2,210 research outputs found
Structure of the high voltage phase of layered P2-Na_(2/3−z)[Mn_(1/2)Fe_(1/2)]O_2 and the positive effect of Ni substitution on its stability
A combination of operando X-ray diffraction, pair distribution function (PDF) analysis coupled with electrochemical measurements and Mössbauer spectroscopy elucidates the nature of the phase transitions induced by insertion and extraction of sodium ions in P2-Na_(0.67)[Ni_yMn_(0.5+y)Fe_(0.5−2y)]O_2 (y = 0, 0.10, 0.15). When phase transitions are avoided, the optimal cathode material – P2-Na_(0.67)Fe_(0.2)Mn_(0.65)Ni_(0.15)O_2 – delivers 25% more energy than the unsubstituted material, sustaining high specific energy (350 Wh kg^(−1)) at moderate rates and maintains 80% of the original energy density after 150 cycles – a significant improvement in performance vs. the unsubstituted analogue. The crystal structure of the high voltage phase is solved for the first time by X-ray PDF analysis of P2-Na_(0.67−z)Fe_(0.5)Mn_(0.5)O_2 (where z ∼ 0.5), revealing that migration of the transition metals – particularly Fe^(3+) – into tetrahedral sites in the interlayer space occurs at high potential. This results in new short range order between two adjacent layers. Although the transition metal migration is reversible as proven by electrochemical performance, it induces a large disfavourable cell polarization. The deleterious high voltage transition is mitigated by substitution of Fe^(3+) by Mn^(4+)/Ni^(2+), giving rise to better cycling performance. Moreover, as demonstrated by ^(57)Fe Mössbauer spectroscopy, the much lower ratio of Fe^(4+)O_6 to Fe^(3+)O_6 observed systematically across the range of Ni content – compared to the values expected from a purely ionic model – suggests redox activity involves the O-2p orbitals owing to their overlap with the transition metal-3d orbitals
Experimental simulation of quantum graphs by microwave networks
We present the results of experimental and theoretical study of irregular,
tetrahedral microwave networks consisting of coaxial cables (annular
waveguides) connected by T-joints. The spectra of the networks were measured in
the frequency range 0.0001-16 GHz in order to obtain their statistical
properties such as the integrated nearest neighbor spacing distribution and the
spectral rigidity. The comparison of our experimental and theoretical results
shows that microwave networks can simulate quantum graphs with time reversal
symmetry. In particular, we use the spectra of the microwave networks to study
the periodic orbits of the simulated quantum graphs. We also present
experimental study of directional microwave networks consisting of coaxial
cables and Faraday isolators for which the time reversal symmetry is broken. In
this case our experimental results indicate that spectral statistics of
directional microwave networks deviate from predictions of Gaussian orthogonal
ensembles (GOE) in random matrix theory approaching, especially for small
eigenfrequency spacing s, results for Gaussian unitary ensembles (GUE).
Experimental results are supported by the theoretical analysis of directional
graphs.Comment: 16 pages, 7 figures, to be published in Phys. Rev.
Scanning X-ray Diffraction Microscopy for Diamond Quantum Sensing
Understanding nano- and micro-scale crystal strain in CVD diamond is crucial
to the advancement of diamond quantum technologies. In particular, the presence
of such strain and its characterization present a challenge to diamond-based
quantum sensing and information applications -- as well as for future dark
matter detectors where directional information of incoming particles is encoded
in crystal strain. Here, we exploit nanofocused scanning X-ray diffraction
microscopy to quantitatively measure crystal deformation from growth defects in
CVD diamond with high spatial and strain resolution. Combining information from
multiple Bragg angles allows stereoscopic three-dimensional reconstruction of
strained volumes; the diffraction results are validated via comparison to
optical measurements of the strain tensor based on spin-state-dependent
spectroscopy of ensembles of nitrogen vacancy (NV) centers in the diamond. Our
results open a path towards directional detection of dark matter via X-ray
measurement of crystal strain, and provide a new tool for diamond growth
analysis and improvement of defect-based sensing.Comment: 15 pages, 17 figures (incl. Supplemental Material
Association between adiposity levels and cognitive impairment in the Chilean older adult population
Although both obesity and ageing are risk factors for cognitive impairment, there is no evidence in Chile on how obesity levels are associated with cognitive function. Therefore, the aim of the present study was to investigate the association between adiposity levels and cognitive impairment in older Chilean adults. This cross-sectional study includes 1384 participants, over 60 years of age, from the Chilean National Health Survey 2009–2010. Cognitive impairment was evaluated using the Mini-Mental State Examination. BMI and waist circumference (WC) were used as measures of adiposity. Compared with people with a normal BMI, the odds of cognitive impairment were higher in participants who were underweight (OR 4·44; 95 % CI 2·43, 6·45; P < 0·0001), overweight (OR 1·86; 95 % CI 1·06, 2·66; P = 0·031) and obese (OR 2·26; 95 % CI 1·31, 3·21; P = 0·003). The associations were robust after adjustment for confounding variables. Similar results were observed for WC. Low and high levels of adiposity are associated with an increased likelihood of cognitive impairment in older adults in Chile
Risk assessment for the spread of Serratia marcescens within dental-unit waterline systems using Vermamoeba vermiformis
Vermamoeba vermiformis is associated with the biofilm ecology of dental-unit waterlines (DUWLs). This study investigated whether V. vermiformis is able to act as a vector for potentially pathogenic bacteria and so aid their dispersal within DUWL systems. Clinical dental water was initially examined for Legionella species by inoculating it onto Legionella selective-medium plates. The molecular identity/profile of the glassy colonies obtained indicated none of these isolates were Legionella species. During this work bacterial colonies were identified as a non-pigmented Serratia marcescens. As the water was from a clinical DUWL which had been treated with Alpronâ„¢ this prompted the question as to whether S. marcescens had developed resistance to the biocide. Exposure to Alpronâ„¢ indicated that this dental biocide was effective, under laboratory conditions, against S. marcescens at up to 1x108 colony forming units/millilitre (cfu/ml). V. vermiformis was cultured for eight weeks on cells of S. marcescens and Escherichia coli. Subsequent electron microscopy showed that V. vermiformis grew equally well on S. marcescens and E. coli (p = 0.0001). Failure to detect the presence of S. marcescens within the encysted amoebae suggests that V. vermiformis is unlikely to act as a vector supporting the growth of this newly isolated, nosocomial bacterium
Deterministic nanoscale quantum spin-defect implantation and diffraction strain imaging
Local crystallographic features negatively affect quantum spin defects by changing the local electrostatic environment, often resulting in degraded or varied qubit optical and coherence properties. Few tools exist that enable the deterministic synthesis and study of such intricate systems on the nano-scale, making defect-to-defect strain environment quantification difficult. In this paper, we highlight state-of-the-art capabilities from the U.S. Department of Energy's Nanoscale Science Research Centers that directly address these shortcomings. Specifically, we demonstrate how complementary capabilities of nano-implantation and nano-diffraction can be used to demonstrate the quantum relevant, spatially deterministic creation of neutral divacancy centers in 4H silicon carbide, while investigating and characterizing these systems on the scale with strain sensitivities on the order of relevant to defect formation dynamics. This work lays the foundation for ongoing studies into the dynamics and deterministic formation of low strain homogeneous quantum relevant spin defects in the solid state
A Combination of Compositional Index and Genetic Algorithm for Predicting Transmembrane Helical Segments
Transmembrane helix (TMH) topology prediction is becoming a focal problem in bioinformatics because the structure of TM proteins is difficult to determine using experimental methods. Therefore, methods that can computationally predict the topology of helical membrane proteins are highly desirable. In this paper we introduce TMHindex, a method for detecting TMH segments using only the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index, which is deduced from a combination of the difference in amino acid occurrences in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, a genetic algorithm was employed to find the optimal threshold value for the separation of TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in a dataset consisting of 70 test protein sequences. The sensitivity and specificity for classifying each amino acid in every protein sequence in the dataset was 0.901 and 0.865, respectively. To assess the generality of TMHindex, we also tested the approach on another standard 73-protein 3D helix dataset. TMHindex correctly predicted 91.8% of proteins based on TM segments. The level of the accuracy achieved using TMHindex in comparison to other recent approaches for predicting the topology of TM proteins is a strong argument in favor of our proposed method. Availability: The datasets, software together with supplementary materials are available at: http://faculty.uaeu.ac.ae/nzaki/TMHindex.htm
Multiple Analytical Approaches Reveal Distinct Gene-Environment Interactions in Smokers and Non Smokers in Lung Cancer
Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR), was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11–2.59,p = 0.01), whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25–0.65,p<0.001 and OR = 0.51;95%CI = 0.33–0.78,p = 0.002 respectively). In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His), SULT1A1 213GG (Arg/Arg) or AA (His/His) and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33–10.55,p = 0.006), whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg) and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15–7.51,p = 0.01). MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His) and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His) with testing balance accuracy (TBA) of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with SULT1A1 Arg213His and EPHX1 Tyr113His in smokers and SULT1A1 Arg213His with GSTP1 Ile105Val and CYP1A1*2C in nonsmokers. These results identified distinct gene-gene and gene environment interactions in smokers and non-smokers, which confirms the importance of multifactorial interaction in risk assessment of lung cancer
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