Increased content and uniformity of enzyme-induced calcite precipitation realized by prehydrolysis and an accelerated injection rate

The utilization of enzyme-induced calcium carbonate precipitation (EICP) to consolidate aeolian sand has received significant attention in recent years. When EICP was used and cementing solution was injected in stages, the calcium carbonate content and uniformity were not improved simultaneously. A method is proposed to alleviate this problem by pre-reacting urea and urease before injecting the cementing solution and speeding up the injection rate. Experiments were designed to compare staged injections of EICP-cemented aeolian sand with and without the use of prehydrolysis and with different injection rates. The results show that 1) at the same injection rate, the content of calcium carbonate in the prehydrolysis samples after 12 injections was 66.1% higher than that in the samples without prehydrolysis. 2) When using prehydrolysis, the calcium carbonate content as a function of the injection rate decreased in the following order: 10 mL/min >15 mL/min >7.5 mL/min. The highest amount of calcium carbonate was generated at an injection rate of 10 mL/min and was mainly distributed on the surface. The calcium carbonate generated with an injection rate of 15 mL/min was uniformly distributed in the sand. These results indicate that the method could improve the efficiency of calcium carbonate generation and distribution uniformity, and could also be applied to form a hard crust on the surface of sandy soil or for reinforcing sandy soil by multiple injections

Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning

Learning-based approaches have achieved remarkable performance in the domain of autonomous driving. Leveraging the impressive ability of neural networks and large amounts of human driving data, complex patterns and rules of driving behavior can be encoded as a model to benefit the autonomous driving system. Besides, an increasing number of data-driven works have been studied in the decision-making and motion planning module. However, the reliability and the stability of the neural network is still full of uncertainty. In this paper, we introduce a hierarchical planning architecture including a high-level grid-based behavior planner and a low-level trajectory planner, which is highly interpretable and controllable. As the high-level planner is responsible for finding a consistent route, the low-level planner generates a feasible trajectory. We evaluate our method both in closed-loop simulation and real world driving, and demonstrate the neural network planner has outstanding performance in complex urban autonomous driving scenarios.Comment: 6 pages, 8 figures, accepted by IROS202

Identification and validation of NAD+ metabolism-related biomarkers in patients with diabetic peripheral neuropathy

BackgroundThe mechanism of Nicotinamide Adenine Dinucleotide (NAD+) metabolism-related genes (NMRGs) in diabetic peripheral neuropathy (DPN) is unclear. This study aimed to find new NMRGs biomarkers in DPN.MethodsDPN related datasets GSE95849 and GSE185011 were acquired from the Gene Expression Omnibus (GEO) database. 51 NMRGs were collected from a previous article. To explore NMRGs expression in DPN and control samples, differential expression analysis was completed in GSE95849 to obtain differentially expressed genes (DEGs), and the intersection of DEGs and NMRGs was regarded as DE-NMRGs. Next, a protein-protein interaction (PPI) network based on DE-NMRGs was constructed and biomarkers were screened by eight algorithms. Additionally, Gene Set Enrichment Analysis (GSEA) enrichment analysis was completed, biomarker-based column line graphs were constructed, lncRNA-miRNA-mRNA and competing endogenouse (ce) RNA networks were constructed, and drug prediction was completed. Finally, biomarkers expression validation was completed in GSE95849 and GSE185011.Results5217 DEGs were obtained from GSE95849 and 21 overlapping genes of DEGs and NMRGs were DE-NMRGs. Functional enrichment analysis revealed that DE-NMRGs were associated with glycosyl compound metabolic process. The PPI network contained 93 protein-interaction pairs and 21 nodes, with strong interactions between NMNAT1 and NAMPT, NADK and NMNAT3, ENPP3 and NUDT12 as biomarkers based on 8 algorithms. Expression validation suggested that ENPP3 and NUDT12 were upregulated in DPN samples (P < 0.05). Moreover, an alignment diagram with good diagnostic efficacy based on ENPP3 and NUDT12 were identified was constructed. GSEA suggested that ENPP3 was enriched in Toll like receptor (TLR) pathway, NUDT12 was enriched in maturity onset diabetes of the young and insulin pathway. Furthermore, 18 potential miRNAs and 36 Transcription factors (TFs) were predicted and the miRNA-mRNA-TF networks were constructed, suggesting that ENPP3 might regulate hsa-miR-34a-5p by affecting MYNN. The ceRNA network suggested that XLOC_013024 might regulate hsa-let-7b-5p by affecting NUDT12. 15 drugs were predicted, with 8 drugs affecting NUDT12 such as resveratrol, and 13 drugs affecting ENPP3 such as troglitazone.ConclusionENPP3 and NUDT12 might play key roles in DPN, which provides reference for further research on DPN

System-level biological effects of extremely low-frequency electromagnetic fields: an in vivo experimental review

During the past decades, the potential effects of extremely low-frequency electromagnetic fields (ELF-EMFs) on human health have gained great interest all around the world. Though the International Commission on Non-Ionizing Radiation Protection recommended a 100 μT, and then a 200 μT magnetic field limit, the long-term effects of ELF-EMFs on organisms and systems need to be further investigated. It was reported that both electrotherapy and possible effects on human health could be induced under ELF-EM radiation with varied EM frequencies and fields. This present article intends to systematically review the in vivo experimental outcome and the corresponding mechanisms to shed some light on the safety considerations of ELF-EMFs. This will further advance the subsequent application of electrotherapy in human health

A Ga-Sn Liquid Metal Mediated Structural Cathode for Li-O2 Batteries

One of the recent challenges in Li–O2 battery technology is the cycle life, which can be severely shortened by cathode passivation induced by discharge product accumulation; this can be eliminated by reducing the amount of discharge products. Herein, we report a feasibility study on the development of a Ga–Sn liquid metal (LM)-functionalized multiwalled carbon nanotubes (MWNTs) cathode. In a comparison of MWNT, LM, m-LM/MWNT (pre-mixed LM and MWNTs), and LM/MWNT (LM-modified MWNTs) cathodes, morphology analysis showed that small Li2O2 flakes rather than large crystals grow on the conductive Ga–Sn LM and MWNTs of the LM/MWNT cathode only. The decomposition of the flaky Li2O2 on the LM/MWNT cathode occurred at lower charge overpotentials, resulting in low polarization; thus, the cathode passivation and the consumption of the Li anode were both alleviated during the cyclic process. The LM/MWNT cathode significantly improved the cycle life, rate performance, and ultimate capacity of Li–O2 batteries