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In this work, cobalt glycerate (CoG@F127) nanosheets grown on the surface of graphene oxide (GO), i.e. CoG@F127/GO, have been synthesized with the assistance of nonionic surfactant Pluronic F127 via a hydrothermal method. After calcination, CoG@F127/GO is transformed into one derivative, Co nanoparticles coated with a trace amount of carbon (Co-C) on GO (Co-C/GO). The Co nanoparticles consist of an atypical core–shell structure, in which the core and the shell are both Co. Co-C anchored on GO can avoid the nanoparticles aggregation and expose more active sites for hydrogen evolution reaction (HER) to significantly improve the catalyst activity of HER. CoG@F127/GO is phosphatized to form the other derivate, cobalt pyrophosphate coated with a small amount of carbon (Co2P2O7-C) on GO (Co2P2O7-C/GO). Co2P2O7-C/GO composite owns a large electrochemical active surface area (ECSA) and fast rate towards oxygen evolution reaction (OER). Furthermore, the two derivatives of CoG@F127/GO, i.e. Co-C/GO and Co2P2O7-C/GO as twin flowers, are assembled into an overall water splitting electrolytic cell with a cell voltage of 1.56 V to deliver a current density of 10 mA cm−2.

Polysulfides (Li2Sx) have become key points that limit capacity improvement of lithium-sulfur batteries because of their high solubility. Oxygen-containing functional groups (such as C–O–H, C–O–C and C O) can effectively relieve a large amount of polysulfide dissolution due to their strong polarity. However, their types and contents on polysulfide-capturing abilities are still unknown. Therefore, three kinds of electrodes containing different contents of hydroxyl (C–O–H), ether (C–O–C) and carbonyl (C O) groups on carbon surface are controlled by changing pyrolysis times of dandelion. Electrochemical performance of lithium-sulfur batteries is tested to analyze influence of these groups on polysulfide-capturing abilities. It is discovered that C O and C–O–H groups can obviously inhibit shuttle effects of polysulfides during their initial production. In addition, a large number of C O bonds are converted to C–O–H bonds. More C–O–H bonds facilitate reversible capture of polysulfides and improve capacities. The introduction of C–O–C groups is not suitable for capturing more polysulfides rapidly and the appearance of ether groups limits conversion process of C–O–H groups. Both S load and discharging/charging process can effectively regulate evolution of three valence bonds, which is conducive to improving rate performance of lithium-sulfur batteries.

The objective of this paper is to experimentally investigate the cavitation patterns and corresponding hydrodynamics of the hydrofoil with leading edge roughness. The aims are to (1) understand the effect of the leading edge roughness on the hydrodynamic performance, and (2) have a good knowledge of the interaction between the leading edge roughness and the cavitation patterns. Experimental results are indicated for the NACA 66 hydrofoils with and without leading edge roughness at different incidence angles for sub and cavitation conditions. The experiments are conducted in the EPFL high-speed cavitation tunnel (Avellan 2015). The results showed that the leading edge roughness has a significant effect on the hydrodynamic performance at the sub cavitation, suppressing the formation of the incipient cavitation. The lift coefficient of the hydrofoil without leading edge roughness is larger than that of the hydrofoil with leading edge roughness, while for the drag coefficients, the results are contrary for the lift coefficient, and the maximum lift-to-drag ratio angle is delayed for the hydrofoil with leading edge roughness. The leading edge roughness modified the local pressure distribution at the leading edge region, which in turn significantly increased the minimum pressure coefficient, hence the incipient cavitation number of the hydrofoil with leading edge roughness. The formation and evolution of the transient cavity for the cloud cavitation is little affected by the leading edge roughness.

We study the effects of horizons on the entanglement harvested between two Unruh-DeWitt detectors via the use of moving mirrors with and without strict horizons. The entanglement reveals the sensitivity of the entanglement harvested to the global dynamics of the trajectories disclosing aspects of the effect that global information loss (where incoming massless scalar field modes from past null infinity cannot reach right future null infinity) has on local particle detectors. We also show that entanglement harvesting is insensitive to the sign of emitted radiation flux., Expanded discussions and added references. New appendix on numerical convergence added

Inducing necroptosis in cancer cells is an effective approach to circumvent drug-resistance. Metal-based triggers have, however, rarely been reported. Ruthenium(II) complexes containing 1,1-(pyrazin-2-yl)pyreno[4,5-e][1,2,4]triazine were developed with a series of different ancillary ligands (Ru1-7). The combination of the main ligand with bipyridyl and phenylpyridyl ligands endows Ru7 with superior nucleus-targeting properties. As a rare dual catalytic inhibitor, Ru7 effectively inhibits the endogenous activities of topoisomerase (topo) I and II and kills cancer cells by necroptosis. The cell signaling pathway from topo inhibition to necroptosis was elucidated. Furthermore, Ru7 displays significant antitumor activity against drug-resistant cancer cells in vivo. To the best of our knowledge, Ru7 is the first Ru-based necroptosis-inducing chemotherapeutic agent.

Lake waters often act as important methane sources for global greenhouse gas emission, but it would be more complex as lakes are regulated by rivers. In this study, seasonal variations of dissolved and emitted methane in the Poyang Lake, the largest freshwater lake in China, are investigated based on a specially designed monitoring. As a typical subtropical linking-to-river lake, the Poyang shows characteristics of the “lake” in wet season and the “river” in dry season alternatively over a year. Consequently, CH4 flux from the Poyang Lake to the Yangtze River closes to the highest in January due to concentrated dissolved CH4 and “river” effects in dry season, while CH4 flux to the atmosphere falls to the lowest in July because of intensified CH4 oxidization and diluted dissolved CH4 as well as “lake” effects in wet season. Overall, CH4 fluxes from Poyang Lake to the atmosphere and to the Yangtze River were 19 and 0.35 Gg CH4 yr−1, respectively. The Three Gorges Dam, the world’s largest dam in the Yangtze River, would further intensify this pattern, enhancing the transformation between “lake phase” and “river phase”. This study also provides the paradigm for CH4 budget from other large lakes in similar situations around the world.

This Minireview summarizes the recent progress of stimuli-responsive purely organic phosphorescence materials. Organic phosphorescence is closely related to the intermolecular interactions, because such interactions are beneficial to promote spin orbital coupling (SOC) and boost intersystem cross (ISC) efficiency and finally are conducive to satisfactory phosphorescence. It is found that the intermolecular interactions, which are essential for organic phosphorescence, are easily disturbed by external stimuli such as mechanical force, photon, acid, chemical vapor, leading to the luminescence change. According to this principle, various purely organic phosphorescence materials sensitive to external stimuli have been developed. This Minireview categorizes reported stimuli-responsive purely organic phosphorescence materials on the basis of different stimuli, including mechanochromism, mechanoluminescence, photoactivity, acid-responsiveness and other stimuli. Some prospective strategies for constructing stimuli-responsive purely organic phosphorescence molecules are provided.

To effectively improve the computation efficiency in the strapdown inertial navigation system (SINS) alignment process, the authors propose a marginalised adaptive sparse-grid quadrature filter (MASGQF). The filtering method combines the virtues of marginalisation technique and accuracy level switching structure to decrease the computational burden and improve the filtering precision simultaneously. With the adaptation criterion and the predefined tolerance value, different integration rules corresponding to the different accuracy levels nested in the proposed filtering method can be adjusted autonomously. It is proved that the MASGQF is exponentially bounded by theoretical analysis. The performance comparison of different filtering methods is demonstrated by the numerical results of the simulation and offline experiment. On the basis of the data performance of the online test, the validity of the proposed MASGQF is verified in the SINS alignment application.

The recycling of heavy metals from solid wastes and transforming these metals into useful materials, such as metal oxides, nanocomposites, and metal–organic frameworks (MOFs), are beneficial for both sustainable development and environmental protection. MOFs are promising for adsorptive desulfurization, owing to their extremely high surface areas and tunable structures. In this paper, for the first time, MIL-53(Cr) was successfully fabricated from electroplating sludge (EPS) as a metal source through a facile hydrothermal method with and without HF. Our synthetic method is novel, green, scalable, and time-efficient. The obtained MIL-53(Cr) was employed as an adsorbent for adsorptive dibenzothiophene removal from liquid fuel. MIL-53(Cr) with HF exhibits a higher desulfurization capacity (40.11 mg g–1) than that of MIL-53(Cr) without HF (32.80 mg g–1). The improved adsorption performance of MIL-53(Cr) with HF is attributed to adding a small amount of HF, which produces highly crystalline and relativity pure MIL-53(Cr) microrods with a high surface area and porosity, and is due to a robust metal–sulfur interaction. Furthermore, the regenerated adsorbent can retain 94% of its initial sulfur adsorption capability even after 5 cycles, implying that MIL-53(Cr) prepared from Cr-EPS is an efficient adsorbent for fuel desulfurization. This study provides new insight for the production of high-value-added MOF materials from solid wastes following the principle of “resource reuse”.

Channel pruning is effective in compressing the pretrained CNNs for their deployment on low-end edge devices. Most existing methods independently prune some of the original channels and need the complete original dataset to fix the performance drop after pruning. However, due to commercial protection or data privacy, users may only have access to a tiny portion of training examples, which could be insufficient for the performance recovery. In this paper, for pruning with limited data, we propose to use all original filters to directly develop new compact filters, named reborn filters, so that all useful structure priors in the original filters can be well preserved into the pruned networks, alleviating the performance drop accordingly. During training, reborn filters can be easily implemented via 1×1 convolutional layers and then be fused in the inference stage for acceleration. Based on reborn filters, the proposed channel pruning algorithm shows its effectiveness and superiority on extensive experiments.

Understanding the nanoparticle deposition process is important for predicting the transport and fate of nanoparticles in natural and engineered aquatic environments. Traditional methods for deposit...

Enhancing sludge dewatering is of importance in reducing environmental burden and disposal costs. In this work, a cationic surfactant, cetyl trimethyl ammonium bromide (CTAB), was combined with Fenton's reagent for sludge dewatering. Results show that the Fenton-CTAB conditioning significantly promotes the sludge dewatering. Using combined techniques of response surface methodology and uniform design, dosages of Fe2+, H2O2, and CTAB for water content response were optimized to be 89, 276, and 233 mg/g dry solids (DS), respectively. The water content of sludge decreased from 79.0% to 66.8% under the optimal conditions. Compared with cationic polyacrylamide, the Fenton-CTAB system exhibited superior sludge dewatering performance. To gain insights into the mechanisms involved in sludge dewatering, the effects of Fenton-CTAB conditioning on the composition of extracellular polymeric substances (EPS) and the morphology of the sludge flocs were investigated. The decomposition of EPS into some dissolved organics and the release of proteins in tightly bound EPS facilitated the conversion of bound water to free water and further reduced the water content of sludge cake. After conditioning, morphology of sludge showed aggregation. Overall, the enhanced sludge dewatering by Fenton-CTAB treatment provides an efficient way for management of sewage sludge.

In this study, for the first time, a novel near-infrared and ratiometric fluorescent probe was conveniently synthesized by reacting PDI-based salicylaldehyde with 2-(hydrazonomethyl)phenol. The probe was designed based on the intramolecular charge transfer (ICT) mechanism and the intramolecular electron transfer (IET) mechanism, which can be blocked by the hypochlorite and a larger conjugation is formed within the probe. Due to the turn-on fluorescence responses triggered by the PET and ICT processes after the ClO− addition, the probe produces simultaneous emission peaks at 600 nm and 820 nm. In addition, the probe shows a rapid fluorescence response towards the ClO− ions within 5 s, a low detection limit (0.8 × 10−7 M), intense color changes (from purple to light green), excellent selectivity, and reversibility. Importantly, cell imaging experiments show that the probe can identify endogenous ClO− successfully.

In this paper, firstly we propose a new protocol for quantum bidirectional teleportation of two particles in a six-qubit entangled channel, which is based on GHZ measurement and unitary operation. Then, also based on the six-qubit entangled state channel, a protocol for quantum bidirectional teleportation of two-three particles is proposed. The protocol utilizes Toffoli gate to convert three-qubit states into two-qubit states and a single qubit, and the rest of the teleportation is the same as the first protocol. Finally, we introduce an auxiliary bit to restore the state of the sender. Both these proposed protocols are more efficient than others in the same situation, which will be compared at the end of the paper.

Quantum nonlocality, one of the most important features of quantum mechanics, is normally connected in experiments with the violation of Bell-Clauser-Horne (Bell-CH) inequalities. We propose effective methods for the rearrangement and linear inequality to prove a large variety of Bell-CH inequalities. We also derive a set of Bell-CH inequalities by using these methods which can be violated in some quantum entangled states., RevTex 4.1, 19 pages, 1 table

In this study, based on depolymerization solution of commercially available sodium lignosulfonate under mild conditions, an efficient method for the chromatographic separation of lignosulfonate depolymerization products was firstly established. The self-built database contains 18 lignin-based standards and the information on their names, formulas, structures, retention times, fragments, and corresponding MSE data was developed. By searching the online spectral data in a novel informatics database, a total of nine aromatic lignin depolymerization products were identified automatically. Thus, a fast standard protocol for detection and identification of real lignin degradation products was preliminary built.

Chromium is a common heavy metal widely present in aquatic environments. Cost-effective remediation of chromium-contaminated environment can be realized by microbial reduction of Cr(VI) to Cr(III). The genus Aeromonas species is one of such Cr(VI) reducers, whose reduction mechanism remains unrevealed and the main factors governing the Cr(VI) reduction pathways are unknown yet. In this work, the performances and mechanisms of Cr(VI) anaerobic reduction by Aeromonas hydrophila ATCC 7966 were investigated. This strain exhibited excellent Cr(VI) resistance and could utilize a suite of electron donors to support Cr(VI) bioreduction. The Cr(VI) bioreduction processes involved both extracellular (the metal-reducing and respiratory pathway) and intracellular reaction pathways. Adding anthraquinone-2,6-disulfonate or humic acid as a mediator substantially enhanced the Cr(VI) bioreduction. The forms and distribution of the Cr(VI) bioreduction products were affected by the medium composition. Soluble organo-Cr(III) complexes were identified as the main Cr(VI) reduction products when basal salts medium was adopted. Given the environmental ubiquity of the genus Aeromonas, the findings in this work may facilitate a better understanding about the transformation behaviors and fates of Cr(VI) in environments and provide useful clues to tune the bioremediation of chromium-contaminated environments. Keywords: Chromium, Chromium-contaminated environments, Bioreduction, Aeromonas, Organo-Cr(III) complexes, Medium composition

Depolymerized lignin products are very complex mixtures. Based on a depolymerization solution of commercially available sodium lignosulfonate under mild conditions, a fast and efficient method for the separation and direct characterization of the degree and efficiency of the acid-catalyzed depolymerization of lignin was developed in this study. Using an ultraviolet detector, the depolymerized lignosulfonate products were well separated and characterized according to the relative molar mass distribution on an advanced polymer chromatographic system with three ethylene-bridged hybrid columns having small pore sizes (45 A) in series and tetrahydrofuran as the mobile phase. The developed advanced polymer chromatography method enabled the detection of low-molecular-weight lignin degradation products (Mn = 260-1100 Da) with high peak resolutions in less than 7.2 min. Furthermore, preliminary advanced polymer chromatography studies to determine the influence of reaction temperature on the depolymerized products indicated that the depolymerized aromatics fell in several molecular weight ranges with an extremely low dispersity. This new approach can be used for the rapid analysis of lignin depolymerization products.

The development of optical imaging techniques has led to significant advancements in single-nanoparticle tracking and analysis, but these techniques are incapable of label-free selective nanoparticle recognition. A label-free plasmonic imaging technology that is able to identify different kinds of nanoparticles in water is now presented. It quantifies the plasmonic interferometric scattering patterns of nanoparticles and establishes relationships among the refractive index, particle size, and pattern both numerically and experimentally. Using this approach, metallic and metallic oxide particles with different radii were distinguished without any calibration. The ability to optically identify and size different kinds of nanoparticles can provide a promising platform for investigating nanoparticles in complex environments to facilitate nanoscience studies, such as single-nanoparticle catalysis and nanoparticle-based drug delivery.

Agricultural landscapes in mountainous areas are facing the destruction due to farmland abandonment. A sustainable conservation mechanism is needed urgently for the rural areas in these places. Dazhai terraces of Longji Terraces, Southwest China are maintained well based on agricultural multi-functions developed by multi-stakeholders. From the perspective of household economics, this study examined the income structure of households in Dazhai and estimated every household’s income based on the collected data via semi-structural interviews and the statistical data. In Dazhai, the income of households is mainly comprised of agricultural income, compensation for maintaining terraces (CMT), tourism income dividend (TID) and income of local non-farm jobs (IINJ). The IINJ and the TID constitute the most and the second more part of the household incomes, respectively, which account for 70.8% and 17.8% of the total household incomes. The agricultural income just plays a slight role in improving the household incomes. 97.7% of households in Dazhai earn a higher income a year from the agricultural multi-functions than those migrant workers in the region. The sustainable high income from terraced multi-functions is the main driving force to maintain Dazhai terraces. The multi-functions of Dazhai terraces are developed jointly by local governments, companies and villagers. More importantly, these stakeholders’ cooperation rests on the reasonable benefit distribution principles between companies and Dazhai and among villagers in Dazhai. In sum, the benefit distribution mechanisms drive multiple stakeholders to maintain terraced landscapes directly or indirectly.

In this paper, a novel protocol for asymmetric bidirectional controlled quantum teleportation (ABCQT) by using the nine-qubit entangled state as a quantum channel is proposed. Alice transmits an arbitrary three-qubit entangled state to Bob and at the same time, Bob transmits an arbitrary single-qubit entangled state to Alice under the permission of a third party as a controller. This protocol is based on the Hadamard (H) gates, controlled-not (CNOT) operations, appropriate unitary operations, and single-qubit Von Neumann measurements (SM) which are more efficient than multi-qubit joint measurements (JM). This scheme explicitly shows how the channel of nine-qubit entangled state prepares, and it is discussed in six types of noisy scenarios (amplitude-damping, phase-damping, bit-flip, phase-flip, bit-phase-flip, and depolarizing noisy scenarios). Then, we analytically derive the fidelities of the ABCQT process and show that they only depend on the amplitude parameter of the initial state and the decoherence noisy rate. Finally, compared with previous schemes, this scheme also shows remarkable advantages.

Leaf water status determination based on mechanical and electrophysiological properties helps determine the inherent as well as instantaneous leaf dehydration tolerance synchronously. The leaf water potential (ΨL), physiological capacitance (CP) and gripping force (F) were determined with leaves of Broussonetia papyrifera (L.) Vent. and Morus alba L. Real-time leaf stiffness (LCSrt) and maximum leaf stiffness (LCSmax) were investigated by compressing a leaf with external gripping force. Results indicated that LT displayed good correlation with F. Compared to M. alba, a better instantaneous dehydration tolerance or pressure resistance in B. papyrifera was correlated to its persistent stronger LCSrt or LCSmax, respectively. B. papyrifera showed better flexibility and tolerance to wider range of pressure than M. alba. The higher leaf mechanical strength helped to maintain a higher outward pulling force of cell walls; thus, the subsequent negative pressure effectively inhibited cellular water loss. B. papyrifera exhibited better drought resistance than M. alba.

A novel scheme is proposed in this paper, which realizes the cyclic and bidirectional teleportation via pseudo multi-qubit entangled states. To realize the teleportation completely, it utilizes controlled-NOT operation to obtain a quantum channel whose number of qubits reaches twelve. In this scheme, Alice can teleport her qubits to Bob and Charlie, Bob can teleport his qubits to Alice and Charlie while Charlie teleports his qubits to Alice and Bob, respectively, they reconstruct the original state and make the scheme perfectly by performing Bell-state measurement and appropriate unitary operation.

Bicycle-metro integration is theoretically considered to be an effective solution for improving public transportation efficiency of “last mile” between home and metro station in cities. However, th...

NACs are important transcriptional factors involved in growth and development as well as responses to abiotic and biotic stresses in plants. In this study, TaNAC6 was identified as a differentially expressed gene between two lines with broad-spectrum resistance to powdery mildew, NAU9918 and OEStpk-V, and their corresponding susceptible isogenic lines, SM-1 and Yangmai158, after Bgt inoculation by transcriptome analysis. Then, three homoeologous genes of TaNAC6 were cloned and named as TaNAC6-A, TaNAC6-B and TaNAC6-D, respectively. Each member of TaNAC6s was subcellular localized to the nucleus and displayed the transcriptional activation activity. However, the responses of them to pathogens and phytohormones were different. Transient overexpression of each TaNAC6 reduced the haustorium index of Yangmai158, and stable transformation of TaNAC6-A enhanced its resistance against Bgt, implying that TaNAC6s play important roles in basal resistance. Silencing of TaNAC6s compromised the resistance of OEStpk-V and NAU9918 suggesting that TaNAC6s play positive roles in the broad-spectrum resistance against Bgt. TaNAC6s might be induced by JA and then feedback regulate the JA pathway leading to improved resistance to Bgt. The role of TaNAC6s and their orthologous genes HvNAC6 and ATAF1 in the powdery mildew resistance implied these NAC6 genes share a common signal pathway across species.

Probing molecular interactions is critical for screening drugs, detecting pollutants, and understanding biological processes at the molecular level, but these interactions are difficult to detect, especially for small molecules. A label-free optical imaging technology that can detect molecule binding kinetics is presented, in which free-moving particles are driven into oscillations with an alternating electrical field and the interferometric scattering patterns of the particles are imaged via an optical imaging method. By tracking the charge-sensitive variations in the oscillation amplitude with sub-nanometer precision, the small molecules and metal ions binding to the surface as well as protein-protein binding kinetics were measured. The capability of the label-free measurement of molecular interactions can provide a promising platform for screening small-molecule drugs, probing conformational changes in proteins, and detecting environmental pollutants.

The geography patterns and generation mechanisms of greenhouse gases (GHGs) in groundwater, especially in saline groundwater, are critical but rarely studied. Herein, we investigated the GHGs distribution in an aquifer, located upstream of Baiyangdian Lake, China, with a distinctive salinity gradient. A total of 132 groundwater samples were collected from 44 new-constructed wells along the lateral dimensions, and analyzed for dissolved GHGs concentrations, physiochemical parameters, and isotopes. The results showed that the dissolved CO2, CH4 and N2O concentrations ranged from 9.47 to 79.3 mg/L, 1.05–56.9 μg/L, and 0.84–7.03 μg/L, respectively. The groundwater was supersaturated with GHGs with respect to atmospheric equilibrium, suggesting groundwater discharge as a potential source of GHGs emission. CO2 significantly decreased while CH4 and N2O distinctively increased with the decline of total dissolved solids (TDS) concentration, illustrating an obvious spatial pattern in the GHGs distribution. The CO2 distributions mainly depended on the bicarbonate radical and TDS, indicating carbonate equilibrium as the main process involving in the CO2 generation. CH4 and N2O was primarily generated through the methanogenesis and denitrification processes, respectively. Nutrients including SO42− and total organic carbon predominately shaped the CH4 distributions, while nitrate mainly governed the N2O distributions. Our study highlights the important roles of hydrochemistry and nutrients in the GHGs generation and distributions, which provides a significant insight on managing the GHGs emissions from the saline groundwater.

The ability to track interfacial dynamics of a single nanoparticle at the solution-solid interface is crucial for understanding physical, chemical, and biological processes, but it remains a challenge. Here, we demonstrated a plasmonic imaging technique that can track unlabeled nanoparticles at the solution-solid interface with high spatial and temporal resolutions. This technique is based on particle-induced interferometric scattering of a surface plasmonic wave, which results in a high vertical sensitivity. Using this ability, we tracked the trajectories of a single nanoparticle interacting with a surface, measured the hydrodynamically hindered diffusion of nanoparticles, and revealed the surface chemistry-dependent behavior of nanoparticles at the interface. The application for tracking formation of membranes from a lipid vesicle was demonstrated, indicating the potential for investigating a broad range of nano-objects at interfaces in a complex environment.

Text classification in low-resource languages (eg Thai) is of great practical value for some information retrieval applications (eg sentiment-analysis-based restaurant recommendation). Due to lacking large-scale corpus for learning comprehensive text representation, bilingual text classification which borrows the linguistics knowledge from a rich-resource language becomes a promising solution. Despite the success of bilingual methods, they largely ignore another source of semantic information---the writing system. Noting that most low-resource languages are phonographic languages, we argue that a logographic language (eg Chinese) can provide helpful information for improving some phonographic languages' text classification, since a logographic character (ie logogram) could represent a sememe or a whole concept, not only a phoneme or a sound. In this paper, by using a phonographic labeled corpus and its machine-translated logographic corpus both, we devise a framework to explore the central theme of utilizing logograms as a "semantic detection assistant''. Specifically, from a logographic labeled corpus, we first devise a statistical-significance-based module to pick out informative text pieces. To represent them and further reduce the effects of translation errors, our approach is equipped with Gaussian embedding whose covariances serve as reliable signals of translation errors. For a test document, all seeds' Gaussian representations are used to convolute the document and produce a logographic embedding, before being fused with its phonographic embedding for final prediction. Extensive experiments validate the effectiveness of our approach and further investigations show its generalizability and robustness.

An efficient synthesis of bisisothiazole-4-yl disulfides via the demethoxylative thioannulation of alkynyl oxime ethers with odorless elemental sulfur has been first developed. This transformation involves the N-O bond cleavage, the formation of multiple C-S and N-S bonds, providing an efficient way for constructions of both isothiazoles and disulfides. Straightforward elaboration of the products to isothiazole thioethers expands the synthetic utility of this reaction.

Artificial light-harvesting systems have attracted great interest in biological photosynthesis and photo-voltaic devices areas due to their unique structures, easy purification, low-cost, and convenient processing abilities. Here, two dendritic molecules based on triphenylamine and naphthalimide have been designed and synthesized, their structures were confirmed by 1 H NMR, ESI-MS, and high resolution mass spectrometry. In these molecules, triphenylamine units perform as the electron donor moiety, and naphthalimide units perform as the electron acceptor. The obvious quenched fluorescence intensity and considerably shortened lifetime of the dendritic molecules combined with the molecular frontier orbital energy levels proved that the dendritic molecules not only are good candidates as hole-transporting materials but also are two excellent photo-induced electron transfer materials. Therefore, it is believed that these dendritic molecules have potential application value in photo-voltaic devices.

High water content is hard to be achieved in conductive hydrogels because a mass of conductive constituent is needed to form an internal conductive pathway. Here, we developed anisotropic electrically conductive hydrogels with high water content based on bacterial cellulose (BC). Polystyrene sulfonate (PSS) was grafted to the acryloyl chloride-modified BC to provide a template for the subsequent synthesis of poly(3,4-ethylenedioxythiophene) (PEDOT). The BC

Polyacrylonitrile fiber was successfully modified with triazine-based dendrimer via grafting method as a promising adsorbent for removal of mercury species from aqueous media. The prepared adsorbent was characterized by elemental analysis, scanning electron microscope, Fourier transform infrared spectroscopy, porous structure analysis and X-ray photoelectron spectroscopy, providing the evidence of successful fabrication. The adsorption conditions were found via varying pH, dosage, coexisting substances, contact time, temperature and concentration. Adsorption performance, described better by the pseudo-second-order kinetics with intraparticle diffusion as rate controlling step and Langmuir isotherm model, indicated a chemisorption process with the maximum Langmuir adsorption amount of 227.64 mg g−1 for mercury ions. Thermodynamically, adsorption of mercury ions was spontaneous and endothermic. Desorption and regeneration experiments demonstrated that it could be reused in five successive adsorption cycles without significant loss of its original performance. Experimental data and density functional theory calculation disclosed the coordination geometries and chelating mechanism between the adsorbent and mercury ions. The proposed study would provide a new prospect for the purification of mercury in aqueous system by functionalizing commercial polyacrylonitrile fiber with dendrimers.

The uncertainty principle, first introduced by Heisenberg in inertial frames, clearly distinguishes quantum theories from classical mechanics. In non-inertial frames, its information-theoretic expressions, namely entropic uncertainty relations, have been extensively studied through delocalized quantum fields, and localization of the quantum fields were discussed as well. However, infeasibility of measurements applied on a delocalized quantum field due to the finite size of measurement apparatuses is left unexplained. Therefore, physical clarification of a quantum protocol revealing entropic uncertainty relations still needs investigation. Building on advances in quantum field theories and theoretical developments in entropic uncertainty relations, we demonstrate a relativistic protocol of an uncertainty game in the presence of localized fermionic quantum fields inside cavities. Moreover, a novel lower bound for entropic uncertainty relations with multiple quantum memories is given in terms of the Holevo quantity, which implies how acceleration affects uncertainty relations., 9 pages, 3 figures

The analysis of plasma microRNAs (miRNAs) has been widely used as a method for finding potential biomarkers for human diseases, especially those with a link to cancer. Methods of analyzing plasma miRNA have been thoroughly discussed from sample extraction to data modeling. However, some issues exist within the process that have rarely been talked about. Rice et al. discussed some issues in plasma miRNA studies, such as the lack of standard methodology including the use of different cycle threshold, time to plasma extraction, among others. These issues can lead to inconsistent data, and thus impact the result and assay reproducibility. Other external issues, such as batch effect and operator effect, may also indirectly impact the statistical analysis. Here, we discuss issues in plasma miRNA studies from a statistical point of view. The interaction effect of different ways of calculating fold-change, the choice of housekeeping genes, and methods of normalization are among the issues we discuss, with data demonstrations. P values are calculated and compared to determine the effect of those issues on statistical conclusions. Statistical methods such as analysis of variance and analysis of covariance are crucial in the analysis of miRNA but investigators are often confused about them; therefore, a brief explanation of these statistical methods is also included. In addition, 3-group classification is discussed, as it is often challenging, compared with 2-group classification.

Training a supernet matters for one-shot neural architecture search (NAS) methods since it serves as a basic performance estimator for different architectures (paths). Current methods mainly hold the assumption that a supernet should give a reasonable ranking over all paths. They thus treat all paths equally, and spare much effort to train paths. However, it is harsh for a single supernet to evaluate accurately on such a huge-scale search space (e.g., $7^{21}$). In this paper, instead of covering all paths, we ease the burden of supernet by encouraging it to focus more on evaluation of those potentially-good ones, which are identified using a surrogate portion of validation data. Concretely, during training, we propose a multi-path sampling strategy with rejection, and greedily filter the weak paths. The training efficiency is thus boosted since the training space has been greedily shrunk from all paths to those potentially-good ones. Moreover, we further adopt an exploration and exploitation policy by introducing an empirical candidate path pool. Our proposed method GreedyNAS is easy-to-follow, and experimental results on ImageNet dataset indicate that it can achieve better Top-1 accuracy under same search space and FLOPs or latency level, but with only $\sim$60\% of supernet training cost. By searching on a larger space, our GreedyNAS can also obtain new state-of-the-art architectures., To appear in CVPR 2020

Keypoint-based detectors have achieved pretty-well performance. However, incorrect keypoint matching is still widespread and greatly affects the performance of the detector. In this paper, we propose CentripetalNet which uses centripetal shift to pair corner keypoints from the same instance. CentripetalNet predicts the position and the centripetal shift of the corner points and matches corners whose shifted results are aligned. Combining position information, our approach matches corner points more accurately than the conventional embedding approaches do. Corner pooling extracts information inside the bounding boxes onto the border. To make this information more aware at the corners, we design a cross-star deformable convolution network to conduct feature adaption. Furthermore, we explore instance segmentation on anchor-free detectors by equipping our CentripetalNet with a mask prediction module. On MS-COCO test-dev, our CentripetalNet not only outperforms all existing anchor-free detectors with an AP of 48.0% but also achieves comparable performance to the state-of-the-art instance segmentation approaches with a 40.2% MaskAP. Code will be available at https://github.com/KiveeDong/CentripetalNet., Accepted by CVPR2020

The real-world networks often compose of different types of nodes and edges with rich semantics, widely known as heterogeneous information network (HIN). Heterogeneous network embedding aims to embed nodes into low-dimensional vectors which capture rich intrinsic information of heterogeneous networks. However, existing models either depend on manually designing meta-paths, ignore mutual effects between different semantics, or omit some aspects of information from global networks. To address these limitations, we propose a novel Graph-Aggregated Heterogeneous Network Embedding (GAHNE), which is designed to extract the semantics of HINs as comprehensively as possible to improve the results of downstream tasks based on graph convolutional neural networks. In GAHNE model, we develop several mechanisms that can aggregate semantic representations from different single-type sub-networks as well as fuse the global information into final embeddings. Extensive experiments on three real-world HIN datasets show that our proposed model consistently outperforms the existing state-of-the-art methods.

We present a lightweight video motion retargeting approach TransMoMo that is capable of transferring motion of a person in a source video realistically to another video of a target person. Without using any paired data for supervision, the proposed method can be trained in an unsupervised manner by exploiting invariance properties of three orthogonal factors of variation including motion, structure, and view-angle. Specifically, with loss functions carefully derived based on invariance, we train an auto-encoder to disentangle the latent representations of such factors given the source and target video clips. This allows us to selectively transfer motion extracted from the source video seamlessly to the target video in spite of structural and view-angle disparities between the source and the target. The relaxed assumption of paired data allows our method to be trained on a vast amount of videos needless of manual annotation of source-target pairing, leading to improved robustness against large structural variations and extreme motion in videos. We demonstrate the effectiveness of our method over the state-of-the-art methods. Code, model and data are publicly available on our project page (https://yzhq97.github.io/transmomo)., Comment: Accepted by CVPR 2020. The first three authors contributed equally. Project page: https://yzhq97.github.io/transmomo/

Remarkable progress has been made in 3D human pose estimation from a monocular RGB camera. However, only a few studies explored 3D multi-person cases. In this paper, we attempt to address the lack of a global perspective of the top-down approaches by introducing a novel form of supervision - Hierarchical Multi-person Ordinal Relations (HMOR). The HMOR encodes interaction information as the ordinal relations of depths and angles hierarchically, which captures the body-part and joint level semantic and maintains global consistency at the same time. In our approach, an integrated top-down model is designed to leverage these ordinal relations in the learning process. The integrated model estimates human bounding boxes, human depths, and root-relative 3D poses simultaneously, with a coarse-to-fine architecture to improve the accuracy of depth estimation. The proposed method significantly outperforms state-of-the-art methods on publicly available multi-person 3D pose datasets. In addition to superior performance, our method costs lower computation complexity and fewer model parameters.

Process model extraction (PME) is a recently emerged interdiscipline between natural language processing (NLP) and business process management (BPM), which aims to extract process models from textual descriptions. Previous process extractors heavily depend on manual features and ignore the potential relations between clues of different text granularities. In this paper, we formalize the PME task into the multi-grained text classification problem, and propose a hierarchical neural network to effectively model and extract multi-grained information without manually-defined procedural features. Under this structure, we accordingly propose the coarse-to-fine (grained) learning mechanism, training multi-grained tasks in coarse-to-fine grained order to share the high-level knowledge for the low-level tasks. To evaluate our approach, we construct two multi-grained datasets from two different domains and conduct extensive experiments from different dimensions. The experimental results demonstrate that our approach outperforms the state-of-the-art methods with statistical significance and further investigations demonstrate its effectiveness.

The goal of the Semantic Scene Completion (SSC) task is to simultaneously predict a completed 3D voxel representation of volumetric occupancy and semantic labels of objects in the scene from a single-view observation. Since the computational cost generally increases explosively along with the growth of voxel resolution, most current state-of-the-arts have to tailor their framework into a low-resolution representation with the sacrifice of detail prediction. Thus, voxel resolution becomes one of the crucial difficulties that lead to the performance bottleneck. In this paper, we propose to devise a new geometry-based strategy to embed depth information with low-resolution voxel representation, which could still be able to encode sufficient geometric information, e.g., room layout, object's sizes and shapes, to infer the invisible areas of the scene with well structure-preserving details. To this end, we first propose a novel 3D sketch-aware feature embedding to explicitly encode geometric information effectively and efficiently. With the 3D sketch in hand, we further devise a simple yet effective semantic scene completion framework that incorporates a light-weight 3D Sketch Hallucination module to guide the inference of occupancy and the semantic labels via a semi-supervised structure prior learning strategy. We demonstrate that our proposed geometric embedding works better than the depth feature learning from habitual SSC frameworks. Our final model surpasses state-of-the-arts consistently on three public benchmarks, which only requires 3D volumes of 60 x 36 x 60 resolution for both input and output. The code and the supplementary material will be available at https://charlesCXK.github.io., Comment: Accepted by CVPR 2020

Sufficient knowledge extraction from the teacher network plays a critical role in the knowledge distillation task to improve the performance of the student network. Existing methods mainly focus on the consistency of instance-level features and their relationships, but neglect the local features and their correlation, which also contain many details and discriminative patterns. In this paper, we propose the local correlation exploration framework for knowledge distillation. It models three kinds of local knowledge, including intra-instance local relationship, inter-instance relationship on the same local position, and the inter-instance relationship across different local positions. Moreover, to make the student focus on those informative local regions of the teacher’s feature maps, we propose a novel class-aware attention module to highlight the class-relevant regions and remove the confusing class-irrelevant regions, which makes the local correlation knowledge more accurate and valuable. We conduct extensive experiments and ablation studies on challenging datasets, including CIFAR100 and ImageNet, to show our superiority over the state-of-the-art methods.

The catalytic properties of ultrafine metal nanoparticles (NPs) are usually limited by their dispersion of NPs; support is thus needed for ultrafine metal NPs. However, single-dimensional supports ...

Recently, peroxymonosulfate (PMS)-based advanced oxidation processes have exhibited broad application prospects in the environment field. Accordingly, a simple, rapid, and ultrasensitive method is highly desired for the specific recognition and accurate quantification of PMS in various aqueous solutions. In this work, SO4•–-induced aromatic hydroxylation was explored, and based on that, for the first time, a novel fluorescence method was developed for the PMS determination using Co2+ as a PMS activator and benzoic acid (BA) as a chemical probe. Through a suite of spectral, chromatographic, and mass spectrometric analyses, SO4•– was proven to be the dominant radical species, and salicylic acid was identified as the fluorescent molecule. As a result, a whole radical chain reaction mechanism for the generation of salicylic acid in the BA/PMS/Co2+ system was proposed. This fluorescence method possessed a rapid reaction equilibrium (

PVDF pyroelectric sensor has been widely applied in many fields, such as intruder alarm. Nowadays, this sensor shows a potential for ultrasonic power measurement. However, the transformation mechanism between the acoustic and pyroelectric signals has not been particularly studied until now. In this paper, a physical model was introduced for theoretical study of the mechanism of energy transformations. In addition, a simulation program based on finite-element analysis method was built up for analyzing the ultrasound propagation characteristics and the temperature rise on the PVDF, as well it predicted the waveform and amplitude of the generated pyroelectric signal. Besides that, a PVDF pyroelectric sensor was fabricated and used for acoustic power measurement experiment. Finally, the experiment and simulation results were compared, confirming that the physical model is suitable for pyroelectric sensor characteristics analysis. It can also provide useful suggestions for the design and fabrication of PVDF pyroelectric sensors with high sensitivity.

Membrane fouling remains a major challenge for applying membrane technology to water treatment and, therefore, new tools to recognize the key foulants are essential for characterizing and evaluating the membrane fouling process. In this work, fluorescence excitation emission matrix coupled with parallel factor framework-clustering analysis was used to investigate the membrane fouling during the filtration process of humic acid (HA) and bovine serum albumin (BSA) solution by polyvinylidene fluoride membrane. Interestingly, the interaction between BSA and HA in the membrane fouling process was observed, and was further confirmed by infrared microspectroscopy and two-dimensional correlation spectroscopic analysis. In addition, the HA-induced membrane fouling was observed to be initially relieved, but became aggravated when a certain amount of BSA was added. Furthermore, with such an integrated approach, the OH groups in HA and amide bands in BSA were found to be mainly responsible for the membrane fouling and the HA-BSA interaction was mainly caused by the encapsulation of BSA with HA. This work develops a new method for probing membrane fouling and demonstrates the interaction between membrane foulants and its roles in membrane fouling process. Furthermore, the integrated approach developed in this work has a potential to explore other types of interfacial interactions.

Ultraviolet/hydrogen peroxide (UV/H2O2) pre-oxidation has the potential to induce reactions with dissolved organic matter (DOM) and alter the generation of disinfection byproducts (DBPs). This study evaluated the influence of UV/H2O2 pretreatment on the formation of iodo-trihalomethanes (I-THMs) during disinfection with chlorine or chloramine. The changes of precursors, I- and Br-, after UV/H2O2 pretreatment were investigated, and then, the formation and speciation of I-THMs during chlorination or chloramination after pre-oxidation were explored. Additionally, the effects of UV doses and H2O2 concentrations on the formation and speciation of I-THMs were studied. It was found that UV/H2O2 pretreatment could change larger molecular weight (MW) DOM to smaller MW species, which had less aromatic organic compounds and fluorescence substances. Additionally, insignificant transformations of I- and Br- were observed after UV/H2O2 treatment. Compared to direct disinfection, UV/H2O2 pretreatment resulted in 23.0 ± 3.5% reduction in I-THMs formation during post-chlorination while an enhancement was observed during post-chloramination at a UV dose of 460 mJ/cm2 and 20 mg/L H2O2. Moreover, total I-THM concentration increased from 43.7 ± 2.4 to 97.6 ± 14.9 nM with the increase of UV doses from 0 to 1400 mJ/cm2 during the post-chlorination process, while reduced when the UV fluence was >460 mJ/cm2 during the post-chloramination. Additionally, the generation of I-THMs during both post-chlorination and post-chloramination was positively related to the H2O2 levels from 0 to 20 mg/L in the UV/H2O2 pretreatment.

In this paper, a novel scheme of bidirectional quantum teleportation is proposed, where two-qubit states are transferred into single qubit superposition by Alice and Bob respectively using controlled-NOT operation, meanwhile the four-qubit cluster states are utilized as quantum channel. Our main novelty, which is the significant difference from other schemes of bidirectional (controlled) quantum teleportation, is: as the receivers, the both legitimate users can reconstruct the target two-qubit states through the corresponding unitary operation and controlled-NOT transmission to realize the more efficient teleportation.

The interaction between cellulose and hemicelluloses is of fundamental importance for understanding the molecular architecture of plant cell walls. Adsorption of xyloglucan (XG) onto regenerated cellulose (RC), sulfated cellulose nanocrystal (s-CNC), and desulfated cellulose nanocrystal (d-CNC) films was studied by quartz crystal microbalance with dissipation monitoring, surface plasmon resonance, and atomic force microscopy. The amount of XG adsorbed onto different cellulose substrates increased in the order RC < s-CNC < d-CNC. The adsorption of XG onto RC films was independent of film thickness (d), whereas XG adsorption was weakly dependent on d for s-CNC films and strongly dependent on d for d-CNC films. However, approximately the same amount of XG adsorbed onto “monolayer-thin” films of RC, s-CNC, and d-CNC. These results suggest that the morphology and surface charge of the cellulose substrate played a limited role in XG adsorption and highlight the importance of film thickness of cellulose nanocrystalline films to XG adsorption.