Mesoporous titania–silica oxide materials of various compositions with high crystallinity and predominantly in the anatase modification were produced by hydrolysis and subsequent heat treatment of a ...mixture of titanium tetrachloride and oligodimethylsiloxane (ODMS) containing terminal Si–Cl groups. The synthesized samples were tested as photocatalysts in the destruction of methylene blue dye in aqueous solutions. The highest activity, significantly exceeding the activity of commercial TiO2, the highest specific surface area, and porosity was exhibited by the photocatalyst prepared from 33 wt.% ODMS. The photocatalysts are active not only under the action of UV but also of visible light. This may be due to the effect of carbon doping of TiO2 during ODMS decomposition, which increases the light absorption and improves the separation of the photogenerated charges.
The article discusses the method of multidisciplinary treatment of patients with a diagnosis of M54.5 "Low back pain" based on the combined use of physiotherapy, kinesitherapy and correction of ...anxious depression. It was established that treatment of patients with lower back pain based on the proposed method reduces the level of subjective assessment of pain according to the VAS scale by 28 ± 3% reduces the clinical manifestations of pain and by 21 ± 4% the level of depression according to A. Beck's psychometric table compared to the control group.
The article discusses the method of multidisciplinary treatment of patients with a diagnosis of M54.5 "Low back pain" based on the combined use of physiotherapy, kinesitherapy and correction of ...anxious depression. It was established that treatment of patients with lower back pain based on the proposed method reduces the level of subjective assessment of pain according to the VAS scale by 28 ± 3% reduces the clinical manifestations of pain and by 21 ± 4% the level of depression according to A. Beck's psychometric table compared to the control group.
The Tunka Advanced Instrument for gamma-ray and cosmic ray Astrophysics (TAIGA) is a hybrid observatory for the detection of extensive air showers (EAS), produced by high-energy gamma rays and cosmic ...rays. The complex consists of such facilities as TAIGA-IACT, TAIGA-HiSCORE, and a variety of others. The goal of the study is to introduce a deep learning-based technique for EAS axis reconstruction. A convolutional neural network (CNN) model is proposed, while HiSCORE events, consisting of time-amplitude data, are treated as images by the model. Reasoning behind the CNN model and model efficacy will be discussed, along with preliminary results for EAS axis direction determination. This article will show that the accuracy of the model reaches 1
–2
for the zenith and azimuthal angles, however, the accuracy of the model does not reach the accuracy of conventional methods.
In recent years, machine learning techniques have seen huge adoption in astronomy applications. In this work, we discuss the generation of realistic synthetic images of gamma-ray events, similar to ...those captured by imaging atmospheric Cherenkov telescopes (IACTs), using the generative model called a conditional generative adversarial network (cGAN). The significant advantage of the cGAN technique is the much faster generation of new images compared to standard Monte Carlo simulations. However, to use cGAN-generated images in a real IACT experiment, we need to ensure that these images are statistically indistinguishable from those generated by the Monte Carlo method. In this work, we present the results of a study comparing the parameters of cGAN-generated image samples with the parameters of image samples obtained using Monte Carlo simulation. The comparison is made using the so-called Hillas parameters, which constitute a set of geometric features of the event image widely employed in gamma-ray astronomy. Our study demonstrates that the key point lies in the proper preparation of the training set for the neural network. A properly trained cGAN not only excels at generating individual images but also accurately reproduces the Hillas parameters for the entire sample of generated images. As a result, machine learning simulations are a compelling alternative to time-consuming Monte Carlo simulations, offering the speed required to meet the growing demand for synthetic images in IACT experiments.
Imaging atmospheric Cherenkov telescopes are used to record images of extensive area showers caused by high-energy particles colliding with the upper atmosphere. The images are analyzed to determine ...events’ physical parameters, such as the type and the energy of the primary particles. The distributions of some of the physical parameters can be used as well, for example, to determine the properties of a gamma ray source. The key problem of any experiment is the calibration of experimental data. For this purpose, Monte Carlo simulated data with known values of the physical parameters are used. The main disadvantage of this method is its extremely high requirements for computing resources and the large amount of time spent on modelling. In this paper, we use an alternative approach: Cherenkov telescope images are simulated with conditional variational autoencoders. We compare the characteristics of both the individual images and their Hillas parameter distributions with those of the images generated by the Monte Carlo method.
Imaging atmospheric cherenkov telescopes (IACTs) of the gamma ray observatory TAIGA detect the extesnive air showers (EASs) originating from the cosmic or gamma rays interactions with the atmosphere. ...Thereby, telescopes obtain images of the EASs. The ability to segregate gamma rays images from the hadronic cosmic ray background is one of the main features of this type of detectors. However, in actual IACT observations, simultaneous observation of the background and the source of gamma rays is needed. This observation mode (called wobbling) modifies images of events, which affects the quality of selection by neural networks. Thus, in this work, the results of the application of neural networks (NN) for the image classification task on Monte Carlo (MC) images of the TAIGA-IACTs are presented. The wobbling mode is considered together with the image adaptation for the adequate analysis by NNs. Simultaneously, we explore several neural network structures that classify events both directly from images or through Hillas parameters extracted from images. In addition, by employing NNs, MC simulation data are used to evaluate the quality of the segregation of rare gamma events with the account of all necessary image modifications.
Purpose: substantiation of pedagogical conditions of health saving functioning organization of comprehensive educational establishment’s headmaster. Material: publications on topic of the research. ...40 literature sources have been analyzed. Results: it has been found that pedagogic conditions of effective health saving functioning of comprehensive educational establishment headmaster are: influence of interconnection of district educational administration’s teaching-methodic departments; activation of headmaster’s personality; understanding of values by headmaster and his acquiring of health related knowledge and knowledge about health saving in process of education; realization of self-education by headmaster; renewal and acquiring of new knowledge and experience, which would ensure personal-professional growth of headmaster and facilitate increase of quality of pupils’ education and teaching. Conclusions: self-education provides wide opportunities for improvement of administrative, communicative and reflexive qualities and skills as well as gives proper tools for independent and creative solution of health saving tasks in favor of pedagogic process’s subjects.
Purpose: to show the essence and structural components of healthsaving activity of comprehensive educational establishments’ leader. Material: conducted an analysis of psychological and pedagogical ...sources. Results: healthsaving activity of comprehensive educational establishments’ leader was conducted. An integral part of leader’s management-pedagogical activity directed on creation of healthy environment (physical-subjective, psychological-communicative, educational) of educational establishment. Also floating, saving and strengthening of health of all participants (pupils, pedagogues, parents) of pedagogical process. It was analysed contents of main components (planning, organization, stimulation, control) of healthsaving activity of leader. Conclusions: constant pedagogical monitoring allows to estimate an effectiveness of educational work of establishment according to the degree of achievement of assigned tasks and to make corresponding corrections in a decision of healthsaving questions of pedagogical process participants.
The Gigaton Volume Detector in Lake Baikal Avrorin, A.; Aynutdinov, V.; Belolaptikov, I. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
05/2011, Letnik:
639, Številka:
1
Journal Article
Recenzirano
Odprti dostop
The objective of the Baikal Project is the creation of a kilometer-scale high-energy neutrino observatory: the Gigaton Volume Detector (GVD) in Lake Baikal. Basic elements of the GVD – new optical ...modules, FADC readout units, and underwater communication systems – were investigated and tested in Lake Baikal with prototype strings in 2008–2010. We describe the results of prototype strings operation and review the preliminary design and expected sensitivity of the GVD telescope.
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