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Abstract High‐precision relative position and attitude measurement technology has a wide range of applications in aerospace and industrial production. Currently, the commonly used method for measurement is based on visual cooperative signs. However, its accuracy significantly decreases as the distance increases. Therefore, a relative positioning system is designed based on light field spatial coding and visual recognition. The projector emits spatially encoded structured light within the coverage of the light field, while the receiving end captures, identifies, measures the code, and calculates its pose in the light field coordinate system. Compared with the traditional measurement method, the measurement accuracy of this system does not decrease greatly with the increase in distance, the measurement distance can be adjusted in real‐time and does not depend on an external light source. By changing the projection pattern with different resolutions without changing hardware systems, it can adjust effective measurement distance accordingly. Theoretical and experimental results show that the proposed method can maintain measurement accuracy with the increase in distance.

Abstract Lymphocyte decline, particularly the depletion of NK cells, is a prominent feature of immunosuppression following severe tissue injury, heightening the susceptibility of severe trauma patients to life-threatening infections. Previous research indicates that the reduction in the number of NK cells is closely associated with the process of cell death. Nonetheless, the precise mechanism of NK cell death remains unknown. Here, we discovered that following severe traumatic injury, NK cells undergo several cell death pathways, dominated by apoptosis and pyroptosis with coexistence of necrotic cell death, immunogenic cell death, ferroptosis, and autophagy. These NK cells with different paradigms of death have diverse cytokine expression profiles and diverse interactions with other immune cells. Further exploration revealed that hypoxia was strongly associated with this diverse paradigm of NK cell death. Detailed investigation of paradigms of cell death may help to enhance comprehension of lymphopenia post-severe trauma, to develop new strategy in preventing immunosuppression, and then to improve outcome for severe trauma population.

Objective To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation （MPR）, and to explore the applicability of cranial suture closure rule in age estimation of northern Chinese Han population. Methods The head CT samples of 132 northern Chinese Han adults aged 29-80 years were retrospectively collected. Volume reconstruction （VR） and MPR were performed on the skull, and 160 cranial suture tomography images were generated for each sample. Then the MPR images of cranial sutures were scored according to the closure grading criteria, and the mean closure grades of sagittal suture, coronal sutures （both left and right） and lambdoid sutures （both left and right） were calculated respectively. Finally taking the above grades as independent variables, the linear regression model and four machine learning models for age estimation （gradient boosting regression, support vector regression, decision tree regression and Bayesian ridge regression） were established for northern Chinese Han adults age estimation. The accuracy of each model was evaluated. Results Each cranial suture closure grade was positively correlated with age and the correlation of sagittal suture was the highest. All four machine learning models had higher age estimation accuracy than linear regression model. The support vector regression model had the highest accuracy among the machine learning models with a mean absolute error of 9.542 years. Conclusion The combination of skull CT-MPR and machine learning model can be used for age estimation in northern Chinese Han adults, but it is still necessary to combine with other adult age estimation indicators in forensic practice.

The continuous increase in communication capacity is accompanied by an increase in transmission frequency, which creates new demands on the transmission efficiency in modern. Signal relay transmission can increase the transmission distance, however, conventional repeaters relay the signal in a specified direction, which is difficult to accommodate communication when a receiving device suddenly appears around the repeater. In this work, we propose a new signal transmission repeater, which is implemented by an adaptively reconfigurable multi-beam reflective metasurface based on multispectral detection. The reconfigurable metasurface with varactor diodes is designed and the mapping of phase profiles to voltages is established by polynomial fitting method. Visual, laser, infrared and ultrasonic detectors are used to detect targets in different scenarios. Thus, the detection information is fed back to the reconfigurable metasurface for adaptively multi-beam switching. As verification, the adaptive metasurface repeater was fabricated and measured to verify our design. All the results exhibit consistency with theoretical design. Importantly, this work paves a new way to intelligent metasurfaces and may find applications in intelligent communications, smart home, etc.