Search

Researchers in cognitive neuroscience, developmental cognitive neuroscience, educational psychology, educational technology, education theory, and other related fields collaborate in the emerging field of educational neuroscience, also known as neuroeducation. This interdisciplinary approach aims to explore the connections between psychological processes and education. By integrating basic discoveries in cognitive neuroscience with educational technology, researchers in neuroeducation strive to enhance curricula to foster curiosity and boost confidence levels in learners. The ultimate objective of neuroeducation is to generate both theoretical insights and practical applications that offer a fresh perspective on learning across various disciplines. The development of confidence is closely related to the principles of curiosity and information processing. When people are interested in a topic, they are more likely to seek out information and engage in learning experiences that can lead to deeper understanding. This information process allows people to analyze and understand the information they encounter, which in turn can increase their confidence in their knowledge and abilities. By embracing curiosity and honing their information-processing skills, people can develop a strong self-confidence that empowers them to take new challenges and pursue their goals with determination. This review study on curiosity have uncovered a fascinating insight into its mechanisms. Researchers found that curiosity aligns with a confidence function resembling an inverted U-shape, peaking when individuals have moderate confidence in their knowledge. Moreover, heightened curiosity drives individuals to actively seek out new information, showcasing the profound impact of curiosity on knowledge acquisition. This revelation holds immense promise for understanding human behavior and learning processes. This study focuses on boosting confidence in individuals through the application of curiosity and information knowledge processing techniques to elevate the standards of education and training across both traditional and modern methodologies. The integration of these principles is poised to revolutionize the learning experience, fostering a more dynamic and effective approach to knowledge acquisition and skill development. This innovative strategy holds immense potential to empower learners, educators, and trainers alike, paving the way for a more enriched and impactful educational landscape.

Abstract This study was conducted in the Central Himalayan middle hills to understand the nature of polycyclic aromatic hydrocarbons (PAHs) embedded in aerosol particles, their sources and human health risk assessments. The level of sum of 15 particle-phase PAHs was between 9 and 335 ng/m3, with an average concentration of 73±66 ng/m3. There were strong seasonal differences in total suspended particles (TSP) and particle-bound PAH concentrations with higher concentrations in winter, followed by pre-monsoon and lowest in monsoon. The main contributor to the suspended particles was 5-ring PAHs (32%), followed by 4-ring (29%), 6-ring (28%), and 3-ring PAHs (11%). Conversely, the gas-phase PAHs showed that 3-ring PAHs contributed utmost to the total particles. The molecular ratios and principal component analysis indicated that both petrogenic and pyrogenic sources, particularly fossil fuel combustion, biomass combustion, and car exhausts, were the major sources of PAHs. The overall average Benzo (a)pyrene equivalent concentration of particulate PAHs was 11.71 ng/m3, which substantially exceeded the WHO guideline (1 ng/m3), and indicated the potential health risks for local residents. The average lifetime inhalation cancer risk (ILCR) estimates associated with carcinogenic PAHs was 8.78×10−6 for adults, suggesting the possible cancer risk and 2.47×10−5 for children, signifying extreme carcinogenic effects of PAHs on children’s health. Therefore, strict measures should be taken to reduce PAHs emissions in the region.

PM2.5 is one of the major air pollutants in Kathmandu Valley, and its emission and the unique atmospheric condition of the valley make it significantly hazardous to human health. The air pollution due to particulate matter is a major health issue with numerous negative impacts on us. This research aims to quantify the health impacts of PM2.5 exposure on the population of Kathmandu Valley. The ambient PM2.5 concentration of Kathmandu Valley was simulated using WRF-Chem model by using a horizontal grid resolution of 3 × 3 km. The concentration obtained from WRF-Chem was used as input in the health equation of an intervention model to quantify the health impacts. This quantitative assessment of atmospheric pollution was applied to evaluate the human exposure to PM2.5 in Kathmandu Valley. PM2.5 concentration and its distribution in the valley along with the ward-wise population distribution were used to find the health impact of the particulate matter in December 2019 in Kathmandu Valley. Exposure analysis using the model showed that 19 people could die due to lung cancer and 175 people could die due to all cause diseases except accidents due to PM2.5 exposure in December 2019. It was estimated that the reduction in the PM2.5 level by half in the valley reduces the monthly mortality by 51.4%. Hence, the exposure analysis of the particulate matter on the urban population could be improved by using air quality models in order to solve the health problems arising from air pollution.

Sifting and fluidization segregation characteristics were determined for 6 different fly ash samples (particle size 'd50' ranging from 68 µm to 141 µm) using standard testers. The results have shown that the coarser particles have a greater tendency to sifting segregation, and the finer powders respond more to fluidization segregation. The angle of repose for the fine ash and coarse ash were 55° and 38°, respectively, which indicated poor to good flowability conditions. The flow function test shows that all the samples were in an easy-flowing to a free-flowing zone. The angle of repose and material flow function have provided a good correlation with the sifting segregation index. In contrast, cohesion between particles, the ratio of free terminal velocities and diameters for coarse to fine particles have shown a good fit with fluidization segregation indices. For both sifting and fluidization segregation, the model correlation values are 0.91 and 0.94, indicating the predicted results are a good fit to the experimental data. [ABSTRACT FROM AUTHOR]

Physical and flow property tests were carried out on eight pharmaceutical powders. The results obtained from heap analysis and shear cell testing have been compared. A relationship to represent the static angle of repose has been developed using a bulk powder-based Froude number and fine size. The experimental results and predictions for a range of bulk properties have shown that the values of static angle of repose decrease with an increase in the value of bulk powder Froude number, increase in particle shape factor and decrease in the median to fine ratio. Out of all the dimensionless parameter groupings, the particle shape factor strongly influences the static angle of repose, as indicated by its larger absolute value of the exponent in the power function format relationship. The relationship can be used as a techno-economic optimization tool for particle processing/synthesis while maintaining the desired powder flowability. [ABSTRACT FROM AUTHOR]

Food security is one of the burning issues in the 21st century, as a tremendous population growth over recent decades has increased demand for food production systems. However, agricultural production is constrained by the limited availability of arable land resources, whereas a significant part of these is already degraded due to overexploitation. In order to get optimum output from the available land resources, it is of prime importance that crops are monitored, analyzed, and mapped at various stages of growth so that the areas having underdeveloped/unhealthy plants can be treated appropriately as and when required. This type of monitoring can be performed using ultra-high-resolution earth observation data like the images captured through unmanned aerial vehicles (UAVs)/drones. The objective of this research is to estimate and analyze the above-ground biomass (AGB) of the wheat crop using a consumer-grade red-green-blue (RGB) camera mounted on a drone. AGB and yield of wheat were estimated from linear regression models involving plant height obtained from crop surface models (CSMs) derived from the images captured by the drone-mounted camera. This study estimated plant height in an integrated setting of UAV-derived images with a Mid-Western Terai topographic setting (67 to 300 m amsl) of Nepal. Plant height estimated from the drone images had an error of 5% to 11.9% with respect to direct field measurement. While R2 of 0.66 was found for AGB, that of 0.73 and 0.70 were found for spike and grain weights respectively. This statistical quality assurance contributes to crop yield estimation, and hence to develop efficient food security strategies using earth observation and geo-information.

The objective of this experiment was to determine the best possible input EEG feature for classification of the workload while designing load balancing logic for an automated operator. The input features compared in this study consisted of spectral features of Electroencephalography, objective scoring and subjective scoring. Method utilizes to identify best EEG feature as an input in Neural Network Classifiers for workload classification, to identify channels which could provide classification with the highest accuracy and for identification of EEG feature which could give discrimination among workload level without adding any classifiers. The result had shown Engagement Index is the best feature for neural network classification.

The cognitive signal processing is one of the important interdisciplinary field came from areas of life sciences, psychology, psychiatry, engi-neering, mathematics, physics, statistics and many other fields of research. Neurophysiologic tests are utilized to assess and treat brain injury, dementia, neurological conditions, and useful to investigate psychological and psychiatric disorders. This paper presents an ongoing research work on development of EEG interface device based on the principles of cognitive assessments and instrumentation. The method proposed engineering and science of cogni-tive signal processing in case of brain computer in-terface based neurophysiologic tests. The future scope of this study is to build a low cost EEG device for various clinical and pre-clinical applications with specific emphasis to measure the effect of cognitive action on human brain.

Nepal has approximately 1000 operational brick kilns, which contribute significantly to ambient air pollution. They also account for 1.81% of the total bricks produced in the South Asian region. Little is known about their emissions, which are consequently not represented in regional/global emission inventories. This study compared emissions from seven brick kilns. Four were Fixed Chimney Bull’s Trench Kilns (FCBTKs) and three were Induced-Draught Zigzag Kilns (IDZKs). The concentrations of carbon dioxide (CO2), sulfur dioxide (SO2), black carbon (BC), and particulate matter (PM) with a diameter less than 2.5 µm (PM2.5) were measured. The respective emission factors (EFs) were estimated using the carbon mass balance method. The average fuel-based EF for CO2, SO2, PM2.5, and BC were estimated as 1633 ± 134, 22 ± 22, 3.8 ± 2.6 and 0.6 ± 0.2 g per kg, respectively, for all FCBTKs. Those for IDZKs were 1981 ± 232, 24 ± 22, 3.1 ± 1, and 0.4 ± 0.2 g per kg, respectively. Overall, the study found that converting the technology from straight-line kilns to zigzag kilns can reduce PM2.5 emissions by ~20% and BC emissions by ~30%, based on emission factor estimates of per kilogram of fuel. While considering per kilogram of fired brick, emission reductions were approximately 40% for PM2.5 and 55% for BC, but this definitely depends on proper stacking and firing procedures.

This study utilized the Weather Research and Forecasting (WRF) model version 3.5.1 to evaluate the impact of urbanization on summertime precipitation in Osaka, Japan. The evaluation was conducted by comparing the WRF simulations with the present land use and no-urban land use (replacing “Urban” with “Paddy”) for August from 2006 to 2010. The urbanization increased mean air temperature by 2.1°C in urban areas because of increased sensible heat flux and decreased mean humidity by 0.8 g kg−1 because of decreased latent heat flux. In addition, the urbanization increased duration of the southwesterly sea breeze. The urbanization increased precipitation in urban areas and decreased in the surrounding areas. The mean precipitation in urban areas was increased by 20 mm month−1 (27% of the total amount without the synoptic-scale precipitation). The precipitation increase was generally due to the enhancement of the formation and development of convective clouds by the increase in sensible heat flux during afternoon and evening time periods. The urbanization in Osaka changes spatial and temporal distribution patterns of precipitation and evaporation, and consequently it substantially affects the water cycle in and around the urban areas of Osaka.

A horizontal double-tube counter-flow heat exchanger with and without twisted tape inserts (twist ratio of 3.2, 4, and 6) has been investigated experimentally using TiO2-H2O nanofluid. In this study, the heat transfer coefficient and friction factor of turbulent flow of TiO2-H2O nanofluid have been determined for Reynolds' number varying from 5,000 to 25,000. Convective heat transfer coefficient for TiO2-H2O nanofluid (0.05% by vol.) is found to be higher than base fluid (4–6%). Also, an increase in the heat transfer coefficients up to 6%, 10.9%, 17.4%, and 23.4% are observed numerically for the 0.05%, 1%, 2%, and 3% volume concertation of nanoparticles of TiO2. On the other hand, when TiO2-H2O nanofluid (0.05% by vol.) is investigated using twisted tape inserts of twist ratio 3.2, the heat transfer coefficient is found to be increasing by 45%. The variation of the heat transfer coefficient for different types of nanofluids such as; TiO2-H2O, Al2O3-H2O, and CuO-H2O with 1% concentration of nanoparticles (by vol.) has also been studied at different Reynolds' numbers. The simulated results show no significant effect of the size (30 nm and 50 nm) of nanoparticles (TiO2) on the heat transfer coefficient values of TiO2-H2O nanofluid at 0.05% volume concentration. [ABSTRACT FROM AUTHOR]