Comparison of different objective functions for parameterization of simple respiration models

The eddy covariance measurements of carbon dioxide fluxes collected around the world offer a rich source for detailed data analysis. Simple, aggregated models are attractive tools for gap filling, budget calculation, and upscaling in space and time. Key in the application of these models is their parameterization and a robust estimate of the uncertainty and reliability of their predictions. In this study we compared the use of ordinary least squares (OLS) and weighted absolute deviations (WAD, which is the objective function yielding maximum likelihood parameter estimates with a double exponential error distribution) as objective functions within the annual parameterization of two respiration models: the Q10 model and the Lloyd and Taylor model. We introduce a new parameterization method based on two nonparametric tests in which model deviation (Wilcoxon test) and residual trend analyses (Spearman test) are combined. A data set of 9 years of flux measurements was used for this study. The analysis showed that the choice of the objective function is crucial, resulting in differences in the estimated annual respiration budget of up to 40%. The objective function should be tested thoroughly to determine whether it is appropriate for the application for which the model will be used. If simple models are used to estimate a respiration budget, a trend test is essential to achieve unbiased estimates over the year. The analyses also showed that the parameters of the Lloyd and Taylor model are highly correlated and difficult to determine precisely, thereby limiting the physiological interpretability of the parameter

Cellular internalization of alpha-synuclein aggregates by cell surface heparan sulfate depends on aggregate conformation and cell type.

Amyloid aggregates found in the brain of patients with neurodegenerative diseases, including Alzheimer's and Parkinson's disease, are thought to spread to increasingly larger areas of the brain through a prion-like seeding mechanism. Not much is known about which cell surface receptors may be involved in the cell-to-cell transfer, but proteoglycans are of interest due to their well-known propensity to interact with amyloid aggregates. In this study, we investigated the involvement of plasma membrane-bound heparan and chondroitin sulfate proteoglycans in cellular uptake of aggregates consisting of α-synuclein, a protein forming amyloid aggregates in Parkinson's disease. We show, using a pH-sensitive probe, that internalization of α-synuclein amyloid fibrils in neuroblastoma cells is dependent on heparan sulfate, whereas internalization of smaller non-amyloid oligomers is not. We also show that α-synuclein fibril uptake in an oligodendrocyte-like cell line is equally dependent on heparan sulfate, while astrocyte- and microglia-like cell lines have other means to internalize the fibrils. In addition, we analyzed the interaction between the α-synuclein amyloid fibrils and heparan sulfate and show that overall sulfation of the heparan sulfate chains is more important than sulfation at particular sites along the chains

Sex pheromone signal and stability covary with fitness

If sexual signals are costly, covariance between signal expression and fitness is expected. Signal–fitness covariance is important, because it can contribute to the maintenance of genetic variation in signals that are under natural or sexual selection. Chemical signals, such as female sex pheromones in moths, have traditionally been assumed to be species-recognition signals, but their relationship with fitness is unclear. Here, we test whether chemical, conspecific mate finding signals covary with fitness in the moth Heliothis subflexa. Additionally, as moth signals are synthesized de novo every night, the maintenance of the signal can be costly. Therefore, we also hypothesized that fitness covaries with signal stability (i.e. lack of temporal intra-individual variation). We measured among- and within-individual variation in pheromone characteristics as well as fecundity, fertility and lifespan in two independent groups that differed in the time in between two pheromone samples. In both groups, we found fitness to be correlated with pheromone amount, composition and stability, supporting both our hypotheses. This study is, to our knowledge, the first to report a correlation between fitness and sex pheromone composition in moths, supporting evidence of condition-dependence and highlighting how signal–fitness covariance may contribute to heritable variation in chemical signals both among and within individuals

Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification

There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to distinguish subjects remains opaque. In this work, we address this issue by comparing 35 structural connectome-building pipelines. We vary diffusion reconstruction models, tractography algorithms and parcellations. Next, we classify structural connectome pairs as either belonging to the same individual or not. Connectome weights and eight topological derivative measures form our feature set. For experiments, we use three test-retest datasets from the Consortium for Reliability and Reproducibility (CoRR) comprised of a total of 105 individuals. We also compare pairwise classification results to a commonly used parametric test-retest measure, Intraclass Correlation Coefficient (ICC).Comment: Accepted for MICCAI 2017, 8 pages, 3 figure

Monitoring Glacier Surface Seismicity in Time and Space Using Rayleigh Waves

Sliding glaciers and brittle ice failure generate seismic body and surface wave energy characteristic to the source mechanism. Here we analyze continuous seismic recordings from an array of nine short-period passive seismometers located on Bench Glacier, Alaska (USA) (61.033°N, 145.687°W). We focus on the arrival-time and amplitude information of the dominant Rayleigh wave phase. Over a 46-hour period we detect thousands of events using a cross-correlation based event identification method. Travel-time inversion of a subset of events (7% of the total) defines an active crevasse, propagating more than 200 meters in three hours. From the Rayleigh wave amplitudes, we estimate the amount of volumetric opening along the crevasse as well as an average bulk attenuation ( Q ¯ = 42) for the ice in this part of the glacier. With the remaining icequake signals we establish a diurnal periodicity in seismicity, indicating that surface run-off and subglacial water pressure changes likely control the triggering of these surface events. Furthermore, we find that these events are too weak (i.e., too noisy) to locate individually. However, stacking individual events increases the signal-to-noise ratio of the waveforms, implying that these periodic sources are effectively stationary during the recording period

A Zoomable Mapping of a Musical Parameter Space Using Hilbert Curves

The final publication is available at Computer Music Journal via http://dx.doi.org/10.1162/COMJ_a_0025

A review on farm household modelling with a focus on climate change adaptation and mitigation

This study systematically reviewed the literature to evaluate how suitable existing farm and farm household models are to study aspects of food security in relation to climate change adaptation, risk management and mitigation. We systematically scanned approximately 16,000 research articles covering more than a 1000 models. We found 126 models that met the criteria for subsequent detailed analysis. Although many models use climate as an input, few were used to study climate change adaptation or mitigation at farm level. Promising mixtures of methodologies include mathematical programming for farm level decision-making, dynamic simulation for the production components and agent based modelling for the spread of information and technologies between farmers. There is a need for more explicit farm level analyses with a focus on adaptation, vulnerability and risk. In general terms, this systematic review concludes that there are enough techniques for integrated assessments of farm systems in relation to climate change, adaptation and mitigation, but they have not yet been combined in a way that is meaningful to farm level decision makers