A digital-controlled SiC-based solid state circuit breaker with soft switch-off method for DC power system

Due to the lower on-state resistance, direct current (DC) solid state circuit breakers (SSCBs) based on silicon-carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) can reduce on-state losses and the investment of the cooling system when compared to breakers based on silicon (Si) MOSFETs. However, SiC MOSFETs, with smaller die area and higher current density, lead to weaker short-circuit ability, shorter short-circuit withstand time and higher protection requirements. To improve the reliability and short-circuit capability of SiC-based DC solid state circuit breakers, the short-circuit fault mechanisms of Si MOSFETs and SiC MOSFETs are revealed. Combined with the desaturation detection (DESAT), a “soft turn-off” short-circuit protection method based on source parasitic inductor is proposed. When the DESAT protection is activated, the “soft turn-off” method can protect the MOSFET against short-circuit and overcurrent. The proposed SSCB, combined with the flexibility of the DSP, has the μs-scale ultrafast response time to overcurrent detection. Finally, the effectiveness of the proposed method is validated by the experimental platform. The method can reduce the voltage stress of the power device, and it can also suppress the short-circuit current

NeAI: A Pre-convoluted Representation for Plug-and-Play Neural Ambient Illumination

Recent advances in implicit neural representation have demonstrated the ability to recover detailed geometry and material from multi-view images. However, the use of simplified lighting models such as environment maps to represent non-distant illumination, or using a network to fit indirect light modeling without a solid basis, can lead to an undesirable decomposition between lighting and material. To address this, we propose a fully differentiable framework named neural ambient illumination (NeAI) that uses Neural Radiance Fields (NeRF) as a lighting model to handle complex lighting in a physically based way. Together with integral lobe encoding for roughness-adaptive specular lobe and leveraging the pre-convoluted background for accurate decomposition, the proposed method represents a significant step towards integrating physically based rendering into the NeRF representation. The experiments demonstrate the superior performance of novel-view rendering compared to previous works, and the capability to re-render objects under arbitrary NeRF-style environments opens up exciting possibilities for bridging the gap between virtual and real-world scenes. The project and supplementary materials are available at https://yiyuzhuang.github.io/NeAI/.Comment: Project page: <a class="link-external link-https" href="https://yiyuzhuang.github.io/NeAI/" rel="external noopener nofollow">https://yiyuzhuang.github.io/NeAI/</a

Elastic properties of nuclear pasta in a fully three-dimensional geometry

Realistic estimations on the elastic properties of neutron star matter are carried out with a large strain ($\varepsilon \lesssim 0.5$) in the framework of relativistic-mean-field model with Thomas-Fermi approximation, where various crystalline configurations are considered in a fully three-dimensional geometry with reflection symmetry. Our calculation confirms the validity of assuming Coulomb crystals for the droplet phase above neutron drip density, which nonetheless does not work at large densities since the elastic constants are found to be decreasing after reaching their peaks. Similarly, the analytic formulae derived in the incompressible liquid-drop model give excellent description for the rod phase at small densities, which overestimates the elastic constants at larger densities. For slabs, due to the negligence on the variations of their thicknesses, the analytic formulae from liquid-drop model agree qualitatively but not quantitatively with our numerical estimations. By fitting to the numerical results, these analytic formulae are improved by introducing dampening factors. The impacts of nuclear symmetry energy are examined adopting two parameter sets, corresponding to the slope of symmetry energy $L = 41.34$ and 89.39 MeV. Even with the uncertainties caused by the anisotropy in polycrystallines, the elastic properties of neutron star matter obtained with $L = 41.34$ and 89.39 MeV are distinctively different, results in detectable differences in various neutron star activities

Factors influencing the quality of clinical trials on traditional Chinese medicine— Qualitative interviews with trial auditors, clinicians and academic researchers

Background: As clinical trials evaluating the efficacy of traditional Chinese medicine (TCM) therapies have increased, several empirical studies have shown that the quality of TCM trials are generally low in terms of risk of bias. This qualitative study aimed to investigate the factors influencing the quality of TCM clinical trials to provide strategic advice on trial quality improvement. Methods: One focus group with clinical trial auditors (n=4) and six indepth semi-structured interviews with clinical research organization managers (n=2), lecturers and researchers in TCM academic institutions (n=2), a chief physician in a TCM oncology department and a PhD candidate specialized in non-pharmaceutical TCM interventions were conducted. The interviews were audio-recorded, transcribed verbatim and thematically analyzed. Results: Factors that influenced the quality of TCM clinical trials merged on the following 6 themes: trial design; trialists/ participants; trial conducting; TCM specified problems; trial monitoring, and finally societal influences. The lack of expertise and time inputs of the trialists were repeatedly mentioned. Methodological difficulties experienced when conducting TCM trials included calculating sample size, analyzing the efficacy of TCM decoctions with multiple ingredients, blinding in trials investigating non-pharmaceutical TCM interventions were highlighted. Interviewees agreed that third-party monitoring can help improving trial quality and improved participant welfare and may accelerate recruiting processes and increase compliance; however more comprehensive regulations and funding requirements would be needed. Conclusions: This study identified real-life issues influencing the quality of TCM clinical trials from design to reporting. In addition to mandatory training for TCM trial designers and coordinators, more effective institutional oversight is required. Future studies should explore specific measures to address the methodological problems in TCM trials and explore how the quality of TCM trials can affect further evidence synthesis and clinical practice

Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space

This paper addresses an important problem of ranking the pre-trained deep neural networks and screening the most transferable ones for downstream tasks. It is challenging because the ground-truth model ranking for each task can only be generated by fine-tuning the pre-trained models on the target dataset, which is brute-force and computationally expensive. Recent advanced methods proposed several lightweight transferability metrics to predict the fine-tuning results. However, these approaches only capture static representations but neglect the fine-tuning dynamics. To this end, this paper proposes a new transferability metric, called \textbf{S}elf-challenging \textbf{F}isher \textbf{D}iscriminant \textbf{A}nalysis (\textbf{SFDA}), which has many appealing benefits that existing works do not have. First, SFDA can embed the static features into a Fisher space and refine them for better separability between classes. Second, SFDA uses a self-challenging mechanism to encourage different pre-trained models to differentiate on hard examples. Third, SFDA can easily select multiple pre-trained models for the model ensemble. Extensive experiments on $33$ pre-trained models of $11$ downstream tasks show that SFDA is efficient, effective, and robust when measuring the transferability of pre-trained models. For instance, compared with the state-of-the-art method NLEEP, SFDA demonstrates an average of $59.1$\% gain while bringing $22.5$x speedup in wall-clock time. The code will be available at \url{https://github.com/TencentARC/SFDA}.Comment: ECCV 2022 camera ready. 24 pages, 11 tables, 5 figure

Model and observation of dispatchable region for flexible distribution network

Soft open points (SOPs), defined as the power electronic devices installed to replace normally open points in distribution network, can improve the flexibility of power control and thus further enhance the reliability and economy of power grids. Flexible distribution network (FDN) is a system-level concept to describe the distribution network equipped with multiple SOPs. Region method is to describe the secure range of the system operating in a geometric view. This paper adopts the region method to observe FDN for the first time. Firstly, the model of dispatchable region of FDN is proposed. The constraints of region space are formulated, considering SOPs, power flow, thermal capacity and voltage profile. Secondly, a simulation-based observation approach is also proposed to obtain the region projections on 2D and 3D sub-space. To illustrate the approach clearly, 2 small cases are given preceding a 7-feeders IEEE RBTS case. The region projections of case grids are observed and their topological characteristics are compared with those of traditional distribution network (TDN). The results indicate that FDN has advantages over traditional distribution network in operation security. For example, the region projections of FDN on 2-dimensional sub-space are about 2–4 times larger than those of TDN with the same network topology. The dispatchable region can be further developed into a useful tool for the secure and high-efficient operation of FDN in the future

Effect of Heterogeneity on the Failure of Rock with an Initial Crack under Uniaxial Compressions: A Numerical Study

AbstractFailure mechanisms of rock are intrinsically intertwined with heterogeneity and natural fracture. However, the effects of heterogeneity on the failure of rock with natural cracks are still far from clear. By simultaneously considering rock heterogeneity and natural fractures, this paper investigated the effects of heterogeneity on the failure of rock with a single initial crack under uniaxial compressions. The RFPA method with consideration of materials properties heterogeneity was employed, and numerical models with different crack angles were developed. The stress-strain curve, crack development, failure pattern, and AE characteristics were obtained. The numerical results were also compared with experimental results. Further, the effects of initial crack angle and heterogeneity on the strength, failure pattern, and acoustic emission (AE) characteristics were investigated by parametric studies. It has been found that, for a small homogeneity, rock failure is dominated by numerous microcracks within the crack bands that are smeared from the initial crack tips to the loading ends. Rock failure is dominated by macrocracks propagated from the initial crack tips to the loading ends for a large homogeneity. A logarithmic function is proposed to describe the relationship between the uniaxial compressive strength and the homogeneity. The AE characteristics and overall damage evolution are also significantly affected by the heterogeneity