“¥”既作为人民币的书写符号，又代表人民币的币制，还表示人民币的单位“元”。在经济往来和会计核算中用阿拉伯数字填写金额时，在金额首位之前加一个“¥”符号，既可防止在金额前填加数字，又可表明是人民币的金额数量。由于“¥”本身表示人民币的单位，所以，凡是在金额前加了“¥”符号的，金额后就不需要再加“元”字。
The review is performed around the J-TEXT and EAST disruption databases depending on the past work13,51. Discharges with the J-Textual content tokamak are employed for validating the success of your deep fusion characteristic extractor, as well as featuring a pre-skilled design on J-Textual content for even more transferring to forecast disruptions from your EAST tokamak. To be certain the inputs from the disruption predictor are kept the identical, 47 channels of diagnostics are picked from both J-Textual content and EAST respectively, as is proven in Table four.
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Mixing info from the two goal and existing devices is one way of transfer learning, occasion-based transfer learning. But the knowledge carried with the limited facts within the goal machine may be flooded by information from the present machines. These works are completed amid tokamaks with comparable configurations and sizes. Having said that, the gap involving long term tokamak reactors and any tokamaks existing today may be very large23,24. Measurements of your device, operation regimes, configurations, feature distributions, disruption leads to, characteristic paths, and other components will all result in several plasma performances and distinctive disruption procedures. Thus, In this particular function we chosen the J-Textual content and also the EAST tokamak that have Visit Site a substantial difference in configuration, operation regime, time scale, function distributions, and disruptive triggers, to show the proposed transfer learning technique.
Tokamaks are the most promising way for nuclear fusion reactors. Disruption in tokamaks is usually a violent function that terminates a confined plasma and triggers unacceptable damage to the device. Equipment Understanding models are extensively used to predict incoming disruptions. However, long run reactors, with A lot better stored Power, are unable to offer more than enough unmitigated disruption data at substantial overall performance to practice the predictor in advance of harmful them selves. Right here we use a deep parameter-dependent transfer Discovering strategy in disruption prediction.
Even so, investigation has it which the time scale with the “disruptive�?phase may vary dependant upon unique disruptive paths. Labeling samples with an unfixed, precursor-related time is a lot more scientifically correct than employing a constant. In our review, we initial properly trained the model applying “serious�?labels based on precursor-linked periods, which made the design a lot more self-assured in distinguishing amongst disruptive and non-disruptive samples. However, we observed which the design’s functionality on unique discharges decreased when compared to your design educated employing regular-labeled samples, as is shown in Desk six. Even though the precursor-similar design was even now in the position to forecast all disruptive discharges, far more Wrong alarms happened and resulted in overall performance degradation.
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La cocción de las hojas se realiza hasta que tomen una coloración parda. Esta coloración se logra gracias a la intervención de los vapores del agua al contacto con la clorofila, ya que el vapor la diluye completamente.
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