Dissolved organic carbon (DOC) has been proposed as an indicator of compost maturity and stability. Further fractionation of compost DOC may be useful for determining how particular composting conditions will influence DOC quality. Eleven composts ranging in input materials and processing techniques were analyzed; concentrations of DOC ranged from 428 mg kg(-1) to 7300 mg kg(-1). Compost DOC was qualified by fractionation into pools of humic acids (HA), fulvic acids (FA), hydrophobic neutrals (HoN), and hydrophilic (Hi) compounds. The range in proportion of DOC pools was highly variable, even for composts with similar total DOC concentrations. Longer composting time and higher temperatures consistently corresponded with a depletion of hydrophilics, suggesting a preferential turnover of these compounds during the thermophilic composting phase. Qualification of DOC pools through fractionation may be an informative tool in predicting the effects of a processing technique on compost quality and, ultimately, soil functional processes.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.biortech.2014.12.054 | DOI Listing |
Radiology
January 2025
From the Department of Cardiology (T.P., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), MIRACL.ai (Multimodality Imaging for Research and Analysis Core Laboratory: and Artificial Intelligence) (T.P., S.T., K.H., T.G., A.L., E.G., A.U., J.G.D., P.H.), Inserm MASCOT-UMRS 942 (T.P., K.H., T.A.S., T.G., A.L., E.G., A.U., J.G.D., P.H.), and Department of Radiology (T.P., V.B., L.H., T.G.), Université Paris Cité, University Hospital of Lariboisière, Assistance Publique-Hôpitaux de Paris, Paris, France; Cardiovascular Magnetic Resonance Laboratory (T.P., T.H., T.U., F.S., S.C., P.G., J.G.) and Cardiac Computed Tomography Laboratory (T.P., T.H., T.L., B.C., T.U., F.S., S.C., H.B., A.N., M.A., P.G., J.G.), Hôpital Privé Jacques Cartier, Institut Cardiovasculaire Paris Sud, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300 Massy, France; Scientific Partnerships, Siemens Healthcare France, Saint-Denis, France (S.T.); Department of Cardiology, Hôpital Universitaire de Bruxelles-Hôpital Erasme, Brussels, Belgium (A.U.); and Department of Cardiovascular Imaging, American Hospital of Paris, Neuilly, France (O.V., M.S.).
Background Multimodality imaging is essential for personalized prognostic stratification in suspected coronary artery disease (CAD). Machine learning (ML) methods can help address this complexity by incorporating a broader spectrum of variables. Purpose To investigate the performance of an ML model that uses both stress cardiac MRI and coronary CT angiography (CCTA) data to predict major adverse cardiovascular events (MACE) in patients with newly diagnosed CAD.
View Article and Find Full Text PDFThe EFSA Panel on Food Contact Materials (FCM) assessed the safety of the recycling process NGR LSP (EU register number RECYC328). The input is hot washed and dried poly(ethylene terephthalate) (PET) flakes mainly originating from collected post-consumer PET containers, with no more than 5% PET from non-food consumer applications. The flakes are dried (step 2), melted in an extruder (step 3) and decontaminated during a melt-state polycondensation step under high temperature and vacuum (step 4).
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Institute of Mathematical Sciences Centre for Health Analytics and Modelling (CHaM), Strathmore University, Nairobi, Kenya.
Background: Measures of diagnostic test accuracy provide evidence of how well a test correctly identifies or rules-out disease. Commonly used diagnostic accuracy measures (DAMs) include sensitivity and specificity, predictive values, likelihood ratios, area under the receiver operator characteristic curve (AUROC), area under precision-recall curves (AUPRC), diagnostic effectiveness (accuracy), disease prevalence, and diagnostic odds ratio (DOR) etc. Most available analysis tools perform accuracy testing for a single diagnostic test using summarized data.
View Article and Find Full Text PDFNat Chem Biol
January 2025
Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA.
Nucleoside triphosphate (NTP)-dependent protein assemblies such as microtubules and actin filaments have inspired the development of diverse chemically fueled molecular machines and active materials but their functional sophistication has yet to be matched by design. Given this challenge, we asked whether it is possible to transform a natural adenosine 5'-triphosphate (ATP)-dependent enzyme into a dissipative self-assembling system, thereby altering the structural and functional mode in which chemical energy is used. Here we report that FtsH (filamentous temperature-sensitive protease H), a hexameric ATPase involved in membrane protein degradation, can be readily engineered to form one-dimensional helical nanotubes.
View Article and Find Full Text PDFAJNR Am J Neuroradiol
January 2025
From the Orthopedic Data Innovation Lab (ODIL), Hospital for Special Surgery (A.M.L.S., M.A.F.), Department of Radiology and Imaging, Hospital for Special Surgery Centre (E.E.X, Z.I, E.T.T, D.B.S, J.L.C)and Department of Population Health Sciences, Weill Cornell Medicine (M.A.F), New York, New York, USA.
Background And Purpose: To train and evaluate an open-source generative adversarial networks (GANs) to create synthetic lumbar spine MRI STIR volumes from T1 and T2 sequences, providing a proof-of-concept that could allow for faster MRI examinations.
Materials And Methods: 1817 MRI examinations with sagittal T1, T2, and STIR sequences were accumulated and randomly divided into training, validation, and test sets. GANs were trained to create synthetic STIR volumes using the T1 and T2 volumes as inputs, optimized using the validation set, then applied to the test set.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!