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        <identifier>oai:figshare.com:article/32141644</identifier>
        <datestamp>2026-04-30T00:00:00Z</datestamp>
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          <identifier identifierType="DOI">10.1021/acs.nanolett.6c00072.s001</identifier>
          <alternateIdentifiers>
            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/journal_contribution/Hybrid-2D_Excitonic_Metasurfaces_for_Complex_Amplitude_Modulation/32141644</alternateIdentifier>
          </alternateIdentifiers>
          <relatedIdentifiers>
            <relatedIdentifier relatedIdentifierType="URL" relationType="HasPart">https://ndownloader.figshare.com/files/64152496</relatedIdentifier>
          </relatedIdentifiers>
          <creators>
            <creator>
              <creatorName>Hoekstra, Tom</creatorName>
              <givenName>Tom</givenName>
              <familyName>Hoekstra</familyName>
            </creator>
            <creator>
              <creatorName>Brongersma, Mark L.</creatorName>
              <givenName>Mark L.</givenName>
              <familyName>Brongersma</familyName>
            </creator>
            <creator>
              <creatorName>van de Groep, Jorik</creatorName>
              <givenName>Jorik</givenName>
              <familyName>van de Groep</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[Hybrid-2D Excitonic
Metasurfaces for Complex Amplitude
Modulation]]></title>
          </titles>
          <subjects>
            <subject>Biophysics</subject>
            <subject>Genetics</subject>
            <subject>Neuroscience</subject>
            <subject>Space Science</subject>
            <subject>Physical Sciences not elsewhere classified</subject>
            <subject>Information Systems not elsewhere classified</subject>
            <subject>tunable excitonic response</subject>
            <subject>second tunable monolayer</subject>
            <subject>active metasurfaces promise</subject>
            <subject>achieve independent control</subject>
            <subject>2d excitonic metasurfaces</subject>
            <subject>uniform amplitude profile</subject>
            <subject>2 &lt;/ sub</subject>
            <subject>passive metasurfaces</subject>
            <subject>monolayer ws</subject>
            <subject>existing metasurfaces</subject>
            <subject>phase control</subject>
            <subject>visible regime</subject>
            <subject>visible light</subject>
            <subject>temporal domain</subject>
            <subject>subwavelength scale</subject>
            <subject>steering metadevice</subject>
            <subject>shape wavefronts</subject>
            <subject>scattering amplitude</subject>
            <subject>results demonstrate</subject>
            <subject>reconfigurable beam</subject>
            <subject>numerically demonstrate</subject>
            <subject>holographic displays</subject>
            <subject>adaptive optics</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="JournalArticle">Journal contribution</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>ACS Publications</publisher>
          <rightsList>
            <rights rightsURI="https://creativecommons.org/licenses/by-nc/4.0/" rightsIdentifier="CC BY-NC 4.0"/>
            <rights rightsURI="http://purl.org/coar/access_right/c_abf2" rightsIdentifier="open access"/>
          </rightsList>
          <descriptions>
            <description descriptionType="Abstract"><![CDATA[Dynamic control of
visible light is crucial for technologies
such
as holographic displays and adaptive optics. Passive metasurfaces
can shape wavefronts at the subwavelength scale, and active metasurfaces
promise to extend this functionality into the temporal domain. However,
existing metasurfaces for dynamic phase manipulation typically cannot
deliver phase modulation across a broad range without causing variations
in the scattering amplitude. Here, we use an inverse-design pipeline
to numerically demonstrate a hybrid-2D excitonic metasurface platform
offering independent amplitude and phase control in the visible regime.
Harnessing the gate-tunable excitonic response of monolayer WS<sub>2</sub> retrieved from experiments, we design a π-phase modulator
with a uniform amplitude profile. Adding a second tunable monolayer,
we achieve independent control of the amplitude and phase over the
full 0–2π phase range, which we leverage for a reconfigurable
beam-steering metadevice. Our results demonstrate how hybrid-2D excitonic
metasurfaces enable electrically tunable wavefront shaping in the
visible regime.]]></description>
          </descriptions>
        </resource>
      </metadata>
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      <header>
        <identifier>oai:figshare.com:article/32141641</identifier>
        <datestamp>2026-04-30T00:00:00Z</datestamp>
        <setSpec>category_4</setSpec>
        <setSpec>category_7</setSpec>
        <setSpec>category_8</setSpec>
        <setSpec>category_19</setSpec>
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        <setSpec>category_64</setSpec>
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          <identifier identifierType="DOI">10.1021/acsomega.5c12846.s001</identifier>
          <alternateIdentifiers>
            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/journal_contribution/Antiviral_Activity_of_Dendritic_Heparan_Sulfate_Mimetics_against_Respiratory_Syncytial_Virus_and_Herpes_Simplex_Virus_1/32141641</alternateIdentifier>
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          <creators>
            <creator>
              <creatorName>Yue, Yiming</creatorName>
              <givenName>Yiming</givenName>
              <familyName>Yue</familyName>
            </creator>
            <creator>
              <creatorName>Chang, Amelia</creatorName>
              <givenName>Amelia</givenName>
              <familyName>Chang</familyName>
            </creator>
            <creator>
              <creatorName>Spijkers-Shaw, Sam</creatorName>
              <givenName>Sam</givenName>
              <familyName>Spijkers-Shaw</familyName>
            </creator>
            <creator>
              <creatorName>Devlin, Rory</creatorName>
              <givenName>Rory</givenName>
              <familyName>Devlin</familyName>
            </creator>
            <creator>
              <creatorName>Li, Ye</creatorName>
              <givenName>Ye</givenName>
              <familyName>Li</familyName>
            </creator>
            <creator>
              <creatorName>Rendle, Phillip M.</creatorName>
              <givenName>Phillip M.</givenName>
              <familyName>Rendle</familyName>
            </creator>
            <creator>
              <creatorName>Nutsford, Ashley</creatorName>
              <givenName>Ashley</givenName>
              <familyName>Nutsford</familyName>
            </creator>
            <creator>
              <creatorName>Sullivan-Hill, Blake</creatorName>
              <givenName>Blake</givenName>
              <familyName>Sullivan-Hill</familyName>
            </creator>
            <creator>
              <creatorName>Wang, Carol</creatorName>
              <givenName>Carol</givenName>
              <familyName>Wang</familyName>
            </creator>
            <creator>
              <creatorName>Zubkova, Olga V.</creatorName>
              <givenName>Olga V.</givenName>
              <familyName>Zubkova</familyName>
            </creator>
            <creator>
              <creatorName>Netzler, Natalie E.</creatorName>
              <givenName>Natalie E.</givenName>
              <familyName>Netzler</familyName>
            </creator>
            <creator>
              <creatorName>Taylor, John A.</creatorName>
              <givenName>John A.</givenName>
              <familyName>Taylor</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[Antiviral Activity
of Dendritic Heparan Sulfate Mimetics
against Respiratory Syncytial Virus and Herpes Simplex Virus‑1]]></title>
          </titles>
          <subjects>
            <subject>Biochemistry</subject>
            <subject>Medicine</subject>
            <subject>Microbiology</subject>
            <subject>Pharmacology</subject>
            <subject>Immunology</subject>
            <subject>Cancer</subject>
            <subject>Hematology</subject>
            <subject>Infectious Diseases</subject>
            <subject>Virology</subject>
            <subject>Biological Sciences not elsewhere classified</subject>
            <subject>Chemical Sciences not elsewhere classified</subject>
            <subject>promising new class</subject>
            <subject>observed synergistic effects</subject>
            <subject>negatively charged sulfate</subject>
            <subject>mediated membrane fusion</subject>
            <subject>lead compound inhibited</subject>
            <subject>spectrum antiviral therapeutics</subject>
            <subject>respiratory syncytial virus</subject>
            <subject>synthetic hs mimetics</subject>
            <subject>clinical antiviral remdesivir</subject>
            <subject>inhibit virus infection</subject>
            <subject>lack anticoagulant activity</subject>
            <subject>inhibit infection</subject>
            <subject>antiviral activity</subject>
            <subject>anticoagulant activity</subject>
            <subject>virus entry</subject>
            <subject>virus binding</subject>
            <subject>clinical use</subject>
            <subject>antiviral potency</subject>
            <subject>vivo &lt;/</subject>
            <subject>vitro &lt;/</subject>
            <subject>viral proteins</subject>
            <subject>receptor decoys</subject>
            <subject>investigated inhibition</subject>
            <subject>hs occurs</subject>
            <subject>hs mimetic</subject>
            <subject>glycosaminoglycan related</subject>
            <subject>electrostatic interactions</subject>
            <subject>carboxyl groups</subject>
            <subject>attachment receptor</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="JournalArticle">Journal contribution</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>ACS Publications</publisher>
          <rightsList>
            <rights rightsURI="https://creativecommons.org/licenses/by-nc/4.0/" rightsIdentifier="CC BY-NC 4.0"/>
            <rights rightsURI="http://purl.org/coar/access_right/c_abf2" rightsIdentifier="open access"/>
          </rightsList>
          <descriptions>
            <description descriptionType="Abstract"><![CDATA[Heparan sulfate (HS) can act as an attachment receptor
for many
different animal viruses. Virus binding to HS occurs through electrostatic
interactions between the negatively charged sulfate and carboxyl groups
of HS and positively charged amino acids present in viral proteins.
Soluble heparin, a glycosaminoglycan related to HS, can inhibit infection
by many viruses, but the clinical use of heparin is limited by its
anticoagulant activity. Synthetic HS mimetics that lack anticoagulant
activity have been developed and can inhibit virus infection <i>in vitro</i> and <i>in vivo</i>. Building on this
precedent, we investigated inhibition of respiratory syncytial virus
(RSV) and herpes simplex virus type-1 (HSV-1) by a set of tri- and
tetrameric dendritic HS mimetics. Several of these compounds exhibited
submicromolar inhibition of both viruses when used as receptor decoys
in assays of virus entry, and a lead compound inhibited the cell-to-cell
spread of RSV <i>in vitro</i> and RSV-mediated membrane
fusion. Additionally, we observed synergistic effects when an HS mimetic
was used in combination with clinical antiviral remdesivir. The solubility,
lack of anticoagulant activity, and antiviral potency of these dendritic
HS mimetics make them a promising new class of broad-spectrum antiviral
therapeutics.]]></description>
          </descriptions>
        </resource>
      </metadata>
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    <record>
      <header>
        <identifier>oai:figshare.com:article/32141638</identifier>
        <datestamp>2026-04-30T00:00:00Z</datestamp>
        <setSpec>category_15</setSpec>
        <setSpec>category_19</setSpec>
        <setSpec>category_106</setSpec>
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          <identifier identifierType="DOI">10.1021/acsomega.5c05861.s001</identifier>
          <alternateIdentifiers>
            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/journal_contribution/Molecular_and_Computational_Basis_of_Taste_Perception_A_Review_toward_the_Digital_Language_of_Taste_/32141638</alternateIdentifier>
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            <relatedIdentifier relatedIdentifierType="URL" relationType="HasPart">https://ndownloader.figshare.com/files/64152487</relatedIdentifier>
          </relatedIdentifiers>
          <creators>
            <creator>
              <creatorName>Ashikhmina, Mariia S.</creatorName>
              <givenName>Mariia S.</givenName>
              <familyName>Ashikhmina</familyName>
            </creator>
            <creator>
              <creatorName>Dutta, Kunal</creatorName>
              <givenName>Kunal</givenName>
              <familyName>Dutta</familyName>
            </creator>
            <creator>
              <creatorName>Normatov, Saadiallakh</creatorName>
              <givenName>Saadiallakh</givenName>
              <familyName>Normatov</familyName>
            </creator>
            <creator>
              <creatorName>Filozop, Vladislav S.</creatorName>
              <givenName>Vladislav S.</givenName>
              <familyName>Filozop</familyName>
            </creator>
            <creator>
              <creatorName>Volodarskiy, Mikhail O.</creatorName>
              <givenName>Mikhail O.</givenName>
              <familyName>Volodarskiy</familyName>
            </creator>
            <creator>
              <creatorName>Volkova, Olga</creatorName>
              <givenName>Olga</givenName>
              <familyName>Volkova</familyName>
            </creator>
            <creator>
              <creatorName>Ulasevich, Sviatlana A.</creatorName>
              <givenName>Sviatlana A.</givenName>
              <familyName>Ulasevich</familyName>
            </creator>
            <creator>
              <creatorName>Skorb, Ekaterina V.</creatorName>
              <givenName>Ekaterina V.</givenName>
              <familyName>Skorb</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[Molecular and Computational
Basis of Taste Perception:
A Review toward the “Digital Language of Taste”]]></title>
          </titles>
          <subjects>
            <subject>Neuroscience</subject>
            <subject>Pharmacology</subject>
            <subject>Science Policy</subject>
            <subject>Biological Sciences not elsewhere classified</subject>
            <subject>Chemical Sciences not elsewhere classified</subject>
            <subject>Information Systems not elsewhere classified</subject>
            <subject>“ digital language</subject>
            <subject>significant limitations remain</subject>
            <subject>provide new avenues</subject>
            <subject>human subjective experience</subject>
            <subject>detailed experimental protocols</subject>
            <subject>taste ” background</subject>
            <subject>predict taste profiles</subject>
            <subject>predict taste characteristics</subject>
            <subject>model taste mechanisms</subject>
            <subject>bridging computational predictions</subject>
            <subject>functional modeling across</subject>
            <subject>multisensory individualized perception</subject>
            <subject>incomplete structural data</subject>
            <subject>including molecular docking</subject>
            <subject>applying ml algorithms</subject>
            <subject>resolution receptor modeling</subject>
            <subject>taste perception</subject>
            <subject>multisensory integration</subject>
            <subject>taste receptors</subject>
            <subject>receptor activation</subject>
            <subject>generate receptor</subject>
            <subject>computational chemistry</subject>
            <subject>computational basis</subject>
            <subject>molecular modeling</subject>
            <subject>modeling salt</subject>
            <subject>transformer architectures</subject>
            <subject>time scales</subject>
            <subject>specific focus</subject>
            <subject>specific compounds</subject>
            <subject>review toward</subject>
            <subject>recent developments</subject>
            <subject>recent advances</subject>
            <subject>prioritize high</subject>
            <subject>primary factors</subject>
            <subject>physiological factors</subject>
            <subject>particularly focusing</subject>
            <subject>molecular dynamics</subject>
            <subject>molecular descriptors</subject>
            <subject>md ),</subject>
            <subject>machine learning</subject>
            <subject>ion channels</subject>
            <subject>integrating md</subject>
            <subject>improving accuracy</subject>
            <subject>future efforts</subject>
            <subject>despite advances</subject>
            <subject>deep learning</subject>
            <subject>coupled receptors</subject>
            <subject>artificial intelligence</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="JournalArticle">Journal contribution</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>ACS Publications</publisher>
          <rightsList>
            <rights rightsURI="https://creativecommons.org/licenses/by-nc/4.0/" rightsIdentifier="CC BY-NC 4.0"/>
            <rights rightsURI="http://purl.org/coar/access_right/c_abf2" rightsIdentifier="open access"/>
          </rightsList>
          <descriptions>
            <description descriptionType="Abstract"><![CDATA[Background: Taste
is a multisensory individualized perception.
The variability of genetic and physiological factors and the lack
of standardized or detailed experimental protocols for research on
taste perception create many methodological difficulties in studies.
Recent advances in computational chemistry, molecular modeling, and
machine learning (ML) provide new avenues to model taste mechanisms,
predict taste profiles, and design novel taste compounds, particularly
focusing on G-protein-coupled receptors and ion channels. Results:
This review synthesizes current computational approaches to taste
research, including molecular docking, molecular dynamics (MD), and
ML. It highlights taste receptors’ structural and functional
modeling across all primary modalitiessweet, bitter, umami,
salty, and sour. Specific focus is given to the challenges of modeling
salt and sour taste, integrating MD with receptor–ligand interactions,
and applying ML algorithms to predict taste characteristics from molecular
descriptors. Recent developments in artificial intelligence (AI) models,
such as deep learning and transformer architectures, are improving
accuracy but still raise questions regarding the interpretability
and generalizability of the data. Conclusions: Despite advances in
taste perception, significant limitations remain. One of the primary
factors is incomplete structural data on taste receptors and problems
with modeling the long-time scales of receptor activation. This leads
to inadequate models for multisensory integration. Future efforts
should prioritize high-resolution receptor modeling, hybrid computational–experimental
validation, and the expansion of AI applications to generate receptor-specific
compounds. Bridging computational predictions with human subjective
experience will be key to advancing digital taste perception.]]></description>
          </descriptions>
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      <header>
        <identifier>oai:figshare.com:article/32141611</identifier>
        <datestamp>2026-04-30T23:36:45Z</datestamp>
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        <setSpec>item_type_1</setSpec>
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          <identifier identifierType="DOI">10.6084/m9.figshare.32141611.v1</identifier>
          <alternateIdentifiers>
            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/figure/Amelogenin_histidine_Figures_1-4/32141611</alternateIdentifier>
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          <creators>
            <creator>
              <creatorName>Diekwisch, Thomas</creatorName>
              <givenName>Thomas</givenName>
              <familyName>Diekwisch</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[Amelogenin histidine Figures 1-4]]></title>
          </titles>
          <subjects>
            <subject>Craniofacial biology</subject>
            <subject>Amelogenin</subject>
            <subject>Histidine</subject>
            <subject>Biomineralization</subject>
            <subject>Tooth Enamel</subject>
            <subject>Ameloblasts</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="Image">Figure</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>figshare</publisher>
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            <rights rightsURI="https://creativecommons.org/licenses/by/4.0/" rightsIdentifier="CC BY 4.0"/>
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          <descriptions>
            <description descriptionType="Abstract"><![CDATA[<p dir="ltr"><b>Figure 1.</b><b> </b><b>Differences in the incisor surface between wild-type, Amel KO, His+ and His- mutant mice.</b> WT incisors displayed a yellowish and smooth surface with Chisel-shaped tips. In contrast, KO mouse incisors were chalky white with a punctuated surface pattern, resulting from the terminal dentin tubule ends, and there was no enamel visible. The incisors of His+ mice displayed broken tips and an enamel layer covering only the basal half of the tooth, exposing the dentin layer at the incisal half. Incisors from His- mice featured defective incisal tips and globular mineral precipitates on the tooth surface.</p><p dir="ltr"><b>Figure 2.</b><b> </b><b>Effect of changes in histidine content on enamel birefringence. </b>(A-D) Images of ground sections under a polarizing microscope, demonstrating enamel birefringence. The WT enamel displayed birefringence, separating it from the adjacent dentin. In contrast, this birefringence was lost in KO, His+ and His- mice. (E-H) Images of molars embedded in resin. Compare the WT enamel occlusal surface characterized by cusps, grooves, and ridges, while the molars from Amel null and histidine mutant mice displayed a rough tooth surface and a worn-down occlusal surface.</p><p dir="ltr"><b>Figure 3.</b><b> </b><b>Reduced enamel thickness and matrix configuration in Histidine mutant mice as revealed by microCT analysis (C,D versus A) and by semithin sections (F-I).</b><b> </b>Wild-type (A) and amelogenin null enamel preparations (B) are displayed for comparison. Note the reduced thickness of the enamel layer in Histidine plus (C) and Histidine minus mice (D). Quantitative comparison (E). Wild-type semithin sections of three days postnatal first mandibular mouse molars (F) display adjacent enamel (en, blue) and dentin (de, purple) mineralized tissues, <a href="" target="_blank">revealing the representative enamel prism fishbone pattern. There were substantial differences between ameloblast (am) and enamel matrix (mx, arrow) shape and structure between all four groups. In comparison to wild-type controls (WT), His plus ameloblasts (G) contained ampulla-shaped vacuoles while there were distinct translucent vesicles in histidine-minus ameloblasts (H). The ameloblasts of amelogenin null mice were interrupted by metachromatic, spindle-shaped matrix deposits. The area of the developing enamel layer of wild-type mice (F) featured a thin layer of globular matrix deposits (mx, arrow) in His plus mice, while His minus mice were characterized by a thin, irregular shaped enamel matrix layer (mx, arrow). Amelogenin null mice highlighted minute matrix deposits only at the secretory tip of ameloblast Tomes processes (mx, arrow). The odontoblast (od) and the predentin layer (pd) were labeled for orientation.</a></p><p dir="ltr"><b>Figure 4.</b><b> </b><b>Representative SEM and TEM micrographs illustrating the changes in histidine content on enamel matrix configuration, prism and crystal structure as revealed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM).</b><b> </b>(A-D) SEM analysis of the shape and organization of enamel prisms. The WT enamel prisms displayed the typical herringbone decussation pattern, with individual crystals bundled into sheaths and prisms. In contrast, the apatite mineral crystals in the enamel region of KO mice were fused into short and densely organized, flower-shaped subunits. The enamel of His+ and His- mice was densely packed into trapezoid bundles (His+, C) or wrought into parallel arrangements (His-, D), abolishing the decussating pattern of their wild-type counterparts. (E-H) Transmission electron microscopy of wild-type mice revealed regular assemblies of nanosphere patterned proteins and initial protein-coated enamel crystals (E). Amelogenin null samples lacked the dense protein coat surrounding elongating crystals (F). Half of the apatite crystals (en) in amelogenin His+ samples were oriented perpendicular to the principal orientation of the crystals from the ameloblast to the dentin surface (en), while matrix subunits (mx) measured 2nm instead of 20nm in diameter (G). Crystal shapes in the His- samples featured uncoated enamel ribbons (rib) instead of crystals, while the matrix (mx) was dissociated from crystal surfaces and lacked the regular matrix pattern observed in the wildtype control (H).</p>]]></description>
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        <identifier>oai:figshare.com:article/32141623</identifier>
        <datestamp>2026-04-30T23:35:33Z</datestamp>
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            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/preprint/OMPRENG_PENDETEKSI_KERACUNAN_MBG/32141623</alternateIdentifier>
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            <relatedIdentifier relatedIdentifierType="URL" relationType="HasPart">https://ndownloader.figshare.com/files/64152439</relatedIdentifier>
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            <creator>
              <creatorName>Darwanto, Agus</creatorName>
              <givenName>Agus</givenName>
              <familyName>Darwanto</familyName>
            </creator>
            <creator>
              <creatorName>Meisya Nazwa, Alya</creatorName>
              <givenName>Alya</givenName>
              <familyName>Meisya Nazwa</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[OMPRENG PENDETEKSI KERACUNAN MBG]]></title>
          </titles>
          <subjects>
            <subject>Food chemistry and food sensory science</subject>
            <subject>Food safety, traceability, certification and authenticity</subject>
            <subject>Ompreng; MBG; Keracunan</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="Preprint">Preprint</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>figshare</publisher>
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            <rights rightsURI="http://purl.org/coar/access_right/c_abf2" rightsIdentifier="open access"/>
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          <descriptions>
            <description descriptionType="Abstract"><![CDATA[<p dir="ltr">Inovasi ompreng pendeteksi keracunan MBG merupakan solusi modern dalam mendukung program Makan Bergizi Gratis (MBG). Karya ini berhasil mengintegrasikan teknologi IoT, sensor gas, <i>machine learning</i>, serta desain ompreng. Melalui ompreng pendeteksi keracunan MBG, cemaran bakteri pada olahan MBG dapat dideteksi lebih dini. Selain itu, dukungan fitur pemantauan berbasis IoT memungkinkan pihak sekolah, pelajar, atau rekanan MBG untuk lebih mengontrol MBG yang disajikan.</p>]]></description>
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        <identifier>oai:figshare.com:article/32141593</identifier>
        <datestamp>2026-04-30T23:28:50Z</datestamp>
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            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/conference_contribution/Supplementary_materials_for_IMCSM26/32141593</alternateIdentifier>
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            <creator>
              <creatorName>Drachal, Krzysztof</creatorName>
              <givenName>Krzysztof</givenName>
              <familyName>Drachal</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[Supplementary materials for IMCSM26]]></title>
          </titles>
          <subjects>
            <subject>Cross-sectional analysis</subject>
            <subject>Economic models and forecasting</subject>
            <subject>Panel data analysis</subject>
            <subject>Time-series analysis</subject>
            <subject>cross-sectional clusters</subject>
            <subject>equal predictive ability</subject>
            <subject>panels of forecasts</subject>
            <subject>time clusters</subject>
            <subject>time-series forecasting</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="ConferenceProceeding">Conference contribution</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>figshare</publisher>
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            <description descriptionType="Abstract"><![CDATA[<p dir="ltr">Supplementary materials associated with the full paper presented at the International May Conference on Strategic Management - IMCSM26 (May 2026, Belgrade, Republic of Serbia)</p>]]></description>
          </descriptions>
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      <header>
        <identifier>oai:figshare.com:article/32141587</identifier>
        <datestamp>2026-04-30T23:26:15Z</datestamp>
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          <identifier identifierType="DOI">10.6084/m9.figshare.32141587.v1</identifier>
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            <alternateIdentifier alternateIdentifierType="URL">https://figshare.com/articles/conference_contribution/TOWARDS_AN_UNDERSTANDING_OF_THE_FORMATION_OF_MIXED-SPECIES_BIOFILMS_IN_THE_FOOD_PROCESSING_INDUSTRY_TEMPERATURE_EFFECTS_ON_BIOFILM_DEVELOPMENT_IN_LISTERIA_MONOCYTOGENES_PSEUDOMONAS_FLUORESCENS_ESCHERICHIA_COLI_AND_SALMONELLA_TYPHIMURIUM/32141587</alternateIdentifier>
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            <relatedIdentifier relatedIdentifierType="URL" relationType="HasPart">https://ndownloader.figshare.com/files/64152151</relatedIdentifier>
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            <creator>
              <creatorName>Akintayo, Obaloluwa Praise</creatorName>
              <givenName>Obaloluwa Praise</givenName>
              <familyName>Akintayo</familyName>
            </creator>
            <creator>
              <creatorName>Dixon, Ron</creatorName>
              <givenName>Ron</givenName>
              <familyName>Dixon</familyName>
            </creator>
            <creator>
              <creatorName>Awolusi, Oluyemi</creatorName>
              <givenName>Oluyemi</givenName>
              <familyName>Awolusi</familyName>
              <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org">0000-0002-3285-3409</nameIdentifier>
            </creator>
            <creator>
              <creatorName>Onarinde, Bukola</creatorName>
              <givenName>Bukola</givenName>
              <familyName>Onarinde</familyName>
              <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org">0000-0001-6506-4185</nameIdentifier>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[TOWARDS AN UNDERSTANDING OF THE FORMATION OF MIXED-SPECIES BIOFILMS IN THE FOOD PROCESSING INDUSTRY: TEMPERATURE EFFECTS ON BIOFILM DEVELOPMENT IN LISTERIA MONOCYTOGENES, PSEUDOMONAS FLUORESCENS, ESCHERICHIA COLI, AND SALMONELLA TYPHIMURIUM]]></title>
          </titles>
          <subjects>
            <subject>Bacteriology</subject>
            <subject>Microbiology not elsewhere classified</subject>
            <subject>Microbial Biofilms</subject>
            <subject>multi-species biofilm</subject>
            <subject>temperature dependent growth rate</subject>
            <subject>Food processing environments</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="ConferenceProceeding">Conference contribution</resourceType>
          <publicationYear>2026</publicationYear>
          <publisher>figshare</publisher>
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            <description descriptionType="Abstract"><![CDATA[<p dir="ltr">Microbial biofilms pose a significant challenge in food processing environments due to their persistence on surfaces, resistance to traditional disinfection methods and substantial contribution to food contamination and spoilage, leading to increased risks to food safety and public health. Biofilm formation can be influenced by environmental conditions commonly associated with food processing environments, including temperature. We have investigated how biofilms form using different single species and combinations of Listeria monocytogenes, Pseudomonas fluorescens, Escherichia coli, and Salmonella typhimurium and to what extent mixed species biofilms are influenced by varying ambient temperatures.</p><p dir="ltr">Listeria monocytogenes, Pseudomonas fluorescens, Escherichia coli, and Salmonella typhimurium, reference strains alone and in combination, were selected for their relevance to food safety and spoilage. Biofilm formation was assessed using microtiter plate assays. Temperature-dependent biofilm formation was evaluated at 25°C and 30°C, and incubated for 72 hours to reflect temperatures relevant to food processing, storage and optimal bacterial growth. Biofilm biomass was quantified using the crystal violet staining technique.</p><p dir="ltr"><br></p>]]></description>
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        <identifier>oai:figshare.com:article/32141590</identifier>
        <datestamp>2026-04-30T23:24:56Z</datestamp>
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              <creatorName>Wright, Chris</creatorName>
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          <titles>
            <title><![CDATA[Revolution in the Twenty-First Century: A Reconsideration of Marxism]]></title>
          </titles>
          <subjects>
            <subject>Social change</subject>
            <subject>Social theory</subject>
            <subject>Social and political philosophy</subject>
            <subject>revolution</subject>
            <subject>cooperatives</subject>
            <subject>solidarity economy</subject>
            <subject>socialism</subject>
            <subject>Karl Marx</subject>
            <subject>Marxism</subject>
            <subject>anarchism</subject>
            <subject>class struggle</subject>
            <subject>historical materialism</subject>
            <subject>anarcho-syndicalism</subject>
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          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
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          </rightsList>
          <descriptions>
            <description descriptionType="Abstract"><![CDATA[<p dir="ltr">This article proposes a revision of the traditional Marxist conceptualization of socialist revolution, a revision that makes the theory more relevant to circumstances in the twenty-first century. It argues that nearly all Marxists have misunderstood the strategic implications of historical materialism for making a revolution.</p>]]></description>
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        <datestamp>2026-04-30T23:22:21Z</datestamp>
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              <creatorName>Martik, Megan</creatorName>
              <givenName>Megan</givenName>
              <familyName>Martik</familyName>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[CZI Image Viewing Instructions]]></title>
          </titles>
          <subjects>
            <subject>Cell development, proliferation and death</subject>
            <subject>Systems biology</subject>
            <subject>Biochemistry and cell biology not elsewhere classified</subject>
            <subject>Genomics</subject>
            <subject>Neural crest cells (NCCs)</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
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            <description descriptionType="Abstract"><![CDATA[<p dir="ltr">This file explains how to view .czi raw images.</p>]]></description>
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        <identifier>oai:figshare.com:article/32141311</identifier>
        <datestamp>2026-04-30T23:12:08Z</datestamp>
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            <creator>
              <creatorName>Chen, Shiyu</creatorName>
              <givenName>Shiyu</givenName>
              <familyName>Chen</familyName>
            </creator>
            <creator>
              <creatorName>Alrashid, Tarfah</creatorName>
              <givenName>Tarfah</givenName>
              <familyName>Alrashid</familyName>
            </creator>
            <creator>
              <creatorName>Noy, Natasha</creatorName>
              <givenName>Natasha</givenName>
              <familyName>Noy</familyName>
              <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org">0000-0002-7437-0624</nameIdentifier>
            </creator>
          </creators>
          <titles>
            <title><![CDATA[LLM Autorater Prompts for Agentic Data FAIRness]]></title>
          </titles>
          <subjects>
            <subject>Autonomous agents and multiagent systems</subject>
            <subject>Information retrieval and web search</subject>
            <subject>prompts</subject>
            <subject>agent</subject>
            <subject>Information retrieval -- Methodology</subject>
          </subjects>
          <dates>
            <date dateType="Created">2026-04-30</date>
            <date dateType="Updated">2026-04-30</date>
          </dates>
          <resourceType resourceTypeGeneral="Other">Online resource</resourceType>
          <publicationYear>2026</publicationYear>
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            <description descriptionType="Abstract"><![CDATA[<p dir="ltr">To assess machine-actionability of dataset pages, we create three autorater prompts guided by the FAIR data principles (Findable, Accessible, Interoperable, and Reusable). Because our focus is on autonomous workflows, these metrics are specifically designed to quantify an agent's ability to successfully discover relevant web pages, ensure they are programmatically accessible, and verify their computational utility for downstream workflows.</p><ul><li><b>Relevance (Findable):</b> Evaluates semantic alignment between the NTCIR-16 query and dataset scope, assigning a score from -1 to 2 (summarized in Table [tab:relevance_rubric]). We deliberately score "Exploratory Matches" as Highly Relevant. In authentic data discovery, users frequently issue broad queries that lack explicit geographic, temporal, or demographic constraints. Returning a highly specific dataset in response to a broad, underspecified query proves the agent successfully navigated the correct semantic domain without violating any explicit user constraints.</li><li><b>Data Accessibility (Accessible):</b> Measures data accessibility via a 7-level rubric (summarized in Table [tab:accessibility_rubric]) to determine if agents can retrieve data with minimal technical barriers. This metric measures the complexity of data extraction.</li><li><b>Dataset Type (Interoperable & Reusable):</b> Measures computational utility by categorizing parsed web content into an 8-category rubric (summarized in Table [tab:dataset_type_rubric]).</li></ul><p></p>]]></description>
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