Abstract
This paper puts forth new recovery guarantees for the source separation problem in the presence of side information, where one observes the linear superposition of two source signals plus two additional signals that are correlated with the mixed ones. By positing that the individual components of the mixed signals as well as the corresponding side information signals follow a joint Gaussian mixture model, we characterise necessary and sufficient conditions for reliable separation in the asymptotic regime of low-noise as a function of the geometry of the underlying signals and their interaction. In particular, we show that if the subspaces spanned by the innovation components of the source signals with respect to the side information signals have zero intersection, provided that we observe a certain number of measurements from the mixture, then we can reliably separate the sources, otherwise we cannot. We also provide a number of numerical results on synthetic data that validate our theoretical findings.

Abstract
We present a novel model for the characterization of musical rhythms that is based on the pervasive rhythmic phenomenon of syncopation. Syncopation is felt when the sensation of the regular beat or pulse in the music is momentarily disrupted; the feeling arises from breaking more expected patterns such as pickups (anacrusis) and faster events that introduce and bridge the notes articulated on the beats. Our model begins with a simple pattern that articulates a beat consistent with the metrical expectations of a listener. Any rhythm is then generated from a unique combination of transformations applied on that simple pattern. Each transformation introduces notes in off-beat positions as one of three basic characteristic elements: (1) syncopations, (2) pickup rhythmic figures and (3) faster notes that articulate a subdivision of the beat. The characterization of a pattern is based on an algorithm that discovers and reverses the transformations in a stepwise manner. We formalize the above transformations and present the characterization algorithm, and then demonstrate and discuss the model through the analysis of the main rhythmic pattern of the song Don't stop till you get enough' by Michael Jackson.

Abstract
Service organizations increasingly understand the importance of managing the customer experience to enhance customer satisfaction and loyalty. This study aims to develop a better understanding of the customer experience by investigating how the customer’s internal mechanisms influence it. That is, how it is perceived and processed at three different levels (visceral, behavioral and reflective), which determines a person’s cognitive and emotional state. To this purpose an exploratory multi-method ethnographic study was undertaken in a healthcare service. The results showed the emotions provoked by the service experience at each level. These levels are interconnected and impact each other working together to influence a person’s cognitive and emotional state, and thus playing a critical role in the overall evaluation of a service. Results show that elements such as servicescape aesthetics, face-to-face and non-human interactions influence emotions and service evaluations. The service should be designed in a way that induces positive emotions, and a feeling of being in control. Especially in healthcare services there is a need to balance the conflicting responses of the emotional stages that may be triggered at the visceral and behavioral levels, while providing reassurance and calm at the reflective level that the health problem is going to be taken care. Using service design approaches this understanding of the customers’ brain can be translated into improving the customer experience. © 2018, Springer Nature Switzerland AG.

Abstract
Social networks, originally built as channels for personal interaction, are being used in the commercial market as a support for product sales. The use of applications integrated in social networks appears as an opportunity to explore by companies. Facestore emerged in 2013 as the first e-commerce solution integrated in social networks, allowing the creation of online stores within Facebook, without the customer having to leave the social network interface. Operations like looking into the catalog, choosing the product, and paying the transaction is carried out without the customer need to open a new website. The use of Facestore offers direct and indirect benefits on the different areas of an organization. At the direct level, there are changes in processes in terms of customer service and marketing and sales. However, its use also potentiates indirect benefits in other organizational areas, such as operations, finance, administration and information technologies support, human resources, and research and development.

Abstract
Lung function tests are critical for diagnosis and monitoring of asthma and other respiratory diseases. Monitoring of lung function, in the absence of a healthcare professional, is very challenging but may be obtained through Smart Devices if_automated quality assessment systems guarantee the proper technique during the forced expiratory manoeuvre. This paper describes the evaluation of one such system that uses the microphone of smart devices, regarding the initial effort of forced expiratory manoeuvres using the Back Extrapolated Volume. A health professional recorded microphone spirometry in 55 children (5-10 years), using a mobile game engineered for the purpose, and registered its quality. At least one acceptable manoeuvre was achieved for 96% of the children using a featured threshold. Using a stricter threshold of 5% of forced vital capacity, it was possible to ensure at least one acceptable manoeuvre for 69%. While the obtained results are comparable to findings in literature for regular spirometry in this age group, further work is required before we can determine whether the proposed algorithm is effective in real life. Copyright

Abstract
The Internet of Things is progressively getting broader, evolving its scope while creating new markets and adding more to the existing ones. However, both generation and analysis of large amounts of data, which are integral to this concept, may require the proper protection and privacy-awareness of some sensitive information. In order to control the access to this data, allowing devices to verify the reliability of their own interactions with other endpoints of the network is a crucial step to ensure this required safeness. Through the implementation of a blockchain-based Public Key Infrastructure connected to the Keybase platform, it is possible to achieve a simple protocol that binds devices’ public keys to their owner accounts, which are respectively supported by identity proofs. The records of this blockchain represent digital signatures performed by this Keybase users on their respective devices’ public keys, claiming their ownership. Resorting to this distributed and decentralized PKI, any device is able to autonomously verify the entity in control of a certain node of the network and prevent future interactions with unverified parties.