The Second International: The Impact of Domestic Factors on International Organization Dysfunction

Cataloged from PDF version of article.This article explores the role of domestic factors in international organization dysfunction, exemplified by the failure of the Second International to agree on a common stance and policy for the prevention of the First World War. Focusing on the French and cof these socialist parties. It concludes that these domestic differences were the source of discrepancy and lack of orchestrated action among the members of the Second International. As a result of these differences, the Second International failed to coordinate and produce a binding resolution that would commit its members to a uniform action against war, hence culminating in international organization dysfunction. © 2013 The Authors. © 2013 Political Studies Association

Conformal Ricci collineations of static spherically symmetric spacetimes

Conformal Ricci collineations of static spherically symmetric spacetimes are studied. The general form of the vector fields generating conformal Ricci collineations is found when the Ricci tensor is non-degenerate, in which case the number of independent conformal Ricci collineations is \emph{fifteen}; the maximum number for 4-dimensional manifolds. In the degenerate case it is found that the static spherically symmetric spacetimes always have an infinite number of conformal Ricci collineations. Some examples are provided which admit non-trivial conformal Ricci collineations, and perfect fluid source of the matter

Building Democracy to Last: The Turkish Experience in Comparative Perspective

This study analyses the relationship between checks and balances and democracy, focusing on Turkey in comparative perspective. In a large-N setting, the effects of checks and balances on the quality of democracy are examined. The findings reinforce the essential relationship between democracy and checks and balances. The article then discusses the implications of the the findings for Turkey. It stresses the need for horizontal accountability via checks and balances vested in different state agencies. In addition to state-level checks and balances, the importance of societal actors as sources of accountability is also elaborated. The study identifies the need for vertical accountability, not only through free elections but also by creating a political setting in which pluralistic media and civil society can thrive. In light of findings, the article stresses the need for a new constitutional framework that can embrace both state- and societal-level checks and balances. © 2015 Taylor & Francis

Explainable Transformer Prototypes for Medical Diagnoses

Deployments of artificial intelligence in medical diagnostics mandate not just accuracy and efficacy but also trust, emphasizing the need for explainability in machine decisions. The recent trend in automated medical image diagnostics leans towards the deployment of Transformer-based architectures, credited to their impressive capabilities. Since the self-attention feature of transformers contributes towards identifying crucial regions during the classification process, they enhance the trustability of the methods. However, the complex intricacies of these attention mechanisms may fall short of effectively pinpointing the regions of interest directly influencing AI decisions. Our research endeavors to innovate a unique attention block that underscores the correlation between 'regions' rather than 'pixels'. To address this challenge, we introduce an innovative system grounded in prototype learning, featuring an advanced self-attention mechanism that goes beyond conventional ad-hoc visual explanation techniques by offering comprehensible visual insights. A combined quantitative and qualitative methodological approach was used to demonstrate the effectiveness of the proposed method on the large-scale NIH chest X-ray dataset. Experimental results showed that our proposed method offers a promising direction for explainability, which can lead to the development of more trustable systems, which can facilitate easier and rapid adoption of such technology into routine clinics. The code is available at www.github.com/NUBagcilab/r2r_proto

Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions: Religion, Ideology, and Hate

Terror attacks have been linked in part to online extremist content. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peaceful Muslims. The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective. Divergent extremist and mainstream contexts challenge machine interpretation, with a particular threat to the precision of classification algorithms. Our context-aware computational approach to the analysis of extremist content on Twitter breaks down this persuasion process into building blocks that acknowledge inherent ambiguity and sparsity that likely challenge both manual and automated classification. We model this process using a combination of three contextual dimensions -- religion, ideology, and hate -- each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible. We utilize domain-specific knowledge resources for each of these contextual dimensions such as Qur'an for religion, the books of extremist ideologues and preachers for political ideology and a social media hate speech corpus for hate. Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate that reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming. Given the potentially significant social impact, we evaluate the performance of our algorithms to minimize mislabeling, where our approach outperforms a competitive baseline by 10.2% in precision.Comment: 22 page

Status of the PANDA barrel DIRC

The PANDA experiment at the future Facility for Antiproton and Ion Research in Europe GmbH (FAIR) at GSI, Darmstadt will study fundamental questions of hadron physics and QCD using high-intensity cooled antiproton beams with momenta between 1.5 and 15 GeV/c. Hadronic PID in the barrel region of the PANDA detector will be provided by a DIRC (Detection of Internally Reflected Cherenkov light) counter. The design is based on the successful BABAR DIRC with several key improvements, such as fast photon timing and a compact imaging region. Detailed Monte Carlo simulation studies were performed for DIRC designs based on narrow bars or wide plates with a variety of focusing solutions. The performance of each design was characterized in terms of photon yield and single photon Cherenkov angle resolution and a maximum likelihood approach was used to determine the π/K separation. Selected design options were implemented in prototypes and tested with hadronic particle beams at GSI and CERN. This article describes the status of the design and R&D for the PANDA Barrel DIRC detector, with a focus on the performance of different DIRC designs in simulation and particle beams