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Theory of Absorption Spectrum in the Nonequilibrium Steady State of Superconductors under Microwave Irradiation
Get PDFWe discuss the absorption spectrum of dirty s-wave superconductors in the nonequilibrium steady state under a homogeneous and monochromatic microwave. In this state, there exists a finite density of states at lower energies than the superconducting gap, and the distribution function is also defined in this energy region. Because of the reduction of the distribution function below the superconducting gap, the absorption by thermally excited quasiparticles is suppressed in the nonequilibrium state compared with that in the equilibrium case. This is in contrast to the cases of the gap function and the absorption by direct excitation, to which the variation of the distribution function above the superconducting gap mainly contributes. It is also shown that amplitude modes are generated by frequency mixing of the pump wave and the probe wave, and two peaks appear in the absorption spectrum.journal articl
Implantable Multimodal Sensing Device for Simultaneous Imaging and Electrophysiological Recording of Mouse Brain Activity
No full textOptical and electrophysiological measurements help us understand mouse brain functions. One type of device available for optical measurements is an implantable complementary metal-oxide-semiconductor (CMOS) image sensor (ICIS). However, an ICIS alone cannot directly measure the electrical signals emitted by mouse brain neurons. Considering this limitation, we have developed an implantable multimodal sensor that can simultaneously make optical and electrophysiological measurements of the neural activity in the brains of mice. The proposed device integrates a CMOS image sensor and a neural amplifier with a recording electrode into a single chip, making it no more invasive than a conventional implantable CMOS image sensor. The proposed device is based on a 0.35-μm CMOS standard process and occupies an area of 0.50 × 5.0 mm2. Furthermore, a hybrid filter is fabricated on the imaging pixel array to remove the excitation light and selectively detect fluorescence. From electrophysiological measurements, we confirm that the neural amplifier features a mid-band gain of 39 dB from 500 mHz to 4 kHz, which is the bandwidth that includes local field and action potentials. Crosstalk noise is observed because of the digital signal used to control the image sensor. However, in vivo experiments demonstrate that the device is capable of simultaneously measuring and processing optical and electrophysiological signals when the amplitude spectrum has a peak of less than 1 μV.research repor
Region-based fully convolutional networks with deformable convolution and attention fusion for steel surface defect detection in industrial Internet of Things
No full textNext-generation 6G networks will fully drive the development of the industrial Internet of Things. Steel surface defect detection as an important application in industrial Internet of Things has recently received increasing attention from the military industry, the aviation industry and other fields, which is closely related to the quality of industrial production products. However, many typical convolutional neural networks-based methods are insensitive to the problem of unclear boundaries. In this article, the authors develop a region-based fully convolutional networks with deformable convolution and attention fusion to adaptively learn salient features for steel surface defect detection. Specifically, deformable convolution is applied into selectively replace the standard convolution in the backbone of the region-based fully convolutional networks, which performs significantly in scenarios with unclear defect boundaries. Moreover, convolutional block attention module is utilised in region proposal network to further enhance detection accuracy. The proposed architecture is demonstrated on two popular steel defect detection benchmarks, including NEU-DET and GC10-DET, which can effectively present the performance of steel surface defect detection by abundant experiments. The mean average precision on two datasets reaches 80.9% and 66.2%. The average precision of defect crazing, inclusion, patches, pitted-surface, rolled-in scale and scratches on NEU-DET is 58.2%, 82.3%, 95.7%, 85.6%, 75.9%, and 87.9% respectively.journal articl
Performance and Stability Enhancement of Fully Solution-Processed a-InZnO Thin-Film Transistors via Argon Plasma Treatment
No full textThe market is now moving to next-generation flexible electronics which requires the integration of functional solution-processed materials using simple and low-temperature fabrication techniques that are compatible with heat-sensitive substrates. Although several studies have reported on the high-performance solution-processed layer in oxide thin-film transistors (TFTs), achieving high mobility while maintaining good stability under the bias stress test remains a challenge. In this report, we show that argon (Ar) plasma treatment is an effective method for achieving fully solution-processed amorphous indium zinc oxide (a-IZO) TFTs with high stability and performance. Particularly, Ar plasma treatment can activate the electrode and induce TFT switching. The electrical performance of the a-IZO TFT was also enhanced by the Ar plasma treatment. From the experimental results, fully solution-processed a-IZO TFTs with high mobility up to 31.12 cm2/(V s) was achieved by Ar plasma treatment for 5 s at an Ar flow rate of 75 sccm. The stability behavior of the self-aligned top gate top contact a-IZO TFT treated with argon plasma was investigated under positive bias stress (PBS) and negative bias stress (NBS) with a smallest threshold voltage shift (ΔVth) of $22120.3 and 0.7 V for PBS and NBS, respectively. ΔVth is improved due to the higher film densification which confirms better film quality. Higher mobile carrier with lower interface trap density and film densification are the main reasons behind the performance and stability improvement of these TFTs. These results show that the performance and stability enhancement of the fully solution-processed a-IZO TFT by plasma treatment has a large potential for future low-temperature flexible device applications.journal articl
Development and validation of an open-source tool for opportunistic screening of osteoporosis from hip CT images
No full textAims
This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images.
Methods
The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.
Results
CT-aBMD was successfully measured in 976/978 hips (99.8%). A significant correlation was found between CT-aBMD and DXA-BMD (r = 0.941; p < 0.001). In the ROC analysis, the area under the curve to diagnose osteoporosis was 0.976. The diagnostic sensitivity and specificity were 88.9% and 96%, respectively, with the cutoff set at 0.625 g/cm2.
Conclusion
Accurate DXA-BMD measurements and diagnosis of osteoporosis were performed from CT images using the system developed herein. As the models are open-source, clinicians can use the proposed system to screen osteoporosis and determine the surgical strategy for hip surgery.journal articl
タンパクシツ コウブンピツ Aspergillus niger カブ ガ ユウスル ヘンイガタ Ire 1 ノ シュツガ コウボ ニオケル キノウ カイセキ
Get PDF奈良先端科学技術大学院大学修士(バイオサイエンス)master thesi
On QSAR-based cardiotoxicity modeling with the expressiveness-enhanced graph learning model and dual-threshold scheme
No full textIntroduction: Given the direct association with malignant ventricular arrhythmias, cardiotoxicity is a major concern in drug design. In the past decades, computational models based on the Quantitative structure-structure relationship (QSAR) have been proposed to screen out cardiotoxic compounds and have shown promising results. The combination of molecular fingerprint and machine learning model shows stable performance for a wide spectrum of problems, however, not long after the advent of the graph neural network (GNN) deep learning model and its variant (e.g., Graph Transformer), it has become the principal way of QSAR-based modeling for its high flexibility in feature extraction and decision rule generation. In spite of all these progresses, the expressiveness (the ability of a program to identify non-isomorphic graph structures) of the GNN model is bounded by the WL isomorphism test, and a suitable thresholding scheme that relates directly to the sensitivity and credibility of a model is still an open question. Methods: In this research, we further improved the expressiveness of the GNN model by introducing the substructure-aware bias by the Graph Subgraph Transformer network (GSTN) model. Moreover, to propose the most appropriate thresholding scheme, a comprehensive comparison of the thresholding schemes was conducted. Results: Based on these improvements,
the best model attains performance with 90.4% Precision, 90.4% Recall, and 90.5% F1-score with a dual threshold scheme (active: 30 uM). the improved pipeline (GSTN model and thresholding scheme) also shows its advantages in terms of the activity cliff problem and model interpretability.journal articl
Novel inhibitory mechanisms for fission yeast TOR complex 1 that controls nutrient-dependent cellular growth
Get PDFdoctoral thesi
Poster-patients relationships show differing content and language on Chinese Weibo: Text classification, sentiment analysis, and topic modeling of posts on breast cancer
Get PDF奈良先端科学技術大学院大学修士(工学)master thesi
Secretion of mitochondrial DNA via exosomes promotes inflammation in Beh$00E7et's syndrome
No full textMitochondrial DNA (mtDNA) leakage into the cytoplasm can occur when cells are exposed to noxious stimuli. Specific sensors recognize cytoplasmic mtDNA to promote cytokine production. Cytoplasmic mtDNA can also be secreted extracellularly, leading to sterile inflammation. However, the mode of secretion of mtDNA out of cells upon noxious stimuli and its relevance to human disease remain unclear. Here, we show that pyroptotic cells secrete mtDNA encapsulated within exosomes. Activation of caspase‐1 leads to mtDNA leakage from the mitochondria into the cytoplasm via gasdermin‐D. Caspase‐1 also induces intraluminal membrane vesicle formation, allowing for cellular mtDNA to be taken up and secreted as exosomes. Encapsulation of mtDNA within exosomes promotes a strong inflammatory response that is ameliorated upon exosome biosynthesis inhibition in vivo. We further show that monocytes derived from patients with Beh$00E7et's syndrome (BS), a chronic systemic inflammatory disorder, show enhanced caspase‐1 activation, leading to exosome‐mediated mtDNA secretion and similar inflammation pathology as seen in BS patients. Collectively, our findings support that mtDNA‐containing exosomes promote inflammation, providing new insights into the propagation and exacerbation of inflammation in human inflammatory diseases.journal articl