In order to improve the convergence time and stabilization accuracy of the real-time state estimation of the power batteries for electric vehicles, a fuzzy unscented Kalman filtering algorithm (F-UKF) of a new type is proposed in this paper, with an improved second-order resistor-capacitor (RC) equivalent circuit model established and an online parameter identification used by Bayes. Ohmic resistance is treated as a battery state of health (SOH) characteristic parameter, F-UKF algorithms are used for the joint estimation of battery state of charge (SOC) and SOH. The experimental data obtained from the ITS5300-based battery test platform are adopted for the simulation verification under discharge conditions with constant-current pulses and urban dynamometer driving schedule (UDDS) conditions in the MATLAB environment. The experimental results show that the F-UKF algorithm is insensitive to the initial value of the SOC under discharge conditions with constant-current pulses, and the SOC and SOH estimation accuracy under UDDS conditions reaches 1.76% and 1.61%, respectively, with the corresponding convergence time of 120 and 140 s, which proves the superiority of the joint estimation algorithm.

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Background: The increase in atmospheric CO 2 is causing a number of changes in plant growth such as increases in leaf area and number, branching, plant size and biomass, and growth rate. Despite the importance of stomatal responses to CO 2 , little is known about the genetic and molecular mechanisms that mediate stomatal development and movement in response to CO 2 levels. Deciphering the mechanisms that sense changes in CO 2 and/or HCO 3 − concentration is critical for unraveling the role of CO 2 in stomatal development movement. In Arabidopsis, CO 2-induced stomatal closure is strongly Ca 2+-dependent. To further dissect this signaling pathway and identify new components in the CO 2 response pathway, we recorded [Ca 2+ ] cyt changes in mutagenized Arabidopsis leaves and screened for mutants with abnormal guard cell behavior in response to CO 2 /HCO 3 −. Results: We observed that 1 mM HCO 3 − induces [Ca 2+ ] cys transient changes in guard cells and stomatal closure both in light and darkness. The changes in [Ca 2+ ] cys induced by HCO 3 − could be detected by an aequorin-based calcium imaging system. Using this system, we identified a number of Arabidopsis mutants defective in both [Ca 2+ ] cyt changes and the stomatal response to CO 2 /HCO 3 −. Conclusions: We provide a sensitive method for isolating stomatal CO 2 /HCO 3 − response genes that function early in stomatal closure and that have a role in regulating [Ca 2+ ] cyt. This method will be helpful in elucidating the Ca 2+-dependent regulation of guard cell behavior in response to CO 2 /HCO 3 − .

IMS Learning Design (LD) has emerged as one of the most significant developments in education technology recently. As focusing on learning processes and activities in E-learning, LD can not only help us to understand the application of ICT into traditional school education better, but also become a effective way to involve the way of ICT in education. This paper introduced IMS learning design first, and then analyzed the feasibility of integration. At last, a case was analyzed to explore the impact of LD on the way of ICT in education.

Background: This study sought to identify the downstream target genes of enolase 1 (ENO1), clarify the role of ENO1 in gastric cancer (GC), and provide novel insights into the regulatory mechanisms of ENO1 in the occurrence and development of GC.Methods: We performed RNA-immunoprecipitation sequencing in MKN-45 cells to study the types and abundance of pre-messenger RNA (mRNA)/mRNA bound by ENO1, the binding sites and motifs, the relationship between ENO1 binding and its regulation of transcription level, and alternative splicing level by combining with RNA-sequencing (RNA-seq) data to further clarify the role of ENO1 in GC.Results: We found that ENO1 stabilized the expression of SRY-box transcription factor 9 (SOX9), vascular endothelial growth factor A (VEGFA), G protein-coupled receptor class C group 5 member A (GPRC5A), and myeloid cell leukemia-1 (MCL1) by binding to their mRNA, which increased the growth of GC. In addition, ENO1 interacted with some other long non-coding RNAs (lncRNAs) or small-molecule kinases, such as NEAT1, LINC00511, CD44, and pyruvate kinase M2 (PKM2), to regulate their expression to affect cell proliferation, migration, and apoptosis.Conclusions: ENO1 may play a role in GC by binding to and regulating GC-related genes. Our findings extend understandings of its mechanism as a clinical therapeutic target.