Face databases have assumed an important role in a variety of clinical and applied research domains. However, the number of datasets accessible to the scientific community is limited and the knowledge of their existence may be concealed from a wider range of specialists. In the present paper we introduce a sizeable dataset of 3D facial scans - FIDENTIS 3D Face Database (F3D-FD or FIDENTIS Database), which is accompanied by basic demographic and descriptive data. The database is structured according to recorded subjects, and comprises single-scan entries as well as a smaller number of multiscan entries. The multi-scan entries vary in the time passed between recording sessions and in the devices employed to collect the 3D data. The total number of 2476 individuals puts our database within the category of large-scale databases. The 3D scans are accessible through a web-based interface at www. fidentis.cz. A licensed version of the database is available to interested parties upon signing a license agreement. Because of its varied composition, and low target-specificity the database has capacity to be of great assistance for the worldwide research community.

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Objectives: The universally recognized indicator of nutritional status, BMI, has some shortcomings, especially in detecting overweight and obesity. A relatively recently introduced normal weight obesity (NWO) describes a phenomenon when individuals are found to have normal weight as indicated by BMI but have an elevated percentage of body fat. Normal weight obese individuals face a higher risk of developing metabolic syndrome, cardiometabolic dysfunction and have higher mortality. No studies have been previously performed which would map NWO in Brno, Czech Republic. Methods: In a sample of 100 women from Brno, we assessed the percentage of normal weight obese individuals using bioelectric impedance analysis (BIA)-three different analyzers were utilized: Tanita BC-545 personal digital scale, InBody 230 and BodyStat 1500MDD. Also, a caliperation method was used to estimate body fat percentage. Various body fat percentage cutoff points were used according to different authors. Results: When the 30% body fat (BF) cutoff was used, up to 14% of the women in our sample were found to be normal weight obese. When the sum of skinfolds or the 35% BF cutoff point are selected as a criterion for identifying normal weight obesity (NOW), only 1 of 100 examined women was identified as normal weight obese; at the 35% BF cutoff , BodyStat analyzer categorized no women as normal weight obese. Also, when the 30% BF or 66th percentile BF cutoff points were utilized, BodyStat identified pronouncedly fewer women from our sample to be normalweight obese than the two other analyzers. Conclusions: On a pilot sample of Czech women, we demonstrated that depending on the selected cutoff (there is no clear agreement on cutoff points in literature), up to 14% of the examined women were found to be normal weight obese.

Sledování individuálního růstu je v pediatrické praxi vyžadováno denně a často je doprovázeno potřebou podrobnějších analýz. Analýzu lidského růstu potřebují také sportovní antropologové a výzkumníci v oblasti biologie člověka. Přínosem by tedy byla pokročilá a zároveň snadno použitelná a bezplatná aplikace, která by pediatrům, auxologům a výzkumným pracovníkům v oblasti biologie člověka umožňovala provádět hloubkovou analýzu postnatálního růstu. Aplikace GROWTH byla vyvinuta na základě pochopení biologických procesů lidského růstu a matematických přístupů, které poskytují nejvhodnější model pro individuální (longitudinální) empirická data. Aplikace je navržena tak, aby ji bylo možné používat v každodenní pediatrické praxi. Poskytuje lékařům nástroje pro sledování růstu, předpovídání dosažené výšky a diagnostiku patologických růstových vzorců. Pokročilá analýza zahrnuje odhad časování hlavních růstových milníků. Současná verze je vyvrcholením několikastupňového vývoje aplikace a je založena na metodě FPCA (funkční analýza hlavních komponent) s numerickou optimalizací. Výstupní parametry jsou snadno použitelné a zobrazují se numericky i graficky.