Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship Between Motivation and Academic Performance Among Medical Students in Riyadh

Background: Motivation is the process whereby goal‐directed activities are initiated and sustained. Motivation is a crucial factor in academic achievement. The study aims to measure students' demographic factors and external environments' effect on their motivation and determine the impact of students' motivation and self-efficacy on their learning engagement and academic performance. Methodology: This is a cross-sectional study that involved distributing an online digital questionnaire, which was applied in the capital of Saudi Arabia, "Riyadh. " The students’ motivation was assessed using three scales that are designed to measure the students' intrinsic/extrinsic motivation, self-efficacy, and learning engagement. Results: In this study, we collected 429 responses from our distributed questionnaire among medical students where males represented 60.1% of the sample. Moreover, we classified the satisfaction level into five subcategories: very satisfied, satisfied, neutral, unsatisfied, and very unsatisfied. We found that most of the students (38.7%) were satisfied with their academic performance, while 17.7% were strongly satisfied. The mean enrollment motivation score in this study was 19.83 (SD 2.69), and when determining its subcategories, we found that the mean intrinsic motivation score was 10.33 (out of 12) and the mean extrinsic motivation score was 10.23 (out of 12). Moreover, the mean self-efficacy score was 9.61 and the mean learning engagement score was 8.97 (out of 12). Moreover, we found that a longer duration needed by the students to reach the college from their residence is significantly associated with lower learning engagement reported by the students (8.54 vs. 9.13 in shorter times, P=0.034). Finally, we found that students who entered medical school as their first choice had significantly higher intrinsic motivation, extrinsic motivation, self-efficacy, and learning engagement. Conclusion: A student's preference for entering medical school will affect their motivation, self-efficacy, and learning engagement. Moreover, intrinsic and extrinsic motivations significantly correlate with self-efficacy and satisfaction with academic performance; however, they have no effect on the grade point average (GPA) of the last semester. The only factor that positively correlates with students' GPA is learning engagement.
Efficient Three-Dimensional Global Models for Climate Studies: Models I and II

Abstract A global atmospheric model is developed with a computational efficiency which allows long-range climate experiments. The model solves the simultaneous equations for conservation of mass, energy and momentum, and the equation of state on a grid. Differencing schemes for the dynamics are based on work of Arakawa; the schemes do not need any viscosity for numerical stability, and can thus yield good results with coarse resolution. Radiation is computed with a semi-implicit spectral integration, including all significant atmospheric gases, aerosols and cloud particles. Cloud cover and vertical distribution are computed. Convection mixes moisture, heat and momentum, with buoyant air allowed to penetrate to a height determined by its buoyancy. Ground temperature calculations include diurnal variation and seasonal heat storage. Ground hydrology incorporates a water-holding capacity appropriate for the root zone of local vegetation. Snow depth is computed. Snow albedo includes effects of snow age and mas.
A systematic review to introduce the most effective postbiotics derived from probiotics for aflatoxin detoxification in vitro

The purpose of this study was to gather information about the percentage of aflatoxin decontamination by postbiotics and to find the most effective postbiotic. In this review article, studies were collected from databases. All the articles related to experimental studies were included in the study. It appeared that the postbiotics derived from Lentilactobacillus kefiri, Lentilactobacillus kefiri, Lacticaseibacillus rhamnosum, Lacticaseibacillus rhamnosum and Pediococcus pentosaceus probiotic bacteria were the most effective postbiotics with 97.22%, 95.27%, 86.2%, 81.4% and 91% inhibitory effect against aflatoxins B1, B2, G1, G2 and M1, respectively. Therefore, postbiotics could be used as safe anti-aflatoxin agents in food products.
EEG and ECG-Based Multi-Sensor Fusion Computing for Real-Time Fatigue Driving Recognition Based on Feedback Mechanism

A variety of technologies that could enhance driving safety are being actively explored, with the aim of reducing traffic accidents by accurately recognizing the driver’s state. In this field, three mainstream detection methods have been widely applied, namely visual monitoring, physiological indicator monitoring and vehicle behavior analysis. In order to achieve more accurate driver state recognition, we adopted a multi-sensor fusion approach. We monitored driver physiological signals, electroencephalogram (EEG) signals and electrocardiogram (ECG) signals to determine fatigue state, while an in-vehicle camera observed driver behavior and provided more information for driver state assessment. In addition, an outside camera was used to monitor vehicle position to determine whether there were any driving deviations due to distraction or fatigue. After a series of experimental validations, our research results showed that our multi-sensor approach exhibited good performance for driver state recognition. This study could provide a solid foundation and development direction for future in-depth driver state recognition research, which is expected to further improve road safety.
Realtime Malicious Traffic Detection Targeted for TCP Out-of-Order Packets Based on FPGA

Currently, with the increasing popularity of high-speed network, in order to protect the network environment, more and more companies start to explore how to efficiently detect malicious traffic. On the software side, traditional detection systems are usually based on CPU which will consume multi-core processing ability to handle huge network traffic. On the hardware side, current researches focus on using specific hardware to offload some functions such as string matching in malicious traffic detection. However, they cannot detect attack behaviors hidden in TCP out-of-order (OOO) packets well, which are very common in modern complex network environments. To deal with this problem, we present an FPGA-based realtime malicious traffic detection method especially to inspect TCP OOO packets. It employs two core function designs for efficient malicious traffic inspection: TCP OOO reassembly and hierarchical packet match. First, the TCP OOO packets are reassembled to in-order packets to prevent the omission check of malicious traffic. Second, we adapt a hierarchical packet match design which can not only detect the packet header and filter the matching traffic, but also has the ability to inspect the carried payload to further determine whether the traffic is benign or malicious. We use Xilinx Alveo U50 accelerator card as the implementation platform to achieve high speed detection. This paper aims to provide a full detection path and implement all the reassembly and inspection process within an FPGA board. We adapt Cisco TRex as the traffic generator to evaluate the system from detection throughput, resource utilization and power consumption. Compared with the CPU-based approaches, the experiment results show that our system has 485% detection throughput increase and 68% average power decrease.
Analysing the Impact of Sudden Capital Inflow Shocks on Kenya's Economic Growth: A Quarterly Time Series Analysis (2008 - 2022)

Economic growth indicates the ability of a country to alleviate the poverty rate, reduce the unemployment rate, attain a surplus in balance of payments, and achieve a sustainable increase in gross domestic product (GDP). To achieve improved and continued growth of the economy in a country, there is a need to consider the stability of macroeconomic factors. Therefore, this study sought to examine the effect of capital inflow shocks on Kenya’s economic growth. The study employed a correlational design using time series quarterly data for a period of fourteen years, spanning from 2008 to 2022. The unit root test realized that capital inflow shock was stationary at levels since p-value<0.05. Correlational analysis results revealed that capital inflow shock had a significant, positive impact on the growth of the economy in Kenya, with a numerical result of 0.7001 and a p-value of 0.0000. Further, the regression analysis results gave a correlational coefficient of 0.3022 and a p-value of 0.0000. Thus, the study recommends that the government reform the existing policies to favor foreign investors and to avoid depending so much on externality to reduce susceptibility to external shocks. In order for Kenya to fulfill the millennial development goals, the government must foster an atmosphere that will attract foreign investors through programs like public-private partnerships (PPP), tax regulations, and other incentives to boost capital inflows.
Combined helical tomotherapy and Gamma Knife stereotactic radiosurgery for high-grade recurrent orbital meningioma: a case report

Orbital meningioma is a rare type of orbital tumor with high invasiveness and recurrence rates, making it extremely challenging to treat. Due to the special location of the disease, surgery often cannot completely remove the tumor, requiring postoperative radiation therapy. Here, we report a case of an elderly male patient with right-sided proptosis, visual impairment, and diplopia. Imaging diagnosis revealed a space-occupying lesion in the extraconal space of the right orbit. Pathological and immunohistochemical examination of the resected tumor confirmed it as a grade 3 anaplastic meningioma. Two months after surgery, the patient complained of right eye swelling and a magnetic resonance imaging (MRI) scan showed a recurrence of the tumor. The patient received helical tomotherapy (TOMO) in the postoperative tumor bed and high-risk areas within the orbit with a total dose of 48Gy. However, there was no significant improvement in the patient’s right eye swelling, and the size of the recurrent lesion showed no significant change on imaging. Gamma knife multifractionated stereotactic radiosurgery (MF-SRS) was then given to the recurrent lesion with 50% prescription dose 13.5Gy/3f, once every other day. An imaging diagnosis performed 45 days later showed that the tumor had disappeared completely. The patient’s vision remained unchanged, but diplopia was significantly relieved after MF-SRS. We propose a new hybrid treatment model for recurrent orbital meningioma, where conventional radiation therapy ensures local control of high-risk areas around the postoperative cavity, and MF-SRS maximizes the radiation dose to recurrent lesion areas while protecting surrounding tissues and organs.
Multicore Fiber Based Phase-Modulation Interferometer for Demodulation of a Fiber Bragg Grating Accelerometer

In this article, we propose a phase-modulation interferometer based on Multicore fiber for demodulation of a fiber Bragg grating (FBG) accelerometer using a multicore fiber (MCF) interferometer. The MCF interferometer are made by using two parallel spatial cores of the MCF. A Michelson interference can be generated by reflected light from two independent cores of a winding MCF. We experimentally demonstrate that the vabriation signal demodulation of a felxible hinge FBG accelerometer using the proposed MCF interferometer system. The experiment results show that the phase demodulation scheme of the FBG accelerometer based on MCF interferometer proposed in this article can demodulate the acceleration with a sensitivity of 2.3 $\pm$ 0.3 rd/g at a frequency band of 20–130 Hz. The usage of the MCF interferometer enhance the integration of the phase demodulation system of the FBG sensors and also show potentials in other optical interferometry and sensing applications.
Two‐dimensional electrical section beneath the eastern margin of Japan Sea

Four ocean bottom electromagnetometers provided seafloor geoelectromagnetic data for more than nine months in order to reveal mantle dynamics beneath the eastern margin of Japan Sea, where several large and hazardous earthquakes have repeatedly occurred so far. High‐quality magnetotelluric (MT) data from the seafloor array, together with those of four additional land sites in northeast Japan, were analyzed and carefully corrected for topographic/bathymetric effects to extract two‐dimensional (2D) MT responses at each site. Here we show how the 2D electrical section derived by inverting the corrected 2D MT responses depicts fluid injection deep into the wedge and back‐arc mantle by the cold and fast subducting Pacific plate. A high conductivity anomaly found beneath the Sado Ridge at depths ranging from 150 to 200 km may be direct field evidence that supports water transportation from the Earth's surface to the wedge and back‐arc mantle in the form of serpentinite.
SUPPORT OF FAMILY ECONOMIC STATUS FOR FULFILLING THE RIGHT TO EDUCATION FOR CHILDREN WITH DISABILITIES

Recognizing the right to education is essential for all groups, including children with disabilities. Therefore, this research was conducted to analyze the relationship between family economic support and the family’s ability to fulfill the educational rights of children with disabilities. Research on disability enhances knowledge in special education and inclusive practices, refining teaching methods and support systems additionally, understanding the vital role of families to advocate for their children's educational rights. This study uses a qualitative approach with a descriptive method. The informant who participated in this study was one of the special school teachers in Yogyakarta who was selected by purposive sampling and had voluntarily agreed to become an informant. Data was collected through structured in-depth interviews and documentation and analyzed inductively. The study results show that family economic support is not the main obstacle in realizing the right to education for children with disabilities. A more significant obstacle that arises in realizing the rights of children with disabilities is parents’ perception in educating their children whether they attend school or not. The results of this study indicate that parents must realize that the right to education must be given to all children, including children with disabilities. Apart from special education, inclusive education must also be widely promoted to increase awareness and the responsibility of parents or families toward their children’s right to education
Forecasting Construction Cost Index through Artificial Intelligence

This study presents a novel approach for forecasting the construction cost index (CCI) of building materials in developing countries. Such estimations are challenging due to the need for a longer time, the influence of inflation, and fluctuating project prices in developing countries. This study used three techniques—a modified Artificial Neural Network (ANN), time series, and linear regression—to predict and forecast the local building material CCI in Pakistan. The predicted CCI is based on materials, including bricks, steel, cement, sand, and gravel. In addition, the swish activation function was introduced to increase the accuracy of the associated algorithms. The results suggest that the ANN model has superior prediction results, with the lowest Mean Error (ME), Mean Absolute Error (MAE), and Theil’s U statistic (U-Stat) values of 0.04, 28.3, and 0.62, respectively. The time series and regression models have ME values of 0.22 and 0.3, MAE values of 30.07 and 28.3, and U-Stat values of 0.65 and 0.64, respectively. The proposed models can assist contractors, project managers, and owners through an accurately estimated cost index. Such accurate CCIs help correctly estimate project budgets based on building material prices to mitigate project risks, delays, and failures.
Relations between geological characteristics and satellite‐derived infrared and microwave emissivities over deserts in northern Africa and the Arabian Peninsula

[1] Infrared and microwave emissivities have been previously calculated over the globe from satellite observations to estimate the longwave radiative budget of the planet in global circulation models (GCM) or to facilitate the assimilation of surface-sensitive satellite observations over land in numerical weather prediction (NWP) models. This study examines the relationship between these emissivities and the soil lithology over the deserts in northern Africa and the Arabian Peninsula at large scales. For this purpose, a lithology map of the area has been carefully derived from combining several geological maps and in situ lithostratigraphic columns. Infrared and microwave emissivities show large spatial variability, much more than often assumed in GCM or in NWP models, that relate well to the surface properties, especially the lithology. Changes in the lithology explain ∼40% and up to 50% of the emissivities variability at the considered frequencies in the infrared and in the microwaves. In particular, siliceous and carbonate outcrops have specific signatures that can be identify in these wavelength ranges, with a surprisingly good sensitivity of the microwaves to the presence of carbonates. This study clearly indicates that geological information is necessary for emissivity modeling, not only in the infrared but also in the microwaves, for GCM and NWP applications. The lithology maps created from the geological maps for this study is available under request. Our study also suggests that the combination of infrared and microwave emissivities has some potential for lithology mapping at large scales, especially for land surface models.
The Antidiabetic Activity of Combining the Aqueous Extracts of Vernonia amygdalina Leaves and Tamarindus indica Fruit Pulp in Streptozotocin-Induced Wistar Rats

Background Many plants are used to reduce the side effects of diabetes mellitus. These plants (including Vernonia amygdalina and Tamarindus indica) are rich in phytochemical compounds that have the ability to reduce glycemia and the effect of diabetes-related oxidative stress. In this study, we aimed to investigate the antioxidant and antidiabetic activities of combining V. amygdalina leaves and T. indica pulp extracts. Methodology We prepared a mixture by combining V. amygdalina leaves and T. indica pulp extracts, and we assessed antioxidant properties via the capacity of both extracts to reduce ferric ions, 2,2-diphenyl-1-picryl-hydrazyl (DPPH) radicals, and hydroxyl radicals. We also assessed antidiabetic properties through the capacity of the extracts’ combination to inhibit alpha-amylase. We evaluated crude fiber, total phenols content (TPC), and total flavonoid content (TFC). Results From our findings, the combination at a concentration of 200 μg/mgE showed that a percentage of 55.17±1.2 could reduce DPPH radicals, 0.366±0.012 could scavenge ferric ions, and 0.233±0.0022 could reduce hydroxyl radicals. With regard to secondary metabolites, we obtained 16.96±0.17 mEGA/gE for total phenol content, 1.74±0.045 mECAT/gE for total flavonoid content, and crude fiber content in our combination at 6.87±1%. These results were obtained with a significant difference at the 5% threshold. The extract combination also showed an alpha-amylase inhibitory percentage of 23.56±4.6% at the concentration of 200 μg/mgE. Daily administration of the combination of extracts significantly lowered the fasting blood glucose, triglycerides, total cholesterol, LDL cholesterol, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, creatinine, and malondialdehyde. However, there was a significant increase in serum proteins and HDL cholesterol. We did not observe an antagonistic effect between our combination and glybenclamide. Conclusion Our formulation, therefore, presents antioxidant and antidiabetic activity and could be used for the management of diabetic patients.
Some magnetic properties of Athabasca Oil Sand samples, Alberta, Canada

A number of induced and remanent magnetic measurements have been performed on 55 cubic samples, each 8 cm3, from a single segment of Athabasca Oil Sand core. Samples are representative of four major lithofacies types, which have been classified in the following manner: facies A—laminated, bitumen-free sediments; facies B—bioturbated (laminae are biologically disrupted to some degree), bitumen-free sediments; facies C—bioturbated sediments with moderate bitumen content; and facies D—massive sand, bitumen-rich sediments. Samples of facies D are divided into subfacies D1 and D2, based upon extremely high percentage values of anisotropy of magnetic susceptibility (AMS) observed for D2 samples. Magnetic fabric ranges progressively from undisturbed in samples of facies A to anomalous, considered highly disturbed, for samples of facies D2. Only samples of facies D record a stable remanent magnetization and, since the magnetic fabric is anomalous, it is inferred that the remanent magnetism may also be anomalous.
Redox flow battery technology development from the perspective of patent applications: A review

With the continuous increase in global energy consumption, the development and utilization of renewable energy become imperative. However, the intermittency and fluctuation of wind and solar power generation prevent direct grid integration, resulting in energy waste. As a large-scale electrochemical energy storage technology, redox flow batteries (RFBs) can effectively store renewable energy and smooth the power output. This paper summarizes the development history of RFBs technology in China by analyzing relevant patent application data, elaborates on the working principles, advantages and disadvantages of various RFBs, and their latest research progress. It analyzes the technical challenges in current RFBs research and presents the application prospects of RFBs commercialization. The results show that although RFBs technology has made significant progress in China, it still faces issues like high battery cost and limited cycle life. To realize the efficient utilization of renewable energy and green low-carbon development, RFBs technology needs continuous optimization and upgrade. This paper can provide references for the development of RFBs technology.
Organizational Culture Orientation and Union Influence

Employee unions are indispensable components of organizational success. The role of the employee union, which could be a consequence of organizational culture, determines the degree of an organization’s success. This study aims to explore the employee unions’ influence on the different cultural orientations of the organization. The study is based on survey data from 23 sample organizations’ 479 respondents. This study employed a mixed approach: a qualitative approach for understanding the fundamentals of employee unions and their influence in the Nepalese context and a quantitative approach for estimating unions’ influence. OCAI to determine the cultural orientation of sample organizations. A survey questionnaire was distributed to the employees, management leaders, and union leaders as respondents to estimate the influence of employee unions. Word clouds, OCAI charts, and descriptive statistics were used to conclude the study. Findings revealed unions’ influence on organizations in different functions like recruitment and selection, training and development, compensation, and the working environment. Union influence is found to be more active and influential in hierarchy culture than in market culture. This study contributes to the Power Resource Approach and Social Exchange Theory. It encourages the organizations’ leaders to orient their culture toward market culture to foster a fair, transparent, and competitive work environment and lessen the adverse influence of employee unions.