Electricity theft is harmful to power grids. Integrating information flows with energy flows, smart grids can help to solve the problem of electricity theft owning to the availability of massive data ...generated from smart grids. The data analysis on the data of smart grids is helpful in detecting electricity theft because of the abnormal electricity consumption pattern of energy thieves. However, the existing methods have poor detection accuracy of electricity theft since most of them were conducted on one-dimensional (1-D) electricity consumption data and failed to capture the periodicity of electricity consumption. In this paper, we originally propose a novel electricity-theft detection method based on wide and deep convolutional neural networks (CNN) model to address the above concerns. In particular, wide and deep CNN model consists of two components: the wide component and the deep CNN component. The deep CNN component can accurately identify the nonperiodicity of electricity theft and the periodicity of normal electricity usage based on 2-D electricity consumption data. Meanwhile, the wide component can capture the global features of 1-D electricity consumption data. As a result, wide and deep CNN model can achieve the excellent performance in electricity-theft detection. Extensive experiments based on realistic dataset show that wide and deep CNN model outperforms other existing methods.
The development of energy‐saving technology for the efficient separation of olefin and paraffin is highly important for the chemical industry. Herein, we report a self‐assembled Fe4L6 capsule ...containing a hydrophobic cavity, which can be used to encapsulate and separate propylene/propane. The successful encapsulation of propylene and propane by the Fe4L6 cage in a water solution was documented by NMR spectroscopy. The binding constants K for the Fe4L6 cage toward propylene and propane were determined to be (5.0±0.1)×103 M−1 and (2.1±0.7)×104 M−1 in D2O at 25 °C, respectively. Experiments and theoretical studies revealed that the cage exhibited multiple weak interactions with propylene and propane. The polymer‐grade propylene (>99.5 %) can be obtained from a mixture of propylene and propane by using the Fe4L6 cage as a separation material in a U‐shaped glass tube. This work provides a new strategy for the separation of olefin/paraffin.
A water‐soluble tetrahedral Fe4L6 metal‐organic cage has been successfully used to separate propane and propylene under ambient conditions. Mixed gases of C3H6 and C3H8 were captured by Fe4L6 at the gas‐liquid interface in a U‐shaped glass tube. Governed by the guest binding affinity, C3H6 is released first after transport of the gases to the receiving arm of the tube.
Abstract
Deuterium labeling is of great value in organic synthesis and the pharmaceutical industry. However, the state-of-the-art C–H/C–D exchange using noble metal catalysts or strong bases/acids ...suffers from poor functional group tolerances, poor selectivity and lack of scope for generating molecular complexity. Herein, we demonstrate the deuteration of halides using heavy water as the deuteration reagent and porous CdSe nanosheets as the catalyst. The deuteration mechanism involves the generation of highly active carbon and deuterium radicals via photoinduced electron transfer from CdSe to the substrates, followed by tandem radicals coupling process, which is mechanistically distinct from the traditional methods involving deuterium cations or anions. Our deuteration strategy shows better selectivity and functional group tolerances than current C–H/C–D exchange methods. Extending the synthetic scope, deuterated boronic acids, halides, alkynes, and aldehydes can be used as synthons in Suzuki coupling, Click reaction, C–H bond insertion reaction etc. for the synthesis of complex deuterated molecules.
The design of adsorbents for rapid, selective extraction of ultra-trace amounts of gold from complex liquids is desirable from both an environmental and economical point of view. However, the ...development of such materials remains challenging. Herein, we report the fabrication of two vinylene-linked two-dimensional silver(I)-organic frameworks prepared via Knoevenagel condensation. This material enables selective sensing of gold with a low limit of detection of 60 ppb, as well as selective uptake of ultra-trace gold from complex aqueous mixtures including distilled water with 15 competing metal ions, leaching solution of electronic waste (e-waste), wastewater, and seawater. The present adsorbent delivers a gold adsorption capacity of 954 mg g
, excellent selectivity and reusability, and can rapidly and selectively extract ultra-trace gold from seawater down to ~20 ppb (94% removal in 10 minutes). In addition, the purity of recovered gold from e-waste reaches 23.8 Karat (99.17% pure).
Recently, traffic flow prediction has drawn significant attention because it is a prerequisite in intelligent transportation management in urban informatics. The massively available traffic data ...collected from various sensors in transportation cyber-physical systems brings the opportunities in accurately forecasting traffic trend. Recent advances in deep learning shows the effectiveness on traffic flow prediction though most of them only demonstrate the superior performance on traffic data from a single type of vehicular carriers (e.g., cars) and does not perform well in other types of vehicles. To fill this gap, in this article, we propose a wide-attention and deep-composite (WADC) model, consisting of a wide-attention module and a deep-composite module, in this article. In particular, the wide-attention module can extract global key features from traffic flows via a linear model with self-attention mechanism. The deep-composite module can generalize local key features via convolutional neural network component and long short-term memory network component. We also perform extensive experiments on different types of traffic flow datasets to investigate the performance of WADC model. Our experimental results exhibit that WADC model outperforms other existing approaches.
The interlay sliding of two-dimensional (2D) metal-organic and covalent-organic frameworks (MOFs and COFs) affects not only the layout features of the structures, but also the functional output of ...the materials. However, the control of interlay stacking is the major hurdle that needs to be overcome to construct new functional layer materials. Herein, we report the preparation of a pair of isostructural 2D copper(
i
) organic frameworks with an eclipsed AA stacking structure, namely
JNM-3-AA
, and a staggered ABC stacking topology, denoted
JNM-3-ABC
, by combining the chemistry of MOFs and COFs. The variation of interlayer stacking largely influences their functionality, including porosity (BET surface areas of 695.61 and 34.22 m
2
g
−1
for
JNM-3-AA
and
JNM-3-ABC
, respectively), chemical stability, and catalytic activities (less than 10% or ∼86% yield using
JNM-3-AA
or
JNM-3-ABC
as catalysts for click reaction, respectively). More interestingly, the structure transformation from
JNM-3-ABC
to
JNM-3-AA
is readily achieved by simple addition of trifluoroacetic acid accompanied by the extension of porosities from BET surface areas of 34.22 to 441.22 m
2
g
−1
, resulting in
in situ
acceleration of the adoption rate (removal efficiency increases from ∼10 to 99.9%), which is rarely observed in 2D MOFs and COFs.
The addition of TFA can trigger the interlay sliding of 2D copper(
i
) organic frameworks prepared by combing the chemistry of MOFs and COFs. The variation of interlay stacking largely affected the porosity, chemical stability and catalytic activities.
360-degree video streaming shows great potential to revolutionize the streaming market, by providing much better immersive experience than standard video streams. However, its wide adoption is ...hindered by the surging demand of network bandwidth due to multi-screen video transmission. To reduce the bandwidth cost, one promising approach is to predict a user's field of view (FoV), and then prefetch video tiles that a user will view a few seconds ahead. The challenge lies in that user behaviors cannot be properly captured with very limited information, especially the viewing time spent on each tile and the FoV switching behavior are hard to predict. In this paper, we propose a novel 360-degree video streaming algorithm called TVG-Streaming to optimize user experiences by learning user view behaviors. Different from previous approaches, our idea is to exploit tile-view graphs (TVGs) generated by real user behaviors and accurately estimate the probability that each tile falls in the FoV. With the tile view probability, we can determine the bitrate of each tile for delivery and buffering with limited bandwidth budget so as to maximize users' quality of experience (QoE). For evaluation, we conduct extensive experiments using real traces and the results show that our proposed TVG-Streaming algorithm significantly outperforms other algorithms by at least 20% improvement in terms of users' QoE.
Deficiency of glutamate transporter GLAST in Müller cells may be culpable for excessive extracellular glutamate, which involves in retinal ganglion cell (RGC) damage in glaucoma. We elucidated how ...GLAST was regulated in rat chronic ocular hypertension (COH) model. Western blot and whole‐cell patch‐clamp recordings showed that GLAST proteins and GLAST‐mediated current densities in Müller cells were downregulated at the early stages of COH. In normal rats, intravitreal injection of the ephrinA3 activator EphA4‐Fc mimicked the changes of GLAST in COH retinas. In purified cultured Müller cells, EphA4‐Fc treatment reduced GLAST expression at mRNA and protein levels, which was reversed by the tyrosine kinase inhibitor PP2 or transfection with ephrinA3‐siRNA (Si‐EFNA3), suggesting that EphA4/ephrinA3 reverse signaling mediated GLAST downregulation. EphA4/ephrinA3 reverse signaling‐induced GLAST downregulation was mediated by inhibiting PI3K/Akt/NF‐κB pathways since EphA4‐Fc treatment of cultured Müller cells reduced the levels of p‐Akt/Akt and NF‐κB p65, which were reversed by transfecting Si‐EFNA3. In Müller cells with ephrinA3 knockdown, the PI3K inhibitor LY294002 still decreased the protein levels of NF‐κB p65 in the presence of EphA4‐Fc, and the mRNA levels of GLAST were reduced by LY294002 and the NF‐κB inhibitor SN50, respectively. Pre‐injection of the PI3K/Akt pathway activator 740 Y‐P reversed the GLAST downregulation in COH retinas. Western blot and TUNEL staining showed that transfecting of Si‐EFNA3 reduced Müller cell gliosis and RGC apoptosis in COH retinas. Our results suggest that activated EphA4/ephrinA3 reverse signaling induces GLAST downregulation in Müller cells via inhibiting PI3K/Akt/NF‐κB pathways, thus contributing to RGC damage in glaucoma.
Main Points
GLAST expression and GLAST‐mediated currents in Müller cells are downregulated in COH retina.
EphA4/ephrinA3 reverse signaling activation mediates GLAST downregulation through inhibiting PI3K/Akt/NF‐κB signaling pathways.
Interference of EphA4/ephrinA3 signaling by siRNA reduces Müller cell gliosis and RGC apoptosis in COH retina.
Abstract
Yingjiang County, which is on the China–Myanmar border, is the main focus for malaria elimination in China. The epidemiological characteristics of malaria in Yingjiang County were analysed ...in a retrospective analysis. A total of 895 malaria cases were reported in Yingjiang County between 2013 and 2019. The majority of cases occurred in males (70.7%) and individuals aged 19–59 years (77.3%).
Plasmodium vivax
was the predominant species (96.6%). The number of indigenous cases decreased gradually and since 2017, no indigenous cases have been reported. Malaria cases were mainly distributed in the southern and southwestern areas of the county; 55.6% of the indigenous cases were reported in Nabang Township, which also had the highest risk of imported malaria. The “1–3–7” approach has been implemented effectively, with 100% of cases reported within 24 h, 88.9% cases investigated and confirmed within 3 days and 98.5% of foci responded to within 7 days. Although malaria elimination has been achieved in Yingjiang County, sustaining elimination and preventing the re-establishment of malaria require the continued strengthening of case detection, surveillance and response systems targeting the migrant population in border areas.
Sentiment analysis on Chinese microblogs has received extensive attention recently. Most previous studies focus on identifying sentiment orientation by encoding as many word properties as possible ...while they fail to consider contextual features (e.g., the long-range dependencies of words), which are, however, essentially important in the sentiment analysis. In this paper, we propose a Chinese sentiment analysis method by incorporating a word2vec model and a stacked bidirectional long short-term memory (Stacked Bi-LSTM) model. We first employ the word2vec model to capture semantic features of words and transfer words into high-dimensional word vectors. We evaluate the performance of two typical word2vec models: continuous bag-of-words (CBOW) and skip-gram. We then use the Stacked Bi-LSTM model to conduct the feature extraction of sequential word vectors. We next apply a binary softmax classifier to predict the sentiment orientation by using semantic and contextual features. Moreover, we also conduct extensive experiments on the real dataset collected from Weibo (i.e., one of the most popular Chinese microblogs). The experimental results show that our proposed approach achieves better performance than other machine-learning models.
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