No description available.

In the case of wideband (aperiodic) signals, the classical signal and noise measures used to characterize stochastic resonance do not work because their way of distinguishing signal from noise fails. In a study published earlier (L. B. Kish, 1996), a new way of measuring and identifying noise and aperiodic (wideband) signals during strongly nonlinear transfer was introduced. The method was based on using cross-spectra between the input and the output. According to the study, in the case of linear transfer and sinusoidal signals, the method gives the same results as the classical method and in the case of aperiodic signals it gives a sensible measure. In this paper we refine the theory and present detailed simulations which validate and refine the conclusions reached in that study. As neural and ion channel signal transfer are nonlinear and aperiodic, the new method has direct applicability in membrane biology and neural science (S.M. Bezrukov and I. Vodyanoy, 1997).

<p>The focus of this dissertation is on phenomena exhibited by multistable systems. Two phenomena of particular importance are chaos control and stochastic resonance. In this work, both models that can predict ordered responses and experiments in which ordered responses occur are explored. In addition, parameter identification methods are presented and improved. </p><p>Chaos control, when implemented with delays, can be an effective way to stabilize unstable periodic orbits within a multistable system experiencing a chaotic response. Delayed control is easy to implement physically but greatly increases the complexity of analyzing such systems. In this work, the spectral element method was adapted to evaluate unstable periodic orbits stabilized by feedback control implemented with delays. Examples are presented for Duffing systems in which the delay is equal to the forcing period. The spectral approach is also extended to analyze the control of chaos with arbitrary delays. Control with arbitrary delays can also be used to stabilize equilibria within the chaotic response. These methods for arbitrary delays are explored in self-excited, chaotic systems.</p><p>Stochastic resonance occurs in multistable systems when an increase in noise results in an ordered response. It is well known that noise excitation of multistable systems results in the system escaping from potential wells or switching between wells. In stochastic resonance, a small external signal is amplified due to these switching events. Methods for modeling stochastic resonance in both underdamped and overdamped systems are presented. In addition, stochastic resonance in a bistable, composite beam excited by colored noise is investigated experimentally. The experimental results are compared with analytical models, and the effect of modal masses on the analytical expressions is explored. Finally, an alternative approach for calculating the effect of colored noise excitation is proposed.</p><p>In order to implement analysis methods related to delay differential equations or stochastic resonance, the parameters of the system must be known in advance or determined experimentally. Parameter identification methods provide a natural connection between experiment and theory. In this work, the harmonic balance parameter identification method was applied to beam energy harvesters and is improved using weighting matrices. The method has been applied to a nonlinear, bistable, piezoelectric beam with a tip mass. Then, an experimental method of determining the number of restoring force coefficients necessary to accurately model the systems was demonstrated. The harmonic balance method was also applied to a bistable, beam system undergoing stochastic resonance. Finally, a new weighting strategy is presented based on the signal to noise ratio of each harmonic.</p> / Dissertation

In this thesis, a set of some prevailing rate-based models for bistable perception have been considered in order to find the implications of the novel results reported in Pastukhov & Braun (2011). These authors have quantified not only salient aspects of bistable perception (mean and dispersion of dominance distributions), but also some hidden hysteresis effects ignored up to now. Extensive computational simulations of different prevailing models rigorously demonstrate that the history-dependence of the perceptual process shown by Pastukhov & Braun (2011), effectively constrains the region of the parameter space able to replicate the empirical data. Concretely, that just small regions residing inside a bistable or two-attractor region of the whole parameter space are actually adequate to reproduce the experimental results, both for BR and KDE displays. Remarkably, the results remain valid across all the different classes of models considered, regardless the details of the neuronal implementation. The biological plausibility of the parameter region found for each of the models considered, is further stressed with respect to the widely known Levelt’s propositions. To that end, we make use of weighted sums across the parameter regions computed for each subject in the first part of this Thesis, an algorithm that constitutes an important improvement to the methodology proposed by Shpiro et al. (2007) to fit behavioral data by rate-based models. It is shown how different neuronal mechanisms clearly differ in their suitability to replicate Levelt’s propositions. For instance, models with a slow fatiguing process given by spike-frequency adaptation Wilson (2003); Shpiro et al. (2007), no matter if they are being described by linear Shpiro et al. (2007) or nonlinear Curtu et al. (2008)) functions of the activity, replicate quite well Levelt’s second law. Oppositely, a notable discrepancy between model and empirical results is found when such negative feedback is described as a long-term depression affecting the synapses between the competing neurons representing the two alternative interpretations Laing & Chow (2002); Shpiro et al. (2007). The present work finishes with a study about the capability of the mentioned models to reproduce the resonance effects happening when varying external frequencies, as shown by Kim et al. (2006). Importantly, a resonance respect to the noise dispersion (i.e., a true stochastic resonance ) is clearly demonstrated here for the first time. Previous estimations of noise dispersion (20 − 30% of the input) and its locus (adaptation variables) are questioned, by demonstrating that increased sensitivity to even weak signals of the order of less than 10% can be obtained with the models considered, with the noise variable simply entering as part of the net input feeding the neuron. / En este trabajo, son considerados una serie de modelos para frecuencia neuronal ampliamente aceptados en percepción bi-estable, con el objetivo de evaluar las implicaciones de los resultados recientemente reportados en Pastukhov & Braun (2011). Estos autores han cuantificado no solamente aspectos más conocidos sobre el fenómeno (media y dispersión de las distribuciones de dominancia), sino también efectos de historia que habían sido ignorados hasta el presente. Por medio de simulaciones computacionales, se demuestra rigurosamente que la dependencia de la historia del proceso perceptual encontrada por Pastukhov & Braun (2011) efectivamente restringe la región válida de parámetros que es adecuada para reproducir los datos empíricos. Concretamente, que solamente pequeñas regiones del espacio de parámetros disponible, y que se encuentran dentro de una región dinámica bi-estable caracterizada por dos atractores, son realmente adecuadas, tanto para rivalidad binocular (BR) como para estímulos de estructura por movimiento (KDE). Resulta importante destacar que los resultados permanecen válidos de un modelo a otro, independientemente de los detalles de implementación neuronal. La plausibilidad biológica de la región de parámetros encontrada para cada modelo es entonces considerada, en el contexto de las ampliamente conocidas proposiciones de Levelt. Con tal objetivo, hacemos uso de un algoritmo de suma pesada para extraer valores medios de la regiones de parámetros correspondientes a cada sujeto. Este algoritmo constituye una importante mejora a la metodología propuesta por Shpiro et al. (2007) para ajustar modelos de frecuencia neuronal a datos comportamentales de percepción bi-estable. Es entonces mostrado como cada mecanismo neuronal considerado es clara- mente diferente en su capacidad para reproducir las proposiciones de Levelt. Por ejemplo, modelos conteniendo procesos lentos de retroalimentación negativa da- dos por adaptación de frecuencia de disparo Wilson (2003); Shpiro et al. (2007), sin importar si están descritos por funciones lineales Shpiro et al. (2007) or no lineales Curtu et al. (2008)) de la actividad, consiguen reproducir de modo razonable la segunda proposición de Levelt. Por el contrario, una notable discrepancia entre modelo y resultados empíricos es encontrada cuando tales procesos están dados por la presencia de depresión sináptica de larga duración. El presente trabajo culmina con un estudio sobre la capacidad de los mencionados modelos para reproducir los efectos de resonancia que ocurren al variar la frecuencia externa de modulación Kim et al. (2006). Es de destacar que en nuestro caso, un efecto de resonancia es encontrado respecto a la dispersión del ruido, lo cual indica la presencia de una verdadera resonancia del tipo estocástico. Este efecto es claramente demostrado para estos modelos, por primera vez, en el presente trabajo. Previas estimaciones de la dispersión del ruido (20 − 30 % de la señal de entrada) y su localización (variables de adaptación) son analizadas. Se demuestra que un incremento de la sensibilidad a incluso muy pequeñas señales de menos del 10% puede ser encontrada en estos modelos, con sólo incluir la variable de ruido como parte de la corriente neta que alimenta la neurona.

abstract: Synthetic biology is a novel method that reengineers functional parts of natural genes of interest to build new biomolecular devices able to express as designed. There is increasing interest in synthetic biology due to wide potential applications in various fields such as clinics and fuel production. However, there are still many challenges in synthetic biology. For example, many natural biological processes are poorly understood, and these could be more thoroughly studied through model synthetic gene networks. Additionally, since synthetic biology applications may have numerous design constraints, more inducer systems should be developed to satisfy different requirements for genetic design. This thesis covers two topics. First, I attempt to generate stochastic resonance (SR) in a biological system. Synthetic bistable systems were chosen because the inducer range in which they exhibit bistability can satisfy one of the three requirements of SR: a weak periodic force is unable to make the transition between states happen. I synthesized several different bistable systems, including toggle switches and self-activators, to select systems matching another requirement: the system has a clear threshold between the two energy states. Their bistability was verified and characterized. At the same time, I attempted to figure out the third requirement for SR – an effective noise serving as the stochastic force – through one of the most widespread toggles, the mutual inhibition toggle, in both yeast and E. coli. A mathematic model for SR was written and adjusted. Secondly, I began work on designing a new genetic system capable of responding to pulsed magnetic fields. The operators responding to pulsed magnetic stimuli in the rpoH promoter were extracted and reorganized. Different versions of the rpoH promoter were generated and tested, and their varying responsiveness to magnetic fields was recorded. In order to improve efficiency and produce better operators, a directed evolution method was applied with the help of a CRISPR-dCas9 nicking system. The best performing promoters thus far show a five-fold difference in gene expression between trials with and without the magnetic field. / Dissertation/Thesis / Masters Thesis Bioengineering 2016

Renewal theory began development in the early 1940s, as the need for it in the industrial engineering sub-discipline operations research had risen. In time, the theory found applications in many stochastic processes. In this thesis I investigated the effect of seasonal effects on Poisson and non-Poisson renewal processes in the form of perturbations. It was determined that the statistical analysis methods developed at UNT Center for Nonlinear Science can be used to detect the effects of seasonality on the data obtained from Poisson/non-Poisson renewal systems. It is proved that a perturbed Poisson process can serve as a paradigmatic model for a case where seasonality is correlated to the noise and that diffusion entropy method can be utilized in revealing this relation. A renewal model making a connection with the stochastic resonance phenomena is used to analyze a previous neurological experiment, and it was shown that under the effect of a nonlinear perturbation, a non-Poisson system statistics may make a transition and end up in the of Poisson basin of statistics. I determine that nonlinear perturbation of the power index for a complex system will lead to a change in the complexity characteristics of the system, i.e., the system will reach a new form of complexity.

No description available.

Our human balance system is critical for preventing falls. The system consists of a complex set of sensorimotor controls that includes integration of sensory inputs including sight, touch and vestibular to produce motor output. Tactile afferents from the plantar surface contribute to the human balance and movement control system. Loss of sensory information could lead to impaired balance primarily because of impaired detection of changes in upright position, delayed postural reflexes, or failure to realize how far one's center of mass has been displaced thus increasing the probability of falls. Somatosensory and visual information must be integrated to interpret complex sensory environment. Sensory pathways that are simultaneously feeding inputs into the system exhibit non-linear behavior and it is unlikely that the role of a single pathway can be characterized in a static environment. As the sensory environment changes, the need to re-weight the relative dependence on each senses is essential for maintaining stability. Thus, attention also plays an important role in postural control. Attention can be defined as the individual's capacity for information processing. Performing two or more tasks at the same time may require more than an individual's attention capacity and thereby may weaken performance in the other task. Stochastic resonance phenomena has been shown to enhance sensory information processing and perception. This series of studies sought to analyze the effects of vibrotactile noise on human postural responses using a sub-threshold vibration (SV) and above-threshold vibration (AV). The vibrotactile noise was applied at the soles of both feet with six DC vibrator disks embedded in open-type footwear. Twenty one healthy adults wearing the vibrating footwear stood quietly on a compliant surface for 90 seconds inside a three-wall virtual environment. The visual conditions were either eyes closed, eyes open or a continuous visual flow field in a pitch-up direction at constant velocity of 30°/sec. A dual task paradigm was presented as a computation task, the Fibonacci sequence. The first 30 seconds of the 90 seconds trial had no vibration followed by 30 seconds of either sub-threshold or above-threshold vibration. Vibration was removed for the final 30 seconds. Root mean squares (RMS) and approximate entropy (ApEn) of center of mass (COM) and center of pressure (COP) excursions were calculated in the anterior-posterior (AP) and medio-lateral (ML) directions for each 30 second time period and normalized to each subject's initial position. Approximate entropy (ApEn) was used to detect movement variability in a time series to determine the unpredictability of the postural responses. COP and COM data were tested for statistical significance using repeated measures analysis of variance (ANOVA) with within-subject factors of vision (3 levels: eyes closed, eyes open and pitch-up), task (2 levels: single task and dual task), and vibration level (2 levels: sub-threshold vibration and above-threshold vibration) at a 95% confidence level (p&lt;0.05). Results supported the hypothesis that the application of SV and AV affected COP regularity and variability differently when subjected to different visual conditions (eyes closed, eyes open and pitch-up). COM randomness increased (higher ApEn) when attention was diverted from postural control which is in agreement with previous studies. The decrease in COM AP randomness (lower ApEn) with vibration suggested that the application of vibration increased the amount of attention invested in postural control or balance when performing an attention demanding cognitive task. The SV increased the COP-AP regularity (lower ApEn) during eyes-closed and eyes-open conditions while AV increased COP-AP variability (increased RMS) during the pitch-up visual condition. In conclusion, posture and balance were affected by the application of vibration noise. The vibration noise enhanced the amount of attention invested in postural control while performing an attention demanding cognitive task and sensory-motor learning was achieved by increasing COM sway structure regularity (lower ApEn) but not the sway magnitude. These results suggest that the interaction between vibration noise and an attention demanding task resulted in the temporal re-structuring of the postural control system without affecting the equilibrium region for the COM sway excursion. Vibration noise appears to facilitate postural control by altering postural response regularity (lower ApEn). For COM, only postural response regularity but not sway variability was affected by vibration noise in relation to vision regardless of the vibration level (SV or AV). For COP postural responses, the effect of SV and AV differs. Due to the perception of self-motion from the pitch-up visual condition, COP postural response most likely arise from cortical level. Since AV only affected COP responses during pitch-up visual condition and not SV, this study suggests that AV applied affected the cortical level of postural control. Effects of SV on postural responses between the eyes-open and eyes-closed vision conditions suggests that SV may affect a subcortical level of postural control. Understanding the effects and mechanism of vibratory noise may help in the design of effective interventions to prevent falls and rehabilitation. These results provide the scientific basis for development of a SR-based rehabilitation device for people with sensory information and processing deficiency as occurs with aging or stroke. The finding of after effects of vibratory noise can be used to determine dosage of vibrotactile stimulation in the design of vibrating footwear. / Bioengineering

Energy harvesting from the rotating system has been an influential topic for researchers over the past several years. Yet, most of these harvesters are linear resonance-based harvesters whose output power drops dramatically under random excitations. This poses a serious problem because a lot of vibrations in rotating systems are stochastic. In this dissertation, a novel energy harvesting strategy for rotating systems was proposed by taking advantage of stochastic resonance. Stochastic resonance is referred to as a physical phenomenon that is manifest in nonlinear bistable systems whereby a weak periodic signal can be significantly amplified with the aid of inherent noise or vice versa. Stochastic resonance can thus be used to amplify the noisy and weak vibration motion. Through mathematical modeling, this dissertation shows that stochastic resonance is particularly favorable to energy harvesting in rotating systems. The conditions for stochastic resonance are satisfied by adding a nonlinear bistable energy harvester to the rotating system because whirl noise and periodic signalㄴ already coexist in the rotating environment. Both numerical and experimental results show that stochastic resonance energy harvester has higher power and wider bandwidth than linear harvesters under a rotating environment. The dissertation also investigates how stochastic resonance changes for the various types of excitation that occur in real-world applications. Under the non-gaussian noise, the stochastic resonance frequency is shifted larger value. Furthermore, the co-existence of the vibrational and stochastic resonance is observed depending on the periodic signal to noise ratio. The dissertation finally proposed two real applications of stochastic resonance energy harvesting. First, stochastic resonance energy harvester for oil drilling applications is presented. In the oil drilling environment, the periodic force in rotating shafts is biased, which can lower the efficacy of stochastic resonance. To solve the problem, an external magnet was placed above the bi-stable energy harvester to compensate for the biased periodic signal. Energy harvester for smart tires is also proposed. The passively tuned system is implemented in a rotating tire via centrifugal force. An inward-oriented rotating beam is used to induce bistability via the centrifugal acceleration of the tire. The results show that larger power output and wider bandwidth can be obtained by applying the proposed harvesting strategy to the rotating system. / Doctor of Philosophy / In this dissertation, a novel energy harvesting strategy for rotating systems was proposed by taking advantage of stochastic resonance. Stochastic resonance is referred to as a physical phenomenon that is manifest in nonlinear bistable systems whereby a weak periodic signal can be significantly amplified with the aid of inherent noise or vice versa. Stochastic resonance can thus be used to amplify the noisy and weak vibration motion. Through mathematical modeling, this dissertation shows that stochastic resonance is particularly favorable to energy harvesting in rotating systems.Both numerical and experimental results show that stochastic resonance energy harvester has higher power and wider bandwidth than linear harvesters under a rotating environment. The dissertation also investigates how stochastic resonance changes for the various types of excitation that occur in real-world applications. The dissertation finally proposed two real applications of stochastic resonance energy harvesting. First, stochastic resonance energy harvester for oil drilling applications is presented. Energy harvester for smart tires is also proposed. The results show that larger power output and wider bandwidth can be obtained by applying the proposed harvesting strategy to the rotating system.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25243号 / 工博第5202号 / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 小森 雅晴, 教授 細田 耕, 准教授 遠藤 孝浩, 教授 松野 文俊 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM