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Exploring EFL teachers’ beliefs and practices of formative assessment in Chinese context
Formative assessment (FA) has become central to effective EFL pedagogy, promoting feedback, engagement, and self-regulated learning. Yet in the Chinese EFL context, little is known about how university teachers actually conceptualize and enact FA in their classrooms. This study explores EFL teachers’ beliefs, self-reported practices, and challenges in implementing FA through a mixed-methods design that combines a survey (N = 288) with follow-up interviews (n = 11). Results revealed that most teachers hold positive beliefs about FA and acknowledge its potential to enhance student motivation and engagement. However, the frequency of FA practices varies significantly among the participants. Teachers tend to select their FA strategies within institutional limits and rely on technological platforms for implementing these strategies. Despite acknowledging FA’s role in informing teaching improvements and student learning, it was frequently used for grading and managing classroom participation. Challenges included time constraints, large class sizes, inadequate technological support, difficulty in establishing clear assessment criteria, and underutilization of self- and peer assessment. These findings highlight the necessity for multifaceted interventions to better align EFL teachers’ beliefs with their practices in FA.
Modeling and optimization of argon-based floating helix electrode cold plasma
Abstract Cold atmospheric pressure plasma (CAP) technology has vast potential in several technological domains, including biomedical engineering. CAP, also known as non-thermal plasma, is characterized by high-energy electrons while the bulk gas remains near room temperature, allowing for effective plasma treatment without thermal damage—critical for biomedical applications. This paper presents a coupled machine learning and statistical technique-based process modeling and optimization approach for a novel floating-helix electrode-based cold plasma device, operating strictly within the cold plasma regime. An artificial neural network (ANN) model was developed to describe the relationship between the process parameters—supply voltage (SV) and frequency (SF)—and performance parameters—power consumption (P), and jet lengths with and without an end ring (JwER and JwoER). The generality and robustness of the ANN model were confirmed through experimental validation and extrapolative predictions. For multi-response optimization, the composite desirability method was employed. Finally, machine learning models for logistic regression—namely, ANN classifier, K-Nearest Neighbor, and Support Vector Machine—were developed to classify the discharge type within the cold plasma operating range, ensuring its suitability for biomedical applications. The proposed system may hold potential for biomedical use, contingent upon further validation through biological testing.
Distance-based ratio metric assay using thread-based devices for Karaya gum detection in food samples
Abstract Karaya gum, a natural food-grade thickener, is an adulterant that compromises product quality and consumer safety. Herein, we develop a low-cost, rapid and portable device that employs thread-based microfluidics integrated with ratio-metric displacement to detect and quantify Karaya gum, with a limit of detection of 0.1%w/v. The interaction between the cellulose in the bamboo viscose thread and the chlor-zinc-iodide reagent causes the thread to turn blue immediately. On addition of simulated Karaya gum samples, a brown region appears beyond the blue region due to hydrogen bond formation between the hydroxyl groups of the thread and the complex sugars in the gum, thereby causing the displacement of iodine, which was confirmed by FTIR analysis. Higher gum concentrations increase viscosity and result in less displacement of iodine, with the blue-to-brown colorimetric ratio being directly proportional to the gum concentration. These observations were confirmed by measuring the viscosity of the Karaya gum and correlating it with the structure and nature of the gum. Furthermore, the variation in the iodine release was quantified using grayscale values utilizing Fiji software. The device was implemented for field trial using commercial basil drink. This approach offers an efficient alternative to conventional cumbersome detection strategies and has enormous potential for onsite food safety and quality control.
Weekly patterns and sociodemographic correlates of adults’ objectively measured physical activity and sedentary behavior
Objectives As well as the dose-response association of physical activity (PA), its combination with other behaviors and daily patterns are associated with health outcomes. Identifying the prevalence of objectively assessed weekly patterns of PA and sedentary behavior (SB) and sociodemographic correlates may contribute to maximizing beneficial intervention strategies. Methods We assessed PA and SB using an accelerometer among 684 participants aged 40–64 years from two Japanese localities. PA and SB combinations were defined as ‘Couch potato’ (low PA and high SB), ‘Light mover’ (low PA and low SB), ‘Sedentary exerciser’ (high PA and high SB), and ‘Busy bee’ (high PA and low SB). Weekly PA patterns were defined as ‘Inactive’ (low PA), ‘Weekend warrior’ (high PA and PA mainly on the weekend), and ‘Regularly active’ (high PA and PA throughout the week). To identify differences in characteristics across the groups, analysis of variance with post-hoc Bonferroni multiple comparison tests was used for continuous variables. For categorical variables, group differences were examined using χ2 tests with post-hoc residual analyses. Results Regarding PA and SB combinations, ‘Couch potato’ and ‘Busy bee’ groups were approximately one-third each, and ‘Light mover’ and ‘Sedentary exerciser’ were approximately one-fifth-to-sixth. Regarding weekly PA patterns, 16.6% and 38.9% of the participants were categorized as ‘Weekend warrior’ and ‘Regularly active’, respectively. Almost 45% of participants were categorized as ‘Inactive’. The characteristics were defined for each category. For instance, women and participants with lower educational attainment were more likely to be ‘Light mover’. Participants with higher educational attainment were more likely to be ‘Weekend warrior’, whereas age and sex were not significantly associated with weekly PA patterns. Conclusions Initiatives to address PA and SB could focus on total amounts and appropriate combinations and patterns depending on the characteristics of the target subgroup.
Effects of robot assisted mirror therapy on motor function and cortical activation in patients with right hemisphere damage
An improved lightweight algorithm for traffic sign detection
Identifying key predictors amongst children of under 5 years of age with fever and rashes amidst measles outbreak in Jharkhand: A case control study
Background There has been a recent rise of viral exanthem outbreaks in Jharkhand and other parts of India over the last 2–3 years. This may be due to low immunization coverage of measles vaccination or due to spread of other causes of fever and rash. This study aims to identify the key predictors of fever and rashes among children under five years old by analysing demographic, clinical, and environmental factors. Methods This study employed age-matched case-control design to investigate the association between fever with rash (cases) and the absence of such symptoms (controls), along with identifying potential predictors. The study was conducted retrospectively among children aged 0–60 months who presented with fever and rash at various healthcare centres across affected districts in Jharkhand during a measles outbreak from January to May 2023. We included 611 cases and control thus making total sample size to be 1222. Multivariable logistic regression was performed to identify independent risk factors associated with fever and rash during the outbreak. Results The mean age for cases was found to be 37.37 ± 22.8 months and while for control it was found to be 25.89 ± 18.6 months. Majority of cases with fever with rash were found among the female child, 50.6% (279) but was not statistically significant. Significant factor as fever and rashes were found to be more amongst the children 200 (68.5%) who had not taken first dose and 325 (53%) of cases who had not taken second dose of measles vaccine with P-value of less than 0.001 and 0.022 respectively. On applying Multivariate analysis religion was 2.5 times more associated and even ethnicity was 3 times more associated with the fever and rash cases. Conclusion The study concludes that ethnicity, religion, and caste are important predictors of fever and rash cases. The most important factor is non-receipt of all age-appropriate vaccine as one of key factors for fever and rashes. The sociodemographic factors have a crucial role in transmission of viral exanthem and stakeholders must keep a vigil over these factors while dealing outbreaks of fever with rash disease.
Association between cardiometabolic index and cardiometabolic multimorbidity in non-alcoholic fatty liver disease patients: evidence from a cross-sectional study
Numerical analysis on the drilling force of pneumatic impactors under different working conditions and structural parameters
Accuracy of day-to-day patient positioning in ocular proton therapy with a dedicated beamline
The purpose of this study was to determine the residual patient positioning error of ocular proton treatment based on daily setup X-ray images and tantalum clips. The residual day-to-day patient positioning accuracy in a cohort of 60 patients and 240 fractions was determined in two steps. The 3D tantalum clips’ positions in the orthogonal X-ray images just prior to aperture placement were registered with 3D clips’ positions derived from the reference data from treatment planning. The aperture, placed before irradiation, reduced the field of view in axial images blocking clips partially or completely in most cases. The clips’ positions after aperture placement in the lateral images were compared with the reference clips’ positions. Partially visible clips in the axial image were registered to the clips in the axial image prior to aperture placement. The day-to-day deviations to aperture placement were corrected with the registration results for translations only. The residual day-to-day patient position variations just prior to irradiation were −0.06 ± 0.27 mm (mean ± 1SD) for the left-right direction, −0.01 ± 0.23 mm for the anterior-posterior direction and −0.01 ± 0.19 mm for the superior-inferior direction. This data was further investigated by differentiating for treated eye, gazing eye and the use of eyelid retractor. This yielded no significant differences. The residual patient positioning errors are small for patients treated at the dedicated eyeline, indicating that the patient positioning workflow using tantalum clips is highly accurate. The reported errors can be used for ocular proton margin calculations and for the evaluation of a clipless ocular proton therapy workflow.
Association of fine particulate matter and wet-bulb globe temperature with depression incidence in a community-based longitudinal study
Fractional-order PID control for elevation and azimuth in a twin rotor system
Uncovering biomarkers and molecular pathways linking NAFLD and AIS: Insights from bioinformatic analysis and experiment
Background Non-alcoholic fatty liver disease (NAFLD) and acute ischemic stroke (AIS) are both closely related to chronic inflammation and metabolic disorders, but the molecular mechanisms between them are not yet clear. This study aims to explore the common molecular characteristics between NAFLD and AIS using bioinformatics methods. Methods We integrated transcriptomic data from GEO (GSE89632 for NAFLD and GSE16561 for AIS) to identify shared molecular signatures. Differentially expressed genes (DEGs) were screened using the limma package, and co-expression modules were identified via WGCNA. Functional enrichment and immune infiltration analyses were conducted using standard bioinformatics tools. Key genes were selected through LASSO and random forest algorithms, and candidate drugs were predicted using the CMap database. Experimental validation included qPCR, immunohistochemistry, and drug intervention in HepG2 and HMC3 cell models, as well as a high-fat diet-induced NAFLD mouse model. Results Through differential expression analysis, 65 common DEGs were identified in both NAFLD and AIS. Functional enrichment analysis showed that these genes mainly involve signal pathways related to immune regulation and inflammatory responses. Immune infiltration analysis showed a significant increase in monocytes, B cells, and plasma cells in NAFLD patients. Ultimately, four potential biomarkers were screened out using LASSO regression and random forest algorithms: CEBPD, SOCS2, THBS1, and IFIT2. Using cMAP, 10 candidate therapeutic drugs, including lamotrigine, were identified. Expression of CEBPD and SOCS2 was consistently upregulated in NAFLD clinical datasets, FFA-treated HepG2 cells, and liver tissues of HFD-induced NAFLD mice, but not in AIS datasets or OGD-treated microglial cells. Furthermore, lamotrigine, cinnarizine, and lenvatinib significantly suppressed FFA-induced CEBPD and SOCS2 expression in HepG2 cells (p < 0.05), supporting their potential regulatory effects. Conclusions This study identified common DEGs between NAFLD and AIS and experimentally validated CEBPD as a potential marker, revealing possible common molecular mechanisms between the two diseases, providing new directions for future diagnosis and treatment.
Investigation on hybrid optimization approach for minimizing surface roughness in the machining of Mg/TiC metal matrix composites using spark EDM
Abstract Electrical discharge machining (EDM) is a non-traditional machining technique in which material is extracted as debris from the workpiece due to a spark produced at the interface of the workpiece and electrode (tool). This paper presents the machining of Mg-TiC composites in a servo-controlled spark EDM using a copper tool as electrode material by varying the input process parameters. Surface roughness (SR) was modeled in terms of four input process variables viz. Mg/TiC composites (WP), pulse on time (T on ), pulse off time (T off ) and input current (I) using artificial neural network (ANN). The predictive performance of the ANN model was better with 93.05% model accuracy. A hybrid optimization methodology integrating ANN with the Jaya algorithm is proposed for the optimization of EDM process parameters to obtain minimum SR. The proposed optimization methodology obtained an optimum value of SR 2.89 µm at optimal process parameters $$WP=8.05\text{\%}$$ , $${T}_{on}=21.00\mu s$$ , $${T}_{off}=75.00\mu s$$ , $$I=8.00A$$ . The performance of the ANN-Jaya integrated optimization methodology was found highly accurate and consistent during the consistency test with lower standard deviation. The increase in pulse on time and input current turns in a rougher surface as observed from surface roughness tester. A study on the surface morphology of the machined component is also presented using scanning electron microscope (SEM) images.
Longitudinal study of pulmonary function trends and associated risk factors in iron ore miners
Abstract The mining industry involves various processes, including extraction, crushing, milling, stacking, and reclaiming mineral substances. Workers in these environments are at risk of respiratory diseases due to exposure to high concentrations of pollutants, such as respirable dust. This study was conducted on sweepers, supervisors, and office workers of an iron ore Concentrate and Raw pellet production plants. Sampling and analysis of respirable dust, crystalline silica, and iron dust were performed according to NIOSH 0600, NIOSH 7601, and OSHA ID-121 methods, respectively. The values of lung function indices were extracted from personnel medical records over the years of their work experiences. The results showed that the highest mean concentration of respirable dust, iron, and crystalline silica dust belongs to the sweeper group and the lowest mean concentration belongs to the office group. The reduction rate of pulmonary functions over time was also higher in the sweeper and supervisor groups than in the office group. The effective factors on the pulmonary functions were age, work experience, academic education level, occupational group, cigarette and waterpipe smoking, and type of employment.
Impact of COVID-19 on breast cancer patients and services in a UK region: Protocol for a mixed methods study
Background Globally, breast cancer screening, diagnosis and treatment services were significantly impacted by the COVID-19 pandemic. Locally, the Northern Ireland Cancer Registry (NICR) reported an 11% reduction in breast cancers diagnosed April-December 2020 compared with the same period 2018−2019 despite an expected increase. This study aims to identify how the patient journey was impacted by the COVID-19 pandemic and how service provision can be improved. Methods Population-based quantitative data will be collected by NICR for individuals diagnosed with invasive breast cancer (ICD 10 code C50). Data on presentation, investigations, comorbidities (including COVID-19 infection), molecular markers, stage at diagnosis, treatment, and survival will be examined. Two time periods will be compared: March-December 2018 (pre-COVID-19 cohort) and March-December 2020 (COVID-19 cohort). Analysis will include descriptive statistics, chi-square tests and ANOVAs. Patient experiences of living with breast cancer and interacting with the healthcare system during the pandemic (March 2020-April 2024) will be captured through an online, self-completed, anonymous cross-sectional international survey. Quality of life will be captured in the survey using the EQ-5D-3L. Detailed descriptive qualitative interviews will be undertaken to better understand the lived experience of breast cancer and recommend ways that services and support programs can effectively meet the needs of this patient group. This study benefits from the inclusion of patient representatives who have been involved since the inception of this project. Discussion This study aims to quantify the impact of the COVID-19 pandemic on breast cancer patient outcomes in a UK region and make recommendations to improve patient care and outcomes in the short and long term.
Antimicrobial and biodegradable PVA/rutin/CuO nanocomposite film for garlic preservation
Abstract The growing demand for sustainable and active packaging materials has led to the exploration of biodegradable polymers reinforced with functional nanomaterials. In this study, polyvinyl alcohol (PVA)-based films were synthesized via solution casting method, incorporating copper oxide nanoparticles (CuO NPs) and rutin to improve their physicochemical and antimicrobial properties for food packaging applications. The incorporation of CuO NPs contributed to notable improvements in mechanical strength, water solubility, water vapor permeability, moisture adsorption, and antimicrobial efficacy against S. aureus, E. coli, and C. albicans. PRC-3 film exhibited zone of inhibition of 38.00 ± 0.66, 29.66 ± 0.44, and 26.66 ± 0.44 mm against S. aureus, E. coli, and C. albicans, respectively. The films also showed excellent biodegradability, reinforcing their promise as an environmentally responsible packaging alternative. Rutin release study revealed minimal diffusion into aqueous media, supporting the films potential for prolonged active function. Notably, the practical application test involving garlic storage demonstrated effective preservation of quality for up to 23 days. Altogether, these results underline the potential of PVA/Rutin/CuO (PRC) nanocomposite films as multifunctional, eco-friendly candidates for next-generation active food packaging systems.
Weakening and fracturing mechanism of roof strength through borehole pressure relief under true triaxial stress
Robust unmanned aerial vehicles tracking amid electronic interference utilizing auxiliary particle filtering
Electronic interference poses a significant challenge to Unmanned Aerial Vehicle (UAV) tracking systems, compromising navigation accuracy and operational safety in critical applications such as surveillance, disaster response, and infrastructure inspection. This study introduces a novel application of the Auxiliary Particle Filter (APF) for robust UAV tracking under interference conditions, focusing on fixed-reference scenarios. The APF incorporates adaptive proposal distributions and robust weight updates to effectively mitigate interference-induced measurement errors. Through comprehensive simulation that evaluates performance under varying interference and sensor degradation scenarios, the APF demonstrates superior accuracy, achieving a mean Root Mean Square Error (RMSE) of 4.82 meters with low variability (σ=0.30m). This significantly outperforms traditional filters, including the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). Notably, the APF maintains stable performance even under severe interference conditions, where conventional approaches exhibit substantial degradation. Statistical validation confirms these improvements across all test scenarios (p < 0.001). The detailed implementation guidelines provided in this study enable adoption across diverse operational contexts. These findings establish the APF as a robust and reliable solution for interference-prone environments and lay the groundwork for its adaptation to more dynamic tracking scenarios in autonomous UAV operations.