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Abstract Organic mechanoluminescence materials, featuring dual emission and ultralong phosphorescence characteristics, exhibit significant potential for applications in real-time stress sensing, pressure-sensitive lighting, advanced security marking techniques, and material breakage monitoring. However, due to immature molecular design strategies and unclear luminescence mechanisms, these materials remain rarely reported. In this study, we propose a valuable molecular design strategy to achieve dual-channel mechano-phosphorescence. By introducing the arylphosphine oxide group into a highly twisted molecular framework, enhanced intra- and intermolecular interactions could be achieved within rigid structures, leading to dual-channel mechanoluminescence with greatly promoted ultralong phosphorescence. Further investigations reveal the substantial boosting effect of intra- and intermolecular interactions on mechanoluminescence and ultralong phosphorescence properties by locking the highly twisted molecular skeleton. This work provides a concise and guiding route to develop novel smart responsive luminescence materials for widespread applications in material science.

Abstract In this study, we concentrate on the seismic signature of subducted sediments and suggest the formation of the L‐discontinuity beneath the ancient craton related to migrated sediment dehydration. We first determined the single‐crystal elasticity of topaz, the product of sediment dehydration, at high pressures and temperatures by Brillouin scattering. Using the derived elastic parameters, we establish the velocity and density profiles of subducted sediments in the upper mantle. According to our modeling results, 8.5–17.5 vol.% sediments intruding into the upper mantle will induce a 2%–4% low‐VS anomaly at 210–260 km. Meanwhile, continuous heating will lead to the dehydration of phengite in sediments. The dehydration of this amount sediments can generate a 3%–6% ISS with negative Clapeyron slopes, satisfying the observed L‐discontinuity in northern Finland and northern America without the anisotropy changes but accompanied by low‐velocity anomalies. Our study thus provides new insights into the origin of the L‐discontinuity.

Abstract Polymeric ultralong organic phosphorescence (UOP) with persistent emission is of great importance in practical applications. However, achieving good water‐resistance for long‐term environmental stability is a formidable challenge. In this contribution, through tailoring the alkyl‐chain length of the hardeners and emitters, polymeric UOPs with varying crosslinking density and hydrophobic effect were obtained. Notably, all the polymers show no obvious decrease in UOP emission after high temperature‐humidity test (85°C/85% relative humidity for 7 days). Detailed investigations demonstrate that the rigid covalent crosslinking networks suppress the quenching of triplet excitons while the hydrophobic microenvironment affords good water/moisture‐resistance ability. Moreover, the polymers with superior processability are successfully applied as optical coatings, prepreg, and afterglow displays. With this work, we provide a new strategy to promote the long‐term stability of polymeric UOP materials in high‐temperature‐humidity conditions.

Impact force identification has always been of significance for structure health monitoring especially on the applications involving composite materials. As a typical inverse problem, impact force reconstruction and localization is undoubtedly a challenging task. The well-known ℓ 1 sparse regularization has a tendency to underestimate the amplitude of impact forces. To alleviate this limitation, we propose an accelerated generalized minimax-concave (AGMC) for sparse regularization that employs a non-convex generalized minimax-concave (GMC) penalty as the regularizer and incorporates an acceleration technique to expedite the attainment of the global minimum. Compared with the classic ℓ 1 -norm penalty, the GMC penalty can not only induce sparsity in the estimation, but also maintain the convexity of the cost function, so that the global optimal solution can be obtained through convex optimization algorithms. This method is applied to solve the impact force identification problem with unknown force locations to simultaneously reconstruct and localize impact forces in the under-determined case utilizing a limited number of sensors. Meanwhile, K-sparsity criterion is used to adaptively select regularization parameters by taking advantage of the sparse prior knowledge on impact forces. Simulations and experiments are conducted on a composite plate to verify the computational efficiency and robustness of the AGMC method in terms of impact force reconstruction and localization, particularly in the presence of noise. Results demonstrate that the proposed AGMC method achieves faster convergence and provides more accurate and sparse reconstruction and localization of impact forces compared to other state-of-the-art sparse regularization methods.

Coastal blue carbon plays an important role in the global climate change and carbon cycle. Ecological restoration and market trading can effectively improve coastal blue carbon sink, which is a cost-effective way to achieve carbon neutrality. In order to explore the potential of coastal blue carbon to promote the realization of carbon neutrality, this paper elaborated advantages of developing coastal blue carbon. At the same time, this paper analyzed the problems faced by coastal blue carbon development in system construction and technology development, then put forward the countermeasures and suggestions: improve the policy measures of coastal blue carbon conservation and carbon sink trading, and promote the mechanism construction of land-sea coordination and ecological compensation. Promote the development of blue carbon greenhouse gas inventories and participation in international cooperation. Set up monitoring and assessment pilots to improve carbon sink measurement and accounting methods. Strengthen the scientific research and radical technical bottlenecks.

Abstract To achieve highly‐efficient organic light‐emitting diodes (OLEDs), great efforts have been devoted into constructing thermally activated delayed fluorescence (TADF) with high horizontal dipole ratios (Θ//). Here, we proposed a design strategy by integrating a rigid electron‐accepting oxygen‐bridged boron core with triple electron‐donating groups, which exhibited a “shamrock‐shape”, namely BO‐3DMAC and BO‐3DPAC. Benefiting from the rigid and large‐planar skeletons brought by shamrock‐shaped design, BO‐3DMAC and BO‐3DPAC exhibit high Θ// of 84%/70% and 93%/94% in neat/doped films, respectively, and finally furnish excellent external quantum efficiencies (EQEs) of up to 28.3% and 38.7% in 20 wt% doped OLEDs with sky‐blue emission, as well as adequate EQEs of up to 21.0% and 16.7% in nondoped OLEDs. This work unveils a promising strategy to establish high‐Θ// TADF emitters by constructing large‐planar molecular structures using shamrock‐shaped design.

Semiconductors typically exhibit long-wavelength LSPR absorption in the infrared region due to lower carrier density. Tuning the carrier density of semiconductors and blue-shifting their LSPR absorption to the visible and near-infrared region has always been a great challenge. Herein, we discussed how the controllable carrier of (Ag)x(MoO3)y composite influences the LSPR based on SERS test and UV–Vis–NIR absorption spectra. We were surprised to find that the LSPR absorption wavelength can be easily tuned from 950 to 735 nm by changing the sputtering power of MoO3 of the (Ag)x(MoO3)y composite. This shows that LSPR can be precisely adjusted by increasing the semiconductor content and even the carrier density. In addition, the carrier density was measured by Hall effect to investigate the SERS intensity change caused by electromagnetic (EM) enhancement, and obtain the relationship between the two. The findings of this work provide an idea for tunable LSPR and the research of EM contributions to SERS.

Slender urban road facilities (SURFs) with extreme aspect ratios are essential roles of the road network and exist everywhere in urban scenarios, such as street lamps, traffic lights, and monitors. Their information provides important knowledge for road safety, traffic control, urban planning, city management, etc. With low cost and high-efficiency benefits, oblique aerial images are easily captured to cover large-scale areas, which can be appropriately used to survey SURFs in urban areas automatically. Meanwhile, instance segmentation methods are frequently applied, predicting bounding boxes and semantic masks of objects simultaneously, yet a minority is delicately designed for SURFs. This research aims to propose an instance segmentation method to automatically extract SURFs from oblique aerial imagery, enhancing both the predicted bounding box and the segmented binary mask. First, we design a dense anchor ratio with an IoU-balanced sampling strategy (DASS) for proposal generation by statistical analysis to improve the predicted bounding box. The proposed sampling strategy can better cover the shape of slender proposals and alleviate the imbalance problem between the target objects and background. Regarding the typical instance segmentation architectures, the binary mask is segmented coarsely due to the downsampling operations. Second, we propose balanced fine-grained features (BFGF) merged into the instance segmentation process via a three-stage architecture, effectively improving the detector’s performance. Specifically, before feature incorporation, the multi-level feature pyramid is refined by rescaling and integrating to obtain balanced features. Moreover, to evaluate the proposed approaches, we contribute an Urban Road Facilities Dataset for our task, URFD, which contains 1075 images and 1378 instances labeled manually and enriches the open resource dataset. By comparative experiments, the proposed method performs superiority in SURF instance segmentation, obtaining an mAP of 0.888 of the predicted bounding box and an mAP of 0.876 of the segmented binary mask.

Developing dynamic organic ultralong roomtemperature phosphorescence (URTP) remains challenging due to the difficulty in manipulating aggregate structures. Herein, the authors report a dish-like molecular architecture featuring guest responsive dynamic URTP.

Abstract Silicate and oxide glasses are often chemically doped with a variety of cations to tune for desirable properties in technological applications, but their performances are often limited by relatively lower mechanical and elastic properties. Finding a new route to synthesize silica-based glasses with high elastic and mechanical properties needs to be explored. Here, we report a dense SiO2-glass with ultra-high elastic moduli using sound velocity measurements by Brillouin scattering up to 72 GPa at 300 K. High-temperature measurements were performed up to 63 GPa at 750 K and 59 GPa at 1000 K. Compared to compression at 300 K, elevated temperature helps compressed SiO2-glass effectively overcome the kinetic barrier to undergo permanent densification with enhanced coordination number and connectivity. This hot compressed SiO2-glass exhibits a substantially high bulk modulus of 361–429 GPa which is at least 2–3 times greater than the metallic, oxide, and silicate glasses at ambient conditions. Its Poisson’s ratio, an indicator for the packing efficiency, is comparable to the metallic glasses. Even after temperature quench and decompression to ambient conditions, the SiO2-glass retains some of its unique properties at compression and possesses a Poisson’s ratio of 0.248(11). In addition to chemical alternatives in glass syntheses, coupled compression and heating treatments can be an effective means to enhance mechanical and elastic properties in high-performance glasses.

Aerial photogrammetric three-dimensional (3D) city models provide photorealistic virtual scenes for various applications, such as urban planning, autonomous driving, emergency management, etc. With the rapid progress of urbanization, glass façades commonly exist on buildings, which cannot be well reconstructed with geometric deformation and distortion due to the limitation of the image-based Multi-View Stereo (MVS) modeling pipeline. The distorted glass façades make building models visually unreal and messy. This paper proposes a workflow to segment and repair glass façades in aerial photogrammetric 3D building models with multiple constraints to resolve the problem, mainly including two aspects: 1) projection-based glass façade segmentation with geometric information and multi-view constraints, and 2) glass façade model repair via mesh smoothing and texture mapping. First, an efficient approach for façade information extraction is proposed, which utilizes the density of the reprojected point clouds and elevation differences because the typical structure of building façades is usually vertically aligned to the ground surface. Second, we project the façade mesh onto the multi-view oblique aerial images. The glass façades are predicted by a deep learning-based semantic segmentation method to distinguish the glass façades. Finally, based on the extracted glass façades, we remedy the geometric deformation using a mesh denoising method by grouping strategy with edge constraints. After smoothing the mesh structure of glass façades, we remap the texture to generate the completed 3D models with optimized glass façades. Our method leverages multiple constraints, including multi-view constraints, façade structure constraints, grouping strategy, and boundary constraints. The multi-view and façade structure constraints help decrease the adverse effects caused by false segmentation; the grouping strategy and boundary constraints can avoid disorders in some specific areas and preserve the sharp feature in the adjacent regions. Thus, our approach is robust and does not worsen the 3D model. Experiments demonstrate that our workflow is feasible for glass façade segmentation and repair for aerial photogrammetric 3D building models.

Epoxy resin (EP), as a kind of dielectric polymer, exhibits the advantages of low-curing shrinkage, high-insulating properties, and good thermal/chemical stability, which is widely used in electronic and electrical industry. However, the complicated preparation process of EP has limited their practical applications for energy storage. In this manuscript, bisphenol F epoxy resin (EPF) was successfully fabricated into polymer films with a thickness of 10~15 μm by a facile hot−pressing method. It was found that the curing degree of EPF was significantly affected by changing the ratio of EP monomer/curing agent, which led to the improvement in breakdown strength and energy storage performance. In particular, a high discharged energy density (Ud) of 6.5 J·cm−3 and efficiency (η) of 86% under an electric field of 600 MV·m−1 were obtained for the EPF film with an EP monomer/curing agent ratio of 1:1.5 by hot pressing at 130 °C, which indicates that the hot−pressing method could be facilely employed to produce high−quality EP films with excellent energy storage performance for pulse power capacitors.

By combining ambient noise interferometry with mineral physics modeling, this work sheds new light on mantle transition zone physics. Their findings provide new evidence of segregated oceanic crust subducted and trapped within the mantle transition zone, implying complex mantle circulation modes.

Rotating blade is one of the most important components for turbomachinery. Blade crack is one of the most common and dangerous failure modes for rotating blade. Therefore, the fault mechanism and feature extraction of blade crack are vital for the safety assurance of turbomachinery. This study is aimed at the nonlinear dynamic model of rotating blade with transverse crack and the prior feature extraction of blade crack faults based on the vibration responses. First and foremost, a high-fidelity breathing crack model (HFBCM) for rotating blade is proposed on the basis of criterion for stress states at crack section. Since HFBCM is physically deduced from the perspective of energy dissipation and the coupling between centrifugal stress and bending stress is considered, the physical interpretability and the accuracy of the crack model are enhanced comparing with conventional models. The validity of the proposed HFBCM is verified through the comparison study among HFBCM, conventional crack models, and finite element-based contact crack model (FECCM). It is suggested that HFBCM behaves best among the analytical models and matches well with FECCM. With the proposed HFBCM, the nonlinear vibration responses are investigated, and four types of blade crack detection indicators for rotating blade and their quantification method are presented. The numerical study manifests that all these indicators can well characterize the occurrence and severity of crack faults for rotating blade. It is indicated that these indicators can serve as the crack-monitoring indexes.

Flexible hydrogen-bonded organic frameworks (FHOFs) are challenging in fabrication but promising materials for applications in separation and sensing. Here, the authors report a stimuli responsive and flexible HOF which can adapt to different guests by regulating the molecular conformation.

This paper proposes a 3D wireless charging cylinder with improved compensation topology to generate a stable rotating magnetic field for charging multiple loads around it. The induced voltage of each receiver is kept constant against load variations when the distance between the transmitter and the receiver is fixed. The 3D charging cylinder has a simple configuration with two perpendicular LCL-compensated transmitter coils driven by separate power inverters sharing a common dc source. The system is fully analyzed with the maximum load limit determined, and design guidance is provided. Both theoretical and experimental results demonstrate that the transmitter currents remain constant against load variations when the total load is within the maximum load limit, and the transfer efficiency is increased with the increase of the total reflected impedance. Compared to the conventional series-series (SS) compensated WPT system, the proposed 3D configuration can maintain the transmitter currents to be constant within the maximum load limit so that multiple loads can be added without affecting each other. It has found that the transmitter currents of the proposed configuration are kept constant at their initial values when four loads with the resistance of 0.5Ω each are randomly placed at 21 cm from the center of the charging cylinder. By contrast, the transmitter currents of the SS compensated WPT system are obviously changed together with the load voltages.

Although great success has been achieved in instance segmentation, accurate segmentation of instances remains difficult, especially at object edges. This problem is more prominent for instance segmentation in remote sensing imagery due to the diverse scales, variable illumination, smaller objects, and complex backgrounds. We find that most current instance segmentation networks do not consider the segmentation difficulty of different instances and different regions within the instance. In this paper, we study this problem and propose an ensemble method to segment instances from remote sensing images, considering the enhancement of hard-to-segment instances and instance edges. First, we apply a pixel-level Dice metric that reliably describes the segmentation quality of each instance to achieve online hard instance learning. Instances with low Dice values are studied with emphasis. Second, we generate a penalty map based on the analysis of boundary shapes to not only enhance the edges of objects but also discriminatively strengthen the edges of different shapes. That is, different areas of an object, such as internal areas, flat edges, and sharp edges, are distinguished and discriminatively weighed. Finally, the hard-to-segment instance learning and the shape-penalty map are integrated for precise instance segmentation. To evaluate the effectiveness and generalization ability of the proposed method, we train with the classic instance segmentation network Mask R-CNN and conduct experiments on two different types of remote sensing datasets: the iSAID-Reduce100 and the JKGW_WHU datasets, which have extremely different feature distributions and spatial resolutions. The comprehensive experimental results show that the proposed method improved the segmentation results by 2.78% and 1.77% in mask AP on the iSAID-Reduce100 and JKGW_WHU datasets, respectively. We also test other state-of-the-art (SOTA) methods that focus on inaccurate edges. Experiments demonstrate that our method outperforms these methods.

The effect of the ZrO2 crystal form on surface-enhanced Raman scattering (SERS) activity was studied. The ratio of the tetragonal (T) and monoclinic (M) phases of ZrO2 nanoparticles (ZrO2 NPs) was controlled by regulating the ratio of two types of additives in the hydrothermal synthesis method. The SERS intensity of 4-mercaptobenzoic acid (4–MBA) was gradually enhanced by changing the M and T phase ratio in ZrO2 NPs. The degree of charge transfer (CT) in the enhanced 4–MBA molecule was greater than 0.5, indicating that CT was the main contributor to SERS. The intensity of SERS was strongest when the ratio of the T crystal phase in ZrO2 was 99.7%, and the enhancement factor reached 2.21 × 104. More importantly, the proposed study indicated that the T and M phases of the ZrO2 NPs affected the SERS enhancement. This study provides a new approach for developing high-quality SERS substrates and improving the transmission efficiency of molecular sensors.

With the progress of photogrammetry and computer vision technology, three-dimensional (3D) reconstruction using aerial oblique images has been widely applied in urban modelling and smart city applications. However, state-of-the-art image-based automatic 3D reconstruction methods cannot effectively handle the unavoidable geometric deformation and incorrect texture mapping problems caused by moving cars in a city. This paper proposes a method to address this situation and prevent the influence of moving cars on 3D modelling by recognizing moving cars and combining the recognition results with a photogrammetric 3D modelling procedure. Through car detection using a deep learning method and multiview geometry constraints, we can analyse the state of a car’s movement and apply a proper preprocessing method to the geometrically model generation and texture mapping steps of 3D reconstruction pipelines. First, we apply the traditional Mask R-CNN object detection method to detect cars from oblique images. Then, a detected car and its corresponding image patch calculated by the geometry constraints in the other view images are used to identify the moving state of the car. Finally, the geometry and texture information corresponding to the moving car will be processed according to its moving state. Experiments on three different urban datasets demonstrate that the proposed method is effective in recognizing and removing moving cars and can repair the geometric deformation and error texture mapping problems caused by moving cars. In addition, the methods proposed in this paper can be applied to eliminate other moving objects in 3D modelling applications.

The source of the anisotropic layer (D'' layer) at the bottom of the lower mantle remains unclear. Here, using high pressure and temperature experiments, the authors find that seismic anisotropy observed at the D'' layer is caused by 50% deformation of the minerals post-perovskite and ferropericlase.

Direct observation of the surface-enhanced Raman scattering (SERS) of molecules adsorbed on nano-sized zirconia (ZrO2) substrates was first reported without the need for the addition of metal particles. It was found that ZrO2 nanoparticles can exhibit unprecedented Raman signal enhancements on the order of 103 for the probe molecule 4-mercaptobenzoic acid (4-MBA). The dramatic effect of the calcination temperature on the ZrO2 nanoparticles was also investigated. The ZrO2 nanoparticles with the particle diameter of 10.5 nm, which were prepared by calcination at a temperature of 500°C, have the highest SERS activity. A comparison between the experimental and calculation results indicates that charge transfer (CT) effects dominate the surface enhancement. The plentiful surface state of ZrO2 active substrate that is beneficial to CT resonance occurs between molecules and ZrO2 to produce a SERS effect. The CT process depends, to a large extent, on the intrinsic properties of the modifying molecules and the surface properties of the ZrO2. This is a new SERS phenomenon for ZrO2 that will expand the application of ZrO2 to microanalysis and is beneficial for studying the basic properties of both ZrO2 and SERS.

The present study aimed to explore the effects of psychological needs on the relationship of peer victimization and anxiety. Methods: A sample of 889 4th, 5th and 6th primary school students in Guangxi Zhuang Autonomous Region were recruited with the measurement of Peer victimization Questionnaire, Psychological needs Scale and Anxiety Scale (SAS). Results showed that: (1) There were no significant gender and grade differences with respect to Peer victimization; (2) Significant negative correlations were found between all types of peer victimization and the subscales of psychological needs. In addition, significant positive correlations were found between all types of peer victimizationand, anxiety and significant negative correlations between all the subscales of psychological needs and anxiety; (3) Psychological needs partially mediated the relationship between Peer victimizationexperience and anxiety.

Surface-enhanced Raman scattering (SERS) is a powerful tool in charge transfer (CT) process research. By analyzing the relative intensity of the characteristic bands in the bridging molecules, one can obtain detailed information about the CT between two materials. Herein, we synthesized a series of Au nanorods (NRs) with different length-to-diameter ratios (L/Ds) and used these Au NRs to prepare a series of core–shell structures with the same Cu2O thicknesses to form Au NR–4-mercaptobenzoic acid (MBA)@Cu2O core–shell structures. Surface plasmon resonance (SPR) absorption bands were adjusted by tuning the L/Ds of Au NR cores in these assemblies. SERS spectra of the core-shell structure were obtained under 633 and 785 nm laser excitations, and on the basis of the differences in the relative band strengths of these SERS spectra detected with the as-synthesized assemblies, we calculated the CT degree of the core–shell structure. We explored whether the Cu2O conduction band and valence band position and the SPR absorption band position together affect the CT process in the core–shell structure. In this work, we found that the specific surface area of the Au NRs could influence the CT process in Au NR–MBA@Cu2O core–shell structures, which has rarely been discussed before.

Automated damage evaluation is of great importance in the maintenance and preservation of heritage structures. Damage investigation of large cultural buildings is time-consuming and labor-intensive, meaning that many buildings are not repaired in a timely manner. Additionally, some buildings in harsh environments are impossible to reach, increasing the difficulty of damage investigation. Oblique images facilitate damage detection in large buildings, yet quantitative damage information, such as area or volume, is difficult to generate. In this paper, we propose a method for quantitative damage evaluation of large heritage buildings in wild areas with repetitive structures based on drone images. Unlike existing methods that focus on building surfaces, we study the damage of building components and extract hidden linear symmetry information, which is useful for localizing missing parts in architectural restoration. First, we reconstruct a 3D mesh model based on the photogrammetric method using high-resolution oblique images captured by drone. Second, we extract 3D objects by applying advanced deep learning methods to the images and projecting the 2D object segmentation results to 3D mesh models. For accurate 2D object extraction, we propose an edge-enhanced method to improve the segmentation accuracy of object edges. 3D object fragments from multiple views are integrated to build complete individual objects according to the geometric features. Third, the damage condition of objects is estimated in 3D space by calculating the volume reduction. To obtain the damage condition of an entire building, we define the damage degree in three levels: no or slight damage, moderate damage and severe damage, and then collect statistics on the number of damaged objects at each level. Finally, through an analysis of the building structure, we extract the linear symmetry surface from the remaining damaged objects and use the symmetry surface to localize the positions of missing objects. This procedure was tested and validated in a case study (the Jiankou Great Wall in China). The experimental results show that in terms of segmentation accuracy, our method obtains results of 93.23% mAP and 84.21% mIoU on oblique images and 72.45% mIoU on the 3D mesh model. Moreover, the proposed method shows effectiveness in performing damage assessment of objects and missing part localization.

Oblique photogrammetry-based three-dimensional (3D) urban models are widely used for smart cities. In 3D urban models, road signs are small but provide valuable information for navigation. However, due to the problems of sliced shape features, blurred texture and high incline angles, road signs cannot be fully reconstructed in oblique photogrammetry, even with state-of-the-art algorithms. The poor reconstruction of road signs commonly leads to less informative guidance and unsatisfactory visual appearance. In this paper, we present a pipeline for embedding road sign models based on deep convolutional neural networks (CNNs). First, we present an end-to-end balanced-learning framework for small object detection that takes advantage of the region-based CNN and a data synthesis strategy. Second, under the geometric constraints placed by the bounding boxes, we use the scale-invariant feature transform (SIFT) to extract the corresponding points on the road signs. Third, we obtain the coarse location of a single road sign by triangulating the corresponding points and refine the location via outlier removal. Least-squares fitting is then applied to the refined point cloud to fit a plane for orientation prediction. Finally, we replace the road signs with computer-aided design models in the 3D urban scene with the predicted location and orientation. The experimental results show that the proposed method achieves a high mAP in road sign detection and produces visually plausible embedded results, which demonstrates its effectiveness for road sign modeling in oblique photogrammetry-based 3D scene reconstruction.

The construction of bridges and other structures across the river will affect the flood discharge capacity and local water potential of the river.Based on navier-Stokes equation of MIKE21FM hydrodynamic module, this paper carries out two-dimensional numerical simulation of part of Shixi River. By optimizing the grid near the piers to reduce the difference brought by the terrain generalized grid of the real river, it simulates and analyzes the length of the curve of yong-high and Yong-water under different flood frequencies,the Nash-Sutcliffe efficiency coefficient and relative error analysis are used to verify the rationality of the results. The simulation results can accurately reflect the real changes of river water level, It provides a theoretical basis for flood impact analysis.

TiO2 nanotube arrays (TNAs) with tube lengths of 4, 6, and 7 μm were prepared via two-step anodization. Thereafter, ultraviolet (UV) photodetectors (PDs) with Au/TiO2/Au structures were prepared using these TNAs with different tube lengths. The effects of TNA length and device area on the performance of the device were investigated using in situ Raman spectroscopy. The maximum laser/dark current ratio was achieved by using a TNA with a size of 1 × 1 cm2 and a length of 7 μm, under a 532 nm laser. In addition, when the device was irradiated with a higher energy laser (325 nm), the UV Raman spectrum was found to be more sensitive than the visible Raman spectrum. At 325 nm, the laser/dark current ratio was nearly 24 times higher than that under a 532 nm laser. Six phonon modes of anatase TNAs were observed, at 144, 199, 395, 514, and 635 cm−1, which were assigned to the Eg(1), Eg(2), B1g(1), A1g/B1g(2), and Eg(3) modes, respectively. The strong low-frequency band at 144 cm−1 was caused by the O-Ti-O bending vibration and is a characteristic band of anatase. The results show that the performance of TNA-based PDs is length-dependent. Surface-enhanced Raman scattering signals of 4-mercaptobenzoic acid (4-MBA) molecules were also observed on the TNA surface. This result indicates that the length-dependent performance may be derived from an increase in the specific surface area of the TNA. In addition, the strong absorption of UV light by the TNAs caused a blueshift of the Eg(1) mode.

Quantitative analysis of formaldehyde (HCHO, FA), especially at low levels, in various environmental media is of great importance for assessing related environmental and human health risks. A highly efficient and convenient FA detection method based on surface-enhanced Raman spectroscopy (SERS) technology has been developed. This SERS-based method employs a reusable and soft silver-coated TiO2 nanotube array (TNA) material, such as an SERS substrate, which can be used as both a sensing platform and a degradation platform. The Ag-coated TNA exhibits superior detection sensitivity with high reproducibility and stability compared with other SERS substrates. The detection of FA is achieved using the well-known redox reaction of FA with 4-amino-3-hydrazino-5-mercapto-1,2,4-triazole (AHMT) at room temperature. The limit of detection (LOD) for FA is 1.21 × 10−7 M. In addition, the stable catalytic performance of the array allows the degradation and cleaning of the AHMT-FA products adsorbed on the array surface under ultraviolet irradiation, making this material recyclable. This SERS platform displays a real-time monitoring platform that combines the detection and degradation of FA.

In this study, ZrO2 and Zn−ZrO2 nanoparticles (NPs) with a series of Zn ion doping amounts were synthesized by the sol-gel process and utilized as substrates for surface-enhanced Raman scattering (SERS). After absorbing the probing molecule 4−mercaptobenzoic acid, the SERS signal intensities of Zn−ZrO2 NPs were all greater than that of the pure ZrO2. The 1% Zn doping concentration ZrO2 NPs exhibited the highest SERS enhancement, with an enhancement factor (EF) value of up to 104. X-ray diffraction, X-ray photoelectron spectroscopy, Ultraviolet (UV) photoelectron spectrometer, UV−vis spectroscopy, Transmission Electron Microscope (TEM), and Raman spectroscopy were used to characterize the properties of Zn−ZrO2 NPs and explore the mechanisms behind the SERS phenomenon. The charge transfer (CT) process is considered to be responsible for the SERS performance of 4−MBA adsorbed on Zn−ZrO2. The results of this study demonstrate that an appropriate doping ratio of Zn ions can promote the charge transfer process between ZrO2 NPs and probe molecules and significantly improve the SERS properties of ZrO2 substrates.

Abstract Background Overexpression of DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is commonly occurred in cancers and causes radioresistance and poor prognosis. In present study, the single-chain variable antibody fragments (scFv) targeting DNA-PKcs was developed for the application of radiosensitization in vitro and in vivo. A humanized semisynthetic scFv library and the phage-display antibodies technology were employed to screen DNA-PKcs scFv antibody. Methods DNA-PKcs epitopes were predicted and cloned. A humanized semisynthetic scFv library and the phage-display antibodies technology were employed to screen DNA-PKcs scFv antibody. DNA damage repair was analyzed by comet assay and immunofluorescence detection of γH2AX foci. The radiosensitization in vivo was determined on Balb/c athymic mice transplanted tumours of HeLa cells. Results Four epitopes of DNA-PKcs have been predicted and expressed as the antigens, and a specific human anti-DNA-PKcs scFv antibody gene, anti-DPK3-scFv, was obtained by screening the phage antibody library using the DNA-PKcs peptide DPK3. The specificity of anti-DPK3-scFv was verified, in vitro. Transfection of HeLa cells with the anti-DPK3-scFv gene resulted in an increased sensitivity to IR, decreased repair capability of DNA double-strand breaks (DSB) detected by comet assay and immunofluorescence detection of γH2AX foci. Moreover, the kinase activity of DNA-PKcs was inhibited by anti-DPK3-scFv, which was displayed by the decreased phosphorylation levels of its target Akt/S473 and the autophosphorylation of DNA-PKcs on S2056 induced by radiation. Measurement of the growth and apoptosis rates showed that anti-DPK3-scFv enhanced the sensitivity of tumours transplanted in Balb/c athymic mice to radiation therapy. Conclusion The antiproliferation and radiosensitizing effects of anti-DPK3-scFv via targeting DNA-PKcs make it very appealing for the development as a novel biological radiosensitizer for cancer therapeutic potential.