The choice of adhesive for the production of yarn glue method

It is proposed to use sericin, a component of silkworm cocoons, as an adhesive compound for the production of yarn by the adhesive method. An experiment was conducted to study the dependence of the adhesion forces of the binder to cellulose on the concentration of the adhesive substance on the example of solutions of PVA, PVA and sericin. A comparative analysis of this dependence is carried out. Mathematical models are constructed to predict the strength of the adhesive joint depending on the concentration of the adhesive composition. The calculation of the adhesion forces per one elementary fiber is carried out.

Experimental modeling of the interaction of hard and aeriform body and the onset of a drag crisis with a significant change in velocity

The paper deals with the possibilities and prospects of experimental modeling of the interaction of a solid and a gaseous body. It is assumed that reliable experimental data have already been obtained and published. The problem of approximating the complex aerodynamic characteristics of air flow around a spherical body is posed and solved. The study was carried out using the «Cut-Glue» method for approximating numerical information about blowing experiments. Generally, this information reflects the dependence of the drag coefficient on the Reynolds number. The choice of the Cut-Glue method for the approximation of complex, multiextremal characteristics that can be obtained in physical experiments is substantiated.

Improving computational efficiency of GLUE method for hydrological model uncertainty and parameter estimation using CPU-GPU hybrid high performance computer cluster

The Generalized Likelihood Uncertainty Estimation (GLUE) method has been thrived for decades, huge number of applications in the field of hydrological model have proved its effectiveness in uncertainty and parameter estimation. However, for many years, the poor computational efficiency of GLUE hampers its further applications. A feasible way to solve this problem is the integration of modern CPU-GPU hybrid high performance computer cluster technology to accelerate the traditional GLUE method. In this study, we developed a CPU-GPU hybrid computer cluster-based highly parallel large-scale GLUE method to improve its computational efficiency. The Intel Xeon multi-core CPU and NVIDIA Tesla many-core GPU were adopted in this study. The source code was developed by using the MPICH2, C++ with OpenMP 2.0, and CUDA 6.5. The parallel GLUE method was tested by a widely-used hydrological model (the Xinanjiang model) to conduct performance and scalability investigation. Comparison results indicated that the parallel GLUE method outperformed the traditional serial method and have good application prospect on super computer clusters such as the ORNL Summit and Sierra of the TOP500 super computers around the world.

Relationship Between Rainfall Duration and Sewer System Performance Measures Within the Context of Uncertainty

Urbanization and climate change have resulted in an increase in catchment runoff, often exceeding the designed capacity of sewer systems. The decision to modernize a sewer system should be based on appropriate criteria. In engineering practice, the above is commonly achieved using a hydrodynamic model of the catchment and the simulation of various rainfall events. The article presents a methodology to analyze the effect of rainfall characteristics parametrized with intensity-duration-frequency (IDF) curves in regard to performance measures of sewerage networks (flood volume per unit impervious surface and share of overfilled manholes in the sewerage network) accounting for the model uncertainty determined via the generalized likelihood uncertainty estimation (GLUE) method. An urban catchment was modeled with the Storm Water Management Model (SWMM). Analyses showed that the model uncertainty exerts a large impact on certain measures of sewage network operation. Therefore, these measures should be analyzed in similar studies. This is very important at the stage of decision making in regard to the modernization and sustainable development of catchments. It was found that among the model parameters, the Manning roughness coefficient of sewer channels yields a key impact on the specific flood volume, while the area of impervious surfaces yields the greatest impact on the share of overflowed manholes.

Improving Efficiency of Hydrological Prediction Based on Meteorological Classification: A Case Study of GR4J Model

Distribution of hydrological parameters is varied under contrasting meteorological conditions. However, how to determine the most suitable parameters on a predefined meteorological condition is challenging. To address this issue, a hydrological prediction method based on meteorological classification is established, which is conducted by using the standardized runoff index (SRI) value to identify three categories, i.e., the dry, normal and wet years. Three different simulation schemes are then adopted for these categories. In each category, two years hydrological data with similar SRI values are divided into a set; then, one-year data are used as the calibration period while the other year is for testing. The Génie Rural à 4 paramètres Journalier (GR4J) rainfall-runoff model, with four parameters x1, x2, x3 and x4, was selected as an experimental model. The generalized likelihood uncertainty estimation (GLUE) method is used to avoid parameter equifinality. Three basins in Australia were used as case studies. As expected, the results show that the distribution of the four parameters of GR4J model is significantly different under varied meteorological conditions. The prediction efficiency in the testing period based on meteorological classification is greater than that of the traditional model under all meteorological conditions. It is indicated that the rainfall-runoff model should be calibrated with a similar SRI year rather than all years. This study provides a new method to improve efficiency of hydrological prediction for the basin.

PERBANDINGAN METODE SIRKUMSISI MODERN (KLAMP DAN LEM) TERHADAP PROSES PENYEMBUHAN LUKA PASCA SIRKUMSISI PADA ANAK

Circumcision is a minor surgical procedure permormed as a modification of part the body by making an incision in the prepurtium of a part of the body by making incision in the prepurtium. The prepurtium that has not been circumcised has bacterial colonies which are risk factor for urinary tract infections. The insidence rate of urinary tract infections in Indonesia in infants who have not been circumcised under 1 year is 35% and children over 1 year are 22% of 200 children. The tecnology that eveloved in circumcision from the conventional methode of suture has shifted to the modern method of seamless circumcision. This study aims to compare the clamp and glue methods to the wound healing process after circumcision in chlidren. The research method was cohort with comparative statistical analysis of Pvalue 0.000<0.05 so there is a significant difference between the result of the klamp method ang glue in the healing process. Where the wound healing process in the glue method is much faster than the klamp method because it is more optimal in the hemostasis and inflammation phase because there are no foreign object namely the klamp. Keywords: Modern circumcision, Klamp, Glue, Wound Healing.

Parallel Hydrological Model Parameter Uncertainty Analysis Based on Message-Passing Interface

Parameter uncertainty analysis is one of the hot issues in hydrology studies, and the Generalized Likelihood Uncertainty Estimation (GLUE) is one of the most widely used methods. However, the scale of the existing research is relatively small, which results from computational complexity and limited computing resources. In this study, a parallel GLUE method based on a Message-Passing Interface (MPI) was proposed and implemented on a supercomputer system. The research focused on the computational efficiency of the parallel algorithm and the parameter uncertainty of the Xinanjiang model affected by different threshold likelihood function values and sampling sizes. The results demonstrated that the parallel GLUE method showed high computational efficiency and scalability. Through the large-scale parameter uncertainty analysis, it was found that within an interval of less than 0.1%, the proportion of behavioral parameter sets and the threshold value had an exponential relationship. A large sampling scale is more likely than a small sampling scale to obtain behavioral parameter sets at high threshold values. High threshold values may derive more concentrated posterior distributions of the sensitivity parameters than low threshold values.

A Successful Approach of the First Ecological Compensation Demonstration for Crossing Provinces of Downstream and Upstream in China

As the first pilot provincial water environmental compensation set up at the national level, the Xin’anjiang River Basin plays a very important exemplary and guiding role in the ecological compensation of transboundary basins in China. There is no paper evaluating the environmental performance in watershed scale after getting rid of the natural factor’s effect. Here we issue a new approach to evaluate it, combing the SPAtially Referenced Regression On Watershed attributes (SPARROW) models and data envelopment analysis (DEA) method, based on counterfactual scenarios. After ecological compensation, the results show that the decrease of total nitrogen (TN) non-point source export coefficient was stable (17.16–17.78% in different sources), while that of total phosphorus (TP; 8.51–17.75%) and permanganate index (CODMn; 13.10–21.41%) was not. The projects of fertilizer application’s effects were relatively obvious; on average, the decreases of the export coefficients were 17.16%, 17.75%, and 21.41% in TN, TP, and CODMn models, respectively, showing the importance of eco-compensation regulation, not only in non-point source pollution reduction but also resulting in high levels of eco-compensation efficiencies, especially in scale efficiencies. By assessing parameter and modeling uncertainty with the use of the generalized likelihood uncertainty estimation (GLUE) method, the models’ structure well represents the hydrological behavior. This study also provides policymakers with a new perspective in accurately measuring the impact of environmental performance, to guide the next step of environmental investment optimization.

Uncertainty Assessment of Urban Hydrological Modelling from a Multiple Objective Perspective

The uncertainty assessment of urban hydrological models is important for understanding the reliability of the simulated results. To satisfy the demand for urban flood management, we assessed the uncertainty of urban hydrological models from a multiple-objective perspective. A multiple-criteria decision analysis method, namely, the Generalized Likelihood Uncertainty Estimation-Technique for Order Preference by Similarity to Ideal Solution (GLUE-TOPSIS) was proposed, wherein TOPSIS was adopted to measure the likelihood within the GLUE framework. Four criteria describing different urban stormwater characteristics were combined to test the acceptability of the parameter sets. The TOPSIS was used to calculate the aggregate employed in the calculation of the aggregate likelihood value. The proposed method was implemented in the Storm Water Management Model (SWMM), which was applied to the Dahongmen catchment in Beijing, China. The SWMM model was calibrated and validated based on the three and two flood events respectively downstream of the Dahongmen catchment. The results showed that the GLUE-TOPSIS provided a more precise uncertainty boundary compared with the single-objective GLUE method. The band widths were reduced by 7.30 m3/s in the calibration period, and by 7.56 m3/s in the validation period. The coverages increased by 20.3% in the calibration period, and by 3.2% in the validation period. The median estimates improved, with an increase of the Nash–Sutcliffe efficiency coefficients by 1.6% in the calibration period, and by 10.0% in the validation period. We conclude that the proposed GLUE-TOPSIS is a valid approach to assess the uncertainty of urban hydrological model from a multiple objective perspective, thereby improving the reliability of model results in urban catchment.