Giant Anisotropic Magnetoresistance in a Quantum Anomalous Hall Insulator

When a three-dimensional (3D) ferromagnetic topological insulator thin film is magnetized out-of-plane, conduction ideally occurs through dissipationless, one-dimensional (1D) chiral states that are characterized by a quantized, zero-field Hall conductance. The recent realization of this phenomenon - the quantum anomalous Hall effect - provides a conceptually new platform for studies of edge-state transport, distinct from the more extensively studied integer and fractional quantum Hall effects that arise from Landau level formation. An important question arises in this context: how do these 1D edge states evolve as the magnetization is changed from out-of-plane to in-plane? We examine this question by studying the field-tilt driven crossover from predominantly edge state transport to diffusive transport in Cr-doped (Bi,Sb)2Te3 thin films, as the system transitions from a quantum anomalous Hall insulator to a gapless, ferromagnetic topological insulator. The crossover manifests itself in a giant, electrically tunable anisotropic magnetoresistance that we explain using the Landauer-Buttiker formalism. Our methodology provides a powerful means of quantifying edge state contributions to transport in temperature and chemical potential regimes far from perfect quantization

Pole Placement and Reduced-Order Modelling for Time-Delayed Systems Using Galerkin Approximations

The dynamics of time-delayed systems (TDS) are governed by delay differential equa- tions (DDEs), which are infinite dimensional and pose computational challenges. The Galerkin approximation method is one of several techniques to obtain the spectrum of DDEs for stability and stabilization studies. In the literature, Galerkin approximations for DDEs have primarily dealt with second-order TDS (second-order Galerkin method), and the for- mulations have resulted in spurious roots, i.e., roots that are not among the characteristic roots of the DDE. Although these spurious roots do not affect stability studies, they never- theless add to the complexity and computation time for control and reduced-order modelling studies of DDEs. A refined mathematical model, called the first-order Galerkin method, is proposed to avoid spurious roots, and the subtle differences between the two formulations (second-order and first-order Galerkin methods) are highlighted with examples. For embedding the boundary conditions in the first-order Galerkin method, a new pseudoinverse-based technique is developed. This method not only gives the exact location of the rightmost root but also, on average, has a higher number of converged roots when compared to the existing pseudospectral differencing method. The proposed method is combined with an optimization framework to develop a pole-placement technique for DDEs to design closed-loop feedback gains that stabilize TDS. A rotary inverted pendulum system apparatus with inherent sensing delays as well as deliberately introduced time delays is used to experimentally validate the Galerkin approximation-based optimization framework for the pole placement of DDEs. Optimization-based techniques cannot always place the rightmost root at the desired location; also, one has no control over the placement of the next set of rightmost roots. However, one has the precise location of the rightmost root. To overcome this, a pole- placement technique for second-order TDS is proposed, which combines the strengths of the method of receptances and an optimization-based strategy. When the method of receptances provides an unsatisfactory solution, particle swarm optimization is used to improve the location of the rightmost pole. The proposed approach is demonstrated with numerical studies and is validated experimentally using a 3D hovercraft apparatus. The Galerkin approximation method contains both converged and unconverged roots of the DDE. By using only the information about the converged roots and applying the eigenvalue decomposition, one obtains an r-dimensional reduced-order model (ROM) of the DDE. To analyze the dynamics of DDEs, we first choose an appropriate value for r; we then select the minimum value of the order of the Galerkin approximation method system at which at least r roots converge. By judiciously selecting r, solutions of the ROM and the original DDE are found to match closely. Finally, an r-dimensional ROM of a 3D hovercraft apparatus in the presence of delay is validated experimentally

Major health-related behaviours and mental well-being in the general population : the health survey for England

Background: Major behavioural risk factors are known to adversely affect health outcomes and be strongly associated with mental illness. However, little is known about the association of these risk factors with mental well-being in the general population. We sought to examine behavioural correlates of high and low mental well-being in the Health Survey for England. Methods: Participants were 13 983 adults, aged 16 years and older (56% females), with valid responses for the combined 2010 and 2011 surveys. Mental well-being was assessed using the Warwick-Edinburgh Mental Well-being Scale (WEMWBS). ORs of low and high mental well-being, compared to the middle-range category, were estimated for body mass index (BMI), smoking, drinking habits, and fruit and vegetable intake. Results: ORs for low mental well-being were increased in obese individuals (up to 1.72, 95% CI 1.26 to 2.36 in BMI 40+ kg/m2). They increased in a linear fashion with increasing smoking (up to 1.98, 95% CI 1.55 to 2.53, >20 cigarettes/day) and with decreasing fruit and vegetable intake (up to 1.53, 95% CI 1.24 to 1.90, <1 portion/day); whereas ORs were reduced for sensible alcohol intake (0.78, 95% CI 0.66 to 0.91, ≤4 units/day in men, ≤3 units/day in women). ORs for high mental well-being were not correlated with categories of BMI or alcohol intake. ORs were reduced among ex-smokers (0.81, 95% CI 0.71 to 0.92), as well as with lower fruit and vegetable intake (up to 0.79, 95% CI 0.68 to 0.92, 1 to <3 portions/day). Conclusions; Along with smoking, fruit and vegetable consumption was the health-related behaviour most consistently associated with mental well-being in both sexes. Alcohol intake and obesity were associated with low, but not high mental well-being

Geo-additive models of Childhood Undernutrition in three Sub-Saharan African Countries

We investigate the geographical and socioeconomic determinants of childhood undernutrition in Malawi, Tanzania and Zambia, three neighboring countries in Southern Africa using the 1992 Demographic and Health Surveys. We estimate models of undernutrition jointly for the three countries to explore regional patterns of undernutrition that transcend boundaries, while allowing for country-specific interactions. We use semiparametric models to flexibly model the effects of selected so-cioeconomic covariates and spatial effects. Our spatial analysis is based on a flexible geo-additive model using the district as the geographic unit of anal-ysis, which allows to separate smooth structured spatial effects from random effect. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques. While the socioeconomic determinants generally confirm what is known in the literature, we find distinct residual spatial patterns that are not explained by the socioeconomic determinants. In particular, there appears to be a belt run-ning from Southern Tanzania to Northeastern Zambia which exhibits much worse undernutrition, even after controlling for socioeconomic effects. These effects do transcend borders between the countries, but to a varying degree. These findings have important implications for targeting policy as well as the search for left-out variables that might account for these residual spatial patterns

Secular trends in the prevalence of female genital mutilation/cuttings among girls: a systematic analysis

Background Current evidence on the decline in the prevalence of female genital mutilation or cutting (FGM/C) has been lacking worldwide. This study analyses the prevalence estimates and secular trends in FGM/C over sustained periods (ie, 1990–2017). Its aim is to provide analytical evidence on the changing prevalence of FGM/C over time among girls aged 0–14 years and examine geographical variations in low-income and middle-income countries. Methods Analysis on the shift in prevalence of FGM/C was undertaken using the Demographic Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS) data sets from Africa and Middle East. A random-effects model was used to derive overall prevalence estimates. Using Poisson regression models, we conducted time trends analyses on the FGM/C prevalence estimates between 1990 and 2017. Findings We included 90 DHS and MICS data sets for 208 195 children (0–14 years) from 29 countries spread across Africa and two countries in Western Asia. The prevalence of FGM/C among children varied greatly between countries and regions and also within countries over the survey periods. The percentage decline in the prevalence of FGM/C among children aged 0–14 years old was highest in East Africa, followed by North and West Africa. The prevalence decreased from 71.4% in 1995 to 8.0% in 2016 in East Africa. In North Africa, the prevalence decreased from 57.7% in 1990 to 14.1% in 2015. In West Africa, the prevalence decreased from 73.6% in 1996 to 25.4% in 2017. The results of the trend analysis showed a significant shift downwards in the prevalence of FGM/C among children aged 0–14 years in such regions and subregions of East Africa, North Africa and West Africa. East Africa has experienced a much faster decrease in the prevalence of the practice (trend=−7.3%, 95% CI −7.5% to −7.1%) per year from 1995 to 2014. By contrast, the decline in prevalence has been much slower in North Africa (trend=−4.4%, 95% CI −4.5% to −4.3%) and West Africa (trend=−3.0%, 95% CI −3.1% to −2.9%). Conclusion The prevalence of FGM/C among children aged 0–14 years varied greatly between countries and regions and also within countries over the survey periods. There is evidence of huge and significant decline in the prevalence of FGM/C among children across countries and regions. There is a need to sustain comprehensive intervention efforts and further targeted efforts in countries and regions still showing high prevalence of FGM/C among children, where the practice is still pervasive

Evaluation of denoising strategies to address motion-correlated artifacts in resting-state functional magnetic resonance imaging data from the human connectome roject

Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR

The 2016 US Presidential Election on Facebook: An Exploratory Analysis of Sentiments

Social media platforms are valuable tools for political campaigns. In this study, we analyze a dataset representing over 22 thousand Facebook posts by candidates and over 48 million comments to understand the nature of online discourse. Specifically, we study the interaction between political candidates and the public during the 2016 presidential elections in the United States. We outline a novel method to classify commentators into four groups: strong supporters, supporters, dissenters, and strong dissenters. Comments by each group on policy-related topics are analyzed using sentiment analysis. Finally, we discuss avenues for future research to study the dynamics of social media platforms and political campaigns

Identification of Wheat Varieties with a Parallel-Plate Capacitance Sensor Using Fisher’s Linear Discriminant Analysis

Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle (θ), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD models. Z and θ of a parallel-plate capacitance system, holding the wheat samples, were measured using an impedance meter, and the C value was computed. The best model developed classified the wheat varieties, with accuracy of 95.4%, over the six wheat varieties tested. This method is simple, rapid, and nondestructive and would be useful for the breeders and the peanut industry