Search

In this experiment, the stable output of a dual-frequency laser source is obtained by an acousto-optic modulator due to the Bragg diffraction effect. Furthermore, the non-polarized dual-laser heterodyne interferometer is designed to measure the micro-movement of stacked piezoelectric (PZT) ceramic. This micro-movement can be dynamically determined by comparing the phase difference between the conference beam and measuring beam. The results indicate that the micro-movement of PZT ceramic changes linearly with the driven-voltage in the range of 0–30 V and the sensitivity of movement to voltage is 58.3 nm/V, which is very close to the theoretical value and this laser heterodyne interferometer can be applied for calibrating parameters of PZT ceramic.

Background: Augmented reality classrooms have become an interesting research topic in the field of education, but there are some limitations. Firstly, most researchers use cards to operate experiments, and a large number of cards cause difficulty and inconvenience for users. Secondly, most users conduct experiments only in the visual modal, and such single-modal interaction greatly reduces the users' real sense of interaction. In order to solve these problems, we propose the Multimodal Interaction Algorithm based on Augmented Reality (ARGEV), which is based on visual and tactile feedback in Augmented Reality. In addition, we design a Virtual and Real Fusion Interactive Tool Suite (VRFITS) with gesture recognition and intelligent equipment. Methods: The ARGVE method fuses gesture, intelligent equipment, and virtual models. We use a gesture recognition model trained by a convolutional neural network to recognize the gestures in AR, and to trigger a vibration feedback after a recognizing a fivefinger grasp gesture. We establish a coordinate mapping relationship between real hands and the virtual model to achieve the fusion of gestures and the virtual model. Results: The average accuracy rate of gesture recognition was 99.04%. We verify and apply VRFITS in the Augmented Reality Chemistry Lab (ARCL), and the overall operation load of ARCL is thus reduced by 29.42%, in comparison to traditional simulation virtual experiments. Conclusions: We achieve real-time fusion of the gesture, virtual model, and intelligent equipment in ARCL. Compared with the NOBOOK virtual simulation experiment, ARCL improves the users' real sense of operation and interaction efficiency.

Ocean acidification (OA) may interact with anthropogenic pollutants, such as heavy metals (HM), to represent a threat to marine organisms and ecosystems. Here, we perform a quantitative meta-analysis to examine the combined effects of OA and heavy metals on marine organisms. The results reveal predominantly additive interactions (67%), with a considerable proportion of synergistic interactions (25%) and a few antagonistic interactions (8%). The overall adverse effects of heavy metals on marine organisms were alleviated by OA, leading to a neutral impact of heavy metals in combination with OA. However, different taxonomic groups showed large variabilities in their responses, with microalgae being the most sensitive when exposed to heavy metals and OA, and having the highest proportion of antagonistic interactions. Furthermore, the variations in interaction type frequencies are related to climate regions and heavy metal properties, with antagonistic interactions accounting for the highest proportion in temperate regions (28%) and when exposed to Zn (52%). Our study provides a comprehensive insight into the interactive effects of OA and HM on marine organisms, and highlights the importance of further investigating the responses of different marine taxonomic groups from various geographic locations to the combined stress of OA and HM.

Virtual experiments have become an interesting research topic in the field of education. However, we found that there are some limitations in the current virtual experiments: first, the researchers used the virtual effects of the simulation to represent the virtual experiments, which led to decrease the immersion of the user's simulated experiments; second, most of the virtual experiments are only mouse or touch screen interactive mode, which reduces the realism of user simulation experiments; third, students independently explore the experimental operation process and spend too much time simulating the experiment, which leads to problems such as overloading the operation and low interaction efficiency. In order to solve the above problems, we propose and implement a multimodal navigational interaction virtual and real fusion chemistry laboratory (MNIVRFCL). We design a new sensing structure intelligent equipment and propose a multimodal navigational interaction algorithm (MMNI) based on auditory and tactile channel, which are verified and applied in MNIVRFCL. The MMNI algorithm can detect user's specific behaviors to understand their behavioral intentions, and then the system guide and rectify users' current correct or incorrect behaviors in the form of voice navigation broadcasts. Finally, we achieve the purpose that students can use virtual and real fusion interactions through tactile and auditory channels, they can independently complete simulations and learning experiments based on experimental navigation. The experimental statistic results show that system's successful understanding of intention is 91.48%, and prove the MNIVRFCL operational load reduce by 23.81% compared to the pure virtual experiment, it can reduce the time consumption and improves the students' interaction efficiency.

The application of virtual reality technology in science experiment education is a research with practical significance and value in human-computer interaction. However, in some existing education tools based on virtual reality, due to the single interaction mode, the complexity of user intention and the non-physical interaction characteristics brought by virtualization, their experimental teaching ability is limited, resulting in the lack of practical value and popularity. In order to solve these problems, a multimodal interaction model is constructed by fusing gesture, speech and pressure information. Specifically, our tasks include: 1) collecting user input information and time series information to construct basic data input tuples. 2) The basic interaction information is used to identify the user's basic intention, and the correlation degree between the user's intentions is considered to determine the correctness of the current identification intention. 3) It allows users to alternate between multi-channel and single channel interaction. Based on this model, we build a multi-modal intelligent interactive virtual experiment platform (MIIVEP), and design and implement a kind of dropper with strong perception ability, which has been verified, tested, evaluated and applied in the intelligent virtual experiment system. In addition, in order to evaluate this work more effectively, we developed a fair scoring criterion for the virtual experimental system (Evaluation scale of virtual experiment system, ESVES), and invited middle school teachers and students to participate in the verification of the results of this work. Through the user's actual use effect verification and result research, we prove the effectiveness of the proposed model and the corresponding implementation.

A novel phosphorous/silicon hybrid containing active amino was synthesized by bisphenol F epoxy resin modified by 0-(2,5-Dihydroxyphenyl)−10-hydro-9-oxa-10-phosphaphenanthrene-10-oxide (ODOPB) and hyperbranched polysiloxane (APTMS-HPSi). At first, APTMS-HPSi was synthesized by a simple reaction among aminoethylamino propyltrimethoxy silane (APTMS) and tripropylene glycol (TPG). ODOPB was used to modify bisphenol F epoxy resin. Then add different content of APTMS-HPSi to the phosphorus-containing modified epoxy resin (P-EP). Fourier Transform Infrared (FTIR) Spectroscopy was used to characterized the chemical structure of APTMS-HPSi. The effects of APTMS-HPSi content on key properties was systemically investigated. Results showed that the addition of APTMS-HPSi and ODOPB effectively improve the toughness and liquid oxygen compatibility. With the increase content of APTMS-HPSi, char yield and limited oxygen index (LOI) value of the cured resin increased, and the liquid oxygen sensitivity coefficient (IRS) decreased. The elongation at break was increased 45.32% by only 6wt% loading with APTMS-HPSi in epoxy resin, and at the same time the IRS of the modified resin was reduced from 7% to 0%. When the addition amount was 6wt%, the fracture elongation, impact strength and fracture toughness K _IC were increased by 52.1%, 81.8% and 54.3% respectively. Therefore, adding phosphorus and hyperbranched polysiloxane to the resin can improve the liquid oxygen compatibility and toughness of the epoxy resin at the same time.