In this review, we focus on the types of smart supramolecular gels whose self-assembly processes are affected or even triggered by physical forces including sonication and mechanical stress ...(mechanical force). The types of gels that are responsive to sonication and mechanical stress are examined and summarised. The gels exhibit non-covalent interactions among the gelator molecules and show dynamic and reversible properties controlled by the stimuli. Upon stimulation, the gelators cause instant and
in situ
gelation of organic solvents or water with different modes and outcomes of self-assembly. On the other hand, sonication and mechanical stress, as external factors, can give rise to dynamic changes in microscopic morphology, optical properties,
etc.
Certain thixotropic supramolecular gels exhibit perfect self-healing characteristics. The driving forces and the mechanism of the self-assembly process and the responsive outcome of morphological and spectroscopic changes are discussed. Those supramolecular gels responding to sonication and mechanical stress offer a wide range of applications in fields such as smart and adaptive materials, switches, drug control and release, and tissue engineering.
Ultrasound and mechanical stress-driven/-responsive LMOGs, which are used extensively to construct self-healing materials with reversibility, are highlighted.
Photosynthesis is a process wherein the chromophores in plants and bacteria absorb light and convert it into chemical energy. To mimic this process, an emissive poly(ethylene glycol)‐decorated ...tetragonal prismatic platinum(II) cage was prepared and used as the donor molecule to construct a light‐harvesting system in water. Eosin Y was chosen as the acceptor because of its good spectral overlap with that of the metallacage, which is essential for the preparation of light‐harvesting systems. Such a combination showed enhanced catalytic activity in catalyzing the cross‐coupling hydrogen evolution reaction, as compared with eosin Y alone. This study offers a pathway for using the output energy from the light‐harvesting system to mimic the whole photosynthetic process.
Harvest lights: An aqueous light‐harvesting system, based on a platinum(II) cage and eosin Y, demonstrates efficient energy transfer. The system showed improved photocatalytic activity in a cross‐coupling hydrogen evolution reaction compared with the reaction employing just eosin Y alone.
This study aimed to analyze spatio-temporal changes in habitat quality in Guizhou Province during the 1990-2018 period and identify factors influencing habitat quality. Land-use data for the period ...were used to evaluate spatio-temporal variations in habitat quality using the InVEST model, and factors influencing habitat quality were analyzed using GeoDetector. According to the results, cultivated land and forestland decreased by 0.48% and 0.88%, respectively, during the study period. Grassland, water, and construction land areas increased, with construction land increasing the most (0.92%) followed by water area (0.37%). The main land-use changes included conversion of cultivated land to forestland, grassland, and construction land. The average habitat quality index for Guizhou Province changed from 0.633 to 0.627 over the 1990-2018 period, showing an overall downward trend. The distribution pattern of habitat quality was spatially "high in the north, south, and, east, and low in the west". High habitat quality areas were mainly located in the western part of Guizhou Province, whereas low habitat quality areas were located in the central region. Land-use was the major factor influencing the spatio-temporal variations in habitat quality, and the interactive effect between any two factors was stronger than that of a single factor. Natural factors and human factors co-dominated the temporal-spatial changes in habitat quality.
In the field of agricultural information, the automatic identification and diagnosis of maize leaf diseases is highly desired. To improve the identification accuracy of maize leaf diseases and reduce ...the number of network parameters, the improved GoogLeNet and Cifar10 models based on deep learning are proposed for leaf disease recognition in this paper. Two improved models that are used to train and test nine kinds of maize leaf images are obtained by adjusting the parameters, changing the pooling combinations, adding dropout operations and rectified linear unit functions, and reducing the number of classifiers. In addition, the number of parameters of the improved models is significantly smaller than that of the VGG and AlexNet structures. During the recognition of eight kinds of maize leaf diseases, the GoogLeNet model achieves a top - 1 average identification accuracy of 98.9%, and the Cifar10 model achieves an average accuracy of 98.8%. The improved methods are possibly improved the accuracy of maize leaf disease, and reduced the convergence iterations, which can effectively improve the model training and recognition efficiency.
An amphiphilic pillar5arene was made. It could self-assemble to form vesicles and multiwalled microtubes in water. Dynamic light scattering, transmission electron microscopy, scanning electron ...microscopy, atomic force microscopy, and UV–vis and FTIR spectroscopy were employed to characterize its self-assembly process and the resultant assemblies. The vesicles could encapsulate calcein within their interiors under neutral conditions and release it in response to a decrease in pH. The microtubes, which have primary amine groups on their surfaces, could adsorb TNT through donor–acceptor interactions.
Eosinophilic gastrointestinal disorders are a series of diseases that include eosinophilic esophagitis, eosinophilic gastritis, eosinophilic gastroenteritis, eosinophilic enteritis, and eosinophilic ...colitis. Among these disorders, eosinophilic gastroenteritis is an uncommon and heterogeneous disease characterized by eosinophilic infiltration of the gastrointestinal tract in the absence of secondary causes, presenting with a variety of gastrointestinal manifestations. Up to now, epidemiology and pathophysiology of eosinophilic gastroenteritis are still unclear. Based on clinical manifestations and depth of eosinophilic infiltration into the gastrointestinal tract wall, eosinophilic gastroenteritis is classified into three different patterns including predominantly mucosal pattern, predominantly muscular pattern, and predominantly serosal pattern. For diagnosing eosinophilic gastroenteritis, it is necessary for clinicians to have a high degree of clinical suspicion. In addition to the gastrointestinal symptoms, other evidences such as laboratory results, radiological findings and endoscopy can also provide important diagnostic evidences for eosinophilic gastroenteritis. And these indirect pieces of information together with histological results will lead to a definitive diagnosis of eosinophilic gastroenteritis. To avoid specific allergen, dietary treatments can be considered as initial treatment strategy before drug treatment. Corticosteroids are the main medication for eosinophilic gastroenteritis and have a dramatic therapeutic efficacy. Yet other medications need to further verify their effects in clinical practice, and surgery should be avoided as far as possible.
As a newly emerging kind of porous material, covalent organic frameworks (COFs) have drawn much attention because of their fascinating structural features (
e.g.
, divinable structure, adjustable ...porosity and total organic backbone). Since the seminal work of Yaghi and co-workers reported in 2005, the COF materials have shown superior potential in diverse applications, such as gas storage, adsorption, optoelectronics, catalysis,
etc.
Recently, COF materials have shown a new trend in sensing fields. This critical review briefly describes the synthesis routes for COF powders and thin films. What's more, the most fascinating and significant applications of COFs in sensing fields including explosive sensing, humidity sensing, pH detection, biosensing, gas sensing, metal ion sensing, and other substance sensing are summarized and highlighted. Finally, the major challenges and future trends of COFs with respect to their preparation and sensing applications are discussed.
Recent advances in covalent organic frameworks (COFs) as a smart sensing material are summarized and highlighted.
Recently, the light-emitting diode (LED) has been considered as an energy-saving and environment-friendly lighting technology, which is ten times more energy efficient than conventional incandescent ...lights. As an emerging photoelectric material, metal halide perovskites have attracted considerable attention due to their adjustable band gap, high photoluminescence quantum yield and high color purity. In particular, the abundant perovskite raw material can reduce the cost and the production process is simple to speed up the production cycle. With their excellent performance, perovskite LEDs (PeLEDs) will become a strong competitor of inorganic LEDs and organic LEDs in the future. In this perspective, we first analyze the cost of perovskite in terms of materials, manufacturing and overhead. Then, the excellent properties and efficiency of PeLEDs are summarized. Finally, we propose the challenging issues of PeLEDs in terms of long lifetime, highly efficient blue electroluminescence, toxicity and bioavailability of lead.
Perovskite LEDs represent a promising avenue for high efficiency and low-cost devices with excellent properties. The perovskite material's impact on lighting and advanced applications needs to be recognized to allow its entry to next-generation display technology.
Continuous maintenance and real-time update of high-definition (HD) maps is a big challenge. With the development of autonomous driving, more and more vehicles are equipped with a variety of advanced ...sensors and a powerful computing platform. Based on mid-to-high-end sensors including an industry camera, a high-end Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU), and an onboard computing platform, a real-time HD map change detection method for crowdsourcing update is proposed in this paper. First, a mature commercial integrated navigation product is directly used to achieve a self-positioning accuracy of 20 cm on average. Second, an improved network based on BiSeNet is utilized for real-time semantic segmentation. It achieves the result of 83.9% IOU (Intersection over Union) on Nvidia Pegasus at 31 FPS. Third, a visual Simultaneous Localization and Mapping (SLAM) associated with pixel type information is performed to obtain the semantic point cloud data of features such as lane dividers, road markings, and other static objects. Finally, the semantic point cloud data is vectorized after denoising and clustering, and the results are matched with a pre-constructed HD map to confirm map elements that have not changed and generate new elements when appearing. The experiment conducted in Beijing shows that the method proposed is effective for crowdsourcing update of HD maps.
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![An Amphiphilic Pillar[5]are...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/0002-7863/small "An Amphiphilic Pillar[5]arene: Synthesis, Controllable Self-Assembly in Water, and Application in Calcein Release and TNT Adsorption")
