256 research outputs found

    Structural Features and Thermoelectric Properties of PbTe-based Materials

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    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

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

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    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

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    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

    Irbesartan Ameliorates Lipid Deposition by Enhancing Autophagy via PKC/AMPK/ULK1 Axis in Free Fatty Acid Induced Hepatocytes

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    Irbesartan has shown significant therapeutic effects in hypertensive patients with non-alcoholic fatty liver disease (NAFLD). To determine the underlying mechanisms of its action, we established an in vitro model of NAFLD by treating human and mouse hepatocytes with free fatty acids (FFAs) and angiotensin (Ang) II. Irbesartan significantly reversed AngII/FFA-induced lipid deposition and mitochondrial dysfunction by restoring ATP production and the mitochondrial membrane potential (MMP), and decreasing the levels of reactive oxygen species (ROS) and inflammatory markers. In addition, irbesartan also increased the autophagy flux, in terms of increased numbers of autolysosomes and autophagosomes, and the upregulation and mitochondrial localization of the autophagic proteins Atg5 and LC3BII/I. Activation of protein kinase C (PKC) and inhibition of the autophagic flux exacerbated mitochondrial dysfunction in the steatotic hepatocytes. Furthermore, AngII upregulated PKC which inhibited AMPK phosphorylation via direct interaction with the AngII receptor AT1-R. Irbesartan inhibited PKC and activated AMPK and its downstream effector ULK1, thereby inducing autophagy, decreasing lipid deposition, and restoring mitochondrial function. Taken together, irbesartan triggers autophagy via the PKC/AMPK/ULK1 axis to ameliorate the pathological changes in the steatotic hepatocytes
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