The Urban heat island (UHI) effect is an increasingly serious problem in urban areas. Information on the driving forces of intra-urban temperature variation is crucial for ameliorating the urban ...thermal environment. Although prior studies have suggested that urban morphology (e.g., landscape pattern, land-use type) can significantly affect land surface temperature (LST), few studies have explored the comprehensive effect of 2D and 3D urban morphology on LST in different urban functional zones (UFZs), especially at a fine scale. Therefore, in this research, we investigated the relationship between 2D/3D urban morphology and summer daytime LST in Wuhan, a representative megacity in Central China, which is known for its extremely hot weather in summer, by adopting high-resolution remote sensing data and geographical information data. The “urban morphology” in this study consists of 2D urban morphological parameters, 3D urban morphological parameters, and UFZs. Our results show that: (1) The LST is significantly related to 2D and 3D urban morphological parameters, and the scattered distribution of buildings with high rise can facilitate the mitigation of LST. Although sky view factor (SVF) is an important measure of 3D urban geometry, its influence on LST is complicated and context-dependent. (2) Trees are the most influential factor in reducing LST, and the cooling efficiency mainly depends on their proportions. The fragmented and irregular distribution of grass/shrubs also plays a significant role in alleviating LST. (3) With respect to UFZs, the residential zone is the largest heat source, whereas the highest LST appears in commercial and industrial zones. (4) Results of the multivariate regression and variation partitioning indicate that the relative importance of 2D and 3D urban morphological parameters on LST varies among different UFZs and 2D morphology outperforms 3D morphology in LST modulation. The results are generally consistent in spring, summer and autumn. These findings can provide insights for urban planners and designers on how to mitigate the surface UHI (SUHI) effect via rational landscape design and urban management during summer daytime.
In this paper, an adaptive mean-shift (MS) analysis framework is proposed for object extraction and classification of hyperspectral imagery over urban areas. The basic idea is to apply an MS to ...obtain an object-oriented representation of hyperspectral data and then use support vector machine to interpret the feature set. In order to employ MS for hyperspectral data effectively, a feature-extraction algorithm, nonnegative matrix factorization, is utilized to reduce the high-dimensional feature space. Furthermore, two bandwidth-selection algorithms are proposed for the MS procedure. One is based on the local structures, and the other exploits separability analysis. Experiments are conducted on two hyperspectral data sets, the DC Mall hyperspectral digital-imagery collection experiment and the Purdue campus hyperspectral mapper images. We evaluate and compare the proposed approach with the well-known commercial software eCognition (object-based analysis approach) and an effective spectral/spatial classifier for hyperspectral data, namely, the derivative of the morphological profile. Experimental results show that the proposed MS-based analysis system is robust and obviously outperforms the other methods.
Land cover (LC) determines the energy exchange, water and carbon cycle between Earth's spheres. Accurate LC information is a fundamental parameter for the environment and climate studies. Considering ...that the LC in China has been altered dramatically with the economic development in the past few decades, sequential and fine-scale LC monitoring is in urgent need. However, currently, fine-resolution annual LC dataset produced by the observational images is generally unavailable for China due to the lack of sufficient training samples and computational capabilities. To deal with this issue, we produced the first Landsat-derived annual China land cover dataset (CLCD) on the Google Earth Engine (GEE) platform, which contains 30 m annual LC and its dynamics in China from 1990 to 2019. We first collected the training samples by combining stable samples extracted from China's land-use/cover datasets (CLUDs) and visually interpreted samples from satellite time-series data, Google Earth and Google Maps. Using 335 709 Landsat images on the GEE, several temporal metrics were constructed and fed to the random forest classifier to obtain classification results. We then proposed a post-processing method incorporating spatial–temporal filtering and logical reasoning to further improve the spatial–temporal consistency of CLCD. Finally, the overall accuracy of CLCD reached 79.31 % based on 5463 visually interpreted samples. A further assessment based on 5131 third-party test samples showed that the overall accuracy of CLCD outperforms that of MCD12Q1, ESACCI_LC, FROM_GLC and GlobeLand30. Besides, we intercompared the CLCD with several Landsat-derived thematic products, which exhibited good consistencies with the Global Forest Change, the Global Surface Water, and three impervious surface products. Based on the CLCD, the trends and patterns of China's LC changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and grassland (−3.29 %), and increase in forest (+4.34 %). In general, CLCD reflected the rapid urbanization and a series of ecological projects (e.g. Gain for Green) in China and revealed the anthropogenic implications on LC under the condition of climate change, signifying its potential application in the global change research. The CLCD dataset introduced in this article is freely available at https://doi.org/10.5281/zenodo.4417810 (Yang and Huang, 2021).
Self-healing materials integrated with excellent mechanical strength and simultaneously high healing efficiency would be of great use in many fields, however their fabrication has been proven ...extremely challenging. Here, inspired by biological cartilage, we present an ultrarobust self-healing material by incorporating high density noncovalent bonds at the interfaces between the dentritic tannic acid-modified tungsten disulfide nanosheets and polyurethane matrix to collectively produce a strong interfacial interaction. The resultant nanocomposite material with interwoven network shows excellent tensile strength (52.3 MPa), high toughness (282.7 MJ m
, which is 1.6 times higher than spider silk and 9.4 times higher than metallic aluminum), high stretchability (1020.8%) and excellent healing efficiency (80-100%), which overturns the previous understanding of traditional noncovalent bonding self-healing materials where high mechanical robustness and healing ability are mutually exclusive. Moreover, the interfacical supramolecular crosslinking structure enables the functional-healing ability of the resultant flexible smart actuation devices. This work opens an avenue toward the development of ultrarobust self-healing materials for various flexible functional devices.
A
bstract
Göttsche-Nakajima-Yoshioka K-theoretic blowup equations characterize the Nekrasov partition function of five dimensional
N
=
1
supersymmetric gauge theories compactified on a circle, which ...via geometric engineering correspond to the refined topological string theory on SU(
N
) geometries. In this paper, we study the K-theoretic blowup equations for general local Calabi-Yau threefolds. We find that both vanishing and unity blowup equations exist for the partition function of refined topological string, and the crucial ingredients are the
r
fields introduced in our previous paper. These blowup equations are in fact the functional equations for the partition function and each of them results in infinite identities among the refined free energies. Evidences show that they can be used to determine the full refined BPS invariants of local Calabi-Yau threefolds. This serves an independent and sometimes more powerful way to compute the partition function other than the refined topological vertex in the A-model and the refined holomorphic anomaly equations in the B-model. We study the modular properties of the blowup equations and provide a procedure to determine all the vanishing and unity
r
fields from the polynomial part of refined topological string at large radius point. We also find that certain form of blowup equations exist at generic loci of the moduli space.
In recent years, the resolution of remotely sensed imagery has become increasingly high in both the spectral and spatial domains, which simultaneously provides more plentiful spectral and spatial ...information. Accordingly, the accurate interpretation of high-resolution imagery depends on effective integration of the spectral, structural and semantic features contained in the images. In this paper, we propose a new multifeature model, aiming to construct a support vector machine (SVM) ensemble combining multiple spectral and spatial features at both pixel and object levels. The features employed in this study include a gray-level co-occurrence matrix, differential morphological profiles, and an urban complexity index. Subsequently, three algorithms are proposed to integrate the multifeature SVMs: certainty voting, probabilistic fusion, and an object-based semantic approach, respectively. The proposed algorithms are compared with other multifeature SVM methods including the vector stacking, feature selection, and composite kernels. Experiments are conducted on the hyperspectral digital imagery collection experiment DC Mall data set and two WorldView-2 data sets. It is found that the multifeature model with semantic-based postprocessing provides more accurate classification results (an accuracy improvement of 1-4% for the three experimental data sets) compared to the voting and probabilistic models.
Exosomes play crucial roles in regulating the crosstalk between normal and cancer cells in the tumor microenvironment, and in regulating cancer proliferation, migration and invasion through their ...cargo molecules.
We analyzed the pro-invasiveness of exosomal circRNA-100,338 in HCC using the transwell invasion assay. The co-culture of human umbilical vein endothelial cells (HUVEC) and exosomes derived from HCC cell lines were used to evaluate the impact of HCC derived exosomes on HUVEC. Nude mice models were used to validate the findings in vitro. Clinically, quantitative RT-PCR was used to quantify the expression of serum exosomal circRNA-100,338 in HCC patients at both pre-surgery within one week and post-surgery within three weeks.
We aim to investigate the pro-invasive role of exosomal circRNA-100,338 in HCC metastasis. We for the first time demonstrated that circRNA-100,338 was highly expressed in both highly metastatic HCC cells and their secreted exosomes. The transwell invasion assay showed that the overexpression or knockdown of exosomal circRNA-100,338 significantly enhanced or reduced the invasive abilities of HCC cells. Subsequently, in vitro and in vivo assays showed that exosomal circRNA-100,338 affected the cell proliferation, angiogenesis, permeability, and vasculogenic mimicry (VM) formation ability of human umbilical vein endothelial cells (HUVEC), and tumor metastasis. Furthermore, we also observed that the persistent high expression of exosomal circRNA-100,338 in serum of HCC patients who underwent curative hepatectomy may be a risk indicator of pulmonary metastasis and poor survival.
Our findings indicated that metastatic ability of HCC cells could be enhanced by transferring exosomal circRNA-100,338 to recipient HUVECs, which could affect proangiogenic activity by regulating angiogenesis.
Circular RNAs (circRNAs) represent a class of endogenous noncoding RNAs that have recently been recognized as important regulators of gene expression and pathological networks. However, their ...transcriptional activities and functional mechanisms in cancer remain largely unknown. Here, we present results from a global circRNA expression and functional analysis of patients with hepatocellular carcinoma (HCC). Using a circRNA microarray, we identified 226 differentially expressed circRNAs, of which 189 were significantly upregulated and 37 were downregulated. High expression of circRNA_100338, one of the upregulated circRNAs in HCC, is closely correlated with a low cumulative survival rate and metastatic progression in HCC patients with hepatitis B. Furthermore, our in silico and experimental analyses identified miR-141-3p as a direct target of circRNA_100338. Thus, circRNA_100338 functions as an endogenous sponge for miR-141-3p in HCC. In addition, we identified the crucial antagonistic roles of circRNA_100338 and miR-141-3p in the regulation of invasive potential in liver cancer cells. Overall, the differential expression of multiple circRNAs in HCC tissues and their clinical significance in hepatitis B-related HCC patients as revealed by our study suggests that circRNA_100338 is a potentially valuable biomarker for HCC diagnosis and target for HCC therapeutics.
Transition metal dichalcogenide materials have been explored extensively as catalysts to negotiate the hydrogen evolution reaction, but they often run at a large excess thermodynamic cost. Although ...activating strategies, such as defects and composition engineering, have led to remarkable activity gains, there remains the requirement for better performance that aims for real device applications. We report here a phosphorus-doping-induced phase transition from cubic to orthorhombic phases in CoSe
. It has been found that the achieved orthorhombic CoSe
with appropriate phosphorus dopant (8 wt%) needs the lowest overpotential of 104 mV at 10 mA cm
in 1 M KOH, with onset potential as small as -31 mV. This catalyst demonstrates negligible activity decay after 20 h of operation. The striking catalysis performance can be attributed to the favorable electronic structure and local coordination environment created by this doping-induced structural phase transition strategy.
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