Computer aided decision support system for mitral valve diagnosis and classification using depthwise separable convolution neural network

Multimedia Tools and Applications - The significance of mitral valve (MV) treatment is increasing recently because of an aging population. The computer vision-based acquisition and quantification...     

Solvent Free Microwave Assisted Isomerization of N‐Nitropyrazoles

This paper describes solvent‐free isomerization of N‐nitropyrazoles under microwave irradiation to achieve a new green chemistry procedure for the synthesis of C‐ nitropyrazoles in good to excellent yields. The presented procedure requires less time, offers simplified workup procedure, needs no obnoxious solvents, and may be used for the preparation of several C‐nitropyrazoles.     

Modal Analysis of Induction Generator Based Wind Farm Connected to Series-compensated Transmission Line and Line Commutated Converter High-Voltage DC Transmission Line

This article presents a comprehensive analysis of the potential of sub-synchronous resonance in induction generator based wind farms connected to a line commutated converter based high-voltage DC transmission line. Since series-compensated lines are also known to cause sub-synchronous resonance in induction generator based (Type 1) wind farms, this study also considers a series-compensated line in parallel with the high-voltage DC line for the investigation of sub-synchronous resonance potential. The CIGRE benchmark high-voltage DC system and the IEEE first benchmark system are considered as the study system components. A linearized state-space model of the study system is developed for eigenvalue analysis followed by participation factor analysis. A sensitivity study of the sub-synchronous resonance modes with respect to variation in different model parameters, such as rectifier firing angle, DC line power flow, and series compensation level, is also reported. It is found that the high-voltage DC rectifier station current regulator does not interact with any of the sub-synchronous modes of the wind farm. However, in the event that the high-voltage DC line is blocked during a contingency, the wind farm will operate radially with the series-compensated line and may experience sub-synchronous resonance oscillation due to the induction generator effect.     

Long-term Sector-wise Electrical Energy Forecasting Using Artificial Neural Network and Biogeography-based Optimization

This article presents a hybrid model involving artificial neural networks and biogeography-based optimization for long-term forecasting of India's sector-wise electrical energy demand. It involves socio-economic indicators, such as population and per capita gross domestic product, and uses two artificial neural networks, which are trained through a biogeography-based optimization algorithm with a goal of perfect mapping of the input–output data in the non-linear space through obtaining the global best weight parameters. The biogeography-based optimization based training of the artificial neural network improves the forecasting accuracy and avoids trapping in local optima besides enhancing the convergence to the lowest mean squared error at the minimum number of iterations than existing approaches. The model requires an input and the year of the forecast and predicts the sector-wise energy demand. Forecasts up to the year 2025 are compared with those of the regression model, the artificial neural network model trained by back-propagation, and the artificial neural network model trained by harmony search algorithm to exhibit its effectiveness.     

Conformation Analysis of GalNAc‐Appended Sugar Amino Acid Foldamers as Glycopeptide Mimics

Sugar amino acid (SAA)‐based foldamers with well‐defined secondary structures were appended with N‐acetylgalactosamine (GalNAc) sugars to access sequence‐defined, multidentate glycoconjugates with full control over number, spacing and position. Conformation analysis of these glycopeptides by extensive NMR spectroscopic studies revealed that the appended GalNAc units had a profound influence on the native conformational behaviour of the SAA foldamers. Whereas the 2,5‐cis glycoconjugate showed a helical structure in water, comprising of two consecutive 16‐membered hydrogen bonds, its 2,5‐trans congener displayed an unprecedented 16/10‐mixed turn structure not seen before in any glycopeptide foldamer.     

A survey of multiscale modeling: Foundations,historical milestones,current status,and future prospects

Research problems in the domains of physical, engineering, biological sciences often span multiple time and length scales, owing to the complexity of information transfer underlying mechanisms. Multiscale modeling (MSM) and high-performance computing (HPC) have emerged as indispensable tools for tackling such complex problems. We review the foundations, historical developments, and current paradigms in MSM. A paradigm shift in MSM implementations is being fueled by the rapid advances and emerging paradigms in HPC at the dawn of exascale computing. Moreover, amidst the explosion of data science, engineering, and medicine, machine learning (ML) integrated with MSM is poised to enhance the capabilities of standard MSM approaches significantly, particularly in the face of increasing problem complexity. The potential to blend MSM, HPC, and ML presents opportunities for unbound innovation and promises to represent the future of MSM and explainable ML that will likely define the fields in the 21st century.     

Dynamic analysis and split range control for maximization of operating range of continuous microbial fuel cell

Human development is inherently connected with availability of water and energy. Energy production requires water, whereas water treatment needs energy. On the other hand, microbial fuel cell has capability to produce energy and water simultaneously from waste water or organic matter. In this paper, first principle-based model of variable volume microbial fuel cell is simulated. Hydraulic retention time is selected as the manipulated variable using the study of steady state and dynamic responses. Classical PI and model predictive control strategies are developed for controlling the produced power from the cell, and its performance is tested for servo problem. Settling time for positive and negative set points is found to be 126 and 889 h in case of classical PI and 120 and 750 h in case of linear MPC, respectively along with large increase (three times order of magnitude) in working volume for negative set point. These control challenges are overcome by using split range controller with variable and constant volume microbial fuel cells. The settling time for negative set point is found to be 49 and 21 h for classical PI and linear MPC schemes, respectively, which is significantly lower than using only variable volume microbial fuel cell. Also, there is no increase in the working volume of the constant volume microbial fuel cell. Hence, operating range of the microbial fuel cell is enhanced using split range controller.     

Evaluation and Predictive Model Development of Oxidative Stability of Biodiesel on Storage

Biodiesel comprises mono-alkyl esters of long-chain fatty acid methyl esters (FAME) derived from a renewable lipid feedstock. A major technical issue with the use of biodiesel is that it is more prone to oxidation during storage, when compared to petroleum fuel, due to the high content of polyunsaturated methyl esters that are easily oxidizable to compounds such as acids, aldehydes, and alcohols. Biodiesel (Jatropha and Pongamia) and antioxidants (Turmeric and butylated hydroxytoulene) were used for this study. We found that the acid value and viscosity for pongamia biodiesel increased significantly by 41.17% and 44.0% and that for jatropha biodiesel increased by 31.5% and 37.0%, respectively, after being stored for 3 months. The impact of antioxidants on the storage stability of biodiesel was examined according to the ASTM D4625 12-week procedure, and best results were found at a concentration level of 2500 ppm. The specific objective of this investigation is to develop models to determine the viscosity of biodiesel at any time “t” during long-term storage based on these experimental trials for upto 12 weeks. In addition, the models were used to predict the level of antioxidants that are to be added to biodiesel in order to minimize the effects of oxidative degradation during storage. The developed model recorded an adjusted R² of 0.86 and a modeling efficiency of 0.88.     

The Distribution of Fatty Acid Biomarkers of Dairy Intake across Serum Lipid Fractions: The Prospective Metabolism and Islet Cell Evaluation (PROMISE) Cohort

Circulating fatty acids (FA) derived largely from dairy consumption have most commonly been measured in total human serum or phospholipid (PL) fractions, and have been used as validated biomarkers of dairy intake in a growing number of epidemiological studies. Nevertheless, measurement and characterization of a wider spectrum of FA biomarkers of dairy across the four major serum lipid fractions is lacking. This study aimed to (1) quantify FA biomarkers of dairy in PL, triacylglycerol (TAG), cholesteryl ester (CE), and unesterified fatty acid (FFA) serum lipid fractions; and (2) identify potential demographic and metabolic factors that may modify the proportions of these FA across serum fractions. Baseline data from 444 adults in the PROMISE cohort were analyzed. FA biomarkers, 15:0, t16:1n-7, 18:2-c9,t11, and t18:1n-7 were quantified from serum. Dairy intake was estimated using the validated Canadian Diet History Questionnaire. Our results show that t18:1n-7 was the most abundant FA biomarker in all fractions except CE, where 18:2-c9,t11 was the most abundant. Positive correlations within fractions, and across FA in the PL, CE, and FFA fractions were found, however, TAG FA were negatively correlated with the other fractions. PL and CE FA were positively associated with dairy intake, and negatively associated with markers of dysmetabolism while, in contrast, these markers were predictors of higher TAG dairy FA. This study is the first to demonstrate distinct proportions of dairy FA in different serum lipid fractions. PL and CE FA marked dairy intake in this cohort, while TAG FA appeared to be markers of dysmetabolism.