Bis(μ-4-amino-3,5-dimethyl-4H-1,2,4-triazole)bis­[diiodidozinc(II)]

In the title compound, [Zn2I4(C4H8N4)2], the ZnII atom is coordinated in a distorted tetra­hedral geometry by two N atoms from the triazole rings of two 4-amino-3,5-dimethyl-4H-1,2,4-triazole (admt) ligands and two iodide ligands. Doubly bridging admt ligands connect two ZnII atoms, forming a centrosymmetric dimer. Weak N—H⋯I and C—H⋯I hydrogen bonds play an important role in the inter­molecular packing

Coexistence of superconductivity with exotic ferromagnetic state in pressurized non-superconducting UTe2_2

The discovery of superconductivity in heavy Fermion UTe$_2$, a candidate topological and triplet-paired superconductor, has aroused widespread interest. However, to date, superconductivity has only been reported in nonstoichiometric crystals of UTe$_2$ with a Te deficit. Here, we demonstrate that the application of uniaxial pressure induces superconductivity in stoichiometric UTe$_2$ crystals. Measurements of resistivity, magnetoresistance and susceptibility reveal that uniaxial pressure results in a suppression of the Kondo coherent state seen at ambient pressure, leading to the emergence of superconductivity initially at 1.5 GP, followed by the development of bulk superconductivity at 4.8 GPa. The superconducting state coexists with an exotic ferromagnetically ordered (FM) state that develops just below the onset temperature of the superconducting transition. High-pressure synchrotron x-ray diffraction measurements performed at 20 K indicate that no structural phase transition occurs over the measured pressure range. Our results not only demonstrate the coexistence of superconductivity with an exotic ferromagnetic state in pressurized stoichiometric UTe$_2$, but also highlight a vital role of Te deficiency in developing superconductivity at ambient pressures.Comment: 17 pages, 4 figure

Automatic Recognition of Laryngoscopic Images Using a Deep-Learning Technique

Objectives/Hypothesis: To develop a deep-learning–based computer-aided diagnosis system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) and improve the clinician-based accuracy of diagnostic assessments of laryngoscopy findings. Study Design: Retrospective study. Methods: A total of 24,667 laryngoscopy images (normal, vocal nodule, polyps, leukoplakia and malignancy) were collected to develop and test a convolutional neural network (CNN)-based classifier. A comparison between the proposed CNN-based classifier and the clinical visual assessments (CVAs) by 12 otolaryngologists was conducted. Results: In the independent testing dataset, an overall accuracy of 96.24% was achieved; for leukoplakia, benign, malignancy, normal, and vocal nodule, the sensitivity and specificity were 92.8% vs. 98.9%, 97% vs. 99.7%, 89% vs. 99.3%, 99.0% vs. 99.4%, and 97.2% vs. 99.1%, respectively. Furthermore, when compared with CVAs on the randomly selected test dataset, the CNN-based classifier outperformed physicians for most laryngeal conditions, with striking improvements in the ability to distinguish nodules (98% vs. 45%, P <.001), polyps (91% vs. 86%, P <.001), leukoplakia (91% vs. 65%, P <.001), and malignancy (90% vs. 54%, P <.001). Conclusions: The CNN-based classifier can provide a valuable reference for the diagnosis of laryngeal neoplasms during laryngoscopy, especially for distinguishing benign, precancerous, and cancer lesions. Level of Evidence: NA Laryngoscope, 130:E686–E693, 2020

Catalytic Cascade Dehydration-Etherification of Fructose into 5-Ethoxymethylfurfural with SO3H-Functionalized Polymers

A series of SO3H-functionalized polymers were prepared and employed as heterogeneous catalysts for one-pot transformation of fructose into 5-ethoxymethylfurfural (EMF) that is considered to be one of potential liquid biofuels. A high EMF yield of 72.8% could be obtained at 110°C for 10 h, and the polymeric acid catalysts could be recycled for five times without significant loss of catalytic performance