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Abstract Archaea play an important role in the biogeochemical cycling of elements in the environment. Heavy metals are ubiquitous pollutants in the environment. Previous studies have revealed a considerable influence of metal pollution on the archaeal community, but the short-term response of the archaeal community to metal pollution remains unclear. Hence, the present study investigated the short versus long-term responses of overall archaeal communities in freshwater sediments after exposure to accidental metal pollution caused by the discharge of heavy metal-containing wastewater from an indium-producing factory. Quantitative PCR was used to determine the archaeal abundance, while Illumina MiSeq sequencing was applied to characterize the diversity and structure of the archaeal community. The abundance (2.47 × 105–1.55 × 108 archaeal 16S rRNA gene copies per gram dry sediment), diversity (Shannon diversity index = 2.49–4.45) and structure of overall archaeal community illustrated a drastic temporal change. The archaeal communities mainly comprised the phyla Euryarchaeota , Thaumarchaeota and Bathyarchaeota. The exposure to metal pollution induced an increase in the proportion of Euryarchaeota but lowered the proportion of Thaumarchaeota. The accidental metal pollution exerted a profound impact on the archaeal community in freshwater sediment. This study could contribute our understanding of the short versus long-term response of archaeal communities to metal pollution. Highlights • Metal impact on freshwater sediment archaeal community was investigated. • Metal pollution affected archaeal abundance, diversity and community structure. • Exposure to metal spill increased Euryarchaeota but decreased Thaumarchaeota. [ABSTRACT FROM AUTHOR]

Heavy metals are widely detected in natural environments, however their impacts on denitrifier community in freshwater ecosystem remain unclear. The present study investigated the changes of denitrifier communities (based on nosZ (nitrous oxide reductase) gene) in a freshwater reservoir contaminated by a severe accidental spill of heavy metals. The abundance of nosZ -denitrifiers drastically decreased, and their community richness, diversity and structure also showed considerable variations. The mainly detected denitrifying bacteria included Pseudogulbenkiania, Pseudomonas and two unknown groups. These major nosZ -denitrifier groups responded in different ways to heavy metal pollution. Metal contamination could exert a profound influence on denitrifier community in freshwater sediment. This work could provide some new insights to the impact of metal pollution on nitrogen cycling. [ABSTRACT FROM AUTHOR]

Better understanding of the colloidal behaviors of nanomaterials impacted by aquatic chemistry parameters is needed for appropriate evaluation of the environmental risks posed by nanomaterials in natural waters. In the study, the colloidal stability of Fe 3 O 4 magnetic nanoparticles (Fe-MNPs) was evaluated over a range of chemistry characteristics [e.g., pH, dissolved organic matter (DOM), salt types, cationic strength] in six synthetic water samples. The findings from the synthetic water samples were further examined with eight “real world” environmental water samples. Our results demonstrated that DOM fraction, humic acid (HA), promoted suspension of Fe-MNPs more by hydrophobic interactions in addition to ligand exchange and electrostatic effects compared with fulvic acid (FA). Capability of cations to increase aggregation of Fe-MNPs were in the order of Ca 2+  > Mg 2+ >> Na + because of their different degrees of bridging complexation with DOM molecules on particle surfaces. As a key parameter for indicating Fe-MNPs colloidal stability, Zeta (ζ) potentials of Fe-MNPs in these waters samples were well correlated to (R 2  = 0.880, P  < 0.001) the contents, types and adsorption forms of DOM and cations. However, several other factors could also affect the hydrodynamic diameter (HDD) of Fe-MNPs in the “real world” environmental waters. It assumed that ampholytic-DOM molecules such as amino acid- and protein-like molecules caused great aggregation of Fe-MNPs. These findings would be helpful for better understanding and evaluating the colloidal behaviors of nanomaterials when they released into natural water environment, thus could shed light on developing relevant pollution control strategies. [ABSTRACT FROM AUTHOR]

[Display omitted] • For the first time, the prismatic dislocation loop with independent nucleation is found in [111] crystallographic orientation of Al 0.3 CroCrFeNi high entropy alloy. • Dislocation tangles and twin boundaries hinder dislocation motion, leading to work hardening. • Free dislocation glide and annihilation, as well as the formation of steps and the partial slip where the slip plane and Burgers vector are parallel to the twin boundary, resulting in materials softening. • Phase-field-crystal simulation confirms that Al 0.3 CoCrFeNi high-entropy alloy with a twin spacing of 24.67 Å has the highest hardness. The competition and balance mechanism between work hardening resulting from the surge in dislocations and material softening caused by plastic deformation during contact loading in Al 0.3 CoCrFeNi high-entropy alloy is unclear. The structural transformation and strain localization of Al 0.3 CoCrFeNi high-entropy alloy during nanoindentation are investigated using molecular dynamics, and the hardening-softening mechanism is discussed. The simulations demonstrate that the prismatic dislocation loop with independent nucleation is discovered for the first time in the [111] orientation. Dislocation multiplication and cross-slip lead to an increase in indentation resistance, resulting in work hardening. Free dislocation slip and dislocation annihilation accommodate plastic strain will reduce indentation resistance, resulting in plastic softening. Twin boundaries can effectively block dislocation propagation, which contributes to hardening. However, twin boundaries cause a softening effect in the later stage of plastic deformation owing to two reasons: (1) the formation of steps and the partial slip where the slip plane and Burgers vector are parallel to the twin boundary, (2) steps and local damage zones in twin boundaries become new nucleation sites for dislocations. The phase-field-crystal method confirms that Al 0.3 CoCrFeNi high-entropy alloy has the highest hardness when the twin spacing is 2.467 nm. [ABSTRACT FROM AUTHOR]

Features calculation and combinatorial screening are necessary and tedious in predicting the hardness of high-entropy alloys by empirical parameters. To simplify the prediction process, we propose a strategy for predicting the hardness of high-entropy alloys based on the compositions to facilitate the rapid design of high-hardness high-entropy alloys. A random forest-based hardness prediction model was constructed using the alloy compositions as input. The Pearson correlation coefficients of the model reached 0.956 and 0.954 in the training and test sets, respectively. Subsequently, optimized alloys by inverse projection and high-throughput screening were verified using experiments. The hardness of Al 1.2 Cr 17.42 Fe 25.42 Ni 28.32 Ti 27.62 high-entropy alloy is up to 869.88 HV, which is 21.15% higher than the highest hardness in the original dataset of the Al-Cr-Fe-Ni-Ti system. The interpretability of the model was improved by introducing the Shapley additive explanation (SHAP). The results showed that the elements Al, Ti, Mo, Cr, and V play a positive role in enhancing the hardness of high-entropy alloys. Ni, Cu, Co, Mn, and Hf weaken the hardness of high-entropy alloys. • This method omits the tedious feature calculation and selection process, and the prediction process is simplified. • The hardness of the Al 1.2 Cr 17.42 Fe 25.42 Ni 28.32 Ti 27.62 is 21.15% higher than that in the dataset of the Al-Cr-Fe-Ni-Ti. • The results confirm that the Al, Ti, Mo, Cr, and V play a positive role in improving the hardness. [ABSTRACT FROM AUTHOR]

Abstract: High concentrations of s-triazine herbicides might occur in soils at spill sites. Selection of a degrader or consortium with high degradation ability is of practical importance to quickly clean up the heavy contamination. However, survival of inoculated degraders might be affected by the abundance of organic matter in soil. In this study, a simazine-degrading bacterium, Arthrobacter sp. SD3-25, was isolated from an agricultural soil. The effects of carbon sources on the strain's growth and degradation ability in both liquid culture and soil microcosm were investigated. The results indicated that the strain had much higher simazine degradation ability than those reported in previous studies, and it could quickly clean up the heavy herbicide contamination in soil. Moreover, instead of having a negative impact, external carbon source could stimulate the strain's growth and enhance simazine biodegradation rate in both culture conditions. Sucrose amendment increased the proportions of simazine-degrading trzN, atzB and atzC genes in bioaugmented soil. Bioaugmentation with the strain SD3-25 could be an option for bioremediation of heavily s-triazine-contaminated soil. However, further studies are necessary in order to elucidate the impacts of various types of carbon sources on different degraders. [Copyright &y& Elsevier]

Highlights: [•] Genetics of salinity tolerance in cucumber studied under NaCl stress. [•] Generation mean analysis revealed heritability and gene effects of cucumber. [•] Narrow-sense heritability of the traits ranged from low to high. [•] Advanced selection for salt tolerance is necessary due to low heritability. [•] Intermating of superior segregants may increase salinity tolerance in cucumber. [Copyright &y& Elsevier]

Abstract: In the present study, we show that the treatment of Epstein–Barr virus (EBV) latently infected Raji cells with TPA/SB caused the cell growth arrest. The Zta-positive cells were predominantly enriched in G0/G1 phase of cell cycle. When Zta expression reached a maximal level, a fraction of Zta expressing cell population reentered S phase. Analysis of the expression pattern of a key set of cell cycle regulators revealed that the expression of Zta and Rta substantially interfered with the cell cycle regulatory machinery in Raji cells, strongly inhibiting the expression of Rb and p53 and inducing the expression of E2F1. Down-regulation of Rb was further demonstrated to be mediated by proteasomal degradation, and p53 and p21 affected at transcription level. The data indicate that both Zta and Rta promote entry into S phase of Raji cells. The important roles of Zta and Rta in EBV lytic reactivation were also demonstrated. Our finding suggests that these two transcriptional activators may act synergistically to govern the expression of downstream early and late genes as well as cellular genes and initiation of lytic cycle and manipulation of cell cycle regulatory mechanisms require the joint and interactive contributions of Rta and Zta. [Copyright &y& Elsevier]

Ti/TiO 2 -NTs/Ag 2 O/PbO 2 anode was prepared by electrodeposition technique and characterized by scanning electron microscope-energy dispersive spectrometer (SEM-EDS), X-ray diffraction (XRD), linear sweep voltammetry (LSV), and accelerated life test. Electrochemical oxidation of persistent organic pollutant wastewater perfluorooctane sulfonate (PFOS) was carried out with the novel PbO 2 anode. Ti/TiO 2 -NTs/Ag 2 O/PbO 2 anode exhibited a pyramid structure, which was the typical PbO 2 electrodes prepared using electrochemical deposition method. XRD spectra indicated that diffraction peaks of PbO 2 coating conformed to that of JCPDS (Joint Committee on Powder Diffraction Standards) card for β-PbO 2 . Ti/TiO 2 -NTs/Ag 2 O/PbO 2 anode showed high oxygen evolution potential, and longer life service, compared with Ti/PbO 2 and Ti/TiO 2 -NTs/PbO 2 anodes. The degradation ratio of PFOS (90 mL of 0.0929 mmol L −1 ) was 74.87%, with a pseudo first-order kinetic constant of 0.0165 min −1 and a half-life of 43.18 min −1 at a constant current density of 30 mA cm −2 after 180 min of electrolysis. PFOS oxidation yielded sulfate, fluoride, and perfluorocarboxyl anions (i.e., C 3 F 7 COO − , C 4 F 9 COO − , C 5 F 11 COO − , C 6 F 13 COO − , and C 7 F 15 COO − ). The electrospray ionization (ESI) mass spectrum confirmed that oxygen in the intermediate products originated from a heavy-oxygen water electrolyte, and the degradation of PFOS was initiated by the dissociation of a sulfonic group. A possible mechanism was revealed; that was, PFOS was desulfated at the anode to form C 8 F 17 · and then transformed into C 8 F 17 OH, followed by intramolecular rearrangement and hydrolysis reactions to form C 7 F 15 COO − . Kolbe decarboxylation occurred in C 7 F 15 COO − at the anode to generate C 7 F 15 ·, which evolved into C 6 F 13 COO − in a similar way and the CF 2 unit fell off from C 7 F 15 COO − . PFOS was gradually degraded into short-chain perfluorocarboxyl anions by repeating the CF 2 unzipping cycle. [ABSTRACT FROM AUTHOR]

Abstract It has been well-documented that the distribution of ammonia-oxidizing bacteria (AOB) and archaea (AOA) in soils can be affected by heavy metal contamination, whereas information about the impact of heavy metal on these ammonia-oxidizing microorganisms in freshwater sediment is still lacking. The present study explored the change of sediment ammonia-oxidizing microorganisms in a freshwater reservoir after being accidentally contaminated by industrial discharge containing high levels of metals. Bacterial amoA gene was found to be below the quantitative PCR detection and was not successfully amplified by conventional PCR. The number of archaeal amoA gene in reservoir sediments were 9.62 × 102–1.35 × 107 copies per gram dry sediment. AOA abundance continuously decreased, and AOA richness, diversity and community structure also considerably varied with time. Therefore, heavy metal pollution could have a profound impact on freshwater sediment AOA community. This work could expand our knowledge of the effect of heavy metal contamination on nitrification in natural ecosystems. Graphical abstract Unlabelled Image [ABSTRACT FROM AUTHOR]

[Display omitted] • The impact of various image preprocessing on machine learning using micrograph dataset is evaluated for the first time. • Color , size variation, normalization and image enhancement are all considered for both classification and regression tasks. • The impact of preprocessing methods on the machine learn is contingent upon the dataset characteristics and task type. Appropriate image preprocessing could improve machine learning performance, but the robustness of machine learning to preprocessing methods in micrograph datasets with significant sample differences remains unexplored. Here we collected hundreds of optical micrographs varied in color, contrast, size and brightness and tensile strength from published literature. After preprocessing including color transformation, size adjustment, normalization and image enhancement, classification model of whether it was texture or not and tensile strength prediction model were established using transfer learning and VGG16 model. Our results showed comparable accuracy between classification models using grayscale and color micrographs. Based on grayscale images, classification model utilizing center cropping achieved an average accuracy 1.09% higher than model employing scaling, while coefficient of determination (R2) of regression model showed an average increase of 0.0404. The combination of cropping and dividing by 255 was preferable for classification model, yielding an accuracy of 90.79%. Similarly, the combination of cropping and min–max normalization had a better effect on regression model, yielding R2 of 0.2167. Histogram equalization emerged as the optimal technique for improving classification model, yielding 2.63% increase in accuracy compared to models without image enhancement. For regression models, gamma correction exhibited the highest improvement effect, with an R2 of 0.2681. [ABSTRACT FROM AUTHOR]

There has been limited research investigating how the mechanisms of aggregation of magnetic nanoparticles (MNPs) are affected by inorganic ions. In this study, Na + , Mg 2 + , Ca 2 + , Sr 2 + and Ba 2 + were selected to systematically study the aggregation mechanisms of Fe 3 O 4 MNPs. The results indicated that divalent cations more significantly affected the stabilities of MNPs than Na + at low concentrations (e.g., 0.1 mM) in a decreasing order of Ba 2 + > Sr 2 + > Ca 2 + > Mg 2 + > Na + . Extended DLVO theory did not offer a satisfactory explanation for the above difference due because it ignores specific ion effects. It was also found that the initial adsorption ratios of these metals by Fe 3 O 4 MNPs were linearly proportional to the hydrodynamic diameter (HDD) of Fe 3 O 4 MNPs before aggregation occurred. In addition to the valence states, the hydration forces and ionic radii of the metal cations were proposed to be other factors that significantly affected the interactions of metal cations with Fe 3 O 4 MNPs based on the excellent linear relationships of the HDD of Fe 3 O 4 MNPs and these three factors. Moreover, a bridging function of divalent cations might develop after aggregation occurred based on the increases in their adsorption amounts and intensities for binding oxygen-containing functional groups. In addition, an increase in the positive ζ potential of MNPs was observed with the addition of divalent cations until 10.0 mM at a pH of 5.0, which potentially enhances the resistance of MNPs to aggregation in aquatic systems compared with Na + . Consequentially, the effects of metal cations on the aggregation of MNPs are determined by the hydration forces, valance states, ionic radii and bond types formed on the MNPs. Thus, the specific ion effects of these cations should be considered in predicting the environmental behaviors of specific nanomaterials. [ABSTRACT FROM AUTHOR]

Porous concrete has found increasing applications in slope ecological protection and water purification. Indigenous microorganisms in porous concrete can play important roles in pollutant removal. However, the porous concrete microbial community and its associated influential factors remain essentially unclear. The current study investigated the influences of plantation and plant species on bacterial and archaeal communities in porous concrete unit treating polluted river water. Illumina MiSeq high-throughput sequencing revealed high microbial richness and diversity in both planted and unplanted porous concrete systems. Bacterial community had higher richness and diversity than archaeal community. The evident layer depth-related changes of microbial community richness, diversity and structure were observed in each porous concrete system. Microbial richness, diversity and structure in porous concrete unit were influenced by both plantation and plant species type. Moreover, Proteobacteria dominated in bacterial communities in both planted and unplanted porous concrete systems, while unplanted porous concrete system displayed much higher proteobacterial proportion than planted ones. Thaumarchaeota microorganisms accounted for a considerable proportion in archaeal communities in porous concrete units. [ABSTRACT FROM AUTHOR]

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis. [Display omitted] • General guidance on machine learning (ML) for heterogeneous catalysis is proposed. • The recent progress in ML from a new perspective is reviewed for the first time. • Performance prediction and parameter optimization via ML is discussed. • The understanding of catalytic mechanism via ML is highlighted. • Challenges and perspectives of ML for energy and environment are put forward. [ABSTRACT FROM AUTHOR]

Microorganisms in surface water constructed wetland (CW) play crucial roles in pollutant removal. However, little is known about the diversity and structure of microbial community in surface water CW. The influential factors regulating microbial community diversity and structure remain poorly known. In the present study, Illumina high-throughput sequencing was used to characterize bacterial and archaeal communities in three lab-scale vertical-flow CW (VF-CW) systems with different substrate materials (fine gravel, steel slag or natural zeolite). The depth-related change of archaeal and bacterial community richness, diversity and structure occurred in these three VF-CW systems. Microbial diversity in three VF-CW systems showed the similar depth-related change pattern, but microbial richness illustrated the different change pattern. Substrate type had a profound effect on bacterial richness but only a slight effect on bacterial diversity. Archaeal richness and diversity were affected by substrate type and wetland depth. Moreover, archaeal community had much lower richness and diversity than bacterial community. Archaeal and bacterial community structure was regulated by substrate type and wetland depth. Proteobacteria and Acidobacteria were the most abundant bacterial phyla, while Euryarchaeota was the predominant archaeal phylum. [ABSTRACT FROM AUTHOR]

The effect of ions on the colloidal behavior of magnetic nanoparticles (MNPs) is an important factor for determining the dispersibility of MNPs. Compared with the effects of cations and organic matter, the effect of anions on MNPs has rarely been studied. Hence, in this study, the effect of anions on the aggregation of Fe 3 O 4 MNPs in the aqueous phase was investigated using F−, Cl−, Br−, NO 3 −, and SO 4 2−. The results indicated that the effect of anions on the colloidal behavior of the MNPs varied widely depending on their valence state, concentration, hydration ability, solution pH, and the magnetic force between the MNPs. Specifically, at pH 5.0, the anions were mainly adsorbed on the particle surface by electrostatic attraction, decreasing the electrostatic repulsion between the MNPs and causing an aggregation of the particles in the order of SO 4 2− > F− > Br− > Cl− ≈ NO 3 −. At pH 9.0, anions strengthened the suspension of the MNPs at low ionic strength (IS) (≤5); however, with increasing IS, an aggregation of the MNPs in the following order was formed: NO 3 − > Cl− > Br− ≥ F− > SO 4 2−. This was a result of the combined effects of the IS of solution, hydrability, and polarizability of the anions. Furthermore, the Derjaguin-Landau-Vervey-Overbeek (DLVO) theory can explain the colloidal behavior of MNPs in the presence of magnetic forces, but it fails to differentiate the MNP behaviors between monovalent anions because the effects of ionic hydrability and polarizability are not considered. Distinctively, the secondary minimum between the MNPs particles were induced via magnetic attraction and played a critical role in adjusting the colloidal stability of the MNPs. Overall, these results indicate that specific ionic effects and magnetic attraction are important for interpreting the colloidal stability of MNPs in aqueous conditions. Unlabelled Image • Adsorption amounts of anions determined the stability of MNPs at pH 5.0 and 9.0. • Anions strengthened the suspension of MNPs at ionic strength below 5.0 at pH 9.0. • The secondary minimum was induced by the magnetic attraction between MNPs. • Ionic hydrability and polarizability largely affected the aggregation of MNPs. [ABSTRACT FROM AUTHOR]