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Thin-walled parts exhibit high flexibility, rendering them susceptible to chatter during milling, which can significantly impact machining accuracy, surface quality, and productivity. Therefore, chatter detection plays a crucial role in thin-wall milling. In this study, a chatter detection method based on multi-sensor fusion and a dual-stream convolutional neural network (CNN) is proposed, which can effectively identify the machining status in thin-wall milling. Specifically, the acceleration signals and cutting force signals are first collected during the milling process and transformed into the frequency domain using fast Fourier transform (FFT). Secondly, a dual-stream CNN is designed to extract the hidden features from the spectrum of multi-sensor signals, thereby avoiding confusion when learning the features of each sensor signal. Then, considering that the characteristics of each sensor are of different importance for chatter detection, a joint attention mechanism based on residual connection is designed, and the feature weight coefficients are adaptively assigned to obtain the joint features. Finally, the joint features feed into a machining status classifier to identify chatter occurrences. To validate the feasibility and effectiveness of the proposed method, a series of milling tests are conducted. The results demonstrate that the proposed method can accurately distinguish between stable and chatter under various milling scenarios, achieving a detection accuracy of up to 98.68%. [ABSTRACT FROM AUTHOR]

High altitude pulmonary edema (HAPE) is a form of life-threatening high altitude idiopathy.This non-cardiogenic pulmonary edema is a serious illness with high risk of morbidity. The mechanisms of HAPEmostly proposed so far in literature include exaggerated hypoxic pulmonary vasoconstriction (HPV) and excessively increased capillary pressure, pulmonary capillary leak, disturbed alveolar fluid clearance, and liquid retention and body fluid imbalance. In this review, we described the advances in HAPE mechanisms and in the clinicaltranslation of therapeutics targeting the central links of HAPE pathophysiology. We also provided views on the fu‐ture prospects for the pharmacological management of HAPE, which should inspire high altitude medical research‐ers to find new measures to prevent and treat HAPE.

Objective To observe hypoxic injuries in 7 cell lines derived from different human tissues to identify a cell model that is sensitive to acute hypoxic injury. Methods Seven cell lines derived from different human tissues, namely CCD 841 CoN, GES-1, HUVEC, HEB, HEK-293, HBE and L02, were exposed to different oxygen concentrations (1% and 5%) for 24 h using a hypoxia workstation. CCK-8 and LDH kits were used to assess the cell proliferation and cell injuries. The cells were then treated with rhodiola (0.625 μmol/L, 2.5 mmol/L) and 3-n-butylphthalide (1, 2 μmol/L) at the start of hypoxic exposure to assess the protective effects of the drugs against hypoxic cell injuries. Results Compared with the cells cultured in normal oxygen concentration (21%), HEB cells exposed to 1% O2 for 24 h showed significantly lowered proliferative activity (P < 0.05). Hypoxic exposure to 5% or 1% O2 for 24 h significantly increased LDH activity in the culture supernatant of HEB, HUVEC, HBE, HEK-293, CCD 841 CoN, GES-1 and L02 cells (P < 0.05 or 0.01). In HEB cells cultured under hypoxic conditions, treatment with rhodiola and 3-n-butylphthalide significantly promoted the cell proliferation and improved the cell viability (P < 0.05), and obviously reversed hypoxia-induced increase in LDH activity (P < 0.05 or P < 0.01). Conclusion Among the 7 cell lines tested in this study, HEB cells are the most sensitive to hypoxia and can serve as an ideal model for studying drug interventions of hypoxic cell injuries.