The mixing tank is important equipment for industrial applications in the wet vanadium extraction process, but in practice, there are problems, such as uneven mixing of minerals. In this study, the effect of different types of impellers and different mixing tank structures on the suspended mass of particles was simulated using the discrete element method and volume of fluid method (DEM-VOF). The simulation results show that the round-bottomed tank performed mixing better than the flat-bottomed tank at different particle densities, and the flat-bottomed tank was prone to particle stratification and other phenomena. The round-bottomed mixing tank could better improve the solid−liquid suspension effect. In this study, the coefficient of variation σ was introduced to characterize the suspended mass of particles. By monitoring the σ value, it was found that the blade pitch angle 45 (BPA45) had the best mixing uniformity in the inclined pitched blade turbine (PBT). As the PBT impeller pitch... [more]

The failing tube-to-tubesheet joint is identified as a primary quality defect in the fabrication of a shell-and-tube heat exchanger. Operating in conditions of high pressure and temperature, a shell-and-tube heat exchanger may be susceptible to leakage around faulty joints. Owing to the ongoing low performance of the adjacent tube-to-tubesheet expansion, the heat exchanger eventually experiences malfunction. A quality improvement study on the assembly process is necessary in order to delve into the tight-fitting of the tube-to-tubesheet joint. We present a non-linear screening and optimization study of the tight-fitting process of P215NL (EN 10216-4) tube samples on P265GH (EN 10028-2) tubesheet specimens. A saturated fractional factorial scheme was implemented to screen and optimize the tube-to-tubesheet expanded-joint performance by examining the four controlling factors: (1) the clearance, (2) the number of grooves, (3) the groove depth, and (4) the tube wall thickness reduction. Th... [more]

By adjusting the synthesis process, silver nanoparticles (AgNp) of various shapes, sizes, and structures can be obtained, all of which have a substantial impact on the biological effect, notably, the regulation of antibacterial activity in the present circumstances of growing bacterial resistance. Due to their relatively small size, nanoparticles may be disseminated evenly throughout the body of the experimental animal, even at low doses, and exert more potent antibacterial activities. Our research was centered on the synthesis, production, and biological evaluation of antibacterial silver nanoparticles. Using the Turkevich method, we were able to effectively synthesize and characterize nanoscale silver particles, with an average crystallite size of 9.49 nm. We examined their acute toxicity and pharmacokinetic characteristics in rats after administering a single dosage. In addition, we evaluated the biological effect of topical AgNp suspension on the progression of burn-type lesions in... [more]

In the medical domain, early identification of cardiovascular issues poses a significant challenge. This study enhances heart disease prediction accuracy using machine learning techniques. Six algorithms (random forest, K-nearest neighbor, logistic regression, Naïve Bayes, gradient boosting, and AdaBoost classifier) are utilized, with datasets from the Cleveland and IEEE Dataport. Optimizing model accuracy, GridsearchCV, and five-fold cross-validation are employed. In the Cleveland dataset, logistic regression surpassed others with 90.16% accuracy, while AdaBoost excelled in the IEEE Dataport dataset, achieving 90% accuracy. A soft voting ensemble classifier combining all six algorithms further enhanced accuracy, resulting in a 93.44% accuracy for the Cleveland dataset and 95% for the IEEE Dataport dataset. This surpassed the performance of the logistic regression and AdaBoost classifiers on both datasets. This study’s novelty lies in the use of GridSearchCV with five-fold cross-valida... [more]

A method of steel structure surface crack identification based on artificial intelligence technology is proposed to solve the problem that steel cracks can not be detected and forewarned in time when they appear in the railway industrial environment. The appearance of steel cracks greatly weakens the stability of steel structures, and will seriously endanger the safety of the railway industry if it is not detected and repaired in time. However, the common steel crack detection methods cannot achieve real-time monitoring of steel structures. In order to monitor the surface of steel structure in real-time and explore the recognition effect and model the advantages of common classification neural network models for surface cracks of railway industrial steel, this study evaluates the network model with multiple indicators and parameters under two experimental conditions. In this study, the steel surface cracks in the railway industrial environment are taken as samples, and the steel cracks... [more]

Efficient waste management, especially in relation to swaste reuse, has become a pressing societal issue. The waste bittern generated during salt production and discarded oyster shells present formidable environmental challenges and a waste of resources for some coastal regions. Therefore, this work developed a two-stage circular process for the environmentally friendly and efficient utilization of both waste materials. In the first stage, CO2 gas and an organic extraction phase comprising Tri(octyl-decyl)amine (R3N) and isoamyl alcohol were introduced into the waste bittern to obtain MgCO3·3H2O (s). The second stage involved reacting the reacted organic extraction phase with oyster shell powders to produce CaCl2·2H2O (s) and CO2 (g) and regenerate R3N. This work focused on investigating the yield of MgCO3·3H2O and the regeneration ratio of R3N, which are crucial indicators for the two stages involved in the process. The results indicate that, under optimal operating conditions, a maxi... [more]

Heat release rate (HRR) is the principal fire characteristic of materials. There are three known methods for the measurement of HRR (based on oxygen consumption, mass loss rate, and combustion products temperature rise). The method based on oxygen consumption is considered to be the reference. However, this method is expensive and for a large part of laboratories and universities unavailable. The simplest method is based on combustion products’ temperature rise. However, this method has a fundamental problem with the temperature dependence of the heat capacity of combustion products and the thermal inertia of the measurement system. This problem has been solved by training neural networks to predict molar heat capacity and the amount of substance (chemical amount) flow rate of combustion products in the cone calorimeter exhaust duct. Data were obtained for six different wood species: birch (Betula verrucosa Ehrh.), oak (Quercus robur L.) spruce (Picea abies (L.) H. Karst.), locust (Rob... [more]

To handle the gangue well and control the settlement of the surface, as well as to reduce the risk of water bleeding, settlement and even blockage and pipe breaking of the gangue slurry in the process of conveying, the rheological characteristics of the slurry should be studied. The rheological properties of slurry with different concentrations prepared from gangue samples of the Ningtiaota coal mine were tested, and the correlation between the rheological characteristics of the coal gangue filling slurry and three factors, namely the gangue mass fraction, grain gradation and standing time, were studied by a single factor method and response surface methodology. The results show that the fitting curve of the Herschel−Bulkley model is mostly linear, that is, the shear stress of coal gangue paste increases as a function of the shear rate. Therefore, these two concentrations are too small to form a stable network structure to wrap large particles and can easily cause pipe blockage. The yi... [more]

The lithium-ion battery is widely used in the power system of pure electric vehicles and hybrid electric vehicles due to its high energy density. However, the chemical and electrochemical reactions generate a lot of heat. If the heat is not transferred through some refrigeration methods in time, it will lead to a rapid rise in the temperature of the battery. In this paper, an electric−thermal coupling model of a cylindrical Panasonic 21700 battery was proposed by using offline parameter identification method. Based on this model, a battery thermal management system using a heat pipe was established. The experimental results show that the model can simulate the actual performance of battery well. When the ambient temperature is 25 °C, the battery parameters change little and battery performance is better. The heat pipe battery thermal management system performs better than the non-heat pipe battery system in the discharge process, and can control the battery temperature well at low and... [more]

The inventory level has a significant influence on the cost of process scheduling. The stochastic cutting stock problem (SCSP) is a complicated inventory-level scheduling problem due to the existence of random variables. In this study, we applied a model-free on-policy reinforcement learning (RL) approach based on a well-known RL method, called the Advantage Actor-Critic, to solve a SCSP example. To achieve the two goals of our RL model, namely, avoiding violating the constraints and minimizing cost, we proposed a two-stage discount factor algorithm to balance these goals during different training stages and adopted the game concept of an episode ending when an action violates any constraint. Experimental results demonstrate that our proposed method obtains solutions with low costs and is good at continuously generating actions that satisfy the constraints. Additionally, the two-stage discount factor algorithm trained the model faster while maintaining a good balance between the two af... [more]

Mobile robot is an automatic vehicle with wheels that can be moved automatically from one place to another. A motor is built in its wheels for mobility purposes, which is controlled using a controller. DC motor speed is controlled by the proportional integral derivative (PID) controller. Kinematic modeling is used in our work to understand the mechanical behavior of robots for designing the appropriate mobile robots. Right and left wheel velocity and direction are calculated by using the kinematic modeling, and the kinematic modeling is given to the PID controller to gain the output. Motor speed is controlled by the PID low-level controller for the robot mobility; the speed controlling is done using the constant values Kd, Kp, and Ki which depend on the past, future, and present errors. For better control performance, the integral gain, differential gain, and proportional gain are adjusted by the PID controller. Robot speed may vary by changing the direction of the vehicle, so to avoid... [more]

Due to the increasing pressures on the environment derived from the intensive use of energy, policy-makers are increasingly aware of the need to design new energy policies capable of addressing those negative impacts on the environment [...]

To solve the problem of deposits formation in the exhaust pipe of a diesel engine SCR (selective catalytic reduction) system, the CFD (computational fluid dynamics) model of the exhaust pipe was established to research the influence of structural parameters on the wall film from the perspective of optimizing the flow field. The solid structure was simplified in the modeling without considering the flow fields inside the catalytic converter. The simulation conditions were obtained through bench tests and vehicle real road tests. The spray and temperature simulation results were verified via high-speed photographic and bench tests under three typical operating conditions. The conclusions are as follows: compared to the case with a step surface, wall film mass was reduced by 48.27~55.4% when the exhaust pipe had no step surface; compared to the case where the nozzle orifices were located 10 mm off center axis, wall film mass reduced by 2.83~6.38% when the nozzle orifices located in the ce... [more]

This paper introduces and studies a new discrete distribution with one parameter that expands the Poisson model, discrete weighted Poisson Lerch transcendental (DWPLT) distribution. Its mathematical and statistical structure showed that some of the basic characteristics and features of the DWPLT model include probability mass function, the hazard rate function for single and double components, moments with auxiliary statistical measures (expectation, variance, index of dispersion, skewness, kurtosis, negative moments), conditional expectation, Lorenz function, and order statistics, which were derived as closed forms. DWPLT distribution can be used as a flexible statistical approach to analyze and discuss real asymmetric leptokurtic data. Moreover, it could be applied to a hyperdispersive data model. Two different estimation methods were derived, i.e., maximal likelihood and the moments technique for the DWPLT parameter, and some advanced numerical methods were utilized for the estimati... [more]

Studies have confirmed the poor stability of layered roofs with weak interlayers, and it is necessary to study the roof-caving mechanism of such roadways. A model of a weak interlayer was established to study the influence of the layer position and horizontal stress of layered roofs with weak interlayers on the stability of roadway roofs. FLAC3D numerical simulation software was used to study the damage characteristics of weak interlayers and different horizontal stresses on roadway roofs. Based on Proctor’s theory, a maximum caving arch model was proposed to obtain the maximum caving arch height and span range. The pressure measurement coefficient and the vertical displacement change of the roof strata conformed to corresponding linear functions by fitting the pressure measurement coefficient and the maximum vertical displacement. A bolt-while-drilling support method (BWD) was proposed based on team measurement-while-drilling (MWD) to accurately determine the location of weak rock lay... [more]

The demand for sustainable economic growth highlights the trade off between environmental and economic targets. From the perspective of economic growth target (EGT) management and green innovation (GI) practice, in this study, we constructed dynamic panel, spatial Dubin, quantile, and threshold models to measure the impact of EGT on GI using the panel data of 284 prefecture cities in China from 2006 to 2018. The results show that EGT has a negative impact on GI, which is characterized by dynamic, superposition, spatial, and nonlinear effects; there is remarkable heterogeneity in different regions, development stages, and urban characteristics, and the empirical conclusion is still credible under many robustness tests. We also studied the heterogeneous impact of economic growth targets with different characteristics on green innovation. This study puts forward policy implications from two perspectives: optimizing top-level design and maximizing the trade off in multi-objective accountab... [more]

The evaluation of groundwater environmental quality and the identification of recharge sources are very important for groundwater utilization. In this study, hydrochemistry and isotope analysis methods are used to investigate the recharge sources and hydrochemical processes of groundwater in Zhanjiang City. The results show that all samples of groundwater were drawn on the left of the global meteoric water line (GMWL: δD = 8δ18O + 10) and local meteorological water lines (LMWL1: δD = 8.17δ18O + 11.74 and LMWL2: δD = 7.50δ18O + 6.18), indicating that the groundwater was mainly recharged by meteoric precipitation and influenced by the effect of evaporation. In the middle and deep confined aquifers, the isotope data depleted with the depth, indicating that there is a relatively weak hydraulic connection between them. In addition, compared with unconfined groundwater, the isotope data of confined groundwater showed relative depletion, indicating that the confined aquifer may be partially r... [more]

The aim of this study was to investigate the influence of thermal treatment and ultrasound on the activity of β-glucosidase and lipoxygenase, enzymes that determine the phenolic composition and sensory profile of virgin olive oil. Enzyme activity was determined spectrophotometrically in model systems consisting of commercial enzymes and their substrates. Thermal treatment was performed by tempering the enzymes and substrates at temperatures between 15 and 40 °C. Enzyme activity was measured 1 min after reaction and again after the additional incubation of the reaction mixture at 25 °C for 30 min to simulate the behavior of the enzymes during the malaxation process. Ultrasonic treatment of the model solutions was performed at 128, 320, and 640 W of the ultrasonic bath power for 1, 5, and 12 min. Enzyme activity was determined immediately after treatment and again after incubation at 25 °C for 30 min. The higher temperatures during thermal treatment increased the activity of both enzymes... [more]

Zinc oxide nanoparticles (ZnO-NPs) have gained significant interest in the agricultural and food industry as a means of killing or reducing the activity of microorganisms. The antibacterial properties of ZnO-NPs may improve food quality, which has a direct impact on human health. ZnO-NPs are one of the most investigated inorganic nanoparticles and have been used in various related sectors, with the potential to rapidly gain attention and increase interest in the agriculture and food industries. In this review, we describe various methods for preparing ZnO-NPs, their characterizations, modifications, applications, antimicrobial activity, testing procedures, and effects, including bactericidal and bacteriostatic mechanisms. It is hoped that this review could provide a better understanding of the preparation and application of ZnO nanoparticles in the field of food and agriculture, and promote their development to advance the field of food and agriculture.

The timely and effective fault diagnosis method is critical to the operation of the air-conditioning system and energy saving of buildings. In this study, a novel fault diagnosis method was proposed. It is combined with the signal demodulation method and machine learning method. The fault signals are demodulated by the demodulation method based on time-frequency analysis and principal component analysis (DPCA). The modulation characteristics of the principal component and DPCA sets with stronger features are obtained. Compared with time domain sets, the correct rate was increased by 16.38%. Then, as a machine learning method, the Visual Geometry Group—Principal Component Analysis (VGG-PCA) model is proposed in this study. The application potential of this model is discussed by using evaluation indexes of fault diagnosis performance and two typical faults of air conditioning systems. Compared with the other two convolution neural network models, the correct rate was increased by 17.1% a... [more]

Microbial pathogens cause a quarter of all deaths worldwide annually due to deadly infectious diseases. Nevertheless, the fast and precise identification of pathogens remains one of the most challenging tasks in the medical sector. Early identification and characterization of microbes through medical diagnosis could pave the way for specific treatment strategies that could dramatically improve infection management, reduce healthcare costs, mitigate increasing antimicrobial resistance, and save numerous lives. To date, numerous traditional and molecular methods have been employed to diagnose illnesses with proven accuracy, reliability, and efficiency. Here, we have reviewed the most reliable tools that are prerequisites for the rapid detection of microbes. In particular, the remarkable roles of surface-enhanced Raman scattering, Fourier-transform infrared, electrochemical impedance, near-infrared, and MALDI-TOF/TOF in the identification and characterization of pathogenic microbes are di... [more]

Optimizing Rural Water Supply Network (RWSN) is the basis for improving rural people’s lives and improving people’s health. Currently, the RWSN in China is relatively backward and can no longer meet the needs of the unified management of rural water resources. To optimize the RWSN, this study innovatively established a Multi-Objective Optimization Mathematical Model (MOMM) of RWSN, combining economic factors and reliability. This experiment first analyzes the characteristics of the RWSN system and then establishes a MOMM of a water supply network. NSGA-II algorithm and LM algorithm are introduced to handle the multi-objective model. The research results show that compared to Web decision tools, the RWSN based on the LM-NSGA-II algorithm can save 5.4% of the total annual cost of water supply pipelines. Therefore, the MOMM of the rural water supply pipeline based on the LM-NSGA-II algorithm has better economy and reliability. The experiment aims to provide certain reference values for th... [more]

is a bacterium that causes various diseases in humans. Cold plasma is found to be an alternative to eliminate S. aureus. Most studies of cold plasma on S. aureus mainly focus on the physiochemical changes of the cells. So far, biological responses of S. aureus to cold plasma treatment under different treatment durations have not yet been evaluated. In this study, the results showed that the cold plasma was effective in eliminating S. aureus. At the initial exposure (1 min), the treated cells showed gene upregulations of stress proteins, antioxidants, nitrosative stress, and transporter proteins, but no significant change in other biological processes, such as cell membrane synthesis, DNA repairing, transcription, and translation. This indicated that the cells actively countered the damage from cold plasma. In contrast, during the prolonged treatment (3 and 5 min), biological processes related to central dogma were affected, including the DNA repairing mechanism, transcription, and tran... [more]

Continuous SiC fiber is a kind of high−performance ceramic fiber that combines many advantages, such as high strength, high modulus, high hardness and low density. It has excellent mechanical properties, high−temperature and oxidation resistance, which could be applied as essential reinforcement in advanced ceramic matrix composites (CMCs) in the fields of aerospace and advanced weaponry. Melt−spinnable polytitanocarbosilane (PTCS) is an important precursor, which can be used to prepare continuous SiC fibers through a precursor−derived method. In this work, low−softening−point polycarbosilane (LPCS) and tetrabutyl titanate were used to prepare polytitanocarbosilane with a ceramic yield of 67.5 wt% at 1000 °C. FT−IR, TGA, GPC, 1H NMR, 29Si NMR, and elemental analysis were used to analyze the composition and structure of the PTCS precursor. Finally, Si−C−Ti−B fibers with an average tensile strength of 1.93 GPa were successfully prepared by melt spinning, pre−oxidation, pyrolysis, and hig... [more]

The excessive utilization of additives in chemical reactions is a troublesome problem in industrial processes, due to their adverse effects on equipment and processes. To acquire oxidative functionalization of alkyl aromatics under additive-free and mild conditions, a large library of metalloporphyrins was applied to the oxygenation of alkyl aromatics as catalysts with H2O2 as an oxidant. On the basis of systematic investigation of the catalytic performance of metalloporphyrins, it was discovered that, surprisingly, only porphyrin irons(II) possessed the ability to catalyze the oxygenation of alkyl aromatics with H2O2 under additive-free conditions and with satisfying substrate scope. Especially with 5,10,15,20-tetrakis(2,6-dichlorophenyl) porphyrin iron(II) (T(2,6-diCl)PPFe) as the catalyst, the substrate conversion reached up to 27%, with the selectivity of 85% to the aromatic ketone in the representative oxygenation of ethylbenzene with H2O2 as oxidant and without any additive used.... [more]