Assessing Work–Life Balance in Malta and Italy: A Cross-Cultural Investigation Using Exploratory Structural Equation Modelling (ESEM) by Bottaro R, De Giovanni K, Faraci P

“…Results from this study also supported its psychometric features and the cross-cultural applicability of the WLBS in two different European countries. …”
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Enhanced Magnetic Resonance Imaging-Based Brain Tumor Classification with a Hybrid Swin Transformer and ResNet50V2 Model by Abeer Fayez Al Bataineh, Khalid M. O. Nahar, Hayel Khafajeh, Ghassan Samara, Raed Alazaidah, Ahmad Nasayreh, Ayah Bashkami, Hasan Gharaibeh, Waed Dawaghreh

“…Resnet 50V2 improves both accuracy and training speed by extracting adaptive features from the Swin Transformer’s dependencies. …”
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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

“…We applied five machine learning algorithms—Random Forest, XGBoost, LightGBM, Stacking, and Convolutional Neural Network Transformers (CNNT)—and evaluated their performance using six metrics: R, RMSE, CSI, MAR, FAR, and fbias, on both validation and testing sets. …”
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Explainable Machine Learning for Radio Environment Mapping: An Intelligent System for Electric Field Strength Monitoring by Yiannis Kiouvrekis, Theodor Panagiotakopoulos, Efthymia Nousi, Ioannis Filippopoulos, Agapi Ploussi, Ellas Spyratou, Efstathios P. Efstathopoulos

“…We evaluate multiple machine learning models—kNN, neural networks, decision trees, random forests, XGBoost, and LightGBM—using a two-semester split for training and assessment. …”
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Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study by Emma Holler, Christina Ludema, Zina Ben Miled, Molly Rosenberg, Corey Kalbaugh, Malaz Boustani, Sanjay Mohanty

“…We trained logistic regression, random forest, extreme gradient boosting (XGB), and neural network models to predict POD using 143 features derived from routine EHR data available at the time of hospital admission. …”
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A Study on Using Transfer Learning to Utilize Information From Similar Systems for Data-Driven Condition Diagnosis and Prognosis by Marcel Braig, Peter Zeiler

“…Two transfer learning approaches are analyzed: parameter transfer with fine-tuning and retraining, and feature alignment. Both concepts are implemented with the neural network types multilayer perceptron, 1D convolutional neural network, and temporal convolutional network. …”
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Semantic Segmentation of Brain Tumors Using a Local–Global Attention Model by Shuli Xing, Zhenwei Lai, Junxiong Zhu, Wenwu He, Guojun Mao

“…In our model, we introduce: (1) a semantic-oriented masked attention to enhance the feature extraction capability of the decoder; and (2) network-in-network blocks to increase channel modeling complexity in the encoder while reducing the parameter consumption associated with residual blocks. …”
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Machine Learning-Based Scoring System to Predict the Risk and Severity of Ataxic Speech Using Different Speech Tasks by Bipasha Kashyap, Pubudu N. Pathirana, Malcolm Horne, Laura Power, David J. Szmulewicz

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A Novel Multi-Task and Ensembled Optimized Parallel Convolutional Autoencoder and Transformer for Speech Emotion Recognition by Zahra Sharifzadeh Jafari, Sanaz Seyedin

“…In this paper, we present a novel model for speech emotion recognition (SER) based on new multi-task parallel convolutional autoencoder (PCAE) and transformer networks. The PCAEs have been proposed to generate high-level informative harmonic sparse features from the input. …”
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RI-ViT: A Multi-Scale Hybrid Method Based on Vision Transformer for Breast Cancer Detection in Histopathological Images by Ehsan Monjezi, Gholamreza Akbarizadeh, Karim Ansari-Asl

“…In this approach, local features are extracted through a combination of residual stages and multi-scale learning, while global features are obtained using the attention mechanism in transformers. …”
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Deep learning model for patient emotion recognition using EEG-tNIRS data by Mohan Raparthi, Nischay Reddy Mitta, Vinay Kumar Dunka, Sowmya Gudekota, Sandeep Pushyamitra Pattyam, Venkata Siva Prakash Nimmagadda

“…To enhance modality fusion, we propose and evaluate three fusion strategies: MA-GF, MP-GF, and MA-MP-GF, which integrate graph convolutional networks with a modality attention mechanism. …”
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Harnessing the Power of Citizen Science for Agroecological Transitions: The Case of the One Million Voices of Agroecology Initiative and Digital Platform by Lisa Elena Fuchs, Lily Cannell van Dien, Maria Rosa ‘Rosy’ Mondardini, Ma Estrella ‘Esther’ Penunia, Irish Baguilat, Sergio Iván Larrea Macías, Marcelo Soares Souza, Eduardo Fernandes Formighieri, Murilo Gelain Gonçalves, Rodrigo B. Westphalen, Vitória Pimentel, Fabio Ricci, Daria Levina, Matthias Geck

“…The OMV initiative used a facilitated co-design process that involved a global review, regional partnerships, and structured dialogues in four regions of the world, and a collective prioritization process to develop the scope and features of the emerging platform. Following the recommendation of the global review to build on existing networks, the project team partnered with Agroecology Map to develop the OMV of Agroecology platform. …”
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Fault Detection in Gearboxes Using Fisher Criterion and Adaptive Neuro-Fuzzy Inference by Houssem Habbouche, Tarak Benkedjouh, Yassine Amirat, Mohamed Benbouzid

“…These selected features are then employed to train an Adaptive Neuro-Fuzzy Inference System (ANFIS), a sophisticated approach that combines the learning capabilities of neural networks with the reasoning abilities of fuzzy logic. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…Meanwhile, the SHAP method is used to analyze the feature importance and enhance the interpretability of the proposed model. …”
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Blasting vibration velocity prediction of open pit mines based on GRA-EPSO-SVM model by Pengfei ZHANG, Yong YUAN, Yunhua HE, Shaojun DAI, Jiazhen LI, Xuehai CHI, Wei LI, Xue SUN, Jiao ZHANG, Runcai BAI, Honglu FEI

“…The peak value of blasting vibration in open pit mine is the main index to evaluate blasting effect. In the scene of coal and rock interbedded blasting in open-pit mine, aiming at the problems that the existing prediction methods of blasting vibration peak value are difficult to achieve ideal prediction results, resulting in unreasonable design of blasting parameters and initiation network, a prediction model of blasting vibration peak value based on integrated particle swarm optimization support vector machine algorithm (GRA-EPSO-SVM) with grey correlation degree feature selection is proposed. …”
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Enhancing Pollen Prediction in Beijing, a Chinese Megacity: Leveraging Ensemble Learning Models for Greater Accuracy by Wenxi Ruan, Ziming Li, Zhaobin Sun, Xingqin An, Yuxin Zhao, Shuwen Zhang, Yinglin Liang, Yaqin Bu, Jingyi Xin, Xiaoyi Hang

“…In contrast, algorithms such as Neural Network, LightGBM, and K-nearest Neighbor demonstrate weaker performance, though all models except Neural NetTorch achieve R2 values above 0.50. …”
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Clinical innovation research model for fundus diseases: 6 elements, 3 ones by WEN Feng, ZHANG Xiongze, LI Miaoling, GAN Yuhong, SU Yongyue

“…This model emphasizes: 1) identifying a single abnormal case during routine fundus evaluation; 2) systematically expanding this observation into a case series through case accumulation, feature extraction, literature review, and comparative analysis; and 3) ultimately proposing or refining novel disease entities or manifestations through critical thinking and innovation. …”
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Depletion of core microbiome forms the shared background against diverging dysbiosis patterns in Crohn’s disease and intestinal tuberculosis: insights from an integrated multi-coho... by Aditya Bajaj, Manasvini Markandey, Amit Samal, Sourav Goswami, Sudheer K. Vuyyuru, Srikant Mohta, Bhaskar Kante, Peeyush Kumar, Govind Makharia, Saurabh Kedia, Tarini Shankar Ghosh, Vineet Ahuja

“…The study aims to decipher CD and ITB-associated gut dysbiosis signatures and identify disease-associated co-occurring modules to evaluate whether this dysbiosis signature is a disease-specific trait or is a shared feature across diseases of diverging etiologies. …”
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Water quality anomaly detection research based on GRU-PINN model by Zhao Xinyu

“…This paper introduces the GRU-PINN model, developed based on the Gated Recurrent Unit (GRU) network and integrated with a Physics-Informed Neural Network (PINN), to analyze real-world monitoring data from a water treatment company. …”
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FLE-YOLO: A Faster, Lighter, and More Efficient Strategy for Autonomous Tower Crane Hook Detection by Xin Hu, Xiyu Wang, Yashu Chang, Jian Xiao, Hongliang Cheng, Firdaousse Abdelhad

“…Firstly, the FasterNet is used as the backbone for feature extraction, and the Triplet Attention mechanism is integrated to effectively emphasize target information while maintaining network lightweightness effectively. …”
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