Search Results (472)

This study proposes a novel metaheuristic algorithm, Cosmic Evolution Optimization (CEO), for numerical optimization and engineering design. Inspired by the cosmic evolution process, CEO simulates physical phenomena including cosmic expansion, universal gravitation, stellar system interactions, and celestial orbital resonance.The algorithm introduces a multi-stellar framework system, which incorporates search agents into distinct subsystems to perform simultaneous exploration or exploitation behaviors, thereby enhancing diversity and parallel exploration capabilities. Specifically, the CEO algorithm was compared against ten state-of-the-art metaheuristic algorithms on 29 typical unconstrained benchmark problems from CEC2017 across different dimensions and 13 constrained real-world optimization problems from CEC2020. Statistical validations through the Friedman test, the Wilcoxon rank-sum test, and other statistical methods have confirmed the competitiveness and effectiveness of the CEO algorithm. Notably, it achieved a comprehensive Friedman rank of 1.28/11, and the winning rate in the Wilcoxon rank-sum tests exceeded 80% in CEC2017. Furthermore, CEO demonstrated outstanding performance in practical engineering applications such as robot path planning and photovoltaic system parameter extraction, further verifying its efficiency and broad application potential in solving real-world engineering challenges. Full article

Recent advancements have been made in the precise prediction of protein structures within the Protein Folding Problem (PFP), particularly in relation to minimizing the energy function to achieve stable and biologically relevant protein structures. This problem is classified as NP-hard within computational theory, necessitating the development of various techniques and algorithms. Bio-inspired algorithms have proven effective in addressing NP-hard challenges in practical applications. This study introduces a novel hybrid algorithm, termed GRSABio, which integrates the strategies of Jumping Spider Algorithm (JSOA) with the Golden Ratio Simulated Annealing (GRSA) for peptide prediction. Furthermore, the GRSABio algorithm incorporates a Convolutional Neural Network for fragment prediction (FCNN), forms an enhanced methodology called GRSABio-FCNN. This integrated framework achieves improved structure refinement based on energy for protein prediction. The proposed enhanced GRSABio-FCNN approach was applied to a dataset of 60 peptides. The Wilcoxon and Friedman statistics test were employed to compare the GRSABio-FCNN results against recent state-of-the-art-approaches. The results of these tests indicate that the GRSABio-FCNN approach is competitive with state-of-the-art methods for peptides up to 50 amino acids in length and surpasses leading PFP algorithms for peptides with up to 30 amino acids. Full article

The Slime Mould Algorithm (SMA) is a widely used swarm intelligence algorithm. Encouraged by the theory of no free lunch and the inherent shortcomings of the SMA, this work proposes a new variant of the SMA, called the BWSMA, in which three improvement mechanisms are integrated. The adaptive greedy mechanism is used to accelerate the convergence of the algorithm and avoid ineffective updates. The best–worst management strategy improves the quality of the population and increases its search capability. The stagnant replacement mechanism prevents the algorithm from falling into a local optimum by replacing stalled individuals. In order to verify the effectiveness of the proposed method, this paper conducts a full range of experiments on the CEC2018 test suite and the CEC2022 test suite and compares BWSMA with three derived algorithms, eight SMA variants, and eight other improved algorithms. The experimental results are analyzed using the Wilcoxon rank-sum test, the Friedman test, and the Nemenyi test. The results indicate that the BWSMA significantly outperforms these compared algorithms. In the comparison with the SMA variants, the BWSMA obtained average rankings of 1.414, 1.138, 1.069, and 1.414. In comparison with other improved algorithms, the BWSMA obtained average rankings of 2.583 and 1.833. Finally, the applicability of the BWSMA is further validated through two structural optimization problems. In conclusion, the proposed BWSMA is a promising algorithm with excellent search accuracy and robustness. Full article

The energy generated from renewable sources has an intermittent nature since solar irradiation and wind speed vary continuously. Hence, their energy should be stored to be utilized throughout their shortage. There are various forms of energy storage systems while the most widespread technique is the battery storage system since its cost is low compared to other techniques. Therefore, batteries are employed in several applications like power systems, electric vehicles, and smart grids. Due to the merits of the lithium-ion (Li-ion) battery, it is preferred over other kinds of batteries. However, the accuracy of the Li-ion battery model is essential for estimating the state of charge (SOC). Additionally, it is essential for consistent simulation and operation throughout various loading and charging conditions. Consequently, the determination of real battery model parameters is vital. An innovative application of the red-billed blue magpie optimizer (RBMO) for determining the model parameters and the SOC of the Li-ion battery is presented in this article. The Shepherd model parameters are determined using the suggested optimization algorithm. The RBMO-based modeling approach offers excellent execution in determining the parameters of the battery model. The suggested approach is compared to other programmed algorithms, namely dandelion optimizer, spider wasp optimizer, barnacles mating optimizer, and interior search algorithm. Moreover, the suggested RBMO is statistically evaluated using Kruskal–Wallis, ANOVA tables, Friedman rank, and Wilcoxon rank tests. Additionally, the Li-ion battery model estimated via the RBMO is validated under variable loading conditions. The fetched results revealed that the suggested approach achieved the least errors between the measured and estimated voltages compared to other approaches in two studied cases with values of 1.4951 × 10⁻⁴ and 2.66176 × 10⁻⁴. Full article

Various parameters and observation conditions contribute to the emergence of color. This phenomenon poses a challenge in modern visual communication systems, which are continuously being enhanced through new insights gained from research into specific psychophysical effects. One such effect is the psychophysical phenomenon of simultaneous contrast. Nearly 90 years ago, Kurt Koffka described one of the earliest illusions related to simultaneous contrast. This study examined the perception of gray tone variations in the Koffka ring against different background color combinations (red, blue, green) displayed on a computer screen. The intensity of the effect was measured using lightness difference ΔL₀₀ across light-, medium-, and dark-gray tones. The results were analyzed using descriptive statistics, while statistically significant differences were determined using the Friedman ANOVA and post hoc Wilcox tests. The strongest visual effect was observed the for dark-gray tones of the Koffka ring on blue/green and red/green backgrounds, indicating that perceptual organization and spatial parameters influence the illusion’s magnitude. The findings suggest important implications for digital media design, where understanding these effects can help avoid unintended color tone distortions caused by simultaneous contrast. Full article

In modern vehicles, Autonomous Driving Systems (ADSs) are designed to operate partially or fully without human intervention. The ADS pipeline comprises multiple layers, including sensors, perception, localization, mapping, path planning, and control. The Robot Operating System (ROS) is a widely adopted framework that supports the modular development and integration of these layers. Among them, the path-planning and control layers remain particularly challenging due to several limitations. Classical path planners often struggle with non-smooth trajectories and high computational demands. Meta-heuristic optimization algorithms have demonstrated strong theoretical potential in path planning; however, they are rarely implemented in real-time ROS-based systems due to integration challenges. Similarly, traditional PID controllers require manual tuning and are unable to adapt to system disturbances. This paper proposes a ROS-based ADS architecture composed of eight integrated nodes, designed to address these limitations. The path-planning node leverages a meta-heuristic optimization framework with a cost function that evaluates path feasibility using occupancy grids from the Hector SLAM and obstacle clusters detected through the DBSCAN algorithm. A dynamic goal-allocation strategy is introduced based on the LiDAR range and spatial boundaries to enhance planning flexibility. In the control layer, a modified Pure Pursuit algorithm is employed to translate target positions into velocity commands based on the drift angle. Additionally, an adaptive PID controller is tuned in real time using the Differential Evolution (DE) algorithm, ensuring robust speed regulation in the presence of external disturbances. The proposed system is practically validated on a four-wheel differential drive robot across six scenarios. Experimental results demonstrate that the proposed planner significantly outperforms state-of-the-art methods, ranking first in the Friedman test with a significance level less than 0.05, confirming the effectiveness of the proposed architecture. Full article

Background: Medical education is considered one of the most academically and emotionally demanding training programs. Throughout their education, medical students are exposed to various factors that can lead to psychological distress, depression, and anxiety. The aim of this longitudinal study was to examine the changes in psychological distress, depression, anxiety levels and internet addiction among medical students throughout their six-year education and to identify the contributing factors. Methods: The study cohort consisted of 282 students who enrolled in the medical faculty in the 2017–2018 academic year. A questionnaire including sociodemographic characteristics, the General Health Questionnaire-12 (GHQ-12), Beck Depression Inventory (BDI), State–Trait Anxiety Inventory (STAI), and Young Internet Addiction Test (IAT) was administered to the students during the first week of their education. The same questionnaire was readministered at the end of the third and sixth years. Friedman’s variance analysis was used to compare measurement data across the three time points, while Cochran’s Q Test was employed for categorical variables. Results: The median scores of the GHQ-12, BDI, S-Anxiety, and IAT significantly increased from the first to the sixth year (p < 0.05). The prevalence of depressive symptoms, S-Anxiety, and risky internet use significantly increased from the first to the final year, particularly between the third and sixth years. According to logistic regression analysis based on sixth-year data, students whose fathers were university graduates, who had been diagnosed with COVID-19, and who were dissatisfied with their social lives were found to be at increased risk for psychological distress and depression. Students with high parental expectations were found to be at risk of depression and S-anxiety. Those dissatisfied with their occupational choice were at risk for both psychological distress and S-anxiety. Conclusions: It was found that the mental health of medical students deteriorated during their education, especially during the clinical years. Given that these students will be responsible for protecting and improving public health in the future, it is essential to prioritize their own mental well-being. Interventions aimed at preserving the mental health of medical students should be planned. Full article

This study investigates the effects of transcutaneous electroacupuncture stimulation (TEAS) on eyeblink rate, EEG, and heart rate variability (HRV), emphasising whether eyeblink data—often dismissed as artefacts—can serve as useful physiological markers. Sixty-six participants underwent four TEAS sessions with different stimulation frequencies (2.5, 10, 80, and 160 pps, with 160 pps as a low-amplitude sham). EEG, ECG, PPG, and respiration data were recorded before, during, and after stimulation. Using non-parametric statistical analyses, including Friedman’s test, Wilcoxon, Conover–Iman, and bootstrapping, the study found significant changes across eyeblink, EEG, and HRV measures. Eyeblink laterality, particularly at 2.5 and 10 pps, showed strong frequency-specific effects. EEG power asymmetry and spectral centroids were associated with HRV indices, and 2.5 pps stimulation produced the strongest parasympathetic HRV response. Blink rate correlated with increased sympathetic and decreased parasympathetic activity. Baseline HRV measures, such as lower heart rate, predicted participant dropout. Eyeblinks were analysed using BLINKER software (v. 1.1.0), and additional complexity and entropy (‘CEPS-BLINKER’) metrics were derived. These measures were more predictive of adverse reactions than EEG-derived indices. Overall, TEAS modulates multiple physiological markers in a frequency-specific manner. Eyeblink characteristics, especially laterality, may offer valuable insights into autonomic function and TEAS efficacy in neuromodulation research. Full article

Background: Surface electromyography (sEMG) enables the non-invasive assessment of muscle activity and is widely used in orthodontics for evaluating masticatory muscles. However, little is known about the dynamic changes in facial expression muscles during orthodontic treatment. This study aimed to investigate alterations in facial muscle tone during the leveling and alignment phase in adult female patients undergoing fixed appliance therapy. Methods: The study included 30 female patients aged 20–31 years who underwent sEMG assessment at four time points: before treatment initiation (T0), at the start of appliance placement (T1), three months into treatment (T2), and six months into treatment (T3). Muscle activity was recorded during four standardized facial expressions: eye closure, nasal strain, broad smile, and lip protrusion. Electrodes were placed on the orbicularis oris, orbicularis oculi, zygomaticus major, and levator labii superioris alaeque nasi muscles. A total of 1440 measurements were analyzed using Friedman and Conover-Inman tests (α = 0.05). Results: Significant changes in muscle tone were observed during treatment. During lip protrusion, the orbicularis oris and zygomaticus major showed significant increases in peak and minimum activity (p < 0.01). Eye closure was associated with altered orbicularis oris activation bilaterally at T3 (p < 0.01). Nasal strain induced significant changes in zygomaticus and levator labii muscle tone, particularly on the right side (p < 0.05). No significant changes were noted during broad smiling. Conclusions: Orthodontic leveling and alignment influence the activity of selected facial expression muscles, demonstrating a dynamic neuromuscular adaptation during treatment. These findings highlight the importance of considering soft tissue responses in orthodontic biomechanics and suggest potential implications for facial esthetics and muscle function monitoring. Full article

Background/Objectives: The glymphatic system plays a crucial role in clearing brain metabolic waste, and its dysfunction has been correlated to various neurological disorders. The Diffusion Tensor Imaging Analysis Along the Perivascular Space (DTI-ALPS) index has been proposed as a non-invasive marker of glymphatic function by measuring diffusivity along perivascular spaces; however, its sensitivity to sleep-related changes in glymphatic activity has not yet been validated. This study aimed to evaluate the feasibility of using the DTI-ALPS index as a quantitative marker of dynamic glymphatic activity during sleep. Methods: Diffusion tensor imaging (DTI) data were obtained from 12 healthy male participants (age = 24.44 ± 2.5 years; Pittsburgh Sleep Quality Index (PSQI) < 5), once while awake and 16 times during sleep, following 24 h sleep deprivation and administration of 10 mg zolpidem. Simultaneous MR-compatible electroencephalography was used to determine whether the subject was asleep or awake. DTI preprocessing included eddy current correction and tensor fitting. The DTI-ALPS index was calculated from nine regions of interest in projection and association areas aligned to standard space. The final analysis included nine participants (age = 24.56 ± 2.74 years; PSQI < 5) who maintained a continuous sleep state for 1 h without awakening. Results: Among nine ROI pairs, three showed significant increases in the DTI-ALPS index during sleep compared to wakefulness (Friedman test; p = 0.027, 0.029, 0.034). These ROIs showed changes at 14, 19, and 25 min after sleep induction, with FDR-corrected p-values of 0.024, 0.018, and 0.018, respectively. Conclusions: This study demonstrated a statistically significant increase in the DTI-ALPS index within 30 min after sleep induction through time-series DTI analysis during wakefulness and sleep, supporting its potential as a biomarker reflecting glymphatic activity. Full article

Aim: To evaluate whether maximum occlusal loading and periodontal status are different between teeth presenting deflective occlusal contacts and those without such contacts, specifically adjacent and homologous teeth. Method: A cross-sectional study was conducted using OccluSense to detect deflective contacts and quantify occlusal load per tooth. For group comparisons, the Kruskal–Wallis, Friedman, Cochran’s Q, and chi-squared tests were used. Results: A total of 493 teeth with deflective contacts were compared to 473 adjacent (first control group) and 457 homologous teeth (second control group). Teeth with deflective contacts showed significantly higher occlusal loading (mean value: 208) than adjacent (72) and homologous teeth (97) (p < 0.05). They also exhibited more advanced periodontal damage, including deeper probing depths, greater gingival recession, alveolar bone loss, and a wider periodontal ligament space. Deflective contacts in centric relation were more strongly linked to periodontal deterioration than those in protrusive or lateral mandibular movements, despite similar occlusal forces. Conclusions: Within this study’s limitations, deflective occlusal contacts are associated with increased occlusal forces and more severe periodontal damage, suggesting a biomechanical factor in periodontal disease progression. Full article

The growing urgency of the climate crisis has heightened the importance of integrating sustainability into health education. Allied health professionals are well positioned to lead sustainable healthcare efforts, yet evidence suggests a persistent gap between student awareness and formal training. This study explored the perspectives, knowledge, and attitudes of Portuguese allied health students regarding sustainability. An online and anonymous cross-sectional survey was conducted among undergraduate and graduate students across multiple allied health disciplines. The questionnaire assessed general knowledge, perceptions of curricular integration, and attitudes toward sustainable clinical practice. A total of 247 (response rate of 8.23%) students participated, with the majority expressing high concern about climate change and strong support for environmentally responsible healthcare. However, the results revealed inconsistent awareness of healthcare’s environmental footprint and a limited exposure to structured sustainability education. Friedman tests indicated significant variability in students’ knowledge, perceived responsibility, and curricular experiences. Students identified priority themes for curricular inclusion—such as the environmental impact of the health system—and recognized their alignment with the UN Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health) and SDG 13 (Climate Action). The findings highlight the need for the systematic, competency-based integration of sustainability into allied health curricula to support a climate-resilient and ecologically responsible future healthcare workforce. Full article

In this in vitro study, we compare the discoloration potential of three premixed calcium silicate cements, specifically EndoCem MTA Premixed, Bio-C Repair, and NeoPUTTY, when applied with or without two surface pretreatments (Nd-YAG laser irradiation or dentin-bonding agents). One hundred extracted human maxillary incisors were allocated into ten groups (n = 10), including the untreated control group. A standard access cavity was prepared in all teeth except the control group. Groups were formed according to the type of premixed calcium silicate cement used and the surface pretreatment applied to the internal surfaces of the cavities. Color measurements were taken with a VITA Easyshade Advance 5.0 spectrophotometer and converted to ΔE values using the CIEDE2000 formula at baseline (T0) and 7 (T1), 30 (T2), 90 (T3), and 180 (T4) days. Data were analyzed using the Shapiro–Wilk test to assess normality, followed by the Friedman and Kruskal–Wallis tests for within- and between-group comparisons, respectively (α = 0.05). No statistically or clinically significant differences in ${∆\mathrm{E}}_{00}$ were detected among materials, surface treatments, or timepoints (p > 0.05). All mean ${∆\mathrm{E}}_{00}$ values remained below the perceptibility threshold (3.5). Within the limitations of this 180-day in vitro model, the tested materials showed favorable short-term color stability, and neither the Nd-YAG laser nor the dentin-bonding agents altered the outcomes. Long-term in vivo studies are required to recommend their clinical use in aesthetically critical areas. Full article

Multilevel thresholding image segmentation plays a crucial role in various image processing applications. However, achieving optimal segmentation results often poses challenges due to the intricate nature of images. In this study, a novel metaheuristic search algorithm named Weighted Chimp Optimization Algorithm with Fitness–Distance Balance (WChOA-FDB) is developed. The algorithm integrates the concept of Fitness–Distance Balance (FDB) to ensure balanced exploration and exploitation of the solution space, thus enhancing convergence speed and solution quality. Moreover, WChOA-FDB incorporates weighted Chimp Optimization Algorithm techniques to further improve its performance in handling multilevel thresholding challenges. Experimental studies were conducted to test and verify the developed method. The algorithm’s performance was evaluated using 10 benchmark functions (IEEE_CEC_2020) of different types and complexity levels. The search performance of the algorithm was analyzed using the Friedman and Wilcoxon statistical test methods. According to the analysis results, the WChOA-FDB variants consistently outperform the base algorithm across all tested dimensions, with Friedman score improvements ranging from 17.3% (Case-6) to 25.2% (Case-4), indicating that the FDB methodology provides significant optimization enhancement regardless of problem complexity. Additionally, experimental evaluations conducted on color image segmentation tasks demonstrate the effectiveness of the proposed algorithm in achieving accurate and efficient segmentation results. The WChOA-FDB method demonstrates significant improvements in Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM) metrics with average enhancements of 0.121348 dB, 0.012688, and 0.003676, respectively, across different threshold levels (m = 2 to 12), objective functions, and termination criteria. Full article

Surgical Site Infection (SSI) can be a devastating complication, leading to increased morbidity, mortality, and healthcare costs. Pre-surgical hand preparation is an effective strategy to prevent SSI. The two most common pre-surgical hand preparation methods are antimicrobial soap for surgical hand scrub and alcohol-based surgical hand rub. The antimicrobial soap hand scrub remains more commonly used among operating theater staff. However, several studies showed that alcohol-based hand rubs are much more effective than antiseptic soap hand scrubs. Objective: This study aimed to compare the effect of the two methods of surgical hand preparation on the number of bacterial colonies. Methods: The design of this study was a comparative study with a pre-test and post-test approach in two groups (a surgical hand scrub using 4% chlorhexidine soap group and a surgical hand rub using 70% ethyl alcohol and 2.5% chlorhexidine group). Hand smear sampling was performed before surgical hand preparation (pre-test), immediately after surgical hand preparation (post-test 1), and after the surgery was completed (post-test 2). Seventy-one hand smear samples (35 samples applied the surgical hand rub, and 36 samples applied the surgical hand scrub) were divided into two groups and examined for colony counts in Colony Forming Units (CFU) using the total plate count method. Descriptive and comparative analysis were applied. Results: The surgical hand-scrub group had average pre-test, post-test 1, and post-test 2 colony counts of 0.202 CFU/cm², 0.007 CFU/cm², and 0.016 CFU/cm², respectively, while the surgical hand-rub group had average pre-test, post-test 1, and post-test 2 colony counts of 0.163 CFU/cm², 0.001 CFU/cm², and 0.001 CFU/cm² respectively. Statistical analysis using the Friedman test showed that both methods significantly reduced the number of colonies (p < 0.01). Based on the Mann–Whitney test, there was no significant difference between the two groups regarding the number of colonies (p > 0.05). Conclusions: Surgical hand-scrub and hand-rub have similar effectiveness in reducing and maintaining the number of colonies on hands during surgery, both gram-positive and gram-negative bacteria. Full article