Fast and efficient energy-oriented cell assignment in heterogeneous networks

The cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms can find optimal solutions to the cell assignment problem, but their execution time increases drastically with realistic network deployments. In turn, heuristics are able to find solutions in reasonable execution times, but they get usually stuck in local optima, thus failing to find optimal solutions. Metaheuristic approaches have been successful in finding solutions closer to the optimum one to combinatorial problems for large instances. In this paper we propose a fast and efficient heuristic that yields very competitive cell assignment solutions compared to those obtained with three of the most widely-used metaheuristics, which are known to find solutions close to the optimum due to the nature of their search space exploration. Our heuristic approach adds energy expenditure reduction in its algorithmic design. Through simulation and formal statistical analysis, the proposed scheme has been proved to produce efficient assignments in terms of the number of served users, resource allocation and energy savings, while being an order of magnitude faster than metaheuritsic-based approaches.This paper has been supported by the National Council of Research and Technology (CONACYT) through Grant FONCICYT/272278 and the ERANetLAC (Network of the European Union, Latin America, and the Caribbean Countries) Project ELAC2015/T100761. This paper is partially supported also by the ADVICE Project, TEC2015-71329 (MINECO/FEDER) and the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 777067 (NECOS Project)

E-Government and its Development in the Region: Challenges

Objective: This article, of a theoretical nature, was oriented to the contextual analysis referred to digital government, its origin, aspects, and trends; mainly, the way in which it was implemented and developed in some Latin American countries was emphasized, in addition to the reflections on the implications related to digital government in the current situation, as well as the challenges it has been facing and future challenges.   Theoretical framework: The universe of more contemporary aspects regarding electronic government was explored from the perspective of state management, as well as the foundations on which it has been consolidating and the changes it has undergone and at the same time generated in its wide spectrum of applications.   Design/Methodology/Approach: A descriptive systematic review has been implemented with the collection of various definitions, approaches and strategies in relation to electronic government. Based on the qualitative approach, the analysis and extraction of various articles with relevant information from various databases such as Scopus, Ebsco, ProQuest and Scielo was carried out; taking into account those of the last four years.   Findings: The acceptance of electronic government processes was based on the characteristics of citizens and their attitude towards technology; public bodies continue to show a series of problems, among which a marked inability to resolve the duties effectively and efficiently in charge despite having the appropriate technological tools and implements stands out. Research, practical and social implications: Future efforts that seek not only electronic government, but also a scaffolding that supports the development of administration processes through TIC and new platforms based on artificial intelligence.   Implications/Originality/Value: The real implementation of an electronic government requires, urges and forces cultural changes in society due to the use of TIC and cutting-edge technological resources

Generally Antisocial Batterers with High Neuropsychological Deficits Present Lower Treatment Compliance and Higher Recidivism

Objective: No studies have considered whether neuropsychological performance moderates the relationship between Holtzworth-Munroe and Stuart's intimate partner violence against women (IPVAW) offender typologies and treatment compliance and recidivism. Therefore, we first aimed to assess whether the typologies show differences in specific neuropsychological variables such as cognitive flexibility and emotion decoding processes. Second, we also assessed whether there are differences in treatment compliance and recidivism between the IPVAW offender typologies, based on their neuropsychological performance. Method: We administered a set of neuropsychological tests (e.g., Wisconsin card sorting test and eyes test) and self-reports to a group of IPVAW offenders (n=424). We also assessed their treatment compliance (i.e., dropout and intervention dose) and recidivism (i.e., risk of recidivism and official recidivism) after treatment. Results: Our analysis revealed that the FO offenders showed the best cognitive performance, followed by the BD group, with the GVA group showing the worst performance. Even though there were significant differences between the IPVAW offenders' typologies in their treatment compliance, and the recidivism, these differences were more pronounced when considering IPVAW offenders' typologies along with neuropsychological performance (high vs low). That is, FO with high cognitive functioning presented highest treatment compliance and lowest rates of recidivism. Conversely, GVA with low cognitive functioning presented the lowest treatment compliance and highest rate of recidivism. Conclusions: Our study highlights the need to design therapeutic programs with coadjutant neuropsychological training to attend not only to the psychological needs of IPVAW offenders, but also to the neuropsychological deficits that might facilitate lower treatment compliance and recidivism

BETWEEN BIOETHICS AND TRANSHUMANISM: REMARKABLE PERSPECTIVES AND ACUTE CHALLENGES IN TRANSIT TO A POSSIBLE DYSTOPIAN FUTURE

Transhumanism, nowadays, is being incorporated into mass culture due to the fact that an increasing number of scientists are beginning to take very seriously the wide range of possibilities it comprises. The aim of this paper is to present an analysis of the problems and dilemmas faced by bioethics and its aspects in relation to transhumanism, showing the ideas in which convergence and divergence can be seen with respect to achievements and perspectives. It also shows the analysis of the current trends from different perspectives (social, legal, technological, moral, philosophical) in which transhumanism has been positioning itself and generating new panoramas. In the same direction, an aspect derived from such development is presented: neuderlaw, regarding the scope, perspectives and contradictions resulting from the development of neurosciences and their application in the legal field

Different associations of intentional and non-intentional non-adherence behaviors with patient experience with healthcare and patient beliefs in medications: a survey of patients with chronic conditions

[Abstract] Purpose: To investigate relationships between intentional and non-intentional non-adherence behaviors and patient experience with healthcare and beliefs in medications. Patients and methods: This is a post hoc analysis of a cross-sectional anonymous survey distributed between May and September 2017 to patients with rheumatic disease, inflammatory bowel disease, HIV infection or diabetes mellitus from outpatient and primary care clinics in Spain. Patients answered five questions about non-adherence behaviors and completed questionnaires on their experience with healthcare (IEXPAC: Instrument to Evaluate the EXperience of PAtients with Chronic diseases) and beliefs about medicines (BMQ: Beliefs About Medicines Questionnaire). Results: Among 1530 respondents, 53% showed ≥1 non-adherence behavior; 35% had ≥1 non-intentional non-adherence behavior, and 33% had ≥1 intentional non-adherence behavior. Patients with HIV infection had the lowest frequency of intentional non-adherence behaviors. Non-intentional non-adherence was associated with patient beliefs (inversely with BMQ overall score) and patient experiences (inversely with IEXPAC Factor 3 sub-score, self-management). Intentional non-adherence was strongly associated with beliefs scores (directly with BMQ concerns and inversely with BMQ necessity sub-score) and inversely associated with HIV infection. Conclusion: The different associations of intentional and non-intentional non-adherence behaviors found in this study help to understand how patient experiences and beliefs influence medical non-adherence, and in the development of strategies for reducing non-adherence

Improvements in the Academic Satisfaction of University Students Through the Effective Use of Learning Management Systems and Pedagogical Innovations

The fast speed of technology has meant that the educational environment has altered characteristics of its environment, making it difficult for various colleges and professional schools to understand the need to incorporate these changes into their educational offerings. In today's interconnected world, a curriculum based on the development of professional competencies and scientific research cannot prepare oblivious students for professional success whether nationally or internationally. Students participating in diverse programs require a flexible curriculum that helps them identify and develop the knowledge, skills, and mindset they will need to succeed in the global markets in which they wish to work. To better prepare students to compete in global markets, it is recommended that a conceptual framework be built to align education with changes in technology and the global environment. The overall objective of this study was to investigate how learning management and innovation affect students' perceptions of their educational experience. Quantitative, fundamental-substantive, explanatory, cross-sectional, and non-experimental methods were used. Random sampling was chosen for practical reasons, and135 university students were selected. The findings showed very high reliability (measured by Cronbach's alpha). Also, multinomial logistic regression examined the data collected after service delivery. Since the tests showed no correlation between the variables, the null hypothesis was accepted and ruled out the significance of the impact of the variable

Machine Learning Algorithms for High Performance Modelling in Health Monitoring System Based on 5G Networks

The development of Internet of Things (IoT) applications for creating behavioural and physiological monitoring methods, such as an IoT-based student healthcare monitoring system, has been accelerated by advances in sensor technology. Today, there are an increasing number of students living alone who are dispersed across large geographic areas, therefore it is important to monitor their health and function. This research propose novel technique in high performance modelling for health monitoring system by 5G network based machine learning analysis. Here the input is collected as EEG brain waves which are monitored and collected through 5G networks. This input EEG waves has been processed and obtained as fragments and noise removal is carried out. The processed EEG wave fragments has been extracted using K-adaptive reinforcement learning. this extracted features has been classified using naïve bayes gradient feed forward neural network. The performance analysis shows comparative analysis between proposed and existing technique in terms of accuracy, precision, recall, F-1 score, RMSE and MAP. Proposed technique attained accuracy of 95%, precision of 85%, recall of 79%, F-1 measure of 68%, RMSE of 52% and MAP of 66%

Rationale and design of the SI! Program for health promotion in elementary students aged 6 to 11 years: A cluster randomized trial

Unhealthy habits in children are increasing at an alarming rate. The school provides a promising setting for effective preventive strategies to improve children's lifestyle behaviors. The SI! Program is a multilevel multicomponent school-based educational intervention aimed at all stages of compulsory education in Spain. Here, we present the design of the SI! Program for Elementary School cluster-randomized controlled trial, targeting children aged 6 to 11 years. This trial aims to study the impact of different timings and intensities of exposure to SI! Program activities on elementary school children and their immediate environment (parents/caregivers, teachers, and school). The trial includes 1770 children from 48 public elementary schools in Madrid (Spain), together with their parents and teachers. Schools and their children were randomly assigned to the intervention group (the SI! curriculum-based educational program over 3 or 6 academic years) or to the control group (standard curriculum). The primary outcomes are the change from baseline at 3-year and 6-year follow-up in children's scores for knowledge, attitudes, and habits (KAH) and health factors (blood pressure, height, weight, waist circumference, and skinfold thickness). Secondary outcomes include 3-year and 6-year changes from baseline in lifestyle questionnaire scores for parents/caregivers and teachers, and in the school environment questionnaire. The overarching goal of the SI! Program is to provide an effective and sustainable health promotion program for the adoption of healthy behaviors in children. The present trial will address the impact and the optimal timing and duration of this educational intervention in the elementary school setting. (Am Heart J 2019;210:9-17.)This study is partly funded by the Daniel & Nina Carasso Foundation and the la Caixa Foundation (LCF/PR/CE16/ 10700001). This study forms part of a project that has received funding from the European Union Horizon 2020 research and innovation programme under Marie Skłodowska- Curie grant agreement No. 707642 and from the American Heart Association under grant No. 14SFRN2049031

Healthcare experience and their relationship with demographic, disease and healthcare-related variables: a cross-sectional survey of patients with chronic diseases using the IEXPAC scale.

[Abstract] BACKGROUND: Patient experience is acknowledged as a principal aspect of quality healthcare delivery, and it has implications with regard to outcomes. OBJECTIVES: Our objective was to evaluate the healthcare experience of patients with chronic diseases to identify patient-perceived healthcare gaps and to assess the influence of demographic and healthcare-related variables on patient experiences. METHODS: A cross-sectional survey was delivered to adult patients with chronic diseases: diabetes mellitus (DM), human immunodeficiency virus (HIV) infection, inflammatory bowel disease (IBD) or rheumatic diseases. Patient experiences were assessed with the Instrument for Evaluation of the Experience of Chronic Patients (IEXPAC) questionnaire, with possible scores ranging from 0 (worst) to 10 (best experience). RESULTS: Of the 2474 patients handed the survey, 1618 returned it (response rate 65.4%). Patients identified gaps in healthcare related mainly to access to reliable information and services, interaction with other patients and continuity of healthcare after hospital discharge. The mean ± standard deviation (SD) IEXPAC score was 6.0 ± 1.9 and was higher for patients with HIV (6.6 ± 1.7) than for those with rheumatic disease (5.5 ± 2.0), IBD (5.9 ± 2.0) or DM (5.9 ± 1.9) (p < 0.001). In multivariate models, better overall IEXPAC experience was associated with follow-up by the same physician, follow-up by a nurse, receiving healthcare support from others and treatment with subcutaneous or intravenous drugs. The multivariate model that confirmed patients with HIV or DM had better experience than did those with rheumatic diseases. CONCLUSIONS: Through IEXPAC, patients identified aspects for healthcare quality improvements and circumstances associated with better experience, which may permit greater redirection of healthcare toward patient-centered goals while facilitating improvements in social care and long-term healthcare quality

Mejoras en la estimación de la frecuencia y magnitud de avenidas torrenciales mediante técnicas dendrogeomorfológicas

Para prevenir el riesgo de inundación, en el análisis científico de la peligrosidad asociada a las avenidas fluviales, clásicamente se han empleado métodos hidrológico-hidráulicos y, en menor medida, histórico-paleohidrológicos y geológico-geomorfológicos. Sin embargo, estas técnicas plantean enormes incertidumbres científicas por la disponibilidad de los datos de partida, su validez espacio-temporal, y su representatividad estadística. La Dendrogeomorfología es un conjunto de técnicas que, aprovechando fuentes de información registradas en las raíces, troncos y ramas de los árboles y arbustos ubicados en determinadas posiciones geomorfológicas (bancos de orilla, barras longitudinales, llanura de inundación, etc.), permite completar (e incluso suplir) el registro sistemático y paleohidrológico de avenidas torrenciales que han acontecido en esa corriente. En este artículo se propone investigar, se muestran los resultados-tipo y se discute sobre la aplicación y limitaciones de las fuentes de datos y los métodos científicos derivados del análisis dendrogeomorfológico. Para llevarlo a cabo, se sugiere una combinación de métodos de adquisición de datos en campo, estudios de laboratorio y análisis de datos en gabinete, con un plan de trabajo que contempla doce tareas o actividades: 1, caracterización geomorfológica; 2, caracterización florística; 3, muestreo de ejemplares: 4, adquisición de datos topográficos detallados; 5, preparación de las muestras; 6, conteo y medida de los anillos de crecimiento; 7, estudio anatómico e histológico; 8, sincronización de las series; 9, detección y datación de eventos; 10, modelación hidráulica de tramos; 11, análisis estadístico de caudales de avenida; y 12, cartografía de las áreas de peligrosidad por avenidas torrenciales y mapas de riesgo. - In order to prevent flood risks, scientific fluvial flood hazard analysis has been carried out traditionally with hydrologic and hydraulic methods, and secondarily, using palaeohydrological-historical and geological-geomorphological methods. Nonetheless, these techniques pose countless uncertainties due to the availability of the data, their spatio-temporal validity and their statistical representativeness. Dendrogeomorphology is a set of techniques that takes advantage of sources of information registered in roots, trunks and branches of trees or treelike bushes placed in certain geomorphological locations (such as banks, longitudinal bars, flood prone areas, etc.), that may be useful to complete the systematic registry or paleohydrologic data of torrential floods that have occurred in a certain stream. The aim of this paper is to research the usefulness and limitations of the data sources and methodologies derived from the dendrogeomorphological analysis. For accomplishing this objective a combination of methods is proposed, from data acquisition methods in field, laboratory studies, to data analysis. The schedule comprises twelve tasks: 1, geomorphologic characterization; 2, floristic characterization; 3, species sampling: 4, acquisition of detailed topographic data; 5, sample arrangement; 6, growth ring count and measurement; 7, hystologic and anatomic study; 8, series synchronization; 9, event detection and dating; 10, hydraulic reach modelling; 11, flow data statistical analysis; y 12, hazard and flood prone areas cartography and risk mapping