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Effects of photobiomodulation on multiple health outcomes: an umbrella review of randomized clinical trials
No full textBackgroundPhotobiomodulation (PBM) is a non-invasive therapy increasingly used for pain, inflammation, and tissue repair, yet a comprehensive synthesis of its effectiveness across multiple health outcomes remains lacking. Herein, we aimed to systematically assess the clinical effects and strength of evidence for PBM across a wide range of health outcomes using data from existing meta-analyses of randomized controlled trials (RCTs).MethodsWe conducted an umbrella review of meta-analyses of RCTs, searching five databases up to December 8, 2023. Two reviewers independently assessed methodological quality using AMSTAR 2 and evaluated certainty of evidence using a modified GRADE framework. Pooled effect sizes were recalculated as equivalent standardized mean differences (eSMD) with 95% confidence intervals (CI). The study was registered with PROSPERO (CRD42023495502).ResultsA total of 15 meta-analyses encompassing 204 RCTs and over 9000 participants were included, covering 35 health endpoints across 15 disease conditions. PBM showed significant effects for 12 outcomes, with moderate certainty of evidence supporting improvements in burning mouth syndrome (pain reduction, eSMD - 0.92 [95% CI - 1.38 to - 0.46]), knee osteoarthritis (disability, 0.65 [0.14 to 1.15]), fibromyalgia (fatigue, 1.25 [0.63 to 1.87]), androgenetic alopecia (hair density, 1.32 [1.00 to 1.63]), and cognitive function (0.49 [0.14 to 0.84]). Most other outcomes exhibited low or very low certainty due to heterogeneity or small-study effects. P-curve and funnel plot analyses indicated evidential value for several outcomes, though potential publication bias was identified in some.ConclusionsPBM appeared beneficial for some health conditions, such as the strongest support for fibromyalgia, osteoarthritis-related disability, and cognitive impairment. However, given the overall low-to-moderate certainty of evidence for most endpoints, further high-quality trials and standardization of PBM protocols are warranted before widespread clinical adoption.TRUEsciescopu
Mode-coupled infinite topological edge state in bulk-lattice-merged mechanical Su–Schrieffer–Heeger chain
No full textBand topology has emerged as a powerful tool for designing mechanical engineering systems, from phononic crystals to metamaterials. Various design principles — whether bulk-based or lattice-based — have been proposed and successfully implemented according to unit cell structures. Here, we present a bulk-lattice merged Su–Schrieffer–Heeger (SSH) chain constructed from single-column woodpile metamaterials. This system consists of a lattice array of cylindrical particles, where each particle's bulk dynamics exhibits local resonance-mode coupling with wave propagation. We demonstrate that topological edge states emerge in direct correspondence with these local resonance modes, manifesting as mode-coupled topological states. Experimentally, we observe the initial emergence of these mode-coupled topological edge states, with their frequencies accurately predicted by nonlinear characteristic equations rooted in continuum dynamics and topological symmetry. Additionally, the system's weak nonlinearity enables simultaneous frequency shifts, allowing multivariate tunability in its topological states. © 2025 Elsevier LtdFALSEsciescopu
Nonconjugated Radical Polymers-Based High-Yield Organic Memory and Ethanol In-Sensor Computing
No full textOrganic memristors are promising candidates for next-generation soft, biorealistic electronics due to their flexibility, biocompatibility, processability, and low power consumption. These features facilitate their seamless incorporation into mechanically compliant platforms, thereby expanding their potential for use in emerging applications such as flexible in-sensor computing architectures. However, conventional organic memristors based on conjugated polymers often suffer from low device yield and reliability due to their semicrystalline nature, which leads to film roughness and pinhole formation. In contrast, nonconjugated radical polymers offer amorphousness and intrinsic memristivity from stable redox activity, making them ideal for uniform memristive switching layers. Furthermore, the molecular tunability of nonconjugated radical polymers enables precise control over polymer properties, which significantly improves the reliability and fabrication yield of organic memristive devices. In this study, we demonstrate a high-yield organic memristor and a soft in-sensor computing system based on a radical polymer tailored through molecular design. This organic memristor arrays shows over 95% fabrication yield, excellent switching performance (on/off >106, retention >4 × 105 s, endurance >500 cycles), and mechanical durability over 1,000 bending cycles. Additionally, the device also shows chemical sensitivity toward ethanol, enabling multifunctional operation in soft in-sensor computing systems. This work demonstrates a polymer engineering strategy that enhances both the physical robustness and multifunctionality of organic memristive materials, advancing their potential in flexible and biointegrated electronics.Master1. INTRODUCTION 1
1.1 Background and motivation of organic memristor 1
1.2 Conjugated and Nonconjugated Polymers for Organic Memristive Devices 3
1.3 Molecular engineering strategies toward high yield device 4
2. EXPERIMENTAL DETAILS 5
2.1 Materials 5
2.2 Synthesis of nonconjugated radical polymer 5
2.3 Characterizations of nonconjugated radical polymer 9
2.4 Memristive device fabrication 10
2.5 Electrical analysis of memristor 11
2.6 In vitro cell viability test 12
3. RESULTS AND DISCUSSION 13
3.1 Nonconjugated radical polymer overview 13
3.2 Synthesis and molecular characterization 16
3.3 Resistive switching performance 29
3.4 Mechanistic aspects of the resistive switching 36
3.5 Multifunctionality of PTEI Devices 45
3.6 In-sensor computing capabilities 53
4. CONCLUSION 60
References 61
Acknowledgements 6
Global, regional and national trends in suicide mortality rates across 102 countries from 1990 to 2021 with projections up to 2050
No full textGlobal trends and future projections of suicide mortality are crucial to providing policy decision-makers with insights into estimating the global and future burden of suicide; however, they require techniques accounting for the effects of age, period and cohort on trends in suicide mortality and considering various factors such as population growth and aging. Therefore, we aimed to estimate the global trends in suicide mortality rates from 1990 to 2021 and the future projection of suicide deaths until 2050 across 102 countries. Global trends were calculated using a locally weighted scatter-plot smoother (LOESS) curve, and the association between the rates and socioeconomic and geographical indicators was investigated. The study also projected future suicide mortality rates up to 2050 using the Bayesian age–period–cohort model. In addition, a decomposition analysis was performed to identify the variations in suicide deaths, specifically examining factors such as population growth, aging and epidemiological changes. Of the 102 countries included in the analysis of suicide mortality, 54 were high-income countries (HICs) and 48 were low- and middle-income countries (LMICs). The LOESS estimate of the global suicide mortality rate decreased from 10.33 (95% confidence interval, 9.67–10.99) deaths per 100,000 people in 1990 to 7.24 (6.58–7.90) deaths per 100,000 people in 2021. Notably, overall global suicide mortality rates were higher among males compared with females, with males showing a decline from 16.41 (15.23–17.58) in 1990 to 11.51 (10.33–12.68) in 2021, and females from 4.65 (4.41–4.89) in 1990 to 3.22 (2.98–3.46) in 2021. In addition, HICs also had higher suicide mortality rates, from 12.68 (11.96–13.40) in 1990 to 8.61 (7.89–9.33) in 2021, compared with LMICs, which showed 7.88 (6.93–8.84) in 1990 and 5.73 (4.77–6.69) in 2021. We also identified an association between the age-standardized suicide rates and several parameters, including the Human Development Index (β, 24.250; P = 0.001), Sociodemographic Index (β, 0.091; P < 0.001), reverse Gender Gap Index (β, −39.913; P = 0.002), Gender Inequality Index (β, 13.229; P = 0.016) and latitude (β, 23.732; P < 0.001). The future predicted number of global suicide deaths up to 2050 would slightly decrease from 8.60 (95% credible interval, 8.40–8.83) deaths in 2021 to 8.42 (6.60–10.61) in 2030, 7.39 (4.25–13.17) in 2040 and 6.49 (2.19–17.57) in 2050. Although population growth and aging had contributed to an increase in the number of deaths, the overall count in 2021 had decreased compared with 1990, primarily due to the decline in the age-standardized suicide mortality rates. A global trend for a decrease in suicide mortality rate was observed from 1990 to 2021. Reflecting the overall decline, future suicide deaths are forecasted to decrease up to 2050 at the global level, with certain groups and countries remaining more vulnerable to suicide deaths. Therefore, these findings suggest the need for more effective strategies and policies to reduce suicide mortality. © 2025 Elsevier B.V., All rights reserved.FALSEscopu
Efficient spin-to-orbital Hall current conversion at THz frequency
No full textThe generation of ultrafast orbital current has emerged as a subject of considerable interest in modern information technology, analogous to the role of spin currents. In this work, we demonstrate that the insertion of a thin Pt interlayer (1-3 nm) introduced between ferromagnetic and nonmagnetic layers significantly enhances the optically-driven terahertz emission. By systematically comparing nonmagnetic elements that exhibit finite spin Hall conductivity alongside relatively large orbital Hall conductivity, we establish the efficient conversion of terahertz spin currents into orbital Hall currents across nanometer-scale distances in magnetic heterostructures. © 2025 SPIE
High on/off ratio ZnS-based ReRAM with multi-level switching characteristics
No full textResistive random-access memory (ReRAM) devices based on zinc sulfide (ZnS) were fabricated and characterized. The devices consist of a Ti/Pt bottom electrode (BE), radio-frequency magnetron sputtered 30-nm-thick ZnS switching layer, and a 150-nm-thick Ag top electrode (TE). X-ray photoelectron spectroscopy (XPS) confirmed the chemical composition and identified intrinsic defects in ZnS, contributing to the resistive switching. Electrical measurements reveal stable cycling behavior, high on/off ratio (∼5 × 103), excellent endurance (∼2 × 103 cycles), and good retention (∼6 × 103 s) characteristics. Cycle-to-cycle and device-to-device variability analysis demonstrated low coefficients of variation (CVs) for resistance states and switching voltages, suggesting stable operation and high uniformity. The resistive switching is attributed to conductive filament (CF) formation and rupture driven by Ag ion migration through ZnS bulk defects. Multi-level switching was achieved by controlling the writing current (IW) and evaluated using bit error rate (BER) analysis. The ZnS-based ReRAM exhibited reliable multi-level switching characteristics up to six distinct resistance states, indicating its potential for high-density memory devices. © 2025TRUEsciescopu
Development of a basic GNSS-based lateral control system for autonomous vehicles
No full textRecently advances in lateral control systems for autonomous vehicles have been focused on achieving high path tracking precision and stable control performance. Building on these efforts, this study designs and implements a lateral control system that addresses limitations such as the absence of path coordinate data, specifically for autonomous vehicles with limited sensor configurations relying solely on GNSS(Global Navigation Satellite System) and IMU(Inertial Measurement Unit). The proposed system consists of three stages: positioning, path tracking, and vehicle control. In the positioning stage, precise positioning is achieved by applying RTK (Real-Time Kinematic) correction and integrating GNSS, IMU data. Additionally, a method is proposed to collect and process path coordinate data in environments where predefined route(path) coordinates are unavailable. In the path tracking stage, an efficient path tracking algorithm based on the Stanley method is implemented and applied to the collected path coordinate data. Finally, in the vehicle control stage, a PID controller is utilized to enhance control precision by minimizing the difference between the vehicle's actual heading and the target heading through adjustments to the steering wheel angle. The experiment was conducted by driving along two target paths within the GIST campus. On the first target path, the Mean Absolute Error(MAE) was recorded at 0.0786m, and the Root Mean Square Error(RMSE) was 0.1140m. Additionally, the average error between the vehicle's target heading and actual heading was recorded as 2.1411°. On the second route, the MAE was 0.0427m, and the RMSE was 0.0802m. The average error between the target heading and actual heading was 2.5000°, demonstrating the performance of the lateral control system. This study demonstrated that stable and efficient path tracking and control performance can be achieved even with limited sensor configurations. It is expected to serve as a foundation for future advanced autonomous driving systems integrating various sensors.MasterList of contents
Abstract i
List of contents ii
List of tables iv
List of figures v
I. INTRODUCTION 1
1. 1. Research Background 1
1. 2. Related Work 2
1. 2. 1. Lateral control of autonomous vehicles 2
1. 2. 2. Autonomous vehicle sensors and positioning · 3
II. Overall System & Positioning 5
2. 1. System overview 5
2. 2. Positioning 7
2. 2. 1. GNSS 7
2. 2. 2. RTK 9
2. 2. 3. GNSS heading 10
2. 2. 4. IMU 11
2. 3. Waypoint Ground Truth Data 12
2. 3. 1. Path coordinate post-processing 12
2. 3. 2. Selected path coordinate data 16
III. Path Tracking 21
3. 1. Selection of path tracking algorithm 21
3. 2. Detailed explanation of the Stanley method 22
3. 2. 1. Application strategy of the Stanley method 23
3. 2. 1. 1. Target point search 23
3. 2. 1. 2. Error calculation 23
IV. Vehicle Control 25
4. 1. PID controller 25
V. Experiments 28
VI. Result & Discussion 30
6. 1. Target path 1 30
6. 2. Target path 2 32
VII. CONCLUSION 36
SUMMARY 3
Noise-Robust Speaker Verification With Attenuated Speech Restoration and Consistency Training
No full textEven though the performance of speaker verification (SV) has been significantly improved with deep learning approaches, it may degrade severely in the presence of background noises. Simple approaches to relieve this issue would be multi-condition training (MCT) and adopting a speech enhancement (SE) module as a pre-processor. However, whether joint-trained with the SV module or not, the SE module may occasionally incur speech attenuation which leads to the partial loss of speaker information. To address this problem, in this paper, we propose a noise-robust SV system with the SE front-end incorporating a speech restoration module using lost information aggregation and consistency training. In the speech restoration module, the lost information obtained from the noisy and enhanced latent representations processed with different sizes of the receptive field is aggregated to produce restored speech features using a loss function penalizing speech attenuation. Moreover, to further improve the robustness to the background noises and unseen data, we adopt consistency training to make the speaker embeddings for the noisy speech similar to those for the clean speech obtained by a pre-trained SV model. Our experimental results demonstrated that the proposed system significantly improved the performance of the speaker verification for the VoxCeleb dataset mixed with environmental noises, and exhibited the generalization capability in the experiment on the CHiME-4 dataset.FALSEsciescopu
Development of advanced aftertreatment catalysts via active site control for industrial emission control
No full textThis research investigates catalyst-based emission control strategies tailored for realistic industrial exhaust conditions, emphasizing active site engineering. The main objective is to understand how different catalyst synthesis methods affect active site structures and catalytic reaction mechanisms, enabling rational design of superior emission control systems. Several studies were conducted under realistic industrial conditions, examining varying gas compositions and synthesis methods to optimize catalyst activity for pollutants such as CO and NH3. Four distinct catalytic systems, from noble metals to transition metal oxides, were explored to evaluate active site control strategies.
The first study developed a Pt-V-W/TiO2 catalyst exhibiting unique bimetallic active sites from strong Pt-V interactions, significantly enhancing N2 selectivity in selective catalytic oxidation of NH3 (NH3-SCO). Under realistic conditions containing NH3 and CO, this catalyst simultaneously oxidized both pollutants effectively. It facilitated in-situ NOx reduction via internal SCR (i-SCR) and CO-assisted SCR (CO-SCR), achieving high conversion to N2. This multifunctional behavior demonstrates its effectiveness under complex exhaust conditions. The second approach involved creating a two-dimensional cobalt silicate catalyst (Co-DML) through hydrothermal delamination of an MWW-type zeolite precursor. Increasing the hydrothermal temperature transformed the structure from 3D to 2D, generating two distinct active sites: framework-incorporated Co (strong Lewis acidity) and dispersed Co3O4 (reducibility). These combined properties enabled effective NH3 adsorption and conversion predominantly via i-SCR mechanisms, enhancing both NH3 conversion and N2 selectivity under realistic conditions.
Subsequent studies examined strong metal-support interactions (SMSI) to selectively form desirable active phases. Specifically, Co supported on Al2O3 typically forms inactive cobalt aluminate phases due to detrimental interactions involving surface hydroxyl groups. To overcome this, a controlled dry impregnation synthesis strategy was developed. Initially, extensive dehydroxylation of γ-Al2O3 under inert conditions removed surface hydroxyl groups, minimizing undesired SMSI. Subsequent cobalt precursor impregnation onto this modified support resulted in highly dispersed Co3O4 nanoparticles, as confirmed by XRD, HR-TEM, and XPS. This method substantially improved NH3 oxidation performance, even at lower cobalt loadings, indicating cost-effective catalyst potential.
Next, to enhance low-temperature NOx reduction under oxygenated hydrocarbon-rich conditions typical in semiconductor fabrication emissions, an AgCo/Al2O3 catalyst was developed using isopropyl alcohol (IPA-SCR). This catalyst demonstrated significantly improved NOx conversion compared to conventional Ag/Al2O3. Characterizations including H2-TPR, EtOH-TPD, in-situ DRIFTS revealed Ag and Co co-impregnation promoted formation of Ag2O-Co3O4 Janus structures, essential for IPA activation. The generated enol-type intermediates facilitated reactive -NCO and -CN species formation, significantly enhancing NOx reduction under low-humidity conditions.
Finally, a sustainable approach was explored to convert spent NCM cathode waste into active oxidation catalysts through chemical delithiation and oxidative heat treatment. Chemical delithiation extracted lithium ions extensively, inducing oxygen vacancies via charge compensation. Subsequent oxidative heat treatment promoted Ni exsolution, forming dispersed NiO active sites. Oxidation-induced volumetric expansion increased specific surface area significantly. The resulting upcycled catalyst showed superior performance in oxidizing CH4, CO, and NH3 compared to conventional catalysts. This approach provides a practical strategy for recycling lithium-ion battery waste, addressing environmental challenges and air pollutant mitigation simultaneously.
In conclusion, this body of work demonstrates that strategic control of active sites across diverse catalytic systems can significantly enhance the selective removal of harmful emissions. By tailoring the composition, structure, and chemical state of active sites, the studied catalysts achieved superior N2 selectivity and oxidation activity, even under the complexed conditions of real-world emission control. The active site engineering strategies proposed herein offer a practical pathway for developing high-performance aftertreatment catalysts that can meet increasingly stringent environmental regulations and contribute meaningfully to industrial emission control.DoctorABSTRACT ⅰ
LIST OF CONTENTS ⅳ
LIST OF TABLES AND FIGURES ⅵ
Ⅰ. Chapter 1: Introduction 1
1.1 Fundamental background about environmental catalyst 1
1.2 Impact of Active Sites Modification in Heterogeneous catalyst 5
1.2.1 Modification of Active Sites 5
1.2.2 Utilizing Strong Metal Support Interaction (SMSI) 6
1.2.3 Support Modification 7
1.3 Strategies to advance environmental catalysts 8
1.3.1 NH3 Selective Catalytic Oxidation (NH3-SCO) 8
1.3.2 Active Phase Control for Designing Superior Oxidation Catalyst 10
1.3.3 DeNOx Catalysis Using Isopropyl Alcohol as a Reductant 11
1.3.4 Upcycling LIB Cathode to Superior Thermal Catalyst 12
1.4 Research objectives 13
Ⅱ. Chapter 2: Experimental Methods 17
2.1 Catalyst Preparation 17
2.1.1 Pt-V-W/TiO2 Catalyst 17
2.1.2 Co-DML Catalyst 18
2.1.3 Dry Impregnation Method for Co/Al2O3 catalyst 18
2.1.4 AgCo/Al2O3 Catalyst for IPA-SCR 19
2.1.5 Delithiation and Heat-treatment method for Upcycling NCM to Thermal Catalyst 19
2.2 Catalytic activity test 20
2.3 Catalyst Characterizations 22
Ⅲ. Chapter 3: Development of NH3-SCO Catalysts via Bimetallic Oxide and Dual Active Sites 25
3.1 Bimetallic Pt-V Oxide Active Sites for Enhanced N2 Selectivity on NH3-SCO Reaction 27
3.1.1 NH3 and CO oxidation performances over Pt-V-W/TiO2 catalyst 27
vi
3.1.2 Revealing the role of Pt-V interaction 33
3.1.3 Internal SCR mechanism during oxidation reaction 7 40
3.1.4 Real-world application via dual-zone monolith catalytic system 49
3.2 Impact of Dual Active Sites Formation over N2 Selectivity on NH3 Oxidation Reaction 50
3.1.1 Synthesis of Co-DML catalyst 50
3.1.2 Elucidating dual active sites formation over Co-DML catalyst 54
3.1.3 NH3-SCO reaction performance of Co-DML catalyst 58
Ⅳ. Chapter 4: Active Phase Control for Oxidation Catalysts via Novel Synthesis Strategy 62
4.1 Selective Co3O4 Active Phase Formation via Dry Impregnation Method 64
4.1.1 Heat treatment and dehydroxylation of Al2O3 64
4.1.2 Morphology of CoS/D-Al2O3 via dry impregnation method 67
4.1.3 Phase and oxidation activity of CoS/D-Al2O3 70
Ⅴ. Chapter 5: Enhancing NOx reduction performance using isopropyl alcohol as a reductant over
AgCo/Al2O3 catalyst for semiconductor FAB emission control 76
5.1 Inhibited SCR Route and Challenges Triggered by Moisture-deficient Condition over Ag/Al2O3 78
5.2 Promotional Role of cobalt co-impregnation over AgCo/Al2O3 Catalyst 83
5.3 Elucidating Co3O4-driven Mechanism Enhancing IPA-SCR Performance 91
Ⅵ. Chapter 6: Upcycling NCM Cathode to Highly Active Thermal Catalyst 96
6.1 Impact of Delithiation and Heat-treatment 97
6.2 Cross-sectional analysis for Surface Diffused NiO Active Sites 104
6.3 Catalytic Activity of Various Thermal Reactions 111
Ⅶ. Chapter 7: Conclusions 116
References 12