Power quality improvements of arc welding power supplies by modified bridgeless SEPIC PFC converter

This paper proposes an efficient bridgeless power factor corrected (PFC) modified single ended primary inductor converter (SEPIC) for arc welding power supplies (AWPS). The overall configuration is composed of two converters: (1) a modified bridgeless SEPIC PFC converter, which is controlled by a PI controller to achieve a high power factor and fast response; and (2) a full bridge buck converter with high-frequency transformer for high-frequency isolation to ensure arc welding stability. The proposed system is simulated under different operating conditions of an AWPS. It is also tested in real time by a hardware-in-the-loop system based on a dSPACE DS1103 control board. The system performances are evaluated based on power quality indices such as power factor, total harmonic distortions of the AC grid current, and voltage regulation. The obtained results show that the proposed controller enhances the weld bead quality by keeping a constant current at the output and a stable arc, meet the international power quality standards and robustness for voltage regulation

Salvia miltiorrhiza water-soluble extract, but not its constituent salvianolic acid B, abrogates LPS-induced NF-kappaB signalling in intestinal epithelial cells

Herbal medicine has become an increasing popular therapeutic alternative among patients suffering from various inflammatory disorders. The Salvia miltiorrhizae water-soluble extract (SME) have been shown to possess antioxidant and anti-inflammatory properties in vitro. However, the mechanism of action and impact of SME on LPS-induced gene expression is still unknown. We report that SME significantly abrogated LPS-induced IκB phosphorylation/degradation, NF-κB transcriptional activity and ICAM-1 gene expression in rat IEC-18 cells. Chromatin immunoprecipitation assay demonstrated that LPS-induced RelA recruitment to the ICAM-1 gene promoter was inhibited by SME. Moreover, in vitro kinase assay showed that SME directly inhibits LPS induced IκB kinase (IKK) activity in IEC-18 cells. To investigate the physiological relevance of SME inhibitory activity on NF-κB signalling, we used small intestinal explants and primary intestinal epithelial cells derived from a transgenic mouse expressing the enhanced green fluorescent protein (EGFP) under the transcriptional control of NF-κB cis-elements (cis-NF-κBEGFP). SME significantly blocked LPS-induced EGFP expression and IκBα phosphorylation in intestinal explants and primary IECs, respectively. However, salvianolic acid B, an activate component of SME did not inhibit NF-κB transcriptional activity and IκB phosphorylation/degradation in IEC-18 cells. These results indicate that SME blocks LPS-induced NF-κB signalling pathway by targeting the IKK complex in intestinal epithelial cells. Modulation of bacterial product-mediated NF-κB signalling by natural plant extracts may represent an attractive strategy towards the prevention and treatment of intestinal inflammation

Physico-chemical Studies in Non-aqueous Solvents: Part XV-Conductance Studies of Some Uni-univalent Electrolytes in Nitromethane at 25°

687-69

Compressed Gaussian Estimation under Low Precision Numerical Representation.

This paper introduces a novel method for computationally efficient Gaussian estimation of high-dimensional problems such as Simultaneous Localization and Mapping (SLAM) processes and for treating certain Stochastic Partial Differential Equations (SPDEs). The authors have presented the Generalized Compressed Kalman Filter (GCKF) framework to reduce the computational complexity of the filters by partitioning the state vector into local and global and compressing the global state updates. The compressed state update, however, still suffers from high computational costs, making it challenging to implement on embedded processors. We propose a low-precision numerical representation for the global filter, such as 16-bit integer or 32-bit single-precision formats for the global covariance matrix, instead of the expensive double-precision, floating-point representation (64 bits). This truncation can inevitably cause filter instability since the truncated covariance matrix becomes overoptimistic or even turns to be an invalid covariance matrix. We introduce a Minimal Covariance Inflation (MCI) method to make the filter consistent while minimizing the truncation errors. Simulation-based experiments results show significant improvement of the proposed method with a reduction in the processing time with minimal loss of accuracy