Germanic Mythology in Music: Cultural Memory and Conflict within the Framework of Modern Globalization

The multi-layered enactment of a national past in music has been strongly intertwined with the usage of mythological elements. Having often been compiled as a coherent narrative during the emergence of the European nation-states (like the Finnish Kalevala), the mythological material has often been perceived as a form of historical truth and national justification. This focal role is also apparent in various music genres ranging from folk revival to metal in post-1989 Europe. Within the globalized context, however, local-national interpretations can collide with earlier nationalist appropriations. This complex and sometimes politically conflicting situation becomes particularly evident with groups falling back on symbols and narrations that had previously been employed by Nazi-Germany. While Nazi-Germany had, among others, tried replace the Christmas tradition with elements and songs from Germanic (and other) mythological sources, modern Neo-Nazi music groups often employ central mythological names (like Odin or Tyr) and iconic elements (like Vikings and warriors) in song lyrics and CD cover designs. However, while many covers and lyrics are legally forbidden in Germany, Scandinavian and Baltic groups (like the Faroese Viking metal group Tyr and the Latvian pagan metal band Skyforger) employ similar elements of Norse mythology, which are often combined with traditional material. Discussing selected case studies, this paper highlights central discursive points of colliding historical-national associations and individual interpretations of the mythological elements in musical contexts. How far can the material be disassociated from the earlier historical political usage and instrumentalization? Is this necessary ? And how can the specific global-local conflict points be approached by a theoretical framework ?

What does local tenderness say about the origin of pain? An investigation of cervical zygapophysial joint pain

BACKGROUND: Mechanical pain sensitivity is assessed in every patient with pain, either by palpation or by quantitative pressure algometry. Despite widespread use, no studies have formally addressed the usefulness of this practice for the identification of the source of pain. We tested the hypothesis that assessing mechanical pain sensitivity distinguishes damaged from healthy cervical zygapophysial (facet) joints. METHODS: Thirty-three patients with chronic unilateral neck pain were studied. Pressure pain thresholds (PPTs) were assessed bilaterally at all cervical zygapophysial joints. The diagnosis of zygapophysial joint pain was made by selective nerve blocks. Primary analysis was the comparison of the PPT between symptomatic and contralateral asymptomatic joints. The secondary end points were as follows: differences in PPT between affected and asymptomatic joints of the same side of patients with zygapophysial joint pain; differences in PPT at the painful side between patients with and without zygapophysial joint pain; and sensitivity and specificity of PPT for 2 different cutoffs (difference in PPT between affected and contralateral side by 1 and 30 kPa, meaning that the test was considered positive if the difference in PPT between painful and contralateral side was negative by at least 1 and 30 kPa, respectively). The PPT of patients was also compared with the PPT of 12 pain-free subjects. RESULTS: Zygapophysial joint pain was present in 14 patients. In these cases, the difference in mean PPT between affected and contralateral side (primary analysis) was −6.2 kPa (95% confidence interval: −19.5 to 7.2, P = 0.34). In addition, the secondary analyses yielded no statistically significant differences. For the cutoff of 1 kPa, sensitivity and specificity of PPT were 67% and 16%, respectively, resulting in a positive likelihood ratio of 0.79 and a diagnostic confidence of 38%. When the cutoff of 30 kPa was considered, the sensitivity decreased to only 13%, whereas the specificity increased to 95%, resulting in a positive likelihood ratio of 2.53 and a diagnostic confidence of 67%. The PPT was significantly lower in patients than in pain-free subjects (P < 0.001). CONCLUSIONS: Assessing mechanical pain sensitivity is not diagnostic for cervical zygapophysial joint pain. The finding should stimulate further research into a diagnostic tool that is widely used in the clinical examination of patients with pain.

A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima

Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.

Ethnography of a Land-Deal. Local Perceptions and Vertical Perspectives of a Large Scale Land Acquisition Project in Northern Sierra Leone

Despite an increased scientific interest in the relatively new phenomenon of large-scale land acquisition (LSLA), data on processes on the local level remain sparse and superficial. However, knowledge about the concrete implementation of LSLA projects and the different impacts they have on the heterogeneous group of project affected people is indispensable for a deepened understanding of the phenomenon. In order to address this research gap, a team of two anthropologists and a human geographer conducted in-depth fieldwork on the LSLA project of Swiss based Addax Bioenergy in Sierra Leone. After the devastating civil war, the Sierra Leonean government created favourable conditions for foreign investors willing to lease large areas of land and to bring “development” to the country. Being one of the numerous investing companies, Addax Bioenergy has leased 57’000 hectares of land to develop a sugarcane plantation and an ethanol factory to produce biofuel for the export to the European market. Based on participatory observation, qualitative interview techniques and a network analysis, the research team aimed a) at identifying the different actors that were necessary for the implementation of this project on a vertical level and b) exploring various impacts of the project in the local context of two villages on a horizontal level. The network analysis reveals a complex pattern of companies, institutions, nongovernmental organisations and prominent personalities acting within a shifting technological and discursive framework linking global scales to a unique local context. Findings from the latter indicate that affected people initially welcomed the project but now remain frustrated since many promises and expectations have not been fulfilled. Although some local people are able to benefit from the project, the loss of natural resources that comes along with the land lease affects livelihoods of vulnerable groups – especially women and land users – considerably. However, this research doesn’t only disclose impacts on local people’s previous lives but also addresses strategies they adopt in the newly created situation that has opened up alternative spaces for renegotiations of power and legitimatisation. Therewith, this explorative study reveals new aspects of LSLA that have not been considered adequately by the investing company nor by the general academic discourse on LSLA.

Local Perceptions and Vertical Perspectives of a Large Scale Land Acquisition Project in Northern Sierra Leone

Despite increased scientific interest in the phenomenon of large-scale land acquisitions (LSLA), accurate data on implementation processes remain sparse. This paper aims at filling this gap by providing empirical in-depth knowledge on the case of the Swiss-based Addax Bioenergy Ltd. in Sierra Leone. Extensive fieldwork allowed the interdisciplinary research team 1) the identification of different actors that are necessary for the implementation on a vertical level and 2) the documentation of the heterogeneous group of project affected people’s perceptions and strategies on a horizontal level. Findings reveal that even a project labeled as best-practice example by UN agencies triggers a number of problematic processes for affected communities. The loss of natural resources that comes along with the land lease and the lack of employment possibilities mostly affects already vulnerable groups. On the other hand, strategies and resistance of local people also affect the project implementation. This shows that the horizontal and vertical levels are not separate entities. They are linked by social networks, social interactions, and means of communication and both levels take part in shaping the project’s impacts.

Global Optimization with Sparse and Local Gaussian Process Models

We present a novel surrogate model-based global optimization framework allowing a large number of function evaluations. The method, called SpLEGO, is based on a multi-scale expected improvement (EI) framework relying on both sparse and local Gaussian process (GP) models. First, a bi-objective approach relying on a global sparse GP model is used to determine potential next sampling regions. Local GP models are then constructed within each selected region. The method subsequently employs the standard expected improvement criterion to deal with the exploration-exploitation trade-off within selected local models, leading to a decision on where to perform the next function evaluation(s). The potential of our approach is demonstrated using the so-called Sparse Pseudo-input GP as a global model. The algorithm is tested on four benchmark problems, whose number of starting points ranges from 102 to 104. Our results show that SpLEGO is effective and capable of solving problems with large number of starting points, and it even provides significant advantages when compared with state-of-the-art EI algorithms.

Deep Points Consolidation

In this paper, we present a consolidation method that is based on a new representation of 3D point sets. The key idea is to augment each surface point into a deep point by associating it with an inner point that resides on the meso-skeleton, which consists of a mixture of skeletal curves and sheets. The deep points representation is a result of a joint optimization applied to both ends of the deep points. The optimization objective is to fairly distribute the end points across the surface and the meso-skeleton, such that the deep point orientations agree with the surface normals. The optimization converges where the inner points form a coherent meso-skeleton, and the surface points are consolidated with the missing regions completed. The strength of this new representation stems from the fact that it is comprised of both local and non-local geometric information. We demonstrate the advantages of the deep points consolidation technique by employing it to consolidate and complete noisy point-sampled geometry with large missing parts.