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One way to increase the power of Brushless Direct Current (BLDC) motors is to switch to ferrite stator cores and increase the Pulse Width Modulation (PWM) frequency of Electronic Speed Controllers (ESC). This is particularly important in UAVs, where the weight of BLDC motors and their specific power are critical. The main problem when operating at high PWM frequency is that all parallel-connected MOSFETs should turn on quickly and in perfect synchronism. Nonsynchronization of transistors leads to thermal or electrical breakdown. The paper proposes new circuit solutions that ensure synchronous operation of high-power MOSFET transistors in the output stages and allow increasing the PWM frequency of Electronic Speed Control controllers (ESC) to 150-200 kHz. The use of ferrite cores in stators will significantly increase the power of BLDC motors while maintaining the same dimensions. Increasing the PWM operating frequency also allows multi-pole BLDC and PMSM motors to operate at higher speeds. The paper reveals a comprehensive methodology for constructing high-frequency ESC controllers for UAVs when switching to ferrite stator cores of BLDC motors. A special contribution is the description of the protective cascade circuits and the Battery Elimination Circuit (BEC) for powering the microprocessor part from a high-voltage current source. [ABSTRACT FROM AUTHOR]

The sediment of alluvial riverbeds plays a significant role in river systems both in engineering and natural processes. However, the sediment composition can show high spatial and temporal heterogeneity, even on river-reach scale, making it difficult to representatively sample and assess. Conventional sampling methods are inadequate and time-consuming for effectively capturing the variability of bed surface texture in these situations. In this study, we overcome this issue by adopting an image-based deep-learning (DL) algorithm. The algorithm was trained to recognise the main sediment classes in videos that were taken along cross sections underwater in the Danube. A total of 27 riverbed samples were collected and analysed for validation. The introduced DL-based method is fast, i.e. the videos of 300–400 m long sections can be analysed within minutes with continuous spatial sampling distribution (i.e. the whole riverbed along the path is mapped with images in ca. 0.3–1 m 2 overlapping windows). The quality of the trained algorithm was evaluated (i) mathematically by dividing the annotated images into test and validation sets and also via (ii) intercomparison with other direct (sieving of physical samples) and indirect sampling methods (wavelet-based image processing of the riverbed images), focusing on the percentages of the detected sediment fractions. For the final evaluation, the sieving analysis of the collected physical samples were considered the ground truth. After correcting for samples affected by bed armouring, comparison of the DL approach with 14 physical samples yielded a mean classification error of 4.5 %. In addition, based upon the visual evaluation of the footage, the spatial trend in the fraction changes was also well captured along the cross sections. Suggestions for performing proper field measurements are also given; furthermore, possibilities for combining the algorithm with other techniques are highlighted, briefly showcasing the multi-purpose nature of underwater videos for hydromorphological assessment. [ABSTRACT FROM AUTHOR]

Thepresent study illustrates the steps toward understanding molecularmechanism of xenon anesthesia by focusing on a link to the structuresand spectra of intermolecular complexes of xenon with small aromaticmolecules. A primary cause of xenon anesthesia is attributed to inhibitionof N-methyl-d-aspartate (NMDA) receptorsby an unknown mechanism. Following the results of quantum mechanics/molecularmechanics (QM/MM) and molecular dynamics (MD) calculations we reportplausible xenon action sites in the ligand binding domain of the NMDAreceptor, which are due to interaction of xenon atoms with aromaticamino-acid residues. We rely in these calculations on computationalprotocols adjusted in combined experimental and theoretical studiesof intermolecular complexes of xenon with phenol. Successful reproductionof vibrational shifts in molecular species upon complexation withxenon measured in low-temperature matrices allowed us to select aproper functional form in density functional theory (DFT) approachfor use in QM subsystems, as well as to calibrate force field parametersfor MD simulations. The results of molecular modeling show that xenonatoms can compete with agonists for a place in the corresponding proteincavity, thus indicating their active role in anesthetic action. [ABSTRACT FROM AUTHOR]

Health traits in dairy cattle have crucial meaning to produce high quality milk. Despite of fertility problems and metabolic disorders in cows, the mastitis has a bigger economic losses influence to include it as selection criteria in cattle breeding. Somatic cell count (SCC) in that case are the good predictor for monitoring udder health cows under whole population level or separate herd. The aim of our study was to assess genetic and genomic components for SCC and their scores (SCS) using experimental dataset by seven herds with the subsequent QTL identification. For six-month observation the 5824 cows with 19786 test-day records were included into analysis. Then EBVs by offspring assessing of 139 genotyped Holstein sires were calculated trough TD Model (BLUPF90) and then it adopted as pseudo-phenotypes for GWAS. After quality control using Plink 1.90, we used ?39K SNP (Illumina 50K). The average values for SCC and SCS were 351±7 thousands cells/ml and 2.86±0.02 score respectively. Heritability coefficients revealed low genetic variation for SCC - 0.119 and moderate for SCS - 0.211. Daily yield for cows with SCC >1000×103 cells/ml was low by -4.0 kg milk to compare individuals with SCC < 100×103 cells/ml. At the same time lactose content and freezing point were decreasing by 4.93 to 4.69% and -0.635 to -0.618°C. By Cattle QTLdb we identified some causal genes for SCC on BTA3 (ROR1), BTA9 (EZR), BTA13 (OSBPL2,DNAJC5,ZBTB46,MTG2), BTA14 (KHDRBS3) and BTA22 (RBMS3). But more relevant GWAS calls were found for SCS by BTA14 (KCNB2, ZFAT) as QTL associated to the milking speed that has unfavorable genetic correlation with clinical mastitis or SCS. Thereby, genes detected under experimental study, are the valuable and informative markers to implementation genomic selection methods for cattle health in creating Russian bulls' reference population. The study was funded by RFBR within project No. 20-316-90050. [ABSTRACT FROM AUTHOR]

Milk fatty acids (FA) derived from infrared spectra are a new type of traits that allow fast and predictability use their in dairy breeding and herd cattle management. The Holstein animals feature are the high milk yield, but milk composition traits can be different according to population or country origin. The purpose of our study was to find out genetic variation for milk FA and detect QTLs associated with Holstein sires' EBV in Russian cattle population. For this analysis, we used an experimental dataset for 36982 milk test records from 14 breeding herds in the Moscow region. Individual milk samples per animal analyzed routinely by MilkoScan7 for different FA types: C14:0, C16:0, C18:0, C18:1, saturated, mono- and polyunsaturated, short-, medium- and long-chain. Total number of bulls consisted 778 individuals including 222 animals with genotypes (39051 SNP, Illumina 50K). For calculating EBV by Sire Model, we applied BLUPF90. Plink 1.90 performed quality check control and GWAS procedure. Heritability coefficients were 0.071-0.155 for C14:0-C18:0 levels, 0.196 for C18:1, 0.083 for SFA, 0.018 for PUFA, 0.176 for MUFA, 0.114-0.155 for SCFA-LCFA levels. GWAS revealed most significant (P < 0.001-0.00001) frequently QTLs associated with FA content that were cited in articles previously for BTA5 (CHST11, C18:1), BTA6 (KCNIP4,C18:1; PPRAGC1A,C18:0), BTA11 (NRXN1,LPIN1,C18:1; NBAS,C18:0), BTA26 (PCDH15,PUFA; PRKG1, C18:1). These genes were responsible for synthesis milk fat, fertility, udder conformation traits, lauric, myristic, myristoleic, palmatoleic, oleic and other types of FA. In addition, we identified several QTLs for C14:0, C16:0, SFA, MUFA, SCFA, LCFA on BTA1 (137.32 Mb), BTA10 (5.50 Mb, 9.79 Mb), BTA14 (44.35 Mb), BTA19 (17.57-17.89 Mb) and BTA22 (14.02-14.06 Mb, 20.29-20.45 Mb). Our results are the first steps toward to understanding genetic and genomic mechanisms for using FA in selection processes to improve milk quality for Holstein cattle in Russia. The study was funded by RSF (project No. 21-76-20046). [ABSTRACT FROM AUTHOR]

Image based analysis is increasingly used in river flow assessment and there are already promising attempts for analyzing sediment features with image techniques, such as the grain size composition of bed material. For the quantification of flow features, the Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) are widely applied. PIV provides 2D or even 3D distributions of the flow velocities in Eulerian approach, i.e. on a fixed grid. PTV, on the other hand, provides single trajectories and related flow velocities of tracers, released in the flow, in a Lagrangian way. Capturing videos of the river bed in gravel bed streams, the movement of the grains becomes detectable, providing suitable input for image analysis techniques. In this study, an attempt will be made towards the coupling of PIV and PTV methods with complementary image based grain size analysis tools to estimate bedload transport. The test underwater videos are made in a large river, where the bedload transport is dominated by the movement of gravel. Local bedload transport rate will be determined as the product of the velocity of bedload particles and the thickness of the bedload layer, which is estimated based on the characteristic grain diameters. [ABSTRACT FROM AUTHOR]