Search Results (173)

Tacrolimus is frequently used in immunosuppressive therapy in renal transplant patients and is characterized by high toxicity, a low therapeutic index, and great individual variability. For these reasons, correct dosing is important to ensure patient safety by reducing the incidence of adverse effects while maintaining an optimal blood level that prevents graft loss. New-onset diabetes after transplantation (NODAT) affects 15–30% of patients treated with tacrolimus, with potential differences between immediate-release (IR) and extended-release (ER) formulations. Objective: This study seeks to compare the incidence of NODAT between IR tacrolimus and ER tacrolimus formulations in renal transplant patients and correlate it with in vitro release characteristics. Methods: This is a retrospective pilot study including 66 renal transplant patients (33 IR tacrolimus, 33 ER tacrolimus) followed for 5 years. NODAT was defined according to standard criteria. In vitro dissolution testing was performed at pH values of 1.2, 4.5, and 6.8, with sampling at 15, 30, 60, 90, 120, and 360 min. Results: The obtained results do not indicate differences regarding the incidence of diabetes mellitus in patients treated with the two forms of tacrolimus. The determined NODAT incidence was 42.4% (ER tacrolimus) vs. 39.4% (IR tacrolimus), p = 0.802, and ER tacrolimus showed slower release without significant pH-dependent variations. Conclusions: No significant differences in NODAT incidence were identified between formulations. The release–clinical outcome correlation requires validation in larger multicenter studies. These results contribute to the evidence base for tacrolimus formulation selection in renal transplant patients and other associated pathologies. Full article

Background: Elite athletes are frequently subjected to high-intensity training regimens, which can result in cumulative physical stress, overtraining, and potential health risks. Monitoring autonomic responses to such load is essential for optimizing performance and preventing maladaptation. Objective: The present study aimed to assess changes in autonomic regulation immediately and two hours after training in athletes, using an integrated framework (combining time- and frequency-domain HRV indices with nonlinear and recurrence quantification analysis). It was investigated how repeated assessments over a 4-month period can reveal cumulative effects and identify athletes at risk. Special attention was paid to identifying signs of excessive fatigue, autonomic imbalance, and cardiovascular stress. Methods: Holter ECGs of 12 athletes (mean age 21 ± 2.22 years; males, athletes participating in competitions) over a 4-month period were recorded before, immediately after, and two hours after high-intensity training, with HRV calculated from 5-min segments. Metrics included HRV and recurrent quantitative analysis. Statistical comparisons were made between the pre-, post-, and recovery phases to quantify autonomic changes (repeated-measures ANOVA for comparisons across the three states, paired t-tests for direct two-state contrasts, post hoc analyses with Holm–Bonferroni corrections, and effect size estimates η²). Results: Immediately after training, significant decreases in SDNN (↓ 35%), RMSSD (↓ 40%), and pNN50 (↓ 55%), accompanied by increases in LF/HF (↑ 32%), were observed. DFA α1 and Recurrence Rate increased, indicating reduced complexity and more structured patterns of RR intervals. After two hours of recovery, partial normalization was observed; however, RMSSD (−18% vs. baseline) and HF (−21% vs. baseline) remained suppressed, suggesting incomplete recovery of parasympathetic activity. Indications of overtraining and cardiac risk were found in three athletes. Conclusion: High-intensity training in elite athletes induces pronounced acute autonomic changes and incomplete short-term recovery, potentially increasing fatigue and cardiovascular workload. Longitudinal repeated testing highlights differences between well-adapted, fatigued, and at-risk athletes. These findings highlight the need for individualized recovery strategies and ongoing monitoring to optimize adaptation and minimize the risk of overtraining and health complications. Full article

Digital fatigue is pervasive among university instructors, yet rigorous evidence on whether generative AI improves well-being is scarce. We conducted an eight-week staggered multiple-baseline AB–AB reversal with eight lecturers at a private Peruvian university. In intervention phases, participants replaced full readings with a daily ≤200-word ChatGPT summary plus three discussion questions (“content-curation sprint”). Outcomes were self-reported digital fatigue (FDU-24) and automatically logged screen time; analyses were carried out using trend-corrected Tau-U and paired-phase Cohen’s d. Across two intervention cycles, screen exposure fell by about 122 min per day (~29% of baseline) and digital fatigue scores decreased by ~22%. Effects were large and replicated (aggregate Tau-U = −0.79; d = −1.5 to −2.2). Treatment fidelity averaged 96%, and post-study technology acceptance was high. These findings provide preliminary experimental evidence that a brief, low-friction ChatGPT workflow can simultaneously reduce screen time and alleviate digital fatigue in higher-education faculty, suggesting a dual productivity-and-well-being dividend and positioning generative AI as a Job Demands–Resources “resource” rather than a stressor. Multi-site randomized trials with active controls, longer follow-up, and cost-effectiveness analyses are warranted. Practical implications for faculty development are immediate. Full article

Background: Children affected by unilateral cleft lip and palate (UCLP) represent a therapeutic challenge requiring the development of novel therapies, such as the implant of a bioengineered tissue—BIOCLEFT—or the use of nasoalveolar molding (NAM). The objective of this work was to evaluate the effects of NAM on the surgical and aesthetic outcomes of children with UCLP. Methods: A total of 36 children with UCLP treated at a craniofacial malformations management unit were evaluated, including 23 patients treated with presurgical NAM followed by palate surgical correction (NAM group) and 13 patients treated surgically without previous NAM (non-NAM group). Measurements were obtained from each patient immediately before palate surgery, including four linear measurements: nasal ala projection length (NAPL), nasal dome height (NDH), superoinferior alar groove position (S-I AGP), and nasal dome position (M-L NDP), and two angular measurements: columellar deviation (CD) and nasal bridge deviation (NBD). Results: When NAM was used, a significant improvement of the basilar view linear measurements of the patient’s nose was found, including the NAPL and NDH, and the frontal view linear measurement M-L NDP, but not S-I AGP. Significant improvements were also observed in the angular measurements of nasal symmetry CD and NBD. All these variables, except the S-I AGP, significantly correlated with the treatment group, and two variables—NAPL and CD—significantly contributed to generate a predictive model developed using binary logistic regression. Conclusions: These findings support the use of NAM to efficiently improve the nasal symmetry and the presurgical outcomes of patients with UCLP. Full article

Technological advances have enabled the development of innovative educational tools, particularly those aimed at supporting English as a Second Language (ESL) learning, with a specific focus on oral skills. However, pronunciation remains a significant challenge due to the limited availability of personalized learning opportunities that offer immediate feedback and contextualized practice. In this context, the present research proposes the design, implementation, and validation of an immersive application that leverages virtual reality (VR) and artificial intelligence (AI) to enhance English pronunciation. The proposed system integrates a 3D interactive environment developed in Unity, voice classification models trained using Teachable Machine, and real-time communication with Firebase, allowing users to practice and assess their pronunciation in a simulated library-like virtual setting. Through its integrated AI module, the application can analyze the pronunciation of each word in real time, detecting correct and incorrect utterances, and then providing immediate feedback to help users identify and correct their mistakes. The virtual environment was designed to be a welcoming and user-friendly, promoting active engagement with the learning process. The application’s distributed architecture enables automated feedback generation via data flow between the cloud-based AI, the database, and the visualization interface. Results demonstrate that using 400 samples per class and a confidence threshold of 99.99% for training the AI model effectively eliminated false positives, significantly increasing system accuracy and providing users with more reliable feedback. This directly contributes to enhanced learner autonomy and improved ESL acquisition outcomes. Furthermore, user surveys conducted to understand their perceptions of the application’s usefulness as a support tool for English learning yielded an average acceptance rate of 93%. This reflects the acceptance of these immersive technologies in educational contexts, as the combination of these technologies offers a realistic and user-friendly simulation environment, in addition to detailed word analysis, facilitating self-assessment and independent learning among students. Full article

T1D and CD commonly occur together. This association has received increasing attention from researchers and is considered in detail in this review. Since CD is over-represented in T1D, it may cause ill health with attendant complications, but because there is an effective dietary treatment, screening has been recommended in children and adults. However, there are many unknowns regarding this association, and understanding the why, when, and how with regard to screening and managing those with dual diagnoses requires thorough consideration when introducing the concept of screening to patients. It is important that patients and, where appropriate, carers are put at the heart of the decision-making process with careful discussion of the issues involved before undertaking screening that might uncover a second life-changing diagnosis, for which, without preparatory preparation and support, individuals may be ill-prepared, causing mental health issues. For some patients, an initial policy of monitoring rather than moving to immediate small bowel biopsy and exposure to a gluten-free diet (GFD) will be appropriate. The correct management of patients will ultimately improve their quality of life medically and socially. Full article

This research presents the development of a type-2 fuzzy-controlled autonomous mobile robot specifically designed for monitoring and actively maintaining indoor air quality. The core of this system is the proposed type-2 fuzzy PID dual-mode controller used for stably patrolling rooms along the walls of the environment. The design method ingeniously merges the fast error correction capability of PID control with the robust adaptability of type-2 fuzzy logic control, which utilizes interval type-2 fuzzy sets. Furthermore, the type-2 fuzzy rule table of the right wall-following controller can be extended from the first designed fuzzy left wall-following controller in a symmetrical design manner. As a result, this study eliminates the drawbacks of excessive oscillations arising from PID control and sluggish response to large initial errors in typical traditional fuzzy control. The following of the stable wall and obstacle is facilitated with ensured accuracy and easy implementation so that effective air quality monitoring and active PM2.5 filtering are achieved in a movable manner. Furthermore, the augmented reality (AR) interface overlays real-time PM2.5 data directly onto a user’s visual field, enhancing situational awareness and enabling an immediate and intuitive assessment of air quality. As this type of control is different from that used in traditional fixed sensor networks, both broader area coverage and efficient air filtering are achieved. Finally, the experimental results demonstrate the controller’s superior performance and its potential to significantly improve indoor air quality. Full article

This study investigates the immediate and delayed effects of processing instruction (PI), which is an input-based pedagogical intervention, and its key component, structured input (SI), which aims to foster making correct form-meaning connections, on the acquisition of the English passive structure. Thirty-four ESL learners, who had not received any formal instruction on the target structure, were randomly assigned to either a PI group (n = 12), SI group (n = 12), or Control group (n = 10). Both the PI and SI groups received 1 hour of computer-based instruction, while the control group did not receive any instruction. A self-paced reading test was used to measure the accuracy of response and response time in selecting the correct pictures. The test was administered before instruction, immediately after instruction, and 3 weeks later. The results indicated that both the PI and SI groups improved significantly in accuracy on both posttests, while the control group did not. No significant gains, however, were found in response time for any of the groups on any of the posttests, although the PI group was comparatively faster than the SI group on the immediate posttest. Full article

There is a need to evaluate Sentinel-2 (S2) fire severity spectral indices (SFSIs) for predicting vegetation and soil burn severity for a variety of ecosystems. We evaluated the performance of 26 SFSIs across three fires in seasonally dry oak–pine forests in central-western Mexico. The SFSIs were derived from composites of S2 multispectral images obtained with Google Earth Engine (GEE), processed using different techniques, for periods of 30, 60 and 90 days. Field verification was conducted through stratified random sampling by severity class on 100 circular plots of 707 m², where immediate post-fire effects were evaluated for five strata, including the canopy scorch in overstory (OCS)—divided in canopy (CCS) and subcanopy (SCS)—understory (UCS) and soil burn severity (SBS). Best fits were obtained with relative, phenologically corrected indices of 60–90 days. For canopy scorch percentage prediction, the indices RBR3c and RBR5n, using NIR (bands 8 and 8a) and SWIR (band 12), provided the best accuracy (R² = 0.82). SBS could be best mapped from RBR1c (using 11 and 12 bands) with relatively acceptable precision (R² = 0.62). Our results support the feasibility to separately map OCS and SBS from S2, in relatively open oak–pine seasonally dry forests, potentially supporting post-fire management planning. Full article

This study examines stock market reactions to female board appointments among 34 publicly listed companies in Saudi Arabia between 2021 and 2024. We employ a multi-method approach covering 36 announcements. Our primary methodology is an event study, which we complement with two distinct robustness checks: the Local Projections (LP) method to capture the evolving nature of market responses and the Quantile-on-Quantile analysis to investigate how market conditions interact with the three phases surrounding the event—the anticipation period before the appointment, the appointment event itself, and the post-appointment adjustment period. This comprehensive methodological framework allows us to capture the immediate market response to appointment announcements and the longer-term implications for firm performance while accounting for various econometric challenges inherent in financial market data. Our findings reveal a negative market reaction that gradually intensifies, becoming marginally significant by the tenth trading day. This pattern suggests that investors in the Saudi market may initially view female board appointments with skepticism, potentially reflecting uncertainty about the impact of gender diversity in a traditionally male-dominated business environment. Furthermore, the evolution from 2021 to 2024 suggests a market that is progressively developing more sophisticated frameworks for evaluating female board appointments. Rather than exhibiting a monotonic trend toward either increasingly positive or negative reactions, the market appears to be engaging in a learning process characterized by periodic reassessments. Moreover, our results indicate that while the immediate event and anticipation phases yield mixed impacts across the return distribution, the adjustment period exhibits a robust and significantly negative interaction with market returns. These findings suggest that market overreactions, particularly during bullish periods, contribute to a pronounced correction effect following female board appointments. Full article

Non-conformities—deviations from established standards or procedures—can significantly impact product quality and process performance. Although various tools and methodologies exist, current research lacks an integrated, deferred, and corrective approach to non-conformance management that bridges day-to-day operations with systematic quality control. The proposed tool aims to address this gap by providing a practical framework that combines batch data processing using the “Daily Challenge” tool with structured problem solving and corrective strategies. It serves as a comprehensive decision-making tool for systematically managing deviations. The methodology begins with identifying non-conformities through data collection and direct observation, followed by focused reporting and active discussion during departmental meetings. Issues are then categorized based on their frequency, operational impact, and resource requirements to determine the appropriate resolution path—whether through immediate correction or detailed analysis using structured tools such as the “Daily Challenge” sheet. It integrates well-established methodologies such as 5M and PDCA into a structured, daily workflow for resolving non-conformities. Implemented solutions are evaluated for effectiveness with ongoing monitoring to ensure continuous improvement. A key feature of this system is the use of the “Daily Challenge” form, which facilitates documentation, accountability, and knowledge retention—helping to reduce the recurrence of similar situations. The case studies illustrate the methodology through two examples: a labeling issue involving the omission of quantity information on product labels due to operator oversight and the management of production downtime caused by equipment and sensor failures. Although a standard existed, the errors revealed the need for reinforced procedures. Corrective actions included revising procedures, retraining personnel, repairing and recalibrating equipment, enhancing maintenance protocols, and using visual documentation to enhance process understanding. The “Daily Challenge” tool provides a replicable framework for managing non-conformities across various industries, aligning operational practices with quality assurance goals. By integrating structured analysis, clear documentation, and corrective strategies, it fosters a culture of continuous improvement and compliance. Full article

Using time-varying Granger causality, Neural Networks Nonlinear VAR, and Wavelet Coherence analysis, we evidence the unstable effect of the money market rate on industrial production and consumer price index in Tunisia. The effect is asymmetric and depends on geopolitical risk (low versus high). We show that global geopolitical risk has both detriments and benefits sides—it is a threat and an opportunity for monetary policy transmission mechanisms. Interacted local projections (LPs) reveal short–medium-term volatility or dampening effects, suggesting that geopolitical uncertainty might weaken the immediate impact of monetary policy on output and prices. In uncertain environments (e.g., high geopolitical risk), economic agents—households and businesses—may adopt a wait-and-see approach. They delay consumption and investment decisions, which could initially mute the impact of monetary policy. Agents may delay their responses until they gain more information about geopolitical developments. Once clarity emerges, they may adjust their behavior, aligning with the long-run effects observed in the Vector Error Correction Model (VECM). Furthermore, we identify an exacerbating investor sentiment following tightening monetary policy, during global and local geopolitical episodes. The impact is even more pronounced under conditions of high domestic weakness. Evidence is extracted through a novel composite index that we construct using Principal Component Analysis (PCA). Our results have implications for the Central Bank’s monetary policy conduct and communication practices. Full article

Wearable devices are gaining prominence in a variety of applications, including athletic and physical activity monitoring. Their effectiveness often relies on the ability to deliver instantaneous feedback, enabling timely responses and supporting their integration into fast-paced, interactive contexts. Based on these aspects, this paper proposes a wearable system that collects accelerometer and gyroscope data using the MPU6050 sensor from three points on a human arm. The collected data are compared to a predefined set of values using Dynamic Time Warping. Each wearable device provides live feedback via a vibration motor if a stroke deviates from the desired motion. The entire system enables swimming coaches to monitor individual strokes in real time using Wi-Fi connectivity while also allowing athletes to receive immediate feedback when their strokes are executed incorrectly. This system aids in identifying improper swimming techniques and enables faster correction, ultimately improving performance. Experiments will be performed in water environment supervised by a specialized swimming coach. Full article

Objectives: Low tidal volume ventilation (LTVV) is a ventilatory strategy with the advantages of minimizing diaphragm movements and reducing hypercapnia and barotrauma risks. This preliminary study aims to report on the safety and effectiveness of LTVV applied during percutaneous US-guided liver ablations of focal malignancies. Methods: Patients affected by focal liver malignancies treated with percutaneous microwaves ablation were retrospectively included in this single-center analysis. Arterial gas analysis was performed immediately before and after ablation to evaluate the arterial pH, partial pressure of carbon dioxide (pCO₂), partial pressure of oxygen (pO₂), and plasma lactate levels. The primary endpoint of this study was to evaluate the safety and efficacy of LTVV during percutaneous liver cancer ablation. The secondary endpoint was to assess the procedural technical success in terms of correct needle probe targeting without the need for repositioning. Results: Ten patients affected by a single liver lesion had been analyzed. The ASA score was three in all patients, with three patients also suffering from COPD. The procedural technical success was 100%: ablations were performed with a single liver puncture without the need for changing access or repositioning the needle. No variations in post-ablation arterial gas analysis requiring anesthesiological management remodulation occurred. Lactate levels remained stable and hemodynamic balance was preserved during all procedures. No switch to standard volume ventilation was required. Conclusions: In this preliminary study, LTVV was a safe and effective anesthesiological protocol in patients treated with percutaneous ablations of liver malignancies, offering an ideal balance between patient safety and percutaneous needle probe positioning precision. Larger prospective studies are needed to confirm these findings. Full article

This study investigated the dynamic factors influencing food security in Saudi Arabia, a critical concern for the nation’s stability and development. The purpose of this research was to analyze the impact of several key determinants on the Food Security Index and to distinguish between their short-term and long-term effects, thereby providing evidence-based policy recommendations. Using annual time-series data spanning 1990 to 2023, the research employs the Autoregressive Distributed Lag (ARDL) and Vector Error Correction Model (VECM) methods. We specifically examined the roles of agricultural GDP contribution, agricultural insurance coverage, food price stability, government policies related to agriculture, climate change impacts, agricultural productivity, and technology adoption. Short-run estimates reveal that agricultural GDP contribution, government policies, and agricultural productivity express a significant positive influence on food security. Importantly, climate change showed a counterintuitive positive association in the short term, potentially indicating immediate adaptive responses. Conversely, food price stability exhibited an unexpected negative association, which may indicate that the index captures high price levels rather than just volatility. The long-run analysis highlights the crucial importance of sustained factors for food security. Agricultural GDP contribution, agricultural insurance coverage, and agricultural productivity are identified as having significant positive impacts over the long term. In contrast, climate change demonstrates a significant negative long-run impact, underscoring its detrimental effect over time. Government policies, while impactful in the short term, become statistically insignificant in the long run, suggesting that sustained structural factors become dominant. Granger causality tests indicate short-term causal relationships flowing from climate change (positively), agricultural GDP contribution, government policies, and agricultural productivity towards food security. The significant error correction term confirms the existence of a stable long-run equilibrium relationship among the variables. On the basis of these findings, the study concludes that strengthening food security in Saudi Arabia requires a multifaceted approach. Short-term efforts should focus on enhancing agricultural productivity and implementing targeted measures to mitigate immediate climate impacts and refine food price stabilization strategies. For long-term resilience, priorities must include expanding agricultural insurance coverage, investing in sustainable agricultural practices, and continuing to boost agricultural productivity. The study contributes to the literature by providing a comprehensive dynamic analysis of food security determinants in Saudi Arabia using robust time-series methods, offering specific insights into the varying influences of economic, policy, environmental, and agricultural factors across different time horizons. Further research is recommended to explore the specific mechanisms behind the observed short-term relationship with climate change and optimize food price policies. Full article