Highly tunable spin-dependent electron transport through carbon atomic chains connecting two zigzag graphene nanoribbons

Motivated by recent experiments of successfully carving out stable carbon atomic chains from graphene, we investigate a device structure of a carbon chain connecting two zigzag graphene nanoribbons with highly tunable spin-dependent transport properties. Our calculation based on the non-equilibrium Green's function approach combined with the density functional theory shows that the transport behavior is sensitive to the spin configuration of the leads and the bridge position in the gap. A bridge in the middle gives an overall good coupling except for around the Fermi energy where the leads with anti-parallel spins create a small transport gap while the leads with parallel spins give a finite density of states and induce an even-odd oscillation in conductance in terms of the number of atoms in the carbon chain. On the other hand, a bridge at the edge shows a transport behavior associated with the spin-polarized edge states, presenting sharp pure $\alpha$-spin and $\beta$-spin peaks beside the Fermi energy in the transmission function. This makes it possible to realize on-chip interconnects or spintronic devices by tuning the spin state of the leads and the bridge position.Comment: 7 pages, 9 figure

Intergenerational Test Generation for Natural Language Processing Applications

The development of modern NLP applications often relies on various benchmark datasets containing plenty of manually labeled tests to evaluate performance. While constructing datasets often costs many resources, the performance on the held-out data may not properly reflect their capability in real-world application scenarios and thus cause tremendous misunderstanding and monetary loss. To alleviate this problem, in this paper, we propose an automated test generation method for detecting erroneous behaviors of various NLP applications. Our method is designed based on the sentence parsing process of classic linguistics, and thus it is capable of assembling basic grammatical elements and adjuncts into a grammatically correct test with proper oracle information. We implement this method into NLPLego, which is designed to fully exploit the potential of seed sentences to automate the test generation. NLPLego disassembles the seed sentence into the template and adjuncts and then generates new sentences by assembling context-appropriate adjuncts with the template in a specific order. Unlike the taskspecific methods, the tests generated by NLPLego have derivation relations and different degrees of variation, which makes constructing appropriate metamorphic relations easier. Thus, NLPLego is general, meaning it can meet the testing requirements of various NLP applications. To validate NLPLego, we experiment with three common NLP tasks, identifying failures in four state-of-art models. Given seed tests from SQuAD 2.0, SST, and QQP, NLPLego successfully detects 1,732, 5301, and 261,879 incorrect behaviors with around 95.7% precision in three tasks, respectively

A new perspective on building efficient and expressive 3D equivariant graph neural networks

Geometric deep learning enables the encoding of physical symmetries in modeling 3D objects. Despite rapid progress in encoding 3D symmetries into Graph Neural Networks (GNNs), a comprehensive evaluation of the expressiveness of these networks through a local-to-global analysis lacks today. In this paper, we propose a local hierarchy of 3D isomorphism to evaluate the expressive power of equivariant GNNs and investigate the process of representing global geometric information from local patches. Our work leads to two crucial modules for designing expressive and efficient geometric GNNs; namely local substructure encoding (LSE) and frame transition encoding (FTE). To demonstrate the applicability of our theory, we propose LEFTNet which effectively implements these modules and achieves state-of-the-art performance on both scalar-valued and vector-valued molecular property prediction tasks. We further point out the design space for future developments of equivariant graph neural networks. Our codes are available at \url{https://github.com/yuanqidu/LeftNet}

Clinical efficacy of the combined use of levofloxacin and different courses of isoniazid and rifampicin in the treatment of mild spinal tuberculosis

Purpose: To investigate the clinical effectiveness of the combined use of levofloxacin and different courses of isoniazid and rifampicin in the treatment of mild spinal tuberculosis (TB). Methods: The clinic data of 100 patients with light spinal TB were retrospectively reviewed. A double-blind technique was used to divide the patients into 6-month treatment group (M6 group, n = 32), 12-month treatment group (M12 group, n = 34) and 18-month treatment group (M18 group, n = 34). All patients were given isoniazid and rifampicin, in combination with levofloxacin. The effects of the different treatment courses on mild spinal TB were determined. Results: There were significantly higher post-treatment levels of inflammatory factors in M6 group than in M12 and M18 groups (p < 0.001). Moreover, there were significantly higher Visual Analogue Scale (VAS) score and erythrocyte sedimentation rate (ESR), and larger focus size in M6 group than in M12 and M18 groups (p < 0.05). However, after treatment, M18 group had significantly higher total incidence of adverse reactions than M6 and M12 groups (p < 0.05). Conclusion: Compared with the short-course treatment, long-course treatment with isoniazid and rifampicin in combination with levofloxacin is more effective in reducing the levels of inflammatory factors and decreasing focus size in patients with mild spinal TB. However, patients given the 18-month treatment tend to develop more adverse reactions. Therefore, 12-month treatment with the combined therapy is a better therapeutic option

A common supersolid low-density skin sliperizing ice and toughening water surface

Skins of water and ice share the same attribute of supersolidity characterized by the identical H-O vibration frequency of 3450 cm-1. Molecular undercoordination and inter-electron-pair repulsion shortens the H-O bond and lengthen the O:H nonbond, leading to a dual process of nonbonding electron polarization. This relaxation-polarization process enhances the dipole moment, elasticity,viscosity, thermal stability of these skins with 25% density loss, which is responsible for the hydrophobicity and toughness of water skin and for the slippery of ice.Comment: arXiv admin note: text overlap with arXiv:1401.804

Hydrogen-bond relaxation dynamics : resolving mysteries of water ice

We present recent progress in understanding the anomalous behavior of water ice under mechanical compression, thermal excitation, and molecular undercoordination (with fewer than four nearest neighbors in the bulk) from the perspective of hydrogen (O:Hsingle bondO) bond cooperative relaxation. We modestly claim the resolution of upwards of ten best known puzzles. Extending the Ice Rule suggests a tetrahedral block that contains two H2O molecules and four O:Hsingle bondO bonds. This block unifies the density-geometry-size-separation of molecules packing in water ice. This extension also clarifies the flexible and polarizable O:Hsingle bondO bond that performs like a pair of asymmetric, coupled, H-bridged oscillators with short-range interactions and memory as well as extreme recoverability. Coulomb repulsion between electron pairs on adjacent oxygen atoms and the disparity between the O:H and the Hsingle bondO segmental interactions relax the O:Hsingle bondO bond length and energy cooperatively under stimulation. A Lagrangian solution has enabled mapping of the potential paths for the O:Hsingle bondO bond at relaxation. The Hsingle bondO bond relaxation shifts the melting point, O 1s binding energy, and high-frequency phonon frequency whereas the O:H relaxation dominates polarization, viscoelasticity, and the O:H dissociation energy. The developed strategies have enabled clarification of origins of the following observations: (i) pressure-induced proton centralization, phase transition-temperature depression and ice regelation; (ii) thermally induced four-region oscillation of the mass density and the phonon frequency over the full temperature range; and (iii) molecular-undercoordination-induced supersolidity that is elastic, hydrophobic, thermally stable, with ultra-low density. The supersolid skin is responsible for the slipperiness of ice, the hydrophobicity and toughness of water skin, and the bi-phase structure of nanodroplets and nanobubbles. Molecular undercoordination mediates the O:H and Hsingle bondO bond Debye temperatures and disperses the quasi-solid phase boundary, resulting in freezing point depression and melting point elevation. O:Hsingle bondO bond memory and water-skin supersolidity ensures a solution to the Mpemba paradox — hot water freezes faster than its cold. These understandings will pave the way toward unveiling anomalous behavior of H2O interacting with other species such as salts, acids and proteins, and excitation of H2O by other stimuli such as electrical and magnetic fields.Accepted versio

Hydrogen-bond memory and water-skin supersolidity resolving the Mpemba paradox

The Mpemba paradox, that is, hotter water freezes faster than colder water, has baffled thinkers like Francis Bacon, René Descartes, and Aristotle since B.C. 350. However, a commonly accepted understanding or theoretical reproduction of this effect remains challenging. Numerical reproduction of observations, shown herewith, confirms that water skin supersolidity [Zhang et al., Phys. Chem. Chem. Phys., DOI: 10.1039/C1034CP02516D] enhances the local thermal diffusivity favoring heat flowing outwardly in the liquid path. Analysis of experimental database reveals that the hydrogen bond (O:H–O) possesses memory to emit energy at a rate depending on its initial storage. Unlike other usual materials that lengthen and soften all bonds when they absorb thermal energy, water performs abnormally under heating to lengthen the O:H nonbond and shorten the H–O covalent bond through inter-oxygen Coulomb coupling [Sun et al., J. Phys. Chem. Lett., 2013, 4, 3238]. Cooling does the opposite to release energy, like releasing a coupled pair of bungees, at a rate of history dependence. Being sensitive to the source volume, skin radiation, and the drain temperature, the Mpemba effect proceeds only in the strictly non-adiabatic ‘source–path–drain’ cycling system for the heat “emission–conduction–dissipation” dynamics with a relaxation time that drops exponentially with the rise of the initial temperature of the liquid source.Published versio

Size, separation, structural order, and mass density of molecules packing in water and ice

The structural symmetry and molecular separation in water and ice remain uncertain. We present herewith a solution to unifying the density, the structure order and symmetry, the size (H-O length dH), and the separation (dOO = dL + dH or the O:H length dL) of molecules packing in water and ice in terms of statistic mean. This solution reconciles: i) the dL and the dH symmetrization of the O:H-O bond in compressed ice, ii) the dOO relaxation of cooling water and ice and, iii) the dOO expansion of a dimer and between molecules at water surface. With any one of the dOO, the density ρ(g·cm−3), the dL, and the dH, as a known input, one can resolve the rest quantities using this solution that is probing conditions or methods independent. We clarified that: i) liquid water prefers statistically the mono-phase of tetrahedrally-coordinated structure with fluctuation, ii) the low-density phase (supersolid phase as it is strongly polarized with even lower density) exists only in regions consisting molecules with fewer than four neighbors and, iii) repulsion between electron pairs on adjacent oxygen atoms dictates the cooperative relaxation of the segmented O:H-O bond, which is responsible for the performance of water and ice.Published versio

Thin-Layer Indium Oxide and Cobalt Oxyhydroxide Cobalt-Modified BiVO₄ Photoanode for Solar-Assisted Water Electrolysis

Fabrication of high-performance tandem cell for solar-assisted water cleavage requires an efficient photoanode with excellent bulk charge separation and surface injection. In light of that, we developed a hybrid photoanode using visible light absorber as main scaffold, a thin layer In₂O₃ middle layer to enhance charge separation in bulk and finally an active CoOOH catalyst as outer decoration for better surface charge injection. Bulk separation was mainly augmented by In₂O₃ addition, while the addition of CoOOH largely advanced photocurrent onset and elevated injection efficiency. The resultant photoanode delivered a high current density at low applied bias, showing promising prospect for incorporation into tandem cell for solar-assisted water electrolysis