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The continuous development of robust machine learning algorithms in recent years has helped to improve the solutions of many studies in many fields of medicine, rapid diagnosis and detection of high-risk patients with poor prognosis as the coronavirus disease 2019 (COVID-19) spreads globally, and also early prevention of patients and optimization of medical resources. Here, we propose a fully automated machine learning system to classify the severity of COVID-19 from electrocardiogram (ECG) signals. We retrospectively collected 100 5-minute ECGs from 50 patients in two different positions, upright and supine. We processed the surface ECG to obtain QRS complexes and HRV indices for RR series, including a total of 43 features. We compared 19 machine learning classification algorithms that yielded different approaches explained in a methodology session.
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This chapter explores Quality of Work Life (QWL) in Macau. We investigate the meanings and importance of QWL and its implications in terms of happiness and business performance. Although QWL is central to people’s lives, research on this topic is still in its infancy in Macau. Our interviews revealed three salient themes of QWL: Work context, the perceived benefits and demands of the job; Organization, mainly work environment and factors within the organizational context mediating QWL; and the implications of QWL on overall living and happiness.
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In 2020, the World Health Organization declared the Coronavirus Disease 19 a global pandemic. While detecting COVID-19 is essential in controlling the disease, prognosis prediction is crucial in reducing disease complications and patient mortality. For that, standard protocols consider adopting medical imaging tools to analyze cases of pneumonia and complications. Nevertheless, some patients develop different symptoms and/or cannot be moved to a CT-Scan room. In other cases, the devices are not available. The adoption of ambulatory monitoring examinations, such as Electrocardiography (ECG), can be considered a viable tool to address the patient’s cardiovascular condition and to act as a predictor for future disease outcomes. In this investigation, ten non-linear features (Energy, Approximate Entropy, Logarithmic Entropy, Shannon Entropy, Hurst Exponent, Lyapunov Exponent, Higuchi Fractal Dimension, Katz Fractal Dimension, Correlation Dimension and Detrended Fluctuation Analysis) extracted from 2 ECG signals (collected from 2 different patient’s positions). Windows of 1 second segments in 6 ways of windowing signal analysis crops were evaluated employing statistical analysis. Three categories of outcomes are considered for the patient status: Low, Moderate, and Severe, and four combinations for classification scenarios are tested: (Low vs. Moderate, Low vs. Severe, Moderate vs. Severe) and 1 Multi-class comparison (All vs. All)). The results indicate that some statistically significant parameter distributions were found for all comparisons. (Low vs. Moderate—Approximate Entropy p-value = 0.0067 < 0.05, Low vs. Severe—Correlation Dimension p-value = 0.0087 < 0.05, Moderate vs. Severe—Correlation Dimension p-value = 0.0029 < 0.05, All vs. All—Correlation Dimension p-value = 0.0185 < 0.05. The non-linear analysis of the time-frequency representation of the ECG signal can be considered a promising tool for describing and distinguishing the COVID-19 severity activity along its different stages.
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This chapter presents a systematic review of research on human resources management (HRM) and employee relations (ER) in Angola to identify the main challenges and opportunities presented. To achieve that goal, this chapter characterises research conducted in the country, investigates its main findings, and proposes some directions for the future. Based on a bibliographic search in the EBSCO Discovery database of empirical articles about HRM and ER in Angola, we collected a sample of 28 studies published between 2009 and 2022. Most studies have focused on the development and retention of human resources. Other topics included diversity management, workplace attitudes and behaviours, scale validations, leadership and decision-making, performance appraisal, quality assessment, corporate social responsibility, and expatriates. We identified three main challenges and opportunities in HRM and ER in Angola. First, the policies and the planning, implementing, and evaluating processes of human resources development and retention strategies should be improved. Second, effective leadership and participation should be promoted while navigating the tensions between autocratic and participative leadership styles. Finally, positive ER and employee well-being should be promoted. Understanding these challenges and opportunities may contribute to the development of human capital in Angola and, ultimately, the country’s socioeconomic development.
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- Flipped classroom metodologiak eskaintzen dituen abantaila pedagogikoak (Ander Goikoetxea Pérez, Hannot Mintegia Beaskoa). - Conocimiento de la actualidad informativa a partir de la participación del alumnado que ejerce de periodista y lector crítico (María del Mar Rodríguez González, Iñigo Marauri Castillo, Guillermo Gurrutxaga Rekongo). - El papel del procesamiento dual de la información en la discriminación de noticias falsas (José Manuel Meza Cano, Cinthia Aranda-Solís, Blanca Olalde López de Arechavaleta, Santiago Palacios Navarro). - No trespassing: Arau, traba eta mugen bidezko metodologia sortzaile bat kazetaritza gradurako (Hannot Mintegia Beaskoa, Ander Goikoetxea Pérez). - Learning digital journalism: Analysing web media in comparative perspective to learn what is quality in digital communication (Javier Díaz-Noci). - El sistema híbrido vehículo de comunicación educativa (Antonio Vaquerizo Mariscal). - The pedagogical role of ethics and deontology for future professionals of communication and media: How to develop and nourish virtues (José Manuel Simões). - Desgaitasuna duten pertsonen Komunikazio ikasketetako prestakuntzari buruzko gogoetak (Terese Mendiguren, Jesús Ángel Pérez Dasilva, Koldobika Meso Ayerdi, Simón Peña, Ainara Larrondo, María Ganzabal). - Teaching Communication (and Journalism) History from Social History Theory: Some proposals (Javier Díaz-Noci).
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Environmental education (EE) has long been practiced worldwide, while Nature-based solutions (NBS) is a relatively new concept. This chapter aims to provide an overview of the EE and NBS practices in East Asia and evaluate how these two valuable applications can be used concurrently. East Asia has a well developed environmental education (EE) programs and activities, both in formal and informal education. These ranges from developing green schools and campuses to establishing policies and acts. While EE has been actively practiced for decades in the region, the adoption of NBS to address environmental and societal challenges is limited. The educational benefits and opportunities from NBS are also lacking. Although there are some projects that can be classified as NBS, like the use of wetlands for wastewater treatment, they are not clearly categorized as one. These projects are also not integrated into environmental education programs. Considering this, the region should develop innovative environmental education programs for schools, universities and communities, that integrate NBS projects. Integrating the two together will boost the effectiveness of environmental education in raising environmental awareness and changing the environmental attitude and behavior of people, which will also help address societal issues.