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To examine the safety of Chinese traditional fermented fish products (CTFPs) available on the Chinese market, nitrite, nitrate, biogenic amines (BAs) and volatile N-nitrosamines (VNAs) content in 33 commercial CTFPs from different provinces was investigated. The mean content of nitrite and nitrate wase 0.63 and 749.5 mg/kg, respectively. Concerning the occurrence of BAs, the accumulation in all CTFPs samples remained at low levels, whereas only in one sample from Guangxi the histamine content exceeded the critical level (50 mg/kg). In addition, six types of VNAs, including N-nitrosodimethylamine (NDMA), N-nitrosoethylmethylamine, N-nitrosopiperidine, N-nitrosopyrrolidine, N-nitrosomorpholine and N-nitrosodiphenylamine, were detected in a high number of samples. The NDMA content in 36.4% of the samples and the total VNAs content in about 63.6% of the samples were unacceptable. Principal component analysis indicated that the accumulation of NDMA and total VNAs was closely related with the content of histamine, tyramine and nitrate.

ABSTRACT: Bentonite buffer in the geological repository for high-level radioactive waste undergoes the heating from the waste package and hydration from the geological formation and goes through coupled thermo-hydro-mechanical-chemical (THMC) changes over the life span of a repository. For better understanding of such process under higher temperatures we report bench-scale laboratory experiments with heating up to 200°C and the corresponding THM model. The bench-scale laboratory experiments included two test columns, with the non-heated control column undergoing only hydration, and a heated column experiencing both heating in the center up to 200°C and hydration from a sand-clay boundary surrounding the column. During the experiment, we took frequent X-ray CT images to provide insight into the spatio-temporal evolution of THMC due to heating, hydration, bentonite swelling/compression. Based on the experiment setup, 2-D axisymmetric simulations were performed for the heated column and the mechanical changes were investigated in 3-D. The model first matched the temperature evolution with step-wise temperature boundary conditions at the heater and calibrated the thermal conductivity and specific heat of the materials. Then model interpreted the spatio-temporal distribution of bulk density by considering the combined effect of hydration, fluid pressure, and porosity change due to swelling/compression. 1 INTRODUCTION Engineered barrier system (EBS) with bentonite buffer has been proposed in the repository design for spent nuclear fuel and waste because of its low permeability, high swelling capacity and radionuclide retention, as well as thermal stability among other desired characteristics. After the emplacement of waste canisters and backfill materials, bentonite will be simultaneously heated from the decaying radioactive waste and hydrated from the surrounding host rock. These perturbations trigger coupled THMC (thermal-hydrological-mechanical-chemical) processes, involving (1) moisture transport controlled by multiphase flow and large thermal gradient near the heat source; (2) swelling and shrinkage due to bentonite hydration or de-hydration; (3) dilution/concentration, migration and exchange of ions impacted by moisture/thermal interactions, (4) dissolution/precipitation and mineral phase transformation, etc. (Zheng et al., 2010). While bentonite behavior for temperature 100°C) conditions (Zheng et al., 2017). Itis important to understand the behavior of bentonite at high temperature for the disposal of high-level nuclear waste to expand the knowledge base regarding the perturbation of bentonite buffer and open the possibility of the designing repository with higher thermal limit. The performance assessment of repository requires prediction of the long-term THMC evolution of bentonite. The reliability of model prediction is hinged on reliable constitutive laws and parameterization to describe the THMC process at scale appropriate for model parameterization for large scale model. Models for the large scale in situ test, e.g. Zheng et al. (2020b), showed that parameters calibrated from modeling column tests can be used for large scale model. Currently, a high temperature experiment in a crystalline rock environment, called HotBENT, is being conducted under the leadership of NAGRA with several international partners (García-Siñeriz and Tuñón, 2020). This full-scale, high-temperature experiment will be conducted at the Grimsel Test Site. Such large-scale tests are extremely important for better understanding of the bentonite EBS system behavior under high temperature and conditions with strong thermal, hydraulic and density gradients. The main objective of the HotBENT experiment is to evaluate whether higher repository temperature would trigger mechanisms that compromise the barrier functions of the engineered system and the host rock. To complement the field scale HotBENT experiment, we had conducted a benchtop-scale laboratory experiment to obtain well-characterized datasets for understanding bentonite THMC processes under heating and hydration for model parameterization and benchmarking (Chang et al., 2021). In this paper, coupled THM models were developed to interpret the data collected from the column test, attempting to calibrate key constitutive relationships and parameters. In the following sections, we will first briefly describe the columns tests and then discuss the THM models

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Thermally stratified environments are universal in "real world" buildings. However, the studies on the machine learning model and mean skin temperature (MST), which was based on the analysis of Local Skin Temperatures (LSTs), were insufficient in thermally stratified environments. To create thermally stratified environments in this study, the air temperatures at the lower body parts in a climatic box were controlled independently from the upper body parts exposed in climate chamber, with 12 air temperature combinations of 22, 25, 28, and 31°C. Sixteen human subjects were recruited to collect thermal perceptions and measure their LSTs. The variations of LSTs and the optimal LSTs to estimate MST and predict thermal state were analyzed. Based on the classifications of LSTs and area of local skin, a new method using chest (0.42), forearm (0.21), thigh (0.30), and foot (0.07) was proposed to estimate MST. Its errors decreased by at least 22.8% as compared to the existing methods. Then, the model based on Random Forest was used to filter the optimal LSTs for the predictions of Thermal Sensation Vote (TSV) and Local Thermal Comfort (LTC). Results showed at least three LSTs were needed to reach a robust model prediction accuracy and generalization ability. The optimal LSTs for the predictions of TSV and LTC were (Forearm, upper arm, foot) and (Forearm, chest, thigh), respectively. This study contributes to provide the basic information of optimal LSTs to improve the accuracies of the thermal comfort predictions and MST estimation in the thermally stratified environments.

Purpose Targeted mutational analysis has been widely used to predict medulloblastoma molecular subgroups. We aimed to identify a gene mutation pattern for individual recurrent risk assessment patients with medulloblastoma. Methods In this monocenter cohort analysis, patients who experienced medulloblastoma recurrence were analyzed for clinical outcomes, including anatomic and temporal patterns of relapse and post-recurrence survival. Differentially mutational genes were examined using a panel of 39 genes to build a gene classifier using an elastic net regression model. The Cox proportional hazards model was used to estimate the multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the prognostic accuracy of this gene classifier. Results A total of 23 of 118 (21%, 95% CI: 12.8–27.8) patients experienced recurrence, with a significant representation of patients in the very high risk group. Most patients exhibited some distal disease 56% (34.9–75.6). Time to relapse and post-recurrence survival did not vary by risk stratification. A recurrent gene signature for medulloblastoma that consisted of 27 genes was generated to classify patients into high and low recurrence risk groups. Patients with high recurrence risk scores had shorter recurrence-free survival (hazard ratio [HR]: 24.304, 6.277–29.723) and overall survival (HR: 7.331, 2.957–18.172) than patients with low-risk scores. These findings of sensitivity analyses suggest that the current results did not change substantially. Conclusion The recurrent score is a reliable prognostic tool for recurrence in patients with medulloblastoma. It can potentially guide treatment decisions for patients at different risks of recurrence.

Purpose: There have been insufficient data for pediatric patients with medulloblastoma who necessitate shunting following resection. This study aims to determine which characters are associated with the incidence in this patient subset. Methods: We surveyed this monocenter, retrospective, observational cohort of patients (aged 18 years or younger) who underwent medulloblastoma resection at our department between July 1, 2010, to August 1, 2021. The primary outcome was the incidence of necessitating permanent shunt censored after medulloblastoma surgery. Subject demographic, tumor biology, and interventions were analyzed using univariate and multivariable adjusted models. Results: 183 patients were admitted to our department. Of these, 131 (71·6%) patients participated. The incidence of necessitating permanent shunt was 25.6% (95% CI: 18.7-34.3). Factors that were independently associated with the incidence were medulloblastoma volume > 46381.5mm3 (OR: 2.919, 95% CI: 1.191-7.156) and ventricular infiltration (OR: 2.849, 95% CI: 1.142-7.102). Manifestations duration could be a covariate of tumor volume and increased risk of shunt need (OR: 1.006, 95% CI: 1.000-1.013). Besides, tumor volume was a probable predictor in patients with subtotal resection (OR: 4.900, 95% CI: 0.992-24.208, P=0.051). Lastly, there was no significant difference between the distribution of molecular subgroups for necessitating permanent shunt patients. Conclusion: Increased incidence was associated with medulloblastoma invasion. Our study implies that the presence of postresection hydrocephalus in patients with medulloblastoma was not high enough to entail a prophylactic permanent shunt in all patients.

Photonic crystals (PCs) prepared from monodispersed nanoparticles into regular lattices has attract great attention in the past decades. PCs have showed great advantages in textiles comparing with the traditional dyes due to their bright color, not fade and environment friendly. However, textiles colored by PCs generally do not have antifouling properties and poor stability on the fabrics makes them not resistant to wash. In this work, monodispersed SiO2 and polydimethylsiloxane (PDMS) with low glass transition temperature is chosen to make up the PCs coatings. To increase the stability of the PCs on the fabrics SiO2 nanoparticles was also modified by PDMS. Then the washability and antifouling properties of the PCs coated fabric was systematically studied. To further verify the availability of this method, fabrics with different chemical compositions, weaving modes, surface densities, and original color were used as the substrate to construct PCs-coatings. The influence of the fabrics structure on the structural color, reflectance spectrum, and stability of the coatings were further studied. This work will play as a guide for constructing washable and antifouling PCs on different fabric surfaces.

Public participation in community-organized disaster mitigation activities is important for improving disaster mitigation capacity. With data from 260 questionnaires, this study compared the current status of public participation in model disaster mitigation communities and nonmodel communities in a geological-disaster-prone area. Three community-organized disaster mitigation education activities were compared cross-sectionally. A binary logistic regression was used to analyze the effects of attitude, perceived behavioral control, disaster experience, and other key factors on the public’s choice to participate in community disaster mitigation activities. The analysis results indicated that model communities had higher public participation in two efforts, evacuation drills and self-help skills training, and lower participation in activities that invited them to express their feedback than nonmodel communities. The influence of attitudinal factors on the decision to participate in disaster mitigation activities had a high similarity across community types. The public participation in model disaster mitigation communities is influenced by factors such as subjective norms and participation cognition; the behavior of people in nonmodel communities is influenced by factors such as previous experience with disasters, perceived behavioral control, risk perception, and participation cognition and has a greater potential for disaster mitigation community construction. This study provides practical evidence and theoretical support for strengthening the sustainable development of disaster mitigation community building.

Here, we report 36 active-layer and 17 permafrost metagenomes from Utqiaġvik, AK, USA. Samples were collected from different topographical features and depths to study Arctic tundra microbiomes.

A recent study predicts that by 2025, up to 75 billion internet of things (IoT) devices will be connected to the internet, in which data sharing is increasingly needed by massive IoT applications as a major driver of the IoT market. However, how to meet the interests of all participants in complex multi-party interactive data sharing while providing secure data control and management is the main challenge in building an IoT data sharing ecosystem. In this article, the authors propose a blockchain-empowered data sharing architecture that supports secure data monitoring and manageability in complex multi-party interactions of IoT systems. First, to build trust among different data sharing parties, the authors apply blockchain technologies to IoT data sharing. In particular, on-chain/off-chain collaboration and sharding consensus process are used to improve the efficiency and scalability of the large-scale blockchain-empowered data sharing systems. In order to encourage IoT parties to actively participate in the construction of shared ecology, the authors use an iterative double auction mechanism in the proposed architecture to maximize the social welfare of all parties as a case-study. Finally, simulation results show that the proposed incentive algorithm can optimize data allocations for each party and maximize the social welfare while protecting the privacy of all parties.

The electrochemical reduction of carbon dioxide (CO2) to chemical feedstocks is an attractive method for the removal of CO2 from the environment. Although copper (Cu)-based catalysts produce hydroc...

The promotion of team creativity has recently become a focus in leadership research. From the perspectives of the input–process–output model and social cognitive theory, we explored leaders' positive and implicit followership theory (LPIFT) and examined team creativity, with 417 paired postgraduate and supervisor participants from a university scientific research team. Results show that LPIFT had a significant positive impact on team creativity, and that team trust (cognitive and emotional) mediated this relationship. Further, team empowerment climate positively moderated both the relationship between LPIFT and team trust (cognitive and emotional) and the mediating role of team trust (cognitive and emotional). Theoretical and practical implications are discussed.

An in-depth understanding of vapor bubble growth characteristics is of great importance for the design and optimization of gas–liquid two-phase flow instruments, which are widely utilized in chemical and thermal engineering processes. The effects of dissolved salts on vapor bubble growth remain unclear at present. In this work, we developed a surface-based bubble growth model to analyze the bubble growth rates and interface hydrodynamics in sodium chloride solution by considering the influence of dissolved salt on bubble growth. The effects of the mass fraction of NaCl and the superheat temperature on bubble growth rates and interface parameters were studied. Further, the characteristics of three typical bubble growth stages were discussed, and the roles of interfacial forces under different operating conditions were demonstrated. The results indicate that the bubble growth rates increased with the increase of the superheat temperature and mass fraction. The effects of the superheat temperature on the bubble duration time are more significant than the NaCl concentration. Besides, the validated surface-based bubble growth model could be extended to other electrolytes by modified solution properties and interface evaporation parameters.

This article focuses on solving disagreement behavior analysis problems for cooperative-antagonistic networks (CANs) subject to switching topologies, for which the extended structural balance theory is developed by concerning the local nodes instead of global CANs. A notion of simultaneously structurally balanced nodes is proposed, which helps get a role identification framework of all nodes by integrating a generalized leader–follower structure for CANs. It is shown that for any switching CANs, the behavior analysis can be performed by identifying the roles of nodes, where the disagreement behaviors are caused because of the existence of different roles of nodes. A specific class of quasi-interval bipartite consensus behaviors is characterized for CANs by the equivalence between the impact index and the number of simultaneously structurally balanced nodes. In particular, the behavior analysis results for CANs can be applied to analyze the dynamic behaviors for cooperative networks despite any switching topologies. Two simulation examples are presented to illustrate the disagreement behavior results for CANs with switching topologies.

Iron-incorporated ordered carbonaceous frameworks (OCFs) have been synthesized by the pyrolysis of iron porphyrin with ethynyl groups as polymerizable/carbonizable moieties at a temperature higher than 600 °C. The pyrolysis behavior is analyzed by thermogravimetry-differential thermal analysis-mass spectrometry, and the obtained carbon materials are characterized by X-ray diffraction, X-ray absorption fine structure, and high-angle annular dark-field scanning transmission electron microscopy. The introduction of ethynyl groups at the meta positions of the peripheral phenyl groups is essential for efficient cross-linking upon thermal polymerization. The thermally stable polymer thus obtained can be transformed into OCFs with high carbonization yield of 93 % at the subsequent carbonization. OCFs possess periodic structural regularity and porphyrin Fe-N4 coordination structure, and exhibit electrocatalysis for the conversion of CO2 into CO.

Working within a vineyard in the Pessac Léognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and normalized difference vegetation index (NDVI) datasets to accurately estimate Bordeaux vineyard soil classes and to quantitatively explore the relationship between vineyard soil types and grapevine vigor. First, co-located electrical tomographic tomography (ERT) and EMI datasets were compared to gain confidence about how the EMI method averaged soil properties over the grapevine rooting depth. Then, EMI data were used with core soil texture and soil-pit based interpretations of Bordeaux soil types (Brunisol, Redoxisol, Colluviosol and Calcosol) to estimate the spatial distribution of geophysically-identified Bordeaux soil classes. A strong relationship (r = 0.75, p

Subsurface biological processes, such as biofilm development, modify flow and permeability in fractured rocks, greatly impacting energy production or treatment efficiencies. This study aims to understand biological–hydrological interactions at a bench scale during the progression and treatment of souring (microbially mediated sulfide production). Few bench-scale studies investigate the role of a biofilm on the flow and permeability evolution, sulfidogensis, and nitrate treatment efficacy in fractured rocks. Our experiment consisted of three sandstone columns that represent differing fracture characteristics due to the mode of fracture initiation: one column with no fracture (as a control), one column with a sawcut fracture, and a third column with a fracture induced by Brazilian loading (tensile). We seek to understand the effects of the biofilm-permeability feedback on flow and nutrient transport characteristics of fractured rocks; specifically, we (1) demonstrate how fracture geometries impact the development of the biomass-permeability feedback within the rock fractures and (2) observe the souring trajectory and effects of nitrate treatment. Observed permeability trends demonstrated that bioclogging modified the flow properties of fractured columns such that they became hydrologically similar to those of the control column. While fractures were initially the main sites of sulfate reduction, when fractures were clogged, the flow in the fractured columns transitioned from a fracture-dominated flow to a matrix-dominated flow, impacting the delivery of an electron acceptor/donor to the microbial population, reducing sulfate reduction rates. Experimental data also demonstrated two distinct stages in the biofilm-permeability development. During the initial biofilm development stage, the growing microbial population had increased reaction rates but decreased permeability, i.e., a negative correlation between reaction rates and permeability. In the later stage, when the biofilm had clogged the columns, a series of biofilm shedding and regrowth directly led to reopening and clogging of the flow channels, affecting microbial accessibility to limiting nutrients. As such, a positive correlation between reaction rates and permeability was observed in this later stage. Post experimental measurements of surface elevations of the fractured surfaces revealed that surface elevations in the sawcut column were lower and more evenly distributed than the surface elevations in the tensile column where the more unevenly fractured surfaces potentially better supported the microbial establishment.

A modified 1-D transient model considering intra-particle thermal conduction is adopted to improve the predictions of the ignition characteristics of isolated coal particles. The study aims at resolving the incorrect prediction on the variation trend of ignition temperature Ti with the change of oxygen concentration XO2, interpreting the contradictory dependencies on coal particle size and furnace temperature and clarifying the conditions when the intra-particle thermal conduction should be considered. The predictions are compared with microgravity data in which the buoyancy effect is minimized. The results reveal that the previous ignition model with transient adiabatic criterion fails to predict the Ti variation with XO2, since it cannot accurately predict Ti and delay time in the low XO2 region. Instead, the ignition model with flammability limit ignition criterion can well predict Ti in a wide range of XO2. Intra-particle thermal conduction causes remarkable temperature differences for large coal particles, and moreover, the variation trends of surface and center temperatures with particle size are very different. The center temperature at ignition drops remarkably with increasing particle size, while the surface temperature barely changes or slightly increases with particle size. At the same particle size, the variation trends of surface and center temperatures with furnace temperature are also opposite. The ignition mode and variation trend of ignition surface temperature with particle size depends on the heating rate and particle size itself. The contradictory experimental results reported by different researchers are attributed to the particle size and temperature measurement location. The conditions necessary to consider the intra-particle thermal conduction are discussed. Lastly, the effect of the intraparticle thermal conduction is shown on an ignition mode diagram.

Giving full play to the public’s initiative for geological disaster reduction is critical for sustainable disaster reduction under a government-led top-down disaster governance approach. According to the public’s intention to participate in geological disaster mitigation activities, this study introduces the analytical framework of the theory of planned behavior (TPB), with attitudes, subjective norms, and perceived behavioral control as the primary explanatory variables, with three added explanatory variables: risk perception, disaster experience, and participation perception. Survey data obtained from 260 respondents in Jinchuan County, Sichuan Province, China, are analyzed using structural equation modeling and combined with multivariate hierarchical regression to test the explanatory power of the model. The results indicate that attitude, subjective normative, perceived behavioral control, and participatory cognition are significant predictors of public intention to participate. Disaster experience is negatively associated with public intention to participate. In addition, the extended TPB model contributes 50.7 % to the explanation of the behavioral intention of public participation. Practical suggestions and theoretical guidance are provided for strengthening geohazard risk management and achieving sustainable disaster reduction. In particular, it is concluded that, while correctly guiding public awareness of disaster reduction activities, policymakers should continue developing participatory mechanisms, paying attention to two-way communication bridges between the public and the government, uniting social forces, and optimizing access to resources.

BACKGROUND: Hirschsprung’s disease (HSCR) is a rare congenital disease in which enteric nervous system (ENS) in the distal intestine is absent. HSCR is a disease involving genetic factors and environmental factors. Despite a series of genes have been revealed to contribute to HSCR, many HSCR associated genes were yet not identified. Previous studies had identified that a potential susceptibility gene of HSCR was an inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase complex-associated protein (IKBKAP). The study aimed to explore the association of genetic variants in IKBKAP and HSCR susceptibility in southern Chinese children. METHODS: Single nucleotide polymorphism (SNPs) were genotyped by the Mass ARRAY iPLEX Gold system (Sequenom, San Diego, CA, USA) on all samples, which included 1,470 HSCR children (cases) and 1,473 healthy children (controls). The associations between SNPs and HSCR or clinical subtypes were assessed by comparing their allele frequencies in corresponding case and control samples. Different genetic models, including additive, recessive, and dominant models, were tested using PLINK 1.9 software. RESULTS: Further subgroup analysis revealed rs2275630 as a total colonic aganglionosis (TCA)-specific susceptibility locus. The present study is the first to indicate that IKBKAP rs2275630 were associated with HSCR susceptibility, especially in TCA patients. CONCLUSIONS: We conclude that IKBKAP rs2275630 is a susceptibility gene of HSCR.

In this paper, the design and operation of a novel coal-fired circulating fluidized bed (CFB) drum boiler that can generate superheated steam using saline water were introduced. The natural circulation water dynamics with a drum was adopted instead of the traditional once-through steam generator (OTSG) design, so that superheated steam can be generated for the better performance of the steam assisted gravity drainage (SAGD) technology in heavy oil recovery. The optimized staged evaporation method was proposed to further decrease the salinity of water in the clean water section of the boiler. The evaporating pipes of the salted water section were rearranged in the back pass of the boiler, where the heat load is low, to further improve the heat transfer safety. A CFB combustion technology was used for coal firing to achieve a uniform heat transfer condition with low heat flux. Pollutant control technologies were adopted to reduce pollutant emissions. Based on the field test, the recommended water standard for the coal-fired CFB drum boilers was determined. With the present technology, the treated recovery wastewater can be reused in steam-injection boilers to generate superheated steam. The engineering applications show that the boiler efficiency is higher than 90%, the blowdown rate is limited within 5.5%, and the superheat of steam can reach up to 30 K. Besides, the heavy oil recovery efficiency is significantly improved. Moreover, the pollutant emissions of SO2, NOx and dust are controlled within the ranges of 20–90 mg/(N·m3), 30–90 mg/(N·m3)and 2–10 mg/(N·m3) respectively.

Global warming and climate change due to anthropogenic carbon dioxide (CO2) have aroused significant concerns at the global scale due to rapid economic growth in industries and other fields. Therefore, CO2 capture, use, and storage have become particularly important. In this review, general background and methods for CO2 capture and separation, in particular, on ionic liquids (ILs)-based solvents and materials, are discussed. Comprehensive surveys of ILs for CO2 absorption are presented, which focused mainly on experimental researches, and then the concept is extended to functionalized absorbents and recent developments for CO2 capture. Major advantages and disadvantages of amines-based and ILs-based absorbents are discussed in this review. Solutions of traditional amines (MEA, MDEA, DEA, AMP, PZ, etc.) and ILs (conventional ILs, functionalized ILs, etc.) are summarized. Moreover, research progresses on CO2 separation are also introduced focusing mainly on amines and ILs-based membranes (e.g. supported amines membranes, SILMs). Futhermore, the fixation of CO2 into cyclic carbonates catalyzed by ILs (pure ILs, complex catalyst system with ILs, supported ILs, etc.) is summarized, clearly explaining the mechanism of CO2 fixation with ILs. Finally, exploration of some recent studies about CO2 capture and conversion by ILs and challenges for further progress are presented and related suggestions are put forward.

The soot formation and distribution in coal jet flames were measured using Laser-Induced Incandescence (LII) technique over a wide range of coal mass concentration (Ccoal). Experiments were conduct...

CO2-responsive switchable emulsions have been of great interest in some industrial processes where the stability of the emulsion is only required temporarily, such as oil transport, drug delivery, and fossil fuel production. The good understanding of the stability and instability mechanism is vital to the switchable behavior between emulsification and demulsification. Herein, a novel approach was developed to determine the interactions between two switchable emulsion droplets directly by a dual-laser optical tweezers instrument. The repulsive force between a couple of tetradecane droplets occurs to increase progressively with the increasing concentration of switchable surfactant in solutions. However, the repulsive force appears to decrease progressively in turn when the switchable surfactant concentration is far higher than the critical micelle concentration (CMC). Moreover, the depletion effect starts to emerge in the higher surfactant concentration which is attributed to the switchable surfactant micelles generated in solutions. In addition, according to the measurements of interaction forces, a mechanism of the switchable behavior is well proposed, which is established by the principle of self-assembly/detachment of the switchable surfactant, resulting in the weakening and re-enhancing of the electrostatic double-layer (EDL) repulsive forces between tetradecane droplets, upon selective introduction and removal of CO2. Based on this work, a novel perspective was provided to study the switchable emulsion, which can contribute instructive messages for the understanding of stability and instability mechanisms of switchable emulsions.

The particle-wall collision behaviors are important to gas-solid separation, a common process in the energy and chemical industries. To model such collisions in simulations, the impulsive equations involving the restitution and friction coefficients are commonly used, with a virtual wall to address the abnormal rebound behaviors for grazing impacts. In the present work, this model was analyzed and compared with experimental data of spherical and non-spherical particles. The results show that a restitution coefficient distribution is necessary to accurate model predictions, because of stochastic energy loss for large impact angles. The updated model is feasible for particle-wall collisions of non-spherical particles, with relative velocity errors up to 15% within the experimental conditions. Non-spherical particles' fitted model parameters are featured with smaller restitution coefficients, larger variations of restitution coefficients, larger friction coefficients and larger deviations of wall inclination angles, as the energy loss increases while the rebounding becomes more stochastic.

The particle-wall collision behavior for non-spherical particles has significant effects on gas-solid separation, which is important in mechanical, energy and other industries. Particle-wall collision experiments of spherical and non-spherical glass particles with polished and rough walls were conducted. The collision velocities were measured by high-speed photography, and the effects of particle sphericity and wall roughness were analyzed. The results show for large impact angles α1, the restitution coefficient e is independent of α1 and increases with increasing particle diameter. For the non-spherical particles or the rough wall, e increases when α1 is small and the friction coefficient f increases with decreasing α1. The non-spherical particles have smaller e, and larger f for small α1. The rough wall has smaller e for large α1 but greater dependence of e on α1, resulting in larger e instead for α1 → 20°. Under sliding condition, f increases with increasing wall roughness or decreasing particle diameter.

The classification performance of model coal mill classifiers with different bottom incoming flow inlets was experimentally and numerically studied. The flow field adjacent to two neighboring impeller blades was measured using the particle image velocimetry technique. The results showed that the flow field adjacent to two neighboring blades with the swirling inlet was significantly different from that with the non-swirling inlet. With the swirling inlet, there was a vortex located between two neighboring blades, while with the non-swirling inlet, the vortex was attached to the blade tip. The vorticity of the vortex with the non-swirling inlet was much lower than that with the swirling inlet. The classifier with the non-swirling inlet demonstrated a larger cut size than that with the swirling inlet when the impeller was stationary (~ 0 r⋅min-1). As the impeller rotational speed increased, the cut size of the cases with non-swirling and swirling inlets both decreased, and the one with the non-swirling inlet decreased more dramatically. The values of the cut size of the two classifiers were close to each other at a high impeller rotational speed (≥ 120 r⋅min-1). The overall separation efficiency of the classifier with the non-swirling inlet was lower than that with the swirling inlet, and monotonically increased as the impeller rotational speed increased. With the swirling inlet, the overall separation efficiency first increased with the impeller rotational speed and then decreased when the rotational speed was above 120 r⋅min-1, and the variation trend of the separation efficiency was more moderate. As the initial particle concentration increased, the cut sizes of both swirling and non-swirling inlet cases decreased first and then barely changed. At a low initial particle concentration (

Large eddy simulation (LES) has become a promising tool for pulverized coal combustion with the development of computational fluid dynamics (CFD) technologies in recent years. LES can better capture the unsteady features and turbulent structures of coal jet flame than Reynolds averaged Navier Stokes (RANS). The coal-fired power plants in China are now required to be operated in a wide load range and quickly respond to the electric grid. The boiler performance of variable loads should be evaluated in terms of flow, heat transfer, and combustion processes. In this paper, LES was applied to simulate a 660 MW ultra-supercritical boiler under BMCR (boiler maximum continue rate), 75%THA-100, and 50%THA-100 conditions. The predicted gas velocities agree well with the thermal calculation and the temperature error is less than 130 K. The simulation results show that the operation load has significant effects on the boiler performance. It is also proved that LES can provide guidance for the design and operation of advanced coal-fired boilers.

We report here a method for the molecular detection of miRNAs in exosomes and imaging in living cells based on CRISPR–Cas9 and catalytic hairpin assembly. With the cascade signal amplification of catalytic hairpin assembly and high specific recognition of CRISPR–Cas9, the detection method showed a sensitivity of 23.5 fM and was applied for accurate exosomal miR-21 detection and in situ miR-21 imaging.

Drop size distribution (DSD) or mean droplet size (d32) and liquid holdup are two key parameters in a liquid–liquid extraction process. Understanding and accurately predicting those parameters are of great importance in the optimal design of extraction columns as well as mixer–settlers. In this paper, the method of built-in endoscopic probe combined with pulse laser was adopted to measure the droplet size in liquid–liquid dispersions with a pump-impeller in a rectangular mixer. The dispersion law of droplets with holdup range 1% to 24% in batch process and larger flow ratio range 1/5 to 5/1 in continuous process was studied. Under the batch operation condition, the DSD abided by log-normal distribution. With the increase of impeller speed or decrease of dispersed phase holdup, the d32 decreased. In addition, a prediction model of d32 of kerosene/deionized system was established as d32/D = 0.13(1 + 5.9φ)We−0.6. Under the continuous operation condition, the general model for droplet size prediction of kerosene/water system was presented as d32/D = C3(1 + C4φ)We−0.6. For the surfactant system and extraction system, the prediction models met a general model as d32/D = bφn We−0.6.

Objective: Hepatocellular carcinoma (HCC) is a severely lethal cancer that usually originates from chronic liver injury and inflammation. Although progress on diagnosis and treatment is obvious, the cause of HCC remains unclear. In this study, we sought to determine key genes in HCC development. Methods: To identify key regulators during HCC progression, we performed transcriptome sequencing to obtain time series gene expression data from a mouse model with diethylnitrosamine-induced liver tumors and further verified gene expression and function in vitro and in vivo. Results: Among the differentially expressed genes, Cyp2c29 was continuously downregulated during HCC progression. Overexpression of Cyp2c29 suppressed NF-κB activation and proinflammatory cytokine production by increasing the production of 14,15-epoxyeicosatrienoic acid in vitro. Furthermore, overexpression of Cyp2c29 in vivo protected against liver inflammation in mouse models of liver injury induced by both acetaminophen and CCl4. Two human homologs of mouse Cyp2c29, CYP2C8 and CYP2C9, were found to be downregulated in human HCC progression, and their expression was positively correlated with overall survival in patients with HCC (significance: P = 0.046 and 0.0097, respectively). Conclusions: Collectively, through systematic analysis and verification, we determined that Cyp2c29 is a novel gene involved in liver injury and inflammation, which may be a potential biomarker for HCC prevention and prognosis determination.

Mitigating plant water stress while reducing irrigation is one of the biggest challenges that sustainable agricultural practices aim to tackle. The rhizosphere is the main unknown component controlling the water distribution in the soil, but non-destructive observations of root physiology are often lacking due to methodological limitations. Numerous studies relate the use of electrical resistivity tomography (ERT) or stem-based methods to measure soil water content changes associated with root water uptake (RWU) in the rhizosphere area. Nevertheless, geoelectrical data are correlated with many rhizosphere parameters and their interpretation needs to be supported by physics-based models of root hydrology.Here, we use a Data Assimilation (DA) framework to combine geoelectrical data with a hydrological model (Mary et al. 2021). DA offers the possibility to estimate model parameters governing RWU, such as in the well-known Feddes approach while introducing data observations to update them. In a synthetic experiment mimicking a top-down infiltration in a rhizotron containing a wine plant (Vitis Vinifera), we simulated different scenarios of ERT data assimilation with the CATHY surface-subsurface hydrological model. The rooting depth associated with the Feddes parameters are perturbed to generate the ensemble states. At each observation time, model states and root depth parameters are updated using the Ensemble Kalman Filter (ENKF). Expected results aim to demonstrate (i) what is the best ENKF scheme to integrate ERT measurements with the hydrological model and (ii) how much the uncertainties on the Feddes parameters can be reduced with the assimilation of ERT data. In a future work, the best approach identified will be applied to real soil and plant observation datasets.Mary, B., Peruzzo, L., Iván, V., Facca, E., Manoli, G., Putti, M., et al. (2021). Combining Models of Root-Zone Hydrology and Geoelectrical Measurements: Recent Advances and Future Prospects. Front. Water 3, 767910. doi:10.3389/frwa.2021.767910.

The multi-objective optimization problem, as one of the most popular hotspots in the current research, is facing both a big opportunity and a great challenge. Multi-group particle swarm optimization is often used to solve multi-objective optimization problems, however, the multi-group particle swarm optimization algorithm is more commonly used in solving static multi-objective optimization problems and less frequently used in solving dynamic multi-objective optimization problems. In solving dynamic multi-objective optimization problems, the algorithm lacks the corresponding environment detection mechanism. In this work, Dynamic Multi-Group Particle Swarm Optimization Algorithm is proposed and verified to solve multi-objective optimization problems of forest spatial structure. The proposed algorithm introduces a new mechanism for environmental detection, which can sense the changes of the situated environment and make the multi-objective optimization results more suitable for the dynamic actual situation. The results show that the average generation distance (\(\stackrel{-}{GD}\)) of the proposed algorithm is less than 0.0753, and the average metric of maximum spread (\(\stackrel{-}{MS}\)) is greater than 0.9852. The spatial structure of the target forest has been optimized three times. The mingling intensity, volume, neighborhood comparison, and open ratio are increased by 40.6%, 2.5%, 18.9%, and 11.8%, respectively; while the competition index and angle index are decreased by 37.9% and 13.1%, respectively. Obviously, the various indicators of the forest improved by our scheme are better than those before optimization.

With the expansion of the civil UAV (Unmanned Aerial Vehicle) market, UAVs are also increasingly being used in illegal activities such as espionage and snooping on privacy. Therefore, how to effectively control the activities of UAVs in cities has become an urgent problem to be solved. Considering the urban background and the radar performance of communication signals, a low-altitude target detection scheme based on 5G base stations is proposed in this paper. A 5G signal is used as the external radiation source, the method of transceiver separation is adopted, and the forward-scattered waves are used to complete the detection of UAV. This paper mainly analyzes the principle of forward scattering detection in an urban environment, where the forward-scattered wave of a target is stronger than the backward-reflected wave and contains both height difference and midline height information on the target. Based on the above theory, this paper proposes a forward-scattered wave recognition algorithm based on YOLOv3-FCWImageNet, which transforms the forward-scattered wave recognition problem into a target detection problem and accomplishes the recognition of forward-scattered waves by using the excellent performance of algorithms in the field of image recognition. Simulation results show that FCWImageNet can distinguish two different low-altitude targets effectively, and realize the monitoring and classification of UAVs.