Identifying cell types from spatially referenced single-cell expression datasets. by Jean-Baptiste Pettit, Raju Tomer, Kaia Achim, Sylvia Richardson, Lamiae Azizi, John Marioni

“…After generating such data one of the key goals is to cluster the cells into groups that correspond to both known and putatively novel cell types. Whilst many clustering algorithms exist, they are typically unable to incorporate information about the spatial dependence between cells within the tissue under study. …”
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Short-term inbound rail transit passenger flow prediction based on BILSTM model and influence factor analysis by Qianru Qi, Rongjun Cheng, Hongxia Ge

“…The proposed model is compared with many current mainstream deep learning algorithms, the effectiveness of the BILSTM model considering influencing factors is validated. …”
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Assessment and simulation of eco-environmental quality changes in rapid rural urbanization: Xiong’an New Area, China by Zhongli Lin, Hanqiu Xu, Xiong Yao, Zhipeng Zhu

“…However, research that combines RSEI with machine learning algorithms to conduct multi-scenario simulation of EEQ is still relatively scarce. …”
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Application of blade element momentum theory with guaranteed convergence to analyze a straight-blade horizontal axis wind turbine by Dang Huy Le, The Bao Nguyen, Van Minh Ngo

“…This theory has been improved many times to address its inherent weakness of convergence capability. …”
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Posttraumatic epilepsy: clinical, diagnostic and therapeutic features by N. E. Maslov, A. A. Litvinova, P. S. Kovalev, N. N. Maslova, N. V. Yuryeva, E. I. Khamtsova

“…It has been proved that no clear algorithms for PTE diagnostics and treatment are currently available, which often leads to insufficient patient care.…”
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Quantifying and optimizing single-molecule switching nanoscopy at high speeds. by Yu Lin, Jane J Long, Fang Huang, Whitney C Duim, Stefanie Kirschbaum, Yongdeng Zhang, Lena K Schroeder, Aleksander A Rebane, Mary Grace M Velasco, Alejandro Virrueta, Daniel W Moonan, Junyi Jiao, Sandy Y Hernandez, Yongli Zhang, Joerg Bewersdorf

“…The spatial and temporal resolution depends on many factors, among which laser intensity and camera speed are the two most critical parameters. …”
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PERFORMANCE EVALUATION OF LIGHTWEIGHT OBJECT DETECTION MODELS FOR REAL-TIME PERSONAL PROTECTIVE EQUIPMENT DETECTION IN THE CONSTRUCTION SITES by Herman, Sandy Alferro Dion, Andik Yulianto

“…Using lightweight machine learning algorithms, object recognition can help to detect if the PPEs are worn correctly. …”
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An optimized deterministic concurrency control approach for geo-distributed transaction processing on permissioned blockchains by Zhibo Han, Zeshun Peng, Gang Wang, Minghe Yu, Xiaohua Li, Yanfeng Zhang, Ge Yu

“…Traditional concurrency control algorithms, such as locking-based protocols, usually suffer from performance degradation due to heavy transaction coordination overheads. …”
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MASSIVE: A scalable framework for agent-based scheduling of micro-grids using market mechanisms by Jakob M. Fritz, Lea Riebesel, André Xhonneux, Dirk Müller

“…This market-mechanism allows to coordinate many individual agents with only few restrictions by using pricing mechanisms. …”
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Decentralized Coordination of Temperature Control in Multiarea Premises by Maria Yukhymchuk, Volodymyr Dubovoi, Viacheslav Kovtun

“…In particular, there are many multiarea premises with conflicting requirements for the comfort of habitats. …”
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LCD: IDENTIFYING INFLUENTIAL NODES IN COMPLEX NETWORKS WITH LAYERED CLUSTERING AND DEGREE by Abdulhakeem Othman Mohammed

“… Identifying influential nodes in networks is a key challenge in understanding how information spreads. While numerous algorithms have been proposed in the literature, many struggle with either limited spreading efficiency or high computational complexity. …”
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A multi-factor integration-based semi-supervised learning for address resolution protocol attack detection in SDIIoT by Zhong Li, Huimin Zhuang

“…Recently, the idea of applying the software-defined networking paradigm to industrial Internet of things is proposed by many scholars since this paradigm has the advantages of flexible deployment of intelligent algorithms and global coordination capabilities. …”
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IMMUNOPATHOGENESIS OF MYASTHENIA GRAVIS (REVIEW) by E. D. Gasymly

“…High clinical heterogeneity of autoimmune myasthenia, initiating the flow, increases the urgency of studying its pathogenesis, searching for specific methods of marker diagnostics, developing algorithms for predicting the features of the development of the disease. …”
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Deep Insights into AI perception in Croatia by Robert Kopal, Darija Korkut, Krešimir Žnidar

“…The risks it can impose in terms of biased and untransparent algorithms, privacy violation concerns, cybersecurity issues, disinformation and deep fakes creation and dissemination, to name just a few. …”
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ESTIMATION OF SATELLITE ALTIMETER ECHO-SIGNAL PARAMETERS BY STATISTICAL FITTING METHODS IN THE COURSE OF RETRACKING by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…The data they provide are used in solving various fundamental and applied problems of geophysics, oceanography, meteorology, etc. In many modern measuring systems the altimeter data is processed in several stages. …”
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Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics. by Lisa M Breckels, Sean B Holden, David Wojnar, Claire M Mulvey, Andy Christoforou, Arnoud Groen, Matthew W B Trotter, Oliver Kohlbacher, Kathryn S Lilley, Laurent Gatto

“…We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. …”
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Computational analysis and experimental validation of gene predictions in Toxoplasma gondii. by Joseph M Dybas, Carlos J Madrid-Aliste, Fa-Yun Che, Edward Nieves, Dmitry Rykunov, Ruth Hogue Angeletti, Louis M Weiss, Kami Kim, Andras Fiser

“…Commonly used gene prediction algorithms produce very disparate sets of protein sequences, with pairwise overlaps ranging from 1.4% to 12%. …”
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Advancements in Machine Learning (ML): Transforming the Future of Blood Cancer Detection and Outcome Prediction by Wiebke Rösler, Michael Roiss, Corinne Widmer

“…Recent studies demonstrate that ML algorithms can rapidly predict hematologic malignancies and patient outcomes, matching or exceeding the accuracy of experienced hematologists. …”
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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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Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…For some signal types, it can already yield improved efficiency and robustness, though in many other areas traditional methods remain dominant. …”
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