While robotics has benefited from inspiration gained from biology, the opposite is not the case: there are few if any cases in which robotic models have lead to genuine insight into biology. We analyze the reasons why biorobotics has been essentially a one-way street. We argue that the development of better tools is essential for progress in this field.

Brain monitoring combined with automatic analysis of EEGs provides a clinical decision support tool that can reduce time to diagnosis and assist clinicians in real-time monitoring applications (e.g., neurological intensive care units). Clinicians have indicated that a sensitivity of 95% with specificity below 5% was the minimum requirement for clinical acceptance. In this study, a high-performance automated EEG analysis system based on principles of machine learning and big data is proposed. This hybrid architecture integrates hidden Markov models (HMMs) for sequential (...) decoding of EEG events with deep learning-based postprocessing that incorporates temporal and spatial context. These algorithms are trained and evaluated using the Temple University Hospital EEG, which is the largest publicly available corpus of clinical EEG recordings in the world. This system automatically processes EEG records and classifies three patterns of clinical interest in brain activity that might be useful in diagnosing brain disorders: (1) spike and/or sharp waves, (2) generalized periodic epileptiform discharges, (3) periodic lateralized epileptiform discharges. It also classifies three patterns used to model the background EEG activity: (1) eye movement, (2) artifacts and (3) background. Our approach delivers a sensitivity above 90% while maintaining a specificity below 5%. We also demonstrate that this system delivers a low false alarm rate, which is critical for any spike detection application. (shrink)

Recent rapid advances in Artificial Intelligence and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve (...) this, we can adapt the concept of human-in-the-loop from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop, which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

Argumentation is a very fertile area of research in Artificial Intelligence, and various semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. When these semantics make conflicting predictions, theoretical arbitration typically relies on ad hoc examples and normative intuition about what prediction ought to be the correct one. We advocate a complementary, descriptive-experimental method, based on the collection of behavioral data about the way human reasoners handle these (...) critical cases. We report two studies applying this method to the case of reinstatement (both in its simple and floating forms). Results speak for the cognitive plausibility of reinstatement and yet show that it does not yield the full expected recovery of the attacked argument. Furthermore, results show that floating reinstatement yields comparable effects to that of simple reinstatement, thus arguing in favor of preferred argumentation semantics, rather than grounded argumentation semantics. Besides their theoretical value for validating and inspiring argumentation semantics, these results have applied value for developing artificial agents meant to argue with human users. (shrink)

Cybernetics, or self-governance of animal and machine, requires the ability to sense the world and to act on it in an appropriate manner. Likewise, self-governance of a human society requires groups of people to collectively sense and act on their environment. I argue that the evolution of political systems is characterized by a series of innovations that attempt to solve two ‘scalability’ problems: scaling up a group’s ability to make sense of an increasingly complex world, and to cooperate in increasingly (...) larger groups. I then explore some recent efforts toward using the Internet and social media to provide alternative means for addressing these scalability challenges, under the banners of crowdsourcing and computer-supported argumentation. I present some lessons from those efforts about the limits of technology, and the research directions more likely to bear fruit. (shrink)

Several psychosocial models have been proposed to explain the etiology of eating disorders and obesity separately despite research suggesting they should be conceptualized within a shared theoretical framework. The objective of the current study was to test an integrated comprehensive model consisting of a host of common risk and protective factors expected to explain both eating and weight disorders simultaneously in a large school-based sample of adolescents. Data were collected from 3,043 youth from 41 schools in the Ottawa region, Canada. (...) Working with interested school staff, validated self-report scales in the form of a questionnaire booklet were administered to participating students to assess several understood risk and protective factors common to both eating disorders and obesity. Anthropometric measurements of weight and height were taken at the end of the questionnaire administration period by trained research staff. Structural equation modeling with cross-validation was used to test the hypothesized model. Findings demonstrated that dysregulated eating was associated with both eating disorder and weight status with diet culture and emotion dysregulation directly associated with some of these disordered eating patterns. It equally pointed to how lifestyle made up of high sedentary behaviors, low vigorous exercise and varied eating patterns contributed to both emotion dysregulation and poor body image which subsequently affected eating issues and weight status simultaneously, signaling the complex interplay of psychosocial factors that underlie these concerns. This study provides evidence for an integrated psychosocial model consisting of socio-environmental, psychological, and behavioral factors may best explain the complex interplay of risk and protective factors influencing eating disorders and obesity. It equally highlights understanding the direct and indirect effects of some of the most salient risk factors involved in eating and weight-related concerns, including the strong effects of diet culture and stressors such as weight-based teasing, providing interventionalists evidence of important risk factors to consider targeting in eating disorder and weight-based prevention efforts. (shrink)

This article extends the combinatorial approach to support the determination of contextuality amidst causal influences. Contextuality is an active field of study in Quantum Cognition, in systems relating to mental phenomena, such as concepts in human memory. In the cognitive field of study, a contemporary challenge facing the determination of whether a phenomenon is contextual has been the identification and management of disturbances. Whether or not said disturbances are identified through the modeling approach, constitute causal influences, or are disregardableas as (...) noise is important, as contextuality cannot be adequately determined in the presence of causal influences. To address this challenge, we first provide a formalization of necessary elements of the combinatorial approach within the language of canonical causal models. Through this formalization, we extend the combinatorial approach to support a measurement and treatment of disturbance, and offer techniques to separately distinguish noise and causal influences. Thereafter, we develop a protocol through which these elements may be represented within a cognitive experiment. As human cognition seems rife with causal influences, cognitive modelers may apply the extended combinatorial approach to practically determine the contextuality of cognitive phenomena. (shrink)

Harmony Search Algorithm (HSA) is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation when trying to solve complex problems. The algorithm relies on three operators for performing improvisation: memory consideration, pitch adjustment, and random consideration. In order to improve algorithm efficiency, we use roulette wheel and tournament selection in memory consideration, replace (...) the pitch adjustment and random consideration with a modified polynomial mutation, and enhance the obtained new harmony with a modified β-hill climbing algorithm. Such modification can help to maintain the diversity and enhance the convergence speed of the modified HS algorithm. β-hill climbing is a recently introduced local search algorithm that is able to effectively solve different optimization problems. β-hill climbing is utilized in the modified HS algorithm as a local search technique to improve the generated solution by HS. Two algorithms are proposed: the first one is called PHSβ–HC and the second one is called Imp. PHSβ–HC. The two algorithms are evaluated using 13 global optimization classical benchmark function with various ranges and complexities. The proposed algorithms are compared against five other HSA using the same test functions. Using Friedman test, the two proposed algorithms ranked 2nd (Imp. PHSβ–HC) and 3rd (PHSβ–HC). Furthermore, the two proposed algorithms are compared against four versions of particle swarm optimization (PSO). The results show that the proposed PHSβ–HC algorithm generates the best results for three test functions. In addition, the proposed Imp. PHSβ–HC algorithm is able to overcome the other algorithms for two test functions. Finally, the two proposed algorithms are compared with four variations of differential evolution (DE). The proposed PHSβ–HC algorithm produces the best results for three test functions, and the proposed Imp. PHSβ–HC algorithm outperforms the other algorithms for two test functions. In a nutshell, the two modified HSA are considered as an efficient extension to HSA which can be used to solve several optimization applications in the future. (shrink)

BackgroundPeople say it is hard to stay truly positive in Lebanon. Studies showed that 63% of Lebanese young adults are highly dissatisfied with their country. In fact, young adults are the most vulnerable population to stressors in Lebanon since their future is at stake and it is their time to shape their lives in a country that cripples them. This study aimed to assess factors associated with positivity among a sample of Lebanese university students despite the various stressors they are (...) facing on top of the economic collapse and the COVID-19 pandemic.MethodsThis cross-sectional study was conducted between November and December 2021. A total of 333 participants was recruited through convenience sampling and snowball technique through several areas in Lebanon’s governorates. A linear regression taking the positivity score as the dependent variable was adopted and all variables that showed a correlation > │0.24│ in absolute value were entered in the final model as independent.ResultsA linear regression taking the positivity score as the dependent variable showed that more positive experiences in life, more flourishing, living in rural area compared to urban, and female gender were significantly associated with more positivity.ConclusionThis study demonstrated that the youth’s positivity is strongly affected by age, gender, residency, and the country they live in that will both directly and indirectly shape their life experiences and their ability to flourish and prosper. Along with all the efforts done to help during this collapse and alleviate the stress that young adults are enduring, follow-up studies are still needed to determine accurate coping techniques that pushes these young adults to think positively in a country where negativity reigns and all else fails. (shrink)

The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in (...) other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors’ rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs. (shrink)

Over the past decade or so, a new interdisciplinary field has emerged in the ground between, on the one hand, computer science – and artificial intelligence in particular – and, on the other, the area of philosophy concentrating on the language and structure of argument. There are now hundreds of researchers worldwide who would consider themselves a part of this nascent community. Various terms have been proposed for the area, including "Computational Dialectics," "Argumentation Technology," and "Argument-based Computing," but the term (...) that has stuck is simply Argument & Computation. It encompasses several specific strands of research, such as: . the use of theories of argument, and dialectic in particular, in the design and implementation of protocols for multi-agent action and communication; . the application of theories of argument and rhetoric in natural language processing and affective computing; . the use of argument-based structures for autonomous reasoning in artificial intelligence, and in particular, for defeasible reasoning; . computer-supported collaborative argumentation – the implementation of software tools for enabling online argument in domains such as education and e-government. These strands come together to form the core of a research field that covers parts of artificial intelligence (AI), philosophy, linguistics, and cognitive science, but, increasingly, is building an identity of its own. (shrink)

Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established (...) ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results. (shrink)

This article introduces a framework for enhancing underwater images using the particle swarm optimization algorithm. A pre-processing step is introduced to reduce the absorbing and scattering effects of water before applying a filter based on this algorithm to enhance the image. The quality of enhanced images is quantitatively assessed by applying the framework on a dataset of underwater images. The obtained results show a considerable improvement.

Millions of children in conflict-affected countries are deprived of their fundamental rights to education. Using the qualitative exploratory research method, this study aims to explore ways of providing education to such children, and to identify the challenges facing their implementation. It also presents two short case studies conducted on Palestinian and Syrian refugees residing in Malaysia to explore their perceptions towards their education in their current situation and future orientation. The results show that despite the educational programmes initiated by various (...) organizations, the affected community continue to face numerous political, financial, psychological, economic, administrative, or institutional challenges. The analysis of the interviews data revealed several categories and themes, among them related to the participants’ current situation, educational needs, roles of different members of the community involved, and the challenges. The study recommends increasing efforts to meet the educational demands of the huge number of children out of schools. (shrink)

Este artículo consta de dos partes. En la primera se corrige la lectura becba por F. Codera (y seguida por autores posteriores) de un dinar acuitado en Ceuta en 543H., corrección que demuestra que se trata de usa dinar antialmohade. En la segunda parte, siguiendo el trabajo pionero de 5. Fontenla, se analiza la cuestión de si tbn Titmart acuitó moneda, proponiendo una respuesta negativa a partir de una discusión sobre el siguificado del "mabdismo" del fundador del movimiento almohade. Una (...) cuestión relacionada es la de la licitud de acuitar moneda, negada por tbn Itazm. Tras discutir basta qué punto la peculiar forma de acuitar moneda por los almohades pudo haber estado influida por las teorías monetarias de tbn Itazm, se plantea la influencia de éstas en época del califa almohade al-Mansúr, así como en época del sultán ayyubí al-Malik al-Kámil Muhanimad. (shrink)

"Featuring seventeen original essays on the ethics of Artificial Intelligence by some of the most prominent AI scientists and academic philosophers today, this volume represents the state-of-the-art thinking in this fast-growing field and highlights some of the central themes in AI and morality such as how to build ethics into AI, how to address mass unemployment as a result of automation, how to avoiding designing AI systems that perpetuate existing biases, and how to determine whether an AI is conscious. As (...) AI technologies progress, questions about the ethics of AI, in both the near-future and the long-term, become more pressing than ever. Should a self-driving car prioritize the lives of the passengers over the lives of pedestrians? Should we as a society develop autonomous weapon systems that are capable of identifying and attacking a target without human intervention? What happens when AIs become smarter and more capable than us? Could they have greater than human moral status? Can we prevent superintelligent AIs from harming us or causing our extinction? At a critical time in this fast-moving debate, thirty leading academics and researchers at the forefront of AI technology development come together to explore these existential questions, including Aaron James, Allan Dafoe, Andrea Loreggia, Andrew Critch, Azim Shariff, Carrick Flynn, Cathy O'Neil, Eliezer Yudkowsky, Eric Schwitzgebel, Frances Kamm, Francesca Rossi, Hanna Gunn, Iyad Rahwan, Jessica Taylor, JF Bonnefon, K. Brent Venable, Kate Devlin, Mara Garza, Nicholas Mattei, Nick Bostrom, Patrick LaVictoire, Peter Asaro, Peter Railton, S. Matthew Liao, Shannon Vallor, Stephen Wolfram, Steve Petersen, Stuart Russell, Susan Schneider, Wendell Wallach "--. (shrink)

This volume offers interreligious and interdisciplinary insight into the cinematic-serial and literary narration of evil. Evil is an important motif in literature, film and series. We encounter it in the most diverse forms - be it the Joker from The Dark Knight, Goethe's Mephisto or in the Shiite theatre ritual of the Taʿziya. This volume attempts a closer exploration of what we know as evil, and yet find difficult to comprehend. In addition to Christian and Islamic perspectives, philosophical and mystical (...) considerations are also addressed. Evil, its aesthetic reception and the resulting perspectives on its reality are the focus of the multidisciplinary contributions. With contributions by Prof. Dr. Thomas Jürgasch, Prof. Dr. Ahmad Milad Karimi, Prof. Dr. Walter Lesch, Prof. Dr. Konrad Paul Liessmann, Dr. Maryam Palizban, Iyad Shraim and Prof. Dr. Reinhold Zwick. (shrink)

‘배교자’에서 시작하여 ‘최초의 근대적 유대인’, 심지어 ‘시오니즘의 선구자’에 이르기까지, 유대인 스피노자는 역사 속에서 다양한 형상 아래 평가되어 왔다. 이 다양한 평가들의 바탕에는 신학정치론의 대부분을 차지하는 유대교 분석이 있다. 이 글에서 나는 스피노자의 유대교 분석의 목표가 무엇인지를 분명히하는 가운데 유대교에 대한 그의 입장을 밝히고자 한다. 스피노자는 우선 당대나 후대의 ‘반유대주의’의 모든 논거를 제시했다고 평가될 만큼, 예언, 선민사상, 의례 등 유대교의 특수성을 이루는 요소들에 대해 실로 가차없는 비판을 가하고 있다. 이 비판은 유대교를 폄하하고 기독교를 편드는 것으로, 혹은 종교 일반을 철학(이성)이나 자유주의 정치에 (...) 복속시키려는 우회적 수단으로 평가되어 왔다. 우리는 이런 평가들을 일면적이라고 보고, 보다 온전한 평가를 위해 스피노자가 신앙의 본질로 간주한 복종의 의미를 고찰한다. 이로부터 우리는 스피노자가 이성의 관점에서 인정하는 종교 고유의 적극적 역할과 더불어 유대교의 장점을 도출한다. 마지막으로 결론에서는 유대교에 대한 스피노자 진술에 나타나는 비일관성이 이 측면을 통해 볼 때 어떻게 해소되는지 보여준다. (shrink)