A little thanks goes a long way: Explaining why gratitude expressions motivate prosocial behavior.

Although research has established that receiving expressions of gratitude increases prosocial behavior, little is known about the psychological mechanisms that mediate this effect. We propose that gratitude expressions can enhance prosocial behavior through both agentic and communal mechanisms, such that when helpers are thanked for their efforts, they experience stronger feelings of self-efficacy and social worth, which motivate them to engage in prosocial behavior. In Experiments 1 and 2, receiving a brief written expression of gratitude motivated helpers to assist both the beneficiary who expressed gratitude and a different beneficiary. These effects of gratitude expressions were mediated by perceptions of social worth and not by self-efficacy or affect. In Experiment 3, we constructively replicated these effects in a field experiment: A manager's gratitude expression increased the number of calls made by university fundraisers, which was mediated by social worth but not self-efficacy. In Experiment 4, a different measure of social worth mediated the effects of an interpersonal gratitude expression. Our results support the communal perspective rather than the agentic perspective: Gratitude expressions increase prosocial behavior by enabling individuals to feel socially valued. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of emulsifier layer,antioxidants and radical initiators in the oxidation of olive oil-in-water emulsions

Lipid oxidation in oil-in-water (O/W) emulsions is largely affected by the properties of the interfacial layer surrounding the oil droplets. In this work, the effect of the emulsifier layer structure, presence of both hydrophilic and lipophilic antioxidants and radical initiators on the development of lipid oxidation in olive oil-in-water emulsions was investigated. The olive oil-in-water emulsion is a suitable model of low fat food emulsions. The rationale of the work was to study the role of the interfacial layer when both the antioxidants and the radical initiators came from the two different emulsion compartments. Emulsions were prepared by using food grade emulsifiers of the Tween series (polyoxyethylene sorbitan esters) in the water phase and Span 80 (sorbitan monoleate) in the oil phase. The properties of the interfacial layer were changed by using Tween 20, Tween 60, Tween 80, which have different hydrophobic tails. These systems were oxidized by means of both hydrophilic (AAPH (2,2′-azobis,2-methyl-propanimidamide dihydrochloride), AIPH (2,2′-azobis[2-(2-imidazolin-2-yl) propane] dihydrochloride) and lipophilic (AMVN (2,2′-azobis(2,4-dimethylvaleronitrile)) radical initiators at 40 °C. A continuous fluorescent method based on the front face technique allowed us to follow directly the development of oxidation in the whole emulsion. The combination Tween 80/Span 80 produced an interfacial layer more resistant to radical attack. Moreover, a polar paradox was verified also for radical initiators, while the results suggest that the best way to protect emulsions is to use a combination of antioxidants in both phases, to promote a synergy and the regeneration of antioxidants mediated by the interfacial layer.     

Preparation of albumin–ferrite superparamagnetic nanoparticles using reverse micelles

BACKGROUND: Micellar systems are widely applied as reactors to encapsulate inorganic nanoparticles in polymeric materials. However, only low inorganic contents and microscale dimensions are often achieved. RESULTS: The adsorption of albumin protein on ferrite nanoparticles permits to increase the stability of inorganic dispersions in water by inhibiting particle flocculation. Subsequent glutaraldehyde addition induces protein crosslinking and ferrite entrapment. Polymer–ferrite composite nanoparticles were obtained in this way. The magnetic albumin nanoparticles (25 nm mean diameter) obtained contain about 40 wt% of ferrite and show superparamagnetic behaviour. The composite powder was successfully functionalized with a model drug and the biological activity was evaluated. CONCLUSION: Using a reverse micelle approach, ferrite–albumin composite nanoparticles with a high inorganic content were obtained. The method permits the formulation of biocompatible magnetic particles of nanoscale dimensions. The exhibited superparamagnetic behaviour permits to hypothesize an application of the powder composite as a carrier in biomedical technologies. Copyright © 2009 Society of Chemical Industry     

User identification for cross-system personalisation

Currently, there is an increasing demand for user-adaptive systems for various purposes in many different domains. Typically, personalisation in information systems occurs separately within each system. The recent trends in user modeling rely on cross-system personalisation, i.e., the opportunity to share information across multiple information systems in order to improve user adaptation. Cooperation among systems in order to exchange user model knowledge is a complex task. This paper addresses a key challenge for cross-system personalisation which is often taken as a starting assumption, i.e., user identification.In this paper, we describe the conceptualization and implementation of a framework that provides a common base for user identification for cross-system personalisation among web-based user-adaptive systems. However, the framework can be easily adopted in different working environments and for different purposes.The framework represents a hybrid approach which draws parallels both from centralized and decentralized solutions for user modeling. To perform user identification, we propose to exploit a set of identification properties that are combined using an identification algorithm.     

From soft constraints to bipolar preferences: modelling framework and solving issues

Real-life problems present several kinds of preferences. We focus on problems with both positive and negative preferences, which we call bipolar preference problems. Although seemingly specular notions, these two kinds of preferences should be dealt with differently to obtain the desired natural behaviour. We technically address this by generalising the soft constraint formalism, which is able to model problems with one kind of preference. We show that soft constraints model only negative preferences, and we add to them a new mathematical structure which allows to handle positive preferences as well. We also address the issue of the compensation between positive and negative preferences, studying the properties of this operation. Finally, we extend the notion of arc consistency to bipolar problems, and we show how branch and bound (with or without constraint propagation) can be easily adapted to solve such problems.