Choosing the path of austerity: how parties and policy coalitions influence welfare state retrenchment in periods of fiscal consolidation

What are the conditions under which some austerity programmes rely on substantial cuts to social spending? More specifically, do the partisan complexion and the type of government condition the extent to which austerity policies imply welfare state retrenchment? This article demonstrates that large budget consolidations tend to be associated with welfare state retrenchment. The findings support a partisan and a politico-institutionalist argument: (i) in periods of fiscal consolidation, welfare state retrenchment tends to be more pronounced under left-wing governments; (ii) since welfare state retrenchment is electorally and politically risky, it also tends to be more pronounced when pursued by a broad pro-reform coalition government. Therefore, the article shows that during budget consolidations implemented by left-wing broad coalition governments, welfare state retrenchment is greatest. Using long-run multipliers from autoregressive distributed lag models on 17 OECD countries during the 1982–2009 period, substantial support is found for these expectations.

Dispersal dynamics in food webs

Studies of food webs suggest that limited nonrandom dispersal can play an important role in structuring food webs. It is not clear, however, whether density-dependent dispersal fits empirical patterns of food webs better than density-independent dispersal. Here, we study a spatially distributed food web, using a series of population-dispersal models that contrast density-independent and density-dependent dispersal in landscapes where sampled sites are either homogeneously or heterogeneously distributed. These models are fitted to empirical data, allowing us to infer mechanisms that are consistent with the data. Our results show that models with density-dependent dispersal fit the α, β, and γ tritrophic richness observed in empirical data best. Our results also show that density-dependent dispersal leads to a critical distance threshold beyond which site similarity (i.e., β tritrophic richness) starts to decrease much faster. Such a threshold can also be detected in the empirical data. In contrast, models with density-independent dispersal do not predict such a threshold. Moreover, preferential dispersal from more centrally located sites to peripheral sites does not provide a better fit to empirical data when compared with symmetric dispersal between sites. Our results suggest that nonrandom dispersal in heterogeneous landscapes is an important driver that shapes local and regional richness (i.e., α and γ tritrophic richness, respectively) as well as the distance-decay relationship (i.e., β tritrophic richness) in food webs.

Improving Management of Distributed Services Using Correlations and Predictions in SLA-Driven Cloud Computing Systems

Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

BitWorker, a Decentralized Distributed Computing System based on BitTorrent

In this paper we present BitWorker, a platform for community distributed computing based on BitTorrent. Any splittable task can be easily specified by a user in a meta-information task file, such that it can be downloaded and performed by other volunteers. Peers find each other using Distributed Hash Tables, download existing results, and compute missing ones. Unlike existing distributed computing schemes relying on centralized coordination point(s), our scheme is totally distributed, therefore, highly robust. We evaluate the performance of BitWorker using mathematical models and real tests, showing processing and robustness gains. BitWorker is available for download and use by the community.

Distributed transpressive continental deformation: The Varto Fault Zone, eastern Turkey

The convergence between the Eurasian and Arabian plates has created a complicated structural setting in the Eastern Turkish high plateau (ETHP), particularly around the Karlıova Triple Junction (KTJ) where the Eurasian, Arabian, and Anatolian plates intersect. This region of interest includes the junction of the North Anatolian Shear Zone (NASZ) and the East Anatolian Shear Zone (EASZ), which forms the northern border of the westwardly extruding Anatolian Scholle and the western boundary of the ETHP, respectively. In this study, we focused on a poorly studied component of the KTJ, the Varto Fault Zone (VFZ), and the adjacent secondary structures, which have complex structural settings. Through integrated analyses of remote sensing and field observations, we identified a widely distributed transpressional zone where the Varto segment of the VFZ forms the most northern boundary. The other segments, namely, the Leylekdağ and Çayçatı segments, are oblique-reverse faults that are significantly defined by uplifted topography along their strikes. The measured 515 and 265 m of cumulative uplifts for Mt. Leylek and Mt. Dodan, respectively, yield a minimum uplift rate of 0.35 mm/a for the last 2.2 Ma. The multi-oriented secondary structures were mostly correlated with “the distributed strike-slip” and “the distributed transpressional” in analogue experiments. The misfits in strike of some of secondary faults between our observations and the experimental results were justified by about 20° to 25° clockwise restoration of all relevant structures that were palaeomagnetically measured to have happened since ~ 2.8 Ma ago. Our detected fault patterns and their true nature are well aligned as being part of a transpressional tectonic setting that supports previously suggested stationary triple junction models.

Fault development and interaction in distributed strike-slip shear zones: an experimental approach

Analogue model experiments using both brittle and viscous materials were performed to investigate the development and interaction of strike-slip faults in zones of distributed shear deformation. At low strain, bulk dextral shear deformation of an initial rectangular model is dominantly accommodated by left-stepping, en echelon strike-slip faults (Riedel shears, R) that form in response to the regional (bulk) stress field. Push-up zones form in the area of interaction between adjacent left-stepping Riedel shears. In cross sections, faults bounding push-up zones have an arcuate shape or merge at depth. Adjacent left-stepping R shears merge by sideways propagation or link by short synthetic shears that strike subparallel to the bulk shear direction. Coalescence of en echelon R shears results in major, through-going faults zones (master faults). Several parallel master faults develop due to the distributed nature of deformation. Spacing between master faults is related to the thickness of the brittle layers overlying the basal viscous layer. Master faults control to a large extent the subsequent fault pattern. With increasing strain, relatively short antithetic and synthetic faults develop mostly between old, but still active master faults. The orientation and evolution of the new faults indicate local modifications of the stress field. In experiments lacking lateral borders, closely spaced parallel antithetic faults (cross faults) define blocks that undergo clockwise rotation about a vertical axis with continuing deformation. Fault development and fault interaction at different stages of shear strain in our models show similarities with natural examples that have undergone distributed shear.