Mechanics Desktop Lab Equipment

This paper overviews the design, implementation and testing of a senior project designed to fix the issue of there being no lab equipment or space for content pertaining to mechanic of materials topics. This is of concern as Cal Poly is reorganizing content as it switches to the semester system and is in need of labs for this material. The solution found was to create a portable miniature universal test machine that could be carted into non-lab classrooms. The goal was to create a device that was low-cost, modifiable, durable, easy to manufacture and repair as these were the qualities that would allow it to compete with other similar products in the market. The report focuses on the manufacturing and verification of this prototype along with a discussion of what was learned. Recommendations are given to those that aim to follow up this project so that the device can better achieve the goals of the project. A final overview of what was and was not achieved is reflected on at the end along with the usefulness of this project’s outcomes

Identifying phase synchronization clusters in spatially extended dynamical systems

We investigate two recently proposed multivariate time series analysis techniques that aim at detecting phase synchronization clusters in spatially extended, nonstationary systems with regard to field applications. The starting point of both techniques is a matrix whose entries are the mean phase coherence values measured between pairs of time series. The first method is a mean field approach which allows to define the strength of participation of a subsystem in a single synchronization cluster. The second method is based on an eigenvalue decomposition from which a participation index is derived that characterizes the degree of involvement of a subsystem within multiple synchronization clusters. Simulating multiple clusters within a lattice of coupled Lorenz oscillators we explore the limitations and pitfalls of both methods and demonstrate (a) that the mean field approach is relatively robust even in configurations where the single cluster assumption is not entirely fulfilled, and (b) that the eigenvalue decomposition approach correctly identifies the simulated clusters even for low coupling strengths. Using the eigenvalue decomposition approach we studied spatiotemporal synchronization clusters in long-lasting multichannel EEG recordings from epilepsy patients and obtained results that fully confirm findings from well established neurophysiological examination techniques. Multivariate time series analysis methods such as synchronization cluster analysis that account for nonlinearities in the data are expected to provide complementary information which allows to gain deeper insights into the collective dynamics of spatially extended complex systems

Seizure localization using pre ictal phase-amplitude coupling in intracranial electroencephalography

Understanding changes in brain rhythms provides useful information to predict the onset of a seizure and to localize its onset zone in epileptic patients. Brain rhythms dynamics in general, and phaseamplitude coupling in particular, are known to be drastically altered during epileptic seizures. However, the neural processes that take place before a seizure are not well understood. We analysed the phaseamplitude coupling dynamics of stereoelectroencephalography recordings (30 seizures, 5 patients) before and after seizure onset. Electrodes near the seizure onset zone showed higher phase-amplitude coupling. Immediately before the beginning of the seizure, phase-amplitude coupling dropped to values similar to the observed in electrodes far from the seizure onset zone. Thus, our results bring accurate information to detect epileptic events during pre-ictal periods and to delimit the zone of seizure onset in patients undergoing epilepsy surgeryFil: Cámpora, Nuria Elide. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Ingeniería Biomédica; ArgentinaFil: Mininni, Camilo Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Kochen, Sara Silvia. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; ArgentinaFil: Lew, Sergio Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería. Instituto de Ingeniería Biomédica; Argentin

‘Functional Connectivity’ Is a Sensitive Predictor of Epilepsy Diagnosis after the First Seizure

Background: Although epilepsy affects almost 1 % of the world population, diagnosis of this debilitating disease is still difficult. The EEG is an important tool for epilepsy diagnosis and classification, but the sensitivity of interictal epileptiform discharges (IEDs) on the first EEG is only 30–50%. Here we investigate whether using ‘functional connectivity ’ can improve the diagnostic sensitivity of the first interictal EEG in the diagnosis of epilepsy. Methodology/Principal Findings: Patients were selected from a database with 390 standard EEGs of patients after a first suspected seizure. Patients who were later diagnosed with epilepsy (i.e. $two seizures) were compared to matched nonepilepsy patients (with a minimum follow-up of one year). The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands. In total, 114 patients were selected. Fifty-seven patients were diagnosed with epilepsy (20 had IEDs on their EEG) and 57 matched patients had other diagnoses. Epilepsy patients had significantly higher SL in the theta band than non-epilepsy patients. Furthermore, theta band SL proved to be a significant predictor of a diagnosis of epilepsy. When only those epilepsy patients without IEDs were considered (n = 74), theta band SL could predict diagnosis with specificity of 76 % and sensitivity of 62%. Conclusion/Significance: Theta band functional connectivity may be a useful diagnostic tool in diagnosing epilepsy

Terminology of polymers and polymerization processes in dispersed systems (IUPAC Recommendations 2011)

A large group of industrially important polymerization processes is carried out in dispersed systems. These processes differ with respect to their physical nature, mechanism of particle formation, particle morphology, size, charge, types of interparticle interactions, and many other aspects. Polymer dispersions, and polymers derived from polymerization in dispersed systems, are used in diverse areas such as paints, adhesives, microelectronics, medicine, cosmetics, biotechnology, and others. Frequently, the same names are used for different processes and products or different names are used for the same processes and products. The document contains a list of recommended terms and definitions necessary for the unambiguous description of processes, products, parameters, and characteristic features relevant to polymers in dispersed systems

Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.Comment: 36 pages, 6 figures, 2 tables; to be published in "Physica A

Neurons in the human amygdala encode face identity, but not gaze direction

The amygdala is important for face processing, and direction of eye gaze is one of the most socially salient facial signals. Recording from over 200 neurons in the amygdala of neurosurgical patients, we found robust encoding of the identity of neutral-expression faces, but not of their direction of gaze. Processing of gaze direction may rely on a predominantly cortical network rather than the amygdala

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page

Operation of MHSP multipliers in high pressure pure noble-gas

We report on the performance of a Micro-Hole & Strip Plate (MHSP) electron multiplier operating in pure Xe, Kr, Ar and Ne at the pressure range of 1 to 6 bar. The maximal gains at 1 bar Xe and Kr are 50000 and 100000, respectively; they drop by about one order of magnitude at 2 bar and by almost another order of magnitude at 5-6 bar; they reach gains of 500 and 4000 at 5 bar in Xe and Kr, respectively. In Ar, the gain varies very little with pressure, being 3000-9000; in Ne the maximum attainable gain, about 100000, is pressure independent above 2 bar. The results are compared with that of single- and triple-GEM multipliers operated in similar conditions. Potential applications are in hard X-ray imaging and in cryogenic radiation detectors.Comment: 16 pages, 4 figures. Submitted to JINST, 9 jan, 200

Scaling Effects and Spatio-Temporal Multilevel Dynamics in Epileptic Seizures

Epileptic seizures are one of the most well-known dysfunctions of the nervous system. During a seizure, a highly synchronized behavior of neural activity is observed that can cause symptoms ranging from mild sensual malfunctions to the complete loss of body control. In this paper, we aim to contribute towards a better understanding of the dynamical systems phenomena that cause seizures. Based on data analysis and modelling, seizure dynamics can be identified to possess multiple spatial scales and on each spatial scale also multiple time scales. At each scale, we reach several novel insights. On the smallest spatial scale we consider single model neurons and investigate early-warning signs of spiking. This introduces the theory of critical transitions to excitable systems. For clusters of neurons (or neuronal regions) we use patient data and find oscillatory behavior and new scaling laws near the seizure onset. These scalings lead to substantiate the conjecture obtained from mean-field models that a Hopf bifurcation could be involved near seizure onset. On the largest spatial scale we introduce a measure based on phase-locking intervals and wavelets into seizure modelling. It is used to resolve synchronization between different regions in the brain and identifies time-shifted scaling laws at different wavelet scales. We also compare our wavelet-based multiscale approach with maximum linear cross-correlation and mean-phase coherence measures