Abstract
Although deep learning is being widely adopted for every topic in pattern recognition, its use for secure and cance-lable biometrics is currently reserved for feature extraction and biometric data preprocessing, limiting achievable performance. In this paper, we propose a novel formulation of the triplet loss methodology, designated as secure triplet loss, that enables biometric template cancelability with end-to-end convolutional neural networks, using easily changeable keys. Trained and evaluated for electrocardiogram-based biometrics, the network revealed easy to optimize using the modified triplet loss and achieved superior performance when compared with the state-of-the-art (10.63% equal error rate with data from 918 subjects of the UofTDB database). Additionally, it ensured biometric template security and effective template cancelability. Although further efforts are needed to avoid template linkability, the proposed secure triplet loss shows promise in template cancelability and non-invertibility for biometric recognition while taking advantage of the full power of convolutional neural networks.

Abstract
Motivated by the Fourth Industrial Revolution, there is an ever-increasing need to integrated Cyber-Physical Systems in industrial production environments. To address the demand for flexible robotics in contemporary industrial environments and the necessity to integrate robots and automation equipment in an efficient manner, an effective, bidirectional, reliable and structured data interchange mechanism is required. As an answer to these requirements, this article presents ROBIN, an open-source middleware for achieving interoperability between the Robot Operating System and CODESYS, a softPLC that can run on embedded devices and that supports a variety of fieldbuses and industrial network protocols. The referred middleware was successfully applied and tested in various industrial applications such as battery management systems, motion, robotic manipulator and safety hardware control, and horizontal integration between a mobile manipulator and a conveyor system.

Abstract
A method based on multiple Fiber Bragg Gratings (FBG) and a structure fabricated using a 3D printer for diameter measurement is proposed and experimentally demonstrated. The sensor is easily developed inserting the FBG on the structure and fixing the FBG in two points. Due to this arrangement, when the diameter is reduced a force is applied on the sensor and this causes a wavelength shift. The study is divided in two steps using one experimental setup. At first, each FBG response is independently evaluated concerning the diameter variation and after that, the FBGs are evaluated together. The results demonstrated that the structure can be used as a way to monitor the diameter variation in some applications.

Abstract
We show that a monopolist's profit is higher if he refrains from collecting coarse information on his customers, sticking to constant uniform pricing rather than recognizing customers' segments through their purchase history. In the Markov perfect equilibrium with coarse information collection, after each commitment period, a new introductory price is offered to attract new customers, creating a new market segment for price discrimination. Eventually, the whole market is covered. Shortening the commitment period results in lower profits. These results sharply differ from the ones obtained when the firm can uncover the exact willingness-to-pay of each previous customer.

Abstract
Payments using cryptocurrencies may require that the user is able to provide proof of ownership and proof of provenance for a specific transaction. In this paper an innovative web based solution is proposed as a framework that issues reports, on request, pertaining proof of ownership and proof of provenance. The proposed framework provides proof of ownership by using micro-payments and, when used recursively, it can produce provenance reports up to a defined granularity level of transactions. A proof of concept prototype of the proposed framework was implemented and its operation and output is presented and explained. Some limitations and future work directions are also identified. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

Abstract
Blood banks face inventory management problems associated to demand uncertainty and high inventory levels. An efficient blood inventory management is related to the use of simple, transparent and easy-to-understand procedures by blood banks’ employees. However, the literature about good practices in blood bank inventory management is scarce, reinforcing new developments need on this subject to ensure a good availability of blood products and reducing wastage. This research presents a blood inventory management system implemented in software, DOAR, able to meet demand while minimizing blood bags wastage. DOAR is simple, user-friendly and able to optimize blood inventory and donations. The purpose of the software is to provide a link between the demand by blood components and collected blood bags.