Wearable MXene-enhanced organic Bio-FET paper patch for glucose detection in sweat with pH and temperature calibration by Milad Farahmandpour, Zoheir Kordrostami

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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Information required to populate the models included the prevalence of lung nodules, risk of lung cancer with different nodule sizes, sensitivity and specificity for nodule detection, nodule type and size distributions in different population, resource use, costs and utilities. …”
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Unveiling the placental bacterial microbiota: implications for maternal and infant health by Zhuojun Xie, Zhongsheng Chen, Yang Chai, Wang Yao, Guangyu Ma

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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…For the detection head, a Generalized Wasserstein Distance Loss (GWDLoss) function is proposed to quantify positional and scale discrepancies, improving the adaptability of bounding box regression to geometric variations. …”
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A Fault-Tolerant Localization Method for 5G/INS Based on Variational Bayesian Strong Tracking Fusion Filtering with Multilevel Fault Detection by Zhongliang Deng, Ziyao Ma, Haiming Luo, Jilong Guo, Zidu Tian

“…Sudden and gradual faults were quickly detected through a dual-channel pre-check, and then, the fault source was identified through AIME. …”
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Location and function of TDP-43 in platelets, alterations in neurodegenerative diseases and arising considerations for current plasma biobank protocols by Ruth Luthi-Carter, Sara Cappelli, Morgan Le Roux-Bourdieu, Noemie Tentillier, James P. Quinn, Tiziana Petrozziello, Lathika Gopalakrishnan, Purva Sethi, Himanshi Choudhary, Giorgia Bartolini, Elias Gebara, Cristiana Stuani, Laure Font, Jiyan An, Vanessa Ortega, Jessica Sage, Edina Kosa, Bianca A. Trombetta, Roberto Simeone, Tamara Seredenina, Tariq Afroz, James D. Berry, Steven E. Arnold, Becky C. Carlyle, Oskar Adolfsson, Ghazaleh Sadri-Vakili, Emanuele Buratti, Robert Bowser, Abdulbaki Agbas

“…Here, we explore its tractability as a plasma biomarker of disease and describe its localization and possible functions in the cytosol of platelets. Novel TDP-43 immunoassays were developed on three different technical platforms and qualified for specificity, signal-to-noise ratio, detection range, variation, spike recovery and dilution linearity in human plasma samples. …”
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The Advanced Role of Carbon Quantum Dots in Nano-Food Science: Applications, Bibliographic Analysis, Safety Concerns, and Perspectives by Abdul Majid, Khurshid Ahmad, Liju Tan, Waqas Niaz, Wang Na, Li Huiru, Jiangtao Wang

“…This article discussed the sources, fabrication methods, advantages, and limitations of CQDs as a sensing for the detection of food contaminants. …”
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Karbon dots (C-dots) dari Bahan Hayati untuk Deteksi Logam Berat by Cut Navita Rahmi, Sri Sugiarti, Alvian Dea Yuliani

“…This study aims to review carbon nanoparticles derived from natural sources for detecting heavy metals. C-dots derived from biological sources have been widely studied as selective heavy metal detection. …”
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THE SUCCESS OF SATELLITE GRAVIMETRY IN GEOPHYSICAL INVESTIGATIONS by Ahmad Alhassan, Okoro Ernest chidi, Mohammed Auwal Adamu, Salisu Tata, Muhammad Shettima Nur, Auwal Aliyu, Yusuf Abdulhameed

“…The successful geophysical researches carried out using satellite acquired gravity data from existing literature were also discussed. …”
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Thermonuclear Superburst of MAXI J1752−457 Observed with NinjaSat and MAXI by Amira Aoyama, Teruaki Enoto, Takuya Takahashi, Sota Watanabe, Tomoshi Takeda, Wataru Iwakiri, Kaede Yamasaki, Satoko Iwata, Naoyuki Ota, Arata Jujo, Toru Tamagawa, Tatehiro Mihara, Chin-Ping Hu, Akira Dohi, Nobuya Nishimura, Motoko Serino, Motoki Nakajima, Takao Kitaguchi, Yo Kato, Nobuyuki Kawai, (NinjaSat collaboration)

“…An uncatalogued bright X-ray transient was detected with MAXI on 2024 November 9, named MAXI J1752−457. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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Design of a Non-Destructive Seed Counting Instrument for Rapeseed Pods Based on Transmission Imaging by Shengyong Xu, Rongsheng Xu, Pan Ma, Zhenhao Huang, Shaodong Wang, Zhe Yang, Qingxi Liao

“…Human–machine interaction software based on PyQt5 was developed, integrating functions such as communication between upper and lower machines, image acquisition, storage, and processing. …”
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Segmentation-Based Detection for Luffa Seedling Grading Using the Seg-FL Model by Sheng Jiang, Fangnan Xie, Jiangbo Ao, Yechen Wei, Jingye Lu, Shilei Lyu, Zhen Li

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Mid-Water Ocean Current Field Estimation Using Radial Basis Functions Based on Multibeam Bathymetric Survey Data for AUV Navigation by Jiawen Liu, Kaixuan Wang, Shuai Chang, Lin Pan

“…This makes unknown ocean currents a significant error source that leads to substantial cumulative positioning errors. …”
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DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model by Panpan Jiang, Xiaohua Yang, Yaping Wan, Tiejun Zeng, Mingxing Nie, Zhenghai Liu

“…Achieving real-time detection with high accuracy, while accommodating the limited resources of edge-computing devices poses a significant challenge for anti-UAV detection. …”
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Innovative Sandia Frequency Shift Islanding Detection for Microgrids Using Interval Type-II Fuzzy Logic and VP-PSO Optimization by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Yeonwoo Lee, Sun-Kyoung Kang, Ilhami Colak, El Manaa Barhoumi, Kei Eguchi

“…The proposed approach further integrates a variable-parameter PSO (VP-PSO) algorithm to optimize both fuzzy membership functions and controller parameters. Comprehensive simulations demonstrate 100% detection accuracy for both PV and wind farm islanding scenarios, significantly outperforming conventional methods: standard SFS (84-86%), type-1 fuzzy SFS (89-91%), and neural network approaches (94-95%). …”
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Leveraging Multimodal Large Language Models (MLLMs) for Enhanced Object Detection and Scene Understanding in Thermal Images for Autonomous Driving Systems by Huthaifa I. Ashqar, Taqwa I. Alhadidi, Mohammed Elhenawy, Nour O. Khanfar

“…Two primary research questions are addressed: the capacity of these models to detect and enumerate objects within thermal images, and to determine whether pairs of image sources represent the same scene. …”
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A deep learning based intrusion detection system for CAN vehicle based on combination of triple attention mechanism and GGO algorithm by Hongwei Yang, Mehdi Effatparvar

“…Within the initial phase, the major features have been extracted, and TAN functions as a descriptor of feature. Then, the discriminating categorizer classifies the current features. …”
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Enhanced YOLOv7-Tiny for Small-Scale Fire Detection via Multi-Scale Channel Spatial Attention and Dynamic Upsampling by Shihao Wu, Yi Xia

“…Furthermore, the Focaler-IoU loss function is employed to focus the model on hard samples, enhancing the accuracy of small fire detection. …”
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The accuracy of a novel stunting risk detection application based on nutrition and sanitation indicators in children aged under five years by Tria Astika Endah Permatasari, Yudi Chadirin, Ernirita Ernirita, Anisa Nurul Syafitri, Devina Alifia Fadhilah

“…This study aimed to develop and evaluate the accuracy of a stunting risk detection application based on nutrition and sanitation indicators in children aged under five years. …”
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