Despite existing protocols and safety guidelines towards reducing the risk of exposure to biological hazards, the health sector still displays poor safety indices as regards biological hazards with particularly abysmal statistics in poor resource settings like Nigeria. Consequently, a robust approach to understanding and improving safety outcomes and performance needs to stem from a system-based approach that recognizes how various facets and factors of an organization can affect the general safety outcome of that organization. Thus, this research focuses on analysing and synthesizing theoretical and conceptual issues involved in the application of the safety climate model towards reducing the risk of exposure to biological hazard. Safety climate has often been tested to result in improved safety performance by impacting workers' safety perception and beahviour. This moderating role of safety climate in impacting safety outcomes positively has often been tested to be valid however, there is a need to analyse and synthesize conceptual issues guiding different methodologies aimed at evaluating safety climate. Also, this research cognizes that the concept of safety climate has sparsely been interrogated in the Nigerian healthcare setting. Against this leitmotif, this research adopts a rigorous systematic, and integrative review of literature. Since it aims to synthesize and analyse concepts and issues with safety climate evaluation, a review of published literature in the safety climate domain which serves as secondary data would aid our analysis of theories and concepts and enable us to identify not just the status of research in Nigeria, but the safety climate dimensions that have been relevant to local research and assess the theoretical framework guiding this research.

This thesis investigates the use of machine learning algorithms for wildfire prediction, aiming to improve existing fire risk assessment methods and support preventive actions. Traditional fire prediction models, which often depend solely on meteorological indices, fail to capture complex relationships between environmental, geographic, and human factors that influence wildfire occurrences. This research reviews current prediction approaches, identifies relevant datasets, and evaluates various machine learning algorithms to improve predictive accuracy. Data was collected from five meteorological stations in Cyprus, covering variables such as temperature, humidity, wind speed, and atmospheric pressure. The study included extensive data pre-processing and feature engineering to optimize the models’ performance. The final model, based on Extreme Gradient Boosting demonstrated the ability of machine learning algorithms to produce reliable fire predictions and adapt to varying environmental conditions. Challenges encountered in this study included limited data availability from forest prone areas and the unpredictable nature of human-caused fires, which are not easily modelled with environmental data alone. To improve the model’s performance, future work could focus on collecting more comprehensive data and including more relevant variables such as precipitation. Overall, this work highlights the promise of machine learning techniques in advancing wildfire prediction, ultimately contributing to a more effective fire prevention strategy.

Introduction: This master thesis analyses the main factor of musculoskeletal disorders (MSDs) in occupational of nurse and the economic impacts of them. Within the healthcare sector, work-related MSDs (WMSDs) stand as a major injury concern among professionals across the World Health Organization in 2020. According to EU-OSHA, 2020, the highest level of exposure to such injuries is found among nurse and healthcare assistants. Objectives: Taking into consideration the economic impact causes by MSDs and in order to minimize musculoskeletal disorders, we have examined the factors that leads to them. Methodology: 40 scientific articles were studied in this literature review from authorized electronic databases such as Scopus, Science Direct, Open Athens, OSHA website that focused on the MSDs and ergonomic hazard in the profession of nursing. Results: The main factors of MSDs were the gender, age, mental health, the physical work environment, work conditions, overmuch stress, psychological/organizational factors, and patient care. Furthermore, MSD is also one of the main causes of sickness absence among hospital nurses and nursing aides, although underreporting is common. To calculate the main costs of MSDs, the next factors must be estimated to direct costs, indirect costs, and intangible costs. Conclusions: Nurses are exposed to ergonomic hazards daily and leading to occupational accidents. Safety and health officers, nurses, nursing administration, and competent authorities are called upon to take measures to reduce musculoskeletal disorders and to promote a safety culture in hospital settings, implantation of health and safety strategies in order to reduce the risks and improvement of labor circumstances for their work force while further research in this topic is required for the protection, with the goal of ensuring the health and safety of nurses and all other employees.

Dr. Loucas Louca is an Associate Professor of Science Education at the European University Cyprus. His research interests focus on student abilities for inquiry in science, on modeling-based learning in scinece and on teachers’ instructional strategies for promoting student inquiry in science. He has also a longstanding interest in supporting professional teacher development in science education. He has been involved in several nationally and EU funded projects focusing on student inquiry in science, teacher professional development, professional learning communities, development of curriculum materials, promoting opportunities for gender balance in science education, STEM education, and promoting inquiry-based teaching and learning in science. He has also experiences in the development and enactment of afternoon clubs for young children in Science, and he also has designed various out-of-school STEM activities for students.

The Mediterranean and Black Sea region is an international centre of economic and commercial development and transactions. At the same time, though, it is characterised by a very volatile and dynamically changing security environment that poses severe threats and challenges on the societies and their prosperity. MEDEA aspires to contribute to the establishment of safer and more secure societies throughout the Mediterranean and Black Sea region using research and innovation as a catalyst to promote collaboration between practitioners from diverse disciplines and countries. The MEDEA project, during its 60 months of implementation aims to: Establish and Operate the MEDEA network. A multi-disciplinary network of security practitioners, with active links to policy makers and users/providers of security innovations across the M&BS countries focusing on Border Protection and other Security- and Disaster-Related tasks. All MEDEA members will engage in activities towards maintaining its sustainability and longevity even after the end of the project. Engage participants in anticipatory governance on emerging security challenges that the Mediterranean and Black Sea regions would face in the coming years (present until +10 years), based on a threefold structure that forms the backbone of the project: i) understanding the unsatisfactory state of play, ii) design the desirable future and iii) define a resilient pathway on how to achieve this. Push for the “co-creation” of security technology and capabilities innovations between practitioners and innovation. Their evaluation and prioritization will be based on a multi-criteria analysis (technology, operational, cost-benefit, etc.) and it will be linked to Human Development, Policy Making and Organizational Improvements in-terms of facilitating their use by the practitioners. Establish and annually update the Mediterranean Security Research and Innovation Agenda (MSRIA), that identifies areas where security & defence research is needed (including the research needs that are not covered by civilian research) and establishes recommendations for European Security & Defence technology investments. It will constitute the common position of the Mediterranean practitioners’ for future call for proposals from European and National funding mechanisms.

GRACE aims to equip European law enforcement agencies with advanced analytical and investigative capabilities to respond to the spread of online child sexual exploitation material. The growth in online child sexual exploitation and abuse material is a significant challenge for European law enforcement agencies. Referrals of CSEM exceed the capacity of LEAs to respond in a practical and timely manner. To safeguard victims, prosecute offenders and limit the spread of CSEM, LEAs need a next-generation AI-powered investigative platform. Background The sexual exploitation and abuse of children, the production of CSEM and subsequent distribution of this material via the internet is a shocking crime. Referrals from Online Service Providers (OSPs) are crucial to fighting CSE. Growth in the number of referrals of CSEM to LEAs is driven both by increased availability and distribution of online CSEM and improved detection and reporting processes. The extent of referrals is affecting LEAs' capacity to respond promptly, leading to an inability to prevent harm to infants and children, rescue those in immediate danger, and investigate and prosecute perpetrators. Core concepts Recent improvements to the referral process have improved LEAs capabilities. However, the sheer volume of data obtained in CSE cases stretches human resources, the limits of manual analysis beyond most LEAs reach. Given there has been a 4,000% increase in referrals since 2014, a new approach to managing, processing and analysing this content is necessary. At the heart of the project, GRACE has three core concepts. Adress the volume and analyse the content of online CSEM through technological innovations; Provide genuine operational value to LEAs in their investigation of online CSEM; and Impact at the strategic and policy level in the harmonisation of EU-wide responses to CSE.

Flipped classroom (FC) is a pedagogical approach in which the conventional notion of classroom-based learning is inverted, so that students are introduced to the learning material before class, with classroom time then being used to deepen understanding through discussion with peers and problem-solving activities facilitated by teachers. Although using FC methods has multiple benefits and is growing popularity, researchers and practitioners indicate that among impediments of widespread usage of FC methods are the additional time and technological support in relation to development of flipped learning activities. The flipped approach often involves the investment of significant time and energy on the part of instructors (e.g., recording video lectures; designing additional in-class activities). It is therefore recommended for teachers flipping their courses in team. By working in team, teachers can share their experiences of implementing flipped classrooms as well as their teaching resources The “Developing Flipped Methods for Teaching” project aims at developing all the necessary flipped learning pedagogical material (out-of-class tasks, pre-assessment tools, in-class activities) for teaching a discipline (psychology) covering a whole academic year course. The project aims at overcoming the difficulties of elaborating multiple materials for teaching with flipped classroom design. By collaboration of six education institutions an entire discipline will be covered with FC materials in seven languages (English, Romanian, Hungarian, Portuguese, Bulgarian, Slovak and Greek), tackling a gap between educational research and practice. One of the project partners, The Mihai Eminescu National Pedagogical High School (Romania) is a secondary-level educational institute. Due to the particularities of the Romanian education system they offer teacher and kindergarten teacher training program, whereby graduates receive a teacher-kindergarten teacher degree. In Romania psychology is part of the secondary-level school curricula, so high schools can also benefit from educational materials translated to Romanian. Their main role in the project is to translate the developed educational methods by the higher education institutes from the partnership, to test and adapt it to the Romanian requirements. The partnership is composed from other six Higher Education Institutes with Teacher Training Faculties, who have important experience as partners or leaders Strategic Partnership projects and educational innovation. The main intellectual output of the project are the pedagogical materials for teaching an entire course of psychology with flipped classroom (FC) methods (materials for 30 courses), available in seven languages. Each pedagogical material is composed of instructional video, out-of-class work plans (online activities) associated with Low-stakes, formative assignments as well as in-class activities and assessment tools.