Article
Physics, Fluids & Plasmas
Tom Ichibha, Verena A. Neufeld, Kenta Hongo, Ryo Maezono, Alex J. W. Thom
Summary: This study evaluates the performance of three methods on energy time series from three QMC methods and describes a hybrid analysis method to provide reliable error estimates, as well as determining the start point estimation method.
Article
Biodiversity Conservation
Lluis Socias-Martinez, Louise R. Peckre, Michael J. Noonan
Summary: Modern home-range estimation relies on expensive radio- or GPS-tracking data, but trap-derived data can also yield accurate estimates of home-range size. In this study, we evaluated the performance of five home-range estimators using simulated data and found that the number of observations and the proportion of the home range within the trapping grid were the most important predictors of accuracy and precision. The use of asymptotic models and distance ordering improved the accuracy and consistency of estimates. These findings were supported by case studies using empirical data from white-tailed deer and jaguars. The results indicate that trapping data can lower the economic costs of home-range analysis and expand the scope of ecology and conservation research.
Article
Computer Science, Information Systems
Rongrong Liu, Birgitta Dresp-Langley
Summary: The study utilizes expert grip force data to investigate the surgical operations in robot-assisted minimally invasive endoscopic surgery, finding that individual grip force is influenced by task specificity. Two data analysis strategies are employed to explore this phenomenon.
Article
Biology
P. A. T. R. I. C. K. B. FINNERTY, C. L. A. R. E. MCARTHUR, P. E. T. E. R. BANKS, C. A. T. H. E. R. I. N. E. PRICE, A. D. R. I. A. N. M. SHRADER
Summary: Odor plays a crucial role in terrestrial ecosystems, as animals use it to gather information and make decisions about movement. The concept of an olfactory landscape helps us understand how animals move in space and time, and how ecological interactions can be altered.
Article
Biology
Melissa Pardi, Larisa R. G. DeSantis
Summary: This synthesis explores the isotopic ecology of North American mammalian herbivores since approximately 7 Ma, revealing that hypsodont taxa often have broader diets that include more browse consumption. The study demonstrates that even generalist taxa may have narrow localized dietary breadth, and that 'grazing-adapted' taxa exhibit dietary flexibility across space and time, potentially reducing competition among ancient herbivores.
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2021)
Article
Environmental Sciences
Lela S. Schlenker, Robin Faillettaz, John D. Stieglitz, Chi Hin Lam, Ronald H. Hoenig, Georgina K. Cox, Rachael M. Heuer, Christina Pasparakis, Daniel D. Benetti, Claire B. Paris, Martin Grosell
Summary: Identifying complex behaviors such as spawning and fine-scale activity in highly migratory fish species is challenging, but essential for fisheries management in a warming ocean. Using remotely transmitted acceleration data, researchers were able to predict spawning events and discovered drivers of high activity in mahi-mahi, showing that this information can be extracted from PSATs to study reproductive behavior and population connectivity in highly migratory fishes. This study highlights the necessity of unveiling fine-scale activity patterns to understand the ecology of highly mobile species.
FRONTIERS IN MARINE SCIENCE
(2021)
Article
Astronomy & Astrophysics
Will J. Percival, Oliver Friedrich, Elena Sellentin, Alan Heavens
Summary: Observational astrophysics involves making inferences about the Universe through data and model comparisons. Credible intervals for model parameters are as important as maximum a posteriori probability values, and intermediate statistics are used to fit models to data. The likelihood for these statistics is usually assumed to have a multivariate Gaussian form and the covariance matrix is estimated from simulations. We introduce a prior that matches the covariance of the posterior to the distribution of true values around the maximum likelihood values, offering a consistent and conservative approach for credible intervals.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Information Science & Library Science
Francesco Caputo, Barbara Keller, Michael Moehring, Luca Carrubbo, Rainer Schmidt
Summary: This paper aims to codify the main phases and challenges of approaching and managing big data analytics in companies' decision-making processes through case studies. It provides a possible depiction of the development stages and challenges of big data analytics and its impact on decision-making processes.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2023)
Article
Environmental Sciences
Eun-Young Lee, Kyung-Ae Park
Summary: Extreme value analysis (EVA) using satellite-observed sea surface temperature (SST) data was used to understand and predict long-term return extreme values in the East/Japan Sea (EJS). The peaks-over-threshold (POT) method showed better performance in deriving SST extremes. The calculated 100-year-return SST values were higher than the average value of satellite-observed SSTs over the past decades. The distribution of the SST extremes followed the known seasonal variation, but with enhanced extreme SSTs in early summer and late autumn. Comparison with climate model simulation results showed a slightly smaller extreme SST with a negative bias. This study highlights the potential of the POT method in understanding future oceanic warming based on satellite observed SSTs.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Green & Sustainable Science & Technology
Jonathan Gumz, Diego Castro Fettermann, Enzo Morosini Frazzon, Mirko Kueck
Summary: Industry 4.0 and its technologies have significant implications for advancements in communication, production, and management efficiency. This study focuses on using smart meter data and household features data to identify the most appropriate methods for predicting energy consumption. Through the application of the CRISP-DM method, Python Platform, and multiple prediction methods, experiments were conducted using data from over 470 smart meters over a three-year period. Support vector machines, random forest regression, and neural networks were found to be the most effective prediction methods. The results have important implications for utilities in offering improved contracts to new households and managing their smart grid infrastructure based on forecasted demand.
Review
Rheumatology
Yu-Hui H. Chang, Matthew R. Buras, John M. Davis III, Cynthia S. Crowson
Summary: Rheumatology research often involves correlated and clustered data. Treating these data as independent observations can lead to incorrect statistical inference. In this study, data from 633 rheumatoid arthritis patients were analyzed using generalized linear models, while adjusting for factors such as rheumatoid factor positivity and sex, as well as considering additional correlation using generalized linear mixed models and generalized estimating equations. The study found that when correlation was accounted for, standard errors increased, resulting in overestimated effect size, narrower confidence intervals, increased type I error, and potentially misleading results.
JOURNAL OF RHEUMATOLOGY
(2023)
Article
Medicine, Legal
Charity A. Holland, Jennifer A. McElhoe, Sidney Gaston-Sanchez, Mitchell M. Holland
Summary: Massively parallel sequencing of mitochondrial DNA can help practitioners fully resolve heteroplasmic sites, especially in forensic DNA analysis. Damage and heteroplasmy can manifest similarly in DNA mixtures, highlighting the importance of differentiating between the two conditions. Controlled experiments involving DNA damage were conducted to evaluate the impact on samples with different template concentrations, aiming to improve mtDNA analysis for low template samples. Damage caused a decrease in mtDNA yield and lower quality sequencing results, especially in samples diluted prior to damage induction, indicating the susceptibility of low template samples to damage. This study's findings will aid forensic laboratories in distinguishing between damage and heteroplasmy, crucial for setting robust mtDNA interpretation guidelines.
INTERNATIONAL JOURNAL OF LEGAL MEDICINE
(2021)
Article
Astronomy & Astrophysics
Virginia Cuomo, Victor P. Debattista, Sarah Racz, Stuart Robert Anderson, Peter Erwin, Oscar A. Gonzalez, J. W. Powell, Enrico Maria Corsini, Lorenzo Morelli, Mark A. Norris
Summary: The short-lived buckling instability is responsible for the formation of some box/peanut (B/P) shaped bulges in barred galaxies, while other B/P bulges form through resonant trapping of stars. The difference lies in the symmetry breaking during buckling, which creates residual mid-plane asymmetry. Simulations and diagnostic tests on galaxies indicate that B/P bulges formed through strong buckling are rare in the past 5 billion years. Mid-plane asymmetry is not observed in galaxies with B/P bulges, suggesting either resonant trapping or buckling events more than 5 Gyr ago as the formation mechanisms.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2023)
Article
Psychology, Mathematical
Maud Beeckmans, Pieter Huycke, Tom Verguts, Pieter Verbeke
Summary: The standard approach of carrying out a goodness-of-recovery study to determine the amount of data needed for useful parameter estimations from a computational model may not always be optimal. This paper proposes a novel approach using a generalized concept of statistical power and a Python-based toolbox to determine the required data size for parameter estimates. Simulations indicate that a high number of trials per person is necessary for high-powered studies in a specific computational model.
BEHAVIOR RESEARCH METHODS
(2023)
Article
Ecology
Rhys Munden, Luca Borger, Rory P. Wilson, James Redcliffe, Rowan Brown, Mathieu Garel, Jonathan R. Potts
Summary: Step selection analysis is a fundamental technique for uncovering the drivers of animal movement decisions. By using high-frequency data and a new method called time-varying iSSA, researchers can better understand and analyze animal movement patterns, leading to more behaviorally-meaningful conclusions. This method allows for more accurate insights into animal decision-making processes and can infer covariates dependent on the time between turns, which was not possible with previous techniques.
METHODS IN ECOLOGY AND EVOLUTION
(2021)