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]

(1) Background: Functional abdominal pain disorders (FAPDs) represent one of the main etiologies of chronic abdominal pain in the pediatric population. A wide spectrum of probiotic or prebiotic mixtures has been evaluated in trials regarding benefits in patients with FAPDs, mainly in the adult population. (2) Methods: This study was interested in evaluating the effect of oral supplementation with a symbiotic mixture on intestinal microbiota in children with functional dyspepsia (FD), irritable bowel syndrome with diarrhea (IBS-D), and irritable bowel syndrome with constipation (IBS-C). A combination of six bacterial strains (Lactobacillus rhamnosus R0011, Lactibacillus casei R0215, Bifidobacterium lactis BI-04, Lactobacillus acidophilus La-14, Bifidobacterium longum BB536, Lactobacillus plantarum R1012) and 210 mg of fructo-oligosaccharides-inulin were administered orally, daily, for 12 weeks and patients were scored for severity of symptoms and fecal microbiota before and after the tr... [more]

Given the urgent pursuit of carbon neutrality and stringent climate policies, the H2 shaft furnace (H2-SF) is starting to gain widespread attention in the steel industry. In this study, the performance of the H2-SF under operation with a dual-row injection top gas recycling system was investigated by a one-dimensional mathematical model. The potential of microwave heating as a means to supply thermal energy in regions of energy deficit was also assessed briefly. The results showed that for scenarios without microwave heating, increasing the upper-row injection rate can improve the furnace performance, and increasing the distance of the upper-row injection level from the furnace top also has a positive effect. A high microwave heating efficiency is expected in regions above the upper-row injection level. For scenarios with microwave heating, a higher microwave power leads to a better furnace performance. Thus, a higher furnace productivity can be achieved by increasing either the upper-... [more]

Purpose: The purpose of this in vivo study was to investigate whether the less invasive approach (reduced thickness of the restoration) will result in a comparable risk of failure and similar aesthetic results, compared to conventional layered full porcelain crowns, and can, therefore, be used as a good alternative. Material and Methods: The tested ceramic was lithium-disilicate ceramic (IPS e.max). Forty-four patients with endodontically treated premolars or molars were randomized into two groups and provided with single crowns. One group received conventional all-ceramic crowns made from a lithium-disilicate core and hand-veneered aesthetic ceramic, while another group received full-contoured lithium-disilicate ceramic crowns with reduced wall thickness than manufactures recommendations. The teeth for conventional crowns were prepared with 1 mm rounded shoulder and 2 mm occlusal reduction, while teeth for monolithic crowns were prepared with 0.6 mm wide rounded shoulder and 1 mm occl... [more]

Hazard and operability (HAZOP) is an important safety analysis method, which is widely used in the safety evaluation of petrochemical industry. The HAZOP analysis report contains a large amount of expert knowledge and experience. In order to realize the effective expression and reuse of knowledge, the knowledge ontology is constructed to store the risk propagation path and realize the standardization of knowledge expression. On this basis, a comprehensive algorithm of ontology semantic similarity based on the ant clony optimization generalized neural network (ACO-GRNN) model is proposed to improve the accuracy of semantic comparison. This method combines the concept name, semantic distance, and improved attribute coincidence calculation method, and ACO-GRNN is used to train the weights of each part, avoiding the influence of manual weighting. The results show that the Pearson coefficient of this method reaches 0.9819, which is 45.83% higher than the traditional method. It could solve t... [more]

Direct interaction with the neuronal cells is a prerequisite to deciphering useful information in understanding the underlying causes of diseases and functional abnormalities in the brain. Precisely fabricated nanoelectrodes provide the capability to interact with the brain in its natural habitat without compromising its functional integrity. Yet, challenges exist in terms of the high cost and complexity of fabrication as well as poor control over the chemical composition and geometries at the nanoscale, all imposed by inherent limitations of current micro/nanofabrication techniques. In this work, we report on electrochemical fabrication and optimization of vertically oriented TiO2 nanotube arrays as nanoelectrodes for neural interface application. The effects of zinc, strontium, and copper doping on the structural, electrochemical, and biocompatibility properties of electrochemically anodized TiO2 nanotube arrays were investigated. It was found that doping can alter the geometric feat... [more]

Considering the helicity of Archimedean spiral coils, this paper proposes accurate expressions of mutual inductance and their numerical calculation methods, which can be applied in the wireless power transmission field, etc. Accurate expressions of mutual inductance are deduced respectively for two coils that are coaxial, laterally misaligned, or non-parallel, and numerical calculations are performed using Gaussian integration as well. In the case of coaxial coils, the calculation results are verified by the 3D finite element method (3D FEM) and compared with the results gained by the traditional method that approximates two spiral coils to two clusters of series-connected circular coils ignoring helicity. The comparison of the three methods shows that results achieved by the proposed expression are close to that of 3D FEM, while there is increasing error with the screw pitches of the coils when using the traditional circular coil approximation method. The influence of relative positio... [more]