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Recently, supercapacitors (SCs) have emerged as one of the most promising energy storage devices, which can be attributed to their exceptional power density, rapid charge–discharge rate, and superior cycling stability. Despite the progress made in the signal metal oxide of SCs, several challenges still need to be addressed, including the poor electrical conductivity, unsatisfactory cyclic stability, and low energy density. It is crucial to develop innovative composite materials with synergistic effects to address these issues. In this study, the cobalt oxide and Co3O4@NiCo2O4 composite were successfully synthesized on Ni foams by a hydrothermal method. Composite electrodes featured by the hierarchical core–shell structures were identified as an effective approach for improving the electrochemical performance of SCs. Noteworthily, the as-fabricated core–shell structures demonstrated excellent specific capacitance of 1514 F g−1 at a current density of 1 A g−1, a stable operating voltage of 0–0.5 V and outstanding cycling stability (with almost no attenuation after 2000 cycles at a charge–discharge current density of 10 A g−1). The enhanced electrochemical behavior can be attributed to the synergistic effect between two electrode active materials and the presence of more electron and ion transport pathways. The as-prepared composite electrodes can be considered as the potential electrode materials for energy storage applications. [ABSTRACT FROM AUTHOR]

Nitric oxide (NO), a gaseous neurotransmitter, has been implicated in the pathogenesis of schizophrenia. Accordingly, several polymorphisms of the gene that codes for the main NO-producing enzyme, the nitric oxide synthase 1 (NOS1), have been found to convey a risk for schizophrenia. This study examined the role of NOS1 gene polymorphisms in cognitive functions and related neural mechanism. First, with a sample of 580 schizophrenia patients and 720 healthy controls, we found that rs3782206 genotype had main effects on the 1-back task (P=0.005), the 2-back task (P=0.049), the AY condition of the dot-pattern expectancy (DPX) task (P=0.001), and the conflict effect of the attention network (ANT) test (P

Kiwifruit has a high decay rate, in part because quality changes during storage cannot be easily monitored in real time. In order to better monitor the shelf life of kiwifruit and understand the quality changing process during storage, internal quality indexes such as hardness, respiratory intensity and TSS(Total Soluble Solid) were considered into the prediction models. The prediction models were constructed based on BPNN (Back Propagation Neural Network), Random Forest (RF) and XGBoost (eXtreme Gradient Boosting) respectively. And transfer learning algorithm was used to construct the quality prediction models with BPNN, RF, and XGBoost algorithms as the base learner. In the experiments, sample data were augmented by adding Gaussian noise, which effectively prevented the model from over-fitting. The experimental results showed that the prediction accuracy of each index based on transfer learning was better than that of individual BPNN, RF and XGBoost. Moreover, the average prediction accuracy of the models based on transfer learning was 96.2%, and that of respiratory intensity was as high as 99.4%. Therefore transfer learning can be used to effectively analyze and predict changes of kiwifruit quality indexes during storage. [ABSTRACT FROM AUTHOR]

The novel design of carbon materials with stable nanoarchitecture and optimized electrical properties featuring simultaneous intercalation of lithium ions (Li+) and sodium ions (Na+) is of great significance for the superb lithium–sodium storage capacities. Biomass‐derived carbon materials with affluent porosity have been widely studied as anodes for lithium‐ion batteries (LIBs) and sodium‐ion batteries (SIBs). However, it remains unexplored to further enhance the stability and utilization of the porous carbon skeleton during cycles. Here, a lotus stems derived porous carbon (LPC) with graphene quantum dots (GQDs) and intrinsic carbon nanowires framework (CNF) is successfully fabricated by a self‐template method. The LPC anodes show remarkable Li+ and Na+ storage performance with ultrahigh capacity (738 mA h g−1 for LIBs and 460 mA h g−1 for SIBs at 0.2 C after 300 cycles, 1C≈372 mA h g−1) and excellent long‐term stability. Structural analysis indicates that the CNFs‐supported porous structure and internal GQDs with excellent electrical conductivity contribute significantly to the dominant capacitive storage mechanism in LPC. This work provides new perspectives for developing advanced carbon‐based materials for multifunctional batteries with improved stability and utilization of porous carbon frameworks during cycles. [ABSTRACT FROM AUTHOR]

The SNP rs2958182 was reported to be significantly associated with schizophrenia (SCZ) in Han Chinese. This study examined this SNP's associations with cognitive functions in 580 SCZ patients and 498 controls. Cognitive functions were assessed using the Wechsler Adult Intelligence Scale-Revised (WAIS-RC), the Attention Network Task (ANT), the Stroop task, the dot pattern expectancy (DPX), task and the N-back working memory task. Results showed significant or marginally significant interaction effects between genotype and diagnosis status on IQ (P=0.011) and attention-related tasks (ie, the forward digit span of WAIS-RC, P=0.005; the ANT conflict effect; P=0.020, and its ratios over mean reaction time (RT), P=0.036; the Stroop conflict effect, P=0.032, and its ratios over mean RT, P=0.062; and the DPX task's error rate under the BX condition, P0.05). Further analysis of the significant genotype-by-diagnosis interactions showed that the risk (T) allele was associated with better performance on cognitive tasks in patients but with worse performance in controls. These results seem to indicate that the association between this SNP and selected cognitive functions may be of an inverted U-shaped pattern. Future research is needed to replicate these results and to explore the biochemical mechanisms behind this association.

Comprehensive Summary: Inverted perovskite solar cells (PerSCs) are a highly promising candidate in the photovoltaic field due to their low‐temperature fabrication process, negligible hysteresis, and easy integration with Si‐based solar cells. A cathode interlayer (CIL) is necessary in the development of inverted devices to reduce the trap density and energy barrier between the electron transport layer (ETL) and the electrode. However, most CILs are highly thickness‐sensitive due to low conductivity and poor film‐forming. In this study, we report on a self‐doping perylene imide‐based ionene polymer (PNPDIN) used as CIL material to modify electrode in inverted PerSCs. PNPDIN exhibits high conductivity and a good solubility in polar solvent, which results in an improved power conversion efficiency (PCE) from 10.05% (device without a CIL) to 16.97%. When the blend of PNPDIN and Bphen was used as a mixed CIL, the PCE of PerSCs can be further increased to 21.28% owing to the excellent morphology and matched energy level. More importantly, the PCE of the device is highly tolerant to the thickness of the mixed CIL, which benefited from the high conductivity of PNPDIN. This development is expected to provide an excellent mixed CIL material for roll‐to‐roll processing efficient and stable inverted PerSCs. [ABSTRACT FROM AUTHOR]