Browse Articles
Discover research articles across all indexed journals
Examination of hydrological variations and their effect on water shortage trends and water-energy production using convolutional neural network and ISSA
Porosity prediction from well logging data via a hybrid MABC-LSSVM model
Porosity is a key parameter for evaluating reservoir performance, but high-precision prediction is highly challenging in complex shale reservoirs due to the strong heterogeneity of the formation and the highly nonlinear relationship between logging parameters and porosity. Traditional prediction methods based on experience or physical models often have low generalization ability and accuracy. This study proposes a hybrid model (MABC-LSSVM) that combines a modified artificial bee colony (MABC) optimization algorithm with a least squares support vector machine (LSSVM) model. Inertia weights and acceleration coefficients are utilized to change the hyperparameters of the optimization model to achieve high-precision prediction of shale reservoir porosity using data-driven methods. The model inputs include compensating neutron log (CNL), density log (DEN), photoelectric absorption cross-section index (PE), and gamma ray log (GR) parameters. The proposed model is compared with the LSSVM, gradient boosting decision tree (GBDT), and ABC-LSSVM. The results show that the MABC-LSSVM model exhibits the best predictive performance. Its prediction results are highly consistent with the true porosity curve. The coefficient of determination ( R 2 ) is 0.93, significantly higher than for all comparison models. The findings demonstrate the effectiveness of combining an intelligent optimization algorithm with the LSSVM model. This approach is reliable for predicting the porosity in complex formations and performing reservoir evaluations in oil and gas exploration and development.
Brazilian adaptation and validation of the Multidimensional Measure of Parasocial Relationships (MMPR)
Abstract Social media has intensified parasocial relationships, one-sided bonds between individuals and media figures. While extensively researched in Western populations, parasocial engagement remains unexplored in culturally diverse contexts, particularly Latin America. The Multidimensional Measure of Parasocial Relationships (MMPR) is a validated tool that captures four dimensions of parasocial relationship engagement: Affective, Cognitive, Behavioral, and Decisional. Cross-cultural validation of parasocial relationship measures is essential for understanding how cultural context shape media psychology phenomena. We aimed to validate the Brazilian Portuguese adaptation of the MMPR, with four primary objectives: (1) replicate the correlated bifactor structure from previous research, (2) evaluate internal consistency and dimensional performance in the Brazilian cultural context, (3) analyze the intercorrelations among those dimensions, and (4) examine measurement invariance across gender. Brazilian participants ( N = 398; M age = 24.66, SD = 9.24) completed the 18-item Brazilian MMPR. We conducted a Confirmatory Factor Analysis (CFA) using the Weighted Least Square Mean and Variance method to test the correlated bifactor model. Internal consistency was evaluated using Cronbach’s Alpha (α) and McDonald’s Omega (ω), with Spearman correlations examining inter-dimensional relationships. Additionally, multi-group confirmatory factor analysis was conducted to assess measurement invariance across gender. CFA supported the correlated bifactor structure with acceptable fit indices ( χ² = 190.89, RMSEA = 0.08, CFI = 0.91). Standardized loadings ranged from − 0.40 to 0.79. The total scale demonstrated high internal consistency (α/ω = 0.88/0.87), while coefficients varied across dimensions (Affective: α/ω = 0.64/0.66; Cognitive: α/ω = 0.75/0.75; Behavioral: α/ω = 0.58/0.58; Decisional: α/ω = 0.82/0.81). The Decisional dimension demonstrated the strongest correlation with overall parasocial engagement (ρ = 0.86), whereas the Behavioral dimension showed the weakest (ρ = 0.65). Measurement invariance testing showed acceptable model fit for women, consistent with the full sample; however, convergence issues for the male subsample prevented further assessment of configural invariance. The Brazilian adaptation of the MMPR replicated the correlated bifactor structure and demonstrated strong overall reliability, supporting its uses as a valid measure of parasocial engagement in Brazilian populations. However, variability in the reliability of individual dimensions, particularly the strong contribution of the Decisional dimension and the weaker performance of the Behavioral dimension, suggest culturally specific patterns in parasocial engagement. Additionally, partial evidence for gender invariance suggests the scale performs more consistently among women than men, warranting further investigation. These findings highlight the need for culturally sensitive psychometric adaptations and provide a foundation for future cross-cultural research in consumer behavior, social media psychology, and therapeutic applications.
Effects of game-based learning and flipped classroom strategies on performance and reasoning in patient safety education for surgical nursing students
Introduction The present study aimed to assess the effect of game-based learning (GBL) on surgical nursing students’ performance and reasoning skills in the management of patient safety incidents in surgical units compared to the flipped classroom method. Method This quasi-experimental study was conducted at Shahid Sadoughi University of Medical Sciences in 2023–2024. One hundred surgical nursing students and surgical nurses participated in this study. In this study, a game-based learning method was implemented in the intervention group, and a flipped classroom method was used in the control group to educate the participants. The student’s reasoning skills in managing patient safety incidents were assessed by a Key Features examination. The participants’ performance was evaluated based on the WHOBARS questionnaire, which includes three sections: Sign-In, Time-Out, and Sign-out. The participants’ reasoning and performance were assessed once before the educational program and twice after the educational interventions (two weeks and two months after the educational program). Data analysis was conducted using descriptive statistics (mean and standard deviation) and Repeated Measures Analysis of Variance in SPSS software version 26. Results The intervention group achieved significantly higher reasoning skill scores than the control group at both Post-test 1 (p < 0.001) and Post-test 2 (p < 0.001). The intervention group showed superior performance compared to the control group at Post-test 1 (p = 0.04). This difference was no longer statistically significant by Post-test 2 (p = 0.63). The effect size of the intervention on reasoning skills was large (partial η² = 0.146), while its effect on performance was moderate (partial η² = 0.03). Conclusion This study demonstrates that game-based learning significantly enhances surgical nurses’ reasoning skills in managing patient safety incidents compared to traditional flipped learning approaches. While the intervention group showed notable short-term performance improvements at the two-week follow-up, these gains diminished over time, suggesting a need for reinforcement strategies to sustain competency.
First record of euglenophytes of the genus Trachelomonas in mountain lakes of Lori Province in the Republic of Armenia
User informed design of oral dispersible strips (ODS) to deliver pediatric antiretroviral therapy in Kenya: A mixed methods evaluation of product preferences and acceptability
Background Innovation to streamline the administration of pediatric antiretroviral therapy to infants and small children is urgently needed. The objective of this study was to assess user acceptability of key characteristics of prototype placebo oral dispersible strips (ODS) that would contain a pediatric HIV regimen of abacavir + lamivudine+ dolutegravir (ALD), and the extent to which they would address current barriers to ART adherence. Methods We conducted 7 focus group discussions with 64 caregivers across three hospitals; 3 FGD with 25 pediatric healthcare providers; and interviews with 25 children living with HIV (6–10 years). All FGD and interviews were audio recorded, translated, transcribed verbatim, and coded for a-priori and emergent themes. We evaluated the acceptability of key characteristics of placebo ALD-ODS (e.g.,flavor, size, dose, dissolution time, colors, and packaging) among caregivers, providers, and children using both qualitative and quantitative methods. Data were integrated and triangulated to optimize understanding of stakeholder feedback. Results Adult participants preferred the neutral “sweet” flavored ALD-ODS which was found highly acceptable among children. Caregivers advocated for a single strip per dose and single dose per day for convenience and to reduce stress of administration. In general, strip size and dissolution time was deemed acceptable, and caregivers stated that a larger size would be acceptable to accommodate a single strip per dose. Providers liked aligning the color of ALD-ODS and its packaging to different weight-based dosing to facilitate dispensing and improve accurate administration among multiple children. Most children stated that they would prefer ALD-ODS to their current regimen given the sweet taste and easy dissolution without the need for water. The competitive advantages of ALD-ODS over traditional pediatric ART options were ease of administration- particularly for infants and small children, a sweet taste, and discretion that protected privacy. Conclusion Providers and caregivers believed the ODS prototypes held great promise to ease ART administration to infants and young children which would improve medication adherence.
Delineating multiobjective ecological management zones and revealing scale effects of thresholds for factors influencing ecosystem services in Jiangxi Province
Study on repair materials and technologies for addressing crack-related damage in the Earthen City Wall of Kaifeng
Rain and snow seepage into the cracks of the soil wall is the leading cause of its surface weathering, and the key to crack repair lies in developing reasonable repair materials. Based on the carbonation principle and mineralization mechanism of quicklime, this study focuses on the cracks in the city wall of Kaifeng as the research subject. Urea urease solution, quicklime, sodium methylsilicate, styrene-acrylic emulsion, waterborne polyurethane, and soil were selected to prepare 27 groups of high-fluidity repair materials with varying proportions. The surface strength, water absorption, surface strength after water absorption, consistency and freeze-thaw cycle tests of crack repair samples were carried out to explore the repair effects of different proportions of repair materials on crack diseases. The results demonstrated that the urease urea solution, along with its mineralization reaction with quicklime and sodium methylsilicate, significantly accelerated the chemical interaction between quicklime and sodium methylsilicate, thereby enhancing the mechanical and waterproofing properties of the repair materials. The group composed of 7.5% quicklime and 7% sodium methylsilicate exhibited a total efficacy coefficient of 96.25, indicating superior mechanical strength and waterproofing performance. Among the tested waterproofing agents—sodium methylsilicate, styrene-acrylic emulsion, and waterborne polyurethane—the effectiveness was ranked as follows: waterborne polyurethane > sodium methylsilicate > styrene-acrylic emulsion. Notably, the group containing 5% sodium methylsilicate combined with 7.5% quicklime achieved the lowest water absorption rate of 3.9%. Thirty cycles of crack-filling experiments revealed that the crack resistance of the filling material surpassed that of the original sample, while maintaining excellent integrity with the earthen structure even after freeze-thaw cycles (Fig 1).
Machine learning analysis of carbon rebound effect dynamics and drivers in Chinese prefecture-level cities
Protocol for a randomized controlled trial of steroid versus methotrexate as first-line monotherapy in the management of idiopathic granulomatous mastitis
Background Idiopathic granulomatous mastitis (IGM) is a rare inflammatory breast disease affecting mainly young to middle aged women. Its aetiology is idiopathic and poorly understood, but recent evidence supports its autoimmunity pathogenesis. This pathogenesis supports the current first line treatment involving steroid monotherapy or steroid combination therapy with methotrexate, however, there is no single well-established treatment protocol that has been shown to most effectively cure the disease. Thus, this prospective, open, two arm randomised controlled trial comparing the effectiveness of steroid versus methotrexate therapy in the treatment of IGM patients was developed, with the hypothesis that methotrexate has a higher 6-months clinical complete response and radiologically complete response rate than steroid monotherapy. Methods This trial will be conducted at the Breast Care Center of the National University Hospital Singapore. To be eligible, patients must have undergone breast ultrasound, biopsy, and histologic diagnosis of IGM. Forty eligible patients between the ages 21–60 will be recruited obtaining informed consent. Baseline blood tests and imaging will be obtained during screening phase. Eligible patients after the screening phase will be randomised to either oral corticosteroid or methotrexate group. Treatment phase commences in which patients in both arms will receive either oral corticosteroid or oral methotrexate over 3 months, with follow-ups conducted at 6- and 12-months post randomisation. Safety measures including reporting of adverse events along the course of the trial will be observed. The primary outcome is 6-month complete clinical or radiological response rate, alongside time to cCR post randomization, treatment failure (TF) rate, and relapse rate (RR). Secondary outcomes include identification of drug adverse effect, frequency of surgical intervention, determination of potential biomarkers, and patient reported outcomes. Ethics and Dissemination This study is approved by the ethics committee of the National University Singapore (DSRB reference number 2023/00773). Results of this trial will be shared and presented in local and international scientific conferences, and will be published in international journals.
This ‘minor’ bird flu strain has potential to spark human pandemic
Optimized generative adversarial network for efficient resolution enhancement of 3D segmented rock tomography
Research on data transaction compliance: A collaborative and co-governance approach considering buyer erroneous feedback
Data transactions are frequently hindered by compliance risks due to participants’ lack of self-regulation and the presence weak regulatory mechanism. To address seller’s non-compliant transaction issues, this study proposes a collaborative governance model that integrates platform audits, government oversight, and buyer supervision. This model considers the heterogeneity of buyer utility and applies evolutionary game theory in a noisy feedback environment. The results indicate that accurate buyer feedback can promote compliance and reduce the supervisory burdens on platforms and governments. The reputation effect can enhance the positive behavior of sellers and platforms but has an “inverted U-shaped” relationship with government regulatory enthusiasm. The government’s subsidy and accountability should avoid a “heavy subsidy and light accountability “and the platform’s reward and punishment mechanism should steer clear of “heavy reward and heavy punishment”. Reducing the benefits of government coordination can also curb “free-riding” behaviors.
Distinguishing acute and chronic TMD in adolescent patients
MONTUR project: Dataset for understanding and forecasting tourist flows
This study presents an advanced system for monitoring and forecasting tourist flows in the Aosta Valley using distributed sensor technologies, cameras, and machine learning algorithms. This innovative system is designed to provide real-time data on arrivals and presences throughout the region, helping to manage traffic and tourism resources more effectively. The research analyzes data collected from portals equipped for traffic detection. Through a multi-phase approach, the project integrates and analyzes over 41 million vehicle passages to support informed decisions for regional economic and social policies. Furthermore, computational processes were conducted to optimize the analysis of the vehicle flow, reducing the dataset and focusing on checkpoints and vehicle categories. This type of time series revealed high stationarity, allowing the use of the eXtreme Gradient Boosting (XGBoost) algorithm for more accurate forecasts than Deep Learning models and other Machine Learning algorithms, such as those highlighted in terms of MAE and MSE. The results represent a significant step forward in managing tourist flows and improving the Aosta Valley’s operational efficiency and visitor experience.
Nardilysin in adipocyte regulates insulin sensitivity via HIF1α and PPARγ
Antibiotics utilization patterns among tertiary care hospitals in Ethiopia
Background Antibiotics are among the most used medicines globally, but antimicrobial resistance (AMR) threatens their effectiveness. The greatest mortality burden associated with AMR is in sub-Saharan Africa. However, antimicrobial prescribing practice and stewardship remain challenges in the African regions. Thus, this study aimed to evaluate and compare antibiotic utilization patterns in tertiary hospitals in Ethiopia during 2022. Method A retrospective cross-sectional study was conducted in adult wards of five public tertiary care hospitals in Ethiopia with a total of 3,283 beds. Data were retrieved from 807 randomly selected patient records using the online Kobo tool. Analysis utilized the World Health Organization (WHO) Anatomical Therapeutic Chemical (ATC) classification system and the Defined Daily Dose (DDD) (ATC/DDD) method. The result was presented using tables, charts, and text. Results A total of 2,718 drugs were prescribed to 807 patients with an average of 3.4 drugs per patient (range 1–7) during a total of 8638 bed-days. Of the total drugs prescribed, antibiotics account for 1,035 (38%), with an average of 1.3 (1,035/807) antibiotics per patient. Five hundred fifty-six (69%) patients were prescribed at least one antibiotic. The overall antibiotic consumption was 108 DDD/100 bed-days, 37.5/100 bed-days for hospital-acquired infections, and 32.8/100 bed-days for community-acquired infections. The rest were for prophylaxis purposes. The majority of antibiotics were prescribed in medical and surgical wards; 34.9/100 and 27.5/100 bed-days, respectively. The most prescribed antibiotics were ceftriaxone, metronidazole, and ceftazidime. Overall, the AWaRe “Watch” group antibiotics use occurred in 74% (73 DDD/100 bed-days) of total antibiotic consumption, which was higher than the WHO recommendation (at least 60% of total antibiotic use should be from the “Access” group, not the “Watch” group). Conclusion Antibiotic use was high in Ethiopian tertiary hospitals, with most patients receiving antibiotics, mainly from the WHO “Watch” group, contrary to guidelines. Three classes (cephalosporins, imidazoles, and glycopeptides) made up the majority of prescriptions, mostly for hospital-acquired infections. Urgent interventions and strengthened antimicrobial stewardship are needed to address inappropriate use and combat resistance.
Nanopriming with zinc oxide nanoparticle boosts seed vigour, photosynthesis, osmolytes accumulation and antioxidant activity in tomato
Evaluating phone call follow-ups in Sub-Saharan Africa: A systematic review and meta-analysis
Background Healthcare systems in Sub-Saharan Africa (SSA) face significant challenges, including limited resources, understaffing, and geographical barriers, which hinder effective healthcare delivery. Phone call follow-ups have emerged as a promising strategy to improve participant retention, enhance data accuracy, and optimize health outcomes in resource-constrained settings. Despite their growing adoption, there is limited synthesized evidence of their effectiveness across various public health contexts in SSA. Methodology This systematic review and meta-analysis included 32 studies published between 2000 and 2024, conducted in 11 SSA countries. Studies employing phone call follow-ups in community and facility-based health interventions were evaluated. Participant retention rates, reasons for loss to follow-up, and health outcomes were analyzed. Risk of bias and quality were assessed using validated tools tailored to study designs, including the Hoy et al. checklist for observational studies and the Joanna Briggs Institute (JBI) checklist for experimental studies. Statistical analysis employed a random-effects model to calculate pooled estimates and sensitivity analysis was conducted to assess the robustness of findings. Although the primary focus was on phone call follow-up interventions, a few included studies also utilized text messaging alongside phone calls. Results The pooled retention rate across studies was 89% (95% CI: 85–91), with substantial variability among countries. Retention rates were highest in Kenya (96%) and Nigeria (87%). In contrast, countries like Cameroon reported a high participant loss rate of 42%. Frequent and consistent follow-up calls were associated with improved retention rates; studies that contacted participants 4–5 times reported retention rates as high as 98%. Barriers to follow-up included network issues, outdated contact information, and participant relocations. Risk of bias assessments showed that 81% of observational studies were rated as low risk. Additionally, 69% of experimental studies were assessed as high quality. Funnel plots assessing publication bias indicated some asymmetry in studies reporting lost rates, suggesting potential bias. Conclusion Phone call follow-ups have enhanced participant retention and improved SSA health outcomes in regions with robust health infrastructure. However, variability in retention rates underscores the need for tailored strategies to address barriers like network challenges and participant mobility. Integrating innovative platforms like WhatsApp and leveraging consistent follow-up methods can enhance their scalability and impact. Policymakers should consider incorporating phone call follow-ups into routine care to optimize healthcare delivery in resource-constrained settings.