Miracle-dz/UniFAR-FTUs huggingface dataset:
Assess the Knowledge and Attitude Regarding Alternative System of Medicine among the Adults in Rural Community Area

Introduction: The folk medicine which is available such as herb, flora, found and minerals. The people taking some treatment for improving health and treat the person which lies in ancient times. Some of the people of the alternative system such as homeopathy, Ayurveda, Siddha, Unani, naturopathy and yoga. The alternative system of medicine is widespread. This leads to improving knowledge regarding the alternative system of medicine in the rural community area. Background: The present study has been designed to capture the knowledge and attitude towards the Alternative health care system of medicine in its user and non-users to compare the differences in its source of knowledge among the rural community people. Knowledge regarding the alternative therapies that are living in the rural community area. The person has some knowledge regarding alternative health such as naturopathy, homeopathy, yoga, Unani and Siddha. The people will have known about alternative therapies. Objective: To assess the knowledge of adults in rural community areas regarding the alternative system of medicine. To assess the attitude towards an alternative system of medicine among rural community areas. Methods: The sample size is 100 among the adults in the rural community area. Results: In the present study 98% of the adults were having a positive attitude and only 2% of them had a negative attitude. Association of knowledge score and attitude score with the selected demographic variables there is a significant in the gender and not significantly associated with education, occupation, caste regarding the alternative system of medicine and significant association between attitude score the gender and not significantly associate with education, occupation, caste regarding the alternative system of medicine. Conclusion: This study revealed that in wardha city, there is relatively high public interest in complementary and alternative medicine and a significant number has a produce good awareness attitude toward complementary and alternative medicine.
Keyseg: adaptive segmentation for spontaneous electroencephalography map series into spatially defined microstates of musicians’ brain

Indra K. Wardani, Phakkharawat Sittiprapaporn, Djohan, Fortunata Tyasrinestu, Prayoon Suyajai Indonesia Institute of the Arts, Yogyakarta, Indonesia Neuropsychological Research Laboratory, Department of Anti-Aging and Regenerative Science, School of Anti-Aging and Regenerative Medicine, Mae Fah Luang University, Bangkok, Thailand Brain Research Unit for Anti-Aging and Regenerative Medicine, School of Anti-Aging and Regenerative Medicine, Mae Fah Luang University, Bangkok, Thailand Department of Psychology, Faculty of Humanities, Mahachulalongkornrajavidyalaya University, Phra Nakhon Si Ayutthaya, Thailand
Covid-19, Workplace Challenges

This paper is written to enlighten how organizations monitor employees' work performance from home versus working in the office as a result of the Covid-19 pandemic. The objective of this article was to determine how organizations were able to measure the performance of their employees when they were working from home. Secondly, to evaluate how organizations were able to monitor virtual workload as versus traditional workload. Finally, through scrutinizing the new workplace normal articles, the author derived the third objective which was to determine how the employees balanced their work and family disputes during the Covid-19 pandemic. Several related articles were scrutinized to demonstrate the current workplace scenario as opposed to the traditional practices. At the end of the article, we proposed several monitoring measures and how employees’ performance can be improved during the Covid-19 pandemic. Flexibility in goal setting, teamwork and regular performance feedback will psychologically lead to positivity in work performance. Whilst, social support, job autonomy, workload and monitoring would reduce employees’ procrastination in carrying out their virtual workload. Lastly, a 360° social support, flexible schedule, mental therapy and boundary management create conductivity working at home and being able to overcome work and mental stress thus create a healthy working environment.
Lung cancer medical images classification using hybrid CNN-SVM

Lung cancer is one of the leading causes of death worldwide. Early detection of this disease increases the chances of survival. Computer-Aided Detection (CAD) has been used to process CT images of the lung to determine whether an image has traces of cancer. This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). This algorithm is capable of automatically classifying and analyzing each lung image to check if there is any presence of cancer cells or not. CNN is easier to train and has fewer parameters compared to a fully connected network with the same number of hidden units. Moreover, SVM has been utilized to eliminate useless information that affects accuracy negatively. In recent years, Convolutional Neural Networks (CNNs) have achieved excellent performance in many computer visions tasks. In this study, the performance of this algorithm is evaluated, and the results indicated that our proposed CNN-SVM algorithm has been succeed in classifying lung images with 97.91% accuracy. This has shown the method's merit and its ability to classify lung cancer in CT images accurately.
Bromazepam changes performance during target shooting but does not affect the interhemispheric coupling in the theta rhythm of the electroencephalography

Bromazepam emulates the inhibitory effect of the neurotransmitter gamma-aminobutyric acid (GABA) and can lead to impaired visuomotor performance. However, few studies have evaluated its effects on cortical coupling in target shooting activities. The present study aimed to analyze the acute effects of bromazepam administration in a target shooting task and the EEG theta rhythm coherence between frontal, temporal, and motor cortical areas in four shooting preparation periods. Thus, a double blind, crossover study was conducted with 30 subjects under two conditions: bromazepam (6mg) and placebo, with electroencephalographic analysis to simultaneously study the theta rhythm coherence in frontal, temporal, and motor cortex in a target shooting task; and the possible interferences of bromazepam administration. Subjects in the bromazepam group showed lower performance on the task compared to placebo (p=0.001). In addition, our analysis showed decreased coherence between regions in the same hemisphere, increased theta rhythm coherence in interhemispheric regions in frontal, temporal and motor cortex at different intervals in the preparation preceding the shooting (p=0.001). The use of bromazepam may influence task execution, possibly due to neurochemical modulation, during decision making, developing shooting preparation strategies, as well as interfering with the flow of information at the level of attention during task execution.
Research on Poverty Alleviation in China Based on Big Data in the Context of COVID-19

Objectives: In order to alleviate the impact of COVID-19 on China's poverty alleviation work, this paper proposesa performance evaluation method and a recommendation algorithm for poverty indicator system suitable forChina's national conditions based on big data technology. Methods: The evaluation method combines the preciseadvantages of Bayesian classifier and the full-volume processing characteristics of big data to comprehensivelyevaluate the past poverty alleviation achievements. The recommendation algorithm takes the poverty alleviationdata over the years as the research object and realizes the construction method of the indicator system in therelative poverty stage. Results: The comparison with Pearson's correlation coefficient shows that the newevaluation method has more accurate confidence calculation ability. And compared with the classic ALSrecommendation algorithm, the new recommendation algorithm has a more scientific and reasonablerecommendation effect. Conclusions: Finally, the paper proposes relevant suggestions for the next stage of policyformulation, proves that medical and health conditions play an important role in supporting poverty alleviation.
Explore Optimal Degree of Parallelism for Distributed XGBoost Training

The XGBoost has been an extremely popular and effective machine learning method which gained its fame through winning multiple Kaggle competitions. One of its strengths lies in parallel processing which makes the computation salable and faster than its counterparts. On the other hand, there are system configurations and model tuning parameters which need to be adjusted in order to achieve its full potential cost-effectively. In this paper, we explore how the training duration changes under different workloads, system configurations and framework parameters. By running multiple of these experiments, practical insights can be learned and applied for the future applications of XGBoost methods.
High-resolution hindcasts for U.S. wave energy resource characterization

The marine and hydrokinetic (MHK) industry is at an early stage of development and has the potential to play a significant role in diversifying the U.S. energy portfolio and reducing the U.S. carbon footprint. Wave energy is the largest among all the U.S. MHK energy resources, which include wave energy, ocean current, tidalinstream, ocean thermal energy conversion, and riverinstream. Wave resource characterization is an essential step for regional wave energy assessments, Wave Energy Converter (WEC) project development, site selection and WEC design. The present paper provides an overview of a joint modelling effort by the Pacific Northwest National Laboratory and Sandia National Laboratories on highresolution wave hindcasts to support the U.S. Department of Energy’s Water Power Technologies Office’s program of wave resource characterization, assessment and classifications in all US coastal regions. Topics covered include the modelling approach, model input requirements, model validation strategies, high performance computing resource requirements, model outputs and data management strategies. Examples of model setup and validation for different regions are provided along with application to development of classification systems, and analysis of regional wave climates. Lessons learned and technical challenges of the long-term, high-resolution regional wave hindcast are discussed. Keywords—U.S. regional wave hindcast, unstructuredgrid wave model, model validation, resource characterization, classification systems.
Enhancement of Vegetative Growth Criteria and Accumulation of Secondary Metabolites by Using Compost Tea and Paclobutrazol on Henna (Lawsonia inermis L.) Plants

(Received 29/04/2021, accepted 11/06/2021) DOI: 10.21608/ejoh.2021. 74606.1173 ©2021 National Information and Documentation Centre (NIDOC) A POT experiment was carried out during the two successive seasons of 2018 and 2019 at Beni-Suef governorate, Egypt, to investigate the effect of compost tea and foliar-spray application of paclobutrazol (PBZ) on vegetative growth characteristics and some chemical constituents of henna plants.
Sub-fractions from Carica Papaya Seed Extracts Can Prevent Potassium Bromate- induced Changes in Activities of Renal Brush Border Membrane Enzymes and Some Enzymes of Carbohydrate Metabolism in the Kidney of Rats

Aim: To investigate the effect of the chromatographic fractions of Carica papaya seed on KBrO3 – induced reduction in the activities of renal brush border membrane (BBM) marker enzymes and the changes in activities of some enzymes of carbohydrate metabolism in the kidney of rats. Study Design: twenty male Wistar rats were divided into four groups, five rats per group; normal control, KBrO3 control, papaya fraction control and KBrO3 group administered with 126mg/kg body weight of the most active fraction of partially purified methanol extract of C. papaya for 48 hours. Place and Duration of Study: Department of Biochemistry Laboratory, Faculty of Basic Medical Sciences, Bayero University Kano, Nigeria. Methodology: The activities of renal BBM marker enzymes: γ-glutamyl transferase, alkaline Original Research Article Kanadi et al.; AJBGMB, 8(4): 1-9, 2021; Article no.AJBGMB. 72011 2 phosphatase, maltase and leucine aminopeptidase were assayed in homogenates of renal cortex and medulla, and in brush border membrane vesicle (BBMV) isolated from cortex using standard methods. Furthermore, activities of the following enzymes representing different pathways of carbohydrate metabolism were determined in renal homogenates: hexokinase (HK), lactate dehydrogenase (LDH), malate dehydrogenase (MDH), glucose 6-phosphatase (G6P), fructose 1,6bisphosphatase (FBP), glucose 6-phosphate dehydrogenase (G6PD) and malic enzyme (ME). Results: KBrO3 administration significantly (P<0.05) decreases the activities of all the BBM marker enzymes in renal homogenates and BBMV. It also decreases the activities of MDH, G6P, FBP and G6PD, and significantly increases (P<0.05) that of HK, LDH and ME in renal homogenates however co-administration of most active fraction of C. papaya seed prevented all the KBrO3 -induced changes in these biochemical parameters. Conclusion: Chromatographic fractions of C. papaya seed extract possesses potent phytochemicals that could prevent KBrO3 –induced reduction in activities of renal BBM marker enzymes and the changes in enzymes of carbohydrate metabolism studied and therefore could be analyzed further to isolate the bioactive compounds.
Effectiveness of Turmeric and Extra Virgin Olive Oil in the Management of IL 6 and IL 10 in Healthy Mice

Background: Anti-Inflammatory properties of turmeric and extra virgin olive oil have numerous health benefits. They exert and promote anti-inflammatory actions, moreover, each gives benefits that go beyond reducing inflammation. Objective: The aim of our study is to evaluate and compare the immunomodulatory effect of each turmeric and extra virgin olive oil (EVOO) alone or in combination. Methods: We demonstrated the serum level of pro-inflammatory cytokines IL-6 and IL-10 in healthy male Swiss albino mice (C57BL/6 strain) after oral intake of curcumin and extra virgin olive oil for six weeks by ELISA assay. Results: Our results showed that dietary intake of turmeric and EVOO had a reducing effect on serum IL-6 level and could increase the production of IL-10 level significantly. Inflammatory responses of turmeric and EVOO combination appear to be more effective on health by inhibition of IL 6 and induce IL 10 production. Conclusion: Anti-inflammatory effect of turmeric and EVOO can play an important role in modulating the level of IL 6 and IL-10. Moreover, co-administration of them having a greater antiinflammatory effect.
The Smoking Behavior of Health Workers in Asia: A Literature Review

Health workers are role models in preventing smoking behavior, yet many are smokers themselves. This study reviews and analyzes the smoking behavior of health workers in Asian countries, based on databases such as PubMed, EBSCO, and Google Scholar in 2013–2018. It is shown that the prevalence of smoking amongst health workers was 4.6–44%, with the nursing profession showing a higher level than other health professions and with a higher ratio of male to female smokers. Health workers are aware of the dangers of smoking, including the effects of cardiovascular disease, respiratory disease, oral cancer, atherosclerosis, hypertension, fetal disorders, and infertility. However, the factors that lead to smoking include stress, the influence of friends or family who smoke, and addiction. Health workers are responsible for providing smoking prevention education. However, there are still obstacles to its implementation due to their smoking habits and lack of expertise in educating others. Smoking prohibition policies in the workplace, the training of health workers, and smoking prevention service facilities need to be considered by Asian countries to prevent smoking. Abstrak Analisis Perilaku Merokok pada Petugas Kesehatan di Asia: Literatur Review. Petugas kesehatan merupakan role model dalam pencegahan perilaku merokok, akan tetapi masih banyak petugas kesehatan yang merokok. Studi ini meninjau dan menganalisis perilaku merokok petugas kesehatan di negara-negara Asia, bersumber pada basis data seperti PubMed, EBSCO, dan Google Scholar, tahun 2013–2018. Hasil studi menunjukkan perilaku merokok petugas kesehatan memiliki prevalensi sebesar 4,6–44% dengan profesi keperawatan menunjukkan tingkat yang lebih tinggi daripada profesi kesehatan lainnya, dan dengan rasio perokok laki-laki lebih tinggi dari perokok perempuan. Petugas kesehatan menyadari bahaya merokok dan dampak penyakitnya seperti penyakit kardiovaskuler, penyakit pernapasan, kanker mulut, aterosklerosis, hipertensi, gangguan janin, dan kemandulan. Faktor yang memengaruhi merokok adalah stres, pengaruh teman atau keluarga yang merokok, dan kecanduan. Petugas kesehatan bertanggung jawab untuk mem-berikan pendidikan pencegahan merokok. Namun, masih terdapat kendala dalam pelaksanaannya karena kebiasaan pribadi merokok mereka dan kurangnya keahlian dalam mendidik orang lain. Kebijakan larangan merokok di tempat kerja, pelatihan tenaga kesehatan, dan fasilitas layanan pencegahan merokok perlu diperhatikan oleh negara-negara Asia untuk pencegahan perilaku merokok. Kata kunci: perilaku merokok, petugas kesehatan, role model
MALICIOUS URL DETECTION USING 1D CNN AND TENSORFLOW JS

: Phishing web sites have been a serious chance to cyber safety which employs each social engineering and technical trick to steal clients’ non-public identity statistics and monetary account information. Recent years have proved the hasty increase of phishing attacks. Phish recognizer is targeted on getting rid of the identity robbery and fraud that result from the growing problem of phishing. We propose phish recognizer, a deep learning based method which uses 1D CNN to build accurate function representation of URLs, which we use to teach a phishing URL classifier.In conclusion, the model that has been trained has a high precision and recall value and the model is converted to tensorflowJS model to run inside a browser extension.
A Deep Learning Technology based OCR Framework for Recognition Handwritten Expression and Text

Recently Optical character recognition (OCR) based on deep learning technology has achieved great advance and broadly applied in various industries. However it still faces many challenging problems in handwritten text recognition and mathematical expression recognition, such as handwritten Chinese recognition, mixture of printed and handwritten Chinese characters, mathematical expression (ME), chemical equations. In traditional OCR, features selection played a vital role for recognition accuracy, while hand-crafted features are costly and time-consuming. In this paper, we introduce a deep learning based framework to detect and recognize handwritten and printed text or math expression. The framework consists of three components. The first component is DCN (Detection & Classification Network), which based on SSD model to detects and classify mathematical expression and text. The second component consists of text recognition and ME recognition models. The final component merges multiple outputs of the second stage into a whole text. Experiment results show that our framework achieves a relative 10% improvement in mixture of texts and MEs which are printed or handwritten in images. The framework has been deployed for recognition paper or homework at one online education platform.
Prevalence of multimorbidity in Thailand: a multilevel analysis of a population-based survey

Studies have reported the prevalence of multimorbidity, risk factors related to multimorbidity, epidemiology and interventions. Reviews have shown that the multimorbidity rate was distributed across age group, gender, and socioeconomic status. Therefore, this study aimed to estimate the prevalence of multimorbidity in Thailand, and to analyze the factors related to multimorbidity using multilevel analysis.
Avian/Bird flu: A review: H5N1 outbreaks in Nepal

Avian/Bird flu is a viral disease of birds, caused by avian influenza virus (AIV). A highly pathogenic avian influenza (HPAI) H5N1 has breached the barrier of species to humans and other animals escalating the pandemic threat. If the H5N1 evolves to a human-to-human transmissible virus retaining its pathogenicity, it can trigger an influenza pandemic. H5N1 has a mortality rate of about 60%, varying with strains. Meaningful antigenic alteration in hemagglutinin (HA) and/or neuraminidase (NA) results in recurring pandemics. The HPAI H5N1 subtype alone has outreached more than 77 nations around the world since the first human case and death was reported in 1997. Wild and migratory birds are the AIV reservoirs. Poultry is primarily impacted by incidents and outbreaks of the disease. A wide range of serological and molecular methods have substantially aided in the identification of bird flu in humans. Candidate vaccines have been developed, yet are not ready for widespread use. Oseltamivir (brand name: Tamiflu) is the preferred drug for the management of human Influenzalike illness (ILI). Surveillance, mass awareness, and pandemic preparedness abiding WHO recommendations are of paramount importance for the prevention of bird flu outbreaks.
Impact of Probiotics on microbiota in the gut of antibiotic treated Vertebrates

The gut microbiota (moreover alluded to as gut flora) is the populace of microscopic organisms that colonizes the human intestine. As the significance of the gut microbiota is getting to be progressively apparent, considers have been carried out with the point of picking up a more comprehensive understanding of the possibly destructive impacts of antibiotics on this fundamental biological system. Clearly antibiotics have bactericidal and bacteriostatic properties against pathogenic organisms. But agreeing to later examinations antibiotics moreover do have a tremendous effect on our gut microbiota particularly on the health advancing good microbes. They halt microscopic organisms within the intestine from making proteins, partitioning, making cell walls and transporting nutrients and also can make gaps within their cell wall or membranes. A few pathogenic microscopic organisms too create antibiotic resistance which may be a genuine issue these days. Hence human intend to intake probiotics after an antibiotic course to maintain their gut microbiota. In this paper I have reviewed about the microflora in vertebrates and the various probiotics that have positive action on them after antibiotic effect.
Triple-layer remote phosphor structure: a selection of the higher color quality and lumen efficiency for WLEDs

Received Dec 14, 2020 Revised Apr 18, 2021 Accepted Jun 14, 2021 To enhance color quality of glass-based phosphor-converted white lightemitting diodes (pc-WLEDs) with multi-layer remote phosphor layer structures, two phosphors, green CdS:In and red ZnS:Te,Mn, are integrated into the glass matrix and applied to the dual-layer and triple-layer WLED packages. The attained results were examined with Mie-scattering theory and Lambert-Beer law. The dual-layer showed significant enhancement in color rendering index (CRI), in the range of approximate 80-90. Meanwhile, CRI in the triple-layer was lower and stayed around 66. In terms of color quality scale (CQS), a more overall color evaluating index, triple-layer structure helps the glass-based WLED achieve higher value than the dual-layer. The triplelayer is also beneficial to the luminous efficacy, according to the experimented results. Thus, the triple-layer structure can be used to strengthen the benefit of the glass matrix used in WLED products.