238 research outputs found

    The new psychoactive substances 5-(2-aminopropyl)indole (5-IT) and 6-(2-aminopropyl)indole (6-IT) interact with monoamine transporters in brain tissue

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    In recent years, use of psychoactive synthetic stimulants has grown rapidly. 5-(2-Aminopropyl)indole (5-IT) is a synthetic drug associated with a number of fatalities, that appears to be one of the newest 3,4-methylenedioxymethamphetamine (MDMA) replacements. Here, the monoamine-releasing properties of 5-IT, its structural isomer 6-(2-aminopropyl)indole (6-IT), and MDMA were compared using in vitro release assays at transporters for dopamine (DAT), norepinephrine (NET), and serotonin (SERT) in rat brain synaptosomes. In vivo pharmacology was assessed by locomotor activity and a functional observational battery (FOB) in mice. 5-IT and 6-IT were potent substrates at DAT, NET, and SERT. In contrast with the non-selective releasing properties of MDMA, 5-IT displayed greater potency for release at DAT over SERT, while 6-IT displayed greater potency for release at SERT over DAT. 5-IT produced locomotor stimulation and typical stimulant effects in the FOB similar to those produced by MDMA. Conversely, 6-IT increased behaviors associated with 5-HT toxicity. 5-IT likely has high abuse potential, which may be somewhat diminished by its slow onset of in vivo effects, whereas 6-IT may have low abuse liability, but enhanced risk for adverse effects. Results indicate that subtle differences in the chemical structure of transporter ligands can have profound effects on biological activity. The potent monoamine-releasing actions of 5-IT, coupled with its known inhibition of MAO A, could underlie its dangerous effects when administered alone, and in combination with other monoaminergic drugs or medications. Consequently, 5-IT and related compounds may pose substantial risk for abuse and serious adverse effects in human users

    Mapping the Future: Policy Applications of Climate Vulnerability Mapping in West Africa

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    We describe the development of climate vulnerability maps for three Sahelian countries – Mali, Burkina Faso, and Niger – and for coastal West Africa, with a focus on the way the maps were designed to meet decision-making needs and their ultimate influence and use in policy contexts. The paper provides a review of the literature on indicators and maps in the science-policy interface. We then assess the credibility, salience, and legitimacy of the maps as tools for decision-making. Results suggest that vulnerability maps are a useful boundary object for generating discussions among stakeholders with different objectives and technical backgrounds, and that they can provide useful input for targeting development assistance. We conclude with a discussion of the power of maps to capture policy maker attention, and how this increases the onus on map developers to communicate clearly uncertainties and limitations. The assessment of policy uptake in this paper is admittedly subjective; the article includes a discussion of ways to conduct more objective and rigorous assessments of policy impact so as to better evaluate the value and use of vulnerability mapping in decision-making processes

    Drivers of Innovation Using BIM in Architecture, Engineering, and Construction Firms

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    This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://doi.org/10.1061/9780784482889.023[Otros] Architecture, engineering, and construction (AEC) firms need to innovate in order to increase their business¿ competitiveness. Many companies around the world are considering the possibility of implementing building information modelling (BIM) in their projects without knowing its actual benefits for the business. The current literature recognizes certain barriers to BIM implementation; therefore, considering these barriers, this work proposes a holistic model that allows managers to explain how BIM can play an important role for the success of the AEC companies. The pillars of the model are a collaborative culture and training of employees in order to break down technological barriers. This way, BIM can help AEC companies to innovate. This proposal takes into consideration the three phases of the infrastructure life-cycle. In the design phase, the model considers 3D shape, scheduling (4D), costs (5D), and sustainability (6D). In the construction phase, the model focuses on supply chain and quality management. During the operation phase, the model is related to the virtual management of maintenance activities. Drivers of innovation should consider several facets: marketing, technology, organization, processes, and products. This model aims to enlighten the positive effects of a good strategic management using BIM on innovation activities in each of the phases of the infrastructure life-cycleVillena, F.; García-Segura, T.; Pellicer, E. (2020). Drivers of Innovation Using BIM in Architecture, Engineering, and Construction Firms. American Society of Civil Engineers. 210-222. https://doi.org/10.1061/9780784482889.023S210222Aibinu, A., & Venkatesh, S. (2014). Status of BIM Adoption and the BIM Experience of Cost Consultants in Australia. Journal of Professional Issues in Engineering Education and Practice, 140(3), 04013021. doi:10.1061/(asce)ei.1943-5541.0000193Alshubbak, A., Pellicer, E., Catalá, J., & Teixeira, J. M. C. (2015). A MODEL FOR IDENTIFYING OWNER’S NEEDS IN THE BUILDING LIFE CYCLE. Journal of Civil Engineering and Management, 21(8), 1046-1060. doi:10.3846/13923730.2015.1027257Autodesk Inc. (2012). Building information modelling [online] [8-06-2012]. Available from Internet: http://usa.autodesk.comAzhar, S., Khalfan, M., & Maqsood, T. (2015). Building information modelling (BIM): now and beyond. Construction Economics and Building, 12(4), 15-28. doi:10.5130/ajceb.v12i4.3032Blayse, A. M., & Manley, K. (2004). Key influences on construction innovation. Construction Innovation, 4(3), 143-154. doi:10.1108/14714170410815060Boland, R. J., Lyytinen, K., & Yoo, Y. (2007). Wakes of Innovation in Project Networks: The Case of Digital 3-D Representations in Architecture, Engineering, and Construction. Organization Science, 18(4), 631-647. doi:10.1287/orsc.1070.0304Bryde, D., Broquetas, M., & Volm, J. M. (2013). The project benefits of Building Information Modelling (BIM). International Journal of Project Management, 31(7), 971-980. doi:10.1016/j.ijproman.2012.12.001Chen, Y.-S. (2007). The Driver of Green Innovation and Green Image – Green Core Competence. Journal of Business Ethics, 81(3), 531-543. doi:10.1007/s10551-007-9522-1Cheng, Y.-M. (2018). Building Information Modeling for Quality Management. Proceedings of the 20th International Conference on Enterprise Information Systems. doi:10.5220/0006796703510358Chesbrough, H., & Crowther, A. K. (2006). Beyond high tech: early adopters of open innovation in other industries. R and D Management, 36(3), 229-236. doi:10.1111/j.1467-9310.2006.00428.xDavies, R., & Harty, C. (2013). Implementing ‘Site BIM’: A case study of ICT innovation on a large hospital project. Automation in Construction, 30, 15-24. doi:10.1016/j.autcon.2012.11.024Du Plessis, M. (2007). The role of knowledge management in innovation. Journal of Knowledge Management, 11(4), 20-29. doi:10.1108/13673270710762684Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2008). BIM Handbook. doi:10.1002/9780470261309Elmualim, A., & Gilder, J. (2013). BIM: innovation in design management, influence and challenges of implementation. Architectural Engineering and Design Management, 10(3-4), 183-199. doi:10.1080/17452007.2013.821399Erdogan, B., Anumba, C. J., Bouchlaghem, D., & Nielsen, Y. (2008). Collaboration Environments for Construction: Implementation Case Studies. Journal of Management in Engineering, 24(4), 234-244. doi:10.1061/(asce)0742-597x(2008)24:4(234)Fox, S., & Hietanen, J. (2007). Interorganizational use of building information models: potential for automational, informational and transformational effects. Construction Management and Economics, 25(3), 289-296. doi:10.1080/01446190600892995Franco, J., Mahdi, F., & Abaza, H. (2015). Using Building Information Modeling (BIM) for Estimating and Scheduling, Adoption Barriers. Universal Journal of Management, 3(9), 376-384. doi:10.13189/ujm.2015.030905Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management, 29(3), 358-390. doi:10.1016/j.jengtecman.2012.03.007Harness S. H. (2008). 2008 documents AIA advance the use of BIM and integrated project delivery [online] [5 Diciembre 2008]. Available from Internet: http://www.aia.orgHobday, M. (2005). Firm-level Innovation Models: Perspectives on Research in Developed and Developing Countries. Technology Analysis & Strategic Management, 17(2), 121-146. doi:10.1080/09537320500088666Hong Y. Hammad A. Sepasgozar S. and Akbarnezhad A. (2019). "BIM adoption model for small and medium construction organizations in Australia" Engineering Construction and Architectural Management 26(2) 154-183. https://doi.org/10.1108/ECAM-04-2017-006410.1108/ECAM-04-2017-0064Hurley, R. F., & Hult, G. T. M. (1998). Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination. Journal of Marketing, 62(3), 42-54. doi:10.1177/002224299806200303Khosrowshahi, F., & Arayici, Y. (2012). Roadmap for implementation of BIM in the UK construction industry. Engineering, Construction and Architectural Management, 19(6), 610-635. doi:10.1108/09699981211277531Kleinschmidt, E. J., de Brentani, U., & Salomo, S. (2007). Performance of Global New Product Development Programs: A Resource-Based View. Journal of Product Innovation Management, 24(5), 419-441. doi:10.1111/j.1540-5885.2007.00261.xLee, S., Yu, J., & Jeong, D. (2015). BIM Acceptance Model in Construction Organizations. Journal of Management in Engineering, 31(3), 04014048. doi:10.1061/(asce)me.1943-5479.0000252Lu, Q., & Lee, S. (2017). Image-Based Technologies for Constructing As-Is Building Information Models for Existing Buildings. Journal of Computing in Civil Engineering, 31(4), 04017005. doi:10.1061/(asce)cp.1943-5487.0000652Miettinen, R., & Paavola, S. (2014). Beyond the BIM utopia: Approaches to the development and implementation of building information modeling. Automation in Construction, 43, 84-91. doi:10.1016/j.autcon.2014.03.009Motamedi, A., Hammad, A., & Asen, Y. (2014). Knowledge-assisted BIM-based visual analytics for failure root cause detection in facilities management. Automation in Construction, 43, 73-83. doi:10.1016/j.autcon.2014.03.012Oduyemi O Okoroh MI Fajana OS. (2017). "The application and barriers of BIM in sustainable building design" Journal of Facilities Management 15(1):15−34. https://doi.org/10.1108/JFM-03-2016-0008.10.1108/JFM-03-2016-0008Olawumi, T. O., Chan, D. W. M., Wong, J. K. W., & Chan, A. P. C. (2018). Barriers to the integration of BIM and sustainability practices in construction projects: A Delphi survey of international experts. Journal of Building Engineering, 20, 60-71. doi:10.1016/j.jobe.2018.06.017Ozorhon, B., & Oral, K. (2017). Drivers of Innovation in Construction Projects. Journal of Construction Engineering and Management, 143(4), 04016118. doi:10.1061/(asce)co.1943-7862.0001234Papadonikolaki, E. (2018). Loosely Coupled Systems of Innovation: Aligning BIM Adoption with Implementation in Dutch Construction. Journal of Management in Engineering, 34(6), 05018009. doi:10.1061/(asce)me.1943-5479.0000644Pellicer, E., Yepes, V., Correa, C. L., & Alarcón, L. F. (2014). Model for Systematic Innovation in Construction Companies. Journal of Construction Engineering and Management, 140(4). doi:10.1061/(asce)co.1943-7862.0000700Poirier, E., Forgues, D., & Staub-French, S. (2016). Collaboration through innovation: implications for expertise in the AEC sector. Construction Management and Economics, 34(11), 769-789. doi:10.1080/01446193.2016.1206660Poirier, E., Staub-French, S., & Forgues, D. (2015). Embedded contexts of innovation. Construction Innovation, 15(1), 42-65. doi:10.1108/ci-01-2014-0013Rowlinson S. Collins R. Tuuli M. and Jia A. (2010). Implementation of Building Information Modeling (BIM) in Construction: A Comparative Case Study. AIP Conference Proceedings. 1233. 572-577. 10.1063/1.3452236.Selçuk Çıdık, M., Boyd, D., & Thurairajah, N. (2017). Innovative Capability of Building Information Modeling in Construction Design. Journal of Construction Engineering and Management, 143(8), 04017047. doi:10.1061/(asce)co.1943-7862.0001337Stock, R. M., Six, B., & Zacharias, N. A. (2012). Linking multiple layers of innovation-oriented corporate culture, product program innovativeness, and business performance: a contingency approach. Journal of the Academy of Marketing Science, 41(3), 283-299. doi:10.1007/s11747-012-0306-5Succar, B., & Kassem, M. (2015). Macro-BIM adoption: Conceptual structures. Automation in Construction, 57, 64-79. doi:10.1016/j.autcon.2015.04.018Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in Construction, 18(3), 357-375. doi:10.1016/j.autcon.2008.10.003Taylor, J. E., & Bernstein, P. G. (2009). Paradigm Trajectories of Building Information Modeling Practice in Project Networks. Journal of Management in Engineering, 25(2), 69-76. doi:10.1061/(asce)0742-597x(2009)25:2(69)Tekla Corporation. (2013). Basic concepts [online] [ 16 Enero 2013]. Available from Internet: http://www.tekla.comVillena Manzanares, F., & Galiano Coronil, A. (2017). EL DESARROLLO URBANO SOSTENIBLE Y SUS IMPLICACIONES PARA LAS EMPRESAS Y LOS TERRITORIOS. Revista de Estudios Empresariales. Segunda Época, (1). doi:10.17561/ree.v0i1.3185Volk, R., Stengel, J., & Schultmann, F. (2014). Building Information Modeling (BIM) for existing buildings — Literature review and future needs. Automation in Construction, 38, 109-127. doi:10.1016/j.autcon.2013.10.023Whyte, J., Bouchlaghem, N., Thorpe, A., & McCaffer, R. (2000). From CAD to virtual reality: modelling approaches, data exchange and interactive 3D building design tools. Automation in Construction, 10(1), 43-55. doi:10.1016/s0926-5805(99)00012-6Wischnevsky, J. D., Damanpour, F., & Méndez, F. A. (2011). Influence of Environmental Factors and Prior Changes on the Organizational Adoption of Changes in Products and in Technological and Administrative Processes. British Journal of Management, 22(1), 132-149. doi:10.1111/j.1467-8551.2010.00700.xWong, K., & Fan, Q. (2013). Building information modelling (BIM) for sustainable building design. Facilities, 31(3/4), 138-157. doi:10.1108/02632771311299412Yepes, V., Pellicer, E., Alarcón, L. F., & Correa, C. L. (2016). Creative Innovation in Spanish Construction Firms. Journal of Professional Issues in Engineering Education and Practice, 142(1), 04015006. doi:10.1061/(asce)ei.1943-5541.0000251Yusof N. Seng Lai K and Mustafa Kamal E. (2017). "Characteristics of innovation orientations in construction companies" Journal of Engineering Design and Technology 15(4) 436-455. https://doi.org/10.1108/JEDT-06-2016-003710.1108/JEDT-06-2016-0037Zhou, Y., Yang, Y., & Yang, J.-B. (2019). Barriers to BIM implementation strategies in China. Engineering, Construction and Architectural Management, 26(3), 554-574. doi:10.1108/ecam-04-2018-015

    Strategic risk appraisal. Comparing expert- and literature-informed consequence assessments for environmental policy risks receiving national attention

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    Strategic risk appraisal (SRA) has been applied to compare diverse policy level risks to and from the environment in England and Wales. Its application has relied on expert-informed assessments of the potential consequences from residual risks that attract policy attention at the national scale. Here we compare consequence assessments, across environmental, economic and social impact categories that draw on ‘expert’- and ‘literature-based’ analyses of the evidence for 12 public risks appraised by Government. For environmental consequences there is reasonable agreement between the two sources of assessment, with expert-informed assessments providing a narrower dispersion of impact severity and with median values similar in scale to those produced by an analysis of the literature. The situation is more complex for economic consequences, with a greater spread in the median values, less consistency between the two assessment types and a shift toward higher severity values across the risk portfolio. For social consequences, the spread of severity values is greater still, with no consistent trend between the severities of impact expressed by the two types of assessment. For the latter, the findings suggest the need for a fuller representation of socioeconomic expertise in SRA and the workshops that inform SRA output

    Does the perception of fairness and standard of care in the health system depend on the field of study? Results of an empirical analysis

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    Background: The main challenge in the context of health care reforms and priority setting is the establishment and/or maintenance of fairness and standard of care. For the political process and interdisciplinary discussion, the subjective perception of the health care system might even be as important as potential objective criteria. Of special interest are the perceptions of academic disciplines, whose representatives act as decision makers in the health care sector. The aim of this study is to explore and compare the subjective perception of fairness and standard of care in the German health care system among students of medicine, law, economics, philosophy, and religion. Methods: Between October 2011 and January 2012, we asked freshmen and advanced students of the fields mentioned above to participate in a paper and pencil survey. Prior to this, we formulated hypotheses. The data were analysed by micro econometric regression techniques. Results: Data from 1,088 students were included in the study. Medical students, freshmen, and advanced students perceive the standard of care significantly as being better than non-medical students. Differences in the perception of fairness are not significant between the freshmen of the academic disciplines; however, they increase with the number of study terms. Besides the field of study, further variables such as gender and health status have a significant impact on perceptions. Conclusions: Our results show that there are differences in the perception of fairness and standard of care between academic disciplines, which might influence the interdisciplinary discussion on health care reforms and priority setting.Leibniz University Hannover/Wege in die Forschung I

    Predictors of mental health in female teachers

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    Objective: Teaching profession is characterised by an above-average rate of psychosomatic and mental health impairment due to work-related stress. The aim of the study was to identify predictors of mental health in female teachers. Material and Methods: A sample of 630 female teachers (average age 47±7 years) participated in a screening diagnostic inventory. Mental health was surveyed with the General Health Questionnaire GHQ-12. The following parameters were measured: specific work conditions (teacher-specific occupational history), scales of the Effort-Reward-Imbalance (ERI) Questionnaire as well as cardiovascular risk factors, physical complaints (BFB) and personal factors such as inability to recover (FABA), sense of coherence (SOC) and health behaviour. Results: First, mentally fit (MH+) and mentally impaired teachers (MH-) were differentiated based on the GHQ-12 sum score (MH+: < 5; MH-: ≥ 5); 18% of the teachers showed evidence of mental impairment. There were no differences concerning work-related and cardiovascular risk factors as well as health behaviour between MH+ and MH-. Binary logistic regressions identified 4 predictors that showed a significant effect on mental health. The effort-reward-ratio proved to be the most relevant predictor, while physical complaints as well as inability to recover and sense of coherence were identified as advanced predictors (explanation of variance: 23%). Conclusion: Contrary to the expectations, classic work-related factors can hardly contribute to the explanation of mental health. Additionally, cardiovascular risk factors and health behaviour have no relevant influence. However, effort-reward-ratio, physical complaints and personal factors are of considerable influence on mental health in teachers. These relevant predictors should become a part of preventive arrangements for the conservation of teachers' health in the future

    British HIV Association guidelines for the treatment of HIV-1-positive adults with antiretroviral therapy 2015

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    Evidence-Based Guidelines for Empirical Therapy of Neutropenic Fever in Korea

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    Neutrophils play an important role in immunological function. Neutropenic patients are vulnerable to infection, and except fever is present, inflammatory reactions are scarce in many cases. Additionally, because infections can worsen rapidly, early evaluation and treatments are especially important in febrile neutropenic patients. In cases in which febrile neutropenia is anticipated due to anticancer chemotherapy, antibiotic prophylaxis can be used, based on the risk of infection. Antifungal prophylaxis may also be considered if long-term neutropenia or mucosal damage is expected. When fever is observed in patients suspected to have neutropenia, an adequate physical examination and blood and sputum cultures should be performed. Initial antibiotics should be chosen by considering the risk of complications following the infection; if the risk is low, oral antibiotics can be used. For initial intravenous antibiotics, monotherapy with a broad-spectrum antibiotic or combination therapy with two antibiotics is recommended. At 3-5 days after beginning the initial antibiotic therapy, the condition of the patient is assessed again to determine whether the fever has subsided or symptoms have worsened. If the patient's condition has improved, intravenous antibiotics can be replaced with oral antibiotics; if the condition has deteriorated, a change of antibiotics or addition of antifungal agents should be considered. If the causative microorganism is identified, initial antimicrobial or antifungal agents should be changed accordingly. When the cause is not detected, the initial agents should continue to be used until the neutrophil count recovers
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