Handbergdickey8154

33)CO3 and calcite phase); eventually, tailings particles were coated with the growth of mineralized carbonates, resulting in a reduction of exposure for tailings (especially sulfur). And thus, Cd release was inhibited. Results from this study will provide a fundamental basis for future in-situ applications of MICP to mitigate heavy metal pollutions.The potential effects of engineered nanoparticles (NPs) on metal bioaccumulation in aquatic organisms have been the focus of increasing research attention. However, while NPs typically aggregate, the role of aggregation in NP-mediated metal bioaccumulation is largely unknown. The present study investigated the effects of polyacrylate-coated TiO2 (anatase) NPs (AnaNPs) on Cd bioaccumulation in zebrafish. The Ca concentration in the experimental medium was manipulated to regulate AnaNP aggregation. At the low Ca concentration, the AnaNPs were well-dispersed and there was little bioaccumulation. Under this condition, Cd bioaccumulation was mainly via the uptake of free ions (Route 1), with only a minor contribution from NP-Cd complexes (Route 2). Therefore, AnaNPs decreased Cd bioaccumulation, as their inductive carrier effect could not offset the inhibition induced by the decrease in the free Cd ion concentration as a result of NP adsorption. At the high Ca concentration, the AnaNPs aggregated and their bioaccumulation increased. Accordingly, Cd bioaccumulation was equally accounted for by Routes 1 and 2 but the overall amount of Cd remained unchanged because the inductive effect of the AnaNPs offset their inhibitory effect. Thus, during risk evaluations of NPs, the contribution of aggregation to metal bioaccumulation should be considered.The control of degrader populations and the stochasticity and certainty of the microbial community in contaminated groundwater are not well-understood. In this study, a long-term contaminated groundwater ecosystem was selected to investigate the impact of BTEX on microbial communities and how microbial communities respond to BTEX pollution. 16S rRNA gene sequencing and metagenomic sequencing provided insights on microbial community assemblage patterns and their role in BTEX cleaning. The operational taxonomy units (OTUs) in the contaminated groundwater ecosystem were clustered distinguishably between the Plume and the Deeper Zone (lower contaminated zone). βNTI analysis revealed that the assembly strategies of abundant and rare OTU subcommunities preferred deterministic processes. Redundancy Analysis (RDA) and mantel testing indicated that benzene, toluene, ethylbenzene, and xylenes (BTEX) strongly drove the abundant OTU subcommunity, while the rare OTU subcommunity was only weakly affected. Deltaproteobacteria, the most dominant degrading microorganism, contains the complete degradation genes in the plume layer. In summary, our finding revealed that BTEX was the major factor in shaping the microbial community structure, and functional bacteria contribute greatly to water cleaning. Investigating the pattern of microbial community assembly will provide insights into the ecological controls of contaminant degradation in groundwater.Recently, sulfate radical-based advanced oxidation processes (SR-AOPs) have shown broad potential for restoring the water environment. However, the application of SR-AOPs to simultaneously remove organic pollutants and Cr(VI) has rarely been reported. Herein, we developed a modified schwertmannite (Sch-PVA) synthesized via the mediation of Acidithiobacillus ferrooxidans in the introduction of polyvinyl alcohol (PVA). This modification significantly changed the morphology and structure of the schwertmannite (Sch). The specific surface area and the density of functional sites also increased. Sch-PVA significantly increased the persulfate (PDS) activation efficiency. Even in 100 mg L-1 rhodamine B (RhB) conditions, 96.3% of RhB was eliminated by 0.5 g L-1Sch-PVA and 6 mM PDS in 120 min. Moreover, excellent performance was exhibited over a wide pH range. The dissolution of the passivation layer facilitated the exposure of new adsorption and reduction sites, thereby enhancing the simultaneous removal of RhB and Cr(VI). Quenching experiments and electron spin resonance (ESR) measurements verified that sulfate and hydroxyl radicals were generated. The hydroxyl groups on the Sch-PVA surface played a key role in the bonding with and the activation of PDS. In conclusion, Sch-PVA provides new insights into the catalyst application for simultaneous removal of organic pollutants and Cr(VI).The Spike protein (S protein) is a critical component in the infection of the new coronavirus (SARS-CoV-2). selleck inhibitor The objective of this work was to evaluate whether peptides from S protein could cause negative impact in the aquatic animals. The aquatic toxicity of SARS-CoV-2 Spike protein peptides derivatives has been evaluated in tadpoles (n = 50 tadpoles/5 replicates of 10 animals) from species Physalaemus cuvieri (Leptodactylidae). After synthesis, purification, and characterization of peptides (PSDP2001, PSDP2002, PSDP2003) an aquatic contamination has been simulated with these peptides during 24 h of exposure in two concentrations (100 and 500 ng/mL). The control group ("C") was composed of tadpoles kept in polyethylene containers containing de-chlorinated water. Oxidative stress, antioxidant biomarkers and AChE activity were assessed. In both concentrations, PSPD2002 and PSPD2003 increased catalase and superoxide dismutase antioxidants enzymes activities, as well as oxidative stress (nitrite levels, hydrogen peroxide and reactive oxygen species). All three peptides also increased acetylcholinesterase activity in the highest concentration. These peptides showed molecular interactions in silico with acetylcholinesterase and antioxidant enzymes. Aquatic particle contamination of SARS-CoV-2 has cholinesterasic effect in P. cuvieri tadpoles. These findings indicate that the COVID-19 can constitute environmental impact or biological damage potential.Phytoremediation is a green technology for heavy metal removal from contaminated soil, and its remediation efficiency and economic feasibility in field trial should be evaluated before large-scale application. However, there is still lacking relevant analysis, especially for phytoremediation with different cropping patterns. In the present study, we performed phytoremediation on slightly Cd-contaminated farmland soil via three cropping systems, i.e. Sedum alfredii monoculture, oilseed rape monoculture, and S. alfredii-oilseed rape intercropping. Dry weights of S. alfredii and oilseed rape were both enhanced under intercropping pattern, while the highest total Cd extraction amount (148 g ha-1) were observed under S. alfredii monoculture. Furtherly, a cost-benefit analysis via Monta Carlo simulation in a ten-year lifetime was conducted. The benefits of S. alfredii monoculture and intercropping schemes would offset the total costs in 6 and 8 years, respectively. S. alfredii monoculture achieved a higher net present value of 1.88 × 104 US$ as compared with intercropping (9.53 × 103 US$). These results indicate that S. alfredii monoculture scheme could be a promising phytoremediation strategy for slightly Cd-contaminated soil owing to better remediation efficiency and economic feasibility. Moreover, the enhancement in mechanization level and the reduction of seedling cost could further improve its economic viability.Biological desulfurization processes of landfill gas yield an enormous amount of biologically produced S (BPS) as a byproduct. Capability of BPS to remove Cd2+ from aqueous solutions was tested and its removal efficiency was compared to that of granular activated carbon (GAC). Kinetics of Cd2+ removal by BPS was a two-stage process with an initial rapid adsorption showing 45% of initial Cd2+ was removed within 5 min, followed by a slower adsorption. Cadmium adsorption onto the BPS fitted the Langmuir isotherm model and maximum adsorption capacity of the BPS (63.3 mg g-1) was 1.8 times higher than that of GAC (36.1 mg g-1). Thermodynamic parameters showed that Cd2+ adsorption by BPS was favorable and endothermic. Data from XPS proved the main adsorption mechanism to be complexation of Cd2+ with sulfides in the BPS. Results demonstrated that BPS can be recycled as a novel adsorbent for Cd2+ removal from wastewater.Deep-learning-based registration methods emerged as a fast alternative to conventional registration methods. However, these methods often still cannot achieve the same performance as conventional registration methods because they are either limited to small deformation or they fail to handle a superposition of large and small deformations without producing implausible deformation fields with foldings inside. In this paper, we identify important strategies of conventional registration methods for lung registration and successfully developed the deep-learning counterpart. We employ a Gaussian-pyramid-based multilevel framework that can solve the image registration optimization in a coarse-to-fine fashion. Furthermore, we prevent foldings of the deformation field and restrict the determinant of the Jacobian to physiologically meaningful values by combining a volume change penalty with a curvature regularizer in the loss function. Keypoint correspondences are integrated to focus on the alignment of smaller structures. We perform an extensive evaluation to assess the accuracy, the robustness, the plausibility of the estimated deformation fields, and the transferability of our registration approach. We show that it achieves state-of-the-art results on the COPDGene dataset compared to conventional registration method with much shorter execution time. In our experiments on the DIRLab exhale to inhale lung registration, we demonstrate substantial improvements (TRE below 1.2 mm) over other deep learning methods. Our algorithm is publicly available at https//grand-challenge.org/algorithms/deep-learning-based-ct-lung-registration/.Recently, more clinicians have realized the diagnostic value of multi-modal ultrasound in breast cancer identification and began to incorporate Doppler imaging and Elastography in the routine examination. However, accurately recognizing patterns of malignancy in different types of sonography requires expertise. Furthermore, an accurate and robust diagnosis requires proper weights of multi-modal information as well as the ability to process missing data in practice. These two aspects are often overlooked by existing computer-aided diagnosis (CAD) approaches. To overcome these challenges, we propose a novel framework (called AW3M) that utilizes four types of sonography (i.e. B-mode, Doppler, Shear-wave Elastography, and Strain Elastography) jointly to assist breast cancer diagnosis. It can extract both modality-specific and modality-invariant features using a multi-stream CNN model equipped with self-supervised consistency loss. Instead of assigning the weights of different streams empirically, AW3M automatically learns the optimal weights using reinforcement learning techniques. Furthermore, we design a light-weight recovery block that can be inserted to a trained model to handle different modality-missing scenarios. Experimental results on a large multi-modal dataset demonstrate that our method can achieve promising performance compared with state-of-the-art methods. The AW3M framework is also tested on another independent B-mode dataset to prove its efficacy in general settings. Results show that the proposed recovery block can learn from the joint distribution of multi-modal features to further boost the classification accuracy given single modality input during the test.