This study proposes a fuzzy analytic hierarchy process (FAHP) method to support strategic decision-makers in choosing a project management research agenda. The analytical hierarchy process (AHP) model is the basic tool used in this study. It is a mathematical tool for evaluating decisions with multiple alternatives by decomposing them into successive levels according to their degree of importance. The Sustainable Development Goals (SDG) oriented theme of project management was chosen from among four themes that emerged from a strategic monitoring study. The FAHP method is an effective decision-making tool for multiple aspects of project management. It eliminates subjectivity and produces decisions based on consistent judgment.

Regarding to the influence of chloride and fluoride ions on the corrosion resistance, the electrochemical behavior of Ti alloys has been deeply studied. In this work, the main goal was to investigate the electrochemical behavior of cp-Ti and Ti-Mo alloys containing 6, 10 and 15 wt% of Mo concentrations. All the samples were immersed in different solutions, such as 0.15 mol L^-1 Na₂SO₄, 0.15 mol L^-1 Ringer, 0.15 mol L^-1 Ringer plus 0.036 mol L^-1 NaF and 0.036 mol L^-1 NaF. Simulating the commercial fluorinated gels, the NaF solutions naturally-aerated were prepared with 1450 ppm of fluoride ions. The electrochemical techniques applied in this work were the open-circuit potential, cyclic voltammetry, besides the technique for chemical identification, which was X-ray photoelectron spectroscopy. The formation and growth of TiO₂ and MoO₂ were identified, without pitting corrosion. The electrochemical stability and the corrosion resistance of the Ti-Mo alloys decreased in the solutions containing chloride and fluoride ions, with an appreciative decrease especially in the fluorinated medium. The Ti-Mo alloy with higher Mo content concentration was the material with higher corrosion resistance. Therefore, it is a promising candidate as a biomaterial, once the osseointegration needs a satisfactory corrosion resistance for being achieved.

The application of governance in recent years appears as a tool of entities that organize sport. Considering this aspect, it was observed that many sports entities present problems in following mechanisms to improve management, both in national and international contexts. Governance materializes with principles of transparency, accountability, equity, institutional integrity, and modernity, in order to aid sports entities. Thus, the development of sports entities could improve management, professionalization, and innovation. Based on the aforementioned, this article aims to demonstrate whether the principles of governance found in the literature are contemplated in Brazilian sports confederations, pointing to the possibility of finding distinct characteristics among the confederations, and the confederation with the highest index for Brazilian sports. The methodology is a longitudinal discursive analysis. The results use data from 2015 to 2022 from the Sou do Esporte Governance Awards and the analysis is based on five governance principles; transparency, equity, accountability, institutional integrity, and modernity. The confederations were found to have adopted the principles of governance to improve, professionalize, and optimize their sports management. The results suggest that the use of governance can enhance the confederations and improve the management, legitimacy, and development of sports in Brazil. The authors consider the nuances reported in the study as imperative to improve the progress of Brazilian sports, and the contribution made could generate other discussions in different contexts and countries.

The construction of gas plants often experiences delays caused by various factors, which can lead to significant financial and operational losses. This research aims to develop an accurate risk model to improve the schedule performance of gas plant projects. The model uses Quantitative Risk Analysis (QRA) and Monte Carlo simulation methods to identify and measure the risks that most significantly impact project schedule performance. A comprehensive literature review was conducted to identify the risk variables that may cause delays. The risk model, pre-simulation modeling, result analysis, and expert validation were all developed using a Focused Group Discussion (FGD). Primavera Risk Analysis (PRA) software was used to perform Monte Carlo simulations. The simulation output provides information on probability distribution, histograms, descriptive statistics, sensitivity analysis, and graphical results that aid in better understanding and decision-making regarding project risks. The research results show that the simulated project completion timeline after mitigation suggested an acceleration of 61–65 days compared to the findings of the baseline simulation. This demonstrates that activity-based mitigation has a major influence on improving schedule performance. This research makes a significant contribution to addressing project delay issues by introducing an innovative and effective risk model. The model empowers project teams to proactively identify, measure, and mitigate risks, thereby improving project schedule performance and delivering more successful projects.

Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.

The use of different energy sources and the worry of running out of some of them in the modern world have made factors such as environmental pollution and even energy sustainability vital. Vital resources for humanity include water, environment, food, and energy. As a result, building strong trust in these resources is crucial because of their interconnected nature. Sustainability in security of energy, water and food, generally decreases costs and improves durability. This study introduces and describes the components of a system named “Desktop Energetic Dark Greenhouse” in the context of the quadruple nexus of water, environment, food, and energy in urban life. This solution can concurrently serve to strengthen the sustainable security of water, environment, food, and energy. For home productivity, a small-scale version of this project was completed. The costs and revenues for this system have been determined after conducting an economic study from the viewpoints of the investor and the average household. The findings indicate that the capital return period is around five years from the investor’s perspective. The capital return on investment for this system is less than 4 years from the standpoint of the households. According to the estimates, this system annually supplies about 20 kg of vegetables or herbs, which means about one third of the annual needs of a family.