The precision of determining rock mass mechanical parameters is notably impacted by mining blast activities. An advanced method for inverse analysis of these parameters, predicated upon measured blasting vibrations, has been developed. This approach employs a meticulous recognition of initial P-wave and S-wave arrivals within the vibrational energy spectrum. Utilizing principles from elastic wave theory, a novel framework has been established, correlating P-wave and S-wave velocities with dynamic characteristics of rock masses. The efficacy of this method has been substantiated through practical implementation, particularly in the Guanbaoshan Open-pit Iron Mine, Liaoning Province. Here, the derived density ratios were observed to range between 0.98 and 1.01, aligning closely with figures provided by authoritative research institutes. Additionally, the dynamic-to-static Poisson's ratio exhibited variations from 0.85 to 1.03, while the modulus of elasticity ratio dynamically to statically spanned from 2.0 to 2.6. These results, falling within anticipated theoretical ranges, underscore the robust applicability and accuracy of this method. The research contributes significantly to the domain of mining operations, particularly in optimizing blasting processes and enhancing the precision of mechanical parameter acquisition. It presents a pioneering approach, essential for addressing similar challenges in the mining sector.

This investigation examines the effects of varied nanoparticle concentrations, such as zinc oxide (ZnO), copper oxide (CuO), and aluminum oxide (Al₂O₃), on the mass fraction and melting characteristics within nano-enhanced phase change materials (NEPCMs). Employing numerical simulations via ANSYS-FLUENT, the study explores these dynamics within a square enclosure subjected to distinct thermal gradients. The enclosure, measuring 10cm×10cm, incorporates a heat-supplying wall, partitioned into quarters, each exhibiting a unique temperature gradient. This setup provides a comprehensive understanding of boundary conditions relevant to NEPCM behavior. The focus lies on a comparative analysis of NEPCM’s thermal properties under varying nanoparticle concentrations: 0.1, 0.3, and 0.5 weight percent. A low-temperature wall, lined with paraffin wax and integrated with these nanomaterials, facilitates the assessment of their impact on the phase change materials (PCMs). Remarkably, an inverse relationship is observed between nanoparticle concentration and mass fraction, ranging from 0.86 to 0.08. This finding underscores the significant role of nanoparticle integration in modulating NEPCM properties. Among the nanoparticles studied, CuO emerges as the most efficacious in enhancing melting due to its low density and high thermal conductivity. The temperature distribution profile within the paraffin wax shifts from a dispersed state to a more uniform and curved pattern upon nanoparticle incorporation. Such a transformation indicates an improved thermal response of the NEPCM system. The implications of this study are manifold, extending to the design and optimization of thermal energy storage systems. These insights are particularly valuable for applications in energy conservation within buildings, solar energy equipment, transportation, and storage solutions. The research elucidates the criticality of selecting appropriate nanoparticle concentrations for achieving desired phase change properties in NEPCM-based systems. Furthermore, it contributes to a deeper understanding of how nanoparticle characteristics influence the thermal behavior of PCMs, thus offering a guide for future innovations in this field.

Linking Norbert Elias’s concept of the triad of controls, to Andrew Willard Jones’ analysis of the ‘complete act’, the paper outlines the relation between culture and personality and the implications of this for any project of localization and the re-embedding of the economy. Re-iterating the reality that degrowth cannot be a liberal project, the paper goes on to explore the relation between Western individualism and Judeo-Christianity. Shorn of the overarching ontology and orienting architecture of Christianity, individualism has become corrosive, unstable and, in the end, self-destructive. The socially conservative preoccupation with a decline in virtue is linked to eroding social capital, anomie, and unhappiness arising from a surfeit of freedom. Hyper-social and -spatial mobility is linked to the suppression of the domain of Livelihood, with its bottom-up, communitarian and family-based forms of social regulation; and a corollary expansion of both top-down collectivist regulation by the State and the transactional logic of the Market. Livelihood is a function of embedded individuals enmeshed in relations not only with other individuals and groups, but with God. In contrast, the materialist metaphysics of Market and State both depend on disembedded, free-wheeling citizen-consumers, severed from any relation to transcendent values. But these same phenomena are also the principal drivers of consumption and ecological degradation. On this basis it is argued that any culture of ecological restraint predicated on the re-embedding of markets must also entail an ontological re-embedding of the sacred conception of the individual (the Imago Dei) into a relation with the divine. Such a project implies a very different understanding of freedom predicated on an external, legitimate authority; a freedom that is ‘fullest not when it serves itself but when it serves truths freely held” ([1], Loc. 419). Applying Christopher Alexander’s theory of pattern languages, the paper goes on to explore what such a sustainability project might look like.

This study introduces an advanced forecasting method, utilizing a higher-order circular Pythagorean fuzzy time series (C-PyFTSs) approach, for the prediction of Alzheimer’s disease progression. Distinct from traditional forecasting methodologies, this novel approach is grounded in the principles of circular Pythagorean fuzzy set (C-PyFS) theory. It uniquely incorporates both positive and negative membership values, further augmented by a circular radius. This design is specifically tailored to address the inherent uncertainties and imprecisions prevalent in medical data. A key innovation of this method is its consideration of the circular nature of time series, which significantly enhances the accuracy and robustness of the forecasts. The higher-order aspect of this forecasting method facilitates a more comprehensive predictive model, surpassing the capabilities of existing techniques. The efficacy of this method has been rigorously evaluated through extensive experiments, benchmarked against conventional time series forecasting methods. The empirical results underscore the superiority of the proposed method in accurately predicting the trajectory of Alzheimer’s disease. This advancement holds substantial promise for improving prognostic assessments in clinical settings, offering a more nuanced understanding of disease progression.

The advent of digital technology has fundamentally altered the traditional modes of information exchange within enterprises, thereby impacting the concentration of supply chains. This study presents an empirical examination of the effects and underlying mechanisms by which digital transformation influences supply chain concentration, utilizing data from Chinese A-share listed companies spanning 2011 to 2021. The findings reveal that digital transformation enhances information transparency and reduces transaction costs, consequently contributing to a decrease in the concentration of enterprise supply chains. It is observed that the adoption of digital transformation leads to a significant diminution in supply chain concentration, a conclusion that retains its significance even under robustness testing. Further investigation indicates a more pronounced impact of digital transformation on diminishing the concentration of state-owned enterprise supply chains compared to their non-state-owned counterparts. This research enriches the understanding of the impact of digital transformation on supply chain concentration, offering theoretical support for the acceleration of a unified large market development in China. The study underscores the transformative role of digital technology in reshaping enterprise supply chains, highlighting the necessity for strategic digital integration in modern business practices.

In the realm of contemporary logistics, the criticality of intermodal terminals as central nodes for seamless cargo transitions between various transportation modes is well-recognized. This study focuses on the strategic integration of Industry 4.0 (I4.0) technologies to advance the operational efficiency of these terminals. A hybrid Multiple Criteria Decision Making (MCDM) methodology, amalgamating the Best-Worst Method (BWM) and Axial Distance based Aggregated Measurement (ADAM), is employed for a systematic evaluation. This approach facilitates the identification and prioritization of key I4.0 technologies. Findings of this study underscore the paramount importance of the Internet of Things (IoT), Artificial and Ambient Intelligence, and Autonomous and Automated Guided Vehicles in revolutionizing terminal efficiency. The efficacy of the proposed hybrid model is demonstrated in its capacity to generate practical, insightful recommendations for technology selection, thereby guiding stakeholders in making informed investments. These investments are projected to significantly enhance the operational capabilities of intermodal terminals and, by extension, the efficiency of the overall supply chain. The contribution of this study lies in its addressal of the existing research gap concerning the applicability and selection of I4.0 technologies in intermodal transport terminals (ITTs). It offers a novel, pragmatic framework for stakeholders within the logistics sector, aimed at facilitating the modernization and optimization of terminal operations. The insights and strategic directions provided herein are anticipated to be of substantial value to those endeavoring to navigate the complexities of terminal modernization in the era of I4.0.

The basic constitutional freedoms and rights of a person and citizen are in principle unlimited: the full scope of their exercise is the rule, and the restriction determined by law can only be an exception based on explicit constitutional authority and the legitimate aim of the restriction determined by the Constitution. That being so, the restrictions - in addition to being based on constitutional authority and pursuing constitutional objectives - should be commensurate with the needs to achieve these objectives. This means that restrictive legal rules must be suitable for achieving the legitimate aim pursued, must not be stricter than necessary and must be balanced between the constitutionally guaranteed subjective right of the individual and the interests of society.

In this paper, the authors point out the economic and legal consequences of the violation of individual privacy and data protection rights caused by the public disclosure of personal data of people who, at a certain time, were obliged to self-isolate due to suspicion of Covid-19 virus infection.

The landscape of livestock farming is undergoing a significant transformation, primarily influenced by the integration of the Internet of Things (IoT) technology. This systematic literature review (SLR) critically examines the role of IoT in enhancing cow health monitoring, a burgeoning field of research drawing considerable attention in recent years. Spanning articles published from 2017 to 2023 in eminent academic forums, this study meticulously selected and analyzed thirty publications. These were chosen through a structured process, evaluating each for its relevance based on title and abstract. The review encapsulates a thorough investigation of the applications, sensors, and devices underpinning IoT-based cow health monitoring systems. It is observed that the current research landscape is dynamically evolving, marked by emerging trends and noticeable gaps in technology and application. This synthesis of existing literature offers an insightful overview of the potential and limitations inherent in current IoT solutions, highlighting their efficacy in real-world scenarios. Furthermore, this review delineates the challenges faced and posits future research directions to address unresolved issues in cow health monitoring. The primary objective of this systematic analysis is to consolidate research findings, thereby advancing the understanding of IoT's impact in this field. It also aims to foster a comprehensive dialogue on the technological advancements and their implications for future research endeavors in livestock farming.

The ambiguous theme of cyberspace and its broad widespread inflict a major effect on the legal procedures of litigations. Since litigation might include several nationalities, because of the cosmopolitan nature of cyberspace, determining the competent court is not as direct as traditional litigations. Cyber litigations complicate this procedural threshold as the traditional application of jurisdiction determinants might not suit cyber disputes. Furthermore, jurisdiction conflicts in cyberspace frustrate settling the dispute as courts avoid giving their judgments due to invalidity.

Therefore, these conflicts introduce a modern issue to private international law theorists. It is indisputable that drafting obvious jurisdictional rules enhances the rule of law in cyberspace. Thus, the research analyses this issue and establishes a comparison to determine the state of the art regarding it. The article reviews the relevant academic contributions and legislation to point out how they crystallize the aspects of the research question. Besides, it studies relevant case laws from the UK and US judiciaries to conclude the legal principle they adopt to settle these conflicts and to enhance the validity of their judgments. Eventually, it introduces a comprehensive theory on settling jurisdiction conflicts regarding cyber litigation, which enhances the rule of law in cyberspace.

Traditional tests for parallel trends in the context of differences-in-differences are based on the observation of the mean values of the dependent variable in the treatment and control groups over time. However, given the new discussions brought by the development of the event study designs, controlling for observable factors may intervene in the fulfilment of the parallel trend assumption. This article presents a simple test based on the statistical significance of pre-treatment periods which can be extended from the classic Differences-in-Differences up to event study designs in universal absorbing treatments. The test requires at least two pre-treatment periods and can done by constructing appropriate dummy variables.