An overview on the key advantages and limitations of batch and dynamic modes of biosorption of metal ions

Water purification using adsorption is a crucial process for maintaining human life and preserving the environment. Batch and dynamic adsorption modes are two types of water purification processes that are commonly used in various countries due to their simplicity and feasibility on an industrial scale. However, it is important to understand the advantages and limitations of these two adsorption modes in industrial applications. Also, the possibility of using batch mode in industrial scale was scrutinized, along with the necessity of using dynamic mode in such applications. In addition, the reasons for the necessity of performing batch adsorption studies before starting the treatment on an industrial scale were mentioned and discussed. In fact, this review article attempts to throw light on these subjects by comparing the biosorption efficiency of some metals on utilized biosorbents, using both batch and fixed-bed (column) adsorption modes. The comparison is based on the effectiveness of the two processes and the mechanisms involved in the treatment. Parameters such as biosorption capacity, percentage removal, and isotherm models for both batch and column (fixed bed) studies are compared. The article also explains thermodynamic and kinetic models for batch adsorption and discusses breakthrough evaluations in adsorptive column systems. The review highlights the benefits of using convenient batch-wise biosorption in lab-scale studies and the key advantages of column biosorption in industrial applications.

Utilization of aquatic biomass as biosorbent for sustainable production of high surface area, nano- microporous, for removing two dyes from wastewater

The majority of environmental researchers are becoming increasingly concerned with the manufacture of inexpensive adsorbents for the detoxification of industrial effluents. To address one of the significant and well-known pollution issues with certain drains that act as hotspots and contribute to coastal pollution in Alexandria, this study aims to develop an economical, ecologically friendly sorbent. This study assessed the efficacy of a biomass-coated magnetic composite and a magnetic active adsorbent for the removal of two dyes from an industrially contaminated sewer using a wetland plant (Phragmites australis). Using magnetic biosorbent, the biosorption of Xylenol orange and Congo red ions from polluted drain discharge in Abu Qir Bay was evaluated in the current study. Using scanning electron microscopy imaging and Fourier transform infra-red analysis; the surface function and morphology of the nano-biosorbent were examined. At room temperature, the effects of initial dye concentration, pH, contact time, and nano-biosorbent concentration have all been investigated. The greatest percentages that nano-biosorbent can remove from Congo red and Xylenol orange are 97% and 47%, respectively. The removal of the initial Congo red concentration varied from 42 to 97%, while the removal of the initial Xylenol orange concentration varied from 30 to 47%. The adsorption capacity was shown to be strongly pH-dependent; capacity dose as pH value increased, with pH 10 being the ideal pH for Congo red and pH 6 being the ideal pH value for Xylenol orange. The adsorption capacity for Congo red varied between 0.96 and 3.36 and the adsorption capacity for Xylenol orange varied between 0.18 and 17.58. The removal capacity decreased from 3.36 to 0.96 mg/g when the biosorbent dosage was increased from 0.05 to 0.5 g/L for Congo red, in case of Xylenol orange, the removal capacity increased from 0.18 to 17.58 mg/g when the biosorbent dosage was increased from 0.05 to 0.5 g/L. The removal capacity of Congo red increases quickly with time and varied from 1.66 to 1.88 of contact time; while the removal capacity of Xylenol orange varied between 3.08 and 4.62 of contact time. For the dyes under study, kinetics and adsorption equilibrium were examined. Within 180 min, the equilibrium was attained because to the quick adsorption process. For Congo red and Xylenol orange, the highest adsorption capacities were 3.36 and 17.58 mg g-1, respectively. The equilibrium data were assessed using a number of isotherm models, including Langmuir, Freundlich, BET, and Tempkin, while the kinetic data were examined using a variety of kinetic models, including pseudo-first- and pseudo-second-order equations. The pseudo-second-order equation provides the greatest accuracy for the kinetic data and Langmuir model is the closest fit for the equilibrium data.

Assessing the effect of organic amendments on the degradation of profoxydim in paddy soils: Kinetic modeling and identification of degradation products

The fate and behavior of herbicides can be altered in an unpredictable way when organic amendments are added to soil as a beneficial management tool. The objective of this work was to investigate the effect exerted by the addition of two different organic amendments (alperujo compost and biochar) to soil in the degradation of one of the most relevant new generation rice herbicides, profoxydim. In unamended soils, the degradation of profoxydim was quite fast and was governed by both chemical (DT50steril soil = from 1.52 to 9.21 days) and microbial (DT50nonsterile soil = from 0.47 to 0.53 days) processes. Alperujo- and biochar-amended soils significantly increased the persistence of the herbicide in both soils, especially in the presence of biochar, due to the high capacity absorption of this amendment, increasing DT90 from 1.92 to 3.54 days for DT90unamended to 41.02-48.41 days for DT90biochar amended. Different kinetics models applied to fit the observed dissipation datasets showed that a HS biphasic model fits well with the dissipation of profoxydim in amended and unamended soils. For the first time, five degradation products (DPs) were identified by HPLC-QTOF-MS/MS in soil and a degradation pathway was described. Main DP was generated via oxidation of the sulfur atom to give rise to the corresponding sulfoxide derivative, with this DP being more persistent than the active substance. These outcomes can be very useful for the assessment of the environmental risk associated with the use of profoxydim in rice crops and the application of organic amendments as potential measures for minimizing the risk of contamination of natural water resources.

Impact of (nano ZnO/multi-wall CNTs) prepared by arc discharge method on the removal efficiency of stable iodine 127I and radioactive iodine 131I from water

Radioactive iodine isotopes especially 131I are used for diagnosis and treatment of different types of cancer diseases. Due to the leak of radioactive iodine into the patient's urine in turn, the wastewater would be contaminated, so it is worth preparing a novel adsorption green material to remove the radioactive iodine from wastewater efficiently. The removal of 127I and 131I contaminants from aqueous solution is a problem of interest. Therefore, this work presents a new study for removing the stable iodine 127I- and radioactive iodine 131I from aqueous solutions by using the novel nano adsorbent (Nano ZnO/MWCNTs) which is synthesized by the arc discharge method. It is an economic method for treating contaminated water from undesired dissolved iodine isotopes. The optimal conditions for maximum removal are (5 mg/100 ml) as optimum dose with shacking (200 rpm) for contact time of (60 min), at (25 °C) in an acidic medium of (pH = 5). After the adsorption process, the solution is filtrated and the residual iodide (127I-) is measured at a maximum UV wavelength absorbance of 225 nm. The maximum adsorption capacity is (15.25 mg/g); therefore the prepared nano adsorbent (Nano ZnO/MWCNTs) is suitable for treating polluted water from low iodide concentrations. The adsorption mechanism of 127I- on to the surface of (Nano ZnO/MWCNTs) is multilayer physical adsorption according to Freundlich isotherm model and obeys the Pseudo-first order kinetic model. According to Temkin isotherm model the adsorption is exothermic. The removal efficiency of Nano ZnO/MWCNTs for stable iodine (127I-) from aqueous solutions has reached 97.23%, 89.75%, and 64.78% in case of initial concentrations; 0.1843 ppm, 0.5014 ppm and 1.0331 ppm, respectively. For the prepared radio iodine (131I-) solution of radioactivity (20 µCi), the dose of nano adsorbent was (10 mg/100 ml) and the contact time was (60 min) at (pH = 5) with shacking (200 rpm) at (25 °C). The filtration process was done by using a syringe filter of a pore size (450 nm) after 2 days to equilibrate. The removal efficiency reached (34.16%) after the first cycle of treatment and the percentage of residual radio iodine was (65.86%). The removal efficiency reached (94.76%) after five cycles of treatment and the percentage of residual radio iodine was (5.24%). This last percentage was less than (42.15%) which produces due to the natural decay during 10 days.

Assessment of biochemical methane potential of dairy wastewater with different co-substrates and evaluation of different kinetic models

Dairy industry wastewater can be considered as an important source of pollution due to its high amounts and pollutant concentrations. Anaerobic treatment is seen as a suitable alternative over aerobic treatment which requires huge aeration systems. Biochemical methane potential (BMP) testing is a widely applied technique for estimating the performance of anaerobic digesters and still has no clear alternative. In the study, the biochemical methane potential change was investigated by mixing dairy wastewater with different co-substrates (cattle manure, chicken manure and slaughterhouse wastewater) at different rates. The highest biogas potential per gram of chemical oxygen demand added (CODadded) was determined as 574 mLbiogas in a mixture of 74% dairy wastewater + 2% chicken manure + 24% slaughterhouse wastewater inoculated with granular sludge. The highest methane potential was determined as 340 mLCH4 in the same co-substrate mixture inoculated with anaerobic sludge. In recent years, mathematical modeling offers an alternative to BMP tests and many different models are used for this purpose. In the study, six different mathematical models were used to simulate the BMP results, and the highest correlation coefficient in almost all mixtures ranged from 0.900 to 0.997 with the Modified Gompertz equation and Fitzhugh models.

Enhancement of Prebiotic Peptide Formation in Cyclic Environments

The dynamic behaviors of prebiotic reaction networks may be critically important to understanding how larger biopolymers could emerge, despite being unfavorable to form in water. We focus on understanding the dynamics of simple systems, prior to the emergence of replication mechanisms, and what role they may have played in biopolymer formation. We specifically consider the dynamics in cyclic environments using both model and experimental data. Cyclic environmental conditions prevent a system from reaching thermodynamic equilibrium, improving the chance of observing interesting kinetic behaviors. We used an approximate kinetic model to simulate the dynamics of trimetaphosphate (TP)-activated peptide formation from glycine in cyclic wet-dry conditions. The model predicts that environmental cycling allows trimer and tetramer peptides to sustain concentrations above the predicted fixed points of the model due to overshoot, a dynamic phenomenon. Our experiments demonstrate that oscillatory environments can shift product distributions in favor of longer peptides. However, experimental validation of certain behaviors in the kinetic model is challenging, considering that open systems with cyclic environmental conditions break many of the common assumptions in classical chemical kinetics. Overall, our results suggest that the dynamics of simple peptide reaction networks in cyclic environments may have been important for the formation of longer polymers on the early Earth. Similar phenomena may have also contributed to the emergence of reaction networks with product distributions determined not by thermodynamics, but rather by kinetics.

Assessment of kinetic and statistical models for predicting breakthrough curves of bio-colloid transport through saturated porous media

The microbial contamination of groundwater and its prevention is a widespread concern in developing countries. The present study simulated the transportation and interception of bio-colloid, Escherichia coli in porous media experimentally using packed columns to address certain aspects of underexplored sorption potential and validated using several kinetic models. The breakthrough curves obtained through experiments are observed to be in good agreement with its prediction using kinetic models namely Thomas, Yoon-Nelson and Modified Dose-Response. The overall comparisons of R2 among all the three models suggest that the MDR model fits more perfectly to experimental results. The combined effect of independent factors (column depth, particle size and alumina content) on response factors (maximum relative concentration and time required to achieve peak concentration) was investigated by using Box-Behnken Design under Response Surface Methodology (RSM) to check statistical significancy of independent factors. The R2 values for both response factors are observed to be 0.94 and 0.99, indicating a very high correlation between predicted and actual values. The results obtained in the present study also confirms that the travel distance and particle size are the statistically significant parameters that efficiently impact on sorption of Escherichia coli during their transport whereas the alumina content also affects the sorption but is observed to be a statistically non-significant.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Kinetics, thermodynamics, and thermal decomposition behavior of palm oil empty fruit bunch, coconut shell, bamboo, and cardboard pyrolysis: an integrated approach using Coats-Redfern method

This study presents the kinetics and thermodynamics of biomass pyrolysis. The kinetics of the pyrolysis process was estimated using ten kinetic models from three different mechanisms, namely chemical reaction, diffusion, and nucleation and growth. Results showed that each pyrolysis subdivision was described by a different reaction model, signifying the complex nature of the pyrolysis process. The average values of activation energy determined from the kinetic models for empty fruit bunch, coconut shell, bamboo, and cardboard are 10.2-64.6 kJ/mol, 18.7-186.2 kJ/mol, 8.0-70.8 kJ/mol, and 13.1-277.3 kJ/mol, respectively. The biomass pyrolysis is endothermic and non-spontaneous and would require external energy to initiate the degradation process. The findings are helpful in characterizing the thermal degradation of biomass in exploring its potential as a source of alternative solid fuel.

Oxygen consumption and formation of recalcitrant organic carbon from the decomposition of free-floating macrophyte leachates

Aquatic macrophytes contain high levels of hydrosoluble compounds. These compounds disproportionately support microbial breakdown and affect biological oxygen demand in eutrophic waters. In this study, we investigated the fate of leachates from free-floating macrophytes (Pistia stratiotes and Eichhornia crassipes) usually present in eutrophic tropical lacustrine environments. After extraction, the leachates were fractioned into high and low molecular weight compounds and incubated under aerobic conditions, in the dark and at 20.0 ± 1.3 °C. The concentrations of dissolved oxygen and the total, dissolved, and particulate organic carbon (TOC, DOC, and POC) were determined during 60 days. The selected leachates supported the detritus trophic chain of the Barra Bonita Reservoir. High rates of carbon transfer were measured, which were ascribed to the temperature selected (20 °C), nutrient availability, and labile fractions of the leachates. Decomposition occurred mainly through catabolic pathways (mineralization), with the formation of POC (immobilization) being only minor. In the early stages of P. stratiotes and E. crassipes decomposition, the mineralization of leachates (mainly the low molecular weight) led to declines in dissolved oxygen. Owing to the low rates of mass loss, the recalcitrant fractions of these leachates should constitute the main forms of organic carbon exported from the reservoir.

Recent Advances in Sustainable Antimicrobial Food Packaging: Insights into Release Mechanisms, Design Strategies, and Applications in the Food Industry

In response to the issues of foodborne microbial contamination and carbon neutrality goals, sustainable antimicrobial food packaging (SAFP) composed of renewable or biodegradable biopolymer matrices with ecofriendly antimicrobial agents has emerged. SAFP offers longer effectiveness, wider coverage, more controllability, and better environmental performance. Analyzing SAFP information, including the release profile of each antimicrobial agent for each food, the interaction of each biomass matrix with each food, the material size, form, and preparation methods, and its service quality in real foods, is crucial. While encouraging reports exist, a comprehensive review summarizing these developments is lacking. Therefore, this review critically examines recent release-antimicrobial mechanisms, kinetics models, preparation methods, and key regulatory parameters for SAFPs based on slow- or controlled-release theory. Furthermore, it discusses fundamental physicochemical characteristics, effective concentrations, advantages, release approaches, and antimicrobial and preservative effects of various materials in food simulants or actual food. Lastly, inadequacies and future trends are explored, providing practical references to regulate the movement of active substances in different media, reduce the reliance on petrochemical-based materials, and advance food packaging and preservation technologies.

Non-enzymatic browning of a composite puree of Choerospondias axillaris, snow pear, and apple: kinetic modeling and correlation analysis

Choerospondias axillaris, snow pear, and apple composite fruit puree can be affected by non-enzymatic browning during storage decreasing the market value of the product. This study aimed to explore, using kinetic methods, the effects of non-enzymatic precursors (polyphenols and ascorbic acid) and intermediates (5-hydroxymethylfurfural) on fruit puree stored at 4 °C for 35 days. The results showed that ascorbic acid fitted the first-order reaction model, while the 5-hydroxymethylfurfural was consistent with the complex reaction model. Furthermore, the 5-hydroxymethylfurfural content was 1.53 ± 0.18 mg/L, (corresponding to an increase of 565%), and the ascorbic acid content was 0.88 ± 0.22 mg/100 g, (corresponding to a decrease of 98.5%). The results also demonstrated a change in the titratable acid, soluble solids, and pH of the fruit puree. Finally, the correlation results revealed a significant correlation between non-enzymatic browning and 5-hydroxymethylfurfural, titratable acid, and pH (p < 0.05). Overall, the results suggest that the Maillard reaction could be responsible for the non-enzymatic browning of fruit purees during storage.

Biogas production from malt bagasse from craft beer industry: kinetic modeling and process simulation

In this work, biogas was synthesized from malt enriched-craft beer bagasse with the objective to generate clean energy. Thus, a kinetic model based on thermodynamic parameters was proposed to represent the process with coefficient determination (R2) of 0.82. A bench-top biodigester of 2.0 × 10-3 m3 was built in glass, and equipped with sensors to measure pressure, temperature, and methane concentration. The inoculum selected for the anaerobic digestion was the granular sludge, and malt bagasse was used as substrate. Data were fitted to a pseudo-first-order model for the formation of methane gas using the Arrehnius equation as basis. For the simulations of biogas production, the Aspen Plus™ software was used. Results from 23 factorial design experiments evidenced that equipment was efficient, and the craft beer bagasse showed great biogas production, with nearly 95% of methane yield. The temperature was the variable that showed most influence in the process. Moreover, the system has a potential for the generation of 10.1 kWh of clean energy. Kinetic constant rate for methane production was 5.42 × 10-7 s-1 and activation energy 8.25 kJ mol-1. A statistical analysis using a math software was performed and evidenced that the temperature played a major role in the biomethane conversion.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10163-023-01715-7.

Different pre-treatments and kinetic models for bioethanol production from lignocellulosic biomass: A review

Lignocellulosic biomass is the generally explored substrate to produce bioethanol for environmental sustainability due to its availability in abundance. However, the complex network of cellulose-hemicellulose-lignin present in it makes its hydrolysis as a challenging task. To boost the effectiveness of conversion, biomass is pre-treated before enzymatic hydrolysis to alter or destroy its original composition. Enzymes like Cellulases are widely used for breaking down cellulose into fermentable sugars. Enzymatic hydrolysis is a complex process involving many influencing factors such as pH, temperature, substrate concentration. This review presents major four pre-treatment methods used for hydrolysing different substrates under varied reaction conditions along with their mechanism and limitations. A relative comparison of data analysis for most widely studied 10 kinetic models is briefly explained in terms of substrates used to get the brief insight about hydrolysis rates. The summary of pre-treatment methods and hydrolysis rates including cellulase enzyme kinetics will be the value addition for upcoming researchers for optimising the hydrolysis process.

Non-destructive monitoring of quality attributes kinetics during the drying process: A case study of celeriac slices and the model generalisation in selected commodities

The potential of Visual-NIR hyperspectral imaging (VNIR-HSI, 425-1700 nm) to predict celeriac quality attributes during the drying process was investigated. The HSI-Gaussian Process Regression (GPR) fusion method excellently predicted moisture content (MC, R² ≈ 1.00, RMSE = 0.77 g_w 100 g_s^-1) and water activity (a_w, R² = 0.98, RMSE = 0.04). Moreover, the rehydration ratio (RR, R² = 0.89, RMSE = 0.04) and colour indices (R² = 0.80-0.93, RMSE = 0.17-1.45) were reasonably predicted. However, antioxidant activity (AA) and total phenolic compounds (TPC) were poorly predicted. These results are potentially due to MC variations dominating the NIR region, masking phenolic compounds. Finally, the celeriac-based-trained model was assessed by predicting the MC of apple, cocoyam, and carrot slices. The results were encouraging; however, a GPR model trained on the data of all four commodities was more robust (R² ≈ 1.00, RMSE = 1-2 g_w 100 g_s^-1).

Cyclic desorption based efficacy of polyvinyl alcohol-chitosan variant resins for multi heavy-metal removal

The simultaneous removal of Cu, Pb and Fe from water bodies has been targeted in this work with polyvinyl alcohol (PVA) and chitosan (low, medium, and high molecular weight) derivative and with cyclic desorption efficacy target. For a varied range of adsorbent loading (0.2-2 g L^-1), initial concentration (187.7-563.1 mg L^-1 for Cu, 5.2-15.6 mg L^-1 for Pb, and 61.85-185.55 mg L^-1 for Fe), and resin contact time (5 to 720 min), batch adsorption-desorption studies were conducted. After first adsorption-desorption cycle, the optimum absorption capacity was 6.85 mg g^-1 for Pb, 243.90 mg g^-1 for Cu, and 87.72 mg g^-1 for Fe for the high molecular weight chitosan grafted polyvinyl alcohol resin (HCSPVA). The alternate kinetic and equilibrium models were analyzed along with the interaction mechanism between metal ions and functional groups. The cyclic desorption studies were carried out with simple eluent systems such as HCl, HNO₃, H₂SO₄, KOH, and NaOH. The experiments revealed that the HCSPVA derivative has been an impressive, reusable, and effective sorbent for the mitigation of Pb, Fe, and Cu in complex wastewater systems. This is due to its easy synthesis, excellent adsorption capacity, quick sorption rate, and remarkable regeneration capabilities.

Ketosynthase mutants enable short-chain fatty acid biosynthesis in E. coli

Cells build fatty acids in tightly regulated assembly lines, or fatty acid synthases (FASs), in which β-ketoacyl-acyl carrier protein (ACP) synthases (KSs) catalyze sequential carbon-carbon bond forming reactions that generate acyl-ACPs of varying lengths-precursors for a diverse set of lipids and oleochemicals. To date, most efforts to control fatty acid synthesis in engineered microbes have focused on modifying termination enzymes such as acyl-ACP thioesterases, which release free fatty acids from acyl-ACPs. Changes to the substrate specificity of KSs provide an alternative-and, perhaps, more generalizable-approach that focuses on controlling the acyl-ACPs available for downstream products. This study combines mutants of FabF and FabB, the two elongating KSs of the E. coli FAS, with in vitro and in vivo analyses to explore the use of KS mutants to control fatty acid synthesis. In vitro, single amino acid substitutions in the gating loop and acyl binding pocket of FabF shifted the product profiles of reconstituted FASs toward short chains and showed that KS mutants, alone, can cause large shifts in average length (i.e., 6.5-13.5). FabB, which is essential for unsaturated fatty acid synthesis, blunted this effect in vivo, but exogenously added cis-vaccenic acid (C18:1) enabled sufficient transcriptional repression of FabB to restore it. Strikingly, a single mutant of FabB afforded titers of octanoic acid as high as those generated by an engineered thioesterase. Findings indicate that fatty acid synthesis must be decoupled from microbial growth to resolve the influence of KS mutants on fatty acid profiles but show that these mutants offer a versatile approach for tuning FAS outputs.

Quantitative models and potential surrogates for rapid evaluation and surveillance of chlorine disinfection efficacy in reclaimed water

Chlorine disinfection has become the most widely applied and indispensable technology in wastewater treatment and reuse to mitigate microbial risk and guarantee water safety. However, owing to complexities and high concentrations of contaminants in reclaimed water, rapid evaluation of chlorine disinfection efficacy is a crucial but challenging issue. Based on intensive experimental and statistical analyses, this study has established kinetic models and potential surrogates for rapid indication of the inactivation of microbial indicators and opportunistic pathogens during chlorine disinfection in different reclaimed waters. Overall, the constructed Selleck models performed very well to simulate log removal values (LRVs) of fecal coliforms, Pseudomonas aeruginosa and heterotrophic plate counts in all reclaimed water samples (R² = 0.877-0.990). Moreover, total and Peak A fluorescence intensity as well as fluorescence integral intensities in Regions II and IV were found to have high response sensitivities during the chlorination process. Nevertheless, their effectiveness to act as potential surrogates of LRVs of microbial indicators needs to be further validated. The results from this study can provide valuable information on microbial safety surveillance of disinfection toward sustainable and long-term water reuse.

Adsorption modelling and fixed-bed column study on milk processing industry wastewater treatment using chitosan zinc-oxide nano-adsorbent-coated sand filter bed

This study aims to develop a chitosan-zinc oxide nano-adsorbent-coated sand (CZOCS) filter bed for getting rid of milk processing industry wastewater (MPIW) in a safe way. Chitosan zinc oxide nano-adsorbent (CZnO) of 88.35 ± 2.89 d.nm size was used to coat naturally available sand through a calcination process at 200 °C for a heating rate of 5 °C/min. The characteristics of the diffraction peaks and functional groups are attributed to the nature of CZnO loading on the sand surface. The increase in breakthrough and exhaustion times is caused by the biological oxygen demand (BOD) and chemical oxygen demand (COD) of influent having more time to interact with the adsorbent as bed height increases, resulting in higher reduction efficiencies. Lower bed heights (10 cm) which saturate faster than higher bed heights (40 cm) result in a shorter mass transfer time. Adsorption capacity at the 95% column exhaustion point increased from 611.04 to 1089.63 mg/g for BOD and from 4512.29 to 5600.81 mg/g for COD. Different kinds of kinetic models have been used to forecast breakthrough curves employing experimental data. Statistical and error function parameters were used to choose the best-fit model. Among the models investigated, the Thomas model was shown to be the best-fit with the highest R-square values of 0.9942 and 0.9939. The CZOCS has high reusability and could be used for up to six cycles of organic pollutant adsorption. Aside from that, novel CZOCS could be used to clean real MPIW, and making it one of the most promising adsorbents.

Drying kinetics and sensory characteristics of dehydrated pumpkin seeds (Cucurbita moschata) obtained by refractance window drying

The current importance of pumpkin (Cucurbita moschata) in national food security has progressively encouraged research on this fruit. This is how pumpkin seeds constitute a potential raw material to obtain dehydrated products for direct consumption. In this research, we compared the drying kinetics, effective diffusivity (D_ef) and sensory perception in a non-trained panel of dehydrated pumpkin seeds through refractance window drying (RW) and convective air drying (CA). RW drying was carried out in a laboratory-scale hydro-dryer and CA drying was carried out in a dryer with hot air circulation; both at 80 ± 2 °C. Sensory acceptability (appearance, aroma, taste and texture) was evaluated by an affective test on a hedonic scale from 1 to 5 with 60 panelists. The drying curves (MR vs t) were fitted to four kinetic models: Newton, Logarithmic, Page and Midilli et al. D_ef was determined by the second Fick’s Law solution. The best model for RW drying was logarithmic, and D_ef was 6.60 × 10⁻¹⁰ m²/s (R² = 0.9927); while for CA, it was Midilli et al., with the D_ef found through this method being 9.60 × 10⁻¹⁰ m²/s (R² = 0.9928). Dry seeds by RW obtained a general acceptance of 3.82, compared to 3.63 by CA. Results allow us to conclude that among the drying methods evaluated, there is not statistically significant differences, in terms of dehydration characteristics and sensory acceptability, constituting RW drying as an alternative method for obtaining dehydrate pumpkins seeds for direct consumption.

Cadmium tolerant microbial strains possess different mechanisms for cadmium biosorption and immobilization in rice seedlings

Heavy metal remediation, such as cadmium (Cd²⁺) by microbial strains is efficient and environment-friendly. In this current study, we exploited the potential of Bacillus strains (Cd²⁺-tolerant; NMTD17, GBSW22, and LLTC96) to regulate Cd²⁺ biosorption mechanisms and improve rice seedling growth. The results showed that initial concentration and contact time affected Cd²⁺ biosorption, and the kinetic models of pseudo orders were effective in the elaborate biosorption process. Mainly, the bacterial cell wall had the potential for Cd²⁺ biosorption, and we found non-significant biosorption alterations among bacterial strains' inner and outer surfaces of cell membranes. Furthermore, the Fourier transform infrared (FTIR) spectroscopy analysis identified the differences in functional groups, such as C-N, PO₂, -SO₃, CO, COOH, C-O, C-N, -OH, and -NH that interact in biosorption by Bacillus strains. The scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) examination revealed that the binding of Cd²⁺ to microbes was mostly based on ion exchange pathways. Moreover, the Bacillus strains responded to Cd²⁺ stress in rice under pot experiment at various concentrations (0, 0.25, and 0.50 mg kg^-1), and they also influenced the chlorophyll contents and antioxidants activities were studied. The analysis of physio-morphological parameters was observed to be increased, which indicated that all Bacillus strains showed significant effects on rice growth under Cd²⁺ stress. These results revealed that the selected strains had the capability for additional use in the development of Cd²⁺ bioremediation methods. These strains also provided plant growth-promoting (PGP) traits that can alleviate the harmful effects of Cd²⁺ in rice plants.

Adsorption mechanisms on perfluorooctanoic acid by FeCl3 modified granular activated carbon in aqueous solutions

Perfluorooctanoic acid (PFOA) is an emerging organic pollutant that is persistent in the environmental, and has been detected in humans, and wildlife. Several technologies, such as activated carbon (AC) adsorption have been used to remove PFOA from water. In this study, Fe-impregnation with/without post-thermal treatment of AC was applied to improve the adsorption of PFOA. The adsorption mechanisms were evaluated using three kinetic models: pseudo-first-order model, pseudo-second-order model, and intra-particle diffusion models. Interpretation of experimental results with the kinetic models revealed that chemical interactions, such as electrostatic attraction or complexation were suggested as the adsorption mechanisms along with physical adsorption. Two isotherm models demonstrated that the modified ACs (171.0-189.9 mg g^-1) had increases in adsorption capacities than the unmodified AC (164.9 mg g^-1), which indicated that modification improved the maximum achievable surface concentrations and adsorption affinity to some extent. The evenly distributed iron content on the modified ACs was visualized using an energy dispersive X-ray spectroscopy. The Fe-impregnated AC showed a reduction in the specific surface area and total pore volume; however, post-thermal treatment largely recovered the pore structures. The isotherms normalized by the accessible surface area revealed the importance of the Fe-impregnated surfaces on PFOA adsorption. Comparable pH values of the point of zero charge and chemical compositions of the ACs implied that an increase in Fe-impregnated surface was crucial to improve PFOA adsorption. Thus, substantial enhancement of PFOA removal can be achieved by implementing a proper strategy for AC modification, especially using Fe-impregnation.

Molecular, Brownian, kinetic and stochastic models of the processes in photosynthetic membrane of green plants and microalgae

The paper presents the results of recent work at the Department of Biophysics of the Biological Faculty, Lomonosov Moscow State University on the kinetic and multiparticle modeling of processes in the photosynthetic membrane. The detailed kinetic models and the rule-based kinetic Monte Carlo models allow to reproduce the fluorescence induction curves and redox transformations of the photoactive pigment P700 in the time range from 100 ns to dozens of seconds and make it possible to reveal the role of individual carriers in their formation for different types of photosynthetic organisms under different illumination regimes, in the presence of inhibitors, under stress conditions. The fitting of the model curves to the experimental data quantifies the reaction rate constants that cannot be directly measured experimentally, including the non-radiative thermal relaxation reactions. We use the direct multiparticle models to explicitly describe the interactions of mobile photosynthetic carrier proteins with multienzyme complexes both in solution and in the biomembrane interior. An analysis of these models reveals the role of diffusion and electrostatic factors in the regulation of electron transport, the influence of ionic strength and pH of the cellular environment on the rate of electron transport reactions between carrier proteins. To describe the conformational intramolecular processes of formation of the final complex, in which the actual electron transfer occurs, we use the methods of molecular dynamics. The results obtained using kinetic and molecular models supplement our knowledge of the mechanisms of organization of the photosynthetic electron transport processes at the cellular and molecular levels.

Silage as a pre-treatment of orange bagasse waste to increase the potential for methane generation

Among the various methods of pre-treatment of lignocellulosic waste with the objective of optimizing the production of methane, silage stands out as a promising alternative due to its operational simplicity, low cost and effective results. In this work, the silage of orange waste (Citrus cinensis) with 14 and 21 days and its influence on the potential of methane generation was evaluated, also evaluating the impacts of silage on the kinetics of the process. Among several configurations of substrate and inoculum studied, the best configuration observed was using the ensiled residue with 21 days and granular anaerobic sludge (ENS21 + GS), reaching a methane generation potential of about 171 N mL·g^-1 VS, increasing by 119% in terms of methane generation potential without silage pre-treatment (WENS+GS), obtaining biogas with 70% in CH₄. In relation to the kinetics, the silage process drastically interfered in the kinetic behavior of the methane production, being the Cone model the one that obtained the best adjustments, among those studied, for the orange bagasse residue in the evaluated experimental conditions. Silage is an attractive alternative to increase the production of methane for lignocellulosic waste, as a pre-treatment, without significantly increasing operating costs, and it can also be associated with other sequential processes to take advantage of the maximum energy potential of lignocellulosic waste.

Algal/bacterial uptake kinetics of dissolved organic nitrogen in municipal wastewater treatment facilities effluents

The simulation and analysis of the degradation process of organic nitrogen contaminants in wastewater treatment facility effluent is important to the estimation of its actual contribution to eutrophication, and it is crucial to the developing of watershed protection plan. In this study, algal and algal/bacterial based bioassay was conducted to study the bioavailability of dissolved organic nitrogen contaminants in wastewater treatment plants effluents, and 4 kinetic models were used to describe the mineralization process. The traditional 1-pool model that was commonly used in water quality models showed poor correlation (r² = 0.613 ± 0.261), while the other three models performed much better (r² > 0.950). The model coefficient and simplicity were studied using Akaike information criterion and Bayesian information criterion, and Gamma model was indicated to be the best model since it presented the most parsimonious fit to the data with the fewest terms. This study exhibited that the bioavailability and degradation rate of organic nitrogen in wastewater effluent varied greatly, and this variation should be considered in water quality models. Besides, Gamma model could be used to modify the current Total Maximum Daily Load models to provide a scientific basis for making watershed protection plans and controlling eutrophication.

Influence of salinity on heavy metal and oil removal from hypersaline oilfield-produced water by electrocoagulation: mechanistic insights

The focus of the present study was to explore how and to what extent ultrahigh salinity affects the adsorption of cadmium and hydrocarbon pollutants onto aluminum hydroxide adsorbents formed in an electrocoagulation process. The changes in the nature and structure of the electro-generated aluminum particles and the possible removal mechanisms due to high salt content were investigated by using FE-SEM/EDS, FTIR, BET, and XRD analyses. The pseudo-second order and Freundlich models proved to fit the data for cadmium adsorption onto the aluminum hydroxides best. It was demonstrated that the adsorption capacities were significantly affected by the high salinity. With the rise of the salinity from 2 to 170 g/L, the cadmium and COD removal yields dropped from 81 to 60% and from 90 to 72%. The increase of the oil content led to the enhanced cadmium adsorption capacity due to surface complexation and ion exchange mechanisms. It was proved that Lagergren pseudo-first-order kinetic model could justify COD abatement trends. FTIR spectra depicted that the negative impact of high salinities on the adsorption was due to causing the formation of less stable adsorbents. According to BET analysis, the occurrence of much wider pore size distribution and smaller specific surface area in high salinity case was the main reason for the decreased adsorption capacity. Based on XRD analysis, the higher crystallinity of the produced aluminum hydroxide particles and their consequential smaller surface areas resulted in the lower adsorption capacity in the hypersaline environment. It was concluded that adsorption via inner-sphere and outer-sphere complexation and sweep flocculation were the possible removal mechanisms. Total treatment cost of 8.75 and 3.49 €/m3 were estimated for low and ultrahigh salinity conditions.

Comparison of Arrhenius model and artificial neuronal network for predicting quality changes of frozen tilapia (Oreochromis niloticus)

The objectives of this study were to study the quality changes (ice crystal morphology, Ca²⁺-ATPase activity, total sulfhydryl [SH] content, intrinsic fluorescence intensity [IFI], and K value [freshness determination]) of tilapia at different storage temperatures for 112 days, and kinetic models and artificial neuronal network (ANN) were developed to predict the changes. There was a dramatic increase in cross-section area and equivalent diameter and a sharp decrease in Ca²⁺-ATPase activity and SH content during the first 4 weeks (p < 0.05). IFI_λmax decreased by 43.95%, 29.77%, 28.97% and 18.58% after 16 weeks at 265 K, 259 K, 253 K, and 233 K. The kinetic model established by IFI_λmax could be accurately described the quality changes during storage at 233-265 K. However, the prediction accuracy established by other indices decreased at later stages (14-16 weeks). The ANN model was superior to Arrhenius models and performed better for all indicators.

Dynamic chaotic gravitational search algorithm-based kinetic parameter estimation of hepatocellular carcinoma on 18F-FDG PET/CT

Background

Kinetic parameters estimated with dynamic ¹⁸F-FDG PET/CT can help to characterize hepatocellular carcinoma (HCC). We aim to evaluate the feasibility of the gravitational search algorithm (GSA) for kinetic parameter estimation and to propose a dynamic chaotic gravitational search algorithm (DCGSA) to enhance parameter estimation.

Methods

Five-minute dynamic PET/CT data of 20 HCCs were prospectively enrolled, and the kinetic parameters k₁ ~ k₄ and the hepatic arterial perfusion index (HPI) were estimated with a dual-input three-compartment model based on nonlinear least squares (NLLS), GSA and DCGSA.

Results

The results showed that there were significant differences between the HCCs and background liver tissues for k₁, k₄ and the HPI of NLLS; k₁, k₃, k₄ and the HPI of GSA; and k₁, k₂, k₃, k₄ and the HPI of DCGSA. DCGSA had a higher diagnostic performance for k₃ than NLLS and GSA.

Conclusions

GSA enables accurate estimation of the kinetic parameters of dynamic PET/CT in the diagnosis of HCC, and DCGSA can enhance the diagnostic performance.

Sorption of benzo[a]pyrene by Chernozem and carbonaceous sorbents: comparison of kinetics and interaction mechanisms

Benzo[a]pyrene (BaP) is a polycyclic aromatic hydrocarbon, highly persistent and toxic and a widespread environmental pollutant. Although various technologies have been developed to remove BaP from the environment, its sorption through solid matrixes has received increasing attention due to cost-effectiveness. The present research compares the adsorption capacity of Haplic Chernozem, granular activated carbon and biochar in relation to BaP from water solution. Laboratory experiments with different initial BaP concentrations in the liquid phase and different ratios of the solid and liquid phases show that Freundlich model describes well the adsorption isotherms of BaP by the soil and both sorbents. Moreover, the BaP isotherm sorption by the Haplic Chernozem is better illustrated by the Freundlich model than the Langmuir equation. The results reveal that the sorption capacity of the carbonaceous adsorbents at a ratio 1:20 (solid to liquid phases) is orders of magnitude higher (13 368 ng mL^-1 of activated carbon and 3 578 ng mL^-1 of biochar) compared to the soil (57.8 ng mL^-1). At the ratio of 0.5:20, the adsorption capacity of the carbonaceous sorbents was 17-45 times higher than that of the soil. This is due to the higher pore volume and specific surface area of the carbonaceous sorbents than soil particles, assessed through scanning electron microscopy. The sorption kinetic of BaP by Chernozem was compared with the adsorption kinetics by the carbonaceous sorbents. Results indicate that the adsorption dynamic involves two steps. The first one is associated with a fast BaP adsorption on the large available surface and inside macro- and meso-pores of the sorbent particles of the granular activated carbon and biochar. Then, the adsorption is followed by a slower process of BaP penetration into the microporous space and/or redistribution into a hydrophobic fraction. The effectiveness of the sorption process depends on both the sorbent properties and the solvent competition. Overall, the granular activated carbon and biochar are highly effective adsorbents for BaP, whereas the Haplic Chernozem has a rather limited capacity to remove BaP from contaminated solutions.

Multi-Objective Optimization Tuning Framework for Kinetic Parameter Selection and Estimation

Semi-mechanistic kinetic (i.e., dynamic) models based on first principles are particularly relevant in biology, as they can explain and predict functional behavior that arises from varying concentrations of the cellular components over time. Here, we describe a computational tuning framework to facilitate both the selection of kinetic parameters for these models and its estimation from experimental data. On the one hand, the tuning framework uses multi-objective optimization to generate a model-based set of guidelines for the selection of the kinetic parameters. These parameter values are the required ones to provide a biological system with desired behavior, while fulfilling the design criteria encoded in the optimization problem itself. On the other hand, this framework can also be used to estimate the parameter values of biological systems from experimental data, once the optimization objectives had been defined appropriately. The methodology gives accurate identification results, as it provides clear orientation on the effect of the parameter values over the system's behavior even under different experimental scenarios. It is particularly useful for easily combining time-course-averaged data and steady-state distribution data. This protocol also addresses aspects related to the appropriate description of the kinetic models and the settings of the software tools. Therefore, it supplies for hands-on testing to evaluate the validity of the underlying technical assumptions of the biological kinetic models.

Effect of pepper (Zanthoxylum bungeanum Maxim.) essential oil on quality changes in rabbit meat patty during chilled storage

In this paper, the components of Zanthoxylum bungeanum Maxim. essential oil (ZBMEO) were analyzed. The efficacy of different concentrations of ZBMEO on the change in physical and chemical indicators of the rabbit meat patty was evaluated. Furthermore, kinetics models were employed to calculate the lipid oxidation induction period and microbial growth lag time. GC-MS analysis revealed that the major chemical components in ZBMEO included linalool, limonene, and sabinene. Results of the storage experiment indicated that ZBMEO had a good inhibition effect on lipid and protein oxidation, microbial growth, and formation of TVB-N, as well as slowed down the rate of change in color and pH during the 12 days storage time of rabbit meat. The models showed that adding ZBMEO could delay the lipid oxidation induction period, and extend the microbial growth lag time. Overall data showed that ZBMEO is a promising natural additive to maintain the quality of rabbit meat patty.

Automatic Assembly and Calibration of Models of Enzymatic Reactions Based on Ordinary Differential Equations

Enzymatic reactions have been studied for more than a 100 years. Indeed, isolation of enzymes from biological materials is no longer the main source of enzymes today, as they are now largely produced using recombinant technology, or can even be synthesized from scratch. Studies of the three-dimensional structures of enzymes can provide answers to many questions, but the kinetics of enzymatic reactions is the only method that can lead to better understanding of their function. The complexity of high-throughput analysis of progress curves of data obtained can only be achieved through numerical solutions of a suitable system of ordinary differential equations. We have developed the freely available server ENZO: a web tool for derivation and evaluation of kinetic models of enzyme-catalyzed reactions ( http://enzo.cmm.ki.si/ ). ENZO can be used for simultaneous analysis of a series of progress curves obtained under many different conditions. In this chapter, we exemplify the principles and possibilities of this type of high-throughput analysis.

From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications

Fake news spreading, with the aim of manipulating individuals' perceptions of facts, is now recognized as a major problem in many democratic societies. Yet, to date, little has been understood about how fake news spreads on social networks, what the influence of the education level of individuals is, when fake news is effective in influencing public opinion, and what interventions might be successful in mitigating their effect. In this paper, starting from the recently introduced kinetic multi-agent model with competence by the first two authors, we propose to derive reduced-order models through the notion of social closure in the mean-field approximation that has its roots in the classical hydrodynamic closure of kinetic theory. This approach allows to obtain simplified models in which the competence and learning of the agents maintain their role in the dynamics and, at the same time, the structure of such models is more suitable to be interfaced with data-driven applications. Examples of different Twitter-based test cases are described and discussed.

Adsorption studies of molybdate(VI)-99Mo onto nano zirconium hydroxide gel

Zr(OH)₄ gels have been prepared by sol-gel method using isoamyl alcohol/ammonia mixture of different concentrations. The nano Zr(OH)₄ gel obtained using 80% isoamyl alcohol and diluted ammonia (6%) gave the highest ⁹⁹Mo distribution coefficient. SEM images indicated a jelly-like appearance of the optimum Zr(OH)₄ gel. XRD analysis proved that Zr(OH)₄ gel is an amorphous material. HRTEM analysis indicated a particle size of ≤100 nm with the existence of particle aggregates. According to DLS studies, the hydrodynamic diameter was found to be 78.82 nm (with a mean number percentage of 21.1%), while zeta potential was found to be 29.2 mV N₂ adsorption/desorption chromatographic analysis calculations stated a BET surface area of 151 m²/g and an average pore diameter of 1.93 nm. Molybdate(VI)-⁹⁹Mo adsorption process onto the optimum Zr(OH)₄ gel was found to follow pseudo 2nd order and (to some extent) film diffusion mass transfer kinetic models. The adsorption isotherm was found to follow Langmuir model. From kinetic and adsorption isotherm studies it could be determined that the optimum Zr(OH)₄ gel has E_a, ΔH° and ΔS° values of 31.29, 50 and 0.185 kJ/mol, respectively, in addition to ΔG° values of -5.09, -7.86 and -11.56 kJ/mol at 25, 40 and 60 °C, respectively. Static molybdate(VI)-⁹⁹Mo capacity (determined from Langmuir adsorption model) was found to be 292.4, 333.3 and 357.1 mg/g at 25, 40 and 60 °C, respectively, while dynamic capacity was found to be 134.3 mg/g at 25 °C.

Ultrasound assisted modulation of yeast growth and inactivation kinetics

The yeast Saccharomyces cerevisiae is well known for its application in the food industry for the purpose of developing fermented food. The ultrasound (US) technology offer a wide range of applications for the food industry, including the enhancement of fermentation rates and inactivation of microbial cells. However, a better understanding and standardization of this technology is still required to ensure the scaling-up process. This study investigated the effect of the US technology on the growth of S. cerevisiae using frequencies of 20, 25, 45 and 130 kHz, treatment periods from 2 to 30 min. Furthermore, yeast kinetics subjected to US treatments were evaluated using modelling tools and scanning electron microscopy (SEM) analysis to explore the impact of sonication on yeast cells. Yeast growth was monitored after different US treatments plotting optical density (OD) at 660 nm for 24 h at 30 ⁰C. Growth curves were fitted using models of modified Gompertz and Scale-Free which showed good parameters of the fit. In particular, US frequencies of 45 and 130 kHz did not have a disruptive effect in lag phase and growth rate of the yeast populations, unlike the frequency of 20 kHz. Moreover, inactivation curves of yeast cells obtained after exposure to 20 and 25 kHz also observed the best fit using the Weibull model. US frequency of 20 kHz achieved significant reductions of 1.3 log cfu/mL in yeast concentration and also induced important cell damage on the external structures of S. cerevisiae. In conclusion, the present study demonstrated the significant effect of applying different US frequencies on the yeast growth for potential application in the food industry.

Synthesis of low-cost bentonite/Duranta erecta's fruit powder imbedded alginate beads and its application in surfactant removal

High industrialization and improved medical facilities are deteriorating aquatic bodies through untreated effluents. This study is aimed to design and characterize the bentonite, Duranta erecta, and their hybrid-alginate beads for the removal of cetyltrimethylammonium bromide (CTAB) from its aqueous solution. D. erecta's seed powder was treated by using a sonochemical method and embedded into alginate beads. All designed beads were characterized by using physicochemical methods, Fourier-transform infrared (FTIR) spectroscopy, and X-ray diffraction (XRD) technique. Hybrid beads were found to form an appropriate hydrogel structure with maximum surface area per unit gram (544 cm² g^-1), 0.42 mg dry weight, and 2.70 mm diameter. Kinetics and intraparticle diffusion models were fitted where involvement of both chemisorption and intraparticle diffusion was observed during the initial 30 and post-30-min phase, respectively. Thermodynamic studies corroborated the spontaneity of the CTAB adsorption process. Bentonite alginate beads showed the highest adsorption capacity of 97.06 mg g^-1 in 100 mg L^-1 CTAB solution at optimized conditions, while hybrid-alginate beads showed excellent efficiency with a wide range of physicochemical conditions frame. Conclusively, designed beads can be used to remove the surfactant, i.e., CTAB, from industrial waste effluents for the betterment of water reservoirs.

Enhanced anaerobic digestion of swine manure via a coupled microbial electrolysis cell

Microbial electrolysis cell coupled anaerobic digestion (MEC-AD) is a new technology in energy recovery and waste treatment, which could be used to recycle swine manure. Here, different applied voltage effects were studied using MEC-AD with swine manure as a substrate. The maximum cumulative biogas and methane yields, both occurring with 0.9 V, were 547.3 mL/g total solid (TS) and 347.7 mL/g TS, respectively. The increased energy can counterbalance the electrical input. First order, logistic, gompertz, and back-propagation artificial neural network (BP-ANN) models were used to study cumulative biogas and methane yields. The BP-ANN model was superior to the other three models. The maximum degradation rate of hemicellulose, cellulose, and lignin was 60.97%, 48.59%, and 31.59% at 0.9 V, respectively. The BP-ANN model establishes a model for cumulative biogas and methane yields using MEC-AD. Thus, MEC-AD enhanced biogas and methane production and accelerated substrate degradation at a suitable voltage.

Photocatalytic removal of bentazon by copper doped zinc oxide nanorods: Reaction pathways and toxicity studies

In this study, bentazon herbicide was degraded photocatalytically by copper doped zinc oxide nanorods fabricated by using a facile co-precipitation method. The crystal structure, morphology, surface composition, functional groups on the surface and valence state of the nanorods were investigated by XRD, SEM-EDX, FTIR, and XPS material characterization techniques. Environmental parameters including solution pH, catalyst dose, bentazon concentration, purging gases, H₂O₂ content, organic compound type and reusability affecting the rate of photocatalytic degradation of bentazon were evaluated. Under the optimal conditions, [Bentazon]₀ = 20 mg L^-1, Cu-ZnO loading = 0.5 g L^-1, H₂O₂ = 2 mM, pH = 7 and in the presence of oxygen gas, 100% of the herbicide was removed within 60 min. By raising bentazon concentration (10-50 mg L^-1), k_obs decreased to values between 0.14 and 0.006 min^-1 and the calculated electrical energy per order (E_Eo) increased from 38.16 to 727.27 (kWh m^-3), respectively. The degradation removal of the herbicide using the UV/Cu-ZnO method (98.28%) was higher than that of the UV/ZnO method (32.14%) process. Interestingly, the photocatalytic performances in the first and fifth reuse cycles during catalyst recyclability tests were found to be similar. Generally, the efficacy of the method in the decomposition of bentazon in drinking water (78.95%) and actual sewage (46.77%) declined because of the presence of other anions due to their role as a scavenger of photogenerated reactive species. Intermediate products in the photocatalytic degradation of bentazon identified by gas chromatography/mass spectrometry (GC/MS) analysis were 2-amino-N-isopropyl-benzamide, 2-amino-benzoic acid, N-isopropyl-2-nitro-benzamide, and acids such as pentenedioic acid, oxalic acid and propenoic acid. Furthermore, the main mechanism for the photocatalytic removal of bentazon was determined to be via attack by hydroxyl radicals (^•OH). The results of toxicity in the photocatalytic removal of bentazon by D. magna showed LC₅₀ and toxicity unit (TU) 48 h equal to 46.10 and 9.56 vol percent.

Kinetic analysis and modeling of L-valine production in fermentation batch from E. coli using glucose, lactose and whey as carbon sources

In this study the effect of the carbon source on L-valine production kinetics using genetically modified E. coli was researched. Glucose, lactose, Whey (W) and deproteinized whey (DW) were tested as carbon sources, keeping the carbon/nitrogen (C/N) ratio constant. Biomass generation and substrate consumption were modeled with Contois and Mass Conservation models, respectively, whereas Mass Conservation Balance and Luedeking-Piret models were used for product obtaining. Results showed that L-valine production is partially associated to growth, with values of 0.485 g L-valine/(g dry cell weight.h), and a product loss effect at a specific rate (β) of 0.019 g L-valine/(g dry cell weight.h) with W. The yield of this product increased 36 % using W concerning glucose or lactose as carbon sources. On the other hand, Mass Balance and Luedeking-Piret models adjust properly to experimental data (R2 >0.90). In conclusion whey is a promising substrate for obtaining L-valine using genetically-modified E. coli.

Advances in flux balance analysis by integrating machine learning and mechanism-based models

The availability of multi-omics data sets and genome-scale metabolic models for various organisms provide a platform for modeling and analyzing genotype-to-phenotype relationships. Flux balance analysis is the main tool for predicting flux distributions in genome-scale metabolic models and various data-integrative approaches enable modeling context-specific network behavior. Due to its linear nature, this optimization framework is readily scalable to multi-tissue or -organ and even multi-organism models. However, both data and model size can hamper a straightforward biological interpretation of the estimated fluxes. Moreover, flux balance analysis simulates metabolism at steady-state and thus, in its most basic form, does not consider kinetics or regulatory events. The integration of flux balance analysis with complementary data analysis and modeling techniques offers the potential to overcome these challenges. In particular machine learning approaches have emerged as the tool of choice for data reduction and selection of most important variables in big data sets. Kinetic models and formal languages can be used to simulate dynamic behavior. This review article provides an overview of integrative studies that combine flux balance analysis with machine learning approaches, kinetic models, such as physiology-based pharmacokinetic models, and formal graphical modeling languages, such as Petri nets. We discuss the mathematical aspects and biological applications of these integrated approaches and outline challenges and future perspectives.

The inhibitory effect of in situ extracellular polymeric substances on trimethoprim adsorption by activated sludge

The extracellular polymeric substances (EPS) of activated sludge are a mixture of high molecular weight polymers secreted by microorganisms, which are mainly composed of proteins, polysaccharides and humic substances. It is widely accepted that EPS have a good adsorption ability for pollutants with different functional groups. However, recent studies showed the EPS had an inhibitory effect on pollutant sorption, which is contradictory to previous viewpoint. Therefore, in this study, three types of activated sludge with different EPS contents and compositions were used to investigate the role of EPS in an antibiotic-trimethoprim (TMP) sorption process at environmentally relevant concentration. The in situ experiments results showed the adsorption capacity of activated sludge for TMP were increased from 2.98, 5.37 and 28.33 μg/g VSS to 7.87, 12.93 and 150.24 μg/g VSS in nitrifying activated sludge, wastewater treatment plant activated sludge and anaerobic ammonia-oxidized activated sludge, respectively after EPS extracted. The adsorption process can be well described by the pseudo-second-order kinetic model. Results of zeta potential, contact angles and infrared spectrum showed TMP replacing proteins embedded into the cell membrane enhancing the TMP adsorption capacity of activated sludge after EPS extraction. Our results demonstrated that less proteins in EPS of activated sludge is more beneficial for TMP adsorption removal.

Higher heating value, exergy, pyrolysis kinetics and thermodynamic analysis of ultrasound-assisted deep eutectic solvent pretreated watermelon rind biomass

The higher heating value (HHV) and exergy of ultrasound-assisted deep eutectic solvent pretreated watermelon rind (WMR) biomass were investigated. Thereafter, the co-pyrolysis of the WMR biomass and coal blends was studied. The pyrolysis kinetics and thermodynamic parameters of the WMR-coal blends were determined using four isoconversional models (Flynn-Wall-Ozawa, Kissinger-Akahira-Sunose, Friedman and Starink). The HHVs of the pretreated WMR ranged between 12.73 and 19.28 MJ/kg, while the exergy value for the raw and pretreated WMR were 16.08 and 21.55 MJ/kg, respectively. The lower heating value related exergy had the greatest influence on the overall exergy of the WMR. The values of the pre-exponential factor showed variations in wide range, and the change in entropy of the system displayed both negative and positive entropies. The activation energy and enthalpy varied directly with the amount of coal in the blends. Amongst the isoconversional model methods, Friedman model was the best predictor of the kinetic parameters.

Thermal degradation characteristics and gasification kinetics of camel manure using thermogravimetric analysis

In this work, the sustainable valorisation of camel manure has been studied using thermogravimetric analysis. The gasification tests were performed from ambient conditions to 950 °C at 10, 20, and 50 °C/min under an O₂ environment. The TGA data were applied to determine the kinetics of the O₂ gasification. Single-heating rate models (Arrhenius and Coats-Redfern) and multi-heating rate models (Distributed activation energy, Friedman, Flynn-Wall-Ozawa, Starink, and Kissinger-Akahira-Sunose) were applied to estimate the kinetics of the process. Between the two single-heating rate models, the Coats-Redfern method fitted best with the experimental data. Among the multi-heating rate models, the Flynn-Wall-Ozawa model fitted best with the experimental results. The kinetic parameters-frequency factor, activation energy, and order of reaction were estimated using the Flynn-Wall-Ozawa model (the best-fitting model) and the estimated kinetic parameters were used to calculate the thermodynamic properties-Gibbs free energy, enthalpy, and entropy. The information on these kinetic and thermodynamic properties can be useful for the design of gasifiers and for optimising the O₂ gasification operating conditions.

Thermal degradation characteristics and gasification kinetics of camel manure using thermogravimetric analysis

In this work, the sustainable valorisation of camel manure has been studied using thermogravimetric analysis. The gasification tests were performed from ambient conditions to 950 °C at 10, 20, and 50 °C/min under an O₂ environment. The TGA data were applied to determine the kinetics of the O₂ gasification. Single-heating rate models (Arrhenius and Coats-Redfern) and multi-heating rate models (Distributed activation energy, Friedman, Flynn-Wall-Ozawa, Starink, and Kissinger-Akahira-Sunose) were applied to estimate the kinetics of the process. Between the two single-heating rate models, the Coats-Redfern method fitted best with the experimental data. Among the multi-heating rate models, the Flynn-Wall-Ozawa model fitted best with the experimental results. The kinetic parameters-frequency factor, activation energy, and order of reaction were estimated using the Flynn-Wall-Ozawa model (the best-fitting model) and the estimated kinetic parameters were used to calculate the thermodynamic properties-Gibbs free energy, enthalpy, and entropy. The information on these kinetic and thermodynamic properties can be useful for the design of gasifiers and for optimising the O₂ gasification operating conditions.

Network Structured Kinetic Models of Social Interactions

The aim of this paper is to study the derivation of appropriate meso- and macroscopic models for interactions as appearing in social processes. There are two main characteristics the models take into account, namely a network structure of interactions, which we treat by an appropriate mesoscopic description, and a different role of interacting agents. The latter differs from interactions treated in classical statistical mechanics in the sense that the agents do not have symmetric roles, but there is rather an active and a passive agent. We will demonstrate how a certain form of kinetic equations can be obtained to describe such interactions at a mesoscopic level and moreover obtain macroscopic models from monokinetics solutions of those. The derivation naturally leads to systems of nonlocal reaction-diffusion equations (or in a suitable limit local versions thereof), which can explain spatial phase separation phenomena found to emerge from the microscopic interactions. We will highlight the approach in three examples, namely the evolution and coarsening of dialects in human language, the construction of social norms, and the spread of an epidemic.

Carbonaceous cathode materials for electro-Fenton technology: Mechanism, kinetics, recent advances, opportunities and challenges

Electro-Fenton (EF) technique has gained significant attention in recent years owing to its high efficiency and environmental compatibility for the degradation of organic pollutants and contaminants of emerging concern (CECs). The efficiency of an EF reaction relies primarily on the formation of hydrogen peroxide (H₂O₂) via 2e^─ oxygen reduction reaction (ORR) and the generation of hydroxyl radicals (^●OH). This could be achieved through an efficient cathode material which operates over a wide pH range (pH 3-9). Herein, the current progresses on the advancements of carbonaceous cathode materials for EF reactions are comprehensively reviewed. The insights of various materials such as, activated carbon fibres (ACFs), carbon/graphite felt (CF/GF), carbon nanotubes (CNTs), graphene, carbon aerogels (CAs), ordered mesoporous carbon (OMCs), etc. are discussed inclusively. Transition metals and hetero atoms were used as dopants to enhance the efficiency of homogeneous and heterogeneous EF reactions. Iron-functionalized cathodes widened the working pH window (pH 1-9) and limited the energy consumption. The mechanism, reactor configuration, and kinetic models, are explained. Techno economic analysis of the EF reaction revealed that the anode and the raw materials contributed significantly to the overall cost. It is concluded that most reactions follow pseudo-first order kinetics and rotating cathodes provide the best H₂O₂ production efficiency in lab scale. The challenges, future prospects and commercialization of EF reaction for wastewater treatment are also discussed.

Simultaneous removal of ammonium nitrogen, dissolved chemical oxygen demand and color from sanitary landfill leachate using natural zeolite

In this study, natural zeolite with maximum adsorption capacity of 3.59 mg g^-1 was used for the simultaneous removal of ammonium nitrogen (NH₄⁺-N), dissolved chemical oxygen demand (d-COD) and color from raw sanitary landfill leachate (SLL). Saturation, desorption and regeneration tests of zeolite were performed. Optimum adsorption conditions were found for particle size 0.930 µm, stirring rate of 1.18 m s^-1, zeolite dosage of 133 g L^-1 and pH 8. NH₄⁺-N removal efficiency reached 51.63 ± 0.80% within 2.5 min of contact. NH₄⁺-N adsorption follows mostly the linear pseudo-second order model, with intra-particle diffusion. NH₄⁺-N desorption follows the linear pseudo-second order model. Adsorption data fitted to the Temkin Isotherm in linear and nonlinear forms. Saturation tests showed that zeolite can be efficiently used in three successive adsorption cycles. NH₄⁺-N release from the saturated zeolite was not completely reversible, suggesting that the zeolite may be used as slow ΝΗ₄⁺-Ν releasing fertilizer and an attractive low cost material for the treatment of SLL. NH₄⁺-N removal with the regenerated zeolite exceeded 40% of the initial concentration in the fluid within 2.5 min. SEM analysis showed significant changes through saturation and regeneration. XPS revealed that adsorption of ΝΗ₄⁺-Ν to the zeolite was accompanied by ion exchange.

Fabrication of sand-based novel adsorbents embedded with biochar or binding agents via calcite precipitation for sulfathiazole scavenging

Fabrication of efficient and low-cost adsorbents through enzyme induced carbonate precipitation (EICP) of sand embedded with binding agents for sulfathiazole (STZ) removal is reported for the first time. Sand enriched with biochar (300 °C, 500 °C, and 700 °C), xanthan gum, guar gum, bentonite, or sodium alginate (1% w/w ratios) was cemented via EICP technique. Enrichment with binding agents decreased the unconfined compressive strength, improved the porosity, and induced functional groups. Biochar enrichment reduced the pH, and increased the calcite contents and electrical conductivity. Fixed-bed column adsorption trials revealed that biochars enrichment resulted in the highest STZ removal (64.7-87.9%) from water at initial STZ concentration of 50 mg L^-1, than the adsorbents enriched with other binding agents. Yoon-Nelson and Thomas kinetic models were fitted well to the adsorption data (R² = 0.91-0.98). The adsorbents embedded with 700 °C biochar (BC7) exhibited the highest Yoon-Nelson rate constants (0.087 L min^-1), 50% breakthrough time (58.056 min), and Thomas model-predicted maximum adsorption capacity (4.925 mg g^-1). Overall, BC7 removed 168% higher STZ from water than pristine cemented sand. Post-adsorption XRD and FTIR analyses suggested the binding of STZ onto the adsorbents. π-π electron-donor-acceptor interactions, aided-by electrostatic interactions and H-bonding were the main STZ adsorption mechanisms.

Inorganic arsenic species removal from water using bone char: A detailed study on adsorption kinetic and isotherm models using error functions analysis

The removal of inorganic arsenic (As) species from water using bone char pyrolyzed at 900 °C was investigated. Results revealed that the Sips model resulted in the best As(III) experimental data fit, while As(V) data were best represented by the Langmuir model. The adsorption rate and mechanisms of both As species were investigated using kinetic and diffusional models, respectively. At low As(III) and As(V) concentrations of 0.5 and 2.5 mg/L, the removal was due to intra-particle interactions and pore diffusion following Pseudo-first-order kinetics. However, at higher concentrations of 5 and 10 mg/L, the pore diffusion mechanism was ineffective, and the adsorption was best described by Pseudo-second-order and Elovich models. The goodness of the fit of linearized and nonlinear forms of all models against experimental data was thoroughly tested using error function analysis. Nonlinear regressions produced lower error values, so they were utilized to calculate the parameters of the models. The changes in bone char surface chemistry were examined using FTIR and Energy-dispersive X-ray spectroscopy (EDS). Arsenic oxide and complexes with metals were the confirmed immobilized forms of As on the bone-char surface. To the authors' knowledge, this study is the first attempt at As(III) adsorption analysis using bone char.