Analysis of the Causes of Urban Sprawl in Iran by keramatollah Ziari, Saeed Zanganeh Shahraki, Negin Rajabzadeh, Mohsen Abbas Nejad Jelogir

“…Experts suggest that urban sprawl in the United States and Western Europe can be understood through 3 historical stages: 1) urban sprawl under the Keynesian-Fordist model of urbanization (1945-1975), 2) the period of urban reconstruction and intensive city redevelopment (1975-1985), and 3) the emergence of a neoliberal and globalized urban model (from 1985 onward) (Bueno-Suárez et al., 2020, pp. 5-9). …”
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Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC by Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf, ALMA Comprehensive High-resolution Extragalactic Molecular Inventory (ALCHEMI) collaboration

“…We combine the neural network with radiative transfer modeling to generate modeled integrated intensities, which we compare to measurements of HCN and HNC from the ALMA Large Program ALCHEMI. …”
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Biogeochemical functioning of Lake Alaotra (Madagascar): a reset of aquatic carbon sources along the land–ocean aquatic continuum by V. F. Razanamahandry, A. V. Borges, L. Brosens, C. Morana, T. Razafimbelo, T. Rafolisy, G. Govers, S. Bouillon

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Hydrological Variability in the Arid Region of Northwest China from 2002 to 2013 by Yanping Cao, Zhuotong Nan, Guodong Cheng, Ling Zhang

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Feasibility of estimating the percentage of desert pavement using Tasseled Cap Transformation indices extracted from Landsat 8 images by farzaneh Fotouhi Firoozabad, Atefeh jebali

“…The obtained model can predict approximately 61% of surface pavement changes in the study area. …”
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Triple oxygen isotope composition of CO₂ in the upper troposphere and stratosphere by G. A. Adnew, G. A. Adnew, G. Koren, N. Mehendale, N. Mehendale, S. Gromov, M. Krol, M. Krol, T. Röckmann

“…StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) conducted intensive campaigns with the high-altitude aircraft M55 <i>Geophysica</i> during the Asian summer monsoon anticyclone (ASMA), providing air samples from altitudes up to 21 km.…”
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Visual Automatic Localization Method Based on Multi-level Video Transformer by Qiping ZOU, Botao LI, Saian CHEN, Xi GUO, Taohong ZHANG

“…After multiple iterations through the MLEs, these tokens are fed into a Multi-Layer Perceptron for final classification predictions, focusing on semantic-level video classification. …”
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Travel in Omani Maqamat Writings: A Textual Semiotic Study [In Arabic] by Saeed Al-Salti

“…Greimas' structural theory can be examined through the actantial model, binary oppositions, and the syntactic model (Contractual, Performative, and Disjunctive sequences) .Travel in the Maqamat represents a structural foundation where the narrator is fundamentally in search of the hero through travel. …”
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A New Rarity Assessment of the “Disk of Satellites”: The Milky Way System Is the Exception Rather Than the Rule in the ΛCDM Cosmology by Chanoul Seo, Suk-Jin Yoon, Sanjaya Paudel, Sung-Ho An, Jun-Sung Moon

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Exploring the effect of multi-modal intervention against cognitive decline on atrophy and small vessel disease imaging markers in the AgeWell.de imaging study by Frauke Beyer, Lukas Kleine, Andrea Zülke, Melanie Luppa, Toralf Mildner, Jochen Gensichen, Thomas Frese, David Czock, Birgitt Wiese, Hans-Helmut König, Hanna Kaduszkiewicz, Wolfgang Hoffmann, Jochen René Thyrian, Arno Villringer, Steffi Riedel-Heller, A.Veronica Witte

“…Preliminary evidence suggested an association of the intervention, increased cerebral blood flow and systolic blood pressure reductions.Abbreviations: ECT, entorhinal cortex thickness; FW, free water fraction; WHO, world health organization; AD, Alzheimer’s disease; VCI, vascular cognitive impairment; FINGER, Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability; MTL, medial temporal lobe; MIND, Mediterranean-DASH Intervention for Neurodegenerative Delay diet; cSVD, cerebral small vessel disease; WMH, white matter hyperintensities of presumed vascular origin; PSMD, peak width of the mean diffusivity distribution; WW-FINGERS, world wide FINGER studies; CAIDE, Cardiovascular Risk Factors, Aging, and Incidence of Dementia; GPP, general practitioner praxis; MRI, magnetic resonance imaging; MST, Mnemonic Similarity Test; TE, echo time; TR, repetition time; FA, flip angle; FOV, field of view; GRAPPA, GeneRalized Autocalibrating Partial Parallel Acquisition; CMRR, Center for Magnetic Resonance Research; BOLD, blood oxygenation level dependent; pcASL: pseudo-continuous arterial spin labeling; EPI, echo-planar imaging; FLAIR, fluid attenuated inversion recovery; CBF, cerebral blood flow; QA, quality assessment; GM, gray matter; HCV, hippocampal volume; eICV, estimated intracranial volume; DWI, diffusion-weighted imaging; MD, mean diffusivity; FA, fractional anisotropy
TBSS: tract-based spatial statistics; CSF, cerebral spinal fluid; ISI, inter-stimulus interval; LDI, lure discrimination index; REC, recognition score; CG, control group; IG, intervention group; MoCA, Montreal Cognitive Assessment; CASMIN, Comparative Analysis of Social Mobility in Industrial Nations; BMI, body mass index; SBP/DBP, systolic/diastolic blood pressure; OSF, open science framework; LMM, linear mixed model; ANOVA, analysis of covariance.…”
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A Demonstration of Interstellar Navigation Using New Horizons by Tod R. Lauer, David H. Munro, John R. Spencer, Marc W. Buie, Edward L. Gomez, Gregory S. Hennessy, Todd J. Henry, George H. Kaplan, John F. Kielkopf, Brian H. May, Joel W. Parker, Simon B. Porter, Eliot Halley Vrijmoet, Harold A. Weaver, Pontus Brandt, Kelsi N. Singer, S. Alan Stern, Anne. J. Verbiscer, Pedro Acosta, Nicolás Ariel Arias, Sergio Babino, Gustavo Enrique Ballan, Víctor Ángel Buso, Steven J. Conard, Daniel Das Airas, Giorgio Di Scala, César Fornari, Jossiel Fraire, Brian Nicolás Gerard, Federico González, Gerardo Goytea, Emilio Mora Guzmán, William Hanna, William C. Keel, Aldo Kleiman, Anselmo López, Jorge Gerardo Machuca, Leonardo Málaga, Claudio Martínez, Denis Martinez, Raúl Meliá, Marcelo Monópoli, Marc A. Murison, Leandro Emiliano Fernandez Pohle, Mariano Ribas, José Luis Ramón Sánchez, Sergio Scauso, Dirk Terrell, Thomas Traub, Pedro Oscar Valenti, Ángel Valenzuela, Ted von Hippel, Wen Ping Chen, Dennis Zambelis

“…These measurements are not of research grade, but directly seeing large stellar parallaxes between two widely separated simultaneous observers is vividly educational. Using the New Horizons positions of the two stars alone, referenced to the three-dimensional model (3D) of the solar neighborhood constructed from Gaia DR3 astrometry, further provides the spacecraft spatial position relative to nearby stars with 0.44 au accuracy. …”
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Recurrent neural networks for anomaly detection in magnet power supplies of particle accelerators by Ihar Lobach, Michael Borland

“…We demonstrate that the RNN outperforms a reasonably complex physics-based model at predicting the PS temperatures and at anomaly detection. …”
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Tree Species Classification at the Pixel Level Using Deep Learning and Multispectral Time Series in an Imbalanced Context by Florian Mouret, David Morin, Milena Planells, Cécile Vincent-Barbaroux

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Thermal Avalanches Drive Logarithmic Creep in Disordered Media by Daniel J. Korchinski, Dor Shohat, Yoav Lahini, Matthieu Wyart

“…We show that these predictions hold both in numerical models of amorphous solids, as well as in experiments with thin crumpled sheets. …”
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Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium by Christopher J. M. Lawley, Marcus Haynes, Bijal Chudasama, Kathryn Goodenough, Toni Eerola, Artem Golev, Steven E. Zhang, Junhyeok Park, Eleonore Lèbre

“…., conservation, biodiversity, freshwater, energy, waste, land use, human development, health and safety, and governance) and a global dataset of news events to train and validate three models for predicting “conflict” events (e.g., disputes, protests, violence) that can negatively impact CRM supply chains: (1) a knowledge-driven fuzzy logic model that yields an area under the curve (AUC) for the receiver operating characteristics plot of 0.72 for the entire model; (2) a naïve Bayes model that yields an AUC of 0.81 for the test set; and (3) a deep learning model comprising stacked autoencoders and a feed-forward artificial neural network that yields an AUC of 0.91 for the test set. …”
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LAGOS-US LANDSAT: Remotely sensed water quality estimates for U.S. lakes over 4 ha from 1984 to 2020 by Patrick J. Hanly, Katherine E. Webster, Patricia A. Soranno

“…Two random forest models were fit for each variable: Holdout-data (75/25 spatially representative train-test split) and Full-data (trained on all data). …”
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Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie by Qianqian Liu, Mark D. Rowe, Richard P. Stumpf, Reagan Errera, Casey Godwin, Justin D. Chaffin, Eric J. Anderson, Tongyao Pu

“…We improved an approach to predict the spatially and temporally resolved probability of microcystins (MCs) exceeding a threshold level (6 μg L−1) in western Lake Erie. …”
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Evaluation of potential productivity in coniferous forests by integrating field data and aerial laser scanning in Hidalgo, México by Rodrigo Ramos-Madrigal, Héctor M. de los Santos-Posadas, José René Valdez-Lazalde, Efraín Velasco-Bautista, Gregorio Ángeles-Pérez, Alma Delia Ortiz-Reyes

“…The Hossfeld IV anamorphic model adjusted as MEM and autocorrelation corrected model showed the best performance for predicting DH growth with R2adj of 0.87 and RMSE of 2.11 m. …”
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Brief communication: Monitoring snow depth using small, cheap, and easy-to-deploy snow–ground interface temperature sensors by C. L. Bachand, C. L. Bachand, C. Wang, B. Dafflon, L. N. Thomas, L. N. Thomas, I. Shirley, S. Maebius, S. Maebius, C. M. Iversen, K. E. Bennett

“…We trained a random forest machine learning model to predict snow depth from variability in snow–ground interface temperature. …”
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Characterization of Crystal Properties and Defects in CdZnTe Radiation Detectors by Manuel Ballester, Jaromir Kaspar, Francesc Massanés, Srutarshi Banerjee, Alexander Hans Vija, Aggelos K. Katsaggelos

“…This characterization allows us to mitigate and compensate for the undesired effects caused by crystal impurities. We tested our model with computer-generated noise-free input data, where it showed excellent accuracy, achieving an average RMSE of 0.43% between the predicted and the ground truth crystal properties. …”
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