Search Results (992)

On 7 January 2025, at Beijing time, an M_w7.1 earthquake occurred in Dingri County, Shigatse, Tibet. To accurately determine the fault that caused this earthquake and understand the source mechanism, this study utilized Differential Interferometric Synthetic Aperture Radar (DInSAR) technology to process Sentinel-A data, obtaining the line-of-sight (LOS) co-seismic deformation field for this earthquake. This deformation field was used as constraint data to invert the geometric parameters and slip distribution of the fault. The co-seismic deformation field indicates that the main characteristics of the earthquake-affected area are vertical deformation and east-west extension, with maximum deformation amounts of 1.6 m and 1.0 m for the ascending and descending tracks, respectively. A Bayesian method based on sequential Monte Carlo sampling was employed to invert the position and geometric parameters of the fault, and on this basis, the slip distribution was inverted using the steepest descent method. The inversion results show that the fault has a strike of 189.2°, a dip angle of 40.6°, and is classified as a westward-dipping normal fault, with a rupture length of 20 km, a maximum slip of approximately 4.6 m, and an average slip angle of about −82.81°. This indicates that the earthquake predominantly involved normal faulting with a small amount of left–lateral strike–slip, corresponding to a moment magnitude of M_w7.1, suggesting that the fault responsible for the earthquake was the northern segment of the DMCF (Deng Me Cuo Fault). The slip distribution results obtained from the finite fault model inversion show that this earthquake led to a significant increase in Coulomb stress at both ends of the fault and in the northeastern–southwestern region, with stress loading far exceeding the earthquake triggering threshold of 0.03 MPa. Through analysis, we believe that this Dingri earthquake occurred at the intersection of a “Y”-shaped structural feature where stress concentration is likely, which may be a primary reason for the frequent occurrence of moderate to strong earthquakes in this area. Full article

The harsh conditions of the Qinghai–Tibet Plateau pose significant physiological challenges to local fauna, often resulting in gastrointestinal disorders. However, Tibetan pigs have exhibited remarkable adaptability to the high-altitude stress of the Tibetan Plateau, a phenomenon that remains not fully understood in terms of their gastrointestinal microbiota. This study collected 57 gastrointestinal tract samples from Tibetan pigs (n = 6) and plain black pigs (n = 6) with comparable genetic backgrounds. Samples from the stomach, jejunum, cecum, colon, and rectum, underwent comprehensive metagenomic analysis to elucidate the gut microbiota-related adaptive mechanisms in Tibetan pigs to the extreme high-altitude environment. A predominance of Pseudomonadota was observed within gut microbiome of Tibetan pigs. Significant differences in the microbial composition were also identified across the tested gastrointestinal segments, with 18 genera and 141 species exhibiting differential abundance. Genera such as Bifidobacterium, Megasphaera, Fusobacterium, and Mitsuokella were significantly more abundant in Tibetan pigs than in their lowland counterparts, suggesting specialized adaptations. Network analysis found greater complexity and modularity in the microbiota of Tibetan pigs compared to black pigs, indicating enhanced ecological stability and adaptability. Functional analysis revealed that the Tibetan pig microbiota was particularly enriched with bacterial species involved in metabolic pathways for propionate and butyrate, key short-chain fatty acids that support energy provision under low-oxygen conditions. The enzymatic profiles of Tibetan pigs, characterized by elevated levels of 4-hydroxybutyrate dehydrogenase and glutaconyl-CoA decarboxylase, highlighted a robust fatty acid metabolism and enhanced tricarboxylic acid cycle activity. In contrast, the gut microbiome of plain black pigs showed a reliance on the succinate pathway, with a reduced butyrate metabolism and lower metabolic flexibility. Taken together, these results demonstrate the crucial role of the gastrointestinal microbiota in the adaptation of Tibetan pigs to high-altitude environments by optimizing carbohydrate metabolism and short-chain fatty acid production for efficient energy utilization. This study not only highlights the metabolic benefits conferred by the gut microbiota of Tibetan pigs in extreme environments, but also advances our understanding of the adaptive gastrointestinal mechanisms in plateau-dwelling animals. These insights lay the foundation for exploring metabolic interventions to support health and performance in high-altitude conditions. Full article

This study investigates the influence of urban tourists’ behaviour on the environmental performance of a destination, particularly in terms of carbon emissions. Tourist-related emissions are shaped by their choices and behaviours, impacting the overall carbon footprint of the locations they visit. To assess this impact, we introduce a methodology for quantifying greenhouse gas emissions linked to tourists’ energy consumption. This approach considers key tourism components—activities, accommodation, and transportation—analysing their roles in emissions across a trip’s temporal and spatial dimensions. By integrating tourists’ spatiotemporal behaviour with emissions data, our framework offers insights that can support local climate-responsive urban and tourism policies. We empirically apply the proposed model to the destination of Donostia/San Sebastián (Spain), where the primary travel sequences of visitors are analysed. We utilise cartographic techniques to map the environmental footprints of different tourist profiles, such as cultural and nature tourists. The findings indicate that visitors primarily motivated by nature and outdoor recreation constitute the segment with the highest greenhouse gas emissions (with a minimum footprint of 30.69 kg CO₂-equivalent per trip), followed by cultural tourists, and finally, other categories of visitors. The results highlight the practical applications of the proposed model for sustainable tourism management, providing valuable guidance for urban planners and policymakers in mitigating the environmental impacts of tourism. Full article

Investigations carried out on 72 fluid samples from 59 sites spread over the area surrounding the Sea of Marmara show that their geochemical and isotopic features are related to different segment settings of the North Anatolian Fault Zone (NAFZ). We collected fluids from thermal and mineral waters including bubbling and dissolved gases. The outlet temperatures of the collected waters ranged from 14 to 97 °C with no temperature-related geochemical features. The free and dissolved gases are a mixture of shallow and mantle-derived components. The large variety of geochemical features comes from intense gas–water (GWI) and water–rock (WRI) interactions besides other processes occurring at relatively shallow depths. CO₂ contents ranging from 0 to 98.1% and helium isotopic ratios from 0.11 to 4.43 Ra indicate contributions, variable from site to site, of mantle-derived volatiles in full agreement with former studies on the NAFZ. We propose that the widespread presence of mantle-derived volatiles cannot be related only to the lithospheric character of the NAFZ branches and magma intrusions have to be considered. Changes in the vertical permeability induced by fault movements and stress accumulation during seismogenesis, however, modify the shallow/deep ratio of the released fluids accordingly, laying the foundations for future monitoring activities. Full article

Background: Referred pain frequently co-exists with visceral pain. However, the exact mechanism governing referred somatic hyperalgesia remains elusive. Methods: By injecting 20% acetic acid into the stomach, we established a mouse model of gastric ulcer (GU). Hematoxylin and eosin (H&E) staining was used as the evaluation criterion for the gastric ulcer model. Evan’s blue (EB) and von Frey tests detected the somatic sensitized area. The DRG neurons distributed among the spinal segments of the sensitized area were prepared for biochemical and electrophysiological experiments. The CCR2 antagonist was intraperitoneally (i.p.) injected into GU mice to test the effect of blocking CCR2 on somatic neurogenic inflammation. Results: GU not only instigated neurogenic plasma extravasation and referred somatic allodynia in the upper back regions spanning the T9 to T11 segments but also augmented the co-expression of T-type Ca²⁺ channels and CCR2 and led to the gating properties of T-type Ca²⁺ channel alteration in T9–T11 small-diameter DRG neurons. Moreover, the administration of the CCR2 antagonist inhibited the T-type Ca²⁺ channel activation, consequently mitigating neurogenic inflammation and referred somatic hyperalgesia. The application of the CCR2 agonist to normal T9–T11 small-diameter DRG neurons simulates the changes in the gating properties of T-type Ca²⁺ channel that occur in the GU group. Conclusions: Therefore, these findings indicate that CCR2 may function as a critical regulator in the generation of neurogenic inflammation and mechanical allodynia by modulating the gating properties of the T-type Ca²⁺ channels. Full article

Poly (butylene adipate-co-terephthalate) (PBAT) foam sheets prepared by foaming supercritical fluids are characterized by high resilience, homogeneous cellular structure, and well-defined biodegradability. However, the inert chemical structure and the rigid hard segments restrict the diffusion of CO₂ within the PBAT matrix, resulting in extremely long gas saturation times as long as 9 h at a thickness of 12 mm. In this study, microporous structures were pre-introduced into the PBAT matrix to provide a fast gas diffusion pathway during the saturation process. After 2 h of saturation, PBAT foam sheets with expansion ratio of 10 to 13.8 times were prepared. The interaction of CO₂ with PBAT was systematically investigated, and the CO₂ sorption process was evaluated kinetically and thermodynamically using the Fickian diffusion theory. The solubility and diffusion rate of CO₂ in pretreated PBAT sheets with different microporous sizes and densities were investigated, and the effects of pretreatment strategies on the foaming behavior and cell structure of PBAT foam sheets were discussed. The introduction of a microporous structure not only reduces saturation time but also enhances solubility, enabling the successful preparation of soft foams with high expansion ratios and resilience. After undergoing foaming treatment, the PBAT pretreated sheets with a 10 μm microporous structure and a density of 0.45 g/cm³ demonstrated improved mechanical properties: their hardness decreased to 35 C while resilience increased to 58%, reflecting enhanced elastic recovery capabilities. The pretreatment method, which increases the diffusion rate of CO₂ in PBAT sheets, offers a straightforward approach that provides valuable insights into achieving rapid and efficient foaming of thick PBAT sheets in industrial applications. Full article

With the advancement of polarimetric synthetic aperture radar (PolSAR) imaging technology and the growing demand for image interpretation, extracting meaningful land cover information from PolSAR images has become a key research focus. To address the segmentation challenge, we propose an innovative method. First, features from co-polarization and cross-polarization channels are separately used as dual inputs, and a cross-attention mechanism effectively fuses these features to capture correlations between different polarization information. Second, a diffusion framework is employed to jointly model target features and class probabilities, aiming to improve segmentation accuracy by learning and fitting the probabilistic distribution of target labels. Finally, experimental results demonstrate that the proposed method achieves superior performance in PolSAR image segmentation, effectively managing complex polarization relationships while offering robustness and broad application potential. Full article

The mechanism of post-acute sequelae of SARS-CoV-2 (PASC) is unknown. Using optical coherence tomography angiography (OCT-A), we compared retinal foveal avascular zone (FAZ), vessel density (VD), and vessel length density (VLD) in non-hospitalized Neuro-PASC patients with those in healthy controls in an effort to elucidate the mechanism underlying this debilitating condition. Neuro-PASC patients with a positive SARS-CoV-2 test and neurological symptoms lasting ≥6 weeks were included. Those with prior COVID-19 hospitalization were excluded. Subjects underwent OCT-A with segmentation of the full retinal slab into the superficial (SCP) and deep (DCP) capillary plexus. The FAZ was manually delineated on the full slab in ImageJ. An ImageJ macro was used to measure VD and VLD. OCT-A variables were analyzed using linear mixed-effects models with fixed effects for Neuro-PASC, age, and sex, and a random effect for patient to account for measurements from both eyes. The coefficient of Neuro-PASC status was used to determine statistical significance; p-values were adjusted using the Benjamani–Hochberg procedure. Neuro-PASC patients (N = 30; 60 eyes) exhibited a statistically significant (p = 0.005) reduction in DCP VLD compared to healthy controls (N = 44; 80 eyes). The sole reduction in DCP VLD in Neuro-PASC may suggest preferential involvement of the smallest blood vessels. Full article

Chinese bayberry (Myrica rubra or Morella rubra) is a valuable fruit, yet the mechanism of its flesh segment development is not well understood. Using paraffin sectioning, we investigated the flower buds of the ‘Biqi’ and ‘Zaojia’ varieties, revealing that the flesh segment development in these Chinese bayberry varieties involved the formation of a primordium outside the ovary wall, the establishment of a simple columnar structure, and the formation of the primary flesh segment. Assessment of endogenous hormone levels indicated the significant reductions in jasmonic acid (JA) and indole-3-acetic acid (IAA) levels at the critical stages of flesh segment development. Correlation analysis highlighted the essential roles of IAA, JA, abscisic acid (ABA), and gibberellins in the flesh segment developmental process, underscoring the complex interactions driven primarily by the IAA, JA, and ABA networks. Gene modules positively correlated with flesh segment development were identified using transcriptome-based weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) were enriched in plant hormone signal transduction pathways, particularly for upregulated genes associated with auxin and JA signaling. Key genes predicted to be involved in flesh segment development included LAX2 and LAX3 (auxin transport), JAZ6 (JA signaling repression), and KAN1 and KAN4 (regulating multiple hormonal signaling pathways). Quantitative real-time polymerase chain reaction (qRT-PCR) validation confirmed that the expression trends for these genes were consistent across both varieties, particularly for CRC, SEP1, SEP3, IAA7, and JAZ6. Immunofluorescence localization studies revealed that auxin was primarily distributed in the central vascular bundle and outer cells of the flesh segment. This uneven auxin distribution might contribute to the unique morphology of flesh segments. Overall, this study provides insights into the hormonal regulation and genetic factors involved in the development of Chinese bayberry flesh segments. Full article

To address the issue of low segmentation accuracy for small objects in the Mask Dino segmentation method, we propose an improved small object segmentation model called FFMask Dino. Initially, we introduce scaled cosine attention and the log-cpb method into the Swin Transformer backbone network. Subsequently, by adjusting the network structure, we enhance the feature extraction process, which helps the model maintain generalization across different datasets and reduces the risk of overfitting. Lastly, we propose the FFPN module to optimize the pathways for feature fusion and transmission. The improved FPN reduces unnecessary computations, accelerates model inference speed, and integrates multi-scale feature details and high-level semantic information to complement object features, thereby enhancing model segmentation accuracy. Experimental results demonstrate that the improved segmentation model achieves a mean Intersection over Union (mIoU) of 42.15% on the ADE20K dataset for semantic segmentation tasks, representing a 0.96% increase compared to the Mask Dino method. On the CoCo dataset for instance segmentation tasks, with the Swin Transformer backbone, the Mask AP and Box AP are 47.10 and 52.60, respectively, showing improvements of 1% and 1.3% over the Mask Dino method. With the ResNet-50 backbone, the Mask AP and Box AP are 40.00 and 44.10, respectively, with improvements of 0.5% and 0.9% over the Mask Dino method. For the CoCo dataset’s panoptic segmentation tasks, with the Swin Transformer backbone, the PQ is 54.95, showing a 0.4% increase over the Mask Dino method. With the ResNet-50 backbone, the PQ is 46.93, showing a 0.9% increase over the Mask Dino method. These results effectively demonstrate the improved accuracy and precision of Mask Dino in segmenting small objects across various segmentation tasks. Full article

Functional membranes with waterproof, breathable, and thermal regulation capabilities are increasingly sought after across various industries. However, developing such functional membranes commonly involves complex multi-step preparation processes. Herein, we introduced perfluorodecyltriethoxysilane (FAS) into the poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) solution for one-step electrospinning, successfully fabricating membranes that combine these properties. The hydrophobicity of the PVDF-HFP/FAS membrane was greatly improved with the water contact angle increased from 120.6° to 142.9° and the solar reflectance rising from 72% to 92% due to the presence of fluorocarbon segments. The synergistic effect of enhanced hydrophobicity, small pore size, and elevated solar reflectivity resulted in robust water resistance (62 kPa), excellent water vapor transmission rate (12.4 kg m⁻² d⁻¹), and superior cooling performance (6.4 °C lower than commercial cotton fabrics). These findings suggest that the proposed PVDF-HFP/FAS membranes, characterized by desired multifunction characteristics and scalable production, hold great potential for application in diverse strategic fields. Full article

The Aburrá Valley, located in the northwestern region of Colombia, has undergone significant land cover changes and urban expansion in recent decades, driven by rapid population growth and infrastructure development. This region, known for its steep topography and dense urbanization, faces considerable environmental challenges. Monitoring these transformations is essential for informed territorial planning and sustainable development. This study leverages Synthetic Aperture Radar (SAR) imagery from the Sentinel-1 mission, covering 2017–2024, to propose a methodology for the multitemporal analysis of land cover dynamics and urban expansion in the valley. The novel proposed methodology comprises several steps: first, monthly SAR images were acquired for every year under study from 2017 to 2024, ensuring the capture of surface changes. These images were properly calibrated, rescaled, and co-registered. Then, various multitemporal fusions using statistics operations were proposed to detect and find different phenomena related to land cover and urban expansion. The methodology also involved statistical fusion techniques—median, mean, and standard deviation—to capture urbanization dynamics. The kurtosis calculations highlighted areas where infrequent but significant changes occurred, such as large-scale construction projects or sudden shifts in land use, providing a statistical measure of surface variability throughout the study period. An advanced clustering technique segmented images into distinctive classes, utilizing fuzzy logic and a kernel-based method, enhancing the analysis of changes. Additionally, Pearson correlation coefficients were calculated to explore the relationships between identified land cover change classes and their spatial distribution across nine distinct geographic zones in the Aburrá Valley. The results highlight a marked increase in urbanization, particularly along the valley’s periphery, where previously vegetated areas have been replaced by built environments. Additionally, the visual inspection analysis revealed areas of high variability near river courses and industrial zones, indicating ongoing infrastructure and construction projects. These findings emphasize the rapid and often unplanned nature of urban growth in the region, posing challenges to both natural resource management and environmental conservation efforts. The study underscores the need for the continuous monitoring of land cover changes using advanced remote sensing techniques like SAR, which can overcome the limitations posed by cloud cover and rugged terrain. The conclusions drawn suggest that SAR-based multitemporal analysis is a robust tool for detecting and understanding urbanization’s spatial and temporal dynamics in regions like the Aburrá Valley, providing vital data for policymakers and planners to promote sustainable urban development and mitigate environmental degradation. Full article

Transport emissions are a major contributor to global CO₂ emissions, requiring interventions to promote sustainable travel behaviors. This study examines how behavior change techniques (BCTs), attitudinal and behavioral segmentation, and time pressure influence green route selection in a simulated journey-planning app. Using a randomized 2 × 3 × 3 factorial design, 600 UK participants completed travel booking tasks under three time-pressure scenarios (low, moderate, high) using either a control app or a BCT-enhanced intervention app. Participants were segmented based on environmental attitudes, public transport preferences, and travel needs. Multilevel logistic regression showed significant main effects for condition, segment, and time pressure. Participants using the intervention app were more likely to select green routes (5.39, p < 0.001). Segments with a more positive attitude to public transport demonstrated higher baseline green route selection compared to those with low public transport attitudes (odds ratio [OR] = 0.31, p = 0.020). Moderate time pressure facilitated the highest likelihood of green route selection, while low (OR = 0.16, p < 0.001) and high (OR = 0.48, p < 0.001) time pressures reduced green bookings. Interaction effects were non-significant, potentially reflecting the sample size. The findings highlight the potential of BCT-enhanced apps to promote sustainable travel, particularly when tailored to user segments and designed to address time pressure. Future research should explore real-world applications and intervention durability. Full article

Aviation’s non-CO₂ effects account for approximately 66% of the sector’s Effective Radiative Forcing (ERF). However, non-CO₂ emissions and their climate effects are particularly challenging to assess due to the number of variables involved. This research provides a framework for characterizing the full climate impact of individual real-world flights in terms of global surface temperature change (ΔT) with the aid of a validated CFM56-7B26/3 engine model and spatially and temporally resolved meteorological data. Different modelling methods were used to evaluate NO_x and soot emissions and the relative differences between them were quantified, while a contrail formation model was implemented to quantify the distances travelled where persistent contrails were formed. The ΔT was evaluated over 77 years using a Linear Temperature Response Model (LTR). The results show that NO_x-induced effects such as the increase in short-term ozone had the highest impact on ΔT in the first year of emissions, while CO₂ was more detrimental to ΔT in the long term. Unlike the mid and long-range flights examined, the climb segment of the short-range flight had a more significant impact on ΔT than the cruise segment. ΔT sensitivity studies for different emission modelling methods showed differences up to 13% for NO_x and 14% for soot. Full article

Cold tolerance in rapeseed is closely related to its growth, yield, and geographical distribution. However, the mechanisms underlying cold resistance in rapeseed remain unclear. This study aimed to explore cold resistance genes and provide new insights into the molecular mechanisms of cold resistance in rapeseed. Rapeseed M98 (cold-sensitive line) and D1 (cold-tolerant line) were used as parental lines. In their F₂ population, 30 seedlings with the lowest cold damage levels and 30 with the highest cold damage levels were selected to construct cold-tolerant and cold-sensitive pools, respectively. The two pools and parental lines were analyzed using bulk segregant sequencing (BSA-seq). The G’-value analysis indicated a single peak on Chromosome C09 as the candidate interval, which had a 2.59 Mb segment with 69 candidate genes. Combined time-course and weighted gene co-expression network analyses were performed at seven time points to reveal the genetic basis of the two-parent response to low temperatures. Twelve differentially expressed genes primarily involved in plant cold resistance were identified. Combined BSA-seq and transcriptome analysis revealed BnaC09G0354200ZS, BnaC09G0353200ZS, and BnaC09G0356600ZS as the candidate genes. Quantitative real-time PCR validation of the candidate genes was consistent with RNA-seq. This study facilitates the exploration of cold tolerance mechanisms in rapeseed. Full article