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During the boll formation stage, cotton bolls exhibit the lowest expression of Bacillus thuringiensis (Bt) insecticidal proteins. Resistance to insects varies notably among different organs, which poses challenges for controlling cotton bollworms. Consequently, an experimental strategy was designed in the 2020–2021 cotton growing season to coordinate the enhancement of protein synthesis and the attenuation of degradation. Two Bt cultivars of Gossypium hirsutum, namely the hybrid Sikang 3 and the conventional Sikang 1, were used as test materials. Three treatments were applied at the peak flowering period: CK (the control), T1 (amino acids), and T2 (amino acids and EDTA). The results show that, in comparison to the CK group, the Bt protein contents were significantly increased in both cotton bolls and their subtending leaves under the T1 and T2 treatments. The maximum levels of increase observed were 67.5% in cotton bolls and 21.7% in leaves. Moreover, the disparity in Bt protein content between cotton bolls and their subtending leaves notably decreased by 31.2%. Correlation analysis suggested that the primary physiological mechanisms for augmenting Bt protein content involve increased protein synthesis and reduced protein catabolism, which are independent of Bt gene expression levels. Stepwise regression and path analysis revealed that elevating the soluble protein content and transaminase activity, while reducing the catabolic enzyme activities, are instrumental in enhancing the Bt protein content. Consequently, the coordinated application of amino acids and EDTA emerges as a strategy that can improve the overall resistance of Bt cotton and mitigate the spatiotemporal variations in Bt toxin concentrations in both cotton bolls and leaves.

Abstract The rotor blades of an axial‐flow turbine are cantilever structures, and there is inevitably a gap between them and the casing. Due to factors such as rotor wear and unit vibration, the eccentricity of the impeller will change during the operation of the turbine, resulting in the impeller being affected by additional radial forces, which can even lead to rubbing or biting between the impeller and the casing. To monitor the eccentricity of the impeller and the additional radial forces in real time during the operation of the turbine, this study conducted numerical simulations of the internal flow of the turbine under different eccentricities of the impeller, and analyzed the characteristics of pressure pulsation and impeller radial force in the turbine using the variational mode decomposition method. The results showed that there was a good linear relationship between the eccentricity of the impeller and the amplitude of the frequency corresponding to the rotor in pressure pulsation at the monitoring point and the Alford force acting on the impeller. Based on this finding, we established mathematical formulas for the relationship between the pressure pulsation at the monitoring point and the eccentricity of the impeller, as well as the eccentricity of the impeller and the Alford force acting on it. According to these formulas, we only need to monitor the pressure pulsation during the operation of the turbine to realize the real‐time monitoring of the eccentricity of the impeller and the Alford force, which is of great significance for ensuring the safe and stable operation of the turbine.

Addressing the challenges for detecting underwater damage to the structures with pile foundation, this study presents the design of an adsorption-operated robotic system. Initially, a prototype is proposed for an adsorption-operated robot that is equipped with an automatic movement mechanism. To account for the disturbance of the drag force in the control system, a hydrodynamic numerical model for the detection robot is established. The numerical results of the drag force are then integrated into the control system, leading to the design of a force-redeemed active disturbance rejection controller. Furthermore, a novel detection algorithm based on the image segmentation network UNet is developed for the automatic identification of damages. The performance of the controller and detection algorithm is evaluated against traditional methods. The results indicate that the proposed force-redeemed active disturbance rejection controller outperforms traditional PID and ADR controllers in terms of overshoot and adjustment time. Moreover, the developed detection algorithm exhibits superior performance in precision, F1 score, and mean intersection over union compared to the traditional algorithms of FCN, PSPnet, Deeplabv3, and UNet. Overall, this paper advances the technology of autonomous robots for underwater detection in the structures with pile foundation.

Automatic image registration of multimodal urban remote sensing images remains a critical challenging task in remote sensing image analysis due to significant nonlinear radiation distortions between multimodal image pairs; most of the traditional methods focus on the feature point detection and its local description and ignore the robust road information in multimodal urban remote sensing images. Motivated by this, we propose a fast and robust registration method for multimodal urban remote sensing images via road intersection triangular features. The proposed method obtains three main stages: Road lines extraction from images, intersection triangular feature construction, and triangular feature matching. The qualitative and quantitative experimental results show that the proposed method significantly outperforms other state-of-the-art methods, even when others completely fail to achieve the registration task of cross-modal images, our method still maintains good robustness and matching efficiency.

In this work, we developed a strategy for local chemo-immunotherapy through simultaneous incorporation of dual immune checkpoint blockade (ICB) antibodies, anti-cytotoxic T-lymphocyte-associated protein 4 (aCTLA-4) and anti-programmed cell death protein 1 (aPD-1), and a chemotherapy drug, doxorubicin (Dox), into a thermo-gelling polypeptide hydrogel. The hydrogel encapsulating Dox or IgG model antibody showed sustained release profiles for more than 12 days in vitro, and the drug release and hydrogel degradation were accelerated in the presence of enzymes. In comparison to free drug solutions or hydrogels containing Dox or antibodies only, the Dox/aCTLA-4/aPD-1 co-loaded hydrogel achieved improved tumor suppression efficiency, strengthened antitumor immune response, and prolonged animal survival time after peritumoral injection into mice bearing B16F10 melanoma. Additionally, after injection of Dox/aCTLA-4/aPD-1 co-loaded hydrogel into the surgical site following tumor resection, a significantly enhanced inhibition on tumor reoccurrence was demonstrated. Thus, the polypeptide hydrogel-based chemo-immunotherapy strategy has potential in anti-tumor therapy and the prevention of tumor reoccurrence.

Automatic matching of multimodal remote sensing images remains a vital yet challenging task, particularly for remote sensing and computer vision applications. Most traditional methods mainly focus on key point detection and description of the original image, thus ignoring the deep semantic feature information such as semantic road features, with the result that the traditional method can not effectively resist nonlinear grayscale distortion, and has low matching efficiency and poor accuracy. Motivated by this, this paper proposes a novel automatic matching method named LURF via learned unstructured road features for the multimodal images. There are four main contributions in LURF. To begin with, the semantic road features were extracted from multimodal images based on segmentation model CRESIv2. Next, based on semantic road features, a stable and reliable intersection point detector has been proposed to detect unstructured key points. Moreover, a local entropy descriptor has been designed to describe key points with the local skeleton feature. Finally, a global optimization strategy is adopted to achieve the correct matching. The extensive experimental results demonstrate that the proposed LURF outperforms other state-of-the-art methods in terms of both accuracy and efficiency on different multimodal image data sets.

Tubular turbine is a type of turbine with low-head. Due to the fact that the runner of a tubular turbine is of axial-flow type, there will be a certain width of blade tip between the blade and the chamber. In order to explore the influence of tip clearance width on the flow inside the turbine, taking the model tubular turbine as the research object, six different tip clearance widths were compared and analyzed. The research shows that the increase in blade tip clearance width affects the performance of the turbine, reduces the minimum pressure at blade tip and causes cavitation in advance. Larger tip clearance width significantly increases pressure pulsation intensity inside the turbine, especially in the vaneless region between the runner and guide vane and the area of the runner tip. However, the increase in tip clearance width can greatly reduce the axial force for about 100 N and radial excitation force for about 50% of rotating parts. Therefore, during the design and processing of tubular turbines, the blade tip clearance width should be carefully selected to ensure safe and stable operation of the unit.

Titanium nitride (TiN) exhibits extremely high wear resistance and corrosion resistance, leading to a broad range of applications. Despite the extensive theoretical efforts on the structural stability of TiN under pressure, a few experimental observations of the pressure-induced phase transition through x-ray diffraction are still in debate. Here, the Raman spectra of TiN under pressure are studied in a diamond anvil cell up to 36 GPa. The discontinuity in the pressure dependent phonon frequencies suggests a phase transition at around 5 GPa with the bonding between Ti and N hardly changing. The phase transition is ascribed to an isostructural transition or a vacancy filling mechanism.

Inter-well fluid flows through porous media are commonly encountered in the production of groundwater, oil, and geothermal energy. In this paper, inter-well porous flow inside a rectangular reservoir is solved based on the complex variable function theory combined with the method of mirror images. In order to derive the solution analytically, the inter-well flow is modeled as a 2D flow in a homogenous and isotropic porous medium. The resulted exact analytical solution takes the form of an infinite series, but it can be truncated to give high accuracy approximation. In terms of nine cases of inter-well porous flow associated with enhanced geothermal systems, the applications of the obtained analytical solution are demonstrated, and the convergence properties of the truncated series are investigated. It is shown that the convergent rate of the truncated series increases with the symmetric level of well distribution inside the reservoir, and the adoption of Euler transform significantly accelerates the convergence of alternating series cases associated with asymmetric well distribution. In principle, the analytical solution proposed in this paper can be applied to other scientific and engineering fields, as long as the involved problem is governed by 2D Laplace equation in a rectangular domain and subject to similar source/sink and boundary conditions, i.e., isolated point sources/sinks and uniform Dirichlet or homogeneous Neumann boundary conditions.

Resistive switching heterojunctions, which are promising for nonvolatile memory applications, usually share a capacitorlike metal-oxide-metal configuration. Here, we report on the nonvolatile resistive switching in Pt/LaAlO_{3}/SrTiO_{3} heterostructures, where the conducting layer near the LaAlO_{3}/SrTiO_{3} interface serves as the “unconventional” bottom electrode although both oxides are band insulators. Interestingly, the switching between low-resistance and high-resistance states is accompanied by reversible transitions between tunneling and Ohmic characteristics in the current transport perpendicular to the planes of the heterojunctions. We propose that the observed resistive switching is likely caused by the electric-field-induced drift of charged oxygen vacancies across the LaAlO_{3}/SrTiO_{3} interface and the creation of defect-induced gap states within the ultrathin LaAlO_{3} layer. These metal-oxide-oxide heterojunctions with atomically smooth interfaces and defect-controlled transport provide a platform for the development of nonvolatile oxide nanoelectronics that integrate logic and memory devices.