The evolutionary landscape of prokaryotic chromosome/plasmid balance by Wenzhi Xue, Juken Hong, Teng Wang

“…This landscape is further validated by the observed pattern of plasmid distributions in the vast collection of prokaryotic genomes retrieved from the NCBI database. …”
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Optimizing IoT intrusion detection with cosine similarity based dataset balancing and hybrid deep learning by Arvind Prasad, Wael Mohammad Alenazy, Naved Ahmad, Gauhar Ali, Hanaa A. Abdallah, Sadique Ahmad

“…Additionally, we developed a hybrid deep learning model integrating RegNet and FBNet architectures to enhance feature extraction and classification performance. …”
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An adaptive search mechanism with convolutional learning networks for online social media text summarization and classification model by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Hassan Alkhiri, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

“…Removing valued patterns and insights from this vast amount of textual data requires advanced methods to provide information while preserving its essential components successfully. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…As environmental sciences increasingly rely on complex datasets, machine learning (ML) has become crucial for identifying patterns and relationships. However, the integration of ML into workflows can pose challenges due to technical barriers or the time-intensive nature of coding. …”
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Sentences, entities, and keyphrases extraction from consumer health forums using multi-task learning by Tsaqif Naufal, Rahmad Mahendra, Alfan Farizki Wicaksono

“…Despite varying loss weights across our three-way MTL models, we did not identify a consistent pattern. While some configurations improved MER and KE performance, none surpassed the best pairwise MTL model for the SR task. …”
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A Case Series of Septicemia Due to Community-acquired Panton–Valentine Toxin Positive Methicillin-resistant <i>Staphylococcus aureus</i> in Children in Abidjan, Côte d'Ivoire by Richard Azagoh-Kouadio, Adjoua Sonia Djè, Sy Kadidia Savané, Claude Ghislain Tué-Bi, Toutou Ismael Koné, Sanemba Aya Fanny, Melissa Cardenat

“…Clinical significance: This case series highlights the need for a high index of suspicion for new antibiotic resistance patterns in emerging countries with limited microbiological diagnostic resources.…”
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Assessing HIV-1 subtype C infection dynamics, therapeutic responses and reservoir distribution using a humanized mouse model by Snehal Kaginkar, Leila Remling-Mulder, Ashashree Sahoo, Tejaswini Pandey, Pranay Gurav, Jyoti Sutar, Amit Kumar Singh, Ella Barnett, Sivasankar Panickan, Ramesh Akkina, Vainav Patel

“…HIV-1C displays distinct genetic and pathogenic features from that of HIV-1B. Thus, treatment approaches developed for HIV-1B need to be suitably optimized for HIV-1C. …”
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Identification and Evolution of Core Technologies in the Chip Field Based on Patent Networks by Ying Wang, Renda Chen, Jindong Chen

“…Currently, the global technological competition pattern is accelerating its restructuring, and chip technology, as a core technology for national strategic security and industrial competition, faces a serious bottleneck that seriously restricts the construction of China’s industrial chain security and innovation ecology. …”
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Research on Damage Detection of Dual-Rotor Synchronous Excitation Mine Screen Beams Based on Strain Mode Difference Vibration Mode Analysis by Xiaohao Li, Yahui Wang, Yang Zhou

“…Based on the characterization of the vibration response of mine screen frame beams with varying degrees of damage at the same location and with the same degree of damage but at different locations, this paper develops a method of strain modal difference vibration pattern analysis and damage feature extraction for the detection of structural damage in beams. …”
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Automated analysis of retinal microcirculation in type 1 diabetes mellitus by Yu. N. Yusef, M. H. Durzhinskaya, V. G. Pavlov, D. V. Petrachkov, I. B. Gurevich, V. V. Yashina, A. T. Tleubaev, V. V. Fadeyev, I. V. Poluboyarinova, A. E. Goldsmid, R. А. Karamullina, D. V. Lipatov, M. V. Budzinskaya

“…BACKGROUND: The paper is dedicated to the assessment of the retinal microvasculature in patients with type 1 diabetes mellitus (DM) with various features of the clinical course and different stages of diabetic retinopathy (DR). …”
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Breeding of a new mid-to-late ripening apple cultivar Wangyuebingcui by XU Haihong, YANG Kai, LI Guangjin, ZHANG Guoqiang, TIAN Ge, AI Bohao, LI Xuqiang, WANG Junya

“…The cultivar combines high budbreak rate with moderate branching capacity, exhibiting spur-type growth pattern, sustained cluster-base productivity, and axillary flowering propensity. …”
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Spatiotemporal Forecasting of Solar and Wind Energy Production: A Robust Deep Learning Model with Attention Framework by Md. Shadman Abid, Razzaqul Ahshan, Mohammed Al-Abri, Rashid Al Abri

“…In this context, a novel robust deep learning model, termed the Convolutional Neural Network-Bidirectional Long Short-Term Memory model with spatiotemporal attention mechanism (CNN-BiLSTM-STA), is developed in this study. The suggested model integrates the feature extraction expertise of CNNs with the sequence modeling proficiency of BiLSTM networks to capture spatial linkages and temporal interdependence adeptly. …”
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Identify suitable artificial groundwater recharge zones using hybrid deep learning models by Navaz Khalillollahi, Mohsen Isari, Hamed Faroqi, Kaywan Othman Ahmed, Kamran Nobakht Vakili, Miklas Scholz, Saad Sh. Sammeng

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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

“…This integration allows for a more comprehensive characterization of precipitation patterns, jointly capturing spatial autocorrelation and covariate-based variability. …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…InSAR techniques allow for high-precision measurements of surface deformation across large areas, making them invaluable in understanding and modeling subsidence patterns. When combined with machine learning approaches, these technologies offer even greater potential for developing predictive models and susceptibility maps, enabling proactive risk management. …”
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Exploring the relationship between sepsis and Golgi apparatus dysfunction: bioinformatics insights and diagnostic marker discovery by Wanli Ma, Xinyi Liu, Ran Yu, Jiannan Song, Lina Hou, Ying Guo, Hongwei Wu, Dandan Feng, Qi Zhou, Haibo Li

“…A diagnostic model was developed using logistic regression, and its performance was validated using ROC curve analysis. …”
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The Conceptual Comparison Between Vecdi Akyüz’s Work Titled Kur’an’da Siyasi Kavramlar and Manzooriddin Ahmad’s Work Titled Islamic Political System in the Modern Age: Theory and P... by Ayşe Aytekin

“…In this manner, it is much more necessary and obligatory to analyze and understand the focal concepts in the process of understanding and making sense of the sacred texts, in which the divine messages that are desired to be conveyed to people are presented in various conceptual patterns, compared to other texts. As a matter of fact, to examine the meaning dimensions of the focal concepts in the Qur’ān correctly, which have connotations, as well as their basic dictionary meanings, and the new meanings they have gained in the context of the Qur’ān, and to explore the adventures of these terms successfully, are very valuable for both understanding and applying the message and in terms of its contribution to the science of tafsīr. …”
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Efficiency of Paraumbilical Trocar Hernias Alloplasty Methods, Combined with Diastasis Recti, Taking Into Account the Risk Factors of Their Relapse (First Notice) by Dadayan V.

“…However, due to the small number of the patients included into this study, it is expedient to continue the further accumulation of the actual material, the processing of which would allow to obtain the substantially probable results of the revealed patterns.…”
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GradCAM-PestDetNet: A deep learning-based hybrid model with explainable AI for pest detection and classification by Ramitha Vimala, Saharsh Mehrotra, Satish Kumar, Pooja Kamat, Arunkumar Bongale, Ketan Kotecha

“…The GradCAM-PestDetNet methodology utilizes object detection models like YOLOv8m, YOLOv8s and YOLOv8n, alongside transfer learning techniques such as VGG16, ResNet50, EfficientNetB0, MobileNetV2, InceptionV3 and DenseNet121 for feature extraction. Additionally, Vision Transformers (ViT) and Swim Transformers were explored for their ability to process complex data patterns. …”
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MobilitApp: A Deep Learning-Based Tool for Transport Mode Detection to Support Sustainable Urban Mobility by Gerard Caravaca Ibanez, Luis J. de la Cruz Llopis, Adrian Catalin Diaconeasa, Alberto Bazan Guillen, Monica Aguilar Igartua

“…By analyzing travel patterns, transport modes, and mode-switching behaviors, it delivers actionable insights to city planners, aiding in the enhancement of urban mobility, promotion of sustainable development, and transition to greener cities.…”
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