Computational Intelligence-based PM2.5 Air Pollution Forecasting

Computational intelligence based forecasting approaches proved to be more efficient in real time air pollution forecasting systems than the deterministic ones that are currently applied. Our research main goal is to identify the computational intelligence model that is more proper to real time PM2.5 air pollutant forecasting in urban areas. Starting from the study presented in [27]a, in this paper we first perform a comparative study between the most accurate computational intelligence models that were used for particulate matter (fraction PM2.5) air pollution forecasting: artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS). Based on the obtained experimental results, we make a comprehensive analysis of best ANN architecture identification. The experiments were realized on datasets from the AirBase databases with PM2.5 concentration hourly measurements. The statistical parameters that were computed are mean absolute error, root mean square error, index of agreement and correlation coefficient

Etiology Study of Acquired Developmental Defects of Enamel and Their Association with Dental Caries in Children between 3 and 19 Years Old from Dolj County, Romania

Background: Developmental defects of enamel (DDE) are frequently encountered in primary and permanent teeth, yet their etiology is not completely known. Enamel hypoplasia is considered a predisposing factor for early caries. The objective of this study was the evaluation of several risk factors potentially causing DDE and the possible association between DDE and dental caries. Methods: This study was performed on a group of 213 rural children from Romania. It combined a thorough dental examination for all children, and a questionnaire filled in by their mothers, regarding the evolution of their pregnancy and the child’s health status in the first years of life. Results: There was no statistically significant association between DDE presence and data regarding the evolution of pregnancy, mothers’ health status or children’s conditions during early childhood. There was a significant association between the use of amoxicillin, ibuprofen, and cephalosporin during the period of formation of permanent teeth, and one environmental factor (water source), and the presence of DDE (Chi Square, p p = 0.001). Conclusions: Children who consumed water from private wells and children who received medication during early childhood developed more enamel defects, presenting a higher risk of caries development

DETERMINATION OF RESISTANCE FORCES FROM MANDIBULAR MOVEMENTS THROUGH DYNAMIC SIMULATION USING KINEMATIC ANALYSIS AND FINITE ELEMENTS METHOD

Aim of the study This study aimed to evaluate the resistance forces that develop in the dental structures of the two left upper premolars during mandibular movements, through dynamic simulation using the kinematic analysis and the finite elements method. Material and methods For this, using several softwares, we obtained a virtual model of the jaw that was attached to a virtual skull. For all the components of the skull and of the dento-maxilar apparatus mechanical properties were given. The movements as mandibule lifting, propulsion, retropulsion and laterality were simulated. Results The study highlighted the presence of resistance forces in the dental structures with values ​​between 31.781 N in the retropulsion movement and 174.104 N in the lateral movement. Conclusions These values ​​are close to the occlusive forces values in the conditions of a balanced occlusion

THREE-DIMENSIONAL MODELING OF THE DENTAL-MAXILLARY SYSTEM

In this paper, a virtual model of the dental-maxillary device was obtained by scanning a skull taken from a corpse, and using a few sets of tomographic images. These images were processed with a program that allows the transformation of tomographic images into three-dimensional geometries based on gray shades. In an initial phase these geometries were in the form of discontinuous surfaces, which were then processed, finalized and transformed into virtual solids. Thus, in the SolidWorks program the dental-maxillary device was obtained as virtual solids. Such a Multi Body model has undergone kinematic simulations in the Motion model of SolidWorks, where the entire load system to which the analyzed model is subjected. At the end of the paper, important conclusions were highlighted

EFFECTS OF OCCLUSAL LOADS IN THE GENESIS OF NON-CARIOUS CERVICAL LESIONS – A FINITE ELEMENT STUDY

Aim of the study This study investigated the magnitude and distribution of stress in a maxillary first premolar subjected to normal and heavy occlusal loads, that were directed vertically and horizontally, using Finite Element Analysis. Material and methods A virtual 3D model of a maxillary first premolar was created using the CT images of a 14 year-old patient and the physical and mechanical properties of the dental tissues used in other studies. We obtained 8 scenarios for the vertical loading and 8 scenarios for the horizontal loading. Results The magnitude and distribution of stress were the least favorable in the case of the heavy horizontal loading applied on the intact tooth. Conclusions Our study showed that the intact tooth was the most affected by stress regardless of the loading applied

THE NUMBER OF LOST TEETH – A POTENTIAL PREDICTIVE MARKER FOR THE CARDIOVASCULAR DISEASES IN A SAMPLE OF HOSPITALIZED ADULTS

Aim of the study: to evaluate the degree of statistical association between the oral parameter represented by the total number of permanent lost teeth (NLT) on both arches, and a certain type of cardiovascular disease. Materials and methods: 84 hospitalized participants in the Cardiology Department from DrobetaTurnu-Severin County Emergency Clinical Hospital were evaluated in the Emergency Dentistry Department of the same hospital. The demographic and clinical data were collected and statistically analyzed using Chi-square and Kendall’s tau-b, followed by two binomial regression models. Results: A strong, positive association between the NLT and the presence of heart valve diseases, respectively cardiomyopathy was highlighted by Chi-square tests (χ2(2) = 8.774, p = 0.023, respectively χ2(2) = 19.137, p < 0.0005) Also, NLT between 9 and 14 may be considered a statistically significant predictor of developing cardiomyopathy (unadjusted OR = 6.548, 95%CI = 1.764 – 24.304, p < 0.0005), and NLT between 15-27 for developing heart valve diseases (unadjusted OR = 7.886, 95% CI = 1.698 – 36.616, p = 0.008). Conclusions: For the group of participants included in the study, NLT had a statistically significant predictive value especially for heart valve diseases and cardiomyopathy