Applications of artificial intelligence in dentistry: A comprehensive review

This work was funded by the Spanish Ministry of Sciences, Innovation and Universities under Projects RTI2018-101674-B-I00 and PGC2018-101904-A-100, University of Granada project A.TEP. 280.UGR18, I+D+I Junta de Andalucia 2020 project P20-00200, and Fapergs/Capes do Brasil grant 19/25510000928-3. Funding for open-access charge: Universidad de Granada/CBUAObjective: To perform a comprehensive review of the use of artificial intelligence (AI) and machine learning (ML) in dentistry, providing the community with a broad insight on the different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research. Materials and methods: The comprehensive review was conducted in MEDLINE/ PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years. Results: Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling. Conclusions: The insight provided by the present work has reported outstanding results in the design of high-performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations. Clinical significance: The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures.Spanish Ministry of Sciences, Innovation and Universities RTI2018-101674-B-I00 PGC2018-101904-A-100University of Granada project A.TEP. 280.UGR18Junta de Andalucia P20-00200Fapergs/Capes do Brasil grant 19/25510000928-3Universidad de Granada/CBU

A Novel Engineering Approach to Modelling and Optimizing Smoking Cessation Interventions

abstract: Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt failure rate. The recent rise in mobile technologies has led to an increased ability to frequently measure smoking behaviors and related constructs over time, i.e., obtain intensive longitudinal data (ILD). Dynamical systems modeling and system identification methods from engineering offer a means to leverage ILD in order to better model dynamic smoking behaviors. In this dissertation, two sets of dynamical systems models are estimated using ILD from a smoking cessation clinical trial: one set describes cessation as a craving-mediated process; a second set was reverse-engineered and describes a psychological self-regulation process in which smoking activity regulates craving levels. The estimated expressions suggest that self-regulation more accurately describes cessation behavior change, and that the psychological self-regulator resembles a proportional-with-filter controller. In contrast to current clinical practice, adaptive smoking cessation interventions seek to personalize cessation treatment over time. An intervention of this nature generally reflects a control system with feedback and feedforward components, suggesting its design could benefit from a control systems engineering perspective. An adaptive intervention is designed in this dissertation in the form of a Hybrid Model Predictive Control (HMPC) decision algorithm. This algorithm assigns counseling, bupropion, and nicotine lozenges each day to promote tracking of target smoking and craving levels. Demonstrated through a diverse series of simulations, this HMPC-based intervention can aid a successful cessation attempt. Objective function weights and three-degree-of-freedom tuning parameters can be sensibly selected to achieve intervention performance goals despite strict clinical and operational constraints. Such tuning largely affects the rate at which peak bupropion and lozenge dosages are assigned; total post-quit smoking levels, craving offset, and other performance metrics are consequently affected. Overall, the interconnected nature of the smoking and craving controlled variables facilitate the controller's robust decision-making capabilities, even despite the presence of noise or plant-model mismatch. Altogether, this dissertation lays the conceptual and computational groundwork for future efforts to utilize engineering concepts to further study smoking behaviors and to optimize smoking cessation interventions.Dissertation/ThesisDoctoral Dissertation Bioengineering 201

Optimization for Sustainable Design through Building Information Modeling

More than thirty years after the definition of the concept of sustainable development, the European Union's Agenda 2030 renews its commitment to protect the Planet and to support the needs of present and future generations. All sectors of human activity have to make their contribution to this significant challenge of our time. Therefore, the construction sector can also make an essential contribution in terms of its impact. In this context, designers are called upon to modify their actions in order to take into account the environmental, social, and economic impacts during the entire life cycle of construction. Therefore, a substantial transformation in the designer's "mentality" is necessary. The digital revolution could be a suitable opportunity for a profound renewal oriented towards sustainability. The new digital technologies and the increased computing power are useful to manage the increasing complexity in current projects and to support collaboration between the many experts involved. The thesis aim is to analyse the current state and identify the signs of change and the cues to imagine possible virtuous complicity between sustainable development goals and the potential of the digital revolution, supported by the operational features of optimization methods. The further intent is to translate the synergy between the three key topics - sustainability, digitization, and optimization - through an operational strategy that can be a concrete demonstration of what is proposed and offered to designers

Managing Water Resources in Large River Basins

Management of water resources in large rivers basins typically differs in important ways from management in smaller basins. While in smaller basins the focus of water resources management may be on project implementation, irrigation and drainage management, water use efficiency and flood operations; in larger basins, because of the greater complexity and competing interests, there is often a greater need for long-term strategic river basin planning across sectors and jurisdictions, and considering social, environmental, and economic outcomes. This puts a focus on sustainable development, including consumptive water use and non-consumptive water uses, such as inland navigation and hydropower. It also requires the consideration of hard or technical issues—data, modeling, infrastructure—as well as soft issues of governance, including legal frameworks, policies, institutions, and political economy. Rapidly evolving technologies could play a significant role in managing large basins. This Special Issue of Water traverses these hard and soft aspects of managing water resources in large river basins through a series of diverse case studies from across the globe that demonstrate recent advances in both technical and governance innovations in river basin management

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017

Advanced Computational Methods for Oncological Image Analysis

[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.

ABSTRACT BOOK 50th World Conference on Lung Health of the International Union Against Tuberculosis and Lung Disease (The Union)

The International Journal of Tuberculosis and Lung Disease is an official journal of The Union. The Journal’s main aim is the continuing education of physicians and other health personnel, and the dissemination of the most up-to-date infor mation in the field of tuberculosis and lung health. It publishes original articles and commissioned reviews not only on the clinical and biological and epidemiological aspects, but also—and more importantly—on community aspects: fundamental research and the elaboration, implementation and assessment of field projects and action programmes for tuberculosis control and the promo tion of lung health. The Journal welcomes articles submitted on all aspects of lung health, including public health-related issues such as training programmes, cost-benefit analysis, legislation, epidemiology, intervention studies and health systems research

Structural insights into phosphoprotein chaperoning of nucleoprotein in measles virus

Instruct Biennial Structural Biology Conference Abstract BookletMeasles virus is an important, highly contagious, human pathogen. The nucleoprotein N binds only to viral genomic RNA and forms the helical ribonucleocapsid that serves as a template for viral replication. We address how N is regulated by another protein, the phosphoprotein, P, to prevent newly synthesized N from binding to cellular RNA. Here, we pulled down an N01-408 fragment lacking most of its C-terminal tail domain by several affinity-tagged, N-terminal, P fragments to map the N0-binding region of P to the first 48 amino acids. We showed biochemically and using P mutants the importance of the hydrophobic interactions for the binding. We fused an N0 binding peptide, P1-48, to the C-terminus of an N021-408 fragment lacking both the N-terminal peptide and the C-terminal tail of N protein to reconstitute and crystallize the N0-P complex. We solved the X-ray structure of the resulting N0-P chimeric protein at 2.7 Å resolution. The structure reveals the molecular details of the conserved N0-P interface and explains how P chaperones N0 preventing both self-assembly of N0 and its binding to RNA. We compare the structure of an N0-P complex to atomic model of helical ribonucleocapsid. We thus propose a model how P may help to start viral RNA synthesis. Our results provide a new insight into mechanisms of paramyxovirus replication. New data on the mechanisms of phosphoprotein chaperone action allows better understanding of the virus genome replication and nucleocapsid assembly. We describe a conserved structural interface for the N-P interaction which could be a target for drug development not only to treat measles but also potentially other paramyxovirus diseases.Non peer reviewe

Biomass for Energy Country Specific Show Case Studies

In many domestic and industrial processes, vast percentages of primary energy are produced by the combustion of fossil fuels. Apart from diminishing the source of fossil fuels and the increasing risk of higher costs and energy security, the impact on the environment is worsening continually. Renewables are becoming very popular, but are, at present, more expensive than fossil fuels, especially photovoltaics and hydropower. Biomass is one of the most established and common sources of fuel known to mankind, and has been in continuous use for domestic heating and cooking over the years, especially in poorer communities. The use of biomass to produce electricity is interesting and is gaining ground. There are several ways to produce electricity from biomass. Steam and gas turbine technology is well established but requires temperatures in excess of 250 °C to work effectively. The organic Rankine cycle (ORC), where low-boiling-point organic solutions can be used to tailor the appropriate solution, is particularly successful for relatively low temperature heat sources, such as waste heat from coal, gas and biomass burners. Other relatively recent technologies have become more visible, such as the Stirling engine and thermo-electric generators are particularly useful for small power production. However, the uptake of renewables in general, and biomass in particular, is still considered somewhat risky due to the lack of best practice examples to demonstrate how efficient the technology is today. Hence, the call for this Special Issue, focusing on country files, so that different nations’ experiences can be shared and best practices can be published, is warranted. This is realistic, as it seems that some nations have different attitudes to biomass, perhaps due to resource availability, or the technology needed to utilize biomass. Therefore, I suggest that we go forward with this theme, and encourage scientists and engineers who are researching in this field to present case studies related to different countries. I certainly have one case study for the UK to present