Comparisons of MPO levels between pre- and post-challenge with LT-ETEC and (LT + ST)-ETEC (log 10 scale). by Xueyan Zhang (277449)

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Prevalence ratios for challenging behavior and related factors using Poisson regression analysis. by Airi Endo (22439141)

Significance of proposed methodology using k-fold validation. by Raafat M. Munshi (17768876)

Top 10 significantly identified features in tiers 1, and 2. by Keenan Elliott (17181211)

The graph shows how different activities are plotted into the four categories of the flow model, based on the first-year students’ assessments of challenge and competence. by Klas Karlgren (6623204)

The graph shows how the different activities are plotted into the four categories of the flow model, based on the final-year students’ assessments of challenge and competence. by Klas Karlgren (6623204)

Dose- and time-dependent effect of IL-13, IL-4, and TGF-β1 on benzamil-sensitive <i>I</i>_sc and TEER in HBECs. by Anusree Sasidharan (19226521)

PWD alleles on Chr16 provide complete protection from lethal IAV challenge. by Bristy Sabikunnahar (11545324)

The rank by challenge and target for Inferno and Dante as measured by single-bin and multi-bin skill. by Dave Osthus (3216351)

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Mean accuracy and variance comparison with statistical significance. by Yaxun Jia (12000572)

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Dataset for an LLM score extraction challenge by Mike Thelwall (452631)

“…</p><p dir="ltr">2*: Quality that is recognised internationally in terms of originality, significance and rigour</p><p dir="ltr">1*: Quality that is recognised nationally in terms of originality, significance and rigour.…”

Reinforcement Learning for Autonomous Process Control in Industry 4.0: Advantages and Challenges by Nuria Nievas (19331156)

“…The analysis focuses on application types, problem modeling, training algorithms, validation methods, and deployment statuses. …”

Fingerprint biometric model. by Sahar A. El_Rahman (17972781)

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Machine learning models. by Turki Aljrees (16715369)

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The primary framework of the challenges to public sector agriculture project supply chain. by Md. Raquibuzzaman Khan (12908483)

Subjects: “…interpretive structural modelling…”

Fit of the similarity models. by Giulio Contemori (7019876)

Significance of our UST dataset in terms of T-Pair test. by Shumaila Khan (11682019)

RNAseq analysis of SARS-CoV-2 genes in challenged mouse lungs. by Katherine S. Lee (13248894)

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Leveraging Machine Learning for Thermoelectric Material Design: Addressing Composition–Property Relations and Data Imbalance Challenges by Deepa Sreedev (18776776)

“…To improve model interpretability, SHAP (SHapley Additive exPlanations) analysis was conducted, which revealed that temperature is the most significant factor for predicting the figure of merit. …”

Supplementary Material for: Therapeutic Challenge of Minicircle Vector Encoding Klotho in Animal Model by Shin Y.J. (6582950)