Impact of hypomineralised second primary molar on preschoolers' oral health-related quality of life-A hierarchical approach.

BACKGROUND: Hypomineralised second primary molar (HSPM) is a developmental enamel defect associated with dental caries. AIM: To evaluate the impact of HSPM on oral health-related quality of life (OHRQoL) in preschoolers through hierarchical analysis. DESIGN: This population-based cross-sectional study assessed 834 5-year-old preschoolers, in Teresina, Piauí, Brazil, using sociodemographic questionnaires and Early Childhood Oral Health Impact Scale (ECOHIS). Dental examination was performed by two calibrated examiners (κ ≥ 0.80) for the diagnosis of HSPM (EAPD), dental caries (dmft and pufa indices), and malocclusion (Foster and Hamilton criteria). Analysis of the determinants of OHRQoL was stratified at three levels (P < .05). RESULTS: Severe HSPM was associated with OHRQoL in bivariate analysis (P < .05). In adjusted final multivariate analysis (model 1), the presence of dental caries with or without clinical consequences was associated with worse OHRQoL (P < .05). In model 2, after the removal of dental caries, preschoolers with severe HSPM had greater probability of having a negative impact on OHRQoL in the child impact section (RR = 2.14; 95% CI = 1.26-3.65), family impact section (RR = 1.99; 95% CI = 1.16-3.42), and total score (RR = 2.09; 95% CI = 1.25-3.49) of the ECOHIS. CONCLUSION: Severe HSPM had a negative impact on the OHRQoL of preschoolers and their families, but the presence of dental caries neutralised this impact.

Hierarchical models of psychopathology: empirical support, implications, and remaining issues.

There is an ongoing revolution in psychology and psychiatry that will likely change how we conceptualize, study and treat psychological problems.- Many theorists now support viewing psychopathology as consisting of continuous dimensions rather than discrete diagnostic categories. Indeed, recent papers have proposed comprehensive taxonomies of psychopathology dimensions to replace the DSM and ICD taxonomies of categories. The proposed dimensional taxonomies, which portray psychopathology as hierarchically organized correlated dimensions, are now well supported at phenotypic levels. Multiple studies show that both a general factor of psychopathology at the top of the hierarchy and specific factors at lower levels predict different functional outcomes. Our analyses of data on a large representative sample of child and adolescent twins suggested the causal hypothesis that phenotypic correlations among dimensions of psychopathology are the result of many familial influences being pleiotropic. That is, most genetic variants and shared environmental factors are hypothesized to non-specifically influence risk for multiple rather than individual dimensions of psychopathology. In contrast, person-specific experiences tend to be related to individual dimensions. This hierarchical causal hypothesis has been supported by both large-scale family and molecular genetic studies. Current research focuses on three issues. First, the field has not settled on a preferred statistical model for studying the hierarchy of causes and phenotypes. Second, in spite of encouraging progress, the neurobiological correlates of the hierarchy of dimensions of psychopathology are only partially described. Third, although there are potentially important clinical implications of the hierarchical model, insufficient research has been conducted to date to rec-ommend evidence-based clinical practices.

Hierarchical Anomaly Detection Model for In-Vehicle Networks Using Machine Learning Algorithms.

The communication and connectivity functions of vehicles increase their vulnerability to hackers. The unintended failure and malfunction of in-vehicle systems caused by external factors threaten the security and safety of passengers. As the controller area network alone cannot protect vehicles from external attacks, techniques to analyze and detect external attacks are required. Therefore, we propose a multi-labeled hierarchical classification (MLHC) intrusion detection model that analyzes and detects external attacks caused by message injection. This model quickly determines the occurrence of attacks and classifies the attack using only existing classified attack data. We evaluated the performance of the model by analyzing its learning space. We further verified the model by comparing its accuracy, F1 score and data learning and evaluation times with the two layers multi-class detection (TLMD) and single-layer multi-class classification (SLMC) models. The simulation results show that the MLHC model has the highest F1 score of 0.9995 and is 87.30% and 99.92% faster than the SLMC and TLMD models in terms of detection time, respectively. Consequently, the proposed model can classify both the type and existence or absence of attacks with high accuracy and can be used in interior communication environments of high-speed vehicles with a high throughput.

Comparison of evaluation parameters in the retinal layer between diabetic cystoid macular edema and postoperative cystoid macular edema after cataract surgery based on a hierarchical approach.

In this study, several variables related to the thickness of the retinal layer were measured via optical coherence tomography (OCT), and the clinical applicability of such measurements was evaluated to differentiate between diabetic cystoid macular edema (DCME) and postoperative cystoid macular edema (PCME). To this end, a total of 120 subjects (30 healthy individuals, 60 DCME patients, and 30 PCME patients) were selected as the experimental subjects. The six risk factors included the thicknesses for the total retina (TR), the inner retina (IR), the photoreceptor outer segments (POS), the outer retina (OR), the ganglion cell (GC), and the retinal nerve fiber layer (RNFL), and these were estimated by using a hierarchical approach through observations from OCT image scans. All of the risk factors were obtained from the OCT images captured within a 6-mm diameter from the center of the macula. The results of the experiment indicated that the proposed method can reliably differentiate between DCME and PCME. Moreover, as DCME and PCME progressed, the most significant deterioration was found in the central macular region. These results suggest that the proposed method has clinical applicability for the diagnosis of DCME and PCME from OCT images.

Plant succession as an integrator of contrasting ecological time scales.

Ecologists have studied plant succession for over a hundred years, yet our understanding of the nature of this process is incomplete, particularly in relation to its response to new human perturbations and the need to manipulate it during ecological restoration. We demonstrate how plant succession can be understood better when it is placed in the broadest possible temporal context. We further show how plant succession can be central to the development of a framework that integrates a spectrum of ecological processes, which occur over time scales ranging from seconds to millions of years. This novel framework helps us understand the impacts of human perturbations on successional trajectories, ecosystem recovery, and global environmental change.