The Annual of scientific discovery: or, Year-book of facts in science and art.

1856

The Annual of scientific discovery: or, Year-book of facts in science and art.

1854

The Annual of scientific discovery: or, Year-book of facts in science and art.

1858

The Annual of scientific discovery: or, Year-book of facts in science and art.

1857

The Annual of scientific discovery: or, Year-book of facts in science and art.

1864

The Annual of scientific discovery: or, Year-book of facts in science and art.

1851

The Annual of scientific discovery: or, Year-book of facts in science and art.

1860

The Annual of scientific discovery: or, Year-book of facts in science and art.

1861

The Annual of scientific discovery: or, Year-book of facts in science and art.

1850

On propositionalization for knowledge discovery in relational databases

Propositionalization, Inductive Logic Programming, Multi-Relational Data Mining

Mass transfer effects on reactive separation processes - discovery of reactive arrheotropes

Membrane reactor, reactive membrane separation, arrheotrope, azeotrope, dusty gas model, esterification, residue curve map, distillation, kinetics, singular point, bifurcation

Effects of neural nitric oxide synthase gene inactivation on the neurodocrine stress response in mice

Neural nitric oxide synthase, neuroendocrine stress response, forced swimming, nNOS KO mice, hypothalamus, adrenal gland

APOE and LDLR Gene Polymorphisms and Dyslipidemia Tracking. Rio de Janeiro Study

Background:Studies show an association between changes in apolipoprotein E (ApoE) and LDLR receptor with the occurrence of dyslipidemia.Objectives:To investigate the association between polymorphisms of the APOE (ε2, ε3, ε4) and LDLR (A370T) genes with the persistence of abnormal serum lipid levels in young individuals followed up for 17 years in the Rio de Janeiro Study.Methods:The study included 56 individuals (35 males) who underwent three assessments at different ages: A1 (mean age 13.30 ± 1.53 years), A2 (22.09 ± 1.91 years) and A3 (31.23 ± 1.99 years). Clinical evaluation with measurement of blood pressure (BP) and body mass index (BMI) was conducted at all three assessments. Measurement of waist circumference (WC) and serum lipids, and analysis of genetic polymorphisms by PCR-RFLP were performed at A2 and A3. Based on dyslipidemia tracking, three groups were established: 0 (no abnormal lipid value at A2 and A3), 1 (up to one abnormal lipid value at A2 or A3) and 2 (one or more abnormal lipid values at A2 and A3).Results:Compared with groups 0 and 1, group 2 presented higher mean values of BP, BMI, WC, LDL-c and TG (p < 0.01) and lower mean values of HDL-c (p = 0.001). Across the assessments, all individuals with APOE genotypes ε2/ε4 and ε4/ε4 maintained at least one abnormal lipid variable, whereas those with genotype ε2/ε3 did not show abnormal values (χ2 = 16.848, p = 0.032). For the LDLR genotypes, there was no significant difference among the groups.Conclusions:APOE gene polymorphisms were associated with dyslipidemia in young individuals followed up longitudinally from childhood.

Discovery and visualization of interesting patterns

Die Preise für Speicherplatz fallen stetig, da verwundert es nicht, dass Unternehmen riesige Datenmengen anhäufen und sammeln. Diese immensen Datenmengen müssen jedoch mit geeigneten Methoden analysiert werden, um für das Unternehmen überlebensnotwendige Muster zu identifizieren. Solche Muster können Probleme aber auch Chancen darstellen. In jedem Fall ist es von größter Bedeutung, rechtzeitig diese Muster zu entdecken, um zeitnah reagieren zu können. Um breite Nutzerschichten anzusprechen, müssen Analysemethoden ferner einfach zu bedienen sein, sofort Rückmeldungen liefern und intuitive Visualisierungen anbieten. Ich schlage in der vorliegenden Arbeit Methoden zur Visualisierung und Filterung von Assoziationsregeln basierend auf ihren zeitlichen Änderungen vor. Ich werde lingustische Terme (die durch Fuzzymengen modelliert werden) verwenden, um die Historien von Regelbewertungsmaßen zu charakterisieren und so eine Ordnung von relevanten Regeln zu generieren. Weiterhin werde ich die vorgeschlagenen Methoden auf weitereModellarten übertragen, die Software-Plattformvorstellen, die die Analysemethoden dem Nutzer zugänglich macht und schließlich empirische Auswertungen auf Echtdaten aus Unternehmenskooperationen vorstellen, die die Wirksamkeit meiner Vorschläge belegen.