Color-based classification of EEG Signals for people with the severe locomotive disorder

The neurons in the brain produces electric signals and a collective firing of these electric signals gives rise to brainwaves. These brainwave signals are captured using EEG (Electroencephalogram) devices as micro voltages. These sequence of signals captured by EEG sensors have embedded features in them that can be used for classification. The signals can be used as an alternative input for people suffering from severe locomotive disorder.Classification of different colors can be mapped for many functions like directional movement. In this paper, raw EEG signals from NeuroSky Mindwave headset (a single electrode EEG sensor) have been classified with an attention based Deep Learning Network. Attention based LSTM Networks have been implemented for classification of two different colors and four different colors. An accuracy of 93.5\% was obtained for classification of two colors and an accuracy of 65.75\% was obtained for classifcation of four signals using the mentioned attention based LSTM network.Comment: 6 pages, 3 figures, 14 graphs, 4 tables, 2 author

Estimation of Vehicular Velocity based on Non-Intrusive stereo camera

The paper presents a modular approach for the estimation of a leading vehicle's velocity based on a non-intrusive stereo camera where SiamMask is used for leading vehicle tracking, Kernel Density estimate (KDE) is used to smooth the distance prediction from a disparity map, and LightGBM is used for leading vehicle velocity estimation. Our approach yields an RMSE of 0.416 which outperforms the baseline RMSE of 0.582 for the SUBARU Image Recognition ChallengeComment: 5 pages, 4 images, 1 tabl

Time and Space Domain Prediction of Water Quality Parameters of Bagmati River Using Deep Learning Methods

Bagmati river is biologically, geologically, religiously and historically significant among the river systems of the Kathmandu Valley. The river is affected by five major tributaries, including Manohara, Dhobi Khola, Tukucha, Bishnumati, and Balkhu Khola, which significantly impact the water chemistry inside the Kathmandu Valley. The data of water quality parameters pH, dissolved oxygen, turbidity, temperature, oxygen reduction potential, conductivity, total dissolved solids, salinity among others was collected using fixed sensors (in period of 5 seconds) and mobile sensors (with latitude and longitude) along the river. The observation is important for two reasons, one because it was collected in real-time and fine scale, which is not normally possible with traditional ways, and next such observation was done for the first time in Bagmati River. The aim of this study was to predict water quality parameters of the Bagmati River using machine learning time series models, specifically ARIMA and LSTM. The LSTM model was designed with one input layer, one encoder layer, one repeat layer, one decoder layer, and one output dense layer to separate the output into temporal slices. Additionally, a DNN model was employed for location-based prediction, utilizing two input layers for latitude and longitude and seven output layers for the seven water quality parameters considered for study. The models demonstrated promising performance, but further data collection and parameter variation are recommended for continued optimization

Time and Space Domain Prediction of Water Quality Parameters of Bagmati River Using Deep Learning Methods

Bagmati river is biologically, geologically, religiously and historically significant among the river systems of the Kathmandu Valley. The river is affected by five major tributaries, including Manohara, Dhobi Khola, Tukucha, Bishnumati, and Balkhu Khola, which significantly impact the water chemistry inside the Kathmandu Valley. The data of water quality parameters pH, dissolved oxygen, turbidity, temperature, oxygen reduction potential, conductivity, total dissolved solids, salinity among others was collected using fixed sensors (in period of 5 seconds) and mobile sensors (with latitude and longitude) along the river. The observation is important for two reasons, one because it was collected in real-time and fine scale, which is not normally possible with traditional ways, and next such observation was done for the first time in Bagmati River. The aim of this study was to predict water quality parameters of the Bagmati River using machine learning time series models, specifically ARIMA and LSTM. The LSTM model was designed with one input layer, one encoder layer, one repeat layer, one decoder layer, and one output dense layer to separate the output into temporal slices. Additionally, a DNN model was employed for location-based prediction, utilizing two input layers for latitude and longitude and seven output layers for the seven water quality parameters considered for study. The models demonstrated promising performance, but further data collection and parameter variation are recommended for continued optimization

Lindernia rotundifolia (Linderniaceae), Picria fel-terrae (Linderniaceae), and Limnophila aromatica (Plantaginaceae): three new records for the flora of Nepal

Lindernia rotundifolia (L.) Alston (Linderniaceae), Picria fel-terrae Lour. (Linderniaceae), and Limnophila aromatica (Lam.) Merr. (Plantaginaceae) are newly reported from Jalthal forest, eastern Nepal. Picria Lour. is a new generic record for Nepal. Descriptions of all the species based on Nepalese specimens are provided, along with notes on diagnostic features, color photographs of the species, distribution maps, and notes on habitats

Natural dyes as photo-sensitizer in solar cells

The objective of this research is to employ the natural dyes in dye-sensitized solar cell (DSSC). On account of eco-friendly, renewable, and non-hazardous properties of natural dyes over silicon, a semiconductor, photo-sensitizer in conventional solar cells,  cyclohexane extract of Terminalia alata, a natural dye, was employed as photo-sensitizer. The photoanodes ZnO and 5% Al-doped ZnO for DSSCs were developed by spray pyrolysis. The X-ray diffraction (XRD) has shown hexagonal wurtzite structure of ZnO with lattice constants a = 3.2487 Å and b = 5.1518 Å having particle size 25.85 nm for ZnO and 33.17 nm for Al-doped ZnO. The DSSC properties such as solar conversion efficiency (η), short-circuit current density (Jsc), open-circuit voltage (Voc), and fill factor (FF) were found to be 0.31%, 2.10 mA/cm2, 0.73V, and 45% for ZnO photoanode and 0.37%, 2.25mA/cm2, 0.70 V, and 52.10% for 5% Al-doped photoanode respectively. BIBECHANA 17 (2020) 27-3

Natural dyes as photo-sensitizer in solar cells

The objective of this research is to employ the natural dyes in dye-sensitized solar cell (DSSC). On account of eco-friendly, renewable, and non-hazardous properties of natural dyes over silicon, a semiconductor, photo-sensitizer in conventional solar cells,  cyclohexane extract of Terminalia alata, a natural dye, was employed as photo-sensitizer. The photoanodes ZnO and 5% Al-doped ZnO for DSSCs were developed by spray pyrolysis. The X-ray diffraction (XRD) has shown hexagonal wurtzite structure of ZnO with lattice constants a = 3.2487 Å and b = 5.1518 Å having particle size 25.85 nm for ZnO and 33.17 nm for Al-doped ZnO. The DSSC properties such as solar conversion efficiency (η), short-circuit current density (Jsc), open-circuit voltage (Voc), and fill factor (FF) were found to be 0.31%, 2.10 mA/cm2, 0.73V, and 45% for ZnO photoanode and 0.37%, 2.25mA/cm2, 0.70 V, and 52.10% for 5% Al-doped photoanode respectively. BIBECHANA 17 (2020) 27-3

Outcome analysis of Cohen’s cross trigonal ureteric reimplantation in paediatric age group

Introduction: Cohen’s cross trigonal ureteric reimplantation is the gold standard for surgical management of vesicoureteric reflux (VUR) in children with high success rate. The objective of this study was to evaluate and assess the outcome of open Cohen’s procedure in children with VUR.  Methods: A retrospective review of all patients with VUR who underwent Cohen’s procedure between March 2010 and February 2020 was done. The following were recorded for each patient: age, sex, grade of reflux, operative time, outcome and complications.  Results: The series consisted of 40 patients (25 girls and 15 boys) who underwent Cohen’s procedure with a mean age of 32 months (6 months to 8 years). Bilateral repairs were performed in 16 patients (40%) in the same setting and unilateral repair in 24 patients (60%). Twenty-two patients (55%) had grade IV VUR, 13 patients (32.5%) had grade V VUR and 05 patients (12.5%) had grade III VUR. Mean operative time for bilateral repairs was 249.4(200-290) minutes and 158.3(130-180) minutes for unilateral repair respectively. The mean length of hospital stay was 10.55 (7-15) days. Major complications included two persistent VURs, and one case of bladder hematoma. Postoperative ultrasound abdomen in all patients and micturating cystourethrogram in few patients was obtained, in which 38 patients (95%) had normal study. Conclusion: Cohen’s uretric reimplantation is a standard procedure in paediatric VUR. For better outcome, patient selection and refinement of operative technique should be pursued

Outcome analysis of Cohen’s cross trigonal ureteric reimplantation in paediatric age group

Introduction: Cohen’s cross trigonal ureteric reimplantation is the gold standard for surgical management of vesicoureteric reflux (VUR) in children with high success rate. The objective of this study was to evaluate and assess the outcome of open Cohen’s procedure in children with VUR.  Methods: A retrospective review of all patients with VUR who underwent Cohen’s procedure between March 2010 and February 2020 was done. The following were recorded for each patient: age, sex, grade of reflux, operative time, outcome and complications.  Results: The series consisted of 40 patients (25 girls and 15 boys) who underwent Cohen’s procedure with a mean age of 32 months (6 months to 8 years). Bilateral repairs were performed in 16 patients (40%) in the same setting and unilateral repair in 24 patients (60%). Twenty-two patients (55%) had grade IV VUR, 13 patients (32.5%) had grade V VUR and 05 patients (12.5%) had grade III VUR. Mean operative time for bilateral repairs was 249.4(200-290) minutes and 158.3(130-180) minutes for unilateral repair respectively. The mean length of hospital stay was 10.55 (7-15) days. Major complications included two persistent VURs, and one case of bladder hematoma. Postoperative ultrasound abdomen in all patients and micturating cystourethrogram in few patients was obtained, in which 38 patients (95%) had normal study. Conclusion: Cohen’s uretric reimplantation is a standard procedure in paediatric VUR. For better outcome, patient selection and refinement of operative technique should be pursued

A cluster-based, spatial-sampling method for assessing household healthcare utilization patterns in resource-limited settings

Background: Implementation of population-based surveys is resource intensive and logistically demanding, especially in areas with rapidly changing demographics and incomplete or no enumeration of the underlying population and their residences. To remove the need for pre-enumeration and to simplify field logistics for the population healthcare utilization survey used for the Surveillance for Enteric Fever in Asia Project in Nepal, we incorporated a geographic information system-based geosurvey and field mapping system into a single-stage cluster sampling approach.Methods: A survey was administered to ascertain healthcare-seeking behavior in individuals with recent suspected enteric fever. Catchment areas were based on residential addresses of enteric fever patients using study facilities; clusters were randomly selected from digitally created grids using available satellite images and all households within clusters were offered enrollment. A tablet-compatible geosurvey and mapping system that allowed for data-syncing and use in areas without cellular data was created using the ArcGIS suite of software.Results: Between January 2017 and November 2018, we surveyed 25 521 households in Nepal (16 769 in urban Kathmandu and 8752 in periurban Kavrepalanchok), representing 84 202 individuals. Overall, the survey participation rate was 90.9%, with geographic heterogeneity in participation rates within each catchment area. Areas with higher average household wealth had lower participation rates.Conclusion: A geographic information system-based geosurvey and field mapping system allowed creation of a virtual household map at the same time as survey administration, enabling a single-stage cluster sampling method to assess healthcare utilization in Nepal for the Surveillance for Enteric Fever in Asia Project . This system removed the need for pre-enumeration of households in sampling areas, simplified logistics and could be replicated in future community surveys