Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and obtained remarkable performance. However, most of the existing CNN-based SISR ...methods mainly focus on wider or deeper architecture design, neglecting to explore the feature correlations of intermediate layers, hence hindering the representational power of CNNs. To address this issue, in this paper, we propose a second-order attention network (SAN) for more powerful feature expression and feature correlation learning. Specifically, a novel train- able second-order channel attention (SOCA) module is developed to adaptively rescale the channel-wise features by using second-order feature statistics for more discriminative representations. Furthermore, we present a non-locally enhanced residual group (NLRG) structure, which not only incorporates non-local operations to capture long-distance spatial contextual information, but also contains repeated local-source residual attention groups (LSRAG) to learn increasingly abstract feature representations. Experimental results demonstrate the superiority of our SAN network over state-of-the-art SISR methods in terms of both quantitative metrics and visual quality.
Binary Matrices for Compressed Sensing Lu, Weizhi; Dai, Tao; Xia, Shu-Tao
IEEE transactions on signal processing,
2018-Jan.1,-1, 2018-1-1, 20180101, Volume:
66, Issue:
1
Journal Article
Peer reviewed
For an m x n binary matrix with d nonzero elements per column, it is interesting to identify the minimal column degree d that corresponds to the best recovery performance. Consider this problem is ...hard to be addressed with currently known performance parameters, we propose a new performance parameter, the average of nonzero correlations between normalized columns. The parameter is proved to perform better than the known coherence parameter, namely the maximum correlation between normalized columns, when used to estimate the performance of binary matrices with high compression ratios n/m and low column degrees d. By optimizing the proposed parameter, we derive an ideal column degree d = √m 1, around which the best recovery performance is expected to be obtained. This is verified by simulations. Given the ideal number d of nonzero elements in each column, we further determine their specific distribution by minimizing the coherence with a greedy method. The resulting binary matrices achieve comparable or even better recovery performance than random binary matrices.
Designing high‐performance and cost‐effective electrocatalysts for water splitting at high current density is pivotal for practical industrial applications. Herein, it is found that atomic‐level ...surface engineering of self‐supported nickel phosphide (NiP) nanoarrays via a facile cation‐exchange method can substantially regulate the chemical and physical properties of catalysts by introducing Co atoms. Such surface‐engineered NixCo1–xP endows several aspects of merits: i) rough nanosheet array electrode structure accessible to diffusion of electrolytes and release of gas bubbles, ii) enriched P vacancies companied by Co doping and thus increased active sites, and iii) the synergy of Ni5P4 and NiP2 beneficial to catalytic activity enhancement. By virtue of finely controlling the Co contents, the optimal Ni0.96Co0.04P electrode achieves remarkable bifunctional electrocatalytic performance for overall water splitting at a large current density of 1000 mA cm−2, showing overpotentials of 249.7 mV for hydrogen evolution reaction and 281.7 mV for oxygen evolution reaction. Furthermore, the Ni0.96Co0.04P electrode at 500 mA cm−2 exhibits an ultralow potential (1.71 V) and ultralong durability (500 h) for overall water splitting. This study implies that the atomic‐level surface engineering of the electrode materials offers a viable route for gaining high‐performance catalysts for water splitting at large current density.
The self‐supported NiP nanosheet array electrode with enriched P vacancies and atomic‐level Co doping is achieved by a controlled cation‐exchange strategy excluding complicated chemical reactions and post‐treatment steps. Such NiP nanoarray electrode exhibits excellent performance and long‐term stability (over 500 h) for electrocatalytic water splitting at large current density, outperforming noble‐metal catalysts in electrocatalytic hydrogen evolution reaction and oxygen evolution reaction.
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A code is said to be an <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula>-local locally repairable code (LRC) if each of its coordinates can be repaired by accessing at most ...<inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> other coordinates. When some of the <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula> coordinates are also erased, the <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula>-local LRC cannot accomplish the local repair, which leads to the concept of <inline-formula> <tex-math notation="LaTeX">(r,\delta) </tex-math></inline-formula>-locality. A <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary <inline-formula> <tex-math notation="LaTeX">n, k </tex-math></inline-formula> linear code <inline-formula> <tex-math notation="LaTeX">\mathcal {C} </tex-math></inline-formula> is said to have <inline-formula> <tex-math notation="LaTeX">(r, \delta) </tex-math></inline-formula>-locality (<inline-formula> <tex-math notation="LaTeX">\delta \ge 2 </tex-math></inline-formula>) if for each coordinate <inline-formula> <tex-math notation="LaTeX">i </tex-math></inline-formula>, there exists a punctured subcode of <inline-formula> <tex-math notation="LaTeX">\mathcal {C} </tex-math></inline-formula> with support containing <inline-formula> <tex-math notation="LaTeX">i </tex-math></inline-formula>, whose length is at most <inline-formula> <tex-math notation="LaTeX">r + \delta - 1 </tex-math></inline-formula>, and whose minimum distance is at least <inline-formula> <tex-math notation="LaTeX">\delta </tex-math></inline-formula>. The <inline-formula> <tex-math notation="LaTeX">(r, \delta) </tex-math></inline-formula>-LRC can tolerate <inline-formula> <tex-math notation="LaTeX">\delta -1 </tex-math></inline-formula> erasures in every local code (i.e., punctured subcode), which degenerates to an <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula>-local LRC when <inline-formula> <tex-math notation="LaTeX">\delta =2 </tex-math></inline-formula>. A <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary <inline-formula> <tex-math notation="LaTeX">(r,\delta) </tex-math></inline-formula> LRC is called optimal if it meets the singleton-like bound for <inline-formula> <tex-math notation="LaTeX">(r,\delta) </tex-math></inline-formula>-LRCs. A class of optimal <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary cyclic <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula>-local LRCs with lengths <inline-formula> <tex-math notation="LaTeX">n\mid q-1 </tex-math></inline-formula> were constructed by Tamo, Barg, Goparaju, and Calderbank based on the <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary Reed-Solomon codes. In this paper, we construct a class of optimal <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary cyclic <inline-formula> <tex-math notation="LaTeX">(r,\delta) </tex-math></inline-formula>-LRCs (<inline-formula> <tex-math notation="LaTeX">\delta \ge 2 </tex-math></inline-formula>) with length <inline-formula> <tex-math notation="LaTeX">n\mid q-1 </tex-math></inline-formula>, which generalizes the results of Tamo et al. Moreover, we construct a new class of optimal <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary cyclic <inline-formula> <tex-math notation="LaTeX">r </tex-math></inline-formula>-local LRCs with lengths <inline-formula> <tex-math notation="LaTeX">n\mid q+1 </tex-math></inline-formula> and a new class of optimal <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula>-ary cyclic <inline-formula> <tex-math notation="LaTeX">(r,\delta) </tex-math></inline-formula>-LRCs (<inline-formula> <tex-math notation="LaTeX">\delta \ge 2 </tex-math></inline-formula>) with lengths <inline-formula> <tex-math notation="LaTeX">n\mid q+1 </tex-math></inline-formula>. The constructed optimal LRCs with length <inline-formula> <tex-math notation="LaTeX">n=q+1 </tex-math></inline-formula> have the best-known length for a given finite field with size <inline-formula> <tex-math notation="LaTeX">q </tex-math></inline-formula> when the minimum distance is larger than 4.
HPV vaccine can prevent HPV infection effectively. The college student’s vaccination status is unclear in mainland China. We assessed the knowledge, practice, and attitude towards HPV vaccine and ...compared the differences between medical and nonmedical students. It was a cross-sectional study using self-administered anonymous questionnaires. Nine-hundred sixty full-time college students were recruited randomly at Peking University in China. The medical students had higher level of knowledge of HPV and its vaccine than the nonmedical students (
p
< 0.001). The vaccinated female students were 9.0%. The high-grade clinical students had a higher uptake rate than the nonmedical students (19.5 vs 8.6%,
p
< 0.05). Awareness of HPV (
p
< 0.01), awareness of the vaccine (
p
< 0.001), and vaccinated family members or friends (
p
< 0.001) were related to the nonmedical students’ vaccination. Vaccinated family members or friends were significant predictor for students’ vaccination status (
p
< 0.001). Medical students knew more about HPV and its vaccine than nonmedical students. Female students’ vaccinated rate was low, and the high-grade clinical students had a higher uptake rate than the nonmedical students.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Random forests (RFs) are recognized as one type of ensemble learning method and are effective for the most classification and regression tasks. Despite their impressive empirical performance, the ...theory of RFs has yet been fully proved. Several theoretically guaranteed RF variants have been presented, but their poor practical performance has been criticized. In this paper, a novel RF framework is proposed, named Bernoulli RFs (BRFs), with the aim of solving the RF dilemma between theoretical consistency and empirical performance. BRF uses two independent Bernoulli distributions to simplify the tree construction, in contrast to the RFs proposed by Breiman. The two Bernoulli distributions are separately used to control the splitting feature and splitting point selection processes of tree construction. Consequently, theoretical consistency is ensured in BRF, i.e., the convergence of learning performance to optimum will be guaranteed when infinite data are given. Importantly, our proposed BRF is consistent for both classification and regression. The best empirical performance is achieved by BRF when it is compared with state-of-the-art theoretical/consistent RFs. This advance in RF research toward closing the gap between theory and practice is verified by the theoretical and experimental studies in this paper.
A hydrogenation of N‐heterocycles mediated by diboronic acid with water as the hydrogen atom source is reported. A variety of N‐heterocycles can be hydrogenated with medium to excellent yields within ...10 min. Complete deuterium incorporation from stoichiometric D2O onto substrates further exemplifies the H/D atom sources. Mechanism studies reveal that the reduction proceeds with initial 1,2‐addition, in which diboronic acid synergistically activates substrates and water via a six‐membered ring transition state.
No metal necessary: An unprecedented expeditious hydrogenation of N‐heterocycles mediated by diboronic acid with water as hydrogen atom source was reported. Mechanism studies revealed that the reduction proceeds with a successive 1,2‐addition, in which diboronic acid synergistically activates substrates and water via a six‐membered ring transition state.
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In distributed storage systems, locally repairable codes (LRCs) have attracted lots of interest recently. If a code symbol can be repaired respectively by t disjoint groups of other symbols, each of ...which has size at most r, we say that the code symbol has (r, t)-locality. LDPC codes are linear block codes defined by low-density parity-check matrices. A regular (τ, p)-LDPC code has the parity-check matrix with uniform column weight τ and uniform row weight p. In this letter, we employ regular LDPC codes to construct optimal binary LRCs with (r, t)-locality for information symbols. After proposing construction frameworks, three detailed constructions of binary LRCs with information locality are obtained, all of which have a single parity symbol in each repair group. All our codes attain the distance bounds of LRCs when each repair group contains a single parity symbol and thus are optimal. For storage systems with hot data, the proposed binary LRCs seem promising for system implementations since the encoding, repairing, parallel reading, and data reconstruction can be performed by simple XOR operations.
We reveal here the first hydrogenation of nitrogen heterocycles catalyzed by carbon–metal covalent bonds‐stabilized palladium nanoparticles in water under mild conditions. Using a one‐phase reduction ...method, smaller metal–carbon covalent bond‐stabilized Pd nanoparticles were prepared with a size distribution of 2.5±0.5 nm, which showed extraordinary synergistic effects with water in the catalytic hydrogenation of nitrogen heterocycles. Water was supposed to accelerate substrate absorption and synergistic activation of molecular hydrogen on the Pd nanoparticles surface. The nanosized Pd catalyst could be easily recovered and reused for 5 runs.
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Porous ultrathin 2D catalysts are attracting great attention in the field of electro/photocatalytic hydrogen evolution reaction (HER) and overall water splitting. Herein, a universal pH‐controlled ...wet‐chemical strategy is reported followed by thermal and phosphorization treatment to prepare large‐size, porous and ultrathin bimetallic phosphide (NiCoP) nanosheets, in which graphene oxide is adopted as a template to determine the size of products. The thickness of the resultant NiCoP nanosheets ranges from 3.5 to 12.8 nm via delicately adjusting pH from 7.8 to 8.5. The thickness‐dependent electrocatalytic performance is evidenced experimentally and explained by computational studies. The prepared large‐size ultrathin NiCoP nanosheets show excellent bifunctional electrocatalytic activity for overall water splitting, with low overpotentials of 34.3 mV for HER and 245.0 mV for oxygen evolution reaction, respectively, at 10 mA cm−2. Furthermore, the NiCoP nanosheets exhibit superior photocatalytic HER performance, achieving a high HER rate of 238.2 mmol h−1 g−1 in combination with commonly used photocatalyst CdS, which is far superior to that of Pt/CdS (81.7 mmol h−1 g−1). All these results demonstrate large‐size porous ultrathin NiCoP nanosheets as an efficient and multifunctional electro/photocatalyst for water splitting.
A facile pH‐controlled wet‐chemical strategy is developed followed by thermal and phosphorization treatment to prepare large‐size porous and ultrathin NiCoP nanosheets. Such NiCoP nanosheets are controlled to ≈3.5 nm in thickness via delicately adjusting pH to balance the nucleation and growth of metal ions, which exhibit excellent electro/photocatalytic performance for water splitting, outperforming noble‐metal catalysts in electro/photocatalytic OER and HER.
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