Pseudohexagonal Nb2O5 Anodes for Fast-Charging Potassium-Ion Batteries

High-rate batteries will play a vital role in future energy storage systems, yet while good progress is being made in the development of high-rate lithium-ion batteries, there is less progress with post-lithium-ion chemistry. In this study, we demonstrate that pseudohexagonal Nb2O5(TT-Nb2O5) can offer a high specific capacity (179 mAh g-1 ∼ 0.3C), good lifetime, and an excellent rate performance (72 mAh g-1 at ∼15C) in potassium-ion batteries (KIBs), when it is composited with a highly conductive carbon framework; this is the first reported investigation of TT-Nb2O5 for KIBs. Specifically, multiwalled carbon nanotubes are strongly tethered to Nb2O5 via glucose-derived carbon (Nb2O5@CNT) by a one-step hydrothermal method, which results in highly conductive and porous needle-like structures. This work therefore offers a route for the scalable production of a viable KIB anode material and hence improves the feasibility of fast-charging KIBs for future applications

Pseudohexagonal Nb2O5-Decorated Carbon Nanotubes as a High-Performance Composite Anode for Sodium Ion Batteries

Pseudohexagonal Nb2O5 (TT-Nb2O5) has been applied in sodium ion batteries (SIBs) for the first time. Lower synthesis temperatures, improved conductivity and stability were achieved by the introduction of a designed carbon framework. The TT-Nb2O5/carbon nanotube composite exhibits high specific capacity (135 mAh g−1 at 0.2 A g−1) in long cycles and good rate capability (53 mAh g−1 at high current density of 5 A g−1). The outstanding electrochemical performance is attributed to the superior electrical conductivity and connectivity, optimal mass transport conditions and the mechanical strength and durability established by the strongly linked TT-Nb2O5 and MWCNT network. This study provides a cost-effective route to the application of Nb2O5 in SIBs

Genome scan linkage analysis comparing microsatellites and single-nucleotide polymorphisms markers for two measures of alcoholism in chromosomes 1, 4, and 7

BACKGROUND: We analyzed 143 pedigrees (364 nuclear families) in the Collaborative Study on the Genetics of Alcoholism (COGA) data provided to the participants in the Genetic Analysis Workshop 14 (GAW14) with the goal of comparing results obtained from genome linkage analysis using microsatellite and with results obtained using SNP markers for two measures of alcoholism (maximum number of drinks -MAXDRINK and an electrophysiological measure from EEG -TTTH1). First, we constructed haplotype blocks by using the entire set of single-nucleotide polymorphisms (SNP) in chromosomes 1, 4, and 7. These chromosomes have shown linkage signals for MAXDRINK or EEG-TTTH1 in previous reports. Second, we randomly selected one, two, three, four, and five SNPs from each block (referred to as Rep1 – Rep5, respectively) to conduct linkage analysis using variance component approach. Finally, results of all SNP analyses were compared with those obtained using microsatellite markers. RESULTS: The LOD scores obtained from SNPs were slightly higher but the curves were not radically different from those obtained from microsatellite analyses. The peaks of linkage regions from SNP sets were slightly shifted to the left when compared to those from microsatellite markers. The reduced sets of SNPs provide signals in the same linkage regions but with a smaller LOD score suggesting a significant impact of the decrease in information content on linkage results. The widths of 1 LOD support interval of linkage regions from SNP sets were smaller when compared to those of microsatellite markers. However, two linkage regions obtained from the microsatellite linkage analysis on chromosome 7 for LOG of TTTH1 were not detected in the SNP based analyses. CONCLUSION: The linkage results from SNPs showed narrower linkage regions and slightly higher LOD scores when compared to those of microsatellite markers. The different builds of the genetic maps used in microsatellite and SNPs markers or/and errors in genotyping may account for the microsatellite linkage signals on chromosome 7 that were not identified using SNPs. Also, unresolved map issues between SNPs and microsatellite markers may be partly responsible for the shifted linkage peaks when comparing the two types of markers

A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits

Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called “missing heritability” has been, at best, modest. Also, the predictive power of common variants identified by GWAS has not been encouraging. Given these observations along with the fact that the effects of rare variants are often, by design, unaccounted for by GWAS and the availability of sequence data, there is a growing need for robust analytic approaches to evaluate the contribution of rare variants to common complex diseases. Here we propose a new method that enables the simultaneous analysis of the association between rare and common variants in disease etiology. We refer to this method as SCARVA (simultaneous common and rare variants analysis). SCARVA is simple to use and is efficient. We used SCARVA to analyze two independent real datasets to identify rare and common variants underlying variation in obesity among participants in the Africa America Diabetes Mellitus (AADM) study and plasma triglyceride levels in the Dallas Heart Study (DHS). We found common and rare variants associated with both traits, consistent with published results

Gene Copy Number Analysis for Family Data Using Semiparametric Copula Model

Gene copy number changes are common characteristics of many genetic disorders. A new technology, array comparative genomic hybridization (a-CGH), is widely used today to screen for gains and losses in cancers and other genetic diseases with high resolution at the genome level or for specific chromosomal region. Statistical methods for analyzing such a-CGH data have been developed. However, most of the existing methods are for unrelated individual data and the results from them provide explanation for horizontal variations in copy number changes. It is potentially meaningful to develop a statistical method that will allow for the analysis of family data to investigate the vertical kinship effects as well. Here we consider a semiparametric model based on clustering method in which the marginal distributions are estimated nonparametrically, and the familial dependence structure is modeled by copula. The model is illustrated and evaluated using simulated data. Our results show that the proposed method is more robust than the commonly used multivariate normal model. Finally, we demonstrated the utility of our method using a real dataset

CoLight: Learning Network-level Cooperation for Traffic Signal Control

Cooperation among the traffic signals enables vehicles to move through intersections more quickly. Conventional transportation approaches implement cooperation by pre-calculating the offsets between two intersections. Such pre-calculated offsets are not suitable for dynamic traffic environments. To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication. Specifically, for a target intersection in a network, CoLight can not only incorporate the temporal and spatial influences of neighboring intersections to the target intersection, but also build up index-free modeling of neighboring intersections. To the best of our knowledge, we are the first to use graph attentional networks in the setting of reinforcement learning for traffic signal control and to conduct experiments on the large-scale road network with hundreds of traffic signals. In experiments, we demonstrate that by learning the communication, the proposed model can achieve superior performance against the state-of-the-art methods.Comment: 10 pages. Proceedings of the 28th ACM International on Conference on Information and Knowledge Management. ACM, 201

Mapping of disease-associated variants in admixed populations

Recent developments in high-throughput genotyping and whole-genome sequencing will enhance the identification of disease loci in admixed populations. We discuss how a more refined estimation of ancestry benefits both admixture mapping and association mapping, making disease loci identification in admixed populations more powerful

Robust Biomass-Derived Carbon Frameworks as High-Performance Anodes in Potassium-Ion Batteries

Potassium-ion batteries (PIBs) have become one of the promising candidates for electrochemical energy storage that can provide low-cost and high-performance advantages. The poor cyclability and rate capability of PIBs are due to the intensive structural change of electrode materials during battery operation. Carbon-based materials as anodes have been successfully commercialized in lithium- and sodium-ion batteries but is still struggling in potassium-ion battery field. This work conducts structural engineering strategy to induce anionic defects within the carbon structures to boost the kinetics of PIBs anodes. The carbon framework provides a strong and stable structure to accommodate the volume variation of materials during cycling, and the further phosphorus doping modification is shown to enhance the rate capability. This is found due to the change of the pore size distribution, electronic structures, and hence charge storage mechanism. The optimized electrode in this work shows a high capacity of 175 mAh g^{-1} at a current density of 0.2 A g^{-1} and the enhancement of rate performance as the PIB anode (60% capacity retention with the current density increase of 50 times). This work, therefore provides a rational design for guiding future research on carbon-based anodes for PIBs

Influence of mixed-phase TiO2 on the activity of adsorption-plasma photocatalysis for total oxidation of toluene

Herein, the effects of different crystalline phases of TiO2 on the adsorption-plasma photocatalytic oxidation of toluene were investigated. First, photocatalysts loaded on a molecular sieve (MS) were characterised and the catalytic performance of toluene abatement was evaluated in a plasma system. The COx yield of the pure anatase (An) sample outperformed other samples in the adsorption-plasma photocatalytic oxidation process, especially for CO2 yield (69.1%). It was revealed that the highest space-time-yield of 2.35 gco(2)/Lcat.h was also achieved using plasma-An/MS. However, the highest total toluene abatement (99.5%) was achieved in the plasma-P25/MS system. The plasma-generated UV flux only played a minor role in photocatalyst activation because of the very low UV flux of 2.7 mu W/cm(2) generated by discharge. For the degradation pathway, compared with the plasma-MS system, byproducts of 1,3-Butadiyne (C4H2), guanidine, methyl-(C2H7N3) did not exist in the TiO2-assisted system, indicating a difference in the toluene degradation pathway. There were no obvious effects of different TiO2 samples on organic byproducts generation, and almost a complete mineralisation of all byproducts was observed after 30 min of treatment, with the exception of ethylamine (C2H7N) and acetaldehyde (C2H4O). Finally, a cycled adsorption-plasma study was conducted to reveal the sustainability of the process. A partial deactivation of plasma-An/MS with less than 7% decrease in CO2 selectivity after 7 cycles was revealed, which is a promising result for use in possible industrial applications