Data protection in telemedicine

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MULTIPACTOR DISCHARGE IN THE ELINAC ACCELERATOR

Abstract This paper concerns numerical simulations and experimental investigation of multipactior discharge in accelerating cavities and the feeding waveguide section of the eLINAC accelerator. The threshold values of the accelerating gradient and of the input power, at which the discharge may occur in these structures, have been obtained experimentally and compared to predictions of numerical simulations. The issues of the influence of secondary emission yield on a discharge growth were also considered

Сhallenges of the modern model of formation and implementation of the Russian state innovation policy

The state innovation policy of modern Russia has been analyzed in the article. The problems of the existing model of formation and implementation of the state innovation policy have been considered. This direction of policy has been studied from the standpoint of institutional, technological and time components, which allows us to characterize the modern model of the state innovation policy of Russia as a model implemented “top-down”, as the center of decision-making was shifted towards the state in the face of government agencies and decision-makers with minimal consideration of the views of other stakeholders. The subject of this study is the interaction of political institutions in the formation and implementation of the state innovation policy of Russia. The role of small and medium-sized enterprises of scientific, technical and innovative orientation in the studied processes as the most “sensitive” market needs has been emphasized, the focus has been shifted to increase the responsibility of the first persons of the regions for regional innovative development, as well as to the nominal nature of the state priority of innovative development of Russia. As a methodological basis, a system-dynamic approach is used, which allows you to reveal systematically the shortcomings of the current system, expressed in the limited interaction of political institutions, their communication and the quality of partnerships. This is largely due to the symbolic (nominal) political demand for such development and the weak setting, optimal for the development of innovation, socio-political environment. The conclusion has been made, that it is possible to correct the current state of affairs when changing: the legal support of the innovation sphere, the subject composition of the participants in the development and implementation of state policy in the field of innovation and the conditions for the development and growth of innovation

Deformation uniformity of additively manufactured materials on the example of austenitic stainless steel 321 and copper C11000

Structural studies and mechanical tests of additively manufactured samples from AISI 321 steel copper C110000 have been carried out. Mechanical tensile tests of 321 steel show slight differences in the ultimate tensile strength (up to 3-4%) and ductility (up to 10%) of test coupons tested along the material growth direction and along the layer deposition direction. The strength of C11000 copper samples is 9.4% higher in the layer deposition direction, but their ductility is 15.4% lower than that of samples deformed in the growth direction. The strain relief on the surface of the polished gage section of the steel test coupons demonstrates changes in the material structure with small elongated grains along the growth direction of the sample. The deformation relief of copper samples is mainly related to the deformation of large columnar grains stretched in the growth direction

Пример успешной терапии нилотинибом пациентки с Ph-позитивным хроническим миелолейкозом в хронической фазе с резистентностью к интерферону и гливеку

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Polarity and conformational analysis of secondary phosphine selenides

The polarities of bis(2-phenylethyl) and bis(2-phenylpropyl) phosphine selenides were determined and conformational analysis of these phosphine selenides was carried out by the method of dipole moments, IR spectroscopy, and quantum chemical calculations. They exist as an equilibrium of several conformers, and the preferred conformers have gauche orientation of the P = Se and Csp3 - Csp3 bonds. © 2013 Copyright Taylor and Francis Group, LLC

Thermodynamic properties of myo-inositol

© 2017 Elsevier Ltd In the present work, the temperature dependence of heat capacity of vitamin B8 (myo-inositol) has been measured for the first time over the range from 8 K to 340 K by precision adiabatic vacuum calorimetry. Based on the experimental data, the thermodynamic functions of the vitamin B8, namely, the heat capacity, enthalpy H°(T)–H°(0), entropy S°(T)–S°(0) and Gibbs function G°(T)–H°(0) have been determined for the range from T → 0 K to 340 K. The value of the fractal dimension D in the function of multifractal generalization of Debye's theory of the heat capacity of solids was estimated and the character of heterodynamics of structure was detected. The enthalpy of combustion (−2747.0 ± 2.1) kJ·mol−1 of the vitamin B8 was measured for the first time using high-precision combustion calorimeter. The standard molar enthalpy of formation in the crystalline state (−1329.3 ± 2.3) kJ·mol−1 of B8 at 298.15 K was derived from the combustion experiments. Using combination of the adiabatic and combustion calorimetry results the thermodynamic functions of formation of the myo-inositol at T = 298.15 K and p = 0.1 MPa have been calculated. The low-temperature X-ray diffraction was used for the determination of coefficients of thermal expansion

Structure formation features of large block-shaped samples from the copper and aluminum alloy produced by the wire-feed electron-beam additive technology

In this work the study of the structure of samples made by the wire-feed electronbeam 3D printing from copper C11000 and aluminum alloy AA5056 was carried out. The presence of a dendritic structure typical of this method was revealed, as well as the presence of pores, cracks and other defects that occurred during printing. Mechanical properties of samples cut in the planar section are at a rather low level. The ultimate tensile strength of copper block samples varies between 165 and 187 MPa. The relative elongation of samples without pores is at 18%, but with the presence of pores it decreases sharply to 7%, while the strength is practically not decreased. The samples of alloy AA5056 demonstrate slightly higher mechanical properties: the strength is at the level of 190-192 MPa and the relative elongation is about 16-18%. In samples with defects such as large pores or discontinuities, the strength drops to almost zero

Using topological data analysis for building Bayesan neural networks

For the first time, a simplified approach to constructing Bayesian neural networks is proposed, combining computational efficiency with the ability to analyze the learning process. The proposed approach is based on Bayesianization of a deterministic neural network by randomizing parameters only at the interface level, i.e., the formation of a Bayesian neural network based on a given network by replacing its parameters with probability distributions that have the parameters of the original model as the average value. Evaluations of the efficiency metrics of the neural network were obtained within the framework of the approach under consideration, and the Bayesian neural network constructed through variation inference were performed using topological data analysis methods. The Bayesianization procedure is implemented through graded variation of the randomization intensity. As an alternative, two neural networks with identical structure were used — deterministic and classical Bayesian networks. The input of the neural network was supplied with the original data of two datasets in versions without noise and with added Gaussian noise. The zero and first persistent homologies for the embeddings of the formed neural networks on each layer were calculated. To assess the quality of classification, the accuracy metric was used. It is shown that the barcodes for embeddings on each layer of the Bayesianized neural network in all four scenarios are between the corresponding barcodes of the deterministic and Bayesian neural networks for both zero and first persistent homologies. In this case, the deterministic neural network is the lower bound, and the Bayesian neural network is the upper bound. It is shown that the structure of data associations within a Bayesianized neural network is inherited from a deterministic model, but acquires the properties of a Bayesian one. It has been experimentally established that there is a relationship between the normalized persistent entropy calculated on neural network embeddings and the accuracy of the neural network. For predicting accuracy, the topology of embeddings on the middle layer of the neural network model turned out to be the most revealing. The proposed approach can be used to simplify the construction of a Bayesian neural network from an already trained deterministic neural network, which opens up the possibility of increasing the accuracy of an existing neural network without ensemble with additional classifiers. It becomes possible to proactively evaluate the effectiveness of the generated neural network on simplified data without running it on a real dataset, which reduces the resource intensity of its development