NeuroVis: Real-Time Neural Information Measurement and Visualization of Embodied Neural Systems

Understanding the real-time dynamical mechanisms of neural systems remains a significant issue, preventing the development of efficient neural technology and user trust. This is because the mechanisms, involving various neural spatial-temporal ingredients [i.e., neural structure (NS), neural dynamics (ND), neural plasticity (NP), and neural memory (NM)], are too complex to interpret and analyze altogether. While advanced tools have been developed using explainable artificial intelligence (XAI), node-link diagram, topography map, and other visualization techniques, they still fail to monitor and visualize all of these neural ingredients online. Accordingly, we propose here for the first time “NeuroVis,” real-time neural spatial-temporal information measurement and visualization, as a method/tool to measure temporal neural activities and their propagation throughout the network. By using this neural information along with the connection strength and plasticity, NeuroVis can visualize the NS, ND, NM, and NP via i) spatial 2D position and connection, ii) temporal color gradient, iii) connection thickness, and iv) temporal luminous intensity and change of connection thickness, respectively. This study presents three use cases of NeuroVis to evaluate its performance: i) function approximation using a modular neural network with recurrent and feedforward topologies together with supervised learning, ii) robot locomotion control and learning using the same modular network with reinforcement learning, and iii) robot locomotion control and adaptation using another larger-scale adaptive modular neural network. The use cases demonstrate how NeuroVis tracks and analyzes all neural ingredients of various (embodied) neural systems in real-time under the robot operating system (ROS) framework. To this end, it will offer the opportunity to better understand embodied dynamic neural information processes, boost efficient neural technology development, and enhance user trust.

Explore synergistic and competitive miRNA regulation mechanisms in the miRNA-mRNA regulatory network from the information decomposition perspective

Since multiple microRNAs can target 3' untranslated regions of the same mRNA transcript, it is likely that these endogenous microRNAs may form synergistic alliances, or compete for the same mRNA harbouring overlapping binding site matches. Synergistic and competitive microRNA regulation is an intriguing yet poorly elucidated mechanism. We here introduce a computational method based on the multivariate information measurement to quantify such implicit interaction effects between microRNAs. Our informatics method of integrating sequence and expression data is designed to establish the functional correlation between microRNAs. To demonstrate our method, we exploited TargetScan and The Cancer Genome Atlas data. As a result, we indeed observed that the microRNA pair with neighbouring binding site(s) on the mRNA is likely to trigger synergistic events, while the microRNA pair with overlapping binding site(s) on the mRNA is likely to cause competitive events, provided that the pair of microRNAs has a high functional similarity and the corresponding triplet presents a positive/negative 'synergy-redundancy' score.

ANALYSIS OF THE capabilities OF the CLOSED-OPEN SYSTEM CORRECTION scheme FOR MEASURING VIBRATIONS OF AIRCRAFT STRUCTURal ELEMENTS

В настоящее время в связи со всевозрастающей степенью сложности проектирования, производства и эксплуатации летательных аппаратов все более важным направлением в области развития информационно-измерительных систем становится совершенствование существующих и разработка новых способов измерения параметров вибрации элементов механических конструкций летательных аппаратов. Целью данной работы является анализ возможности и перспективности построения системы для измерения вибраций элементов конструкции самолета на основе использования микромеханических инерциальных измерительных блоков в качестве основных виброметрических измерителей. При этом объектом исследования является система измерения параметров вибрации, а предметом – ее структура, состав, алгоритмы функционирования и ожидаемые точностные характеристики. Для достижения поставленной цели строится информационно-измерительная система на базе инерциальных приборов, а также датчиков для непосредственных измерений перемещений, используются численные и аналитические методы высшей математики и теоретической механики, методы теории случайных процессов и оптимального оценивания. В статье рассмотрены принципы построения такой системы на примере варианта системы измерения параметров вибраций крыла самолета, представлен краткий обзор существующих решений в предметной области и обоснована актуальность и целесообразность предложенного варианта технического решения. Приведены базовый состав и структура системы, описаны основные принципы ее работы, основанные на использовании данных датчиков перемещения, инерциальных измерителей и оптимального калмановского оценивания и коррекции. Показаны основные алгоритмы работы системы, включая алгоритмы ориентации и навигации, оценивания и коррекции при замкнуто-разомкнутой схеме включения оптимального фильтра Калмана, алгоритм вычисления параметров вибрации, представленыматематические модели ошибок основных измерителей системы, показаны полученные предварительные результаты имитационного моделирования, демонстрирующие работоспособность системы и ее ожидаемые приемлемые точностные характеристики, подтверждающие возможность эффективного использования системы и перспективность выбранного направления работ. At present, because of the ever-increasing degree of complexity of aircrafts design, production and operation, the improvement of the existing methods and development of new ones for vibration parameters measurement of aircrafts mechanical structural elements is still an important direction in the field of information-measurement systems development. The purpose of this work is to analyze the possibility and prospects of constructing a system for measuring vibrations of aircraft structural elements based on the use of micromechanical inertial measurement units as the main vibrometric transducers. In this case, the object of research is the vibration parameters measurement system, and the subject is its structure, composition, operations algorithms and the expected accuracy characteristics. To achieve this purpose, an information-measurement system is built on the basis of inertial devices, as well as sensors for direct displacements measurements, numerical and analytical methods of higher mathematics and theoretical mechanics, methods of random processes theory and optimal estimation are used. The article discusses the principles of constructing such system taking as an example a system for measuring the vibration parameters of an aircraft wing, provides a brief overview of the existing solutions in this field of applications and substantiates the relevance and expediency of the proposed methodology of the technical solution. The basic components and structure of the system are presented, the basic principles of its operation are described, based on the use of data from displacement sensors, inertial meters and optimal Kalman estimation and correction. The main algorithms of the system operation are shown, including the orientation and navigation algorithm, estimation and correction algorithm for a closed-open scheme of optimal Kalman filter inclusion in the system, algorithm for calculating vibration parameters, beside the mathematical errors models of the main system sensors and channels are presented, preliminary results of simulation modeling are shown and they demonstrate the operability of the system and its expected acceptable accuracy characteristics, confirming the possibility of the effective use of the proposed system and the prospects of the chosen direction of work.

Children and Multidimensional Poverty: Four Measurement Strategies

Empirically, official multidimensional measures of poverty often show children to be the poorest age group. Such poverty measures and their analysis can be used to directly inform policies to reduce children’s multiple deprivations. This paper introduces methods to produce official national statistics on multidimensional poverty that inform child-focused anti-poverty policies. In doing so, it recognises the importance of parsimonious, consistent measures, given practical constraints such as policy makers’ time. The paper does not recommend constructing several disjoint poverty measures which cannot be straightforwardly interpreted and used alongside one another, as these may create confusion or dilute policy attention. To create a compact and high-information measurement platform, the paper introduces four measurement strategies that have been used to directly uncover policy-relevant data on children’s experience of multidimensional poverty, and that are consistent with official population-level statistics. The four are as follows: (1) Include children’s deprivations as indicators of multidimensional poverty in national measures. (2) Disaggregate multidimensional poverty indices and their associated information platform to compare children and adults. (3) Analyse individual child deprivations and explore gendered and intra-household inequalities. (4) Construct an individual measure of child multidimensional poverty that is directly linked to the official national measure, but contains additional indicators across the life course of children. The paper illustrates these four strategies and the child-relevant statistics they yield, using examples from official poverty measures and previous research. It discusses the strengths and challenges of each method from conceptual, policy, and technical perspectives, and examines how they can be used for descriptive and prescriptive purposes in line with the Sustainable Development Goals.

Information theory-based approach towards studying anti-coincidence detection via graded amplitude dendritic action potentials.

In contrast to typical all or none action potential, recent discovery of graded amplitude action potentials in cortical neurons enabled the dendrites to perform XOR computation, previously thought to be performed only at network level. Thus, these special neurons can perform anti-coincidence detection at the dendritic level, but a lot is unanswered about this phenomenon. Can such experimentally observed dendritic action potential generating system transmit information about stimuli having varying degrees of temporal overlap? Can the system add to the repertoire of computations performed at dendritic level by enhancing the information transmission about varying amplitude stimuli? In this information theory-based study done in single compartment and two-compartment dendritic models, it is shown that such a system can indeed transmit information about the temporal overlap of stimuli as well as amplitudes of stimuli even at high input noise levels. First, the calculation of mutual information between single stimulus and response i.e. I(S;R) with varying noise showed that the information about temporally overlapping nature of stimuli is precisely transmitted by such a system. Secondly, the time evolution of mutual information was simulated through data from the system and it positively reinforced the above-mentioned result. Next, varying amplitude input stimuli was provided to the system and calculation of mutual information between two stimuli and one response i.e. I(S1,S2;R) with varying noise levels revealed that such a system optimally transmits the information about stimuli even at high noise levels. Finally, calculation of this information measurement with respect to time in an experiment with constant overlap but varying input amplitude again positively reinforced the result.

Intelligent Content-Centric Networking Routing Strategy: A Bacterial Quorum Inspired Pattern

In recent years, the Content-Centric Networking (CCN) has attracted much attention from the global Internet experts; in particular, it has demonstrated the outstanding effect on the application in the field of Internet of Things (IoT). At present, the routing technique of ICN is subjected to the dynamic change of network environment with the development of mobile Internet. Therefore, this paper proposes an Intelligent CCN routing strategy based on Bacterial Quorum pattern (ICBQ). The ICBQ tries to simulate the behaviors of bacteria, including quorum sensing and adaptive chemotaxis. Meanwhile, the quorum sensing can obtain the parameter information on bandwidth, delay, and error rate to facilitate the subsequent forwarding of packets. The adaptive chemotaxis can select the optimal interface to forward the packets through the information measurement. The simulation is driven based on the real Netflix dataset over the GTS network topology, and the experimental results show that the proposed ICBQ has better performance in terms of routing success rate, routing delay, load balance, and energy efficiency.