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Cucumber is one of the top ten vegetables globally and is widely cultivated worldwide. However, Fusarium wilt, caused by Fusarium oxysporum f. sp. Cucumerinum, is one of the most serious soil-borne diseases in cucumber cultivation, causing significant economic losses. Biological control has great potential in the prevention of cucumber wilt disease, but the mechanism involved still needs further research. In this study, biocontrol isolate Bacillus subtilis 1JN2, which was isolated in our previous work, was evaluated in field conditions against Fusarium wilt, and the rhizosphere fungal diversity was analyzed. The results indicated that the biocontrol efficacy of B. subtilis 1JN2 reached 58.5% compared with the blank control, and the population density of F. oxysporum in the rhizosphere decreased from 495 copies/g of soil before inoculation to 20 copies/g 14 days after treatment. High-throughput sequencing demonstrated that after an inoculation of 1JN2, the populations that decreased significantly include the genera of Olpidium and Pseudallescheria, from more than 20% to less than 8%. And the most increased population belonged to the family Chaetomiaceae, from 6.82% to 18.77%, 12.39%, 44.41%, and 19.41% at the four sample time points after treatment. In addition, soil-related enzyme activities, including catalase, soil dehydrogenase, alkaline phosphatase, and polyphenol oxidase, were analyzed before and after treatment with 1JN2. The results indicated that all the enzyme activities showed an upward trend following inoculation. These findings demonstrate the potential of using B. subtilis 1JN2 as a biocontrol agent for controlling Fusarium wilt in cucumber. [ABSTRACT FROM AUTHOR]

The discrete Legendre transform is a powerful tool for analyzing the properties of convex lattice sets. In this paper, for t > 0 , we study a class of convex lattice sets and establish a relationship between vertices of the polar of convex lattice sets and vertices of the polar of its t − dilation. Subsequently, we show that there exists a class of convex lattice sets such that its polar is itself. In addition, we calculate upper and lower bounds for the discrete Mahler product of a class of convex lattice sets. [ABSTRACT FROM AUTHOR]

The reservoir in the Anyue gas field, located in the Sichuan basin of China, belongs to the second member of the Dengying formation and has distinctive geological features. It is characterized by strong heterogeneity, low porosity, low permeability, and locally developed natural fractures. The reservoir space consists primarily of corrosion holes, natural fractures, and similar voids. Moreover, the lower reservoir exhibits high water saturation and a homogeneous bottom-water interface. Since it is a carbonate-based hydrocarbon reservoir with low porosity and permeability, deep acid fracturing has proven to be an efficient method for enhancing individual well production. However, the reconstruction of the second member of the Dengying formation reservoir poses significant challenges. The reservoir contains high-angle natural fractures, small vertical stress differences, and is located in close proximity to the gas–water interface. As a result, it becomes difficult to control the height of the acid break. Improper acid break treatment may easily result in water production affecting gas well production. To explore ways to control the longitudinal extension of acid fractures, 3D numerical models focusing on the initiation and expansion of acid fractures have been developed. This model takes into account geological and engineering factors such as stress differences, acid fracture displacements and scales, and their effects on the longitudinal extension of acid fractures. It was revealed that the pressure difference is the main controlling factor for the acid fracture height, followed by the reservoir thickness, the interlayer thickness, and the viscosity of the working fluid. Technical countermeasures for controlled fracture and high-acid fracturing tailored to different reservoir characteristics have been proposed, and design parameters for controlled fracture and high-acid fracturing can be optimized. By effectively controlling the vertical extension of the acid fracture, it is possible to maximize production from a single well while avoiding interference from the lower water layer. This study provides theoretical guidance for the application of deep-acid-fracturing techniques in low-permeability bottom-water gas reservoirs. [ABSTRACT FROM AUTHOR]

Bitespiramycin, has been shown to have a therapeutic effect against respiratory tract inflammation, including a potential effect against COVID-19. A current clinical trial in China showed that bitespiramycin was an effective treatment for severe pneumonia and intracranial infection. However, there is lack of an analytical method to elucidate the distribution of bitespiramycin. In this study, a highly sensitive, rapid and reliable UPLC–MS/MS method was developed to comprehensively characterize the bitespiramycin distribution in various bio-samples, which is significantly improved upon the published work. A rapid sample preparation method was developed by using n-butanol as the solvent to extract bitespiramycin from different bio-samples. The extract was then directly analyzed by UPLC–MS/MS coupled with an alkaline-resistant column after centrifugation which avoids the time-consuming concentration process under nitrogen and redissolution. The method was employed to accurately quantify bitespiramycin and its metabolites in rat plasma, tissues, and human cerebrospinal fluid. Notably, the presence of bitespiramycin and its metabolites was identified for the first time in various rat organs including brain, testis, bladder and prostate as well as in human cerebrospinal fluid. This newly developed approach shows great promise for drug distribution assays including other antibiotics and can help elucidate the ADME of bitespiramycin. [ABSTRACT FROM AUTHOR]

Integrins are heterodimeric cell-surface receptors that regulate cell–cell adhesion and cellular functions through bidirectional signaling. On the other hand, anomalous trafficking of integrins is also implicated in severe pathologies as cancer, thrombosis, inflammation, allergies, and multiple sclerosis. For this reason, they are attractive candidates as drug targets. However, despite promising preclinical data, several anti-integrin drugs failed in late-stage clinical trials for chronic indications, with paradoxical side effects. One possible reason is that, at low concentration, ligands proposed as antagonists may also act as partial agonists. Hence, the comprehension of the specific structural features for ligands' agonism or antagonism is currently of the utmost interest. For α4β1 integrin, the situation is particularly obscure because neither the crystallographic nor the cryo-EM structures are known. In addition, very few potent and selective agonists are available for investigating the mechanism at the basis of the receptor activation. In this account, we discuss the physiological role of α4β1 integrin and the related pathologies, and review the few agonists. Finally, we speculate on plausible models to explain agonism vs. antagonism by comparison with RGD-binding integrins and by analysis of computational simulations performed with homology or hybrid receptor structures. [ABSTRACT FROM AUTHOR]

In order to address the challenges of small and micro-water pollution in parks and the low level of 3D visualization of water quality monitoring systems, this research paper proposes a novel wireless remote water quality monitoring system that combines the Internet of Things (IoT) and a 3D model of reality. To begin with, the construction of a comprehensive 3D model relies on various technologies, including unmanned aerial vehicle (UAV) tilt photography, 3D laser scanning, unmanned ship measurement, and close-range photogrammetry. These techniques are utilized to capture the park's geographical terrain, natural resources, and ecological environment, which are then integrated into the three-dimensional model. Secondly, GNSS positioning, multi-source water quality sensors, NB-IoT wireless communication, and video surveillance are combined with IoT technologies to enable wireless remote real-time monitoring of small and micro-water bodies. Finally, a high-precision underwater, indoor, and outdoor full-space real-scene three-dimensional visual water quality monitoring system integrated with IoT is constructed. The integrated system significantly reduces water pollution in small and micro-water bodies and optimizes the water quality monitoring system. [ABSTRACT FROM AUTHOR]

The three-phase imbalance in low-voltage distribution networks (LVDNs) seriously threatens the security and stability of the power system. At present, a standard solution is automatic phase commutation, but this method has limitations because it does not address the branch imbalance and premature convergence or instability of the commutation algorithm. Therefore, this paper proposes a novel refined regulation commutation system, combined with a modified optimized commutation algorithm, and designs a model and simulation for feasibility verification. The refined regulatory model incorporates branch control units into the traditional commutation system. This effectively disperses the main controller's functions to each branch and collaborates with intelligent fusion terminals for precise adjustment. The commutation algorithm designed in this paper, combined with the above model, adopts strategies such as symbol encoding, cubic chaotic mapping, and adaptive adjustment based on traditional genetic algorithms. In addition, in order to verify the effectiveness of the proposed method, this paper establishes a mathematical model with the minimum three-phase imbalance and commutation frequency as objectives and establishes a simulation model. The results of the simulation demonstrate that this method can successfully lower the three-phase imbalance of the low-voltage distribution network. It leads to a decrease of the main circuit's three-phase load imbalance rate from 27% to 6% and reduces each branch line's three-phase imbalance ratio to below 10%. After applying the method proposed in this paper, the main and branches circuit three-phase imbalance are both lower than the limit ratio of the LVDNs, which can improve the quality and safety of electricity consumption. Additionally, the results also prove that the commutation algorithm under this method has faster convergence speed, better application effect, and better stability, which has promotion and application value. [ABSTRACT FROM AUTHOR]

Chronic gastritis (CG) is a common clinical digestive system disease, which is not easyily cured and is prone to recurrence. Traditional Chinese medicine (TCM) plays a significant role in the treatment of CG and has attracted increasing attention for clinical applications. In recent years, a large number of reports have shown that TCM has good therapeutic effect on CG. The aim of this paper is to investigate the pharmacological activities and mechanism of action of TCM in the treatment of CAG. Therefore, by searching the databases of Pubmed, China National Knowledge Infrastructure, Wanfang, and Baidu academic databases, this paper has summarized the molecular mechanisms of TCM in improving CG. The results show that the improvement of GC by TCM is closely related to a variety of molecular mechanisms, including the inhibition of Helicobacter pylori (Hp) infection, alleviation of oxidative stress, improvement of gastric function, repair of gastric mucosa, inhibition of inflammatory response, and apoptosis. More importantly, IRF8-IFN-γ, IL-4-STAT6, Hedgehog, pERK1/2, MAPK, PI3K-Akt, NF-κB, TNFR-c-Src-ERK1/2-c-Fos, Nrf2/HO-1, and HIF-1α/VEGF signaling pathways are considered as important molecular targets for TCM in the treatment of GC. These important findings will provide a direction and a basis for further exploring the pathogenesis of GC and tapping the potential of TCM in clinical treatment. This review also puts forward a bright prospect for future research of TCM in the treatment of CG. [ABSTRACT FROM AUTHOR]

Urbanization is a crucial indicator which reflects the socio-economic development of a country or region. The regions across the Taiwan Strait (TSR) have garnered attention worldwide as being representative of typical urbanization development along the southeastern coast. Currently, research in the TSR predominantly focuses on individual regions, with limited academic achievements comparing urbanization paths across the strait. In particular, the domain of comparative analysis of the spatiotemporal characteristics of urbanization dynamics in TSR by using long time series of nighttime light data remains largely underexplored. Therefore, this study focused on comparing the urbanization paths in the TSR and analyzing the spatiotemporal characteristics of urbanization by using the long-term nighttime light data from 1992 to 2020. Additionally, some methods such as Theil–Sen median trend analysis, Mann–Kendall significance test, Hurst exponent, spatial statistics, and time series were used to quantitatively analyze the spatial distribution patterns and temporal trends of nighttime lights in the TSR since 1992. The results were as follows: (1) From 1992 to 2020, the spatial distribution of nighttime light data in TSR exhibited significant spatial heterogeneity, with high-value areas mainly located in southeastern Fujian and northwestern Taiwan, while low-value areas were concentrated in Fujian's inland regions; (2) During this period, nighttime lighting data increased from 729,863 in 1992 to 2,729,052 in 2020, and the percentage of its high-value (40–063) increased from 2.59% in 1992 to 12.22% in 2020; (3) Comparison of nighttime light data across representative cities from Taiwan (Taipei, Hsinchu) and Fujian (Xiamen, Fuzhou) uncovered distinct growth patterns—while Taiwanese cities had a high initial brightness value (the lowest value in the last 30 years was 518,379.4), their growth was relatively slow (average growth rate of 17%); Fujian cities, on the other hand, started from lower initial brightness value (the lowest value in the last 30 years was 35,123.1), but displayed substantial growth vigor (average growth rate of 222%); (4) During the study period, the nighttime light data of the vast majority of cities in the TSR demonstrated a significant increasing trend, particularly in coastal areas and urban centers; (5) Predictions of future trend variation suggest that the significantly increasing trend of cities surrounding Taiwan's primary metropolitan areas will intensify, whereas metropolitan regions such as Keelung may witness a decline in future trend variations. However, only a mere 0.03% of the nighttime light data show a significant decreasing trend. Additionally, there are distinct differences in the urbanization development stages of the TSR. Fujian is currently undergoing rapid urbanization, while Taiwan's urbanization has entered a stable stage. The study reveals that factors such as geographical location, natural resources, transportation infrastructure, population size, and industrial structure collectively influence the urbanization characteristics of the TSR. This research bears substantial significance for deepening the comprehension of the patterns and processes of urbanization development in the TSR and provides valuable insights for urban construction and development across the strait. [ABSTRACT FROM AUTHOR]

To solve the problem of inadequate feature extraction by the model due to factors such as occlusion and illumination in person re-identification tasks, this paper proposed a model with a joint cross-consistency learning and multi-feature fusion person re-identification. The attention mechanism and the mixed pooling module were first embedded in the residual network so that the model adaptively focuses on the more valid information in the person images. Secondly, the dataset was randomly divided into two categories according to the camera perspective, and a feature classifier was trained for the two types of datasets respectively. Then, two classifiers with specific knowledge were used to guide the model to extract features unrelated to the camera perspective for the two types of datasets so that the obtained image features were endowed with domain invariance by the model, and the differences in the perspective, attitude, background, and other related information of different images were alleviated. Then, the multi-level features were fused through the feature pyramid to concern the more critical information of the image. Finally, a combination of Cosine Softmax loss, triplet loss, and cluster center loss was proposed to train the model to address the differences of multiple losses in the optimization space. The first accuracy of the proposed model reached 95.9% and 89.7% on the datasets Market-1501 and DukeMTMC-reID, respectively. The results indicated that the proposed model has good feature extraction capability. [ABSTRACT FROM AUTHOR]

The protection of mangroves through nature reserves has been demonstrated to be effective. There were many studies evaluating the mangrove protection effect. However, the evaluation of mangrove growth quality with positive or negative growth trends, as well as restoration potential against disturbance in nature reserves, is still lacking. Thus, this study proposed a hierarchical evaluation framework for mangrove protection in nature reserves, which takes long-term metrics at three levels of loss and gain areas, patch pattern dynamics, and pixel growth trends into account. The continuous change detection and classification (CCDC) was utilized to identify the change condition of mangroves in six nature reserves of the Guangdong–Hong Kong–Macao Greater Bay Area. The Entropy Weight Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was utilized for scores evaluation of protection effort comparison from 2000 to 2020. The study results had the following three main findings. Firstly, the mangrove forest area increased by about 294.66 ha in four reserves and slightly decreased by about 58.86 ha in two. Most reserves showed an improved patches intact pattern and more positive growth trends. Secondly, the establishment of nature reserves and afforestation were the main causes of mangrove area gain. Until 2010, aquaculture, agriculture, and urban development were the biggest threats to mangroves. Finally, the protection of the reserves was successful in the early decades, but the general evaluation scores showed a decline in recent years once we considered the growth trends for quality. The proposed hierarchical evaluation methods provide a new sight to research the impacts of abrupt change and protection resilience status of the gradual restoration of nature reserves. [ABSTRACT FROM AUTHOR]

Open-pit mining and reclamation damage the land, resulting in unknown and significant changes to the regional ecology and ecosystem services. Surface mining restoration procedures necessitate a significant amount of money, typically at an unclear cost. Due to temporal and regional variability, few studies have focused on the cumulative impacts of mining activities. To investigate the ecological cumulative effects (ECE) of past mining and reclamation activities, this study continuously tracked land cover changes spatially and temporally based on phenological indices and focuses on the spatial and temporal evolution of past mining and reclamation areas using the LandTrendr algorithm. The cumulative trends of ecosystem services in the Pingshuo mining area from 1986 to 2021 were revealed using a uniform standard value equivalent coefficient. Meanwhile, the cumulative ecological effects due to essential ecosystem service functions were analyzed, including soil formation and protection, water containment, biodiversity maintenance, climate regulation, and food production. The synergistic effects and trade-offs among the functions were also explored using Spearman's correlation coefficient. The results showed that (1) open-pit mining resulted in 93.51 km2 of natural land, 39.60 km2 of disturbed land, and 44.58 km2 of reclaimed land in the Pingshuo mine; (2) open-pit mining in the mine mainly resulted in the loss of 122.18 km2 (80.91%) of native grassland, but, through reclamation into grassland (31.30 km2), cropland (72.95 km2), and forest land (10.62 km2), the damaged area caused by mining only slightly increased; (3) the cumulative ecological value of the mining area declined by 128.78 million RMB; however, the real cumulative value per unit area was lower in the disturbance area (1483.47 million RMB) and the reclamation area (1297.00 million RMB) than in the natural area (2120.98 million RMB); (4) the cumulative value of the food production function in the study area increased, although the values of all individual functions in the study area decreased. Most of the cumulative values of services had a strong synergistic relationship. However, in the natural area, food production (FP) showed a trade-off relationship with the cumulative value of biodiversity maintenance (BM), soil formation and protection (SP), and water conservation (WC) service functions, respectively. This study constructed a methodology for analyzing mining-impacted ecosystem services using time-series processes, reproducing historically complete information for policymakers and environmental regulators. [ABSTRACT FROM AUTHOR]

Characteristic towns represent relatively small industrial platforms, characterized by clear industrial positioning, cultural connotations, tourism, and certain community functions. Determining the spatial spillover scope of characteristic towns is of importance for both spatial decision-making and policy optimization. By using the gradient difference method, this paper aims to determine the spatial spillover scope of characteristic towns in 2014 and 2020. The research is based on the nighttime light data of the first three batches of Zhejiang characteristic towns. The results suggest that (1) there is a spatial spillover phenomenon in Zhejiang characteristic towns; namely, the results of 84 characteristic towns are either consistent or partially consistent with the expected results; (2) there is an inverse S-shaped decreasing trend from the boundary of characteristic towns; the trend rapidly decreases with an increase at the boundary distance of characteristic towns; and (3) characteristic towns are formed around the 1 km core spillover area and 2 km secondary spillover area. Provincial characteristic towns have relatively high maturity and account for 43.86% of the total. They are concentrated in the 1 km range. Compared to previous research, this study was able to accurately identify the spatial spillover scope of characteristic towns using the gradient difference method. Specifically, the spatial spillover scope is concentrated primarily in the core spillover area of 1 km. These findings serve as reference for the adjustment and optimization of characteristic town policies as well as of town's spatial layouts. [ABSTRACT FROM AUTHOR]

Rock resistivity is a major geophysical technical parameter in geological and geotechnical engineering, geothermal prospecting, and oil and gas exploration. Its accurate measurement is of great significance to achieve the goal of "carbon peak and carbon neutrality". To solve anisotropic problems, a method to test the radial resistivity in cylindrical core samples has been proposed and has been deemed the universal method, as it has the virtues of no specially processed sample being needed and nondestructive testing. However, there is still a difference in the radial resistivities obtained from this method and another testing method that is commonly used for cuboid samples. Furthermore, the differences between these methods have not yet been made clear in China or elsewhere. Therefore, we compared the results of the above-two testing methods via numerical simulations after establishing the potential field distribution, and, in combination with their methodological principles, illustrated the differences between the resistivities determined in samples with distinct shapes obtained using the two testing methods, summarized the conditions when there was zero difference and considerable difference when using the two methods, and provided a theoretical basis for the reasonable selection of an appropriate method to test the resistivity anisotropy. [ABSTRACT FROM AUTHOR]

Farmland consolidation (FC) is among the measures to solve farmland issues, such as farmland fragmentation, and its impact on the ecological environment has always been controversial. In terms of long-term series and large-area analysis, the calculation of a large amount of data makes the analysis of the ecological–environmental quality of farmland consolidation very difficult. To solve this problem, our study applied a remote sensing ecological index model on the Google Earth Engine platform to analyze the changes in the ecological–environmental quality in two prefecture-level cities in Liaoning Province over the past 20 years. In addition, we analyzed the impacts of FC projects on the ecological environment from 2006 to 2018 and compared them to farmland without consolidation. The study results show that FC caused negative impacts on the quality of the ecological environment during the FC period (2006–2018) and that the FC's positive effects take time to develop. In each FC phase, the results showed that FC exhibited negative effects before 2010 because the proportion of ecological–environmental quality reductions (0–47.67%) was higher than the proportion of increases (9.62–46.15%) in those FC phases. Since 2011, the area experiencing positive ecological–environmental benefits (31.96–72.01%) enabled by FC is higher than the area of negative impact (2.24–18.07%). This seems to be triggered by policy evolution. Based on the trend analysis, the proportion of FC areas with improved ecological–environmental quality grew faster (Gini index decreased 0.09) than that of farmland without consolidation (Gini index decreased 0.05) from before FC to after FC. Moreover, the new FC projects (2011–2018) performed better than the early projects (2006–2010), which may be due to policy evolution and technological advancements. However, the new FC projects (2011–2018) caused a dramatic decrease in ecological–environmental quality in a small number of areas due to the study time constraints. In conclusion, we believe that FC could improve the ecological–environmental quality of farmland, whereas some measures are needed to reduce its temporal negative impact on ecological–environmental quality, which may be caused by human interference. The remote sensing ecological index obtained using the Google Earth Engine platform provided an effective and reliable method for detecting the impacts of FC on the ecological–environmental quality of farmland. This could provide the basis and support for the monitoring of ecological–environmental changes in FC areas at a regional level. [ABSTRACT FROM AUTHOR]

Stroke is a leading cause of death and long-term disability worldwide. Astrocytes structurally compose tripartite synapses, blood–brain barrier, and the neurovascular unit and perform multiple functions through cell-to-cell signaling of neurons, glial cells, and vasculature. The crosstalk of astrocytes and other cells is complicated and incompletely understood. Here we review the role of astrocytes in response to ischemic stroke, both beneficial and detrimental, from a cell–cell interaction perspective. Reactive astrocytes provide neuroprotection through antioxidation and antiexcitatory effects and metabolic support; they also contribute to neurorestoration involving neurogenesis, synaptogenesis, angiogenesis, and oligodendrogenesis by crosstalk with stem cells and cell lineage. In the meantime, reactive astrocytes also play a vital role in neuroinflammation and brain edema. Glial scar formation in the chronic phase hinders functional recovery. We further discuss astrocyte enriched microRNAs and exosomes in the regulation of ischemic stroke. In addition, the latest notion of reactive astrocyte subsets and astrocytic activity revealed by optogenetics is mentioned. This review discusses the current understanding of the intimate molecular conversation between astrocytes and other cells and outlines its potential implications after ischemic stroke. "Neurocentric" strategies may not be sufficient for neurological protection and recovery; future therapeutic strategies could target reactive astrocytes. [ABSTRACT FROM AUTHOR]

Peptide-decorated nanosystems have demonstrated higher stability and improved cellular uptake as compared to bare NPs and appear highly promising in diagnostics and theranostics of cancer. Herein, we discuss the preparation and structural characterization of peptide-functionalized silica/PEG NPs, starting from peptide–block copolymers, prepared in turn by conjugation of the peptides to block copolymers before NP formation. This synthetic design allowed full control of density and composition of peptide surface coverage. Preliminary experiments support the low toxicity of the fluorescent peptide–NPs and their ability of cell internalization. [ABSTRACT FROM AUTHOR]

Lesion segmentation is a critical task in skin cancer analysis and detection. When developing deep learning-based segmentation methods, we need a large number of human-annotated labels to serve as ground truth for model-supervised learning. Due to the complexity of dermatological images and the subjective differences of different dermatologists in decision-making, the labels in the segmentation target boundary region are prone to produce uncertain labels or error labels. These labels may lead to unsatisfactory performance of dermoscopy segmentation. In addition, the model trained by the errored one-hot label may be overconfident, which can lead to arbitrary prediction and model overfitting. In this paper, a superpixel-oriented label distribution learning method is proposed. The superpixels formed by the simple linear iterative cluster (SLIC) algorithm combine one-hot labels constraint and define a distance function to convert it into a soft probability distribution. Referring to the model structure of knowledge distillation, after Superpixel-oriented label distribution learning, we get soft labels with structural prior information. Then the soft labels are transferred as new knowledge to the lesion segmentation network for training. Ours method on ISIC 2018 datasets achieves an Dice coefficient reaching 84%, sensitivity 79.6%, precision 80.4%, improved by 19.3%, 8.6% and 2.5% respectively in comparison with the results of U-Net. We also evaluate our method on the tasks of skin lesion segmentation via several general neural network architectures. The experiments show that ours method improves the performance of network image segmentation and can be easily integrated into most existing deep learning architectures. [ABSTRACT FROM AUTHOR]

Characteristic towns have emerged along with China's economic and social development. As a new model of small-town development, they have played an essential role in promoting industrial transformation and upgrade, improving the living environment, and promoting regional innovation and development. Accurate identification of the expansion characteristics of National Characteristic Towns (NCTs) is vital for optimizing the spatial layout of characteristic towns and adjusting the policies of characteristic towns. This study used a dataset on nighttime light to identify expanding NCTs and measure their expansion from 2000 to 2020. In total, 233 expanding NCTs were identified, accounting for 58.25% of the NCTs in China. The areas with the most significant intensity of expansion are primarily located in the East, South, and North economic regions. The critical period of NCTs expansion primarily occurred in the periods 2008–2011 and 2011–2014. Our results show that NCTs are highly consistent with the spatial distribution of urban agglomerations, and the development of NCTs is inherently related to the development of urban agglomerations in the region. The implementation of NCT policies has significantly promoted the development of NCTs in the Central and Western economic regions, which face challenging development issues and differ from those in the Eastern region. The method proposed in this study can effectively identify the 'hot spots' of expanding NCTs and the critical periods of their expansion. [ABSTRACT FROM AUTHOR]

Age-related macular degeneration (AMD) is a retinal disorder affecting the elderly, and society's aging population means that the disease is becoming increasingly prevalent. The vision in patients with early AMD is usually unaffected or nearly normal but central vision may be weakened or even lost if timely treatment is not performed. Therefore, early diagnosis is particularly important to prevent the further exacerbation of AMD. This paper proposed a novel automatic detection method of AMD from optical coherence tomography (OCT) images based on deep learning and a local outlier factor (LOF) algorithm. A ResNet-50 model with L2-constrained softmax loss was retrained to extract features from OCT images and the LOF algorithm was used as the classifier. The proposed method was trained on the UCSD dataset and tested on both the UCSD dataset and Duke dataset, with an accuracy of 99.87% and 97.56%, respectively. Even though the model was only trained on the UCSD dataset, it obtained good detection accuracy when tested on another dataset. Comparison with other methods also indicates the efficiency of the proposed method in detecting AMD. [ABSTRACT FROM AUTHOR]

Socioeconomic development is often dependent on the production of mining resources, but both opencast and underground mining harm vegetation and the eco-environment. Under the requirements of the construction for ecological civilization in China, more attention has been paid to the reclamation of mines and mining management. Thus, it is the basement of formulating policies related to mining management and implementing reclamation that detection of mining disturbance rapidly and accurately. This research carries on an empirical study in the Dexing copper mine, Jiangxi, China, aiming at exploring the process of distance and reclamation. Based on the dense time-series stack derived from the Landsat archive on Google Earth Engine (GEE), the disturbance of surface mining in the 1986–2020 period has been detected using the continuous change detection and classification (CCDC) algorithm. The results are that: (1) the overall accuracy of damage and recovery is 92% and 88%, respectively, and the Kappa coefficient is 85% and 84% respectively. This means that we obtained an ideal detection effect; (2) the surface-mining area was increasing from 1986–2020 in the Dexing copper mine, and the accumulation of mining damage is approximately 2865.96 ha with an annual area of 81.88 ha. We also found that the area was fluctuating with the increase. The detected natural restoration was appraised at a total of 544.95 ha in the 1988–2020 period with an average restoration of 16.03 ha. This means that it just restores less in general; (3) it has always been the case that the Dexing mine is damaged by mining and reclamation in the whole year (it is most frequently damaged month is July). All imageries in the mine are detected by the CCDC algorithm, and they are classified as four types by disturbing number in pixel scale (i.e., 0, 1, 2, more than 2 times). Based on that, we found that the only once disturbed pixels account for 64.75% of the whole disturbed pixels, which is the majority in the four classes; (4) this method provides an innovative perspective for obtaining the mining disturbed dynamic information timely and accurately and ensures that the time and number of surface mining disturbed areas are identified accurately. This method is also valuable in other applications including the detection of other similar regions. [ABSTRACT FROM AUTHOR]

In tropical/subtropical monsoon regions, accurate rice mapping is hampered by the following factors: (1) The frequent occurrence of clouds in such areas during the rice-growing season interferes strongly with optical remote sensing observations; (2) The agro-landscape in such regions is fragmented and scattered. Rice maps produced using low spatial resolution data cannot well delineate the detailed distribution of rice, while pixel-based mapping using medium and high resolutions has significant salt-and-pepper noise. (3) The cropping system is complex, and rice has a rotation schedule with other crops. Therefore, the Phenology-, Object- and Double Source-based (PODS) paddy rice mapping algorithm is implemented, which consists of three steps: (1) object extraction from multi-temporal 10-m Sentinel-2 images where the extracted objects (fields) are the basic classification units; (2) specifying the phenological stage of transplanting from Savitzky–Golay filtered enhanced vegetation index (EVI) time series using the PhenoRice algorithm; and (3) the identification of rice objects based on flood signal detection from time-series microwave and optical signals of the Sentinel-1/2. This study evaluated the potential of the combined use of the Sentinel-1/2 mission on paddy rice mapping in monsoon regions with the Hangzhou-Jiaxin-Huzhou (HJH) plain in China as the case study. A cloud computing approach was used to process the available Sentinel-1/2 imagery from 2019 and MODIS images from 2018 to 2020 in the HJH plain on the Google Earth Engine (GEE) platform. An accuracy assessment showed that the resultant object-based paddy rice map has a high accuracy with a producer (user) accuracy of 0.937 (0.926). The resultant 10-m paddy rice map is expected to provide unprecedented detail, spatial distribution, and landscape patterns for paddy rice fields in monsoon regions. [ABSTRACT FROM AUTHOR]

This paper presents the four-quadrant operation modes of bidirectional chargers for electric vehicles (EVs) framed in smart car parks. A cascaded model predictive control (MPC) scheme for the bidirectional two-stage off-board chargers is proposed. The controller is constructed in two stages. The model predictive direct power control for the grid side is applied to track the active/reactive power references. The model predictive direct current control is proposed to achieve constant current charging/discharging for the EV load side. With this MPC strategy, EV chargers are able to transmit the active and reactive powers between the EV batteries and the power grid. Apart from exchanging the active power, the vehicle-for-grid (V4G) mode is proposed, where the chargers are used to deliver the reactive power to support the grid, simultaneously combined with grid-to-vehicle or vehicle-to-grid operation modes. In the V4G mode, the EV battery functions as the static var compensator. According to the simulation results, the system can operate effectively in the full control regions of the active and reactive power (PQ) plane under the aforementioned operation modes. Fast dynamic response and great steady-state system performances can be verified through various simulation and experimental results. [ABSTRACT FROM AUTHOR]

Harmonic overvoltage in electric railway traction networks can pose a serious threat to the safe and stable operation of the traction power supply system (TPSS). Existing studies aim at improving the control damping of grid-connected converters, neglecting the impedance frequency characteristics (IFCs) of the actual TPSS. The applicable frequency range of these studies is relatively low, usually no more than half of the switching frequency, and there is a large gap with the actual traction network harmonic overvoltage frequency range of 750 Hz–3750 Hz. In this paper, first, the IFCs of the actual TPSS in the wide frequency range of 150 Hz–5000 Hz are obtained through field tests, and the resonant frequency distribution characteristics of TPSS are analyzed. After that, the aliasing effect of the sampling process and the sideband effect of the modulation process of the digital control of the grid-connected converter are considered. Based on the relative relationships among the inherent resonant frequency of the TPSS, sampling frequency and switching frequency, an impedance matching analysis method is proposed for the wide frequency range of the vehicle–grid coupling system. By this method, the sampling frequency and switching frequency can be decoupled, and the harmonic overvoltage of traction network in the frequency range of two times switching frequency and above can be directly estimated. Finally, the method proposed in this paper is validated by the comparative simulation analysis of seven different cases. [ABSTRACT FROM AUTHOR]

Nitrogen plays an important role in improving soil productivity and maintaining ecosystem stability. Mapping and monitoring the soil total nitrogen (STN) content is the basis for modern soil management. The Google Earth Engine (GEE) platform covers a wide range of available satellite remote sensing datasets and can process massive data calculations. We collected 6823 soil samples in Shandong Province, China. The random forest (RF) algorithm predicted the STN content in croplands from 2002 to 2016 in Shandong Province, China on the GEE platform. Our results showed that RF had the coefficient of determination (R2) (0.57), which can predict the spatial distribution of the STN and analyze the trend of STN changes. The remote sensing spectral reflectance is more important in model building according to the variable importance analysis. From 2002 to 2016, the STN content of cropland in the province had an upward trend of 35.6%, which increased before 2010 and then decreased slightly. The GEE platform provides an opportunity to map dynamic changes of the STN content effectively, which can be used to evaluate soil properties in the future long-term agricultural management. [ABSTRACT FROM AUTHOR]

The development and utilization of mining resources are basic requirements for social and economic development. Both open-pit mining and underground mining have impacts on land, ecology, and the environment. Of these, open-pit mining is considered to have the greatest impact due to the drastic changes wrought on the original landform and the disturbance to vegetation. As awareness of environmental protection has grown, land reclamation has been included in the mining process. In this study, we used the Shengli Coalfield in the eastern steppe region of Inner Mongolia to demonstrate a mining and reclamation monitoring process. We combined the Google Earth Engine platform with time series Landsat images and the LandTrendr algorithm to identify and monitor mining disturbances to grassland and land reclamation in open-pit mining areas of the coalfield between 2003 and 2019. Pixel-based trajectories were used to reconstruct the temporal evolution of vegetation, and sequential Landsat archive data were used to achieve accurate measures of disturbances to vegetation. The results show that: (1) the proposed method can be used to determine the years in which vegetation disturbance and recovery occurred with accuracies of 86.53% and 78.57%, respectively; (2) mining in the Shengli mining area resulted in the conversion of 89.98 km2 of land from grassland, water, etc., to barren earth, and only 23.54 km2 was reclaimed, for a reclamation rate of 26.16%; and (3) the method proposed in this paper can achieve fast, efficient identification of surface mining land disturbances and reclamation, and has the potential to be applied to other similar areas. [ABSTRACT FROM AUTHOR]

Since the reform and opening up, Chinese economic and social development has undergone great changes, and the people's living standards have improved markedly. For the national economy, the engineering construction is not only a carrier for specific economic tasks, but also a driving force for rapid and sustained economic development. With the continuous expansion of the scale of construction projects, safety management problems of construction projects are constantly exposed. How to effectively avoid accidents has become an important issue to be solved urgently in the construction industry. This paper mainly evaluates human factors in the process of construction project management, such as workers' proficiency, workers' safety awareness, technical workers' quality, and workers' emergency capacity, with the purpose of helping China's construction projects proceed smoothly. In this research, we provide a multiple attribute group decision-making (MAGDM) technique based on Pythagorean 2-tuple linguistic numbers (P2TLNs) and the VIseKriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) method for evaluating the human factors of construction projects. P2TLNs are used to represent the performance assessments of decision makers. Relying on a P2TLWA operator, P2TLWG operator, and the essential VIKOR method, a general framework is established. An application is presented to test the validity of the new method, and a comparative analysis with two algorithms and the P2TL-TODIM method is illustrated with detail. [ABSTRACT FROM AUTHOR]

Steel bars play an important role in modern construction projects and their quality enormously affects the safety of buildings. It is urgent to detect whether steel bars meet the specifications or not. However, the existing manual detection methods are costly, slow and offer poor precision. In order to solve these problems, a high precision quality inspection system for steel bars based on machine vision is developed. We propose two algorithms: the sub-pixel boundary location method (SPBLM) and fast stitch method (FSM). A total of five sensors, including a CMOS, a level sensor, a proximity switch, a voltage sensor, and a current sensor have been used to detect the device conditions and capture image or video. The device could capture abundant and high-definition images and video taken by a uniform and stable smartphone at the construction site. Then data could be processed in real-time on a smartphone. Furthermore, the detection results, including steel bar diameter, spacing, and quantity would be given by a practical APP. The system has a rather high accuracy (as low as 0.04 mm (absolute error) and 0.002% (relative error) of calculating diameter and spacing; zero error in counting numbers of steel bars) when doing inspection tasks, and three parameters can be detected at the same time. None of these features are available in existing systems and the device and method can be widely used to steel bar quality inspection at the construction site.