Explanation-Based Auditing

To comply with emerging privacy laws and regulations, it has become common for applications like electronic health records systems (EHRs) to collect access logs, which record each time a user (e.g., a hospital employee) accesses a piece of sensitive data (e.g., a patient record). Using the access log, it is easy to answer simple queries (e.g., Who accessed Alice's medical record?), but this often does not provide enough information. In addition to learning who accessed their medical records, patients will likely want to understand why each access occurred. In this paper, we introduce the problem of generating explanations for individual records in an access log. The problem is motivated by user-centric auditing applications, and it also provides a novel approach to misuse detection. We develop a framework for modeling explanations which is based on a fundamental observation: For certain classes of databases, including EHRs, the reason for most data accesses can be inferred from data stored elsewhere in the database. For example, if Alice has an appointment with Dr. Dave, this information is stored in the database, and it explains why Dr. Dave looked at Alice's record. Large numbers of data accesses can be explained using general forms called explanation templates. Rather than requiring an administrator to manually specify explanation templates, we propose a set of algorithms for automatically discovering frequent templates from the database (i.e., those that explain a large number of accesses). We also propose techniques for inferring collaborative user groups, which can be used to enhance the quality of the discovered explanations. Finally, we have evaluated our proposed techniques using an access log and data from the University of Michigan Health System. Our results demonstrate that in practice we can provide explanations for over 94% of data accesses in the log.Comment: VLDB201

Camalexin Quantification in Arabidopsis thaliana Leaves Infected with Botrytis cinerea

Phytoalexins are heterogeneous low molecular mass secondary metabolites with antimicrobial activity produced in response to pathogen invasion attempts at the infection site and represent an important part of the plant defense repertoire. Camalexin (3-Thiazol-2′-yl-indole) is a known phytoalexin first detected and isolated in Camelina sativa, from which it takes its name, infected with Alternaria brassicae (Browne et al., 1991). Production of camalexin is also induced in Arabidopsis thaliana leaves by a range of biotrophic and necrotrophic plant pathogens (bacteria, oomycetes, fungi and viruses) (Ahuja et al., 2012) as well as by abiotic stresses, such as UV and chemicals (e.g. acifluorfen, paraquat, chlorsulfuron and α-amino butyric acid) (Zhao et al., 1998; Tierens et al., 2002). Camalexin originates from tryptophan and CYP79B2 and CYP71B15 (PAD3) are P450 enzymes that catalyze important steps in its biosynthetic pathway (Glawischnig, 2007). In this protocol the detection and quantification of camalexin produced in Arabidopsis leaves infected with the necrotrophic fungus Botrytis cinerea is described

Microarray sub-grid detection: A novel algorithm

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2007 Taylor & Francis LtdA novel algorithm for detecting microarray subgrids is proposed. The only input to the algorithm is the raw microarray image, which can be of any resolution, and the subgrid detection is performed with no prior assumptions. The algorithm consists of a series of methods of spot shape detection, spot filtering, spot spacing estimation, and subgrid shape detection. It is shown to be able to divide images of varying quality into subgrid regions with no manual interaction. The algorithm is robust against high levels of noise and high percentages of poorly expressed or missing spots. In addition, it is proved to be effective in locating regular groupings of primitives in a set of non-microarray images, suggesting potential application in the general area of image processing

thermal comfort cfd maps for architectural interior design

Abstract Within the context of nearly Zero-Energy Buildings, it is debated that the energy-centred notion of design, proposed by regulatory frames, needs to be combined with a further focus toward users' comfort and delight. Accordingly, the underlying theory of the research is that designers should take responsibility for understanding the heat flows through the building parts and its spaces. A design, which is sensible to the micro-thermal conditions coexisting in space, allows the inhabitants to control the building to their needs and desires: for instance, maximising the benefits of heat gain from the sun moving a series of internal partitions so as to avoid the danger of over-heating. It is thus necessary that existing simulation software tools are tested to the purpose of modelling and visualising the indoor thermal environment complexity. The research discusses how thermal comfort maps, which are prepared with the use of Computational Fluid Dynamic simulation method, could integrate energy simulation outputs to uphold qualitative architectural design decisions. Mean radiant temperature maps were thus used to design the retrofit of a small educational building in Copenhagen. The thermal opportunities of movable interior partitions (operated by the users) could be estimated, providing a new layer of information to the designer. The applicability of the thermal maps within an architectural design process is discussed adopting standard energy simulation comfort outputs as a reference. The capabilities and the limitations of the method are appraised

Water Defluoridation: Nanofiltration vs Membrane Distillation

Nowadays, fluoride contamination of drinking water is a major problem for various countries, because high concentrations of fluoride pose a risk of dental and skeletal fluorosis. Over past years, membrane nanofiltration (NF) has been proposed as convenient defluoridation technology. However, NF cannot be applied to water systems with high fluoride concentration, and the disposal of the membrane concentrate remains an issue. In this work, we compared a commercial polyester NF membrane and a polypropylene hollow-fiber membrane distillation (MD) module for their ability to remove fluoride ions from water in the presence of hardness ions and organic fouling agents. The NF membrane can offer more than 10 times higher water productivity than MD, under realistic gradients of temperature and pressure, respectively. Despite that, after reaching a concentration factor of about 3, fouling and scaling caused the flux to drop to about 80% with respect to its initial value. Moreover, F- retention decreased from 90% to below 80%, thus providing a permeate of scarce quality. MD was operated in the direct-contact mode on a polypropylene hollow-fiber membrane, which was charged with a hot feed flow (average T = 58 °C) on one side and a cooled (20 °C) permeate flow of distilled water on the other side. The concentration of fluoride ions in the permeate was always below the detection limit of our electrode (0.2 ppm), regardless of the fluoride concentration in the feed. Moreover, the MD module showed higher resistance to fouling and scaling than NF, and CaF2 crystals were recovered from the MD concentrate after cooling. These results suggest that the synergic combination of the two techniques might be beneficial for the purification of fluoride-contaminated water systems: MD can be used to further concentrate the NF retentate, thus producing high-purity water and recovering CaF2 crystals.Fil: Moran Ayala, Lucia Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Paquet, Marie. University of Aalborg; DinamarcaFil: Janowska, Katarzyna. University of Aalborg; DinamarcaFil: Jamard, Paul. University of Aalborg; DinamarcaFil: Quist Jensen, Cejna A.. University of Aalborg; DinamarcaFil: Bosio, Gabriela Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Martire, Daniel Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Fabbri, Debora. Università di Torino; ItaliaFil: Boffa, Vittorio. University of Aalborg; Dinamarc

THE ALGORITHMIC AUTOREGULATION SOFTWARE DEVELOPMENT METHODOLOGY

We present a new self-regulating methodology for coordinating distributed team work called Algorithmic Autoregulation (AA), based on recent social networking concepts and individual merit. Team members take on an egalitarian role, and stay voluntarily logged into so-called AA sessions for part of their time (e.g. 2 hours per day), during which they create periodical logs — short text sentences — they wish to share about their activity with the team. These logs are publicly aggregated in a Website and are peer-validated after the end of a session, as in code review. A short screencast is ideally recorded at the end of each session to make AA logs more understandable. This methodology has shown to be well-suited for increasing the efficiency of distributed teams working on what is called Global Software Development (GSD), as observed in our experience in actual real-world situations. This efficiency boost is mainly achieved through 1) built-in asynchronous on-demand communication in conjunction with documentation of work products and processes, and 2) reduced need for central management, meetings or time-consuming reports. Hence, the AA methodology legitimizes and facilitates the activities of a distributed software team. It thus enables other entities to have a solid means to fund these activities, allowing for new and concrete business models to emerge for very distributed software development. AA has been proposed, at its core, as a way of sustaining self-replicating hacker initiatives. These claims are discussed in a real case-study of running a distributed free software hacker team called Lab Macambira.O artigo apresenta uma nova metodologia para a coordenação do trabalho de uma equipe dispersa fisicamente chamada Autorregulação algorítmica (AA). A metodologia se baseia em conceitos recentes de redes sociais e mérito individual. Os membros da equipe assumem papéis igualitários e se mantêm logados voluntariamente a sessões de AA por parte do seu tempo (por exemplo, duas horas por dia), criando logs periódicos — frases curtas — que desejam compartilhar com os demais envolvidos nas atividades da equipe. Estes logs são agregados publicamente em um website e são validados pelos pares após o fim da sessão, da mesma forma que se faz na revisão de código. Preferencialmente, um breve screencast é gravado ao final de casa sessão para tornar os logs de AA mais compreensíveis. Esta metodologia se demonstrou adequada para aumentar a eficiência de equipes dispersas fisicamente trabalhando em projetos de Desenvolvimento de Software Global (GSD), conforme observado em nossa experiência em situações de uso cotidiano. O aumento de eficiência é obtido principalmente por meio de: 1) comunicação assíncrona e sob demanda em conjunto com a documentação dos produtos do trabalho e processos, e 2) necessidade reduzida de gestão centralizada, reuniões ou relatórios que consomem tempo. Assim, a metodologia AA legitima e facilita as atividades de uma equipe de desenvolvimento de software distribuída. Ela possibilita que outras entidades disponham de meios para financiar essas atividades, possibilitando que novos e concretos modelos de negócio se tornem possíveis para desenvolvimentos de software muito distribuídos. A AA foi proposta, em sua essência, como uma forma de possibilitar a auto-replicação de iniciativas de atividade hacker. Estes argumentos são discutidos com base em um estudo de caso real de atuação de uma equipe hacker de software livre distribuído chamada Lab Macambira