User Activity Classification and Domain-Wise Ranking Through Social Interactions

Twitter has gained a significant prevalence among the users across the numerous domains, in the majority of the countries, and among different age groups. It servers a real-time micro-blogging service for communication and opinion sharing. Twitter is sharing its data for research and study purposes by exposing open APIs that make it the most suitable source of data for social media analytics. Applying data mining and machine learning techniques on tweets is gaining more and more interest. The most prominent enigma in social media analytics is to automatically identify and rank influencers. This research is aimed to detect the user's topics of interest in social media and rank them based on specific topics, domains, etc. Few hybrid parameters are also distinguished in this research based on the post's content, post’s metadata, user’s profile, and user's network feature to capture different aspects of being influential and used in the ranking algorithm. Results concluded that the proposed approach is well effective in both the classification and ranking of individuals in a cluster.

The Impact of Covid-19 on Ophthalmological Emergency Department Visits at King Khaled Eye Specialist Hospital in Riyadh City, Saudi Arabia

Purpose: This study aimed to assess the impact of COVID-19 on ophthalmological emergency department visits at King Khaled eye specialist hospital in Riyadh city, Saudi Arabia. Method: A Retrospective Record Review was conducted at KKESH in Riyadh city during a pandemic period from 2 March to 30 June of 2019 and same period in 2020. Data include all patients who visited the ophthalmology emergency department with all age groups.

HuDA_COVID Human Disposition Analysis during COVID-19 using Machine Learning

Coronavirus has greatly impacted various aspects of human life, including human psychology & human disposition. In this paper, we attempted to analyze the impact of the COVID-19 pandemic on human health. We propose Human Disposition Analysis during COVID-19 using machine learning (HuDA_COVID), where factors such as age, employment, addiction, stress level are studied for human disposition analysis. A mass survey is conducted on individuals of various age groups, regions & professions, and the methodology achieved varied accuracy ranges of 87.5% to 98%. The study shows people are worried about lockdown, work & relationships. Furthermore, 23% of the respondents have not had any effect. 45% and 32% have had positive and negative effects, respectively. It is a novel study in human disposition analysis in COVID-19 where a novel weighted assignment indicating the health status is also proposed. HuDA_COVID clearly indicates a need for a methodical approach towards the human psychological needs to help the social organizations formulating holistic interventions for affected individuals.

Prevalence and diversity of ectoparasites in Wild Rock Pigeon (Columba livia) in Punjab region, Pakistan

The current study was carried out to estimate the prevalence and diversity of ectoparasites in rock pigeons in different regions of Punjab, Pakistan. A total of 120 birds were captured from March 2017 to February 2019. The ectoparasites were collected by standard procedures and preserved in 70% ethanol containing one drop of glycerin. Data related to age, health status, sex, type of area, sampling location and season were collected using a standardized form. Ectoparasites were identified based on morphological characteristics by using identification keys. Ninety-six (80%) birds were infested with ectoparasites. A total of seven families and thirteen species of different ectoparasites were observed. Mainly, seven species of lice, two species of flies, one species of tick and three species of mites were recovered from infested birds. The female pigeons were more often infested (89.02%) than male pigeons (60.52%). The prevalence was found higher during summer (100%) as compared to other seasons. The infestation rate was higher in Industrial area (97.50%) as compared to other regions. The highest prevalence of ectoparasites (100%) was recorded from Sargodha district. There was significant (P < 0.05) variation among number of ectoparasites on wing, chest, tail and neck within age groups, seasons and ecological zones. The occurrence of parasites in relation to area, age, health status, sex and season were significant. The infestation rate of parasites in rock pigeon is high in different districts of Punjab. It is recommended that these wild birds infested with multiple species of ectoparasites could be the potential source of infestations in domesticated birds if they come in contact with them. The contact of domesticated birds should be prevented from wild birds to minimize the chance of cross species transmission of ectoparasites.

PREVENTION OF CANDIDIASIS IN PATIENTS USING REMOVABLE DENTURES

Despite innovations in orthopedic dentistry, removable dentures belong to the most popular orthopedic care category. Removable dentures are combined stimuli that affect the mucous membrane and neuro-receptor apparatus. Acrylic plastic prostheses, widely used in prosthetic dentistry, have a negative side mechanical, chemical-toxic, sensitizing, and thermal insulating effect on oral tissue and prosthetic impression area. This is often complicated by a violation of the biocenosis of the oral cavity, the growth of pathogenic microflora that releases toxins, especially an increase in the number of yeast colonies that irritate the oral mucosa and prosthetic stomatitis. It was observed 100 patients with oral candidiasis of various age groups from 45 to 65 years. Of these, 60 patients with removable plate prostheses; 40 patients with partially removable prostheses. Chronic forms of candidiasis were diagnosed in 40 patients and with exacerbation of chronic forms of candidiasis in 60 people. The number of untreated carious cavities and poor hygienic condition of the oral cavity directly affects the severity of candidiasis. Acute forms of candidiasis were observed mainly in patients with high DMF and PMA indices. The severity of candidiasis depends on the degree and duration of wearing dentures and hygienic conditions - the most severe forms of invasive candidiasis were observed in the presence of removable plate prostheses, the complete absence of teeth, and the use of a prosthesis for more than 10-15 years. A combined lesion of the oral mucosa and the red border of the lips was observed mainly in patients older than 60 years. The presence of candidiasis in the oral cavity in patients with removable plate prostheses leads to a statistically significant change in the indicators of local immunity of the oral cavity: an increase in the concentration of serum IgG and IgA and the values of the coefficient of the balance of local immunity factors.

HuDA_COVID Human Disposition Analysis During COVID-19 Using Machine Learning

Coronavirus has greatly impacted various aspects of human life, including human psychology & human disposition. In this paper, we attempted to analyze the impact of the COVID-19 pandemic on human health. We propose Human Disposition Analysis during COVID-19 using machine learning (HuDA_COVID), where factors such as age, employment, addiction, stress level are studied for human disposition analysis. A mass survey is conducted on individuals of various age groups, regions & professions, and the methodology achieved varied accuracy ranges of 87.5% to 98%. The study shows people are worried about lockdown, work & relationships. Furthermore, 23% of the respondents have not had any effect. 45% and 32% have had positive and negative effects, respectively. It is a novel study in human disposition analysis in COVID-19 where a novel weighted assignment indicating the health status is also proposed. HuDA_COVID clearly indicates a need for a methodical approach towards the human psychological needs to help the social organizations formulating holistic interventions for affected individuals.

Factors Affecting Customer Intention to Adopt a Mobile Chronic Disease Management Service

The Mobile Chronic Disease Management Service (MCDMS) is an emerging medical service for chronic disease prevention and treatment, but limited attention has been paid to the factors that affect users’ intention to adopt the service. Based on the unified theory of acceptance and use of technology 2 and the protection motivation theory, the authors built an MCDMS adoption model. The authors also verified the differentiating age effect on the service adoption intention from experiential distance perspective of the construal level theory. Empirical results showed that the young group focused more on the impact of effort expectancy, whereas the elderly group focused more on performance expectancy, imitating others, and perceived severity. Furthermore, the young group, however, focused more on the impact of perceived vulnerability, and offline medical habits showed no significant influence on either group’s intention to adopt, which were not consistent with the original hypotheses. The findings can aid MCDMS providers in selecting marketing strategies targeted toward different age groups.

User’s Activity Classification And Domain Wise Ranking Through Social Interactions

Twitter has gained a significant prevalence among the users across the numerous domains, in the majority of the countries, and among different age groups. It servers a real-time micro-blogging service for communication and opinion sharing. Twitter is sharing its data for research and study purposes by exposing open APIs that make it the most suitable source of data for social media analytics. Applying data mining and machine learning techniques on tweets is gaining more and more interest. The most prominent enigma in social media analytics is to automatically identify and rank influencers. This research is aimed to detect the user's topics of interest in social media and rank them based on specific topics, domains, etc. Few hybrid parameters are also distinguished in this research based on the post's content, post’s metadata, user’s profile, and user's network feature to capture different aspects of being influential and used in the ranking algorithm. Results concluded that the proposed approach is well effective in both the classification and ranking of individuals in a cluster.

A Case study on Hypermetropia in North Uttar Pradesh Population

India has done a very much towards to become a developed country but still India is a part of developing countries and for this reason most of the factors are responsible and from these one of the factor is poverty and their index. Poverty index, directly affect the standard of living in a population , that why various major and minor diseases are occur in the various age groups of people, and Hypermetropia is one of these that can occur due to unhealthy life style. Hyperopia, also termed hypermetropia or farsightedness, is a common refractive error in children and adults. Its effect on an individual and the symptoms produced varies greatly, depending on the magnitude of hyperopia, the age of the individual, the status of the accommodative and convergence system, and the demands placed on the visual system. Individuals with uncorrected hyperopia may experience symptoms such as blurred vision, asthenopia (e.g., headaches and eyestrain) while reading, accommodative/binocular dysfunction, amblyopia, and/or strabismus. This article outlines several discussion points as related to hyperopia: definition and classifications, prevention, clinical presentations, importance of early detection, examination techniques, risks of uncorrected hyperopia, and management strategies. Keywords: Amblyopia, Hyperopia, Refractive error, Strabismus, Visual development.