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Change detection (CD) stands out as a pivotal yet challenging task in the interpretation of remote sensing images. Significant developments have been witnessed, particularly with the rapid advancements in deep learning techniques. Nevertheless, challenges such as incomplete detection targets and unsmooth boundaries remain as most CD methods suffer from ineffective feature fusion. Therefore, this paper presents a multi-scale gated fusion network (MSGFNet) to improve the accuracy of CD results. To effectively extract bi-temporal features, the EfficientNetB4 model based on a Siamese network is employed. Subsequently, we propose a multi-scale gated fusion module (MSGFM) that comprises a multi-scale progressive fusion (MSPF) unit and a gated weight adaptive fusion (GWAF) unit, aimed at fusing bi-temporal multi-scale features to maintain boundary details and detect completely changed targets. Finally, we use the simple yet efficient UNet structure to recover the feature maps and predict results. To demonstrate the effectiveness of the MSGFNet, the LEVIR-CD, WHU-CD, and SYSU-CD datasets were utilized, and the MSGFNet achieved F1 scores of 90.86%, 92.46%, and 80.39% on the three datasets, respectively. Furthermore, the low computational costs and small model size have validated the superior performance of the MSGFNet. [ABSTRACT FROM AUTHOR]

Defoliation and accelerating ripening are important measures for cotton mechanization, and judging the time of defoliation and accelerating the ripening and harvest of cotton relies heavily on the boll opening rate, making it a crucial factor to consider. The traditional methods of cotton opening rate determination are time-consuming, labor-intensive, destructive, and not suitable for a wide range of applications. In this study, the relationship between the change rate of the vegetation index obtained by the unmanned aerial vehicle multi-spectrum and the ground boll opening rate was established to realize rapid non-destructive testing of the boll opening rate. The normalized difference vegetation index (NDVI) and green normalized difference vegetation index (GNDVI) had good prediction ability for the boll opening rate. NDVI in the training set had an R2 of 0.912 and rRMSE of 15.387%, and the validation set performance had an R2 of 0.929 and rRMSE of 13.414%. GNDVI in the training set had an R2 of 0.901 and rRMSE of 16.318%, and the validation set performance had an R2 of 0.909 and rRMSE of 15.225%. The accuracies of the models based on GNDVI and NDVI were within the acceptable range. In terms of predictive models, random forests achieve the highest accuracy in predictions. Accurately predicting the cotton boll opening rate can support decision-making for harvest and harvest aid spray timing, as well as provide technical support for crop growth monitoring and precision agriculture. [ABSTRACT FROM AUTHOR]

Concerning the vision of achieving carbon neutral and peak carbon goals, wind energy is extremely important as a renewable and clean energy source. However, existing research ignores the implicit features of the data preprocessing technique and the role of the internal mechanism of the optimization algorithm, making it difficult to achieve high-accuracy prediction. To fill this gap, this study proposes a wind speed forecasting model that combines data denoising techniques, optimization algorithms, and machine learning algorithms. The model discusses the important parameters in the data decomposition technique, determines the best parameter values by comparing the model's performance, and then decomposes and reconstructs the wind speed time series. In addition, a novel optimization algorithm is used to optimize the parameters of the machine learning algorithm using a waiting strategy and an aggressive strategy to improve the effectiveness of the model. Several control experiments were designed and implemented using 10-min wind speed data from three sites in Penglai, Shandong Province. Based on the numerical comparison results and the discussion of the proposed model, it is concluded that the developed model can obtain high accuracy and reliability of wind speed prediction in the short term relative to other comparative models and can have further applications in wind power plants. [ABSTRACT FROM AUTHOR]

The integrated system with the strapdown inertial navigation system (SINS) and the global positioning system (GPS) is the most popular navigation mode. It has been used in many navigation fields. Before the integrated system works properly, it must determine the initial attitude for SINS. In SINS/GPS-integrated systems, the navigational velocity can be used to carry out the initial alignment when the system is installed in the in-motion vehicle. However, the initial velocity errors are not considered in the current popular in-motion alignment methods for SINS/GPS integration. It is well-known that the initial velocity errors must exist when the initial velocity is obtained from the GPS outputs. In this paper, an improved method was proposed to solve this problem. By analyzing the original observation vectors in the in-motion coarse alignment method, an average operation was used to construct the intermediate vectors, and the new observation vector can be calculated by subtracting the intermediate vector from the original observation vector. Then, the initial velocity errors can be eliminated from the newly constructed observation vector. Thus, the interferences of the initial velocity errors for the initial alignment process can be suppressed. The simulation and field tests are designed to verify the performance of the proposed method. The tests results showed that the proposed method can obtain the higher accurate results than the current methods when the initial velocity is considered. Additionally, the results of the proposed method were similar to the current methods when the initial velocity errors were not considered. This shows that the initial velocity errors were eliminated effectively by the proposed method, and the alignment accuracy were not decreased. [ABSTRACT FROM AUTHOR]

A large number of metalworking fluids in industrial manufacturing processes generate high-concentrations of oil mist pollution, which is a typical semi-volatile aerosol and is generally composed of liquid particles and volatile gas components. Long-term exposure to oil mist pollution brings a series of occupational diseases to workers. For the semi-volatile aerosol, the traditional filter sampling method will lead to particle volatilization, which underestimates the concentration of particles and overestimates the concentration of gas. Therefore, this study combined the advantages of the electrostatic method and the Tenax tube adsorption method, to develop a more accurate measurement technology. First, a dichotomous sampler that could efficiently separate the gas and liquid phases of aerosols was optimized through a numerical model, which was validated by literature results. Next, a test table for oil mist sampling was built with a sampler which was fabricated by 3D printing, and the performance of the sampler was evaluated. The results show that the sampling technique can separate the gas and particulate phases of the oil mist efficiently and accurately. Compared with the traditional single sampling methods, the new sampler can better determine the true concentration of oil mist. [ABSTRACT FROM AUTHOR]

In monocarpic plants, stem cells are fated to die. However, the potential mechanism of stem cell death has remained elusive. Here, we reveal that the levels of two forms of reactive oxygen species (ROS), superoxide anion free radical ( O 2 · − ) and hydrogen peroxide (H2O2), show dynamic changes in the shoot apex during the plant life cycle of Arabidopsis thaliana. We found that the level of O 2 · − decreased and disappeared at four weeks after bolting (WAB), while H2O2 appeared at 3 WAB and showed a burst at 5 WAB. The timing of dynamic changes in O 2 · − and H2O2 was delayed for approximately three weeks in clv3-2, which has a longer lifespan. Moreover, exogenous application of H2O2 inhibited the expression of the stem cell determinant WUSCHEL (WUS) and promoted the expression of the developmentally programmed cell death (dPCD) marker gene ORESARA 1 (ORE1). These results indicate that H2O2 triggers an important signal inducing dPCD in stem cells. Given that O 2 · − plays roles in maintaining WUS expression and stem cell activity, we speculate that the dynamic shift from O 2 · − to H2O2 in the shoot apex results in stem cell death. Our findings provide novel insights for understanding ROS-mediated regulation during plant stem cell death. [ABSTRACT FROM AUTHOR]

In the field of robotic automation, achieving high position accuracy in robotic vision systems (RVSs) is a pivotal challenge that directly impacts the efficiency and effectiveness of industrial applications. This study introduces a comprehensive modeling approach that integrates kinematic and joint compliance factors to significantly enhance the position accuracy of a system. In the first place, we develop a unified kinematic model that effectively reduces the complexity and error accumulation associated with the calibration of robotic systems. At the heart of our approach is the formulation of a joint compliance model that meticulously accounts for the intricacies of the joint connector, the external load, and the self-weight of robotic links. By employing a novel 3D rotary laser sensor for precise error measurement and model calibration, our method offers a streamlined and efficient solution for the accurate integration of vision systems into robotic operations. The efficacy of our proposed models is validated through experiments conducted on a FANUC LR Mate 200iD robot, showcasing notable improvements in the position accuracy of robotic vision system. Our findings contribute a framework for the calibration and error compensation of RVS, holding significant potential for advancements in automated tasks requiring high precision. [ABSTRACT FROM AUTHOR]

Simple Summary: Liver receptor homolog-1 (LRH-1) is highly observed in tissues with secretory function, such as the ovaries, suggesting that LRH-1 may play an essential role in the ovarian endocrine. In particular, ovarian granulosa cells (GCs) are the functional cells that produce steroid hormones. The fate of GCs directly affects follicular development or atresia. These effects were lost in granulosa-specific LRH-1-knockout mice, showing that LRH-1 is a central modulator of ovarian function. However, the underlying mechanism LRH-1 in the bovine ovaries remains unclear. We aimed to detect the effect of LRH-1 on steroid hormones in bovine GCs and explore the potential relationship between LRH-1 and the fate of GCs. The results show that LRH-1 was specifically highly expressed in GCs of atretic follicles. Mechanistically, LRH-1 induced the apoptosis of bovine GCs by the progestogen receptor signaling pathway. While this finding provided new ideas for the study of follicular atresia, it also provided a theoretical basis for the clinical diagnosis and treatment for infertility in cow. The purpose of the present investigation was to assess the function of LRH-1 on GCs and the mechanisms involved. Here, LRH- was highly expressed in the bovine GCs of atretic follicles. Treatment with 50 μM of LRH-1 agonist (DLPC) significantly induced the expression of LRH-1 (p < 0.05). In particular, LRH-1 activation blocked the progestogen receptor signaling pathway via downregulating progesterone production and progestogen receptor levels (p < 0.05), but had no effect on 17 beta-estradiol synthesis. Meanwhile, LRH-1 activation promoted the apoptosis of GCs and increased the activity of caspase 3 (p < 0.05). Importantly, upregulating the progestogen receptor signaling pathway with progestogen could attenuate the LRH-1-induced proapoptotic effect. Moreover, treatment with progestogen decreased the activity of the proapoptotic gene caspase 3 and increased the expression of antiapoptotic gene Bcl2 in LRH-1 activated GCs (p < 0.05). Taken together, these results demonstrate that LRH-1 might be dependent on the progestogen receptor signaling pathway to modulate bovine follicular atresia. [ABSTRACT FROM AUTHOR]

High light intensity as one of the stresses could lead to generation of large amounts of reactive oxygen species (ROS) in plants, resulting in severe plant growth retardation. The photorespiration metabolism plays an important role in producing and removing a variety of ROS, maintaining the dynamic balance of the redox reaction, and preventing photoinhibition. Arabidopsis hydroxypyruvate reductase 1 (HPR1) is a primary metabolic enzyme in the photorespiration cycle. However, the role of HPR1 in plants response to high light is not clear. Here, we found that the expression of HPR1 could be induced by high light intensity. The growth and photosynthetic capacity of hpr1 mutants are seriously affected under high light intensity. The absence of HPR1 suppresses the rates of photorepair of Photosystem II (PSII), aggravates the production of ROS, and accelerates photorespiration rates. Moreover, the activity of ROS scavenging enzymes in the hpr1 mutants is significantly higher. These results indicate that HPR1 is involved in plant response to high light intensity and is essential for maintaining the dynamic balance of ROS and photorespiration. [ABSTRACT FROM AUTHOR]

Soft sensing technology has been proved to be an effective tool for the online estimation of unmeasured or variables that are difficult to directly measure. The performance of a soft sensor depends heavily on its convergence speed and generalization ability to a great extent. Based on this idea, we propose a new soft sensor model, Isomap-SVR. First, the sample data set is divided into training set and testing set by using self-organizing map (SOM) neural network to ensure the fairness and symmetry of data segmentation. Isometric feature mapping (Isomap) method is used for dimensionality reduction of the model input data, which could not only reduce the structure complexity of the proposed model but speed up learning speed, and then the Support Vector Machine Regression (SVR) is applied to the regression model. A novel bat algorithm based on Cauchy mutation and Lévy flight strategy is used to optimize parameters of Isomap and SVR to improve the accuracy of the proposed model. Finally, the model is applied to the prediction of the temperature of rotary kiln calcination zone, which is difficult to measure directly. The simulation results show that the proposed soft sensor modeling method has higher learning speed and better generalization ability. Compared with other algorithms, this algorithm has obvious advantages and is an effective modeling method. [ABSTRACT FROM AUTHOR]

To investigate the failure effects of critical fissures in rock specimens subjected to plane strain compression (PSC), five types of internal fissures in rock specimens were designed and twelve PSC tests were conducted for two lithologies based on the discrete element method (DEM). The results were analyzed in terms of the fracture mode, data characteristics, and crack evolution. The results indicated the following. (1) The rock samples with a critical fissure under PSC showed a weak face shear fracture mode, which was influenced by lithology, fissure angle, and fissure surface direction. (2) There were four critical expansion points (CEPs) of axial stress of the rocks under PSC, which were the stage signs of rock materials from local damage to complete fracture. The rock-bearing capacity index (RockBCI) was further proposed. (3) The bearing capacity of rock samples with horizontal fissures, fissures whose angles coincided with the fracture surface, and fissures whose surface was perpendicular to the lateral confine direction was the worst; their BCI2 values were found to be 80.6%, 70.8%, and 56.9% of the rock samples without any fissures, respectively. The delayed fracture situation under PSC was identified and analyzed. (4) The crack evolution followed the unified law of localization, and the fissures in the rocks changed the mode of crack development and the path of the deepening and connecting of crack clusters, as well as affecting the time process from damage to collapse. This research innovatively investigated the behavior characteristics of rock samples with a fissure under PSC, and it qualitatively and quantitatively analyzed the bearing capacity of rock mass from local damage to fracture. [ABSTRACT FROM AUTHOR]

The high crystal quality and low dislocation densities of aluminum nitride (AlN) grown on flat and nano-patterned sapphire substrate that are synthesized by the metal-organic chemical vapor deposition (MOCVD) method are essential for the realization of high-efficiency deep ultraviolet light-emitting diodes. The micro-strains of 0.18 × 10−3 cm−2 for flat substrate AlN and 0.11 × 10−3 cm−2 for nano-patterned substrate AlN are obtained by X-ray diffractometer (XRD). The screw and edge dislocation densities of samples are determined by XRD and transmission electron microscope (TEM), and the results indicate that the nano-patterned substrates are effective in reducing the threading dislocation density. The mechanism of the variation of the threading dislocation in AlN films grown on flat and nano-patterned substrates is investigated comparatively. The etch pit density (EPD) determined by preferential chemical etching is about 1.04 × 108 cm−2 for AlN grown on a nano-patterned substrate, which is slightly smaller than the results obtained by XRD and TEM investigation. Three types of etch pits with different sizes are all revealed on the AlN surface using the hot KOH etching method. [ABSTRACT FROM AUTHOR]

Simple Summary: As a member of the bone morphogenetic protein families (BMPs), BMP6 is a key regulatory factor in the ovaries. It is expressed in the ovarian granulosa cells (GCs) of different species and plays an important regulatory role in follicular growth and development. Moreover, the steroid hormones secreted by ovarian granulosa cells are involved in important physiological processes such as follicle development, ovulation, and embryo implantation. However, the role of BMP6 in steroid hormone synthesis in goat ovarian GCs remains unclear. We aimed to examine the effects of BMP6 on the function of goat ovarian GCs. The results showed that BMP6 did not significantly affect the proliferation, cell cycle, and apoptosis of ovarian GCs but it up-regulated the expression of the steroid hormone synthesis rate-limiting enzymes CYP19A1 and CYP11A1 to promote the production of 17 beta-estradiol (E2) and progesterone (P4). This finding provides a new idea for the study of steroid hormone synthesis in follicles. The purpose of this study was to investigate the effects of BMP6 on the function of goat ovarian granulosa cells (GCs). The results showed that the exogenous addition of BMP6 did not affect the EdU-positive ratio of ovarian GCs and had no significant effect on the mRNA and protein expression levels of the proliferation-related gene PCNA (p > 0.05). Meanwhile, BMP6 had no significant effect on the cycle phase distribution of GCs but increased the mRNA expression of CDK4 (p < 0.05) and CCND1 (p < 0.01) and decreased the mRNA expression of CCNE1 (p < 0.01). Moreover, BMP6 had no significant effect on the apoptosis rate of GCs and did not affect the mRNA expression levels of apoptosis-related genes BAX, BCL2, and Caspase3 (p > 0.05). Importantly, BMP6 upregulated the secretion of 17 beta-estradiol (E2) and progesterone (P4) in ovarian GCs (p < 0.01). Further studies found that BMP6 inhibited the mRNA expression of 3β-HSD and steroid synthesis acute regulator (StAR) but significantly promoted the mRNA expression of the E2 synthesis rate-limiting enzyme CYP19A1 and the P4 synthesis rate-limiting enzyme CYP11A1 (p < 0.01). Taken together, these results showed that the exogenous addition of BMP6 did not affect the proliferation, cell cycle, and apoptosis of goat ovarian GCs but promoted the secretion of E2 and progesterone P4 in ovarian GCs by upregulating the mRNA expressions of CYP19A1 and CYP11A1. [ABSTRACT FROM AUTHOR]

AP2/ERF (APETALA2/ethylene responsive factor) is a family of plant-specific transcription factors whose members are widely involved in many biological processes, such as growth, development, and biotic and abiotic stress responses. Here, 20 AP2/ERF genes were identified based on wheat RNA-seq data before and after drought stress, and classified as AP2, ERF, DREB, and RAV. The analysis of gene structure revealed that about 85% of AP2/ERF family members had lost introns, which are presumed to have been lost during the formation and evolution of the wheat genome. The expression of 20 AP2/ERF family genes could be verified by qRT-PCR, which further supported the validity of the RNA-seq data. Subsequently, subcellular localization and transcriptional activity experiments showed that the ERF proteins were mainly located in the nucleus and were self-activating, which further supports their functions as transcription factors. Furthermore, we isolated a novel ERF gene induced by drought, salt, and cold stresses and named it TaERF-6-3A. TaERF-6-3A overexpression increased sensitivity to drought and salt stresses in Arabidopsis, which was supported by physiological and biochemical indices. Moreover, the expression of stress- and antioxidant-related genes was downregulated in TaERF-6-3A-overexpressing plants. Overall, these results contribute to the further understanding of the TaERF-6-3A gene function in wheat. [ABSTRACT FROM AUTHOR]

Surface plasmon (SP) enhancement of photoluminescence (PL) from a green-emitting InGaN/GaN quantum well (QW) using nanoparticles (NPs) made of different metals and their combinations was investigated. The NPs were formed by annealing the metal films in N2 followed by rapid cooling. Four-fold enhancement in PL intensity was achieved using random metal NPs made of Cu on Mg (Cu-Mg) double metal film that was more than two folds of the enhancement observed by AgNPs. Reversing the order of metal film deposition (Mg on Cu) resulted in much lower PL intensity due to significantly different NPs size distribution as the given annealing conditions did not cause homogeneous alloying of the two metals. The results pave the way for the application of NPs of relatively low-cost unconventional metals and their combinations in the SP enhancement of LEDs. [ABSTRACT FROM AUTHOR]

Surface plasmon (SP)-enhanced quantum-well (QW) LEDs have proved their potential in replacing conventional lighting devices for their high-performance capabilities in ultraviolet (UV), blue and green spectral ranges. The SP-enhanced QW-LEDs have applications in light emission enhancement, light polarization, color conversion, and speed modulation. The electric field of the plasmonic mode of a metal couples with the exciton energy of QWs in resonance results in efficiency enhancement to several folds. The strength of the SP–QW coupling is mainly influenced by the type of metal used for SP enhancement, the metal nanostructure geometry, and the penetration depth of the SP fringing field in the p-GaN. The use of an appropriate dielectric interlayer between the metal and the p-GaN allows further control over SP resonance with QW emission wavelength. The penetration depth defines the p-GaN thickness and the QW period number for effective SP–QW coupling. The optimization of these parameters is key to achieve high efficiencies in SP-enhanced QW-LEDs for various applications. This review explains the SP enhancement mechanism and the key challenges facing the SP enhancement of QW-LEDs. The main factors that affect the SP–QW coupling have been explained in detail based on recent reports devoted to this field. [ABSTRACT FROM AUTHOR]

AlN epilayers were grown on a 2-inch [0001] conventional flat sapphire substrate (CSS) and a nano-patterned sapphire substrate (NPSS) by metalorganic chemical vapor deposition. In this work, the effect of the substrate template and temperature on stress and optical properties of AlN films has been studied by using Raman spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), UV-visible spectrophotometer and spectroscopic ellipsometry (SE). The AlN on NPSS exhibits lower compressive stress and strain values. The biaxial stress decreases from 1.59 to 0.60 GPa for AlN on CSS and from 0.90 to 0.38 GPa for AlN on NPSS sample in the temperature range 80–300 K, which shows compressive stress. According to the TEM data, the stress varies from tensile on the interface to compressive on the surface. It can be deduced that the nano-holes provide more channels for stress relaxation. Nano-patterning leads to a lower degree of disorder and stress/strain relaxes by the formation of the nano-hole structure between the interface of AlN epilayers and the substrate. The low crystal disorder and defects in the AlN on NPSS is confirmed by the small Urbach energy values. The variation in bandgap (Eg) and optical constants (n, k) with temperature are discussed in detail. Nano-patterning leads to poor light transmission due to light scattering, coupling, and trapping in nano-holes. [ABSTRACT FROM AUTHOR]

Group III–V semiconductors with direct band gaps have become crucial for optoelectronic and microelectronic applications. Exploring these materials for spintronic applications is an important direction for many research groups. In this study, pure and cobalt doped GaN nanowires were grown on the Si substrate by the chemical vapor deposition (CVD) method. Sophisticated characterization techniques such as X-ray diffraction (XRD), Scanning Electron Microscope (SEM), Energy Dispersive X-Ray Spectroscopy (EDS), Transmission Electron Microscopy (TEM), High-Resolution Transmission Electron Microscopy (HRTEM) and photoluminescence (PL) were used to characterize the structure, morphology, composition and optical properties of the nanowires. The doped nanowires have diameters ranging from 60–200 nm and lengths were found to be in microns. By optimizing the synthesis process, pure, smooth, single crystalline and highly dense nanowires have been grown on the Si substrate which possess better magnetic and optical properties. No any secondary phases were observed even with 8% cobalt doping. The magnetic properties of cobalt doped GaN showed a ferromagnetic response at room temperature. The value of saturation magnetization is found to be increased with increasing doping concentration and magnetic saturation was found to be 792.4 µemu for 8% cobalt doping. It was also depicted that the Co atoms are substituted at Ga sites in the GaN lattice. Furthermore N vacancies are also observed in the Co-doped GaN nanowires which was confirmed by the PL graph exhibiting nitrogen vacancy defects and strain related peaks at 455 nm (blue emission). PL and magnetic properties show their potential applications in spintronics. [ABSTRACT FROM AUTHOR]

Psoriasis is a skin disease that is characterized by a high degree of inflammation caused by immune dysfunction. (R)-salbutamol is a bronchodilator for asthma and was reported to alleviate immune system reactions in several diseases. In this study, using imiquimod (IMQ)-induced mouse psoriasis-like dermatitis model, we evaluated the therapeutic effects of (R)-salbutamol in psoriasis in vivo, and explored the metabolic pathway involved. The results showed that, compared with IMQ group, (R)-salbutamol treatment significantly ameliorated psoriasis, reversed the suppressive effects of IMQ on differentiation, excessive keratinocyte proliferation, and infiltration of inflammatory cells. Enzyme-linked immunosorbent assays (ELISA) showed that (R)-salbutamol markedly reduced the plasma levels of IL-17. Cell analysis using flow cytometry showed that (R)-salbutamol decreased the proportion of CD4+ Th17+ T cells (Th17), whereas it increased the percentage of CD25+ Foxp3+ regulatory T cells (Tregs) in the spleens. (R)-salbutamol also reduced the increased weight ratio of spleen to body. Furthermore, untargeted metabolomics showed that (R)-salbutamol affected three metabolic pathways, including (i) arachidonic acid metabolism, (ii) sphingolipid metabolism, and (iii) glycerophospholipid metabolism. These results demonstrated that (R)-salbutamol can alleviate IMQ-induced psoriasis through regulating Th17/Tregs cell response and glycerophospholipid metabolism. It may provide a new use of (R)-salbutamol in the management of psoriasis. [ABSTRACT FROM AUTHOR]