32 research outputs found
A Non-intrusive Approach for Physics-constrained Learning with Application to Fuel Cell Modeling
A data-driven model augmentation framework, referred to as Weakly-coupled
Integrated Inference and Machine Learning (IIML), is presented to improve the
predictive accuracy of physical models. In contrast to parameter calibration,
this work seeks corrections to the structure of the model by a) inferring
augmentation fields that are consistent with the underlying model, and b)
transforming these fields into corrective model forms. The proposed approach
couples the inference and learning steps in a weak sense via an alternating
optimization approach. This coupling ensures that the augmentation fields
remain learnable and maintain consistent functional relationships with local
modeled quantities across the training dataset. An iterative solution procedure
is presented in this paper, removing the need to embed the augmentation
function during the inference process. This framework is used to infer an
augmentation introduced within a Polymer electrolyte membrane fuel cell (PEMFC)
model using a small amount of training data (from only 14 training cases.)
These training cases belong to a dataset consisting of high-fidelity simulation
data obtained from a high-fidelity model of a first generation Toyota Mirai.
All cases in this dataset are characterized by different inflow and outflow
conditions on the same geometry. When tested on 1224 different configurations,
the inferred augmentation significantly improves the predictive accuracy for a
wide range of physical conditions. Predictions and available data for the
current density distribution are also compared to demonstrate the predictive
capability of the model for quantities of interest which were not involved in
the inference process. The results demonstrate that the weakly-coupled IIML
framework offers sophisticated and robust model augmentation capabilities
without requiring extensive changes to the numerical solver
Ph3P Catalyzed Synthesis of Alkyl 2-(4-Oxopyridin-1(4H)-yl)acrylates by Nucleophilic Addition to Alkyl Propiolates
4-Hydroxypyridine undergoes a smooth reaction with alkyl propiolates in the presence of triphenylphosphine to produce and Ī²-substituted alkyl acrylate products. When the reaction was performed with 4-hydroxyquinoline onlyĀ Ī±-substituted alkyl acrylates were obtained.Keywords: 4-hydroxypyridine, 4-hydroxyquinoline, Alkyl Acrylates, Alkyl Propiolates, Triphenylphosphin
Synthesis and characterization of functionalized dihydropyrimidinones via one-pot isocyanide-based three-component reaction of N-formyl urea and dialkyl ACETYLENEDICARBOXYLATES
The reactive intermediate generated by the addition of alkyl isocyanides to dialkyl acetylenedicarboxylates was trapped by N-formyl urea to produce highly functionalized dihydropyrimidinones in fairly good yields
Direct electrochemical detection of clozapine by RuO2 nanoparticles-modified screen-printed electrode
This study introduces the sensitive electrochemical detection of clozapine with the use of a ruthenium(iv) oxide nanoparticle (RuO2 NP)-modified screen-printed electrode (RuO2 NPs/SPE). The electrochemical behaviors of clozapine at RuO2 NP/SPE have been examined via cyclic voltammetry (CV), differential pulse voltammetry (DPV) and chronoamperometry (CHA). According to the results, the modified electrode has been accompanied by a decreasing over-potential (ca. 170 mV) and enhancement in the peak current (3 times) in comparison with the bare SPE. The results indicated that RuO2 NP/SPE markedly augmented electro-catalytic activities toward clozapine oxidation. In addition, linear responses have been observed in the range between 0.2 and 500.0 ĆĀ¼M with a sensitivity of 0.076 ĆĀ¼A ĆĀ¼M-1 and a limitation of detection of 0.07 ĆĀ¼M (3Ćļæ½). Moreover, the successful application of RuO2 NP/SPE has been seen in detecting clozapine in real samples, which showed satisfied recoveries. Therefore, outputs suggest that RuO2 NP/SPE will be promising for functional utilization. ĆĀ© 2020 The Royal Society of Chemistry
Transcriptome Analysis of Human Diabetic Kidney Disease
OBJECTIVE: Diabetic kidney disease (DKD) is the single leading cause of kidney failure in the U.S., for which a cure has not yet been found. The aim of our study was to provide an unbiased catalog of gene-expression changes in human diabetic kidney biopsy samples. RESEARCH DESIGN AND METHODS: Affymetrix expression arrays were used to identify differentially regulated transcripts in 44 microdissected human kidney samples. DKD samples were significant for their racial diversity and decreased glomerular filtration rate (~25ā35 mL/min). Stringent statistical analysis, using the Benjamini-Hochberg corrected two-tailed t test, was used to identify differentially expressed transcripts in control and diseased glomeruli and tubuli. Two different web-based algorithms were used to define differentially regulated pathways. RESULTS: We identified 1,700 differentially expressed probesets in DKD glomeruli and 1,831 in diabetic tubuli, and 330 probesets were commonly differentially expressed in both compartments. Pathway analysis highlighted the regulation of Ras homolog gene family member A, Cdc42, integrin, integrin-linked kinase, and vascular endothelial growth factor signaling in DKD glomeruli. The tubulointerstitial compartment showed strong enrichment for inflammation-related pathways. The canonical complement signaling pathway was determined to be statistically differentially regulated in both DKD glomeruli and tubuli and was associated with increased glomerulosclerosis even in a different set of DKD samples. CONCLUSIONS: Our studies have cataloged gene-expression regulation and identified multiple novel genes and pathways that may play a role in the pathogenesis of DKD or could serve as biomarkers
Fabrication of magnetic iron oxide-supported copper oxide nanoparticles (Fe3O4/CuO): Modified screen-printed electrode for electrochemical studies and detection of desipramine
The present investigation examines a sensitive electrochemical technique to detect desipramine through Fe3O4/CuO nanoparticles (NPs). Fe3O4/CuO NPs were synthesized via a coprecipitation procedure, and the products were characterized via energy disperse spectroscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and vibrating sample magnetometer. The voltage-current curve and differential pulse voltammetry examinations of Fe3O4/CuO-modified screen-printed electrode (Fe3O4/CuO/SPE) were followed by the determination of electro-catalytic activities toward desipramine oxidation in a phosphate buffer solution (pH = 7.0). In addition, the value of diffusion coefficient (D = 3.0 Ćļæ½ 10-6 cm2 s-1) for desipramine was calculated. Then, based on the optimum conditions, it was observed that the currents of the oxidation peak were linearly proportionate to the concentration of desipramine in the broad range between 0.08 and 400.0 ĆĀ¼M and LOD of 0.03 ĆĀ¼M (S/N = 3). Finally, our new sensor was successfully utilized to detect desipramine in the real samples, with reasonable recovery in the range of 97.2 to 102.7. This journal is ĆĀ© 2020 The Royal Society of Chemistry