Cartographie interactive et multimédia : vers une aide à la réflexion géographique by Jean-Philippe Antoni, Olivier Klein, Stéphane Moisy

“…They mainly rely on Geographic Information Systems (GIS) and on the experience of Eploratory Data Analysis (EDA). The main characteristics of this multimedia and interactive cartography can be structured in a synthetic figure. …”
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Examining interaction effects among land-use policies to reduce household vehicle travel: An exploratory analysis by Kwangyul Choi, Robert Paterson

“…In this study, we explore how three well-known land-use strategies (densification, mixed-use development, and street network improvement) interact with each other by testing possible combinations of land-use factors and focus on how these interactive effects vary by the level of development intensity. …”
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Spatial self-selection in land-use–travel behavior interactions: accounting simultaneously for attitudes and socioeconomic characteristics by João de Abreu e Silva

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Factors associated with drug–drug interactions involving citalopram in the UK Biobank by Benjamin Laplace, Win Lee Edwin Wong, Marco Menchetti, Diana De Ronchi, Paolo Fusar-Poli, Giuseppe Fanelli, MNESYS – Mood and Psychosis Sub-Project (Spoke 5), Alessandro Serretti, Cathryn M. Lewis, Chiara Fabbri

“…Results In UK Biobank primary care data, 25 508 participants received citalopram prescription(s), among which 11 941 (46.8%) had at least one DDI, with an average of 1.96 interacting drugs. …”
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Towards interactive AI-authoring with prototypical few-shot classifiers in histopathology by Petr Kuritcyn, Rosalie Kletzander, Sophia Eisenberg, Thomas Wittenberg, Volker Bruns, Katja Evert, Felix Keil, Paul K. Ziegler, Katrin Bankov, Peter Wild, Markus Eckstein, Arndt Hartmann, Carol I. Geppert, Michaela Benz

“…The models achieved classification performance of around 90% on a multiscanner and multicenter database, which is on par with the accuracy achieved on the primary single-center single-scanner data. Various convolutional neural network (CNN) architectures can be used for feature extraction in the few-shot model. …”
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Catch Data Can Unravel Elasmobranch Aggregation Dynamics and Group Behaviours by A. G. McInturf, M. Cantor, I. A. Bouyoucos, T. K. Chapple, S. F. Debaere, K. Eustache, J. Mourier, S. Planes, J. A. Sulikowski, K. W. Zillig, N. A. Fangue, J. L. Rummer

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Prevalence of OATP1B‐Mediated Drug–Drug Interactions in an Academic Medical Center by Mathilde Bories, David Malnoë, Pascal Le Corre

“…This retrospective study aimed to determine the prevalence of potential drug–drug interactions (pDDIs) mediated by the hepatic transporter OATP1B1/3 in a cohort of 44,877 patients hospitalized at Rennes Academic Medical Center, using data from the Clinical Data Warehouse. …”
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The use of emerging autonomous technologies for ocean monitoring: insights and legal challenges by Aspasia Pastra, Tafsir Matin Johansson, Joana Soares, Frank E. Muller-Karger

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Land use–transport interaction modeling: A review of the literature and future research directions by Ransford Antwi Acheampong, Elisabete Silva

“…The aim of this review paper is to provide comprehensive and up-to-date material for both researchers and practitioners interested in land-use-transport interaction (LUTI) modeling. The paper brings together some 60 years of published research on the subject. …”
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Interaction between opium use and cigarette smoking on bladder cancer: An inverse probability weighting approach based on a multicenter case-control study in Iran by Rahim Akrami, Maryam Hadji, Hamideh Rashidian, Maryam Nazemipour, Ahmad Naghibzadeh-Tahami, Alireza Ansari-Moghaddam, Kazem Zendehdel, Mohammad Ali Mansournia

“…Recently, the International Agency for Research on Cancer (IARC) classified opium as a Group 1 carcinogen in 2020. Method: Using data from a multicenter case-control study in Iran called IROPICAN, involving 717 cases of bladder cancer and 3477 controls, we assessed the interactions on the causal additive scale between opium use and cigarette smoking and their attributing effects to evaluate public health relevance and test for different mechanistic interaction forms to provide new insights for developing of bladder cancer. …”
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MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models by Feng Wang, Jinming Chu, Liyan Shen, Shan Chang

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Discovering customer segments through interaction behaviors for home appliance business by Youngjung Suh

“…Here, we applied two data mining algorithms, clustering and NMF (Non-negative Matrix Factorization), based on the data of 40,911 actual customers in the home appliance business using the designed multidimensional behavioral characteristic variables. …”
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Differences in characteristics and interactions with close contacts among PWID in the San Diego Border Region before and during the COVID-19 pandemic by Lara K Marquez, Natasha K Martin, Steffanie A Strathdee, Britt Skaathun

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Effect modification and interaction between ethnicity and socioeconomic factors in severe COVID-19: analyses of linked national data for Scotland by Aziz Sheikh, Alastair H Leyland, Chris Robertson, Srinivasa Vittal Katikireddi, Colin R Simpson, Anna Pearce, Evangelia Demou, Colin McCowan, Lewis Ritchie, Eliud Kibuchi, Ronan McCabe, Sarah Amele, Patricia Irizar, Karen Jeffrey, Igor Ruden

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Flight Trajectory Prediction Based on Automatic Dependent Surveillance-Broadcast Data Fusion with Interacting Multiple Model and Informer Framework by Fan Li, Xuezhi Xu, Rihan Wang, Mingyuan Ma, Zijing Dong

“…The experiments are conducted using real flight surveillance data received from automatic dependent surveillance-broadcast (ADS-B) sensors to validate the effectiveness of the proposed method. …”
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Interactions between vitamin D deficiency and inflammation on diabetes risk: data from 336,500 UK Biobank adults by Jatupol Kositsawat, Shangshu Zhao, George A. Kuchel, Lisa C. Barry, Richard H. Fortinsky, Ben Kirk, Gustavo Duque, Chia-Ling Kuo

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Classifying horse activities with big data using machine learning by Derya Birant, Emircan Tepe

“… Using big data-assisted machine learning methods in animal science has received increasing attention in recent years since they extract useful insights from large-scale animal datasets. …”
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The interaction between land‐use change and fire regimes, directly and indirectly, affects the urban avian assemblages of Darwin, Australia by Sarah Fischer, Andrew C. Edwards, Stephen T. Garnett, Timothy G. Whiteside, Patrice Weber

“…By compiling two sets of spatial data, land‐use change, and fire history mapping, we were able to investigate their interaction and impact on the avian assemblages in the Darwin urban area. …”
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Coincidence and Complexity: Complex Interaction of Society, Environment, and Conjuncture in the Eastern Roman World ca. 500–1100 CE by John Haldon

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Using Weather Data for Improved Analysis of Vehicle Energy Efficiency by Reno Filla

“…It is known that weather has a significant impact, yet there is a lack of literature showing how the wealth of openly available data from professional weather observations can be used in this context. …”
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