Abstract:Climate change (CC) implies recent, rapid and more intense changes in climate. Its effects are reflected by the planet\'s natural processes and in human activities that impact socioeconomic and environmental systems. The research objective was to identify the perception of CC of the inhabitants of Cúlico 2nd Section, Huimango 1st Section and ejido La Chonita, through the Correspondence Analysis (CA) and vulnerability elements, estimating the criteria of Exposure (E), Sensitivity (S) and Adaptive Capacity (CA) that allows strengthening, through social participation, the capacities and values of the population. The study area is located near oil fields that generate environmental impacts, mainly on cocoa (Theobroma cacao) and corn (Zea mays) crops. A qualitative and quantitative analysis was carried out on a sample of 180 individuals. The results suggest that the population is exposed to the consequences of climatic events and degradation of natural resources, that there is sensitivity in their productive systems to diseases and in the quality of basic services, which limits the capacity for adequate response; it is important to generate actions to address local vulnerability, to strengthen the capacities and socio-environmental values of the population and to implement mitigation and adaptation actions, based on social participation and the formation of collaborative networks with other communities
Abstract:A comparison study on Extreme Gradient Boosting, Support Vector Machine, and Deep Learning algorithms, to be specific Python xgboost, SVR from sklearn.svm respectively and LSTM from Keras, is investigated to find out the performance of each algorithm on world climate data. In our experimental study, we used big data on global climate which covers only part of climate data to find out how accurately our ML algorithms predict the climate where the data with limited regional coverage are provided. Keeping in mind that the performance of individual machine learning algorithm is heavily dependent on the dataset, we find XGB shows relatively better performance consuming more computing resources over SVM and LSTM.
Abstract:Rainfall has a vital role in sustainable river watershed management, while river watershed management can also be carried out in various physical and non-physical ways. In certain areas, efforts to physically manage river basins are often hampered by the lack of rainfall data that is representative enough according to the characteristics of the river basin in question so that the existence of TRMM precipitation data can be an alternative to solving solutions. This research used five rain observation stations in the Lesti Watershed with an observation period of 21 years. This research aims to determine the relationship between TRMM 3B42 and observation station postal data by carrying out regression analysis as the method. The study results show that the TRMM 3B42 data shows fairly good accuracy over the entire region on daily and annual time scales, and the TRMM 3B42 rainfall data trend is slightly more significant than the data from rain gauge stations. With the help of the SPSS application, it can be seen that the results of the significance test for two variables have a value of <0.05, so it can be said that the correlation is moderately positive. A positive correlation value means that the relationship between the trend of the observation station rain data and the TRMM rain data has the same direction; this shows that the higher the rain data at the observation station, the higher the TRMM rain data, and vice versa. The validation results of corrected TRMM rain data produce Nash-Sutcliffe Efficiency (NSE), Root Mean Squared Error (RMSE), Correlation Coefficient (R), and Relative Error (RE).
Abstract:Abstract \nBackground: Primary health care acts as the initial point of contact between individuals, families, and the healthcare system, making healthcare easily accessible in the areas where people live and work. Many healthcare systems emphasize the relationship between primary and secondary care, with primary care physicians delivering primary health care (PHC) and identifying patients in need of secondary healthcare. Consequently, strengthening the primary healthcare sector is essential for enhancing both the accessibility and quality of healthcare.to fill the gaps in health infrastructure, a sound referral system is essential. The provision of care services to patients by general practitioners in outpatient university clinics is associated with several challenges, necessitating the referral of patients to specialty clinics for secondary and expert care. The reasons and rates of referral to the specialty clinics differ depending on the patient\'s condition and general practitioners\' competencyTypes of healthcare settings, such as residential care, influenced the patterns of referral to secondary care. Family and resident general practitioners displayed different patterns and rates of referral of their clients.
Abstract:Background and Study Aim: In department of sports sciences students have to be success in theoretical and practical lessons. Especially background of athletic career could be helped individuals about performance in practical lessons, because there are some required difficult basic movements in each sport. If a student hasn’t got an athletic background he/she has a disadvantage. Then sometimes, it might be difficult for an individual to perform in front of the other people. The anxiety levels of students increase while the learning and practicing techniques of different sports in lessons. So, the purpose of this study was to compare the pre and post anxiety levels of students who have learning butterfly and breaststroke swimming due to 8-week training in Department of Sport Sciences.\nMaterial and Methods: In this study most commonly technique in descriptive research models, the survey method is used. The “State-Trait Anxiety Questionnaires” developed by Spielberger et al. in 1970 and adapted to Turkish culture by Öner and Le Compte (1983) were used for data collecting. The data were analyzed by descriptive statistical analyzes, normality test, paired samples t-test performed for pre and post scores comparisons and also t-test and Anova tests were compared with various variables.\nResults: As a result, it was figured out that data had normal distribution. Also, it was determined that there’s no significant difference between the state and trait anxiety scores before and after 8-week lessons. But according to the students’ scores, there were significantly different according to their variables such as; gender, mother’s working statue, athletic statue and fathers’ education statue.\nConclusions: In the field of sports sciences, \"swimming\" lessons especially \"advanced swimming\" lesson is a lesson that students perceive as \"difficult\". In the current study, the state and trait anxiety levels of the students were moderate according to the pre and post score results. Considering that half of the individuals participating in the study are athletes (n=8; 50%), it is understandable that students why have anxiety at medium level. It is seen as a limitation that the selected research group consists of only one university.
Abstract:Asthma is a chronic inflammatory disorder of the respiratory tract characterized by increased\nresponsiveness of the tracheobronchial tree to various stimuli resulting in episodic reversible\nnarrowing and inflammation of the respiratory airways. Bronchial asthma impacts the lifestyle of\nchildren to various extents based on bronchial asthma severity. School-age children with asthma\nexperience more hospitalizations, more school absenteeism, academic under-achievement,\ndecreased overall activity, sleep disturbances, poor self-concept, and disruption of family\nfunctioning when compared to their healthy classmates. This study aimed to assess the\ncontributing factors of asthma among school-age children in the Taif area of Saudi Arabia to\nbetter manage these factors and improve the lifestyle of children. Research methodology:\nAssessment interview sheet was used to collect the data from 100 school-age children\nrespondents; 49 of them (49% incidence) reported having bronchial asthma, whereas 51 of them\ndid not have the diagnosis. Results: More than half of children (52%) had neutral lifestyle,\n(44%) had good life style, while only (4%) of them had bad life style. Conclusion and\nrecommendations: According to the study\'s findings, the majority of the participants led neutral\nlifestyles, with both good and bad lifestyles following suit.
Abstract:Background: Parkinson\'s disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopamine-producing neurons in the brain. It affects approximately 10 million people worldwide and primarily manifests in older adults. Treatment focuses on managing symptoms, but there is currently no cure.\nObjectives: To compile and provide descriptions of medications that has successfully completed Phase 4 clinical trials for the treatment of Parkinson\'s disease in older adults.\nMethods: We examined the applications of the tested medications for Parkinson\'s disease by analyzing relevant phase IV trials that were publicly registered at clinicaltrials.gov\nResults: On March 13, 2023, we found 3,418 trials on clinicaltrials.gov. After filtering, 98 eligible trials remained. Out of those, 44 trials met all the inclusion criteria for the study. 23 medications were tested in these trials, such as rotigotine, pramipexole, and rasagiline, which can help manage symptoms such as pain, non-motor issues (apathy, depression), cognitive impairments, fatigue, and various challenges. Showing effectiveness in managing the symptoms, but no cure has been identified.\nConclusions: The management of Parkinson\'s disease requires careful consideration of specific factors pertaining to the patient, including symptoms, age, and the stage of the disease. A wide range of pharmacological, nonpharmacological, and surgical therapies are available to alleviate patients\' symptoms and enhance their quality of life.
Abstract:The objective of this study was to explore the effect of incorporating mathematical reasoning skills (MRS) in lectures’ made-test (LMT) on students’ mathematics achievement. A mix-method case study design was applied to measure a sample size of 203 undergraduate students and five lecturers. The students’ competency in mathematics was determined by making use of the curriculum for higher education majoring in mathematics education and mathematics. Mathematics examination paper was organized by incorporating MRS questions. Through in-person, one-on-one semi-structured interviews, the students\' opinions regarding the integration of MRS within the LMT were ascertained. The quantitative results, which were subjected to descriptive and regression analyses, showed that the MRS\'s inclusion in the LMT contributed 22,4% of the LMT\'s mastery level in mathematics and 68,1% of the reached mathematics score. One of the difficulties in integrating MRS in the LMT is the lack of student maturity and misconceptions about mathematics. The difficulties in implementing MRS in the LMT had a good impact on lectures\' pedagogical approach in that they were able to come up with a fresh plan for catering to students\' requirements and teaching topics in new ways
Abstract:Universal preventive measures have been implemented to limit the transmission of COVID-19. Public adherence to these preventative measures is influenced by sociodemographic determinants, which impact the knowledge, attitude, and practices (KAP) level towards COVID-19. Therefore, a countrywide survey consisting of sociodemographic determinants and a questionnaire to assess KAP towards COVID-19 was conducted to estimate the differences in KAP based on heterogeneous sociodemographic participants. Data were analyzed using ANOVA (Bonferroni) to compare sociodemographic subgroups. The general linear model (GLM) was used to estimate the association between sociodemographic determinants and COVID-related KAP. Among 1,363 participants, the average knowledge, attitude, and practice scores were 12.34±2.02, 15.47±2.49, and 3.19±1.92, respectively. Healthcare workers and educated participants demonstrated higher knowledge (p<0.001), attitude (p<0.001), and practice (p<0.001). Participants over 50, married, with no history of COVID-19, and full-time employed had a higher knowledge (p<0.001). Female participants had a higher level of knowledge, but they had lower practice (p <0.05). Participants of the Northern region demonstrated better knowledge (p<0.001); however, the Eastern region’s participants had a better attitude (p <0.05). Working in the health sector was the most significant contributor to the model, followed by education status, residence region, employment status, age, gender, history of COVID-19, and marital status. Therefore, sociodemographic factors significantly affect COVID-related KAP.