Emergence of cellular nematic order is a conserved feature of gastrulation in animal embryos by Xin Li, Robert J. Huebner, Margot L. K. Williams, Jessica Sawyer, Mark Peifer, John B. Wallingford, D. Thirumalai

“…To explain the common physical mechanism, we created a theoretical model that not only explains the experimental observations but also predicts that the nematic phase should be disrupted upon loss of planar cell polarity (frog), cell adhesion (frog), and notochord boundary formation (zebrafish). …”
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Spatiotemporal orchestration of calcium-cAMP oscillations on AKAP/AC nanodomains is governed by an incoherent feedforward loop. by Lingxia Qiao, Michael Getz, Ben Gross, Brian Tenner, Jin Zhang, Padmini Rangamani

“…In this work, we develop computational models of the Ca2+/cAMP pathway and AKAP/AC nanodomain formation that give rise to the two important predictions: instead of an arbitrary phase difference, the out-of-phase Ca2+/cAMP oscillation reaches Ca2+ trough and cAMP peak simultaneously, which is defined as inversely out-of-phase; the in-phase and inversely out-of-phase oscillations associated with Ca2+-cAMP dynamics on and away from the nanodomains can be explained by an incoherent feedforward loop. …”
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DTCNet: finger flexion decoding with three-dimensional ECoG data by Fufeng Wang, Zihe Luo, Wei Lv, XiaoLin Zhu

“…Specifically, current models tend to confuse the movement information of different fingers and fail to fully exploit the dependencies within time series when predicting long sequences, resulting in limited decoding performance. …”
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On the Formation of Planets in the Milky Way’s Thick Disk by Tim Hallatt, Eve J. Lee

“…Disk temperatures exceed the sublimation temperatures of common volatile species for ≳Myr timescales, predicting more spatial homogeneity in gas chemical composition. …”
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Analysis of space solar array arc images based on deep learning techniques by Afaf M. Abd El-Hameed, Ahmed S. Farahat, Khaled Y. Youssef, M. Elfarran, I. M. Selim

“…Leveraging advanced Deep Learning (DL) methodologies, including Convolutional Neural Networks (CNN) and Transfer Learning, a robust predictive model has been developed to analyze arc behavior and identify defective cells based on image data. …”
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Wastewater-based surveillance data to determine the COVID-19 trends in communities with low populationMendeley Data by Aiswarya Rani Pappu, Ashley Green, Melanie Oakes, Sunny Jiang

“…This dataset will help to 1) improve future wastewater based epidemiological models, 2) improve understanding on PMMoV concentration ranges in wastewater at low population communities, 3) develop methods to support data interpretation, and 4) understand the effects of spatial scales on sampling frequency and infection outbreak detection.…”
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A Spectroastrometric Study of the Low-velocity Wind from DG Tau A by Yu-Ru Chou, Michihiro Takami, Shin-Ping Lai, Emma Whelan, Noah B. Otten, Min Fang, Akito Tajitsu, Masaaki Otsuka, Hsien Shang, Chun-Fan Liu, Jennifer Karr, Aisling Murphy

“…We find that the observed line profiles and the spatial scales of the LVC emission do not agree with the existing predictions for photoevaporative or magnetohydrodynamical disk winds. …”
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Molecular Dynamics-Based Two-Dimensional Simulation of Powder Bed Additive Manufacturing Process for Unimodal and Bimodal Systems by Yeasir Mohammad Akib, Ehsan Marzbanrad, Farid Ahmed

“…The packing density in the powder bed dictates the bulk powder behavior and in-process performance and, therefore, significantly impacts the mechanical and physical properties of the printed components. Numerical modeling of the powder bed process helps to understand the powder spreading process and predict experimental outcomes. …”
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Reflection of two-dimensional surface polaritons by metallic nano-plates on atomically thin crystals by Lee Seojoo, Kang Ji-Hun

“…Owning to their unusual optical properties, such as electrical tunability and strong spatial confinement, two-dimensional surface polaritons (2DSPs) hold great promise for deep sub-wavelength manipulation of light in a reduced low-dimensional space. …”
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S. pombe kinesins-8 promote both nucleation and catastrophe of microtubules. by Muriel Erent, Douglas R Drummond, Robert A Cross

“…Our evidence identifies Klp5 and 6 as spatial regulators of microtubule dynamics that enhance both microtubule nucleation at the cell centre and microtubule catastrophe at the cell ends.…”
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Travel patterns in China. by Tini Garske, Hongjie Yu, Zhibin Peng, Min Ye, Hang Zhou, Xiaowen Cheng, Jiabing Wu, Neil Ferguson

“…Travel patterns in both populations were well-fitted by a gravity model with a lognormal kernel function. The results provide the first quantitative information on human travel patterns in modern China, and suggest that a pandemic emerging in a less developed area of rural China might spread geographically sufficiently slowly for containment to be feasible, while spatial spread in the more economically developed areas might be expected to be much more rapid, making containment more difficult.…”
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A topological approach to understanding crack initiation and propagation in carbon fiber reinforced polymer composites under an opening load by Mayrene Uy, Daiki Kido, Masao Kimura

“…From a materials perspective, this methodology allows integration of not just crack length but also 3D crack shape into predictive models, offering valuable insights for optimizing the performance and extending the lifetime of carbon fiber/epoxy composites.…”
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Globally scalable glacier mapping by deep learning matches expert delineation accuracy by Konstantin A. Maslov, Claudio Persello, Thomas Schellenberger, Alfred Stein

“…Here we address this gap and propose Glacier-VisionTransformer-U-Net (GlaViTU), a convolutional-transformer deep learning model, and five strategies for multitemporal global-scale glacier mapping using open satellite imagery. …”
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Segregation of particles during maize loading process in a center-loaded silo by Guixiang Chen, Chaosai Liu, Deqian Zheng, Dianxuan Wang

“…Inorganic impurities mainly accumulated in the 1/4–3/4 radius, while other organic impurities accumulated mostly near the wall of the silo. A nonlinear model considering kernel breakage and segregation was developed to predict the porosity distribution in the vertical and radial direction in the silo. …”
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Recombinant expression and functional analysis of transgelin-like protein from the shell of Mytilus coruscus by JIANG Yuting, SUN Qi, XU Huanzhi, SHEN Wang, ZHANG Xiaolin, FAN Meihua, LIAO Zhi

“…Sequence analysis showed that the TLP contained a calponin homology (CH) domain, and the spatial structure of TLP predicted by SWISS-MODEL presented a conformation formed predominately by α-helices. …”
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Advances in tumor subclone formation and mechanisms of growth and invasion by Yuhong Zhang, Weidong Wang

“…Major methodologies for studying tumor subclones include single-cell sequencing, liquid biopsy, and spatial transcriptomics, which provide insights into clonal architecture and dynamic evolution. …”
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Detecting forest and linear woody feature change between 1954 and 2019 in Southeastern Canadian agroecosystems for regional biodiversity assessment by Darren Pouliot, Niloofar Alavi, Mao Mao, Jon Pasher, Jason Duffe

“…The deep learning model developed here successfully mapped forests and LWFs between 1954 and 2019 using just a single image band, enabling reliable change estimation. …”
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Comparing US state resident IQ, socioeconomic status, and racial-ethnic composition as predictors of state violent crime rates by Stewart J. H. McCann

“…Generally, the results underline the importance of evaluating potential crime rate predictors in a multiple regression model rather than testing their predictive capacities only as single variables.…”
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Disaster recovery and business continuity: A case of MSMEs in Dar es Salaam by Tumpale Sakijege

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How the hadron gas affects X(3872) and ψ(2S) production in heavy ion collisions by Abreu Luciano M., Navarra Fernando S., Vieira Hildeson P.L.

“…The initial conditions for this evolution are given by the coalescence model, which depends on the spatial configuration of the states and yields quite different numbers for compact tetraquarks and extended meson molecules. …”
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