Radiomics and Machine Learning in Oral Healthcare

The increasing storage of information, data, and forms of knowledge has led to the development of new technologies that can help to accomplish complex tasks in different areas, such as in dentistry. In this context, the role of computational methods, such as radiomics and Artificial Intelligence (AI) applications, has been progressing remarkably for dentomaxillofacial radiology (DMFR). These tools bring new perspectives for diagnosis, classification, and prediction of oral diseases, treatment planning, and for the evaluation and prediction of outcomes, minimizing the possibilities of human errors. A comprehensive review of the state‐of‐the‐art of using radiomics and machine learning (ML) for imaging in oral healthcare is presented in this paper. Although the number of published studies is still relatively low, the preliminary results are very promising and in a near future, an augmented dentomaxillofacial radiology (ADMFR) will combine the use of radiomics‐based and AI‐based analyses with the radiologist's evaluation. In addition to the opportunities and possibilities, some challenges and limitations have also been discussed for further investigations.     

Strategy for a Scale‐up Correlation in a Dissolved Air Flotation Chamber

Beginning with a laboratory‐scale physical model, a scale‐up correlation for a pilot unit project was determined based on the analysis of dynamic similarity correlations involving the predominant phenomena of a dissolved air flotation (DAF) chamber. The implantation costs of pilot units require special strategies due to the lack of correlations of this type, as novel flotation methods have been considered strictly from an economic standpoint. With the aid of computational fluid dynamics and videos of microbubble and floc flow, inertia and gravity were identified as the predominant phenomena in a DAF chamber. The strategy described herein is simple and reduces the likelihood of future risks in scale‐up investments.     

Building a bridge between performance management,radical innovation,and innovation networks: A systematic literature review

Research on performance management (PM) of networks and radical innovation has largely developed along two isolated paths. On the one hand, a growing body of knowledge addresses the use of performance management systems in the context of networks (notably for production and incremental innovation). On the other hand, radical innovation scholars have shown how innovation initiatives that are more uncertain demand the use of new approaches (e.g., new project management routines or different evaluative tools for portfolios). Some scholars even suggest that traditional PM may suppress radical innovation. Our study takes a different approach. It aims to bridge radical innovation and network performance management through a systematic review of the literature. Here, we adopt a hybrid approach that combines bibliometrics with content analysis. Whereas the literature often separates the issues of network performance management and radical innovation, our contribution expands the theory of network management and radical innovation by developing a conceptual framework based on these concepts, thus combining them. We also offer suggestions for further research on this approach. Our framework suggests that overall, the performance management of radical innovation networks presents different features (e.g., recursive rather than linear) and constructs (e.g., openness and unintended performance) from those of innovation network management.     

Intrinsic Fluorescence of the Active and the Inactive Functional Forms of Human Thymidylate Synthase

The observables associated with protein intrinsic fluorescence – spectra, time decays, anisotropies – offer opportunities to monitor in real time and non-invasively a protein‘s functional form and its interchange with other forms with different functions. We employed these observables to sketch the fluorometric profiles of two functional forms of human thymidylate synthase (hTS), a homodimeric enzyme crucial for cell proliferation and thus targeted by anticancer drugs. The protein takes an active and an inactive form. Stabilization of the latter by peptides that, unlike classical hTS inhibitors, bind it at the monomer/monomer interface offers an alternative inhibition mechanism that promises to avoid the onset of drug resistance in anticancer therapy. The fluorescence features depicted herein can be used as tools to identify and quantify each of the two protein forms in solution, thus making it possible to investigate the kinetic and thermodynamic aspects of the active/inactive conformational interchange. Two examples of fluorometrically monitored interconversion kinetics are provided.     

The renewable energy market in Brazil: Current status and potential

Renewable energy offers a range of options with which to meet the growing demand for energy, particularly in the context of the pursuit (especially in developing countries) of economic development which takes into account social and environmental issues. Brazil has abundant natural sources of renewable energy, such as wind and solar power, hydraulic energy, small hydroelectric plants, ethanol and bio-diesel. These sources form part of the Brazilian strategy aimed at satisfying the demand for 6300 MW of fresh capacity per year arising out of projected economic growth of 5.1% per year over the next 10 years. Renewable energy sources currently provide 47.2% of the internal supply of primary energy in Brazil. Brazil has been pursuing a strategy of maintaining its renewable energy matrix and developing and providing incentives for further low carbon initiatives.In this study we set out an overview of the renewable energy options available in Brazil, their current status, the main positive results obtained to date and future potential. We describe the market for renewable energy in Brazil and examine specific public policies aimed at overcoming barriers to this market, thereby promoting its consolidation and expansion.     

Optimal design of extractive distillation columns—A systematic procedure using a process simulator

The separation of binary mixtures which form azeotropes is not possible through conventional distillation and they are usually separated by extractive or azeotropic distillation. The optimization of extractive distillation columns is usually performed using a process simulator; however, normally, the result is only obtained after several simulations and the simultaneous analysis of several graphs. This paper sets out to present a systematic procedure, using a process simulator (Aspen Plus^®), in order to obtain the optimum condition for extractive distillation columns. The optimization achieved is characterized by the fact that it is not necessary to perform various simulations, and it also avoids the simultaneous analysis of dozens of curves. The dehydration of aqueous mixtures of ethanol using ethylene glycol as solvent was the system chosen as a case study.     

Inhibitory action of aqueous coffee ground extracts on the corrosion of carbon steel in HCl solution

The effects of aqueous extracts of spent coffee grounds on the corrosion of carbon steel in a 1 mol L⁻¹ HCl were examined. Two methods of extraction were studied: decoction and infusion. The inhibition efficiency of C-steel in 1 mol L⁻¹ HCl increased as the extract concentration and temperature increased. The coffee extracts acted as a mixed-type inhibitor with predominant cathodic effectiveness. In this study, the adsorption process of components of spent coffee grounds extracts obeyed the Langmuir adsorption isotherm. The chlorogenic acids isolated do not seem to explain the corrosion inhibition observed during the use of the coffee extracts.