ALBERT

Description: We consider a class of linear inhomogeneous equations in a Banach space not solvable with respect to the fractional Caputo derivative. Such equations are called degenerate. We study the case of the existence of a resolving operators family for the respective homogeneous equation, which is an analytic in a sector. The existence of a unique solution of the Cauchy problem and of the Showalter—Sidorov problem to the inhomogeneous degenerate equation is proved. We also derive the form of the solution. The approximate controllability of infinite-dimensional control systems, described by the equations of the considered class, is researched. An approximate controllability criterion for the degenerate fractional order control system is obtained. The criterion is illustrated by the application to a system, which is described by an initial-boundary value problem for a partial differential equation, not solvable with respect to the time-fractional derivative. As a corollary of general results, an approximate controllability criterion is obtained for the degenerate fractional order control system with a finite-dimensional input.

Description: Intensive development of South Yakutia, a mountainous area in the Russian sporadic permafrost zone, must be founded on knowledge about regional permafrost conditions. New permafrost maps for mountainous areas in South Yakutia (the Elkon Mountains and the Olekma-Chara Upland) are presented that provide a more detailed and updated description of permafrost distribution in the area than those that were hitherto available. These maps are based on the previously-developed and tested method of detecting permafrost and unfrozen ground using Landsat-5/TM satellite data with relatively high resolution. The method represents a scheme for permafrost identification based on a set of landscape indicators: terrain elevation, slope angle and exposition, vegetation, snow cover, and land surface temperature (LST). A correlation analysis of satellite data to full-scale field data has been carried out for the two areas under consideration. Indicator properties of LST obtained by Landsat-5/TM Band 6 Infrared have been characterized in detail for detection and regional mapping of permafrost. The effect of landscape factors (landscape cryo-indicators) on ground temperature and condition, frozen or unfrozen reflected in LST intensity, is demonstrated.

Description: The behavior of the resistivity and thermopower of the Gd0.2Sr0.8FeO3−δ ferrite samples with a perovskite structure and the sample stability in an inert gas atmosphere in the temperature range of 300–800 K have been examined. It has been established that, in the investigated temperature range, the thermoelectric properties in the heating‒cooling mode are stabilized at δ ≥ 0.21. It is shown that the temperature dependencies of the resistivity obtained at different δ values obey the activation law up to the temperatures corresponding to the intense oxygen removal from a sample. The semiconductor‒semiconductor electronic transitions accompanied by a decrease in the activation energy have been observed with increasing temperature. It is demonstrated that the maximum thermoelectric power factor of 0.1 µW/(cm·K2) corresponds to a temperature of T = 800 K.

Description: In this paper, we demonstrated a novel, all-fiber highly sensitive bend sensor based on a four-core fiber rod with a diameter of 2.1 mm. We observed a high resolution of the sensor at a level of 3.6 × 10−3 m−1. Such a sensor design can be used in harsh environments due to the relatively small size and all-fiber configuration, containing no adhesive, nor welded joints.

Description: Over recent years, quantum dots (QDs) based on ternary metal dichalcogenides have attracted a lot of attention due to their unique properties and a range of potential applications. Here, we review the latest studies on the optical properties of AgInS2/ZnS QDs with emphasis on their theoretical modeling, and present our investigations of electronic transitions invisible in unstructured absorption spectra of AgInS2/ZnS QDs. The analysis of the absorption, photoluminescence excitation (PLE), and magnetic circular dichroism (MCD) spectra of hydrophobic and hydrophilic AgInS2/ZnS QDs of different sizes enables us to determine positions of electron transitions in these QDs. We demonstrate that the use of the second derivative of PLE spectra provides more unequivocal data on the position of the energy transitions compared with the second derivative of absorption spectra. Analysis of the MCD spectra reveals that the magnetic field induces energy level mixing in AgInS2/ZnS QDs in contrast to the traditional Cd-based QDs, where MCD is associated only with removing degeneracy of the excited energy level.

Description: Lakes constitute a significant freshwater resource and are often regarded as being an important part of a country’s natural heritage. However, their geological heritage (geoheritage) value remains significantly understudied. Three small lakes, namely the Salt Lake, the Gruzskoe Lake and the Big Yashalta Lake, located in the central part of the Russian South were studied in this paper. The main focus of this research was to search for relevant unique geological features. This paper established that these lakes are distinguishable from other lakes by the presence of dark-colored mud that is rich in sulfides and methane. As a result of excessive summer evaporation, the lakes desiccate (partly or even fully) and this results in exposure of the mud as well as the formation of salt crystals and crusts. This bottom mud (peloid, therapeutic mud) forms as a result of highly-complex biogeochemical processes in semi-arid environments. This mud is interpreted as being part of the lake’s geoheritage as it belongs to sedimentary, geochemical and other types. Moreover, this geoheritage has a high ranking nationally. The most representative example can be found at the Big Yashalta Lake and for that reason, this lake is proposed as a geosite. Established sites of geoheritage importance are vital to geoscience research and geotourism activities and thus, these sites are considered to be a resource. Together with the development of local ecotourism and the use of peloids for the health industry purposes, the exploitation of this geoheritage resource would contribute to the sustainable development of the local area.

Description: The coastal peloidis a peculiar and poorly-studied geological substance. Peloids occurin the Bugaz, Kiziltash, and Vityazevolimans and the Chemburka Lake on the southern coast of the Taman Peninsula. The studied peloids are dark-colored mud enriched in hydrogen sulfide and methane and constitute the uppermost 10–20 cm of bottom sediments. Being geologically unique, the coastal peloids of the Taman Peninsula can be recognized as ageoheritage site. Their uniqueness is linked to sediment type, biogeochemical processes, economic value, and depositional environment. The most typical peloids are found in the BugazLiman and the Chemburka Lake, proposed as geosites. The recognized coastal geoheritage site can be used for the purposes of science, education, and tourism, and its utility seems to be especially high because of its close location to the big resort area of Anapa. It appears to be important to balance management of this geoheritagesite with peloid extraction for balneological purposes. The studied coastal muds should be involved into the regional planning programs aimed at sustainable development (international experience and, particularly, some examples from the British coasts should be taken into consideration). Particularly, it is necessary to put peloid use into the context of regional planning and sustainable natural resource management.

Description: The possibilities of chlorophyll a (Chl a) and total suspended matter (TSM) retrieval using Sentinel-2/MSI imagery and in situ measurements in the Gorky Reservoir are investigated. This water body is an inland freshwater ecosystem within the territory of the Russian Federation. During the algal bloom period, the optical properties of water are extremely heterogeneous and vary on scales of tens of meters. Additionally, they vary in time under the influence of currents and wind forcing. In this case, the usage of the traditional station-based sampling to describe the state of the reservoir may be uninformative and not rational. Therefore, we proposed an original approach based on simultaneous in situ measurements of the remote sensing reflectance by a single radiometer and the concentration of water constituents by an ultraviolet fluorescence LiDAR from a high-speed gliding motorboat. This approach provided fast data collection including 4087 synchronized LiDAR and radiometric measurements with high spatial resolutions of 8 m for two hours. A part of the dataset was coincided with Sentinel-2 overpass and used for the development of regional algorithms for the retrieval of Chl a and TSM concentrations. For inland waters of the Russian Federation, such research was performed for the first time. The proposed algorithms can be used for regular environmental monitoring of the Gorky Reservoir using ship measurements or Sentinel-2 images. Additionally, they can be adapted for neighboring reservoirs, for example, for other seven reservoirs on the Volga River. Moreover, the proposed ship measurement approach can be useful in the practice of limnological monitoring of inland freshwater ecosystems with high spatiotemporal variability of the optical properties.

Description: Timely detection of surface damages on wind turbine blades is imperative for minimizing downtime and avoiding possible catastrophic structural failures. With recent advances in drone technology, a large number of high-resolution images of wind turbines are routinely acquired and subsequently analyzed by experts to identify imminent damages. Automated analysis of these inspection images with the help of machine learning algorithms can reduce the inspection cost. In this work, we develop a deep learning-based automated damage suggestion system for subsequent analysis of drone inspection images. Experimental results demonstrate that the proposed approach can achieve almost human-level precision in terms of suggested damage location and types on wind turbine blades. We further demonstrate that for relatively small training sets, advanced data augmentation during deep learning training can better generalize the trained model, providing a significant gain in precision.

Description: Configuration entropy is believed to stabilize disordered solid solution phases in multicomponent systems at elevated temperatures over intermetallic compounds by lowering the Gibbs free energy. Traditionally, the increment of configuration entropy with temperature was computed by time-consuming thermodynamic integration methods. In this work, a new formalism based on a hybrid combination of the Cluster Expansion (CE) Hamiltonian and Monte Carlo simulations is developed to predict the configuration entropy as a function of temperature from multi-body cluster probability in a multi-component system with arbitrary average composition. The multi-body probabilities are worked out by explicit inversion and direct product of a matrix formulation within orthonomal sets of point functions in the clusters obtained from symmetry independent correlation functions. The matrix quantities are determined from semi canonical Monte Carlo simulations with Effective Cluster Interactions (ECIs) derived from Density Functional Theory (DFT) calculations. The formalism is applied to analyze the 4-body cluster probabilities for the quaternary system Cr-Fe-Mn-Ni as a function of temperature and alloy concentration. It is shown that, for two specific compositions (Cr 25Fe 25Mn 25Ni 25 and Cr 18Fe 27Mn 27Ni 28), the high value of probabilities for Cr-Fe-Fe-Fe and Mn-Mn-Ni-Ni are strongly correlated with the presence of the ordered phases L1 2 -CrFe 3 and L1 0-MnNi, respectively. These results are in an excellent agreement with predictions of these ground state structures by ab initio calculations. The general formalism is used to investigate the configuration entropy as a function of temperature and for 285 different alloy compositions. It is found that our matrix formulation of cluster probabilities provides an efficient tool to compute configuration entropy in multi-component alloys in a comparison with the result obtained by the thermodynamic integration method. At high temperatures, it is shown that many-body cluster correlations still play an important role in understanding the configuration entropy before reaching the solid solution limit of high-entroy alloys (HEAs).