Production of calcium carbonate from steelmaking slag and captured CO2- optimisation of the carbonation process and product quality

The X2PCC pilot plant produces precipitated calcium carbonate (PCC) from calcium extracted from steel slag and CO2 gas. This work investigates the carbonation process in order to optimise it to produce PCC of the desired morphology and size. A literature review is presented showing the potential effects of different parameters on the morphology, size and quality of the PCC produced. Experiments are conducted varying different parameters and the morphology and size of the PCC are analysed based on this. Supersaturation is seen as key to understanding and controlling the process, so a model is built to show the supersaturation of the system. This involves activity coefficient modelling using the Pitzer model and estimations of the CO2 solubility and solubility product, Ksp. Pure rhombohedral calcite is produced and needle-like aragonite is produced up to a purity of 70%

Development of protocol for reduction in central line associated blood stream infections

Background: Central line associated blood stream infections (CLABSIs) are a highly expensive and deadly hospital associated infections (HAIs). Recent studies focus on reducing the CLABSI rate in both intensive care units (ICUs) and non-intensive care units. Each study focused on multiple aspects to reduce CLABSIs at the insertion of the line and the maintenance period, which is the length the central line, remains in place after the insertion. The results have shown there are many possible ways to reduce CLABSIs in the hospital setting. Objectives: The purpose of this study is to evaluate the effectiveness of an audit tool to assess the compliance of nurse documentation and bedside duties of central line care and maintenance in a University-affiliated tertiary care hospital. The implementation of this audit is expected decrease the hospital’s CLABSI rate. Methods: This study has two portions. The first is a prospective examination of nurse documentation and bedside practices for patients with central lines in ICUs and non-ICUs. The second portion is a retrospective analysis of documentation of patients that developed CLABSIs compared to those who did not develop a CLABSI. Results: All units increased compliance in 90.4% of documentation and bedside assessments. Weekly trends indicated increasing compliance as the audit period progressed. The retrospective analysis also revealed that daily line necessity (evidence that a patient still requires the central line in place) was not properly documented for patients that developed CLABSIs compared to patients that did not develop a CLABSI (n=621, OR=4.99, Fisher exact P=0.016). Conclusions: These results suggest initial success in increasing compliance by nurses and other clinicians providing care and maintenance of central lines. The retrospective analysis shows the importance of documenting daily line necessity in order to remove unnecessary central lines which may lead to infections. Future studies should be carried out to determine the cause of poor compliance. Public Health Significance: The audit used in this study reflects prior research shown to reduce the CLABSI rate. With further use of this audit, the CLABSI rate should be reduced which can be help decrease patient morbidity and mortality and decrease costs to the patient and hospital

Share experiences : receiving word of mouth and its effect on relationships with donors

Purpose: Although antecedents and consequences for the sender of word of mouth (WOM) are well evaluated in many research fields, non-profit service research focusing on consequences for WOM receivers is limited. Thus, the purpose of this paper is to provide evidence for the positive effect that WOM has on commitment, trust, satisfaction and identification (relationship-related factors) and on intentional loyalty of blood donors. Furthermore, the role of the social reference group and the incentive ethics are analysed. Design/methodology/approach: Blood donors of the German Red Cross Blood Donor Service were invited to take part in an online survey during May/June 2016. A total of 702 (23.74 per cent) blood donors, who first donated in 2015/2016, participated. The data were analysed using partial least squares structural equation modelling. Findings: The results provide evidence that the mere presence of receiving WOM positively influences commitment, satisfaction and identification as well as intentional loyalty. The negative moderation effect of incentive ethics was partially confirmed. Practical implications: This study recommends using WOM approaches to bind donors but first evaluating the exact consequences of provided WOM rewards. WOM is an effective strategy, and non-profit organizations (NPOs) should use this to strengthen their relationship with donors. Originality value: The paper provides and tests a theoretical framework to evaluate the impact of receiving WOM on relationship-related factors and intentional loyalty. It fills a gap in current discussions about the effectiveness of WOM as a marketing strategy to strengthen donor–NPO relationships

Efficient Numerical Optimization for Parallel Dynamic Optimal Power Flow Simulation Using Network Geometry

In this work, we present a parallel method for accelerating the multi-period dynamic optimal power flow (DOPF). Our approach involves a distributed-memory parallelization of DOPF time-steps, use of a newly developed parallel primal-dual interior point method, and an iterative Krylov subspace linear solver with a block-Jacobi preconditioning scheme. The parallel primal-dual interior point method has been implemented and distributed in the open-source PETSc library and is currently available. We present the formulation of the DOPF problem, the developed primal dual interior point method solver, the parallel implementation, and results on various multi-core machines. We demonstrate the effectiveness our proposed block-Jacobi preconditioner and various Krylov subspace methods at improving parallel performance

Anwendungen von #SAT Solvern für Produktlinien: Masterarbeit

Product lines are widely used for managing families of similar products. Typically, product lines are complex and infeasible to analyze manually. In the last two decades, product-line analyses have been reduced to satisfiability problems which are well understood. However, there are methods for which satisfiability is not sufficient. Recently, researchers begun to reduce other problems to #SAT. Yet, only few applications have been considered and those are fairly limited in their scope. Furthermore, the authors mainly propose ad-hoc solutions that are only applicable under certain restrictions or do not scale to large product lines. In this thesis, we aim show the benefits of applying #SAT for the analysis of product lines. To this end, we make the following contributions: First, we summarize applications dependent on #AT considered in the literature and propose new applications to motivate the usage of #SAT technology. Second, we present a variety of algorithms and optimizations for these applications including new proposals. Third, we empirically evaluate 10 proposed algorithms with 14 off-the-shelf #SAT solvers on 131 industrial feature models to identify the fastest algorithms and solvers. Our results show that for each analysis at least one algorithm and solver scale on a vast majority of the feature models, whereas Linux and an automotive model not be analyzed at all. In addition, our results further reveal the benefits of knowledge compilation to deterministic decomposable negation normal form for performing counting-based analyses. Overall, our work shows that #SAT dependent analyses for feature models open a new variety of different applications and scale to a large number of industrial feature models.Produktlinien sind weit verbreitet für die Verwaltung von Familien verwandter Pro- dukte. In der Regel sind Produktlinien komplex und manuell schwer zu analysieren. In den letzten zwei Jahrzehnten wurden Produktlinienanalysen auf Erfüllbarkeit- sprobleme reduziert, für welche es eine Vielzahl an effizienten Werkzeugen gibt. Allerdings ist Erfüllbarkeit nicht für alle Analysen hinreichend. Kürzlich haben Forscher damit begonnen, andere Probleme auf #SAT zu reduzieren. Es wur- den jedoch nur wenige Anwendungen in Betracht gezogen und auch der Anwen- dungsbereich ist begrenzt. Darüber hinaus schlagen die Autoren hauptsächlich Ad-hoc-Lösungen vor, die nur unter bestimmten Einschränkungen der Produktlin- ien anwendbar sind oder nicht für große Produktlinien skalieren. In dieser Arbeit zeigen wir die Vorteile von #SAT Anwendungen für Produtlinien auf. Unser wis- senschaftlicher Beitrag besteht aus den folgenden drei Punkten: Zuerst fassen wir die in der Literatur betrachteten #SAT-Anwendungen zusammen und schlagen neue Anwendungen vor, um den Einsatz von #SAT-Technologien zu motivieren. Zweit- ens stellen wir eine Vielzahl von Algorithmen und Optimierungen für diese Anwen- dungen vor, einschließlich neuer Vorschläge. Drittens führen wir eine empirische Evaluation von 10 der vorgeschlagenen Algorithmen mit 14 #SAT-Solvern auf 131 industriellen Feature-Modellen aus, um die schnellsten Algorithmen und Solver zu identifizieren. Die Ergebnisse der Evaluation zeigen, dass wir für jede Analyse wenig- stens einen Algorithmus und Solver identifiziert haben, die für industrielle Feature- Modelle skalieren. Dazu sind die Ergebnisse ein starker Indikator für die Vorteile des Einsatzes von d-DNNFs bei #SAT-Anwendungen. Insgesamt zeigt unsere Ar- beit, dass #SAT-abhängige Analysen für Feature-Modelle eine Vielzahl neuer un- terschiedlicher Anwendungen ermöglicht und für viele industirelle Feature-Modelle skaliert