A 3D hierarchical meso‐ and macroporous Na3V2(PO4)3‐based hybrid cathode with connected Na ion/electron pathways is developed for ultra‐fast charge and discharge sodium‐ion batteries. It delivers an ...excellent rate capability (e.g., 86 mA h g−1 at 100 C) and outstanding cycling stability (e.g., 64% retention after 10 000 cycles at 100 C), indicating its superiority in practical applications.
Producing indices composed of multiple input variables has been embedded in some data processing and analytical methods. We aim to test the feasibility of creating data-driven indices by aggregating ...input variables according to principal component analysis (PCA) loadings. To validate the significance of both the theory-based and data-driven indices, we propose principles to review innovative indices. We generated weighted indices with the variables obtained in the first years of the two-year panels in the Medical Expenditure Panel Survey initiated between 1996 and 2011. Variables were weighted according to PCA loadings and summed. The statistical significance and residual deviance of each index to predict mortality in the second years was extracted from the results of discrete-time survival analyses. There were 237,832 surviving the first years of panels, represented 4.5 billion civilians in the United States, of which 0.62% (95% CI = 0.58% to 0.66%) died in the second years of the panels. Of all 134,689 weighted indices, there were 40,803 significantly predicting mortality in the second years with or without the adjustment of age, sex and races. The significant indices in the both models could at most lead to 10,200 years of academic tenure for individual researchers publishing four indices per year or 618.2 years of publishing for journals with annual volume of 66 articles. In conclusion, if aggregating information based on PCA loadings, there can be a large number of significant innovative indices composing input variables of various predictive powers. To justify the large quantities of innovative indices, we propose a reporting and review framework for novel indices based on the objectives to create indices, variable weighting, related outcomes and database characteristics. The indices selected by this framework could lead to a new genre of publications focusing on meaningful aggregation of information.
Although Zn metal has been regarded as the most promising anode for aqueous batteries, it persistently suffers from serious side reactions and dendrite growth in mild electrolyte. Spontaneous Zn ...corrosion and hydrogen evolution damage the shelf life and calendar life of Zn‐based batteries, severely affecting their industrial applications. Herein, a robust and homogeneous ZnS interphase is built in situ on the Zn surface by a vapor–solid strategy to enhance Zn reversibility. The thickness of the ZnS film is controlled via the treatment temperature, and the performance of the protected Zn electrode is optimized. The dense ZnS artificial layer obtained at 350 °C not only suppresses Zn corrosion by forming a physical barrier on the Zn surface, but also inhibits dendrite growth via guiding the Zn plating/stripping underneath the artificial layer. Accordingly, a side reaction‐free and dendrite‐free Zn electrode is developed, the effectiveness of which is also convincing in a MnO2/ZnS@Zn full‐cell with 87.6% capacity retention after 2500 cycles.
Based on the sulfur phase diagram, a dense and robust artificial layer of ZnS is introduced on the surface of Zn metal via an in situ vapor–solid strategy. This ZnS protective layer not only suppresses side reactions by blocking water from the surface of such a Zn electrode in a Zn‐ion battery, but also inhibits Zn dendrite growth by guiding homogenous Zn plating/stripping.
Handwritten Chinese text recognition based on over-segmentation and path search integrating multiple contexts has been demonstrated successful, wherein the language model (LM) and character shape ...models play important roles. Although back-off N-gram LMs (BLMs) have been used dominantly for decades, they suffer from the data sparseness problem, especially for high-order LMs. Recently, neural network LMs (NNLMs) have been applied to handwriting recognition with superiority to BLMs. With the aim of improving Chinese handwriting recognition, this paper evaluates the effects of two types of character-level NNLMs, namely, feedforward neural network LMs (FNNLMs) and recurrent neural network LMs (RNNLMs). Both FNNLMs and RNNLMs are also combined with BLMs to construct hybrid LMs. For fair comparison with BLMs and a state-of-the-art system, we evaluate in a system with the same character over-segmentation and classification techniques as before, and compare various LMs using a small text corpus used before. Experimental results on the Chinese handwriting database CASIA-HWDB validate that NNLMs improve the recognition performance, and hybrid RNNLMs outperform the other LMs. To report a new benchmark, we also evaluate selected LMs on a large corpus, and replace the baseline character classifier, over-segmentation, and geometric context models with convolutional neural network (CNN) based models. The performance on both the CASIA-HWDB and the ICDAR-2013 competition dataset are improved significantly. On the CASIA-HWDB test set, the character-level accurate rate (AR) and correct rate (CR) achieve 95.88% and 95.95%, respectively.
•We evaluate comprehensively neural network language models (NNLMs) and hybrid NNLMs in handwritten Chinese text recognition.•We apply CNNs to over-segmentation and geometric context modeling in addition to character recognition.•By training NNLMs on large corpus and integrating CNN shape models, we achieve new state-of-the-art performance on standard datasets.•We analyze the upper bound of performance of the text recognition system by calculating the lattice error rate.
In order to increase the number of general concepts of safety and security science which can be used to represent the comprehensive safety and security level of a system, a compound word of safety ...and security civilization (SSC) is proposed, based on the connotation and attributes of words of civilization, safety and security. Then, the narrow and generalized definitions and their connotations of SSC are given respectively. Further analysis shows that properties of SSC have implications of comprehensiveness, generality, abstractness and progressiveness. On this basis, various classifications of SSC are made from different perspectives and dimensions, and the similarities and differences between SSC and safety culture are compared. SSC is an advanced part of generalized safety culture and can be used to guide the construction of safety culture. The research shows that the new concept of SSC can be widely used to express the whole safety and security level at a certain time and space, and has important value in practical applications.
A new growing method for simplex-based endmember extraction algorithms (EEAs), called simplex growing algorithm (SGA), is presented in this paper. It is a sequential algorithm to find a simplex with ...the maximum volume every time a new vertex is added. In order to terminate this algorithm a recently developed concept, virtual dimensionality (VD), is implemented as a stopping rule to determine the number of vertices required for the algorithm to generate. The SGA improves one commonly used EEA, the N-finder algorithm (N-FINDR) developed by Winter, by including a process of growing simplexes one vertex at a time until it reaches a desired number of vertices estimated by the VD, which results in a tremendous reduction of computational complexity. Additionally, it also judiciously selects an appropriate initial vector to avoid a dilemma caused by the use of random vectors as its initial condition in the N-FINDR where the N-FINDR generally produces different sets of final endmembers if different sets of randomly generated initial endmembers are used. In order to demonstrate the performance of the proposed SGA, the N-FINDR and two other EEAs, pixel purity index, and vertex component analysis are used for comparison
Enabling real‐time monitoring and control of the biomanufacturing processes through product quality insights continues to be an area of focus in the biopharmaceutical industry. The goal is to ...manufacture products with the desired quality attributes. To realize this rigorous attribute‐focused Quality by Design approach, it is critical to support the development of processes that consistently deliver high‐quality products and facilitate product commercialization. Time delays associated with offline analytical testing can limit the speed of process development. Thus, developing and deploying analytical technology is necessary to accelerate process development. In this study, we have developed the micro sequential injection process analyzer and the automatic assay preparation platform system. These innovations address the unmet need for an automatic, online, real‐time sample acquisition and preparation platform system for in‐process monitoring, control, and release of biopharmaceuticals. These systems can also be deployed in laboratory areas as an offline analytical system and on the manufacturing floor to enable rapid testing and release of products manufactured in a good manufacturing practice environment.
Self‐supported nanotube arrays of sulfur‐doped TiO2 on metal substrates are fabricated using electrochemical anodization and subsequent sulfidation. The nanotube arrays can serve as an efficient ...anode for sodium storage, enabling ultrastable cycling (retaining 91% of the 2nd capacity up to 4400 cycles) and robust rate capability (167 mA h g−1 at 3350 mA g−1), remarkably outperforming any other reported TiO2‐based electrodes.
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