Citrus diseases detection using innovative deep learning approach and Hybrid Meta-Heuristic. by Nouman Butt, Muhammad Munwar Iqbal, Shabana Ramzan, Ali Raza, Laith Abualigah, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…The proposed framework outperforms existing methods, offering a robust and scalable solution for disease detection in citrus farming, contributing to more sustainable agricultural practices.…”
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Retracted: A Microgrid Security Defense Method Based on Cooperation in an Edge-Computing Environment by Journal of Electrical and Computer Engineering

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Rapid and simple detection of Candida albicans using closed dumbbell-mediated isothermal amplification by Yanli Zhang, Xuhan Chen, Yeling Zhong, Fei Guo, Guifang Ouyang, Rui Mao

“…In addition, the CA-OL-CDA method holds potential in on-site detection for C. albicans using color shift by adopting the reaction mixture based on HNB.…”
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Nanomaterials based biosensors applied for detection of aflatoxin B1 in cereals: a review by Loyce Namanya, Emma Panzi Mukhokosi, Ediriisa Mugampoza

“…Different biosensors have been fabricated using various nanoparticles to detect aflatoxins in food. This review provides the recent developments on the occurrence of AFB1 in cereals, different biosensors based on nanomaterials applied for AFB1 detection in cereals, and offers future directions for the production of affordable analytical equipment for detection of AFB1, based on nanomaterials to address some open questions regarding their limit of detection, stability, and affordability. …”
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A novel feature extraction method based on dynamic handwriting for Parkinson's disease detection. by Huimin Lu, Guolian Qi, Dalong Wu, Chenglin Lin, Songzhe Ma, Yingqi Shi, Han Xue

“…Given the easy accessibility of handwriting samples, many researchers have proposed handwriting-based detection methods for Parkinson's disease. Extracting more discriminative features from handwriting is an important step. …”
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Detecting Latent Topics and Trends in Global Publications on Brucellosis Disease Using Text Mining by Meisam Dastani, Jalal Mardaneh, Omid Pouresmaeil

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Unified Dynamic Dictionary and Projection Optimization With Full-Rank Representation for Hyperspectral Anomaly Detection by Hongran Li, Chao Wei, Yizhou Yang, Zhaoman Zhong, Ming Xu, Dongqing Yuan

Subjects: “…hyperspectral anomaly detection (HAD)…”
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A Star‐Nose‐Inspired Bionic Soft Robot for Nonvisual Spatial Detection and Reconstruction by Qiwei Shan, Yunqi Cao, Haozhen Chi, Shuyu Fan, Ziying Zhu, Dibo Hou

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VulMPFF: A Vulnerability Detection Method for Fusing Code Features in Multiple Perspectives by Xiansheng Cao, Junfeng Wang, Peng Wu, Zhiyang Fang

“…Existing deep learning-based detection methods have proven their effectiveness. …”
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Defense against Feeding by Spring Aphid Parasitism in the Upper Leaf Parts of Host Plants by Yuuka Murakami, Hisashi Kawai, Akane Shindo, Eisuke Hasegawa

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Preparation of Restricted Access Media-Molecularly Imprinted Polymers for the Detection of Chloramphenicol in Bovine Serum by Shanwen Zhao, Chanling Wei, Zhian Sun, Huachun Liu, Yanqiang Zhou, Xiaoxiao Wang, Jianmin Li, Bolin Gong

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Preparation of specific components of Elisa test-system for detection of Schmallenberg desease virus antigens by O. G. Gubenko, O. P. Bjadovskaya, S. V. Kononova, Yu. Yu. Babin, N. A. Soloukhina, A. V. Kononov

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Coproantigen detection and molecular identification of Cryptosporidium species among newborn and adult farm animals by Dina Aboelsoued, Nagwa I. Toaleb, Kadria N. Abdel Megeed

“…Therefore, this study aimed to evaluate an early diagnosis of cryptosporidiosis using the anti-Cryptosporidium parvum oocyst immunoglobulin IgG polyclonal antibodies (anti-C. parvum IgG PAbs)-based sandwich enzyme-linked immunosorbent assay (ELISA) for the detection of Cryptosporidium oocyst antigens in fecal samples of farm animals in Egypt. …”
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Grassmannian Constellation Based on Antipodal Points and Orthogonal Design and Its Simplified Detecting Algorithm by Li Peng, Dacong Hu, Lin Zhang, Zhen Qin

“…The antipodal constellation enables an intrinsic simplified ML detecting algorithm. The algebraic orthogonal USTM constellation is also an antipodal constellation which, apart from being adaptive to the antipodal simplified ML detector, also has another simplified ML detector based on its self-indexing features, and the latter is simpler because of getting rid of the matrix operation. …”
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Inflammasomes, Autophagy, and Cell Death: The Trinity of Innate Host Defense against Intracellular Bacteria by Teresa Krakauer

“…Inflammasome activation is an innate host defense mechanism initiated upon sensing pathogens or danger in the cytosol. …”
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Implementation of lightweight intrusion detection model for security of smart green house and vertical farm by Jun-Ho Huh

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Subspace Method Aided Data-Driven Fault Detection Based on Principal Component Analysis by Lingling Ma, Xiangshun Li

“…The model-based fault detection technique, which needs to identify the system models, has been well established. …”
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Detection of mite infested saffron plants using aerial imaging and machine learning classifier by Hossein Sahabi, Jalal Baradaran-Motie

“… Aim of study: To evaluate and develop a machine learning code that uses aerial images in visible and near infrared (NIR) spectra to detect mite-infested Saffron (Crocus sativus L.) plants through processing the spectral indices to classify healthy and diseased plants. …”
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Detection of Emerging Faults on Industrial Gas Turbines Using Extended Gaussian Mixture Models by Yu Zhang, Chris Bingham, Miguel Martínez-García, Darren Cox

“…This paper extends traditional Gaussian mixture model (GMM) techniques to provide recognition of operational states and detection of emerging faults for industrial systems. …”
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Differentiation of high risk prostate cancer with a facile urinary exosome detection workflow by Shuai Qiu, Yue Li, Zheng Zhang, Chunchang Li, Haoyu Wang, Ao Chen, Zhi Yan, Yang Liu, Zifei Li, Hua Huang, Yi Liu, Yiqi Seow, Ruibing Chen, Jinhong Guo, Simeng Wen, Jing Tian, Hongtuan Zhang, Ranlu Liu, Gang Han, Baolong Wang, Yong Wang, Yuanjie Niu, HaiFang Yin

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