Hasil untuk "Competition"

Guojia Li, Cheng Zhou

The collaboration between economic and ecological departments in land-use planning is crucial for advancing sustainable development. However, existing research has largely focused on macro-level policies and technical instruments, paying insufficient attention to the micro-level logics of behavior and strategic interactions between these two departments. This research employs a rigorous mixed-methods approach to bridge empirical depth with analytical rigor. The qualitative phase, encompassing 41 semi-structured interviews and analysis of 327 internal documents, examines the departments’ real-world motivations, strategic behaviors, and the cost–benefit structures underlying their decision-making. Based on these empirical findings, a tailored evolutionary game theory model is constructed to formally simulate the dynamic pathways and stable equilibria of collaboration between the Economic and Ecological Departments. Our analysis reveals that the evolutionary game system converges toward a dichotomy of stable states: a non-cooperative equilibrium characterized by development-oriented land-use planning with adaptive regulation, and a cooperative equilibrium underpinned by green-coordinated planning supported by stringent regulatory enforcement. A cooperative equilibrium is more readily achieved when both departments demonstrate a willingness to simultaneously increase their cost investment parameters in sustainable land-use planning. Conditions contrary to this mutual commitment lead to a non-cooperative equilibrium. Building on these findings, the study synthesizes this interplay into a novel “Institutional-Situational-Behavioral” (ISB) framework. This framework provides a cohesive theoretical lens for diagnosing and fostering interdepartmental collaboration in sustainable land governance. The research thus offers a theoretical foundation for analyzing the evolutionary dynamics of interdepartmental collaboration and delivers mechanism-informed policy guidance for enhancing sustainable land-use planning.

Emil Kragh Toft, Carolin Schmidt, Daniele Gammelli et al.

Autonomous Mobility-on-Demand (AMoD) systems promise to revolutionize urban transportation by providing affordable on-demand services to meet growing travel demand. However, realistic AMoD markets will be competitive, with multiple operators competing for passengers through strategic pricing and fleet deployment. While reinforcement learning has shown promise in optimizing single-operator AMoD control, existing work fails to capture competitive market dynamics. We investigate the impact of competition on policy learning by introducing a multi-operator reinforcement learning framework where two operators simultaneously learn pricing and fleet rebalancing policies. By integrating discrete choice theory, we enable passenger allocation and demand competition to emerge endogenously from utility-maximizing decisions. Experiments using real-world data from multiple cities demonstrate that competition fundamentally alters learned behaviors, leading to lower prices and distinct fleet positioning patterns compared to monopolistic settings. Notably, we demonstrate that learning-based approaches are robust to the additional stochasticity of competition, with competitive agents successfully converging to effective policies while accounting for partially unobserved competitor strategies.

Tetyana Ivanova, Halyna Kryshtal, Volodymyr Metelytsia et al.

This article analyzes the implementation of investment-oriented innovations in the field of medical insurance to establish an effective and sustainable healthcare financing model amidst digital economic transformation. The authors provide theoretical justification for the role of innovations and investments in the development of the medical insurance sector, along with a deep analysis of the current state of medical services and the main barriers hindering innovation in this area. Special attention is given to assessing the impact of digitalization on the accessibility and quality of medical services, as well as the potential of using advanced technologies such as telemedicine and online platforms for insurance companies. It is considered that digital technologies, including telemedicine and online services, have the potential to significantly improve access to medical services and reduce costs. However, the implementation of these innovations faces several challenges, including issues of internet access, the lack of proper legal frameworks for regulating digital technologies in medical insurance, and the need to enhance financial literacy among the population. The authors summarize and propose a list of barriers (technical, regulatory, financial, cultural, psychological barriers, barriers related to human resources, and competition-related barriers) in attracting investments to the sector. Practical recommendations are offered for stakeholders, including insurance companies, government bodies, and users of medical services, to facilitate more effective innovation implementation and ensure sustainable financing of medical services. The strategic approaches to sustainable healthcare financing proposed in the article aim to ensure equal access to medical services for all population segments, improve the quality of insurance services, and optimize costs through digital tools.

Colin S. Doherty, Oliver R. Barley, Lauren V. Fortington

Abstract Background Mixed martial arts (MMA) and Muay Thai (MT) are widely practiced combat sports, yet research on the full spectrum of competition-related health problems (HPs) remains limited, particularly for MT. Existing studies in both sports primarily focus on retrospective analyses of severe injuries, often estimating time lost from training or competition. This study describes the incidence of all competition HPs reported seven days after MMA and MT contests, and determines the number of days impacted by tracking athletes’ self-identified worst HPs until resolution. Methods Data on competition HPs were collected using an online questionnaire completed seven days after each MMA and MT event (n = 26). The questionnaire included the Oslo Sports Trauma Research Centre Questionnaire on Health Problems 2 (OSTRC-H2). The Combat Sports Commission of Western Australia provided competition exposure time data. Incidence rates of HPs were calculated per 100 min of exposure (HPIRME). Competitors reporting HPs were followed up weekly using the OSTRC-H2 questionnaire until their worst HPs resolved. Results Of the 175 competitors (238 responses) who completed the questionnaire (76% male; age: 27 ± 6 years), 81 competitors (92 responses) reported a total of 411 HPs (315 injuries, 96 illnesses). Among the 92 worst HPs, 26 were substantial, and 24 prevented training. The HPIRME was 20.1 (95% CI: 16.5–24.4) for MMA and 25 (95% CI: 22.3–28) for MT. Follow-up captured 78 (85%) of the worst HPs, with 175 responses collected over 14–70 days post-competition. The median days impacted by the worst HPs were 20 for MMA and 16 for MT. Conclusions Among respondents, 39% reported at least one HP. On average, the worst HPs resolved in less than three weeks. These findings provide valuable insights into the frequency and impact of competition HPs,offering important information for promoters, athletes, coaches, and regulatory bodies to better understand and address the health challenges faced by combat sports athletes.

Rabah Amir, Igor V. Evstigneev, Mikhail V. Zhitlukhin

The paper compares two types of industrial organization in the Cournot duopoly: (a) the classical one, where the market players maximize profits and the outcome of the game is a Cournot-Nash equilibrium; (b) a contest in which players strive to win a fixed prize/bonus employing unbeatable strategies. Passing from (a) to (b) leads to a perfect competition with zero profits of the players (Schaffer's paradox). Transition from (b) to (a) results in a substantial decline in the production output, which also seems paradoxical, as it is commonly accepted that competition increases efficiency. We examine these phenomena in two versions of the Cournot model: with a homogeneous good and with differentiated goods.

Kiki Juli Anggoro, Nurmala Nurmala

Technological advances have introduced English instructors to various ways of delivering successful online classes. Using an Interactive Response System (IRS) as a supporting tool is one of them. This qualitative study investigates the perceptions of foreign English language teachers in Thai universities regarding the use of IRS in online classes. The study involved 10 non-native English university teachers, 7 females and 3 males, aged 27 to 35, with 3 to 6 years of teaching experience in Thailand. They are affiliated with three different Thai universities. Data were gathered through multiple online interviews and observations via Zoom or Google Meet, tailored to each participant’s convenience. The data analysis was conducted using a robust content analysis approach. The findings of this study showed that educators integrated IRS tools to boost engagement, benefiting both students and instructors. Additionally, peer influence encouraged IRS adoption and enhanced teaching methods. IRS tools served various roles, ranging from assessment to promoting motivation and enhancing comprehension. The advantages of IRS tools included increased interactivity, competition, and engagement. They aided in monitoring student attentiveness and comprehension while fostering independent learning. Challenges such as unequal internet access, device limitations, technology literacy, fees, workload, and language barriers existed, along with concerns about potential cheating during IRS activities.

Samyuktha Ramesh, Samyuktha Ramesh, Margareta Go et al.

B cells surveil the body for foreign matter using their surface-expressed B cell antigen receptor (BCR), a tetrameric complex comprising a membrane-tethered antibody (mIg) that binds antigens and a signaling dimer (CD79AB) that conveys this interaction to the B cell. Recent cryogenic electron microscopy (cryo-EM) structures of IgM and IgG isotype BCRs provide the first complete views of their architecture, revealing that the largest interaction surfaces between the mIg and CD79AB are in their transmembrane domains (TMDs). These structures support decades of biochemical work interrogating the requirements for assembly of a functional BCR and provide the basis for explaining the effects of mutations. Here we report a focused saturating mutagenesis to comprehensively characterize the nature of the interactions in the mIg TMD that are required for BCR surface expression. We examined the effects of 600 single-amino-acid changes simultaneously in a pooled competition assay and quantified their effects by next-generation sequencing. Our deep mutational scanning results reflect a feature-rich TMD sequence, with some positions completely intolerant to mutation and others requiring specific biochemical properties such as charge, polarity or hydrophobicity, emphasizing the high value of saturating mutagenesis over, for example, alanine scanning. The data agree closely with published mutagenesis and the cryo-EM structures, while also highlighting several positions and surfaces that have not previously been characterized or have effects that are difficult to rationalize purely based on structure. This unbiased and complete mutagenesis dataset serves as a reference and framework for informed hypothesis testing, design of therapeutics to regulate BCR surface expression and to annotate patient mutations.

Jakub Pokrywka, Piotr Wierzchoń, Kornel Weryszko et al.

Multimodal models, which combine visual and textual information, have recently gained significant recognition. This paper addresses the multimodal challenge of Text-Image retrieval and introduces a novel task that extends the modalities to include temporal data. The Temporal Image Caption Retrieval Competition (TICRC) presented in this paper is based on the Chronicling America and Challenging America projects, which offer access to an extensive collection of digitized historic American newspapers spanning 274 years. In addition to the competition results, we provide an analysis of the delivered dataset and the process of its creation.

Alexander Rom

This paper investigates the impact of banking competition on interest rates for household consumption loans in the Euro Area from 2014 to 2020. Utilizing a panel data regression approach, we analyze how various factors, including local banking competition, influence the interest rates set by banks across 13 Euro-area countries. Our key independent variable, local banking competition, is measured by the number of commercial bank branches per 100,000 adults. Control variables include the ECB interest rate, euro exchange rate, real GDP growth rate, inflation rate, unemployment rate, bank business volumes, and country risk. We address potential endogeneity and heterogeneity biases and employ both Fixed Effects and Hausman-Taylor models to ensure robust results. Our findings indicate that higher local banking competition is associated with a slight increase in interest rates for household loans. Additionally, factors such as ECB interest rate, country risk, and euro appreciation significantly affect interest rates. The results offer insights into how competitive dynamics in the banking sector influence borrowing costs for households, providing valuable implications for policymakers and financial institutions in the Euro Area.

Jiawei Zhang

The advent of ChatGPT has sparked over a year of regulatory frenzy. However, few existing studies have rigorously questioned the assumption that, if left unregulated, AI chatbot's output would inflict tangible, severe real harm on human affairs. Most researchers have overlooked the critical possibility that the information market itself can effectively mitigate these risks and, as a result, they tend to use regulatory tools to address the issue directly. This Article develops a yardstick for reevaluating both AI-related content risks and corresponding regulatory proposals by focusing on inter-informational competition among various outlets. The decades-long history of regulating information and communications technologies indicates that regulators tend to err too much on the side of caution and to put forward excessive regulatory measures when encountering the uncertainties brought about by new technologies. In fact, a trove of empirical evidence has demonstrated that market competition among information outlets can effectively mitigate most risks and that overreliance on regulation is not only unnecessary but detrimental, as well. This Article argues that sufficient competition among chatbots and other information outlets in the information marketplace can sufficiently mitigate and even resolve most content risks posed by generative AI technologies. This renders certain loudly advocated regulatory strategies, like mandatory prohibitions, licensure, curation of datasets, and notice-and-response regimes, truly unnecessary and even toxic to desirable competition and innovation throughout the AI industry. Ultimately, the ideas that I advance in this Article should pour some much-needed cold water on the regulatory frenzy over generative AI and steer the issue back to a rational track.

Mireille Berton

This article investigates the impact of streaming on serial writing, using the case of puzzle series and, more specifically, the German science fiction series Dark (Baran bo Odar and Jantje Friese, Netflix, 2017-2020) broadcasted on Netflix. How do we understand the critical success of series that challenge interpretation by multiplying the "cognitive dissonance" effects (Kiss & Willemsen 2018)? Is it a response to the economic imperative of renewal of forms and formats in a context of increased competition? Is it a way of translating, by intensifying them, the contradictions and dilemmas of the current world? Or is it the result of a transformation of the audiovisual landscape and digital technologies that facilitate the spatio-temporal manipulations? Without excluding other interpretations, we will defend the hypothesis that puzzle series are the sign of the streaming giants' aim to personalize their offer, on the one hand by disavowing their debt to "traditional" television, and on the other by imitating the interactivity of video games. More broadly, puzzle series question the economic and ideological stakes of this extreme form of "Complex TV" (Mittell 2015), which encourages fan investment through various means suitable for data mining. The aim is therefore to highlight the economic impact of the digital broadcasting model, which relies both on the power of the audience's collective intelligence and on that of algorithmic computation.

Yen-Wen Wang, Holly Elmore, Anne Pringle

Uniparental inheritance of mitochondria enables organisms to avoid the costs of intracellular competition among potentially selfish organelles. By preventing recombination, uniparental inheritance may also render a mitochondrial lineage effectively asexual and expose mitochondria to the deleterious effects of Muller’s ratchet. Even among animals and plants, the evolutionary dynamics of mitochondria remain obscure, and less is known about mitochondrial inheritance among fungi. To understand mitochondrial inheritance and test for mitochondrial recombination in one species of filamentous fungus, we took a population genomics approach. We assembled and analyzed 88 mitochondrial genomes from natural populations of the invasive death cap <i>Amanita phalloides</i>, sampling from both California (an invaded range) and Europe (its native range). The mitochondrial genomes clustered into two distinct groups made up of 57 and 31 mushrooms, but both mitochondrial types are geographically widespread. Multiple lines of evidence, including negative correlations between linkage disequilibrium and distances between sites and coalescent analysis, suggest low rates of recombination among the mitochondria (ρ = 3.54 × 10⁻⁴). Recombination requires genetically distinct mitochondria to inhabit a cell, and recombination among <i>A. phalloides</i> mitochondria provides evidence for heteroplasmy as a feature of the death cap life cycle. However, no mushroom houses more than one mitochondrial genome, suggesting that heteroplasmy is rare or transient. Uniparental inheritance emerges as the primary mode of mitochondrial inheritance, even as recombination appears as a strategy to alleviate Muller’s ratchet.

Akaki Mamageishvili, Jan Christoph Schlegel

We study shared sequencing for different chains from an economic angle. We introduce a minimal non-trivial model that captures cross-domain arbitrageurs' behavior and compare the performance of shared sequencing to that of separate sequencing. While shared sequencing dominates separate sequencing trivially in the sense that it makes it more likely that cross-chain arbitrage opportunities are realized, the investment and revenue comparison is more subtle: In the simple latency competition induced by First Come First Serve ordering, shared sequencing creates more wasteful latency competition compared to separate sequencing. For bidding-based sequencing, the most surprising insight is that the revenue of shared sequencing is not always higher than that of separate sequencing and depends on the transaction ordering rule applied and the arbitrage value potentially realized.

Peng Li, Huiqing Ye, Yong Hu et al.

The competition between magnetic order and Kondo effect is essential for the rich physics of heavy fermion systems. Nevertheless, how such competition is manifested in the quasiparticle bands in a real periodic lattice remains elusive in spectroscopic experiments. Here we report a high-resolution photoemission study of the antiferromagnetic Kondo lattice system CeCoGe3 with a high TN1 of 21K. Our measurements reveal a weakly dispersive 4f band at the Fermi level near the Z point, arisingfrom moderate Kondo effect. The intensity of this heavy 4f band exhibits a logarithmic increase with lowering temperature and begins to deviate from this Kondo-like behavior below 25 K, just above TN1, and eventually ceases to grow below 12 K. Our work provides direct spectroscopic evidence for the competition between magnetic order and the Kondo effect in a Kondo lattice system with local-moment antiferromagnetism, indicating a distinct scenario for the microscopic coexistence and competition of these phenomena, which might be related to the real-space modulation.

Maximilian Jerdee, M. E. J. Newman

Patterns of wins and losses in pairwise contests, such as occur in sports and games, consumer research and paired comparison studies, and human and animal social hierarchies, are commonly analyzed using probabilistic models that allow one to quantify the strength of competitors or predict the outcome of future contests. Here we generalize this approach to incorporate two additional features: an element of randomness or luck that leads to upset wins, and a "depth of competition" variable that measures the complexity of a game or hierarchy. Fitting the resulting model to a large collection of data sets we estimate depth and luck in a range of games, sports, and social situations. In general, we find that social competition tends to be "deep," meaning it has a pronounced hierarchy with many distinct levels, but also that there is often a nonzero chance of an upset victory, meaning that dominance challenges can be won even by significant underdogs. Competition in sports and games, by contrast, tends to be shallow and in most cases there is little evidence of upset wins, beyond those already implied by the shallowness of the hierarchy.

Miyu Seii, Tomoki Harano, Masao Doi et al.

Some types of hydro-gels have almost the same equilibrium swelling volume in water and in ethylene glycol (EG), a highly viscous liquid completely miscible with water. Experiments showed that when a gel fully swollen with EG is immersed into a large amount of water, it temporarily swells up and then relaxes to the equilibrium volume in water. The temporary swelling is explained by the friction force exerted on the gel network from the outward EG flux In this paper, we experimentally show that the temporary swelling is suppressed by adding linear PEG (polyethylene glycol) in the outer water. Although the suppression seems to be explained by the osmotic pressure (i.e., by the same mechanism as the conventional osmotic squeezing), our theoretical analysis reveals that the effect of PEG is much stronger than that expected from the equilibrium osmotic pressure, implying that the PEG chains are condensed on the gel surface.

Zoia S. Podoba, Victor A. Gorshkov, Anastasiya A. Ozerova

By empirically examining the commodity structure of Japan's exports in 2000–2020, the authors have identified product groups with increased, diminished, newly emerged, and lost revealed comparative advantages (RCA). In 2020, Japan had RCA in 24 product groups with relatively high levels of product complexity and thus managed to maintain its highly diversified trade portfolio. However, increasing global competition poses potential risks to Japan's exports. Eight product groups with diminished and two product groups with lost RCA are signs of Japan's unsuccessful adaptation to the structural changes on the world markets. The newly emerged RCA, predominantly in the chemicals and allied industries, still mostly have lower index values in comparison to major trade partners, however, their contribution to Japan's exports is likely to expand. To enhance its comparative advantages, Japan should foster innovation which may positively affect national competitiveness but this depends on how the country will adapt to domestic and global challenges.

Stanley Bak, Changliu Liu, Taylor Johnson

This report summarizes the second International Verification of Neural Networks Competition (VNN-COMP 2021), held as a part of the 4th Workshop on Formal Methods for ML-Enabled Autonomous Systems that was collocated with the 33rd International Conference on Computer-Aided Verification (CAV). Twelve teams participated in this competition. The goal of the competition is to provide an objective comparison of the state-of-the-art methods in neural network verification, in terms of scalability and speed. Along this line, we used standard formats (ONNX for neural networks and VNNLIB for specifications), standard hardware (all tools are run by the organizers on AWS), and tool parameters provided by the tool authors. This report summarizes the rules, benchmarks, participating tools, results, and lessons learned from this competition.

Julian D. Cortes, Diego Garcia, Edgar Rodriguez et al.

The study aims to generate a map of the knowledge based on the research on topics related to governance and security, risks, competition and cooperation for the FDDI (Fudan Development Institute) proceedings publishing project: 'Reflections on Governance: Security and Risks, Competition and Cooperation.' That mapping exercise would enable a broader audience to delve into the current state, and interdisciplinary pathways of the research published worldwide for addressing complex problems of governance. Following this introduction, the second section presents the bibliometric methods used and the results' interpretation. The third section presents the results, followed by the fourth and fifth sections of discussion and conclusion, respectively.

Ruben Tolosana, Ruben Vera-Rodriguez, Carlos Gonzalez-Garcia et al.

This article presents SVC-onGoing, an on-going competition for on-line signature verification where researchers can easily benchmark their systems against the state of the art in an open common platform using large-scale public databases, such as DeepSignDB and SVC2021_EvalDB, and standard experimental protocols. SVC-onGoing is based on the ICDAR 2021 Competition on On-Line Signature Verification (SVC 2021), which has been extended to allow participants anytime. The goal of SVC-onGoing is to evaluate the limits of on-line signature verification systems on popular scenarios (office/mobile) and writing inputs (stylus/finger) through large-scale public databases. Three different tasks are considered in the competition, simulating realistic scenarios as both random and skilled forgeries are simultaneously considered on each task. The results obtained in SVC-onGoing prove the high potential of deep learning methods in comparison with traditional methods. In particular, the best signature verification system has obtained Equal Error Rate (EER) values of 3.33% (Task 1), 7.41% (Task 2), and 6.04% (Task 3). Future studies in the field should be oriented to improve the performance of signature verification systems on the challenging mobile scenarios of SVC-onGoing in which several mobile devices and the finger are used during the signature acquisition.