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Structured ZSM-5/SiC foam catalysts for bio-oils upgrading
Get PDFZSM-5 zeolite coating supported on SiC foams was prepared by a precursor dispersion-secondary growth method and the resulting structured ZSM-5/SiC foam catalyst was used for the proof-of-concept study of catalytic bio-oils upgrading (i.e. deoxygenation of the model compounds of methanol and anisole) in reference to ZSM-5 catalyst pellets. A layer of ZSM-5 coating with inter-crystal porosity on SiC foams was produced by curing the zeolite precursor thermally at 80 °C. The use of SiC foam as the zeolite support significantly improved transport phenomena compared to the packed-bed using ZSM-5 pellets, explaining the comparatively good catalytic performance achieved by the structured ZSM-5/SiC foam catalyst. In comparison with the ZSM-5 pellets, the ZSM-5/SiC foam catalyst showed 100.0% methanol conversion (at the weight hourly space velocity, WHSV, of 8 h–1) and 100.0% anisole conversion (at WHSV =5 h−1) at the initial stage of the processes, while only about 3% were obtained for the ZSM-5 pellets, under the same conditions. Based on the comparative analysis of the characterisation data on the fresh and spent catalysts, the deactivation mechanisms of the ZSM-5/SiC and the ZSM-5 pellet catalysts were explained. The process intensification using SiC foam to support ZSM-5 improved the global gas-to-solid mass transfer notably, and hence mitigating the pore blocking due to the carbon deposition on the external surface of supported ZSM-5
Investigation of potential cognition factors correlated to fire evacuation
Get PDFThe design of a navigation system to support indoor fire evacuation depends not only on speed but also a relatively thorough consideration of the cognition factors. This study has investigated potential cognition factors which can affect the human behaviours and decision making during fire evacuation by taking a survey among indoor occupants in age of 20s under designed virtual scenarios. It mainly focuses on two aspects of Fire Responses Performances (FRP), i.e. indoor familiarity (spatial cognition) and psychological stress (situ-ated cognition). The collected results have shown that these cognition factors can be affected by gender and user height and they are correlated with each other in certain ways. It has also investigated users‟ attitudes to the navigation services under risky and non-risky conditions. The collected answers are also found to be correlated with the selected FRP factors. These findings may help to further design of personalized indoor navigation support for fire evacuation
Magnetically-accelerated photo-thermal conversion and energy storage based on bionic porous nanoparticles
Get PDFRecently, the technology of mixing phase change materials with high thermal conductivity fillers was developed, which has allowed thermal energy storage to be implemented in a wide range of industrial technologies and processes. In the present study, a hierarchical bionic porous nano-composite was prepared, which efficiently merged the nanomaterial characteristics of magnetism and high thermal conductivity in order to form a magnetically-accelerated solar-thermal energy storage method. The morphology and thermo-physical properties of materials were analysed. The experimental outcomes of phase change heat transfer demonstrated that the maximum storage efficiency increases by 102.7% when the hierarchical bionic porous structure is used, and a further 27.1% improvement can be achieved with the magnetic field. At the same time, the heat transfer process of energy storage in hierarchical porous composites under external physical fields is explained by simulation. Therefore, this magnetically-accelerated method demonstrated the superior solar-thermal energy storage characteristics within a hierarchical bionic porous structure which is particularly beneficial for the utilisation of solar direct absorption collectors and energy storage technology
Continuous use of fitness apps and shaping factors among college students: a mixed-method investigation
Get PDFObjective: This current study pursued an exploration of the psychological mechanism that determines college students’ continuance intention to use fitness apps. Methods: This current study adopted a mixed methods research that composed two distinct phases. Study 1 was quantitative research that helped to identify determinants of Chinese college students’ continuance intention to use. A self-reported questionnaire was completed by 379 college students to ascertain their user experience. Study 2 was qualitative research. A semi-structured interview was conducted with a sample of 10 college students. Study 2 can be seen as a follow-up study and it pursued an in-depth understanding on how college students use fitness apps in the everyday life and their views towards study 1’s major findings. Results: The results revealed that five factors (confirmed usefulness, confirmed ease of use, satisfaction, fitness achievement and social connection) were found to significantly and positively affect college students’ continuous intention to use fitness apps. Entertainment did not show obvious impact. In the interview, college students reported that even if they don't obtain entertainment from fitness apps, they will still push themselves to use them, because they have a very specific goal when using fitness apps, which is to achieve health and fitness. Conclusion: These findings indicated that successful fitness apps should make users feel convenient to use and indeed improves the fitness user's efficiency. Besides, people are more eager to get the information with strong credibility with the negligible effort. This implies more efforts should be made to design apps that can provide high-quality services. Moreover, if apps designers can pay more attention to protecting the personal information and data, it will inspire more people to use social connection functions
The effects of Jesus and God on pro-sociality and discrimination
Get PDFThis study contributes to the debate over whether religion is a force for social good or harm. It shows that different belief concepts within the same religion can have different effects on distributive behaviour. A dictator game experiment, with two different charities as potential recipients, measures how priming the concepts of God and Jesus affects both the pro-sociality of Christians and their propensity to discriminate against LGBTQ people, an identity group traditionally opposed by their religion. Priming Jesus significantly raises the amounts Christians give to charity, but priming God has no such effect. Christians are found, at borderline significance, to discriminate against LGBTQ people, but this discrimination does not significantly increase when Jesus or God are primed
Adoption of electronic supply chain management systems: the mediation role of information sharing
Get PDFPurpose: Based on structural embeddedness theory and resource dependence theory, this research aims to examine the mediation role of information sharing in the relationship between deendency structures and electronic supply chain management system (eSCM) adoption and a firm's intention to adopt eSCMs. Design/methodology/approach: A survey questionnaire was undertaken from 212 companies based in Mainland China. Three-stage least squares (3SLS) regression was employed to test the research model. Findings: The results from 3SLS regressions showed that the effect of interdependence on eSCM adoption intention is fully mediated through information sharing when relationship duration is either below or about the mean. Interdependence and dependence disadvantage was shown to have significant positive effects on eSCM adoption while the effect of dependence advantage was statistically insignificant. Relationship duration was found to negatively moderate the relationship between information sharing and adoption intention. Originality/value: Through investigating factors of inter-organizational relationships, this study fills the knowledge gap in the traditional paradigms which ignore the collaborative nature of eSCM and analyse related problems based on a single firm's point of view
Proportional step perturbation method MPPT for boost circuit of TEG
Get PDFIn order to improve the working efficiency of thermoelectric generation (TEG), maximum power point tracking (MPPT) is usually used in the system. The perturbation method is a traditional method for MPPT. The perturbation of the step length is normally fixed. It will lead to be not accurate enough if the step size is too big. If the step size is too small, it will lead to take a long time. Therefore, the proportional step perturbation method MPPT is proposed in the paper. This method can be implemented by using large steps at the beginning to save time. When it is near the maximum power point, small steps can be used to achieve the accurate purpose. The derivation of the method has been described in details in the paper. The simulation model is established based on Matlab. The simulation results show that the method is feasible
Evaluation of the accuracy of SRTM3 and ASTER GDEM in the Tibetan Plateau mountain ranges
Get PDFTopographic data on The Tibetan Plateau (TP) terrain are fundamental for geoscientific research, but are difficult to obtain. The Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are two commonly used GDEM data. Verifying the accuracy of the two dataset for the TP mountain areas provides a reference point for the application of both DEMs. For evaluating the elevation accuracy and topographic information, we used 8242 field measurements from Differential Global Positioning System (DGPS) points and DEM data generated from 1:100,000 topographic maps to examine the accuracy of ASTER GDEM V2 and SRTM3 V4.1 elevation results. The average RMSE for elevation differences between DGPS and ASTER GDEM across the study areas was 18.56m while the average RMSE between DGPS and SRTM3 was 10.39m. The average RMSEs of ASTER GDEM and SRTM3 in glaciated areas were 8.55m and 5.87m, respectively. The vertical accuracy of SRTM3 is better than that of ASTER GDEM. The vertical accuracy of both DEMs do not vary with altitude, but is related to aspect and slope
Multisystem optimization for an integrated production scheduling with resource saving problem in textile printing and dyeing
Get PDFResource saving has become an integral aspect of manufacturing in industry 4.0. This paper proposes a multisystem optimization (MSO) algorithm, inspired by implicit parallelism of heuristic methods, to solve an integrated production scheduling with resource saving problem in textile printing and dyeing. First, a real-world integrated production scheduling with resource saving is formulated as a multisystem optimization problem. Then, the MSO algorithm is proposed to solve multisystem optimization problems that consist of several coupled subsystems, and each of the subsystems may contain multiple objectives and multiple constraints. The proposed MSO algorithm is composed of within-subsystem evolution and cross-subsystem migration operators, and the former is to optimize each subsystem by excellent evolution operators and the later is to complete information sharing between multiple subsystems, to accelerate the global optimization of the whole system. Performance is tested on a set of multisystem benchmark functions and compared with improved NSGA-II and multiobjective multifactorial evolutionary algorithm (MO-MFEA). Simulation results show that the MSO algorithm is better than compared algorithms for the benchmark functions studied in this paper. Finally, the MSO algorithm is successfully applied to the proposed integrated production scheduling with resource saving problem, and the results show that MSO is a promising algorithm for the studied problem. © 2020 Haiping Ma et al
A regularized attribute weighting framework for naive bayes
Get PDFThe Bayesian classification framework has been widely used in many fields, but the covariance matrix is usually difficult to estimate reliably. To alleviate the problem, many naive Bayes (NB) approaches with good performance have been developed. However, the assumption of conditional independence between attributes in NB rarely holds in reality. Various attribute-weighting schemes have been developed to address this problem. Among them, class-specific attribute weighted naive Bayes (CAWNB) has recently achieved good performance by using classification feedback to optimize the attribute weights of each class. However, the derived model may be over-fitted to the training dataset, especially when the dataset is insufficient to train a model with good generalization performance. This paper proposes a regularization technique to improve the generalization capability of CAWNB, which could well balance the trade-off between discrimination power and generalization capability. More specifically, by introducing the regularization term, the proposed method, namely regularized naive Bayes (RNB), could well capture the data characteristics when the dataset is large, and exhibit good generalization performance when the dataset is small. RNB is compared with the state-of-the-art naive Bayes methods. Experiments on 33 machine-learning benchmark datasets demonstrate that RNB outperforms the compared methods significantly
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