Sea buckthorn fly, manifestations of its turn and control in agrocenoses of buckthorn by T. Moskalets, V. Moskalets, I. Grynyk, I.V. Shevchuk

“…To investigate the bioecological and morphological features of the sea buckthorn fly, to evaluate the manifestations of parasitism and methods of phytophage control in agrocenoses of the sea buckthorn. …”
Get full text

Automated Detection and Biomarker Identification Associated with the Structural and Functional Progression of Glaucoma on Longitudinal Color Fundus Images by Iyad Majid, Zubin Mishra, Ziyuan Chris Wang, Vikas Chopra, Dale Heuer, Zhihong Jewel Hu

“…To detect glaucoma progression from ocular hypertension both structurally and functionally, and identify potential objective early biomarkers associated with progression, we developed and evaluated deep convolutional long short-term memory (CNN-LSTM) neural network models using longitudinal CFPs from the Ocular Hypertension Treatment Study (OHTS). …”
Get full text

A comparative study and simple baseline for travel time prediction by Chuang-Chieh Lin, Ming-Chu Ho, Chih-Chieh Hung, Hui-Huang Hsu

“…Based on these insights, we propose a baseline that fuses the complementary strengths of XGBoost and LSTM via a gating network. This approach dynamically allocates weights, guided by key statistical features, to each model, enabling the model to robustly adapt to both stable and volatile traffic conditions and achieve superior prediction accuracy compared to existing methods. …”
Get full text

Prediction of Myopia Among Undergraduate Students Using Ensemble Machine Learning Techniques by Isteaq Kabir Sifat, Tajin Ahmed Jisa, Jyoti Shree Roy, Nourin Sultana, Farhana Hasan, Md Parvez Mosharaf, Md. Kaderi Kibria

“…Using these features, ensemble methods, including logistic regression artificial neural network, RF, Support Vector Machine, extreme gradient boosting, and light gradient boosting machine were employed for prediction. …”
Get full text

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…However, these models require manual methods for feature extraction, and the prediction accuracy greatly depends on the type of feature extracted. …”
Get full text

Development and Validation of a Clinical Risk Model for Predicting Malignancy in Patients with Thyroid Nodules by Shiva Borzouei, Ali Safdari, Erfan Ayubi

“…The diagnostic performance of the GLM was compared with five machine learning (ML) algorithms, including linear discriminant analysis (LDA), random forest, neural network, support vector machine, and k-nearest neighbor.  …”
Get full text

A non-invasive wearable microwave sensor for Alzheimer's Stage differentiation using realistic 3D human head phantoms by Jinan N. Shehab, Malik Jasim Farhan, Saad Al-Azawi

“…The proposed system features a compact antenna design that achieves an optimal balance between gain and size, along with a realistic head phantom that enhances testing accuracy.While not yet validated for clinical deployment, its performance was evaluated using a vector network analyzer (VNA), and the results confirmed its high compatibility with biological tissues, demonstrating its effectiveness in accurately detecting Alzheimer's-related dielectric changes through microwave technology.…”
Get full text

Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
Get full text

Identifying COVID-19-Infected Segments in Lung CT Scan Through Two Innovative Artificial Intelligence-Based Transformer Models by Zeinab Momeni pour, Ali Asghar Beheshti Shirazi

“…The proposed networks were evaluated using a 5-fold cross-validation methodology, along with data augmentation techniques, applied to the COVID-19-CT-Seg and MosMed datasets. …”
Get full text

CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer by Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu

“…To overcome the limitations of existing public datasets, which often feature a narrow range of crack types and simplistic backgrounds, this study introduces TunnelCrackDB, a dataset encompassing diverse crack types and complex backgrounds.Experimental evaluations on both the public Crack dataset and the newly developed TunnelCrackDB demonstrate the efficacy of CGV-Net. …”
Get full text

Application of machine learning algorithms in osteoporosis analysis based on cardiovascular health assessed by life’s essential 8: a cross-sectional study by Haolin Shi, Yangyi Fang, Xiuhua Ma

Get full text

Radiation shielding study of tungsten impact on tellurite-bismuth based glasses by Kh.A. Bashar, M.F.N. Jaafar, Y. Mansur, S.O. Baki, M.A. Mahdi

“…The phase formation of all samples is analyzed by XRD (x-ray diffraction) were found they are without any crystallization network. Some physical properties like density and molar volume were estimated as well. …”
Get full text

A Multimodal Pain Sentiment Analysis System Using Ensembled Deep Learning Approaches for IoT-Enabled Healthcare Framework by Anay Ghosh, Saiyed Umer, Bibhas Chandra Dhara, G. G. Md. Nawaz Ali

“…In the second phase, the system extracts discriminant and divergent features from the facial region using deep learning techniques, utilizing some convolutional neural network (CNN) architectures, which are further refined through transfer learning and fine-tuning of parameters, alongside fusion techniques aimed at optimizing the model’s performance. …”
Get full text

Is highly purified cannabidiol a treatment opportunity for drug‐resistant epilepsy in subjects with typical Rett syndrome and CDKL5 deficiency disorder? by Aglaia Vignoli, Giulia Prato, Enrico Alfei, Irene Bagnasco, Alberto Danieli, Massimiliano Celario, Jacopo Favaro, Sara Matricardi, Francesca Felicia Operto, Alessandro Orsini, Davide Paolo Bernasconi, Nicola Pietrafusa, Emilia Ricci, Luca Manfredini, Giulia Balletto, Paolo Bonanni, Maria Paola Canevini, Valentina De Giorgis, Lino Nobili, Stefano Sartori, Miriam Nella Savini, Ilaria Viganò, Nicola Specchio

Get full text

Rational Molecular Engineering of Amidonaphthoquinone Cathodes: Precise Hydrogen Bond and Size Control for High‐Performance Lithium Organic Batteries by Qianglong Chen, Fangfang Xing, Jia Cai, Xiujuan Wang, Xiaoming He

“…This study presents a facile synthesis strategy for three naphthoquinone derivatives (NQ1‐NQ3) featuring tunable amide functionalities and molecular dimensions, followed by a systematic evaluation of their electrochemical performance in lithium‐organic batteries (LOBs). …”
Get full text

A multimodal educational robots driven via dynamic attention by An Jianliang, An Jianliang

“…In addition, the model integrates a VGG19-based convolutional network for image feature extraction and utilizes a dynamic attention mechanism to dynamically focus on relevant parts of multimodal inputs. …”
Get full text

Research on building energy consumption prediction algorithm based on customized deep learning model by Zheng Liang, Junjie Chen

“…This paper proposes a customized convolutional neural network with Q-Learning (CCNN-QL) based reinforcement learning algorithm for predicting energy consumption in building.The suggested CCNN-QL model offers an auto-learning feature that predicts building energy consumption through an automated method, continually improving its predictive accuracy.To assess its performance, various building types were selected to study the factors influencing excessive energy consumption, and data were collected from multiple Chinese cities. …”
Get full text

Investigation on the physical–mechanical response characteristics and failure mechanisms of shale under the laser thermal field by Yuze Du, Jing Xie, Zheqiang Jia, Li Ren, Zeyu Zhu, Junjun Liu, Lei Yang, Ting Ai, Bengao Yang, Mingzhong Gao

“…It investigates the spatiotemporal evolution characteristics of the shale temperature field under laser irradiation, the propagation features of cracks on shale surface, and the physicochemical fracture mechanisms. …”
Get full text

Identifying diagnostic biomarkers for glaucoma based on transcriptome combined with Mendelian randomization by Xiuli Lin, Chuanyong Ma, Xiaoxue Zhang, Yuzhe Qiu, Yi Cui, Nuo Xu

“…Using the GSE9944 dataset, differentially expressed genes (DEGs) were identified and analyzed through protein-protein interaction (PPI) networks and functional enrichment. MR analysis selected DEGs for further evaluation using support vector machine-recursive feature elimination (SVM-RFE), with genes exhibiting high differential expression and an area under the curve (AUC) > 0.7 considered as candidate biomarkers. …”
Get full text

Planning for Cultural Connectivity: Modeling and Strategic Use of Architectural Heritage Corridors in Heilongjiang Province, China by Lyuhang Feng, Jiawei Sun, Tongtong Zhai, Mingrui Miao, Guanchao Yu

“…A closed-loop strategy of “identification–analysis–optimization” is developed, featuring tiered collaboration, cultural–ecological synergy, and multi-agent dynamic evaluation. …”
Get full text