Magnetically induced elastic deformations of magnetic gels and elastomers containing particles of mixed size

Soft elastic composite materials can serve as actuators when they transform changes in external fields into mechanical deformation. Here, we address the corresponding deformational behavior of magnetic gels and elastomers, consisting of magnetizable colloidal particles in a soft polymeric matrix and exposed to external magnetic fields. Since many practical realizations of such materials involve particulate inclusions of polydisperse size distributions, we concentrate on the effect that mixed particle sizes have on the overall deformational response. To perform a systematic study, our focus is on binary size distributions. We systematically vary the fraction of larger particles relative to smaller ones and characterize the resulting magnetostrictive behavior. The consequences for systems of various different spatial particle arrangements and different degrees of compressibility of the elastic matrix are evaluated. In parts, we observe a qualitative change in the overall response for selected systems of mixed particle sizes. Specifically, overall changes in volume and relative elongations or contractions in response to an induced magnetization can be reversed into the opposite types of behavior. Our results should apply to the characteristics of other soft elastic composite materials like electrorheological gels and elastomers when exposed to external electric fields as well. Overall, we hope to stimulate the further investigation on the purposeful use of mixed particle sizes as a means to design tailored requested material behavior.Comment: 14 pages, 17 figure

Bewertung gesellschaftlicher Nebenleistungen von ökologischen und konventionellen Milchviehbetrieben Süddeutschlands innerhalb der Treibhausgasbilanzierung

Allocation of greenhouse gas emissions with economic allocation for milk and beef is well established in carbon foot printing, but many organic and extensive farms fulfill a wide range of additional ecosystem services for society such as management of renewable natural resources as well as preservation of biodiversity and cultural landscapes. Farms are compensated for these ecosystem services by the second pillar of the Common Agricultural Policy of the European Union. This study introduces a new aspect by examining an economic allocation for greenhouse gas emissions including ecosystem services besides milk and beef for 113 dairy farms located in grassland-based areas of Southern Germany. Results are carbon footprints of 1.66 kg CO2eq/kg fat and protein corrected milk (FPCM) on average in “conventional economic allocation”. Economic allocation, which includes ecosystem services based on the farm net income, results in a carbon footprint of 1.5 kg CO2eq/kg FPCM on average. Especially organic and extensive systems are favored with this approach. This approach shows that carbon footprints of dairy farms should not be examined one-dimensionally based solely on the amount of milk and meat that is produced on the farm; rather, a broader approach is necessary especially in organic farms

Augmenting Data with Generative Adversarial Networks to Improve Machine Learning-Based Fraud Detection

While current machine learning methods can detect financial fraud more effectively, they suffer from a common problem: dataset imbalance, i.e. there are substantially more non-fraud than fraud cases. In this paper, we propose the application of generative adversarial networks (GANs) to generate synthetic fraud cases on a dataset of public firms convicted by the United States Securities and Exchange Commission for accounting malpractice. This approach aims to increase the prediction accuracy of a downstream logit, support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost) classifier by training on a more well-balanced dataset. While the results indicate that a state-of-the-art machine learning model like XGBoost can outperform previous fraud detection models on the same data, generating synthetic fraud cases before applying a machine learning model does not improve performance

Einfluss von Milchleistung und Nutzungsdauer auf den Product Carbon Footprint von Milch bei ökologisch wirtschaftenden Betrieben in Süddeutschland

Quantification and mitigation of greenhouse gas emissions is an intensively discussed topic. For dairy farms many studies consider a higher milk yield per cow for greenhouse gas mitigation but this often results in a reduction in herd fertility and thus more heifers are needed which may lead to more emissions in total. This paper presents the Product Carbon Footprint of 36 organic dairy farms and analyses the influence of milk yield per cow and longevity of dairy cows. Results are: (1) a product carbon footprint of 1,61 kg CO2eq/kg fat and protein corrected milk on average, (2) increasing milk yield per cow causes decreasing product carbon footprints (coefficient of determination 48 %) and (3) decreasing longevity per cow causes decreasing product carbon footprints but to a lower degree of influence (coefficient of determination 16 %). With regard to climate protection, not considering ethical aspects, a high milk yield per cow should be achieved rather than to focus on longevity

Erhebliche Effizienzpotenziale in der Färsenaufzucht der ökologischen Milchproduktion

In many organic farms there is a huge potential to increase efficiency in rearing heifers for replacement. This is the result of a study in 36 organic dairy farms with pasture from South Germany, which were analyzed economically in the years 2009 – 2011. In particular farms with high production efficiency and low production costs per heifer show decreased production times per cow for some months, but this effect is overcompensated by higher milk yields per cow. This is one reason why they perform economically better with regard to the dairy farm. The most important factors influencing the production costs per heifer are the costs for forage and labor. Based on the results of this study, more efficient rearing of heifers with lower production costs seems necessary and worthwhil

The biogeochemical cycle of dissolved aluminium in the Atlantic Ocean

The work presented in this thesis focuses on the biogeochemical cycle of dissolved aluminium in surface waters and the water column of the Atlantic Ocean

Resistive Switching and Current Conduction Mechanisms in Hexagonal Boron Nitride Threshold Memristors with Nickel Electrodes

The two-dimensional (2D) insulating material hexagonal boron nitride (h BN) has attracted much attention as the active medium in memristive devices due to its favorable physical properties, among others, a wide bandgap that enables a large switching window. Metal filament formation is frequently suggested for h-BN devices as the resistive switching (RS) mechanism, usually supported by highly specialized methods like conductive atomic force microscopy (C-AFM) or transmission electron microscopy (TEM). Here, we investigate the switching of multilayer hexagonal boron nitride (h-BN) threshold memristors with two nickel (Ni) electrodes through their current conduction mechanisms. Both the high and the low resistance states are analyzed through temperature-dependent current-voltage measurements. We propose the formation and retraction of nickel filaments along boron defects in the h-BN film as the resistive switching mechanism. We corroborate our electrical data with TEM analyses to establish temperature-dependent current-voltage measurements as a valuable tool for the analysis of resistive switching phenomena in memristors made of 2D materials. Our memristors exhibit a wide and tunable current operation range and low stand-by currents, in line with the state of the art in h-BN-based threshold switches, a low cycle-to-cycle variability of 5%, and a large On/Off ratio of 10${^7}$.Comment: 39 page

3D-printed facet-attached optical elements for beam shaping in optical phased arrays

We demonstrate an optical phased-array equipped with a 3D-printed facet-attached element for shaping and deflection of the emitted beam. The beam shaper combines freeform refractive surfaces with total-internal-reflection mirrors and is in-situ printed to edge-emitting waveguide facets using high-resolution multi-photon lithography, thereby ensuring precise alignment with respect to on-chip waveguide structures. In a proof-of-concept experiment, we achieve a grating-lobe free steering range of $\pm$30$^{\circ}$ and a full-width-half-maximum beam divergence of approximately 2$^{\circ}$. The concept opens an attractive alternative to currently used grating structures and is applicable to a wide range of integration platforms