J, Volume 6, Issue 4 (December 2023) – 7 articles

This study aims to improve the computational efficiency of the frequency domain analysis of medium-frequency transformers (MFTs) with the presence of large clearance distances and fine foil windings. The winding loss and magnetic energy in MFTs in the medium-frequency range are calculated utilizing a finite element method (FEM) using common triangular and alternative rectilinear mesh elements. Additionally, in order to improve the computational efficiency of the calculations, a spectral element method (SEM) is coupled with a FEM, thus creating a hybrid FEM–SEM formulation. In such a hybrid approach, the FEM is used to calculate the current density distribution in the two-dimensional (2D) cross-section of the foil conductors to achieve reliable accuracy, and the SEM is adopted in the nonconducting clearance distances of the winding window to reduce the system of equations. The comparative analysis of the calculated resistance and reactance of the under-study models showed that the FEM with rectilinear mesh elements and the FEM–SEM model outperformed the FEM with triangular mesh elements in terms of accuracy and computational cost. The hybrid FEM–SEM model enables a reduced system of equations for modeling the electromagnetic behavior of MFTs. This research provides valuable insights into both the computational approaches and meshing challenges in the analysis of MFTs and offers a foundation for future research on the design and optimization of MFTs. Full article

Lipopolysaccharides are components of Gram-negative bacteria. The relationship between blood lipopolysaccharide levels and health status has mainly been investigated in Europe, and there is a lack of information about Asia, particularly Japan. This study aimed to investigate the relationship between blood lipopolysaccharide levels and health status in the Japanese. We conducted two cross-sectional studies in 36 healthy subjects (Study 1) and 36 patients with abnormal glucose metabolism (AGM; Study 2). The plasma lipopolysaccharide concentration in healthy subjects was positively correlated with body mass index. The plasma lipopolysaccharide concentration in AGM patients was obviously higher than that in healthy subjects. Furthermore, in AGM patients, the plasma lipopolysaccharide concentration was positively correlated with C-peptide, fasting plasma glucose levels, triglycerides, and stage of diabetic nephropathy. The plasma lipopolysaccharide concentration was also negatively correlated with 20/(C-peptide × fasting plasma glucose), an indicator of insulin resistance, and high-density lipoprotein cholesterol. In particular, the correlation between plasma lipopolysaccharide concentration and triglycerides in AGM patients was maintained in multiple regression analyses adjusted for age, sex, or body mass index. These results suggest a possible role of lipopolysaccharides in obesity in healthy subjects and in the deterioration of triglyceride metabolism in AGM patients in the Japanese population. Full article

This study evaluated the phytochemical composition and antioxidant activity of Piliostigma thonningii (Schumach.) Milne-Redh, Psorospermum febrifugum Spach, Inula glomerata Oliv. and Hiern, Zanthoxylum chalybeum Engl. and Monotes africanus A.DC., claimed to treat cancer by Malawian traditional herbal practitioners. Ground and dried plant extracts were analyzed for total phenolic content (TPC), total flavonoid content (TFC), total alkaloid content (TAC), ferric reducing antioxidant power (FRAP) and 2,2-Diphenyl-1-Picrylhydrazyl (DPPH) using standard assays. The TPC, TFC, and TAC ranged from 539 ± 2.70 to 4602 ± 32 mg GAE/g DW, 6.18 ± 0.03 to 64.04 ± 0.16 mg QE/g DW and 19.25 ± 0.07 to 76.05 ± 0.36 mg CE/g DW, respectively, and the variations were significant, p < 0.05. FRAP values ranged from 82.15 ± 0.7 to 687.28 ± 0.71 mg TEAC/g DW and decreased in the following order: P. thoningii (Schumach.) Milne-Redh > P. febrifugum Spach > M. africanus A.DC > Z. chalybeum Engl > I. glomerata Oliv. and Hiern. The scavenging activity (SA₅₀) of the extracts ranged from 0.09 ± 0.01 to 1.57 ± 0.01 μg/mL of extract with P. thonningii (Schumach.) Milne-Redh showing the lowest value. Based on the levels of phenolic compounds and their antioxidant activity, the plants in this study could be considered for use as medicinal agents and sources of natural bioactive compounds and antioxidants. Full article

Data visualization plays a crucial role in gaining insights from high-dimensional datasets. ISOMAP is a popular algorithm that maps high-dimensional data into a lower-dimensional space while preserving the underlying geometric structure. However, ISOMAP can be computationally expensive, especially for large datasets, due to the computation of the pairwise distances between data points. The motivation behind this study is to improve efficiency by leveraging an approximate method, which is based on random kitchen sinks (RKS). This approach provides a faster way to compute the kernel matrix. Using RKS significantly reduces the computational complexity of ISOMAP while still obtaining a meaningful low-dimensional representation of the data. We compare the performance of the approximate ISOMAP approach using RKS with the traditional t-SNE algorithm. The comparison involves computing the distance matrix using the original high-dimensional data and the low-dimensional data computed from both t-SNE and ISOMAP. The quality of the low-dimensional embeddings is measured using several metrics, including mean squared error (MSE), mean absolute error (MAE), and explained variance score (EVS). Additionally, the runtime of each algorithm is recorded to assess its computational efficiency. The comparison is conducted on a set of protein sequences, used in many bioinformatics tasks. We use three different embedding methods based on k-mers, minimizers, and position weight matrix (PWM) to capture various aspects of the underlying structure and the relationships between the protein sequences. By comparing different embeddings and by evaluating the effectiveness of the approximate ISOMAP approach using RKS and comparing it against t-SNE, we provide insights on the efficacy of our proposed approach. Our goal is to retain the quality of the low-dimensional embeddings while improving the computational performance. Full article

The biogenic synthesis of copper oxide nanoparticles was explored using the Myriophyllum spicatum plant through a process involving co-precipitation and was utilized as an effective photocatalyst for the reduction of Cr(VI) and Pb(II) ions in an aqueous solution. The plant-mediated CuO nanoparticles were characterized using microscopic techniques (TEM and SEM), FT-IR, and XRD analyses. The amount of the reduced metal ions was determined by UV–visible and Atomic Absorption (AA) spectrophotometers. The analyses of the functional group present in the leaf extract revealed the type of bioactive molecules that were involved in the formation of copper oxide nanoparticles. The nanoparticles were used in the photo-enhanced reduction of hexavalent Cr and divalent Pb ions, and the impact of solution pH, initial metal concentrations, and photocatalyst dosage was investigated to establish the optimal performance of the CuO nanoparticles. Results revealed a direct association between the reduction of metal ions and catalyst dosage in both cases. A maximum percentage reduction of 89.2% and 79.1% was achieved for Cr(VI) and Pb(II), respectively, using 3 g of the CuO nanoparticles. This confirms that the CuO nanoparticles exhibited higher efficiency for Cr(VI) reduction as compared to Pb(II) reduction and indicates that CuO nanoparticles are a promising photocatalyst that is capable of reducing these metal ions into less toxic products. Full article

The friction factor is a widely used parameter in characterizing flow resistance in pipes and open channels. Recently, the application of machine learning and artificial intelligence (AI) has found several applications in water resource engineering. With this in view, the application of artificial intelligence techniques on Moody’s diagram for predicting the friction factor in pipe flow for both transition and turbulent flow regions has been considered in the present study. Various AI methods, like Random Forest (RF), Random Tree (RT), Support Vector Machine (SVM), M5 tree (M5), M5Rules, and REPTree models, are applied to predict the friction factor. While performing the statistical analysis (root-mean-square error (RMSE), mean absolute error (MAE), squared correlation coefficient (R²), and Nash–Sutcliffe efficiency (NSE)), it was revealed that the predictions made by the Random Forest model were the most reliable when compared to other AI tools. The main objective of this study was to highlight the limitations of artificial intelligence (AI) techniques when attempting to effectively capture the characteristics and patterns of the friction curve in certain regions of turbulent flow. To further substantiate this behavior, the conventional algebraic equation was used as a benchmark to test how well the current AI tools work. The friction factor estimates using the algebraic equation were found to be even more accurate than the Random Forest model, within a relative error of ≤±1%, in those regions where the AI models failed to capture the nature and variation in the friction factor. Full article

Increasingly sophisticated techniques for falsifying and forging legal documents demand non-destructive and accurate analysis methods. Researchers have extensively investigated ink discrimination through an interdisciplinary analysis involving Raman spectroscopy and chemometrics, which is now regarded as a leading forensic document analysis approach. In this study, a groundbreaking method was developed to identify the specific origin of blue-ink pens used in written documents. By employing Raman spectroscopy in conjunction with principal component analysis (PCA), we successfully differentiated between 45 different blue-ink pens used on various documents. The Raman spectroscopy analysis provided a visual examination of each blue ink’s unique Raman signature, and PCA was then applied to the processed spectral data. Moreover, we successfully distinguished highly similar ink types in documents through the combined use of Raman spectroscopy, Pearson’s correlation analysis, and a statistical approach (PCA). Full article