Using learning networks to understand complex systems: a case study of biological, geophysical and social research in the Amazon

Developing high-quality scientific research will be most effective if research communities with diverse skills and interests are able to share information and knowledge, are aware of the major challenges across disciplines, and can exploit economies of scale to provide robust answers and better inform policy. We evaluate opportunities and challenges facing the development of a more interactive research environment by developing an interdisciplinary synthesis of research on a single geographic region. We focus on the Amazon as it is of enormous regional and global environmental importance and faces a highly uncertain future. To take stock of existing knowledge and provide a framework for analysis we present a set of mini-reviews from fourteen different areas of research, encompassing taxonomy, biodiversity, biogeography, vegetation dynamics, landscape ecology, earth-atmosphere interactions, ecosystem processes, fire, deforestation dynamics, hydrology, hunting, conservation planning, livelihoods, and payments for ecosystem services. Each review highlights the current state of knowledge and identifies research priorities, including major challenges and opportunities. We show that while substantial progress is being made across many areas of scientific research, our understanding of specific issues is often dependent on knowledge from other disciplines. Accelerating the acquisition of reliable and contextualized knowledge about the fate of complex pristine and modified ecosystems is partly dependent on our ability to exploit economies of scale in shared resources and technical expertise, recognise and make explicit interconnections and feedbacks among sub-disciplines, increase the temporal and spatial scale of existing studies, and improve the dissemination of scientific findings to policy makers and society at large. Enhancing interaction among research efforts is vital if we are to make the most of limited funds and overcome the challenges posed by addressing large-scale interdisciplinary questions. Bringing together a diverse scientific community with a single geographic focus can help increase awareness of research questions both within and among disciplines, and reveal the opportunities that may exist for advancing acquisition of reliable knowledge. This approach could be useful for a variety of globally important scientific questions.

Architecture, sedentism, and social complexity at Pre-Pottery Neolithic A WF16, Southern Jordan

Recent excavations at Pre-Pottery Neolithic A (PPNA) WF16 in southern Jordan have revealed remarkable evidence of architectural developments in the early Neolithic. This sheds light on both special purpose structures and “domestic” settlement, allowing fresh insights into the development of increasingly sedentary communities and the social systems they supported. The development of sedentary communities is a central part of the Neolithic process in Southwest Asia. Architecture and ideas of homes and households have been important to the debate, although there has also been considerable discussion on the role of communal buildings and the organization of early sedentarizing communities since the discovery of the tower at Jericho. Recently, the focus has been on either northern Levantine PPNA sites, such as Jerf el Ahmar, or the emergence of ritual buildings in the Pre-Pottery Neolithic B of the southern Levant. Much of the debate revolves around a division between what is interpreted as domestic space, contrasted with “special purpose” buildings. Our recent evidence allows a fresh examination of the nature of early Neolithic communities.

Communication and social regulation. the criminalization of work-related death

This paper addresses the movement towards criminalization as a tool for the regulation of work-related deaths in the United Kingdom and elsewhere in the last 20 years. This can be seen as reflecting dissatisfaction with the relevant law, although it is best understood in symbolic terms as a response to a disjunction between the instrumental nature and communicative aspirations of regulatory law. This paper uses empirical data gathered from interviews with members of the public to explore the role that such an offence might play. The findings demonstrate that the failures of regulatory law give rise to a desire for criminalization as a means of framing work-related safety events in normative terms.

Bayesian parameter estimation for latent Markov random fields and social networks

Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an intractable normalising constant. This problem has received much attention, but very little of this has focussed on the important practical case where the data consists of noisy or incomplete observations of the underlying hidden structure. This paper specifically addresses this problem, comparing two alternative methodologies. In the first of these approaches particle Markov chain Monte Carlo (Andrieu et al., 2010) is used to efficiently explore the parameter space, combined with the exchange algorithm (Murray et al., 2006) for avoiding the calculation of the intractable normalising constant (a proof showing that this combination targets the correct distribution in found in a supplementary appendix online). This approach is compared with approximate Bayesian computation (Pritchard et al., 1999). Applications to estimating the parameters of Ising models and exponential random graphs from noisy data are presented. Each algorithm used in the paper targets an approximation to the true posterior due to the use of MCMC to simulate from the latent graphical model, in lieu of being able to do this exactly in general. The supplementary appendix also describes the nature of the resulting approximation.

Continuity of care for people with psychotic illness: its relationship to clinical and social functioning.

Background: The relationship between continuity of care and user characteristics or outcomes has rarely been explored. The ECHO study operationalized and tested a multi-axial definition of continuity of care, producing a seven-factor model used here. Aims: To assess the relationship between user characteristics and established components of continuity of care, and the impact of continuity on clinical and social functioning. Methods: The sample comprised 180 community mental health team users with psychotic disorders who were interviewed at three annual time-points, to assess their experiences of continuity of care and clinical and social functioning. Scores on seven continuity factors were tested for association with user-level variables. Results: Improvement in quality of life was associated with better Experience & Relationship continuity scores (better user-rated continuity and therapeutic relationship) and with lower Meeting Needs continuity factor scores. Higher Meeting Needs scores were associated with a decrease in symptoms. Conclusion: Continuity is a dynamic process, influenced significantly by care structures and organizational change.

Robust abandoned object detection integrating wide area visual surveillance and social context

This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner).

Consumption and social identity: evidence from India

We examine spending on consumption items which have signaling value in social interactions across groups with distinctive social identities in India, where social identities are defined by caste and religious affiliations. Using nationally representative micro data on household consumption expenditures, we find that disadvantaged caste groups such as Other Backward Castes spend 8 percent more on visible consumption than Brahmin and High Caste groups while social groups such as Muslims spend 14 percent less, after controlling for differences in permanent income, household assets and household demographic composition. The differences across social groups are significant and robust and these differences persist within different sub populations. We find that the higher spending of OBC households on visible consumption is diverted from education spending, while Muslim households divert spending from visible consumption and education towards greater food spending. Additionally, we find that these consumption patterns can be partly explained as a result of the status signaling nature of the consumption items. We also discuss alternative sources of differences in consumption patterns across groups which stem from religious observance.