three-party collection model (Model M-V-TP) stands out for its environmental benefits, achieving collection rates between 14.95 % and 25.65 %. Intriguingly, while competition intensity does not influence the outcomes of single-channel models, it diminishes both economic and environmental benefits in dual- and triple-channel scenarios. Moreover, enhanced consumer environmental awareness consistently elevates the economic benefits of all models, though its effect on environmental benefits varies—enhancing collection rates in single- and dual-channel models but detrimentally impacting the triple-channel model.

Shaping individual competitiveness: The role of discipline, parental expectations, and participation in extracurricular activities

PurposeThis research seeks to extend previous research into student discipline and competitiveness, at the macro or national level, to the micro or individual level. The role of factors with the potential to impact individual competitiveness, namely the expectations of the mother and the father, the importance of school discipline played in primary and secondary schools, and past participation in sport and music were examined. Design/methodology/approachData from a sample of current university students and recent graduates representing Western (the United States) and Asian regions (South Korea and China) were analysed using multiple regressions to establish the explanatory power of independent variables in the competitiveness model, including testing for moderation effects of country of birth. ResultsThe study found that personal discipline is significantly associated with individual competitiveness. The importance placed on discipline in primary schools was found to predict individual competitiveness as were parents’ expectations, yet with nuances in terms of maternal and paternal expectations. Surprisingly, neither participation in music nor discipline at secondary school was found to significantly associate with individual competitiveness. At the same time, the study did find moderating effects of country of birth and the number of years students played sport in predicting competitiveness. Originality/valueGuided by the Ecological Systems Theory and the notion of the Pygmalion effect, we develop a framework of factors that shape an individual's competitiveness. The results make several theoretical contributions by establishing new drivers of individual competitiveness, and as such illuminating the importance of discipline during schooling and how parental expectations drive performance. Implications for employers, educational institutions, and parents are outlined and directions for further research are offered.

BCLAF1 is a novel regulator of fetal and adult hematopoietic stem cell function

Abstract Hematopoietic stem cells (HSCs) adapt to blood production and maintenance needs of a developing organism. Mouse fetal liver HSCs undergo rapid perinatal proliferation and possess high repopulation capacity. Adult HSCs establish residence in the bone marrow and lose repopulation capacity with age. This shift is characterized by epigenetic and transcriptional cues. The objective of our study is to determine the developmental context-dependent role for BCLAF1 in HSC function. Conditional loss of BCLAF1 results in a reduction of fetal HSCs that persists into adulthood, while induced deletion of BCLAF1 in adult mice does not affect HSC numbers. These results suggest the context of fetal liver HSC development may exacerbate effects of BCLAF1 loss. In competitive transplant models, we have found that both fetal and adult BCLAF1-deficient HSCs have significantly reduced repopulation capacity. CITEseq of fetal Vav-Cre:Bclaf1fl/fl hematopoietic cells reveals a reduction in long-term repopulating HSCs and elevated AP-1 gene expression. Consistent with these results, in vitro HSC differentiation culture assays demonstrate that BCLAF1-deficient HSCs have increased myeloid differentiation. Current BCLAF1 CUT&RUN sequencing experiments on fetal and adult HSCs will define specific changes in DNA-binding patterns of BCLAF1 over development. Collectively, these results suggest that BCLAF1 acts in fetal and adult HSCs to transcriptionally restrain AP-1 activity and promote HSC function.

Ammonium ion removal from aqueous solutions in the presence of organic compounds, using biochar from banana leaves. Competitive isotherm models

BackgroundIndustrial, e.g. food industrial and domestic wastewaters contain huge amount of compounds causing eutrophication, and should be removed with high cost during wastewater treatment. However, these compounds could be utilized as fertilizers too. Biochar can remove a wide range of pollutants from water, such as ammonium, which can be found in relatively high concentration in dairy wastewaters. However, adsorption performance may be affected by the presence of other wastewater pollutants. Thus, this study aims to determine the efficiency of biochar as an adsorbent of ammonium in aqueous solutions in the presence of some selected organic compounds of typical dairy wastewaters such as bovine serum albumin (BSA), lactose, and acetic acid. Methods: The biochar was produced from banana leaves at 300 °C, modified with NaOH, and characterized by Scanning Electron Microscope – Energy Dispersive X-Ray Spectroscopy (SEM-EDX), Fourier-transform infrared spectra (FTIR) analysis, and specific surface area measurements. Batch experiments were carried out to investigate the ammonium adsorption capacity and the ion competitive adsorption mechanism. Significant Findings: Results show that the surface structure of the biochar derived from banana leaves is different from other biochars previously studied; although the specific surface area is not very considerable and despite having nitrogen within the elemental composition, the biochar studied is capable of adsorbing 2.60 mg NH4+/m2, the highest ammonium removal in 2 h occurs at pH 9 and 500 mg biochar dose. Langmuir model in the monolayer phase analysis fits better for all scenarios and the maximum NH4+ adsorption capacity was 0.97 mg/g without organic compounds. In the multilayer adsorption phase, the isotherm model that best fits the data obtained is the Harkins-Jura model without organic compounds. The presence of organic compounds in the aqueous solution significantly impacts the adsorption of ammonium by biochar since it improves the adsorption capacity (1.132 mg/g BSA, 0.975 mg/g lactose, and 1.874 mg/g acetic acid). The Aranovich-Donohue isotherm model fitted the data obtained during ion competitive adsorption experiments well.

A Simple Model of Corporate Tax Incidence

We analyze the incidence of a linear corporate tax using a simple and portable competitive general equilibrium model in which capital owners choose to invest either in domestic production or a foreign investment opportunity and workers make extensive margin labor supply decisions. Our analysis explores the effect of corporate taxation on wages, employment, domestic profits, and domestic investment. Analytical results and numerical simulations generate insights in line with recent empirical evidence on corporate tax incidence: the burden of the corporate tax is shared between workers and firms, with larger responses among more capital-intensive firms.

Research on the competitiveness of the Arctic transportation route under the belt and road initiative

AbstractWith the continuous improvement of the navigation environment of the Arctic routes, the commercialization potential of the Arctic routes is enhanced, which brings new challenges to the Suez Canal route and the China–Europe railway Express. In addition, geopolitical factors such as the Russia–Ukraine conflict and the Red Sea crisis have also brought some impact on the Eurasian transport pattern. In this context, the future trade and transportation between China and Europe will take on a new pattern. In order to study the transport competition pattern between China and Europe under the opening of the Arctic routes, this article takes into account the time‐value cost of goods and geopolitical factors, constructs a logit competition model, and quantitatively investigates the competitiveness of the Arctic route and the traditional routes of the “Belt and Road Initiative” using major international transportation hub cities in China. The results show that the types of cargo and the level of freight are important factors affecting the competitiveness of Arctic routes. Under the influence of geopolitics, the competitive advantage of the Arctic routes are highlighted.

Generalized multiscale finite element method for language competition modeling II: Online approach

In this paper, we consider language competition in a heterogeneous medium. The mathematical model considers bilingualism, population growth, and social pressure to use specific languages (diglossia). The transition from one language group to another is determined by probabilities that depend on status, group size, and spatial location. The model considers not only diffusive spread but also convective spread, which models seasonal migrations of speaker populations. We develop multiscale approaches for coarse grid modeling while maintaining reasonable accuracy. We present offline and online approaches based on the Generalized Multiscale Finite Element Method. We consider a model problem in a heterogeneous environment to test these approaches. The results show that both approaches can significantly reduce the discrete problem’s size. However, the online approach achieves better accuracy.

“Research on the construction of internet based aerobics competitive ability assessment model”

A vast field that focuses on restoring motor abilities through exercise is known as sports rehabilitation training, which is also sometimes referred to as recovery athletic exercise. A background in sporting recovery can assist competitors in getting back into peak physical condition, recovering from injuries, preventing additional damage, and better coping with the demands of regular practice. The importance of sports rehabilitation teaching for physical activity is analyzed and discussed at length throughout this research. The definition of sports therapy is presented first, followed by an examination of how it might be used to fitness. Make use of this information as a reference to discover how to include physical therapy in the workout plan you use for sports conditioning. Many tried-and-true algorithms for monitoring patients' vitals over time have emerged as a result of widespread use and advancements in IHM technology, which has led to an increase in the number of such algorithms. The purpose of this research is to investigate the ways in which intelligent health monitoring systems can be applied to the process of developing rehab methods for athletes. It not only provides the structure for a smart wellness terminal, but it also offers the usual ways for monitoring a moving object. Methods such as this include the optical flow strategy, the frame contrast technique, and the background difference method, to name just a few examples. The process of rehabilitation that an athlete went through in X city is presented as an example to show the processes that are included in an ideal study. According to the findings of the study, 92.6 percent of the athletes with injuries were able to make a full recovery with the support of rehabilitative physical exercise. The researchers were able to determine this by keeping close track on the athletes' vital signs in real time using sophisticated health monitoring equipment.

The Impact of Role Models on Women’s Self-Selection into Competitive Environments

In this paper, we show that competitive female role models reduce women’s perceived stereotype threat and increase their willingness to compete. Competitive male role models have the opposite effect: they reduce women’s willingness to compete, and the gender gap in tournament entry increases. Results are strongest for the best performing women who would benefit most from competing. Role models have no impact on low performing women, and on men.

The complexity analysis of decision-making for horizontal fresh supply chains under a trade-off between fresh-keeping and carbon emission reduction

This study primarily focuses on the impact of carbon emissions generated during the fresh product fresh-keeping process on the traditional fresh supply chain (FSC1) and the low-carbon fresh supply chain with emission reduction behavior (FSC2). Its objective is to investigate how these supply chains dynamically adjust the production quantity, fresh-keeping level, and emission reduction level of fresh products when constrained by the dual-carbon policy. The decision competition model between the two supply chains was explored under two scenarios: the horizontal Nash (HN) game and the long-term Stackelberg (LS) game, wherein FSC1 assumes the role of the leader. The findings indicate that as the carbon tax and carbon trading price increase, the fresh supply chain tends to decrease fresh-keeping intensity while increasing investment in emission reduction. Carbon emissions generated during the fresh product fresh-keeping process have a smaller impact on FSC2's profit than on FSC1, and FSC2 exhibits stronger adaptability under the dual-carbon policy. Irrespective of the game structure, if the adjustment speed of FSC1's production decision exceeds the stable range, its own profit will decrease while the other party's profit will increase. However, if the adjustment speed of FSC2's production decision surpasses the stable range, it will lead to a decrease in profits for both sides. Interestingly, in the LS game, when the adjustment speed of FSC1's production decision exceeds the stable range, FSC1 demonstrates a leader advantage and experiences a rapid increase in profit as the adjustment speed of FSC2's production decision increases, this phenomenon suggests that in the LS game, the leader prevails amidst market chaos.

Challenges of Including Wet Grasslands with Variable Groundwater Tables in Large-Area Crop Production Simulations

Large-scale assessments of agricultural productivity necessitate integrated simulations of cropland and grassland ecosystems within their spatiotemporal context. However, simultaneous simulations face limitations due to assumptions of uniform species distribution. Grasslands, particularly those with shallow groundwater tables, are highly sensitive to water availability, undergoing rapid species composition changes. We hypothesised that predicting above-ground biomass (AGB) remains challenging due to these dynamic responses. Ten years of data from four lysimeters at a German wet grassland site, with varying water table treatments, was utilised to test this hypothesis. Correlation analysis revealed a strong positive indirect effect of the water regime on AGB, with a one-year time lag (r = 0.97). The MONICA model initially exhibited fair agreement (d = 0.69) in simulating Leaf-Area-Index (LAI) but performed poorly in replicating AGB (d = 0.3). After removing the species composition change effect from the LAI and AGB datasets, the simulation notably improved, with the overall relative root mean square error (rRMSE) of AGB decreasing from 1.55 to 0.90 between the first and second simulations. This demonstrates MONICA’s ability to predict grass growth patterns amidst changing water supply levels for constant species composition. However, it needs a competition model to capture biomass growth changes with varying water supply.

Disclosure services and welfare gains in matching markets for indivisible assets

We present a competitive matching model in which indivisible assets are reallocated among many traders. The model has three features: (i) traders are heterogeneous in their prospects as buyers, sellers, and also in their stand-alone values with endowed assets, (ii) buyers do not know true values of assets sold, (iii) sellers can disclose values of their assets by paying fees. Despite its complexity, the model admits closed-form solutions. Two main results emerge. First, if full Disclosure is facilitated by a monopolist, it captures a large fraction of the welfare gains. Second, adding the option of minimum disclosure, when combined with a cap regulation on price-dependent fees for full disclosure, significantly weakens the monopolist’s power.

MEKANISME SISTEM PROPORSIONAL TERBUKA PADA PEMILIHAN DEWAN PERWAKILAN RAKYAT DI INDONESIA

The aim of this research is to analyze the mechanism of the open proportional system in the General Election of the People's Representative Council in Indonesia by referring to Law Number 7 of 2017 concerning General Elections which regulates the open list Proportional Election System, where this system can give rise to a polemic in the struggle for seats. in a very competitive parliament that has the effect of giving birth to an unhealthy model of competition between candidates that only aims to gain as many votes as possible from voters by relying solely on money and popularity. This research method uses normative juridical in answering the problems in this paper. Meanwhile, the results of the research obtained are that an open Proportional System makes it possible for anyone to nominate themselves as members of the legislature. In this system, a person who gets the most votes can take a seat as a member of the People's Representative Council even though the person concerned is at the bottom of the ballot paper.

Optimal contraception control for a nonlinear competitive vermin population model with spatial diffusion and size structure in a polluted environment

Optimal contraception control for a nonlinear competitive vermin population model with spatial diffusion and size structure in a polluted environment

Research on Complex Network Models and Characteristics of Building Material Enterprises Based on Competitive Relationships

Based on complex network theory, this paper establishes a Boolean competitive relationship network model and a weighted competitive relationship network model for building material enterprises based on big data and performs empirical analyses with construction prefabricated component (PC) enterprises in the Beijing–Tianjin–Hebei region as research samples. Results show the competitive relationship network of PC enterprises in the Beijing–Tianjin–Hebei region is characterised by the development of a small-world network, and its cumulative degree and out-degree (in-degree) intensity distributions are single-scale networks with fast-decaying tails. The network has strong network clustering and assortativity, and it can truly reflect the competitive status and dynamics of the enterprises.

Competition in cargo and passenger between high-speed rail and airlines—considering the vertical structure of transportation

High-speed rail (HSR) services are experiencing rapid global expansion, posing competition not only in the traditional passenger sector but also challenging air cargo with their attributes of speed and punctuality. In this study, we establish a straightforward model for air-HSR competition in both passenger and cargo markets, taking into account the vertical structure of transportation supply chain. We explore various market equilibria based on the combination of three factors: 1) HSR's provision of cargo services, 2) the integration or separation of HSR's ownership and operation, and 3) uniform or differentiated airport administrative fees for passenger and cargo airlines. The analytical results of our model indicate that the entry of HSR into the cargo market consistently enhances social welfare and may even improve the profit of cargo airlines. However, if airports adopt uniform pricing or there is vertical separation in HSR sector, this could potentially weaken the positive impact on welfare enhancement. These findings have important implications for transportation policy, highlighting how strategic management of infrastructure can significantly influence the effectiveness and societal benefits of HSR's expansion into cargo services.

The pro-competitive effects of trade agreements

How does trade policy affect competition? Using the universe of product exports by firms from eleven low and middle income countries, we document that tariff reductions under trade agreements have strong pro-competitive effects — they encourage entry and reduce the (tariff exclusive) price-cost markups of exporters. This finding, that markups fall with tariff cuts, contradicts a core prediction of standard oligopolistic competition models of trade. We extend a workhorse international pricing model of oligopolistic competition to include multiple countries and a rich preference structure. Our preference structure allows for fierce competition among firms from the same country and less intense competition among firms from different countries. We show a firm’s optimal markup after a tariff cut can rise or fall depending on the parameters of the preference structure and tariff-induced reallocation of market share among firms and across countries.

Misapplied management makes matters worse: Spatially explicit control leverages biotic interactions to slow invasion.

A wide range of approaches has been used to manage the spread of invasive species, yet invaders continue to be a challenge to control. In some cases, management actions have no effect or may even inadvertently benefit the targeted invader. Here, we use the mid-20th century management of the Red Imported Fire Ant, Solenopsis invicta, in the US as a motivating case study to explore the conditions under which such wasted management effort may occur. Introduced in approximately 1940, the fire ant spread widely through the southeast USand became a problematic pest. Historically, fire ants were managed with broad-spectrum pesticides; unfortunately, these efforts were largely unsuccessful. One hypothesis suggests that, by also killing native ants, mass pesticide application reduced competitive burdens thereby enabling fire ants to invade more quickly than they would in the absence of management. We use a mechanistic competition model to demonstrate the landscape-level effects of such management. We explicitly model the extent and location of pesticide applications, showing that the same pesticide application can have a positive, neutral, or negative effect on the progress of an invasion, depending on where it is applied on the landscape with respect to the invasion front. When designing management, the target species is often considered alone; however, this work suggests that leveraging existing biotic interactions, specifically competition with native species, can increase the efficacy of management. Our model not only highlights the potential unintended consequences of ignoring biotic interactions, but also provides a framework for developing spatially explicit management strategies that take advantage of these biotic interactions to work smarter, not harder.

Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

Blockchain-based cooperative game bilateral matching architecture for shared storage

The development of IPFS (InterPlanetary File System) and blockchain-based distributed storage projects has brought new possibilities to the field of storage. This paper proposes a blockchain-based cooperative game bilateral matching architecture as a novel approach for shared storage networks. In traditional competitive (non-cooperative) game models, the allocation of storage resources is centered around pricing, leading to a scenario where node providers often engage in price competition to obtain greater rewards, resulting in an imbalance in resource allocation for both buyers and sellers. In contrast, a distributed storage model based on cooperative game theory can better facilitate cooperation and resource sharing among node providers. This paper designs a storage resource allocation algorithm based on the stable marriage matching algorithm, demonstrating the stability of this algorithm as a matching solution. The paper also analyzes the differences between cooperative and non-cooperative game models in the market, and explores an equilibrium pricing mechanism guided by supply and demand. Furthermore, the paper introduces a trading mechanism for storage resources, including publication standards and matching schemes, ensuring efficient and trustworthy interaction between storage suppliers and demanders in a decentralized network centered around storage resources, thus enabling the circulation of the value of storage resources. A prototype of a blockchain-based shared storage trading system is implemented in this paper, utilizing bilateral matching for tradings. System evaluation and experimental testing are conducted, with results showing that the average utility value of the matching trading mechanism proposed in this paper outperforms the Double Auction-based matching model under any Poisson distribution (λ = 0.1, 0.2, 0.3, …, 0.9) conditions set in the experiments. Additionally, compared to the traditional approach of directly storing complete data content on the chain, the design proposed in this paper effectively reduces on-chain storage consumption by approximately 27.06%.