935 resultados para INTEGRATIVE TAXONOMY


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An effective approach to research on farmers' behaviour is based on: i) an explicit and well-motivated behavioural theory; ii) an integrative approach; and iii) understanding feedback processes and dynamics. While current approaches may effectively tackle some of them, they often fail to combine them together. The paper presents the integrative agent-centred (IAC) framework, which aims at filling this gap. It functions in accordance with these three pillars and provides a conceptual structure to understand farmers' behaviour in agricultural systems. The IAC framework is agent-centred and supports the understanding of farmers' behavior consistently with the perspective of agricultural systems as complex social-ecological systems. It combines different behavioural drivers, bridges between micro and macro levels, and depicts a potentially varied model of human agency. The use of the framework in practice is illustrated through two studies on pesticide use among smallholders in Colombia. The examples show how the framework can be implemented to derive policy implications to foster a transition towards more sustainable agricultural practices. The paper finally suggests that the framework can support different research designs for the study of agents' behaviour in agricultural and social-ecological systems.

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Angiotensin I-converting enzyme (ACE) inhibition is one of the mechanisms by which reduction in blood pressure is exerted. Whey proteins are a rich source of ACE inhibitory peptides and have shown a blood pressure reduction effect i.e. antihypertensive activity. The aim of this work was to develop a simplified process using a combination of adsorption and microfiltration steps for the production of hydrolysates from whey with high ACE inhibitory activity and potency; the latter was measured as the IC50, which is the peptide concentration required to reduce ACE activity by half. This process integrates the selective separation of β-lactoglobulin and casein derived peptides (CDP) from rennet whey and their hydrolysis, which results in partially pure, less complex hydrolysates with high bioactive potency. Hydrolysis was carried out with protease N ‘Amano’ in a thermostatically controlled membrane reactor operated in a batch mode. By applying the integrative approach it was possible to produce from the same feedstock two different hydrolysates that exhibited high ACE inhibition. One hydrolysate was mainly composed of casein-derived peptides with IC50= 285 μg/mL. In this hydrolysate we identified the well known potent ACE-I and anti-hypertensive tri-peptide Ile-Pro-Pro (IPP) and another novel octa-peptide Gln-Asp-Lys-Thr-Glu-Ile-Pro-Thr (QDKTEIPT). The second hydrolysate was mainly composed of β-lactoglobulin derived peptides with IC50=128 µg/mL. This hydrolysate contained a tetra-peptide (Ile-Ile-Ala-Glu) IIAE as one of the two major peptides. A further advantage to this process is that enzyme activity was substantially increased as enzyme product inhibition was reduced.

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The overall aim of this work was to characterize the major angiotensin converting enzyme (ACE) inhibitory peptides produced by enzymatic hydrolysis of whey proteins, through the application of a novel integrative process. This process consisted of the combination of adsorption and microfiltration within a stirred cell unit for the selective immobilization of β-lactoglobulin and casein derived peptides (CDP) from whey. The adsorbed proteins were hydrolyzed in-situ which resulted in the separation of peptide products from the substrate and fractionation of peptides. Two different hydrolysates were produced: (i) from CDP (IC50 =287μg/mL) and (ii) from β-lactoglobulin (IC50=128μg/mL). IC50 is the concentration of inhibitor needed to inhibit ACE by half. The well known antihypertensive peptide IPP and several novel peptides that have structural similarities with reported ACE inhibitory peptides were identified and characterized in both hydrolysates. Furthermore, the hydrolysates were assessed for bitterness. No significant difference was found between the control (milk with no hydrolysate) and hydrolysate samples at different concentrations (at, below and above the IC50).

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Initial phase of all Enterprise Architecture (EA) initiatives is important. One of the most crucial tasks in that phase is to sell EA to the top management by explaining its purpose. In this paper, by using semiotic framework we show that there is a clear gap between the definition of EA and its purpose. Contribution of this paper is a taxonomy that expands knowledge of pragmatics of EA, and that can be used as a tool for explaining the purpose of EA. Grounded theory is used to form the taxonomy. Data is collected from a discussion group used by EA practitioners. Results indicate that the purpose of EA is to meet organisations‟ stakeholder‟s goals and to create value to organisation. Results are in line with current literature. Most interesting result is that EA practitioners seem to realise that technical solutions are not the purpose of EA, but means for fulfilling it.

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The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.

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Cognitive theories of social anxiety indicate that negative cognitive biases play a key role in causing and maintaining social anxiety. On the basis of these cognitive theories, laboratory-based research has shown that individuals with social anxiety exhibit negative interpretation biases of ambiguous social situations. Cognitive Bias Modification for interpretative biases (CBM-I) has emerged from this basic science research to modify negative interpretative biases in social anxiety and reduce emotional vulnerability and social anxiety symptoms. However, it is not yet clear if modifying interpretation biases via CBM will have any enduring effect on social anxiety symptoms or improve social functioning. The aim of this paper is to review the relevant literature on interpretation biases in social anxiety and discuss important implications of CBM-I method for clinical practice and research.

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This paper presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easy to other regions in developing countries with similar conditions.

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High ionic calcium concentration and the absence of caseinmacropeptides (CMP) in acid whey could influence the production of angiotensin-I-converting enzyme (ACE)-inhibitory hydrolysate and its bioactivity through the application of the integrative process. Therefore, the aim of the present study was to produce a hydrolysate from acid whey applying the integrative process. Process performance was evaluated based on protein adsorption capacity and conversion in relation to ACE-inhibitory activity (ACEi%) and ionic calcium concentration. Hydrolysates with high potency of their biological activity were produced (IC50 = 206-353 μg mL-1). High ionic calcium concentration in acid whey contributed to ACE-inhibitory activity. However, low β-lactoglobulin adsorption and conversion was observed. Optimisation of the resin volume increased the adsorption of β-lactoglobulin significantly but with lower selectivity. The changes in conversion value were not significant even at higher concentration of enzyme. Several ACE inhibitors derived from β-lactoglobulin that were identified before in sweet whey hydrolysates such as, IIAEKT, IIAE, IVTQ, LIVTQ, LIVTQT, LDAQ and LIVT were found. New peptides such as, SNICNI and ECCHGD derived from α-lactalbumin and BSA respectively were identified.

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1. The rapid expansion of systematic monitoring schemes necessitates robust methods to reliably assess species' status and trends. Insect monitoring poses a challenge where there are strong seasonal patterns, requiring repeated counts to reliably assess abundance. Butterfly monitoring schemes (BMSs) operate in an increasing number of countries with broadly the same methodology, yet they differ in their observation frequency and in the methods used to compute annual abundance indices. 2. Using simulated and observed data, we performed an extensive comparison of two approaches used to derive abundance indices from count data collected via BMS, under a range of sampling frequencies. Linear interpolation is most commonly used to estimate abundance indices from seasonal count series. A second method, hereafter the regional generalized additive model (GAM), fits a GAM to repeated counts within sites across a climatic region. For the two methods, we estimated bias in abundance indices and the statistical power for detecting trends, given different proportions of missing counts. We also compared the accuracy of trend estimates using systematically degraded observed counts of the Gatekeeper Pyronia tithonus (Linnaeus 1767). 3. The regional GAM method generally outperforms the linear interpolation method. When the proportion of missing counts increased beyond 50%, indices derived via the linear interpolation method showed substantially higher estimation error as well as clear biases, in comparison to the regional GAM method. The regional GAM method also showed higher power to detect trends when the proportion of missing counts was substantial. 4. Synthesis and applications. Monitoring offers invaluable data to support conservation policy and management, but requires robust analysis approaches and guidance for new and expanding schemes. Based on our findings, we recommend the regional generalized additive model approach when conducting integrative analyses across schemes, or when analysing scheme data with reduced sampling efforts. This method enables existing schemes to be expanded or new schemes to be developed with reduced within-year sampling frequency, as well as affording options to adapt protocols to more efficiently assess species status and trends across large geographical scales.