A hegemonic neoliberal ideology dominates all areas of work in Turkey, including healthcare. Though neoliberalism has been studied extensively from the perspective of meaning, values, and processes, managerial and leadership behavior dynamics require further research. This study analyzes the relationship between managerialism, toxic leadership, and ethical climate in an industry swept up by untamed neoliberalism, particularly in a nation where employment and human rights are ceremoniously protected. Through an analysis of medical doctors working in 207 public and private university hospitals in Turkey, we explored the role of managerialism and four distinct ethical climate types, resulting in the emergence of toxic leadership behaviors during the global pandemic. We theorize the extent to which toxic leaders emerge from managerialism. We further explain why the hegemonic Turkish leadership culture thrives in toxic behaviors such as paternalism, fealty, ingratiation, nepotism, and cronyism in the context of neoliberal expansion.

The long, continuous deposition of dust in the Chinese loess plateau offers a unique opportunity to study the nature of Fe oxide formation in a wide range of climatic conditions. A technique to obtain quantitative estimates of the concentration of hematite and goethite in loess and paleosol samples is reported. Experiments using diffuse reflectance spectroscopy on sets of laboratory mixed and natural loess and paleosol samples show that it is possible to obtain rapid and quantitative estimates of the absolute concentration of hematite and goethite in the Chinese loess sediments. Typical loess and paleosol samples were deferrated using the CBD procedure to produce a natural matrix material to which hematite and goethite in known weight percentages were added to produce a set of calibration standards. Spectral violet, blue, green, yellow, orange, red and brightness of standards were calculated from the reflectance data and served as independent variables for a multiple linear regression analysis. The effect of changing matrix from loess to paleosol was overcome by including a variety of different loess and paleosol samples in the regression equations. The resulting calibration equations provide estimates of wt.% hematite and goethite and have correlation coefficients >0.93. The total measured hematite and goethite concentrations exhibited consistent variations with CBD extractable iron. Tests of the equations for buffering changes in matrix composition were run with samples of varying mineralogical composition (calcite, illite, etc.) and demonstrated that the equations are well buffered for changes in matrix composition from loess to paleosol.

Many judgment analysis studies employ multiple regression procedures to estimate the importance of cues. Some studies test the significance of regression coefficients in order to decide whether or not specific cues are attended to by the judge or decision maker. This practice is dubious because it ignores type II error. The purposes of this note are (1) to draw attention to this issue, specifically as it appears in studies of self-insight, (2) to illustrate the problem with examples from the judgment literature, and (3) to provide a simple method for calculating post-hoc power in regression analyses in order to facilitate the reporting of type II errors when regression models are used.

The objective was to establish a multivariate model using two complementary multivariate statistical techniques, factor analysis and multiple stepwise regression to predict carcase characteristics, carcase cuts, internal fat, viscera and loin eye area from body measurements of goats Boer mestizos. Thirty-two goats were used, with initial average weights of 3.3 ± 0.61 kg and final average weights of 16 ± 2.5 kg. Before slaughter and after 16 h of fasting, body weight was measured along with the biometric measurements (BMs) of each animal: body length, withers height, croup height, chest width, croup width, croup perimeter, thoracic perimeter, leg length and thigh circumference. The half carcases were sectioned in six anatomical regions that made up the commercial cuts: neck, palette, rib, handsaw, loin and ham. BMs showed a high correlation with a few exceptions; most of the correlations are above 50%. What also happens with the Carcass weight and cuts were also correlated above 50% with BMs. The data presented an index for the Kaiser–Meyer–Olkin test of 0.80, demonstrating the adequacy of the factor analysis. Through factor analysis, it was possible to observe that the first two factors extracted accumulated 75.47% of the total variance of the studied characteristics. Moderate to high and positive correlations of morphological characteristics with body weight, carcase characteristics and primary carcase cuts suggested the adequacy of morphological characteristics as criteria for early selection of crossbred Boer goats for their body weight and carcase characteristics without slaughter.

We use attribution theory to show that firms that make more internal attributions to positive performance outcomes engage slack resources more freely for corporate entrepreneurship (CE) than firms that make fewer of such attributions. In addition, we show that the way in which companies make external attributions to performance outcomes moderates this relationship. To examine this empirically, we explore how top management teams discuss the factors that contribute to firm performance. Specifically, we look at attributions provided in the Management's Discussion and Analysis section of the annual reports of 144 pharmaceutical firms over a 2-year period. In line with our predictions, we find that greater internal attribution to positive performance outcomes leads to increased use of slack resources for CE. Furthermore, we find that this effect is stronger when firms make more external attributions to negative performance outcomes than positive performance outcomes.

The yield potential and the effect on yield loss of canola of different densities of volunteer barley were investigated at three locations in western Canada. Field studies were conducted from 1982 to 1986. Rectangular hyperbolic models based on data pooled over years, locations, and canola cultivars, and incorporating different densities of volunteer barley and canola accurately portrayed field responses in most instances. Results indicated that volunteer barley severely reduced canola yield. However, financial losses due to reduced canola yield were partly offset by the volunteer barley crop.

The competitive ability of annual round-leaved mallow was determined in spring wheat and lentil at Indian Head and Regina, Saskatchewan, in 1985 and 1986 using paired quadrats. Significant biomass and seed yield loss occurred in three of four tests in lentil and two of three tests in spring wheat. Differences in numbers of wheat tillers produced between weedy and weed-free plots were found in three of four tests. A two-variable model comprised of early season crop density loss and round-leaved mallow biomass best accounted for the majority of variation in crop yield loss for both lentil and wheat, and tiller density loss in wheat. In 1985 at Indian Head, where no yield loss occurred for either wheat or lentil, round-leaved mallow had been seeded immediately before the crop. Greater yield losses occurred at Regina, in the presence of an older, well-established infestation. In the years and locations with the greatest crop yield losses, round-leaved mallow emerged before the crop causing poor crop emergence. At Regina in 1986, crop yield losses were more than 60% in wheat and 90 to 100% in lentil because of large differences in crop density between weed-free and weedy subplots. Round-leaved mallow exhibited great variability in growth, producing more biomass per plant, more capsules per plant, and more capsules per gram of biomass in the less competitive crop, lentil, than in wheat. Density and biomass of round-leaved mallow were not correlated; with a density of 200 plants m−2, round-leaved mallow biomass in wheat ranged from 100 to 500 g m−2; while in lentil, from 200 to as high as 1000 g m−2, approximately double the range found in wheat. The type of round-leaved mallow infestation (newly seeded or well-established) and environmental conditions (mainly early season precipitation) account for differences between sites and between years.

Knowledge of the influence of environmental factors on weed populations is important in developing sustainable turfgrass management practices. Studies were conducted to evaluate the relationship of green and false-green kyllinga population densities with elevation and edaphic factors in turfgrass systems. Studies were conducted on five different golf courses in North Carolina, three affected by green kyllinga, and two affected by false-green kyllinga. According to Spearman correlation coefficients, both green and false-green kyllinga were correlated with increasing soil volumetric water content, whereas correlation of other edaphic variables varied among sites and species. Stepwise logistic regression confirmed the correlation of volumetric water with green kyllinga presence, but model components varied among sites for false-green kyllinga. Increasing green kyllinga populations correlated with increasing soil sodium; however, sodium did not reach a level believed to be detrimental to turfgrass growth. No other variables correlated with green or false-green kyllinga across all sites. We hypothesized that the lack of significant correlations was due to the overall influence of relative elevation on edaphic variables. According to principal components analysis (PCA), relative elevation had a profound impact on the measured edaphic variables at all sites. However, results of PCA at one site differed sharply from other sites. Results from that site demonstrate the potentially strong effects of management practices to alter edaphic trends normally observed with topography.

Image pre-processing is highly significant in automated analysis of microscopy images. In this work, non-uniform illumination correction has been attempted using the surface fitting method (SFM), multiple regression method (MRM), and bidirectional empirical mode decomposition (BEMD) in digital microscopy images of tuberculosis (TB). The sputum smear positive and negative images recorded under a standard image acquisition protocol were subjected to illumination correction techniques and evaluated by error and statistical measures. Results show that SFM performs more efficiently than MRM or BEMD. The SFM produced sharp images of TB bacilli with better contrast. To further validate the results, multifractal analysis was performed that showed distinct variation before and after implementation of illumination correction by SFM. Results demonstrate that after illumination correction, there is a 26% increase in the number of bacilli, which aids in classification of the TB images into positive and negative, as TB positivity depends on the count of bacilli.

The augmented multiple regression model for the analysis of data from selected twin pairs was extended to facilitate analyses of data from twin pairs and nontwin siblings. Fitting this extended model to data from both selected twin pairs and siblings yields direct estimates of heritability (h2) and the difference between environmental influences shared by members of twin pairs and those of sib or twin–sib pairs (i.e., c2(t) – c2 (s)). When this model was fitted to reading performance data from 293 monozygotic and 436 dizygotic pairs selected for reading difficulties, and 291 of their nontwin siblings, h2 = .48 ± .22, p = .03, and c2 (t) – c2 (s) = .22 ± .12, p = .06. Although the test for differential shared environmental influences is only marginally significant, the results of this analysis suggest that environmental influences on reading performance that are shared by members of twin pairs (.36) may be substantially greater than those for less contemporaneous twin–sibling pairs (.14).

The spatial pattern of lichen species richness was analyzed in a forest ecosystem impacted for 50 years by industrial emissions from a steelworks. Geostatistical tools were used to characterize the spatial pattern of the number of lichen species and multiple regression analysis was used to identify factors influencing it. Spatial analysis showed high variation of lichen species richness on a local scale, caused by patchiness of natural habitat factors (species composition of trees, their age, shade, etc.). On a large spatial scale, species richness differentiated the western from the eastern part of the forest. The western part, closer to the sources of pollution, had fewer species (average 6–10 per locality) than the eastern part (10–15 per locality). Multiple regression analysis was used to examine the relationships between the species richness of lichens and several environmental variables: input of ions with bulk precipitation (SO42−, NO−3, Cl−, Ca2+, Mg2+, Fe3+, Zn3+, Pb2+, Cd2+), distance to forest edge, tree stand age, and number of species per locality. Regression analysis was preceded by factor analysis for the input of ions to obtain uncorrelated variables. Regression explained 53% of the variation of lichen species richness. Highly significant predictor variables were the factor connected with the input of pollutants (Fe3+, Zn2+) emitted by the steelworks (negative effect) and the number of trees per locality (positive effect). Species richness was also affected by the age structure of the tree stand; more species were recorded in old forests.