33 research outputs found
Study of the Forces Acting on the Animal in the Installation for Fixing with Veterinary Treatments
The study of the forces acting on the animal in the installation for fixing with veterinary treatments. The most time consuming processes in service animals are zootechnical and veterinary treatment of sheep. During the year, it is necessary to carry out more than ten such treatments of each animal, which requires a lot of labor. Almost all animal treatments such as feed to the operatorβs workplace and their fixation in a convenient position for him requires significant physical effort of the operator. Therefore, today the technologies and technical means should be created to reduce labor costs for various treatments. The relevance of the problem is due to the lack of theoretical foundations and experimental data for the creation of technological equipment for fixing sheep in zootechnical and veterinary treatments. The purpose of the study is the theoretical and experimental justification of the installation for fixing sheep in zootechnical and veterinary treatments with the justification of the existing efforts on the animal, excluding injury. Developed installation and presented a scheme with two of the conveyor belts forming the grooved shape When designing the installation, the main focus was on the justification of structural elements and modes of operation from the viewpoint of eliminating the possibility of injury to the animal. The experimental studies have confirmed the correctness of the obtained analytical dependences. The obtained results will enable designers to create equipment for the fixation of sheep at the zootechnical and veterinary treatments, precluding injury to the animal and reducing labor costs
Low molecular weight blood plasma proteome β a source of differential diagnostic biomarkers of ovarian cancer
At present, there is no screening test for the early detecting of ovarian cancer, one of the most lethal form of gynaecological malignancy in theΒ worldwide. In this study the new methodology for the search of tumor markers of ovarian cancer, involving profiling the low-molecular bloodΒ plasma proteomes, is developed, unified and approved. The given approach included three basic components: pre-preparation of samples,Β matrix-assisted laser desorption / ionization time-of-flight mass spectrometry and bioinformatics software for mass spectral data processing.Β Opportunities and prospects of the developed approach for the detection of potential ovarian cancer markers were shown. For search of potentialΒ tumor markers, screening of 56 blood plasma samples from ovarian cancer patients and 36 benign ovarian neoplasia samples were carried out.As a result of the present research, peptides / polypeptides which can be used in future for detecting this pathology were found out
First atom lifetime and scattering length measurements
The results of a search for hydrogen-like atoms consisting of
mesons are presented. Evidence for atom production
by 24 GeV/c protons from CERN PS interacting with a nickel target has been seen
in terms of characteristic pairs from their breakup in the same target
() and from Coulomb final state interaction (). Using
these results the analysis yields a first value for the atom lifetime
of fs and a first model-independent measurement of
the S-wave isospin-odd scattering length
( for isospin ).Comment: 14 pages, 8 figure
Evidence for -atoms with DIRAC
We present evidence for the first observation of electromagnetically bound
-pairs (-atoms) with the DIRAC experiment at the CERN-PS.
The -atoms are produced by the 24 GeV/c proton beam in a thin Pt-target
and the and -mesons from the atom dissociation are analyzed in
a two-arm magnetic spectrometer. The observed enhancement at low relative
momentum corresponds to the production of 173 54 -atoms. The mean
life of -atoms is related to the s-wave -scattering lengths, the
measurement of which is the goal of the experiment. From these first data we
derive a lower limit for the mean life of 0.8 fs at 90% confidence level.Comment: 15 pages, 9 figure
ΠΠΠΠΠΠΠΠΠΠΠΠ‘Π’Π¬ ΠΠΠ’ΠΠ ΠΠΠΠ Π£Π‘ΠΠΠ ΠΠΠ€ΠΠΠ¦ΠΠΠ Π ΠΠ‘ΠΠΠΠΠΠΠ‘Π’Π Π¦ΠΠ ΠΠ£ΠΠ―Π¦ΠΠ ΠΠΠΠΠΠΠΠΠΠΠΠΠ’ΠΠ«Π₯ ΠΠΠ’ΠΠ ΠΠΠΠ Π£Π‘ΠΠ ΠΠ ΠΠΠΠΠ’ΠΠ Π«Π₯ Π’ΠΠ Π ΠΠ’ΠΠ ΠΠ―Π₯ Π ΠΠ‘Π‘ΠΠ Π 2017 ΠΠΠΠ£
Aim: Characteristics of enterovirus infection morbidity and study of peculiarities of enterovirus circulation on some territories of Russia in 2017. Materials and methods: We investigated more than 5000 samples from the patients with enterovirus infection. The isolation and identification of enteroviruses were conducted by virological method and by partial sequencing of the genome region VP1. Phylogenic trees were constructed according to the method of Bayesian Monte Carlo Markov Chain. Results: Epidemic process and clinical picture of enterovirus infection were not the same on different territories. Peculiarities of the circulation of different types of enteroviruses on the territories were also different. In Saratov region 65% of cases were represented by enterovirus meningitis. In Murmansk region and in the Komi Republic enterovirus infection with exanthema prevailed, 95% and 60% correspondingly. In Saratov region enterovirus ECHO18 was the etiological agent of enterovirus meningitis. In Murmansk region and in the Komi Republic the cases were connected mainly with Coxsackieviruses A6. The strains of enterovirus ECHO18 were distributed to three clusters. The strains which provoked enterovirus meningitis in Saratov region belonged to cluster 3, they were formed separately from other strains of this enterovirus type and differed from the stains of ECHO18 which circulated in the North-West of Russia. The strains of Coxsackieviruses A6 identified in the North-West of Russia belonged to three sub-genotypes 5, 6, 8 of pandemic genotype of CoxsackievirusesA6. The majority of the strains belonged to sub-genotypes 6 and 8 which in 2017 dominated in the structure of Coxsackieviruses A6 in the North-West of Russia and in Russia. Conclusion: Epidemic peaks of enterovirus infection represented by different clinical forms of the disease were provoked by different types of enteroviruses. Enterovirus ECHO18 was the etiological agent of enterovirus meningitis. The main etiological factors of enterovirus infection with exanthema were Coxsackieviruses A6 of different sub-genotypes.Π¦Π΅Π»Ρ: Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ ΠΈ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΡΠΈΡΠΊΡΠ»ΡΡΠΈΠΈ Π½Π΅ΠΏΠΎΠ»ΠΈΠΎΠΌΠΈΠ΅Π»ΠΈΡΠ½ΡΡ
ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠΎΠ² Π½Π° ΡΡΠ΄Π΅ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ Π ΠΎΡΡΠΈΠΈ Π² 2017 Π³. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΎ Π±ΠΎΠ»Π΅Π΅ 5000 ΠΏΡΠΎΠ± ΡΠ΅ΠΊΠ°Π»ΠΈΠΉ ΠΎΡ Π±ΠΎΠ»ΡΠ½ΡΡ
ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ. ΠΡΠ΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΈ ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠΎΠ² ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π²ΠΈΡΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΈ ΠΏΡΡΡΠΌ ΡΠ°ΡΡΠΈΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΠΊΠ²Π΅Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΎΠ±Π»Π°ΡΡΠΈ Π³Π΅Π½ΠΎΠΌΠ° VP1. Π€ΠΈΠ»ΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π΅ΡΠ΅Π²ΡΡ Π±ΡΠ»ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Bayesian Monte Carlo Markov Chain. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΈ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΎΡΠ²Π»Π΅Π½ΠΈΡ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π½Π° ΡΠ°Π·Π½ΡΡ
ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΡΡ
ΠΎΡΠ»ΠΈΡΠ°Π»ΠΈΡΡ. ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΠΈΡΠΊΡΠ»ΡΡΠΈΠΈ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠΎΠ² ΡΠ°Π·Π½ΡΡ
ΡΠΈΠΏΠΎΠ² Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΡΡ
ΡΠ°ΠΊΠΆΠ΅ Π±ΡΠ»ΠΈ ΡΠ°Π·Π½ΡΠΌΠΈ. Π Π‘Π°ΡΠ°ΡΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ 65% Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ Π±ΡΠ»ΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΡΠΌ ΠΌΠ΅Π½ΠΈΠ½Π³ΠΈΡΠΎΠΌ. Π ΠΡΡΠΌΠ°Π½ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ Π² Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ΅ ΠΠΎΠΌΠΈ ΠΏΡΠ΅ΠΎΠ±Π»Π°Π΄Π°Π»ΠΈ ΡΠΊΠ·Π°Π½ΡΠ΅ΠΌΠ½ΡΠ΅ ΡΠΎΡΠΌΡ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ, ΡΠΎΡΡΠ°Π²ΠΈΠ²ΡΠΈΠ΅ 95% ΠΈ 60% ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ. Π Π‘Π°ΡΠ°ΡΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΡΡΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ ΠΌΠ΅Π½ΠΈΠ½Π³ΠΈΡΠ° ΠΎΠΊΠ°Π·Π°Π»ΡΡ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡ ΠΠ‘ΠΠ 18. Π ΠΡΡΠΌΠ°Π½ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ Π² Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ΅ ΠΠΎΠΌΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ Π±ΡΠ»ΠΈ ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Ρ Π² ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠΌ Coxsackievirus Π6. Π¨ΡΠ°ΠΌΠΌΡ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ° ΠΠ‘ΠΠ 18 ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»ΠΈΠ»ΠΈΡΡ ΠΏΠΎ ΡΡΠ΅ΠΌ ΠΊΠ»Π°ΡΡΠ΅ΡΠ°ΠΌ. Π¨ΡΠ°ΠΌΠΌΡ, ΠΎΠ±ΡΡΠ»ΠΎΠ²ΠΈΠ²ΡΠΈΠ΅ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΡΠΌ ΠΌΠ΅Π½ΠΈΠ½Π³ΠΈΡΠΎΠΌ Π² Π‘Π°ΡΠ°ΡΠΎΠ²ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ, Π²ΠΎΡΠ»ΠΈ Π² ΠΊΠ»Π°ΡΡΠ΅Ρ 3, ΠΎΠ½ΠΈ ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π»ΠΈΡΡ ΠΎΡΠ΄Π΅Π»ΡΠ½ΠΎ ΠΎΡ ΡΡΠ°ΠΌΠΌΠΎΠ² ΡΡΠΎΠ³ΠΎ ΡΠΈΠΏΠ° Π²ΠΈΡΡΡΠ° ΠΈ ΠΎΡΠ»ΠΈΡΠ°Π»ΠΈΡΡ ΠΎΡ ΡΡΠ°ΠΌΠΌΠΎΠ² ΠΠ‘ΠΠ18, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠΈΡΠΊΡΠ»ΠΈΡΠΎΠ²Π°Π»ΠΈ Π½Π° ΡΠ΅Π²Π΅ΡΠΎ-Π·Π°ΠΏΠ°Π΄Π΅ Π ΠΎΡΡΠΈΠΈ. Π¨ΡΠ°ΠΌΠΌΡ Π²ΠΈΡΡΡΠ° Coxsackievirus Π6, ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ Π½Π° ΡΠ΅Π²Π΅ΡΠΎ-Π·Π°ΠΏΠ°Π΄Π΅ Π ΠΎΡΡΠΈΠΈ, ΠΎΡΠ½ΠΎΡΠΈΠ»ΠΈΡΡ ΠΊ ΡΡΠ΅ΠΌ ΡΡΠ±Π³Π΅Π½ΠΎΡΠΈΠΏΠ°ΠΌ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π³Π΅Π½ΠΎΡΠΈΠΏΠ° Π²ΠΈΡΡΡΠ° Coxsackievirus Π6 β 5, 6 ΠΈ 8. ΠΠΎΠ»ΡΡΠΈΠ½ΡΡΠ²ΠΎ ΡΡΠ°ΠΌΠΌΠΎΠ² ΠΎΡΠ½ΠΎΡΠΈΠ»ΠΈΡΡ ΠΊ ΡΡΠ±Π³Π΅Π½ΠΎΡΠΈΠΏΠ°ΠΌ 6 ΠΈ 8, ΠΊΠΎΡΠΎΡΡΠ΅ Π² 2017 Π³. Π΄ΠΎΠΌΠΈΠ½ΠΈΡΠΎΠ²Π°Π»ΠΈ Π² ΡΡΡΡΠΊΡΡΡΠ΅ Coxsackieviruses Π6 Π½Π° ΡΠ΅Π²Π΅ΡΠΎ-Π·Π°ΠΏΠ°Π΄Π΅ Π ΠΎΡΡΠΈΠΈ ΠΈ Π² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π² ΡΠ΅Π»ΠΎΠΌ. ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅: ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΠ΄ΡΠ΅ΠΌΡ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΠΎΠΉ ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌΠΈ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠΎΡΠΌΠ°ΠΌΠΈ, Π±ΡΠ»ΠΈ ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Ρ ΡΠ°Π·Π½ΡΠΌΠΈ ΡΠΈΠΏΠ°ΠΌΠΈ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠΎΠ². ΠΡΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ Π°Π³Π΅Π½ΡΠΎΠΌ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΠ½ΠΎΠ³ΠΎ ΠΌΠ΅Π½ΠΈΠ½Π³ΠΈΡΠ° Π±ΡΠ»ΠΈ ΡΠ½ΡΠ΅ΡΠΎΠ²ΠΈΡΡΡΡ ΠΠ‘ΠΠ 18. ΠΡΠ½ΠΎΠ²Π½ΡΠΌ ΡΡΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ ΡΠΊΠ·Π°Π½ΡΠ΅ΠΌΠ½ΡΡ
ΡΠΎΡΠΌ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ Π±ΡΠ»ΠΈ Coxsackieviruses A6 ΡΠ°Π·Π½ΡΡ
ΡΡΠ±Π³Π΅Π½ΠΎΡΠΈΠΏΠΎΠ²
Specification of mechanisms of earthquake sources in the Carpathian region
One of the urgent problems - a solution of the focal mechanism of an earthquake is considered. On the example of several events occurred in the Carpathian region of Ukraine, the solving of this problem with a graphic method is proposed. This method is based on identifying the best location option of nodal planes relatively to both the fuzzy P-wave arrivals and the values of the logarithm of the ratio of the S-wave amplitude to the P-wave amplitude. A sequence of plotting diagrams for determining the focal mechanism is presented. The focal mechanisms and types of faults are determined by using this method for 6 events occurred in the Transcarpathian region. The similarity of the focal mechanisms for repeated earthquakes is shown. The dynamic parameters of the sources of 4 earthquakes occurred in 2012-2013 are retrieved by using data from the spectra of records converted into displacements according to the Brune model