Retrospective study on NIPT or NIPT plus combined with ultrasound in screening fetal chromosomal abnormalities by Meilin Chen, Peisong Chen, Siyang Yu, Lu Ai, Xuegao Yu, Ruizhi Wang, Jinghai Yan, Shaobin Lin

“…False negatives were more prevalent in standard NIPT, particularly for SCA, MMS, and RAT, emphasizing its limitations for detecting complex chromosomal abnormalities. NIPT plus, when combined with ultrasound, offers significant improvements in the detection of rare chromosomal abnormalities like SCA, MMS, and RAT, while maintaining high detection rates for common trisomies. …”
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PAPR Reduction in DCO-OFDM Visible Light Communication Systems Using Optimized Odd and Even Sequences Combination by Wei-Wen Hu

“…Simulation results show that the proposed scheme can achieve comparable PAPR reduction performance with the conventional selected mapping (CSLM) scheme with random and chaotic sequences, but at a considerably low computational complexity. Moreover, the proposed blind SI detection scheme provides almost the same bit error rate (BER) performance as that of the CSLM scheme with a perfect SI detection and symmetric selected mapping for a DCO-OFDM VLC system with 1024 subcarriers and 16-QAM. …”
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Applying a system dynamics approach for decision-making in software testing projects. by Wang Li, Chih-Chiang Fang

“…This includes factors such as resource allocation, testing efficiency, error detection rates, and the feedback loops among these elements. …”
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Sugarcane leaf disease classification using deep neural network approach by Saravanan Srinivasan, S. M. Prabin, Sandeep Kumar Mathivanan, Hariharan Rajadurai, Suresh Kulandaivelu, Mohd Asif Shah

“…Discussion The study demonstrates the effectiveness of DL models, particularly EfficientNet-B7 and DenseNet201, for fast, accurate, and automatic disease detection in sugarcane leaves. …”
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A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

“…Conclusion The proposed approach offers an efficient solution for early detection of CHD by identifying critical indicators, reducing diagnostic complexity, and improving predictive accuracy, thus potentially leading to more effective CHD management.…”
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Mapping the Global Public Health Intelligence Landscape, 2023 by Mrs Alba Mendez Brito, Mrs Romy Kerber, Dr Angela Fehr, Mrs Sarah Esquevin, Dr Andreas Jansen, Dr Carlos L Correa-Martínez

“…Introduction: Public health intelligence (PHI) is becoming increasingly crucial for early threat detection, leveraging efficient identification and information exchange. …”
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Rethinking feature representation and attention mechanisms in intelligent recognition of leaf pests and diseases in wheat by Yuhan Zhang, Dongsheng Liu

“…RReNet captures key information more efficiently by focusing on complex pest and disease characteristics and fusing multi-semantic feature information. …”
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A Fire Segmentation Method with Flame Detail Enhancement U-Net in Multispectral Remote Sensing Images Under Category Imbalance by Rui Zou, Zhihui Xin, Guisheng Liao, Penghui Huang, Rui Wang, Yuhu Qiao

“…Additionally, Haar wavelet downsampling is applied to retain image detail and improve the detection of small-scale flame regions. Experimental results show that the FDE U-Net model exhibits robust performance in fire detection, accurately extracting flame regions even when their proportion is low and the background is complex. …”
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Micro- and Nano-Plastics in Drinking Water: Threat or Hype? Critical State-of-the-Art Analysis of Risks and Approaches by Andrea G. Capodaglio

“…MP decomposition generates smaller nanoplastics (NPs) with different properties, closer to engineered nanoparticles than to MP. Their detection is more complex and laborious than MP’s, and, as such, their fate and effects are still poorly studied. …”
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Field programmable silicon microring WDM transceiver leveraging monolithically integrated phase-change materials by Xing Yang, Shihuan Ran, Ziquan Li, Liangjun Lu, Yu Li, Ngon Phu Wai, MingHua Zhang, Guo-Qiang Lo, Jianping Chen, Linjie Zhou

“…These advancements position Sb2Se3-integrated MRRs as a promising solution for large-scale, energy-efficient photonic transceivers in next-generation optical communication systems.…”
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Defect intelligent recognition of membrane product based on deep learning by Maonian Wu, Ling Li, Wei Peng, Tao Wu, Jinwei Yu, Bo Zheng, Shaojun Zhu

“…This enhances the recognition accuracy of bounding boxes, ensuring that the model maintains high detection accuracy even after complex scenarios. Moreover, the proposed methodology exhibits broad applicability across a wide spectrum of prevalent defect detection paradigms. …”
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Text Removal for Trademark Images Based on Self-Prompting Mechanisms and Multi-Scale Texture Aggregation by Wenchao Zhou, Xiuhui Wang, Boxiu Zhou, Longwen Li

“…These mechanisms are capable of efficiently extracting multilevel features and multiscale textual information, which enhances the model’s stability and adaptability in complex scenarios. …”
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The analysis of landscape design and plant selection under deep learning by Lian Li, JiYon Lee

“…The key innovation of this paper lies in the first application of multi-scale feature fusion and attention mechanisms within the FCN model, effectively improving the segmentation capability of complex landscape images. Moreover, background noise interference is reduced by using object detection techniques. …”
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Camera Pose Generation Based on Unity3D by Hao Luo, Wenjie Luo, Wenzhu Yang

“…Deep learning models performing complex tasks require the support of datasets. With the advancement of virtual reality technology, the use of virtual datasets in deep learning models is becoming more and more widespread. …”
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JET: Fast Estimation of Hierarchical Time Series Clustering by Phillip Wenig, Mathias Höfgen, Thorsten Papenbrock

“…One such application is the development of jet engines, which involves numerous test runs and failure detection processes. While effective data mining algorithms exist for the detection of anomalous and structurally conspicuous test recordings, these algorithms do not perform any semantic labeling. …”
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Optimised Extension of an Ultra-Low-Power RISC-V Processor to Support Lightweight Neural Network Models by Qiankun Liu, Sam Amiri

“…With the increasing demand for efficient deep learning models in resource-constrained environments, Binary Neural Networks (BNNs) have emerged as a promising solution due to their ability to significantly reduce computational complexity while maintaining accuracy. …”
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Precision medicine in oncology: role and prospects of mass spectrometry by E. S. Khmelevskaya, E. A. Perina, E. E. Buyko, A. A. Ufandeev, O. A. Kaidash, V. V. Ivanov, A. N. Baikov, E. V. Parochkina, E. V. Udut

“…Mass spectrometry is becoming an indispensable tool in basic and applied research due to its sensitivity, specificity, and accuracy. It allows for efficient analysis of complex biological compounds, even at low concentrations. …”
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Developing an ISO11783-compliant prescription map for variable rate spraying in vineyards based on 3D canopy reconstruction by Björn Poss, Nikos Tsoulias, Galibjon M. Sharipov, Andreas Heiß, Dimitrios S. Paraforos

“…With the advent of the digital era in viticulture and the use of increasingly complex implements from different manufacturers, a standardised communication interface is essential. …”
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Highly customizable, ultrawide-temperature free-form flexible sensing electronic systems based on medium-entropy alloy paintings by Weiwei Li, Yingzhe Li, Manzhang Xu, Yilin Zhou, Ruoyan Miao, Kexin Wang, Yunqiang Cao, Yizhong Song, Siying Dang, Lu Zheng, Xuewen Wang, Wei Huang

“…Abstract High-performance flexible sensing electronics on complex surfaces operating across broad temperatures are critical for aerospace and industrial applications. …”
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Unveiling smart contract vulnerabilities: Toward profiling smart contract vulnerabilities using enhanced genetic algorithm and generating benchmark dataset by Sepideh HajiHosseinKhani, Arash Habibi Lashkari, Ali Mizani Oskui

“…Many of them, such as rule-based methods, machine learning techniques, and neural networks, also struggle to detect complex vulnerabilities due to limited data availability. …”
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