This review comprehensively summarizes various preparatory methods of polymeric bone scaffolds using conventional and modern advanced methods. Compilations of the various fabrication techniques, specific composition, and the corresponding properties obtained under clearly identified conditions are presented in the commercial formulations of bone scaffolds in current orthopedic use. The gaps and unresolved questions in the existing database, efforts that should be made to address these issues, and research directions are also covered. Polymers are unique synthetic materials primarily used for bone and scaffold applications. Bone scaffolds based on acrylic polymers have been widely used in orthopedic surgery for years. Polymethyl methacrylate (PMMA) is especially known for its widespread applications in bone repair and dental fields. In addition, the PMMA polymers are suitable for carrying antibiotics and for their sustainable release at the site of infection.

Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.

Bagasse fiber from sugarcane waste is used with epoxy resin to make natural composites. The raw fibers are treated chemically to improve compatibility and adherence with the epoxy polymer. It’s anticipated that epoxy resin matrix composites reinforced with bagasse particles would work as a trustworthy replacement for conventional materials utilized in the building and automobile sectors. The amount and distribution of reinforcing particles inside the matrix are two factors that impact the composite’s strength. Furthermore, the precise proportion of reinforcing elements—roughly 20–30 weight percent—into the matrix plays a critical role in providing a noticeable boost in improving the properties of the composites. This research investigates the impact of reinforcing alkali-treated bagasse and untreated bagasse powder into an epoxy matrix on aspects of mechanical and morphological characteristics. The hand layup technique is used to create alkali-treated bagasse and untreated bagasse powder-reinforced epoxy composites. Composites are designed with six levels of reinforcement weight percentages (5%, 10%, 15%, 20%, 25%, and 30%). Microstructural analysis was performed using SEM and optical microscopes to assess the cohesion and dispersion of the reinforcing particles throughout the hybrid composites’ matrix phase. With reinforcement loading up to 20 wt%, the tensile strength, impact strength, and toughness of epoxy-alkali-treated bagasse and untreated bagasse powder-reinforced composites increased. In contrast, treated bagasse epoxy composites were superior to untreated epoxy composites in terms of efficacy. The results indicate that 20 wt% alkali bagasse powder provides better mechanical properties than other combinations.

This study focused on the topic of competences and challenges faced by university teachers in Ecuadorian higher education. The objective of this study was to identify the essential competences that university teachers must possess to confront the current challenges in the Ecuadorian educational field. A mixed research methodology was utilized. A concurrent triangulation design (DITRIAC) was applied. The data collection technique was through documentary study and focus groups. Eight experts in Ecuadorian higher education participated as key informants. Among the findings, there was a consensus on 7 key competences (disciplinary mastery, pedagogical competences, technological skills, research and continuous updating, critical thinking development, ethical and social commitment, flexibility and adaptability to change). It was concluded that Ecuadorian higher education requires teaching professionals who not only master their disciplines and possess advanced pedagogical and technological skills, but who are also leaders in research, promoters of critical thinking, and exemplify ethical commitment and adaptability.

This study presents a simple yet informative bibliometric analysis of servant leadership literature, aiming to provide a basic overview of its scholarly landscape and identify general trends. We conducted this analysis in September 2023. We focused solely on the Scopus database to understand the current state of servant leadership research. Despite extensive search efforts, we found no similar bibliometric analyses within the servant leadership domain during our study period. Therefore, our focus is to present a brief and straightforward analysis of current research in this field based on identification trends over time, connection between co-occurrence of author keywords, most and less discussed keyword, and areas of high and low concentration. Our findings show an increase in scholarly publications, reflecting a growing acknowledgment of servant leadership’s relevance in management practices. Interconnected keywords and themes such as leadership, transformational leadership, job satisfaction, work engagement, authentic leadership, ethical leadership, organizational citizenship behavior, trust, and leadership development emerge prominently. Additionally, less-discussed keywords such as accountability, core self-evaluations, educational leadership, stewardship, customer orientation, and psychological well-being provide alternative perspectives on these research results. While acknowledging limitations inherent in our bibliometric research, such as potential publication bias and language restrictions, our study offers valuable insights for scholars and practitioners interested in this area.

The quality of indoor classroom conditions influences the well-being of its occupants, students and teachers. Especially the temperature, outside acceptable limits, can increase the risk of discomfort, illness, stress behaviors and cognitive processes. Assuming the importance of this, in this quantitative observational study, we investigated the relationship between two environmental variables, temperature and humidity, and students’ basic emotions. Data were collected over four weeks in a secondary school in Spain, with environmental variables recorded every 10 minutes using a monitoring kit installed in the classroom, and students’ emotions categorized using Emotion Recognition Technology (ERT). The results suggest that high recorded temperatures and humidity levels are associated with emotional responses among students. While linear regression models indicate that temperature and humidity may influence students’ emotional experiences in the classroom, the explanatory power of these models may be limited, suggesting that other factors could contribute to the observed variability in emotions. The implications and limitations of these findings for classroom conditions and student emotional well-being are discussed. Recognizing the influence of environmental conditions and monitoring them is a step toward establishing smart classrooms.