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Wet tissue adhesive polymeric powder hydrogels for skeletal muscle regeneration

Bioactive Materials 2024年第10期40卷 334-344页

作者： Mingyu Lee Daun Seo Junggeon Park Sun Hong Lee Jin Jeon Woochan Kim Jangho Kim Hee Seok Yang Jae Young Lee School of Materials Science and Engineering Gwangju Institute of Science and TechnologyGwangju61005Republic of Korea Department of Nanobiomedical Science&BK21 FOUR NBM Global Research Center for Regenerative Medicine Dankook UniversityCheonan31116Republic of Korea Department of Convergence Biosystems Engineering Chonnam National UniversityGwangju61186Republic of Korea Department of Rural and Biosystems Engineering Chonnam National UniversityGwangjuRepublic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National UniversityGwangju61186Republic of Korea

Volumetric muscle loss(VML)frequently results from traumatic incidents and can lead to severe functional *** have been widely employed for VML tissue regeneration,which are unfortunately ineffective because of the lack of intimate contact with injured tissue for structural and mechanical *** hydrogels allow for strong tissue connections for wound ***,conventional adhesive hydrogels exhibit poor tissue adhesion in moist,bleeding wounds due to the hydration layer at the tissue–hydrogel interfaces,resulting in insufficient *** this study,we developed a novel,biocompatible,wet tissue adhesive powder hydrogel consisting of dextran-aldehyde(dex-ald)and gelatin for the regeneration of *** powder absorbs the interfacial tissue fluid and buffer solution on the tissue,spontaneously forms a hydrogel,and strongly adheres to the tissue via various molecular interactions,including the Schiff base *** particular,the powder composition with a 1:4 ratio of dex-ald to gelatin exhibited optimal characteristics with an appropriate gelation time(258 s),strong tissue adhesion(14.5 kPa),and ***-ald/gelatin powder hydrogels presented strong adhesion to various organs and excellent hemostasis compared to other wet hydrogels and fibrin glue.A mouse VML injury model revealed that the dex-ald/gelatin powder hydrogel significantly improved muscle regeneration,reduced fibrosis,enhanced vascularization,and decreased ***,our wet-adhesive powder hydrogel can serve as an effective platform for repairing various tissues,including the heart,muscle,and nerve tissues.

关键词： Powder Hydrogel Wet-adhesive Skeletal muscle regeneration

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Detecting Foreground in Videos via Posterior Regularized Robust Bayesian Tensor Factorization 19

Detecting Foreground in Videos via Posterior Regularized Rob...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Xia, Shenghao Zhang, Yinwei Zhang, Biao Liu, Jian University of Arizona Statistics & Data Science Gidp Program Department of Mathematics United States University of Arizona Department of System & Industrial Engineering United States Abb Inc. United States

ISBN: (纸本)9798350320695

Foreground detection is a critical step for separating the moving object from the background in video processing. Tensor factorization has been used in foreground detection due to its ability to process complex high-dimensional data, such as color images and videos. However, traditional tensor factorization often lacks the ability for uncertainty quantification. Bayesian tensor factorization can measure the uncertainty by considering the distributions of the tensor factorization model parameters. Besides, domain knowledge is commonly available and could improve the accuracy of foreground detection of the Bayesian tensor factorization model if it can be appropriately incorporated. In this work, a new Bayesian tensor factorization model, named Posterior Regularized Bayesian Robust Tensor Factorization (PR-BRTF), is proposed with incorporating characteristics of dynamic foreground, as a sparsity posterior regularization term. Furthermore, the variational Bayesian inference and L1 norm is combined for inducing sparsity with an efficient inference. The experiments in real-world case studies have shown the performance improvement of the proposed model over state-of-art methods. © 2023 IEEE.

关键词： Inference engines

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The Effect of Air Cavity on Water Resistance of a High-Speed Ferry with a Several-Stepped Hull 33rd

The Effect of Air Cavity on Water Resistance of a High-Speed...

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33rd International Ocean and Polar engineering Conference, ISOPE 2023

作者： Anggriani, Andi Dian Eka Mutsuda, Hidemi Nakashima, Takuji Ardianti, Andi Baso, Suandar Transportation and Environmental System Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima-shi Higashihiroshima Japan Transportation and Environmental Systems Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima-shi Higashihiroshima Japan Naval Architecture Study Program Hasanuddin University South Sulawesi Gowa Indonesia

ISBN: (纸本)9781880653807

A planing hull high-speed ferry with a stepped hull becomes a well-liked mode of water transportation for archipelago countries. On the other hand, the shape of steps on the bottom hull has not been recently taken into explicit consideration regarding the speed requirement and hydrodynamic properties. In this study, the step W shapes, were adopted to find the improved hydrodynamic performance in the planing conditions. To provide a more precise prediction of the pressure, velocity fields, and void fraction, the CFD was applied the Finite Volume Method (FVM) and coupled with Volume of Fluid Method (VOF) to capture air cavity The numerical conditions of the planing hull were trimmed by the stern with 2, and 3 degrees. This study discussed the air cavity that occurred behind the stepped area that can affect the hydrodynamic behaviour. © 2023 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Finite volume method

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Spatial Selection Configuration on EEG Stroke Signal 1

Spatial Selection Configuration on EEG Stroke Signal

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1st International Conference on Information system and Information Technology, ICISIT 2022

作者： Firdaus, Fulki Hapsari, Anggit Fauzi, Hilman Shapiai, Ibrahim Fuadah, Yunendah Telkom University Telecommunication Engineering Study Program Faculty of Electrical Engineering Bandung Indonesia Telkom University Biomedical Engineering Study Program Faculty of Electrical Engineering Bandung Indonesia Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Electrical System Engineering Kuala Lumpur Malaysia

ISBN: (数字)9781665402002

ISBN: (纸本)9781665402002

Stroke is one of the cerebrovascular health disorders caused by a blockage of blood flow to the brain. Data from South East Asian Medical Information Center (SEAMIC) explain that the most significant stroke mortality occurred in Indonesia, Philippines, Singapore, Brunei, Malaysia, and Thailand. There are several methods for diagnosing stroke, one of which is an electroencephalograph (EEG). EEG is one of the more widely used BCI methods due to its lower price, portability, ease of use, and high temporal resolution than other methods. Most EEG require signals from various places on the scalp to achieve good performance. However, using a large number of channels can degrade signal performance in the EEG. Spatial selection can be used for channel selection in the EEG stroke signal which can then be useful for evaluation of stroke therapy. Therefore, this study will select the optimized channel using the spatial selection method to see which channels are relevant to the EEG stroke signal. Also, using the Power Spectral Density extraction feature and Extreme Learning Machine classification. The L2-norm energy calculation method gets better results than other methods. This method can also select the active channel relevant to the stroke EEG signal. The results show that the spatial selection method can increase accuracy by 15 percent and optimize the system with 37.5 percent channel reductions. © 2022 IEEE.

关键词： Learning systems

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A Hybrid Approach with BRKGA and Data Mining for the Early/Tardy Scheduling Problem 13

A Hybrid Approach with BRKGA and Data Mining for the Early/T...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Mendonça, Israel Fatyanosa, Tirana Noor Aritsugi, Masayoshi Silva, Pedro Henrique González Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan Brawijaya University Faculty of Computer Science Malang Indonesia Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil

ISBN: (纸本)9798350308365

This paper introduces a novel hybrid genetic algorithm combined with data mining to solve a version of the early/tardy scheduling problem in which no unforced idle time may be inserted in a sequence. The chromosome representation of the problem is based on random keys and we use the Biased Random-Key Genetic Algorithm (BRKGA) to establish an order in which jobs are scheduled. A data mining component gathers data from the evolutionary steps of BRKGA and suggests chromosomes based on past observations. In this way, we address a key challenge in BRKGA - the exploration of solutions near an individual gene - by leveraging data-driven insights to refine and enhance the search space. Comparative analysis reveals that our hybrid algorithm significantly benefits from the pattern recognition capabilities of data mining, leading to improved scheduled efficiency. The results of a series of computational experiments underscore the potential of this hybrid approach that, although requiring slightly longer computational times, is better than the previous baseline BRKGA algorithm in terms of solution quality. © 2024 IEEE.

关键词： Scheduling algorithms

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Scaffolding Process-Aware Information systems with the AKIP Platform 1

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18th International Conference on Web Information systems and Technologies, WEBIST 2022

作者： Telemaco Neto, Ulisses Oliveira, Toacy Pillat, Raquel Alencar, Paulo Cowan, Don Melo, Glaucia David R. Cheriton School of Computer Science University of Waterloo Waterloo Canada System Engineering and Computing Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9783031430886

ISBN: (纸本)9783031430879

Business Process Automation (BPA) refers to the automation of business processes through technology, with the goal of improving efficiency, reducing errors, and increasing productivity by eliminating manual and repetitive tasks. Over the past few years, the number of BPA platforms has increased, including both open-source and proprietary solutions. However, some challenges and limitations still exist related to the adoption of these solutions, such as vendor lock-in, limited UI/UX, limited integration, outdated technology stack, and lack of support for non-process features. To address these issues, this paper presents the AKIP platform, an open-source framework for developing process-aware information systems (PAISs) using code generation techniques. AKIP generates functional process-aware web applications from BPMN business process models, making it the only known software tool capable of generating fully functional process-aware web applications. To evaluate the effectiveness of the AKIP platform, a case study was conducted in the industry and six business processes automated into a process-oriented web application were analyzed in this paper. The study showed that the AKIP platform was able to generate a functional web application while supporting the automation of business processes with different model sizes and complexities. Furthermore, this study showed that even a team of professionals with little experience was able to produce such results by using the AKIP platform. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Automation

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A Location Estimation Algorithm Combined with TDOA and TOA Considering Repeaters

A Location Estimation Algorithm Combined with TDOA and TOA C...

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International Conference on Ubiquitous and Future Networks, ICUFN

作者： Seul-Bi Jeon Heui-Seon Park Tae-Ho Jo Suk-Seung Hwang Department of Electronic Engineering Interdisciplinary Program in IT-Bio Convergence System Chosun University Gwangju Korea Interdisciplinary Program in IT-Bio Convergence System School of Electronic Engineering Chosun University Gwangju Korea

Location Detection Technology (LDT), which accurately estimates the location of a mobile station (MS), is one of core techniques for the modern communication system. Among various LDTs, Time of arrival (TOA) and Time Difference of Arrival (TDOA) are the most commonly employed method, which calculates the location of MS based on at least three signals from base stations (BSs). In the urban environment, many repeaters have been installed for overcoming the radio shadow area problem of a receiver, but they cause the serious errors of the location estimation when we utilize signals passed through repeaters. In order to enhance this problem, in this paper, we introduce the combined location estimation approach with TDOA and TOA considering the repeater, based on signals from two repeaters and one BS.

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Coevolution of Myoelectric Hand Control under the Tactile Interaction among Fingers and Objects

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Cyborg and Bionic systems 2022年第1期2022卷 285-302页

作者： Yuki Kuroda Yusuke Yamanoi Shunta Togo Yinlai Jiang Hiroshi Yokoi Joint Doctoral Program for Sustainability Research Graduate School of Informatics and Engineering The University of Electro-CommunicationsTokyoJapan Department of Mechan ical and Intelligent System Engineering Graduate School of Informatics and Engineering The University of Electro Communications TokyoJapan Center for Neuroscience and Biomedical Engineering The University of Electro Communications TokyoJapan Bejing Innovation Center for Inelligent Robots and Systems BeijingChina

The usability of a prosthetic hand difers significantly from that of a real ***,the complexity of manipulation increases as the number of degrees of freedom to be controlled increases,making manipulation with biological signals extremely *** overcome this problem,users need to select a grasping posture that is adaptive to the object and a stable grasping method that prevents the object from *** previous studies,these have been left to the operating skills of the user,which is extremely difficult to *** this study,we demonstrate how stable and adaptive grasping can be achieved according to the object regardless of the user's operation *** required grasping technique is achieved by determining the correlation bet ween the motor output and each sensor through the interaction between the prosthetic hand and the surrounding stimuli,such as myoelectricity,sense of touch,and grasping *** agents of the 16 DOF robot hand were trained with the myoelectric signals of six participants,including one child with a congenital forearm ***,each agent could open and close the hand in response to the myoeletric stimuli and could accomplish the object pickup *** the tasks,the agents successfully identified grasping patterns suitable for practical and stable positioning of the *** addition,the agents were able to pick up the object in a similar posture regardless of the partiipant,suggesting that the hand was optimized by evolutionary computation to a posture that prevents the object from being dropped.

关键词： robot Objects overcome

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Comparison Analysis of Intrusion Detection using Deep Learning in IoT Networks 11

Comparison Analysis of Intrusion Detection using Deep Learni...

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11th International Conference on Information and Communication Technology, ICoICT 2023

作者： Ikhwan, Syariful Purwanto, Purwanto Rochim, Adian Fatchur Diponegoro University Doctoral Program of Information System School of Postgraduate Studies Semarang Indonesia Institut Teknologi Telkom Purwokerto D3 Telecommunication Engineering Banyumas Indonesia Diponegoro University Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Diponegoro University Faculty of Engineering Department of Computer Engineering Semarang Indonesia

ISBN: (纸本)9798350321982

This study focuses on network security for Internet of Things (IoT) devices, which are particularly vulnerable to attack due to limited security measures. To protect IoT networks from attackers, the research implemented intrusion detection on the networks. The study compared several Deep Learning algorithms, including DNN, CNN, LSTM, and AE, to identify the most effective algorithm for solving network security problems using intrusion detection. The research used the UNSW-NB15 dataset for testing and employed binary classification for evaluation. The results showed that the DNN algorithm achieved an accuracy value of 99.76% and a loss value of 0.006%, outperforming the other algorithms. This study highlights the importance of implementing intrusion detection in protecting IoT devices and networks and demonstrates the efficacy of the DNN algorithm in detecting and preventing network security breaches. © 2023 IEEE.

关键词： Internet of things

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Automatic LPI Radar Waveform Recognition Using Vision Transformer

Automatic LPI Radar Waveform Recognition Using Vision Transf...

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2023 IEEE International Radar Conference, RADAR 2023

作者： Kim, Junseob Cho, Sunghwan Hwang, Sunil Choi, Yeongyoon Korea Military Academy Department of Electrical Engineering 01805 Korea Republic of Defense Acquisition Program Administration Maneuver System Coordination and Contract Team 13809 Korea Republic of Gist Department of Electrical Engineering and Computer Science 61005 Korea Republic of

ISBN: (纸本)9781665482783

This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at -10dB SNR. © 2023 IEEE.

关键词： Convolutional neural networks

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