Hasil untuk "Law"

A. Atangana

L. Brinson

Wei-bing Gao, Yufu Wang, A. Homaifa

I. Ehrlich

D. Cheng

M. Biot

C. Law

J. Donnay, D. Harker

H. Kelsen

D. Mackay, W. Shiu

F. Lucchin, S. Matarrese

W. Baum

T. F. Sherman

A large part of the branching vasculature of the mammalian circulatory and respiratory systems obeys Murray's law, which states that the cube of the radius of a parent vessel equals the sum of the cubes of the radii of the daughters. Where this law is obeyed, a functional relationship exists between vessel radius and volumetric flow, average linear velocity of flow, velocity profile, vessel-wall shear stress, Reynolds number, and pressure gradient in individual vessels. In homogeneous, full-flow sets of vessels, a relation is also established between vessel radius and the conductance, resistance, and cross- sectional area of a full-flow set.

Balazs Gyenis

I argue that if a special science satisfies certain key assumptions that are familiar from physicalist accounts of the special sciences and from physics, then its causal regularities have an associated notion of entropy, and that this causal entropy cannot decrease from a robust cause to its effect. Due to its analogy with the second laws of thermodynamics and statistical physics, I call the latter conclusion the causal second law. In this paper, I clarify the key assumptions, prove the causal second law, give sufficient conditions for causal entropy increase, relate the causal second law to statistical mechanics and thermodynamics, and argue that the reversibility objection does not threaten it. In addition, I claim that the causal second law is compatible with a non-metaphysical understanding of supervenience and the open systems view, argue that it does not imply a causal time arrow, reflect on relaxing the robustness condition, question whether it is necessary to invoke thermodynamics to show that special sciences' time arrows exist, and discuss a transition-relative-frequency-based, special-science-internal characterization of causal regularities.

Stuart G. Hall

Orsetta Giolo

En este ensayo, quisiera proponer una reflexión inicial sobre la significativa convergencia entre el iusfeminismo y el pacifismo jurídico en la crítica a la guerra. En primer lugar, mencionaré brevemente algunas consideraciones sobre el iusfeminismo como matriz constitutiva de las teorías críticas del derecho; posteriormente, intentaré analizar la naturaleza del pacifismo jurídico como una teoría crítica del Derecho. A continuación, tras precisar por qué el iusfeminismo y el pacifismo jurídico deben entenderse como “saberes inéditos”, me detendré, de forma esquemática, en el análisis de su convergencia metodológica, teórica y temática.

Dicky Janeman Paseki, Carlo Aldrin Gerungan, Djoly Alfrits Sualang

This study aims to analyze the role of the Minahasa Regency General Election Commission (KPU) in ensuring the fulfillment of Minahasa residents' voting rights in the 2024 General Election (Pemilu) in accordance with Law No. 7 of 2017 concerning General Elections. This study uses a qualitative approach with a descriptive-analytical method that focuses on the implementation of duties, authorities, and challenges faced by the KPU in managing the permanent voter list (DPT), election socialization, and providing accessibility for vulnerable groups. The results of the study indicate that the Minahasa Regency KPU has a strategic role in implementing inclusive election stages through voter education programs, factual verification of voter data, and strengthening equal community participation for all levels of citizens including the disabled. However, the lack of voter understanding and technical challenges in the field require integrated solutions.

Imma Lory Aprea, Gianni Bosi, Gabriele Sbaiz et al.

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) information is incorporated. More specifically, we extend the standard portfolio volatility framework based on the financial aspects to a new paradigm where the sustainable credits are taken into account. In the portfolio’s construction, we consider the classical constraints concerning budget and box requirements. To deal with these new asset allocation models, in this paper, we develop an improved Multi-Objective Particle Swarm Optimizer (MOPSO) embedded with ad hoc repair and projection operators to satisfy the constraints. Moreover, we implement a deep learning architecture to improve the quality of estimating the portfolio diversification objective. Finally, we conduct empirical tests on datasets from three different countries’ markets to illustrate the effectiveness of the proposed strategies, accounting for various levels of ESG volatility.

Mingwei Su, Yunbo Zheng

Abstract The purpose of this paper is to understand the spatial and temporal evolution of the level of rule of law government construction in China and the mechanism of influence, in an attempt to expand the research direction of legal geography, and to provide empirical cases for how developing countries can promote the rule of law construction under unbalanced geographic, economic and institutional conditions. The study investigates the spatiotemporal variations and influencing factors of law-based government construction levels in each of China’s 31 provincial administrative regions from 2015 to 2022, employing the Moran index and geographic detectors. The results show: (1) The construction level of law-based government in each provincial administrative region has exhibited a clear upward trend, shifting from predominantly “low” and “medium-low” levels to predominantly “medium-high” and “high” levels. (2) The construction level of law-based government and its development type exhibit clear spatial aggregation in each region. The spatial distribution of the four categorized types shows continuity and obvious characteristics of agglomeration. (3) The construction of a law-based government is influenced by economic, social, environmental, and political factors. The basic economic system, level of economic development, and resources per capita available to the administration have the greatest impact. The interaction between these factors significantly enhances their influence on the level of law-based government construction. The improvement of the level of rule of law government construction not only depends on the economic foundation and institutional resources, but is also affected by multiple factors such as urbanization development, demographic structure, public service provision, and institutional innovation path.

Xiaowei Gao, James Haworth, Ilya Ilyankou et al.

Predicting traffic accidents is the key to sustainable city management, which requires effective address of the dynamic and complex spatiotemporal characteristics of cities. Current data-driven models often struggle with data sparsity and typically overlook the integration of diverse urban data sources and the high-order dependencies within them. Additionally, they frequently rely on predefined topologies or weights, limiting their adaptability in spatiotemporal predictions. To address these issues, we introduce the Spatiotemporal Multiview Adaptive HyperGraph Learning (SMA-Hyper) model, a dynamic deep learning framework designed for traffic accident prediction. Building on previous research, this innovative model incorporates dual adaptive spatiotemporal graph learning mechanisms that enable high-order cross-regional learning through hypergraphs and dynamic adaptation to evolving urban data. It also utilises contrastive learning to enhance global and local data representations in sparse datasets and employs an advance attention mechanism to fuse multiple views of accident data and urban functional features, thereby enriching the contextual understanding of risk factors. Extensive testing on the London traffic accident dataset demonstrates that the SMA-Hyper model significantly outperforms baseline models across various temporal horizons and multistep outputs, affirming the effectiveness of its multiview fusion and adaptive learning strategies. The interpretability of the results further underscores its potential to improve urban traffic management and safety by leveraging complex spatiotemporal urban data, offering a scalable framework adaptable to diverse urban environments.