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Deep Learning-Based Single-Shot Computational Spectrometer Using Multilayer Thin Films
No full textComputational spectrometers hold significant potential for mobile applications, such as on-site detection and self-diagnosis, due to their compact size, fast operation time, high resolution, wide working range, and low-cost production. Although extensively studied, prior demonstrations have been confined to a few examples of straightforward spectra. This study demonstrates a deep learning (DL)-based single-shot computational spectrometer capable of recovering narrow and broad spectra using a multilayer thin-film filter array. Our device can measure spectral intensities of incident light by combining a filter array, fabricated using wafer-level stencil lithography, with a complementary metal-oxide-semiconductor (CMOS) image sensor through a simple attachment. All the intensities were extracted from a monochrome image captured with a single exposure. Our DL architecture, comprising a dense layer and a U-Net backbone with residual connections, was employed for spectrum reconstruction. The measured intensities were input into the DL architecture to reconstruct the spectra. We collected 3,223 spectra, encompassing both broad and narrow spectra, using color filters and a monochromator to train and evaluate the proposed model. We reconstructed 323 test spectra, achieving an average root mean squared error of 0.0288 over a wavelength range from 500 to 850 nm with a 1 nm spacing. Additionally, the proposed multilayer thin-film filters were validated through scanning electron microscope (SEM) analysis, which confirmed uniform layer deposition and a high fabrication yield. Our computational spectrometer boasts a compact design, a rapid measurement time, a high reconstruction accuracy, a broad spectral range, and CMOS compatibility, making it well-suited for commercialization.TRUEsciescopu
Polymorphing Hydrogels through the Collaboration of Light and Photo-reactive DNA Cross-links
No full textPolymorphing hydrogels enable reprogrammable shape transformations, surpassing conventional hydrogels whose morphability is predetermined during fabrication. This adaptability originates from hydrogel swelling, photo-reactive DNA cross-links, and dynamically patterned light. The DNA cross-links undergo wavelength-dependent changes, allowing precise and reversible modulation of geometry. By tuning irradiation parameters, hydrogels morph from simple lines to complex patterns and extend from 2D into 3D architectures with programmable actuation.
The combined features of reprogrammability, spatiotemporal controllability, and structural versatility highlight their potential in soft robotics and 4D printing. Beyond these applications, such hydrogels may advance bio-inspired actuators, adaptive tissue models, and multifunctional soft machines capable of operating in complex environments.
ERAP2 as a Potential Marker for Ovarian Ageing and Spontaneous Ovulation Recovery in Women With Premature Ovarian Insufficiency
No full textObjective: To explore novel biomarkers for clinical prognosis in patients with ovarian ageing, especially in premature ovarian insufficiency (POI).
Design: Prospective Cohort Study.
Setting: Reproductive Hospital Affiliated with Shandong University, China.
Population: Sixty POI patients and 60 control women recruited from 2018 to 2019.
Methods :Machine learning algorithms were used to screen features of ovarian ageing from public ovarian transcriptome data. The candidate serum biomarker, endoplasmic reticulum aminopeptidase-2 (ERAP2), was compared between 60 POI patients and 60 control women. A prospective follow-up of 4 years was conducted on POI patients, and prediction models were established for intermittent recovery of ovarian function and clinical pregnancy based on serum ERAP2 levels.
Main Outcome Measures: Intermittent recovery of ovarian function and clinical pregnancy.
Results: Machine learning models identified ERAP2 as a novel biomarker associated with ovarian ageing. POI patients exhibited significantly elevated serum ERAP2 levels compared to controls (5.78 +/- 2.29 ng/mL vs. 4.81 +/- 2.20 ng/mL, p = 0.018). With a prospective follow-up of these POI patients, ERAP2 was found to be a new biomarker for predicting intermittent recovery of ovarian function (AUROC = 0.763, 95% CI 0.734-0.792) and clinical pregnancy (AUROC = 0.768, 95% CI 0.749-0.787). Integrating ERAP2 into existing indices significantly improved their prediction accuracy both in predicting intermittent recovery of ovarian function (IDI = 0.166, p = 0.008) and in clinical pregnancy (NRI = 0.442, p = 0.034; IDI = 0.208, p = 0.018).Conclusions Serum ERAP2 can serve as a biomarker for intermittent recovery of ovarian function and clinical pregnancy in patients with POI. Combining ERAP2 with other clinical indicators may facilitate personalised intervention strategies for patients with POI in clinic.FALSEsciescopu
Electric field-induced anomalous structural dynamics of nanodomains in BaTiO3-based relaxor ferroelectric thin films
No full textRelaxor ferroelectrics (RFEs) exhibit ultra-high piezoresponse and unique frequency-dependent dielectric properties making them an attractive choice for next-generation electronic devices. However, the underlying mechanisms governing the structural evolution and dynamic behavior of polar nanodomains (PNDs) under an applied electric field remain a significant open question. Here, time-resolved X-ray microdiffraction technique with picosecond resolution is utilized to investigate the structural dynamics of PNDs in (111)-oriented Sn-doped BaTiO3 (BTS) epitaxial RFE thin films. The findings demonstrate that the polarization of nanodomains rotates towards the out-of-plane direction, leading to modulation of d-spacing values as well as contributing to an ultra-high piezoelectric response. An anomalous polarity dependence in piezoelectric strain is observed, with a higher strain under a negative electric field. The strain response also shows a strong dependence on the pulse width/frequency of the electric field, along with an ultra-high piezoelectric strain of up to 1.2%, outperforming various Pb-based relaxor systems. Our findings reveal an intricate interplay between polarization rotation dynamics and electric field polarity in RFEs. These insights not only redefine our understanding of PND dynamics but also pave the way for the development of sustainable, high-performance Pb-free piezoelectrics, ultra-high energy density capacitors, nanoactuators and ultra-compact electronic devices. © 2025 Elsevier B.V., All rights reserved.FALSEsciescopu
Antioxidant and Neuroregenerative Properties of hDPSC Secretome Identified by LC-MS/MS Proteomics in Ischemic Stroke Models
No full textIschemic stroke causes extensive neuronal damage due to oxidative stress, mitochondrial dysfunction, and apoptotic cell death. The secretome derived from human dental pulp stem cells (hDPSCs) has emerged as a promising paracrine therapeutic candidate, offering antioxidant and neuroregenerative potential. In this study, we performed a comprehensive proteomic analysis of the hDPSC secretome using LC-MS/MS to elucidate its mechanism of action, with a focus on its effects across multiple models of ischemia-induced neural injury, including HT22 hippocampal neurons, BV-2 microglial cells, and mouse brain cortex and hippocampus tissues. Proteins identified from the hDPSC secretome were compared with those present in serum-free DMEM to isolate high-confidence factors, resulting in the selection of 346 proteins detected consistently in at least two biological replicates. Gene Ontology (GO) enrichment analysis revealed that these proteins were strongly associated with extracellular vesicles, extracellular matrix structural components, and antioxidant activity. Molecular function and pathway enrichment pointed to regulation of oxidative stress, apoptosis, and neurogenesis, with significant representation in processes such as “wound healing,” “response to reactive oxygen species,” and “negative regulation of apoptotic process.” In HT22 hippocampal neurons subjected to hypoxic stress, proteomic analysis of the hDPSC secretome revealed DEPs associated with mitochondrial homeostasis. Notably, components related to electron transport and mitochondrial permeability transition were reduced, suggesting mitigation of mitochondrial ROS generation. In parallel, proteins linked to mitophagy regulation were also identified, indicating a potential role of the secretome in modulating mitochondrial turnover. These observations support the role of the hDPSC secretome in reducing oxidative stress and suppressing mitophagy-associated apoptotic pathways under hypoxic conditions. In BV-2 microglial cells exposed to hypoxic conditions, proteomic analysis indicated that the hDPSC secretome modulated not only components of the TNF signaling pathway, a key mediator of neuroinflammatory responses, but also pathways related to the cell cycle and oxidative phosphorylation. These findings suggest that the secretome attenuates pro-inflammatory activation and supports a shift toward an anti-inflammatory, M2-like microglial phenotype. In ischemia-affected cortex and hippocampus tissues, proteomic signatures of the hDPSC secretome included factors involved in extracellular matrix remodeling and synaptic maintenance. In the hippocampus specifically, a reduction in ROS levels was observed, potentially mediated by antioxidant enzymes and the regulation of mitophagy-related pathways. These findings point to a coordinated mechanism through which the secretome supports mitochondrial stability and reduces oxidative damage in ischemic brain regions. In summary, LC-MS/MS-based proteomic profiling of the hDPSC secretome reveals a diverse array of neuroprotective proteins that collectively regulate oxidative stress, mitochondrial dynamics, and inflammatory signaling across multiple ischemia-relevant models. These findings highlight the therapeutic potential of the hDPSC secretome as a cell-free strategy for treating ischemic stroke and provide a molecular framework for its neuroprotective effects.DoctorABSTRACT i
CONTENTS iii
LIST OF FIGURES v
I. INTRODUCTION 1
II. MATERIALS AND METHODS 4
2.1. Animals and ethics approval 4
2.2. Primary hDPSC culture 4
2.3. Preparation of the hDPSC secreotme 5
2.4. Cell culture, hypoxia induction, and treatment with the hDPSC secretome 5
2.5. Induction of photothrombotic stroke and treatment with the hDPSC secretome 6
2.6. Cell viability 7
2.7. ROS detection 7
2.8. Superoxide dismutase activity 8
2.9. Apoptosis analysis 8
2.10. Western blot analysis 8
2.11. Real-time quantitative PCR (RT-qPCR) 9
2.12. Tissue preparation and immunohistochemistry 10
2.13. Protein extraction and digestion 10
2.14. LC-MS/MS data acquisition 11
2.15. LC-MS/MS data analysis 12
2.16. Behavioral tests 12
2.17. Statistical analyses 13
III. RESULTS 15
3.1. hDPSC secretome mitigates cellular stress induced by hypoxia 15
3.2. Hypoxia and hDPSC secretome predominantly influence mitochondrial dynamics in HT22 neurons . 16
3.3. hDPSC secretome reduces mitochondrial ROS and suppresses mitophagy in hypoxia-induced HT 22
neurons 17
3.4. hDPSC secretome attenuates intracellular ROS and apoptosis in HT22 neurons by regulating autophagy
and enhancing anti-apoptotic signaling 18
3.5. hDPSC secretome reduces cerebral infarction and neuronal apoptosis in a mouse model of ischemic
stroke 19
3.6. Quantitative proteomic analysis reveals brain and microglial responses to stroke and hDPSC secretome
treatment 20
3.7. hDPSC secretome reduces mitochondrial ROS in the post-stroke brain by enhancing mitophagy and
antioxidant pathways 21
3.8. hDPSC secretome reprograms hypoxia-induced immunometabolic alterations in BV-2 microglial cells
. 23
3.9. hDPSC secretome promotes neurovascular remodeling in the dentate gyrus and cortex after stroke 25
3.10. hDPSC secretome restores synaptic structure and plasticity in the post-stroke brain 27
3.11. hDPSC secretome promotes cognitive and motor recovery after ischemic stroke 29
IV. DISCUSSION 73
CONCLUSION 78
REFERENCE 79
ABSTRACT IN KOREAN 86
ACKNOWLEGEMENT 88
CURRICULUM VITAE 8
Cooperative Merging in Mixed Traffic Based on Strategic Influence of Connected Automated Vehicles on Human-Driven Vehicle Behavior
No full textCooperative on-ramp merging control for connected and automated vehicles (CAVs) can significantly enhance traffic flow and fuel efficiency at highway merging points. However, in mixed traffic scenarios where CAVs coexist with human-driven vehicles (HDVs), the unpredictable behavior of HDVs poses challenges to safety and coordination. While many cooperative merging strategies focus on individual CAV control, fewer have addressed the coordination of multiple CAVs in such settings. This study introduces an optimization-based cooperative merging strategy for all CAVs within a control zone, considering interactions with HDVs of uncertain intentions. A key innovation is the strategic influence of CAVs on HDV behavior by slowing down the CAV preceding HDVs, thereby allowing other CAVs on the adjacent road to merge in front of the HDVs with reduced uncertainty. The optimal slowdown pattern is identified by evaluating CAV throughput across various candidate patterns, with dynamic optimization applied at each time a new vehicle enters the control zone to effectively manage HDV uncertainties. Experimental results from various mixed-traffic scenarios show that the proposed strategy reduces the average travel time delay by up to 31% compared to an existing optimization-based approach. © 2025 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH.TRUEsciescopu
Autonomous Operation of UAS in Complex Environments Using Data- and Vision-Based Deep Reinforcement Learning and Validation by AirSim and Flight Test
No full textReal-time autonomous path planning is a critical capability in unmanned aerial vehicle (UAV) operations, especially in complex environments that involve both static and dynamic obstacles. This study proposes a dual-layer unmanned mobility framework that integrates dynamic obstacle avoidance based on data communication with static obstacle avoidance based on vision. The data communication-based layer utilizes the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to process real-time position and velocity data from the Ground Control System (GCS), thereby reducing collision risks and enabling safe route planning in multi-UAV operations. The vision- based layer utilizes a depth camera to detect and avoid previously unknown or unpredictable obstacles, enabling real-time trajectory adjustments without relying on pre-mapped data. The duallayer UAS operation system underwent a rigorous multi-phase validation process. Initially, the system was validated through Software-in-the-Loop (SITL) simulations conducted using Microsoft's AirSim platform, which provided a high-fidelity environment for realistic training and performance assessment. SITL enabled effective testing of decision-making algorithms in complex environments containing both static and dynamic obstacles. To further enhance the reliability of the proposed system and assess its performance under hardware constraints, Hardware-in-the-Loop (HITL) testing was subsequently implemented as an intermediate verification step. The HITL configuration enabled real-time assessment of attitude and angular rate tracking through flight controllers, ensuring system stability and precise control before actual flight testing. Finally, actual flight tests were conducted at the drone test field of the Gwangju Institute of Science and Technology (GIST). Consistent results observed across SITL, HITL, and flight tests validated the system's practicality, robustness, and applicability to real-world UAV operations in complex obstacle environments. This dual-layer hybrid framework demonstrates the effective integration of data communication and vision-based strategies, enabling reliable and efficient UAV navigation in complex environments. The findings support the potential of this system for advanced UAV applications in urban logistics, military missions, and disaster response operations
pH-Dependent Solid-Phase Extraction for Enhanced Detection of Persistent Toxic Substances in Consumer Products by High-Resolution Mass Spectrometry
No full textPhase-dependent amplification switching in a double-Raman system
No full textWe experimentally observed phase-dependent optical gain a double-A active Raman gain (ARG) system, which may offer potential applications in quantum field amplification as well as bio-imaging techniques. The optical gain in a double-A ARG system was conditioned by the relative phase between two probe fields. By detuning the double-A ARG system from the optical transition states, spontaneous decay was effectively suppressed, thereby enabling a fully coherent process. By optimizing the multi-photon interaction parameters, we achieved probe field amplification of up to 5 times of their initial intensities. The gain could be all-optically switched off by simply varying the relative phase between the probe fields to it within the loop, demonstrating theoretical analysis of a double-A ARG system.FALSEsciescopu
Wearable Image-Based Colorimetric Sensor for Real-Time Gas Detection with High Chromaticity
No full textFlexible gas sensing technologies are essential for a wide range of environments and applications, from wearable devices to large-scale industrial systems. Among various approaches, colorimetric sensing stands out for its distinct advantages, including energy-free operation, intuitive visual feedback, and high resistance to environmental disturbances. Leveraging ultrathin resonators, colorimetric sensing achieves enhanced chromaticity and angular stability. In this study, a flexible colorimetric gas sensor is introduced based on a resonator array integrated with polyvinyl alcohol (PVA). This sensor achieves nearly 100% coverage of the standard RGB color gamut, enabling precise and visually distinguishable gas detection. Fabricated on a flexible substrate, it demonstrates remarkable angular robustness, maintaining consistent color under incident light angle variations of up to 60°. This capability, combined with rapid response times of 180ms for PVA swelling and 210ms for shrinking, highlights the sensor's adaptability for diverse applications, including wearable devices and industrial-scale monitoring. Furthermore, the sensor is evaluated under various volatile organic compounds (VOCs) and imaging conditions, showcasing its potential for image-based analysis and accurate VOC detection. Notably, it demonstrated the ability to detect VOC concentrations that are indistinguishable using a single sensor by simultaneously analyzing data from four sensor arrays. © 2025 The Author(s). Advanced Electronic Materials published by Wiley-VCH GmbH.TRUEsciescopu