Holography for Black Holes in General Relativity and Beyond

Both extremal and non-extremal Kerr black holes have been considered to be holographically dual to two-dimensional (2D) conformal field theories (CFTs). In this thesis, we study the holography to the case of a rotating Janis-Newman-Winicour (JNW) black holes, a rotating Brans-Dicke-Kerr (BDK) black hole, and an asymptotically anti-de Sitter (AdS) rotating charged black holes in $f$($T$) gravity, where $f(T) = T + \alpha T^2$, where $\alpha$ is a constant. Firstly, we find that the rotating JNW solution does not satisfy the Einstein field equation. Thus, we could not establish a well-defined Kerr/CFT correspondence in this theory. Secondly, we find that the scalar wave equation in the background of BDK black hole is not separable. The existence of the $SL(2,R)_L\times SL(2,R)_R$ symmetry can be found in the radial equation of the scalar probe around the non-extremal black hole. Therefore, the inseparability of the scalar wave equation eliminates the possibility of any holography aspect for BDK black hole. Thirdly, we find that the scalar wave radial equation at the near-horizon region implies the existence of the 2D conformal symmetries. We note that the $2\pi$ identification of the azimuthal angle $\phi$ in the black hole line element, corresponds to a spontaneous breaking of the conformal symmetry by left and right temperatures $T_{L}$ and $T_{R}$, respectively. We show that choosing proper central charges for the dual CFT, we produce exactly the macroscopic Bekenstein-Hawking entropy from the microscopic Cardy entropy for the dual CFT. These observations suggest that the rotating charged AdS black hole in $f$($T$) gravity is dual to a 2D CFT at finite temperatures $T_{L}$ and $T_{R}$ for a specific value of mass $M$, rotational, charge, and $f$($T$) parameters, $\Omega$, $Q$, and \abs{\alpha}, respectively

Implementation Science for Point-of-Care Diagnostics

This book focuses on the application of implementation science methods to enable the rapid uptake and sustainable implementation of new diagnostics into routine health practices to strengthen health systems.Diagnostics are essential for the success of universal health coverage and improved health outcomes. The increased development and deployment of diagnostics for use at the point of care will not guarantee improved access to diagnostics and health outcomes if their implementation is not optimized. Optimal implementation will need to be guided by theories and methods that aim to promote evidence-based practices and findings of research into routine practice, taking into consideration quality systems and contexts

Proceedings of the 1st Conference on Central Asian Languages and Linguistics (ConCALL)

The Conference on Central Asian Languages and Linguistics (ConCALL) was founded in 2014 at Indiana University by Dr. Öner Özçelik, the residing director of the Center for Languages of the Central Asian Region (CeLCAR). As the nation’s sole U.S. Department of Education funded Language Resource Center focusing on the languages of the Central Asian Region, CeLCAR’s main mission is to strengthen and improve the nation’s capacity for teaching and learning Central Asian languages through teacher training, research, materials development projects, and dissemination. As part of this mission, CeLCAR has an ultimate goal to unify and fortify the Central Asian language learning community by facilitating networking between linguists and language educators, encouraging research projects that will inform language instruction, and provide opportunities for professionals in the field to both showcase their work and receive feedback from their peers. Thus ConCALL was established to be the first international academic conference to bring together linguists and language educators in the languages of the Central Asian region, including both the Altaic and Eastern Indo-European languages spoken in the region, to focus on research into how these specific languages are represented formally, as well as acquired by second/foreign language learners, and also to present research driven teaching methods. Languages served by ConCALL include, but are not limited to: Azerbaijani, Dari, Karakalpak, Kazakh, Kyrgyz, Lokaabharan, Mari, Mongolian, Pamiri, Pashto, Persian, Russian, Shughnani, Tajiki, Tibetan, Tofalar, Tungusic, Turkish, Tuvan, Uyghur, Uzbek, Wakhi and more!The Conference on Central Asian Languages and Linguistics held at Indiana University on 16-17 May 1014 was made possible through the generosity of our sponsors: Center for Languages of the Central Asian Region (CeLCAR), Ostrom Grant Programs, IU's College of Arts and Humanities Center (CAHI), Inner Asian and Uralic National Resource Center (IAUNRC), IU's School of Global and International Studies (SGIS), IU's College of Arts and Sciences, Sinor Research Institute for Inner Asian Studies (SRIFIAS), IU's Department of Central Eurasian Studies (CEUS), and IU's Department of Linguistics

xxAI - Beyond Explainable AI

This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.https://digitalcommons.unomaha.edu/isqafacbooks/1000/thumbnail.jp

Engines of Order

Over the last decades, and in particular since the widespread adoption of the Internet, encounters with algorithmic procedures for ‘information retrieval’ – the activity of getting some piece of information out of a col-lection or repository of some kind – have become everyday experiences for most people in large parts of the world

xxAI - Beyond Explainable AI

This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science

Challenges and perspectives of hate speech research

This book is the result of a conference that could not take place. It is a collection of 26 texts that address and discuss the latest developments in international hate speech research from a wide range of disciplinary perspectives. This includes case studies from Brazil, Lebanon, Poland, Nigeria, and India, theoretical introductions to the concepts of hate speech, dangerous speech, incivility, toxicity, extreme speech, and dark participation, as well as reflections on methodological challenges such as scraping, annotation, datafication, implicity, explainability, and machine learning. As such, it provides a much-needed forum for cross-national and cross-disciplinary conversations in what is currently a very vibrant field of research