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.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

Рецензия на статью «Полиморфизм гена опиоидного μ1-рецептора (OPRM1) может иметь значение в генезе злокачественных новообразований почки»

.Изучение особенностей структуры генов, предрасполагающих к возникновению онкологических заболеваний, включая рак почки, несомненно, является актуальным. В рассматриваемой работе исследовано возможное влияние полиморфизма 118A>G гена опиоидного μ-рецептора 1 типа (OPRM1) на возникновение рака почки. Исходя из имеющихся в литературе данных по некоторым злокачественным опухолям, исследование гена OPRM1 при раке почки следует считать оправданной постановкой вопроса. В обсуждаемой работе частота полиморфизма 118A>G гена OPRM1 определена в группах доброкачественных и злокачественных опухолей почки

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 $\geq$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