Warped matrix-variate Gaussian processes with structured kernels for multi-step-ahead driving behaviour prediction by Seiya Takano, Tomohiko Jimbo

“…Furthermore, the proposed method directly captures the periodicity using separate kernels to express the characteristics of rows and columns, making the parameters easier to interpret. …”
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Power Improved Generalized Heronian Mean Operators Utilizing Hamacher Operations with Picture Fuzzy Information by Baolin Li, Lihua Yang

“…Meanwhile, to remove the impact of abnormal data and capture the correlations among attributes in MADM issue, we propose the power improved generalized Heronian mean (PIGHM) operators in this paper, which have the merits of both power average (PA) operator and improved generalized Heronian mean (IGHM) operator. …”
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Then and Now: COVID-19 Pandemic Lockdown Misfire Atmospheric Methane over India by Manoj Hari, Rajesh Kumar Sahu, MS Shyam Sunder, Bhishma Tyagi

“…The study analyzed the lockdown variations (24 March-31 May) of tropospheric CH4 over India with the same period of 2019 and 2021 using TROPOMI to find the changes in CH4 concentrations over different regions of India due to lockdown. Our results capture the undeviating north (low)-south (high) gradient in the CH4 concentration with anticipated regional intensifications, likely, in the eastern and western coastal regions, with more comprehensive details than it ever has been presented before.…”
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Context-dependent modulation of spatial attention: prioritizing behaviourally relevant stimuli by Noah Britt, Jackie Chau, Hong-jin Sun

“…Over time, we learn to allocate attention resources towards stimuli that are behaviourally relevant to ongoing action, leading to attention capture by meaningful peripheral stimuli. A common example includes, while driving, stimuli that imply a possibly hazardous scenario (e.g. a pedestrian about to cross the road) warrant attentional prioritization to ensure safe proceedings. …”
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Static and Dynamic Model Calibration for Upper Thermosphere Determination by Haibing Ruan, Jiuhou Lei, Jianyong Lu

“…Abstract Thermospheric density, a crucial factor in spacecraft operations, poses a significant challenge in accurate determination due to the intricate coupling of the thermosphere‐ionosphere system. Despite capturing long‐term trends, the widely used empirical models, which are used for low Earth orbit spacecraft operations, often fail to reproduce small‐scale or short‐term variations in the thermosphere. …”
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Deep Learning-Assisted Short-Term Power Load Forecasting Using Deep Convolutional LSTM and Stacked GRU by Fath U Min Ullah, Amin Ullah, Noman Khan, Mi Young Lee, Seungmin Rho, Sung Wook Baik

“…Next, the sequence of refined data is passed into a modified convolutional long short-term memory (ConvLSTM) network that captures the spatiotemporal correlations from the sequence and generates the feature maps. …”
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Public Health Evaluation of COVID-19 Vaccine Acceptability and Health Behaviors in South Africa: Past, Current, and Future Implications (2020–2022) by Handan Wand, Jayajothi Moodley, Tarylee Reddy, Sarita Naidoo

“…Semiparametric regression models were used to capture the nonlinear association between the vaccine acceptability and health behaviors. …”
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Trajectory Simulation of Emergency Vehicles and Interactions with Surrounding Traffic by Cristián E. Cortés, Bruno Stefoni

“…To validate the design, a real EMV trip captured by the footage was simulated by the API. The simulation considerably reduced the degree of error in delineating the path followed by the EMV compared to the default simulations generated by most commercially available software, thereby demonstrating that the API can provide highly accurate estimates of EMV trip times in an emergency context.…”
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Impact of Vein Wall Hyperelasticity and Blood Flow Turbulence on Hemodynamic Parameters in the Inferior Vena Cava with a Filter by Jafar Moradicheghamahi, Debkalpa Goswami

“…Simulations are conducted with varying sizes of clots captured in the filter. The findings show that, in regions of high wall shear stress, the rigid wall model predicted higher TAWSS values, suggesting an increased disease risk compared to the hyperelastic model. …”
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Enhancing real estate price prediction using optimized least squares moment balanced machine by Radian Khasani Riqi

“…Traditional methods often struggle to capture the complex relationships between these variables, resulting in inefficient land use and suboptimal resource allocation. …”
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Automatic Recognition of Financial Instruments Based on Anisotropic Partial Differential Equations by Wenfu Pan, Li Chen, Ruxing Zhang

“…Firstly, it obtains the invoices of the group enterprise, uses scanning technology and related image recognition technology to capture, process, compress and slice the paper bill content, and then carries out data identification and verification of the image. …”
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Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model by Edward Natenberg, Jidong Gao, Ming Xue, Frederick H. Carr

“…High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. …”
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Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells. by Xuexing Du, Jennifer Crodelle, Victor James Barranca, Songting Li, Yunzhu Shi, Shangbang Gao, Douglas Zhou

“…We develop Hodgkin-Huxley-based models for these channels and integrate them to capture the cells' electrical activity. To ensure the model accurately reflects cellular responses under depolarizing currents, we develop a parallel simulation-based inference method for determining the model's free parameters. …”
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The Experience of Emotional Distancing in The Managementagement of Compulsive Hoarding: A Visual Methods Approach Using The “Hoard” Acronym Tool by Colin Jones, Satwant Singh

“…Results: The experiences of participants were captured using semi-structured interviews, which were digitally recorded and later transcribed verbatim. …”
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A hybrid multiscale feature fusion model for enhanced cardiovascular arrhythmia detection by Md. Alamin Talukder

“…Traditional arrhythmia classification methods often struggle with class imbalance and fail to capture critical multiscale temporal and spatial features, leading to suboptimal diagnostic performance. …”
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Efficiency Analysis of Turkish Container Ports: SFA or DEA? by İsmail Yenilmez

“…Ports like MIP MERSİN and EVYAP demonstrated high efficiency in both methods, while discrepancies were detected in ports like MARDAŞ and ÇELEBİ BANDIRMA. SFA better captures external factors and operational challenges, whereas DEA emphasizes relative efficiency. …”
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Therapeutic exercise protocol for the prevention of anterior cruciate ligament injuries in female soccer players with dynamic knee valgus (RCT) by Amanda Coves García, Emilio José Poveda Pagán

“…The biomechanics of the lower limbs, the jump-landing dynamics, and the pre- and post-training satisfaction of the players will be evaluated. Image capture and processing systems will be used as well as tests such as the DVJ and the LESS scoring system, among others. …”
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Enhanced SOC estimation method for lithium-ion batteries using Bayesian-optimized TCN–LSTM neural networks by Taotao Hu, Xiting Zhu, Maokai Tian

“…The TCN is utilized to extract temporal features of the battery parameters, while the LSTM network captures long-term dependencies in sequential data. …”
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Chaotic dynamics of string around charged black brane with hyperscaling violation by Da-Zhu Ma, Dan Zhang, Guoyang Fu, Jian-Pin Wu

“…There is a threshold value z∗ = 2, below which the string is captured by the black brane no matter where the string is placed at the beginning. …”
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Predicting EV battery state of health using long short term degradation feature extraction and FEA TimeMixer by Weijie Tang, Jiayan Chen, Dongjiao Chen

“…Finally, a Frequency Enhanced Attention (FEA) mechanism is introduced to improve the TimeMixer model, which integrates time-domain and frequency-domain information to overcome the limitations of the original model in capturing frequency-domain features. Experimental results show that the proposed method achieves a Mean Absolute Error of less than 0.0219 for short-term SOH predictions and less than 0.1007 for long-term SOH predictions, outperforming other deep learning models in prediction accuracy over multiple prediction lengths.…”
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