Gezielte Gestaltung lohnt sich

In der Diskussion um Löhne gehen die Lohnnebenleistungen oft vergessen. Ergebnisse der HR-Barometer-Studie belegen, dass Zufriedenheit mit den Lohnnebenleistungen starke, positive Effekte auf die Arbeitseinstellung der Mitarbeitenden ausübt

Smac Mimetics and TNFalpha: A Dangerous Liaison?

Inhibitor of apoptosis proteins (IAPs) such as XIAP, cIAP1, and cIAP2 are upregulated in many cancer cells. It has been thought that small-molecule mimetics of Smac, an endogenous IAP antagonist, might potentiate apoptosis in cancer cells by promoting caspase activation. However, three recent papers, two in Cell (Vince et al., 2007; Varfolomeev et al., 2007) and one in Cancer Cell (Petersen et al., 2007), now report that Smac mimetics primarily kill cancer cells via a different mechanism, the induction of autoubiquitination and degradation of cIAPs, which culminates in TNFalpha-mediated cell death

Large Scale Image Segmentation with Structured Loss based Deep Learning for Connectome Reconstruction

We present a method combining affinity prediction with region agglomeration, which improves significantly upon the state of the art of neuron segmentation from electron microscopy (EM) in accuracy and scalability. Our method consists of a 3D U-NET, trained to predict affinities between voxels, followed by iterative region agglomeration. We train using a structured loss based on MALIS, encouraging topologically correct segmentations obtained from affinity thresholding. Our extension consists of two parts: First, we present a quasi-linear method to compute the loss gradient, improving over the original quadratic algorithm. Second, we compute the gradient in two separate passes to avoid spurious gradient contributions in early training stages. Our predictions are accurate enough that simple learning-free percentile-based agglomeration outperforms more involved methods used earlier on inferior predictions. We present results on three diverse EM datasets, achieving relative improvements over previous results of 27%, 15%, and 250%. Our findings suggest that a single method can be applied to both nearly isotropic block-face EM data and anisotropic serial sectioned EM data. The runtime of our method scales linearly with the size of the volume and achieves a throughput of about 2.6 seconds per megavoxel, qualifying our method for the processing of very large datasets

Codifying and commodifying nature: Narratives on forest property rights and the implementation of tenure regularization policies in Northwestern Argentina

Environmental resource management requires negotiation among state and non-state actors with conflicting goals and different levels of influence. In northwestern Argentina, forest policy implementation is described as weak, due to governance structure and ambiguities in the law. We studied how policy actors’ attitudes and their positions in the forest governance network relate to the implementation of land tenure regularization in a context where land tenure regularization is at the core of struggles over environmental policies. We focused on the Chaco Salteño part of the Gran Chaco ecosystem, one of the world’s major deforestation frontiers. We argue that the presence of weak advocacy coalitions requires an analysis of agency to understand this policy process. Our policy network analysis revealed a lack of clear contrasting factions, due to a core–periphery structure. The core of the network brings together all core beliefs but not all of the most influential actors. Assessing network centrality and reputational influence enabled us to identify actors with exceptional agency. We contribute to the debates on advocacy coalitions and on land tenure by distinguishing between attitudes toward tenure regularization policies and their actual implementation in a context where actors have diverging interests and objectives

Talking about trees: the territorial classification of native forests in the Argentinian Chaco

Deforestation represents an important contributor to climate change. For this reason, identifying conditions that enable the adoption of policies halting or reversing this process is crucial to avoid catastrophic climate change. The Argentinian Gran Chaco is a hotspot of deforestation, mainly due to the expansion of capital-intensive agriculture. In Argentina, the introduction of the national forest law (NFL) represents an important step to protect the remaining forests. However, in the Chaco ecoregion, the implementation of the NFL by the different provinces is extremely heterogeneous. Previous research has provided rich descriptions of the dynamics behind the implementation of the NFL. Yet this research, mainly based on qualitative approaches, does not allow for a systematic analysis of the conditions leading to more or less stringent implementations of the NFL. To address this gap, we first combine the socio-ecological systems framework with historical materialism to generate a plausible hypothesis for the heterogeneous implementation of the NFL across the 12 different provinces of the Argentinian Chaco. Specifically, we hypothesise that it is the differences in contextual factors (i.e. differences in forest cover), material/economic conditions (i.e. presence and extent of capital-intensive agriculture) and the strength of pro- and anti-deforestation coalitions, which lead to a heterogeneous territorial classification of native forests across the various provinces. Subsequently, we test the hypothesis by developing thorough case studies via qualitative comparative analysis. This approach allows us to study in a more systematic way the reasons for the observed institutional heterogeneity. The results show that the proportion of native forests characterised as of low conservation value reflects both the environmental context (i.e. the extent of native forests) as well as the material/economic conditions (i.e. the extent of capital-intensive agriculture) and the presence of strong pro-deforestation cultures, expressed via pro-deforestation coalitions

Collaborative governance networks: A case study of argentina’s forest law

Deforestation causes biodiversity loss and the eviction of small-scale ranchers and indigenous people. Accordingly, it is a global issue in environmental politics. This article analyzes a participatory governance system associated with the implementation of Argentina’s forest law in a hotspot of deforestation: the province of Salta in the Gran Chaco ecoregion. Specifically, this article investigates policy actors’ core beliefs, how they match with policy network clusters, and how this affects the implementation of the forest law. The study is based on a unique data set derived from extensive fieldwork and a network survey among all actors who participate in the policy forums. After defining three main core beliefs that describe policy actors’ motivations, we systematically analyze all key actors’ beliefs as well as their interactions in the various policy networks. This analysis shows that it is necessary to empirically identify coalitions based on both behavior and core beliefs to understand the limited implementation of the law. Our methodological approach holds promise for the analysis of other governance systems where multiple stakeholders engage in consensus-oriented decision-making