Search Results (95)

Arabinoxylan is a polysaccharide with film-forming properties, present in corn fiber, and a low-value by-product. The extract has a deep brown color, producing films of the same shade, which may not be appealing. This study addresses, for the first time, the adsorption of colored compounds present in an arabinoxylan extract using resin MN102. The resin successfully adsorbed the colored compounds from the arabinoxylan extract. After four consecutive adsorption/desorption cycles, the efficiency of the resin was similar, only decreasing from 63.3% to 52.9%. Langmuir and Freundlich models were fitted to the results of adsorption isotherm experiments, with the Freundlich model demonstrating the best fit to the experimental results. A fixed-bed column loaded with the resin was used for the removal of the colored compounds from the arabinoxylan extract, and the effect of the volumetric flow rate was investigated. The Yan and log-Gompertz models showed the best fit to the experimental breakthrough curves. This study systematically evaluated the adsorption conditions, providing a comprehensive analysis of the performance of the resin in the removal of the colored compounds. Additionally, the ability of the extract to maintain its film-forming properties after decolorization was evaluated, and some of the film’s key characteristics were evaluated, namely its color, solubility in water and mechanical properties. Full article

Allergy is recognized as a public health problem with pandemic consequences and is estimated to affect more than 50% of Europeans in 2025. Prebiotic and probiotic food implementation has recently emerged as an alternative strategy to promote immunomodulatory beneficial effects in allergic patients. Among prebiotics, Phaeophyceae algae represent a niche of research with enormous possibilities. The present study aims to evaluate the in vitro prebiotic potential of fucoidan from Fucus vesiculosus, Macrocystis pyrifera, and Undaria pinnatifida algae, to promote the growth of Limosilactobacillus reuteri and Lacticaseibacillus rhamnosus GG as probiotic bacteria added to the formulation of a novel yogurt. Concentrations of fucoidan of 100 and 2000 µg/mL were added to reference growth media and kinetic growth curves for both microorganisms were fitted to the Gompertz equation. Optimized prebiotic conditions for fucoidan were selected to validate in vitro results by means of the formulation of a novel fermented prebiotic yogurt. Conventional yogurts (including Streptococcus thermophilus and Lactobacillus delbrueckii subs. bulgaricus) were formulated with the different fucoidans, and production batches were prepared for L. rhamnosus and L. reuteri. Increased L. reuteri and L. rhamnosus populations in 1.7–2.2 log₁₀ cycles just after 48 h of in vitro exposure were detected in fucoidan supplemented yogurt. M. pyrifera and U. pinnatifida fucoidans were the most effective ones (500 µg/mL) promoting probiotic growth in new formulated yogurts (during the complete shelf life of products, 28 days). Diet supplementation with fucoidan can be proposed as a strategy to modulate beneficial microbiota against allergy. Full article

This study addresses the growing concern of water contamination by pharmaceutical residues, focusing on the simultaneous removal of paracetamol (PAR) and metronidazole (MTZ). Batch and fixed-bed column adsorption processes were evaluated using activated carbon. In the batch experiments, the effects of pH (3, 7, and 11), adsorbent mass (0.5, 1.25, and 2 g), and contact time (10, 30, and 60 min) were evaluated, while the fixed-bed column was optimized considering initial pollutants concentration (30, 40, and 50 mg/L), adsorbent mass (0.5, 0.75, and 1 g), and flow rate (5, 10, and 15 mL/min) to improve the maximum adsorption capacity of the bed for both pollutants (q_maxPAR and q_maxMTZ). Parameter estimation and model selection were performed using a Bayesian Monte Carlo approach. Optimal conditions in the batch system (pH = 7, W = 2 g, and time = 60 min) led to high removal efficiencies for both compounds (≥98%), while in the column system, the initial pollutant concentration was the most significant parameter to improve the maximum adsorption capacity of the bed, resulting in values equal to 49.5 and 43.6 mg/g for PAR and MTZ, respectively. The multicomponent Gompertz model showed the best performance for representing the breakthrough curves and is suitable for scale-up (R² ≥ 0.75). These findings highlight the complexity of multicomponent adsorption and provide insights, contributing to the development of more efficient and sustainable water treatment technologies for pharmaceutical residues. Full article

This study was conducted on New Zealand White male and female rabbits over a period of 133 days to ascertain their potential growth rates, body composition for major body parts, and chemical makeup. A total of 220 New Zealand White rabbits, evenly distributed between males and females, were used for this study. One hundred rabbits for potential growth were weighed from day 14 to day 140, while twelve rabbits, six males and six females, were randomly selected at days 14, 21, 28, 35, 42, 56, 70, 84, 112, and 140 for carcass analysis. Although the rate of maturation was faster in females than in males, the Gompertz equation fitted separately to the growth data for males and females indicated that the body weights were similar throughout the trial (0.0243 vs. 0.0239), but males had a higher mature weight (315 g) than the females (309 g). Mature body protein weights averaged 1497 g in males and 843 g in females, and mature body lipid contents averaged 252 and 227 g, respectively. The rate of maturation per day of pelt-free body protein of males and females was 0.0103 and 0.0172, while that of body lipids was 0.0410 and 0.0471, respectively. Separate equations were required for males and females to describe the allometric relationship between protein and lipids in the pelt-free body. The rate of maturation of pelts in females was higher than in males (0.0249 vs. 0.0214/d), and the mature weight was lower (456 vs. 523 g, respectively). Full article

In groundwater quality analysis, nonlinear models are typically used, with domains spanning the entire real number line. In this study, alongside these models (Logistic, Gompertz and Richards), nonlinear models defined based on functions whose domain is only the positive part of the real number line are presented (Michaelis–Menten, Hill 1 and 2 and Rosin–Rammler 1 and 2). Two case studies were observed in the paper: (i) the dependence of nitrate concentration on the pumping rate in the Bartolovec wellfield, and (ii) the dependence of nitrate concentration on the distance from the source of pollution in the Varaždin wellfield. Both wellfields are located in the alluvial aquifer in northwestern Croatia. In this way, the curves obtained on the basis of the mentioned mathematical functions were fitted to the experimental data. The results show a good fit, so that the values of the coefficients of determination R² are greater than 0.82 for the case study (i) and greater than 0.96 for the case study (ii). Since the models differ in the number of parameters (e.g., three parameters for Michaelis–Menten and five parameters for Rosin–Rammler), the corrected Akaike information criterion (AIC_c) was used for their comparison. In this way, the best fit for the case study (i) was obtained for the Rosin–Rammler 1 model, while for the case study (ii), it was for the Hill 1 model. A t-test was performed for all models, and they can be considered reliable at a significance level of 0.05. However, t-values and p-values were also calculated for each parameter of each model. Based on these results, it is concluded that all model parameters can be considered reliable at a significance level of 0.05 only for the Hill 1 and Rosin–Rammler 1 models in both case studies. For this reason, these models can generally be considered the best fit to the experimental data. The study demonstrates the superiority of nonlinear models with domains restricted to positive real numbers (e.g., Hill 1, Rosin–Rammler 1) over traditional models (e.g., Logistic, Richards) in groundwater quality analysis. These findings offer practical tools for predicting contaminant extremes (e.g., maximum/minimum concentrations) and optimizing groundwater management strategies. Full article

This paper explores the application of a mathematical trend model to analyze product sales performance. A logistic trend model was utilized to analyze product sales performance, employing monthly sales data collected over three years. The model assessed impacts across various phases of the product life cycle. Significant sales trends were identified and modeled from historical data, demonstrating how sales dynamics mirror broader economic phenomena and consumer behaviors. In addition to logistic trends, linear and quadratic trends were also evaluated. To assess the significance of the sales trends for three products, the Mann–Kendall test was applied. The results indicate a statistically significant positive trend in the sales of product A. For evaluating the quality of data fit in model comparison, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were deemed appropriate. The analysis revealed that the logistic model effectively delineates different sales phases—from introduction to maturity—and highlights opportunities for optimizing strategic sales planning and customer satisfaction in alignment with market demands. The study’s findings are crucial for businesses seeking to enhance product lifecycle management and boost sales forecasting precision. Full article

Maritime transportation is responsible for most global trade and is generally considered more environmentally efficient compared to other modes of transport, particularly for long-distance trade. With increasingly stringent emission regulations, however, accurately quantifying emissions and identifying their key determinants has become essential for effective environmental management. This study introduced a structured and comparative statistical modeling framework for ship-based emission modeling using gross tonnage (GT) as the primary predictor variable, due to its strong correlation with emission levels. Emissions for hydrocarbon (HC), carbon monoxide (CO), particulate matter with an aerodynamic diameter of less than 10 μm (PM10), carbon dioxide (CO₂), sulfur dioxide (SO₂), nitrogen oxides (NO_x), and volatile organic compounds (VOC) were estimated using a bottom-up approach based on emission factors and formulas defined by the U.S. Environmental Protection Agency (EPA), using data from 38,304 vessel movements through the Bosphorus in 2021. These EPA-estimated values served as dependent variables in the modeling process. The modeling framework followed a three-step strategy: (1) outlier detection using Rosner’s test to reduce the influence of outliers on model accuracy, (2) curve fitting with 12 regression models representing four curve types—polynomial (e.g., linear, quadratic), concave/convex (e.g., exponential, logarithmic), sigmoidal (e.g., logistic, Gompertz, Weibull), and spline-based (e.g., cubic spline, natural spline)—to capture diverse functional relationships between GT and emissions, and (3) model comparison using difference performance metrics to ensure a comprehensive assessment of predictive accuracy, consistency, and bias. The findings revealed that nonlinear models outperformed polynomial models, with spline-based models—particularly natural spline and cubic spline—providing superior accuracy for HC, PM₁₀, SO₂, and VOC, and the Weibull model showing strong predictive performance for CO and NO_x. These results underscore the necessity of using pollutant-specific and flexible modeling strategies to capture the intricacies of maritime emission dynamics. By demonstrating the advantages of flexible functional forms over standard regression techniques, this study highlights the need for tailored modeling strategies to better capture the complex relationships in maritime emission data and offers a scalable and transferable framework that can be extended to other vessel types, emission datasets, or maritime regions. Full article

The large-scale use of air-conditioning equipment, while providing a comfortable living environment, has also brought about a series of problems. This study focuses on the growth and reproduction of Staphylococcus aureus on the surface of activated carbon in air-conditioning filtration systems. Experimental data were obtained under temperature conditions of 20 °C and 30 °C and relative humidity conditions of 10%, 50%, and 75% RH. Based on the experimental data, a mathematical model was established to predict the growth and reproduction of Staphylococcus aureus. The Logistic and Gompertz equations were used to fit the growth and reproduction curves under different temperature and humidity conditions, and the two models, commonly used for simulating microbial growth curves, were compared. The model with the best fit was selected to predict the amount of Staphylococcus aureus, providing some guidance for the actual lifespan of the adsorbent in filters. Full article

The vehicle fleets in Latin America are increasingly incorporating hybrid electric vehicles due to the economic and non-economic incentives provided by governments aiming to reduce energy consumption and emissions in the transportation sector. However, the impacts of implementing hybrid vehicles remain uncertain, especially in Latin American, which poses a risk to the achievement of environmental objectives in developing countries. The aim of this study is to evaluate the benefits of incorporating hybrid vehicles to replace internal combustion vehicles, considering the improvement in the level of emission standards. This study uses data reported by Colombian vehicle importers during the homologation process in Colombia and the number of vehicles registered in the country between 2010 and 2022. The Gompertz model and logistic growth curves are used to project the total number of vehicles, taking into account the level of hybridization and including conventional natural gas and electric vehicles. In this way, tailpipe emissions and energy efficiency up to 2040 are also projected for different hybrid vehicle penetration scenarios. Results show that the scenario in which the share of hybrid vehicles remains stable (Scenario 1) shows a slight increase in energy consumption compared to the baseline scenario, about 1.72% in 2035 and 2.87% in 2040. The scenario where the share of MHEVs, HEVs, and PHEVs reaches approximately 50% of the vehicle fleet in 2040 (Scenario 2) shows a reduction in energy consumption of 24.64% in 2035 and 33.81% in 2040. Finally, the scenario that accelerates the growth of HEVs and PHEVs while keeping MHEVs at the same level of participation from 2025 (Scenario 3) does not differ from Scenario 2. Results show that the introduction of full hybrids and plug-in hybrid vehicles improve fleet fuel consumption and emissions. Additionally, when the adoption rates of these technologies are relatively low, the benefits may be questionable, but when the market share of hybrid vehicles is high, energy consumption and emissions are significantly reduced. Nevertheless, this study also shows that Mild Hybrid Electric Vehicles (MHEVs) do not provide a significant improvement in terms of fuel consumption and emissions. Full article

Biopreservation technology has emerged as a promising approach to enhance food safety and extend shelf life by leveraging the antimicrobial properties of beneficial microorganisms. This study aims to develop precise predictive models to characterize the growth and interaction dynamics of lactic acid bacteria (LAB) and Listeria monocytogenes, which serve as bioprotective agents in food systems. Using both traditional and machine learning modelling approaches, we analyzed data from previously published growth curves in broth (BHI) and milk under isothermal conditions (4, 10, and 30 °C). The models evaluated mono-culture conditions for L. monocytogenes and LAB, as well as their competitive interactions in co-culture scenarios. The modified Gompertz model demonstrated the best performance for mono-culture simulations, while a combination of the modified Gompertz and Lotka–Volterra models effectively described co-culture interactions, achieving high adjusted R-squared values (adjusted R² = 0.978 and 0.962) and low root mean square errors (RMSE = 0.324 and 0.507) for BHI and milk, respectively. Machine learning approaches further validated these findings, with improved statistical indices (adjusted R² = 0.988 and 0.966, RMSE = 0.242 and 0.475 for BHI and milk, respectively), suggesting their potential as robust alternatives to traditional methods. The integration of machine learning-assisted software developed in this work into predictive microbiology demonstrates significant advancements by bypassing the conventional primary and secondary modelling steps, enabling a streamlined, precise characterization of microbial interactions in food products. Full article

Animal experiments have long been used as an educational tool in pharmacological education; however, from the perspective of animal welfare, it is necessary to decrease the number of animals used. ingAlthough using of simulators is effective, the development of these simulators is necessary when there is no existing simulator for animal experiments. In this review, we describe free, downloadable, and commercial simulators that are currently used in pharmacological education. Furthermore, we introduce two strategies to create simulators of animal experiments: (1) bioassay, and (2) experiments that measure the reaction time. We also describe five sigmoid curves (logistic curve, cumulative distribution function [CDF] of normal distribution, Gompertz curve, von Bertalanffy curve, and CDF of Weibull curve) to fit the results and their inverse functions. Using this strategy, it is possible to create a simulator that calculates the reaction time following drug administration. Moreover, we introduce a statistical model for local anesthetic agents using hierarchical Bayesian modeling. Considering the correlation among estimated parameters, we suggest it is possible to create simulators that give results more similar to those of animal experiments. The pharmacological education will be possible by these simulators at educational institutions where animal experiments are difficult due to various restrictions. It is expected that the number of simulator-based education programs will increase in the future. Full article

Shared kitchens have a lower entry barrier than traditional kitchens, which generally require a significant initial investment, and have thus attracted attention as the most realistic new business model for restaurants in the sharing economy. The restaurant industry is founded on ensuring the safety of the food it serves in order to prevent the spread of foodborne diseases within the community, so strict quality control is essential. Existing food quality management typically employs continuous quality assistance, which is difficult to apply to the highly volatile shared kitchen environment and its various stakeholders. Therefore, in this study, a predictive model for managing food quality that can monitor volatility using quantitative indicators, especially microbial counts, is proposed. Stakeholder- and quality-related factors associated with shared kitchens are first defined, then a modified Gompertz growth curve and the transfer rate equation are used to quantify them. The proposed model, utilizing E. coli as a practical indicator for easily measuring changes in general environments, can be used to systematically manage food quality within the shared kitchen industry, thus supporting the establishment of this new business model. Full article

The palm Euterpe precatoria holds great social, cultural, and environmental importance. The heart of palm and the fruit are the main products used for industrialization due to their energetic properties. Thus, the aim of this study was to establish a suspension cultivation protocol for the species using different explant sources. For this, eight lineages of E. precatoria embryogenic calluses were tested, with five in liquid medium Murashige and Skoog (MS) with 5 μM Picloram and three for comparison in semisolid medium MS with 20 μM Picloram and 5 μM 2iP. The growth curve was obtained by weighing the calli from 60 to 180 days of cultivation. The Gompertz model was applied, and growth kinetics were evaluated. At 100 days, the contents of total soluble sugars (TSSs) and total soluble proteins (TSPs) were determined. Principal components (PCA) were measured. According to the analysis of the data, the cultivation of E. precatoria lineages in liquid medium was successfully carried out, and the establishment was achieved. The model can be considered adequate since the R² values found describe more than 90% of the growth kinetics of the lineages. In the liquid system, lineages L1 (from leaf explants and multiplied in semisolid medium—SM), L2 (from leaf explants and multiplied in SM), and L6 (from zygotic embryo explants and multiplied in liquid medium—LM) showed the shortest time to double the biomass accumulation. Multivariate analysis reveals a significant increase in masses in liquid cultures, represented by lineages L6 and L2. There was statistical difference in the amount of TSSs extracted; the highest TSS levels were observed in lineages cultivated in LM. The protein content found was very low, showing statistical differences among the lineages. In this work, the establishment and multiplication of embryogenic calli of E. precatoria are described for the first time, and they emerge as viable alternatives for the vegetative propagation of the species. Full article

Appropriate growth curves can reflect more sophisticated growth patterns of animals than body weight, and thus, the identification of genes and variants related to the growth curve parameter traits contributes to revealing the fine growth and development characteristics of livestock. However, the ability of single genome-wide association analysis (GWAS) and transcriptome analyses to identify valuable genes and variants is limited. In this study, based on genome and transcriptome data, the growth curve parameter traits of hybrid pigs were analyzed, and a set of genes and variants were identified. The Gompertz–Laird growth curve model was optimized to reveal the growth pattern of F₂ individuals of Duroc × Erhualian pigs over four time points. Five growth parameters were estimated, including initial body weight ${(W}_0)$, instantaneous growth rate per day (L), coefficient of relative growth or maturing index (k), body weight at inflection point ${(W}_i)$, and average growth rate (GR). These five parameters were subjected to a genome-wide association study, differential gene expression analysis, and weighted gene co-expression network analysis (WGCNA). In the study, 336 pigs were genotyped, and 39,494 SNP markers were used for each pig in the analysis. Thirty of these pigs were also included in the transcriptomics analysis. Based on genome and transcriptome data, the integrated analyses identified five putative SNPs (including INRA0056566 on chromosome X, DRGA0004151 on chromosome 3, INRA0056460 on chromosome X, H3GA0049324 on chromosome 17, and H3GA0037747 on chromosome 13) and 15 candidate genes (PDGFA, VEGFD, CSPP1, EFHC1, PIK3C3, ZZZ3, GCC2, MAPK14, ZPR1, ISG15, ANG, CEBPD, ZHX3, CTBP2, and MYNN). The functional analysis indicated that these candidate genes played important roles in cell division and differentiation, development and aging, and skeletal muscle and fat formation. Our results provide insight into the genetic mechanisms underlying the growth and development of hybrid pigs and offer a theoretical basis for genomic breeding. Full article

Osmotically dehydrated cherry tomatoes and spinach leaves were incorporated into Greek salad-type (including OD-treated and air-dried feta cheese trimmings and air-dried olive rings) and green salad-type (including OD-treated and air-dried feta cheese trimmings and roasted ground peanuts) ready-to-eat (RTE) product prototypes, respectively. The osmotic dehydration of cherry tomatoes and spinach leaves was conducted in a pilot scale setting (100 L) in a 60% glycerol-based solution at 35 °C and 25 °C for 180 min and 60 min, respectively. To quantify the moisture transfer between the three ingredients of different moisture content (and water activity), the moisture equilibrium curves for each ingredient of the RTE product were determined. The equilibrium water activity of RTE products was 0.86 and 0.76, respectively. The quality of the RTE products (more specifically, tomato and spinach color and texture, instrumentally measured and sensorially perceived, sensory characteristics) was evaluated. The shelf life of the prototypes (from 4 °C to 20 °C) was kinetically modeled based on sensory deterioration and microbial growth, using the zero-order kinetic model and the Gompertz model, respectively. In the case of the tomato-based product, a shelf life of 54 days (based on sensory deterioration) was achieved at 4 °C, a shelf-life extension of 40 days compared to untreated, fresh-cut tomato. The shelf life of the spinach-based product (based on sensory deterioration) was 36 days at 4 °C, 30 days longer when compared to untreated spinach. Our results indicate that osmotic dehydration was successful in significantly extending the shelf life of such products, contributing to the increased temperature resilience of their keeping quality and allowing for their distribution and storage in a variable cold chain. Full article