Individualized Inter-Stimulus Interval Estimation for Neural Facilitation in Human Motor System: A Particle Filtering Approach

2018 ◽  
Author(s):  
Kentaro Takemura ◽  
Euisun Kim ◽  
Jun Ueda
Keyword(s):  
Particle Filtering ◽  
Motor Evoked Potentials ◽  
Search Algorithm ◽  
Interval Estimation ◽  
Stimulus Interval ◽  
Optimal Interval ◽  
Incremental Method ◽  
Therapeutic Exercises ◽  
Wide Range ◽  
Neuromotor System

Quantitative understanding of the human neuromotor system is essential for the implementation of the future robotic therapeutic exercises. For this purpose, sensorimotor adaptations in voluntary and involuntary movements facilitated by peripheral stimulation and resultant motor-evoked potentials (MEP) must be well characterized. One such facilitation exercise is paired associative stimulation (PAS). However, effective inter-stimulus intervals between cortical and peripheral stimulations are highly variable between individuals due to different physiological characteristics. Past studies measured MEPs in a wide range of time by incrementally varying inter-stimulus intervals to find the optimal interval in a specific subject, which has been a time-consuming process. This paper develops a search algorithm based on particle filtering to estimate individualized inter-stimulus intervals for PAS with mechanical muscle tendon stimulation realized by a pneumatically-operated robotic neuromodulatory system. The particle filter-based method reduces the number of PAS trials 70%–80% in comparison to the conventional incremental method. An accelerometer attached to the robotic system that measures exact timings of tendon stimulation can further reduce the number of trials.

scholarly journals A Classification of Basic Helix-Loop-Helix Transcription Factors of Soybean

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Karen A. Hudson ◽  
Matthew E. Hudson
Keyword(s):  
Transcription Factors ◽  
Genome Sequence ◽  
Search Algorithm ◽  
Soybean Genome ◽  
Binding Potential ◽  
Future Research ◽  
Basic Helix Loop Helix ◽  
Helix Loop Helix ◽  
Bhlh Genes ◽  
Wide Range

The complete genome sequence of soybean allows an unprecedented opportunity for the discovery of the genes controlling important traits. In particular, the potential functions of regulatory genes are a priority for analysis. The basic helix-loop-helix (bHLH) family of transcription factors is known to be involved in controlling a wide range of systems critical for crop adaptation and quality, including photosynthesis, light signalling, pigment biosynthesis, and seed pod development. Using a hidden Markov model search algorithm, 319 genes with basic helix-loop-helix transcription factor domains were identified within the soybean genome sequence. These were classified with respect to their predicted DNA binding potential, intron/exon structure, and the phylogeny of the bHLH domain. Evidence is presented that the vast majority (281) of these 319 soybean bHLH genes are expressed at the mRNA level. Of these soybean bHLH genes, 67% were found to exist in two or more homeologous copies. This dataset provides a framework for future studies on bHLH gene function in soybean. The challenge for future research remains to define functions for the bHLH factors encoded in the soybean genome, which may allow greater flexibility for genetic selection of growth and environmental adaptation in this widely grown crop.

Optimal Design of Power System Stabilizer Using a Novel Evolutionary Algorithm

2018 ◽  
Vol 7 (3) ◽  
pp. 24-46
Author(s):  
Sourav Paul ◽  
Provas Roy
Keyword(s):  
Optimal Design ◽  
Power System ◽  
Search Algorithm ◽  
Low Frequency ◽  
Optimal Solution ◽  
Power System Stabilizer ◽  
Low Frequency Oscillation ◽  
Large Power ◽  
Wide Range ◽  
System Stabilizer

In this article, an Oppositional Differential search algorithm (ODSA) is comprehensively developed and successfully applied for the optimal design of power system stabilizer (PSS) parameters which are added to the excitation system to dampen low frequency oscillation as it pertains to large power system. The effectiveness of the proposed method is examined and validated on a single machine infinite bus (SMIB) using the Heffron-Phillips model. The most important advantage of the proposed method is as it reaches toward the optimal solution without the optimal tuning of input parameters of the ODSA algorithm. In order to verify the effectiveness, the simulation was made for a wide range of loading conditions. The simulation results of the proposed ODSA are compared with those obtained by other techniques available in the recent literature to demonstrate the feasibility of the proposed algorithm.

scholarly journals UAV-LiCAM SYSTEM DEVELOPMENT: CALIBRATION AND GEO-REFERENCING

2018 ◽  
Vol XLII-1 ◽  
pp. 107-114 ◽  
Author(s):  
C. Cortes ◽  
M. Shahbazi ◽  
P. Ménard
Keyword(s):  
Particle Filtering ◽  
System Development ◽  
Low Cost ◽  
Base Station ◽  
Dual Frequency ◽  
Body Frame ◽  
Integrated Sensor ◽  
Sensor Orientation ◽  
Wide Range ◽  
Gnss Measurements

<p><strong>Abstract.</strong> In the last decade, applications of unmanned aerial vehicles (UAVs), as remote-sensing platforms, have extensively been investigated for fine-scale mapping, modeling and monitoring of the environment. In few recent years, integration of 3D laser scanners and cameras onboard UAVs has also received considerable attention as these two sensors provide complementary spatial/spectral information of the environment. Since lidar performs range and bearing measurements in its body-frame, precise GNSS/INS data are required to directly geo-reference the lidar measurements in an object-fixed coordinate system. However, such data comes at the price of tactical-grade inertial navigation sensors enabled with dual-frequency RTK-GNSS receivers, which also necessitates having access to a base station and proper post-processing software. Therefore, such UAV systems equipped with lidar and camera (UAV-LiCam Systems) are too expensive to be accessible to a wide range of users. Hence, new solutions must be developed to eliminate the need for costly navigation sensors. In this paper, a two-fold solution is proposed based on an in-house developed, low-cost system: 1) a multi-sensor self-calibration approach for calibrating the Li-Cam system based on planar and cylindrical multi-directional features; 2) an integrated sensor orientation method for georeferencing based on unscented particle filtering which compensates for time-variant IMU errors and eliminates the need for GNSS measurements.</p>

An Iterated Local Search Algorithm for Task Assignment in Distributed Computing Systems

2012 ◽  
Vol 588-589 ◽  
pp. 1308-1311
Author(s):  
Qin Ma Kang ◽  
Hong He ◽  
Hai Ning Jiang
Keyword(s):  
Distributed Computing ◽  
Local Search ◽  
Search Algorithm ◽  
Task Assignment ◽  
Computation Time ◽  
Iterated Local Search ◽  
Local Search Algorithm ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Wide Range

This paper considers the problem of task assignment in heterogeneous distributed computing systems with the goal of minimizing the total execution and communication costs. An iterated local search algorithm is proposed for finding the suboptimal task assignment in a reasonable amount of computation time. We study the performance of the proposed algorithm over a wide range of parameters such as the problem scales, the ratio of average communication time to average computation time, and task interaction density of applications. The effectiveness of the algorithm is manifested by comparing it with other competing algorithms in the relevant literature.

scholarly journals Xenon iron oxides predicted as potential Xe hosts in Earth’s lower mantle

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Feng Peng ◽  
Xianqi Song ◽  
Chang Liu ◽  
Quan Li ◽  
Maosheng Miao ◽  
...  
Keyword(s):  
Iron Oxides ◽  
Lower Mantle ◽  
Search Algorithm ◽  
Mass Density ◽  
Mantle Minerals ◽  
Fe Oxides ◽  
Structure Search ◽  
Wide Range ◽  
Deep Earth ◽  
Calculated Mass

Abstract An enduring geological mystery concerns the missing xenon problem, referring to the abnormally low concentration of xenon compared to other noble gases in Earth’s atmosphere. Identifying mantle minerals that can capture and stabilize xenon has been a great challenge in materials physics and xenon chemistry. Here, using an advanced crystal structure search algorithm in conjunction with first-principles calculations we find reactions of xenon with recently discovered iron peroxide FeO2, forming robust xenon-iron oxides Xe2FeO2 and XeFe3O6 with significant Xe-O bonding in a wide range of pressure-temperature conditions corresponding to vast regions in Earth’s lower mantle. Calculated mass density and sound velocities validate Xe-Fe oxides as viable lower-mantle constituents. Meanwhile, Fe oxides do not react with Kr, Ar and Ne. It means that if Xe exists in the lower mantle at the same pressures as FeO2, xenon-iron oxides are predicted as potential Xe hosts in Earth’s lower mantle and could provide the repository for the atmosphere’s missing Xe. These findings establish robust materials basis, formation mechanism, and geological viability of these Xe-Fe oxides, which advance fundamental knowledge for understanding xenon chemistry and physics mechanisms for the possible deep-Earth Xe reservoir.

scholarly journals Transcranial random noise stimulation (tRNS): a wide range of frequencies is needed for increasing cortical excitability

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Beatrice Moret ◽  
Rita Donato ◽  
Massimo Nucci ◽  
Giorgia Cona ◽  
Gianluca Campana
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Primary Motor Cortex ◽  
Cortical Excitability ◽  
Motor Evoked Potentials ◽  
Random Noise ◽  
High Frequency Band ◽  
Neural Excitability ◽  
Transcranial Random Noise Stimulation ◽  
Wide Range

Abstract Transcranial random noise stimulation (tRNS) is a recent neuromodulation protocol. The high-frequency band (hf-tRNS) has shown to be the most effective in enhancing neural excitability. The frequency band of hf-tRNS typically spans from 100 to 640 Hz. Here we asked whether both the lower and the higher half of the high-frequency band are needed for increasing neural excitability. Three frequency ranges (100–400 Hz, 400–700 Hz, 100–700 Hz) and Sham conditions were delivered for 10 minutes at an intensity of 1.5 mA over the primary motor cortex (M1). Single-pulse transcranial magnetic stimulation (TMS) was delivered over the same area at baseline, 0, 10, 20, 30, 45 and 60 minutes after stimulation, while motor evoked potentials (MEPs) were recorded to evaluate changes in cortical excitability. Only the full-band condition (100–700 Hz) was able to modulate excitability by enhancing MEPs at 10 and 20 minutes after stimulation: neither the higher nor the lower sub-range of the high-frequency band significantly modulated cortical excitability. These results show that the efficacy of tRNS is strictly related to the width of the selected frequency range.

scholarly journals A Note on the Identification of Common Geographies

2015 ◽  
Vol 46 (2) ◽  
pp. 288-299 ◽  
Author(s):  
Adam Slez ◽  
Heather A. O’Connell ◽  
Katherine J. Curtis
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Search Algorithm ◽  
Geographic Information ◽  
Good Effect ◽  
Data Sets ◽  
Sociological Research ◽  
Combine Data ◽  
Wide Range ◽  
Simple Search

Areal data have been used to good effect in a wide range of sociological research. One of the most persistent problems associated with this type of data, however, is the need to combine data sets with incongruous boundaries. To help address this problem, we introduce a new method for identifying common geographies. We show that identifying common geographies is equivalent to identifying components within a k-uniform k-partite hypergraph. This approach can be easily implemented using a geographic information system in conjunction with a simple search algorithm.

A New Method to Detect P-Wave Based on Quadratic Function

2011 ◽  
Vol 267 ◽  
pp. 462-467
Author(s):  
Nan Quan Zhou
Keyword(s):  
Quadratic Function ◽  
Least Square Method ◽  
Detection Algorithm ◽  
Least Square ◽  
P Wave ◽  
Good Effect ◽  
Rate Variation ◽  
Optimal Interval ◽  
Wave Detection ◽  
Wide Range

The paper presents a P-wave detection algorithm based on fitting function in the optimal interval. In the algorithm we used quadratic function to fit the P wave by this means of least square method in every interval, which was shifted in local range. Then we found the optimal fitting interval of P wave by comparing the error of fitting. Finally, we obtained the characteristic points of P wave by using the fitting function to fit P wave in the optimal interval. The performance of the algorithm tested using the records of the MIT-BIH database was effective and accurate. The algorithm on the wide range of heart rate variation and small P wave of ECG P-wave detection has good effect. Also it has some capabilities of anti-interference, particularly the false dismissal probability is quite low.

scholarly journals Detecting Community Structures Within Complex Networks Using a Discrete Unconscious Search Algorithm

2021 ◽  
Vol 12 (2) ◽  
pp. 15-32
Author(s):  
Ehsan Ardjmand ◽  
William A. Young II ◽  
Najat E. Almasarwah
Keyword(s):  
Social Networks ◽  
Complex Networks ◽  
Community Detection ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Academic Community ◽  
Detection Methods ◽  
The Unconscious ◽  
Comprehensive Review ◽  
Wide Range

Detecting the communities that exist within complex social networks has a wide range of application in business, engineering, and sociopolitical settings. As a result, many community detection methods are being developed by researchers in the academic community. If the communities within social networks can be more accurately detected, the behavior or characteristics of each community within the networks can be better understood, which implies that better decisions can be made. In this paper, a discrete version of an unconscious search algorithm was applied to three widely explored complex networks. After these networks were formulated as optimization problems, the unconscious search algorithm was applied, and the results were compared against the results found from a comprehensive review of state-of-the-art community detection methods. The comparative study shows that the unconscious search algorithm consistently produced the highest modularity that was discovered through the comprehensive review of the literature.

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