10 papers · ranked by Valyu relevance
Authors not listed
High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing dataset scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and…
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The integration of artificial intelligence technologies into pharmaceutical research is crucial for gaining an early understanding of molecular properties, thereby facilitating successful drug design. Constructing a machine learning (ML) model however, requires knowledge spanning from data preprocessing and feature…
Adarsh Arun, Jana Weber, Zhen Guo, Alexei Lapkin
As the chemical sector looks to decarbonize, one promising solution is the utilization of bio-feedstocks and biowaste to produce functional molecules. There is, therefore, great interest in understanding how and where to integrate these resources within chemical supply chains. To assist such efforts, screening…
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While Raman spectroscopy offers notable experimental advantages as a probe of complex mixtures, its application in practice often confronts samples that present an overwhelming fluorescence background. Here, we explore the efficacy of two particular Raman spectrometric strategies for quantitative analysis under…
Hunter Dlugas, Xiang Zhang, Seongho Kim
In mass spectrometry (MS)-based metabolomics, compound identification relies on Liquid Chromatography-MS (LC-MS) and Gas Chromatography-MS (GC-MS). The most popular and efficient approach for this purpose is the comparison of similarity scores between experimental spectra and reference spectra. Among the various single…
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Kinetic modeling is essential for predicting changes in food quality during processing and storage. This study evaluates the application of physics-informed neural networks (PINN) for food kinetic modeling, integrating kinetic insights into neural network frameworks. Based on three case studies, namely seed drying…
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We present TAPAS (Transient Absorption Processing and Analysis Software), an open-source, Python-based graphical platform that covers the entire transient absorption (TA) workflow, from raw data import and preprocessing to visualization, global and target fitting, and statistical evaluation. Users operate TAPAS through…
Aaron Liu, Myeongyeon Lee, Rahul Venkatesh, Jessica Bonsu + 4 more
Polymer-based semiconductors and organic electronics encapsulate a significant research thrust for informatics-driven materials development. However, device measurements are described by a complex array of design and parameter choices, many of which are sparsely reported. For example, the mobility of a polymer-based…
Keisuke Ozawa
Statistically weighted principal component analysis (wPCA) is widely used to reduce the noise of scanning transmission electron microscopy-energy-dispersive X-ray (STEM-EDX) spectroscopy data. It is beneficial to retain the spatial resolution of observation in each step of the analysis, but the direct application of…
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This work focuses on a novel human-centered digital assistant combining Mixed Reality (MR), Computer Vision and Machine Learning regression to guide professionals and students on how to operate and correctly parameterize battery manufacturing machinery. Our Concept article aim is to provide a proof of concept of our…