In recent years, meat production and consumption has become a topic of intense debate for environmental, animal welfare and health reasons. Research on more sustainable alternatives to meat production has increased. Our goal is to gain insight into the purchase of meat from transhumance livestock and to explore the main factors driving this process. This type of meat is more respectful towards the environment and animal welfare, provides financial stability for many rural families and helps preserve an activity that is part of the cultural heritage in rural areas. From a methodological point of view, we have adopted the theoretical alphabet theory model proposed by Zepeda and Deal in 2009 to explain sustainable purchase behavior. For this purpose, we created two different models, one for lamb meat and one for beef meat. The data come from an online survey of Spanish meat consumers. We applied a structural equation modeling technique to test the suggested model and hypothesis. The results allow us to conclude that the alphabet theory is a suitable theory for our data. The level of knowledge on transhumance and contextual factors, such as the content of fat or the type of meat, impact the creation of attitudes towards this type of livestock farming, but demographic variables do not. In both models, buying meat with a designation of origin and buying meat at specialty retailers are habits that positively influence purchase intention. Our results are highly relevant to help meat of transhumant origin reach the markets and to differentiate it from other products.

Individuals with discordantly high apoB to LDL-cholesterol levels carry a higher risk of atherosclerotic CVD compared with those with average or discordantly low apoB to LDL-cholesterol. We aimed to determine associations between apoB and LDL-cholesterol discordance in relation to nutrient patterns (NP) using National Health and Nutrition Examination Survey data. Participants were grouped by established LDL-cholesterol and apoB cut-offs (Group 1: low apoB/low LDL-cholesterol, Group 2: low apoB/high LDL-cholesterol, Group 3: high apoB/low LDL-cholesterol, Group 4: high apoB/high LDL-cholesterol). Principle component analysis was used to define NP. Machine learning (ML) and structural equation models were applied to assess associations of nutrient intake with apoB/LDL-cholesterol discordance using the combined effects of apoB and LDL-cholesterol. Three NP explained 63·2 % of variance in nutrient consumption. These consisted of NP1 rich in SFA, carbohydrate and vitamins, NP2 high in fibre, minerals, vitamins and PUFA and NP3 rich in dietary cholesterol, protein and Na. The discordantly high apoB to LDL-cholesterol group had the highest consumption of the NP1 and the lowest consumption of the NP2. ML showed nutrients that had the greatest unfavourable dietary contribution to individuals with discordantly high apoB to LDL-cholesterol were total fat, SFA and thiamine and the greatest favourable contributions were MUFA, folate, fibre and Se. Individuals with discordantly high apoB in relation to LDL-cholesterol had greater adherence to NP1, whereas those with lower levels of apoB, irrespective of LDL-cholesterol, were more likely to consume NP3.

This article describes the development of the ENCUIST (Extroversion, Neuroticism, Callous-Unemotional, Instability, Short-Test) questionnaire, which has been created to provide a personality profiling method based on a cognitive diagnostic modeling framework. The ENCUIST measures the attributes of extroversion, neuroticism, callous unemotionality and overt expressions of anger that are relevant in a forensic context. The scores provided by the ENCUIST are binary classifications of the individuals (high/low) in these attributes. The ENCUIST was developed using a sample of 516 subjects to study its validation through psychometric procedures, including factor analysis, cognitive diagnostic modeling and structural equation modeling. The results supported a four-factor structure. Linear regressions were used to evaluate the predictive validity of the scores provided by ENCUIST with respect to two external criteria that are relevant in the forensic context, namely behavioral activation and behavioral inhibition. The results showed that the extroversion dimension is positively related to behavioral activation, although the effect size is modest and the proportion of explained variance is only 11%. Moreover, the dimensions of neuroticism and anger expression are positively related to behavioral inhibition, with 7% of the variance explained. Together, these results suggest that cognitive diagnostic models are useful tools for the elaboration of personality profiles based on classifying subjects along binary attributes.

Identifying the relative importance of urban and non-urban land-use types for potential denitrification derived N2O at a regional scale is critical for quantifying the impacts of human activities on nitrous oxide (N2O) emission under changing environments. In this study we used a regional dataset from China including 197 soil samples and six land-use types to evaluate the main predictors (land use, heavy metals, soil pH, soil moisture, substrate availability, functional and broad microbial abundances) of potential denitrification using multivariate and pathway analysis. Our results provide empirical evidence that soils on farms have the greatest potential denitrifying ability (PDA) (10.92±6.08ng N2O-N·g–1 dry soil·min–1) followed by urban soil (6.80±5.35ng N2O-N·g–1 dry soil·min–1). Our models indicate that land use (low vs. high human activity), followed by total nitrogen (TN) and heavy metals (Cu, Zn, Pb, Cd) was the most important driver of PDA. In addition, our path analysis suggests that at least part of the impacts of land use on potential denitrification were mediated via microbial abundance, soil pH and substrates including TN, dissolved organic carbon and nitrate. This study identifies the main predictors of denitrification at a regional scale which is needed to quantify the impact of human activities on ecosystem functionality under changing conditions.

Organic crop production is often limited by the inability to control weeds. An 18-yr data set of weed cover in organic crop rotations at the long-term Farming Systems Project at Beltsville, MD, was analyzed to identify meteorological and management factors influencing weed abundance. A path analysis using structural equation models was employed to distinguish between the direct effect of factors on weed cover and the indirect effect on weed cover through effects on crop competitiveness. Grain yield of corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] served as a surrogate for crop competitiveness and was found to be the most important factor influencing weed cover. Precipitation during late vegetative and early reproductive crop growth had a strong positive effect on crop yield, and thereby a negative indirect effect on weed cover, but this effect was partially offset by a positive direct effect on weed cover. Delayed crop planting date and crop rotational diversification including crops other than summer row crops had a moderate negative effect on weed cover, while having minimal effect on crop performance. Rotary hoeing also had a direct negative effect on weed cover, but a corresponding negative effect on crop performance resulted in a diminished total effect on weeds. Results demonstrate the complex interactions that define the relative abundance of weeds faced by organic growers, but, generally, factors that enhanced crop competitiveness provided the most effective weed management.

Love has been a recurrent topic throughout history, and especially, literature. Moreover, there is generalized agreement about its relevance for health emotional well-being, and quality of life. This study was carried out with a sample of 376 persons with ID. The goals of the work were to analyze a theoretical model of love in people with intellectual disabilities by means of the methodology of structural equations, and to analyze their perception of love and of amorous relations with regard to other aspects such as amorous satisfaction, perceived satisfaction, absence of family interference, self-determination, and emotional well-being. The results revealed that (a) the construct under study has three factors: Commitment, stability, and idealization, Passion and physiological excitement, and Intimacy and romanticism; (b) the perception of love in this collective is, in general, idealized and affected by the context; and (c) self-determination and the lack of family interference are relevant variables to explain both love and emotional well-being.