Selective gas detection using Mn3O4/WO3 composites as a sensing layer

Pure WO3 sensors and Mn3O4/WO3 composite sensors with different Mn concentrations (1 atom %, 3 atom % and 5 atom %) were successfully prepared through a facile hydrothermal method. As gas sensing materials, their sensing performance at different temperatures was systematically investigated for gas detection. The devices displayed different sensing responses toward different gases at specific temperatures. The gas sensing performance of Mn3O4/WO3 composites (especially at 3 atom % Mn) were far improved compared to sensors based on pure WO3, where the improvement is related to the heterojunction formed between the two metal oxides. The sensor based on the Mn3O4/WO3 composite with 3 atom % Mn showed a high selective response to hydrogen sulfide (H2S), ammonia (NH3) and carbon monoxide (CO) at working temperatures of 90 degrees C, 150 degrees C and 210 degrees C, respectively. The demonstrated superior selectivity opens the door for potential applications in gas recognition and detection

Approach to Identifying Raindrop Vibration Signal Detected by Optical Fiber

Optical Fiber Vibration pre-Warning System (OFVWS) is widely applied to pipeline transportation, defense boundary and military base. One of its key technologies is signal feature extraction and vibration source identification. However, some harmless vibration signals often affect the reliability of this identification process due to the false alarms. Therefore, it is very important to identify various harmless vibration signals effectively. In this paper, we analyze the energy distribution feature of nature raindrop vibration signal detected by optical fiber. Based on this analysis, we develop an energy information entropy model and an approach to identify the harmless raindrop vibration signal. Study shows that the nature raindrop vibration signal can be detected and identified automatically by extracting the energy information entropy value and combining with the statistical detection method. The field tests result also showed that this approach based on energy information entropy model is able to effectively identify harmless raindrop vibration signal. Its identification probability is high and its false alarm and false recognition probability is low, hence the working performance of the OFVWS can be improved by using the presented approach

Incremental Bilateral Preference Stable Planning over Event Based Social Networks

In recent years, Event Based Social Networks (EBSNs) appear in people’s daily life and are becoming increasing popular. In EBSNs, one typical task is to make personalized plans for users. Existing studies only consider the preference of users. They make plans by selecting interesting events for users. However, for organizers of events, they also would like more high-quality users to participate in their events, which may make the events more exciting. Existing studies are user-centered and ignore the requirement of organizers. What is more, organizers are allowed to modify their events dynamically before they are held. The platforms should be able to dynamically adjust the schedules of users. Therefore, we identify a new Incremental Bilateral Preference Stable Planning (IBPSP) problem over EBSNs and propose several solutions to deal with different situations. We conduct extensive experiments to verify the efficiency and effectiveness of the proposed algorithms

Liquid crystal elastomer composites for soft actuators

ABSTRACTLiquid crystal elastomers are active materials that combine the anisotropic properties of liquid crystals with the elasticity of polymer networks. The LCEs exhibit remarkable reversible contraction and elongation capabilities in response to external stimuli, rendering them highly promising for diverse applications, such as soft robotics, haptic devices, shape morphing structures, etc. However, the predominant reliance on heating as the driving stimulus for LCEs has limited their practical applications. This drawback can be effectively addressed by incorporating fillers, which can generate heat under various stimuli. The recent progress in LCE composites has significantly expanded the application potential of LCEs. In this minireview, we present the design strategies for soft actuators with LCE composites, followed by a detailed exploration of photothermal and electrothermal LCE composites as prominent examples. Furthermore, we provide an outlook on the challenges and opportunities in the field of LCE composites

Research on path guidance of logistics transport vehicle based on image recognition and image processing in port area

Abstract Due to the messy logistics goods in the port area, some automatic transport vehicles often have errors in cargo transportation due to large path identification errors. Based on this, this study is based on image recognition technology, taking the most common logistics transport vehicles in the port area as the research object and using video image recognition technology as a guiding technology to perform image recognition processing on the ground guidance path. Simultaneously, this study determined the image preprocessing method which is more favorable for visual navigation, used the morphological knowledge of the image to detect the edge of the path image, then determined the position of the path center line, and carried out simulation analysis. The research shows that the results of this study have certain practicality and can provide theoretical references for subsequent related research

The Determinants of Impulsive Buying Behavior in Electronic Commerce

Consumers’ online impulsive buying behavior has become more and more frequent in the digital era. There is increasing concern regarding the adverse consequences that impulsive buying has generated for consumer wellbeing and the sustainability of our society and environment. In search of a way to decreasing impulsive consumption, this article proposes a comprehensive framework to explore the potential determinants of online impulsive buying behavior from the perspective of consumer characteristics grounded on the literature on sustainability, psychology and consumer behavior. Through an online survey, a total of 425 valid responses were obtained. Extroversion and neuroticism in personality, negative emotions, collectivism in culture and the cognitive and affective factors of impulsive buying tendency are found to be positively correlated with impulsive buying behavior, whereas self-control shows a negative impact on impulsive buying behavior. Furthermore, this study identifies the mediating roles that negative emotions and collectivism play. Specifically, in addition to the direct routes, neuroticism, self-control and the affective factor of impulsive buying tendency can indirectly influence impulsive buying behavior through the mediation of negative emotions, whereas extroversion can indirectly affect impulsive buying behavior with collectivism as the mediator. To conclude, theoretical and practical implications of this research are elaborated to promote sustainable consumption from both the micro and macro perspectives