Abstract
Modern mobile ticketing service solutions facilitate access to mobility services and free customers from difficult purchasing decisions. However, implementing these solutions is complex, as they involve many different stakeholders, with sometimes conflicting interests. This paper presents a survey of mobile ticketing services in the urban mobility context. It starts by defining mobile ticketing and explores the different electronic ticket schemes that are being implemented around the world, as well as the most used technologies to provide the service. Then, it addresses the complex mobile ticketing ecosystem, identifying the main actors involved, their motivations, and concerns. This allows the authors to define their role and contribution to the mobile ticketing ecosystem. Finally, the paper presents future trends and research directions related to mobile ticketing services, being a valuable guide for researchers and practitioners.

Abstract

Abstract
This article describes a classification model of optical coherence tomography images using convolution neural network. The dataset used was the Labeled Optical Coherence Tomography provided by (Kermany et al., 2018) with a total of 84495 images, with 4 classes: normal, drusen, diabetic macular edema and choroidal neovascularization. To evaluate the generalization capacity of the models k-fold cross-validation was used. The classification models were shown to be efficient, and as a result an average accuracy of 94.35% was obtained.

Abstract
The rapid expansion of high-quality genome assemblies, exemplified by ongoing initiatives such as the Genome-10K and i5k, demands novel automated methods to approach comparative genomics. Of these, the study of inactivating mutations in the coding region of genes, or pseudogenization, as a source of evolutionary novelty is mostly overlooked. Thus, to address such evolutionary/genomic events, a systematic, accurate and computationally automated approach is required. Here, we present PseudoChecker, the first integrated online platform for gene inactivation inference. Unlike the few existing methods, our comparative genomics-based approach displays full automation, a built-in graphical user interface and a novel index, PseudoIndex, for an empirical evaluation of the gene coding status. As a multi-platform online service, PseudoChecker simplifies access and usability, allowing a fast identification of disruptive mutations. An analysis of 30 genes previously reported to be eroded in mammals, and 30 viable genes from the same lineages, demonstrated that PseudoChecker was able to correctly infer 97% of loss events and 95% of functional genes, confirming its reliability. PseudoChecker is freely available, without login required, at http://pseudochecker.ciimar.up.pt.

Abstract
With the increasing complexity of software systems, software developers would benefit from instant and continuous feedback about the system they are maintaining and evolving. Despite existing several solutions providing feedback and suggesting improvements, many tools require explicit invocations, leading developers to miss some improvement opportunities, such as important refactorings, due to the loss of their train of thought. Therefore, to address these limitations, we developed a Visual Studio Code plugin providing real-time feedback - - and also information about each commit made to the version control system. This tool is also capable of recommending two types of refactorings. To validate this approach, we did a preliminary controlled experiment using hypothesis-tests to check specific results. However, in this initial stage, we didn't have enough data to confirm our research questions, and we weren't able yet to confirm the main hypothesis.

Abstract
A main problem for predicting cell line interactions with chemical compounds is the lack of a computational representation for cell lines. We describe a method for characterizing cell lines from scientific literature. We retrieve and process cell line-related scientific papers, perform a document classification algorithm, and then obtain a description of the information space of each cell line. We have successfully characterized a set of 300+ cell lines.