211 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
Corrosion Protection of the Zone of Thermal Action (Zone of Butt of Tubes While Welding) from the Inside When Laying Multifunctional Pipeline Systems
The work is aimed at handling a main problem of corrosion protection of the pipeline s interior section adjacent to a weld butt. It is proposed to execute fastening of elements of the protective system of pipes by application of the pulse-magnetic technology which has essential technical and economical advantages over other methods. Protection of end sections of pipes is performed by pulse-magnetic pressing-in of a bush made from stainless steel or by pulse-magnetic welding of rings from a protective material. Commercial tests of the pipelines produced by the technology being proposed supported good prospects of this technology use
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
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