Topological Defects Coupling Smectic Modulations to Intra-unit-cell Nematicity in Cuprate

We study the coexisting smectic modulations and intra-unit-cell nematicity in the pseudogap states of underdoped Bi2Sr2CaCu2O8+{\delta}. By visualizing their spatial components separately, we identified 2\pi topological defects throughout the phase-fluctuating smectic states. Imaging the locations of large numbers of these topological defects simultaneously with the fluctuations in the intra-unit-cell nematicity revealed strong empirical evidence for a coupling between them. From these observations, we propose a Ginzburg-Landau functional describing this coupling and demonstrate how it can explain the coexistence of the smectic and intra-unit-cell broken symmetries and also correctly predict their interplay at the atomic scale. This theoretical perspective can lead to unraveling the complexities of the phase diagram of cuprate high-critical-temperature superconductors

Machine Learning in Electronic Quantum Matter Imaging Experiments

Essentials of the scientific discovery process have remained largely unchanged for centuries: systematic human observation of natural phenomena is used to form hypotheses that, when validated through experimentation, are generalized into established scientific theory. Today, however, we face major challenges because automated instrumentation and large-scale data acquisition are generating data sets of such volume and complexity as to defy human analysis. Radically different scientific approaches are needed, with machine learning (ML) showing great promise, not least for materials science research. Hence, given recent advances in ML analysis of synthetic data representing electronic quantum matter (EQM), the next challenge is for ML to engage equivalently with experimental data. For example, atomic-scale visualization of EQM yields arrays of complex electronic structure images, that frequently elude effective analyses. Here we report development and training of an array of artificial neural networks (ANN) designed to recognize different types of hypothesized order hidden in EQM image-arrays. These ANNs are used to analyze an experimentally-derived EQM image archive from carrier-doped cuprate Mott insulators. Throughout these noisy and complex data, the ANNs discover the existence of a lattice-commensurate, four-unit-cell periodic, translational-symmetry-breaking EQM state. Further, the ANNs find these phenomena to be unidirectional, revealing a coincident nematic EQM state. Strong-coupling theories of electronic liquid crystals are congruent with all these observations.Comment: 44 pages, 15 figure

Simulations of black hole air showers in cosmic ray detectors

We present a comprehensive study of TeV black hole events in Earth's atmosphere originated by cosmic rays of very high energy. An advanced fortran Monte Carlo code is developed and used to simulate black hole extensive air showers from ultrahigh-energy neutrino-nucleon interactions. We investigate the characteristics of these events, compare the black hole air showers to standard model air showers, and test different theoretical and phenomenological models of black hole formation and evolution. The main features of black hole air showers are found to be independent of the model considered. No significant differences between models are likely to be observed at fluorescence telescopes and/or ground arrays. We also discuss the tau ``double bang'' signature in black hole air showers. We find that the energy deposited in the second bang is too small to produce a detectable peak. Our results show that the theory of TeV-scale black holes in ultrahigh-energy cosmic rays leads to robust predictions, but the fine prints of new physics are hardly to be investigated through atmospheric black hole events in the near future.Comment: 18 pages, 9 figure

Reading In English By Children In Korea: Frequency, Effectiveness, And Barriers

A study of the English non-textbook reading of fourth graders in Korea revealed that about 80% had done at least some reading, confirming that there is enthusiasm for English reading. About half, however, had read only five books or fewer. Non-readers said that the reason they did not read in English was the difficulty of English texts. Those who read more did better on a test of English spelling and vocabulary

Commensurate 4a04a_0 period Charge Density Modulations throughout the Bi2Sr2CaCu2O8+xBi_2Sr_2CaCu_2O_{8+x} Pseudogap Regime

Theories based upon strong real space (r-space) electron electron interactions have long predicted that unidirectional charge density modulations (CDM) with four unit cell (4$a_0$) periodicity should occur in the hole doped cuprate Mott insulator (MI). Experimentally, however, increasing the hole density p is reported to cause the conventionally defined wavevector $Q_A$ of the CDM to evolve continuously as if driven primarily by momentum space (k-space) effects. Here we introduce phase resolved electronic structure visualization for determination of the cuprate CDM wavevector. Remarkably, this new technique reveals a virtually doping independent locking of the local CDM wavevector at $|Q_0|=2\pi/4a_0$ throughout the underdoped phase diagram of the canonical cuprate $Bi_2Sr_2CaCu_2O_8$. These observations have significant fundamental consequences because they are orthogonal to a k-space (Fermi surface) based picture of the cuprate CDM but are consistent with strong coupling r-space based theories. Our findings imply that it is the latter that provide the intrinsic organizational principle for the cuprate CDM state

Analytical theory of forced rotating sheared turbulence: The perpendicular case

Rotation and shear flows are ubiquitous features of many astrophysical and geophysical bodies. To understand their origin and effect on turbulent transport in these systems, we consider a forced turbulence and investigate the combined effect of rotation and shear flow on the turbulence properties. Specifically, we study how rotation and flow shear influence the generation of shear flow (e.g., the direction of energy cascade), turbulence level, transport of particles and momentum, and the anisotropy in these quantities. In all the cases considered, turbulence amplitude is always quenched due to strong shear (ξ=νky2/A⪡1, where A is the shearing rate, ν is the molecular viscosity, and ky is a characteristic wave number of small-scale turbulence), with stronger reduction in the direction of the shear than those in the perpendicular directions. Specifically, in the large rotation limit (Ω⪢A), they scale as A−1 and A−1|ln ξ|, respectively, while in the weak rotation limit (Ω⪡A), they scale as A−1 and A−2/3, respectively. Thus, flow shear always leads to weak turbulence with an effectively stronger turbulence in the plane perpendicular to shear than in the shear direction, regardless of rotation rate. The anisotropy in turbulence amplitude is, however, weaker by a factor of ξ1/3|ln ξ| (∝A−1/3|ln ξ|) in the rapid rotation limit (Ω⪢A) than that in the weak rotation limit (Ω⪡A) since rotation favors almost-isotropic turbulence. Compared to turbulence amplitude, particle transport is found to crucially depend on whether rotation is stronger or weaker than flow shear. When rotation is stronger than flow shear (Ω⪢A), the transport is inhibited by inertial waves, being quenched inversely proportional to the rotation rate (i.e., ∝Ω−1) while in the opposite case, it is reduced by shearing as A−1. Furthermore, the anisotropy is found to be very weak in the strong rotation limit (by a factor of 2) while significant in the strong shear limit. The turbulent viscosity is found to be negative with inverse cascade of energy as long as rotation is sufficiently strong compared to flow shear (Ω⪢A) while positive in the opposite limit of weak rotation (Ω⪡A). Even if the eddy viscosity is negative for strong rotation (Ω⪢A), flow shear, which transfers energy to small scales, has an interesting effect by slowing down the rate of inverse cascade with the value of negative eddy viscosity decreasing as |νT|∝A−2 for strong shear. Furthermore, the interaction between the shear and the rotation is shown to give rise to a nondiffusive flux of angular momentum (Λ effect), even in the absence of external sources of anisotropy. This effect provides a mechanism for the existence of shearing structures in astrophysical and geophysical systems

Analytical theory of forced rotating sheared turbulence: The parallel case

Forced turbulence combined with the effect of rotation and shear flow is studied. In a previous paper [N. Leprovost and E. J. Kim, Phys. Rev. E 78, 016301 (2008)], we considered the case where the shear and the rotation are perpendicular. Here, we consider the complementary case of parallel rotation and shear, elucidating how rotation and flow shear influence the generation of shear flow (e.g., the direction of energy cascade), turbulence level, transport of particles, and momentum. We show that turbulence amplitude and transport are always quenched due to strong shear (ξ=νky2∕A⪡1, where A is the shearing rate, ν is the molecular viscosity, and ky is a characteristic wave number of small-scale turbulence), with stronger reduction in the direction of the shear than those in the perpendicular directions. In contrast with the case where rotation and shear are perpendicular, we found that rotation affects turbulence amplitude only for very rapid rotation (Ω⪢A) where it reduces slightly the anisotropy due to shear flow. Also, concerning the transport properties of turbulence, we find that rotation affects only the transport of particle and only for rapid rotation, leading to an almost isotropic transport (whereas, in the case of perpendicular rotation and shear, rotation favors isotropic transport even for slow rotation). Furthermore, the interaction between the shear and the rotation is shown to give rise to nondiffusive flux of angular momentum (Λ effect), even in the absence of external sources of anisotropy, which can provide a mechanism for the creation of shearing structures in astrophysical and geophysical systems

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP

Air pollution dispersion from biomass stoves to neighboring homes in Mirpur, Dhaka, Bangladesh.

BACKGROUND: Indoor air pollution, including fine particulate matter (PM2.5) and carbon monoxide (CO), is a major risk factor for pneumonia and other respiratory diseases. Biomass-burning cookstoves are major contributors to PM2.5 and CO concentrations. However, high concentrations of PM2.5 (> 1000 μg/m3) have been observed in homes in Dhaka, Bangladesh that do not burn biomass. We described dispersion of PM2.5 and CO from biomass burning into nearby homes in a low-income urban area of Dhaka, Bangladesh. METHODS: We recruited 10 clusters of homes, each with one biomass-burning (index) home, and 3-4 neighboring homes that used cleaner fuels with no other major sources of PM2.5 or CO. We administered a questionnaire and recorded physical features of all homes. Over 24 h, we recorded PM2.5 and CO concentrations inside each home, near each stove, and outside one neighbor home per cluster. During 8 of these 24 h, we conducted observations for pollutant-generating activities such as cooking. For each monitor, we calculated geometric mean PM2.5 concentrations at 5-6 am (baseline), during biomass burning times, during non-cooking times, and over 24 h. We used linear regressions to describe associations between monitor location and PM2.5 and CO concentrations. RESULTS: We recruited a total of 44 homes across the 10 clusters. Geometric mean PM2.5 and CO concentrations for all monitors were lowest at baseline and highest during biomass burning. During biomass burning, linear regression showed a decreasing trend of geometric mean PM2.5 and CO concentrations from the biomass stove (326.3 μg/m3, 12.3 ppm), to index home (322.7 μg/m3, 11.2 ppm), neighbor homes sharing a wall with the index home (278.4 μg/m3, 3.6 ppm), outdoors (154.2 μg/m3, 0.7 ppm), then neighbor homes that do not share a wall with the index home (83.1 μg/m3,0.2 ppm) (p = 0.03 for PM2.5, p = 0.006 for CO). CONCLUSION: Biomass burning in one home can be a source of indoor air pollution for several homes. The impact of biomass burning on PM2.5 or CO is greatest in homes that share a wall with the biomass-burning home. Eliminating biomass burning in one home may improve air quality for several households in a community

Insulin Induces Microtubule Stabilization and Regulates the Microtubule Plus-end Tracking Protein Network in Adipocytes

Insulin-stimulated glucose uptake is known to involve microtubules, although the function of microtubules and the microtubule-regulating proteins involved in insulin action are poorly understood. CLASP2, a plus-end tracking microtubule-associated protein (+TIP) that controls microtubule dynamics, was recently implicated as the first +TIP associated with insulin-regulated glucose uptake. Here, using protein-specific targeted quantitative phosphoproteomics within 3T3-L1 adipocytes, we discovered that insulin regulates phosphorylation of the CLASP2 network members G2L1, MARK2, CLIP2, AGAP3, and CKAP5 as well as EB1, revealing the existence of a previously unknown microtubule-associated protein system that responds to insulin. To further investigate, G2L1 interactome studies within 3T3-L1 adipocytes revealed that G2L1 coimmunoprecipitates CLASP2 and CLIP2 as well as the master integrators of +TIP assembly, the end binding (EB) proteins. Live-cell total internal reflection fluorescence microscopy in adipocytes revealed G2L1 and CLASP2 colocalize on microtubule plus-ends. We found that although insulin increases the number of CLASP2-containing plus-ends, insulin treatment simultaneously decreases CLASP2-containing plus-end velocity. In addition, we discovered that insulin stimulates redistribution of CLASP2 and G2L1 from exclusive plus-end tracking to "trailing" behind the growing tip of the microtubule. Insulin treatment increases alpha-tubulin Lysine 40 acetylation, a mechanism that was observed to be regulated by a counterbalance between GSK3 and mTOR, and led to microtubule stabilization. Our studies introduce insulin-stimulated microtubule stabilization and plus-end trailing of +TIPs as new modes of insulin action and reveal the likelihood that a network of microtubule-associated proteins synergize to coordinate insulin-regulated microtubule dynamics.TRIF Space Exploration and Optical Sciences (TRIF-SEOS) grantThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]