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There are many methods to treat keloid, including various excision operations, laser, injection and radiotherapy. However, few studies have explored the effectiveness of single-hole punch excision in keloid treatment. This study aimed to investigate the efficacy and safety of lateral punch excision combined with intralesional steroid injection for keloid treatment through self-control trial. In this self-controlled trial, 50 patients meet the diagnosis of nodular keloid, and try to choose left–right symmetrical control, one skin lesion in the control group (50 skin lesionsin total) and the other in the observation group (50 skin lesions in total).The keloids in the treatment group were initially treated with punch excision combined with intralesional steroid injection, followed by injection treatment alone. Keloids in the control group received intralesional steroid injection alone. The Vancouver Scar Scale (VSS) of the keloid before and after the punch excision was evaluated; the keloid scores at different time points and the number of injection treatments required in both groups were compared, and adverse reactions were observed. The effective rate of the observation group was 86.0%, which was significantly higher than that of the control group (66.0%), and the recurrence rate of 22% was lower than that of the control group (χ 2  = 4.141,63417), all of which were statistically significant (all P  < 0.05). At the end of treatment, the VSS and total injection times in the observation group were significantly lower than those in the control group (t = 5.900,3.361), with statistical significance ( P  < 0.01). The combination of single-hole punch excision and intralesional steroid injection is an effective method to treat multiple nodular keloids, shortening the treatment course of tralesional steroid injection without obvious adverse reactions.

Cervical cancer is the second leading cause of morbidity and mortality in women worldwide. Traditional treatment methods have become limited. Naringenin, a flavonoid abundant in various fruits and herbal medicines, has demonstrated anti-tumor properties among other effects. This research undertook to elucidate the mechanism of naringenin in the context of cervical cancer treatment by leveraging network pharmacology and performing experimental validation. Initial steps involved predicting potential naringenin targets and subsequently screening for overlaps between these targets and those related to cervical cancer, followed by analysis of their interrelationships. Molecular docking was subsequently utilized to verify the binding effect of the central target. Within the framework of network pharmacology, it was discovered that naringenin might possess anti-cancer properties specific to cervical cancer. Following this, the anti-tumor effects of naringenin on Hela cell viability, migration, and invasion were assessed employing CCK-8, transwell, wound healing assays, and western blotting. Experimental data indicated that naringenin attenuates the migration and invasion of Hela cells via downregulation EGFR/PI3K/AKT signaling pathway. Thus, our findings suggest that naringenin has therapeutic impacts on cervical cancer via multiple mechanisms, primarily by inhibiting the migration and invasion through the EGFR/PI3K/AKT/mTOR pathway. This study offers fresh insights for future clinical studies.

Snowdrift, as a natural disaster, constantly compromises railway traffic by affecting how snow accumulates on the subgrade. This paper establishes a unified set of similarity criteria for wind tunnel testing, using viscous silica sand to simulate snow particles. By employing a geometric scale model (1:30) and similarity criteria (size, motion, dynamics, accumulation patterns, and time scales), it systematically investigates the evolution patterns of wind-induced snow accumulation on two types of roadbed structures: embankments and excavations. This study also evaluates the effectiveness of snow fences, proposing optimized placement distances and quantifying the effects of snow accumulation platform width. The results showed the following: (1) Snow on embankments has a “U”-shaped distribution, with the lowest wind speed (<0.5 m/s) and maximum accumulation at the leeward slope’s foot. In excavations, snow forms an “M”-shaped distribution, with significantly reduced wind speeds (<1 m/s) on the accumulation platform. (2) Snow fences effectively manage snow placement by lowering wind speed (below 1 m/s). A single-row snow fence with a porosity of 50% and a height of 3 m performs best when placed at seven times its height (7 H) from the slope’s toe. (3) A 5 m snow accumulation platform in excavations reduces surface snow accumulation (distribution coefficient drops to 1.6), outperforming scenarios without a platform (coefficient of 2.0). These findings contribute to the prevention and control of snowdrift disasters along railway lines in cold regions. They offer practical guidance for optimizing snow fence configurations, while also laying a foundation for future improvements in experimental accuracy through advanced techniques such as PIV and real-snow testing.

Landslide susceptibility assessment is critical for hazard mitigation and land-use planning. This study evaluates the impact of two different non-landslide sampling methods—random sampling and sampling constrained by the Global Landslide Hazard Map (GLHM)—on the performance of various machine learning and deep learning models, including Naïve Bayes (NB), Support Vector Machine (SVM), SVM-Random Forest hybrid (SVM-RF), and XGBoost. The study area is a 2 km buffer zone along the Duku Highway in Xinjiang, China, with 102 landslide and 102 non-landslide points extracted by aforementioned sampling methods. Models were tested using ROC curves and non-parametric significance tests based on 20 repetitions of 5-fold spatial cross-validation data. GLHM sampling consistently improved AUROC and accuracy across all models (e.g., AUROC gains: NB +8.44, SVM +7.11, SVM–RF +3.45, XGBoost +3.04; accuracy gains: NB +11.30%, SVM +8.33%, SVM–RF +7.40%, XGBoost +8.31%). XGBoost delivered the best performance under both sampling strategies, reaching 94.61% AUROC and 84.30% accuracy with GLHM sampling. SHAP analysis showed that GLHM sampling stabilized feature importance rankings, highlighting STI, TWI, and NDVI as the main controlling factors for landslides in the study area. These results highlight the importance of hazard-informed sampling to enhance landslide susceptibility modeling accuracy and interpretability.

As carbon capture and storage (CCS) technologies mature, the concept of a low-carbon or net-zero-carbon economy becomes more and more feasible. While many chemical and energy products do not contain carbon in their compounds, the upstream production process does. An added CCS module allows the removal of carbon emissions from the production process, which expands the value chain. This paper focuses on one of such commodities—low-carbon-intensity ammonia (LCIA). Even though ammonia is carbon-free in its final product, it is commonly made from natural gas, and the production process could generate significant carbon emissions. The idea of LCIA is to reduce the carbon footprint of the ammonia production process (e.g., blue ammonia) or eliminate carbon from the production process (e.g., green ammonia via electrolysis) so that the entire supply chain is decarbonized. The goal of this paper is two-fold. We first explore the US domestic market and the international market for LCIA. We then discuss relevant federal and local policies that could help grow markets for LCIA. The agricultural sector will be the center of the discussion, which consumes an estimated 70–90% of the global ammonia supply as fertilizers. The paper also examines other potential uses of LCIA, such as alternative fuels for decarbonizing agricultural machinery and transportation sectors. Finally, we argue that developing a comprehensive LCIA value chain, supported by dedicated policy measures and broad stakeholder engagement, is critical for materializing the potential of LCIA in contributing to a climate-resilient and sustainable economy.

Clouds in the sky can significantly affect full-disk observations of the Sun. In cloud-covered full-disk H α images, certain solar features become obscured, posing challenges for further solar research. Obtaining both cloud-covered and corresponding cloud-free images is often challenging, resulting in poor alignment of image pairs in the dataset, which adversely affects the performance of cloud removal models. We use RPix2PixHD, a novel network designed to translate cloud-covered images into cloud-free ones while mitigating the effects of misaligned data on the model. RPix2PixHD comprises two main components, Pix2PixHD and RegNet. Pix2PixHD includes a multiresolution generator and a multiscale discriminator. The generator takes cloud-covered images as input to produce cloud-free images. RegNet computes a deformation field using the generated cloud-free images and the ground truth cloud-free images. This deformation field is then used to resample the generated cloud-free images, resulting in registered images. The correction loss is calculated based on these registered images and utilized for training the generator, thereby enhancing the model’s cloud removal effectiveness. We conducted cloud removal experiments on full-disk H α images obtained from the Huairou Solar Observing Station (HSOS). The experimental results demonstrate that RPix2PixHD effectively removes clouds from cloud-covered solar H α images, successfully restoring solar feature details and outperforming comparative methods.

Emotional responses are significant for understanding public perceptions of urban green space (UGS) and can be used to inform proposals for optimal urban design strategies to enhance public emotional health in the times of COVID-19. However, most empirical studies fail to consider emotion-oriented landscape assessments under dynamic perspectives despite the fact that individually observed sceneries alter with angle. To close this gap, a real-time sentimental-based landscape assessment framework is developed, integrating facial expression recognition with semantic segmentation of changing landscapes. Furthermore, a case study using panoramic videos converted from Google Street View images to simulate changing scenes was used to test the viability of this framework, resulting in five million big data points. The result of this study shows that through the collaboration of deep learning algorithms, finer visual variables were classified, subtle emotional responses were tracked, and better regression results for valence and arousal were obtained. Among all the predictors, the proportion of grass was the most significant predictor for emotional perception. The proposed framework is adaptable and human-centric, and it enables the instantaneous emotional perception of the built environment by the general public as a feedback survey tool to aid urban planners in creating UGS that promote emotional well-being.

In recent years, customer pick-up at collection and delivery points has become a popular alternative to traditional home delivery, which is under great pressure. However, current service of pick-up facilities has seldom been geographically evaluated despite its general uneven distribution and diverse needs. In this paper, in order to interpret the differentiation in customers’ service demands toward reception alternatives and in facilities’ service excludability in different built environments, a two-step floating catchment area (2SFCA) method is improved to measure customers’ spatial accessibility to pick-up facilities, providing a methodology to evaluate the match relation between the differentiated supply and demand of pick-up service. A case study of widespread automated parcel stations (APSs) is conducted in Hangzhou, China and correlative factors to residents’ accessibility are discussed. From the results, residents’ accessibility to pick-up service shows significant spatial unevenness and social inequity in the study area, which is found to correlate most to residences’ maintenance management. As well-managed, gated communities generally hold effective access to exclusive services, most open communities and self-built, single houses are in need of improvement due to inadequate service stemming from a high aging rate, lack of property management, and low service availability of nonexclusive facilities in open areas.

Greenbelt policies are important urban containment policies. On the one hand, they can effectively control the disorderly growth of a city; on the other hand, they can cause other social problems because of their strict control over land development. This paper uses data from 2000 and 2010 and the difference-in-differences (DID) method to evaluate the effects of greenbelt deregulation policies on urban land development in the Seoul metropolitan area (SMA) through a quasi-natural experiment. The results show that first, the deregulation of the greenbelt has significantly furthered urban land development that was not caused by economic development or other factors. Second, the greenbelt deregulation had no significant effects on urban land development in the city centers, but has furthered urban land development near the boundary of Seoul City and greenbelt boundaries. Third, in terms of the effects on land development, the greenbelt deregulation has resulted in regional heterogeneity. Specifically, the greenbelt deregulation has had a significant impact on the urban land development in the southern section of the Han River, whereas the effects of the greenbelt deregulation in the northern area of the Han River are not as obvious.

There is a continued need for investigating the roles of microRNAs and their targets on the pathogenesis of pulmonary arterial hypertension (PAH) vascular remodeling. We recently identified the association of myeloid miR-182-3p and its new target, Myeloid-Associated Differentiation Marker (Myadm), with vascular remodeling. Here, we aimed to determine the role of miR-182-3p/Myadm on PAH vascular remodeling and the underlying molecular mechanism. The miR-182-3p/Myadm expression profiles were detected in PAH patients and experimental rodent models. Loss-of-function and gain-of-function studies using gene knock-in or gene knock-out and the combinations of the proteomic technology and genome-wide ChIP-Seq were employed to determine the downstream targets of miR-182-3p/Myadm in response to monocrotaline (MCT)-induced PAH. The miR-182-3p/Myadm expression was altered in PAH patients and experimental rodent models. Both miR-182-3p inhibitor and overexpression of Myadm augmented the pathological progression in rats in response to MCT-induced PAH. In contrast, miR-182-3p mimic and Myadm gene knockout attenuated the changes in the hemodynamics and structure of the cardio-pulmonary system in MCT-induced PAH in rats. Myadm mediated the proliferation of pulmonary artery smooth muscle cells (PASMCs) by altering the cell cycle kinase inhibitor (p21/Cip1) expression through the transcription factor Krüppel-like factor 4 (KLF4) translocation into the cytoplasm. Our findings indicate the prognostic and therapeutic significance of miR-182-3p in PAH and provide a new regulatory model of the myeloid-derived miR-182-3p/Myadm/KLF4/p21 axis in PAH vascular remodeling.