Search Results (46)

Background/Objectives: Spinal decompression surgery shows variable outcomes, with reoperation rates up to 37.5%. Surgeons lack objective intraoperative tools to assess decompression adequacy. Mechanomyography (MMG) measures nerve excitability through mechanical muscle responses to electrical stimulation. While compressed nerves require higher stimulation thresholds, optimal quantification approaches remain undefined. We explored associations between intraoperative MMG threshold changes and six-week pain outcomes, comparing metrics anchored to a 2.0 mA reference threshold versus percentage-based measures. Methods: Prospective exploratory pilot study of 42 patients (112 nerves) undergoing lumbar or cervical decompression. MMG thresholds were recorded pre- and post-decompression. Numeric Pain Scale scores were obtained preoperatively and at six weeks. Three metrics were compared: percentage change, Threshold Reduction Ratio (TRR; measuring proportion of threshold elevation above 2.0 mA eliminated by decompression), and Threshold Excess (TE; residual threshold remaining above 2.0 mA), with TRR and TE anchored to 2.0 mA based on published normal ranges. Results: Among 40 patients with baseline pain, threshold-anchored metrics showed substantially stronger correlations with pain improvement than percentage-based measures (TRR: r = 0.656, p < 0.001 vs. percentage: r = 0.397, p = 0.011). Threshold Excess was associated with a linear dose–response: each 1 mA above 2.0 mA corresponded to 6.3% less pain improvement (p = 0.001). Patients achieving ≤2.0 mA had 6.1-fold increased odds of complete pain relief versus those above 2.0 mA (76.5% vs. 34.8%, p = 0.013). Internal leave-one-out cross-validation suggested internal stability (TRR shrinkage ≈ 9.3%; TE’s dose–response slope remained stable). Conclusions: In this exploratory pilot study, threshold-anchored MMG metrics (TRR and TE) showed stronger correlations with early pain outcomes than percentage-based measures. These exploratory findings require external validation in independent cohorts before clinical implementation. If validated prospectively, these metrics could provide objective, real-time feedback for clinical interpretation to inform surgical decision-making during spinal decompression, enabling surgeons to tailor decompression to individual physiology rather than relying on standardized anatomical criteria. Future work should explore patient-specific threshold targets that account for age, chronicity, and comorbidities. Full article

One of the main challenges faced by DC microgrid (DCMG) is their low inertia, which leads to rapid and significant voltage fluctuations during load or generation changes. These fluctuations can negatively impact sensitive loads and protection devices. Previous studies have addressed this by enabling battery converters to mimic the behavior of synchronous generators (SGs), but this approach becomes ineffective when the converters or batteries reach their current or energy limits, leading to a loss of inertia and potential system instability. In interconnected multi-microgrid (MMG) systems, the presence of multiple batteries offers the potential to enhance system inertia, provided there is a coordinated control strategy. This research introduces a hierarchical control method that combines decentralized and centralized approaches. Decentralized control allows individual converters to emulate SG behavior, while the centralized control uses Internet of Things (IoT) technology to enable real-time coordination among all Energy Storage Units (ESUs). This coordination improves inertia across the DCMMG system, enhances energy management, and strengthens overall system stability. IoT integration ensures real-time data exchange, monitoring, and collaborative decision-making. The proposed scheme is validated through MATLAB simulations, with results confirming its effectiveness in improving inertial response and supporting the integration of renewable energy sources within DCMMGs. Full article

The maneuvering performance of ships in marginal ice zones is critical for navigational safety, yet most existing studies focus on icebreaking vessels. This study develops a coupled numerical framework that integrates the Non-Smooth Discrete Element Method (NDEM) for simulating ship–ice interactions with the three-degree-of-freedom MMG model for ship dynamics. The framework was applied to an S175 container ship, and numerical simulations were conducted for turning circle and Zig-Zag maneuvers under varying ice concentrations (0–60%), floe sizes, and rudder angles. NDEM efficiently handles complex, high-frequency multi-body collisions with larger time steps compared to conventional DEM or CFD–DEM approaches, enabling large-scale simulations of realistic ice conditions. Results indicate that increasing ice concentration from 0% to 60% reduces the turning diameter from 4.11L to 3.21L and decreases steady turning speed by approximately 53%. Larger floes form stable force chains that restrict lateral motion, while higher rudder angles improve responsiveness but may induce dynamic instability. These findings improve understanding of non-icebreaking ship maneuverability in ice and provide practical guidance for safe and efficient Arctic navigation. Full article

Mechanomyography (MMG) is a non-invasive technique for assessing muscle activity by measuring mechanical signals, offering high sensitivity and real-time monitoring capabilities, and it has many applications in rehabilitation training. Traditional MMG-based motion recognition relies on feature extraction and classifier training, which require segmenting continuous actions, leading to challenges in real-time performance and segmentation accuracy. Therefore, this paper proposes an innovative method for the real-time segmentation and classification of upper limb rehabilitation actions based on the You Only Look Once (YOLO) algorithm, integrating the Squeeze-and-Excitation (SE) attention mechanism to enhance the model’s performance. In this paper, the collected MMG signals were transformed into one-dimensional time-series images. After image processing, the training set and test set were divided for the training and testing of the YOLOv5s-SE model. The results demonstrated that the proposed model effectively segmented isolated and continuous MMG motions while simultaneously performing real-time motion category prediction and outputting results. In segmentation tasks, the base YOLOv5s model achieved 97.9% precision and 98.0% recall, while the improved YOLOv5s-SE model increased precision to 98.7% (+0.8%) and recall to 98.3% (+0.3%). Additionally, the model demonstrated exceptional accuracy in predicting motion categories, achieving an accuracy of 98.9%. This method realizes the automatic segmentation of time-domain motions, avoids the limitations of manual parameter adjustment in traditional methods, and simultaneously enhances the real-time performance of MMG motion recognition through image processing, providing an effective solution for motion analysis in wearable devices. Full article

In the domain of course control, traditional methods such as proportional–integral–derivative (PID) control often exhibit limitations when addressing complex nonlinear systems and uncertain disturbances. To mitigate these challenges, the adaptive neuro-fuzzy inference system (ANFIS) has been integrated into course control strategies. The primary objective of this study is to investigate the course control characteristics of vessels governed by the ANFIS controller under both normal and severe sea conditions. A three-degree-of-freedom (3-DOF) maneuvering model set (MMG) was employed and validated through sea turning tests. The design of the ANFIS controller involved a combination of the backpropagation algorithm with the least square method. Training data for the ANFIS control system were derived from a linear control framework, followed by simulation tests conducted under normal and severe sea conditions to assess control performance. The simulation results indicate that in normal sea conditions, ANFIS has more stable heading control (smaller A_ψ), but at the cost of more energy consumption (larger I_δ). Notably, response time is reduced by approximately 36.7% compared to that of the linear controller. Conversely, during severe sea conditions, ANFIS exhibits an increase in response time by about 33.3% relative to the linear controller while maintaining a smaller I_δ. In the whole course control stage, the stability is better than the linear controller, and it has better energy-saving characteristics. Under scenarios involving small and large course alterations, A_ψ values for ANFIS are approximately 11.28% and 13.97% higher than those observed with the best-performing linear controller (λ_ψ = 60), respectively. As the propeller speed increases, the A_ψ value of the ANFIS controller decreases significantly, to about 62.71%, indicating that the energy efficiency is improved and the course stability is also enhanced. In conclusion, it can be asserted that the implementation of an ANFIS controller yields commendable performance in terms of controlling vessel courses effectively. Full article

In a sustainable energy system, managing the charging demand of electric vehicles (EVs) becomes increasingly critical. Uncontrolled charging behaviors of large-scale EV fleets will exacerbate loads imbalanced in a multi-microgrid (MMG). At the same time, the time cost of users will increase significantly. To improve users’ charging experience and ensure stable operation of the MMG, we propose a new joint scheduling strategy that considers both time cost of users and spatial load balancing among MMGs. The time cost encompasses many factors, such as traveling time, queue waiting time, and charging time. Meanwhile, spatial load balancing seeks to mitigate the impact of large-scale EV charging on MMG loads, promoting a more equitable distribution of power resources across the MMG system. Compared to the Shortest Distance Matching Strategy (SDMS) and the Time Minimum Matching Strategy (TMMS) methods, our approach improves the average peak-to-valley ratio by 9.5% and 10.2%, respectively. Similarly, compared to the Load Balancing Matching Strategy (LBMS) and the Improved Load Balancing Matching Strategy (ILBMS) methods, our approach reduces the average time cost by 31.8% and 25% while maintaining satisfactory spatial load balancing. These results demonstrate that the proposed method achieves good results in handling electric vehicle scheduling problems. Full article

Objective: To assess the efficacy of contrast-enhanced mammography (CEM) in differentiating benign from malignant breast lesions in Asian patients with bloody nipple discharge (BND). Methods: This retrospective study included 58 women with BND (mean age: 51.7 years) who underwent standardized CEM at institutions in Taiwan and Singapore. Lesion characteristics (size, enhancement, conspicuity, shape, margins) were evaluated on CEM by blinded radiologists. Non-enhanced mammography (MMG) and ultrasound (US) within a defined timeframe were compared for diagnostic accuracy. Benign or malignant status was confirmed by biopsy or 2-year imaging follow-up. Results: Malignancy was found in 29 of 58 lesions (50.0%), with ductal carcinoma in situ (DCIS) being the most common. CEM demonstrated a 100% negative predictive value (NPV) for non-enhancing lesions. Significant predictors of malignancy on multivariate analysis include enhancing lesions of size ≥ 1.5 cm (p-value 0.025) and suspicious morphological features (irregular/spiculated margins, irregular shape, segmental/linear NME distribution) (p-value < 0.001). CEM outperformed MMG (sensitivity: 58.6%) and US (sensitivity: 79.3%), achieving a sensitivity of 100% and the highest diagnostic accuracy at 81.3%. Additionally, a CEM size cut-off of 1.5 cm yielded a sensitivity of 73.5% and a specificity of 84.3%. Conclusions: CEM effectively differentiates benign from malignant lesions in patients with BND, improving diagnostic accuracy and potentially reducing unnecessary interventions. Full article

As the share of renewable energy generation continues to increase, the new-type power system exhibits the characteristics of coordinated operation between the main grid, distribution networks, and microgrids. The microgrid is primarily concerned with achieving self-balancing between power sources, the network, loads, and storage. In decentralized multi-microgrid (MMG) access scenarios, the aggregation of distributed energy within a region enables the unified optimization of scheduling, which improves regional energy self-sufficiency while mitigating the impact and risks of distributed energy on grid operations. However, the cooperative operation of MMGs involves interactions among various stakeholders, and the absence of a reasonable operational mechanism can result in low energy utilization, uneven resource allocation, and other issues. Thus, designing an effective MMG operation strategy that balances the interests of all stakeholders has become a key area of focus in the industry. This paper examines the definition and structure of MMGs, analyzes their current operational challenges, compiles existing research methods and practical experiences, explores synergistic operational mechanisms and strategies for MMGs under different transaction models, and puts forward prospects for future research directions. Full article

At present, the International Maritime Organization (IMO) has issued interim guidelines for the direct stability assessment of surf-riding and broaching for the second-generation intact stability criteria. Accurately and efficiently predicting surf-riding and broaching remains a key problem to be solved for the direct stability assessment of surf-riding and broaching. Therefore, a six-degree-of-freedom(6DOF) coupled mathematical model is established in this paper. Firstly, the four-degree-of-freedom(4DOF) coupled equations of surge–sway–roll–yaw motions are built based on the traditional MMG maneuvering mathematical model by considering Froude–Krylov forces, diffraction forces and restoring forces, and the heave and pitch are approximately calculated by iteratively solving improved static equilibrium equations in real-time, effectively solving the divergence problem in direct time-domain seakeeping calculations of high-speed ships in stern-quartering waves. Secondly, the hydrodynamic lift forces due to the coexistence of wave particle velocity and ship forward velocity are taken into account in the propeller-thrust and rudder-force models. In addition, the real-time emersion of twin rudders in waves is considered in the rudder-force models. At the same time, the free-running model experiments with a ONR tumblehome vessel are carried out in stern-quartering waves, and the pure loss of stability and broaching motions are observed. Finally, comparative validations between the calculations and the experiments of surf-riding and broaching in stern-quartering waves are carried out, and the effects of the ship speed, the instantaneous wetted surface of the hull, rudder exposure, heave and pitch motions on predicting surf-riding and broaching motions are investigated. The computation results show that the established 6DOF mathematical model has enough accuracy to be used for the direct stability assessment of the surf-riding and broaching failure modes. Full article

The multi-modal two-step floating catchment area (MM-2SFCA) method is an extension of the two-step floating catchment area (2SFCA) method that incorporates the impact of different transportation modes, thereby facilitating more accurate calculations of the spatial accessibility of public facilities in urban areas. However, the MM-2SFCA method does not account for the impact of distance within the search radius on supply–demand capacities, and it assumes an idealized supply–demand relationship. This paper introduces the gravity model into the MM-2SFCA method, proposing a multi-modal gravity-based 2SFCA (MM-G2SFCA) method to better account for distance decay and supply–demand relationships. Furthermore, a standardized gravity model is proposed based on the traditional gravity model. This model imposes constraints on upper and lower limits for distance decay weights without compromising the fundamental curve characteristics of the gravity model, thereby avoiding extreme weight scenarios. The accessibility of public hospitals in Shenzhen is evaluated through the integration of basic geographic information data, resident travel data, and official statistical data. The findings demonstrate that the standardized gravity model effectively addresses the issue of excessively high local distance weights in the traditional gravity model, making it more suitable as a distance decay function. The MM-G2SFCA method improves the consideration of distance and supply–demand relationships, thereby facilitating a more rational distribution of accessibility on a global scale. This study discovers differences in the spatial allocation of public hospital resources across the Shenzhen’s districts. Accessibility within the metropolitan core is significantly higher than that outside the core. Additionally, there is a notable difference in the level of accessibility among the districts. Accessibility is found to be better in district centers and along the main traffic arteries. Full article

Green hydrogen is central to the energy transition, but its production often requires expensive materials and poses environmental risks due to the perfluorinated substances used in electrolysis. This study introduces a transformative approach to green hydrogen production via chemical looping, utilizing an iron-based oxygen carrier with yttrium-stabilized zirconium oxide (YSZ). A significant innovation is the replacement of Al₂O₃ with SiO₂ as an inert support pellet, enhancing process efficiency and reducing CO₂ contamination by minimizing carbon deposition by up to 700%. The major findings include achieving a remarkable hydrogen purity of 99.994% without the need for additional purification methods. The Fe-YSZ oxygen carrier possesses a significantly higher pore volume of 323 mm³/g and pore surface area of 18.3 m²/g, increasing the pore volume in the iron matrix by up to 50%, further improving efficiency. The catalytic system exhibits a unique self-cleaning effect, substantially reducing CO₂ contamination. Fe-YSZ-SiO₂ demonstrated CO₂ contamination levels below 100 ppm, which is particularly noteworthy. This research advances our understanding of chemical looping mechanisms and offers practical, sustainable solutions for green hydrogen production, highlighting the crucial synergy between support pellets and oxygen carriers. These findings underscore the potential of chemical looping hydrogen (CLH) technology for use in efficient and environmentally friendly hydrogen production, contributing to the transition to cleaner energy sources. Full article

The objective of this study is to perform a comparative analysis of the impact of incorporating alkaline earth metal carbonates (MCO₃, where M–Mg, Ca, Sr, Ba) into low-calcium fly ash (FA) on the geopolymerization processes and the resultant properties of composite geopolymers. Mechanical activation was employed to enhance the reactivity of the mixtures. The reactivity of the mechanically activated (FA + alkaline earth carbonate) blends towards NaOH solution was experimentally studied using XRD analysis and FTIR spectroscopy. In agreement with thermodynamic calculations, MgCO₃ demonstrated the most active interaction with the alkaline solution, whereas strontium and barium carbonates exhibited little to no chemical interaction, and calcite was situated in the transition region. As the calcite content in the mixture with FA increased, the compressive strength of the geopolymers continuously improved. The addition of Mg, Sr, and Ba carbonates to the FA did not enhance the strength of geopolymers. However, the strength of geopolymers based on these blends was comparable with that of geopolymers based on 100% FA. The strength of geopolymers synthesized from the 100% FA and from the (90% FA + 10% MCO₃) blends, mechanically activated for 180 s, at the age of 180 days was 11.0 MPa (0% carbonate), 11.1 MPa (10% MgCO₃), 36.5 MPa (10% CaCO₃), 13.6 MPa (10% SrCO₃), and 12.4 MPa (10% BaCO₃) MPa, respectively. The influence of carbonate additives on the properties of the composite geopolymers was examined, highlighting filler, dilution, and chemical effects. The latter determined the unique position of calcite among the carbonates of alkaline earth metals. Full article

Due to the reduction in fossil fuel abundance and the harmful environmental effects of burning them, the renewable resource potentials of microgrid (MG) structures have become highly highly. However, the uncertainty and variability of MGs leads to system frequency deviations in islanded or stand-alone mode. Usually, battery energy storage systems (BESSs) reduce this frequency deviation, despite limitations such as reducing efficiency in the long term and increasing expenses. A suitable solution is to use electric vehicles (EVs) besides BESSs in systems with different energy sources in the microgrid structure. In this field, due to the fast charging and discharging of EVs and the fluctuating character of renewable energy sources, controllers based on the traditional model cannot ensure the stability of MGs. For this purpose, in this research, an ultra-local model (ULM) controller with an extended state observer (ESO) for load frequency control (LFC) of a multi-microgrid (MMG) has been systematically developed. Specifically, a compensating controller based on the single-input interval type fuzzy logic controller (FLC) was used to remove the ESO error and improve the LFC performance. Since the performance of the ULM controller based on SIT2-FLC depends on specific parameters, all of these coefficients were adjusted by an improved harmony search algorithm (IHSA). Simulation and statistical analysis results show that the proposed controller performs well in reducing the frequency fluctuations and power of the system load line and offers a higher level of resistance than conventional controllers in different MG scenarios. Full article

Treatment of volumetric muscle loss (VML) faces challenges due to its unique pathobiology and lower priority in severe musculoskeletal injury management. Consequently, a need exists for multi-stage VML treatment strategies to accommodate delayed interventions owing to comorbidity management or prolonged casualty care in combat settings. To this end, polyvinyl alcohol (PVA) was used at concentrations of 5%, 7.5%, and 10% to generate provisional muscle void fillers (MVFs) of varying stiffness values (1.125 kPa, 3.700 kPa, and 7.699 kPa) to stabilize VML injuries as part of a two-stage approach. These were implanted into a rat model for a duration of 4 weeks, then explanted and either left untreated (control) or treated through minced muscle grafting (MMG). Additional benchmarks included acute MMG and unrepaired groups. At the MVF explant, the 7.5% PVA group exhibited superior neuromuscular function compared to the 5% and 10% PVA groups, the least fibrosis, and the largest median myofiber size among all groups at the 12-week endpoint. Despite the 7.5% PVA’s superiority amongst the two-stage treatment groups, neuromuscular function was neither improved nor impaired relative to acute treatment benchmarks. This suggests that the future success of a two-stage VML treatment strategy will necessitate a more effective definitive intervention. Full article

Semi-hydrogenation of acetylene to ethylene over metal oxide-supported Au nanoparticles is an interesting topic. Here, a hydrotalcite-based MMgAlO_x (M=Cu, Ni, and Co) composite oxide was exploited by introducing different Cu, Ni, and Co dopants with unique properties, and then used as support to obtain Au/MMgAlO_x catalysts via a modified deposition–precipitation method. XRD, BET, ICP-OES, TEM, Raman, XPS, and TPD were employed to investigate their physic-chemical properties and catalytic performances for the semi-hydrogenation of acetylene to ethylene. Generally, the catalytic activity of the Cu-modified Au/CuMgAlO_x catalyst was higher than that of the other modified catalysts. The TOR for Au/CuMgAlO_x was 0.0598 h⁻¹, which was 30 times higher than that of Au/MgAl₂O₄. The SEM and XRD results showed no significant difference in structure or morphology after introducing the dopants. These dopants had an unfavorable effect on the Au particle size, as confirmed by the TEM studies. Accordingly, the effects on catalytic performance of the M dopant of the obtained Au/MMgAlO_x catalyst were improved. Results of Raman, NH₃-TPD, and CO₂-TPD confirmed that the Au/CuMgAlO_x catalyst had more basic sites, which is beneficial for less coking on the catalyst surface after the reaction. XPS analysis showed that gold nanoparticles exhibited a partially oxidized state at the edges and surfaces of CuMgAlO_x. Besides an increased proportion of basic sites on Au/CuMgAlO_x catalysts, the charge transfer from nanogold to the Cu-doped matrix support probably played a positive role in the selective hydrogenation of acetylene. The stability and deactivation of Au/CuMgAlO_x catalysts were also discussed and a possible reaction mechanism was proposed. Full article