Search Results (616)

To overcome the low accuracy of conventional methods for estimating liquid volume and food nutrient content in bowl-type tableware, as well as the tool dependence and time-consuming nature of manual measurements, this study proposes an integrated approach that combines geometric reconstruction with deep learning–based segmentation. After a one-time camera calibration, only a frontal and a top-down image of a bowl are required. The pipeline automatically extracts key geometric information, including rim diameter, base diameter, bowl height, and the inner-wall profile, to complete geometric modeling and capacity computation. The estimated parameters are stored in a reusable bowl database, enabling repeated predictions of liquid volume and food nutrient content at different fill heights. We further propose Bowl Thick Net to predict bowl wall thickness with millimeter-level accuracy. In addition, we developed a Geometry-aware Feature Pyramid Network (GFPN) module and integrated it into an improved Mask R-CNN (Region-based Convolutional Neural Network) framework to enable precise segmentation of bowl contours. By integrating the contour mask with the predicted bowl wall thickness, precise geometric parameters for capacity estimation can be obtained. Liquid volume is then predicted using the geometric relationship of the liquid or food surface, while food nutrient content is estimated by coupling predicted food weight with a nutritional composition database. Experiments demonstrate an arithmetic mean error of −3.03% for bowl capacity estimation, a mean liquid-volume prediction error of 9.24%, and a mean nutrient-content (by weight) prediction error of 11.49% across eight food categories. Full article

During deepwater completion and testing, the platform and riser system are subjected to long-term motions induced by ocean currents, which may cause structural damage and potential failure of the landing string. This study investigates the mechanical and fatigue performance of a subsea Christmas tree and landing string under environmental conditions of the LH11-1 Oilfield in the South China Sea. A global–local simulation framework is used to build a coupled dynamic model of the riser–landing string system and a local model for the landing string, considering load-transfer characteristics, current profiles, periodic features, and two representative environmental conditions (typhoon and non-typhoon). For seventeen typical operating scenarios, the strength of the riser–landing string system is evaluated, and wave-induced and vortex-induced fatigue analyses are performed for the key components. The stress distribution strongly depends on operating conditions, but local strength results confirm that stresses in the primary landing string components remain below allowable limits in all scenarios. Fatigue analysis indicates that the most severe wave-induced damage in the riser occurs at its bottom section, with a fatigue life of about 15.12 years, while in the landing string, it is concentrated near the lower end, with an estimated life of about 52.68 years. The maximum vortex-induced fatigue damage occurs near the riser surface region, with a corresponding fatigue life of about 18.52 years. Full article

Soil erosion in the hilly and gully region of the middle reaches of the Yellow River is severe, threatening regional ecological security and the water–sediment balance of the Yellow River. The area features fragmented topography and significant spatial heterogeneity in soil thickness, forming a unique binary “soil–rock” structural system. The soil in the study area is characterized by silt-based loess, and the underlying bedrock is an interbedded Jurassic-Cretaceous sandstone and sandy shale. It has strong weathering, well-developed fissures, and good permeability, rather than dense impermeable rock layers. However, the spatiotemporal differentiation mechanism of soil moisture in this system remains unclear. This study focuses on the typical hilly and gully region—the Geqiugou watershed. Through field investigations, soil thickness sampling, multi-scale soil moisture monitoring, and analysis of meteorological data, it systematically examines the cascade relationships among microtopography, soil–rock combinations, soil moisture, and meteorological drivers. The results show that: (1) Based on the field survey of 323 sampling points in the study area, it was found that soil samples with a thickness of less than 50 cm accounted for 85%, which constituted the main structure of soil thickness in the region. Macrotopographic units control the spatial differentiation of soil thickness, forming a complete thickness gradient from erosional units (e.g., Gully and Furrow) to depositional units (e.g., Gently sloped terrace). Based on this, five typical soil–rock combination types with soil thicknesses of 10 cm, 30 cm, 50 cm, 70 cm, and 90 cm were identified. (2) Soil–rock combination structures regulate the vertical distribution and seasonal dynamics of soil moisture. In thin-layer combinations, soil moisture is primarily retained within the shallow soil profile with higher dynamics, whereas in thick-layer combinations, under conditions of substantial rainfall, moisture can percolate deeply and become notably stored within the fractured bedrock, sometimes exceeding the moisture content in the overlying soil. (3) The response of soil moisture to precipitation is hierarchical: light rain events only affect the surface layer, whereas heavy rainfall can infiltrate to depths below 70 cm. Under intense rainfall, the soil–rock interface acts as a rapid infiltration pathway. (4) The influence of meteorological drivers on soil moisture exhibits vertical differentiation and is significantly modulated by soil–rock combination types. This study reveals the critical role of microtopography-controlled soil–rock combination structures in the spatiotemporal differentiation of soil moisture, providing a scientific basis for the precise implementation of soil and water conservation measures and ecological restoration in the region. Full article

The extraction of the light stripe center is a pivotal step in line-structured light vision measurement. This paper addresses a key challenge in the online measurement of train wheel treads, where the diverse and complex profile characteristics of the tread surface lead to uneven gray-level distribution and varying width features in the stripe image, ultimately degrading the accuracy of center extraction. To solve this problem, a region-adaptive multiscale method for light stripe center extraction is proposed. First, potential light stripe regions are identified and enhanced based on the gray-gradient features of the image, enabling precise segmentation. Subsequently, by normalizing the feature responses under Gaussian kernels with different scales, the locally optimal scale parameter (σ) is determined adaptively for each stripe region. Sub-pixel center extraction is then performed using the Hessian matrix corresponding to this optimal σ. Experimental results demonstrate that under on-site conditions featuring uneven wheel surface reflectivity, the proposed method can reliably extract light stripe centers with high stability. It achieves a repeatability of 0.10 mm, with mean measurement errors of 0.12 mm for flange height and 0.10 mm for flange thickness, thereby enhancing both stability and accuracy in industrial measurement environments. The repeatability and reproducibility of the method were further validated through repeated testing of multiple wheels. Full article

Background: Early molecular changes on the facial skin surface during early adulthood remain insufficiently characterized. We integrated biophysical readouts with untargeted skin surface lipid (SSL) profiling to identify region-dependent, age-associated features in women with combination skin. Methods: Eighty healthy Chinese women were stratified into 22–28 years (n = 40) and 29–35 years (n = 40). Sebum was measured on the cheek and forehead; cheek elasticity, hydration (CM), transepidermal water loss (TEWL), pH, and tone indices were assessed under standardized conditions. SSLs from both regions were profiled by UPLC–QTOF–MS. Differential features were prioritized using OPLS-DA (VIP > 1) with univariate screening (p < 0.05; fold change > 2 or <0.5). Results: TEWL, CM, and pH were comparable between age groups, whereas the older group showed lower cheek elasticity and reduced sebum. Lipidomics revealed clearer remodeling on the cheek than the forehead: 30 and 59 differential SSL features were identified in the cheek and forehead, respectively. Cheek changes in the older group were characterized by lower ceramides (including acylceramides), TG/DG and long-chain fatty acids, alongside relatively higher cholesteryl esters. Conclusions: Conventional barrier indices remained largely stable across this age window, while cheek SSL profiles captured earlier molecular shifts, providing candidates for targeted validation and longitudinal follow-up. Full article

Background: Device-detected subclinical atrial fibrillation (SCAF) and atrial high-rate episodes (AHRE) are increasingly recognized in patients with cardiac implantable electronic devices and through long-term rhythm monitoring. Although often asymptomatic, these episodes are associated with a higher risk of clinical atrial fibrillation (AF), stroke, and heart failure. Aims: This narrative review summarizes clinical, electrocardiographic, echocardiographic, and circulating biomarkers associated with the development and progression of device-detected SCAF/AHRE. Methods: We performed a comprehensive search of PubMed, Embase, and Scopus using combinations of the terms “subclinical atrial fibrillation”, “atrial high-rate episodes”, “device-detected AF”, “predictive factors”, “P-wave morphology”, “echocardiographic parameters”, “left atrial strain”, and “biological markers”. We included English-language-only studies of patients with cardiac implantable electronic devices or long-term monitoring and reporting incident SCAF/AHRE or AF as outcomes, published in the last 10 years. Results: Older age, high body mass index, heart failure, obstructive sleep apnea, and C₂HEST score are consistently associated with SCAF. On-surface electrocardiogram (ECG) and device electrograms, prolonged and dispersed P-wave indices, low atrial sensing amplitude, and specific pacing configurations, particularly right ventricular apical pacing with wide QRS, predict incident and longer-lasting AHRE. Echocardiographic markers of atrial cardiomyopathy, including increased left atrial volume and impaired atrial strain, together with indices of left ventricular diastolic dysfunction, further refine risk. Among circulating biomarkers, galectin-3 and high-sensitivity C-reactive protein show the most reproducible associations with incident AHRE. Conclusions: A multiparametric approach combining clinical profile, ECG features, advanced echocardiography, and selected biomarkers may improve identification of patients at risk for device-detected SCAF. Further prospective studies are needed to define risk thresholds that justify intensified rhythm surveillance and early initiation of anticoagulation or rhythm control strategies, especially in AHRE shorter than 24 h. Full article

Artificial intelligence (AI) is becoming more and more integrated into manufacturing processes, revolutionizing conventional production, like CNC (Computer Numerical Control) machining. This study analyzes how large language models (LLMs), exemplified by ChatGPT, behave when tasked with G-code optimization for improving surface quality and productivity of automotive metal parts, with emphasis on systematically documenting failure modes and limitations that emerge when general-purpose AI encounters specialized manufacturing domains. Even if software programming remains essential for highly regulated sectors, free AI tools will be increasingly used due to advantages like cost-effectiveness, adaptability, and continuous innovation. The condition is that there is sufficient technical expertise available in-house. The experiment carried out involved milling three identical parts using a Haas VF-3 SS CNC machine. The G-code was generated by SolidCam and was optimized using ChatGPT considering user-specified criteria. The aim was to improve the quality of the part’s surface, as well as increase productivity. The measurements were performed using an ISR C-300 Portable Surface Roughness Tester and Axiom Too 3D measuring equipment. The experiment revealed that while AI-generated code achieved a 37% reduction in cycle time (from 2.39 to 1.45 min) and significantly improved surface roughness (Ra—arithmetic mean deviation of the evaluated profile—decreased from 0.68 µm to 0.11 µm—an 84% improvement), it critically eliminated the pocket-milling operation, resulting in a non-conforming part. The AI optimization also removed essential safety features including tool length compensation (G43/H codes) and return-to-safe-position commands (G28), which required manual intervention to prevent tool breakage and part damage. Critical analysis revealed that ChatGPT failures stemmed from three factors: (1) token-minimization bias in LLM training leading to removal of the longest code block (31% of total code), (2) lack of semantic understanding of machining geometry, and (3) absence of manufacturing safety constraints in the AI model. This study demonstrates that current free AI tools like ChatGPT can identify optimization opportunities but lack the contextual understanding and manufacturing safety protocols necessary for autonomous CNC programming in production environments, highlighting both the potential, but also the limitation, of free AI software for CNC programming. Full article

Innate-like T cells (iLTCs) are rapid sentinels at epithelial surfaces, yet their spatial organisation and tissue-linked programmes in psoriatic inflammation remain incompletely defined. Spatial transcriptomics from independent cohorts maps γδT and mucosal-associated invariant T cells (MAIT) niches across psoriatic skin and reveals sharply divergent skin-layer arrangements. Psoriatic plaques show expansion of both niches, with γδT transcriptional signatures present in dermis and epidermis and MAIT signatures strongly enriched in the epidermis. Their compartment-specific positioning is mirrored by distinct transcriptional activities that support dermal-sentinel behaviour for γδT-enriched niches and epithelial-retention programmes for MAIT niches. Clinical severity associates with opposite niche dynamics, marked by decreasing dermal γδT frequencies and increasing epidermal MAIT abundance. Functional profiles reinforce this divergence, as dermal γδT niches display rising exhaustion-associated features with greater severity, whereas epidermal MAIT niches show stronger inflammatory and proliferation-related signals. Peripheral CITE-seq profiling identifies parallel systemic patterns, with reduced γδT frequencies and increased MAIT frequencies in blood, along with exhaustion-associated features in γδT cells and MAIT-specific trafficking cues that align with their behaviour in psoriatic tissue. Together the findings define a spatially imbalanced γδT–MAIT axis in psoriatic inflammation that is linked to layer-specific organisation to local inflammatory cues, systemic immune engagement and clinical severity. Full article

Chalcone-based derivatives were designed as dual-acting ligands targeting the histamine H₃ receptor (H₃R) and monoamine oxidase B (MAO-B), based on the lead compound DL76. Three series of compounds (1–18) were synthesised and characterised, including simple chalcones (1–9) and piperidinyl chalcones (10–18). All piperidinyl derivatives exhibited nanomolar affinity for human H₃R (hH₃R), with compounds 10–12 achieving K_i values ≤ 30 nM. Simple chalcones showed potent human MAO-B (hMAO-B) inhibition (IC₅₀: 0.85–337 nM), especially 3,4-dichloro derivatives. Compound 15 was the most active hybrid, with a K_i of 46.8 nM for hH₃R and an IC₅₀ of 212.5 nM for hMAO-B. Molecular docking and 250 ns simulations revealed stabilising interactions at both binding sites and clarified structural features behind dual activity. Preliminary ADMET profiling showed low Caco-2 permeability and rapid microsomal metabolism, mainly via hydroxylation. Compound 15 exhibited micromolar cytotoxicity in SH-SY5Y and HepG2 cells, induced G2/M arrest, disrupted mitochondrial homeostasis, and was genotoxic in Peripheral Blood Mononuclear Cells (PBMCs). Additionally, for H₃R ligands (15, DL76, pitolisant), the study reports the first use of Surface Plasmon Resonance Microscopy (SPRM) to assess their interactions with this receptor. Therefore, piperidinyl chalcones show promise as ligands with dual action on H₃R and MAO-B, useful in the treatment of neurodegeneration and/or CNS cancers. Full article

Pavement macrotexture, quantified by mean texture depth (MTD) and mean profile depth (MPD), is a critical parameter for road safety and performance. The traditional sand patch test is labor-intensive and slow, creating a bottleneck for modern pavement management systems. Accurately translating the rich point cloud data into reliable MTD values using the 3D scanning method remains a challenge, with current methods often relying on oversimplified correlations. This research addresses this gap by developing and validating a novel machine learning framework to predict MTD and MPD directly from high-resolution 3D laser scans. A comprehensive dataset of 127 pavement samples was created, combining traditional sand patch measurements with detailed 3D point clouds. From these point clouds, 27 distinct surface features spanning statistical, spatial, spectral, and geometric domains were developed. Six machine learning algorithms, consisting of Random Forest, Gradient Boosting, Support Vector Regression, k-Nearest Neighbor, Artificial Neural Networks, and Linear Regression, were implemented. The results demonstrate that the ensemble-based Random Forest model achieved superior performance, predicting MTD with an R² of 0.941 and a mean absolute error (MAE) of 0.067 mm, representing a 56% improvement in accuracy over traditional digital correlation methods. Model interpretation via SHAP analysis identified root mean square height (Sq) and surface skewness (Ssk) as the most influential features. Full article

Archaeological surface features on desert pavements, including geoglyphs, are notoriously difficult to assess. Lacking temporally diagnostic artifacts, they may be impossible to place chronologically, limiting their inferential utility. Not surprisingly, controversies have developed in the North American desert west over certain of these features. We describe methods for chronometrically constraining the ages of desert pavement features using three approaches to rock varnish dating: varnish lamination (VML), lead-profile dating, and the cation ratio (CR) as an additional tool. Each of these techniques may be applied to rock varnished cobbles that have been upthrust into areas previously cleared of the original pavement through cultural or natural processes. We use these methods to resolve two archaeological issues: the age of the intaglios (geoglyphs) along the lower Colorado River corridor and whether the Topock (or ‘Mystic’) Maze is the product of Precontact Indigenous or late-nineteenth-century railroad construction. Ethnographic analysis allows us to contextualize these features and to consider two additional issues: the antiquity of the Yuman speakers’ cultural pattern in the lower Colorado River region and the function of the Topock Maze. Full article

Weissella viridescens has been proposed as a probiotic candidate, but strain-level multi-omics evidence remains limited. The complete genome of the human-derived W. viridescens strain Wv2365 was sequenced through a hybrid assembly of Illumina and PacBio sequencing reads and compared with eight publicly available W. viridescens genomes. Pangenome analysis and functional annotation were performed, and metabolites were profiled by broadly targeted metabolomic analysis. In addition, the acid and bile tolerance, auto-aggregation and cell surface hydrophobicity, and antioxidant activity of the strain, as well as both in silico and phenotypic safety, were assessed. Wv2365 carries a single chromosome of 1.57 Mb with 41.3% G+C content. The species has an open pangenome with 803 core genes. Genomic and metabolomic features converged on carbohydrate and amino acid metabolism, including glycolysis/tricarboxylic acid (TCA) cycle and arginine pathways, and a carbohydrate-active enzyme (CAZyme) repertoire dominated by glycosyltransferases. In vitro, Wv2365 tolerated pH 3.0 and 0.3% bile, showed auto-aggregation, surface hydrophobicity, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) and hydroxyl radical scavenging. The strain was susceptible to 10 antibiotics tested except for its intrinsic vancomycin non-susceptibility and was non-hemolytic and gelatinase negative. No acquired antimicrobial resistance or virulence genes were found in the genome. These findings indicate that W. viridescens Wv2365 is safe with probiotic traits relevant to gastrointestinal survival, colonization, and redox balance. Full article

Objectives: This study aimed to evaluate the malignant transformation (MT) risk profile in patients with oral proliferative leukoplakia (OPL) referred to the Oral Medicine and Oral Surgery units of Umberto I Hospital, Sapienza University of Rome. Methods: The departmental database and medical records of OPL patients were reviewed from January 2014 to June 2024. Demographic, clinical, and histopathological features and treatment strategies were collected in a de-identified dataset. Results: A total of 51 OPL patients (33 females and 18 males; mean age 62.86 ± 13.55 years) were included. MT occurred in 17.6% (n = 9) after a mean follow-up of 4.78 ± 2.59 years. A higher percentage of the presence of a previous history of solid or hematological tumor was observed in patients with MT, with an OR of 2.940 (95% CI 0.064–1.350), without statistical significance. The homogeneous clinical form was more common in patients without MT (78.57%), and the speckled clinical form was more common in patients with MT (44.44%). The percentage of patients with lesions located on the floor of the mouth, ventral surface of the tongue, and dorsal surface of the tongue was higher in patients with MT. The tongue was the most common site of MT, followed by the gingiva, buccal mucosa, and palate. At the histological level, a verrucous, nodular, or bulky architecture was more commonly observed in patients with MT, and the presence of band-like lymphocytic infiltrate was observed in all patients with MT. Higher dysplasia grades were significantly associated with MT (p = 0.009). No significant association was found between the treatment modality and MT risk, although laser ablation was associated with a trend toward lower risk. Conclusions: This study further suggests that the clinical morphology, lesion site, and histological grading may be important predicting factors for MT in OPL. The presence of a non-homogeneous lesion form, a higher grade of dysplasia, and a history of previous solid or hematological tumor led to a more aggressive disease course. Individualized risk assessment and long-term surveillance may be advisable. Full article

Pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis characterized by chronic, painful ulcerations. Despite increasing evidence suggesting immunological dysregulation, the role of IL-36 cytokines in PG remains poorly defined. To evaluate serum levels of IL-36α, IL-36β, IL-36γ, IL-36Ra, IL-37, and IL-38 in PG patients compared to healthy controls, and to assess their correlation with selected clinical parameters and cytokine ratios. 44 PG patients and 40 healthy controls were included in this case–control study. Serum cytokine levels were measured using ELISA. Correlations between cytokine levels and clinical features were analyzed using nonparametric tests. PG patients showed significantly lower serum levels of IL-36α and IL-36γ (p = 0.0003 and p = 0.02, respectively), with no difference in IL-36β. Conversely, levels of IL-36Ra, IL-37, and IL-38 were significantly higher in PG patients (p < 0.0001 for all). In the PG group, significant positive correlations were observed between IL-36α and IL-36β, and between IL-36β and IL-36γ, while IL-37 correlated negatively with IL-38. IL-36α was inversely associated with serum IgA levels and total ulcer surface area, and IL-36γ correlated negatively with white blood cell count. Our findings reveal a dysregulated IL-36 cytokine profile in pyoderma gangrenosum, marked by reduced serum levels of IL-36α and IL-36γ and elevated levels of IL-36Ra, IL-37, and IL-38. This may reflect a compensatory response to chronic inflammation. The inverse correlation between IL-36α and ulcer size suggests its potential involvement in wound healing. Despite lower serum levels of agonists, local biological activity of IL-36 cytokines may remain elevated due to tissue-level activation and consumption. These results highlight the therapeutic relevance of targeting the IL-36 pathway—particularly in treatment-resistant cases—and support further research into cytokine activity beyond serum concentration to guide novel therapeutic strategies. Full article

Soil profile moisture (0–200 cm) in agricultural fields is a critical variable determining root-zone water storage and irrigation scheduling accuracy, yet continuous deep-layer monitoring is constrained by equipment costs and installation difficulties. This study developed a near-real-time reconstruction model for soil moisture profiles across the 0–200 cm depth based on shallow-layer (0–20 cm, 20–40 cm) real-time monitoring data and multi-day accumulated meteorological features. Using field measurements from 2023 to 2025, Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Support Vector Regression (SVR) models were compared across different input scenarios and cumulative time windows. The results showed that using only surface moisture as input (Scenario A), prediction R² ranged from 0.87 to 0.93 for shallow layers (≤80 cm) but decreased to 0.58 for deep layers (140–200 cm). Incorporating multi-day meteorological accumulation (Scenario B) improved R² by 0.05–0.08. When dual-layer moisture and meteorological drivers were combined (Scenario D), shallow-layer R² reached 0.96–0.98 with RMSE < 7 mm, mid-layer performance maintained at 0.85–0.90, and deep layers still achieved 0.76–0.84. Optimal time windows exhibited depth-dependent patterns: 5–10 days for shallow layers, 10–15 days for mid-layers, and ≥20 days for deep layers. Rolling validation demonstrated high consistency between model predictions and observations in the 0–80 cm range (R² > 0.90, RMSE < 10 mm), enabling stable estimation of 0–200 cm profile dynamics. This approach eliminates the need for deep probes while achieving low-cost, interpretable, and deployable near-real-time deep moisture estimation, providing an effective technical pathway for precision irrigation and water management in semi-arid regions. Full article