bluuebunny/crossref_metadata_2025_split huggingface dataset:
Covid-19 Vaccines Available in India
Authors: Mukim Mohammad , Sharma Pratishtha , Patweker Mohsina , Patweker Faheem , Kukkar Rajiv , Patel Rakesh 
Published: March 2022

Abstract:
The present review covers the list of approved vaccines available in India, i.e., Covaxin,
Covishield, and Sputnik-V. Covaxin’s code name is BBV152. Covaxin was prepared by Hyderabad-
based Bharat Biotech International Ltd. in collaboration with the National Institute of Virology
(NIV) and ICMR. The effectiveness of Covaxin was found to be 78-81%. Covishield, which is
available by code name AZD1222, was developed by the SII, Oxford University, and AstraZeneca.
Covishield’s effectiveness was found to be 90%. The time gap between the two doses of Covaxin and
Covishiled is 4-6 weeks and 12-16 weeks, respectively. One more vaccine, i.e., Sputnik V, by the
code name rAd26-S and rAd5-S, was developed by Gamaleya Research Institute of Epidemiology
and Microbiology, which involves an interval gap of 21 days between the two doses. Covaxin releases
Anti-SARS-CoV-2 IgG, which is specific to RBD (receptor-binding domain) protein, whereas a
high degree of antibody response dissipates on the 28th day of vaccination. The protective efficacy of
Sputnik-V was found to be ±92.2% (95% CI ±82.6-92.3), while that of Covishield was found to be
±90 % (95% CI 68.2-98.0±, p = 0.01) 2-standard dose: (61.2%, 95% CI 42.2-76.1±). In the case of
Covaxin, the rate of seroconversion was found to be 93.9% (95% CI 85.2-98.2) in the 3-μg group and
97.2% (95% CI 93.1-105.1) in the 6-μg group. No significant difference was observed in local or systemic
adverse reactions of the vaccine in the groups of 3 μg and 6 μg. The protective efficacious dose
of Covaxin has not yet been identified. The cellular response median SFCs PBPMC of Covishield at
the standard dose in the age group of 18-55 years was found to be±1201; 55-70 years: ±758 and ≥75
years: ±975. No significant increase was observed in the per million peripheral mononuclear cells
(PBPMC) after administration of the booster dose of Covishield vaccine (p = 0.45 in paired student’s
t-test on the 28th day vs. the 42nd day). The cellular response to Sputnik V was found to be 100%.
Higher levels of T cells CD8+, CD4+ T cells, and IFN- γ secretion were reported in all volunteers
who had undergone vaccination. Cell proliferation was found as follows: CD4+: +1.5% and CD8+ :
+1.3% in the lyophilized formulation and CD4+ : + 2.6% and CD8+ : +1.5% in the frozen formulation.
Antigen-specific IgG geometric mean titer (GMT) levels of Covishield were found to be highest
on the 28th day with 160 geometric mean ELISA units (GMEU).
A Study on the Impact of Sentiment Analysis on Stock Market Prediction
Authors: Dhanasekaren Kiran , Aluri Sri Teja , Karthikeyan Neeraj , Baskaran Saravanan Hari , Selvanambi Ramani 
Published: March 2022

Background:
Investors estimate how a company's stock or financial instrument will
perform in the future, which is known as the stock market prediction. Stock markets are one of
the many industries that have benefited substantially from the incredible breakthroughs in
machine learning. To effectively estimate these markets, many researchers and companies are
continually researching and developing various state-of-the-art approaches and algorithms.

Objective:
The objective is to predict stock prices based on public sentiments. With a big
collection of data from microblogging sites like Twitter, it is possible to analyse the thoughts or
feelings of users on a wide scale. These sentiments play a major part in the way the stock market
works. We review multiple papers and provide the advantages and disadvantages of various
methods.

Method:
An in-depth examination of the most recent methodologies for predicting stock market
values using sentiment analysis is offered, as well as the multiple consequences for stock markets
when epidemics or major events occur.

Results:
According to the findings, impact sentiment analysis has a significant part in predicting
stock market price movement, allowing for greater profit.

Conclusion:
With modern machine learning and deep learning processes, we can forecast stock
costs with a few degrees of precision. This research examines how stock expectations have
changed over time, as well as the most recent and effective technique for forecasting, supplying,
and minimizing speculators' losses.
TAXPAYER COMPLIANCE AND TAX AMNESTY; DOES TAX AMNESTY WORK?
Authors: Ardiansyah Riyans , Sudarma Made , Djamhuri Ali , Andayani Wuryan 
Published: March 2022

This study aimed to analyze tax amnesty from the perspective of taxpayers, such as large-scale entrepreneurs, small-scale entrepreneurs, private company employees, tax consultants, and lecturers, and assessing whether tax amnesty can increase taxpayer compliance.Â This study used an interpretive paradigm and transcendental phenomenology. The interpretive paradigm aims to understand and explain the social world from a personal perspective. Transcendental phenomenology is a suitable method to analyze the experience of informants after joining the tax amnesty policy.Â Based on the results of the study, it can conclude several findings. First, taxpayers participate in tax amnesty because they want to report all assets without being penalized; second, taxpayers want to get a low tax rate. Third, taxpayers want to avoid tax audits. The analysis of transcendental phenomenology concluded that tax amnesty could increase taxpayer compliance but not for a long time.
Pengembangan Media Pembelajaran Biologi Berbasis Foto untuk Guru Biologi SMA di Daerah Istimewa Yogyakarta
Authors: Wibowo Yuni , Subiantoro Agung Wijaya , Handziko Rio Christy 
Published: March 2022

Media belajar merupakan instrumen untuk meningkatkan kualitas proses pembelajaran. Media belajar yang banyak digunakan guru biologi antara lain gambar dan foto. Disisi lain saat ini kemajuan teknologi memungkinkan individu memiliki alat fotografi yang dapat digunakan untuk memproduksi foto yang baik. Program pengabdian pada masyarakat ini bertujuan untuk meningkatkan kemampuan dan kompetensi guru dalam memproduksi media pembelajaran berupa foto. Kegiatan berupa pelatihan/workshop fotografi biologi. Kegiatan dibagi menjadi 3 acara yaitu: 1) penyampaian materi konsep dasar fotografi biologi dan teknik-teknik pengambilan foto biologi, 2) penugasan pengambilan/hunting foto objek biologi dilingkungan sekitar, dan 3) pengemasan foto objek biologi dalam media pembelajaran. Kegiatan workshop diikuti oleh 13 guru biologi dari MGMP DIY yang berasal dari Kabupaten/Kota di DIY. Tampak peserta workshop telah memahami konsep dasar fotografi biologi. Peserta telah memiliki sensitivitas terhadap objek dan fenomena biologi dilingkungan sekitar yang dapat digunakan sebagai media pembelajaran.Kata kunci: fotografi biologi, objek biologi, media pembelajaran.
A Machine Learning Approach to Predict the Outcome of Urinary Calculi Treatment Using Shock Wave Lithotripsy: Model Development and Validation Study
Authors: Moghisi Reihaneh , El Morr Christo , Pace Kenneth T , Hajiha Mohammad , Huang Jimmy 
Published: March 2022

Background
Shock wave lithotripsy (SWL), ureteroscopy, and percutaneous nephrolithotomy are established treatments for renal stones. Historically, SWL has been a predominant and commonly used procedure for treating upper tract renal stones smaller than 20 mm in diameter due to its noninvasive nature. However, the reported failure rate of SWL after one treatment session ranges from 30% to 89%. The failure rate can be reduced by identifying candidates likely to benefit from SWL and manage patients who are likely to fail SWL with other treatment modalities. This would enhance and optimize treatment results for SWL candidates.

Objective
We proposed to develop a machine learning model that can predict SWL outcomes to assist practitioners in the decision-making process when considering patients for stone treatment.

Methods
A data set including 58,349 SWL procedures performed during 31,569 patient visits for SWL to a single hospital between 1990 and 2016 was used to construct and validate the predictive model. The AdaBoost algorithm was applied to a data set with 17 predictive attributes related to patient demographics and stone characteristics, with success or failure as an outcome. The AdaBoost algorithm was also applied to a training data set. The generated model’s performance was compared to that of 5 other machine learning algorithms, namely C4.5 decision tree, naïve Bayes, Bayesian network, K-nearest neighbors, and multilayer perceptron.

Results
The developed model was validated with a testing data set and performed significantly better than the models generated by the other 5 predictive algorithms. The sensitivity and specificity of the model were 0.875 and 0.653, respectively, while its positive predictive value was 0.7159 and negative predictive value was 0.839. The C-statistics of the receiver operating characteristic (ROC) analysis was 0.843, which reflects an excellent test.

Conclusions
We have developed a rigorous machine learning model to assist physicians and decision-makers to choose patients with renal stones who are most likely to have successful SWL treatment based on their demographics and stone characteristics. The proposed machine learning model can assist physicians and decision-makers in planning for SWL treatment and allow for more effective use of limited health care resources and improve patient prognoses.
Patients’ Experiences of Using an eHealth Pain Management Intervention Combined With Psychomotor Physiotherapy: Qualitative Study
Authors: Eiken Anne-Grethe , Nordanger Dag Ø , Solberg Nes Lise , Varsi Cecilie 
Published: March 2022

Background
Chronic pain is a major health challenge to those affected. Blended care with psychomotor physiotherapy (PMP) combined with eHealth self-management might be beneficial.

Objective
This study aims to explore how patients with chronic pain experience the combination of PMP and the use of EPIO, an eHealth self-management intervention for chronic pain.

Methods
Individual semistructured interviews were conducted with 5 adult patients with chronic pain (ie, participants) who used EPIO in combination with PMP over a period of 10 to 15 weeks. Interviews explored participants’ experiences using this treatment combination in relation to their pain and analyzed their experiences using systematic text condensation.

Results
Participants described having benefited from using EPIO in combination with PMP in terms of increased awareness of bodily signals and how pain was related to stress and activity. They also described changes in the relationship to themselves in terms of increased self-acceptance, self-assertion, and hope and their relationship to their pain in terms of seeing pain as less harmful and engaging in more active coping strategies.

Conclusions
Results indicate that a blended care approach combining eHealth self-management interventions such as EPIO with PMP may be of value to patients living with chronic pain.

Trial Registration
ClinicalTrials.gov NCT03705104; https://clinicaltrials.gov/ct2/show/NCT03705104
Assessing the Availability of Teleconsultation and the Extent of Its Use in Malaysian Public Primary Care Clinics: Cross-sectional Study
Authors: Ng Sock Wen , Hwong Wen Yea , Husin Masliyana , Ab Rahman Norazida , Nasir Nazrila Hairizan , Juval Kawselyah , Sivasampu Sheamini 
Published: March 2022

Background
The integration of teleconsultation into health care systems as a complement to existing approaches to care is growing rapidly. There is, however, limited information on the extent of its implementation across low- and middle-income countries.

Objective
The aim of this study was to determine the availability and the extent of teleconsultation in Malaysian primary care clinics.

Methods
A cross-sectional study of public primary care clinics in Malaysia was conducted between November 2020 and December 2020. All clinics in Malaysia that see more than 300 daily patients were recruited. A web-based, self-administered questionnaire including questions on availability of the service, whether it uses video or telephone, and the types of services it provides was distributed to the medical officer in charge of each clinic.

Results
In total, 97.6% (249/255) of the clinics responded. Out of these clinics, 45.8% (114/249) provided teleconsultation. A majority of the clinics providing consultation (69/114, 60.5%) provided only telephone consultation, while 24.6% (28/114) of the clinics offered video and telephone consultation, and 14.9% (17/114) offered only video consultation. Eighty percent (92/114) of the clinics were located in urban areas. A breakdown by state showed that 17.5% (20/114) and 16.7% (19/114) of the clinics were from two larger states; other states comprised less than 10% each (range 7-9/114). For the clinics providing video consultation, funding for the service came mostly (42/45, 93%) from the Ministry of Health. Conversely, nearly 1 out of 4 (23/97) clinics that provided telephone consultation funded the service either from donations or through self-funding. Most of the clinics provided teleconsultation for diabetes and hypertension. Less than 50% of the clinics with teleconsultation used it for follow up with allied health care providers or pharmacists (video consultation, 20/45; telephone consultation, 36/97).

Conclusions
Our findings show that telephone consultation is more widely used than video consultation, despite a quarter of its funding being self-subsidized or obtained through donations. Also, teleconsultation was less utilized by allied health care providers and pharmacists. Plans for the expansion of teleconsultation in Malaysian primary health care should take into consideration these findings to ensure a better and more cost-effective implementation of the service.
Access to and Use of Mobile Phone by Postpartum, Married Women in Punjab, India: Secondary Analysis of mHealth Intervention Pilot Data
Authors: Pendse Ruchita S , El Ayadi Alison M , Sharma Preetika , Ahuja Alka , Hosapatna Basavarajappa Darshan , Duggal Mona , Kankaria Ankita , Singh Pushpendra , Kumar Vijay , Bagga Rashmi , Diamond-Smith Nadia G 
Published: March 2022

Background
As mobile phone uptake in India continues to grow, there is also continued interest in mobile platform–based interventions for health education. There is a significant gender gap in mobile phone access—women’s access to mobile phones is constrained by economic and social barriers. Pregnancy and postpartum care is one of many targets for mobile health (mHealth) interventions that particularly rely upon women’s access to and facility with mobile phone use.

Objective
We aimed to describe the dynamics and patterns of married pregnant and postpartum women’s mobile phone access and use (among both phone owners and nonowners) who participated in an mHealth postpartum care intervention and to identify potential barriers to their participation in mobile platform–based interventions.

Methods
A secondary analysis was performed on mixed methods data obtained for a pilot mHealth intervention for postpartum care of mothers in rural Punjab from July 2020 to February 2021. Two formative sources included exploratory in-depth interviews among postpartum women (n=20; 1-3 months postpartum) and quantitative maternal health survey among women who were pregnant or who had recently given birth (n=102). We also utilized mixed methods intervention assessment data from early postpartum women who participated in the pilot intervention (n=29), including intervention moderator perspectives. Qualitative and quantitative analyses were performed, and pertinent findings were grouped thematically.

Results
The majority of women owned a phone (maternal health survey: 75/102, 74%; demographic survey: 17/29, 59%), though approximately half (53/102, 52%) still reported sharing phones with other family members. Sharing a phone with female family members typically allowed for better access than sharing with male family members. Some households had strict preferences against daughters-in-law having phones, or otherwise significantly restricted women’s phone access. Others reported concerns about phone use–related health hazards for mother and infant during the pregnancy or postpartum period.

Conclusions
These findings suggest nuance regarding what is meant by women’s phone ownership and access—there were numerous additional constraints on women’s use of phones, particularly during pregnancy and the postpartum period. Future research and mHealth interventions should probe these domains to better understand the dynamics governing women’s access, use, and fluency with mobile phones to optimally design mHealth interventions.
The Effects of Using the Sun Safe App on Sun Health Knowledge and Behaviors of Young Teenagers: Results of Pilot Intervention Studies
Authors: Clare Isabelle M , Gamage Nisali , Alvares Gail A , Black Lucinda J , Francis Jacinta , Jaimangal Mohinder , Lucas Robyn M , Strickland Mark , White James , Nguyen Rebecca , Gorman Shelley 
Published: March 2022

Background
A balanced approach toward sun exposure and protection is needed by young people. Excessive sun exposure increases their risk for skin cancers such as melanoma, whereas some exposure is necessary for vitamin D and healthy bones. We have developed a new iOS smartphone app—Sun Safe—through a co-design process, which aims to support healthy and balanced decision-making by young teenagers (aged 12-13 years).

Objective
The aim of this study was to test the capacity of Sun Safe to improve sun health knowledge and behaviors of young teenagers in 3 pilot intervention studies completed in 2020.

Methods
Young teenagers (aged 12-13 years; N=57) were recruited through the web or through a local school via an open-access website and given access to Sun Safe (29/57, 51%) or a placebo (SunDial) app (28/57, 49%). Participants completed sun health questionnaires and knowledge quizzes before and after the 6-week intervention (either on the web or in class) and rated the quality of the app they used via a survey.

Results
Of the 57 participants, 51 (89%) participants (26, 51% for placebo arm and 25, 49% for the Sun Safe arm) completed these studies, with most (>50%) reporting that they used a smartphone to access their designated app either “once a fortnight” or “once/twice in total.” Improved sun health knowledge—particularly about the UV Index—was observed in participants who were given access to Sun Safe compared with those who used the placebo (−6.2 [percentage correct] difference in predicted means, 95% CI –12.4 to –0.03; P=.049; 2-way ANOVA). Unexpectedly, there were significantly more sunburn events in the Sun Safe group (relative risk 1.7, 95% CI 1.1-1.8; P=.02; Fisher exact test), although no differences in time spent outdoors or sun-protective behaviors were reported. COVID-19 pandemic–related community-wide shutdowns during April 2020 (when schools were closed) reduced the time spent outdoors by >100 minutes per day (–105 minutes per day difference in predicted means, 95% CI –150 to –59 minutes per day; P=.002; paired 2-tailed Student t test). Sun Safe was well-rated by participants, particularly for information (mean 4.2, SD 0.6 out of 5).

Conclusions
Access to the Sun Safe app increased sun health knowledge among young teenagers in these pilot intervention studies. Further investigations with larger sample sizes are required to confirm these observations and further test the effects of Sun Safe on sun-protective behaviors.
A Machine Learning Approach to Predict the Outcome of Urinary Calculi Treatment Using Shock Wave Lithotripsy: Model Development and Validation Study (Preprint)
Authors: Moghisi Reihaneh , El Morr Christo , Pace Kenneth T , Hajiha Mohammad , Huang Jimmy 
Published: March 2022

BACKGROUND

Shock wave lithotripsy (SWL), ureteroscopy, and percutaneous nephrolithotomy are established treatments for renal stones. Historically, SWL has been a predominant and commonly used procedure for treating upper tract renal stones smaller than 20 mm in diameter due to its noninvasive nature. However, the reported failure rate of SWL after one treatment session ranges from 30% to 89%. The failure rate can be reduced by identifying candidates likely to benefit from SWL and manage patients who are likely to fail SWL with other treatment modalities. This would enhance and optimize treatment results for SWL candidates.

OBJECTIVE

We proposed to develop a machine learning model that can predict SWL outcomes to assist practitioners in the decision-making process when considering patients for stone treatment.

METHODS

A data set including 58,349 SWL procedures performed during 31,569 patient visits for SWL to a single hospital between 1990 and 2016 was used to construct and validate the predictive model. The AdaBoost algorithm was applied to a data set with 17 predictive attributes related to patient demographics and stone characteristics, with success or failure as an outcome. The AdaBoost algorithm was also applied to a training data set. The generated model’s performance was compared to that of 5 other machine learning algorithms, namely C4.5 decision tree, naïve Bayes, Bayesian network, K-nearest neighbors, and multilayer perceptron.

RESULTS

The developed model was validated with a testing data set and performed significantly better than the models generated by the other 5 predictive algorithms. The sensitivity and specificity of the model were 0.875 and 0.653, respectively, while its positive predictive value was 0.7159 and negative predictive value was 0.839. The C-statistics of the receiver operating characteristic (ROC) analysis was 0.843, which reflects an excellent test.

CONCLUSIONS

We have developed a rigorous machine learning model to assist physicians and decision-makers to choose patients with renal stones who are most likely to have successful SWL treatment based on their demographics and stone characteristics. The proposed machine learning model can assist physicians and decision-makers in planning for SWL treatment and allow for more effective use of limited health care resources and improve patient prognoses.