On a role of quadruple component of magnetic field in defining solar activity in grand cycles

In this paper we revise our prediction of solar activity using a solar background magnetic field as a proxy by the inclusion of eigen vectors of solar magnetic waves produced by quadruple magnetic sources, in addition to the principal eigen modes generated by two-layer dipole sources (Zharkova et al., 2015). By considering the interference of two dipole and one quadruple waves we produce the revised summary curve for the last 400 years accounting for the additional minima of solar activity occurred at the beginning of 19th (Dalton minimum) and 20th centuries. Using the dynamo model with meridional circulation and selecting the directions of circulation for quadruple waves, we estimate the parameters of quadrupole waves best fitting the observations in the past grand cycle. The comparison shows that the quadruple wave has to be generated in the inner layer of the solar convective zone, in order to provide the additional minima observed in 19 and 20 centuries, thus, naturally accounting for Gleissberg centennial cycle. The dynamo wave simulated for the dipole and quadruple sources reveals much closer correspondence of the resulting summary curve derived from the principal components of magnetic field variations to the solar activity oscillations derived from the average sunspot numbers in the current grand cycle

Reply to comment on the paper “ on a role of quadruple component of magnetic field in defining solar activity in grand cycles” by Usoskin (2017)

In this communication we provide our answers to the comments by Usoskin (2017) on our recent paper (Popova et al, 2017a). We show that Principal Component Analysis (PCA) allows us to derive eigen vectors with eigen values assigned to variance of solar magnetic field waves from full disk solar magnetograms obtained in cycles 21–23 which came in pairs. The current paper (Popova et al, 2017a) adds the second pair of magnetic waves generated by quadruple magnetic sources. This allows us to recover a centennial cycle, in addition to the grand cycle, and to produce a closer fit to the solar and terrestrial activity features in the past millennium

Automatic linear measurements of the fetal brain on MRI with deep neural networks

Timely, accurate and reliable assessment of fetal brain development is essential to reduce short and long-term risks to fetus and mother. Fetal MRI is increasingly used for fetal brain assessment. Three key biometric linear measurements important for fetal brain evaluation are Cerebral Biparietal Diameter (CBD), Bone Biparietal Diameter (BBD), and Trans-Cerebellum Diameter (TCD), obtained manually by expert radiologists on reference slices, which is time consuming and prone to human error. The aim of this study was to develop a fully automatic method computing the CBD, BBD and TCD measurements from fetal brain MRI. The input is fetal brain MRI volumes which may include the fetal body and the mother's abdomen. The outputs are the measurement values and reference slices on which the measurements were computed. The method, which follows the manual measurements principle, consists of five stages: 1) computation of a Region Of Interest that includes the fetal brain with an anisotropic 3D U-Net classifier; 2) reference slice selection with a Convolutional Neural Network; 3) slice-wise fetal brain structures segmentation with a multiclass U-Net classifier; 4) computation of the fetal brain midsagittal line and fetal brain orientation, and; 5) computation of the measurements. Experimental results on 214 volumes for CBD, BBD and TCD measurements yielded a mean $L_1$ difference of 1.55mm, 1.45mm and 1.23mm respectively, and a Bland-Altman 95% confidence interval ($CI_{95}$) of 3.92mm, 3.98mm and 2.25mm respectively. These results are similar to the manual inter-observer variability. The proposed automatic method for computing biometric linear measurements of the fetal brain from MR imaging achieves human level performance. It has the potential of being a useful method for the assessment of fetal brain biometry in normal and pathological cases, and of improving routine clinical practice.Comment: 15 pages, 8 figures, presented in CARS 2020, submitted to IJCAR

A technique for determining a relationship between the prices of heat and electricity generated by CHP

A technique was developed to optimize operations of a combined heat and power (CHP) plant taking into account changes in thermal loads. The technique is based on determining the relationship between changes in the price of electricity and changes in the price of heat. The price range is determined, on the basis of which the Pareto-optimal set of decisions is built. This set of solutions helps to find options for technical solutions that ensure the competitiveness of CHP plant relative to single-product heat and power generating plants and the most effective option to choose. It is required to solve three optimization problems to construct a Pareto-optimal set of solutions: the problem of minimizing the price of electricity for a given heat price and the rate of return on investment, the problem of minimizing the energy price to determine the maximum heat price, and the problem of minimizing the exergy price to find the minimum boundary of the heat price range. The technique was tested on the example of a cogeneration gas turbine plant. The cogeneration gas turbine plant has a waste-heat boiler and a contact heat exchanger for heating the make-up network water. The heat price range for the investigated a cogeneration gas turbine plant has been determined. Optimization studies of the operating modes of a cogeneration gas turbine plant were carried out in this range with a certain step. The results obtained can be used to select the optimal technical solutions, select the optimal combination of circuit-parametric solutions that ensure the competitiveness of the products of a cogeneration gas turbine plant

Accounting for variable operation conditions when optimizing cogeneration GTU and CCGT

The paper deals with a new approach to mathematical modeling and optimization of cogeneration GTU and CCGT, taking into account the variable conditions of their work, developed at the ISEM SB RAS. An analysis was carried out of the features of using this approach in relation to the thermal power plants. According to this approach at mathematical modelling of the plant there are structural optimized parameters (affecting the design of the plant), mode optimized parameters (affecting the operation of the plant in the mode with partial thermal loads) and balancing parameters affecting solution of the system of equations in the nominal mode and in modes at partial loads The connection between the design calculation (at rated loads) and verification calculations (at partial thermal loads) is carried out through the structural characteristics of the plant elements, determined during the design calculation. Taking into account these features, the problem of optimization of continuously changing parameters of cogeneration TPP was formulated, focused on the use of the developed optimization method. New mathematical models of the elements of the thermal power plants have been created. Optimization technical and economic studies of the considered plants were carried out in relation to various climatic conditions

Microstructure and Phase Composition of the Two-Phase Ceramic Synthesized from Titanium Oxide and Zinc Oxide

We have made investigations of the phase formation and microstructure on the ceramics obtained from a starting nanopowder mixture with the weight ratio ZnO : TiO2 = 4 : 1. Ceramic is obtained at different sintering temperatures, namely, 948, 1223 and 1473 К. Using the characterization methods of electron microscopy, energy dispersive microanalysis and X-ray diffraction phase analysis it has been shown that the ceramics structure is consisted of two dispersed phases of Zn2TiO4 and ZnO with the grain sizes being in range 0,5-1 μm. It has been found also that, at ceramic`s sintering temperature of 1223 К, the solid phase interactions are completed with the structure ZnO : Zn2TiO4 ≈ 1 : 1,5 phase ratio

Microstructure and phase composition of the two-phase ceramic synthesized from titanium oxide and zinc oxide

We have made investigations of the phase formation and microstructure on the ceramics obtained from a starting nanopowder mixture with the weight ratio ZnO : TiO2 = 4 : 1. Ceramic is obtained at different sintering temperatures, namely, 948, 1223 and 1473 К. Using the characterization methods of electron microscopy, energy dispersive microanalysis and X-ray diffraction phase analysis it has been shown that the ceramics structure is consisted of two dispersed phases of Zn2TiO4 and ZnO with the grain sizes being in range 0,5-1 μm. It has been found also that, at ceramic`s sintering temperature of 1223 К, the solid phase interactions are completed with the structure ZnO : Zn2TiO4 ≈ 1 : 1,5 phase ratio

On the nature of citrate-derived surface species on Ag nanoparticles: insights from X-ray photoelectron spectroscopy

Citrate is an important stabilizing, reducing, and complexing reagent in the wet chemical synthesis of nanoparticles of silver and other metals, however, the exact nature of adsorbates, and its mechanism of action are still uncertain. Here, we applied X-ray photoelectron spectroscopy, soft X-ray absorption near-edge spectroscopy, and other techniques in order to determine the surface composition and to specify the citrate-related species at Ag nanoparticles 3 immobilized from the dense hydrosol prepared using room-temperature reduction of aqueous Ag+ ions with ferrous ions and citrate as stabilizer (Carey Lea method). It was found that, contrary to the common view, the species adsorbed on the Ag nanoparticles are, in large part, products of citrate decomposition comprising an alcohol group and one or two carboxylate bound to the surface Ag, and minor unbound carboxylate group; these may also be mixtures of citrate with lower molecular weight anions. No ketone groups were specified, and very minor surface Ag(I) and Fe (mainly, ferric oxyhydroxides) species were detected. Moreover, the adsorbates were different at AgNPs having various size and shape. The relation between the capping and the particle growth, colloidal stability of the high-concentration sol and properties of AgNPs is briefly considered

On the nature of citrate-derived surface species on Ag nanoparticles: insights from X-ray photoelectron spectroscopy

Citrate is an important stabilizing, reducing, and complexing reagent in the wet chemical synthesis of nanoparticles of silver and other metals, however, the exact nature of adsorbates, and its mechanism of action are still uncertain. Here, we applied X-ray photoelectron spectroscopy, soft X-ray absorption near-edge spectroscopy, and other techniques in order to determine the surface composition and to specify the citrate-related species at Ag nanoparticles 3 immobilized from the dense hydrosol prepared using room-temperature reduction of aqueous Ag+ ions with ferrous ions and citrate as stabilizer (Carey Lea method). It was found that, contrary to the common view, the species adsorbed on the Ag nanoparticles are, in large part, products of citrate decomposition comprising an alcohol group and one or two carboxylate bound to the surface Ag, and minor unbound carboxylate group; these may also be mixtures of citrate with lower molecular weight anions. No ketone groups were specified, and very minor surface Ag(I) and Fe (mainly, ferric oxyhydroxides) species were detected. Moreover, the adsorbates were different at AgNPs having various size and shape. The relation between the capping and the particle growth, colloidal stability of the high-concentration sol and properties of AgNPs is briefly considered