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China's Yunnan Province, known for its tea plantations, faces significant challenges in smart pest management due to its ecologically intricate environment. To enable the intelligent monitoring of pests within tea plantations, this study introduces a novel image recognition algorithm, designated as YOLOv8n-WSE-pest. Taking into account the pest image data collected from organic tea gardens in Yunnan, this study utilizes the YOLOv8n network as a foundation and optimizes the original loss function using WIoU-v3 to achieve dynamic gradient allocation and improve the prediction accuracy. The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model's complexity. The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. The research results demonstrate that compared to the original YOLOv8n model, the improved YOLOv8n-WSE-pest model shows increases in the precision, recall, mAP50, and F1 score by 3.12%, 5.65%, 2.18%, and 4.43%, respectively. In external validation, the mAP of the model outperforms other deep learning networks such as Faster-RCNN, SSD, and the original YOLOv8n, with improvements of 14.34%, 8.85%, and 2.18%, respectively. In summary, the intelligent tea garden pest identification model proposed in this study excels at precise the detection of key pests in tea plantations, enhancing the efficiency and accuracy of pest management through the application of advanced techniques in applied science. [ABSTRACT FROM AUTHOR]

Frequency conversion process based on periodically poled thin-film lithium niobate (PPTFLN) has been widely recognized as an important component for quantum information and photonic signal processing. Benefiting from the tight confinement of optical modes, the normalized conversion efficiency (NCE) of nanophotonic waveguides is improved by orders of magnitude compared to their bulk counterparts. However, the power conversion efficiency of these devices is limited by inherent nanoscale inhomogeneity of thin-film lithium niobate (TFLN), leading to undesirable phase errors. In this paper, we theoretically present a novel approach to solve this problem. Based on dispersion engineering, we aim at adjusting the waveguide structure, making local waveguide width adjustment at positions of different thicknesses, thus eliminating the phase errors. The adapted waveguide width design is applied for etched and loaded waveguides based on PPTFLN, achieving the ultrahigh power conversion efficiency of second harmonic generation (SHG) up to 2.1 × 104%W−1 and 6936%W−1, respectively, which surpasses the power conversion efficiency of other related works. Our approach just needs standard periodic poling with a single period, significantly reducing the complexity of electrode fabrication and the difficulty of poling, and allows for the placing of multiple waveguides, without individual poling designs for each waveguide. With the advantages of simplicity, high production, and meeting current micro–nano fabrication technology, our work may open a new way for achieving highly efficient second-order nonlinear optical processes based on PPTFLN. [ABSTRACT FROM AUTHOR]

Photodetectors have a wide range of applications across various fields. Self-powered photodetectors that do not require external energy have garnered significant attention. The photoelectrochemical type of photodetector is a self-powered device that is both simple to fabricate and offers high performance. However, developing photoelectrochemical photodetectors with superior quality and performance remains a significant challenge. The electrolyte, which is a key component in these detectors, must maintain extensive contact with the semiconductor without degrading its material quality and efficiently catalyze the redox reactions of photogenerated electrons and holes, while also facilitating rapid charge carrier transport. In this study, α -Ga2O3 nanorod arrays were synthesized via a cost-effective hydrothermal method to achieve a self-powered solar-blind photodetector. The impacts of different electrolytes—Na2SO4, NaOH, and Na2CO3—on the photodetector was investigated. Ultimately, a self-powered photodetector with Na2SO4 as the electrolyte demonstrated a stable photoresponse, with the maximum responsivity of 0.2 mA/W at 262 nm with the light intensity of 3.0 mW/cm2, and it exhibited rise and decay times of 0.16 s and 0.10 s, respectively. The α -Ga2O3 nanorod arrays and Na2SO4 electrolyte provided a rapid pathway for the transport of photogenerated carriers and the built-in electric field at the semiconductor–liquid heterojunction interface, which was largely responsible for the effective separation of photogenerated electron–hole pairs that provided the outstanding performance of our photodetector. [ABSTRACT FROM AUTHOR]

With the rapid development of optical communication and quantum information, the demand for efficient and broadband nonlinear frequency conversion has increased. At present, most single-frequency conversion processes in lithium niobate on insulator (LNOI) waveguides suffer from lateral leakage without proper design, leading to an additional increase in propagation loss. Achieving broadband frequency conversion also encounters this problem in that there are no relevant works that have solved this yet. In this paper, we theoretically propose an efficient and flat broadband second harmonic generation (SHG) in silicon nitride loaded apodized chirped periodically poled LNOI waveguides. By using a bound states in the continuum (BICs) mechanism to reduce the propagation loss and utilizing the characteristic that the BICs are insensitive to wavelength, an ultra-low-loss wave band of 80 nm is realized. Then, by employing an apodized chirped design, a flat broadband SHG is achieved. The normalized conversion efficiency (NCE) is approximately 222%W−1cm−2, and the bandwidth is about 100 nm. Moreover, the presented waveguides are simple and can be fabricated without direct etching of lithium niobate, exhibiting excellent fabrication tolerance. Our work may open a new avenue for exploring low-loss and flat broadband nonlinear frequency conversion on various on-chip integrated photonic platforms. [ABSTRACT FROM AUTHOR]

To investigate the variation in flavonoids content in ancient tree sun–dried green tea under abiotic stress environmental conditions, this study determined the flavonoids content in ancient tree sun−dried green tea and analyzed its correlation with corresponding factors such as the age, height, altitude, and soil composition of the tree. This study uses two machine−learning models, Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression, to build a predictive model based on the selection of effective variables. During the process, bootstrap was used to expand the dataset for single−factor and multi−factor comparative analyses, as well as for model validation, and the goodness−of−fit was assessed using the Akaike information criterion (AIC). The results showed that pH, total potassium, nitrate nitrogen, available phosphorus, hydrolytic nitrogen, and ammonium nitrogen have a high accuracy in predicting the flavonoids content of this model and have a synergistic effect on the production of flavonoids in the ancient tree tea. In this prediction model, when the flavonoids content was >6‰, the area under the curve of the training set and validation set were 0.8121 and 0.792 and, when the flavonoids content was >9‰, the area under the curve of the training set and validation set were 0.877 and 0.889, demonstrating good consistency. Compared to modeling with all significantly correlated factors (p < 0.05), the AIC decreased by 32.534%. Simultaneously, a visualization system for predicting flavonoids content in ancient tree sun−dried green tea was developed based on a nomogram model. The model was externally validated using actual measurement data and achieved an accuracy rate of 83.33%. Therefore, this study offers a scientific theoretical foundation for explaining the forecast and interference of the quality of ancient tree sun−dried green tea under abiotic stress. [ABSTRACT FROM AUTHOR]

To explore the changes in epigallocatechin gallate (EGCG) content in tea under abiotic stress conditions, we collected tea samples, along with corresponding soil and altitude data, and utilized the measured data for single-factor analysis. At the same time, the LASSO regression method, which is rarely used in agriculture, was employed to screen modeling factors, a prediction model was established, and the Akaike information criterion (AIC) was introduced to compare the goodness of fit. The results show that LASSO screening reduced the AIC value of the model by 13.8%. The average area under the curve of the training set and the validation set was 0.81 and 0.76, respectively, and the calibration curve also showed good consistency. Based on the nomogram model, a visual prediction system was developed, and the content prediction curve was introduced for detailed soil evaluation. The accuracy rate reached 75% after external verification. This study provides a theoretical basis for elucidating the prediction and intervention of Pu'er tea quality under abiotic stress conditions. [ABSTRACT FROM AUTHOR]

In order to solve the problem of an accurate recognition of tea picking through tea picking robots, an edge device detection method is proposed in this paper based on ShuffleNetv2-YOLOv5-Lite-E for tea with one bud and two leaves. This replaces the original feature extraction network by removing the Focus layer and using the ShuffleNetv2 algorithm, followed by a channel pruning of YOLOv5 at the neck layer head, thus achieving the purpose of reducing the model size. The results show that the size of the improved generated weight file is 27% of that of the original YOLOv5 model, and the mAP value of ShuffleNetv2-YOLOv5-Lite-E is 97.43% and 94.52% on the pc and edge device respectively, which are 1.32% and 1.75% lower compared to that of the original YOLOv5 model. The detection speeds of ShuffleNetv2-YOLOv5-Lite-E, YOLOv5, YOLOv4, and YOLOv3 were 8.6 fps, 2.7 fps, 3.2 fps, and 3.4 fps respectively after importing the models into an edge device, and the improved YOLOv5 detection speed was 3.2 times faster than that of the original YOLOv5 model. Through the detection method, the size of the original YOLOv5 model is effectively reduced while essentially ensuring recognition accuracy. The detection speed is also significantly improved, which is conducive to the realization of intelligent and accurate picking for future tea gardens, laying a solid foundation for the realization of tea picking robots. [ABSTRACT FROM AUTHOR]

Aqueous zinc-ion hybrid supercapacitors (AZHSs) are promising candidates for powering mobile devices due to their intrinsically high safety, the high theoretical capacity of zinc anodes, and the wide range of sources of raw materials for activated carbon (AC) cathodes. Here, we report that there is a synergistic effect between the anions of an AZHS electrolyte, which can significantly improve the specific capacity and rate capability of an AC cathode. The results showed that the specific capacities of the AC cathode//2 M ZnSO4(aq)//Zn anode energy storage system were 115 and 41 mAh g−1 at 0.1 and 5 A g−1 current densities, respectively. The specific capacity at a 0.1 A g−1 current density was enhanced to 136 mAh g−1 by doping 0.5% ZnCl2 and 0.5% Zn(CF3SO3)2 in the 2 M ZnSO4 electrolyte. The specific capacity at a 5 Ag−1 current density was enhanced to 69 mAh g−1 by doping 1% ZnCl2 and 0.5% Zn(CF3SO3)2 in the 2 M ZnSO4 electrolyte. In addition, the co-doped electrolyte increased the energy consumption of the binding of the AC surface groups with H+ and inhibited the precipitation of Zn4SO4(OH)6·5H2O. This provides an important perspective for improving the performance of AZHSs. [ABSTRACT FROM AUTHOR]

Laser metal-wire deposition (LMwD) exhibits a larger molten pool and layer height during printing, compared to powder bed fusion additive manufacturing; in the present study, these features revealed a more inhomogeneous but easily observable microstructure. The coaxial double laser used herein makes the energy distribution of the molten pool more complex than that afforded by a single laser source, and the microstructure of the LMwD parts was more heterogeneous as well. We observed the microstructure of Ti6Al4V by the double LMwD as-built samples by conducting a laboratory experiment and a simulation. The precipitated martensite (α') phase was defined after eliminating the influence of the β element in an X-ray diffraction analysis, which has not been discussed previously in the literature. We also propose a theory regarding the formation of heat-affected zone (HAZ) bands in an environment that includes the α' phase. Our experiments revealed only white HAZ bands, which can be attributed to the solute partitioning caused by sequential thermal cycling and the absence of the β element. The microhardness of the HAZ band areas was lower than that of both the upper and lower sides. The simulation results indicate that the maximum temperature of 2925 °C restrains the generating of HAZ bands in the final two deposited layers, due to its great difference from the β transus temperature. Moreover, the higher heat accumulation in the upper layers promoted the migration of β-grain boundaries, which may explain why the coarse columnar β grains tended to grow at the edge area in the layers deposited later. We also observed that with the use of high temperature, the nucleation of β grains is more easily promoted in the lower layers. We conclude that the concentration of residual stress in the fusion zone and the first layer is favorable to the nucleation of equiaxed grains. [ABSTRACT FROM AUTHOR]

To precisely control the manta ray robot and improve its swimming and turning speed, the hydrodynamic parameters corresponding to different motion control variables must be tested experimentally. In practice, too many input control parameters will bring thousands of groups of underwater experiments, posing challenges to the duration and operability of the engineering project. This study proposes a generative adversarial network model to reduce the experimental period by predicting the hydrodynamic experimental time-series data of forces and torques in the three-coordinate directions in a Cartesian coordinate system through different combinations of motion control parameters. The motion control parameters include the rotation amplitude, frequency, and phase difference of the four steering gears which drive the pectoral fins. We designed the prototype and experimental platform and obtained 150 sets of experimental data.To prevent overfitting, the size of the dataset was expanded to 2250 groups by slicing time series, and the subsequences of varying lengths were extended to the same length by LSTM. Finally, the GAN model is used to predict the hydrodynamic time series corresponding to the different motion parameters. The results show that the GAN model can accurately predict the input both from the validation set and the unlearned interpolated motion parameters. This study will save experimental time and cost and provide detailed hydrodynamic experimental data for the precise control of manta rays. [ABSTRACT FROM AUTHOR]

Oscillating pectoral fins' spanwise flexibility is a key factor influencing the forwarding propulsion performance of bionic cownose rays, including thrust and heave-pitch stability. This study explores the effects of the bionic pectoral fin ray's spanwise flexibility on its propulsion performance via experiments. Inspired by the cownose ray, a pair of bionic pectoral fins with fin rays and fabric skin was designed, and two motors drive the controllable flapping motion. The bionic pectoral fins' flexibility can be quantified by using fin rays' bending stiffness. The experiments were carried out in a water tank to measure the thrust, the lift force, and the pitch moment of the bionic cownose ray. The fin rays are divided into plastic sheets of five thicknesses and three fin rays with more obvious stiffness variations. The movement parameters included the following: the flapping frequency of 0.3–0.7 Hz, the flapping amplitude of 20–40°, and the phase difference of 20–40°. The experimental results show that the stiffness of the bionic pectoral fin rays plays an important role in the thrust, lift force, and pitch moment. The fin rays with high stiffness root segment and low stiffness tip segment have lower lift and pitch moment while maintaining a high thrust. This shows that the pectoral fins' flexible characteristics of the cownose ray are of great significance to the design of the bionic prototype. [ABSTRACT FROM AUTHOR]

Perovskite Solar Cells are a promising solar energy harvesting technology due to their low cost and high-power conversion efficiency. A high-quality perovskite layer is fundamental for a highly efficient perovskite Solar Cell. Utilizing a gas quenching process (GQP) can eliminate the need for toxic, flammable, and expensive anti-solvents in the preparation of perovskite layers. It is a promising candidate technology for large scale preparation of perovskite layers, as it can be easily integrated in a production line by coupling up-scalable techniques. The GQP removes the need for polar solvents in the precursor solution layer by using nitrogen flow, rather than extracting them with non-polar solvents. The crystallization dynamics in this process can be significantly different. In this study, we found that the quality of perovskite crystal from GQP is much more sensitive to Lewis base molecules (LBMs) in the precursor solution than it is in anti-solvents technology. Thus, the processing parameters of the LBMs in anti-solvents technology cannot be directly transferred to the GQP. An XRD and 1H NMR study explains the origin of the S-shaped J–V curves and how these LBMs hinder the reaction between PbI2 and monovelent cations. [ABSTRACT FROM AUTHOR]

Perovskite solar cells (PSC) are considered promising next generation photovoltaic devices due to their low cost and high-power conversion efficiency (PCE). The perovskite material in the photovoltaic devices plays the fundamental role for the unique performances of PSC. Formamidinium based perovskite materials have become a hot-topic for research due to their excellent characteristics, such as a lower band gap (1.48 V), broader light absorption, and better thermal stability compared to methylammonium based perovskite materials. There are four phases of perovskite materials, named the cubic α-phase, tetragonal β-phase, orthorhombic γ-phase, and δ-phase (yellow). Many research focus on the transition of α-phase and δ-phase. α-Phase FA-based perovskite is very useful for photovoltaic application. However, the phase stability of α-phase FA-based perovskite materials is quite poor. It transforms into its useless δ-phase at room temperature. This instability will lead the degradation of PCE and the other optoelectronic properties. For the practical application of PSC, it is urgent to understand more about the mechanism of this transformation and boost the stability of α-Phase FA-based perovskite materials. This review describes the strategies developed in the past several years, such as mixed cations, anion exchange, dimensions controlling, and surface engineering. These discussions present a perspective on the stability of α-phase of FA-based perovskite materials and the coming challenges in this field. [ABSTRACT FROM AUTHOR]

The SARS-CoV virus spreads in the atmosphere mainly in the form of aerosols. Particle air filters are widely used in indoor heating, ventilation, and air-conditioning (HVAC) systems and filtration equipment to reduce aerosol concentration and improve indoor air quality. Requirements arise to rate filters according to their mass-based filtration efficiency. The size distribution of test aerosol greatly affects the measurement results of mass-based filtration efficiency and dust loading of filters, as well as the calibration of optical instruments for fine-particle (PM2.5) mass concentration measurement. The main objective of this study was to find a new method to generate a chemically nontoxic aerosol with a similar particle size distribution to atmospheric aerosol. We measured the size distribution of aerosols generated by DEHS (di-ethyl-hexyl-sebacate), PSL (poly-styrene latex), olive oil, and 20% sucrose solution with a collision nebulizer in a wide range of 15 nm–20 μm. Individually, none of the solutions generated particles that share a similar size distribution to atmospheric aerosol. We found that the 20% sucrose solution + olive oil mixture solution (Vss:Voo = 1:2) could be used to generate a chemically nontoxic aerosol with similar particle number/volume size distribution to the atmospheric aerosol (t-test, p < 0.05). The differences in the mass-base filtration efficiency measured by the generated aerosol and the atmospheric aerosol were smaller than 2% for MERV 7, 10, 13, and 16 rated filters. The aerosol generated by the new method also performed well in the calibration of optical-principle-based PM2.5 concentration measurement instruments. The average relative difference measured by a tapered element oscillating microbalance (TEOM) and a Dusttrak Model 8530 (calibrated by aerosol generated by the new method) was smaller than 5.8% in the real-situation measurement. [ABSTRACT FROM AUTHOR]

In the present study, four new compounds including a pair of 2-benzoyl tetrahydrofuran enantiomers, namely, (−)-1S-myrothecol (1a) and (+)-1R-myrothecol (1b), a methoxy-myrothecol racemate (2), and an azaphilone derivative, myrothin (3), were isolated along with four known compounds (4–7) from cultures of the deep-sea fungus Myrothecium sp. BZO-L062. Enantiomeric compounds 1a and 1b were separated through normal-phase chiral high-performance liquid chromatography. The absolute configurations of 1a, 1b, and 3 were assigned by ECD spectra. Among them, the new compound 1a and its enantiomer 1b exhibited anti-inflammatory activity, inhibited nitric oxide formation in lipopolysaccharide-treated RAW264.7 cells, and exhibited antioxidant activity in the 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) and oxygen radical absorbance capacity assays. [ABSTRACT FROM AUTHOR]

This article investigated the microstructure of Ti6Al4V that was fabricated via selective laser melting; specifically, the mechanism of martensitic transformation and relationship among parent β phase, martensite (α') and newly generated β phase that formed in the present experiments were elucidated. The primary X-ray diffraction (XRD), transmission electron microscopy (TEM) and tensile test were combined to discuss the relationship between α', β phase and mechanical properties. The average width of each coarse β columnar grain is 80–160 μm, which is in agreement with the width of a laser scanning track. The result revealed a further relationship between β columnar grain and laser scanning track. Additionally, the high dislocation density, stacking faults and the typical ( 10 1 ¯ 1 ) twinning were identified in the as-built sample. The twinning was filled with many dislocation lines that exhibited apparent slip systems of climbing and cross-slip. Moreover, the α + β phase with fine dislocation lines and residual twinning were observed in the stress relieving sample. Furthermore, both as-built and stress-relieved samples had a better homogeneous density and finer grains in the center area than in the edge area, displaying good mechanical properties by Feature-Scan. The α' phase resulted in the improvement of tensile strength and hardness and decrease of plasticity, while the newly generated β phase resulted in a decrease of strength and enhancement of plasticity. The poor plasticity was ascribed to the different print mode, remained support structures and large thermal stresses. [ABSTRACT FROM AUTHOR]