Inflammation of the lungs, called pneumonia, is a disease characterized by inflammation of the air sacs that interfere with the exchange of oxygen and carbon dioxide. It is caused by a variety of infectious organisms, including viruses, bacteria, fungus, and parasites. Pneumonia is more common in people who have pre-existing lung diseases or compromised immune systems, and it primarily affects small children and the elderly. Diagnosis of pneumonia can be difficult, especially when relying on medical imaging, because symptoms may not be immediately apparent. Convolutional neural networks (CNNs) have recently shown potential in medical imaging applications. A CNN-based deep learning model is being built as part of ongoing research to aid in the detection of pneumonia using chest X-ray images. The dataset used for training and evaluation includes images of people with normal lung conditions as well as photos of people with pneumonia. Various preprocessing procedures, such as data augmentation, normalization, and scaling, were used to improve the accuracy of pneumonia diagnosis and extract significant features. In this study, a framework for deep learning with four pre-trained CNN models—InceptionNet, ResNet, VGG16, and DenseNet—was used. To take use of its key advantages, transfer learning utilizing DenseNet was used. During training, the loss function was minimized using the Adam optimizer. The suggested approach seeks to improve early diagnosis and enable fast intervention for pneumonia cases by leveraging the advantages of several CNN models. The outcomes show that CNN-based deep learning models may successfully diagnose pneumonia in chest X-ray pictures.

Intra-regional trade serves as a key growth engine for East Asian economies. Accompanying the rapid growth of bilateral and intra-regional trade ties, the East Asian economies are becoming increasingly connected and interdependent. Infrastructure connectivity plays a crucial role in bridging different areas of the East Asian region and enabling them to reap the full socioeconomic benefits of economic cooperation and integration. Nevertheless, further improvement of infrastructure in the region faces major challenges due to the lack of effective mechanisms for coordination and dialogue on regional integration through funding infrastructure projects, as well as the serious trust deficit among member states that has arisen from the on-going territorial and historical disputes.

With the rapid development of digital technology, the digital infrastructure enables the rapid formation, modification and refactoring of digital products through continuous experimentation and implementation, reduces the cost of innovation, and facilitates the implementation of digital innovation. To solve the problem that the technical scope of digital innovation is relatively concentrated and the knowledge flow between the achievements of digital innovation is insufficient, this study investigates the impact of digital infrastructure on organizational digital innovation in China. The cross-sectional study was conducted from November 2023 to March 2024 among 384 employees and managers in the core industries of the digital economy, as well as enterprises in traditional industries in China. Data were collected using closed-ended questionnaires adapted from previous literature. Structural equation modelling (SEM) was employed to analyze the data using SPSS 28 and AMOS 28. The results reveal that both the information infrastructure and the innovation infrastructure have a positive and direct effect on organizational digital innovation in China, as well as an indirect effect through data flows. Converged infrastructure has only an indirect impact on organizational digital innovation through the flow of data.

Pakistan is grappling with significant economic and political challenges stemming from various factors. Positioned at the heart of the Chinese Belt and Road Initiative, Pakistan has been presented with a diverse array of opportunities encompassing trade, investment, energy resource development, Special Economic Zones (SEZs), the expansion of the Gwadar port, integration of its economy with neighboring nations via various connectivity projects, and the generation of employment prospects. Given the contemporary interdependence of economic performance and political stability, the potential for economic stability and the creation of opportunities through the China-Pakistan Economic Corridor (CPEC) is seen as crucial. The project helped Pakistan to attract a huge amount of Foreign Direct Investment (FDI), created hundreds of thousands of jobs, significantly improved infrastructure, established nine SEZs, developed Gwadar port, increased its trade volume with China and controlled energy crisis to a significant level. Political development, stability and peace have also been positively influenced by economic development. This study aims to evaluate the impact of CPEC from both economic and political perspectives, especially as it approaches its 10th anniversary, and assess how it has shaped Pakistan’s economic and political landscapes. The forthcoming second phase of CPEC is poised to further bolster Pakistan’s economic growth, fortify industrialization through SEZs, and enhance its international trade. Additionally, the project is set to transform Pakistan into a pivotal regional trade corridor through its advanced connectivity initiatives and the development of the Gwadar port.

This study critically examines the implications of international transport corridor projects for Central Asian countries, focusing on the Western-backed Transport Corridor Europe-Caucasus-Asia (TRACECA), the Chinese initiative “One Belt—One Road”, and the International North-South Transport Corridor (INSTC) supported by the Russian Federation, India, and Iran. The analysis underscores the risks associated with Western projects, highlighting a need for a more explicit commitment to substantial infrastructure investments and persistent contradictions among key investors and beneficiaries. While the Chinese initiative presents significant benefits such as transit participation, infrastructure development, and economic investments, it also carries risks, notably an increased debt burden and potential monopolization by Chinese corporations. The study emphasizes that Central Asian countries, though indirect beneficiaries of INSTC, may not be directly involved due to geographical constraints. Study findings advocate for Central Asian nations to balance foreign investments, promote economic integration, and safeguard political and economic sovereignty. The study underscores the region’s wealth of natural and human resources, emphasizing the potential for increased demand for goods and services with improved living standards, strategically positioning these countries in the evolving global economic landscape.

STEAM (science, technology, engineering, arts, and mathematics) education has recently been encouraged and attracted much national attention. This qualitative study aimed to conduct a thematic analysis of college student STEAM open responses to provide an examination of college students’ perceptions of their STEAM experiences into the STEAM field. Based on transformative learning theory, a thematic analysis of 756 written responses to seven prompts by 108 college student participants revealed three primary themes: (1) exciting and challenging difficulties, and transdisciplinary learning in STEAM; (2) STEAM learning of gradual process, problem-oriented instruction, and creative problem solving; and (3) metacognition development in STEAM. The findings revealed that undergraduates’ STEAM perceptions provide strong support for STEAM implementation to enhance teaching effectiveness in higher education.