We provide a critical review on the recent development of flexible lithium‐ion batteries (FLIBs) for flexible electronic devices. The innovative designs of cell configuration for bendable and ...stretchable FLIBs, selection of active materials, and evaluation methods for FLIBs are discussed. The grand challenges for FLIBs are energy density and scale‐up fabrication as demonstrated in the review. Furthermore, the lack of quantitative evaluation methods for FLIBs' performance and nondestructive tools to probe the mechanical degradation may significantly hinder the development of FLIB technologies. Perspectives for future research directions, based on the current state of progress, are discussed.
The development of flexible lithium‐ion batteries for flexible electronic devices is reviewed from the aspects of battery structural design, active materials incorporation, and techniques to evaluate mechanical and electrochemical performance. Future research direction, particularly the need for standardized operando methods to probe the degradation of FLIBs is discussed.
The existing deep learning-based Personal Protective Equipment (PPE) detectors can only detect limited types of PPE and their performance needs to be improved, particularly for their deployment on ...real construction sites. This paper introduces an approach to train and evaluate eight deep learning detectors, for real application purposes, based on You Only Look Once (YOLO) architectures for six classes, including helmets with four colours, person, and vest. Meanwhile, a dedicated high-quality dataset, CHV, consisting of 1330 images, is constructed by considering real construction site background, different gestures, varied angles and distances, and multi PPE classes. The comparison result among the eight models shows that YOLO v5x has the best mAP (86.55%), and YOLO v5s has the fastest speed (52 FPS) on GPU. The detection accuracy of helmet classes on blurred faces decreases by 7%, while there is no effect on other person and vest classes. And the proposed detectors trained on the CHV dataset have a superior performance compared to other deep learning approaches on the same datasets. The novel multiclass CHV dataset is open for public use.
Fine-grained visual recognition is to classify objects with visually similar appearances into subcategories, which has made great progress with the development of deep CNNs. However, handling subtle ...differences between different subcategories still remains a challenge. In this paper, we propose to solve this issue in one unified framework from two aspects, i.e., constructing feature-level interrelationships, and capturing part-level discriminative features. This framework, namely PArt-guided Relational Transformers (PART), is proposed to learn the discriminative part features with an automatic part discovery module, and to explore the intrinsic correlations with a feature transformation module by adapting the Transformer models from the field of natural language processing. The part discovery module efficiently discovers the discriminative regions which are highly-corresponded to the gradient descent procedure. Then the second feature transformation module builds correlations within the global embedding and multiple part embedding, enhancing spatial interactions among semantic pixels. Moreover, our proposed approach does not rely on additional part branches in the inference time and reaches state-of-the-art performance on 3 widely-used fine-grained object recognition benchmarks. Experimental results and explainable visualizations demonstrate the effectiveness of our proposed approach.
With the development of economy, numerous techniques, tools, and concepts have appeared to fit the intensive and competitive market. Especially for some enterprises in retail industry, they face the ...problem of digital transformation, which requires advanced organizational strategies, business analytics technology, dynamic capabilities, value-creating actions to help solve the problem. This paper analyzes the real cases of digital transformation in some Chinese enterprises to show how business intelligence gradually developed into business analysis and how it creates value to the business. Real experience of the author and the research resources of her internship in a consulting company are also shared. Enterprises often use SAP, ERP, IaaS, SaaS, PaaS to build the cloud services and infrastructure of data ware, which are the products of business analytics. The author analyzes how business analytics help enterprises use effective and intelligent analysis on the data and business to improve the performance of the enterprises, which can make the enterprises become competitive and outstanding. In addition, the difference between business intelligence and business analytics, and how the value business analytics creates to the enterprises in theoretical and practical way are introduced. Finally, the author finds the significant of data and analytical tools to the present and future development in different industries, and predicts the general trend that might happen in the future. People can also realize the impact that data brings to their daily life.
Targeted delivery of a nanovaccine loaded with a tumor antigen and adjuvant to the lymph nodes (LNs) is an attractive approach for improving cancer immunotherapy outcomes. However, the application of ...this technique is restricted by the paucity of suitable tumor-associated antigens (TAAs) and the sophisticated technology required to identify tumor neoantigens. Here, we demonstrate that a self-assembling melittin-lipid nanoparticle (α-melittin-NP) that is not loaded with extra tumor antigens promotes whole tumor antigen release in situ and results in the activation of antigen-presenting cells (APCs) in LNs. Compared with free melittin, α-melittin-NPs markedly enhance LN accumulation and activation of APCs, leading to a 3.6-fold increase in antigen-specific CD8
T cell responses. Furthermore, in a bilateral flank B16F10 tumor model, primary and distant tumor growth are significantly inhibited by α-melittin-NPs, with an inhibition rate of 95% and 92%, respectively. Thus, α-melittin-NPs induce a systemic anti-tumor response serving as an effective LN-targeted whole-cell nanovaccine.
Fine-grained object recognition aims to learn effective features that can identify the subtle differences between visually similar objects. Most of the existing works tend to amplify discriminative ...part regions with attention mechanisms. Besides its unstable performance under complex backgrounds, the intrinsic interrelationship between different semantic features is less explored. Toward this end, we propose an effective graph-based relation discovery approach to build a contextual understanding of high-order relationships. In our approach, a high-dimensional feature bank is first formed and jointly regularized with semantic- and positional-aware high-order constraints, endowing rich attributes to feature representations. Second, to overcome the high-dimension curse, we propose a graph-based semantic grouping strategy to embed this high-order tensor bank into a low-dimensional space. Meanwhile, a group-wise learning strategy is proposed to regularize the features focusing on the cluster embedding center. With the collaborative learning of three modules, our module is able to grasp the stronger contextual details of fine-grained objects. Experimental evidence demonstrates our approach achieves new state-of-the-art on 4 widely-used fine-grained object recognition benchmarks.
Circular RNA (circRNA), a novel type of endogenous noncoding RNA (ncRNA), has become a research hotspot in recent years. CircRNAs are abundant and stably exist in creatures, and they are found with ...covalently closed loop structures in which they are quite different from linear RNAs. Nowadays, an increasing number of scientists have demonstrated that circRNAs may have played an essential role in the regulation of gene expression, especially acting as miRNA sponges, and have described the potential mechanisms of several circRNAs in diseases, hinting at their clinical therapeutic values. In this review, the authors summarized the current understandings of the biogenesis and properties of circRNAs and their functions and role as biomarkers in cardiovascular diseases.
There is high demand for techniques to estimate human mental workload during some activities for productivity enhancement or accident prevention. Most studies focus on a single physiological sensing ...modality and use univariate methods to analyse multi-channel electroencephalography (EEG) data. This paper proposes a new framework that relies on the features of hybrid EEG–functional near-infrared spectroscopy (EEG–fNIRS), supported by machine-learning features to deal with multi-level mental workload classification. Furthermore, instead of the well-used univariate power spectral density (PSD) for EEG recording, we propose using bivariate functional brain connectivity (FBC) features in the time and frequency domains of three bands: delta (0.5–4 Hz), theta (4–7 Hz) and alpha (8–15 Hz). With the assistance of the fNIRS oxyhemoglobin and deoxyhemoglobin (HbO and HbR) indicators, the FBC technique significantly improved classification performance at a 77% accuracy for 0-back vs. 2-back and 83% for 0-back vs. 3-back using a public dataset. Moreover, topographic and heat-map visualisation indicated that the distinguishing regions for EEG and fNIRS showed a difference among the 0-back, 2-back and 3-back test results. It was determined that the best region to assist the discrimination of the mental workload for EEG and fNIRS is different. Specifically, the posterior area performed the best for the posterior midline occipital (POz) EEG in the alpha band and fNIRS had superiority in the right frontal region (AF8).
A hydrogen atom transfer (HAT)-initiated Dowd–Beckwith rearrangement reaction was developed, which enables the efficient assembly of diversely functionalized polyquinane frameworks. By incorporation ...of an iridium-catalyzed regio- and enantioselective hydrogenation and a diastereocontrolled ODI-5+2 cycloaddition/pinacol rearrangement cascade reaction, the asymmetric total syntheses of eight tetraquinane natural products, including (−)-crinipellins A–F and (−)-dihydrocrinipellins A and B, have been achieved in a concise and divergent manner.
Orbital angular momentum (OAM), which describes tailoring the spatial physical dimension of light waves into a helical phase structure, has given rise to many applications in optical manipulation, ...microscopy, imaging, metrology, sensing, quantum science, and optical communications. Light beams carrying OAM feature two distinct characteristics, i.e., inherent orthogonality and unbounded states in principle, which are suitable for capacity scaling of optical communications. In this paper, we give an overview of OAM and beyond in free-space optical communications. The fundamentals of OAM, concept of optical communications using OAM, OAM modulation (OAM modulation based on spatial light modulator, high-speed OAM modulation, spatial array modulation), OAM multiplexing (spectrally efficient, high capacity, long distance), OAM multicasting (adaptive multicasting,
-dimensional multicasting), OAM communications in turbulence (adaptive optics, digital signal processing, auto-alignment system), structured light communications beyond OAM (Bessel beams, Airy beams, vector beams), diverse and robust communications using OAM and beyond (multiple scenes, turbulence-resilient communications, intelligent communications) are comprehensively reviewed. The prospects and challenges of optical communications using OAM and beyond are also discussed at the end. In the future, there will be more opportunities in exploiting extensive advanced applications from OAM beams to more general structured light.
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