Search Results (40)

Brain functional connectivity evolves dynamically during brain development, aging, illness, and cognitive activities. Traditional methods rely on static network snapshots, which do not capture the dynamics of the brain. We propose two new indices: Dynamic Network Similarity (DNS) to measure both temporal and structural dynamic similarity and Dynamic Network Evolution Similarity (DNES) to specifically measure the temporal evolution of dynamic networks. Performance was tested using simulated dynamic networks controlled by four variables (Δφ, λ, α, and β) concerning evolution variations in phase, relative amplitude, noise power, and the span of connectivity strength, respectively. Furthermore, real-world fMRI data from 25 stroke patients pre/post transcranial direct current stimulation (tDCS) rehabilitation were used to test the indices. Patients were randomly sub-grouped into tDCS1 and tDCS2. DNS and DNES thus compared those who received the same therapy (ST: tDCS1 versus tDCS2) and those who received different therapies (DT: tDCS1 versus sham-tDCS). The results showed that DNS was sensitive to all dynamic features, and DNES was primarily sensitive to Δφ and λ. Both indices were able to detect overall difference and capture significantly higher similarity in the ST groups than in the DT groups. Briefly, DNS and DNES appear to be effective tools for studying dynamically evolving brain networks, and may serve as alternatives to traditional static methods. They are particularly useful for analyzing longitudinal neuroimaging data in contexts such as neurodevelopment, aging, and recovery from illness. Full article

A swarm intelligence optimization algorithm called white shark optimizer (WSO) has been proposed and successfully applied in regard to many aspects. In this paper, the location problem of sports facilities is regarded as a multi-objective problem, and the number of residents covered by sports facilities and the Weber problem are introduced as objective functions. A multi-objective white shark optimizer (MOWSO) is proposed, and MOWSO introduced an archived mechanism to store the non-dominated solutions obtained by the algorithm. When the Pareto solutions in the archive overflow, the solutions are removed by calculating the true distance of the Pareto optimal solution. The performance of the MOWSO is verified on CEC 2020 benchmark functions, and the results show that the proposed MOWSO is better than other algorithms in the diversity and distribution of solutions. The MOWSO is applied to solve the rural sports facilities location problem, and a variety of different sports facilities location schemes are obtained. It can provide a variety of options for the location of rural sports facilities, and promote the intelligent design of sports facilities. Full article

Background: Health issues among school-age children have emerged as a global public health concern. These conditions often do not occur in isolation but tend to cluster, indicating a widespread issue of multimorbidity among this population. This study examined the prevalence and clustering of multimorbidity among school-aged school students in the Yangzhou district. Methods: A repeated cross-sectional analysis was conducted from 2019 to 2024, including 22,512 students aged 6–18 years. Common diseases, under national key monitoring, including myopia, dental caries, obesity, elevated blood pressure, and growth disorders, were assessed. Multimorbidity patterns were identified using association rule mining (Apriori algorithm) with predefined thresholds (support ≥ 2.0%, confidence ≥ 20.0% and lift > 1). Results: The multimorbidity prevalence among school-age students in the Yangzhou district is 53.95%. The most frequent multimorbidity was found in dental caries and myopia, while the most common ternary pattern was found in obesity, dental caries, and myopia. The following gender differences were observed: boys had a higher multimorbidity prevalence (56.4%) compared to girls (51.2%), with boys more likely to exhibit obesity and dental caries, while girls showed a higher prevalence of myopia-related multimorbidity. By educational stage, primary school students showed a multimorbidity rate of 50.3%, junior high showed a rate of 54.6%, and senior high showed a rate of 57.9%, indicating a rising trend across age groups. Patterns of multimorbidity varied but were interrelated. Conclusions: From 2019 to 2024, the prevalence of multimorbidity among school-aged children in Yangzhou remained relatively high, primarily manifesting as co-occurring myopia and other health issues. Patterns of multimorbidity across gender and educational stage varied but were interrelated. Full article

The workshop is a crucial site for ensuring the smooth operation of production activities within an enterprise, playing a significant role in its long–term development. A well–designed workshop layout can reduce material–handling costs during production and enhance the overall efficiency of the enterprise. This paper establishes a mathematical model for the workshop layout problem, aiming to minimize logistics transportation costs and maximize non–logistics relationships. Using a real–world case study, the White Shark Optimizer (WSO) algorithm is applied to solve the model. The results show that the transportation distance of the layout scheme obtained by the WSO algorithm is reduced by 381 m, 82 m, and 56 m, respectively, compared with the original layout, the Genetic Algorithm (GA), and the Sparrow Search Algorithm (SSA), and the non–logical relationship is increased by 24.84% and 1.6%, respectively. The layout scheme obtained by using the WSO algorithm is more excellent and can effectively improve the production efficiency of enterprises. Full article

Background: Early evaluation of treatment efficacy in adolescents and young adults with major depressive episodes (MDEs) remains a clinical challenge, often delaying timely therapeutic adjustments. Electroencephalography (EEG) alpha traveling waves, particularly those elicited by intermittent photic stimulation (IPS), may serve as biomarkers reflecting neural dynamics. This study aimed to investigate whether IPS-induced alpha traveling waves could predict early treatment outcomes in transitional-aged youth with MDEs. Methods: We recorded EEG signals from 119 patients aged 16–24 years at admission, prior to a standardized two-week treatment regimen. IPS was applied using multiple stimulus frequencies, and alpha traveling waves were analyzed in terms of directionality (forward vs. backward) and hemispheric lateralization. Results: Alpha traveling wave amplitudes varied across individuals, depending on stimulus frequency and hemisphere. Notably, a higher amplitude of backward alpha traveling waves at 10 Hz IPS in the left hemisphere significantly predicted positive early treatment response. In contrast, forward waves and right hemisphere responses did not show predictive value. Conclusions: IPS-induced backward alpha traveling waves in the left hemisphere may represent promising EEG biomarkers for early prediction of treatment efficacy in youth with MDEs. These findings offer a potential neurophysiological tool to support personalized treatment strategies and inform future clinical applications in adolescent and young adult depression. Full article

This paper proposes a Q-learning-driven butterfly optimization algorithm (QLBOA) by integrating the Q-learning mechanism of reinforcement learning into the butterfly optimization algorithm (BOA). In order to improve the overall optimization ability of the algorithm, enhance the optimization accuracy, and prevent the algorithm from falling into a local optimum, the Gaussian mutation mechanism with dynamic variance was introduced, and the migration mutation mechanism was also used to enhance the population diversity of the algorithm. Eighteen benchmark functions were used to compare the proposed method with five classical metaheuristic algorithms and three BOA variable optimization methods. The QLBOA was used to solve the green vehicle routing problem with time windows considering customer preferences. The influence of decision makers’ subjective preferences and weight factors on fuel consumption, carbon emissions, penalty cost, and total cost are analyzed. Compared with three classical optimization algorithms, the experimental results show that the proposed QLBOA has a generally superior performance. Full article

To investigate the potential of ferulic acid (FA) in attenuating the deleterious effects of oxidized fish oil (OF) on Macrobrachium nipponense, four experimental diets were formulated: 3% fresh fish oil (CT group, peroxide value: 2.2 mmol/kg), 3% oxidized fish oil (OF group, peroxide value: 318 mmol/kg), and 3% OF with an additional 160 and 320 mg/kg of FA (OF+FA160 group and OF+FA320 group, respectively). M. nipponense (initial weight: 0.140 ± 0.015 g) were randomly divided into four groups with six replicates (60 individuals per replicate) and reared for a period of 10 weeks. The results showed that the OF treatments significantly reduced the growth performance, the expression of antioxidant genes in the hepatopancreas, the levels of low-density lipoprotein cholesterol, and the gene expression levels of ACC, FAS, FABP10, ACBP, G6PDH, and SCD in the hepatopancreas (p < 0.05). OF supplementation significantly increased the levels of high-density lipoprotein cholesterol in hemolymph and the gene expression levels of CPT1 (p < 0.05). Addition of FA to the OF group significantly increased total bile acids (p < 0.05). In addition, it was found by Oil Red staining that the proportion of lipid droplets was significantly increased in the OF group (p < 0.05). However, the lipid droplets were alleviated by FA supplementation in the diet. OF was found to significantly reduce the diversity of intestinal microbiota by 16S rDNA sequencing and significantly increase the Firmicutes/Bacteroidetes (F/B) ratio (p < 0.05). Functional analysis of gut microbiota also showed that OF reduced lipolysis and led to fat deposition, which is related to gut microbiota. However, this study found that the composition of the gut microbiome of M. nipponense was changed by the addition of FA in the diet, including an increase in the abundance of Ruminococcaceae UCG-005 and Lachnospiraceae, a reduction in the F/B ratio, and an improvement in lipid metabolism. In conclusion, the OF induced oxidative stress, disturbed the balance of intestinal microbiota, promoted lipid accumulation, and caused disorders of lipid metabolism in M. nipponense by increasing lipid synthesis and reducing β-oxidation. However, the results of this study highlighted the potential of FA supplementation to modulate intestinal microbial composition, promote bile acid production, and activate genes related to lipid metabolism in the hepatopancreas, ultimately leading to a reduction in lipid deposition in M. nipponense. Full article

To tackle the challenges of cold start and data sparsity in recommendation systems, an increasing number of researchers are integrating item features, resulting in the emergence of multimodal recommendation systems. Although graph convolutional network-based approaches have achieved significant success, they still face two limitations: (1) Users have different preferences for various types of features, but existing methods often treat these preferences equally or fail to specifically address this issue. (2) They do not effectively distinguish the similarity between different modality item features, overlook the unique characteristics of each type, and fail to fully exploit their complementarity. To solve these issues, we propose the user perception-guided graph convolutional network for multimodal recommendation (UPGCN). This model consists of two main parts: the user perception-guided representation enhancement module (UPEM) and the multimodal two-step enhanced fusion method, which are designed to capture user preferences for different modalities to enhance user representation. At the same time, by distinguishing the similarity between different modalities, the model filters out noise and fully leverages their complementarity to achieve more accurate item representations. We performed comprehensive experiments on the proposed model, and the results indicate that it outperforms other baseline models in recommendation performance, strongly demonstrating its effectiveness. Full article

An accurate assessment of the state of charge (SOC) of electric vehicle batteries is critical for implementing frequency regulation and peak shaving. This study proposes mechanism- and data-driven SOC fusion calculation methods. First, a second-order Thevenin battery model is developed to obtain the physical parameters of the battery. Second, data from the Thevenin battery model and data from four standard cycling conditions in the electric vehicle industry are added to the dataset of the feed-forward neural network data-driven model to construct the test and training sets of the data-driven model. Finally, the error of the mechanism and data-driven fusion modeling method is quantitatively analyzed by comparing the estimation error of the method for the battery SOC at different temperatures with the accuracy of the data-driven SOC estimation method. The simulation results show that the root mean square error, the mean age absolute error, and the maximum error of mechanism and data-driven method for the estimation error of battery SOC are lower than those of the data-driven method by 0.9%, 0.65%, and 1.3%, respectively. The results show that the mechanism and data-driven fusion SOC estimation method has better generalization performance and higher SOC estimation accuracy. Full article

Closely-related plant groups with distinct microbiomes, chemistries and ecological characteristics represent tractable models to explore mechanisms shaping species spread, competitive dynamics and community assembly at the interface of native and introduced ranges. We investigated phyllosphere microbial communities, volatile organic compound (VOC) compositions, and potential interactions among introduced S. trilobata, native S. calendulacea and their hybrid in South China. S. trilobata exhibited higher α diversity but significantly different community composition compared to the native and hybrid groups. However, S. calendulacea and the hybrid shared certain microbial taxa, suggesting potential gene flow or co-existence. The potent antimicrobial VOC profile of S. trilobata, including unique compounds like p-cymene (13.33%), likely contributes to its invasion success. The hybrid’s intermediate microbial and VOC profiles suggest possible consequences for species distribution, genetic exchange, and community assembly in heterogeneous environments. This hybrid deserves further study as both an opportunity for and threat to diversity maintenance. These differentiating yet connected plant groups provide insight into ecological and evolutionary dynamics shaping microbiome structure, species co-occurrence and competitive outcomes during biological exchange and habitat transformation. An interdisciplinary approach combining chemical and microbial ecology may reveal mechanisms underlying community stability and change, informing management of species spread in a globalized world. Full article

Body size may drive the molecular evolution of mitochondrial genes in response to changes in energy requirements across species of different sizes. In this study, we perform selection pressure analysis and phylogenetic independent contrasts (PIC) to investigate the association between molecular evolution of mitochondrial genome protein-coding genes (mtDNA PCGs) and body size in terrestrial Cetartiodactyla. Employing selection pressure analysis, we observe that the average non-synonymous/synonymous substitution rate ratio (ω) of mtDNA PCGs is significantly reduced in small-bodied species relative to their medium and large counterparts. PIC analysis further confirms that ω values are positively correlated with body size (R² = 0.162, p = 0.0016). Our results suggest that mtDNA PCGs of small-bodied species experience much stronger purifying selection as they need to maintain a heightened metabolic rate. On the other hand, larger-bodied species may face less stringent selective pressures on their mtDNA PCGs, potentially due to reduced relative energy expenditure per unit mass. Furthermore, we identify several genes that undergo positive selection, possibly linked to species adaptation to specific environments. Therefore, despite purifying selection being the predominant force in the evolution of mtDNA PCGs, positive selection can also occur during the process of adaptive evolution. Full article

Film cooling needs to be applied to serpentine nozzles due to an increase in thermal load. Adverse pressure gradients (APGs) near the upper wall of such nozzles hinder the forward flow of the coolant, and they may even induce a recirculation zone that complicates the cooling of the film in serpentine nozzles under different APGs. In this study, the film cooling characteristics of a serpentine nozzle under various APGs are investigated through numerical simulations. The studied pressure gradients include strong, moderate, and weak APGs. The results show that the APG weakened the adhesion of the coolant to the surface, thereby reducing the film cooling effectiveness (FCE) and the convective heat transfer coefficient (CHTC). The stronger the APG, the greater its obstructive effect. However, the recirculation zone induced by the strong APG was composed of the coolant, and it adhered tightly to the wall, thereby significantly strengthening the FCE and CHTC. The CHTC under the moderate APG significantly increased due to the convergence of two jets ejected from different holes. For the four blowing ratios, the area-averaged FCE under the strong APG was 29.8% and 24.5% higher than that under the moderate and weak APGs, while the area-averaged ratios of the CHTC under the moderate APG were 1.6% and 16.7% higher than those under the strong and weak APGs. Therefore, more holes should be arranged on the film in the zones of moderate and weak APGs. Full article

The polyphenol–Maillard reaction is considered one of the important pathways in the formation of humic-like substances (HLSs). Glucose serves as a microbial energy source that drives the humification process. However, the effects of changes in glucose, particularly its concentration, on abiotic pathways remain unclear. Given that the polyphenol–Maillard reaction requires high precursor concentrations and elevated temperatures (which are not present in soil), gibbsite was used as a catalyst to overcome energetic barriers. Catechol and glycine were introduced in fixed concentrations into a phosphate-buffered solution containing gibbsite using the liquid shake-flask incubation method, while the concentration of glucose was controlled in a sterile incubation system. The supernatant fluid and HLS components were dynamically extracted over a period of 360 h for analysis, thus revealing the influence of different glucose concentrations on abiotic humification pathways. The results showed the following: (1) The addition of glucose led to a higher degree of aromatic condensation in the supernatant fluid. In contrast, the supernatant fluid without glucose (Glu0) and the control group without any Maillard precursor (CK control group) exhibited lower degrees of aromatic condensation. Although the total organic C (TOC) content in the supernatant fluid decreased in all treatments during the incubation period, the addition of Maillard precursors effectively mitigated the decreasing trend of TOC content. (2) While the C content of humic-like acid (C_HLA) and the C_HLA/C_FLA ratio (the ratio of humic-like acid to fulvic-like acid) showed varying increases after incubation, the addition of Maillard precursors resulted in a more noticeable increase in C_HLA content and the C_HLA/C_FLA ratio compared to the CK control group. This indicated that more FLA was converted into HLA, which exhibited a higher degree of condensation and humification, thus improving the quality of HLS. The addition of glycine and catechol without glucose or with a glucose concentration of 0.06 mol/L was particularly beneficial in enhancing the degree of HLA humification. Furthermore, the presence of glycine and catechol, as well as higher concentrations of glucose, promoted the production of N-containing compounds in HLA. (3) The presence of Maillard precursors enhanced the stretching vibration of the hydroxyl group (–OH) of HLA. After the polyphenol–Maillard reaction of glycine and catechol with glucose concentrations of 0, 0.03, 0.06, 0.12, or 0.24 mol/L, the aromatic C structure in HLA products increased, while the carboxyl group decreased. The presence of Maillard precursors facilitated the accumulation of polysaccharides in HLA with higher glucose concentrations, ultimately promoting the formation of Al–O bonds. However, the quantities of phenolic groups and phenols in HLA decreased to varying extents. Full article

Cadmium (Cd) has been widely used in industry applications, leading to water and soil contamination. This study investigated the potential ability of Pseudomonas nitroreducens (11830) to perform the biosorption of cadmium from aqueous solution and soil. The biosorption characteristics were described using equilibrium isotherm and kinetic studies. The Langmuir adsorption isotherm indicated a better fit with the experimental data (R² = 0.980), with a maximum capacity of 160.51 mg/g at 30 °C in an initial aqueous solution of 300 mg/L Cd²⁺. The experiments followed a pseudo-second-order kinetics model (R² > 0.99), especially at a low initial concentration. The biosorption mechanisms involved were determined through scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive spectroscopy (EDS) and protein analysis. The SEM and TEM figures showed that the morphology of cells changed before and after the adsorption of Cd, and the EDS confirmed that Cd was absorbed on the surface of the cell. The analysis of proteins indicated that the protein species increased after the stimulation of Cd, which further confirmed the biosorption mechanism. A pot experiment confirmed that 11830 could passivate the cadmium in soil and reduce its uptake and utilization by Houttuynia cordata Thunb (H. cordata). This work demonstrates the potential application of microorganisms in inhibiting the accumulation of Cd in crops. Full article

Feature selection aims to select crucial features to improve classification accuracy in machine learning and data mining. In this paper, a new binary grasshopper optimization algorithm using time-varying Gaussian transfer functions (BGOA-TVG) is proposed for feature selection. Compared with the traditional S-shaped and V-shaped transfer functions, the proposed Gaussian time-varying transfer functions have the characteristics of a fast convergence speed and a strong global search capability to convert a continuous search space to a binary one. The BGOA-TVG is tested and compared to S-shaped and V-shaped binary grasshopper optimization algorithms and five state-of-the-art swarm intelligence algorithms for feature selection. The experimental results show that the BGOA-TVG has better performance in UCI, DEAP, and EPILEPSY datasets for feature selection. Full article