Force measurement at the insertion process of cochlear implant electrodes

Several research groups have reported studies on the insertion force measurement at different cochlear implant electrodes. So far, all experimental setups to measure the forces applied to the electrode outside the cochlea (inner ear), ie have measured externally. Our aim was to integrate the sensors into an automatically operating instrument insertion, so that the forces can be measured, which act directly on the electrode, ie an internal force measurement

On Coloring Resilient Graphs

We introduce a new notion of resilience for constraint satisfaction problems, with the goal of more precisely determining the boundary between NP-hardness and the existence of efficient algorithms for resilient instances. In particular, we study $r$-resiliently $k$-colorable graphs, which are those $k$-colorable graphs that remain $k$-colorable even after the addition of any $r$ new edges. We prove lower bounds on the NP-hardness of coloring resiliently colorable graphs, and provide an algorithm that colors sufficiently resilient graphs. We also analyze the corresponding notion of resilience for $k$-SAT. This notion of resilience suggests an array of open questions for graph coloring and other combinatorial problems.Comment: Appearing in MFCS 201

Automated Classification of Airborne Laser Scanning Point Clouds

Making sense of the physical world has always been at the core of mapping. Up until recently, this has always dependent on using the human eye. Using airborne lasers, it has become possible to quickly "see" more of the world in many more dimensions. The resulting enormous point clouds serve as data sources for applications far beyond the original mapping purposes ranging from flooding protection and forestry to threat mitigation. In order to process these large quantities of data, novel methods are required. In this contribution, we develop models to automatically classify ground cover and soil types. Using the logic of machine learning, we critically review the advantages of supervised and unsupervised methods. Focusing on decision trees, we improve accuracy by including beam vector components and using a genetic algorithm. We find that our approach delivers consistently high quality classifications, surpassing classical methods

Functional architecture of reward learning in mushroom body extrinsic neurons of larval Drosophila.

The brain adaptively integrates present sensory input, past experience, and options for future action. The insect mushroom body exemplifies how a central brain structure brings about such integration. Here we use a combination of systematic single-cell labeling, connectomics, transgenic silencing, and activation experiments to study the mushroom body at single-cell resolution, focusing on the behavioral architecture of its input and output neurons (MBINs and MBONs), and of the mushroom body intrinsic APL neuron. Our results reveal the identity and morphology of almost all of these 44 neurons in stage 3 Drosophila larvae. Upon an initial screen, functional analyses focusing on the mushroom body medial lobe uncover sparse and specific functions of its dopaminergic MBINs, its MBONs, and of the GABAergic APL neuron across three behavioral tasks, namely odor preference, taste preference, and associative learning between odor and taste. Our results thus provide a cellular-resolution study case of how brains organize behavior

Testing a Mahalanobis Distance Model of Black Bear Habitat Use in the Ouachita Mountains of Oklahoma

Regional wildlife–habitat models are commonly developed but rarely tested with truly independent data. We tested a published habitat model for black bears (Ursus americanus) with new data collected in a different site in the same ecological region (i.e., Ouachita Mountains of Arkansas and Oklahoma, USA). We used a Mahalanobis distance model developed from relocations of black bears in Arkansas to produce a map layer of Mahalanobis distances on a study area in neighboring Oklahoma. We tested this modeled map layer with relocations of black bears on the Oklahoma area. The distributions of relocations of female black bears were consistent with model predictions. We conclude that this modeling approach can be used to predict regional suitability for a species of interest

Triggered optical coherence tomography for capturing rapid periodic motion

Quantitative cross-sectional imaging of vocal folds during phonation is potentially useful for diagnosis and treatments of laryngeal disorders. Optical coherence tomography (OCT) is a powerful technique, but its relatively low frame rates makes it challenging to visualize rapidly vibrating tissues. Here, we demonstrate a novel method based on triggered laser scanning to capture 4-dimensional (4D) images of samples in motu at audio frequencies over 100 Hz. As proof-of-concept experiments, we applied this technique to imaging the oscillations of biopolymer gels on acoustic vibrators and aerodynamically driven vibrations of the vocal fold in an ex vivo calf larynx model. Our results suggest that triggered 4D OCT may be useful in understanding and assessing the function of vocal folds and developing novel treatments in research and clinical settings

Well-quasi-ordering versus clique-width : new results on bigenic classes.

Daligault, Rao and Thomassé conjectured that if a hereditary class of graphs is well-quasi-ordered by the induced subgraph relation then it has bounded clique-width. Lozin, Razgon and Zamaraev recently showed that this conjecture is not true for infinitely defined classes. For finitely defined classes the conjecture is still open. It is known to hold for classes of graphs defined by a single forbidden induced subgraph H, as such graphs are well-quasi-ordered and are of bounded clique-width if and only if H is an induced subgraph of P4P4. For bigenic classes of graphs i.e. ones defined by two forbidden induced subgraphs there are several open cases in both classifications. We reduce the number of open cases for well-quasi-orderability of such classes from 12 to 9. Our results agree with the conjecture and imply that there are only two remaining cases to verify for bigenic classes