Topological kink states at a tilt boundary in gated multi-layer graphene

The search for new realization of topologically protected edge states is an active area of research. We show that a tilt boundary in gated multi-layer graphene supports topologically protected gapless kink states, associated with quantum valley Hall insulator (QVH). We investigate such kink states from two perspectives: the microscopic perspective of a tight-binding model and an ab-initio calculation on bilayer, and the perspective of symmetry protected topological (SPT) states for general multi-layer. We show that a AB-BA bilayer tilt boundary supports gapless kink states that are undeterred by strain concentrated at the boundary. Further, we establish the kink states as concrete examples of edge states of {\it time-reversal symmetric} ${\mathbb Z}$-type SPT, protected by no valley mixing, electron number conservation, and time reversal $T$ symmetries. This allows us to discuss possible phase transitions upon symmetry changes from the SPT perspective. Recent experimental observations of a network of such tilt boundaries suggest that transport through these novel topological kink states might explain the long standing puzzle of sub-gap conductance. Further, recent observation of gap closing and re-opening in gated bi-layer might be the first example of a transition between two distinct SPT's: QVH and LAF.Comment: Improved a discussion of the structural aspects of the tilt boundary. Included a discussion of boundary condition dependence. Added new section on connection to experiment

Reaction mechanism and kinetics for CO₂ reduction on nickel single atom catalysts from quantum mechanics

Experiments have shown that graphene-supported Ni-single atom catalysts (Ni-SACs) provide a promising strategy for the electrochemical reduction of CO₂ to CO, but the nature of the Ni sites (Ni-N₂C₂, Ni-N₃C₁, Ni-N₄) in Ni-SACs has not been determined experimentally. Here, we apply the recently developed grand canonical potential kinetics (GCP-K) formulation of quantum mechanics to predict the kinetics as a function of applied potential (U) to determine faradic efficiency, turn over frequency, and Tafel slope for CO and H₂ production for all three sites. We predict an onset potential (at 10 mA cm⁻²) U_(onset) = −0.84 V (vs. RHE) for Ni-N₂C₂ site and U_(onset) = −0.92 V for Ni-N₃C₁ site in agreement with experiments, and U_(onset) = −1.03 V for Ni-N₄. We predict that the highest current is for Ni-N₄, leading to 700 mA cm⁻² at U = −1.12 V. To help determine the actual sites in the experiments, we predict the XPS binding energy shift and CO vibrational frequency for each site

Homologues of archaeal rhodopsins in plants, animals and fungi: structural and functional predications for a putative fungal chaperone protein

AbstractThe microbial rhodopsins (MR) are homologous to putative chaperone and retinal-binding proteins of fungi. These proteins comprise a coherent family that we have termed the MR family. We have used modeling techniques to predict the structure of one of the putative yeast chaperone proteins, YRO2, based on homology with bacteriorhodopsins (BR). Availability of the structure allowed depiction of conserved residues that are likely to be of functional significance. The results lead us to predict an extracellular protein folding function and a transmembrane proton transport pathway. We suggest that protein folding is energized by a novel mechanism involving the proton motive force. We further show that MR family proteins are distantly related to a family of fungal, animal and plant proteins that include the human lysosomal cystine transporter (LCT) of man (cystinosin), mutations in which cause cystinosis. Sequence and phylogenetic analyses of both the MR family and the LCT family are reported. Proteins in both families are of the same approximate size, exhibit seven putative transmembrane α-helical spanners (TMSs) and show limited sequence similarity. We show that the LCT family arose by an internal gene duplication event and that TMSs 1–3 are homologous to TMSs 5–7. Although the same could not be demonstrated statistically for MR family members, homology with the LCT family suggests (but does not prove) a common evolutionary pathway. Thus, TMSs 1–3 and 5–7 in both LCT and MR family members may share a common origin, accounting for their shared structural features

Macroscopic Dark Matter Detection with Gravitational Wave Experiments

We study signatures of macroscopic dark matter (DM) in current and future gravitational wave (GW) experiments. Transiting DM with a mass of $\sim10^5-10^{15}$ kg that saturates the local DM density can be potentially detectable by GW detectors, depending on the baseline of the detector and the strength of the force mediating the interaction. In the context of laser interferometers, we derive the gauge invariant observable due to a transiting DM, including the Shapiro effect, and adequately account for the finite photon travel time within an interferometer arm. In particular, we find that the Shapiro effect can be dominant for short-baseline interferometers such as Holometer and GQuEST. We also find that proposed experiments such as Cosmic Explorer and Einstein Telescope can constrain a fifth force between DM and baryons, at the level of strength $\sim 10^3$ times stronger than gravity for, e.g., kg mass DM with a fifth-force range of $10^6$ m.Comment: 40 pages, 6 figure

Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification

The target echo signals obtained by Synthetic Aperture Radar (SAR) and Ground Moving Target Indicator (GMTI platforms are mainly composed of two parts, the micro-Doppler signal and the target body part signal. The wheeled vehicle and the track vehicle are classified according to the different character of their micro-Doppler signal. In order to overcome the mode mixing problem in Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) is employed to decompose the original signal into a number of Intrinsic Mode Functions (IMF). The correlation analysis is then carried out to select IMFs which have a relatively high correlation with the micro-Doppler signal. Thereafter, four discriminative features are extracted and Support Vector Machine (SVM) classifier is applied for classification. The experimental results show that the features extracted after EEMD decomposition are effective, with up 90% success rate for classification using one feature. In addition, these four features are complementary in different target velocity and azimuth angles

Deep sequencing of HPV E6/E7 genes reveals loss of genotypic diversity and gain of clonal dominance in high-grade intraepithelial lesions of the cervix

Table S2. HPV E6/E7 sequencing: dideoxy (Sanger) vs. deep (Illumina). (PDF 236 kb

Practicable assessment of cochlear size and shape from clinical CT images

Abstract: There is considerable interpersonal variation in the size and shape of the human cochlea, with evident consequences for cochlear implantation. The ability to characterize a specific cochlea, from preoperative computed tomography (CT) images, would allow the clinician to personalize the choice of electrode, surgical approach and postoperative programming. In this study, we present a fast, practicable and freely available method for estimating cochlear size and shape from clinical CT. The approach taken is to fit a template surface to the CT data, using either a statistical shape model or a locally affine deformation (LAD). After fitting, we measure cochlear size, duct length and a novel measure of basal turn non-planarity, which we suggest might correlate with the risk of insertion trauma. Gold-standard measurements from a convenience sample of 18 micro-CT scans are compared with the same quantities estimated from low-resolution, noisy, pseudo-clinical data synthesized from the same micro-CT scans. The best results were obtained using the LAD method, with an expected error of 8–17% of the gold-standard sample range for non-planarity, cochlear size and duct length

Genomic Data Mining Reveals Abundant Uncharacterized Transporters in Coccidioides immitis and Coccidioides posadasii

Coccidioides immitis and Coccidioides posadasii are causative agents of coccidioidomycosis, commonly known as Valley Fever. The increasing Valley Fever cases in the past decades, the expansion of endemic regions, and the rising azole drug-resistant strains have underscored an urgent need for a better understanding of Coccidioides biology and new antifungal strategies. Transporters play essential roles in pathogen survival, growth, infection, and adaptation, and are considered as potential drug targets. However, the composition and roles of transport machinery in Coccidioides remain largely unknown. In this study, genomic data mining revealed an abundant, uncharacterized repertoire of transporters in Coccidioides genomes. The catalog included 1288 and 1235 transporter homologs in C. immitis and C. posadasii, respectively. They were further annotated to class, subclass, family, subfamily and range of substrates based on the Transport Classification (TC) system. They may play diverse roles in nutrient uptake, metabolite secretion, ion homeostasis, drug efflux, or signaling. This study represents an initial effort for a systems-level characterization of the transport machinery in these understudied fungal pathogens

Comparing Platforms for C. elegans Mutant Identification Using High-Throughput Whole-Genome Sequencing

Whole-genome sequencing represents a promising approach to pinpoint chemically induced mutations in genetic model organisms, thereby short-cutting time-consuming genetic mapping efforts.We compare here the ability of two leading high-throughput platforms for paired-end deep sequencing, SOLiD (ABI) and Genome Analyzer (Illumina; "Solexa"), to achieve the goal of mutant detection. As a test case we used a mutant C. elegans strain that harbors a mutation in the lsy-12 locus which we compare to the reference wild-type genome sequence. We analyzed the accuracy, sensitivity, and depth-coverage characteristics of the two platforms. Both platforms were able to identify the mutation that causes the phenotype of the mutant C. elegans strain, lsy-12. Based on a 4 MB genomic region in which individual variants were validated by Sanger sequencing, we observe tradeoffs between rates of false positives and false negatives when using both platforms under similar coverage and mapping criteria.In conclusion, whole-genome sequencing conducted by either platform is a viable approach for the identification of single-nucleotide variations in the C. elegans genome

A Hidden Markov Model for Copy Number Variant prediction from whole genome resequencing data

Motivation: Copy Number Variants (CNVs) are important genetic factors for studying human diseases. While high-throughput whole genome re-sequencing provides multiple lines of evidence for detecting CNVs, computational algorithms need to be tailored for different type or size of CNVs under different experimental designs. Results: To achieve optimal power and resolution of detecting CNVs at low depth of coverage, we implemented a Hidden Markov Model that integrates both depth of coverage and mate-pair relationship. The novelty of our algorithm is that we infer the likelihood of carrying a deletion jointly from multiple mate pairs in a region without the requirement of a single mate pairs being obvious outliers. By integrating all useful information in a comprehensive model, our method is able to detect medium-size deletions (200-2000bp) at low depth (<10× per sample). We applied the method to simulated data and demonstrate the power of detecting medium-size deletions is close to theoretical values. Availability: A program implemented in Java, Zinfandel, is available at http://www.cs.columbia.edu/~itsik/zinfandel