Search Results (8,312)

This study investigated the influence of different pectin concentrations (0%, 0.1%, and 0.5%) on the physicochemical, antioxidant, and sensory properties of blackberry jam (Rubus fruticosus L.) prepared from fruits harvested at three altitudinal locations (wild: 998 m; cultivated: 500 m and 1090 m). The jams were analyzed for phenolic profile, antioxidant capacity, color, texture, and sensory attributes. The results showed that altitude strongly affected the phenolic profile and antioxidant capacity, with wild blackberries exhibiting the highest levels of total phenolics, flavonoids, and anthocyanins. Pectin addition in moderate levels (0.1%) enhanced sensory acceptance, particularly in jams from higher altitudes. Furthermore, jams with added pectin showed improved vitamin C retention and reduced bitterness associated with phenolic compounds. Overall, the findings highlight the dual role of pectin in modulating the functional and sensory qualities of blackberry jam, while also demonstrating the impact of altitudinal variation on fruit-derived products. Full article

Color accuracy is both important and elusive in cultural heritage imaging. An established method for improving color accuracy is dual-RGB imaging, where RGB images of an object are captured sequentially under two different conditions and then combined. As part of an initiative to increase accessibility to color-accurate imaging, the use of lighting filters with the dual-RGB method is investigated. Gel lighting filters are low-cost and can be directly integrated into an imaging workflow by placing them in front of the existing light sources. This research found that color accuracy can be increased by using lighting filters, but it can also be decreased by a poor selection of filter combinations. The identity of the best-performing filters is highly dependent on the light source and can be affected by the pixels selected to represent the color target. Current simulation approaches are insufficient to predict which filters will increase color accuracy. While lighting filters are a promising method for accessible multispectral imaging, their practical implementation is complex and requires further research and adjustments to the method. Full article

Against the backdrop of the rapid proliferation of electric vehicles (EVs), gender-oriented behavioral mechanisms remain underexplored, particularly the unique pathways of female users in usage experience, value assessment, and purchase decision-making. This study constructs an integrated framework based on the Stimulus–Organism–Response (SOR) model, leveraging social media big data to analyze in depth how gender differences influence EV users’ purchase intentions. By integrating natural language processing techniques, grounded theory coding, and structural equation modeling (SEM), this study models and analyzes 272,083 pieces of user-generated content (UGC) from Chinese social media platforms, identifying key functional and emotional factors shaping female users’ perceptions and attitudes. The results reveal that esthetic value, safety, and intelligent features more strongly drive emotional responses among female users’ decisions through functional cognition, with gender significantly moderating the pathways from perceived attributes to emotional resonance and cognitive evaluation. This study further confirms the dual mediating roles of functional cognition and emotional experience and identifies a masking (suppression) effect for the ‘intelligent perception’ variable. Methodologically, it develops a novel hybrid paradigm that integrates data-driven semantic mining with psychological behavioral modeling, enhancing the ecological validity of consumer behavior research. Practically, the findings provide empirical support for gender-sensitive EV product design, personalized marketing strategies, and community-based service innovations, while also discussing research limitations and proposing future directions for cross-cultural validation and multimodal analysis. Full article

Background: Lumbar disk herniation is a common cause of low back pain and radiculopathy, significantly impacting patients’ life quality and functional capacity. Magnetic Resonance Imaging (MRI) remains the gold standard for its assessment due to its superior soft tissue contrast and multiplanar imaging capabilities. However, recent advances in spectral computed tomography (CT), particularly dual-energy CT (DECT), have introduced new diagnostic opportunities, offering improved soft tissue characterization. Objective: To evaluate the diagnostic performance of DECT in detecting and grading lumbar disk herniations using dedicated color-coded fat maps. Materials and Methods: A total of 205 intervertebral levels from 41 consecutive patients with lumbar symptoms were prospectively analyzed. All patients underwent both DECT and MRI within 3 days. Three radiologists with varying years of experience independently assessed DECT images using color-coded reconstructions. A five-point grading score was attributed to each lumbar level: 1 = normal disk, 2 = bulging/protrusion, 3 = focal herniation, 4 = extruded herniation, and 5 = migrated fragment. The statistical analysis included Pearson’s correlation for score consistency, Cohen’s Kappa for interobserver agreement, generalized estimating equations for a cluster-robust analysis, and an ROC curve analysis. The DECT diagnostic accuracy was assessed in a dichotomized model (grades 1–2 = no herniation; 3–5 = herniation), using MRI as reference. Results: A strong correlation was observed between DECT and MRI scores across all readers (mean Pearson’s r = 0.826, p < 0.001). The average exact agreement between DECT and MRI was 79.4%, with the highest concordance at L1–L2 (86.7%) and L5–S1 (80.4%). The interobserver agreement was substantial (mean Cohen’s κ = 0.765), with a near-perfect agreement between the two most experienced readers (κ = 0.822). The intraclass correlation coefficient was 0.906 (95% CI: 0.893–0.918). The ROC analysis showed excellent performance (AUC range: 0.953–0.986). In the dichotomous model, DECT demonstrated a markedly higher sensitivity than conventional CT (95.1% vs. 57.2%), with a comparable specificity (DECT: 99.0%; CT: 96.5%) and improved overall accuracy (98.4% vs. 90.0%). Subgroup analyses by age and disk location revealed no statistically significant differences. Conclusions: The use of DECT dedicated color-coded fat map reconstructions showed high diagnostic performance in the assessment of lumbar disk herniations compared to MRI. These findings support the development of dedicated post-processing tools, facilitating the broader clinical adoption of spectral CT, especially in cases where MRI is contraindicated or less accessible. Full article

The aim of this study was the evaluation of egg quality between three different farming systems. Eggs collected from intensive (IS), extensive (ES), and dual-purpose systems (DPSs) at three stages of the production cycle (age) were analyzed for both external and internal traits. ISs represent high-input systems while ESs and DPSs represent low-input systems. Both the farming system and age had significant effects on quality characteristics. Eggs from the ES displayed a greater egg weight (64.3 ± 0.20 g) and shell weight (6.6 ± 0.03 g). Eggs from the IS farms displayed a higher Haugh unit score (83.2 ± 0.50), darker colored yolks (12.0 ± 0.06), and a lower incidence of blood spots (0.2 ± 0.05). The age and farming system influenced the fatty acid profile of eggs across farming systems. In particular, DPS eggs showed higher levels of unsaturated (62.2 ± 0.20%) and lower levels of saturated (37.8 ± 0.10%) fatty acids. The effect of age was also significant on the oxidation stability of yolks. The interaction effect (farming system × age) had significant effects on most traits. However, the farming system alone accounted for a greater portion of the variation in most egg quality parameters. Full article

Understanding how electromagnetic (EM) waves travel through different tissues is important for EM medical imaging, sensing, and in-body communication. It is known that EM waves in lossy bio-tissues are nonuniform and do not strictly follow the least time or least loss paths. Instead, they exhibit two distinct wavefronts: the phase wavefront and the amplitude wavefront, which are generally oriented at different angles. The impact of that on imaging and in-body communications is investigated and validated through comprehensive analysis and full-wave EM simulations. Additionally, the impact of a matching medium, commonly used to reduce antenna–skin interface reflections in medical EM applications, on the direction of EM wavefronts, travel time, phase changes, and attenuation is analyzed and quantified. The results show that the Fermat principle of least travel time, often used to estimate EM wave travel time for localization in medical imaging and wireless endoscopy, is only accurate when the loss tangent or dissipation factor of both the matching medium and tissues is very low. Otherwise, the results will be inaccurate, and the dual wavefronts should be considered. The presented analysis and results provide guidance on EM wave travel time and the direction of phase and amplitude wavefronts. This information is valuable for developing reliable processing algorithms for sensing, imaging, and in-body communication. Full article

Background/Objectives: Decision-making under socially evaluative stress engages a dynamic interplay between cognitive control, emotional appraisal, and motivational systems. Contemporary models of multi-level co-regulation posit that these systems operate in reciprocal modulation, redistributing processing resources to prioritise either rapid socio-emotional alignment or deliberate evaluation depending on situational demands. Methods: Adopting a neurofunctional approach, a novel dual-task protocol combining the MetaCognition–Stress Convergence Paradigm (MSCP) and the Social Stress Test Neuro-Evaluation (SST-NeuroEval), a simulated social–evaluative speech task calibrated across progressive emotional intensities, was implemented. Twenty professionals from an HR consultancy firm participated in the study, with concurrent recording of frontal-temporoparietal electroencephalography (EEG) and bespoke psychometric indices: the MetaStress-Insight Index and the TimeSense Scale. Results: Findings revealed that decision contexts with higher socio-emotional salience elicited faster, emotionally guided choices (mean RT difference emotional vs. cognitive: −220 ms, p = 0.026), accompanied by oscillatory signatures (frontal delta: F(1,19) = 13.30, p = 0.002; gamma: F(3,57) = 14.93, p ≤ 0.001) consistent with intensified socio-emotional integration and contextual reconstruction. Under evaluative stress, oscillatory activity shifted across phases, reflecting the transition from anticipatory regulation to reactive engagement, in line with models of phase-dependent stress adaptation. Across paradigms, convergences emerged between decision orientation, subjective stress, and oscillatory patterns, supporting the view that cognitive–emotional regulation operates as a coordinated, multi-level system. Conclusions: These results underscore the importance of integrating behavioural, experiential, and neural indices to characterise how individuals adaptively regulate decision-making under socially evaluative stress and highlight the potential of dual-paradigm designs for advancing theory and application in cognitive–affective neuroscience. Full article

This study investigated the effect of piranha solution etching duration on the shear bond strength of zirconia ceramics bonded to resin cement, comparing it to conventional sandblasting treatment. Fifty fully sintered zirconia specimens (6.0 mm diameter, 4.0 mm thickness) were prepared and randomly divided into five groups (n = 10): sandblasting control and piranha solution treatment for 1, 2, 3, and 4 min. Piranha solution was prepared by mixing 98% H₂SO₄ and 35% H₂O₂ in a 3:1 ratio. All specimens were bonded to resin composite cylinders using dual-cure resin cement. Shear bond strength testing was performed using a universal testing machine at a 0.5 mm/min crosshead speed. Failure modes were analyzed using a stereomicroscope and classified as adhesive, cohesive, or mixed failures. One-way ANOVA revealed significant differences between groups (p < 0.05). Tukey’s post hoc test showed that 1-min piranha treatment produced significantly lower bond strength (7.64 ± 2.02 MPa) compared to all other groups. The 2-min (15.17 ± 2.79 MPa), 3-min (14.99 ± 3.27 MPa), and 4-min (18.34 ± 3.15 MPa) piranha treatments showed no significant differences compared to sandblasting (15.41 ± 2.61 MPa). Failure mode analysis revealed 100% adhesive failures for the 1-min group, while all other groups showed 80% adhesive and 20% mixed failures. Piranha solution treatment duration significantly affected zirconia bonding performance. While 1-min treatment proved inadequate, 2–4 min treatments achieved bond strengths comparable to sandblasting. The findings suggest that piranha solution treatment for 2–4 min represents a viable alternative to sandblasting for zirconia surface preparation, with the 2-min protocol being the most efficient choice for clinical application. Full article

Background: Nurse-manager competencies shape workforce stability, yet role-based perception gaps between managers and staff may influence staff nurses’ turnover cognitions. Objectives: To (1) compare nurse managers’ self-ratings with staff nurses’ ratings of the same managers on the Nurse Manager Competency Inventory (NMCI); (2) compare both groups’ perceptions of staff nurses’ turnover intention (EMTIS); (3) examine domain-specific links between perceived competencies and perceived turnover intention; and (4) explore demographic influences (age, education, experience) on these perceptions. Methods: Cross-sectional dual-rater study with 225 staff nurses and 171 nurse managers in two tertiary hospitals in Saudi Arabia. Data were collected from August to November 2024. Managers completed NMCI self-ratings, and staff nurses rated their managers on the same NMCI domains; both groups rated staff nurses’ turnover intention using EMTIS. Between-group differences were tested with one-way ANOVA (two-tailed α = 0.05), and associations were examined with Pearson’s r (95% CIs). Findings: Managers consistently rated themselves higher than staff rated them across all nine NMCI domains; the largest descriptive gaps were in Promoting Staff Retention, Recruit Staff, Perform Supervisory Responsibilities, and Facilitate Staff Development (e.g., overall NMCI: managers M = 3.67, SD = 0.61 vs. staff M = 3.04, SD = 0.74; F = 0.114, p = 0.73)with comparatively smaller divergence for Ensure Patient Safety and Quality. Managers and staff did not differ significantly on EMTIS (overall EMTIS: managers M = 3.16, SD = 1.28 vs. staff M = 3.00, SD = 1.15; F = 21.32, p = 0.173). Specific competency domains—retention, supervision, staff development, safety/quality leadership, and quality improvement—showed small inverse correlations with EMTIS facets (typical r ≈ −0.11 to −0.19; p < 0.05), whereas the global NMCI–overall EMTIS correlation was non-significant (r = −0.077, p = 0.124). Effect sizes were modest and should be interpreted cautiously. Conclusions: Actionable signals reside at the domain (micro-competency) level rather than in global leadership composites. Targeted, continuous, unit-embedded development in human- and development-focused competencies—tracked with dual-lens (manager–staff) measurement and linked to retention KPIs—may help nudge turnover cognitions downward. Key limitations include the cross-sectional, perception-based design and two-site setting. Findings nonetheless align with international workforce challenges and may be transferable to similar hospital contexts. Full article

To address the limitations of traditional cotton leaf nitrogen content estimation methods, which include low efficiency, high cost, poor portability, and challenges in vegetation index acquisition owing to environmental interference, this study focused on emerging non-destructive nutrient estimation technologies. This study proposed an innovative method that integrates multi-color space fusion with deep and machine learning to estimate cotton leaf nitrogen content using smartphone-captured digital images. A dataset comprising smartphone-acquired cotton leaf images was processed through threshold segmentation and preprocessing, then converted into RGB, HSV, and Lab color spaces. The models were developed using deep-learning architectures including AlexNet, VGGNet-11, and ResNet-50. The conclusions of this study are as follows: (1) The optimal single-color-space nitrogen estimation model achieved a validation set R² of 0.776. (2) Feature-level fusion by concatenation of multidimensional feature vectors extracted from three color spaces using the optimal model, combined with an attention learning mechanism, improved the validation R² to 0.827. (3) Decision-level fusion by concatenating nitrogen estimation values from optimal models of different color spaces into a multi-source decision dataset, followed by machine learning regression modeling, increased the final validation R² to 0.830. The dual fusion method effectively enabled rapid and accurate nitrogen estimation in cotton crops using smartphone images, achieving an accuracy 5–7% higher than that of single-color-space models. The proposed method provides scientific support for efficient cotton production and promotes sustainable development in the cotton industry. Full article

Global efforts to achieve carbon neutrality increasingly rely on institutional green policy that reshape corporate environmental behavior. This study examines whether green policy improves corporate environmental performance (EP). Using panel data of the A-share listed firms from 2010 to 2022, we exploit the rollout of pilot cities as a quasi-natural experiment and apply a difference-in-differences (DID) framework, supplemented by double machine learning (DML) and robustness tests. The results show that the New Energy Demonstration City (NEDC) policy notably increases EP, with stronger effects for state-owned enterprises, large firms, and regulated industries. Mechanism analysis indicates that artificial intelligence innovation capacity and the stringency of regional environmental regulation amplify the policy’s effectiveness, revealing a “innovation–regulation” dual mechanism. By focusing on integrated EP rather than single outcomes, this paper extends the literature on green policy instruments. It demonstrates that structural policies combining fiscal incentives and regulatory constraints can correct market failures and foster long-term green transition. Beyond China, the findings provide insights for other developing economies where market-based instruments alone may be insufficient to trigger low-carbon transformation. Full article

Identifying hospitals that disproportionately serve minority and publicly insured patients is important because patients at these hospitals often experience worse outcomes. Studies commonly identify disproportion by using the top decile of hospitals with the greatest proportion of Black discharges nationally. Our study aimed to identify a broader measure that accounts for disproportion by multiple characteristics. Using fee-for-service Medicare data, we classified hospitals as either serving disproportionately or not, examined overlaps in classification, and assessed differences in hospital quality. We found that using a combined measure for any hospitals in the top decile or above a threshold of twice their local healthcare market average of Black, Hispanic, minority, or dual-eligible discharges classified 28.1% (n = 680/2420) of hospitals as serving disproportionately, compared to only 10% (n = 242/2420) when using the top decile of a single characteristic. The combined measure detected moderate differences in hospital star quality ratings (mean difference of 0.57–0.87, all p-values < 0.000; standardized mean difference: 0.50–0.79, 95% CIs all above 0). The combined measure identified hospitals that were smaller, more rural, and served other minorities, namely, Asian and American Indian populations. Future work should consider using this combined measure to more comprehensively identify hospitals that disproportionately serve minority or publicly insured patients. Full article

We report the simultaneous generation of conventional solitons (CSs) and dissipative solitons (DSs) in an erbium-doped mode-locked fiber laser with a dual-branch cavity configuration based on the nonlinear polarization rotation (NPR) technique. By incorporating fibers with different dispersion properties in two propagation branches, the laser can establish simultaneous operation in the normal and anomalous dispersion regimes within the respective loops, enabling the generation of two distinct soliton types. The CSs exhibit a 3 dB spectral bandwidth of 9.7750 nm and a pulse duration of 273 fs, while the DSs have a quasi-rectangular spectrum spanning 18.7074 nm and a pulse duration of 2.2 ps, which can be externally compressed to 384 fs. The fundamental repetition rate is approximately 21 MHz, with a repetition rate difference of 216 Hz for the two pulse trains. Stable second-order, third-order, and fourth-order harmonic mode-locking (HML) can be achieved through optimization of pump power and intracavity polarization states. The laser we build in this work has significant potential for applications in high-precision spectroscopy and asynchronous optical sampling. Full article

Background: Total hip arthroplasty (THA) is a common procedure, yet instability and dislocation remain leading causes of revision. Dual mobility (DM) acetabular constructs improve stability, but comparative data across modular DM systems are limited. This study compared the safety and efficacy of three modular DM implants in primary THA, focusing on acetabular revision and functional recovery. Methods: We retrospectively reviewed 963 primary THAs performed from 2016–2024 using three modular DM systems. Patients with revision or bilateral THA, age < 18, or <2 years of follow-up were excluded. Outcomes included acetabular revision, 90-day readmission, and Hip Disability and Osteoarthritis Outcome Score for Joint Replacement (HOOS, JR). Kaplan–Meier analysis estimated 3-year implant survivorship for each implant, and non-inferiority of Implant A was tested against a combined “Dual Mobility Control” cohort (Implants B + C) using a prespecified −10% margin. Results: A total of 297 patients met inclusion criteria (142 Implant A, 110 Implant B, 45 Implant C). Revision rates were 4.9% for Implant A, 6.4% for Implant B, and 8.9% for Implant C. HOOS, JR scores improved significantly in all cohorts with comparable 2-year outcomes. Kaplan–Meier analysis showed 3-year survivorship of 98.3% for Implant A, 98.4% for Implant B, and 96.9% for Implant C (log-rank p = 0.053). The Dual Mobility Control cohort survivorship was 98.0%, and the difference between Implant A and controls (95% CI: −2.19% to 2.69%) met the non-inferiority margin (log-rank p = 0.796). Conclusions: Implant A demonstrated non-inferior 3-year survivorship and comparable short-term patient-reported outcomes relative to two other modular DM implants. Larger, multicenter studies with longer follow-up are warranted to confirm these findings. Full article

Background/Objectives: While oral nutritional supplements (ONSs) are known to support general growth in undernourished children, their specific effects on body composition and bone health remain underexplored. This manuscript evaluates the impact of ONS combined with dietary counselling (DC) on these outcomes in Indian children aged 3 to 6.9 years at nutritional risk, within the framework of a larger randomized controlled trial assessing multiple growth parameters. Methods: This prospective, randomized controlled trial was conducted among Indian children, both male and female participants with picky eating habits and at risk of undernutrition, aged 3 to 6.9 years (height-for-age and weight-for-height below the 25th percentile per WHO Growth Standards and Growth Reference). Participants were randomized in a 1:1 ratio to receive either ONS + DC or DC alone for 6 months. Body composition, bone mineral density (BMD), and bone mineral content (BMC) were measured using dual-energy X-ray absorptiometry (DXA) at baseline and after 6 months. Group differences were analyzed to evaluate intervention effects. Results: A total of 223 children were enrolled and randomized. At 6 months, the test group showed significantly greater improvements in BMD (0.023 g/cm²) compared to the control (0.017 g/cm²; p = 0.004), and a greater gain in BMC (36.60 g vs. 28.48 g; p =0.0007). Lean mass increased significantly more in the test group (926.33 g) versus the control (801.48 g; p = 0.0401). Fat mass showed a numerical reduction in the test group (−171.42 g) compared with the control group (−114.60 g), although this difference was not statistically significant. Conclusions: These findings highlight the potential of targeted nutritional interventions to favorably improve body composition and bone health during critical growth periods in undernourished children, offering a promising approach to address early-life nutritional deficits with lasting health benefits. Full article