NuSTAR Detection of an Absorption Feature in ESP 39607: Evidence for an Ultrafast Inflow? by Alessandro Peca, Michael J. Koss, Roberto Serafinelli, Claudio Ricci, C. Megan Urry, Giulia Cerini, Peter G. Boorman

“…Alternative explanations, including associations with the warm-hot intergalactic medium or outflows of lighter elements, are investigated but found unlikely. If confirmed, this detection represents a rare example of a UFI, providing valuable evidence into extreme and/or nonstandard accretion processes near supermassive black holes. …”
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Improving Railway Track Detection With a Mixed-Modality Deep Learning Approach by Wichian Ooppakaew, Jakkrit Onshaunjit, Saifun Khrueakhrai, Jakkree Srinonchat

“…Despite the increased computational parameters, the improved models paradoxically enable quicker processing across all models.…”
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Near Miss Detection Using Distancing Monitoring and Distance-Based Proximal Indicators by Lek Ming Lim, Lu Yang, Wen Zhu, Ahmad Sufril Azlan Mohamed, Majid Khan Majahar Ali

“…Despite efforts to improve road safety, accidents persist due to insufficient evidence from manual police reporting, non-optimized detection algorithms, and technical limitations in real-time video processing and modelling. …”
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Mechanisms for Securing Autonomous Shipping Services and Machine Learning Algorithms for Misbehaviour Detection by Marwan Haruna, Kaleb Gebremichael Gebremeskel, Martina Troscia, Alexandr Tardo, Paolo Pagano

“…On one side, our solution is intended to secure communication channels between the SCCs and the vessels using Secure Exchange and COMmunication (SECOM) standard; on the other side, it aims to secure the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly and intrusion detection. …”
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CD4C: Change Detection for Remote Sensing Image Change Captioning by Xiliang Li, Bin Sun, Zhenhua Wu, Shutao Li, Hu Guo

“…Subsequently, based on whether changes are detected, samples are classified and processed through the C-Stream and N-Stream of the multitemporal difference feature fusion (MDF) module to extract visual change features. …”
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Time Series Foundation Model for Improved Transformer Load Forecasting and Overload Detection by Yikai Hou, Chao Ma, Xiang Li, Yinggang Sun, Haining Yu, Zhou Fang

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The Sulfur Plume in the Horsehead Nebula: New Detections of S2H, SH+, and CO+ by A. Fuente, G. Esplugues, P. Rivière-Marichalar, D. Navarro-Almaida, R. Martín-Doménech, G. M. Muñoz-Caro, A. Sánchez-Monge, A. Taillard, H. Carrascosa, J. J. Miranzo-Pastor, A. Tasa-Chaveli, P. Fernández-Ruiz, V. V. Guzmán, J. R. Goicoechea, M. Gerin, J. Pety

“…Instead, we propose that S _2 H is desorbed from irradiated grain surfaces by nonthermal processes. The SH ^+ detection indicates that sulfur is not significantly depleted at the UV-irradiated edge of the molecular cloud, arguing against a major refractory sulfur reservoir in the interior of molecular clouds.…”
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Transformer-Based Vulnerability Detection in IoT Firmware Binaries Using Opcode Sequences by M. Nandish, Jalesh Kumar, H. G. Mohan, M. V. Manoj Kumar

“…Firmware security is critical for maintaining the integrity of embedded systems. However, detecting vulnerabilities in firmware binaries is a challenging task. …”
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Research on object detection and recognition in remote sensing images based on YOLOv11 by Lu-hao He, Yong-zhang Zhou, Lei Liu, Wei Cao, Jian-hua Ma

“…Future studies will focus on expanding the dataset, refining the model architecture, and improving its performance in detecting small targets and processing complex scenes, paving the way for its broader applications in environmental protection, urban planning, and multiobject detection.…”
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AI-Driven Improvements in Electrochemical Biosensors for Effective Pathogen Detection at Point-of-Care by Inderpreet Singh, Asmita Gupta, Chansi Gupta, Ashish Mani, Tinku Basu

“…The rapid and accurate detection of pathogens is vital for effective disease management and control. …”
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Deep Learning for Automatic Detection of Volcanic and Earthquake-Related InSAR Deformation by Xu Liu, Yingfeng Zhang, Xinjian Shan, Zhenjie Wang, Wenyu Gong, Guohong Zhang

“…Deep learning has revolutionized data analysis, offering exceptional capabilities for processing large datasets. Leveraging these advancements, automatic detection of volcanic and earthquake deformation from extensive InSAR datasets has emerged as a major research focus. …”
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First Detection of Low-frequency Striae in Interplanetary Type III Radio Bursts by Vratislav Krupar, Eduard P. Kontar, Jan Soucek, Lynn B. Wilson III, Adam Szabo, Oksana Kruparova, Hamish A. S. Reid, Mychajlo Hajos, David Pisa, Ondrej Santolik, Milan Maksimovic, Jolene S. Pickett

“…These low-frequency fine structures, which drift slowly in frequency and exhibit narrow bandwidths, provide a novel diagnostic of plasma processes in the inner heliosphere. The detected striae, interpreted as fundamental plasma emission, exhibit a frequency drift rate of 0.328 Hz s ^−1 and a bandwidth of 1.3 kHz. …”
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SwinSegFormer: Advancing Aerial Image Semantic Segmentation for Flood Detection by Muhammad Tariq Shaheen, Hafsa Iqbal, Numan Khurshid, Haleema Sadia, Nasir Saeed

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Qseek: A data-driven Framework for Automated Earthquake Detection, Localization and Characterization by Marius Isken, Sebastian Heimann, Peter Niemz, Jannes Münchmeyer, Simone Cesca, Hannes Vasyura-Bathke, Torsten Dahm

“… We introduce a data-driven method and software for detecting and locating earthquakes in large seismic datasets. …”
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CLINICO PATHOLOGICAL STUDY AND MOLECULAR DETECTION OF IBD INFECTED BROILERS IN BASRAH PROVINCE by Dheyaa abbas abdali, Waleed Majeed Seger Almayahi

“…Upon the clinical finding and postmortemlesions of the necropsied birds; bursa of fabricius, kidney, Junction between gizzardand proventriculus and thigh muscles were processed for histopathological andmolecular detection with PCR. …”
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Airport Clearance Detection Based on Vision Transformer and Multi-Scale Feature Fusion by Yutong Chen, Yufen Liu, Zhixiong Guo, Qiang Gao

“…Finally, improve the loss function to enhance the ability of bounding box regression processing. The experimental results show that the model achieves high detection accuracy which has reached mAP@0.5 at 93.7%, an improvement of 5.4% compared to YOLOv8n.…”
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Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…This paper presents a novel algorithm that leverages cutting-edge machine-learning techniques to accurately and efficiently detect AI-generated texts. Rapid advancements in natural language processing models have led to the generation of text closely resembling human language, making it increasingly difficult to differentiate between human and AI-generated content. …”
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Ultrasensitive Detection of Biomarkers Based on Anisotropic Gold Nanorods and Dark-Field Imaging by Chaoshan Zhao, Shunbo Li

“…However, these methods have certain limitations, such as low sensitivity, poor stability, complex processes, and long reaction time. In recent years, the imaging technique combined with precious metal and dark-field microscopy has gained popularity in the field of highly sensitive biochemical detection due to its high spatiotemporal resolution and independence of signal reporter molecules. …”
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Automatic plant disease detection using computationally efficient convolutional neural network by Muhammad Rizwan, Samina Bibi, Sana Ul Haq, Muhammad Asif, Tariqullah Jan, Mohammad Haseeb Zafar

“…Alternatively, automatic approaches utilize 2D plant images processed through machine learning. The current study opts for the later approach due to its advantages in terms of speed, efficiency, and convenience. …”
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SDA-YOLO: An Object Detection Method for Peach Fruits in Complex Orchard Environments by Xudong Lin, Dehao Liao, Zhiguo Du, Bin Wen, Zhihui Wu, Xianzhi Tu

“…To address insufficient feature fusion flexibility caused by scale variations from occlusion and illumination differences in multi-scale peach detection, a novel Adaptive Multi-Scale Fusion Pyramid (AMFP) module is proposed to enhance the neck network, improving flexibility in processing complex features. …”
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