Anaerobic co-digestion (AcoD) is a widely employed technique to produce biogas from simultaneous digestion of various biomasses. However, the selection of the optimal proportions of the substrates in the mixtures presents a challenge. This research used a mixture design to investigate the interactions between the liquid fraction of piglet manure (PM), cow manure (CWM), and starch wastewater (SWW). A modified Gompertz model was used to identify the statistically significant parameters of the methane production curves. The optimal compositions of the mixtures were identified based on multi-objective optimization of the maximal methane yield (YCH4) and maximal methane specific production rate (rCH4) parameters. The study was validated using a double mixture of PM and CWM and a triple mixture. The estimated degradation rates for both mixtures were faster than the predicted ones. The absolute relative errors of rCH4 were 27.41% for the double mixture and 5.59% for the triple mixture, while... [more]

This work presents an experimental and modelling evaluation of the preferential oxidation of CO (CO PROX) from a H2-rich gas stream typically produced from fossil fuels and ultimately intended for hydrogen fuel cell applications. A microchannel reactor containing a washcoated 8.5 wt.% Ru/Al2O3 catalyst was used to preferentially oxidise CO to form CO2 in a gas stream containing (by vol.%): 1.4% CO, 10% CO2, 18% N2, 68.6% H2, and 2% added O2. CO concentrations in the product gas were as low as 42 ppm (99.7% CO conversion) at reaction temperatures in the range 120−140 °C and space velocities in the range 65.2−97.8 NL gcat−1 h−1. For these conditions, less than 4% of the H2 feed was consumed via its oxidation and reverse water-gas shift. Furthermore, a computational fluid dynamic (CFD) model describing the microchannel reactor for CO PROX was developed. With kinetic parameter estimation and goodness of fit calculations, it was determined that the model described the reactor with a confide... [more]

A three-dimensional numerical study of a single droplet splashing vertically on a liquid film is presented. The numerical method is based on the finite volume method (FVM) of Navier−Stokes equations coupled with the volume of fluid (VOF) method, and the adaptive local mesh refinement technology is adopted. It enables the liquid−gas interface to be tracked more accurately, and to be less computationally expensive. The relationship between the diameter of the free rim, the height of the crown with different numbers of collision Weber, and the thickness of the liquid film is explored. The results indicate that the crown height increases as the Weber number increases, and the diameter of the crown rim is inversely proportional to the collision Weber number. It can also be concluded that the dimensionless height of the crown decreases with the increase in the thickness of the dimensionless liquid film, which has little effect on the diameter of the crown rim during its growth.

Nowadays, network attacks are the most crucial problem of modern society. All networks, from small to large, are vulnerable to network threats. An intrusion detection (ID) system is critical for mitigating and identifying malicious threats in networks. Currently, deep learning (DL) and machine learning (ML) are being applied in different domains, especially information security, for developing effective ID systems. These ID systems are capable of detecting malicious threats automatically and on time. However, malicious threats are occurring and changing continuously, so the network requires a very advanced security solution. Thus, creating an effective and smart ID system is a massive research problem. Various ID datasets are publicly available for ID research. Due to the complex nature of malicious attacks with a constantly changing attack detection mechanism, publicly existing ID datasets must be modified systematically on a regular basis. So, in this paper, a convolutional recurrent... [more]

Hazard and operability analysis (HAZOP) is one of the most commonly used hazard analysis methods in the petrochemical industry. The large amount of unstructured data in HAZOP reports has generated an information explosion which has led to a pressing need for technologies that can simplify the use of this information. In order to solve the problem that massive data are difficult to reuse and share, in this study, we propose a new deep learning framework for Chinese HAZOP documents to perform a named entity recognition (NER) task, aiming at the characteristics of HAZOP documents, such as polysemy, multi-entity nesting, and long-distance text. Specifically, the preprocessed data are input into an embeddings from language models (ELMo) and a double convolutional neural network (DCNN) model to extract rich character features. Meanwhile, a bidirectional long short-term memory (BiLSTM) network is used to extract long-distance semantic information. Finally, the results are decoded by a conditi... [more]

Radiation-based instruments have been widely used in petrochemical and oil industries to monitor liquid products transported through the same pipeline. Different radioactive gamma-ray emitter sources are typically used as radiation generators in the instruments mentioned above. The idea at the basis of this research is to investigate the use of an X-ray tube rather than a radioisotope source as an X-ray generator: This choice brings some advantages that will be discussed. The study is performed through a Monte Carlo simulation and artificial intelligence. Here, the system is composed of an X-ray tube, a pipe including fluid, and a NaI detector. Two-by-two mixtures of four various oil products with different volume ratios were considered to model the pipe’s interface region. For each combination, the X-ray spectrum was recorded in the detector in all the simulations. The recorded spectra were used for training and testing the multilayer perceptron (MLP) models. After training, MLP neura... [more]

In this paper, a data-driven based spatiotemporal model reduction approach is proposed for predicting the temperature distribution and developing the computation speeds in the microwave heating process. Due to the mixed boundary conditions, it is difficult for the traditional spectral method to directly obtain the analytical eigenfunctions. Motivated by the time/space separation theory, we first propose a general framework of spatiotemporal model reduction, which can effectively develop the computation speeds in the numerical analysis of multi-physical fields. Subsequently, the empirical eigenfunctions are generated by applying the Karhunen−Loève theory to decompose the snapshots. Then, the partial differential Equation (PDE) model is discretized into a class of recursive equations and transformed as the reduced-order ordinary differential Equation (ODE) model. Finally, the effectiveness and superiority of the proposed approach is demonstrated by a comparison study with a traditional m... [more]

In China, safety policies interfere with the occurrence of work accidents in the form of guidance and restrictions. In this study, the impact of types of safety policies on work accident prevention is quantitatively analyzed. Based on a statistical analysis of China’s safety policies and work-related accidents from 2000 to 2020, the following four policy indexes that reflect the impact of safety policies are identified: the stringency level of the policy; the scope; its technical content; and its industrial target. A vector autoregressive model (VAR) is used, and a dynamic analysis of the model is conducted with an impulse response function. The model’s degree of fit is 92.9%, the number of deaths and the number of safety policies are linearly related, and the relative error between the fitted values and the real values is approximately 5%. The negative correlation between the death rate per 100 million yuan and the stringency level, scope, technical content, and industrial targets of... [more]

The aim of this paper is to perform optimization of photopolymerization process of dental composites in order to obtain maximum hardness. Samples (5 mm diameter; 2, 3 and 4 mm thickness) were made of Universal Composite (UC), Bulk fill Composite (BC) and Flowable Composite (FC). Light curing of specimens was performed with 600, 1000 and 1500 mW/cm2 light intensity and an irradiation time of 20, 40 and 60 s. Vickers microhardness on the top and bottom surfaces of samples was measured. Optimization was carried out via regression analysis using QStatLab software. Photopolymerization process parameters were calculated using a specially designed MatLab software-based algorithm. For all composites, regression models for hardness on top and bottom surfaces of composite layer were established. Layer thickness as well as hardness on top and bottom surfaces of each composite was calculated for 21 curing modes varying with light intensity and irradiation time. It was established that photopolymer... [more]

A 2D axi-symmetric theoretical model of dielectric porous media in intermittent microwave (IMW) thermal process was developed, and the electromagnetic energy, multiphase transport, phase change, large deformation, and glass transition were taken into consideration. From the simulation results, the mass was mainly carried by the liquid water, and the heat was mainly carried by liquid water and solid. The diffusion was the dominant mechanism of the mass transport during the whole process, whereas for the heat transport, the convection dominated the heat transport near the surface areas during the heating stage. The von Mises stress reached local maxima at different locations at different stages, and all were lower than the fracture stress. A material treated by a longer intermittent cycle length with the same pulse ratio (PR) tended to trigger the phenomena of overheat and fracture due to the more intense fluctuation of moisture content, temperature, deformation, and von Mises stress. Th... [more]

This study aimed to observe the effect of the direct-acting antiviral (DAA) therapy on liver stiffness (LS) and serum biomarkers. We prospectively observed 35 patients with chronic hepatitis C infection and attained a sustained virological response (SVR) after antiviral therapy. Shear wave elastography (SWE) measurement was performed at the beginning of DAA treatment and at 48 weeks after the end of treatment (EOT48w). The METAVIR score and the score for varices needing treatment (VNT) were determined based on the LS values; the fibrosis-4 (FIB4) score was calculated from laboratory tests. The baseline LS (mean ± standard deviation = 2.59 ± 0.89 m/s) decreased significantly after successful DAA therapy (1.90 ± 0.50 m/s; p < 0.001). The METAVIR score showed significant improvement at EOT48w (F0/1 = 9, F2 = 2, F3 = 10, F4 = 14) compared to the initial status (F0/1 = 2, F2 = 1, F3 = 7, F4 = 25; p < 0.028). The FIB4 score indicated less fibrosis after therapy (2.04 ± 1.12) than at ba... [more]

Because geologic sedimentation and hydrofracturing processes are not homogeneous, the reservoirs of enhanced geothermal systems (EGSs) are also heterogeneous; this has a significant influence on the electricity generation performance of EGS. Presently, there are a lack of systematic and profound studies on the effect of vertical permeability heterogeneity in stratified formation on the electricity generation performance of EGS. In order to uncover the effect of vertical permeability heterogeneity on electricity generation performance of EGS, in this work we analyzed the influence of vertical permeability heterogeneity on electricity generation performance of EGS through a numerical method based on geological data at the Yangbajing geothermal field. The results indicate that when the average permeability of stratified formations is constant for a homogeneous reservoir, the system attains maximum water production rate, maximum electric power, minimum reservoir impedance and maximum pump... [more]

The aim of this study is to evaluate the potential of dried Cystoseira barbata alga for ethanol production through alcoholic fermentation. The influence of the main factors affecting the fermentation are studied in the frame of a 23 factorial experimental plan. The main factors influencing the process are the fermentation temperature (t from 25 °C to 35 °C), the solid to liquid ratio (S/L from 0.040 g/g to 0.080 g/g), and the cellulase ratio (R from 8 U/g d.m to 16 U/g d.m.). The maximum volatile compounds yield of 0.2808 g/g d.m and ethanol yield of 0.0158 g/g d.m were favored by the following experimental conditions: process temperature of 35 °C, solid to liquid ratio of 0.0415, and enzyme ratio of 16 U/g d.m. A statistical model was used to correlate the product yield with the process factors. Additionally, 19 interesting bioactive compounds were found in the enzymatic hydrolysis and alcoholic fermentation broths which seem likely to maintain natural defence mechanisms against disea... [more]

As third-generation neural network models, spiking neural P systems (SNP) have distributed parallel computing capabilities with good performance. In recent years, artificial neural networks have received widespread attention due to their powerful information processing capabilities, which is an effective combination of a class of biological neural networks and mathematical models. However, SNP systems have some shortcomings in numerical calculations. In order to improve the incompletion of current SNP systems in dealing with certain real data technology in this paper, we use neural network structure and data processing methods for reference. Combining them with membrane computing, spiking neural membrane computing models (SNMC models) are proposed. In SNMC models, the state of each neuron is a real number, and the neuron contains the input unit and the threshold unit. Additionally, there is a new style of rules for neurons with time delay. The way of consuming spikes is controlled by a... [more]

The self-learning capabilities of artificial neural networks (ANNs) from large datasets have led to their deployment in the prediction of various physical and chemical phenomena. In the present work, an ANN model was developed to predict the yield sooting index (YSI) of oxygenated fuels using the functional group approach. A total of 265 pure compounds comprising six chemical classes, namely paraffins (n and iso), olefins, naphthenes, aromatics, alcohols, and ethers, were dis-assembled into eight constituent functional groups, namely paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic −CH=CH2 groups, naphthenic CH-CH2 groups, aromatic C-CH groups, alcoholic OH groups, and ether O groups. These functional groups, in addition to molecular weight and branching index, were used as inputs to develop the ANN model. A neural network with two hidden layers was used to train the model using the Levenberg−Marquardt (ML) training algorithm. The developed model was tested... [more]

Tea is a popular beverage worldwide and also has great medical value. A fundamental understanding of tea shoot growth and a precision picking model should be established to realize mechanized picking of tea shoots with a small product loss. Accordingly, the terminal bud length (Lbud), tea stem length (Lstem), terminal bud angle (αbud), tea stem angle (αstem), and growth time (t) were considered as the key growth parameters; the sum of the vertical lengths of the terminal bud and stem (ξ), the picking radius (r), and the vertical length of the stem (Zstem) were considered as the picking indexes of the tea shoots. The variations in growth parameters with time were investigated using a 3-D coordinate instrument, and the relationships between the growth parameters and the picking indexes were established using an artificial neural network (ANN). The results indicated that the tea growth cycles for periods P1, P2, P3, P4, P5, and P6 were 14, 7, 6, 4, 4, and 6 d, respectively. A growth cycle... [more]

Methane is one of the most common gaseous fuels that also exist in nature as the main part of the natural gas, the flammable part of biogas or as part of the reaction products from biomass pyrolysis. In this respect, the biogas and biomass installations are always subjected to explosion hazards due to methane. Simple methods for evaluating the explosion hazards are of great importance, at least in the preliminary stage. The paper describes such a method based on an elementary analysis of the cubic law of pressure rise during the early stages of flame propagation in a symmetrical cylindrical vessel of small volume (0.17 L). The pressure−time curves for lean, stoichiometric and rich methane−air mixtures were recorded and analyzed. From the early stages of pressure−time history, when the pressure increase is equal to or less than the initial pressure, normal burning velocities were evaluated and discussed. Qualitative experiments were performed in the presence of a radioactive source of 6... [more]

The state of cellulosic solid kraft paper (CSKP) insulation, to a large extent, is an indication of a transformer’s health. It not only reflects the condition of transformer but also diagnose its residual life. The quantity of 2-furfuraldehyde (2-FAL), carbon dioxide (CO2), and carbon monoxide (CO) dissolved in the transformer oil are useful diagnostic indicators to predict the state of the CSKP insulation. In this work, the current physical state of the CSKP is determined with the help of easily measurable parameters, like temperature, moisture, and the aging time. Here, the degree of deterioration of CSKP insulation has been determined using an integrated insulation health assessment system. This technique integrates a two-stage system comprising of a neural network (NN) model followed by a Smart Life Prediction Approach (SLPA). A thermo-moisture-aging multi-layer feed-forward NN model has been developed to predict the concentrations of 2-FAL, CO2, and CO, which are further correlate... [more]

For the winemaking bioprocess of jujube wine, the selection of optimal starter cultures is one of the major concerns before fermentation. In this study, we investigated the effects of different winemaking yeasts on the composition of aroma-active compounds in the fermented jujube wine and identified the principal components that determine the flavor quality. It showed that the starter winemaking yeasts produced a total of 43 aroma-active compounds, of which esters (e.g., ethyl caprylate, ethyl decanoate, ethyl hexanoate, and phenethyl acetate) contribute more to the wine quality attributes, especially for the improvement of the aroma. Moreover, the composition of aroma-active compounds, for example, the ratio of the content of esters and alcohols, exerts a great impact on the flavor quality of jujube wine. Different starter winemaking yeasts resulted in significant differences in the composition (both species and content) of aroma-active compounds, and thus formed different flavors in... [more]

In bioprocess engineering the Qualtiy by Design (QbD) initiative encourages the use of models to define design spaces. However, clear guidelines on how models for QbD are validated are still missing. In this review we provide a comprehensive overview of the validation methods, mathematical approaches, and metrics currently applied in bioprocess modeling. The methods cover analytics for data used for modeling, model training and selection, measures for predictiveness, and model uncertainties. We point out the general issues in model validation and calibration for different types of models and put this into the context of existing health authority recommendations. This review provides a starting point for developing a guide for model validation approaches. There is no one-fits-all approach, but this review should help to identify the best fitting validation method, or combination of methods, for the specific task and the type of bioprocess model that is being developed.

This paper evaluates the influence of crude oil (vacuum residue) properties, the processing of fluid catalytic cracking slurry oil, and recycle of hydrocracked vacuum residue diluted with fluid catalytic cracking heavy cycle oil, and the operating conditions of the H-Oil vacuum residue hydrocracking on the quality of the H-Oil liquid products. 36 cases of operation of a commercial H-Oil® ebullated bed hydrocracker were studied at different feed composition, and different operating conditions. Intercriteria analysis was employed to define the statistically meaningful relations between 135 parameters including operating conditions, feed and products characteristics. Correlations and regression equations which related the H-Oil® mixed feed quality and the operating conditions (reaction temperature, and reaction time (throughput)) to the liquid H-Oil® products quality were developed. The developed equations can be used to find the optimal performance of the whole refinery considering that... [more]

Interest in the interaction between energy and health within the built environment has been increasing in recent years, in the context of sustainable development. However, in order to promote health and wellbeing across all ages it is necessary to have a better understanding of the association between health and energy at household level. This study contributes to this debate by addressing the case of Portugal using data from the Household Budget Survey (HBS) microdata database. A two-part model is applied to estimate health expenditures based on energy-related expenditures, as well as socioeconomic variables. Additional statistical methods are used to enhance the perception of relevant predictors for health expenditures. Our findings suggest that given the high significance and coefficient value, energy expenditure is a relevant explanatory variable for health expenditures. This result is further validated by a dominance analysis ranking. Moreover, the results show that health gains a... [more]

Pathogens, which survive from stressed environmental conditions and evolve with antimicrobial resistance, cause millions of human diseases every year in the world. Fortunately, the NCBI Pathogen Detection Isolates Browser (NPDIB) collects the detected stress response genes and antimicrobial resistance genes in pathogen isolates sampled around the world. While several studies have been conducted to identify important antimicrobial resistance genes, little work has been done to analyze the stress response genes in the NPDIB database. In order to address this, this work conducted the first comprehensive statistical analysis of the stress response genes from five countries of the major residential continents, including the US, the UK, China, Australia, and South Africa. Principal component analysis was first conducted to project the stress response genes onto a two-dimensional space, and hierarchical clustering was then implemented to identify the outlier (i.e., important) genes that show... [more]

Nowadays, FDM technology permits obtaining functional prototypes or even end parts. The process parameters, such as layer thickness, building orientation, fill density, type of support, etc., have great influence on the quality, functionality and behavior of the obtained parts during their lifetime. In this paper, we present a study concerning the possibilities of obtaining certain values for clearance in revolute joints of non-assembly mechanisms manufactured by FDM 3D Printing. To ensure the functioning of the assembly, one must know the relationship between the imposed and measured clearances by taking into account the significant input data. One way is to use the automat learning method with an artificial neuronal network (ANN). The data necessary for the training, testing, and validation of ANN were experimentally obtained, using a complete L 27 Taguchi experimental plan. A total of 27 samples were printed with different values of the following parameters: the infill density, the... [more]

Medical and pharmaceutical research has shown that liposomes are very efficient in transporting drugs to targets. In this study, we prepared six liposome formulas, three in which we entrapped caffeic acid (CA), and three with only phospholipids and without CA. Determination of entrapment efficiency (EE) showed that regardless of the phospholipids used, the percentage of CA entrapment was up to 76%. The characterization of the liposomes was performed using Dynamic Light Scattering (DLS), Atomic Force Microscopy (AFM), zeta potential and polydispersity and showed that about 75−99% of the liposomes had dimensions between 40 ± 0.55−500 ± 1.45 nm. The size and zeta potential of liposomes were influenced by the type of phospholipid used to obtain them. CA release from liposomes was performed using a six-cell Franz diffusion system, and it was observed that the release of entrapped CA occurs gradually, the highest amount occurring in the first eight hours (over 80%), after which the release i... [more]