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		<title>Hand-crafted features beat raw sequences when battery protocols shift</title>
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		<pubDate>Mon, 19 Oct 2026 18:49:44 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Attention Mechanism]]></category>
		<category><![CDATA[formulations]]></category>
		<category><![CDATA[knee-point prediction]]></category>
		<category><![CDATA[lithium-ion battery]]></category>
		<category><![CDATA[LSTM]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[multi-step]]></category>
		<category><![CDATA[prognosis]]></category>
		<category><![CDATA[protocol shift]]></category>
		<category><![CDATA[Single-step]]></category>
		<category><![CDATA[statistical replication]]></category>
		<category><![CDATA[versus]]></category>
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					<description><![CDATA[Every lithium-ion cell in an electric vehicle carries a hidden countdown. Long before capacity visibly fades, subtle electrochemical fingerprints in early charging cycles already encode how quickly the battery will age, when its degradation curve will bend sharply downward at]]></description>
		
		
		
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