We developed and implemented a method-independent, fully numerical, finite difference approach to calculating nuclear magnetic resonance shieldings, using gauge-including atomic orbitals. The resulting capability can be used to explore non-standard methods, given only the energy as a function of finite-applied magnetic fields and nuclear spins. For example, standard second-order Møller-Plesset theory (MP2) has well-known efficacy for 1H and 13C shieldings and known limitations for other nuclei such as 15N and 17O. It is, therefore, interesting to seek methods that offer good accuracy for 15N and 17O shieldings without greatly increased compute costs, as well as exploring whether such methods can further improve 1H and 13C shieldings. Using a small molecule test set of 28 species, we assessed two alternatives: κ regularized MP2 (κ-MP2), which provides energy-dependent damping of large amplitudes, and MP2.X, which includes a variable fraction, X, of third-order correlation (MP3). The aug-cc-pVTZ basis was used, and coupled cluster with singles and doubles and perturbative triples [CCSD(T)] results were taken as reference values. Our κ-MP2 results reveal significant improvements over MP2 for 13C and 15N, with the optimal κ value being element-specific. κ-MP2 with κ = 2 offers a 30% rms error reduction over MP2. For 15N, κ-MP2 with κ = 1.1 provides a 90% error reduction vs MP2 and a 60% error reduction vs CCSD. On the other hand, MP2.X with a scaling factor of 0.6 outperformed CCSD for all heavy nuclei. These results can be understood as providing renormalization of doubles amplitudes to partially account for neglected triple and higher substitutions and offer promising opportunities for future applications.
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http://dx.doi.org/10.1063/5.0145130 | DOI Listing |
Clin Chem Lab Med
January 2025
School of Dentistry and Medical Science, Faculty of Science and Health, 110481 Charles Sturt University, Wagga Wagga, NSW, Australia.
This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence Review tool was used to formulate the keywords, and then a comprehensive literature search was performed using several databases, importing the search results directly into Covidence (n=379). Title, abstract screening, duplicate removal, and full-text screening were done.
View Article and Find Full Text PDFJ Food Sci Technol
February 2025
Department of Biochemistry, Faculty of Science, University of Dschang, Dschang, Cameroon.
Unlabelled: Production of instant cassava tuber flour for is an appealing process because of a significant reduction in cooking time, it involves less tedious preparation, the flour has improved odor with a significant increase in shelf life, and is of better quality. However, the optimum cassava fermentation and precooking parameters; two critical unit operations in the process, as well as their effects on the quality and shelf life of the product have not been studied elaborately. The Doehlert design was employed to optimize the fermentation and the precooking processes of cassava () tuber to produce instant flour for .
View Article and Find Full Text PDFFront Neurosci
January 2025
Graduate Program in Electrical Engineering, Federal University of Pará - UFPA, Belém, Brazil.
Introduction: Wavelet thresholding techniques are crucial in mitigating noise in data communication and storage systems. In image processing, particularly in medical imaging like MRI, noise reduction is vital for improving visual quality and accurate analysis. While existing methods offer noise reduction, they often suffer from limitations like edge and texture loss, poor smoothness, and the need for manual parameter tuning.
View Article and Find Full Text PDFJ Sci Food Agric
January 2025
Center of Research and Innovation, Asia International University, Bukhara, Uzbekistan.
Background: Wheat-maize cropping systems in semi-arid regions are expected to be affected by climate change in the future, which is alarming for global food security, environmental sustainability and socioeconomic development. Therefore, management practices like optimized plant geometry and fertilization need to be explored to counter these expected threats. To do this, the APSIM model was calibrated using 5-year data (from 2017/2018 to 2022) regarding yield, biomass, plant height, emergence, anthesis and crop maturity of wheat and maize from farmer fields.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; The Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Air-pollution monitoring is sparse across most of the United States, so geostatistical models are important for reconstructing concentrations of fine particulate air pollution (PM) for use in health studies. We present XGBoost-IDW Synthesis (XIS), a daily high-resolution PM machine-learning model covering the contiguous US from 2003 through 2023. XIS uses aerosol optical depth from satellites and a parsimonious set of additional predictors to make predictions at arbitrary points, capturing near-roadway gradients and allowing the estimation of address-level exposures.
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