Block diagram for IoT-based irrigation system. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”

Flow chart of Average Value-based control system. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”

Hardware design for IoT-based irrigation system. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”

Physics-Assisted Machine Learning for the Simulation of the Slurry Drying in the Manufacturing Process of Battery Electrodes: A Hybrid Time-Dependent VGG16-DEM Model by Diego E. Galvez-Aranda (9436672)

“…In this study, we present a hybrid Physics-Assisted Machine Learning (PAML) model that integrates Deep Learning (DL) techniques with the classical Discrete Element Method (DEM) to simulate slurry drying during a lithium-ion battery electrode manufacturing process. …”

Table 1_Student wellbeing during COVID-19—Impact of individual characteristics, learning behavior, teaching quality, school system-related aspects and home learning environment.pdf... by Julian Brauchle (20788490)

“…</p>Methods<p>In the present study, we used a cross-sectional survey design to examine the impact of individual student characteristics and learning behavior, teaching quality, school system-related aspects and home learning environment on the wellbeing of N = 1,212 secondary school students from Germany and Switzerland (grade level: 5–13; age: 10–20) during the pandemic. …”

Nonadjacent dependency learning in Swiss toddlers (Bodard et al., 2025) by Julie Bodard (21715023)

“…However, at 27 months, we observed a significant decrease in gaze duration for ungrammatical test trials between the first and the second blocks, together with a tendency to look longer at grammatical stimuli in the second block, a pattern of results that, if confirmed in future studies, might indicate the start of novel NAD learning.…”

Dataset study -Impact of Technical Standardization on Pneumothorax and Chest Tube Insertion Rates: A Retrospective Learning Curve Analysis of CT-Guided Lung Biopsies by Rosa Alba Pugliesi (20766383)

Table 2_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Despite their efficacy, inconsistencies in model quality remain a concern. This review aims to evaluate existing ML-based SA-AKI mortality prediction models, with a focus on development quality, methodological rigor, and predictive performance.…”

Table 4_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Despite their efficacy, inconsistencies in model quality remain a concern. This review aims to evaluate existing ML-based SA-AKI mortality prediction models, with a focus on development quality, methodological rigor, and predictive performance.…”

Table 3_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Despite their efficacy, inconsistencies in model quality remain a concern. This review aims to evaluate existing ML-based SA-AKI mortality prediction models, with a focus on development quality, methodological rigor, and predictive performance.…”

Table 1_Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.xlsx by Xu Li (23864)

“…Despite their efficacy, inconsistencies in model quality remain a concern. This review aims to evaluate existing ML-based SA-AKI mortality prediction models, with a focus on development quality, methodological rigor, and predictive performance.…”

The ROC curves and AUC values of the diagnostic model. by Zhe Wu (582498)

Limma differential analysis results for IS and OSA. by Zhe Wu (582498)

Co-expression network of IS and OSA. by Zhe Wu (582498)

GSVA pathway scores for IS and OSA. by Zhe Wu (582498)

LASSO regression for screening candidate diagnostic biomarkers. by Zhe Wu (582498)

ssGSEA is employed to analyze immune infiltration in IS and OSA. by Zhe Wu (582498)

Participants demographics at baseline. by Dawn M. Sears (4807302)

“…</p><p>Objective</p><p>To determine if a shared learning, social-based leadership development program will impact burnout and career trajectory for female physicians.…”

Data Sheet 1_Source attribution of human Campylobacter infection: a multi-country model in the European Union.docx by Cecilie Thystrup (19125203)

“…The aim of this study was to predict the sources of human campylobacteriosis cases across multiple countries using available whole-genome sequencing (WGS) data and explore the impact of data availability and sample size distribution in a multi-country source attribution model.</p>Methods<p>We constructed a machine-learning model using k-mer frequency patterns as input data to predict human campylobacteriosis cases per source. …”

Branching behavior of a N = 10 units network at trial T (case of weak inhibition = 0.55). by Elif Köksal-Ersöz (20378631)