Ga₂O₃ thin films were fabricated by the electron-beam evaporation technique at a varying oxygen partial pressure from 0 to 2.0 × 10⁻² Pa. The effect of oxygen partial pressure on the crystalline structure and optical properties of the Ga₂O₃ films was analyzed using sophisticated techniques including X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Raman spectroscopy, spectroscopic ellipsometry, ultraviolet-visible spectroscopy and a laser-induced damage test system. The correlation between the oxygen partial pressure and the film’s properties in optics and materials were investigated. XRD and Raman revealed that all films were amorphous in spite of applying a varying oxygen partial pressure. With the change of oxygen partial pressure, XPS data indicated that the content of oxygen in the Ga₂O₃ films could be broadly modulable. As a result, a changeable refractive index of the Ga₂O₃ film is realizable and a variable blue-shift of absorption edges in transmittance spectra of the films is achievable. Moreover, the damage threshold value varied from 0.41 to 7.51 J/cm² according to the rise of oxygen partial pressure. These results demonstrated that the optical properties of Ga₂O₃ film can be broadly tunable by controlling the oxygen content in the film.

As the energy crisis environmental concerns rise, harnessing renewable energy sources like photovoltaics (PV) is critical for sustainable development. However, the seasonal variability and random intermittency of solar power pose significant forecasting challenges, threatening grid stability. Therefore, this paper proposes a novel renewable energy hybrid forecasting method, NCPO-ELM, to adequately capture spatial and temporal dependencies within meteorological data crucial for accurate predictions. To effectively optimize the performance of the Extreme Learning Machine (ELM), the Normal Cloud Parrot Optimization (NCPO) algorithm is developed, inspired by Pyrrhura Molinae parrots’ flock behavior and cloud model theory. NCPO integrates five unique search strategies and utilizes a random structure to explore and exploit. By introducing the normal cloud model to generate random samples with specific distributions, the algorithm enhances solution space coverage. NCPO is subsequently employed to optimize the Single-Layer Feedforward Network (SLFN) hidden layer hyperparameters, yielding optimal weights and biases for the output layer, thereby reducing benchmark ELM’s sensitivity to noise and instability from random initialization. The actual forecasting results of PV stations across different regions demonstrate that the proposed NCPO-ELM shows superior prediction accuracy and performance compared to existing hybrid forecasting approaches, particularly for time series with diverse data characteristics and seasonal variations.

Background: Chiral safety, especially chiral drug inversion in vivo, is the top priority of current scientific research. Medicine researchers and pharmacists often ignore that one enantiomer will be converted or partially converted to another enantiomer when it is ingested in vivo. So that, in the context that more than 50% of the listed drugs are chiral drugs, it is necessary and important to pay attention to the inversion of chiral drugs. Methods: The metabolic and stereoselective pharmacokinetic characteristics of seven chiral drugs with one chiral center in the hydroxy group were reviewed in vivo and in vitro including the possible chiral inversion of each drug enantiomer. These seven drugs include (S)-Mandelic acid, RS-8359, Tramadol, Venlafaxine, Carvedilol, Fluoxetine and Metoprolol. Results: The differences in stereoselective pharmacokinetics could be found for all the seven chiral drugs, since R and S isomers often exhibit different PK and PD properties. However, not every drug has shown the properties of one direction or two direction chiral inversion. For chiral hydroxyl group drugs, the redox enzyme system may be one of the key factors for chiral inversion in vivo. Conclusion: In vitro and in vivo chiral inversion is a very complex problem and may occur during every process of ADME. Nowadays, research on chiral metabolism in the liver has the most attention, while neglecting the chiral transformation of other processes. Our review may provide the basis for the drug R&D and the safety of drugs in clinical therapy.

A six-channel fan-shaped integrated narrow-band filter on a silicon substrate was designed on the basis of the Fabray–Perot (FP) theory and was fabricated using e-beam thermal evaporation. The central wavelength was modulated by modifying the FP cavity thickness using the combination mask method. Germanium and zinc sulfide were selected as the high and low refractive index film materials, respectively. Its average peak transmission reached 83.3%, the cut-off transmittance was less than 1%, and the full width at half maximum (FWHM) changed from 55 and 94 nm, and the central wavelength positioning accuracy error was less than 0.35%. Furthermore, transmittance was also calculated inversely, using the thickness of each layer of films, in order to deduce the reason of the decrease in peak transmittance. Thickness deviation of each layer and interface scattering contributed to the decrease of peak transmittance. Compared with the same type of products in the market, our filter showed better properties than that of some published and commercial filter.

The growth mechanism of nanocolumnar silver thin film deposited on a smooth silicon substrate using electron beam evaporation process at an oblique angle was simulated with the Kinetic Monte Carlo method. Following the simulated silver nanostructured thin film, a further computational simulation was done using COMSOL for surface-enhanced Raman scattering effects. The simulation results were compared against corresponding experimental results, which demonstrated high agreement between simulation results and experimental data. It was found that as the incident deposition angle increased, the density of the Ag thin film significantly decreased and the surface roughness increased. When the incident deposition angle was at 75° and 85°, the resulting nanocolumnar structure was significantly tilted. For Ag thin films deposited at all investigated angles, surface-enhanced Raman scattering effects were observed. Particularly, the Ag nanocolumns deposited at 85° showed remarkable Surface-enhanced Raman Scattering effects. This was seen in both COMSOL simulations and experimental results: Enhancement factors were 2 × 10⁷ in COMSOL simulation and 3.3 × 10⁵ in the experiment.

To address challenges such as large-scale variations, high density of small targets, and the large number of parameters in deep learning-based target detection models, which limit their deployment on UAV platforms with fixed performance and limited computational resources, a lightweight UAV target detection algorithm, YOLO-LSM, is proposed. First, to mitigate the loss of small target information, an Efficient Small Target Detection Layer (ESTDL) is developed, alongside structural improvements to the baseline model to reduce parameters. Second, a Multiscale Lightweight Convolution (MLConv) is designed, and a lightweight feature extraction module, MLCSP, is constructed to enhance the extraction of detailed information. Focaler inner IoU is incorporated to improve bounding box matching and localization, thereby accelerating model convergence. Finally, a novel feature fusion network, DFSPP, is proposed to enhance accuracy by optimizing the selection and adjustment of target scale ranges. Validations on the VisDrone2019 and Tiny Person datasets demonstrate that compared to the benchmark network, the YOLO-LSM achieves a mAP0.5 improvement of 6.9 and 3.5 percentage points, respectively, with a parameter count of 1.9 M, representing a reduction of approximately 72%. Different from previous work on medical detection, this study tailors YOLO-LSM for UAV-based small object detection by introducing targeted improvements in feature extraction, detection heads, and loss functions, achieving better adaptation to aerial scenarios.