Stability analysis of two-terminal HVDC transmission systems using SISO open-loop gains

The ports of a three-phase voltage source converter have multiple frequency electrical parameters, which makes HVDC systems with these converters present multiple input multiple output (MIMO) characteristics. The generalized Nyquist criterion of the MIMO model is often used to analyze the system stability. However, this model is more difficult to obtain than the single-input single-output (SISO) model, and the stability margin and the oscillation frequency band are difficult to capture. To solve these problems, this paper took the two-terminal HVDC transmission system as the research object to derive a SISO model that can be measured by a port. Moreover, this study also proposed a method for analyzing the system stability through envelope SISO open-loop gains. Finally, the key port and parameters affecting the system stability were analyzed according to the stability margin, which provided theoretical support for the design of the system parameters. The established model and the proposed analysis method were verified in a MATLAB/Simulink simulation model

Application of Magnetic Nanoseparation Technology in Rapid Detection of Foodborne Pathogens

Foodborne pathogens are important factors that contribute to foodborne illnesses, posing significant threats to food safety and human health, and presenting a major challenge for global healthcare systems. Contaminated food matrices are complex and often have low concentrations of early-stage pathogens, which hinder the sensitivity of existing detection methods. Traditional microbial culture methods are typically used to increase the concentration of pathogens for detection purposes, but these methods are time-consuming and labor-intensive, making them inadequate for the rapid testing needs of regulatory authorities. Therefore, there is an urgent need for effective methods of isolating and enriching foodborne pathogens to accurately detect early-stage contamination in food and ensure food safety. In recent years, magnetic nanoparticles have been extensively studied. By modifying their surfaces with recognition elements that can specifically bind to pathogens, they can effectively isolate and enrich foodborne pathogens in complex food matrices. When combined with existing highly sensitive detection methods, these magnetic nanoparticles enable rapid early-stage detection of foodborne pathogens. This article provides an overview of Magnetic nanoseparation technology, the coupling methods of magnetic nanoparticles with recognition elements, the types of recognition elements, and the application of combined detection methods. The aim is to provide reference for the development of rapid detection methods for foodborne pathogens

Grey relational analysis model with cross-sequences and its application in evaluating air quality index

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.It is important to detect the internal operating regularity in system developing with poor information. To identify the real relationship among multi factors, we propose a grey relational analysis (GRA) method inspired by the characteristics of sequences variation. The proposed model considers the changes of fluctuating sequences like cross-sequences both in domain time and between time intervals. To obtain the quantitative change about sequences, relative angle change is employed to determine the variation in each interval, and the relative angle oscillation change is utilized for measuring variations between intervals. To find the optimal time lag or time intervals, the corresponding cycles are extracted by time-delay models. The reliability of the proposed models will be verified through cases in identifying crucial factors for air quality, and the final detection will then be made. To compare with existing representative GRA models clearly, the relation between two fluctuating sequences shaped in cross-sequences is examined by the proposed model. The empirical results show that the relation degree between pollutants and air quality is reasonable. The compared experiment shows that the GRA for cross-sequences can effectively identify the relationship among fluctuating sequences and the impact of time-delay is small for the proposed model with similar shapes

Altered fecal microbiome and correlations of the metabolome with plasma metabolites in dairy cows with left displaced abomasum

Left displaced abomasum (LDA) in postpartum dairy cows contributes to significant economic losses. Dairy cows with LDA undergo excessive lipid mobilization and insulin resistance. Although gut dysbiosis is implicated, little is known about the role of the gut microbiota in the abnormal metabolic processes of LDA. To investigate the functional links among microbiota, metabolites, and disease phenotypes in LDA, we performed 16S rDNA gene amplicon sequencing and liquid chromatography-tandem mass spectrometry (LC-MS/MS) of fecal samples from cows with LDA (n = 10) and healthy cows (n = 10). Plasma marker profiling was synchronously analyzed. In the LDA event, gut microbiota composition and fecal metabolome were shifted in circulation with an amino acid pool deficit in dairy cows. Compared with the healthy cows, salicylic acid derived from microbiota catabolism was decreased in the LDA cows, which negatively correlated with Akkermansia, Prevotella, non-esterified fatty acid (NEFA), and β-hydroxybutyric acid (BHBA) levels. Conversely, fecal taurolithocholic acid levels were increased in cows with LDA. Based on integrated analysis with the plasma metabolome, eight genera and eight metabolites were associated with LDA. Of note, the increases in Akkermansia and Oscillospira abundances were negatively correlated with the decreases in 4-pyridoxic acid and cytidine levels, and positively correlated with the increases in NEFA and BHBA levels in amino acid deficit, indicating pyridoxal metabolism-associated gut dysbiosis and lipolysis. Changes in branched-chain amino acids implicated novel host-microbial metabolic pathways involving lipolysis and insulin resistance in cows with LDA. Overall, these results suggest an interplay between host and gut microbes contributing to LDA pathogenesis

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Nanotechnology in Cement-Based Materials: A Review of Durability, Modeling, and Advanced Characterization

In the context of increasing applications of various nanomaterials in construction, this work reviews the renewed knowledge of nanotechnology in cement-based materials, focusing on the relevant papers published over the last decade. The addition of nanomaterials in cement-based materials, associated with their dispersion in cement composites, is explored to evaluate their effects on the resistance of cement-based materials to physical deteriorations, chemical deteriorations, and rebar corrosion. This review also examines the proposed nanoscale modeling of interactions between admixed nanomaterials and cement hydration products. At last, the recent progress of advanced characterization that employs techniques to characterize the properties of cement-based materials at the nanoscale is summarized

In situ grown nanoscale platinum on carbon powder as catalyst layer in proton exchange membrane fuel cells (PEMFCs)

An extensive study has been conducted on the proton exchange membrane fuel cells (PEMFCs) with reducing Pt loading. This is commonly achieved by developing methods to increase the utilization of the platinum in the catalyst layer of the electrodes. In this paper, a novel process of the catalyst layers was introduced and investigated. A mixture of carbon powder and Nafion solution was sprayed on the glassy carbon electrode (GCE) to form a thin carbon layer. Then Pt particles were deposited on the surface by reducing hexachloroplatinic (IV) acid hexahydrate with methanoic acid. SEM images showed a continuous Pt gradient profile among the thickness direction of the catalytic layer by the novel method. The Pt nanowires grown are in the size of 3 nm (diameter)×10 nm (length) by high solution TEM image. The novel catalyst layer was characterized by cyclic voltammetry (CV) and scanning electron microscope (SEM) as compared with commercial Pt/C black and Pt catalyst layer obtained from sputtering. The results showed that the platinum nanoparticles deposited on the carbon powder were highly utilized as they directly faced the gas diffusion layer and offered easy access to reactants (oxygen or hydrogen).</p