Book review: madness, distress and the politics of disablement edited by Helen Spandler, Jill Anderson and Bob Sapey

In Madness, Distress and the Politics of Disablement, editors Helen Spandler, Jill Anderson and Bob Sapey bring together contributors to explore the challenges of applying theories and policies of disability to understandings of madness and distress. With a number of essays drawing on close engagement with lived experience, this is a rewarding and frequently compelling read that does not shy away from grappling with the uncertainties surrounding its field of inquiry, finds Peter Barham

Thinking about schizophrenia, thinking about schizophrenic thinking, and schizophrenic thinking

The thesis treats of schizophrenia as a social institution; consideration is given to the way in which schizophrenics speak and think, and to the ideas and practices that have developed around them. Such ideas and practices - both scientific and non-scientific - it is argued, have been generated by the requirements of living in Western societies. The inquiry is in three parts. First, a detailed study of the way in which a single chronic schizophrenic patient engages with the world. Second, a consideration of prevailing approaches to the study of language and thought in schizophrenia. Singled out for special emphasis is the personal construct theory approach to the study of thought disorder; close attention is given to an examination of repertory grids taken from a number of chronic schizophrenic patients. The account of schizophrenic thought that is given by personal construct theory is shown to be inadequate in its own terms, and more generally as servicing human interests that are falsifying both of schizophrenics and of non- schizophrenics. The final section builds on the earlier discussion, and introduces material from other sources, to suggest that, typically, the ideas and practices that have been developed around schizophrenics in the name of a particular version of science have had as their function the restoration of forms of order, relevance and relation to which, in our society, we strongly adhere and of which the schizophrenic is disruptive. Some suggestions are made as to the requirements for an alternative form of response and relation to the tribulations of schizophrenics, and for a formal characterisation of the way in which the schizophrenic engages with the world

Dynamic Control Flow in Large-Scale Machine Learning

Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcement learning depend on recurrence relations, data-dependent conditional execution, and other features that call for dynamic control flow. These applications benefit from the ability to make rapid control-flow decisions across a set of computing devices in a distributed system. For performance, scalability, and expressiveness, a machine learning system must support dynamic control flow in distributed and heterogeneous environments. This paper presents a programming model for distributed machine learning that supports dynamic control flow. We describe the design of the programming model, and its implementation in TensorFlow, a distributed machine learning system. Our approach extends the use of dataflow graphs to represent machine learning models, offering several distinctive features. First, the branches of conditionals and bodies of loops can be partitioned across many machines to run on a set of heterogeneous devices, including CPUs, GPUs, and custom ASICs. Second, programs written in our model support automatic differentiation and distributed gradient computations, which are necessary for training machine learning models that use control flow. Third, our choice of non-strict semantics enables multiple loop iterations to execute in parallel across machines, and to overlap compute and I/O operations. We have done our work in the context of TensorFlow, and it has been used extensively in research and production. We evaluate it using several real-world applications, and demonstrate its performance and scalability.Comment: Appeared in EuroSys 2018. 14 pages, 16 figure

Intercolony variation in reproductive skipping in the African penguin

In long-lived species, reproductive skipping is a common strategy whereby sexually mature animals skip a breeding season, potentially reducing population growth. This may be an adaptive decision to protect survival, or a non-adaptive decision driven by individual-specific constraints. Understanding the presence and drivers of reproductive skipping behavior can be important for effective population management, yet in many species such as the endangered African penguin (Spheniscus demersus), these factors remain unknown

Bayesian inference reveals positive but subtle effects of experimental fishery closures on marine predator demographics

Global forage-fish landings are increasing, with potentially grave consequences for marine ecosystems. Predators of forage fish may be influenced by this harvest, but the nature of these effects is contentious. Experimental fishery manipulations offer the best solution to quantify population-level impacts, but are rare. We used Bayesian inference to examine changes in chick survival, body condition and population growth rate of endangered African penguins Spheniscus demersus in response to 8 years of alternating time-area closures around two pairs of colonies. Our results demonstrate that fishing closures improved chick survival and condition, after controlling for changing prey availability. However, this effect was inconsistent across sites and years, highlighting the difficultly of assessing management interventions in marine ecosystems. Nevertheless, modelled increases in population growth rates exceeded 1% at one colony; i.e. the threshold considered biologically meaningful by fisheries management in South Africa. Fishing closures evidently can improve the population trend of a forage-fish-dependent predator-we therefore recommend they continue in South Africa and support their application elsewhere. However, detecting demographic gains for mobile marine predators from small no-take zones requires experimental time frames and scales that will often exceed those desired by decision makers

An approach for virtual appliance distribution for service deployment

Fulfilling a service request in highly dynamic service environments may require deploying a service. Therefore, the effectiveness of service deployment systems affects initial service response times. On Infrastructure as a Service (IaaS) cloud systems deployable services are encapsulated in virtual appliances. Services are deployed by instantiating virtual machines with their virtual appliances. The virtual machine instantiation process is highly dependent on the size and availability of the virtual appliance that is maintained by service developers. This article proposes an automated virtual appliance creation service that aids the service developers to create efficiently deployable virtual appliances in former systems this task was carried out manually by the developer. We present an algorithm that decomposes these appliances in order to replicate the common virtual appliance parts in IaaS systems. These parts are used to reduce the deployment time of the service by rebuilding the virtual appliance of the service on the deployment target site. With the prototype implementation of the proposed algorithms we demonstrate the decomposition and appliance rebuilding algorithms on a complex web service. © 2010 Elsevier Inc. All rights reserved

Progressing from multidisciplinary to interdisciplinary restoration science: monitoring and applied studies on the Nisqually River Delta

Restoration science is often described as an ultimate test of ecological theory; assessing the value of restoration actions is challenged by difficulties in measuring complex interactions between restored physical processes and the response of biological resources. Yet, demonstrating the value of restoration is a key to sustaining future public investment, especially in light of uncertainty of future climate change effects. At the Nisqually River Delta, a restoration partnership between the U. S. Fish and Wildlife Service Nisqually National Wildlife Refuge (Refuge), the Nisqually Indian Tribe (Tribe), and Ducks Unlimited culminated in re-established tidal flow to 360 ha of historic floodplain and delta representing the largest estuarine restoration in the Pacific Northwest. Restoration of this large delta was expected to result in a substantial improvement in ecological functions and services in southern Puget Sound. The goal of our scientific team, led by the U. S. Geological Survey (USGS) for the project partners, was to assess the biophysical response to restoration. Science objectives were built into a monitoring framework to include hydrodynamics, geomorphology, sedimentation and nearshore processes with vegetation, invertebrate food resources, waterbird, and fisheries. Our science partners included the U. S. Geological Survey, Refuge, Tribe, non-governmental organizations, and universities representing several disciplines. Funding the science was challenging, since as with most wetland restoration projects, adequate funds are rarely included in costs. Instead, the managers and scientists worked together to raise funds through special funds and competitive grants including addressing climate change. With this funding model, a major challenge for the team was communicating and sustaining a vision to make separate multidisciplinary efforts into unified interdisciplinary science. Here, we use lessons learned from early results of the Nisqually River Delta restoration to discuss restoration science in planning processes, funding costs and approaches, monitoring versus applied studies, and advancing interdisciplinary findings from multidisciplinary efforts