An effective and interpretable method for document classification

As the number of documents has been rapidly increasing in recent time, automatic text categorization is becoming a more important and fundamental task in information retrieval and text mining. Accuracy and interpretability are two important aspects of a text classifier. While the accuracy of a classifier measures the ability to correctly classify unseen data, interpretability is the ability of the classifier to be understood by humans and provide reasons why each data instance is assigned to a label. This paper proposes an interpretable classification method by exploiting the Dirichlet process mixture model of von Mises–Fisher distributions for directional data. By using the labeled information of the training data explicitly and determining automatically the number of topics for each class, the learned topics are coherent, relevant and discriminative. They help interpret as well as distinguish classes. Our experimental results showed the advantages of our approach in terms of separability, interpretability and effectiveness in classification task of datasets with high dimension and complex distribution. Our method is highly competitive with state-of-the-art approaches.     

Unkeito Suppresses RANKL-Mediated Osteoclastogenesis via the Blimp1–Bcl6 and NF-κB Signaling Pathways and Enhancing Osteoclast Apoptosis

Osteoporosis is a common bone disease, particularly in menopausal women. Herein, we screened four Kampo medicines (Unkeito (UKT), Kamishoyosan (KSS), Kamikihito (KKT), and Ninjinyoeito (NYT)), frequently used to treat menopausal syndromes, for their effects on receptor activator of nuclear factor-kappaB ligand (RANKL)-induced osteoclast differentiation in RAW 264 cells. Considering that UKT exhibited the most potent effect, we examined its effect on RANKL-induced osteoclastogenesis, the induction of osteoclast apoptosis, and the mechanisms underlying its effects. UKT inhibits RANKL-induced osteoclast differentiation in the early stage and decreases osteoclast-related genes, including tartrate-resistant acid phosphatase (Trap), dendritic cell-specific transmembrane protein (Dcstamp), matrix metalloproteinase-9 (Mmp9), and cathepsin K (Ctsk). Specifically, UKT inhibits the nuclear factor of activated T cells 1 (NFATc1), which is essential for osteoclastogenesis. UKT increases Bcl6, which antagonizes NFATc1 and Dc-stamp, thereby blocking the progression of osteoclasts to maturation. UKT also decreased nuclear translocation by downregulating the activity of p65/NF-κB. In addition, UKT enhances mononuclear osteoclast apoptosis via activation of caspase-3. Herein, we demonstrate that UKT suppresses RANKL-mediated osteoclastogenesis via the Blimp1–Bcl6 and NF-κB signaling pathways and enhances mononuclear osteoclast apoptosis. Furthermore, UKT prevents bone loss in OVX mice. Thus, UKT might be a potential therapeutic agent for postmenopausal osteoporosis.     

Design of a wideband miniature dielectric-filled waveguide antennafor collision-avoidance radar

This article presents a theoretical and experimental study of the design of a miniaturized wideband dielectric-filled waveguide (DFW) antenna. The operational frequency is X band, i.e., 9.0⩽f⩽10.5 GHz. The desired bandwidth is 1.5 GHz. The antenna uses an air-gap matching network to reduce its high aperture reflection. In order to ease the integration with antenna circuits and to increase the bandwidth, two E-plane steps are used. The antenna is designed to have -3 dB beamwidths of 60° and 100° for the E- and H-plane patterns, respectively. An input reflection of less than -10 dB for the desired bandwidth is observed. The gain of the antenna is 7 dBi. A cross-polar level of less than -25 dB is achieved. This article discusses the mathematical model for input reflection, the design scenarios, and the experimental results     

Association of Ligamentum Flavum Hypertrophy with Adolescent Idiopathic Scoliosis Progression—Comparative Microarray Gene Expression Analysis

The role of the ligamentum flavum (LF) in the pathogenesis of adolescent idiopathic scoliosis (AIS) is not well understood. Using magnetic resonance imaging (MRI), we investigated the degrees of LF hypertrophy in 18 patients without scoliosis and on the convex and concave sides of the apex of the curvature in 22 patients with AIS. Next, gene expression was compared among neutral vertebral LF and LF on the convex and concave sides of the apex of the curvature in patients with AIS. Histological and microarray analyses of the LF were compared among neutral vertebrae (control) and the LF on the apex of the curvatures. The mean area of LF in the without scoliosis, apical concave, and convex with scoliosis groups was 10.5, 13.5, and 20.3 mm², respectively. There were significant differences among the three groups (p < 0.05). Histological analysis showed that the ratio of fibers (Collagen/Elastic) was significantly increased on the convex side compared to the concave side (p < 0.05). Microarray analysis showed that ERC2 and MAFB showed significantly increased gene expression on the convex side compared with those of the concave side and the neutral vertebral LF cells. These genes were significantly associated with increased expression of collagen by LF cells (p < 0.05). LF hypertrophy was identified in scoliosis patients, and the convex side was significantly more hypertrophic than that of the concave side. ERC2 and MAFB genes were associated with LF hypertrophy in patients with AIS. These phenomena are likely to be associated with the progression of scoliosis.     

Neural Network–Based Intelligent Compaction Analyzer for Estimating Compaction Quality of Hot Asphalt Mixes

Continuous real-time estimating of compaction quality during the construction of a hot mix asphalt (HMA) pavement is addressed in this paper. The densification of asphalt pavements during construction usually is accomplished by using vibratory compactors. During compaction, the compactor and the asphalt mat form a coupled system whose dynamics are influenced by the changing stiffness of the mat. The measured vibrations of the compactor along with process parameters such as lift thickness, mix type, mix temperature, and compaction pressure can be used to predict the asphalt mat density. Contrary to existing techniques in the literature in which a model is developed to fit experimental data and to predict mat density, a neural network-based approach is adopted that is model-free and uses pattern-recognition techniques to estimate density. The neural network is designed to read the entire frequency spectrum of roller vibrations and to classify these vibrations into different levels. The intelligent asphalt compaction analyzer (IACA) is then trained to convert these vibration levels into a “number” indicative of the asphalt mat density at a given location. This two-step process eliminates the need for regression analysis and produces more accurate density measurements than those reported elsewhere in the literature. Compaction studies of HMA mixes on a stiff subgrade indicate that the changes in the vibration characteristics of the roller are attributable to an increased compaction of the HMA base. The results also show that, with the neural network working as a classifier, the IACA can estimate the density continuously, and in real time, with accuracy levels adequate for quality control in the field.     

Direct Reprogramming and Induction of Human Dermal Fibroblasts to Differentiate into iPS-Derived Nucleus Pulposus-like Cells in 3D Culture

Intervertebral disc (IVD) diseases are common spinal disorders that cause neck or back pain in the presence or absence of an underlying neurological disorder. IVD diseases develop on the basis of degeneration, and there are no established treatments for degeneration. IVD diseases may therefore represent a candidate for the application of regenerative medicine, potentially employing normal human dermal fibroblasts (NHDFs) induced to differentiate into nucleus pulposus (NP) cells. Here, we used a three-dimensional culture system to demonstrate that ectopic expression of MYC, KLF4, NOTO, SOX5, SOX6, and SOX9 in NHDFs generated NP-like cells, detected using Safranin-O staining. Quantitative PCR, microarray analysis, and fluorescence-activated cell sorting revealed that the induced NP cells exhibited a fully differentiated phenotype. These findings may significantly contribute to the development of effective strategies for treating IVD diseases.     

Polyacrylonitrile‐carbon Nanotube‐polyacrylonitrile: A Versatile Robust Platform for Flexible Multifunctional Electronic Devices in Medical Applications

Flexible multifunctional electronic devices are of high interest for a wide range of applications including thermal therapy and respiratory devices in medical treatment, safety equipment, and structural health monitoring systems. This paper reports a scalable and efficient strategy of manufacturing a polyacrylonitrile‐carbon nanotube‐polyacrylonitrile (PAN‐CNT‐PAN) robust flexible platform for multifunctional electronic devices including flexible heaters, temperature sensors, and flexible thermal flow sensors. The key advantages of this platform include low cost, porosity, mechanical robustness, and electrical stability under mechanical bending, enabling the development of fast‐response flexible heaters with a response time of ≈1.5 s and relaxation time of ≈1.7 s. The temperature‐sensing functionality is also investigated with a range of temperature coefficient of resistances from ?650 to ?900 ppm K^?1. A flexible hot‐film sensing concept is successfully demonstrated using PAN‐CNT‐PAN with a high sensitivity of 340 mV (m s^?1)^?1. The sensitivity enhancement of 50% W^?1 is also observed with increasing supply power. The low cost, porosity, versatile, and robust properties of the proposed platform will enable the development of multifunctional electronic devices for numerous applications such as flexible thermal management, temperature stabilization in industrial processing, temperature sensing, and flexible/wearable devices for human healthcare applications.     

A stochastic reward net-based assessment of reliability,availability and operational cost for a software-defined network infrastructure

The Journal of Supercomputing - The networking infrastructure of a software-defined network (SDN) requires further study to achieve continuity and high availability of data transactions for cloud...