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With the maturity of fault-block reservoirs, the water percolation channels are formed after long-term waterflooding, which leads to large amounts remaining oil unrecovered and low recovery efficiency. Thus, it is imperative to seek for enhancing oil recovery methods to improve the development performance of mature fault-block reservoirs. Well pattern adjustment and heterogeneous phase combined flooding are both feasible technologies for enhancing oil recovery in mature fault-block reservoirs. Nevertheless, both technologies have their limitations. Thus, a hybrid approach combining WPA and HPCF was proposed. In this study, the large-scale plate sand-pack model flooding experiments were conducted to investigate whether hybrid strategy has better EOR ability than the single WPA or HPCF. Thereafter, on the basis of incremental oil recovery and distribution of remaining oil, the mechanism of the synergistic effect of WPA and HPCF was illustrated. Finally, the influence of reservoir inclination on development performance was proposed. The results show that EOR of hybrid strategy is the highest, followed by single HPCF, and single WPA is the least. The HPCF mainly recovers remaining oil on both sides of main streamline after water flooding, and it prolongs the period of EOR validity. WPA can change the fluid flow direction and force the subsequent liquid enters the un-swept non-main streamline areas in the water flooding stage. Furthermore, by combining WPA and HPCF, the HPCF can enter the non-main streamline areas to expand sweep volume and improve oil displacement efficiency under the induction of WPA. Besides, the reservoir inclination has an obvious influence on the development performance of fault-block reservoir. With the increase of reservoir inclination, the incremental oil recovery of the single strategy or hybrid strategy decreases. Thus, these findings of this study can help for better understanding the synergetic effect of HPCF and WPA, which can provide a hybrid strategy for enhancing oil recovery in mature fault-block reservoir.

Polymer-electrolyte aqueous two-phase systems (ATPS) have demonstrated their superior performance in the separation and purification of high-value biomolecules. However, these powerful platforms are still a major academic curiosity, without their acceptance and implementation by industry. One of the major obstacles is the absence of models to predict the partition of biomolecules in ATPS in an easy and predictive way. To address this limitation, modelling studies on the binodal curve behavior of polymer-electrolyte ATPS and the partitioning of biomolecules in these aqueous electrolyte solutions are carried out in this work. First, a comprehensive database targeting the studied systems is established. In total, 11,998 experimental binodal data points covering 276 polymer-electrolyte ATPS at different temperatures (273.15K-399.15K) and 626 experimental partition data points involving 22 biomolecules in 42 polymer-electrolyte ATPS at different temperatures (283.15K-333.15K) are included. Then, a novel modeling strategy that combines a well-known machine learning algorithm, i.e., artificial neural network (ANN) and group contribution (GC) method is proposed. Based on this modeling strategy, an ANN-GC model (ANN-GC model1) is built to describe the binodal curve behavior of polymer-electrolyte ATPS, while another ANN-GC model (ANN-GC model2) is developed to predict the partition of biomolecules in these biphasic systems. ANN-GC model1 gives a mean absolute error (MAE) of 0.0132 and squared correlation coefficient (R2) of 0.9878 for the 9,598 training data points, and for the 1,200 validation data points they are 0.0141 and 0.9858, respectively. Meanwhile, it also gives a MAE of 0.0143 and R2 of 0.9846 for the 1,200 test data points. On the other hand, ANN-GC model2 gives root-mean-square deviation (RMSD) of 0.0577 for 501 training data points, and for the 62 validation data points and 63 test data points their RMSD are 0.0849 and 0.0885, respectively. Furthermore, the obtained results also indicate that the tie-line length of polymer-electrolyte ATPS calculated from ANN-GC model1 can be directly used in ANN-GC model2 for predicting the partition performance coefficient of biomolecules in these ATPS. The developed models offer the possibility to predict the partition of biomolecules in ATPS without any requirement of experimental data. Based on the developed ANN-GC models, some high-performance ATPS are identified to partition four well-known biomolecules.

The composition of raw coke oven gas, mainly consisting of H2 and CH4, has a significant impact on its utilization in the industry. To better utilize this product, a novel modeling strategy is presented in this work to predict the concentration of H2 and CH4. Initially, both thermodynamic- and kinetic-based models are established to simulate the coal coking process in Aspen Plus. Following this, a sample pseudo-data set is generated from the kinetic-based model to better describe the coal coking process, and this is followed by data calibration using actual operating data from the industry. Based on these calibrated simulation data and the collected actual operating data, a machine learning model is developed to predict the concentration of H2 and CH4. In this work, four well-known and high-performance algorithms (i.e., artificial neural network, Random forest, XGBoost, and LightGBM) are used and compared in the model development. LightGBM provides the best modeling performance, with the coefficient of determination (R2) on H2 and CH4 being 0.99952 and 0.99964, respectively. Furthermore, the Shapley Additive exPlanations (SHAP) technique is employed to identify the ranking of key parameters that have a major impact on the concentrations of H2 and CH4.

In recent years, several approaches have been applied to modify metal-organic frameworks (MOFs) owing to their excellent structural tunability such as higher extraction efficiency than that of primitive crystals. Herein, Zr-based MOFs (UiO-66-NH2) with a suitable size modulated by acetic acid were successfully synthesized for effective DNA extraction. The bonding conformations and adsorption mechanism indicated a high affinity between UiO-66-NH2 and the DNA molecules. Furthermore, Fe3O4 nanoparticles were immobilized on the UiO-66-NH2 surface to allow MOFs with magnetism. The magnetic zirconium-organic framework (MZMOF) retained the intact structure of MOFs and simplified subsequent extraction operations. In the DNA recovery investigation, MZMOF showed high recovery efficiency for both short-stranded DNA (90.4%) and pseudovirus DNA (95.1%). In addition, it showed superior DNA extraction efficiency from plasma (57.6%) and swab preservation solution (86.5%). The prepared MZMOF was employed for highly specific extraction of viral DNA and cfDNA from samples. To further simplify the extraction process, MZMOF was applied to immiscible phase filtration assisted by a surface tension (IFAST) chip for facilitating rapid DNA extraction with sensitive point-of-care testing. The developed MZMOF-based extraction method has significant potential for increasing the demand for rapid and efficient nucleic acid extraction.

Extractive distillation (ED) can be used to separate mixtures with low relative volatilities that are even close to unity. It is widely adopted for the separation of aromatics and nonaromatics in t...

The branched-preformed particle gel (B-PPG) is a novel viscoelastic particle gel used for improving sweep efficiency and enhancing oil recovery in a heterogeneous mature reservoir. To improve the p...

Prediction of thermodynamic behavior is essential for the early design stage of separation processes including solvent selection, process optimization, and its performance evaluation. In order to better utilize ionic liquids (ILs) as solvents in gas separation processes, the UNIFAC-IL model of IL-liquid solute systems is extended to IL-gas systems by using experimental data from published works and pseudo-experimental data specifically generated from a calibrated COSMO-RS model. In this work, we consider in the model development a total number of 100 ILs from 6 cation families (i.e., imidazolium, pyridinium, pyrrolidinium, ammonium, phosphonium, and guanidium), 24 anion families [i.e., bis(trifluoromethanesulfonyl)amide, tetrafluoroborate, hexafluorophosphate, dimethylphosphate, heptafluorobutyrate, trifluoroacetate, trifluoromethanesulfonate, methylsulfonate, methylsulfate, ethylsulfate, nitrate, p-toluenesulfonate, 2-(2-methoxyethoxy)ethylsulfate, chloride, bromide, dicyanamide, tetracyanoborate, tris(pentafluoroethyl)trifluorophosphate, lactate, levulinate, saccharinate, succinamate, tetrafluoroethanesulfonate, bis(2,4,4-trime-thylpentyl)phosphinate], and 13 gases including CO2, SO2, H2S, NH3, N2O, CO, N2, O2, H2, CH4, C2H4, C2H6, and C3H8. The extended UNIFAC-IL-Gas model consists of two submodels, namely, the UNIFAC-IL-Gas (Exp.) model and the UNIFAC-IL-Gas (Pseudo-Exp.) model. The training and testing of the UNIFAC-IL-Gas (Exp.) model is based on 100% experimental data, while the training of the UNIFAC-IL-Gas (Pseudo-Exp.) model is based on pseudo-experimental data, but its testing is also based on 100% experimental data.

The present study focused on comparing the effects of different active parts of five-year-old ginseng on the immunological activity of cyclo-phosphamide (CTX)-induced immunosuppressed mice. Preparation of ginseng water extract, total ginsenoside complex, ginseng glycoprotein complex, ginseng glycopeptide complex, by water extraction and alcohol precipitation method and enzymolysis method. The immunomodulatory effects of different effective parts of ginseng were determined by carbon clearance test, immune organ index, delayed type hypersensitivity (DTH) response, leukocyte count in peripheral blood, spleen lymphocyte transformation experiment, splenic NK cell activity, serum hemolysin and Experiment on the determination of cytokines. The results showed that ginseng water extract, total ginsenoside complex, ginseng glycoprotein complex and ginseng glycopeptide complex improved immune organs indices, DTH response, leukocyte count, NK cell activity, cytokine content, hemolysin content and the phagocytosis of macrophages in immunosuppressive mice. Ginseng glycoprotein complex and ginseng glycopeptide complex had more effectiveness on cellular immunity. Total ginsenoside complex and ginseng glycoprotein complex can better enhance the humoral immune function of mice. Total ginsenoside complex, ginseng glycoprotein complex and ginseng glycopeptide complex had a better effect on improving the function of macrophages phagocytosis. The enhancing effect of ginseng glycoprotein on NK cell activity was better than other extracts. Total ginsenoside complex, ginseng glycoprotein complex and ginseng glycopeptide complex can significantly increase the content of TNF-α in mice, ginseng water extract can significantly in-crease the content of IL-2, ginseng water extract and total ginsenoside complex are more effective in enhancing IL-6 levels in mice. Different effective parts of ginseng can improve the immunity of mice, and the effect of ginseng glycoprotein is more obvious. It is speculated that ginseng glycoprotein is the main active site of ginseng against CTX immunosuppression. This study laid a theoretical foundation for further study on the pharmacodynamic material basis and mechanism of ginseng to improve immunity.

The production of ethylbenzene from dry gas is a representative of an energy-intensive process in oil refineries, and the distillation process accounts for the major energy consumption and carbon emissions. Due to the increasing energy and environmental challenges, there is a strong demand for new technologies or intensified process designs that enable us to have energy-efficient and sustainable process operations. In this work, an ionic liquid (IL)-based energy-efficient extractive distillation (ED) process with low carbon emission is proposed for the distillation process of ethylbenzene production from dry gas. First, the structure of task-specific ILs is optimized through the computer-aided IL design (CAILD) method with a novel design objective. An ammonium-based IL ethylammonium trifluoromethanesulfonate ([C2H8N][TfO]), that has the best objective performance, is identified by solving a mixed-integer nonlinear programming (MINLP) problem. The energy, environmental (carbon emission), and economic performance of this [C2H8N][TfO]-based ED process in the ethylbenzene production is then thoroughly evaluated on the basis of optimized process operations in Aspen Plus. For demonstration purposes, a case study for the separation process of an industrial-scale ethylbenzene production in a Chinese refining industry is performed. When compared to the conventional process that is currently used in the petrochemical industry, our proposed [C2H8N][TfO]-based ED separation process has 40 % energy (hot utility) savings and a 11 % cost reduction. Notably, the IL-based ED separation process has 40 % lower carbon emissions versus the conventional process, indicating its great potential for sustainable operation in the production of ethylbenzene from dry gas.

Face processing is known to decline in older adults; however, a clear understanding of the brain networks behind this cognitive decline is still lacking. In this study, we investigated the neural correlates of the declined face processing with aging from a resting-state brain network perspective. Nineteen healthy old adults and 22 young adults were recruited and underwent two functional magnetic resonance imaging (fMRI) scanning sessions (i.e., resting-state and localizer task) and two behavioral tests (face matching and symbol-form matching). We examined age-related alterations in resting-state functional connectivity (FC) within face network as well as between face network and other networks, and tested their associations with behavioral performance of face and symbol-form processing. We found that (a) compared with young adults, old adults exhibited decreased FC between face-selective regions (fusiform face area and occipital face area), but increased FC between face-selective regions and non-face-selective regions; (b) these age-related FC alterations were correlated with individuals' behavioral performance of face and symbol-form processing. Collectively, these findings suggest the declines of face processing are associated with a mixture of decreased integration within the face network and segregation beyond the face network in the aging brain, and provide evidence for a neural basis of cognitive aging in face processing from an intrinsic brain network perspective.

This study examined the effects of different narrative modes (writing and speaking) on the theme (Agency and Communion) and the level of positive processing through a group counseling based on psychobiographical therapy. A qualitative study approach was used to encode and analyze the life stories collected by group counseling. Results: The number of Communion in the speaking group was higher than that in the writing group, and the positive processing level of the writing group was higher than that of the speaking group. Conclusion: Different narrative modes have different effects on the theme and the level of positive processing.

In process industries, separation techniques need to be employed to match product quality and purity specifications. Most vapour-liquid based separation techniques involving the separation of close-boiling or azeotropic as well as gaseous mixtures are energy intensive. Downstream separations from bioreactors are, on the other hand, difficult because of relatively small amounts of products in large amounts of reactants and carriers such as water. With growing energy and environmental challenges, novel, sustainable and innovative separation techniques are receiving increasing attention. Because of their non-volatility and other tuneable properties, ionic liquids (ILs) based separation techniques are promising alternatives. In this work, a systematic method that combines group contribution (GC)-based property prediction and IL-based separation process design is presented. That is, the optimal IL molecular structure and the corresponding optimal flowsheet configuration for a specific IL-based separation process are simultaneously identified. Case studies involving the separation of azeotropic mixtures such as ethanol-water and acetone-methanol are presented to highlight the application of the method for synthesis-design of the IL-based separation technology.

Selecting an appropriate separation technique is essential for the application of in situ product removal (ISPR) technology in biological processes. In this work, a three-stage systematic design method is proposed as a guide to integrate ionic liquid (IL)-based separation techniques into ISPR. This design method combines the selection of a suitable ISPR processing scheme, the optimal design of an IL-based liquid-liquid extraction (LLE) system followed by process simulation and evaluation. As a proof of concept, results for a conventional acetone-butanol-ethanol fermentation are presented (40,000 ton/year butanol production). In this application, ILs tetradecyl(trihexyl)phosphonium tetracyanoborate ([TDPh][TCB]) and tetraoctylammonium 2-methyl-1-naphthoate ([TOA] [MNaph]) are identified as the optimal solvents from computer-aided IL design (CAILD) method and reported experimental data, respectively. The dynamic simulation results for the fermentation process show that, the productivity of IL-based in situ (fed-batch) process and in situ (batch) process is around 2.7 and 1.8fold that of base case. Additionally, the IL-based in situ (fed-batch) process and in situ (batch) process also have significant energy savings (79.6% and 77.6%) when compared to the base case.

Microcarriers are beads with a diameter of 60-250 µm and a large specific surface area, which are commonly used as carriers for large-scale cell cultures. Microcarrier culture technology has become one of the main techniques in cytological research and is commonly used in the field of large-scale cell expansion. Microcarriers have also been shown to play an increasingly important role in in vitro tissue engineering construction and clinical drug screening. Current methods for preparing microcarriers include microfluidic chips and inkjet printing, which often rely on complex flow channel design, an incompatible two-phase interface, and a fixed nozzle shape. These methods face the challenges of complex nozzle processing, inconvenient nozzle changes, and excessive extrusion forces when applied to multiple bioink. In this study, a 3D printing technique, called alternating viscous-inertial force jetting, was applied to enable the construction of hydrogel microcarriers with a diameter of 100-300 µm. Cells were subsequently seeded on microcarriers to form tissue engineering modules. Compared to existing methods, this method offers a free nozzle tip diameter, flexible nozzle switching, free control of printing parameters, and mild printing conditions for a wide range of bioactive materials.

Microcarriers are beads with a diameter of 60-250 µm and a large specific surface area, which are commonly used as carriers for large-scale cell cultures. Microcarrier culture technology has become one of the main techniques in cytological research and is commonly used in the field of large-scale cell expansion. Microcarriers have also been shown to play an increasingly important role in in vitro tissue engineering construction and clinical drug screening. Current methods for preparing microcarriers include microfluidic chips and inkjet printing, which often rely on complex flow channel design, an incompatible two-phase interface, and a fixed nozzle shape. These methods face the challenges of complex nozzle processing, inconvenient nozzle changes, and excessive extrusion forces when applied to multiple bioink. In this study, a 3D printing technique, called alternating viscous-inertial force jetting, was applied to enable the construction of hydrogel microcarriers with a diameter of 100-300 µm. Cells were subsequently seeded on microcarriers to form tissue engineering modules. Compared to existing methods, this method offers a free nozzle tip diameter, flexible nozzle switching, free control of printing parameters, and mild printing conditions for a wide range of bioactive materials.

Ionic liquid-based aqueous biphasic systems (IL-ABS) have attracted much attention in both academia and industries due to their superior performance in many applications. In order to better utilize these novel biphasic liquid–liquid systems for recovering hydrophilic ILs from their dilute aqueous solutions, a machine learning (ML)-based ABS design method is proposed for such a purpose in this work. In this method, an ML-based model, i.e., artificial neural network (ANN)-group contribution (GC) model, is employed to predict the phase equilibrium behaviors of IL-ABS. Based on the integration with a computer-aided design technique, the optimal IL-ABS is determined by formulating and solving an optimization-based mixed-integer non-linear programming problem, where the structure of IL-ABS is denoted as the input vector in the ANN-GC model. As a proof of the concept, results of the recovery of 1-butyl-3-methylimidazolium chloride ([C4mIm][Cl]) and n-butylpyridinium trifluoromethanesulfonate ([C4Py][TfO]) from aqueous solutions are presented. The ABS [C4mIm][Cl]-H2O-(NH4)2SO3 (identified in this work) gives an IL recovery efficiency of 95.0 wt % and a salting-out agent input of 2.36 kg/kg IL recovery, and for the ABS [C4mIm][Cl]-H2O-K2CO3 (reported in the literature), they are 81.7 and 5.25, respectively. For the second case, our proposed ABS [C4Py][TfO]-H2O-KH2PO4 gives an IL recovery efficiency of 95.6 wt % and a salting-out agent input of 1.81 kg/kg IL recovery, and for the reported ABS [C4Py][TfO]-H2O-(NH4)2SO4, they are 80.6 and 3.16, respectively

Melamine, as a typical chemical intermediate, is widely applied in the plastics and coatings industry. However, its synthesis process releases large amounts of NH3 and CO2 gas mixtures. A tail gas treatment is therefore a necessary process followed by its production steps. The traditional separation technology for tail gas treatment is water scrubbing for NH3 absorption, but this option suffers from high energy consumption and lots of NH3-containing waste water. In this work, a novel ionic liquid (IL)-based solvent, is proposed for the separation of NH3/CO2 mixtures from melamine tail gas. As models for prediction of solubility of NH3 in ionic liquids are not available, first the UNIFAC-IL model is adopted and extended to the NH3-IL systems based on available measured data together with other Group Contribution-based pure component property models. Then, a systematic computer-aided IL design for NH3/CO2 separation is performed by formulating and solving a mixed-integer nonlinear programming problem. Considering NH3 solubility, NH3/CO2 selectivity and feasibility for industrial application as selection criteria, a hydroxyl-functionalized imidazolium-based IL is found to be optimal. Based on the established thermodynamic models, both the IL-based process and a traditional water scrubbing process for NH3/CO2 separation are simulated and evaluated in terms of energy consumption, economic analysis and net CO2 emission under the same NH3 recovery. The simulation results show that compared with the traditional processes, the IL-based process represents a 45%, 35% and 19% reduction in overall equivalent energy, separation cost and net CO2 emission, respectively.

Panax ginseng is a valuable traditional herbal medicine material with numerous applications. Ginsenosides are the key bioactive compounds in ginseng. Cold stress can activate stress tolerance mechanisms that regulate biomass and biosynthesis in ginseng tissue. In this study, the effects of short- and long-term cold stress (5°C) on the physiological characteristics, tissue-specific ginsenoside distributions, and ginsenoside synthesis gene expressions of 3-year-old P. ginseng during the flowering period were investigated. Short-term cold stress significantly reduced ginseng biomass (root fresh weight and dry weight), and increased malondialdehyde, proline, soluble sugar, and soluble protein concentrations. Superoxide dismutase, peroxidase, and catalase activities also increased significantly under cold stress. With prolongation of the cold stress period, all antioxidant enzyme activity decreased. The protopanaxatriol-type ginsenoside concentrations in the taproots (phloem and xylem) and fibrous roots, as well as the protopanaxadiol-type ginsenoside concentrations in the leaves, increased significantly under short-term cold stress. The key genes (SE, DS-II, CYP716A52v2, and CYP716A53v2) involved in the ginsenoside biosynthesis pathway were significantly positively correlated with the ginsenoside accumulation trends. Thus, short-term cold stress can stimulate membrane lipid peroxidation, in turn stimulating the antioxidant enzyme system to alleviate oxidative damage and increasing the expression of key enzyme genes involved in ginsenoside biosynthesis. During agricultural production, protopanaxadiol/protopanaxatriol ratios could be manipulated by low-temperature storage or treatments.

Properties of ionic liquids (ILs) are required for the design of products and processes involving ILs. Although innumerable ILs may be generated through the combination of a variety of cations, anions, and substituents, only a small part of them have been reported to exist (have been synthesized). The available experimental data are generally limited and sometimes even contradictory. A detailed knowledge about the properties of ILs is critically important, especially for ILs not yet available. Based on collected experimental data from numerous literature sources, a series of group contribution models have been developed for estimating various properties (density, heat capacity, viscosity, surface tension, melting point) of ILs. To evaluate the predictive capability of the proposed or employed group contribution models, nearly 70% of the data sets (i.e., training sets) are used for correlation, and then the remaining data sets (i.e., test sets) not included in the training sets are used for prediction. The calculation results show that the proposed group contribution models can predict the properties of studied ILs with sufficient accuracy. These property estimation models can both be used easily and also provide estimation of important properties for previously unstudied ILs, some of which may be considered as potential solvents in many industrial applications.

Three different IBV genotypes/serotypes, designated ck/CH/LDL/150434-I (LDL/150434-I), ck/CH/LDL/150434-II (LDL/150434-II) and ck/CH/LDL/150434-III (LDL/150434-III), were detected in a single tracheal sample from a chicken showing signs of respiratory disease. The viruses were isolated using a cross-neutralization test and limiting dilution in embryonated specific-pathogen-free (SPF) eggs. Isolate LDL/150434-I was a re-isolation of H120 vaccine strain that was introduced into the chicken flock by vaccination, transmitted between chickens, and later accumulated several genomic mutations. Isolate LDL/150434-II was a novel variant that originated from recombination events between H120 and ck/CH/LDT3/03-like viruses. The widespread use of H120 vaccine, which offered incomplete protection against heterotypic IBVs in the fields, may play important roles in the emergence of such a novel genetic variant. Based on the analysis of S1 and complete genomic sequence, isolate LDL/150434-III was related genetically but distinct from the established strains of nrTW I type viruses of GI-7 lineage circulating in Mainland China since 2009. The three IBV isolates were avirulent when they infected SPF chickens. Furthermore, synergistic effects on pathogenicity were not observed when the different types co-infected the SPF chickens. However, the isolates persisted in the respiratory tracts longer in combined infected birds than those in individual infected birds. The results provide insights into the evolution of the viruses and co-infection of chickens with different virus serotypes.