Prediction of axial capacity of corrosion-affected RC columns strengthened with inclusive FRP.

The primary cause behind the degradation of reinforced concrete (RC) structures is the propagation of corrosion in the steel-RC structures. Nowadays, numerous retrofitting techniques are available in the construction sector. Fiber-reinforced polymer (FRP) is one of the efficient rehabilitation measures that can be implemented on corroded structures to enhance structural capacities. However, the estimation of axial strength of FRP-strengthened columns affected by corrosion has been a challenging and tedious task in the laboratory as well as on the site. Considering such shortcomings, the prediction of axial capacity can be done using various analytical methods and artificial intelligence (AI) techniques. In this study, a comprehensive dataset of circular columns was extracted from the literature to predict the axial strength of FRP-wrapped and unstrengthened RC corroded columns. The laboratory results from the assembled dataset were compared to corresponding values estimated using relevant design codes provided by American Concrete Institute (ACI 440.2R-17 and ACI 318-19), and Bureau of Indian Standard (IS 456:2000). Five machine learning models were employed on columns to predict the axial load carrying capacity of FRP-strengthened and un-strengthened RC corroded columns. The results discovered that the extreme gradient boosting (XGBoost) model achieves superior accuracy with the least errors and could be used by the scientific community and FRP applicators to forecast the axial performance of corroded columns strengthened with and without FRP. The findings from the design codes revealed that prediction errors were available in high margins. Furthermore, feature importance analysis was conducted using the Shapley Additive exPlanation algorithm to know the contribution and influence of each input parameter on axial capacity. The feature analysis found that unconfined compressive strength of concrete plays an important role in deciding the axial capacity of columns. Moreover, to enhance the precision of axial capacity computation and improving the overall efficacy in engineering practice, a web-based user-friendly interface was developed for FRP applicators and engineers to simplify the process.

Endoscopic Assessment of Cholesteatoma Following Microscope Assisted Tympano: Mastoidectomy: Study design: a cross section descriptive study.

Complete surgical removal of cholesteatoma has been traditionally performed by microscopic approaches. In recent years, use of endoscopes in middle ear surgery is gaining increasing importance. The wide field view offered by the endoscopes in comparison to the narrow field of view of the binocular microscope enables a surgeon to see and dissect around corners, thereby exposing 'hidden recesses' of the middle ear which can be useful during cholesteatoma surgery. To identify remnant cholesteatoma in difficult access sites of the middle ear cleft using endoscopes following a microscope assisted mastoidectomy. A cross sectional study was conducted in patients who were clinically diagnosed with cholesteatoma. Patients were subjected to High Resolution Computed Tomography of the temporal bone and pre-operative audiological tests. Mastoid exploration was performed microscopically followed by endoscopic evaluation and clearance of disease in the same setting. Patients were then followed up post-operative and endoscopically evaluated to look for any remnant disease. A total of 45 patients were included, all of which underwent microscopic assisted mastoidectomy. Remnant cholesteatoma was discovered in 15 out of 45 cases (33%) distributed in the hidden areas; in the region of sinus tympani 9(60%), anterior epitympanum 4(27%), hypotympanum 1(7%) and tip Cells 1(7%). It can be concluded that endoscopes have a definite role in evaluation and complete surgical clearance of cholesteatoma particularly from the hidden areas of middle ear cleft which would have otherwise been missed by the straight line view of a microscope thereby grossly reducing the rate of remnant disease. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-023-04263-6.

Ensemble learning based compressive strength prediction of concrete structures through real-time non-destructive testing.

This study conducts an extensive comparative analysis of computational intelligence approaches aimed at predicting the compressive strength (CS) of concrete, utilizing two non-destructive testing (NDT) methods: the rebound hammer (RH) and the ultrasonic pulse velocity (UPV) test. In the ensemble learning approach, the six most popular algorithms (Adaboost, CatBoost, gradient boosting tree (GBT), random forest (RF), stacking, and extreme gradient boosting (XGB)) have been used to develop the prediction models of CS of concrete based on NDT. The ML models have been developed using a total of 721 samples, of which 111 were cast in the laboratory, 134 were obtained from in-situ testing, and the other samples were gathered from the literature. Among the three categories of analytical models-RH models, UPV models, and combined RH and UPV models; seven, ten, and thirteen models have been used respectively. AdaBoost, CatBoost, GBT, RF, Stacking, and XGB models have been used to improve the accuracy and dependability of the analytical models. The RH-M5, UPV-M6, and C-M6 (combined UPV and RH model) models were found with highest performance level amongst all the analytical models. The MAPE value of XGB was observed to be 84.37%, 83.24%, 77.33%, 59.46%, and 81.08% lower than AdaBoost, CatBoost, GBT, RF, and stacking, respectively. The performance of XGB model has been found best than other soft computing techniques and existing traditional predictive models.

Air pollution status and attributable health effects across the state of West Bengal, India, during 2016-2021.

Air pollution is one of the most significant threats to human safety due to its detrimental health consequences worldwide. This study examines the air pollution levels in 22 districts of West Bengal from 2016 to 2021, using data from 81 stations operated by the West Bengal Pollution Control Board (WBPCB). The study assesses the short- and long-term impacts of particulate matter (PM) on human health. The highest annual variation of PM10 was noted in 2016 (106.99 ± 34.17 µg/m3), and the lowest was reported in 2020 (88.02 ± 13.61 µg/m3), whereas the highest annual variations of NO2 (µg/m3) were found in 2016 (35.17 ± 13.55 µg/m3), and lowest in 2019 (29.72 ± 13.08 µg/m3). Similarly, the SO2 level was lower (5.35 µg/m3) in 2017 and higher in 2020 (7.78 µg/m3). In the state, Bardhaman, Bankura, Kolkata, and Howrah recorded the highest PM10 concentrations. The monthly and seasonal variations of pollution showed higher in December, January, and February (winter season) and lowest observed in June, July, and August (rainy season). The southern part of West Bengal state has recorded higher pollution levels than the northern part. The short- and long-term health impact assessment due to particulate matter shows that the estimated number of attributable cases (ENACs) for incidence of chronic bronchitis in adults and prevalence of bronchitis in children were 305,234 and 14,652 respectively. The long-term impact of PM2.5 on human health ENACs for mortality due to chronic obstructive pulmonary disease for adults, acute lower respiratory infections in children aged 0-5, lung cancer, and stroke for adults were 21,303, 12,477, 25,064, 94,406, and 86,272 respectively. This outcome assists decision-makers and stakeholders in effectively addressing the air pollution and health risk concerns within the specified area.

Development of EST-SSR markers in Bergenia ciliata using de novo transcriptome sequencing.

Bergenia ciliata (Haw.) Sternb. is an important herb predominantly found in the Indian Himalayan Region. It is widely used in medicines, healthcare systems, cosmetics, fodder, and ornamental purposes. The Illumina sequencing and de novo transcriptome assembly were carried out in B. ciliata to develop and identify simple sequence repeat markers. A total of 18 226 simple sequence repeats (SSRs) were identified wherein di-nucleotides were found to be abundant (47.88%), followed by mono-nucleotide (35.03%) and tri-nucleotide (15.88%) repeats. A total of 11 839 EST-SSR primers were designed, of which 96 primer pairs were commercially synthesized. Finally, 17 primer pairs revealed clear, distinct polymorphic bands, and these primers were validated with 40 diverse B. ciliata accessions. The present study revealed moderate level of genetic diversity (Ho = 0.389, He = 0.542, and PIC = 0.513). Furthermore, the transcriptome data and EST-SSR markers generated during the present investigation could be an important genetic resource for functional genomics, population studies, and conservation genetics of the genus Bergenia.

Nanocellulose: A comprehensive review investigating its potential as an innovative material for water remediation.

Rapid growth in industrialization sectors, the wastewater treatment plants become exhausted and potentially not able to give desirable discharge standards. Many industries discharge the untreated effluent into the water bodies which affects the aquatic diversity and human health. The effective disposal of industrial effluents thus has been an imperative requirement. For decades nanocellulose based materials gained immense attraction towards application in wastewater remediation and emerged out as a new biobased nanomaterial. It is light weighted, cost effective, mechanically strong and easily available. Large surface area, versatile surface functionality, biodegradability, high aspect ratio etc., make them suitable candidate in this field. Majorly cellulose based nanomaterials are used in the form of cellulose nanocrystals (CNCs), cellulose nanofibers (CNFs), or bacterial nanocellulose (BNC). This review specifically describes about a variety of extraction methods to produced nanocellulose and also discusses the modification of nanocellulose by adding functionalities in its surface chemistry. We majorly focus on the utilization of nanocellulose based materials in water remediation for the removal of different contaminants such as dyes, heavy metals, oil, microbial colony etc. This review mainly emphasizes in ray of hope towards nanocellulose materials to achieve more advancement in the water remediation fields.

Stigma towards mental illness in Asian nations and low-and-middle-income countries, and comparison with high-income countries: A literature review and practice implications.

Background: Stigma related to mental illness (and its treatment) is prevalent worldwide. This stigma could be at the structural or organizational level, societal level (interpersonal stigma), and the individual level (internalized stigma). Vulnerable populations, for example, gender minorities, children, adolescents, and geriatric populations, are more prone to stigma. The magnitude of stigma and its negative influence is determined by socio-cultural factors and macro (mental health policies, programs) or micro-level factors (societal views, health sectors, or individuals' attitudes towards mentally ill persons). Mental health stigma is associated with more serious psychological problems among the victims, reduced access to mental health care, poor adherence to treatment, and unfavorable outcomes. Although various nationwide and well-established anti-stigma interventions/campaigns exist in high-income countries (HICs) with favorable outcomes, a comprehensive synthesis of literature from the Low- and Middle-Income Countries (LMICs), more so from the Asian continent is lacking. The lack of such literature impedes growth in stigma-related research, including developing anti-stigma interventions. Aim: To synthesize the available mental health stigma literature from Asia and LMICs and compare them on the mental health stigma, anti-stigma interventions, and the effectiveness of such interventions from HICs. Materials and Methods: PubMed and Google Scholar databases were screened using the following search terms: stigma, prejudice, discrimination, stereotype, perceived stigma, associate stigma (for Stigma), mental health, mental illness, mental disorder psychiatric* (for mental health), and low-and-middle-income countries, LMICs, High-income countries, and Asia, South Asian Association for Regional Cooperation/SAARC (for countries of interest). Bibliographic and grey literature were also performed to obtain the relevant records. Results: The anti-stigma interventions in Asia nations and LMICs are generalized (vs. disorder specific), population-based (vs. specific groups, such as patients, caregivers, and health professionals), mostly educative (vs. contact-based or attitude and behavioral-based programs), and lacking in long-term effectiveness data. Government, international/national bodies, professional organizations, and mental health professionals can play a crucial in addressing mental health stigma. Conclusion: There is a need for a multi-modal intervention and multi-sectoral coordination to mitigate the mental health stigma. Greater research (nationwide surveys, cultural determinants of stigma, culture-specific anti-stigma interventions) in this area is required.

A Drug Utilization Study of Anti-glaucoma Drugs in a Tertiary Care Hospital.

BACKGROUND AND OBJECTIVES: Today, branded medications and polytherapy are frequently prescribed for glaucoma, even without giving the patient the proper instructions. Hence, the safety, effectiveness, cost, and patient compliance of glaucoma medication must be weighed, and the anti-glaucoma medicine usage must be studied. Analysis of glaucoma patients' prescription usage was the objective of this study. MATERIAL AND METHODS: Between January 2021 and February 2022, this prospective and observational study was carried out at Andhra Medical College in Vishakhapatnam. One hundred prescriptions of those with primary open-angle and angle closure glaucoma were assessed. Age and gender-based subgroup analyses were conducted. R software (version 4.2.1) (The R Foundation for Statistical Computing, Vienna, Austria) was leveraged for data analysis. RESULTS: Out of 146 examined prescriptions, 100 (69%) were deemed suitable for analysis. Participants' mean age was 54.2 ± 10.8 years. Sixty-two were over 50 years old, and 36 were men. The mean intraocular pressure was 25.4 ± 1.7 mm of Hg. Per prescription, there were about 1.75 anti-glaucoma drugs. Fixed-dose combinations (FDC) were found in 43 prescriptions. Generic medications and patient instructions prevailed in most prescriptions (78%) and (84%). Timolol was used in each FDC with brimonidine, dorzolamide, or bimatoprost. CONCLUSION: The most often prescribed anti-glaucoma drug, timolol, was also identified as an essential component of the FDC. Doctors must prescribe generic medications with detailed directions for the patients.

A Study on the Attitude and Perception of Bachelor of Medicine and Bachelor of Surgery (MBBS) Students Regarding Post-MBBS Compulsory Service Bond in Uttar Pradesh, India.

Background To increase the availability of doctors in the public healthcare delivery system, the state government of Uttar Pradesh, India, has implemented a two-year compulsory service bond since 2018. Students of the 2018 batch are going to complete their Bachelor of Medicine, Bachelor of Surgery (MBBS) in 2023 and are supposed to serve through this bond. There are many dilemmas in the minds of medical students regarding their compulsory service bond. Hence, there is a need to know their attitude and perceptions regarding the compulsory service bond. This study was conducted to assess the attitude and perception of undergraduate medical students toward compulsory service bonds. Methods This was a mixed-method study conducted in July-September 2022 among undergraduate medical students at Baba Raghav Das Medical College, Gorakhpur, Uttar Pradesh, India. For quantitative data, a structured questionnaire was developed using Google Forms (Google LLC, Mountain View, California, United States) and circulated via WhatsApp (Meta Platforms, Inc., Menlo Park, California, United States) through the random sampling method. Focused group discussions were carried out to collect the qualitative data. Result Regarding the compulsory service bond after MBBS, 100 (31.8%) medical students were found to be interested and 56 (17.8%) were disinterested. The majority (n=158; 50.4%) of participants were neutral, while 278 (88.6%) medical students perceived it as an opportunity to help poor people. Higher possibilities of social recognition and respect were some noticeable perceptions of 243 (77.4%) MBBS students. Lack of confidence to tackle serious cases without a senior doctor's supervision was perceived as an important hurdle by 286 (91%) participants. Non-availability of advanced medical facilities, issues like the safety of doctors, and the lack of availability of electricity, roads, and infrastructure were also perceived as hurdles. Conclusions and recommendations Students perceived the compulsory service bond as an opportunity if met with certain conditions like a transparent method of posting and basic facilities or an incentive for accommodation and transportation. The compulsory service bond for addressing the shortfall of doctors in the public healthcare delivery system may be more effective if these hurdles are corrected and certain opportunities are met, as mentioned in the present study. This will help the government move smoothly towards achieving Universal Health Coverage (UHC).

Parametric Optimization of Torsional Parameters of Ferrocement "U" Wrapped Beams Using Recent Meta-Heuristic Optimization Algorithms.

Structural elements are subjected to different types of loads, one of which is a torsional load. Due to the complexity of the analysis, torsion was not given much importance in earlier days. With stringent updates in codal provisions and due to architectural modifications, torsion is now considered one of the major parameters for structural design. The main aim of this paper is to analyze distressed elements due to torsion. It highlights different approaches, such as destructive and non-destructive processes, to be adopted to estimate the torsional parameters of a ferrocement "U" wrapped beam. The destructive method is the experimental determination of parameters, which is absolutely necessary. The non-destructive method includes an analytical method based on a softened truss model as well as a soft computing method. The soft computing method is based on the regression coefficient analysis method along with two recent optimization algorithms, i.e., (1) ARO (artificial rabbits optimization) and (2) DAOA (dynamic arithmetic optimization algorithm). The predicted results are found to be in agreement with the experimental values (destructive method). Lastly, the obtained results from both proposed methods are analyzed, and it is found that both algorithms can be utilized in any engineering problem to determine the global optimum value with corresponding input optimal settings. As the experimental method is time-consuming and expensive, analytical, and soft computing methods can be preferred over the experimental method.

Green Synthesis of CdS and CdS/rGO Nanocomposites: Evaluation of Electrochemical, Antimicrobial, and Photocatalytic Properties.

The green approach has been employed for the synthesis of various types of nanomaterials including metal nanoparticles, metal oxides, and carbon-based nanomaterials. These processes involve natural sources that contain bioactive compounds that act as reducing, stabilizing, and capping agents for the formation and stabilization of nanomaterials. This study reports the green synthesis of CdS and CdS/rGO nanocomposites using Lactobacillus bacteria. The UV-visible spectrophotometer, field emission scanning electron microscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy, Raman spectroscopy, and Fourier transform infrared spectroscopy spectra confirm the synthesis of the nanocomposite. The electrochemical characterization using cyclic voltammetry, differential pulse voltammetry, and EIS revealed that the CdS/rGO nanocomposites showed a higher electron transfer rate compared with CdS nanoparticles, indicating the potential of the nanocomposites for biosensing applications. The zone of inhibition revealed significant antimicrobial activity against Escherichia coli and Staphylococcus aureus for both CdS nanoparticles and CdS/rGO nanocomposites. Additionally, CdS/rGO nanoparticles exhibited high photocatalytic activity for the degradation of methylene blue dye. Overall, this study demonstrates that the synthesized CdS and CdS/rGO nanocomposites have good electrochemical properties, photocatalytic, and antimicrobial activity and, therefore, can be employed for various applications such as biosensing, photocatalysis, and antimicrobial activity.

Functional hBN decorated Ni(OH)2 nanosheets synthesized for remarkable adsorption performance for the elimination of fluoride ions.

Occurrence of fluoride in groundwater is a serious concern due to its fatal effects. Functionalized hexagonal boron nitride sheets have been combined with nickel hydroxide nanoparticles by a one step process and a hybrid adsorbent Ni(OH)2@hBN has been developed with an exceptionally high fluoride adsorption capacity of 365 mg g-1, higher than those of Ni(OH)2 and hBN. This maximum adsorption capacity is higher than those of most common adsorbents used for defluoridation including activated alumina, reported nickel oxide and carbon-based 2D material-supported alumina adsorbents. The presence of functionalized boron nitride significantly increased the surface area to 680 m2 g-1 with a pore volume of 0.33687 cm3 g-1 and provided rich hydroxyl group-containing surface sites for the removal of fluoride present in contaminated water. In addition, the adsorption of fluoride onto boron nitride-modified nickel hydroxide followed pseudo-second-order kinetics and the equilibrium data fitted well with the Langmuir adsorption isotherm, suggesting a monolayer adsorption mechanism. Furthermore, the material developed is tested with the water sample collected from a real affected area, from the Dhar district of India, and the material showed promising results in terms of fluoride removal efficacy.

A Compact Circular Rectenna for RF-Energy Harvesting at ISM Band.

With low-power gadgets proliferating, the development of a small, effective rectenna is crucial for wirelessly energizing devices. A simple circular patch with a partial ground plane for RF-energy harvesting at ISM (2.45 GHz) band is proposed in this work. The simulated antenna resonates at 2.45 GHz with an input impedance of 50 Ω and a gain of 2.38 dBi. An L-section matching a circuit with a voltage doubler is proposed to provide excellent RF-to-DC transformation efficiency at low power input. The proposed rectenna is fabricated and the results show that the return loss and realized gain have good characteristics at the ISM band with 52% of RF-to-DC transformation efficiency, with an input of 0 dBm power. The projected rectenna is apt for power-up low sensor nodes in wireless sensor applications.

Utility of the Parkland Grading Scale to determine intraoperative challenges during laparoscopic cholecystectomy: a validation study on 206 patients at an academic medical center in Nepal.

BACKGROUND: Most of the scoring systems to predict difficult laparoscopic cholecystectomy are based on pre-operative clinical and radiological findings. Recently the Parkland Grading Scale system was introduced as a simple intra-operative grading scale. This study aims to utilize the Parkland Grading Scale system to assess the intraoperative challenges during laparoscopic cholecystectomy. METHOD: This was a prospective, cross-sectional study done at Chitwan Medical College and Teaching Hospital, Chitwan, Nepal. All the patients underwent laparoscopic cholecystectomy from April 2020 to March 2021. Based on the initial intra-operative finding, Parkland Grading Scale was noted and at the end of the surgery, the level of difficulty was given by the operating surgeon. All the pre-operative, intra-operative, and post-operative findings were compared with the scale. RESULTS: Out of 206 patients, there were 176 (85.4%) females, and 30 (14.6%) males. The median age was 41 years (Range 19-75). The median body mass index was 23.67 kg/m2. There were 35(17%) patients with a history of previous surgery. The rate of conversion to open surgery was 5.8%. According to Parkland Grading Scale, 67(32.5%), 75(36.4%), 42(20.4%), 15(7.3%), and 7(3.4%) were graded as grade 1, 2, 3, 4, and 5 respectively. There was a difference in the Parkland grading scale in patients with a history of acute cholecystitis, gallbladder wall thickness, pericholecystic collection, stone size, and body mass index (p < 0.05). The total operative time, level of difficulty in surgery, rate of help needed from colleagues or replacement as the main surgeon, bile spillage, drain placement, gallbladder decompression, and conversion rate all increased with an increase in scale (p < 0.05). There was a significant increase in the development of post-operative fever, and post-operative hospital stay as the scale increased (p < 0.05). The Tukey-Kramer test for all pair-wise comparisons revealed that each grade was significantly different from each other (p < 0.05) on the difficulty of surgery except for grade 4 from 5. CONCLUSION: Parkland Grading Scale system is a reliable intra-operative grading system to assess the difficulty in laparoscopic cholecystectomy and helps the surgeon to change the strategy of surgery. An increase in scale is associated with an increased difficulty level of the surgery.

Machine learning intelligence to assess the shear capacity of corroded reinforced concrete beams.

The ability of machine learning (ML) techniques to forecast the shear strength of corroded reinforced concrete beams (CRCBs) is examined in the present study. These ML techniques include artificial neural networks (ANN), adaptive-neuro fuzzy inference systems (ANFIS), decision tree (DT) and extreme gradient boosting (XGBoost). A thorough databank with 140 data points about the shear capacity of CRCBs with various degrees of corrosion was compiled after a review of the literature. The inputs parameters of the implemented models are the width of the beam, the effective depth of the beam, concrete compressive strength (CS), yield strength of reinforcement, percentage of longitudinal reinforcement, percentage of transversal reinforcement (stirrups), yield strength of stirrups, stirrups spacing, shear span-to-depth ratio (a/d), corrosion degree of main reinforcement, and corrosion degree of stirrups. The coefficient of determination of the ANN, ANFIS, DT, and XGBoost models are 0.9811, 0.9866, 0.9799, and 0.9998, respectively. The MAPE of the XGBoost model is 99.39%, 99.16%, and 99.28% lower than ANN, ANFIS, and DT models. According to the results of the sensitivity examination, the shear strength of the CRCBs is most affected by the depth of the beam, stirrups spacing, and the a/d. The graphical displays of the Taylor graph, violin plot, and multi-histogram plot additionally support the XGBoost model's dependability and precision. In addition, this model demonstrated good experimental data fit when compared to other analytical and ML models. Accurate prediction of shear strength using the XGBoost approach confirmed that this approach is capable of handling a wide range of data and can be used as a model to predict shear strength with higher accuracy. The effectiveness of the developed XGBoost model is higher than the existing models in terms of precision, economic considerations, and safety, as indicated by the comparative study.

Enhancing Sustainability of Corroded RC Structures: Estimating Steel-to-Concrete Bond Strength with ANN and SVM Algorithms.

The bond strength between concrete and corroded steel reinforcement bar is one of the main responsible factors that affect the ultimate load-carrying capacity of reinforced concrete (RC) structures. Therefore, the prediction of accurate bond strength has become an important parameter for the safety measurements of RC structures. However, the analytical models are not enough to estimate the bond strength, as they are built using various assumptions and limited datasets. The machine learning (ML) techniques named artificial neural network (ANN) and support vector machine (SVM) have been used to estimate the bond strength between concrete and corroded steel reinforcement bar. The considered input parameters in this research are the surface area of the specimen, concrete cover, type of reinforcement bars, yield strength of reinforcement bars, concrete compressive strength, diameter of reinforcement bars, bond length, water/cement ratio, and corrosion level of reinforcement bars. These parameters were used to build the ANN and SVM models. The reliability of the developed ANN and SVM models have been compared with twenty analytical models. Moreover, the analyzed results revealed that the precision and efficiency of the ANN and SVM models are higher compared with the analytical models. The radar plot and Taylor diagrams have also been utilized to show the graphical representation of the best-fitted model. The proposed ANN model has the best precision and reliability compared with the SVM model, with a correlation coefficient of 0.99, mean absolute error of 1.091 MPa, and root mean square error of 1.495 MPa. Researchers and designers can apply the developed ANN model to precisely estimate the steel-to-concrete bond strength.

Acceptance and hesitancy of COVID-19 vaccine among Nepalese population: A cross-sectional study.

INTRODUCTION: COVID-19 is an emerging infectious disease with a high transmission rate and substantial deaths. Various vaccines have been developed to combat it. This study is aimed to assess COVID-19 vaccine acceptance and hesitancy among the Nepalese population through a web-based survey. MATERIALS AND METHODS: This is a web-based cross-sectional descriptive study of Nepalese people 18 years and above from different regions of Nepal who use social media (Facebook, Twitter, Reddit) as well as instant messaging applications (Messenger, Viber, WhatsApp). The duration of the study was 3 months from 1st June 2021 to 31st August 2021. The sampling technique used was self-selected non-probability sampling. A validated questionnaire had been taken to record the data. RESULTS: A total of 307 participants were included in the study. About three-fourths of participants 231 (75.2%) had not been vaccinated while 76 (24.8%) had been vaccinated with COVID -19 vaccine. Out of 231 non-vaccinated participants, most of participants 213 (92.2%) had shown acceptance of the COVID-19 vaccine. More than two-thirds of participants believed that the vaccine would protect them, their family members, and the community from having COVID-19 in the future. Very few participants 18 (7.2%) were hesitant to receive the vaccine against COVID-19. About two-thirds of participants were being afraid of adverse effects of the COVID-19 vaccine while more than half of participants hesitated due to lack of enough information regarding COVID-19 vaccine. CONCLUSION: This study can aid in the planning of vaccination campaigns and the direction of future public health efforts aimed at increasing COVID-19 vaccine uptake.

Case of Botryoid Rhabdomyosarcoma Mimicking Biliary Hydatid Disease.

Hepatobiliary rhabdomyosarcoma (RMS) is a soft tissue malignant musculoskeletal tumor of the biliary tract. It is rare tumor, mostly seen in children and mimics common benign biliary condition. Here, we present a case of 1 year 9 months child of biliary RMS who presented with obstructive jaundice and diagnosed after biopsy. This case highlights the unusual childhood malignancy of bile duct RMS in obstructive jaundice with atypical imaging findings.

Open Cholecystectomy among Patients undergoing Laparoscopic Cholecystectomy in a Tertiary Care Centre: A Descriptive Cross-sectional Study.

Introduction: In the current era, laparoscopic cholecystectomy is the treatment of choice for symptomatic gallstone disease. The aim of this study is to find out the prevalence of open cholecystectomy among patients undergoing laparoscopic cholecystectomy in a tertiary care centre. Methods: It is a descriptive cross-sectional study done among 345 patients at the Department of Surgery of a tertiary care centre from June, 2020 to May, 2021 after receiving ethical clearance from the Institutional Review Committee (Reference number: CMC-IRC/0770798-271). Convenience sampling was done. Successive patients who underwent elective laparoscopic cholecystectomy during the study period were included. Standard 4 port laparoscopic technique was used for the laparoscopic cholecystectomy and sub-costal Kocher incision was used for the open cholecystectomy respectively. After data collection, entry and analysis were done in Microsoft Excel. Point estimate at a 95% Confidence Interval was calculated along with frequency and percentages for binary data. Results: Out of 345 patients, the prevalence of open cholecystectomy among patients undergoing laparoscopic cholecystectomy was 6 (1.73%) (0.35-3.11 at a 95% Confidence Interval). Conclusions: This study showed that the prevalence of open cholecystectomy among patients undergoing laparoscopic cholecystectomy was lower when compared to similar studies conducted in similar settings. Keywords: cholecystectomy; cholelithiasis; laparoscopic cholecystectomy.