Stormwater Quality Characteristics and Reuse Analysis of Different Underlying Surfaces at Wanzhou North Station

In response to the water shortage in Wanzhou North Station (WNS), the authors investigated the stormwater quality characteristics with different underlying surfaces of WNS and carried out stormwater reuse analysis in conjunction with the InfoWorks ICM model. The results show that during heavy, torrential, and moderate rainfall, the road stormwater runoff has the highest concentrations of pollutants, with an average EMC (event mean concentration) value of 206 mg/L for COD. For the square runoff, the average EMC values of COD, SS, TN, and TP are 108 mg/L, 395 mg/L, 2.113 mg/L, and 0.128 mg/L, in comparison, the average EMC values of the corresponding indexes for the roof runoff are 65 mg/L, 212 mg/L, 1.449 mg/L, and 0.086 mg/L, respectively, demonstrating their potential for reuse. The R2 (coefficient of determination) of SS and COD in both roof and square runoff are greater than 0.85, with a good correlation, indicating that SS removal is the key to stormwater purification. InfoWorks ICM analysis shows that the recyclable volume of rainwater from WNS in 2018 is 29,410 m3 , accounting for 61.8% of the total annual rainfall. This study is expected to provide an ideal reference for the stormwater management of public buildings in mountainous areas

Omics-based interpretation of synergism in a soil-derived cellulose-degrading microbial community

Reaching a comprehensive understanding of how nature solves the problem of degrading recalcitrant biomass may eventually allow development of more efficient biorefining processes. Here we interpret genomic and proteomic information generated from a cellulolytic microbial consortium (termed F1RT) enriched from soil. Analyses of reconstructed bacterial draft genomes from all seven uncultured phylotypes in F1RT indicate that its constituent microbes cooperate in both cellulose-degrading and other important metabolic processes. Support for cellulolytic inter-species cooperation came from the discovery of F1RT microbes that encode and express complimentary enzymatic inventories that include both extracellular cellulosomes and secreted free-enzyme systems. Metabolic reconstruction of the seven F1RT phylotypes predicted a wider genomic rationale as to how this particular community functions as well as possible reasons as to why biomass conversion in nature relies on a structured and cooperative microbial community

The conservation and uniqueness of the caspase family in the basal chordate, amphioxus

<p>Abstract</p> <p>Background</p> <p>The caspase family, which plays a central role in apoptosis in metazoans, has undergone an expansion in amphioxus, increasing to 45 members through domain recombination and shuffling.</p> <p>Results</p> <p>In order to shed light on the conservation and uniqueness of this family in amphioxus, we cloned three representative caspase genes, designated as <it>bbtCaspase-8, bbtCaspase-1/2 </it>and <it>bbtCaspase3</it>-like, from the amphioxus <it>Branchiostoma belcheri tsingtauense</it>. We found that <it>bbtCaspase-8 </it>with conserved protein architecture is involved in the Fas-associated death domain-Caspase-8 mediated pro-apoptotic extrinsic pathway, while <it>bbtCaspase3</it>-like may mediate a nuclear apoptotic pathway in amphioxus. Also, <it>bbtCaspase-1/2 </it>can co-localize with <it>bbtFADD2 </it>in the nucleus, and be recruited to the cytoplasm by amphioxus apoptosis associated speck-like proteins containing a caspase recruitment domain, indicating that <it>bbtCaspase-1/2 </it>may serve as a switch between apoptosis and caspase-dependent innate immune response in invertebrates. Finally, amphioxus extrinsic apoptotic pathway related caspases played important roles in early embryogenesis.</p> <p>Conclusions</p> <p>Our study not only demonstrates the conservation of <it>bbtCaspase-8 </it>in apoptosis, but also reveals the unique features of several amphioxus caspases with novel domain architectures arose some 500 million years ago.</p

The Role of Echocardiography in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disease and appears in all ethnic groups. HCM is diagnosed on the basis of left ventricular hypertrophy. Echocardiography is a key technique in the diagnosis of HCM, the prognosis of patients with HCM, the management strategy for HCM, and the follow-up of patients with HCM. This review briefly describes and discusses the practical use of established echocardiography techniques and the current and emerging echocardiographic methods that can help physicians in the correct diagnostic and pathophysiological assessment of patients with HCM

Improved permeability prediction based on the feature engineering of petrophysics and fuzzy logic analysis in low porosity–permeability reservoir

Abstract Permeability is difficult to evaluate in reservoir petrophysics property, especially in low porosity–permeability reservoir. The conventional permeability estimation model with establishment of the regression relationship between permeability and porosity is not applicable. This regression hypothesis based on the correlation between porosity and permeability (logarithm) is not available in low porosity–permeability reservoir. It remains a challenging problem in tight and heterogeneous formations’ petrophysical interpretation. Feature engineering process, as the most significant procedure in data-driven analytics, indicates that accurate modelling should be based on the main control factor on permeability ignoring its concrete mathematical expression. To select the factors that influence the main function of the model, and use the appropriate model to carry out the model structure, fusion and optimization is the main task to permeability estimation in low porosity–permeability reservoirs. Fuzzy logic, as a widely used approach in estimation of permeability, can be used to estimate the permeability with the advantage of tolerance. Its good adaptation in objective contradictory concepts and false elements in computational processes outweighs the traditional method on permeability estimation which always lies in a wide distribution of orders of magnitude. The research takes the permeability estimation issue in Mesozoic strata, Gaoqing area as example. The area of study mainly contains reservoirs with low-to-ultra-low porosity–permeability. The relationship between porosity and permeability is somewhat certain but insufficient using the regression method to predict. The research combined specialized feature engineering process with the fuzzy logic analysis to predict permeability. First, this paper analyzes that the main control factors of permeability in the region is the homogenization by diagenetic with statistical multivariate variance analysis SNK (Student–Newman–Keuls) method. It can be characterized by $$\varDelta {\varphi }$$ Δφ , the changing degrees of porosity. To characterize the permeability response in well logs, the variables standing for a comprehensive reflection of the formation hydrology, lithology, and diagenesis are selected in the result of the electrofacies, SP, LLS, AC by multivariate variable selection method. The study is trying to combine the logging principle to explain its physical meaning by the statistical results. For discrete variables like electrofacies in modelling, scale quantization should be conducted by the optimal scale analysis considering discrete variables influences on permeability instead of manual labelling by numbers. Finally, the fuzzy logic analysis is carried out to achieve the results. The study makes a comparison of results in three ways to indicate the importance of feature engineering. That is, improved results with optimized model, model without feature engineering, and ordinary regression model. The optimized model with feature engineering predicts the permeability more conformed to the core data

Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions

Hydrological models have been widely used to predict runoff in regions with observed discharge data, and regionalization methods have been extensively discussed for providing runoff predictions in ungauged basins (PUB), especially during the PUB decade (2003–2012). Great progress has been achieved in the field of regionalization in previous studies, in which different hydrological models have been coupled with various regionalization methods. However, different conclusions have been drawn due to the use of different hydrological models, regionalization methods, and study regions. In this study, we assessed the performance of the five most widely used regionalization methods (spatial proximity with parameter averaging option (SP-par), spatial proximity with output averaging option (SP-out), physical similarity with parameter averaging option (Phy-par), physical similarity with output averaging option (Phy-out), and regression methods (PCR)) and four daily rainfall-runoff models (GR4J, WASMOD, HBV and XAJ, with 6, 8, 13, and 17 parameters, respectively) at the same time. Our aim was to evaluate how the performance of the regionalization methods depends on (a) the selection of hydrological models, (b) nonstationary climate conditions, and (c) different climatic regions. This investigation used data from 86 independent catchments evenly distributed throughout Norway, covering three different climate zones (oceanic, continental and polar tundra) according to the Köppen-Geiger classification. The results showed that (a) the SP-out and Phy-out methods performed better than the SP-par and Phy-par for all the hydrological models, and the regression method performed worst in most cases; (b) the difference between the parameter averaging option and the output averaging option is positively related to the number of hydrological model parameters, i.e. the greater the number of parameters, the larger the difference between the two options; (c) the XAJ model with the greatest number of parameters produced the best results in most cases, and models with fewer parameters tend to produce similar performance for the different regionalization methods; (d) models with more parameters displayed larger declines in performance than those with fewer parameters for nonstationary conditions; and (e) clear differences in the performance of the regionalization methods exist among the three climatic regions. This study provides insight into the relationship between the complexity of hydrological models and regionalization methods in cold and seasonally snow-covered regions