Circular geodesics and accretion disks in Janis-Newman-Winicour and Gamma metric

We study here circular timelike geodesics in the Janis-Newman-Winicour and Gamma metric spacetimes which contain a strong curvature naked singularity and reduce to the Schwarzschild metric for a specific value of one of the parameters. We show that for both the metrics the range of allowed parameters can be divided into three regimes where structure of the circular geodesics is qualitatively different. It follows that the properties of the accretion disks around such naked singularities can be significantly different from those of disks around black holes. This adds to previous studies showing that if naked singularities exist in nature, their observational signature would be significantly different from that of the black hole

Online Covariate Shift Detection based Adaptive Brain-Computer Interface to Trigger Hand Exoskeleton Feedback for Neuro-Rehabilitation

A major issue in electroencephalogram (EEG) based brain-computer interfaces (BCIs) is the intrinsic non-stationarities in the brain waves, which may degrade the performance of the classifier, while transitioning from calibration to feedback generation phase. The non-stationary nature of the EEG data may cause its input probability distribution to vary over time, which often appear as a covariate shift. To adapt to the covariate shift, we had proposed an adaptive learning method in our previous work and tested it on offline standard datasets. This paper presents an online BCI system using previously developed covariate shift detection (CSD)-based adaptive classifier to discriminate between mental tasks and generate neurofeedback in the form of visual and exoskeleton motion. The CSD test helps prevent unnecessary retraining of the classifier. The feasibility of the developed online-BCI system was first tested on 10 healthy individuals, and then on 10 stroke patients having hand disability. A comparison of the proposed online CSD-based adaptive classifier with conventional non-adaptive classifier has shown a significantly (p<0.01) higher classification accuracy in both the cases of healthy and patient groups. The results demonstrate that the online CSD-based adaptive BCI system is superior to the non-adaptive BCI system and it is feasible to be used for actuating hand exoskeleton for the stroke-rehabilitation applications

Active Physical Practice Followed by Mental Practice Using BCI-Driven Hand Exoskeleton: A Pilot Trial for Clinical Effectiveness and Usability

Appropriately combining mental practice (MP) and physical practice (PP) in a post-stroke rehabilitation is critical for ensuring a substantially positive rehabilitation outcome. Here we present a rehabilitation protocol incorporating a separate active PP stage followed by MP stage, using a hand exoskeleton and brain-computer interface (BCI). The PP stage was mediated by a force sensor feedback based assist-as-needed control strategy, whereas the MP stage provided BCI based multimodal neurofeedback combining anthropomorphic visual feedback and proprioceptive feedback of the impaired hand extension attempt. A 6 week long clinical trial was conducted on 4 hemiparetic stroke patients (screened out of 16) with left hand disability. The primary outcome, motor functional recovery, was measured in terms of changes in Grip-Strength (GS) and Action Research Arm Test (ARAT) scores; whereas the secondary outcome, usability of the system, was measured in terms of changes in mood, fatigue and motivation on a visual-analog-scale (VAS). A positive rehabilitative outcome was found as the group mean changes from the baseline in the GS and ARAT were +6.38 kg and +5.66 accordingly. The VAS scale measurements also showed betterment in mood (-1.38), increased motivation (+2.10) and reduced fatigue (-0.98) as compared to the baseline. Thus the proposed neurorehabilitation protocol is found to be promising both in terms of clinical effectiveness and usability

The biogeochemical interaction and alteration of hydrocarbons in shallow sediments of the Scotian Slope, Nova Scotia

1 online resource (x, 138 pages) : colour illustrations, colour maps, colour charts, colour graphsIncludes abstract.Includes bibliographical references (pages 24-33, 66-69, 100-104, 107, 137-138).This thesis presents findings from a study on headspace gas and methane clumped isotopic data obtained from various core samples along the Scotian Slope of Nova Scotia. The research aimed to quantify i) gas loss during sample storage, ii) evaluate the effectiveness of frozen sediment cores in identifying the sulfate methane transition zones, and iii) understand the origins and mechanisms of hydrocarbon gases at deep marine, cold seep sites. Results indicated an average of 75% gas loss for Isojars during the first nine months of storage, emphasizing the importance of proper preservation techniques. Optimal conditions for sample analysis were established, aiding in methane core profile construction for identifying shallow sediment, geochemical transition zones. Methane clumped isotopologue analysis revealed a deep biosphere approximately one kilometer below the seabed, sustained by microbial gas production, supporting seep sites near salt diapirs. This study highlights the significance of direct seep gas samples and provides insights into methane dynamics in marine environments and how deep biosphere methane gas production can impact ocean floor community ecology in diapir controlled cold seep localities

Corticomuscular co-activation based hybrid brain-computer interface for motor recovery monitoring

The effect of corticomuscular coactivation based hybrid brain-computer interface (h-BCI) on post-stroke neurorehabilitation has not been explored yet. A major challenge in this area is to find an appropriate corticomuscular feature which can not only drive an h-BCI but also serve as a biomarker for motor recovery monitoring. Our previous study established the feasibility of a new method of measuring corticomuscular co-activation called correlation of band-limited power time-courses (CBPT) of EEG and EMG signals, outperforming the traditional EEG-EMG coherence in terms of accurately controlling a robotic hand exoskeleton device by the stroke patients. In this paper, we have evaluated the neurophysiological significance of CBPT for motor recovery monitoring by conducting a 5-week long longitudinal pilot trial on 4 chronic hemiparetic stroke patients. Results show that the CBPT variations correlated significantly (p-value< 0.05) with the dynamic changes in motor outcome measures during the therapy for all the patients. As the bandpower based biomarkers are popular in literature, a comparison with such biomarkers has also been made to cross-verify whether the changes in CBPT are indeed neurophysiological. Thus the study concludes that CBPT can serve as a biomarker for motor recovery monitoring while serving as a corticomuscular co-activation feature for h-BCI based neurorehabilitation. Despite an observed significant positive change between pre- and post-intervention motor outcomes, the question of the clinical effectiveness of CBPT is subject to further controlled trial on a larger cohort