An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Engineered nanomaterials (ENMs) have been reported to facilitate extracellular electron transfer (EET) by increasing the electrical conductivity of electroactive biofilms. However, the mechanisms between different nanomaterials and anoxygenic photoelectrogenic bacteria for degrading organic pollutants remain unclear. In this study, we investigated the mechanism of metronidazole(MNZ) degradation by different concentrations of carbon nanotubes (CNTs), Iron(III) oxide (Fe3O4) NPs, and titanium dioxide (TiO2) NPs in R.palustris based photoelectrogenic biofilms. At 74μg/L, CNTs enhance the electrochemical activity and EET capacity of the biofilm, possibly by increasing the DNA concentration and cellular activity in the cathodic biofilm. However, at high concentrations, the ecological toxicity of CNTs significantly amplified, resulting in a decline in the MNZ degradation rate (0.29179h-1 at 185μg/L and 0.27801h-1 at 370μg/L). TiO2NPs only enhance photosynthetic current (37.7%) and MNZ degradation (48.65%) at 185μg/L compared to the control group. A high TiO2NPs concentration (370μg/L) significantly boosts the MNZ degradation rate (133% increase) via photocatalytic activity. But it thinned the biofilm and inhibited EET. Fe3O4NPs strengthened photosynthetic current and MNZ degradation from low to high concentrations (74-370μg/L), promoting EET. At 185μg/L, the photosynthetic current and MNZ degradation rate increased by 138% and 142%, respectively. However, excessive concentrations may limit the utilization rate of iron ions and EET. Moderate Fe3O4NPs concentrations (74-185μg/L) can enhance microbial activity and improve biofilm performance in photosynthetic electron extraction and MNZ degradation. These findings were not only important for optimizing the performance of anoxygenic photoelectrogenic biofilms but also for regulating the ecological impact of nanomaterials in natural environments.
For massive multiuser multiple-input multiple-output (MIMO) systems, linear detectors, such as minimum mean square error (MMSE), suffer from unbearable computational pressure due to the large-scale matrix inversions. Various iterative detectors, such as Jacobi and steepest descent (SD) as well as their enhanced variants, are applied to improve the performance and complexity trade-off. However, their benefits would not maintain when: 1) the number of users is close to that of the base station antennas and 2) channel correlation is considered. To address this problem, an iterative detector based on SD and Barzilai-Borwein (BB) algorithms entitled SDBB is introduced in this paper. Furthermore, a novel enhanced SDBB (ESDBB) detector is proposed, which combines SDBB with SD to achieve better performance in the challenging scenarios. Both theoretical and numerical results are detailed to demonstrate the advantages of ESDBB in balancing the performance and complexity. Specifically, attaining faster convergence and better bit error rate (BER) results, ESDBB outperforms methods, including adaptive Jacobi and successive over relaxation (SOR). An efficient hardware architecture for the ESDBB detector is also proposed. Implementation results on a Xilinx Virtex-7 XC7VX690T FPGA show the advantages of the proposed ESDBB detector compared to the state of the art (SOA) in terms of throughput (31.3 Mb/s) and efficiency.
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