Search Results (12,476)

This study investigates the selection of suitable statistical models for speckle reflections from the underlying surface under low-altitude sensing conditions. A parametric approach to modeling speckle images of terrain fragments typical of synthetic aperture radar (SAR) is presented. We use a phenomenological model of speckle formation during radio wave interference, taking into account the spectrum of fluctuations, the roughness of the reflecting surface, the angle of incidence, and other radar parameters. We investigate the influence of the properties of the reflecting surface and the probing parameters on the nature of speckle images. The values of the sample cumulative coefficients for various multiplicative models of the reflection distribution are obtained. The properties and characteristics of various classes of distributions for describing the intensity and amplitude of speckles are considered: the gamma distribution, the K-distribution, and the classes of non-Gaussian probability densities G and G⁰. A generalized Gaussian (GG) distribution is used to model the complex components of reflected signals. We compare the obtained model characteristics with the sample characteristics of real terrain fragments in synthesized speckle images obtained by the on-board radar system. Based on a comparative analysis of cumulants, this paper examines methods for modeling amplitude and intensity speckle images using several classes of backscatter probability densities. Limitations in specific applications have been identified, and a modeling method using quadrature components has been developed in cases of extremely rough reflections. Full article

The presence of human herpesviruses is frequently detected in the oral cavity, yet their disease-specific role in chronic inflammatory oral mucosal disorders remains uncertain. This comparative observational study investigated Epstein–Barr virus (EBV) and human herpesvirus-7 (HHV-7) genomic sequences in saliva and virus-specific antibodies in serum among patients with oral lichen planus (OLP; n = 35), aphthous stomatitis (AS; n = 31), and healthy controls (n = 34). Salivary viral loads were quantified using real-time PCR, while EBV and HHV-7-specific IgG and IgM antibodies were measured using ELISA-based assays. EBV and HHV-7 DNA in saliva were commonly detected across all groups, demonstrating high baseline shedding and marked interindividual variability. Although EBV IgG levels were higher in OLP compared with AS in univariate analysis, multivariate regression revealed that age, rather than disease status, was the primary determinant of EBV IgG levels. After adjustment for age, sex, and discomfort, neither EBV nor HHV-7 salivary loads showed independent associations with OLP or AS. HHV-7 salivary loads were uniformly distributed among groups. These findings suggest that salivary detection of EBV and HHV-7 reflects widespread latent infection rather than disease-specific activity in OLP or AS. Longitudinal and tissue-based studies integrating immunological profiling are warranted to clarify whether herpesvirus reactivation contributes to disease severity in defined patient subgroups. Full article

Cotton, as a globally significant economic crop, is intricately regulated in its growth and development by the key genes for SA (Salicylic acid) biosynthesis. In the present study, a systematic analysis of genes related to SA biosynthesis was conducted across four cotton species, leading to the identification of 70 genes. Specifically, the tetraploid species Gossypium hirsutum and G. barbadense were found to harbor 22 and 23 genes, respectively, representing a substantial expansion compared to the 12 and 13 genes identified in the diploid progenitors G. arboreum and G. raimondii. Comprehensive characterization of chromosomal localization, phylogeny, domain architecture, and promoter cis-elements revealed a uniform distribution of key genes involved in SA biosynthesis across A/D sub-genomes of tetraploids with extensive interspecific collinearity; whole-genome and segmental duplication act as the dominant drivers for the expansion of this gene family, while partial gene loss following polyploidization results in non-doubled gene copy numbers in tetraploids relative to diploids, which reflects the evolutionary selection for genomic dosage balance. The key genes for SA biosynthesis demonstrate a high degree of conservation in protein sequences, protein structures, and conserved motifs, which constitute the structural basis for the stable maintenance of their core functions in the SA biosynthesis pathway during plant evolution. This is closely related to their core function in the salicylic acid (SA) synthesis pathway and serves as the structural basis for the stable maintenance of gene functions during evolution. Analysis of cis-elements revealed that the expression of key genes involved in SA biosynthesis is governed by a complex interplay of phytohormones, stress signals, and transcription factors. Yeast one-hybrid (Y1H) assays confirmed the interaction between the GhPAL and GhICS gene and predicted candidate transcription factors, specifically the binding of GhWRKY21 to GhICS2-1 promoter and GhMYB12 to GhPAL1-2 promoter, thus elucidating their stage-specific regulatory mechanisms in cotton fiber development and reflecting their evolution. This study provides a fundamental basis for investigating the role of the SA signaling pathway in cotton development and offers support for cotton molecular breeding. Full article

The long-term success of dental implants is significantly influenced by primary stability, which is commonly assessed through insertion torque (IT) and removal torque (RT) measurements in vitro. While polyurethane (PU) blocks are accepted by the American Society for Testing and Materials (ASTM) as the standard bone analog material for biomechanical testing, the use of polyethylene (PE) as a bone model material for dental implant research remains limited and not well established. This operator-blinded, in vitro study compared the IT and RT values of dental implants placed in PE and PU blocks of identical density (60 pounds per cubic foot [pcf]; 0.96 g/cm³). A total of 60 tapered dental implants (4.2 × 12 mm, RBM surface, platform switching) were placed into PE (n = 30) and PU (n = 30) blocks by a calibrated operator blinded to the material type. Implant sockets were prepared by an independent surgeon following the manufacturer’s drilling protocol. IT and RT values were recorded using a physiodispenser with torque measurement capability (5–80 N·cm). Statistical analysis was performed using Student’s t-test (α = 0.05), with Mann–Whitney U tests reported as a sensitivity analysis for non-normally distributed variables. No statistically significant difference was observed in IT between PE and PU groups (58.50 ± 8.42 vs. 58.17 ± 9.60 N·cm; p = 0.887; Cohen’s d = 0.04; 95% CI of mean difference: −4.33 to 5.00 N·cm). However, RT was significantly higher in the PU group compared to the PE group (71.17 ± 7.15 vs. 64.33 ± 9.17 N·cm; p = 0.002; Cohen’s d = 0.83; 95% CI: −11.08 to −2.58 N·cm; Mann–Whitney U sensitivity analysis p = 0.004). Under the specific high-density (60 pcf) conditions tested, the absence of a statistically significant IT difference does not constitute formal evidence of equivalence or non-inferiority, and the significantly higher RT in PU indicates that PE and PU are not interchangeable bone analogs. Further studies across a range of densities, implant macrogeometries, and using formal equivalence testing are required before PE can be considered for in vitro dental implant stability research. Full article

Understanding the spatial distribution patterns and environmental drivers of plant communities is fundamental for biodiversity conservation and ecosystem management. Bombax ceiba is a widely distributed tree species that occurs in both humid tropical rainforests and drought-prone dry-hot valleys, representing two strongly contrasting ecological environments. However, the spatial patterns and environmental drivers of plant communities associated with B. ceiba across these habitats remain poorly understood. In this study, we investigated B. ceiba-associated plant communities in two representative habitats in Yunnan Province, Southwest China: a tropical rainforest in Mengla and a dry-hot valley in Yuanjiang. The species composition, community structure, and spatial coordinates of associated plants were recorded in replicated 20 m × 20 m plots. Spatial distribution patterns were analyzed using the pair-correlation function g(r), while environmental drivers were examined using Pearson correlation analysis and redundancy analysis (RDA). Species richness was substantially higher in the tropical rainforest (41 species from 33 families) than in the dry-hot valley (19 species from 14 families). Both communities contained a substantial proportion of tropical Asian floristic elements. Most dominant species exhibited aggregated spatial distributions at small spatial scales (0–7 m), indicating strong dispersal limitation and microhabitat heterogeneity. Spatial associations varied across scales: in the dry-hot valley, species associations alternated between positive and negative correlations at small scales (0–5 m) and shifted toward positive correlations at larger distances, whereas in the tropical rainforest negative associations were more common at small scales and positive associations increased at larger spatial scales. Environmental drivers differed markedly between habitats. In the dry-hot valley, community attributes were positively associated with slope, precipitation, and soil ammonium nitrogen, suggesting that community assembly is influenced by interactions between topography and water availability. In contrast, tropical rainforest communities were more strongly associated with soil phosphorus availability and temperature-related variables. These findings highlight distinct community assembly mechanisms in contrasting habitats and provide ecological insights for vegetation restoration in dry-hot valleys and biodiversity conservation in tropical rainforests. Full article

In response to the influence of extreme disasters, damage to distribution lines and user outages, a parallel implementation strategy is proposed for emergency repair of disaster-damaged distribution networks and rapid restoration of power supply for users, considering the collaboration of “human–vehicle–road–pile” resources. This strategy constructs a hierarchical optimization framework, with the upper-level model aiming to minimize the repair time for disaster damage. It adopts a collaborative optimization approach between repair resources and transportation routes to quickly repair the connection between the distribution network and the main power network. In the lower-level model, a model predictive control mechanism is adopted to schedule electric vehicles (EVs) in Real-time as mobile energy storage systems, and vehicle-to-grid (V2G) service technology is used to provide an emergency power supply for key loads during the repair period, achieving parallel optimization of “repair–restoration”. Considering constraints such as emergency repair resources, time-varying transportation, electric vehicle scheduling and power management, charging pile capacity, power flow safety of the distribution network, and topology of the distribution network, second-order cone relaxation technology is adopted to improve solving efficiency. The simulation results show that compared with the traditional serial restoration strategy, the proposed strategy delivers a dual benefit: it significantly eliminates the power supply vacuum period without compromising the efficiency of emergency repair operations. Specifically, it increases weighted load restoration by 57.2% compared with traditional sequential methods and reduces the average outage time for key loads from 3.22 h to 0.5 h, effectively enhancing the resilience and restoration ability of the power supply guarantee of the distribution network. Full article

Background: Apremilast (APM) is a selective phosphodiestrase-4 (PDE-4) inhibitor currently administered orally for the treatment of psoriasis. However, gastrointestinal irritation, frequent dosage regimens, and patient noncompliance limit its oral administration. Additionally, the poor permeability and solubility of APM make dermal administration challenging. Objective: The current study aims to formulate an optimized APM-loaded nanoemulsion formulation (APM-NE) to enhance drug delivery to deep psoriatic skin layers, thereby increasing dermal drug concentration for the effective treatment of psoriasis. Method: Using the phase titration method, the nanoemulsion (NE) was made with Capryol 90, Tween 20, and Labrasol as oil, surfactant, and co-surfactant, respectively. Results: The optimized formulation (F5) exhibited favorable physicochemical properties: mean droplet size of 147.4 ± 2.4 nm, and an entrapment efficiency (EE) reaching 86.30 ± 2.54%. TEM confirmed spherical, uniformly distributed droplets. In vitro release (86.1 ± 0.24%) followed zero-order kinetics. To enhance skin retention, F5 was incorporated into 2% Carbopol 980 gel, yielding F5G with pseudoplastic flow. Ex vivo permeation showed significantly higher drug delivery for F5 (1266.50 ± 5.6 µg/cm²) and F5G (1057.7 ± 6.76 µg/cm²) compared to crude APM gel (CR-APMG). In vivo, the inhibition of edema in rat paws was highest with F5G (66.83 ± 0.23%). RAW 264.7 cell studies showed 92.37% nitric oxide inhibition, and histopathology confirmed reduced inflammation. Conclusions: These results support APM-NE gel as a promising topical strategy for psoriasis therapy. Full article

Cell-free network architectures are a promising candidate for sixth-generation (6G) communications, as densely distributed access points (APs) flexibly accommodate traffic demands and mitigate inter-cell interference. In practical cell-free systems employing direct-conversion receivers, however, performance is severely degraded by analog front-end impairments such as in-phase/quadrature (IQ) imbalance and carrier frequency offset (CFO). Conventional orthogonal frequency division multiplexing (OFDM)-based algorithms address these impairments separately, but their joint impact is insufficiently mitigated because IQ imbalance and CFO mutually interfere, leaving residual errors when either is estimated first. To overcome this, we extend our previously proposed adaptive compensation scheme based on time-frequency interferometry-OFDM (TFI-OFDM) by introducing a decision-feedback mechanism. Preliminary CFO estimation and compensation are first performed to suppress inter-symbol interference (ISI), followed by joint estimation and compensation of IQ imbalance and CFO via decision feedback, achieving accurate channel estimation with low pilot overhead. Simulation results demonstrate that the proposed scheme effectively mitigates the mutual interference of both impairments, achieving bit-error-rate (BER) performance close to an ideal impairment-free system. These results confirm that TFI-OFDM-based joint compensation with decision feedback is a promising approach for practical 6G cell-free deployments. Full article

Armenia is located within the central segment of the Arabia–Eurasia continental collision zone and is exposed to significant seismic hazard. This study presents an updated probabilistic seismic hazard assessment (PSHA) for Armenia based on an integrated seismotectonic framework incorporating active fault data, paleoseismological evidence, and historical and instrumental seismicity. A hybrid seismic source model was developed by combining fault-based characteristic earthquake sources with distributed background seismicity. Hazard calculations were performed using the OpenQuake engine within a logic-tree framework to account for epistemic uncertainties in earthquake occurrence and ground-motion prediction. Ground motion was estimated using a weighted set of ground motion prediction equations (GMPEs). Peak ground acceleration (PGA) hazard maps were computed for several return periods, with emphasis on the 475-year return period (10% probability of exceedance in 50 years). The results indicate PGA values across Armenia ranging from approximately 0.2 g to 0.5 g, with the highest hazard levels in northwestern Armenia along the Pambak–Sevan–Syunik Fault System. Hazard deaggregation shows that seismic hazard in major Armenian cities is primarily controlled by shallow earthquakes with magnitudes Mw 6.8–7.4 occurring within ~30 km of urban centers. The results provide a scientific basis for seismic hazard assessment, zonation, and earthquake risk mitigation in Armenia. Full article

Low-dose contrast-enhanced computed tomography (CT) is widely used to reduce contrast-induced toxicity, but reduced iodine concentration and inconsistent acquisition conditions often produce uneven contrast attenuation and spatial misalignment between scans. In this context, we define dose-up translation as the computational process of synthetically enhancing low-dose contrast images to approximate the visual and diagnostic quality of full-dose acquisitions. These factors limit the effective use of routinely acquired imaging data for dose-up translation, particularly in veterinary abdominal CT where respiratory motion and postural variability further degrade anatomical correspondence. We present a weakly aligned enhancement framework designed to operate under spatial misalignment and limited paired data. Registration-based pseudo-references are constructed using a hybrid strategy that combines deformable anatomical alignment with feature-level correspondence. Dose-up translation is performed using structure-preserving translation with multi-scale consistency and edge-aware regularization to maintain anatomical boundaries. To address limited low-dose datasets, a two-stage knowledge transfer strategy transfers anatomical and contrast priors from abundant pre-contrast data. Quantitative evaluation demonstrated region-level contrast-to-noise ratio improvements of up to 31.5% (e.g., from 5.55 to 8.38 in the caudal vena cava (CVC), P < 0.05) compared with baseline enhancement methods across 1171 test slices. Experiments demonstrate consistent improvements in structural fidelity, distributional realism, and region-level vascular conspicuity compared with paired, unpaired, and synthetic-pairing baselines. These findings suggest that the dose-up translation of low-enhanced CT is better formulated as a weakly aligned domain adaptation problem rather than a strictly paired reconstruction task, enabling practical image translation under realistic clinical acquisition variability. Full article

Plant pathogens pose a severe threat to global agricultural production, and their pathogenicity is closely linked to the biosynthesis of secondary metabolites. Basidiomycete within the family Ustilaginaceae represent significant plant pathogens, among which Ustilago maydis, as a model species, has been extensively studied for its secondary metabolites. However, the biosynthetic potential of other species within this family remains poorly understood. In this study, we conducted whole-genome bioinformatic analyses of 16 Ustilaginaceae species, including U. maydis, to systematically identify the distribution of biosynthetic gene clusters (BGCs), core gene domain compositions, and interspecies similarities. A total of 181 predicted BGCs were identified, averaging approximately 11 per species. BGCs for mannosylerythritol lipids (MELs), siderophores, and itaconic acid, as well as the melanin-associated genes pks1 and pks2, were widely distributed across most species. Conversely, an additional melanin biosynthetic gene cluster was found exclusively in U. maydis strain 521, indicating species-specific occurrence. Furthermore, this study identified a novel class of polyketide synthase (PKS) gene clusters with uncharacterized functions across 15 species, exhibiting high sequence and structural conservation between species. These findings reveal the rich metabolic diversity and species-specific biosynthetic potential of Ustilaginaceae, and by using U. maydis as a reference model, we highlight several BGCs (e.g., for MELs, siderophores, itaconic acid, and melanin) that are known to contribute to virulence or pathogenicity in plant hosts. This provides new insights into their pathogenic mechanisms. Full article

In this study, binary and ternary DES systems were prepared using choline chloride (ChCl) with lactic acid (LA), glycerol (GL), urea, and acrylic acid (AA) to extract lignin from Paulownia. The chemical structure of lignin was analyzed to evaluate the structural changes induced by various DES systems, and the isolated lignin was used to prepare DES gels. The results showed that lignin extracted using different DES systems shares similarities in its basic structural framework, with all samples retaining an intact benzene ring structure. However, there are certain differences in the content of the linking bonds and the S/G ratio, and the acidic DES caused the breakage of the β-O-4′ linkage in the lignin molecule, promoting its separation. The molecular weight distribution varied among the DES systems. In the ternary DES, the addition of acrylic acid disrupted lignin’s internal chemical linkages, leading to the precipitation of relatively small lignin molecules. TGA results demonstrated varying levels of thermal resistance among lignin extracted from different DES systems varied, with the best stability observed for lignin extracted from the ChCl-LA system. Lignin extracted from Paulownia using different DES systems was added to the DES gels, and the effects of lignin structure on the properties of the DES gels were investigated. The mechanical, swelling, microstructural, and thermal properties of DES gels prepared from different Paulownia lignin structures showed slight differences; however, no significant discrepancies were observed among the gels. The present work offers a novel strategy for the valorization of lignin derived from lignocellulosic biomass. Full article

Hepatitis B virus (HBV) is the smallest partially double-stranded, reverse-transcribing DNA virus, with four open reading frames (ORFs) encoding viral proteins. It is classified into nine geographically distributed genotypes (A–I). In Kenya, the molecular characterization of HBV among patients seeking medical care remains poorly defined. This observational study aimed to characterize HBV among patients seeking medical care in Kenya’s endemic region, focusing on circulating genotypes and ORF mutations. Serum samples were collected from the outpatient departments of selected health facilities, with demographic and clinical information extracted from patients’ medical records. Hepatitis B surface antigen (HBsAg) was tested at the facilities, and 85 HBsAg-positive samples were collected for molecular analysis. The basal core promoter and pre-core (BCP/PC), polymerase, and surface regions of the viral genome were amplified and sequenced to determine genotypes and to profile their mutations. Out of 85 HBsAg-positive samples, 38 samples tested positive for HBV DNA, and 26 samples were successfully sequenced. HBV genotype A was prevalent at 73.1% (19/26), followed by genotype D at 23.1% (6/26), and genotype E at 3.8% (1/26). Genotype A sequences clustered with both A1 Asian and African subgenotypes, whereas genotype D clustered with subgenotypes D6 and D1. All HBV genotype A, D, and E sequences were serotypes adw2, ayw2, and ayw4, respectively. HBV core promoter mutations (A1762T/G1764A) were detected in both genotype D and genotype A isolates. The pre-core G1896A mutation was highly prevalent in genotype D samples (5/6; 83.3%) but was not observed in genotypes A or E. Analysis of mutations within the “a” determinant region revealed genotype-specific patterns: genotype A predominantly harbored V14A, P46H, S58C, and P67Q substitutions; genotype E showed N59S; and genotype D exhibited V14A, C69stop, S104T, and W182stop mutations. Two drug resistance mutations (V191I and A194T) were present in two chronic patients, one with genotype A and the other with genotype D. In conclusion, HBV genotypes A and D are the most prevalent among Kenyan patients with chronic HBV infection. The presence of point mutations in the ORFs among patients seeking medical care highlights the need for molecular surveillance to better understand the viral diversity and its potential clinical and public health implications. Full article

As social infrastructure intensively developed during the high economic growth period of the 1970s faces simultaneous aging, there is an urgent need to transition from conventional reactive maintenance to preventive maintenance utilizing various data (data-driven asset management. However, the greatest barrier in practice is that inspection data is unevenly distributed in analog formats such as paper and unstructured files, and heavily relies on the subjective visual evaluation of expert engineers (e.g., discrete graded evaluations from A to D). The intervention of this “Assessor Bias” makes it difficult to ensure the robustness required for direct statistical analysis. This paper serves as a bridge between this analog expert knowledge and quantitative data science. It formulates human cognitive conflicts (true state, peer pressure, avoidance of cognitive load) using the distance-decay model of the Analytic Hierarchy Process (AHP) and the Softmax function, constructing a micro-macro link model accompanied by stochastic variations. Through large-scale multi-agent simulations ($N={10}^7$) validating the model’s convergence, it was demonstrated that in long-tail distributions formed under peer pressure, macroscopic statistical distance metrics such as the Kullback-Leibler (KL) divergence ignore the fact that a small number of true signals are non-linearly suppressed, causing a statistical misinterpretation that “the error is within an acceptable range”. This implies that as long as macroscopic statistical indicators are over-trusted, signs of critical deterioration (minorities) will be structurally marginalized. Returning to the debate on “Homogeneity (Homogenität)” in German social statistics, this paper advocates that in order to realize objective “Micro-segmentation of Homogeneous Statistical Populations,” a paradigm shift from qualitative methods relying on human intuition to quantitative methods incorporating multi-criteria decision making is essential, rather than simply expanding the sample size. Full article

Geological hazards induced by large-scale and high-intensity mining activities worldwide are primary drivers of regional ecological degradation and pose significant threats to human safety and property. To construct efficient monitoring systems and enhance early warning capabilities, it is essential to clarify the formation mechanisms of various hazards and the suitability of corresponding technologies. Focusing on four typical geological hazards prevalent in mining areas (surface subsidence, ground fissures, landslides, collapses, and sinkholes), this paper characterizes their specific features and monitoring requirements. It systematically analyzes the physical principles, accuracy levels, and technical advantages and limitations of ground-based, aerial, and spaceborne monitoring, as well as multi-source remote sensing data fusion and emerging technologies (e.g., distributed optical fiber, light detection and range, microseismical monitoring, and deep learning). Utilizing case studies from an open-pit coal mine in Turkey and a loess gully mining area in China, the paper evaluates the effectiveness of methods like multi-temporal InSAR and UAV photogrammetry in identifying the evolution of these hazards. The findings indicate that the technological framework for mining area monitoring is transitioning from single-method approaches to integrated systems. However, given the complex mining environment, several bottleneck challenges remain, including single data dimensions, the limited environmental adaptability of aerospace remote sensing, insufficient stability of deep monitoring equipment, and weak anti-interference capabilities under extreme operating conditions. Consequently, this paper proposes that future innovations in geological hazard monitoring in mining areas will focus on multi-platform hierarchical collaboration, the development of multi-parameter fusion early warning criteria, and the construction of digital and visual platforms. Constructing a comprehensive monitoring system characterized by multi-scale collaboration and dynamic prediction capabilities is vital for improving safety standards in mining areas and achieving coordinated development between resource exploitation and environmental protection. The findings provide a theoretical foundation for the precise prevention and control of mining hazards, as well as for land ecological restoration. Full article