Channelrhodopsin-2 (ChR2) is an important tool for optogenetics, and some of its mutants are Ca2+-selective channels. However, the mechanism for Ca2+-selective permeation is still unclear. In this study, molecular dynamic (MD) simulations for the Ca2+ permeation of the CatCh mutant were carried out to investigate the fundamental features of the selectivity of Ca2+. Research on the conformational changes in the key residues near the central gate (CG) of the channel suggested that E83, E90, and D253 play an important role in Ca2+ conductivity. The clustering analysis indicates that the above “EED triad” acts as a filter, and Ca2+ can only pass through if the EED is in a certain conformation. It was also found that hydrated Ca2+ can be coordinated with carboxyl groups, resulting in the loss of part of the water molecules in the hydrated shell and a reduction in ionic radius, which helps Ca2+ enter the channel.

Considering a class of complex nonlinear systems whose dynamics are mostly governed by statistical regulations, the pattern-moving theory was developed to characterise such systems and successfully estimate the outputs or states. However, since the pattern class variable is not computable directly, this study establishes a clustered generalized cell mapping (C-GCM) to reveal system characteristics. C-GCM is a two-stage approach consisting of a pattern-moving-based description and analysis method. First, a density algorithm, named density-based spatial clustering of applications with noise (DBSCAN), is designed to obtain cell space Ω and the corresponding classification guidelines; this algorithm is initiated after the initial pre-image cells, and the total number of entity cells amounts to Ns. Then, the GCM provides several image cells based on a cell mapping function that refers to the multivariate ARMAX model. The global dynamic analysis employing both searching and storing algorithm... [more]

This study deals with the synthesis and characterization of a series of hybrid photocatalysts consisting of different loadings of TiO2, Cd, and Fe on mesoporous SBA-15 material. The prepared samples were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and scanning electron microscopy (SEM), and tested for the removal of the neonicotinoid insecticide imidacloprid. The results showed that uncalcined 10% Cd-SBA-15 catalyst exhibited the best photocatalytic activity. The photocatalytic degradation of the imidacloprid was carried out in a batch photoreactor at different pH values, and in the presence or absence of additional compounds such as peroxymonosulfate (PMS) and peroxydisulfate (PDS). The best degradation results were achieved at a pH value of 6.5 with 10% Cd/SBA-15. The degradation performance increased with the addition of PMS and PDS. Based on the results of the experimental measurements, Cd/SBA-15 is a good candidate that can show a rea... [more]

In this paper, a hybrid three-stage methodology based on in vitro experiments, simulations, and metaheuristic optimization is presented to enhance the corrosion resistance of hydroxyapatite (HA)-coated magnesium implants in biomedical applications. In the first stage, we add cerium (Ce) to HA and present a new coating (named HA+Ce) to improve the resistance of the coating to corrosion. Then, various HA+Ce compounds with different factors (e.g., concentration, pH, immersion time, and temperature) are generated and their propensity for corrosion is examined in a physiological environment using EIS and DC polarization tests in a simulated body fluid solution. Eventually, a comprehensive dataset comprising 1024 HA+Ce coating samples is collected. In the second stage, machine learning using random forest (RF) is used to learn the relation between the input factors of the coating and its corrosion resistance. In the third stage, a metaheuristic algorithm based on the whale optimization algor... [more]

In this study, the kinetics of extracting pyridine, quinoline, and indole from model fuels using natural deep eutectic solvents (NaDES) composed of carboxylic acids, xylitol, and water were investigated under static conditions. This research marks the first examination of extraction kinetics in this context. The key kinetic parameters of the extraction process were identified. Notably, it was observed that the mass transfer coefficient for indole was in the range of 3.4 × 10−6 to 1.2 × 10−6, depending on NaDES. That is significantly lower, by an order of magnitude, than for pyridine and quinoline under identical experimental conditions. The study revealed that, under specific conditions, where thermodynamic equilibrium for indole cannot be reached, it becomes possible to achieve kinetic separation of the components. The presented experimental data obtained on a centrifugal extractor showed a decrease in the degree of indole extraction with increasing flow: Extraction efficiency decreas... [more]

Terpenoids are enormous and different types of naturally occurring metabolites playing an important role in industrial applications. Cost-effective and sustainable production of terpenoids at commercial scale is the big challenge because of its low abundance from their natural sources. Metabolic and genetic engineering in microorganisms provide the ideal platform for heterologous overexpression protein systems. The photosynthetic green alga Chlamydomonas reinhardtii is considered as a model host for the production of economic and sustainable terpenoids, but the regulation mechanism of their metabolisms is still unclear. In this study, we have investigated the genetic and metabolic synthetic engineering strategy of MYB transcriptional factors (MYB TFs) in terpenoids’ synthesis from C. reinhardtii for the first time. We heterologous overexpressed MYB TFs, specifically SmMYB36 from Salvia miltiorrhiza in C. reinhardtii. MYB upregulated the key genes involved in the 2-C-methyl-D-erythritol... [more]

The efficiency of the vapor phase crystallization (VPC) process in zeolite formation using mixtures of a natural source (obsidian) and common waste materials (red mud and fly ash) was analyzed. The aim was to demonstrate that water molecules available during this treatment control mainly the synthesis of sodalite, regardless of the raw material used, as long as it is rich in amorphous silica and alumina pre-fused with NaOH. The data indicate that increasing the temperature to generate steam from distilled water during the VPC process results in the continuous transformation of amorphous material into sodalite and, subordinately, cancrinite. The formation of the newly formed phases was monitored by powder XRD and SEM.

Aiming at the low efficiency of heavy-oil thermal recovery, a downhole multi-thermal fluid generator (DMTFG) can improve the viscosity reduction effect by reducing the heat loss of multi-thermal fluid in the process of wellbore transportation. The steam generated by the MDTFG causes damage to the packer and casing, owing to the return upwards along the annular space passage of the oil casing. To mitigate this damage, a heat transfer model for multi-channel coiled tubing wells and a prediction model for the upward return of the steam temperature field in the annulus were established with the basic laws of thermodynamics. Models were further verified by ANSYS. The results indicate the following four conclusions. First of all, when the surface pressure is constant, the deeper the located DMTFG, the shorter the distance for the steam to return would be. It is easier to liquefy the steam. Second, the higher the temperature of the steam produced by the downhole polythermal fluid generator, t... [more]

The heat-integrated distillation column (HIDiC) has more energy-saving potential than conventional distillation columns. However, its nonlinearity and coupling effects pose significant challenges for the online operation of the HIDiC. To overcome these challenges, it becomes necessary to utilize accurate nonlinear models for design optimization or control schemes. Traditional modeling methods require extensive tray information, implying the impractical use of numerous sensors in real-world applications. This paper proposes a modeling approach for the HIDiC based on a limited number of measurements. It only requires the measurement of a finite amount of tray information to construct a global model of the HIDiC. This method serves as an online observer, providing real-time information about the entire column, and also enables the prediction of tray concentration changes. The proposed model forms the basis for developing model-based online monitoring and control schemes. Experimental simu... [more]

The upper Shasi reservoir in the LN block is characterized by low abundance and greater depth, low porosity, low permeability, and low pressure. Due to high water injection pressure, the LN block has been developed in an elastic way. The natural productivity of oil wells in this block is low, but the productivity can be improved after fracturing. However, the field development effects show that the oil well has high initial production, but rapid decline and rapid pressure drop. At present, the recovery factor of this block is only 0.38%, and it is difficult to realize the economic and effective development of a difficult-to-develop block by conventional fracturing technology. Based on the geological characteristics of the LN block and the fracturing experience of adjacent wells, the fracturing process is optimized and the key fracturing parameters are determined in combination with the sand body distribution and logging curve of well LN-1. Due to the low-pressure coefficient and medium... [more]

In addressing the issue of a low drawing rate in a steeply inclined and extremely thick coal seam, this study focused on the engineering background of the +575 horizontal working faces in the Wudong Coal Mine. By utilizing physical similarity simulation experiments, research was carried out on the top-coal-drawing rate and the gangue ratio at different coal-drawing intervals in horizontal segment mining for steeply inclined and thick coal seams, in which the relationships between the top-coal-drawing law and the drawing interval and technologies were revealed. The discrete element method was used to establish a numerical simulation model for the horizontal segment mining of steeply inclined and thick coal seams, and the roof-drawing law in the cases of the three-interval-group-of-support and drawing-once-every-two-support methods were analyzed before finally obtaining the optimal drawing technology. Through field practice, the coal-drawing effect of the technology was verified. The res... [more]

With increasing computational capacities and advances in numerical methods, a simulation-based process and product design approach for spray dried products has become the focus of many researchers. In this context, a novel unresolved CFD-DEM simulation approach for single suspension droplets is presented, which models the drying and solidification process in a hot gas environment. The solidification process is described by the formation of bonds between the primary particles in the suspension droplet, showing a plausible solidification behavior, which starts when a critical solid concentration is reached at the droplet surface. The drying conditions for the single-droplet simulations are determined from a large-scale spray dryer simulation for different droplet size classes. The resulting solid particles from the CFD-DEM simulation show a higher tendency to form hollow particles at high drying rates when the locking point is reached at earlier stages of the drying process. Using these... [more]

In today’s industrial landscape, the imperative of fault warning for equipment and systems underscores its critical significance in research. The deployment of fault warning systems not only facilitates the early detection and identification of potential equipment failures, minimizing downtime and maintenance costs, but also bolsters equipment reliability and safety. However, the intricacies and non-linearity inherent in industrial data often pose challenges to traditional fault warning methods, resulting in diminished performance, especially with complex datasets. To address this challenge, we introduce a pioneering fault warning approach that integrates an enhanced Coati Optimization Algorithm (ICOA) with a Bidirectional Long Short-Term Memory (Bi-LSTM) network. Our strategy involves a triple approach incorporating chaos mapping, Gaussian walk, and random walk to mitigate the randomness of the initial solution in the conventional Coati Optimization Algorithm (COA). We augment its sea... [more]

The design of new drug delivery systems has been widely sought after. The stability, solubility, and difficulty of targeting active sites for new drugs have always been challenging and remain one of the major drawbacks to the efficiency of certain drugs. Liposomes are phospholipid vesicles enclosing one or more aqueous compartments. Depending on its properties, a drug is embedded in the lipid bilayer or the aqueous medium. Thus, liposomes can act as drug carriers for both lipo- and hydrophilic compounds. New strategies such as “drug-in-cyclodextrin-in liposomes” (DCLs) have been developed as safe and effective carriers for exploiting the inclusion properties of water-soluble cyclodextrins known to form host−guest complexes with lipophilic molecules. Once inclusion complexes are formed, they can be inserted into a liposome aqueous core in order to stabilize it and better control the drug release. Our review will provide an update on the use of DCLs in the field of drug delivery for vari... [more]

The new energy structure needs to balance energy security and dual carbon goals, which has brought major challenges to coal-fired power plants. The pollution reduction and carbon emissions reduction in coal-fired power plants will be a key task in the future. In this paper, an optimization technique for the operation of an electrostatic precipitator is proposed. Firstly, the voltage-current model is constructed based on the modified dust charging mechanism; the modified parameters are trained through the gradient descent method. Then, the outlet dust concentration prediction model is constructed by coupling the mechanism model with the data model; the data model adopts the long short-term memory network and the attention mechanism. Finally, the particle swarm optimization algorithm is used to achieve the optimal energy consumption while ensuring stable outlet dust concentration. By training with historical data collected on site, accurate predictions of the secondary current and outlet... [more]

A new idea to deal with the backmixing problem in a scaled-up multi-inlet vortex mixer is proposed in this paper. Firstly, a Reynolds-averaged Navier−Stokes−large-eddy simulation hybrid model was used to simulate the flow field in a vortex mixer, and the numerical simulation results were compared with those from a particle image velocimetry experiment in order to validate the shielded detached eddy simulation model in the rotating shear flow. Then, by adding a series of columns in the mixing chamber, the formation of wake vortexes was promoted. The flow field in the vortex mixer with different column arrangements were simulated, and the residence time distribution curves of the fluid were obtained. Meanwhile, the degree of backmixing in the vortex mixer was evaluated by means of a tanks-in-series model. In the total ten cases related with four groups of variables, it was found that increasing the diameter of the column was the most efficient for weakening the backmixing in the vortex m... [more]

Burning hydrogen-rich syngas fuels derived from various sources in combustion equipment is an effective pathway to enhance energy security and of significant practical implications. Emissions from the combustion of hydrogen-rich fuels have been a main concern in both academia and industry. In this study, the NO and CO emission characteristics of both laminar and turbulent counterflow premixed hydrogen-rich syngas/air flames were experimentally and numerically studied. The results showed that for both laminar and turbulent counterflow premixed flames, the peak NO mole fraction increased as the equivalence ratio increased from 0.6 to 1.0 and decreased as the strain rate increased. Compared with the laminar flames at the same bulk flow velocity, turbulent flames demonstrated a lower peak NO mole fraction but broader NO formation region. Using the analogy theorem, a one-dimensional turbulent counterflow flame model was established, and the numerical results indicated that the small-scale t... [more]

The flow field characteristic is crucial for the separation process of cyclones, which includes time−mean and dynamic characteristics. The structural parameters of the cyclone have an important influence on the internal flow field characteristics, among which the cylinder diameter and vortex finder diameter are important structural parameters. This experimental study aimed to assess the effects of diameter parameters on the flow field characteristics of cyclones, especially the dynamic characteristics, which have received less attention in the literature. A hot wire anemometer (HWA) was employed in measuring the instantaneous tangential velocities in cyclones with different cylinder and vortex finder diameters. Time and frequency domain analyses of the measured data revealed that the diameter parameters of cyclones affected not only the distributions of the time−mean and instantaneous tangent velocities but also the intensity and dominant frequency of the instantaneous tangential veloc... [more]

In the wake of Industry 4.0, the ubiquitous internet of things provides big data to potentially quantify the environmental footprint of green products. Further, as the concept of Industry 5.0 emphasizes, the increasing mass customization production makes the product configurations full of individuation and diversification. Driven by these fundamental changes, the design for sustainability of a high-mix low-volume product−service system faces the increasingly deep coupling of technology-driven product solutions and value-driven human-centric goals. The multi-criteria decision making of sustainability issues is prone to fall into the complex, contradictory, fragmented, and opaque flood of information. To this end, this work presents a data-driven quantitative method for the sustainability assessment of product−service systems by integrating analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods to measure the sustainability of customized products and promote the Ind... [more]

To enhance the accuracy of the comprehensive evaluation of reservoir quality in shale oil fractured horizontal wells, the Pearson correlation analysis method was employed to study the correlations between geological parameters and their relationship with production. Through principal component analysis, the original factors were linearly combined into principal components with clear and specific physical meanings, aiming to eliminate correlations among factors. Furthermore, Gaussian membership functions were applied to delineate fuzzy levels, and the entropy weight method was used to determine the weights of principal components, establishing a fuzzy comprehensive evaluation model for reservoir quality. Without using principal component analysis, the correlation coefficient between production and evaluation results for the 40 wells in the Cangdong shale oil field was only 0.7609. However, after applying principal component analysis, the correlation coefficient increased to 0.9132. Fiel... [more]

Assessing oxidation−reduction potential (ORP) is of paramount importance in the efficient management of wastewater within both chemical and biological treatment processes. However, despite its critical role, insufficient information exists about how reactive chemical species generated by cold plasma (CP) in chemical treatment are associated with ORP and air flow rate. Therefore, we aim to identify the correlation between ORP and the removal of organic pollutants when using CP treatment. Additionally, we introduce a machine-learning-based operation to predict removal efficiency in the CP process. Results reveal a significant correlation of over 0.9 between real-time ORP and total organic carbon (TOC), which underscores the efficacy of ORP as a key parameter. This approach made it possible to control OH radical generation by regulating the air flow rate of the CP. This study posits that smart management facilitated by machine learning has the potential to enhance the economic viability o... [more]

The integration of theoretical insights and current findings in the articles included in this Special Issue holds the potential to bridge the gap between academic research and real-world challenges in enhancing physical−chemical processes [...]

The production of hydrogen-based dense energy carriers (DECs) has been proposed as a combined solution for the storage and dispatch of power generated through intermittent renewables. Frameworks that model and optimize the production, storage, and dispatch of generated energy are important for data-driven decision making in the energy systems space. The proposed multiperiod framework considers the evolution of technology costs under different levels of promotion through research and targeted policies, using the year 2021 as a baseline. Furthermore, carbon credits are included as proposed by the 45Q tax amendment for the capture, sequestration, and utilization of carbon. The implementation of the mixed-integer linear programming (MILP) framework is illustrated through computational case studies to meet set hydrogen demands. The trade-offs between different technology pathways and contributions to system expenditure are elucidated, and promising configurations and technology niches are i... [more]

With the development of Industry 4.0 and the implementation of the 14th Five-Year Plan, intelligent manufacturing has become a significant trend in the steel industry, which can propel the steel industry toward a more intelligent, efficient, and sustainable direction. At present, the operation mode of unmanned warehouse area for slabs and coils has become relatively mature, while the positioning accuracy requirement of bars is getting more stringent because they are stacked in the warehouse area according to the stacking position and transferred by disk crane. Meanwhile, the traditional laser ranging and line scanning method cannot meet the demand for precise positioning of the whole bundle of bars. To deal with the problems above, this paper applies machine vision technology to the unmanned warehouse area of bars, proposing a binocular vision-based measurement method. On the one hand, a 3D reconstruction model with sub-pixel interpolation is established to improve the accuracy of 3D r... [more]

Effective fault diagnosis for diaphragm pumps is crucial. This paper proposes a diaphragm pump fault diagnosis method based on deep learning and multi-source information fusion (DMF). The time-domain features, frequency-domain features, and modulation features are extracted from the vibration signals from eight different positions. After feature enhancement and data preprocessing, the features are input into auto encoders (AE), convolutional neural networks (CNN), and support vector machines (SVM) to obtain the diagnostic results. The results indicate that the DMF method achieves a fault diagnosis accuracy of 99.98%, which is on average 9.09% higher than using a single diagnostic model. The demodulation method is more suitable for vibration signal feature extraction of the diaphragm pump, while the CNN is more suitable for identification of diaphragm pump faults. Specifically, it outperformed the sampling point 1-DPCA-AE model by 13.98% and the sampling point 4-DPCA-SVM model by 8.98%.