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  <doc>
    <id>9996</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
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    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
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    <title language="eng">Reconstructing sudden ambient temperature changes for forensic death time estimation using temperatures in two closed compartments: Proof of concept</title>
    <abstract language="eng">Ambient temperature TA has a strong impact on temperature-based time since death estimation (TTDE). Frequently TA is lowered instantaneously at some time t0 from a previous value TA0 to TA1 &lt; TA0 by, e.g., opening a window or a door. We aim at reconstructing TA0 and t0. &#13;
TTDE literature suggests temperature measurements in closed compartments such as cupboards or neighboring rooms, where TA0 could have been ‘preserved’ after t0. We aim to estimate t0 and TA0 from temperature measurements TZ(t) in closed compartments Z at times t &gt; t0. &#13;
We obtain promising results assuming Newtonian cooling for boxes filled with air, heaps of clothes, or books in two different experimental scenarios. Two different parameter estimators, (TA0^, t0^) based on four temperature measurements and (TA0*, t0*) for 4N measurements were tested.&#13;
Our results in a climate chamber were partially appropriate for TTDE input. A decline at time t0 from TA0 = 22.5°C ↓ TA1 = 14°C was reconstructed at t = t0 + 95min with relative deviations ρt0^ = 27% and ρTA0^ = 19% relative to t - t0 and TA0 – TA1 respectively, for N = 1 with span Δt = 50min. For N = 200 in a time interval [t0 + 95min, t0  + 295min] we found ρt0^ = 5% and ρTA0^ = 11% with the same Δt. &#13;
Further research is necessary to guarantee applicability in routine casework, in particular with respect to more elaborate cooling models, estimation algorithms, and evaluation localization.</abstract>
    <parentTitle language="deu">International Journal of Legal Medicine</parentTitle>
    <identifier type="old">bioRXiv https://doi.org/10.1101/2025.11.14.688394</identifier>
    <enrichment key="PeerReviewed">yes</enrichment>
    <enrichment key="SubmissionStatus">accepted for publication</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="AcceptedDate">2026-03-08</enrichment>
    <author>Jayant Shanmugam Subramaniam</author>
    <submitter>Martin Weiser</submitter>
    <author>Michael Hubig</author>
    <author>Sebastian Schenkl</author>
    <author>Holger Muggenthaler</author>
    <author>Steffen Springer</author>
    <author>Martin Weiser</author>
    <author>Jakob Sudau</author>
    <author>Faisal Shah</author>
    <author>Gita Mall</author>
    <collection role="institutes" number="num">Numerical Mathematics</collection>
    <collection role="persons" number="weiser">Weiser, Martin</collection>
    <collection role="projects" number="UJena-Forensic">UJena-Forensic</collection>
    <collection role="institutes" number="MSoCP">Modeling and Simulation of Complex Processes</collection>
    <collection role="persons" number="sudau">Sudau, Jakob</collection>
    <collection role="persons" number="shah">Shah, Faisal</collection>
  </doc>
</export-example>
