Landsat Time Series Reconstruction Using a Closed-Form Continuous Neural Network in the Canadian Prairies Region by Masoud Babadi Ataabadi, Darren Pouliot, Dongmei Chen, Temitope Seun Oluwadare

Get full text

Comparing a New Passive Lining Method for Jet Noise Reduction Using 3M™ Nextel™ Ceramic Fabrics Against Ejector Nozzles by Alina Bogoi, Grigore Cican, Laurențiu Cristea, Daniel-Eugeniu Crunțeanu, Constantin Levențiu, Andrei-George Totu

“…In contrast, the Nextel lining achieves comparable reductions in overall noise, especially in high-frequency ranges, while minimizing structural impact and promoting spatial energy dissipation. Analyses in both the time-frequency and spatial–spectral domains demonstrate that the Nextel configuration not only lowers acoustic energy but also disrupts coherent noise patterns, making it particularly effective for near-field protection in compact propulsion systems. …”
Get full text

Modeling the spatiotemporal dynamic heterogeneity of pre-synthetic stage breast cancer tumor-immune interactions by Kennedy Mensah, Joseph Abeiku Ackora-Prah, Dominic Otoo, Atta Kwame Gyamfi

“…The steady state of the spatially homogeneous model exhibits stability but becomes unstable when spatial effects are incorporated. …”
Get full text

Toward Hand Gesture Recognition Using a Channel-Wise Cumulative Spike Train Image-Driven Model by Yang Yu, Zeyu Zhou, Yang Xu, Chen Chen, Weichao Guo, Xinjun Sheng

“…Here, we propose a channel-wise cumulative spike train (cw-CST) image-driven model (cwCST-CNN) for hand gesture recognition, leveraging the spatial activation patterns of motor unit firings to distinguish motor intentions. …”
Get full text

Early embryonic development of the German cockroach Blattella germanica by Ariel Bar-Lev Viterbo, Judith R. Wexler, Orel Mayost Lev-Ari, Ariel D. Chipman

“…Results We present a detailed time series of nuclear division and distribution from fertilization through germband formation and report patterns of expression for the early patterning genes hunchback, caudal, and twist in order to understand early polarization and mesoderm formation. …”
Get full text

Optimizing Group Activity Recognition With Actor Relation Graphs and GCN-LSTM Architectures by M. R. Tejonidhi, C. V. Aravinda, S. V. Aruna Kumar, C. K. Madhu, A. M. Vinod

“…Traditional video-based activity recognition methods often grapple with persistent obstacles such as environmental noise, background clutter, and the inter-class similarities inherent in activity patterns. Recent advancements in this field have largely focused on spatial feature extraction, which alone proves inadequate for thorough group activity analysis. …”
Get full text

Application of a Multi‐Layer Artificial Neural Network in a 3‐D Global Electron Density Model Using the Long‐Term Observations of COSMIC, Fengyun‐3C, and Digisonde by Wang Li, Dongsheng Zhao, Changyong He, Yi Shen, Andong Hu, Kefei Zhang

Get full text

Ecological restoration zoning and its driving factors in Beijing-Tianjin-Hebei based on landscape ecological risk and ecosystem services by Wendi Wang, Ying Chen, Zhe Du, Shanting Bi, Qing Zhang, Teng Ye

“…Key results indicate: (1) Overall improvements in most ES (FS, WY, SR, MESLI) alongside decreasing ERI and declines in CS and HQ over the study period; (2) Predominantly significant negative spatial correlations between ERI and ES (except for WY); (3) Delineation of four distinct ecological restoration zones prioritizing different management strategies; (4) Elevation, the normalized differential vegetation index, and the human footprint identified as primary drivers of the zoning patterns. …”
Get full text

Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

“…Our model uses the Air Quality Open Dataset (AQD), combining data from ground sensors, meteorological sources, and satellite imagery to create a diverse dataset. CNNs extract spatial pollutant patterns from satellite images, whereas BiLSTM networks simulate temporal dynamics in pollutant and weather data. …”
Get full text

GTN-GCN: Real-Time Traffic Forecasting Using Graph Convolutional Network and Transformer by Sadia Naj Jinia, Sumaiya Binte Azad, Rima Akter, Taivan Reza Dipto, Md. Khaliluzzaman

“…The DTM dynamically updates graph structures based on real-time traffic conditions, while GATs focus on identifying critical spatial relationships. GRUs efficiently capture temporal dependencies, and the transformer model captures long-term sequential patterns, providing a comprehensive framework for real-time traffic forecasting. …”
Get full text

Learn from Simulations, Adapt to Observations: Super-Resolution of Isoprene Emissions via Unpaired Domain Adaptation by Antonio Giganti, Sara Mandelli, Paolo Bestagini, Stefano Tubaro

“…We extensively demonstrate the proposed method’s effectiveness and robustness in restoring fine-grained patterns of observed isoprene emissions. Moreover, we compare different setups and validate our approach using different emission inventories from both domains. …”
Get full text

Spatio-Temporal Data Augmentation Method for Network Traffic Prediction by Sung Oh, Myeong-Jun Oh, Jong-Kyung Im, Ji-Yeon Park, Joung-Sik Kim, Na-Rae Yi, Myung-Ho Kim, Sung-Ho Bae

“…Despite this need, existing studies have largely overlooked data augmentation techniques that simultaneously address spatial and temporal features. Moreover, network traffic data often exhibits localized and granular patterns, meaning that augmented data with significant spatial deviations from the original distribution can undermine structural consistency, leading to severe performance degradation in prediction models. …”
Get full text

Airborne radiometric data for digital soil mapping of peat at broad and local scales by Dave O’Leary, Colin Brown, Jim Hodgson, John Connolly, Louis Gilet, Patrick Tuohy, Owen Fenton, Eve Daly

“…Peat soils are high in soil organic matter (SOM) and are recognised stores of carbon. Knowledge of the spatial distribution of peat soils is becoming the focus of many studies and is related closely to peatland mapping. …”
Get full text

Remote sensing techniques to assess badlands dynamics: insights from a systematic review by Rosa Colacicco, Marco La Salandra, Isabella Lapietra, Alberto Refice, Domenico Capolongo

“…Satellite imagery is a leading tool due to its extensive spatial and temporal coverage, enhancing land-use change monitoring and erosion modeling capabilities. …”
Get full text

Evaluation of Rural Housing Structural Transformations Based on the Rural Livelihood; Case Study : Riab Village in Khorasan Razavi Province by Abasalt Askari Rabori, Shahab Abbaszadeh, Ali Asghar Abroon

“…In the physical dimension, it is found that material and structural changes, ornamental simplification have been noticeable. In spatial organization dimension, the changes in spatial integration and spatial configuration were among evident findings.…”
Get full text

Biomass prediction of Typha latifolia on a paludiculture site by combining structural and spectral features from UAS data by Christina Hellmann, Bernd Bobertz, Fabian Hübner, Nora Köhn, Jürgen Kreyling, Sebastian van der Linden

“…Uncrewed Aerial Systems (UAS) can aid in monitoring crop growth and spatial heterogeneity in vegetation patterns, and hence contribute to improved management. …”
Get full text

Vegetation Growth Simulation of the Community Land Model in the Southwest China by Lihuan WANG, Yaqiong LÜ, Ziyi WANG

“…Under the background of global warming， the temperature has increased frequently in the southwest， and the ecosystem in the southwest is vulnerable and sensitive to climate change in the past few decades.The southwest region is an important carbon sink area in China.Monitoring and simulation of vegetation variations is of great significance for an in-depth understanding of the carbon cycle mechanism and promoting sustainable economic development.Leaf Area Index （LAI） and Gross Primary Productivity （GPP）， as indicators of vegetation health and ecosystem stability， can be used to quantify vegetation studies and characterize dynamic changes of vegetation.Vegetation dynamic Model is one of the important means to study vegetation growth and change.Community Land Model （CLM） is one of the earliest land model with the function of vegetation dynamic simulation， the most developed and widely used land model in the world.Model evaluation is an indispensable part of model development， which provides a basis for model development and improvement.This study uses the Community Land Model version5 （CLM5） to simulate and analyze the spatial and temporal variations of the leaf area index （LAI） and total primary productivity （GPP） in the southwest region across 2000 -2016， and compare it with multiple sets of remote sensing data to evaluate LAI and GPP simulations of CLM5 in the southwest.The results showed that CLM5 could well simulate the seasonal variation of LAI and GPP in southwest China， but overestimated LAI in growing season.The CLM5 can reasonably simulate LAI of temperate deciduous broadleaf shrubs， LAI， GPP of alpine C3 meadow and GPP of C3 meadow.CLM5 could capture the spatial distribution pattern of LAI and GPP in the southwest， which is decreasing from southeast to northwest， but CLM5 overestimates LAI in the whole southwest region， especially in the karst landform area of Guizhou.Contrary to the overestimation of LAI simulation， CLM5's overall simulation of GPP in Southwest China is low， especially in Yunnan province.In addition， CLM5 has a poor simulation of LAI and GPP trend in the southwest.Especially in most parts of Yunnan， remote sensing data mainly shows an upward trend， while CLM5 simulation shows a downward trend.In a word， CLM5 can simulate the seasonal change and spatial distribution of LAI and GPP in the southwest， but the simulation of the trend in some areas of Yunnan and Guizhou is poor， and more in-depth parametric schemes for the development of farmland in Sichuan Basin， Yunnan forests， and karst vegetation in Guizhou are needed to improve the simulation.…”
Get full text

Dust detection in western and southwestern Iran based on DAI index algorithm and Modis spectral data by Azar Faryabi, Hamid Reza Matinfar, Seyyed Kazem Alavi Panah, Ali Akbar Norouzi

“…Results and discussion: In general, it was found that all AOD maps generated from the direct method showed a very good spatial distribution of the local aerosol pattern compared to other methods. …”
Get full text

Phase field simulation of excavation damage zone in natural fractured rock mass by LIU Junjie, LIU Jianfeng, YANG Jianxiong, XUE Fujun, WEI Jinbing, GAO Chunyu

“…Three models with identical fracture patterns but different spatial scales confirmed that damage increased as fracture proximity to the tunnel decreased.Focusing on the near-field fracture model, simulations under varying lateral pressure coefficients (f = 0.6–1.4) revealed that tunnel stability decreased with increasing f. …”
Get full text

ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types by Tevfik Umut Dincer, Jason Ernst

“…It then for each cell type produces ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and ChromScore tracks of overall predicted regulatory activity. …”
Get full text