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
Breast cancer is one of the most common malignanciesaffecting women worldwide. However, despite its incidence trends have increased, the mortality rate has significantly decreased. The primary concern in any cancer treatment is the oncological outcome but, in the case of breast cancer, the surgery aesthetic result has become an important quality indicator for breast cancer patients. In this sense, an adequate surgical planning and prediction tool would empower the patient regarding the treatment decision process, enabling a better communication between the surgeon and the patient and a better understanding of the impact of each surgical option. To develop such tool, it is necessary to create complete 3D model of the breast, integrating both inner and outer breast data. In this review, we thoroughly explore and review the major existing works that address, directly or not, the technical challenges involved in the development of a 3D software planning tool in the field of breast conserving surgery.

Abstract
Endoscopic capsules are vitamin-sized devices that create 8 to 10 hour videos of the digestive tract. They are the leading diagnosing method for the small bowel, a region not easily accessible with traditional endoscopy techniques. However, these capsules do not provide localization information, even though it is crucial for the diagnosis, follow-ups and surgical interventions. Currently, the capsule localization is either estimated based on scarce gastrointestinal tract landmarks or given by additional hardware that causes discomfort to the patient and represents a cost increase. Current software methods show great potential, but still need to improve in order to overcome their limitations. In this work, a visual odometry method for capsule localization inside the small bowel is proposed.

Abstract
Skeletal muscle dispersion and optical clearing (OC) kinetics were studied experimentally to prove the existence of the refractive index (RI) matching mechanism of OC. Sample thickness and collimated transmittance spectra were measured during treatments with glucose (40%) and ethylene glycol (EG; 99%) solutions and used to obtain the time dependence of the RI of tissue fluids based on the proposed theoretical model. Calculated results demonstrated an increase of RI of tissue fluids and consequently proved the occurrence of the RI matching mechanism. The RI increase was observed for the wavelength range between 400 and 1000 nm and for the 2 probing molecules explored. We found that for 30 min treatment with 40% glucose and 99% EG, RI of sarcoplasm plus interstitial fluid was increased at 800 nm from 1.328 to 1.348 and from 1.328 to 1.369, respectively.

Abstract
High data rate optical fiber links are usually deployed in core IP networks to transport bulky [...]

Abstract
Security attacks using USB interfaces and devices are becoming more advanced, which boost efforts to develop counter measures in order to protect systems and data. One of the most recent attacks using USB devices is the BadUSB attack, performed by spoofing the device’s firmware and allowing the attackers to execute a set of malicious actions, e.g. an USB storage device could be mounted as USB keyboard in order to inject malicious scripts into the system. This paper proposes a protection agent against BadUSB attack developed for Windows operative systems. It allows a user to check the class of an USB device ready to be mounted, though enabling the detection of a potential attack if the expected functionality of the device does not match with its class type. The results show that the proposed protection agent is capable of detecting potential intrusions by blocking the installation of the device, scanning the device for something that identifies it, searching for a description locally and finally warning the user about the device meaning that all devices must be approved by the user when plugged in if the system protection agent is running. Copyright