Abstract
Types in logic programming have focused on conservative approximations of program semantics by regular types, on one hand, and on type systems based on a prescriptive semantics defined for typed programs, on the other. In this paper, we define a new semantics for logic programming, where programs evaluate to true, false, and to a new semantic value called wrong, corresponding to a run-time type error. We then have a type language with a separated semantics of types. Finally, we define a type system for logic programming and prove that it is semantically sound with respect to a semantic relation between programs and types where, if a program has a type, then its semantics is not wrong. Our work follows Milner’s approach for typed functional languages where the semantics of programs is independent from the semantic of types, and the type system is proved to be sound with respect to a relation between both semantics.

Abstract
There is a growing need for fast and accurate methods for testing developmental neurotoxicity across several chemical exposure sources. Current approaches, such as in vivo animal studies, and assays of animal and human primary cell cultures, suffer from challenges related to time, cost, and applicability to human physiology. Prior work has demonstrated success employing machine learning to predict developmental neurotoxicity using gene expression data collected from human 3D tissue models exposed to various compounds. The 3D model is biologically similar to developing neural structures, but its complexity necessitates extensive expertise and effort to employ. By instead focusing solely on constructing an assay of developmental neurotoxicity, we propose that a simpler 2D tissue model may prove sufficient. We thus compare the accuracy of predictive models trained on data from a 2D tissue model with those trained on data from a 3D tissue model, and find the 2D model to be substantially more accurate. Furthermore, we find the 2D model to be more robust under stringent gene set selection, whereas the 3D model suffers substantial accuracy degradation. While both approaches have advantages and disadvantages, we propose that our described 2D approach could be a valuable tool for decision makers when prioritizing neurotoxicity screening. © 2019 IEEE.

Abstract
Relation Extraction (RE) is part of Information Extraction (IE) and aims to obtain instances of semantic relations in textual documents. The countless possibilities of relations, the myriad of subjects, the difficulty in identifying emotions and the amount of unstructured and heterogeneous data, have challenged the researchers to define innovative and even more accurate methodologies. This paper presents the evaluation results obtained with a set of RE systems on identifying semantic relations in criminal police reports. We have evaluated different applications with documents in English and Portuguese. The results obtained give us useful insights to continue the research work, and to design the relation extraction system applied to related domain. © 2019, Springer Nature Switzerland AG.

Abstract
Each person carries digital devices that communicate with other person's devices and may transmit sensitive data. When the transmitted data is sensitive, it becomes necessary to implement secure mechanisms to hide the information and thus avoid it from being analyzed by third parties. This paper aims to present Ncryptr, a web-based application that allows its users to exchange encrypted instant messages in real time. Outside parties are unable to extract the contents of the messages exchanged between two or more users. Ncryptr allows its users to choose the type of encryption employed, being this a major distinction with others already existing instant messaging applications. The performance analysis is made by comparing the efficiency and latency time of different encryption methods, showing the pros and cons of using each one.

Abstract
The IoT (Internet of Things) is a network composed of several devices (things) connected to the Internet and to each other. IoT services are increasingly growing and are allowing companies to deploy scalable solutions with reduced costs and instantaneous data access. These solutions require seamless authentication, data privacy, security, robustness against attacks, easy deployment, and self- maintenance. Such requirements can be given to a company's IoT solution by applying blockchain technology. This paper analyzes the blockchain technology and the advantages and challenges behind its implementation in an IoT environment. A blockchain in IoT scenario was developed to evaluate the performance of different cryptographic hash functions in the IoT device RaspberryPi. Conclusions were drawn when it comes to the viability of some hash functions mainly based on the low resource characteristic shared by the IoT devices, which compromises the performance of the hash function.

Abstract
The crime is spread in every daily newspaper, and particularly on criminal investigation reports produced by several Police departments, creating an amount of data to be processed by Humans. Other research studies related to relation extraction (a branch of information retrieval) in Portuguese arisen along the years, but with few extracted relations and several computer methods approaches, that could be improved by recent features, to achieve better performance results. This paper aims to present the ongoing work related to SEM (Simple Event Model) ontology population with instances retrieved from crime-related documents, supported by an SVO (Subject, Verb, Object) algorithm using hand-crafted rules to extract events, achieving a performance measure of 0.86 (F-Measure). © Gonçalo Carnaz, Vitor Beires Nogueira, and Mário Antunes.