Reduction Techniques for Graph Isomorphism in the Context of Width Parameters

We study the parameterized complexity of the graph isomorphism problem when parameterized by width parameters related to tree decompositions. We apply the following technique to obtain fixed-parameter tractability for such parameters. We first compute an isomorphism invariant set of potential bags for a decomposition and then apply a restricted version of the Weisfeiler-Lehman algorithm to solve isomorphism. With this we show fixed-parameter tractability for several parameters and provide a unified explanation for various isomorphism results concerned with parameters related to tree decompositions. As a possibly first step towards intractability results for parameterized graph isomorphism we develop an fpt Turing-reduction from strong tree width to the a priori unrelated parameter maximum degree.Comment: 23 pages, 4 figure

An omics-based machine learning approach to predict diabetes progression:a RHAPSODY study

Aims/hypothesis: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA 1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. Methods: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA 1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel’s C statistic. Results: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0–11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3–11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA 1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA 1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. Conclusions/interpretation: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. Data availability: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch. Graphical Abstract: (Figure presented.).</p

Junior Recital: Andrew J. Yi, Percussion

This recital is presented in partial fulfillment of requirements for the degree Bachelor of Music in Music Performance. Mr. Yi studies percussion with John Lawless.https://digitalcommons.kennesaw.edu/musicprograms/2286/thumbnail.jp

Distinct molecular signatures of clinical clusters in people with type 2 diabetes:an IMI-RHAPSODY study

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the aetiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic- (N=12828), metabolomic- (N=2945), lipidomic- (N=2593) and proteomic (N=1170) data were obtained in plasma. In each datatype each cluster was compared with the other four clusters as the reference. The insulin resistant cluster showed the most distinct molecular signature, with higher BCAAs, DAG and TAG levels and aberrant protein levels in plasma enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher cytokines. A subset of the mild diabetes cluster with high HDL showed the most beneficial molecular profile with opposite effects to those seen in the insulin resistant cluster. This study showed that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous diseas

The CIELO collaboration: Progress in international evaluations of neutron reactions on Oxygen, Iron, Uranium and Plutonium

The CIELO collaboration has studied neutron cross sections on nuclides that significantly impact criticality in nuclear technologies – 16O, 56Fe, 235,8U and 239Pu – with the aim of improving the accuracy of the data and resolving previous discrepancies in our understanding. This multi-laboratory pilot project, coordinated via the OECD/NEA Working Party on Evaluation Cooperation (WPEC) Subgroup 40 with support also from the IAEA, has motivated experimental and theoretical work and led to suites of new evaluated libraries that accurately reflect measured data and also perform well in integral simulations of criticality

Etude et suivi des ions bromate au cours du traitement de potabilisation de l'eau

Cette étude a pour objet d'évaluer l'impact du traitement de potabilisation dans les conditions d'exploitation habituelles, , sur les teneurs en bromate et en bromure (précurseur des ions bromate) dans trois usines de production d'eau potable de la région parisienne.Une méthode analytique par chromatographie ionique couplée à un détecteur conductimétrique a été développée. La limite de quantification est de 2 et 5 æg/L respectivement pour les ions bromate et bromure.Les résultats obtenus montrent que la préozonation ne contribue pas à la formation d'ions bromate. Les ions bromate sont formés au cours de la post-ozonation et sont introduits au cours de la chloration. Etant donné que les teneurs en bromate dans les eaux produites par ces trois usines excèdent parfois les limites de qualité fixées par la législation française, des essais ont été entrepris en usine de manière à minimiser la formation des ions bromate sans nuire à la désinfection. L'ensemble des essais montrent la difficulté, voire l'impossibilité de respecter les critères de potabilité vis-à-vis du paramètre bromate.La dernière partie de l'étude est consacrée à l'évaluation de l'impact éventuelle d'acides aminés (la glycine, l'acide aspartique, l'acide glutamique et l'isoleucine) sur la formation des ions bromate. Les premiers résultats montrent que l'impact des acides aminés sur la formation des ions bromate semble dépendre du rapport molaire acide aminé/bromure, du pH et de l'acide aminé.The object of this study is to evaluate the impact of drinking water treatment under usual exploitation conditions, on bromate and bromide concentrations in three waterworks upstream Paris.An analytical method based on ionic chromatography coupled with a conductivity detector was developed. The quantification limit of bromate and bromide is 2 and 5 æg/L respectively.The results obtained show that preozonation doesn't play a role in bromate formation. Bromate ions are formed during post-ozonation and are introduced during the chlorination step. Bromate concentrations encountered in drinking water produced by these three waterworks exceed the quality parameters fixed by French regulation, especially in summer. Studies were therefore realised in the plants to minimize bromate formation. The results show the difficulty or even the impossibility to reach the objective.The last part of the study is dedicated to the impact of amino acids (glycine, aspartic acid, glutamic acid and isoleucine) on bromate formation. The first results show that the impact of amino acid seems to depend on amino acid/bromide molar ratio, pH and on the nature of the amino acid.ORSAY-PARIS 11-BU Sciences (914712101) / SudocSudocFranceF

Revisiting the role of the (n,γf)(n,\gamma f) process in the low-energy fission of 235^{235}U and 239^{239}Pu

International audienceThe (n,γf) process is reviewed in light of modern nuclear reaction calculations in both slow and fast neutron-induced fission reactions on U235 and Pu239. Observed fluctuations of the average prompt fission neutron multiplicity and average total γ-ray energy below 100-eV incident neutron energy are interpreted in this framework. The surprisingly large contribution of the M1 transitions to the prefission γ-ray spectrum of Pu239 is explained by the dominant fission probabilities of 0+ and 2+ transition states, which can only be accessed from compound nucleus states formed by the interaction of s-wave neutrons with the target nucleus in its ground state, and decaying through M1 transitions. The impact of an additional low-lying M1 scissors mode in the photon strength function is analyzed. We review experimental evidence for fission fragment mass and kinetic-energy fluctuations in the resonance region and their importance in the interpretation of experimental data on prompt neutron data in this region. Finally, calculations are extended to the fast energy range where (n,γf) corrections can account for up to 3% of the total fission cross section and about 20% of the capture cross section