Abstract
Imaging and chromosome conformation capture studies have revealed several layers of chromosome organization, including segregation into megabase-sized active and inactive compartments, and partitioning into sub-megabase domains (TADs). It remains unclear, however, how these layers of organization form, interact with one another and influence genome function. Here we show that deletion of the cohesin-loading factor Nipbl in mouse liver leads to a marked reorganization of chromosomal folding. TADs and associated Hi-C peaks vanish globally, even in the absence of transcriptional changes. By contrast, compartmental segregation is preserved and even reinforced. Strikingly, the disappearance of TADs unmasks a finer compartment structure that accurately reflects the underlying epigenetic landscape. These observations demonstrate that the three-dimensional organization of the genome results from the interplay of two independent mechanisms: cohesin-independent segregation of the genome into fine-scale compartments, defined by chromatin state; and cohesin-dependent formation of TADs, possibly by loop extrusion, which helps to guide distant enhancers to their target genes.

Abstract
This chapter presents the early stages of a metadata application profile (MAP) development that uses a process of reverse engineering. The context of this development is the European poetry, more specifically the poetry metrics and all dimensions that exist around this context. This community of practice has a certain number of digital repertoires that store this information and that are not interoperable. This chapter presents some steps of the definition of the MAP Domain Model. It shows how the developers having as starting point these repertoires, and by means of a reverse engineering process are modeling the functional requirements of each repertoire using the use-case modeling technique and are analyzing every database logical models to extract the conceptual model of each repertoire. The final goal is to develop a common conceptual model in order to use it as basis, together with other sources of information, for the definition of the Domain Model.

Abstract
"Masseiras" is an ancient Portuguese agriculture system, where soil was developed from sand dunes enriched with seaweeds over more than a century. Due to the importance for the local economy, this system evolved for greenhouse structures. In this study we compared the bacterial community composition and structure of "Masseiras" soil, aiming at assessing the potential impact of different agricultural practices. The bulk soil of two greenhouses (following or not the recommended agriculture good practices, FGP and NFGP, respectively) was compared based on their physicochemical properties and bacterial community. In both FGP and NFGP, Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes, and Gemmatimonadetes were in a proportion of 5:1:1:1:1:1. However, the bacterial community of soil FGP was richer and more diverse than that of soil NFGP. Members of the classes Bacilli and Gemm-1, with higher relative abundance in NFGP and FGP, respectively, were those contributing most for distinguishing the bacterial communities of both soils. The differences in the structure of the bacterial communities correlated (Mantel test) with some soil physicochemical properties, such as electrical conductivity and nitrate and Zn contents, which were significantly higher in soil NFGP than in soil FGP.

Abstract
Background and Objectives: In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window. Methods: The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacketml while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way. Results: A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis. Conclusions: The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.

Abstract

Abstract
In this work we present a greenhouse case study with a new energy model based on a Biomass energy source, once it is a more profitable and sustainable energy system, but demands special safety measures. Biomass has some dangerous aspects along the process from transport, to storage until its' use. The paper foccus on safety for equipment operation, storage of biofuels, the design of the facilities and health of the employees, in a context of primary renewable energy source of greenhouses farming systems, for intensive cultivation of flowers and vegetables for human consumption. Similarly, exposure to biologically active material (mustiness and spores) may constitute a danger to the health of those involved in handling biomass. These properties and their use determine safety conditions in handling and storage. This energy model is constituted with several proposals, both technological and energy alternatives/renewable energy, to meet the needs of electric power and heat, with the objective of increasing the competitiveness in agricultural greenhouses, in the management, financial and environmental aspects. The model was developed with the purpose of improving efficiency and sustainability, with the inclusion of sensors that allow controlling the various components of a greenhouse, with the perspective of a quick distribution in the market, increasing the economic benefits and supported on efficient and intelligent management systems energy.