Identification of the best housekeeping gene for RT-qPCR analysis of human pancreatic organoids. by Alessandro Cherubini, Francesco Rusconi, Lorenza Lazzari

“…In the last few years, there has been a considerable increase in the use of organoids, which is a new three-dimensional culture technology applied in scientific research. The main reasons for their extensive use are their plasticity and multiple applications, including in regenerative medicine and the screening of new drugs. …”
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A Versatile Panel of Reference Gene Assays for the Measurement of Chicken mRNA by Quantitative PCR. by Karen Staines, Ambalika Batra, William Mwangi, Helena J Maier, Steven Van Borm, John R Young, Mark Fife, Colin Butter

“…GeNorm and NormFinder algorithms were able to select appropriate reference gene sets in each case. …”
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A Review of Vibration Control Studies of Double-Layered Cylindrical Shells Under Transient Excitation in Water by Zhen Zhang, Yinglong Zhao, Feng Chen

“…In recent years, with the wide application of underwater vehicles, the vibration and noise problems generated during their operation have attracted great attention from the academic community. Compared with the field of traditional mechanical noise, research on vibration control of the noise that is transiently excited underwater still has significant deficiencies in terms of its theoretical depth and systematicity. …”
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Landslide Identification from Post-Earthquake High-Resolution Remote Sensing Images Based on ResUNet–BFA by Zhenyu Zhao, Shucheng Tan, Yiquan Yang, Qinghua Zhang

“…However, the availability of publicly accessible deep learning datasets specifically for landslide detection remains limited, posing challenges for researchers in meeting task requirements. To address this issue, this study develops and releases a deep learning landslide dataset using Google Earth imagery, focusing on the impact zones of the 2008 Wenchuan Ms8.0 earthquake, the 2014 Ludian Ms6.5 earthquake, and the 2017 Jiuzhaigou Ms7.0 earthquake as the research areas. …”
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Site-specific prediction of O-GlcNAc modification in proteins using evolutionary scale model. by Ayesha Khalid, Afshan Kaleem, Wajahat Qazi, Roheena Abdullah, Mehwish Iqtedar, Shagufta Naz

“…Computational approaches, including protein language models and machine learning algorithms, have emerged as valuable tools for predicting O-GlcNAc sites, reducing experimental costs, and enhancing efficiency. …”
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Evaluating the Effectiveness of Various Small RNA Alignment Techniques in Transcriptomic Analysis by Examining Different Sources of Variability Through a Multi-Alignment Approach by Xinwei Zhao, Eberhard Korsching

“…This framework can be used to compare results from different alignment programs and algorithms on the same dataset, allowing for a comprehensive analysis of subtle to significant differences. …”
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PUBLICATIONS OF HISTORIANS OF THE COSSACK EMIGRATION AS A SOURCE OF INFORMATION ON THE NEW ECONOMIC POLICY IN THE DON AND KUBAN REGIONS (1920-s) by A. Baranov, O. Ratushnyak

“…The topic is relevant for rethinking the features of the New economic policy of 1921-1929 in the South of Russia, to clarify the discourse of publications of historians of the Cossacks' abroad of the first generation. The novelty of the research consists in comparing the level of awareness and assessments of NEP in the Cossack, socialist and liberal historical traditions abroad, introducing a number of publications in the periodical press of the 1920s into scientific circulation. …”
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Blood biomarker discovery for autism spectrum disorder: A proteomic analysis. by Laura Hewitson, Jeremy A Mathews, Morgan Devlin, Claire Schutte, Jeon Lee, Dwight C German

“…Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. …”
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Klasifikasi Katarak Berdasarkan Optic Disc Citra Fundus Smartphone: Perbandingan Ekstraksi Ciri Tekstur Dan Metode Neural Network by Muchtar Ali Setyo Yudono, Fabrobi Fazlur Ridha, Dani Mardiyana, Faturrohman Al-Ghozi, Aldi Maulana

“…Conventional fundus cameras, while effective, are expensive and less portable, limiting accessibility in remote areas. This research aims to develop an automatic cataract classification system using smartphone-based fundus cameras, offering a more cost-effective and portable solution compared to conventional devices. …”
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TerraCraft: City-scale generative procedural modeling with natural languages by Zichen Xi, Zhihao Yao, Jiahui Huang, Zi-Qi Lu, Hongyu Yan, Tai-Jiang Mu, Zhigang Wang, Qun-Ce Xu

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TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique by Muhammad Waqas, Fengli Zhang, Asif Ali Laghari, Ahmad Almadhor, Filip Petrinec, Asif Iqbal, Mian Muhammad Yasir Khalil

“…The advancement of machine learning algorithms in multiple fields also attracted the attention of Automatic Personality Prediction (APP). …”
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A review of deep-learning-based models for afaan oromo fake news detection on social media networks by Kedir Lemma Arega, Kula Kekeba Tune, Asrat Mulatu Beyene, Wegderes Tariku, Nurhussen Menza Bune

“…Abstract This study explores fake news detection techniques in Afan Oromo using deep learning methods. It compares machine learning and deep learning algorithms, proposes future studies using picture data, and encourages more effective methodologies. …”
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Population Structure of the Invasive Asian Tiger Mosquito, Aedes albopictus, in Europe by Margaret K. Corley, Luciano Veiga Cosme, Peter A. Armbruster, Nigel Beebe, Anna Bega, Sebastien Boyer, Beniamino Caputo, Chun‐Hong Chen, Jacob E. Crawford, Alessandra dellaTorre, Roger Eritja, Michael C. Fontaine, Richard J. Gill, Trang Huynh, Perparim Kadriaj, Kevin Maringer, Ademir Jesus Martins, Andrew Maynard, Shomen Mukherjee, Leonard E. Munstermann, Verena Pichler, Maria Sharakhova, Sinnathamby Noble Surendran, Sandra Urbanelli, Enkelejda Velo, Isra Wahid, Muhammet Mustafa Akiner, Georgios Balatsos, Gilles Besnard, Maria Louise Borg, Daniel Bravo‐Barriga, Rubén Bueno Marí, Francisco Collantes, Cintia Horvath, Mihaela Kavran, Raquel Medialdea‐Carrera, Tanya Melillo, Antonios Michaelakis, Ognyan Mikov, Arianna Puggioli, Elton Rogozi, Francis Schaffner, Kayleigh Hackett, Thomas Johnson, Tina Wu, João Pinto, Vera Valadas, Adalgisa Caccone

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Anomaly detection using machine learning and adopted digital twin concepts in radio environments by Mohamed Hussien Moharam, Omar Hany, Ahmed Hany, Amenah Mahmoud, Mariam Mohamed, Sohila Saeed

“…To validate the effectiveness of this framework, multiple machine learning algorithms based on traditional classifiers which are compared for their ability to detect anomalies, particularly jamming attacks. …”
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Event-Triggered Adaptive Synchronous Control of Interconnected Microgrids Under Denial-of-Service Attacks by Xiaodan Li, Lei Zhang, Hongbin Liu, Xiaoyu Yi, Xiaochun Liu, Zichen Yi

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Predictive value of the stone-free rate after percutaneous nephrolithotomy based on multiple machine learning models by Zhao Rong Liu, Zhao Rong Liu, Zhan Jiang Yu, Jie Zhou, Jian Biao Huang

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Sepsis-Associated Acute Kidney Disease Incidence, Trajectory, and Outcomes by Hsiu-Yin Chiang, Chih-Chia Liang, Ya-Luan Hsiao, Uyen-Minh Le, Yi-Ching Chang, Pei-Shan Chen, David Ray Chang, I-Wen Ting, Hung-Chieh Yeh, Chin-Chi Kuo

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Neurofibromatosis-Noonan syndrome: a prospective monocentric study of 26 patients and literature review by Didier Bessis, Dominique Vidaud, Pierre Meyer, Laurence Pacot, de La Villeon G, Adeline Alice Bonnard, Yline Capri, Christine Coubes, Fanchon Herman, Didier Lacombe, Nicolas Molinari, Laura Poujade, Agathe Roubertie, Julien Van Gils, Alain Verloes, David Geneviève, Hélène Cavé, Marjolaine Willems

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Bi-LSTM based fault diagnosis scheme having high accuracy for Medium-Voltage Direct Current systems using pre- and post-processing by Jae-Sung Lim, Haesong Cho, Do-Hoon Kwon, Gyu-Sub Lee

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Propensity score methodology for confounding control in health care utilization databases by Elisabetta Patorno, Alessandra Grotta, Rino Bellocco, Sebastian Schneeweiss

“…This article provides an overview of the use of propensity score methodology for pharmacoepidemiologic research with large health care utilization databases, covering recent discussions on covariate selection, the role of automated techniques for addressing unmeasurable confounding via proxies, strategies to maximize clinical equipoise at baseline, and the potential of machine-learning algorithms for optimized propensity score estimation. …”
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