18,217 research outputs found
Consistency of Loop Regularization Method and Divergence Structure of QFTs Beyond One-Loop Order
We study the problem how to deal with tensor-type two-loop integrals in the
Loop Regularization (LORE) scheme. We use the two-loop photon vacuum
polarization in the massless Quantum Electrodynamics (QED) as the example to
present the general procedure. In the processes, we find a new divergence
structure: the regulated result for each two-loop diagram contains a
gauge-violating quadratic harmful divergent term even combined with their
corresponding counterterm insertion diagrams. Only when we sum up over all the
relevant diagrams do these quadratic harmful divergences cancel, recovering the
gauge invariance and locality.Comment: 33 pages, 5 figures, Sub-section IIIE removed, to be published in
EPJ
Numerical Calculation of Transient Thermal Characteristics in Gas-Insulated Transmission Lines
For further knowledge of the thermal characteristics in gas-insulated transmission lines (GILs) installed above ground, a finite-element model of coupling fluid field and thermal field is established, in which the corresponding assumptions and boundary conditions are given. Transient temperature rise processes of the GIL under the conditions of variable ambient temperature, wind velocity and solar radiation are respectively investigated. Equivalent of surface convective heat transfer coefficient and heat flux boundary conditions are updated in the analysis process. Unlike the traditional finite element method (FEM), the variability of the thermal properties with temperature is considered. The calculation results are validated by the tests results reported in the literature. The conclusion provides method and theory basis for the knowledge of transient temperature rise characteristics of GILs in open environment
Investigating into segmentation methods for diagnosis of respiratory diseases using adventitious respiratory sounds
Respiratory condition has received a great amount of attention nowadays since respiratory diseases recently become the globally leading causes of death. Traditionally, stethoscope is applied in early diagnosis but it requires clinician with extensive training experience to provide accurate diagnosis. Accordingly, a subjective and fast diagnosing solution of respiratory diseases is highly demanded. Adventitious respiratory sounds (ARSs), such as crackle, are mainly concerned during diagnosis since they are indication of various respiratory diseases. Therefore, the characteristics of crackle are informative and valuable regarding to develop a computerised approach for pathology-based diagnosis. In this work, we propose a framework combining random forest classifier and Empirical Mode Decomposition (EMD) method focusing on a multi-classification task of identifying subjects in 6 respiratory conditions (healthy, bronchiectasis, bronchiolitis, COPD, pneumonia and URTI). Specifically, 14 combinations of respiratory sound segments were compared and we found segmentation plays an important role in classifying different respiratory conditions. The classifier with best performance (accuracy = 0.88, precision = 0.91, recall = 0.87, specificity = 0.91, F1-score = 0.81) was trained with features extracted from the combination of early inspiratory phase and entire inspiratory phase. To our best knowledge, we are the first to address the challenging multi-classification problem
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