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Deep Learning-Assisted Rapid Assessment of Food Freshness Using an Anti-interfering Triple-Emission Ratiometric Fluorescent Sensor

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ACS Sustainable Chemistry and engineering 2024年第6期12卷 2465-2475页

作者： Wu, Chun Chang, Hongrong Chen, Xianjin Yang, Si Dai, Yanfa Tan, Ping Chen, Yuhui Shen, Chengao Lu, Zhiwei Sun, Mengmeng Su, Gehong Wang, Yanying Zou, Yuanfeng Wang, Hui-Min David Rao, Hanbing Liu, Tao College of Science Sichuan Agricultural University Xinkang Road Yucheng District Ya’an625014 China College of Information Engineering Sichuan Agricultural University Xinkang Road Yucheng District Ya’an625014 China Wuxi School of Medicine Jiangnan University Binhu District Wuxi214122 China College of Veterinary Medicine Sichuan Agricultural University Huimin Road Wenjiang District Chengdu611130 China Graduate Institute of Biomedical Engineering National Chung Hsing University No. 145 Xingda Rd. South Dist. Taichung City402 Taiwan

The assessment of food freshness is of paramount significance for the maintenance of human health. However, the presence of an interfering background signal from food samples often leads to inevitable false negative results, which remains a formidable challenge in the rapid assessment of food freshness. To address this issue, a bioinspired anti-interfering triple-emission ratiometric fluorescent sensor was developed based on a deep learning strategy to enhance the signal-to-noise ratio in complex real sample and to allow for the rapid real-time detection with significantly reduced sample size. It was enriched with tubular foot-like functional groups (-NH2 and -COOH), which showed good linearity between pH 2.5-9.5 with successive fluorescence color change from blue-green to light green, light yellow, orange, and red. Three YOLO deep learning algorithm models were used to construct self-designed smart WeChat applets for high-throughput analysis, and two unique 3D printing toolboxes based on a 96-well plate and cuvette for sample analysis were also designed. The rapid high-throughput classification of a wide range of beverages and real-time monitoring of food freshness based on a hydrogel tag were also validated for reference. Prospectively, deep learning-assisted creation of proportional sensors will be critical to increasing the diversity and high throughput of real-time monitoring. © 2024 American Chemical Society.

关键词： 3D printing

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Pharma 4.0 Implementation Challenges and Potential Solutions

Pharma 4.0 Implementation Challenges and Potential Solutions

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Innovative Research in Applied Science, engineering and Technology (IRASET),Conference on

作者： Vincent Junior Phiri Ilham Battas Atae Semmar Hicham Medromi Fouad Moutaouakkil Engineering Research Laboratory (LRI) System Architecture Team (EAS) Engineering National High School of Electricity and Mechanic (ENSEM) Hassan II University Casablanca Morocco Research Laboratory Graduate School of Biomedical Engineering and Health Techniques (SUPTECH) Mohamedia Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Pharma 4.0 utilizes emerging Industry 4.0 technologies to improve production efficiency, quality management, and supply chain operations. However, its adoption faces significant challenges which are compounded by stringent regulations. This review aims to identify these challenges and propose solutions based on existing literature. Using a systematic literature review methodology, studies published between 2014 and 2024 in Scopus and Web of Science databases were analyzed. The findings reveal the main challenges across production and maintenance, quality management, supply chain management, and workforce readiness. To address the identified challenges, scalable and modular frameworks were identified. These frameworks offer a practical pathway for organizations to adopt Pharma 4.0 incrementally while addressing the challenges. Additionally, these frameworks enable gradual integration of advanced technologies, improving traceability and compliance, supply chain transparency as well as establishing the required workforce competencies. Thus, this review provides valuable insights for industry experts, policymakers, and scholars by offering them strategies to effectively navigate the challenges of Pharma 4.0 implementation.

关键词： Supply chain management Databases Supply chains Production Organizations Maintenance Fourth Industrial Revolution Rigidity Quality management Systematic literature review

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Determination of diffusion coefficient by image-based fluorescence recovery after photobleaching and single particle tracking system implemented in a single platform

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Journal of Innovative Optical Health Sciences 2021年第2期4卷 93-101页

作者： Donghee Lee Jeonghoon Lee Jung Kyung Kim Department of Genetics Cell Biology and Anatomy University of Nebraska Medical CenterOmahaNE 68198USA School of Mechanical Engineering KOREA TECH Cheonan 31253Republic of Korea School of Mechanical Engineering and Department of Integrative Biomedical Science and Engineering Graduate School Kookmin University Seoul 02707Republic of Korea

Fluorescence recovery after photobleaching(FRAP)and single particle tracking(SPT)techni-ques determine the diffusion coefficient from average diffusive motion of high-concentration molecules and from trajectories of low-concentration single molecules,*** dif-fusion coefficients measured by FRAP and SPT techniques for the same biomolecule on cell membrane have exhibited inconsistent values across laboratories and platforms with larger dif-fusion coefficient determined by FRAP,but the sources of the inconsistency have not been investigated ***,we designed an image-based FRAP-SPT system and made a direct comparison between FRAP and SPT for diffusion coefficient of submicron particles with known theoretical values derived from Stokes-Einstein equation in aqueous *** combined iFRAP-SPT technique allowed us to measure the diffusion coefficient of the same fluorescent particle by utilizing both techniques in a single platform and to scrutinize inherent errors and artifacts of *** results reveal that diffusion coefficient overestimated by FRAP is caused by inaccurate estimation of the bleaching spot size and can be corrected by simple image *** iFRAP-SPT technique can be potentially used for not only cellular membrane dynamics but also for quantitative analysis of the spatiotemporal distribution of the solutes in small scale analytical devices.

关键词： Diffusion coefficient fluorescence recovery after photobleaching(FRAP) single particle tracking(SPT)

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Development of a Taiwanese Speech Synthesis System Using Hidden Markov Models and a Robust Tonal Phoneme Corpus

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Journal of Information Science and engineering 2024年第2期40卷 283-302页

作者： Sher, Yung-Ji Hsu, Ming-Chun Chiu, Yu-Hsien Chen, Yeou-Jiunn Wu, Chung-Hsien Wu, Jiunn-Liang Department of Special Education Graduate Institute of Rehabilitation Counseling National Taiwan Normal University Taipei106 Taiwan Wistron Neweb Corporation Hsinchu300 Taiwan NSTC AI Biomedical Research Center National Cheng Kung University Tainan701 Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Tainan701 Taiwan Department of Electrical Engineering Southern Taiwan University of Science and Technology Tainan710 Taiwan Department of Otorhinolaryngology National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan704 Taiwan

The number of young native speakers of Taiwanese, the variant of Southern Min spoken in Taiwan, has decreased. Technological advancements such as text-to-speech (TTS) systems could help arrest this decline. The aim of this study was to design a robust tonal phoneme corpus and a speech synthesis system for Modern Literal Taiwanese (MLT). MLT subsyllables were analyzed using phonetics and phonology to establish tonal phoneme models. These robust tonal phoneme models and hidden Markov models were used to construct an MLT TTS synthesis system. Algorithm-based training resulted in 869 balanced sentences containing 12,544 syllables, with each sentence containing an average of 14.4 syllables. In total, 218 sentences, which included rare phonemes, were manually drafted to supplement the corpus. The synthesized phonemes were deemed to have high intelligibility and could be included in the developed TTS system. According to the HTK speech recognition tool, the overall phoneme recognition rate was 96.47%. Testers, who were native Taiwanese speakers, assigned the synthesized sentences a mean opinion score of 4, indicating that they sounded natural. This developed system and the results described herein can inspire future developments in speech technology and computational linguistics. © 2024 Institute of Information Science. All rights reserved.

关键词： Hidden Markov models

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PhageBox: An Open Source Digital Microfluidic Extension with Applications for Phage Discovery

TechRxiv

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TechRxiv 2023年

作者： Albin, Dreycey Buecherl, Lukas Kochavi, Eitan Niehaus, Elise Novack, Sasha Uragoda, Shenali Myers, Chris J. Alistar, Mirela Department of Computer Science CU Boulder BoulderCO United States Biomedical Engineering Program CU Boulder United States Department of Electrical Computer and Energy Engineering and Biomedical Engineering Program CU Boulder United States ATLAS Institute The Department of Computer Science CU Boulder BoulderCO United States

Objective: Recent advancements demonstrate the significant role of digital microfluidics in automating laboratory work with DNA and on-site viral testing. However, since commercially available instruments are limited to droplet manipulation, our work addresses the need for accelerated integration of other components, such as temperature control, that can expand the application domain. Methods: We developed PhageBox— an accessible device that can be used as a biochip extension. At hardware level, PhageBox integrates temperature and electromagnetic control modules. At software level, PhageBox is controlled by embedded software containing a unique model for bio-protocol programming, and a graphical user interface for visual device feedback and operation. Results: To evaluate PhageBox’s efficacy for biomedical applications, we performed functional testing. Similarly, we validated the temperature control using thermography, obtaining a range of ±0.2◦C. The electromagnets produced a magnetic force of 15 milliTesla, demonstrating precise immobilization of magnetic beads. We show the potential of PhageBox for bacteriophage research through three initial protocols: a universal framework for PCR, T7 bacteriophage restriction enzyme digestion, and concentrating X174 RF genomic DNA. Conclusion: Our work presents an open-source hardware and software extension for digital microfluidics devices. This extension integrates temperature and electromagnetic modules, demonstrating efficacy in biomedical applications and potential for bacteriophage research. Significance: We developed PhageBox to be accessible: the components are off-the-shelf at a low cost (≤$200), and the hardware designs and software code are open-source. With the long aim of ensuring reproducibility and accelerating collaboration, we also provide a DIY-build document. (GitHub: https://***/Dreycey/PhageBox) © 2023, CC BY-SA.

关键词： Digital microfluidics

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Pulmonary Tuberculosis Detection Using an Ensemble of ConvNeXts

Pulmonary Tuberculosis Detection Using an Ensemble of ConvNe...

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International Conference on biomedical engineering (IBIOMED)

作者： Seng Hansun Ahmadreza Argha Hamid Alinejad-Rokny Siaw-Teng Liaw Branko G. Celler Guy B. Marks South West Sydney (SWS) School of Clinical Medicine University of New South Wales Woolcock Institute of Medical Research Sydney Australia Universitas Multimedia Nusantara Tangerang Indonesia Graduate School of Biomedical Engineering Tyree Institute of Health Engineering (IHealthE) Ageing Future Institute (AFI) University of New South Wales Sydney Australia BioMedical Machine Learning Lab Graduate School of Biomedical Engineering Tyree Institute of Health Engineering (IHealthE) Ageing Future Institute (AFI) University of New South Wales Sydney Australia School of Population Health University of New South Wales Sydney Australia Biomedical Systems Research Laboratory School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia

ISBN: (数字)9798350389265

ISBN: (纸本)9798350389272

This study evaluates the effectiveness of a novel ensemble transfer learning (TL) method for tuberculosis (TB) detection. We employed the recently introduced ConvNeXt convolutional-based deep learning architecture as the backbone model. Two TL approaches were applied at intermediate layers of the pre-trained model (PTM), specifically ConvNeXt-Tiny, Small, and Base variants: Hard Cut, where features from an intermediate layer are directly passed to the classifier, and Soft Cut, where features from an intermediate layer are fine-tuned before classification. Experimental results on two widely used TB datasets-the Montgomery County (MC) and the Shenzhen (SZ) datasets demonstrate that the proposed ensemble TL method enhances detection performance. The Soft Cut approach yielded accuracy improvements of approximately 11.46% (Tiny), 8.71% (Small), 3.58% (Base) for MC, and 11.18% (Tiny), 10.27% (Small), 6.65% (Base) for SZ compared to the direct method, compared to the direct method.

关键词： Visualization Accuracy Tuberculosis Explainable AI Lungs Transfer learning Deep architecture biomedical engineering

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Self-Healable Sandfish Scale-Inspired Scalable Triboelectric Layer for Hybrid Energy Harvesting in Desert Environment

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Small 2024年第4期21卷 e2404637页

作者： Chen, An-Rong Parashar, Parag Sharma, Manish Kumar Shih, Jing-Siang Yeh, Hsuan-Yu Lin, Yen-Jui Kaswan, Kuldeep Fan, Kai-Po Chen, Po-Yu Lin, Zong-Hong Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan

In deserts, sedimentation from frequent dust activities on solar cells poses a substantial technical challenge, reducing efficiency and necessitating advanced cost-inefficient cleaning mechanisms. Herein, a novel sandfish scale-inspired self-healing fluorinated copolymer-based triboelectric layer is directly incorporated on top of the polysilicon solar cell for sustained hybrid energy harvesting. The transparent biomimetic layer, with distinctive saw-tooth microstructured morphology, exhibits ultra-low sand adhesion and high abrasion-resistant properties, inhibits sedimentation deposition on solar cells, and concurrently harvests kinetic energy from wind-driven sand particles through triboelectric nanogenerator (TENG). The film exhibits a low friction coefficient (0.149), minimal sand adhesion force (27 nN), and a small wear area (327 µm2). In addition, over 2 months, a solar cell with the sandfish scale-inspired structure demonstrates only a 16% decline in maximum power output compared to the bare solar cell, which experiences a 60% decline. Further, the sandfish scale-based TENG device's electrical output is fully restored to its original value after a 6-h self-healing cycle and maintains consistent stable outputs. These results highlight the exceptional advantages of employing biomimetic self-healing materials as robust triboelectric layers, showcasing sustained device stability and durability for prolonged use in harsh desert environments, ultimately contributing to a low cost-of-electricity generation paradigm. © 2024 Wiley-VCH GmbH.

关键词： Nanogenerators

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NPB-REC: A Non-parametric Bayesian Deep-learning Approach for Undersampled MRI Reconstruction with Uncertainty Estimation

arXiv

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arXiv 2024年

作者： Khawaled, Samah Freiman, Moti The Interdisciplinary program in Applied Mathematics Faculty of Mathematics Technion Israel Institute of Technology Israel The Faculty of Biomedical Engineering Technion Israel Institute of Technology Israel

The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI temporal resolution and reducing acquisition times. Deep learning methods have been proposed for this task, but the lack of verified methods to quantify the uncertainty in the reconstructed images hampered clinical applicability. We introduce "NPB-REC", a non-parametric fully Bayesian framework, for MRI reconstruction from undersampled data with uncertainty estimation. We use Stochastic Gradient Langevin Dynamics during training to characterize the posterior distribution of the network parameters. This enables us to both improve the quality of the reconstructed images and quantify the uncertainty in the reconstructed images. We demonstrate the efficacy of our approach on a multi-coil MRI dataset from the fastMRI challenge and compare it to the baseline End-to-End Variational Network (E2E-VarNet). Our approach outperforms the baseline in terms of reconstruction accuracy by means of PSNR and SSIM (34.55, 0.908 vs. 33.08, 0.897, p Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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The Fluorescent Effect of Chitosan Magnetitic Nanoparticles for Near-Infrared Imaging 3

The Fluorescent Effect of Chitosan Magnetitic Nanoparticles ...

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3rd Novel Intelligent and Leading Emerging Sciences Conference, NILES 2021

作者： Abuelmakarem, Hala S. Ahmed, Wafaa A. Mofed, Dina Wael, Mohammed Sami, Sherif A. The Higher Institute of Engineering Elshrouk Academy Biomedical and Systems Engineering Department Egypt Biochemistry and Molecular Biology Unit National Cancer Institute Cairo University Cancer Biology Department Giza Egypt Cairo University Zoology graduate program Department of zoology Faculty of science Giza Egypt Cairo University Faculty of Engineering Department of Biomedical Engineering and Systems Giza Egypt

ISBN: (纸本)9781665421577

Early cancer detection increases the healing rate according to the cancer stage. Nanotechnology is an advanced technique in cancer management due to the permeability and retention effect. Nano contrast agents are chief in early cancer detection because they diffuse in the cancerous tissue due to permeability and retention. This study aims to synthesize Chitosan Magnetic Nanoparticles (CM NPS) to evaluate them as a contrast agent for cells imaging, in vitro, under near-infrared irradiation. CM NPs were synthesized using the wetted chemical method. They were characterized using Dynamic Light Scattering, High-resolution Transmission Electronic Microscopy (HR- TEM), Fourier Transform Infrared (FTIR) Spectroscopy, and X-ray diffraction (XRD). The shining effect of the CM NPs was evaluated under the inverted microscopy over through a human lung epithelial cell culture in vitro. The characterization results ensured the successful synthesis of CM NPs. The photomicrographs appeared shining light of CM NPs on the cells photographed under the inverted microscope. © 2021 IEEE.

关键词： Chitosan

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Characterization of silk fibroin-based microneedles and in vitro study of stromal cell-derived factor-1-loaded microneedles on adipose stem cell recruitment

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International Journal of Biological Macromolecules 2023年第1期233卷 123537页

作者： Chen, Wu-Xun Cheng, Nai-Chen Chen, Yan-Jun Lee, I-Chi Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Surgery National Taiwan University Hospital and College of Medicine 7 Chung-Shan S Rd Taipei100 Taiwan Graduate Institute of Biomedical Engineering Chang Gung University Taoyuan Taiwan

Silk fibroin (SF) has good biocompatibility, degradability and mechanical properties. In this study, SF-based microneedle (MN) patches were fabricated as stromal cell-derived factor-1 (SDF-1) carriers that may be used for adipose stem cell (ASC) recruitment. Therefore, SF was chosen as the main MN material to achieve sustained drug release. In addition, the variations in SF-based MN crystallinity after water annealing treatment were also determined. The results indicated that SF-based MN patches were successfully fabricated with a 3M™ commercial template and Polydimethylsiloxane mold. Through optical coherence tomography, it was found that all of the SF-based MN patches prepared in this study had sufficient strength to penetrate the skin to a depth of approximately 400 μm. Sustained release of the model drug-dextran from the SF-based MNs was demonstrated. Although SF-based MNs release SDF-1 in a sustained manner, the quantity released can be regulated and improved. Subsequently, dual-layer SDF-1-loaded MNs fabricated with a gelatin tip and SF body were prepared to enhance SDF-1 release for ASC recruitment. SF-based MNs can show good penetration ability and provide good sustained release while dual-layer MNs can regulate the amount of drug released, which could present an alternative for stem cell therapy. © 2023 Elsevier B.V.

关键词： Silicones

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