The Consent Paradox: Accounting for the Prominent Role of Consent in Data Protection

The concept of consent is a central pillar of data protection. It features prominently in research, regulation, and public debates on the subject, in spite of the wide-ranging criticisms that have been levelled against it. In this paper, I refer to this as the consent paradox. I argue that consent continues to play a central role not despite but because the criticisms of it. I analyze the debate on consent in the scholarly literature in general, and among German data protection professionals in particular, showing that it is a focus on the informed individual that keeps the concept of consent in place. Critiques of consent based on the notion of “informedness” reinforce the centrality of consent rather than calling it into question. They allude to a market view that foregrounds individual choice. Yet, the idea of a data market obscures more fundamental objections to consent, namely the individual’s dependency on data controllers’ services that renders the assumption of free choice a fiction

Protocol for a randomized controlled trial on risk adapted damage control orthopedic surgery of femur shaft fractures in multiple trauma patients

<p>Abstract</p> <p>Background</p> <p>Fractures of the long bones and femur fractures in particular are common in multiple trauma patients, but the optimal management of femur fractures in these patients is not yet resolved. Although there is a trend towards the concept of "Damage Control Orthopedics" (DCO) in the management of multiple trauma patients with long bone fractures as reflected by a significant increase in primary external fixation of femur fractures, current literature is insufficient. Thus, in the era of "evidence-based medicine", there is the need for a more specific, clarifying trial.</p> <p>Methods/Design</p> <p>The trial is designed as a randomized controlled open-label multicenter study. Multiple trauma patients with femur shaft fractures and a calculated probability of death between 20 and 60% will be randomized to either temporary fracture fixation with fixateur externe and defined secondary definitive treatment (DCO) or primary reamed nailing (early total care). The primary objective is to reduce the extent of organ failure as measured by the maximum sepsis-related organ failure assessment (SOFA) score.</p> <p>Discussion</p> <p>The Damage Control Study is the first to evaluate the risk adapted damage control orthopedic surgery concept of femur shaft fractures in multiple trauma patients in a randomized controlled design. The trial investigates the differences in clinical outcome of two currently accepted different ways of treating multiple trauma patients with femoral shaft fractures. This study will help to answer the question whether the "early total care" or the „damage control” concept is associated with better outcome.</p> <p>Trial registration</p> <p>Current Controlled Trials ISRCTN10321620</p

The double focal transformation and its application to data reconstruction

Many seismic data processing and imaging processes require densely and regularly sampled data, whereas the actual measurements are mostly irregularly and sparsely sampled. Therefore, seismic data reconstruction methods are utilised as a pre-processing step. Within the class of transformation-based reconstruction techniques, observed seismic data is decomposed into certain basis functions, such as plane waves, parabolas or curvelets. In the corresponding model space the aliasing noise is assumed to have different properties than the seismic signal and can be suppressed. However, in many cases subsurface information is available that cannot be used in these traditional reconstruction methods. Therefore, the double focal transformation was derived as a way to incorporate knowledge about the subsurface in the reconstruction algorithm. The basic principle of the double focal transformation is to focus seismic energy by a back-propagation of the seismic data at the source and receiver side to certain depth levels. As a result, the seismic data are represented by a limited number of samples in the focal domain in a localised area, whereas aliasing noise spreads out. By imposing a sparse solution in the focal domain, aliasing noise is suppressed and data reconstruction beyond aliasing is achieved. To facilitate the process, only a few effective depth levels need to be included, preferably along the major boundaries in the subsurface. Propagation operators from these boundaries to the surface (focal operators) serve as the basis functions of this data decomposition method. Including more depth levels allows a sparser data representation, and hence, increases the reconstruction capability. The more precise the subsurface information is known, the more accurate these propagators can be computed. However, very precise operators are not necessary for a good reconstruction result, because in the reconstruction step (the inverse focal transformation) the effect of these operators is again removed. The calculation of the double focal transformation requires a non-linear inversion process, where the samples in the focal domain are estimated such that they - after inverse transformation - match the input data at the measurement locations. Because the inversion process is under-determined, an extra constraint on the focal domain is applied, for which the minimum L1 norm is chosen. This forces the distribution in the focal domain to be sparse and - thereby - suppresses the aliasing noise. For the inversion a so-called spgl1 solver has been used that is guaranteed to converge to the desired minimum of the defined objective function. It utilises a steepest decent type iterative process, called Spectral Projected Gradient. Seismic data reconstruction via the double focal transform method appears to be robust against inaccuracies in the focal operators up to roughly ten percent velocity error. Furthermore, the method was extended to the full 3D case, where each focal transform sub-domain in principle contains a 5D data space. In addition to the basic focal transformation, the method can be combined with other transforms in order to increase data compression. As an example, the double focal transformation can be combined with the linear Radon transformation, such that the seismic data can be represented sparser and fewer focal operators are necessary. Satisfactory results of focal domain data reconstruction beyond aliasing on 2D and 3D synthetic and 2D field data illustrate the method’s virtues.Department of Imaging PhysicsApplied Science

Osteosynthesis of distal radial fractures with a volar locking screw plate system

We developed a locking screw plate system for the stabilisation of distal radial fractures, which can be inserted through a standard volar approach and in which the locking mechanism allows early post-operative mobilisation. Forty-nine patients with 50 fractures underwent surgical treatment; 66% were type C fractures. The mean follow-up was 26 months. According to the scores of Gartland and Werley and Green and O'Brien, 92% and 68% respectively had an excellent or good outcome; 46% were radiologically identical to the uninjured side and in 42% the reduction remained unchanged after 2 years. The most frequent complication was rupture of the flexor pollicis longus tendon, which occurred in six cases (12%) at a mean of 10 months after operation

The utilization of the double focal transformation for sparse data representation and data reconstruction

In many cases, seismic measurements are coarsely sampled in at least one dimension. This leads to aliasing artefacts and therefore to problems in the subsequent processing steps. To avoid this, seismic data reconstruction can be applied in advance. The success and reliability of reconstruction methods are dependent on the assumptions they make on the data. In many cases, wavefields are assumed to (locally) have a linear space–time behaviour. However, field data are usually complex, with strongly curved events. Therefore, in this paper, we propose the double focal transformation as an efficient way for complex data reconstruction. Hereby, wavefield propagation is formulated as a transformation, where one-way propagation operators are used as its basis functions. These wavefield operators can be based on a macro velocity model, which allows our method to use prior information in order to make the data decomposition more effective. The basic principle of the double focal transformation is to focus seismic energy along source and receiver coordinates simultaneously. The seismic data are represented by a number of localized events in the focal domain, whereas aliasing noise spreads out. By imposing a sparse solution in the focal domain, aliasing noise is suppressed, and data reconstruction beyond aliasing is achieved. To facilitate the process, only a few effective depth levels need to be included, preferably along the major boundaries in the data, from which the propagation operators can be calculated. Results on 2D and 3D synthetic data illustrate the method's virtues. Furthermore, seismic data reconstruction on a 2D field dataset with gaps and aliased source spacing demonstrates the strength of the double focal transformation, particularly for near-offset reflections with strong curvature and for diffractions.ImPhys/Acoustical Wavefield Imagin

Dispersive multi-modal mud-roll elimination using feedback-loop approach

In a shallow water environment, mud-rolls are often dominant and appear as a prevailing coherent noise in OBC seismic data. Their complex properties make the noise elimination notably challenging in seismic processing. To address these challenges, we propose a dispersive multimodal mud-roll elimination method using a feedback-loop approach with a sparse inversion of focal/Radon transformation. In this paper, we illustrate the proposed method, and show some examples on synthetic seismic data to demonstrate its virtues.Geoscience & EngineeringCivil Engineering and Geoscience