Abstract
This article presents Kadabra, a Java source-to-source compiler that allows users to make code queries, code analysis and code transformations, all user-programmable using the domain-specific language LARA. We show how Kadabra can be used as the basis for developing a runtime autotuning and adaptivity framework, able to adapt existing source Java code in order to take advantage of runtime autotuning. Specifically, this article presents the framework, consisting of Kadabra and an API for runtime adaptivity. We show the use of the framework to extend Java applications with autotuning and runtime adaptivity mechanisms to target performance improvement and/or energy saving goals.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Abstract
As gamification spreads to new areas, new applications are being developed and the interest in evaluating gamified systems continues to grow. To date, however, no one has comprehensively approached this topic: multiple evaluation dimensions and measures have been proposed and applied without any effort to organize them into a full gamut of tools for the multi-dimensional evaluation of gamified systems. This paper addresses this gap by proposing GATUGU, a set of six perspectives of evaluation of gamified systems: General effects of gamification, Area-specific effects of gamification, Technical quality of gamified systems, Use of gamified systems, Gamefulness of gamified systems, and User experience of gamified systems. For each perspective, GATUGU indicates the relevant dimensions of evaluation, and, for each dimension, one measure is suggested. GATUGU does not introduce any new measurement tools but merely recommends one of the available tools for each dimension, considering their popularity and ease of use. GATUGU can guide researchers in selecting gamification system evaluation perspectives and dimensions and in finding adequate measurement tools. Thanks to conforming to GATUGU, the published gamification system evaluation results will become easier to compare and to perform various kinds of meta-analyses on them.

Abstract
Performance of transactional systems is degraded by update hotspots as conflicts lead to waiting and wasted work. This is particularly challenging in emerging large-scale database systems, as latency increases the probability of conflicts, state-of-the-art lock-based mitigations are not available, and most alternatives provide only weak consistency and cannot enforce lower bound invariants. We address this challenge with Multi-Record Values (MRVs), a technique that can be layered on existing database systems and that uses randomization to split and access numeric values in multiple records such that the probability of conflict can be made arbitrarily small. The only coordination needed is the underlying transactional system, meaning it retains existing isolation guarantees. The proposal is tested on five different systems ranging from DBx1000 (scale-up) to MySQL GR and a cloud-native NewSQL system (scale-out). The experiments explore design and configuration trade-offs and, with the TPC-C and STAMP Vacation benchmarks, demonstrate improved throughput and reduced abort rates when compared to alternatives.

Abstract
This work presents a multi-parameter optical fiber monitoring solution applied to an underground power distribution network. The monitoring system demonstrated herein uses Fiber Bragg Grating (FBG) sensors to measure multiple parameters, such as the distributed temperature of the power cable, external temperature and current of the transformers, liquid level, and intrusion in the underground manholes. To monitor partial discharges of cable connections, we used sensors that detect radio frequency signals. The system was characterized in the laboratory and tested in underground distribution networks. We present here the technical details of the laboratory characterization, system installation, and the results of 6 months of network monitoring. The data obtained for temperature sensors in the field tests show a thermal behavior depending on the day/night cycle and the season. The temperature levels measured on the conductors indicated that in high-temperature periods, the maximum current specified for the conductor must be reduced, according to the applied Brazilian standards. The other sensors detected other important events in the distribution network. All the sensors demonstrated their functionality and robustness in the distribution network, and the monitored data will allow the electric power system to have a safe operation, with optimized capacity and operating within tolerated electrical and thermal limits.

Abstract
The MiFiRE (Microgravity Fine Regolith Experiment) experiment, which will be launched this year on a suborbital space flight, currently scheduled for August 2023, was designed with the aim of better understanding the initial stages of planetary formation. The fundamental and embryonic question is to contribute to the study of how the mineral and rock particles, which do not have enough mass for the gravitational force to be influential, can then aggregate through electrostatic forces. In order to recreate the environment of deep space, it is assumed that the composition of meteorites that collide with the Earth, are mainly of silicate mineralogical composition or rich in metallic alloys (eg Fe-Ni). Therefore, in the experiment some fine material, identical to the lunar regolith (JSC-1), is used, in other words, amphiboles, pyroxenes, olivines and volcanic glass, along with two larger elements, a basalt cube and a metalic (siderite) meteorite cube (Octahedrite from Campo del Cielo, Argentina). It is intended that the particles be subjected to the microgravity environment and thus contribute to a better understanding of the general behaviour and the processes of preference of aggregation between the various components. This, in turn, contributes the characterization of the progressive development of planetesimals. This experiment was selected amongst 5 competing proposals in a contest launched by Massachusetts Institute of Technology's national representation, MIT Portugal, in 2020. © 2023 International Multidisciplinary Scientific Geoconference. All rights reserved.

Abstract
In the last few years we have been seeing a drastic change in the way software is developed. Large-scale software projects are being assembled by a flexible composition of many (small) components possibly written in different programming languages and deployed anywhere in the cloud - the so-called microservices-based applications. The dramatic growth in popularity of microservices-based applications has pushed several companies to apply major refactorings to their software systems. However, this is a challenging task that may take several months or even years. We propose a methodology to automatically evolve monolithic web applications that use object-relational mapping into microservices-based ones. Our methodology receives the source code and a microservices proposal and refactors the original code to create each microservice. Our methodology creates an API for each method call to classes that are in other services. The database entities are also refactored to be included in the corresponding service. The evaluation performed in 120 applications shows that our tool can successfully refactor about 72% of them. The execution of the unit tests in both versions of the applications yield exactly the same results.