Stability Evaluation of a Toppling Deformed Body in Miaowei Hydropower Station

By analyzing the instability characteristics of deformed body after impoundment and using limit equilibrium algorithm and UDEC discrete element simulation, the failure mechanism and stability of deformed body are studied in the paper. According to the deformation degree and instability characteristics of the deformed body in different storage periods, the mechanism of instability is analyzed. Based on the regional topographic map, a two-dimensional limit equilibrium model is established to calculate the potential failure surface range and slope stability factor of QD18 deformed body under the conditions of 1314m, 1364m and 1401m water level storage. And the displacement nephogram, velocity nephogram and rock block deformation map of the deformed body under the condition of 1401 m water level are simulated by using the discrete element software, and the stress changes of each part of the deformed body after water storage are analyzed, and the failure mechanism is summarized

Analysis of the Metals in Soil-Water Interface in a Manganese Mine

In order to reveal the influence of the metals of soil-water interface in a manganese mine (Xiangtan, China), on local water environment, there are six kinds of metals (Mn, Ni, Cu, Zn, Cd, and Pb) characterized by measuring their concentration, correlation, source, and special distribution using principal component analysis, single factor, and Nemero comprehensive pollution index. The results showed that the corresponding average concentration was 0.3358, 0.045, 0.0105, 0.0148, 0.0067, and 0.0389 mg/L. The logarithmic concentration of Mn, Zn, and Pb was normal distribution. The correlation coefficients (between Mn and Pb, Mn and Zn, Mn and Ni, Cu and Zn, Cu and Pb, and Zn and Cd) were found to range from 0.5 to 0.6, and those between Cu and Ni and Cu and Cd were below 0.3. It was found that Zn and Mn pollution were caused primarily by ore mining, mineral waste transportation, tailing slag, and smelting plants, while Cu and Ni mainly originate from the mining industry activities and the traffic transportation in the mining area. In addition, the Cd was considered to be produced primarily from the agricultural or anthropogenic activities. The pollution indexes indicated that metal pollution degree was different in soil-water interface streams as listed in increasing order of pollution level as Zn > Ni > Cu > Pb > Mn > Cd. For all of the pollution of the soil-water interface streams, there was moderate metal pollution but along the eastern mine area the pollution seemed to get more serious. There was only a small amount of soil-water interface streams not contaminated by the metals

Analysis of the Metals in Soil-Water Interface in a Manganese Mine

In order to reveal the influence of the metals of soil-water interface in a manganese mine (Xiangtan, China), on local water environment, there are six kinds of metals (Mn, Ni, Cu, Zn, Cd, and Pb) characterized by measuring their concentration, correlation, source, and special distribution using principal component analysis, single factor, and Nemero comprehensive pollution index. The results showed that the corresponding average concentration was 0.3358, 0.045, 0.0105, 0.0148, 0.0067, and 0.0389 mg/L. The logarithmic concentration of Mn, Zn, and Pb was normal distribution. The correlation coefficients (between Mn and Pb, Mn and Zn, Mn and Ni, Cu and Zn, Cu and Pb, and Zn and Cd) were found to range from 0.5 to 0.6, and those between Cu and Ni and Cu and Cd were below 0.3. It was found that Zn and Mn pollution were caused primarily by ore mining, mineral waste transportation, tailing slag, and smelting plants, while Cu and Ni mainly originate from the mining industry activities and the traffic transportation in the mining area. In addition, the Cd was considered to be produced primarily from the agricultural or anthropogenic activities. The pollution indexes indicated that metal pollution degree was different in soil-water interface streams as listed in increasing order of pollution level as Zn > Ni > Cu > Pb > Mn > Cd. For all of the pollution of the soil-water interface streams, there was moderate metal pollution but along the eastern mine area the pollution seemed to get more serious. There was only a small amount of soil-water interface streams not contaminated by the metals

Benchmark experiment with iron slab by Time-of-flight technique at CIAE

In order to validate the evaluated nuclear data, leakage spectra in the range of 0.8 to 15 MeV from samples were measured by time-of-flight (TOF) technique using a D-T neutron source. An experimental system for benchmark validation of nuclear data with slab samples has been set up at China Institute of Atomic Energy (CIAE). In this study, test samples are iron slabs, of which the thickness are 5cm, 10cm and 15cm, and the measured angles were chosen to be about 60° and 120°. By comparing measured leakage spectrum with calculated ones by MCNP-4C code, using the data from the CENDL-3.1, ENDF/B-VIII.0, JENDL-4.0 and JEFF-3.3 nuclear data files, and the comparison was made by the spectrum shape and by the C/E values in different energy regions

Benchmark experiment with iron slab by Time-of-flight technique at CIAE

In order to validate the evaluated nuclear data, leakage spectra in the range of 0.8 to 15 MeV from samples were measured by time-of-flight (TOF) technique using a D-T neutron source. An experimental system for benchmark validation of nuclear data with slab samples has been set up at China Institute of Atomic Energy (CIAE). In this study, test samples are iron slabs, of which the thickness are 5cm, 10cm and 15cm, and the measured angles were chosen to be about 60° and 120°. By comparing measured leakage spectrum with calculated ones by MCNP-4C code, using the data from the CENDL-3.1, ENDF/B-VIII.0, JENDL-4.0 and JEFF-3.3 nuclear data files, and the comparison was made by the spectrum shape and by the C/E values in different energy regions

Discovery of potent and selective urea-based ROCK inhibitors: Exploring the inhibitor’s potency and ROCK2/PKA selectivity by 3D-QSAR, molecular docking and molecular dynamics simulations

[Display omitted] An activity model and a selectivity model from 3D-QSAR studies were established by CoMFA and CoMSIA to explore the SAR. Then docking was used to study the binding modes between ligand and kinases (ROCK2 and PKA), and the molecular docking results were further validated by MD simulations. Computational results suggested that substitution containing positive charge attached to the middle phenyl ring, or electropositive group in urea linker was favored for both activity and ROCK2/PKA selectivity. Finally, three compounds were designed, and biological evaluation demonstrated that these molecular models were effective for guiding the design of potent and selective ROCK inhibitors

Discovery of bis-aryl urea derivatives as potent and selective Limk inhibitors: Exploring Limk1 activity and Limk1/ROCK2 selectivity through a combined computational study

[Display omitted] Lim kinase (Limk), a proline/serine-rich sequence, can regulate the polymerization of the actin filaments by phosphorylating, and it is found to be highly involved in various human diseases. In this paper, 47 reported Limk1 inhibitors with bis-aryl urea scaffold were used to design potent and selective Limk inhibitors by computational approaches. Firstly, the structure-Limk1 activity relationship models (3D-QSAR) and structure-Limk1/ROCK2 selectivity relationship models (3D-QSSR) were developed and both 3D-QSAR and 3D-QSSR models showed good correlative and predictive abilities. Then, the molecular docking and molecular dynamics (MD) simulations were employed to validate the optimal docking conformation and explore the binding affinities. Finally, five new compounds were designed and all of them exhibited good Limk1 inhibition and Limk1/ROCK2 selectivity after synthesis and biological evaluation, which demonstrated that the obtained information from computational studies were valuable to guide Limk inhibitors’ design

A risk prediction model for efficient intubation in the emergency department: A 4‐year single‐center retrospective analysis

Abstract Objective To analyze the risk factors associated with intubated critically ill patients in the emergency department (ED) and develop a prediction model by machine learning algorithms. Methods This study was conducted in an academic tertiary hospital in Hangzhou, China. Critically ill patients admitted to the ED were retrospectively analyzed from May 2018 to July 2022. The demographic characteristics, distribution of organ dysfunction, parameters for different organs’ examination, and status of mechanical ventilation were recorded. These patients were assigned to the intubation and non‐intubation groups according to ventilation support. We used the eXtreme Gradient Boosting (XGBoost) algorithm to develop the prediction model and compared it with other algorithms, such as logistic regression, artificial neural network, and random forest. SHapley Additive exPlanations was used to analyze the risk factors of intubated critically ill patients in the ED. Results Of 14,589 critically ill patients, 10,212 comprised the training group and 4377 comprised the test group; 2289 intubated patients were obtained from the electronic medical records. The mean age, mean scores of vital signs, parameters of different organs, and blood oxygen examination results differed significantly between the two groups (p < 0.05). The white blood cell count, international normalized ratio, respiratory rate, and pH are the top four risk factors for intubation in critically ill patients. Based on the risk factors in different predictive models, the XGBoost model showed the highest area under the receiver operating characteristic curve (0.84) for predicting ED intubation. Conclusions For critically ill patients in the ED, the proposed model can predict potential intubation based on the risk factors in the clinically predictive model