Nano-integrating green and low-carbon concepts into ideological and political education in higher education institutions through K-means clustering.

Universities and colleges play a pivotal role in the pursuit of a future that is sustainable through their pedagogical efforts and the execution of state-of-the-art research endeavors aimed at mitigating the effects of climate change. Higher Education Institutions (HEIs) serve as crucial catalysts in advancing sustainable development. HEIs are increasingly embracing precise measures to reduce their carbon footprint (CF) while also educating students on global sustainability. These nano-methods provide a quantitative framework for assessing a campus's sustainability efforts in line with Green Campus (GC) initiatives to lower carbon emissions align with GC goals. This study employs K-means clustering to analyze the integration of green and low-carbon principles in higher education political and ideological studies. Its goal is to identify patterns, assess teaching effectiveness, and improve sustainability education, aligning with Green Campus initiatives to enhance institutional contributions to sustainable growth through informed pedagogical strategies. Input data includes curriculum content, teaching methods, student engagement, and institutional goals related to sustainability. Seeking to improve sustainability education align with Green Campus initiatives, higher education can strategically enhance their contributions to long-term sustainability and growth through effective pedagogical approaches. Cluster 3 has the lowest WCSS value of 1200, indicating tighter cohesion and less variability within this cluster compared to Cluster 1 (1500) and Cluster 2 (1800). Cluster 3 stands out with the highest silhouette score of 0.7, suggesting well-defined and distinct clusters, while Cluster 2 has the lowest score of 0.4, indicating some overlap or ambiguity in data points. Cluster 1 has the lowest Davies-Bouldin Index of 0.4, implying better separation between clusters compared to Cluster 2 (0.6) and Cluster 3 (0.5). Cluster 3 is well-defined and cohesive, showing strong integration of green practices. Cluster 1 displays good separation and cohesion, while Cluster 2 requires refinement due to potential overlap in sustainability integration.

Tapping the biosynthetic potential of marine Bacillus licheniformis LHG166, a prolific sulphated exopolysaccharide producer: structural insights, bio-prospecting its antioxidant, antifungal, antibacterial and anti-biofilm potency as a novel anti-infective lead.

The escalating global threat of antimicrobial resistance necessitates prospecting uncharted microbial biodiversity for novel therapeutic leads. This study mines the promising chemical richness of Bacillus licheniformis LHG166, a prolific exopolysaccharide (EPSR2-7.22 g/L). It comprised 5 different monosaccharides with 48.11% uronic acid, 17.40% sulfate groups, and 6.09% N-acetyl glucosamine residues. EPSR2 displayed potent antioxidant activity in DPPH and ABTS+, TAC and FRAP assays. Of all the fungi tested, the yeast Candida albicans displayed the highest susceptibility and antibiofilm inhibition. The fungi Aspergillus niger and Penicillium glabrum showed moderate EPSR2 susceptibility. In contrast, the fungi Mucor circinelloides and Trichoderma harzianum were resistant. Among G+ve tested bacteria, Enterococcus faecalis was the most susceptible, while Salmonella typhi was the most sensitive to G-ve pathogens. Encouragingly, EPSR2 predominantly demonstrated bactericidal effects against both bacterial classes based on MBC/MIC of either 1 or 2 superior Gentamicin. At 75% of MBC, EPSR2 displayed the highest anti-biofilm activity of 88.30% against B. subtilis, while for G-ve antibiofilm inhibition, At 75% of MBC, EPSR2 displayed the highest anti-biofilm activity of 96.63% against Escherichia coli, Even at the lowest dose of 25% MBC, EPSR2 reduced biofilm formation by 84.13% in E. coli, 61.46% in B. subtilis. The microbial metabolite EPSR2 from Bacillus licheniformis LHG166 shows promise as an eco-friendly natural antibiotic alternative for treating infections and oxidative stress.

Psychosocial Predictors of Ventilator weaning Outcomes among patients in intensive care units.

Background: Ventilator weaning is a process of discontinuing mechanical ventilation and transitioning patients to independent breathing after a period of mechanical support. Weaning outcomes among the critically ill in intensive care units (ICUs) vary significantly among individuals, leading to considerable variation in healthcare costs, length of hospital stay, morbidity and mortality. Addressing psychosocial aspects of care can improve weaning outcomes. Objective: This study aimed to determine the effect of psychosocial factors (social support, family/significant other support, ability to communicate) on weaning outcome within intensive care patients. This research hypothesized that psychological and social factors play a role in determining ventilator weaning outcomes among ICU patients. Methods: This study used a longitudinal, retrospective research design to analyze positive and negative psychosocial predictors of ventilator weaning outcomes. Data collection methods include interviews and questionnaires with patients and their families, as well as clinical data from the patient's medical records. Results: presence of anxiety, depression, and hallucinations, have a negative relationship with weaning outcomes regarding a patient's psychological characteristics (rs = -0.207, -0.163, -0.158), while communication with a patient during mechanical ventilation have a positive relationship with weaning outcomes regarding a patient's psychological characteristics (rs = 0.152; p ≤ 0.05). Moreover patients who have fear during weaning trials, feeling neglected, and feeling insecurity have a negative relationship with weaning outcomes while gaining family support during mechanical ventilation have a positive relationship with weaning outcomes (rs = 0.144; p ≤ 0.05).Significance of results, the findings suggests that psychosocial factors, such as anxiety, depression, patient's perception of their illness, motivation to wean, and family involvement can influence the success of ventilator weaning among patients in ICUs.

Utilizing nanotechnology and advanced machine learning for early detection of gastric cancer surgery.

Nanotechnology has emerged as a promising frontier in revolutionizing the early diagnosis and surgical management of gastric cancers. The primary factors influencing curative efficacy in GIC patients are drug inefficacy and high surgical and pharmacological therapy recurrence rates. Due to its unique optical features, good biocompatibility, surface effects, and small size effects, nanotechnology is a developing and advanced area of study for detecting and treating cancer. Considering the limitations of GIC MRI and endoscopy and the complexity of gastric surgery, the early diagnosis and prompt treatment of gastric illnesses by nanotechnology has been a promising development. Nanoparticles directly target tumor cells, allowing their detection and removal. It also can be engineered to carry specific payloads, such as drugs or contrast agents, and enhance the efficacy and precision of cancer treatment. In this research, the boosting technique of machine learning was utilized to capture nonlinear interactions between a large number of input variables and outputs by using XGBoost and RNN-CNN as a classification method. The research sample included 350 patients, comprising 200 males and 150 females. The patients' mean ± SD was 50.34 ± 13.04 with a mean age of 50.34 ± 13.04. High-risk behaviors (P = 0.070), age at diagnosis (P = 0.034), distant metastasis (P = 0.004), and tumor stage (P = 0.014) were shown to have a statistically significant link with GC patient survival. AUC was 93.54%, Accuracy 93.54%, F1-score 93.57%, Precision 93.65%, and Recall 93.87% when analyzing stomach pictures. Integrating nanotechnology with advanced machine learning techniques holds promise for improving the diagnosis and treatment of gastric cancer, providing new avenues for precision medicine and better patient outcomes.

Nursing Students' Knowledge, Attitude, and Practice Regarding Disaster Preparedness: A Cross-Sectional Study.

Background: Nations are considered to be within at hazard of crises, which create greater challenges for healthcare systems and healthcare workers. Nursing staff and student nurse play a critical role in responding to disasters, and having knowledge and a skill on disasters preparedness is crucial. The aim of the current study was to investigate the nursing students' knowledge, attitude, and practice regarding disaster preparedness. Methods: A cross-sectional study included a sample of 206 nursing students at College of Applied Medical Sciences in Al-Kharj, Saudi Arabia. Undergraduate students from all years were asked to complete an online questionnaire on knowledge, attitude, and practices regarding disaster preparedness. Results: The results/findings showed that more than two thirds of the participants had adequate knowledge (69%) and positive attitude (72%) regarding disaster preparedness; however, most of them had inadequate practice (84%). There were statistically significant relations between nursing students' knowledge and their GPA (p = 0.003), students' attitude and their gender (p = 0.014), and students' practice and their age (p = 0.008). Moreover, nursing students' knowledge was positively correlated with their attitude (r = 0.194). Conclusion and Recommendations: Most of participated students had adequate knowledge and a positive attitude toward disaster preparedness; most of them had inadequate practice. Continuing education and training of student nurse on disaster preparedness is critical to enhance their knowledge and practices; and to be proficient in preparation for and management of any potential disasters or risks. The findings of the current study offer data that would help in the creation of educational policies for student nurse about disaster preparedness.