The Maternal Personhood of Cattle and Plants at a Hindu Center in the United States

Religious experiences with sacred nonhuman natural beings considered to be “persons” remain only vaguely understood. This essay provides a measure of clarification by engendering a dialogue between psychoanalytic self psychology on one side and, on the other, religious experiences of cattle and Tulsi plants as holy mothers at a Hindu cattle sanctuary in the United States. Ethnographic data from the Hindu center uncover experiences of sacred maternal natural beings that are tensive, liminal, and colored with affective themes of nurturance, respect, and intimacy, much like psychoanalytic maternal selfobjects. Devotees protect cattle and ritually venerate plants because these actions facilitate a limited experiential grounding of religiosity on what is perhaps the most fundamental of all relationships, the relationship with the mother, within a theological worldview that somewhat embraces nonhuman natural beings in both doctrine and practice

Estimates of live-tree carbon stores in the Pacific Northwest are sensitive to model selection

<p>Abstract</p> <p>Background</p> <p>Estimates of live-tree carbon stores are influenced by numerous uncertainties. One of them is model-selection uncertainty: one has to choose among multiple empirical equations and conversion factors that can be plausibly justified as locally applicable to calculate the carbon store from inventory measurements such as tree height and diameter at breast height (DBH). Here we quantify the model-selection uncertainty for the five most numerous tree species in six counties of northwest Oregon, USA.</p> <p>Results</p> <p>The results of our study demonstrate that model-selection error may introduce 20 to 40% uncertainty into a live-tree carbon estimate, possibly making this form of error the largest source of uncertainty in estimation of live-tree carbon stores. The effect of model selection could be even greater if models are applied beyond the height and DBH ranges for which they were developed.</p> <p>Conclusions</p> <p>Model-selection uncertainty is potentially large enough that it could limit the ability to track forest carbon with the precision and accuracy required by carbon accounting protocols. Without local validation based on detailed measurements of usually destructively sampled trees, it is very difficult to choose the best model when there are several available. Our analysis suggests that considering tree form in equation selection may better match trees to existing equations and that substantial gaps exist, in terms of both species and diameter ranges, that are ripe for new model-building effort.</p

Empirical Investigation of Radiologists' Priorities for PACS Selection: An Analytical Hierarchy Process Approach

Picture archiving and communication systems (PACS) are being widely adopted in radiology practice. The objective of this study was to find radiologists' perspective on the relative importance of the required features when selecting or developing a PACS. Important features for PACS were identified based on the literature and consultation/interviews with radiologists. These features were categorized and organized into a logical hierarchy consisting of the main dimensions and sub-dimensions. An online survey was conducted to obtain data from 58 radiologists about their relative preferences. Analytical hierarchy process methodology was used to determine the relative priority weights for different dimensions along with the consistency of responses. System continuity and functionality was found to be the most important dimension, followed by system performance and architecture, user interface for workflow management, user interface for image manipulation, and display quality. Among the sub-dimensions, the top two features were: security, backup, and downtime prevention; and voice recognition, transcription, and reporting. Structured reporting was also given very high priority. The results point to the dimensions that can be critical discriminators between different PACS and highlight the importance of faster integration of the emerging developments in radiology into PACS.close2

Animal-assisted intervention for autism spectrum disorder: a systematic literature review

The inclusion of animals in therapeutic activities, known as animal-assisted intervention (AAI), has been suggested as a treatment practice for autism spectrum disorder (ASD). This paper presents a systematic review of the empirical research on AAI for ASD. Fourteen studies published in peer-reviewed journals qualified for inclusion. The presentation of AAI was highly variable across the studies. Reported outcomes included improvements for multiple areas of functioning known to be impaired in ASD, namely increased social interaction and communication as well as decreased problem behaviors, autistic severity, and stress. Yet despite unanimously positive outcomes, most studies were limited by many methodological weaknesses. This review demonstrates that there is preliminary "proof of concept" of AAI for ASD and highlights the need for further, more rigorous research

The effectiveness of service delivery initiatives at improving patients' waiting times in clinical radiology departments: a systematic review.

We reviewed the literature for the impact of service delivery initiatives (SDIs) on patients' waiting times within radiology departments. We searched MEDLINE, EMBASE, CINAHL, INSPEC and The Cochrane Library for relevant articles published between 1995 and February, 2013. The Cochrane EPOC risk of bias tool was used to assess the risk of bias on studies that met specified design criteria. Fifty-seven studies met the inclusion criteria. The types of SDI implemented included extended scope practice (ESP, three studies), quality management (12 studies), productivity-enhancing technologies (PETs, 29 studies), multiple interventions (11 studies), outsourcing and pay-for-performance (one study each). The uncontrolled pre- and post-intervention and the post-intervention designs were used in 54 (95%) of the studies. The reporting quality was poor: many of the studies did not test and/or report the statistical significance of their results. The studies were highly heterogeneous, therefore meta-analysis was inappropriate. The following type of SDIs showed promising results: extended scope practice; quality management methodologies including Six Sigma, Lean methodology, and continuous quality improvement; productivity-enhancing technologies including speech recognition reporting, teleradiology and computerised physician order entry systems. We have suggested improved study design and the mapping of the definitions of patient waiting times in radiology to generic timelines as a starting point for moving towards a situation where it becomes less restrictive to compare and/or pool the results of future studies in a meta-analysis