Search Results (856)

Adverse imaging conditions such as fog, rain, and low light degrade the reliability of vision-based Personal Protective Equipment (PPE) detection systems on construction sites, yet most existing models are trained under clear-weather assumptions. This paper introduces a physics-based weather augmentation framework integrated with the YOLOv8n architecture to improve PPE detection robustness under adverse environmental conditions. The original Color Helmet and Vest (CHV) dataset was expanded from 1330 clear-weather images to 6650 images across five conditions using four physically grounded augmentation models: the Koschmieder atmospheric scattering model for fog, the Garg–Nayar streak model for rain, gamma-corrected attenuation with Poisson–Gaussian noise for low light, and a PSF-based glare model for bright sunlight. The weather-resistant model, a clear-weather baseline, and an augmented baseline were evaluated on the same 665-image weather-augmented test set. The weather-resistant model achieves 89.2% mAP50, a 5.7 percentage-point improvement over the clear-weather baseline (83.5%), with a nearly four-fold improvement in cross-condition stability (standard deviation 1.5% vs. 5.7%). Under matched training-data volume, the weather-resistant model still outperforms a conventionally augmented baseline across all five simulated conditions, indicating that these gains stem from physics-based modeling rather than larger training-data volume. The largest gain occurs under low light, where mAP50 improves from 73.4% to 87.9%. Gradient-weighted Class Activation Mapping (Grad-CAM) analysis confirms that the weather-resistant model directs more attention toward PPE regions across all conditions, with the largest improvement under low light (+10.0 percentage points). The lightweight design (3.0 M parameters) and quantitative and qualitative validation on 205 annotated real-world construction site images under normal and low-light conditions provide preliminary evidence of practical applicability. Full article

The fatigue life of additively manufactured GH4169 components is strongly affected by internal defects, stress concentration, and life scatter, making reliable structural assessment difficult. In this study, a probability-based fatigue life prediction framework was developed by extending the conventional surface weakest link concept to a volume-defect weakest link formulation. Fatigue tests of smooth specimens with different build orientations were first conducted to establish baseline probabilistic fatigue relationships, and both log-normal and two-parameter Weibull distributions were considered. The proposed framework was then applied to a feature specimen representing the critical region of an aero-engine exhaust frame by combining the baseline fatigue statistics with element-wise maximum principal stress and volume information extracted from finite element analysis. The results show that the log-normal distribution provided a more stable statistical description of the smooth-specimen fatigue data than the Weibull distribution. For the feature specimens tested at 11,200 N, the measured fatigue lives ranged from 25,585 to 61,989 cycles. Compared with the conventional local stress method, the weakest link framework gave a more reasonable description of the structural fatigue life distribution, and the log-normal weakest link model showed the best overall agreement with the experimental results. Full article

Ultrasonic inspection of welded steel components remains challenging due to weld-scale material gradients, local anisotropy, attenuation, and aperture limitations. These factors severely distort both the first-arrival wavefield and the late-arriving scattered wavefield. To address this, this study presents a numerical proof of concept for three-dimensional cross-weld virtual-array coda-wave tomography (VACWT). The “virtual array” utilizes a synthetic aperture created by re-indexing sequential source–receiver records from two opposing line scans into midpoint–angle–depth coordinates. This approach enables line-based data acquisition to achieve multi-angle volumetric coverage without requiring a two-dimensional matrix array. A parameterized welded-solid benchmark model was developed, incorporating effective longitudinal and shear wave velocities, attenuation, and out-of-plane tilt fields. Four defect scenarios were evaluated: a cylindrical void, a lack-of-fusion ribbon, a porosity cluster, and an interference case. For each source–receiver path, four observables were extracted from the synthetic records: first-arrival travel time perturbations, coda wave stretching, coda decorrelation, and late-window energy ratios. These observables were then coupled into a volumetric inverse problem to separate smooth slowness variations, distributed scattering strength, and compact defect occupancy. Under the current simulation conditions, VACWT achieved smaller recovered support volumes and higher volumetric overlap compared to the delay-and-sum total focusing method (DAS-TFM), background-corrected TFM, and reverse time migration (RTM). In the interference case, applying a fixed defect-free calibration threshold yielded a centroid error of 0.48 mm, a volumetric intersection over union (IoU) of 0.856, and a false-positive volume fraction of 0.0%. While these findings serve as benchmark results rather than generalized experimental validation, the study demonstrates that late scattered wave observables provide valuable constraints for volumetric support recovery in a controlled welded-solid model. Future experimental verification on welded steel specimens with known defects remains necessary. Full article

To address the limited constraints of ground-based lidar with few channels in retrieving aerosol microphysical parameters in urban atmospheres, this study developed a method to retrieve aerosol volume size distribution and effective radius from a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar system. The method uses 3β + 2α optical quantities as input constraints, applies Mie scattering theory as the forward model, parameterizes the volume size distribution with B-spline functions, and achieves stable solutions through Tikhonov regularization and cross-validation. To reduce uncertainties in prior parameters, including the complex refractive index, particle size range, and lidar ratio, an optimization strategy based on parameter search, retrieval reconstruction, and error minimization was introduced. Numerical simulations showed that the method reproduced the main features of a bimodal lognormal aerosol volume size distribution with good feasibility and stability. Two case studies further showed fine-mode dominance and decreasing extinction coefficient, depolarization ratio, and effective radius with height under good air quality conditions, but enhanced coarse-mode contribution and effective radius in the upper cloud-influenced layer under lightly polluted conditions, as inferred from the combined variations in RSCS, extinction coefficient, depolarization ratio, and effective radius. Full article

We present a novel algorithm for the retrieval of non-spherical particle microphysical parameters (PMP) from 3β + 2α + 3δ optical data taken with multiwavelength lidar. The 3β + 2α + 3δ optical datasets describe particle backscatter coefficients (β) at three wavelengths, λ = 355, 532, and 1064 nm, particle extinction coefficients (α) at two wavelengths, λ = 355 and 532 nm, and particle linear depolarization ratios (PLDR, δ) at three wavelengths, λ = 355, 532, and 1064 nm. The algorithm can be used for retrieving bimodal particle size distributions (PSDs). The PSDs can comprise mixtures of spheres and spheroids (SS). One or both modes can comprise spheroid-shaped particles or spherically shaped particles. The spheroids are used for approximating an arbitrary ensemble of non-spherical particles. The algorithm works on the basis of a combination of direct and analytical inversion methods. The algorithm uses the spheroid reference look-up table (RLUT) we developed and presented in part 1 of our research work. The algorithm uses constraints regarding the particle complex refractive index (CRI) and information on relative humidity (RH) in the atmosphere (in the case of aerosol lidar observation) for suppressing retrieval uncertainties. We carried out a numerical simulation study to evaluate the algorithm’s performance. In these numerical simulations, we considered perturbed synthetic 3β + 2α + 3δ optical data that mimic different organic carbon (OC)–dust (D) mixtures. Such mixtures are suitable examples for describing bimodal PSDs that consist of a fine mode of spherical particles and a coarse mode of non-spherical particles. The results of the numerical simulation show that (1) the PMPs of each mode of these particle mixtures can be found separately, (2) the mean retrieval errors of the effective radius, number, surface-area, and volume concentrations of these mixtures are 25%, 52%, 9%, and 28%, respectively, and (3) the mean retrieval error of single-scattering albedo (SSA) at 355 nm of these mixtures is as low as ±0.02. SSA retrieval accuracies at 532 and 1064 nm degrade because the complex refractive index (CRI) of OC and D particles depends on the measurement wavelength. In future studies, we will upgrade the algorithm such that it takes into account a spectrally dependent CRI. We also compare the results of our novel algorithm with our TiARA2.1 algorithm. The errors obtained from the TiARA2.1 algorithm are approximately three times larger compared to the errors we obtain with our novel ATLAS algorithm for the case of the OC-D mixtures considered in the present study. We explain the higher accuracy of the PMP retrievals by the use of three PLDRs and the extra constraints placed on CRI and RH. Full article

Background/Objectives: Recessive titinopathies caused by biallelic TTN truncating variants (TTNtvs) present a clinically heterogeneous spectrum from fetal demise to late-onset slowly progressive distal muscular dystrophy. Prognostic counseling is challenging due to the vast size of the TTN gene, complex splicing patterns, and differential expression throughout developmental stages and tissues. This paper aims to delineate the regional genotype patterns and clinical characteristics of recessive titinopathies described from the prenatal period onwards to inform genotype–phenotype associations and genetic counseling. Methods: We analyzed clinical and genetic data from a prenatal-onset cohort with biallelic TTNtvs from both previously reported cases and novel cases from our center. To characterize the regional distribution of biallelic variants within this specific cohort, a two-dimensional scatter plot was utilized to map variants onto 10 biological regions (R1–R10) and 55 analytical units (U1–U55). We also performed Fisher’s exact tests on the subset of 50 cases with confirmed survival records to evaluate statistically significant associations between biallelic regional or percent spliced-in (PSI) thresholds combinations and severe clinical endpoints (intrauterine demise or death before 5 years). Results: A total of 96 prenatal cases from 76 unrelated families were analyzed. Decreased fetal movement was the most commonly reported symptom, observed in 81.3% (78/96) of cases, which was followed by arthrogryposis in 45.8% (44/96) and amniotic fluid volume abnormalities in 35.4% (34/96). Additionally, of the 95 cases with known pregnancy outcomes, 25.3% (24/95) resulted in termination and 11.6% (11/95) resulted in intrauterine demise (IUD), while 63.2% (60/95) reached birth with over 16.7% (10/60) being preterm. Among 60 live-born infants, severe postnatal morbidity was high: 45.0% (27/60) experienced respiratory failure, and 33.3% (20/60) died before the age of five. In this cohort, 84.4% (81/96) of cases possessed at least one TTNtv in either the metatranscript-only or A-band regions. The most common biallelic changes involved TTNtvs in both the A-band and metatranscript-only regions, accounting for 35.4% (34/96) of cases, followed by metatranscript-only combined with I-band variants at 16.7% (16/96), regardless of the PSI score of exons. Overall, 83.3% (80/96) had ≥1 variant on low-PSI (<50%) exons, and 19.8% (19/96) had both alleles on these low-PSI exons. In the 50 patients with confirmed survival records, biallelic changes (excluding splice-site variants) affecting both high-PSI (>90%) exons were significantly associated with severe outcomes (intrauterine demise or death before 5 years; exact p = 0.015), whereas the metatranscript-only plus I-band combination conferred a significantly lower risk of lethality before 5 years of age (exact p = 0.001). Conclusions: Our findings add to the accumulating evidence that TTNtvs on low PSl exons or metatranscript-only regions are frequently observed among reported prenatal-onset recessive titinopathy. Health surveillance for heterozygous carriers among family members is warranted due to the substantial risk for adult-onset dilated cardiomyopathy and peripartum cardiomyopathy. Full article

To address the scattered protection efforts and uneven effectiveness of traditional villages in southwestern Hubei, this study focuses on 92 nationally recognized traditional villages in Enshi Prefecture. By integrating literature research, field investigation, and multi-source data fusion, we developed an innovative model that combines the Analytic Network Process (ANP), entropy weight, and fuzzy comprehensive evaluation, thereby integrating subjective and objective weighting to improve evaluation accuracy. A quantitative evaluation was conducted across 13 criteria and 32 indicators, including traffic conditions, intangible cultural heritage resources, and industrial foundation. The results reveal that traditional villages in Enshi Prefecture exhibit a significant spatial pattern of “overall dispersion with local concentration,” accompanied by a high concentration index. Traffic conditions, intangible cultural heritage, and infrastructure emerge as the core factors affecting protection effectiveness, and a spatial differentiation pattern of “two cores and one corridor” is identified within the region. Based on the quantitative evaluation, we propose targeted cluster protection strategies, including a “dual-core multi-node” transportation network, “three-industry linkage” industrial collaboration, and a living heritage approach that integrates cultural relics with intangible cultural heritage. These strategies were validated in pilot villages such as Yejiaoyuan Village, resulting in significant increases in village satisfaction and tourist volume. The findings provide methodological support and practical paradigms for the systematic protection and sustainable development of traditional villages in southwestern ethnic minority areas. Full article

This study proposes a novel analytical model to predict one-dimensional moisture transport in concrete under cyclic drying and wetting conditions. The framework distinguishes between two physical mechanisms: diffusion-driven evaporation during drying and capillary-driven suction during wetting. Governing equations for weight loss and gain are derived for each respective phase. During the drying phase, weight loss follows a linear relationship with the square root of time, allowing the diffusion coefficient to be determined via evaporation tests. For the wetting phase, a modified sorptivity approach is employed, incorporating an error-function baseline to account for residual moisture. A calibration coefficient of ε is utilized to correct for varying conditions between standard water suction tests and environmental wetting, particularly for air-entrained concrete characterized by larger capillary volumes and complex tortuosity. Experimental validation was conducted on concrete with varying water-to-cement ratios. The model demonstrated excellent agreement with experimental data, maintaining relative errors below 10% for standard mixes. While higher-porosity samples exhibited greater scatter due to “water traps” and complex pore structures, the model effectively captured cumulative moisture trends over multiple cycles. This framework provides a robust tool for assessing the durability of concrete structures in unsheltered environments. Full article

Aerosol scattering strongly influences the Earth’s atmosphere energy balance and actinic flux, yet its efficiency remains uncertain due to limited understanding of chemical effects. Scattering efficiency primarily depends on aerosol size, scattering refractive index, and hygroscopicity, which are determined by emissions and chemical processes; however, their covariation characteristics are rarely explored. Here, we use long-term measurements of submicron aerosol size distributions, chemical composition, scattering properties, and hygroscopicity in Guangzhou to investigate their covariations and links to secondary aerosol formation. The results indicate that dry-state volume scattering efficiency (VSE) was mainly driven by variations in aerosol size (R² = 0.74), despite substantial refractive index variability (1.4–1.6), which showed overall independent variations with size. Source apportionment and case analyses suggest distinct size ranges for secondary organic (SOA) and inorganic aerosols (SIA). Accordingly, a new lognormal fitting methodology is proposed to retrieve particle volume size distribution (PVSD)-associated aerosol components by combining PVSD and composition data. Retrieved geometric mean diameters of SOA ($D_{g,SOA}$, 175–400 nm; 246 ± 44 nm) and SIA ($D_{g,SIA}$, 200–600 nm; 382 ± 68 nm) are significantly correlated (R² = 0.43), indicating coupled formation of SOA and SIA and their interdependent roles in aerosol scattering. In addition, pronounced joint increases in dry-state VSE and aerosol hygroscopicity driven by the co-enhancement of aerosol size and hygroscopicity are further revealed. These results demonstrate the interconnected roles of secondary aerosol formation in controlling scattering efficiency and underscore the need to better represent SOA–SIA interactions in simulating aerosol radiative effects and address the covariations of aerosol hygroscopicity and dry-state scattering efficiency in aerosol remote sensing. Full article

The formation of stereocomplex (SC) crystallites in poly(L-lactide) (PLLA)/poly(D-lactide) (PDLA) blends has attracted significant attention due to its potential to enhance the performance of biodegradable polymer films. In this study, the effect of solvent evaporation kinetics on the crystallization behavior, microstructure, and functional properties of PLLA/PDLA blend films was systematically investigated. Films with various blend ratios were prepared under open-lid (fast evaporation) and closed-lid (slow evaporation) conditions. Differential scanning calorimetry (DSC), wide-angle X-ray diffraction (WAXD), and small-angle X-ray scattering (SAXS) analyses revealed that slow solvent evaporation significantly promotes stereocomplex formation, particularly at the equimolar (50:50) composition, resulting in a higher degree of crystallinity and a more compact structure compared to fast evaporation conditions. These structural changes were directly correlated with improved functional properties. The optimized PLLA/PDLA (50:50) films exhibited a substantial reduction in water vapor permeability from 22.7 to 3.11 g·mm/m²·day·kPa (~86% decrease) and a marked decrease in microbial growth, as evidenced by reduced total plate count (TPC) values compared to neat polymers. The enhanced barrier performance and reduced microbial proliferation were attributed to the reduced free volume and increased tortuosity associated with densely packed stereocomplex crystallites, as supported by DSC and WAXD results. These findings demonstrate the importance of solvent evaporation kinetics in tailoring structure–property relationships to control stereocomplex formation and multiscale structural organization, providing a practical strategy for biodegradable packaging films. Full article

The dramatic increase in the volume of postconsumer textile waste poses not only a major environmental problem but also an untapped opportunity for the development of sustainable infrastructure through the use of synthetic and composite textile waste-derived materials (SCTWDMs) in the field of asphalt pavement engineering, contributing to the achievement of the United Nations Sustainable Development Goals (SDGs 9, 11, 12, and 13). This systematic review was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A systematic search of the literature in the field of SCTWDMs in asphalt pavement engineering was performed between 2010 and 2025 using the Web of Science and Scopus databases. A total of 65 studies were identified and analysed according to the inclusion and exclusion criteria of the current review. The quality of the studies and the risk of bias were assessed according to the transparency of the methods and the reporting of the results. The triangulated methodological framework consisted of bibliometric analysis, systematic review, and SWOT analysis. The bibliometric analysis was carried out via VOSviewer software version 1.6.20. The results of this study indicate an increase in the number of publications in SCTWDMs; however, there is fragmentation in the field. This denotes poor interrelationships among themes, insufficient collaboration across research streams, and scattered networks of keyword associations, suggesting a lack of a coherent research framework for SCTWDM research. The results of this study indicate that SCTWDMs generally improve the rheological properties, cracking resistance, and mechanical characteristics of asphalt mixtures. However, variability in fibre properties, optimisation of dosage, and limited field validation remain major challenges in SCTWDMs. The SWOT analysis also highlights important technical, institutional, and standardisation barriers, as well as opportunities for further development in sustainable pavement technologies. Despite this, the body of evidence is limited by heterogeneity in study design and a lack of long-term results. The review is not preregistered, but all the methodological procedures are transparently described. In conclusion, this body of evidence offers a strategic direction for further research, policy development, and industry practice, highlighting the importance of linking laboratory results to applications to position SCTWDMs as a viable option within the global sustainability agenda. Full article

This study investigates the effect of mass-based replacement of natural coarse aggregate with electric arc furnace (EAF) slag on the performance of ordinary Portland cement (OPC) concrete. Replacement levels of 0%, 30%, 50%, and 100% were examined, with particular attention to the volumetric changes induced by the higher density of EAF slag, which leads to an increase in paste volume. Fresh, mechanical, durability-related, and microstructural properties were evaluated. Results show a continuous reduction in workability with increasing slag content, despite the increase in paste volume, indicating the dominant influence of aggregate morphology on rheological behavior. Mechanical performance exhibited a non-linear response. Within the tested series, the 50% replacement mixture showed the highest mean compressive and splitting tensile strengths; however, the compressive strength difference relative to the control mixture remained small and within typical experimental scatter. In contrast, water absorption decreased progressively, reflecting improved matrix densification. However, this densification did not translate into enhanced mechanical performance, highlighting a decoupling between durability-related indicators and strength. A screening-level CO₂ assessment further showed that reductions in aggregate-related emissions were offset by increased cement content associated with mass-based replacement. The results emphasize the importance of considering volumetric effects when interpreting the behavior and sustainability of slag-based concrete. Note: all strength comparisons are based on mean values from three-specimen sets without formal statistical testing and should be regarded as exploratory observations. Full article

Background: Platinum-based chemotherapy, including cisplatin and carboplatin, is widely used to treat various cancers, including ovarian cancer. However, its clinical application is limited by dose-limiting toxicities and resistance, with a poor 5-year overall survival rate for ovarian cancer (35–40%). In this study, we used ionisable lipids and developed pH-responsive lipid nanoparticles (LNPs) to address platinum-resistance in ovarian carcinoma. Methods: Cisplatin was loaded into three LNP systems containing monoolein (MO) and synthetic cationic ionisable lipids (OE-Mo, OA-Py, and OA-Pi) dispersed in Pluronic F-127 with 0.9% NaCl. Cisplatin-loaded LNPs (Cis-OE-Mo-NP, Cis-OA-Py-NP, and Cis-OA-Pi-NP) were characterised for size, zeta potential, and internal mesophase structure. Encapsulation efficiencies were determined via HPLC after removing free drug by ultrafiltration. In vivo efficacy was tested using cisplatin-resistant human patient-derived xenograft (PDX) models. Results: The LNPs were well dispersed with particle size of 219–250 nm and a drug loading of ~1.2 mg/mL. Encapsulation efficiencies were 62%, 59%, and 64%, for Cis-OE-Mo-NP, Cis-OA-Py-NP, and Cis-OA-Pi-NP, respectively. Small angle X-ray scattering (SAXS) results showed that the LNPs are pH responsive with structural transitions from a cubic to a hexagonal phase at an acidic pH. Among the tested formulations, Cis-OA-Py-NP resulted in the most significant reduction in tumour volume by ~60% compared to treatment with cisplatin alone. However, they also showed significant toxicity, including >10% weight loss and gross lung and kidney damage, as confirmed by histology. Conclusions: These findings highlight the potential of Cis-OA-Py-NP in reducing tumour volume but underscore the need for further optimisation to improve safety and therapeutic applicability. Full article

Aiming at the inherent bottlenecks of traditional smoke detection technologies in high and large-volume building scenarios, this paper conducts research on an early fire smoke detection method for high and large-volume spaces based on Light Detection and Ranging (LiDAR). A special experimental platform was independently designed to obtain the physical characteristics of smoke particles from standard smoldering fires. Combined with the optical scattering and reflection interaction mechanism between laser and particulate matter, the theoretical feasibility of LiDAR for smoke detection was systematically verified. Smoke irradiation experiments were carried out in the full detection distance, and the LiDAR point cloud characterization characteristics of smoldering smoke were clarified. A special smoke detection algorithm based on point cloud features was designed, a LiDAR smoke detection system was built, and multi-condition comparative experiments with traditional photoelectric smoke detection methods were carried out in a full-scale laboratory. The experimental results show that the LiDAR-based smoke detection method proposed in this paper has significant advantages over traditional detection methods in terms of alarm response speed, detection coverage, and height adaptability. This research provides a brand-new technical path and reference for the theoretical research and engineering application of early fire warning technology for high and large-volume buildings. Full article

Omega-6 polyunsaturated fats (ω-6 PUFAs) are vital for many physiological functions, but their impact on cardiovascular disease (CVD) risk is controversial. Eryptosis alters blood viscosity by providing a procoagulant surface and leads to anemia, which is a recognized risk factor for CVD. This study examines the toxic mechanisms of adrenic acid (ADR), an ω-6 PUFA enriched in inflammatory and oxidative conditions, in red blood cells (RBCs). Purified RBCs were prepared from healthy volunteers and treated with 10–100 μM of ADR for 24 h at 37 °C under various physiological conditions. Eryptotic markers were studied through flow cytometry including Ca²⁺ (Fluo4/AM), loss of volume (forward scatter), phosphatidylserine (PS) exposure (annexin-V-FITC), and oxidative stress (H₂DCFDA). Moreover, hemolytic markers were measured by colorimetric methods, whereas cellular morphology was visualized using a scanning electron microscope. ADR led to significant Ca²⁺ elevation, cell shrinkage and schistocyte formation, PS externalization, hemolysis, and oxidative stress. While guanosine, heparin, and NSC 23766 prevented eryptosis and hemolysis, melatonin, ATP, adenine, and L-NAME only prevented eryptosis. Conversely, mannitol and urea exacerbated eryptosis, whereas caffeine, mannitol, and urea under Ca²⁺ deprivation and membrane potential dissipation aggravated hemolysis. ADR induces erythrocyte membrane injury and eryptosis through Ca²⁺ elevation, oxidative stress, and metabolic exhaustion subject to inhibition by the Rac1 GTPase/NOS/COX pathway. Altogether, these findings present a novel mechanistic link between lipid dysregulation and RBC dysfunction which may improve dietary strategies to prevent and manage CVD. Full article