Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.
Ischemic stroke is the second leading cause of mortality and morbidity worldwide. Due to the urgency of implementing immediate therapy, acute stroke necessitates prompt diagnosis. The current gold standards for vascular imaging in stroke include computed tomography angiography (CTA), digital subtraction angiography (DSA) and magnetic resonance angiography (MRA). However, the contrast agents used in these methods can be costly and pose risks for patients with renal impairment or allergies. The aim of this paper is to provide a comprehensive overview of current MRI techniques and sequences for evaluating ischemic stroke, emphasizing the importance of non-contrast options and their clinical implications for radiologists in the diagnosis and management of ischemic stroke. Standard MRI sequences-such as T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), fluid-attenuated inversion recovery (FLAIR), diffusion-weighted imaging (DWI), DWI-FLAIR mismatch, and apparent diffusion coefficient (ADC)-are essential for determining infarct location, volume, and age. Additionally, incorporating susceptibility-weighted imaging (SWI) sequence aids in identifying signs of hemorrhagic transformation within the infarcted region. Advanced techniques like arterial spin labeling (ASL) can serve as a non-contrast alternative for mapping cerebral blood flow (CBF) and allowing for comparison between infarcted and healthy brain areas. Adding ASL to the routine sequence allows ASL-DWI mismatch analysis that is useful for quantifying salvageable tissue volume and facilitate timely recanalization, while time-of-flight (TOF) MRA and magnetic resonance venography (MRV) help assess venous thrombosis, stenosis, or arterial occlusions. Finally, MR spectroscopy can provide insights into critical brain metabolites, including N-acetylaspartate (NAA), and lactate (Lac) to determine patient prognosis. Current MRI technology provides a myriad of sequence options for the comprehensive evaluation of ischemic stroke without the need for contrast material. A thorough understanding of the advantages and limitations of each sequence is crucial for its optimal implementation in diagnosis and treatment.