EMPress Enables Tree-Guided, Interactive, and Exploratory Analyses of Multi-omic Data Sets

ABSTRACT Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality—including ordination integration and animations—alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of ‘omic data. IMPORTANCE Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets.

Identification and Synoptic Analysis of the Highest Precipitation Linked to Ars in Iran

Atmospheric rivers are long, narrow, concentrated structures of water vapour that are highly associated with rainfall and floods. To identify and introduce the highest rainfall occurring during the presence of atmospheric rivers from November to April (2007-2018) while showing the importance of this phenomenon in creating super heavy rainfall and introducing the areas affected by it, analyzed the synoptic factors affecting them slowly. In order to identify atmospheric rivers, vertical integral data of water vapour flow were used and thresholds were documented on them. The date of occurrence of each atmospheric river with their daily rainfall was examined and ten of the highest rainfall events Station (equivalent to the 95th percentile of maximum rainfall) related to atmospheric rivers was introduced and analyzed. It is found that the South Gram has been directly and indirectly the main source of atmospheric rivers associated with heavy rainfall. The source of most of these atmospheric rivers is at the peak of the Red Sea, the Gulf of Aden and the Horn of Africa. Synonymously, the origins of 7 cases from Atmospheric rivers have been of the Sudanese low pressure and in the remaining three cases have been integrated systems. In Sudanese systems, the predominant structure of the meridional inclination jet and in Integration systems has been oriented. Due to the dominance of a strong upstream current in the vicinity of the highest flux, moisture of heavy convective currents has caused super heavy rainfall and the station with the highest rainfall in the east and North West of the negative omega field or upstream streams.

Fission yields and cross sections: correlated or not?

Cross sections and fission yields can be correlated, depending on the selection of integral experimental data. To support this statement, this work presents the use of experimental isotopic compositions (both for actinides and fission products) from a sample irradiated in a reactor, to construct correlations between various cross sections and fission yields. This study is therefore complementing previous analysis demonstrating that different types of nuclear data can be correlated, based on experimental integral data.

THE PRINCESS PROJECT: FROM DIFFERENTIAL TO INTEGRAL EXPERIMENTS

Following the shutdown of the CEA Valduc experimental facilities, where, for more than 50 years, IRSN used to perform experiments related to criticality safety, IRSN initiated a new project named PRINCESS (PRoject for IRSN Neutron physics and Criticality Experimental data Supporting Safety). The objective is to continue collecting experimental data necessary for the IRSN missions in nuclear safety. For this purpose, collaborations with various national and international laboratories have been established. The PRINCESS project covers various nuclear physics fields from nuclear data to criticality-safety and reactor physics providing information to both differential and integral data improvements.

APPLICATION OF RECENT DEVELOPMENTS IN INTEGRAL DATA ASSIMILATION TO IN-DEPTH ANALYSIS OF UH1.2 EXPERIMENT AND TRANSPOSITION TO WHOLE PWR CORE

Recent developments in the Integral Data Assimilation (IDA) methods within Bayesian framework have been achieved at CEA to tackle the problem of correlated experiments (through technological uncertainties) and neutron transport model numerical effects. Hence, reference Monte-Carlo and deterministic calculations (TRIPOLI4® and APOLLO3®) are used together to solve neutron transport equations and get the sensitivity profiles. Furthermore, the analysis of the mock-up experiments technological parameters is performed to get accurate uncertainties and correlations between the experiments (finally the covariance experimental matrix required for IDA). We apply here the IDA approach with a new, extend set of statistical indicators (Cook’s distance, Bayesian and Aikike Information criteria (BIC, AIC)) implemented in the nuclear physics CEA CONRAD code, to the integral experiments UH1.2 in reference and voided configurations (standard PWR fuel assembly in the EOLE mock-up reactor). The adjusted multigroup cross-sections and posterior covariances are compared by choosing different ingredients in the assimilation process. Finally, the investigated key neutron parameters; reactivity, reactivity worth (void effects) and fissions rates are transposed (with the same CONRAD code) to a standard PWR core. This in-depth analysis enables us to predict the residual uncertainties and biases due to the multigroup cross-section adjustments assessing at the same time the similarity of these integral experiments for the main PWR neutronic safety parameters. In addition, technological parameters uncertainties and their impact on Bayesian adjustment process are taken into account through a global experimental covariance matrix. We point out that the UH1.2 experiments bring relevant additional information to PWR keff calculations reducing significantly the posterior results but are less relevant for fission rate distribution in reference and voided configurations.

Diagnostic errors in patients with diseases of the chest cavity and ways to reduce them

This paper presents an algorithm for reducing the risk of errors in the diagnosis of diseases of the chest cavity within 14 days after treatment of patients. The developed algorithm, based on multivariate analysis of the integrated assessment of clinical and radiological descriptors (signs) of diseases, determination of the probability coefficient of errors, software for comparing individual integral data with established typical characteristics for differentiable pathological processes, improved diagnostics, aimed the doctor at an adequate examination, and reduced the risk of error by 20.1%.

Learn-ing-Based On-AP TCP Performance Enhancement

Data transmissions suffer from TCP’s poor performance since the introduction of the first commercial wireless services in the 1990s. Recent years have witnessed a surge of academia and industry activities in the field of TCP performance optimization. For a TCP flow whose last hop is a wireless link, congestions in the last hop dominate its performance. We implement an integral data sampling, network monitoring, and rate control software-defined wireless networking (SDWN) system. By analysing our sampled data, we find that there exist strong relationships between congestion packet loss behaviors and the instant cross-layer network metric measurements (states). We utilize these qualitative relationships to predict future congestions in wireless links and enhance TCP performance by launch necessary rate control locally on the access points (AP) before the congestions. We also implement modeling and rate control modules on this platform. Our platform senses the instant wireless dynamic and takes actions promptly to avoid future congestions. We conduct real-world experiments to evaluate its performance. The experiment results show that our methods outperform the bottleneck bandwidth and RTT (BBR) protocol and a recently proposed protocol Vivace on throughput, delay, and jitter performance at least 16.5%, 25%, and 12.6%, respectively.