Abstract
The huge amount of genomic and transcriptomic data obtained to characterize human diversity can also be exploited to indirectly gather information on the human microbiome. Here we present the pipeline QmihR designed to identify and quantify the abundance of known microbiome communities and to search for new/rare pathogenic species in RNA-seq datasets. We applied QmihR to 36 RNA-seq tumor tissue samples from Ukrainian gastric carcinoma patients available in TCGA, in order to characterize their microbiome and check for efficiency of the pipeline. The microbes present in the samples were in accordance to published data in other European datasets, and the independent BLAST evaluation of microbiome-aligned reads confirmed that the assigned species presented the highest BLAST match-hits. QmihR is available at GitHub (https://github.com/ Pereira-lab/QmihR).

Abstract
Motivation: The exponential growth of publicly available RNA-sequencing (RNA-Seq) data poses an increasing challenge to researchers wishing to discover, analyse and store such data, particularly those based in institutions with limited computational resources. EMBL-EBI is in an ideal position to address these challenges and to allow the scientific community easy access to not just raw, but also processed RNA-Seq data. We present a Web service to access the results of a systematically and continually updated standardized alignment as well as gene and exon expression quantification of all public bulk (and in the near future also single-cell) RNA-Seq runs in 264 species in European Nucleotide Archive, using Representational State Transfer. Results: The RNASeq-er API (Application Programming Interface) enables ontology-powered search for and retrieval of CRAM, bigwig and bedGraph files, gene and exon expression quantification matrices (Fragments Per Kilobase Of Exon Per Million Fragments Mapped, Transcripts Per Million, raw counts) as well as sample attributes annotated with ontology terms. To date over 270 00 RNA-Seq runs in nearly 10 000 studies (1PB of raw FASTQ data) in 264 species in ENA have been processed and made available via the API.

Abstract

Abstract
The overall aim of the Efficiency Framework is to encourage a culture of continuous improvement and sustainability within manufacturing and process industries. The framework presented supports informed decision-making processes and helps to define strategies for continuous performance improvement. The proposed innovative Efficiency Framework, materialized through the integration of concepts and results provided by eco-efficiency methodology, namely Eco-Efficiency Integrated Methodology for Production Systems (ecoPROSYS) and the lean based resource efficiency assessment method, Multi-layer Stream Mapping (MSM). Thus, the framework assesses simultaneously the environmental, economic and efficiency performance of complex production systems, which helps to identify major inefficiencies and circumstances of low eco-efficiency performance, consequently leading to the definition of improvement priorities. Ultimately, this framework aims to facilitate the overall efficiency performance assessment, by an integrated multi-dimensional analysis, presented as the Total Efficiency Index. The logic behind this index is to combine, for each unit process and for the overall production process, two fundamental efficiency aspects, namely eco-efficiency and operations efficiency.

Abstract
Social Network Analysis (SNA) is an important research area. It originated in sociology but has spread to other areas of research, including anthropology, biology, information science, organizational studies, political science, and computer science. This has stimulated research on how to support SNA with the development of new algorithms. One of the critical areas involves calculation of different centrality measures. The challenge is how to do this fast, as many increasingly larger datasets are available. Our contribution is an incremental version of the Laplacian Centrality measure that can be applied not only to large graphs but also to dynamically changing networks. We have conducted several tests with different types of evolving networks. We show that our incremental version can process a given large network, faster than the corresponding batch version in both incremental and full dynamic network setups.

Abstract
The sharp decrease of the remnant ferroelectric and piezoelectric properties of Pb(Mg1/3Nb2/3)O-3-PbTiO3 (PMNT) thin films close to the Morphotropic Phase Boundary (MPB) respect to their corresponding bulk ceramics is a major drawback for their integration in microdevices. In order to take full advantage of the excellent piezoelectric properties of polycrystalline PMNT in thin film form, a multilayer configuration with PbTiO3 (PT) layers is proposed. The PT layers generate an internal electric bias within the PMNT layer, which anchor an induced polarization in it. This results in a significant improvement of the piezoelectric behavior, obtaining remnant piezoelectric coefficients, d(33) (r), as high as 67 pm V-1. The role of the thickness of the PT layers used is discussed, in order to find the optimum configuration for these multilayers.