Search results for: Bigul Pokharel

Authors: K. C. Apil, Keshab Sharma, Bigul Pokharel

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Kathmandu Valley, capital city of Nepal houses numerous historical monuments as well as religious structures which are as old as from the 4th century A.D. The city alone is home to seven UNESCO’s world heritage sites including various public squares and religious sanctums which are often regarded as living heritages by various historians and archeological explorers. Recently on April 25, 2015, the capital city including other nearby locations was struck with Gorkha earthquake of moment magnitude (Mw) 7.8, followed by the strongest aftershock of moment magnitude (Mw) 7.3 on May 12. This study reports structural failures and collapse of heritage structures in Kathmandu Valley during the earthquake and presents preliminary findings as to the causes of failures and collapses. Field reconnaissance was carried immediately after the main shock and the aftershock, in major heritage sites: UNESCO world heritage sites, a number of temples and historic buildings in Kathmandu Durbar Square, Patan Durbar Square, and Bhaktapur Durbar Square. Despite such catastrophe, a significant number of heritage structures stood high, performing very well during the earthquake. Preliminary reports from archeological department suggest that 721 of such structures were severely affected, whereas numbers within the valley only were 444 including 76 structures which were completely collapsed. This study presents recorded accelerograms and geology of Kathmandu Valley. Structural typology and architecture of the heritage structures in Kathmandu Valley are briefly described. Case histories of damaged heritage structures, the patterns, and the failure mechanisms are also discussed in this paper. It was observed that performance of heritage structures was influenced by the multiple factors such as structural and architecture typology, configuration, and structural deficiency, local ground site effects and ground motion characteristics, age and maintenance level, material quality etc. Most of such heritage structures are of masonry type using bricks and earth-mortar as a bonding agent. The walls' resistance is mainly compressive, thus capable of withstanding vertical static gravitational load but not horizontal dynamic seismic load. There was no definitive pattern of damage to heritage structures as most of them behaved as a composite structure. Some structures were extensively damaged in some locations, while structures with similar configuration at nearby location had little or no damage. Out of major heritage structures, Dome, Pagoda (2, 3 or 5 tiered temples) and Shikhara structures were studied with similar variables. Studying varying degrees of damages in such structures, it was found that Shikhara structures were most vulnerable one where Dome structures were found to be the most stable one, followed by Pagoda structures. The seismic performance of the masonry-timber and stone masonry structures were slightly better than that of the masonry structures. Regular maintenance and periodic seismic retrofitting seems to have played pivotal role in strengthening seismic performance of the structure. The study also recommends some key functions to strengthen the seismic performance of such structures through study based on structural analysis, building material behavior and retrofitting details. The result also recognises the importance of documentation of traditional knowledge and its revised transformation in modern technology.

Keywords: Gorkha earthquake, field observation, heritage structure, seismic performance, masonry building

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Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

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Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

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Authors: A. Pokharel, A. Farooque, B. Acharya

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Pyrolysis can be used for energy production from waste biomass of agriculture and forestry. Biochar is the solid byproduct of pyrolysis and its cascading use can offset the cost of the process. A wide variety of research on biochar has highlighted its ability to absorb nutrients, metal and complex compounds; filter suspended solids; enhance microorganisms’ growth; retain water and nutrients as well as to increase carbon content of soil. In addition, sustainable biochar systems are an attractive approach for carbon sequestration and total waste management cycle. Commercially available biochar from Sigma Aldrich was studied for adsorption of nitrogen from effluent of municipal wastewater treatment plant. Adsorption isotherm and breakthrough curve were determined for the biochar. Similarly, biochar’s effects in aerobic as well as anaerobic bioreactors were also studied. In both cases, the biomass was increased in presence of biochar. The amount of gas produced for anaerobic digestion of fruit mix (apple and banana) was similar but the rate of production was significantly faster in biochar fed reactors. The cumulative goal of the study is to use biochar in various wastewater treatment units like aeration tank, secondary clarifier and tertiary nutrient recovery system as well as in anaerobic digestion of the sludge to optimize utilization and add value before being used as a soil amendment.

Keywords: biochar, nutrient recyling, wastewater treatment, soil amendment

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Liping Wu, Durga Bhakta Pokharel, Junhua Dong, Changgang Wang, Lin Zhao, Wei Ke, Nan Chen

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Hazenite conversion coating was deposited on AZ31 Mg alloy in a deaerated phosphate solution containing 0.1 M K₂HPO₄ and 0.1 M Na₂HPO₄ (Na₀.₁K0₀.₁) with pH 9 at −0.8 V. The coating mechanism of hazenite was elucidated by in situ potentiostatic current decay, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), electron probe micro-analyzer (EPMA) and differential scanning calorimetry (DSC). The volume of H₂ evolved during potentiostatic polarization was measured by a gas collection apparatus. The degradation resistance of the hazenite coating was evaluated in simulated body fluid (SBF) at 37℃ by using potentiodynamic polarization (PDP). The results showed that amorphous Mg(OH)₂ was deposited first, followed by the transformation of Mg(OH)₂ to amorphous MgHPO₄, subsequently the conversion of MgHPO₄ to crystallized K-struvite (KMgPO₄·6H₂O), finally the crystallization of crystallized hazenite (NaKMg₂(PO₄)₂·14H₂O). The deposited coating was composed of four layers where the inner layer is comprised of Mg(OH)₂, the middle layer of Mg(OH)₂ and MgHPO₄, the top layer of Mg(OH)₂, MgHPO₄ and K-struvite, the topmost layer of Mg(OH)₂, MgHPO₄, K-struvite and hazenite (NaKMg₂(PO₄)₂·14H₂O). The PD results showed that the hazenite coating decreased the corrosion rate by two orders of magnitude.

Keywords: magnesium alloy, potentiostatic technique, hazenite, mineral conversion coating

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Authors: Asish Subedi, Krishna Pokharel, Birendra Prasad Sah, Pashupati Chaudhary

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Objectives: To evaluate an association between preoperative Nepali pain catastrophizing scale (N-PCS) scores and postoperative pain intensity and total opioid consumption. Methods: In this prospective cohort study we enrolled 135 patients with an American Society of Anaesthesiologists physical status I or II, aged between 18 and 65 years, and scheduled for surgery for lower-extremity fracture under spinal anaesthesia. Maximum postoperative pain reported during the 24 h was classified into two groups, no-mild pain group (Numeric rating scale [NRS] scores 1 to 3) and a moderate-severe pain group (NRS 4-10). The Spearman correlation coefficient was used to compare the association between the baseline N-PCS scores and outcome variables, i.e., the maximum NRS pain score and the total tramadol consumption within the first 24 h after surgery. Logistic regression models were used to identify the predictors for the intensity of postoperative pain. Results: As four patients violated the protocol, the data of 131 patients were analysed. Mean N-PCS scores reported by the moderate-severe pain group was 27.39 ±9.50 compared to 18.64 ±10 mean N-PCS scores by the no-mild pain group (p<0.001). Preoperative PCS scores correlated positively with postoperative pain intensity (r =0.39, [95% CI 0.23-0.52], p<0.001) and total tramadol consumption (r =0.32, [95% CI 0.16-0.47], p<0.001). An increase in catastrophizing scores was associated with postoperative moderate-severe pain (odds ratio, 1.08 [95% confidence interval, 1.02-1.15], p=0.006) after adjusting for gender, ethnicity and preoperative anxiety. Conclusion: Patients who reported higher pain catastrophizing preoperatively were at increased risk of experiencing moderate-severe postoperative pain.

Keywords: nepali, pain catastrophizing, postoperative pain, trauma

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Authors: Neeta Pokharel

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Cultural beliefs and practices have been shaping indigenous community’s resource use and attitude toward the conservation of natural flora and fauna around them. Understanding these cultural dimensions is vital for identifying effective strategies that align with conservation efforts. This study focused on investigating the wildlife-related cultural beliefs and practices of two indigenous communities: Bote and Musahars. The study applied ethnographic methods that included Key-informant interviews, Focal Group discussion, and Household survey methods. Out of 100 respondents, 51% were male and 49% female. A significant portion (65%) of the respondents confirmed animal worship, with a majority worshipping tigers (81.5%), rhinos (73.8%), crocodiles (66%), and dolphins (40%). Additionally, 16.9% disclosed worshipping Elephants, while 10 % affirmed animal worship without specifying the particular animals. Ritualistic practices often involve the sacrifice of pigs, goats, hens, and pigeons. Their cultural ethics place a significant emphasis on biodiversity conservation, as the result shows 41 % refraining from causing harm to wild animals and 9% doing so for ethical considerations, respectively. Moreover, the majority of the respondents believe that cultural practices could enhance conservation efforts. However, the encroachment of modernization and religious conversion within the community poses a tangible risk of cultural degradation, highlighting the urgent need to preserve the cultural practices. Integrating such indigenous practices into the National Biodiversity Strategy and conservation policies can ensure sustainable conservation of endangered animals with appropriate cultural safeguards.

Keywords: tribal communities, societal belief, wild fauna, “barana”, safeguarding

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Authors: Binaya Tamang, Buddhi R. Pokharel, Narayan Gautam, Puspa R. Dhakal, Yuresh Twayana

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Background and Objective: Microalbuminuria is often regarded as a sign of end-organ damage due to hypertension, with an increased risk for renal diseases. The present study was designed to find the prevalence of microalbuminuria in hypertensive patients by determining albumin creatinine ratio (ACR) and the association of ACR and microalbuminuria status with different stages and duration of hypertension (HTN). Also, to establish the correlation of systolic and diastolic blood pressure (SBP and DBP) with various parameters viz; ACR, urinary microalbumin (UMA), estimated glomerular filtration rate (eGFR), urinary creatinine (Ucreat), serum creatinine (Screat), and find out their significance among HTN and ACR status. Materials and Methods: A hospital-based cross-sectional study was conducted in the Department of Biochemistry in collaboration with the Department of Internal Medicine, UCMS, Bhairahawa, Nepal from April 2019 to September 2019 after obtaining ethical approval from institutional review committee (IRC), UCMS. A total of 120 hypertensive patients were enrolled whose blood, and spot urine samples were taken. eGFR was calculated by using Cockcroft-Gault formula after determining Screat while ACR was calculated after measuring Ucreat and UMA from the spot urine sample. Creatinine was estimated from modified jaffes’ reaction, whereas urinary micro albumin was done by Mispa i3 analyzer. Data were analyzed by using SPSS. 20 using p-value ≤ 0.05 as statistically significant. Results: In our study, the highest enrolled were grade II HTN (36.7%) followed by normal (33.3%), grade I (20.8%) and grade III (9.2%). Evaluating the ACR status, 19.2% were microalbuminuria, and the rest were normal. Though the ACR status (normal and microalbuminuria) was not statistically significant with HTN status (P=0.860) and the duration of HTN status (P=0.165), 5 (45.5%) out of 11 grade III HTN were microalbuminuria and the prevalence was also higher for longer duration .i.e., more than 10 years. In microalbuminuria, both the SBP (p=0.023, r=0.471) and DBP (P=0.034, r= 0.444) were strongly and positively correlated with Screat, in contrast to eGFR, which was negatively but weakly correlated. With the significant difference between the HTN group, the mean ACR (P=0.047) and UMA (P=0.02) were found to be highest among grade III patients, i.e., 84.3 ± 113.3 mg/gm. and 88.4 ± 83.9 mg/l respectively. The mean eGFR (64.2 ± 24.8 vs 77.2 ± 18.1 ml/min) was considerably lower in microalbuminuria ( p=0.026) than the normal in contrast to the SBP (160 ± 33.7 vs. 146.6 ± 19.5 mm of Hg) which was significantly higher (P=0.008). Among the different BMI category, the mean ACR was found to be significantly different (P= 0.01) with the highest value in underweight (115.2 ± 51.5 mg/gm.) and lowest in overweight (31.8 ± 4.3 mg/gm.). Conclusion: The study recommends that the microalbuminuria can be a very useful and imperative predictor of deranged kidney functions in hypertensive patients. The high value of ACR and UMA in hypertensive patients along with significant increased Screat, SBP whereas decreased eGFR in microalbuminuria patients explicitly supports the above statement.

Keywords: albumin creatinine ratio, hypertension, microalbuminuria, renal disease

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Authors: Pratima Pokharel

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When sewer overflow due to rainfall in urban areas, this leads to public health risks when an individual is exposed to that contaminated floodwater. Nevertheless, it is still unclear the extent to which the infections pose a risk to public health. This study analyzed reported diarrheal cases by month and age in Bangkok, Thailand. The results showed that the cases are reported higher in the wet season than in the dry season. It was also found that in Bangkok, the probability of infection with diarrheal diseases in the wet season is higher for the age group between 15 to 44. However, the probability of infection is highest for kids under 5 years, but they are not influenced by wet weather. Further, this study introduced a vulnerability that leads to health risks from urban flooding. This study has found some vulnerability variables that contribute to health risks from flooding. Thus, for vulnerability analysis, the study has chosen two variables, economic status, and age, that contribute to health risk. Assuming that the people's economic status depends on the types of houses they are living in, the study shows the spatial distribution of economic status in the vulnerability maps. The vulnerability map result shows that people living in Sukhumvit have low vulnerability to health risks with respect to the types of houses they are living in. In addition, from age the probability of infection of diarrhea was analyzed. Moreover, a field survey was carried out to validate the vulnerability of people. It showed that health vulnerability depends on economic status, income level, and education. The result depicts that people with low income and poor living conditions are more vulnerable to health risks. Further, the study also carried out 1D Hydrodynamic Advection-Dispersion modelling with 2-year rainfall events to simulate the dispersion of fecal coliform concentration in the drainage network as well as 1D/2D Hydrodynamic model to simulate the overland flow. The 1D result represents higher concentrations for dry weather flows and a large dilution of concentration on the commencement of a rainfall event, resulting in a drop of the concentration due to runoff generated after rainfall, whereas the model produced flood depth, flood duration, and fecal coliform concentration maps, which were transferred to ArcGIS to produce hazard and risk maps. In addition, the study also simulates the 5-year and 10-year rainfall simulations to show the variation in health hazards and risks. It was found that even though the hazard coverage is very high with a 10-year rainfall events among three rainfall events, the risk was observed to be the same with a 5-year and 10-year rainfall events.

Keywords: urban flooding, risk, hazard, vulnerability, health risk, framework

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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