Chapter Polyimide Films for Digital Isolators

Digital isolators provide compelling benefits over legacy opto-couplers in terms of high speed, low power consumption, high reliability, small size, high integration, and ease of use. Billions of digital isolators using micro-transformers have been widely adopted in many markets including automotive, industry automation, medical, and energy. What are essential for the high voltage performance for these digital isolators are polyimide films deposited in between the top spiral winding and bottom spiral winding for the stacked winding transformers. In this chapter, digital isolator construction using polyimide films as isolation layers will be reviewed. To meet various safety standards such as UL and VDE, digital isolators need to satisfy various high voltage performances, such as short duration withstand voltage, surge voltage, and working voltage. Polyimide aging behavior under various high voltage waveforms such as AC or DC was studied, and isolator’s working voltage is extrapolated through a polyimide lifetime model. Structural improvements to improve polyimide high voltage lifetime will also be discussed

Polyimide Films for Digital Isolators

Digital isolators provide compelling benefits over legacy opto-couplers in terms of high speed, low power consumption, high reliability, small size, high integration, and ease of use. Billions of digital isolators using micro-transformers have been widely adopted in many markets including automotive, industry automation, medical, and energy. What are essential for the high voltage performance for these digital isolators are polyimide films deposited in between the top spiral winding and bottom spiral winding for the stacked winding transformers. In this chapter, digital isolator construction using polyimide films as isolation layers will be reviewed. To meet various safety standards such as UL and VDE, digital isolators need to satisfy various high voltage performances, such as short duration withstand voltage, surge voltage, and working voltage. Polyimide aging behavior under various high voltage waveforms such as AC or DC was studied, and isolator’s working voltage is extrapolated through a polyimide lifetime model. Structural improvements to improve polyimide high voltage lifetime will also be discussed

Heat conduction of (111) Co/Cu superlattices

We report the observation of a large negative magnetothermal resistance in (111) Co/Cu superlattices grown by molecular beam epitaxy (MBE) techniques. The observed field dependence is proportional to that of the electrical resistance, in accordance with the Wiedemann–Franz law. The Lorentz number deduced from the measurements is (2.7±0.3)×10−8 V2/K2(2.7±0.3)×10−8V2/K2. The magnetothermopower also shows a similar correlation with resistivity. These findings reveal that large-angle elastic scattering of conduction electrons, arising from a spin-dependent density of states at the Fermi level, is the dominant process responsible for the observed large magnetotransport effects. In zero field, both electrons and phonons contribute to the thermal conduction of the MBE-grown Co/Cu system, at a ratio of about 1:2 near 300 K becoming nearly equal below 150 K. © 1997 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70031/2/JAPIAU-81-8-4586-1.pd

Mining Word Boundaries in Speech as Naturally Annotated Word Segmentation Data

Inspired by early research on exploring naturally annotated data for Chinese word segmentation (CWS), and also by recent research on integration of speech and text processing, this work for the first time proposes to mine word boundaries from parallel speech/text data. First we collect parallel speech/text data from two Internet sources that are related with CWS data used in our experiments. Then, we obtain character-level alignments and design simple heuristic rules for determining word boundaries according to pause duration between adjacent characters. Finally, we present an effective complete-then-train strategy that can better utilize extra naturally annotated data for model training. Experiments demonstrate our approach can significantly boost CWS performance in both cross-domain and low-resource scenarios.Comment: latest versio

Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph

Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference. In contrast to the previous studies, we propose a fast and lightweight model named as PTPCG. In our model, we design a novel strategy for event argument combination together with a non-autoregressive decoding algorithm via pruned complete graphs, which are constructed under the guidance of the automatically selected pseudo triggers. Compared to the previous systems, our system achieves competitive results with 19.8\% of parameters and much lower resource consumption, taking only 3.8\% GPU hours for training and up to 8.5 times faster for inference. Besides, our model shows superior compatibility for the datasets with (or without) triggers and the pseudo triggers can be the supplements for annotated triggers to make further improvements. Codes are available at https://github.com/Spico197/DocEE .Comment: Accepted to IJCAI'202

Heat conduction in Ba 1−x K x BiO 3

We have investigated heat conduction of single crystal Ba 1−x K x BiO 3 in the temperature range of 2–300 K and in a magnetic field of up to 6 Tesla. Temperature dependence of thermal conductivity κ(T) reveals the participation of both electrons and phonons with their relative contributions that depend critically on the potassium doping concentration. Crystals underdoped with potassium (samples with higher T c ) exhibit a strong suppression of κ and a glass-like temperature dependence. In contrast, those with a higher potassium content (lower T c ) show an increase as temperature decreases with a peak near 23 K. Field dependence of κ(H) is also very sensitive to the level of potassium doping. Crystals exhibiting a large phonon contribution show an initial drop in κ(H) at low fields followed by a minimum and then a slow rise to saturation as the field increases. The initial drop is due to the additional phonon scattering by magnetic vortices as the sample enters a mixed state. The high field behavior of κ(H) , arising from a continuous break-up of Cooper pairs, exhibits scaling which suggests the presence of an unconventional superconducting gap structure in this material.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45123/1/10948_2004_Article_BF00722826.pd

Time variant natural frequencies of a roadway bridge under stochastic vehicle flow

A general framework for investigating the on-load frequencies of roadway bridges under stochastic traffic flows was developed. The cellular automaton (CA) model was adopted to develop the stochastic traffic flow. The on-load natural frequencies of the bridge are analyzed statistically. The results show that the on-load frequencies of bridge are less than the corresponding natural frequencies of the bridge. For higher or lower traffic occupancies, the fluctuation of on-load natural frequencies of the bridge becomes smaller than that under the middle range of traffic flow densities. A linear relationship exists between the mean frequency difference and the traffic flow density, with the mean slope of regression lines for the first four natural frequencies being 0.0844. There is a stronger linear relationship between the mean frequency difference and the total traffic weight, with the mean slope being 0.482. Based on traffic flow density or total traffic weight on the bridge, it is possible to make an estimate of the effect of traffic flows on the on-load frequency of a reinforced concrete continuous beam bridge using the regression relationships

The expression and antigenicity of a truncated spike-nucleocapsid fusion protein of severe acute respiratory syndrome-associated coronavirus

<p>Abstract</p> <p>Background</p> <p>In the absence of effective drugs, controlling SARS relies on the rapid identification of cases and appropriate management of the close contacts, or effective vaccines for SARS. Therefore, developing specific and sensitive laboratory tests for SARS as well as effective vaccines are necessary for national authorities.</p> <p>Results</p> <p>Genes encoding truncated nucleocapsid (N) and spike (S) proteins of <it>SARSCoV </it>were cloned into the expression vector <it>pQE30 </it>and fusionally expressed in <it>Escherichia coli </it>M15. The fusion protein was analyzed for reactivity with SARS patients' sera and with anti-sera against the two human coronaviruses <it>HCoV </it>229E and <it>HCoV </it>OC43 by ELISA, IFA and immunoblot assays. Furthermore, to evaluate the antigen-specific humoral antibody and T-cell responses in mice, the fusion protein was injected into 6-week-old BALB/c mice and a neutralization test as well as a T-cell analysis was performed. To evaluate the antiviral efficacy of immunization, BALB/c mice were challenged intranasally with <it>SARSCoV </it>at day 33 post injection and viral loads were determined by fluorescent quantitative RT-PCR. Serological results showed that the diagnostic sensitivity and specificity of the truncated S-N fusion protein derived the SARS virus were > 99% (457/460) and 100.00% (650/650), respectively. Furthermore there was no cross-reactivity with other two human coronaviruses. High titers of antibodies to <it>SRASCoV </it>appeared in the immunized mice and the neutralization test showed that antibodies to the fusion protein could inhibit <it>SARSCoV</it>. The T cell proliferation showed that the fusion protein could induce an antigen-specific T-cell response. Fluorescent quantitative RT-PCR showed that BALB/c mice challenged intranasally with <it>SARSCoV </it>at day 33 post injection were completely protected from virus replication.</p> <p>Conclusion</p> <p>The truncated S-N fusion protein is a suitable immunodiagnostic antigen and vaccine candidate.</p

Mirror: A Universal Framework for Various Information Extraction Tasks

Sharing knowledge between information extraction tasks has always been a challenge due to the diverse data formats and task variations. Meanwhile, this divergence leads to information waste and increases difficulties in building complex applications in real scenarios. Recent studies often formulate IE tasks as a triplet extraction problem. However, such a paradigm does not support multi-span and n-ary extraction, leading to weak versatility. To this end, we reorganize IE problems into unified multi-slot tuples and propose a universal framework for various IE tasks, namely Mirror. Specifically, we recast existing IE tasks as a multi-span cyclic graph extraction problem and devise a non-autoregressive graph decoding algorithm to extract all spans in a single step. It is worth noting that this graph structure is incredibly versatile, and it supports not only complex IE tasks, but also machine reading comprehension and classification tasks. We manually construct a corpus containing 57 datasets for model pretraining, and conduct experiments on 30 datasets across 8 downstream tasks. The experimental results demonstrate that our model has decent compatibility and outperforms or reaches competitive performance with SOTA systems under few-shot and zero-shot settings. The code, model weights, and pretraining corpus are available at https://github.com/Spico197/Mirror .Comment: Accepted to EMNLP23 main conferenc