Informational Mode of the Brain Operation and Consciousness as an Informational Related System

Introduction: the objective of the investigation is to analyse the informational operating-mode of the brain and to extract conclusions on the structure of the informational system of the human body and consciousness. Analysis: the mechanisms and processes of the transmission of information in the body both by electrical and non-electrical ways are analysed in order to unify the informational concepts and to identify the specific essential requirements supporting the life. It is shown that the electrical transmission can be described by typical YES/NO (all or nothing) binary units as defined by the information science, while the inter and intra cell communication, including within the synaptic junction, by mechanisms of embodiment/disembodiment of information. The virtual received or operated information can be integrated in the cells as matter-related information, with a maximum level of integration as genetically codified info. Therefore, in terms of information, the human appears as a reactive system changing information with the environment and between inner informational subsystems which are: the centre of acquisition and storing of information (acquired data), the centre of decision and command (decision), the info-emotional system (emotions), the maintenance informational system (matter absorption/desorption/distribution), the genetic transmission system (reproduction) and info-genetic generator (genetically assisted body evolution). The dedicated areas and components of the brain are correlated with such systems and their functions are specified. Result: the corresponding cognitive centres projected into consciousness are defined and described according to their specific functions. The cognitive centres, suggestively named to appropriately include their main characteristics are detected at the conscious level respectively as: memory, decisional operation (attitude), emotional state, power/energy status and health, associativity and offspring formation, inherited predispositions, skills and mentality. The near-death and religious experiences can be explained by an Info-Connection pole. Conclusion: consciousness could be fully described and understood in informational terms

Components of palliative care interventions addressing the needs of people with dementia living in long term care: a systematic review

© The Author(s) 2020. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).Background: People with dementia requiring palliative care havemultiple needs that require complex, multicomponent interventions. Thisneed is amplified in the long term care setting. The European Associationfor Palliative Care (EAPC) White Paper offers recommendations forpalliative care in dementia and highlights domains of care integral forthis population, thus providing useful guidance to developing suchinterventions. This review maps components of palliative careinterventions for people with dementia in LTCFs, with a particular focuson shared decision-making.Peer reviewe

Addressing the Health Needs of an Aging America: New Opportunities for Evidence-Based Policy Solutions

This report systematically maps research findings to policy proposals intended to improve the health of the elderly. The study identified promising evidence-based policies, like those supporting prevention and care coordination, as well as areas where the research evidence is strong but policy activity is low, such as patient self-management and palliative care. Future work of the Stern Center will focus on these topics as well as long-term care financing, the health care workforce, and the role of family caregivers

Managing Dust on Unpaved Roads and Airports

INE/AUTC 14.1

Bringing Comfort to People with Advanced Dementia

Educational Objectives 1. Explain the purpose of looking at palliative care through a dementia lens. 2. Define dementia-capable palliative care. 3. Identify and provide examples of specific care practices that can bring comfort to people with advanced dementia. 4. Describe the process that staff use in identifying what brings comfort to individual residents

Creating Excellence in Dementia Care: A Research Review for Ireland's National Dementia Strategy

Examines the prevalence and economic and social costs of dementia; policies, practices, and data on health and social care services in community-based, acute care, and long-term residential settings; and proposed elements for a new strategy

The Informational Model of Consciousness: Mechanisms of Embodiment/Disembodiment of Information

It was shown recently that information is the central concept which it is to be considered to understand consciousness and its properties. Arguing that consciousness is a consequence of the operational activity of the informational system of the human body, it was shown that this system is composed by seven informational components, reflected in consciousness by corresponding cognitive centers. It was argued also that consciousness can be connected to the environment not only by the common senses, but also by a special connection pole to the bipolar properties of the universe, allowing to explain the associated phenomena of the near-death experiences and other special phenomena. Starting from the characteristics of this model, defined as the Informational Model of Consciousness and to complete the info-communication panorama, in this paper it is analyzed the info-connectivity of the informational system with the body itself. The brain areas where the activity of each informational component are identified, and a definition of consciousness in terms of information is proposed. As the electrical connectivity by means of the nervous system was already proved, allowing the application of the analysis and developing tools of the information science, a particular attention is paid to the non-electrical mechanisms implied in the internal communication. For this, it is shown that the key mechanisms consists in embodiment/disembodiment processes of information during the inter and intra communication of the cells. This process can be modeled also by means of, and in correlation with specific concepts of the science and technology of information, referred to network communication structures, and is represented by epigenetic mechanisms, allowing the acquired trait transmission to the offspring generation. From the perspective of the informational model of consciousness, the human organism appears therefore as a dynamic reactive informational system, actuating in correlation with matter for adaptation, by embodiment/disembodiment processes of information

Investigation of Team Formation in Dynamic Social Networks

Team Formation Problem (TFP) in Social Networks (SN) is to collect the group of individuals who match the requirements of given tasks under some constraints. It has several applications, including academic collaborations, healthcare, and human resource management. These types of problems are highly challenging because each individual has his or her own demands and objectives that might conflict with team objectives. The major contribution of this dissertation is to model a computational framework to discover teams of experts in various applications and predict the potential for collaboration in the future from a given SN. Inspired by an evolutionary search technique using a higher-order cultural evolution, a framework is proposed using Knowledge-Based Cultural Algorithms to identify teams from co-authorship and industrial settings. This model reduces the search domain while guiding the search direction by extracting situational knowledge and updating it in each evolution. Motivated from the above results, this research examines the palliative care multidisciplinary networks to identify and measure the performance of the optimal team of care providers in a highly dynamic and unbalanced SN of volunteer, community, and professional caregivers. Thereafter, a visualization framework is designed to explore and monitor the evolution in the structure of the care networks. It helps to identify isolated patients, imbalanced resource allocation, and uneven service distribution in the network. This contribution is recognized by Hospice and the Windsor Essex Compassion Care Community in partnership with the Faculty of Nursing. In each setting, several cost functions are attempted to measure the performance of the teams. To support this study, the temporal nature of two important evaluation metrics is analyzed in Dynamic Social Networks (DSN): dynamic communication cost and dynamic expertise level. Afterward, a novel generic framework for TFP is designed by incorporating essential cost functions, including the above dynamic cost functions. The Multi-Objective Cultural Algorithms (MOCA) is used for this purpose. In each generation, it keeps track of the best solutions and enhances exploration by driving mutation direction towards unexplored areas. The experimental results reach closest to the exact algorithm and outperform well-known searching methods. Subsequently, this research focuses on predicting suitable members for the teams in the future, which is typically a real-time application of Link Prediction. Learning temporal behavior of each vertex in a given DSN can be used to decide the future connections of the individual with the teams. A probability function is introduced based on the activeness of the individual. To quantify the activeness score, this study examines each vertex as to how actively it interacts with new and existing vertices in DSN. It incorporates two more objective functions: the weighted shortest distance and the weighted common neighbor index. Because it is technically a classification problem, deep learning methods have been observed as the most effective solution. The model is trained and tested with Multilayer Perceptron. The AUC achieves above 93%. Besides this, analyzing common neighbors with any two vertices, which are expected to connect, have a high impact on predicting the links. A new method is introduced that extracts subgraph of common neighbors and examines features of each vertex in the subgraph to predict the future links. The sequence of subgraphs\u27 adjacency matrices of DSN can be ordered temporally and treated as a video. It is tested with Convolutional Neural Networks and Long Short Term Memory Networks for the prediction. The obtained results are compared against heuristic and state-of-the-art methods, where the results reach above 96% of AUC. In conclusion, the knowledge-based evolutionary approach performs well in searching through SN and recommending effective teams of experts to complete given tasks successfully in terms of time and accuracy. However, it does not support the prediction problem. Deep learning methods, however, perform well in predicting the future collaboration of the teams