285 research outputs found

    Comparison of Visual Datasets for Machine Learning

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    One of the greatest technological improvements in recent years is the rapid progress using machine learning for processing visual data. Among all factors that contribute to this development, datasets with labels play crucial roles. Several datasets are widely reused for investigating and analyzing different solutions in machine learning. Many systems, such as autonomous vehicles, rely on components using machine learning for recognizing objects. This paper compares different visual datasets and frameworks for machine learning. The comparison is both qualitative and quantitative and investigates object detection labels with respect to size, location, and contextual information. This paper also presents a new approach creating datasets using real-time, geo-tagged visual data, greatly improving the contextual information of the data. The data could be automatically labeled by cross-referencing information from other sources (such as weather)

    Association of p53 rs1042522, MDM2 rs2279744, and p21 rs1801270 polymorphisms with retinoblastoma risk and invasion in a Chinese population.

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    Single nucleotide polymorphisms (SNPs) of p53 rs1042522, MDM2 rs2279744 and p21 rs1801270, all in the p53 pathway, which plays a crucial role in DNA damage and genomic instability, were reported to be associated with cancer risk and pathologic characteristics. This case-control study was designed to analyse the association between these SNPs and retinoblastoma (RB) in a Chinese Han population. These SNPs in 168 RB patients and 185 adult controls were genotyped using genomic DNA from venous blood. No significant difference was observed in allele or genotypic frequencies of these SNPs between Chinese RB patients and controls (all P > 0.05). However, the rs1042522 GC genotype showed a protective effect against RB invasion, as demonstrated by event-free survival (HR = 0.53, P = 0.007 for GC versus GG/CC). This effect was significant for patients with a lag time >1 month and no pre-enucleation treatment (P = 0.007 and P = 0.010, respectively), indicating an interaction between p53 rs1042522 and clinical characteristics, including lag time and pre-enucleation treatment status. Thus, the rs1042522 SNP may be associated with RB invasion in the Han Chinese population; however, further large and functional studies are needed to assess the validity of this association

    Two Low-Complexity Efficient Beamformers for an IRS- and UAV-Aided Directional Modulation Network

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    As excellent tools for aiding communication, an intelligent reflecting surface (IRS) and an unmanned aerial vehicle (UAV) can extend the coverage area, remove the blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance of directional modulation (DM) networks using an IRS and UAV in combination. To fully explore the benefits of the IRS and UAV, two efficient methods are proposed to enhance the SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS phase shift matrix (PSM), which is called Max-SR-SLNR. To reduce the computational complexity, the CM, artificial noise (AN) beamforming, and IRS phase shift design are independently designed in the following method. The CM beamforming vector is constructed based on the maximum ratio transmission (MRT) criteria along the channel from Alice-to-IRS, the AN beamforming vector is designed by null-space projection (NSP) on the remaining two channels, and the PSM of the IRS is directly given by the phase alignment (PA) method. This method is called the MRT-NSP-PA. The simulation results show that the SR performance of the Max-SR-SLNR method outperforms the MRT-NSP-PA method in the cases of small-scale and medium-scale IRSs, and the latter approaches the former in performance as the IRS tends to a larger scale

    Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

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    Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30M⊙M_{\odot} for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

    Natural Gas Accumulation Characteristics in the Linxing Area, Ordos Basin, NW China: Revealed from the Integrated Study of Fluid Inclusions and Basin Modeling

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    The Linxing area is located in the north of the eastern margin of the Ordos Basin, which has great resource potential for tight gas. In this paper, fluid inclusion analysis and basin modeling are the main means to clarify the gas accumulation mechanism of the Upper Paleozoic in the Linxing area. Petrographic analysis shows that fluid inclusions can be classified into 5 types: aqueous inclusions, hydrocarbon-bearing aqueous inclusions, hydrocarbon inclusions, crystal-bearing aqueous inclusions, and aqueous-carbonic inclusions. According to the statistical analysis of homogenization temperature and salinity of fluid inclusions, combined with the burial-thermal evolution, the study area was divided into 3 areas: the inner-magma baking area, the middle-anomal thermal area, and the outer-normal thermal area. The gas accumulation characteristics are differences among the 3 areas, the closer to Zijinshan magmatic pluton, the earlier gas accumulation period; and the vertical gas accumulation in the inner-magma baking area and the middle-anomal thermal area was not a slow and gradual process from bottom to top. The period from the Middle Jurassic to the Early Cretaceous is the key period for rapid pressure accumulation in the Upper Paleozoic reservoirs, which is consistent with the period of natural gas accumulation. The area near the Zijinshan magmatic pluton was the high fluid potential area during the gas accumulation period, which indicates that natural gas and other fluids migrated from Zijinshan magmatic pluton to the surrounding area. It is concluded that in the Linxing area, the Zijinshan magmatic pluton had a significant impact on natural gas accumulation, and the natural gas accumulation model under the control of magmatic thermal-tectonic effect was proposed

    Fast Approach for SAR Imaging of Ground-Based Moving Targets Based on Range Azimuth Joint Processing

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    The synthetic aperture radar (SAR) images of a moving target may be out of focus, given the motions of a non-cooperative target. Doppler ambiguities, including the Doppler center blur and spectrum ambiguity, will easily appear due to the limitations of pulse repetition frequency, which causes difficulty in moving-target imaging. Therefore, a robust fast Doppler ambiguity approach for SAR imaging of a ground-based moving target using range azimuth joint processing (RAJP) is presented. Firstly, the use of RAJP, based on a two-dimensional cross-correlation function and linear range cell migration (LRCM) compensation function, is proposed to simultaneously obtain the first- and second-order phase parameters in the fast-time and azimuth-frequency domains. Then, a corresponding azimuth reference function is constructed to image the moving target. Additionally, a principal component analysis-based operation is introduced to solve the mismatch with the LRCM compensation function. The couplings between the range and azimuth and between the first- and second-order parameters can be simultaneously decoupled by the proposed RAJP operation, which simplifies the processing steps. The developed approach can simultaneously obtain the first- and second-order parameters in the fast-time and azimuth-frequency domains, which avoids the propagation error of parameter estimation caused by the stepwise processing operation. The proposed method is relatively fast, given the need for fewer processing steps. The presented approach is robust in terms of Doppler ambiguity and handles the blind speed sidelobe well. In this study, simulated and real data are processed to verify the proposed approach

    Highlighting Fibroblasts Activation in Fibrosis: The State-of-The-Art Fibroblast Activation Protein Inhibitor PET Imaging in Cardiovascular Diseases

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    Fibrosis is a common healing process that occurs during stress and injury in cardiovascular diseases. The evolution of fibrosis is associated with cardiovascular disease states and causes adverse effects. Fibroblast activation is responsible for the formation and progression of fibrosis. The incipient detection of activated fibroblasts is important for patient management and prognosis. Fibroblast activation protein (FAP), a membrane-bound serine protease, is almost specifically expressed in activated fibroblasts. The development of targeted FAP-inhibitor (FAPI) positron emission tomography (PET) imaging enabled the visualisation of FAP, that is, incipient fibrosis. Recently, research on FAPI PET imaging in cardiovascular diseases increased and is highly sought. Hence, we comprehensively reviewed the application of FAPI PET imaging in cardiovascular diseases based on the state-of-the-art published research. These studies provided some insights into the value of FAPI PET imaging in the early detection of cardiovascular fibrosis, risk stratification, response evaluation, and prediction of the evolution of left ventricular function. Future studies should be conducted with larger populations and multicentre patterns, especially for response evaluation and outcome prediction

    Two Low-complexity Efficient Beamformers for IRS-and-UAV-aided Directional Modulation Networks

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    As the excellent tools for aiding communication,intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) can extend the coverage area, remove blind area, and achieve a dramatic rate improvement. In this paper, we improve the secrecy rate (SR) performance at directional modulation (DM) networks using IRS and UAV in combination. To fully explore the benefits of IRS and UAV, two efficient methods are proposed to enhance SR performance. The first approach computes the confidential message (CM) beamforming vector by maximizing the SR, and the signal-to-leakage-noise ratio (SLNR) method is used to optimize the IRS phase shift matrix, which is called Max-SR-SLNR. Here, Eve is maximally interfered by transmitting artificial noise (AN) along the direct path and null-space projection (NSP) on the remaining two channels. To reduce the computational complexity, the CM, AN beamforming and IRS phase shift design are independently designed in the following methods. The CM beamforming vector is constructed based on maximum ratio transmission (MRT) criteria along the channel from Alice-to-IRS, and phase shift matrix of IRS is directly given by phase alignment (PA) method. This method is called MRT-NSP-PA. Simulation results show that the SR performance of the Max-SR-SLNR method outperforms the MRT-NSP-PA method in the cases of small-scale and medium-scale IRSs, and the latter approaches the former in performance as IRS tends to lager-scale

    Identifying Two Common Types of Breast Benign Diseases Based on Multiphoton Microscopy

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    Multiphoton microscopy has attracted increasing attention and investigations in the field of breast cancer, based on two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG). However, the incidence of breast benign diseases is about 5 to 10 times higher than breast cancer; up to 30% of women suffer from breast benign diseases and require treatment at some time in their lives. Thus, in this study, MPM was applied to image fibroadenoma and fibrocystic lesion, which are two of the most common breast benign diseases. The results show that MPM has the capability to identify the microstructure of lobule and stroma in normal breast tissue, the interaction of compressed ducts with surrounding collagen fiber in fibroadenoma, and the architecture of cysts filled with cystic fluid in fibrocystic disease. These findings indicate that, with integration of MPM into currently accepted clinical imaging system, it has the potential to make a real-time diagnosis of breast benign diseases in vivo, as well as breast cancer
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