The Determinants of Participation in Land Use-Related Education and Training: A Case Study of the State of Michigan

In recent years, numerous policy makers and educators in Michigan have advocated increasing participation of land use planning officials in land use-related education and training. The Michigan Land Use Leadership Council, commissioned by Governor Granholm, recommended that 60% of planning and zoning officials complete basic land use planning, zoning, and smart growth educational programs by 2010. However, while demographic information has been gathered on planning officials, little empirical research has been conducted on the determinants of participating in land use education and training. This paper uses regression analysis to estimate and interpret a demand function for participation in land use-related education and training. Results indicate willingness to participate in land use-related training is a function of education, perceived benefit, and length in service. These findings have important programmatic and policy implications. Training programs should be geared towards those planning officials who are beginning to serve. Educators should focus on promoting and educating communities and planning officials on the potential benefits of land use-related training.Land Economics/Use, Teaching/Communication/Extension/Profession,

Forms and Functions of Participatory Evaluation in International Development: A Review of the Empirical and Theoretical Literature

Background: Since the late 1970s participatory approaches have been widely promoted to evaluate international development programs. However, there is no universal agreement of what is meant by participatory evaluation.  For some evaluators, participatory evaluations involve the extensive participation of all stakeholder groups (from donor to non-recipients) in every phase of the evaluation (from design to dissemination). For others, the participation of donors in the design constitutes a participatory evaluation approach. Participatory evaluation approaches are best considered on a continuum. In other words, there are many gradations to participation and evaluations should be classified accordingly.  Purpose: The lack of shared meaning of participatory evaluation approaches also impedes serious discussion on their use including their merits and demerits, suggestions for their improvement, and their overall effectiveness. The purpose of this article is to present an examination of the literature on participatory evaluation approaches to highlight commonalities and differences. Setting: Not applicable Intervention: Not applicable. Research Design: Not applicable. Data Collection and Analysis: Desk review. Findings: This article clearly demonstrates how broadly participatory evaluation is conceptualized and practiced and underscores the clear need for specification and precision when discussing what is meant by participatory evaluation. Recommendations for how evaluators should describe participatory evaluations are provided. Keywords: participatory evaluation; collaborative evaluation; empowerment evaluation; stakeholder-based evaluatio

Wearable GPS and Accelerometer Technologies for Monitoring Mobility and Physical Activity in Neurodegenerative Disorders:A Systematic Review

Neurodegenerative disorders (NDDs) constitute an increasing global burden and can significantly impair an individual’s mobility, physical activity (PA), and independence. Remote monitoring has been difficult without relying on diaries/questionnaires which are more challenging for people with dementia to complete. Wearable global positioning system (GPS) sensors and accelerometers present a cost-effective and noninvasive way to passively monitor mobility and PA. In addition, changes in sensor-derived outcomes (such as walking behaviour, sedentary, and active activity) may serve as potential biomarkers of disease onset, progression, and response to treatment. We performed a systematic search across four databases to identify papers published within the past 5 years, in which wearable GPS or accelerometers were used to monitor mobility or PA in patients with common NDDs (Parkinson’s disease, Alzheimer’s disease, motor neuron diseases/amyotrophic lateral sclerosis, vascular parkinsonism, and vascular dementia). Disease and technology-specific vocabulary were searched singly, and then in combination, identifying 4985 papers. Following deduplication, we screened 3115 papers and retained 28 studies following a full text review. One study used wearable GPS and accelerometers, while 27 studies used solely accelerometers in NDDs. GPS-derived measures had been validated against current gold standard measures in one Parkinson’s cohort, suggesting that the technology may be applicable to other NDDs. In contrast, accelerometers are widely utilised in NDDs and have been operationalised in well-designed clinical trials

Retinoic acid degradation shapes zonal development of vestibular organs and sensitivity to transient linear accelerations

Each vestibular sensory epithelium in the inner ear is divided morphologically and physio- logically into two zones, called the striola and extrastriola in otolith organ maculae, and the central and peripheral zones in semicircular canal cristae. We found that formation of striolar/central zones during embryogenesis requires Cytochrome P450 26b1 (Cyp26b1)- mediated degradation of retinoic acid (RA). In Cyp26b1 conditional knockout mice, formation of striolar/central zones is compromised, such that they resemble extrastriolar/peripheral zones in multiple features. Mutants have deficient vestibular evoked potential (VsEP) responses to jerk stimuli, head tremor and deficits in balance beam tests that are consistent with abnormal vestibular input, but normal vestibulo-ocular reflexes and apparently normal motor performance during swimming. Thus, degradation of RA during embryogenesis is required for formation of highly specialized regions of the vestibular sensory epithelia with specific functions in detecting head motions

Molecular Longitudinal Tracking of Mycobacterium abscessus spp. during Chronic Infection of the Human Lung

<div><p>The <i>Mycobacterium abscessus</i> complex is an emerging cause of chronic pulmonary infection in patients with underlying lung disease. The <i>M. abscessus</i> complex is regarded as an environmental pathogen but its molecular adaptation to the human lung during long-term infection is poorly understood. Here we carried out a longitudinal molecular epidemiological analysis of 178 <i>M. abscessus</i> spp. isolates obtained from 10 cystic fibrosis (CF) and 2 non CF patients over a 13 year period. Multi-locus sequence and molecular typing analysis revealed that 11 of 12 patients were persistently colonized with the same genotype during the course of the infection while replacement of a <i>M. abscessus sensu stricto</i> strain with a <i>Mycobacterium massiliense</i> strain was observed for a single patient. Of note, several patients including a pair of siblings were colonized with closely-related strains consistent with intra-familial transmission or a common infection reservoir. In general, a switch from smooth to rough colony morphology was observed during the course of long-term infection, which in some cases correlated with an increasing severity of clinical symptoms. To examine evolution during long-term infection of the CF lung we compared the genome sequences of 6 sequential isolates of <i>Mycobacterium bolletii</i> obtained from a single patient over an 11 year period, revealing a heterogeneous clonal infecting population with mutations in regulators controlling the expression of virulence factors and complex lipids. Taken together, these data provide new insights into the epidemiology of <i>M. abscessus</i> spp. during long-term infection of the CF lung, and the molecular transition from saprophytic organism to human pathogen.</p></div

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

A physical supply-use table framework for energy analysis on the energy conversion chain

In response to the oil crises of the 1970s, energy accounting experienced a revolution and became the much broader field of energy analysis, in part by expanding along the energy conversion chain from primary and final energy to useful energy and energy services, which satisfy human needs. After evolution and specialization, the field of energy analysis today addresses topics along the entire energy conversion chain, including energy conversion systems, energy resources, carbon emissions, and the role of energy services in promoting human well-being and development. And the expanded field would benefit from a common analysis framework that provides data structure uniformity and methodological consistency. Building upon recent advances in related fields, we propose a physical supply-use table energy analysis framework consisting of four matrices from which the input-output structure of an energy conversion chain can be determined and the effects of changes in final demand can be estimated. Real-world examples demonstrate the physical supply-use table framework via investigation of energy analysis questions for a United Kingdom energy conversion chain. The physical supply use table framework has two key methodological advances over the building blocks that precede it, namely extending a common energy analysis framework through to energy services and application of physical supply-use tables to both energy and exergy analysis. The methodological advances enable the following first-time contributions to the literature: (1) performing energy and exergy analyses on an energy conversion chain using physical supply-use table matrices comprised of disaggregated products in physical units when the last stage is any of final energy, useful energy, or energy services; (2) performing structural path analysis on an energy conversion chain; and (3) developing and utilizing a matrix approach to inhomogeneous units. The framework spans the entire energy conversion chain and is suitable for many sub-fields of energy analysis, including net energy analysis, societal energy analysis, human needs and well-being, and structural path analysis, all of which are explored in this paper

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Inferring the role of transcription factors in regulatory networks

<p>Abstract</p> <p>Background</p> <p>Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays.</p> <p>Results</p> <p>We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of <it>E. coli </it>extracted from the literature (1529 nodes and 3802 edges), and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to <it>S. cerevisiae </it>transcriptional network (2419 nodes and 4344 interactions), by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions). In addition, we report predictions for 14.5% of all interactions.</p> <p>Conclusion</p> <p>Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine a significant portion of regulatory effects. This is a key practical asset compared to statistical methods for network reconstruction. We demonstrate that our approach is able to provide accurate predictions, even when the network is incomplete and the data is noisy.</p