Open Access

Diese Seminararbeit handelt von der Programmierung und Aktivierung von magnetresponsiven Materialien mithilfe des Finite-Elemente Programms COMSOL Multiphysics® mit dem Modul magnetic fields no currents. Es werden die grundlegenden Gleichungen der magnetischen Feldtheorie aufgebaut, ohne Bezug auf einen Strom I als Ursache für das Magnetfeld zu nehmen. Des Weiteren werden einfache Simulationsmodelle vorgestellt, bei denen die Magnetisierungsmodelle relative Permeabilität, Magnetisierung und Jiles-Atherton verwendet werden. Dabei wird auf ein durch eine Spule induziertes Magnetfeld in dieser Arbeit verzichtet, stattdessen ist die Vorgabe des magnetischen Skalarpotentials Φ gewählt worden, um ein homogenes magnetisches Feld, wie es in einer unendlich langen Spule mit unendlich vielen Windungen vorliegen würde, nachzubilden. Für die entstandenen Simulationsmodelle werden analytische Vergleichsrechnungen durchgeführt, sofern es die Komplexität der Modelle zulässt. Dabei soll eingeordnet werden, ob eine Umsetzung des Verhaltens von 4D-Printing Objekten im Modul magnetic fields no currents, im Hinblick auf die „Programmierung“ also das Magnetisieren, sowie die „Aktivierung“ mit Vorgabe des magnetischen Skalarpotentials in der zweidimensionalen Simulation gelingen kann.

The growing number of embedded devices with interconnection to the Internet causes severe security risks. VPN-oriented countermeasures suffer from the fact that embedded devices come with only very limited resources. This contribution discusses the requirements for an embedded VPN based on IPsec. IPsec is an extension of the IP protocol to encrypt and to authenticate IP packets for secure transmission.

A novel, unsupervised, artificial intelligence system is presented, whose input signals and trainable weights consist of complex or hypercomplex values. The system uses the effect given by the complex multiplication that the multiplicand is not only scaled but also rotated. The more similar an input signal and the reference signal are, the more likely the input signal belongs to the corresponding class. The data assigned to a class during training is stored on a generic layer as well as on a layer extracting special features of the signal. As a result, the same cluster can hold a general description and the details of the signal. This property is vital for assigning a signal to an existing or a new class. To ensure that only valid new classes are opened, the system determines the variances by comparing each input signal component with the weights and adaptively adjusts its activation and threshold functions for an optimal classification decision. The presented system knows at any time all boundaries of its clusters. Experimentally, it is demonstrated that the system is able to cluster the data of multiple classes autonomously, fast, and with high accuracy.

In previous articles we presented HPTLC (High- Performance Thin-Layer Chromatography) applications for a series of medicinal plants, such as Ginkgo (Analytix 5/2016), Hypericum (Analytix 1/2017) or Ginseng (Analytix Reporter Issue 2/2018). With this article, we continue this series with an application note for passion flower, to further demonstrate the effectiveness of HPTLC for fingerprints of botanicals. Our comprehensive offering of analytical reagents and standards includes all consumables (TLC/HPTLC plates, solvents, analytical standards and extract reference materials) used for this application.

Irrigation with wastewater releases pharmaceuticals, pathogenic bacteria, and resistance genes, but little is known about the accumulation of these contaminants in the environment when wastewater is applied for decades. We sampled a chronosequence of soils that were variously irrigated with wastewater from zero up to 100 years in the Mezquital Valley, Mexico, and investigated the accumulation of ciprofloxacin, enrofloxacin, sulfamethoxazole, trimethoprim, clarithromycin, carbamazepine, bezafibrate, naproxen, diclofenac, as well as the occurrence of Enterococcus spp., and sul and qnr resistance genes. Total concentrations of ciprofloxacin, sulfamethoxazole, and carbamazepine increased with irrigation duration reaching 95% of their upper limit of 1.4 µg/kg (ciprofloxacin), 4.3 µg/kg (sulfamethoxazole), and 5.4 µg/kg (carbamazepine) in soils irrigated for 19–28 years. Accumulation was soil-type-specific, with largest accumulation rates in Leptosols and no time-trend in Vertisols. Acidic pharmaceuticals (diclofenac, naproxen, bezafibrate) were not retained and thus did not accumulate in soils. We did not detect qnrA genes, but qnrS and qnrB genes were found in two of the irrigated soils. Relative concentrations of sul1 genes in irrigated soils were two orders of magnitude larger (3.15×10−3±0.22×10−3 copies/16S rDNA) than in non-irrigated soils (4.35×10−5±1.00×10−5 copies/16S rDNA), while those of sul2 exceeded the ones in non-irrigated soils still by a factor of 22 (6.61×10–4±0.59×10−4 versus 2.99×10−5±0.26×10−5 copies/16S rDNA). Absolute numbers of sul genes continued to increase with prolonging irrigation together with Enterococcus spp. 23S rDNA and total 16S rDNA contents. Increasing total concentrations of antibiotics in soil are not accompanied by increasing relative abundances of resistance genes. Nevertheless, wastewater irrigation enlarges the absolute concentration of resistance genes in soils due to a long-term increase in total microbial biomass.