Comprehensive Transcriptome Sequencing and Analysis of <i>Euspira gilva</i>: Insights into Aquaculture and Conservation by Zhixing Su, Jiayuan Xu, Xiaokang Lv, Xuefeng Song, Yanming Sui, Benjian Wang, Xiaoshan Wang, Bianbian Zhang, Baojun Tang, Liguo Yang

“…The findings of this research elucidate the full-length transcriptome profile of <i>E. gilva</i>, thereby establishing a foundational dataset and providing valuable insights for the species’ aquaculture, health management, conservation efforts, and future molecular biological investigations.…”
Get full text

Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care by Annarita Vignapiano, Annarita Vignapiano, Francesco Monaco, Francesco Monaco, Stefania Landi, Luca Steardo, Carlo Mancuso, Claudio Pagano, Gianvito Petrillo, Alessandra Marenna, Martina Piacente, Stefano Leo, Carminia Marina Ingenito, Rossella Bonifacio, Benedetta Di Gruttola, Marco Solmi, Marco Solmi, Marco Solmi, Marco Solmi, Maria Pontillo, Giorgio Di Lorenzo, Giorgio Di Lorenzo, Alessio Fasano, Alessio Fasano, Alessio Fasano, Giulio Corrivetti, Giulio Corrivetti

Get full text

Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking by Jun Liu, Yu Liu, Kai Dong, Ziran Ding, You He, Qichao Li

Get full text

Harnessing artificial intelligence role in oral cancer diagnosis and prediction: A comprehensive exploration by Archana Behera, N. Aravindha Babu, Remya Rajan Renuka, Mukesh Kumar Dharmalingam Jothinathan

“…The areas in need of refinement or expansion include research, data interoperability, and global partnerships. …”
Get full text

Transcriptomic Analysis of the Spleen from Asian Seabass (<i>Lates calcarifer</i>) Infected with Infectious Spleen and Kidney Necrosis Virus by Hong-Yi Xin, Lim Xin Ying, Lee Ching Pei Carmen, Mookkan Prabakaran

“…These findings provide new insights into the molecular mechanisms driving ISKNV infection in Asian seabass. Future research should focus on elucidating the regulatory functions of these key genes and their roles in ISKNV pathogenesis.…”
Get full text

Diagnosis and activity prediction of SLE based on serum Raman spectroscopy combined with a two-branch Bayesian network by Qianxi Xu, Qianxi Xu, Qianxi Xu, Xue Wu, Xue Wu, Xue Wu, Xinya Chen, Ziyang Zhang, Jinrun Wang, Jinrun Wang, Zhengfang Li, Zhengfang Li, Zhengfang Li, Xiaomei Chen, Xiaomei Chen, Xiaomei Chen, Xin Lei, Xin Lei, Zhuoyu Li, Zhuoyu Li, Zhuoyu Li, Mengsi Ma, Mengsi Ma, Mengsi Ma, Chen Chen, Lijun Wu, Lijun Wu

“…The model’s potential for clinical applications and research value in early diagnosis and activity assessment of SLE is significant.…”
Get full text

GrapeSLAM: UAV-based monocular visual dataset for SLAM, SfM and 3D reconstruction with trajectories under challenging illumination conditionszenodo by Kaiwen Wang, Sergio Vélez, Lammert Kooistra, Wensheng Wang, João Valente

“…However, there are limited public datasets to implement and develop robotic algorithms for agricultural environments. Therefore, we collected dataset “GrapeSLAM”. …”
Get full text

Domain-Adaptive and Per-Fraction Guided Deep Learning Framework for Magnetic Resonance Imaging-Based Segmentation of Organs at Risk in Gynecologic Cancers by Reza Kalantar, PhD, Manasi Ingle, FRCR, Romelie Rieu, BA, BmBCh, Sebastian Curcean, MD, Jessica Mary Winfield, PhD, Gigin Lin, MD, PhD, Christina Messiou, MD, MRCP, FRCR, Susan Lalondrelle, FRCR, Dow-Mu Koh, MD, FRCP, FRCR, Matthew David Blackledge, PhD

Get full text

THE RESULTS OF MYOCARDIAL REVASCULARIZATION IN NON-ST-ELEVATION ACUTE CORONARY SYNDROME PATIENTS AND MULTIVESSEL DISEASE by R. S. Tarasov, Yu. N. Neverova, V. I. Ganyukov, S. V. Ivanov, O. A. Nagirnyak, O. L. Barbarash, L. S. Barbarash

Get full text

Linking online activity to offline behavior: A meta-review of three decades of online-to-offline scholarship with future implications for AI by Scott Leo Renshaw, Kathleen M. Carley

“…Finally, we conduct a Term Frequency-Inverse Document Frequency (TF-IDF) analysis of terms used in the titles of these online/offline research papers, from 1990 to 2023, to identify the evolution of researchers’ conceptualization and framing of Online and Offline research across the past 30 years. …”
Get full text

SURGICAL TREATMENT OF SOLITARY ADRENAL METASTASIS FROM NON-SMALL CELL LUNG CANCER by A. G. Muradyan, A. A. Kostin, A. O. Tolkachev, N. V. Vorobyev

Get full text

Maize and soybean yield prediction using machine learning methods: a systematic literature review by Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon

“…These papers were thoroughly analysed for generating common consensus and future research recommendations. Results revealed the temperature, precipitation, historical crop yield, normalized difference vegetation index (NDVI), and soil pH to be the most utilized ML features for yield prediction research. …”
Get full text

Analyzing Random Forest&#x2019;s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…This explorative study aims to uncover the potential of random forest machine learning algorithms as survival models within the biomedical context of T1D. …”
Get full text

An survey on application of artificial intelligence in 5G system by Jianwu ZHANG, Luxin WANG, Lingfen SUN, Qianye ZHANG, Hangguan SHAN

“…With the continuous development of 5G, the era of the internet of everything is coming.Problems such as massive device connections, massive application requests, ultra-high network load and complex dynamic network environment pose great challenges to the optimization of 5G systems in the context of the internet of everything.Facing these challenges, artificial intelligence (AI) shows its unique advantages.Firstly, the advantages of deep learning driven AI algorithms in 5G system compared with conventional algorithms were briefly introduced.Then, the application of AI algorithms in multi-access edge computing (MEC) and mmWave massive multiple-input multiple-output (MIMO) system were described in detail, with advantages and disadvantages of each method being compared and analyzed.Finally, according to the existing research, the shortcomings of AI algorithms in 5G application scenarios were summarized and the future research directions were forecasted.…”
Get full text

AI and consumer behavior: Trends, technologies, and future directions from a scopus-based systematic review by Aditya Nanda Riandhi, Muhammad Rifqi Arviansyah, Mery Citra Sondari

“…The study examines research trends (RQ1), prevalent AI technologies (RQ2), key variables (RQ3), methodological approaches (RQ4), future research directions (RQ5), and AI’s transformative impact on consumer behavior (RQ6). …”
Get full text

Description of route dependencies for computer-based railway signalling systems by Michał Grzybowski, Jakub Młyńczak, Lucyna Sokołowska

“…In addition, during research algorithms for automatic verification of conflicting route exclusion correctness have been designed, which allows for reduction of effort required for verification of conflicting route exclusion function. …”
Get full text

Progress and current trends in prediction models for the occurrence and prognosis of cancer and cancer-related complications: a bibliometric and visualization analysis by Siyu Li, Wenrui Li, Xiaoxiao Wang, Wanyi Chen

“…Emerging modeling techniques, such as neural networks and deep learning algorithms, are likely to play a pivotal role in current and future cancer-related prediction model research. …”
Get full text

Portable EEG for assessing attention in educational settings: A scoping review by Jian-Wei Wang, Da-Wei Zhang, Stuart J. Johnstone

“…Two authors extracted data items from 45 eligible studies. Results: Three research aims were identified in previous studies: examining the effects of learning-related factors on attention captured by portable EEG (n = 23), developing attention classification algorithms (n = 7) and software for monitoring and promoting attention (n = 10), and verifying the signal quality of EEG derived from portable EEG in attentional tasks (n = 5). …”
Get full text

Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD by Chenghang Wang, Xiaochun Shen, Zhaoxiang Zhang, Chengyang Tao, Yuelei Xu

Get full text

Predicting the Acceptance of Informal Learning Technologies: A Case of the TikTok Application by Ahmed Al-Azawei, Ali Alowayr

“…Moreover, previous literature focused on the use of structural equation modeling (SEM) to predict technology acceptance, whereas the application of data mining algorithms is rare in this direction of research. This study, therefore, aims to (1) propose an integrated framework based on the DeLone and McLean information system model, the diffusion theory, the interactivity theory, the intrinsic motivation theory, and the security perceptions, (2) predict the adoption of TikTok as a learning means in an informal educational space, and (3) compare the performance of data mining techniques and SEM in predicting users’ behavioral intention towards TikTok acceptance. …”
Get full text