Dealing with artefacts In JET iterative bolometric tomography using masks

Bolometric tomography is a widely applied technique to infer important indirect quantities in magnetically confined plasmas, such as the total radiated power. However, being an inverse and ill-posed problem, the tomographic algorithms have to be carefully steered to converge on the most approriate solutions and often specialists have to balance the quality of the obtained reconstructions between the core and the edge of the plasma. Given the topology of the emission and the layout of the diagnostics in practically all devices, the tomographic inversions of bolometry are often affected by artefacts, which can influence derived quantities and specific studies based on the reproduced tomograms, such as power balance studies and benchmarching of gyrokinetic simulations. This article deals with the introduction of a simple, but very efficient methodology. It is based on constraining the solution of the tomographic inversions by using a specific estimate of the initial solution, built with the data from specific combinations of detectors (called ‘masks’). It has been tested with phantoms and with real data, using the Maximum Likelihood approach at JET. Results show how the obtained tomograms improve sensibly both in the core and at the edge of the device when compared with those obtained without the use of masks as initial guess. The correction for the main artefacts can have a significant impact on the interpretation of both the core (electron transport, alpha heating) and the edge physics (detachment , SOL). The method is completely general and can be applied by any iterative algorithm starting from an initial guess for the emission profile to be reconstructed.

Systematic Revision of a New Butterfly Genus, Cisandina Nakahara & Espeland, n. gen., with Descriptions of Three New Taxa (Lepidoptera: Nymphalidae: Satyrinae)

We here establish a new genus in the nymphalid butterfly subtribe Euptychiina, Cisandina Nakahara & Espeland, n. gen. to harbor five species hitherto placed within two polyphyletic genera, namely Magneuptychia Forster, 1964 and Euptychoides Forster, 1964. We compiled data from over 350 specimens in 17 public and private collections, as well as DNA sequence data for all relevant species, to revise the species-level classification of this new genus. According to our multi-locus molecular phylogeny estimated with the maximum likelihood approach, Cisandina lean. comb., Cisandina philippan. comb. & reinst. stat., Cisandina fidan. comb., Cisandina sanmarcosn. comb., and Cisandina trinitensisn. comb. are proposed as new taxonomic combinations, since these species are distantly related to the type species of Magneuptychia and Euptychoides and cannot reasonably be accommodated in any other genus. Lectotypes are designated for Papilio lea Cramer, 1777, Papilio junia Cramer, 1780, Euptychia philippa Butler, 1867, and Eupytchia fida Weymer, 1911. Two new species of Cisandinan. gen. are named and described herein, C. esmeralda Nakahara & Barbosa, n. sp. and C. castanya Lamas & Nakahara, n. sp., increasing the described species diversity of the genus to seven. The immature stages of C. castanyan. sp. and C. philippan. comb. & reinst. stat. are documented along with their natural hostplants, representing the first two species of the genus with known life history information. We describe a new subspecies, Cisandina fida directa Nakahara & Willmott, n. ssp., based on a limited number of specimens from southern Ecuador and central Peru. We were unable to obtain genetic data for the nominate race of C. fidan. comb., and thus, this taxonomic hypothesis is currently based solely on phenotypic characters.

A comparison of spectral reconstruction methods applied to non-zero temperature NRQCD meson correlation functions

We present results from the fastsum collaboration’s programme to determine the spectrum of the bottomonium system as a function of temperature. Three different methods of extracting spectral information are discussed: a Maximum Likelihood approach using a Gaussian spectral function for the ground state, the Backus Gilbert method, and the Kernel Ridge Regression machine learning procedure. We employ the fastsum anisotropic lattices with 2+1 dynamical quark flavours, with temperatures ranging from 47 to 375 MeV.

TiMEG: an integrative statistical method for partially missing multi-omics data

Multi-omics data integration is widely used to understand the genetic architecture of disease. In multi-omics association analysis, data collected on multiple omics for the same set of individuals are immensely important for biomarker identification. But when the sample size of such data is limited, the presence of partially missing individual-level observations poses a major challenge in data integration. More often, genotype data are available for all individuals under study but gene expression and/or methylation information are missing for different subsets of those individuals. Here, we develop a statistical model TiMEG, for the identification of disease-associated biomarkers in a case–control paradigm by integrating the above-mentioned data types, especially, in presence of missing omics data. Based on a likelihood approach, TiMEG exploits the inter-relationship among multiple omics data to capture weaker signals, that remain unidentified in single-omic analysis or common imputation-based methods. Its application on a real tuberous sclerosis dataset identified functionally relevant genes in the disease pathway.

Prevalence of and Risk Factors for Sagittal Posture Abnormalities in Children Born With Esophageal Atresia: A Prospective Cohort Study

Introduction: Scoliosis is a well-described complication of esophageal atresia (EA) caused by the associated spine malformations and/or thoracotomy. However, the sagittal posture abnormalities in patients with EA have not been described. The aim of this study was to evaluate the prevalence of and risk factors for sagittal posture abnormalities at the age of 6 years in patients operated on for EA.Methods: A prospective cohort of 123 patients with EA was examined by the same rehabilitation doctor at the time of a multidisciplinary visit scheduled at the age of 6 years. Children presenting with scoliosis (n = 4) or who missed the consultation (n = 33) were excluded. Univariate and multivariate logistic regression models with Firth's penalized-likelihood approach were used to identify risk factors associated with sagittal posture anomalies. Candidate risk factors included neonatal characteristics, associated malformations, atresia type, postoperative complications, psychomotor development retardation, orthopedic abnormalities, and neurological hypotonia.Results: The prevalence rates of sagittal posture abnormalities were 25.6% (n = 22; 95% CI, 16.7–36.1%). Multivariate analysis showed that minor orthopedic abnormalities (OR: 4.02, 95% CI: 1.29–13.43, P = 0.021), and VACTERL (OR: 3.35, 95% CI: 1.09–10.71, P = 0.042) were significant risk factors for sagittal posture abnormalities.Conclusion: This study shows that sagittal posture anomalies occur frequently in children operated on at birth for EA and are not directly linked to the surgical repair. These children should be screened and treated using postural physiotherapy, especially those with VACTERL and minor orthopedic abnormalities.

MLEFlow: Learning from History to Improve Load Balancing in Tor

Tor has millions of daily users seeking privacy while browsing the Internet. It has thousands of relays to route users’ packets while anonymizing their sources and destinations. Users choose relays to forward their traffic according to probability distributions published by the Tor authorities. The authorities generate these probability distributions based on estimates of the capacities of the relays. They compute these estimates based on the bandwidths of probes sent to the relays. These estimates are necessary for better load balancing. Unfortunately, current methods fall short of providing accurate estimates leaving the network underutilized and its capacities unfairly distributed between the users’ paths. We present MLEFlow, a maximum likelihood approach for estimating relay capacities for optimal load balancing in Tor. We show that MLEFlow generalizes a version of Tor capacity estimation, TorFlow-P, by making better use of measurement history. We prove that the mean of our estimate converges to a small interval around the actual capacities, while the variance converges to zero. We present two versions of MLEFlow: MLEFlow-CF, a closed-form approximation of the MLE and MLEFlow-Q, a discretization and iterative approximation of the MLE which can account for noisy observations. We demonstrate the practical benefits of MLEFlow by simulating it using a flow-based Python simulator of a full Tor network and packet-based Shadow simulation of a scaled down version. In our simulations MLEFlow provides significantly more accurate estimates, which result in improved user performance, with median download speeds increasing by 30%.

Technical Analysis of Tourism Price Process in the Eurozone

This study is a specific contribution to investigating normalities in prices to a well-established cointegrated vector autoregressive model (VAR). While the role of prices in computational economics has been investigated, the real prices vis-à-vis nominal prices in the decision process has been neglected. The paper investigates the transition from nominal to real time-series of prices without losing information in the data set when deflating or de-seasonalizing. The likelihood approach is based on careful specifications of the (co)integration characteristics of tourism prices. The results confirm that the transmission of tourism prices in the Eurozone positively impacts Slovenian tourism prices when the spatial consolidated cointegrated VAR model is used. The theoretical-conceptual and empirical contribution is twofold: first, the study develops and empirically applies bona fide divisor of normality consolidation for time-series in levels instead of routinely utilised inflation integers, and second, the study introduces perfection of prices on a long-run time-series treatment.