Social media platforms like X (formerly Twitter) generate vast volumes of user-generated content that provide real-time insights into public sentiment. Despite the widespread use of traditional machine learning methods, their limitations in capturing contextual nuances in noisy social media text remain a challenge. This study leverages the Sentiment140 dataset, comprising 1.6 million labeled tweets, and develops predictive models for binary sentiment classification using Naive Bayes, Logistic Regression, and the transformer-based BERT model. Experiments were conducted on a balanced subset of 12,000 tweets after comprehensive NLP preprocessing. Evaluation using accuracy, F1-score, and confusion matrices revealed that BERT significantly outperforms traditional models, achieving an accuracy of 89.5% and an F1-score of 0.89 by effectively modeling contextual and semantic nuances. In contrast, Naive Bayes and Logistic Regression demonstrated reasonable but consistently lower performance. To support practical deployment, we introduce SentiFeel, an interactive tool enabling real-time sentiment analysis. While resource constraints limited the dataset size and training epochs, future work will explore full corpus utilization and the inclusion of neutral sentiment classes. These findings underscore the potential of transformer models for enhanced public opinion monitoring, marketing analytics, and policy forecasting.

Background: Dysphagia is a common functional impairment in elderly populations, often leading to severe complications such as malnutrition and aspiration pneumonia, significantly increasing healthcare burdens. Currently, effective prognostic assessment tools are lacking. The absolute lymphocyte count (ALC), a biomarker reflecting immune-nutritional status, has potential predictive value in this context, though its role in dysphagia prognosis remains unclear. Methods: This retrospective cohort study included 253 dysphagic patients who received percutaneous endoscopic gastrostomy (PEG) or total parenteral nutrition (TPN) between 2014 and 2017. Five patients with missing ALC were excluded. Cox regression models assessed the association between ALC and mortality. ALC was analyzed as both continuous variable (using restriocted cubic splines) and categorical tertiles, with additional threshold analyses to assess non-linearity. Kaplan–Meier survival curves and subgroup analyses were also performed. Results: Lower ALC was associated with poorer nutritional status, higher inflammatory markers, and greater comorbidity burden. Higher ALC was independently associated with reduced mortality (adjusted HR: 0.60; 95% CI: 0.44–0.83; p = 0.002). Patients in the highest tertile had significantly better survival than those in the lowest (HR: 0.37; 95% CI: 0.23–0.59; P < 0.001). A non-linear threshold effect was identified at ALC = 1.899×10⁹/L (p for non-linearity = 0.009). Kaplan–Meier analysis confirmed improved survival with higher ALC (p < 0.0001). Subgroup analyses showed the protective effect of higher ALC was consistent across age, sex, BMI, PEG use, and comorbidity strata, with no significant interactions. Conclusions: ALC is an independent, non-linear predictor of mortality in older dysphagic patients and may aid clinical risk stratification across diverse patient subgroups.

This article presents a mathematical model designed to simulate the impact of targeted interventions aimed at preventing HIV transmission among female sex workers (FSWs) and their clients, while also analyzing their effects on the health of the general population. The compartmental model distinguishes between high-risk populations (FSWs and their clients) and low-risk populations (sexually active men and women in the general population), and links prevention efforts in high-risk groups to the evolution of the epidemic in the low-risk population. The fundamental properties of the model, such as the positivity of solutions and the boundedness of the system, have been verified, and the basic reproduction number R₀ has been calculated. Finally, the stability of the model was studied using Varga’s theorem and the Lyapunov method. Simulation results show that targeted prevention among FSWs and their clients reduces HIV incidence in the general population. This framework provides a valuable tool for guiding policymakers in the design of effective strategies to combat the epidemic, especially relevant in the context of suspension of USAID funding.

Legionnaires' disease became widely known following an outbreak of pneumonia in the United States in 1976. It is often caused by infection from artificial water sources such as cooling towers, water supply and heating systems, and recirculating hot tubs. To effectively implement infection prevention measures for Legionnaires' disease, collaboration among healthcare workers, water supply and heating system managers, building hygiene personnel, and other relevant parties is essential. It is important to note that outbreaks of Legionnaires' disease continue to occur frequently both domestically and internationally. While the number of reported cases of Legionnaires' disease in Japan has increased, the mortality rate has decreased but has stabilized at a lower level. Caution is also required as reports have been made in association with disasters and travel, in addition to artificial environmental water.

The national museum of a country, as a cultural symbol of the nation, plays an important role in cultural communication at home and abroad. This study explores the online brand identity construction of two national museums—the British Museum and the National Museum of China—to inform cultural brands of the discursive strategies to distinguish themselves from others and communicate with their audiences effectively. Informed by multimodal critical discourse analysis, this paper analyzes the websites of the two museums and their social media posts, depicts their brand identity prisms, and evaluates the effectiveness of their online communication. The results show that both museums use multimodal and hypertextual resources to create unique and congruent brand images in website design and social media interaction with their target audiences, fulfilling the institutional functions of museums as the symbol of national culture or world civilization. They express differential personalities and cultural values to reinforce their brand identities in different sociocultural and political contexts. The findings may provide insight into the use of multimodality in online communication for cultural institutions to enhance their brand images and promote cultural exchanges.

Respiratory syncytial virus (RSV) is commonly known as a pathogen of the bronchiolitis in children, however, recently also as a pathogen of the severe virus pneumonia in adults, especially elderly persons, and vaccines for elderly persons have been developed. There are two vaccines, such as the vaccines targeted for subgroup A with the adjuvant, and that targeted for both subgroup A and B but not included the adjuvant in Japan. Both vaccines are considered effective to prevent not only the incident of RSV infection/pneumonia, but also the exacerbations of the elderly persons with underlying diseases including chronic cardiopulmonary diseases.

Background: Scapulohumeral periarthritis commonly afflicts individuals in their middle age. Its etiology is multifaceted, and treatment presents a challenge with a high risk of recurrence. The main symptoms include shoulder pain and limited joint mobility, seriously affect the quality of life of the patients. Recent research indicate that acupuncture combined with bloodletting cupping can significantly improve the function of activity of shoulder joint and the pain in individuals with scapulohumeral periarthritis. However, these studies have typically been limited in scope, therefore additional research to substantiate the efficacy and safety of these intervention. Methods: To evaluate the efficacy of acupuncture combined with bloodletting cupping for treating patients with scapulohumeral periarthritis. We conducted an online search of databases in both Chinese and English, including PubMed, the Cochrane Library, Embase, Web of Science, CNKI, Wangfang Data, China Science and Technology Journal Database (VIP) and Chinese BioMedical Literature Database (CBM), to collect randomized controlled trials (RCTs) concerning the use of acupuncture combined with bloodletting cupping in scapulohumeral periarthritis patients. We also examined the references within the identified literature. Search utilised subject headings and free-text terms in both languages, without racial restrictions, for records up to April 3, 2024. Two researchers independently screened the literature, extracted data, and evaluated their qualities. RevMan 5.3 software was used for meta-analysis of the included studies. The protocol of this review was recorded in the International Platform of Registered Systematic Review and Meta-analysis Protocols (PROSPERO). Its registration number is CRD42023454614. Results: This review incorporated 22 RCTs involving a total of 1,774 patients. The results of meta-analysis showed that the clinical effective rate (RR=1.25, 95%CI [1.20, 1.30], P＜0.00001) of treating scapulohumeral periarthritis with acupuncture combined with bloodletting cupping was higher in the experimental group than in the control group. The all of Visual Analogue Scale (VAS) score (MD=-1.70, 95% CI [-2.17, -1.22], P＜0.00001). Melle score (SMD=-2.45, 95% CI [-2.55, -2.34], P=0.007]) and recurrence rate (RR=0.23, 95% CI [0.07, 0.77], P=0.02) were lower in the experimental group than in the control group with statistical significance (P<0.05). Conclusion: The acupuncture combined with bloodletting cupping for the treatment of shoulder impingement syndrome demonstrates definite efficacy and safety, with superior clinical effectiveness, pain relief, improvement in shoulder joint mobility, and reduction in recurrence compared to acupuncture alone. Therefore, it is worthy of being promoted and applied clinically.

Background: Proper umbilical cord care prevents neonatal infections and reduces neonatal mortality. Despite global recommendations for evidence-based cord care practices, traditional beliefs, and inadequate maternal knowledge often lead to unsafe practices, particularly in low-resource settings like Bangladesh. This study aimed to assess the understanding of umbilical cord care among mothers of neonates in Sherpur District, Bangladesh, and identify factors associated with knowledge levels. Methods: A descriptive cross-sectional study was conducted from July to October 2020 at Sherpur Sadar Hospital. A total of 193 mothers of neonates were recruited using a non-randomized purposive sampling method. Data was collected through a pre-tested, semi-structured, interviewer-administered questionnaire. Knowledge levels were categorized as "Good" (>6) or "Poor" (≤6) based on responses to 10 structured questions. Statistical analyses, including chi-square tests and crude odds ratios (COR), were performed to identify socio-demographic factors associated with knowledge levels. Results: Of the 193 participants, 48.7% demonstrated "Good" knowledge, while 51.3% had "Poor" knowledge. Education level (p = 0.01), occupation (p = 0.02), family type (p < 0.001), and family size (p = 0.04) were significantly associated with knowledge levels. Mothers with higher education and those from joint families exhibited better knowledge. However, 28.5% of respondents were unaware of the typical umbilical cord-shedding timeframe, and 44% could not identify signs of infection. Unsafe practices, such as using medications (14.5%) or hot compression (7.2%) for drying the cord, were reported. Conclusion: The study reveals significant gaps in maternal knowledge regarding umbilical cord care in Sherpur District, driven by socio-demographic disparities and cultural practices. Targeted health education programs, emphasizing evidence-based cord care practices and leveraging local social structures, are urgently needed to improve neonatal health outcomes in similar resource-limited settings. Future research should evaluate the effectiveness of these interventions to inform policy and practice.

With an increasing diversity of learners in today’s educational set-ups, there is an insurmountable need to cater for individual differences including the cultural variations among learners. It is therefore necessary for educators to develop culturally responsive teaching that enhances intercultural competencies of learners. As educators strive to provide inclusive learning environments in which learners from diverse cultural backgrounds learn equitably, differentiated instruction becomes a practical tool. This paper explores how differentiated instruction can support and enhance culturally responsive teaching by examining how tailored instructional approaches can bridge cultural gaps and enhance educational outcomes. The aim is to provide a comprehensive understanding of how educators can effectively integrate differentiated instructional methodologies to achieve the goals of Culturally Responsive Teaching. The study used a descriptive survey design to determine the use of differentiated instruction by junior school teachers in Kenya and a systematic review of literature, practical examples, and studies on teachers’ practices in culturally responsive teaching. The study outcomes indicated that teachers used various differentiated instructional strategies with flexible grouping being the most commonly used strategy. However, there arises a concern, that teachers were not very familiar with cultural variations of learners in their classrooms even as they developed their differentiated instructional strategies. Literature provided the principles and practices of culturally responsive teaching. The combination of these results were used to formulate a conceptual framework for Culturally Responsive Differentiated Instruction (CRDI) that provides insights for practitioners to develop and implement culturally responsive differentiated instructional strategies. The study recommends that a framework to support teachers in the implementation of inclusive and equitable curriculum through CRDI be developed, CRDI be integrated into the teaching processes and the teachers be trained on providing for learner differences through CRDI.

Background: Nursing students are exposed to significant stress due to academic and clinical demands, which can adversely affect their mental health, academic performance, and future clinical competence. Despite the global acknowledgment of this issue, limited research has been conducted to explore the prevalence and determinants of stress among nursing students in Bangladesh. Methods: This cross-sectional study was conducted from December 2023 to February 2024 among 372 nursing students enrolled in selected nursing colleges in Bangladesh. A purposive sampling technique was used, and data was collected using a semi-structured questionnaire. The questionnaire assessed socio-demographic characteristics, academic challenges, and psychological symptoms, with mental health stress measured using a Likert scale. Descriptive statistics and Chi-square tests were used to analyze the data, with a 95% confidence interval applied to all analyses. Results: The findings revealed that 31.7% of nursing students experienced severe stress, 23.9% reported moderate stress, and 16.7% had mild stress. Age, academic semester, and course load difficulties were significantly associated with stress levels (p < 0.05). Psychological symptoms such as anxiety, difficulty concentrating, and loss of interest in activities were also significantly linked to higher stress levels. Notably, students in their first semester and those reporting harder course loads were more likely to experience stress. However, gender was not significantly associated with stress levels. Conclusions: This study underscores the high prevalence of stress among nursing students in Bangladesh, driven by academic and clinical challenges and psychological symptoms. The findings highlight the need for targeted interventions, such as stress management training, enhanced mental health support, and policies to alleviate academic pressures. Future research should explore longitudinal trends in stress and evaluate the effectiveness of interventions to support a resilient nursing workforce.

The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

Background: The COVID-19 pandemic posed significant psychological challenges to frontline healthcare workers (HCWs), including anxiety, stress, and emotional strain. Aim: This study investigates the psychological impact on HCWs during the pandemic and explores coping strategies employed to manage distress. Methods: An integrative review was conducted using 24 studies published between January and December 2020. These studies were analyzed to identify common psychological outcomes and coping mechanisms among HCWs. Results: Healthcare workers experienced significant psychological distress during the COVID-19 pandemic, including anxiety, stress, insomnia, and depression. Anxiety was the most commonly reported issue, particularly among women, younger healthcare workers, and frontline staff. Stress levels were heightened by high workloads, exposure to COVID-19 patients, and inadequate protective measures. Coping strategies and self-care behaviors, such as seeking social support and utilizing institutional resources, varied in effectiveness across populations. Conclusion: The findings highlight the urgent need for targeted mental health support and resilience programs for HCWs, ensuring they are better equipped to face future health crises.

Background: Diabetes is a chronic global health issue that requires effective management to improve patient outcomes and quality of life. Nursing education plays a critical role in empowering diabetic patients with self-management skills. Aim This systematic review evaluates the impact of diabetes-focused nursing education on patient outcomes and quality of life. Methods: This study uses PRISMA guidelines and a systematic approach to identify and evaluate relevant literature. Results and Discussion: Among the 14 studies reviewed, eight emphasized self-management education, while four incorporated multidisciplinary approaches. Findings consistently demonstrated that structured nursing education programs significantly improved self-management behaviors, glycemic control, and patient knowledge. For instance, nurse-led self-management programs resulted in substantial enhancements in self-care skills and diabetes-related knowledge. Moreover, interventions that combined health education with psychological support were particularly effective, leading to better blood glucose control and increased adherence to treatment. Studies that examined quality of life reported reductions in anxiety, improved lifestyle habits, and better overall self-management. These findings highlight the multifaceted benefits of nursing education, suggesting that structured, supportive programs positively impact both clinical and psychological aspects of diabetes care. Conclusion: The review emphasizes the value of comprehensive nursing education that integrates both clinical guidance and psychological support for holistic diabetes management. Implications: Ongoing professional development and culturally sensitive education programs are recommended to address the diverse needs of diabetic patients. Future research should investigate the long-term effects of nursing education and explore innovative strategies to enhance diabetes management outcomes.

Foods rich in phytochemicals are well recognized for their role in the prevention of chronic disease development, in addition to fulfilling the nutrient requirements. However, different processing methods employed during preparation may affect their levels and functionality as they are sensitive to different processing parameters such as temperature and light. This study aimed to evaluate the effects of three common processing methods; boiling, fermentation, and drying (sun and solar drying, with and without blanching), on total phenolic content and total flavonoid content in cassava (Manhot esculenta Crantz), black jack (Bidens pilosa) and bitter lettuce leaves (Launaea cornuta) grown in Mkuranga District in the Eastern part of Tanzania. Total phenolic content and total flavonoid content were analyzed by using the spectrophotometric method with the use of Folin-Ciocalteu and Aluminum Chloride reagents, respectively. Total phenolic content ranged from 0.9±0.14 to 85.7 ± 0.56 mg Gallic Acid Equivalent (GAE)/100g and flavonoids ranged from 0.03±0.00 to 3.9±0.03 mg/100g across the treatments. Both parameters were adversely affected by fermentation and boiling, while solar and sun drying only reduced the flavonoid content. Results showed that direct solar and sun drying appear to be effective processing methods, for the retention and maintenance of total phenolic content in all samples while, none proved to be effective for flavonoid content.

This article focuses on primary liver cancer and tries to present a possible CBT-Cognitive Behavioral Therapy group intervention of 6 sessions and a follow up based on a scientific review. We present an international national data analyze of the problem and characterize it in terms of symptoms, diagnosis and treatment. From the psychological point of view our goal is to show and reflect on the connection between theory and practice in research mental health and the quality of life of people suffering from liver cancer. CBT interventions programme have shown efficacy and effectiveness on improving quality of life of patients. The expected outcomes of CBT intervention are mainly a better adaptation to cancer and a better perception on quality of live.

Baloxavir marboxil (BXM) is a novel anti-influenza agent that developed in Japan and inhibit the cap endonuclease specifically, and suggested the more clinical effectiveness in influenza. BXM reduces viral shedding more than do neuraminidase inhibitors (NAIs), and its clinical efficacy is equivalent to that of NAIs but is superior to that of NAIs in the case of type B influenza. BXM does not demonstrate any issues with safety, and treatment with BXM reduces the incidences of complicating sinusitis and bronchitis. Prophylactic administration of BXM inhibits intrafamilial transmission of influenza although low susceptible viruses with a PA/I38X substitution are isolated with a certain frequency following administration of BXM. Finally, In influenza treatment for patients aged 12−19 years and for adult outpatients, BXM can be used with the same recommendation level as oseltamivir.

Background: The titers of SARS-COV-2 antigens are frequently used as markers of viral activity and threshold for release from quarantine and treatment. COVID-19 patients were treated with several antiviral agents, including remdesivir (RDV) and ensitrelvir (ESV), which is a novel anti-SARS-CoV-2 agent recently suggested to have strong antiviral activity. Cases: We present the cases of two patients whose SARS-CoV-2 antigens were successfully decreased by oral administration of ESV after they could not be decreased by RDV drip infusion. Case 1 was a 74-year-old man who was admitted with SARS-CoV-2 infection and had been infected by the virus a month earlier and relapsed twice. He had been treated with rituximab for diffuse B cell lymphoma and not received vaccination for SARS-CoV-2. RDV was administered intravenously two weeks earlier and again 4 days earlier, but it failed to control the infection, and he was transferred to our hospital (day 1). Intravenous RDV was restarted on day 1, but viral antigens remained high until day 5. The RDV was then switched to oral ESV, and viral antigen titers were successfully decreased on days 8, 10, and 12. Case 2 was an 81-year-old man who was admitted with SARS-CoV-2 infection on day 0. He had heart failure and diabetes mellitus, and had not received vaccination for SARS-CoV-2. Intravenous RDV was started on day 1, but viral antigens were still high until day 8. He was then switched from RDV to oral ESV, and viral antigen titers were successfully decreased on day 11. Conclusions: These cases suggest that ESV might be more effective than RDV for reducing viral activity, and it is easy to administer orally.

The price of grains like maize and sorghum is subject to significant fluctuations, which can have a significant impact on a country's economy and food security. The aim of the study is to model sorghum and maize price volatility in Nigeria. The data utilized in the study was extracted from World Bank Commodity Price Data (WBCPD), 2022. The data consists of monthly prices in nominal US dollars for maize and sorghum from January 1960 – August 2022. The Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models were utilized for capturing the two-grain price volatility. Two types of conditional heteroscedastic models exist, the first group uses exact functions to control the evolution of , while the second group describes with stochastic equations. It is inferred from the result that inherent uncertainties and fluctuations existed in the prices of maize and sorghum in Nigeria which implies that the price volatility is positive and statistically significant suggesting that historical information and past shocks play a crucial role in determining the volatility observed in the grains. It is recommended that the ARCH, GARCH, EGARCH, TGARCH, PARCH, CGARCH, and IGARCH models should be employed for modeling and managing the volatility of maize and sorghum prices in Nigeria. These models have shown effectiveness in capturing different aspects of volatility, including the impact of past shocks, conditional volatility, asymmetry, and other relevant factors.

The quality of communication between healthcare providers and pregnant women is a topic of paramount importance within the realm of maternal healthcare. It is not merely an aspect of medical interaction; rather, it is the prerequisite that influences various critical dimensions of maternal care, including maternal satisfaction, health outcomes, and shared decision-making. Effective communication between healthcare providers and pregnant women is essential for optimal maternal care during pregnancy and childbirth. Maternal satisfaction is a fundamental metric of patient-centered care, and improved communication, characterized by empathy, information sharing, and active listening, cultivates trust and enhances women's contentment with their care experiences. Positive provider-patient interactions are associated with improved emotional well-being, reduced stress levels, and increased adherence to prenatal recommendations, contributing to positive health outcomes for both mother and fetus. Shared decision-making is impacted by open and transparent dialogue between healthcare providers and pregnant women. Inclusive discussions about available interventions, risks, and benefits empower women to make informed choices aligned with their preferences and values. This shared decision-making promotes autonomy, self-efficacy, and a collaborative care partnership, potentially influencing the birthing experience and postpartum adaptation. However, challenges persist in communication quality, such as variability in healthcare provider communication styles, cultural considerations, and system-level factors. Addressing these challenges through targeted interventions, training, and policy implementation can further enhance the overall maternal care experience. Further research is needed to explore innovative strategies that optimize communication and promote positive outcomes throughout the continuum of maternal care.