Search Results (24)

This study provides novel insight into herbaceous-layer dynamics across three distinct South African savanna bioregions (Central Bushveld, Lowveld, and Mopane) using a Total Count Quadrat approach to investigate species densities, community composition, diversity, and spatial patterns. A total of 196 unique herbaceous species were recorded across all bioregions. Contrary to typical expectations, our findings reveal no statistically significant differences in overall herbaceous density (ranging from 24.3 ± 2.31 to 32.0 ± 1.28 individuals/m²; F_2,6 = 1.89, p = 0.23), species richness (F_2,6 = 1.91, p = 0.23), or Shannon diversity (F_2,6 = 3.23, p = 0.11) among bioregions, suggesting a more complex interplay of environmental drivers beyond broad climatic gradients. However, there was significant within-bioregion spatial heterogeneity in density, notably in the Central Bushveld (F_2,87 = 4.96, p = 0.009) and Mopane (F_2,87 = 7.54, p < 0.001) regions, indicating important fine-scale variation, unlike in the Lowveld region (F_2,87 = 1.25, p = 0.292). Growth form analysis revealed that forbs consistently dominated species richness across all three bioregions (Central Bushveld: ~64%; Lowveld: ~70%; and Mopane: ~67%) and were also the dominant growth form by density in the Lowveld (54.3%) and Mopane (63.8%) regions. While numerical differences in grass density were observed, no statistically significant difference was found across bioregions (F_2,6 = 4.15, p = 0.07). Sedges consistently contributed a small proportion to both species richness and total density. Non-metric multidimensional scaling further revealed patterns of dispersion in herbaceous community compositions between the Lowveld and Mopane regions, with Central Bushveld communities exhibiting greater variability. These findings underscore the critical ecological importance of forbs in South African savannas, not only for biomass but also for driving herbaceous diversity and highlighting the necessity of considering fine-scale spatial variation in future ecological research and conservation strategies. Full article

The role of high-speed rail (HSR) in facilitating the spatial restructuring of regional and urban networks has long interested scholars and policymakers. This study explored HSR-facilitated city-network evolution in less-developed regions through the example of Jiangxi Province, China. Applying social network analysis methods, the study calculated indicators of network association strength, density, centrality, and cohesive subgroups using HSR passenger flow data from Jiangxi’s counties and cities for the years of 2009, 2014, 2019, and 2024. The quadratic assignment procedure (QAP) method was utilized to measure the factors that influence of HSR passenger flow network in Jiangxi Province. Research on the spatial network structure of HSR passenger flow and its influencing factors to promote the sustainable development of less-developed regions via HSR construction was explored. The main findings are as follows: Jiangxi’s city-network structure experienced a substantial increase from 2009 to 2024 in network properties, including the degree of association, network density, and the centrality of cities. The structure of the subgroups remained relatively stable, with a few exceptions. Cities in different subgroups form close and strong connections with each other resulting from HSR. HSR has effectively shortened the time and space distances and enhanced the spatial links between cities. Five factors, including population size, geographic distance, spatial proximity, economic development, and administrative hierarchy, demonstrated significant impacts on the HSR passenger flow network in Jiangxi Province. As HSR services continue to expand throughout the less-developed regions, optimizing HSR’s network effects should focus on strengthening the driving role of central HSR cities, promoting cross-regional coordination, and integrating HSR fully with other transportation modes. Full article

In 2021, Ejsmont and Biernacki showed that the free tangent distribution can be used to measure household satisfaction with durable consumer goods. This distribution arises as the limit of free random variables. This, new article serves as the theoretical introduction to the continuation of the research presented in the paper from 2021. We continue the study of the limit of specific quadratic forms in free probability, which is the first step towards constructing a new distribution for the evaluation of satisfaction with material affluence among household. We formulate a non-central limit theorem for weighted sums of commutators and square of the sums for free random variable. In addition we give the random matrix models for these limits. Full article

Although the effects of invasive alien plants on natural ecosystems are well known, the effects of specific plant species can vary across habitat types and disturbance intensity. This study was carried out to analyze the effects of Lantana camara on associated vegetation and soil physico-chemical properties at invaded and non-invaded sites across three different habitat types (forest edge, fallow land, and roadside) in central Nepal. We sampled 50 pairs of 5 m × 5 m (for shrub species) and 1 m × 1 m (for herbs species) plots at invaded and non-invaded sites in each habitat and recorded community variables for each species within the sampling plots for both wet (monsoon) and dry (pre-monsoon) seasons. Further, we collected soil samples from each quadrat and determined the soil physico-chemical properties. We recorded 137 species of flowering plants (119 from non-invaded and 97 from invaded plots) and classified them in accordance with life form/habit. In invaded sites, we found a significant decline in species diversity as indicated by the Simpson and Shannon diversity indices. Specifically, L. camara reduced the species richness, Simpson index, and Shannon diversity index by 36.84%, 11.84%, and 40.21%, respectively. Soil nutrients such as total nitrogen, soil organic carbon, and available phosphorus were significantly higher in invaded sites than non-invaded ones except for available potassium and soil pH. This study provided evidence that Lantana L. camara has a substantial impact on the understory plant community assemblage and the physico-chemical properties of soil. The results suggest that the protection of native plant community requires management of L. camara by implementing appropriate measures. Full article

Antibiotic contamination of water sources is a significant environmental and public health concern. This contamination is classified among the most dangerous types of pollution currently because of their harmful effects. Therefore, it is essential to identify effective and environmentally friendly ways to deal with those dangerous compounds. Within this context, this work looked into whether soils made from volcanic ash could be used as cost-effective adsorbents to remove the antibiotic trimethoprim (TRM) from aqueous solutions. To examine the impacts of the main operating parameters on TRM removal, which are the initial antibiotic concentration (C), contact time (t), stirring speed (S), and solid-to-liquid ratio (R), a Central Composite Design (CCD) based on the Response Surface Methodology (RSM) was employed. Full quadratic polynomial models were used to correlate the experimental data, allowing for the estimation of each factor’s influence. With a predicted removal efficiency of 77.59%, the removal process optimization yielded the following set of optimal conditions: C = 4.5 mg/L, t = 45.5 min, S = 747 rpm, and R = 0.04 g/mL. Experiments conducted under predicted ideal conditions supported both the result and the previously developed model’s capacity for prediction. Additionally, the adsorption mechanism was also proposed based on the characterization of the adsorbent before and after the treatment. The study’s findings provide the possibility of using soils formed from volcanic ash as a cost-effective adsorbent material for the removal of TRM and likely other similar pollutants from contaminated waters. Full article

Attitude control of a satellite with three flexible elements is considered. Control torque is developed by a set of reaction wheels, which are installed on the central hub of the satellite. The flexible elements are large, so the control torque constraints must be taken into account. In the paper, a control algorithm based on a linear-quadratic regulator is studied. The asymptotic stability of this control is shown. The choice of the control parameters is based on the closed form solution of the corresponding algebraic Riccati equation, which is supplemented by the linear matrix inequality. To increase the convergence rate, particle swarm optimization is used to tune the control parameters. Full article

We study a graph-based generalization of the Galam opinion formation model. Consider a simple connected graph which represents a social network. Each node in the graph is colored either blue or white, which indicates a positive or negative opinion on a new product or a topic. In each discrete-time round, all nodes are assigned randomly to groups of different sizes, where the node(s) in each group form a clique in the underlying graph. All the nodes simultaneously update their color to the majority color in their group. If there is a tie, each node in the group chooses one of the two colors uniformly at random. Investigating the convergence time of the model, our experiments show that the convergence time is a logarithm function of the number of nodes for a complete graph and a quadratic function for a cycle graph. We also study the various strategies for selecting a set of seed nodes to maximize the final cascade of one of the two colors, motivated by viral marketing. We consider the algorithms where the seed nodes are selected based on the graph structure (nodes’ centrality measures such as degree, betweenness, and closeness) and the individual’s characteristics (activeness and stubbornness). We provide a comparison of such strategies by conducting experiments on different real-world and synthetic networks. Full article

In cognitive radio (CR), cooperative spectrum sensing (CSS) employs a fusion of multiple decisions from various secondary user (SU) nodes at a central fusion center (FC) to detect spectral holes not utilized by the primary user (PU). The energy detector (ED) is a well-established technique of spectrum sensing (SS). However, a major challenge in designing an energy detector-based SS is the requirement of correct knowledge for the distribution of decision statistics. Usually, the Gaussian assumption is employed for the received statistics, which is not true in real practice, particularly with a limited number of samples. Another big challenge in the CSS task is choosing an optimal fusion strategy. To tackle these issues, we have proposed a beamforming-assisted ED with a heuristic-optimized CSS technique that utilizes a more accurate distribution of decision statistics by employing the characterization of the indefinite quadratic form (IQF). Two heuristic algorithms, genetic algorithm with multi-parent crossover (GA-MPC) and constriction factor particle swarm-based optimization (CF-PSO), are developed to design optimum beamforming and optimum fusion weights that can maximize the global probability of detection $p_d$ while constraining the global probability of false alarm $p_f$ to below a required level. The simulation results are presented to validate the theoretical findings and to asses the performance of the proposed algorithm. Full article

In recent years, manufacturing development has received renewed attention from developing and developed countries alike. As mega-city regions (MCRs) are where manufacturing industries converge, the research on urban networks of MCRs under the dominance of manufacturing transaction linkages is currently insufficient. Based on the buyer–supplier linkages of listed manufacturing firms, this paper investigated the characteristics of the urban network in the Yangtze River Delta region (YRDR) in China using the social network analysis method; explored the determinants of nodal centrality and city dyads of the urban network by the stepwise regression and quadratic assignment procedures, respectively; and proposes a “characteristics-determinants-strategies” technical framework for the analysis and optimization of interurban collaboration in manufacturing transactions within MCRs. The findings were as follows: (1) The characteristics of the urban manufacturing transaction networks differed from those of transaction linkages of advanced producer services (APS) firms, intra-firm organization hierarchies, and innovation cooperation networks; (2) the network and geographical “core-periphery” structure of urban power and the circulation corridor of the urban manufacturing transaction network was formed within the YRDR; (3) cooperation parks, innovation collaboration, high-speed rail (HSR) linkage, and geographical proximity between cities were found to facilitate the formation of urban manufacturing transaction networks, and the similarity of industry structures and driving distance between cities inhibits the network; (4) the number of urban industrial firms, GDP per capita, and city government spending on science and technology contributed to the centrality of a city in urban manufacturing transaction networks, while the urban population in a city had a negative impact. The research provides a complementary perspective to the urban network research of MCRs under the perspective of production factors and product circulation and provides policy and urban planning insights for the synergistic development of interurban manufacturing in MCRs. Full article

Using a Central Composite Design, the extraction of bioactive compounds from red grape Băbească neagră peels was optimized by applying a conventional solvent extraction. On the anthocyanin content, total phenolic content, and antioxidant activity (using the DPPH method), the effects of extraction factors, including ethanol and citric acid concentrations, extraction temperature, and duration, were investigated. For each of the investigated parameters, a quadratic model was suggested. The maximum and minimum variables investigated in the coded form of the experimental plan are the concentrations of citric acid (0.10–2.64%), ethanol (38.06–96.93%), operating temperature (13.06–71.90 °C), and extraction time (11.36–78.63 min). The optimal mixture for recovering the most significant amount of polyphenol content and antioxidant activity was 85% ethanol, 0.85% citric acid, 52.14 min, and 57 °C. Based on the experimental approach, the anthocyanin content ranged from 1.71 to 2.74 mg C3G/g DW, the total phenolic content ranged from 24.67 to 43.97 mg/g, and the antioxidant activity ranged from 15.95 to 20.98 mM TE/g DW. Overall, it should be stressed that establishing operating factors to maximize model responses can improve the extraction process and the obtaining of red grape peel value-added extracts for creating functional food products. Full article

Brick is a common building material that is used in society for constructing buildings. A viable environmental strategy to lessen the amount of plastic waste involves the inclusion of plastic trash in building materials. Globally, there is a severe issue with the disposal of plastic garbage in landfills. The primary and secondary carbon bonds that are formed in plastic packaging wastes can severely contaminate the environment. Hence, managing plastic waste to generate new and useful items is essential. One of the most practical ways to safeguard the environment is to manufacture eco-bricks from PET waste and epoxy resin. Additionally, as there is no combustion involved in the production of this eco-brick; it does not harm the environment. Eco-brick can be defined as a novel concept and approach to waste management and recycling. Eco-bricks have many advantages, such as easy availability and being environmentally friendly. This study aimed to improve the composition of the eco-brick using a mixture of epoxy resin and PET particles. In this study, a mathematical modelling technique called the Response Surface Method (RSM) was designed using the Central Composite Design (CCD). Variable input factors were used to develop eco-bricks such as mixture ratio (10–90%), particle size (1–5 mm), and drying time (1–7 days), whereas the variable response included the compressive strength. The complete experimental design was developed using Design Expert 11 software, and simulation experiments with 17 sets of parameters were generated. The microstructural characteristics of the eco-brick were examined using SEM. The results of the experiments indicated that the most optimised parameters that could be used for eco-brick application were: a PET particle size of 1.1 mm, a mixing ratio of 89.9%, and a curing time of 6.9 days. Earlier research that was conducted regarding the production of eco-bricks using a PET particle and epoxy resin mixture showed that these materials had a high potential to boost compressive strength. The quadratic model was used as the basis for the regression analysis for generating the response equations. Since the difference between the experimental and anticipated values was less than 5%, it was concluded that the results of the experimental and predictive tests showed good agreement. The model used in this study yielded noteworthy outcomes. As a result, the suggested statistical model can offer a clear understanding of designing experiments and variables that affect the production of eco-brick using a blend of PET particles and epoxy resin. Full article

This study aimed to extract bioactives from red onion skins for use as edible colorants that are both natural and functional. The extraction of bioactive chemicals from red onion skins using a conventional solvent extraction was optimized using a Central Composite Design (CCD). The influence of extraction parameters, such as ethanol and citric acid concentrations, extraction temperature, and time, on anthocyanin content and antioxidant activity (DPPH method) was studied. A quadratic model was suggested for all of the parameters examined and employed. Citric acid concentration (0.05–2.64%), ethanol concentration (6.36–73.63%), operation temperature (16.47–58.52 °C), and extraction duration (10–234.54 min) were the variables studied in the coded form of the experimental plan. The best conditions for maximum anthocyanins and antioxidant activity recovery were: 60% ethanol, 0.87% citric acid, 179.99 min, and 25 °C. The anthocyanins concentration varied from 0.45 to 1.43 mg C3G/g DW, while the antioxidant activity varied from 24.29 to 37.20 mM TE/g DW, according to the experimental design. Overall, it should be emphasized that the extraction process can be enhanced by settling the operating factors to maximize the model responses. The current findings demonstrate that extracts from red onion skins would be useful in developing functional food products. Full article

For a univariate distribution, its M-quantiles are obtained as solutions to asymmetric minimization problems dealing with the distance of a random variable to a fixed point. The asymmetry refers to the different weights awarded to the values of the random variable at either side of the fixed point. We focus on M-quantiles whose associated losses are given in terms of a power. In this setting, the classical quantiles are obtained for the first power, while the expectiles correspond to quadratic losses. The M-quantiles considered here are computed over distorted distributions, which allows to tune the weight awarded to the more central or peripheral parts of the distribution. These distorted M-quantiles are used in the multivariate setting to introduce novel families of central regions and their associated depth functions, which are further extended to the multiple output regression setting in the form of conditional and regression regions and conditional depths. Full article

Graph neural networks (GNNs) have developed rapidly in recent years because they can work over non-Euclidean data and possess promising prediction power in many real-word applications. The graph classification problem is one of the central problems in graph neural networks, and aims to predict the label of a graph with the help of training graph neural networks over graph-structural datasets. The graph pooling scheme is an important part of graph neural networks for the graph classification objective. Previous works typically focus on using the graph pooling scheme in a linear manner. In this paper, we propose the real quadratic-form-based graph pooling framework for graph neural networks in graph classification. The quadratic form can capture a pairwise relationship, which brings a stronger expressive power than existing linear forms. Experiments on benchmarks verify the effectiveness of the proposed graph pooling scheme based on the quadratic form in graph classification tasks. Full article

(1) Background: This study is designed to extract the bioactive compounds from beetroot peel for future use in the food industry. (2) Methods: Spectrophotometry techniques analyzed the effect of conventional solvent extraction on betalains and polyphenolic compounds from beetroot peels. Several treatments by varying for factors (ethanol and citric acid concentration, temperature, and time) were applied to the beetroot peel samples. A Central Composite Design (CCD) has been used to investigate the effect of the extraction parameters on the extraction steps and optimize the betalains and total polyphenols extraction from beetroot. A quadratic model was suggested for all the parameters analyzed and used. (3) Results: The maximum and minimum variables investigated in the experimental plan in the coded form are citric acid concentration (0.10–1.5%), ethanol concentration (10–50%), operating temperature (20–60 °C), and extraction time (15–50 min). The experimental design revealed variation in betalain content ranging from 0.29 to 1.44 mg/g DW, and the yield of polyphenolic varied from 1.64 to 2.74 mg/g DW. The optimized conditions for the maximum recovery of betalains and phenols were citric acid concentration 1.5%, ethanol concentration 50%, temperature 52.52 °C, and extraction time 49.9 min. (4) Conclusions: Overall, it can be noted that the extraction process can be improved by adjusting operating variables in order to maximize the model responses. Full article