Search Results (826)

Surface congestion and taxiing delays at high-density airports increasingly constrain aviation sustainability, as ground-phase fuel consumption and emissions constitute a significant share of total airport emissions. Existing studies typically decouple air traffic flow management from ground resource scheduling, hindering coordinated optimization of punctuality, environmental benefits, and resource utilization. This paper proposes a multi-objective optimization method for runway-taxiway systems oriented toward air–ground collaborative decision-making, integrating Calculated Take-Off Time (CTOT) compliance constraints. A tri-objective mixed-integer programming model is formulated to minimize CTOT deviation, total taxiing time, and runway workload imbalance. A hybrid intelligent algorithm, SSA-SCA-NSGA-II, is designed with a bidirectional elite feedback mechanism to address this NP-hard problem. Validation uses real operational data of 58 departure flights during a peak period at Beijing Daxing International Airport. The results demonstrate that the proposed method achieves effective trade-offs on the Pareto front: CTOT compliance rate increased from 77.6% to 89.7–96.6%; total taxiing time decreased from 692 min to 551–635 min; and dual-runway utilization imbalance declined from 5.2% to 1.7–3.8%. These improvements translate into quantifiable sustainability gains: fuel consumption is reduced by 1425–3525 kg and CO₂ emissions by 4503–11,139 kg per peak hour, alongside a 19-percentage point improvement in punctuality that lowers passenger delay costs and reduces controller coordination workload. By simultaneously advancing environmental sustainability (carbon footprint reduction), economic sustainability (fuel and operational cost savings), and social sustainability (service punctuality and labor efficiency), the framework provides a measurable, monitorable, and policy-relevant decision-support tool for green airport surface operations aligned with sustainable development goals (SDGs). Full article

Background/Objectives: The relationship between body composition (BC), sarcopenia, and multiple sclerosis (MS) remains poorly understood. A high body mass index (BMI) is associated with a higher risk of MS and brain atrophy. However, limited data are available on BC in patients in the early stages of the disease. This study investigates differences in BC and sarcopenia between early-diagnosed patients with MS (pwMS) and healthy controls (HC), while exploring correlations with brain atrophy and biomarkers of oxidative stress and axonal injury. Methods: This project is part of BPS-ARMS, a cross-sectional study conducted in 2019–2022 at Verona University involving 51 participants aged 18–40 years, diagnosed with MS in the last two years, and currently not taking disease-modifying drugs. Seventeen (69% females) pwMS consented to be enrolled in this sub-study, matched by age and body mass index (BMI) to 17 HC; BC was assessed using Dual-Energy X-ray Absorptiometry (DXA). Collected variables included BMI, fat and lean mass, and sarcopenia index (SI). A brain MRI scan was performed in pwMS between 6 months before and 1 month after inclusion, to assess T2 lesion, normalized brain (NBV), white matter (WMV) and gray matter (GMV) volumes, and presence of gadolinium-enhancing (Gd+) lesions. Biomarker analysis was performed on blood samples collected at baseline. Oxidative stress was assessed as plasma gluthatione (GSH) and gluthatione disulphide (GSSG) levels and STAT1 phosphorylation at Tyr 701 (pSTAT) in peripheral blood cells, while axonal damage was measured as serum neurofilament light chain (NfL) levels. Results: A significantly lower SI was found in pwMS compared to HC (p = 0.038), particularly in female cases. In the pwMS group, WMV was inversely correlated with SI (p = 0.028) and lean body mass (p = 0.016). BMI was inversely correlated with WMV (r = −0.658, p = 0.02). A significant inverse correlation of plasma GSSG level was found with SI (r = −0.546, p = 0.023) and lean mass (r = −0.585, p = 0.014); the ratio of GSH over GSSG (GSH/GSSG) was directly correlated with SI (r = 0.518, p = 0.036) and lean mass (r = 0.568, p = 0.017). Conclusions: Patients with early-stage untreated MS and low-grade disability are more prone to sarcopenia than HC. Moreover, MS subjects with higher BMI show lower brain white matter volume and a lower global brain volume. Full article

Background: HS is a chronic inflammatory skin disease in which inflammatory nodules and abscesses coexist with tunnels, fibrosis, and scarring. This dual biology explains why medical therapy often improves inflammatory dissease activity without fully addressing fixed tissue damage, whereas surgery can achieve durable local control but does not treat diffuse inflammatory burden. Contemporary international guidelines increasingly endorse multimodal and medicosurgical care. Objective: To critically compare the evidence supporting medical and surgical management of HS, with emphasis on outcomes, indications, limitations, and clinical decision-making relevant to contemporary practice. Methods: A structured review was undertaken using PubMed/MEDLINE, the Cochrane Library, and major dermatology guideline sources, with searches updated to 7 May 2026. Priority was given to clinical guidelines, systematic reviews and meta-analyses, randomized controlled trials, and higher-quality observational studies. Evidence was synthesized narratively because endpoints, populations, and follow-up intervals differed markedly across medical and surgical studies. Results: Medical evidence is strongest for biologic therapy in moderate-to-severe inflammatory HS. Weekly adalimumab improved week-12 HiSCR in the phase 3 PIONEER trials; secukinumab improved week-16 and week-52 outcomes in SUNSHINE/SUNRISE; and bimekizumab improved week-16 HiSCR50 in BE HEARD I/II. Surgical evidence is strongest for wide excision in structurally advanced disease, particularly when compared with local excision or incision and drainage. Meta-analytic data consistently show lower recurrence after wide excision than after local excision, and lower recurrence after flap or graft reconstruction than after primary closure. Combined therapy is increasingly supported: peri-operative adalimumab improved outcomes in SHARPS, and surgery plus adalimumab outperformed adalimumab alone in a pragmatic 12-month RCT. Conclusions: HS is best managed by matching treatment to disease phenotype. Medical therapy is essential for inflammatory control; surgery is essential for persistent tunnels, fibrosis, and scarred regional disease. The strongest overall clinical position is an integrated, multidisciplinary model in which systemic therapy reduces inflammatory load and surgery definitively treats irreversible tissue damage. Full article

Upper-limb rehabilitation and elderly exercise programs require lightweight, reliable, and physiotherapy-oriented assistive technologies capable of supporting controlled joint motion while enabling objective performance assessment. This paper presents experimental validation of ASSIST-FEEv3, a cable-driven elbow assisting device that is designed for flexion–extension exercises with emphasis on usability, portability, and physiotherapy integration. The device employs a dual-cable antagonistic mechanism that is actuated by servomotors housed in a compact module, allowing guided motion in the arm sagittal plane with minimal wearable load mass. A testing campaign was conducted with 25 healthy volunteers under the supervision of physiotherapy experts following a properly designed protocol for three sessions of ten repetitions each. Joint kinematics was acquired through integrated sensing, and performance metrics including maximum flexion, maximum extension, and range of motion (ROM) were analyzed to assess repeatability, motion smoothness, and user-specific variability. The results demonstrate consistent motion assistance across repeated cycles, variability between sessions, and comparable ROM distributions between sexes. Observed deviations were considered due to individual temporary conditions rather than device-related limitations. The device operated with low energy consumption as required in home-based applications. Test findings validate both the mechanical reliability and the physiotherapy-oriented operational framework of the ASSIST-FEEv3 device. Full article

Background/Objectives: Gamma-aminobutyric acid (GABA) is increasingly recognized as an important modulator of pancreatic beta-cell function, but the mechanisms by which it regulates intracellular Ca²⁺ oscillations and coordinated beta-cell activity remain insufficiently understood. The aim of this study was to investigate how GABA influences the amplitude, frequency, phase adjustment, entrainment, and synchronization of beta-cell Ca²⁺ oscillations. Methods: We developed a reduced ATP–Ca²⁺ oscillation model, based on established beta-cell oscillatory frameworks, and coupled it to the GABA-shunt subsystem derived from our previously established Dual Anaplerotic Model. The model incorporates explicit dynamics of cytosolic Ca²⁺, endoplasmic reticulum Ca²⁺, ATP, and a regulatory variable controlling Ca²⁺ influx, while the interstitial GABA signal is represented as a delayed feedback signal acting on cellular excitability. Single-cell and two-cell simulations were performed to analyze GABA-dependent oscillatory regulation and intercellular coupling. Results: The model reproduced key experimental observations under both control and GABA-deficient conditions, including reduced Ca²⁺-oscillation amplitude and a prolonged oscillation period when GABA production was suppressed. Mechanistically, GABA affected single-cell oscillations through two complementary pathways: metabolically, by modulating ATP production through PEP-related and TCA-related contributions linked to the GABA shunt, and as an interstitial/paracrine signal, by adjusting the phase of Ca²⁺ influx through fast and delayed inhibitory feedback. In the reduced two-cell model, delayed interstitial GABA signaling could phase-lock non-identical oscillators over finite ranges of parameter mismatch. When included as an additional weak effective term, electrical coupling broadened these ranges, consistent with a complementary interaction between GABA-mediated phase adjustment and established electrical coupling. Conclusions: GABA acts as a dual regulator of beta-cell dynamics, linking intracellular metabolism to Ca²⁺-oscillation patterning and promoting coordinated activity through intercellular phase adjustment. The model provides a mechanistic framework connecting GABA metabolism, ATP dynamics, Ca²⁺ signaling, and beta-cell synchronization in pancreatic islets. Full article

In maritime navigation, vessel dynamics and open-water environments often exhibit inherent symmetries, whereas control objectives, particularly collision avoidance and COLREGs compliance, are strictly asymmetric, specifying unique responsibilities (e.g., give-way versus stand-on) and distinct desired trajectories. This paper proposes a runtime-assured, dual-envelope predictive safety-control framework for autonomous surface vehicles (ASVs) that directly addresses the symmetry and asymmetry in complex encounters. To manage asymmetric semantic objectives, a large language model (LLM) serves as a semantic-governance module, generating structured COLREGs labels (encounter type, vessel responsibility, and maneuver tendency). These semantic outputs are strictly validated before entering the control stack. In parallel, to break the dangerous symmetry of collision risks, vessel-motion prediction and uncertainty inflation construct a physical safety envelope. A deterministic MPC-CBF safety filter then computes admissible control commands, balancing the symmetric homogeneous tracking dynamics with asymmetric collision-avoidance constraints. A runtime assurance monitor supervises semantic validity and solver latency, preventing unsafe decisions. Simulation results demonstrate that the proposed intelligent decision-making and control scheme significantly improves rule-aware collision avoidance while reducing excessive conservatism, providing a profound perspective for viewing maritime safety through symmetric and asymmetric control theory. Full article

Ultra-shallow and confined water environments are challenging to survey with conventional towed side-scan sonar (SSS) due to limited access and positioning uncertainties. This study introduces a portable, battery-powered acoustic survey system that integrates a pole-mounted dual-frequency side-scan sonar (600/1600 kHz) with RTK GNSS (Real-Time Kinematic Global Navigation Satellite System), deployable from a small inflatable boat. The system was validated in two settings: an inland lake and a marina. Field trials demonstrated reliable acquisition of high-resolution sonar imagery and effective detection of both natural and anthropogenic seabed features, including small and low-reflectivity objects. The high-frequency channel (1600 kHz) produced superior image quality and interpretability compared to the lower frequency. While there are limitations associated with fixed sonar mounting and limited altitude control, the system offers high mobility, rapid deployment, and operational safety. This approach represents a practical, cost-effective solution for high-resolution acoustic remote sensing in ultra-shallow water settings where traditional survey methods are ineffective or impractical. Full article

To address the prevalent issues of slow convergence, low exploration efficiency, and large value estimation bias in traditional Deep Q-Networks for intelligent vehicle path planning, this paper proposes an improved Dueling Double Deep Q-Network (D3QN) path-planning method guided by the Dynamic Window Approach (DWA) heuristic. The Dueling Double DQN architecture decouples state value and action advantage representations, while the dual estimator of Double DQN mitigates Q-value overestimation. A Prioritized Experience Replay (PER) mechanism samples transitions non-uniformly based on Temporal Difference error with importance sampling correction, improving the reuse of critical samples and training stability. DWA evaluation criteria are transformed into dense heuristic reward signals, enabling the agent to receive continuous multi-dimensional guidance during exploration without executing online trajectory optimization. The environment augments the sparse navigation objective with a Chebyshev goal-progress term motivated by potential-based reward shaping theory together with auxiliary DWA-style channels. The policy-invariance property of potential-based shaping is referenced only for the goal term added to the sparse task reward rather than for the full composite training return. A continuous Ackermann steering kinematic model with a pure-pursuit path-tracking controller is adopted for deployment to ensure executable trajectories under non-holonomic constraints. The proposed method (DWA-D3QN) is systematically evaluated against sparse-reward D3QN, PBRS-guided D3QN, DQN, DDQN, Dueling DQN, APF-DQN, PPO, SAC, TD3, A*, and classical DWA in a grid map environment with static and dynamic obstacles. Results are reported with statistical significance over multiple random seeds. Under complex difficulty, DWA-D3QN achieves a success rate of 94.1 ± 3.4% with a collision rate of 5.9 ± 3.4% over 15 seeds, representing improvements of 64.1 and 8.4 percentage points over the sparse-reward and PBRS-guided D3QN baselines, respectively. Ablation experiments reveal the differentiated contributions of clearance, heading, and velocity shaping terms: clearance awareness provides the strongest single contribution, heading alignment reinforces directional guidance, and velocity regularization refines trajectory quality under the joint constraints of the former two. The full composite reward achieves the lowest variance among all evaluated DRL methods, confirming enhanced training stability. Comparisons with PPO, SAC, and TD3 confirm the statistically significant advantages of the proposed framework (PPO: $p=0.0010$, SAC: $p=0.0007$, TD3: $p=0.0024$). ROS/Gazebo validation with an Ackermann-steered vehicle achieves a success rate of 96.0% with a collision rate of 4.0% over 50 trials, further confirming the applicability of the learned policy in continuous-state environments with realistic vehicle kinematics. Full article

Multi-UAV cooperative persistent tracking in complex obstacle environments requires agents to approach dynamic targets while ensuring obstacle avoidance and flight safety; however, standard multi-agent reinforcement learning (MARL) methods typically rely on a single policy to implicitly handle both objectives, making it difficult to balance task performance and risk control. To address this issue, this paper proposes a Target-Aware Safety-Residual Pursuit Reinforcement Learning (TASRP) framework for constrained three-dimensional environments. A continuous-control 3D tracking environment is constructed in IsaacLab, where two multirotor UAVs cooperatively track a dynamic target under random, target-blocking, and gate-like obstacle layouts, boundary constraints, and inter-agent collision risks, with each UAV producing a four-dimensional action composed of normalized thrust and body-frame torques. TASRP adopts a dual-head residual policy in which a pursuit branch generates nominal actions, and a safety branch predicts corrective residuals, together with a risk-aware gating mechanism, a target-guided teacher for obstacle detouring, and a dual-critic safety-constrained optimization scheme. Under clean observations, TASRP achieves task success rates of 75–79%, obstacle crash rates of 13–15%, and boundary crash rates of 1–2% across three representative scenarios. Under noisy observations, TASRP achieves 72.1% task success, 20.3% obstacle crash, and 2.8% boundary crash, outperforming MAPPO (61.2%, 61.2%, 5.6%) and HAPPO (58.1%, 73.5%, 4.1%). These results indicate that explicitly decoupling target-oriented control and safety correction enables a more effective and robust performance–safety trade-off under both clean and moderately noisy observations. Full article

Background/Objectives: Furan derivatives are commonly encountered in food and environmental matrices and may exert biological effects, but their acute cardiovascular actions and potential mitochondrial targets remain insufficiently characterised. This study examined the effects of two simple furan compounds, 2-acetylfuran (2AF) and 5-methylfurfural (5MFF), on arterial blood pressure in vivo and on oxidative phosphorylation in isolated rat liver mitochondria. Methods: Arterial blood pressure was recorded invasively in anaesthetised rats after intraperitoneal administration of 2AF or 5MFF (0.3 µL/g). Systolic, diastolic, and mean arterial pressures, as well as heart rate, were monitored over time. Mitochondrial respiration was assessed in isolated rat liver mitochondria using high-resolution respirometry. Results: Both 2AF and 5MFF induced a rapid hypotensive response, with significant reductions in systolic, diastolic, and mean arterial pressures within 10–15 min after administration. MAP was reduced to a similar extent by both compounds. However, their chronotropic and pulse pressure responses differed: 5MFF increased heart rate and pulse pressure, whereas 2AF induced a delayed bradycardic response without a significant change in pulse pressure. In isolated liver mitochondria, both compounds markedly reduced ADP-stimulated respiration and decreased the respiratory control index, indicating reduced coupling efficiency. Both compounds also increased the cytochrome c effect, suggesting partial impairment of outer mitochondrial membrane integrity. Conclusions: 2AF and 5MFF exert acute hypotensive effects in anaesthetised rats and impair oxidative phosphorylation in isolated rat liver mitochondria. This study provides the first in vivo evidence that 2AF and 5MFF exert hypotensive effects and identifies them as bioactive furan compounds with dual haemodynamic and bioenergetic actions. Full article

A dual-platform mushroom cultivation system integrating artificial intelligence (AI)-assisted environmental monitoring and controlled-environment agriculture (CEA) was developed to support experiential STEM education across K–12 and undergraduate settings. Hands-on instruction with multicellular fungi is often limited by reliance on microbial models and by constraints associated with field-based activities. To address this gap, we implemented an indoor instructional platform that combines a commercial AI-assisted automated cultivation unit with a tent-based chamber for hands-on environmental control. Representative cultivated species included oyster mushrooms (Pleurotus spp.) and lion’s mane (Hericium erinaceus). The AI-assisted system provided sensor/camera-based monitoring, app-based feedback, and software-assisted regulation of humidity, light, and airflow, whereas the tent-based system enabled direct student manipulation of cultivation conditions. Together, the systems allowed students to observe fungal development, manage environmental parameters, and collect quantitative and qualitative data within a single academic term. Post-harvest activities, including mushroom-based food preparation and tasting, further connected fungal biology with food and sustainability. A matched pre- and post-course survey (n = 30) showed increases in students’ self-reported perceived understanding, cultivation confidence, and engagement, with mean scores increasing from approximately 2–4 to 6–8. Because the survey instrument was not formally validated and no control group was included, these results are interpreted as preliminary self-reported perceptions rather than objective evidence of learning gains. The platform provides a practical model for integrating fungal biology, AI-assisted environmental monitoring, and CEA into STEM education. Full article

Background: Appetite regulation is governed by a complex neuroendocrine network that integrates peripheral peptide signals with hypothalamic and brainstem circuits to coordinate energy intake and maintain energy homeostasis. Disruption of these pathways contributes to obesity and other disorders characterised by dysregulated feeding behaviour. Objective: To map and synthesise the current evidence on the role of appetite-regulating peptide hormones and central neural pathways in appetite control, obesity pathophysiology, and emerging therapeutic approaches. Methods: A scoping review of the literature was conducted to identify and synthesise evidence relating to the physiological and pathological mechanisms of appetite regulation. The review examined the actions of key peptide hormones, including ghrelin, glucagon-like peptide-1 (GLP-1), peptide YY (PYY), leptin, and insulin, their interactions within the gut–brain axis, and their effects on central appetite-regulating circuits. Results The evidence highlights the central role of the arcuate nucleus in integrating peripheral hormonal signals with neural pathways controlling feeding behaviour. Appetite regulation is mediated by the balance between orexigenic neuropeptide Y/agouti-related peptide (NPY/AgRP) neurons and anorexigenic pro-opiomelanocortin/cocaine- and amphetamine-regulated transcript (POMC/CART) neurons, with further modulation by the paraventricular, lateral, and ventromedial hypothalamic nuclei. The literature identifies hormone resistance, impaired satiety signalling, and altered neuroendocrine feedback as major contributors to obesity. Evidence on therapeutic interventions demonstrates the potential of GLP-1 receptor agonists, including liraglutide and semaglutide, and the dual incretin agonist tirzepatide, while also highlighting challenges related to treatment durability, adverse effects, and weight regain following discontinuation. Conclusions: Current evidence demonstrates that appetite regulation involves highly interconnected peripheral and central signalling pathways. The reviewed literature supports the development of multi-target and precision-based therapeutic strategies for obesity and identifies important areas for future research, including mechanisms of treatment resistance, long-term efficacy, and inter-individual variability in neuroendocrine responses. Full article

Background/Objectives: Mass spectrometry-based newborn screening for small-molecule biomarkers typically employs a rapid first-tier screen that omits chromatographic separations before mass spectrometric analysis, followed, only for a subset of samples and disorders, by a longer, more specific second-tier assay that includes liquid chromatographic separation prior to mass spectrometry. The second-tier screen is used when the primary biomarker lacks sufficient specificity and may result in higher false-positive rates. The throughput and specificity of first-tier newborn screening assays have been relatively stagnant over the past two decades despite significant improvements in mass spectrometry instrumentation. With the continuous expansion of disorders added to the Recommended Uniform Screening Panel in the United States, newborn screening laboratories have a need for higher-throughput assays and improved specificity. Methods: We developed and evaluated two first-tier tandem mass spectrometry approaches using a modern dual-needle, dual-loop LC-MS/MS platform: (1) a 30-s flow injection analysis tandem mass spectrometry (FIA-MS/MS) assay and (2) a rapid first-tier liquid chromatography tandem mass spectrometry (LC-MS/MS) assay using a hydrophilic interaction chromatography (HILIC) guard column (1TH). Analytical performance was assessed using dried blood spot quality control and linearity materials, including evaluations of recovery, precision, linearity, and matrix effects. Results: The 30-s FIA-MS/MS assay quadrupled the throughput of current 2-min FIA-MS/MS assays used routinely in newborn screening laboratories. The throughput improvement was achievable due to increased scan speeds of the mass spectrometer as well as the dual needle/loop design of the autosampler. In addition, these instrumentation improvements made it possible to employ liquid chromatographic separations prior to MS/MS analysis without sacrificing the approximately 2-min sample-to-sample throughput of conventional FIA-MS/MS workflows. The 1TH LC-MS/MS method separated critical isobaric and isomeric biomarkers, reduced matrix effects, improved specificity and quantification accuracy, and demonstrated acceptable recovery, precision, and linearity for newborn screening applications. Conclusions: Recent advances in LC-MS/MS instrumentation can be leveraged to either substantially increase first-tier newborn screening throughput or improve analytical specificity while maintaining current workflow timelines. First-tier LC-MS/MS using a HILIC guard column provides improved specificity that can reduce the need for second-tier testing, thereby improving overall throughput and turnaround time of the newborn screening workflow. These approaches provide flexible solutions for newborn screening laboratories seeking to accommodate expanding screening panels without compromising analytical quality or efficiency. Full article

This study examines how two forms of financial literacy—objective financial literacy (OFL; demonstrated knowledge of interest rates, inflation, and diversification) and perceived financial literacy (PFL; self-assessed confidence in financial matters)—relate to financial wellbeing through distinct capability pathways, and whether self-regulation conditions these links. We use three nationally representative cross-sections from Portugal (2015, 2020, 2023; N = 3648), a European setting marked by declining objective literacy and constrained market participation. Guided by capability theory, we propose a dual-lane model in which OFL operates through behavioural capability (BC; enacted saving, investing, and planning behaviours) to shape objective financial wellbeing (OFW; resilience, assets, and saving), while PFL operates through perceived capability (PC; financial self-efficacy and perceived control) to shape subjective financial wellbeing (SFW; perceived security, satisfaction, and freedom from financial stress). We also test whether non-impulsive, future-oriented behaviour (NIB) strengthens the associations along the objective lane. Structural equation models provide partial support for the dual-lane model, revealing three asymmetries with implications for European policy: (1) the link between behavioural capability and objective financial wellbeing weakens in 2023, suggesting that macroeconomic conditions can undercut even prudent financial behaviour; (2) perceived financial literacy directly predicts subjective financial wellbeing, but perceived capability does not mediate this association, indicating that financial confidence shapes wellbeing independently of self-efficacy; and (3) non-impulsive, future-oriented behaviour amplifies the association between objective literacy and objective wellbeing in 2015 and 2023 but not in 2020, showing that the benefits of self-regulation are context-dependent. The findings inform financial education and policy across Europe by distinguishing intervention levers for objective versus subjective outcomes and identifying conditions under which behavioural interventions are most effective. Full article

Multi-terminal voltage-source-converter-based HVDC (VSC-MTDC) systems are increasingly used to integrate renewable energy and interconnect asynchronous AC grids, but conventional fixed-coefficient droop control cannot simultaneously limit DC-voltage deviations, reduce operating losses, and preserve converter power margins during operating-point switching. This paper hypothesizes that a rule-based fuzzy adjustment of the droop slope can provide smooth multi-objective coordination without inter-station communication. A dual Mamdani fuzzy controller is developed: one controller adjusts the weighting between loss-oriented and power-margin-oriented droop coefficients according to converter power margin, while the other introduces a voltage-deviation correction according to DC-bus voltage. The controller is implemented and verified in a five-terminal MMC-based VSC-MTDC model built in PSCAD/EMTDC, where simulation data are generated under heavy-load, light-load, and power-reference switching scenarios using specified line and converter parameters. Compared with conventional droop control, the proposed strategy improves power-margin utilization, reduces operating-point discontinuities, and raises the minimum DC voltage from 370.2 kV to 381.4 kV in the severe switching case. The results confirm that fuzzy-slope droop control can achieve smoother operating-point switching and better coordinated optimization among voltage stability, operating loss, and converter reserve margin. Full article