Estimating the Cooling Effect of Pocket Green Space in High Density Urban Areas in Shanghai, China

Recently, pocket green spaces (PGS), i.e., small green spaces, have attracted growing attention for their various ecological and social services. As a crucial part of urban green spaces in high-density urban areas, PGS facilitates recreation and relaxation for neighborhoods and thus improves the livability of cities at the local scale. However, whether and how the PGS cools the urban heat island effect is still unclear. This research was performed in the highly developed areas of the city of Shanghai during hot summer daytime. We applied a set of cooling effect indicators to estimate the cooling extent, cooling intensity, and cooling efficiency of PGS. We further examined whether and how landscape features within and surrounding the PGS influence its cooling effects. The results showed that 90% of PGS are cooler than their surroundings. Among the landscape features, the land surface temperature of PGS logarithmically decreased with its area, and the maximum local cool island intensity and maximum cooling area logarithmically increased with the area of PGS. The vegetation types and their composition within the PGS also influenced their surface temperature and the cooling effect. The PGS dominated by tree-shrub-grass showed the highest cooling efficiency. The surrounding landscape patterns, especially the patch density and the landscape shape index, influence the cooling effect of PGS at both class and landscape levels. These findings add new knowledge on factors influencing the cooling effect of PGS, and provide the biophysical theoretical basis for developing nature-based cooling strategies for urban landscape designers and planners.Peer Reviewe

Spatiotemporal Evolution of Urban Agglomeration and Its Impact on Landscape Patterns in the Pearl River Delta, China

An urban agglomeration is the engine of regional and national economic growth, but also causes many ecological and environmental issues that emerge from massive land changes. In this study, the spatiotemporal evolution of an urban agglomeration was quantified and its impacts on the urban and regional landscape patterns were evaluated. It showed that the urbanized land area of the Pearl River Delta Urban Agglomeration (PRDUA) in China nearly quadrupled, having linearly increased from 1819.8 km2 to 7092.2 km2 between 1985 and 2015. The average annual growth rate presented a bimodal wave-like pattern through time, indicating that the PRDUA has witnessed two rounds of the urbanization process. The growth modes (e.g., leapfrog, edge-expansion, infilling) were detected and they exhibited co-existing but alternating dominating patterns during urbanization, demonstrating that the spatiotemporal evolution of the urban development of the PRDUA follows the “spiral diffusion-coalescence” hypothesis. The morphology of the PRDUA presented an alternating dispersal-compact pattern over time. The city-level and regional-level landscape patterns changed synchronously with the spatiotemporal evolution of the PRDUA over time. The urbanization of the PRDUA increased both the complexity and aggregation of the landscape, but also resulted in an increasing fragmentation and decreasing connectivity of the natural landscape in the Pearl River Delta region. These findings are helpful for better understanding how urban agglomerations evolve and in providing insights for regional urban planning and sustainable land management.Natural Science Foundation of ChinaNational Key R&D Program of ChinaChina Postdoctoral Science FoundationJoint-PhD project of Shanghai Jiao Tong University and The University of MelbournePeer Reviewe

Urban Treetop Detection and Tree-Height Estimation from Unmanned-Aerial-Vehicle Images

Individual tree detection for urban forests in subtropical environments remains a great challenge due to the various types of forest structures, high canopy closures, and the mixture of evergreen and deciduous broadleaved trees. Existing treetop detection methods based on the canopy-height model (CHM) from UAV images cannot resolve commission errors in heterogeneous urban forests with multiple trunks or strong lateral branches. In this study, we improved the traditional local-maximum (LM) algorithm using a dual Gaussian filter, variable window size, and local normalized correlation coefficient (NCC). Specifically, we adapted a crown model of maximum/minimum tree-crown radii and an angle strategy to detect treetops. We then removed and merged the pending tree vertices. Our results showed that our improved LM algorithm had an average user accuracy (UA) of 87.3% (SD± 4.6), an average producer accuracy (PA) of 82.8% (SD± 4.1), and an overall accuracy of 93.3% (SD± 3.9) for sample plots with canopy closures less than 0.5. As for the sample plots with canopy closures from 0.5 to 1, the accuracies were 78.6% (SD± 31.5), 73.8% (SD± 10.3), and 68.1% (SD± 12.7), respectively. The tree-height estimation accuracy reached more than 0.96, with an average RMSE of 0.61 m. Our results show that the UAV-image-derived CHM can be used to accurately detect individual trees in mixed forests in subtropical cities like Shanghai, China, to provide vital tree-structure parameters for precise and sustainable forest management.National Key R&D Program of ChinaNational Natural Science Foundation of ChinaChina Postdoctoral Science FoundationPeer Reviewe

Mapping Impervious Surface Using Phenology-Integrated and Fisher Transformed Linear Spectral Mixture Analysis

The impervious surface area (ISA) is a key indicator of urbanization, which brings out serious adverse environmental and ecological consequences. The ISA is often estimated from remotely sensed data via spectral mixture analysis (SMA). However, accurate extraction of ISA using SMA is compromised by two major factors, endmember spectral variability and plant phenology. This study developed a novel approach that incorporates phenology with Fisher transformation into a conventional linear spectral mixture analysis (PF-LSMA) to address these challenges. Four endmembers, high albedo, low albedo, evergreen vegetation, and seasonally exposed soil (H-L-EV-SS) were identified for PF-LSMA, considering the phenological characteristic of Shanghai. Our study demonstrated that the PF-LSMA effectively reduced the within-endmember spectral signature variation and accounted for the endmember phenology effects, and thus well-discriminated impervious surface from seasonally exposed soil, enhancing the accuracy of ISA extraction. The ISA fraction map produced by PF-LSMA (RMSE = 0.1112) outperforms the single-date image Fisher transformed unmixing method (F-LSMA) (RMSE = 0.1327) and the other existing major global ISA products. The PF-LSMA was implemented on the Google Earth Engine platform and thus can be easily adapted to extract ISA in other places with similar climate conditions.Peer Reviewe

Spatiotemporal Evolution of Urban Agglomeration and Its Impact on Landscape Patterns in the Pearl River Delta, China

An urban agglomeration is the engine of regional and national economic growth, but also causes many ecological and environmental issues that emerge from massive land changes. In this study, the spatiotemporal evolution of an urban agglomeration was quantified and its impacts on the urban and regional landscape patterns were evaluated. It showed that the urbanized land area of the Pearl River Delta Urban Agglomeration (PRDUA) in China nearly quadrupled, having linearly increased from 1819.8 km2 to 7092.2 km2 between 1985 and 2015. The average annual growth rate presented a bimodal wave-like pattern through time, indicating that the PRDUA has witnessed two rounds of the urbanization process. The growth modes (e.g., leapfrog, edge-expansion, infilling) were detected and they exhibited co-existing but alternating dominating patterns during urbanization, demonstrating that the spatiotemporal evolution of the urban development of the PRDUA follows the “spiral diffusion-coalescence” hypothesis. The morphology of the PRDUA presented an alternating dispersal-compact pattern over time. The city-level and regional-level landscape patterns changed synchronously with the spatiotemporal evolution of the PRDUA over time. The urbanization of the PRDUA increased both the complexity and aggregation of the landscape, but also resulted in an increasing fragmentation and decreasing connectivity of the natural landscape in the Pearl River Delta region. These findings are helpful for better understanding how urban agglomerations evolve and in providing insights for regional urban planning and sustainable land management

Mapping Impervious Surface Using Phenology-Integrated and Fisher Transformed Linear Spectral Mixture Analysis

The impervious surface area (ISA) is a key indicator of urbanization, which brings out serious adverse environmental and ecological consequences. The ISA is often estimated from remotely sensed data via spectral mixture analysis (SMA). However, accurate extraction of ISA using SMA is compromised by two major factors, endmember spectral variability and plant phenology. This study developed a novel approach that incorporates phenology with Fisher transformation into a conventional linear spectral mixture analysis (PF-LSMA) to address these challenges. Four endmembers, high albedo, low albedo, evergreen vegetation, and seasonally exposed soil (H-L-EV-SS) were identified for PF-LSMA, considering the phenological characteristic of Shanghai. Our study demonstrated that the PF-LSMA effectively reduced the within-endmember spectral signature variation and accounted for the endmember phenology effects, and thus well-discriminated impervious surface from seasonally exposed soil, enhancing the accuracy of ISA extraction. The ISA fraction map produced by PF-LSMA (RMSE = 0.1112) outperforms the single-date image Fisher transformed unmixing method (F-LSMA) (RMSE = 0.1327) and the other existing major global ISA products. The PF-LSMA was implemented on the Google Earth Engine platform and thus can be easily adapted to extract ISA in other places with similar climate conditions

BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features

Abstract Background Understanding how biomolecules interact is a major task of systems biology. To model protein-nucleic acid interactions, it is important to identify the DNA or RNA-binding residues in proteins. Protein sequence features, including the biochemical property of amino acids and evolutionary information in terms of position-specific scoring matrix (PSSM), have been used for DNA or RNA-binding site prediction. However, PSSM is rather designed for PSI-BLAST searches, and it may not contain all the evolutionary information for modelling DNA or RNA-binding sites in protein sequences. Results In the present study, several new descriptors of evolutionary information have been developed and evaluated for sequence-based prediction of DNA and RNA-binding residues using support vector machines (SVMs). The new descriptors were shown to improve classifier performance. Interestingly, the best classifiers were obtained by combining the new descriptors and PSSM, suggesting that they captured different aspects of evolutionary information for DNA and RNA-binding site prediction. The SVM classifiers achieved 77.3% sensitivity and 79.3% specificity for prediction of DNA-binding residues, and 71.6% sensitivity and 78.7% specificity for RNA-binding site prediction. Conclusions Predictions at this level of accuracy may provide useful information for modelling protein-nucleic acid interactions in systems biology studies. We have thus developed a web-based tool called BindN+ (http://bioinfo.ggc.org/bindn+/) to make the SVM classifiers accessible to the research community

Developing Ophiostoma floccosum as a novel expression system

"This thesis is based on the following articles, referred to in the text by the Roman numerals given below. In addition some unpublished results are presented. I. Caiyan Wu ... [et al] Improvement of the secretion of extracellular proteins and isolation and characterization of the amylase I (amyI) gene from Ophiostoma floccosum [pub. in ] Gene 384: 96-103 -- II. Caiyan Wu ... [et al.] Activity-based identification of secreted serine proteases of the filamentous fungus Ophiostoma. Accepted by Biotechnology letters DOI 10.1007/s10529-007-9333-6 -- III. Caiyan Wu ...[et al.] Expression of a thermostable bacterial xylanase in the filamentous fungus Ophiostoma floccosum. Submitted to Letters in applied microbiology in July 2007." - leaf 9.Thesis (PhD)--Macquarie University, Division of Environmental and Life Sciences, Dept. of Chemistry & Biomolecular Sciences, 2007.Bibliography: leaves 100-123.Introduction -- Materials and methods -- Results and discussion -- Conclusion and future aspects -- References -- Publications I, II and III.Ophiostoma spp. belong to the Ophiostomataceae family, a large group of ascomycetes, which are the most frequent blue stain fungi isolated from stained wood. Most Ophiostoma species do not compromise the strength properties of wood, but do reduce the aesthetic quality of timber and therefore decrease the economic value of lumber. Some albino variants of O. floccosum and O. piliferum have been used as biological control agents to prevent blue staining. This successful whole organism approach plus the added capability of extracellular protein secretion makes Ophiostoma spp. attractive for industrial application. In addition, Ophiostoma produces only a small range of abundantly secreted proteins in liquid culture, which can facilitate downstream purification of any recombinant gene product introduced into the system. Genes encoding efficiently secreted proteins provide a potential souce for strong promoters for high-level gene expression. These characteristics provide an excellent starting point for the development of a novel expression system.In this study, UV-mutagenesis was applied to improve protein secretion in Ophiostoma floccosum. Amylase activity was used as an indicator for enhanced protein secretion after repeated rounds of mutagenic treatment. Several mutants of O. floccosum derived by UV mutagenesis were isolated and the total amount of secreted protein was increased by 4 to 6 times. The amylase activity in the culture supernatant of the best mutant (MQ.5.1) was increased by more than 240-fold compared to the initial parental strain. At the same time, the amount of total secreted protein was about six times greater to that of the parental strain. Proteinase profiles in the culture supernatants of several key mutants were characterized for the future matching of an expression host with a particular gene product. N-terminal sequencing of the five dominant proteins separated by SDS-PAGE from the culture supernatant was conducted. Two of the proteins identified were subtilisin-like proteinases and one was a pepsin-like proteinase. In addition, one protein was identified as an_-amylase and one remained unidentified. A 6.5 kb DNA fragment was isolated by Genomic Walking PCR using primers based on the _-amylase amino acid sequence. The amplified fragment contained the entire gene encoding_-amylase (amyl) and its regulatory sequences. Analysis showed that multiple transcripts were generated from the single _-amylase gene locus.A series of expression vectors containg the _-amylase regulatory sequences and partial amyl gene were constructed. Several selection markers were screened and the hph gene conferring hygromycin resistance under the regulation of the Aspergillus nidulans gpd promoter was chosen and inserted into the amyl expression vectors. The gene encoding a red fluorescent protein DsRed-E5 was used as a reporter gene to test the expression system using mutant MQ.5.1 as host. However, no transformants were obtained by either biolistic transformation or protoplast transformation. Subsequently, an alternative strategy was developed using a thermostable xylanase B as a reporter. Thermostable xylanase activity was detected in the culture supernatants of several transformants. Production of xylanase by transformant SS41 which exhibited high secreted xylanase activity was investigated. Xylanase activity in the culture supernatant of SS41 was visualized by a zymogram gel assay. Two active proteins with molecular masses of around 27 and 30 kDA, which were larger than the predicted Mr of 25 kDA were detected. This is the first report describing successful expression of a recombinant thermostable bacterial enzyme in Ophiostoma.Mode of access: World Wide Web.158 leaves col. il

Optical Properties of Plasma Dimer Nanoparticles for Solar Energy Absorption

Plasmonic nanofluids have excellent optical properties in solar energy absorption and have been widely studied in solar thermal conversion technology. The absorption of the visible region of solar energy by ordinary metal nanoparticles is usually limited to a narrow resonance band, so it is necessary to enhance the coupling effect of nanoparticles in the visible spectrum region to improve absorption efficiency. However, it is still a difficult task to improve solar energy absorption by adjusting the structure and performance of nanoparticles. In this paper, a plasma dimer Ag nanoparticle is proposed to excite localized surface plasmon resonance (LSPR). Compared with an ordinary Ag nanoparticle in the visible region, the plasmonic Ag dimer nanoparticle produces more absorption peaks and broader absorption bands, which can broaden solar energy absorption. By analyzing the electromagnetic field of the nanoparticle, the resonance mode of the plasma dimer is discussed. The effects of the geometric dimensions of the nanoparticle and the embedding of two spheres on the optical properties are studied. In addition, the effects of a trimer and its special structure on the optical properties are also analyzed. The results show that the proposed plasma dimer Ag nanoparticle has broad prospects for application in solar thermal conversion technology

Development of Ophiostoma as a novel fungal expression host

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