Search Results (281)

As the global urbanization process accelerates, rural settlements in China are facing the challenges of rural hollowing and widening urban–rural disparities. The establishment of the national scenic area system has made scenic settlements a primary direction for tourism development. However, industrial transformation has led to significant restructuring of the human–land relationship and the spatial functions of these settlements, resulting in issues such as over-tourism, ecological degradation, and cultural loss. This paper focuses on the Mosuo settlements around Lugu Lake, selecting nine villages, including Gesha Village, Wuzhiluo Village, and Daluoshui Village, to explore the formation and expression of Mosuo spatial concepts. Through spatial measurement, area statistics, and the analysis of development paths, the core of the research is to propose that “there is consistency between conceptual order and spatial form,” revealing the multi-dimensional evolutionary mechanism of Mosuo settlement spatial morphology under the intertwining of traditional concepts, market logic, and institutional policies, providing a replicable Chinese reference for global cultural heritage rural areas. Full article

We explore the realm of uncertainty theory by investigating diverse notions of convergence and statistical convergence concerning complex uncertain sequences. Complex uncertain variables can be described as measurable functions mapping from an uncertainty space to the set of complex numbers. They are employed to represent and model complex uncertain quantities. We introduce the concept of lacunary almost statistical convergence of order $\alpha$$(0<\alpha \le 1)$ for complex uncertain sequences, examining various aspects of uncertainty such as distribution, mean, measure, uniformly almost sure convergence and almost sure convergence. Additionally, we establish connections between the constructed sequence spaces by providing illustrative instances. Importantly, lacunary almost statistical convergence provides a flexible framework for handling sequences with irregular behavior, which often arise in uncertain environments with imprecise data. This makes our approach particularly useful in practical fields such as engineering, data modeling and decision-making, where traditional deterministic methods are not always applicable. Our approach offers a more flexible and realistic framework for approximating functions in uncertain environments where classical convergence may not apply. Thus, this study contributes to approximation theory by extending its tools to settings involving imprecise or noisy data. Full article

We introduce a novel entropy-related function, non-repeatability, designed to capture dynamical behaviors in complex systems. Its normalized form, mutability, has been previously applied in statistical physics as a dynamical entropy measure associated with any observable stored in a sequential file. We now extend this concept by calculating the sorted mutability for the same data file previously ordered by increasing or decreasing value. To present the scope and advantages of these quantities, we analyze two distinct systems: (a) Monte Carlo simulations of magnetic moments on a square lattice, and (b) seismic time series from the United States Geological Survey catalog. Both systems are well established in the literature, serving as robust benchmarks. Shannon entropy is employed as a reference point to assess the similarities and differences with the proposed measures. A key distinction lies in the sensitivity of non-repeatability and mutability to the temporal ordering of data, which contrasts with traditional entropy definitions. Moreover, sorted mutability reveals additional insights into the critical behavior of the systems under study. Full article

Ordinal patterns have proven to be a valuable tool in many fields. Here, we address the need for theoretical models. A paradigmatic example shows that a model for frequencies of ordinal patterns can be determined without any numerical values. We specify the important concept of stationary order and the fundamental problems to be solved in order to establish a genuine statistical methodology for ordinal time series. Full article

The 2012 Emilia earthquake highlighted the vulnerability of fortified architecture. Based on the observed seismic behaviors, this research proposes a GIS geodatabase, designed with a proactive approach, for the prediction and prevention—at a territorial scale—of the most frequent damage mechanisms of the investigated typology. The designed geo-database allows for the identification of possible correlations between constructive features and the occurrence of damage, through statistical and geo-referenced analysis. Moreover, the designed geodatabase, by enabling the comparison of the damage level data with the seismic action of the site, through INGV (National Institute of Geophysics and Volcanology) shakemaps, allowed the definition of experimental fragility curves, for three of the most common damage mechanisms. By applying these functions to castles in the province of Parma, it was possible to define future seismic risk scenarios for the mechanisms considered, thanks to the use of the seismic hazard map. Therefore, the described methodology could be functional to identify the most urgent and high-priority interventions in order to optimize the management of economic resources. The final aim is to promote the application of the concept of minimum intervention, and more in general to preserve the architectural heritage, avoiding emergency interventions and aiming instead to apply planned conservation strategies. Full article

The description of a combination of technologies as ‘artificial intelligence’ (AI) is misleading. To ascribe intelligence to a statistical model without human attribution points towards an attempt at shifting legal, social, and ethical responsibilities to machines. This paper exposes the deeply flawed characterisation of AI and the unearned assumptions that are central to its current definition, characterisation, and efforts at controlling it. The contradictions in the framing of AI have been the bane of the incapacity to regulate it. A revival of applied definitional framing of AI across disciplines have produced a plethora of conceptions and inconclusiveness. Therefore, the research advances this position with two fundamental and interrelated arguments. First, the difficulty in regulating AI is tied to it characterisation as artificial intelligence. This has triggered existing and new conflicting notions of the meaning of ‘artificial’ and ‘intelligence’, which are broad and largely unsettled. Second, difficulties in developing a global consensus on responsible AI stem from this inconclusiveness. To advance these arguments, this paper utilises functional contextualism to analyse the fundamental nature and architecture of artificial intelligence and human intelligence. There is a need to establish a test for ‘artificial intelligence’ in order ensure appropriate allocation of rights, duties, and responsibilities. Therefore, this research proposes, develops, and recommends an adaptive three-elements, three-step threshold for achieving responsible artificial intelligence. Full article

Based on data from broadband dielectric spectroscopy (BDS) and a molecular model based on the Landau–de Gennes concept, the effect of confinement on the structural, dielectric, and dynamic properties of 4-n-pentyl-4′-cyanobiphenyl (5CB) in the nematic phase is studied. The dielectric permittivity and relaxation times were previously obtained by the BDS technique in a wide frequency range ($1\mathrm{MHz}\le \mathrm{f}\le 1\mathrm{GHz}$) in the nematic phase composed of 5CB molecules confined to Anopore membranes with pore sizes of 0.2 $\mathsf{\mu }$m. The distance-dependent values of the order parameter $P_2\left(r\right)$, the relaxation time $\tau \left(r\right)\equiv {\tau }_{00}^1\left(r\right)$, the rotational diffusion coefficient $D_{\perp }\left(r\right)$, and both rotational viscosity coefficients ${\gamma }_i\left(r\right)$ ($i=1,2$) as functions of the distance r away from the bounding surface are calculated by a combination of existing statistical-mechanical approaches and data obtained by the BDS technique. Reasonable agreement between the calculated and experimental values of ${\gamma }_i(i=1,2)$ for bulk 5CB is obtained. Full article

This systematic review answers questions about whether or not a model of metacognition is well accepted and if it can be used in cognitive architecture design. Self-planning, self-monitoring, and self-evaluation are the model concepts, which are viewed as metacognitive experiences. A newly formulated theoretical approach named Attention as Action was targeted, as it is shown to be used in cognitive architecture design. In order to link the model to the theoretical approach, specific concepts like mental imagery and learning experience were researched. The method includes the statistical analysis of key phrases in articles that were collected based on a system of criteria. Data were retrieved from 91 scientific papers to allow statistical analysis of the relationship between the model of metacognition and the theoretical approach to cognitive architecture design. Several observations from the data show that the model is applicable for designing cognitive monitoring systems that depict experiences of metacognition. Furthermore, the results point out that the researched fields require explanations about the concepts defined in the theoretical approach of Attention as Action. Systematically formulated as types of internal attentional experiences, new relations are provided for researching cognitive and metacognitive concepts in terms of the cognitive cycle. Full article

Backgrounds: Korean society is entering an aging society, and this phenomenon indicates the need for preparation for aging in Korean society. In such a situation, exploring the characteristics of the elderly can be considered important for preparation. The objective of this study is to identify the determinants of medical expenses among older adults in South Korea. The key factors analyzed include food, leisure, and housing expenses, as well as lifestyle choices such as drinking and smoking. Method: Data from the Korean Longitudinal Study of Aging, covering 7374 observations from the years 2018 and 2020, are adopted for statistical analysis. This research explores the inverted-U-shape effect of food, leisure, and housing expenditures on medical costs, grounded in the concepts of diminishing marginal utility and mental accounting. A quadratic panel regression analysis is used to test the hypotheses, controlling for variables such as birth year, gender, and personal assets. Results: The results show that food and housing expenses have an inverted-U relationship with medical expenditures based on diminishing marginal utility and mental accounting as the theoretical foundation. However, leisure expenses, drinking, and smoking do not significantly affect medical expenses. Furthermore, this study identifies the optimal expenditure levels for maximizing medical spending through the first-order condition. Conclusions: These findings provide important insights for the development of policies aimed at improving the financial well-being of older adults in South Korea. Moreover, this study contributes to the literature by applying the concepts of mental accounting and the law of diminishing marginal utility to better understand the financial behavior of older adults. Full article

This study proposes a comprehensive framework for integrating data-driven approaches into policy analysis and intervention strategies. The methodology is structured around five critical components: data collection, historical analysis, policy impact assessment, predictive modeling, and intervention design. Leveraging data-driven approaches capabilities, the line of work enables advanced multilingual data processing, advanced statistics in population trends, evaluation of policy outcomes, and the development of evidence-based interventions. A key focus is on the theoretical integration of social order mechanisms, including communication modes as institutional structures, token optimization as an efficiency mechanism, and institutional memory adaptation. A mixed methods approach was used that included sophisticated visualization techniques and use cases in the hospitality sector, in global food security, and in educational development. The framework demonstrates its capacity to inform government and industry policies by leveraging statistics, visualization, and AI-driven decision support. We introduce the concept of “institutional intelligence”—the synergistic integration of human expertise, AI capabilities, and institutional theory—to create adaptive yet stable policy-making systems. This research highlights the transformative potential of data-driven approaches combined with large language models in supporting sustainable and inclusive policy-making processes. Full article

Background/Objectives: Many commercial light-emitting diode (LED) devices are available for consumer home usage. The performance characteristics in respect to the dosimetry of many of the devices, currently on direct sale to the public, have not been subject to formal appraisal. In order to ‘bridge the gap’ between the evidence-based photobiomodulation therapy (PBMT) community and other interested parties, an evaluation is made of a selection of torch type hand-held LED PBMT products currently available for home use. Methods: Five randomly chosen intra-oral and hand-held LED PBMT devices were selected. The optical delivery parameters of the devices were measured, including the beam divergence angle, surface area exposure as well as the output power at the level of the LEDs. The surface and sub-surface temperature changes in porcine tissue samples were assessed under standardised conditions. The manufacturer’s patient instructions were correlated to the measured optical parameters. Calculations were made of irradiance and surface radiant exposure. Consumer satisfaction ratings and feedback data were collated, and a relevant statistical analysis conducted. Results: The results were heterogeneous with a wide range of applied wavelengths, output power and irradiance. Power output stability was variable, and, together with a wide beam divergence angle of 74°, the manufacturer’s directions for dosimetry were found to be inconsistent with an accurate dose delivery. Conclusions: The manufacturer’s proposed dosimetry fails to consider the relevance of the beam divergence angle and optical attenuation in view of the scatter and absorption. Appropriate instructions on how best to gain and optimise an acceptable clinical outcome were inconsistent with an evidence-based approach. Subject to validation by well-planned clinical trials, the concept of home PBMT may open interesting new therapeutic approaches. Full article

With the advancement of non-classical light sources such as single-photon and entangled-photon sources, innovative microscopy based on quantum principles has been proposed for traditional microscopy. This paper introduces the experimental demonstration of a quantum polarization microscopic technique that incorporates a quantum-entangled photon source. Although the point that employs the variation in polarization angle due to reflection or transmission at the sample is similar to classical polarization microscopy, the method for constructing the image contrast is significantly different. The image contrast is constructed by the coincidence count of signal and idler photons. In the case that the coincidence count is recorded from both the signal and idler photons, the photon statistics resemble a thermal state, similar to the blackbody radiation, but with a significantly higher peak intensity in the second-order autocorrelation function at zero delay that is derived from the coincidence count, while, when the coincidence count is taken from either the signal or idler photon only, although the photon state exhibits a thermal state again, the photon statistics become more dispersive and result in a lower peak intensity of the autocorrelation function. These different thermal states can be switched by slightly changing the photon polarization, which is suddenly aroused within a narrow range of the analyzer angle. The autocorrelation function g²(0) at the thermal state exhibits a sensitivity that is three times higher compared to the classical coincidence count rate, and this concept can be effectively utilized to enhance the contrast of the image. One of the key achievements of our proposed method is ensuring a low power of illumination (in the order of Pico-joules) for constructing the image. In addition, the robustness without any precise setup is also favorable for practical use. This polarization microscopic technique can provide a superior imaging technique compared to the classical method, opening a new frontier for research in material sciences, biology, and other fields requiring high-resolution imaging. Full article

Studies on difference sequences was introduced in the 1980s, and since then, many mathematicians have studied this kind of sequences and obtained some generalized difference sequence spaces. In this paper, using the generalized difference operator, we introduce the concept of the deferred f-statistical convergence of generalized difference sequences of the order $\alpha$ and give some inclusion relations between the deferred f-statistical convergence of generalized difference sequences and deferred f-statistical convergence of generalized difference sequences of the order $\alpha$. Our results are more general than the corresponding results in the existing literature. Full article

The objective of this study was to analyse the evolutionary field of sustainable human resource management (S-(HRM)) over four strategically chosen sub-periods in order to understand its behaviour in the period from 1991 to 2024. We started by conducting a comprehensive review of research articles related to our topic, aiming to produce a scientific, accurate, and well-argued result through quantitative and empirical research, incorporating both factorial and exploratory analyses. We began by carrying out an exhaustive review of different research articles related to our topic in order to generate a scientific, truthful and argumentative result, from quantitative and empirical research, in relation to a factorial and exploratory analysis. Regarding the analysis of the period between the years chosen for this research (1991–2024), we observe that the subject analysed has gradually evolved, with an increase in publications, as evidenced in the different graphs. In turn, the analysis of the most prominent themes for the sub-periods is illustrated by their classification in strategic diagrams and structured spheres quantified in the statistical software SciMAT v1.1.06, through keywords, which is the strategy best adapted to this type of research. The analysis (keywords) configures the most important concepts of the research field. Full article

A new method to discover open-loop, unstable, longitudinal aerodynamic parameters, using a ‘two-stage optimization approach’ for designing optimal inputs, and with an application on the fighter aircraft platform, has been presented. System identification of supersonic aircraft requires formulating optimal inputs due to the extremely limited maneuver time, high angles of attack, restricted flight conditions, and the demand for an enhanced computational effect. A pre-requisite of the parametric model identification is to have a priori aerodynamic parameter estimates, which were acquired using linear regression and Least Squares (LS) estimation, based upon simulated time histories of outputs from heuristic inputs, using an F-16 Flight Dynamic Model (FDM). In the ‘first stage’, discrete-time pseudo-random binary signal (PRBS) inputs were optimized using a minimization algorithm, in accordance with aircraft spectral features and aerodynamic constraints. In the ‘second stage’, an innovative concept of integrating the Fisher Informative Matrix with cost function based upon D-optimality criteria and Crest Factor has been utilized to further optimize the PRBS parameters, such as its frequency, amplitude, order, and periodicity. This unique optimum design also solves the problem of non-convexity, model over-parameterization, and misspecification; these are usually caused by the use of traditional heuristic (doublets and multistep) optimal inputs. After completing the optimal input framework, parameter estimation was performed using Maximum Likelihood Estimation. A performance comparison of four different PRBS inputs was made as part of our investigations. The model performance was validated by using statistical metrics, namely the following: residual analysis, standard errors, t statistics, fit error, and coefficient of determination $({\mathrm{R}}^2)$. Results have shown promising model predictions, with an accuracy of more than 95%, by using a Single Sequence Band-limited PRBS optimum input. This research concludes that, for the identification of the decoupled longitudinal Linear Time Invariant (LTI) aerodynamic model of supersonic aircraft, optimum PRBS shows better results than the traditional frequency sweeps, such as multi-sine, doublets, square waves, and impulse inputs. This work also provides the ability to corroborate control and stability derivatives obtained from Computational Fluid Dynamics (CFD) and wind tunnel testing. This further refines control law design, dynamic analysis, flying qualities assessments, accident investigations, and the subsequent design of an effective ground-based training simulator. Full article