Diversity, urban space and the right to the provincial city

Using three vignettes of the same physical space this article contributes to understanding of how the right to the city is contested in provincial England in the early twenty-first century. Oral history and ethnographic material gathered in Peterborough between 2010 and 2012 are drawn on to shed new light on the politics of diversity and urban space. This highlights the multiple place attachments and trans-spatial practices of all residents, including the white ethnic majority, as well as contrasting forms of active intervention in space with their different temporalities and affective intensities. The article carries its own diversity politics, seeking to reduce the harm done by racism through challenging the normalisation of the idea of a local, indigenous population, left out by multiculturalism. It simultaneously raises critical questions about capitalist regeneration strategies in terms of their impact both on class inequality and on the environment

SMART (Stochastic Model Acquisition with ReinforcemenT) learning agents: A preliminary report

We present a framework for building agents that learn using SMART, a system that combines stochastic model acquisition with reinforcement learning to enable an agent to model its environment through experience and subsequently form action selection policies using the acquired model. We extend an existing algorithm for automatic creation of stochastic strips operators [9] as a preliminary method of environment modelling. We then define the process of generation of future states using these operators and an initial state and finally show the process by which the agent can use the generated states to form a policy with a standard reinforcement learning algorithm. The potential of SMART is exemplified using the well-known predator prey scenario. Results of applying SMART to this environment and directions for future work are discussed

Abductive knowledge induction from raw data

For many reasoning-heavy tasks with raw inputs, it is challenging to design an appropriate end-to-end pipeline to formulate the problem-solving process. Some modern AI systems, e.g., Neuro-Symbolic Learning, divide the pipeline into sub-symbolic perception and symbolic reasoning, trying to utilise data-driven machine learning and knowledge-driven problem-solving simultaneously. However, these systems suffer from the exponential computational complexity caused by the interface between the two components, where the sub-symbolic learning model lacks direct supervision, and the symbolic model lacks accurate input facts. Hence, they usually focus on learning the sub-symbolic model with a complete symbolic knowledge base while avoiding a crucial problem: where does the knowledge come from? In this paper, we present Abductive Meta-Interpretive Learning (MetaAbd) that unites abduction and induction to learn neural networks and logic theories jointly from raw data. Experimental results demonstrate that MetaAbd not only outperforms the compared systems in predictive accuracy and data efficiency but also induces logic programs that can be re-used as background knowledge in subsequent learning tasks. To the best of our knowledge, MetaAbd is the first system that can jointly learn neural networks from scratch and induce recursive first-order logic theories with predicate invention

Fast relational learning using bottom clause propositionalization with artificial neural networks

Relational learning can be described as the task of learning first-order logic rules from examples. It has enabled a number of new machine learning applications, e.g. graph mining and link analysis. Inductive Logic Programming (ILP) performs relational learning either directly by manipulating first-order rules or through propositionalization, which translates the relational task into an attribute-value learning task by representing subsets of relations as features. In this paper, we introduce a fast method and system for relational learning based on a novel propositionalization called Bottom Clause Propositionalization (BCP). Bottom clauses are boundaries in the hypothesis search space used by ILP systems Progol and Aleph. Bottom clauses carry semantic meaning and can be mapped directly onto numerical vectors, simplifying the feature extraction process. We have integrated BCP with a well-known neural-symbolic system, C-IL2P, to perform learning from numerical vectors. C-IL2P uses background knowledge in the form of propositional logic programs to build a neural network. The integrated system, which we call CILP++, handles first-order logic knowledge and is available for download from Sourceforge. We have evaluated CILP++ on seven ILP datasets, comparing results with Aleph and a well-known propositionalization method, RSD. The results show that CILP++ can achieve accuracy comparable to Aleph, while being generally faster, BCP achieved statistically significant improvement in accuracy in comparison with RSD when running with a neural network, but BCP and RSD perform similarly when running with C4.5. We have also extended CILP++ to include a statistical feature selection method, mRMR, with preliminary results indicating that a reduction of more than 90 % of features can be achieved with a small loss of accuracy

Refined clothespin relocation test and assessment of motion

Background: Advancements in upper limb prosthesis design have focused on providing increased degrees of freedom for the end effector through multiple articulations of a prosthetic hand, wrist and elbow. Measuring improvement in patient function with these devices requires development of appropriate assessment tools. Objectives: This study presents a refined clothespin relocation test for measuring performance and assessing compensatory motion between able-bodied subjects and subjects with upper limb impairments. Study Design: Comparative analysis Methods: Trunk and head motions of 13 able-bodied subjects who performed the refined clothespin relocation test were compared to the motion of a transradial prosthesis user with a single degree of freedom hand. Results: There were observable differences between the prosthesis user and the able-bodied group. The assessment used provided a clear indication of the differences in motion through analysis of compensatory motion. Conclusion: The refined clothespin relocation test provides additional benefits over the standard clothespin assessment and makes identification of compensatory motions easily identifiable to the researcher. While this paper establishes the method for the new assessment, further validation will need to be performed with more users

An objective spinal motion imaging assessment (OSMIA): reliability, accuracy and exposure data.

BACKGROUND: Minimally-invasive measurement of continuous inter-vertebral motion in clinical settings is difficult to achieve. This paper describes the reliability, validity and radiation exposure levels in a new Objective Spinal Motion Imaging Assessment system (OSMIA) based on low-dose fluoroscopy and image processing. METHODS: Fluoroscopic sequences in coronal and sagittal planes were obtained from 2 calibration models using dry lumbar vertebrae, plus the lumbar spines of 30 asymptomatic volunteers. Calibration model 1 (mobile) was screened upright, in 7 inter-vertebral positions. The volunteers and calibration model 2 (fixed) were screened on a motorized table comprising 2 horizontal sections, one of which moved through 80 degrees. Model 2 was screened during motion 5 times and the L2-S1 levels of the volunteers twice. Images were digitised at 5fps. Inter-vertebral motion from model 1 was compared to its pre-settings to investigate accuracy. For volunteers and model 2, the first digitised image in each sequence was marked with templates. Vertebrae were tracked throughout the motion using automated frame-to-frame registration. For each frame, vertebral angles were subtracted giving inter-vertebral motion graphs. Volunteer data were acquired twice on the same day and analysed by two blinded observers. The root-mean-square (RMS) differences between paired data were used as the measure of reliability. RESULTS: RMS difference between reference and computed inter-vertebral angles in model 1 was 0.32 degrees for side-bending and 0.52 degrees for flexion-extension. For model 2, X-ray positioning contributed more to the variance of range measurement than did automated registration. For volunteer image sequences, RMS inter-observer variation in intervertebral motion range in the coronal plane was 1.86 degrees and intra-subject biological variation was between 2.75 degrees and 2.91 degrees. RMS inter-observer variation in the sagittal plane was 1.94 degrees. Radiation dosages in each view were below the levels recommended for a plain film. CONCLUSION: OSMIA can measure inter-vertebral angular motion patterns in routine clinical settings if modern image intensifier systems are used. It requires skillful radiography to achieve optimal positioning and dose limitation. Reliability in individual subjects can be judged from the variance of their averaged inter-vertebral angles and by observing automated image registration

Enriching Visual with Verbal Explanations for Relational Concepts -- Combining LIME with Aleph

With the increasing number of deep learning applications, there is a growing demand for explanations. Visual explanations provide information about which parts of an image are relevant for a classifier's decision. However, highlighting of image parts (e.g., an eye) cannot capture the relevance of a specific feature value for a class (e.g., that the eye is wide open). Furthermore, highlighting cannot convey whether the classification depends on the mere presence of parts or on a specific spatial relation between them. Consequently, we present an approach that is capable of explaining a classifier's decision in terms of logic rules obtained by the Inductive Logic Programming system Aleph. The examples and the background knowledge needed for Aleph are based on the explanation generation method LIME. We demonstrate our approach with images of a blocksworld domain. First, we show that our approach is capable of identifying a single relation as important explanatory construct. Afterwards, we present the more complex relational concept of towers. Finally, we show how the generated relational rules can be explicitly related with the input image, resulting in richer explanations

Biology ideology and pastiche hegemony

As knowledge about the biological foundation of the modern patriarchal gender order is increasingly challenged within late-modern social worlds enclaves persist in which men and women can attempt to recreate understandings of the "natural" basis of sex difference. Within "Power Gym," male boxers were able to symbolize their bodies and behaviors in such a manner. The language and logic of popular scientific discourses authored and authorized notions of an "innate" manhood. The ability to instrumentally deploy one's manliness in symbolically legitimate ways could then be represented and emotionally experienced as a man's biological right and obligation. Through scripted performances of "mimetic" violence and self-bullying, the boxers were able to experience this discursive naturalness and carve out a masculinity-validating social enclave. As such, they accessed a "patriarchal dividend" by securing a local pastiche hegemony in which discourses surrounding men's natural place as physically and psychologically dominant remained largely uncontested. Through the reflexive appropriation of "science," within appropriate subcultural codes, these men could negotiate taboos and restrictions that are characteristic of late-modern social worlds. When considered in this way, the power of "scientific" truth claims to explain and justify a certain level of violence, aggression, and behaviors coded as masculine, comes to the fore

Cytogerontology since 1881: A reappraisal of August Weismann and a review of modern progress

Cytogerontology, the science of cellular ageing, originated in 1881 with the prediction by August Weismann that the somatic cells of higher animals have limited division potential. Weismann's prediction was derived by considering the role of natural selection in regulating the duration of an organism's life. For various reasons, Weismann's ideas on ageing fell into neglect following his death in 1914, and cytogerontology has only reappeared as a major research area following the demonstration by Hayflick and Moorhead in the early 1960s that diploid human fibroblasts are restricted to a finite number of divisions in vitro. In this review we give a detailed account of Weismann's theory, and we reveal that his ideas were both more extensive in their scope and more pertinent to current research than is generally recognised. We also appraise the progress which has been made over the past hundred years in investigating the causes of ageing, with particular emphasis being given to (i) the evolution of ageing, and (ii) ageing at the cellular level. We critically assess the current state of knowledge in these areas and recommend a series of points as primary targets for future research