From Data Disclosure to Privacy Nudges: A Privacy-aware and User-centric Personal Data Management Framework

Although there are privacy-enhancing tools designed to protect users' online privacy, it is surprising to see a lack of user-centric solutions allowing privacy control based on the joint assessment of privacy risks and benefits, due to data disclosure to \emph{multiple} platforms. In this paper, we propose a conceptual framework to fill the gap: aiming at the user-centric privacy protection, we show the framework can not only assess privacy risks in using online services but also the added values earned from data disclosure. Through following a human-in-the-loop approach, it is expected the framework provides a personalized solution via preference learning, continuous privacy assessment, behavior monitoring and nudging. Finally, we describe a case study towards "leisure travelers" and several future areas to be studied in the ongoing project

Cheat-Proof Trust Model for Cloud Computing Markets

Abstract. Online Reputation Systems would help mitigate the information asymmetry between clients and providers in Cloud Computing Markets. However, those systems raise two main drawbacks: the disagreement for assuming the cost of ownership of such services and their vulnerability to reputation attacks from dishonest parties that want to increase their reputation. This paper faces both problems by describing a decentralized model that would not need from the intervention of a central entity for managing it. This model includes mechanisms for allowing participants to avoid such dishonest behaviour from other peers: each client statistically analyses the external reports about providers and accordingly weights them in the overall trust calculation. The validity of the model is demonstrated through experiments for several use cases

TEMPERAMENT AND CHARACTER TRAITS IN MAJOR DEPRESSIVE DISORDER: INFLUENCE OF MOOD STATE AND RECURRENCE OF EPISODES

Background: The objective of this study was to compare personality traits between major depressive disorder (MDD) patients and healthy comparison subjects (HC) and examine if personality traits in patients are associated with specific clinical characteristics of the disorder. Methods: Sixty MDD patients (45 depressed, 15 remitted) were compared to 60 HC using the Temperament and Character Inventory. Analysis of covariance, with age and gender as covariates, was used to compare the mean Temperament and Character Inventory scores among the subject groups. Results: Depressed MDD patients scored significantly higher than HC on novelty seeking, harm avoidance, and self-transcendence and lower on reward dependence, self-directedness, and cooperativeness. Remitted MDD patients scored significantly lower than HC only on self-directedness. Comorbidity with anxiety disorder had a main effect only on harm avoidance. Harm avoidance was positively correlated with depression intensity and with number of episodes. Self-directedness bad an inverse correlation with depression intensity. Conclusions: MDD patients present a different personality profile from HC, and these differences are influenced by mood state and comorbid anxiety disorders. When considering patients who have been in remission for some time, the differences pertain to few personality dimensions. Cumulated number of depressive episodes may result in increased harm avoidance. Depression and Anxiety 26.382-388, 2009. (c) 2009 Wiky-Liss, Inc.UTHSCSA GCRC[M01-RR-01346]NARSADKrus Endowed Chair in Psychiatry (UTHSCSA)Veterans AdministrationAmerican Foundation for Suicide Prevention (ASFP)[MH 01736][MH 068662

The Potential of Using Bisr Date Powder as a Novel Ingredient in Beef Burgers: The Effect on Chemical Composition, Cooking Properties, Microbial Analysis, and Organoleptic Properties

Overproduction of date fruits with limited industrial utilization leads to huge waste and losses, especially in bisr (the first stage of date maturity). Therefore, this study aimed to investigate the potential of using bisr date powder (BDP), which is rich in dietary fiber, flavonoids, and phenolic and antioxidant compounds, as a replacement for breadcrumbs in the beef burgers. The beef burger samples were produced by replacing breadcrumb powder with different concentration levels of BDP (0.0, 25, 50, 75, and 100%). All the samples were evaluated for their quality characteristics, including chemical composition, cooking properties, texture profile, organoleptic characteristics, and microbial profile. The results revealed that the gradual replacement of breadcrumbs with BDP in beef burgers significantly decreased moisture, protein, and lipid contents and significantly increased ash and carbohydrate contents compared to the control. The substitution of breadcrumbs with BDP at 50, 75, and 100% significantly decreased the cooking yield and increased the cooking loss and shrinking percentage of a beef burger. On the other hand, the textural profile of all beef burger samples showed a significant decrease in burgers’ hardness, gumminess, and chewiness with increasing substitution levels of breadcrumbs by BDP compared to the control. However, the treatment containing 25% BDP was more resilient than the control. In addition, the replacement of breadcrumbs with BDP up to 100% did not significantly affect the organoleptic properties of beef burger products compared to the control. Moreover, the microbiological analysis revealed that all beef burger treatments were safe with acceptable levels of bacterial load according to the Council of the European Communities’ standard specifications. In conclusion, there is a possibility of using BDP as a promising natural replacer of breadcrumbs to produce beef burgers without deteriorating the quality profile and safety of the product

Safety assurance of open adaptive systems - a survey

Open adaptive systems are the basis for a promising new generation of embedded systems with huge economic potential. In many application domains, however, the systems are safety-critical and an appropriate safety assurance approach is still missing. In recent years, models at runtime have emerged as a promising way to systematically engineer adaptive systems. This approach seems to provide the indispensable leverage for applying safety assurance techniques in adaptive systems. Therefore, this survey analyzes the state-of-the-art of models at runtime from a safety engineering point of view in order to assess the potential of this approach and to identify open gaps that have to be closed in future research to yield a safety assurance approach for open adaptive systems