Miracle-dz/UniFAR-FTUs huggingface dataset:
Alterations in Serum Magnesium and Electrocardiographic Variables of Adult Hypertensive Humans

As the most important risk factor for cardiovascular diseases worldwide, Hypertension has been found to be a major public health challenge with high prevalence in Africans and Nigerians especially with a rapidly growing population. It has been postulated that hypomagnesemia contributes to the development of hypertension and cardiovascular disease. This study was therefore undertaken to determine the relationship between serum magnesium levels and electrocardiographic changes in adult humans with hypertension. To achieve this, one hundred and sixty two (162) hypertensives were recruited from the University of Benin Teaching Hospital (UBTH), Benin City, Edo State, Nigeria. Participants’ Blood pressure, electrocardiographic changes, antihypertensive medications and serum magnesium (Mg2+) levels were investigated. Using the Pearson Product Moment Correlation Coefficient and ANOVA, Statistical measures of association (correlation) were conducted on obtained variables. A low incidence of hypomagnesaemia was observed on the average, with a high incidence of patients presenting with abnormal ECG changes; including Left Ventricular Hypertrophy. In addition, only weak correlations were observed for ECG parameter and serum Mg2+levels for sampled subjects, with p-value returning a statistically significant decrease upon comparison of means (Using the One-Way Analysis of Variance (ANOVA); Other influences like antihypertensive medications, blood pressure duration and control returned an significant (weak negative) correlation with serum Mg2+ concentration. There is therefore a weak negative correlation between serum magnesium levels and ECG variables, including Q wave duration and QT interval duration in hypertensive adults
Next Place Prediction and Alert System

One of the most powerful features of modern smartphones is their ability to provide us with real-time, locationally aware information. For instance, if you enable the location services on your device, you can find out the approximate amount of time it would take for you to get to your desired destination using your smart phone after you offer the necessary data. The location services on mobile devices have provided us with a number of advantages and advancements but it has its own limitations. The user needs to input certain before they can get any relevant information on any given subject. Predictability is a tool provided to us with the advancement in technology and artificial intelligence. By processing the previously stored data, patterns can be observed in the behavior and a prediction model can be developed. Imagine the following situation. You hop in your car to head to the gym after work. You don’t turn on your phone’s navigation because you know the way, but there is an accident on your route and a lot of traffic. If your phone knows where you are going without you telling it, it could warn you before you start driving and help you reroute. If our smartphones could predict our destination by observing patterns in our previous behavior, they could give us more relevant information about the places we are heading to. The idea of someone having knowledge of your previous, current and future whereabouts may seem unnerving but if this data is processed on your individual devices without any secondary storage or data revelation, the entire concept becomes much more appealing. For our project we created a system that can predict a user’s next location using their current and previous location with regards to time, learning only from that user’s location history.
CLASSROOM MANAGEMENT STYLE AND TEACHING STYLE WTH LINUS ACHIEVEMENT IN ELEMENTARY SCHOOLS

LINUS was a new extension of the KIA2M for continuing their objectives and purposes. Factors such as socioeconomic, classroom management style and teaching style are often overlooked. Thus, students’ LINUS achievement has become an important issue to be studied. The purpose of this study was to investigate the relationship among LINUS students’ socioeconomic, teachers’ classroom management style and teachers’ teaching style in teaching LINUS subjects, Bahasa Melayu and Mathematics. The research site was elementary schools in the eastern zone of Kluang, Johor. This study used the quantitative method which using questionnaire as the tool for the data collection. Cluster random sampling method was applied in the selection of 102 as research respondents. All the statistical analysis performed by using Statistical Package for Social Sciences version 20 (SPSS 20.0). The quantitative data was analyzed through descriptive statistics (frequency, percentage, mean and standard deviation) and inferential statistic involving parametric test (Rank Biserial Correlation). A pilot test was carried out for Behavior and Instructional Management Scale (BIMS) and Teaching Style (TSI) with the Cronbach’s Alpha coefficient values of 0.815 and 0.837 respectively. In descriptive analysis, the study found that the highest proportion in education, occupation and income were middle school, labor business and salary between RM 2001 to RM 3001. Majority of parents’ background had lowered socioeconomic. In addition, the dominant levels of classroom management style and teaching style obtained high mean scores according to interpretive scale. The inferential analysis results found little significant relationship between LINUS students’ socioeconomic status and measures of LINUS achievement and non-significant relationships were found between elementary school teachers’ classroom management and teachers’ teaching style and student LINUS achievement.
Low Latency Message Brokers

1,2Dept. of Computer Science and Engineering, R V College of Engineering, Bengaluru ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Message Brokers form an essential and irreplaceable part of microservices, real time and cloud native applications as they are used to communicate between various application services. They handle variety of data of massive volume in short period of time having a high throughput and low latency. Message Brokers supports replication and distribution of workload which are essential for any big data processing or streaming applications. Currently numerous messaging systems are present in the market, with new ones being proposed ever so often. This luxury of choice creates confusion in the industry on what Message Broker to be chosen for application development. In depth study is needed to decide the choice of Message Broker suitable for an application. This paper discusses available Message Brokers and gives deeper insight on three most popular Message Brokers – Redis, RabbitMQ and Apache Kafka. For the benefit of the reader introduction is given on Message Brokers and their use case. Comparison of these systems should facilitate readers in making knowledgeable decision.
COGNITIVE RADIO – AN EMERGING TECHNOLOGY

In recent times, there are many IoT applications that leads to the increase in network load. For remotely accessing, the IoT connects the heterogeneous devices wirelessly and control them. Most of the devices use licensed wireless spectrum bands. Soon there will be a congestion in the spectrum, thus creating the interference among the users which leads to the spectrum scarcity problem. The spectrum must be used effectively and efficiently to support large deployment of IoT systems. This leads to the raise of emergent technology called Cognitive Radio (CR) [4]. Cognitive Radio is a dynamic spectrum utilization technique where transceiver has the intelligence to detect the channels which are in use and those which are not in use. As the result, it makes the use of available spectrum efficiently and minimize the interference among users. A overview of CR architecture, functions of CR, challenges in each function of CR environment and issues in CR are investigated in this paper. A energy power allocation method is discussed to that facilitates the efficient utilization of the spectrum.
Effect of Rifampicin and Isoniazid Coadministration on the Metabolism and Pharmacokinetics of Isoniazid in Mice

Objective To study the pharmacokinetics changes of isoniazid and its metablites in rifampicin and isoniazid coadministrated mice.Methods Plasma samples were collected after 10 consecutive days of administration of isoniazid or rifampicin plus isoniazid once a day to mice.Isoniazid and its metablites-acetylhydrazine and hydrazine were determined by liquid chromatography/tandem mass spectrometry.Results Compared with isoniazid group,Ke,Cmax and AUC0-12h of acetylhydrazine increased significantly and t1/2 decreased significantly in rifampicin coadministrated group.AUC0-12h of hydrazine increased by 20% in rifampicin coadministrated group.Conclusion Acetylhydrazine and hydrazine,metabolites of isoniazid,increased significantly when isoniazid was coadministrated with rifampicin,suggesting that the increase of acetylhydrazine concentration plays a role in the hepatotoxicity of isoniazid and rifampicin coadministration.
PERFORMANCE AND ANALYZE OF CROSS DIPOLE ANTENNA WITH PARASITIC ELEMENTS

[1]Professor, Department of ECE, Panimalar Institute of Technology, Tamilnadu, India [2], [3], [4]Final Year Student, Department of ECE, Panimalar Institute of Technology, Tamilnadu, India --------------------------------------------------------------------------***----------------------------------------------------------------------Abstract — The broadband Circularly polarized (CP) crossed dipole antenna is presented. The proposed antenna consists of crossed bowtie dipole with four unequal cross slots and four unequal parasitic rectangular strips. The sequential phases of crossed bowtie dipole contain cross slots that can generate a CP mode. The proposed antenna contain two asymmetric bowtie dipole antenna. The one CP mode are generate by parasitic strips due to sequentially rotated configuration. The broadband CP operation is achieved by combining of the crossed bowtie dipole with cross slot and parasitic strips. The experimental and simulated results are studied in arranged manner. The proposed antenna achieved a wide impedance bandwidth and axial ratio bandwidth are shown. The proposed antenna produces a peak gain of 6.84 dBi .
Towards high fidelity materials property prediction from multiscale modelling and simulation

The current approach to materials discovery and design remains dominated by experimental testing, frequently based on little more than trial and error. With the advent of ever more powerful computers, rapid, reliable and reproducible computer simulations are beginning to represent a feasible alternative. As high performance computing reaches the exascale, exploiting the resources efficiently presents interesting challenges and opportunities. Multiscale modelling and simulation of materials is an extremely promising candidate for exploiting these resources based on the assumption of a separation of scales in the architectures of nanomaterials. We present examples of hierarchical and concurrent multiscale approaches which benefit from the weak scaling of monolithic applications, thereby efficiently exploiting large scale computational resources. We discuss several multiscale techniques, incorporating the electronic to the continuum scale, which can be applied to the efficient design of a range of nanocomposites. We then discuss our work on the development of a software toolkit designed to provide verification, validation and uncertainty quantification to support actionable prediction from such calculations.
The implications of organizational environment questionnaire for the assessment of occupational injury among medical workers

Abstract Organization environment has significant influence on occupational health among medical workers. In current study, based on previous established questionnaires, we constructed a new questionnaire to evaluate the effects of organizational environment on occupational injury of medical workers. In a large-scale of investigation, a total of 2350 medical workers from 54 hospitals in Zhuhai city, China, were surveyed by the new questionnaire, and 2111 (91.2%) questionnaires were used for final analysis. The average score of organization environment of medical workers questionnaire was 91.33 ± 21.95. We found that as compared with the average levels, medical workers have higher incidences of behavioral symptoms such as depressed mood, obsessional thinking, and anxiety and so on. We also demonstrated the questionnaire scores correlated with the incidence of occupational disease, occupational injuries and the scores of SCL-90, implying its potential application to objectively measure the conditions of medial safety of medical workers in China. In all, we concluded that organizational environment has important implications on the assessment of occupational health of medical workers.
Applications of Discrete Element Method in the Research of Agricultural Machinery: A Review

As a promising and convenient numerical calculation approach, the discrete element method (DEM) has been increasingly adopted in the research of agricultural machinery. DEM is capable of monitoring and recording the dynamic and mechanical behavior of agricultural materials in the operational process of agricultural machinery, from both a macro-perspective and micro-perspective; which has been a tremendous help for the design and optimization of agricultural machines and their components. This paper reviewed the application research status of DEM in two aspects: First is the DEM model establishment of common agricultural materials such as soil, crop seed, and straw, etc. The other is the simulation of typical operational processes of agricultural machines or their components, such as rotary tillage, subsoiling, soil compaction, furrow opening, seed and fertilizer metering, crop harvesting, and so on. Finally, we evaluate the development prospects of the application of research on the DEM in agricultural machinery, and look forward to promoting its application in the field of the optimization and design of agricultural machinery.
CRIME PREDICTION AND VISUALISATION USING DATA ANALYTICS

Crime analysis and prevention is a structured and methodical application which is utilised to identify and analyse models, patterns and trends in crime. The system analyses the crime data, evaluates the likelihood for crime occurrence in each area and builds visualisations for the same. The ubiquitous use of computerized systems for a wide array of applications paves way for crime data analysts to assist the law in pacing the process of solving and thereby preventing crimes. There has been far-reaching implications of crime across India in recent times developing to being a huge menace for the government and the citizens of the country[1]. Thus we aim to study these patterns of crime based on the data acquired from Indian Government website. The algorithms such as Linear Regression, Random Forest and Support Vector Machine were employed to achieve the objective. The output is generated using simple visualisation charts.
Evaluation for Potential Drug–Drug Interaction of MT921 Using In Vitro Studies and Physiologically–Based Pharmacokinetic Models

MT921 is a new injectable drug developed by Medytox Inc. to reduce submental fat. Cholic acid is the active pharmaceutical ingredient, a primary bile acid biosynthesized from cholesterol, endogenously produced by liver in humans and other mammals. Although individuals treated with MT921 could be administered with multiple medications, such as those for hypertension, diabetes, and hyperlipidemia, the pharmacokinetic drug–drug interaction (DDI) has not been investigated yet. Therefore, we studied in vitro against drug-metabolizing enzymes and transporters. Moreover, we predicted the potential DDI between MT921 and drugs for chronic diseases using physiologically-based pharmacokinetic (PBPK) modeling and simulation. The magnitude of DDI was found to be negligible in in vitro inhibition and induction of cytochrome P450s and UDP-glucuronosyltransferases. Organic anion transporting polypeptide (OATP)1B3, organic anion transporter (OAT)3, Na+-taurocholate cotransporting polypeptide (NTCP), and apical sodium-dependent bile acid transporter (ASBT) are mainly involved in MT921 transport. Based on the result of in vitro experiments, the PBPK model of MT921 was developed and evaluated by clinical data. Furthermore, the PBPK model of amlodipine was developed and evaluated. PBPK DDI simulation results indicated that the pharmacokinetics of MT921 was not affected by the perpetrator drugs. In conclusion, MT921 could be administered without a DDI risk based on in vitro study and related in silico simulation. Further clinical studies are needed to validate this finding.
Role of Emotional Intelligence in Leadership and Organizational success

Emotional Intelligence (EI) plays a significant role in creating leadership skills and making an effective workplace. Positive work environment will enable everyone to understand each other, manage their own emotions in positive ways to relieve stress, communicate effectively, empathize with others, and help to manage relationships within the organization. The objective was to explore the association of emotional intelligence in leadership and organizational success among the
Extraction of baicalin from Scutellaria baicalensis Georgi and its alleviative effect on acute respiratory distress syndrome in rats

Many natural products have the anti-inflammatory activities (Amaral et al., 2017; Felhi et al., 2017; Lee et al., 2019; Costa et al., 2020). Baicalin (C21H18O11) is one of the effective components of Scutellaria baicalensis Georgi, a herbal medicine commonly used in China. Modern scientific research has proved that, baicalin has the obvious anti-inflammatory (Shen et al., 2003) activity. It is reported that, baicalin can ameliorate the lipopolysaccharide-induced acute lung injury in mice by suppressing oxidative stress and inflammation via the activation of the nuclear erythroid factor 2-mediated heme oxygenase-1 signaling pathway (Ranieri et al., 1999).
Effective Addition of Organic Chloride Salts on Atom Transfer Radical Polymerization in Fluoroalcohols

Atom transfer radical polymerization (ATRP) of methyl methacrylate (MMA) in the presence of organic chloride salts, imidazolium chlorides, using alkyl bromide initiator was carried out in 2,2,2-trifluoroethanol (TFE) at 333 K. The ATRP using a sufficient large amount of chloride salts proceeded in a controlled manner to produce polymers with narrow molecular weight distributions (Mw/Mn < 1.2). The model reaction using an alkyl bromide and the imidazolium chloride indicated that a halogen exchange reaction occurred during the ATRP in TFE to form a chloride-terminated propagating species from the alkyl bromide. ATRP of MMA in TFE using an alkyl chloride initiator and CuCl catalyst, however, gave low initiation efficiency and loss of control over the polymerization. The combination of the alkyl bromide initiator, CuBr, and a sufficient amount of organic chloride salts was very effective to improve the control of ATRP in protic solvents, especially in fluoroalcohols. A methacrylate monomer bearing imidazolium.
Incorporating Stand-up Comedy in Drama Therapy as a Narrative Model

Stand-up comedy is the purposeful use of humor while telling personal thoughts, experiences, and vulnerabilities to an audience. This literature review will explore what constitutes humor, its benefits to psychotherapy, how it exists in drama therapy, applications of narrative therapy, and applying stand-up comedy to drama therapy. By combining stand-up comedy and drama therapy, the author will argue how this combination can provide an additional viewpoint for drama therapy techniques and an alternative and therapeutic aspect to stand-up comedy.
A Real Time Crime Intelligence System using Data Mining

detecting the crime pattern and its frequency in the respective localities the respective paper concentrate particularly about the crime even which happen in very small localities, by developing a system application for the investigating agencies by using the concepts of data mining with the help of comparative analysis of two algorithms i.e. Apriori and apriori tid with the association rule combined. Which lead to the decrease in the crime rate because precaution is better than cure.
AN EXPERIMENTAL ANALYSIS ON EFFECT OF NOISY IMAGE DATASETS ON PERFORMANCE OF DEEP LEARNING MODELS

Deep Learning is a sub field of Machine Learning which works based on neural network structures. Deep Learning has been increasing the capabilities of Artificial Intelligent systems rapidly in many emerging areas like video analytics, data analytics and autonomous systems. The availability of the labelled data is increased due to enhancements in digital technology. The generation and labelling of training data become easier as many advanced and low-cost sensors are developed. Even though various sensors are available, Noise is the one of the major concerns of the database creation. In case of limited availability of data, Noise can be used to normalize the model to avoid overfit. But in huge databases, noise decreases the inference accuracy of the trained model. So, it is very important to understand the effect of noise on model performance. This paper presents an experimental analysis on the individual and combined effect of noise present in training database and validation database. Here, Standard CIFAR-10 database with 60000 images is used as labelled data. A comparative analysis is made to observe the behavior of trained model in terms of inference accuracy against three types of injected noises such as Gaussian Noise, Salt & Pepper Noise and Speckle Noise at different variance levels.
Mind Controlled Robot

The advancement in robot control systems is increased throughout the years and one of the latest technologies introduced in the robot control system is BCI (Brain Computation Interface). The BCI is a alternative technology where the EEG (electroencephalography) signals are used to control the robot for the physically challenged people. In this paper an attempt has been made to control a four wheel robot by different frequency signals generated by the brain and the eye blinks from a person. A Neurosky Headset is used to extract this EEG signals.
THE ROLE OF HIGH FREQUENCY ULTRASOUND IN EARLY DETECTION OF JOINT DISEASE IN PATIENTS WITH HAEMOPHILIA

Background: The study highlights the role of ultrasonography as a non-invasive method to identify early arthropathic changes in patients with haemophilia (PwH). 120 joints were evaluated by Ultrasound (US) in 20 patients with severe haemophilia A (Mean age 11.6 ± 4.36 years; inhibitor negative). The same joints were evaluated in 20 ageand sexmatched control subjects (Mean age 11.20 ± 4.77 years). US images were obtained and US scores were generated. Results: US abnormalities were noted in 7.5% of the control group joints compared to 63.4% of the joints in PwH. Joint effusion was reported in 7.5% of the control group joints (the only finding) compared to 42.5% of the joints in PwH and 31.7% in the healthy joints sub-group of the PwH with no history of previous overt bleeds.The joint US scores were significantly higher in knee joints, significantly lower in patients on prophylaxis, and significantly improved 12 months after the onset of secondary prophylaxis. Also, joint scores increased with increased age, increased ABR, presence of pain with active motion, and in target joints with a high statistical significance. Haemophilia joint health clinical scores (HJHS) correlated well with the US score. Conclusion: Despite the limitations, US could be a valuable tool to detect the earliest sub-clinical joint abnormalities in PwH, correlate the severity of the joint disease to different demographic and clinical variables, reflect the response to replacement protocols and evaluate treatment outcomes on regular patient follow-ups.