Brain wave classification for divergent hand movements

Brain-Computer Interface (BCI) is an emerging technology in medical diagnosis and rehabilitation. In this study, by the acquisition of Electroencephalogram (EEG) signals from 30 healthy participants who perform four different hand movements, necessary features are extracted and classified to determine their accuracies. Statistical time domain features are extracted from the mu and beta frequency band. The Event related desynchronization (ERD)/Event related synchronization (ERS) measurements are extracted, from which it was evident that both mu and beta frequency bands are more efficient in the C3 channel. By applying the Paired Samples t-test, the extracted features are analyzed and were determined to have a 95% significant level of difference between the mu and beta band, being statistically efficient in the beta band of the C3 channel. By employing different classifiers such as Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Naïve Bayesian classifier and Binary Decision Tree (BDT) algorithms on both channel’s mu and beta frequency bands, it was observed that the performance of beta frequency band classifiers shows 90% accuracy in binary class classification. In the comparative study of all these classifiers, LDA and Naïve Bayes show above 95% accuracy for binary class classification

Brain wave classification for divergent hand movements

765-773Brain-Computer Interface (BCI) is an emerging technology in medical diagnosis and rehabilitation. In this study, by the acquisition of Electroencephalogram (EEG) signals from 30 healthy participants who perform four different hand movements, necessary features are extracted and classified to determine their accuracies. Statistical time domain features are extracted from the mu and beta frequency band. The Event related desynchronization (ERD)/Event related synchronization (ERS) measurements are extracted, from which it was evident that both mu and beta frequency bands are more efficient in the C3 channel. By applying the Paired Samples t-test, the extracted features are analyzed and were determined to have a 95% significant level of difference between the mu and beta band, being statistically efficient in the beta band of the C3 channel. By employing different classifiers such as Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Naïve Bayesian classifier and Binary Decision Tree (BDT) algorithms on both channel’s mu and beta frequency bands, it was observed that the performance of beta frequency band classifiers shows 90% accuracy in binary class classification. In the comparative study of all these classifiers, LDA and Naïve Bayes show above 95% accuracy for binary class classification

Preparation and Characterization of Silver Nanoparticle/Aloe Vera Incorporated PCL/PEO matrix for wound dressing application

Polymeric wound dressing materials have remarkable mechanical, structural, and biocompatible behavior. In this work, a polymer matrix of Polycaprolactone (PCL)/Polyethylene Oxide (PEO) incorporated with Aloe Vera (AV) extract and silver nanoparticles were prepared for wound dressing application. Initially, the phytochemicals from AV were extracted by Soxhlet apparatus, and then the aloe extract was used as a reducing agent to synthesize silver nanoparticles (Ag NP). Ag NP's formation was confirmed by the presence of a characteristic UV absorbance peak at 420 nm. Ag NP's average diameter and shape were found to be between 10-50 nm and spherical, respectively. AV extract and Ag NP were incorporated into PCL/PEO polymer solution to prepare the polymer matrix by solution casting method. Box-Behnken design (BBD) was used to study the effect of Ag NP concentration, AV extract percentage, and PEO weight percentage concerning PCL on wound dressing application. Water Vapor Transmission Rate (WVTR) and swelling properties of all the sample were tested and found that the PEO and AV extract plays a major role in both swelling and WVTR irrespective of Ag NP concentration. The antimicrobial property of synthesized Ag NP was studied against gram-negative bacteria Escherichia coli with control samples (PCL and PCL/PEO), Ag NP with 150 mg concentration showed a higher zone of inhibition than the other concentrations. Thus, the prepared PCL/PEO polymer matrix incorporated with AV extract and Ag NP can be used as an effective wound dressing material

Preparation and Characterization of Silver Nanoparticle/Aloe Vera Incorporated PCL/PEO matrix for wound dressing application

35-44Polymeric wound dressing materials have remarkable mechanical, structural, and biocompatible behavior. In this work, a polymer matrix of Polycaprolactone (PCL)/Polyethylene Oxide (PEO) incorporated with Aloe Vera (AV) extract and silver nanoparticles were prepared for wound dressing application. Initially, the phytochemicals from AV were extracted by Soxhlet apparatus, and then the aloe extract was used as a reducing agent to synthesize silver nanoparticles (Ag NP). Ag NP's formation was confirmed by the presence of a characteristic UV absorbance peak at 420 nm. Ag NP's average diameter and shape were found to be between 10-50 nm and spherical, respectively. AV extract and Ag NP were incorporated into PCL/PEO polymer solution to prepare the polymer matrix by solution casting method. Box-Behnken design (BBD) was used to study the effect of Ag NP concentration, AV extract percentage, and PEO weight percentage concerning PCL on wound dressing application. Water Vapor Transmission Rate (WVTR) and swelling properties of all the sample were tested and found that the PEO and AV extract plays a major role in both swelling and WVTR irrespective of Ag NP concentration. The antimicrobial property of synthesized Ag NP was studied against gram-negative bacteria Escherichia coli with control samples (PCL and PCL/PEO), Ag NP with 150 mg concentration showed a higher zone of inhibition than the other concentrations. Thus, the prepared PCL/PEO polymer matrix incorporated with AV extract and Ag NP can be used as an effective wound dressing material

Effect of potential bioinoculants and organic manures on root-rot and wilt, growth, yield and quality of organically grown Coleus forskohlii in a semiarid tropical region of Bangalore (India)

Based on earlier results obtained in pot experiments, 2-year field experiments were conducted with five bioinoculants and neem cake under organic field conditions (with vermicompost as a nutritional supplement) to evaluate their potential to control root-rot and wilt (a complex problem involving Fusarium chlamydosporum and Ralstonia solanacearum) of the medicinal plant Coleus forskohlii. Plants treated with arbuscular mycorrhizal fungus (Glomus fasciculatum), neem cake or Pseudomonas fluorescens showed significantly increased plant height (15-31%), plant spread (25-33%), number of branches (63-67%) and dry root (129-200%) yields, and reduced disease incidence (47-50%) compared to controls. Increases in yields were reflected by increases in N (51-81%), P (17-76%) and K (44-74%) uptake. The forskolin content of the roots was found not to be affected by any of the bioinoculants, but forskolin yield (calculated) was increased significantly by treatment with G. fasciculatum (227%), neem cake (222%) or P. fluorescens (159%)

Stressed out symbiotes:hypotheses for the influence of abiotic stress on arbuscular mycorrhizal fungi

Abiotic stress is a widespread threat to both plant and soil communities. Arbuscular mycorrhizal (AM) fungi can alleviate effects of abiotic stress by improving host plant stress tolerance, but the direct effects of abiotic stress on AM fungi are less well understood. We propose two hypotheses predicting how AM fungi will respond to abiotic stress. The stress exclusion hypothesis predicts that AM fungal abundance and diversity will decrease with persistent abiotic stress. The mycorrhizal stress adaptation hypothesis predicts that AM fungi will evolve in response to abiotic stress to maintain their fitness. We conclude that abiotic stress can have effects on AM fungi independent of the effects on the host plant. AM fungal communities will change in composition in response to abiotic stress, which may mean the loss of important individual species. This could alter feedbacks to the plant community and beyond. AM fungi will adapt to abiotic stress independent of their host plant. The adaptation of AM fungi to abiotic stress should allow the maintenance of the plant-AM fungal mutualism in the face of changing climates. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00442-016-3673-7) contains supplementary material, which is available to authorized users