Graptolite−argillites (black shales) are studied as potential source of different metals. In the processing technologies of graptolite−argillites, a preceding thermal treatment is often applied. In this study, the thermal behavior of Estonian graptolite−argillite (GA) samples from Toolse, Sillamäe and Pakri areas were studied using a Setaram Labsys Evo 1600 thermoanalyzer coupled with the Pfeiffer OmniStar Mass Spectrometer. The products of thermal treatment were studied by XRD, FTIR, and SEM analytical methods. The experiments were carried out under non-isothermal conditions of up to 1200 °C at different heating rates in the atmosphere containing 79% Ar and 21% O2. The differential isoconversional Friedman method was applied for calculating the kinetic parameters. All studied GA samples are characterized with high content of orthoclase (between 38.0 and 57.3%) and quartz (between 23.8 and 35.5%), and with lower content of muscovite, jarosite, pyrite, etc. The content of organic carbon... [more]

Watermelon is a fruit produced around the world. Unfortunately, about half of it—the rind—is usually discarded as waste. To transform such waste into a useful product like flour, a thermal treatment is needed. The drying temperature for the rind that produces flour with the best characteristics is most important. A multiobjective optimization (MOO) procedure was applied to define the optimum drying temperature for the rind flour fabrication to be used in bakery products. A neural network model of the fabrication process was developed with the drying temperature as input and five process indicators as outputs. The group of process indicators comprised acidity, pH, water-holding capacity (WHC), oil-holding capacity (OHC), and batch time. Those indicators represent conflicting objectives that are to be balanced by the MOO procedure using the weighted distance method. The MOO process showed that the temperature interval from 67.3 °C to 73.1 °C holds the compromise solutions for the conflic... [more]

A phenomenological multi-response multi-parameter Acetone−Butanol−Ethanol fermentation dynamic model is developed and calibrated for fermentation process studies. The model was constructed based on other models reported in the literature and was calibrated with a maximum likelihood parameter estimation over Acetone−Butanol−Ethanol fermentation experimental data from the literature. After parameter estimation, a rigorous statistical analysis was conducted to evaluate standard deviations of estimated parameters and predicted responses as well as their respective 95% probability confidence intervals for correct parameters and responses. The significance of parameters was assessed via a Fisher’s F test. From the Base-Model with 17 parameters, a tight, more compact, Reduced-Model was developed with 9 highly significant parameters after deleting 8 nonsignificant parameters from the Base-Model and re-estimating the remaining 9 parameters. This Reduced-Model showed good adherence to the experi... [more]

In this study, we analyze gas−liquid interaction characteristics using a heterogeneous two-fluid model to investigate the influence of interphase force on multiphase pump performance. Two-phase transport platforms are used in oil and gas development to eliminate the need for separation equipment and reduce costs. Full-channel numerical calculations were conducted for an axial-flow multiphase pump based on different inlet gas void fractions (IGVFs) and flow rates. The results indicate that the interaction force of each phase is relatively large in the rotor−stator interference region, and the drag, lift, virtual mass, and turbulent dispersion forces increase with an increase in IGVF or when deviating from the design condition (Q = 50 m3/h). The interphase forces (resistance, lift, virtual mass force, and turbulent dispersion) increase considerably in the impeller passage and minimally in the guide blade passage. Under the conditions of small and high flows, the force of each phase chang... [more]

Four-mecanum-wheeled omnidirectional mobile robots (FMOMR) are widely used in many practical scenarios because of their high mobility and flexibility. However, the performance of trajectory tracking would be degenerated largely due to various reasons. To deal with this issue, this paper proposes a data-driven algorithm by using the T-S fuzzy quaternion-value neural network (TSFQVNN). TSFQVNN is tailored to obtain the controlled autoregressive integral moving average (CARIMA) model, and then the generalized predictive controller (GPC) is designed based on the CARIMA model. In this way, the spatial relationship between the three-dimensional pose coordinates can be preserved and training times can be reduced. Furthermore, the convergence of the proposed algorithm is verified by the Stone−Weierstrass theorem, and the convergence conditions of the algorithm are discussed. Finally, the proposed control scheme is applied to the three-dimensional (3D) trajectory tracking problem on the arc sur... [more]

Spice plants are popularly used as ingredients in food products. Promoting healthy eating, paying attention to the quality of products, means that organic and self-produced ingredients, whose origin and growing conditions are known, are gaining popularity. The study determined the concentration of mercury (Hg) in popular leafy spice plants: peppermint (Mentha piperita), common basil (Ocimum basilicum), lovage (Levisticum officinale) and parsley (Petroselinum crispum). Self-grown spices and ready-made commercial products were selected for the study. The Hg content in the test samples was determined by the AAS method (AMA 254, Altec, Praha, Czech Republic). The range of Hg content in the tested spice samples ranged from 1.20 to 17.35 µg/kg, on average 6.95 µgHg/kg. The highest concentration of Hg was recorded in the peppermint, 9.39 µg/kg. In plants grown independently, the concentration of Hg was statistically significantly higher than in commercial products purchased in a store. There... [more]

The increase in demand and generator reaching reactive power limits may operate the power system in stressed conditions leading to voltage instability. Thus, the voltage stability assessment is essential for estimating the loadability margin of the power system. The grid operators urgently need a voltage stability assessment (VSA) method with high accuracy, fast response speed, and good scalability. The static VSA problem is defined as a regression problem. Moreover, an artificial neural network is constructed for online assessment of the regression problem. Firstly, the training sample set is obtained through scene simulation, power flow calculation, and local voltage stability index calculation; then, the class imbalance problem of the training samples is solved by the random under-sampling bagging (RUSBagging) method. Then, the mapping relationship between each feature and voltage stability is obtained by an artificial neural network. Finally, taking the modified IEEE39 node system... [more]

Particle size distribution is an important parameter of metallurgical coke for use in blast furnaces. It is usually analyzed by traditional sieving methods, which cause delays and require maintenance. In this paper, a coke particle detection model was developed using a deep learning-based object detection algorithm (YOLOv3). The results were used to estimate the particle size distribution by a statistical method. Images of coke on the main conveyor belt of a blast furnace were acquired for model training and testing, and the particle size distribution determined by sieving was used for verification of the results. The experiment results show that the particle detection model is fast and has a high accuracy; the absolute error of the particle size distribution between the detection method and the sieving method was less than 5%. The detection method provides a new approach for fast analysis of particle size distributions from images and holds promise for a future online application in t... [more]

Common upper limb peripheral artery diseases (PADs) are atherosclerosis, embolic diseases, and systemic diseases, which are often asymptomatic, and the narrowed arteries (stenosis) will gradually reduce blood flow in the right or left upper limbs. Upper extremity vascular disease (UEVD) and atherosclerosis are high-risk PADs for patients with Type 2 diabetes or with both diabetes and end-stage renal disease. For early UEVD detection, a fingertip-based, toe-based, or wrist-based photoplethysmography (PPG) tool is a simple and noninvasive measurement system for vital sign monitoring and healthcare applications. Based on time-domain PPG analysis, a Duffing−Holmes system with a master system and a slave system is used to extract self-synchronization dynamic errors, which can track the differences in PPG morphology (in amplitudes (systolic peak) and time delay (systolic peak to diastolic peak)) between healthy subjects and PAD patients. In the preliminary analysis, the self-synchronization... [more]

Waste streams with high ammonia nitrogen (NH3-N) concentrations are very commonly produced due to human intervention and often end up in waterbodies with effluent discharge. The removal of NH3-N from wastewater is therefore of utmost importance to alleviate water quality issues including eutrophication and fouling. In the present study, vacuum thermal stripping of NH3-N from high strength synthetic wastewater was conducted using a rotary evaporator and the process was optimized and modeled using response surface methodology (RSM) and RSM−artificial neural network (ANN) approaches. RSM was first employed to evaluate the process performance using three independent variables, namely pH, temperature (°C) and stripping time (min), and the optimal conditions for NH3-N removal (response) were determined. Later, the obtained data from the designed experiments of RSM were used to train the ANN for predicting the responses. NH3-N removal was found to be 97.84 ± 1.86% under the optimal conditions... [more]

A two-step model of the anaerobic digestion process is mathematically and numerically studied. The focus of the paper is put on the hydrolysis and methanogenesis phases when applied to the digestion of waste with a high content of solid matter: existence and stability properties of the equilibrium points are investigated. The hydrolysis step is considered a limiting step in this process using the Contois growth function for the bacteria responsible for the first degradation step. The methanogenesis step being inhibited by the product of the first reaction (which is also the substrate for the second one), and the Haldane growth rate is used for the second reaction step. The operating diagrams with respect to the dilution rate and the input substrate concentrations are established and discussed.

Developing successful municipal waste management planning strategies is crucial for implementing sustainable development. The research proposed the application of an optimized artificial neural network (ANN) to forecast quantities of waste in Poland. The neural network coupled with particle swarm optimization (PSO) algorithm is compared to the conventional neural network using five assessment metrics. The metrics are coefficient of efficiency (CE), Pearson correlation coefficient (R), Willmott’s index of agreement (WI), root mean squared error (RMSE), and mean bias error (MBE). Selected explanatory factors are incorporated in the developed models to reflect the influence of economic, demographic, and social aspects on the rate of waste generation. These factors are population, employment to population ratio, revenue per capita, number of entities by type of business activity, and number of entities enlisted in REGON per 10,000 population. According to the findings, the ANN−PSO model (C... [more]

A car side-outer is an iron mold that is applied in the design and safety of the side of a vehicle, and is subjected to a complicated and detailed molding process. The side-outer has three features that make its quality inspection difficult to automate: (1) it is large; (2) there are many objects to inspect; and (3) it must fulfil high-quality requirements. Given these characteristics, the industrial vision system for the side-outer is nearly impossible to apply, and indeed there is no reference for an automated defect-inspection system for the side-outer. Manual inspection of the side-outer worsens the quality and cost competitiveness of the metal-cutting companies. To address these problems, we propose a large-scale Object-Defect Inspection System based on Regional Convolutional Neural Network (R-CNN; RODIS) using Artificial Intelligence (AI) technology. In this paper, we introduce the framework, including the hardware composition and the inspection method of RODIS. We mainly focus o... [more]

Small molecule lipophilicity is often included in generalized rules for medicinal chemistry. These rules aim to reduce time, effort, costs, and attrition rates in drug discovery, allowing the rejection or prioritization of compounds without the need for synthesis and testing. The availability of high quality, abundant training data for machine learning methods can be a major limiting factor in building effective property predictors. We utilize transfer learning techniques to get around this problem, first learning on a large amount of low accuracy predicted logP values before finally tuning our model using a small, accurate dataset of 244 druglike compounds to create MRlogP, a neural network-based predictor of logP capable of outperforming state of the art freely available logP prediction methods for druglike small molecules. MRlogP achieves an average root mean squared error of 0.988 and 0.715 against druglike molecules from Reaxys and PHYSPROP. We have made the trained neural network... [more]

The main objective of this study was to examine the chemical characteristics, possible sources, and health risks of fine particle-bound Polycyclic Aromatic Hydrocarbons (PAHs) in the Baoshan area of Shanghai. Here, ambient particles with five-size ranges were collected during the spring and late summer of 2017. The PAHs were determined by the Gas Chromatography-Mass Spectrometry (GC-MS). Our results showed that the average mass concentration of 13 species of PAHs in spring and in late summer was 4.83 (1.88~12.1) ng/m3 and 4.27 (2.09~5.75) ng/m3 in Total Suspended Particles (TSPs), respectively. The higher PAH ratios (PM1.1/TSPs) indicated that PAHs are mainly concentrated in PM1.1, especially in late summer. The values of BaA/(BaA+CHR) were under 0.50 and IcdP/(IcdP+BghiP) were in range from 0.20 to 0.50 for TSP and PM1.1, suggesting that petroleum combustion and diesel emissions could be considered as key sources of PAHs, which tend to be associated with PM1.1. Moreover, the Principal... [more]

In the development of high-tech industries, graphite has become increasingly more important. The world has gradually entered the graphite era from the silicon era. In order to make good use of high-quality graphite resources, a graphite classification and recognition algorithm based on an improved convolution neural network is proposed in this paper. Based on the self-built initial data set, the offline expansion and online enhancement of the data set can effectively expand the data set and reduce the risk of deep convolution neural network overfitting. Based on the visual geometry group 16 (VGG16), residual net 34 (ResNet34), and mobile net Vision 2 (MobileNet V2), a new output module is redesigned and loaded into the full connection layer. The improved migration network enhances the generalization ability and robustness of the model; moreover, combined with the focal loss function, the superparameters of the model are modified and trained on the basis of the graphite data set. The si... [more]

In this paper, the deterministic ensemble Kalman filter is implemented with a parallel technique of the message passing interface based on our in-house black oil simulator. The implementation is separated into two cases: (1) the ensemble size is greater than the processor number and (2) the ensemble size is smaller than or equal to the processor number. Numerical experiments for estimations of three-phase relative permeabilities represented by power-law models with both known endpoints and unknown endpoints are presented. It is shown that with known endpoints, good estimations can be obtained. With unknown endpoints, good estimations can still be obtained using more observations and a larger ensemble size. Computational time is reported to show that the run time is greatly reduced with more CPU cores. The MPI speedup is over 70% for a small ensemble size and 77% for a large ensemble size with up to 640 CPU cores.

This study proposed a hybrid modeling framework for membrane separation processes where lithium from batteries is recovered. This is a pertinent problem nowadays as lithium batteries are popularized in hybrid and electric vehicles. The hybrid model is based on an artificial intelligence (AI) structure to model the mass transfer resistance of several experimental separations found in the literature. It is also based on a phenomenological model to represent the transient system regime. An optimization framework was designed to perform the AI model training and simultaneously solve the Ordinary Differential Equation (ODE) system representing the phenomenological model. The results demonstrate that the hybrid model can better represent the experimental validation sets than the phenomenological model alone. This strategy opens doors for further investigations of this system.

In this work, the relaxation parameter (τ) and fractionality order (α) in the fractional single phase lag (FSPL) non-Fourier heat conduction model are estimated by employing the conjugate gradient inverse method (CGIM). Two different physics of skin tissue are chosen as the studied cases; single and three-layer skin tissues. Single-layer skin is exposed to laser radiation having the constant heat flux of Qin. However, a heat pulse with constant temperature is imposed on the three-layer skin. The required inputs for the inverse problem in the fractional diffusion equation are chosen from the outcomes of the dual phase lag (DPL) theory. The governing equations are solved numerically by utilizing implicit approaches. The results of this study showed the efficiency of the CGIM to estimate the unknown parameters in the FSPL model. In fact, obtained numerical results of the CGIM are in excellent compatibility with the FSPL model.

In this study, major phytochemical compounds of Vaccinium bracteatum Thunb. (VB) aqueous leaf extract were isolated and analyzed using a HPLC-based method, followed by method validation in accordance with the International Conference on Harmonisation (ICH) guidelines for drug development. Five major compounds were isolated in VB extract. Apart from vaccinoside, which had been the only compound isolated in VB extract to date, vanillic acid and protocatechuic acid were isolated for the first time. Isolation of orientin and isoorientin in the VB extract helped validate the reverse-phase analytical method. A new simple and rapid high-performance liquid chromatography (HPLC)-based method was developed for the validation of orientin and isoorientin in VB extract and was determinated according to the ICH guidelines. The analytical method was validated through a Waters Alliance HPLC System containing an e2695 separation module and a 2998 photodiode array (PDA) detector. The VB extract and solu... [more]

Recently, identifying speech emotions in a spontaneous database has been a complex and demanding study area. This research presents an entirely new approach for recognizing semi-natural and spontaneous speech emotions with multiple feature fusion and deep neural networks (DNN). A proposed framework extracts the most discriminative features from hybrid acoustic feature sets. However, these feature sets may contain duplicate and irrelevant information, leading to inadequate emotional identification. Therefore, an support vector machine (SVM) algorithm is utilized to identify the most discriminative audio feature map after obtaining the relevant features learned by the fusion approach. We investigated our approach utilizing the eNTERFACE05 and BAUM-1s benchmark databases and observed a significant identification accuracy of 76% for a speaker-independent experiment with SVM and 59% accuracy with, respectively. Furthermore, experiments on the eNTERFACE05 and BAUM-1s dataset indicate that th... [more]

A scaled-up process for paddy drying was developed using hot air (HA) combined with radio frequency (RF) heating. The study was conducted using hot air (control treatment) arranged in descending order in four temperature levels, namely 80 °C at moisture content of 25−26%, 70 °C at moisture content of 20−25%, 60 °C at moisture content of 17−20%, and 50 °C at moisture content of 13−17%, as well as with hot air combined with radio frequency (HA/RF) at different paddy temperatures (45−60 °C) by adjusting the appropriate RF energy when passing through RF heating chamber, namely HA/RF45, HA/RF50, HA/RF55, and HA/RF60. Each treatment was performed in three replicates and data were statistically analyzed in a randomized complete block design. The quality attributes of paddies affected by the drying process were assessed: fissure percentage, color, milling quality, and sensory evaluation. The drying efficiency showed that the drying time and the specific energy consumption could be decreased by... [more]

Standalone and sequential ultrasound (US) and ozone (OZ) processes were applied to cashew apple juice. An unsupervised method, by principal component analysis (PCA), was used to understand the effect of the non-thermal treatments on the cashew apple composition. The US processing (373 W/cm2; 10 min; 40 °C) promoted the highest peroxidase inactivation and increased the flavonoid content and antioxidant activity (DPPH ABTS and FRAP methods). The ozone processing (0.24 mg O3/mL) increased total phenolic compounds (TPC). Sequential processing was carried out by applying both of the processes, using the best processing conditions for US and OZ. Sequential processing resulted in the higher retention of yellow flavonoids than in the control and single processing. However, the effect of sequential US and OZ processing can be deleterious to vitamin C and TPC after 30 days of cold storage while maintaining the flavonoids of the cashew apple juice. Furthermore, the synergy between US and OZ reduc... [more]

Endometriosis is a disorder characterized by the presence of endometrial tissue outside the uterine cavity, primarily into the peritoneal cavity. It is known as a complex, chronic inflammatory disease and it is strongly associated with immune dysregulation. Various soluble mediators of the immune and inflammatory responses, including chemokines, play an important role in these processes. The aim of the study was to understand the role of the chemokines MCP-1, MCP-2, MCP-3, MCP-4, MIP-1 α, MIP-1β, eotaxin 2, eotaxin 3, ENA-78, and fractalkine in the development of endometriosis through their assessment in the peritoneal fluid of women with endometriosis. The study group included 58 women with endometriosis who were diagnosed during laparoscopy and then confirmed by histopathology. In 15 women from the reference group, laparoscopic examination demonstrated a normal status of the pelvic organs without any evidence of endometriosis nor inflammation in the peritoneal cavity. The peritoneal... [more]

The present research aimed to synthesize ketoprofen prodrugs and to demonstrate their potentiality for oral treatment to treat chronic inflammation by reducing its hepatotoxicity and gastrointestinal irritation. Methyl 2-(3-benzoyl phenyl) propanoate, ethyl 2-(3-benzoyl phenyl) propanoate and propyl 2-(3-benzoyl phenyl) propanoate was synthesized by esterification and identified by nuclear magnetic resonance (1HNMR) and infrared (IR) spectrometric analysis. In silico SwissADME and ProTox-II analysis stated methyl derivative as ideal candidate for oral absorption, having a >30-fold LD50 value compared to ketoprofen with no hepatotoxicity. Moreover, in vivo hepatotoxicity study demonstrates that these ester prodrugs have significantly lower effects on liver toxicity compared to pure ketoprofen. Furthermore, ex vivo intestinal permeation enhancement ratio was statistically significant (* p < 0.05) compared to ketoprofen. Likewise, the prodrugs were found to exhibit not only remarkable... [more]