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Accurate and efficient ship tracking by geosynchronous orbit (GEO) satellites holds great significance for large-scale maritime surveillance. Nevertheless, ship tracking continues to grapple with a multitude of challenges as follows: 1) the targets are small and often obscured by cloud interference, leading to weakened features; 2) the contrasts between the ships and the background are relatively low, complicating the identification and tracking process; and 3) the frame-to-frame relative positioning accuracy is poor, posing difficulties in reflecting the actual movement trends of ships. In response to these challenges, we proposed TS-Track, a novel framework employing multilevel supervision paradigm to improve tracking performance. Initially, this framework restructured the tracking task into three key sub-modules: image enhancement, object tracking, and trajectory adjustment, inherently fostering a unified training protocol that naturally encompasses all components. Subsequently, a trajectory-based frame fusion strategy was proposed, utilizing consecutive three-frame images to enhance target features and produce consistent motion feature patterns; Last but not least, a trajectory adjustment network was developed to correct the position of ships during tracking, resulting in stable tracking trajectories, and reproduce the actual movement trends of ships. The experimental results on GaoFen-4 dataset validated that our method delivered a significant improvement in ship tracking and achieved state-of-the-art (SOTA) performance. Source codes are available at https://github.com/KTqizhi/KTqizhi.github.io.

Spectral library-based spectral super-resolution is an effective but challenging way to obtain high-spatial hyperspectral images (HSIs) from high-spatial multispectral images (MSIs). However, the incomplete spectral coverage of spectral response functions (SRFs) makes it impossible to comprehensively sense the spectral information in the imaging model, thus greatly limits the performance of spectral super-resolution. To deal with this problem, a new spectral library-based spectral super-resolution method under incomplete spectral coverage conditions is proposed in this article. More specifically, a strategy for acquiring a typical set of spectra from the spectral library is proposed, trying to provide spectral observations under incomplete spectral coverage conditions. Second, taking the typical set of spectra and the remaining spectral library as a priori, a new spectral super-resolution model is established under sparse and low-rank constraints. And then, the spectral dictionary is optimized utilizing the spectral information supplied by the prior spectral library. Finally, its corresponding coefficient matrix is optimized using the spatial information supplied by the MSI and the spectral similarity constraint on the typical spectra. Experimental results using different datasets with different SRFs show that our proposed method outperforms other relative state-of-the-art methods in terms of both spectral reconstruction and spatial preservations.

Spectral library-based spectral super-resolution from high-spatial multispectral (MS) to hyperspectral (HS) image is one of the most efficient ways to obtain high-spatial HS satellite images, which can be used in various applications. Although most of the published universal spectral libraries can really provide reliable spectral information of the common ground objects, poor region specificity of the universal spectral libraries may limit the accuracy of spectral super-resolution and thus the subsequent applications. To address the above issue, this article proposes a new spectral super-resolution method for high-spatial MS satellite images by using the universal and private jointed spectral library. Specifically, a private spectral library consisting of the spectra of interested ground objects is introduced to the universal spectral library, to form a new joint spectral library, and a new spectral super-resolution model by using the joint spectral library is constructed. Then, band matching between the desired high-spatial HS image and the joint spectral library will be carried out, to map the joint spectral library into a specific spectral library. After that, contributions of the two universal and private spectral dictionaries will be well balanced by a weighting factor under the sparse representation framework. And finally, the spectral dictionary and its related coefficients will be optimized by the alternating direction method of multipliers (ADMMs). Comparison results with the relative state-of-the-art methods have shown the superiority of this proposed method, and two typical applications of the tobacco and wheat classification will also be given to evaluate its effectiveness in practical applications.

Hollow nanomaterials have attracted significant interest. However, developing an effective growth mechanism for synthesizing seed-like hollow nanoparticles (SHNPs) with tailored structures still remains challenging. In this study, we developed a dynamic interfacial-tension-controlled polar growth strategy to synthesize SHNPs with a narrow size distribution using a metal–organic coordination compound. The synthesis was performed in an oil-in-water emulsion system comprising disulfiram (DSF) oil nanodroplets and cis-dichlorodiamine platinum(II) (Cpt) aqueous phases. The DSF nanodroplets exhibited dynamic interfacial tension owing to the gradual consumption of DSF molecules, resulting in the polar growth of DSF nanodroplets from a spherical to anisotropic seed-like morphology. This method produced seed-like hollow nanostructures with tailored morphologies, such as pomegranate, peanut, bean sprout, and pistachio structures and desired lengths. Additionally, we constructed a seed-like nanomotor by loading small platinum (Pt) nanoparticles onto the surface of SHNPs, which exhibit an enhanced diffusion coefficient and exceptional oriented movement in response to the hydrogen peroxide (H2O2) fuel.

Patch-based spatial dictionary has been widely used to fuse a high-resolution panchromatic (PAN) image with a low-resolution multispectral (LMS) image under the framework of sparse representation (SR). However, patch-based dictionary in the spatial domain is not sufficient to preserve spectral information, which may lead to large spectral distortion. To solve this problem, a new spectral dictionary-based pansharpening method using subpixel-shift decomposition and joint optimization (termed PANDA) is proposed. In this method, the model of pansharpening is formulated in a decomposed spectral domain under the sparse and low-rank constraint, as a joint optimization procedure of the spectral dictionary and its coefficients. Specifically, a subpixel- shift decomposition is first constructed, to decompose the PAN image into a series of subimages with the same spatial resolution as the LMS image. Then, a new imaging model for the pansharpening problem of the LMS image and the decomposed PAN subimages is formulated, with sparse and low-rank constraints. And finally, a joint optimization procedure for the spectral dictionary and its coefficients are theoretically derived, using the spectral information provided by the LMS image and the spatial information provided by the entire PAN subimages, respectively. Experimental results on different datasets show that the pansharpening performance of the proposed PANDA method outperforms the state-of-the-art methods in both spatial and spectral domains.

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In a pancreatic tumor microenvironment, activated pancreatic stellate cells (PSCs) produce extracellular matrix (ECM) to form a barrier to drug penetration. Moreover, the interaction between cancer cells and activated PSCs promotes the tumor growth. Vitamin D receptor (VDR), as a key regulator to promote the recovery of PSCs to the resting state, is an attractive therapeutic target for pancreatic cancer. Herein, we reported the design and synthesis of 57 nonsecosteroidal VDR modulators based on the skeleton of phenyl-pyrrolyl pentane. Among them, compounds C4, I5, and I8exhibited excellent VDR affinity and effective inhibition of the activation of PSCs, as well as potent suppression of the interaction between cancer cells and PSCs in vitro. In vivo, compound I5combined with gemcitabine achieved efficacious antitumor activity without causing hypercalcemia. In conclusion, the compounds designed in our study can remodel the tumor microenvironment and are expected to be candidates for the treatment of pancreatic cancer.

Intraocular pressure (IOP) is the prime indicator for the diagnosis and treatment of glaucoma. IOP has circadian rhythm changes and is dependent on body gestures; therefore, a single measurement in the clinic can be misleading for diagnosis. Herein, few-layer graphene is utilized to develop non-invasive sensors with high transparency, sensitivity, linearity, and biocompatibility for 24 h continuous IOP monitoring. The graphene Wheatstone bridge consisting of two strain gauges and two compensating resistors is designed to improve the sensitivity and accuracy of IOP measurement. Testing results on a silicone eyeball indicate that the output voltage of the sensor is proportional to the IOP fluctuation. Under the various ranges and speeds of IOP fluctuation, the sensor exhibits excellent performance of dynamic cycles and step responses with an average sensitivity of 150 μV/mmHg. With the linear relationship, the average relative error between the calibrated IOP and the standard pressure is maintained at about 5%. More than 100 cycles and interval time measurements illustrate that the sensor possesses significant stability, durability, and reliability. Furthermore, a wireless system is designed for the sensor to realize IOP monitoring using a mobile phone. This sensor, with the average transparency of 85% and its ease of fabrication, as well as its portability for continuous IOP monitoring, brings new promise to the diagnosis and treatment of glaucoma.

A series of trimetallic Pt–Sn–Ce catalysts supported on chloride Al2O3was prepared by a sequential impregnation method and applied for n-heptane reforming and characterized by several techniques, including N2physiosorption, transmission electron microscopy, X-ray diffraction, hydrogen temperature-programmed reduction, CO chemisorption, ammonia temperature-programmed desorption, pyridine desorption Fourier-transform infrared spectroscopy, and in situ diffuse reflectance infrared Fourier transform spectroscopy. We have demonstrated that the introduction of Ce can promote isomerization reactions by suppressing undesirable hydrogenolysis reactions, whereas it does not significantly influence the dehydrocyclization reactions. The characterization results show that CeOxcan enhance the reducibility of Pt species via enhancing the Pt dispersion. In addition, Ce increases the proportion of medium-strength acid sites, which does not only promote isomerization activity, but also suppresses the undesirable reactions such as hydrogenolysis and cracking.

Recently, flexible and wearable mechanical sensors have attracted great attention because of their potential applications in monitoring various physiological signals. However, conventional mechanical sensors rarely have both pressure and strain sensing abilities that can meet the demands of both subtle and large human motion detection. Besides, the mechanical sensors with tunable sensitivity or measuring range are also essential for their practical applications. Herein, the graphene ink dip-coating method with merits of time saving, low cost, and large scale was used to fabricate the foam-structured graphene sensors with both pressure and strain sensing performance. Because of high elasticity of styrene butadiene rubber (SBR) substrates and stacked graphene flakes, the tunable mechanical sensors exhibit a high gauge factor (GF) and large measuring range for specific human motion detection. The pressure sensor shows a GF of 2.02 kPa–1with a pressure range up to 172 kPa, and the strain sensor displays a GF of 250 with a strain range up to 86%. On the one hand, various detections of subtle vital signals with small strain change were demonstrated by the pressure sensor because of its flexibility and high sensitivity. On another hand, the strain sensor with large strain change shows excellent ability to detect various large human motions including the bending of neck, finger, wrist, and knee. Interestingly, both the pressure sensor and strain sensor exhibit great capability for recognizing 26 letters written by hand. The working mechanism based on the contact area variation was also investigated by the morphology evolution and resistance model. We suppose that the foam-structured graphene mechanical sensors would be promising in wearable electronics for human healthcare and activity monitoring in the future.

To obtain accurate finite-element (FE) models for structural health monitoring (SHM), effective modeling techniques are essential. This paper presents the process for establishing a 131-m large transmission tower’s SHM-oriented FE model. Incorporated procedures are appropriate modeling, manual tuning, model updating, and model validation. Through these works, a detailed realistic model that can reproduce all the experimental dynamic characteristics is obtained, and important conclusions about establishing SHM-oriented FE models for large steel pylon structures can be drawn accordingly: (1) it is necessary to model all the bar members using beam or truss elements of equivalent cross sections for local structural behavior exploration; (2) some components (e.g., ladders, steel plates, and rivets) are no influence on the structural overall stiffness, but their contributions to mass cannot be ignored in modeling; (3) the response surface (RS)-based FE model updating method is effective for complicated pylon models; (4) manual tunings are needed to ensure the quality of model updating.

In this work, the presence of ascorbic acid (AsA) in MIL-88B(Fe)/H2O2system was demonstrated to significantly increase the sulfamethoxazole (SMX) degradation efficiency. The SMX degradation rate in AsA/MIL-88B(Fe)/H2O2system was 0.177L/(mg∙min), which was 60 times that of the MIL-88B(Fe)/H2O2system. Moreover, the study shows that AsA not only promotes SMX degradation in Fenton-like systems but also expands its pH application range. The effect of coexisting anions on the catalytic performance of the AsA/MIL-88B(Fe)/H2O2system was also investigated. Then, reactive species were detected via quenching experiments, which indicated •OH as the dominant free radical contributing to SMX degradation. Meanwhile, ESR determinations confirmed the existence of •OH and O2−• in AsA/MIL-88B(Fe)/H2O2system. The high activity of the AsA/MIL-88B(Fe)/H2O2system was attributed to the effective surface Fe(III)/Fe(II) cycle promoted by AsA, and a possible mechanism of the AsA/MIL-88B(Fe)/H2O2system is proposed. The possible pathways for SMX and AsA degradation in the AsA/MIL-88B(Fe)/H2O2system are proposed based on the identified intermediates and the ecotoxicity analysis was conducted by ECOSAR. Finally, experimental results using the actual surface water and groundwater revealed the excellent availability of AsA/MIL-88B(Fe)/H2O2system in remediating SMX contaminated water. This study presents a novel, efficient Fenton-like system using AsA and iron-based metal-organic frameworks for sulfonamide removal from water.