Metal surface defect detection using SLF-YOLO enhanced YOLOv8 model by Yuan Liu, Yilong Liu, Xiaoyan Guo, Xi Ling, Qingyi Geng

“…Abstract This paper addresses the industrial demand for precision and efficiency in metal surface defect detection by proposing SLF-YOLO, a lightweight object detection model designed for resource-constrained environments. …”
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Loss Function Optimization Method and Unsupervised Extraction Approach D-DBSCAN for Improving the Moving Target Perception of 3D Imaging Sonar by Jingfeng Yu, Aigen Huang, Zhongju Sun, Rui Huang, Gao Huang, Qianchuan Zhao

“…Compared to 2D sonar images, 3D sonar images offer superior spatial positioning capabilities, although the data acquisition cost is higher and lacks open source references for data annotation, target detection, and semantic segmentation. …”
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An Embodied Intelligence System for Coal Mine Safety Assessment Based on Multi-Level Large Language Models by Yi Sun, Faxiu Ji

“…By leveraging the tool invocation and reasoning capabilities of LLM in conjunction with a coal mine safety knowledge base, the system achieves logical inference, anomalous data detection, and potential safety risk prediction. Furthermore, its memory functionality ensures the learning and utilization of historical experiences, providing a solid foundation for continuous assessment processes. …”
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The Impact of Differences in Renovation Models of Abandoned Boiler Rooms on Community Vitality—A Case Study of Shenyang, China by Lei Chen, Yahang Cheng, Zixi Zhou, Yibo Wen

“…Unlike prior studies that rely on single data sources or unidimensional metrics, our multi-source approach enhances spatiotemporal resolution, improves the accuracy of subjective perceptions, and enables cross-validation between objective behavioral trajectories and residents’ self-reports, thereby significantly strengthening the comprehensiveness and reliability of community vitality measurement. …”
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QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…To address these challenges, we present QPPLab, an open-source MATLAB-based toolbox for detecting, analyzing, and visualizing QPPs from fMRI time series. …”
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Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

“…Quality assessment and artifact detection in functional magnetic resonance imaging (fMRI) data is essential for clinical applications and brain research. …”
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Urban Traffic State Sensing and Analysis Based on ETC Data: A Survey by Yizhe Wang, Ruifa Luo, Xiaoguang Yang

“…The construction of multi-source data fusion frameworks enables effective complementarity between ETC data, floating car data, and video detection data, significantly improving traffic state estimation accuracy. …”
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Fine-grained building function recognition with street-view images and GIS map data via geometry-aware semi-supervised learning by Weijia Li, Jinhua Yu, Dairong Chen, Yi Lin, Runmin Dong, Xiang Zhang, Conghui He, Haohuan Fu

“…In this work, we propose a geometry-aware semi-supervised method for fine-grained building function recognition, which effectively uses multi-source geoinformation data to achieve accurate function recognition in both single-city and cross-city scenarios. …”
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MTAHG and MTBHG: Modified Approaches for Interpreting Gravity Data by Hazel Deniz Toktay, Hanbing Ai, Ahmad Alvandi, Kejia Su, Jinlei Li

“…This paper proposes two effective edge detection tools: one combining the balanced total horizontal gradient (BHG), and the hyperbolic tangent function, abbreviated as “MTBHG”; and the other combining the tilt angle of the total horizontal gradient (TAHG) and the hyperbolic tangent function, abbreviated as “MTAHG.” …”
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Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China by Yiheng Zang, Jing Chen, Muhammad Awais, Mukhtar Iderawumi Abdulraheem, Moshood Abiodun Yusuff, Kuan Geng, Yongqi Chen, Yani Xiong, Linze Li, Yanyan Zhang, Vijaya Raghavan, Jiandong Hu, Junfeng Wu, Guoqing Zhao

“…Soil nitrate nitrogen (NO₃⁻-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO₃⁻-N detection, but interference from complex soil organic matter affects its accuracy. …”
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Cloning and Functional Analysis of Skin Host Defense Peptides from Yakushima Tago’s Brown Frog (<i>Rana tagoi yakushimensis</i>) and Development of Serum Endotoxin Detection System... by Taichi Aono, Saki Tamura, Yua Suzuki, Taichi Imanara, Ryosei Niwa, Yoshie Yamane, Tetsuya Kobayashi, Sakae Kikuyama, Itaru Hasunuma, Shawichi Iwamuro

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Non-Line-of-Sight Location With Gauss Filtering Algorithm Based on a Model of Photon Flight by Yu Ren, Zongliang Xie, Yihan Luo, Shaoxiong Xu, Haotong Ma, Yi Tan

“…Recently, non-line-of-sight (NLOS) detection based on time of flight (TOF) has been investigated. …”
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Remote Sensing Extraction of Damaged Buildings in the Shigatse Earthquake, 2025: A Hybrid YOLO-E and SAM2 Approach by Zhimin Wu, Chenyao Qu, Wei Wang, Zelang Miao, Huihui Feng

“…Subsequently, SAM2 follows as a refinement step, incorporating shapefile information from pre-disaster sources to apply precise, pixel-level segmentation. …”
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CdZnTe- and TlBr-detectors response simulation for registration of the mixed beta- and gamma-radiation by A. I. Skrypnyk

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SegTrackDetect: A window-based framework for tiny object detection via semantic segmentation and tracking by Aleksandra Kos, Karol Majek, Dominik Belter

“…This work introduces SegTrackDetect, an open-source, window-based framework for small and tiny object detection. …”
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ENDOCRINE PANCREATIC FUNCTION IN ACUTE PANCREATITIS by P. V. Novokhatny

“…In a significant proportion of patients who recovered from acute pancreatitis, exocrine and endocrine functional impairments were found. This finding was not detected only in patients after severe acute pancreatitis. …”
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Systematic investigation of photon strength functions with monochromatic γ-ray beams by Gheorghe Ioana, Aumann Thomas, Baumann Martin, van Beek Patrick, Kuchenbrod Philipp, Lalić Nikolina, Scheit Heiko, Symochko Dmytro, Wang Hongwei, Fan Gongtao, Nishio Katsuhisa, Ohtsuki Tsutomu, Suzaki Fumi, Hirose Kentaro, Inagaki Makoto, Ari-izumi Takashi, Garrote Frank L. Bello, Bjørøen Marianne, Eriksen Tomas, Ingeberg Vetle Wegner, Paulsen Wanja, Pedersen Line G., Reaz Fardous, Belyshev Sergey, Stopani Konstantin, Lui Yiu-Wing, Filipescu Dan, Tudora Anabella, Goriely Stephane, Miyamoto Shuji, Utsunomiya Hiroaki

“…Following the main objective of the IAEA Coordinated Research Project on Photonuclear Data and Photon Strength Functions (Code F41032; Duration 2016-2019), new measurements of photoneutron and photofission cross sections in the Giant Dipole Resonance energy region have been performed at the laser Compton-scattering γ-ray source of the NewSUBARU synchrotron radiation facility. …”
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Sustainable Materials Enabled Terahertz Functional Devices by Baoning Wang, Haolan Wang, Ying Bao, Waqas Ahmad, Wenhui Geng, Yibin Ying, Wendao Xu

“…Highlights Sources and types of sustainable materials and their advantages in fabricating high performance terahertz (THz) functional devices are systematically reviewed. …”
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Mineral Content of Four Mexican Edible Flowers Growing in Natural Conditions and Backyards from Indigenous Communities by Rubí Marcos-Gómez, Araceli M. Vera-Guzmán, Mónica L. Pérez-Ochoa, Laura Martínez-Martínez, Sanjuana Hernández-Delgado, David Martínez-Sánchez, José L. Chávez-Servia

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Hardcoded vulnerability detection approach for IoT device firmware by Chao MU, Xin WANG, Ming YANG, Heng ZHANG, Zhenya CHEN, Xiaoming WU

“…With the popularization of IoT devices, more and more valuable data is generated.Analyzing and mining big data based on IoT devices has become a hot topic in the academic and industrial circles in recent years.However, due to the lack of necessary detection and protection methods, many IoT devices have serious information security risks.In particular, device hard-coded information is closely related to system encryption and decryption, identity authentication and other functions, which can provide confidentiality protection for core data.Once this information is exploited by malicious attackers, serious consequences such as sensitive information leakage, backdoor attacks, and unauthorized logins will occur.In response to this problem, a multi-type character recognition and positioning scheme was designed and a hard-coded vulnerability detection method in executable files was proposed based on the study of the characteristics of hard-coded vulnerabilities in IoT devices.The proposed method extracted the firmware of IoT devices and filtered all executable files as the source to be analyzed.Then, a solution to identify and locate three types of hard-coded characters was provided.Further, the reachability of the function, where the hard-coded character was located, was analyzed according to the function call relationship.Meanwhile, the instruction heterogeneity was mitigated by an intermediate representation (IR) model.The character and parameter hard-coded values was obtained through a data flow analysis approach.A symbolic execution method was devised to determine the trigger conditions of the hard-coded vulnerabilities, and then the vulnerability detection result was output.On the one hand, the proposed method introduced the method of symbolic execution based on the use of the intermediate representation model, which eliminated the dependency of instruction architecture and reduces the false positive rate of vulnerabilities; On the other hand, this method can integrate characters, files, and cryptographic implementation to realize the different characteristics of three types of hard-coded characters, which increased the coverage of vulnerability detection and improves the versatility of the detection method.The experimental results show that the proposed method can effectively detect three types of hard-coded vulnerabilities of characters, files and cryptographic implementation in various IoT devices, and has good detection accuracy, which can provide certain guidance for the deployment of subsequent security protection technologies.…”
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