Evaluating the Performance of a Max-Stable Process for Estimating Intensity-Duration-Frequency Curves

To explicitly account for asymptotic dependence between rainfall intensity maxima of different accumulation duration, a recent development for estimating Intensity-Duration-Frequency (IDF) curves involves the use of a max-stable process. In our study, we aimed to estimate the impact on the performance of the return levels resulting from an IDF model that accounts for such asymptotical dependence. To investigate this impact, we compared the performance of the return level estimates of two IDF models using the quantile skill index (QSI). One IDF model is based on a max-stable process assuming asymptotic dependence; the other is a simplified (or reduced) duration-dependent GEV model assuming asymptotic independence. The resulting QSI shows that the overall performance of the two models is very similar, with the max-stable model slightly outperforming the other model for short durations (d≤10h). From a simulation study, we conclude that max-stable processes are worth considering for IDF curve estimation when focusing on short durations if the model’s asymptotic dependence can be assumed to be properly captured

Estimating IDF Curves Consistently over Durations with Spatial Covariates

Given that long time series for temporally highly resolved precipitation observations are rarely available, it is necessary to pool information to obtain reliable estimates of the distribution of extreme precipitation, especially for short durations. In this study, we use a duration-dependent generalized extreme value distribution (d-GEV) with orthogonal polynomials of longitude and latitude as spatial covariates, allowing us to pool information between durations and stations. We determine the polynomial orders with step-wise forward regression and cross-validated likelihood as a model selection criterion. The Wupper River catchment in the West of Germany serves as a case study area. It allows us to estimate return level maps for arbitrary durations, as well as intensity-duration-frequency curves at any location—also ungauged—in the research area. The main focus of the study is evaluating the model performance in detail using the Quantile Skill Index, a measure derived from the popular Quantile Skill Score. We find that the d-GEV with spatial covariates is an improvement for the modeling of rare events. However, the model shows limitations concerning the modeling of short durations d≤30min. For ungauged sites, the model performs on average as good as a generalized extreme value distribution with parameters estimated individually at the gauged stations with observation time series of 30–35 years available

Impact of lattice dynamics on the phase stability of metamagnetic FeRh: Bulk and thin films

We present phonon dispersions, element-resolved vibrational density of states (VDOS) and corresponding thermodynamic properties obtained by a combination of density functional theory (DFT) and nuclear resonant inelastic X-ray scattering (NRIXS) across the metamagnetic transition of B2 FeRh in the bulk material and thin epitaxial films. We see distinct differences in the VDOS of the antiferromagnetic (AF) and ferromagnetic (FM) phase which provide a microscopic proof of strong spin-phonon coupling in FeRh. The FM VDOS exhibits a particular sensitivity to the slight tetragonal distortions present in epitaxial films, which is not encountered in the AF phase. This results in a notable change in lattice entropy, which is important for the comparison between thin film and bulk results. Our calculations confirm the recently reported lattice instability in the AF phase. The imaginary frequencies at the $X$-point depend critically on the Fe magnetic moment and atomic volume. Analyzing these non vibrational modes leads to the discovery of a stable monoclinic ground state structure which is robustly predicted from DFT but not verified in our thin film experiments. Specific heat, entropy and free energy calculated within the quasiharmonic approximation suggest that the new phase is possibly suppressed because of its relatively smaller lattice entropy. In the bulk phase, lattice degrees of freedom contribute with the same sign and in similar magnitude to the isostructural AF-FM phase transition as the electronic and magnetic subsystems and therefore needs to be included in thermodynamic modeling.Comment: 15 pages, 12 figure

Effects of Chronic Ethanol Treatment on Neocortex

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66043/1/j.1530-0277.1986.tb05133.x.pd

Amyloid as a Depot for the Formulation of Long-Acting Drugs

Amyloids are highly organized protein aggregates that are associated with both neurodegenerative diseases such as Alzheimer disease and benign functions like skin pigmentation. Amyloids self-polymerize in a nucleation-dependent manner by recruiting their soluble protein/peptide counterpart and are stable against harsh physical, chemical, and biochemical conditions. These extraordinary properties make amyloids attractive for applications in nanotechnology. Here, we suggest the use of amyloids in the formulation of long-acting drugs. It is our rationale that amyloids have the properties required of a long-acting drug because they are stable depots that guarantee a controlled release of the active peptide drug from the amyloid termini. This concept is tested with a family of short- and long-acting analogs of gonadotropin-releasing hormone (GnRH), and it is shown that amyloids thereof can act as a source for the sustained release of biologically active peptides

Forced Moves or Good Tricks in Design Space? Landmarks in the Evolution of Neural Mechanisms for Action Selection

This review considers some important landmarks in animal evolution, asking to what extent specialized action-selection mechanisms play a role in the functional architecture of different nervous system plans, and looking for “forced moves” or “good tricks” (see Dennett, D., 1995, Darwin’s Dangerous Idea, Penguin Books, London) that could possibly transfer to the design of robot control systems. A key conclusion is that while cnidarians (e.g. jellyfish) appear to have discovered some good tricks for the design of behavior-based control systems—largely lacking specialized selection mechanisms—the emergence of bilaterians may have forced the evolution of a central ganglion, or “archaic brain”, whose main function is to resolve conflicts between peripheral systems. Whilst vertebrates have many interesting selection substrates it is likely that here too the evolution of centralized structures such as the medial reticular formation and the basal ganglia may have been a forced move because of the need to limit connection costs as brains increased in size

Small Heat Shock Proteins Potentiate Amyloid Dissolution by Protein Disaggregases from Yeast and Humans

The authors define how small heat-shock proteins synergize to regulate the assembly and disassembly of a beneficial prion, and then they exploit this knowledge to identify the human amyloid depolymerase