Search

Green-emitting phosphorus-functionalized mesoporous silica (PMPS) nanospheres were fabricated by modifying their surfaces with (8-hydroxyquinoline) zinc (Znq2). A simulated body fluid soaking test and subsequent gas-adsorption measurements revealed that Znq2-modification could dramatically suppress the biodegradation of the nanospheres. This study establishes Znq2 as a novel and potential surface modifier of mesoporous silicas and demonstrates that effective surface design of the hosts will allow the exploitation of potential functionalities of the modifier.

Studies have shown that driver fatigue or unpleasant emotions significantly increase driving risks. Detecting driver emotions and fatigue states and providing timely warnings can effectively minimize the incidence of traffic accidents. However, existing models rarely combine driver emotion and fatigue detection, and there is space to improve the accuracy of recognition. In this paper, we propose a non-invasive and efficient detection method for driver fatigue and emotional state, which is the first time to combine them in the detection of driver state. Firstly, the captured video image sequences are preprocessed, and Dlib (image open source processing library) is used to locate face regions and mark key points; secondly, facial features are extracted, and fatigue indicators, such as driver eye closure time (PERCLOS) and yawn frequency are calculated using the dual-threshold method and fused by mathematical methods; thirdly, an improved lightweight RM-Xception convolutional neural network is introduced to identify the driver’s emotional state; finally, the two indicators are fused based on time series to obtain a comprehensive score for evaluating the driver’s state. The results show that the fatigue detection algorithm proposed in this paper has high accuracy, and the accuracy of the emotion recognition network reaches an accuracy rate of 73.32% on the Fer2013 dataset. The composite score calculated based on time series fusion can comprehensively and accurately reflect the driver state in different environments and make a contribution to future research in the field of assisted safe driving.

Phosphonate-containing mesoporous silica (PMPS) spheres were successfully synthesized using diethyl(2-bromoethyl)phosphonate and non-ionic and cationic surfactants. The spherical PMPS particles with the mesopores were effectively formed under the basic condition through the hydrolysis and condensation reactions of tetraethoxysilane, even though the BET surface area of the particles decreased with increasing the added phosphonate amount. The hollow structures with the mesopores were obtained in the preferential amount of the phosphonate.

Defined by its potential for self-renewal, differentiation and tumorigenicity, cancer stem cells (CSCs) are considered responsible for drug resistance and relapse. To understand the behavior of CSC, the effects of the microenvironment in each tissue are a matter of great concerns for scientists in cancer biology. However, there are many complicated obstacles in the mimicking the microenvironment of CSCs even with current advanced technology. In this context, novel biomaterials have widely been assessed as in vitro platforms for their ability to mimic cancer microenvironment. These efforts should be successful to identify and characterize various CSCs specific in each type of cancer. Therefore, extracellular matrix scaffolds made of biomaterial will modulate the interactions and facilitate the investigation of CSC associated with biological phenomena simplifying the complexity of the microenvironment. In this review, we summarize latest advances in biomaterial scaffolds, which are exploited to mimic CSC microenvironment, and their chemical and biological requirements with discussion. The discussion includes the possible effects on both cells in tumors and microenvironment to propose what the critical factors are in controlling the CSC microenvironment focusing the future investigation. Our insights on their availability in drug screening will also follow the discussion.

In order to improve the spatial resolution of an optical micro-scanning thermal microscope system, the micro-scanning position must be accurately calibrated. An adaptive calibration method based on image registration and plane coordinate system is proposed. The meaning of calibration is given, and the principle and method of point calibration are introduced in detail and experiments using the real system were done. Different reconstruction methods were applied to reconstruct the visible light image and the real thermal microscope image, and the evaluation scores are given. Results of simulation and real thermal imaging processing show that the method can successfully calibrate the micro-scanning position. The method can significantly improve the oversampled reconstructed image quality, thus enhancing the spatial resolution of the system. This method can also be used in other electro-optical imaging systems.