3D hierarchical heterostructure NiFe LDH@NiCoP/NF electrodes are prepared successfully on nickel foam with special interface engineering and synergistic effects. This research finds that the as-prepared NiFe LDH@NiCoP/NF electrodes have a more sophisticated inner structure and intensive interface than a simple physical mixture. The NiFe LDH@NiCoP/NF electrodes require an overpotential as low as 120 and 220 mV to deliver 10 mA cm −2 for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in 1 m KOH, respectively. Tafel and electrochemical impedance spectroscopy further reveal a favorable kinetic during electrolysis. Specifically, the NiFe LDH@NiCoP/NF electrodes are simultaneously used as cathode and anode for overall water splitting, which requires a cell voltage of 1.57 V at 10 mA cm −2 . Furthermore, the synergistic effect of the heterostructure improves the structural stability and promotes the generation of active phases during HER and OER, resulting in excellent stability over 100 h of continuous operation. Moreover, the strategy and interface engineering of the introduced heterostructure can also be used to prepare other bifunctional and cost-efficient electrocatalysts for various applications.

The study of algorithms to automatically answer visual questions currently is motivated by visual question answering (VQA) datasets constructed in artificial VQA settings. We propose VizWiz, the first goal-oriented VQA dataset arising from a natural VQA setting. VizWiz consists of over 31,000 visual questions originating from blind people who each took a picture using a mobile phone and recorded a spoken question about it, together with 10 crowdsourced answers per visual question. VizWiz differs from the many existing VQA datasets because (1) images are captured by blind photographers and so are often poor quality, (2) questions are spoken and so are more conversational, and (3) often visual questions cannot be answered. Evaluation of modern algorithms for answering visual questions and deciding if a visual question is answerable reveals that VizWiz is a challenging dataset. We introduce this dataset to encourage a larger community to develop more generalized algorithms that can assist blind people.

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