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The objective of this study is to examine the role of external factors including MP, CP, and NP on the intention to adopt Cloud Based Accounting Information System (CB-AIS). The study proposes a theoretical framework based on institutional theory (INT). The data were collected from small and medium sized enterprise (SMEs) operating in Jordan. A total of 600 questionnaires were distributed to selected SMEs and only 142 were returned and used for the analysis. The empirical data were analyzed using the PLS-SEM modelling. The findings showed that MP, CP, and NP had significant direct associations with the CB-AIS intention to adopt. The results provide important insights to managers, researchers and policymakers to help them understand the importance of CB-AIS adopting to enhance firm performance.

Key Clinical Message In countries like Sudan, where several infectious diseases are prevalent, health care providers should not be satisfied with initial detection of a single pathogen and whenever it is feasible, they should investigate coinfections. Infections with high mortality or severe morbidity should be prioritized during the differential diagnosis particularly for diseases with similar clinical manifestations to reduce the death and disability rates. However, this requires substantial improvement in the diagnostic capacity. Abstract Here we report a case of dengue and malaria coinfection from the southeast region of Sudan, bordering Ethiopia and Eritrea. A 25‐year‐old male from Sudan presented with symptoms of fever, chills, vomiting, and muscle and joint pain. Laboratory investigations confirmed a coinfection of dengue and malaria, which is assumingly not uncommon in areas heavily syndemic with several diseases but it is severely under‐detected, underreported, and underestimated. The case has fully recovered after the supportive care for dengue and chemotherapy treatment for malaria. In such a case, it was important to monitor the patient's recovery and the treatment outcome through clinical indicators and laboratory parameters to update the treatment course whenever needed, according to response. The increasing burden and outbreaks of vector‐borne diseases including dengue and malaria in Sudan, indicates the need for improving the implementation of the global vector control response that established by the World Health Organization. Additionally, the increasing prevalent of coinfections is urging substantial improvement in the diagnostic capacity in endemic countries.

ABSTRACT Background Previous meta‐analyses have shown mixed results regarding the association between eating disorders (EDs) and type 1 diabetes mellitus (T1DM). Our paper aimed to analyse different EDs and disordered eating behaviours that may be practiced by patients with T1DM. Methods A literature search of PubMed, Scopus and Web of Science was conducted on 17 January 2023, using the key terms “T1DM,” “Eating Disorders” and “Bulimia.” Only observational controlled studies were included. The Revman software (version 5.4) was used for the analysis. Results T1DM was associated with increased risk of ED compared with nondiabetic individuals (RR = 2.47, 95% CI = 1.84–3.32, p‐value

This paper focusses on the nonlinear fractional Kadomtsev–Petviashvili (FKP) equation in space–time, employing the conformable fractional derivative (CFD) approach. The main objective of this paper is to examine the application of the (G’/G)-expansion method in order to find analytical solutions to the FKP equation. The (G’/G)-expansion method is a powerful tool for constructing traveling wave solutions of nonlinear evolution equations. However, its application to the FKP equation remains relatively unexplored. By employing traveling wave transformation, the FKP equation was transformed into an ordinary differential equation (ODE) to acquire exact wave solutions. A range of exact analytical solutions for the FKP equation is obtained. Graphical illustrations are included to elucidate the physical characteristics of the acquired solutions. To demonstrate the impact of the fractional operator on results, the acquired solutions are exhibited for different values of the fractional order α, with a comparison to their corresponding exact solutions when taking the conventional scenario where α equals 1. The results indicate that the (G’/G)-expansion method serves as an efficient method and dependable in solving the nonlinear FKP equation.

Feedback is a well-known advantage for language learning. Primary studies on feedback in computer-assisted language learning (CALL) demonstrates that feedback has a significant effect on student language learning. Previous reviews (e.g., Azevedo & Bernard, 1995; Kang & Han 2015; Li, 2010) provided important insights on language learning. However, these reviews showed that there has never been a meta-analysis synthesizing the effectiveness of feedback in CALL studies and the moderators moderating the effect of feedback in CALL. With the aim of summarizing years of research on feedback in CALL studies and identifying the moderators of feedback in CALL, a meta-analysis was conducted. By establishing rigorous inclusion and exclusion criteria, the investigator located 21 primary studies that met the inclusion and exclusion criteria. The findings indicated under the Random-Effects (RE) model that feedback in CALL has a significant medium effect size on student language learning outcomes (g = 0.56). The results also showed that the effect of feedback is moderated by a host of variables, including learners' mother tongue, intervention provider (i.e., teacher, researcher), target language, and so on. The study concluded that feedback in CALL is a promising field for language learning and provided implications for teachers and future research.

A key challenge in developing Machine Learning (ML) models for predicting or diagnosing Cardiovascular Disease (CVD), is selecting suitable algorithms and fine-tuning their parameters. In this study, we employed three ML techniques, namely Auto-WEKA, Decision Table/Naive Bayes (DTNB), and Multiobjective Evolutionary (MOE) fuzzy classifier to create diagnostic models using the Heart Disease Dataset from IEEE Dataport. Auto-WEKA generated a highly accurate model with a 100% success rate through optimal classifier selection and hyperparameter configuration. The DTNB classifier yielded a satisfactory 85.63% prediction accuracy concerning patients' risk levels. Further refinements, though, could help reduce possible misclassifications. Finally, the MOE fuzzy classifier achieved approximately 81.6% accuracy, indicating the potential for enhancing precision and recall values by adjusting classifier settings. Our findings underscore the promise of ML tools in CVD diagnosis and suggest further optimization of classifier parameters for superior performance.

Myocardial Infarction (MI) is a condition often leading to death. It arises from inadequate blood flow to the heart, therefore, the classification of MI complications contributing to lethal outcomes is essential to save lives. Machine learning algorithms provide solutions to support the categorization of the MI complication attributes and predict lethal results. This paper compares various machine learning algorithms to classify myocardial infarction complications and to predict fatal consequences. The considered algorithms are Multilayer Perceptron (MLP), Naive Bayes (NB), and Decision Tree (DT). The main objective of this paper is to compare these algorithms in two scenarios: initially using the full dataset once and then using the dataset again, after implementing the WEKA attribute selection algorithm. To accomplish this goal, data from the Krasnoyarsk Interdistrict Clinical Hospital were employed. Results in general revealed that the MLP classifier demonstrated optimal performance regarding the full MI data, whereas the DT classifier emerged as more favorable when the dataset sample size was diminished through an attribute selection algorithm.

This article aims to review the application of the concept of Amar Ma'ruf Nahi Munkar Qadi al-Baqilany using Hassan Hanafi's phenomenological hermeneutics as an analytical approach. The socio-political and thought conditions of al-Baqilany's time became a problem in itself. The diversity of society that is not only from the Arab community also raises problems that require special handling. Qadi al-Baqilani had a view of Amar Ma'ruf Nahi Munkar who could respond to the realities of the time. This research uses qualitative methods with the type of literature study. The choice of Hasan Hanafi's phenomenological hermeneutics as an approach aims to deepen the study so as to get a complete picture of the real implementation of Amar Ma'ruf Nahi Munkar Qadi al-Baqilany. The researcher's analysis includes socio-historical conditions, texts, reality and people's consciousness. The main instruments are reduction data, display data and conclusions. The results show that a) the socio-historical, political and thought of society is very diverse. There was a lot of poverty and misthinking by the Mu'tazilites as key holders of the madhhab in government. So that the implementation carried out by Al-Baqilany is to conduct scientific debates to several schools or schools, especially the Mu'tazilites, Jahmiyah and Shia in the place provided by the government. And also by contradicting the Roman king, b) the incorporation of reason and naqli in every argument, c) the use of linguistic elements needed in his works and debates, d) the use of communicative, systematic, simple and understandable language at every level of his works and e) the existence of mass awareness efforts.

ABSTRACTUsed pesticides result in soil pollution, which potentially seep into groundwater, posing risks to human and animal health. The current study examines the use of a new cheap material for removing four commonly used pesticides from polluted groundwater before use for drinking. These pesticides are Malathion, Methomyl, Abamectin, and Thiamethoxam. Activated charcoal obtained from the trunk of “Salix mucronata” trees is introduced for removing these pesticides by surface adsorption. Activation treatment using gold-nitrate solution is introduced to enhance the charcoal adsorption capacity, because removal of pesticides is difficult due to their large-sized molecules and lack of obvious surface electrostatic charges. Physical and chemical properties of the studied pesticides and the activated charcoal were determined. Batch experiments tested the effects of solution pH, contact time, dose of charcoal, and initial concentrations on the charcoal adsorption capacity. Langmuir adsorption linear isotherm test was done to use for the prediction of adsorption behavior. Fixed-bed column experiments tested clean-up of polluted water using charcoal filter under steady flow. Gold-nitrate activated charcoal adsorption capacities were almost three times higher than other charcoals for the same pesticides at the same initial concentrations. Maximum adsorption capacities achieved in the current study were 16.17, 14.59, 9.55, and 8.99 mg/g, respectively, at the initial concentrations of 50.0 mg/l. Meanwhile, treatment times in steady-flow fixed-bed columns were much lower compared to other studies. Preparation cost of gold-nitrate activated charcoal in the current study was lower than other adsorbents. The charcoal introduced in this study is recommended for use in low-cost removal of pesticides from polluted groundwater on the national scale, including small treatment units for rural communities with limited facilities.