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Statistical learning (SL) is essential in enabling humans to extract probabilistic regularities from the world. The ability to accomplish ultimate learning performance with training (i.e., the potential of learning) has been known to be dissociated with performance improvement per amount of learning time (i.e., the efficiency of learning). Here, we quantified the potential and efficiency of SL separately through mathematical modeling and scrutinized how they were affected by various executive functions. Our results showed that a high potential of SL was associated with poor inhibition and good visuo-spatial working memory, whereas high efficiency of SL was closely related to good inhibition and good set-shifting. We unveiled the distinct characteristics of SL in relation to potential and efficiency and their interaction with executive functions.

Recent studies of lithium–sulfur (Li–S) batteries have identified that a modified separator plays a critical role in challenging the capacity fading and shuttle effect of lithium polysulfides (LiPSs). Herein, we report a polyaniline-encapsulated hollow Co–Fe Prussian blue analogue (CFP@PANI) for separator modification. The open frame-like hollow CFP was synthesized via oriented attachment (OA). To improve the catalytic effect and electrical conductivity, PANI was coated on the synthesized CFP. The resulting CFP@PANI was applied on the conventional polypropylene (PP) separator (CFP@PANI-PP) with vacuum filtration. With a ketjen black/sulfur (KB/S) cathode with 66% of the sulfur load, the CFP@PANI-PP exhibited an initial capacity of 723.1 mAh g–1 at a current density of 1 A g–1. Furthermore, the CFP@PANI-PP showed stable cycling performance with 83.5% capacity retention after 100 cycles at 1 A g–1. During the 100 cycles, each cycle maintained high coulombic efficiency above 99.5%, which indicates that the CFP@PANI-PP could inhibit LiPS migration to the anode side without a Li+ transport disturbance across the separator. Overall, the CFP@PANI-PP efficiently suppressed LiPSs, resulting in enhanced electrochemical performance. The current study provides useful insight into designing a nanostructure for separator modification of Li–S batteries.

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To investigate the effect of long chain branching (LCB) on melt fractures of metallocene-catalyzed linear low-density polyethylene (mLLDPE), we prepared a series of sparsely long-chain-branched mLLDPEs with well-defined degrees of LCB. Gross melt fractures were observed to decrease as the degree of LCB increases. This is in accordance with a prediction based on the observation that LCB enhances chain entanglement and consequently increases the melt strength of a polymer. However, sharkskin melt fracture (SMF) was observed to be more severe with the degree of LCB. There have been debates over the effect of LCB on SMF. According to a well-known mechanism of SMF, SMF is expected to decrease with the degree of LCB. Therefore, the majority of research groups believe that SMF decreases with the degree of LCB. This study clearly shows that the SMF becomes more severe with an increase of the degree of LCB and suggests another possible mechanism for the SMF. V C 2012 Wiley Periodicals, Inc. J Appl Polym Sci 126: E322-E329, 2012