The Theoretical Basis of Soybean Cutting Process and Knife Selection

This scientific research presents that a theoretical analysis of the methods and forces involved in the soybean seeding process. Detailed information on the projection of forces, the effect of forces on the working body of the soybean seeding device is given

Modelling of gas dynamical properties of the KATRIN tritium source and implications for the neutrino mass measurement

The KATRIN experiment aims to measure the effective mass of the electron antineutrino from the analysis of electron spectra stemming from the beta-decay of molecular tritium with a sensitivity of 200 meV. Therefore, a daily throughput of about 40 g of gaseous tritium is circulated in a windowless source section. An accurate description of the gas flow through this section is of fundamental importance for the neutrino mass measurement as it significantly influences the generation and transport of beta-decay electrons through the experimental setup. In this paper we present a comprehensive model consisting of calculations of rarefied gas flow through the different components of the source section ranging from viscous to free molecular flow. By connecting these simulations with a number of experimentally determined operational parameters the gas model can be refreshed regularly according to the measured operating conditions. In this work, measurement and modelling uncertainties are quantified with regard to their implications for the neutrino mass measurement. We find that the systematic uncertainties related to the description of gas flow are represented by $\Delta m_{\nu}^2=(-3.06\pm 0.24)\cdot10^{-3}$ eV$^2$, and that the gas model is ready to be used in the analysis of upcoming KATRIN data.Comment: 28 pages, 13 figure

Brain–computer interface and assist-as-needed model for upper limb robotic arm

https://journals.sagepub.com/doi/10.1177/1687814019875537Post-stroke paralysis, whereby subjects loose voluntary control over muscle actuation, is one of the main causes of disability. Repetitive physical therapy can reinstate lost motions and strengths through neuroplasticity. However, manually delivered therapies are becoming ineffective due to scarcity of therapists, subjectivity in the treatment, and lack of patient motivation. Robot-assisted physical therapy is being researched these days to impart an evidence-based systematic treatment. Recently, intelligent controllers and brain–computer interface are proposed for rehabilitation robots to encourage patient participation which is the key to quick recovery. In the present work, a brain–computer interface and assist-as-needed training paradigm have been proposed for an upper limb rehabilitation robot. The brain–computer interface system is implemented with the use of electroencephalography sensor; moreover, backdrivability in the actuator has been achieved with the use of assist-as-needed control approach, which allows subjects to move the robot actively using their limited motions and strengths. The robot only assists for the remaining course of trajectory which subjects are unable to perform themselves. The robot intervention point is obtained from the patient’s intent which is captured through brain–computer interface. Problems encountered during the practical implementation of brain–computer interface and achievement of backdrivability in the actuator have been discussed and resolved

The Future of the Russian Orthodox Church in the Context of Rapid Computerization of Society

The work considers the adaptation of the Russian Orthodox Church to the conditions of rapid computerization of society. The problem of translation of the sphere of spiritual life to the internet. Adaptation of the Church to the new conditional of existence.В работе рассматривается адаптация Русской православной церкви к условиям стремительной компьютеризации общества. Проблема перехода сферы духовной жизни в Интернет. Приспособление церкви к новым условиям существования

Bioinformatics analysis of the interaction of miRNAs and piRNAs with human mRNA genes having di- and trinucleotide repeats

The variability of nucleotide repeats is considered one of the causes of diseases, but their biological function is not understood. In recent years, the interaction of miRNAs and piRNAs with the mRNAs of genes responsible for developing neurodegenerative and oncological diseases and diabetes have been actively studied. We explored candidate genes with nucleotide repeats to predict associations with miRNAs and piRNAs. The parameters of miRNAs and piRNA binding sites with mRNAs of human genes having nucleotide repeats were determined using the MirTarget program. This program defines the start of the initiation of miRNA and piRNA binding to mRNAs, the localization of miRNA and piRNA binding sites in the 5'-untranslated region (5'UTR), coding sequence (CDS) and 3'-untranslated region (3'UTR); the free energy of binding; and the schemes of nucleotide interactions of miRNAs and piRNAs with mRNAs. The characteristics of miRNAs and piRNA binding sites with mRNAs of 73 human genes were determined. The 5'UTR, 3'UTR and CDS of the mRNAs of genes are involved in the development of neurodegenerative, oncological and diabetes diseases with GU, AC dinucleotide and CCG, CAG, GCC, CGG, CGC trinucleotide repeats. The associations of miRNAs, piRNAs and candidate target genes could be recommended for developing methods for diagnosing diseases, including neurodegenerative diseases, oncological diseases and diabetes

Online Entertainment Trends and Its Current Development

The aim of this study is to identify the various types and trends present in the online information space, along with providing an overview of entertainment resources found on the internet. We have examined the concepts of virtual reality, online entertainment, and their classifications, along with assessing the influence of virtual worlds

Superparamagnetic properties of La1 - xSrxMn0.925Zn0.075O3 (x = 0.075, 0.095, and 0.115) lanthanum manganites

Lanthanum-strontium manganites doped with zinc are studied by the method of electron magnetic resonance. Nano-objects with ferromagnetically correlated spins, which behave themselves like superparamagnetic particles in the magnetic resonance spectrum, have been found in the paramagnetic phase. The temperature dependences of the resonance magnetic field and magnetic resonance linewidth for La1 - xSrxMn0.925Zn0.075O3 ceramic samples at temperatures ranging from 100 to 340 K have been analyzed on the basis of the Raikher-Stepanov theory of superparamagnetic particles. The magnetic moment, anisotropy field, and characteristic size of the regions of the ferromagnetically correlated spins have been determined. © 2013 Pleiades Publishing, Inc

Analytics of Heterogeneous Breast Cancer Data Using Neuroevolution

https://ieeexplore.ieee.org/document/8632897Breast cancer prognostic modeling is difficult since it is governed by many diverse factors. Given the low median survival and large scale breast cancer data, which comes from high throughput technology, the accurate and reliable prognosis of breast cancer is becoming increasingly difficult. While accurate and timely prognosis may save many patients from going through painful and expensive treatments, it may also help oncologists in managing the disease more efficiently and effectively. Data analytics augmented by machine-learning algorithms have been proposed in past for breast cancer prognosis; and however, most of these could not perform well owing to the heterogeneous nature of available data and model interpretability related issues. A robust prognostic modeling approach is proposed here whereby a Pareto optimal set of deep neural networks (DNNs) exhibiting equally good performance metrics is obtained. The set of DNNs is initialized and their hyperparameters are optimized using the evolutionary algorithm, NSGAIII. The final DNN model is selected from the Pareto optimal set of many DNNs using a fuzzy inferencing approach. Contrary to using DNNs as the black box, the proposed scheme allows understanding how various performance metrics (such as accuracy, sensitivity, F1, and so on) change with changes in hyperparameters. This enhanced interpretability can be further used to improve or modify the behavior of DNNs. The heterogeneous breast cancer database requires preprocessing for better interpretation of categorical variables in order to improve prognosis from classifiers. Furthermore, we propose to use a neural network-based entity-embedding method for categorical features with high cardinality. This approach can provide a vector representation of categorical features in multidimensional space with enhanced interpretability. It is shown with evidence that DNNs optimized using evolutionary algorithms exhibit improved performance over other classifiers mentioned in this paper

The need of transition to insurance medicine in Kazakhstan

Целью данной работы является выявление сущности и преимуществ добровольного медицинского страхования, его проблем и перспектив развития в Республике Казахстан.The aim of this work is to identify the nature and advantages of voluntary health insurance, its problems and prospects of development in the Republic of Kazakhstan