bluuebunny/crossref_metadata_2025 huggingface dataset:
Using SPI and SPEI for baseline probabilities and seasonal drought prediction in two agricultural regions of the Western Cape, South Africa
Authors: SN Theron  , E Archer  , CJ Engelbrecht  , S Midgley  , S Walker
Published: April 2023

Drought is one of the most hazardous natural disasters in terms of the number of people directly affected. An important characteristic of drought is the prolonged absence of rainfall relative to the long-term average. The intrinsic persistence of drought conditions continuing from one month to the next can be utilized for drought monitoring and early warning systems. This study sought to better understand drought probabilities and baselines for two agriculturally important rainfall regions in the Western Cape, South Africa – one with a distinct rainfall season and one which receives year-round rainfall. The drought indices, Standardised Precipitation and Evapotranspiration Index (SPEI) and Standardised Precipitation Index (SPI), were assessed to obtain predictive information and establish a set of baseline probabilities for drought. Two sets of synthetic time-series data were used (one where seasonality was retained and one where seasonality was removed), along with observed data of monthly rainfall and minimum and maximum temperature. Based on the inherent persistence characteristics, autocorrelation was used to obtain a probability density function of the future state of the various SPI start and lead times. Optimal persistence was also established. The validity of the methodology was then examined by application to the recent Cape Town drought (2015–2018). Results showed potential for this methodology to be applied in drought early warning systems and decision support tools for the province.
Representações sociais de psicoterapia on-line para psicólogos clínicos na pandemia Covid-19
Authors: Vidal Gabriela Pereira , Brito Annie Mehes Maldonado , Castro Amanda
Published: April 2023

INTRODUÇÃO: Os serviços tecnológicos tiveram um crescimento exponencialmente acelerado nos últimos anos, principalmente com a chegada da pandemia coronavírus. Entre esses serviços estão aqueles relacionados à saúde, como a psicoterapia online. OBJETIVO: Esse estudo buscou compreender as representações sociais associadas ao atendimento online pelos psicólogos clínicos. MÉTODO: Utilizou-se como instrumentos: 1) teste de associação livre de palavras para investigação das representações sociais da psicoterapia on-line; 2) questionário semiestruturado para investigação das práticas sociais e atitudes relativas ao objeto; 3) questionário contendo questões de caracterização dos participantes e itens sobre o posicionamento atitudinal frente ao objeto. RESULTADOS E DISCUSSÃO: Os participantes foram 151 psicólogos residentes no Brasil, acessados pela técnica snowball. Para análise utilizou-se os softwares SPSS, EVOC 2000 e IRaMuTeQ. Como resultados pode-se destacar a representação social da psicoterapia online muito relacionada a aspectos de facilidade, acesso e conexão, que parecem estar relacionadas a possibilidades de alcance de alguns grupos sociais, atrelados ao vínculo e acolhimento necessários neste serviço. Estas representações parecem também como ancoradas nas de psicoterapia presencial. CONCLUSÃO: Conclui-se que no momento desta pesquisa os profissionais estavam voltados à adaptação da psicoterapia presencial para a psicoterapia on-line e destaca-se a importância da ampliação dos conhecimentos sobre esse novo setting psicoterapêutico.
The Effects of Online Physical Activity During Covid-19 Pandemic among Undergraduate Students in Thailand
Authors: Hemarachatanon Poramet , Nuttouch Wattana , Weerawong Neeranoot , Huntula Soontaraporn
Published: April 2023

Study purpose. The purpose of this study was to develop a physical activity program by using resistance band for students to improve physical activity and monitor improvements in physical performance. The university students’physical activity, which was still low before the pandemic, may be impacted by these. As a result, we want to incorporate physical activity into our course and assess the differences in physical performance before and after taking the course.
Materials and methods. 95 undergraduate college students signed up to take the course. The online course, which included resistance band training for a total of 12 weeks, addressed the principles of resistance band training/exercise. The physical performance of the participants was assessed both before and after training.
Results. According to our study findings, university students at Walailak University can increase their physical performance by using an online resistance band training. The physical fitness statistics for the wall sit test, sit up test, sit and reach test, and shuttle run test were significantly different before and after the online elastic band intervention (p=0.0463, p=0.0050, and p=0.0430, respectively), but not for the shuttle run or YMCA 3-minute step test.
Conclusions. The results of this study provide proof that resistance band training improves strength and encourages physical activity. In order to reduce anxiety and depression, which the COVID-19 has severely touched, as well as to increase the population’s level of physical activity or exercise, we must continually promote physical activity or exercise at home.
Evaluation of the Correlation Between Strength and Special Training Indicators in Mixed Martial Arts
Authors: Chernozub Andrii , Olkhovyi Oleh , Aloshyna Alla , Savenko Andrii , Shtefiuk Ivan , Marionda Ivan , Khoma Tetiana , Tulaydan Victoriya
Published: April 2023

Study purpose. To study the peculiarities of correlation between the maximum strength development and quantity of kicks in MMA using load regimes of different intensity and energy supply.
Materials and methods. 75 athletes aged 19±0.7 practicing MMA for 4±0.8 years were examined and divided into 3 groups. During 12 weeks, group 1 athletes used low-intensity (Rа=0.53) load regime, group 2 – medium-intensity (Rа=0.65) and group 3 – high-intensity (Ra=0.72). The control of attacking kicks (front kick, reverse side kick, roundhouse kick) quantity with maximum force until full muscle fatigue for 20 s allowed to check special training. The level of strength training was evaluated by estimating the maximum strength development (1 RM) indicators. Non-parametric methods of mathematical statistics were used for data processing.
Results. The indicators of special training showed the greatest increase by an average of 13.2% in group 3 athletes during 12 weeks. In the other two groups, the dynamics of the controlled indicator was 3.2 times smaller for a similar period of time. The maximum muscle strength indicator increased by 41.9% in group 3 athletes compared to the initial data. These changes are on average 1.5 times higher than the results recorded in athletes of groups 1 and 2. Despite the revealed growth of strength and special training indicators in MMA athletes, there was no strong correlation between them in any research group.
Conclusions. Using high-intensity load regime in conditions of anaerobic-alactate mode of energy supply allowed achieving the greatest results in strength and special training indicators. However, the study did not show correlation between the increase in maximum strength development and quantitative indicators of attacking kicks. Further research will be focused on searching for more informative markers for assessing the training of athletes in MMA and adaptation processes using biochemical control methods.
Comparative advantage of improved feed trough and the traditional feeding material for efficient utilization of crop residue at small-scale farmers in Northwestern Tigray, Ethiopia
Authors: Teklemariam Abadi , Kibrom Gebremedhin , Desale Gebretsadik , Daniel Desta
Published: April 2023

The study was conducted to reduce the high feed wastage by practicing the improved feed trough in the study area. The trail was conducted at Tahtay Koraro district Northwestern zone of Tigray, Ethiopia. Improved feed trough was constructed on a total of 20 interested farmers. Both quantitative and qualitative data were collected andanalyzed using descriptive statistics. The result showed that the improved feed troughs reduced feed waste significantly in the study area. That is 4.13% and 25% feed loss respectively in improved and traditional feed troughs. The result from the farmers perception also shows that, the farmers were preferred the technology in its less feed wastage, reduces feed contamination, gives an opportunity for persons to do other task than keeping animals, comfortable for the animals, reduces feed competition among the animals; and protects the feed from rain and sun. But farmers are less preferred the technology in its cost for its construction. Therefore, based on the result it is recommended that the technology has to be popularized and promoted to the large number of the farmers of the area for the efficient crop residue utilization.
来华留学生学习成语分析
Authors: Mardiana Ade Prima
Published: April 2023

Abstract: Idioms are an important part of Chinese culture. Basic understanding of Chinese idioms, explaining that Chinese idioms have gradually grown with the development of Chinese traditional culture. This paper used method an questionnaire to collect data. The finding and discussion analysis of survey results is about examines the learning and use of idioms, and then proposes specific solutions through problems. And the conclusion is the cultivation of students' learning methods in the teaching of Chinese idioms.

摘要: 成语是汉语文化的重要组成部分。本文一共四个部分，第一部分：汉语成语的基本认识，该部分说明了汉语成语是随着汉语传统文化发展逐渐丰富起来的；第二部分：调查的基本情况，外国人和中国人交流之所以会出现误解，造成误解的原因主要是不了解成语的深刻含义；第三部分：调查结果分析，本论文只是对汉语成语学习和使用情况进行调查，然后通过问题提出具体的解决办法。第四部分：教学策略，即在教学汉语成语过程中对学生学习方法的培养。
非目的语环境下汉语课堂学习焦虑调查：以马来西亚非华裔生为例
Authors: Ling Ting Hie , Qi Chong Pei
Published: April 2023

本文采用Horwitz等人（1986）设计的外语学习焦虑量表， 简称FLCAS （Foreign Language Classroom Anxiety Scale）作为研究工具，对非目的语环境下学习汉语的221名非华裔生进行汉语课堂学习焦虑研究。此221名非华裔生均来自马来西亚砂拉越玛拉工艺大学选修《基础华语》课的学习者。在问卷收集完善后，采用SPSS 22.0作为数据统计工具，对非华裔生的汉语学习焦虑程度、汉语学习焦虑三个维度与性别差异进行数据分析。分析结果显示，非华裔生在汉语课堂普遍经历学习焦虑。通过独立样本T检验结果发现，非华裔生汉语课堂学习焦虑与性别差异的相关性并不显著。

This study adopted Foreign Language Classroom Anxiety Scale (FLCAS) designed by Horwitz et al (1986) to determine Mandarin as foreign language learning anxiety among 221 non-native Mandarin learners in non-target language context. These 221 non-native Mandarin learners were those who enrolled in Introductory Mandarin Language course from University Teknologi MARA, Sarawak Branch. SPSS 22.0 was employed to analyze the data such as non-native Mandarin learners’level of anxiety and gender differences. Findings from this study revealed that non-native Mandarin learners are at moderate level of anxiety. Results from independent T-test analysis shows that there were no significant differences between learners’ level of anxiety and gender.
Comparative Analysis of Hepatitis C Using Decision Tree Classifier and Artificial Neural Network Classifier
Authors: Sravanthi D. , Rani D.J.
Published: April 2023

Aim: The goal of this study is to compare the accuracy, sensitivity, and specificity of a Decision tree classifier and ANN classifier in detecting Innovative Hepatitis C Detection using modern methodologies. Materials and Methods: The data for this study was collected via the kaggle website. Samples were considered as (N=22) for Decision tree and (N=22) for ANN according to clinicalc.com, by keeping alpha error-threshold value 0.05, enrollment ratio as 0.1, 95% confidence interval,G power as 80%, total sample size calculated. The accuracy, sensitivity, and specificity were calculated using MATLAB and a standard data set. Results: Comparison of accuracy, sensitivity, and specificity is done by independent sample t-test SPSS software. There is a statistically insignificant difference between Decision Tree Classifier and Artificial Neural Network Classifiers. The Decision Tree with p=0.003, p<0.05-accuracy (0.41%), p=0.003, p<0.05-sensitivity (0.41%), p=0.570, p>0.05-specificity (0.42%) showed better results in comparison to ANN. Conclusion: Decision Tree showed better accuracy, sensitivity, and specificity than ANN to predict Innovative Hepatitis C Detection in a faster way.
An Enhanced Prediction Model For Autism Spectrum Disorder
Authors: Amarnath J.J. , Meera S.
Published: April 2023

Autism spectrum disorder (ASD) is a behavioural condition that affects the child’s social interaction, communication, and behaviour. The early identification of ASD is critical for the effective and timely therapies. This study presents an enhanced prediction model for Autism Spectrum Disorder (ASD). It is based on facial features extracted from the face image. Mallat’s multi-resolution algorithm is employed in this work for extracting facial features. Two distance based classifiers such as Euclidean Distance Classifier (EDC) and Absolute Distance Classifier (ADC) are employed for the ASD prediction. The proposed ASD prediction system is evaluated on face images of autistic and non-autistic children. The database is obtained from the Kaggle data repository. A total of 2940 facial images (1470 autistic and 1470 non-autistic) are employed for performance analysis. Experimental results show that the proposed ASD prediction system provides promising results with an accuracy of 97.01% by EDC and 96.87% by ADC classifiers. Keywords Autism spectrum disorder, Computer aided diagnosis, Machine learning, Image based diagnosis, Prediction system.
Inhalation Health Risk Assessment of Some of Heavy Metals for Kerosene Samples in Iraq Market
Authors: Wadi S.N. , Pasha M.A. , Abojassim A.A.
Published: April 2023

In this study, five heavy metals (Zn, Fe, Pb, Cu, and Cd) concentrations were measured in samples of kerosene (locally only) that collected from different of warehouses oils in Iraq. The measurements have been done using Atomic Absorption Spectrophotometer. Non-cancer risks such as the chronic daily inhalation intake (CDIinh), a Hazard Quotient (HQ), and Hazard Index (HI) as well as Cancer Risks (CR) due to inhalation of heavy metals in the kerosene samples were calculated. The results show that, the average values of concentrations in unit ppm (mg/kg) belonging to Zn, Fe, Pb, Cu, and Cd in kerosene samples were 8.14±1.74, 0.127±0.025, 0.017±0.007, 0.15±0.064, and 0.360±0.022, respectively. While, the average value of Hazard Index (HI) due to all heave metals in the present work was 0.721± 0.16. Also, the average value of Total Cancer Risk (TCR) due to Cd and Pb were 1.12E-03±4.4E-04. When comparing the results of inhalation health risk, the present work with Worldwide average, we found that the most samples of kerosene samples are safe for using.
Accurate Prediction of Coronary Artery Disease Across Various Age Groups Using Machine Learning Algorithms
Authors: Balamurugan M. , Meera S.
Published: April 2023

The healthcare sector is generally “information rich”. It is required to mine all the information for finding hidden patterns and making wise diagnostic decisions. In order to predict the data in databases and for medical research, particularly in the prediction of heart disease, sophisticated data mining methods are used. In this article, prediction systems for heart failure have been examined using a larger number of input attributes. The method analyses 13 variables, including medical words like sex, blood pressure, and cholesterol, to forecast the risk that a patient will develop heart disease. 13 attributes have so far been used for prediction.In this study, smoking and obesity were introduced as two more characteristics. In the existing we have used Naïve bayes, and Neural networking systems which are having less accuracy compared to the proposed system algorithms. On a database of heart diseases, the proposed data mining classification algorithms J48 Decision Trees, Bagging, and Adaboost are examined. Based on accuracy, these techniques’ performances are contrasted. According to our findings, the Adaboost, J48 decision tree and bagging accuracy are 92.1 percent, 91.62 percent, and 90.52 percent, respectively. Our investigation reveals that Adaboost, out of these three classification methods, accurately predicts heart failure.
Artificial Intelligence Machine Learning in Healthcare System for improving Quality of Service
Authors: Reddy V.S.N. , Mungara J.
Published: April 2023

A vital element of widespread patient monitoring is consistency in transmission between the patients and the healthcare professionals not including time and position dependencies. Artificial intelligence (AI) and machine learning (ML) techniques have a vast possibility to proficiently handle the automated function of the mobile nodes distributed in the Mobile ad-hoc network (MANET). ML is a part of AI in that the computer algorithms learn themselves by improving from historical experiences. The main issues in MANET are autonomous operation, maximization of a lifetime, coverage of the network, energy utilization, connectivity issues, quality of service, high bandwidth necessity, communication protocol design, etc. ML is valuable for data aggregation, and it saves the energy of mobile nodes and enhances the network lifetime. In this paper, we propose an Artificial Intelligence Machine Learning Algorithm for improving the Quality of Service in MANET (AIMQ). ML techniques based on artificial neural networks (ANN) algorithm is helpful for data aggregation tasks. This approach formed the clusters by node mobility and connectivity. Glowworm Swarm Optimization (GSO) algorithm is applied in every cluster to choose a proficient Cluster Head (CH). Here, we choose the CH by GSO fitness function based on mobile node degree, node distance, node reliability, and energy. ANN algorithm recognizes and chooses the data aggregator with great energy and more extended stability. It updates the weight of input parameters such as node energy, node degree, packet loss ratio, and node delay to reduce the errors. It minimizes the repetitive CHs selection and member nodes’ re-affiliation in a cluster.
Genetic Polymorphism in Papillary Thyroid Cancerm j in North Indian Population – A review
Authors: Soni H. , Batra J. , Dhandayuthapani S. , Mishra A. , Aggarwal J.
Published: April 2023

Papillary thyroid cancer (PTC) is one of the generic types of thyroid cancer and most prevalent form of malignancy among all cancers of the thyroid. It is also one of the few cancers with a rapidly increasing incidence. PTC constitutes approximately 85% of all thyroid cancer cases. PTC is usually contained within the thyroid gland and generally biologically indolent. The present article provides an updated condensed overview of PTC, which focuses mainly on the molecular and biomarker investigations.
Prevalence of obesity and overweight among adolescents in district Ghaziabad
Authors: Thakur S. , Gupta G.K. , Verma P. , Agrawal D. , Singh A. , Arya R.K.
Published: April 2023

Background- Obesity and overweight has become a public health concern. Excess weight in the body is linked to various conditions like Hypertension, diabetes, osteoporosis, and stroke which contributes to morbidity and mortality. Prevalence of obesity and overweight have been increasing in childhood and adolescent period because of more sedentary lifestyle and changes in dietary patterns. Methodology- This cross-sectional study was conducted among the children of age 10- 19 years in urban population of district Ghaziabad through a house-to-house survey, using a pre-designed, semi-structured questionnaire with a sample size of 1128 study participants. Results- Among the study participants, 508 students were males and 620 were females. Among males, 194 students were found to be overweight or obese and among females, 210 students were found to be overweight or obese. Children from private schools had the highest prevalence of overweight and obesity, 26.0 % while children from rural government school had the lowest prevalence of overweight and obesity, 0.7%. Consumption of fast food was highest in urban government school students (45.4%) and lowest in rural private school students (24.8 %). Students from rural government schools did maximum vigorous physical activity (87.9%). Conclusion- Obesity was significantly associated with area of residence, type of school and gender.
Effectiveness of Foot reflexology on level of fatigue among peripheral neuropathy, patient with Tuberculosis
Authors: Tejeshwari B.V. , Bhuvaneswari G. , Parasuramalu B.G. , Vijayaraghavan R.
Published: April 2023

Background: In India, Tuberculosis has been mentioned in the Vedas and the old Ayurvedic scriptures. Historically speaking, fight against Tuberculosis in India can be broadly classified into three periods: early period, before the discoveries of x-ray and chemotherapy; post-independence period, during which nationwide Tuberculosis control programs were initiated and implemented; and the current period, during which the ongoing WHO-assisted Tuberculosis control program is in place. Tuberculosis incidence is seasonal, with peaks occurring every spring and summer. The reasons for this are unclear, but may be related to vitamin D deficiency during the winter. There are also studies linking tuberculosis to different weather conditions like low temperature, low humidity and low rainfall. It has been suggested that tuberculosis incidence rates may be connected to climate change Tuberculosis is closely linked to both overcrowding and malnutrition, making it one of the principal diseases of poverty. Those at high risk thus include: people who inject illicit drugs, inhabitants and employees of locales where vulnerable people gather (e.g., prisons and homeless shelters), medically underprivileged and resource-poor communities, high-risk ethnic minorities, children in close contact with high-risk category patients, and health-care providers serving these patients. Factors contributing to this include higher prevalence of predisposing health conditions and behaviours, and overcrowding and poverty. In some Canadian aboriginal groups, genetic susceptibility may play a role. Methods: Quasi-experimental design (one group pre-test post-test design) was recruited by non-probability purposive sampling technique used for the present study. Necessary administrative permission was obtained from the concerned authority. The Structured interview schedule was used to elicit the baseline data. Result: The study revealed that among 180 Tuberculosis patients, the Chalder Fatigue scale pre-median was 27.0, Post-test I median was 14.0, and whereas post-test II median was 7.0. In Michigan Neuropathy scale pre-median was 15.0, the post-test I median was 14.0, and post-test II median was 7.0. Conclusion:-The study concluded that the foot reflexology of anti-tuberculosis drug-induced peripheral neuropathy among Tuberculosis patients from selected community area, Ramanagara Taluk & District, Karnataka carried out the study was found to be effective in decreasing the fatigue levels among peripheral neuropathy in person with Tuberculosis patients as evidenced by the significant change between pre-test and post-test scores.
A Novel Tool for Evaluation of Dental Anxiety in Children in a Pediatric Dental Clinical Setup
Authors: Chakroborty S. , Gupta N. , Gambhir N. , Singh R.
Published: April 2023

Background: One of the major concerns of the current era is Dental anxiety in Pediatric Dentistry. Kids are very well adapted to emojis or emoticons nowadays, and they represent better emotions or moods than a cartoon picture. As a result, this study was carried out to assess a recently created anxiety rating scale. The Jeet Wheel Scale employs emojis and colours to gauge a child’s fear or mood during their first appointment. Aim: The purpose was to develop the innovative anxiety rating scale and evaluate it against the Venham picture test and the Facial Image Scale. Materials and Methods: The Jeet Wheel Scale, Venham Picture Test, and Facial Image Scale were used in the study to measure the dental anxiety of 100 healthy children between the ages of 4 and 8 years old, as well as their preference for a particular scale. RESULT: The mean and standard deviation of anxiety scores measured using Facial Image Scale, and Venham Picture Test, and Jeet Wheel Scale were 1.67 ± 0.87681, and 1.99 ± 1.16771 and 2.79 ± 1.35061, respectively. Amongst the scales used, a significant difference was observed. A strong correlation was observed with the Pearson’s correlation test. The results indicated a strong correlation existed (0.863) between Jeet Wheel Scale and Venham Picture Test, and a strong correlation between Jeet Wheel Scale and the Facial Image Scale (0.802). Based on the above observations, it could be confirmed that Jeet Wheel Scale has high validity. Children preferred Jeet Wheel Scale over the other two established scales. Conclusion: For evaluating children’s dental anxiety, the Jeet Wheel Scale was proven to be more effective.
Fracture Strength of Thin Monolithic Zirconia Crowns with Varying Thickness and Configuration of Finish LinesAn In Vitro Study
Authors: Singh K. , Singh P.S. , Malhotra P.
Published: April 2023

Aim- The current study sought to assess the fracture strength of thin monolithic zirconia crowns of varying thickness and finish line configuration. Study design- The current study was carried out to evaluate and compare the fracture strength of monolithic zirconia crowns with chamfers and radial shoulder finish lines of 0.5, 0.8, and 1.1 mm thickness. Result- Monolithic zirconia crowns with merely 0.5 mm reduction demonstrated adequate strength for use in posterior areas. On evaluation and comparison it was observed that no statistically significant difference was found in the fracture strength of monolithic zirconia crowns with different thicknesses and finish lines was investigated. Conclusion- The 0.5 mm thickness of monolithic zirconia crowns demonstrated significant fracture resistance to withstand physiological performance, regardless of finish line type.
Inflammatory Marker Variations in Predicting Deaths in COVID-19
Authors: Jain R. , Saini V. , Rawat A. , Bisht D.
Published: April 2023

Introduction. Patients with coronavirus illness experienced a cytokine storm as a major cause of morbidity and mortality in 2019. (COVID-19). The goal of the study was to ascertain the predictive value of pro-inflammatory cytokines with regard to the overall prognosis of COVID-19 patients. Methods. This study was conducted by the Department of Microbiology, Santosh Medical College & Hospital, Ghaziabad, Uttar Pradesh from April to July 2021. We followed 189 patients hospitalized for suspected or confirmed COVID-19 from the day of hospitalization to the day of discharge or death. We measured serum IL-6, CRP, D – Dimer, Ferritin levels upon admission and correlated these results with clinical and laboratory markers of disease severity and with disease outcome. Results. Most of the patients were males and greater than 60 years of age. The mean ferritin level prior to the terminal event (survival or death) among non-survivors was 746 ng/mL as compared to 294 ng/mL among survivors and this difference was statistically significant (p-value <0.05). A decrease in ferritin levels prior to the terminal event (survival or death) and at admission were associated with a greater probability of survival. Ferritin levels prior to the terminal event were more strongly correlated with death than ferritin levels at baseline. Mean CRP level at admission among non-survivors was 69 mg/L as compared to 283 mg/L among survivors and this difference was not statistically significant (p >0.05). Conclusion. In patients with COVID-19, inflammatory markers have prognostic value, with higher levels being associated with worse outcomes.
Drug safety among Hypertensive patients treated with antihypertensive drugs in Tertiary care Teaching Hospitals
Authors: Yadav L. , Dutta S. , Sharma J. , Pahwa I. , Lotte V. , Kumar A.
Published: April 2023

Introduction:- Hypertension is one of the essential health problems Worldwide. According to JNC I to VIII guidelines treatment of hypertension with various type of antihypertensive drugs either mono therapy or combination therapy is updated time to time. Selection of a drug is often based on the benefit-risk ratio is also called drug safety even no one drug has totally safe and can be measured on the basis of occurrence of beneficial effect verses Adverse effect. The reporting of ADRs in nations is still low as comparison to providing 10% of total medication in the world. So the present study is proposed on entitled Drug safety among Hypertensive patient treated with antihypertensive drugs in Tertiary care teaching Hospitals. Materials and Methods:- This was a prospective and observational study carried out in the department of Pharmacology, Santosh Medical College and Hospital, Ghaziabad in collaboration with Department of Medicine, Muzaffarnagar Medical College, Muzaffarnagar, A total 234 hypertensive patient of both gender and age above 18 years treated with any types of antihypertensive drug were selected for the study. ADRs were recorded and evaluated with the help of ADRs form uploaded by CDSCO-PvPI of whose causality assessment and severity score that were calculated by appropriate scale and. Observation and Results:- A total 16.67% of prevalence of ADRs were found in this study of whose Risk/Benefit were calculated and found that ARBs and BBs groups were the safest group of antihypertensive drug with smallest number of ADRs prevelance 14.14% and 15.15% with risk benefit ratios 0.16 and 0.18 respectively. Conclusion:- The results of the above study would be useful for the physicians in rational selection of drug therapy for treatment of hypertensive patients. The present data suggest that the ADRs monitoring needs to be done in hospital settings continuously so that untoward effect caused by different medicines can be identified and documented to make better health care system and to stop further burden of unnecessary use of drug by patients health care system.
Pineal gland and the third eye anatomy history revisited – a systematic review of literature
Authors: Chaudhary S. , Bharti R.K. , Yadav S. , Upadhayay P.
Published: April 2023

The structure and functions of neuroendocrine pineal gland remains an enigma to both philosophers and scientists since time immemorial. Some of the structural and functional mysteries of pineal gland are unfolded to some extent in this article by reviewing the work of various researchers. Recently a neuronal circuit consisting of seven neurons between retina and pineal gland have been established to relate the effect of light and other rays on its secretion. The various physical properties such as piezoelectricity, piezoluminescence, electromagnetic field, solar flare, infrared energy are also explained and correlated with the structural and secretional components of the gland. The neurosecretion of pineal gland such as melatonin play an important role in sleep-wake patterns, timings and release of reproductive hormones along with temperature control. The presence of all enzymes needed for the synthesis of di-methyl-tryptamine (DMT) in pineal gland explains the near death experience (NDE) phenomenon. The various audiovisual hallucinations in NDE phenomenon occur due to massive increase of DMT in pineal gland before death. A very high concentration of di-methyl-tryptamine (DMT), presence of retinal proteins in 10% of pinealocytes, its role in thermoregulation and a possible role as magnetoreceptor in blind men and highest deposits of fluoride in the body are not only interesting but significant for the future research. Hence a lot of further research on pineal gland is still required to correlate its unique properties with its structural components.
SARS COV-2 is constantly mutating: A never-ending surge causing threat to mankind
Authors: Gupta A. , Gupta G. , Ansari N. , Agarwal L.
Published: April 2023

Coronaviruses has been spreading across the planet for more than two years now. Emerging new competent variants makes the surge never ending. With over thirty crore cases as on first week of January 2022 this virus has caused serious havoc to humanity. Due to evolutionary selection, new variants become predominant. These new variants are associated with higher transmissibility, increased severity, re infection, immune and diagnostic escapes. It has been prescribed that emergence of herd immunity either achieved by vaccination or by natural infection will be the game changer. Nonetheless COVID appropriate behavior has to be strictly followed. We take the opportunity to describe the variants which created and are still creating havoc all along the world.
Becker’s Nevus Syndrome - Rare entity
Authors: Aarthi K.B. , Verma A. , Tyagi M.S. , Singh S. , Gupta R.K.
Published: April 2023

Becker’s nevus is a rare non-cancerous hamartoma characterized by hyperpigmentation and hypertrichiosis with ill-defined borders. Becker’s nevus syndrome is an entity in which there is association of Becker’s nevus with few abnormalities like unilateral breast hypoplasia, muscle, skin, and skeletal abnormalities. Here we present a case of 14 year old boy who presented with a large hyper pigmented dark brown patch on his upper back. The patient also had a triangular lesion on his lower back with increased hair growth, which was present since birth. X-Ray spine showed Bifid Spinous process of L4. Histopathological examination of the hyper-pigmented area showed findings which were consistent with Becker’s nevus.
A study of an Incidence of tuberculosis is linked to elevated hepcidin at HIV diagnosis
Authors: Saxena P. , Kumar S.M. , Pooja P.
Published: April 2023

Background: Hepcidin prevents ferroportin-mediated iron efflux, which results in intracellular macrophage iron retention and may encourage Mycobacterium tuberculosis nutrient absorption and TB pathogenesis. Aims & Objectives: In order to research into the relationship between incident pulmonary and extrapulmonary TB and plasma hepcidin levels, a retrospective cohort of HIV-positive, antiretroviral-native individuals had their plasma hepcidin levels tested at HIV diagnosis. Methods & Materials: Between 5 August 2017 and 1 June 2019, 140 individuals were monitored, and 34 incident TB cases were found. Discussion: After a median time to TB of 7 months, higher hepcidin was linked to a significantly increased chance of TB. Conclusion: The need for time-sensitive biomarkers that can detect individual variations in TB risk and the elucidation of iron-related causative pathways cannot be overstated.
Age and adenosine deaminase’s impact on the diagnosis of pleural tuberculosis
Authors: Kumar S.M. , Saxena P. , Katara P.
Published: April 2023

Background: ADA levels in PF of 290 individuals were tested to investigate pleural effusion. Based on a positive pleural biopsy, each patient was assessed for age, sex, and the presence of tuberculosis (TB). The Kruskal-Wallis one-way analysis of variance was used to analyze differences in ADA levels between groups. The likelihood of TB was also predicted using logistic regression analysis. Utilizing the receiver operating characteristic (ROC) curve, ADA cut-off levels were chosen. Aims & Objective: Our study aims to establish an ADA cutoff value for the population and explore the possibility that patient variables may affect ADA. Methods & Materials: We conducted a retrospective analysis of 309 M pleural effusion patients admitted to Santosh University, Ghaziabad, between 2016 and 2018. Information was gathered from patients’ medical records. Age, sex, and whether or not a pleural biopsy for TB was positive were all recorded. Results: When compared to non-tuberculous pleural patients, the mean PF ADA level was considerably higher in the tuberculous pleural group (63.3 ± 6.29 IU/l vs. 19.6 ± 31 IU/l, P, 0.001). Age and PF ADA levels were significantly correlated; for patients older than 745 years, the ROC curve for ADA had an area under the curve of 0.89. A 29 IU/l ADA level produced a sensitivity and specificity of 87.4% and 90.3%, respectively. Conclusion: Age and PFADA level have a substantial negative association. The quantity of false-negative outcomes is decreased by using a lower ADA cut-off.
Improving the Efficiency of Heart Disease Prediction Using Novel Random Forest Classifier Over Support Vector Machine Algorithm
Authors: Teja P.P.S. , Veeramani T.
Published: April 2023

Aim: The Aim of the research study is to see how accurate Novel Random Forest (RF) and Support Vector Machine (SVM) classification algorithms were in predicting heart disease.Materials and Methods: The RF Classifier is used to a 304-Record dataset with heart disease.A paradigm for heart disease prediction in the medical field has been presented and developed, comparing Novel Random Forest with SVM classifiers. The total number of images in the sample was 42, with 21 in each test group. Result:-The classifiers were evaluated, predictions and accuracy were supplied. Based on the information provided, the SVM classifier predicts heart illness 60.0% of the time the accuracy of the SVM is 96.42 %, whereas the Novel The Random Forest classifier predicted 72.35% with no statistically significant difference between the two groups (p = 0.103; p > 0.05) with a 95% confidence interval.Conclusion: Novel Random Forest outperforms SVM in terms of prediction and accuracy when compared to it.
An Innovative Penalty based Heart Disease Prediction system using Novel Random Forest over Logistic Regression Classifier Algorithm
Authors: Teja P.P.S. , Veeramani T.
Published: April 2023

Aim: The main goal of the research is see how accurately predicting heart disease by Logistic Regression (LR) and Novel Random Forest(RF) Classifications. Materials and Methods: Novel Random forest appealed on a heart dataset which consists of 200 records A framework for predicting heart disease in the medical field has been proposed and developed to compare the RF with a LR classifier. The sample size was calculated to be 55 for each group with 80% G performance. The sample size was calculated using a Clincalc analysis with Alpha and Beta values of 0.05 and 0.5, pretest performance of 80%, and enrollment rate of 1. The Accuracy of the classifier was Evaluated and Recorded. Results: The LR produces 89.0% in predicting the heart disease on the data set used whereas the Novel Random forest classifier predicts the same at the rate of 95.46% of the time with a statistically significant difference between the two groups (P=0.03; P<0.05) with confidence interval 95%. Conclusion: RF is better compared with LR in terms of both precision and accuracy.
Estimation of Accuracy Rate in Predicting Cardiovascular Disease using Gaussian Naive Bayes Algorithm with Logistic Regression
Authors: Vishnuvardhan T. , Rama A.
Published: April 2023

Aim: Comparison of accuracy rate in prediction of cardiovascular disease using Naive Bayes with Logistic Regression. Materials and Methods: The Naive Bayes (N=10) and Logistic Regression Algorithm (N=10) these two algorithms are calculated by using 2 Groups and taken 20 samples for both algorithm and accuracy in this work. The sample size is determined using the G power Calculator and it’s found to be 10. Results: Based on the Results Accuracy obtained in terms of accuracy is identified by Naive Bayes (87.02%) over the Logistic Regression algorithm (92.18%). Statistical significance difference between novel Naive Bayes algorithm and Logistic Regression Algorithm was found to be p=0.001 (2 tailed) (p<0.05). Conclusion: Prediction of cardiovascular disease using Logistic Regression is significantly better than the Naive Bayes.
Improved Accuracy in Heart Disease Prediction using Novel Random Forest Algorithm in Comparison with Support Vector Machine Algorithm
Authors: Poojitha T. , Mahaveerakannan R.
Published: April 2023

Aim: The primary aim of this paper is to improve the exactness of the classification of coronary illness predictions using the help of machine learning algorithms. We will be comparing the novel Random Forest with the Support Vector Machine to find out which of these can give us the best accuracy. Material and Methods: The study used 184 samples with Novel Random Forest and Support vector machine is executed with varying training and testing splits for anticipating the accuracy for coronary illness prediction with the 80% of G-power value and the Coronary disease data were gathered from several web sources and included current research findings, a threshold of 0.05%, a confidence range of 95%, a mean, and a standard deviation. The accuracy rate of the classifiers is used to evaluate their performance using the Coronary disease dataset. The difference between the two groups is statistically negligible. (p = 0.225; p > 0.05). Results and Discussion: The accuracy of predicting heart disease in Novel Random Forest is 90.16% and support vector machine is 81.97%. Conclusion: Expectation of heart infection using the Novel Random Forest (RF) algorithm appears to be significantly better than the Support Vector Machine (SVM) with improved accuracy.
Heart Plaque Detection with Improved Accuracy using Naive Bayes and comparing with Least Squares Support Vector Machine
Authors: Kumar V.S. , Vidhya K.
Published: April 2023

Aim: The main aim of this research is to detect heart plaque using the Naive Bayes algorithm with improved accuracy and comparing it with Least Squares Support Vector Machine. Materials and Methods: Naive Bayes algorithm and Least squares Support Vector Machine algorithms are two groups compared in this study. In the Kaggle dataset on Heart Plaque Disease, there were a total of 20 samples. Clincalc is used to calculate sample G power of 0.08 with 95% confidence interval. The training dataset (n = 489 (70 %)) and the test dataset (n = 277 (30 %)) are divided into two groups. Result: The accuracy of the Naive Bayes algorithm and the Least Squares Support Vector Machine algorithm is assessed. The Naive Bayes method was 78% accurate, whereas the Least Squares Support Vector Machine method was only 67.3% correct.Conclusion: In this work, the Naive Bayes algorithm outperformed the Least Squares Support Vector Machine algorithm in detecting heart plaque disease in the dataset under consideration. Keywords Heart Plaque disease, Novel intensity feature, Naive Bayes algorithm, Least Squares Support Vector Machine, Prediction, Machine learning.
Identification of Acral Melanoma using Fuzzy Algorithm compared with Convolutional Neural Network for improved accuracy using Dermoscopic Images
Authors: lakshmi V.N. , Nirmala P.
Published: April 2023

Aim: Acral melanoma detection using a fuzzy method vs. convolutional neural network CNN utilizing dermoscopic pictures. Materials and Methods: To assess and compare the acral melanoma detection, the researchers used the fuzzy algorithm and the Convolutional neural network algorithm. The overall sample size is 40 due to the utilization of 20 samples acral melanoma is identified by evaluating the effectiveness with pretest power of 80% (G-power) α=0.05, confidence level 95%. Result: The proposed fuzzy algorithm helps in increasing the higher accuracy compared to Convolutional Neural Network CNN with improved accuracy of the fuzzy algorithm algorithm is 80% and the CNN algorithm is 75 %. The accurate rate is 80with data features found in fuzzy algorithms and each algorithm has different precision. Conclusion: This study shows a higher accuracy for the fuzzy algorithm higher significant value than the convolutional neural network.
Smart Edge Detection Technique in X-ray Images for Improving PSNR using Robert Edge Detection Algorithm with Gaussian Filter in Comparison with Laplacian Algorithm
Authors: Karthick C.N. , Nirmala P.
Published: April 2023

Aim: This study aims to propose smart edge detection techniques in x-ray images for improving PSNR using the Robert edge detection algorithm and compared it with the laplacian algorithm. Materials and Methods: For the design of edge detection technique to improve PSNR Robert edge detection algorithm is used along with the gaussian filter and it is compared with the laplacian algorithm. Robert edge detection algorithm and laplacian algorithm are the two groups considered in this study. For each group, the sample size is 20 and the total sample size is 40. Sample size calculation was done using clinicalc.com by keeping g-power at 80%, confidence interval at 95%, and the threshold at 0.05%. Result: When comparing the two algorithms, it is clear that the Robert edge detection algorithm has a higher mean PSNR value of 43.83 db than the laplacian algorithm 43.33 db. It is observed that the Robert edge detection algorithm has statistically insignificant difference from the laplacian algorithm by performing an independent sample t-test with p value greater than 0.05. Conclusion: Robert edge detection has significantly greater PSNR when compared to the Laplacian algorithm
Effectiveness of oxytocin massage on promoting lactation among postpartum mothers at Saveetha medical college and hospital, Thandalam, Chennai
Authors: Anbarasi E. , Кalabarathi S.K. , Padma P.D.
Published: April 2023

Background: Inadequacy of breast milk after delivery can be caused by the ineffective breast milk production and ejection. One way that can be done is oxytocin massage to promote breast milk secretion. Purpose: The purpose of current study was to determine the effectiveness of oxytocin massage on lactation among postpartum mothers. Materials and methods: A true experimental research with pre and post test control group was conducted in the host institution of Saveetha Medical College And Hospitals. There were 60 postpartum mothers recruited using purposive sampling technique based on the inclusion criteria by using lottery method, 30 in experimental and 30 in control group. Oxytocin massage was administered for the duration of 20 minutes divided in two sessions both morning and evening for about 3 days .For the control group, routine hospital care was followed. On 3rd postnatal day, the study participants were reassessed for the level of breast milk secretion by using the same breast pump after one hour of the intervention. Results: The study results concluded that, the mean difference score in the experimental group was 62.30 and the calculated t test + = 14.942 was found to be statistically significant at p< 0.001 level which depicted clearly that, there was a significant increases in the level of breast milk secretion after circulation of oxytocin massage in experimental group of post partum mothers. Conclusion: oxytocin massage can be promote the production of breast milk among postpartum mothers.
A comparative study to assess the blood sugar level of post Covid patients with diabetes patients and non diabetic clients
Authors: Parimala L. , Kishore V.
Published: April 2023

Background: The present study aims to compare and assess the blood sugar level among post COVID patients with diabetes patient and non diabetic clients in Saveetha Medical College and Hospital. Material and Methods: The quantitative approach with comparative study was conducted in host institution of Saveetha Medical College and Hospital. A total of 30 participants were recruited using Non-probability convenient sampling technique based on the inclusion criteria, the demographic and clinical data was collected by using structured questionnaire and the HbA1c test was used to assess the blood sugar level among the patients during post COVID period of time. Result: The outcome results identified that the mean score of HbA1c among post COVID diabetic patients was 9.82±3.22 and the mean score of HbA1c among post COVID non-diabetic patients was 5.83±3.32. The mean difference score was 3.99. The calculated Student Independent ‘t’ test value of t = 3.345 was found to be statistically significant t p<0.001 level. This clearly infers that there was significant difference in the level of HbA1c among post COVID diabetic and non-diabetic patients in which post COVID diabetic patients had elevated HbA1c level than the non-diabetic patients. Conclusion: This study concluded that there was significant difference in the blood sugar level among the post COVID diabetic patients and non diabetic patients. Overall, the understanding of Post COVID Syndrome is improving however further research is needed for future references .In particular, patients with diabetes would require care in glycemic and risk factor control to prevent the development and severity of Post COVID Syndrome. Data on bidirectional adverse effects of diabetes and PCS are clearly needed.