Based on the fact that the converter mouth flame is the comprehensive external appearance of the physical and chemical reactions in the converter during the steelmaking process, the continuous spectrum information of the converter mouth flame was obtained by USB4000 spectrometer. In the framework of the Internet of Things (IoT), a bidirectional recursive multi-scale convolution depth neural network algorithm, which can take into account the characteristics of frequency domain structure and time domain dynamic sequence. It is applied to the deep-learning of the converter mouth flame spectrum information. The dynamic prediction model of carbon content and temperature value in molten steel at the later stage of steelmaking is constructed. The static control system and dynamic prediction model of automatic steelmaking are intelligently fused to realize one-key steelmaking control. The results show that the average hit rate of carbon content, temperature and carbon temperature at the end of steelmaking is 94.78%, 98.41% and 93.43%, which makes the end-point control of steelmaking more stable and the blowing rate less than 1%.

Remote ischemic conditioning (RIC) is an endogenous strategy that mitigates cerebral injury in preclinical stroke models. However, its bench-to-bedside translation is frequently hindered by complex patient environments that induce RIC resistance and limit its neuroprotective efficacy. To bridge this translational gap, this review systematically examines the extrinsic pathophysiological and pharmacological barriers to RIC. We categorize RIC resistance into three mechanism-driven phenotypes. Impaired signal initiation (Type I) is often linked to diabetic sensorimotor polyneuropathy and the reactive oxygen species-scavenging effects of propofol. Signal transmission blockade (Type II) is associated with specific P2Y12 inhibitors and smoking-induced endothelial dysfunction. Furthermore, effector desensitization (Type III) involves target-organ unresponsiveness exacerbated by aging, chronic hyperglycemia, and postmenopausal estrogen depletion. To address these barriers, potential phenotype-specific optimization strategies are discussed. Ultimately, transitioning from generalized empirical protocols to mechanism-based precision strategies may help bypass RIC resistance in clinical settings and enhance stroke cerebroprotection.