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https://scholars.lib.ntu.edu.tw/handle/123456789/38484
2024-03-28T12:49:33ZCharacterization of Single-Spheroid Oxygen Consumption Using a Microfluidic Platform and Fluorescence Lifetime Imaging Microscopy
https://scholars.lib.ntu.edu.tw/handle/123456789/640761
標題: Characterization of Single-Spheroid Oxygen Consumption Using a Microfluidic Platform and Fluorescence Lifetime Imaging Microscopy
作者: Kannan, Santhosh; Peng, Chien Chung; HSIAO-MEI WU; Tung, Yi Chung
摘要: Oxygen consumption has been used to evaluate various cellular activities. In addition, three-dimensional (3D) spheroids have been broadly exploited as advanced in vitro cell models for various biomedical studies due to their capability of mimicking 3D in vivo microenvironments and cell arrangements. However, monitoring the oxygen consumption of live 3D spheroids poses challenges because existing invasive methods cause structural and cell damage. In contrast, optical methods using fluorescence labeling and microscopy are non-invasive, but they suffer from technical limitations like high cost, tedious procedures, and poor signal-to-noise ratios. To address these challenges, we developed a microfluidic platform for uniform-sized spheroid formation, handling, and culture. The platform is further integrated with widefield frequency domain fluorescence lifetime imaging microscopy (FD-FLIM) to efficiently characterize the lifetime of an oxygen-sensitive dye filling the platform for oxygen consumption characterization. In the experiments, osteosarcoma (MG-63) cells are exploited as the spheroid model and for the oxygen consumption analysis. The results demonstrate the functionality of the developed approach and show the accurate characterization of the oxygen consumption of the spheroids in response to drug treatments. The developed approach possesses great potential to advance spheroid metabolism studies with single-spheroid resolution and high sensitivity.2024-02-01T00:00:00ZOptimizing BESS performance: Anisotropic thermal properties and innovative parallel-flow cooling solutions
https://scholars.lib.ntu.edu.tw/handle/123456789/640756
標題: Optimizing BESS performance: Anisotropic thermal properties and innovative parallel-flow cooling solutions
作者: Huang, Xin Yu; YEN-WEN LU; JING-TANG YANG
摘要: As the demand for efficient energy storage solutions intensifies, container-type battery energy storage systems (BESS) have gained prominence. BESS usually utilizes large-format laminated lithium-ion battery (LIB) modules, which inherently possess unique anisotropic thermal properties. Specifically, the surface regions with elevated temperatures exhibit high thermal conductivity, while the cooler zones at both ends manifest reduced conductivity. Such disparities emphasize the challenge of developing an effective battery thermal management system (BTMS) for these modules. To address this, our study introduces an innovative BTMS configuration wherein the batteries are aligned in series, while cooling air flows parallel to them. This parallel-flow cooling approach capitalizes on the anisotropic properties, intensifying airflow over the surfaces and recirculating cooling air to optimize heat dissipation from hotspots. Consequently, our system reduces the peak temperature from 42.3 °C to 37.5 °C, as well as the temperature difference (ΔT) from 14.3 °C to 10.2 °C across the entire BESS, respectively representing 11.3 % and 28.7 % changes. This leads to a substantial 75.9 % enhancement in the performance index, significantly augmenting both the safety and commercial viability of the BESS.2024-06-01T00:00:00ZLaser-Induced Forward Transfer for Biosensor Application
https://scholars.lib.ntu.edu.tw/handle/123456789/639930
標題: Laser-Induced Forward Transfer for Biosensor Application
作者: Das, Ankit; Majumder, Samarpan Deb; Kozak, Drazan; CHIEN-FANG DING
摘要: Additive manufacturing is the future of advanced manufacturing. One of the additive manufacturing techniques that can be successfully, efficiently, and widely utilized is the laser-induced forward transfer (LIFT) process. In recent years, LIFT has been exploited extensively in printing thin films, and it has also been incorporated into manufacturing and printing sensor materials. Additionally, with the rise in miniaturization, the use of thin films in sensor applications has significantly increased. Recently, biosensors are a comprehensively studied area of research, for their easy, rapid, low-cost, highly sensitive, and highly selective properties. Biosensors have shown significant potential in areas of analytical biotechnology such as healthcare. Furtherance of biosensors for next-generation medicines and healthcare has been predominantly observed. Furthermore, biosensors have the ability to provide real-time information in healthcare applications. One of the major concerns over the use of biosensors is its expensive and time-consuming manufacturing processes. LIFT as a one-step process poses to be an efficient solution by collectively saving cost and time. This chapter imparts an elaborate description and overview on the LIFT process used for biosensor fabrication. First, biosensors are introduced in brief. Subsequently, a number of manufacturing processes used in biosensor fabrication along with their shortcomings are discussed. Following the biosensor discussion, LIFT is introduced. The process parameters and descriptions are reviewed in detail to provide a better insight into the LIFT process. Finally, considering the limitations offered by conventional biosensor manufacturing processes, the potential and advantages of the LIFT process are presented. It has been seen that the accuracy, cost, and time effectiveness of the LIFT process enable the efficient fabrication of biosensors, thereby proving itself as a potential manufacturing option for the future.2024-01-01T00:00:00ZAnalyzing chicken activity level under heat stress condition using deep convolutional neural networks
https://scholars.lib.ntu.edu.tw/handle/123456789/639781
標題: Analyzing chicken activity level under heat stress condition using deep convolutional neural networks
作者: Chang, Kai Rong; Shih, Fu Pang; Hsieh, Ming Kun; Hsieh, Kuang Wen; YAN-FU KUO
摘要: Chicken is a major source of protein. The production value of chicken accounted for 39.65 % of total animal husbandry sales in Taiwan. Because Taiwan is a subtropical country, heat stress may occur on chickens due to the high temperature and humidity in summer. Without appropriate care, heat stress may cause sudden death of chickens. Chickens may become inactive when they suffer from heat stress. Therefore, detecting the activity levels of chickens is a straightforward way to measure their risk of heat stress. This study aimed to measure the activity levels of chickens under various temperature conditions using computer vision. In the experiment, chicken eight weeks of age were raised in an experiment chicken house. The chickens were treated with normal or high temperature conditions. A raspberry-pi and a web camera were used to acquire overhead video of the chickens at a rate of five frames per second. A You Only Look Once-version 4 tiny model (YOLOv4-tiny) was trained to detect and to localize chickens in the video frames. Simple online and real-time tracking (SORT) was used for chicken tracking and quantify the movement from the detected location provided by YOLOv4-tiny model. The mean average precision of trained YOLOv4-tiny model achieved 93.20% in chicken detection. SORT achieved a multiple object accuracy of 99.2%, a multiple object precision of 84.3%, and an identification F1-score of 96.6%. The activity level found in different temperature conditions can be quantified as chicken's risk of heat stress.2022-01-01T00:00:00Z