Investigation of Methane and Nitrous Oxide Greenhouse Gases Emissions on Wastewater Treatment Plant

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Yinchen Linggui Zhugan Decoction Ameliorates Nonalcoholic Fatty Liver Disease in Rats by Regulating the Nrf2/ARE Signaling Pathway

Yinchen Linggui Zhugan Decoction (YCLGZGD) is the combination of Linggui Zhugan (LGZGD) and Yinchenhao (YCHD) decoctions, two famous traditional Chinese medicine prescriptions. In previous studies, we found that Yinchen Linggui Zhugan Decoction (YCLGZGD) could regulate lipid metabolism disorder and attenuate inflammation in pathological process of nonalcoholic fatty liver disease (NAFLD). However, the exact underlying mechanism remains unknown. The aim of this study was to explore the effect of Yinchen Linggui Zhugan Decoction on experimental NAFLD and its mechanism in rats with high-fat diet (HFD) which was established by 8-week administration of HFD. YCLGZGD, LGZGD, and YCHD were administered daily for 4 weeks, after which the rats were euthanized. The level of blood lipid, liver enzymes, H&E, and Oil Red O staining were determined to evaluate NAFLD severity. Western blotting and real-time polymerase chain reaction were, respectively, used to determine hepatic protein and gene expression of Keap1, Nrf2, NQO1, and HO-1. Oral YCLGZGD ameliorated HFD-induced NAFLD. Furthermore, YCLGZGD increased the protein and gene expression of Nrf2, NQO1, and HO-1 without changing Keap1. Overall, these results suggest that YCLGZGD ameliorates HFD-induced NAFLD in rats by upregulating the Nrf2/ARE signaling pathway

Measurement-device-independent quantum key distribution over untrustful metropolitan network

Quantum cryptography holds the promise to establish an information-theoretically secure global network. All field tests of metropolitan-scale quantum networks to date are based on trusted relays. The security critically relies on the accountability of the trusted relays, which will break down if the relay is dishonest or compromised. Here, we construct a measurement-device-independent quantum key distribution (MDIQKD) network in a star topology over a 200 square kilometers metropolitan area, which is secure against untrustful relays and against all detection attacks. In the field test, our system continuously runs through one week with a secure key rate ten times larger than previous result. Our results demonstrate that the MDIQKD network, combining the best of both worlds --- security and practicality, constitutes an appealing solution to secure metropolitan communications.Comment: 17 pages, 4 figure

Experimental measurement-device-independent quantum digital signatures over a metropolitan network

Quantum digital signatures (QDS) provide a means for signing electronic communications with informationtheoretic security. However, all previous demonstrations of quantum digital signatures assume trusted measurement devices. This renders them vulnerable against detector side-channel attacks, just like quantum key distribution. Here, we exploit a measurement-device-independent (MDI) quantum network, over a 200-square-kilometer metropolitan area, to perform a field test of a three-party measurement-device-independent quantum digital signature (MDI-QDS) scheme that is secure against any detector side-channel attack. In so doing, we are able to successfully sign a binary message with a security level of about 1E-7. Remarkably, our work demonstrates the feasibility of MDI-QDS for practical applications.Comment: 5 pages, 1 figure, 2 tables, supplemental materials included as ancillary fil

Abstract Syntax Tree for Programming Language Understanding and Representation: How Far Are We?

Programming language understanding and representation (a.k.a code representation learning) has always been a hot and challenging task in software engineering. It aims to apply deep learning techniques to produce numerical representations of the source code features while preserving its semantics. These representations can be used for facilitating subsequent code-related tasks. The abstract syntax tree (AST), a fundamental code feature, illustrates the syntactic information of the source code and has been widely used in code representation learning. However, there is still a lack of systematic and quantitative evaluation of how well AST-based code representation facilitates subsequent code-related tasks. In this paper, we first conduct a comprehensive empirical study to explore the effectiveness of the AST-based code representation in facilitating follow-up code-related tasks. To do so, we compare the performance of models trained with code token sequence (Token for short) based code representation and AST-based code representation on three popular types of code-related tasks. Surprisingly, the overall quantitative statistical results demonstrate that models trained with AST-based code representation consistently perform worse across all three tasks compared to models trained with Token-based code representation. Our further quantitative analysis reveals that models trained with AST-based code representation outperform models trained with Token-based code representation in certain subsets of samples across all three tasks. We also conduct comprehensive experiments to evaluate and reveal the impact of the choice of AST parsing/preprocessing/encoding methods on AST-based code representation and subsequent code-related tasks. Our study provides future researchers with detailed guidance on how to select solutions at each stage to fully exploit AST.Comment: submitted to ACM Transactions on Software Engineering and Methodology. arXiv admin note: text overlap with arXiv:2103.10668 by other author

Human umbilical cord blood-derived mononuclear cell transplantation: case series of 30 subjects with Hereditary Ataxia

<p>Abstract</p> <p>Background</p> <p>The differential diagnosis for hereditary ataxia encompasses a variety of diseases characterized by both autosomal dominant and recessive inheritance. There are no curative treatments available for these neurodegenerative conditions. This open label treatment study used human umbilical cord blood-derived mononuclear cells (CBMC) combined with rehabilitation training as potential disease modulators.</p> <p>Methods</p> <p>30 patients suffering from hereditary ataxia were treated with CBMCs administered systemically by intravenous infusion and intrathecally by either cervical or lumbar puncture. Primary endpoint measures were the Berg Balance Scale (BBS), serum markers of immunoglobulin and T-cell subsets, measured at baseline and pre-determined times post-treatment.</p> <p>Results</p> <p>A reduction of pathological symptoms and signs was shown following treatment. The BBS scores, IgG, IgA, total T cells and CD3+CD4 T cells all improved significantly compared to pre-treatment values (<it>P </it>< 0.01~0.001). There were no adverse events.</p> <p>Conclusion</p> <p>The combination of CBMC infusion and rehabilitation training may be a safe and effective treatment for ataxia, which dramatically improves patients' functional symptoms. These data support expanded double blind, placebo-controlled studies for these treatment modalities.</p