The objective of this article is to investigate the impacts of thermo-diffusion effect on unsteady axisymmetric Casson flow over a time-dependent radially stretching sheet with a multi-slip parameter and the force of chemical reaction. We employed an established similarity transformation to this non-linear partial differential system to convert it into a system of ordinary differential equations. The numerical results are attained for this system by using KELLER-BOX implicit finite difference scheme. It has great reliability and accuracy even a very short time period for computational simulation. The impacts of influential flow parameters on fluid flow are sketched through graphs and the numerical results are thoroughly argued. The temperature, velocity and wall concentration control parameters are analyzed. (i) It is witnessed that chemical reaction is not favorable to enhance the velocity profile. (ii) Multi-slip parameters vary inversely with velocity profile. (iii) The fluid concen... [more]

The pathogenesis of Parkinson’s disease (PD) is closely associated with the aggregation of α-synuclein (αS) protein. Finding the effective inhibitors of αS aggregation has been considered as the primary therapeutic strategy for PD. Recent studies reported that two neurotransmitters, dopamine (DA) and norepinephrine (NE), can effectively inhibit αS aggregation and disrupt the preformed αS fibrils. However, the atomistic details of αS-DA/NE interaction remain unclear. Here, using molecular dynamics simulations, we investigated the binding behavior of DA/NE molecules and their structural influence on αS44−96 (Greek-key-like core of full length αS) protofibrillar tetramer. Our results showed that DA/NE molecules destabilize αS protofibrillar tetramer by disrupting the β-sheet structure and destroying the intra- and inter-peptide E46−K80 salt bridges, and they can also destroy the inter-chain backbone hydrogen bonds. Three binding sites were identified for both DA and NE molecules interacti... [more]

Solid waste management needs re-evaluating in developing countries like Pakistan, which currently employs landfilling as a first option. Over time, increasing population will result in decreasing space for landfill sites, ultimately increasing the cost of landfilling, while increasing accumulated waste will cause pollution. Locating and preparing a sanitary landfill includes the securing of large sectors and also everyday activity with the end goal to limit potential negative impacts. Energy production from municipal solid waste (MSW) is a perceptive idea for large cities, such as Karachi, as waste, which is an undesirable output that adds to land and air pollution, is transformed into a vital source of energy. The current study strives to provide a destination to solid waste by evaluating the energy potential that waste provides for power generation by the process of incineration. A sustainable energy generation plant based on the Rankine cycle is proposed. This study evaluates the va... [more]

Fed-batch enzymatic hydrolysis has the potential to improve the overall process of converting cellulosic biomass into ethanol. This paper utilizes a process simulation approach to identify and quantify techno-economic differences between batch and fed-batch enzymatic hydrolysis in cellulosic ethanol production. The entire process of converting corn stover into ethanol was simulated using SuperPro Designer simulation software. The analysis was conducted for a plant capacity of 2000 metric tons of dry biomass per day. A literature review was used to identify baseline parameters for the process. The sensitivity of the ethanol production cost to changes in sugar conversion efficiency, plant capacity, biomass cost, power cost, labor cost, and enzyme cost was evaluated using the process simulation. For the base scenario, the ethanol unit production cost was approximately $0.10/gallon lower for fed-batch hydrolysis. The greatest differences were seen in facilities costs, labor costs, and capi... [more]

An equilibrium model is applied to study the effect of forced temperature gradients introduced through heat exchange via specific segments of the wall of a chromatographic column operating with a liquid mobile phase. For illustration of the principle, the column is divided into two segments in such a manner that the first segment is kept at a fixed reference temperature, while the temperature of the second segment can be changed stepwise through fixed heating or cooling over the column wall to modulate the migration speeds of the solute concentration profiles. The method of characteristics is used to obtain the solution trajectories analytically. It is demonstrated that appropriate heating or cooling in the second segment can accelerate or decelerate the specific concentration profiles in order to improve certain performance criteria. The results obtained verify that the proposed analysis is well suited to evaluate the application of forced segmented temperature gradients. The suggeste... [more]

Wind and other renewable energy protects the ecological environment and improves economic efficiency. However, it is difficult to accurately predict wind power because of the randomness and volatility of wind. This paper proposes a new parallel heterogeneous model to predict the wind power. Parallel meta-heuristic saves computation time and improves solution quality. Four communication strategies, which include ranking, combination, dynamic change and hybrid, are introduced to balance exploration and exploitation. The dynamic change strategy is to dynamically increase or decrease the members of subgroup to keep the diversity of the population. The benchmark functions show that the algorithms have excellent performance in exploration and exploitation. In the end, they are applied to successfully realize the prediction for wind power by training the parameters of the neural network.

The enzyme-assisted aqueous extraction process (EAEP) is an environmentally friendly strategy that simultaneously extracts oil and protein from several food matrices. The aim of this study was to investigate the effects of pH (6.5−9.5), temperature (45−55 °C), solids-to-liquid ratio (SLR) (1:12−1:8), and amount of enzyme (0.5−1.0%) on the extraction and separation of oil and protein from almond flour using a fractional factorial design. Oil and protein extraction yields from 61 to 75% and 64 to 79% were achieved, respectively. Experimental conditions resulting in higher extractability were subsequently replicated for validation of the observed effects. Oil and protein extraction yields of 75 and 72% were achieved under optimized extraction conditions (pH 9.0, 50 °C, 1:10 SLR, 0.5% (w/w) of enzyme, 60 min). Although the use of enzyme during the extraction did not lead to significant increase in extraction yields, it did impact the extracted protein functionality. The use of enzyme and a... [more]

Accurately predicting wind power is crucial for the large-scale grid-connected of wind power and the increase of wind power absorption proportion. To improve the forecasting accuracy of wind power, a hybrid forecasting model using data preprocessing strategy and improved extreme learning machine with kernel (KELM) is proposed, which mainly includes the following stages. Firstly, the Pearson correlation coefficient is calculated to determine the correlation degree between multiple factors of wind power to reduce data redundancy. Then, the complementary ensemble empirical mode decomposition (CEEMD) method is adopted to decompose the wind power time series to decrease the non-stationarity, the sample entropy (SE) theory is used to classify and reconstruct the subsequences to reduce the complexity of computation. Finally, the KELM optimized by harmony search (HS) algorithm is utilized to forecast each subsequence, and after integration processing, the forecasting results are obtained. The... [more]

A kinetic model for the dithiolactone-mediated radical polymerization of vinyl monomers based on the persistent radical effect and reversible addition (negligible fragmentation) was used to calculate the polymerization rate and describe molar mass development in the polymerization of methyl methacrylate at 60 °C, using 2,2-azobisisobutyronitrile (AIBN) as an initiator, as well as dihydro-5-phenyl-2(3H)-thiophenethione (DTL1) and dihydro-2(3H)-thiophenethione (DTL2) as controllers. The model was implemented in the PREDICI commercial software. A good agreement between experimental data and model predictions was obtained.

The whole plant of Vernonia mespilifolia is widely used as a traditional remedy for obesity in South Africa. The aim of this study was to investigate the anti-obesity and cytotoxic effects of Vernonia mespilifolia extracts in vitro. The α-amylase, α-glucosidase, and lipase inhibitory activities of aqueous and ethanol extracts of Vernonia mespilifolia were investigated, while the cytotoxic effects of these extracts were analyzed using Hoechst 33342 and propidium iodide (PI) dual staining on a human cervical HeLa cell line. The results showed that the LC50 (the concentration of a material will kill 50% of test organisms) values of aqueous and ethanol extracts of Vernonia mespilifolia were >200 and 149 µg/mL, respectively, to HeLa cells. Additionally, the ethanol extract exhibited the strongest inhibitory effect on the pancreatic lipase (Half-maximal inhibitory concentration (IC50) = 331.16 µg/mL) and on α-amylase (IC50 = 781.72 µg/mL), while the aqueous extract has the strongest α-glucos... [more]

Models involving decision variables in both discrete and continuous domain spaces are prevalent in process design. Generalized Disjunctive Programming (GDP) has emerged as a modeling framework to explicitly represent the relationship between algebraic descriptions and the logical structure of a design problem. However, fewer formulation examples exist for GDP compared to the traditional Mixed-Integer Nonlinear Programming (MINLP) modeling approach. In this paper, we propose the use of GDP as a modeling tool to organize model variants that arise due to characterization of different sections of an end-to-end process at different detail levels. We present an illustrative case study to demonstrate GDP usage for the generation of model variants catered to process synthesis integrated with purchasing and sales decisions in a techno-economic analysis. We also show how this GDP model can be used as part of a hierarchical decomposition scheme. These examples demonstrate how GDP can serve as a u... [more]

Symmetry in mathematical optimization may create multiple, equivalent solutions. In nonconvex optimization, symmetry can negatively affect algorithm performance, e.g., of branch-and-bound when symmetry induces many equivalent branches. This paper develops detection methods for symmetry groups in quadratically-constrained quadratic optimization problems. Representing the optimization problem with adjacency matrices, we use graph theory to transform the adjacency matrices into binary layered graphs. We enter the binary layered graphs into the software package nauty that generates important symmetric properties of the original problem. Symmetry pattern knowledge motivates a discretization pattern that we use to reduce computation time for an approximation of the point packing problem. This paper highlights the importance of detecting and classifying symmetry and shows that knowledge of this symmetry enables quick approximation of a highly symmetric optimization problem.

The extraction of phytochemical compounds from intact red sorghum grains was developed as an alternative process for producing bioactive material in the pharmaceutical industry. A mechanistic model is needed to better understand the process and enable predictive simulations for designing commercial-scale extraction systems. This paper presents a mathematical model for predicting phytochemical concentrations in the solvent and inside the pericarp of the grain at different positions during the extraction. The model is based on the mass transfer mechanism from inside the pericarp to its solid surface by diffusion, and then from the surface to a solvent during the extraction of bioactive compounds. It was numerically solved while using finite-difference approximation. The parameters considered were effective diffusivity inside the pericarp (Dep), mass transfer coefficient from the pericarp surface to the solvent (kc), and distribution coefficient (H). The model simulates the extraction per... [more]

Terrestrial ecosystem carbon storage plays an important role in mitigating global warming. Understanding the characteristics and drivers of changes in carbon storage can provide a scientific basis for urban planning and management. The objective of this study was to reveal the ways in which urbanization influences the spatial and temporal variations in carbon storage. In this study, we investigated the changes in carbon storage from 1990−2000, 2000−2010, and 2010−2018 in the Su-Xi-Chang region, which is a typical fast-growing urban agglomeration in China, based on the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. Moreover, we analyzed the impacts of urbanization-induced land-use changes on carbon storage. The results showed that in terms of space and time, the greatest loss of carbon storage occurred in developing urban areas and during the rapidly urbanizing stage. Our study revealed that the reduction in cultivated land was the greatest contributor to carbo... [more]

This study examined change in pore structure and microstructure of nanoporous carbon after surface oxidation and how it affects the adsorption performance of metronidazole antibiotics. The surface oxidation was performed by hydrogen peroxide at 60 °C. The properties of porous carbon were investigated by N2-sorption analysis (pore structure), scanning electron microscopy (surface morphology), the Boehm titration method (quantification of surface functional group), and Fourier transform infrared spectroscopy (type of surface functional group). The results showed that the oxidation of porous carbon by hydrogen peroxide has a minor defect in the carbon pore structure. Only a slight decrease in specific surface area (8%) from its original value (973 m2g−1) was seen but more mesoporosity was introduced. The oxidation of porous carbon with hydrogen peroxide modified the amount of oxide groups i.e., phenol, carboxylic acid and lactone. Moreover, in the application the oxidized carbon exhibited... [more]

Process capability indices (PCIs) have always been used to improve the quality of products and services. Traditional PCIs are based on the assumption that the data obtained from the quality characteristic (QC) under consideration are normally distributed. However, most data on manufacturing processes violate this assumption. Furthermore, the products and services of the manufacturing industry usually have more than one QC; these QCs are functionally correlated and, thus, should be evaluated together to evaluate the overall quality of a product. This study investigates and extends the existing multivariate non-normal PCIs. First, a multivariate non-normal PCI model from the literature is modeled and validated. An algorithm to generate non-normal multivariate data with the desired correlations is also modeled. Then, this model is extended using two different approaches that depend on the well-known Box−Cox and Johnson transformations. The skewness reduction is further improved by applyin... [more]

Companies in the field of the collection and treatment of waste cooking oils (WCO) for subsequent biodiesel production usually have to cope with high acidity oils, which cannot be directly transformed into fatty acid methyl esters due to soap production. Since glycerine is the main byproduct of biodiesel production, these high acidity oils could be esterified with the glycerine surplus to transform the free fatty acids (FFA) into triglycerides before performing the transesterification. In this work, commercial glycerol was esterified with commercial fatty acids and commercial fatty acid/lampante olive oil mixtures over tin (II) chloride. In the first set of experiments, the esterification of linoleic acid with glycerol excess from 20 to 80% molar over the stoichiometric was performed. From 20% glycerol excess, there was no improvement in FFA reduction. Using 20% glycerol excess, the performance of a biochar obtained from heavy metal-contaminated plant roots was compared to that of SnCl... [more]

With the increasing availability of large amounts of data, methods that fall under the term data science are becoming important assets for chemical engineers to use. Methods, broadly speaking, are needed to carry out three tasks, namely data management, statistical and machine learning and data visualization. While claims have been made that data science is essentially statistics, consideration of the three tasks previously mentioned make it clear that it is really broader than just statistics alone and furthermore, statistical methods from a data-poor era are likely insufficient. While there have been many successful applications of data science methodologies, there are still many challenges that must be addressed. For example, just because a dataset is large, does not necessarily mean it is meaningful or information rich. From an organizational point of view, a lack of domain knowledge and a lack of a trained workforce among other issues are cited as barriers for the successful imple... [more]

The sleeve regulating valve is widely used in the pipeline systems of process industries to control fluid flow. When flowing through the sleeve regulating valve, the water is easy to reach cavitation because of the pressure drop in the partial region, which may cause serious damage to pipeline system. In this paper, the pressure drop and cavitation characteristics in the sleeve regulating valve for different pressure differences and valve core displacements are investigated using a multiphase cavitation model. The pressure drop, velocity and vapor volume distribution in the regulating valves are obtained and analyzed. The total vapor volumes are also predicted and compared. The results show that the decrease of the valve core displacement induces the enlargement of the vapor distribution region and the increase of the vapor density. The increase of the pressure difference induces a more serious cavitation. The pressure difference has a slight influence on the cavitation intensity and d... [more]

The aerobic denitrifying phosphate accumulating bacteria (ADPB) use NO3− as an electron acceptor and remove nitrate by denitrification and concomitant uptake of excessive phosphorus in aerobic conditions. Activated sludge was collected from the A2O aerobic biological pool of the sewage treatment plant at Hezuo Town, Chengdu City. The candidate ADPB strains were obtained by cultivation in the enriched denitrification media, followed by repeated isolation and purification on bromothymol blue (BTB) solid plates. The obtained candidates were further screened for ADPB strains by phosphorus uptake experiment, nitrate reduction test, metachromatic granules staining, and poly-β-hydroxybutyrate (PHB) staining. The 16 sedimentation ribosome deoxyribonucleic acid (16 S rDNA) molecular technique was used to determine their taxonomy. Further, the denitrification and dephosphorization capacities of ADPB strains were ascertained through their growth characteristics in nitrogen-phosphorus-rich liquid... [more]

Carbon capture, utilization, and storage (CCUS) is one of the most effective technologies to reduce CO2 emissions and has attracted wide attention all over the world. This paper proposes a real option model to analyze the investment decisions of a coal-fired power plant on CCUS technologies under imperfect carbon emission trading schemes in China. Considering multiple uncertainties, which include carbon trading price volatility, carbon utilization revenue fluctuation, and changes in carbon transport and storage cost, the least squares Monte Carlo simulation method is used to solve the problems of path dependence. The research results show that the independent effects of carbon trading mechanisms on investment stimulation and emission reduction are limited. The utilization ratio of captured CO2 has significant impacts on the net present value and investment value of the CCUS project. Moreover, the investment threshold is highly sensitive to the utilization proportion of food grade CO2 w... [more]

Infections after bone reconstructive surgery become an authentic therapeutic and economic issue when it comes to a modern health care system. In general; infected bone defects are regarded as contraindications for bone grafting. Since the pathogens develop a biofilm on the inner surface of the bone; local delivery of antibiotics becomes more important. The present work focuses on the synthesis of Mesoporous Hydroxyapatite (MPHAP) loaded with drug Vancomycin (Van) and to investigate its loading and leaching ability in phosphate buffer solution (PBS), to be used for post-operative infections. The effect of pore size on MPHAP was analyzed using different fatty acids as organic modifiers. The impacts of various fatty acids chain length on the morphology and pore size were studied. A simple impregnation technique with optimized conditions ensured a high antibiotic loading (up to 0.476 + 0.0135 mg/mL), with a complete in vitro release obtained within 50 h.

The present research work deals with prediction of hydrogen consumption of a fuel cell in an energy storage system. Due to the fact that these kind of systems have a very nonlinear behaviour, the use of traditional techniques based on parametric models and other more sophisticated techniques such as soft computing methods, seems not to be accurate enough to generate good models of the system under study. Due to that, a hybrid intelligent system, based on clustering and regression techniques, has been developed and implemented to predict the necessary variation of the hydrogen flow consumption to satisfy the variation of demanded power to the fuel cell. In this research, a hybrid intelligent model was created and validated over a dataset from a fuel cell energy storage system. Obtained results validate the proposal, achieving better performance than other well-known classical regression methods, allowing us to predict the hydrogen consumption with a Mean Absolute Error (MAE) of 3.73... [more]

There are many interference components in Fourier amplitude spectrum of a contaminated fault signal, and thus the segment obtained based on the spectrum can lead to serious over-decomposition of empirical wavelet transform (EWT). Aiming to resolve the above problems, a novel method named improved empirical wavelet transform (IEWT) is proposed. Because the power spectrum is less sensitive to the contaminated interference and manifests the presence of fault feature information, IEWT replaces the Fourier amplitude spectrum of EWT with power spectrum in segment acquirement, and threshold processing is also introduced to eliminate the bad influence on the acquirement, and thus the best decomposition result of IEWT can be obtained based on feature energy ratio (FER). The loose slipper fault signal of hydraulic pump is tested and verified. The result demonstrates that the proposed method is superior and can extract the fault feature information accurately.

We characterize the long-term development of high-viscosity gas−liquid intermittent flows by means of a detrended fluctuation analysis (DFA). To this end, the pressures measured at different locations along an ad hoc experimental flow line are compared. We then analyze the relevant time-series to determine the evolution of the various kinds of intermittent flow patterns associated with the mixtures under consideration. Although no pattern transitions are observed in the presence of high-viscosity mixtures, we show that the dynamical attributes of each kind of intermittence evolves from one point to another within the transport system. The analysis indicates that the loss of a long-range correlation between the pressure responses are due to the discharge processes.