Search

This paper proposes a novel structural damage identification approach coupling the Mayfly algorithm (MA) with static displacement-based response surface (RS). Firstly, a hybrid optimal objective function is established that simultaneously considers the sensitivity-based residual errors of static damage identification equation and the static displacement residual. In the objective function, the static damage identification equation is addressed by the Tikhonov regularization technique. The MA is subsequently employed to conduct an optimal search and pinpoint the location and intensity of damages at the structural element level. To handle the inconformity of the static loading points and the measurement points of displacements, the model reduction and displacement extension techniques are implemented to reconstruct the static damage identification equation. Meanwhile, the static displacement-based RS is constructed to calculate the displacement residual in the hybrid objective function, thereby circumventing the time-consuming finite element calculations and improving computational efficiency. The identification results of the numerical box girder bridge demonstrate that the proposed method outperforms the particle swarm optimization, differential evolution, Jaya and whale optimization algorithms about both convergence rate in optimal searching and identification accuracy. The proposed method enables more accurate damage identification compared to methods solely based on the indicator of the residual of static damage identification equations or displacement residual. The results of identifying damage in the 21 element-truss structure and the static experiments on identifying damage in an aluminum alloy cantilever beam confirm the high efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Background: Fractures heal through a process that involves angiogenesis and osteogenesis but may also lead to non-union or delayed healing. Bone marrow mesenchymal stem cells (BMSCs) have been reported to play a pivotal role in bone formation and vascular regeneration and the p75 neurotrophin receptor (p75NTR) as being an important regulator of osteogenesis. Herein, we aim to determine the potential mediation of BMSCs by p75NTR in bone healing. Methods: Rat BMSCs were identified by flow cytometry (FCM) to detect cell cycle and surface markers. Then transfection of si/oe-p75NTR was performed in BMSCs, followed by Alizarin red staining to detect osteogenic differentiation of cells, immunofluorescence double staining was performed to detect the expression of p75NTR and sortilin, co-immunoprecipitation (CO-IP) was conducted to analyze the interaction between p75NTR and sortilin, and EdU staining and cell scratch assay to assess the proliferation and migration of human umbilical vein endothelial cells (HUVECs). The expression of HIF-1α, VEGF, and apoptosis-related proteins were also detected. In addition, a rat fracture healing model was constructed, and BMSCs-si-p75NTR were injected, following which the fracture condition was observed using micro-CT imaging, and the expression of platelet/endothelial cell adhesion molecule-1 (CD31) was assessed. Results: The results showed that BMSCs were successfully isolated, p75NTR inhibited apoptosis and the osteogenic differentiation of BMSCs, while si-p75NTR led to a decrease in sortilin expression in BMSCs, increased proliferation and migration in HUVECs, and upregulation of HIF-1α and VEGF expression. In addition, an interaction was observed between p75NTR and sortilin. The knockdown of p75NTR was found to reduce the severity of fracture in rats and increase the expression of CD31 and osteogenesis-related proteins. Conclusion: Silencing p75NTR effectively modulates BMSCs to promote osteogenic differentiation and angiogenesis, offering a novel perspective for improving fracture healing. [ABSTRACT FROM AUTHOR]

Recommender systems are widely used in e-commerce, movies, music, social media, and other fields because of their personalized recommendation functions. The recommendation algorithm is used to capture user preferences, item characteristics, and the items that users are interested in are recommended to users. Matrix factorization is widely used in collaborative filtering algorithms because of its simplicity and efficiency. However, the simple dot-product method cannot establish a nonlinear relationship between user latent features and item latent features or make full use of their personalized information. The model of a neural network combined with an attention mechanism can effectively establish a nonlinear relationship between the potential features of users and items and improve the recommendation accuracy of the model. However, it is difficult for the general attention mechanism algorithm to solve the problem of attention interaction when the number of features between the users and items is not the same. To solve the above problems, this paper proposes an attention interaction matrix factorization (AIMF) model. The AIMF model adopts a symmetric structure using MLP calculation. This structure can simultaneously extract the nonlinear features of user latent features and item latent features, thus reducing the computation time of the model. In addition, an improved attention algorithm named slide-attention is included in the model. The algorithm uses the sliding query method to obtain the user's attention to the latent features of the item and solves the interaction problem among different dimensions of the user, and the latent features of the item. [ABSTRACT FROM AUTHOR]

Objectives The histopathologic diagnosis of colorectal sessile serrated lesions (SSLs) and hyperplastic polyps (HPs) is of low consistency among pathologists. This study aimed to develop and validate a deep learning (DL)–based logical anthropomorphic pathology diagnostic system (LA-SSLD) for the differential diagnosis of colorectal SSL and HP. Methods The diagnosis framework of the LA-SSLD system was constructed according to the current guidelines and consisted of 4 DL models. Deep convolutional neural network (DCNN) 1 was the mucosal layer segmentation model, DCNN 2 was the muscularis mucosa segmentation model, DCNN 3 was the glandular lumen segmentation model, and DCNN 4 was the glandular lumen classification (aberrant or regular) model. A total of 175 HP and 127 SSL sections were collected from Renmin Hospital of Wuhan University during November 2016 to November 2022. The performance of the LA-SSLD system was compared to 11 pathologists with different qualifications through the human-machine contest. Results The Dice scores of DCNNs 1, 2, and 3 were 93.66%, 58.38%, and 74.04%, respectively. The accuracy of DCNN 4 was 92.72%. In the human-machine contest, the accuracy, sensitivity, and specificity of the LA-SSLD system were 85.71%, 86.36%, and 85.00%, respectively. In comparison with experts (pathologist D: accuracy 83.33%, sensitivity 90.91%, specificity 75.00%; pathologist E: accuracy 85.71%, sensitivity 90.91%, specificity 80.00%), LA-SSLD achieved expert-level accuracy and outperformed all the senior and junior pathologists. Conclusions This study proposed a logical anthropomorphic diagnostic system for the differential diagnosis of colorectal SSL and HP. The diagnostic performance of the system is comparable to that of experts and has the potential to become a powerful diagnostic tool for SSL in the future. It is worth mentioning that a logical anthropomorphic system can achieve expert-level accuracy with fewer samples, providing potential ideas for the development of other artificial intelligence models. [ABSTRACT FROM AUTHOR]

Monitoring agricultural abandonment is essential in understanding the effects on the environment and food security. Polarimetric synthetic aperture radar (PolSAR) is an efficient approach for the monitoring of large-scale agricultural land cover in cloudy and rainy areas. However, previous studies have not taken advantage of the valuable phase information and not fully utilized the spatiotemporal features of farmland parcels, which has seriously limited the abandoned land identification accuracy. In this study, we developed a new method for the mapping of abandoned land based on the spatiotemporal features from PolSAR Single Look Complex (SLC) images via deep learning methods. First, backscattering coefficients (σ0VV, σ0VH) were derived, and the polarimetric parameters (entropy, anisotropy and mean alpha angle) were obtained based on Cloude–Pottier polarimetric decomposition. Then, the VGG16 deep convolutional network was innovatively used to extract spatial features from both the backscattering coefficients and polarimetric parameters. Next, the separability index was calculated to select the most effective spatial features. Finally, LSTM classifications were conducted based on the time series of backscattering features, the polarimetric parameters, the extracted spatial features and their combinations. The results showed that the introduction of multitemporal polarimetric parameters and spatial features both led to an improvement in the abandoned land identification accuracy. The combination of backscattering features, polarimetric parameters and spatial features yielded the best performance in identifying abandoned land, with producer's accuracy of 88.29% and user's accuracy of 84.03%. This study demonstrated the potential of polarimetric parameters and validated the effectiveness of spatiotemporal features in abandoned land identification. It provided a practical method for the production of a highly reliable abandoned land mapping in cloudy and rainy areas. [ABSTRACT FROM AUTHOR]

The regions near the Tropic of Cancer are a latitudinal geographical zone with typical climatic, topographic, and human landscape features. It is necessary to explore the region's net primary productivity (NPP) dynamics as it combines complex topography, various vegetation types, and intense human activities. The study sets the transect near the Tropic of Cancer (TCT) and uses the Carnegie–Ames–Stanford (CASA) model to estimate the NPP from 2000 to 2020. After using the RESTREND method, the paper calculates and compares the relative contributions of climate variability and anthropogenic activities to NPP changes. Finally, the geographical detector (Geodetector) model is applied to evaluate how anthropogenic and natural factors affect spatial distribution patterns and NPP changes. The results indicated that the average annual NPP is 820.39 gC·m−2·yr−1 during the 21 years. In addition, when the NPP varies, it increases over the entire study area, with a slope of 4.81 gC·m−2·yr−1, particularly in the western region. Across the entire research area, 63.39% and 77.44% of the total pixels positively contribute to climate variability and human activities in NPP, with a contribution of 0.90 and 3.91 gC·m−2·yr−1, respectively. Within the western, central, and eastern regions, anthropogenic activities have a stronger impact on NPP than climate variability, particularly pronounced in the eastern region. Furthermore, vegetation cover is the dominant factor in the spatial patterns and NPP trends across the TCT and the three regions. In contrast, climate factors are shown to be less influential in NPP distribution than in the western region. The results also demonstrated that the effect of population density and the GDP on NPP gradually rises. Two-factor interaction is much larger than any individual factor, with the dominant interaction factor being vegetation cover with climatic factors. Lastly, the findings revealed that anthropogenic activities positively promote NPP accumulation across the TCT, thus highlighting the importance of human activity-led ecological restoration and ecological protection measures that contribute to regional carbon sequestration and carbon balance. [ABSTRACT FROM AUTHOR]

Background: Syndactyly (SD) refers to a deformity caused by the fusion and limb differentiation disorder of soft tissues and/or skeletons to varying extents between adjacent fingers (toes). The main features of this disease are phenotypic heterogeneity and genetic heterogeneity. In this study, we examined four generations of a Chinese Mongolian with different phenotypes of syndactylia and analysed and identified the pathogenic genetic variants of SD by exon sequencing. Methods: The clinical phenotypes of patients were analysed, and the hands and feet were examined by X-ray. The pedigree was drawn, and the family data were analysed. Peripheral blood was collected from the family members, and genomic DNA was extracted. The candidate genes of SD were identified by exon sequencing, and the mutation sites of the captured candidate genes were amplified by PCR and verified by Sanger sequencing. Results: The family has congenital syndactyly, which is an autosomal dominant disease. At present, this condition has been passed down for 4 generations and was identified in 9 patients, including 4 males and 5 females. Five patients, I2, II4, III5, III,7 and III10, had unilateral syndactyly, and four patients, III16, IV3, IV6 and IV7, had bilateral finger syndactyly. All of their toes were unaffected. The proband and the other patients in this family had a c.917G > A (p.R306Q) mutation, which is located at position 917 of the second exon of the HOXD13 gene. This mutation results in a change in the amino acid at position 306, in which arginine is changed to glutamine. This mutation cosegregates in unaffected individuals and affected patients in this family. Moreover, 201 Mongolian genome databases and a thousand human genome databases were referenced to further confirm that the pathogenic genetic variant that causes syndactyly in this family is found in HOXD13. Conclusion: This study found that the mutation site of the pathogenic gene in this family was HOXD13, c.917G > A (p.R306Q). The phenotype of the family member III12 was normal, but this member was also a carrier of the pathogenic genetic variant. This indicates that the disease of this family has incomplete penetrance characteristics. Our results further enrich the expression profile of the HOXD13 gene. [ABSTRACT FROM AUTHOR]

Since the outbreak of the Ukrainian-Russian conflict on 24 February 2022, Ukraine's economy, society, and cities have been devastated and struck on multiple fronts, with large numbers of refugees fleeing to neighboring countries. The lighting systems in Ukrainian cities have been severely restricted due to Russian missile bombing and curfew policies. The power shortages adversely affected the livelihoods of the Ukrainian residents dramatically. For a timely assessment of the power shortages' extent and the affected population in Ukraine, this study tracked the dynamics of nighttime light emissions in Ukraine based on the newly developed daily Black Marble product (VNP46A2) from NASA. The results show that the average light radiance in Ukrainian urban areas has decreased by about 37% since the eruption of the war, with Kiev city being the most dramatic region, having a post-conflict decrease of about 51%. In addition, by introducing near-real-time population data, we have implemented a survey of the affected population in Ukraine suffering from war-induced power shortages. Estimates show that about 17.3 million Ukrainian residents were affected by power shortages. In more detail, the number of children under 10 years old was about 2.35 million (about 5.24% of the total population), while the number of elderly people over 60 years old was about 3.53 million (about 7.86% of the total population). Generally, the results of this study could contribute positively to the timely assessment of the impact of the conflict and the implementation of humanitarian relief. [ABSTRACT FROM AUTHOR]

• It proposes a new homotopy approach to conduct the stochastic static model updating with large measurement errors. • A stochastic model updating equation is solved by combining the homotopy analysis method with a regularization technique. • The proposed method has a higher accuracy than low-order perturbation methods in cases with large measurement errors. • It requires very less computational efforts than conventional Bayesian methods. Large measurement errors are a major challenge in structural model updating. Based on the concept of homotopy, a new stochastic static model updating method is proposed to update structural models using uncertain static data with large measurement errors. First, considering the uncertainty of the static measurement, a stochastic model updating equation for element update factors is set up. To solve the stochastic model updating equation, a series of homotopy deformation equations are presented to establish the relationship between the deterministic update factors and the random update factors. Furthermore, the homotopy series expansions of the random update factors can be determined by solving the homotopy deformation equations. Since the measured degrees of freedom of updated structures are usually limited or unavailable, a static condensation technique is used for stochastic model updating. To address the ill-posed problems caused by incomplete measurement information and static measurement errors, the Tikhonov regularization method is used in the process of solving the homotopy deformation equations. Three numerical examples are given to demonstrate the validity of the proposed stochastic model updating method. The numerical results clearly show that unlike the second-order perturbation method, this new method can produce better accuracy in cases with large measurement errors. Compared with the Bayesian method with the Delayed Rejection Adaptive Metropolis sampling technique and even a fast Bayesian method, the proposed method utilizes much less computational time and provides an equivalent accuracy. Finally, static loading experiments on a two-span continuous concrete beam are implemented to validate the proposed model updating method. [ABSTRACT FROM AUTHOR]

Based on the transmission characteristics of networks and the systematization of technical risks in national major science and technology projects, the risk transmission mechanism of national major science and technology projects is deeply discussed herein. Firstly, the system of systems (SoS) engineering process model of national major science and technology projects is constructed, including two levels and three stages. Secondly, the hierarchical structure of national major science and technology projects is analyzed, and the risks are divided into different levels, such as SoS, system, subsystem, equipment, module, and components. Finally, we describe the risk transfer mechanism using the forest-fire model and outline a risk control strategy. The results show that the findings are helpful for recognizing the essence and transmission mechanism of technical risks of national major science and technology projects and for reducing the risk from the source. The research results can be applied to project management in the transportation field. [ABSTRACT FROM AUTHOR]

Urban waterlogging seriously threatens urban sustainable development and human life. The effects of various landscape elements on urban waterlogging have been extensively documented. However, less attention is deserved to the spatial heterogeneity effects of urban landscape elements on urban waterlogging. The spatial pattern of dominant driving forces and how the interactive effects of landscape elements affect urban waterlogging with different environmental configurations have not been well examined. These shortcomings have hindered the development of target-specific urban waterlogging mitigation strategies. To shed some light on this topic, an innovative method that integrated the boruta algorithm, cubist regression tree, and geographical detector model is presented to investigate the spatial heterogeneous mechanisms of urban waterlogging and map the waterlogging dominant driving forces with different local conditions. The results show that the boruta algorithm proposed in this study introduces shadow variables as a benchmark, thus enabling an unbiased and stable selection of representative waterlogging driving factors based on local conditions. By comparing with two other commonly used regression methods (global regression model, spatial lag model), the cubist regression tree divides the urban waterlogging space into multiple homogeneous subgroups to quantify the spatial non-stationarity relationship and spatially explicit the local driving forces in Guangzhou and Shenzhen, with the adjusted R 2 of 0.79 and 0.88. The geographical detector model denotes that waterlogging magnitude within different subgroups is affected by different dominant factors. Even for the same dominant factor, its contribution to waterlogging varies considerably in different subgroups. The independent contribution of the dominant factor in Guangzhou was 23.28%–57.82%, while in Shenzhen it ranged from 25.95% to 53.59%. In addition to the dominant factor of each subgroup, it is noteworthy that in some subgroups the combined effect of different representative factors on waterlogging is significantly stronger than the contribution of their dominant factors. In view of this, urban planners and local authorities need to comprehensively consider the interaction effect between representative factors, which develop urban waterlogging mitigation strategies that integrate multiple factors. The results from this study extend our scientific understanding of the site-specific mechanism of urban waterlogging, which facilitates the implementation of more targeted and effective mitigation strategies, rather than a "one-size-fits-all" policy. [Display omitted] • Objectively select waterlogging representative factors based on environmental configurations. • The cubist regression tree spatially reveals waterlogging local driving forces. • Waterlogging driving forces vary with local site conditions. • Even for the same factor, its impact on waterlogging varies considerably in different locations. • The site-specific mechanism facilitates the implementation of more targeted mitigation strategies. [ABSTRACT FROM AUTHOR]

Urban forests are fundamental components of localized surface energy budgets. Understanding the factors controlling urban forest surface temperatures (UFSTs) should be helpful in mitigating the negative effects of urbanization on urban energy budgets. This study aimed to identify the factors controlling the spatial-temporal pattern of UFSTs by utilizing a variety of data layers and spatial statistical analysis methods. Our results showed that UFST values become more spatially heterogeneous as urbanization progresses. Elevation and degree of slope were the main factors explaining the increase in spatial heterogeneity. Human activities were also significantly related to variations in UFST. Interactions between human activities and almost all environmental factors were related to higher UFST values. Therefore, human activity directly impacts on the spatial heterogeneity of UFST and indirectly affects variations in landscape patterns. Human activities compatible with ecologically sustainable development should be considered for mitigating the deterioration of urban thermal environments. [ABSTRACT FROM AUTHOR]

Background: Human leukocyte antigen-E (HLA-E) has been extensively investigated in various human cancers including glioma. However, the clinical significance of HLA-E expression in glioma patients has not been elucidated. The current study aimed to investigate the association of HLA-E expression with clinicopathological features and survival in patients with diffuse glioma.Methods: A total of 261 glioma patients were enrolled, subsequently, mRNA microarray analysis was conducted to identify the relationship of HLA-E with clinicopathological features and patient survival.Results: HLA-E was significantly overexpressed in high-grade gliomas compared to low-grade gliomas (LGGs). Moreover, HLA-E expression was significantly higher in diffuse astrocytomas than oligodendrogliomas (p = 0.032, t-test). Kaplan-Meier analysis showed that progression-free survival (PFS) and overall survival (OS) were significantly better in LGG patients with low HLA-E expression (p = 0.018 for PFS and p = 0.020 for OS, Log-rank test). Furthermore, HLA-E expression was identified to be an independent prognostic factor by Cox analysis (p = 0.020 for PFS and p = 0.024 for OS).Conclusions: This is the first study which identified the clinical significance of HLA-E in diffuse glioma. HLA-E expression was correlated with more aggressive tumor grade and histological type and was identified as an independent prognostic biomarker in LGG patients. [ABSTRACT FROM AUTHOR]

Many studies have explored the complex mechanisms of urban heat islands by examining the relationship between land surface temperature (LST) and greenspace spatial patterns. Few, however, have explored the relative contributions of greenspace spatial composition and configuration to LST using comparisons between cities. In this study, the authors sought to identify the relative contributions of greenspace spatial composition and configuration to LST and the stability mechanisms linking LST to greenspace at multiple locations. We looked at four highly-urbanized Chinese cities in a comparative study. Landsat 5/8 images for summer and winter were used to estimate LST and greenspace data were extracted from 0.5-m resolution imagery. The complex relationship between LST and greenspace spatial patterns was quantified and compared using a novel method that combines stepwise regression with hierarchical partitioning analysis concerning statistical size variations. The results indicated that greenspace spatial composition and configuration both consistently affect LST. However, the magnitude and significance of these relationships were very different. The combined contributions of the greenspace landscape metrics played a more critical role in determining LST than their independent contributions, especially in summer. However, the relative importance of spatial composition and spatial configuration was largely dependent on specific variables such as season or selected statistical grid size. The urban heat island (UHI) effect can be reduced not only by increasing the amount of greenspace, but also by optimizing greenspace spatial configuration; the latter is more effective than the former. Although scale dependence continued to be evident in our study, we were not able to confirm a universal "best" scale for analysis. This study extended our understanding of the complex mechanisms of UHI in the region with respect to seasonal and scale factors, and has provided valuable information to support UHI adaptation strategy development by urban planners. Unlabelled Image • Spatial pattern of heat and cool clusters shifted greatly with seasons. • Whether greenspace spatial composition or configuration is more important significantly depends on specific variables. • Joint contributions of landscape metrics of greenspace had stronger effects on LST variations. • "Best" scale in determining LST-greenspace relationship varied among cities. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of inter-city connectivity is important for regional planning. However, most studies adopted only one single data source for measurements, which is incomplete since each source has its own limitations. There are biases and uncertainties in the connectivity results when using different data sources. To address this problem, our study proposed a novel method that could combine the advantages of multi-source data. First, we measured inter-city connectivities using several datasets individually, and then analyzed each city's node strength based on the connectivities. Next, the performance of each dataset was validated according to several correlation analyses between the node strength and various socio-economic metrics. Based on these validations, we used the genetic algorithm to search for the optimal weights for combination. Only those datasets with higher weights were retained for further calculation. The final connectivity result is more reasonable than any single result according to the validation. For the first time, this study compares different data sources related to inter-city connectivity, and combines their advantages based on selective weighted combination. The results are expected to provide strong support for large-scale regional planning. In addition, the proposed method could be further applied to other large areas for analyzing inter-city connectivities. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) phenomenon is among the most evident features of human impact on the Earth's system. This phenomenon has been widely observed and documented in many cities around the world. UHI-related publications have increased rapidly over the last three decades. However, because of a refined methodology and widening scope, a holistic understanding of research patterns and issues related to UHI research is lacking. Although others have summarized developments in UHI studies, these publications have focused on describing the current state of research rather than uncovering research trends and prospects. In the present study, we examined the evolution of UHI-related research from 1990 to 2017 and applied a scientometrics approach to identify research trends. The characteristics of publication outputs, key scientific disciplines, and cooperation between countries and institutions were determined by a citation analysis. We also discuss research trends, including future directions, approaches, and expected data. We identified two potential directions for UHI research through the results of key co-word clustering and discriminant analyses: negative impacts of UHI on public health and strategies to mitigate and adapt to UHI effects. We provide a broad review of the development of UHI research that may inspire future studies on the UHI phenomenon by new researchers in this field. [ABSTRACT FROM AUTHOR]

Interleukin (IL)-6 has been implicated in the invasion and metastasis of hepatocellular carcinoma (HCC). However, the molecular events that mediate this process are poorly understood. Here, we showed that IL-6 promoted the epithelial-mesenchymal transition (EMT) in HCC cell lines, and upregulated a disintegrin and metalloprotease 9 (ADAM9) expression by activating the JNK signaling pathway. ADAM9 was upregulated in human HCCs which promoted HCC cell invasion and the EMT by interacting with NADPH oxidase 1 and inducing reactive oxygen species generation. Knockdown of ADAM9 inhibited the IL-6-induced EMT. Additionally, ADAM9 expression was positively correlated with IL-6 and Snail expression in human HCC specimens. Taken together, our results showed that ADAM9 is an important mediator of IL-6-induced HCC cell migration and invasion, and may provide a novel therapeutic target for HCC management. [ABSTRACT FROM AUTHOR]

• A novel homotopy based stochastic FE model updating method is proposed to deal with the correlation of static measurement data firstly. • The Karhunen–Loeve expansion is used to express the correlated measurement displacements by independent random variables. • It is very significant to check the consistence of the correlation coefficients of the responses of updated model with those of the measured data. • The proposed method can effectively update structural model in the case of correlated measurement errors. This paper focuses on studying the impaction of the correlation between the measurement data on structural model updating. A new homotopy based stochastic finite element model updating frame is constructed to cope with the correlated static measurement data. To judge whether considering the correlation of the measurement data, the sensitivity analysis of structural responses about structural parameters is implemented firstly. Then the discrete Karhunen–Loeve expansion is utilized to transform the correlated measurement data into a linear combination of multiple independent random variables. Furthermore, a novel stochastic model updating equation about the correlated static measurement data is set up, and is solved by the homotopy stochastic finite element method. It is significant to check the consistence of the correlation coefficients of the responses of the updated model with those of the measured data when the correlation actually exists. In this case, the proposed approach can effectively update the structural model. [ABSTRACT FROM AUTHOR]

• Construct a wetland damage index (WDI) to characterize the destruction and risk. • The WDI comprises wetland area variation, human pressure and RSEI. • Where WDI is high, the probability of subsequent wetland loss is also high. • The WDI is useful for measuring wetlands that are not protected. Wetlands are formed by the interaction between terrestrial and aquatic systems and are of substantial importance in the study of global environmental change. However, the global wetland area is rapidly declining, and wetlands are experiencing environmental stress caused by human activities. Existing methods neither consider thought-out human pressure factors nor depict the spatial variation in wetland risks in detail. Therefore, constructing a wetland damage index (WDI) that characterizes the destruction and risk of wetlands is necessary. In this study, we constructed a WDI based on wetland area variation, human pressure, and a remote sensing-based ecological index and used it to analyze the wetland damage conditions of Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The results demonstrated the following: (1) The wetland area in the GBA decreased by 12.13% between 2000 and 2020. Wetlands are often found on the west bank of the Pearl River, whereas inner-city wetlands are scarce. Ponds and rivers on the west bank are also hotspots of wetland loss. Additionally, many wetlands in peripheral cities of the GBA have been restored; (2) the WDI is indicative of wetland evolution. In the case of small grid units (2.5–10.0 km), the correlation between the WDI and the landscape indices decreased, showing the former's ability to account for human pressures and environmental ecology conditions that landscape indices fail to consider. The WDI can be used to distinguish the extent of damage to various types of wetlands. In general, the probability of subsequent wetland loss is greater in places with high WDI than in places with low WDI, and vice versa; and (3) the WDI can adapt to various data and different research scales. However, the policies of local authorities must be considered in practical applications because these factors can directly affect the disappearance or survival of wetlands. The WDI is an indicator of wetland destruction and risk for most wetlands that are neither designated as nature reserves nor benefit from environmental protection measures. [ABSTRACT FROM AUTHOR]

• The effect of tree coverage and microtopography on air temperatures was quantified. • Cooling capacity of the green space was positively correlated with total leaf area. • Microtopographic modification can enhance the cooling effect on adjacent open space. • Slope angle of microtopography control the extending cooling rate from the green space. The tree coverage of a green space strongly influences its cooling effects; however, knowledge about how the cooling capacity extends beyond a given green space remains limited, along with how modifications to micro-topography affect local thermal environments. Here, we aimed to clarify the cooling effects within and beyond a green space by systematically evaluating differing tree coverage and micro-topographic conditions. Specifically, idealized scenarios were designed and simulated using the micro-climate model ENVI-met. We found that both canopy size and tree number clearly influenced thermal environment conditions within and outside a green space during the daytime. The cooling capacity of the green space during the daytime was linearly correlated with the total leaf area of trees. We also found that modifications to micro-topography had stronger cooling effects on both the green space and adjacent open space in contrast to flat terrain scenarios. Increasing the connectivity of impervious spaces and green areas, along with appropriate micro-topographic modifications, could prevent surrounding impervious surfaces from becoming micro-scale heat islands during the daytime; thus, ameliorating heat stress conditions. The results of this research provide a baseline for climate-adaptive designs and planning of thermally comfortable urban landscapes in the future. [ABSTRACT FROM AUTHOR]

Background: Human leukocyte antigen B27 (HLA-B27)-associated uveitis is the most common reason for non-infectious uveitis. This purpose of the research was to study the expression and significance of T lymphocyte subsets and CD CD T regulatory (Treg) cells in peripheral blood of patients with Human leukocyte antigen B27-positive acute anterior uveitis (HLA-B27-positive AAU). Methods: The concentrations of Th1, Th2, Th17, CD CD, and CDCDFOXP3 Treg cells in peripheral blood were tested by flow cytometry. C-reactive protein (CRP) in peripheral blood was detected by immunoturbidimetry (ITM). Spearman's rank correlation was used to analyze the relationships between the concentration of Th1, Th2, Th17, CD CD, and CDCDFOXP3 Treg cells in peripheral blood and disease activity score and CRP content. Results: The ratio of both γ [interferon (IFN)-γ] CD4Th1 cells and CD4IL-17Th17 cells in peripheral blood of patients with HLA-B27-positive AAU ( P = 0.041) was higher than that of the control group ( P = 0.002). The concentration of CD4CD25FOXP3 T cells in peripheral blood of patients with AAU was lower than that of the control group ( P = 0.026). The concentration of Th1 cells in peripheral blood of the patients had no correlation with disease activity score ( P = 0.50) or CRP content ( P = 0.383). This was also true of the concentration of Th2 cells (Disease activity score: R = 0.068, P = 0.817; CRP content: R = 0.439, P = 0.116). Th17 cell concentration positively correlated with disease activity score ( R = 0.805, P = 0.001). The concentration of CD4CD25 T cells showed no correlation with disease activity score ( R =−0.209, P = 0.472) or CRP content ( R =−0.169, P = 0.563), whereas the concentration of CD4CD25FOXP3 T cells negatively correlated with disease activity score but did not correlate with CRP ( R =−0.248, P = 0.392). Conclusions: The peripheral blood of patients with HLA-B27-positive AAU showed a higher expression of interferon-γ and interleukin-17 cells in CD4T cells, whereas CD4CD25FOXP3 T cells displayed a lower expression of the cytokines. The balance between Th17 cells and CD4 + CD25 + FOXP3+ T cells may contribute to the activity of HLA-B27-positive AAU. [ABSTRACT FROM AUTHOR]

We studied the feasibility of evaluating the stages of liver fibrosis with tissue Doppler imaging (TDI) and tissue strain imaging (TSI) for patients with chronic hepatitis B virus infection. One hundred ten patients were divided into two groups: normal adult group (n = 38) and chronic liver disease group (n = 72, patients infected with HBVs). The chronic liver disease group was divided into three subgroups on the basis of the Scheuer scoring system and clinical evidence: mild fibrosis (S0 and S1, n = 11), moderate fibrosis (S2 and S3, n = 27) and cirrhosis (S4 and clinically typical cirrhosis, n = 34) groups. TDI was performed for a chosen oblique section. Four regions of interest (ROIs), A–D, were chosen in the hepatic parenchyma based on the direction of propagation from the heart to the liver. Strain rate curves were obtained on the basis of TDI and TSI findings. Strain peak rates (SPRs) of all ROIs and the differences in times to SPRs for the four ROIs (T A-B, T B-C and T C-D) in the hepatic parenchyma were measured with TDI and TSI. Strain rate curves were analyzed for each ROI. The strain rate curves for the normal adult group were synchronous, whereas those for the chronic liver disease group were asynchronous. SPRs of the ROIs gradually decreased with the progression of liver fibrosis. The SPRs of ROI B significantly correlated with chronic liver disease severity (r = 0.991, p < 0.05). Areas under the curve (AUCs) of the ROI A and ROI B SPRs at the moderate fibrosis and cirrhosis stages were 0.86 ± 0.06, 0.81 ± 0.56 and 0.90 ± 0.65, 0.92 ± 0.04, respectively. The AUC of the SPRs of ROIs A and B correlated better than the platelet/age/phosphatase/α-fetoprotein/aspartate aminotransferase (PAPAS) index for advanced fibrosis. The differences in time to SPRs among the peaks of the four ROIs (T A-B, T B-C and T C-D) gradually increased with the progression of liver fibrosis. TDI and TSI with quantitative measurements using tissue Doppler analysis software (TDIQ, GE Medical Systems, Horten, Norway) provided reliable information for evaluating non-invasive liver fibrosis in patients with chronic hepatitis B. [ABSTRACT FROM AUTHOR]

Most endolysins of dsDNA phages are exported by a holin-dependent mechanism, while in some cases endolysins are exported via a holin-independent mechanism. However, it is still unclear whether the same endolysins can be exported by both holin-dependent and holin-independent mechanisms. This study investigated the lysis system of OP2-like phage X2 infecting Xanthomonas oryzae pv. oryzae, causing devastating bacterial leaf blight disease in rice. Based on bioinformatics and protein biochemistry methods, we show that phage X2 employs the classic "holin-endolysin" lysis system. The endolysin acts on the cell envelope and exhibits antibacterial effects in vitro, while the holin facilitates the release of the protein into the periplasm. We also characterized the role of the transmembrane domain (TMD) in the translocation of the endolysin across the inner membrane. We found that the TMD facilitated the translocation of the endolysin via the Sec secretion system. The holin increases the efficiency of protein release, leading to faster and more efficient lysis. Interestingly, in E. coli, the expression of either holin or endolysin with TMDs resulted in the formation of long rod shaped cells. We conclude that the TMD of X2-Lys plays a dual role: One is the transmembrane transport while the other is the inhibition of cell division, resulting in larger cells and thus in a higher number of released viruses per cell. [ABSTRACT FROM AUTHOR]

Road density (i.e., km/km2) is a useful broad index of the road network in a landscape and has been linked to several ecological effects of roads. However, previous studies have shown that road density, estimated by grid computing, has weak correlation with landscape fragmentation. In this article, we propose a new measure of road density, namely, kernel density estimation function (KDE) and quantify the relation between road density and landscape fragmentation. The results show that road density estimated by KDE (km/km2) elucidates the spatial pattern of the road network in the region. Areas with higher road density are dominated by a larger proportion of built-up landscape and less possession of forest and vice versa. Road networks segregated the landscape into smaller pieces and a greater number of patches. Furthermore, Spearman rank correlation model indicates that road density (km/km2) is positively related to landscape fragmentation. Our results suggest that road density, estimated by KDE, may be a better correlate with effects of the road on landscape fragmentation. Through KDE, the regional spatial pattern of road density and the prediction of the impact of the road on landscape fragmentation could be effectively acquired. [ABSTRACT FROM AUTHOR]

[Display omitted] • The potential synergistic effects of climate and land use change on 191 Chinese endemic Rhododendron species were studied. • A nearly equal number of species was projected to lose or gain their suitable habitat. • Low-elevation species are more vulnerable to climate and land use change than high-elevation species. • The species at lower altitudes need more conservation attention under climate and land use change. • Endemic Rhododendrons can be good indicators for the assessment of biodiversity conservation. The combination of climate change and land use change may have profound effects on terrestrial biodiversity in more significant ways than either has separately. However, most studies focus largely on the climate change impacts, which hampers our ability to develop appropriate conservation strategies in a dramatically changing world. Here, we predict the distributions of 191 Chinese endemic Rhododendron species under future climate and land use change, combining two dispersal constraint scenarios by using a species distribution model. We then assess the vulnerability and extinction risk of these species and identify areas at risk of highest species loss. We find that 52% of the species are predicted to expand and shift their geographic ranges, typically to the northwest and north. The remaining 48% of species are predicted to contract in geographic ranges under the 'perfect-dispersal' scenario. And only 7% of Rhododendron are predicted to keep 'still', while the rest of species shrank with varying degree under the 'no-dispersal' scenario. Species lost particularly at lower elevations, and we also identify four regions at particularly high risk from the impacts of climate and land use change, namely the parallel ridge-and-valley areas of eastern Sichuan, southeastern Tibet, western and eastern Yunnan, southern Shaanxi, plus scattered areas in Guangdong, Hainan and Taiwan. We conclude that Chinese endemic Rhododendron species at lower elevations are highly vulnerable to climate and land use change, facing an elevated risk of extinction under varying scenarios. These species therefore call for more attention and protection. We highlight the critical role of endemic Rhododendron species as good indicators for measuring, evaluating and understanding the effectiveness of our biodiversity conservation efforts. Our work provides insight into the status, trends and threats regarding endemic Rhododendron species, identifying risks and prioritizing conservation in a rapidly changing world. [ABSTRACT FROM AUTHOR]

Urban green infrastructures (UGI) can effectively reduce surface runoff, thereby alleviating the pressure of urban waterlogging. Due to the shortage of land resources in metropolitan areas, it is necessary to understand how to utilize the limited UGI area to maximize the waterlogging mitigation function. Less attention, however, has been paid to investigating the threshold level of waterlogging mitigation capacity. Additionally, various studies mainly focused on the individual effects of UGI factors on waterlogging but neglected the interactive effects between these factors. To overcome this limitation, two waterlogging high-risk coastal cities—Guangzhou and Shenzhen, are selected to examine the effectiveness and stability of UGI in alleviating urban waterlogging. The results indicate that the impact of green infrastructure on urban waterlogging largely depends on its area and biophysical parameter. Healthier or denser vegetation (superior ecological environment) can more effectively intercept and store rainwater runoff. This suggests that while increasing the area of UGI, more attention should be paid to the biophysical parameter of vegetation. Hence, the mitigation effect of green infrastructure would be improved from the "size" and "health". The interaction of composition and spatial configuration greatly enhances their individual effects on waterlogging. This result underscores the importance of the interactive enhancement effect between UGI composition and spatial configuration. Therefore, it is particularly important to optimize the UGI composition and spatial pattern under limited land resource conditions. Lastly, the effect of green infrastructure on waterlogging presents a threshold phenomenon. The excessive area proportions of UGI within the watershed unit or an oversized UGI patch may lead to a waste of its mitigation effect. Therefore, the area proportion of UGI and its mitigation effect should be considered comprehensively when planning UGI. It is recommended to control the proportion of green infrastructure at the watershed scale (24.4% and 72.1% for Guangzhou and Shenzhen) as well as the area of green infrastructure patches (1.9 ha and 2.8 ha for Guangzhou and Shenzhen) within the threshold level to maximize its mitigation effect. Given the growing concerns of global warming and continued rapid urbanization, these findings provide practical urban waterlogging prevention strategies toward practical implementations. [ABSTRACT FROM AUTHOR]

This paper proposes a new damage identification approach for beam structures with stochastic parameters based on uncertain static measurement data. This new approach considers not only the static measurement errors, but also the modelling error of the initial beam structures as random quantities, and can also address static damage identification problems with relatively large uncertainties. First, the stochastic damage identification equations with respect to the damage indexes were established. On this basis, a new homotopy analysis algorithm was used to solve the stochastic damage identification equations. During the process of solution, a static condensation technique and a L1 regularization method were employed to address the limited measurement data and ill-posed problems, respectively. Furthermore, the definition of damage probability index is presented to evaluate the possibility of existing damages. The results of two numerical examples show that the accuracy and efficiency of the proposed damage identification approach are good. In comparison to the first-order perturbation method, the proposed method can ensure better accuracy in damage identification with relatively large measurement errors and modelling error. Finally, according to the static tests of a simply supported concrete beam, the proposed method successfully identified the damage of the beam. [ABSTRACT FROM AUTHOR]

Urban waterlogging is a hydrological cycle problem that seriously affects people's life and property. Characterizing waterlogging variation and explicit its driving factors are conducive to prevent the damage of such disasters. Conventional methods, because of the high spatial heterogeneity and the non-stationary complex mechanism of urban waterlogging, are not able to fully capture the urban waterlogging spatial variation and identify the waterlogging susceptibility areas. A more robust method is recommended to quantify the variation trend of urban waterlogging. Previous studies have simulated the waterlogging variation in relatively small areas. However, the relationship between variables is often ignored, which cannot comprehensively reveal the dominant drivers affecting urban waterlogging. Therefore, a novel approach is proposed that combined stepwise cluster analysis model (SCAM) and hierarchical partitioning analysis (HPA) within a general framework and verifies the applicability through logistic regression, artificial neural network, and support vector machine. According to the dominant driving factors, different simulation scenarios are established to analyze waterlogging density variation. Results found that the SCAM provides accurate and detailed simulated results both in urban centers where waterlogging frequently occurs and urban fringe with few waterlogging events, which shows an excellent performance with a high classification accuracy and generalization capability. HPA detected that the impervious surface abundance (28.07%), vegetation abundance (20.80%), and cumulate precipitation (16.25%) are the dominant drivers of waterlogging. This result suggests that priority should be given to controlling these three factors to mitigate the risk of waterlogging. It is interesting to note that under different urbanization and rainfall scenarios, the urban waterlogging susceptibility has a considerable variation. The watershed spatial location and watershed characteristics are relevant aspects to be considered in identifying and assessing waterlogging susceptibility, which provides original insights that urban waterlogging mitigation strategies should be developed according to different local conditions and future scenarios. Unlabelled Image • The SCAM-HPA is applied to explicit urban waterlogging variation and its driving factors. • The SCAM shows high classification accuracy and generalization capability. • The impervious surface, vegetation coverage, and precipitation are the dominant drivers. • Under different scenarios, the waterlogging susceptibility has a great variation. • Formulate waterlogging prevention strategies according to watershed conditions. [ABSTRACT FROM AUTHOR]

Burkholderia glumae and B. gladioli are seed-borne rice pathogens that cause bacterial panicle blight (BPB) disease, resulting in huge rice yield losses worldwide. However, the excessive use of chemical pesticides in agriculture has led to an increase in environmental toxicity. Microbe-mediated nanoparticles (NPs) have recently gained significant attention owing to their promising application in plant disease control. In the current study, we biologically synthesize zinc oxide nanoparticles (ZnONPs) from a native Bacillus cereus RNT6 strain, which was taxonomically identified using 16S rRNA gene analysis. The biosynthesis of ZnONPs in the reaction mixture was confirmed by using UV–Vis spectroscopy. Moreover, XRD, FTIR, SEM-EDS, and TEM analysis revealed the functional groups, crystalline nature, and spherical shape of ZnONPs with sizes ranging from 21 to 35 nm, respectively. Biogenic ZnONPs showed significant antibacterial activity at 50 µg mL−1 against B. glumae and B. gladioli with a 2.83 cm and 2.18 cm zone of inhibition, respectively, while cell numbers (measured by OD600) of the two pathogens in broth culture were reduced by 71.2% and 68.1%, respectively. The ultrastructure studies revealed the morphological damage in ZnONPs-treated B. glumae and B. gladioli cells as compared to the corresponding control. The results of this study revealed that ZnONPs could be considered as promising nanopesticides to control BPB disease in rice. [ABSTRACT FROM AUTHOR]

The DMSP/OLS Nighttime light (NTL) data directly reflect the spatial distribution and light intensity of artificial lighting from the Earth's surface at night, and has become an emerging instrument for urbanization research, including in the monitoring of urban expansion, assessment of socio-economic vitality, and estimation of energy consumption and population. However, due to the imperfect sensor design of DMSP/OLS, the dynamic range of the digital number (DN) of NTL is limited (0, 63), leading to a significant saturation problem when describing the actual light intensity, especially in dense urban areas with high light intensity. This saturation problem masks spatial differences in light intensity and weakens the reliability of DMSP/OLS NTL data. Therefore, this study proposes a novel desaturation indicator that combines NDBI and POI, the Building and POI Density-Adjusted Nighttime Light Index (BPANTLI), to regulate the DMSP/OLS NTL saturation problem based on the spatial characteristics of urban structures and human activity intensity. The proposed method is applied to three urban agglomerations with the most severe light saturation issues in China. The geographical detector model is firstly utilized to quantify the effectiveness of NDBI and POI in reflecting the difference in light intensity distribution from the NTL potential saturation region (NTL DN value (53, 63)) and NTL unsaturation region (NTL DN value (0, 52)), so as to clarify the feasibility of developing the BPANTLI. The applicability of BPANTLI is validated through three aspects—comparison of the desaturation capacity and the performance of delineating light intensity; verification of the consistency of BPANTLI with radiometric calibration nighttime light product (RCNTL) and NPP/VIIRS data; and assessing the accuracy of the BPANTLI in estimating socio-economic parameters (GDP, electricity consumption, population density). The results indicate that the BPANTLI possesses superior capability in regulating the NTL saturation problem, achieving good performance in distinguishing inner-urban structures. The regulated results reveal a remarkably improved correspondence with the RCNTL and NPP/VIIRS data, providing a more realistic picture of the light intensity distribution. It is worth noting that, given the advantages of NDBI and POI vector data in spatial resolution, the BPANTLI established in this study can overcome the limitation of the spatial resolution of DMSP/OLS nighttime lighting data and achieve dynamic transformation of the spatial resolution. The higher spatial resolution desaturation results allow for a better characterization of the light intensity distribution. Moreover, the BPANTLI-regulated light intensity significantly improves the accuracy of estimating electricity consumption, GDP, and population density, which provides a valuable reference for urban socio-economic activity assessment. Thus, the BPANTLI proposed in this study can be considered as a reasonable desaturation method with a high application value. [ABSTRACT FROM AUTHOR]

• A novel non-linear numerical model for thin-walled members is presented. • Four classes of H-section members are selected to study the hysteretic behaviour. • The comparison of test results and those of the proposed model is accomplished. • The deformation mode, buckling effects, and material nonlinearity are considered. Based on Gonçalves's geometrically exact beam theory considering cross-section deformation, the warping and distortional deformation of thin-walled members are described in this paper by means of a combination of section deformation modes. By integrating with the J2 elastic‒plasticity theory for the steel, a numerical model is established for the hysteretic behaviour of thin-walled steel members. Four classes of H-section members are selected on account of the design codes, and the influence of section warping and distortion deformation modes on the calculation of the hysteretic behaviour of components with different section types is analysed. The crucial aspect lies in the bending hysteresis behaviour around the strong and weak axes of the cross-section for H-beam steel members subjected to typical thin-walled members with relatively large widths and thicknesses. Test results on the hysteretic behaviour of H-section steel members are compared with those calculated from the proposed model in terms of the hysteric behaviour of components, strength degradation, energy-dissipating capacity, etc. These findings validate the correctness and feasibility of the established non-linear analysis model for thin-walled members. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the safety and efficacy of intravitreal injections of 0.5 mg conbercept in patients with choroidal neovascularization secondary to pathological myopia (pmCNV). Methods: The 177 pmCNV patients were randomly assigned in a 3:1 ratio to receive conbercept or sham injection, respectively. The conbercept group receive conbercept intravitreal injections administered on a pro re nata (PRN) basis after 3 monthly loading doses. The sham group received three consecutive monthly sham injections and then one conbercept injection followed by PRN conbercept intravitreal injections. Results: At month 3, the mean BCVA for the two groups were improved by 12.0 letters (conbercept group, from 54.05 letters to 66.05 letters) and 0.6 letters (sham group, from 49.77 letters to 50.33 letters), respectively (p < 0.001). The mean central retinal thickness (CRT) at month 3 in the two groups decreased 62.0 μm (conbercept group, from 348.90 μm to 286.18 μm) and 4.4 μm (sham group, from 347.86 μm to 343.47 μm) (p < 0.001). At month 9, the mean BCVA improved by 13.3 letters in the conbercept group and 11.3 letters in the sham group. The mean CRT decreased 73.6 μm in the conbercept group and 55.9 μm in the sham group (p < 0.001). The most common ocular adverse events were associated with intravitreal injections, such as conjunctival haemorrhage and increased intraocular pressure. Conclusion: Intravitreal injections of 0.5 mg conbercept provided improvement in visual and anatomical outcomes in pmCNV patients with low rates of ocular and nonocular safety events. [ABSTRACT FROM AUTHOR]

Background and Aim Methods Results Conclusion False positives (FPs) pose a significant challenge in the application of artificial intelligence (AI) for polyp detection during colonoscopy. The study aimed to quantitatively evaluate the impact of computer‐aided polyp detection (CADe) systems' FPs on endoscopists.The model's FPs were categorized into four gradients: 0–5, 5–10, 10–15, and 15–20 FPs per minute (FPPM). Fifty‐six colonoscopy videos were collected for a crossover study involving 10 endoscopists. Polyp missed rate (PMR) was set as primary outcome. Subsequently, to further verify the impact of FPPM on the assistance capability of AI in clinical environments, a secondary analysis was conducted on a prospective randomized controlled trial (RCT) from Renmin Hospital of Wuhan University in China from July 1 to October 15, 2020, with the adenoma detection rate (ADR) as primary outcome.Compared with routine group, CADe reduced PMR when FPPM was less than 5. However, with the continuous increase of FPPM, the beneficial effect of CADe gradually weakens. For secondary analysis of RCT, a total of 956 patients were enrolled. In AI‐assisted group, ADR is higher when FPPM ≤ 5 compared with FPPM > 5 (CADe group: 27.78% vs 11.90%; P = 0.014; odds ratio [OR], 0.351; 95% confidence interval [CI], 0.152–0.812; COMBO group: 38.40% vs 23.46%, P = 0.029; OR, 0.427; 95% CI, 0.199–0.916). After AI intervention, ADR increased when FPPM ≤ 5 (27.78% vs 14.76%; P = 0.001; OR, 0.399; 95% CI, 0.231–0.690), but no statistically significant difference was found when FPPM > 5 (11.90% vs 14.76%, P = 0.788; OR, 1.111; 95% CI, 0.514–2.403).The level of FPs of CADe does affect its effectiveness as an aid to endoscopists, with its best effect when FPPM is less than 5. [ABSTRACT FROM AUTHOR]

Rationale: Hypercholesterolemia is an important risk factor for cardiovascular diseases and death. This study performed pseudo‐targeted lipidomics to identify differentially expressed plasma lipids in hypercholesterolemia, to provide a scientific basis for the diagnosis and pathogenesis of hypercholesterolemia. Methods: Pseudo‐targeted lipidomic analyses of plasma lipids from 20 patients with hypercholesterolemia and 20 normal control subjects were performed using liquid chromatography–mass spectrometry. Differentially expressed lipids were identified by principal component analysis and orthogonal partial least squares discriminant analysis. Receiver operating characteristic curves were used to identify differentially expressed lipids with high diagnostic value. The Kyoto Encyclopedia of Genes and Genomes pathway database was used to identify enriched metabolic pathways. Results: We identified 13 differentially expressed lipids in hypercholesterolemia using variable importance of projection > 1 and p < 0.05 as threshold parameters. The levels of eight sphingomyelins and cholesterol sulfate were higher and those of three triacylglycerols and lysophosphatidylcholine were reduced in hypercholesterolemia. Seven differentially expressed plasma lipids showed high diagnostic value for hypercholesterolemia. Functional enrichment analyses showed that pathways related to necroptosis, sphingolipid signaling, sphingolipid metabolism, and steroid hormone biosynthesis were enriched. Conclusions: This pseudo‐targeted lipidomics study demonstrated that multiple sphingomyelins and cholesterol sulfate were differentially expressed in the plasma of patients with hypercholesterolemia. We also identified seven plasma lipids, including six sphingomyelins and cholesterol sulfate, with high diagnostic value. [ABSTRACT FROM AUTHOR]

This paper proposes a new stochastic model updating method based on the homotopy surrogate model (HSM) and Bayesian sampling. As a novel intrusive surrogate model, the HSM is established by the homotopy stochastic finite element (FE) method. Then combining the advanced delayed‐rejection adaptive Metropolis–Hastings sampling technology with HSM, the structural FE model can be updated by uncertain measurement modal data. The numerical results show that the updating effectiveness of the proposed method is better than that of the Bayesian methods with the non‐intrusive surrogate models, such as stochastic response surface model and Kriging model. Compared to the Bayesian method with the intrusive second‐order perturbation model, the updating results of the proposed method are more accurate, especially when the fluctuation of the uncertain measured data is large and the stiffness of the structure significantly changes. The model updating results of a cable‐stayed bridge show that the statistic modal properties of the updated bridge model have a very good agreement with the uncertain measurement modal data. [ABSTRACT FROM AUTHOR]

Background The choice of polypectomy device and surveillance intervals for colorectal polyps are primarily decided by polyp size. We developed a deep learning-based system (ENDOANGEL-CPS) to estimate colorectal polyp size in real time. Methods ENDOANGEL-CPS calculates polyp size by estimating the distance from the endoscope lens to the polyp using the parameters of the lens. The depth estimator network was developed on 7297 images from five virtually produced colon videos and tested on 730 images from seven virtual colon videos. The performance of the system was first evaluated in nine videos of a simulated colon with polyps attached, then tested in 157 real-world prospective videos from three hospitals, with the outcomes compared with that of nine endoscopists over 69 videos. Inappropriate surveillance recommendations caused by incorrect estimation of polyp size were also analyzed. Results The relative error of depth estimation was 11.3% (SD 6.0%) in successive virtual colon images. The concordance correlation coefficients (CCCs) between system estimation and ground truth were 0.89 and 0.93 in images of a simulated colon and multicenter videos of 157 polyps. The mean CCC of ENDOANGEL-CPS surpassed all endoscopists (0.89 vs. 0.41 [SD 0.29]; P <0.001). The relative accuracy of ENDOANGEL-CPS was significantly higher than that of endoscopists (89.9% vs. 54.7%; P <0.001). Regarding inappropriate surveillance recommendations, the system's error rate is also lower than that of endoscopists (1.5% vs. 16.6%; P <0.001). Conclusions ENDOANGEL-CPS could potentially improve the accuracy of colorectal polyp size measurements and size-based surveillance intervals. [ABSTRACT FROM AUTHOR]

As two main drivers of vegetation dynamics, climate variability and human activities greatly influence net primary productivity (NPP) variability by altering the hydrothermal conditions and biogeochemical cycles. Therefore, studying NPP variability and its drivers is crucial to understanding the patterns and mechanisms that sustain regional ecosystem structures and functions under ongoing climate variability and human activities. In this study, three indexes, namely the potential NPP (NPPp), actual NPP (NPPa), and human-induced NPP (NPPh), and their variability from 2000 to 2020 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) were estimated and analyzed. Six main scenarios were generated based on change trends in the three indexes over the past 21 years, and the different relative impacts of climate variability and human activities on NPPa variability were quantitatively analyzed and identified. The results showed that the NPPp, NPPa, and NPPh had heterogeneous spatial distributions, and the average NPPp and NPPa values over the whole study area increased at rates of 3.63 and 6.94 gC·m−2·yr−1 from 2000 to 2020, respectively, while the NPPh decreased at a rate of −4.43 gC·m−2·yr−1. Climate variability and the combined effects of climate variability and human activities were the major driving factors of the NPPa increases, accounting for more than 72% of the total pixels, while the combined effects of the two factors caused the NPPa values to increase by 32–54% of the area in all cities expect Macao and across all vegetation ecosystems. Human activities often led to decreases in NPPa over more than 16% of the total pixels, and were mainly concentrated in the central cities of the GBA. The results can provide a reference for understanding NPP changes and can offer a theoretical basis for implementing ecosystem restoration, ecological construction, and conservation practices in the GBA. [ABSTRACT FROM AUTHOR]

• Day/Night remote sensing scheme was used to monitor coastal zone eco-environment. • The feasibility of large-scale RSEI was explored based on medium-resolution imagery. • Reveals the ecological changes in coastal zone at different urbanization intensities. With the rapid development of urbanization and population migration, since the 20th century, the natural and eco-environment of coastal areas have been under tremendous pressure due to the strong interference of human response. To objectively evaluate the coastal eco-environment condition and explore the impact from the urbanization process, this paper, by integrating daytime remote sensing and nighttime remote sensing, carried out a quantitative assessment of the coastal zone of China in 2000–2019 based on Remote Sensing Ecological Index (RSEI) and Comprehensive Nighttime Light Index (CNLI) respectively. The results showed that: 1) the overall eco-environmental conditions in China's coastal zone have shown a trend of improvement, but regional differences still exist; 2) during the study period, the urbanization process of cities continued to advance, especially in seaside cities and prefecture-level cities in Jiangsu and Shandong, which were much higher than the average growth rate; 3) the Coupling Coordination Degree (CCD) between the urbanization and eco-environment in coastal cities is constantly increasing, but the main contribution of environmental improvement comes from non-urbanized areas, and the eco-environment pressure in urbanized areas is still not optimistic. As a large-scale, long-term series of eco-environment and urbanization process change analysis, this study can provide theoretical support for mesoscale development planning, eco-environment condition monitoring and environmental protection policies from decision-makers. [ABSTRACT FROM AUTHOR]

Aerosol optical depth (AOD) is a key parameter that reflects the characteristics of aerosols, and is of great help in predicting the concentration of pollutants in the atmosphere. At present, remote sensing inversion has become an important method for obtaining the AOD on a large scale. However, AOD data acquired by satellites are often missing, and this has gradually become a popular topic. In recent years, a large number of AOD recovery algorithms have been proposed. Many AOD recovery methods are not application-oriented. These methods focus mainly on to the accuracy of AOD recovery and neglect the AOD recovery ratio. As a result, the AOD recovery accuracy and recovery ratio cannot be balanced. To solve these problems, a two-step model (TWS) that combines multisource AOD data and AOD spatiotemporal relationships is proposed. We used the light gradient boosting (LightGBM) model under the framework of the gradient boosting machine (GBM) to fit the multisource AOD data to fill in the missing AOD between data sources. Spatial interpolation and spatiotemporal interpolation methods are limited by buffer factors. We recovered the missing AOD in a moving window. We used TWS to recover AOD from Terra Satellite's 2018 AOD product (MOD AOD). The results show that the MOD AOD, after a 3 × 3 moving window TWS recovery, was closely related to the AOD of the Aerosol Robotic Network (AERONET) (R = 0.87, RMSE = 0.23). In addition, the MOD AOD missing rate after a 3 × 3 window TWS recovery was greatly reduced (from 0.88 to 0.1). In addition, the spatial distribution characteristics of the monthly and annual averages of the recovered MOD AOD were consistent with the original MOD AOD. The results show that TWS is reliable. This study provides a new method for the restoration of MOD AOD, and is of great significance for studying the spatial distribution of atmospheric pollutants. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) seriously affects children's health. Recently, propionic acid (PA) has been reported to play a significant role in the formation of ASD. In this study, we investigated the community structure of PA-related bacteria in healthy and ASD children by isolation and culture, while a group of representative PA-related bacteria were identified and characterized based on colony morphological observation, physiological and biochemical tests, as well as living/dead cells staining analysis and 16S rRNA gene sequencing. The results showed that the number of PA-related bacteria in healthy children was >100-fold higher than that in ASD children, while compared to healthy children, greater diversity was found in PA-associated bacteria from ASD children. The sensitivity of the representative strains to PA was affected by bacterial species, PA concentration and incubation time. The decrease of pH value was found in PA-resistant Lactobacillus plantarum strain 6-1 but not in PA-sensitive Enterococcus lactis strain 4-1, while biofilm formation of both strains were unaffected by PA. Furthermore, PA inhibited the propagation of the two selected bacteria rather than killed them, while the greater inhibitory effect was observed on strain 4-1. Overall, the result is of great significance for revealing the role of PA-related bacteria in development of ASD. • ASD children caused a >100-fold reduction in number of PA-related bacteria. • Greater diversity was noted in PA-associated bacteria from ASD children. • Representative PA-related bacteria were isolated, identified and characterized. • PA inhibited the propagation of bacteria rather than killed them. • A PA-resistant strain was obtained in ASD children. [ABSTRACT FROM AUTHOR]

Urban waterlogging disasters are affected by environmental conditions and human activities. Previous studies had explored the effect of land-use type on waterlogging in relatively small watersheds. Few, however, have comprehensively revealed the relative contributions of the environmental and anthropogenic factors to urban waterlogging concerning different scales of analysis. Indeed what is less known, are the dominant factors and the appropriate scale of analysis. To overcome this limitation, a novel method that integrates the stepwise regression model with hierarchical partitioning analysis is presented. The purpose is to investigate the complex mechanism of urban waterlogging by identifying the relative contribution of each environmental and anthropogenic factor and the stability linking waterlogging to influencing factors at multiple scales of analysis (i.e. 1 km, 2 km, 3 km, 4 km, and 5 km). We consider waterlogging events in the central urban districts of Guangzhou (PR China) from 2009 to 2015 as a case study. The results show that the spatial distribution of waterlogging events in the central urban area presents a strong agglomeration pattern. The waterlogging hot spots are mainly concentrated in the historical area of Guangzhou. Under all analysis scales, we find that the percent cover of urban green spaces (44.74%), percent cover of residential area (41.03%), and slope.std (36.85%) both have a dominant contribution to urban waterlogging, which suggests the importance of land cover composition in determining urban waterlogging. However, the relative contribution and dominant factors of waterlogging varied across different analysis scales, presenting a strong scale effect. Under a small analysis scale (1 km), the topography factors (slope.std and relative elevation) are confirmed as the dominant variables; however, with the increase of analysis scale, the influence of land cover composition (greenspace, residence area, grassland) and land cover spatial configuration (LPI, AI, Cohesion index) on waterlogging magnitude is greater than other factors. This finding provides additional insights that the urban waterlogging can be alleviated by balancing the relative composition of land cover features as well as by optimizing their spatial configuration. Since the optimal statistical scale for urban waterlogging studies only worked for specific influencing factors, the appropriate analysis scale for urban waterlogging study should be determined by the characteristics of study areas. This study has the capability to extend our scientific understanding of the complex mechanisms of waterlogging in the highly urbanized coastal city, providing useful support for the prevention and management of urban waterlogging. Image 1 • The urban waterlogging events present a strong agglomeration pattern. • The dominant factors varied across different analysis scales. • Urban greenspace, residential area, and slope.std have a dominant contribution. • The best analysis scale should be determined by the characteristics of study areas. [ABSTRACT FROM AUTHOR]

Extremely high temperatures, a major cause for weather-related public health issues, are projected to intensify and become more frequent. To mitigate the adverse effects, a low-cost and effective risk assessment method should be developed. Therefore, we applied automatic meteorological station data and population mobility data to develop a high spatiotemporal resolution temperature risk assessment method. The population mobility analysis results showed the working/residential complex pattern in Tianhe District, with hotspots of spatial clustering located in the north, southwest, and southeast of the study area. Taking the population mobility patterns into consideration, high-temperature risk assessment results with a resolution of 100 m were obtained. The total mortality cases in 2014 and 2015 were used to validate this result. The validation showed that the total mortality in the high-temperature risk areas accounted for over 36% of that in Tianhe District. Thus, the method introduced in this study is capable of reflecting weather-related risk. Furthermore, the high-temperature risk assessment results showed that most of the risky areas were located in the southwest of the study area. Two peak times of the risk areas were determined, being before dawn and in the evening. Compared with the risk areas during weekdays, those at weekends expanded. In addition, we used the geographically weighted regression model to investigate the potential influencing factors. Individual factor contributed more than 22.4% to the spatial distribution of heat exposure. Catering services, transportation services, and living services were higher than others, with mean R 2 values of 0.28, 0.23, and 0.25, respectively. More than 47.9% of spatial distribution of heat exposure was attributed to joint function of influencing factors, with global R 2 ranged from 0.23 to 0.34. Our research introduces a spatial-specific method to quantitatively assess high-temperature risk. Moreover, the mechanisms behind the spatial distribution of the high-temperature risk were discussed. The theoretical and management implications can help urban designers and energy governors to develop useful strategies to mitigate weather-related public health risks. • Population mobility is involved in heat-exposure assessment. • A high spatiotemporal heat-exposure assessment method is developed. • Influencing factors were detected. [ABSTRACT FROM AUTHOR]

The traditional view holds that a weakened upwelling has often been observed off the coast of southeast Vietnam during the post-El Niño summer. This study investigated a strong upwelling and concurrent phytoplankton bloom off the coast of southeast Vietnam in August 2016 by comparing it with another case in 1998. Analyses of the upwelling structure and formation mechanisms indicated that the abnormal strong upwelling in August 2016 was attributable to strong wind-driven offshore Ekman transport and Ekman pumping, which were caused by the accompanying southwesterly anomalies south of the anomalous cyclone (AC) over the western North Pacific (WNP), and vice versa in August 1998. This anomalous southwesterly wind associated with the AC over the WNP could not be explained by La Niña, the negative Indian ocean dipole, or the positive Pacific meridional mode events. Further analyses showed that the Madden–Julian oscillation (MJO)-induced westerly winds could have contributed more than 75% of the original zonal winds. Nine tropical cyclones generated over the WNP were favorable for excessive precipitation. The opposite configurations of precipitation patterns over the WNP and the Maritime Continent could have further strengthened the AC via a Gill response. [ABSTRACT FROM AUTHOR]

Green roofs have been treated as practical low impact development (LID) strategies to retain stormwater runoff and alleviate the rainfall-induced flooding risks in urban regions. The purpose of this study was to analyze the hydrological effects of the spatial location of green roofs in urbanized catchments. In the built-up region of Beijing, 12 urbanized catchments with various architectural patterns were chosen as the study areas. To distinguish the spatial characteristics of roof surfaces, we defined the effective roof surfaces to distinguish from other types of roofs, which have more convenient or direct hydrological connections to drainage systems. A hydrological model was then used to simulate the stormwater mitigation performance of green roofs for the study catchments, which were assigned to different rainfall conditions. The simulation results confirmed the benefits of implementing green roofs for urban stormwater regulation. However, the spatial variability of green roofs showed inherent influences on the runoff mitigation capacity in urbanized catchments. Greening on effective roof surfaces would provide more effective stormwater regulation benefits, for reductions in both runoff volume and peak flow. In addition, the spatial arrangement characteristics of roof surfaces also influenced the hydrological efficiency of green roofs. The effect of the spatial location of green roofs on runoff mitigation was rainfall-dependent. These findings provide insights into the hydrological role of green roofs, and suggest that proper siting of LID facilities should be a consideration for urban stormwater management in order to fulfill the hydrological efficiency and cost-effectiveness planning target. • Green roofs behave as effective facility for urban stormwater management. • Spatial location of green roofs shows significant influence on stormwater retention. • Diverse building arrangements also affect the hydrological performance of green roofs. • Contribution of green roofs for runoff mitigation is rainfall-dependent. [ABSTRACT FROM AUTHOR]

Climate change and human interference play significant roles on dynamic of water body abundance, and drive related hydrological, biochemical and social/economic processes. Documenting and monitoring surface water area with high resolution multi-temporal satellite imagery provide new perspective to evaluate the dynamics of surface water area, especially in continental and global scale. In this study, based on the Landsat images from 1980s to 2015, we surveyed the spatial and temporal variation of surface water area, including rivers, lakes and reservoirs, in 10-yr temporal slice across China. Furthermore, the driving forces of the variation has been identified to reveal the interaction of water bodies and the changing environment. The results show that, the water surface area expanded over all three decades with strong spatial and temporal difference, despite the drier and warmer climate background; although lakes comprise the largest portion of the surface water area, the highest contributor of surface water expansion was new constructed reservoir located in the densely populated region; climatic parameters alteration, like precipitation and temperature, resulted in the water surface expansion in the northwestern basin by growing water input linked with rain and glacier melting; in the rest part of China, rise of water surface area was predominately attributed to human relocation of water resource, which yielded more new water storage area than the disappeared water body caused by less precipitation and stronger evapotranspiration. The conclusions highlight the integrative water resource management, especially in water conservation and restoration. [ABSTRACT FROM AUTHOR]

We assessed the spatial heterogeneity of warming due to total anthropogenic heat release (AHR) and building anthropogenic heat release under different heat release scenarios and its relationship with building properties in the highly urbanized portion of Guangzhou using the Weather Research and Forecasting (WRF) model. The simulation results show that different AHR scenarios result in different temperature rise outcomes. A rise of 0.40 °C and 0.23 °C results from a normal total AHR scenario and normal building AHR scenario, while a rise of 0.71 °C and 0.41 °C arises when total AHR and building AHR is doubled. This indicates that more anthropogenic heat results in a more serious warming effect. Moreover, the spatial heterogeneity of the AHR-caused temperature rise is affected by the building area. The AHR-derived warming effect is most serious in high-height-medium-density (H-M) and high-height-high-density (H-H) building areas, where temperature rose by 0.36 °C and 0.34 °C due to building AHR under two AHR scenarios, while it was least serious in low-height-high-density (L-H) and high-height-low-density (H-L) areas, where temperature rose by 16 °C and 0.25 °C under two building AHR scenarios. When AHR is doubled, the hot spot of AHR-derived warming tends to become more concentrated. The quantitative relationship between building AHR-derived warming and building property data was assessed using a multiple linear regression model. The model shows that the combination of building height and building density provides better predictor of building AHR warming than either property alone; and the relationship is best predicted in L-H and H-L areas, with R 2 values of 0.68 and 0.79, respectively. Warming due to AHR should be considered as one of the most serious urban warming forces and the land surface properties are the key factors that influence AHR-derived warming. This study provides evidence for the significance of AHR in the urban environment and offers suggestions for mitigating urban thermal heating. Figure a) and b) shows the warming effect of total anthropogenic heat release under different AHR scenarios; figure c) and d) shows the warming effect of building anthropogenic heat release under different AHR scenarios. Unlabelled Image • Quantitatively assessed the warming effect caused by total AHR and building AHR • Revealed relationships between building AHR warming and building characteristics • Identified the building area types most suited for mitigating AHR warming [ABSTRACT FROM AUTHOR]

Background: Endothelial cell-specific molecule-1 (ESM-1) is a biomarker associated with tumor progression in pituitary adenoma. We specifically focused on one type of pituitary adenoma, namely null cell adenoma (NCA) and evaluated the relationship between invasion and ESM-1 expression in both vascular endothelial and adenoma tissues. Methods: Tissue samples from 94 patients with pituitary NCA were obtained through microscopic transsphenoidal resection. Tumor size and invasion were determined through preoperative magnetic resonance imaging. Immunohistochemical staining was performed to detect ESM-1 expression. ESM-1 index of ≥3 was defined as high expression. Results: Signs of invasion were observed in 46 (47.9%) of the 94 patients. Significant differences were observed in the invasion state and maximum tumor diameter between high and low expression of ESM-1 in vascular endothelial tissues (both P < 0.05). Significant positive associations were noted between ESM-1 expression in vascular endothelial tissues and tumor invasion (P = 0.002) and tumor size (P = 0.020). However, only tumor size was associated with ESM-1 expression in adenoma tissues (P = 0.016). Conclusion: In NCA, a significant positive association between tumor invasion and ESM-1 expression was observed only in vascular endothelial tissues, suggesting that tumor progression occurs mainly through ESM-1-associated mechanism. [ABSTRACT FROM AUTHOR]

Background: Workplace heat exposure can cause a series of heat-related illnesses and injuries. Protecting workers especially those undertake work outdoors from the risk of heat strain is a great challenge for many workplaces in China under the context of climate change. The aim of this study is to investigate the perceptions and adaptation behaviors of heat exposure among construction workers and to provide evidence for the development of targeted heat adaptation strategies nationally and internationally.Methods: In 2020, we conducted a cross-sectional online questionnaire survey via WeChat Survey Star in China, using a purposive snowball sampling approach. A total of 326 construction workers submitted completed questionnaires. The perceptions of workplace heat exposure were measured using seven indicators: concerns over high temperature, perception of high temperature injury, attitudes towards both heat-related training and regulations, adjustment of working habits during heat, heat prevention measures in the workplace, and reduction of work efficiency. Bivariate and multivariate regression analyses were used to identify the factors significantly associated with workers' heat perceptions and behavioral responses.Results: 33.3% of the respondents were moderately or very concerned about heat exposure in the workplace. Less than half of the workers (43.8%) were worried about heat-related injuries. Workers who have either experienced work-related injuries (OR = 1.30, 95% CI 1.03-1.62) or witnessed injuries to others during high temperatures (OR = 1.12, 95% CI 1.02-1.27) were more concerned about heat exposure compared to other workers. Most respondents (63.5%) stated that their work efficiency declined during extremely hot weather. The factors significantly associated with a reduction of work efficiency included undertaking physically demanding jobs (OR = 1.28, 95% CI 1.07-1.54) and witnessing other workers' injuries during high temperatures (OR = 1.26, 95% CI 1.11-1.43). More than half of the workers were willing to adjust their work habits to adapt to the impact of high temperatures (81.6%). The internet was the most common method to obtain heat prevention information (44.7%), and the most frequently used heat prevention measure was the provision of cool drinking water (64.8%).Conclusions: Chinese construction workers lack heat risk awareness and are not well prepared for the likely increasing heat exposure in the workplace due to global warming. Therefore, there is a need to improve their awareness of heat-related injuries, strengthen high temperature related education and training, and update the current heat prevention policies to ensure compliance and implementation. [ABSTRACT FROM AUTHOR]