Theoretic Framework Research Articles

Preventing Price-Mediated Contagion Due to Fire Sales Externalities: Strategic Foundations of Macroprudential Regulation

In economics and finance, most game theoretic frameworks are “classical” in that actors do not face any constraints. In this paper, we consider the case of banks that are financial institutions subject to capital ratio constraints. After an adverse shock, when the capital ratio of a given bank is lower than its minimum regulatory requirement, a bank will typically try to restore its capital ratio back above the minimum required by selling assets such as stocks and bonds. When the value of each asset decreases with the quantity sold, something called price impact in Finance, the capital ratio constraint of a given bank depends upon the asset sale of other banks. The deleveraging problem (asset sale) thus becomes a generalized game. We both consider the case of a generalized game under individual constraints (microprudential regulation) but also under shared constraint, interpreted as a macroprudential regulation from a financial point of view.

To Bequeath, or Not to Bequeath? On Labour Income Risk and Top Wealth Concentration

Abstract Recent theoretical advances suggest that capital income risk, rather than earnings uncertainty, is the key determinant of fat-tailed behavior of stationary wealth distributions. I provide novel insights into this issue by studying an incomplete market model with general time and state separable preferences, where parental altruism and unobservable idiosyncratic shocks engender non-linear bequest rules. I analytically pin down conditions on the preference structure and other model’s primitives under which optimal bequest behavior hinders intergenerational wealth transmission for any degree of capital income risk, causing the dynamics of wealth to converge to a unique (stationary) distribution with thin tails. These results imply, in particular, that (i) the stochastic properties of labour income risk (as shaped by, e.g. fiscal policies) may play a role in defining the structure of the upper tail of the limiting distribution of wealth, and that (ii) matching empirically documented fat tails with choice theoretic frameworks of wealth dynamics requires joint restrictions on preferences and calibrated earnings processes to be met.

Fictionality in “Fog on the Barrow-downs”: Myth and Reference

Exploring fictionality as the link between imagined and referential reality, the paper draws on the theoretic al framework of cognitive narratology in examining the mechanisms on which the creation of myth relies in the narratives introduced at the beginning of J. R. R. Tolkien’s Lord of the Rings, in Chapters 7 and 8 of The Fellowship of the Ring. In the introductory section, the authors review relevant literature pertaining to the manner in which immersion occurs, how analogous links are formed between fiction and reality, and whether the pragmatic dichotomy of the fictional and factual holds in all fictional circumstances. Essentially, the reviewed literature offers an insight into how text reception depends on context and the imported or integrated rhetorical frame of the fictional text. Next, the paper uses these two chapters as illustration, with reference to the appendices relevant to their interpretation, from the perspective of the formulated framework. The concluding remarks summarise the importance of immersion, as well as other automatic processes activated during reading, in internalising truth programs contained within fiction and myths that render their fictionality almost irrelevant.

Impact of port integration on port service quality in the context of shipping alliance

This paper explores the impact of port integration on the port service quality under a chain structure where the interactions among ports, shippers and shipping lines are considered. A game theoretic framework is proposed to investigate the decisions of ports (the determination of quality-of-service level), shippers (the choice of departure ports) and shipping lines (whether forming an alliance and the corresponding operating arrangement) jointly. Based on the game theoretic framework, the mathematical models are established and the corresponding solution algorithm is designed. The methodology is applied in two representative port clusters with port integration in China. The case-study results demonstrate two important findings. Firstly, both positive and negative impact of port integration on the level of quality-of-service for shippers and for shipping lines is likely to appear. The effect on the port service quality would vary with the difference in the integration scenarios. Secondly, the port integration would stimulate shipping lines to offer more frequent portcalls, indicating that the hinterland shippers would enjoy more opportunities to be served by shipping lines. However, when excessive port integration takes place, the shipping lines would tend to change the strategy of forming an alliance to the strategy of competing.

Multiple distinct evolutionary mechanisms govern the dynamics of selfish mitochondrial genomes in Caenorhabditis elegans

Cells possess multiple mitochondrial DNA (mtDNA) copies, which undergo semi-autonomous replication and stochastic inheritance. This enables mutant mtDNA variants to arise and selfishly compete with cooperative (wildtype) mtDNA. Selfish mitochondrial genomes are subject to selection at different levels: they compete against wildtype mtDNA directly within hosts and indirectly through organism-level selection. However, determining the relative contributions of selection at different levels has proven challenging. We overcome this challenge by combining mathematical modeling with experiments designed to isolate the levels of selection. Applying this approach to many selfish mitochondrial genotypes in Caenorhabditis elegans reveals an unexpected diversity of evolutionary mechanisms. Some mutant genomes persist at high frequency for many generations, despite a host fitness cost, by aggressively outcompeting cooperative genomes within hosts. Conversely, some mutant genomes persist by evading inter-organismal selection. Strikingly, the mutant genomes vary dramatically in their susceptibility to genetic drift. Although different mechanisms can cause high frequency of selfish mtDNA, we show how they give rise to characteristically different distributions of mutant frequency among individuals. Given that heteroplasmic frequency represents a key determinant of phenotypic severity, this work outlines an evolutionary theoretic framework for predicting the distribution of phenotypic consequences among individuals carrying a selfish mitochondrial genome.

Research on the Impact of Digital Finance Development on a Green Oriented Transition of Manufacturing Industry

With the increasing severity of the global climate change, low-carbon transformation in manufacturing industry has become the key to sustainable development. Globally, the rapid rise of digital finance has had a profound impact on the economic structure and development transformation of manufacturing industry. The study focuses on how digital finance to influence on Low-carbon transition in manufacturing industry, deeply exploring the mechanism at work of digital finance in both financing and industrial upgrading. By theoretic analysis, it establishes the theoretic framework for digital finance promoting the transformation, illustrating the role and path of digital finance for a green oriented and low-carbon transition of manufacturing. Suggestions such as strengthening digital financial supervision, improving the regulatory system, developing advanced green technologies, and integrating production and education are proposed, which provides policymakers with a new perspective to speed up the low-carbon transition of the manufacturing industry. This is of great significance for promoting economic green development and improving international competitiveness of manufacturing industry.

“It’s easier to take a pill than fix a problem:” qualitative analysis of barriers and facilitators to antimicrobial stewardship program implementation in carceral settings

BackgroundWidespread antibiotic prescribing contributes to globally emerging antimicrobial resistance (AMR). Despite stewardship recommendations by the Infectious Diseases Society of America, there is a lack of literature identifying barriers and facilitators to antimicrobial stewardship programs (ASPs) in United States (U.S.) carceral settings.MethodsGuided by the Theoretic Domains Framework, we performed in-depth interviews with 68 key stakeholders in Massachusetts carceral settings to contextualize barriers and facilitators to ASP implementation. We recruited 32 people incarcerated in Massachusetts jails and 36 carceral clinicians, correctional officers/administrators in Massachusetts and other U.S. states, and Massachusetts community clinicians for interviews.ResultsFrom the completed semi-structured in-depth interviews, we identified seven salient themes—four barriers and three facilitators—both specific to and across stakeholder groups. Barriers included the following: (1) jail being viewed as a “dirty place” that increases the risk of infections; (2) variable awareness and knowledge of AMR and ASPs; (3) clinicians’ opposition to change and oversight of their antibiotic prescribing; (4) competing priorities taking precedence over ASP implementation. Facilitators included (5) interest in changing the narrative about carceral healthcare through ASP implementation; (6) opportunities for education about ASP and AMR; and (7) the development of systems, policies, and regulations to improve antibiotic prescribing.ConclusionsTo our knowledge, this is the first qualitative study to leverage broad criminal-legal stakeholder groups to inform the next steps in developing and implementing ASPs in carceral settings in the U.S.

Quantum query complexity of Boolean functions under indefinite causal order

The standard model of quantum circuits assumes operations are applied in a fixed sequential “causal” order. In recent years, the possibility of relaxing this constraint to obtain causally indefinite computations has received significant attention. The quantum switch, for example, uses a quantum system to coherently control the order of operations. Several computational and information-theoretical advantages have been demonstrated, raising questions as to whether advantages can be obtained in a more unified complexity theoretic framework. In this paper, we approach this problem by studying the query complexity of Boolean functions under general higher-order quantum computations. To this end, we generalize the framework of query complexity from quantum circuits to quantum supermaps to compare different models on an equal footing. We show that the recently introduced class of quantum circuits with quantum control of causal order cannot lead to any reduction in query complexity, and that any potential advantage arising from causally indefinite supermaps can be bounded by the polynomial method, as is the case with quantum circuits. Nevertheless, we find some functions for which the minimum error with which they can be computed using two queries is strictly lower when exploiting causally indefinite supermaps. Published by the American Physical Society 2024

Nonparametric statistical analysis of system resilience migration and application for electric distribution structures

This paper proposes a set of nonparametric statistical tools for analyzing the system resilience of civil structures and infrastructure and its migration upon changes in critical system parameters. The work is founded on the classic theoretic framework that system resilience is defined in multiple dimensions for a constructed system. Consequentially, system resilience can lose its parametric form as a random variable, falling into the realm of nonparametric statistics. With this nonparametric shift, traditional distribution-based statistics are ineffective in characterizing the migration of system resilience due to the variation of system parameters. Three statistical tools are proposed under the nonparametric statistical resilience analysis (npSRA) framework, including nonparametric copula-based sensitivity analysis, two-sample resilience test analysis, and a novel tool for resilience attenuation analysis. To demonstrate the use of this framework, we focus on electric distribution systems, commonly found in many urban, suburban, and rural areas and vulnerable to tropical storms. A novel procedure for considering resourcefulness parameters in the socioeconomic space is proposed. Numerical results reveal the complex statistical relations between the distributions of system resilience, physical aging, and socioeconomic parameters for the power distribution system. The proposed resilience distance computing and resilience attenuation analysis further suggests two proper nonparametric distance metrics, the Earth Moving Distance (EMD) metric and the Cramévon Mises (CVM) metric, for characterizing the migration of system resilience for electric distribution systems.

An Exact Theory of Causal Emergence for Linear Stochastic Iteration Systems.

After coarse-graining a complex system, the dynamics of its macro-state may exhibit more pronounced causal effects than those of its micro-state. This phenomenon, known as causal emergence, is quantified by the indicator of effective information. However, two challenges confront this theory: the absence of well-developed frameworks in continuous stochastic dynamical systems and the reliance on coarse-graining methodologies. In this study, we introduce an exact theoretic framework for causal emergence within linear stochastic iteration systems featuring continuous state spaces and Gaussian noise. Building upon this foundation, we derive an analytical expression for effective information across general dynamics and identify optimal linear coarse-graining strategies that maximize the degree of causal emergence when the dimension averaged uncertainty eliminated by coarse-graining has an upper bound. Our investigation reveals that the maximal causal emergence and the optimal coarse-graining methods are primarily determined by the principal eigenvalues and eigenvectors of the dynamic system's parameter matrix, with the latter not being unique. To validate our propositions, we apply our analytical models to three simplified physical systems, comparing the outcomes with numerical simulations, and consistently achieve congruent results.

Dynamics of Ethnic Boundaries: Rethinking Insider-Outsider Dichotomy in Northeast India

Northeast India has a history of being strategically populated with non-tribal people since colonialism, leading to resentment among the indigenous population and the emergence of sub-nationalism rooted in local culture and history. This sub-nationalism asserts the insider-outsider dichotomy, (native tribal v/s non-native settler), resulting in ethnic conflicts and demands for secession. Amidst the region’s rich cultural diversity and the presence of numerous smaller ethnic groups, the contemporary literature from Northeast India, including poetry, fiction, nonfiction and drama, serves as a critical lens to unravel the dynamics of ethnic boundaries. Integrating Fredrik Barth’s notion of “ethnic boundaries,” which posits that migration and mobility, with their accompanying social processes of exclusion and incorporation, maintain distinct ethnic categories, this article attempts to analyze how contemporary literature from the region unveils the myth of the insider-outsider dichotomy at play. This will be examined through a nuanced interpretation of two contemporary novels from Northeast India, Mamang Dai’s The Black Hill (2014) and Anjum Hasan’s Lunatic in My Head (2007). By foregrounding Barth’s theoretic framework, the select novels decipher the underlying dynamics of exclusion and incorporation, challenging the conventional binary of “insider” and “outsider.” This study makes a noteworthy contribution to the discussions around society, ethnicity, and peace in Northeast India, using textual analysis method where literary narratives are interpreted in their sociopolitical contexts. It highlights the importance of challenging existing suppositions regarding ethnic identity and adopting a comprehensive and inclusive approach toward promoting peace in the region.

Why did the Hornbill not cross the river? Upland habitats rather than a physical barrier limit the distribution of the Brown Hornbill

AbstractAimIn continuous environments, niche limits of species often determine their distribution limits. However, when these limits spatially coincide with a perceived dispersal barrier, the determinants of species' ranges may be confounded. We investigate the distribution pattern of the Brown Hornbill (Aves: Bucerotidae), which spans significant riverine barriers, but stops south of the Brahmaputra River. Considering its preference for low‐elevation evergreen forests, we posit that the lack of sufficient habitats north of the Brahmaputra prevents dispersal of the Brown Hornbill, and not the river itself.LocationThe Brahmaputra valley and the Indo‐Burma hotspot.TaxaAnorrhinus austeni, Aceros nipalensis.MethodsWe analysed citizen‐science occurrence data on hornbill presence against a suite of climatic, canopy‐specific and topographical predictors to model the environmental niche of the Brown Hornbill. We used presence‐only maximum entropy modelling in an information theoretic framework, in conjunction with constructing binary logistic regression models using presence and pseudoabsence data. We compared niche models of the Brown Hornbill and the Rufous‐necked hornbill, a close relative with a similar distribution, but which has spanned the Brahmaputra River.ResultsDespite the presence of suitable wet‐evergreen forests north of the Brahmaputra River, the hilly terrains in the region act as a biogeographic barrier for the Brown Hornbill, which prefers lowland evergreen forests. Further, highly suitable regions for the Brown and the Rufous‐necked Hornbills precisely delineate low and high‐elevation evergreen forests respectively, indicating that these birds are separated along an elevational axis.Main ConclusionsThe Brahmaputra River lies at the cusp of two subtly different environmental regimes. It may therefore serve as the niche limit for certain organisms and not as a physical obstacle to their dispersal. Our study implicitly predicts how widespread deforestation prevalent in the lowland evergreen forests of this region adversely impacts the distributions of organisms that depend on them, such as the Brown Hornbill. Further, our study proffers an approach to ascertain determinants of species distributions in a hypothesis testing framework.

Quantum Nonlocality: Multicopy Resource Interconvertibility and Their Asymptotic Inequivalence.

Quantum nonlocality, pioneered in Bell's seminal work and subsequently verified through a series of experiments, has drawn substantial attention due to its practical applications in various protocols. Evaluating and comparing the extent of nonlocality within distinct quantum correlations holds significant practical relevance. Within the resource theoretic framework this can be achieved by assessing the interconversion rate among different nonlocal correlations under free local operations and shared randomness. In this study we, however, present instances of quantum nonlocal correlations that are incomparable in the strongest sense. Specifically, when starting with an arbitrary many copies of one nonlocal correlation, it becomes impossible to obtain even a single copy of the other correlation, and this incomparability holds in both directions. Such incomparable quantum correlations can be obtained even in the simplest Bell scenario, which involves two parties, each having two dichotomic measurements setups. Notably, there exist an uncountable number of such incomparable correlations. Our result challenges the notion of a "unique gold coin," often referred to as the "maximally resourceful state," within the framework of the resource theory of quantum nonlocality. To this end, we provide examples of isotropic quantum correlations that cannot be distilled up to the Tsirelson point, and thus partially answer a long-standing open question in nonlocality distillation.

A Decision Theoretic Framework for Message Prioritization via Machine Learning Algorithm in Vehicular Networks

A Decision Theoretic Framework for Message Prioritization via Machine Learning Algorithm in Vehicular Networks

Spatial Patterning Analysis of Cellular Ensembles (SPACE) discovers complex spatial organization at the cell and tissue levels.

Spatial patterns of cells and other biological elements drive both physiologic and pathologic processes within tissues. While many imaging and transcriptomic methods document tissue organization, discerning these patterns is challenging, especially when they involve multiple elements in complex arrangements. To address this challenge, we present Spatial Patterning Analysis of Cellular Ensembles (SPACE), an R package for analysis of high-plex spatial data. SPACE is compatible with any data collection modality that records values (i.e., categorical cell/structure types or quantitative expression levels) at fixed spatial coordinates (i.e., 2d pixels or 3d voxels). SPACE detects not only broad patterns of co-occurrence but also context-dependent associations, quantitative gradients and orientations, and other organizational complexities. Via a robust information theoretic framework, SPACE explores all possible ensembles of tissue elements - single elements, pairs, triplets, and so on - and ranks the most strongly patterned ensembles. For single images, rankings reflect patterns that differ from random assortment. For sets of images, rankings reflect patterns that differ across sample groups (e.g., genotypes, treatments, timepoints, etc.). Further tools then thoroughly characterize the nature of each pattern for intuitive interpretation. We validate SPACE and demonstrate its advantages using murine lymph node images for which ground truth has been defined. We then use SPACE to detect new patterns across varied datasets, including tumors and tuberculosis granulomas.

The opportunities and challenges of crisis cartel during demand disruptions: A game theoretic study

AbstractCrisis cartel refers to the collaboration between organisations during unprecedented conditions to counter the effect of disruption during an economic crisis. Despite its prevalence, scholarly attention to this phenomenon remains scant. Employing a dual‐channel framework involving manufacturers, online retailers (ORs) and traditional brick‐and‐mortar retailers (BMRs), the authors scrutinised the efficacy of crisis cartels in mitigating the impact of negative demand disruptions. Three distinct game theoretic frameworks were applied to model the interactive dynamics between the supply chain partners, namely, the horizontal Nash game, the Stackelberg game and the collusion game. It was observed that, during disruption under crisis cartels, the optimal price and profit of both the downstream channel partners increased, whereas the optimal order quantity decreased. Manufacturers and consumers are worse off in terms of profit and consumer surplus, respectively, during the crisis cartel engagement between BMR and OR. Nonetheless, a crisis cartel emerged as a potential solution to address negative demand disruptions. In evaluating post‐disruption cartels, the study finds the necessity of regulating crisis cartels. The findings offer valuable insights for policymakers, market regulators and practitioners, suggesting the need for strategic regulatory adjustments to effectively manage disruptions through the prudent utilisation of crisis cartel as a proactive management tool. The study expands existing theory by providing novel insights into the strategic interactions and dynamics within collaborative responses to demand disruptions, thus offering a pioneering approach to crisis management research.

Spectral properties of Schrödinger operators with locally $H^{-1}$ potentials

We study half-line Schrödinger operators with locally H^{-1} potentials. In the first part, we focus on a general spectral theoretic framework for such operators, including a Last–Simon-type description of the absolutely continuous spectrum and sufficient conditions for different spectral types. In the second part, we focus on potentials which are decaying in a local H^{-1} sense; we establish a spectral transition between short-range and long-range potentials and an \ell^{2} spectral transition for sparse singular potentials. The regularization procedure used to handle distributional potentials is also well suited for controlling rapid oscillations in the potential; thus, even within the class of smooth potentials, our results apply in situations which would not classically be considered decaying or even bounded.

An Assessment of the Resurgence of Historical and Classical fashion due to the economical use of language in South Africa

The common trend of fashion is that it comes and goes as history changes and human development advances. However, as humans develop and are supposed to be progressing, sometimes in terms of fashion they also retrogress. The assumption is that language used by advertisers and designers influences people to revisit history. The purpose of this study was to argue that the work of art never expires as it gets repackaged, remodelled and modified over the ages. Some works and designs of art used in a particular period of history may have become obsolete, but the use of a language in a future epoch may bring them back to popularity. In this conceptual qualitative study, literature from both online and offline was used in making the case that art develops with the use of language than perishing. Within this desktop conceptual study, it was found that the language of advertisement is crucial in portraying fashion because language use can revive fashion. The power of language creates a hunt and frenzy to wear clothes of the 1500s calling them ‘vintage’. Using an analytic theoretic framework, this paper investigated the linguistic power and its influence on different epochs. This study specifically argued for the necessary merger between art and linguistics as that would be beneficial in creating classical fashion trends. The recommendation thereof was that teachers of art must work together with language specialists and incorporate both value and language in advertisements. This study posits that language has much power to influence the economy, culture, fashion, and even lifestyle of many people across generations. Keywords: Fashion Fads, Language Potency, Vintage, Economic Language, Fashion Resurgence

Out‐of‐band transaction pool sync for large dynamic blockchain networks

AbstractSynchronization of transaction pools (mempools) has shown potential for improving the performance and block propagation delay of state‐of‐the‐art blockchains. Indeed, various heuristics have been proposed in the literature to incorporate early exchanges of unconfirmed transactions into the block propagation protocol. In this work, we take a different approach, maintaining transaction synchronization externally (and independently) of the block propagation channel. In the process, we formalize the synchronization problem within a graph theoretic framework and introduce a novel algorithm (SREP—set reconciliation‐enhanced propagation) with quantifiable guarantees. We analyze the algorithm's performance for various realistic network topologies and show that it converges on static connected graphs in a time bounded by the diameter of the graph. In graphs with dynamic edges, SREP converges in an expected time that is linear in the number of nodes. We confirm our analytical findings through extensive simulations that include comparisons with MempoolSync, a recent approach from the literature. Our simulations show that SREP incurs reasonable bandwidth overhead and scales gracefully with the size of the network (unlike MempoolSync).

Game-theoretic analysis of competition between access service providers utilizing a Nash genetic algorithm

Fiber-to-the-home (FTTH) technology is a promising solution for providing advanced service delivery to end-users, but its implementation requires substantial capital expenditures. To minimize investment risks and aid decision-making for access service providers, we propose a game theoretic framework based on a modified Nash genetic algorithm. We illustrate how this framework can be applied to analyze the competition between access providers offering a flat-rate FTTH service on multiple geographical areas. Each provider determines its price for all areas simultaneously and decides whether to invest on a particular area depending on the anticipated revenues. Two distinct demand models are adopted to describe different types of consumer behavior. A solution engine, based on a modified mixed-variable Nash genetic algorithm is implemented under an open-source license. The significance and practical implications of the equilibrium points obtained for both single and multiple area games are discussed. The proposed framework and the solution engine developed, aid both providers and regulatory bodies to analyze competitive environments. They can also be used to implement decision support tools for similar problems as well. The paper concludes by pointing out further research directions in this context.