Determining States of Movement in Humans Using Minimally Processed EEG Signals and Various Classification Methods

Electroencephalography (EEG) is a non-invasive technique used in both clinical and research settings to record neuronal signaling in the brain. The location of an EEG signal as well as the frequencies at which its neuronal constituents fire correlate with behavioral tasks, including discrete states of motor activity. Due to the number of channels and fine temporal resolution of EEG, a dense, high-dimensional dataset is collected. Transcranial direct current stimulation (tDCS) is a treatment that has been suggested to improve motor functions of Parkinson’s disease and chronic stroke patients when stimulation occurs during a motor task. tDCS is commonly administered without taking biofeedback such as brain state into account. Additionally, the administration of tDCS by a technician during motor tasks is a tiresome process. Machine learning and deep learning algorithms are often used to perform classification tasks on high-dimensional data, and have been successfully used to classify movement states based on EEG features. In this thesis, a program capable of performing live classification of motor state using machine learning and EEG as biofeedback is proposed. This program would allow for the development of a device that optimally administers tDCS dosage during motor tasks. This is achieved by surveying the literature for motor classification techniques based on EEG signals, recreating the methods in the surveyed literature, measuring their accuracy, and creating an application to perform online capturing and analysis of EEG recordings using the classifier with the highest accuracy to demonstrate the feasibility of real-time classification. The highest accuracy of motor classification is achieved by training a random forest on binned spectral decomposition from a normalized signal. While live classification was successfully performed, accuracy was limited by external changes to the recording environment, skewing the input to the trained model

Alien Registration- Barnett, Maurice B. (Millinocket, Penobscot County)

https://digitalmaine.com/alien_docs/7937/thumbnail.jp

Maurice Barnett in a Senior Trumpet Recital and Steve Hand in a Sophomore Trumpet Recital

This is the program for the senior trumpet recital of Maurice Barnett and the sophomore trumpet recital of Steve Hand. Janada Barnett, pianist, Ouida Eppinette, pianist and organist, and David Glaze, organist, assisted. The recital was held on April 29, 1968, in Mitchell Hall

Weather conditions and daily television use in the Netherlands, 1996–2005

This study examines the impact of daily atmospheric weather conditions on daily television use in the Netherlands for the period 1996–2005. The effects of the weather parameters are considered in the context of mood and mood management theory. It is proposed that inclement and uncomfortable weather conditions are associated with lower human mood, and that watching entertainment and avoiding informational programs may serve to repair such mood. We consequently hypothesize that people spend more time watching television if inclement and uncomfortable weather conditions (low temperatures, little sunshine, much precipitation, high wind velocity, less daylight) coincide with more airtime for entertainment programs, but that they view less if the same weather conditions coincide with more airtime devoted to information fare. We put this interaction thesis to a test using a time series analysis of daily television viewing data of the Dutch audience obtained from telemeters (T = 3,653), merged with meteorological weather station statistics and program broadcast figures, whilst controlling for a wide array of recurrent and one-time societal events. The results provide substantial support for the proposed interaction of program airtime and the weather parameters temperature and sunshine on aggregate television viewing time. Implications of the findings are discussed

The Solar Neutrino Puzzle: An Oscillation Solution with Maximal Neutrino Mixing

If, as suggested by the SuperKamiokande results, the mu neutrino and tau neutrino are maximally and ``rapidly'' mixed, this alone determines the mapping from current to mass eigenstates up to one rotation angle (theta) mixing the electron neutrino ``more slowly'', with an equal combination of the mu neutrino and tau neutrino. For sin 2 theta = 1, the resulting minimal number of free parameters, yet maximal mixing, shows agreement between extant observations of solar neutrinos and predictions by the standard solar model with minor modifications.Comment: 10 pages, latex, revtex source, two postscript figure

Biallelic loss-of-function variants in PLD1 cause congenital right-sided cardiac valve defects and neonatal cardiomyopathy

Congenital heart disease is the most common type of birth defect, accounting for one-third of all congenital anomalies. Using whole-exome sequencing of 2718 patients with congenital heart disease and a search in GeneMatcher, we identified 30 patients from 21 unrelated families of different ancestries with biallelic phospholipase D1 (PLD1) variants who presented predominantly with congenital cardiac valve defects. We also associated recessive PLD1 variants with isolated neonatal cardiomyopathy. Furthermore, we established that p.I668F is a founder variant among Ashkenazi Jews (allele frequency of ~2%) and describe the phenotypic spectrum of PLD1-associated congenital heart defects. PLD1 missense variants were overrepresented in regions of the protein critical for catalytic activity, and, correspondingly, we observed a strong reduction in enzymatic activity for most of the mutant proteins in an enzymatic assay. Finally, we demonstrate that PLD1 inhibition decreased endothelial-mesenchymal transition, an established pivotal early step in valvulogenesis. In conclusion, our study provides a more detailed understanding of disease mechanisms and phenotypic expression associated with PLD1 loss of function

Cardiac regeneration: different cells same goal

Cardiovascular diseases are the leading cause of mortality, morbidity, hospitalization and impaired quality of life. In most, if not all, pathologic cardiac ischemia ensues triggering a succession of events leading to massive death of cardiomyocytes, fibroblast and extracellular matrix accumulation, cardiomyocyte hypertrophy which culminates in heart failure and eventually death. Though current pharmacological treatment is able to delay the succession of events and as a consequence the development of heart failure, the only currently available and effective treatment of end-stage heart failure is heart transplantation. However, donor heart availability and immunorejection upon transplantation seriously limit the applicability. Cardiac regeneration could provide a solution, making real a dream of both scientist and clinician in the previous century and ending an ongoing challenge for this century. In this review, we present a basic overview of the various cell types that have been used in both the clinical and research setting with respect to myocardial differentiation