200 research outputs found
Π‘ΡΠ°Π²Π½ΠΈΡΠ΅Π»ΡΠ½Π°Ρ Ρ Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠΎΡΡΠΎΠ² Π’ΠΎΠΌΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ ΡΠ΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ»ΡΠ°ΠΉ
Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ Π±ΡΠ»Π° ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π° ΡΡΠ°Π²Π½ΠΈΡΠ΅Π»ΡΠ½Π°Ρ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΡΠΎΡΡΠΎΠ² Π’ΠΎΠΌΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ ΡΠ΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ»ΡΠ°ΠΉ. ΠΠ»Ρ ΡΡΠΈΡ
ΡΠΎΡΡΠΎΠ² Π±ΡΠ»ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈ Π³ΡΡΠΏΠΏΠΎΠ²ΠΎΠΉ ΡΠΎΡΡΠ°Π²Ρ.
Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ Π²ΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠΎΡΡΠ° Ρ ΠΌΠ΅ΡΡΠΎΡΠΎΠΆΠ΄Π΅Π½ΠΈΠΉ Π’ΠΎΠΌΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈ ΡΠ΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ»ΡΠ°ΠΉ ΠΎΡΠ»ΠΈΡΠ°ΡΡΡΡ ΠΏΠΎ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΠ°Π·Π»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΈ Π·ΠΎΠ»ΡΠ½ΠΎΡΡΠΈ. Π ΡΠΎΡΡΠ°Ρ
ΡΠ΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ»ΡΠ°ΠΉ ΠΏΠΎΠ»ΡΡΠΈΠ»ΠΈ Π±ΠΎΠ»ΡΡΠ΅Π΅ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ Π³ΡΠΌΠΈΠ½ΠΎΠ²ΡΡ
ΠΊΠΈΡΠ»ΠΎΡ ΠΈ Π»ΠΈΠ³Π½ΠΈΠ½Π° ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΡΠΎΡΡΠ°ΠΌΠΈ Π’ΠΎΠΌΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ .
ΠΡΠΎΠΌΠ΅ ΡΡΠΎΠ³ΠΎ, Π² ΡΠΎΡΡΠ°Ρ
ΡΠ΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ»ΡΠ°ΠΉ Π²ΡΡΠ²Π»Π΅Π½ΠΎ Π½ΠΈΠ·ΠΊΠΎΠ΅ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ Π±ΠΈΡΡΠΌΠΎΠ² ΠΈ ΡΠ³Π»Π΅Π²ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ° ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½Π½ΠΎΠ΅ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ Π³ΡΠΌΠΈΠ½ΠΎΠ²ΡΡ
ΠΊΠΈΡΠ»ΠΎΡ ΠΈ Π»ΠΈΠ³Π½ΠΈΠ½Π°. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ Π½Π° Π±Π°Π·Π΅ ΠΌΠ΅ΡΡΠΎΡΠΎΠΆΠ΄Π΅Π½ΠΈΠΉ ΡΠ΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ»ΡΠ°ΠΉ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Π° ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° Π³ΡΠΌΠΈΠ½ΠΎΠ²ΡΡ
ΠΊΠΈΡΠ»ΠΎΡ ΠΈ Π±ΠΈΡΡΠΌΠΎΠ² Π² ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ
ΡΠ°Π·ΠΌΠ΅ΡΠ°Ρ
.In this work the comparative characteristic of peats of the Tomsk region and Altai Republic has been carried out. For these peats, the technical and group compositions were determined.
As a result of the researches it is revealed that peats from deposits of the Tomsk region and Altai Republic differ on extent of decomposition and an ash-content. In peats of Altai Republic have received the bigger content of humic acids and a lignin in comparison with peats of the Tomsk region.
Besides, in peats of Altai Republic the low content of bitumens and a carbohydrate complex and the increased content of humic acids and a lignin is revealed. It is established that on the basis of fields of Altai Republic the organization of production of humic acids and bitumens in limited sizes is possible
Analysis of 2D airglow imager data with respect to dynamics using machine learning
We demonstrate how machine learning can be easily applied to support the analysis of large quantities of excited hydroxyl (OH*) airglow imager data. We use a TCN (temporal convolutional network) classification algorithm to automatically pre-sort images into the three categories βdynamicβ (images where small-scale motions like turbulence are likely to be found), βcalmβ (clear-sky images with weak airglow variations) and βcloudyβ (cloudy images where no airglow analyses can be performed). The proposed approach is demonstrated using image data of FAIM 3 (Fast Airglow IMager), acquired at Oberpfaffenhofen, Germany, between 11 June 2019 and 25 February 2020, achieving a mean average precision of 0.82 in image classification. The attached video sequence demonstrates the classification abilities of the learned TCN.
Within the dynamic category, we find a subset of 13 episodes of image series showing turbulence. As FAIM 3 exhibits a high spatial (23βm per pixel) and temporal (2.8βs per image) resolution, turbulence parameters can be derived to estimate the energy diffusion rate. Similarly to the results the authors found for another FAIM station (Sedlak et al., 2021), the values of the energy dissipation rate range from 0.03 to 3.18βWβkgβ1
Schallemissionsanalyse zur Untersuchung des SchΓ€digungsverhaltens im Auszugversuch eines in Beton eingebetteten Multifilamentgarns
Zur Untersuchung der SchΓ€digungs- und Versagensmechanismen eines in Beton eingebetteten Multifilamentgarns im Auszugversuch wurde die Schallemissionsanalyse zur Identifizierung und Lokalisierung von FilamentbrΓΌchen eingesetzt. Im ersten Schritt wurden dazu die Schall emittierenden Ursachen (Filamentriss, FilamentablΓΆsung und Mikroriss im Beton) fΓΌr eine Differenzierung charakterisiert. Es wurden Versuche zur Erzeugung von isolierten Signalen durchgefΓΌhrt, welche mit Hilfe der Signal- und Frequenzanalyse untersucht wurden. Bei dem durchgefΓΌhrten Garnauszugversuch konnte eine hohe Lokalisierungsgenauigkeit der FilamentbrΓΌche erzielt werden. Der SchΓ€digungsverlauf des Garns wΓ€hrend des Auszugversuchs konnte detailliert untersucht werden
Deformation around neutron-rich Cr isotopes in axially symmetric Skyrme-Hatree-Fock-Bogoliubov method
We analyse deformation mechanism in neutron-rich Cr, Fe and Ti isotopes with
N=32-44 by means of a Skyrme-Hartree-Fock-Bogoliubov mean-field code employing
a two-dimensional mesh representation in the cylindrical coordinate system.
Evaluating systematically the quadrupole deformation energy, we show that the
Skyrme parameter set SkM* gives a quadrupole instability around the neutron
number N38-42 in Cr isotopes, where the deformation energy curve suggests
a transitional behavior with a shallow minimum extending to a large prolate
deformation. Roles of a deformed N=38 gap and the position of the neutron g9/2
orbit are analysed in detail
Discovery of the Cadmium Isotopes
Thirty-seven cadmium isotopes have so far been observed; the discovery of
these isotopes is discussed. For each isotope a brief summary of the first
refereed publication, including the production and identification method, is
presented.Comment: to be published in Atomic Data and Nuclear Data Table
Spuren der durch die Eruption des Hunga Tonga-Hunga Ha'apai ausgelΓΆsten Druckwelle auch in der Mittleren AtmosphΓ€re ΓΌber Europa
On January 15th 2022 the Hunga Tonga β Hunga Ha'apai volcano erupted and generated strong atmospheric pressure waves of which some propagated several times across the globe. At the Environmental Research Station βSchneefernerhausβ (UFS), as well as in whole Europe, signals could be detected even at MLT (Mesosphere-Lower-Thermosphere) heights (80-100 km) using the GRIPS (GRound-based Infrared P-branch Spectrometer) and the BAIER (Bavarian Airglow ImagER) instruments for the observation of the OH and the O2 airglow
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