Influence of Aggregates on Stripping Behavior of Bituminous Mixes

Moisture damage leads to premature failure of flexible pavements. The removal of bituminous coating from aggregates lead to the disintegration of bituminous mixes and is known as stripping. Various mechanisms and factors have been identified to play a role in the process, properties of aggregates being one of the major factors. This study is an attempt to analyze the influence of chemical, mineralogical and physical properties of aggregates on the stripping propensity of the loose mix. For this purpose, aggregates are chosen from six different quarry sites with diverse chemical compositions used for construction and maintenance of a large network of roads. Stripping tests are thereafter conducted on the aggregates using different percentage of hydrated lime. The amount of hydrated lime required for the prevention of stripping for concerned aggregate sources is determined. The research leads to the findings that the presence of elements such as silicon and potassium leads to a decrease in bond strength whereas the presence of calcium, sodium, iron, magnesium and aluminium enhanced the bond strength. Statistical tools and techniques are used to verify the results. Comparatively softer aggregates showed lesser resistance to stripping which could be inferred from aggregate impact and Los Angeles abrasion tests. The findings of the study can be helpful in the selection of aggregates with different chemical content for bituminous road construction depending upon the sensitivity to stripping. Doi: 10.28991/cej-2021-03091671 Full Text: PD

An EEG-EMG Correlation-based Brain-Computer Interface for Hand Orthosis Supported Neuro-Rehabilitation

Background Corticomuscular coupling has been investigated for long, to find out the underlying mechanisms behind cortical drives to produce different motor tasks. Although important in rehabilitation perspective, the use of corticomuscular coupling for driving brain-computer interface (BCI)-based neurorehabilitation is much ignored. This is primarily due to the fact that the EEG-EMG coherence popularly used to compute corticomuscular coupling, fails to produce sufficient accuracy in single-trial based prediction of motor tasks in a BCI system. New Method In this study, we have introduced a new corticomuscular feature extraction method based on the correlation between band-limited power time-courses (CBPT) associated with EEG and EMG. 16 healthy individuals and 8 hemiplegic patients participated in a BCI-based hand orthosis triggering task, to test the performance of the CBPT method. The healthy population was equally divided into two groups; one experimental group for CBPT-based BCI experiment and another control group for EEG-EMG coherence based BCI experiment. Results The classification accuracy of the CBPT-based BCI system was found to be 92.81±2.09% for the healthy experimental group and 84.53±4.58% for the patients’ group. Comparison with existing method The CBPT method significantly (p−value < 0.05) outperformed the conventional EEG-EMG coherence method in terms of classification accuracy. Conclusions The experimental results clearly indicate that the EEG-EMG CBPT is a better alternative as a corticomuscular feature to drive a BCI system. Additionally, it is also feasible to use the proposed method to design BCI-based robotic neurorehabilitation paradigms

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

Formulation and Characterization of Alginate Microbeads of Clonidine Hydrochloride by Ionotropic Gelation Technique

The objective of this study was to prepare and evaluate sodium alginate microbeads with calcium chloride as cross-linking agent for Clonidine hydrochloride by ionotropic gelation method. Clonidine hydrochloride a centrally acting sympatholytic and imidazoline-derivative hypotensive agent; selective α2-adrenergic agonist. It stimulates alpha2-adrenergic receptors in the brainstem to decrease sympathetic nervous system outflow. It is also administered epidurally to treat pain. Microbeads offer numerous advantages for releasing one of the drugs or part of the same drug immediately while remaining drug or parts of the same can be sustained release. Prepared microbeads were evaluated for particle size, polydispersity index, zeta potential, particle shape, surface morphology, entrapment efficiency and In vitro drug release. The prepared beads were free flowing and white in color. The drug loaded beads showed 72.9±2.4% to 94.6±2.6 % drug entrapment, which was found to increase with increase in alginate concentration. In vitro drug release study of these microbeads indicated controlled release for Clonidine hydrochloride 83.46% release after 48 hours. Hence the observations of all results of the different batches, MBD 11 showed controlled release action and improved drug availability. From this study it could be concluded that the free flowing microbeads of Clonidine hydrochloride could be successfully prepared by ionotropic gelation technique with high entrapment efficiency and prolonged release characteristics. Keywords: Clonidine hydrochloride, Microbeads, Sodium alginate, Calcium chloride, Ionotropic gelation method

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