Monte Carlo simulations of ultra high energy secondary neutrino detection in the DUNE experiment

In this research we do an evaluation on expected secondary neutrino flux in the DUNE detector from ultra high energy cosmic rays. Using Monte Carlo simulation software SimProp v.2.r.4. spectra of ultra high energy secondary neutrinos were obtained, and their flux on the Earth was evaluated. Two different primary sources (free protons and 56Fe cores) that correspond to different cosmic rays origins were used. For the calculations the source was considered to have cosmic ray injection power as L≈1045 erg/year. Simulations were conducted at three distances (in terms of redshift z): z = 0.1, z = 1.0 and z = 3.0. Numbers of secondary neutrino events in DUNE over 1 year is expected to be: 39.7, 0.17 and 0.006 for protons and 0.006, 0.0002 and 1.6 • 10−5 for 56Fe cores accordingly

The neutron 'thunder' accompanying the extensive air shower

Simulations show that neutrons are the most abundant component among extensive air shower hadrons. However, multiple neutrons which appear with long delays in neutron monitors nearby the EAS core ('neutron thunder') are mostly not the neutrons of the shower, but have a secondary origin. The bulk of them is produced by high energy EAS hadrons hitting the monitors. The delays are due to the termalization and diffusion of neutrons in the moderator and reflector of the monitor accompanied by the production of secondary gamma-quanta. This conclusion raises the important problem of the interaction of EAS with the ground, the stuff of the detectors and their environment since they have often hydrogen containing materials like polyethilene in neutron monitors. Such interaction can give an additional contribution to the signal in the EAS detectors. It can be particularly important for the signals from scintillator or water tank detectors at km-long distances from the EAS core where neutrons of the shower become the dominant component after a few mcsec behind the EAS front.Comment: 12 pages, 4 figures, accepted by J.Phys.G: Nucl.Part.Phy

Different metastasis promotive potency of small G-proteins RalA and RalB in in vivo hamster tumor model

<p>Abstract</p> <p>Background</p> <p>Previously we have shown that oncogenic Ha-Ras stimulated <it>in vivo </it>metastasis through RalGEF-Ral signaling. RalA and RalB are highly homologous small G proteins belonging to Ras superfamily. They can be activated by Ras-RalGEF signaling pathway and influence cellular growth and survival, motility, vesicular transport and tumor progression in humans and in animal models. Here we first time compared the influence of RalA and RalB on tumorigenic, invasive and metastatic properties of RSV transformed hamster fibroblasts.</p> <p>Methods</p> <p>Retroviral vectors encoding activated forms or effector mutants of RalA or RalB proteins were introduced into the low metastatic HET-SR cell line. Tumor growth and spontaneous metastatic activity (SMA) were evaluated on immunocompetent hamsters after subcutaneous injection of cells. The biological properties of cells, including proliferation, clonogenicity, migration and invasion were determined using MTT, wound healing, colony formation and Boyden chamber assays respectively. Protein expression and phosphorylation was detected by Westen blot analysis. Extracellular proteinases activity was assessed by substrate-specific zymography.</p> <p>Results</p> <p>We have showed that although both Ral proteins stimulated SMA, RalB was more effective in metastasis stimulation <it>in vivo </it>as well as in potentiating of directed movement and invasion <it>in vitro</it>. Simultaneous expression of active RalA and RalB didn't give synergetic effect on metastasis formation. RalB activity decreased expression of Caveolin-1, while active RalA stimulated MMP-1 and uPA proteolytic activity, as well as CD24 expression. Both Ral proteins were capable of Cyclin D1 upregulation, JNK1 kinase activation, and stimulation of colony growth and motility. Among three main RalB effectors (RalBP1, exocyst complex and PLD1), PLD1 was essential for RalB-dependent metastasis stimulation.</p> <p>Conclusions</p> <p>Presented results are the first data on direct comparison of RalA and RalB impact as well as of RalA/RalB simultaneous expression influence on <it>in vivo </it>cell metastatic activity. We showed that RalB activation significantly more than RalA stimulates SMA. This property correlates with the ability of RalB to stimulate <it>in vitro </it>invasion and serum directed cell movement. We also found that RalB-PLD1 interaction is necessary for the acquisition of RalB-dependent high metastatic cell phenotype. These findings contribute to the identification of molecular mechanisms of metastasis and tumor progression.</p

Оптимизация параметров лазерного раскалывания силикатных стекол эллиптическими пучками в плоскости, параллельной поверхности

Regression and neural network models of the process of laser splitting of silicate glasses by elliptical beams in a plane parallel to the surface were obtained. To conduct a numerical experiment, a central compositional plan was used. The processing speed, laser beam power and its geometric parameters were selected as variable factors. As responses, the values of maximum temperatures and the values of maximum thermoelastic tensile stresses in the processing zone were determined, the calculation of which was performed using the APDL programming language. An effective architecture for an artificial neural network created using the TensorFlow program has been established. A comparative analysis of neural network and regression models was carried out. The influence of input parameters on responses was assessed. Using the MOGA algorithm of the ANSYS program, the optimal modes for the formation of laser-induced cracks by elliptical beams were determined, ensuring the effective implementation of parallel laser splitting of silicate glass.Получены регрессионные и нейросетевые модели процесса лазерного раскалывания силикатных стекол эллиптическими пучками в плоскости, параллельной поверхности. Для проведения численного эксперимента был использован центральный композиционный план. В качестве варьируемых факторов выбраны скорость обработки, мощность лазерного пучка и его геометрические параметры. В качестве откликов определялись значения максимальных температур и значения максимальных термоупругих напряжений растяжения в зоне обработки, расчет которых был выполнен с применением языка программирования APDL. Установлена эффективная архитектура искусственной нейронной сети, созданной с использованием программы TensorFlow. Проведен сравнительный анализ нейросетевых и регрессионных моделей. Выполнена оценка влияния входных параметров на отклики. С использованием алгоритма MOGA программы ANSYS определены оптимальные режимы формирования эллиптическими пучками лазерно-индуцированных трещин, обеспечивающие эффективную реализацию параллельного лазерного раскалывания силикатного стекла

Оптимизация параметров импульсной лазерной наплавки стали 30ХГСН2А с использованием генетического алгоритма

The paper presents the optimization of pulsed laser cladding of structural steel using a genetic algorithm. Using the ANSYS Workbench software, finite element modelling of laser cladding on a 30ХГСН2А steel substrate with an additive in the form of wire was conducted, considering the temperature dependence of the material's thermophysical properties. A surrogate model for pulsed laser cladding of 30ХГСН2Аsteel was developed employing a face-centered version of the central composite design experiment. The time intervals corresponding to the end time of the three fronts of the laser pulse and the diameter of the filler wire were considered as variable factors. The maximum temperatures in the treatment zone were used as responses. In order to optimize pulsed laser cladding of 30ХГСН2А steel, the maximum temperature limit values in the treatment zone were established for three moments of time that corresponded to the laser pulse fronts at the three points in the finite element model. A comparison was made between the parameters obtained from optimization and those derived from finite element modelling. When determining temperatures, the maximum percentage error of the results obtained via the genetic algorithm did not exceed 3.5 %.В работе с использованием генетического алгоритма выполнена оптимизация импульсной лазерной наплавки конструкционной стали. Конечно-элементное моделирование лазерной наплавки на основу из стали 30ХГСН2А присадкой в виде проволоки выполнялось с учетом зависимости теплофизических свойств материала от температуры в программе ANSYS Workbench. С использованием гранецентрированного варианта центрального композиционного плана эксперимента была получена суррогатная модель импульсной лазерной наплавки стали 30ХГСН2А. В качестве варьируемых факторов эксперимента использовались временные интервалы, соответствующие времени окончания трех фронтов лазерного импульса, и диаметр присадочной проволоки. В качестве откликов использовались максимальные температуры в зоне обработки. Оптимизация импульсной лазерной наплавки стали 30ХГСН2А выполнялась при задании предельных значений максимальной температуры в зоне обработки для трех моментов времени, соответствующих фронтам лазерного импульса, в трех точках конечно-элементной модели. Выполнено сравнение параметров, полученных в результате оптимизации, и параметров, полученных в результате конечно-элементного моделирования. При определении температур максимальная относительная погрешность результатов, полученных с использованием генетического алгоритма, не превысила 3,5 %

Определение параметров лазерной обработки алмазов с применением метода конечных элементов и искусственных нейронных сетей

This paper provides the simulation of laser processing of diamonds by using a combination of artificial neural networks and the finite element method. The training data array and the data array for testing neural networks were generated in ANSYS. The calculations were performed for 600 types of input parameters, 60 of which were used to test artificial neural networks. The influence of the parameters of neural network models on the accuracy of determining temperatures in the laser processing area were studied. The parameters of neural networks were established that provide acceptable results in predicting temperatures generated by laser radiation in diamonds. The results obtained can be used to determine the technological parameters of the laser processing of diamonds.С помощью сочетания искусственных нейронных сетей и метода конечных элементов выполнено моделирование процесса лазерной обработки алмазов. Обучающий массив данных и массив данных для тестирования нейронных сетей были сформированы с использованием программы конечно-элементного анализа ANSYS. Расчеты выполняли для 600 вариантов входных параметров, 60 из которых использовали для тестирования искусственных нейронных сетей. Исследовано влияние параметров нейросетевых моделей на точность определения температур в зоне лазерной обработки. Установлены параметры нейронных сетей, обеспечивающие приемлемые результаты при прогнозировании температур, формируемых лазерным излучением в алмазах. Полученные результаты могут быть использованы при определении технологических параметров процессов лазерной обработки алмазов

Measurement of the integrated luminosity of the Phase 2 data of the Belle II experiment

© 2019 Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Sciences and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd. From April to July 2018, a data sample at the peak energy of the γ(4S) resonance was collected with the Belle II detector at the SuperKEKB electron-positron collider. This is the first data sample of the Belle II experiment. Using Bhabha and digamma events, we measure the integrated luminosity of the data sample to be (496.3 ± 0.3 ± 3.0) pb-1, where the first uncertainty is statistical and the second is systematic. This work provides a basis for future luminosity measurements at Belle II

Spectral Correlation in Incommensurate Multi-Walled Carbon Nanotubes

We investigate the energy spectra of clean incommensurate double-walled carbon nanotubes, and find that the overall spectral properties are described by the so-called critical statistics of Anderson metal-insulator transition. In the energy spectra, there exist three different regimes characterized by Wigner-Dyson, Poisson, and semi-Poisson distributions. This feature implies that the electron transport in incommensurate multi-walled nanotubes can be either diffusive, ballistic, or intermediate between them, depending on the position of the Fermi energy.Comment: final version to appear in Phys. Rev. Let