The problem of the current study is to study the moderating role of Blockchain technology on the impact of the use of financial technology (FinTech) on the competitive advantage of Jordanian banks. Quantitative analysis is appropriate. The study population consists of (600) employees in three banks at Jordan (Arab Bank, Islamic Bank, Ahli Bank) with its branches in various governorates. A questionnaire was developed to collect study data and distributed electronically. The number of participants was (240) respondents. The study confirms that there is an impact of the mediating role of Blockchain technology in the impact of the use of financial technology (FinTech) on competitive advantage. The study recommends increasing spending on financial technology applications to improve banking services provided to customers, especially through electronic applications and technologies. The study also recommends rebuilding current banking systems using Blockchain technology, which will remove the central database structure and replace it with a decentralized data environment via the blockchain, thus reducing the risk of database hacking. Since transactions via blockchain technology are verified by every node of the chain, it will make transactions more secure which will make the world’s banking systems faster and more secure.

The impact of crude oil price fluctuations on the real effective exchange rate (REER) has been widely debated, but specific evidence, particularly for developing countries in Southeast Asia, is scarce and inconclusive. This issue, especially concerning both short- and long-term relationships, remains inadequately addressed, affecting these countries for risk management related to oil price fluctuations. This study aims to fill this gap by examining these relationships in Thailand context to provide more evidence on how the REER in Southeast Asia responds to changes in crude oil prices. Monthly data of crude oil prices in Dubai market and the Thai baht REER from 2000 to 2019 were employed. Johansen co-integration test and Vector Error Correction Model (VECM) were used for analyzing long-term and short-term relationships, respectively. The results indicate a significant negative long-term relationship between crude oil prices and the REER, with a 0.31% reduction in the REER for every 1% increase in the real price of oil. However, in the short term, VECM analysis reveals significant movements in the REER in response to external shocks. On average from 2000–2019, the significant fluctuations in the REER are quickly alleviated and adjusted to its long-run equilibrium, typically by 2% in the following month following external shocks such as crude oil price fluctuations. Given these findings, which highlight the long-term relationship between the REER and crude oil prices and its short-term adjustment, it is suggested that when there is a shock from the crude oil prices, the government can strengthen short-term oil price controls or monetary subsidies to mitigate the extensive repercussions of energy market fluctuations, as such interventions would have a lesser impact on the long-term equilibrium of the REER.

The purpose of this study was to investigate the published literature on human resource management and school performance from January 2012 to December 2022. Numerous literature evaluations have been conducted on human resource management and organizational performance, but school or teacher performance has received less attention than organizational performance. The PICOC (population, intervention, comparison, outcome, and context) technique is integrated into each stage of the PSALSAR framework to assure the study’s objective and comparability. This in-depth research is conducted in three stages: identifying pertinent keywords, screening pertinent papers, and selecting pertinent publications for review utilizing the PRISMA (Preferred Reporting Items for Systematic Reviews and Mata Analysis) technique. This made a final database with 44 publications that met the study’s requirements for inclusion. This study reveals that HRM practices and school performance are correlated. The results of the research identify the eight most essential HRM practices for improving school performance, which included planning, organizing, recruitment and selection, training and development, performance management, employee relations and involvement, reward and compensation, health, safety, and work-life balance. Leadership style, motivation, satisfaction, productivity and task performance, competency, culture and climate, empowerment, and commitment were among the performance-influencing elements.

The suspicion of mediastinal alterations, always includes in its initial study, the chest radiography. The identification of mediastinal alterations in the X-ray is a priority. The knowledge of the mediastinal references and the identification of their alterations allows the suspicion of a pathology specific to each of the mediastinal spaces. When the semiology of mediastinal lesions, their location and the three most frequent pathologies are taken into account, the possibility of having an etiological diagnosis increases^[1]. This is a review article based on a detailed literature search, in which radiological mediastinal references are studied, with emphasis on the epidemiological data of each one of them.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.