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Estimating the spectral response of vegetation using unmanned aerial vehicle sensors for non-destructive remote sensing represents a key element for monitoring crop growth and development. Given the extensive presence of commercial unmanned aerial vehicle (UAV) based solutions on the market, there is a need for clear information on the performance of these products to guide the end user in their selection and use for precision agriculture applications. The aim of this paper is to compare and evaluate the effectiveness of supporting the practical application of remote sensing methods using DJI P4M and senseFly eBee X UAVs in the production of the crop barley. The features of these commercial UAVs and the results of their application are described. The NDVI indices were calculated when processing survey data from both unmanned aerial vehicles. Based on the results, the r-Pearson correlation of the two UAVs was calculated to be between 0.78 and 0.80. Also, the block diagram showing the processing of the results of barley crop survey by means of two UAVs under study was developed. As a result of the comparative analysis of the two UAVs, senseFly eBee X proved to be the best in most indicators. [ABSTRACT FROM AUTHOR]

Under conditions of changing climate, unsustainable use of agricultural land and increasing anthropogenic pressure on the environment, the natural bioproductivity of the soil is being lost. The integration of geographic information systems (GIS) and remote sensing has been shown to promote precision farming technology and sustainable land use practices. In this study, based on the Revised Universal Soil Loss Equation (RUSLE) method, a digital elevation model of an experimental site in eastern Kazakhstan was developed. It was found that one of the main causes of erosion is critically low content of humus in the soil in the range of 0.82-1.66 %, so the use of spatial modelling methods can help determine the best management practices to reduce and prevent soil erosion and improve its quality by increasing the content of humus in the soil. Calculations of actual soil losses after gully formation, which amount to about 185 ha of land, have been made; a predictive model of the relief of the study area and increase of humus content to 3.5-5% with the proposed fertility restoration measures has been developed to prevent further soil erosion, preserve and restore fertility. [ABSTRACT FROM AUTHOR]

This paper presents the results of testing certain remote sensing indices (vegetation health index, temperature index, normalized drought difference index, and others). Multitemporal data of nine indices from Sentinel-2 and MODIS satellites for the vegetation period over 5 years were used to simulate the spring wheat yield of the Experimental farm of oilseeds. Results of spring wheat yield modeling have shown that the range of mean absolute error (MAE) values was 3.2 to 3.7, and fit index (d) values were 0.78 to 0.86. It was found that the best model R2 = 0.53 based on NDWI, VSDI, and NDVI indices can serve as the most effective predictor for monitoring and forecasting spring wheat yields in eastern Kazakhstan. [ABSTRACT FROM AUTHOR]

The study of agricultural production and land use in the north-east of Kazakhstan is based on the data obtained after processing medium spatial resolution space images of Kazakh (KazEOSat-2, KazSTSat) and foreign (Sentinel-2, Landsat-8) satellites for the period from May to September 2017 - 2021. It is shown that the use of methods of objective remote sensing allows for comprehensive monitoring of agricultural land of the country. The authors have developed scientifically substantiated methods of evaluation of the main indicators of pastures with a total area of 8,127,000 ha and crops with an area of 1,211,000 ha in the steppe and arid-steppe zones of Pavlodar region of Kazakhstan. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to planning experiments for hydrometallurgical processing of gold from waste printed circuit boards of cell phones by aqueous thiourea solution with and without ultrasound exposure. It is established that the use of the probabilistic-deterministic approach to the planning of experiments significantly reduces the consumption of resources and energy by reducing the number of experiments. It is shown that the models obtained using the probabilistic-deterministic approach of Malyshev V.P. allow forecasting the gold extraction from the electronic waste with sufficient accuracy. Obtained the values of gold recovery under the optimal conditions calculated by simulation which were 84.66% without ultrasound and 91.46% with ultrasound, respectively. The experimental gold recovery under optimal conditions was 79.6% without ultrasound and 88.2% with ultrasound. The correlation coefficient of the ultrasonic leaching model was R = 0.87, with a significance of the correlation coefficient tR = 12.34 > 2. The correlation coefficient of the leaching model without ultrasound was R = 0.86; the significance of the correlation coefficient tR = 11.5 > 2. Evaluating the influence of each factor individually and in aggregate to find the optimal process parameters, we built a mathematical model of the dependence of leaching and the degree of extraction of gold from e-waste. [ABSTRACT FROM AUTHOR]

Orthopaedic surgery is becoming increasingly common due to recent significant improvements in medical imaging, biomechanical modelling, and additive manufacturing. For the pelvis, surgical reconstruction using metal implants remains challenging due to the involvement of complex anatomical structures. In Kazakhstan, these operations are performed using typical implants. The purpose of the present work is to develop a spersonalised implant and its real application to work out the procedure and master the technology. This article describes all the relevant stages, from medical imaging to an accurate three-dimensional anatomical model of the implant. This described procedure can also be fundamental for virtual preoperative planning and the development of patient-specific incision guides. [ABSTRACT FROM AUTHOR]

This study aims to develop a method for modelling early forecasting of alfalfa yield on a farm scale located in East Kazakhstan. The authors evaluated the correlation coefficient between forage crop yield and different data sets, including weather data, climate indices, spectral indices from drones and satellite observations. An ensemble machine learning model was developed by combining three commonly used basic training modules: random forest (RF), support vector method (SVM), and multiple linear regression (MLR). It is found that the best yield prediction algorithm in this study is the Random Forest (RF) algorithm, which predicts yields with R2 = 0.94 and RMSE = 0.25 t/ha. The results of this study showed that combining remote sensing drought indices with climatic and weather variables from UAV and satellite imagery using machine learning is a promising approach for alfalfa yield prediction. [ABSTRACT FROM AUTHOR]

In this work, the authors proposed a method of determining the yield of spring wheat based on the analysis of the dynamics of spectral parameters of its growth and development, determined by multispectral satellite images. It was found that by processing the satellite images of the fields in selected spectral regions, it is possible to estimate with a high degree of reliability the productivity of plants, biomass value, photosynthesis intensity and other parameters. By means of mathematical processing of the statistical data array of phosphorus, potassium and nitrogen content in the soil according to the Remote Sensing (RS) data in comparison with the actual data obtained after agrochemical analysis of soil samples, the total value of the average error (the average absolute error ranging from 24 to 36 % for the analysed period) was calculated. Using remote sensing data and Convolutional Neural Networks (CNN), the forecast of spring wheat yield in the conditions of soil and climatic zone of Eastern Kazakhstan was carried out. The results obtained with the predictive model are close to the actual yield results of the previous year (the error smaller than 9 %), indicating the relationship between yield and agrochemical analysis of the soil. [ABSTRACT FROM AUTHOR]

Observations of the dynamics of crop development using remote sensing data showed that in the spectral characteristics space, each crop species forms a compact cluster (a set of homogeneous photometric points) at a certain time and stage of development. It was found that derivation of images from satellite data by processing according to special algorithms in selected spectral regions allows studying plant productivity, biomass, photosynthesis intensity, and other parameters. In the present work, the authors developed a preliminary version of the algorithm for forecasting crop yield on the example of sunflower, which showed good accuracy. The method allows for early forecasting. Approximation of the dynamic curves corresponding to the values of the seven-day composite NDVI (Normalized Difference Vegetation Index) indices has been proposed using the Gaussian function and the Levenberg-Marquardt algorithm. The use of the approximating function for predicting the annual maximum NDVI on the arable land mask showed the magnitude of the average absolute prediction error depending on the predicted week ranging from 0.67 to 10.7 % per year in the evaluated period, which is acceptable accuracy for seasonal forecasts. [ABSTRACT FROM AUTHOR]

The article provides the outcomes of field experiments related to studying influence of plant growth stimulant “Fullerenol” (foliar application) when soybeans are cultivated under conditions of piedmont zone of East Kazakhstan on agricultural lands. The obtained results of soybeans foliar application by fullerene derivatives С60 enabled to identify the range of its concentration that have positive effect on biometric characteristics of soybeans herbage growth and indicate the need for further researches for improvement of concentrates compositions in order to strengthen growth stimulating functions. It has been observed that leaves, stems, and roots herbage are increased on 27-30 %, and when Fullerenol concentration 0.002 g/dm³ was used (from the entire range of concentrations), soybeans crop yield is increased by 8.51 %. [ABSTRACT FROM AUTHOR]

In this study, for remote recognition of crops of agroecosystems in Kazakhstan by methods of comparative and historical analogy with the active use of mathematical modelling, the yield indicator of agricultural crops was determined, their dynamic characteristics were studied to predict productivity. The parameters of the dynamicstatistical biomass model were determined separately for each region of the Republic of Kazakhstan based on training data for 21 y (2000 – 2021). The correlation coefficient between the calculated yield values and the official statistics is 0.84. According to the results of cross-validation, the correlation coefficient between the actual and predicted yield of spring wheat was ~ 0.70, which indicates a sufficient resistance of the model to the variability of meteorological conditions for the formation of the crop. [ABSTRACT FROM AUTHOR]

This article uses methods for predicting plant performance indicators in Kazakhstan. In the work, using deep learning, visualization of predicted indicators (indicators and others), statistics from predicted values and identified changes, time series have been developed. Sentinel satellite data and statistical indicators for the last few years for the agricultural territories of Kazakhstan are used as primary data. It is found that the upward trend in wheat quality, however, increases the size of fertilizers, variables based on the NDVI also significantly contribute to the forecasting model. It has been shown that the amount of applied fertilizer has stabilized in the past few years due to economic and environmental constraints, so NDVI-based models will become increasingly important for enhancing forecasting models. Four machine learning algorithms have been evaluated and compared, namely boosted regression trees (BRT) and support vector machine (SVM), to map and predict the field yield of the Experimental Oil Farm in East Kazakhstan using readily available additional data. Based on the results of the work, a forecast of crop yields and general statistical recommendations for increasing yields were obtained. [ABSTRACT FROM AUTHOR]

The article proposes an environmentally friendly method for processing industrial waste by the example of slags from the Balkhash copper smelting plant (Kazakhstan). The first stage involved copper extraction. The second stage is gold recovery. For a more complete extraction of copper, microwave activation was used at various stages of the process. As a result, the recovery of copper using microwave radiation was 91 %, zinc 87.2 % and iron 94 % and without copper 65.7 %, zinc 84.6 % and iron 93.4 %, respectively. Such efficiency of copper recovery allows using thiourea as a reagent for gold recovery and avoiding the use of cyanides. [ABSTRACT FROM AUTHOR]

The work comprises researches on studying the possibility to use Fluoro-Anhydrite - fluor-hydric acid production waste in building industry. The effect of the dispersion and the amount of the neutralising agent on the completeness of the neutralisation reaction of acid Fluoro-Anhydrite is investigated. A method for obtaining a synthanite from hydrofluoric acid production waste is proposed, including neutralisation of the waste with a lime-containing component, followed by grinding and separation of the binder, characterized in that the production waste is additionally denaturalised by its chemical activation with quicklime to pH 12 and a sulfate additive, followed by grinding to a specific surface area of 9,000 cm² /g. Ensuring that the pH level of the binder mixture reaches 10-12 leads to an improvement in the physical and technical properties of synthanite: an increase in strength by 3.5-4 times, a reduction in the setting time by up to 9-12 times. The possibility has been proved to produce М25 and М50 dry plasters intended for finishing work based on developed airhardening synthanite. It is recommended to use plasters inside the premises when air humidity is not higher than (60-70) %. [ABSTRACT FROM AUTHOR]

This article explores an environmentally friendly method of complex processing of printed circuit boards of cell phones in order to extract gold and other valuable components without cyanides. Thiourea was used as reagents for leaching gold and silver. A nitric acid-based solder solvent was used to separate the electronic components and gold plating from the printed circuit boards. To eliminate the harmful effect of copper on thiourea, the printed circuit boards were not crushed at the gold recovery stage. As a result, Ag 51 % and Au 89 % were extracted at t = 60 °C and a thiourea concentration of 12 g/L. The presented method is environmentally friendly in comparison with cyanide methods of gold recovery and effective in terms of the amount of gold recovery. [ABSTRACT FROM AUTHOR]

The article discusses the possibility of a new method for processing tin-containing raw materials using a renewable carbon source - rice husks. A review of the literature on this topic showed the absence of publications on the possibility of using unconventional reducing agents in tin metallurgy. The work is devoted to filling the gap in the study of the possibility of using rice husks as a reducing agent in tin metallurgy. The process of pyrolysis of rice husks and reduction of tin oxide using rice husks were compared with traditional reducing agents, coal and coke. Heating was carried out in an inert atmosphere (argon). Thermal effects were studied using thermogravimetric analysis and differential scanning calorimetry. The optimal heating rate (5 °C/min) with the maximum decomposition of rice husks (up to 82 %) was found experimentally. It was found that the reduction of SnO2 with coal and rice hulls begins already at ≥ 800 °C, while interaction with coke does not occur even at 900 °C and above. Rice husks have been proven a promising reductant for SnO2. [ABSTRACT FROM AUTHOR]

The use of metallurgical slag for the synthesis of ceramics is considered as an alternative way to manage this waste. A significant effect on the physic-mechanical characteristics of ceramic materials when metallurgical slags are added is exerted by the heat treatment mode. Aluminosilicates were used as the main raw material metallurgical slags of lead and copper production were used as an additive-regulator of the properties of ceramics. It is shown that the addition of slag leads to an increase in mechanical strength. It was established that the maximum mechanical strength of 73.43 MPa is possessed by a sample obtained from a mixture of zeolite-bentonite-copper slag in the proportions of 50% - 30% - 20%, at a moisture content of 15% after calcination at 1,000 °C. [ABSTRACT FROM AUTHOR]

Wastes from titanium-magnesium production are characterized by a variety of composition, properties and a wide range of applications. As a result of the research on industrial effluents utilization in titanium-magnesium production a technology was proposed that includes the separation of effluents by centrifugation into liquid and solid parts and the demineralization of the liquid part using vacuum evaporation. As a result of laboratory studies, the optimal composition of the building mixture was determined, which can be used to prepare new materials for the construction industry with high strength characteristics. Optimal cement-sand ratio in the charge of building mixture is 1:3, water-cement ratio is 0.4, thickened pulp of industrial wastes contains 100 - 240 g/dm³ of solid part. [ABSTRACT FROM AUTHOR]

This article provides an overview of methods for processing electronic waste (mobile phones, smartphones, printed circuit boards). The possibility of extracting tin from the waste of printed circuit boards of mobile phones using hydrochloric acid is shown. Established that the deposition of tin from the productive solution occurs due to cementation - an electrochemical displacement reaction between a cementing metal (aluminum) and a cemented ion (tin). The possibility of intensification of the process using a vibrating installation is evaluated. An environmentally friendly and efficient method for processing tin-containing electronic waste is proposed. [ABSTRACT FROM AUTHOR]

For ecological catalysis, including the purification of exhaust gases, the most promising are block catalysts. The synthesis of ceramic block catalyst carrier was carried out based on classical methods of powder metallurgy, in which moulding compounds were prepared from the starting materials in the form of powders, which were then extruded with thermal training at each stage. It is proposed to use ceramic block carriers synthesized from a mixture of natural Kazakhstan aluminosilicates and metallurgical slag of lead and copper production for environmental catalysis. The obtained results prove the possibility of extruding new materials for use as ceramic carriers for catalysts from a mixture of natural Kazakhstan's aluminosilicates and metallurgical slag of lead and copper production without additional preliminary chemical treatments. In works of other authors haven't found such combinations of components for the manufacture of catalysts. [ABSTRACT FROM AUTHOR]