207 research outputs found
Conformally maximal metrics for Laplace eigenvalues on surfaces
The paper is concerned with the maximization of Laplace eigenvalues on
surfaces of given volume with a Riemannian metric in a fixed conformal class. A
significant progress on this problem has been recently achieved by
Nadirashvili-Sire and Petrides using related, though different methods. In
particular, it was shown that for a given , the maximum of the -th
Laplace eigenvalue in a conformal class on a surface is either attained on a
metric which is smooth except possibly at a finite number of conical
singularities, or it is attained in the limit while a "bubble tree" is formed
on a surface. Geometrically, the bubble tree appearing in this setting can be
viewed as a union of touching identical round spheres. We present another proof
of this statement, developing the approach proposed by the second author and Y.
Sire. As a side result, we provide explicit upper bounds on the topological
spectrum of surfaces.Comment: 52 pages, 3 figures, added a section on explicit constant in
Korevaar's inequality, minor correction
Drift chamber readout system of the DIRAC experiment
A drift chamber readout system of the DIRAC experiment at CERN is presented. The system is intended to read out the signals from planar chambers operating in a high current mode. The sense wire signals are digitized in the 16-channel time-to-digital converter boards which are plugged in the signal plane connectors. This design results in a reduced number of modules, a small number of cables and high noise immunity. The system has been successfully operating in the experiment since 1999
Conformally maximal metrics for Laplace eigenvalues on surfaces
The paper is concerned with the maximization of Laplace eigenvalues on surfaces of given volume with a Riemannian metric in a fixed conformal class. A significant progress on this problem has been recently achieved by Nadirashvili-Sire and Petrides using related, though different methods. In particular, it was shown that for a given k, the maximum of the k-th Laplace eigenvalue in a conformal class on a surface is either attained on a metric which is smooth except possibly at a finite number of conical singularities, or it is attained in the limit while a "bubble tree" is formed on a surface. Geometrically, the bubble tree appearing in this setting can be viewed as a union of touching identical round spheres. We present another proof of this statement, developing the approach proposed by the second author and Y. Sire. As a side result, we provide explicit upper bounds on the topological spectrum of surfaces
Joint Verification and Reranking for Open Fact Checking Over Tables
Structured information is an important knowledge source for automatic verification of factual claims. Nevertheless, the majority of existing research into this task has focused on textual data, and the few recent inquiries into structured data have been for the closed-domain setting where appropriate evidence for each claim is assumed to have already been retrieved. In this paper, we investigate verification over structured data in the open-domain setting, introducing a joint reranking-and-verification model which fuses evidence documents in the verification component. Our open-domain model achieves performance comparable to the closed-domain state-of-the-art on the TabFact dataset, and demonstrates performance gains from the inclusion of multiple tables as well as a significant improvement over a heuristic retrieval baseline
Π Π΅ΡΠ΅Π½Π·ΠΈΡ Π½Π° ΡΡΠ°ΡΡΡ Β«ΠΠΎΠ»ΠΈΠΌΠΎΡΡΠΈΠ·ΠΌ Π³Π΅Π½Π° ΠΎΠΏΠΈΠΎΠΈΠ΄Π½ΠΎΠ³ΠΎ ΞΌ1-ΡΠ΅ΡΠ΅ΠΏΡΠΎΡΠ° (OPRM1) ΠΌΠΎΠΆΠ΅Ρ ΠΈΠΌΠ΅ΡΡ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ Π² Π³Π΅Π½Π΅Π·Π΅ Π·Π»ΠΎΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ Π½ΠΎΠ²ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΠΎΡΠΊΠΈΒ»
.ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΡΡΡΡΠΊΡΡΡΡ Π³Π΅Π½ΠΎΠ², ΠΏΡΠ΅Π΄ΡΠ°ΡΠΏΠΎΠ»Π°Π³Π°ΡΡΠΈΡ
ΠΊ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ ΠΎΠ½ΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ, Π²ΠΊΠ»ΡΡΠ°Ρ ΡΠ°ΠΊ ΠΏΠΎΡΠΊΠΈ, Π½Π΅ΡΠΎΠΌΠ½Π΅Π½Π½ΠΎ, ΡΠ²Π»ΡΠ΅ΡΡΡ Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΠΌ. Π ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΠΌΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΎ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΠΏΠΎΠ»ΠΈΠΌΠΎΡΡΠΈΠ·ΠΌΠ° 118A>G Π³Π΅Π½Π° ΠΎΠΏΠΈΠΎΠΈΠ΄Π½ΠΎΠ³ΠΎ ΞΌ-ΡΠ΅ΡΠ΅ΠΏΡΠΎΡΠ° 1 ΡΠΈΠΏΠ° (OPRM1) Π½Π° Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΠ΅ ΡΠ°ΠΊΠ° ΠΏΠΎΡΠΊΠΈ. ΠΡΡ
ΠΎΠ΄Ρ ΠΈΠ· ΠΈΠΌΠ΅ΡΡΠΈΡ
ΡΡ Π² Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ΅ Π΄Π°Π½Π½ΡΡ
ΠΏΠΎ Π½Π΅ΠΊΠΎΡΠΎΡΡΠΌ Π·Π»ΠΎΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌ ΠΎΠΏΡΡ
ΠΎΠ»ΡΠΌ, ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π³Π΅Π½Π° OPRM1 ΠΏΡΠΈ ΡΠ°ΠΊΠ΅ ΠΏΠΎΡΠΊΠΈ ΡΠ»Π΅Π΄ΡΠ΅Ρ ΡΡΠΈΡΠ°ΡΡ ΠΎΠΏΡΠ°Π²Π΄Π°Π½Π½ΠΎΠΉ ΠΏΠΎΡΡΠ°Π½ΠΎΠ²ΠΊΠΎΠΉ Π²ΠΎΠΏΡΠΎΡΠ°. Π ΠΎΠ±ΡΡΠΆΠ΄Π°Π΅ΠΌΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΎΡΠ° ΠΏΠΎΠ»ΠΈΠΌΠΎΡΡΠΈΠ·ΠΌΠ° 118A>G Π³Π΅Π½Π° OPRM1 ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π° Π² Π³ΡΡΠΏΠΏΠ°Ρ
Π΄ΠΎΠ±ΡΠΎΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΈ Π·Π»ΠΎΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ ΠΏΠΎΡΠΊΠΈ
The multilevel trigger system of the DIRAC experiment
The multilevel trigger system of the DIRAC experiment at CERN is presented.
It includes a fast first level trigger as well as various trigger processors to
select events with a pair of pions having a low relative momentum typical of
the physical process under study. One of these processors employs the drift
chamber data, another one is based on a neural network algorithm and the others
use various hit-map detector correlations. Two versions of the trigger system
used at different stages of the experiment are described. The complete system
reduces the event rate by a factor of 1000, with efficiency 95% of
detecting the events in the relative momentum range of interest.Comment: 21 pages, 11 figure
Domain-matched Pre-training Tasks for Dense Retrieval
Pre-training on larger datasets with ever increasing model size is now a proven recipe for increased performance across almost all NLP tasks. A notable exception is information retrieval, where additional pre-training has so far failed to produce convincing results. We show that, with the right pre-training setup, this barrier can be overcome. We demonstrate this by pre-training large bi-encoder models on 1) a recently released set of 65 million synthetically generated questions, and 2) 200 million post-comment pairs from a preexisting dataset of Reddit conversations. We evaluate on a set of information retrieval and dialogue retrieval benchmarks, showing substantial improvements over supervised baselines
Π€ΠΈΠ±ΡΠΎΠΌΠ° ΠΌΠ΅ΠΆΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΎΠ²ΠΎΠΉ ΠΏΠ΅ΡΠ΅Π³ΠΎΡΠΎΠ΄ΠΊΠΈ Ρ Π΄Π²ΡΡΡΠΎΡΠΎΠ½Π½Π΅ΠΉ ΠΎΠ±ΡΡΡΡΠΊΡΠΈΠ΅ΠΉ Π²ΡΡ ΠΎΠ΄Π½ΡΡ ΡΡΠ°ΠΊΡΠΎΠ² ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΎΠ²
Heart fibroma accounts for about 5% of all primary neoplasms and is registered in children in 80% of cases. The ventricles or interventricular septum (IVS) are most often affected; in half of cases, the tumor has intracavitary growth. The clinical picture of the disease and its prognosis depend on the size and location of the tumor. The most unfavorable is the defeat of the IVS, since it causes obstruction of the output tract of one of the ventricles. Being localized in IVS, can involve a conducting system of heart, thereby increasing risk of sudden death.A retrospective study of a case of cardiac fibroma in a child aged 4.5 months, confirmed by echocardiography, magnetic resonance imaging and successfully operated on in the Central Federal District Center of Penza, is presented. A large tumor, localized in the IVS, caused atypical obstruction of the outflow tracts of both ventricles simultaneously. In the domestic and foreign literature, hemodynamic disturbances of only one of the ventricles are described, and we did not find a single case with simultaneous obstruction of both tracts. The possibility of MRI in the diagnosis of heart tumors has been shown.Π€ΠΈΠ±ΡΠΎΠΌΠ° ΡΠ΅ΡΠ΄ΡΠ° ΡΠΎΡΡΠ°Π²Π»ΡΠ΅Ρ ΠΎΠΊΠΎΠ»ΠΎ 5% Π²ΡΠ΅Ρ
ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ
Π½ΠΎΠ²ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠΉ ΠΈ Π² 80% ΡΠ»ΡΡΠ°Π΅Π² ΡΠ΅Π³ΠΈΡΡΡΠΈΡΡΠ΅ΡΡΡ Ρ Π΄Π΅ΡΠ΅ΠΉ. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ°ΡΡΠΎ ΠΏΠΎΡΠ°ΠΆΠ°ΡΡΡΡ ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΈ ΠΈΠ»ΠΈ ΠΌΠ΅ΠΆΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΎΠ²Π°Ρ ΠΏΠ΅ΡΠ΅Π³ΠΎΡΠΎΠ΄ΠΊΠ° (ΠΠΠ), Π² ΠΏΠΎΠ»ΠΎΠ²ΠΈΠ½Π΅ ΡΠ»ΡΡΠ°Π΅Π² ΠΎΠΏΡΡ
ΠΎΠ»Ρ ΠΈΠΌΠ΅Π΅Ρ Π²Π½ΡΡΡΠΈΠΏΠΎΠ»ΠΎΡΡΠ½ΠΎΠΉ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ ΡΠΎΡΡΠ°. Π Π°ΡΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ ΠΈ ΡΠ°Π·ΠΌΠ΅Ρ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΡΡ ΠΊΠ°ΡΡΠΈΠ½Ρ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ· Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΌ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΠ΅ ΠΠΠ, ΠΏΠΎΡΠΊΠΎΠ»ΡΠΊΡ Π²ΡΠ·ΡΠ²Π°Π΅Ρ ΠΎΠ±ΡΡΡΡΠΊΡΠΈΡ Π²ΡΡ
ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΡΡΠ°ΠΊΡΠ° ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΈΠ· ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΎΠ². ΠΠΎΠΊΠ°Π»ΠΈΠ·ΡΡΡΡ Π² ΠΠΠ, ΠΌΠΎΠΆΠ΅Ρ Π²ΠΎΠ²Π»Π΅ΠΊΠ°ΡΡ ΠΏΡΠΎΠ²ΠΎΠ΄ΡΡΡΡ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠ΅ΡΠ΄ΡΠ°, ΡΠ΅ΠΌ ΡΠ°ΠΌΡΠΌ ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Ρ ΡΠΈΡΠΊ Π²Π½Π΅Π·Π°ΠΏΠ½ΠΎΠΉ ΡΠΌΠ΅ΡΡΠΈ.ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΎ ΡΠ΅ΡΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ»ΡΡΠ°Ρ ΡΠΈΠ±ΡΠΎΠΌΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΡΠ΅Π±Π΅Π½ΠΊΠ° Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ΅ 4,5 ΠΌΠ΅Ρ, ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ ΡΡ
ΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ, ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎ-ΡΠ΅Π·ΠΎΠ½Π°Π½ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ ΠΈ ΡΡΠΏΠ΅ΡΠ½ΠΎ ΠΎΠΏΠ΅ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π² Π€Π¦Π‘Π‘Π₯ Π³. ΠΠ΅Π½Π·Ρ. ΠΠΏΡΡ
ΠΎΠ»Ρ Π±ΠΎΠ»ΡΡΠΈΡ
ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ², Π»ΠΎΠΊΠ°Π»ΠΈΠ·ΡΡΡΡ Π² ΠΠΠ, Π²ΡΠ·ΡΠ²Π°Π»Π° Π½Π΅ΡΠΈΠΏΠΈΡΠ½ΡΡ ΠΎΠ±ΡΡΡΡΠΊΡΠΈΡ ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ Π²ΡΡ
ΠΎΠ΄Π½ΡΡ
ΡΡΠ°ΠΊΡΠΎΠ² ΠΎΠ±ΠΎΠΈΡ
ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΎΠ². Π ΠΎΡΠ΅ΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΈ Π·Π°ΡΡΠ±Π΅ΠΆΠ½ΠΎΠΉ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ΅ ΠΎΠΏΠΈΡΡΠ²Π°ΡΡΡΡ Π½Π°ΡΡΡΠ΅Π½ΠΈΡ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ ΡΠΎΠ»ΡΠΊΠΎ ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΈΠ· ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠΎΠ², ΠΈ Π½Π°ΠΌΠΈ Π½Π΅ Π±ΡΠ»ΠΎ Π½Π°ΠΉΠ΄Π΅Π½ΠΎ Π½ΠΈ ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΡΠ»ΡΡΠ°Ρ Ρ ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΎΠ±ΡΡΡΡΠΊΡΠΈΠ΅ΠΉ ΠΎΠ±ΠΎΠΈΡ
ΡΡΠ°ΠΊΡΠΎΠ². ΠΠΎΠΊΠ°Π·Π°Π½Π° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΠ Π’ Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ ΡΠ΅ΡΠ΄ΡΠ°
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