49 research outputs found
Design of a Multiband Antenna for LTE/GSM/UMTS Band Operation
This paper proposes a multiband antenna for LTE/GSM/UMTS band operation. The proposed antenna consists of a meandered planar inverted-F antenna with an additional branch line for wide bandwidth and a folded-loop antenna. The antenna provides a wide bandwidth to cover the hepta-band LTE/GSM/UMTS operation. The measured 6 dB return loss bandwidth is 169 MHz (793–962 MHz) at the low-frequency band and 1030 MHz (1700–2730 MHz) at the high-frequency band. The overall dimension of the proposed antenna is 55 mm × 110 mm × 5 mm
Echocardiographic View Classification with Integrated Out-of-Distribution Detection for Enhanced Automatic Echocardiographic Analysis
In the rapidly evolving field of automatic echocardiographic analysis and
interpretation, automatic view classification is a critical yet challenging
task, owing to the inherent complexity and variability of echocardiographic
data. This study presents ECHOcardiography VIew Classification with
Out-of-Distribution dEtection (ECHO-VICODE), a novel deep learning-based
framework that effectively addresses this challenge by training to classify 31
classes, surpassing previous studies and demonstrating its capacity to handle a
wide range of echocardiographic views. Furthermore, ECHO-VICODE incorporates an
integrated out-of-distribution (OOD) detection function, leveraging the
relative Mahalanobis distance to effectively identify 'near-OOD' instances
commonly encountered in echocardiographic data. Through extensive
experimentation, we demonstrated the outstanding performance of ECHO-VICODE in
terms of view classification and OOD detection, significantly reducing the
potential for errors in echocardiographic analyses. This pioneering study
significantly advances the domain of automated echocardiography analysis and
exhibits promising prospects for substantial applications in extensive clinical
research and practice
A Unified Approach for Comprehensive Analysis of Various Spectral and Tissue Doppler Echocardiography
Doppler echocardiography offers critical insights into cardiac function and
phases by quantifying blood flow velocities and evaluating myocardial motion.
However, previous methods for automating Doppler analysis, ranging from initial
signal processing techniques to advanced deep learning approaches, have been
constrained by their reliance on electrocardiogram (ECG) data and their
inability to process Doppler views collectively. We introduce a novel unified
framework using a convolutional neural network for comprehensive analysis of
spectral and tissue Doppler echocardiography images that combines automatic
measurements and end-diastole (ED) detection into a singular method. The
network automatically recognizes key features across various Doppler views,
with novel Doppler shape embedding and anti-aliasing modules enhancing
interpretation and ensuring consistent analysis. Empirical results indicate a
consistent outperformance in performance metrics, including dice similarity
coefficients (DSC) and intersection over union (IoU). The proposed framework
demonstrates strong agreement with clinicians in Doppler automatic measurements
and competitive performance in ED detection
Self supervised convolutional kernel based handcrafted feature harmonization: Enhanced left ventricle hypertension disease phenotyping on echocardiography
Radiomics, a medical imaging technique, extracts quantitative handcrafted
features from images to predict diseases. Harmonization in those features
ensures consistent feature extraction across various imaging devices and
protocols. Methods for harmonization include standardized imaging protocols,
statistical adjustments, and evaluating feature robustness. Myocardial diseases
such as Left Ventricular Hypertrophy (LVH) and Hypertensive Heart Disease (HHD)
are diagnosed via echocardiography, but variable imaging settings pose
challenges. Harmonization techniques are crucial for applying handcrafted
features in disease diagnosis in such scenario. Self-supervised learning (SSL)
enhances data understanding within limited datasets and adapts to diverse data
settings. ConvNeXt-V2 integrates convolutional layers into SSL, displaying
superior performance in various tasks. This study focuses on convolutional
filters within SSL, using them as preprocessing to convert images into feature
maps for handcrafted feature harmonization. Our proposed method excelled in
harmonization evaluation and exhibited superior LVH classification performance
compared to existing methods.Comment: 11 pages, 7 figure
Exploring aryl hydrocarbon receptor expression and distribution in the tumor microenvironment, with a focus on immune cells, in various solid cancer types
IntroductionAryl hydrocarbon receptor (AhR) is a transcription factor that performs various functions upon ligand activation. Several studies have explored the role of AhR expression in tumor progression and immune surveillance. Nevertheless, investigations on the distribution of AhR expression, specifically in cancer or immune cells in the tumor microenvironment (TME), remain limited. Examining the AhR expression and distribution in the TME is crucial for gaining insights into the mechanism of action of AhR-targeting anticancer agents and their potential as biomarkers.MethodsHere, we used multiplexed immunohistochemistry (mIHC) and image cytometry to investigate the AhR expression and distribution in 513 patient samples, of which 292 are patients with one of five solid cancer types. Additionally, we analyzed the nuclear and cytosolic distribution of AhR expression.ResultsOur findings reveal that AhR expression was primarily localized in cancer cells, followed by stromal T cells and macrophages. Furthermore, we observed a positive correlation between the nuclear and cytosolic expression of AhR, indicating that the expression of AhR as a biomarker is independent of its localization. Interestingly, the expression patterns of AhR were categorized into three clusters based on the cancer type, with high AhR expression levels being found in regulatory T cells (Tregs) in non-small cell lung cancer (NSCLC).DiscussionThese findings are anticipated to serve as pivotal evidence for the design of clinical trials and the analysis of the anticancer mechanisms of AhR-targeting therapies
Synthesis of heterocyclic-fused benzofurans via C–H functionalization of flavones and coumarins
An efficient method to effect C–O cyclization was developed via the C–H functionalization of chromones and coumarins, affording heterocyclic-fused benzofurans.124281sciescopu
Tandem Dehydrogenation/Oxidation/Oxidative Cyclization Approach to Wrightiadione and Its Derivatives
Wrightiadione contains a unique tetracyclic isoflavone moiety and has been shown to exhibit a broad range of biological activities. An efficient and straightforward synthetic method for generating the molecular complexity of wrightiadione was developed through three-step tandem dehydrogenation/oxidation/oxidative cyclization reactions with a Pd/Cu catalytic system. This unprecedented one-pot route utilizes a broad range of substrates, providing a convenient and powerful synthetic tool for accessing naturally occurring tetracyclic isoflavone wrightiadione and its nitrogen-containing derivatives. © 2015 American Chemical Society1771sciescopu
Effect of Filler Concentration on Tracking Resistance of ATH-Filled Silicone Rubber Nanocomposites
It is necessary for polymeric materials to have superior tracking resistance against various stress conditions for outdoor applications. In this study, the effect of nano-sized alumina tri-hydrate (ATH) particles on the tracking resistance of silicone rubber (SiR) is studied. Specimens with filler loadings of 1, 3, 5, 10, and 20 wt % are used for performance characterization. From the inclined plane test (IPT) results, apparent improvement in tracking resistance was achieved by mixing 3 wt % of nano-sized fillers, compared to unfilled specimens. ATH/SiR nanocomposites with 5 wt % loading showed comparable tracking performance to SiO2/SiR microcomposites with 20 wt % loading. For detailed analysis, measurements of surface contact angle (SCA) and surface leakage current, and thermo-gravimetric analysis (TGA) were performed. As the nano-ATH filler concentration increased, both thermal stability and leakage current characteristics were improved. Such results agreed with the tracking resistance performance by showing that thermal decomposition and surface charge transport is inhibited in ATH/SiR nanocomposites. Furthermore, performance improvement in nanocomposites was achieved, even at low filler loadings, compared to microcomposites. Meanwhile, the change in SCA was found to be rather limited, regardless of filler loading and filler size
Rh(iii)-catalyzed direct C-H/C-H cross-coupling of quinones with arenes assisted by a directing group: Identification of carbazole quinones as GSKβ inhibitors
Rh-catalyzed direct C-H/C-H cross-coupling reaction of various (hetero)arenes with quinones is developed. This protocol is effective for a broad range of both quinone and arene substrates and a wide range of directing groups for this reaction, affording structurally diverse aryl-substituted quinones with high synthetic utility. Moreover, the present synthetic route allowed for the rapid construction of the carbazole quinone moiety that was identified as a new inhibitor scaffold for GSKβ. This journal is © The Royal Society of Chemistry 2015119211sciescopu