bluuebunny/crossref_metadata_2025 huggingface dataset:
New Chelate Resins Prepared with Direct Red 23 for Cd2+, Ni2+, Cu2+ and Pb2+ Removal
Authors: Marin Nicoleta , Ficai Anton , Constantin Lucian , Motelica Ludmila , Trusca Roxana
Published: December 2022

In this paper, two chelate resins prepared by a simple procedure were used for the removal of Cd2+, Ni2+, Cu2+, and Pb2+ (M2+) from aqueous solutions. Amberlite IRA 402 strongly basic anion exchange resin in Cl− form (IRA 402 (Cl−) together with Amberlite XAD7HP acrylic ester co-polymer (XAD7HP) were functionalized with chelating agent Direct red 23 (DR 23). The chelate resins (IRA 402-DR 23 and XAD7HP-DR 23) were obtained in batch mode. The influence of interaction time, pH and the initial concentration of DR 23 solution was investigated using UV-Vis spectrometry. The time necessary to reach equilibrium was 90 min for both resins. A negligible effect of adsorption capacity (Qe) was obtained when the DR 23 solution was adjusted at a pH of 2 and 7.9. The Qe of the XAD7HP resin (27 mg DR 23/g) is greater than for IRA 402 (Cl−) (21 mg DR 23/g). The efficiency of chelating resins was checked via M2+ removal determined by the atomic adsorption spectrometry method (AAS). The M2+ removal by the IRA 402-DR 23 and XAD7HP-DR 23 showed that the latter is more efficient for this propose. As a consequence, for divalent ions, the chelated resins followed the selectivity sequence: Cd2+ > Cu2+ > Ni2+ > Pb2+. Additionally, Cd2+, Cu2+ and Ni2+ removal was fitted very well with the Freundlich model in terms of height correlation coefficient (R2), while Pb2+ was best fitted with Langmuir model for IRA 402-DR 23, the Cu2+ removal is described by the Langmuir model, and Cd2+, Ni2+ and Pb2+ removal was found to be in concordance with the Freundlich model for XAD7HP-DR 23. The M2+ elution from the chelate resins was carried out using 2 M HCl. The greater M2+ recovery from chelating resins mass confirmed their sustainability. The chelate resins used before and after M2+ removal by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) analysis were evaluated.
Sodium Alginate/β-Cyclodextrin Reinforced Carbon Nanotubes Hydrogel as Alternative Adsorbent for Nickel(II) Metal Ion Removal
Authors: Zakaria Aiza Farhani , Kamaruzaman Sazlinda , Abdul Rahman Norizah , Yahaya Noorfatimah
Published: December 2022

Water pollution issues, particularly those caused by heavy metal ions, have been significantly growing. This paper combined biopolymers such as sodium alginate (SA) and β-cyclodextrin (β-CD) to improve adsorption performance with the help of calcium ion as the cross-linked agent. Moreover, the addition of carbon nanotubes (CNTs) into the hybrid hydrogel matrix was examined. The adsorption of nickel(II) was thoroughly compared between pristine sodium alginate/β-cyclodextrin (SA-β-CD) and sodium alginate/β-cyclodextrin immobilized carbon nanotubes (SA-β-CD/CNTs) hydrogel. Both hydrogels were characterized by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) spectral analysis, field emission scanning electron microscopy (FESEM), electron dispersive spectroscopy (EDX), thermogravimetric analysis (TGA) and Brunauer–Emmett–Teller (BET) surface area analysis. The results showed SA-β-CD/CNTs hydrogel exhibits excellent thermal stability, high specific surface area and large porosity compared with SA-β-CD hydrogel. Batch experiments were performed to study the effect of several adsorptive variables such as initial concentration, pH, contact time and temperature. The adsorption performance of the prepared SA-β-CD/CNTs hydrogel was comprehensively reported with maximum percentage removal of up to 79.86% for SA-β-CD/CNTs and 69.54% for SA-β-CD. The optimum adsorption conditions were reported when the concentration of Ni(II) solution was maintained at 100 ppm, pH 5, 303 K, and contacted for 120 min with a 1000 mg dosage. The Freundlich isotherm and pseudo-second order kinetic model are the best fits to describe the adsorption behavior. A thermodynamic study was also performed. The probable interaction mechanisms that enable the successful binding of Ni(II) on hydrogels, including electrostatic attraction, ion exchange, surface complexation, coordination binding and host–guest interaction between the cationic sites of Ni(II) on both SA-β-CD and SA-β-CD/CNTs hydrogel during the adsorption process, were discussed. The regeneration study also revealed the high efficiency of SA-β-CD/CNTs hydrogel on four successive cycles compared with SA-β-CD hydrogel. Therefore, this work signifies SA-β-CD/CNTs hydrogel has great potential to remove Ni(II) from an aqueous environment compared with SA-β-CD hydrogel.
Progress of Polymer Application in Coated Proppant and Ultra-Low Density Proppant
Authors: Chen Tao , Gao Jie , Zhao Yuan , Liang Tian , Hu Guowen , Han Xiaobing
Published: December 2022

Design, synthesis and application of low-density proppant (LDP) are of great significance for efficient and clean exploitation of low permeability oil and gas. On the basis of a brief introduction of hydraulic fracturing and the application of traditional proppants, this review systematically summarized the polymer application progress in LDP, including coated sand, coated ceramics, coated nutshells, especially for polymer composites based ultra-low density proppant (ULDP). Finally, the existing problems and future development direction are also prospected.
Structural Features of Eu3+ and Tb3+-Bipyridinedicarboxamide Complexes
Authors: Miroshnichenko Anna S. , Deriabin Konstantin V. , Rashevskii Artem A. , Suslonov Vitalii V. , Novikov Alexander S. , Mukhin Ivan S. , Islamova Regina M.
Published: December 2022

Photoluminescent lanthanide complexes of Eu3+ and Tb3+ as central atoms and N6,N6’-diisopropyl-[2,2′-bipyridine]-6,6′-dicarboxamide as ligand were synthesized. The structure of these complexes was established by single-crystal X-ray diffraction, mass spectrometry, 1H and 13C nuclear magnetic resonance, ultraviolet-visible, infrared spectroscopy, and thermogravimetry. Bipyridinic ligands provide formation of coordinatively saturated complexes of lanthanide ions and strong photoluminescence (PL). The Eu3+- and Tb3+-complexes exhibit PL emission in the red and green regions observed at a 340 nm excitation. The quantum yield for the complexes was revealed to be 36.5 and 12.6% for Tb3+- and Eu3+-complexes, respectively. These lanthanide compounds could be employed as photoluminescent solid-state compounds and as emitting fillers in polymer (for example, polyethylene glycol) photoluminescent materials.
Injectable Nanomedicine–Hydrogel for NIR Light Photothermal–Chemo Combination Therapy of Tumor
Authors: Qi Dashan , Zhu Haowei , Kong Yingjie , Shen Qingming
Published: December 2022

Traditional hydrogels have drawbacks such as surgical implantation, large wound surfaces, and uncontrollable drug release during tumor treatment. In this paper, targeted nanomedicine has been combined with injectable hydrogel for photothermal–chemotherapy combination therapy. First, targeted nanomedicine (ICG—MTX) was fabricated by combining near-infrared (NIR) photothermal reagents (ICG) and chemotherapy drugs (MTX). The ICG—MTX was then mixed with the hydrogel precursor and radical initiator to obtain an injectable hydrogel precursor solution. Under the irradiation of NIR light, the precursor solution could release alkyl radicals, which promote the transition of the precursor solution from a liquid to a colloidal state. As a result, the nanomedicine could effectively remain at the site of the tumor and continue to be released from the hydrogel. Due to the targeted nature of MTX, the released ICG—MTX could target tumor cells and improve the accuracy of photothermal–chemo combination therapy. The results indicated that the injectable nanomedicine–hydrogel system has a favorable therapeutic effect on tumors.
A New Stress-Based Formulation for Modeling Notched Fiber-Reinforced Laminates
Authors: Liu Xian , Wang Linxin , Luo Quantian , Bai Zhonghao , Li Qing , Hu Jian
Published: December 2022

Laminated plates are often modeled with infinite dimensions in terms of the so-called Whitney–Nuismer (WN) stress criteria, which form a theoretical basis for predicting the residual properties of open-hole structures. Based upon the WN stress criteria, this study derived a new formulation involving finite width; the effects of notch shape and size on the applicability of new formulae and the tensile properties of carbon-fiber-reinforced plastic (CFRP) laminates were investigated via experimental and theoretical analyses. The specimens were prepared by using laminates reinforced by plain woven carbon fiber fabrics and machined with or without an open circular hole or a straight notch. Standard tensile tests were performed and measured using the digital image correlation (DIC) technique, aiming to characterize the full-field surface strain. Continuum damage mechanics (CDMs)-based finite element models were developed to predict the stress concentration factors and failure processes of notched specimens. The characteristic distances in the stress criterion models were calibrated using the experimental results of un-notched and notched specimens, such that the failure of carbon fiber laminates with or without straight notches could be analytically predicted. The experimental results demonstrated well the effectiveness of the present formulations. The new formula provides an effective approach to implementing a finite-width stress criterion for evaluating the tensile properties of notched fiber-reinforced laminates. In addition, the notch size has a great effect on strength prediction while the fiber direction has a great influence on the fracture mode.
Evaluation of Lapatinib-Loaded Microfibers Prepared by Centrifugal Spinning
Authors: Bitay Enikő , Gergely Attila Levente , Kántor József , Szabó Zoltán-István
Published: December 2022

Lapatinib (Lap) is a lypophilic drug frequently used in cancer treatment; however, due to its limited solubility and permeability, achieving therapeutic dose through oral administration proves to be a challenge. There are various methods for enhancing the solubility of Lap and other similar drugs, one being the preparation of amorphous solid dispersions (ASD). In this study, a Lap-loaded polyvinylpyrrolidone (PVP) fiber mat was created with centrifugal spinning from a PVP/Lap solution in dimethyl formamide and ethanol. The production rate was 12.2 g/h dry fibers, and the fibers had an average thickness of 2.55 ± 0.92 μm. In the differential scanning calorimetry (DSC) thermogram of the fiber mat, the melting peak of the crystalline Lap was not visible, suggesting that Lap was in an amorphous state. A dissolution study was carried out in 0.2 M phosphate buffer saline solution at 37 °C. UV spectrophotometry data indicated that in the sample containing the fiber mat, the Lap concentration was 332 μg/mL (66%) in 10 min, decreasing to 227 μg/mL by 45 min. Meanwhile the crystalline Lap formed a 30–40 μg/mL (6–8%) solution in 5 min, maintaining that concentration. We conclude that centrifugal spinning can be an effective and easy method to produce ASDs.
Prediction of the Viscoelastic Properties of a Cetyl Pyridinium Chloride/Sodium Salicylate Micellar Solution: (II) Prediction of the Step Rate Experiments
Authors: Huang Shuxin
Published: December 2022

The reliable viscoelastic characterization and prediction of micellar solution is still required in industrial applications of the solution, e.g., in surfactant flooding and pharmaceuticals. Based on the recent theoretical characterization of the viscoelastic properties of a cetyl pyridinium chloride/sodium salicylate (CPyCl/NaSal) wormlike micellar solution with a structuralized constitutive model in the work published in 2022, the present work predicted five groups of transient shear viscoelasticities of the solution experimentally obtained in 2010, which include the first normal stress difference (N1) versus time curve in the start-up experiment, the shear stress (τ12) in the start-up experiment, τ12 in the long-term start-up experiment, the stress relaxation upon cessation of steady shear flow, and the transient N1/τ12 in the step strain experiment. The study findings clearly show an improvement in the predictions of the viscoelastic properties of the micellar solution compared with those predicted previously. For example, the experimental N1/τ12 is 9 at the strain of 9 in the step strain experiment, and the corresponding previous and present predictions are 2.47 and 8.45, respectively.
On Efficient Powder Manufacturing Using Process Control Methods and Cybernetics: A Background, Results and Policy Case Study
Authors: Nsugbe Ejay
Published: December 2022

Powder manufacturing processes involve a systematic processing of particulate material towards forming a final product which needs to meet specific quality standards. A means towards ensuring that standards are met in a manufacturing plant is to apply self-regulating intelligent machinery that can take mitigatory actions in the presence of a process deviation or unsatisfactory process behavior. Given a case study of an open-loop batch powder agglomeration process, this work synthesizes the process of how a feedback element can be applied towards the powder manufacturing plant in order to allow for self-regulation and process optimization which, in turn, would increase process efficiency, minimize waste and ensure that the overall product quality meets production targets. Focusing on a proposed cybernetic loop with a feedback element, a vital component is the ability to measure key quality attributes of the powder mixture, which is crucial towards ensuring the control algorithm is able to implement the most reflective and appropriate control strategy on the powder process; thus, this work discusses heavily the sensing and associated signal processing component of the cybernetic loop. The results from the reviewed signal processing scenarios which comprised the in-process material spanned estimation accuracies of 3–10%, depending on the scenario that was considered. This paper also addresses the feared dystopian view of mass redundancy and job losses in the age of the introduction of enhanced automation technology within a manufacturing process, where it is distilled what kinds of knock-on effects can be expected as a result of the technology, in addition to means by which policy makers can contribute towards ensuring that the adaptation and transition process is as smooth as possible.
Magnetic Activated Biochar Fe3O4-MOS Made from Moringa Seed Shells for the Adsorption of Methylene Blue
Authors: Li Meiping , Dong Cheng , Guo Caixia , Yu Ligang
Published: December 2022

In recent years, more and more biochars have been employed to treat dye wastewater. In order to increase the utilization of moringa seed shell resources and enrich the removal method of methylene blue (MB) in solution, in the current study, the magnetic moringa seed shells biochar was prepared through ultrasonic-assisted impregnation and pyrolysis, while Fe3O4 was used to activate the material to obtain adsorption (Fe3O4-MOS). The prepared adsorbents were characterized by SEM-EDS, XRD, XPS, FTIR, N2 adsorption and desorption and VSM. Under the suitable experimental conditions, the removal rate can be close to 100% and the maximum adsorption capacity of MB could be 219.60 mg/g. The Freundlich model provided a good match to the data presented by the adsorption isotherm, and the adsorption of MB on Fe3O4-MOS was a spontaneous and endothermic reaction. Study of the mechanism indicated that pore adsorption, electrostatic interaction, hydrogen bond, and π-π interaction were the major adsorption mechanisms. After five cycles, it was found that Fe3O4-MOS had a high removal rate for MB, which was close to 90%. This work provides a new idea for moringa seed shells and the results confirm that Fe3O4-MOS has substantial potential for dye wastewater treatment.
3D Computational Fluid Dynamics Analysis of a Convective Drying Chamber
Authors: Daza-Gómez Miguel Andrés Mauricio , Gómez Velasco Carlos Andrés , Gómez Daza Juan Carlos , Ratkovich Nicolás
Published: December 2022

The drying industry has grown considerably due to the tremendous demand for non-perishable food. Convective drying is one of the most popular equipment in the drying industry (food, chemical, pharmaceutical, etc.). One of the drawbacks of this equipment, when used for convective drying, is the non-uniformity in the final product quality. This study presents the development of a numerical model through Computational Fluid Dynamics (CFD). The drying chamber of a heat pump dryer is assessed from the perspective of drying air velocity and temperature profiles. The model was developed by solving different transport phenomena-related equations. The established methodology was set up to evaluate how the drying air velocity and temperature distribution affect the drying chamber. These results will define if there is a need to redesign it. The air velocity and temperature profile results show a need to redesign the chamber. Only trays 2, 3, and 4 are the ones that would achieve the drying of the products. The proposed solution is to implement air distributors or modify the tray positioning to make the drying air and temperature distribution homogeneous.
A Resilience-Oriented Bidirectional ANFIS Framework for Networked Microgrid Management
Authors: Afzal Muhammad Zeshan , Aurangzeb Muhammad , Iqbal Sheeraz , Rehman Atiq ur , Kotb Hossam , AboRas Kareem M. , Elgamli Elmazeg , Shouran Mokhtar
Published: December 2022

This study implemented a bidirectional artificial neuro-fuzzy inference system (ANFIS) to solve the problem of system resilience in synchronized and islanded grid mode/operation (during normal operation and in the event of a catastrophic disaster, respectively). Included in this setup are photovoltaics, wind turbines, batteries, and smart load management. Solar panels, wind turbines, and battery-charging supercapacitors are just a few of the sustainable energy sources ANFIS coordinates. The first step in the process was the development of a mode-specific control algorithm to address the system’s current behavior. Relative ANFIS will take over to greatly boost resilience during times of crisis, power savings, and routine operations. A bidirectional converter connects the battery in order to keep the DC link stable and allow energy displacement due to changes in generation and consumption. When combined with the ANFIS algorithm, PV can be used to meet precise power needs. This means it can safeguard the battery from extreme conditions such as overcharging or discharging. The wind system is optimized for an island environment and will perform as designed. The efficiency of the system and the life of the batteries both improve. Improvements to the inverter’s functionality can be attributed to the use of synchronous reference frame transformation for control. Based on the available solar power, wind power, and system state of charge (SOC), the anticipated fuzzy rule-based ANFIS will take over. Furthermore, the synchronized grid was compared to ANFIS. The study uses MATLAB/Simulink to demonstrate the robustness of the system under test.
Digital Twin Modelling Method of Five-Axis Machine Tool for Predicting Continuous Trajectory Contour Error
Authors: Lyu Dun , Liu Jian , Luo Shiyou , Liu Shuo , Cheng Qunlin , Liu Hui
Published: December 2022

The CNC machine tool is the passive executor of machining code. It cannot predict the machining accuracy during machining. If the error is found to be out of tolerance after processing, it will not only scrap the parts, but also greatly affect the processing efficiency. This phenomenon is very prominent when machining sculptured surface parts with five-axis machine tools. Therefore, this paper proposes a Digital Twin (DT) modeling method of five-axis machine tools for predicting Continuous Trajectory Contour Error (CTCE) caused by tracking errors and geometric errors. The DT consists of three parts: the Setpoints Trajectory (ST) model, the Actual Trajectory (AT) model considering tracking errors and geometric errors and the CTCE model. For a specific machine tool, according to the basic geometric information of the machine tool (tool length, kinematic chain information, etc.) and 41 geometric errors, the DT can be established. Inputting the Setpoints Positions (SPs) and the Linear Encoder Detection Positions (LEDPs), the DT can be used to predict the Tool-Tip Position Trajectory (TTPT) contour error and the Tool Orientation Trajectory (TOT) contour error. In order to verify the proposed method experimentally, the KMC400S U five-axis machine tool is selected to establish its DT by which the contour error of the S-shaped trajectory are predicted offline. Then, the DMU50 five-axis machine tool is selected to establish its DT to predict the contour error of the circular trajectory in real time. Combined with the deep motion mechanism, this paper proposes a DT modeling method for the vertical application scene of parts machining accuracy prediction, which is of great significance to developing the DT application theory and ensuring the machining accuracy of parts.
Dynamics of Pressure Variation in Closed Vessel Explosions of Diluted Fuel/Oxidant Mixtures
Authors: Giurcan Venera , Razus Domnina , Mitu Maria , Movileanu Codina
Published: December 2022

Nitrous oxide is widely used as oxidizer or nitriding agent in numerous industrial activities such as production of adipic acid and caprolactam and even for production of some semiconductors. Further, it is used as an additive in order to increase the power output of engines, and as an oxidizer in propulsion systems of rockets, because it has a large heat of formation (+81.6 kJ mol−1). N2O is highly exothermic, and during its decomposition a supplementary heat amount is released, so it needs special handling conditions. The combustion of fuels in nitrous oxide atmosphere can lead to high unstable and turbulent deflagrations that speedily self-accelerate and therefore a deflagration can change to a detonation. The peak explosion pressure and the maximum rate of pressure rise of explosions in confined spaces are key safety parameters to evaluate the hazard of processes running in closed vessels and for design of enclosures able to withstand explosions or of their vents used as relief devices. The present study reports some major explosion parameters such as the maximum (peak) explosion pressures pmax, explosion times θmax, maximum rates of pressure rise (dp/dt)max and severity factors KG for ethylene-nitrous oxide mixtures (lean and stoichiometric) diluted with various amounts of N2, at various initial pressures (p0 = 0.50–1.50 bar), in experiments performed in a spherical vessel centrally ignited by inductive-capacitive electric sparks. The influence of the initial pressure and composition on pmax, θmax and (dp/dt)max is discussed. The data are compared with similar values referring to ethylene-air mixtures measured in the same initial conditions. It was found that at identical C/O ratios with ethylene-air, ethylene-N2O-N2 mixtures develop higher explosion pressures and higher rates of pressure rise, due to the exothermic dissociation of N2O under flame conditions.
Derivation and Verification of Gaussian Terrain Wake Model Based on Wind Field Experiment
Authors: Liu Wei , Zhu Xiaoxun , Wang Kaike , Gao Xiaoxia , Zhang Shaohai , Dong Lijiang , Shi Zeqi , Lu Hongkun , Zhou Jie
Published: December 2022

Aiming at the problem where the current engineering wake model does not describe the wind speed distribution of the wake in the complex terrain wind farm completely, based on the three-dimensional full wake model (3DJGF wake model), this paper proposed a wake model that can predict the three-dimensional wind speed distribution of the entire wake region in the complex wind farm, taking into account the Coanda effect, wind shear effect, and wake subsidence under the Gaussian terrain. Two types of Doppler lidar were used to conduct wind field experiments, and the inflow wind profile and three-dimensional expansion of the wake downstream of the wind turbine on the Gaussian terrain were measured. The experimental results showed that the wake centerline and terrain curve showed similar variation characteristics, and the near wake profile was similar to a super-Gaussian shape (asymmetric super-Gaussian shape) under low-wind-speed conditions, while the near wake profile presented a bimodal shape (asymmetric bimodal shape) under high-wind-speed conditions. The predicted profiles of the Gaussian terrain wake model were compared with the experimental data and the three typical wake models. The comparison results showed that the newly proposed Gaussian terrain wake model fit well with the experimental data in both near wake and far wake regions, and it had better performance in predicting the wake speed of the Gaussian terrain wind farm than the other three wake models. It can effectively predict the three-dimensional velocity distribution in the whole wake region of complex terrain.
Experimental Study and an RSM Modelling on Drilling Characteristics of the Sheep Horn Particle Reinforced Epoxy Composites for Structural Applications
Authors: Anjinappa Chandrashekar , Y. J Manjunath , Ahmed Omar Shabbir , Abbas Mohamed , Alahmadi Ahmad Aziz , Alwetaishi Mamdooh , Alzaed Ali Nasser
Published: December 2022

Recent environmental concern has been raised about the development of biocomposites because of their low cost, eco-friendliness, and biodegradability. Machining of polymeric composite is inevitable during assembly of structural components. In view of creating holes in structural composites, drilling is necessary and it is essential to carry out research to find the optimal machining parameters. The experimental assessment and prediction of the thrust force and torque involved in drilling composites reinforced with sheep horn are presented in this work. The matrix and sheep horn particles were combined in the right proportions before being moulded and poured into a mould, then allowed to cure at room temperature. Investigated properties included ultimate tensile strength, flexural strength, and hardness. To evaluate the quality of the hole, micrographs of the drilled hole were employed. When the mixture was optimised based on the properties, it was found that a 70:30 ratio produced the best results. Thrust force and torque of 58 N and 4.8 N-mm, respectively, were observed for sheep horn filler laminates which were drilled using the combination of 6 mm diameter, 0.1 mm/rev feed rate, and 400 rpm speed. This is by far the best among the combinations used in the experiment. Additionally, the experimental outcomes indicate that the feed rate and spindle speed are the most significant factors affecting the thrust force. Since there were minimal errors in the comparison, the central composite design modelling is consummate. Overall, the extensive experimental effort offers several options to utilise this composite material in future applications across a wide range of fields.
Production of Ultra-Clean Coal by the Combined Method of Grinding and Collector Gasification Flotation
Authors: Shen Liang , Gong Jiabao , Liu Yifang
Published: December 2022

The preparation and application of ultra-clean coal is one of the important aspects of clean energy technology. However, the preparation of ultra-clean coal is mainly chemical methods, which are low in efficiency, high in energy consumption and expensive. It is urgent to find an effective method to prepare ultra-clean coal. In this paper, the combined method of grinding and the collector gasification flotation method was used to obtain ultra-clean coal. The effects of grinding time on the particle size composition, mineral dissociation, surface properties and flotation results of coal samples were studied. The grinding test results show that with the increase in grinding time, the particle size and the pore diameter of coal samples decreased gradually, while the specific surface area and pore volume of coal samples gradually increased. When the grinding time was 20 min, the D90 and D[4,3] of grinding products were 5.20 um and 4.23 um, respectively. The ash content of −1.3 g/cm3 was less than 1% when the grinding time was 20 min. Compared with the traditional flotation method, the collector gasification flotation method can obtain a higher concentrate yield and lower concentrate ash content. When the amount of collector was 2.0 kg/t, the yield of clean coal obtained by the collector gasification flotation method was 4.1% higher than that by the traditional flotation method, while the ash content of clean coal was 0.3% lower.
Modeling Study on Melt Flow, Heat Transfer, and Inclusion Motion in the Funnel-shaped Molds for Two Thin-Slab Casters
Authors: Xu Lin , Pei Qun-Wu , Han Ze-Feng , Yang Shuo , Wang Jian-Yu , Yao Yan-Tao
Published: December 2022

For the purpose of studying compact strip production (CSP) funnel-shaped mold and flexible thin-slab rolling (FTSR) funnel-shaped mold, a three-dimensional (3D) multi-field coupling mathematical model was established to describe the electromagnetic braking (EMBr) continuous casting process. To investigate the metallurgical effect of EMBr in the CSP and FTSR funnel-shaped thin-slab molds, a Reynolds-averaged Navier–Stokes (RANS) turbulence model, together with an enthalpy–porosity approach, was established to numerically simulate the effect of ruler EMBr on the behaviors of melt flow, heat transfer, solidification, and inclusion movement in high-speed casting. The simulation results indicate that the application of ruler EMBr in the CSP and FTSR molds shows great potential to improve the surface temperature of molten steel and reduce the penetration depth of downward backflow. This contributes to the melting of the slag rim near the meniscus region and facilitates the floating removal of the inclusions in the molten pool. In addition, in comparison with the case of no EMBr, the parametric study shows that the braking effect of ruler EMBr with an electromagnetic parameter of 0.5 T can enhance the upward backflow in the two high-speed thin-slab molds. The enhanced upward backflow can successfully entrain the inclusions to the top of the mold and improve the activity of surface fluctuations to avoid the formation of the slag rim. For instance, for the ruler EMBr applied to the FTSR mold, the maximum amplitude of surface fluctuation and the floatation removal quantity of inclusions with a diameter of 100 μm are increased by 4.6 percent and 51 percent, respectively.
Analysis of Influencing Factors in Pilot Experiment for Synthesis of Natural Gas Hydrate by Spray Method
Authors: Ma Yun , Zhu Jinzhao , Meng Qingguo , Ding Chunxiao , Teng Jinbing , Wang Xin , Lu Qian
Published: December 2022

In recent years, the technology of storing and transporting natural gas in the form of hydrate has received a lot of attention. At present, the research on the synthesis of natural gas hydrate for the purpose of storage and transportation is still in the laboratory stage, and its synthesis process is in the design and conception stage. The influencing factors of natural gas hydrate synthesis under pilot-scale conditions are more complex. Moreover, pilot experiments are oriented to actual production, and its economic feasibility and operational convenience have higher requirements. This paper aimed to study the influencing factors of gas hydrate synthesis by spray method under pilot-scale conditions. Under specific conditions of surfactant and pressure, we carried out research on the effects of reaction temperature, different forms of atomizers, high-pressure pump flow, experimental water, and other factors. Experiments show that the optimal synthesis conditions were a temperature of −5 °C, a pressure of 5 MPa, a conical nozzle, a generated gas hydrate as the hydrate of type I structure, and a gas storage capacity of 1:123 (gas–water ratio).
Interaction between Iron Fluoride and Molten FLiBe
Authors: Arkhipov Stepan P. , Zaikov Yury P. , Arkhipov Pavel A. , Mullabaev Albert R.
Published: December 2022

The equilibrium potentials of iron in a LiF-BeF2-FeF2 melt were measured using the EMF method and were dependent upon the temperature and iron fluoride concentrations. The empirical equations for the isotherms and equilibrium polytherms of the iron fluoride concentration were obtained. The cathode polarization of iron fluoride in the molten mixture of lithium and beryllium fluoride was measured using the current switch off method from the stationary state. It was found that in the studied temperature and concentration ranges of iron fluoride in the LiF-BeF2 electrolyte, the valence state of iron in the melt is mainly +2. According to the experimental values of the equilibrium potentials of the iron electrode in the LiF-BeF2-FeF2 melt, the conditional standard potentials of iron were calculated relative to the fluoride reference electrode in the molten mixture of lithium and beryllium fluoride. The conditional standard values of the Gibbs energy change were calculated at the formation of iron difluoride from the element in the form of dilute solutions, as were the thermodynamic values (enthalpy and entropy) when iron difluoride was mixed with LiF-BeF2.
Assessing Waste Marble Powder Impact on Concrete Flexural Strength Using Gaussian Process, SVM, and ANFIS
Authors: Sharma Nitisha , Thakur Mohindra Singh , Kumar Raj , Malik Mohammad Abdul , Alahmadi Ahmad Aziz , Alwetaishi Mamdooh , Alzaed Ali Nasser
Published: December 2022

The study’s goal is to assess the flexural strength of concrete that includes waste marble powder using machine learning methods, i.e., ANFIS, Support vector machines, and Gaussian processes approaches. Flexural strength has also been studied by using the most reliable approach of sensitivity analysis in order to determine the influential independent variable to predict the dependent variable. The entire dataset consists of 202 observations, of which 120 were experimental and 82 were readings from previous research projects. The dataset was then arbitrarily split into two subsets, referred to as the training dataset and the testing dataset, each of which contained a weighted percentage of the total observations (70–30). Output was concrete mix flexural strength, whereas inputs comprised cement, fine and coarse aggregates, water, waste marble powder, and curing days. Using statistical criteria, an evaluation of the efficacy of the approaches was carried out. In comparison to other algorithms, the results demonstrate that the Gaussian process technique has a lower error bandwidth, which contributes to its superior performance. The Gaussian process is capable of producing more accurate predictions of the results of an experiment due to the fact that it has a higher coefficient of correlation (0.7476), a lower mean absolute error value (1.0884), and a smaller root mean square error value (1.5621). The number of curing days was identified as a significant predictor, in addition to a number of other factors, by sensitivity analysis.
Fore-Giving in Time: A Husserlian Reading of Genesis, Luke, and John
Authors: Costello Peter R.
Published: December 2022

This paper attempts to perform a phenomenology of forgiveness by way of careful analysis of texts on time-consciousness and alterity by Edmund Husserl. It does so in two ways: first, by identifying the manner in which we give time to ourselves as both absolute and concrete subjectivity; and second by identifying the way in which our relation to other persons has an isomorphic, structural similarity with our self-relation as temporality. The final part of the paper engages with three biblical texts—the story of Joseph and his brothers in Genesis, where forgiveness is mentioned for the first time—and two short passages in the Gospels of Luke and John. Ultimately, the paper concludes that forgiveness of self and other occurs as a kind of pre-giving or fore-giving in the sense of opening up new meaning for us all to inhabit.
The Integral Formation of Catholic School Teachers
Authors: Roberts Amy E. , O’Shea Gerard
Published: December 2022

The Catholic Church has a long history of conducting schools as part of its mission to evangelize. This paper will contend that in order for teachers to implement the evangelistic mission of Catholic schools, they themselves need an integral formation that puts every dimension of their human nature—body, emotions, will, and intellect—in ongoing communion with Christ and His Church. A brief examination of the impact of secularization in the United States on the Catholic school mission indicates that teachers are inadequately formed to fulfill that mission. Contemplative practice, a common faith formation practice used for Catholic school teachers, will be evaluated as insufficient for achieving its goal because it does not fully account for the way God created human beings. Contemplative practice relies heavily on the work of John Dewey, who applied inadequate anthropological principles to the task of human learning and teacher education. By contrast, faith formation efforts that account for human nature engage both the intellectus and the ratio, and in so doing engage the teacher’s whole integrated person. Teacher faith formation can facilitate the teacher’s encounter with God, allowing Him to form her, by providing analogical encounters with Him through the transcendentals and sacramental encounters with Him in the liturgy.
Comparison of Classic Classifiers, Metaheuristic Algorithms and Convolutional Neural Networks in Hyperspectral Classification of Nitrogen Treatment in Tomato Leaves
Authors: Benmouna Brahim , Pourdarbani Raziyeh , Sabzi Sajad , Fernandez-Beltran Ruben , García-Mateos Ginés , Molina-Martínez José Miguel
Published: December 2022

Tomato is an agricultural product of great economic importance because it is one of the most consumed vegetables in the world. The most crucial chemical element for the growth and development of tomato is nitrogen (N). However, incorrect nitrogen usage can alter the quality of tomato fruit, rendering it undesirable to customers. Therefore, the goal of the current study is to investigate the early detection of excess nitrogen application in the leaves of the Royal tomato variety using a non-destructive hyperspectral imaging system. Hyperspectral information in the leaf images at different wavelengths of 400–1100 nm was studied; they were taken from different treatments with normal nitrogen application (A), and at the first (B), second (C) and third (D) day after the application of excess nitrogen. We investigated the performance of nine machine learning classifiers, including two classic supervised classifiers, i.e., linear discriminant analysis (LDA) and support vector machines (SVMs), three hybrid artificial neural network classifiers, namely, hybrid artificial neural networks and independent component analysis (ANN-ICA), harmony search (ANN-HS) and bees algorithm (ANN-BA) and four classifiers based on deep learning algorithms by convolutional neural networks (CNNs). The results showed that the best classifier was a CNN method, with a correct classification rate (CCR) of 91.6%, compared with an average of 85.5%, 68.5%, 90.8%, 88.8% and 89.2% for LDA, SVM, ANN-ICA, ANN-HS and ANN-BA, respectively. This shows that modern CNN methods should be preferred for spectral analysis over other classical techniques. These CNN architectures can be used in remote sensing for the precise detection of the excessive use of nitrogen fertilizers in large extensions.
Impact of Satellite Attitude on Altimetry Calibration with Microwave Transponders
Authors: Kokolakis Costas , Piretzidis Dimitrios , Mertikas Stelios P.
Published: December 2022

Satellite altimetry plays a key role in monitoring changes in sea level and climate change. The quality of satellite altimetry products is commonly ensured through dedicated calibration. One such calibration is with microwave transponders acting as ground reference point targets. It is common practice that satellite ranges between the transponder phase center and the satellite center of gravity (CoG) are compared against the true geometric ranges to determine bias. Transponder ranges are, however, realized by the two phase centers of the altimeter and the ground transponder. So, to make this comparison feasible, the space origin of the measured range is transferred from the altimeter phase center (APC) to the satellite CoG by applying a constant offset, usually referred to as “CoG correction”. Instead of a fixed “CoG correction”, this work introduces the actual vector between APC and CoG in space, by examining the satellite attitude. Thus, the observed and geometric distances to the transponder are both referred to the APC. The case of Jason-3 and Sentinel-6A Michael Freilich (Sentinel-6A MF) with two transponders on Crete (CDN1) and Gavdos (GVD1) islands is examined. At first, the attitude of Jason-3 is determined by its quaternions. Then, analysis reveals that the transponder bias is correlated with the Jason-3 satellite attitude. The revised calibration brings about bias changes which fluctuate from about −2 mm to 1 mm in range and from −110μs to +110 μs in datation for Jason-3. Spectral analysis on the bias differences between the revised and conventional transponder calibrations reveals constituents with periods of 117, 39 and 23 days. Finally, the revised methodology on crossover calibrations over the GVD1 transponder results in an improvement between the mean bias of the ascending and descending orbits by 12% for Jason-3 and by 14% (preliminary) for Sentinel-6A MF.
Ore-Waste Discrimination Using Supervised and Unsupervised Classification of Hyperspectral Images
Authors: Abdolmaleki Mehdi , Consens Mariano , Esmaeili Kamran
Published: December 2022

Ore and waste discrimination is essential for optimizing exploitation and minimizing ore dilution in a mining operation. The conventional ore/waste discrimination approach relies on the interpretation of ore control by geologists, which is subjective, time-consuming, and can cause safety hazards. Hyperspectral remote sensing can be used as an alternative approach for ore/waste discrimination. The focus of this study is to investigate the application of hyperspectral remote sensing and deep learning (DL) for real-time ore and waste classification. Hyperspectral images of several meters of drill core samples from a silver ore deposit labeled by a site geologist as ore and waste material were used to train and test the models. A DL model was trained on the labels generated by a spectral angle mapper (SAM) machine learning technique. The performance on ore/waste discrimination of three classifiers (supervised DL and SAM, and unsupervised k-means clustering) was evaluated using Rand Error and Pixel Error as disagreement analysis and accuracy assessment indices. The results showed that the DL method outperformed the other two techniques. The performance of the DL model reached 0.89, 0.95, 0.89, and 0.91, respectively, on overall accuracy, precision, recall, and F1 score, which indicate the strong capability of the DL model in ore and waste discrimination. An integrated hyperspectral imaging and DL technique has strong potential to be used for practical and efficient discrimination of ore and waste in a near real-time manner.
A Multi-Source Data Fusion Method to Improve the Accuracy of Precipitation Products: A Machine Learning Algorithm
Authors: Assiri Mazen E. , Qureshi Salman
Published: December 2022

In recent decades, several products have been proposed for estimating precipitation amounts. However, due to the complexity of climatic conditions, topography, etc., providing more accurate and stable precipitation products is of great importance. Therefore, the purpose of this study was to develop a multi-source data fusion method to improve the accuracy of precipitation products. In this study, data from 14 existing precipitation products, a digital elevation model (DEM), land surface temperature (LST) and soil water index (SWI) and precipitation data recorded at 256 gauge stations in Saudi Arabia were used. In the first step, the accuracy of existing precipitation products was assessed. In the second step, the importance degree of various independent variables, such as precipitation interpolation maps obtained from gauge stations, elevation, LST and SWI in improving the accuracy of precipitation modelling, was evaluated. Finally, to produce a precipitation product with higher accuracy, information obtained from independent variables were combined using a machine learning algorithm. Random forest regression with 150 trees was used as a machine learning algorithm. The highest and lowest degree of importance in the production of precipitation maps based on the proposed method was for existing precipitation products and surface characteristics, respectively. The importance degree of surface properties including SWI, DEM and LST were 65%, 22% and 13%, respectively. The products of IMERGFinal (9.7), TRMM3B43 (10.6), PRECL (11.5), GSMaP-Gauge (12.5), and CHIRPS (13.0 mm/mo) had the lowest RMSE values. The KGE values of these products in precipitation estimation were 0.56, 0.48, 0.52, 0.44 and 0.37, respectively. The RMSE and KGE values of the proposed precipitation product were 6.6 mm/mo and 0.75, respectively, which indicated the higher accuracy of this product compared to existing precipitation products. The results of this study showed that the fusion of information obtained from different existing precipitation products improved the accuracy of precipitation estimation.
Effects of Inter- and Intra-Specific Interactions on Moose Habitat Selection Limited by Temperature
Authors: Bao Heng , Zhai Penghui , Wen Dusu , Zhang Weihua , Li Ye , Yang Feifei , Liang Xin , Yang Fan , Roberts Nathan J. , Xu Yanchun , Jiang Guangshun
Published: December 2022

Habitat selection and daily activity patterns of large herbivores might be affected by inter- and intra-specific interaction, changes of spatial scale, and seasonal temperature. To reveal what factors were driving the habitat selection of moose, we collected moose (Alces alces) and roe deer (Capreolus pygargus bedfordi) occurrence data, analyzed the multi-scale habitat selection and daily activity patterns of moose, and quantified the effects of spatial heterogeneity distribution of temperature, as well as the occurrence of roe deer on these habitat selection processes. Our results suggested that moose and roe deer distribution spatially overlap and that moose habitat selection is especially sensitive to landscape variables at large scales. We also found that the activity patterns of both sexes of moose had a degree of temporal separation with roe deer. In the snow-free season, temperatures drove moose habitat selection to be limited by threshold temperatures of 17 °C; in the snowy season, there were no similar temperature driving patterns, due to the severe cold environment. The daily activity patterns of moose showed seasonal change, and were more active at dawn and nightfall to avoid heat pressure during the snow-free season, but more active in the daytime for cold adaptation to the snow season. Consequently, this study provides new insights on how the comprehensive effects of environmental change and inter- and intra- specific relationships influence the habitat selection and daily activity patterns of moose and other heat sensitive animals with global warming.