Age estimation by facial analysis based on applications available for smartphones.

BACKGROUND: Forensic Dentistry has an important role in the human identification cases and, among the analyses that can be performed, age estimation has an important value in establishing an anthropological profile. Modern technology invests for new mechanisms of age estimation: software apps, based on special algorithms, because there is not interference based on personal knowledge, cultural and personal experiences for facial recognition. MATERIALS AND METHODS: This research evaluated the use of two different apps: "How Old Do I Look? - Age Camera" and "How Old Am I? - Age Camera, Do You Look Like in Selfie Face Pic?", for age estimation analysis in a sample of 100 people (50 females and 50 males). Univariate and multivariate statistical methods were used to evaluate data. RESULTS: A great reliability was seen when used for the male volunteers. However, for females, no equivalence was found between the real age and the estimated age. CONCLUSION: These applications presented satisfactory results as an auxiliary method, in male images.

Leachate/domestic wastewater aerobic co-treatment: A pilot-scale study using multivariate analysis.

Multivariate analysis was used to identify the variables affecting the performance of pilot-scale activated sludge (AS) reactors treating old leachate from a landfill and from domestic wastewater. Raw leachate was pre-treated using air stripping to partially remove the total ammoniacal nitrogen (TAN). The control AS reactor (AS-0%) was loaded only with domestic wastewater, whereas the other reactor was loaded with mixtures containing leachate at volumetric ratios of 2 and 5%. The best removal efficiencies were obtained for a ratio of 2%, as follows: 70 ± 4% for total suspended solids (TSS), 70 ± 3% for soluble chemical oxygen demand (SCOD), 70 ± 4% for dissolved organic carbon (DOC), and 51 ± 9% for the leachate slowly biodegradable organic matter (SBOM). Fourier transform infrared (FTIR) spectroscopic analysis confirmed that most of the SBOM was removed by partial biodegradation rather than dilution or adsorption of organics in the sludge. Nitrification was approximately 80% in the AS-0% and AS-2% reactors. No significant accumulation of heavy metals was observed for any of the tested volumetric ratios. Principal component analysis (PCA) and partial least squares (PLS) indicated that the data dimension could be reduced and that TAN, SCOD, DOC and nitrification efficiency were the main variables that affected the performance of the AS reactors.

A structure-activity relationship study of quinone compounds with trypanocidal activity.

A set of 25 quinone compounds with anti-trypanocidal activity was studied by using the density functional theory (DFT) method in order to calculate atomic and molecular properties to be correlated with the biological activity. The chemometric methods principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA), Kth nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA) were used to obtain possible relationships between the calculated descriptors and the biological activity studied and to predict the anti-trypanocidal activity of new quinone compounds from a prediction set. Four descriptors were responsible for the separation between the active and inactive compounds: T5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors give information on the kind of interaction that occurs between the compounds and the biological receptor. The prediction study was done with a set of three new compounds by using the PCA, HCA, SDA, KNN and SIMCA methods and two of them were predicted as active against the Trypanosoma cruzi.