Optimizing sheep growth curves using a meta-heuristic algorithm.

Sheep were among the first animals domesticated by humans, and to this day, small ruminants are primarily raised for their meat, milk, and wool. This study evaluated the goodness of fit for growth curve models using observed age and weight data from crossbred lambs of various breeds based on the mean values between paired breeds. We employed a hybrid metaheuristic algorithm, combining a simulated annealing (SA) algorithm and a genetic algorithm (GA) called SAGAC, to determine the optimal parameter values for growth models, ensuring the best alignment between simulated and observed curves. The goodness of fit and model accuracy was assessed using the coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). Errors were measured by comparing the criteria differences between simulated and observed data. Thirty crossbreed combinations were simulated, considering the average weight. Analysis of the observed and simulated growth curves indicated that specific crossbreeding scenarios produced promising results. This simulation approach is believed to assist geneticists in predicting potential crossbreeding outcomes, thereby saving time and financial resources in field research.

Optimized irrigation and fertilization can mitigate negative CO2 impacts on seed yield and vigor of hybrid maize.

Seed yield and vigor of hybrid maize determine the planting, yield, and quality of maize, and consequently affect food, nutrition, and livelihood security; however, the response of seed yield and vigor to climate change is still unclear. We established an optimization-simulation framework consisting of a water­nitrogen crop production function, a seed vigor and a gridded process-based model to optimize irrigation and nitrogen fertilization management, and used it to evaluate seed yield and vigor in major seed production locations of China, the USA, and Mexico. This framework could reflect the influence of water and nitrogen inputs at different stages on seed yield and vigor considering the spatio-temporal variability of climate and soil properties. Projected seed yield and vigor decreased by 5.8-9.0 % without adaptation by the 2050s, due to the 1.3-5.8 % decrease in seed number and seed protein concentration. Seed yield was positively correlated with CO2 and negatively correlated with temperature, while seed vigor depended on the response of components of seed vigor to climatic factors. Under optimized management, the direct positive effects of temperature on seed protein concentration and CO2 on seed number were strengthened, and the direct negative effects of temperature on seed number and CO2 on seed protein concentration were weakened, which mitigated the reductions in both seed yield and vigor. Elevated CO2 was projected to exacerbate the 2.6 % seed vigor reduction and mitigate the 2.9 % seed yield loss without adaptation, while optimized management could increase seed yield by 4.1 % and mitigate the 2.2 % seed vigor reduction in the Hexi Corridor of China, and decrease the seed yield and vigor reduction by 2.4-5.8 % in the USA and Mexico. Optimized management can strengthen the positive and mitigate the negative effects of climate change on irrigated hybrid maize and inform high-yield and high-quality seed production globally.

Bioconversion of L-Tyrosine into p-Coumaric Acid by Tyrosine Ammonia-Lyase Heterologue of Rhodobacter sphaeroides Produced in Pseudomonas putida KT2440.

p-Coumaric acid (p-CA) is a valuable compound with applications in food additives, cosmetics, and pharmaceuticals. However, traditional production methods are often inefficient and unsustainable. This study focuses on enhancing p-CA production efficiency through the heterologous expression of tyrosine ammonia-lyase (TAL) from Rhodobacter sphaeroides in Pseudomonas putida KT2440. TAL catalyzes the conversion of L-tyrosine into p-CA and ammonia. We engineered P. putida KT2440 to express TAL in a fed-batch fermentation system. Our results demonstrate the following: (i) successful integration of the TAL gene into P. putida KT2440 and (ii) efficient bioconversion of L-tyrosine into p-CA (1381 mg/L) by implementing a pH shift from 7.0 to 8.5 during fed-batch fermentation. This approach highlights the viability of P. putida KT2440 as a host for TAL expression and the successful coupling of fermentation with the pH-shift-mediated bioconversion of L-tyrosine. Our findings underscore the potential of genetically modified P. putida for sustainable p-CA production and encourage further research to optimize bioconversion steps and fermentation conditions.

Entropy Production and Filling Time in Hydrogen Refueling Stations: An Economic Assessment.

A multi-objective optimization is performed to obtain fueling conditions in hydrogen stations leading to improved filling times and thermodynamic efficiency (entropy production) of the de facto standard of operation, which is defined by the protocol SAE J2601. After finding the Pareto frontier between filling time and total entropy production, it was found that SAE J2601 is suboptimal in terms of these process variables. Specifically, reductions of filling time from 47 to 77% are possible in the analyzed range of ambient temperatures (from 10 to 40 °C) with higher saving potential the hotter the weather conditions. Maximum entropy production savings with respect to SAE J2601 (7% for 10 °C, 1% for 40 °C) demand a longer filling time that increases with ambient temperature (264% for 10 °C, 350% for 40 °C). Considering average electricity prices in California, USA, the operating cost of the filling process can be reduced between 8 and 28% without increasing the expected filling time.

Encapsulation of Phenolic Compounds Extracted from Beet By-Products: Analysis of Physical and Chemical Properties.

Beet is a nutritious and health-promoting food with important bioactive compounds in its industrial by-products. The encapsulation of antioxidants from beet by-products has been proposed for valorization. For this, an ethanol-water extract was mixed with polyvinylpyrrolidone (PVP) (used as a carrier agent) and then encapsulated. The encapsulation was performed by spray drying, where the effects of temperature (140-160 °C), extract input flow rate (10-30%), and extraction solvent (ethanol-water 50/50 v/v and ethanol) were evaluated for the total phenol content and the spray-drying yield. The yields obtained were between 60 and 89%, and total phenols were between 136 and 1026 mg gallic acid equivalents/g of encapsulated product. Both responses were affected (p < 0.05) by the extraction solvent. The optimal spray-drying conditions were determined by response surface methodology (RSM). The encapsulated product obtained at optimal conditions was characterized by infrared spectrometry, X-ray fluorescence, Ultra-High Performance Liquid Chromatography, and scanning electron microscopy analysis. The results show that the encapsulated product has a high content of total phenols and compounds such as betanin, isobetanin, and neobetanin. Considering the results of physicochemical properties and the bioactive compounds, the optimized encapsulated product could be applied in the food industry as a bioactive ingredient or natural colorant. However, the further investigation of alternative carrier agents needs to be performed to reduce caking.

Interaction between modified magnetic nanoparticles and human albumin: Kinetics and isotherm studies and application in protein depletion.

Magnetic nanoparticles modified with tetraethyl orthosilicate (Fe3O4@TEOS) and bovine serum albumin (Fe3O4@TEOS@BSA) were evaluated as sorbent in albumin depletion from human serum samples by magnetic dispersive solid phase extraction. Characterization studies were carried out by X-ray diffraction, thermogravimetry, Fourier transform infrared spectroscopy, zeta potential, and scanning electron microscopy. Both nanoparticles also showed high thermal stability and pH-dependent surface charges. The human serum albumin adsorption protocol was optimized using a central composite rotatable design. Nanoparticle mass, pH, and albumin concentration were the most influential variables. Avrami's fractional order and Freundlich isotherm models best fitted the data for human albumin adsorption kinetic and isotherm studies for Fe3O4@TEOS and Fe3O4@TEOS@BSA, and the maximum adsorption capacities were 11.93 and 14.89 mg g-1, respectively. The protein desorption was influenced by the pH of samples and eluent volume. Electrophoresis in a polyacrylamide gel containing sodium dodecyl sulfate showed different patterns of serum protein bands when consecutive depletions were performed. The Fe3O4@TEOS showed greater affinity for HSA and efficiency in depletion. The process was versatile, and the depleted albumin proportion could be controlled by the nanoparticle masses. The proposed method is a powerful sample preparation technique for rapid, reliable, and specific depletion of albumin.

Genomics, Proteomics, and Antifungal Activity of Chitinase from the Antarctic Marine Bacterium Curtobacterium sp. CBMAI 2942.

This study aimed to evaluate the genomic profile of the Antarctic marine Curtobacterium sp. CBMAI 2942, as well as to optimize the conditions for chitinase production and antifungal potential for biological control. Assembly and annotation of the genome confirmed the genomic potential for chitinase synthesis, revealing two ChBDs of chitin binding (Chi C). The optimization enzyme production using an experimental design resulted in a 3.7-fold increase in chitinase production. The chitinase enzyme was identified by SDS-PAGE and confirmed through mass spectrometry analysis. The enzymatic extract obtained using acetone showed antifungal activity against the phytopathogenic fungus Aspergillus sp. series Nigri CBMAI 1846. The genetic capability of Curtobacterium sp. CBMAI 2942 for chitin degradation was confirmed through genomic analysis. The basal culture medium was adjusted, and the chitinase produced by this isolate from Antarctica showed significant inhibition against Aspergillus sp. Nigri series CBMAI 1846, which is a tomato phytopathogenic fungus. This suggests that this marine bacterium could potentially be used as a biological control of agricultural pests.

Improving the coverage area and flake size of ReS2through machine learning in APCVD.

Machine learning is playing a crucial role in optimizing material synthesis, particularly in scenarios where several parameters related to growth exhibit different and significant outcomes. An example of such complexity is the growth of atomically thin semiconductors through chemical vapor deposition (CVD), where multiple parameters can influence the thermodynamics and reaction kinetics involved in the synthesis. Herein, we performed a set of orthogonal experiments, varying the key parameters such as temperature, carries gas flux and precursor position to identify the optimal conditions for maximizing covered area and the size of rhenium disulfide (ReS2) crystals. The experimental results were used to establish correlations among the three thermodynamic variables through an artificial neural network. Contour plots were then generated to visualize the impact on the coverage and flake size of the crystals. This study demonstrates the capability of machine learning to enhance the potential of CVD-growth for the integration of 2D semiconductors like ReS2at larger scales.

Effects of LED lights and cytokinin on the phytotreatment of simulated swine wastewater by Azolla spp.: Pollutant removal and biomass valorization.

Phytoremediation is an eco-friendly and affordable option for tackling wastewater pollutants. The study focused on how light-emitting diodes (LED) light exposure, measured by intensity and duration (photoperiod), along with cytokinin, impacts Azolla microphylla's simulated swine wastewater treatment performance and biomass production. Under optimal treatment conditions, high removals of COD (89.2 % to 90.8 %), N-NH4+ (72.6 % to 91.2 %), N-NO3- (84.4 % to 88.6 %), Cu (75.4 % to 86.4 %), sulfamethoxazole (77.0 % to 79.0 %), P-PO43- (54.1 % to 59.9 %) and DOC (67.4 % to 71.3 %) while Zn presented a more moderate reduction (2.0 % to 9.7 %). Biomass productivity reached up to 34.8 t ha-1 yr-1. Protein production accounted for 23 % to 27 % of dry weight, while lipids ranged from 20 % to 34 % of dry biomass. Carbohydrate content varied from 8 % to 28 % of fresh weight. Higher light intensities, with both high or low values of photoperiods, and low concentrations of cytokinin were identified as optimal conditions for removal of almost all pollutants. However, pollutant removal was impacted differently by LED light and cytokinin concentration. In treatment conditions with the shortest photoperiods (8 h), the lowest residual Cu and Zn concentrations, whereas with longer photoperiods (24 h), the lowest residual concentrations of N-NH4+ and P-PO43- concentrations were recorded. On the other hand, SMX was the only parameter in which cytokinin had a clear influence on its removal, with the lowest residual concentration observed under 8-hour photoperiods combined with the lowest tested cytokinin concentrations (0.3 mg L-1). For residual COD and N-NO3-, no discernible pattern was evident for any of the analyzed factors. Therefore, the study demonstrates the potential for treating simulated swine wastewater using Azolla microphylla, aligned with its ability to produce biomass rich in high-value compounds.

Tailoring Plasmonic Nanoheaters Size for Enhanced Theranostic Agent Performance.

The introduction of optimized nanoheaters, which function as theranostic agents integrating both diagnostic and therapeutic processes, holds significant promise in the medical field. Therefore, developing strategies for selecting and utilizing optimized plasmonic nanoheaters is crucial for the effective use of nanostructured biomedical agents. This work elucidates the use of the Joule number (Jo) as a figure of merit to identify high-performance plasmonic theranostic agents. A framework for optimizing metallic nanoparticles for heat generation was established, uncovering the size dependence of plasmonic nanoparticles optical heating. Gold nanospheres (AuNSs) with a diameter of 50 nm and gold nanorods (AuNRs) with dimensions of 41×10 nm were identified as effective nanoheaters for visible (530 nm) and infrared (808 nm) excitation. Notably, AuNRs achieve higher Jo values than AuNSs, even when accounting for the possible orientations of the nanorods. Theoretical results estimate that 41×10 nm gold nanorods have an average Joule number of 80, which is significantly higher compared to larger rods. The photothermal performance of optimal and suboptimal nanostructures was evaluated using photoacoustic imaging and photothermal therapy procedures. The photoacoustic images indicate that, despite having larger absorption cross-sections, the large nanoparticle volume of bigger particles leads to less efficient conversion of light into heat, which suggests that the use of optimized nanoparticles promotes higher contrast, benefiting photoacoustic-based procedures in diagnostic applications. The photothermal therapy procedure was performed on S180-bearing mice inoculated with 41×10 nm and 90×25 nm PEGylated AuNRs. Five minutes of laser irradiation of tumor tissue with 41×10 nm produced an approximately 9.5% greater temperature rise than using 90×25 AuNRs in the therapy trials. Optimizing metallic nanoparticles for heat generation may reduce the concentration of the nanoheaters used or decrease the light fluence for bioscience applications, paving the way for the development of more economical theranostic agents.

Load estimation data using direct search method based on pattern search.

Accurately estimating load is essential for effective electric distribution planning, assets management, precise power flow predictions, accurate power losses calculations, and efficient integration of distributed energy resources. This work describes a dataset that was generated using Matlab and OpenDSS to produce several simulations in which load estimation is performed using a direct search method called pattern search. These simulations were conducted on three typical distribution feeders (IEEE 13-bus, 37-bus, and 123-bus) that support studies in distribution planning, assets management, power flow predictions, power losses calculations, and distributed resource integration. The dataset includes individual demand profiles of residential, commercial, and industrial consumers specified for the three distribution feeders, comprising 96 distinct scenarios. An optimization method was developed to obtain the dataset, which employs the pattern search technique to estimate loads through the optimization of objective functions and specified constraints. The load estimation quality was assessed for all three feeders, utilizing estimation quality indices proposed by the authors. These indices evaluated both the initial and proposed load estimation methods across the developed scenarios. Furthermore, the data provided in this article can be utilized for comparison with future load estimation studies, particularly regarding the quality of the method's results.

Optimization and Tradeoff Analysis for Multiple Configurations of Bio-Energy with Carbon Capture and Storage Systems in Brazilian Sugarcane Ethanol Sector.

Bio-energy systems with carbon capture and storage (BECCS) will be essential if countries are to meet the gas emission reduction targets established in the 2015 Paris Agreement. This study seeks to carry out a thermodynamic optimization and analysis of a BECCS technology for a typical Brazilian cogeneration plant. To maximize generated net electrical energy (MWe) and carbon dioxide CO2 capture (Mt/year), this study evaluated six cogeneration systems integrated with a chemical absorption process using MEA. A key performance indicator (gCO2/kWh) was also evaluated. The set of optimal solutions shows that the single regenerator configuration (REG1) resulted in more CO2 capture (51.9% of all CO2 emissions generated by the plant), penalized by 14.9% in the electrical plant's efficiency. On the other hand, the reheated configuration with three regenerators (Reheat3) was less power-penalized (7.41%) but had a lower CO2 capture rate (36.3%). Results showed that if the CO2 capture rates would be higher than 51.9%, the cogeneration system would reach a higher specific emission (gCO2/kWh) than the cogeneration base plant without a carbon capture system, which implies that low capture rates (<51%) in the CCS system guarantee an overall net reduction in greenhouse gas emissions in sugarcane plants for power and ethanol production.

An enzymatic hydrolysis-based platform technology for the efficient high-yield production of cellulose nanospheres.

This study evaluates the feasibility of using enzymatic technology to produce novel nanostructures of cellulose nanomaterials, specifically cellulose nanospheres (CNS), through enzymatic hydrolysis with endoglucanase and xylanase of pre-treated cellulose fibers. A statistical experimental design facilitated a comprehensive understanding of the process parameters, which enabled high yields of up to 82.7 %, while maintaining a uniform diameter of 54 nm and slightly improved crystallinity and thermal stability. Atomic force microscopy analyses revealed a distinct CNS formation mechanism, where initial fragmentation of rod-like nanoparticles and subsequent self-assembly of shorter rod-shaped nanoparticles led to CNS formation. Additionally, adjustments in process parameters allowed precise control over the CNS diameter, ranging from 20 to 100 nm, highlighting the potential for customization in high-performance applications. Furthermore, this study demonstrates how the process framework, originally developed for cellulose nanocrystals (CNC) production, was successfully adapted and optimized for CNS production, ensuring scalability and efficiency. In conclusion, this study emphasizes the versatility and efficiency of the enzyme-based platform for producing high-quality CNS, providing valuable insights into energy consumption for large-scale economic and environmental assessments.

Strategic location model for oil spill response vessels (OSRVs) considering oil transportation and weather uncertainties.

In the event of oil spills in offshore oil and gas projects, containment and dispersion equipment must be sent to the affected areas within a critical time by vessels known as oil spill response vessels (OSRVs). Here, we developed an optimization tool, integrated with an oil spill trajectory simulation model, both in deterministic and stochastic alternatives, to support decision-making during the strategic planning of OSRV operations. The tool was constructed in Python using GNOME for oil spill simulations and the GUROBI to solve the optimization model. The tool was applied to a case study in Brazil and afforded relevant recommendations. In terms of research contributions, we proved the viability of the integration between oil spill simulation and mathematical modeling for OSRV strategic operation planning, we explored the stochasticity of the problem with an innovative strategy and we demonstrated flexibility and easy applicability of the framework on real operations.

Optimization of Phenolic Compounds Extraction from Aerial Parts of Fabiana punensis S. C. Arroyo by Ultrasound- and Microwave-Assisted Extraction.

Fabiana punensis S. C. Arroyo is a subshrub or shrub that is indigenous to the arid and semiarid region of northern Argentina and is known to possess several medicinal properties. The objective of this study was to optimize the extraction conditions so as to maximize the yield of bioactive total phenolic compound (TPC) and flavonoids (F) of F. punensis' aerial parts by using non-conventional extraction methods, namely ultrasound-assisted extraction, UAE, and microwave-assisted extraction, MAE, and to compare the biological activities and toxicity of optimized extracts vs. conventional extracts, i.e., those gained by maceration. Response Surface Methodology (RSM) was used to apply factorial designs to optimize the parameters of extraction: solid-to-liquid ratio, extraction time, ultrasound amplitude, and microwave power. The experimental values for TPC and F and antioxidant activity under the optimal extraction conditions were not significantly different from the predicted values, demonstrating the accuracy of the mathematical models. Similar HPLC-DAD patterns were found between conventional and UAE- and MAE-optimized extracts. The main constituents of the extracts correspond to phenolic compounds (flavonoids and phenolic acids) and apigenin was identified. All extracts showed high scavenger capacity on ABTS•+, O2•- and H2O2, enabling the inhibition of the pro-inflammatory enzymes xanthine oxidase (XO) and lipoxygenase (LOX). They also showed an antimutagenic effect in Salmonella Typhimurium assay and cytotoxic/anti-proliferative activity on human melanoma cells (SKMEL-28). Toxicological evaluation indicates its safety. The results of this work are important in the development of efficient and sustainable methods for obtaining bioactive compounds from F. punensis for the prevention of chronic degenerative diseases associated with oxidative stress, inflammation, and DNA damage.

Optimizing Lactic Acid Bacteria Proportions in Sourdough to Enhance Antifungal Activity and Quality of Partially and Fully Baked Bread.

The organic acids produced by lactic acid bacteria (LAB) during the fermentation of sourdoughs have the ability to reduce the growth of different molds. However, this ability depends on the LAB used. For this reason, in this study, the proportions of different LAB were optimized to obtain aqueous extracts (AEs) from sourdough to reduce fungal growth in vitro, control the acetic acid concentration, and obtain a specific lactic to acetic acid ratio. In addition, the optimized mixtures were used to formulate partially baked bread (PBB) and evaluate the mold growth and bread quality during refrigerated storage. Using a simplex-lattice mixture design, various combinations of Lactiplantibacillus plantarum, Lacticaseibacillus casei, and Lactobacillus acidophilus were evaluated for their ability to produce organic acids and inhibit mold growth. The mixture containing only Lpb. plantarum significantly reduced the growth rates and extended the lag time of Penicillium chrysogenum and P. corylophilum compared with the control. The AEs' pH values ranged from 3.50 to 3.04. Organic acid analysis revealed that using Lpb. plantarum yielded higher acetic acid concentrations than when using mixed LAB. This suggests that LAB-specific interactions significantly influence organic acid production during fermentation. The reduced radial growth rates and extended lag times for both molds compared to the control confirmed the antifungal properties of the AEs from the sourdoughs. Statistical analyses of the mixture design using polynomial models demonstrated a good fit for the analyzed responses. Two optimized LAB mixtures were identified that maximized mold lag time, targeted the desired acetic acid concentration, and balanced the lactic to acetic acid ratio. The addition of sourdough with optimized LAB mixtures to PBB resulted in a longer shelf life (21 days) and adequately maintained product quality characteristics during storage. PBB was subjected to complete baking and sensory evaluation. The overall acceptability was slightly higher in the control without sourdough (7.50), followed by bread formulated with the optimized sourdoughs (ranging from 6.78 to 7.10), but the difference was not statistically significant (p > 0.05). The sensory analysis results indicated that the optimization was used to successfully formulate a sourdough bread with a sensory profile closely resembling that of a nonsupplemented one. The designed LAB mixtures can effectively enhance sourdough bread's antifungal properties and quality, providing a promising approach for extending bread shelf life while maintaining desirable sensory attributes.

Optimization of petroleum products distribution via pipeline systems: Modeling and computational challenges.

Optimizing the distribution of refined oil products using pipeline systems has been posing a meaningful challenge to the operations research field of exceptional economic importance for the oil and gas industry. The solution of this problem stands on the interface of chemical engineering and operations research, the former has been the most important contributor, and the latter has been paying an increasing amount of attention to its solution over the last ten years or so. The goal of this work is fourfold: to unveil the current shape of the accomplished research work on this topical area according to its descriptive analytics, to present and discuss its modeling research perspectives, to outline its emerging research trends and to trigger discussions on its future research avenues. A future research agenda should study more realistic mathematical models for the system and solution procedures that exploit their algebraic structure.

Optimization of enzymatic hydrolysis of cellulose extracted from bamboo culm for bioethanol production by Saccharomyces cerevisiae modified via CRISPR/Cas9.

In the context of biorefinery, researchers have been looking for lignocellulosic biomasses and ideal treatments to produce economically viable biofuels. In this scenario, the bamboo culm appears as a plant matrix of great potential, given the high cellulose content of low crystallinity. Thus, the objective and differential of this work was to determine the best conditions for enzymatic hydrolysis of cellulose extracted from bamboo culm and to evaluate its potential application in the production of bioethanol through Separate Hydrolysis and Fermentation (SHF) and Saccharification and Simultaneous Fermentation (SSF) by Saccharomyces cerevisiae modified via CRISPR/Cas9. The average cellulose extraction yield was 41.87 % with an extraction efficiency of 86.76 %. In general, as the hydrolysis time increased, an increase in glucose production was observed in almost all assays, with higher hydrolysis efficiency values at 72 h. The results ranged from 2.09 to 19.8 g/L of glucose obtained with efficiency values of 10.47 to 99 %. The best conditions were found in test 5 (temperature of 36 °C and pH 5.0, with only 10 FPU/g of substrate Cellic Ctec2 Novozymes ® cocktail). It is observed that for all hydrolysis times the independent variables pH and temperature were significant under the hydrolysis efficiency, showing a negative effect, indicating that higher values of the same promote lower values of the response variable. For bioethanol production, a maximum concentration of 7.84 g/L was observed for the SSH process after 4 h of fermentation, while for the SSF process it was 12.6 g/L after 24 h of fermentation, indicating the large potential of the simultaneous process together with the application of bamboo culm biomass for high production of biofuel.

Optimizing Encapsulation of Active Compounds of Carrot By-Product in TPP-Chitosomes.

Liposomes coated with chitosan by ionic gelation with tripolyphosphate (TPP-chitosomes) are interesting particles for stabilizing active compounds. However, the encapsulation condition must be optimized. The aim of this study was to optimize the encapsulation of phenolics and carotenoids of carrot pomace in TPP-chitosomes by using a Central Composite Design 23 and response surface methodology. The independent variables were the phospholipid (0.8-4.2 mg/mL), chitosan (2.6-9.4 mg/mL), and carrot pomace (4-14 g/100 mL of ethanol) concentrations; the responses were the encapsulation efficiency in TPP-chitosomes (EE) of phenolics, a-carotene, and b-carotene and the particle size and zeta potential of the particles. The zeta potential ranged from +17 to +37 mV, indicating that the liposomes were coated with chitosan and that the particle sizes were in the nanometric to submicrometric scale. The optimized condition for encapsulating carotenoids was 2.5 mg/mL phospholipids, 6.0 mg/mL chitosan, and 12 g of carrot pomace/100 mL of ethanol. In this condition, the EE of phenolics and α- and ß-carotene was 95%, 98%, and 99%, respectively. Therefore, TPP-chitosomes containing encapsulated phenolics and carotenoids, which can be obtained from agro-industrial by-products, have potential application as natural pigments in food or cosmetics. TPP-chitosomes can also be used to encapsulate other types of natural pigments.

Waste management optimization with NLP modeling and waste-to-energy in a circular economy.

This work presents a methodology integrating Non-Linear Programming (NLP) for multi-objective and multi-period optimization, addressing sustainable waste management and energy conversion challenges. It integrates waste-to-energy (WtE) technologies such as Anaerobic Digestion (AD), Incineration (Inc), Gasification (Gsf), and Pyrolysis (Py), and considers thermochemical, technical, economic, and environmental considerations through rigorous non-linear functions. Using Mexico City as a case study, the model develops waste management strategies that balance environmental and economic aims, considering social impacts. A trade-off solution is proposed to address the conflict between objectives. The economical optimal solution generates 1.79M$ with 954 tons of CO2 emissions while the environmental one generates 0.91M$ and reduces emissions by 54%, where 40% is due to gasification technology. Moreover, the environmentally optimal solution, with incineration and gasification generates 9500 MWh/day and 5960 MWh/day, respectively, demonstrates the capacity of the model to support sustainable energy strategies. Finally, this work presents an adaptable framework for sustainable waste management decision-making.