Search Results (39)

Considering the lightweight requirement of modular multilevel converter (MMC), the implementation of arm multiplexing significantly improves submodule utilization and achieves remarkable lightweight performance. However, the challenges of overvoltage and energy imbalance during pole-to-ground fault still exist. To address these issues, this paper proposes a hybrid half-wave alternating MMC (HHA-MMC) and presents its fault ride-through strategy. First, a transient equivalent model based on topology and operation principles is established to analyze fault characteristics. Depending on the arm’s alternative multiplexing feature, the half-wave shift non-blocking fault ride-through strategy is proposed to eliminate system overvoltage and fault current. Furthermore, to eliminate energy imbalance caused by asymmetric operation during non-blocking transients, dual-modulation energy balancing control based on the third-harmonic current and the phase-shifted angle is introduced. This strategy ensures capacitor voltage balance while maintaining 50% rated power transmission during the fault period. Finally, simulations and experiments demonstrate that the lightweight HHA-MMC successfully accomplishes non-blocking pole-to-ground fault ride-through with balanced arm energy distribution, effectively enhancing power supply reliability. Full article

Sustainability and resource optimization have spurred interest in giving a second life to used equipment, often discarded after limited use. Within this framework, we conducted a multidisciplinary, final-year engineering project to explore the reverse engineering and repurposing of commercial hoverboards for an auto-stabilizing, modular robotic platform, with emphasis on medical applications such as transporting medication. The innovation lies in recycling hoverboards to develop a teleoperated, stabilized base that can accommodate additional modules—for instance, a multifunctional arm or a transport shelf—akin to existing commercial robots. Our methodology involves disassembling and reprogramming the hoverboard’s motor controllers and sensors to maintain horizontal stability. Control is realized through the sensor fusion of accelerometer and gyroscope data, processed by a Kalman filter and implemented in a Proportional-Integral-Derivative (PID) loop. A user-friendly Human-Machine Interface (HMI), hosted on an ESP32 microcontroller, enables remote operation and monitoring. Experimental results show that the platform autonomously balances, carries payloads, and achieves high energy efficiency, highlighting its potential as a sustainable and versatile solution in modular robotic applications. Full article

This research describes a multi-objective trajectory planning method for robotic arms based on time, energy, and impact. The quintic Non-Uniform Rational B-Spline (NURBS) curve was employed to interpolate the trajectory in joint space. The quintic NURBS interpolation curve can make the trajectory become constrained within the kinematic limits of velocity, acceleration, and jerk while also satisfying the continuity of jerk. Then, based on the Parrot Optimization (PO) algorithm, through improvements to reduce algorithmic randomness and the introduction of appropriate multi-objective strategies, the algorithm was extended to the Multi-Objective Parrot Optimization (MOPO) algorithm, which better balances global search and local convergence, thereby more effectively solving multi-objective optimization problems and reducing the impact on optimization results. Subsequently, by integrating interpolation curves, the multi-objective optimization of joint trajectories could be performed under robotic kinematic constraints based on time–energy-jerk criteria. The obtained Pareto optimal front can provide decision-makers in industrial robotic arm applications with flexible options among non-dominated solutions. Full article

The globally robust control of a four-link manipulator arm (FLMA) is an important subject for a wide range of industrial applications such as COVID-19 prevention robotics, lower limb rehabilitation robotics and underwater robotics. This article uses the feedback linearized approach to stabilize the complex nonlinear FLMA without applying a nonlinear approximator that includes the fuzzy approach and neural network optimal approach. This article proposes a new approach based on the “first” derived nonlinear convergence rate formula of the FLMA to control highly nonlinear dynamics. The linear quadratic regulator (LQR) method is often applied in the balance controlling space of the underactuated manipulator. This proposed approach takes the place of the LQR approach without the necessary trial and error operations. The implications of the proposed approach are “globally” effective, whereas the Jacobian linearized approach is “locally” valid. In addition, the main innovation of the proposed approach is to perform “simultaneously” additional performances including almost disturbance decoupling performance, which takes the place of the traditional posture–energy approach and avoids some torque chattering behaviour in the swing-up space, and globally exponential stable performance, without the need to solve the Hamilton–Jacobin equation. Simulations of comparative examples show that the proposed controller is superior to the singular perturbation and fuzzy approaches. Full article

In modular multilevel converter battery energy storage systems (MMC-BESS), state-of-charge (SOC) balancing is essential for ensuring safe and reliable operation. Existing methods based on linear controllers or conventional model-predictive control (MPC) often suffer from slow balancing speed, difficult parameter tuning, and high computational burden. To address these challenges, this paper proposes a fast SOC balancing strategy based on nonlinear MPC. A nonlinear state-space model is first developed and then linearized to enable discrete single-step prediction of arm- and phase-level SOC values. A two-stage control scheme is introduced to coordinate inter-arm and inter-phase SOC balancing, significantly reducing the number of state variables involved in the MPC formulation. The proposed method eliminates the need for circulating current reference calculation and control parameter tuning. Simulation results demonstrate that the proposed method takes approximately 17.5 s and 39 s for inter-arm and inter-phase SOC balancing, respectively, while traditional three-level SOC balancing takes approximately 42 s and 88 s. Full article

Background/Objectives: Inflammatory bowel disease (IBD), encompassing ulcerative colitis and Crohn’s disease, is characterized by chronic gut inflammation driven by microbial dysbiosis and immune dysfunction. Current therapies primarily involve anti-inflammatory and immunomodulatory strategies; however, many patients experience an inadequate response or a gradual loss of efficacy over time. This study evaluates the clinical efficacy of personalized microbiome modulation (PMM)—an AI-driven intervention designed to restore microbial balance and improve key treatment outcomes such as symptom control and remission rates. Methods: This was a single-arm, open-label validation trial involving 27 patients with moderate-to-severe IBD who had experienced prior treatment failure. Participants underwent three months of PMM, which included personalized dietary modifications, targeted probiotic supplementation, and antimicrobial interventions based on gut microbiome sequencing. Primary outcomes included stool frequency and consistency as well as inflammatory markers (C-reactive protein and fecal calprotectin), while secondary outcomes assessed nutritional status, metabolic function, and quality of life. Statistical analyses included paired t-tests and repeated measures ANOVA to determine significant changes over time. Results: PMM led to significant clinical improvements, including a 58% reduction in stool frequency (p < 0.001) and improved stool consistency. CRP and fecal calprotectin levels decreased markedly (p < 0.001), suggesting reduced systemic inflammation. Additionally, iron, vitamin B12, and vitamin D deficiencies improved (p < 0.001), alongside weight gain and increased energy levels. Notably, patients on anti-TNF biologics showed enhanced response rates, suggesting potential synergistic effects between microbiome modulation and biologic therapy. Conclusions: This study highlights PMM as a promising adjunctive therapy for IBD, demonstrating benefits across clinical, inflammatory, and metabolic parameters. While findings support the role of microbiome-targeted interventions in disease management, larger randomized controlled trials are required to confirm the long-term efficacy and applicability in broader patient populations. Full article

The growing need for effective and sustainable solutions in humanitarian construction has prompted scholars and practitioners to explore technical approaches that address the challenges of natural disasters, health emergencies, armed conflicts and migratory flows. These solutions often encompass temporary shelters, durable shelters and multifunctional buildings designed to balance rapid deployment, cultural sensitivity and environmental sustainability. However, the assessment of sustainability in humanitarian construction remains insufficiently defined due to the complexities of crises, the variability of local materials and the impact of local climatic conditions. This study aims to bridge this gap by integrating Building Information Modeling (BIM) and simulation tools such as COMSOL Multiphysics 6.0 to study sustainable strategies for humanitarian housing. Using case studies aligned with IFRC, UNHCR and CRL (Red Cross of Luxembourg) family shelter standards, the research assessed a Climate and Local Skill-Centered Design (CLCD) by examining the performance of key design elements, including wall material emissivity and reflectance, natural lighting, and energy efficiency within the context of indoor thermal comfort. Simulation results revealed that wall finishing material reflectance significantly influences average daylight factors (D), with variations of 2% to 5% linked to lower reflectance values and changes in the window-to-floor ratio (WFR). Conversely, thermal comfort metrics indicated minimal variations in heat discomfort hours, maintaining indoor temperatures between 19 °C and 25 °C, consistent with ASHRAE Standard 55 thermal comfort criteria. This paper underscores the importance of integrating advanced IT tools and green local techniques and materials to optimize humanitarian housing for health, comfort and environmental performance, offering actionable insights for future humanitarian sustainable designs. Full article

Sparse modular multilevel converters (SMMCs) are a new type of lightweight high-voltage large-power AC/AC converter that significantly reduces the number of components compared to modular multilevel matrix converters (M3Cs). This study proposes a fault ride through a control strategy for SMMC to address the issues of arm energy imbalances and valve-side overvoltage, which occur during asymmetric faults on the low-frequency side. First, we establish models of the energy deviation of the arms under asymmetric short-circuit faults on the low-frequency side of SMMC. We also study the influence mechanism of the control strategies on the arm energy imbalance during faults. On this basis, an arm energy balancing strategy based on zero-sequence voltage injections combined with AC voltage control is proposed; this can achieve arm energy balance and suppress the negative sequence current and overvoltage of the SMMC. Finally, we construct a simulation model of an offshore wind power low-frequency transmission system based on the SMMC. The simulation results show that the proposed energy balance strategy can realize the stable operation of the low-frequency transmission system (LFTS) under asymmetric faults on the low-frequency side, that the maximum capacitor voltage deviation during the fault does not exceed 10% and that capacitor voltage returns to normal 0.25 s after the fault occurs. Full article

Blockchain has several unique features: data integrity, security, privacy, and immutability. For this reason, it is considered one of the most promising new technologies for a wide range of applications. Initially prominent in cryptocurrencies such as Bitcoin, its applications have expanded into areas such as the Internet of Things. However, integrating blockchain into IoT systems is challenging due to the limited computing and storage capabilities of IoT devices. Efficient blockchain mining requires lightweight hash functions that balance computational complexity with resource constraints. In this study, we employed a structured methodology to evaluate hash functions for blockchain–IoT systems. Initially, a survey is conducted to identify the most commonly used hash functions in such environments. Also, this study identifies and evaluates a lightweight hash function, designated as HashLEA, for integration within blockchain-based IoT systems. Subsequently, these functions are implemented and evaluated using software coded in C and Node.js, thereby ensuring compatibility and practical applicability. Performance metrics, including software efficiency, hardware implementation, energy consumption, and security assessments, were conducted and analyzed. Ultimately, the most suitable hash functions, including HashLEA for blockchain–IoT applications, are discussed, striking a balance between computational efficiency and robust cryptographic properties. Also, the HashLEA hash function is implemented on a Raspberry Pi 4 with an ARM processor to assess its performance in a real-world blockchain–IoT environment. HashLEA successfully passes security tests, achieving a near-ideal avalanche effect, uniform hash distribution, and low standard deviation. It has been shown to demonstrate superior execution time performance, processing 100 KB messages in 0.157 ms and 10 MB messages in 15.48 ms, which represents a significant improvement in execution time over other alternatives such as Scrypt, X11, and Skein. Full article

This paper presents a robust control strategy for trajectory-tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimises trajectory-tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy is aimed at counteracting the effects of disturbances caused by the slip phenomena through the wheel–terrain contact and bidirectional interactions propagated by mechanical coupling between the SSMM base and arm. These interactions are modelled using a coupled nonlinear dynamic framework that integrates bounded uncertainties for the mobile base and arm joints. The model is developed based on principles of full-body energy balance and link torques. Then, a centralized control architecture integrates a nominal NMPC (disturbance-free) and ancillary controller based on Active Disturbance-Rejection Control (ADRC) to strengthen control robustness, operating the full system dynamics as a single robotic body. While the NMPC strategy is responsible for the trajectory-tracking control task, the ADRC leverages an Extended State Observer (ESO) to quantify the impact of external disturbances. Then, the ADRC is devoted to compensating for external disturbances and uncertainties stemming from the model mismatch between the nominal representation and the actual system response. Simulation and field experiments conducted on an assembled Pioneer 3P-AT base and Katana 6M180 robotic arm under terrain constraints demonstrate the effectiveness of the proposed method. Compared to non-robust controllers, the R-NMPC approach significantly reduced trajectory-tracking errors by 79.5% for mobile bases and 42.3% for robot arms. These results highlight the potential to enhance robust performance and resource efficiency in complex navigation conditions. Full article

Background/Objectives: Despite advances in maternal nutritional knowledge, the effect of maternal diet, micronutrient status and undernutrition, and the effect of maternal supplementation on fetal, neonatal and infant outcomes still have gaps in the literature. This overview of reviews is intended to assess the available information on these issues and identify the main maternal nutritional factors associated with offspring outcomes in low- and middle-income countries as possible targets for public health interventions. Methods: The literature search was performed in Medline (PubMed) and Cochrane Library datasets in June 2024. Pre-specified outcomes in offspring were pooled using standard meta-analytical methods. Results: We found consistent evidence on the impact of maternal undernutrition indicated by low body mass index (BMI), mid-upper arm circumference (MUAC), and stature, but not of individual micronutrient status, on intrauterine-growth retardation, preterm birth, low birth weight, and small for gestational age, with research showing a possible effect of maternal undernutrition in later child nutritional status. Studies on micronutrient supplementation showed possible beneficial effects of iron, vitamin D, and multiple micronutrients on birthweight and/or decreasing small for gestational age, as well as a possible effect of calcium on preterm birth reduction. Interventions showing more consistent beneficial outcomes were balanced protein-energy and lipid base supplements, which demonstrated improved weight in newborns from supplemented mothers and a decreased risk of adverse neonatal outcomes. Conclusions: Further research is needed to identify the benefits and risks of maternal individual micronutrient supplementation on neonatal and further child outcomes. Full article

In resource-intensive Internet of Things applications, Lightweight Stream Ciphers (LWSCs) play a vital role in influencing both the security and performance of the system. Numerous LWSCs have been proposed, each offering certain properties and trade-offs that carefully balance security and performance requirements. This paper presents a comprehensive evaluation of prominent LWSCs, with a focus on their performance and resource consumption, providing insights into efficiency, efficacy, and suitability in the real-world application of resource-intensive live video feed encryption on an ARM processor. The study involves the development of a benchmarking tool designed to evaluate key metrics, including encryption frame rate, throughput, processing cycles, memory footprint, ROM utilization, and energy consumption. In addition, we apply the E−Rank metric, which combines key performance and resource metrics to derive a unified comparative measure for overall software performance. Full article

The background of this work is related to the scheduling of household appliances, taking into account variations in energy costs during the day from official Brazilian domestic tariffs: constant and white. The white tariff can reach an average price of around 17% lower than the constant, but charges twice its value at peak hours. In addition to cost reduction, we propose a methodology to reduce user discomfort due to time-shifting of controllable devices, presenting a balanced solution through the analytical analysis of a new method referred to as tariff space, derived from white tariff posts. To achieve this goal, we explore the geometric properties of the movement of devices through the tariff space (geometric locus of the load), over which we can define a limited region in which the cost of a load under the white tariff will be equal to or less than the constant tariff. As a trial for the efficiency of this new methodology, we collected some benchmarks (such as execution time and memory usage) against a classic multi-objective algorithm (hierarchical) available in the language portfolio in which the project has been executed (the Julia language). As a result, while both methodologies yield similar results, the approach presented in this article demonstrates a significant reduction in processing time and memory usage, which could lead to the future implementation of the solution in a simple, low-cost embedded system like an ARM cortex M. Full article

Intermittent energy-restricted diets have shown improved metabolic health and alterations in postprandial glucose and lipid responses. Given these diets’ inherent low carbohydrate content due to fasting and carbohydrates’ crucial role in postprandial metabolism, it is essential to determine if the observed benefits are primarily due to decreased carbohydrate consumption. This study aims to evaluate the acute metabolic effects of carbohydrate restriction on postprandial substrate metabolism, both in the presence and absence of energy restriction, compared to an iso-caloric balanced diet. Twelve (six male) healthy adults (27.33 ± 1.82; 26.64 ± 1.64 kg/m²) participated in this acute, three-arm crossover study. Participants consumed three pre-prepared intervention diets for one day (36 h), each separated by a 5-day washout period: a normal-carbohydrate (55% of energy) energy-balanced diet (nEB), a low-carbohydrate (50 g/day) energy-balanced (100% energy) diet (LCEB), and a low-carbohydrate (50 g/day) energy-restricted (25% energy) diet (LC25). Following each 36 h diet phase, blood metabolites were measured in the morning fasted state and serially across 360 min postprandially. Concurrently, substrate utilization (RQ) and energy expenditure were evaluated using indirect calorimetry. Data were analysed using repeated-measures ANOVA and Wilcoxon signed-ranks, with results displayed as mean ± SEM. Resting energy expenditure and postprandial thermogenesis showed no significant difference across the three study arms (p > 0.05) although RQ was markedly decreased in both LC arms (p < 0.001). Elevated hepatic 3-β-hydroxybutyrate production was observed in both low-carb groups compared to control (p < 0.01). Following 36 h of both low-carbohydrate diet improved postprandial TAG levels (p < 0.001). However, glucose tolerance was impaired in both low-carb diets (p = 0.04), while insulin responses showed no statistical difference between all diets (p > 0.05). Fasted and postprandial NEFA levels increased in both low-carb diets (p = 0.02, p < 0.01, respectively). Similarly, fasting GLP-1 levels rose in low-carb arms (p < 0.5), declining postprandially (p < 0.05). No significant difference was found between them in all analysed parameters (p < 0.05). This data suggest that limiting carbohydrates without concurrent energy restriction can mimic the short-term metabolic effects of fasting. Further research is needed to evaluate the long-term impacts of intermittent low-carb diets and their viability as alternatives to traditional energy-restricted plans, factoring in tolerance, sustainability, and lasting physiological effects. Full article

Modular multilevel converters (MMCs) with integrated battery energy storage systems (BESSs) are becoming crucial for modern power grids. This paper investigates the modeling and control of a grid-connected MMC-BESS, with a specific emphasis on state-of-charge (SoC) balancing. Compared to conventional hard arm SoC balancing control (HASBC), this paper proposes an alternative soft arm SoC balancing control (SASBC). The simulation results and analysis indicate the following: 1. SASBC provides superior performance in achieving SoC balance both between and within the arms, as compared to HASBC. 2. The MMC-BESS power fluctuates between phases, arms, and individual submodules to balance the SoC of batteries. After the accomplishment of SoC equalization, the power is equally distributed, and the circulating current is well eliminated. 3. MMC-BESS can operate in both the charging and discharging modes, and the total harmonic distortion (THD) of the output current is reduced from 6.80% to 1.13% after SoC balancing is achieved. 4. A robustness test shows the control system’s effective performance in handling component variations. Full article