Influence of the preliminary annealing conditions on step motion at the homoepitaxy on the Si(100) surface

In this paper, the motion of steps SA and SB on the Si(100) surface in the process of Si Molecular beam epitaxy (MBE) is explored. The study was carried out by means of the reflection intensity dependence behavior analysis of reflection high-energy electron diffraction (RHEED) corresponding to the (2×1) and (1×2) reconstructions. Superstructural rearrangement from a two-domain to a single-domain surface is associated with the bilayer step formation, which occurs due to the different motion rates of the steps SA and SB. Based on the research conducted, the conditions under which the step doubling occurs were determined. A behavior analysis of the diffraction reflection intensity dependences showed that an increasing of preliminary annealing time and temperature facilitates to the faster convergence of the steps SA and SB, but to the slower recovery of the initial surface. The presented experimental results indicate that step movement rate difference depends on the step A edge kink density

Estimation of gas turbine technical condition using machine learning methods

This paper considers the method to estimate the technical condition of gas turbine power for natural gas transportation, using machine learning methods. Source data was used to archive gas-dynamic parameters from the automatic control system of the gas turbine. The method is based on changing the enthalpy of the natural gas before and after the centrifugal gas compressor is used for creating a dataset with measured parameters and power from the gas turbine. The actual power is determined from the line of modes for a certain period. The software is implemented using Python and the Scikit-learn library is used to create machine learning models. A mean average percentile error is chosen as the model quality criterion. In this paper, different sets of feature parameters and sample sizes are researched by the quality of the prediction machine learning models. Recommendations on the use of models are given. It has been established that the approach is not applicable for predicting future technical condition without the presence of data on a similar technical condition in the training sample. It is recommended to use the described approach to determine the technical condition in a period of operation in the past. © Published under licence by IOP Publishing Ltd.Terentyev S.Romanova I.Gibadullin A.Gibadullin A

Technical Condition Estimation of the Gas Turbine Axial Compressor

The paper describes an approach for determining the technical state of an axial compressor as part of a gas turbine unit, based on thermogasdynamic parameters that are measured at the operating facility. As a criterion for the technical condition, it is proposed to use the ratio of the actual efficiency of an axial compressor to the reference efficiency in such modes. To do this, it is enough to know the temperatures and pressures of the air at the inlet and outlet of the axial compressor. A method for selecting such modes is described and some features of filtering the operating parameters of a gas turbine plant are noted. In the proposed approach, the choice of modes for analyzing the technical state of an axial compressor is carried out according to the value of the effective power of the gas turbine unit. Some results of determining the criterion of the technical condition of an axial compressor for a gas turbine unit, which drives a centrifugal compressor of natural gas, are presented. Based on the analysis of the degradation of the technical condition criterion, it is possible to determine its predicted value. The results of the work can be used to create automated systems for assessing and predicting the technical condition of drive gas turbine units at their facilities. The application of the obtained results of the work expands the possibilities of servicing gas turbine plants according to the actual state. The proposed approach can be adapted and applied for gas turbine plants for various purposes, as well as for their individual units. © 2022 Institute of Physics Publishing. All rights reserved

The Physiological and Biochemical Mechanisms Providing the Increased Constitutive Cold Resistance in the Potato Plants, Expressing the Yeast SUC2 Gene Encoding Apoplastic Invertase

The expression of heterologous genes in plants is an effective method to improve our understanding of plant resistance mechanisms. The purpose of this work was to investigate the involvement of cell-wall invertase and apoplastic sugars into constitutive cold resistance hypothermia conditions compared to WT-plants. This fact allows us to consider cell-wall invertase as a enzyme of carbohydrate metabolism playing an important regulatory role in the metabolic signaling upon forming increased plant resistance to low temperature. Thus, the potato line with the integrated SUC2 gene is a convenient tool to study the role of the apoplastic invertase and the products of its activity during growth, development and formation constitutive resistance to hypothermia

Antibacterial and quorum sensing regulatory activities of some traditional Eastern-European medicinal plants

The objective of this study was to screen extracts of twenty Eastern European medicinal plants, using wild-type and reporter Chromobacterium violaceum bioassays, for novel components that target bacterial cells and their quorum sensing (QS) communication systems. Three types of activity and their combinations were revealed: (i) direct antimicrobial growth-inhibitory activity, (ii) non-specific and specific pro-QS activities, (iii) anti-QS activity. Among seven plant extracts showing direct growth-inhibitory activity, the strongest effect was shown by Arctostaphylos uva-ursi (bearberry) leaves. Many plants stimulated violacein production by wild-type C. violaceum ATCC 31532 in a non-specific manner, and only the herb Bidens tripartita (three-lobe beggarticks) contained compounds that mimic acyl-homoserine lactone and operated as a QS agonist. Anti-QS activity was found in eleven plants including Quercus robur (oak) cortex, Betula verrucosa (birch) buds and Eucalyptus viminalis (Manna Gum) leaves. Subsequent statistical analysis showed differences between antimicrobial and anti-QS activities, whereas both activities were defined by phylogenetic position of the medicinal resource plant. Finally, extract from Quercus robur cortex revealed at least two fractions, showing different anti-QS mechanisms. These data confirm that multi-component anti-infectious mechanisms are used by plants, which may be useful for drug development

Application of Machine Learning Methods to Determine the Parameters of a Gas Turbine

В работе рассматривается возможность оценки параметров работы газотурбинной установки, используемой для транспортировки природного газа, при помощи методов машинного обучения. Произведена оценка качества прогноза моделей машинного обучения в зависимости от разных наборов параметров-признаков.The paper considers the possibility of evaluating the parameters of the operation of a gas turbine unit used for the transportation of natural gas using machine learning methods. The quality of forecasting machine learning models was assessed depending on different sets of feature parameters

Parietal and occipital hair loss patterns in initial stages of androgenic alopecia in men

Background. The initial stages of androgenetic alopecia in men are characterized by a variety of clinical manifestation in the parietal or occipital scalp regions. However, the differences in the pathogenesis of hair loss patterns are not well understood, selective treatment has not been developed. Aims. Trichological characteristics of patients with initial stages of androgenetic alopecia with identification of genetic and non-genetic factors that determine the hair loss in the different scalp regions, and their response to conservative therapy. Materials and methods: Trichograms were photodocumented using an AramoSG microcamera (Republic of Korea). The genetic factor was analyzed by mini-sequencing of single nucleotide polymorphisms rs929626, rs5919324, rs1998076, rs12565727, rs756853. The non-genetic factors study included hormonal status (total and free testosterone, dihydrotestosterone, 17OH-progesterone, dehydroepiandrostenone, SHBG) and blood content of trace elements (Mg, Ca, Zn, Cu, Se, Fe) and vitamins (B12, D, E, folic acid). Conservative treatment was topical application of a minoxidil 5% (twice-a-day, 4 months) and a micronutrient deficiencies personalized correction. Results. The study included 47 man with initial stages of androgenetic alopecia. Their trichological examination showed two patterns, consisting a predominant decrease in the hair density and diameter in the parietal and occipital scalp regions, which were subgroups formation criteria. An intergroup comparison revealed similar genetic risk, while hormonal parameters (increased dihydrotestosterone levels, a decrease in free testosterone) characterized the subgroup with parietal hair loss pattern. Also, a multiple deficiency of Zn, Cu, Se and vitamins B12, D, folic acid was detected in all patients. Subsequent conservative treatment had a positive effect in patients with parietal hair loss pattern, while in patients with occipital pattern no significant response was observed. Conclusions. The study develops ideas about differences between androgen-dependent parietal and androgen-independent occipital hair loss patterns in the initial stages of androgenetic alopecia, which requires different approaches to their conservative therapy

Massive blow-out craters formed by hydrate-controlled methane expulsion from the Arctic seafloor

Widespread methane release from thawing Arctic gas hydrates is a major concern, yet the processes, sources, and fluxes involved remain unconstrained. We present geophysical data documenting a cluster of kilometer-wide craters and mounds from the Barents Sea floor associated with large-scale methane expulsion. Combined with ice sheet/gas hydrate modeling, our results indicate that during glaciation, natural gas migrated from underlying hydrocarbon reservoirs and was sequestered extensively as subglacial gas hydrates. Upon ice sheet retreat, methane from this hydrate reservoir concentrated in massive mounds before being abruptly released to form craters. We propose that these processes were likely widespread across past glaciated petroleum provinces and that they also provide an analog for the potential future destabilization of subglacial gas hydrate reservoirs beneath contemporary ice sheets.authorsversionPeer reviewe

Issues of Eroded Axial Compressor Blades Classification with Machine Learning Methods

В статье рассматривается возможная постановка задачи по прогнозированию степени эрозии лопаток осевого компрессора, входящего в состав газоперекачивающего агрегата, методами машинного обучения. В качестве исходных данных используются результаты численного моделирования течения потока в изолированной ступени. Определен набор моделей машинного обучения, целевой параметр и сформированы наборы параметров- признаков. В результате первичного исследования наилучшие результаты продемонстрировала модель случайного леса при использовании всех доступных параметров. Развитие работы связано с созданием модели для прогнозирования технического состояния проточной части всего компрессора.The article supposes possible problem statement for predicting the erosion of the axial compressor blades using machine learning methods. The results of numerical simulation of the flow in an isolated stage are used as initial data. A set of machine learning models, a target parameter are defined, and sets of feature parameters are formed. As a result of the primary study, the random forest model showed the best results when using all available parameters. The development of the work relates to the creation of a model for predicting the technical condition of the flow path of the entire compressor