Structural Features and Thermoelectric Properties of PbTe-based Materials

Thermoelectric (TE) materials are used to directly interconvert heat and electricity. The semiconductor PbTe with narrow band gap is one of the leading thermoelectric materials in mid-temperature range due to intrinsically low lattice thermal conductivity and large Seebeck coefficient. Recently, various strategies have produced p-type and n-type PbTe-based materials with greatly enhanced TE properties. However, there are still many fascinating features which are needed to be studied. First, phase analysis and TE properties of binary polycrystalline Pb‒Te samples prepared by various heat treatments have been investigated. Since europium with its 4f electrons was expected to have strong influence on the thermoelectric behavior of PbTe, the constitution and thermoelectric behavior of two substitution schemes with possible Eu2+ and Eu3+ in the Pb–Eu–Te ternary system have been examined. As sodium is widely used as substituting element for p-type PbTe-based TE materials, the crystal structural features and TE properties of two series of polycrystalline samples Pb1-yNayTe1-y/2 and Pb1-xNaxTe have been studied. The local atomic arrangement of sodium by different substitution schemes has been revealed by NMR. Finally, we present the reproducibility of TE properties and microstructure evolutions of high-ZT Eu-substituted and Na-substituted PbTe during different heat treatments. From binary PbTe to ternary Pb–Eu–Te and Pb–Na–Te, and final with quaternary Pb–Eu–Na–Te, the comprehensive picture of the structure and TE properties for Pb–Eu–Na–Te system is constructed

Residents’ Support for Rural Tourism: Community Empowerment, Life Domain Satisfaction and QoL

Based on empowerment theory, spillover theory, and cognitive appraisal theory, this study examined the interactive relationships among residents’ community empowerment, life domain satisfaction (LDS), overall quality of life (QoL), and support for tourism (SFT) in rural contexts. Using data collected from 412 residents in rural destinations, the results indicated that psychological empowerment directly influenced residents’ support for tourism and political empowerment positively affected their overall QoL, while all the 3 dimensions of community empowerment influenced life domain satisfaction directly. Besides, the findings found that life domain satisfaction partially mediated the relationships between community empowerment and SFT. Finally, community empowerment affected residents’ SFT through LDS and overall QoL. Theoretical and practical implications were discussed as well

Showing more kindness to disabled tourists because of understanding: The interaction among the perceived level of information, affection and altruistic behavior intention

It is the common responsibility of the whole society to provide friendly and appropriate help for disabled tourists.However, the altruistic behavior of ordinary tourists towards disabled tourists has been ignored in academia, and few studies have focused on the internal factors that affect the altruistic behavior of ordinary tourists. To fill in these gaps, planning to investigate 500 respondents, based on The Tri-component attitude model, this study, applying SEM, will examine the effect of ordinary tourists\u27 perceived level of information about the travel barriers faced by physical disabled tourists on their empathy and discomfort, which positively affected their altruistic behavior intention to physical disabledtourists. Moreover, the contents of ordinary tourists\u27 perceived level of information and information source will be explored through 10 in-depth interviews. Theoretical and practical implications of this research were discussed as well

Host-guest interaction in P2P accommodation under the epidemic: Motivations, behavior and influences

The epidemic has reshaped tourists demands and changed the way they interact with others. Using qualitative grounded theory, from the perspective of tourists, this study developed a framework to further illustrate the driving factors, other external factors, the new content of the interaction between the hosts and the guests, and the outcomes of such interaction in the context of epidemic. The result shows that exploring meaningful interpersonal relationship and releasing depression and anxiety are the driving factors for guests to engage in face-to-face interactions. Furthermore, guests’ perceived hygienic attributes of P2P accommodation during the stay influenced them infection risk perceptions. Guests with high-risk perceptions preferring to contactless or without interaction with the host, those with lower risk perceptions choosing to face-to-face interaction. The face-to-face and contactless interaction will enhance guests’ psychological capital and lead to tourist citizenship behaviors. The theoretical and practical implications were discussed as well

Tourists’ green behavior: Co-creation and emotional experience

Based on the theory of inseparability nature of service, service dominant logic, and SOR model, this study examined the interactive relationships among tourists’ co-creation of experience, self-esteem, satisfaction with travel experience, quality of life, and green behavior. Using data collected from 493 tourists in China, the results indicated that co-creation of experience directly influenced their self-esteem, satisfaction with travel experience, and green behavior. Besides, the findings found that emotional experience (satisfaction with travel experience, self-esteem, quality of life) partially mediated the relationships between co-creation experience and green behavior. Finally, co-creation affected tourists’ green behavior through the chain mediating role of self-esteem, satisfaction with travel experience, and quality of life. Theoretical and practical implications were discussed as well

Spatiotemporal Graph Neural Networks with Uncertainty Quantification for Traffic Incident Risk Prediction

Predicting traffic incident risks at granular spatiotemporal levels is challenging. The datasets predominantly feature zero values, indicating no incidents, with sporadic high-risk values for severe incidents. Notably, a majority of current models, especially deep learning methods, focus solely on estimating risk values, overlooking the uncertainties arising from the inherently unpredictable nature of incidents. To tackle this challenge, we introduce the Spatiotemporal Zero-Inflated Tweedie Graph Neural Networks (STZITD-GNNs). Our model merges the reliability of traditional statistical models with the flexibility of graph neural networks, aiming to precisely quantify uncertainties associated with road-level traffic incident risks. This model strategically employs a compound model from the Tweedie family, as a Poisson distribution to model risk frequency and a Gamma distribution to account for incident severity. Furthermore, a zero-inflated component helps to identify the non-incident risk scenarios. As a result, the STZITD-GNNs effectively capture the dataset's skewed distribution, placing emphasis on infrequent but impactful severe incidents. Empirical tests using real-world traffic data from London, UK, demonstrate that our model excels beyond current benchmarks. The forte of STZITD-GNN resides not only in its accuracy but also in its adeptness at curtailing uncertainties, delivering robust predictions over short (7 days) and extended (14 days) timeframes

Quality Mapping of Offset Lithographic Printed Antenna Substrates and Electrodes by Millimeter-Wave Imaging

Offset lithographic printed flexible antenna substrate boards and electrodes have attracted much attention recently due to the boost of flexible electronics. Unmanned quality inspection of these printed substrate boards and electrodes demands high-speed, large-scale and nondestructive methods, which is highly desired for manufacturing industries. The work here demonstrates two kinds of millimeter (mm)-wave imaging technologies for the quality (surface uniformity and functionality parameters) inspection of printed silver substrates and electrodes on paper and thin polyethylene film, respectively. One technology is a mm-wave line scanner system and the other is a terahertz-time domain spectroscopy-based charge-coupled device (CCD) imaging system. The former shows the ability of detecting transmitted mm-wave amplitude signals only; its detection is fast in a second time scale and the system shows great potential for the inspection of large-area printed surface uniformity. The latter technology achieves high spatial resolution images of up to hundreds of micrometers at the cost of increased inspection time, in a time scale of tens of seconds. With the exception of absorption rate information, the latter technology offers additional phase information, which can be used to work out 2D permittivity distribution. Moreover, its uniformity is vital for the antenna performance. Additionally, the results demonstrate that compression rolling treatment significantly improves the uniformity of printed silver surfaces and enhances the substrate’s permittivity values

Ultrasensitive amyloid β-protein quantification with high dynamic range using a hybrid graphene-gold surface-enhanced Raman spectroscopy platform.

Surface enhanced Raman spectroscopy (SERS) holds great promise in biosensing because of its single-molecule, label-free sensitivity. We describe here the use of a graphene-gold hybrid plasmonic platform that enables quantitative SERS measurement. Quantification is enabled by normalizing analyte peak intensities to that of the graphene G peak. We show that two complementary quantification modes are intrinsic features of the platform, and that through their combined use, the platform enables accurate determination of analyte concentration over a concentration range spanning seven orders of magnitude. We demonstrate, using a biologically relevant test analyte, the amyloid β-protein (Aβ), a seminal pathologic agent of Alzheimer's disease (AD), that linear relationships exist between (a) peak intensity and concentration at a single plasmonic hot spot smaller than 100 nm, and (b) frequency of hot spots with observable protein signals, i.e. the co-location of an Aβ protein and a hot spot. We demonstrate the detection of Aβ at a concentration as low as 10-18 M after a single 20 μl aliquot of the analyte onto the hybrid platform. This detection sensitivity can be improved further through multiple applications of analyte to the platform and by rastering the laser beam with smaller step sizes

Construction of lncRNA and mRNA co-expression network associated with nasopharyngeal carcinoma progression

Nasopharyngeal carcinoma is a type of head and neck cancer with a high incidence in men. In the past decades, the survival rate of NPC has remained around 70%, but it often leads to treatment failure due to its distant metastasis or recurrence. The lncRNA-mRNA regulatory network has not been fully elucidated. We downloaded the NPC-related gene expression datasets GSE53819 and GSE12452 from the Gene Expression Omnibus database; GSE53819 included 18 NPC tissues and 18 normal tissues, and GSE12452 included 31 NPC tissues and 10 normal tissues. Weighted gene co-expression network analysis was performed on mRNA and lncRNA to screen out modules that were highly correlated with tumor progression. The two datasets were subjected to differential analysis after removing batch effects, and then Venn diagrams were used to screen for overlapping genes in the module genes and differential genes. The lncRNA-mRNA co-expression network was then constructed, and key mRNAs were identified by MCODE analysis and expression analysis. GSEA analysis and qRT-PCR were performed on key mRNAs. Through a series of analyses, we speculated that BTK, CD72, PTPN6, and VAV1 may be independent predictors of the prognosis of NPC patients.Taken together, our study provides potential candidate biomarkers for NPC diagnosis, prognosis, or precise treatment