An investigation of the correlations between years of service in pastoral work and the scores of the Minnesota Multiphasic personality inventory

In the August Twentieth issue of Life Magazine an article appeared entitled, “Why Ministers Are Breaking Down.”1 Three months later, the Christian Century answered this article in Life with “Are Ministers Cracking Up?”2 The conclusions of these two articles were in disagreement. However, they were alike in that they were based upon personal observations of a few cases and not upon careful study. Since then other periodicals have carried like articles written in like style.3 A casual examination of the books on a minister’s personal problems in the library of any theological seminary will manifest the same general trend of enumerating and evaluating the problems upon the basis of personal experience and general observations with no attempt to test the material scientifically

Detecting Fire and Grazing Patterns in Tallgrass Prairie Using Spectral Mixture Analysis

Global grasslands are typically under management practices (such as fire and grazing) that alter nutrient cycling, ecosystem composition, and distribution of organic matter from the unmanaged condition. We evaluated landscape-level response to fire and grazing treatments in the Konza Tallgrass Prairie Research Natural Area, Kansas, using spectral mixture analysis of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired 31 August 1990. Spectral mixture analysis derives the fractional abundances of spectrally unique components in the landscape. The reflectance spectra of these components are called endmembers. Endmember fractions values were compared against ground values of live biomass, current standing dead biomass, and litter for 12 watersheds. Analysis of variance (ANOVA) was performed on 37 watersheds with known burning and grazing histories for each of the remote sensing variables. Seven endmembers were selected from the AVIRIS data using a manual endmember selection method: nonphotosynthetic vegetation (NPV), soil, rock, shade, and three green vegetation endmembers (GV1, GV2, and GV3). Each vegetation endmember correlated differently to biomass measurements and revealed unique relationships to management treatments. From regressions, ANOVAs, and image analysis, these three endmembers were inferred to represent canopy vertical structure or leaf area index (LAI), greenness, and fractional cover of grass, respectively. There was a stronger relationship between the sum of GV1 and GV3 fractions and live grass biomass values than there was with the (unsummed) individual fractions. In an ANOVA, the sum separated both burn and grazing treatments as well as the treatment interaction. The NPV fraction was strongly correlated with ground measurements of litter and standing dead biomass, and significantly separated burn treatments. The soil fraction differentiated grazing treatments, and analysis of the soil fraction image revealed a spatial coherence of grazing patterns along drainages. Similar analyses were perfomed on the Normalized Difference Vegetation Index (NDVI), a commonly used two-band index computed from red and near-infrared reflectance. NDVI, shown in previous studies to estimate the fraction of photosynthetically active radiation absorbed by green vegetation (FPAR), was a poor indicator of canopy biomass, but it successfully separated fire treatments. Broad-scale assessment of the state and structure of managed grassland systems requires the identification of several indicator variables. Spectral mixture analysis, unlike NDVI, not only separated treatments but also allowed for the identification of five remotely sensible factors affected by the management treatments, namely, vertical structure, percentage cover or patchiness, greenness, and distribution of soil and litter

A comparison of spectral mixture analysis an NDVI for ascertaining ecological variables

In this study, we compare the performance of spectral mixture analysis to the Normalized Difference Vegetation Index (NDVI) in detecting change in a grassland across topographically-induced nutrient gradients and different management schemes. The Konza Prairie Research Natural Area, Kansas, is a relatively homogeneous tallgrass prairie in which change in vegetation productivity occurs with respect to topographic positions in each watershed. The area is the site of long-term studies of the influence of fire and grazing on tallgrass production and was the site of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) from 1987 to 1989. Vegetation indices such as NDVI are commonly used with imagery collected in few (less than 10) spectral bands. However, the use of only two bands (e.g. NDVI) does not adequately account for the complex of signals making up most surface reflectance. Influences from background spectral variation and spatial heterogeneity may confound the direct relationship with biological or biophysical variables. High dimensional multispectral data allows for the application position of techniques such as derivative analysis and spectral curve fitting, thereby increasing the probability of successfully modeling the reflectance from mixed surfaces. The higher number of bands permits unmixing of a greater number of surface components, separating the vegetation signal for further analyses relevant to biological variables

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings

Componentes menores y estabilidad a la oxidación mediante DSC de aceite de colza fraccionado y estructurado mediante catálisis con lipasa

Natural fats and oils can be modified by various methods to prepare products with desired physical, chemical and nutritional properties. The enrichment and retention of the minor lipid components, the incorporation of capric acid and oxidative stability in low temperature fractionated rapeseed oil (RSO) in acetone were assessed in this study. The fractionated liquid part (L-RSO), the solid part (S-RSO) and the RSO were transesterified with capric acid (CA) at different mole ratios using lipase. The yields of L-RSO and S-RSO were 30 and 70 g per 100 g, respectively. The L-RSO contained higher levels of linoleic acid and linolenic acid, and a lower level of oleic acid compared to the S-RSO. The S-RSO contained a higher amount of total sterols than the RSO and the L-RSO. In contrast, the L-RSO contained a higher amount of total tocopherols than the RSO and the S-RSO. The incorporation of CA was ideal at a mole ratio of 1:3. The content of sterols and tocopherols gradually decreased with an increased mole ratio for the CA incorporation. The oxidative stability shown as onset temperature, determined by DSC, of the S-RSO was higher compared to those of the L-RSO and RSO.Las grasas y aceites naturales pueden ser modificados mediante diversos métodos para preparar productos con propiedades físicas, químicas y nutricionales deseadas. El enriquecimiento y la retención de componentes lipídicos menores, la incorporación de ácido cáprico y estabilidad a la oxidación a baja temperatura de aceites de colza (RSO) fraccionado en acetona, se evaluaron en este estudio. La fracción líquida (L-RSO), la fracción sólida (S-RSO) y el RSO son transesterificados con ácido cáprico (CA) en diversas relaciones molares utilizando lipasa. Los rendimientos de las fracciones L-RSO y RSO-S fueron de 30 y 70 g por 100 g, respectivamente. La fracción líquida L-RSO contenía un mayor nivel de los ácidos linoleico y linolénico, y un menor nivel de ácido oleico en comparación con la fracción sólida S-RSO. La fracción sólida S-RSO tiene mayor contenido total de esteroles que RSO y que L-RSO. En contraste, la fracción L-RSO contenía mayor contenido de tocoferoles totales que RSO y que S-RSO. La incorporación de CA fue excelente con una relación molar de 1:3. El contenido de esteroles y tocoferoles disminuyó gradualmente con un incremento de la relación molar de la incorporación de CA. La estabilidad oxidativa muestra cómo la temperatura de inicio, determinada mediante DSC, de la fracción S-RSO fue mayor en comparación con la de la L-RSO y RSO

Workforce Projections 2010-2020: Annual Supply and Demand Forecasting Models for Physical Therapists Across the United States

BACKGROUND: Health human resources continue to emerge as a critical health policy issue across the United States. OBJECTIVE: The purpose of this study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the United States into 2020. DESIGN: A traditional stock-and-flow methodology or model was developed and populated with publicly available data to produce estimates of supply and demand for physical therapists by 2020. METHODS: Supply was determined by adding the estimated number of physical therapists and the approximation of new graduates to the number of physical therapists who immigrated, minus US graduates who never passed the licensure examination, and an estimated attrition rate in any given year. Demand was determined by using projected US population with health care insurance multiplied by a demand ratio in any given year. The difference between projected supply and demand represented a shortage or surplus of physical therapists. RESULTS: Three separate projection models were developed based on best available data in the years 2011, 2012, and 2013, respectively. Based on these projections, demand for physical therapists in the United States outstrips supply under most assumptions. LIMITATIONS: Workforce projection methodology research is based on assumptions using imperfect data; therefore, the results must be interpreted in terms of overall trends rather than as precise actuarial data-generated absolute numbers from specified forecasting. CONCLUSIONS: Outcomes of this projection study provide a foundation for discussion and debate regarding the most effective and efficient ways to influence supply-side variables so as to position physical therapists to meet current and future population demand. Attrition rates or permanent exits out of the profession can have important supply-side effects and appear to have an effect on predicting future shortage or surplus of physical therapists

Free energy barrier for melittin reorientation from a membrane-bound state to a transmembrane state

An important step in a phospholipid membrane pore formation by melittin antimicrobial peptide is a reorientation of the peptide from a surface into a transmembrane conformation. In this work we perform umbrella sampling simulations to calculate the potential of mean force (PMF) for the reorientation of melittin from a surface-bound state to a transmembrane state and provide a molecular level insight into understanding peptide and lipid properties that influence the existence of the free energy barrier. The PMFs were calculated for a peptide to lipid (P/L) ratio of 1/128 and 4/128. We observe that the free energy barrier is reduced when the P/L ratio increased. In addition, we study the cooperative effect; specifically we investigate if the barrier is smaller for a second melittin reorientation, given that another neighboring melittin was already in the transmembrane state. We observe that indeed the barrier of the PMF curve is reduced in this case, thus confirming the presence of a cooperative effect

Evaluating drug targets through human loss-of-function genetic variation

Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous 'knockout' humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development.Peer reviewe

The mutational constraint spectrum quantified from variation in 141,456 humans

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes(1). Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.Peer reviewe