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For system identification under impulsive-noise environments, the gradient-based generalized maximum correntropy criterion (GB-GMCC) algorithm can achieve a desirable filtering performance. However, the gradient method only uses the information of the first-order derivative, and the corresponding stagnation point of the method can be a maximum point, a minimum point or a saddle point, and thus the gradient method may not always be a good selection. Furthermore, GB-GMCC merely uses the current input signal to update the weight vector; facing the highly correlated input signal, the convergence rate of GB-GMCC will be dramatically damaged. To overcome these problems, based on the Newton recursion method and the data-reusing method, this paper proposes a robust adaptive filtering algorithm, which is called the Newton recursion-based data-reusing GMCC (NR-DR-GMCC). On the one hand, based on the Newton recursion method, NR-DR-GMCC can use the information of the second-order derivative to update the weight vector. On the other hand, by using the data-reusing method, our proposal uses the information of the latest M input vectors to improve the convergence performance of GB-GMCC. In addition, to further enhance the filtering performance of NR-DR-GMCC, a random strategy can be used to extract more information from the past M input vectors, and thus we obtain an enhanced NR-DR-GMCC algorithm, which is called the Newton recursion-based random data-reusing GMCC (NR-RDR-GMCC) algorithm. Compared with existing algorithms, simulation results under system identification and acoustic echo cancellation are conducted and validate that NR-RDR-GMCC can provide a better filtering performance in terms of filtering accuracy and convergence rate. [ABSTRACT FROM AUTHOR]

The electrification of road freight vehicles is an important approach to reduce air pollution and carbon emissions from the trucking industry. In its current stage, electric truck adoption in China is concentrated in a few cities that provide strong support for the technology. This article reviews the promotion policies adopted by ten major Chinese cities pioneering electric logistics vehicle (ELV) adoption. These policies include operational subsidies, road access privileges, subsidies for charger installation and operation, and other incentives for ELV charging and parking. As local purchasing subsidies for ELVs have been phased down, the operational subsidies and road access privileges provide the main impetus for urban ELV adoption. In addition, a holistic regional assessment identifying high‐potential provinces for future electric truck deployment in the country is described. The assessment takes into account eight indicators under three relevant categories of considerations (i.e., the unique attributes of the technology, where it is most needed, and where it has the most support) and shows that provinces favorable for electric truck deployments are concentrated in the east and south of China. Fleet operators, policymakers, and other industry stakeholders should consider prioritizing electric truck deployments in these regions. Some of these eight indicators are difficult or impossible to change, and policymakers looking to encourage more logistics vehicle electrification must therefore focus on those policy factors that can be changed. Policy recommendations are then formulated in light of the city‐level policy analysis as well as the regional assessment, which is expected to help inform future policymaking and speed ELV adoption in cities across the high‐potential regions and even nationwide. This article is categorized under:Cities and Transportation > Electric MobilityPolicy and Economics > Regional and International Strategies [ABSTRACT FROM AUTHOR]

To enhance the stability and robustness of the DC converter, a two-dimensional (2D) iterative learning control method suitable for the Buck converter is proposed. This control method is derived through a continuous-discrete model. Combining the error dynamics equation and the iterative learning method (ILM) described with Roesser theory, effective learning rules and sufficient conditions for convergence are obtained. By contrast with the iterative learning algorithm of the conventional Buck converter, this algorithm clarifies the learning gain, deeply learns the structure and parameters of the converter, and obtains an accurate learning dynamics model. Moreover, numerical simulations of the Buck converter with specific circuit parameters are also conducted. The simulation results demonstrate that the control learning rules are less restrictive with a swift transient response, which are robust without complex feedback compensation circuits. Thereby, it elucidates a new approach to the application of the Buck converter. [ABSTRACT FROM AUTHOR]

The present study aimed to examine microRNA (miR)-940 expression in esophageal squamous cell carcinoma (ESCC) tissues and cells, analyze its association with the clinicopathological features and prognosis of patients, and explore the potential underlying mechanisms. miR-940 expression in ESCC cell lines and a normal esophageal cell line was detected using reverse transcription-quantitative (RT-q)PCR. Furthermore, 210 resected ESCC tissue and para-carcinoma tissue specimens were collected, and miR-940 expression in those tissues was detected by RT-qPCR. In addition, the association of miR-940 with the clinicopathological features and prognosis of patients was analyzed. In an in vitro experiment, miR-940 mimics were transduced into ESCC cells by the liposome method. An MTT assay was used to detect the effect of miR-940 on the viability of ESCC cells. The influence of miR-940 on the cell cycle and apoptotic rate of ESCC cells was detected by flow cytometry. The present results indicated that the expression levels of miR-940 in human ESCC tissues and cell lines were markedly downregulated, and that low expression of miR-940 in ESCC tissues was significantly associated with a poor degree of differentiation, positive lymph node metastasis and advanced clinical stage. Kaplan-Meier survival analysis suggested that low miR-940 expression was associated with poor prognosis. Cox regression analysis revealed that lymph node metastasis, clinical stage and miR-940 expression were independent risk factors affecting the prognosis of patients. Overexpression of miR-940 in ESCC cells markedly reduced the cell viability, blocked the cell cycle at G0/G1 phase and promoted cell apoptosis. These results suggest that miR-940 is downregulated in ESCC, which is linked to the occurrence and progression of ESCC. Conversely, overexpression of miR-940 reduced the cell viability and promoted apoptosis of ESCC cells. Therefore, miR-940 may be a promising novel prognostic marker and anti-cancer target in ESCC. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate the expression of microRNA-495 (miR-495) in non-small cell lung cancer (NSCLC) tissues and cells, as well as its function on the proliferation of lung cancer cells. The expression of miR-495 in 122 pairs of NSCLC tissues and matched paracarcinoma tissues, as well as in human lung cancer cell lines (A549, H460, H1650, H520 and SK-MES-1) and the normal human pulmonary bronchial epithelial cell line 16HBE was determined using reverse transcription quantitative polymerase chain reaction (RT-qPCR). As predicted by bioinformatics analysis, high mobility group A2 (HMGA2) may be a potential target gene of miR-495. In addition, the regulatory function of miR-495 on its target gene HMGA2 was evaluated using a dual-luciferase reporter assay, RT-qPCR and western blotting. Furthermore, the effect of miR-495 on the proliferation of A549 lung cancer cells was investigated using a Cell Counting Kit-8 (CCK-8) assay. The results demonstrated that the expression of miR-495 in NSCLC tissues and cells was significantly downregulated compared with the control. In addition, downregulated expression of miR-495 was associated with tumor differentiation, lymph node metastasis and tumor, node and metastasis staging. Additionally, a dual-luciferase reporter assay revealed that miR-495 could directly associated with the 3′-untranslated region of HMGA2. Upregulated expression of miR-495 significantly downregulated the mRNA and protein expression levels of HMGA2 in A549 cells. Furthermore, the results of CCK-8 assay revealed that upregulated expression of miR-495 significantly suppressed the proliferation of A549 cells; HMGA2 overexpression reversed this inhibition. In summary, the findings of the present study demonstrated that miR-495 was downregulated in NSCLC tissues and cells. In addition, miR-495 suppressed the proliferation of lung cancer cells by directly targeting HMGA2. [ABSTRACT FROM AUTHOR]

Developing cathode materials with high specific capability and excellent electrochemical performance is crucial for the advancement of aluminum-ion batteries, which leverage the high theoretical energy density of aluminum metal anodes. In this paper, we investigated the interaction ofAlCl4cluster and Al atom with AlN (-100) and (001) monolayer using density functional theory to assess the applicability of AlN as cathode material for aluminum-ion batteries. The results show that the AlN (001) monolayer is the most effective for adsorbing and accommodatingAlCl4clusters. Moreover, the AlN (001) monolayer maintains metallic behavior at different concentrations of theAlCl4cluster, laying the foundation for its battery application. The theoretical storage capacity of theAlCl4cluster is 105.93mAhg-1,which exceeds that of the Al/graphite battery. The formation energy ofAlCl4-intercalated AlN compounds is -2.74 eV, and the intercalant gallery height is moderate. Furthermore, the diffusion barrier of 0.19 eV forAlCl4cluster between the AlN (001) monolayer provides high rate capability. The results indicate that AlN monolayer may be a potential cathode material for aluminum-ion batteries., (© 2023 IOP Publishing Ltd.)