Theoretical Insights into the Impact of Pyrrole and Imidazole Substituents on the BODIPY Chromophore by Patrycja Piękoś, Paweł Lipkowski, Wim Dehaen, Robert Wieczorek, Aleksander Filarowski

“…This paper concerns the in silico studies of the influence of heterocyclic substituents as well as their protonated and deprotonated forms on the spectral characteristics of BODIPY (4,4-difluoro-4-bora-3a,4a-diaza-<i>s</i>-indacene) dyes. Computational studies were carried out in order to reveal the most effective method of modeling of the spectral features of fluorescent BODIPY dyes. …”
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Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning by Yan Zhu, Li Wang, Aichao Ruan, Zhiyu Peng, Zhenzhong Zhang

“…Therefore, the objective of this study is to rely on clinical parameters and radiomic features extracted from chest computed tomography (CT) scans to facilitate the preoperative classification of TMLs. …”
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Harmonic Path Integral Diffusion by Hamidreza Behjoo, Michael Chertkov

“…This feature positions H-PID as a strong alternative to traditional methods sampling, such as simulated annealing, particularly for applications that demand analytical control, computational efficiency, and scalability.…”
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No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics by Rongyao Yu, Fang Yang, Yi Liu, Jianghui He, Qingjiang Pang, Yang Song

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Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution by Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG, Bingchao WU, Meng LIU

“…The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by underground monitoring equipment, which seriously affects the real-time performance of mining safety monitoring equipment, is not good for subsequent computer vision tasks, and it is difficult to collect underground data. …”
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Wavefront Sensor for the Determination of Nanostructured Surface Defects by V.V. Buchenko, A.A. Goloborodko, V.V. Lendel, O.S. Oberemok

“…The feature of the original wave formation in the system of double Fourier transform with the reflection of light from the surface with structured local inhomogeneities of the refractive index is shown. …”
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COMPLEXITY IN A COURNOT DUOPOLY GAME WITH DIFFERENTIATED GOODS BETWEEN SEMI-PUBLIC AND PRIVATE FIRMS by Georges SARAFOPOULOS, Kosmas PAPADOPOULOS

“…Numerical simulations are carried out to show the complex behaviour. The chaotic features are justified numerically via computing Lyapunov numbers, sensitive dependence on initial conditions, bifurcation diagrams and strange attractors.…”
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Exact collective occupancies of the Moshinsky model in two-dimensional geometry by Arkadiusz Kuroś, Adam Pieprzycki, Edyta Gawin, Przemysław Kościk

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LMGDoc: Light Multigranular GNN for Efficient Document Understanding by Abdellatif Sassioui, Yasser Elouargui, Mohamed El Kamili, Rachid Benouini, El Mehdi Benyoussef, Meriyem Chergui, Mohammed Ouzzif

“…In this paper, we propose LMGDoc, a lightweight model capable of understanding and processing VRDs composed of three main components: a Feature Extractor using GloVe for text embedding and a novel layout encoding method, a Graph Constructor for representing document structures at multiple granular levels (word, region, and page), and a Graph Convolution Network (GNN). …”
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AgriLiteNet: Lightweight Multi-Scale Tomato Pest and Disease Detection for Agricultural Robots by Chenghan Yang, Baidong Zhao, Madina Mansurova, Tianyan Zhou, Qiyuan Liu, Junwei Bao, Dingkun Zheng

“…Real-time detection of tomato pests and diseases is essential for precision agriculture, as it requires high accuracy, speed, and energy efficiency of edge-computing agricultural robots. This study proposes AgriLiteNet (Lightweight Networks for Agriculture), a lightweight neural network integrating MobileNetV3 for local feature extraction and a streamlined Swin Transformer for global modeling. …”
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A multimodal functional structure-based graph neural network for fatigue detection by Dongrui Gao, Zhihong Zhou, Zongyao Peng, Haokai Zhang, Shihong Liu, Manqing Wang, Hongli Chang

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Classification of Epileptic Seizures by Simple Machine Learning Techniques: Application to Animals&#x2019; Electroencephalography Signals by Illia Pidvalnyi, Anna Kostenko, Oleksandr Sudakov, Dmytro Isaev, Oleksandr Maximyuk, Oleg Krishtal, Olena Iegorova, Ievgen Kabin, Zoya Dyka, Steffen Ortmann, Peter Langendorfer

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The structure of the local detector of the reprint model of the object in the image by A. A. Kulikov

“…The local detector is able, in addition to determining the modified object, to determine the original shape of the object as well. A special feature of TA is the representation of image sections in a compact form and the evaluation of the parameters of the affine transformation. …”
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Parametric optimization of flow in a solar chimney power plant under variable semi elliptical constraints by Rajamurugu Natarajan, S. Yaknesh, K B Prakash, Mohammed Al Awadh, Qasem M. Al-Mdallal

“…Abstract In response to the ongoing quest for more efficient renewable energy sources, this research addresses a significant gap in understanding the performance variations of Solar Chimney Power Plant (SCPP) models, particularly focusing on the influence of flow parameters in full and half-inclined collector sections featuring semi-elliptical curvature. …”
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Transferable deep learning with coati optimization algorithm based mitotic nuclei segmentation and classification model by Amal Alshardan, Nazir Ahmad, Achraf Ben Miled, Asma Alshuhail, Yazeed Alzahrani, Ahmed Mahmud

“…Numerous pattern recognition algorithms for cell-sized objects in HIs depend upon segmentation to assess features. The correct description of the segmentation has been difficult, and feature outcomes can be highly complex to the segmentation. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…This study explores the application of advanced machine learning (ML) models to predict CO₂ solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). …”
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Conformalons: a new class of black hole mimickers by Leonardo Modesto, Ali Akil, Cosimo Bambi

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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

“…Secondly, a hybrid loss function has been developed with weights optimized employing the Bayesian Optimization algorithm to provide a strategic method for parameter tuning in similar research. Lastly, the fixed window size of Swin-Transformer is dynamically adjusted to enhance computational efficiency and maintain accuracy. …”
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Enhancing efficient deep learning models with multimodal, multi-teacher insights for medical image segmentation by Khondker Fariha Hossain, Sharif Amit Kamran, Joshua Ong, Alireza Tavakkoli

“…Through this technique, the student model inherits the capacity for fine segmentation while operating with a significantly reduced parameter set and computational footprint. Additionally, introducing a novel training strategy optimizes knowledge transfer, ensuring the student model captures the intricate mapping of features essential for high-fidelity segmentation. …”
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Automatic Identification of the Main Ionospheric Trough in Total Electron Content Images by Gregory Starr, Sebastijan Mrak, Yukitoshi Nishimura, Michael Hirsch, Prakash Ishwar, Joshua Semeter

“…We show that statistics computed on the resulting labels are robust to our choice of algorithm parameters and that we are able to match the results of Aa, Zou, et al. (2020, doi:https://doi.org/10.1029/2019JA027583) with a particular selection of the parameters. …”
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