Abstract
In some industries, recruiting qualified resources can be a problem for SMEs, one option is to start a transformation process, and move from a traditional team to a distributed team, gaining access to a much larger base of possible human resources and business opportunities. Digital transformation can be used to help SMEs in taking the steps needed to become distributed companies. This paper shows how applying a lightweight TOGAF-based methodology to an ongoing digital transformation process, specifically targeting a SME information system, can create opportunities for the company.

Abstract

Abstract
Teaching industrial robots by demonstration can significantly decrease the repurposing costs of assembly lines worldwide. To achieve this goal, the robot needs to detect and track each component with high accuracy. To speedup the initial object recognition phase, the learning system can gather information from assembly manuals in order to identify which parts and tools are required for assembling a new product (avoiding exhaustive search in a large model database) and if possible also extract the assembly order and spatial relation between them. This paper presents a detailed analysis of the fine tuning of the Stanford Named Entity Recognizer for this text tagging task. Starting from the recommended configuration, it was performed 91 tests targeting the main features / parameters. Each test only changed a single parameter in relation to the recommend configuration, and its goal was to see the impact of the new configuration in the precision, recall and F1 metrics. This analysis allowed to fine tune the Stanford NER system, achieving a precision of 89.91%, recall of 83.51% and F1 of 84.69%. These results were retrieved with our new manually annotated dataset containing text with assembly operations for alternators, gearboxes and engines, which were written in a language discourse that ranges from professional to informal. The dataset can also be used to evaluate other information extraction and computer vision systems, since most assembly operations have pictures and diagrams showing the necessary product parts, their assembly order and relative spatial disposition. © 2017 IEEE.

Abstract
Software Product Lines (SPLs) are families of systems that share a high number of common assets while differing in others. In component-based systems, components themselves can be SPLs, i.e., each component can be seen as a family of variations, with different interfaces and functionalities, typically parameterized by a set of features and a feature model that specifies the valid combinations of features. This paper explores how to safely replace such families of components with more refined ones. We propose a notion of refinement for Interface Featured Timed Automata (IFTA), a formalism to model families of timed automata with support for multi-action transitions. We separate the notion of IFTA refinement into behavioral and variability refinement, i.e., the refinement of the underlying timed automata and feature model. Furthermore, we define behavioral refinement for the semantic level, i.e., transition systems, as an alternating simulation between systems, and lift this definition to IFTA refinement. We illustrate this notion with examples throughout the text and show that refinement is a pre-order and compositional.

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
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.