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Characterization of a new triaxial nanofiber membrane and osteogenic differentiation capacity of human bone marrow mesenchymal stem cells for bone repair

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Journal of Materials Research 2025年 1-18页

作者： Altundag-Erdogan, Özlem Çetinkaya, Hayrullah Çelebi-Saltik, Betül Altun, Belgin Şahin, Mehtap Mağden, Gamze Kara Öteyaka, Mustafa Özgür Department of Stem Cell Sciences Graduate School of Health Sciences and Center for Stem Cell Research and Development Hacettepe University Sihhiye Ankara06100 Turkey Department of Chemical Engineering Eskisehir Osmangazi University Eskişehir26040 Turkey Vocational School Health Services Hacettepe University Sihhiye Ankara06100 Turkey BUGAMED Biotechnology Industry and Trade Inc Eskişehir26380 Turkey Eskişehir Vocational School Electronics and Automation Eskisehir Osmangazi University Mechatronic Program Eskişehir26250 Turkey

A triaxial nanofiber membrane was developed using a custom triaxial nozzle during electrospinning. The membrane consisted of three layers (outer middle (PVA-Collagen Type I-BMP-2), and inner (PVA-nHAP)). TEM revealed the diameters of the outer, middle, and inner layers as 167.5, 142.6, and 119.3 nm, respectively. The triaxial nanofiber membrane exhibited superior tensile strength (36 MPa) and elastic modulus (2.5 GPa), along with a roughness of 359 nm and hydrophilic properties. In addition, it demonstrated a 200% swelling ratio and reduced bacterial colonization by 10.8-fold. Both Calcium deposition and ALP activity were significantly higher and increased expression of BSP (eightfold), OCN (13-fold), and OPN (488-fold) genes were observed in membrane + OST groups (p © The Author(s), under exclusive licence to The Materials Research Society 2025.

关键词： Bone

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Development of EEG-Based Optimal Biomarkers for Decoding Fatigue during Motor Imagery Tasks

Development of EEG-Based Optimal Biomarkers for Decoding Fat...

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International Winter Workshop on Brain-Computer Interface (BCI)

作者： Jun-Seok Lee Seung-Won Lee Sang-Rok Kim Han-Jeong Hwang Dept. Electronics and Information Engineering Korea University Sejong Republic of Korea Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong Republic of Korea

ISBN: (数字)9798331521929

ISBN: (纸本)9798331521936

This study aimed to identify electroencephalography (EEG)-based neurophysiological biomarkers for monitoring mental fatigue during motor imagery (MI) tasks. We used EEG data recorded from 29 healthy adults during MI tasks. For the preprocessing of the EEG data, we sequentially performed down-sampling into 200 Hz, independent component analysis (ICA), band-pass filtering between 0.5 and 50 Hz, and common average reference (CAR). The preprocessed EEG data were analyzed using a fast Fourier transform (FFT) to calculate spectral power in the δ (0.5-3 Hz), θ (4–7 Hz), $a$ (8–13 Hz), and β (13–30 Hz) frequency bands. Subsequently, seventeen fatigue-related metrics were calculated using individual spectral powers and their combinations. These fatigue-related metrics were averaged for the frontal lobe (F3 and F4), central lobe (FCC3h and FCC4h), parietal lobe (P3 and P4), and occipital lobe (POO1 and POO2). The statistical significance of the average fatigue metrics was evaluated through Pearson correlation analysis with the sequence of trials. As a result, we observed strong positive correlations (r < 0.9, p < 0.001) between beta power in the frontal and central regions and the sequence of trials. These findings suggest that central and frontal beta activity can serve as reliable biomarkers for estimating fatigue during MI tasks, supporting their potential for real-time fatigue monitoring.

关键词： Measurement Correlation Fast Fourier transforms Biomarkers Fatigue Motors Electroencephalography Decoding Reliability Monitoring

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Output Feedback Control of TS Fuzzy Systems with Unmeasured Nonlinearities via a Local Separation Principle

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IFAC-PapersOnLine 2023年第2期56卷 2164-2169页

作者： Anh-Tu Nguyen Pedro Coutinho Márcia Peixoto Thierry-Marie Guerra Reinaldo Palhares LAMIH UMR CNRS 8201 Université Polytechnique Hauts-de-France France Federal University of Minas Gerais Graduate Program in Electrical Engineering Brazil Federal University of Minas Gerais Department of Electronics Engineering Brazil

This paper presents a fuzzy observer-based control framework for TS fuzzy models with nonlinear consequents (N-TS). The N-TS fuzzy model is constructed such that only measured nonlinearities are considered to obtain the fuzzy membership functions, and all unmeasured nonlinearities are modeled as local consequent parts. Based on the differential mean value theorem, the closed-loop system is rewritten in an adequate format, which allows proving the separation principle for asymptotic TS fuzzy observer-based control design. Sufficient design conditions, expressed in terms of linear matrix inequalities, are derived via delayed nonquadratic Lyapunov functions for the synthesis of both stabilizing fuzzy controller and Luenberger-like fuzzy observer. Using Lyapunov-based arguments of a local separation principle, a constructive procedure is provided to maximize the closed-loop domain of attraction (DoA) estimation, which is guaranteed to be included inside the predefined fuzzy modeling region. Numerical examples are given to illustrate the effectiveness of the proposed approach.

关键词： Takagi-Sugeno fuzzy systems observer-based fuzzy control separation principle unmeasured premise variables linear matrix inequality

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Multi-modal Multitask Learning Model for Simultaneous Classification of Two Epilepsy Biomarkers 27th

Multi-modal Multitask Learning Model for Simultaneous Classi...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Broti, Nawara Mahmood Sawada, Masaki Takayama, Yutaro Iijima, Keiya Iwasaki, Masaki Ono, Yumie Electrical Engineering Program Graduate School of Science and Technology Meiji University Kanagawa Kawasaki Japan Department of Neurosurgery Yokohama City University Hospital Kanagawa Yokohama Japan Department of Neurosurgery National Center Hospital National Center of Neurology and Psychiatry Tokyo Kodaira Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University Kanagawa Kawasaki Japan

ISBN: (纸本)9783031781971

Accurate estimation of the epileptogenic zone is critical for surgical treatment of drug-resistant epilepsy. While epilepsy biomarkers detection for epileptogenic zone localization has traditionally relied on expert clinician knowledge, the use of deep learning in this context has recently gained appeal for objective diagnosis and reducing clinician burden. However, previously proposed classifiers for electrocorticogram data focused on only single biomarkers among many types, requiring separate models and large datasets for each. To minimize clinicians’ workload and patients’ sufferings, innovative methods to classify multiple biomarkers using small training datasets and minimal computation time is required. This research marks the first implementation of multi-modal multitask learning in epilepsy biomarker classification, proposing a model to automatically classify two biomarkers—high-frequency oscillations (HFO) and interictal epileptiform discharges (IED)—from separate datasets simultaneously. We validated the proposed model on 1500 annotated HFO and IED candidate signals each, obtained from 5 patients. Our proposed model can perform both HFO and IED classification simultaneously, with cross-validation accuracies of 90.99% and 93.99%;F1 scores were reported as 0.80 and 0.82, respectively. Our leave-one-patient-out experiments achieved 78.03% and 81.19% accuracy for HFO and IED classification, respectively. Compared to existing state-of-the-art classification architectures, our model is shown to be efficient and robust, yet simple and lightweight. The usefulness of sharing parameters between the two classifiers was confirmed in this practical clinical setting of epileptic biomarker detection, potentially contributing to minimizing the number of annotated datasets and realizing robust, accurate, and simultaneous identification of two biomarkers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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Energy Material for Extreme Environment: Unveiling Novel Self-Resilience of Hf1-xZrxO2 for Electrostatic Energy Storage (EES) and Pyroelectric Energy Harvesting (PEH)

Energy Material for Extreme Environment: Unveiling Novel Sel...

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International Electron Devices Meeting (IEDM)

作者： C.-H. Liu K.-Y. Hsiang F.-S. Chang Y.-T. Chang C. W. Liu M. H. Lee Program for Semiconductor Devices Materials and Hetero-integration Graduate School of Advanced Technology National Taiwan University Taipei Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan

ISBN: (数字)9798350365429

ISBN: (纸本)9798350365436

The antiferroelectric (AFE) Hf02-based capacitor has been proposed as dual-functional for electrostatic energy storage and pyroelectric energy harvesting (PEH) for the first time. The partial-AFE (P-AFE) has a superior power and energy density capability of 1.46x10 10 W/kg and 0.96 Wh/kg, respectively, as compared with state-of-the-art capacitors and cell batteries. Furthermore, the harvestable energy density (HED) of P-AFE was experimentally measured at an outstanding 10.37 J/cm 3 within $\Delta \mathrm{T}=223\mathrm{K}$ (RT to 77K). The HfO 2 -based energy material is examined in low-temperature and X-ray irradiation and validates the degradation dominated by E-field cycling. The AFE capacitors inherently reflect the self-resilience effect and the physical mechanism of the fatigue and recovery are unveiled by VOs redistribution. There is great potential for utilizing benefits in energy storage and harvesting through the novel recovery strategy toward an unlimited lifetime of energy devices for extreme environments.

关键词： Radiation effects Temperature Density measurement Capacitors Electrostatic discharges Fatigue Iron Energy harvesting Electrostatics Energy storage

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Mathematical Analysis and Space Vector Modulation of the Three-phase Buck-Boost Rectifier with Reactive Power Capability

Mathematical Analysis and Space Vector Modulation of the Thr...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Yan Pontes Figueiredo Montie Alves Vitorino Jens Friebe Graduate Program in Electrical Engineering (PPgEE-COPELE) Industrial Electronics and Machine Drive Laboratory (LEIAM) Federal University of Campina Grande (UFCG) Campina Grande Brazil Department of Power Electronics University of Kassel Kassel Germany

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Buck-boost current-source based converters are attractive for applications in electric vehicles (EVs) due to several inherent benefits regarding high-power charging. However, methods are still needed to increase the efficiency of these converters. This paper covers a mathematical analysis of the three-phase buck-boost rectifier with reactive power capability and shows its equation and operating conditions for a wide range of power factors. In addition, the control strategy based on space vector modulation (SVM) is presented in detail, as well as the passive elements design. Experimental results show that the converter modulated by SVM is more efficient in terms of switching losses compared to scalar modulation.

关键词： Support vector machines Reactive power Mathematical analysis Modulation Rectifiers Switching loss Energy conversion Aerospace electronics Electric vehicles Vectors

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Dynamic Volumetric Video Coding with Tensor Decomposition

Dynamic Volumetric Video Coding with Tensor Decomposition

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IEEE Visual Communications and Image Processing (VCIP)

作者： Ju-Yeon Shin Yeoneui Kim Je-Won Kang Gun Bang Dept. of Electronic and Electrical Engineering and Graduate Program in Smart Factory Ewha Womans University Seoul South Korea Electronics and Telecommunications Research Institute Daejeon South Korea

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

Recently, volumetric video coding based on neural radiance fields has gained significant attention for storing and transmitting three-dimensional (3D) scenes captured from multi-view video. Because the neural networks are trained to produce novel view synthesis of surrounding 3D scenes, compressing the model and then rendering the colors and geometry through the decompressed model can be utilized as a 3D video coding system. However, although this approach provides superior performance compared to conventional 3D video coding standards using depth video, challenges remain in reducing overall model sizes to improve coding efficiency. In this paper, we propose a novel dynamic volumetric video coding technique that employs a Group of Volume (GoV) to divide multi-view video sequences into smaller chunks, addressing complex temporal dynamics. Our method uses volumetric video features represented with 3D spatial and temporal tensor matrices and vectors and encodes them with the GoVs. The tensors are compressed by existing 2D video codec, allowing for fast rendering and easing deployment. Experimental results validate that our method not only reduces memory footprint but also maintains high-quality rendering as compared to state-of-the-art studies.

关键词： Video coding Solid modeling Three-dimensional displays Image coding Tensors Visual communication Video sequences Rendering (computer graphics) Video codecs Standards

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Quantum Wrapper Networking: Investigating the Noise Impact of Classical Headers on the Quantum Payload

Quantum Wrapper Networking: Investigating the Noise Impact o...

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2024 Frontiers in Optics, FiO 2024

作者： Gül, Gamze On, Mehmet Berkay Tan, Shannon G. Proietti, Roberto Kanter, Gregory S. Yoo, S.J. Ben Kumar, Prem Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy

We study the impact in time and frequency domains of classical headers on quantum payloads in quantum wrapper networking. We identify and characterize in-fiber scattering processes that produce noise photons degrading...

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Adaptive Control Applied to Half-Bridge Synchronous Buck Converter using LCL Filter for Charging Batteries 16

Adaptive Control Applied to Half-Bridge Synchronous Buck Con...

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16th Seminar on Power electronics and Control, SEPOC 2024

作者： Rodrigues, Vinicius Descovi Merlo, Joao Vitor Tibola, Jonas Roberto Tambara, Rodrigo Varella Federal University of Santa Maria Research and Development Center in Electrical Engineering NUPEDEE Santa Maria Brazil Federal University of Santa Maria Graduate Program in Electrical Engineering PPGEE Santa Maria Brazil Federal University of Santa Maria Research and Development Center in Electrical and Computational Systems GSEC Santa Maria Brazil Federal University of Santa Maria Group of Power Electronics and Control GEPOC Santa Maria Brazil

ISBN: (纸本)9798350379419

This paper proposes a discrete-time Model Reference Adaptive Controller (MRAC), applied to a Half-Bridge synchronous buck converter for charging batteries. The system uses an LCL filter that interfaces the power converter and the batteries. A virtual plant method is proposed for better transitory response of the adaptive control system. The model reference utilizes a reduced order, to simplify the project of the adaptive controller. Simulation results are presented for validation of the control project. © 2024 IEEE.

关键词： Buck converter

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Microwave-Based Complementary Split-Ring Resonator for the Detection of Variations in Aqueous Media

Microwave-Based Complementary Split-Ring Resonator for the D...

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Microelectronics Technology and Devices (SBMicro)

作者： Reinaldo Velásquez Diego Tami Gilberto Medeiros-Ribeiro Cássio G. Rego Jhonattan C. Ramirez Graduate Program in Electrical Engineering UFMG Brazil Institute of Technological Sciences UNIFEI Brazil Department of Computer Science UFMG Brazil Department of Electronics Engineering UFMG Brazil

In this paper, we demonstrated a highly sensitive microwave-based resonator sensor capable of detecting variations in an aqueous medium of up to 0.94 mg/dL. In the presented device, the intrinsic resonant response (resonant amplitude, resonant frequency, and quality factor) is capacitively perturbed in reaction to the sample presence. To achieve higher sensitivity, the sample under testing generally is placed on the resonator surface, where the electric field is highly concentrated at the operating frequency. Thus, demonstrating excellent results in terms of sensitivity and reproducibility.

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