Methodology for plotting the flight planned route change of the aircraft in flight by M. A. Kiselev, Y. S. Kalyuzhny, A. V. Karpov, S. F. Borodkin

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Mechanosynthesis and thermal bio–sensing of beryllium–based molecularly imprinted polymers by Ana I. Furtado, Joseph W. Lowdon, Kasper Eersels, Bart van Grinsven, Adriana Cruz, Jacinta Serpa, Vasco D.B. Bonifácio, Raquel Viveiros, Teresa Casimiro

“…Subsequently, supercritical CO2 (scCO2) technology was used for efficiently desorb of the template, yielding vacant receptors. …”
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Attention-Module-Guided Time-Lapse Leakage Plume Imaging Driven by LeakInv-CUNet GPR Inversion Framework by Honghua Wang, Shan Wang, Fei Zhou, Yi Lei, Bin Zhang

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An Organ-on-a-Chip Modular Platform with Integrated Immunobiosensors for Monitoring the Extracellular Environment by Anastasia Kanioura, Myrto Kyriaki Filippidou, Dimitra Tsounidi, Panagiota S. Petrou, Stavros Chatzandroulis, Angeliki Tserepi

“…Despite the potential of OoC technology in emulating tissue complexity, a significant gap persists in the continuous real-time monitoring of cellular behaviors and their responses to external stimuli, arising from the lack of biosensors integrated onto OoC microfluidic platforms. …”
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Lightweight CNN-based seizure classification via leveraging chimera states in iEEG recordings by Fatemeh Azad, Saeed Bagheri Shouraki, Soheila Nazari, Mansun Chan

“…These states provide a potential tool for predicting and detecting epileptic seizures. Effective detection and classification of chimera states in intracranial electroencephalography (iEEG) signals are critical for improving patient outcomes and deepening our understanding of neurological disorders. …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…Abstract Accurate estimation of permeability reduction in clay-rich sandstones during low-salinity water flooding is critical for optimizing enhanced oil recovery (EOR) strategies and ensuring efficient reservoir management. Traditional methods often rely on costly experiments or simplified empirical correlations, which struggle to capture the complex, non-linear interactions governing this phenomenon. …”
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Direction-Aware Lightweight Framework for Traditional Mongolian Document Layout Analysis by Chenyang Zhou, Monghjaya Ha, Licheng Wu

“…Our framework introduces three key innovations: a modified MobileNetV3 backbone with asymmetric convolutions for efficient vertical feature extraction, a dynamic feature enhancement module with channel attention for adaptive multi-scale information fusion, and a direction-aware detection head with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mo form="prefix">sin</mo><mi>θ</mi><mo>,</mo><mo form="prefix">cos</mo><mi>θ</mi><mo>)</mo></mrow></semantics></math></inline-formula> vector representation for accurate orientation modeling. …”
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Plant recognition of maize seedling stage in UAV remote sensing images based on H-RT-DETR by Yunlong Wu, Shouqi Yuan, Lingdi Tang

“…In order to quickly and accurately identify and count maize seedlings in a complex field environment, this study proposes an end-to-end maize seedling plant detection model H-RT-DETR (Hierarchical-Real-Time DEtection TRansformer) based on hierarchical feature extraction and RT-DETR (Real-Time DEtection TRansformer). …”
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Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management by Mahmoud Badee Rokaya Mahmoud, Dalia Ismaeil Ibrahim Hemdan, Samah Hazzaa Alajmani, Raneem Yousif Alyami, Ghada Elmarhomy, Hassan Hashim, El-Sayed Atlam

“…However, water leak detection and irrigation scheduling traditional AI models are often computationally intensive and require complex hyperparameter tuning, making them less scalable. …”
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Cellulosic-based microneedles for sensing heavy metals in fish samples by Houman Kholafazad, Mahdiyeh Pazhuhi, Mohammad Hasanzadeh, Nicolas H. Voelcker, Nasrin Shadju, Azadeh Nilghaz

“…The MNs exhibit low reagent and sample volume requirements along with flexibility and ease of penetration into samples, and filtration capabilities that allow efficient detection with minimal interference. The structure of MNs was investigated by field emission scanning electron microscopy (FE-SEM), revealing a conical shape with an average height of ∼750 µm and a diameter of ∼500 µm. …”
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PlantHealthNet: Transformer-Enhanced Hybrid Models for Disease Diagnosis and Severity Estimation in Agriculture by Abid Iqbal

“…The suggested system improves precision agriculture by making disease detection and management reliable, scalable, and efficient. …”
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Determination of 15 Rare Earth Elements in Phosphate Ores by Inductively Coupled Plasma-Mass Spectrometry with Atmospheric Pressure Closed Microwave Digestion by Nan ZHANG, Zhikang ZHENG, Jiasong WANG, Jiangping ZENG

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Defense scheme for the world state based attack in Ethereum by Zhen GAO, Dongbin ZHANG, Xiao TIAN

“…Ethereum is taken as the representative platform of the second generation of blockchain system.Ethereum can support development of different distributed applications by running smart contracts.Local database is used to store the account state (named world state) for efficient validation of transactions, and the state root is stored in the block header to guarantee the integrity of the state.However, some researches revealed that the local database could be easily tempered with, and attackers can issue illegal transactions based on the modified account state to obtain illegitimate benefits.This world-state based security problem was introduced, and the preconditions for attack were analyzed.Compared with the two common security threats under the PoW (proof of work) consensus, it was found that when the attacker controls the same mining computing power, the world-state based attack brought higher risk, and the success rate approached 100%.In order to deal with this threat, a practical scheme for attack detection and defense was proposed accordingly.The secondary verification and data recovery process were added to the Ethereum source code.The feasibility and complexity of the proposed scheme was evaluated with single-machine multi-threading experiments.The proposed scheme improves Ethereum’s tolerance to malicious tampering of account state, and is applicable to other blockchain platforms applying local database for transaction validation, such as Hyperledger Fabric.In addition, the time and computational overhead brought by the proposed scheme are not prominent, so it has good applicability and induces acceptable impact on the performance of original system.…”
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Energy-aware federated learning for secure edge computing in 5G-enabled IoT networks by Milad Rahmati

“…To address these challenges, we propose an energy-aware federated learning (EAFL) framework, integrating adaptive client selection, quantization-aware model updates, and blockchain-enhanced security mechanisms to improve both energy efficiency and resistance to model poisoning attacks and adversarial gradient manipulations. …”
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Optimizing Fire Scene Analysis: Hybrid Convolutional Neural Network Model Leveraging Multiscale Feature and Attention Mechanisms by Shakhnoza Muksimova, Sabina Umirzakova, Mirjamol Abdullaev, Young-Im Cho

“…The proposed model integrates advanced convolutional neural networks with multiscale feature extraction, attention mechanisms, and ensemble learning to achieve superior performance in real-time fire detection. By leveraging the strengths of pre-trained networks such as ResNet50, VGG16, and EfficientNet-B3, the model captures detailed features at multiple scales, ensuring robust detection capabilities. …”
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Uncertainty CNNs: A path to enhanced medical image classification performance by Vasileios E. Papageorgiou, Georgios Petmezas, Pantelis Dogoulis, Maxime Cordy, Nicos Maglaveras

“…In this paper, we introduce a low-complexity uncertainty-based CNN architecture for medical image classification, particularly focused on tumor and heart failure (HF) detection. …”
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An Automated Image Segmentation, Annotation, and Training Framework of Plant Leaves by Joining the SAM and the YOLOv8 Models by Lumiao Zhao, Kubwimana Olivier, Liping Chen

“…Recognizing plant leaves in complex agricultural scenes is challenging due to high manual annotation costs and real-time detection demands. …”
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Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…However, these models often struggle to effectively handle the temporal dependencies, complexity, and scalability required for real-time threat detection. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…These methods struggle to detect complex or subtle patterns associated with early-stage faults. …”
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Drainage Pipeline Multi-Defect Segmentation Assisted by Multiple Attention for Sonar Images by Qilin Jin, Qingbang Han, Jianhua Qian, Liujia Sun, Kao Ge, Jiayu Xia

“…Drainage pipeline construction projects are vulnerable to a range of defects, such as branch concealed joints, variable diameter, two pipe mouth significances, foreign object insertion, pipeline rupture, and pipeline end disconnection, generated during long-term service in a complex environment. This paper proposes two enhancements to multiple attention learning to detect and segment multiple defects. …”
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