scholarly journals Diversity of Immobilized Bacterial Communities and Nitrates Removal by Instantaneous Heterotrophic Denitrification Treating Nitrate-Polluted Water Using 3D-BERs-GAC: Effects of pH and COD/NO3- -N Ratio

2020 ◽  
Author(s):  
Mahdi Hassan ◽  
Guangcan Zhu ◽  
Zhonglian Yang ◽  
Yongze Lu ◽  
Huang Shan
Keyword(s):  
High Throughput Sequencing ◽  
Three Dimensional ◽  
Denitrification Rate ◽  
Polluted Water ◽  
Bottom Surface ◽  
Adaptation Period ◽  
Low Carbon ◽  
Treatment Technology ◽  
Microbial Composition ◽  
Denitrification Process

In this study, a three-dimensional bioelectrochemical reactor system (3D-BERs) with granular activated carbon (GAC) epitomizes a novel treatment technology for treating nitrate-polluted water. The conventional denitrification process faces many challenges, including the huge demand for organic carbon, long-term accumulation of intermediate products, and the adaptation period. Results shown that under the optimal conditions of the COD/NO3--N ratio was 1.5, the denitrification efficiency reached 98.62%, when compared to 81.12% at COD/ NO3--N ratio of 3.5, and the initial pH of 7.5 ± 0.5, NO3--N was entirely removed at 2.2 h without accumulation of nitrite. The high initial ratio of NO2--N/NO3--N is mainly to accelerate the denitrification rate by accelerating the reduction of nitrite. Denitrification process followed by zero-order kinetics linear model for at different concentrations of inlet NO3--N, and achieved higher denitrification rate at greater inlet NO3--N concentration. High-throughput sequencing shows that the community structure and relative abundance of bacteria changed significantly, especially at the genes and the phyla level in immobilized GAC particles. Microbial composition enhanced the removal of nitrogen at the inner surface (IS) and bottom surface (BS) of immobilized GAC carriers. Therefore, this system is expected to be a more efficient and useful supplement or a cost-effective alternative compared to the traditional low carbon to nitrogen wastewater treatment system.

scholarly journals The removal performance of nitrates in the novel 3D-BERS with GAC and diversity of immobilized microbial communities treating nitrate-polluted water: Effects of pH and COD/NO3--N ratio

2021 ◽  
Vol 27 (2) ◽  
pp. 200526-0
Author(s):  
Mahdi Hassan ◽  
Guangcan Zhu ◽  
Zhonglian Yang ◽  
Yongze Lu ◽  
Huang Shang ◽  
...  
Keyword(s):  
Removal Efficiency ◽  
Three Dimensional ◽  
Polluted Water ◽  
Bottom Surface ◽  
Zero Order Kinetics ◽  
Initial Ph ◽  
Water Effects ◽  
Effects Of Ph ◽  
Denitrifying Microorganisms ◽  
Denitrification Process

In this work, a three-dimensional bioelectrochemical reactor system (3D-BERs) with granular activated carbon (GAC) was utilized to study the feasibility of simultaneous removal of nitrates by autotrophic-heterotrophic denitrification process under different pH levels. In this present study, it was found that when the influent COD/ NO3--N ratio ranged between 1.5 and 3.5, both autotrophic and heterotrophic denitrifying microorganisms played an important role in denitrification. The experimental results demonstrated that the highest removal efficiency of nitrates under the optimum COD/NO3--N ratio of 1.5 (98.62%) was achieved with an initial pH of 7.5 ± 0.4. Likewise, when the COD/NO3--N ratio of 3.5, the nitrates removal efficiency (81.12%) was achieved with an initial pH of 8.2 ± 0.3, respectively. Batch denitrification processes followed zero-order kinetics at various NO3--N concentrations obtained. The bacterial community structure and relative abundance of bacteria changed at the level of genes and the phylum of immobilized GAC particles. Moreover, the diversity of bacterial composition enhanced the removal of NO3--N at the inner surface (IS), and bottom surface (BS) of immobilized GAC carriers were Gammaproteobacteria, Bacilli, Proteobacteria, and Thauera. In general, this technique is more effective for enhancing the denitrification process in the 3D-BER system.

Three-dimensional stromatolites from Maastrichtian–Danian Yacoraite Formation, Argentina: modelling and assessing hydrodynamic controls on growth patterns

2021 ◽  
pp. 1-17
Author(s):  
Patricio Guillermo Villafañe ◽  
Carlos Cónsole-Gonella ◽  
Paolo Citton ◽  
Ignacio Díaz-Martínez ◽  
Silvina de Valais
Keyword(s):  
Environmental Factors ◽  
Methodological Approach ◽  
Three Dimensional ◽  
Growth Patterns ◽  
External Morphology ◽  
Water Dynamics ◽  
Microbial Composition ◽  
Depositional Processes ◽  
Run Off ◽  
Internal Arrangement

Abstract Stromatolites are biogenic sedimentary structures formed by the interplay of biological (microbial composition) and environmental factors (local hydrodynamic conditions, clastic input and/or water chemistry). Well-preserved, three-dimensional (3D) fossil stromatolites are key to assessing the environmental factors controlling their growth and resulting morphology in space and time. Here, we report the detailed analysis of well-exposed, highly informative stromatolite build-ups from a single stratigraphic horizon within the Maastrichtian–Danian Yacoraite Formation (Argentina). This study focuses on the analysis of depositional processes driving intertidal to shallow subtidal stromatolites. Overall depositional architecture, external morphology and internal arrangement (mega, macro, meso and microstructures) of stromatolite build-ups were analysed and combined with 3D photogrammetric models, allowing us to decipher the links between stromatolite structure and tidal dynamics. Results suggest that external morphology and architecture of elongated and parallel clusters grew under the influence of run-off channels. The internal morphology exhibits columnar structures where the space between columns is interpreted as recharge or discharge channels. This work supports the theory that stromatolites can be used as a high-resolution tool in the assessment of water dynamics, and provides a new methodological approach and data for the dynamic reconstruction of intertidal stromatolite systems through the geological record.

scholarly journals Disentangling Responses of the Subsurface Microbiome to Wetland Status and Implications for Indicating Ecosystem Functions

2021 ◽  
Vol 9 (2) ◽  
pp. 211
Author(s):  
Jie Gao ◽  
Miao Liu ◽  
Sixue Shi ◽  
Ying Liu ◽  
Yu Duan ◽  
...  
Keyword(s):  
Microbial Community ◽  
High Throughput Sequencing ◽  
Carbon Fixation ◽  
Microbial Community Composition ◽  
Ecosystem Functions ◽  
Microbial Composition ◽  
Wetland Ecosystems ◽  
Soil Microbial ◽  
Geochemical Properties ◽  
Microbial Groups

In this study, we analyzed microbial community composition and the functional capacities of degraded sites and restored/natural sites in two typical wetlands of Northeast China—the Phragmites marsh and the Carex marsh, respectively. The degradation of these wetlands, caused by grazing or land drainage for irrigation, alters microbial community components and functional structures, in addition to changing the aboveground vegetation and soil geochemical properties. Bacterial and fungal diversity at the degraded sites were significantly lower than those at restored/natural sites, indicating that soil microbial groups were sensitive to disturbances in wetland ecosystems. Further, a combined analysis using high-throughput sequencing and GeoChip arrays showed that the abundance of carbon fixation and degradation, and ~95% genes involved in nitrogen cycling were increased in abundance at grazed Phragmites sites, likely due to the stimulating impact of urine and dung deposition. In contrast, the abundance of genes involved in methane cycling was significantly increased in restored wetlands. Particularly, we found that microbial composition and activity gradually shifts according to the hierarchical marsh sites. Altogether, this study demonstrated that microbial communities as a whole could respond to wetland changes and revealed the functional potential of microbes in regulating biogeochemical cycles.

scholarly journals Experimental infection with the hookworm, Necator americanus, is associated with stable gut microbial diversity in human volunteers with relapsing multiple sclerosis

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Timothy P. Jenkins ◽  
David I. Pritchard ◽  
Radu Tanasescu ◽  
Gary Telford ◽  
Marina Papaiakovou ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Experimental Infection ◽  
High Throughput Sequencing ◽  
Alpha Diversity ◽  
Placebo Treatment ◽  
Sequencing Data ◽  
Faecal Microbiota ◽  
Microbial Composition ◽  
Necator Americanus ◽  
Human Volunteers

Abstract Background Helminth-associated changes in gut microbiota composition have been hypothesised to contribute to the immune-suppressive properties of parasitic worms. Multiple sclerosis is an immune-mediated autoimmune disease of the central nervous system whose pathophysiology has been linked to imbalances in gut microbial communities. Results In the present study, we investigated, for the first time, qualitative and quantitative changes in the faecal bacterial composition of human volunteers with remitting multiple sclerosis (RMS) prior to and following experimental infection with the human hookworm, Necator americanus (N+), and following anthelmintic treatment, and compared the findings with data obtained from a cohort of RMS patients subjected to placebo treatment (PBO). Bacterial 16S rRNA high-throughput sequencing data revealed significantly decreased alpha diversity in the faecal microbiota of PBO compared to N+ subjects over the course of the trial; additionally, we observed significant differences in the abundances of several bacterial taxa with putative immune-modulatory functions between study cohorts. Parabacteroides were significantly expanded in the faecal microbiota of N+ individuals for which no clinical and/or radiological relapses were recorded at the end of the trial. Conclusions Overall, our data lend support to the hypothesis of a contributory role of parasite-associated alterations in gut microbial composition to the immune-modulatory properties of hookworm parasites.

Screening and Characterization of a Bacterium Capable of Simultaneous Heterotrophic Nitrification and Aerobic Denitrification at High Concentrations of Ammonia-Nitrogen

2014 ◽  
Vol 665 ◽  
pp. 487-490
Author(s):  
Te Wang ◽  
Zhao Xia Liu ◽  
Mei Juan Wu ◽  
Fu Hui Kang ◽  
Qing Chen ◽  
...  
Keyword(s):  
16S Rdna ◽  
Ammonia Nitrogen ◽  
Heterotrophic Nitrification ◽  
Denitrification Rate ◽  
Aerobic Denitrification ◽  
Optimal Conditions ◽  
Carbon And Nitrogen ◽  
Mass Ratios ◽  
High Concentrations ◽  
Denitrification Process

A bacterium capable of simultaneous heterotrophic nitrification and aerobic denitrification at high concentrations of ammonia-nitrogen was screened and identified and the denitrification property was investigated in this paper. The strain was isolated from aeration tank of wastewater disposed by activated sludge and analyzed and identified by 16S rDNA. The effects of different carbon sources and carbon and nitrogen mass ratios on denitrification rate were studied. The changes of various forms of ammonia-nitrogens during the simultaneous heterotrophic nitrification and aerobic denitrification process were characterized. A strain capable of simultaneous heterotrophic nitrification and aerobic denitrification at 600 mg/L nitrogen concentration has been isolated and screened. Comparison of its 16S rDNA sequence showed 100% similarity to Bacillus licheniformis strain Lr124/6. The strain was named as Bacillus sp. A22. The optimal conditions for degradation of ammonia-nitrogen by Bacillus sp. A22 were trisodium citrate as carbon source and carbon and nitrogen mass ratios of 10. The denitrification rate was 98.2% after 96 h of culture under the optimal conditions and there was hardly any intermediates accumulation in the denitrification process. It has practical applications that the denitrification can be performed efficiently at high concentrations of ammonia-nitrogen by method of simultaneous heterotrophic nitrification and aerobic denitrification by Bacillus sp. A22 in nitrogen purification treatment of wastewater with high concentrations of ammonia-nitrogen.

Laser Forming for Flexible Fabrication

2000 ◽  
Vol 16 (02) ◽  
pp. 97-109
Author(s):  
Koichi Masubuchi ◽  
Jerry E. Jones
Keyword(s):  
Three Dimensional ◽  
Low Carbon Steel ◽  
High Strength Steels ◽  
Cost Benefit ◽  
Network Models ◽  
High Strength ◽  
Laser Forming ◽  
Low Carbon ◽  
Flat Plates ◽  
Neural Network Models

A 36-month program supported by the Defense Advanced Research Projects Agency (DARPA) was conducted to demonstrate the feasibility to predictably laser form a variety of ferrous and non-ferrous metals of different thickness. Laser forming provides a method of producing complex shapes in sheet, plate, and tubing without the use of tooling, molds, or dies. By heating a localized area with a laser beam, it is possible to create stress states that result in predictable deformation. This research program has developed, refined and demonstrated constitutive and empirical, and neural network models to predict deformation as a function of critical parametric variables and established an understanding of the effect of laser forming on some metallurgical properties of materials. The program was organized into two, time-phased tasks. The first task involved forming flat plates to one-dimensional (I -D) shapes, such as, hinge bends in various materials including low-carbon steel, high-strength steels, nickel-based super alloys, and aluminum alloys. The second task expanded the work conducted in the first task to investigate three-dimensional (3-D) configurations. The models were updated, 3-D specimens fabricated and evaluated, and cost benefit analyses were performed.

The Effect of Severe Plastic Deformation on the Brittle-Ductile Transition in Low Carbon Steel

2009 ◽  
Vol 633-634 ◽  
pp. 471-480
Author(s):  
Masaki Tanaka ◽  
Kenji Higashida ◽  
Tomotsugu Shimokawa
Keyword(s):  
Fracture Toughness ◽  
Carbon Steel ◽  
Grain Boundaries ◽  
Three Dimensional ◽  
Low Carbon Steel ◽  
Dislocation Dynamics ◽  
Strain Rates ◽  
Low Carbon ◽  
Dislocation Source ◽  
Brittle Ductile Transition

Brittle-ductile transition (BDT) behaviour was investigated in low carbon steel deformed by an accumulative roll-bonding (ARB) process. The temperature dependence of its fracture toughness was measured by conducting four-point bending tests at various temperatures and strain rates. The fracture toughness increased while the BDT temperature decreased in the specimens deformed by the ARB process. Arrhenius plots between the BDT temperatures and the strain rates indicated that the activation energy for the controlling process of the BDT was not changed by the deformation with the ARB process. It was deduced that the decrease in the BDT temperature by grain refining was not due to the increase in the dislocation mobility controlled by short-range barriers. Quasi-three-dimensional simulations of dislocation dynamics, taking into account of crack tip shielding due to dislocations, were performed to investigate the effect of a dislocation source spacing along a crack front on the BDT. The simulation indicated that the BDT temperature is decreased with decreasing in the dislocation source spacing. Molecular dynamics simulations revealed that moving dislocations were impinged against grain boundaries and were reemitted from there with increasing strain. It indicates that grain boundaries can be new sources in ultra-fine grained materials, which increases toughness at low temperatures.

Analysis of the effect of the size of three-dimensional micro-geometric structures on physical adhesion phenomena using microprint technique

2018 ◽  
Vol 41 (5) ◽  
pp. 277-283 ◽  
Author(s):  
Akiko Oota-Ishigaki ◽  
Toru Masuzawa ◽  
Kazuaki Nagayama
Keyword(s):  
Shear Rate ◽  
Secondary Flow ◽  
Thrombus Formation ◽  
Three Dimensional ◽  
Flow Simulation ◽  
Quantitative Relationship ◽  
Bottom Surface ◽  
Material Surface ◽  
Computational Fluid Dynamics Analysis ◽  
Biomaterial Surfaces

Thrombus formation on biomaterial surfaces with microstructures is complex and not fully understood. We have studied the micro-secondary flow around microstructures that causes components of blood to adhere physically in a low Reynolds number region. The purpose of this study was to investigate the effect of micro-column size on the adhesion phenomena and show a quantitative relationship between the micro-secondary flow and physical adhesion phenomena, considering microstructures of various sizes. The flow simulation and quantitative assessment of adhesion rates around micro-columns was conducted using four sizes of micro-columns. This study also calculated the vectors of micro-secondary flow and average shear rate around a micro-column using a computational fluid dynamics analysis. The simulation showed the micro-secondary flow toward the bottom surface at upstream side and low shear rate distribution generated around a micro-column. Furthermore, physical adhesion tests were conducted using microbeads and a perfusion circuit to examine the size effect of the micro-columns on the physical adhesion. The results showed that the average adhesion rate around the micro-column increases with the associated size increase of the micro-column. Our results indicate that quantification of micro-secondary flow on a material surface with microstructures of several sizes and shapes (such as in a rough surface) is important for the evaluation of the adhesion phenomenon even though the surface roughness value on the material surface is small.

scholarly journals Bioconductor workflow for microbiome data analysis: from raw reads to community analyses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1492 ◽  
Author(s):  
Ben J. Callahan ◽  
Kris Sankaran ◽  
Julia A. Fukuyama ◽  
Paul J. McMurdie ◽  
Susan P. Holmes
Keyword(s):  
High Throughput Sequencing ◽  
Linear Models ◽  
Reference Database ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Nonparametric Testing ◽  
Abundance Estimates ◽  
Taxonomic Markers ◽  
Microbiome Data ◽  
Microbiome Data Analysis

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, including both parameteric and nonparametric methods. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests, partial least squares and linear models as well as nonparametric testing using community networks and the ggnetwork package.

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