Search Results (4,139)

Rice yield prediction at high spatial resolution is essential to support precision management and sustainable intensification in irrigated systems. While many remote sensing studies provide yield estimates at the field scale, pixel-level predictions are required to characterize within-field variability. This study assesses the potential of multitemporal Sentinel-2 imagery and machine learning to estimate rice yield at pixel level in the Albufera rice area (Valencia, Spain). Yield data from combine harvester maps were collected for ‘JSendra’ and ‘Bomba’ Japonica varieties over five growing seasons (2020–2024) and linked to 10 m Sentinel-2 bands in the visible, near-infrared (NIR) and short-wave infrared (SWIR) regions. Random Forest (RF) and XGBoost (XGB) models were trained with 2020–2023 data and independently validated in 2024. XGB systematically outperformed RF, achieving at 110 and 130 DAS (days after showing), R² values of 0.74 and 0.85 and RMSE values of 0.63 and 0.28 t·ha⁻¹ for ‘JSendra’ and ‘Bomba’. Prediction accuracy increased as the season progressed, and models using all spectral bands clearly outperformed configurations based only on spectral indices, confirming the dominant contribution of NIR reflectance. Spatial error analysis revealed errors at field edges and headlands, while central pixels were more accurately predicted. Overall, the proposed approach provides accurate, spatially explicit rice yield maps that capture within-field variability and support both end-of-season yield estimation and early season forecasting, enabling the identification of potentially low-yield zones to support targeted management decisions. Full article

This study presents the design and implementation of a full-stack IoT ecosystem based on ESP32 microcontrollers and web-based visualization dashboards to support scientific reasoning in first-year engineering students. The proposed architecture integrates a four-layer model—perception, network, service, and application—enabling students to deploy real-time environmental monitoring systems for agriculture and beekeeping. Through a sixteen-week Project-Based Learning (PBL) intervention with 91 participants, we evaluated how this technological stack influences technical proficiency. Results indicate that the transition from local code execution to cloud-based telemetry increased perceived learning confidence from $\mu =3.9$ (Challenge phase) to $\mu =4.6$ (Reflection phase) on a 5-point scale. Furthermore, 96% of students identified the visualization dashboards as essential Human–Computer Interfaces (HCI) for debugging, effectively bridging the gap between raw sensor data and evidence-based argumentation. These findings demonstrate that integrating open-source IoT architectures provides a scalable mechanism to cultivate data literacy in early engineering education. Full article

Emotional dysregulation (ED) reflects a heightened reactivity to stimuli, characterized by excessive negative affect and impulsive behaviors. This study aimed to evaluate ED in workers seeking care for occupational stress and to examine its associations with sociodemographic characteristics, occupational stress, and the severity of anxiety and depressive symptoms. Eighty-seven workers referred for work-related stress were assessed using the Psychological Stress Measure (PSM) and the Job Content Questionnaire (JCQ) for stress, the Beck Depression Inventory-II (BDI-II) and the Self-Rating Anxiety Scale (SAS) for psychopathology, and the RIPoSt-40 for ED. Group comparisons and correlation analyses were conducted using parametric or non-parametric tests, as appropriate. Forty-six percent of participants met criteria for Adjustment Disorders and 54% for Major Depressive Disorder. No significant differences between diagnostic groups emerged for ED or symptom severity. Women reported higher perceived stress and anxiety than men. Negative ED domains—affective instability, negative emotionality, and emotional impulsivity—showed moderate-to-strong positive correlations with stress, anxiety, and depressive symptoms. Affective instability was also related to job stress dimensions, correlating negatively with decision latitude and positively with job demands. Negative emotional dysregulation appears to be a transdiagnostic vulnerability factor for stress-related psychopathology. Screening for ED may support early detection and targeted preventive interventions in occupational settings. Full article

This paper aims to examine the current landscape of novel biomarkers in diabetes mellitus (DM), with particular emphasis on emerging candidates, and their roles in early diagnosis, monitoring disease progression, risk stratification, and managing complications. Given the global prevalence of DM and its complex pathophysiology, identifying reliable biomarkers is critical for optimizing prevention strategies and personalized treatment approaches. This review highlights the shift from traditional glycemic markers, which remain clinically useful but limited, to a broader array of novel biomarkers that more accurately reflect the complex pathophysiology of DM. In addition to conventional measures, inflammatory and oxidative stress mediators, along with genetic and epigenetic regulators, provide added predictive value for disease susceptibility, progression, and complications. Recent research has identified emerging biomarkers, such as adiponectin, adropin, netrin-1, α-hydroxybutyrate, fetuin-A, lipo-protein(a), and lysophosphatidylcholine, which detect early metabolic imbalances and reveal mechanistic links to insulin resistance, β-cell dysfunction, and vascular injury. Their integration into multimarker panels holds particular promise for precision medicine, supporting tailored prevention, targeted therapy, and improved outcomes for individuals with prediabetes and DM. Full article

Background/Objectives: Autologous dentin matrix (ADM) has been suggested as a biologically plausible biomaterial for alveolar bone regeneration after tooth extraction. However, clinical evidence regarding its biological activity and early healing outcomes is limited. This exploratory, randomized controlled pilot study aimed to descriptively assess early alveolar healing patterns and bone morphogenetic protein 4 (BMP4) expression following tooth extraction using ADM compared with other grafting approaches. Methods: Patients requiring tooth extraction were allocated to one of four groups: ADM, xenograft, ADM combined with platelet-rich fibrin, and a graft-free control group. Histological and immunohistochemical analyses were performed four months after extraction to descriptively assess cellular features of healing and BMP4 expression. The trial was registered at the Brazilian Registry of Clinical Trials (ReBEC; RBR-24mdgrf) and conducted under prior ethics committee approval. Results: BMP4 expression was detected in 67.9% of the analyzed histological fields, predominantly localized in osteocytic, osteoblastic, and medullary areas. Although descriptive differences in BMP4-positive fields were observed among the groups, no statistically significant differences were identified between the groups. Histological evaluation revealed an active cellular environment across all treatment modalities, consistent with early post-extraction healing. No adverse events related to surgical procedures or grafting materials were reported during the study period. Conclusions: Within the limitations of this pilot randomized clinical trial, ADM exhibited consistent biological behavior during early post-extraction alveolar healing. The observed BMP4 expression likely reflects a general physiological healing response rather than a material-specific effect. This finding supports the biological plausibility of dentin-derived grafts as osteoconductive biomaterials. These findings are hypothesis-generating, and larger, adequately powered randomized clinical trials with standardized molecular and histological assessments are required to determine their clinical relevance. Full article

While multi-view visualization systems are widely used for mining vehicle teleoperation, they often impose high cognitive load and restrict operator attention. To explore a more efficient alternative, this study evaluated a merged-view interface that integrates multiple camera perspectives into a single coherent display. In a controlled experiment, 35 participants navigated a teleoperated robot along a 50 m lab-scale path representative of an underground mine under both multi-view and merged-view conditions. Task performance and eye-tracking data—including completion time, path adherence, and speed-limit violations—were collected for comparison. The merged-view system enabled 6% faster completion times, 21% higher path adherence, and 28% fewer speed-limit violations. Eye-tracking metrics indicated more efficient and distributed attention: blink rate decreased by 29%, fixation duration shortened by 18%, saccade amplitude increased by 11%, and normalized gaze-transition entropy rose by 14%, reflecting broader and more adaptive scanning. NASA-TLX scores further showed a 27% reduction in perceived workload. Regression-based sensitivity analysis revealed that gaze entropy was the strongest predictor of efficiency in the multi-view condition, while fixation duration dominated under merged-view visualization. For path adherence, blink rate was most influential in the multi-view setup, whereas fixation duration became key in merged-view operation. Overall, the results indicated that merged-view visualization improved visual attention distribution and reduced cognitive tunneling indicators in a controlled laboratory teleoperation task, offering early-stage, interface-level insights motivated by mining-relevant teleoperation challenges. Full article

Background: Dementia and mild cognitive impairment (MCI) are major public health concerns in rapidly aging societies. However, evidence from non-Western populations with self- or proxy-reported physician-diagnosed cognitive outcomes remains limited. Methods: This study investigated the four-year (2018–2022) incidence of self- or proxy-reported dementia and MCI, and their multidomain risk markers in a nationally representative sample of 3432 Korean adults aged ≥ 65 years from the Korean Longitudinal Study of Aging. Weighted descriptive analyses and multinomial logistic regression accounting for the complex survey design (sampling weights, strata, and clusters) were used to identify demographic, functional, mental health, and social factors associated with the incidence of cognitive impairment. Adjusted predicted probabilities were estimated for age, depressive symptoms, and instrumental activities of daily living (IADL). Results: Over the four-year follow-up period, among 3432 initially cognitively normal community-dwelling older adults, 34 participants developed MCI and 70 developed dementia. Older age, increased IADL impairment, depressive symptoms, and multimorbidity were significantly associated with a higher likelihood of incident cognitive impairment, while living with family was associated with a lower likelihood. Frequent social interaction showed a protective association against dementia. Predicted probabilities demonstrated overall increasing trends across age, depressive symptoms, and IADL, reflecting general risk patterns. Conclusions: These findings emphasize the importance of multidomain assessments for early detection and community-based prevention strategies. By identifying key clinical and social markers, this study provides culturally relevant evidence to support dementia risk management in rapidly aging populations, highlighting the protective roles of family co-residence and frequent social interaction among Korean older adults. Full article

Background: Hypertensive disorders of pregnancy (HDP) have significant implications for women’s long-term health, including at least a twofold increased lifetime risk of cardiovascular disease (CVD). The Blood Pressure Postpartum (BP²) Study was a three-arm randomised trial evaluating follow-up and lifestyle behaviour change strategies during the first year after HDP. Methods: This qualitative sub-study, embedded within the BP² Study, explored women’s experiences of life in the first year following HDP. Semi-structured telephone interviews were conducted with 34 women, approximately 10–12 months postpartum. Interviews were transcribed verbatim and a thematic analysis was undertaken. Results: Participants reflected on their experiences post-HDP; three major themes were identified: Navigating life with a newborn, The value of support, and Processing and Moving forward. Some women felt informed and empowered to make positive lifestyle changes; others were still processing their HDP experience and/or feeling overwhelmed by the demands of early motherhood. Responses were influenced by their HDP experience, available support, prior experience with healthy behaviours, and financial stability. Conclusions: The findings highlight that postpartum women who experienced HDP face unique challenges, including physical recovery, emotional processing, and intensive infant care. It often takes time for these women to begin prioritising their own health, as they navigate these challenges. The insights generated from women’s experiences suggest that flexible, accessible, and individually tailored support may facilitate postpartum health, promote lifestyle change, and help reduce long-term CVD risk. Full article

For hot-rolled ferritic stainless steels with preferential α-fiber texture, the strong α-fiber texture is retained after annealing, greatly affecting the texture and plastic formability during the subsequent cold-rolling process. For optimizing the texture of hot-rolled steels toward the favorable γ-fiber type, it is essential to control the annealing temperature in the annealing process. To investigate the evolution of the microstructure, texture, and properties of hot-rolled ferritic stainless steel with preferential α-fiber orientation, a series of annealing tests was performed at the lab scale at 800, 840, 880, 910, 930, and 950 °C for 3 min. The microstructure, texture, and grain boundary characteristics of the tested samples were analyzed using optical microscopy (OM) and electron back-scattered diffraction (EBSD). The mechanical properties and plastic strain ratio (r-value) were determined through universal tensile testing. The results show that at temperatures above 840 °C, more than 93% of recrystallization occurs, leading to significant microstructural refinement. The α-fiber texture intensity typically diminishes with rising temperature, whereas the γ-fiber texture initially weakens during the early stages of recrystallization (below 840 °C) and subsequently exhibits a slight increase at higher temperatures. The improved formability of the material is mainly attributed to microstructural refinement and texture refinement, as reflected by the I(γ)/I(α) texture intensity ratio. At an annealing temperature of 930 °C, the I(γ)/I(α) ratio peaks at 0.85, static toughness is maximized, the strain-hardening exponent (n) reaches a high value of 0.28, and the maximum average plastic strain ratio ($\overline{r}$) is 0.96. This result represents the optimum balance between mechanical properties and formability, making it suitable for subsequent cold-rolling. Full article

Background: Cardiovascular risk models, such as the Framingham and atherosclerotic cardiovascular disease (ASCVD) calculators, have improved risk prediction but often fail to identify individuals who experience ASCVD events despite low or intermediate predicted risk. This suggests that underrecognized, non-traditional risk factors may contribute significantly to the development of atherosclerosis. Objective: This narrative review synthesizes and summarizes recent evidence on high-yield non-traditional risk factors for atherosclerosis, with a focus on clinically significant, emerging, and applicable contributors beyond conventional frameworks. This review is distinct in that it aggregates a wide array of non-traditional risk factors while also consolidating recent data on ASCVD in more vulnerable populations. Unlike the existing literature, this manuscript integrates in a single comprehensive review various domains of non-traditional atherosclerotic risk factors, including inflammatory, metabolic, behavioral, environmental, and physical pathways. An additional unique highlight in the same manuscript is the discussion of non-traditional risk factors for atherosclerosis in more vulnerable populations, specifically South Asians. We also focus on clinically actionable factors that can guide treatment decisions for clinicians. Results: Key non-traditional risk factors identified include inflammation and biomarker-based risk factors such as C-reactive protein or interleukin-6 levels, metabolic and microbial risk factors, behavioral factors such as E-cigarette use, and environmental or infectious risk factors such as air and noise pollution. We explore certain physical exam findings associated with atherosclerotic burden, such as Frank’s sign and Achilles tendon thickness. Conclusions: Atherosclerosis is a multifactorial process influenced by diverse and often overlooked factors. Integrating non-traditional risks into clinical assessment may improve early detection, guide prevention and personalize care. Future risk prediction models should incorporate molecular, behavioral, and environmental data to reflect the complex nature of cardiovascular disease. Full article

The use of machine learning (ML) and deep learning (DL) in lung cancer detection and classification offers great promise for improving early diagnosis and reducing death rates. Despite major advances in research, there is still a significant gap between successful model development and clinical use. This review identifies the main obstacles preventing ML/DL tools from being adopted in real healthcare settings and suggests practical advice to tackle them. Using PRISMA guidelines, we examined over 100 studies published between 2022 and 2024, focusing on technical accuracy, clinical relevance, and ethical aspects. Most of the reviewed studies rely on computed tomography (CT) imaging, reflecting its dominant role in current lung cancer screening workflows. While many models achieve high performance on public datasets (e.g., >95% sensitivity on LUNA16), they often perform poorly on real clinical data due to issues like domain shift and bias, especially toward underrepresented groups. Promising solutions include federated learning for data privacy, synthetic data to support rare subtypes, and explainable AI to build trust. We also present a checklist to guide the development of clinically applicable tools, emphasizing generalizability, transparency, and workflow integration. The study recommends early collaboration between developers, clinicians, and policymakers to ensure practical adoption. Ultimately, for ML/DL solutions to gain clinical acceptance, they must be designed with healthcare professionals from the beginning. Full article

Engineering programmes have been giving more weight to experiential learning, largely because many students still find it difficult to see how classroom theory connects to the work that engineers handle on the ground. With this in mind, a robotics-centred Project-based Learning (PBL) module was introduced to first-year general engineering students as part of the faculty’s engineering spine. The module asks students to design, build, and program small autonomous robots capable of navigating and competing in a set arena. Even a simple task of this kind draws together multiple strands of engineering. Students shift between sketching mechanical layouts, wiring basic circuits, writing code, testing prototypes, and negotiating the usual challenges that arise when several people share responsibility for the same piece of hardware. To explore how students learned through the module, a mixed-methods evaluation was carried out using survey responses alongside reflective pieces written by the students themselves. Certain patterns appeared repeatedly. Many students felt that their technical skills had grown, particularly in breaking down a messy problem into smaller, more workable components. Teamwork also surfaced as a prominent theme. Groups often had to sort out issues such as a robot veering off course due to a misaligned sensor or a block of code producing unpredictable behaviour. These issues were undoubtedly challenging for the students, but they also had a certain pedagogical flavour, with many students describing them as a source of frustration as well as a learning opportunity. Later iterations of the module may benefit from more targeted support at key stages. Despite the many challenges, robotics has been shown to be an attractive way for students to step into engineering practice. The project helped them build technical capability, but it also encouraged habits that matter just as much in real work, such as planning, communicating clearly, and returning to a problem until it behaves as expected. Taken together, the experience offers useful guidance for curriculum designers seeking to create early learning environments that feel authentic and manageable and for motivating students who are just beginning their engineering journey. Full article

Background/Objectives: The extent to which patients with cancer discontinue dental treatment for financial reasons remains unclear. This study compared the prevalence of financially driven dental treatment discontinuation between patients with cancer and without cancer (controls) and identified factors associated with discontinuation among patients with cancer. Methods: This cross-sectional, questionnaire-based survey conducted in November 2024 comprised 500 patients who had one of five common cancers in Japan and 500 non-cancer participants allocated to reflect the cancer group age distributions, sex, and household income. Only patients who received cancer treatment within the past 5 years and had a family dental clinic were included. Discontinuation was assessed from self-reported dental treatment cessation for economic reasons. Univariate analyses were employed for group comparisons (p < 0.05). Results: Dental treatment discontinuation for financial reasons occurred in 3.4% (95% CI 2.1–5.4%) of patients with cancer and 5.8% (95% CI 4.1–8.2%) of controls (p = 0.096). Among the patients with cancer, those who discontinued were younger (58.8 vs. 66.1 years, p = 0.010) and frequently reported physical or psychological barriers to dental care and discontinuation being financially driven (all p < 0.001). They also had poor oral health-related quality of life (Oral Health Impact Profile-14: 17.4 vs. 7.8, p < 0.001) and greater financial toxicity (Comprehensive Score for Financial Toxicity: 24.6 vs. 29.3, p = 0.001). Conclusions: Oral health-related quality of life was lower among participants reporting dental treatment discontinuation. Early identification of financial barriers and support may warrant further study. Full article

Background: Helmet therapy is considered to be a treatment for infants with positional plagiocephaly. Although some studies suggest that anterior fontanelle (AF) size may also affect treatment outcomes, evidence and influence remain unclear. The aim of this study is to assess the impact of anterior fontanelle size on the effectiveness of helmet therapy, with the goal of determining the optimal timing and patient criteria for treatment. Methods: We conducted a retrospective study of 94 infants treated with helmet therapy for positional plagiocephaly at Kwangju Christian Hospital between January 2020 and December 2021. Patients were divided into two age groups (≤6 months and >6 months) and three SAF quartiles (≤25%, 25–75%, ≥75%). Parameters reflecting the degree of cranial asymmetry correction, including cranial vault asymmetry (CVA) and cranial vault asymmetry index (CVAI), were recorded at the start and end of treatment. Results: Infants aged ≤6 months showed significantly greater improvements in cranial vault asymmetry (CVA) and cranial vault asymmetry index (CVAI) compared to older infants (CVA: 4.57 ± 2.30 mm vs. 7.04 ± 3.85 mm, p = 0.003; CVAI: 3.10 ± 1.55% vs. 4.45 ± 2.44%, p = 0.011). When analyzed by anterior fontanelle (AF) size quartiles (≤25%, 25–75%, ≥75%), no significant differences in treatment outcomes were observed at the end of therapy for CVA (p = 0.88) or CVAI (p = 0.91). In infants ≤6 months, SAF quartile analysis also showed no significant differences in CVA (p = 0.97) or CVAI (p = 0.98) improvements. Conclusions: Our findings indicate that anterior fontanelle size is not a predictor of helmet therapy outcomes in positional plagiocephaly. Early initiation of helmet therapy (≤6 months) remains the most critical factor for achieving optimal results. Full article

Background: Red cell distribution width (RDW) and the RDW-to-platelet ratio (RPR) have emerged as readily available hematologic markers reflecting systemic inflammation in neonates with hypoxic–ischemic encephalopathy (HIE); however, their early postnatal trajectories across the clinical spectrum of HIE remain insufficiently characterized. Methods: This retrospective cohort study included 229 term or near-term infants diagnosed with HIE. Among them, 166 infants received therapeutic hypothermia, whereas 63 infants who did not undergo cooling served as the reference group. RDW and RPR values were measured at birth and at 72 h of life (after completion of cooling in the hypothermia group). Results: In the reference group, RDW values significantly decreased at 72 h, reflecting normal postnatal hematologic adaptation. In contrast, the hypothermia group demonstrated a blunted decline, with RDW levels remaining relatively stable over the first 72 h, consistent with a blunted early postnatal RDW decline. RPR values showed a mild, non-significant upward trend during the first 72 h of life; however, exploratory analyses suggested an association between higher RPR levels and increasing HIE severity. Conclusions: Across the spectrum of hypoxic–ischemic encephalopathy, RDW demonstrated a blunted postnatal decline, whereas RPR showed a mild, non-significant increase during the early neonatal period. These readily available hematologic markers may provide complementary insights into early systemic inflammatory and hematologic responses in HIE. Prospective multicenter studies are needed to determine their prognostic value and relationship with clinical and neurodevelopmental outcomes. Full article