Misconceptional views about epilepsy exist across social class system of society

Epilepsy affects over 1% of population worldwide. Studies have shown that although our understanding about epilepsy has come a long way, misconceptions about its etiology and treatment exist in rural slums. However, no study has been conducted to see whether such misconceptions exist in middle and upper socio-economic class. This study aims to explore the existence of misconceptions and social stigma in the middle and upper socio-economic class. Materials and Methods: We conducted a survey-based study about epilepsy on 227 participants, belonging to middle and upper socio-economic class. Results: The symptoms of generalized tonic-clonic seizures were correctly described by participants. However, magic, superstition and ‘jin’ were considered as the etiology by some. Incorrect treatment options, like shoe sniffing and ‘taweez’ etc., were also mentioned. Social stigmas regarding sharing information about epilepsy and marrying epileptics also existed. Discussion: Our study shows that although the general understanding about epilepsy was correct in majority of participants belonging to the middle upper socio-economic class, it was restricted to generalized tonic clonic seizures. Key misconceptions regarding the etiology and treatment of epilepsy and social stigma associated with it did exist. These findings emphasize the need to educate all segments of the society about epileps

ISSUES, CHALLENGES AND OPPORTUNITIES IN BLOCKCHAIN-BASED EDUCATIONAL PARADIGMS: A SYSTEMATIC LITERATURE REVIEW PROTOCOL

Blockchain is a new technology that provides services of immutability, trust, disintermediation, collaboration, transparency. Nowadays, the use of this new technology is mostly used for Bitcoin and other cryptocurrencies, but apart from this, blockchain technology improved the performance level of other areas of life i.e. Higher Education Institution (HEI) and stakeholders, certificate verification, and many other domains. Students and educational institutions' important data are mostly shared via different networks. The data integrity, privacy, and security are the major issues for these in blockchain technology which cannot be avoided. This paper is a documented plan for to conduct or a protocol based on which a systematic literature review would be conducted focusing on the issues, challenges, and major strengths of blockchain and its educational paradigms. The result of this review will be highly helpful for the new researchers to overcome the proposed issues and challenges, exploring educational paradigms in Blockchain, elaborate the major strengths helping the educational institutes in adapting process and increase the level of satisfaction. This study plans to explore some educational types with some issues and challenges such as scalability, immutability, and easy adaptation

Assessment of Knowledge and Practice of Various Eye Diseases in Sulaimani: A Descriptive Study

Knowledge and practice of public, especially patients about eye diseases are important to reduce magnitude of human blindness. Vision and sight are very essential because they allow us to connect to each other’s. In accordance to the recently published data; the estimation of 253 million people lives with vision impairment, 36 million are blind and 217 million suffer from moderate to severe vision impairment. A descriptive cross-sectional study was conducted at Shahid Dr. Aso Hospital in Sulaimani city-Iraq, from April to August 2017 by face-to-face interview through close ended questionnaire for data collecting. All data were analyzed by Statistical Package for Social Sciences version 22.0 software. P-value of < 0.05 was considered as a statistically significant. A total of 430 patients were randomly chosen to participate in the study. They were 254 (59.1%) males and 176 (40.9%) females. 76.7% of respondents was worrying about vision loss, 0.7% was worrying about hair loss. Of the participants, 32.8% was with a good knowledge level and 40.5% was with a poor knowledge level, as well as 3.1% was in a good practice and 58.8% was in a poor practice level. Female knowledge mean score was 9.53±4.96 and male knowledge mean score was 8.42±5.45, the practice mean score of males was 4.33±1.96 and mean practice score of females was 4.13±1.93. The study data indicate the worrying of participates about vision loss is in the highest proportion and the awareness and practice of patients about eye diseases is unsatisfactory. Health education campaigns are needed to improve personal awareness about vision related problems and for better eye health

Attendance of Patients with ophthalmological problems about Eye Protection from UV/blue Light Radiation from Sun light and Electronic Devices in Sulaimani City

Ultraviolet (UV) and blue light are affecting eyes during the daily time and may cause many eye’s problems and diseases. Therefore, this study aimed to explore the awareness of patients with ophthalmological problems on UV/blue light protection measures and to evaluate their knowledge and protection measures about radiation that emits from sun light and other electronic devices. It comprised a cross-sectional survey on a representative target population with eye diseases who visited the Shahid Aso Eye Hospital at Sulaimani city (sample size = 500). A special designed cross-sectional questionnaire was performed on a random sampling for data collection from 9th September 2017 to 1st January 2018. The statistical analysis was performed using SPSS version 22.0. There was an even distribution between male and female participants across the groups. The highest percentage of patients with light sensitivity was (79.6%) and the lowest percentage with eye injury was (7.8%). Most of participants had knowledge about the effects of UV/blue light on eye diseases by (52%), cataract (57.8%), glaucoma and red eye with percentage of (45.8%) and (43.4%) respectively. There was a significant difference for the males who were more game-player and using electronic devices like smartphone/tablet /iPad than females. There was a significant difference between male and female participants about the knowledge on harmful effects of radiation from electronic devices. Furthermore, only the patients with sun light sensitivity and cataract had a significant knowledge about harmful effects of radiation from electronic devices on human eyes. Finally, most of the patients with dry eyes, eye/lid infection and glaucoma and cataract had significantly more practices for taking visual breaks when using electronic devices. This study concluded that the patients with ophthalmological problems show a low level of knowledge and protection measurements on the harmful effects of UV/blue light on human eyes and radiation protection. Additionally, this study has discovered that sun protection measures are commonly inadequate among the participants and on a regular basis only a small portion of participants were used the sun protection requirements

Experimental studies on vacancy induced ferromagnetism in undoped TiO2

Room temperature ferromagnetism is observed in undoped TiO2 films deposited on Si substrates using pulsed laser deposition (PLD). The ferromagnetic properties of the samples depend on the oxygen partial pressure during the PLD synthesis. The appearance of higher binding energy component (HBEC) in the oxygen 1s core peak from x-ray photoelectron spectroscopy (XPS) suggests the presence of oxygen vacancies in these samples. The amount of oxygen during the synthesis determines the vacancy concentration in the samples which is directly related to the magnetic behavior of the samples. The magnetic moment decreases with oxygen vacancy concentration in the samples. Valence band measurements were performed to study the electronic structure of both stoichometric and reduced TiO2. The analyses show the presence of Ti 3d band near the Fermi level in reduced TiO2 samples. These bands are otherwise empty in stoichiometric TiO2 and reside in the conduction band which makes them unobservable by XPS. The existence of this Ti 3d band near the Fermi level can possibly lead to Stoner splitting of the band.Comment: 20 pages, 9 figur

The application of GIS based multi-criteria analysis for selecting an optimum water reservoir site

Malaysia is well endowed with abundance of natural water resources, which has significantly contributed to the socio-economic development of the country. However, the situation has somewhat changed over the last decade. The water demand was 174.22 M/l/d in year 2010 and it is projected to be 270.77 M/l/d in 2050. In such scenario, a reliable and safe supply of water for future generations, more and more reservoirs will be required. The aim of this study is to apply GIS in identifying the most suitable location for water reservoir for area of Batu Pahat, Johor, West Malaysia. Methodology is designed in such a way to achieve the objectives of this study as to identify the important criteria for locating water reservoir, to model the location of reservoir using Analytical Hierarchy Process (AHP) and to analyze and evaluate the most potential sites for water reservoir using ArcGIS 10.1 software. Based on the criteria chosen, the data are processed and analyzed the existing 52 reservoir locations and their capacities. Based on the projected number of population for the year 2050, as a result, 5 new reservoir locations have been identified to fulfill the future demands of water for the study area. Thus, it can be concluded that the weights derived from AHP integrated in ArcGIS can be a useful tool in GIS analysis for the determination of suitable locations for water reservoir in the study area

Automatic Topic Title Predicting from News Articles Using Semantic-Based NMF Model

Social medical being a predominant form of communication, millions of texts in terms of news articles, tweets, and snippets are generated worldwide every hour. From them discovering concise and useful knowledge has caught the interest from both academia and the business industry. Since the text document has an infinite amount of contextual information and it is sparse and ambiguous, therefore, learning topics automatically from them is a significant issue and challenge. To address this problem, this research paper proposes a non-negative matrix factorization (NMF) semantics-based model for extracting concise and meaningful topic titles for the text to grasp the whole text theme. The model is efficiently integrated with the semantic correlations between words and their context, which are learned through skip-gram. The NMF method is used to tackle this issue by using a block coordinate algorithm. In terms of topic coherence, extensive quantitative evaluations of the proposed models on a variety of real-world text datasets show that they outperform various state-of-the-art methods. The interpretability of these models demonstrated by qualitative semantic analysis, which identifies significant and consistent topics. It is an effective standard topic model for unstructured sparse text due to its superior performance and simple construction

Application of GIS based multi-criteria analysis in site selection of water reservoirs (case study: Batu Pahat, Malaysia)

Malaysia is well endowed with abundance of natural water resources, which has significantly contributed to the socio-economic development of the country. However, the situation has somewhat changed over the last decade. The aim of this study is to apply GIS in identifying the most suitable location for water reservoir for area of Batu Pahat, Johor in Malaysia. The main criteria selected for this study are pipe line, elevation, rive, Land use, road network, water supply network and slope. Methodology is designed in such a way to achieve the objectives of this study as to identify the important criteria for locating water reservoir, to model the location of reservoir using Analytical Hierarchy Process (AHP) and Weighted Overlay (WO) methods. Based on the criteria chosen, the data are processed and analyzed the existing 52 reservoir locations and their capacities. Based on the projected number of population for the year 2050, as a result, 5 new reservoir locations have been identified to fulfill the future demands of water for the study area. Thus, it can be concluded that the weights derived from AHP integrated in Arc GIS can be a useful tool in GIS analysis for the determination of suitable locations for water reservoir in the study area

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model

Abstract One of the important concerns in the field of exercise immunology is determining the appropriate intensity and duration of exercise to prevent suppression of the immune system. Adopting a reliable approach to predict the number of white blood cells (WBCs) during exercise can help to identify the appropriate intensity and duration. Therefore, this study was designed to predict leukocyte levels during exercise with the application of a machine-learning model. We used a random forest (RF) model to predict the number of lymphocytes (LYMPH), neutrophils (NEU), monocytes (MON), eosinophils, basophils, and WBC. Intensity and duration of exercise, WBCs values before exercise training, body mass index (BMI), and maximal aerobic capacity (VO2 max) were used as inputs and WBCs values after exercise training were assessed as outputs of the RF model. In this study, the data was collected from 200 eligible people and K-fold cross-validation was used to train and test the model. Finally, model efficiency was assessed using standard statistics (root mean square error (RMSE), mean absolute error (MAE), relative absolute error (RAE), root relative square error (RRSE), coefficient of determination (R2), and Nash–Sutcliffe efficiency coefficient (NSE)). Our findings revealed that the RF model performed well for predicting the number of WBC with RMSE = 0.94, MAE = 0.76, RAE = 48.54, RRSE = 48.17, NSE = 0.76, and R2 = 0.77. Furthermore, the results showed that intensity and duration of exercise are more effective parameters than BMI and VO2 max to predict the number of LYMPH, NEU, MON, and WBC during exercise. Totally, this study developed a novel approach based on the RF model using the relevant and accessible variables to predict WBCs during exercise. The proposed method can be applied as a promising and cost-effective tool for determining the correct intensity and duration of exercise in healthy people according to the body’s immune system response