bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Figure S5 from Bladder Preservation with Durvalumab plus Tremelimumab and Concurrent Radiotherapy in Patients with Localized Muscle-Invasive Bladder Cancer (IMMUNOPRESERVE): A Phase II Spanish Oncology GenitoUrinary Group Trial
Authors: Garcia-del-Muro Xavier , P. Valderrama Begoña , Medina-Colmenero Ana , Etxaniz Olatz , Gironés Sarrió Regina , Juan-Fita María José , Costa-García Marcel , Moreno Rafael , Miras Rodríguez Isabel , Ortiz Irene , Cuéllar Andrés , Ferrer Ferran , Vigués Francesc , de Haro Piedra Roberto , Candal Gomez Arturo , Villà Salvador , Pontones José Luis , Murria Yasmina , Lendínez-Cano Guillermo , Alemany Ramon
Published: February 2025

Supplementary Figure 5. Measurement of soluble inflammatory mediators in peripheral blood by multiplex assay. Heatmap showing changes in the expression of each biomarker in the standard of care (SOC) cohort. Values have been normalized against basal levels and between analytes.
Supplementary Table S2 from Next-Generation Sequencing–Based MSI Scoring Predicts Benefit in Mismatch Repair–Deficient Tumors Treated with Nivolumab: Follow-up on NCI-MATCH Arm Z1D
Authors: Schoenfeld Jonathan D. , Azad Nilofer S. , Gross Jacob , Chen Li , Overman Michael J. , Kao Katrina , Jackson Latifa , Brunnquell Donna , Bu Xiangning , Coppola Christina , Guan Ping , Lee Jennifer , Sims David , Fuchs Rebecca , Weirather Jason L. , Pfaff Kathleen L. , Gunasti Lauren , Ranasinghe Srin , Hamilton Stanley R. , Wang Victoria , O’Dwyer Peter J. , Wu Catherine J. , Rodig Scott J. , Patton David R. , Harris Lyndsay
Published: February 2025

Representativeness of study participants
Supplementary Figure S5 from Next-Generation Sequencing–Based MSI Scoring Predicts Benefit in Mismatch Repair–Deficient Tumors Treated with Nivolumab: Follow-up on NCI-MATCH Arm Z1D
Authors: Schoenfeld Jonathan D. , Azad Nilofer S. , Gross Jacob , Chen Li , Overman Michael J. , Kao Katrina , Jackson Latifa , Brunnquell Donna , Bu Xiangning , Coppola Christina , Guan Ping , Lee Jennifer , Sims David , Fuchs Rebecca , Weirather Jason L. , Pfaff Kathleen L. , Gunasti Lauren , Ranasinghe Srin , Hamilton Stanley R. , Wang Victoria , O’Dwyer Peter J. , Wu Catherine J. , Rodig Scott J. , Patton David R. , Harris Lyndsay
Published: February 2025

Mutational comparisons with clinical benefit
Supplementary Figure S5 from Smoking-Associated Carcinogen–Induced Inflammation Promotes Lung Carcinogenesis via IRAK4 Activation
Authors: Aggarwal Ritesh K. , Sidoli Simone , Wang Jingli , Sahu Srabani , Sanawar Rahul , Gupta Varun , Aluri Srinivas , Sukrithan Vineeth , Vegivinti Charan T.R. , Zavras Phaedon D. , Verma Divij , Gordon-Mitchell Shanisha , Agarwal Beamon , Verma Tanya , Starczynowski Daniel T. , Steidl Ulrich G. , Shastri Aditi , Halmos Balazs , LaFave Lindsay M. , Cheng Haiying , Verma Amit , Zou Yiyu
Published: February 2025

Supplementary Figure S5. Annotated MS/MS spectrum of the phosphopeptide of MYH9 modified with serine 1943 phosphorylation. Red and blue lines indicate matches between observed and expected fragment masses (red is the b series, while blue is the y series). Fragments annotated as “-Phos” indicate that the phosphorylation fragmented out of the peptide leaving a diagnostic mass of -96 Da.
Supplemental Table 1 from Phase I/II Trial of Exportin 1 Inhibitor Selinexor plus Docetaxel in Previously Treated, Advanced KRAS-Mutant Non–Small Cell Lung Cancer
Authors: von Itzstein Mitchell S. , Burns Timothy F. , Dowell Jonathan E. , Horn Leora , Camidge D. Ross , York Sally J. , Eaton Keith D. , Kyle Kelly , Fattah Farjana , Liu Jialiang , Mu-Mosley Hong , Gupta Arjun , Nadeem Urooba , Gao Ang , Zhang Song , Gerber David E.
Published: February 2025

Supplemental Table 1. Representativeness of study participants.
Table S8 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

Supplementary Table 8. Survival information about 47 medullary carcinoma patients with ICIs
Table S6 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

Supplementary Table 6. Sample IDs and their corresponding relationships
Table S4 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

Supplementary Table 4. Rawdata based on nCounter IO360 panel
Table S3 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

Supplementary Table 3. Total of 96 samples for multiplexed immunofluorescence
Table S13 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

Supplementary Table 13. GSEA results between MeC and nMeC using hallmark gene sets from the MSigDB database
Figure S5 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

sFigure5. Immune features of different pathological types in The Cancer Genome Atlas.
Figure S3 from Multiomics Reveals the Immunologic Features and the Immune Checkpoint Blockade Potential of Colorectal Medullary Carcinoma
Authors: Liu Chao , Zou Haoyi , Ruan Yuli , Fang Lin , Wang Bojun , Cui Luying , Wu Tong , Chen Zhuo , Dang Tianjiao , Lan Ya , Zhao Wenyuan , Zhang Chunhui , Meng Hongxue , Zhang Yanqiao
Published: February 2025

sFigure3. Screening transcriptional level difference between colorectal medullary carcinoma and non-colorectal medullary carcinoma.
Data from Complete Remissions of HER2-Positive Trastuzumab-Resistant Xenografts Using a Potent [225Ac]Ac-Labeled Anti-HER2 Antibody–Drug Radioconjugate
Authors: Pougoue Ketchemen Jessica , Njotu Fabrice Ngoh , Babeker Hanan , Monzer Alissar , Nwangele Emmanuel , Tikum Anjong Florence , Henning Nikita , Hassani Nava , Frye Sarah , Perron Randy , Byrne Chris , Didychuk Candice , Qi Qi , Bannister Laura , Doroudi Alireza , Fonge Humphrey
Published: February 2025

AbstractPurpose:
There is overwhelming interest to use actinium-225 ([225Ac]Ac) to develop targeted α therapies. Antibody–drug conjugates (ADC) are highly cytotoxic. Combining [225Ac]Ac with an ADC to develop an antibody–drug radioconjugate [225Ac]Ac–macropa–trastuzumab(T)–PEG6–emtansine (DM1), is expected to be more effective than its ADC (T–PEG6–DM1) against breast cancer.
Experimental Design:
[89Zr]Zr–p-isothiocyanatobenzyl desferrioxamine (DFO)–T–PEG6–DM1 (imaging) and [225Ac]Ac–macropa–T–PEG6–DM1 (radiotherapy) were developed. Biodistribution and safety evaluations of [225Ac]Ac–macropa–T-PEG6–DM1 were carried out in non–tumor-bearing BALB/c mice. MicroPET imaging and biodistribution were done using [89Zr]Zr-DFO–T–PEG6–DM1, and radiotherapy using [225Ac]Ac–macropa–T–PEG6–DM1 was carried out in athymic BALB/c nude mice bearing trastuzumab-resistant HCC1954 and trastuzumab-DM1 (T-DM1)/trastuzumab-resistant JIMT-1 tumor-bearing mice.
Results:
After 7 days of incubation at 37°C, [225Ac]Ac–macropa–T–PEG6–DM1 was stable in both human serum (89.2% ± 0.9%) and PBS (82.8% ± 0.4%). T–PEG6–DM1 (8 mg/kg) and [225Ac]Ac–macropa–T–PEG6–DM1 (3 × 18 kBq) administered separately in non–tumor-bearing mice 10 days apart were well tolerated biochemically and hematologically. Imaging and biodistribution showed high tumor uptake of [89Zr]Zr-DFO–T–PEG6–DM1 in tumor-bearing mice at 120 hours after injection: 38.1% ± 2.8% IA/g (HCC1954) and 14.6% ± 1% IA/g (JIMT-1). In HCC1954 tumor-bearing mice, all treatment groups had complete remission (8/8), indicative of the responsiveness of the xenograft to T-DM1–based treatments, whereas for JIMT-1 xenografts (having 1/8 complete remission) at 23 days after treatment, tumor volumes were 332.1 ± 77.5 vs. 244.6 ± 63 vs. 417.9 ± 62.1 vs. 102.4 ± 18.5 for the saline (negative control), T-DM1 (positive control), T–PEG6–DM1, and [225Ac]Ac–macropa–T–PEG6–DM1, respectively.
Conclusions:
[225Ac]Ac–macropa–T–PEG6–DM1 is more potent than ADC against trastuzumab-resistant breast cancer and necessitates clinical translation.
Determinants of Response to Sequential Pembrolizumab with Trastuzumab Plus Platinum/5FU in HER2-positive Gastric Cancer: A Phase II Chemoimmunotherapy Trial
Authors: Lim Sung Hee , An Minae , Lee Hyuk , Heo You Jeong , Min Byung-Hoon , Mehta Arnav , Wright Samuel , Kim Kyoung-Mee , Kim Seung Tae , Klempner Samuel J. , Lee Jeeyun
Published: February 2025

Purpose: Adding pembrolizumab to first-line 5FU/platinum chemotherapy plus trastuzumab improves outcomes in advanced HER2+ gastroesophageal adenocarcinomas, but the benefit is largely confined to dual HER2+ and PD-L1+ patients. To assess the contributions of components, we conducted a phase II trial evaluating 5FU/platinum/trastuzumab and added pembrolizumab in cycle 2 in patients with metastatic HER2+ disease. Patients and Methods: Treatment naive advanced HER2+ gastroesophageal cancer patients underwent a baseline biopsy, and received a single dose of 5FU/platinum with trastuzumab followed by repeat biopsy. Pembrolizumab was added, and a third biopsy was performed after 6 cycles. The primary endpoint was the objective response rate (ORR). Secondary endpoints included progression free (PFS), and overall survival. Exploratory biomarker analysis and dynamic changes in HER2 and PD-L1 were prespecified. Results: Sixteen patients were enrolled. The ORR was 69%, and the median PFS was 11.9 months. Serial whole-exome, single-cell RNA, T-cell receptor sequencing and spatial transcriptomics from pre-treatment and on-treatment samples revealed early trastuzumab-induced natural killer cell infiltration in HER2+ tumor beds and an increase in Fc receptor (FcR) gamma III expression in macrophages, suggesting that trastuzumab directs FcR-mediated antibody-dependent cytotoxicity. This favorable remodeling was enhanced by the addition of pembrolizumab, primarily in PD-L1+ samples. We observed TGF-β signaling in HER2-negative tumor regions, which was associated with non-responder status. Conclusions: These data highlight the biology of intratumoral heterogeneity, and the impact of tumor and immune cell features on clinical outcomes and may partly explain the lesser magnitude of pembrolizumab benefit in HER2+ and PD-L1 negative subgroups.
Supplemental Figure 5 from Dynamic Tracking of Tumor Microenvironment Modulation Using Kaede Photoconvertible Transgenic Mice Unveils New Biological Properties of Viral Immunotherapy
Authors: Diers Anne R. , Guo Qiuchen , Li Zhi , Richardson Erin , Idris Suaad , Willis Claire , Tak Paul P. , Withers David R. , Barone Francesca
Published: February 2025

Supplemental Figure 5 shows the flow cytometry gating scheme applied to tumor-draining lymph node samples
Figure 6 from Dynamic Tracking of Tumor Microenvironment Modulation Using Kaede Photoconvertible Transgenic Mice Unveils New Biological Properties of Viral Immunotherapy
Authors: Diers Anne R. , Guo Qiuchen , Li Zhi , Richardson Erin , Idris Suaad , Willis Claire , Tak Paul P. , Withers David R. , Barone Francesca
Published: February 2025

Tumor-recruited, tumor-retained, and tumor-experienced Tregs, which egress tumors, adopt an altered phenotype after CAN-2409 + prodrug treatment. The effect of CAN-2409 + prodrug treatment on proliferative status of Treg cells was assessed using Ki67 as a marker coupled with the PD-1 expression. A, Representative flow cytometry plots for total, KG+, and KR+ Treg cells. Quantification of tumor experiencing Treg (KR+) for proliferation status (Ki67), B, and immune suppressive functional markers (PD-1, C, N = 4–6. Two-tailed t test, *, P < 0.05; ***, P < 0.001.
Electrodiagnostic Tests as Potential Efficacy Endpoints in Clinical Trials of Novel Pharmacological Therapies for Acquired Retinal Disorders
Authors: Neveu Magella M. , Chong Victor , Empeslidis Theo , Scholl Hendrik P.N. , Robson Anthony G.
Published: February 2025

Background
Electrodiagnostic tests (EDTs) provide non-invasive, objective and measurable indications of retinal and visual pathway function. These hold the promise of evaluating drug efficacy and disease progression over shorter periods than traditional ‘end-stage’ outcome measures (e.g., best-corrected visual acuity) in various ophthalmological pathologies. The International Society for Clinical Electrophysiology of Vision has defined rigorous standards for EDTs, intended to optimise diagnostic power, enabling meaningful inter-laboratory comparisons and facilitating application as outcome measures in increasing numbers of multicentre clinical trials.
Summary
This review outlines the main EDTs, including full-field, pattern and multifocal electroretinography, the electro-oculogram and the cortical visual evoked potential, and highlights the possible role for monitoring disease progression and assessing treatment safety and efficacy. The utility and potential of EDTs are highlighted in studies that have assessed function and tested or monitored treatment safety or efficacy for a range of acquired retinal and optic nerve disorders, including central retinal vein occlusion, diabetic retinopathy, glaucoma, age-related macular degeneration, posterior uveitis and autoimmune-related retinopathies.
Key messages
EDTs are fundamental to the diagnosis and phenotyping of many acquired retinal and visual pathway disorders. They also provide methods for the objective assessment of the efficacy and safety of potential novel treatments across short periods. Conventional psychophysical tests, such as visual acuity, are of limited value in localizing and characterizing dysfunction, and are not always suitable for monitoring purposes. This review highlights where EDTs may address the need for better outcome measures to evaluate novel treatments within clinical trials, helping to select early treatment candidates and for the assessment of safety and efficacy.
Optimizing potato crop productivity: a meteorological analysis and machine learning approach
Authors: Hoque Md. Jiabul , Islam Md. Saiful , Al Noman Abdullah , Hoque Md. Abrarul , Chowdhury Irfan A. , Saifuddin Mohammad
Published: February 2025

Motivated by the critical need to enhance potato production in Bangladesh, particularly in the face of a changing climate, this study investigates the significant impact of weather on potato yield. This research employs various statistical and machine-learning approaches to identify key weather factors influencing potato crops. We utilize ANOVA F regression and random forest (RF) with feature importance analysis to pinpoint crucial monthly weather variables. Additionally, a correlation study employing Pearson's and Spearman's coefficients alongside p-values is conducted to determine the relationships between weather conditions and crop yield. Seaborn's bivariate kernel density estimation is then used to visualize ideal weather conditions for optimal harvests. Furthermore, to predict future yields, the study implements thoroughly trained and validated machine learning models including k-nearest neighbors (KNN), RF, and support vector regressor (SVR). Our analysis reveals that the RF model emerges as the most reliable predictor, achieving a high correlation coefficient (R²=0.9990), and minimal error values (mean absolute percentage error (MAPE)=0.70, mean absolute error (MAE)=0.0803, and root mean square error (RMSE)=0.1114). These findings provide valuable insights to guide informed agricultural decisions and climate-related strategies, particularly for resource-limited countries like Bangladesh.
Diabetes mellitus diagnosis method based random forest with bat algorithm
Authors: Anam Syaiful , Deny Tisna Amijaya Fidia , Hadi Wijoyo Satrio , Eka Ratnawati Dian , Ayu Dwi Lestari Cynthia , Ilyas Muhaimin
Published: February 2025

Diabetes mellitus (DM) is a very dangerous disease and can cause various problems. Early diagnosis of DM is essential to avoid severe effects and complications. An affordable DM diagnosis method can be developed by applying machine learning. Random forest (RF) is a machine learning technique that is applied to develop a DM diagnosis method. However, the optimization of RF hyperparameters determines the performance of RF approach. Swarm intelligence (SI) could be used to solve the hyperparameter optimization problem on RF. It is robust and simple to be applied and doesn’t require derivatives. Bat algorithm (BA) is one of SI techniques that gives a balance between exploration and exploitation to find a global optimal solution. This article proposes developing an RF-BA-based technique for diagnosing DM. The results of the experiment demonstrate that RF-BA can diagnose DM more accurately than conventional RF. RF-BA has higher performance compared to RF-particle swarm optimization (PSO) in terms of computational time. The RF-BA also are able to solve the overfitting problem in the conventional RF. In the future, the proposed method has a high chance of being implemented for helping people with early DM diagnosis with high accuracy, low cost, and high-speed process.
Enhancing sepsis detection using feed-forward neural networks with hyperparameter tuning techniques
Authors: N. Smitha , R. Tanuja , S. H. Manjula
Published: February 2025

This paper investigates the use of feed-forward neural networks for sepsis detection, emphasizing class imbalance mitigation and hyperparameter optimization. Leveraging random oversampling, synthetic minority over-sampling technique (SMOTE), and random sampling techniques, we address class imbalance, significantly improving feed-forward neural network performance. The resulting model achieves an impressive 83% accuracy on the test set, with notable enhancements in precision, recall, and F1-score for the positive class. Hyperparameter tuning using RandomizedSearchCV identifies optimal parameters, including an alpha value of 0.01 and the logistic activation function, leading to a remarkable 57.5% test accuracy. GridSearchCV also contributes to model refinement, albeit with a slightly lower test accuracy of 51.5%. These findings underscore the importance of robust hyperparameter tuning methods in optimizing feed-forward neural network models for imbalanced datasets, particularly in sepsis detection. The insights gained hold promise for the development of more accurate diagnostic tools, ultimately improving patient outcomes in clinical practice.
Enhanced intrusion detection through dual reduction and robust mean
Authors: Taha Archi , Benattou Mohammed
Published: February 2025

The exponential growth of online networks necessitates a paradigm shift in intrusion detection systems (IDS). Traditionalmethods falter under the massive influx of data, resulting in high false positives and reduced detection accuracy. This research introduces a novel approach combining principal component analysis (PCA) and linear discriminant analysis (LDA), augmented by robust generalized sample mean, to enhance IDS performance. PCA efficiently reduces data dimensionality, while LDA extracts critical features that differentiate normal network traffic from anomalies. The robust generalized sample mean counteracts the influence of outliers, ensuring accurate and reliable analysis. Implemented on the UNSW-NB15 dataset, our method achieves an average 6% reduction in false positives and a 10% increase in detection rate. Additionally, our testing methodology closely mirrors real-world conditions, making the results more representative of practical scenarios compared to existing work. These advancements demonstrate substantial improvements in IDS performance and robustness over existing techniques.
Improved convolutional neural networks for aircraft type classification in remote sensing images
Authors: Alraba'nah Yousef , Hiari Mohammad
Published: February 2025

With the exponential growth of available data and computational power, deep convolutional neural networks (CNNs) have become as powerful tools for a wide range of applications, ranging from image classification to natural language processing. However, during last decade, remote sensing imagery has emerged as one of the most prominent areas in image processing. Variations in image resolution, size, aircraft types and complex backgrounds in remote sensing images challenge the aircraft classification task. This study proposes an effective aircraft classification model based on CNN architecture. The CNN network architecture is improved to achieve more accuracy rate and to avoid overfitting and underfitting problems. To validate the proposed model, a new public aircraft dataset called multi-type aircraft remote sensing images 2 (MTARSI2) has been used. Through an analysis of existing methodologies and experimental validation, the model shows the superior performance of the proposed CNN model in comparison to state-of-the-art deep learning approaches.
A comparative study of natural language inference in Swahili using monolingual and multilingual models
Authors: Faki Ali Hajra , Alfa Krisnadhi Adila
Published: February 2025

Recent advancements in large language models (LLMs) have led to opportunities for improving applications across various domains. However, existing LLMs fine-tuned for Swahili or other African languages often rely on pre-trained multilingual models, resulting in a relatively small portion of training data dedicated to Swahili. In this study, we compare the performance of monolingual and multilingual models in Swahili natural language inference tasks using the cross-lingual natural language inference (XNLI) dataset. Our research demonstrates the superior effectiveness of dedicated Swahili monolingual models, achieving an accuracy rate of 69%. These monolingual models exhibit significantly enhanced precision, recall, and F1 scores, particularly in predicting contradiction and neutrality. Overall, the findings in this article emphasize the critical importance of using monolingual models in low-resource language processing contexts, providing valuable insights for developing more efficient and tailored natural language processing systems that benefit languages facing similar resource constraints.
Artificial intelligence algorithms to predict customer satisfaction: a comparative study
Authors: Berrada Chakour Othman , Ettaoufik Abdelaziz , Aissaoui Khalid , Maizate Abderrahim
Published: February 2025

Customer satisfaction is the key for every business successful. Therefore, keeping the current customer portfolio and expanding it over time is the main goal for any business. Hence, we need first to satisfy these clients. The customer satisfaction helps to retain consumers of its products, increase the life value of the customer, also make known its brand through positive word of mouth to get a better reputation and thus increase turnover. For this reason, several studies have been conducted on this subject to explore all tools and technologies that will help retain customers and reduce their churn rate. Based on various customer satisfaction studies for different types of businesses, this paper shows the review of promising research areas and artificial intelligence (AI) application models in predicting customer satisfaction. The results of this study allowed the identification of the best algorithms with the highest score of performance metrics that can be applied as part of the customer satisfaction prediction, through a detailed benchmark performed. The result shows that random forest (RF) and gradient boost (GB) algorithms in machine learning (ML) and convolutional neural network - long short-term memory (CNN-LSTM) in deep learning (DL) are giving the best performance. The most used metrics are accuracy and
F1-score. In addition, DL models outperform ML models in most cases.
Literature review on forecasting green hydrogen production using machine learning and deep learning
Authors: Rhafes Mohamed Yassine , Moussaoui Omar , Raboaca Maria Simona
Published: February 2025

Green hydrogen is a sustainable and clean energy source, for this purpose, it conducts the global energy transition. The integration of artificial intelligence (AI), especially machine learning (ML) and deep learning (DL) with the process of green hydrogen production is essential in enhancing its production. This literature review studies in detail the intersection between AI and green hydrogen. Firstly, it concentrates on ML and DL algorithms used in forecasting green hydrogen production. Secondly, it presents an analysis of the studies released from 2021 to March 2024. Finally, the focus is on the results realized by the ML and DL algorithms proposed by the studies reviewed. This study provides a summary that explains the trends and methods used, as well as highlights the gaps and the opportunities in the field of AI and green hydrogen production. This liternature review presents a solid foundation for future research initiatives in this field.
Quality and shelf-life prediction of cauliflower using machine learning under vacuum and modified atmosphere packaging
Authors: Hosen Md. Apu , Md. Galib Dr. Syed
Published: February 2025

Ensuring the freshness and quality of cauliflower during storage and transportation is essential due to its high perishability. This study harnesses the power of machine learning to predict the quality and shelf-life of cauliflower under cost-effective vacuum and modified atmosphere packaging (MAP) techniques. By investigating key parameters such as total soluble solids (TSS), pH, weight loss, and color change, a significant impact on post-packaging quality was identified. To address the challenge of accurate color change measurement, an innovative method utilizing a bilateral filter for noise reduction and particle swarm optimization (PSO) with Markov random field (MRF) segmentation was developed. TSS, weight loss, and color change were identified as key parameters, and leveraging these parameters, artificial neural networks (ANN) were employed to create highly precise predictive models, achieving R-squared values of 0.952 for TSS, 0.992 for weight loss, and 0.981 for color change. This approach not only enhances the efficiency and sustainability of food production and distribution but also minimizes food waste and maximizes profitability for cauliflower in global markets through the use of cost-effective packaging solutions.
Predicting students’ intentions for post-COVID-19 face-to-face classes
Authors: Quah Wei Boon , Gopal Krishnavehni
Published: February 2025

The COVID-19 pandemic led to community college closures, with reopening being considered as a potential strategy to enhance learning outcomes. However, existing literature lacks insights into the factors that determine students’ intention to attend limited face-to-face classes. To address this gap, a study was conducted to explore the intentions of 122 English students at a Malaysian community college regarding attendance in such classes post-reopening, using the theory of planned behavior as a framework. Results indicated a moderate level of intention to attend. Perceived behavioral control (PBC) and subjective norm positively predicted students’ intentions, while attitude did not significantly contribute. These findings highlight the critical role of PBC and subjective norms in shaping students’ intentions. As many community colleges prepare for phased reopening, understanding students’ diverse perspectives is crucial for informed decision-making regarding in-person instruction. Institutions must consider these factors to gain nuanced insights into students’ inclinations towards face-to-face classes, thereby facilitating effective planning amidst ongoing uncertainties.
Challenges and solutions in organizing geological field trips for Moroccan secondary school life and earth sciences teachers
Authors: Eddif Aâtika , Selmaoui Sabah , Chalak Hanaa , Chakour Radouan
Published: February 2025

Teaching and learning earth sciences (ES), notably geology, are conducted across various environments, encompassing the classroom, laboratory, and, most significantly, the field. The field trip is recognized as a key component of practical training and the overall success of the educational process in ES. This paper elucidates the findings of a survey aimed at understanding the challenges faced by Moroccan secondary school teachers of life and earth sciences (LES) in organizing geological field trips. The survey sought to identify the difficulties these teachers encounter and propose potential support mechanisms to mitigate these challenges. The study revealed that teachers often do not arrange geological field trips due to challenges related to administration, personal factors, pedagogy, and didactics. In an effort to address this situation, the study underscores the importance of integrating practical work into teacher training and student education. It also emphasizes the need for the provision of more adequate teaching materials and logistical support to facilitate geological excursions, thereby enriching the appreciation of earth sciences disciplines among both teachers and students. Finally, the establishment of electronic collaboration between local Moroccan universities and secondary schools is recommended as a crucial step towards further improvement.
Learning competencies in the electrical installations laboratory for engineering students
Authors: Murillo Manrique Margarita F. , Sánchez Ayte Jorge A. , Meléndez Murillo Antonio A.
Published: February 2025

The research addresses the lack of practical competencies in the electrical installations-I (IE-1) course at the School of Mechanical and Electrical Engineering (EPIME) at the National Technological University of Lima Sur, where the current content is mostly theoretical. To solve this problem, the course was moved to the Electrical Installations Laboratory (LABIE) and the conceive, design, implement, and operate (CDIO) methodology was applied, combining theory with practice to develop competencies in knowledge, skills, and attitudes. The laboratory guides were aligned with the new IE-1 syllabus, including single-phase and three-phase systems of 220 V at 60 Hz, which were not previously covered. Two groups of 15 students were compared: an experimental group (EG) and a control group (CG). Both took a pre-test with similar results. The CG followed traditional classes, while the EG worked in the LABIE with CDIO. At the end, a post-test showed significant improvements in the EG, validating the effectiveness of CDIO in enhancing practical training in IE-1. It is concluded that this methodology should be implemented in the new EPIME curriculum.
International atmosphere impact on faculty engagement in internationalization: international attitudes mediation
Authors: Yan Liu Hai , Ping Yang Su
Published: February 2025

Globalization continues to reshape higher education, driving increased international exchanges and collaboration. This study investigates the impact of the international atmosphere on faculty engagement in internationalization (FEI), with a focus on local applied universities in China. Despite the recognized importance of faculty in facilitating internationalization efforts, limited research exists on their involvement. Utilizing surveys and structural equation modeling, data was collected from faculty members in local applied universities in China. The survey instrument covered demographics, perceptions of the international environment, engagement in international activities, and attitudes towards internationalization results indicate significant positive correlations between the international atmosphere, faculty international attitudes (FIA), and engagement in international activities. Specifically, the international atmosphere positively influences FIA and subsequent engagement in internationalization. Furthermore, FIA were found to partially mediate the relationship between the international atmosphere and engagement. This study contributes to the understanding of faculty involvement in internationalization efforts, addressing a gap in the literature. By identifying the factors influencing faculty engagement, institutions can develop targeted strategies to promote global engagement in higher education, ultimately enhancing the internationalization process.
Exploring university students’ engagement and motivation: critical factors
Authors: Ghanem Reham , Abdelhameed Hoda , Abdulmonem Mona , Alfrehat Rawan , Altaisan Reem , Soliman Mona , Hameed Hager Abdel , Abduljawad Rania , Alrashed Yousef , Nasr Nahed
Published: February 2025

The study aimed to investigate the critical factors for success students' motivation and their engagement in their learning of Jordan's universities. The quantitative method was employed using a survey questionnaire as the research method to measure students' evaluation of factors. Simple sampling was used to obtain a group of university students. The questionnaire was distributed to 265 university students in Jordan. Data analysis was performed using several analyses such as descriptive analysis, Pearson correlation and regression analysis. The results of the study partially supported several factors influencing students' motivation. The results evidenced that assessment, teaching/learning strategy and students attitudes significantly influenced students learning motivation. The results of this have implications to literature, academicians and decision makers to review and discover the proper methods to invest the necessary tools that can enhance the quality of students learning in the higher education institutions.
Factors affecting pre-service teachers to adopt augmented reality in science learning
Authors: Rizki Iqbal Ainur , Suprapto Nadi , Awwalina Denissa Putri , Wanti Wilujeng Trismaya , Sabrina Nadya Mazayu Nur
Published: February 2025

The advancement of augmented reality (AR) technology and its application in education presents an opportunity for pre-service teachers to incorporate it into the learning process, particularly in science subjects with abstract and microscopic materials. However, the adoption of AR technology among pre-service teachers remains suboptimal. Therefore, this study aims to analyze the factors influencing pre-service teachers’ adoption of AR in science learning. By employing partial least squares structural equation modeling, we gathered 211 responses through a questionnaire. The developed model has met the criteria of validity and reliability. The study’s findings reveal that perceived control and learning content significantly influence behavioral intention, while visual attraction and knowledge-ability do not. Clearly, their focus is on pedagogically implementing AR technology rather than visually developing it. Thus, it is recommended to provide training for pre-service teachers to apply AR science because many of them need an understanding of integrating this technology as a science learning media. This research implies offering insightful analysis and practical suggestions for the successful integration of AR technology into science learning, especially by addressing the variables affecting its uptake.
Improving ESP Vietnamese learners’ EFL speaking fluency and vocabulary with DMGA scaffolding: a modular approach
Authors: Nhi Nguyen Tran Uyen , AlSaqqaf Asmaa
Published: February 2025

Teaching English as a foreign language (EFL) speaking in an English for specific purposes (ESP) classroom can be challenging as many Vietnamese students find it difficult to master this language skill. To address this issue, scaffolding is believed to be beneficial in language learning programs. This paper aims to investigate the effectiveness of the Diagnosing, Modeling, Sharing, Guiding, and Applying (DMGA) scaffolding-based module on improving the speaking skills of ESP Vietnamese learners at a public university in Vietnam in terms of fluency and vocabulary use. The study employed a quantitative method with an experimental design. The participants were 25 ESP undergraduates. The English-speaking performance test (ESPT), which served as a pretest and posttest, revealed that most posttest indicators improved from pretest values, though significance and size effects varied. Students performed significantly better in both breakdown fluency and speech rate, but there was no progress in repair fluency. While there was no statistically significant improvement in all vocabulary metrics (type-token ratios (TTR), voice-to-text ratio (VOCD), English vocabulary profile (EVP)), the students did achieve higher mean scores on the measures of vocabulary used in the post-test. Based on the findings, the DMGA scaffolding model should be applied to teach speaking skills in ESP settings within an EFL context to benefit both teachers and learners.
Influence of social networks on the mental health of university students in Huancayo, Peru
Authors: Galarza Nilton David Vilchez , Espejo Luis Angel Huaynate , Echevarría Carmen Rocío Ricra
Published: February 2025

Since the appearance of signed social networks (SSNs), their use has increased steadily among young people, not only in terms of the number of users but also in terms of the time they devote to managing the platforms, a situation that may be influencing their behavior. This study aimed to analyze the influence of the use of social networks (SNs) on the mental health of young university students. For this purpose, a quantitative, basic, and correlational study was carried out. We worked with a sample of 361 undergraduate students in health careers at a university in Huancayo. The PERMA-Profiler scale for mental health and the brief social network addiction questionnaire were used as data collection instruments to evaluate the use of SNs. The results indicate that there is a statistically significant influence of the use of SNs on the mental health of students, which explains a variability of 53.5% to 79.9%, according to the values of the Nagelkerke Pseudo X2 calculation for SNs. This suggests that the use of SNs hurts students’ mental health.
Drama-based strategies for vocabulary development in young English learners in the western region of Saudi Arabia
Authors: Alelyani Abdulaziz Ali Fayz , Alharbi Mohammed Salim
Published: February 2025

This study investigates the efficacy of drama-based methodologies in English vocabulary acquisition among young learners in Saudi Arabia, addressing a significant gap in the Saudi English as a foreign language (EFL) context. Employing a descriptive, quantitative research design, the study surveyed 137 English language instructors from the Jeddah Educational Directorate. The findings reveal that diverse dramatic activities yield substantial benefits in English language learning, particularly in vocabulary acquisition. Key advantages include enhanced motivation for contextual vocabulary usage, improved learner engagement, increased self-confidence, and enhanced communication skills. The study highlights the superiority of varied and engaging drama-based techniques, such as role-playing, over traditional methods in fostering a dynamic and conducive learning atmosphere. While acknowledging challenges like increased teacher preparation time and students’ initial reluctance towards active participation, the research concludes that drama-based instruction represents an effective pedagogical approach for teaching English vocabulary to young learners. The study proposes significant implications for educational policy, recommending the integration of drama-based English textbooks into the curriculum and the incorporation of drama techniques in teacher training programs. This research contributes valuable insights to ongoing discourse on innovative EFL teaching methodologies in the Saudi Arabian context.
Flipped classroom approach of language education: a systematic review
Authors: Mazlan Rohaida , Mahamod Zamri , Jamaludin Khairul Azhar
Published: February 2025

The flipped classroom approach has emerged as an innovative pedagogical model in language education, transforming traditional teaching methods by reversing the conventional sequence of instruction and homework. The objectives of this systematic literature review are to examine the impact of various technological enhancements on the effectiveness and student engagement in flipped classrooms. Secondly, to explore the perceptions and attitudes of students and teachers towards flipped classroom methodologies across different educational contexts. Thirdly, to assess the effects of flipped classroom approaches on students’ academic performance and critical thinking skills across various disciplines. This study conducted an extensive search of scholarly articles from reputable databases such as Scopus and Web of Science, focusing on studies published from 2021 until 2024. The flow of the study is based on the PRISMA framework. The database search identified 35 final primary studies that were analyzed. The findings were divided into three themes: i) technological enhancements in flipped classrooms, which were found to significantly improve student engagement and learning outcomes; ii) student and teacher perceptions of flipped classrooms, which were generally positive, with many highlighting increased interaction and autonomy in learning; and iii) outcomes and effectiveness of flipped classroom approaches, showing a positive impact on students’ academic performance and critical thinking skills. In conclusion, the flipped classroom approach holds considerable promise for language education, offering a more effective and engaging alternative to traditional instruction. This review provides valuable insights for educators and policymakers seeking to adopt innovative teaching strategies in language education.
Exploring the relationship between strategic planning and educational performance: a systematic literature review
Authors: Endo Semail , Busari Abdul Halim , Ibrahim Dayang Kartini Abang
Published: February 2025

In the evolving landscape of education, strategic planning has emerged as a critical tool for enhancing institutional performance and achieving educational excellence. This systematic literature review aims to explore the intricate link between strategic planning and educational performance by synthesizing findings from a diverse array of studies. The review addresses the pressing need for a structured approach to improving educational outcomes. To achieve this, we conducted an extensive search of scholarly articles from reputable databases such as Scopus and Web of Science, focusing on studies published between 2020 and 2024. The flow of the study based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework. The database found (n=28) final primary data was analyzed. The finding was divided into three themes which are: i) competency development and assessment in education; ii) strategic planning and management in higher education; and iii) technological integration and innovation in education. The results highlight the significance of implementing a comprehensive and flexible framework for strategic planning that aligns with the specific requirements and environments of educational institutions. In conclusion, this research offers insightful information to educators, administrators and policymakers who want to use strategic planning to support long-term improvements in student performance and eventually advance the larger objective of educational excellence.
The methodology for assessing the impact of appraisal on teachers’ professional development
Authors: Shilibekova Aidana , Vildanova Saule , Mussarova Venera , Yessingeldinov Baurzhan , Ablayeva Moldir , Kaldybek Amina
Published: February 2025

In Kazakhstan, the teacher appraisal processes intended to support professional development frequently fall short of their objectives because of an excessive focus on test outcomes. This focus distorts the purpose of the appraisal, leading to a misalignment between the assessment outcomes and the actual improvement of educational practices. Addressing this critical issue, this study proposes a methodology based on Kane’s argument-based approach to validity, aimed at more accurately assessing the impact of appraisal on teachers’ professional development. By applying Toulmin’s model of argumentation, the validity and reliability of the existing appraisal procedures were assessed, allowing key factors influencing their effectiveness to be identified. The methods also included reviewing the appraisal documents (professional standards, appraisal rules, and teacher qualification requirements) for data triangulation. The findings reveal that the proposed methodology enhances the objectivity and fairness of teacher qualification evaluations and supports meaningful professional growth. By ensuring a more comprehensive and evidence-based assessment, this methodology can improve the transparency and effectiveness of the appraisal process, ultimately contributing to higher educational standards in Kazakhstan. The study also offers practical recommendations for implementing the methodology across different levels of the education system, emphasizing its adaptability and potential for broader application.
Digital media’s role in overcoming anxiety, enhancing linguistic elements and fostering motivation for developing speaking skills
Authors: Syamsudin Syamsudin , Budianto Langgeng , Prihadi Kususanto Ditto , Susanto Djoko , Rohman Abdul , Kholil Ahmad , Firdousi Muhammad Anwar
Published: February 2025

The qualitative study investigated the digital media impact on language learning, focusing on overcoming anxiety, enhancing linguistic elements, and fostering motivation for developing speaking skills among four English as foreign language (EFL) learners at an Islamic University in Malang, Indonesia. Through the use of observations and in-depth interviews, the study found that learners utilized various digital media such as storytelling, movies, variety shows, and song videos to aid their speaking learning process. The findings indicated that digital media played a significant role in helping learners overcome language anxiety by providing a platform for practice without direct peer interaction, thereby reducing feelings of fear and shyness. Additionally, digital media usage contributed to linguistic element enhancement, including vocabulary, pronunciation, grammar, and speaking fluency. Moreover, learners’ motivation for developing speaking skills was positively influenced by the enjoyment derived from using digital media which increased their willingness to practice speaking. The study underscores the importance of integrating digital media into EFL speaking instruction due to its potential to address language anxiety, improve linguistic elements, and foster motivation for speaking ability development. By leveraging digital media tools effectively, educators can create engaging and supportive learning milieus that provide to the diverse needs of language learners, eventually enhancing learners’ speaking skills.