INVESTIGATION OF STUDENTS’ ATTITUDES TOWARD MATHEMATICS IN MIDDLE SCHOOLS IN SAUDI ARABIA

Many students in Saudi Arabia complain that they achieve poor results in mathematics and appear to have a negative attitude toward the subject. The current study, therefore, investigates students’ attitudes towards mathematics, using a mixed method approach, in 13-16 years old students from the intermediate level of education. The age was important because this period is thought to be crucial to the formation of lasting attitudes and opinions. The first main research question, the study aims to address is therefore, “What are students’ attitudes towards mathematics in Saudi middle schools?” The study also aims to explore gender issues using a second research question, “Is there any significant gender difference in students’ attitudes towards mathematics?” The survey was conducted in two government-run middle schools in Saudi Arabia, one boys’ school and one girls’ school, because Saudi Arabia has an exclusively single-sex education system. 180 participants (90 boys and 90 girls) were asked to complete a questionnaire to show their views about mathematics. Qualitative and quantitative data were collected at the same time, but the analysis of each type of information was conducted separately to enable the full picture to be understood. T-test was used to explore any gender differences. The main findings were that both male and female students in two Saudi middle schools show a positive attitude towards mathematics, with female students being slightly more positive than males. The factors which affect attitudes towards mathematics in both genders include the usefulness of mathematics in everyday and future life and career, the teacher, enjoyment of mathematics and the difficulty of the subjects. Girls’ attitudes towards mathematics were also affected by the influence of social media personalities and internet teachers.   Article visualizations

Machine Learning-Based Approach for Modeling the Nanofluid Flow in a Solar Thermal Panel in the Presence of Phase Change Materials

Considering the importance of environmental protection and renewable energy resources, particularly solar energy, the present study investigates the temperature control of a solar panel using a nanofluid (NFD) flow with eco-friendly nanoparticles (NPs) and a phase change material (PCM). The PCM was used under the solar panel, and the NFD flowed through pipes within the PCM. A number of straight fins (three fins) were exploited on the pipes, and the output flow temperature, heat transfer (HTR) coefficient, and melted PCM volume fraction were measured for different pipe diameters (D_Pipe) from 4 mm to 8 mm at various time points (from 0 to 100 min). Additionally, with the use of artificial intelligence and machine learning, the best conditions for obtaining the lowest panel temperature and the highest output NFD temperature at the lowest pressure drop have been determined. While the porosity approach was used to model the PCM melt front, a two-phase mixture was used to simulate NFD flow. It was discovered that the solar panel temperature and output temperature both increased considerably between t = 0 and t = 10 min before beginning to rise at varying rates, depending on the D_Pipe. The HTR coefficient increased over time, showing similar behavior to the panel temperature. The entire PCM melted within a short time for D_Pipes of 4 and 6 mm, while a large fraction of the PCM remained un-melted for a long time for a D_Pipe of 8 mm. An increase in D_Pipe, particularly from 4 to 6 mm, reduced the maximum and average panel temperatures, leading to a lower output flow temperature. Furthermore, the increased D_Pipe reduced the HTR coefficient, with the PCM remaining un-melted for a longer time under the panel.Deanship of Scientific Research at Najran UniversityPeer Reviewe

Numerical Analysis of the Effect of Nanoparticles Size and Shape on the Efficiency of a Micro Heatsink

In this paper, two novel micro heat sinks (MHSs) were designed and subjected to thermal analysis using a numerical method. The fluid used was Boehmite alumina–water nanofluid (NFs) with high volume fractions (VOFs). Studies were conducted to determine the influence of a variety of nanoparticle (NP) shapes, such as platelet brick, blade, cylinder, and Os. The heatsink (HS) was made of copper, and the NFs entered it through the middle and exited via four outlets at the side of the HS. The finite element method was used to simulate the NFs flow and heat transfer in the HSs. For this purpose, Multi Physics COMSOL software was used. The maximum and middle values of HS temperature (T-MAX and T-Mid), thermal resistance (TH-R), heat transfer coefficient (h), FOM, etc., were studied for different NP shapes, and with Reynolds numbers (Re) of 300, 1000, and 1700, and VOFs of 0, 3, and 6%. One of the important outcomes of this work was the better thermal efficiency of the HS with rectangular fins. Moreover, it was discovered that a rise in Re increased the heat transfer. In general, adding NPs with high VOFs to MHSs is not appropriate in terms of heat. The Os shape was the best NP shape, and the platelet shape was the worst NP shape for high NPVOF. When NPs were added to an MHS, the temperature of the MHS dropped by an average of 2.8 or 2.19 K, depending on the form of the pin-fins contained inside the MHS (circular or square). The addition of NPs in the MHS with circular and square pin-fins enhanced the pressure drop by 13.5% and 13.3%, respectively, when the Re = 1700.National Research Priorities funding programPeer Reviewe

Investigating the Effect of Tube Diameter on the Performance of a Hybrid Photovoltaic–Thermal System Based on Phase Change Materials and Nanofluids

The finite element (FEM) approach is used in this study to model the laminar flow of an eco-friendly nanofluid (NF) within three pipes in a solar system. A solar panel and a supporting phase change material (PCM) that three pipelines flowed through made up the solar system. An organic, eco-friendly PCM was employed. Several fins were used on the pipes, and the NF temperature and panel temperature were measured at different flow rates. To model the NF flow, a two-phase mixture was used. As a direct consequence of the flow rate being raised by a factor of two, the maximum temperature of the panel dropped by 1.85 °C, and the average temperature dropped by 1.82 °C. As the flow rate increased, the temperature of the output flow dropped by up to 2 °C. At flow rates ranging from low to medium to high, the PCM melted completely in a short amount of time; however, at high flow rates, a portion of the PCM remained non-melted surrounding the pipes. An increase in the NF flow rate had a variable effect on the heat transfer (HTR) coefficient.The Deanship of Scientific Research at Najran UniversityPeer Reviewe

Profile Analysis of COVID-19 Patients in Jambi Province

Background: The potential for COVID-19 transmission has increased sharply, so the government must implement various strategies to control the spread, especially in Jambi Province. The number of positive confirmed cases of COVID-19 in Jambi Province until August 26, 2021, was 27,422 people, with a case fatality rate is 2.37%. This condition illustrates that the spread of COVID-19 is increasing every day, so the government has set a lockdown at Level 4. Method: This research aims to analyze the profile of COVID-19 patients in Jambi Province (secondary data analysis) with a cross-sectional study design. Data analysis includes univariate analysis with the mean difference test and Chi-Square test. Result: The results show that the age of COVID-19 patients is significantly different between men and women. Furthermore, based on the Chi-Square test, it shows a significant relationship between age and gender and between region and age with a p-value <0.05. Conclusion: Indeed, the risk of COVID-19 cases increases with age and differs for each gender with a high level of mobility

ASSOCIATION BETWEEN LOCUS OF CONTROL OF HEALTH, RELIGIOUS ATTITUDE, AND SPIRITUALITY IN OLDER ADULTS IN PSYCHIATRIC HOSPITALS OF JEDDAH

Background: A common perception in Muslim society is there that, in old age people see God (Allah) to close as well as they spend most of their time in worshiping and other religious as well spiritual based activities. While role of health and locus of health control is also playing such religious and spiritual practices. Aim of Study: To check the correlation between health locus of control, religious attitude, and spirituality among older Saudi Arabians adults Method: A cross-sectional descriptive research design was used on the 109 older adults, who were selected through online questionnaire by using convenient purposive sampling technique. As we used three questionnaire such as health locus of control, religious attitude scale and spirituality index. Findings & Results: It was found that older adults have a high level of religious attitude as 71.2% and spirituality as 80.1%. The correlation of the sub-domain of health locus of control in its powerful others dimension has a low but statistically significant correlation with religious attitude (r = .278, p < .01) and does not have a correlation with spirituality, thus, a level high religious attitude makes it more likely that older adults have a locus of control over health powerful others at a high level (odds = 3.11, 2.21 – 7.22).  Conclusion: There is higher level of religious attitude in Saudi older Adults. While health locus of control has a significant impact in practicing religious activities as well as showing spirituality

Machine learning-based approach for modeling the nanofluid flow in a solar thermal panel in the presence of phase change materials

Considering the importance of environmental protection and renewable energy resources, particularly solar energy, the present study investigates the temperature control of a solar panel using a nanofluid (NFD) flow with eco-friendly nanoparticles (NPs) and a phase change material (PCM). The PCM was used under the solar panel, and the NFD flowed through pipes within the PCM. A number of straight fins (three fins) were exploited on the pipes, and the output flow temperature, heat transfer (HTR) coefficient, and melted PCM volume fraction were measured for different pipe diameters (D_Pipe) from 4 mm to 8 mm at various time points (from 0 to 100 min). Additionally, with the use of artificial intelligence and machine learning, the best conditions for obtaining the lowest panel temperature and the highest output NFD temperature at the lowest pressure drop have been determined. While the porosity approach was used to model the PCM melt front, a two-phase mixture was used to simulate NFD flow. It was discovered that the solar panel temperature and output temperature both increased considerably between t = 0 and t = 10 min before beginning to rise at varying rates, depending on the D_Pipe. The HTR coefficient increased over time, showing similar behavior to the panel temperature. The entire PCM melted within a short time for D_Pipes of 4 and 6 mm, while a large fraction of the PCM remained un-melted for a long time for a D_Pipe of 8 mm. An increase in D_Pipe, particularly from 4 to 6 mm, reduced the maximum and average panel temperatures, leading to a lower output flow temperature. Furthermore, the increased D_Pipe reduced the HTR coefficient, with the PCM remaining un-melted for a longer time under the panel.The Deanship of Scientific Research at Najran University.https://www.mdpi.com/journal/processesam2023Mechanical and Aeronautical Engineerin

An Analysis of the Binding Characteristics of a Panel of Recently Selected ICAM-1 Binding Plasmodium falciparum Patient Isolates.

The basis of severe malaria pathogenesis in part includes sequestration of Plasmodium falciparum-infected erythrocytes (IE) from the peripheral circulation. This phenomenon is mediated by the interaction between several endothelial receptors and one of the main parasite-derived variant antigens (PfEMP1) expressed on the surface of the infected erythrocyte membrane. One of the commonly used host receptors is ICAM-1, and it has been suggested that ICAM-1 has a role in cerebral malaria pathology, although the evidence to support this is not conclusive. The current study examined the cytoadherence patterns of lab-adapted patient isolates after selecting on ICAM-1. We investigated the binding phenotypes using variant ICAM-1 proteins including ICAM-1Ref, ICAM-1Kilifi, ICAM-1S22/A, ICAM-1L42/A and ICAM-1L44/A using static assays. The study also examined ICAM-1 blocking by four anti-ICAM-1 monoclonal antibodies (mAb) under static conditions. We also characterised the binding phenotypes using Human Dermal Microvascular Endothelial Cells (HDMEC) under flow conditions. The results show that different isolates have variant-specific binding phenotypes under both static and flow conditions, extending our previous observations that this variation might be due to variable contact residues on ICAM-1 being used by different parasite PfEMP1 variants

Phobia Exposure Therapy Using Virtual and Augmented Reality: A Systematic Review

A specific phobia is a common anxiety-related disorder that can be treated efficiently using different therapies including exposure therapy or cognitive therapy. One of the most famous methods to treat a specific phobia is exposure therapy. Exposure therapy involves exposing the target patient to the anxiety source or its context without the intention to cause any danger. One promising track of research lies in VR exposure therapy (VRET) and/or AR exposure therapy (ARET), where gradual exposure to a negative stimulus is used to reduce anxiety. In order to review existing works in this field, a systematic search was completed using the following databases: PubMed, ProQuest, Scopus, Web of Science, and Google Scholar. All studies that present VRET and/or ARET solutions were selected. By reviewing the article, each author then applied the inclusion and exclusion criteria, and 18 articles were selected. This systematic review aims to investigate the previous studies that used either VR and/or AR to treat any type of specific phobia in the last five years. The results demonstrated a positive outcome of virtual reality exposure treatment in the treatment of most phobias. In contrast, some of these treatments did not work for a few specific phobias in which the standard procedures were more effective. Besides, the study will also discuss the best of both technologies to treat a specific phobia. Furthermore, this review will present the limitations and future enhancements in this field

Short-Term Prediction of COVID-19 Using Novel Hybrid Ensemble Empirical Mode Decomposition and Error Trend Seasonal Model

In this article, a new hybrid time series model is proposed to predict COVID-19 daily confirmed cases and deaths. Due to the variations and complexity in the data, it is very difficult to predict its future trajectory using linear time series or mathematical models. In this research article, a novel hybrid ensemble empirical mode decomposition and error trend seasonal (EEMD-ETS) model has been developed to forecast the COVID-19 pandemic. The proposed hybrid model decomposes the complex, nonlinear, and nonstationary data into different intrinsic mode functions (IMFs) from low to high frequencies, and a single monotone residue by applying EEMD. The stationarity of each IMF component is checked with the help of the augmented Dicky–Fuller (ADF) test and is then used to build up the EEMD-ETS model, and finally, future predictions have been obtained from the proposed hybrid model. For illustration purposes and to check the performance of the proposed model, four datasets of daily confirmed cases and deaths from COVID-19 in Italy, Germany, the United Kingdom (UK), and France have been used. Similarly, four different statistical metrics, i.e., root mean square error (RMSE), symmetric mean absolute parentage error (sMAPE), mean absolute error (MAE), and mean absolute percentage error (MAPE) have been used for a comparison of different time series models. It is evident from the results that the proposed hybrid EEMD-ETS model outperforms the other time series and machine learning models. Hence, it is worthy to be used as an effective model for the prediction of COVID-19