Age estimation from median palatine suture using computed tomography reconstructed 3D images: a comparison of Northern and Southwestern Chinese populations.

To investigate the potential of computed tomography (CT) images of median palatine suture (MP) for adult age estimation in the Northern and Southwestern Chinese populations. A total of 1110 cranial CT scans from individuals aged 10-79 years, including 557 northern Chinese and 553 southwestern Chinese, were collected for analysis. After volume reformation and multiplanar reconstruction, a total of 20 slices of median palatine suture were selected from each individual.

SignalFormer: Hybrid Transformer for Automatic Drone Identification Based on Drone RF Signals.

With the growing integration of drones into various civilian applications, the demand for effective automatic drone identification (ADI) technology has become essential to monitor malicious drone flights and mitigate potential threats. While numerous convolutional neural network (CNN)-based methods have been proposed for ADI tasks, the inherent local connectivity of the convolution operator in CNN models severely constrains RF signal identification performance. In this paper, we propose an innovative hybrid transformer model featuring a CNN-based tokenization method that is capable of generating T-F tokens enriched with significant local context information, and complemented by an efficient gated self-attention mechanism to capture global time/frequency correlations among these T-F tokens.

Efficient Localization Method Based on RSSI for AP Clusters.

The localization accuracy is susceptible to the received signal strength indication (RSSI) fluctuations for RSSI-based wireless localization methods. Moreover, the maximum likelihood estimation (MLE) of the target location is nonconvex, and locating target presents a significant computational complexity. In this paper, an RSSI-based access point cluster localization (APCL) method is proposed for locating a moving target.

Delay robustness-constrained control of integrating processes with optimal tracking and quantified disturbance rejection.

Regarding a general class of integrating processes subject to uncertain delays, this paper investigates a two-degree-of-freedom (2-Dof) control scheme with a proportional-derivative (PD) controller and disturbance observer (DOB). Relative delay margin is introduced as a paramount metric to evaluate the delay robustness, with which a set of novel and explicit tuning formulae for PD controller is analytically derived under the single external loop. In this individual frame, the stability boundaries associated with the governing parameters are first studied, indicating the nominal stability conditions for the 2-Dof control system.

Data-driven iterative tuning based active disturbance rejection control for FOPTD model.

Active Disturbance Rejection Control (ADRC) emerges as a promising control method that can effectively handle uncertainties and disturbances. However, many model-based ADRC tuning methods turn laborious to achieve satisfactory control performance, when the critical process parameters are difficult to accurately obtain, especially the time delay information. To this end, this paper aims to propose a data-driven iterative tuning method for time-delayed ADRC (TD-ADRC).

Aberrant DNA methylation in radon and/or cigarette smoke-induced malignant transformation in BEAS-2B human lung cell line.

It is well known that cigarette smoking (CS) and/or radon (Rn) induce malignant transformation in lung cells. To investigate the mechanisms underlying lung carcinogenesis induced by CS, Rn; or Rn followed by CS using BEAS-2B cell line derived from human bronchial epithelial cells. BEAS-2B cells were exposed to either Rn (20,000 Bq/m) for 30 min or CS (20%) for 10 min or Rn followed by CS for 40 min.