The Yellowstone Permutation

Define a sequence of positive integers by the rule that a(n) = n for 1 <= n = 4, a(n) is the smallest number not already in the sequence which has a common factor with a(n-2) and is relatively prime to a(n-1). We show that this is a permutation of the positive integers. The remarkable graph of this sequence consists of runs of alternating even and odd numbers, interrupted by small downward spikes followed by large upward spikes, suggesting the eruption of geysers in Yellowstone National Park. On a larger scale the points appear to lie on infinitely many distinct curves. There are several unanswered questions concerning the locations of these spikes and the equations for these curves.Comment: 10 pages, 6 figures. Mar 7 2015: mostly stylistic change

Biogenic volatile organic compound emissions from bioenergy plants and potential impacts on air chemistry

Bioenergy plant production is expected to rapidly expand in Europe in the near future. This might not only affect resource availability but will also influence the environment. Since many bioenergy plants do emit different amounts and different compositions of biogenic volatile organic compounds (BVOCs) compared to conventional agricultural crops, the new blend of highly reactive compounds might change the chemical composition of the atmosphere. BVOCs have a strong potential to enhance the photochemical O3 production, increase the formation of secondary organic aerosols (SOA), and prolong CH4 lifetime due to fast reactions with OH. These environmental impacts of bioenergy plants on air quality and the regional climate, however, are difficult to evaluate since accurate field observations of relevant crops are not available. Therefore, I studied a large range of BVOC fluxes from the most prominent bioenergy plants in Germany, which are maize, ryegrass, and oilseed rape, by applying field measurements and biogeochemical modeling. The plants were cultivated in Dedelow, Brandenburg, Germany and observed throughout the vegetative and reproductive development stages. Combining automatically moving large chambers and a proton transfer reaction–mass spectrometer (PTR-MS), I quantified the emission of numerous highly reactive terpenoids, together with several other BVOCs, including alcohols, aldehydes, ketones, benzenoids, and fatty acid derivatives. The characteristic seasonal BVOC flux pattern of each species, could be divided into groups and was associated to the different plant growth stages. The observations from the field campaigns were used to parameterize a biogeochemical ecosystem model coupled to a process-based BVOC emission model. The parameters for the BVOC model were fitted for each compound individually and comprise the standardized emission factor, an emission function curvature coefficient, and the fractionation into a light dependent (de novo emission) and light independent (pool emission) function. Therefore, I merged a mechanistic process-based de novo model with a pool emission approach into a joint BVOC emission model which was embedded in the biogeochemical framework LandscapeDNDC. Finally, total annual emissions were calculated in dependence on simulated plant growth and photosynthesis. Simulated BVOC emissions show that considerable differences between the investigated bioenergy plants exist with oilseed rape having 37-fold higher total annual emissions than maize (oilseed rape: 91.3 ± 8.0 mmol m-2 a-1; maize: 2.5 ± 0.1; and ryegrass: 15.7 ± 0.6). The differences in potential annual impacts on air chemistry are less pronounced between the plants, due to the large fraction of highly reactive terpenoids in the maize BVOC emissions. In particular, the difference is reduced to the 6-fold when the potential impact on OH-reactivity (a measure for O3 and SOA forming potential as well as indirect radiative forcing) is considered and to the 4.5-fold when the theoretically produced electricity yield is additionally taken as a reference. Thus, the results indicate that BVOC fluxes from large-scale bioenergy fields should be better differentiated, especially with regard to BVOC composition and reactivity. Additionally, the large impact of plant phenology on emission factors demands for elaborated models that should be based on measurements that cover the whole plant growth period.Es wird erwartet, dass der Anbau von Bioenergiepflanzen in Europa in naher Zukunft stark zunehmen wird. Dies hat nicht nur Einfluss auf die Ressourcenversorgung, sondern auch auf die Umwelt. Da viele Energiepflanzen andere Emissionsmengen und Gruppierungen von hochreaktiven biogenen flüchtigen organischen Verbindungen (BVOCs) aufweisen als die meisten sonstigen Agrarpflanzen, könnte die chemische Zusammensetzung der Atmosphäre beeinflusst werden. BVOCs in der Atmosphäre können zu einer Zunahme der Konzentrationen von Ozon und sekundären organischen Aerosolen (SOA) führen, sowie die Lebensdauer des klimaschädlichen Gases Methan (CH4) durch Reaktionen mit dem Hydroxyl-Radikal (OH) verlängern. Diese negativen Einflüsse durch den vermehrten Anbau von Bioenergiepflanzen auf die Luftqualität und das regionale Klima sind jedoch schwer zu quantifizieren, da ausreichende Feldmessungen an diesen Pflanzen fehlen. Deshalb habe ich biogenic volatile organic compound (BVOC)-Flüsse aus den in Deutschland meistgenutzten Bioenergiepflanzen Mais, Weidelgras und Raps mittels Feldmessungen und biogeochemischer Modellierung genauer untersucht. Die Pflanzen wurden in Dedelow, Brandenburg, Deutschland angebaut und während der gesamten vegetativen und reproduktiven Entwicklungsstadien untersucht. Mit einer Kombination aus sich automatisch öffnenden und schließenden Großkammern und einem Protonentransferreaktionsmassenspektrometer (PTR-MS) konnte ich hohe Emissionsanteile von hochgradig reaktiven Terpenoiden sowie anderen BVOCs, darunter Alkohole, Aldehyde, Ketone, Benzonoide und Fettsäurederivate quantifizieren. Die Saisonalität der BVOC-Flüsse konnte in charakteristische Gruppen eingeteilt und den verschiedenen Entwicklungsstadien der Pflanze zugeordnet werden. Die Beobachtungen aus den Feldmessungen wurden unter anderem dafür verwendet, ein physiologisch-orientiertes BVOC Modell, das an ein biogeochemisches Ökosystem gekoppelt wurde, weiter zu entwickeln und zu parametrisieren. Die Parameter wurden für jeden einzelnen Stoff angepasst und beinhalten den Standardemissionsfaktor, den Krümmungskoeffizienten der Emissionsfunktion und den Anteil der lichtabhängigen und lichtunabhängigen Emissionsfunktion. Dazu wurde in dieser Arbeit ein Modell zusammengeführt, welches Emissionen von neu gebildeten Stoffen (lichtabhängige) und Emissionen aus dem Stoffspeicher (lichtunabhängig) simulieren kann. Das Modell wurde anschließend dazu verwendet, Jahresbilanzen der Emissionen zu erstellen, die nicht nur von der direkten meteorologischen Situation angetrieben werden, sondern auch vom Pflanzenwachstum und der Photosynthese abhängen. Simulierte jährliche BVOC-Gesamtemissionen weichen zwischen den Bioenergiepflanzen um den Faktor 37 zwischen der Art mit den niedrigsten und der mit den höchsten Emissionen ab (2.5 ± 0.1, 15.7 ± 0.6, and 91.3 ± 8.0 mmol m-2 a-1 aus Mais, Weidelgras und Raps). Aufgrund des hohen Anteils von hochreaktiven Terpenoiden an den emittierten BVOCs aus Mais, sind die Unterschiede von möglichen Auswirkungen auf die Luftchemie zwischen den Pflanzen weniger stark ausgeprägt. Bei Berücksichtigung der potentiellen OH-Reaktivität (ein Maß, das den Einfluss auf O3 und SOA Bildung, sowie den indirekten Klimaeinfluss wiedergibt) verringert sich dadurch der Unterschied zwischen den Arten in Bezug auf die Luftchemie auf den Faktor 6. Wenn zusätzlich auf die theoretische produzierbare Menge Strom skaliert wird, ergibt sich sogar nur ein Unterschied von dem Faktor 4.5. Die Ergebnisse zeigen, dass BVOC-Flüsse aus großflächigem Bioenergieanbau in Zukunft besser differenziert werden sollten. Dazu müssen eine Vielzahl unterschiedlicher Stoffe berücksichtigt werden. Da für den Einfluss auf die Luftchemie häufig eine zeitlich hoch aufgelöste Einschätzung der BVOC-Emission notwendig ist, muss zudem berücksichtigt werden, dass sich die Emissionsfaktoren mit dem Entwicklungsstadium ändern. Daher sollten auch Messungen verstärkt über längere Messzeiträume durchgeführt werden, die über mehrere Entwicklungsstufen hinweg gehen

Study on fibre optic sensors embedded into metallic structures by selective laser melting

Additive Manufacturing, which builds components layer by layer, opens up exciting possibilities to integrate sophisticated internal features and functionalities such as fibre optic sensors directly into the heart of a metal component. This can create truly smart structures for deployment in harsh environments. The innovative and multidisciplinary study conducted in this thesis demonstrates the feasibility to integrate fibre optics sensors with thin, protective nickel coatings (outer diameter ~350 μm) into stainless steel (SS 316) coupons by Selective Laser Melting technology (SLM). Different concepts for fibre embedment by SLM are investigated. The concepts differ in which way the fibre is positioned and how the powder is deposited and solidified by the laser in respect to the optical fibre. Only one approach is found suitable to reliably and repeatable encapsulate fibres whilst preserving their structural integrity and optical properties. In that approach SS 316 components are manufactured using SLM, incorporating U-shaped grooves with dimensions suitable to hold nickel coated optical fibres. Coated optical fibres containing Fibre Bragg Gratings (FBG) for strain and temperature sensing are placed in the groove. Melting subsequent powder layers on top of the FBGs fuses the fibre’s metallic jacket to the steel and completes the integration of the fibre sensor into the steel structure. Cross-sectional microscopy analysis of the fabricated components, together with analysis of fibre optic sensors’ behaviour during fabrication, indicates proper stress and strain transfer between coated fibre and added SS 316 material. During the SLM process embedded Fibre Bragg grating (FBG) sensors provide in-situ temperature measurements and potentially allow measuring the build-up of residual stresses. Subsequently, FBG sensors embedded into SS 316 structures using our approach follow elastic and plastic deformations of the SS 316 component, with a resolution of better than 3 pm*μɛ-1. Temperature measurements are also conducted with a precision of 3 pm*K-1. Such embedded fibre sensors can also be used to high temperatures of up to ~400 °C. However, at elevated temperatures issues arise from the significantly larger thermal expansion coefficient of SS 316, leading to delamination of the more rapidly expanding metal from the glass. Rapid thermal expansion of the metal also leads to high axial stresses within the glass exceeding the fibres tensile strength and ultimately leading to structural damage of the optical fibre

Zur Eignung der Schwartz-Formel in der pädiatrischen Onkologie

Die Schwartz-Formel (Glomeruläre Filtrationsrate GFR= Konstante k x Körpergröße L / Plasmakreatininkonzentration Pcr) als vereinfachte Methode zur Abschätzung der Nierenfunktion bei Kindern. Ob die Anwendung der Formel auch bei einem onkologischen Patientengut, mit einem möglicherweise gesteigerten Muskelzellzerfall unter Polychemotherapie, zuverlässig ist, wurde hier erarbeitet. Ein Anstieg der Plasmakreatininkonzentration oder ein deutlicher Abfall der Muskelmasse wurde nicht beobachtet. Jedoch überschätztz die Schwartz-Formel die berechnete 24-Stunden-Kreatininclearance signifikant und erkennt im Falle einer reduzierten Nierenfunktion dieses nicht. Auch mit einer modifizierten Konstante k gelingt keine sichere Abschätzung der Nierenfuntkion. Eine Beibehaltung der Nierenfunktionsmessung mittels 24-Stunden-Sammelurin-Kreatininclearance wird demnach für Kinder in der Onkologie weiterhin empfohlen

Saccadic Adaptation to Moving Targets

Saccades are so called ballistic movements which are executed without online visual feedback. After each saccade the saccadic motor plan is modified in response to post-saccadic feedback with the mechanism of saccadic adaptation. The post-saccadic feedback is provided by the retinal position of the target after the saccade. If the target moves after the saccade, gaze may follow the moving target. In that case, the eyes are controlled by the pursuit system, a system that controls smooth eye movements. Although these two systems have in the past been considered as mostly independent, recent lines of research point towards many interactions between them. We were interested in the question if saccade amplitude adaptation is induced when the target moves smoothly after the saccade. Prior studies of saccadic adaptation have considered intra-saccadic target steps as learning signals. In the present study, the intra-saccadic target step of the McLaughlin paradigm of saccadic adaptation was replaced by target movement, and a post-saccadic pursuit of the target. We found that saccadic adaptation occurred in this situation, a further indication of an interaction of the saccadic system and the pursuit system with the aim of optimized eye movements

Land Use Effects on Climate: Current State, Recent Progress, and Emerging Topics

As demand for food and fiber, but also for negative emissions, brings most of the Earth’s land surface under management, we aim to consolidate the scientific progress of recent years on the climatic effects of global land use change, including land management, and related land cover changes (LULCC)

Synchronisation of spatiotemporal complex states by incoherent coupling

Synchronisation of spatiotemporal continuous disorder is realised in a Liquid Crystal Light Valve single feedback system with an incoherent, unidirectional master-slave-coupling scheme as excellent model system for synchronisation. Thus, complex states disordered in space and time were completely synchronised by using identical systems as master and slave. Thereby the impeding role of system differences is demonstrated in comparison to former experiments. A novel imaging method is introduced, in which the synchronisation process and effects like a time lag can be more easily characterised

Modeling Intra‐ and Interannual Variability of BVOC Emissions From Maize, Oil‐Seed Rape, and Ryegrass

Air chemistry is affected by the emission of biogenic volatile organic compounds (BVOCs), which originate from almost all plants in varying qualities and quantities. They also vary widely among different crops, an aspect that has been largely neglected in emission inventories. In particular, bioenergy-related species can emit mixtures of highly reactive compounds that have received little attention so far. For such species, long-term field observations of BVOC exchange from relevant crops covering different phenological phases are scarcely available. Therefore, we measured and modeled the emission of three prominent European bioenergy crops (maize, ryegrass, and oil-seed rape) for full rotations in north-eastern Germany. Using a proton transfer reaction–mass spectrometer combined with automatically moving large canopy chambers, we were able to quantify the characteristic seasonal BVOC flux dynamics of each crop species. The measured BVOC fluxes were used to parameterize and evaluate the BVOC emission module (JJv) of the physiology-oriented LandscapeDNDC model, which was enhanced to cover de novo emissions as well as those from plant storage pools. Parameters are defined for each compound individually. The model is used for simulating total compound-specific reactivity over several years and also to evaluate the importance of these emissions for air chemistry. We can demonstrate substantial differences between the investigated crops with oil-seed rape having 37-fold higher total annual emissions than maize. However, due to a higher chemical reactivity of the emitted blend in maize, potential impacts on atmospheric OH-chemistry are only 6-fold higher

Effects of crop residue incorporation and properties on combined soil gaseous N2_{2}O, NO, and NH3_{3} emissions—A laboratory-based measurement approach

Crop residues may serve as a significant source of soil emissions of N$_{2}$O and other trace gases. According to the emission factors (EFs) set by the Intergovernmental Panel on Climate Change (IPCC), N$_{2}$O emission is proportional to the amount of N added by residues to the soil. However, the effects of crop residues on the source and sink strength of agroecosystems for trace gases are regulated by their properties, such as the C and N content; C/N ratio; lignin, cellulose, and soluble fractions; and residue humidity. In the present study, an automated dynamic chamber method was used in combination with soil mesocosms to simultaneously measure the effects of nine different crop residues (oilseed rape, winter wheat, field pea, maize, potato, mustard, red clover, sugar beet, and ryegrass) on soil respiration (CO$_{2}$) and reactive N fluxes (N$_{2}$O, NO, and NH$_{3}$) at a high temporal resolution. Specifically, crop residues were incorporated in the 0–4 cm topsoil layer and incubated for 60 days at a constant temperature (15 °C) and water-filled pore space (60% WFPS). Residue incorporation immediately and sharply increased soil N$_{2}$O and CO$_{2}$ emissions, but these were short-lived and returned to background levels within respectively 10 and 30 days. The magnitude of increase in soil NO flux following residue incorporation was lower than that in CO$_{2}$ and N$_{2}$O fluxes, with peak emissions observed around day 20. Overall, the N content or C/N ratio of the applied residue could not sufficiently explain the variation in soil N2O and NO emissions. The range of the calculated N$_{2}$O EFs over a 60-day period was −0.17 to +4.5, being wider than that proposed by the IPCC (+0.01 to +1.1). Therefore, the residue maturity stage may be used as a simple proxy to estimate the N$_{2}$O + NO emissions from incorporated residue