12 research outputs found
The Impact of International Financial Integration on Industry Growth
No full textThe empirical relationship between financial openness and growth is examined in this paper. In contrast to a large body of cross-country work investigating this link, I study the impact of financial integration on growth at the industry level. This paper provides evidence that financial openness has a positive effect on growth of industrial sectors, regardless of their characteristics. Moreover, industries that rely relatively more on external finance grow disproportionately faster in countries with more integrated financial systems. However, this industry-specific effect of financial openness decreases when I control for the development of the domestic financial system. Finally, the hypothesis that financial integration improved growth also by enhancing the functioning of the domestic financial system is tested. I find evidence of this indirect transmission channel of financial openness.Financial Integration, Financial Development, Growth
Effects of personality on postdivorce partnership trajectories
No full textPersonality is known to be a key predictor for several aspects of close relationship functioning. Most likely, the influence of this psychological factor is even growing in contemporary societies, where the individual life biography is increasingly the result of personal preferences and less influenced by normative expectations and cultural institutions. In an era of high relationship instability, more and more people engage in a second union. Although it becomes increasingly relevant to study the effects of personality on close relationship functioning in higher order unions, this remained understudied until now. This study examines the impact of personality on partnership trajectories following divorce. First, we construct a typology of eight partnership trajectories, capturing the occurrence, order, and timing of different partnership events (e.g., repartnering, cohabiting, getting married) in the first 7 years after separation. Then, we use multinomial logistic regression to examine the association between personality and the post-separation partnership trajectories, thereby controlling for sociodemographic variables. The analyses are based on data from a large-scale representative survey, the Divorce in Flanders Survey. Results show that personality and sociodemographic factors are both important determinants for explaining post-separation partnership trajectories. Extraversion tends to increase the likelihood and speed of repartnering. Neuroticism lowers the stability in partnerships. Conscientiousness is related with a higher likelihood to remarry. A higher age at separation and the presence of children at home decrease the likelihood to repartner, while education increases this. The present study delivers an important contribution for unraveling part of the complex association between personality and partner relationship dynamics.sponsorship: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: An Katrien Sodermans received funding KU Leuven postdoctoral grant funding. Sofie vanassche received funding from the Research Foundation Flanders (FWO). (KU Leuven postdoctoral grant, Research Foundation Flanders (FWO))status: Publishe
Business models for building material circularity: Learnings from frontrunner
No full textOne of the expected key outcomes of the Horizon 2020 BAMB (Buildings As Material Banks) project is new business models for material circularity. The team has interviewed four “frontrunner” cases which have pioneered in incorporating elements of building circularity. The study included well-known cases such as the new Venlo city hall (the Netherlands), PROgroup (Luxembourg), Rotor DC (Belgium) and Karlstad hospital (Sweden), while taking a fresh focus on business aspects such as value propositions, stakeholders, financials and operations. Preliminary analysis suggests that successful circular building projects are devised with a holistic view on various sustainability elements and ecosystem stakeholders. In comparison to more developed building sustainability elements such as energy, material circularity is still rather new in many aspects. Related business models vary significantly in maturity depending on product/material category, overall with ample room for growth. Supplier buyback agreements and product-service systems are being developed, though how to put retrieved items back into the economy, as well as how to establish solid financial cases for involved stakeholders, are among the topics which still need further substantiation. Encouraging advance has been made in deconstruction business models, while more attention is needed to developing second-hand market demand. The potentials of public procurement and regulatory incentives as additional key drivers are also to be further investigated
Hurdles in the investigation of influent fractionation for measurement campaigns under diluted wastewater conditions
No full textWorking with knowledge in the automotive supply chain
No full textNotes: February 2002Notes: Includes bibliographical references (p. 31-32)http://deepblue.lib.umich.edu/bitstream/2027.42/1486/2/95574.0001.001.pd
Correction to: Vena cava filters in patients presenting with major bleeding during anticoagulation for venous thromboembolism (Internal and Emergency Medicine, (2019), 14, 7, (1101-1112), 10.1007/s11739-019-02077-5)
No full textIn the original publication, part of the conflict of statement was incorrectly published as “Dr. Bikdeli reports that he was approached by lawyers on behalf of plaintiffs in litigation related to IVC filters”. The correct statement should read as “Dr. Bikdeli reports that he is a consulting expert (on behalf of the plaintiff) for litigation related to a specific type of IVC filters”. In addition, the affiliation of first author was incorrectly published. The corrected affiliation is given in this erratum
A machine learning approach to identify patients at risk for long-term consequences after pulmonary embolism
No full textPulmonary embolism (PE) can result in long-term sequelae, such as post-PE syndrome, including persistent dyspnea and chronic thromboembolic pulmonary hypertension (CTEPH). Existing prediction tools for severe post-PE complications lack sensitivity and specificity. This study aimed to develop a machine learning model to identify patients at risk for long-term consequences after PE. Using data from the RIETE registry, the largest prospective international PE registry, we developed supervised machine learning models to identify patients at increased risk of CTEPH and post-PE syndrome. Our approach involved data preprocessing, model training via random forest algorithm, and validation through Monte-Carlo cross-validation. The performance of the CTEPH prediction model was benchmarked against an existing score. Of the 57,981 PE patients in the RIETE registry, 5,217 were eligible for inclusion. Median age was 68 years, with 50.6% men. Machine learning was based on 111 predictor variables, with 171 patients (3.3%) developing CTEPH. The CTEPH model demonstrated good performance with an AUC of 0.74 (95%CI: 0.73-0.75), significantly outperforming the existing CTEPH prediction score (0.57; 0.54-0.61). Additionally, 1,310 (25.1%) patients were defined as having post-PE syndrome six months after index PE. The post-PE syndrome model showed poorer performance with an AUC of 0.62 (0.61-0.62). Key predictor variables across both models included chest pain at presentation, PE location, troponin, side of clot, and dyspnea at presentation. Machine learning models show promise in predicting CTEPH but are less effective for post-PE syndrome. Future refinement, including integrating imaging data, is necessary to improve predictive performance and clinical utility.
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