1,868 research outputs found
Reprinted in Siri/Mayr 2011
No full textSiri J, Mayr K. Management as a Symbolizing Construction? Re-Arranging the Understanding of Management. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research. 2010;11(3):Art. 21
ARTSpeak: Siri Hustvedt
No full textNotable writer Siri Hustvedt lectures on one or more of the many topics that she has explored in her writing. Siri Hustvedt is the author of a book of poetry, three collections of essays, a work of nonfiction, and six novels, including the international bestsellers What I Loved and The Summer Without Men. Her most recent novel The Blazing World was long-listed for the Man Booker Prize and won The Los Angeles Book Prize for fiction. In 2012 she was awarded the International Gabarron Prize for Thought and Humanities. She has a PhD in English from Columbia University and is a lecturer in psychiatry at Weill Cornell Medical College in New York. Her work has been translated into over 30 languages.This event is part of ARTSpeak, an interdisciplinary program presented by the departments of Fine Arts and History of Art. ARTSpeak is made possible in part through funding by the FIT Student-Faculty Corporation, the School of Art and Design, and the School of Liberal Arts
REPRINT OF Siri, Jasmin (gem. mit Katharina Mayr) (2010). Management as a Symbolizing Construction? Re-Arranging the Understanding of Management. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 11(3), Art. 21.
No full textSiri J, Mayr K. Management as a Symbolizing Construction? Re-Arranging the Understanding of Management. Historical Social Research (HSR). 2011;36(135):160-179
Computational Thinking and Coding for K-8
No full textChris Ross, Assistant Professor of Math & Physics, and Siri Anderson, Associate Professor of Education received a $1,600 Curriculum Development Award to develop a two course online graduate level program for librarians or teachers to learn how to teach coding and computational thinking to students in grades K-8
Prognostic Value of SIRI in Sepsis: A Retrospective Study and Machine Learning-Based Model Development
Get PDFYilin Zhu,1,&ast; Zhiyang Wang,2,&ast; Shifeng Li,3,&ast; Xin Xiao,3 Yujie Liu,3 Jiachen He,3 Fang Huang,3 Jun Wang3 1Department of Critical Care Medicine, Zhangjiagang Hospital Affiliated to Soochow University/The First People’s Hospital of Zhangjiagang City, Zhangjiagang, 215600, People’s Republic of China; 2Department of Emergency and Critical Care Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, 215006, People’s Republic of China; 3Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, Suzhou, 215006, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun Wang, Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, People’s Republic of China, Email [email protected] Fang Huang, Department of Critical Care Medicine, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, People’s Republic of China, Email [email protected]: In recent years, the Systemic Inflammation Response Index (SIRI) has demonstrated unique advantages in evaluating sepsis prognosis. This study aims to investigate the predictive value of SIRI for 28-day outcomes in sepsis patients, and develop and validate a prognostic model for 28-day mortality.Methods: The demographic characteristics, disease severity, laboratory tests, treatments, and outcome measures were recorded from the adult sepsis patients. The restricted cubic splines and the ROC curve analysis were employed to evaluate the relationship and predictive capability of SIRI. Next, SIRI was categorized into tertiles, and univariate and multivariate Cox regression analyses were performed to assess its association with prognosis, supplemented by Kaplan-Meier (K-M) curves, and compare mortality differences. Patients from the First Affiliated Hospital of Soochow University were randomly allocated into training and internal validation sets at a 3:1 ratio, using the Boruta algorithm and LASSO regression and a prognostic model was constructed via logistic regression, while patients from the First People’s Hospital of Zhangjiagang City served as the external validation set. Then, the predictive performance, accuracy, and clinical utility of the model were validated using the ROC curve, Hosmer-Lemeshow test, calibration curve, and decision curve analysis (DCA).Results: The 380 patients from the First Affiliated Hospital of Soochow University and 240 patients from the First People’s Hospital of Zhangjiagang City were enrolled for the present study. The restricted cubic spline analysis revealed a nonlinear increasing trend in mortality risk with rising SIRI levels. The ROC curve analysis demonstrated that SIRI has superior predictive capability than the APACHE II and SOFA scores. When SIRI was categorized into tertiles, both the univariate and multivariate Cox regression analyses identified SIRI as significantly associated to 28-day prognosis (p< 0.001). The K-M curves further confirmed that higher SIRI levels correlated to lower 28-day survival rates (p< 0.001). In the training set, the Boruta algorithm combined with LASSO regression selected six independent risk factors: blood urea nitrogen (BUN), age, phosphorus (P), lactate (Lac), mechanical ventilation (MV), and SIRI. These were incorporated into the predictive model through logistic regression analysis. The ROC curve analysis revealed that the model exhibited good predictive performance across the training set (AUC: 0.851), internal validation set (AUC: 0.908), and external validation set (AUC: 0.792). The calibration of the model was verified using the Hosmer-Lemeshow test and calibration curve, while DCA was performed to confirm its clinical utility.Conclusion: SIRI is significantly correlated to the 28-day prognosis in sepsis patients, and has excellent predictive value for short-term outcomes. The prediction model that incorporated SIRI exhibited high prognostic accuracy.Keywords: sepsis, systemic inflammation response index, prognosis, prediction model, nomogra
Wie beobachten? Was tun? Perspektiven der kritischen Systemtheorie
No full textSiri J, Möller K. Wie beobachten? Was tun? Perspektiven der kritischen Systemtheorie. In: Siri J, Möller K, eds. Systemtheorie und Gesellschaftskritik. Perspektiven der Kritischen Systemtheorie. 2016: 7-18
Systemtheorie und Diskursanalyse
No full textSiri J. Systemtheorie und Diskursanalyse. In: Möller K, Siri J, eds. Systemtheorie und Gesellschaftskritik. Perspektiven der kritischen Systemtheorie. Bielefeld: Transcript; In Press
Insurance-Based Investment Products: Regulatory Responses and Policy Issues
No full textThe chapter aims to analyse the recent reform of the EU regulatory framework as regards insurance-based investment products (IBIPs). The current regime provided for IBIPs offers stronger protection to all customers, regardless of the channel of distribution. In line with the EU plan to provide consistent cross-sectorial investor protection across all Member States, many IDD provisions are based on the corresponding MiFID II rules, even though some differences remain and should be further elaborated in connection with the inconsistencies, overlaps and gaps in the investor protection as far as the distribution of the IBIPs is concerned. Furthermore, several Member States have exercised the discretions recognised by the IDD as regards IBIPs mainly to gold plate investor protection measures. However, such an uncoordinated approach undermines the internal market’s objectives. Therefore, the chapter advises EIOPA to use its powers to coordinate Member States’ measures and ensure transparency about National Competent Authorities’ measures in this respect
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