Browse Articles

A novel approach to coincidence point results via proximal contractions with application

Root mixing effects on belowground decomposition depend on mycorrhizal type

Abstract While there has been significant progress in understanding how species mixing affects leaf litter decomposition, the consequences for belowground root decomposition remains less known. This represents a critical knowledge gap, as roots are key contributors to soil carbon input. Here, we experimentally assess absorptive root decomposition in 138 paired-species combinations from 57 tree species, revealing significant non-additive mixing effects in 70% of all root combinations, with the majority of them decomposing faster than predicted from single species. Notably, non-additive effects occur only in mixtures containing at least one ectomycorrhizal species, with no net mixture effects in combinations of two arbuscular mycorrhizal species. We further find that these root mixing effects are associated with dissimilarities in condensed tannins across all mycorrhizal types and with nitrogen concentration when only ectomycorrhizal species are present. Overall, these root mixing effects are three times stronger than those documented for leaf litter decomposition in past studies. Collectively, our findings suggest that tree species mixing effects on decomposition are particularly robust belowground, especially in forests with ectomycorrhizal species of contrasting root chemistry. Absorptive root decomposition may have an essential role in how tree species mixing affects soil carbon and nutrient dynamics.

Advanced deep learning techniques for automated license plate recognition

Abstract This research improves the capacity of automated license plate recognition (ALPR) to meet not only the needs of its methodology but also those it is confronted with in everyday situations. By combining YOLOv10 with a specially customized Tesseract OCR engine, the aim was to achieve the recognition of the Thai–Roman mixed-script car license plates, which represents a difficult and scarcely resolved problem in the literature. To ensure the system can be thoroughly tested in a wide range of scenarios, we have assembled a large-scale dataset that comprises 50,000 images and 10,000 video clips depicting different lighting and weather conditions. We have tested real-time capability on Jetson Nano and our results support the possibility of scaling for intelligent transportation systems. Comparing our experiments to the results of the latest detectors (YOLOv5, YOLOv8, YOLOv9, Faster R-CNN, SSD), we find that YOLOv10 consistently gives better results with detection accuracy of 99.16%, an F1-score of 0.992, and an inference time of 1.0 ms/image, while under severe conditions there is no significant decrease of performance. In sum, these empirical results turn the proposed system into a both novel and practical contribution for regionally adaptive ALPR research.

SEPT9 methylation as a diagnostic and predictive biomarker in the progression of ductal carcinoma in situ to invasive breast cancer

Palladium-catalyzed enantioselective dienylation of propargylic carbonates via sulfonimidamide desymmetrization

Integrated use of meteorological and hydrological indices for drought early warning in the mountainous catchments of the Himalaya-Karakorum-Hindukush region

Interpretable machine learning analysis of clinicopathological and immunonutritional biomarkers for predicting lymph node metastasis in gastric cancer

Thermally programmed one-pot CRISPR assay for on-site pandemic surveillance

Investigation of the North Face Corridor in the Great Pyramid of Giza using Electrical Resistivity Tomography

Abstract Despite some impressive examples of Electrical Resistivity Tomography (ERT) characterizing the internal structure of historical monuments, ERT is rarely considered a primary method for this purpose because it is challenging to adjust measurement procedures and inversion techniques for such intricate objects. In this study, ERT was first applied in the Great Pyramid of Giza to detect the presence of the ScanPyramids North Face Corridor (SP-NFC). The ERT measurement technique and data analysis procedure were adapted for this case, which was characterized by complex surface topography and limited space for placing ERT lines. A 3D CAD model of the Chevron area was designed for inversion based on a 3D point cloud. The inversion results show the existence of the SP-NFC, with average dimensions of approximately 2.5 m by 2.5 m, starting at a depth of around 1 m and extending at least 2 m into the pyramid. The ERT study thus provided volumetric data confirming both the size and extent of the SP-NFC, complementing the ground-penetrating radar (GPR) and ultrasound tomography (UST) studies conducted simultaneously in the Chevron area.

An efficient federated learning based defense mechanism for software defined network cyber threats through machine learning models

Strength-plasticity synergy from ambient to high temperature via gradient-ordering in boride-reinforced WTaV medium-entropy alloy

Multimorbidity, disease clusters and risk of all-cause and cause-specific mortality: a population-based prospective cohort study

Abstract The number of people living with ≥ two health conditions, termed multimorbidity, is increasing. We investigated the impact of multimorbidity on all-cause and cause-specific mortality risk in 502,370 UK Biobank participants aged 40 to 70 years. Participants attended an assessment centre between 2006 and 2010 and self-reported medical conditions during a nurse-led verbal interview. The presence of ≥ 2 long-term conditions from a preselected list of 43 conditions was used to define multimorbidity. In a training sample (80% of participants with multimorbidity), disease clusters were identified in four groups: women aged (1) 40–59 or (2) 60–70, and men aged (3) 40–59 or (4) 60–70. Mortality was ascertained from linkage to death records. Multivariate Cox proportional-hazards regression models were used to assess the association between multimorbidity and mortality adjusted for age, sex, ethnicity, socioeconomic status and education. Over a 16-year follow-up period (median = 13 years) dose–response associations were observed between number of multimorbid conditions and risk of all-cause mortality (n = 44,399 deaths), and particularly strong dose-response associations with cause-specific deaths due to cardiovascular and respiratory conditions. For women, a mental health/cancer/pain-related conditions cluster at ages 40–59 (Hazard Ratio [HR] = 2.61, 95% Confidence Interval [CI] 2.33–2.93), and a respiratory and pain-related conditions cluster at ages 60–70 (HR = 2.03, 95% CI 1.0–2.17), were associated with the greatest risk of mortality. For men, clusters of cardiometabolic conditions at ages 40–59 (HR = 3.43, 95% CI 3.14–3.74) and 60–70 (HR = 2.24, 95% CI 2.13–2.35) were associated with greater mortality risk. These findings suggest that understanding the impact of multimorbidity, and especially clusters of disease, is important for tailoring healthcare approaches for mortality risk reduction.

Effect of adding gonadotropin-releasing hormone agonists for luteal support in antagonist cycles on pregnancy outcomes

An integrated platform for liquid handling and cell imaging in life science applications

Exploring the predictive values of ABSI and BRI in premature coronary artery disease based on a real world study

Ex vivo perfusion recellularization of acellular rat hindlimbs for vascular composite allotransplantation

The zinc finger of DNA ligase 3α binds to nucleosomes via an arginine anchor

DEM-FDM investigation of bedding plane properties’ impact on laminated roof stability

Spatial variation in risk factors for anti-hepatitis E antibody titers in a population-based German study

Abstract The transmission of hepatitis E virus (HEV) genotype 3 remains unclear. Up to date, it is predominantly considered a foodborne disease. However, there is growing evidence that other transmission pathways exist. The aim of this study was to analyze risk factors for anti-HEV IgG titers in the Study of Health in Pomerania, a population-based cohort located in Northeast Germany. We performed cross-sectional analyses using quantile and logistic regression. Spatial location was included as an interaction term to explore whether residential location of the participant acts as an effect modifier. The risk factors assessed were consumption frequency of meat, sausage, fish and raw vegetables, high-risk occupation and animal contact. The estimated seroprevalence of anti-HEV IgG was 27.3% (95% confidence interval [CI] 26.0%, 28.6%). Participants living in rural coastal areas had 14.5 U/ml higher antibody titers both for high meat (95% CI 3.9, 25.2; P  = 0.008) and high sausage consumption (95% CI 4.1, 24.9; P  = 0.006) in comparison with low consumption. In urban areas, participants who had contact with domestic carnivores had higher antibody titers (by 12.8 U/ml; 95% CI 0.3, 25.3; P  = 0.046). Our results imply that risk factors of HEV exposure might differ among geographical regions. More research is needed to clarify the mechanisms underlying these findings.

Imaging of electrically controlled van der Waals layer stacking in 1T-TaS2

Abstract Van der Waals materials exhibit a variety of states that can be switched with low power at low temperatures, offering a viable cryogenic ‘flash memory’ required for the classical control electronics for solid-state quantum information processing. In 1 T -TaS 2 , a non-volatile metallic ‘hidden’ state can be induced from an insulating equilibrium charge-density wave ground state using either optical or electrical pulses. Given that conventional memristors form localized, filamentary channels which support the current, a key question for design concerns the geometry of the conduction region in highly energy-efficient 1 T -TaS 2 devices. Here, we report in operando micro-beam X-ray diffraction, fluorescence, and concurrent transport measurements, allowing us to spatially image the non-thermal hidden state induced by electrical switching of 1 T -TaS 2 . The results reveal a long-range ordered switching region that extends well below the electrodes, implying that the self-organized, collective growth of the hidden phase is driven by charge rearrangement and concomitant lattice strain. Our combination of techniques showcases the potential of non-destructive, three-dimensional X-ray imaging to study bulk switching in microscopic detail, exemplified here by electrical control of the charge-density wave state of a van der Waals material.