Sigmoidal Equation Research Articles

Microstructural influences on the damage evolution and kinetics of high temperature hydrogen attack in a C-0.5 Mo welded joint

In the refining industry, steels can be susceptible to a damage mechanism known as high temperature hydrogen attack (HTHA). The detection of damage in such structures through non destructive testing (NDT) requires insight into the damage development in various parts of welded joints. Once damage is detected, the tracking of the damage progression and estimation of remaining life is problematic. The performance of C-0.5 Mo steels in such environments is also variable, and the current tendency is to regard the HTHA resistance of C-0.5 Mo as similar to that of carbon steels. The current investigation explores the possibility of using high-temperature capsule strain-gauges for the in-situ evaluation of swelling – which generally accompanies HTHA in susceptible steels – and, thereby, evaluate the development and kinetics of HTHA damage for a C-0.5 Mo steel welded joint. Specimens were prepared representing the base metal (BM), the HAZ region, both fine-grained and coarse-grained, and the weld-metal (WM). The specimens were exposed to hydrogen at 200 bar at a temperature of 500 °C in an autoclave, with certain specimens fitted with high-temperature strain gauges; i.e. instrumented test labelled as IWM, IHAZ and IBM. Metallographic evaluation of the specimens – regarding the three locations mentioned – were performed; with exposure times reflecting both incipient and advanced damage. In the case of the base metal and the fine grained HAZ, and after pronounced damage, macrocracks were observed. The orientation and location of these cracks were aligned with the rolling direction, and the cracks were evident in the through-thickness plane of the plate. It was found that the reason for this observation was due to preferential damage accumulation within banded regions, where high concentrations of carbides were observed. A sigmoidal equation was developed that described the swelling kinetics of the HAZ. The expression of swelling-induced strain rate (SISR) versus time showed a low initial SISR until incipient damage is formed, followed by accelerated attack. The peak SISR was observed midway through the damage evolution, where after the SISRs decreased as the presense of carbides – that feed the methane reaction – diminishes. It is proposed that the attachment of the encapsulated strain gauges to structures or components where HTHA damage is suspected, will assist in the tracking of damage and the estimation of remaining life; if used in conjunction with the developed sigmoidal equation.

Solventless solid‐phase extraction using Zn ion‐imprinted polymer detected by colorimetric method

AbstractIon‐imprinted polymers attract a lot of attention and are actively studied because of easy preparation and their high selectivity. Zn is known to be essential mineral in human body; however, when it is absorbed into our body, it is hardly discharged completely and causes various disease or side effects. To suggest new method for selective Zn extraction, Zn ion‐imprinted polymer (ZIIP) was synthesized by bulk polymerization and NZIIP (non‐ZIIP) was prepared as a control. Then, ZIIP and NZIIP were characterized by Fourier‐transform infrared spectroscopy, Scanning electron microscope, and X‐ray photoelectron spectroscopy to investigate structural changes during polymerization. Adsorption isotherm studies indicated that sigmoidal Langmuir isotherm equation was fitted well and the maximum adsorption capacity and affinity of Zn on ZIIP was superior to NZIIP. Dithizone was used to chelate with Zn in supernatant for colorimetric determination. ZIIP‐solid‐phase extraction potentially used as Zn ion filter was investigated showing good removal efficiency.

Comparing basal area growth models for Norway spruce and Scots pine dominated stands

Models that predict forest development are essential for sustainable forest management. Constructing growth models via regression analysis or fitting a family of sigmoid equations to construct compatible growth and yield models are two ways these models can be developed. In this study, four species-specific models were developed and compared. A compatible growth and yield stand basal area model and a five-year stand basal area growth model were developed for Scots pine ( L.) and Norway spruce ( (L.) Karst.). The models were developed using data from permanent inventory plots from the Swedish national forest inventory and long-term experiments. The species-specific models were compared, using independent data from long-term experiments, with a stand basal area growth model currently used in the Swedish forest planning system Heureka (Elfving model). All new models had a good, relatively unbiased fit. There were no apparent differences between the models in their ability to predict basal area development, except for the slightly worse predictions for the Norway spruce growth model. The lack of difference in the model comparison showed that despite the simplicity of the compatible growth and yield models, these models could be recommended, especially when data availability is limited. Also, despite using more and newer data for model development in this study, the currently used Elfving model was equally good at predicting basal area. The lack of model difference indicate that future studies should instead focus on model development for heterogeneous forests which are common but lack in growth and yield modelling research.Pinus sylvestrisPicea abies

A constitutive equation for the kinetics of high temperature hydrogen attack and its use for structural life prediction

The damage due to high temperature hydrogen attack (HTHA) accumulates over time through the formation, growth, and coalescence of methane-filled cavities, followed by microcrack and macrocrack formation and presenting a threat to structural integrity. Early attempts at the prevention of this damage mechanism from occurring in steels in hydrogen service at high temperatures were based on the first publication of the Nelson Curves in 1949 but have not always been successful. The consequence of HTHA failures have often been disastrous and much work is currently being done with a view to better prediction of the course of the HTHA damage process and assessment of structural integrity in the face of HTHA. Current work coordinated by the WRC is based on the calculation of the dynamic methane pressure in grain boundary cavities, since the methane pressure provides the driving force for cavity growth and damage evolution. The WRC work makes use of a Methane Factor, α, which is material and microstructure specific. It also utilizes a concept of an “additional stress”, Δσ, due to the internal methane pressure.In this paper, high-temperature strain gauging was used on samples exposed to accelerated HTHA conditions in an autoclave. The strain gauges were applied to various zones of a C-0.5Mo welded joint in order to track the damage evolution in the base metal, HAZ and weld metal. Over time, the process of HTHA damage gave rise to steadily increasing strain due to the formation and growth of voids and the subsequent HTHA damage processes, up to a saturation point, beyond which the strain remained static. These curves were subsequently converted to Damage Fraction - Time curves, with the Damage Fraction ranging from 0 to 1, similar to the MPC-Omega creep curves used in API 579. It was found that the kinetics of HTHA damage evolution could be described by a single sigmoidal equation with different constants for the various weld zones and for different steels. The results of published strain-time curves for a carbon steel were similarly analyzed and similar findings were made.Analysis of the HTHA damage evolution rate vs time curves, indicate that the damage rate steadily increases with increasing time up to a maximum value, where after it decreases steadily up to the point where the damage rate is zero, at the end of the HTHA damage evolution process. The time corresponding to maximum damage evolution was generally found to be midway through the HTHA damage process. This behavior was attributed to the depletion of carbides with increasing damage evolution, resulting in declining damage rates at times beyond the time corresponding with the maximum damage rate. It is shown how the HTHA damage curves can be compared to experimentally determined or calculated creep damage curves in order to determine the “additional stress” and Methane Factor terms, used in the WRC HTHA structural integrity assessments. It was furthermore discussed how the kinetic equations formulated can be used in conjunction with the in-situ application of high-temperature strain gauges to various structural elements in HTHA service, can be used as an aid in HTHA life assessment.

An Adaptive Biosystems Engineering Approach towards Modeling the Soluble-to-Insoluble Phase Transition of Clofazimine.

Clofazimine (CFZ) is a weakly basic, small-molecule antibiotic used for the treatment of mycobacterial infections including leprosy and multidrug-resistant tuberculosis. Upon prolonged oral administration, CFZ precipitates and accumulates within macrophages throughout the host. To model the pharmacokinetics of CFZ, the volume of distribution (Vd) was considered as a varying parameter that increases with continuous drug loading. Fitting the time-dependent change in drug mass and concentration data obtained from CFZ-treated mice, we performed a quantitative analysis of the systemic disposition of the drug over a 20-week treatment period. The pharmacokinetics data were fitted using various classical compartmental models sampling serum and spleen concentration data into separate matrices. The models were constructed in NONMEM together with linear and nonlinear sigmoidal expansion functions to the spleen compartment to capture the phase transition in Vd. The different modeling approaches were compared by Akaike information criteria, observed and predicted concentration correlations, and graphically. Using the composite analysis of the modeling predictions, adaptive fractional CFZ sequestration, Vd and half-life were evaluated. When compared to standard compartmental models, an adaptive Vd model yielded a more accurate data fit of the drug concentrations in both the serum and spleen. Including a nonlinear sigmoidal equation into compartmental models captures the phase transition of drugs such as CFZ, greatly improving the prediction of population pharmacokinetics and yielding further insight into the mechanisms of drug disposition.

Determination of the asymmetric parameter in complementary relations of evaporation in alpine grasslands of the Tibetan Plateau

Complementary equations have been widely applied to evaporation (E) estimation in poorly monitored areas and under changing conditions. It is essential to determine a priori the key parameter called the asymmetric parameter (or land surface parameter in the sigmoid equation) b for predictive application of complementary equations. A previous study (Wang et al., 2020a) suggested ecosystem mean b values at the global scale, which, however, exhibit significant variation for specific ecosystem types, especially for grasslands. This brings a challenge for accurate estimation of E. In this study, taking the alpine grassland ecosystem on the Tibetan Plateau (TP) as an example, eddy covariance data from 10 EC monitoring sites across TP were used to investigate b and its control factors. Our results show that 1) b ranges from 0.48 to 2.56 with a mean value of 1.52 ± 0.65 (mean ± standard deviation) in alpine grasslands of the TP, and b is significantly correlated (R2 = 0.97, p-value < 0.01) with the mean annual surface soil water content, which results in an empirical formula to determine b; 2) the sigmoid generalized complementary equation aided by the estimated b exhibits a high efficiency of evaporation calculation with a mean Nash–Sutcliffe coefficient of 0.88 on the TP; and 3) a small perturbation in b could cause a high bias in the E estimation, especially in areas of low soil moisture. The proposed empirical formula to estimate b lays the foundation for accurate evaporation prediction on the TP under fast-changing conditions.

Modeling of the Kinetics of Strain‐Induced Martensite Transformation and the Transformation‐Induced Plasticity Effect in a Lean‐Alloyed Metastable Austenitic Stainless Steel

This article investigates the influence of temperature and strain on second‐phase transformation strengthening and the resulting mechanical properties in a lean AISI 301LN austenitic stainless steel within a temperature range of −60 to 180 °C. The volume fraction of martensite evolved is determined using nondestructive magnetic Ferritescope measurements that are adjusted by using a calibration factor of 1.7, which is established using the saturation magnetization measurements, X‐ray, and neutron diffraction measurements. The kinetics of strain‐induced martensite transformation (SIMT) as a function of strain and temperature is accurately described by a set of modified constitutive Boltzmann sigmoidal equations at temperatures below 75 °C. For this steel, the Md (30/50) temperature is determined as 61 °C. The absolute Md temperature is established as ≈109 °C, and no athermal transformation to martensite is observed upon cooling to −270 °C using cryogenic neutron diffraction facilities. Extended JMAK analysis of the transformation is used to shed light on the mechanism of martensitic transformation. It is found that the transformation‐induced plasticity (TRIP) effect due to SIMT is at a maximum at 75 °C, which is the maximum elongation temperature (MET) and calculations are performed regarding alloy development which will reduce the MET to room temperature.

355. A Novel Likelihood-Based Model to Estimate SARS-CoV-2 Viral Titer from Next-Generation Sequencing Data

BackgroundThe quantitative level of pathogens present in a host is a major driver of infectious disease (ID) state and outcome. However, the majority of ID diagnostics are qualitative. Next-generation sequencing (NGS) is an emerging ID diagnostics and research tool to provide insights, including tracking transmission, evolution, and identifying novel strains.MethodsWe built a novel likelihood-based computational method to leverage pathogen-specific genome-wide NGS data to detect SARS-CoV-2, profile genetic variants, and furthermore quantify levels of these pathogens. We used de-identified clinical specimens tested for SARS-CoV-2 using RT-PCR, SARS-CoV-2 NGS Assay (hybrid capture, Twist Bioscience), or ARTIC (amplicon-based) platform, and COVID-DX software. A training (n=87) and validation (n=22) set was selected to establish the strength of our quantification model. We fit non-uniform probabilistic error profiles to a deterministic sigmoidal equation that more realistically represents observed data and used likelihood maximized over several different read depths to improve accuracy over a wide range of values of viral load. Given the proportion of the genome covered at varying depths for a single sample as input data, our model estimated the Ct of that sample as the value that produces the maximum likelihood of generating the observed genome coverage data.ResultsThe model fit on 87 SARS-CoV-2 NGS Assay training samples produced a good fit to the 22 validation samples, with a coefficient of correlation (r2) of ~0.8. The accuracy of the model was high (mean absolute % error of ~10%, meaning our model is able to predict the Ct value of each sample within a margin of ±10% on average). Because of the nature of the commonly used ARTIC protocol, we found that all quantitative signals in this data were lost during PCR amplification and the model is not applicable for quantification of samples captured this way. The ability to model quantification is a major advantage of the SARS-CoV-2 NGS assay protocol.The likelihood-based model to estimate SARS-CoV-2 viral titer LeftObserved genome coverage (y-axis) plotted against Ct value (x-axis). The best-fitting logistic curve is demonstrated with a red line with shaded areas above and below representing the fitted error profile. RIGHT: Model-estimated Ct values (y-axis) compared to laboratory Ct values (x-axis) with grey bars representing estimated confidence intervals. The 1:1 diagonal is shown as a dotted line.ConclusionTo our knowledge, this is the first model to incorporate sequence data mapped across the genome of a pathogen to quantify the level of that pathogen in a clinical specimen. This has implications in ID diagnostics, research, and metagenomics.Disclosures Heather L. Wells, MPH, Biotia, Inc. (Consultant) Joseph Barrows, MS, Biotia (Employee) Mara Couto-Rodriguez, MS, Biotia (Employee) Xavier O. Jirau Serrano, B.S., Biotia (Employee) Marilyne Debieu, PhD, Biotia (Employee) Karen Wessel, PhD, Labor Zotz/Klimas (Employee) Christopher Mason, PhD, Biotia (Board Member, Advisor or Review Panel member, Shareholder) Dorottya Nagy-Szakal, MD PhD, Biotia Inc (Employee, Shareholder) Niamh B. O’Hara, PhD, Biotia (Board Member, Employee, Shareholder)

Baroreflex Curve Fitting Using a WYSIWYG Boltzmann Sigmoidal Equation.

Arterial baroreflex assessment using vasoactive substances enables investigators to collect data pairs over a wide range of blood pressures and reflex reactions. These data pairs relate intervals between heartbeats or sympathetic neural activity to blood pressure values. In an X-Y plot the data points scatter around a sigmoidal curve. After fitting the parameters of a sigmoidal function to the data, the graph’s characteristics represent a rather comprehensive quantitative reflex description. Variants of the 4-parameter Boltzmann sigmoidal equation are widely used for curve fitting. Unfortunately, their ‘slope parameters’ do not correspond to the graph’s actual slope which complicates the analysis and bears the risk of misreporting. We propose a modified Boltzmann sigmoidal function with preserved goodness of fit whose parameters are one-to-one equivalent to the sigmoidal curve’s characteristics.

Effect of pretreatments on refractance window drying, color kinetics and bioactive properties of white sweet cherries ( Prunus avium L. stark gold)

The aim of this study was to investigate the effects of different pretreatments (citric acid, sucrose and freezing) on the refractance window (RW) drying, color kinetics and bioactive properties of white sweet cherries. The shortest drying time (180 min) was obtained with freezing pretreatment (FP). The highest Deff was 2.38346 × 10–9 m2/s in FP. Cubic and Sigmoid equations were the best drying models for the control and FP, respectively. Furthermore, quadratic equation was the most appropriate color model for all sweet cherries. FP increased the total phenolic content (4.18 ± 0.86 mg gallic acid eq/g dry matter, DM) and antioxidant capacity (ferric reducing antioxidant power, FRAP) (13.17 ± 1.05 µmol trolox eq/g DM) of dried cherry, as compared to control and other pretreatments. Results indicated that citric acid and sucrose pretreatments (CAP and SP) were not much effective as freezing in cherry drying. This study showed that the combination of FP and RW drying can be an alternative drying for white sweet cherry. Practical applications White sweet cherry is a perishable seasonal fruit whose long term use is not possible during the off-season. Fresh sweet cherries are processed into various food products such as juice, vinegar, alcoholic drink or jam right after the collection from the field. However, other food sectors like bakery & pastry, chocolate, and dairy demand to reach to ingredients any time of the year, and this would be only possible to use the off-seasonal ingredients in dried form. White sweet cherry is one of the preferred ingredients because of its sweet taste, nutritious and bioactive contents. In order to meet the demand of those food sectors, the sweet cherry has been mostly dried using hot air technique; however, this research showed that the refractance window drying can be a good alternative to improve the product quality with the reduction in drying time and energy.

Methanesulfonic acid-mediated conversion of microalgae Scenedesmus obliquus biomass into levulinic acid

In this study, we produced levulinic acid (LA) from green microalgae Scenedesmus obliquus under a methanesulfonic acid (MSA)-mediated conversion. To optimize reaction condition and evaluate their reciprocal interactions of reaction factors, a statistical experimental approach with central composite design was used. By optimizing the reaction conditions, LA was formed at a yield of 40.74% based on total carbohydrate at 180 °C, 12.5% biomass, 1.875 M MSA (0.15 M MSA/1% biomass), and 40 min. The combined severity factor (CSF) evaluation showed that glucose formation matched the non-linear sigmoidal equation with high regression. However, the LA formation was matched to the non-linear model (exponential decay) with high regression. The highest LA was observed at CSF > 3.5. The availability of microalgae as biomass and MSA as a catalyst was proven for producing sugar and platform chemicals.

Determination method and strain-attribute interact in the calculation of precompression stress from soil compression curves

Determination of soil precompression stress (σp) from compression curves has markedly changed in recent decades, with several available methods of varying complexity. The graphical procedure proposed more than eight decades ago remains a standard, though it is now emulated by statistical and numerical procedures. We tested nine determination methods based on linear, polynomial, nonlinear and spline regressions. Four attributes were used to represent soil deformation during compression (strain-attributes): bulk density (ρb), void ratio (e), total porosity (ϕ) and strain (ε). Undisturbed soil samples equilibrated either at 10 or 100 kPa water tension were subjected to confined, drained uniaxial compression tests. The experimental factors (determination method, strain-attribute, and water tension) and their interaction affected the determination of σp. Sigmoid equations converged for 84%–95% of the compression curves, failing for samples at 100 kPa with with steep virgin compression lines. Methods based on fourth-degree polynomials resulted in 10-94% of the values outside the range 10–1550 kPa, depending on the strain-attribute. Although ε and e are linearly related, the former suits better the application of methods based on polynomial and spline regression, also fitting well for methods based on sigmoid equations with samples at 10 kPa. The bi-linear intersection methods presented relaistic σp values for bi-linear curves and should be solely applied to ρb. The spline method resulted in σp values clustered along the loads applied during the compression tests.

Smart Hydrogels: Preparation, Characterization, and Determination of Transition Points of Crosslinked N-Isopropyl Acrylamide/Acrylamide/Carboxylic Acids Polymers.

Smart hydrogels (SH) were prepared by thermal free radical polymerization of N-isopropyl acrylamide (NIPAAm), acrylamide (AAm) with acrylic acid (A) or maleic acid (M), and N,N′-methylene bisacrylamide. Spectroscopic and thermal characterizations of SHs were performed using FTIR, TGA, and DSC. To determine the effects of SHs on swelling characteristics, swelling studies were performed in different solvents, solutions, temperatures, pHs, and ionic strengths. In addition, cycle equilibrium swelling studies were carried out at different temperatures and pHs. The temperature and pH transition points of SHs are calculated using a sigmoidal equation. The pH transition points were calculated as 5.2 and 4.2 for SH-M and SH-A, respectively. The NIPAAm/AAm hydrogel exhibits a critical solution temperature (LCST) of 28.35 °C, while the SH-A and SH-M hydrogels exhibit the LCST of 34.215 °C and 28.798 °C, respectively, and the LCST of SH-A is close to the body. temperature. Commercial (CHSA) and blood human serum albumin (BHSA) were used to find the adsorption properties of biopolymers on SHs. SH-M was the most efficient SH, adsorbing 49% of CHSA while absorbing 16% of BHSA. In conclusion, the sigmoidal equation or Gaussian approach can be a useful tool for chemists, chemical engineers, polymer and plastics scientists to find the transition points of smart hydrogels.

Modeling the drying kinetics of alginate particles considering shrinkage

AbstractAlginate is an anionic and biodegradable biopolymer of natural occurrence, typically obtained from brown algae, being studied, and used in several applications in biomedicine and food industry by its low toxicity, low cost, and its gelification obtained by the addition of bivalent cations (Ca2+), besides being able to storage large amounts of liquid in its structure. In this context, this work aims to study the drying and shrinkage kinetics of this biomaterial. Microparticles of alginate were synthesized by the ionic gelification method using calcium chloride as reticulant agent. These microparticles were submitted to drying experiments conducted at 40, 50, and 60°C. A mathematical model which considers the microparticles moisture and volume change with time was proposed to model the drying process. Considering that the radius depends on time as Page and Sigmoid equations, two mathematical models were obtained. Both models were able to describe the experimental data and the kinetic parameters were adjusted as an exponential function of temperature (R2 = 0.99). The statistical analysis of the residues between calculated and experimental data indicates an adequate prediction, with Page's model fitting more accurately to the data sets. Akaike's test also indicated the coupled Page model as the most adequate.Practical ApplicationsThe results presented in this paper provide mathematical methods of modelling the hydration kinetics of alginate particles and fitting the parameters which can help understanding the mass transfer and shrinkage phenomena during drying. Those characteristics are essential in describing alginate particles due to the high amount of water that they contain. Describing the drying kinetics of such particles may help to project and optimize equipment involved in alginate particles production process.

Distinct Neuronal Excitability in the Paraventricular Nucleus of Hypothalamus after Baroreflex Challenge in Salt‐Loaded Rats

High salt intake is a determinant factor for hypertension in humans and animals’ models. Many studies indicate that the paraventricular hypothalamus (PVH) contributes to the regulation of body fluids homeostasis and neural control of circulation in salt-induced hypertension, with the involvement of the baroreflex function, as part of a hypothalamic-brainstem circuitry. Here, our aim was to evaluate the autonomic balance and the neuronal activity of PVH in response to baroreflex activation of animals subjected to high salt intake. Ethical protocols were approved by the Institutional Animal Care and Use Committee (n.127/2017) of the ICB/USP. Male Wistar rats (300-400 g) received a solution of NaCl 2% in replacement of the tap water (SALT) for 7 days, while the control (CT) received only tap water. On the sixth day, rats had femoral artery catheterized for monitoring of the MAP and HR, and the femoral vein to infusion of drugs. The next day, baroreflex function was evaluated by bolus injections of phenylephrine (PHE; 0.1-12,8 µg/Kg) and sodium nitroprusside (NPS: 0.2-25.6 µg/Kg)]. Sigmoidal logistic equation was used to analysis baroreflex function. The cardiac autonomic balance was evaluated with injection of muscarinic receptor antagonist (ATROP; methylatropine bromide; 2 mg/Kg) and 15 min later with beta-1-adrenergic receptor antagonist atenolol (ATN; 4 mg/Kg). The neuronal activity in the PVH was evaluated by the FOS expression during baroreflex function challenge [a ramp infusion PHE (18-22 µg/Kg/min)]. After 90 min the animals were euthanized, and brain tissue fixed for immunoperoxidase procedures, and subsequent cells counting analysis. Data were expressed as mean±SEM, analyzed by Student's t-test or ANOVA two-way (*P<0.05). Salt-loading elicited an increase in the MAP (SALT: 115±3 vs. CT: 109±3* mmHg, t-test, n=11) and HR (SALT: 406±10 vs. CT: 318±9* b/min, t-test, n=11) followed by an attenuation on the range of the baroreflex function (SALT: 169±14 vs. CT: 233±22* b/min, t-test, n=6). As for the autonomic balance salt-loaded rats have shown an increase in the sympathetic tonus (SALT: 104±11 vs. CT: 59±7* Δb/min, t-test, n=6), but no change in the parasympathetic tonus (SALT: -68±13 vs. CT: -48±11 Δb/min, t-test, n=6). The activation of the arterial baroreflex resulted in an increase in the number FOS neurons in the PVH in SALT group (SALT-PHE: 1,012±96*) compared to CT-PHE: 345±57, (ANOVA: *P<0,05, n=4), but no change among CT-PHE vs. CT-NOT-PHE neither SALT-NOT-PHE. The large number of FOS-positive neurons occurred in medial level of the PVH in the SALT group, specifically in the neuron clusters of the lateral magnocellular (90%), dorsal cap (83%), medial parvicellular (71%) and ventral part (66%) when compared to the other groups. Taken together, these results show that 7 days of high salt intake elicits hypertension, impairment of baroreflex function and increase in the sympathetic tone to the heart with activation of distinct neuronal populations in the PVN. The precise neuronal mechanisms involved in these responses are still under investigation.

Platform chemicals production from lipid-extracted Chlorella vulgaris through an eco-friendly catalyst

Microalgae are a widely available, renewable, and sustainable resource for bioenergy which may be used as a carbon-neutral alternative. We conducted hydrothermal conversion with MSA to obtain levulinic (LA) and formic acids (FA) from the lipid-extracted Chlorella vulgaris. Based on our analysis of reciprocal interactions between reaction conditions, maximum LA yields were obtained at high temperature, mid-range catalyst concentration, and mid-/long-range reaction time. Maximum FA yields were obtained at high temperature, high-range acid concentration, and short-/mid-range time. Using the Box-Behnken method to optimize the reaction, yields of 39.17% for LA and 20.19% for FA were obtained with 5% biomass, 0.5 M MSA at 195 °C for 35 min. Moreover, the effect of CSF on yield of LA and FA could be suitably represented by Sigmoidal equations with high R2. Overall, the application of lipid-extracted microalgae residue and eco-friendly MSA may prove useful for platform chemicals production.

A novel method to obtain solid–liquid equilibrium and eutectic points for hydrocarbon mixtures by using differential scanning calorimetry and numerical integration

Solid-liquid equilibrium (SLE) is essential for some separation processes in chemical industries. SLE for hydrocarbon mixtures, biofuels, phase change materials (PCM) or deep eutectic solvents (DES) are current topics in literature. Most common study involves binary systems and very often eutectic points are presented.A new method has been developed to determine the solid–liquid equilibrium and the eutectic compositions of hydrocarbon binary systems. Differential Scanning Calorimetry (DSC) and numerical integration are combined and only two DSC analyses are required. A deconvolution procedure with Asymmetric Double Sigmoidal (ADS) equation is proposed to analyse the peaks individually when the thermogram peaks overlap. The ADS equation produced the most accurate fit for five different DSC peaks.The new method was successfully validated against the conventional method by comparing fourteen samples from four eutectic binary systems (naphthalene/n-tetracosane, naphthalene/n-octacosane, p-xylene/n-hexadecane and n-octane/1-methyl-naphthalene).Uncertainty analysis carried out for the new method leads to SLE data errors of 0.612 K and 0.011 for temperature and mole fraction, respectively. The new method for the calculation of compositions, masses and eutectic points was applied for several samples of each system. The SLE and eutectic data obtained were compared with the conventional method, achieving standard deviations of 2.23 K and 0.04 for temperature and mole fraction, respectively. The new method can save at least a 50% of the experimental time and its associated resources compared to the conventional method.

Mathematical modeling applied to ruminal digestion and gas production in vitro

The ruminal digestion performed by ruminants is one of the essential and most important processes for the use of dietary nutrients. However, the use of mathematical models applied to digestion kinetics has been widely applied to provide prediction of animal performance, maximize the use of nutrients and reduce nutritional losses due to excreta and a reduction in the cost of animal production. In this context, it aimed to conduct a literature review on the use of mathematical models and to analyze comparisons of different models to predict ruminal digestion. The in vitro gas production technique provides direct measurement of the ruminal digestion rate associated with gas production and the respective gravimetric measurement of the food or diet under test. Nonlinear models are chosen to evaluate ruminal digestion due to a better interpretation of biological parameters, they produce exponential and sigmoidal growth equations. However, the most suitable model for evaluation depends on the type of food or diet. The two-compartment logistical model presents a better adjustment of the gas production curve, mainly for foods with a high proportion of fiber. Among this, single-compartment models can be well applied to evaluate the degradation kinetics of foods with low fibrous carbohydrate content. Therefore, the choice of the most appropriate model is up to the researcher to assess which model best suits the chemical-chemical composition of the food or diet.

Hydrothermal conversion of microalgae Chlorella sp. into 5-hydroxymethylfurfural and levulinic acid by metal sulfate catalyst

Microalgae are renewable, eco-friendly, and sustainable bioresources that have the potential to substitute fuels and chemicals originated fossil resources. The conversion of Chlorella sp. to obtain 5-hydroxymethylfurfural (5-HMF) and levulinic acid (LA) via thermochemical reaction with a metal-sulfate catalyst (Al2(SO4)3) is introduced here. The statistical approach is introduced to optimize the conversion conditions. By optimization of the 5-HMF yield, about 23.46% of 5-HMF was obtained under 5% biomass amount and 0.75 g-catalyst/g-biomass at 165 °C and 30 min; the highest LA yield of 32.89% was obtained under 2.5% biomass and 1.0 g-catalyst/g-biomass at 205 °C and 60 min. Furthermore, under such harsh temperature condition and high catalyst amount, the maximum 5-HMF yield of 31.46% was obtained at 0 min, which indicates the time required to attain the set reaction temperature. In the evaluation of the catalytic performance via relationship between combined severity factor and 5-HMF/LA, the yields of 5-HMF and LA were demonstrated to be reasonably satisfied for non-linear sigmoidal equations with high regression. Hence, the application of microalgae and metal-salt catalyst has high potential and accessibility in the production of platform chemicals.

Blood rheological and electrical properties and relationships with the microvascular tone regulation in patients with diabetes mellitus type 2

Aim. The study aims to evaluate impairment of the rheological and electrical properties of blood, plasma viscosity and blood conductivity in patients with type 2 diabetes mellitus (T2DM) in comparison with the data of the control group of healthy individuals. It also aims to investigate the changes of the skin blood flow responses to cold stress in T2DM patients through wavelet analysis of the peripheral skin temperature pulsations and to estimate their relationships with the blood viscosity and blood conductivity parameters, obtained from the simulation of experimental data with mathematical equations.Materials and methods. The whole blood viscosity was measured by Contraves LS30 viscometer (Switzerland) at a steady flow in 9 healthy individuals and in 13 patients with type 2 diabetes mellitus. Time variation of whole blood conductivity σ under transient flow at rectangular and trapezium shaped Couette viscometric flow and under electric field of 2 kHz was determined. The amplitudes of the skin temperature pulsations (ASTP) were monitored by «Microtest» device («FM-Diagnostics», Russia). To analyze the temperature fluctuations, wavelet transformation analysis of the low amplitude oscillations of skin temperature in accordance with myogenic (0.05–0.14 Hz), neurogenic (0.02–0.05 Hz), and endothelial (0.0095–0.02 Hz) control mechanisms of the vascular tone (WAST method) was applied.Results. Blood viscosity was increased in the T2DM patients’ group, while blood conductivity decreased in comparison to controls. Two sigmoidal equations were applied to describe the kinetics of blood conductivity. Both models include conductivity indices (σ1 , σ2 , σ3 ) and time indices too. The Pearson correlations between these parameters and the ASTP in the frequency ranges, corresponding to the myogenic, neurogenic and endothelial mechanisms of the microcirculation tone regulation were analyzed. The correlation analysis revealed good ASTP–(σ1 , σ2 , σ3 ) relationships in the neurogenic range 3 minutes after the cold test, while the ASTP–(σ1 , σ2 , σ3 ) correlation in the myogenic frequency range before the cold test was negative (r&lt;–0.8, p&lt;0.5).Conclusion. The results complement the studies of the microvascular regulatory mechanisms and endothelial dysfunction in patients with type 2 diabetes mellitus, as well as their relationships with the rheological and electrical properties of blood.