Parameter estimates of linear mixed effects models for juvenile <i>M</i>. <i>mercenaria</i>, juvenile <i>M</i>. <i>arenaria</i> and juvenile <i>A</i>. <i>islandica</i> proportional... by Teagan McMahon (20108036)

Detailed information of the observation datasets. by Weidong Ji (129916)

“…Understanding spatial-temporal characteristics of wind speed is significant in meteorology, coastal engineering design and maritime industries. …”

General technical specification for GW154/6700. by Weidong Ji (129916)

“…Understanding spatial-temporal characteristics of wind speed is significant in meteorology, coastal engineering design and maritime industries. …”

Sociodemographic and employment baseline characteristics. by Beatriz Arregui-Gallego (21553735)

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Evolution of mean values of posttraumatic stress symptomatology according to sociodemographic and occupational variables from baseline to 12-month. by Beatriz Arregui-Gallego (21553735)

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Baseline comparison of posttraumatic stress symptomatology according to sociodemographic and occupational variables. by Beatriz Arregui-Gallego (21553735)

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Psychological and coping factors baseline characteristics. by Beatriz Arregui-Gallego (21553735)

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Geometric manifold comparison visualization by Eloy Geenjaar (21533195)

“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”

Hyperparameter ranges by Eloy Geenjaar (21533195)

“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”

Convolutional vs RNN context encoder by Eloy Geenjaar (21533195)

“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”

Ether Cleavage Decreases the Ion Exchange Capacity of Anion Exchange Membranes by Shakkira Erimban (6882539)

Ether Cleavage Decreases the Ion Exchange Capacity of Anion Exchange Membranes by Shakkira Erimban (6882539)

High Stability, Piezoelectric Response, and Promising Photocatalytic Activity on the New Pentagonal CGeP₄ Monolayer by José A. S. Laranjeira (18870824)

“…Under compressive strain, the band gap decreases almost linearly to 2.65 eV at −8% strain and then drops sharply to 0.97 eV, an ∼69% variation. …”

High Stability, Piezoelectric Response, and Promising Photocatalytic Activity on the New Pentagonal CGeP₄ Monolayer by José A. S. Laranjeira (18870824)

“…Under compressive strain, the band gap decreases almost linearly to 2.65 eV at −8% strain and then drops sharply to 0.97 eV, an ∼69% variation. …”

ROBINS-I assessments. by Martha R. Smith (20410184)

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Exercise protocols and results of included studies. by Martha R. Smith (20410184)

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Participant characteristics in studies of children with biopsy-proven NAFLD. by Martha R. Smith (20410184)

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RoB 2 assessments. by Martha R. Smith (20410184)

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Data of soil response to nitrogen deposition.xlsx by Runcheng Zhu (20305665)

“…To fill this gap, we conducted an investigation into the effect of different N deposition levels on N-poor soil in tropical regions, aiming to ascertain the response of soil acidification to both increased and decreased N deposition.…”

Effect of Molecular Structure on the B3LYP-Computed HOMO–LUMO Gap: A Structure −Property Relationship Using Atomic Signatures by Ahmed Mohamed (628889)

“…The use of atomic Signatures as molecular descriptors successfully inferred correlations between different structural motifs and <i>E</i>_gap. The atomic fragments containing π-bonds in various aromatic compounds were found to be the most significant atomic Signatures, explaining nearly 50% of the variance in the data, with regression coefficients that decreased <i>E</i>_gap. …”