Alzheimer's disease (AD) is a severe degenerative neurological disease which leads to progressive cognitive decline and memory impairment. We have affirmed amyloid-β (Aβ) plaques and tau tangles as the primary pathological hallmarks for a long time. However, many therapeutic approaches have found out that both Aβ and tau alone have achieved little success. Increasing evidence indicates that the neuroinflammation, which primarily related with microglia and astrocytes, takes the central role of causing and exacerbating the disease. Microglia and astrocytes not only respond to Aβ and tau but also control their accumulation, propagation, and associated neurotoxicity. They are also influenced by a kind ofrisky gene related to late-onset AD calls ApoE, which can further modulate them by regulating lipid metabolism and glial responses. This review synthesizes current knowledge on the roles of microglia, astrocytes, Aβ, tau, and ApoE in AD, emphasizing their interconnected contributions to pathogenesis and therapeutic opportunities.

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Blood oxygen saturation is a critical physiological parameter for evaluating human cardiopulmonary function and blood oxygen-carrying capacity. Non-invasive pulse oximeters based on the principle of photoplethysmography (PPG) have been widely used in clinical monitoring and home health care due to their simple operation and rapid response. This paper reviews the core technologies of pulse oximeters, focusing on the operating principles of their photoelectric sensor modules, hardware circuit design, key performance indicators, and the challenges they face. The article discusses in detail the differences between transmissive and reflective sensors, as well as the design of key circuits in signal processing such as amplification, filtering, and analog-to-digital conversion. Furthermore, it points out the impact of factors such as motion artifacts, low perfusion, and skin color differences on measurement accuracy. Finally, the future development of oximeters towards intelligence, multi-functionality, and high robustness is prospected. This paper aims to provide a theoretical reference for the design optimization and performance improvement of oximeters.

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Urban Transportation Network Design (TND) is a highly complex system engineering. It has always been regarded as a very difficult problem in urban planning and transportation. This study tries to sort out and summarize the existing research system and development process in this field. From the perspective of mathematical modeling, the multi-objective property, nonlinear characteristics, uncertainty and NP-hard computational complexity of the TND problem are explained one by one, and a series of solution difficulties derived from them also appear. Classical optimization methods, such as linear programming, integer programming, bi-level programming models and so on, have advantages in solving structured problems. But their limitations in large-scale dynamic situations are also pointed out. In comparison, new intelligent and simulation optimization methods, such as heuristic algorithms, data-driven modeling strategies and simulation-optimization coupling frameworks, provide more potential ways to solve complex traffic network design problems. The current mainstream research paradigm can be summarized as the progressive process of "theoretical analysis—optimization solution—simulation verification". Different tools work together in this process to deepen the understanding of the problem and improve the solution efficiency. Network planning with dynamic and multiple uncertainties still faces many unsolved difficulties. Big data technology, artificial intelligence methods and the interdisciplinary integration may become the key driving forces for the future breakthrough in the TND field. This review aims to provide basic theoretical reference and framework support for the follow-up related research.

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Metal meshes are commonly used as reflective elements in far infrared astronomical instruments, where spectrally uniform reflectivity is important for stable Fabry–Perot interferometer performance and reliable calibration. In this work, we quantitatively compare the spectral reflectivity uniformity of representative metal mesh geometries using full wave electromagnetic simulations. Square and circular meshes with inductive and capacitive topologies are analyzed over the 200 to 400 GHz band. A figure of merit based on the normalized root mean square deviation of reflectance from a target value is used to evaluate spectral flatness. Parameter sweeps over lattice pitch and normalized feature size reveal well defined regions that minimize spectral variation. All four geometries can achieve comparable reflectivity uniformity when properly optimized, with square inductive meshes yielding the lowest figure of merit within the explored design space. The results provide practical guidance for selecting metal mesh geometries with flat reflectance profiles in far infrared Fabry–Perot interferometers and related optical systems.

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