Browse Articles

Seasonal assessment of water quality and major ion chemistry in the lower region of Lake Kariba, Zambia

2D grid map creation based on RGBD-camera and LiDAR data

A cadaveric feasibility study of the LM-B screw as a novel posterolateral C1 lateral mass to C2 vertebral body fixation trajectory

AI-enhanced soil classification with incomplete CPT data for offshore wind farm

Abstract Accurate soil classification is fundamental to offshore wind farm foundation design, yet conventional cone penetration test (CPT) based methods often require complete datasets that are costly and challenging to obtain in offshore environments. This study presents an artificial intelligence (AI) enhanced framework for soil classification based on the Robertson Classification, with a particular emphasis on robustness under incomplete CPT data. A comprehensive synthetic CPT database comprising 229,808 samples was generated using both uniform and statistically distributed sampling strategies to represent a wide range of realistic soil conditions. Among the four evaluated machine learning models, the random forest model achieved the best performance, with an R² of 0.99 and a classification accuracy of 92.53%. Simulations of missing CPT input parameters reveal that reliable predictions can be maintained even under incomplete data scenarios. Feature importance indicates that cone tip resistance ( q c ), sleeve friction ( f s ) and effective stress ( σ’ v ), are the dominant factors governing soil classification. Prediction uncertainty using Monte Carlo simulations shows model performance within a 95% confidence interval. Overall, the proposed AI-enhanced framework provides a robust and practical solution for CPT-based soil classification using incomplete datasets for offshore wind farm geotechnical design.

Hyperfine spectroscopy of optical-cycling transitions in singly ionized thulium

Abstract We present a spectroscopic investigation of $$^{169}\text {Tm}^+$$ that provides two key foundations for its use as a platform for advanced quantum applications. First, we establish the complete spectroscopic road map for optical cycling (including laser cooling) by performing high-resolution spectroscopy on $$^{169}\text {Tm}^+$$ ions in an ion trap. We characterize the primary 313 nm and complementary 448/453 nm cycling transitions, identify the essential near-infrared repumping frequencies, and determine the magnetic-dipole hyperfine A constants for all relevant levels. Second, we report a detailed characterization of a metastable state as a candidate for hosting a robust qubit, performing lifetime measurements and Zeeman-resolved microwave hyperfine spectroscopy with $$\textrm{kHz}$$ precision.

Near-surface geophysics: from measurements to reliable models

Acute physical activity supports inhibitory control in primary school children: a randomised cross-over trial

Abstract Studies have found inconsistent results regarding the acute effects of physical activity on inhibitory control in children. More naturalistic studies that have real-world validity and use objective measures of physical activity are essential. This study investigated the acute effects of a pre-existing school-based group physical activity session on inhibitory control. Fifty-five primary school children (9 ± 1 years old, 40% female) participated in a pre-existing school-based group physical activity session and a sedentary poster-making control condition, both lasting approximately 30 min, in a randomised, cross-over manner. Cognitive tasks were completed before and after both conditions, and measures of performance on these tasks were used as dependent variables in all analyses. Time engaged in moderate-to-vigorous physical activity during each condition was measured by accelerometry and used as a manipulation check. After physical activity there were faster reaction times (β = -176, 95%CI: -296.43, -59.51) and more commission errors (β = 1.06, 95%CI: 0.18, 1.95) in the simple reaction time task, but fewer commission errors (β = -4.64, 95%CI: -9.00 -0.28) in the inhibition task compared to the control condition. Using the same statistical approach, a supplementary analysis was run on a reduced sample of 32 (9 ± 1 years old, 44% female) whose adherence to conditions was confirmed by accelerometry. Results showed faster reaction times (β = -205, 95%CI: -384.58, -33.37) in the simple reaction time task and fewer commission errors (β = -6.10, 95%CI: -11.75, -0.45) in the inhibition task following physical activity. This suggests that an acute bout of physical activity facilitates inhibitory control in primary school children. Optimal effects are seen when participants achieved higher intensity physical activity during the intervention.

Epigenetic regulation of the glucocorticoid receptor gene through methylation is linked to post-traumatic stress disorder

Unconventional superconductivity in the presence of long-range interactions in transition metal dichalcogenide moiré heterobilayers

Evidence of a putative new species Haemagogus ‘Trinidad sp. A’ from the Caribbean sharing mitogenome lineages with species endemic to the Amazon

A multi-strategy framework for enhancing Harris hawks optimization for global optimization problems

Deep learning for incidence rate prediction and radiation risk assessment of solid tumors

M2 macrophages predict response to neoadjuvant chemotherapy in triple negative breast cancer patients

Investigating the impact of electric vehicles on increasing the reliability of the distribution system using the enhanced gray wolf evolutionary algorithm model

The association of TyG-BMI with MAFLD and liver fibrosis: a cross-sectional study

Early detection of construction project risks in Saudi Arabia: a mixed-methods study on warning signs and mitigation

Short-term physiological effects of pressure rise time modulation during volume-guaranteed neonatal ventilation

Abstract Pressure rise time (PRT) is an adjustable ventilator parameter that regulates the rate of inspiratory flow delivery and may influence ventilator mechanics and tissue oxygenation. However, its short-term physiological effects in neonates receiving volume-targeted ventilation remain incompletely characterized. Seventeen hemodynamically stable neonates receiving assist-control volume guarantee (AC-VG) and pressure support volume guarantee (PSV-VG) ventilation were studied using three different PRT settings (0.10, 0.20, and 0.30 s), each applied for 20-minute periods. Ventilator parameters, peripheral oxygen saturation (SpO₂), and cerebral regional oxygen saturation (CrSO₂) measured by near-infrared spectroscopy (NIRS) were continuously monitored. During AC-VG ventilation, modulation of PRT did not result in significant changes in ventilator parameters or oxygenation. During PSV-VG ventilation, peak inspiratory pressure increased with longer PRTs, while mean airway pressure, SpO₂, and CrSO₂ remained unchanged. In this short-term physiological study, modulation of pressure rise time influenced selected ventilator mechanics without producing significant changes in peripheral or cerebral oxygenation under stable clinical conditions. Larger prospective studies incorporating longer observation periods and clinically relevant outcomes are required to further define the role of pressure rise time adjustment in neonatal mechanical ventilation. Trial registration: This study was retrospectively registered at ClinicalTrials.gov (Identifier NCT07465237).

Conformable Fractional Deep Neural Networks (CFDNN) for high-speed cyber-attack detection

Abstract The growing sophistication of cyber-attacks exposes the limitations of conventional deep neural networks, which often suffer from slow convergence and high computational costs. This paper introduces the Conformable Fractional Deep Neural Network (CFDNN), a framework that replaces standard backpropagation with conformable fractional gradient descent. By operating in the super-integer regime ( $$\alpha \in [1.2, 1.8]$$ ), the model smooths the loss landscape to accelerate training. Evaluated on NSL-KDD and CIC-IDS2018 using cross-validation, the CFDNN achieves 99.42% and 99.86% accuracy, respectively. It attains these results in just 30 epochs–a 40% reduction in training time. On the large-scale CIC-IDS2018 dataset, the model converged in approximately 24.2 minutes on a system equipped with an standard CPU. The CFDNN thus provides a computationally efficient, high-performance alternative to classical methods, offering a robust solution for modern cyber-defense.

CSF1 regulates inflammation and apoptosis in intervertebral disc degeneration

Quality and reliability of femoral neck fracture educational short videos: a cross-sectional study

Background: Femoral neck fracture (FNF) patients increasingly use short-video platforms (TikTok, Bilibili) for education, but content quality and reliability are underexplored. Objective: To systematically evaluate FNF-related educational short videos on TikTok and Bilibili, and explore associations between video characteristics, user engagement, and quality scores. Methods: This cross-sectional study analyzed 166 top-ranked videos (accessed in May 2025 as guest users) using modified DISCERN, Global Quality Score (GQS), the newly developed Femoral Neck Fracture-Specific Clinical Comprehensiveness Score (FNF-SCCS), and Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V). Videos were categorized by uploader type and content theme; non-parametric statistics, Cohen’s kappa, and Intraclass Correlation Coefficient (ICC) assessed associations and inter-rater reliability. Results: Professionals created 59.04% of content, non-professionals 25.9%. Bilibili videos were longer (162s vs. 59s, P  < 0.05) and higher-quality (GQS ≥ 4: 43.7% vs. 12.6%; DISCERN ≥ 4: 40.9% vs. 23.2%, P  < 0.05). Disease knowledge and rehabilitation training videos scored highest (DISCERN = 4, GQS = 4), personal experiences lowest (DISCERN = 2, GQS = 2). FNF-SCCS (ICC = 0.91) and PEMAT-A/V (ICC = 0.89) showed excellent inter-rater reliability; professional institutions/individuals outperformed non-professionals in FNF-SCCS and PEMAT understandability (Median = 75.0% vs. 58.3%, P  < 0.001), while overall actionability was low except for rehabilitation training videos (Median = 100.0%). Engagement weakly correlated with quality ( r =-0.21–0.08); Cohen’s kappa = 0.806–0.839. Conclusions: FNF-related content on TikTok and Bilibili exhibits suboptimal quality, with professional sources outperforming non-professional ones. Critical gaps exist in guideline adherence and actionable instructions. Platforms and healthcare professionals should optimize medical content dissemination.