401 results on '"Ghimire, A."'
Search Results
2. 5G Network Deployment Planning Using Metaheuristic Approaches.
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Sapkota, Binod, Ghimire, Rijan, Pujara, Paras, Ghimire, Shashank, Shrestha, Ujjwal, Ghimire, Roshani, Dawadi, Babu R., and Joshi, Shashidhar R.
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PARTICLE swarm optimization ,GREY Wolf Optimizer algorithm ,RADIO access networks ,NETWORK performance ,SIMULATED annealing - Abstract
The present research focuses on optimizing 5G base station deployment and visualization, addressing the escalating demands for high data rates and low latency. The study compares the effectiveness of Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Grey Wolf Optimizer (GWO) in both Urban Macro (UMa) and Remote Macro (RMa) deployment scenarios that overcome the limitations of the current method of 5G deployment, which involves adopting Non-Standalone (NSA) architecture. Emphasizing population density, the optimization process eliminates redundant base stations for enhanced efficiency. Results indicate that PSO and GA strike the optimal balance between coverage and capacity, offering valuable insights for efficient network planning. The study includes a comparison of 28 GHz and 3.6 GHz carrier frequencies for UMa, highlighting their respective efficiencies. Additionally, the research proposes a 2.6 GHz carrier frequency for Remote Macro Antenna (RMa) deployment, enhancing 5G Multi-Tier Radio Access Network (RAN) planning and providing practical solutions for achieving infrastructure reduction and improved network performance in a specific geographical context. [ABSTRACT FROM AUTHOR]
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- 2024
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3. Spatial Sediment Erosion and Yield Using RUSLE Coupled with Distributed SDR Model.
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Ghimire, Sanyam, Singh, Umesh, Panthi, Krishna Kanta, and Bhattarai, Pawan Kumar
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UNIVERSAL soil loss equation ,RIVER sediments ,SOIL erosion ,WATERSHEDS ,WATER supply - Abstract
Estimating sediment yield in a river is a challenging task in the water resources field. Different methods are available for estimating sediment erosion and yield, but generally they are not spatially distributed in nature. This paper presents the application of the Revised Universal Soil Loss Equation (RUSLE) for estimating soil erosion and integrates it with spatially distributed Sediment Delivery Ratio (SDR) to calculate sediment yield in a Himalayan river. The study area is Kabeli sub-catchment, located upstream of the Koshi River Basin in the eastern part of Nepal. The Kabeli River is where numerous hydropower projects are envisaged, and sediment-related issues are of major concern. With the use of the RUSLE, the mean annual soil erosion is estimated at 35.96 tons/ha/yr. The estimated specific sediment yield (SSY) from the distributed SDR method is 6.74 tons/ha/yr, which is close to the observed SSY of 7.26 tons/ha/yr using the data records of ~8 years. Based on correlation analysis, the topographic factor ( L S ) is the most sensitive RUSLE parameter with respect to sediment erosion. The sloping areas near the river hillslope are particularly vulnerable to soil erosion. The results indicate that the approach employed in this study may be potentially applied in other catchments with similar physiographic characteristics for the estimation of sediment yield. [ABSTRACT FROM AUTHOR]
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- 2024
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4. Pilot Evaluation of Field Pea Accessions Under Water Deficit Conditions.
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Vinarao, Grace B., Ghimire, Krishna, and Harris, Donna K.
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CLIMATE extremes , *SUSTAINABLE agriculture , *LEGUMES , *CLIMATE change , *WATER purification - Abstract
Field pea, a key pulse crop for sustainable agriculture, faces significant production challenges due to drought, exacerbated by extreme climatic changes. This study evaluated 17 field pea plant introductions (PIs) and two commercial varieties under greenhouse conditions to assess their performance, determine the relationships between agronomic traits and grain yield (GY), and identify genotypes with stable yields under drought stress. Two water treatments were applied: 100% field capacity for well-watered (WW) and 60% field capacity for water deficit (WD) conditions, with drought stress imposed 21 days after planting. Significant genotypic variation was observed under both conditions. Water deficit significantly reduced GY, the number of pods per plant (NPP), plant height (PH), aboveground dry vegetative biomass (ADVB), and days to maturity (DTM) while increasing stomatal density on both adaxial (SD.ADX) and abaxial leaf surfaces (SD.ABX). Traits associated with GY in WW, such as NPP, PH, ADVB, and SD.ADX, showed stronger correlations under WD, with DTM being significantly associated with GY only in WD. Top-performing genotypes in both conditions exhibited higher pod numbers, increased aboveground dry vegetative biomass, late maturity, and lower adaxial stomatal density. Notably, PI 272215 was identified as a top performer under both conditions, with an 88% yield stability index. PI 180702 demonstrated comparable performance to PI 272215 but with no yield loss under the same conditions. These findings can be used for future field pea breeding programs aimed at developing drought-tolerant field pea varieties. [ABSTRACT FROM AUTHOR]
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- 2024
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5. Ubiquitin Ligase U-Box51 Positively Regulates Drought Stress in Potato (Solanum tuberosum L.).
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Wei, Meng, Ghimire, Shantwana, Rijal, Anuja, Wang, Kaitong, Zhang, Huanhuan, Si, Huaijun, and Tang, Xun
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The ubiquitin-proteasome system (UPS) is a key protein degradation pathway in eukaryotes, in which E3 ubiquitin ligases mediate protein ubiquitination, directly or indirectly targeting substrate proteins to regulate various biological processes, including plant growth, hormone signaling, immune responses, and adaptation to abiotic stress. In this study, we identified plant U-box protein 51 in Solanum tuberosum (StPUB51) as an E3 ubiquitin ligase through transcriptomic analysis, and used it as a candidate gene for gene-function analysis. Quantitative real-time PCR (qRT-PCR) was used to examine StPUB51 expression across different tissues, and its expression patterns under simulated drought stress induced by polyethylene glycol (PEG 6000) were assessed. Transgenic plants overexpressing StPUB51 and plants with down-regulated StPUB51 expression were generated to evaluate drought tolerance. The activities of key antioxidant enzymes-superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) as well as malondialdehyde (MDA) content in transgenic plants' leaves were measured under drought conditions. Protein–protein interactions involving StPUB51 were explored via yeast two-hybrid (Y2H) screening, with interaction verification by bimolecular fluorescence complementation (BiFC). StPUB51 was predominantly expressed in stems, with lower expression observed in tubers, and its expression was significantly upregulated in response to 20% PEG-6000 simulated drought. Subcellular localization assays revealed nuclear localization of the StPUB51 protein. Under drought stress, StPUB51-overexpressing plants exhibited enhanced SOD, POD, and CAT activities and reduced MDA levels, in contrast to plants with suppressed StPUB51 expression. Y2H and BiFC analyses identified two interacting proteins, StSKP2A and StGATA1, which may be functionally linked to StPUB51. Collectively, these findings suggest that StPUB51 plays a positive regulatory role in drought tolerance, enhancing resilience in potato growth and stress adaptation. [ABSTRACT FROM AUTHOR]
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- 2024
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6. Multi-Objective Framework for Resilient Post-Disaster Self-Built Residential Buildings.
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Ghimire, Prashnna, Paneru, Suman, Pokharel, Sudan, Kandel, Ayushma, Ehlert, Rick, and Burke, Kyle
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STONEMASONRY ,RURAL housing ,FINITE element method ,BUILDING design & construction ,SOCIOECONOMIC factors ,EARTHQUAKE resistant design - Abstract
Highlights: This study introduced a five-stage multi-objective framework for developing earthquake-resilient residential buildings. Proposed gabion building technology, G-2.1, contributes to multi-objective aspects including architectural, structural, and socio-economic aspects. The locally sourced materials and craftsmanship ensures affordability and encourages knowledge transfer. The 2015 seismic events in Nepal highlighted critical challenges in constructing earthquake-resilient, self-built stone masonry houses in rural mountain areas. The Department of Urban Development and Building Construction (DUDBC), however, provided designs that failed to preserve the local architectural landscape and craftsmanship while adding unfamiliar knowledge and technology. To address the shortcomings of DUDBC model houses related to architecture, structure, and socio-economic concerns in designing and implementing post-earthquake houses, a need-based building development framework is required for standardized practice. This study proposes a novel framework to assess, design, and implement a self-built house after a disaster, consisting of five stages: (1) post-disaster problem assessment, (2) need identification, (3) material selection, (4) design development, and (5) validation and implementation. Based on this framework, we proposed a novel gabion building construction technology for two-story stone masonry structures that effectively mitigate post-disaster challenges such as logistic, resilience, and socio-economic aspects while improving disaster resiliency specifically in the high-elevation rural areas of Nepal. The proposed two-story gabion building preserves local architectural values, enhances structural integrity, and provides cost-effectiveness when compared with its DUDBC peer models while providing much-needed relief to the vulnerable community. The proposed resilient house, G-2.1, utilizes locally sourced materials and craftsmanship, and innovative gabion technology that ensures affordability and facilitates knowledge transfer. The contribution of this study includes a multi-objective framework for a two-story gabions house that is most suitable for self-built resilient homes that preserves the local architecture and socio-economic conditions while providing structural integrity and safety. [ABSTRACT FROM AUTHOR]
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- 2024
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7. Flight Altitude and Sensor Angle Affect Unmanned Aerial System Cotton Plant Height Assessments.
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Adedeji, Oluwatola, Abdalla, Alwaseela, Ghimire, Bishnu, Ritchie, Glen, and Guo, Wenxuan
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- 2024
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8. Transcranial Magnetic Stimulation–Electroencephalography (TMS-EEG) in Neurosurgery: Unexplored Path Towards Personalized Brain Surgery.
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Oliveira, Martim, Ribeiro, Sofia, Baig Mirza, Asfand, Vastani, Amisha, Díaz-Baamonde, Alba, Tanaka, Masumi, Elhag, Ali, Marchi, Francesco, Ghimire, Prajwal, Fayez, Feras, Patel, Sabina, Gullan, Richard, Bhangoo, Ranjeev, Ashkan, Keyoumars, Vergani, Francesco, Mirallave-Pescador, Ana, and Lavrador, José Pedro
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TRANSCRANIAL magnetic stimulation ,BRAIN surgery ,EPILEPSY surgery ,PEOPLE with epilepsy ,DATA extraction - Abstract
Background: Transcranial Magnetic Stimulation–Electroencephalography (TMS-EEG) is a non-operative technique that allows for magnetic cortical stimulation (TMS) and analysis of the electrical currents generated in the brain (EEG). Despite the regular utilization of both techniques independently, little is known about the potential impact of their combination in neurosurgical practice. Methods: This scoping review, conducted following PRISMA guidelines, focused on TMS-EEG in epilepsy, neuro-oncology, and general neurosurgery. A literature search in Embase and Ovid MEDLINE returned 3596 records, which were screened based on predefined inclusion and exclusion criteria. After full-text review, three studies met the inclusion criteria. Two independent investigators conducted study selection and data extraction, with mediators resolving disagreements. The NHLBI tool was used to assess risk of bias in the included studies. Results: A total of 3596 articles were screened following the above-mentioned criteria: two articles and one abstract met the inclusion criteria. TMS-EEG is mentioned as a promising tool to evaluate tumor–brain interaction, improve preoperative speech mapping, and for lateralization epileptic focus in patients undergoing epilepsy surgery. Lack of detailed patient and outcome information preclude further considerations about TMS-EEG use beyond the potential applications of this technique. Conclusions: TMS-EEG research in neurosurgery is required to establish the role of this non-invasive brain stimulation-recording technique. Tumor–brain interaction, preoperative mapping, and seizure lateralization are in the front row for its future applications. [ABSTRACT FROM AUTHOR]
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- 2024
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9. Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System.
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Ghimire, Amrit Babu, Magar, Binod Ale, Parajuli, Utsav, and Shin, Sangmin
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MISSING data (Statistics) ,WATER distribution ,MUNICIPAL water supply ,REGRESSION trees ,REGRESSION analysis ,MULTIPLE imputation (Statistics) - Abstract
Resilience-based decision-making for urban water distribution systems (WDSs) is a challenge when WDS sensing data contain incomplete or missing values. This study investigated the impact of missing data imputation on a WDS resilience evaluation depending on missing data percentages. Incomplete datasets for the nodal pressure of the C-town WDS were developed with 10%, 30%, and 50% missing data percentages by manipulating a true dataset for normal operation conditions produced using EPANET. This study employed multiple imputation methods including classification and regression trees, predictive mean matching, linear regression regarding model error, and linear regression using projected values. Then, resilience values were evaluated and compared using unimputed and imputed datasets. An analysis of performance indicators based on NRMSE, NMAE, NR-Square, and N-PBIAS revealed that higher missing-data percentages led to increased deviation between the true and imputed datasets. The resilience evaluation using unimputed datasets produced significant deviations from the true resilience values, which tended to increase as the missing data percentages increased. However, the imputed datasets substantially contributed to reducing the deviations. These findings underscore the contributions of data imputation to enhancing resilience evaluation in WDS decision-making and suggest insights into advancing a resilience evaluation framework for urban WDSs with more reliable data imputation approaches. [ABSTRACT FROM AUTHOR]
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- 2024
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10. Impact of the Quadriceps Angle on Health and Injury Risk in Female Athletes.
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Gant, Hannah, Ghimire, Nabin, Min, Kisuk, Musa, Ibrahim, Ashraf, Maryam, and Lawan, Ahmed
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- 2024
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11. Differential TLR-ERK1/2 Activity Promotes Viral ssRNA and dsRNA Mimic-Induced Dysregulated Immunity in Macrophages.
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Shrestha, Rakshya, Johnson, Paige Marie, Ghimire, Roshan, Whitley, Cody John, and Channappanavar, Rudragouda
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NF-kappa B ,MITOGEN-activated protein kinases ,TOLL-like receptors ,CELL membranes ,IMMUNE response - Abstract
RNA virus-induced excessive inflammation and impaired antiviral interferon (IFN-I) responses are associated with severe disease. This innate immune response, also referred to as "dysregulated immunity" is caused by viral single-stranded RNA (ssRNA)- and double-stranded-RNA (dsRNA)-mediated exuberant inflammation and viral protein-induced IFN antagonism. However, key host factors and the underlying mechanism driving viral RNA-mediated dysregulated immunity are poorly defined. Here, using viral ssRNA and dsRNA mimics, which activate toll-like receptor 7 (TLR7) and TLR3, respectively, we evaluated the role of viral RNAs in causing dysregulated immunity. We observed that murine bone marrow-derived macrophages (BMDMs), when stimulated with TLR3 and TLR7 agonists, induced differential inflammatory and antiviral cytokine response. TLR7 activation triggered a robust inflammatory cytokine/chemokine induction compared to TLR3 activation, whereas TLR3 stimulation induced significantly increased IFN/IFN stimulated gene (ISG) response relative to TLR7 activation. To define the mechanistic basis for dysregulated immunity, we examined cell-surface and endosomal TLR levels and downstream mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-kB) activation. We identified significantly higher cell-surface and endosomal TLR7 levels compared to TLR3, which were associated with early and robust MAPK (p-ERK1/2, p-P38, and p-JNK) and NF-kB activation in TLR7-stimulated macrophages. Furthermore, blocking EKR1/2 and NF-kB activity reduced TLR3/7-induced inflammatory cytokine/chemokine levels, whereas only ERK1/2 inhibition enhanced viral RNA mimic-induced IFN/ISG responses. Collectively, our results illustrate that high cell-surface and endosomal TLR7 expression and robust ERK1/2 activation drive viral ssRNA mimic-induced excessive inflammatory and reduced IFN/ISG response and blocking ERK1/2 activity would likely mitigate viral-RNA/TLR-induced dysregulated immunity. [ABSTRACT FROM AUTHOR]
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- 2024
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12. Designing and Evaluating Games for Landslides, Earthquakes, and Fires: Lesson Learned from Schools in Nepal.
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Marahatta, Deepak, Ghimire, Jiwnath, and Poplin, Alenka
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The Himalayan country of Nepal is vulnerable to landslides, earthquakes, and fires. Its inhabitants need to be empowered on how to react in emergencies to prevent fatalities and respond to crises efficiently while promoting longer-term sustainability and resilience. This research project, a collaborative effort involving teachers, students, and researchers, highlights the design and implementation of games for disaster risk reduction tested in remote schools. Three interactive games were developed using an iterative game design process and testing in workshops aiming to ensure the inclusivity and diversity of the project. The games targeted preparedness and response to landslides, earthquakes, and house fires. The outcome has proven that the game-based approach to teaching and learning is crucial in empowering underserved school children often left out in formal and informal disaster management processes. This study has shown that game-based learning of disaster preparedness and response effectively empowers resource-deficient communities and regions of the Global South. [ABSTRACT FROM AUTHOR]
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- 2024
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13. Population Pharmacokinetic Model of Vitamin D 3 and Metabolites in Chronic Kidney Disease Patients with Vitamin D Insufficiency and Deficiency.
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Tuey, Stacey M., Ghimire, Avisek, Guzy, Serge, Prebehalla, Linda, Roque, Amandla-Atilano, Roda, Gavriel, West 3rd, Raymond E., Chonchol, Michel B., Shah, Nirav, Nolin, Thomas D., and Joy, Melanie S.
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CHOLECALCIFEROL , *VITAMIN D deficiency , *CHRONIC kidney failure , *CHRONICALLY ill , *VITAMIN D - Abstract
Vitamin D insufficiency and deficiency are highly prevalent in patients with chronic kidney disease (CKD), and their pharmacokinetics are not well described. The primary study objective was to develop a population pharmacokinetic model of oral cholecalciferol (VitD3) and its three major metabolites, 25-hydroxyvitamin D3 (25D3), 1,25-dihydroxyvitamin D3 (1,25D3), and 24,25-dihydroxyvitamin D3 (24,25D3), in CKD patients with vitamin D insufficiency and deficiency. CKD subjects (n = 29) were administered one dose of oral VitD3 (5000 I.U.), and nonlinear mixed effects modeling was used to describe the pharmacokinetics of VitD3 and its metabolites. The simultaneous fit of a two-compartment model for VitD3 and a one-compartment model for each metabolite represented the observed data. A proportional error model explained the residual variability for each compound. No assessed covariate significantly affected the pharmacokinetics of VitD3 and metabolites. Visual predictive plots demonstrated the adequate fit of the pharmacokinetic data of VitD3 and metabolites. This is the first reported population pharmacokinetic modeling of VitD3 and metabolites and has the potential to inform targeted dose individualization strategies for therapy in the CKD population. Based on the simulation, doses of 600 International Unit (I.U.)/day to 1000 I.U./day for 6 months are recommended to obtain the target 25D3 concentration of between 30 and 60 ng/mL. These simulation findings could potentially contribute to the development of personalized dosage regimens for vitamin D treatment in patients with CKD. [ABSTRACT FROM AUTHOR]
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- 2024
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14. Forecasting Multi-Step Soil Moisture with Three-Phase Hybrid Wavelet-Least Absolute Shrinkage Selection Operator-Long Short-Term Memory Network (moDWT-Lasso-LSTM) Model.
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Jayasinghe, W. J. M. Lakmini Prarthana, Deo, Ravinesh C., Raj, Nawin, Ghimire, Sujan, Yaseen, Zaher Mundher, Nguyen-Huy, Thong, and Ghahramani, Afshin
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MACHINE learning ,ARTIFICIAL intelligence ,DISCRETE wavelet transforms ,FEATURE selection ,INDEPENDENT variables ,DEEP learning - Abstract
To develop agricultural risk management strategies, the early identification of water deficits during the growing cycle is critical. This research proposes a deep learning hybrid approach for multi-step soil moisture forecasting in the Bundaberg region in Queensland, Australia, with predictions made for 1-day, 14-day, and 30-day, intervals. The model integrates Geospatial Interactive Online Visualization and Analysis Infrastructure (Giovanni) satellite data with ground observations. Due to the periodicity, transience, and trends in soil moisture of the top layer, time series datasets were complex. Hence, the Maximum Overlap Discrete Wavelet Transform (moDWT) method was adopted for data decomposition to identify the best correlated wavelet and scaling coefficients of the predictor variables with the target top layer moisture. The proposed 3-phase hybrid moDWT-Lasso-LSTM model used the Least Absolute Shrinkage and Selection Operator (Lasso) method for feature selection. Optimal hyperparameters were identified using the Hyperopt algorithm with deep learning LSTM method. This proposed model's performances were compared with benchmarked machine learning (ML) models. In total, nine models were developed, including three standalone models (e.g., LSTM), three integrated feature selection models (e.g., Lasso-LSTM), and three hybrid models incorporating wavelet decomposition and feature selection (e.g., moDWT-Lasso-LSTM). Compared to alternative models, the hybrid deep moDWT-Lasso-LSTM produced the superior predictive model across statistical performance metrics. For example, at 1-day forecast, The moDWT-Lasso-LSTM model exhibits the highest accuracy with the highest R 2 ≈ 0.92469 and the lowest RMSE ≈ 0.97808 , MAE ≈ 0.76623 , and SMAPE ≈ 4.39700 %, outperforming other models. The moDWT-Lasso-DNN model follows closely, while the Lasso-ANN and Lasso-DNN models show lower accuracy with higher RMSE and MAE values. The ANN and DNN models have the lowest performance, with higher error metrics and lower R2 values compared to the deep learning models incorporating moDWT and Lasso techniques. This research emphasizes the utility of the advanced complementary ML model, such as the developed moDWT-Lasso-LSTM 3-phase hybrid model, as a robust data-driven tool for early forecasting of soil moisture. [ABSTRACT FROM AUTHOR]
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- 2024
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15. Exploring the Role of Dietary Calcium Intake in Muscle and Cardiovascular Performance Among Young Athletes.
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Sharma Ghimire, Pragya, Ding, Xiyan, and Eckart, Adam
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DIETARY calcium ,FOOD consumption ,BODY composition ,LACROSSE players ,BONE metabolism ,PEARSON correlation (Statistics) - Abstract
The importance of dietary calcium intake in bone metabolism has been well established; however, it is still less investigated in health-related components, especially addressing muscle performance. This study aims to compare dietary calcium intake and its relationship with cardiovascular and muscular performance in young athletes (Lacrosse, Baseball, and soccer players). In this cross-sectional study, 95 participants (ages 18 to 30) participated during two visits to the Human Performance Laboratory. Participants completed body composition, lower and upper body muscle performance, cardiorespiratory protocol, and questionnaires related to dietary calcium intake. One-way ANOVA was used to determine the difference in the calcium intake between groups. The Pearson Correlation Coefficient was used to investigate the relationship between dietary calcium intake and muscle performance variables. Further, linear regression was used to assess the predictive value of calcium variables on overall muscle performance. Lacrosse players had significantly higher calcium intake than Baseball and soccer players (p < 0.05). There was a significant positive correlation between dietary calcium intake and the number of push-ups (r = 0.28; p = 0.03). CIBW and CI explained 4.3% and nearly 25% of the change in MPI, respectively (p < 0.001). This suggests the possible role of dietary calcium intake in enhancing health-related fitness components and highlights the need to explore its involvement in muscle-bone crosstalk. [ABSTRACT FROM AUTHOR]
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- 2024
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16. Evaluating the Photocatalytic Activity of Green Synthesized Iron Oxide Nanoparticles.
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Khadka, Devendra, Gautam, Prayas, Dahal, Rabin, Ashie, Moses D., Paudyal, Hari, Ghimire, Kedar Nath, Pant, Bishweshwar, Poudel, Bhoj Raj, Bastakoti, Bishnu Prasad, and Pokhrel, Megh Raj
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ENERGY dispersive X-ray spectroscopy ,IRON oxide nanoparticles ,FOURIER transform infrared spectroscopy ,ENVIRONMENTAL remediation ,ULTRAVIOLET-visible spectroscopy ,METHYLENE blue ,IRRADIATION - Abstract
Water pollution from dyes is a major environmental challenge, demanding advanced materials for efficient degradation. In this study, we synthesized iron oxide nanoparticles (IONPs) using an aqueous extract of Senegalia catechu leaves and evaluated their photocatalytic activity in methylene blue (MB) dye degradation under sunlight irradiation. The IONPs were characterized by UV-visible spectroscopy (UV–vis), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-ray Spectroscopy (EDS). XRD pattern showed a highly crystalline structure with an average crystallite size of 34.7 nm, while SEM images revealed predominantly spherical particles with uneven surface texture. Photocatalytic efficiency exceeded 80% MB dye degradation after 120 min of sunlight exposure. Optimization of catalyst dose, pH, dye concentration, and other parameters is essential for maximizing degradation efficiency. The IONPs demonstrated reusability over four degradation cycles, retaining effective photocatalytic performance. This study underscores the potential of green-synthesized IONPs as eco-friendly photocatalysts for wastewater treatment and environmental remediation. [ABSTRACT FROM AUTHOR]
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- 2024
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17. Prevalence of Antimicrobial Resistant Escherichia coli from Sinking Creek in Northeast Tennessee.
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Alali, Walid Q., Scheuerman, Phillip, McClure, Clara, Ghimire, Achala, Owusu-Mensah, Priscilla, Schultz, Jacob, and Joyner, Timothy Andrew
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- 2024
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18. Introductory Physics Students Who Typically Worked Alone or in Groups: Insights from Gender-Based Analysis Before and During COVID-19.
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Ghimire, Apekshya and Singh, Chandralekha
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COVID-19 pandemic ,PEER pressure ,PHYSICS students ,GENDER mainstreaming ,SELF-efficacy ,PROBLEM solving - Abstract
Collaboration with peers both inside and outside the classroom can be an invaluable tool for helping students learn physics. We investigated the impact of peer collaboration on learning physics by examining the characteristics of women and men who typically worked alone versus those who typically collaborated with peers in their algebra-based introductory physics course when they took the course before and during the COVID-19 pandemic when the classes were on Zoom. Our findings indicate that, on average, students who worked with peers had higher grades and reported greater peer influence on their physics self-efficacy during the pandemic compared to those who worked alone. We also observed that, for both women and men, a larger percentage of students typically worked in groups before the pandemic, while a greater percentage typically worked alone during the pandemic. We discuss these results in relation to students' prior academic preparation, physics grades, self-efficacy and their perception of the effectiveness of peer collaboration on their physics self-efficacy. [ABSTRACT FROM AUTHOR]
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- 2024
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19. Assessing Biofungicides and Host Resistance against Rhizoctonia Large Patch in Zoysiagrass.
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Ghimire, Bikash, Orellana, Rolando, Chowdhury, Shukti R., Vermeer, Christopher Brian, Patel, Paige, Raymer, Paul, Milla-Lewis, Susana, Buck, James W., Martinez-Espinoza, Alfredo D., and Bahri, Bochra A.
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BIOFUNGICIDES ,PROPICONAZOLE ,DISEASE resistance of plants ,FUNGICIDES ,BACILLUS subtilis ,RHIZOCTONIA solani - Abstract
Rhizoctonia large patch (Rhizoctonia solani AG2-2 LP) significantly reduces turfgrass quality, aesthetics, and playability. Synthetic fungicides are commonly used for managing this disease, but they present high costs, potential for fungicide resistance, and environmental concerns. We conducted in vitro assays to test the effectiveness of three biofungicides, seven synthetic fungicides, and ten combinations against R. solani. We then assessed seven spray programs that included Bacillus subtilis QST713 and propiconazole, either alone or tank-mixed, on zoysiagrass 'El Toro' in a growth chamber and in field trials. Biofungicide B. subtilis QST713 reduced pathogen growth by up to 100% in vitro. B. subtilis QST713 alone or combined with synthetic fungicides and/or in rotation was as effective as the standalone synthetic fungicide, reducing disease severity and AUDPC by 81 and 77% (growth chamber) and by 71 and 52% (field), respectively, while maintaining acceptable turfgrass quality. Additionally, we screened zoysiagrass genotypes and advanced breeding lines against three R. solani isolates in growth chamber studies. Five genotypes and two breeding lines demonstrated resistance to Rhizoctonia large patch across isolates, highlighting their potential for developing disease-resistant cultivars. Our findings suggest that integrating biofungicides, resistant cultivars with chemical controls offer sustainable and effective strategies for managing Rhizoctonia large patch [ABSTRACT FROM AUTHOR]
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- 2024
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20. Anthrax in Humans, Animals, and the Environment and the One Health Strategies for Anthrax Control.
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Subedi, Deepak, Pantha, Saurav, Jyoti, Sumit, Gautam, Bickal, Kaphle, Krishna, Yadav, Rakesh Kumar, Ghimire, Shristi, and Dhakal, Santosh
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ANTHRAX ,BACILLUS anthracis ,BACTERIAL spores ,BIOLOGICAL weapons ,INFECTIOUS disease transmission - Abstract
Anthrax is a notorious disease of public health importance caused by Bacillus anthracis. The causative agent can also be used as a biological weapon. Spores of these bacteria can sustain extreme environmental conditions and remain viable in soil for decades. Domestic and wild ruminants are highly susceptible to this pathogen, which usually presents as a peracute to acute disease. In humans, cutaneous anthrax is frequent but pulmonary and enteric anthrax are more serious. Humans, animals, and the environment are all involved, making anthrax a perfect target for a One Health approach. The environment plays a key role in disease transmission. At a time when the One Health concept is not mere slogans, collaborative efforts of medical professionals, veterinarians, and environmental scientists will be valuable for the prevention and control of this disease. In this review, we discussed the transmission dynamics of anthrax in the environment, animals, and humans, as well as One Health strategies to control and prevent anthrax. [ABSTRACT FROM AUTHOR]
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- 2024
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21. A Parallel Approach to Enhance the Performance of Supervised Machine Learning Realized in a Multicore Environment.
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Ghimire, Ashutosh and Amsaad, Fathi
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MACHINE learning ,SUPERVISED learning ,CREDIT card fraud ,PARALLEL processing ,IMAGE recognition (Computer vision) - Abstract
Machine learning models play a critical role in applications such as image recognition, natural language processing, and medical diagnosis, where accuracy and efficiency are paramount. As datasets grow in complexity, so too do the computational demands of classification techniques. Previous research has achieved high accuracy but required significant computational time. This paper proposes a parallel architecture for Ensemble Machine Learning Models, harnessing multicore CPUs to expedite performance. The primary objective is to enhance machine learning efficiency without compromising accuracy through parallel computing. This study focuses on benchmark ensemble models including Random Forest, XGBoost, ADABoost, and K Nearest Neighbors. These models are applied to tasks such as wine quality classification and fraud detection in credit card transactions. The results demonstrate that, compared to single-core processing, machine learning tasks run 1.7 times and 3.8 times faster for small and large datasets on quad-core CPUs, respectively. [ABSTRACT FROM AUTHOR]
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- 2024
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22. Prevalence of Perinatal Depression and Its Associated Risk Factors among Nepalese Women in Kathmandu, Nepal.
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Wasti, Pratikshya, Panta, Prem Prasad, Gc, Vijay S., Ghimire, Biwash, Sapkota, Pooja, and Wasti, Sharada Prasad
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MENTAL depression risk factors ,RISK assessment ,CROSS-sectional method ,POISSON distribution ,MATERNAL health services ,INTIMATE partner violence ,INTERVIEWING ,NEPALI people ,DISEASE prevalence ,DESCRIPTIVE statistics ,TERTIARY care ,AGE distribution ,SURVEYS ,RACE ,WOMEN'S health ,CONFIDENCE intervals ,FAMILY support ,PREGNANCY complications ,COUNSELING ,SOCIAL support ,MENTAL depression ,PERINATAL period ,REGRESSION analysis - Abstract
Perinatal mental health is a major public health issue that arises during pregnancy and/or after birth, with substantial implications for social, parental, and maternal functioning, as well as overall quality of life. The study aimed to determine the prevalence of perinatal depression and its associated risk factors among women who visited a maternity hospital in Kathmandu, Nepal. A cross-sectional study was conducted at the Paropakar Maternity and Women's Hospital in Kathmandu. A total of 300 women in their perinatal period were interviewed. The Edinburgh Perinatal Depression Scale (EPDS) was used to measure perinatal depression. The Poisson regression model was used to determine risk factors associated with perinatal depression. The mean age of respondents was 25.5 (SD 4.5) years; average age during their first pregnancy was 23.5 (SD 3.7) years; and 53.7% of respondents were in the antenatal period. The prevalence of depressive symptoms (EPDS ≥ 10) was 40% (95% CI 31.4% to 45.8%). Unsupportive family members (adjusted prevalence ratio [aPR] 2.23; 95% CI 1.75–2.86), postnatal period (aPR 2.64; 95% CI 1.97–3.53), complications faced during delivery (aPR 1.76; 95%CI 1.30–2.39), history of intimate partner violence (aPR 0.48; 95% CI 0.36–0.64), and first pregnancy at the age of ≤25 years (aPR 0.61; 95% CI 0.42–0.88) were identified as key risk factors of perinatal depression. Strong family support and the active involvement of partners in counselling can contribute to alleviating perinatal depression symptoms. Targeted interventions in health and well-being services should be implemented to address mental health burden during both pregnancy and postpartum periods. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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23. Machine Learning-Based Weld Classification for Quality Monitoring
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Ghimire, Rojan, primary and Selvam, Rajiv, additional
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- 2024
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24. Pulmonary Actinomycosis in a 65-Year-Old Female with Poor Oral Dentition.
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Yi, Sha, Ghimire, Rabindra, Sporn, Thomas A., Sutton, Ann T., Lebron Figueroa, Dora A., and Markantonis, John E.
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ADULT respiratory distress syndrome , *ACTINOMYCOSIS , *TREATMENT delay (Medicine) , *PLEURAL effusions , *ACTINOMYCES - Abstract
Pulmonary actinomycosis is an uncommon clinical entity that can be challenging to diagnose due to its non-specific symptomatology. Misdiagnosis and delayed treatment may result in invasive procedures and extended antimicrobial treatment courses. We report a case involving a 65-year-old female with poor oral dentition admitted for acute respiratory failure subsequently found to have a left-sided pleural effusion and perihepatic abscess formation. Cytopathology examination and microbiology studies confirmed the diagnosis of pulmonary actinomycosis. [ABSTRACT FROM AUTHOR]
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- 2024
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25. Association between Salt-Related Knowledge, Attitudes, and Behaviours and 24 h Urinary Salt Excretion in Nepal.
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Ghimire, Kamal, Mishra, Shiva Raj, Neupane, Dinesh, Kallestrup, Per, and McLachlan, Craig S.
- Abstract
This study examined the association between salt-related knowledge, attitudes, and behaviors (KAB) and salt excretion using the 24-hour (24 h) urinary collection method. Data were utilized from the Community-Based Management of Non-Communicable Diseases in Nepal (COBIN) Salt Survey, a community-based cross-sectional study conducted among a sub-sample of COBIN cohort in Pokhara Metropolitan City, Western Nepal, from July to December 2018, among adults aged 25–70 years. A total of 451 adults participated in the study, and a single 24 h urine sample was collected from each participant. The mean [(standard deviation (SD)] age of the participants was 49.6 (9.82) years, and the majority were female (65%). The mean urinary salt excretion was 13.28 (SD: 4.72) g/day, with 98% of participants consuming ≥5 g of salt/day. Although 83% of participants knew the risks of high salt intake and 87% believed it was important to reduce their intake, only 10% reported doing so. Salt-related attitude i.e., self-perceived salt intake was significantly associated with urinary salt excretion, adding extra salt to food, consuming processed foods, and taking actions to salt control. Participants who perceived themselves as consuming high salt had higher urinary salt excretion [(14.42 g/day; 95% confidence interval (95% CI): 13.45, 15.39, p = 0.03)], were more likely to add extra [(Odds ratio (OR) = 3.59; 95% CI: 2.03, 6.33, p < 0.001)], and consume processed foods more often (OR = 1.90; 95% CI: 1.06, 3.40, p < 0.05) compared to those who self-perceived consuming a normal amount of salt. Conversely, participants who perceived themselves as consuming low salt were more likely to take actions to control salt intake (OR = 4.22; 95% CI: 1.90, 9.37, p < 0.001) compared to their counterparts who perceived consuming a normal amount of salt. There existed a gap between salt-related knowledge, attitudes, and actual behaviors, resulting in a high salt intake among the Nepalese population. Nepal urgently requires tailored national salt reduction programs that comprise both policy and community-level interventions to achieve a 30% reduction in mean population salt intake by 2025. Further validation studies are needed to assess the effectiveness of community-based intervention in Nepal. [ABSTRACT FROM AUTHOR]
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- 2024
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26. Copula-Probabilistic Flood Risk Analysis with an Hourly Flood Monitoring Index.
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Chand, Ravinesh, Nguyen-Huy, Thong, Deo, Ravinesh C., Ghimire, Sujan, Ali, Mumtaz, and Ghahramani, Afshin
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FLOOD risk ,FLOOD warning systems ,RISK assessment ,RAINFALL ,FLOODS ,NATURAL disasters - Abstract
Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak, and accumulated rainfall-based damage is likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index ( S W R I 24 − h r − S ) derived from normalising the existing 24-hourly water resources index ( W R I 24 − h r − S ) in the literature to monitor flood risk on an hourly scale. The proposed S W R I 24 − h r − S is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V), and peak (Q). The comprehensive result analysis establishes the practical utility of S W R I 24 − h r − S in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji's study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak, and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data are available, offering crucial information for flood risk monitoring and assessment and for the development of effective mitigation strategies. [ABSTRACT FROM AUTHOR]
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- 2024
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27. Evaluating Community Forest User Groups (CFUGs)' Performance in Managing Community Forests: A Case Study in Central Nepal.
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Dhungana, Nabin, Lee, Chun-Hung, Khadka, Chiranjeewee, Adhikari, Samjhana, Pudasaini, Nabaraj, and Ghimire, Pramod
- Abstract
The community forests (CF) in Nepal, facilitated by Community Forest User Groups (CFUGs), is widely recognized as an effective model of community-based forest management. Despite this recognition, there is a notable lack of comprehensive studies assessing the performance of CFUGs in sustaining community forests. Addressing this gap, this study examined twenty-two indicators across five performance criteria, such as user group management, forest management, financial management, livelihood management, and collaboration and networking management, within four CFUGs in central Nepal. Data were collected through household surveys (n = 275) and focus group discussions (n = 4), and indicators of performance criteria were assessed using a Likert scale. Reliability was measured using the coefficient of Cronbach's alpha. ANOVA was employed to compare mean performance criteria across the four CFUGs, providing an evaluative perspective on overall CFUG performance. The findings underscored collaboration and networking management as high performers, showing an index value of 0.71, while user group management exhibited moderate performance with an index value of 0.56, alongside other moderately performing criteria. Noteworthy disparities were evident across the four performance criteria (p < 0.01), with the exception of collaboration and network management. Approximately 55% of the indicators were rated low to moderate, revealing CFUGs' deficiencies in regular functions, limited uptake of adaptive and market-oriented management practices, minimal contributions to biodiversity conservation, insufficient capacity for forest revenue generation and mobilization, and restricted income generation and benefit-sharing with communities. The absence of timely and pertinent actions further stifled interaction between CFUGs and community forests, undermining the potential for revenue generation, job creation, and collective actions essential for productive community forest management. Prioritization of the indicators based on the performance index value offers critical policy direction to ensure CFUG sustainability and augment participatory management of common pool resources. Strategies to address identified weaknesses and build on strengths are essential for the success of Nepal's community forests. [ABSTRACT FROM AUTHOR]
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- 2024
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28. Estimating Lung Volume Capacity from X-ray Images Using Deep Learning.
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Ghimire, Samip and Subedi, Santosh
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- 2024
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29. Chitosan-GSNO Nanoparticles and Silicon Priming Enhance the Germination and Seedling Growth of Soybean (Glycine max L.).
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Steven, Senabulya, Islam, Mohammad Shafiqul, Ghimire, Amit, Methela, Nusrat Jahan, Kwon, Eun-Hae, Yun, Byung-Wook, Lee, In-Jung, Kim, Seong-Hoon, and Kim, Yoonha
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GERMINATION ,GENE expression ,SEEDLINGS ,NANOPARTICLES ,ABSCISIC acid ,SOYBEAN ,SOYBEAN farming ,PLANT hormones - Abstract
Soybean, a major legume crop, has seen a decline in its production owing to challenges in seed germination and the development of seedlings. Thus, in this study, we systematically investigated the influence of various chitosan–S-nitrosoglutathione (chitosan-GSNO) nanoparticle (0, 25, 50, and 100 µM) and Si (0, 0.5, and 1 mM) priming concentrations on soybean seed germination and seedling growth over five different priming durations (range: 1–5 h at each concentration). Significant differences were observed in all parameters, except seedling diameter, with both treatments. Seed germination was significantly enhanced after 3 h of priming in both treatments. The final germination percentage (FGP), peak germination percentage (PGP), vigor index (VI), seedling biomass (SB), hypocotyl length (HL), and radical length (RL) of 100 μM chitosan-GSNO-nanoparticle-primed seeds increased by 20.3%, 41.3%, 78.9%, 25.2%, 15.7%, and 65.9%, respectively, compared with those of the control; however, the mean germination time (MGT) decreased by 18.43%. Si priming at 0.5 mM increased the FGP, PGP, VI, SB, HL, and RL by 13.9%, 55.17%, 39.2%, 6.5%, 22.5%, and 25.1%, respectively, but reduced the MGT by 12.29% compared with the control treatment. Chitosan-GSNO and Si treatment up-regulated the relative expression of gibberellic acid (GA)-related genes (GmGA3ox3 and GmGA2ox1) and down-regulated that of abscisic acid (ABA)-related genes (GmABA2, GmAAO3, and GmNCED5). Chitosan-GSNO and Si application increased bioactive GA
4 levels and simultaneously reduced ABA content. Hence, the use of exogenous chitosan-GSNO nanoparticles and Si as priming agents had a beneficial effect on seed germination and seedling growth because of the up-regulation in the expression of GA and down-regulation in the expression of ABA. Additional research is needed to understand the combined impact of Si and chitosan-GSNO nanoparticles, including their effects on the expression levels of other hormones and genes even in the later growth stage of the crop. [ABSTRACT FROM AUTHOR]- Published
- 2024
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30. Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data.
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Islam, Mohammad Shafiqul, Ghimire, Amit, Lay, Liny, Khan, Waleed, Lee, Jeong-Dong, Song, Qijian, Jo, Hyun, and Kim, Yoonha
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- *
LOCUS (Genetics) , *LOCUS of control , *SOYBEAN , *RIBOSOMAL proteins , *SINGLE nucleotide polymorphisms , *PROTEIN kinases , *SOYBEAN diseases & pests - Abstract
Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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31. The Estimation of Shear Wave Velocity for Shallow Underground Structures in the Central Himalaya Region of Nepal.
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Thapa, Umesh Jung, Paudel, Satish, Bhusal, Umesh Chandra, Ghimire, Hari, and Khadka, Shyam Sundar
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UNDERGROUND construction ,SHEAR waves ,TUNNEL design & construction ,SANDY soils ,SOIL classification - Abstract
A subsurface investigation was conducted to assess the suitability of a site for potential tunnel construction, focusing on the determination of shear wave velocities (Vs) in subsurface materials. This study employed three distinct methods to analyze Vs in weathered soft rock: drilling mechanism, multichannel analysis of surface waves (MASW), and microtremor array measurement (MAM). Through the utilization of MASW and MAM, empirical relationships were established, enabling the determination of Vs based solely on soil type and depth, offering a practical alternative to the limitations of SPT N-Value, particularly when exceeding 50 blows. The comparison of Vs values obtained from these methods revealed a close alignment between empirical techniques and MASW/MAM, which proved to be cost-effective and an efficient alternative to drilling for comprehensive underground structure assessments. The reliability of MASW was further underscored through its comparison with existing empirical methods. Moreover, the empirical approach demonstrated its efficacy in predicting velocities in weathered soft rock within the Central Himalayan region of Nepal, thus enhancing the feasibility study of underground structures. Lastly, this study proposed a Vs-Depth correlation specifically tailored for highly weathered meta-sandstone bedrock resulting in clay and sandy soils. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
32. Predictive Validity of Multifactorial Injury Risk Models and Associated Clinical Measures in the U.S. Population.
- Author
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Eckart, Adam C., Ghimire, Pragya Sharma, and Stavitz, James
- Abstract
Background: Popular movement-based injury risk screens were shown to lack predictive precision, leading to interest in multifactorial models. Furthermore, there is a lack of research regarding injury risk assessment for those currently or planning to be recreationally active. This study aims to provide injury risk insights by analyzing multifactorial injury risk models and associated clinical measures in the U.S. population. Methods: Data related to injury, inflammatory markers, physical functioning, body composition, physical activity, and other variables from 21,033 respondents were extracted from NHANES. Odds ratios for self-reported injury were calculated for single predictors and risk models. Case–control and principal component analyses (PCA) were conducted to elucidate confounders and identify risk factor clusters, respectively. Receiver operating characteristic analysis was used to test the precision of a risk factor cluster to identify pain points and functional difficulties. Results: Sociodemographic, individual, and lifestyle factors were strongly associated with higher odds of injury. Increases in fibrinogen and C-reactive protein were significantly associated with all risk groups. Membership to the high-risk group (age over 40, obesity, no muscle-strengthening activities, sedentary lifestyle, and low back pain) predicted at least one functional difficulty with 67.4% sensitivity and 87.2% specificity. In the injury group, bone turnover markers were higher, yet confounded by age, and there was a significantly higher prevalence of self-reported osteoporosis compared to the control. In males, low testosterone was associated with injury, and high estradiol was associated with pain and functional difficulties. In females, high follicle-stimulating hormone was associated with functional difficulties. PCA revealed four high-risk profiles, with markers and activities showing distinct loadings. Conclusions: A comprehensive approach to injury risk assessment should consider the nexus of aging, lifestyle, and chronic disease to enhance tailored injury prevention strategies, fostering safe and effective physical activity participation and reducing the burden of musculoskeletal disorders. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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33. Design of an Ultrasound Sensing System for Estimation of the Porosity of Agricultural Soils.
- Author
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Bradley, Stuart and Ghimire, Chandra
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- *
SOIL porosity , *ULTRASONIC imaging , *ANIMAL tracks , *ACOUSTIC reflection , *POROUS materials - Abstract
The design of a readily useable technology for routine paddock-scale soil porosity estimation is described. The method is non-contact (proximal) and typically from "on-the-go" sensors mounted on a small farm vehicle around 1 m above the soil surface. This ultrasonic sensing method is unique in providing estimates of porosity by a non-invasive, cost-effective, and relatively simple method. Challenges arise from the need to have a compact low-power rigid structure and to allow for pasture cover and surface roughness. The high-frequency regime for acoustic reflections from a porous material is a function of the porosity ϕ, the tortuosity α∞, and the angle of incidence θ. There is no dependence on frequency, so measurements must be conducted at two or more angles of incidence θ to obtain two or more equations in the unknown soil properties ϕ and α∞. Sensing and correcting for scattering of ultrasound from a rough soil surface requires measurements at three or more angles of incidence. A system requiring a single transmitter/receiver pair to be moved from one angle to another is not viable for rapid sampling. Therefore, the design includes at least three transmitter/reflector pairs placed at identical distances from the ground so that they would respond identically to power reflected from a perfectly reflecting surface. A single 25 kHz frequency is a compromise which allows for the frequency-dependent signal loss from a natural rough agricultural soil surface. Multiple-transmitter and multiple-microphone arrays are described which give a good signal-to-noise ratio while maintaining a compact system design. The resulting arrays have a diameter of 100 mm. Pulsed ultrasound is used so that the reflected sound can be separated from sound travelling directly through the air horizontally from transmitter to receiver. The average porosity estimated for soil samples in the laboratory and in the field is found to be within around 0.04 of the porosity measured independently. This level of variation is consistent with uncertainties in setting the angle of incidence, although assumptions made in modelling the interaction of ultrasound with the rough surface no doubt also contribute. Although the method is applicable to all soil types, the current design has only been tested on dry, vegetation-free soils for which the sampled area does not contain large animal footprints or rocks. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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34. Suspended Sediment Source and Transport Mechanisms in a Himalayan River.
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Ghimire, Sanyam, Singh, Umesh, Panthi, Krishna Kanta, and Bhattarai, Pawan Kumar
- Subjects
SUSPENDED sediments ,RIVER sediments ,WATERSHEDS ,GROUNDWATER flow ,GROUNDWATER ,SEDIMENT transport - Abstract
The process of estimating sediment load has been a daunting issue in hydraulics and the water resource field. Several methods exist for predicting the sediment load in a catchment or river, but the majority of these methods are empirical and depend on the specific location where they are used. Understanding the underlying mechanism of sediment generation and its transport in connection with precipitation, topography, and subsurface conditions to characterize its process is helpful for determining the sediment load in a river. For this purpose, we analyzed the daily suspended sediment data measured for 8 years at the headworks of the Kabeli A hydropower project in the Kabeli River, which originates from the Himalayan region. The analyses show that the suspended sediment concentration (SSC) varies in an orderly manner over time and asynchronously between seasons with respect to the river discharge. Clockwise hysteresis is observed in the yearly plots between the SSC and river discharge. The hysteresis becomes narrower when compared with the direct runoff obtained from a digital filtering algorithm and, even more so with the direct runoff from the hydrological model SWAT. The analysis shows that the sediment concentration is controlled not only by the total discharge in the river but also by the contribution of ground water to the river discharge, indicating that the total discharge alone cannot reflect the seasonal variation in SSC. It is inferred that the river is supply-limited and the hillslope is transport-limited with respect to sediment sources. The SWAT model suggests that the base flow contribution to the total river discharge is 78%. Here, we present a method for constructing the suspended sediment rating curve by comparing the direct runoff with the sediment concentration. The deduced sediment rating curve captures 84.51% of the total sediment load over the study period in the Kabeli River. This method may potentially be used in similar catchments with supply-limited rivers and transport-limited hillslopes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
35. Divergent Nitrogen, Phosphorus, and Carbon Concentrations among Growth Forms, Plant Organs, and Soils across Three Different Desert Ecosystems.
- Author
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Khan, Alamgir, Liu, Xu-Dong, Waseem, Muhammad, Qi, Shi-Hua, Ghimire, Shantwana, Hasan, Md. Mahadi, and Fang, Xiang-Wen
- Subjects
DESERTS ,ECOSYSTEMS ,BOTANICAL chemistry ,SOIL chemistry ,PLANT physiology - Abstract
Quantifying the dryland patterns of plant carbon (C), nitrogen (N), and phosphorus (P) concentrations and their stoichiometric values along environmental gradients is crucial for understanding ecological strategies. To understand the plant adaptive strategies and ecosystem nutrient concentrations across three desert ecosystems (e.g., desert, steppe desert, and temperate desert), we compiled a dataset consisting of 1295 plant species across three desert ecosystems. We assessed the element concentrations and ratios across plant growth forms, plant organs, and soils and further analysed the leaf vs. root N, P, and N:P scaling relationships. We found that the leaf N, P, and C concentrations were significantly different only from those of certain other growth forms and in certain desert ecosystems, challenging the generality of such differences. In leaves, the C concentrations were always greater than the N and P concentrations and were greater than those in soils depending on the soil chemistry and plant physiology. Thus, the element concentrations and ratios were greater in the organs than in the soils. The values in the leaf versus the root N, P, and N:P scaling relationships differed across the three desert ecosystems; for example, αN (1.16) was greater in the desert, αP (1.10) was greater in the temperate desert ecosystem, and αN:P (2.11) was greater in the desert ecosystem. The mean annual precipitation (MAP) and mean annual temperature (MAT) did not have significant effects on the leaf elemental concentrations or ratios across the desert ecosystems. This study advances our understanding of plant growth forms and organs, which support resource-related adaptive strategies that maintain the stability of desert ecosystems via divergent element concentrations and environmental conditions. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
36. Assessing the Effectiveness of Regional Storm Surge Reduction Strategies and Tank Level Structural Mitigation Measures for Aboveground Storage Tanks.
- Author
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Ghimire, Santosh and Kameshwar, Sabarethinam
- Subjects
STORM surges ,MONTE Carlo method ,OIL spill cleanup ,STORAGE tanks ,OIL spill management ,SEA level - Abstract
The effectiveness of regional storm surge reduction strategies and tank-level structural mitigation measures in reducing the failure probability of aboveground storage tanks (ASTs) were studied. Given past failures during flood and hurricane events, several studies have developed fragility models for ASTs. However, the suitability of these fragility models for different hurricane hazard scenarios is unknown. Furthermore, to combat climate change and sea level rise, several regional storm surge reduction strategies are being proposed. However, the effectiveness of these strategies in improving the safety of ASTs is also unknown. So, herein, a framework was proposed that facilitates assessing the suitability of fragility models and the quantification of AST failures and their consequences while propagating uncertainties using Monte Carlo simulations. The application of the proposed framework to Cameron, Louisiana, provided several key insights: (1) fragility models that do not model wave loads and dislocation failure are not suitable for the region; (2) a regional risk mitigation strategy was insufficient for lowering future spill volume, repair, and cleanup costs; and (3) considering bottom-plate failure of anchored tanks—a structural risk mitigation measure—would lead to a 47–72% reduction in the consequences of tank failure. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
37. Differentiating Cell Entry Potentials of SARS-CoV-2 Omicron Subvariants on Human Lung Epithelium Cells.
- Author
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Katte, Revansiddha H., Ao, Yuanyun, Xu, Wang, Han, Yang, Zhong, Guohua, Ghimire, Dibya, Florence, Jon, Tucker, Torry A., and Lu, Maolin
- Subjects
SARS-CoV-2 Omicron variant ,LUNGS ,SARS-CoV-2 Delta variant ,SARS-CoV-2 ,EPITHELIUM ,MEMBRANE fusion - Abstract
The surface spike (S) glycoprotein mediates cell entry of SARS-CoV-2 into the host through fusion at the plasma membrane or endocytosis. Omicron lineages/sublineages have acquired extensive mutations in S to gain transmissibility advantages and altered antigenicity. The fusogenicity, antigenicity, and evasion of Omicron subvariants have been extensively investigated at unprecedented speed to align with the mutation rate of S. Cells that overexpress receptors/cofactors are mostly used as hosts to amplify infection sensitivity to tested variants. However, systematic cell entry comparisons of most prior dominant Omicron subvariants using human lung epithelium cells are yet to be well-studied. Here, with human bronchial epithelium BEAS-2B cells as the host, we compared single-round virus-to-cell entry and cell-to-cell fusion of Omicron BA.1, BA.5, BQ.1.1, CH.1.1, XBB.1.5, and XBB.1.16 based upon split NanoLuc fusion readout assays and the S-pseudotyped lentivirus system. Virus-to-cell entry of tested S variants exhibited cell-type dependence. The parental Omicron BA.1 required more time to develop full entry to HEK293T-ACE2-TMPRSS2 than BEAS-2B cells. Compared to unchanged P681, S-cleavage constructs of P681H/R did not have any noticeable advantages in cell entry. Omicron BA.1 and its descendants entered BEAS-2B cells more efficiently than D614G, and it was slightly less or comparable to that of Delta. Serine protease-pretreated Omicron subvariants enhanced virus-to-cell entry in a dose-dependent manner, suggesting fusion at the plasma membrane persists as a productive cell entry route. Spike-mediated cell-to-cell fusion and total S1/S2 processing of Omicron descendants were similar. Our results indicate no obvious entry or fusion advantages of recent Omicron descendants over preceding variants since Delta, thus supporting immune evasion conferred by antigenicity shifts due to altered S sequences as probably the primary viral fitness driver. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
38. Exploring Machine Learning for Predicting Cerebral Stroke: A Study in Discovery.
- Author
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Mia, Rajib, Khanam, Shapla, Mahjabeen, Amira, Ovy, Nazmul Hoque, Ghimire, Deepak, Park, Mi-Jin, Begum, Mst Ismat Ara, and Hosen, A. S. M. Sanwar
- Subjects
STROKE ,MACHINE learning ,K-nearest neighbor classification ,BLOOD flow ,RANDOM forest algorithms - Abstract
Cerebral strokes, the abrupt cessation of blood flow to the brain, lead to a cascade of events, resulting in cellular damage due to oxygen and nutrient deprivation. Contemporary lifestyle factors, including high glucose levels, heart disease, obesity, and diabetes, heighten the risk of stroke. This research investigates the application of robust machine learning (ML) algorithms, including logistic regression (LR), random forest (RF), and K-nearest neighbor (KNN), to the prediction of cerebral strokes. Stroke data is collected from Harvard Dataverse Repository. The data includes—clinical, physiological, behavioral, demographic, and historical data. The Synthetic Minority Oversampling Technique (SMOTE), adaptive synthetic sampling (ADASYN), and the Random Oversampling Technique (ROSE) are used to address class imbalances to improve the accuracy of minority classes. To address the challenge of forecasting strokes from partial and imbalanced physiological data, this study introduces a novel hybrid ML approach by combining a machine learning method with an oversampling technique called ADASYN_RF. ADASYN is an oversampling technique used to resample the imbalanced dataset then RF is implemented on the resampled dataset. Also, other oversampling techniques and ML models are implemented to compare the results. Notably, the RF algorithm paired with ADASYN achieves an exceptional performance of 99% detection accuracy, exhibiting its dominance in stroke prediction. The proposed approach enables cost-effective, precise stroke prediction, providing a valuable tool for clinical diagnosis. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
39. Impact of Land Use and Land Cover Change on Hydrological Processes in Urban Watersheds: Analysis and Forecasting for Flood Risk Management.
- Author
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Banjara, Mandip, Bhusal, Amrit, Ghimire, Amrit Babu, and Kalra, Ajay
- Subjects
LAND cover ,FLOOD risk ,URBAN watersheds ,FLOOD forecasting ,LAND use ,ZONING ,STREAMFLOW - Abstract
Land use and land cover (LULC) change is one of the primary contributors to hydrological change in urban watersheds and can potentially influence stream flow and flood volume. Understanding the impacts of LULC change on urban hydrological processes is critical to effective urban water management and minimizing flood risks. In this context, this study aims to determine the impacts of LULC change on hydrological response in a fast transitioning watershed for the predicted years of 2050 and 2080. This research employs the hybrid land use classification technique, Cellular Automata–Markov (CA–Markov) model to predict land use changes, utilizing land use data from 2001, 2013, and 2021. Additionally, it incorporates a calibrated, event-specific hydrologic model known as the Personal Computer Storm Water Management Model (PCSWMM) to assess alterations in hydrological responses for storm events of various magnitudes. The findings indicate a transition of the watershed into an urbanized landscape, replacing the previous dominance of agriculture and forested areas. The initial urban area, constituting 11.6% of the total area in 2021, expands to cover 34.1% and 44.2% of the total area by 2050 and 2080, respectively. Due to the LULC changes, there are increases in peak discharge of 5% and 6.8% and in runoff volume of 8% and 13.3% for the years 2050 and 2080 for a 100-year return period storm event. Yet, the extent of these changes intensifies notably during storm events with lower return periods. This heightened impact is directly attributed to the swift urbanization of the watershed. These results underscore the pressing necessity to regulate LULC change to preserve the hydrological equilibrium. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
40. Use of Artificial Intelligence in Design, Development, Additive Manufacturing, and Certification of Multifunctional Composites for Aircraft, Drones, and Spacecraft.
- Author
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Ghimire, Ritesh and Raji, Asokan
- Subjects
ARTIFICIAL intelligence ,SPACE vehicles ,DRONE aircraft ,FAILURE mode & effects analysis ,MACHINE learning ,CARBON composites ,ARTIFICIAL neural networks - Abstract
Multifunctional composites provide more than one function from the same part. The anisotropy, material, and process characterization challenges and the lack of standardization on the 3D-printed multifunctional carbon composites make it difficult for application into aerospace. The current solutions for additive manufacturing (AM) technologies and additively manufactured monofunctional and multifunctional composites are not mature enough for safety-critical applications. A new approach is proposed to explore the use of machine learning (ML) in the design, development, AM, testing, and certification of multifunctional composites for aircraft, unmanned aircraft systems (UAS), and spacecraft. In this work, an artificial neural network (ANN) architecture is proposed. An AM-embedded building block approach integrates the complete lifecycle of aircraft, UAS, and spacecraft using ANN to support the continued operational safety (COS) of aircraft, spacecraft, and UAS. The proposed method exploits the power of ANN on the metadata for the characterization of multifunctional material properties and processes and the mapping of the failure modes compared with the predicted models and history. This paper provides an in-depth analysis and explanation of the new methods needed to overcome the existing barriers, problems, and situations. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
41. Acellular Human Amniotic Fluid-Derived Extracellular Vesicles as Novel Anti-Inflammatory Therapeutics against SARS-CoV-2 Infection.
- Author
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Chanda, Debarati, Del Rivero, Tania, Ghimire, Roshan, More, Sunil, Mitrani, Maria Ines, Bellio, Michael A., and Channappanavar, Rudragouda
- Subjects
EXTRACELLULAR vesicles ,SARS-CoV-2 ,COVID-19 pandemic ,ADULT respiratory distress syndrome ,THERAPEUTICS - Abstract
The ongoing COVID-19 pandemic caused by SARS-CoV-2 is associated with acute respiratory distress syndrome (ARDS) and fatal pneumonia. Excessive inflammation caused by SARS-CoV-2 is the key driver of ARDS and lethal disease. Several FDA-approved drugs that suppress virus replication are in clinical use. However, despite strong evidence for the role of virus-induced inflammation in severe COVID-19, no effective anti-inflammatory drug is available to control fatal inflammation as well as efficiently clear the virus. Therefore, there is an urgent need to identify biologically derived immunomodulators that suppress inflammation and promote antiviral immunity. In this study, we evaluated acellular human amniotic fluid (acAF) containing extracellular vesicles (hAF-EVs) as a potential non-toxic and safe biologic for immunomodulation during COVID-19. Our in vitro results showed that acAF significantly reduced inflammatory cytokine production in TLR2/4/7 and SARS-CoV-2 structural protein-stimulated mouse macrophages. Importantly, an intraperitoneal administration of acAF reduced morbidity and mortality in SARS-CoV-2-infected mice. A detailed examination of SARS-CoV-2-infected lungs revealed that the increased protection in acAF-treated mice was associated with reduced viral titers and levels of inflammatory myeloid cell infiltration. Collectively, our results identify a novel biologic that has potential to suppress excessive inflammation and enhance survival following SARS-CoV-2 infection, highlighting the translational potential of acAF against COVID-19. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
42. Co-Circulation of Dengue Virus Serotypes 1, 2, and 3 during the 2022 Dengue Outbreak in Nepal: A Cross-Sectional Study
- Author
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Rimal, Sandesh, Shrestha, Sabin, Pandey, Kishor, Nguyen, Thanh Vu, Bhandari, Parmananda, Shah, Yogendra, Acharya, Dhiraj, Adhikari, Nabaraj, Rijal, Komal Raj, Ghimire, Prakash, Takamatsu, Yuki, Pandey, Basu Dev, Fernandez, Stefan, Morita, Kouichi, Ngwe Tun, Mya Myat, Dumre, Shyam Prakash, Rimal, Sandesh, Shrestha, Sabin, Pandey, Kishor, Nguyen, Thanh Vu, Bhandari, Parmananda, Shah, Yogendra, Acharya, Dhiraj, Adhikari, Nabaraj, Rijal, Komal Raj, Ghimire, Prakash, Takamatsu, Yuki, Pandey, Basu Dev, Fernandez, Stefan, Morita, Kouichi, Ngwe Tun, Mya Myat, and Dumre, Shyam Prakash
- Abstract
The largest dengue outbreak in the history of Nepal occurred in 2022, with a significant number of casualties. It affected all 77 districts, with the nation’s capital, Kathmandu (altitude 1300 m), being the hardest hit. However, the molecular epidemiology of this outbreak, including the dengue virus (DENV) serotype(s) responsible for this epidemic, remain unknown. Here, we report the epidemic trends, clinico-laboratory features, and virus serotypes and their viral load profiles that are associated with this outbreak in Nepal. Dengue-suspected febrile patients were investigated by routine laboratory, serological, and molecular tools, including a real-time quantitative polymerase chain reaction (qRT-PCR). Of the 538 dengue-suspected patients enrolled, 401 (74.5%) were diagnosed with dengue. Among these dengue cases, 129 (32.2%) patients who required hospital admission had significant associations with myalgia, rash, diarrhea, retro-orbital pain, bleeding, and abdominal pain. DENV-1, -2, and -3 were identified during the 2022 epidemic, with a predominance of DENV-1 (57.1%) and DENV-3 (32.1%), exhibiting a new serotype addition. We found that multiple serotypes circulated in 2022, with a higher frequency of hospitalizations, more severe dengue, and more deaths than in the past. Therefore, precise mapping of dengue and other related infections through integrated disease surveillance, evaluation of the dynamics of population-level immunity and virus evolution should be the urgent plans of action for evidence-based policy-making for dengue control and prevention in the country., Viruses, 15(2), art. no. 507; 2023
- Published
- 2023
43. Evaluation of Morpho-Physiological Traits of Oat (Avena sativa L.) under Drought Stress †.
- Author
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Ghimire, Krishna, McIntyre, Isabel, and Caffe, Melanie
- Subjects
OATS ,DROUGHTS ,GRAIN yields ,CLIMATE change ,PLANT yields ,DROUGHT tolerance - Abstract
The increase in intensity and frequency of drought due to global climate change has increased the urgency of developing crop cultivars suitable for dry environments. Drought tolerance is a complex trait that involves numerous physiological, biochemical, and morphological responses. A better understanding of those mechanisms is critical to develop drought tolerant cultivars. In this study, we aimed to understand the morphophysiological changes at the shoot and root levels in response to drought stress of ten oat genotypes with diverse root morphological characteristics. Twenty-one-day old plants were subjected to drought stress in a greenhouse by withholding water for two weeks. Several characteristics including chlorophyll content, relative water content (RWC), stomatal conductance, stomata number, shoot dry weight (SDW), root dry weight (RDW), root-to-shoot biomass ratio (RSR), root length, root area, and root volume were measured on well-watered, and drought-stressed plants. Grain yield was evaluated by continuing the drought treatment with a drying and rewatering cycle every 15 days until physiological maturity. The water regime had a significant impact on all traits evaluated. A significant interaction between genotype and water treatment was observed for RWC, chlorophyll content, stomatal conductance, stomata number, and grain yield but not for root traits, suggesting that the root system of all genotypes responded similarly to drought stress. Hayden, the cultivar with the lowest reduction in grain yield from the drought treatment, was among the genotypes with the lowest reduction in RWC and chlorophyll content but with a sharp decrease in stomata number, thus indicating that regulating the plant water status and maintaining the photosynthesis level are important for oat plants to maintain grain yield under drought stress. The size of the root system was not correlated with grain yield under drought, but the RWC and grain yield were significantly correlated under drought, thus suggesting that maintaining the RWC is an important characteristic for oat plants to maintain yield under drought stress. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
44. Elucidating the Role of Optical Activity of Polymers in Protein–Polymer Interactions.
- Author
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Jahan, Samin, Doyle, Catherine, Ghimire, Anupama, Combita, Diego, Rainey, Jan K., Wagner, Brian D., and Ahmed, Marya
- Subjects
POLYMERS ,OPTICAL rotation ,ACRYLAMIDE ,POLYZWITTERIONS ,PANTOTHENIC acid ,HYDROPHILIC interactions ,NUCLEAR magnetic resonance - Abstract
Proteins are biomolecules with potential applications in agriculture, food sciences, pharmaceutics, biotechnology, and drug delivery. Interactions of hydrophilic and biocompatible polymers with proteins may impart proteolytic stability, improving the therapeutic effects of biomolecules and also acting as excipients for the prolonged storage of proteins under harsh conditions. The interactions of hydrophilic and stealth polymers such as poly(ethylene glycol), poly(trehalose), and zwitterionic polymers with various proteins are well studied. This study evaluates the molecular interactions of hydrophilic and optically active poly(vitamin B5 analogous methacrylamide) (poly(B5AMA)) with model proteins by fluorescence spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and circular dichroism (CD) spectroscopy analysis. The optically active hydrophilic polymers prepared using chiral monomers of R-(+)- and S-(−)-B5AMA by the photo-iniferter reversible addition fragmentation chain transfer (RAFT) polymerization showed concentration-dependent weak interactions of the polymers with bovine serum albumin and lysozyme proteins. Poly(B5AMA) also exhibited a concentration-dependent protein stabilizing effect at elevated temperatures, and no effect of the stereoisomers of polymers on protein thermal stability was observed. NMR analysis, however, showed poly(B5AMA) stereoisomer-dependent changes in the secondary structure of proteins. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
45. Opportunities and Challenges of Generative AI in Construction Industry: Focusing on Adoption of Text-Based Models.
- Author
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Ghimire, Prashnna, Kim, Kyungki, and Acharya, Manoj
- Subjects
GENERATIVE artificial intelligence ,LANGUAGE models ,CONSTRUCTION industry ,ARTIFICIAL intelligence ,WORD frequency ,KNOWLEDGE gap theory - Abstract
In the last decade, despite rapid advancements in artificial intelligence (AI) transforming many industry practices, construction largely lags in adoption. Recently, the emergence and rapid adoption of advanced large language models (LLMs) like OpenAI's GPT, Google's PaLM, and Meta's Llama have shown great potential and sparked considerable global interest. However, the current surge lacks a study investigating the opportunities and challenges of implementing Generative AI (GenAI) in the construction sector, creating a critical knowledge gap for researchers and practitioners. This underlines the necessity to explore the prospects and complexities of GenAI integration. Bridging this gap is fundamental to optimizing GenAI's early stage adoption within the construction sector. Given GenAI's unprecedented capabilities to generate human-like content based on learning from existing content, we reflect on two guiding questions: What will the future bring for GenAI in the construction industry? What are the potential opportunities and challenges in implementing GenAI in the construction industry? This study delves into reflected perception in literature, analyzes the industry perception using programming-based word cloud and frequency analysis, and integrates authors' opinions to answer these questions. This paper recommends a conceptual GenAI implementation framework, provides practical recommendations, summarizes future research questions, and builds foundational literature to foster subsequent research expansion in GenAI within the construction and its allied architecture and engineering domains. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
46. Evaluating Non-Stationarity in Precipitation Intensity-Duration-Frequency Curves for the Dallas–Fort Worth Metroplex, Texas, USA.
- Author
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Ghimire, Binita, Kharel, Gehendra, Gebremichael, Esayas, and Cheng, Linyin
- Subjects
WATER management ,STANDARD deviations ,WATER resources development ,AKAIKE information criterion ,EMERGENCY management ,BIAS correction (Topology) - Abstract
Extreme precipitation has become more frequent and intense with time and space. Infrastructure design tools such as Intensity-Duration-Frequency (IDF) curves still rely on historical precipitation and stationary assumptions, risking current and future urban infrastructure. This study developed IDF curves by incorporating non-stationarity trends in precipitation annual maximum series (AMS) for Dallas–Fort Worth, the fourth-largest metropolitan region in the United States. A Pro-NEVA tool was used to develop non-stationary IDF curves, taking historical precipitation AMS for seven stations that showed a non-stationary trend with time as a covariate. Four statistical indices—the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and Nash–Sutcliffe Efficiency (NSE)—were used as the model goodness of fit evaluation. The lower AIC, BIC, and RMSE values and higher NSE values for non-stationary models indicated a better performance compared to the stationary models. Compared to the traditional stationary assumption, the non-stationary IDF curves showed an increase (up to 75%) in the 24 h precipitation intensity for the 100-year return period. Using the climate change adaptive non-stationary IDF tool for the DFW metroplex and similar urban regions could enable decision makers to make climate-informed choices about infrastructure investments, emergency preparedness measures, and long-term urban development and water resource management planning. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
47. Improving Numerical Accuracy of the Localized Oscillatory Radial Basis Functions Collocation Method for Solving Elliptic Partial Differential Equations in 2D.
- Author
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Lamichhane, Anup, Khatri Ghimire, Balaram, and Dangal, Thir
- Subjects
- *
RADIAL basis functions , *ELLIPTIC differential equations , *PROBLEM solving - Abstract
Recently, the localized oscillatory radial basis functions collocation method (L-ORBFs) has been introduced to solve elliptic partial differential equations in 2D with a large number of computational nodes. The research clearly shows that the L-ORBFs is very convenient and useful for solving large-scale problems, but this method is numerically less accurate. In this paper, we propose a numerical scheme to improve the accuracy of the L-ORBFs by adding low-degree polynomials in the localized collocation process. The numerical results validate that the proposed numerical scheme is highly accurate and clearly outperforms the results of the L-ORBFs. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
48. Hydraulic Transient Impact on Surrounding Rock Mass of Unlined Pressure Tunnels.
- Author
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Ghimire, Sanyam, Panthi, Krishna Kanta, and Vereide, Kaspar
- Subjects
TUNNELS ,PORE water pressure ,HYDROELECTRIC power plants ,POWER plants ,CYCLIC loads - Abstract
The frequent pressure pulsations due to hydraulic transients in hydropower plants induce cyclic loading on the rock mass that may contribute to increased instances of block falls and increased risk of tunnel collapse over the power plant lifetime. This study focuses on understanding the effect of frequent start and stop sequences of hydropower in unlined pressure tunnels. For this purpose, data from a pore water pressure monitoring system is utilized, which was installed at the downstream end of the headrace tunnel at the 50 MW Roskrepp hydropower plant in southern Norway. The objective of this study is to analyze the recorded data and quantify the impact of the hydraulic transient on the surrounding rock mass in the unlined pressure tunnel. The monitoring of pressure data over several years clearly shows that frequent load changes could cause a considerable effect on the rock mass and constituent joint system. A delayed response of the pressure in boreholes in the rock mass compared with inside the tunnel is seen in all start and stop sequences and is considered to be the main reason for instability caused by transients. The response of pore pressure in boreholes is greatly influenced by the characteristics of joints. The results show that the start sequence and shorter shutdown duration exert a greater impact on rock mass as compared to the stop sequence and longer shutdown duration. Therefore, it is recommended to increase the shutdown duration so that the impact can be minimized to increase the tunnel lifetime. This study recommends implementing a more conservative design approach in tunnels with weak rock masses in projects that involve frequent load changes. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
49. Which Policies and Factors Drive Electric Vehicle Use in Nepal?
- Author
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Ghimire, Laxman Prasad, Kim, Yeonbae, and Dhakal, Nawa Raj
- Subjects
- *
GREENHOUSE gases , *CLEAN energy , *PLUG-in hybrid electric vehicles , *CONSUMER preferences , *ELECTRIC vehicle batteries - Abstract
Electric vehicles (EVs) offer a viable technological solution for mitigating greenhouse gas emissions in the transportation industry, addressing pressing societal concerns regarding climate change, air pollution, and sustainable energy consumption. To effectively promote widespread adoption of EVs, it is crucial to understand consumer preferences and evaluate market dynamics. In Nepal, where proven fossil fuel reserves are absent, the government is actively working towards accelerating EV adoption, leveraging the nation's significant hydroelectric power generation potential to fulfill EVs' charging demands. To gain insight into consumer preferences and evaluate market dynamics regarding EVs in Nepal, this study employs a comprehensive approach. Stated preference data are collected through a meticulously designed survey, and sophisticated analytical techniques, namely, the mixed logit model and latent class model, are applied for estimation purposes. The results of this study show that potential EV consumers with small family sizes, lower monthly travel distances, heightened environmental awareness, and substantial knowledge about electric vehicles are more inclined to embrace EV technology. Notably, the study highlights that a reduction in the purchase price exerts the most significant influence on increasing consumers' likelihood of adopting battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Market simulation results suggest that a policy mix scenario, encompassing a combination of supportive measures, proves more effective in promoting EV adoption compared to relying on single policy initiatives. Furthermore, through latent class estimation, the study identifies three distinct classes of consumers within Nepal, each exhibiting significant variations in preferences. Recognizing and addressing these variations within policy frameworks is crucial for the successful promotion and widespread acceptance of EVs in Nepal. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
50. Sex Differences in Bone, Muscle, and Inflammatory Markers and Their Associations with Muscle Performance Variables.
- Author
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Sharma Ghimire, Pragya, Eckart, Adam, Al-Makhzoomy, Ibtihal K., and Stavitz, James
- Subjects
TUMOR necrosis factors ,VERTICAL jump ,SCIENTIFIC apparatus & instruments ,MUSCLE proteins ,SCLEROSTIN ,BONE density ,VITAMIN D - Abstract
The importance of various markers such as Sclerostin, Dickkopf-1 (DKK-1), Irisin, receptor activator of NF-kB ligand (RANKL), and Vitamin D have been well studied in bone metabolism. Additionally, inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and Interleukin 6 (IL-6) have been shown to hinder muscle protein synthesis, leading to the loss of muscle and strength. However, a research gap exists in understanding their role in muscle function and physical activity. Therefore, this study aims to explore the serum levels of Sclerostin, DKK-1, Irisin, IL-6, RANKL, Vitamin D, and TNF-α and assess their relationships with upper- and lower-body strength in young adults. In this study, 38 college-aged students (18–23 years), males and females, participated and completed the protocols. The participants' lower and upper body strength were assessed by the vertical jump test (Just Jump, Probotic, AL) with a Tendo FitroDyne (Tendo Sports Machines, Trencin, Slovak Republic) and handgrip (HG) dynamometry (Takei Scientific Instruments, Yashiroda, Japan), respectively. Fasting morning blood samples were analyzed for serum levels of biomarkers by ELISA. The results indicate significant sex differences in Sclerostin, DKK-1, Irisin, and Vitamin D levels (p < 0.05). Furthermore, a positive association was observed between Sclerostin, DKK-1, and Vitamin D, with lower body muscle performance variables (p < 0.05). Conversely, a significant negative correlation was observed between TNF-α and lower-body muscle performance variables (p < 0.05). The results suggest that these markers may have a distinct effect on muscle performance, underscoring the need for further investigation to elucidate the concept of muscle–bone crosstalk. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
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