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This study presents the optimal process parameters of zirconium nitride (ZrN) thin films prepared by ion-assisted deposition (IAD) technology combined with electron-beam evaporation based on plasma surface treatment and the Taguchi method. We use Minitab statistical software (Version 20.2.0) and L9 orthogonal array parameter design combined with the response surface method (RSM). The quadratic polynomial regression equation was optimized by the RSM. Based on the control factor screening test of the Taguchi method, we determined the most critical factor combination for the process and derived the optimized process parameters of the ZrN thin films. In the coating experiments, we successfully achieved the optimal combination of good refractive index, adequate residual stress, and lower surface roughness on B270 glass substrates. These results indicate that the optimized preparation process can simultaneously achieve several desirable properties, improving the performance and application of ZrN thin films. Furthermore, our research method not only reduces the number of experiments and costs but also improves the efficiency of research and development. By screening key factors and optimizing process parameters, we can find the best process parameter more rapidly, reduce the demand for expenses given materials and equipment costs, and contribute to improving the electron-beam evaporation process. According to the experimental results, it can be observed that under certain conditions, the properties of ZrN thin films reached optimal values. These results are highly useful for optimizing the process parameters of ZrN thin films and provide a basis for further improvement of the thin film properties.

This study aims to investigate the thermomechanical properties of vanadium dioxide (VO2) thin films. A VO2 thin film was simultaneously deposited on B270 and H-K9L glass substrates by electron-beam evaporation with ion-assisted deposition. Based on optical interferometric methods, the thermal–mechanical behavior of and thermal stresses in VO2 films can be determined. An improved Twyman–Green interferometer was used to measure the temperature-dependent residual stress variations of VO2 thin films at different temperatures. This study found that the substrate has a great impact on thermal stress, which is mainly caused by the mismatch in the coefficient of thermal expansion (CTE) of the film and the substrate. By using the dual-substrate method, thermal stresses in VO2 thin films from room temperature to 120 °C can be evaluated. The thermal expansion coefficient is 3.21 × 10−5 °C−1, and the biaxial modulus is 517 GPa.

The undoped and tungsten (W)-doped vanadium dioxide (VO2) thin films were prepared by electron beam evaporation associated with ion-beam-assisted deposition (IAD). The influence of different W-doped contents (3–5%) on the electrical, optical, structural, and thermo-mechanical properties of VO2 thin films was investigated experimentally. Spectral transmittance results showed that with the increase in W-doped contents, the transmittance in the visible light range (400–750 nm) decreases from 60.2% to 53.9%, and the transmittance in the infrared wavelength range (2.5 μm to 5.5 μm) drops from 55.8% to 15.4%. As the W-doped content increases, the residual stress in the VO2 thin film decreases from −0.276 GPa to −0.238 GPa, but the surface roughness increases. For temperature-dependent spectroscopic measurements, heating the VO2 thin films from 30 °C to 100 °C showed the most significant change in transmittance for the 5% W-doped VO2 thin film. When the heating temperature exceeds 55 °C, the optical transmittance drops significantly, and the visible light transmittance drops by about 11%. Finally, X-ray diffraction (XRD) and scanning electron microscope (SEM) were used to evaluate the microstructure characteristics of VO2 thin films.

Owing to increased biosecurity and industrial demands, the poultry houses in Taiwan are generally nonopen and closed types, with automatic environmental control and sensor equipment gradually being installed in such houses. Environmental sensors and poultry health monitoring systems are necessary to improve poultry feeding efficiency and safety. In this work, we developed a goose surface temperature monitoring system based on deep learning using visible image and integrated with infrared thermal image. This system could detect the geese in visible image and obtain the individual goose surface temperature automatically. This system consisted of an embedded system with the trained goose detection model, a visible camera, and an infrared thermal camera. The Mask R-convolutional neural network algorithm was employed to train the goose detection model by the collected goose images. The visible camera captured visible images in the poultry house, in which the geese could be identified by the trained goose detection model. The individual surface temperatures of the geese were obtained through integration of the visible and infrared thermal images. The developed monitoring systems were installed in the land and pool areas of a commercial goose house to monitor the surface temperature of the geese and achieved a precision of 97.1% and recall of 95.1%. In addition, the goose surface temperature of the pool area was observed to be lower than that of the land area. The collected individual goose surface temperature would be used as a management index to poultry house managers.

This paper presents the optimization design of a miniaturized five-element wide-angle fisheye lens using a deep learning algorithm. Zemax optical design software was used to simulate and optimize the wide-angle fisheye lens. A deep learning algorithm helped to find the best combination of different lens materials. We first used six lens elements as an initial configuration to design miniaturized wide-angle fisheye lenses using the optimization process. The optical system components were gradually decreased to five lens elements. Both OKP4HT and polymethyl methacrylate (PMMA) plastic aspheric lenses were selected to replace the second spherical glass lens in the original design. We propose two types of wide-angle fisheye lens designs with four spherical lenses and one aspheric lens. The results for these designs indicated a viewing angle of 174°, a total length of less than 15 mm, a spot size of less than 6 μm, lateral color within ±1 μm, field curvature within ±0.02 mm, and F-θ distortion of ±3.5%. In addition, the MTF value was larger than 0.4 at the spatial frequency of 100 cycles/mm.

Background/Aim: Immunotherapy has been considered a promising approach for brain tumor treatment since the discovery of the brain lymphatic system. Glioblastoma (GBM), the most aggressive type of brain tumor, is associated with poor prognosis and a lack of effective treatment options. Materials and Methods: To test the efficacy of human anti-PD-1, we used a humanized PD-1 knock-in mouse to establish an orthotopic GBM-bearing model. Results: Nivolumab, a human anti-PD-1, effectively inhibited tumor growth, increased the survival rate of mice, enhanced the accumulation and function of cytotoxic T cells, reduced the accumulation and function of immunosuppressive cells and their related factors, and did not induce tissue damage or biochemical changes. The treatment also induced the accumulation and activation of CD8+ cytotoxic T cells, while reducing the accumulation and activation of myeloid-derived suppressor cells, regulatory T cells, and tumor-associated macrophages in the immune microenvironment. Conclusion: Nivolumab has the potential to be a treatment for GBM. [ABSTRACT FROM AUTHOR]