Exploring oral hygiene practices, nutritional habits and caries risk among children, adolescents and young adults: a multiregional perspective in the post-COVID-19 era by Azhar Iqbal, Osama Khattak, Yasir Dilshad Siddiqui, Saud Hamdan Almaeen, Saeed Alqahtani, Saleh Ali Alqahtani, Saeed Awod Bin Hassan, Faisal Hasan Alshehri, Ali Y. Alsaeed, Mahmoud K. AL-Omiri

“…Results There was a notable increase in the caries experience rate, which escalated from 26.1% before the onset of the COVID-19 pandemic to 45.0% during the pandemic (P < 0.001). …”
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Intra-familial transmission of Hepatitis B virus in a peri-urban community from the Democratic Republic of the Congo by Florence Cindibu Kalonji, Yu Nakagama, Evariste Tshibangu-Kabamba, Nadine Kayiba Kalenda, Shun Nakagama, Sachie Nakagama, Pathy Kamanga Nkolongo, Nestor Kalala-Tshituka, Alphonse Lufuluabu Mpemba, Faustin Ndjibu Mpoji, André Kabongu Kalala, Benjamin Muamba Mpoyi, Dieudonné Mumba Ngoyi, Natsuko Kaku, Yusuke Shimakawa, Ghislain Tumba Disashi, Yasutoshi Kido

“…The overall HBsAg prevalence was 3.8% [95% CI 2.6–5.7], with the highest rate (10.1% [95% CI 4.9–18.2]) found in children aged 5 years and younger. …”
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A mobile app to improve adherence to colorectal cancer screening and post polypectomy surveillance guidelines by María A. Casas, Francisco Schlottmann, Leandro Steinberg, Xavier Bessa, Anna Serradesanferm, Angels Pozo, Sonia Torres, Antoni Castells, Francesc Balaguer, Jaume Grau, Lisandro Pereyra, María Pellisé

“…Users’ characteristics, consultation types, and patient data were analyzed to assess app’s implementation, usage patterns, and impact on CRC screening and surveillance outcomes. …”
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Toward AI-Augmented Formal Verification: A Preliminary Investigation of ENGRU and Its Challenges by Chanon Dechsupa, Teerapong Panboonyuen, Wiwat Vatanawood, Praisan Padungweang, Chakchai So-In

“…In this paper, we present ENGRU (Enhanced Gated Recurrent Units), a novel deep learning-based approach for formal verification. …”
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Ultrafast complex-valued 4D fMRI reveals sleep-induced brain respiratory pulsation changes in both magnitude and phase signals by Saara Sofia Syväoja, Lauri Raitamaa, Heta Helakari, Jussi Kantola, Matti Järvelä, Janne Kananen, Ville Isokoski, Vesa Korhonen, Tommi Väyrynen, Timo Tuovinen, Jürgen Hennig, Vesa Kiviniemi

“…To study these pulsations more deeply, we employed ultrafast magnetic resonance encephalography (MREG) to capture complex-valued 4D fMRI brain data at a critical 10 Hz sampling rate in healthy volunteers during wakefulness and sleep. …”
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Progressive subcortical involvement as spinocerebellar ataxia type 3 advances by Pubing Yuan, Yonghua Huang, Minghui Dai, Xin Jin, Dingxin Zheng, Die Xiao, Lihua Deng, Peiling Ou, Linfeng Shi, Yifan Chen, Jian Wang, Wei Chen, Yuanchao Zhang, Chen Liu

“…Abstract Background and objectives Spinocerebellar ataxia type 3 (SCA3) is a progressive neurodegenerative disease characterized by heterogeneous motor and nonmotor manifestations. The progressive pattern of subcortical shape abnormalities and their associations with the clinical phenotypes in SCA3 remain unknown. …”
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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The study proposes a novel automated technique for diagnosing Schizophrenia based on electroencephalogram (EEG) sensor data, aiming to enhance interpretability and prediction performance.MethodsThis research utilizes Deep Learning (DL) models, including the Deep Neural Network (DNN), Bi-Directional Long Short-Term Memory-Gated Recurrent Unit (BiLSTM- GRU), and BiLSTM with Attention, for the detection of Schizophrenia based on EEG data. …”
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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…Concurrently, variational mode decomposition (VMD) provides frequency-domain decomposition capability, while the gated recurrent unit (GRU) captures long-term dependencies. …”
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Multiscale Water Cycle Mechanisms and Return Flow Utilization in Paddy Fields of Plain Irrigation Districts by Jie Zhang, Yujiang Xiong, Peihua Jiang, Niannian Yuan, Fengli Liu

“…We propose an integrated optimization strategy combining tillering-stage irrigation/drainage control, multiscale hydraulic interception (control gates and pond weirs), and dynamic watershed storage scheduling. …”
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Trade-offs between machine learning and deep learning for mental illness detection on social media by Zhanyi Ding, Zhongyan Wang, Yeyubei Zhang, Yuchen Cao, Yunchong Liu, Xiaorui Shen, Yexin Tian, Jianglai Dai

“…This study evaluates multiple ML models, including logistic regression, random forest, and LightGBM, alongside DL architectures such as ALBERT and Gated Recurrent Units (GRUs), for both binary and multi-class classification of mental health conditions. …”
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The diagnostic utility of lung ultrasound in the assessment of interstitial lung disease associated with rheumatoid arthritis by Shaoyu Zheng, Zexuan Zhou, Guangzhou Du, Qingzi Chen, Shaoqi Chen, Jianqun Lin, Shijian Hu, Weijin Zhang, Kedi Zheng, Jinghua Zhuang, Meigan Huang, Barbara Ruaro, Cosimo Bruni, Anna-Maria Hoffmann-Vold, Marco Matucci-Cerinic, Daniel E. Furst, Yukai Wang

“…Sonographic ILD was detected in 76 patients who underwent LUS examination. The concordance rate between two modalities was 83.33% (Kappa value = 0.64, 95% CI 0.50–0.78). …”
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Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning by Mohammed Assiri, Mahmoud M. Selim

“…For the feature extraction process, the squeeze-and-excitation capsule network (SE-CapsNet) effectively captures spatial hierarchies and complex relationships within gesture patterns. In addition, an ensemble of classification processes, such as bidirectional gated recurrent unit (BiGRU), Variational Autoencoder (VAE), and bidirectional long short-term memory (BiLSTM) technique, is employed. …”
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Wind Speed Forecasting in the Greek Seas Using Hybrid Artificial Neural Networks by Lateef Adesola Afolabi, Takvor Soukissian, Diego Vicinanza, Pasquale Contestabile

“…Of all the ANNs examined, the hybrid model combining Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks demonstrated superior forecasting performance compared to the individual models, as evaluated by standard statistical metrics, while it also exhibited a very good performance at high wind speeds, i.e., greater than 15 m/s. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…Hybrid forecasting models were then constructed by integrating VMD with both statistical (autoregressive integrated moving average [ARIMA]) and deep learning (gated recurrent unit [GRU], long short-term memory [LSTM], and Transformer) architectures. …”
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An Overview of Deep Learning Applications in Groundwater Level Modeling: Bridging the Gap between Academic Research and Industry Applications by Ahmed Shakir Ali Ali, Farhad Jazaei, Peyman Babakhani, Muhammad Masood Ashiq, Alireza Bakhshaee, Brian Waldron

“…Later, this article delves specifically into the latest advancements in DL for modeling GWL, including recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU), and discusses their technical promising performance and advantages. …”
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Multi-view mixture-of-experts for predicting molecular properties using SMILES, SELFIES, and graph-based representations by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Indra Priyadarsini, Seiji Takeda

“…Our analysis of routing activation patterns reveals that MoL-MoE dynamically adjusts its use of different molecular representations based on task-specific requirements. …”
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An Iterative Pixel-Based Dimensional Voting Model for High Spatial-Resolution Image Classification by Muhamad Asyraf Mohd Pouzi, Haza Nuzly Abdull Hamed, Muhammad Razib Othman, Hishammuddin Asmuni, Mohd Adham Isa, Husni Ruslai

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Mediodorsal thalamic nucleus mediates resistance to ethanol through Cav3.1 T-type Ca2+ regulation of neural activity by Charles-francois V Latchoumane, Joon-Hyuk Lee, Seong-Wook Kim, Jinhyun Kim, Hee-Sup Shin

“…Thalamocortical activity is known to orchestrate sensory gating and consciousness switching. The precise thalamic regions involved, or the firing patterns related to the unconsciousness, remain unclear. …”
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Hybrid GIS-Transformer Approach for Forecasting Sentinel-1 Displacement Time Series by Lama Moualla, Alessio Rucci, Giampiero Naletto, Nantheera Anantrasirichai, Vania Da Deppo

“…This study presents a deep learning-based approach for forecasting Sentinel-1 displacement time series, with particular attention to irregular temporal patterns—an aspect often overlooked in previous works. …”
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Analysis of HBV infection characteristics and OBI prevalence in pregnant women: a focus on HBcAb + alone or in combination with HBeAb + subgroups in Northwest China by Yun Xie, Ru Kang, Xiaoyue Cheng, Dan Li, Qi Wang, Jiao Li, Xuan Guo, Wenhui Gao, Xin He, Liutong Jiang, Gaili Meng

“…Abstract Background Hepatitis B virus (HBV) infection is a major global health concern. Serological patterns such as “HBeAb + and HBcAb+” or “HBcAb + only” are typically markers, which may represent either resolved infection or potential occult HBV infection (OBI) with risk of vertical transmission. …”
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