Metafysiske tegn. Skønlitteratur som religionsvidenskabeligt objekt

Analysing The Black Book, a novel by the contemporary Turkish writer Orhan Pamuk, this paper suggests that fiction can serve as an illuminating source in understanding one of the many roles that religion can play for modern man. Pamuk´s literary perspective is aesthetic and he disagrees with an essentialistic way of understanding and defining personal or cultural identity and cultural phenomena. In the novel he tries to create and describe alternative ways of conceiving reality. First and foremost by writing a novel without a fixed centre, but with many layers of undetermined meaning and persons with unclear, changing identities. Considering reality as chaotic and heterogenous he wants to avoid the common, monolitic descriptions of ‘tradition’, ‘modernity’, ‘East’ and ‘West’ and at the same time reintroduce elements long forgotten in the Turkish culture. It is at this point that Islam – or rather parts of the Islamic tradition - becomes interesting to Pamuk, who uses themes, metaphors and narrative structures especially from the Sufi-literature. Not only do these components present parts of a forgotten, but very rich, part of the Turkish culture, but the Sufi vocabulary and pictures are also useful vehicles to express the fluid and immaterial way of perceiving cultural as well as personal identities

Extent and effects of microplastic pollution in soil with focus on recycling of sewage sludge and composted household waste and experiences from the long-term field experiment CRUCIAL

Microplastics (MP) occur in household waste products, which can be recycled as fertilizers in agricultural fields. Recycling of waste products has many benefits but concerns of the effects of MP on soil health limit recycling. MP are present in composted household waste and sewage sludge. Sewage sludge contains many small particles (primarily fibers and fragments), whereas compost mainly contains larger fragments (flakes from packaging and bags). Here, we review the extent and possible consequences of MP pollution in soil with focus on waste product recycling. We summarize the results from studies that have measured MP concentration in soil and waste products. We review the possible hazards of MP on soil invertebrates, plant growth and microbial communities based on published studies. We discuss these results in relation to MP quantities measured in agricultural fields and generally find that MP contents in fields are below the MP levels that cause negative effects in most current effects studies. Finally, we present results from the long-term field experiment CRUCIAL, which have received composted household waste and sewage sludge in dosages corresponding to more than 100 years of legal amendment. Experiments with earthworms and quantification of various soil organisms do not indicate that household waste and sewage sludge, including the inherent contaminants, affect soil health negatively. In fact, growth of earthworms and abundances of organisms were often higher in these treatments compared to NPK-fertilized or unfertilized plots, probable due to the content of organic matter in the waste product. Based on these assessments, we conclude that the potential risk of current levels of microplastics in terrestrial environments is low for agricultural soils, but more studies are needed to perform a robust risk assessment

The shortcomings of equal weights estimation and the composite equivalence index in PLS-SEM

Purpose The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM). Design/methodology/approach The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI. Findings The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM. Research limitations/implications In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison. Practical implications The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights. Originality/value To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators

Extraordinary Claims Require Extraordinary Evidence: A Comment on “Recent Developments in PLS”

Evermann and Rönkkö (2023) review recent developments in partial least squares (PLS) with the aim of providing guidance to researchers. Indeed, the explosion of methodological advances in PLS in the last decade necessitates such overview articles. In so far as the goal is to provide an objective assessment of the technique, such articles are most welcome. Unfortunately, the authors’ extraordinary and questionable claims paint a misleading picture of PLS. Our goal in this short commentary is to address selected claims made by Evermann and Rönkkö (2023) using simulations and the latest research. Our objective is to bring a positive perspective to this debate and highlight the recent developments in PLS that make it an increasingly valuable technique in IS and management research in general

Nitrous oxide production in sputum from cystic fibrosis patients with chronic Pseudomonas aeruginosa lung infection

Chronic lung infection by Pseudomonas aeruginosa is the major severe complication in cystic fibrosis (CF) patients, where P. aeruginosa persists and grows in biofilms in the endobronchial mucus under hypoxic conditions. Numerous polymorphonuclear leukocytes (PMNs) surround the biofilms and create local anoxia by consuming the majority of O2 for production of reactive oxygen species (ROS). We hypothesized that P. aeruginosa acquires energy for growth in anaerobic endobronchial mucus by denitrification, which can be demonstrated by production of nitrous oxide (N2O), an intermediate in the denitrification pathway. We measured N2O and O2 with electrochemical microsensors in 8 freshly expectorated sputum samples from 7 CF patients with chronic P. aeruginosa infection. The concentrations of NO 3- and NO2- in sputum were estimated by the Griess reagent. We found a maximum median concentration of 41.8 μM N2O (range 1.4-157.9 μM N2O). The concentration of N2O in the sputum was higher below the oxygenated layers. In 4 samples the N2O concentration increased during the initial 6 h of measurements before decreasing for approximately 6 h. Concomitantly, the concentration of NO3- decreased in sputum during 24 hours of incubation. We demonstrate for the first time production of N2O in clinical material from infected human airways indicating pathogenic metabolism based on denitrification. Therefore, P. aeruginosa may acquire energy for growth by denitrification in anoxic endobronchial mucus in CF patients. Such ability for anaerobic growth may be a hitherto ignored key aspect of chronic P. aeruginosa infections that can inform new strategies for treatment and prevention. © 2014 Kolpen et al

Prediction: coveted, yet forsaken? Introducing a cross-validated predictive ability test in partial least squares path modeling

Management researchers often develop theories and policies that are forward‐looking. The prospective outlook of predictive modeling, where a model predicts unseen or new data, can complement the retrospective nature of causal‐explanatory modeling that dominates the field. Partial least squares (PLS) path modeling is an excellent tool for building theories that offer both explanation and prediction. A limitation of PLS, however, is the lack of a statistical test to assess whether a proposed or alternative theoretical model offers significantly better out‐of‐sample predictive power than a benchmark or an established model. Such an assessment of predictive power is essential for theory development and validation, and for selecting a model on which to base managerial and policy decisions. We introduce the cross‐validated predictive ability test (CVPAT) to conduct a pairwise comparison of predictive power of competing models, and substantiate its performance via multiple Monte Carlo studies. We propose a stepwise predictive model comparison procedure to guide researchers, and demonstrate CVPAT's practical utility using the well‐known American Customer Satisfaction Index (ACSI) model

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives