Why Are Male Social Relationships Complex in the Doubtful Sound Bottlenose Dolphin Population?

Copyright 2008 Elsevier B.V., All rights reserved.Peer reviewedPublisher PD

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

The NRG1 gene is frequently silenced by methylation in breast cancers and is a strong candidate for the 8p tumour suppressor gene.

Neuregulin-1 (NRG1) is both a candidate oncogene and a candidate tumour suppressor gene. It not only encodes the heregulins and other mitogenic ligands for the ERBB family, but also causes apoptosis in NRG1-expressing cells. We found that most breast cancer cell lines had reduced or undetectable expression of NRG1. This included cell lines that had translocation breaks in the gene. Similarly, expression in cancers was generally comparable to or less than that in various normal breast samples. Many non-expressing cell lines had extensive methylation of the CpG island at the principal transcription start site at exon 2 of NRG1. Expression was reactivated by demethylation. Many tumours also showed methylation, whereas normal mammary epithelial fragments had none. Lower NRG1 expression correlated with higher methylation. Small interfering RNA (siRNA)-mediated depletion of NRG1 increased net proliferation in a normal breast cell line and a breast cancer cell line that expressed NRG1. The short arm of chromosome 8 is frequently lost in epithelial cancers, and NRG1 is the most centromeric gene that is always affected. NRG1 may therefore be the major tumour suppressor gene postulated to be on 8p: it is in the correct location, is antiproliferative and is silenced in many breast cancers

Negative parental responses to coming out and family functioning in a sample of lesbian and gay young adults

Parental responses to youths' coming out (CO) are crucial to the subsequent adjustment of children and family. The present study investigated the negative parental reaction to the disclosure of same-sex attraction and the differences between maternal and paternal responses, as reported by their homosexual daughters and sons. Participants' perceptions of their parents' reactions (evaluated through the Perceived Parental Reactions Scale, PPRS), age at coming out, gender, parental political orientation, and religiosity involvement, the family functioning (assessed through the Family Adaptability and Cohesion Evaluation Scales, FACES IV), were assessed in 164 Italian gay and lesbian young adults. Pearson correlation coefficients were calculated to assess the relation between family functioning and parental reaction to CO. The paired sample t-test was used to compare mothers and fathers' scores on the PPRS. Hierarchical multiple regression was conducted to analyze the relevance of each variable. No differences were found between mothers and fathers in their reaction to the disclosure. The analysis showed that a negative reaction to coming out was predicted by parents' right-wing political conservatism, strong religious beliefs, and higher scores in the scales Rigid and Enmeshed. Findings confirm that a negative parental reaction is the result of poor family resources to face a stressful situation and a strong belief in traditional values. These results have important implications in both clinical and social fields

Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?

Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.The authors would like to thank COST Action FP0804-Forest Management Decision Support Systems (FORSYS) for financing a three month Short-Term Scientific Mission (STSM) in Forest Research (Roslin, UK) in 2012, making possible this research; Spanish Ministry of Economy and Competitiveness for supporting the project Multicriteria Techniques and Participatory Decision-Making for Sustainable Management (Ref. ECO2011-27369) where the leading author is involved; and the Regional Ministry of Education, Culture and Sports (Valencia, Spain) for financing a research fellowship (Ref. ACIF/2010/248).Valls Donderis, P.; Ray, D.; Peace, A.; Stewart, A.; Lawrence, A.; Galiana, F. (2013). Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?. Scandinavian Journal of Forest Research. 29(1):71-83. https://doi.org/10.1080/02827581.2013.837950S7183291Arnstein, S. R. (1969). A Ladder Of Citizen Participation. Journal of the American Institute of Planners, 35(4), 216-224. doi:10.1080/01944366908977225Atwell, R. C., Schulte, L. A., & Westphal, L. M. (2011). Tweak, Adapt, or Transform: Policy Scenarios in Response to Emerging Bioenergy Markets in the U.S. Corn Belt. Ecology and Society, 16(1). doi:10.5751/es-03854-160110Barac, A., Kellner, K., & De Klerk, N. (2004). Land User Participation in Developing a Computerised Decision Support System for Combating Desertification. Environmental Monitoring and Assessment, 99(1-3), 223-231. doi:10.1007/s10661-004-4022-6Bennet, A., & Bennet, D. (2008). The Decision-Making Process in a Complex Situation. Handbook on Decision Support Systems 1, 3-20. doi:10.1007/978-3-540-48713-5_1Blackstock, K. L., Kelly, G. J., & Horsey, B. L. (2007). Developing and applying a framework to evaluate participatory research for sustainability. Ecological Economics, 60(4), 726-742. doi:10.1016/j.ecolecon.2006.05.014Breuer, N. E., Cabrera, V. E., Ingram, K. T., Broad, K., & Hildebrand, P. E. (2007). AgClimate: a case study in participatory decision support system development. Climatic Change, 87(3-4), 385-403. doi:10.1007/s10584-007-9323-7Bunch, M. J., & Dudycha, D. J. (2004). Linking conceptual and simulation models of the Cooum River: collaborative development of a GIS-based DSS for environmental management. Computers, Environment and Urban Systems, 28(3), 247-264. doi:10.1016/s0198-9715(03)00021-8Byrne, E., & Sahay, S. (2007). Participatory design for social development: A South African case study on community-based health information systems. Information Technology for Development, 13(1), 71-94. doi:10.1002/itdj.20052Cain, J. ., Jinapala, K., Makin, I. ., Somaratna, P. ., Ariyaratna, B. ., & Perera, L. . (2003). Participatory decision support for agricultural management. A case study from Sri Lanka. Agricultural Systems, 76(2), 457-482. doi:10.1016/s0308-521x(02)00006-9Chakraborty, A. (2011). Enhancing the role of participatory scenario planning processes: Lessons from Reality Check exercises. Futures, 43(4), 387-399. doi:10.1016/j.futures.2011.01.004Cinderby, S., Bruin, A. de, Mbilinyi, B., Kongo, V., & Barron, J. (2011). Participatory geographic information systems for agricultural water management scenario development: A Tanzanian case study. Physics and Chemistry of the Earth, Parts A/B/C, 36(14-15), 1093-1102. doi:10.1016/j.pce.2011.07.039Drew, C. H., Nyerges, T. L., & Leschine, T. M. (2004). Promoting Transparency of Long‐Term Environmental Decisions: The Hanford Decision Mapping System Pilot Project. Risk Analysis, 24(6), 1641-1664. doi:10.1111/j.0272-4332.2004.00556.xDriedger, S. M., Kothari, A., Morrison, J., Sawada, M., Crighton, E. J., & Graham, I. D. (2007). Using participatory design to develop (public) health decision support systems through GIS. International Journal of Health Geographics, 6(1), 53. doi:10.1186/1476-072x-6-53Evers, M. (2008). An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53. doi:10.1108/14777830810840354Iivari, N. (2011). Participatory design in OSS development: interpretive case studies in company and community OSS development contexts. Behaviour & Information Technology, 30(3), 309-323. doi:10.1080/0144929x.2010.503351Innes, J. E., & Booher, D. E. (1999). Consensus Building and Complex Adaptive Systems. Journal of the American Planning Association, 65(4), 412-423. doi:10.1080/01944369908976071Jakku, E., & Thorburn, P. J. (2010). A conceptual framework for guiding the participatory development of agricultural decision support systems. Agricultural Systems, 103(9), 675-682. doi:10.1016/j.agsy.2010.08.007Jessel, B., & Jacobs, J. (2005). Land use scenario development and stakeholder involvement as tools for watershed management within the Havel River Basin. Limnologica, 35(3), 220-233. doi:10.1016/j.limno.2005.06.006Kautz, K. (2011). Investigating the design process: participatory design in agile software development. Information Technology & People, 24(3), 217-235. doi:10.1108/09593841111158356Kowalski, K., Stagl, S., Madlener, R., & Omann, I. (2009). Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis. European Journal of Operational Research, 197(3), 1063-1074. doi:10.1016/j.ejor.2007.12.049Lawrence, A. (2006). ‘No Personal Motive?’ Volunteers, Biodiversity, and the False Dichotomies of Participation. Ethics, Place & Environment, 9(3), 279-298. doi:10.1080/13668790600893319Mao, J., & Song, W. (2008). Empirical study of distinct features and challenges of joint development of information systems: The case of ABC bank. Tsinghua Science and Technology, 13(3), 414-419. doi:10.1016/s1007-0214(08)70066-xMenzel, S., Nordström, E.-M., Buchecker, M., Marques, A., Saarikoski, H., & Kangas, A. (2012). Decision support systems in forest management: requirements from a participatory planning perspective. European Journal of Forest Research, 131(5), 1367-1379. doi:10.1007/s10342-012-0604-yMoote, M. A., Mcclaran, M. P., & Chickering, D. K. (1997). RESEARCH: Theory in Practice: Applying Participatory Democracy Theory to Public Land Planning. Environmental Management, 21(6), 877-889. doi:10.1007/s002679900074Peleg, M., Shachak, A., Wang, D., & Karnieli, E. (2009). Using multi-perspective methodologies to study users’ interactions with the prototype front end of a guideline-based decision support system for diabetic foot care. International Journal of Medical Informatics, 78(7), 482-493. doi:10.1016/j.ijmedinf.2009.02.008Pretty, J. N. (1995). Participatory learning for sustainable agriculture. World Development, 23(8), 1247-1263. doi:10.1016/0305-750x(95)00046-fReed MS. 2008. Stakeholder participation for environmental management: a literature review. Sustainability Research Institute, School of Earth and Environment, University of Leeds.Reed, M. S., & Dougill, A. J. (2010). Linking degradation assessment to sustainable land management: A decision support system for Kalahari pastoralists. Journal of Arid Environments, 74(1), 149-155. doi:10.1016/j.jaridenv.2009.06.016Rowe, G., & Frewer, L. J. (2000). Public Participation Methods: A Framework for Evaluation. 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Describing the longitudinal course of major depression using Markov models: Data integration across three national surveys

BACKGROUND: Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. METHODS: Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada) were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. RESULTS: The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study using the WHO Mental Health Composite International Diagnostic Interview (WMH-CIDI). Consistent with previous work, transition probabilities reflecting recovery were high in the initial weeks of the episodes, and declined by a fixed proportion with each passing week. CONCLUSION: Markov models provide a framework for integrating psychiatric epidemiological data. Previous studies have illustrated the utility of Markov models for decomposing prevalence into its various determinants: incidence, recovery and mortality. This study extends the Markov approach by distinguishing several recurrence categories

Rotating black rings on Taub-NUT

In this paper, we construct new solutions describing rotating black rings on Taub-NUT using the inverse-scattering method. These are five-dimensional vacuum space-times, generalising the Emparan-Reall and extremal Pomeransky-Sen'kov black rings to a Taub-NUT background space. When reduced to four dimensions in Kaluza-Klein theory, these solutions describe (possibly rotating) electrically charged black holes in superposition with a finitely separated magnetic monopole. Various properties of these solutions are studied, from both a five- and four-dimensional perspective.Comment: 33 pages, 3 figures, LaTe

Instability of black hole formation under small pressure perturbations

We investigate here the spectrum of gravitational collapse endstates when arbitrarily small perfect fluid pressures are introduced in the classic black hole formation scenario as described by Oppenheimer, Snyder and Datt (OSD) [1]. This extends a previous result on tangential pressures [2] to the more physically realistic scenario of perfect fluid collapse. The existence of classes of pressure perturbations is shown explicitly, which has the property that injecting any smallest pressure changes the final fate of the dynamical collapse from a black hole to a naked singularity. It is therefore seen that any smallest neighborhood of the OSD model, in the space of initial data, contains collapse evolutions that go to a naked singularity outcome. This gives an intriguing insight on the nature of naked singularity formation in gravitational collapse.Comment: 7 pages, 1 figure, several modifications to match published version on GR

Why I tense up when you watch me: inferior parietal cortex mediates an audience’s influence on motor performance

The presence of an evaluative audience can alter skilled motor performance through changes in force output. To investigate how this is mediated within the brain, we emulated real-time social monitoring of participants’ performance of a fine grip task during functional magnetic resonance neuroimaging. We observed an increase in force output during social evaluation that was accompanied by focal reductions in activity within bilateral inferior parietal cortex. Moreover, deactivation of the left inferior parietal cortex predicted both inter- and intra-individual differences in socially-induced change in grip force. Social evaluation also enhanced activation within the posterior superior temporal sulcus, which conveys visual information about others’ actions to the inferior parietal cortex. Interestingly, functional connectivity between these two regions was attenuated by social evaluation. Our data suggest that social evaluation can vary force output through the altered engagement of inferior parietal cortex; a region implicated in sensorimotor integration necessary for object manipulation, and a component of the action-observation network which integrates and facilitates performance of observed actions. Social-evaluative situations may induce high-level representational incoherence between one’s own intentioned action and the perceived intention of others which, by uncoupling the dynamics of sensorimotor facilitation, could ultimately perturbe motor output