Identification of Hysteresis in Human Meridian Systems Based on NARMAX Model

It has been found that the response of acupuncture point on the human meridian line exhibits nonlinear dynamic behavior when excitation of electroacupuncture is implemented on another meridian point. This nonlinear phenomenon is in fact a hysteretic phenomenon. In order to explore the characteristic of human meridian and finally find a way to improve the treatment of diseases via electro-acupuncture method, it is necessary to identify the model to describe the corresponding dynamic hysteretic phenomenon of human meridian systems stimulated by electric-acupuncture. In this paper, an identification method using nonlinear autoregressive and moving average model with exogenous input (NARMAX) is proposed to model the dynamic hysteresis in human meridian. As the hysteresis is a nonlinear system with multivalued mapping, the traditional NARMAX model is unavailable to it directly. Thus, an expanded input space is constructed to transform the multi-valued mapping of the hysteresis to a one-to-one mapping. Then, the identification method using NARMAX model on the constructed expanded input space is developed. Finally, the proposed method is applied to hysteresis modeling for human meridian systems

Characterization of corneal structure in keratoconus

Producción CientíficaThe increasing volume of patients interested in refractive surgery and the new treatment options available for keratoconus have generated a higher interest in achieving a better characterization of this pathology. The ophthalmic devices for corneal analysis and diagnosis have experienced a rapid development during the past decade with the implementation of technologies such as the Placido-disk corneal topography and the introduction of others such as scanning-slit topography, Scheimpflug photography, and optical coherence tomography, which are able to accurately describe not only the geometry of the anterior corneal surface but also that of the posterior surface, as well as pachymetry and corneal volume. Specifically, anterior and posterior corneal elevation, corneal power, pachymetry maps, and corneal coma-like aberrometry data provide sufficient information for an accurate characterization of the cornea to avoid misleading diagnoses of patients and provide appropriate counseling of refractive surgery candidates

Advances in Biomechanical Parameters for Screening of Refractive Surgery Candidates: A Review of the Literature, Part III

Corneal biomechanical properties have garnered significant interest in their relation to the development of ectatic corneal disease. Alongside the advent of corneal tomography and Scheimpflug imaging such as Pentacam and Galilei, there have been advances in assessing the cornea based on its biomechanical characteristics. Though the aforementioned imaging systems are highly capable of identifying morphologic abnormalities, they cannot assess mechanical stability of the cornea. This article, in contrast to Parts I and II of this article series, will focus on in vivo corneal biomechanical imaging systems. The two most readily available commercial systems include the Corvis ST and the Ocular Response Analyzer. Both of these systems aimed to characterize corneal biomechanics via distinct measurements. While in Parts I and II of this article series the authors focused on elevation, pachymetric, and keratometric data, the purpose of this article was to summarize biomechanical parameters and their clinical use in screening refractive surgery candidates. Moreover, this article explores biomechanical decompensation and its role in the development of corneal ectasia and keratoconus. There is a focus on the diagnostic accuracy of biomechanical indices in the identification of diseases such as keratoconus that may preclude a patient from undergoing refractive surgery

Aerospace Medicine and Biology: a Continuing Bibliography with Indexes (supplement 330)

This bibliography lists 156 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System during November 1989. Subject coverage includes: aerospace medicine and psychology, life support system and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Monitoring, modelling and quantification of accumulation of damage on masonry structures due to recursive loads

The use of induced seismicity is gaining in popularity, particularly in Northern Europe, as people strive to increase local energy supplies. Τhe local building stock, comprising mainly of low-rise domestic masonry structures without any aseismic design, has been found susceptible to these induced tremors. Induced seismicity is generally characterized by frequent small-to-medium magnitude earthquakes in which structural and non-structural damage have been reported. Since the induced earthquakes are caused by third parties liability issues arise and a damage claim mechanism is activated. Typically, any damage are evaluated by visual inspections. This damage assessment process has been found rather cumbersome since visual inspections are laborious, slow and expensive while the identification of the cause of any light damage is a challenging task rendering essential the development of a more reliable approach. The aim of this PhD study is to gain a better understanding of the monitoring, modelling and quantification of accumulation of damage in masonry structures due to recursive loads. Fraeylemaborg, the most emblematic monument in the Groningen region dating back to the 14 th century, has experienced damage due to the induced seismic activity in the region in recent years. A novel monitoring approach is proposed to detect damage accumulation due to induced seismicity on the monument. Results of the monitoring, in particular the monitoring of the effects of induced seismic activity,, as well as the usefulness and need of various monitoring data for similar cases are discussed. A numerical model is developed and calibrated based on experimental findings and different loading scenarios are compared with the actual damage patterns observed on the structure. Vision-based techniques are developed for the detection of damage accumulation in masonry structures in an attempt to enhance effectiveness of the inspection process. In particular, an artificial intelligence solution is proposed for the automatic detection of cracks on masonry structures. A dataset with photographs from masonry structures is produced containing complex backgrounds and various crack types and sizes. Moreover, different convolutional neural networks are evaluated on their efficacy to automatically detect cracks. Furthermore, computer vision and photogrammetry methods are considered along with novel invisible markers for monitoring cracks. The proposed method shifts the marker reflection and its contrast with the background into the invisible wavelength of light (i.e. to the near-infrared) so that the markers are not easily distinguishable. The method is thus particularly vi suitable for monitoring historical buildings where it is important to avoid any interventions or disruption to the authenticity of the basic fabric of construction.. Further on, the quantification and modelling of damage in masonry structures are attempted by taking into consideration the initiation and propagation of damage due to earthquake excitations. The evaluation of damage in masonry structures due to (induced) earthquakes represents a challenging task. Cumulative damage due to subsequent ground motions is expected to have an effect on the seismic capacity of a structure. Crack patterns obtained from experimental campaigns from the literature are investigated and their correlation with damage propagation is examined. Discontinuous modelling techniques are able to reliably reproduce damage initiation and propagation by accounting for residual cracks even for low intensity loading. Detailed models based on the Distinct Element Method and Finite Element Model analysis are considered to capture and quantify the cumulative damage in micro level in masonry subjected to seismic loads. Finally, an experimental campaign is undertaken to investigate the accumulation of damage in masonry structure under repetitive load. Six wall specimens resembling the configuration of a spandrel element are tested under three-point in-plane bending considering different loading protocols. The walls were prepared adopting materials and practices followed in the Groningen region. Different numerical approaches are researched for their efficacy to reproduce the experimental response and any limitations are highlighted

Structural and seismic monitoring of historical and contemporary buildings: general principles and applications

Structural Health Monitoring (SHM) indicates the continuous or periodic assessment of the conditions of a structure or a set of structures using information from sensor systems, integrated or autonomous, and from any further operation that is aimed at preserving structural integrity. SHM is a broad and multidisciplinary field, both for the spectrum of sciences and technologies involved and for the variety of applications. The technological developments that have made the advancement of this discipline possible come from many fields, including physics, chemistry, materials science, biology, but above all aerospace, civil, electronic and mechanical engineering. The first applications, at the turn of the sixties and seventies, concerned the integrity control of remote structural elements, such as foundation piles and submerged parts of off-shore platforms, but nowadays this type of monitoring is practiced on airplanes, vehicles spacecraft, ships, helicopters, automobiles, bridges, buildings, civil infrastructure, power plants, pipelines, electronic systems, manufacturing and processing facilities, and biological systems. This paper carries out an extensive examination of the theoretical and applicative foundations of structural and seismic monitoring, focusing in particular on methods that exploit natural vibrations and their use both in the diagnosis and in the prediction of the seismic response of civil structures, infrastructure networks, and traditional and modern architectural heritage

Measures of disease activity in glaucoma

Glaucoma is the leading cause of irreversible blindness globally which significantly affects the quality of life and has a substantial economic impact. Effective detective methods are necessary to identify glaucoma as early as possible. Regular eye examinations are important for detecting the disease early and preventing deterioration of vision and quality of life. Current methods of measuring disease activity are powerful in describing the functional and structural changes in glaucomatous eyes. However, there is still a need for a novel tool to detect glaucoma earlier and more accurately. Tear fluid biomarker analysis and new imaging technology provide novel surrogate endpoints of glaucoma. Artificial intelligence is a post-diagnostic tool that can analyse ophthalmic test results. A detail review of currently used clinical tests in glaucoma include intraocular pressure test, visual field test and optical coherence tomography are presented. The advanced technologies for glaucoma measurement which can identify specific disease characteristics, as well as the mechanism, performance and future perspectives of these devices are highlighted. Applications of AI in diagnosis and prediction in glaucoma are mentioned. With the development in imaging tools, sensor technologies and artificial intelligence, diagnostic evaluation of glaucoma must assess more variables to facilitate earlier diagnosis and management in the future

Biomechanical aspects of the anterior segment in human myopia

The thesis investigates the relationship between the biomechanical properties of the anterior human sclera and cornea in vivo using Schiotz tonometry (ST), rebound tonometry (RBT, iCare) and the Ocular Response Analyser (ORA, Reichert). Significant differences in properties were found to occur between scleral quadrants. Structural correlates for the differences were examined using Partial Coherent Interferometry (IOLMaster, Zeiss), Optical Coherent tomography (Visante OCT), rotating Scheimpflug photography (Pentacam, Oculus) and 3-D Magnetic Resonance Imaging (MRI). Subject groups were employed that allowed investigation of variation pertaining to ethnicity and refractive error. One hundred thirty-five young adult subjects were drawn from three ethnic groups: British-White (BW), British-South-Asian (BSA) and Hong-Kong-Chinese (HKC) comprising non-myopes and myopes. Principal observations: ST demonstrated significant regional variation in scleral resistance a) with lowest levels at quadrant superior-temporal and highest at inferior-nasal; b) with distance from the limbus, anterior locations showing greater resistance. Variations in resistance using RBT were similar to those found with ST; however the predominantly myopic HKC group had a greater overall mean resistance when compared to the BW-BSA group. OCT-derived scleral thickness measurements indicated the sclera to be thinner superiorly than inferiorly. Thickness varied with distance from the corneolimbal junction, with a decline from 1 to 2 mm followed by a successive increase from 3 to 7 mm. ORA data varied with ethnicity and refractive status; whilst axial length (AL) was associated with corneal biometrics for BW-BSA individuals it was associated with IOP in the HKC individuals. Complex interrelationships were found between ORA Additional-Waveform-Parameters and biometric data provided by the Pentacam. OCT indicated ciliary muscle thickness to be greater in myopia and more directly linked to posterior ocular volume (from MRI) than AL. Temporal surface areas (SAs, from MRI) were significantly smaller than nasal SAs in myopic eyes; globe bulbosity (from MRI) was constant across quadrants

Evaluation and neurocomputational modelling of visual adaptation to optically induced distortions

Spatial geometrical distortions are major artefacts in vision aid optical spectacles. Progressive additional lenses (PALs) are among such spectacles incurring inherent distortions. Distortions alter perceived features of the natural environment and are one of the causes for visual discomforts, such as apparent motion perception and spatial disorientation, experienced by novice spectacle wearers. Thus, fast and efficient visual adaptation to the distortions is a necessity to increase the users’ comfort and consequently overcome the related problems, e.g. risk of fall in the elderly when using PALs. Inspired by this necessity, the work is targeted to investigate the visual mechanisms underlying adaptation to distortions, in particular in PALs. Psychophysical procedures are employed to probe the characteristics of the neural mechanisms underlying the adaptation process in natural viewing conditions. With psychophysical approaches, three main properties of distortion adaptation are revealed; its cortical origin, the reference frame in which it is achieved and its long-term temporal dynamics. In order to discern how the functional organization of neurons enables the visual system to carry out a robust distortion adaptation in a natural environment, biologically plausible recurrent neural network models are utilized. Prediction performance of model variants with different neural network complexity and temporal dynamics of operation were assessed. From the model simulations, major functional roles of recurrent bottom-up and top-down cortical interactions in neural response tuning and in mediating adaptation at different time scales were depicted. The outcomes would further contribute to suggest a solution for facilitating adaptation. The relevance of the research within these aforementioned studies is not restricted to PALs but extends to distortions in other daily used optical utilities, such as virtual reality (VR) displays. Optical distortions are also artefacts in artificial sensory systems, like lens distortions in cameras used in machine vision. Understanding the neural correlates of distortion adaptation in human vision will thereby elicit characteristic features of robust and flexible neural systems to be implemented in brain inspired artificial vision