Spatiotemporal risk avoidance varies seasonally, relative to risk intensity, in a reestablishing predator–prey system by Cara J. Thompson, Nicole M. Tatman, Zachary J. Farley, Scott T. Boyle, Scott T. Boyle, Allison R. Greenleaf, James W. Cain

“…Risk metrics included predicted wolf presence, habitat openness, and predicted risky places modeled from attributes of locations where wolves killed elk. …”
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Environmental Gradients in Lizard Colouration by Lekshmi B. Sreelatha, Pedro Tarroso, Ossi Nokelainen, Zbyszek Boratyński, Miguel Angel Carretero

“…We studied direct and indirect (mediated by body mass) relationships between environmental variables and the lightness of lizards, by piecewise structural equation modelling. We simultaneously tested predictions from Gloger's (darker colouration in warm and humid environments), thermal melanism (darker colouration in colder environments), photoprotection (darker colouration in areas with higher intensity of solar radiation) and Bergmann's (larger body size in colder environments) hypotheses. …”
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Ventilation of the Bay of Bengal oxygen minimum zone by the Southwest Monsoon Current by P. M. F. Sheehan, B. G. M. Webber, B. G. M. Webber, A. Sanchez-Franks, B. Y. Queste

“…Consequently, we suggest that predictability of the annual oxygen flux is likely aided by understanding and predicting the physical forcing of the Southwest Monsoon Current. …”
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Multiscale excitations in the diluted two-dimensional S=1/2 Heisenberg antiferromagnet by Liuyun Dao, Hui Shao, Anders W. Sandvik

“…A magnon with anomalous logarithmic dispersion, close to our result, was predicted in spin wave and T-matrix theory [Chernyshev et al., Phys. …”
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The impact of offshore wind turbine foundations on local hydrodynamics and stratification in the Southern North Sea by Erik Hendriks, Kobus Langedock, Luca A. van Duren, Jan Vanaverbeke, Wieter Boone, Karline Soetaert, Karline Soetaert

“…Furthermore, our research provides valuable data for validating and improving the models used to predict the ecological impact of OWFs.…”
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Variations of soil thermal conductivity in the Three-River Source Region, Qinghai‒Xizang Plateau by Jia Liu, Dong-Liang Luo, Wen-Jie Lei, Fang-Fang Chen, Rui-Xia He, Cheng-Song Yang, Yan Lu, Shi-Zhen Li

“…Meanwhile, our results show that an artificial neural network model (R2 = 0.78, p < 0.0001) incorporating ten measured soil physical parameters, outperforms traditional theoretical and empirical models in predicting STC. …”
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Durable resistance or efficient disease control? Adult Plant Resistance (APR) at the heart of the dilemma by Rimbaud, Loup, Papaïx, Julien, Rey, Jean-François, Moury, Benoît, Barrett, Luke G., Thrall, Peter H.

“…Using the demogenetic, spatially explicit, temporal, stochastic model landsepi, this study is a first attempt to investigate how resistance efficiency, age at the time of resistance activation and target pathogenicity trait jointly impact resistance durability and disease control at the landscape scale. …”
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Multi‐Frequency Oscillatory Hydraulic Tomography Improves Heterogeneity Imaging and Resolution and Reduces Uncertainty by Jeremy R. Patterson, Michael Cardiff

“…Abstract Understanding subsurface heterogeneity is crucial to predicting groundwater flow pathways, mixing, and other processes in aquifers and other fluid reservoirs. …”
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Remote sensing reveals the role of forage quality and quantity for summer habitat use in red deer by Thomas Rempfler, Christian Rossi, Jan Schweizer, Wibke Peters, Claudio Signer, Flurin Filli, Hannes Jenny, Klaus Hackländer, Sven Buchmann, Pia Anderwald

“…Results The combination of vegetation indices and optical traits greatly improved predictive power in both the biomass (R2 = 0.60, Root mean square error (RMSE) = 88.55 g/m2) and relative nitrogen models (R2 = 0.34, RMSE = 0.28%). …”
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Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks by Yongxu Zhang, Catalin Mitelut, David J. Arpin, David Vaillancourt, Timothy Murphy, Shreya Saxena

“…To enable the network to utilize all temporal features of the neural input data, and to enhance the memory of recurrent neural networks, this paper proposes a novel approach: recurrent neural networks with time-varying weights, here termed Time-varying recurrent neural networks. These models are able to not only predict the class of the time-sequence correctly, but also lead to accurate classification earlier in the sequence than standard recurrent neural networks, while also stabilizing gradient dynamics. …”
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NF-κB RelA regulates temporal oligodendrocyte differentiation in the postnatal brains by Kamonrapat Sompub, Norihisa Bizen, Albert S. Baldwin, Albert S. Baldwin, Hirohide Takebayashi, Hirohide Takebayashi, Hirohide Takebayashi

“…In RelA cKO mice, we observed a transient delay of oligodendrocyte differentiation in the postnatal cerebral cortex, albeit in a spatially and temporally restricted manner. Similarly, in the primary cultured oligodendrocyte differentiation model, the loss of RelA resulted in impaired terminal differentiation. …”
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Experimental measurement of mean transition path velocities of colloidal particles surmounting energy barriers by Brandon R Ferrer, Juan Ruben Gomez-Solano

“…Owing to the slow dynamics of the bead in this viscous medium, we can spatially resolve the mean velocity profiles of the transition paths for distinct potentials, which agree with theoretical predictions of a one-dimensional model for the motion of a Brownian particle traversing a parabolic barrier. …”
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Isotopic niche plasticity of American alligators within the southern Everglades. by Mathew J Denton, Michael S Cherkiss, Frank J Mazzotti, Laura A Brandt, Sidney T Godfrey, Darren Johnson, Kristen M Hart

“…Alligators within the estuary had a larger niche driven by a wider range in stable carbon isotope ratios than those sampled in freshwater habitats. Spatially, model predictability was higher at the smaller scale, reflecting the variability in basal sources and biochemistry among capture sites. …”
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The influence of farm connectedness on foot‐and‐mouth disease outbreaks in livestock by Jean B. Contina, Rachel L. Seibel, Bhim Chaulagain, Karasi B. Mills, Michael J. Tildesley, Christopher C. Mundt

“…The objectives were to (1) determine the impact of connectivity of the initially infected farm on the size of FMD outbreaks in four counties of differing connectivity; (2) compare FMD spread in counties that have different mean farm connectivity levels over all farms in the county; and (3) determine how connectivity relationships affect an example control measure. We used a spatially explicit stochastic model to simulate FMD outbreaks on livestock farm operations in four UK counties. …”
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Fourier Analysis of CMFD Method in Cylindrical Geometry by WEN Yuchen, HAO Chen, WANG Yizhen

“…Building on the aforementioned Fourier analysis, this study develops a cylindrical pebble-bed reactor model for steady-state 3D neutron simulation. The results demonstrate that the acceleration efficiency of the CMFD method aligns with the phenomena predicted by the Fourier analysis in cylindrical geometry. …”

Temporal RAGE Over-Expression Disrupts Lung Development by Modulating Apoptotic Signaling by Derek M. Clarke, Madison N. Kirkham, Logan B. Beck, Carrleigh Campbell, Hayden Alcorn, Benjamin T. Bikman, Juan A. Arroyo, Paul R. Reynolds

“…This study sought to evaluate the role of RAGE in lung development by using a transgenic (TG) mouse model that spatially and temporally controlled RAGE overexpression. …”
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Assessing Gonipterus defoliation levels using multispectral unmanned aerial vehicle (UAV) data in Eucalyptus plantations by Phumlani Nzuza, Michelle L. Schröder, Rene J. Heim, Louis Daniels, Bernard Slippers, Brett P. Hurley, IIaria Germishuizen, Benice Sivparsad, Jolanda Roux, Wouter. H Maes

“…As conventional insect pest monitoring methods are time-consuming and spatially restrictive, this study assessed the potential of UAV monitoring. …”
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Estimating Near-Surface Air Temperature From Satellite-Derived Land Surface Temperature Using Temporal Deep Learning: A Comparative Analysis by Jangho Lee

“…Seasonal and diurnal evaluations show higher errors in spring and midday hours, likely due to rapid vegetation changes and stronger physical and dynamical processes that make T2M less predictable. Spatially, stations with denser vegetation exhibit elevated errors, suggesting that transpiration and canopy effects complicate the LST-T2M linkage. …”
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Skin-associated Corynebacterium amycolatum shares cobamides by M. H. Swaney, N. Henriquez, T. Campbell, J. Handelsman, L. R. Kalan

“…Therefore, we hypothesize that cobamide sharing mediates skin community dynamics. Preliminary work predicts that several skin-associated Corynebacterium species encode de novo cobamide biosynthesis and that their abundance is associated with skin microbiome diversity. …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…Specifically, we used artificial neural networks (ANN) to incorporate object detection into segmentation. The proposed ANN model extracts the most useful information to differentiate different IS datasets. …”
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