Background: Lumbar radiculopathy caused by disc herniation is frequently accompanied by pain, functional disability, and impairments in sensorimotor control, including reduced proprioception and altered motor control. Interventions that integrate neural and mechanical components may enhance rehabilitation outcomes beyond exercise alone. Objectives: To investigate the effects of manual therapy combined with neurodynamic exercise and motor control exercise (MTN) with motor control exercise alone (MCE) on lumbar proprioception, motor control, and functional disability in patients with lumbar radiculopathy. Design: Randomized, single-blind clinical trial. Methods: Thirty patients with lumbar radiculopathy due to L4–S1 disc herniation were randomly assigned to either the MTN group or the MCE group. Both groups participated in supervised interventions three times per week for six weeks. The MTN group received lumbar joint mobilization and slider-based neurodynamic mobilization integrated with motor control exercise, whereas the MCE group performed motor control exercise only. Lumbar proprioception was assessed using joint position error during trunk flexion and extension. Motor control was evaluated using pressure biofeedback–based abdominal drawing- in performance. Functional disability was assessed using the Korean version of the Oswestry Disability Index. Outcomes were measured at baseline and during follow-up. Results: Significant group-by-time effects were observed for lumbar joint position error, motor control outcomes, and functional disability. The MTN group demonstrated earlier and greater improvements across all outcome measures compared with the MCE group, whereas improvements in the MCE group were more gradual. Conclusion: Compared with motor control exercise alone, the addition of manual therapy and neurodynamic exercise resulted in superior improvements in lumbar proprioception, motor control, and functional disability. An integrated MTN approach may be an effective rehabilitation strategy for patients with lumbar radiculopathy.

Background: Weakness of the abdominal muscles reduces trunk control and impairs respiratory function in stroke patients. To strengthen the abdominal muscles, threshold expiratory muscle training and trunk FES can be used. Objectives: This study aimed to investigate whether a combined intervention of threshold expiratory muscle training and trunk FES is more effective in improving trunk control and respiratory function than threshold expiratory muscle training alone. Design: Randomized controlled trial. Methods: Thirty individuals with stroke were randomly assigned to either the experimental group (n=15) or the control group (n=15). The experimental group received threshold expiratory muscle training with trunk electrical stimulation, while the control group performed threshold expiratory muscle training only. Both groups underwent training three times per week for four weeks. Trunk control and respiratory function were assessed pre and post the intervention. Results: Both groups showed significant post-intervention improvement in respiratory function; however, the experimental group demonstrated a greater change than the control group. The control group showed significant improvement only in the total TIS score, whereas the experimental group showed significant improvement across all TIS subcomponents. Conclusion: Combining threshold expiratory muscle training with trunk FES is an effective approach for enhancing not only respiratory function but also trunk control. Synchronizing electrical stimulation with expiratory timing may increase efficiency and strengthen functional muscle contraction, suggesting meaningful clinical value.

Activated carbons with high micro-/meso-porosity derived from biomass are increasingly popular as sustainable materials. However, these carbons often struggle with low carbon content and limited structural stability. Here, we present Mongolian anthracite-based carbons synthesized via carbonization and chemical activation. Structural analysis shows that Act-MRA samples develop plate-like morphologies with reduced particle size and greater porosity as KOH content increases. The Act-MRA samples have a disordered carbon structure with small graphitic domains, even at higher KOH ratios without significant crystal defects. Notably, Act -MRA3 displays a large specific surface area and high pore volume, with welldeveloped micropores (7–20 Å) and mesopores (20–50 Å) that expand as KOH ratios rise. Electrochemical tests indicate that Act -MRA3 achieves high specific capacitance (220.6 F/g at 5 mV/s) and rate retention (~ 80% at 300 mV/s), owing to its optimized pore structure and enhanced ion transport. These findings underscore the importance of tailored pore structures and defect engineering in boosting activated carbon performance for energy storage.

Ambrosia trifida is an invasive annual plant species that creates dense stands, suppressing native vegetation in affected habitats. To assess its ecological impact and the short-term effectiveness of mechanical management, we conducted field removal experiments using cutting and uprooting methods. We examined plant community composition, species richness, and diversity before and after treatment. Mechanical removal significantly altered plant community structure, leading to increased emergence of native species and reduced dominance of A. trifida, while control plots showed minimal change. Treated plots also had substantially lower soil seed bank density, with most remaining seeds concentrated in the upper 0-5 cm layer, indicating that limiting annual seed input is crucial for suppressing population persistence. However, recovery responses varied by site: Mugunri experienced notable declines in A. trifida cover and a greater establishment of native species, whereas the CCZ site retained A. trifida as a sub-dominant and saw limited recruitment of native species. These differing outcomes suggest that site-specific environmental conditions, initial species pools, and residual seed bank size may affect vegetation recovery after invasive plant removal. While this study demonstrates that mechanical removal disrupts A. trifida dominance and encourages short-term vegetation recovery, its one-year duration limits our understanding of longterm successional pathways. Continued monitoring, repeated annual removal, and assessments across multiple sites are necessary to better understand the mechanisms driving post-removal recovery and to inform the development of effective restoration strategies.

This paper investigates the problem of ship course control in the presence of model uncertainties, external disturbances, and actuator saturation. A high-performance autopilot is developed based on a direct neural network adaptive dynamic surface control (DSC) framework integrated with deep reinforcement learning. To compensate for lumped uncertainties arising from unmodeled dynamics and disturbances, a radial basis function (RBF) neural network is employed to provide online approximation within the control design. Moreover, the actuator saturation constraint is explicitly incorporated into the controller, avoiding performance degradation commonly encountered in conventional DSC schemes.To alleviate the reliance on manual parameter tuning, the controller parameter adaptation is formulated as a continuous-action optimization problem and solved using a deep deterministic policy gradient (DDPG) algorithm. The DDPG agent learns an optimal tuning policy by maximizing a reward function that penalizes course tracking errors, excessive control variations, and energy consumption. Simulation results demonstrate that the proposed method achieves improved tracking accuracy, smoother control inputs, and enhanced robustness under complex operating conditions, thereby validating the effectiveness of the DDPG-based adaptive tuning strategy for autonomous ship navigation.

This paper investigates the problem of ship course control in the presence of model uncertainties, external disturbances, and actuator saturation. A high-performance autopilot is developed based on a direct neural network adaptive dynamic surface control (DSC) framework integrated with deep reinforcement learning. To compensate for lumped uncertainties arising from unmodeled dynamics and disturbances, a radial basis function (RBF) neural network is employed to provide online approximation within the control design. Moreover, the actuator saturation constraint is explicitly incorporated into the controller, avoiding performance degradation commonly encountered in conventional DSC schemes.To alleviate the reliance on manual parameter tuning, the controller parameter adaptation is formulated as a continuous-action optimization problem and solved using a deep deterministic policy gradient (DDPG) algorithm. The DDPG agent learns an optimal tuning policy by maximizing a reward function that penalizes course tracking errors, excessive control variations, and energy consumption. Simulation results demonstrate that the proposed method achieves improved tracking accuracy, smoother control inputs, and enhanced robustness under complex operating conditions, thereby validating the effectiveness of the DDPG-based adaptive tuning strategy for autonomous ship navigation.

Aiming at the control problem of nonlinear uncertain systems with asymmetric saturated actuators and u nknown external disturbances, a composite control method integrating dynamic surface control (DSC), ad aptive neural network estimation, and a nonlinear saturation compensation mechanism is proposed. In the scenarios of ship course and trajectory tracking, the system faces multiple challenges such as symmetric and asymmetric actuator saturation, as well as unknown external disturbances. Radial basis function (R BF) neural networks are utilized for online approximation of unknown nonlinear functions and external d isturbances. Combined with dynamic surface technology, the problem of "explosion of complexity" in tra ditional backstepping control is eliminated. A nonlinear function with inverse correlation to error gain is designed to dynamically adjust the control gain, balancing the requirements of tracking accuracy and sat uration suppression. Furthermore, a Gaussian error function is introduced to construct a continuously diff erentiable asymmetric saturation model. An auxiliary dynamic system is integrated to compensate for the saturation nonlinear effect, achieving smooth amplitude limitation of rudder angle commands. Comparati ve MATLAB simulation results demonstrate that the course tracking error is reduced by 1°, the fluctuati on amplitude of the rudder angle is decreased by approximately 50%, the number of rudder angle satura tion events is reduced by about 60%, and the error convergence time is shortened by roughly 30%. The proposed composite control method effectively addresses the issues of asymmetric saturation and externa l disturbances, significantly enhancing the accuracy and robustness of the ship course control system.

To address the issue of low heading tracking efficiency caused by nonlinear dynamic characteristics in ship heading motion, this paper proposes a neural network-based adaptive hyperbolic tangent control method for ship heading. By designing a second-order system robust controller, a saturated auxiliary design system is introduced into the regulator for direct internal compensation, enhancing the system's anti-interference capability under complex operating conditions. Meanwhile, hyperbolic tangent nonlinear modification is incorporated into the control strategy to optimize the output characteristics of control signals. The controller adopts a backstepping approach to design virtual control laws for trajectory tracking and utilizes the Radial Basis Function (RBF) of neural networks to approximate the uncertain parts of the ship model. The control algorithm is simulated and tested in the MATLAB environment, and its tracking effect is analyzed. Simulation results show that the control algorithm can ensure the stability of the closed-loop system under conditions of dynamic changes in system parameters, external disturbances, and uncertainties, and effectively solve the nonlinear problems in ship traffic control during trajectory tracking. The controller is designed concisely, meets the requirements of engineering practice, improves ship maneuverability, and has reference value for ship control.

Against the backdrop of the rapid development of the global shipping industry and the deep advancement of “dual carbon” goals, energy transition, energy conservation, and emission reduction have become core issues in marine transportation. As a critical component of clean and renewable energy, the efficient development and utilization of wind energy are pivotal for achieving low-carbon shipping. Exhaust turbine sails, an innovative application of active suction control in marine aerodynamic propulsion, regulate boundary layer flow through active suction to enhance wind energy utilization efficiency, which has emerging as a research hotspot in the green transformation of modern shipping. This paper aims to synthesize research on exhaust turbine sails. First, based on fundamental fluid mechanics principles, it analyzes the impact of boundary layer separation on the aerodynamic characteristics of structural bodies. Second, through case studies, it summarizes flow control effects under different suction parameters. It further introduces combined blowing and suction control strategies to explore their influence on boundary layer management. Finally, it details the research progress of exhaust turbine sails, explaining their core principle: active suction control delays or prevents boundary layer separation, effectively suppressing vortex shedding, thereby significantly reducing ship navigation resistance and enhancing lift. The study reveals that the aerodynamic performance of exhaust turbine sails is jointly influenced by oncoming flow conditions, suction power, and structural parameters, necessitating multi-objective optimization to achieve energy efficiency balance. The paper concludes by addressing key challenges in their marine applications and envisioning future directions for integrating these sails with emerging technologies, providing practical implications for promoting the green and low-carbon transformation of the shipping industry.

With the rapid expansion of renewable energy deployment, power systems are increasingly exposed to issues such as higher output variability. Photovoltaic generation, as the most widely installed variable renewable energy source both domestically and internationally, exhibits significant fluctuations due to weather conditions. These characteristics lead to operational challenges including increased curtailment, higher reserve requirements, and even risks of large-scale outages. This study aimed to improve the accuracy of photovoltaic power generation forecasting by developing a data quality control procedure for meteorological data collected at a PV plant. The quality-controlled data were used as inputs to SVM and XGBoost, resulting in improved forecasting accuracy, with MAPE decreasing from 7–10% to 6.32% and 6.08%, respectively. The results demonstrate that meteorological data quality control significantly enhances PV forecasting performance and can contribute to distributed energy resource operation and curtailment mitigation strategies.

This paper presents the design and experimental validation of an intelligent tire alignment and lifting control system for an under-vehicle autonomous parking robot. The proposed system enables the robot to autonomously enter beneath a vehicle, recognize tire positions using a LiDAR-based sensing module, and perform precise lifting through a fork-type mechanism. A YOLOv8 instance segmentation algorithm is employed to detect tire regions from LiDAR point cloud data and estimate their geometric centers. The detected tire positions are then matched with a vehicle database to determine the correct alignment for lifting. Experiments were conducted on three different vehicle types under various surface conditions. The results show that the proposed system achieved a tire recognition accuracy exceeding 95%, a lifting success rate of 100%, and an average lifting operation time of 12.3 seconds. These results demonstrate the reliability and practicality of the proposed method for real-world autonomous parking applications.

In this paper, we describe the control of safely grasping various objects using a three-finger gripper. An experimental device was constructed for the characteristic experiment of a three-finger gripper, a control system for closed-loop control was constructed, and experiments were conducted to obtain proportional gain and differential gain experimentally. As a result of the experiment, the proportional gain of the three-finger gripper was Kp=0.25, and the differential gain was Kd=5.0. As a result of the special experiment, the rising time was within 0.31 seconds, the steady-state error was within ±0.02 N, and the overshoot was within 0.03 N. By applying this to control the gripping force, it was possible to safely grip various objects. Therefore, we believe that applying the control method of this study to a three-finger gripper will enable it to grasp various objects safely.

Electric arc furnace (EAF) steelmaking is increasingly adopting sustainable carbon sources to improve slag foaming and reduce energy consumption. Among them, spent tire-derived carbon represents a viable alternative to coal, offering high volatile and carbon contents. However, its elevated sulfur level and modified slag chemistry can markedly affect foaming stability and desulfurization. This study elucidates the interactive effects of spent tire substitution (0-30 wt%) and slag basicity (CaO/SiO2 = 1.5-2.4) on foaming dynamics, bubble evolution, and sulfur behavior at 1,600 °C. Real-time imaging and quantitative analyses demonstrated that moderate substitution (10-20 wt%) enhanced initial foaming due to volatile-induced gas release, whereas excessive addition (30 wt%) caused unstable coalescence and premature collapse from sulfur-driven surface tension reduction. Lower basicity limited early foaming but improved long-term stability via increased viscosity, while higher basicity promoted rapid collapse and reduced sulfur retention. The optimal condition (CaO/SiO2 = 2.0) maintained stable foaming for over 40 min, achieving superior sulfur capture (about 24 %) and minimal refractory attack. Overall, these findings reveal the mechanistic coupling between carbon source, basicity, and interfacial properties, offering practical guidance for sustainable slag design and efficient sulfur control in EAF operations employing waste-derived carbonaceous materials.

Metcalfa pruinosa is an invasive planthopper that has rapidly spread across South Korea since its first detection in 2005. Long-term suppression is difficult using chemical control alone. This study developed a cocoon-based outdoor release technique for the parasitoid Neodryinus typhlocybae, a major natural enemy of M. pruinosa, and analyzed the seasonal occurrence patterns of both species while evaluating the establishment and parasitism of N. typhlocybae across multiple regions. A rain-shielded release device was designed to facilitate adult emergence and escape, resulting in emergence from more than 75% of the cocoons and the successful escape of 88.9% of the emerged adults. The optimal timing for parasitoid release was identified as mid-to-late June when 4th-instar M. pruinosa nymphs are predominant, while parasitism assessments were best conducted in mid-to-late July during the 5th-instar stage. Between 2024 and 2025, N. typhlocybae cocoons were detected in eight municipalities across five provinces. Notably, cocoon densities reached 8.2 cocoons per 20 leaves in Jangseong in 2024 and 3.2 cocoons in Asan in 2025, clearly demonstrating successful parasitism and overwintering under Korean field conditions. Cocoons also persisted at sites where releases were conducted between 2020 and 2022, without additional releases. No significant relationships were observed between cocoon density and release amount, region, or year, suggesting that host density, microclimate, and other field-level environmental factors have greater influences on parasitism outcomes. This study provides key foundational data supporting the practical implementation of N. typhlocybae for the biological control of M. pruinosa in South Korea.

As renewable energy penetration continues to increase, the output variability and forecasting uncertainty of photovoltaic generation have emerged as major operational risks in power systems. This study establishes a sensor-based data quality control procedure to ensure the reliability of meteorological data collected at a PV plant. For temperature, humidity, and wind speed, a four stage QC process physical range check, persistence check, step change check, and median filtering was applied. Solar radiation, which exhibits strong temporal and distributional characteristics, was processed using a three-stage QC procedure consisting of physical range, step change, and frequency distribution checks. Using the quality-controlled meteorological data, PV generation forecasting was performed with SVM and XGBoost models. As a result, the MAPE values improved to 6.32% for SVM and 6.08% for XGBoost after QC application. The findings confirm that meteorological data quality control significantly enhances PV forecasting accuracy and can support future strategies for distributed energy resource management, curtailment mitigation, and power system risk reduction.

Oil-in-water (O/W) emulsified foods are highly susceptible to lipid oxidation, a reaction predominantly initiated at the oil-water interface where multiple reactive pathways operate simultaneously. In such complex multiphase systems, the efficacy of natural antioxidants is severely limited by their chemical instability and their inability to effectively reach this critical interfacial region. These constraints necessitate the development of structural delivery systems to improve the spatial distribution and persistence of natural antioxidants in emulsified food matrices. Liposomes offer an adaptable nanocarrier platform that enhances interfacial accessibility, protects encapsulated antioxidants from environmental stressors (such as oxygen and metal ions), and modulates their retention and release kinetics. However, the practical application of liposomes in food matrices remains challenging due to the intrinsic structural properties of food-grade phospholipids, the complex interfacial behavior of lipid bilayers, and significant restrictions imposed by current preparation methods. These factors collectively govern the physicochemical attributes essential for liposome performance in complex food environments. This review synthesizes structural and mechanistic perspectives on oxidation in O/W emulsions. It evaluates how liposomal design parameters— including phospholipid composition, cholesterol incorporation, surface modification, and solvent-dependent manufacturing strategies—influence efficient antioxidant delivery. By integrating these critical considerations, this review aims to establish key design principles for advancing food-grade liposomal systems, thereby supporting their potential as an approach to enhance oxidative stability and reduce reliance on synthetic antioxidants.

운전 시뮬레이션을 이용하여 3-수준 자율주행 상황을 구현한 후 청년 및 고령운전자가 주간/야간 운전 조건과 비 운전과제(nonm-driving task: NDT) 수행 여부에 따라 보이는 제어권 인수시간(takeover time: TOT), 차량제어 (vehicle control :VC) 및 주관적 작업부하(subjective workload: SW) 수준에서의 차이를 비교하였다. 실험참가자들에 게는 자율주행 중 NDT를 수행하도록 하였고 NDT 수행 도중 제어권 인수가 요청되면 제어권을 빠르고 정확하게 인수받아 수동운전으로 전방의 장애물을 회피하도록 하였다. 본 연구 결과를 요약하면 다음과 같다. 첫째, 야간 운전 조건과 NDT 수행 조건에서 실험참가자들의 TOT는 증가하였고, 차량에 대한 종적 및 횡적수행 모두 저하되었으며, SW 수준은 더 높았다. 둘째, 청년운전자 집단에 비해 고령운전자들의 VC 수행이 상대적으로 더 저조하였다. 셋째, 고령운전자들은 야간 운전과 NDT 수행 요구가 결합되면 모든 종속측정치에서 청년운전자들에 비해 상대적으로 더 저하된 수행을 보였다. 이러한 결과는 야간 자율주행에서 고령운전자의 주의가 분산될 경우 자율주행 차량과의 상호 작용 및 긴급한 상황에서의 장애물 회피에서 어려움이 증가할 수 있다는 것을 시사한다.

본 연구는 국내의 해조류 양식에서 심각한 피해를 유발하는 주요 병원체인 난균류 김 붉은갯병(Pythium chondricola)을 방제하기 위한 친환경적 대안을 탐색하였다. 병원체 억제에 대한 효능과 안전성을 평가하기 위해 과산화수소, 과초산, 항균펩타이드를 포함한 여러 후보 물질들을 실험하였다. 그 중 과산화수소(H₂O₂)에서 가장 효과적인 결과를 보여주었다. 특히 4,000ppm 농도의 과산화수소를 10~20초간 처리했을 때 병원체의 성장을 효과적으로 억제하였으며, 김 엽체 조직에 손상도 유발하지 않았다. 반면 과초산은 노출 시간이 길어질수록 김 조직에 괴사를 유발했으며, 항균 펩타이드는 유의미한 항균 효과를 보이지 않았다. 특히 과산화수소는 pH 6.2~6.4 수준의 중성 범위를 유지했다는 것이다. 이는 현재 사용되고 있는 인체 건강과 환경 안전에 잠재적인 위험성을 가진 강산성 무기산과는 구별이 된다. 더 나아가, 인위감염 후에도 과산화수소 처리는 붉은갯병의 확산을 현저히 감소시켰다. 이러한 결과는 실제 양식장 환경에서도 과산화수소가 안전하고, 효과적이며, 친환경적인 질병 방제 대안으로 적용될 수 있음을 시사한다.

Purpose: This study interprets how infection control nurses (ICNs) experienced and understood administrative support during infection-prevention activities, and to clarify how this support influenced their practice, well-being, and professional identity in post-pandemic clinical settings. Methods: This qualitative study used interpretative phenomenological analysis. Through purposive and snowball sampling, six ICNs from tertiary and general hospitals in Korea, each with at least 3 years of ICN experience and direct involvement in the COVID-19 response, participated in two semi-structured, in-depth interviews between August 20 and September 3, 2025. Interviews were audio-recorded, transcribed verbatim, and analyzed first idiographically, then across cases, following Smith’s procedures. Reflexive notes and an audit trail ensured analytic rigor. Results: Analysis identified six interrelated themes, expressed in participants’ terms and specific work contexts. First, the realities and challenges of infection-prevention practice reflected ongoing workload pressure, delayed outcome visibility, and crisis-driven surges that caused moral strain. Second, meanings and experiences of managerial support indicated that support was genuine when leaders listened, made prompt decisions, and backed ICN judgments; its absence led to isolation and role fatigue. Third, the operation of resources and institutional arrangements showed that staffing, budgets, equipment, and clear decision pathways either enabled or limited timely, consistent action. Fourth, organizational culture and interprofessional barriers revealed that hierarchical norms, siloed routines, and skepticism hindered cooperation, while open, learning-oriented environments supported the adoption of precautions. Fifth, emotional turbulence and professional identity highlighted tensions between enforcement and caregiving roles, which undermined self-efficacy; recognition and small practice successes restored pride in the specialized role. Finally, conditions for recovery and change emphasized that practical support and formal acknowledgment-along with after-action reviews, protocol updates, cross-disciplinary drills, and aligned incentives-helped transform individual learning into resilient, sustainable organizational capability. Conclusion: For ICNs, administrative support extends beyond resources by providing authority, psychological safety, and feasibility for infection-prevention efforts. To maintain prevention measures beyond crises, hospitals should ensure governance structures, rapid decision-making channels, stable staffing and budgets, and regular debriefings with protocol updates. Connecting infection-control performance to recognition and professional development may reduce burnout, strengthen professional identity, and enhance patient safety.