To date, ionic conducting hydrogel attracts tremendous attention as an alternative to the conventional rigid metallic conductors in fabricating flexible devices, owing to their intrinsic ...characteristics. However, simultaneous realization of high stiffness, toughness, ionic conductivity, and freezing tolerance through a simple approach is still a challenge. Here, a novel highly stretchable (up to 660%), strong (up to 2.1 MPa), tough (5.25 MJ m−3), and transparent (up to 90%) ionic conductive (3.2 S m−1) organohydrogel is facilely fabricated, through sol–gel transition of polyvinyl alcohol and cellulose nanofibrils (CNFs) in dimethyl sulfoxide‐water solvent system. The ionic conductive organohydrogel presents superior freezing tolerance, remaining flexible and conductive (1.1 S m−1) even at −70 °C, as compared to the other reported anti‐freezing ionic conductive (organo)hydrogel. Notably, this material design demonstrates synergistic effect of CNFs in boosting both mechanical properties and ionic conductivity, tackling a long‐standing dilemma among strength, toughness, and ionic conductivity for the ionic conducting hydrogel. In addition, the organohydrogel displays high sensitivity toward both tensile and compressive deformation and based on which multi‐functional sensors are assembled to detect human body movement with high sensitivity, stability, and durability. This novel organohydrogel is envisioned to function as a versatile platform for multi‐functional sensors in the future.
A polyvinyl alcohol/cellulose nanofibril organohydrogel with simultaneously improved strength, toughness, and ionic conductivity is rationally designed. The organohydrogel shows outstanding freezing tolerance while maintains high ionic conductivity (1.1 S m−1) at −70 °C due to the presence of high dielectric dimethyl sulfoxide‐water binary solvent. The organohydrogel demonstrates great promise in serving as multi‐functional sensors under extreme conditions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In skeleton-based action recognition, graph convolutional networks (GCNs), which model the human body skeletons as spatiotemporal graphs, have achieved remarkable performance. However, in existing ...GCN-based methods, the topology of the graph is set manually, and it is fixed over all layers and input samples. This may not be optimal for the hierarchical GCN and diverse samples in action recognition tasks. In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods. In this work, we propose a novel two-stream adaptive graph convolutional network (2s-AGCN) for skeleton-based action recognition. The topology of the graph in our model can be either uniformly or individually learned by the BP algorithm in an end-to-end manner. This data-driven method increases the flexibility of the model for graph construction and brings more generality to adapt to various data samples. Moreover, a two-stream framework is proposed to model both the first-order and the second-order information simultaneously, which shows notable improvement for the recognition accuracy. Extensive experiments on the two large-scale datasets, NTU-RGBD and Kinetics-Skeleton, demonstrate that the performance of our model exceeds the state-of-the-art with a significant margin.
We examine the effects of trade liberalization in China on the evolution of markups and productivity of manufacturing firms. Although these dimensions of performance cannot be separately identified ...when firm output is measured by revenue, detailed price deflators make it possible to estimate the average effect of tariff reductions on both. Several novel findings emerge. First, cuts in output tariffs reduce markups, but raise productivity. Second, pro-competitive effects are most important among incumbents, while efficiency gains dominate for new entrants. Third, cuts in input tariffs raise both markups and productivity. We highlight mechanisms that explain these findings in the Chinese context.
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BFBNIB, CEKLJ, INZLJ, IZUM, KILJ, NMLJ, NUK, ODKLJ, PILJ, PNG, SAZU, UL, UM, UPUK, ZRSKP
In this paper, a technique is presented for the fusion of multispectral (MS) and hyperspectral (HS) images to enhance the spatial resolution of the latter. The technique works in the wavelet domain ...and is based on a Bayesian estimation of the HS image, assuming a joint normal model for the images and an additive noise imaging model for the HS image. In the complete model, an operator is defined, describing the spatial degradation of the HS image. Since this operator is, in general, not exactly known and in order to alleviate the burden of solving the inverse operation (a deconvolution problem), an interpolation is performed a priori . Furthermore, the knowledge of the spatial degradation is restricted to an approximation based on the resolution difference between the images. The technique is compared to its counterpart in the image domain and validated for noisy conditions. Furthermore, its performance is compared to several state-of-the-art pansharpening techniques, in the case where the MS image becomes a panchromatic image, and to MS and HS image fusion techniques from the literature.
Gesture is a natural interface in human-computer interaction, especially interacting with wearable devices, such as VR/AR helmet and glasses. However, in the gesture recognition community, it lacks ...of suitable datasets for developing egocentric (first-person view) gesture recognition methods, in particular in the deep learning era. In this paper, we introduce a new benchmark dataset named EgoGesture with sufficient size, variation, and reality to be able to train deep neural networks. This dataset contains more than 24 000 gesture samples and 3 000 000 frames for both color and depth modalities from 50 distinct subjects. We design 83 different static and dynamic gestures focused on interaction with wearable devices and collect them from six diverse indoor and outdoor scenes, respectively, with variation in background and illumination. We also consider the scenario when people perform gestures while they are walking. The performances of several representative approaches are systematically evaluated on two tasks: gesture classification in segmented data and gesture spotting and recognition in continuous data. Our empirical study also provides an in-depth analysis on input modality selection and domain adaptation between different scenes.
Neural networks (NNs) have demonstrated the potential to recover finer textural details from lower-resolution images by superresolution (SR). Given similar grid-based data structures, some ...researchers have transferred image SR methods to digital elevation models (DEMs). These efforts have yielded better results than traditional spatial interpolation methods. However, terrain data present inherently different characteristics and practical meanings compared with natural images. This makes it unsuitable for existing SR methods on perceptually visual features of images to be directly adopted for extracting terrain features. In this paper, we argue that the problem lies in the lack of explicit terrain feature modeling and thus propose a terrain feature-aware superresolution model (TfaSR) to guide DEM SR towards the extraction and optimization of terrain features. Specifically, a deep residual module and a deformable convolution module are integrated to extract deep and adaptive terrain features, respectively. In addition, explicit terrain feature-aware optimization is proposed to focus on local terrain feature refinement during training. Extensive experiments show that TfaSR achieves state-of-the-art performance in terrain feature preservation during DEM SR. Specifically, compared with the traditional bicubic interpolation method and existing neural network methods (SRGAN, SRResNet, and SRCNN), the RMSE of our results is improved by 1.1% to 23.8% when recovering the DEM from 120 m to 30 m, by 4.9% to 22.7% when recovering the DEM from 60 m to 30 m, and by 7.8% to 53.7% when recovering the DEM from 30 m to 10 m. The source code that has been developed is shared on Figshare (https://doi.org/10.6084/m9.figshare.19597201).
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Este trabajo tiene como objetivo explorar la situación de los préstamos del chino en el español actual, basándose en los datos obtenidos de diversos diccionarios y corpus textuales. Tras la ...definición tipológica del préstamo léxico de Gómez Capuz (2004) y los criterios de inclusión formulados por Cannon (1988) para los préstamos chinos en inglés, presentamos el concepto de sinismo y una propuesta clasificatoria. Los análisis cuantitativos realizados desde los aspectos de morfología, semántica, etiquetas de uso, fecha de introducción y geolecto origen muestran que: a) los sustantivos constituyen la mayor parte de este repertorio y se usan mayoritariamente en los contextos relacionados con China o Asia; b) la mayoría de los sinismos se utiliza tanto en el español peninsular como en el americano; c) el número de sinismos ha ido aumentando en español desde el siglo xvi; d) el mandarín es el geolecto origen más importante, y la forma gráfica de los sinismos está cada vez más influida por el pinyin.
This ethnographic work is about the recruitment and enculturation of novice scientists in the laboratory. Interviews and participant observation were conducted in a biochemistry research lab at a ...small liberal arts college. I take a predominantly interpretive approach and ask the question of how novice scientists make sense of their decisions and behaviors as they gain membership into the laboratory and the community of scientists. Revising the value-neutral and the structure-centered depiction of science, I represent novice scientists as agents who are subjected to their sociohistorical positionalities but also who consciously maneuver with purpose and agenda. Novice scientists’ attempts to strategize and negotiate access to resources are epitomized by the culture of cold emailing. Additionally, I elucidate a process of how prospective medical students later gravitate to careers in science. While many initially anticipate a career in medicine, high retention in science has been observed when quality mentorship, friendly workplace culture, and supportive family members are present. I also present episodes of normative, value-laden practices—and how novices engage with them—to capture the cosmology of scientists. I make the interpretation that the becoming of scientists is a rite of passage facilitated by behavioral habituation and values imprinting,
via
which cultural norms are transmitted and reproduced.
The development of smart delivery systems that are robust in circulation and quickly release drugs following selective internalization into target cancer cells is a key to precision cancer therapy. ...Interestingly, reduction-sensitive polymeric nanomedicines showing high plasma stability and triggered cytoplasmic drug release behavior have recently emerged as one of the most exciting platforms for targeted delivery of various anticancer drugs including small chemical drugs, proteins, and nucleic acids. In vivo studies in varying tumor models reveal that these reduction-sensitive multifunctional nanomedicines outperform the currently used clinical formulations and reduction-insensitive counterparts, bringing about not only significantly enhanced tumor selectivity, accumulation and inhibition efficacy but also markedly reduced systemic toxicity and improved therapeutic index. In this review, we will highlight the cutting-edge advancement with a focus on in vivo performances as well as future perspectives on reduction-sensitive polymeric nanomedicines for targeted cancer therapy.
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10.
Hematopoietic Hierarchy – An Updated Roadmap Zhang, Yifan; Gao, Shuai; Xia, Jun ...
Trends in cell biology,
December 2018, 2018-12-00, 20181201, Volume:
28, Issue:
12
Journal Article
Peer reviewed
The classical roadmap of hematopoietic hierarchy has been proposed for nearly 20 years and has become a dogma of stem cell research for most types of adult stem cells, including hematopoietic stem ...cells (HSCs). However, with the development of new technologies such as omics approaches at single-cell resolution, recent studies in vitro and in vivo have suggested that heterogeneity is a common feature of HSCs and their progenies. While these findings broaden our understanding of hematopoiesis, they also challenge the well-accepted hematopoietic hierarchy roadmap. Here, we review recent advances in the hematopoiesis field and provide an updated view to incorporate these new findings as well as to reflect on the complexity of HSCs and their derivatives in development and adulthood.
The classical hematopoietic hierarchy roadmap illustrates that hematopoiesis is a stepwise process, from multi-, oligo-, and unipotent progenitors to mature hematopoietic cells.
An updated view of hematopoietic hierarchy reveals that hematopoiesis is a continuous differentiation process, and that the differentiation of megakaryocyte lineage can bypass the intermediate steps.
The discovery of lineage-biased HSCs remodels the balanced hierarchy roadmap.
Hematopoiesis is maintained by distinct stem/progenitor cell populations in native and stress states, indicating that the hematopoietic hierarchy roadmap is flexible to adapt to different physiological conditions.
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