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  1. 3581

    Severity of the present-day climate in the Polar regions of Siberia by E. V. Maksyutova, L. B. Bashalkhanova

    Published 2019-06-01
    “…Together with the space-time dynamics of the actual TA values, important values of TA are its threshold values (more than 30 and more than 45 units) which determine a degree of discomfort. …”
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    Article
  2. 3582

    Social Capital Measurement in Turkiye: Creating an Index by Province by Abdulmuttalip Pilatin, Hasan Ayaydın

    Published 2022-12-01
    “…Since social capital does not change in a short period of time for countries, regions, and cities, the index values for the years between 2007, 2011 and 2018 were created with the linear interpolation method using the data, as applied in similar studies. …”
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    Article
  3. 3583

    Test-retest and intrasession reliability of assisted sprint outcome measurements using a motorized resistance device by Ola Eriksrud, Frederic Westheim

    Published 2025-06-01
    “…Furthermore, most outcome variables were rated as good and ok for SWC. Similar findings were observed for intrasession reliability with very high ICC values for all outcome measurements except maximum acceleration (0.85–0.93) and 0–5 time for session 2–4 (0.88–0.92). …”
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    Article
  4. 3584

    CIRCADIAN BLOOD PRESSURE MONITORING AND ARTERIAL TONE FEATURES IN YOUNG PEOPLE WITH HIGH NORMAL BLOOD PRESSURE by E. L. Snigur, M. E. Statsenko, E. I. Volchansky, A. N. Zhidkikh

    Published 2010-12-01
    “…In participants with normal or decreased arteriolar tone, the values of time index, BP variability, morning surge rate and mean 24 BP were significantly lower. …”
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    Article
  5. 3585

    Optimization of Chromium (VI) Adsorption using Microalgae Biomass (Spirulina sp.) and its Application in Leather Tannery Waste by Nais Pinta Adetya, Uma Fadzilia Arifin, Emiliana Anggriyani, Laili Rachmawati

    Published 2023-12-01
    “…The values of the solution pH, adsorption time, and concentration of the best metal solution were used to determine the center points of the optimization variables through Response Surface Methodology (RSM). …”
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    Article
  6. 3586

    A Calculus of Evolving Objects by M. Dezani-Ciancaglini, P. Giannini, O. Nierstrasz

    Published 2008-12-01
    “…To this end we present an original calculus in which objects can adapt their behaviour at run-time. Both objects and environments are represented by first-class mappings between variables and values. …”
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  7. 3587

    Mathematical Modelling and Optimisation of Low-Temperature Drying on Quality Aspects of Rough Rice by Shakeel Ahmed Soomro, Kunjie Chen, Sohail Ahmed Soomro

    Published 2020-01-01
    “…Response surface methodology (RSM) with a central composite design was employed to study the effects of variables, i.e., temperature (X1), time (X2), and air velocity (X3) on responses, i.e., head rice yield (HRY), hardness, lightness, and cooking time. …”
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    Article
  8. 3588

    Operational Semantics of Annotated Reflex Programs by Igor S. Anureev

    Published 2019-12-01
    “…It stores a complete history of changes of the values of shared variables for a more precise description of the time properties of the program and its environment. …”
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    Article
  9. 3589

    Economic Impacts of Disasters and Economic Events on Commercial Fishery—The Case of Mississippi Blue Crabs by Benedict C. Posadas

    Published 2025-01-01
    “…The estimated marine economic recovery model explained 93 percent of the variations in real dockside values. Two independent variables are statistically significant, including blue crab landings and time. …”
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    Article
  10. 3590

    Detecting the Spatiotemporal Relationship of Vegetation Changes with Climatic Elements in Mazandaran Province by Mohadeseh Ghanbari Motlagh, Behzad Amraei

    Published 2020-08-01
    “…One of the most important of these indices is EVI, which has a high sensitivity to structural variables of vegetation. On the basis, data from the MODIS satellite data and products by making time series of EVI were applied in the current study to determine the dynamics of this index relative to two main climate variables (land surface temperature and rainfall) over a period of time. 2-Materials and Methods In this study, spatiotemporal analysis of GIS was used to model the relationship between vegetation dynamics based on EVI from MODIS satellite. …”
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    Article
  11. 3591

    Temporal analysis of Phoma leaf spot of coffee plants at different altitudes by Humberson Rocha Silva, Edson Ampélio Pozza, Aurivan Soares de Freitas, Marcelo Loran de Oliveira Freitas, Mauro Peraro Barbosa Junior, Marcelo Angelo Cirillo

    Published 2025-04-01
    “…ABSTRACT Phoma leaf spot (Phoma spp.) of coffee causes losses of between 15 and 43%, and presents significant variability over time and space, especially in mountain coffee production. …”
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    Article
  12. 3592

    Integrated Machine Learning Models for Bakery Product Defect Prediction by Nataliia Zaiets, Nataliia Lutska, Lidiia Vlasenko

    Published 2025-04-01
    “…The article also proposes different methods for adjusting the values of control variables based on historical data. …”
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  13. 3593

    Lower Extremity Kinematic Waveform Analysis During a Single Leg Drop Task – Including a Single Subject Design by Nickolai JP Martonick, Youngmin Chun, Lukas Krumpl, Joshua P Bailey

    Published 2022-12-01
    “…Six out of the nine participants had bilateral differences for all six kinematic time-series. # CONCLUSIONS The lack of significant differences at the group level may have been masked by movement variability amongst participants. …”
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  14. 3594

    Intransitive Temporal Multi-agent Logic with Agents’ Multi-valuations. Decidability by K. V. Grekovich, V.V. Rybakov, V.V. Rimatskiy

    Published 2025-03-01
    “…This logic is defined in a semantic way, as a set of formulas, which are true at linear models with multi-valued variables by agents’ and clusters of states. …”
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    Article
  15. 3595

    A Stochastic Model for Adsorption Kinetics by Silvia Rodríguez-Narciso, Juan Antonio Lozano-Álvarez, Rogelio Salinas-Gutiérrez, Netzahualcóyotl Castañeda-Leyva

    Published 2021-01-01
    “…These ranges indicate the flexibility of the stochastic model to obtain fractional n values, resulting in high R2 values. The variability in each system was evaluated based on σ2. …”
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  16. 3596

    Notes on Recent Achievements in Proving Stability using KeYmaeraX by Thomas Baar, Horst Schulte

    Published 2021-12-01
    “…While the plant is basically an aggregation of continuous variables whose values change over time accordingly to physical laws, the controller can be seen as an algorithm formulated in a classical programming language. …”
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    Article
  17. 3597

    Assessment of test-retest reproducibility by [18F]Bavarostat for PET imaging of HDAC6 by Mika Naganawa, Ming-Qiang Zheng, Jean-Dominique Gallezot, Robin Bonomi, Jiwei Gu, Hong Gao, Swanee Jacutin-Porte, Nabeel B. Nabulsi, Michel Koole, Koen Van Laere, David Matuskey, Yiyun Huang, Richard E. Carson

    Published 2025-06-01
    “…Conclusions The test-retest variability of [18F]Bavarostat V T values demonstrated favorable results for a one-month scan interval, comparable to the reported values.…”
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  18. 3598

    Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

    Published 2025-04-01
    “…Traditional methods for predicting pavement performance rely on complex finite element modelling and empirical equations, which are computationally expensive and time-consuming. However, machine learning models offer a time-efficient solution for predicting pavement performance. …”
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  19. 3599

    PENDEKATAN SISTEM 2D MODEL STREETER-PHELPS UNTUK MODEL POLUSI SUNGAI by RUDY WOLTER MATAKUPAN

    Published 2011-03-01
    “…Applications to positive 2D system can follow Steeter-Phelps model to river flow model. by modifying the discrete values. mathematical model structure provided by the river flow at time step t is proportional to the length of rivers and water velocity. …”
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  20. 3600

    APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

    Published 2025-04-01
    “…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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    Article