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The thermal management system is one of the important assemblies that ensure the secure operation of electric vehicles (EVs). Using intelligent algorithms to optimize the control strategy of the thermal management system can reduce energy consumption under the premise of effective heat dissipation of EVs. This paper attempts to construct the control strategy of EV thermal management system by coupling the modified genetic algorithm (MGA) and support vector regression (SVR). Firstly, the double-population adaptive mutation method and a novel optimization process are adopted to obtain MGA. Afterward, the performance of MGA is verified by four benchmark functions compared with three typical algorithms, which are genetic algorithm (GA), double-population genetic algorithm (DPGA), and quantum genetic algorithm (QGA). The results demonstrate that the accuracy and stability of MGA are obviously better than the other three algorithms. Secondly, MGA is applied to modify parameters of SVR kernel function, and the accuracy of MGA-SVR algorithm is verified by the Auto-MPG and Computer Hardware data sets. The mean square deviations of the SVR algorithm test set are 0.0186 and 0.0806, respectively, and the mean square deviations of the MGA-SVR algorithm test set are 0.0099 and 0.0054, respectively, which fully shows that MGA-SVR have more accurate forecasting capabilities. Finally, the thermal management system model of EV is built by the one-dimensional simulation software KULI. Under the Chinese working condition, fan speed which meets the cooling requirements of the motor and controller is obtained from the KULI model, and the database is constructed. Then, MGA-SVR is trained by database and employed to predict fan speed under the Chinese working condition and obtain control strategy of the thermal management system. Compared with traditional control strategy, the thermal management system based on MGA-SVR control strategy can not only meet the radiating requirements, but also effectively reduce the power consumption of fans. [ABSTRACT FROM AUTHOR]

In this work, we designed and synthesized a novel naphthalenediimide-based n-type conjugated polymer PNDICI, which bears asymmetric backbone containing a 3-chlorothiophene unit. The asymmetric structure associated with steric effects of the chlorine atom imparts remarkable solubility to PNDICI in various organic solvents, enabling the fabrication of all-polymer solar cells (all-PSCs) by using an environmentally friendly solvent of d-limonene. Combined with a novel pyrrolo[3,4-f]benzotriazole-5,7(6H)-dione based p-type conjugated polymer P2F-Si with deep highest occupied molecular orbital energy level, the resulting d-limonene-processed all-PSCs presents an impressively high open-circuit voltage of approaching 1.0 V, corresponding to a very small energy loss of 0.49 eV. Through further morphology optimization by using γ-valerolactone, we demonstrated an impressive device efficiency of 4.2%, which is among the best photovoltaic performance of devices processed using d-limonene and comparable to that processed by conventional solvent, suggesting the great promise of using greener solvent for fabricating high-performance all-PSCs. [ABSTRACT FROM AUTHOR]

Metal–air batteries exhibit high potential for grid-scale energy storage because of their high theoretical energy density, their abundance in the earth’s crust, and their low cost. In these batteries, the oxygen evolution reaction (OER) occurs on the air electrode during charging. This study proposes a method for improving the OER electrode performance. The method involves sequentially depositing a Ni underlayer, Sn whiskers, and a Ni protection layer on the metal mesh. Small and uniform gas bubbles form on the Ni/Sn/Ni mesh, leading to low overpotential and a decrease in the overall resistance of the OER electrode. The results of a simulated life cycle test indicate that the Ni/Sn/Ni mesh has a life cycle longer than 1,300 cycles when it is used as the OER electrode in 6 M KOH. [ABSTRACT FROM AUTHOR]

Abiotic stresses disrupt protein folding and induce endoplasmic reticulum (ER) stress, which in turn activates the unfolded protein response (UPR) to aid in the refolding or degradation of misfolded proteins. The phytohormone ABA regulates many aspects of plant development and plays a central role in the stress response; however, the role of ABA in transducing stress signals to activate the UPR has not been recognized. In this study, a gene encoding the maize ortholog of AtbZIP17, a transmembrane transcription factor functioning as an ER stress transducer, was identified from the MaizeGDB database, and designated ZmbZIP17. ZmbZIP17 was induced by both ABA and ER stress-eliciting agents such as dithiotreitol (DTT) and tunicamycin (TM). Transiently expressed yellow fluorescent protein (YFP)–ZmbZIP17 co-localized with the ER marker HDEL–mCherry under control conditions, but partially translocated into the nucleus upon TM treatment or removal of the transmembrane domain. TM-induced processing of ZmbZIP17 was confirmed by Western blot analysis. When overexpressed in Arabidopsis, ZmbZIP17 triggered ER stress response gene expression and tolerance to DTT and TM, elevated ABA-responsive gene expression and ABA sensitivity both pre- and post-germination. Additionally, ABA was found to induce ER stress response gene expression, alone or synergistically with ZmbZIP17, in the absence of DTT or TM; while ZmbZIP17 was capable of interacting with ABA-responsive cis-elements (ABREs) that exist in promoters of known ABA-responsive genes. Together, our results reveal a direct link between ER stress and ABA signaling pathways involving the ZmbZIP17 transcription factor. [ABSTRACT FROM PUBLISHER]

Functional genomic elements, including transposable elements, small RNAs and non-coding RNAs, are involved in regulation of gene expression in response to plant stress. To identify genomic elements that regulate dehydration and alkaline tolerance in Boea hygrometrica, a resurrection plant that inhabits drought and alkaline Karst areas, a genomic DNA library from B. hygrometrica was constructed and subsequently transformed into Arabidopsis using binary bacterial artificial chromosome (BIBAC) vectors. Transgenic lines were screened under osmotic and alkaline conditions, leading to the identification of Clone L1-4 that conferred osmotic and alkaline tolerance. Sequence analyses revealed that L1-4 contained a 49-kb retroelement fragment from B. hygrometrica, of which only a truncated sequence was present in L1-4 transgenic Arabidopsis plants. Additional subcloning revealed that activity resided in a 2-kb sequence, designated Osmotic and Alkaline Resistance 1 (OAR1). In addition, transgenic Arabidopsis lines carrying an OAR1-homologue also showed similar stress tolerance phenotypes. Physiological and molecular analyses demonstrated that OAR1-transgenic plants exhibited improved photochemical efficiency and membrane integrity and biomarker gene expression under both osmotic and alkaline stresses. Short transcripts that originated from OAR1 were increased under stress conditions in both B. hygrometrica and Arabidopsis carrying OAR1. The relative copy number of OAR1 was stable in transgenic Arabidopsis under stress but increased in B. hygrometrica. Taken together, our results indicated a potential role of OAR1 element in plant tolerance to osmotic and alkaline stresses, and verified the feasibility of the BIBAC transformation technique to identify functional genomic elements from physiological model species. [ABSTRACT FROM AUTHOR]