Balancing Capability Research Articles

The Effectiveness of Therapeutic Exercise Interventions With Virtual Reality on Balance and Walking Among Persons With Chronic Stroke: Systematic Review, Meta-Analysis, and Meta-Regression of Randomized Controlled Trials.

Well-targeted balance, walking, and weight-shift training can improve balance capabilities in the chronic phase of stroke. There is an urgent need for a long-term approach to rehabilitation that extends beyond the acute and subacute phases, supporting participation without increasing the demand for health care staff. This study aims to evaluate the effectiveness of therapeutic exercise interventions with virtual reality (VR) training on balance and walking at the activity and participation levels in individuals with chronic stroke, compared with control groups receiving no treatment, conventional physical therapy, specific training, similar treatment, or identical treatment without VR. Studies were searched across 6 databases. The inclusion criteria were as follows: Adults aged 18 years or older with a stroke diagnosis for at least 6 months (population). Therapeutic exercises within a VR environment, using VR glasses or interactive games (intervention). Control groups without the use of VR (including no treatment, conventional physical therapy, specific training, similar treatment without VR, or identical treatment without the additional use of VR; comparison). We evaluated the Berg Balance Scale score, Functional Reach Test performance, Activities-specific Balance Confidence Scale score, Six-minute Walk Test, Two-minute Walk Test, 10-meter Walk Test results, and cadence (outcome measures). We investigated randomized controlled trials (study design). A meta-analysis and a meta-regression analysis were conducted to evaluate whether the content of VR interventions or control groups, as well as the level of VR immersion used, was related to balance or walking outcomes. A total of 43 randomized controlled trials involving 1136 participants were included in this review. The use of VR training in therapeutic exercise interventions had a large effect on balance (standardized mean difference 0.51, 95% CI 0.29-0.72; P<.001) and a moderate effect on walking (standardized mean difference 0.31, 95% CI 0.09-0.53; P=.006) in individuals with chronic stroke, compared with pooled control groups (no treatment, conventional physical therapy, specific training, similar treatment, or identical treatment without the use of VR). According to the meta-regression findings, the content of VR interventions (P=.52), the type of control groups (P=.79), and the level of VR immersion (P=.82) were not significantly related to the pooled balance or walking outcomes. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) was moderate for balance and low for walking. Therapeutic exercise training with VR had a positive, albeit moderate, effect on balance and a low impact on walking at the level of activity (capacity), even in the chronic phase of stroke, without serious side effects. The results are applicable to working-aged stroke rehabilitees who are able to walk without assistance. Further research is needed with defined VR methods and outcomes that assess performance at the level of real-life participation.

GSADDQN: Combining GraphSAGE and reinforcement learning for routing optimization in software-defined optical transport network

As a result of rapid development of network communication technology, optical transport network (OTN) traffic has also experienced rapid growth in terms of information volume scale, traffic complexity, and spatiotemporal distribution dynamics. Because the OTN traffic demand has complex spatiotemporal fluctuations, the traditional deep reinforcement learning (DRL) algorithm has been applied to the routing optimization of software-defined OTNs. However, the traditional DRL algorithm has problems such as slow convergence, weak generalization ability, and load imbalance when performing routine tasks. To address these issues, we propose a graph sampling and aggregation (GraphSAGE)-based dueling deep Q-network (GSADDQN) algorithm for software-defined OTN routing optimization. First, we design a DRL-based routing decision model to find the best routing strategy for each optical network’s source–destination traffic demand. Second, considering the sparse connection characteristics of optical network nodes, we use sampling neighbors and a deep aggregation mechanism as the neural network model of the Dueling Deep Q-Network (Dueling DQN) algorithm so that the reinforcement learning agent can consciously aggregate important network information and improve the model’s convergence performance and generalization ability. Finally, we design simulation routing experiments based on Gym and evaluate the algorithm’s load balancing and generalization capabilities for different network topologies. The experimental results show that the GSADDQN algorithm has good convergence performance and load balancing ability in routing optimization of optical transmission networks and can generalize new network structures, maintaining good decision-making ability even during network node failures.

Biomechanical analysis of balance control in the elderly By Ba Duan Jin

This study aims to evaluate the biomechanical effects of Ba Duan Jin on balance control in the elderly, seeking effective fitness methods to enhance their balance capabilities and reduce the risk of falls. Methods: Participants were randomly assigned to an experimental group (EG) and a control group (CG), with 25 individuals in each. The Berg Balance Scale (BBS) and mechanical measurements were utilized to evaluate the participants’ balance abilities and biomechanical performance. Statistical analyses were performed to compare the outcomes between the EG and CG, ensuring a comprehensive assessment of the differences. Results: The experimental group demonstrated a significant improvement in the Berg Balance Scale (BBS) scores (p &lt; 0.01), with a notable increase in the eyes-closed standing task (BBS6), which reached significance (p &lt; 0.05), indicating a consistent advantage for the experimental group in this area. Biomechanical measurements revealed that the experimental group exhibited significantly higher parameters compared to the control group, including stability index (EG: 0.7 ± 0.1/2.2 ± 0.4, CG: 0.6 ± 0.1/1.9 ± 0.3), power (EG: 3.2 ± 0.5/3.8 ± 0.6, CG: 2.9 ± 0.4/3.5 ± 0.5), energy expenditure (EG: 20.1 ± 3.8/25.0 ± 4.3, CG: 16.5 ± 3.2/20.3 ± 3.8), and step frequency (EG: 95.0 ± 5.5/105.0 ± 6.0, CG: 85.0 ± 5.0/100.0 ± 5.5). Additionally, peak force (EG: 345.2 ± 30.1/412.6 ± 35.8, CG: 310.4 ± 28.5/310.4 ± 28.5), impact force (EG: 68.3 ± 7.2/85.7 ± 8.9, CG: 55.8 ± 6.7/72.4 ± 8.1), average force (EG: 280.5 ± 25.6/320.7 ± 30.2, CG: 245.3 ± 22.8/280.1 ± 26.4), and direction of force (EG: 10.0 ± 2.0/15.0 ± 2.5, CG: 8.5 ± 1.5/12.0 ± 2.0) also exhibited significant differences (p &lt; 0.05). Notably, the static single-leg stance (EG: 3.38 ± 0.39, CG: 2.38 ± 0.50), dynamic sit-to-stand (EG: 3.77 ± 0.34, CG: 2.85 ± 0.37), turning movements (EG: 3.88 ± 0.27, CG: 2.58 ± 0.56), and double-leg step-ups (EG: 4.00 ± 0.02, CG: 2.69 ± 0.49) displayed extremely significant differences (p &lt; 0.01). These results indicate that Ba Duan Jin training effectively enhances balance control and reduces the risk of falls among the elderly. Conclusion: As a traditional form of physical exercise, Ba Duan Jin effectively enhances balance control and reduces the risk of falls among older adults, providing valuable practical evidence for health management in this population. Future research should focus on conducting more long-term studies with larger sample sizes to verify the applicability and long-term effects of Ba Duan Jin across various age groups and health conditions in older individuals.

Dynamic power allocation for the new energy hybrid hydrogen production system based on WOA-VMD: Improving fluctuation balance and optimizing control strategy

The new energy hydrogen production system is subject to intermittent fluctuations, which compromise efficiency and equipment lifespan. This study proposes a new dynamic power allocation and control strategy for hybrid hydrogen production systems. By using the Whale Algorithm Optimized Variable Modal Decomposition (WOA-VMD), the fluctuating power of new energy is quantitatively decomposed and reconstructed. Based on a multi-objective optimization function, low-frequency variation components and high-frequency fluctuation components are accurately allocated between alkaline electrolyzers (ALK) and proton exchange membrane electrolyzers (PEM). The strategy effectively improves the source-load balancing capability, reducing the low-frequency fluctuation rate by 60% and reducing the high-frequency power amplitude by 70%, significantly reducing the operational demands on ALK electrolyzers, the capacity requirements of PEM electrolyzers, and the need for energy storage configuration, while also increasing hydrogen production efficiency by 7%. Compared to existing methods, the strategy has a transparent analysis process, strong interpretability, and good data reusability, making it valuable for engineering applications.

The Impact of Modern Technologies on the Balance of Basketball Players with Ages between 13-14

This preliminary research investigates the effectiveness of Fitlight technology in enhancing the balance and reactive balance skills of male basketball players aged 13-14. Employing a comprehensive research design, the study involved 19 athletes from the "LPS Târgu-Mures" team over an eight-week period. The effectiveness of a specific training programme was evaluated through a series of Y balance tests and Reactive Y balance tests. The results demonstrated significant improvements in the athletes' balance capabilities, as evidenced by increased mean distances and Cohens effect sizes in the Y balance tests and enhanced reaction times in the Reactive Y balance tests.

Age-Related Influence on Static and Dynamic Balance Abilities: An Inertial Measurement Unit-Based Evaluation.

Balance control, a complex sensorimotor skill, declines with age. Assessing balance is crucial for identifying fall risk and implementing interventions in the older population. This study aimed to measure age-dependent changes in static and dynamic balance using inertial measurement units in a clinical setting. This study included 82 healthy participants aged 20-85 years. For the dynamic balance test, participants stood on a horizontally swaying balance board. For the static balance test, they stood on one leg. Inertial measurement units attached to their bodies recorded kinematic data, with average absolute angular velocities assessing balance capabilities. In the dynamic test, the younger participants had smaller average absolute angular velocities in most body parts than those of the middle-aged and older groups, with no significant differences between the middle-aged and older groups. Conversely, in the single-leg stance tests, the young and middle-aged groups outperformed the older group, with no significant differences between the young and middle-aged groups. Thus, dynamic and static balance decline at different stages with age. These results highlight the complementary role of inertial measurement unit-based evaluation in understanding the effect of age on postural control mechanisms, offering valuable insights for tailoring rehabilitation protocols in clinical settings.

Sensor-Based Multifaceted Feature Extraction and Ensemble Elastic Net Approach for Assessing Fall Risk in Community-Dwelling Older Adults.

Accurate identification of community-dwelling older adults at high fall risk can facilitate timely intervention and significantly reduce fall incidents. Analyzing gait and balance capabilities via feature extraction and modeling through sensor-based motion data has emerged as a viable approach for fall risk assessment. However, the existing approaches for extracting key features related to fall risk lack inclusiveness, with limited consideration of the non-linear characteristics of sensor signals, such as signal complexity, self-similarity, and local stability. In this study, we developed a multifaceted feature extraction scheme employing diverse feature types, including demographic, descriptive statistical, non-linear, spatiotemporal and spectral features, derived from three-axis accelerometers and gyroscope data. This study is the first attempt to investigate non-linear features related to fall risk in multi-task scenarios from a dynamic system perspective. Based on the extracted multifaceted features, we propose an ensemble elastic net (E-E-N) approach for handling imbalanced data and offering high model interpretability. The E-E-N utilizes bootstrap sampling to construct base classifiers and employs a weighting mechanism to aggregate the base classifiers. We conducted a set of validation experiments using real-world data for comprehensive comparative analysis. The results demonstrate that the E-E-N approach exhibits superior predictive performance on fall risk classification. Our proposed approach offers a cost-effective tool for accurately assessing fall risk and alleviating the burden of continuous health monitoring in the long term.

Double-pancake superconducting coil integrated with DFIG-based wind power systems under voltage-dip events: Design and performance analysis study

The doubly fed induction generator (DFIG)-based wind turbine provides massive development in power generation. Uncertain power oscillations and voltage-dip events affect the stability of the DFIG. To mitigate the effect of voltage-dips in short period, superconducting magnetic energy storage (SMES), which possess rapid energy exchange and high power density, is integrated with large-scale renewable power systems. SMES is integrated at the DC link of the DFIG to ensure the power balance and fault ride-through (FRT) capability. During this operation, frequent current changes occur in the high-temperature superconducting (HTS) coil, which leads to an increase in AC losses. As a remedy, an additional power converter structure controlled with a model-predictive controller (MPC) is proposed. Firstly, a scale-down HTS double-pancake coil model is designed using a finite element model by which transport current loss and magnetic field formulation are studied. Additionally, the critical coil current is also verified through experimental studies. The effectiveness of the proposed MPC-based SMES integrated DFIG on DC link voltage and grid current under IEC-61000-4-11 standard, symmetrical and asymmetrical voltage-dip cases are investigated. The obtained results demonstrate that the proposed system effectively reduces transients in DC link voltage and improves the FRT capabilities of the grid.

FACTS: Present and Future

Flexible AC Transmission Systems (FACTS) are pivotal in modernizing power systems, enhancing their stability, controllability, and efficiency. Currently, FACTS devices such as Static VAR Compensators (SVCs), Static Synchronous Compensators (STATCOMs), and Unified Power Flow Controllers (UPFCs) are employed to manage power flow, mitigate system instabilities, and improve voltage regulation across transmission networks. These technologies address present challenges, including the integration of renewable energy sources, reduction of transmission losses, and enhancement of system reliability in the face of fluctuating power demands. However, the growing complexity of power grids, driven by the increasing penetration of intermittent renewable energy, electric vehicles, and distributed generation, necessitates advanced and scalable solutions. The future of FACTS lies in the development of more sophisticated, adaptive, and intelligent devices that leverage real-time data analytics, artificial intelligence, and machine learning to optimize power flow dynamically. Future advancements are expected to focus on enhancing the interoperability of FACTS with smart grid technologies, improving the resilience of power systems against cyber-physical threats, and facilitating the transition towards more decentralized and sustainable energy systems. Moreover, the integration of energy storage with FACTS devices could revolutionize their functionality, offering not only reactive power compensation but also energy balancing capabilities. This paper explores the current applications of FACTS and envisions their future role in addressing the evolving challenges of global power systems, emphasizing the importance of innovation and strategic investment in the ongoing transformation of electrical networks.

Three-month functional training programme improves knee joint function in athletes post-ACL reconstruction surgery.

Rehabilitation and recovery duration following anterior cruciate ligament reconstructive surgery play a pivotal role in restoring optimal knee functionality in athletes. This study aimed to explore the impact of a 3-month functional training programme aligned with enhanced recovery after surgery on recuperation subsequent to anterior cruciate ligament reconstructive surgery. A quasi-experimental study. A cohort of 34 patients aged 14 to 24, who underwent anterior cruciate ligament reconstructive surgery and adhered to enhanced recovery after surgery protocols during the perioperative period, were allocated to an experimental group and a control group according to their eligibility, capacity, and willingness to engage in the functional training programme. The participants in the experimental group underwent a 3-month regimen of functional training following anterior cruciate ligament reconstructive surgery, whereas the control group followed a conventional recovery approach. Evaluations were conducted both prior to and following the 3-month recovery interval, utilizing the Y-Balance Test, Functional Movement Screening, and Isokinetic Knee Test. Assessment outcomes of the Y-Balance Test, Isokinetic Knee Test, and Functional Movement Screening exhibited significant enhancement (p < 0.05) within the experimental group, as opposed to the control group. These findings underscore that those athletes who undertook the 3-month functional training regimen within the experimental group exhibited heightened dynamic balance capabilities, increased knee joint mobility, and enhanced stability compared with their counterparts in the control group. Consequently, this underscores the efficacy of the 3-month functional training protocol aligned with enhanced recovery after surgery, as a means to effectively facilitate recuperation subsequent to anterior cruciate ligament reconstructive surgery.

On the Reliability of Wireless Sensor Networks with Multiple Sinks.

The convergence of heterogeneous wireless sensor networks provides many benefits, including increased coverage, flexible load balancing capabilities, more efficient use of network resources, and the provision of additional data by different types of sensors, thus leading to improved customer service based on more complete information. However, despite these advances, the challenge of ensuring reliability and survivability remains due to low-cost sensor requirements and the inherent unreliability of the wireless environment. Integrating different sensor networks and unifying protocols naturally leads to the creation of a network with multiple sinks, necessitating the exploration of new approaches to rational reliability assurance. The failure of some sensors does not necessarily lead to a shutdown of the network, since other sensors can duplicate information and deliver data to sinks via an increased number of alternative routes. In this paper, the reliability indicator is defined as the probability that sinks can collect data from a given number of sensors. In this context, a dedicated reliability metric is introduced and examined for its effectiveness. This metric is computed using an algorithm rooted in the modified factoring method. Furthermore, we introduce a heuristic algorithm designed for optimal sink placement in wireless sensor networks to achieve the highest level of network reliability.

Investigating the relationship between sagittal spinal curvature and fall incidence and fall risk among elderly nursing home residents.

Poor balance is an underlying cause of falling in the elderly, for which a change in the natural curvature of the spine plays a major role. Little is known about the relationship between spinal curvatures and fall incidence in this population. We primarily aimed to investigate the relationship between sagittal plane spinal curvatures and fall incidence over 1year among nursing facility residents. Secondarily, we aim to determine associations of sagittal plane spinal curvatures with participants' perception of fall risk and balance capability. Participants (100 residents mean age 70.17 ± 6.01years) underwent standing measures of sagittal plane spinal curvatures (flexible ruler technique) and forward displacement of the head relative to the cervical spine. The Tinetti Performance Oriented Mobility Assessment (POMA) and Fall Efficacy Scale assessed participants' perception of balance and fear of falling. Incident falls were self-reported monthly and tracked across 1year. Spearman's correlations and logistic regression evaluated associations between fall incidence and spinal curvature. Predictive performance of spinal curvature and fall risk was determined by the corresponding ROC for defining a cut-off for variables of spinal curvature and fall risk indicators. Predictive performance of spinal curvature and fall risk factors indicated 84% and 77% of participants were correctly classified using models of kyphosis and head angle, respectively. Our study adds new data on spinal curvatures and incident falls among nursing facility residents. Efforts are needed to intervene to counter progression of spinal curvatures and improve fall prevention practices.

Deep reinforcement learning-based resource scheduling for energy optimization and load balancing in SDN-driven edge computing

Traditional techniques for edge computing resource scheduling may result in large amounts of wasted server resources and energy consumption; thus, exploring new approaches to achieve higher resource and energy efficiency is a new challenge. Deep reinforcement learning (DRL) offers a promising solution by balancing resource utilization, latency, and energy optimization. However, current methods often focus solely on energy optimization for offloading and computing tasks, neglecting the impact of server numbers and resource operation status on energy efficiency and load balancing. On the other hand, prioritizing latency optimization may result in resource imbalance and increased energy waste. To address these challenges, we propose a novel energy optimization method coupled with a load balancing strategy. Our approach aims to minimize overall energy consumption and achieve server load balancing under latency constraints. This is achieved by controlling the number of active servers and individual server load states through a two stage DRL-based energy and resource optimization algorithm. Experimental results demonstrate that our scheme can save an average of 19.84% energy compared to mainstream reinforcement learning methods and 49.60% and 45.33% compared to Round Robin (RR) and random scheduling, respectively. Additionally, our method is optimized for reward value, load balancing, runtime, and anti-interference capability.

Simulations of design and high load operation of a model Francis turbine using bridged approach to turbulence modelling

Abstract Off-design operation of hydraulic turbines is contemporarily frequented for balance of variable energy intermittence in the electric grid. Being operationally highly flexible, these turbines allow a quick transition to off-design operation from the design point. However, such operational flexibility, and therefore the grid balancing capability is impeded by generation of flow instabilities like vortex breakdown during off-design operation. Vortex breakdown causes losses in efficiency and pressure recovery, pressure fluctuations and possibly mechanical vibrations in event of resonance between system natural and flow field fluctuation frequencies. While substantial experimental and numerical effort has already been made to study draft tube vortex breakdown, an accurate numerical flow characterization of the phenomenon is still a challenge. To this end, operation of a high head model Francis turbine under design and high load regimes using a bridged turbulence modelling approach is simulated. The approach allows a seamless transition between direct numerical simulation and Reynolds averaged Navier-Stokes equations. The highest attainable accuracy is limited by the mesh size. As such a satisfactory compromise between desired accuracy and invested computational effort is attained. The flow in the draft tube is free of anomalies under design specified operation. However, at high load an axial flow stagnation occurs centrally, and the flow is separated about the stagnated zone. The core of the vortex is enlarged with flow recirculation within it. Shear layers between the central stagnant zone and surrounding outflow kink and roll up transforming it into a spiral structure. In this work, a basic yet accurate numerical flow characterization of the aforementioned flow situations is achieved.

Clinical efficacy of vestibular assessment and rehabilitation training in peripheral vestibular vertigo.

To evaluate the clinical efficacy of vestibular assessment and rehabilitation training in patients with peripheral vestibular vertigo. This was a retrospective study. A total of 169 patients diagnosed with peripheral vestibular vertigo, admitted to Cangzhou People's Hospital between January 2020 and January 2023 were divided into control group (83 cases) and observation group (86 cases). The control group received medication-based treatment, while the observation group was provided with combined treatment of medication and vestibular rehabilitation training. Assessment of recovery included the Dizziness Handicap Inventory (DHI), Vestibular Symptom Index (VSI), and Activities-specific Balance Confidence (ABC) scale before and at two, four, and eight weeks post-treatment. Psychological status, sleep quality, and life quality were evaluated. Both groups underwent the Fukuda stepping test and timed balance test. At two, four, and eight weeks post-treatment, both groups exhibited significantly lower DHI-P, DHI-F, DHI-E, VSI, and ABC scores compared to pre-treatment (p<0.05). The observation group showed significantly lower DHI-P, DHI-F, DHI-E, VSI, and ABC scores than the control group at two and four weeks post-treatment (p<0.05). After treatment, both groups demonstrated reduced body deviation angles and increased time without falling in the Fukuda stepping test (p<0.05). Notably, the observation group had significantly better outcomes (p<0.05). In comparison to medication-based treatment alone, a combined approach involving medication treatment and vestibular rehabilitation training may demonstrate early improvements in vertigo symptoms, enhance balance capabilities, and ameliorate psychological well-being, sleep quality, and overall quality of life for patients.

The Development and Reliability of an Updated Dance-Specific Star Excursion Balance Test Protocol.

Background: While the previous research has made crucial developments in a dance-specific version of the SEBT, current modifications to the SEBT have not conclusively produced a valid dance-specific dynamic balance test. Purpose: The aim of this paper was to utilize the most practical dance-specific variations from previous research and incorporate them into a reliable test to be considered for future screenings for dancers. Methods: Twenty-one female dancers voluntarily took part in the research (age: 20.86 ± 3.68 years). This protocol consists of 3 stages, each increasing in difficulty; stage one: dsSEBT Average Tempo, stage two: dsSEBT Block, and stage three: a combination of stage 1 and stage 2, the dsSEBT Average Tempo on Block. Reach distance (% of limb length), error scores, and average time to complete each stage were recorded. A stage completion criteria was developed to move from one stage to the next wherein certain reach distance and error score standards needed to be met. Results: Between previous research using the same participants and the current study, each reach direction exhibits a statistically significant correlation (P < .05) with good to excellent ICC values ranging from .750 to .918, suggesting that test-retest reliability is high. Overall, 90.48% of participants succeeded in passing stage one, 19.05% of total participants passed stage two, and only 4.76% of the 21 participants passed all 3 stages with statistically significant differences detected for reach distance and incomplete trials between stages (P < .05). Conclusion: This data suggests that the test is challenging enough to show dancers weaknesses and push the limits of their balance capabilities. With a clear increase in difficulty from stage to stage, the test adds layers of demanding tasks designed to test the dancer proprioceptively.

Assessing fall risk in osteoporosis patients: a comparative study of age-matched fallers and nonfallers.

This study aimed to investigate sway parameters and physical activity level of the age/gender-matched older adults with osteoporosis faller and nonfaller patients. By examining these factors, our objective was to understand how these faller and nonfaller groups with osteoporosis differed particularly in terms of balance capabilities and their impact on physical activity levels. We recruited 24 patients with osteoporosis: 12 who reported a fall within a year before recruitment (fallers) and 12 without falls (nonfallers). Given the close association between biochemical markers of musculoskeletal health such as serum calcium, parathyroid hormone (PTH), Vitamin D, and renal function, we compared these markers in both groups. As a result, elderly individuals with osteoporosis and with a history of falls within the preceding year indicated significantly higher sway velocity (P = 0.012*), sway area (P < 0.001*), and sway path length (P = 0.012*). Furthermore, fallers had significantly lower calcium (P = 0.02*) and Parathyroid hormone (PTH) (P = 0.02*), as well as higher Alkaline Phosphatase (ALP) (P = 0.02*) as compared to nonfallers despite similar vitamin D and creatinine levels. In conclusion, diminished biochemical factors in the osteoporosis faller group could possibly cause postural instability resulting in lower physical activity levels in the osteoporosis fall group and increasing the risk of falls.

Self-Voltage Balanced Switched-Capacitor Seven-Level Inverter for Asymmetrical Solar PV Source Applications

In this paper, a novel structure of self-voltage balanced switched-capacitor-based seven-level inverter (SVB-SCSLI) is proposed for asymmetrical input energy source applications. SVB-SCSLI develops a seven-level staircase waveform with a minimum number of semiconductor devices compared to existing multilevel inverters (MLIs). The proposed converter is more suitable for the solar PV system where unequal DC voltage sources are available. The SVB-SCSLI also resolves the main difficulty of connecting many inverters in parallel to achieve staircase voltage. Besides, it attains voltage balancing capability at DC-link by holding constant capacitor voltage at every cycle. The detailed loss and steady-state analysis of the SVB-SCSLI are examined. Furthermore, the proposed converter’s efficiency improves with better power quality than other topologies reported in the literature. Finally, a prototype is fabricated, and experimental results are presented to validate the feasibility of SVB-SCSLI.

A mixed integer linear programming model for quarantine-based home healthcare scheduling under uncertainty

Home healthcare companies (HHC) have emerged as vital alternatives to traditional hospitals, particularly in meeting the healthcare needs of individuals within the comfort of their homes. The COVID-19 pandemic has amplified the significance of HHC services, offering a crucial alternative for patients and the elderly to follow quarantine protocols while receiving essential healthcare at home. Consequently, HHC companies must align their planning strategies with the World Health Organization (WHO) health guidelines. This research introduces a Mixed Integer Linear Programming (MILP) model tailored for home healthcare services during COVID-19, aiming to ensure strict adherence to quarantine protocols while enhancing service efficiency and quality. The proposed vehicle routing problem with pickup/delivery and time window formulation incorporates critical elements such as patient and caregiver classification, work and break regulations adherence, workload balancing, and multi-depot capabilities. The model addresses uncertain demand and service times through a stochastic programming approach to enhance practicality. K-means clustering is applied to streamline scenarios, with a sensitivity analysis determining the optimal number of clusters. Additionally, measures intrinsic to stochastic programming, such as the Expected Value of Perfect Information (EVPI) and Value of Stochastic Solution (VSS), are computed for comprehensive analysis.

Short-term effects of kinesiology taping on static and dynamic balance in healthy subjects.

As a therapeutic tool, kinesiology taping (KT) has become increasingly popular for musculoskeletal injuries utilized by physiotherapists. KT has been found to have effects on facilitating muscle strength by generating a concentric pull on the fascia. However, little is known about KT in the improvement of dynamic and static balance. This study aims to explore whether KT on the quadriceps muscle has any immediate effects on static and dynamic balance. Twenty-seven healthy individuals (13 males and 14 females, aged 22 to 29) were recruited in a crossover study with two conditions: KT and no taping. KT was applied to the quadriceps muscle for the taping group, with the control receiving no taping. Pre- and post-test measurements were taken to give an indication of the effect of the tape on balance performance. Center of Pressure Excursion (COPE) and Time to Stabilization (TTS) when landing from a hop test and Y Balance test combined score (YBTCS) were used to assess a stabilizing balance activity and a dynamic balance. The pre- and post-intervention were collected, with differences explored using repeated measures ANOVA with time and condition (tape) factor analysis. We found a significant improvement (p ≤ 0.05) with a moderate to large effect size in YBTCS between KT and no taping, indicating enhanced balance performance in the KT group. However, no significant difference (p ≥ 0.05) with small to moderate effect size was found in COPE or TTS between the two conditions during landing tests, suggesting similar balance capabilities in these specific measures. The use of KT shows no significant immediate effect on static balance in healthy individuals when applied to the quadriceps muscles; however, it demonstrates a positive immediate effect on dynamic balance.