Abstract: Background: Self-care is an important concept in public health. As there is no cure for COVID-19, symptomatic treatment is encouraged. South Africans have been practicing self-care using steam inhalation as an indigenous health practice to successfully treat respiratory infections. Older adults are vulnerable to COVID-19 but are also indigenous health knowledge holders. The study examines the use of steam inhalation as self-care practice during COVID-19 by older adults. Methods: This qualitative study used secondary qualitative data from 87 interviews with 26 older adults. Ten transcripts met the inclusion criteria and were analysed thematically. Results: Four themes and eight subthemes emerged revealing older adults of 61-75 years asserting their self-care practice of steaming with herbs, encouraging their families to steam, continuing with their chronic medications and getting relieve from respiratory symptoms. They shared their believes in steam inhalation as an acceptable self-care practice to promote health and well-being. Conclusions: Older adults are indigenous knowledge holders who use steam inhalation as self-care practice to promote health and well-being. Steaming is acceptable self-care practice which should promoted.

Abstract: This paper provides a set of category-theoretic analyses of Gödel’s incompleteness theorems and Tarski’s indefinability theorem (see Appendix). We view the first-order theory as a mathematical language and introduce the notion of "language charge" as a monad within a category. For each analysis, we introduce a pair of adjunct categories: a syntactic category and a semantic category. We show that the Gödel numbering can be modeled as a pair of adjoint functors between these categories—a right functor from syntax to semantics and a left functor in the reverse direction. We prove that the Gödel numbering functor serves as a limit in a functor category. Additional analyses focus on the expressibility and definability in the twin theorems. Each of these is linked to natural transformations. In addition, we establish a formal account of "spontaneous naturality breaking" in the context of Gödel’s independent statements and Tarski’s indefinability. Finally, it touches higher order categories. By composing a syntactic category and a semantic category, we constructed a 2-Category with two layers of structures. Note that 2-category is one of the current research interests in category theory. Further, by decomposing and recomposing the syntactic category, we constructed a 3-Category.

Abstract: Aurora kinase B (AURKB) is one of the components that make up a complex called the chromosome passenger complex (CPC). The major functions of AURKB are to regulate kinetochore-microtubule attachments as well as cytokinesis. In colorectal cancer (CRC) cells treated with ETC-1922159, AURKB was found to be down regulated along with other genes. A recently developed search engine ranked combinations of AURKB-X (X, a particular gene/protein) at 2nd order level after drug administration. Some of these combinations have been tested in wet lab, however many have been pointed out by the search engine that are yet to be explored/tested. These rankings re- veal which AURKB-X combinations might be working synergistically in CRC. In this research work, I cover combinations of AURKB with ZW10 interacting kinetochore protein (ZWINT/ZWINT-1), inner centromere protein (INCENP), targeting protein for xenopus kinesin-like protein 2 (TPX2), WNT pathway components, chromatin licens- ing and DNA replication factor 1 (CDT1), G2 and S-phase expressed 1 (GTSE1), vaccinia related kinase 1 (VRK1), RecQ like helicase 4 (RECQL4), histone H3 associated protein kinase (HASPIN/GSG2), centromere protein (CENP), E2F transcription factor (E2F), cell division cycle (CDC), ubiquitin specific peptidase (USP), Nucleoporin (NUP), gem nuclear organelle associated protein (GEMIN), mitotic arrest deficient 2 like (MAD2L), homeobox (HOX), DExH-box helicase (DHX), polo like kinase (PLK), budding uninhibited by benzimidazoles (BUB), DNA topoisomerase (TOP), cyclin dependent kinase (CDK), alkB homolog lysine demethylase (ALKBH), protein arginine methyltransferase (PRMT), shugoshin (SGO), spindle and kinetochore associated com- plex subunit (SKA), growth arrest specific (GAS) and kinesin family member (KIF) family.

Abstract: Background: The COVID-19 pandemic supplied remarkable challenges for healthcare workers globally, with nurses in Albania playing an important role in response efforts. expertise their studies, challenges, and perceptions throughout this era is essential to tell future preparedness techniques and support the healthcare body of workers. Aims: This study aimed to explore demographic characteristics, stress levels, adherence to safety measures, impact on professional relationships, and overall perceptions of nurses in Albania during the COVID-19 pandemic, with a particular focus on training experiences.Methods: Population and Sample Selection: The study was conducted with the participation of 160 nurses randomly selected from hospitals and Health Centres in Tirana, Albania. Data were collected in May 2021. The sample included nurses from various services, including Infection, Oncology, Cardiothoracic Surgery, Endocrinology, Neurology, and Psychiatry, as well as primary healthcare services in Health Centres No. 10 and No. 3 in Tirana. Sample Size: After being knowledgeable approximately, the purpose of the take a look at, a pattern of 160 participating nurses filled out questionnaires at their workplaces anonymously and voluntarily.Statistical Analyses: A questionnaire with 32 questions was used for this study. After the forms were completed by 160 nurses, all data were collected into a database and then analyzed. They are expressed in numerical data but also in percentages to have a clearer picture. It is a descriptive study. Survey methodology was used. Quantitative and qualitative data were collected from the statistical survey over 11 days. Results The study conducted in May 2021 with 160 nurses revealed significant observations regarding their demographics, including gender distribution, years of experience, education levels, and age distribution. Stress levels were found to peak at the onset of the pandemic but showed a gradual decline over time. Nurses demonstrated a high level of adherence to safety measures and reported improvements in professional relationships, despite challenges related to mask-wearing. Additionally, the study highlighted nurses' high dedication to patient care and the challenges they face, including workload variability and dissatisfaction with salaries. Training experiences were also examined, revealing the need for ongoing education and skill development among nurses.Conclusion: Findings underscore the resilience, dedication, and ongoing training needs of nurses in Albania amidst the challenges posed by the COVID-19 pandemic. Despite facing significant obstacles, nurses have shown extraordinary commitment to their professional responsibilities and patient care. These observations emphasize the importance of continuous training, support, recognition, and investment in the nursing workforce to ensure an effective response to future crises.

Abstract: Sheath blight (ShB) causes severe yield loss in rice. Previously, we demonstrated that the sugar will eventually be exported transporter 11 (SWEET11) mutation significantly improves rice resistance to ShB, but causes severe defect in the seed development. The present study found that WRKY36 and PIL15 directly activate SWEET11 to negatively regulate ShB. Interestingly, WRKY36 interacted with PIL15, WRKY36 and PIL15 directly activate miR530 to negatively regulate seed development. WRKY36 interacted with a key BR signaling transcription factor WRKY53. AOS2 is an effector protein from R. Solani that interacts with WRKY53. Interestingly, AOS2 also interacts with WRKY36 and PIL15 to activate SWEET11 for sugar nutrition for R. solani. These data collectively suggest that WRKY36–PIL15 negatively regulates ShB resistance and seed development via the activation of SWEET11 and miR530, respectively. In addition, WRKY36 and PIL15 are the partners of effector protein AOS2 by which R. solani hijacks sugar nutrition from rice.

Abstract:

Injectable hydrogels have been utilized in therapies related to joints. Using biocompatible, tunable hydrogel systems, they may be applied without surgery to repair or regenerate a joint. They can incorporate therapeutic agents to deliver them immediately or locally into the affected tissues. Natural and synthetic polymers can be used to create these hydrogel systems that will imitate the extracellular matrix (ECM) in cartilage and allow controlled release of bioactive additives such as growth factors and even stem cells. Other innovative examples include the advent of an "intelligent" thermos-responsive and pH-responsive hydrogel, which dynamically changes in response to its environment to provide a targeted treatment. Preclinical trials have proven that hydrogels indeed facilitate cartilage repair under inflammatory conditions and will eventually be developed into clinical trials. Such advances, however, can be seen only at the very beginning of the road given existing roadblocks such as mechanical strength, biocompatibility, and scale-up. Future directions include bringing more multi-functionality into hydrogels, personalized therapies, and solid clinical validation to bridge the parlance gap between laboratory innovation and real-world application. This review offers deeper insights into the properties, applications, challenges, and future directions of these injectable hydrogels concerning joint repair and the transformative potential they possess in regenerative medicine.

Abstract: Mega facility management has long been inefficient due to manual, reactive approaches. This study examines the transformative integration of AI and DT technologies into Building Information Modeling (BIM) frameworks using IoT sensors for real-time data collection and predictive analytics. The study uses case studies and simulation models for dynamic data integration and scenario-based analyses. Key findings show a significant reduction in maintenance costs (25%) and energy consumption (20%), as well as increased asset utilization and operational efficiency. With an F1-score of more than 90%, the system shows excellent predictive accuracy for equipment failures and energy forecasting. Practical applications in hospitals and airports demonstrate the developed the ability of the platform to integrate IoT and BIM technologies, shifting facilities management from reactive to proactive. This paper presents a demo platform that integrates the BIM model with DT to improve the predictive maintenance as HVAC systems, equipment, security systems, etc., by recording data from different assets which help streamline asset management, enhance energy efficiency and support decision-making for the buildings’ critical systems.

Abstract: Climate change and increased demand for water are causing supply problems in the Mexico City and State of Mexico. The lack of complete and up-to-date meteorological information makes it difficult to understand and analyze climate phenomena such as droughts. Climate Engine (http://ClimateEngine.org) provides decades of climate data to analyze such changes. In this study, CHIRPS and DAYMET were used to calculate SPEI at scales of 1, 3, 6, 9, 12 and 24 months between 1981 and 2023 in the study area. The Mann-Kendall test for precipitation showed no significant change, while maximum and minimum temperatures showed a significant growth trend, which was reflected in the SPEI values. In the last 10 years, droughts have become more frequent and severe in the western part of the State of Mexico and south of Mexico City. When analyzing the last 14 years, the highest moisture values occurred in 2010, 2015 and 2018, while the most severe drought values were recorded in 2017, 2019, 2020, 2021 and 2023.

Abstract: This paper envisions an innovative framework to tackle challenges in modern education through a comprehensive Metaverse classroom model. Drawing on immersive learning theories and filling critical gaps in current virtual learning approaches, the study structured a Metaverse-driven Multi-layered Immersive Learning Environment (Meta-MILE). The Meta-MILE framework integrates essential elements such as Metaverse infrastructure, personalized interactions, social collaboration, and advanced assessment techniques. The Meta-MILE model emphasized immersive Three-Dimensional (3D) environments, Artificial Intelligence (AI)-driven personalization, gamified learning pathways, and scenario-based evaluations to boost engagement and provide customized learning experiences. In light of potential challenges, we explored issues around accessibility, infrastructure demands, and data security, suggesting practical strategies to ensure equitable access and secure interactions. Empirical findings underscored Meta-MILE’s effectiveness in enhancing engagement and skill acquisition, and the discussion addressed educational policy implications and the role of immersive classrooms in moving toward competency-based, experiential learning. Future research recommendations included longitudinal studies to validate learning outcomes and continued technological innovation to make virtual learning more accessible and secure. Ultimately, this study highlighted the transformative potential of the Metaverse classroom in creating inclusive, future-ready educational environments tailored to 21st-century needs.

Abstract: In an era of urgent need of sustainability, initiatives aimed at developing competences for sustainability need assessment tools to effectively support understanding on their impact. This work presents the creation process of a questionnaire to assess the GreenComp framework competences “Valuing Sustainability”, “Supporting fairness”, and “Promoting nature”. After a literature review on research about sustainability competencies and its data collection tools, it was developed a questionnaire using a mixed-methods study design concerning three phases. From this research resulted a versatile tool that has been specifically crafted for extensive use in the realm of sustainability education research, although easily applied in a wide range of research, educational, and training contexts.