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This work was conducted to understand the covalent interactions of whey protein isolate (WPI) with some phytochemical compounds including chlorogenic acid (CQA), rosmarinic acid (RA) and quercetin (Q) (0.3 mmol/g protein). The influences of such interactions on the chemical, structural and functional properties of the WPI were studied. The changes in protein–phenolic conjugates properties were characterized by the change in free amino and thiol groups, tryptophan content, UV–Vis scan and particle size. Moreover, the electrospray ionization-quadrupole-time of flight (ESI-Q-TOF) mass spectrometry, RP-HPLC, TEAC and DPPH assays were also used to evaluate these changes. In addition, the change in isoelectric points of modified proteins was examined using the change in the zeta potential at different pH values. The results showed that these interactions caused a decrease in both free amino and thiol groups and tryptophan content, where the addition of CQA, RA and Q led to decrease in the thiol groups content by about 47.6, 96.1 and 65.8%, respectively. While, the content of tryptophan residue decreased from 29.9 ± 0.3 (nmol/mg protein, for WPI control) to 19.3 ± 0.1, 7.9 ± 0.1 and 17.2 ± 1.0 after interacting with CQA, RA and Q, respectively. The structure of WPI- phenolic conjugates altered compared to the structure of WPI control. The modified proteins displayed very slight shifts in the isoelectric points compared to the unmodified ones. Moreover, these interactions increased the antioxidant capacity of proteins about 2.7 to 3.4 folds compared to WPI control. Therefore, it is strongly recommended to use the modified WPI for preparing functional food products with a high antioxidative power.

MyDispense is one of the virtual simulations that has already been established as a suitable alternative for live experiential education in the pharmacy curriculum. However, there are no structured validated questionnaires available to assess the students' perception while integrating MyDispense with pharmacy practice experiential education. Therefore, the present study aimed to validate a structured questionnaire and use the questionnaire to assess the student perception of various pharmacy practice experiential education. Content and construct validity procedure was used to validate the questionnaire. Two hundred students consented to participate in validating the questionnaire. The validated questionnaire assessed the students' perception of integrating MyDispense with Introductory Pharmacy Practice Experience 2 (IPPE2) and Advanced Pharmacy Practice Experience (APPE) courses. The questionnaire was structured with four domains which were: exercise, instructor, technical, and communication. Each domain carried five items; therefore, the whole questionnaire had 20 items that succeeded in content validity. In the survey, 121 fourth-year and 117 fifth-year Pharm.D. students volunteered to convey their perception of integrating MyDispense with IPPE 2 and APPE, respectively. The survey was conducted before and after the MyDispense exam in both the courses. The Cronbach's α and McDonald's ω coefficients were > 0.8 in all four domains, indicating that the items related to the four domains have good internal consistency. In Exploratory Factor Analysis (EFA), two items were found to cross-load in the exercise domain and removed. Therefore, the EFA proposes 18 items for the confirmatory factor analysis (CFA). In CFA, five fit indices were found to be satisfactory, and this indicates construct was good enough to assess the student perception. In IPPE 2, the pre-test response, the students had significantly higher satisfaction (p < 0.05) with all five items related to the technical domain. In APPE, the students had a significantly (p < 0.05) higher perception of all the items related to the exercise and technical domain in the pre-test compared to the post-test. Therefore, the student's pre-test feedback allowed the instructor to identify and make the necessary corrections in the exercises to improve the quality exercises. This study provides a validated 18-item questionnaire to assess the student perception of integrating MyDispense in experiential education. The integration of MyDispense in experiential education needs to be done carefully by assessing student perception.

Medication adherence is an essential aspect of healthcare for patients and is important for achieving medical objectives. However, the lack of standard techniques for measuring adherence is a global concern, making it challenging to accurately monitor and measure patient medication regimens. The use of sensor technology for medication adherence monitoring has received much attention lately since it makes it possible to continuously observe patients’ medication adherence behavior. Sensor devices or smart wearables utilize state-of-the-art machine learning (ML) methods to analyze intricate data patterns and provide predictions accurately. The key aim of this work is to develop a sensor-based hand gesture recognition model to predict medication activities. In this research, a smart sensor device-based hand gesture prediction model is developed to recognize medication intake activities. The device includes a tri-axial gyroscope, geometric, and accelerometer sensors to sense and gather data from hand gestures. A smartphone application gathers hand gesture data from the sensor device, which is then stored in the cloud database in a .csv format. These data are collected, processed, and classified to recognize the medication intake activity using the proposed novel neural network model called Sea Horse Optimization–Deep Neural Network (SHO-DNN). The SHO technique is implemented to update the biases and weights and the number of hidden layers in the DNN model. By updating these parameters, the DNN model is improved in classifying the samples of hand gestures to identify the medication activities. The research model demonstrates impressive performance, with an accuracy of 98.59%, sensitivity of 97.82%, precision of 98.69%, and an F1 score of 98.48%. Hence, the proposed model outperformed the most available models in all the aforementioned aspects. The results indicate that this model is a promising approach for medication adherence monitoring in healthcare applications, instilling confidence in its effectiveness.

Quality fish feed is the prime need for successful aquaculture. Feed qualities determine the fish flesh quality including appearance, color, odor, flavor, texture, nutritive value, and shelf-life. Nowadays, consumers are very much concerned about various issues regarding way of fish farming, types of feed ingredients used etc. The current study was conducted to assess the heavy metal contents and nutritional composition of some selected commercial fish feeds used in Bangladesh. The major heavy metal concentrations and proximate composition (moisture, crude protein, crude lipid, ash, crude fiber, and carbohydrate) of the collected feed samples were analyzed. The results showed that the feeds contained a number of heavy metals in varying proportions. The highest concentrations (mg/kg) of heavy metals such as lead (Pb), cadmium (Cd), chromium (Cr), copper (Cu), and zinc (Zn) analyzed in fish feed samples were 0.189, 0.027, 1.023, 0.303, and 1.468, respectively. There were significant differences between the nutritive values provided by feed companies and the values observed in this finding. The present study recommends that adequate measures are required to be taken by commercial fish feed manufacturers to ensure the nutritional quality of feed as well as to avoid the contamination of feed from heavy metals. Otherwise, fish and human, the ultimate consumer, may be predisposed to the assimilation and accumulation of the assessed heavy metals.

Optical transport networks rely on reactive fault management, which guarantees service disruption during the onset of soft failures. We present a framework for proactive soft-failure prediction that combines physics-inspired feature engineering, tree-ensemble machine learning, and Infrastructure-as-Code (IaC) orchestration. The framework is validated on (i) a multi-physics stochastic simulation spanning five degradation modes (Ornstein–Uhlenbeck, exponential, Weibull, step, oscillatory) and (ii) a publicly available real optical telemetry benchmark (Ghosh & Adhya, 2025) comprising 756 lightpaths 4 failure classes 900 samples (2.72 M records). A Random Forest regressor augmented with velocity, acceleration, and rolling-statistic features predicts time-to-failure with 17.9 s mean absolute error (MAE) on synthetic test data and 73.2 0.03 s MAE (95% CI, seeds) on the real benchmark, outperforming heuristic baselines by 6 and matching a tuned XGBoost (  s) while surpassing LSTM and 1D-CNN sequence models trained under identical conditions. A trajectory-level train/test split eliminates temporal leakage. SHapley Additive exPlanations (SHAP) applied to four operational case studies (EDFA-aging, NLI-accelerating, stable-link, and false-alarm trajectories) show that alarm decisions are driven primarily by current OSNR, rolling-window statistics, and velocity, yielding interpretable diagnostics at the moment of alert. An end-to-end latency budget of the proposed IaC pipeline, measured stage-by-stage, totals 6.7 s mean wall-clock, dominated by Kubernetes reconciliation and Terraform apply; machine-learning inference contributes < 0.5%. The framework is scoped to gradual OSNR-degrading failures (EDFA pump aging, nonlinear-interference drift); extension to laser-current-visible ECL failures through multi-channel feature fusion is identified as future work.

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) are widely prescribed, yet medication adherence varies. This study evaluated real-world adherence and persistence to semaglutide and empagliflozin among adults with T2D and assessed the associations between adherence and clinical outcomes. A retrospective observational study was performed using electronic health records and pharmacy dispensing data from a military hospital in Tabuk, Saudi Arabia, between July 1, 2023 and June 30, 2024. Adults with T2D (≥18 years old) prescribed semaglutide or empagliflozin were included. Medication adherence was quantified using proportion of days covered (PDC). Persistence was defined by absence of treatment gap ≥60 days. Associations between adherence and patient characteristics, and clinical out-comes, were examined. Among 5087 patients (mean age 57.9 ± 12.3 years, mean T2D duration 10.3 ± 7.6 years), 4020 received empagliflozin and 1067 initiated semaglutide. Adherence (PDC ≥ 80%) was observed in 57.7% of semaglutide and 60% of empagliflozin users. Persistence was lower 40% (semaglutide) and 45% (empagliflozin) met the criteria. Sociodemographic variables were not significant predictors of medication adherence. Medication adherence and persistence to both semaglutide once-weekly injection and oral empagliflozin were suboptimal among T2D patients. Adherent patients to both medications experienced a significant improvement in glycemic control. Targeted strategies are needed to enhance patient motivation for consistent medication use and timely refills.

Question Answering is a crucial natural language processing task. This field of research has attracted a sudden amount of interest lately due mainly to the integration of the deep learning models in the Question Answering Systems which consequently power up many advancements and improvements. This survey aims to explore and shed light upon the recent and most powerful deep learning-based Question Answering Systems and classify them based on the deep learning model used, stating the details of the used word representation, datasets, and evaluation metrics. It aims to highlight and discuss the currently used models and give insights that direct future research to enhance this increasingly growing field.

Understanding of intellectual capital’s influence on the firm performance has received immense interest in recent years. In this view, the impact of various intellectual capital components, including human, structural, and relational capital, on the performance of small- and medium-sized Malaysian manufacturing enterprises were examined. A correlation between intellectual capital and firm performance were established based on the mediating role of innovation capability. To achieve this goal, a stratified sampling method was used wherein 262 participants’ responses from the focused manufacturing firms were obtained and analyzed via the structural equation model (SEM) and resource-based view (RBV). Statistical tools like SPSS.v25 and SmartPLS.v3 were used. The results showed that the relationship between intellectual capital and firm performance was strengthened due to the mediation of innovation capability, thereby gaining higher competitive advantages. It was asserted that the present comprehensive analyses may offer a useful information and guidance to the academics, owners/managers, and policymakers involving the impact of intellectual capital development towards improving the Malaysian SMEs performance.

Fluoroquinolones (FQs) are among the most popular antimicrobials that are highly effective against various infections. Although FQs are the most frequently used and generally tolerated, there are issues with their safety. This study assessed the rate, severity, seriousness, outcomes, and types of FQs adverse drug reactions (ADRs) in reports submitted to a regional spontaneous ADR database. This was a retrospective cross-sectional observational study involving all patients with reported ADRs related to FQs or other antibiotics (ABs) that were submitted to the Regional Pharmacovigilance Center (PVC) database between January 2019 and December 2022. Data were extracted in the form of Saudi ADR from the PVC database, which is consistent with the MedWatch ADR form of the U.S Food and Drug Authority (FDA). In total, 605 ADRs related to antibiotic use were reported. ADRs caused by FQs use were the most frequently reported (177; 29.3%), followed by penicillin (100; 23.4%) and cephalosporin (90; 21%). There was no significant difference in ADRs caused by FQs between men (104; 58%) and women (OR 1.17, 95% CI 0.82-1.67, p=0.386). FQ-related ADRs were more frequent among those over 40 years-old (OR 1.56, 95% CI 1.09-2.22, p=0.015). Most of the detected FQ-related ADRs were of moderate severity (157; 88.7%), required interventions (83; 46.9%), and recovered after receiving medical interventions (154; 87%). Patients who received FQs were fourfold more likely to experience neurological adverse events (OR 4.15, 95% CI 2.48-6.93, p <0.001). The FQs drug class exhibited a higher incidence of ADRs than other ABs. Regularly assessing the safety of ABs is crucial to improve public and healthcare providers' awareness of the correct utilization of ABs and to limit the use of FQs to infections that cannot be effectively managed with alternative ABs.

There is a high tendency for conversion from a statistical economy based on measuring tangible assets into investigating non-tangible capital drive in the present economic status worldwide. The implications of intellectual capital on innovation performance have widely attracted attention among researchers in the global arena. The present study investigated the impacts of intellectual capital on innovation performance in the banking sector as influencing non-tangible assets. Besides, the role of dynamic capabilities in moderating the relationship between intellectual capital and innovation performance was examined. A purposive sampling technique was applied to 364 participants from Iraqi commercial banks as the research context. Thereafter, structural equation modelling (SEM) was utilised to analyse the collected data from the survey questionnaire using SPSS.v25 and AMOS.v24. The study found that the employees’ levels of intellectual capital significantly increased toward innovativeness through the moderating role of dynamic capabilities between intellectual capital and innovation performance in the commercial banking sector for better competitive advantages. Consequently, the study provides valuable insights and guidance for academicians and practitioners on the impacts of developing intellectual capital on enhancing competitive performance, especially in the context of Iraqi commercial banks.