Measurements, Models, Systems and Design

531 s.

Effective pore size and radius of capture for K+ ions in K-channels

Indexación: Web of Science; Scopus.Reconciling protein functional data with crystal structure is arduous because rare conformations or crystallization artifacts occur. Here we present a tool to validate the dimensions of open pore structures of potassium-selective ion channels. We used freely available algorithms to calculate the molecular contour of the pore to determine the effective internal pore radius (r(E)) in several K-channel crystal structurss. r(E) was operationally defined as the radius of the biggest sphere able to enter the pore from the cytosolic side. We obtained consistent r(E) estimates for MthK and Kv1.2/2.1 structures, with r(E) = 5.3-5.9 angstrom and r(E) = 4.5-5.2 angstrom, respectively. We compared these structural estimates with functional assessments of the internal mouth radii of capture (r(C)) for two electrophysiological counterparts, the large conductance calcium activated K-channel (r(C) = 2.2 angstrom) and the Shaker K-v-channel (r(C) = 0.8 angstrom), for MthK and Kv1.2/2.1 structures, respectively. Calculating the difference between r(E) and r(C), produced consistent size radii of 3.1-3.7 angstrom and 3.6-4.4 angstrom for hydrated K+ ions. These hydrated K+ estimates harmonize with others obtained with diverse experimental and theoretical methods. Thus, these findings validate MthK and the Kv1.2/2.1 structures as templates for open BK and Kv-channels, respectively.http://recursosbiblioteca.unab.cl:2226/articles/srep1989

Fault diagnostics for advanced cycle marine gas turbine using genetic algorithm

The major challenges faced by the gas turbine industry, for both the users and the manufacturers, is the reduction in life cycle costs , as well as the safe and efficient running of gas turbines. In view of the above, it would be advantageous to have a diagnostics system capable of reliably detecting component faults (even though limited to gas path components) in a quantitative marmer. V This thesis presents the development an integrated fault diagnostics model for identifying shifts in component performance and sensor faults using advanced concepts in genetic algorithm. The diagnostics model operates in three distinct stages. The rst stage uses response surfaces for computing objective functions to increase the exploration potential of the search space while easing the computational burden. The second stage uses the heuristics modification of genetics algorithm parameters through a master-slave type configuration. The third stage uses the elitist model concept in genetic algorithm to preserve the accuracy of the solution in the face of randomness. The above fault diagnostics model has been integrated with a nested neural network to form a hybrid diagnostics model. The nested neural network is employed as a pre- processor or lter to reduce the number of fault classes to be explored by the genetic algorithm based diagnostics model. The hybrid model improves the accuracy, reliability and consistency of the results obtained. In addition signicant improvements in the total run time have also been observed. The advanced cycle Intercooled Recuperated WR2l engine has been used as the test engine for implementing the diagnostics model.SOE Prize winne

Adaptive Methods for Point Cloud and Mesh Processing

Point clouds and 3D meshes are widely used in numerous applications ranging from games to virtual reality to autonomous vehicles. This dissertation proposes several approaches for noise removal and calibration of noisy point cloud data and 3D mesh sharpening methods. Order statistic filters have been proven to be very successful in image processing and other domains as well. Different variations of order statistics filters originally proposed for image processing are extended to point cloud filtering in this dissertation. A brand-new adaptive vector median is proposed in this dissertation for removing noise and outliers from noisy point cloud data. The major contributions of this research lie in four aspects: 1) Four order statistic algorithms are extended, and one adaptive filtering method is proposed for the noisy point cloud with improved results such as preserving significant features. These methods are applied to standard models as well as synthetic models, and real scenes, 2) A hardware acceleration of the proposed method using Microsoft parallel pattern library for filtering point clouds is implemented using multicore processors, 3) A new method for aerial LIDAR data filtering is proposed. The objective is to develop a method to enable automatic extraction of ground points from aerial LIDAR data with minimal human intervention, and 4) A novel method for mesh color sharpening using the discrete Laplace-Beltrami operator is proposed. Median and order statistics-based filters are widely used in signal processing and image processing because they can easily remove outlier noise and preserve important features. This dissertation demonstrates a wide range of results with median filter, vector median filter, fuzzy vector median filter, adaptive mean, adaptive median, and adaptive vector median filter on point cloud data. The experiments show that large-scale noise is removed while preserving important features of the point cloud with reasonable computation time. Quantitative criteria (e.g., complexity, Hausdorff distance, and the root mean squared error (RMSE)), as well as qualitative criteria (e.g., the perceived visual quality of the processed point cloud), are employed to assess the performance of the filters in various cases corrupted by different noisy models. The adaptive vector median is further optimized for denoising or ground filtering aerial LIDAR data point cloud. The adaptive vector median is also accelerated on multi-core CPUs using Microsoft Parallel Patterns Library. In addition, this dissertation presents a new method for mesh color sharpening using the discrete Laplace-Beltrami operator, which is an approximation of second order derivatives on irregular 3D meshes. The one-ring neighborhood is utilized to compute the Laplace-Beltrami operator. The color for each vertex is updated by adding the Laplace-Beltrami operator of the vertex color weighted by a factor to its original value. Different discretizations of the Laplace-Beltrami operator have been proposed for geometrical processing of 3D meshes. This work utilizes several discretizations of the Laplace-Beltrami operator for sharpening 3D mesh colors and compares their performance. Experimental results demonstrated the effectiveness of the proposed algorithms

The 1st International Conference on Computational Engineering and Intelligent Systems

Computational engineering, artificial intelligence and smart systems constitute a hot multidisciplinary topic contrasting computer science, engineering and applied mathematics that created a variety of fascinating intelligent systems. Computational engineering encloses fundamental engineering and science blended with the advanced knowledge of mathematics, algorithms and computer languages. It is concerned with the modeling and simulation of complex systems and data processing methods. Computing and artificial intelligence lead to smart systems that are advanced machines designed to fulfill certain specifications. This proceedings book is a collection of papers presented at the first International Conference on Computational Engineering and Intelligent Systems (ICCEIS2021), held online in the period December 10-12, 2021. The collection offers a wide scope of engineering topics, including smart grids, intelligent control, artificial intelligence, optimization, microelectronics and telecommunication systems. The contributions included in this book are of high quality, present details concerning the topics in a succinct way, and can be used as excellent reference and support for readers regarding the field of computational engineering, artificial intelligence and smart system

ANALYSIS AND SIMULATION OF PHOTOVOLTAIC SYSTEMS INCORPORATING BATTERY ENERGY STORAGE

Solar energy is an abundant renewable source, which is expected to play an increasing role in the grid\u27s future infrastructure for distributed generation. The research described in the thesis focuses on the analysis of integrating multi-megawatt photovoltaics (PV) systems with battery energy storage into the existing grid and on the theory supporting the electrical operation of components and systems. The PV system is divided into several sections, each having its own DC-DC converter for maximum power point tracking and a two-level grid connected inverter with different control strategies. The functions of the battery are explored by connecting it to the system in order to prevent possible voltage fluctuations and as a buffer storage in order to eliminate the power mismatch between PV array generation and load demand. Computer models of the system are developed and implemented using the PSCADTM/EMTDCTM software

Applications of EMG in Clinical and Sports Medicine

This second of two volumes on EMG (Electromyography) covers a wide range of clinical applications, as a complement to the methods discussed in volume 1. Topics range from gait and vibration analysis, through posture and falls prevention, to biofeedback in the treatment of neurologic swallowing impairment. The volume includes sections on back care, sports and performance medicine, gynecology/urology and orofacial function. Authors describe the procedures for their experimental studies with detailed and clear illustrations and references to the literature. The limitations of SEMG measures and methods for careful analysis are discussed. This broad compilation of articles discussing the use of EMG in both clinical and research applications demonstrates the utility of the method as a tool in a wide variety of disciplines and clinical fields

The development of peptide-based inhibitors for Tau aggregation as a potential therapeutic for Alzheimer’s disease

There are currently approximately 50 million individuals worldwide with dementia resulting in predicted global societal costs of up to US $1 trillion. Approximately 60-70% of these individuals have Alzheimer’s disease, which results in a chronic and insidious decline in memory. One of the main proteins that misfolds in this disease is Tau protein, which aggregates into toxic oligomers and neurofibrillary tangles. It is these aggregates, which cause damage to the brain resulting in dementia. As a result, it is imperative to be able to prevent or suppress the pathogenic aggregation of this protein, so the onset of dementia is halted or delayed, improving quality of life. Certain amino acid sequences in Tau such as VQIINK and VQIVYK play important roles in aggregation. Targeting these sequences can potentially prevent aggregation. This project aims to produce effective peptide inhibitors based on the human Tau peptide sequences VQIINK and VQIVYK, to specifically target pathogenic Tau aggregation. Using molecular docking softrware ‘ICM-Pro’ the potential binding locations of a variety of peptide candidates were computationally investigated to determine which will be most successful in a laboratory setting. Recombinant TauΔ1-250 was incubated in the prescense of heparin and subsequently aggregated to display highly ordered parallel, in-register β-strand structures; including fibrils and paired helical filaments presenting the characteristic twist under transmission electron microscope. This aggregation was achieved using of 20μM Tau at pH 7.4 in the presence of 20mM Tris buffer, 1mM DTT, 5μM Heparin, and 15uM ThT and incubated at 37 °C for 48 hours. The first generation of peptides AG01, AG02, AG02, AG02R4, AG02R5, AGR502, AG02PR5, AG02R6, AG02R9, AG02TAT, AG02ΔI, AG02ΔV inhibited approximately 50% of Tau aggregation determined by Thioflavin-T (ThT) fluorescence assay. The next generation, AG03 was slightly more effective, however when retroinverted (RI-AG03) inhibited over 90% of Tau aggregation, confirmed by Thioflavin-T fluorescence assay, transmission electron microscopy, circular dichroism and Congo red birefringence. RI-AG03 was determined to be stable in cells at therapeutic concentrations. After determining stability of RI-AG03 using SDS-PAGE, thermal circular dichroism and mass spectrometry, it was tested in vivo in rough eye Drosophila model. Results suggested that RI-AG03 partially rescued the rough eye phenotype in this model. This research demonstrates that retro-inverted peptide RI-AG03 is a potent inhibitor of Tau aggregation and can be further developed as a novel therapeutic for Tauopathies like Alzhimer’s Disease

Deployable Vibration Control Systems for Lightweight Structures

The recent push towards lightweight, efficient, and innovative structural designs has brought forth a range of vibration control issues related to implementation, effectiveness, and control system design that are not fully addressed by existing strategies. In many cases, these structures are capable of withstanding day-to-day loads and only experience excessive vibrations during predictable peak-loading events such as large crowds or wind storms. At the same time, the use of lightweight material coupled with innovative construction methods has given rise to temporary structures which are designed to facilitate rapid implementation and intended for short-term applications. Both scenarios point towards a vibration control system that is suitable for immediate, short-term applications which motivates the concept of deployable autonomous control systems (DACSs). The deployability aspect implies the control system is capable of being readily implemented on a range of structures with only minor customization to the structure or device while the autonomy aspect refers to the ability of the system to react to changes in the dynamic response and effectively control different structural modes of vibration. A prototype device, consisting of an electromagnetic mass damper (EMD) mounted on an unmanned ground vehicle (UGV) equipped with vision sensors and on-board computational hardware, is developed to study the vibration control performance and demonstrate the advantages of the DACS concept. Both numerical and experimental modelling techniques are used to identify system models for each component of the prototype device. Given the system models, the dynamic interaction between the device and underlying structure is derived theoretically and validated experimentally. The use of an EMD and UGV introduce a number of practical challenges associated with controller design. These challenges arise due to the presence of physical operating constraints as well as uncertainty in the controller model. Three different candidate controllers, based on linear-quadratic Gaussian (LQG), model-predictive control (MPC), and robust H-infinity control theory, are formulated for the prototype device and comparatively assessed with respect to their ability to address these challenges. The MPC framework provides a systematic approach to incorporate physical operating constraints directly in the control formulation while robust synthesis of an H-infinity controller is well suited for addressing uncertainty in both the controller and structure models. A key property of the prototype device is the ability to reposition itself at different locations on the structure. To study the impact of this mobility on the overall control performance, a simultaneous localization and mapping (SLAM) solution is implemented for bridge structures. The SLAM solution generates a map of the structure that can later be used for autonomous navigation of the prototype device. In achieving autonomous mobility, the location of the control force can be added as an additional parameter in the controller formulation. The overall performance of the prototype device is evaluated through a combination of numerical simulations and experimental studies. Real-time hybrid simulation (RTHS) is used extensively to study the dynamic interaction effects and evaluate the control performance of the prototype device on various structures. A full-scale modular aluminum pedestrian bridge is used to demonstrate autonomous navigation and assess the advantages of a mobile control device. The results from each study point towards DACSs as being a favourable alternative to existing control systems for immediate, short-term vibration control applications