3D seismic imaging of buried Younger Dryas mass movement flows: Lake Windermere, UK

Windermere is a glacially overdeepened lake located in the southeastern Lake District, UK. Using the threedimensional(3D) Chirp subbottom profiler, we image mass movement deposits related to the Younger Dryas(YD) within a decimetre-resolution 3D seismic volume, documenting their internal structure and interactionwith preexisting deposits in unprecedented detail. Three distinct flow events are identified and mappedthroughout the 3D survey area. Package structures and seismic attributes classify them as: a small (totalvolume of c. 1500 m3) debris flow containing deformed translated blocks; a large (inferred total volume ofc. 500,000 m3), homogeneous fine-grained mass flow deposit; and a debris flow (inferred total volume ofc. 60,000 m3) containing small (c. 8.0×2.0 m) deformed translated blocks. Geomorphological mapping oftheir distribution and interaction with preexisting sediments permit the reconstruction of a depositionalhistory for the stratigraphic units identified in the seismic volume.<br/

A sampling-based approach for information-theoretic inspection management

A partially supervised approach to Structural Health Monitoring is proposed, to manage the cost associated with expert inspections and maximize the value of monitoring regimes. Unlike conventional data-driven procedures, the monitoring classifier is learnt online while making predictions—negating the requirement for complete data before a system is in operation (which are rarely available). Most critically, periodic inspections are replaced (or enhanced) by an automatic inspection regime, which only queries measurements that appear informative to the evolving model of the damage-sensitive features. The result is a partially supervised Dirichlet process clustering that manages expert inspections online given incremental data. The method is verified on a simulated example and demonstrated on in situ bridge monitoring data

Foundations of population-based SHM, Part I : homogeneous populations and forms

In Structural Health Monitoring (SHM), measured data that correspond to an extensive set of operational and damage conditions (for a given structure) are rarely available. One potential solution considers that information might be transferred, in some sense, between similar systems. A population-based approach to SHM looks to both model and transfer this missing information, by considering data collected from groups of similar structures. Specifically, in this work, a framework is proposed to model a population of nominally-identical systems, such that (complete) datasets are only available from a subset of members. The SHM strategy defines a general model, referred to as the population form, which is used to monitor a homogeneous group of systems. First, the framework is demonstrated through applications to a simulated population, with one experimental (test-rig) member; the form is then adapted and applied to signals recorded from an operational wind farm

Probabilistic inference for structural health monitoring: new modes of learning from data

In data-driven structural health monitoring (SHM), the signals recorded from systems in operation can be noisy and incomplete. Data corresponding to each of the operational, environmental, and damage states are rarely available a priori; furthermore, labeling to describe the measurements is often unavailable. In consequence, the algorithms used to implement SHM should be robust and adaptive while accommodating for missing information in the training data—such that new information can be included if it becomes available. By reviewing novel techniques for statistical learning (introduced in previous work), it is argued that probabilistic algorithms offer a natural solution to the modeling of SHM data in practice. In three case-studies, probabilistic methods are adapted for applications to SHM signals, including semisupervised learning, active learning, and multitask learning

Geometry and slip rate of the Aigion fault, a young normal fault system in the western Gulf of Corinth

The Aigion fault is one of the youngest major normal faults in the Gulf of Corinth, Greece, with an immature displacement profile. Based on geometry, slip rate and comparison with regional faults, we estimate the fault system length at ~10 km. We find the slip rate of the fault system is ~3.5 ± 1 mm/yr decreasing to ~2.5 ± 0.7 mm/yr close to its eastern tip. Complex fault geometry and displacement profiles on the shelf east of Aigion are consistent with the latter as the eastern tip location. Analysis of slip on this fault system and the established fault to the south (Western Eliki Fault) suggests that slip was transferred rapidly but not homogeneously between the two faults during the period of contemporaneous activity. Together with a lack of evidence of lateral propagation at the eastern fault tip in the last 10–13 k.y., we suggest that the fault developed and established its current length rapidly, within its 200–300 k.y. history. These results contribute to our understanding of the process of northward fault migration into the rift and the development of new normal faults

Probabilistic active learning : an online framework for structural health monitoring

A novel, probabilistic framework for the classification, investigation and labelling of data is suggested as an online strategy for Structural Health Monitoring (SHM). A critical issue for data-based SHM is a lack of descriptive labels (for measured data), which correspond to the condition of the monitored system. For many applications, these labels are costly and/or impractical to obtain, and as a result, conventional supervised learning is not feasible. This fact forces a dependence on outlier analysis, or one-class classifiers, in practical applications, as a means of damage detection. The model suggested in this work, however, allows for the definition of a multi-class classifier, to aid both damage detection and identification, while using a limited number of the most informative labelled data. The algorithm is applied to three datasets in the online setting; the Z24 bridge data, a machining (acoustic emission) dataset, and measurements from ground vibration aircraft tests. In the experiments, active learning is shown to improve the online classification performance for damage detection and classification

Radiative cooling of carbon cluster anions C2n+1− (n = 3–5)

Radiative cooling of carbon cluster anions C2n+1− (n = 3–5) is investigated using the cryogenic electrostatic ion storage ring DESIREE. Two different strategies are applied to infer infrared emission on slow (milliseconds to seconds) and ultraslow (seconds to minutes) timescales. Initial cooling of the ions over the millisecond timescale is probed indirectly by monitoring the decay in the yield of spontaneous neutralization by thermionic emission. The observed cooling rates are consistent with a statistical model of thermionic electron emission in competition with infrared photon emission due to vibrational de-excitation. Slower cooling over the seconds to minutes timescale associated with infrared emission from low-frequency vibrational modes is probed using time-dependent action spectroscopy. For C9− and C11−, cooling is evidenced by the time-evolution of the yield of photo-induced neutralization following resonant excitation of electronic transitions near the detachment threshold. The cross-section for resonant photo-excitation is at least two orders of magnitude greater than for direct photodetachment. In contrast, C7− lacks electronic transitions near the detachment threshold

The sensorium at work: the sensory phenomenology of the working body

The sociology of the body and the sociology of work and occupations have both neglected to some extent the study of the ‘working body’ in paid employment, particularly with regard to empirical research into the sensory aspects of working practices. This gap is perhaps surprising given how strongly the sensory dimension features in much of working life. This article is very much a first step in calling for a more phenomenological, embodied and ‘fleshy’ perspective on the body in employment, and examines some of the theoretical and conceptual resources available to researchers wishing to focus on the lived working-body experiences of the sensorium. We also consider some possible representational forms for a more evocative, phenomenologically-inspired portrayal of sensory, lived-working-body experiences, and offer suggestions for future avenues of research

Nietzsche’s Negative Ecologies

Malcolm Bull offers a detailed analysis of nihilism in Nietzsche's works. Along with accompanying commentaries by Cascardi and Clark, he explores the significance of Nietzscheís views given the fact that a wide range of readers have come to embrace his ideas as new orthodoxy. There seem to be no anti-Nietzscheans today, but Bull demonstrates that this wide embrace of Nietzsche runs counter to the very meaning of nihilism as Nietzsche understood it