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At present, research on intelligent wheelchairs mostly focuses on motion control, while research on attitude-based adjustment is relatively insufficient. The existing methods for adjusting wheelchair posture generally lack collaborative control and good human–machine collaboration. This article proposes an intelligent wheelchair posture-adjustment method based on action intention recognition by studying the relationship between the force changes on the contact surface between the human body and the wheelchair and the action intention. This method is applied to a multi-part adjustable electric wheelchair, which is equipped with multiple force sensors to collect pressure information from various parts of the passenger’s body. The upper level of the system converts the pressure data into the form of a pressure distribution map, extracts the shape features using the VIT deep learning model, identifies and classifies them, and ultimately identifies the action intentions of the passengers. Based on different action intentions, the electric actuator is controlled to adjust the wheelchair posture. After testing, this method can effectively collect the body pressure data of passengers, with an accuracy of over 95% for the three common intentions of lying down, sitting up, and standing up. The wheelchair can adjust its posture based on the recognition results. By adjusting the wheelchair posture through this method, users do not need to wear additional equipment and are less affected by the external environment. The target function can be achieved with simple learning, which has good human–machine collaboration and can solve the problem of some people having difficulty adjusting the wheelchair posture independently during wheelchair use.

Accurate recognition of disabled persons’ behavioral intentions is the key to reconstructing hand function. Their intentions can be understood to some extent by electromyography (EMG), electroencephalogram (EEG), and arm movements, but they are not reliable enough to be generally accepted. In this paper, characteristics of foot contact force signals are investigated, and a method of expressing grasping intentions based on hallux (big toe) touch sense is proposed. First, force signals acquisition methods and devices are investigated and designed. By analyzing characteristics of signals in different areas of the foot, the hallux is selected. The peak number and other characteristic parameters are used to characterize signals, which can significantly express grasping intentions. Second, considering complex and fine tasks of the assistive hand, a posture control method is proposed. Based on this, many human-in-the-loop experiments are conducted using human–computer interaction methods. The results showed that people with hand disabilities could accurately express their grasping intentions through their toes, and could accurately grasp objects of different sizes, shapes, and hardness using their feet. The accuracy of the action completion for single-handed and double-handed disabled individuals was 99% and 98%, respectively. This proves that the method of using toe tactile sensation for assisting disabled individuals in hand control can help them complete daily fine motor activities. The method is easily acceptable in terms of reliability, unobtrusiveness, and aesthetics.

By constructing a static map, the library robot can navigate and access documents autonomously, which greatly improves efficiency; however, for libraries where shelves can be moved, map changes do not allow for direct navigation, and also sensors such as radar and camera are relatively expensive, so we propose a low-cost navigation algorithm based on real-time ranging data and map matrices, and designed a mobile archive access robot. In order to obtain real-time distance data, nine near/long range sensors were mounted on the chassis and a composite digital filtering algorithm was designed based on different moving area characteristics; then the access task matrix and map matrix were designed based on the archive access task and the location characteristics of the archive shelf placement, the robot can rely on the range data to update the map matrix during the moving process, complete its own positioning, and use the task matrix The robot can use the task matrix to complete autonomous navigation and access to multiple files. Experiments show that the filtered positioning accuracy can reach 1cm, while the robot can move to the target shelf autonomously, which is more practical and less costly.

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.

The temperature dependence of the Al2O3 solubility in bridgmanite has been determined in the system MgSiO3–Al2O3 at temperatures of 2750–3000 ​K under a constant pressure of 27 ​GPa using a multi-anvil apparatus. Bridgmanite becomes more aluminous with increasing temperatures. A LiNbO3-type phase with a pyrope composition (Mg3Al2Si3O12) forms at 2850 ​K, which is regarded as to be transformed from bridgmanite upon decompression. This phase contains 30 ​mol% Al2O3 at 3000 ​K. The MgSiO3 solubility in corundum also increases with temperatures, reaching 52 ​mol% at 3000 ​K. Molar volumes of the hypothetical Al2O3 bridgmanite and MgSiO3 corundum are constrained to be 25.95 ​± ​0.05 and 26.24 ​± ​0.06 ​cm3/mol, respectively, and interaction parameters of non-ideality for these two phases are 5.6 ​± ​0.5 and 2.2 ​± ​0.5 ​KJ/mol, respectively. The increases in Al2O3 and MgSiO3 contents, respectively, in bridgmanite and corundum are caused by a larger entropy of Al2O3 bridgmanite plus MgSiO3 corundum than that of MgSiO3 bridgmanite plus Al2O3 corundum with temperature, in addition to the configuration entropy. Our study may help explain dynamics of the top lower mantle and constrain pressure and temperature conditions of shocked meteorites.