Browse Articles

Integrating multiple slack bus operations and metaheuristic techniques for power flow optimization

Abstract The increasing complexity of modern energy grids amplifies the importance of realistic power flow studies in power system analysis. This study implements a Multiple Slack Bus Operation (MSO) framework to enhance the realism and efficiency of optimal power flow (OPF) analysis. This paper introduces a comparative evaluation of three metaheuristic algorithms: particle swarm optimization (PSO), cuckoo search algorithm (CSA), and grey wolf optimization (GWO) within the MSO framework. These algorithms are assessed based on their effectiveness in minimizing system loss, optimizing line loading, adjusting the angle of the generator voltage, and optimizing the generation distribution. Using the Reduced Nordic 44 model and the IEEE benchmark test systems in various load conditions, the findings reveal that the GWO algorithm, when integrated with the MSO framework, achieves the most significant reduction in total system losses. The implementation of MSO alone reduced system losses by 5%, and its combination with GWO led to an additional 8.3% decrease. This study investigates the application of metaheuristic algorithms within a multiple slack bus context, highlighting their potential to enhance power network efficiency and suggesting broader applications for future power flow optimization strategies.

Investigation of mixing performance in electro-osmotic micromixers through rigid baffle design and parameter optimization

Measuring the cyclic compressional behaviour of soil under constrained lateral deformations

Biomechanical evaluation of the new intramedullary system II for treating reverse obliquity trochanteric fractures

Anti-aging protein α-Klotho is potential for reducing comorbidity risk of cardiometabolic diseases in vulnerable populations and enhancing long-term prognosis

Abstract This study investigated the impact of anti-aging protein α-Klotho on cardiometabolic diseases (CMDs) among middle-aged and elderly population. A total of 11,198 participants aged 40–79 years were included in the National Health and Nutrition Examination Survey (NHANES) spanning 2007–2016. Serum α-Klotho levels were quantified via enzyme-linked immunosorbent assays. CMDs comprised cardiovascular disease (CVD), and four metabolic disorders: type 2 diabetes (T2DM), obesity, chronic kidney disease (CKD), and non-alcoholic fatty liver disease (NAFLD). Weighted logistic regression analysis, subgroup analysis, mediation analysis, restricted cubic splines (RCS), and Cox proportional hazards regression analysis were used. α-Klotho exhibited negative associations with each single CMD except T2DM, and RCS showed U-shape and L-shape dose-response relationships of α-Klotho with risk of T2DM and CKD, respectively. Ordered logistic regression analysis revealed that higher levels of Klotho markedly reduced the cumulative number of metabolic comorbidities complicating CVD (OR 0.56 (0.35, 0.91)). Simple mediation analysis showed CKD may explain up to 20.42% of the association between Klotho and CVD. Notably, α-Klotho’s association with cardiometabolic comorbidities was particularly evident among individuals who were widowed/divorced/separated, non-Hispanic Black, lower-income, or less educated, with hypertension, current smokers, lower leisure and commuting physical activity, but higher work-related physical activity. Regarding long-term effects, higher α-Klotho levels were associated with lower all-cause mortality among participants with CMDs, but not among those without CMDs. Higher α-Klotho levels were associated with lower CMD prevalence, particularly in high-risk cardiovascular populations with lower socioeconomic status and unfavorable lifestyles and reduced all-cause mortality risk among CMD patients.

Screening of rhizobacteria from monkey pod trees for plant growth promoters and evaluating the antifungal potential of the biosynthesized selenium nanoparticles

Dry sliding tribological characteristics evaluation and prediction of TiB2-CDA/Al6061 hybrid composites exercising machine learning methods

Scream’s roughness grants privileged access to the brain during sleep

Abstract During sleep, recognizing threatening signals is crucial to determine when to wake up and when to continue vital sleep functions. Screaming is perhaps the most efficient way for communicating danger at a distance or in conditions of limited visibility. Screams are characterized by rapid modulations of sound pressure in the so-called roughness range (i.e., 30–150 Hz) which are particularly powerful in capturing attention. However, whether these rough sounds are also processed in a privileged manner during sleep is unknown. We tested this hypothesis by presenting human participants with low-intensity vocalizations, including rough screams and neutral, low-roughness vocalizations during wakefulness and during a full night of sleep. We found that screams evoked cortical responses with higher theta phase-consistency as compared to neutral vocalizations during both wakefulness and NREM sleep. In addition, screams boosted sleep spindle power, suggesting elevated stimulus salience. These findings demonstrate that, even at low sound intensity (e.g., from a distant source), vocalizations’ roughness conveys stimulus relevance and enhances exogenous processing in both the waking and sleeping states. Preserved differential neural responses based on stimulus salience may ensure adaptive reactions in a state where the brain is mostly disconnected from external inputs.

Clinical and radiographic outcome of a bioceramic sealer compared to a resin-based sealer: a retrospective study

Abstract Effective sealing of root canal systems is paramount in achieving favorable and enduring prognosis of root canal treatments (RCTs). Root canal sealers play a pivotal role in sealing the canal system. To date, there is a scarcity of clinical research investigating the implications and long-term performance of bioceramic (BC) sealers. This study aims to compare the treatment outcome of resin-based (RB) and BC root canal sealers. Retrospective data comparing clinical outcomes of 248 endodontically treated teeth was performed utilizing dental records and radiographic assessments. Clinical outcome of the RCTs using both types of sealers were measured by percentages of success rates. Chi square statistical test was used to analyze data at 0.01 and level of significance via SPSS software. Success rate of RCTs was not influenced by patient’s age, gender, tooth type and number of visits. There were no significant differences in the success rate amongst treatment types, obturation techniques, quality of restoration and the sealer type. BC and RB sealers revealed comparable clinical and radiographic outcomes with high success rates. The choice between BC and RB sealers should be guided by case-specific factors, including tooth’s anatomical considerations, patient’s dental health status, obturation techniques and clinician’s skills.

1H NMR metabolomic profiling of resistant and susceptible oil palm root tissues in response to Ganoderma boninense at the nursery stage

Abstract Oil palm plantations face serious challenges from Ganoderma boninense, a pathogen that causes basal stem rot (BSR), leading to significant productivity losses, with an estimated economic impact of 68.73%. Ganoderma spreads through direct root contact and airborne spores, affecting plantations across Indonesia, Malaysia, and other countries. Understanding the mechanisms of oil palm resistance to Ganoderma is crucial for developing effective strategies. Metabolomic profiling, ¹H NMR spectroscopy, offers a promising tool for identifying and quantifying metabolic changes associated with Ganoderma resistance. This study, ¹H NMR was employed to analyze root tissues of resistant, susceptible, and control oil palm seedlings exposed to Ganoderma. The results indicated that PCA effectively differentiated resistant palms from susceptible ones, while PLS-DA identified 14 significant metabolites. Further analysis using OPLS-DA and ROC revealed that ascorbic acid, D-gluconic acid, D-fructose, and 2-oxoisovalerate could serve as potential biomarkers for screening resistant palms. The metabolites identified in this study hold considerable promise for supporting breeding programs to develop oil palm varieties with enhanced resistance to BSR.

Single and combined effect of beetroot juice and caffeine intake on muscular strength, power and endurance performance in resistance-trained males

A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning

Prediction model of mitochondrial energy metabolism related genes in idiopathic pulmonary fibrosis and its correlation with immune microenvironment

Mice grow bigger brains when given this stretch of human DNA

Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques

Abstract This research focuses on enhancing the thermal conductivity of coir fibre-reinforced polyvinyl chloride (PVC) composites using advanced optimization techniques. While coir fibre adds sustainability and biodegradability, it poses challenges in achieving optimal thermal performance when integrated into PVC. To address these challenges, the study uses Response Surface Methodology (RSM) and three nature-inspired optimization methods viz. Particle Swarm Optimization (PSO), Dragonfly Optimization (DFO) and Cuckoo Search Algorithm (CSA) to improve factors like fibre content, particle size and chemical treatment. A Box-Behnken experimental design helps to create composite samples using hydraulic injection moulding and thermal conductivity is measured with a two-slab guarded hot plate device. Among the optimization methods, CSA emerges as the most effective, achieving a maximum thermal conductivity of 0.801 W/mK with minimal error deviation (0.01–5.5%) by the process parameters such as potassium hydroxide treatment, coir content of 2 wt% and powder diameter of 75 (µm). DFO delivers consistent results with slightly higher error rates, while PSO demonstrates rapid convergence but greater variability. The comparison shows that CSA performs better, providing a dependable and long-lasting way to create high-quality coir-reinforced PVC composites that are good for industrial use. This work is among the first to compare multiple bio-inspired optimization algorithms for enhancing the thermal properties of coir-reinforced PVC composites, offering a new pathway for developing high-performance, eco-friendly materials for industrial applications.

Secure command transmission techniques for industrial remote control

Abstract Operating a factory near a war zone or in a country with an unstable political environment poses significant risks. These risks can be mitigated by managing production lines remotely. To preserve technical knowledge and specific algorithms, it is essential to implement secure, precise, and efficient remote control in industrial applications, especially considering the risks associated with storing operational code on controllers. To address these challenges, we propose a novel technique where executable commands are dynamically transmitted from a Python script to an ESP32-WROOM-32 microcontroller. Unlike conventional methods that preload code onto the controller, this approach interprets, executes, and erases commands immediately after execution, thereby enhancing security and precision. The proposed system was evaluated through a comparative analysis of eleven distinct methods, which varied in command transmission strategies and employed dual-core processing for performance optimization. VPN technology was integrated to enable remote control from geographically distant locations, demonstrating the system’s adaptability for global industrial operations. The results indicate that this method significantly outperforms the traditional on-site approach, where operational code is preloaded onto the microcontroller. Specifically, bundled command transmission combined with dual-core processing proved particularly effective, reducing latency and improving reliability. These findings highlight the robustness of the proposed approach as a secure and flexible solution for modern smart factories.

Oxa-π, σ-Methane Rearrangement Approach for Epoxide Synthesis

Pharmacological inhibition of hypoxia induced acidosis employing a CAIX inhibitor sensitizes gemcitabine resistant PDAC cells

Deep magma sources beneath Central Kamchatka inferred from teleseismic tomography

Digital support for female students in physical education universities in Japan

Abstract Alongside acquiring specialized knowledge and accomplishing developmental tasks, athletic colleges require young athletes to also be active. We investigated the use of a smartphone application, ME-FULLNESS, as an unprecedented support method for female college students currently enrolled in athletic colleges. ME-FULLNESS is an application that infers one’s psychological state from their facial information and improves their psychological state with music, vibration, and images that match that psychological state. We conducted a psychological survey with purposively selected female university students (18 to 24 years) at the International Pacific University in Okayama, Japan, before and after one month of using ME-FULLNESS ( N  = 76) and a group of non-users ( N  = 25). The app-using group showed significant improvement in depressive symptoms ( p  = 0.002), anxiety symptoms ( p  = 0.000), stress ( p  = 0.000), insomnia ( p  = 0.002), severity of premenstrual syndrome ( p  = 0.000), and resilience scores ( p  = 0.000), while the non-app-using group showed improvement in anxiety ( p  = 0.009) and resilience scores ( p  = 0.000). This study suggests that using the ME-FULLNESS app may improve depression, stress, insomnia, and resilience among athletic female students, positively contributing to their college life and sports performance.