Development of Technology of Arsenic Removal from Acidic Waste Solutions in the Form of Arsenic Trisulfide

During the laboratory tests the conditions of arsenic removal from acidic waste solutions of metallurgical enterprise in the form of arsenic trisulfide were determined. The technology based on the reduction of pentavalent arsenic to trivalent state with sodium pyrosulfite solution and following arsenic trisulfide precipitation from acidic solution after treatment with sodium sulfide solution was proposed. The arsenic removal proceeds with mechanical stirring, dosing the calculated amounts of reagents and collecting emissions of hydrogen sulfide. With such treatment, about 95% of arsenic, which was in the initial solution, passes into the precipitate. An enlarged laboratory experiment was carried out and the precipitate with 42.6% of arsenic and 46.9% of sulfur was obtained. The precipitate yield was ∼25.7 kg (dry weight) out of 1 m3 of the initial arsenic containing solution. Keywords: arsenic, arsenic trisulfide, acidic waste solutions, sodium sulfide, sodium pyrosulfit

Training algorithms for artificial neural network in predicting of the content of chemical elements in the upper soil layer

Models based on Artificial Neural Networks (ANN) in recent years are increasingly being used in environmental studies. Among the many types of ANN, the network type Multilayer Perceptron (MLP) has become most widespread. Such networks are universal, simple, and suitable for most tasks. The main problem when modelling using MLP is the choice of the learning algorithm. In this paper, we compared several learning algorithms: Levenberg-Marquart (LM), LM with Bayes regularization (BR), gradient descent (GD), and GD with the speed parameter setting (GDA). The data for modelling were taken from the results of the soil screening of an urbanized area. The spatial distribution of the chemical element Chromium (Cr) in the surface layer of the soil was simulated. The structure of the MLP network was chosen using computer simulations based on minimization of the root mean squared error (RMSE). The model using the LM training algorithm showed the best accuracy. © 2018 Author(s)

Statistical analysis of the spatial distribution of impurities in the snow cover in the vicinity of copper mine in the Middle Ural of Russia

Statistical analysis of the monitoring data of industrial enterprises influence zones is an important part of the researches related to natural environment changes. In present study, a cluster analysis of the elemental composition of the snow cover in the vicinity of a copper mine was carried out. The data were obtained as a result of the chemical analysis of the snow samples collected during annual environmental monitoring in the region of Rezh town (the Middle Ural of Russia), where Safyanovsky Copper Mine and Rezhevsky Nickel Plant are located. The elements identified by chemical analysis were grouped according to the strength of the correlation bond. The cluster analysis of these groups made it possible to identify and separate the influence zones of the Plant, Mine and other industrial objects located in the area. The obtained results became the basis for adjusting the snow cover monitoring scheme. © 2018 Author(s).The research is supported by the project of the Ural Branch of Russian Academy of Sciences No. 18-5-2345-56

Mucociliary clearance and microbiota of the nasal passages, sinuses in patients with chronic rhinosinusitis associated with gastroesophageal reflux disease

The aim of our investigation was to estimate the mucociliary clearance (MC), the spectrum of bacterial communities discharged from the middle meatus and sinus aspirates in patients with chronic rhinosinusitis (CRS) associated with gastroesophageal reflux disease (GERD), patients with CRS without GERD and healthy volunteers. The study included 30 patients with CRS and GERD, 34 patients without GERD аnd 30 healthy volunteers. Association with CRS and GERD was characterized by statistically significant slowing of MC and quantitative and qualitative changing of characteristics of the nasal mucosa microflora, but not of the paranasal sinuses. In the group of patients with CRS with GERD, MC amounted to 28.5 ± 4.7 min, in the group without GERD - 23.6 ± 2.7 min, in the healthy group - 5.8 ± 1 min. S. аureus (р = 0.009), E. mli (р = 0.029) and Candida albicans (р = 0.013) were detected in the mucosa of the middle meatus of patients with CRS and GERD more than in patients with CRS without GERD. No significant differences in the microflora of the paranasal sinus aspirate were revealed

High variation subarctic topsoil pollutant concentration prediction using neural network residual kriging

The work deals with the application of neural networks residual kriging (NNRK) to the spatial prediction of the abnormally distributed soil pollutant (Cr). It is known that combination of geostatistical interpolation approaches (kriging) and neural networks leads to significantly better prediction accuracy and productivity. Generalized regression neural networks and multilayer perceptrons are classes of neural networks widely used for the continuous function mapping. Each network has its own pros and cons; however both demonstrated fast training and good mapping possibilities. In the work, we examined and compared two combined techniques: generalized regression neural network residual kriging (GRNNRK) and multilayer perceptron residual kriging (MLPRK). The case study is based on the real data sets on surface contamination by chromium at a particular location of the subarctic Novy Urengoy, Russia, obtained during the previously conducted screening. The proposed models have been built, implemented and validated using ArcGIS and MATLAB environments. The networks structures have been chosen during a computer simulation based on the minimization of the RMSE. MLRPK showed the best predictive accuracy comparing to the geostatistical approach (kriging) and even to GRNNRK. © 2017 Author(s)

Attributive portrait of human’s internal qualities in Russian and Chinese linguistic culture

The article is devoted to the problem of studying the attributive portrait of human’s internal qualities in Russian and Chinese linguistic culture via analysis of language material; comparison; methods of classification, generalization, and differentiation. As a result, when a person is calm, fluid, flexible in his actions, it indicates his sensitivity and therefore impartiality. In conclusion, in Russian linguacultural there are more units with a positive assessment of the individua

Difficulties of iron-deficiency anemia diagnostics

The aim of clinical case presentation. To illustrate difficulties of detection of sources of gastro-intestinal bleeding (GIB) at investigation of patient with severe chronic iron-deficiency anemia.Key points. At the moment of hospital admission in obvious cause of GIB has not been revealed. At complex investigation potential sources of blood loss were found out: hiatal hernia (HH) and diverticula of the large intestine. Pathology data in some cases are complicated both by overt clinical GIB, and microlosses. Presented case illustrates extremely high adaptive potential of female body to chronic blood loss - patient continued to work down to the moment of hospital admission. Definite feature of presented case is the dissociation between severity of anemia and absence of clinical symptoms of HH and diverticular disease.Conclusion. Presented case emphasizes exclusive importance of control of total blood count in women in postmenopausal period and necessity in prophylactic medical examination of patients