Application of microscopic smartphone attachment for remote preoperative lab testing by Kefan Song, Kefan Song, Alexander T. Adams, Alexander T. Adams

“…The system’s cell counting algorithm was tailored to process the captured images, featuring a streamlined workflow that includes image processing and automated cell detection using a Hough circle algorithm.ResultsThe new system provided good-quality raw images with 26.3 px/μm pixel resolution and 2.19 μm spatial resolution, facilitating effective cell recognition and counting. …”
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An Efficient In Vitro Regeneration Protocol and the Feature of Root Induction with Phloroglucinol in <i>Paeonia ostii</i> by Keyuan Zheng, Luming Yao, Yumei Xie, Shuiyan Yu, Yonghong Hu, Mulan Zhu

“…However, significant challenges persist in tissue culture, particularly with regards to the reproduction coefficient of shoots and the rooting process. This study reports an efficacious protocol for <i>P. ostii</i> micropropagation, focusing on in vitro root development facilitated through the application of phloroglucinol (PG). …”
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Indoor and Outdoor Air Microbial Contamination During Different Reconstruction Methods of Historic Buildings by Anett Lippai, Ádám Leelőssy, Donát Magyar

“…In both buildings, elevated concentrations of airborne fungi were detected during the main reconstruction period. The fungal genera found in the indoor air were also detected on surfaces and in dust samples. …”
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Unraveling the neural dynamics of mathematical interference in english reading: A novel approach with deep learning and fNIRS data by Zhijie Liang, Ling Wang, Jianyu Su, Bo Sun, Daifa Wang, Juan Yang

“…Furthermore, crucial brain channels for interference detection are pinpointed through grid search, and alterations in vital brain regions (R-Broca and L-Broca) are unveiled via association rule analysis. …”
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Advancements in Aircraft Engine Inspection: A MEMS-Based 3D Measuring Borescope by Jonathan Gail, Felix Kruse, Shanshan Gu-Stoppel, Ole Schmedemann, Günther Leder, Wolfgang Reinert, Lena Wysocki, Nils Burmeister, Lars Ratzmann, Thorsten Giese, Patrick Schütt, Gundula Piechotta, Thorsten Schüppstuhl

“…A critical part of this inspection process is accurately measuring any detected damage to determine whether it exceeds allowable limits. …”
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Artificial intelligence applied to precision livestock farming: A tertiary study by Damiano Distante, Chiara Albanello, Hira Zaffar, Stefano Faralli, Domenico Amalfitano

“…To this end, a tertiary systematic mapping study was conducted following recognized guidelines to ensure reliability and replicability. The research process involved formulating 10 research questions, designing a comprehensive search strategy, and performing a rigorous quality assessment of the identified studies. …”
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Rationalizing the Unexpected Inefficiencies of 3D Porphyrin‐MOFs as Singlet Oxygen Photosensitizers Against Botrytis cinerea by Océane Boudreau, Paul Asselin, Seyed Mehrzad Sajjadinezhad, Paul‐Ludovic Karsenti, Peter Moffett, Kamal Bouarab, Pierre D. Harvey

“…This in‐depth study examines the direct detection of 1O2(g) phosphorescence at the solid–air interface, binding of the PMOFs with the spores of B. cinerea by fluorescence microscopy, fluorescence quenching of the PMOFs by oxygen, and rates of exciton migration evaluated through the singlet‐singlet annihilation process. …”
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Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

“…However, this research demonstrates the strong efficacy of the CNN model in handling complicated image data, making it a more sophisticated tool for osteoporosis detection.…”
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Mapping <i>Polylepis</i> Forest Using Sentinel, PlanetScope Images, and Topographical Features with Machine Learning by Diego Pacheco-Prado, Esteban Bravo-López, Luis Á. Ruiz

“…The findings confirm that, despite the limited area of the <i>Polylepis</i> stands, integrating topographic and spectral variables at a 10 m pixel resolution improves detection accuracy.…”
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A Robust joint coverless image steganography scheme based on two independent modules by Chang Ren, Bin Wu

“…Due to the irreversibility of the process of generating secret images from message codeword, the recovery accuracy of the latter is very poor. …”
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MYLK-AS1 improves fracture by targeting miR-146a-5p to regulate cell viability and apoptosis in osteoblasts by Wuluhan Mahan, Haoze Gao, Ning Liu, Zhenyu Zhao, Yingxuan Huang

“…Therefore, early diagnosis and detection are important for the treatment of DFH. The long non-coding RNA (LncRNA) MYLK-AS1 is abnormally expressed in patients with DFH and has the potential to be used as a diagnostic marker. …”
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Core-Sheath Structured Yarn for Biomechanical Sensing in Health Monitoring by Wenjing Fan, Cheng Li, Bingping Yu, Te Liang, Junrui Li, Dapeng Wei, Keyu Meng

“…Here, we present a bioinspired, hierarchically structured core-sheath yarn sensor (CSSYS) engineered through an efficient dip-coating process, which synergistically integrates the two-dimensional conductive MXene nanosheets and one-dimensional silver nanowires (AgNWs). …”
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Determination of Sulfur in Fly Ash by High Frequency Combustion Infrared Absorption Spectroscopy with Matrix Matching by Weiting CAI, Junpeng SONG, Minghui ZHANG, Anli WANG, Wenna RONG, Bei LI

“…The sulfur content in fly ash is determined by the barium sulfate mass method, which has a complicated process, complicated operation, and strict requirements for personnel and operation. …”
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A Highly Sensitive NiO Flexible Temperature Sensor Prepared by Low-Temperature Sintering Electrohydrodynamic Direct Writing by Ting Wang, Xianruo Du, Gaofeng Zheng, Zhiyuan Xue, Junlin Zhang, Huatan Chen, Libo Gao, Wenwang Li, Xiang Wang, Yifang Liu, Jiaxin Jiang

“…However, the current flexible temperature sensor preparation generally suffers from process complexity, which limits its development and application. …”
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Federated learning and GWO-enabled consumer-centric healthcare internet of things for pancreatic tumour by Nuha Alruwais, Ghada Moh. Samir Elhessewi, Muhammad Kashif Saeed, Menwa Alshammeri, Othman Alrusaini, Abdulwhab Alkharashi, Samah Al Zanin, Yahia Said

“…Grading can be a tedious and time-consuming process for experts and doctors when the case is complex. …”
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Dynamic hand and finger load distribution patterns in the first year following surgically treated distal radius fracture by Johannes Karnatz, Christoph Harms, Dagmar-Christiane Fischer, Thomas Mittlmeier

“…Analysis of changes in grip patterns following a distal radius fracture provides a new perspective on documenting the recovery process of this common injury. Our aim was also to investigate the relationships between load distribution during a maximum force grip and other hand function parameters to better understand the implications for follow-up and rehabilitation. …”
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Effect of Systematic Errors on Building Component Sound Insulation Measurements Using Near-Field Acoustic Holography by Wei Xiong, Wuying Chen, Zhixin Li, Heyu Zhu, Xueqiang Wang

“…However, based on Green’s function, the microphone array’s inherent amplitude and phase mismatch errors will exponentially amplify the sound field inversion process, significantly reducing the measurement accuracy. …”
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Development of a fluorophilic ion-exchange material with dual binding mechanism for solid-phase extraction of PFAS by Johanna Freilinger, Jan O. Back, Raphael Plangger, Herwig Schottenberger, Christian W. Huck, Marco Rupprich, Rania Bakry

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Deterministic quantum dot cavity placement using hyperspectral imaging with high spatial accuracy and precision by Quirin Buchinger, Constantin Krause, Aileen Zhang, Giora Peniakov, Mohamed Helal, Yorick Reum, Andreas Theo Pfenning, Sven Höfling, Tobias Huber-Loyola

“…We introduce periodic alignment markers for improved marker detection accuracy and investigate overall imaging accuracy achieving (9.1 ± 2.5) nm through image correction. …”
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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

“…The blending is flexible, and it is controlled by a parameter α, hence the process is termed as alpha blending. The utilization of alpha blending facilitates the generation of a composite feature set that incorporates different characteristics from both the scalogram and binary versions.ResultsFor experiments, a total of 162 ECG recordings from the PhysioNet database were used. …”
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