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LaFexNi1−xO3 perovskite oxides were prepared by the sol–gel method under various conditions, including different pH values (pH 0 and pH 7) and different calcination temperatures (500–800 °C) as well as different Fe/Ni ratios (1/9, 3/7, 5/5, 7/3, 9/1). The samples were examined by XRD, DRS, BET, and SEM to reveal their crystallinity, light-absorption ability, specific surface area, and surface features, respectively. The photocatalytic Fenton reaction was conducted using various LaFexNi1−xO3 perovskite oxides to decompose the methylene blue molecules. Accordingly, the synthesis condition of pH 0, calcination temperature at 700 °C, and Fe/Ni ratio = 7/3 could form LaFe0.7Ni0.3O3 perovskite oxides as highly efficient photocatalysts. Moreover, various conditions during the photocatalytic degradation were verified, such as pH value, catalyst dosage, and the additional amount of H2O2. LaFe0.7Ni0.3O3 perovskite oxides could operate efficiently under pH 3.5, catalyst dosage of 50 mg/150 mL, and H2O2 concentration of 133 ppm to decompose the MB dye in the 1st order kinetic rate constant of 0.0506 s−1.

C-type lectins (CTLs) are a superfamily of Ca2+-dependent carbohydrate-recognition proteins, and an important pattern recognition receptor (PRR) in insect innate immunity which can mediate humoral and cellular immunity in insects. In this study, we report a novel dual carbohydrate-recognition domain (CRD) CTL from Plutella xylostella which we designate PxIML. PxIML is a protein with a 969 bp open reading frame (ORF) encoding 322 amino acids, containing a signal peptide and a dual-CRD with EPN (Glu124-Pro125-Asn126) and QPD (Gln274-Pro275-Asp276) motifs. The expression of PxIML mRNA in the fat body was significantly higher than in hemocytes and midgut. The relative expression levels of PxIML in the whole insect and the fat body were significantly inhibited after infection with Bacillus thuringiensis 8010 (Bt8010) at 18 h, while they were significantly upregulated after infection with Serratia marcescens IAE6 or Pichia pastoris. The recombinant PxIML (rPxIML) protein could bind to the tested pathogen-associated molecular patterns (PAMPs), and the bacteria of Enterobacter sp. IAE5, S. marcescens IAE6, Staphylococcus aureus, Escherichia coli BL21, and Bt8010 in a Ca2+-dependent manner, however, it showed limited binding to the fungus, P. pastoris. The rPxIML exhibited strong activity in the presence of Ca2+ to agglutinate Bt8010, Enterobacter sp. IAE5 and S. aureus, but it only weakly agglutinated with E. coli BL21, and could not agglutinate with S. marcescens IAE6 or P. pastoris. Furthermore, the rPxIML could bind to hemocytes, promote the adsorption of hemocytes to beads, and enhance the phenoloxidase (PO) activity and melanization of P. xylostella. Our results suggest that PxIML plays an important role in pathogen recognition and in mediating subsequent humoral and cellular immunity of P. xylostella.

Silicon-based electronic-photonic integrated circuits are promising for various applications, but their mid-infrared optical modulation is elusive. Here, tunable mid-infrared electro-absorption modulation, with broadband operation range >140 nm, is achieved in GeSn alloys on Si by controlling the Sn content.

Recently, autonomous driving has become one of the most popular topics for smart vehicles. However, traditional control strategies are mostly rule-based, which have poor adaptability to the time-varying traffic conditions. Similarly, they have difficulty coping with unexpected situations that may occur any time in the real-world environment. Hence, in this paper, we exploited Deep Reinforcement Learning (DRL) to enhance the quality and safety of autonomous driving control. Based on the road scenes and self-driving simulation modules provided by AirSim, we used the Deep Deterministic Policy Gradient (DDPG) and Recurrent Deterministic Policy Gradient (RDPG) algorithms, combined with the Convolutional Neural Network (CNN), to realize the autonomous driving control of self-driving cars. In particular, by using the real-time images of the road provided by AirSim as the training data, we carefully formulated an appropriate reward-generation method to improve the convergence speed of the adopted DDPG and RDPG models and the control performance of moving driverless cars.

Plant microRNAs (miRNAs) have recently been reported to be involved in the cross-kingdom regulation of specific cellular and physiological processes in animals. However, little of this phenomenon is known for the communication between host plant and insect herbivore. In this study, the plant-derived miRNAs in the hemolymph of a cruciferous specialist Plutella xylostella were identified by small RNAs sequencing. A total of 39 miRNAs with typical characteristics of plant miRNAs were detected, of which 24 had read counts ≥ 2 in each library. Three plant-derived miRNAs with the highest read counts were validated, and all of them were predicted to target the hemocyanin domains-containing genes of P. xylostella. The luciferase assays in the Drosophila S2 cell demonstrated that miR159a and novel-7703-5p could target BJHSP1 and PPO2 respectively, possibly in an incomplete complementary pairing mode. We further found that treatment with agomir-7703-5p significantly influenced the pupal development and egg-hatching rate when reared on the artificial diet. The developments of both pupae and adults were severely affected upon their transfer to Arabidopsis thaliana, but this might be independent of the cross-kingdom regulation of the three plant-derived miRNAs on their target genes in P. xylostella, based on expression analysis. Taken together, our work reveals that the plant-derived miRNAs could break the barrier of the insect mid-gut to enter the circulatory system, and potentially regulate the development of P. xylostella. Our findings provide new insights into the co-evolution of insect herbivore and host plant, and novel direction for pest control using plant-derived miRNAs.

This study performed thermal effect analysis and an experimental verification of the effects of ultrafast picosecond pulsed laser micro-drilling of aluminum nitride ceramic substrates. COMSOL Multiphysics was used to determine a laser drilling thermal field distribution; develop a thermal conductivity model; and further analyze the effects of different laser power levels, pulse durations, and focal points on hole diameter and hole depth after drilling. After results were obtained from the theoretical model, verification was performed through experiments. Using single-variable changes in laser power, laser pulse duration, and focal point, this study determined the relationships between each parameter and the machining effect and compared the simulation and experimental results. [ABSTRACT FROM AUTHOR]