Precise pose recovery of distal locking holes from single calibrated fluoroscopic image via a novel variable decomposition approach

This paper presents a novel variable decomposition approach for pose recovery of the distal locking holes using single calibrated fluoroscopic image. The problem is formulated as a model-based optimal fitting process, where the control variables are decomposed into two sets: (a) the angle between the nail axis and its projection on the imaging plane, and (b) the translation and rotation of the geometrical model of the distal locking hole around the nail axis. By using an iterative algorithm to find the optimal values of the latter set of variables for any given value of the former variable, we reduce the multiple-dimensional model-based optimal fitting problem to a one-dimensional search along a finite interval. We report the results of our in vitro experiments, which demonstrate that the accuracy of our approach is adequate for successful distal locking of intramedullary nails.

The role of peat decomposition in patterned mires: a case study from the central Swiss Alps

A number of hydrological, botanical, macro- and micro-climatological processes are involved in the formation of patterned peatlands. La Grande Tsa at 2336 m a.s.l. is probably the highest bog in the central Swiss Alps and is unique in its pattern. In two of five pools there is in the contact zone between the basal peat and the overlying gyttja an unconformity in the depth-age models based on radiocarbon dates. Palynostratigraphies of cores from a ridge and a pool confirm the occurrence of an unconformity in the contact zone. We conclude that deepening of the pools results from decomposition of peat. The fact that the dated unconformities in the two pools and the unconformity in the ridge-core all fall within the Bronze Age suggest they were caused by events external to the bog. We hypothesize that early transhumance resulted in anthropogenic lowering of the timberline, which resulted in a reduction in the leaf-area index and evapotranspiration, and in higher water levels and thus pool formation.

Topographic time-frequency decomposition of the EEG

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.