Bis(1H-imidazole-κN 3)bis­(2-methyl­benzoato-κO)bis­(2-methyl­benzoic acid-κO)copper(II)

The structure of the title compound, [Cu(C8H7O2)2(C3H4N2)2(C8H8O2)2], consists of centrosymmetric monomeric units, in which the CuII atom has a tetra­gonally distorted octa­hedral coordination involving two imidazole N atoms and two carboxyl­ate O atoms in the square plane [Cu—N = 1.964 (3) and Cu—O = 1.960 (2) Å] and 2-methyl­benzoic acid O atoms in axial sites [Cu—O = 2.753 (3) Å]. Within the complex, the carb­oxy­lic acid forms intra­molecular O—H⋯O hydrogen bonds, while the mol­ecules are assembled through N—H⋯O(carbox­yl) hydrogen bonds into chains extending along the a-axis direction. These chains are further linked by weak π–π inter­actions [centroid–centroid separation = 3.930 (2) Å]

A Generalized Robust Minimization Framework for Low-Rank Matrix Recovery

This paper considers the problem of recovering low-rank matrices which are heavily corrupted by outliers or large errors. To improve the robustness of existing recovery methods, the problem is solved by formulating it as a generalized nonsmooth nonconvex minimization functional via exploiting the Schatten p-norm (0 < p ≤1) and Lq(0 < q ≤1) seminorm. Two numerical algorithms are provided based on the augmented Lagrange multiplier (ALM) and accelerated proximal gradient (APG) methods as well as efficient root-finder strategies. Experimental results demonstrate that the proposed generalized approach is more inclusive and effective compared with state-of-the-art methods, either convex or nonconvex

Design of a 1-THz 4th-harmonic gyrotron driven by large-orbit beam

In this paper, the design of a 4th-harmonic gyrotron with 1-kW-level output power at 1 terahertz (THz) is presented. A unique advantage of this design is that, with a well-optimized magnetic-cusp large-orbit electron gun, the designed gyrotron can operate from 1st harmonic to 4th harmonic in multiple discrete bands by varying the operating voltage. By carefully balancing the competing modes, the gyrotron can be tuned to operate at six candidate modes, including TE1,2 for fundamental harmonic, TE2,3 and TE2,4 for 2nd harmonic, TE3,5 and TE3,6 for 3rd harmonic, and TE4,8 for 4th harmonic interactions. As the main operating mode, the TE4,8 can generate a peak output power of 1.68 kW, with an efficiency of about 2.1%, and a magnetically controlled frequency tuning range of about 1.8 GHz around 1 THz. The impact of the longitudinal nonuniformity of the cavity at high-harmonic interaction was also studied. It shows a radial tolerance of several micrometers will significantly elevate the start-oscillation current and deteriorate output performance. This design is towards the development of a synthesizing THz source with ultra-wideband tuning capability ranging from the sub-millimeter-wave to 1-THz bands

Glioma Grading on Conventional MR Images: A Deep Learning Study With Transfer Learning

Background: Accurate glioma grading before surgery is of the utmost importance in treatment planning and prognosis prediction. But previous studies on magnetic resonance imaging (MRI) images were not effective enough. According to the remarkable performance of convolutional neural network (CNN) in medical domain, we hypothesized that a deep learning algorithm can achieve high accuracy in distinguishing the World Health Organization (WHO) low grade and high grade gliomas.Methods: One hundred and thirteen glioma patients were retrospectively included. Tumor images were segmented with a rectangular region of interest (ROI), which contained about 80% of the tumor. Then, 20% data were randomly selected and leaved out at patient-level as test dataset. AlexNet and GoogLeNet were both trained from scratch and fine-tuned from models that pre-trained on the large scale natural image database, ImageNet, to magnetic resonance images. The classification task was evaluated with five-fold cross-validation (CV) on patient-level split.Results: The performance measures, including validation accuracy, test accuracy and test area under curve (AUC), averaged from five-fold CV of GoogLeNet which trained from scratch were 0.867, 0.909, and 0.939, respectively. With transfer learning and fine-tuning, better performances were obtained for both AlexNet and GoogLeNet, especially for AlexNet. Meanwhile, GoogLeNet performed better than AlexNet no matter trained from scratch or learned from pre-trained model.Conclusion: In conclusion, we demonstrated that the application of CNN, especially trained with transfer learning and fine-tuning, to preoperative glioma grading improves the performance, compared with either the performance of traditional machine learning method based on hand-crafted features, or even the CNNs trained from scratch

Development of a magnetic cusp gun for a 1-THz harmonic gyrotron

High-quality axis-encircling electron beam is essential to drive a high-harmonic gyrotron. A magnetic cusp gun that can generate a low-spread axis-encircling electron beam at an extremely high magnetic-compression ratio was developed for a 1-THz 4th-harmonic gyrotron toward continuous-wave operation. The optimized gun could generate an axis-encircling electron beam with 80-kV voltage, 1-A current, and a nearly constant pitch factor of about 1.5 in a wide range of magnetic field strength. The transverse velocity spread was less than 2.1% and the guiding center radius was 26.6 µm. The design was verified by using MAGIC, EGUN, and CST simulations and good agreements were achieved