The utility of electronically conductive metal–organic frameworks (EC‐MOFs) in high‐performance devices has been limited to date by a lack of high‐quality thin film. The controllable thin‐film ...fabrication of an EC‐MOF, Cu3(HHTP)2, (HHTP=2,3,6,7,10,11‐hexahydroxytriphenylene), by a spray layer‐by‐layer liquid‐phase epitaxial method is reported. The Cu3(HHTP)2 thin film can not only be precisely prepared with thickness increment of about 2 nm per growing cycle, but also shows a smooth surface, good crystallinity, and high orientation. The chemiresistor gas sensor based on this high‐quality thin film is one of the best room‐temperature sensors for NH3 among all reported sensors based on various materials.
A wafer‐thin sensor: The preparation of a crystalline, highly‐oriented, and thickness‐controlled thin film with an electronically conductive MOF is reported. Chemiresistive sensors based on these thin films show a high response, excellent selectivity, fast response speed, and good long‐term stability towards NH3 gas at room temperature.
Soil erosion control and water resource protection can closely interact during restoration of terrestrial ecosystems. In semi‐arid ecosystems, an urgent issue is how vegetation restoration can ...achieve the goal of soil erosion mitigation and water conservation, which in turn, feeds back to ecosystem functioning.
We reviewed 78 articles from 22 countries in semi‐arid areas to evaluate the effects of vegetation type (i.e. forest, grassland and scrubland) on runoff and sediment yields across different environmental conditions (i.e. vegetation coverage, rainfall intensity, slope gradient and soil texture).
Our meta‐analysis shows that runoff and sediment reduction both increased as the vegetation coverage increased, and tended to be stable when vegetation coverage exceeded 60%. Vegetation provided a greater benefit for sediment reduction than for runoff control under intense rainfall. Grasslands were generally more effective in reducing sediment than other vegetation types. Forests, grasslands and scrublands were most efficient in soil erosion control on 20°–30°, 0°–25° and 10°–25° slopes respectively. Grasslands and scrublands generally performed better with respect to soil erosion control on moderately coarse soils, whereas forests were most effective on medium‐textured and moderately fine soils.
Synthesis and applications. Effective restoration and soil erosion control in semi‐arid ecosystems strongly depends on the selection of vegetation type. Our study further indicates that, for land managers, it is critical to consider local slope, and soil texture, and maintain appropriate vegetation coverage to achieve ecosystem sustainability. Grasslands might be particularly suitable to optimize the trade‐off between soil erosion control and surface water resource in semi‐arid regions.
抽象
半干旱区水保型植被恢复过程中如何实现水土流失控制且维系地表水资源的目标，并进一步反馈于植被生态系统功能，是目前亟待解决的问题。
本研究基于公开发表的来源于22个国家、78篇关于半干旱区植被对土壤侵蚀影响的文献报道，应用Meta‐analysis方法，系统评价了不同植被类型（林地，草地和灌木地）在不同环境条件（植被盖度、降雨强度、坡度和土壤质地）下对径流量和产沙量的影响。
研究结果表明，植被减流效应和减沙效应均随植被盖度的增加而增加，并在植被盖度达到60%时趋于稳定。强降雨下，植被减沙效应大于其减流效应。总体上，三种植被类型中，草地具有最高的减沙效应。林地、草地和灌木地分别在20°‐30°、0°–25°和10º‐25°坡度范围内表现出较高的减流效应和减沙效应。且草地和灌木地在中等粗糙质地土壤中的减流效应和减沙效应较高，林地在中等质地和中等细密质地土壤中的减流效应和减沙效应较高。
综合应用：半干旱区的水保型植被水土流失调控的有效性很大程度上取决于适宜的植被类型。本研究表明，在全球半干旱区，建设草地植被可有效实现水土流失调控与地表水资源维系的权衡。同时，在水保型植被建设过程中，应综合考虑坡度和土壤质地等实际情况并维持适宜的植被盖度，以实现植被生态系统的可持续性。
Effective restoration and soil erosion control in semi‐arid ecosystems strongly depends on the selection of vegetation type. Our study further indicates that, for land managers, it is critical to consider local slope, and soil texture, and maintain appropriate vegetation coverage to achieve ecosystem sustainability. Grasslands might be particularly suitable to optimize the trade‐off between soil erosion control and surface water resource in semi‐arid regions.
Deep convolutional neural network models pre-trained for the ImageNet classification task have been successfully adopted to tasks in other domains, such as texture description and object proposal ...generation, but these tasks require annotations for images in the new domain. In this paper, we focus on a novel and challenging task in the pure unsupervised setting: fine-grained image retrieval. Even with image labels, fine-grained images are difficult to classify, letting alone the unsupervised retrieval task. We propose the selective convolutional descriptor aggregation (SCDA) method. The SCDA first localizes the main object in fine-grained images, a step that discards the noisy background and keeps useful deep descriptors. The selected descriptors are then aggregated and the dimensionality is reduced into a short feature vector using the best practices we found. The SCDA is unsupervised, using no image label or bounding box annotation. Experiments on six fine-grained data sets confirm the effectiveness of the SCDA for fine-grained image retrieval. Besides, visualization of the SCDA features shows that they correspond to visual attributes (even subtle ones), which might explain SCDA's high-mean average precision in fine-grained retrieval. Moreover, on general image retrieval data sets, the SCDA achieves comparable retrieval results with the state-of-the-art general image retrieval approaches.
In this study, we used an argon-based round atmospheric-pressure plasma jet (APPJ) for enhancing wound healing in streptozotocin (STZ) induced diabetic rats. The APPJ was characterized by optical ...emission spectroscopy. We induced Type 1 and Type 2 diabetes in rats with different amounts of STZ combined with normal and high-fat diets, respectively. The wound area ratio of all the plasma-treated normal and diabetic groups was greatly reduced (up to 30%) compared with that of the untreated groups during healing. Histological analysis revealed faster re-epithelialization, collagen deposition, less inflammation, and a complete skin structure in the plasma-treated groups was found as compared with the untreated control groups. In addition, the new blood vessels of plasma-treated tissues decreased more than untreated tissues in the middle (Day 14) and late (Day 21) stages of wound healing. The plasma-treated wounds demonstrated more transforming growth factor beta (TGF-β) expression in the early stage (Day 7), whereas they decreased in the middle and late stages of wound healing. The levels of superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT) increased after plasma treatment. In addition, plasma-treated water had a higher concentration of hydrogen peroxide, nitrite and nitrate when the plasma treatment time was longer. In summary, the proposed argon APPJ based on the current study could be a potential tool for treating diabetic wounds.
The construction of hydrophobic nanochannel with hydrophilic sites for bionic devices to proximally mimick real bio‐system is still challenging. Taking the advantages of MOF chemistry, a highly ...oriented CuTCPP thin film has been successfully reconstructed with ultra‐thin nanosheets to produce abundant two‐dimensional interstitial hydrophobic nanochannels with hydrophilic sites. Different from the classical active‐layer material with proton transport in bulk, CuTCPP thin film represents a new type of active‐layer with proton transport in nanochannel for bionic proton field‐effect transistor (H+‐FETs). The resultant device can reversibly modulate the proton transport by varying the voltage on its gate electrode. Meanwhile, it shows the highest proton mobility of ≈9.5×10−3 cm2 V−1 s−1 and highest on‐off ratio of 4.1 among all of the reported H+‐FETs. Our result demonstrates a powerful material design strategy for proximally mimicking the structure and properties of bio‐systems and constructing bionic electrical devices.
A MOF thin film‐based bionic proton field‐effect transistor (H+‐FET) has been fabricated for the first time. It displays the highest proton mobility and highest on–off ratio among all reported H+‐FETs.
Challenges remain in the development of novel multifunctional electrocatalysts and their industrial operation on low‐electricity pair‐electrocatalysis platforms for the carbon cycle. Herein, an ...enzyme‐inspired single‐molecular heterojunction electrocatalyst ((NHx)16‐NiPc/CNTs) with specific atomic nickel centers and amino‐rich local microenvironments for industrial‐level electrochemical CO2 reduction reaction (eCO2RR) and further energy‐saving integrated CO2 electrolysis is designed and developed. (NHx)16‐NiPc/CNTs exhibit unprecedented catalytic performance with industry‐compatible current densities, ≈100% Faradaic efficiency and remarkable stability for CO2‐to‐CO conversion, outperforming most reported catalysts. In addition to the enhanced CO2 capture by chemisorption, the sturdy deuterium kinetic isotope effect and proton inventory studies sufficiently reveal that such distinctive local microenvironments provide an effective proton ferry effect for improving local alkalinity and proton transfer and creating local interactions to stabilize the intermediate, ultimately enabling the high‐efficiency operation of eCO2RR. Further, by using (NHx)16‐NiPc/CNTs as a bifunctional electrocatalyst in a flow cell, a low‐electricity overall CO2 electrolysis system coupling cathodic eCO2RR with anodic oxidation reaction is developed to achieve concurrent feed gas production and sulfur recovery, simultaneously decreasing the energy input. This work paves the new way in exploring molecular electrocatalysts and electrolysis systems with techno‐economic feasibility.
An enzyme‐inspired single‐molecular heterojunction electrocatalyst with accurate amino‐rich microenvironments around the active sites is uniquely designed to enable efficient CO2 capture and fast proton ferrying during CO2 electroreduction, which achieves concurrent CO production at the cathode and sulfur recovery at the anode with industrial‐level current density and lower energy consumption.
Small interfering RNA (siRNA) is an effective therapeutic to regulate the expression of target genes in vitro and in vivo. Constructing a siRNA delivery system with high serum stability, especially ...responsive to endogenous stimuli, remains technically challenging. Herein we develop anti-degradation Y-shaped backbone-rigidified triangular DNA bricks with sticky ends (sticky-YTDBs) and tile them onto a siRNA-packaged gold nanoparticle in a programmed fashion, forming a multi-functional three-dimensional (3D) DNA shell. After aptamers are arranged on the exterior surface, a biocompatible siRNA-encapsulated core/shell nanoparticle, siRNA/Ap-CS, is achieved. SiRNAs are internally encapsulated in a 3D DNA shell and are thus protected from enzymatic degradation by the outermost layer of YTDB. The siRNAs can be released by endogenous miRNA and execute gene silencing within tumor cells, causing cell apoptosis higher than Lipo3000/siRNA formulation. In vivo treatment shows that tumor growth is completely (100%) inhibited, demonstrating unique opportunities for next-generation anticancer-drug carriers for targeted cancer therapies.
Evolutionary transitions from outcrossing to selfing in flowering plants have convergent morphological and genomic signatures and can involve parallel evolution within related lineages. Adaptive ...evolution of morphological traits is often assumed to evolve faster than nonadaptive features of the genomic selfing syndrome. We investigated phenotypic and genomic changes associated with transitions from distyly to homostyly in the Primula oreodoxa complex. We determined whether the transition to selfing occurred more than once and investigated stages in the evolution of morphological and genomic selfing syndromes using 22 floral traits and both nuclear and plastid genomic data from 25 populations. Two independent transitions were detected representing an earlier and a more recently derived selfing lineage. The older lineage exhibited classic features of the morphological and genomic selfing syndrome. Although features of both selfing syndromes were less developed in the younger selfing lineage, they exhibited parallel development with the older selfing lineage. This finding contrasts with the prediction that some genomic changes should lag behind adaptive changes to morphological traits. Our findings highlight the value of comparative studies on the timing and extent of transitions from outcrossing to selfing between related lineages for investigating the tempo of morphological and molecular evolution.
Scalable Algorithms for Multi-Instance Learning Wei, Xiu-Shen; Wu, Jianxin; Zhou, Zhi-Hua
IEEE transaction on neural networks and learning systems,
04/2017, Letnik:
28, Številka:
4
Journal Article
Multi-instance learning (MIL) has been widely applied to diverse applications involving complicated data objects, such as images and genes. However, most existing MIL algorithms can only handle ...small- or moderate-sized data. In order to deal with large-scale MIL problems, we propose MIL based on the vector of locally aggregated descriptors representation (miVLAD) and MIL based on the Fisher vector representation (miFV), two efficient and scalable MIL algorithms. They map the original MIL bags into new vector representations using their corresponding mapping functions. The new feature representations keep essential bag-level information, and at the same time lead to excellent MIL performances even when linear classifiers are used. Thanks to the low computational cost in the mapping step and the scalability of linear classifiers, miVLAD and miFV can handle large-scale MIL data efficiently and effectively. Experiments show that miVLAD and miFV not only achieve comparable accuracy rates with the state-of-the-art MIL algorithms, but also have hundreds of times faster speed. Moreover, we can regard the new miVLAD and miFV representations as multiview data, which improves the accuracy rates in most cases. In addition, our algorithms perform well even when they are used without parameter tuning (i.e., adopting the default parameters), which is convenient for practical MIL applications.
Minimal Gated Unit for Recurrent Neural Networks Zhou, Guo-Bing; Wu, Jianxin; Zhang, Chen-Lin ...
International journal of automation and computing,
06/2016, Letnik:
13, Številka:
3
Journal Article
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Recurrent neural networks （RNN） have been very successful in handling sequence data. However, understanding RNN and finding the best practices for RNN learning is a difficult task, partly because ...there are many competing and complex hidden units, such as the long short-term memory （LSTM） and the gated recurrent unit （GRU）. We propose a gated unit for RNN, named as minimal gated unit （MCU）, since it only contains one gate, which is a minimal design among all gated hidden units. The design of MCU benefits from evaluation results on LSTM and GRU in the literature. Experiments on various sequence data show that MCU has comparable accuracy with GRU, but has a simpler structure, fewer parameters, and faster training. Hence, MGU is suitable in RNN＇s applications. Its simple architecture also means that it is easier to evaluate and tune, and in principle it is easier to study MGU＇s properties theoretically and empirically.
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