The study of the refractive index of traditional lenses is one of the foundational topics in the field of optics. The refractive index of a lens determines its ability to refract and focus light, making it a key parameter in optical design and applications. For the measurement of the refractive index of blind samples of finished lenses, this paper proposes a measurement method based on the use of a focal length measuring instrument and an aspheric profilometer to measure the surface shape data of the front and back surfaces of the lens. This method combines curve fitting algorithms and curvature radius fitting algorithms, ultimately reconstructing the lens model using Zemax and back-calculating the refractive index of the lens. For the samples employed in this paper, the measurement accuracy of the focal length can achieve 1.06%, the fitting accuracy of the curvature radius can reach 0.138%, and the recovery accuracy of the refractive index can attain 6.303 × 10⁻⁴%.

A four-stage condensers in series system was adopted to solve the problems of insufficient condensation of high-temperature pyrolysis steam and difficulty in the classification and recovery of pyrolysis oil, where the internal fluids conducted countercurrent convection heat exchange. A steady-state physical and mathematical model of a single condenser was established to clarify the discipline of heat transfer between the internal fluids. Meanwhile, the model of pyrolysis steam coupled multi-stage condensers was proposed with the help of the model compound firstly. A numerical simulation was carried out and the results showed that when the number of condensers in series was four, the heat transfer process of the system reached saturation, and the heat exchange of the cold and hot fluids was completely realized, and it was of little significance to continue to connect more condensers in series for the condensation of pyrolysis steam. To quickly condense the hot fluid, the key was to increase the mass flow rate of the cold fluid in the first-stage condenser. Compared with the experimental values, the calculated values of hot fluid outlet temperature were not higher than 10%, indicating that the model was highly reliable.

In this study, we analyzed the spatiotemporal distribution of annealing temperature using a dual-beam dynamic scanning annealing technique based on a CO₂ laser (10.6 μm) and a 785 nm laser, and the effects of laser energy density, scanning speed, and preheating temperature on the resulting temperature. We systematically examined the influence of key process parameters, including laser energy density, scanning speed, and preheating temperature, on the annealing temperature. Our aim was to optimize annealing conditions to enhance the electrical properties of the materials, as indicated by reduced sheet resistance, controlled diffusion depth of doped ions, and higher activation rates. This approach ensured high activation rates of doped ions while limiting dopant re-diffusion to merely 3.6 nm in the depth direction, as confirmed by concentration profile analysis. Furthermore, based on temperature distribution, deformation of the wafer surface was analyzed. The results indicate that under the employed process parameters, no significant adverse effects on wafer flatness or structural integrity were observed.

A special dual-tube reactor-dual fluidized bed reactor (DFBR), including an external heat exchanger (EHE) and a bypass, was designed to solve the problems that the waste heat of the hot fluid cannot be fully utilized and the reaction temperature cannot be accurately adjusted. Two connection schemes of DFBR and EHE with their thermodynamic equilibrium models and algorithms were proposed, and the optimal scheme was obtained by comparing the outlet temperature and thermal load. The results of the thermodynamic and operating characteristics of the optimal scheme showed that the hot fluid and the cold fluid had positive and negative effects on the heat transfer process, respectively. Increasing the cold fluid mass flow rate in the main stream can enhance the thermal load of the system and increasing the cold fluid mass flow rate in the bypass helped to increase the thermal load of DFBR, even exceeding that of EHE. Adding a bypass can adjust temperature precisely and increasing the inlet temperature can more effectively increase the adjustment range of the reaction zone temperature. The experimental results showed that introducing a bypass can significantly reduce the calculation deviation (12.8%), which decreased with the increasing temperature.

With the rapid development of low-altitude UAVs, accurate wind detection is crucial for ensuring flight safety and enabling broader applications. To address this need, this paper introduces a highly integrated CDWL system specifically designed for compact UAV platforms. The system incorporates a self-compensating Harris Hawks Optimization (SC-HHO) retrieval algorithm, which is tailored to the high-dynamic flight environment and stringent payload constraints of UAVs. This algorithm enables real-time wind retrieval with low dependence on external reference data while effectively compensating for platform motion. The performance of the proposed system was validated through the comparative experiment and the UAV-borne experiment. In the comparative experiment, the CDWL showed correlation coefficients above 0.976 in horizontal wind speed and 0.987 in horizontal wind direction relative to a benchmark airborne CDWL system, with corresponding root-mean-square errors better than 0.395 m/s and 4.135°, respectively. During the UAV-borne experiment, the CDWL retrieved platform velocity using the self-compensating mechanism, achieving a standard deviation of 0.080 m/s relative to global navigation satellite system (GNSS) measurements, and successfully acquired wind field information. These results confirm that the developed system provides a viable and practical technical solution for UAV-based remote wind sensing.

In the field of edge computing, quantizing convolutional neural networks (CNNs) using extremely low bit widths can significantly alleviate the associated storage and computational burdens in embedded hardware, thereby improving computational efficiency. However, such quantization also presents a challenge related to substantial decreases in detection accuracy. This paper proposes an innovative method, called Adaptive Global Power-of-Two Ternary Quantization Based on Unfixed Boundary Thresholds (APTQ). APTQ achieves adaptive quantization by quantizing each filter into two binary subfilters represented as power-of-two values, thereby addressing the accuracy degradation caused by a lack of expression ability of low-bit-width weight values and the contradiction between fixed quantization boundaries and the uneven actual weight distribution. It effectively reduces the accuracy loss while at the same time presenting strong hardware-friendly characteristics because of the power-of-two quantization. This paper extends the APTQ algorithm to propose the APQ quantization algorithm, which can adapt to arbitrary quantization bit widths. Furthermore, this paper designs dedicated edge deployment convolutional computation modules for the obtained quantized models. Through quantization comparison experiments with multiple commonly used CNN models utilized on the CIFAR10, CIFAR100, and Mini-ImageNet data sets, it is verified that the APTQ and APQ algorithms possess better accuracy performance than most state-of-the-art quantization algorithms and can achieve results with very low accuracy loss in certain CNNs (e.g., the accuracy loss of the APTQ ternary ResNet-56 model on CIFAR10 is 0.13%). The dedicated convolutional computation modules enable the corresponding quantized models to occupy fewer on-chip hardware resources in edge chips, thereby effectively improving computational efficiency. This adaptive CNN quantization method, combined with the power-of-two quantization results, strikes a balance between the quantization accuracy performance and deployment efficiency in embedded hardware. As such, valuable insights for the industrial edge computing domain can be gained.