SuDS & sponge cities:A comparative analysis of the implementation of pluvial flood management in the UK and China

In recent decades, rapid urbanization has resulted in a growing urban population, transformed into regions of exceptional socio-economic value. By removing vegetation and soil, grading the land surface and saturating soil air content, urban developments are more likely to be flooded, which will be further exacerbated by an anticipated increase in the number of intense rainfall events, due to climate change. To date, data collected show that urban pluvial flood events are on the rise for both the UK and China. This paper presents a critical review of existing sustainable approaches to urban flood management, by comparing UK practice with that in China and critically assessing whether lessons can be learnt from the Sponge City initiative. The authors have identified a strategic research plan to ensure that the sponge city initiative can successfully respond to extreme climatic events and tackle pluvial flooding. Hence, this review suggests that future research should focus on (1) the development of a more localized rainfall model for the Chinese climate; (2) the role of retrofit SuDS (Sustainable Drainage Systems) in challenging water environments; (3) the development of a robust SuDS selection tool, ensuring that the most effective devices are installed, based on local factors; and (4) dissemination of current information, and increased understanding of maintenance and whole life-costing, alongside monitoring the success of sponge cities to increase the confidence of decision makers (5) the community engagement and education about sponge cities

Flavanone-rich citrus beverages counteract the transient decline in postprandial endothelial function in humans: a randomised, controlled, double-masked, cross-over intervention study

Specific flavonoid-rich foods/beverages are reported to exert positive effects on vascular function; however, data relating to effects in the postprandial state are limited. The present study investigated the postprandial, time-dependent (0–7 h) impact of citrus flavanone intake on vascular function. An acute, randomised, controlled, double-masked, cross-over intervention study was conducted by including middle-aged healthy men (30–65 years, n 28) to assess the impact of flavanone intake (orange juice: 128·9 mg; flavanone-rich orange juice: 272·1 mg; homogenised whole orange: 452·8 mg; isoenergetic control: 0 mg flavanones) on postprandial (double meal delivering a total of 81 g of fat) endothelial function. Endothelial function was assessed by flow-mediated dilatation (FMD) of the brachial artery at 0, 2, 5 and 7 h. Plasma levels of paringenin/hesperetin metabolites (sulphates and glucuronides) and nitric oxide species were also measured. All flavanone interventions were effective at attenuating transient impairments in FMD induced by the double meal (7 h post intake; P <0·05), but no dose–response effects were observed. The effects on FMD coincided with the peak of naringenin/hesperetin metabolites in circulation (7 h) and sustained levels of plasma nitrite. In summary, citrus flavanones are effective at counteracting the negative impact of a sequential double meal on human vascular function, potentially through the actions of flavanone metabolites on nitric oxide

Microtermolides A and B from Termite-Associated Streptomyces sp. and Structural Revision of Vinylamycin

Microtermolides A (1) and B (2) were isolated from a Streptomyces sp. strain associated with fungus-growing termites. The structures of 1 and 2 were determined by 1D- and 2D-NMR spectroscopy and high-resolution mass spectrometry. Structural elucidation of 1 led to the re-examination of the structure originally proposed for vinylamycin (3). Based on a comparison of predicted and experimental $^1$H and $^{13}$C NMR chemical shifts, we propose that vinylamycin’s structure be revised from 3 to 4

Stability analysis of loess fill slope supported by frame prestressed anchors considering tensile strength cut-off

Abstract In the stability analysis of loess fill slope, the fissure nature of loess is often ignored, which makes the stability calculation of fill slope too conservative. Based on the upper limit theory of plastic limit analysis, the stability analysis model of loess-filled fissured slope supported by frame prestressed anchors was established. Considering the tensile strength cut-off yield property of soil, the stability coefficient of slope was calculated, and the influence of different factors on slope stability was analyzed. The results show that ignoring the fissures in loess will overestimate the stability of the fill slope, and the support structure can significantly improve the stability of the loess-filled fissure slope. The research results of this paper can further enrich the stability analysis theory of loess-filled fissured slope supported by frame prestressed anchors, which is of great significance to guide engineering practice

Natural Product Discovery Using Planes of Principal Component Analysis in R (PoPCAR)

Rediscovery of known natural products hinders the discovery of new, unique scaffolds. Efforts have mostly focused on streamlining the determination of what compounds are known vs. unknown (dereplication), but an alternative strategy is to focus on what is different. Utilizing statistics and assuming that common actinobacterial metabolites are likely known, focus can be shifted away from dereplication and towards discovery. LC-MS-based principal component analysis (PCA) provides a perfect tool to distinguish unique vs. common metabolites, but the variability inherent within natural products leads to datasets that do not fit ideal standards. To simplify the analysis of PCA models, we developed a script that identifies only those masses or molecules that are unique to each strain within a group, thereby greatly reducing the number of data points to be inspected manually. Since the script is written in R, it facilitates integration with other metabolomics workflows and supports automated mass matching to databases such as Antibase

Neural network model based on global and local features for multi-view mammogram classification

Mammography is an important screening criterion for breast cancer, one of the major diseases causing numerous deaths among female patients. Meanwhile, manual diagnosis of mammography is a time-consuming and labor-consuming job. Mammogram classification based on deep learning plays a vital role in computer-aided diagnosis (CAD) systems to mitigate the pressure on physicians. This paper proposes a learning-based multi-view mammogram classification model that captures long-distance dependence and extracts features of multiple receptive fields. Our model considers global and local features of mammography images using Transformer for global features and the proposed multiplex convolutions module for local features. We evaluate our proposed method on a dataset of mammography images obtained from a hospital in China. The proposed method achieves 90.57% accuracy and 94.86% AUC in benign or malignant classification tasks and outperforms other advanced methods for mammogram classification. It is worth noting that the proposed method only requires image-level labels and acts on the whole raw mammogram, which has clinical significance

GhERF.B4-15D: A Member of ERF Subfamily B4 Group Positively Regulates the Resistance against <i>Verticillium dahliae</i> in Upland Cotton

Verticillium wilt is a fungal disease in upland cotton and exerts a significant effect on growth and potential productivity. This disease is mainly caused by V. dahliae Kleb. Ethylene response factor (ERF) is one of the superfamilies of transcription factors that is involved in the development and environmental adaption of crops. A total of 30 ERF.B4 group members were detected in upland cotton and divided into 6 subgroups. Gene structures, conserved motifs, and domain analysis revealed that members in each subgroup are highly conserved. Further, the 30 GhERF.B4 group members were distributed on 18 chromosomes, and 36 gene synteny relationships were found among them. GhERF.B4 genes were ubiquitously expressed in various tissues and developmental stages of cotton. Amongst them, GhERF.B4-15D was predominantly expressed in roots, and its expression was induced by V. dahliae infection. In addition, GhERF.B4-15D responded to methyl jasmonate (MeJA), methyl salicylate (MeSA), and ethylene (ET) phytohormones. It was also found that the V. dahliae resistance was enhanced due to overexpression of GhERF.B4-15D in Arabidopsis thaliana. On the contrary, interference of GhERF.B4-15D by virus-induced gene silencing (VIGS) technology decreased the V. dahliae resistance level in upland cotton. The subcellular localization experiment showed that GhERF.B4-15D was located in the nucleus. Yeast two-hybrid (Y2H) and luciferase complementation (LUC) approaches demonstrated that GhERF.B4-15D interacted with GhDREB1B. Additionally, the V. dahliae resistance was significantly decreased in GhDREB1B knockdowns. Our results showed that GhERF.B4-15D plays a role during V. dahliae infection in cotton

Comparison of Conductor-Temperature Calculations Based on Different Radial-Position-Temperature Detections for High-Voltage Power Cable

In this paper, the calculation of the conductor temperature is related to the temperature sensor position in high-voltage power cables and four thermal circuits—based on the temperatures of insulation shield, the center of waterproof compound, the aluminum sheath, and the jacket surface are established to calculate the conductor temperature. To examine the effectiveness of conductor temperature calculations, simulation models based on flow characteristics of the air gap between the waterproof compound and the aluminum are built up, and thermocouples are placed at the four radial positions in a 110 kV cross-linked polyethylene (XLPE) insulated power cable to measure the temperatures of four positions. In measurements, six cases of current heating test under three laying environments, such as duct, water, and backfilled soil were carried out. Both errors of the conductor temperature calculation and the simulation based on the temperature of insulation shield were significantly smaller than others under all laying environments. It is the uncertainty of the thermal resistivity, together with the difference of the initial temperature of each radial position by the solar radiation, which led to the above results. The thermal capacitance of the air has little impact on errors. The thermal resistance of the air gap is the largest error source. Compromising the temperature-estimation accuracy and the insulation-damage risk, the waterproof compound is the recommended sensor position to improve the accuracy of conductor-temperature calculation. When the thermal resistances were calculated correctly, the aluminum sheath is also the recommended sensor position besides the waterproof compound