The process of gear machining consumes a large amount of energy and causes serious pollution to the environment. Developing a proper process route of gear machining is the key to conserving energy and reducing emissions. Nowadays, the proper process route of gear machining is based on experience and is difficult to keep up with the development of modern times. In this article, a calculation model of low-carbon and low-energy consumption in gear machining processes was established based on an analysis of the machining process. With processing parameters as independent variables, the grey wolf algorithm was used to solve the problem. The effectiveness of the method was proven by an example of the machining process of an automobile transmission shaft.

Underground commercial buildings have received increasing attention as an emerging place of consumption. However, previous studies on underground commercial buildings have mainly focused on the impact of a specific environment on comfort or energy consumption. Few studies have been conducted from the perspective of functional use. The purpose of this paper is to investigate, in terms of functional angles, the indoor thermal environment and air quality of an underground commercial building in Zhengzhou, China, and put forward an optimal control strategy of ventilation organization. The results showed that the relative humidity of the underground shopping mall was generally above 60%, and the average temperature of 29.1 °C led to a thermal comfort problem in the catering area in summer. Meanwhile, the concentration of CO2 exceeded the allowed figures during the peak of the customer flow rate, and PM2.5 concentration in the catering area also exceeded the standard, by 43.3% and 33.3%, res... [more]

Hydrocracking is an energy-intensive process, and its control system aims at stable product specifications. When the main product is diesel, the quality measure is usually 95% of the true boiling point. Constant diesel quality is hard to achieve when the feed characteristics vary and feedback control has a long response time. This work suggests a feedforward model predictive control structure for an industrial hydrocracker. A state-space model, an autoregressive exogenous model, a support vector machine regression model, and a deep neural network model are tested in this structure. The resulting reactor temperature decisions and final diesel product quality values are compared against each other and against the actual measurements. The results show the importance of the feed character measurements. Significant improvements are shown in terms of product quality as well as energy savings through decreasing the heat duty of the preheating furnace.

Phenolic pollutants in industrial wastewater are considered to be harmful aromatic compounds. With the development of industry and pharmaceuticals, phenolic pollutants and their derivatives have gradually started to affect people’s daily lives. Therefore, it is necessary to strictly control the content of phenolic pollutants in industrial wastewater, not only for the natural environment but also for human life. The research optimized the existing treatment methods for classified pollutants, and successfully prepared a heterogeneous photo-Fenton catalyst Fe3O4@B-rGO (9.3%). The characterization results of the catalyst showed that the synthesis of the catalyst was successful, and its specific surface area was 11.28 (m2/g), and the pore volume area was 0.137 (m3/g), respectively, which were larger than those of the other two comparative catalysts. In addition, the research conclusion also showed that the catalyst prepared during the research had good catalytic activity, the treatment effi... [more]

The purpose of this study was to gain an insight into the manner in which several extraction processes (both classical as well as innovative) affected bioactive compound yield, and subsequently to assess several of their biological activities. Red clover extracts were obtained using maceration, Soxhlet extraction, turbo-extraction, ultrasound-assisted extraction, and a combination of the last two. The resulting extracts were analyzed for total phenolic and flavonoid content. The extracts presenting the best results were subjected to a phytochemical assessment by way of HPLC-MS analysis. After a final sorting based on the phytochemical profiles of the extracts, the samples were assessed for their antimicrobial activity, anti-inflammatory activity, and oxidative stress reduction potential, using animal inflammation models. The Soxhlet extraction yielded the most satisfactory results both qualitatively and quantitatively. The ultrasound-assisted extraction offered comparable yields. The e... [more]

(anise) is a dense vegetal matrix with considerable amounts of bioactive components known for its pharmacological properties. The optimization of extraction constitutes an important key to improving efficacy and avoiding wasting time. Within this framework, the present study was designed to select the most appropriate extractor solvent mixture to extract phenolic and flavonoids using Mixture Design Methodology. The concerned responses were the total phenolic content (TPC), total flavonoid content (TFC) and antioxidant ability examined by 2,2-diphenyl-l-picrylhydrazyl (DPPH) assay. Before mixture design optimization, a screening of solvents was conducted on ten polar and nonpolar solvents to choose the best solvents that give a maximum of total phenolic compounds. This first step has shown that water, ethanol and methanol were the best-used solvents. Later, an augmented centroid design investigated the solvent system’s optimization. The results of simultaneous optimization have shown th... [more]

Artificial neural networks (ANNs) have achieved great success in performing machine learning tasks, including classification, regression, prediction, image processing, image recognition, etc., due to their outstanding training, learning, and organizing of data. Conventionally, a gradient-based algorithm known as backpropagation (BP) is frequently used to train the parameters’ value of ANN. However, this method has inherent drawbacks of slow convergence speed, sensitivity to initial solutions, and high tendency to be trapped into local optima. This paper proposes a modified particle swarm optimization (PSO) variant with two-level learning phases to train ANN for image classification. A multi-swarm approach and a social learning scheme are designed into the primary learning phase to enhance the population diversity and the solution quality, respectively. Two modified search operators with different search characteristics are incorporated into the secondary learning phase to improve the a... [more]

This article addresses the decentralized multi-performance (MP) fuzzy control problem of nonlinear large-scale descriptor (LSD) systems. The considered LSD system contains several subsystems with nonlinear interconnection and external disturbances, and the Takagi−Sugeno fuzzy model (TSFM) is adopted to represent each nonlinear subsystem. Based on the proportional-plus-derivative state feedback (PDSF) scheme, we aim to design a decentralized MP fuzzy controller that guarantees the stabilization, mixed H∞, and passivity performance control (MHPPC), and the guaranteed cost control (GCC) performance of the closed-loop Takagi−Sugeno LSD (TSLSD) systems. Furthermore, we introduce the Lyapunov stability theory and the free-weighting matrix scheme to analyze the stability of the TSLSD system. The proposed sufficient conditions can be transformed as linear matrix inequality (LMI) forms through Schur’s complement, which can be easily solved with the LMI Toolbox. Finally, to illustrate the propos... [more]

Wax deposition is the main flow assurance problem that affects the oil and gas industry at various points of oil transport, hence a solution is being sought. The aim of this paper is to establish a solution using Jatropha curcas seed oil (JSO) from Malaysia and its sustainability as a wax inhibitor component. Extraction of JSO was carried out using a Soxhlet extractor and n-Hexane solvent. Characterization of JSO by gas chromatography−mass spectrometry (GC−MS) and Fourier transform infrared spectroscopy (FTIR) was performed to identify the components of JSO and their functional groups. GC−MS analysis showed that oleic acid was the major component of JSO with 44.91%. FTIR analysis showed the presence of ester fatty acid groups at a peak of 1746.48 cm−1. The analysis revealed that the high content of oleic acid in JSO has great potential as a wax inhibitor to mitigate paraffin wax deposition and improve the flowability of crude oil. This research was extended by the discovery of the proc... [more]

The increasing public attention on unceasing food safety incidents prompts the requirements of analytical techniques with high sensitivity, reliability, and reproducibility to timely prevent food safety incidents occurring. Food analysis is critically important for the health of both animals and human beings. Due to their unique physical and chemical properties, nanomaterials provide more opportunities for food quality and safety control. To date, nanomaterials have been widely used in the construction of sensors and biosensors to achieve more accurate, fast, and selective food safety detection. Here, various nanomaterial-based sensors for food analysis are outlined, including optical and electrochemical sensors. The discussion mainly involves the basic sensing principles, current strategies, and novel designs. Additionally, given the trend towards portable devices, various smartphone sensor-based point-of-care (POC) devices for home care testing are discussed.

The COVID-19 period has had a significant impact on both the global environment and daily living. The COVID-19 lockdown may provide an opportunity to enhance environmental quality. This study has evaluated the effect of the COVID-19 lockdown on the distribution of polycyclic aromatic hydrocarbons (PAHs) in the street dust (diameter < 20 µm) of different land use areas in Dhaka city, Bangladesh, using gas chromatography−mass spectrometry (GC−MS). The maximum (2114 ng g−1) concentration of ∑16 PAHs was found in the industrial area during without lockdown conditions and the minimum (932 ng g−1) concentration was found in the public facilities area during the complete lockdown. Meanwhile, due to the partial lockdown, a maximum of 30% of the ∑16 PAH concentration decreased from the situation of without lockdown in the industrial area. The highest result of 53% of the ∑16 PAH concentration decreased from the situation without lockdown to the complete lockdown in the commercial area. The 4... [more]

Understanding chemical processes at the single-molecule scale represents the ultimate limit of analytical chemistry. Single-molecule detection techniques allow one to reveal the detailed dynamics and kinetics of a chemical reaction with unprecedented accuracy. It has also enabled the discoveries of new reaction pathways or intermediates/transition states that are inaccessible in conventional ensemble experiments, which is critical to elucidating their intrinsic mechanisms. Thanks to the rapid development of single-molecule junction (SMJ) techniques, detecting chemical reactions via monitoring the electrical current through single molecules has received an increasing amount of attention and has witnessed tremendous advances in recent years. Research efforts in this direction have opened a new route for probing chemical and physical processes with single-molecule precision. This review presents detailed advancements in probing single-molecule chemical reactions using SMJ techniques. We s... [more]

A series of studies were conducted to demonstrate the feasibility of low-temperature bonding by the forming and heating an Al-8wt%Si alloy thick film on a B4C surface by cold spraying. The results show that: (1) The cracks near the joining interface are closed by the Al alloy by the process studied in this study, and a joining strength of about 220 and 240 MPa is achieved by low temperature joining of 580 °C and 600 °C, respectively.; (2) The amount of weak intermetallic compounds at the joining interface is reduced; (3) It is assumed that the reduction in the amount of Al-B-C compounds is due to the formation of the β phase during the solidification process of the Al-Si alloy, which hinders the growth of the compounds.; (4) On the primary joint surface, a continuous void group is formed in the vicinity of the β phase that surrounds the α phase, causing a decrease in the joining strength.

Soil and groundwater systems have natural attenuation potential to degrade or detoxify contaminants due to biogeochemical processes. However, such potential is rarely incorporated into active remediation strategies, leading to over-remediation at many remediation sites. Here, we propose a framework for designing and searching optimal remediation strategies that fully consider the combined effects of active remediation strategies and natural attenuation potentials. The framework integrates machine-learning and process-based models for expediting the optimization process with its applicability demonstrated at a field site contaminated with arsenic (As). The process-based model was employed in the framework to simulate the evolution of As concentrations by integrating geochemical and biogeochemical processes in soil and groundwater systems under various scenarios of remedial activities. The simulation results of As concentration evolution, remedial activities, and associated remediation c... [more]

With the continuous expansion of industrial production scale, most of the chemical process variables are nonlinear, multi-modal and dynamic. For some traditional multivariate statistical monitoring and fault diagnosis algorithms, such as principal component analysis (PCA), the premise of its application is that the process data is time-independent. To this end, a dynamic principal component analysis (DPCA) method is proposed. However, since the input matrix of DPCA fault diagnosis needs to add an augmented matrix to the original data matrix, the number of eigenvalues of the augmented matrix is too large and there are many redundant eigenvectors. Therefore, this paper proposes a fault diagnosis and monitoring algorithm combining feature selection and DPCA, which considers the dynamic characteristics of multivariate data and reduces the dimension of the input matrix. At present, the average modeling and diagnostic accuracy of PCA-based fault diagnosis on T2 statistic is 65.49%, and that... [more]

In this paper we consider a mathematical continuous-time model for biodegradation of phenol in the presence of sodium salicylate in a chemostat. The model is described by a system of three nonlinear ordinary differential equations. Based on the dynamical systems theory we provide mathematical investigations of the model including local and global analysis of the solutions. The local analysis consist in computation of two equilibrium points—one interior and one boundary (washout) equilibrium—in dependance of the dilution rate as a key model parameter. The local asymptotic stability of the equilibria is also presented. The global analysis of the model solutions comprises proving existence, uniqueness and uniform boundedness of positive solutions, as well as global asymptotic stabilizability of the dynamics. The theoretical investigations are illustrated by some numerical examples. The results in this study can be used in practice as a tool to control and optimize the chemostat performanc... [more]

The flapping hydrofoil bionic pump drives the hydrofoil to make simple harmonic motion and completes one-way water pumping in the flow passage. As a new pump device that can realize ultra-low head water delivery, the flapping hydrofoil device can effectively enrich the drainage methods of plain rivers and improve water delivery efficiency, and the passage structure is the key factor of ultra-low head devices. In this paper, the two-dimensional flow passage models are established, and the flapping of the airfoil is realized by using the dynamic grid technology. Based on the continuity equation, k-ε turbulence model, and Reynolds time-averaged equation, the flapping hydrofoil device is simulated by transient calculation. The hydraulic performance characteristics of various passages with different widths, such as square passages, micro-arc passages, and convergent−divergent passages, are calculated and simulated. The results show that, under the fixed motion parameters, the narrower the p... [more]

The COD reduction in gas to liquid (GTL) process water was optimized using response surface methodology (RSM). The biodegradation process was carried out in a spouted bed bioreactor (SBBR) using Pseudomonas aeruginosa immobilized in polyvinyl alcohol (PVA) gel. Different factors affecting the biological treatment of GTL process water (PW) were investigated. Three variables including PVA volume fraction, initial COD, and pH were investigated in the batch experiments. The biodegradation experiments were carried out by varying the initial COD values from 1000 to 3000 mg/L, pH from 5 to 8, and PVA v% from 20 to 30%. The maximum COD reduction was estimated to occur at an initial COD of 2595 mg/L, PVA v% of 27%, and pH of 7.3. At optimum conditions, the bioreactor system was able to achieve a maximum COD reduction of 89%, which is quite close to the RSM prediction value of 90%. The optimum operating conditions were used to carry out continuous biodegradation, and the results indicated that t... [more]

Since the beginning of the 21st century, agility and sustainability have played a significant role in the global manufacturing industry. The manufacturing paradigm leaning toward green procurement and organizational agility has crossed all levels of sustainability by colossally influencing the firms’ sustainable practices, innovation capacity, and eco-friendly procurements. Integrating sustainable practices in manufacturing is a complex task that demands that global economies conduct comprehensive research on the factors influencing the firms’ sustainable practices. Therefore, the study considers empirical research between organizational agility and sustainable manufacturing practices. The data was collected from 461 respondents working in the manufacturing sector by applying a convenience sampling technique. We utilized structural equation modeling (SEM) for direct and indirect hypothesis testing. The study results revealed that operational, customer, and partnering agility significan... [more]

Low speed, low capacity, and poor scalability make size-exclusion chromatography (SEC) unattractive for use in the preparative separation of proteins. We discuss a novel z2 cuboid SEC device that addresses these challenges. A z2 cuboid SEC device (~24 mL volume) was systematically compared with a conventional SEC column having the same volume and packed with the same resin. The primary objective of this study was to use the same volume of SEC medium in a much more efficient way by using the novel device. At any given flow rate, the pressure drop across the z2 cuboid SEC device was lower by a factor of 6 to 8 due to its shorter bed height and greater cross-sectional area. Under overloaded conditions, the peaks obtained during protein separation with the conventional column were poorly resolved and showed significant fronting, while those obtained with the z2 cuboid SEC device were much better resolved and showed no fronting. At any given flow rate, better resolution was obtained with th... [more]

The antibiotic azithromycin (AZM) is one of the most persistent in the environment, with potential to cause serious health and environmental problems. As some polluting discharges containing this antibiotic can reach the soil, it is clearly relevant determining the ability of soils with different characteristics to retain it. In this research, AZM adsorption and desorption were studied for a variety of soils, using batch-type experiments. The results show that, at low doses of antibiotic added (less than or equal to 50 µmol L−1), the adsorption always reached 100%, while when higher concentrations were added (between 200 and 600 µmol L−1) the highest adsorption corresponded to soils with higher pH values. Adsorption data were fitted to the Linear, Langmuir and Freundlich models, with the latter showing the best fit, in view of the determination coefficient. No desorption was detected, indicating that AZM is strongly adsorbed to the soils evaluated, suggesting that the risks of environm... [more]

The uneven pore water distribution in unsaturated soil will cause water movement, change the hydraulic and mechanical characteristics of soil, and then cause soil damage. Therefore, it is important to study the hydraulic characteristics of unsaturated soil. In this paper, the law of conservation of mass and Darcy’s law were used to analyze the unit soil after seepage to obtain a continuous equation. Combined with the soil-water characteristic curve (SWCC), the effect of matric suction and permeability coefficient of unsaturated soil on infiltration rate is substituted into the equation. Through the analysis of pore water stress of the unit soil, the function of the unsaturated permeability coefficient with the effective saturation degree is obtained, and the theoretical formula of the one-dimensional infiltration rate of unsaturated soil is derived. Compared with other models, this formula has fewer parameters and is easy to use.

The over-exploitation of shallow groundwater in the People’s Victory Canal irrigation area has led to the continuous decline in the groundwater level. The formation of a groundwater drawdown cone has changed the original runoff conditions and hydrochemical environment. Based on the groundwater data in the irrigated area from 1996 to 2022, multivariate statistical analysis, traditional hydrochemical methods, and inverse geochemical modeling were used to reveal the impact of the formation of the groundwater depression cone on hydrochemical evolution. The results show that the formation of the groundwater depression cone near the central area in 2003 changed the direction of the canal head flowing to the northwest area, making the groundwater flow from the canal head and the northwest area to the central area. The change in the hydrodynamic fields also caused the groundwater with high salinity in the northwest region to flow to the funnel area, and the ion concentration of groundwater alo... [more]

Two Mn0.15Ce0.85O2−δ mixed oxides were synthesized by a co-precipitation method using Mn(NO3)2 and KMnO4 as the manganese precursors, respectively. Structural analyses by X-ray powder diffraction and Raman spectroscopy reveal the formation of MnO-CeO2 solid solutions. The Mn0.15Ce0.85O2−δ catalyst prepared from the high-valent manganese precursor exhibits higher activity for the catalytic oxidation of NO. The advantage of KMnO4 is related to the improved redox property of the catalyst as supported by H2 temperature-programmed reduction (TPR) and O2 temperature-programmed desorption (TPD). The Mn-Ce interactions create more Mn4+, Ce3+ and oxygen vacancies on the KMnO4-synthesized mixed oxides based on the Raman and X-ray photoelectron spectra (XPS).

The application of polyetheretherketone (PEEK) in additive manufacturing (AM) can effectively reduce material and energy waste in the manufacturing process and help achieve lightweight parts. As a result, AM PEEK is considered an emerging technology in line with green manufacturing concepts. However, 3D-printed PEEK parts often suffer from low mechanical strength and poor surface quality due to the immaturity of the manufacturing process. Therefore, this research investigates the feasibility of improving the surface quality of 3D-printed parts by dry milling post-processing. Meanwhile, the mechanical strength of the parts is improved by optimizing the printing process parameters, and the effects of mechanical strength on milling quality are investigated. The novelty of this research is to design experiments based on the anisotropy of 3D-printed parts. For the first time, the delamination of the milling post-processing surface of 3D-printed PEEK parts is investigated. The results show t... [more]