In this study, we develop a generalized classification scheme for toroidal (TCNT) and helical carbon nanotubes (HCNT) containing both pentagons and heptagons simultaneously. We show that a particular class of TCNTs with n-fold rotational symmetry and well-defined latitude coordinates can be uniquely characterized by a set of four indices, and each of the indices can be linked to the relative arrangement of pentagons and heptagons in the corresponding torus. Chiral isomers or the corresponding helical derivatives, HCNTs, can also be readily derived either by introducing a chiral vector or dissecting a distorted TCNT through certain longitude. This generalized scheme can generate the whole family of fullerenes with genus one, ranging from giant TCNTs down to small ones containing only a few hundred atoms. To the best of our knowledge, almost all of the construction methods for TCNTs in the literature belong to special cases of our generalized classification scheme.
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http://dx.doi.org/10.1021/ci800395r | DOI Listing |
Microbiol Spectr
January 2025
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Considering that the human microbiota plays a critical role in health and disease, an accurate and high-resolution taxonomic classification is thus essential for meaningful microbiome analysis. In this study, we developed an automatic system, named MultiTax pipeline, for generating taxonomy from full-length 16S rRNA sequences using the Genome Taxonomy Database and other existing reference databases. We first constructed the MultiTax-human database, a high-resolution resource specifically designed for human microbiome research and clinical applications.
View Article and Find Full Text PDFCancer Prev Res (Phila)
January 2025
Rice University, Houston, Texas, United States.
Oral cancer is a major global health problem. It is commonly diagnosed at an advanced stage although often preceded by clinically visible oral mucosal lesions, termed oral potentially malignant disorders associated with an increased risk for oral cancer development. There is an unmet clinical need for effective screening tools to assist front-line healthcare providers to determine which patients should be referred to an oral cancer specialist for evaluation.
View Article and Find Full Text PDFAnal Methods
January 2025
Jiangsu Beier Machinery Co. Ltd, Jiangsu, 215600, China.
Plastic waste management is one of the key issues in global environmental protection. Integrating spectroscopy acquisition devices with deep learning algorithms has emerged as an effective method for rapid plastic classification. However, the challenges in collecting plastic samples and spectroscopy data have resulted in a limited number of data samples and an incomplete comparison of relevant classification algorithms.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Lehrstuhl für Theoretische Chemie, Universität Erlangen-Nürnberg, Egerlandstr. 3, D-91058 Erlangen, Germany.
Methods based on density-functional theory usually treat open-shell atoms and molecules within the spin-unrestricted Kohn-Sham (KS) formalism, which breaks symmetries in real and spin space. Symmetry breaking is possible because the KS Hamiltonian operator does not need to exhibit the full symmetry of the physical Hamiltonian operator, but only the symmetry of the spin density, which is generally lower. Symmetry breaking leads to spin contamination and prevents a proper classification of the KS wave function with respect to the symmetries of the physical electron system.
View Article and Find Full Text PDFBioelectromagnetics
January 2025
Department of Electrical Engineering and ITEMS, University of Southern California, Los Angeles, California, USA.
As the clinical applicability of peripheral nerve stimulation (PNS) expands, the need for PNS-specific safety criteria becomes pressing. This study addresses this need, utilizing a novel machine learning and computational bio-electromagnetics modeling platform to establish a safety criterion that captures the effects of fields and currents induced on axons. Our approach is comprised of three steps: experimentation, model creation, and predictive simulation.
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