Wearable sensors based on solid-contact ion-selective electrodes (SC-ISEs) are currently attracting intensive attention in monitoring human health conditions through real-time and non-invasive analysis of ions in biological fluids. SC-ISEs have gone through a revolution with improvements in potential stability and reproducibility. The introduction of new transducing materials, the understanding of theoretical potentiometric responses, and wearable applications greatly facilitate SC-ISEs. We review recent advances in SC-ISEs including the response mechanism (redox capacitance and electric-double-layer capacitance mechanisms) and crucial solid transducer materials (conducting polymers, carbon and other nanomaterials) and applications in wearable sensors. At the end of the review we illustrate the existing challenges and prospects for future SC-ISEs. We expect this review to provide readers with a general picture of SC-ISEs and appeal to further establishing protocols for evaluating SC-ISEs and accelerating commercial wearable sensors for clinical diagnosis and family practice.

In this study, ultra-thick Li-ion battery electrodes were prepared using 450, 800 and 1200 mm cell size of metal foam current collectors for large scale energy storage. The thickness and the mass loading of the electrodes were in the range of 300-600 mm and 30-60 mg cm À2 respectively, which were much thicker and heavier comparing with the commercial electrodes. The cell using 1200 mm cell size of metal foam exhibited the highest capacity (8.8 mA h cm À2 ) at lower current density (1 mA cm À2 ) owing to the highest mass loading of the active material. However, the deterioration of capacity and the voltage drop in plateau region were relatively much more with the increase of current density so that the capacity of cell using 800 mm cell size of metal foam becomes the highest. AC impedance analysis showed that the charge transfer resistance difference between the cells using 450 and 800 mm cell size of metal foams was only 1.5 U cm 2 whereas it was 8 U cm 2 between the cells using 450 and 1200 mm cell size of metal foams. Furthermore, the slope of the straight line scanned at lower frequencies, which has relation with the diffusion limitation of Li was much lower for the cell using 1200 mm cell size of metal foam.Considering both of the cell capacity and rate performance, the cell size of metal foam between 450 and 800 mm is promising for commercial Li-ion batteries. Although the kinetic performance can be improved further by using the smaller cell size of metal foam, the cell capacity could be sacrificed due to the lower mass loading of the active material.

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In this study, a three dimensional NiCrAl alloy foam was used as a current collector for high-power and high-capacity lithium iron phosphate batteries. A charge-discharge test revealed that at a high current rate, the electrode using a metal foam had better power performance and its capacity faded much less than in the case of a conventional foil-type current collector. The cyclic voltammetric analysis showed that the redox reaction occurred much faster in the case of the metal foam than in the case of the foil. The reason for this is that in the case of metal foam, the electrons transfer rapidly at the junction of the metal frame, the active material, and the electrolyte, but, in the case of foil, the electrons transfer relatively slowly between the foil current collector and the electrode surface of the active material. An impedance analysis showed that the charge transfer resistance was much lower for the metal foam than for the foil.

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BackgroundDNA-binding proteins (DBPs) play fundamental roles in many biological processes. Therefore, the developing of effective computational tools for identifying DBPs is becoming highly desirable.ResultsIn this study, we proposed an accurate method for the prediction of DBPs. Firstly, we focused on the challenge of improving DBP prediction accuracy with information solely from the sequence. Secondly, we used multiple informative features to encode the protein. These features included evolutionary conservation profile, secondary structure motifs, and physicochemical properties. Thirdly, we introduced a novel improved Binary Firefly Algorithm (BFA) to remove redundant or noisy features as well as select optimal parameters for the classifier. The experimental results of our predictor on two benchmark datasets outperformed many state-of-the-art predictors, which revealed the effectiveness of our method. The promising prediction performance on a new-compiled independent testing dataset from PDB and a large-scale dataset from UniProt proved the good generalization ability of our method. In addition, the BFA forged in this research would be of great potential in practical applications in optimization fields, especially in feature selection problems.ConclusionsA highly accurate method was proposed for the identification of DBPs. A user-friendly web-server named iDbP (identification of DNA-binding Proteins) was constructed and provided for academic use.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1201-8) contains supplementary material, which is available to authorized users.

Results from the current survey indicate that mental disorders are steadily reported more commonly in rapidly-developing urban China. Several interesting sociodemographic correlates were observed (e.g. male gender and non-immigrant status) that warrant further investigation and could be used to profile persons in need of preventive intervention.