Abstract
In the past decades, the resource on the resource-constrained project scheduling problem (RCPSP) has grown rapidly, resulting in an overwhelming amount of solution procedures that provide (near)-optimal solutions in a reasonable time. Despite the rapid progress, little is still known what makes a project instance hard to solve. Inspired by a previous research study that has shown that even small instances with only up to 30 activities is sometimes hard to solve, the current study provides an analysis of the project data used in the academic literature. More precisely, it investigates the ability of four well-known resource indicators to predict the hardness of an RCPSP instance. The study introduces a new instance equivalence concept to show that instances might have very different values for their resource indicators without changing any possible solution for this instance. The concept is based on four theorems and a search algorithm that transforms existing instances into new equivalent instances with more compact resources. This algorithm illustrates that the use of resource indicators to predict the hardness of an instance is sometimes misleading. In a set of computational experiment on more than 10,000 instances, it is shown that the newly constructed equivalent instances have values for the resource indicators that are not only different than the values of the original instances, but also often are better in predicting the hardness the project instances. It is suggested that the new equivalent instances are used for further research to compare results on the new instances with results obtained from the original dataset.

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Abstract
The European Project Semester (EPS) is a multicultural and multidisciplinary project-based learning semester offered by a network of providers, including the Instituto Superior de Engenharia do Porto (ISEP). In the spring of 2020/2021, five EPS@ISEP students from different areas of studies and countries - Portugal, Romania, Poland and France - teamed up. Given the disorganization and overcrowding affecting the experience of attendees at large events, the team decided to create a Crowd Orchestration solution for large outdoor festivals. To this end, the team designed ScanGo with real time alerts about the number of people in predefined areas, suggestion of alternative activities within the event or indication of the best route to go from one stage to the another. This way, ScanGo also intends to minimize the effects of the undergoing pandemic, allowing people to safely experience open air festivals. This paper reports the different stages of the teamwork, encompassing the preliminary studies and the design of ScanGo, followed by the development and test of a proof of concept prototype.

Abstract
Although previous research on the e-learning system acceptance has been conducted usingUTAUT, no study followed the longitudinal approach. Accordingly, this research examines the engineering students' (N = 291) e-learning system acceptance by three years of study. The structural equation modelling analysis confirmed UTAUT relationships in each year. Effort expectancy and social influence resulted as significant predictors of behavioural intention in all three years. In contrast, performance expectancy influence got lower in later usage. Altogether, our longitudinal study presented that the UTAUT model has weakened over time. Therefore, we propose extending the UTAUT model in future research to better understand user satisfaction and positively contribute to system acceptance. Our research findings can be used for university leaders to investigate and evaluate any implemented information system acceptance through the years.

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Abstract
<p>Air ions are ubiquitous in the atmosphere. These charge carriers can be found in various forms as charged molecules, nanoclusters as well as aerosol particles. The population of air ions normally concentrates in the cluster size range (0.8 – 1.7 nm in mobility equivalent diameters) in the absence of particle formation processes. A concentration burst in the intermediate size range (1.7 – 7 nm) can be typically observed during atmospheric new particle formation (NPF) and in precipitation episodes <sup>1</sup>. Contrary to the intermediate ions formed during NPF that favour growth to larger sizes, intermediate ion bursts resulting from precipitation tend to shrink <sup>2,3</sup>. The production of intermediate ions during precipitation has been attributed to the Lenard effect and they are usually referred to as the balloelectric ions <sup>3</sup>.</p><p>During precipitation the rain-out and wash-out of radon progeny increase the gamma dose at ground level <sup>4</sup>. Being a type of ionising radiation, gamma creates positive and negative charges in the air. These charges are either lost in recombination or transformed into air ions. It is therefore interesting to understand whether the precipitation-associated elevation in gamma radiation plays any role in forming or neutralising the balloelectric ions. At SMEAR II station in Hyytiälä, Finland <sup>5</sup>, we have conducted measurements of air ions, gamma radiation, precipitation together with other meteorological parameters. A similar establishment of the measurement set stands also at SMEAR Estonia station in Jarvseljä, Estonia <sup>6</sup>. The data collected at Hyytiälä from 2017.7 to 2018.8 show that the intermediate ion concentration correlates with rainfall only when the precipitation intensity is greater than 1 mm/h. For milder rainfall with the precipitation intensity being 0.1-1 mm/h, the intermediate ion concentration increases with an increase in the gamma counts. The work is under progress and we intend to extend the analysis to Jarvseljä data for a comprehensive understanding of the observations.</p><p>Acknowledgements: This work received financial supports from European Regional Development Fund (project MOBTT42) under the Mobilitas Pluss programme and from Estonian Research Council project PRG714.</p><p>References:</p><p>1. Tammet, H., Komsaare, K. & Hõrrak, U. Intermediate ions in the atmosphere. Atmospheric Research <strong>135-136</strong>, 263-273, doi:10.1016/j.atmosres.2012.09.009 (2014).</p><p>2. Hõrrak, U. et al. Formation of Charged Nanometer Aerosol Particles Associated with Rainfall: Atmospheric Measurements and Lab Experiment. Report Series in Aerosol Science <strong>80</strong>, 180-185 (2006).</p><p>3. Tammet, H., Hõrrak, U. & Kulmala, M. Negatively charged nanoparticles produced by splashing of water. Atmos. Chem. Phys. <strong>9</strong>, 357–367 (2009).</p><p>4. Paatero, J. & Hatakka, J. Wet deposition efficiency of short-lived radon-222 progeny in central Finland. Boreal Env. Res. <strong>4</strong>, 285-293 (1999).</p><p>5. Hari, P. & Kulmala, M. Station for measuring ecosystem-atmosphere relations (SMEAR II). Boreal Environ. Res. <strong>10</strong>, 315-322 (2005).</p><p>6. Noe, S. M. et al. SMEAR Estonia: Perspectives of a large-scale forest ecosystem – atmosphere research infrastructure. Forestry Studies <strong>63</strong>, doi:10.1515/fsmu-2015-0009 (2015).</p>