The beam-steering device is a critical component in LiDAR systems for 3D imaging. Solid-state beam-steering devices attract the most attention for their advantages of robustness, fast beam-steering speed, and stability. However, solid-state beam-steering devices, such as optical phased arrays (OPAs), are challenging to realize 2D scanning ability. Here we employed a virtually imaged phased array (VIPA) in the LiDAR system to realize all solid-state two-dimensional (2D) beam-steering based on dispersion only. A frequency swept laser source is used for performing optical frequency-modulated continuous-wave (FMCW) ranging and 2D beam steering simultaneously. The 2D disperser is compact and can be easily implemented owing to its simple structure. The mechanism of continuous scanning and ranging is beneficial for obtaining high lateral resolution, and a lateral resolution of 0.06° is achieved. 3D maps of the object at a distance of 2 m are obtained with cm-level ranging precision. The frame rate of the proposed LiDAR system only depends on the wavelength-tuning speed of the swept laser source, with the potential to realize ultrafast solid-state LiDAR systems.

Objectives18F-fluorodeoxyglucose (FDG) PET/CT has been widely used in tumor diagnosis, staging, and response evaluation. To determine an optimal therapeutic strategy for lung cancer patients, accurate staging is essential. Semi-quantitative standardized uptake value (SUV) is known to be affected by multiple factors and may fail to differentiate between benign and malignant lesions. Lymph nodes (LNs) in the mediastinal and pulmonary hilar regions with high FDG uptake due to granulomatous lesions such as tuberculosis, which has a high prevalence in China, pose a diagnostic challenge. This study aims to evaluate the diagnostic value of the quantitative metabolic parameters derived from dynamic 18F-FDG PET/CT in differentiating metastatic and non-metastatic LNs in lung cancer.MethodsOne hundred and eight patients with pulmonary nodules were enrolled to perform 18F-FDG PET/CT dynamic + static imaging with informed consent. One hundred and thirty-five LNs in 29 lung cancer patients were confirmed by pathology. Static image analysis parameters including LN-SUVmax, LN-SUVmax/primary tumor SUVmax (LN-SUVmax/PT-SUVmax), mediastinal blood pool SUVmax (MBP-SUVmax), LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter. Quantitative parameters including K1, k2, k3 and Ki and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. Ki/K1 was computed subsequently as a separate marker. We further divided the LNs into mediastinal LNs (N=82) and pulmonary hilar LNs (N=53). Wilcoxon rank-sum test or Independent-samples T-test and receiver-operating characteristic (ROC) analysis was performed on each parameter to compare the diagnostic efficacy in differentiating lymph node metastases from inflammatory uptake. P<0.05 were considered statistically significant.ResultsAmong the 135 FDG-avid LNs confirmed by pathology, 49 LNs were non-metastatic, and 86 LNs were metastatic. LN-SUVmax, MBP-SUVmax, LN-SUVmax/MBP-SUVmax, and LN-SUVmax/short diameter couldn’t well differentiate metastatic from non-metastatic LNs (P>0.05). However, LN-SUVmax/PT-SUVmax have good performance in the differential diagnosis of non-metastatic and metastatic LNs (P=0.039). Dynamic metabolic parameters in addition to k3, the parameters including K1, k2, Ki, and Ki/K1, on the other hand, have good performance in the differential diagnosis of metastatic and non-metastatic LNs (P=0.045, P=0.001, P=0.001, P=0.001, respectively). For ROC analysis, the metabolic parameters Ki (AUC of 0.672 [0.579-0.765], sensitivity 0.395, specificity 0.918) and Ki/K1 (AUC of 0.673 [0.580-0.767], sensitivity 0.570, specificity 0.776) have good performance in the differential diagnosis of metastatic from non-metastatic LNs than SUVmax (AUC of 0.596 [0.498-0.696], sensitivity 0.826, specificity 0.388), included the mediastinal region and pulmonary hilar region.ConclusionCompared with SUVmax, quantitative parameters such as K1, k2, Ki and Ki/K1 showed promising results for differentiation of metastatic and non-metastatic LNs with high uptake. The Ki and Ki/K1 had a high differential diagnostic value both in the mediastinal region and pulmonary hilar region.

By using narrow infrared (IR) optical beams, optical wireless communication (OWC) system can realize ultra-high capacity and high-privacy data transmission. However, due to the point-to-point connection approach, a high accuracy localization system and beam-steering antenna (BSA) are required to steer the signal beam to user terminals. In this paper, we proposed an indoor beam-steering IR OWC system with high accuracy and calibration-free localization ability by employing a coaxial frequency modulated continuous wave (FMCW) light detection and ranging (LiDAR) system. In the meantime, benefitting from the mm-level ranging accuracy of the LiDAR system, a useful approach to assess the feasibility of the link alignment between beam-steering antenna and users is first demonstrated. With the assistance of the LiDAR system, we experimentally achieved the localization of user terminals with a 0.038-degree localization accuracy and on-off keying (OOK) downlink error-free transmission of 17 Gb/s in free space at a 3-m distance is demonstrated. The highest transmission data rate under the forward error correction (FEC) criterion (Bit error rate (BER) <3.8×103) can reach 24 Gb/s.

In practical building control, quickly obtaining detailed indoor temperature distribution is necessary for providing satisfying personal comfort and improving building energy efficiency. The aim of this study is to propose a fast prediction method for indoor temperature distribution without knowing the thermal boundary conditions in practical applications. In this method, the index of contribution ratio of indoor climate (CRI), which represents the independent contribution of each heat source to the temperature distribution, has been combined with the air temperature collected by one mobile sensor at the height of the working area. Based on a typical office model, the effectiveness of using mobile sensors was discussed, and the influence of its acquisition height and acquisition distance on the prediction accuracy was analyzed as well. The results showed that the proposed prediction method was effective. When the sensors fixed on the wall were used to predict the indoor temperature distribution, the maximum average relative error was 27.7%, whereas when the mobile sensor was used to replace the fixed sensors, the maximum average relative error was 4.8%. This indicates that using mobile sensors with flexible acquisition location can help promote both reliability and accuracy of temperature prediction. In the human activity area, data from a set of mobile sensors were used to predict the temperature distribution at four heights. The prediction accuracy was 2.1%, 2.1%, 2.3%, and 2.7%, respectively. However, the influence of acquisition distance of mobile sensors on prediction accuracy cannot be ignored. The distance should be large enough to disperse the distribution of the acquisition points. Due to the influence of airflow, some distance between the acquisition points and the room boundaries should be given.

No abstract