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Social Networking Sites have now become a part of daily life for every teenager. It makes them to grow up socially through connecting with people in a short span of time. Considering this matter, the study aims to explore the perceptions of teenage students about how Facebook plays a role in the process of socialization from rural areas of Nepal. It attempts to examine secondary level students' views about the significance of Facebook in the domain of socialization and how it assists students to socialize. This study is based on qualitative in nature. It follows phenomenological research design and conducts semi-structured interview through open-ended research questions. The data is collected from 15 teenage students' of three rural community secondary schools in Devdaha Municipality. The finding indicates that Facebook plays a significant role in the process of socialization of teenage students. With the help of social networking sites, teenagers connect to the entire world and show their acquaintance through their social networking participation and intellectual achievement. Although Facebook makes teenagers pay less attention to their study and find their love and relation in the strangers, its users are more satisfied because they learn new things; connect with people all around the world, and connect it as e-learning resource.

Persistent overuse of water supplies from the Colorado River during recent decades has substantially depleted large storage reservoirs and triggered mandatory cutbacks in water use. The river holds critical importance to more than 40 million people and more than two million hectares of cropland. Therefore, a full accounting of where the river’s water goes en route to its delta is necessary. Detailed knowledge of how and where the river’s water is used can aid design of strategies and plans for bringing water use into balance with available supplies. Here we apply authoritative primary data sources and modeled crop and riparian/wetland evapotranspiration estimates to compile a water budget based on average consumptive water use during 2000–2019. Overall water consumption includes both direct human uses in the municipal, commercial, industrial, and agricultural sectors, as well as indirect water losses to reservoir evaporation and water consumed through riparian/wetland evapotranspiration. Irrigated agriculture is responsible for 74% of direct human uses and 52% of overall water consumption. Water consumed for agriculture amounts to three times all other direct uses combined. Cattle feed crops including alfalfa and other grass hays account for 46% of all direct water consumption.

Abstract Background In rural Nepal, poor road and transport networks and few testing laboratories impede tuberculosis diagnosis. A drone transport system was established to transport sputum samples to laboratories with advanced molecular diagnostic machines – GeneXpert MTB/RIF. This study explored the perceptions of using drones for tuberculosis diagnosis among community stakeholders, female community health volunteers, and healthcare providers from communities with drones implemented and without drone programs. Methods In December 2019, we conducted focus group discussions in two drone-implemented and three without drone programs. We purposively selected 40 participants: Female community health volunteers (n=16), community stakeholders (n=18), and healthcare providers (n=6). Focus group discussions employed semi-structured questions, which were audio-recorded, transcribed, and translated into English. Codebook thematic analysis was performed and charted using three levels of the socioecological model: individual, community, and health system. Results We identified four themes (i) Trust in drones underpins successful use for tuberculosis diagnosis; (ii) Drone-based sample transport optimised connectivity and accessibility for people with tuberculosis and healthcare providers; (iii) Drones create opportunities to improve community and health system, and (iv) External factors impede the use of drones to facilitate tuberculosis diagnosis. The study reported, at an individual level, people’s trust in drones mainly through community-based events. For local healthcare providers, drones reduce transport time, opportunity costs, and immediate cash costs of transport. At the community level, drone use creates opportunities to increase the skills of local people as drone pilots. At the health system level, drone transport increases efficient sputum sample delivery and provides opportunities to transport medicines and other biomedical samples. Perceived challenges of using drones were adverse weather, limitations in skilled human resources, and financial resources to operate drones sustainably. Conclusions Healthcare providers, female community health volunteers, and community stakeholders reported high levels of trust in drones and perceived their use for tuberculosis diagnosis and care to substantially benefit people with tuberculosis and providers in rural Nepal. There was a high level of demand for application to other healthcare services and wider geographical coverage, demonstrating drones as a potential tool for enhancing access to healthcare in geographically remote communities.

Accurate representation of the hourly variation in the NO2-column-to-surface relationship is essential for interpreting geostationary observations of NO2 columns. Previous research indicated inconsistencies in this hourly variation. This study employs the high-performance configuration of the GEOS-Chem model (GCHP) to analyze daytime hourly NO2 total columns and surface concentrations during summer. We use measurements from globally distributed Pandora sun photometers and aircraft observations over the United States. We correct Pandora total NO2 vertical columns for (1) hourly variations in effective temperature driven by vertically resolved contributions to the total column and (2) changes in local solar time along the Pandora line of sight. These corrections increase the total NO2 columns by 5–6 × 1014 molec. cm−2 at 09:00 and 18:00 across all sites. Fine-scale simulations from GHCP (∼12 km) reduce the normalized bias (NB) against Pandora total NO2 columns from 19 % to 10 % and against aircraft measurements from 25 % to 13 % in Maryland, Texas, and Colorado. Similar reductions are observed in NO2 columns over the eastern US (17 % to 9 %), the western US (22 % to 14 %), Europe (24 % to 15 %), and Asia (29 % to 21 %) when compared to 55 km simulations. Our analysis attributes the weaker hourly variability in the total NO2 column to (1) hourly variations in column effective temperature, (2) local solar time changes along the Pandora line of sight, and (3) differences in hourly NO2 variability from different atmospheric layers, with the lowest 500 m exhibiting greater variability, while the dominant residual column above 500 m exhibits weaker variability.

Abstract Background Type I interferons (IFN-I) are potent alarm factors that initiate cancer cell elimination within tumors by the immune system. This critical immune response is often suppressed in aggressive tumors, thereby facilitating cancer immune escape and unfavorable patient outcome. The mechanisms underpinning IFN-I suppression in tumors are incompletely understood. Arginase-1 (ARG1)-expressing immune cells that infiltrate tumors can restrict arginine availability by ARG1-mediated arginine degradation. We hypothesized that arginine restriction suppresses the IFN-I response in tumors. Methods Comprehensive, unbiased open approach omics analyses, various in vitro techniques, including microscopy, qPCR, immunoblotting, knock-down experiments, and flow cytometry were employed, as well as ex vivo analysis of tumor tissue from mice. Several functional bioassays were utilized to assess metabolic functions and autophagy activity in cancer cells. Results Arginine restriction potently induced expression of selective autophagy receptors, enhanced bulk and selective autophagy and strongly suppressed the IFN-I response in cancer cells in an autophagy-dependent manner. Conclusion Our study proposes a mechanism for how tumor-infiltrating immune cells can promote cancer immune escape by dampening the IFN-I response. We suggest ARG1 and autophagy as putative therapeutic targets to activate the IFN-I response in tumors.

IntroductionCardiopulmonary resuscitation (CPR) is an evidence-based intervention that saves lives. In low- and middle-income countries like Nepal, the occurrence of the problem and its outcome are seldom studied. The study aims to highlight the prevalence, performance, and outcome of CPR in government hospitals of Nepal.MethodsA mixed method study was done for two months in central and provincial government hospitals of Nepal. A total of 80 resuscitations were evaluated using a questionnaire based on the American Heart Association 2020 guidelines for cardiopulmonary resuscitation. An in-depth interview was conducted with 15 active participants of the resuscitation in different sites. Thematic analysis was done using the framework of the chain of survival of arrest victims.ResultsThe overall prevalence of CPR was found to be 1.92% [95% CI: 0.01,0.02] with 5.4% in central hospitals and 0.65% in provincial hospitals with 60% cardiac arrests occurring in the intensive care unit. Estimated time from recognition of the arrest to initiating CPR was 1.9 ±1.4 minutes. Asystole 66.25% was the commonest arrest rhythm and 21.25% had difficulty interpreting rhythm. Only 11.25% of the victims had return of spontaneous circulation and were subsequently transferred for post-arrest care. The qualitative analysis highlighted the lack of trained staff, a dedicated system, feedback mechanism, and provision of post-arrest care.ConclusionAcross various level of Nepal's healthcare system, cardiopulmonary resuscitation is prevalent with poor performance and outcome. To improve outcomes, it is essential to implement standardized procedures and ensure high quality resuscitation delivery before and after the event supported by well-trained healthcare personnel and adequate infrastructure.

Political accountability is essential for maintaining trust and transparency in governance. However, the factors that influence political parties' accountability remain underexplored in Nepal. This paper examines the factors influencing citizens' perceptions of political parties' accountability in Nepal, utilizing data from the National Governance Survey 2017/18 (N = 4191). A four-stage multiple cluster sampling technique was used to randomly select respondents from 43 out of 77 districts in Nepal. Data were collected between December 2017 and March 2018. Results from logistic regression analysis indicate that citizens' perceptions of political parties' honesty, transparency, adherence to rules, and corruption control significantly impact political parties' accountability. While citizen engagement in political discussions was positively associated with political parties' accountability, this factor did not demonstrate statistical significance. These findings highlight the importance of honesty, transparency, rule of law, and anti-corruption measures in fostering political parties' accountability. This study contributes to the literature on democratic governance and offers practical insights for authorities seeking to strengthen accountable political institutions in Nepal. The insights of this paper provide a roadmap for political parties to prioritize ethical conduct, proactive information sharing, regulatory compliance, and anti-graft efforts to build public trust and accountability.

In this study, thalli nitrogen (N) and metal ions contents in the two fruticose lichens (Ramalina intermedia and Usnea cornuta) were quantified, which were collected from a pristine Himalayan forest of Shey Phoksundo National Park of western Nepal. Besides, the probable impacts of N and metal ions in physicochemical responses such as electrical conductivity, chlorophyll contents, and chlorophyll degradation were studied. Our initial hypothesis was there are considerable amounts of thallus N and metal ions in lichens from the study area, and it has substantial impacts on physicochemical responses. In comparison, the thalli N concentration was observed to be the greatest in R. intermedia thalli (0.24%–1.15%). However, comparable amounts of metal ions in both lichen species were observed. Regression analysis revealed the least or no impacts of N and metal ions in physicochemical responses. The principal component analysis suggests the contribution of different environmental variable and their correlation with lichen’s variables. This study provides evidence of the least concentration of N and metal ions and only minor impacts on the physicochemical integrity of the two sensitive lichens in our study area. This study is likely to contribute as field-based reference information for further studies on the species-specific N and metal ions accumulation in lichens from different Himalayan forest systems to monitor ecosystem health.

Citrus fruit cultivation, especially mandarin oranges, is crucial to the economy of Nepal’s hilly regions due to their ideal geoclimatic conditions. Despite its economic importance, the sector faces several challenges, such as inadequate grafting techniques, low-quality saplings, and ineffective post-harvest storage. This paper explores these issues and proposes innovative solutions through the use of Internet of Things (IoT) technology. To address these challenges, we identified key areas for improvement. First, we focused on extending grafting practices during the off-season to ensure a higher success rate and better-quality saplings. Second, we examined different post-harvest storage methods to determine their effectiveness in terms of shelf life, decay loss, and quality of fruit. In addition to exploring post-harvest strategies, this paper provides preharvest recommendations for farmers, emphasizing methods to enhance fruit quality and longevity through effective pre-storage practices. Our IoT-based approach introduces off-season grafting in polyhouses and advanced monitoring for post-harvest storage. The results are promising: We achieved grafting success rates of 91% for acid lime and 92% for local mandarin orange varieties. Additionally, our research compared different post-harvest storage methods for mandarin oranges, including room, cellar, and cold chamber. We assessed these methods based on shelf life, physiological weight loss, and the total soluble solids (TSS) to titratable acidity (TA) ratio. The cold chamber proved to be the most effective method, offering superior conditions for storing mandarin oranges. The IoT-based monitoring system played a crucial role in maintaining optimal temperature, humidity, and gas content within the cold chamber, resulting in reduced post-harvest losses and extended shelf life. These findings highlight the transformative potential of IoT technology in mandarin orange cultivation and post-harvest storage.

Escherichia coli in untreated milk leads to economic losses from subclinical mastitis and reduced milk production, while also posing a public health risk due to the emergence of antimicrobial resistant strains, particularly associated with consuming unpasteurized milk and dairy products. This study aimed to determine the prevalence and antimicrobial resistance (AMR) of E. coli isolated from buffalo milk in Siddarthanagar Municipality of Rupandehi district, Nepal. A total of 102 milk samples were collected from lactating buffaloes. The isolation and identification of E. coli were carried out using enrichment media, selective media, and biochemical tests. Antimicrobial susceptibility testing was carried out using the Kirby–Bauer disk diffusion method on Mueller–Hinton agar (Merck), according to the Clinical and Laboratory Standards Institute (CLSI) recommendations. Resistance was tested against gentamicin, amikacin, ciprofloxacin, enrofloxacin, ceftriaxone, ceftazidime, cotrimoxazole, and chloramphenicol. In addition to this, farmers were administered a questionnaire consisting of both open- and close-ended questions to identify various animal-related and management-related risk factors associated with the prevalence of E. coli. The prevalence of E. coli in our study was 29.4% (n = 30/102). Ceftriaxone and ceftazidime showed 100% resistance, while cotrimoxazole and amikacin showed 86.7% and 80% resistance, respectively. Furthermore, 86.7% of E. coli isolates were multidrug resistant (MDR). Despite suggestive trends, associations between E. coli prevalence and risk factors lacked statistical significance, necessitating further research. While some antibiotics exhibited effectiveness, many faced resistance, highlighting the need for prudent antimicrobial usage and increased awareness among farmers. Raising awareness about milk pasteurization and implementing food safety practices is essential for ensuring farmers and public health.

Efficient water use and sustainable crop production are vital for ensuring both food and water security amidst the growing global population and changing climate. With expected increases in hydroclimatic extremes under climate change, irrigated agriculture is projected to rise, further interlinking food and water security. Hence, the need for future crop yield projections has become more urgent, including knowledge about the accuracy of crop growth modeling in terms of crop yield and water consumption. To this end, our study evaluates two crop growth models—AquaCrop-OS and PCR-GLOBWB 2-WOFOST. The coupled hydrological-crop growth model PCR-GLOBWB 2-WOFOST was applied using both its original settings and harmonized with AquaCrop-OS input, resulting in two model experiments that were compared to the AquaCrop-OS results, allowing analyses of differences in both model structure and parametrizations. AquaCrop-OS and PCR-GLOBWB 2-WOFOST (with original and harmonized input) were used to simulate the yield of irrigated maize, soybean, winter wheat and spring wheat across the contiguous United States (CONUS) from 2001 to 2019. Model outputs were compared in terms of crop water consumption, biomass production, and crop yield and the model sensitivity under dry and warm conditions was evaluated.For all considered crops, PCR-GLOBWB 2-WOFOST (original) simulated yields align closely with mean reported yields, with the harmonized version showing some underestimates for soybeans and winter wheat (∼23 %). AquaCrop-OS generally overestimates crop yields (up to ∼34 %). Our results also highlight significant differences in spatial patterns of crop water consumption, biomass, and crop yield between AquaCrop-OS and PCR-GLOBWB 2-WOFOST (original and harmonized) models. Specifically, differences between the AquaCrop-OS and PCR-GLOBWB 2-WOFOST (harmonized) models are attributed to variations in how biomass is converted to yield within each model. Also, AquaCrop-OS is found to be much less sensitive to higher air temperatures than the PCR-GLOBWB 2-WOFOST model. Finally, the differences between PCR-GLOBWB 2-WOFOST original and its harmonized settings emphasize the importance of using local- and up-to-date information on crop-specific parametrization in crop growth modeling. These findings underscore the importance of model selection and parameterization in accurately simulating crop yield and crop water consumption under climate extremes, which is essential for improving agricultural practices under climate change.

The Great Salt Lake of Utah (US) is of great economic, cultural, and spiritual importance, yet rapid depletion of the lake in recent decades gravely threatens these values. The lake's shrinkage is attributable to anthropogenic consumption of 62% of river water that would have otherwise reached and replenished the lake. The lake's water balance has been in deficit for much of the past century, but during recent decades climate warming and drought has reduced basin runoff, while anthropogenic water consumption has not been reduced to a commensurate degree, driving the lake's water budget further into deficit condition and causing an average lake level decline of 0.1 meter/year during 1989−2022. Agriculture accounts for 71% of anthropogenic depletions, with 80% of agricultural water going to cattle-feed crops (alfalfa and grass hay) to support ∼980,000 head of cattle for dairy and beef production. We propose a target goal of reducing total anthropogenic consumption by 35% to stabilize and begin refilling the lake, and explore potential policy solutions for attaining this conservation goal. We find that the most potent solutions would involve a 61% reduction in alfalfa production along with fallowing of 26–55% of grass hay production, resulting in reductions of agricultural revenues of US$97 million per year, or 0.04% of the state's GDP. Farmers and ranchers involved in cattle-feed production, along with related agricultural businesses, could be fully compensated for lost revenue generation at a cost ranging from US$29-$124 per Utah resident each year, depending upon which water conservation strategies are deployed. Dairies dependent upon alfalfa produced in the Great Salt Lake basin would need to increase imports of these crops from other river basins to sustain production at current levels. This case study of a water-stressed basin with dominant agricultural water use illustrates globally transferable approaches for rebalancing the water budget of stressed water basins by reducing consumptive water use on irrigated farms. The approaches described here require detailed accounting of water consumed by individual crop types.

Fructose-1, 6- bisphosphatase deficiency is a rare autosomal recessive inborn error of fructose metabolism which mainly affects gluconeogenesis. It often presents with ketotic hypoglycemia and lactic acidosis, with hyperventilation. The disease has a high mortality rate when undiagnosed.Here we report a case of this rare disorder, referred to our hospital in Western Nepal, diagnosed originally as pneumonia. The patient presented in respiratory distress with severe metabolic acidosis and dehydration. She also demonstrated hypoglycemia, hypernatremia, coagulation dysfunction and albuminuria, all of which gradually improved, though her lactate remained consistently elevated. This led to investigation of urinary ketones which were positive suggesting a defect in the metabolism of carbohydrates. Urine organic acid profile and whole exome sequencing finally confirmed the diagnosis of Fructose-1, 6- bisphosphatase deficiency. To our knowledge this is the first case report of this disease diagnosed in Nepal.

Contemporarily, one of the most pressing concerns is reliable and rapid weather forecasting. In Nepal, the Department of Hydrology and Meteorological uses a numerical modeling approach to forecast the weather, which is tardy and requires high-end equipment to process the information, so a deep learning approach will be the best alternative. This project aims to forecast the next 2-hour Precipitation and Air Temperature for Pokhara Domestic Airport meteorological station and the next day's Precipitation, Maximum and Minimum Air Temperature forecast for Lumle, Begnas, and Lamachaur meteorological station, total of four meteorological stations of the Kaski District, Nepal using Long Short-Term Memory (LSTM): a Recurrent Neural Network (RNN) and deploy the outputs through the web portal. The four hourly parameters: Rainfall, Relative Humidity (R.H), Wind Speed, and Air Temperature, were used for modeling the airport station forecast, whereas Rainfall, Relative Humidity (R.H), Maximum and Minimum Temperature were used for modeling the Begnas and Lumle station forecast and only Precipitation data was used for Lamachaur station. Averaging and linear interpolation techniques were used to fill out the missing values and outliers were detected using Box Plot and replaced with threshold value for each parameter. Stochastic Gradient Descent and Adam optimizer are used to optimize the LSTM model. Among all the models prepared, Root Mean Square Error (RMSE) values range from 0.58 to 4.08 for the precipitation model and from 0.16 to 0.82 for the air temperature model, and Mean Absolute Error (MAE) values range from 0.21 to 2.87 for the precipitation model and from 0.12 to 0.64 for air temperature model were the values of the final model that indicates better accuracy for air temperature. The R² values range from 0.89 to 0.99, indicating the train and test data were fitted to the model really well.

The pasting properties of rice starch can be improved by blending it with native or modified starch. This research investigated the pasting profiles and gel properties of rice flour (RF) blended at different concentrations with tapioca starch (TS), lowand highdegrees of crosslinked starch (LCL and HCL), and lowand highdegrees of substitution of acetylated starch (LAC and HAC). The results showed that substituting RF with both native and modified starches tended to decrease the pasting temperature of the flour blends. The increase in HCL in flour blends resulted in a higher pasting temperature, final viscosity, and setback. At the same time, adding LAC and HAC did not affect the pasting temperature, but a significantly decreased final viscosity was observed. RF-HCL10 and RF-HAC10 exhibited significantly higher swelling power than RF alone. Blending RF with HCL at 5, and 10% by weight could improve the freeze-thaw stability of the gels made from each blend. The information obtained herein is useful for the prediction of product properties that are rich in starch.

In this study, the development of diverse antenna designs using additive manufacturing processes, specifically spanning from L-band to K-band is proposed. All designs are implemented on a flexible FR4 substrate to make them suitable for wearable sensors and biomedical applications. The fabrication process involves the utilization of aerosol jet printing with nanoparticle silver ink, followed by curing in a vacuum chamber. Additionally, screen printing with copper paste is employed as another method, with subsequent curing in a laminator. The reflection coefficient (S11) and radiation patterns for the simulated design and fabricated samples were found to align closely. The achieved return loss consistently reaching −10 dB across fairly large operating frequency range underscores the efficacy of the proposed antennas and their associated additive manufacturing mechanisms. The design and simulation were performed using Ansys high frequency structural simulator (HFSS), and the parameters under test for the fabricated antennas were validated using a vector network analyzer (VNA) to assess overall performance.

Betel leaves (Piper betle) are a species of Piper genus which is rich in phytonutrients like steroids, phenols, flavonoids, alkaloids, steroids, saponins and terpenoids. Anti-cancer, antibacterial, anti-inflammatory, antioxidant, anti-mutagenic, antiplaque, and anti-diabetic properties are among the health benefits of this plant's leaf extract. This study aimed to quantify the phytochemical constituents and assess the antioxidant capacity of piper betle leaves. In this study, qualitative phytochemical screening were used done by using test for alkaloids, glycosides, phenols, flavonoids, steroids, terpenoids, saponins. Additionally, we calculated the betel leaves' total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity using DPPH, H202 scavenging activity after extraction by methanol using Soxhlet apparatus. The TPC and TFC was noted 51.5278 mg GAE/gm and 33.769 mg QE/gm respectively. There was a significant positive connection found between DPPH and Total Phenolic Content. (R²=0.9939) (p value= 0.0002), H202 (R²=0.9979) (p value