Temporal and spatial analysis of near fault stations in terms of impulsive behavior

Increasing number of seismic stations located in close proximity to active faults allows analysis of seismic signals that are recorded in near fault regions. Unique seismic signals, called \u201cimpulsive\u201d or \u201cpulse shaped\u201d signals, are captured in velocity waveforms in numerous large magnitude earthquakes. In such waveforms, the earthquake is recorded as a one or several long period high amplitude signals. Long period signals are important in engineering seismology due to their large loads on structures. Ground motion prediction equations and design codes fail to capture the amplitudes in long periods of the impulsive signals. In this thesis nature of impulsive signals and their spatial distribution in near fault regions are investigated. To do that two different algorithm are developed in order to distinguish impulsive signals from non-impulsive signals. Moreover, the probability of the pulse shaped signal occurrence is estimated. In order to investigate the impulsive signals, near fault records from major crustal earthquakes are merged into a dataset. It contains waveforms that are coming from well known seismogenic zones. Waveforms in the dataset are also analyzed by implementing several previous studies to make comparison. The first pulse shaped signal classification algorithm is developed using wavelet analysis. Wavelet analysis decomposes the signal into time-frequency domain which provides the energy variation with time and frequency. The wavelet power spectrum of velocity waveforms are analyzed by using Ricker and Morlet wavelets. A threshold of minimum amplitude is applied. A comparison is made between the total energy of a signal and the energy of the time incidence where peak ground velocity is measured. Furthermore time incidence where maximum spectral energy is located in time is also taken into consideration. Energy ratios are used for determination of impulsive signals. It is found that a Ricker wavelet explains the features of the impulsive part of the velocity waveforms more accurately than the Morlet wavelet. It can measure the period of the pulse and the phase shift of the impulsive parts of the waveform. Spectral features of the impulsive signals are also captured successfully using a Ricker wavelet. The second classification algorithm uses convolutional neural networks. In order to train the convolutional neural networks, synthetic impulsive signals are created. A model is developed using real non-impulsive velocity waveforms from the dataset and synthetic impulsive waveforms. Impulsive signals are manually labeled as impulsive or non-impulsive. The trained model is run on the real manually picked impulsive signals of the dataset and the performance of the convolutional neural network, the wavelet method and various previously published methods are benchmarked. The convolutional neural networks approach correctly identifies almost 97% of the impulsive signals. Accuracy rate of the model is superior than other models. In order to understand the probability of the impulsive signals on earthquakes, a multi-variate Bayes classifier method is implemented on the dataset. Various information about the fault, earthquake and station are analyzed and 3 parameters that are correlated with the impulsive signals are used for the probability calculations. Probability models are developed for normal, reverse and strike slip faults. The validity of this model is tested on the data set. Developed models can provide pulse probability distributions without requiring earthquake-specific parameters. A relation between the period of the pulses and the moment magnitude is also developed

Functional and Structural MRI Studies on Impulsiveness: Attention-Deficit/Hyperactive Disorder and Borderline Personality Disorders

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Simulation study on giant panda population dynamics model with due consideration for deforestation

AbstractDeforestation has destroyed the home of giant panda and poses a direct threat to their survival. Based on the idea of habitat protection of the trinity of “forest-bamboo-giant panda”, a “forest-bamboo-giant panda” nonlinear dynamics model is established with due consideration for pulse deforestation. Computer numerical simulation is used to study the periodic solutions of this dynamics model and chaos strange attractor, and the ecological significance of the dynamic results. A threshold value in deforestation is thus obtained. That is, when the pulse intensity of deforestation is beyond a given threshold, the giant panda population will be almost extinct even though some forest still remains. When the pulse intensity of deforestation is within a given threshold, an ecological balance among “Forest-bamboo-giant panda” will kept for them to continue to exist

BRAIN CONNECTIVITY AND TREATMENT RESPONSE IN ADULT ADHD:understanding the relationship between individual differences in fronto-parietal and fronto-striatal brain networks and response to chronic treatment with methylphenidate

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, characterised by disrupted anatomical and/or functional connectivity, mainly in the fronto-striatal and fronto-parietal networks. Stimulants, such as methylphenidate (MPH), represent a first-line treatment in ADHD, but one third of patients fail to respond, with severe consequences for the individual and the society at large. Hence, a comprehensive understanding of the relationship between individual differences in brain abnormalities and treatment response is needed.This thesis focused on two main brain networks: the fronto-striatal network, a central theme in ADHD research, and the fronto-parietal attentive network, formed by the three branches of the superior longitudinal fasciculus (SLF). The SLF branches have been only recently described in humans, and there is no detailed analysis of their distinct functional roles and involvement in disorders such as ADHD. Therefore, I first investigated the functional anatomy of the SLF branches by combining a meta-analytic approach with tractography, and revealed novel findings about the anatomical and functional segregation and integration of brain functions within fronto-parietal networks. Then, I showed, for the first time, that the three SLF branches are all significantly right-lateralised in ADHD patients but not in controls, and provided preliminary evidence that the pattern of lateralisation of the SLF I may be related to poor attentive performance in ADHD patients.Finally, I conducted functional and structural connectivity analysis to test whether a relationship exists between brain abnormalities and treatment response in adult ADHD. I employed a longitudinal crossover follow-up design. 60 non-medicated adult ADHD patients were recruited and underwent behavioural assessment (Qb test) and magnetic resonance imaging (MRI) scanning twice, once under placebo and once under a clinically effective dose of MPH. Clinical and behavioural response was measured after two months of treatment with MPH. I demonstrated for the first time that there is a relationship between ‘connectivity’ abnormalities within fronto-parietal networks and treatment response in adult ADHD, both at the anatomical and functional level.Ultimately, my investigation contributed towards the identification of potential biomarkers of treatment response, which in the future may help clinicians deliver more individualised treatments.<br/

Deviations in neural activity and network integration underpinning the co-occurrence of emotion dysregulation and attention-deficit/hyperactivity disorder: Analyses of fMRI task activations and functional brain network topology

The aim of this thesis was to improve our understanding of the relationship between Attention-deficit/hyperactivity disorder (ADHD) and emotion dysregulation and the underlying neural activity. Three research articles examine specific aspects of the relationship between ADHD and emotion dysregulation, namely the perception of emotional stimuli, the association between functional brain topology and emotion dysregulation in different ADHD presentations, and emotion dysregulation-related neurobiological and phenotypical predictors of the course of ADHD. All three articles are based on functional magnetic resonance imaging (fMRI) data. Individuals with ADHD exhibited aberrant amygdala reactivity and ventromedial prefrontal cortex coupling in the perception and processing of emotional face stimuli. Moreover, functional network topology of the right insula was shown to affect emotion dysregulation in ADHD and emotion dysregulation and integration of emotion-related brain networks were shown to affect intraindividual change in ADHD severity throughout late adolescence. In Summary, the thesis provides evidence that neural activity and functional connectivity between brain structures affecting emotion may be related to the co-occurrence of emotion dysregulation and ADHD. ADHD and the common co-occurring emotional problems should not be attributed to single, isolated systems, e.g., for executive functions and cognitive control. The neurobiological roots appear to be complex and heterogeneous, involving the interplay of different brain networks that are at least partly emotion-related

Neuronal basis of emotion processing and regulation in conduct disorder

Emotion regulation, a key component of healthy development, has been shown to be deficient in several psychiatric conditions, including conduct disorder. Conduct disorder is a neuropsychiatric disorder of childhood and adolescence characterized by severe aggressive behavior and violation of societal norms. It is highly prevalent and results in substantial economic costs and negative social consequences. Neuroimaging evidence has revealed brain activity alterations in several regions, including prefrontal, temporal, and limbic cortex (amygdala, insula, and cingulate gyrus). While the neuronal basis of emotion processing in conduct disorder has been intensely investigated, the brain correlates of implicit and explicit emotion regulation remain unclear. The main aim of this dissertation was to extend current knowledge by investigating the neuronal mechanisms of emotion regulation in children and adolescents with conduct disorder. First, we conducted a meta-analysis in order to identify the neuronal correlates of emotion processing in adolescents with aggressive behavior. We then developed an affective Stroop task designed to investigate the interplay between emotion and cognition in a paediatric population, and validated it in healthy young adults. We then employed the task to study the neuronal characteristics of implicit emotion-cognition interaction in children and adolescents with conduct disorder. Finally, we investigated explicit emotion regulation by cognitive reappraisal (i.e., reinterpretation of the meaning of an emotional stimulus) in conduct disorder. We here present findings on altered brain function during tasks assessing implicit and explicit emotion regulation in adolescents with conduct disorder that are in agreement with behaviorally observed deficits. Our meta-analysis on emotion processing in conduct disorder summarized previous literature indicating prefrontal and limbic brain structure and function alterations. The results from our study employing the affective Stroop task in healthy adults validated the usefulness of our task design and replicated previous findings suggesting that emotion significantly impacts cognition on a behavioral and neuronal level. Using the affective Stroop and cognitive reappraisal tasks in adolescents with conduct disorder revealed neuronal alterations within prefrontal and limbic regions, brain areas implicated in both emotion and cognition. Overall, the results of this dissertation provide novel evidence on the neuronal basis of emotion regulation deficits in conduct disorder. Future studies shall further investigate emotion regulation in specific subgroups of conduct disorder, for example those with psychopathic traits or high levels of anxiety with the ultimate goal of influencing the child’s immediate environment and society as a whole

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

Intra-individual variability in adult ADHD: an exploration of the viability of distinct purely inattentive condition

Researchers have suggested that intraindividual variability (IIV), or variation in cognitive testing performance within an individual across a measure or group of measures, may be an endophenotypic marker of Attention-Deficit/Hyperactivity Disorder (ADHD). However, not all studies have consistently demonstrated significant differences in IIV between individuals with and without ADHD. One potential explanation for this ambiguity is experimental group heterogeneity owing to Sluggish Cognitive Tempo (SCT). Individuals with SCT exhibit behavioral characteristics dissimilar from individuals with ADHD; rather than being impulsive, hyperactive, and aggressive, they tend to be shy, day-dreamy, and cognitively slow. Researchers have hypothesized that the presence of SCT in the absence of hyperactivity may reflect a distinct purely-inattentive condition that is currently diagnosed as ADHD. If these purely inattentive individuals are included in ADHD experimental groups, they could obfuscate between-groups differences. Unfortunately, few studies have attempted to separate purely inattentive individuals from those with ADHD, with none having examined cognitive functioning after such a separation and in adults. The purpose of the current study, then, was to attempt to identify and separate adults with “pure inattention” from adults with ADHD, and to then compare the groups’ performances on a large neuropsychological test battery. Of particular interest were measured group differences in IIV—operationalized as both reaction time standard deviation and intraindividual standard deviation (ISD)—and SCT as assessed by objective cognitive testing. Cluster analysis was used to identify experimental groups via responses to twelve items on the Wender Utah Rating Scale (WURS). Individuals were also grouped, in separate analyses, by DSM-IV-TR ADHD subtype, and by their degree of endorsed SCT-like symptoms on the WURS. Results indicated that the use of the selected items from the WURS, combined with cluster analysis, was not an effective method of delineating a purely inattentive group. No significant between-groups effects were identified across any of the three grouping methods with respect to IIV or SCT. The implications of these results are discussed, and future research directions are suggested

Biomedical Engineering

Biomedical engineering is currently relatively wide scientific area which has been constantly bringing innovations with an objective to support and improve all areas of medicine such as therapy, diagnostics and rehabilitation. It holds a strong position also in natural and biological sciences. In the terms of application, biomedical engineering is present at almost all technical universities where some of them are targeted for the research and development in this area. The presented book brings chosen outputs and results of research and development tasks, often supported by important world or European framework programs or grant agencies. The knowledge and findings from the area of biomaterials, bioelectronics, bioinformatics, biomedical devices and tools or computer support in the processes of diagnostics and therapy are defined in a way that they bring both basic information to a reader and also specific outputs with a possible further use in research and development