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PDTB143ETR
+NomenclatureTRANS PREBIAS PNP 0.46W
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FabricantNexperia USA Inc.
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Pièce fabricant #PDTB143ETR
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Package TO-236-3, SC-59, SOT-23-3
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En stock2054
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Spécifications
| Attribut | Valeur |
| Supplier | Nexperia USA Inc. |
| Package | Tape & Reel (TR),Cut Tape (CT) |
| ProductStatus | Active |
| TransistorType | PNP - Pre-Biased |
| Current-Collector(Ic)(Max) | 500 mA |
| Voltage-CollectorEmitterBreakdown(Max) | 50 V |
| Resistor-Base(R1) | 4.7 kOhms |
| Resistor-EmitterBase(R2) | 4.7 kOhms |
| DCCurrentGain(hFE)(Min)@IcVce | 60 @ 50mA, 5V |
| VceSaturation(Max)@IbIc | 100mV @ 2.5mA, 50mA |
| Current-CollectorCutoff(Max) | 500nA |
| Frequency-Transition | 140 MHz |
| Power-Max | 320 mW |
| MountingType | Surface Mount |
| Package/Case | TO-236-3, SC-59, SOT-23-3 |
Présentation
Description
- PDTB is a richly annotated English corpus that encodes discourse connectives and their discourse relations (e.g., Expansion, Contingency, Temporal, Comparison) between text spans.
- It supports research in discourse parsing, text understanding, summarization, and argument structure.
- A course/module named PDTB143ETR would typically cover:
- PDTB annotation scheme and relation taxonomy
- Data preprocessing, segmentation, and alignment
- Methods for automatic discourse relation classification and connective identification
- Experimental design and evaluation metrics (precision/recall/F1, ROC, cross-domain)
- Hands-on labs using PDTB data
- Applications to NLP tasks and a final project
- Prerequisites: basic NLP and Python programming.
If you meant something else by PDTB143ETR, please share the context and I’ll tailor the intro.
Equivalent
Application
- High-speed fiber-optic communication receivers and data links
- Laser power monitoring and feedback control in optical systems
- Light detection in analytical instruments (spectroscopy, fluorescence, environmental sensing)
- Time-domain measurements, ranging, and lidar applications
- Ambient light/optical sensing in consumer and industrial electronics