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The development of oxidation catalysts that are resistant to sulfur poisoning is crucial for extending the lifespan of catalysts in real‐working conditions. Herein, we describe the design and synthesis of oxide‐metal interaction (OMI) catalyst under oxidative atmospheres. By using organic coated TiO2, an oxide/metal inverse catalyst with non‐classical oxygen‐saturated TiO2 overlayers were obtained at relatively low temperature. These catalysts were found to incorporate ultra‐small Pd metal and support particles with exceptional reactivity and stability for CO oxidation (under 21 vol % O2 and 10 vol % H2O). In particular, the core (Pd)‐shell (TiO2) structured OMI catalyst exhibited excellent resistance to SO2 poisoning, yielding robust CO oxidation performance at 120 °C for 240 h (at 100 ppm SO2 and 10 vol % H2O). The stability of this new OMI catalyst was explained through density functional theory (DFT) calculations that interfacial oxygen atoms at Pd−O−Ti sites (of oxygen‐saturated overlayers) serve as non‐metal active sites for low‐temperature CO oxidation, and change the SO2 adsorption from metal(d)‐to‐SO2(π*) back‐bonding to much weaker σ(Ti−S) bonding. [ABSTRACT FROM AUTHOR]

The development of oxidation catalysts that are resistant to sulfur poisoning is crucial for extending the lifespan of catalysts in real‐working conditions. Herein, we describe the design and synthesis of oxide‐metal interaction (OMI) catalyst under oxidative atmospheres. By using organic coated TiO2, an oxide/metal inverse catalyst with non‐classical oxygen‐saturated TiO2 overlayers were obtained at relatively low temperature. These catalysts were found to incorporate ultra‐small Pd metal and support particles with exceptional reactivity and stability for CO oxidation (under 21 vol % O2 and 10 vol % H2O). In particular, the core (Pd)‐shell (TiO2) structured OMI catalyst exhibited excellent resistance to SO2 poisoning, yielding robust CO oxidation performance at 120 °C for 240 h (at 100 ppm SO2 and 10 vol % H2O). The stability of this new OMI catalyst was explained through density functional theory (DFT) calculations that interfacial oxygen atoms at Pd−O−Ti sites (of oxygen‐saturated overlayers) serve as non‐metal active sites for low‐temperature CO oxidation, and change the SO2 adsorption from metal(d)‐to‐SO2(π*) back‐bonding to much weaker σ(Ti−S) bonding. [ABSTRACT FROM AUTHOR]

Zeolites are a promising support for Pd catalysts in lean methane (CH 4) combustion. Herein, three types of zeolites (H-MOR, H-ZSM-5 and H-Y) were selected to estimate their structural effects and deactivation mechanisms in CH 4 combustion. We show that variations in zeolite structure and surface acidity led to distinct changes in Pd states. Pd/H-MOR with external high-dispersing Pd nanoparticles exhibited the best apparent activity, with activation energy (E a) at 73 kJ/mol, while Pd/H-ZSM-5 displayed the highest turnover frequency (TOF) at 19.6 × 10−3 sec−1, presumably owing to its large particles with more step sites providing active sites in one particle for CH 4 activation. Pd/H-Y with dispersed PdO within pore channels and/or Pd2+ ions on ion-exchange sites yielded the lowest apparent activity and TOF. Furthermore, Pd/H-MOR and Pd/H-ZSM-5 were both stable under a dry condition, but introducing 3 vol.% H 2 O caused the CH 4 conversion rate on Pd/H-MOR drop from 100% to 63% and that on Pd/H-ZSM-5 decreased remarkably from 82% to 36%. The former was shown to originate from zeolite structural dealumination, and the latter principally owed to Pd aggregation and the loss of active PdO. [Display omitted] [ABSTRACT FROM AUTHOR]

This work proposes an intra-Class-confidence and inter-Class-confusion guided Dynamic Contrastive (CCDC) learning framework for medical image segmentation. A core contribution is to dynamically select the most expressive pixels to build positive and negative pairs for contrastive learning at different training phases. For the positive pairs, dynamically adaptive sampling strategies are introduced for sampling different sets of pixels based on their hardness (namely the easiest, easy, and hard pixels). For the negative pairs, to efficiently learn from the classes with high confusion degree w.r.t a query class (i.e., a class containing the query pixels), a new hard class mining strategy is presented. Furthermore, pixel-level representations are extended to the neighbourhood region to leverage the spatial consistency of adjacent pixels. Extensive experiments on the three public datasets demonstrate that the proposed method significantly surpasses the state-of-the-art. • Dynamically adapting sampling selects pixels based on their difficulty to form positive pairs. • The hard class mining strategy facilitates efficient learning from classes with high confusion relative to a query class, for constructing negative pairs. • A spatial prior expands pixel-level representations to neighboring regions, leveraging spatial coherence among adjacent pixels. [ABSTRACT FROM AUTHOR]

[Display omitted] • The oxygen vacancies content of 1-ZOG has increased by 46% compared to pure ZnO. • Under UV irradiation, the response of 1-ZOG sensor to 100 ppm n-butanol is 3.6 times that of pure ZnO, up to 636.81. • The response signal of 1-ZOG to n-butanol is at least 6.32 times that of other gases. N-butanol gas is a common volatile organic compound (VOC) that can pose a threat to human health and pollute the atmospheric environment. However, the n-butanol gas sensors suffer from low response and selectivity. Herein, we synthesized the Ga-doped ZnO (ZOG) sensors by one-step hydrothermal treatment and subsequent calcination. The oxygen vacancies content of 1-ZOG has increased by 46 % compared to pure ZnO. Rich oxygen vacancies can increase the response signal of 1-ZOG to 174.78 in darkness for 100 ppm n-butanol, which is 2.4 times that of ZnO. Furthermore, the gas sensing performance of 1-ZOG is improved by light excitation. Under UV irradiation, the response of 1-ZOG sensor to 100 ppm n-butanol is 3.6 times that of pure ZnO, up to 636.81. Meanwhile, the response signal of 1-ZOG to n-butanol is at least 6.32 times that of other gases under UV light, showing ultra-high selectivity. This study proved that both Ga doped and photo-excited are effective strategies for improving the sensitivity and selectivity of ZnO based gas sensors. [ABSTRACT FROM AUTHOR]

Herein, K-OMS-2 catalysts with different levels of Ca2+ loading were synthesized to investigate the influence of Ca2+ deposition on the catalytic oxidation of CB. The micromorphology, redox ability, oxygen species, and surface acidity of the prepared catalysts were analyzed via SEM, HR-TEM, H 2 -TPR, O 2 -TPD, Py-IR, and GC–MS. After the Ca addition, CB conversion on the catalyst was achieved at <220 °C and the polychlorinated by-product yield decreased significantly. Although CaCO 3 formation on the catalyst surface from Ca2+ caused a decline in number and fluidity of the surface lattice oxygen species, no significant impact on surface adsorbed oxygen species content was observed. Furthermore, CaCO 3 reacted with dissociated chlorine species (HCl and polychlorinated products generated in situ), which inhibited chlorine poisoning of the active phase. [ABSTRACT FROM AUTHOR]

In this paper, a novel one-bit feedback algorithm by exploiting cumulative positive feedback information is proposed to achieve carrier phase alignment at the receiver for distributed transmit beamforming. The proposed synchronization algorithm speeds up the convergence process by introducing a mechanism to increase the perturbation size adaptively, especially in situation with sudden change. Moreover, the proposed algorithm has the ability to track time-varying channels without the knowledge of channel state information. In situation with time-varying channels, the proposed algorithm not only has better convergence speed, but also provides better steady performance by compared with the existing algorithms. [ABSTRACT FROM AUTHOR]

The low percentage of pores at which droplets are formed results in lower production efficiency, which is one of the main issues hampering the application of microporous membrane emulsification on a large scale. The effect of microporous membrane pore activation on the droplet's formation and emulsion performance was systemically investigated by changing both transmembrane pressures and membrane wettability during membrane emulsification. It indicated that the high transmembrane pressure increased the pore activation ratio (the percentage of pores at which droplets are formed) by the growing flux. These induced the enhancements of emulsification efficiency and the degradation of emulsion performance. Different wettability of membrane inflow and outflow influenced the pore activation speed (the speed which droplets are formed at pores). It indicated that the wettability of membrane outflow had a key effect on droplet formation and the high pore activation speed avoided splashing for high emulsion performance. [ABSTRACT FROM AUTHOR]

• Nb modified Cu-HZSM-5 catalyst had high resistance to Cl poisoning. • H 2 O preferentially adsorbed at Nb-Cu interfaces. • Cl preferentially adsorbed Nb sites that protected Cu and ensured O 2 activation. • Inhibited CuCl 2 formation led to less polychlorinated byproducts. • Catalyst designed with multiple active centers can solve environmental challenge. In this article, we unveiled the feasibility of designing a multi-active center catalyst system for the efficient destruction of chlorinated organics. Cu-HZSM-5 catalysts modified by Nb were developed, which was subsequently utilized for the catalytic elimination of chlorobenzene (CB). The underlying reaction mechanisms, particularly H 2 O activation and Cl adsorption/desorption behaviors, were explored using in situ DRIFTS, H 2 O-TPD and Density Functional Theory (DFT) calculations. Experimental results indicated that Brønsted acidic HZSM-5 and Nb-OH provided sufficient H protons to react with Cl, forming the HCl at low temperature and facilitating the Cl desorption. H 2 O molecule preferentially adsorbed on Cu-Nb interfaces, followed by dissociation on Cu sites, which generated enriched hydroxyls to form HCl. Dissociated Cl preferentially adsorbed on Nb sites that protected the active Cu species and maintained the activation of gaseous O 2 , thereby hindering electrophilic chlorination to form more toxic polychlorinated byproducts. [ABSTRACT FROM AUTHOR]

• Pb loading deactivated the V 2 O 5 -WO 3 /TiO 2 catalyst by attacking the V O sites. • Reaction route of chlorobenzene oxidation was varied with the loading of excessive Pb. • Doped Pb in the TiO 2 lattice led to generation of Ti3+ and oxygen vacancies. • The presence of oxygen vacancies favored polychlorinated byproducts formation. • The Pb acted as a sink to capture Cl that hindered electrophilic chlorination. Catalytic elimination of chlorinated volatile organic compounds (CVOCs) from the industrial sources of emission usually confronted with catalyst deactivation and secondary pollution. As a widely used catalyst in selective catalytic reduction (SCR) of nitric oxides, V 2 O 5 -WO 3 /TiO 2 catalysts (denoted as VWT) have been also applied for eliminating the CVOCs, especially those from the municipal solid waste (MSW) incineration. However, the effect of heavy metals on the reaction characteristics of this catalyst is lack of exploration, which has been considered to be a main cause for catalyst deactivation. Herein, we investigated the effect of lead (Pb), a critical heavy meal in the flue gas of MSW incineration, on the catalytic elimination of chlorobenzene (CB) over the VWT catalyst. Variations of catalytic activity, CO 2 /HCl selectivity and chlorine adsorption/desorption behaviors were evaluated. In particular, the reaction byproducts with and without Pb loadings were qualitatively and quantitatively analyzed. It was noted that the loading of excessive Pb could change the reaction route over the VWT catalyst, leading to low CB oxidation efficiency and CO 2 selectivity. However, these Pb spices likely acted as "a sink" to capture the dissociated Cl that hindered the electrophilic chlorination reaction, and avoided the formation of more toxic polychlorinated byproducts. [ABSTRACT FROM AUTHOR]

• Discovery and confirmation that the oblique instabilities and slipping MR exists in 3D LTSTMR. • Discovery and confirmation that magnetic energy conversion is dominated by turbulence induced oblique instabilities in 3D LTSTMR. • Discovery and confirmation that turbulent acceleration is an independent acceleration mechanism. • Discovery and confirmation that charged particles can be accelerated at a longer time scale and to relativistic energies. Quantitatively analyzing the role of turbulence in the magnetic fluctuation-induced self-generating-organization region and the plasma turbulence-induced self-feeding-sustaining region, which is closely related to the evolution of null points and the magnetic helical structure, represents the key issues in understanding the magnetic energy release-conversion, plasma heating, and charged particles energization and acceleration in three-dimensional large temporal-spatial scale turbulent magnetic reconnection (3D LTSTMR). The first part of this two-paper series developed and validated the continuous kinetic-dynamic-hydro fully coupled temporal-spatial scale relativistic hybrid particle-in-cell and lattice Boltzmann (RHPIC-LBM) model and code for investigating the fine structure evolution of the 2.5D solar atmosphere LTSTMR activities. Based on the model and code developed in Part I, in this paper, we investigate the turbulence of the magnetic helical structure, current density vector fields, self-generating-organization magnetic potential vector fields, self-feeding-sustaining plasma motion, and the ion and electron acceleration of 3D LTSTMR with 100,000 CPU cores on the Tianhe-2 from National Supercomputer Center in Guang Zhou (NSCC-GZ). According to the simulation evidence, we discovered and confirmed the following results: (i) Slipping magnetic reconnection (MR) exists in the adjacent magnetic field lines (MFLs) during the compress-stretch-slip process on the quasi-separatrix layers (QSLs and MFLs drastically change and form a linkage span) and the adjacent MFLs' break-rejoin MR exists on the separatrix surfaces (SLs). Both are consistent to observations; (ii) The slipping MR (defined as 1st type MR) and the MFLs' break-rejoin MR (defined as 2nd type MR) are closely linked with the oblique and resistive tearing instabilities, respectively. In the 3D model, the 1st type MR forms O -type null points, while the 2nd type MR forms X -type null points. The magnetic energy conversion is dominated by turbulence-induced oblique instabilities in the 3D model instead of the resistive tearing instabilities in the 2D/2.5D model, which is consistent with the 3D observations; (iii) Magnetic energy conversion occurs in the interaction of the plasmoid-to-flux rope, plasmoid-to-plasmoid, and flux rope-to-flux rope. The turbulent acceleration is an independent acceleration mechanism in LTSTMR, induced by the interaction of waves-to-waves and waves-to-particles, which is different from the original hybrid acceleration mechanism (composed of parallel electric fields, betatron, shock and Fermi) ; (iv) Particles can be energized and accelerated at a longer time scale (−30 s) and can be accelerated to relativistic energies after being pre-accelerated by a Fermi-Betatron-shock wave acceleration process. These results are in agreement with the observations. [ABSTRACT FROM AUTHOR]

• Development and validation of a RHPIC-LBM for kinetic-dynamic-hydro LTSTMR. • Testing and validation of the RHPIC-LBM on Tianhe-2. • Investigation and validation of solar atmosphere activities. • All the simulation results agree well with observations and theories. Magnetic energy release conversion, plasma heating and charged particle energization-acceleration in the magnetic fluctuation-induced self-generating-organization region and the plasma turbulence-induced self-feeding-sustaining region are key issues for large temporal-spatial scale turbulent magnetic reconnection (LTSTMR; observed current sheet thickness to characteristic electron length, electron Larmor radius for low- β and electron inertial length for high- β , ratios on the order of 1010∼1011; observed evolution time to electron cyclotron time ratios on the order of 1010∼1011) that ranges from Earth's magnetosphere to solar eruptions and other astrophysical phenomena. As the first part of a two-paper series, this paper introduces a relativistic hybrid particle-in-cell and lattice Boltzmann (RHPIC-LBM) model that describes the continuous kinetic-dynamic-hydro fully coupled LTSTMR evolution process. First, based on the governing equations of resistive relativistic magnetohydrodynamics (MHD), the relativistic discrete distribution functions for a magnetic field (D3Q7), electric field (D3Q13), electromagnetic field (D3Q13), charged particle (D3Q19) and neutral particle (D3Q27) of different plasma species are obtained for the RHPIC-LBM lattice grid. Then, the numerical process, algorithm, pseudocode, flowchart and GPU-CPU heterogenous framework of the RHPIC-LBM are described. Finally, this model is tested and validated on Tianhe-2 from the National Supercomputer Center in Guang Zhou (NSCC-GZ) with 10,000 ∼ 100,000 CPU cores and 50∼120 hours per case. We investigate the solar atmosphere LTSTMR activities, including the picoscale (10 − 2 m ∼ 10 5 m), nanoscale (10 5 m ∼ 10 6 m), microscale (10 6 m ∼ 10 7 m), macroscale (10 7 m ∼ 10 8 m) and large hydroscale (10 8 m ∼ 10 9 m). All the simulation results are consistent with observations and theories. The validated model is applied to explore the turbulence evolution of the interactions of the magnetic helical structures in the 3D LTSTMR self-generating-organization magnetic field region and self-feeding-sustaining plasma region in Part II. [ABSTRACT FROM AUTHOR]

[Display omitted] • Composting performance persistently altered by green waste and sewage sludge ratio. • The ratio about 1:2 is the optimal raw material feeding strategy. • Higher fraction of sewage sludge intensifies potential bacterial cooperation. • Modules 1 and 4 in bacterial co-occurrence network would promote humification. • Bacterial properties explained the dominant variation of humic acid concentration. Composting with five levels of green waste and sewage sludge was compared to examine how feeding ratios affected composting performance with special focus on humification, and the underlying mechanisms. The results showed that the raw material ratio persistently affected compost nutrients and stability. Humification and mineralization were promoted by higher proportion of sewage sludge. Bacterial community composition and within-community relationships were also significantly affected by the raw material feeding ratio. Network analysis indicated that clusters 1 and 4 which dominated by Bacteroidetes, Proteobacteria, and Acidobacteria shown significantly positive correlation with humic acid concentration. Notably, the structural equational model and variance partitioning analysis demonstrated that bacterial community structure (explained 47.82% of the variation) mediated the effect of raw material feeding ratio on humification, and exceeded the effect of environmental factors (explained 19.30% of the variation) on humic acid formation. Accordingly, optimizing the composting raw material improves the composting performance. [ABSTRACT FROM AUTHOR]

• Present the methodologies and evaluation results for the cardiac segmentation algorithms selected from the submissions to the MS-CMRSeg challenge, in conjunction with MICCAI 2019. • Provide a fair and intuitive comparison between the supervised methods and UDA algorithms for cardiac segmentation. • Provide datasets and evaluation tools for an ongoing development of MS-CMR based cardiac segmentation algorithms. [Display omitted] Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suffering from myocardial infarction (MI). Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) provides an important protocol to visualize MI. However, compared with the other sequences LGE CMR images with gold standard labels are particularly limited. This paper presents the selective results from the Multi-Sequence Cardiac MR (MS-CMR) Segmentation challenge, in conjunction with MICCAI 2019. The challenge offered a data set of paired MS-CMR images, including auxiliary CMR sequences as well as LGE CMR, from 45 patients who underwent cardiomyopathy. It was aimed to develop new algorithms, as well as benchmark existing ones for LGE CMR segmentation focusing on myocardial wall of the left ventricle and blood cavity of the two ventricles. In addition, the paired MS-CMR images could enable algorithms to combine the complementary information from the other sequences for the ventricle segmentation of LGE CMR. Nine representative works were selected for evaluation and comparisons, among which three methods are unsupervised domain adaptation (UDA) methods and the other six are supervised. The results showed that the average performance of the nine methods was comparable to the inter-observer variations. Particularly, the top-ranking algorithms from both the supervised and UDA methods could generate reliable and robust segmentation results. The success of these methods was mainly attributed to the inclusion of the auxiliary sequences from the MS-CMR images, which provide important label information for the training of deep neural networks. The challenge continues as an ongoing resource, and the gold standard segmentation as well as the MS-CMR images of both the training and test data are available upon registration via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/mscmrseg/). [ABSTRACT FROM AUTHOR]