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The timely identification of rail internal defects and the application of corresponding preventive measures would greatly reduce catastrophic failures, such as rail breakage. Ultrasonic rail defect detection is the current mainstream rail defect detection method thanks to its advantages of strong penetration, high accuracy, and ease to deploy. The 2D B-scan image output by ultrasonic detectors contains rich features of defects; however, rail engineers manually identify and localize the defect image, which can be time-consuming, and the image may be subject to missing identification or mistakes. This paper adopted state-of-the-art deep learning algorithms for novel B-scan images for the automatic identification and localization of rail internal tracks. First, through image pre-processing of classification, denoising, and augmentation, four categories of defect image datasets were established, namely crescent-shaped fatigue cracks, fishbolt hole cracks, rail web cracks, and rail base transverse cracks; then, four representatives of deep learning object detection networks, YOLOv8, YOLOv5, DETR, and Faster R-CNN, were trained with the defects dataset and further applied to the testing dataset for defect identification; finally, the performances of the three detection networks were compared and evaluated at the data level, the network structure level, and the interference adaptability level, respectively. The results show that the YOLOv8 network can effectively classify and localize four categories of internal rail defects in B-scan images with a 93.3% mean average precision at three images per second, and the detection time is 58.9%, 376.8%, and 123.2% faster than YOLO v5, DETR, and Faster R-CNN, respectively. The proposed approach could ensure the real-time, accurate, and efficient detection and analysis of internal defects to a rail. [ABSTRACT FROM AUTHOR]

Cangzhou is located in the northeast part of the North China Plain; here, groundwater is the main water source for production and living. Due to the serious regional land subsidence caused by long-term overexploitation of groundwater, the monitoring of land subsidence in this area is significant. In this paper, we used the Small Baseline Subsets Interferometric Point Target Analysis (SBAS-IPTA) technique to process the Envisat-ASAR, Radarsat-2, and Sentinel-1A data and obtained the land subsidence of Cangzhou from 2004 to 2020. Additionally, we obtained winter wheat distribution information in Cangzhou using the Pixel Information Expert Engine (PIE-Engine) remote sensing cloud platform. On this basis, we analyzed the relationship between ground water level, winter wheat planting area, and the response of land subsidence according to the land use type and groundwater level monitoring data near the winter wheat growing area. The results show that during 2004–2020, the average annual subsidence rate of many places in Cangzhou was higher than 30 mm/year, and the maximum subsidence rate was 115 mm/year in 2012. From 2004 to 2020, the area of the subsidence funnel showed a trend of first increasing and then decreasing. In 2020, the subsidence funnel area reached 6.9 × 103 km2. The winter wheat planting area in the urban area showed a trend of first decreasing, then increasing and then decreasing, and it accounted for a large proportion in the funnel area. At the same time, we studied the relationship between the land subsidence rate and the water level at different burial depths and the response of winter wheat planting area. The results showed that the change of confined water level had a stronger response with the other two variables. [ABSTRACT FROM AUTHOR]

Log-based public key infrastructure(PKI) refers to a robust class of CA-attack-resilient PKI that enhance transparency and accountability in the certificate revocation and issuance process by compelling certificate authorities (CAs) to submit revocations to publicly and verifiably accessible logs. However, log-based PKIs suffer from a reliance on centralized and consistent sources of information, rendering them susceptible to split-world attacks, and they regrettably fail to provide adequate incentives for recording or monitoring CA behavior. Blockchain-based PKIs address these limitations by enabling decentralized log audits through automated financial incentives. However, they continue to face challenges in developing a scalable revocation mechanism suited for lightweight clients. In this paper, we introduce BRT, a scalable blockchain-based system for certificate and revocation transparency. It serves to log, audit, and validate the status of certificates within the transport layer security (TLS)/secure sockets layer(SSL) PKI domain. We designed an audit-on-chain framework, coupled with an off-chain storage/computation system, to enhance the efficiency of BRT when operating in a blockchain environment. By implementing a blockchain-based prototype, we demonstrate that BRT achieves storage-efficient log recording with a peak compression rate reaching 8%, cost-effective log updates for large-scale certificates, and near-instantaneous revocation checks for users. [ABSTRACT FROM AUTHOR]

To address the topic of building age-friendly cities that better meet the needs of the elderly in a sustainable-city-oriented manner, this paper focuses on the interaction between the needs of the elderly and urban facilities in the urban built environment in order to propose a comprehensive evaluation method regarding the friendliness of urban facilities with respect to the elderly in large urban areas. The development of the proposed method was guided by the distribution characteristics of the elderly population and combines a spatial measurement evaluation, which is based on the spatial distribution characteristics of urban facilities for the elderly, and a post-use measurement evaluation, which is based on the characteristics of use by the elderly. Taipei City and New Taipei City are then taken as examples for evaluation. From the final evaluation results of the Boston four-quadrant analysis, the areas with higher spatial and post-use metric evaluation values were defined as areas of high concern, while those with lower spatial and higher post-use metric evaluation values were defined as advantage-maintained areas. These two types of areas accounted for about 58% of the total area, and are distributed in the Taipei urban area and northeast New Taipei City. The areas with higher spatial and lower post-use metric evaluation values were defined as priority improvement areas, while those with lower spatial and post-use metric evaluation values were defined as key complement areas. These two types of area accounted for about 42%, and are mainly distributed in the northwest part of Taipei City, as well as the western and southern mountainous areas of New Taipei City. Accordingly, region-specific planning policy recommendations were provided. [ABSTRACT FROM AUTHOR]

High-speed railways in the Beijing–Tianjin–Hebei (BTH) Plain are gradually becoming more widespread, covering a greater area. The operational safety of high-speed railways is influenced by the continuous development of land subsidence. It is necessary to predict the subsidence along the high-speed railways; thus, this work is of critical importance to the safety of high-speed railway operation. In this study, we processed Sentinel-1A data using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the land subsidence in the typical BTH area. Then, we combined the Empirical Mode Decomposition (EMD) and Gradient Boosting Decision Tree (GBDT) methods (EMD-GBDT) to forecast land subsidence along high-speed railways. The results revealed that some parts of the high-speed railways in the BTH plain had passed through or approached the land subsidence area; the maximum cumulative subsidence of the Beijing–Shanghai, Tianjin–Baoding and Shijiazhuang–Jinan high-speed railways reached 326 mm, 384 mm and 350 mm, respectively. The forecasting accuracy for land subsidence along high-speed railways was enhanced by the EMD-GBDT model. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.38 mm to 0.56 mm and 0.23 mm to 0.38 mm, respectively. [ABSTRACT FROM AUTHOR]

Mitochondrial alternative oxidase 1a (AOX1a) plays an extremely important role in the critical node of seed viability during storage. However, the regulatory mechanism is still poorly understood. The aim of this study was to identify the regulatory mechanisms by comparing OsAOX1a-RNAi and wild-type (WT) rice seed during artificial aging treatment. Weight gain and time for the seed germination percentage decreased to 50% (P50) in OsAOX1a-RNAi rice seed, indicating possible impairment in seed development and storability. Compared to WT seeds at 100%, 90%, 80%, and 70% germination, the NADH- and succinate-dependent O2 consumption, the activity of mitochondrial malate dehydrogenase, and ATP contents all decreased in the OsAOX1a-RNAi seeds, indicating that mitochondrial status in the OsAOX1a-RNAi seeds after imbibition was weaker than in the WT seeds. In addition, the reduction in the abundance of Complex I subunits showed that the capacity of the mitochondrial electron transfer chain was significantly inhibited in the OsAOX1a-RNAi seeds at the critical node of seed viability. The results indicate that ATP production was impaired in the OsAOX1a-RNAi seeds during aging. Therefore, we conclude that mitochondrial metabolism and alternative pathways were severely inhibited in the OsAOX1a-RNAi seeds at critical node of viability, which could accelerate the collapse of seed viability. The precise regulatory mechanism of the alternative pathway at the critical node of viability needs to be further analyzed. This finding might provide the basis for developing monitoring and warning indicators when seed viability declines to the critical node during storage. [ABSTRACT FROM AUTHOR]

As ancient cities are spaces that represent the development of civilization, it is worth exploring and studying their characteristics and conceptions of land use. In this regard, the focus has turned to the issue of how to achieve the efficient mining of massive urban remote sensing data through human–computer collaboration. In this paper, a new intelligent method of analyzing urban land use characteristics and their cultural significance is proposed; it is feasible, effective, accurate, manageable, and portable. The method is based on a geographic information system (GIS) and a specific algorithm. The city plan was calibrated with the help of satellite remote sensing images and sites. By constructing the "urban element area acquisition and analysis model", various operations for areas in the city plan were realized, including an area value calculation, land use structure calculation, area modulus analysis, area ratio analysis between areas, and determination of the cultural significance of numbers and ratios. Taking the Sui and Tang dynasties capital city of Chang'an as an example, we found the existence of a set of urban planning techniques through area modulus (standard area units) for the first time; it took the market area as the modulus A and the area of Daxing Palace as the expanded modulus 2A, made the area of important areas in the city an integer multiplied by the modulus value (for example, the overall scope of the city is 100A, the rectangular urban area is 90A, and the small city area is 10A), and made the key values and numerical ratios have a cultural significance (such as 4.5, 5.5, 10, 25, 30, 100, 12:10, 1.618:1, 9:5, 45:1, 2:1), reflecting the planning and design concept of the capital city, into which the ancient Chinese deliberately integrated "number, shape and meaning". In addition, we carried out supplementary verification with the Roman city of Timgad and the Japanese city of Heijo-kyo, discovering that they also have design methods for area planning. We believe that land use planning can better meet the practical needs of urban resource distribution. Compared with urban form design, it might have chronological precedence. By setting the area modulus and the modulus value of each area, the grid-shaped city achieves the rational distribution of land and the establishment of order in an efficient way, and this thought and operation method greatly contributed to the advancement of ancient civilizations. [ABSTRACT FROM AUTHOR]

The automated detection of distress such as cracks or potholes is a key basis for assessing the condition of pavements and deciding on their maintenance. A fine-grained pavement distress-detection algorithm based on integrated data using a digital twin is proposed to solve the challenges of the insufficiency of high-quality negative samples in specific scenarios An asphalt pavement background model is created based on UAV-captured images, and a lightweight physical engine is used to randomly render 5 types of distress and 3 specific scenarios to the background model, generating a digital twin model that can provide virtual distress data. The virtual data are combined with real data in different virtual-to-real ratios (0:1 to 5:1) to form an integrated dataset and used to fully train deep object detection networks for fine-grained detection. The results show that the YOLOv5 network with the virtual-to-real ratio of 3:1 achieves the best average precision for 5 types of distress (asphalt pavement MAP: 75.40%), with a 2-fold and 1.5-fold improvement compared to models developed without virtual data and with traditional data augmentation, respectively, and achieves over 40% recall in shadow, occlusion and blur. The proposed approach could provide a more reliable and refined automated method for pavement analysis in complex scenarios. [ABSTRACT FROM AUTHOR]

The digital economy is fundamentally altering human productivity and lifestyles, gradually becoming a new engine that drives energy technology transformation and optimizes the energy consumption structure. This paper examines the impact of the digital economy on upgrading the energy consumption structure using panel data from 30 Chinese provinces from 2013 to 2019. The empirical findings indicate that the digital economy's development can help to improve energy consumption structure, and this impact can have a threshold effect. Heterogeneity analysis reveals that upgrading the energy consumption structure affected by the digital economy is more significant in lower digital divide regions, the eastern and central regions, and provinces with high economic development levels. Moreover, the findings of a mechanism analysis demonstrate that the digital economy primarily influences green technology innovation, and government environmental regulation affects the major upgrades of the energy consumption structure. [ABSTRACT FROM AUTHOR]

How to combine science and technology with the humanities in the research on ancient cities to reveal ancient peoples' urban planning thoughts is worthy of in-depth study. The capitals of the Western Han dynasty as well as the Sui and Tang dynasties were some of the greatest cities in the world at the time. This paper takes them as its subjects and puts forward a method to study the spatial relationship between ancient cities and the natural environment by combining spatial information technology and cultural analysis. Firstly, satellite images, elevation maps, urban ichnographies, and literature materials were collected and sorted to deeply understand the cultural thoughts involved in ancient urban planning; based on this, key element points were marked and rechecked on the spot, and the above drawings were accurately superimposed by GIS technology to form a geographic information base that integrated multisource information. Then, Python was used to construct a "decision model of spatial relationship between urban elements and natural elements", and rules as well as parameters were set through man–machine collaboration. The decision model was used to test the geographic information base, and the information of strong correlations between urban objects and natural objects was outputted. The drawings were exported after screening, and a visual expression was realized with Illustrator software. The research results indicated that this analysis method was feasible, effective, and easy to promote. The new archaeological discoveries included eight important line segments with a 9:6 proportional relationship (which represents the balance of Yin and Yang) and two important line segments with a 9:5 proportional relationship (which represents the supreme imperial power) in the capitals of the Western Han dynasty as well as the Sui and Tang dynasties, and 16 contraposition lines in a positive direction or oblique 45° direction (which reflects the close relationship between urban elements and natural elements). We consider that the two capitals were intentionally closely related to natural environments such as mountain peaks and valley entrances in the planning stage, and that proportions and scales with profound humanistic meaning were selected. The capital of the Sui and Tang dynasties was specially aligned with the capital of the Western Han dynasty in space. These characteristics embody ancient Chinese Confucian cultural thoughts such as the "integration of yang and yin", "harmony between nature and humans", the "supremacy of emperors", and the "use of numbers and shapes to convey meaning". [ABSTRACT FROM AUTHOR]

The Allee effect is widespread among endangered plants and animals in ecosystems, suggesting that a minimum population density or size is necessary for population survival. This paper investigates the stability and pattern formation of a predator–prey model with nonlinear reactive cross-diffusion under Neumann boundary conditions, which introduces the Allee effect. Firstly, the ODE system is asymptotically stable for its positive equilibrium solution. In a reaction system with self-diffusion, the Allee effect can destabilize the system. Then, in a reaction system with cross-diffusion, through a linear stability analysis, the cross-diffusion coefficient is used as a bifurcation parameter, and instability conditions driven by the cross-diffusion are obtained. Furthermore, we show that the system (5) has at least one inhomogeneous stationary solution. Finally, our theoretical results are illustrated with numerical simulations. [ABSTRACT FROM AUTHOR]

A rapid and accurate determination method for total phenolic content is of great importance for controlling the quality of wine samples. A promising potentiometric detection approach, based on permanganate ion fluxes across ion-selective electrode membranes, is fabricated for measuring the total phenolic content of wine. The results show that the presence of phenols, such as gallic acid, leads to a potential increase for the potentiometric sensor. Additionally, the present sensor exhibits a linear potential response with the concentration range from 0.05 to 3.0 g/L with a detection limit of 6.6 mg/L calculated using gallic acid. These sensors also exhibit a fast response time, an acceptable reproducibility and long-term stability. These results indicate that the proposed potentiometric sensor can be a promising and reliable tool for the rapid determination of total phenolic content in wine samples. [ABSTRACT FROM AUTHOR]

A colorimetric immunoassay has been reported for prostate-specific antigen (PSA) detection with CuO nanoparticles (CuO NPs) as signal labels. The method is based on Cu2+-catalyzed oxidation of ascorbic acid (AA) by O2 to depress the formation of colored gold nanoparticles (AuNPs). Specifically, HAuCl4 can be reduced by AA to produce AuNPs in situ. In the presence of target, CuO NPs-labeled antibodies were captured via the sandwich-type immunoreaction. After dissolving CuO nanoparticles with acid, the released Cu2+ catalyzed the oxidation of AA by O2, thus depressing the generation of AuNPs. To demonstrate the accuracy of the colorimetric assay, the released Cu2+ was further determined by a fluorescence probe. The colorimetric immunoassay shows a linear relationship for PSA detection in the range of 0.1~10 ng/mL. The detection limit of 0.05 ng/mL is comparable to that obtained by other CuO NPs-based methods. The high throughput, simplicity, and sensitivity of the proposed colorimetric immunoassay exhibited good applicability for assays of serum samples. [ABSTRACT FROM AUTHOR]

The cell microenvironment consists of multiple types of biophysical and biochemical factors, and represents a complex integrated system that is variable in both time and space. Studies show that changes in biochemical and biophysical factors in cell microenvironments result in significant changes in cellular forms and functions, especially for stem cells. Mesenchymal stem cells (MSCs) are derived from adult stem cells of the mesoderm and play an important role in tissue engineering, regenerative medicine and even cancer therapy. Furthermore, it is found that MSCs can interact with multiple types of tumor cells. The interaction is reflected as two totally different aspects. The negative aspect is that MSCs manifest as tumor-associated fibroblasts and could induce migration of cancer cells and promote tumor formation. On the other hand, MSCs can home to sites of the tumor microenvironment, directionally migrate toward tumor cells and cause tumor cell apoptosis. In this study, we designed and made a simple microfluidic chip for cell co-culture, and studied stem cell homing behavior in the interaction between MSCs and liver cancer cells. Moreover, by etching a three-dimensional microstructure on the base and adding transforming growth factor-β (TGF-β) in the co-culture environment, we studied the impact of biophysical and biochemical factors on stem cell homing behavior, and the causes of such impact., Competing Interests: The authors declare no conflict of interest.