In this paper, the research progress of stimulus-responsive application systems based on shape memory polymers (SMPs) is systematically reviewed. SMPs have shown great potential in the field of drug-controlled release due to their excellent biocompatibility, degradability and shape memory ability. With the continuous advancement of biomedical engineering and intelligent material science, SMP-based drug delivery systems have emerged as a promising strategy to achieve precise spatial and temporal control of drug release. These systems can respond to specific physiological or external stimuli, thereby improving therapeutic efficacy while minimizing side effects. This paper focuses on the design of SMP system under various stimuli-responsive mechanisms such as thermal response, enzyme response, magnetic response, light response and acoustic response, including multi-responsive fibers, electrospun membranes, balloons and other structural forms, and systematically evaluates its performance from the aspects of biocompatibility, drug release kinetics, on-demand release ability and physical properties. In addition, this paper also discusses the advantages and challenges of various response mechanisms, and puts forward prospects for the construction of multi-mode collaborative response systems, the promotion of animal and clinical experiments, and large-scale production in the future.

The development of Radio communication technology is an important milestone, and the TRF receiver, as a critical innovation in early wireless communication, is of great significance in promoting the development of this field. Although the TRF receiver is rarely used in modern wireless systems, understanding its principle, composition, advantages, and disadvantages helps understand wireless communication technology's evolution. Systematical analysis describes the TRF receiver's core principle, including signal acquisition, selection, RF amplification, information recovery, and audio amplification. The main components of the TRF receiver, such as the antenna, bandpass filter, RF amplifier, and detector, are described in detail. Then, the advantages and disadvantages of TRF receivers are compared with heterodyne receivers, and the problems of TRF receivers are pointed out, such as low sensitivity, poor selectivity, and only suitable for AM modulation. The results highlight the TRF receiver's advantages of simplicity, good noise performance, frequency stability, and low power, suggesting performance optimization through feedback and sampling window adjustment. It discusses the TRF receiver's prospects in wireless sensor networks, satellite communications, and specific applications. Finally, it concludes that the TRF receiver is a wireless communication milestone, laying the foundation despite limitations, with potential for further development through continuous innovation.

Remote sensing technology has become a core method in modern disaster emergency management because of its wide coverage, rapid response capability, and objective observation advantages. This paper systematically reviews the key role of remote sensing throughout the monitoring–assessment–decision support chain in disaster emergency response. In disaster monitoring, remote sensing has gradually shifted from single post-disaster observation to integrated space-air-ground collaborative observation, supporting multi-disaster, dynamic, and continuous early warning. In disaster assessment, artificial intelligence and image interpretation algorithms have promoted the transformation from traditional manual visual interpretation to automated and quantitative intelligent assessment, improving the efficiency and accuracy of disaster loss evaluation. In decision support, remote sensing products have evolved from basic situation maps into intelligent decision-making tools embedded in emergency command systems, providing spatial evidence for rescue deployment, risk zoning, and resource allocation. This paper further compares the characteristics, advantages, and limitations of optical, Synthetic Aperture Radar, and thermal infrared remote sensing. Finally, it discusses current challenges in multi-source data collaboration, model generalisation, real-time processing, and operational integration, and proposes future directions for more intelligent disaster emergency applications.