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Abstract The Eastern Mausoleum of Qin State is a significant component of the Qin Dynasty's royal tombs, reflecting the social development level during the Warring States period (475 BC ~ 221 BC) in China. At the onset of our investigation, we mapped the site's boundaries utilizing Corona satellite imagery and employed the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) to identify archaeological features. Additionally, this study is the first to propose the use of thermal infrared band data from the SDGSAT-1 satellite to explore thermal archaeological traces, demonstrating their viability for archaeological site analysis. Subsequently, electromagnetic (EM) prospection was utilized to validate the presence of an ancient burial chamber passage. Landscape monitoring and analysis of the No.1 Mausoleum were performed using Corona and Google Earth images, revealing the accuracy of the Geomancy Theory of Chinese mausoleums through dynamic remote sensing of surface changes. Furthermore, our employment of space-to-ground observational modalities and resultant Digital Elevation Models (DEM) have been used to provided new insights into the application of Remote Sensing (RS) and Geomancy in archaeology, thereby emphasizing the pivotal role of site selection in heritage preservation. This research underscores the promise of synergistic space-ground observations in both exploiting the archaeological riches of cultural heritage sites and ensuring the enduring conservation of these irreplaceable patrimonial assets.

Abstract Weiyang Palace, the royal palace of the Western Han Dynasty, is a part of the Silk Roads: the Routes Network of Chang’an-Tianshan Corridor on the World Heritage list. The south palace wall of Weiyang Palace is a well-preserved earthen heritage site within the palace, but it is undergoing continuous deterioration due to the influence of vegetation and external environmental factors. This study pioneers the integration of high-resolution three-dimensional LiDAR scanning with multi-source data analysis, including unprecedented on-site botanical surveys, to explore the subtle effects of different vegetation types on the structural integrity of the south palace wall. Through contour line analysis and facade grid analysis, we extracted the deterioration locations of typical sections of the earthen heritage sites. And we classified the overlying vegetation types on the wall using an object-oriented classification algorithm. Our findings reveal a complex interaction between vegetation and earthen structures: paper mulberry exhibits protective qualities against erosion, while Ziziphus jujuba significantly exacerbates structural vulnerabilities. The methodologies applied in this study for extracting deterioration at earthen heritage sites and integrating multi-source spatial data can serve as a technical application model for monitoring and analyzing the driving forces of earthen heritage sites along the entire Silk Road network, thereby better guiding the conservation of earthen heritage sites.

The sharing of pathological data is highly important in various applications, such as remote diagnosis, graded diagnosis, illness treatment, and specialist system development. However, ensuring reliable, secure, privacy-preserving, and efficient sharing of pathological data poses significant challenges. This paper presents a novel solution that leverages blockchain technology to ensure reliability in pathological data sharing. Additionally, it employs conditional proxy re-encryption (C-PRE) and public key encryption with equality test technology to control the scope and preserve the privacy of shared data. To assess the practicality of our solution, we implemented a prototype system using Hyperledger Fabric and conducted evaluations with various metrics. We also compared the solution with relevant schemes. The results demonstrate that the proposed solution effectively meets the requirements for pathological data sharing and is practical in production scenarios.

Study region: The Kaidu River Basin originates from the southern slope of the Tienshan Mountains in the Xinjiang Uygur Autonomous Region, China. Study focus: Accurate runoff simulation and prediction significantly affect flood control, drought resilience, and water resource allocation decisions. This study establishes the GR4J-6 model (modèle du Génie Rural à 4 paramètres Journalier-6, including a snowmelt module) and integrates it with the LSTM (Long Short-Term Memory) model to construct the hybrid GR4J-6-LSTM model and enhance the simulation accuracy of snowmelt runoff. A case study is conducted in the Kaidu River Basin to demonstrate the applicability of these models in cold and arid regions. The accuracy of the GR4J-6, LSTM, and GR4J-6-LSTM models is evaluated using Nash-Sutcliffe efficiency (NSE), Kling-Gupta Efficiency (KGE), and Root Mean Squared Error (RMSE) metrics. In addition, the contributions of each feature variable in the models are analyzed using the SHapley Additive exPlanations (SHAP) method to enhance the reliability of the results. New hydrological insights for the region: The GR4J-6 model demonstrated good applicability in the Kaidu River Basin, with NSE, KGE, and RMSE values of 0.69, 0.79, and 39.39 m3/s during the validation period, respectively. The hybrid model GR4J-6-LSTM exhibited the highest comprehensive accuracy among all the models, with NSE, KGE, and RMSE values of 0.84, 0.87, and 28.79 m3/s, respectively. In the LSTM model, temperature and precipitation were found to significantly influence the simulated runoff, indicating that higher temperature and precipitation lead to increased runoff. In the GR4J-6-LSTM model, Tmin (minimum temperature) and the hydrological feature variable Qsim exhibited a strong positive correlation with simulated runoff, as Tmin and Qsim increased, they promoted stronger flow production. This study provides a framework for runoff simulation in snowmelt river basins, offering a reference for projecting extreme hydrological events under climate change.

Urban development under a changing climate pose threats to heritage conservation, necessitating vigilant monitoring of human activities and natural disasters. This study proposes a dynamic monitoring and risk assessment technology aimed at identifying interferences to heritage sites along the Silk Road. The characterization of land use was investigated, and changes within the protected areas were extracted using an object-based deep learning method to reveal instances of human interference. Nighttime light changes were analyzed to assess socio-economic development in heritage regions and cross-referenced with results indicating human interference to examine the relationship between urban development and heritage conservation. Additionally, we extracted various environmental and climate variables to evaluate the risk of flood disasters for these heritage sites. The findings suggest that heritage sites along the Silk Road are generally in good condition. Nevertheless, the substantial increase in construction land highlights challenges in heritage conservation and economic development. This study highlights the importance of vegetation coverage and water diversion measures to prevent floods, emphasizing the effectiveness of space observation in identifying risks. Such observation can help the government manage and protect valuable sites, advancing heritage protection within the framework of sustainable development goals (SDGs).

ABSTRACTClassification of individual tree species (ITS) is critical for fine-scale forest surveys. However, it is difficult to obtain the complete and high-precision data needed for ITS classification in large areas. Lower spatial resolution time-series imagery is more accessible than other types of imagery and contains rich phenological information. In this study, after delineating individual tree crowns using a 0.2-m unmanned aerial vehicle (UAV) image, we used 3-m time-series imagery and a new 3DLSTM model to identify ITS at the Gaofeng Forest Farm in Guangxi Province, China. The 3DLSTM ITS classification model combines three-dimensional convolutional neural network (3D CNN) and long short-term memory (LSTM) models; thus, spatial, multiband, and time-series information can be extracted simultaneously to identify ITS more accurately. In this study, when only 3-m Planet time-series imagery was used for classification, the 3DLSTM model offered an ITS classification accuracy of 92.68%, outperforming two ITS classifiers (DenseNet or AlexNet model) based on one individual image. Moreover, the 3DLSTM model was better at identifying broad-leaved tree species than other deep-learning models. The experimental results proved that ITS classification could be significantly improved using only 3DLSTM and time-series images, offering the possibility of classifying large-scale ITS at a low cost.

As urbanization accelerates, World Heritage properties, critical conservation areas, face a growing threat of urban densification, jeopardizing their Outstanding Universal Value (OUV). States Parties, the countries that have ratified the World Heritage Convention, are responsible for submitting periodic reports on the state-of-conservation of their World Heritage properties. These reports should explicitly address any instances of urban densification that may be occurring. But do they? This research investigates the relationship between urban densification and reporting practices in World Heritage properties over time and space. Through a spatiotemporal analysis, by analyzing changes in the built-up area within the core zones of cultural World Heritage properties from 1985 to 2015. We found that urban development, including housing, infrastructure, and tourism facilities, has significantly impacted World Heritage properties and an increase in built-up area can be observed especially in properties not reporting on urban threats.

In this paper, a novel method was proposed to improve the production efficiency and formability of titanium alloy, which was named triple-layer sheet hot stamping with a cold die cooling (THF). The titanium alloy sheet was clamped by two steel sheets with no adhesive added, then heated, transferred and formed together. In order to verify the ability in enhancing formability of this process, spherical part forming tests were carried out to study the formability under the single-layer sheet hot stamping (SHF) and THF. Finally, a plug socket part was formed to verify the practicability of the novel forming process. The finite element (FE) model was established to analyze the forming process finding that the formability of the parts were significantly improved after using THF process. Comparing with SHF process, the stamping depth increases by 135.7% at 900 °C in the THF process. The forming limit strain increases from 0.18 of the single-layer sheet to 0.51 of the triple-layer sheet. The forming limit strain obtained by the THF process is close to that of isothermal forming. The friction state is one of the main reason for improving formability. Moreover, for plug socket parts, there is almost no thinning of the part in the THF process at 900 °C. In conclusion, it has great advantages in improving the formability of titanium alloy using the THF process.

Sonodynamic therapy (SDT) has emerged as a novel and highly researched advancement in the medical field. Traditional ultrasound contrast agents and novel bubble-shaped agents are used to stimulate cavitation and enhance SDT efficiency. However, the impact of artificially modified shell structures on the acoustic properties of microbubbles remains to be explored. Alternatively, in the absence of bubble-shaped agents, some clinically available organic sonosensitizers and advanced inorganic materials are also used to enhance the efficacy of SDT. Diagnostic and therapeutic ultrasound can also activate cavitation bubbles, which supply energy to sonosensitive agents, leading to the production of cytotoxic free radicals to achieve therapeutic effects. While inorganic materials often spark controversy in clinical applications, their relatively simple structure enables researchers to gain insight into the mechanism by which SDT produces various free radicals. Some organic–inorganic hybrid sonosensitive systems have also been reported, combining the benefits of inorganic and organic sonosensitive agents. Alternatively, by employing cell surface modification engineering to enable cells to perform functions such as immune escape, drug loading, gas loading, and sonosensitivity, cellular sonosensitizers have also been developed. However, further exploration is needed on the acoustic properties, ability to generate reactive oxygen species (ROS), and potential clinical application of this cellular sonosensitizer. This review offers a comprehensive analysis of vesical microbubbles and nanoscale sonocatalysts, including organic, inorganic, combined organic–inorganic sonosensitizers, and cellular sonosensitizers. This analysis will enhance our understanding of SDT and demonstrate its important potential in transforming medical applications.

Blockchain is commonly employed in access control to provide safe medical data exchange because of the characteristics of decentralization, nontamperability, and traceability. Patients share personal health data by granting access rights to users or medical institutions. The major purpose of the existing access control techniques is to identify users who are permitted to access medical data. They hardly ever recognize internal assailants from legitimate entities. Medical data will involve multilayer access within the authorized organizations. Considering the cost of permissions management and the problem of insider malicious node attacks, users hope to implement authorization constraints within the authorized institutions. It can prevent their data from being maliciously disclosed by end-users from different authorized healthcare domains. For the purpose to achieve the fine-grained permissions propagation control of medical data in sharing institutions, a trust-based authorization access control mechanism is suggested in this study. Trust thresholds are assigned to different privileges based on their sensitivity and used to generate zero-knowledge proof to be broadcasted among blockchain nodes. This method evaluates the trust of each user through the dynamic trust calculation model. And meanwhile, smart contract is employed to verify whether the user’s trust can activate some permissions and ensure the privacy of the user’s trust in the process of authorization verification. In addition, the authorization transaction between users and institutions is recorded on the blockchain for patient traceability and accountability. The feasibility and effectiveness of the scheme are demonstrated through comprehensive comparisons and extensive experiments.

Thumbnail-preserving encryption (TPE) can balance the usability and the privacy of images in the cloud. Most ideal TPE schemes obtain thumbnails by dividing the plaintext image into multiple blocks, and then perform substitution and permutation operations in each block. The size of partitioned blocks affect the usability and the privacy of the encrypted images. The size of the pixel groups in the blocks, i.e., the number of encrypted pixels per time, has experienced the development from 2-pixel to n-pixel in recent years. Existing solutions cannot promote the real implementation and commercial realization because of inefficiency and instability. In this paper, we propose an efficient and stable TPE scheme, which can select intelligently different sizes of pixel groups in each block. Theoretical analysis indicates that the encryption time is influenced by the sum and the number of pixels in a pixel group. The length of the pixel group and the sum of pixel values in a group influence each other. We try to determine the optimal combination of these two factors. Through the analysis of Markov model, the proposed scheme has the nonce-respecting security. The experimental results of comparison show that, for the images with size of 480 × 320, the average encryption time of the proposed scheme is 61.7% less than that of 3-pixel flexible TPE, which is the most effective scheme up to now. And the fluctuation value decreases by 34.8%.

The Beijing-Hangzhou Grand Canal in China became a World Cultural Heritage Site in 2014, and the water quality of this ancient man-made canal has increasingly attracted societal attention. This study focuses on monitoring the water quality of the Beijing section of the Grand Canal (BGC) using remote sensing technology. Analysis of the comprehensive trophic level index (TLI) indicates that the water in the Canal was predominantly light eutrophic from 2016 to 2022. The annual average results of the TLI reveal that the water quality in the Kunming Lake and North Canal of BGC is generally good, characterized by some mesotrophic waters, and others are in light eutrophication. The TLI for the entire BGC water body decreased from 64.7 in 2016 to 60.3 in 2022, indicating an improvement trend in water quality. Notably, the proportion of good water with TLI less than 60 increased from 50% in 2016 to 83% in 2022. This improvement of water quality may be attributed to the reduced use of fertilizers and pesticides and the implementation of various environmental policies by Beijing Municipal government. These findings offer valuable insights for the management and protection of the water resources of the BGC, and further contribute to the evaluation of the United Nations Sustainable Development Goal (SDG) 11.4.

The saline, alkaline environment of arid soils is conducive to the diffusion of the metalloid arsenic (As). Desert plants in this area are of great ecological importance and practical value. However, there are few studies on the mechanism of arsenic action in desert plants. Therefore, in this study, Eremostachys moluccelloides Bunge was treated with different concentrations of As2O5 [As(V)] to analyze the physiological, biochemical, and transcriptomic changes of its roots and leaves and to explore the molecular mechanism of its response to As(Ⅴ) stress. The activities of catalase, superoxidase, peroxidase, and the contents of malondialdehyde and proline in roots and leaves first increased and then decreased under the As(Ⅴ) stress of different concentrations. The content of As was higher in roots than in leaves, and the As content was positively correlated with As(Ⅴ) stress concentration. In the differentially expressed gene analysis, the key enzymes of the oxidative stress response in roots and leaves were significantly enriched in the GO classification. In the KEGG pathway, genes related to the abscisic acid signal transduction pathway were co-enriched and up-regulated in roots and leaves. The related genes in the phenylpropanoid biosynthesis pathway were significantly enriched and down-regulated only in roots. In addition, the transcription factors NAC, HB-HD-ZIP, and NF-Y were up-regulated in roots and leaves. These results suggest that the higher the As(V) stress concentration, the more As is taken up by roots and leaves of E. molucelloides Bunge. In addition to causing greater oxidative damage, this may interfere with the production of secondary metabolites. Moreover, it may improve As(V) tolerance by regulating abscisic acid and transcription factors. The results will deepen our understanding of the molecular mechanism of As(Ⅴ) response in E. moluccelloides Bunge, lay the foundation for developing and applying desert plants, and provide new ideas for the phytoremediation of As pollution in arid areas.

The quantification of the extent and dynamics of land-use changes is a key metric employed to assess the progress toward several Sustainable Development Goals (SDGs) that form part of the United Nations 2030 Sustainable Development Agenda. In terms of anthropogenic factors threatening the conservation of heritage properties, such a metric aids in the assessment of achievements toward heritage sustainability solving the problem of insufficient data availability. Therefore, in this study, 589 cultural World Heritage List (WHL) properties from 115 countries were analyzed, encompassing globally distributed and statistically significant samples of “monuments and groups of buildings” (73.2%), “sites” (19.3%), and “cultural landscapes” (7.5%). Land-cover changes in the WHL properties between 2015 and 2020 were automatically extracted from big data collections of high-resolution satellite imagery accessed via Google Earth Engine using intelligent remote sensing classification. Sustainability indexes (SIs) were estimated for the protection zones of each property, and the results were employed, for the first time, to assess the progress of each country toward SDG Target 11.4. Despite the apparent advances in SIs (10.4%), most countries either exhibited steady (20.0%) or declining (69.6%) SIs due to limited cultural investigations and enhanced negative anthropogenic disturbances. This study confirms that land-cover changes are among serious threats for heritage conservation, with heritage in some countries wherein the need to address this threat is most crucial, and the proposed spatiotemporal monitoring approach is recommended.

Abstract Chlorella sp. TLD 6B, a microalgae growing in the Taklamakan Desert, Xinjiang of China, is a good model material for studying the physiological and environmental adaptation mechanisms of plants in their arid habitats, as its adaptation to the harsh desert environment has led to its strong resistance. However, when using real-time quantitative polymerase chain reaction (RT-qPCR) to analyze the gene expression of this algae under abiotic stress, it is essential to find the suitable endogenous reference genes so to obtain reliable results. This study assessed the expression stability of 9 endogenous reference genes of Chlorella sp. TLD 6B under four abiotic stresses (drought, salt, cold and heat). These genes were selected based on the analysis results calculated by the three algorithmic procedures of geNorm, NormFinder, and BestKeeper, which were ranked by refinder. Our research showed that 18S and GTP under drought stress, 18S and IDH under salt stress, CYP and 18S under cold stress, GTP and IDH under heat stress were the most stable endogenous reference genes. Moreover, UBC and 18S were the most suitable endogenous reference gene combinations for all samples. In contrast, GAPDH and α-TUB were the two least stable endogenous reference genes in all experimental samples. Additionally, the selected genes have been verified to be durable and reliable by detecting POD and PXG3 genes using above endogenous reference genes. The identification of reliable endogenous reference genes guarantees more accurate RT-qPCR quantification for Chlorella sp. TLD 6B, facilitating functional genomics studies of deserts Chlorella as well as the mining of resistance genes.

Abstract Scientific cognition and assessment of threats to cultural heritage and surrounding landscapes are prerequisites for targeted management and protection of cultural heritage. This study took 530 city sites in the Central Plains of China as the research object. Based on the survey information of city sites in the third national cultural heritage survey in China, a combination of high resolution google images and land use/land cover data products and city sites survey data enables a comprehensive evaluation of landscape elements impacts on city sites. With spatial statistical method, we divided city site landscape types, and constructed a landscape element risk assessment model and an urbanization intensity index to analyze the threats of each landscape element to city site protection. The results indicated that 40.64% of the sites are in farmland landscapes, where agricultural cultivation, irrigation, and other production activities may affect the surface and subsurface remains of the sites. The sites (16.82%) in urban landscapes are affected by activities such as building houses and roads. Only six sites belong to the water landscape area, which may be affected by water erosion. Other sites (2.84%) are mainly affected by plant root growth in forest landscapes. The city sites distributed in urban areas such as Zhengzhou or the urban–rural junction were significantly affected by urban expansion and got the greatest protection pressure. City sites in agricultural landscapes have the second highest conservation risk. Plant erosion and flooding mainly affected the city sites in the northwest-southwest mountainous areas or near the water area of the study area, and the risks were relatively small. It can be seen that landscape types such as urban and farmland, which are closely related to human activities, bring the most pressure to the protection of city sites, and it is necessary to focus on the impact of human activities such as urban construction on city sites and the surrounding environment in the future, while paying attention to the protection and rational use of city sites with high assessment risk in urban planning and management for the protection of the city site proper and landscape scenery.

As a World Cultural Heritage site with sacred landscape featuring an exceptional range of Buddhist art and architecture, much attention has been focused on the sustainable development of Bagan (Myanmar). Particularly, the monitoring of landscape surface subsidence and monument instability is of great importance to the protection and development planning of the Bagan heritage site. In this study, we applied high resolution TerraSAR-X imagery acquired from 2019 to 2020 for deformation monitoring based on the small baseline subset (SBAS) and persistent scatterer synthetic aperture radar interferometry (PSInSAR) approaches. We identified several hotspots and pagodas with displacement anomalies linked to land cover change and previous earthquakes. The cross comparison between SBAS and PSInSAR and the precision of height estimates derived by PSInSAR indicated a millimetric precision of the derived deformation products. The combination of the two multi-temporal SAR interferometry approaches satisfies the two-scale monitoring requirements from landscapes to monuments, particularly for large-scale World Heritage sites. The non-contact monitoring method has potential when traditional methods using field accessibility and surveillance are constrained.

With the warming and humidification process in the Northwest Arid Zone over the past 30 years, the runoff of a vast majority of rivers has been affected to different degrees. In this paper, the runoff from the Weigan River, a typical inland river in the arid zone of Northwest China, is taken as an example, and seven types of CMIP6 data are selected with the help of a SWAT model to predict the runoff volume of the Weigan River in the next 30 years under climate change. The results show that (1) the SWAT model can simulate the runoff from the Weigan River well and has good applicability in this study area. (2) With an increase in radiative forcing, the temperature, precipitation and runoff in the study area show an increasing trend. (3) Under the four radiative forcing scenarios in 2030 and 2050, the runoff from the Weigan River out of the mountain is predicted to be maintained at 25.68 to 30.89 × 108 m3, which is an increase of 1.35% to 21.91% compared with the current runoff, of which the contribution to the increase in future runoff caused by the changes in temperature and precipitation is 68.71% and 27.24%, respectively. It is important to explore the impact of climate change on the runoff from the Weigan River to understand the impact of climate change on the Northwest Arid Region scientifically and rationally, and to provide a scientific basis for evaluating the risk of climate change and formulating policies to deal with it.

Jiuzhaigou Valley is recognized as both a world natural heritage site and a biosphere reserve. Conducting research on vegetation health within its scope can provide a demonstration role for sustainable development research. In this study, we proposed a technology integration approach that combined remote sensing intelligent identification and quantitative retrieval, and achieved vegetation health monitoring and susceptibility mapping of unhealthy trees. Leveraging WorldView-2 high-resolution satellite images, unhealthy trees were elaborately identified through the object-oriented classification method employing spectral and texture features, with F1 Score exceeding 75%. By applying fuzzy operations on indices related to leaf pigment and canopy architecture, we ultimately generated susceptibility maps of unhealthy trees on Sentinel-2 satellite images, with Area Under the Curve (AUC) exceeding 0.85. Our findings underscore that the vegetation health in Jiuzhaigou Valley is predominantly influenced by human activities and geological hazards. The forests of Jiuzhaigou Valley exhibit a certain degree of resilience to geological disasters, while human activities have been continuously exerting adverse effects on forest health in recent years, necessitating heightened attention. The methodology proposed in this study for mapping unhealthy trees susceptibility presents a cost-effective solution that can be readily applied for vegetation health monitoring and early warning in analogous biosphere reserves.

Ecological water conveyance is an important way to promote the restoration of degraded ecosystems in arid watersheds. However, there are few previous research results on how to quantitatively evaluate the effect of ecological water conveyance on ecological restoration. In this regard, this paper selects the Tarim River Basin as a typical area, analyzing the changes of desert riparian vegetation and hydrological elements, constructing a watershed ecological environment quality evaluation system, and comprehensively evaluating the ecological water conveyance effect of the damaged desert forest ecosystem. The conclusion showed that the proportion of the pixel area with an upward trend of Fractional Vegetation Cover (FVC) from 2000 to 2021 is as high as 84.3%. The plant diversity index in the ecological water conveyance area showed the characteristics of first obvious increase and then stable. The main body of groundwater depth showed an upward trend, and the Temperature Vegetation Dryness Index (TVDI) showed a downward trend of pixel area accounting for 57.0%, which indicated that ecological water conveyance had played a positive role in groundwater recharge and ecological restoration along the Tarim River. The ecological environment quality of the river basin showed a trend of transition from low-grade to high-grade, and the area with excellent ecological quality had increased from 4,635.50 km2 in 2000 to 12,335.0 km2 in 2021. The above research provides important scientific reference for the protection and restoration of vegetation degradation in arid watersheds.

In order to use water resources more efficiently, the construction of water conservation projects in dryland watersheds has changed the natural water cycle processes. This study used the SWAT (Soil and Water Assessment Tool) model coupled with the glacier module to simulate the hydrological processes in the upper reaches of the Weigan River estuary from 1965 to 1991, to restore and quantitatively evaluate the conditions of the estuarine runoff in the no-reservoir scenario, and to analyse the impact of the construction of water conservation projects on the estuarine runoff based on this model. The results show that the SWAT model has good applicability in the study area, with 41.45% and 58.55% of the increase in runoff due to increased precipitation and temperature, respectively, over the 52 years study period. The degree of influence of the construction of water conservation projects on runoff from the mountain in different seasons was spring > autumn > winter > summer, with 83.28% of the spring runoff being influenced by artificial regulation. The construction of water conservation projects has alleviated water shortage problems to a certain extent, and is an effective measure for achieving the efficient allocation of water resources in arid areas.

In arid regions with scarce water resources, lakes play an extremely vital role in maintaining the ecological environment. Therefore, the Chinese government has launched an ecological water conveyance project in the Tarim River basin in Xinjiang with the aim of restoring the ecological environment of the area. In previous studies, there was no complete evaluation system used to quantify changes in the ecological environment of arid regions after ecological water conveyance. In this paper, Lake Taitema was selected as the study area, which is both a terminal lake in the Tarim River basin and an object of the ecological water conveyance project. This study utilized Landsat TM/OLI satellite remote sensing images and MODIS datasets to build a remote sensing ecological index model and systematically evaluated the changes in the ecological environment and land use types in the Taitema Lake area. A structural equation model was constructed to analyze the correlation between the area of Taitema Lake and its driving factors. The results show that over the selected 20 years, the proportion of pixels with an upward trend (Zc > 0) of the RSEI was 56.5%, while the proportion of pixels with a downward trend (Zc < 0) of the RSEI was 43.5%. The area proportion of regions with poor ecological environment quality decreased by about 40%, and the area proportions of regions with moderate, good, and excellent ecological environment quality increased by 29.7%, 10%, and 0.6%, respectively. By comparing the land use data from 2000 and 2020, the proportion of grassland increased by 6%, the proportion of water area increased by 4.4%, and the proportion of unused land decreased by 9.6%. In summary, after the implementation of the ecological water conveyance project, the ecological environment quality of the Lake Taitema area gradually improved, and ecological water conveyance was the main driving factor of the area change in Lake Taitema.

The microscopic deformation behavior of Inconel 625 superalloy has been investigated by means of nanoindentation experiments and crystal plasticity finite element simulations. Based on the electron backscattered diffraction characterizations, the nanoindentation simulations were performed on grains with various orientations. The simulated load–displacement curves match well with those of experiment and the maximum difference in materials hardness between the experimental and the simulation result is about 6.86%, which is within the accuracy of the model. Moreover, surface Schmid factor (SSF) and interior Schmid factor (ISF) were proposed out and the scanning electron microscope and atomic force microscope characterizations were carried out. The results show that the pile-up tends to occur at the locations with a large SSF. Subsequently, the simulations of nanoindentation on [001]-, [011]-, and [111]-oriented grains were performed by the established model. It is revealed that the residual topography changes periodically when the indenter is fixed and the crystal only rotates around the Z-axis of the sample coordinate system. Combining with the analysis of the ISF, this periodicity of residual topography reflects the superimposed effect of the slip systems, and a large ISF promotes the in-plane displacement of the interior material which inhibiting the evolution of pile-up, while a small ISF leads to a high pile-up.

Abstract The Great Wall of China is one of the largest architectural heritage sites globally, and its sustainability is a significant concern. However, its large extent and diverse characteristics are challenges for deformation monitoring. In this study, the Shanhaiguan section of the Great Wall was investigated in a case study to ascertain the damage and potential hazards of the architectural site. Two standard multi-temporal synthetic aperture radar interferometry (MTInSAR) technologies, including persistent scatterer SAR interferometry (PSInSAR) and small baseline subset (SBAS) SAR interferometry, were used for deformation monitoring using high-resolution TerraSAR-X data acquired in 2015–2017. The results of the two MTInSAR approaches reveal the health condition of the Great Wall. The Shanhaiguan section was stable, but local instabilities caused by rock falls were detected in some mountainous areas. In addition, the applicability of PSInSAR and SBAS was evaluated. The performance analysis of the two approaches indicated that a more reliable and adaptable MTInSAR technique needs to be developed for monitoring the Great Wall. This study demonstrates the potential of MTInSAR technology with high-resolution data for the health diagnosis of heritage sites with a linear structure, such as the Great Wall.

Imaging radar has been dramatically developed over the past decades enabling a better understanding of cultural heritage from a microwave perspective. Nonetheless, a dedicated survey and analysis of the performance of such technology in cultural heritage monitoring and management is required. In order to fill this gap, we first review the technology advance of imaging radar, including ground penetration radar, ground-based and airborne/satellite radar, in the focused cultural applications to grasp the development trend of these technologies. We then analyse the performance and limitations of imaging radar technologies based on their respective characteristics to facilitate the technology service in practical applications. Finally, we propose a flexible solution of imaging radar in cultural heritage through technical integration with pilot synergy applications in archaeological prospection and cultural heritage diagnosis and conservation.

Accurate identification of individual tree species (ITS) is crucial to forest management. However, current ITS identification methods are mainly based on traditional image features or deep learning. Traditional image features are more interpretative, but the generalization and robustness of such methods are inferior. In contrast, deep learning based approaches are more generalizable, but the extracted features are not interpreted; moreover, the methods can hardly be applied to limited sample sets. In this study, to further improve ITS identification, typical spectral and texture image features were weighted to assist deep learning models for ITS identification. To validate the hybrid models, two experiments were conducted; one on the dense forests of the Huangshan Mountains, Anhui Province and one on the Gaofeng forest farm, Guangxi Province, China. The experimental results demonstrated that with the addition of image features, different deep learning ITS identification models, such as DenseNet, AlexNet, U-Net, and LeNet, with different limited sample sizes (480, 420, 360), were all enhanced in both study areas. For example, the accuracy of DenseNet model with a sample size of 480 were improved to 87.67% from 85.41% in Huangshan. This hybrid model can effectively improve ITS identification accuracy, especially for UAV aerial imagery or limited sample sets, providing the possibility to classify ITS accurately in sample-poor areas.

Skeleton-based action recognition depends on skeleton sequences to detect categories of human actions. In skeleton-based action recognition, the recognition of action scenes with more than one subject is named as interaction recognition. Different from the single-subject action recognition methods, interaction recognition requires an explicit representation of the interaction information between subjects. Recalling the success of skeletal graph representation and graph convolution in modeling the spatial structural information of skeletal data, we consider whether we can embed the inter-subject interaction information into the skeletal graph and use graph convolution for a unified feature representation. In this paper, we propose the interaction information embedding skeleton graph representation (IE-Graph) and use the graph convolution operation to represent the intra-subject spatial structure information and inter-subject interaction information in a uniform manner. Inspired by recent pre-training methods in 2D vision, we propose unsupervised pre-training methods for skeletal data as well as contrast loss. In SBU datasets, JointContrast achieves 98.2% recognition accuracy. in NTU60 datasets, JointContrast respectively achieves 94.1% and 96.8% recognition accuracy under Cross-Subject and Cross-View evaluation metrics.

Architectural heritage has important historical, artistic, and technological value. However, these sites are subject to long-term degradation and are sensitive to disturbances from the surrounding landscape, resulting in the potential deterioration of the architecture. Deformation is a quantitative indicator of the vulnerability of architectural heritage. The extraction of three-dimensional (3D) deformation via existing geodetic approaches, such as global navigation satellite systems (GNSS) and interferometric synthetic aperture radar (InSAR), proves to be a challenging task. In this study, we proposed an adaptable methodology for the preventive monitoring of architectural heritage by integrating differential SAR tomography (D-TomoSAR) and a finite element method (FEM) to overcome the limitations of current geodetic approaches in cultural applications (i.e., sparse measurements in space; time- and labor-intensive). The Angkor Wat Temple, a well-known monument at the Angkor World Heritage site, Cambodia, was selected as the investigation target. We used D-TomoSAR to calculate the deformation, height, and thermal dilation of the structure using 46 TerraSAR-X images acquired during 2011–2013. InSAR deformation measurements were used as the constraint for the 3D deformation simulation and structural monitoring using an integrated approach to diagnose the soundness of the architectural structure. The experimental results demonstrate the following: 1) the integration of InSAR measurements prevented the underestimation of structural instabilities and linked the simplified physical model and mechanical parameters to the FEM simulation. 2) The Angkor Wat Temple appeared stable; however, structural instabilities were detected with an absolute deformation rate of up to 3 mm/yr. 3) Daily changes in thermal-related deformations caused by incoming frontal and posterior solar radiation-induced the bending of the architecture and the risk of structural defects. Our study reveals the defect mechanism of the Angkor Wat Temple and demonstrates the potential of the proposed method for the health diagnosis and preventive safeguarding of architectural heritages across the globe.

Airborne laser scanning (ALS) has recently been identified as a potential tool in topographic mapping for archaeological prospection. However, most existing applications in this field refers to manned ALS systems, for which the high operation and maintenance costs limits its application in small-scale archaeological investigation. In this paper, we conducted an exploratory study on the application of the unmanned aerial vehicle (UAV) laser scanning (ULS) system in ancient micro-topography detection over wooded areas. Compared with manned ALS technology, we analyzed the advantages and potentials of ULS technology for archaeological applications. Then we outlined existing mainstream survey-grade UAV-based laser scanners, data processing and visualization approaches. Furthermore, we performed case studies in three cultural heritage sites in Zhejiang Province, China using two representative mainstream survey-grade ULS systems. Results were then verified by an in-site investigation. Finally, the correct selection of ULS devices, the planning of data acquisition missions and the use of appropriate data processing methods specifically for archaeological prospection were discussed. This paper provides a cost-effective and flexible solution for micro-topography detection in wooded areas. ULS technology, as demonstrated here, can be an important supplement to existing archaeological investigation methods, particularly for small-scale areas, and has promising prospects in archaeological applications.

In this study, an integrated monitoring and evaluation approach was proposed to fix the systematic safeguarding gap of the Great Wall corridor using space technologies. Two representative sections of the Great Wall located in Qingtongxia County and Zhangjiakou City in China were selected for a preliminary comparative investigation to ascertain the coupling mechanism and spatiotemporal characteristics of the driving forces for the heritage damage. The surface deformation rates were estimated by synthetic aperture radar interferometry, and the interaction between the deformation rates and the normalized difference vegetation index (NDVI) and meteorological and topographic data was calculated using the correlation matrix. The results showed the following: 1) the surface motions along the observed landscape corridor of the Great Wall were decreased in 2015-2018; 2) the correlation coefficients between the deformation rate and the elevation, slope, annual wind speed, and NDVI in Qingtongxia were 0.524, 0.115, 0.582, and 0.522, respectively, indicating the dominant influence of surface runoff and high winds on the degradation of the rammed-earth wall in the western arid regions; vice versa, 3) the correlation coefficients between the deformation rate and the aforementioned factors in Zhangjiakou were 0.065, 0.027, 0.025, and 0.052, respectively, indicating negligible effects of natural processes for the decline of Great Wall in the eastern section. This study not only provides new insights into preventive monitoring and risk assessment of the entire Great Wall but also highlights the potential of space technologies and a geographical perspective for the sustainable conservation of large-scale heritage sites.

The preventive monitoring and sustainable conservation of large-scale cultural heritage sites require satellite-based Earth observations. In this study, we present the first monitoring and thematic mapping results of the Badaling Great Wall (Beijing, China) using deformation indicators calculated from very high-resolution (VHR) multi-temporal spotlight TerraSAR-X data. The proposed coarse–fine search algorithm achieved high computational efficiency for calculating the unknown parameters of the two-tier network persistent scatterer synthetic aperture radar (SAR) interferometry (PSInSAR) approach. The spatiotemporal deformation anomalies, characterized by the absolute velocity, deformation deviation and acceleration, are informative to identify suspected hotspots for prioritizing monitoring activities. We provide an understandable method for thematic mapping and subsequent sustainable conservation of heritage sites by synergistically exploiting impacts from natural degradation and the tourism industry. We determine that the optimum tourist capacity of the site could be 1.0 million per month based on comparing pre- and post-COVID data (2019–2020). This study demonstrates the potential and performance of spaceborne PSInSAR tools for the intelligent management of large-scale architectural heritage sites by integrating InSAR deformation products with environmental and social data.

Abstract Incorporating 50 years of flood data for the Manas River Kenswat Hydrological Station from 1957 to 2006, the Pettitt test and Mann–Kendall trend test are used to analyse non‐stationarity of the flood characteristic sequences. Moreover, the Pearson type‐III (P‐III) distribution, the mixed distribution (MD) and conditional probability distribution (CPD) models are employed to analyse frequency and to calculate the design flood process line. The results showed that the annual maximum peak discharge and the annual maximum flood volume are most likely to change in 1993. The MD model considering the non‐stationarity of the flood sequence is more accurate than the CPD model and the traditional P‐III distribution model. There are significant differences in the design flood process lines of the 1996 typical flood process obtained by the three methods using the same frequency scaling method. In addition, under different design standards, the design value of the MD model is 20–53% smaller than the design value approved in 2008 (approved by China Renewable Energy Engineering Institute) and 4–48% higher than the traditional P‐III distribution design value. The results can provide a new reference for the management of non‐stationary floods in Manas River.

Contributing to the United Nations 2030 Sustainable Development Goals (SDGs) within Target 11.4 “Strengthen efforts to protect and safeguard the world’s cultural and natural heritage”, it is critical to monitor the spatial and temporal stabilities of cultural heritages. The study of the interactive relationship between earthquakes and the protection of cultural heritages needs to be strengthened. On 27 September 2021, the destructive Mw 5.9 Arkalochori earthquake occurred ~25 km away from the city of Heraklion (Greece) where the Heraklion City Wall (HCW), a representative cultural heritage of Greece and Europe, was located. This offered a proper case to investigate the shortcomings aforementioned. Here, we intend to set up and answer the following three questions (Whether, Where and What, 3Ws): Whether there were impacts on the HCW caused by the Arkalochori earthquake? Where did the maximum deformation occur? What was the relationship between seismic deformation between the epicenter and the HCW over time? We performed two-dimensional (2D) InSAR measurements for both co-seismic and post-seismic deformations using the ascending and descending Sentinel-1A SAR images. The spatial-temporal characteristics of Up–Down (UD) and East–West (EW) were revealed. The 2D co-seismic deformation field showed that the near-filed deformations were dominating compared with the deformations at the HCW, the UD deformation was mainly featured with subsidence with a maximum value of ~21 cm, the EW deformation was ~9 cm westward and ~10 cm eastward. The time-series measurements showed that: (1) temporally, the HCW responded quickly to the Arkalochori earthquake, and the accumulative deformations at the seven different bastions of the HCW showed the same trend as the near-field area over time. (2) Spatially, the closer to the Mw 5.9 epicenter, the larger the deformations that occurred. (3) The EW and UD deformation trends of the HCW that were consistent with the Mw 5.9 epicenter were interrupted at the middle time spot (22 January 2022), indicating the influence of another earthquake sequence consisting of eight earthquakes with magnitudes larger than 3.5 that happened on 16–18 January 2022. Respectively, to summarize and address the aforementioned 3Ws based on the post-seismic analysis accomplished by the MSBAS method, the Arkalochori earthquake did affect the HCW; besides, the influences of the ~13 km earthquake sequence were also detected; the nearest part to the epicenter suffered the most; the deformation trends of the HCW were approximately the same with the epicenter area of the Arkalochori earthquake both in the UD and EW directions.

The past few decades have witnessed unprecedented global urbanisation, with direct or indirect impacts on global cultural heritage sites. Research on the spatial relationship between cultural heritage sites and urban areas has provided a new perspective for understanding the impact processes between them, which have previously been discussed at the regional scale. In this article, we analyse the spatial relationship between world cultural heritage sites and neighbouring towns through systematic observations at the global scale and attempt to model change processes and identify impact mechanisms. We adopt spatial analysis and spatial statistics to analyse the changing characteristics of the spatial relationship between world cultural heritage sites and neighbouring towns from 1990 to 2018 and to analyse the impact processes at different spatial and temporal scales by combining indicators, such as income levels and urbanisation rates, at the national scale. The results show that 8.52% of world cultural heritage sites have been incorporated into urban areas over the aforementioned 28 years, with a certain aggregation in the spatial distribution of these sites, and that the growth rate can be divided into three phases, including two periods of rapid growth. The spatial relationship between towns and the 523 world cultural heritage sites that were previously located outside towns has not yet changed substantially, but the distances between most of the towns and these sites have been decreasing, with 81% of the world cultural heritage sites having a variation in distance from the corresponding town of 7.60 km or less. We also analysed the variation in distance between cultural heritage sites and neighbouring towns and found a relationship with indicators, such as the income level and urbanisation rate of the country to which a site belongs. Among the indicators, variation in national urbanisation rates most greatly affected the distance between heritage sites and towns. This study shows that world cultural heritage sites are affected by urbanisation and that particular attention should be given to the relationship between cultural heritage sites and neighbouring towns, especially in countries undergoing rapid urbanisation, so that the authenticity and integrity of cultural heritage are not compromised. This article provides a basis for development plans and policies in urban design, especially those that are sensitive to cultural heritage, and may also provide ideas and references for heritage conservation against the background of urbanisation.

In the community medical Internet of Things (IoT) environment, there exist a large number of device nodes, network nodes and user nodes which form a heterogeneous network. In order to ensure smooth data exchange, some gateway nodes are adopted to connect different network spaces. Therefore, how to identify and authenticate the identities of heterogeneous nodes is an urgent problem to be solved. In this paper, we start with node security identity authentication, make uses of the mechanism of elliptic curve encryption algorithm signature and session key symmetric encryption, design an efficient community medical IoT node secure two-way identity authentication method, and propose a secure and reliable update mechanism for the update of authentication keys and session keys. These measures can effectively ensure the legality of nodes and communication security in the community medical IoT system. Through the analysis and comparison of experimental performance, this scheme is more suitable for the scene of community medical Internet of Things.

Desert riparian vegetation forms an ecological corridor in extremely arid environments, and ecological water conveyance is an important measure of vegetation restoration and biodiversity conservation in desert riparian zones. Studying the responses of vegetation to ecological water conveyance and changes in this process in arid desert riparian zones and assessing the comprehensive benefits of ecological water conveyance are highly significant for ecological conservation and restoration in addition to the formulation of water transfer policies. Previous studies mainly used a single indicator to evaluate the ecological restoration of the mainstream Tarim River in Northwest China; thus, systematic and comprehensive assessments based on multiple indicators have not been conducted. In the present study, remote sensing data and field surveys were used to analyze the ecological restoration status of the Tarim River during 2015–2021 in terms of hydrological responses, vegetation responses, and ecological water conveyance benefits. The results showed that groundwater levels and soil moisture in the mainstream area of the Tarim River increased significantly from 2015 to 2021. The amount of groundwater storage also increased. Ecological water conveyance has created good hydrological conditions for groundwater recharge and ecological restoration on both sides of the mainstream area of the Tarim River. Desert forest ecosystems, mainly comprising Populus euphratica and Tamarix ramosissima, have been saved and rejuvenated in water conveyance areas. After ecological water conveyance, the Simpson and Shannon–Wiener indices increased significantly, but the diversity level began to decline and then stabilize with the increase in water conveyance frequency. The overall habitat status improved and the quality of the ecological environment below the Wusiman section of the middle reaches of the Tarim River improved significantly.

Monitoring deformation of architectural heritage sites is important for the quantitative evaluation of their stability. However, deformation monitoring of sites in mountainous areas remains challenging whether utilizing global navigation satellite system (GNSS) or interferometric synthetic aperture radar (InSAR) techniques. In this study, we improved the small baseline subset (SBAS) approach by introducing the pseudo-baseline combination strategy to avoid the errors caused by inaccurate external DEM, resulting in robust deformation estimations in mountainous areas where the architectural heritage site of the Great Wall is located. First, a simulated dataset and a real dataset were used to verify the reliability and effectiveness of the algorithm, respectively. Subsequently, the algorithm was applied in the landscape deformation monitoring of the Shanhaiguan section of the Great Wall using 51 Sentinel-1 scenes acquired from 2016 to 2018. A thematic stability map of the Shanhaiguan Great Wall corridor was generated, revealing that the landscape was generally stable save for local instabilities due to to unstable rocks and wall monuments. This study demonstrated the capabilities of adaptive multitemporal InSAR (MTInSAR) approaches in the preventive landscape deformation monitoring of large-scale architectural heritage sites in complex terrain.

The effective integration of Community Medical Internet of Things (CMIoT) and the core technology IPv6 about the next generation of Internet will create a new pattern for the medical field. However, as a heterogeneous network system, the interconnection of different CMIoT components is the primary problem, which needs to be solved. Traditional protocol conversion gateway in the Internet of Things only implements the packet format conversion. When the network environment changes, it is difficult to effectively implement the data path. We propose a CMIoT architecture with the assist of the communication auxiliary gateway, and design the simplified protocol message format under the premise of satisfying the functional requirements. At the same time, the CMIoT architecture model is built based on the Ptolemy II modeling environment and implemented in a community, and it is proved that the interconnection between the IPv6 network and the physical network can be realized more effectively.

Network utility maximization has been widely adopted to allocate the resource of networks. However, it suffers from slow convergence under distributed computational environment. This paper proposes a fast rate control algorithm to maximize network utility for energy harvesting in a wireless sensor network. Energy harvesting and channel bandwidth limits are considered together to formulate as a utility maximization problem. Then, an accelerated distributed gradient method is proposed to solve the problem for energy harvesting. Numerical experiments show that the accelerated method achieves faster convergence to the optimal sampling rate under energy and channel constraints than traditional gradient descent methods.

With the acceleration of human economic activities and dramatic changes in climate, the validity of the stationarity assumption of flood time series frequency analysis has been questioned. In this study, a framework for flood frequency analysis is developed on the basis of a tool, namely, the Generalized Additive Models for Location, Scale, and Shape (GAMLSS). We introduced this model to construct a non-stationary model with time and climate factor as covariates for the 50-year snowmelt flood time series in the Kenswat Reservoir control basin of the Manas River. The study shows that there are clear non-stationarities in the flood regime, and the characteristic series of snowmelt flood shows an increasing trend with the passing of time. The parameters of the flood distributions are modelled as functions of climate indices (temperature and rainfall). The physical mechanism was incorporated into the study, and the simulation results are similar to the actual flood conditions, which can better describe the dynamic process of snowmelt flood characteristic series. Compared with the design flood results of Kenswat Reservoir approved by the China Renewable Energy Engineering Institute in December 2008, the design value of the GAMLSS non-stationary model considers that the impact of climate factors create a design risk in dry years by underestimating the risk.

The development of spaceborne Synthetic Aperture Radar (SAR) technology declares that the golden era of SAR remote sensing in archeology is approaching; however, nowadays its methodology framework is still lacking due to the inadequate case studies validated by ground-truths. In this study, we investigated the crop marks using multi-temporal Cosmo-SkyMed data acquired in 2013 by applying a two-step decision-tree classifier in conjunction with a spatial analysis in an area of archeological interest nearby the archeological site of Han-Wei capital city (1900–1500 BP), in Luoyang, China. The time-series backscattering anomalies related to the wheat growth cycle were identified and then further validated in two zones by geophysical investigations (Ground Penetration Radar and electrical measurements) and in a third zone by archeological excavations made after the SAR data acquisition. This study provides a new approach for the relic detection, shallowly buried and covered by the crop vegetation, by temporal crop marks on spaceborne SAR images. We also emphasize the necessity to establish a satellite-to-ground methodology framework for the promotion of remote-sensing technology in archeology.

Recently, the use of intelligent technologies in clinical decision making in the telehealth environment has begun to play a vital role in improving the quality of patients' lives and helping reduce the costs and workload involved in their daily healthcare. In this paper, an effective medical recommendation system that uses a fast Fourier transformation-coupled machine learning ensemble model is proposed for short-term disease risk prediction to provide chronic heart disease patients with appropriate recommendations about the need to take a medical test or not on the coming day based on analysing their medical data. The input sequence of sliding windows based on the patient's time series data are decomposed by using the fast Fourier transformation in order to extract the frequency information. A bagging-based ensemble model is utilized to predict the patient's condition one day in advance for producing the final recommendation. A combination of three classifiers-artificial neural network, least squares-support vector machine, and naive bayes-are used to construct an ensemble framework. A real-life time series telehealth data collected from chronic heart disease patients are utilized for experimental evaluation. The experimental results show that the proposed system yields a very good recommendation accuracy and offers an effective way to reduce the risk of incorrect recommendations as well as reduce the workload for heart disease patients in conducting body tests every day. The results conclusively ascertain that the proposed system is a promising tool for analyzing time series medical data and providing accurate and reliable recommendations to patients suffering from chronic heart diseases.

Hot deformation behavior and the microstructural evolution of Inconel 625 superalloy plates are investigated by hot compression tests in a range of working temperatures (800–1050 °C) and strain rates (0.001–1 s−1). The microstructural observation shows that a strong texture forms when the processing temperature is below 950 °C, whose intensity decreases with the increases of the temperature, and it disappears when compressing above 950 °C. During the compression test, twin-related dynamic recrystallization (DRX) occurs in the investigated temperature range, and the intensity of twin-related DRX increases with the increases of the temperature. In addition, as the temperature increases, the intensity of continuum DRX decreases.

Physicallybased constitutive equations are increasingly used for finite element simulations of metal forming processes due to the robust capability of modelling of underlying microstructure evolutions. However, one of thelimitations of current models is the lack of practical validation using real microstructure data due to the difficulties in achieving statistically meaningful data at a sufficiently large microstructure scale. Particularly, dislocation density and grain size governing the hardening in sheet deformation are of vital importance and need to be precisely quantified. In this paper, a set of dislocation mechanics-based plane stress material model is constructed for hot forming aluminum alloy. This material model is applied to high strength 7075 aluminum alloy for the prediction of the flow behaviorsconditioned at 300–400 °C with various strain rates. Additionally, an electron backscatter diffraction (EBSD) technique was applied to examine the average grain size and geometrical necessary dislocation (GND) density evolutions, enabling both macro- and micro- characteristics to be successfully predicted. In addition, to simulate the experienced plane stress states in sheet metal forming, the calibrated model is further extended to a plane stress stateto accuratelypredict the forming limits under hot conditions.The comprehensively calibrated material model could be used for guidinga better selection of industrial processing parameters and designing process windows, taking into account both the formed shape as well as post formed microstructure and, hence, properties.

Different from the traditional healthcare field, Medical Cyber Physical Systems (MCPS) rely more on wireless wearable devices and medical applications to provide better medical services. The secure storage and sharing of medical data are facing great challenges. Blockchain technology with decentralization, security, credibility and tamper-proof is an effective way to solve this problem. However, capacity limitation is one of the main reasons affecting the improvement of blockchain performance. Certificateless aggregation signature schemes can greatly tackle the difficulty of blockchain expansion. In this paper, we describe a two-layer system model in which medical records are stored off-blockchain and shared on-blockchain. Furthermore, a multi-trapdoor hash function is proposed. Based on the proposed multi-trapdoor hash function, we present a certificateless aggregate signature scheme for blockchain-based MCPS. The purpose is to realize the authentication of related medical staffs, medical equipment, and medical apps, ensure the integrity of medical records, and support the secure storage and sharing of medical information. The proposed scheme is highly computationally efficient because it does not use bilinear maps and exponential operations. Many certificateless aggregate signature schemes without bilinear maps in Internet of things (IoT) have been proposed in recent years, but they are not applied to the medical field, and they do not consider the security requirements of medical data. The proposed scheme in this paper has high computing and storage efficiency, while meeting the security requirements in MCPS.

The region near Dujiangyan City and Wenchuan County, Sichuan China, including significant giant panda habitats, was severely impacted by the Wenchuan earthquake. Large-area landslides occurred and seriously threatened the lives of people and giant pandas. In this paper, we report the development of an enhanced multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology to monitor potential post-seismic landslides by analyzing coherent scatterers (CS) and distributed scatterers (DS) points extracted from multi-temporal l-band ALOS/PALSAR data in an integrated manner. Through the integration of phase optimization and mitigation of the orbit and topography-related phase errors, surface deformations in the study area were derived: the rates in the line of sight (LOS) direction ranged from −7 to 1.5 cm/a. Dozens of potential landslides, distributed mainly along the Minjiang River, Longmenshan Fault, and in other the high-altitude areas were detected. These findings matched the distribution of previous landslides. InSAR-derived results demonstrated that some previous landslides were still active; many unstable slopes have developed, and there are significant probabilities of future massive failures. The impact of landslides on the giant panda habitat, however ranged from low to moderate, would continue to be a concern for conservationists for some time in the future.

With the development of Synthetic Aperture Radar (SAR) in terms of multi-band, multi-polarization and high-resolution data, space radar remote sensing for archaeology has become a potential field for research. Nevertheless, the archaeological detection capability of this technology has so far not been fully assessed. This paper is a pioneering effort to assess the potential of satellite SAR X-band data in the detection of archaeological marks. We focus on the results obtained from a collaborative contribution jointly carried out by archaeologists and remote sensing experts in order to test the use of COSMO-SkyMed data in different contexts and environmental conditions. The methodological approaches we adopted are based on two different feature-enhancement procedures: (i) multi-temporal analysis performed to reduce noise and highlight archaeological marks; (ii) single-date analysis to assess the ability of the single SAR scene to detect archaeological features like with optical remote sensing. Results from multi-temporal data analysis, conducted using 40 scenes from COSMO-SkyMed X-band Stripmap data (27 February to 17 October 2013), enable us to detect unknown archaeological crop, soil, and shadow marks representing Luoyang city, dating from the Eastern-Han to Northern-Wei Dynasties. Single-date analyses were conducted using COSMO-SkyMed Spotlight scenes acquired for Sabratha (Libya) and Metapontum (southern Italy). These case studies were selected because they are characterized by diverse superficial conditions (desert and Mediterranean area) and archaeological marks (crop, soil and shadow). The results we obtained for both of them show that even a single SAR X-band acquisition is a feasible and effective approach for archaeological prospection. Overall, the methodological approach adopted demonstrated that both multi-temporal and single-date analysis are suitable for the enhancement of archaeological and palaeoenvironmental features.