Long-term operation of a multi-channel cosmic muon system based on scintillation counters with MRS APD light readout

A Cosmic Ray Test Facility (CRTF) is the first large-scale implementation of a scintillation triggering system based on a new scintillation technique known as START. In START, the scintillation light is collected and transported by WLS optical fibers, while light detection is performed by pairs of avalanche photodiodes with the Metal-Resistor-Semiconductor structure operated in the Geiger mode (MRS APD). START delivers 100% efficiency of cosmic muon detection, while its intrinsic noise level is less than 10^{-2} Hz. CRTF, consisting of 160 START channels, has been continuously operated by the ALICE TOF collaboration for more than 25 000 hours, and has demonstrated a high level of stability. Fewer than 10% of MRS APDs had to be replaced during this period.Comment: Proceedings of NDIP-2008. 8 pages, 8 figures, 6 reference

Identification of earthquake precursors in the hydrogeochemical and geoacoustic data for the Kamchatka peninsula by flicker-noise spectroscopy

A phenomenological systems approach for identifying potential precursors in multiple signals of different types for the same local seismically active region is proposed based on the assumption that a large earthquake may be preceded by a system reconfiguration (preparation) at different time and space scales. A nonstationarity factor introduced within the framework of flicker-noise spectroscopy, a statistical physics approach to the analysis of time series, is used as the dimensionless criterion for detecting qualitative (precursory) changes within relatively short time intervals in arbitrary signals. Nonstationarity factors for chlorine-ion concentration variations in the underground water of two boreholes on the Kamchatka peninsula and geacoustic emissions in a deep borehole within the same seismic zone are studied together in the time frame around a large earthquake on October 8, 2001. It is shown that nonstationarity factor spikes (potential precursors) take place in the interval from 70 to 50 days before the earthquake for the hydrogeochemical data and at 29 and 6 days in advance for the geoacoustic data.Comment: 8 pages, 4 figures; to be published in Nat. Hazards Earth Syst. Sc

Scintillation counter with MRS APD light readout

START, a high-efficiency and low-noise scintillation detector for ionizing particles, was developed for the purpose of creating a high-granular system for triggering cosmic muons. Scintillation light in START is detected by MRS APDs (Avalanche Photo-Diodes with Metal-Resistance-Semiconductor structure), operated in the Geiger mode, which have 1 mm^2 sensitive areas. START is assembled from a 15 x 15 x 1 cm^3 scintillating plastic plate, two MRS APDs and two pieces of wavelength-shifting optical fiber stacked in circular coils inside the plastic. The front-end electronic card is mounted directly on the detector. Tests with START have confirmed its operational consistency, over 99% efficiency of MIP registration and good homogeneity. START demonstrates a low intrinsic noise of about 10^{-2} Hz. If these detectors are to be mass-produced, the cost of a mosaic array of STARTs is estimated at a moderate level of 2-3 kUSD/m^2.Comment: 6 pages, 5 figure

START as the detector of choice for large-scale muon triggering systems

Further progress in building high-granular large-scale systems based on Scintillation Tiles with MRS APD light readout (START) became possible thanks to the creation of an improved version of MRS APD. The cost of the system may now be significantly reduced by using inexpensive extruded scintillator. More than 160 START samples were assembled based on this design modification and proved to possess 100% MIP detection efficiency and the intrinsic noise rate of less than 0.08 Hz. Long-term stability of START characteristics was confirmed after 3.5 months of operation

АВТОМАТИЗИРОВАННАЯ СИСТЕМА ОБНАРУЖЕНИЯ ОБЪЕМНЫХ ОБРАЗОВАНИЙ В ЛЕГКИХ КАК ЭТАП РАЗВИТИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ДИАГНОСТИКЕ РАКА ЛЕГКОГО

In the century of the fourth industrial revolution, there is a rapid progress of technological developments in medicine. Possibilities of collecting large amounts of digital information and the modern computer capacity growth are reasons for the increased attention to artificial intelligence (AI) and its role in the diagnostics and the prediction of diseases. In the diagnostics, AI aims to model the human intellectual activity, providing assistance to a practicing doctor in the processing of big data. Development of AI can be considered as a way for implementation and ensuring of national political and economic interests in the health care improvement. Lung cancer is on the first position of cancer incidences. This implies that the development and implementation of computed-aided systems for lung cancer diagnostic is very urgent and important. The article presents the results concerning the development of a computed-aided system for the lung nodule detection, which is based on the processing of computed tomography data. Perspectives of the AI application to the lung cancer diagnostics are discussed. There is a few information about a role of Russian developments in this area in foreign and domestic literature.В эпоху четвертой промышленной революции отмечается стремительный прогресс технологических разработок в области медицины. Возможности накопления больших объемов цифровой информации и рост производительности современных компьютеров стали причиной повышенного внимания к искусственному интеллекту (ИИ) и его роли в диагностике и прогнозировании заболеваний. В диагностике искусственный интеллект призван моделировать человеческую деятельность, которая считается интеллектуальной, обеспечивая помощь практикующему врачу в обработке больших объемов данных (big data). Развитие ИИ может быть рассмотрено как мера реализации и обеспечения национальных интересов политической и экономической направленности в развитии здравоохранения. Рак легкого занимает лидирующую позицию в структуре онкологической заболеваемости, это диктует актуальность разработки и внедрения автоматизированных систем диагностики (АСД), ориентированных именно на рак легкого как социально значимого заболевания. В статье приводятся сведения о результатах разработки автоматизированной системы обнаружения объемных образований в легких на основе обработки данных компьютерной томографии, отражена перспектива ее использования в диагностике рака легкого с помощью ИИ. В зарубежной и отечественной литературе пока нет достаточного количества сведений о месте российских разработок в этой области

Study of QGP signatures with the phi->K+K- signal in Pb-Pb ALICE events

The phi->K+K- decay channel in Pb-Pb collisions at LHC is studied through a full simulation of the ALICE detector. The study focuses on possible signatures in this channel of quark-gluon plasma (QGP) formation. On a basis of 10^6 collisions at high centrality some proposed QGP signatures are clearly visible both in K+K- invariant mass and transverse mass distributions. The high significance of this observation appears to reside heavily on the use of the TOF (Time Of Flight) system of ALICE in addition to its central tracking detectors.Comment: 9 pages, 7 figures, to appear in EPJ

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Rare <i>Wolbachia</i> genotypes in laboratory <i>Drosophila melanogaster</i> strains

Symbiotic bacteria of the genus Wolbachia are widespread in Drosophila melanogaster populations. Based on the polymorphism of the Wolbachia genome, the symbionts’ diversity in D. melanogaster is presented by two groups: MEL (wMel, wMel2, wMel3 and wMel4) and CS (wMelCS and wMelCS2). The wMel genotype is predominant in natural D. melanogaster populations and is distributed all over the world. The CS genotypes, on the other hand, are of particular interest because it is unclear how they are maintained in the fruit f ly populations since they should have been eliminated from them due to their low frequency and genetic drift or been replaced by the wMel genotype. However, this is not what is really observed, which means these genotypes are supported by selection. It is known that the wMelPlus strain of the wMelCS genotype can increase the lifespan of infected f lies at high temperatures. The same genotype also increases the intensity of dopamine metabolism in Drosophila compared to the MEL-group genotypes. In the present study, we searched for the rare Wolbachia wMelCS and wMelCS2 genotypes, as well as for new genotypes in wild-type D. melanogaster strains and in several mutant laboratory strains. The symbiont was found in all populations, in 200 out of 385 wild-type strains and in 83 out of 170 mutant strains. Wolbachia diversity in D. melanogaster wild-type strains was represented by the wMel, wMelCS and wMelCS2 genotypes. More than 90 % of the infected strains carried wMel; 9 %, wMelCS2; and only two strains were found to carry wMelCS. No new Wolbachia genotypes were found. The northernmost point reported for the wMelCS2 genotype was Izhevsk city (Udmurtia, Russia). For the f irst time the wMelCS2 genotype was detected in D. melanogaster from the Sakhalin Island, and wMelCS, in the f lies from Nalchik (the North Caucasus). A comparison of Wolbachia genetic diversity between the wild-type laboratory strains and previously obtained data on mutant laboratory strains demonstrated differences in the frequencies of rare CS genotypes, which were more prevalent in mutant strains, apparently due to the breeding history of these Drosophila strains