Three Essays on Estimating and Forecasting Residential Markets

This dissertation covers three different aspects of estimating and forecasting residential real estate markets. Chapter 1: The first chapter aims to examine whether there are differences between the long and short-term relationship of house prices and interest rates. The elasticity of house prices to monetary policy changes, e.g. via interest rates, is from a theoretical perspective and in the long-run negative. However, house prices adapt in the short-run dynamically to economic, financial, institutional and demographic factors. In this chapter, we confirm the aforementioned negative relationship for the Nordic housing markets but provide evidence of drastic deviations in the short run, especially in the context of the financial crisis. Chapter 2: The second chapter tests the prediction accuracy of two innovative methods proposed along the hedonic debate: The Geographically Weighted Regression (GWR) and the Generalized Additive Model (GAM). We compare the predictions of linear, spatial and non-linear hedonic models based on a very large dataset in Germany. The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. However, the simplicity of the OLS approach is not substantially outperformed by the semi-parametric approach. Since sample size is essential when estimating and forecasting hedonic models this study covers more than 570,000 observations which is – to the authors' knowledge – one of the largest datasets used for spatial real estate analysis. Chapter 3: Google Trends offers virtually unlimited, instantaneously available, spatially and textually adjustable and, in addition, free data. Real estate markets appear to be particularly well-suited for search volume related studies, as the “products” of this market involve a large financial commitment, which demands an extensive information gathering process. Although Google Trends data can be accessed already since 2008, many interpretation and usage misunderstandings can be found amongst the literature. Therefore, the third chapter will focus on two main objectives: Firstly, I will give an overview of what Google data is in the first place and what the potential pitfalls are. Secondly, I will conduct an empirical analysis to find out, whether the results are still in line with the literature after accounting for those difficulties

BlueCollar: Optimizing Worker Paths on Factory Shop Floors with Visual Analytics

The optimization of a factory\u27s productivity regarding quality and efficiency is an important task in the manufacturing domain. To optimize the productivity, production lines are optimized to have short transportation paths and short processing times at the stations that process intermediate components or the final product. A factory\u27s layout is a key factor in this optimization aspect. This optimization mostly comprises the machine tools\u27 positions with respect to places where supply goods are being delivered and other tools are stationed, often neglecting the paths that workers need to take at the shop floor. This impairs a factory\u27s productivity, as machines may need to wait for workers, who operated another machine and are still on the way due to the long distance between the machines. In this work, we present BlueCollar, a visual analytics approach that supports layout planners to explore and optimize existing factory layouts regarding the paths taken by workers. Planners can visually inspect the paths that workers need to take based on their work schedule and the factory\u27s layout. An estimation of distribution algorithm supports them in choosing which layout elements, e.g., shared tool caches, to relocate. Its intermediate and final results are used to provide visual cues for suitable relocation areas, and to suggest new layouts automatically. We demonstrate our approach through an application scenario based on a realistic prototype layout provided by an external company

The Geriatric-Oncologic Conference, a new approach in decision-making

Onkologen entscheiden auf der Basis von Alter und klinischem Eindruck täglich, welche Patienten welche Chemotherapie erhalten sollen. Bei älteren Patienten sind diese Entscheidungen aufgrund fehlender Evidenz von der persönlichen Erfahrung und „Behandlungsphilosophie“ des jeweils behandelnden Onkologen abhängig. Ein umfassendes geriatrisches Assessment wurde vorgeschlagen, um diese Entscheidung datenbasiert und reproduzierbar treffen zu können. Beide Strategien haben Vor- und Nachteile. In der vorliegenden Arbeit wird eine Synthese beider Ansätze beschrieben und weiter untersucht. Bei der Kombination beider Ansätze wird innerhalb einer geriatrisch-onkologischen Konferenz auf der Datengrundlage eines umfassenden geriatrischen Assessments und zusätzlich unter Einbeziehung des Behandlers, eines erfahrenen Onkologen und eines Geriaters sowie der das Assessment durchführenden Berufsgruppen eine gemeinsame Entscheidung getroffen. Anhand der Daten eines umfassenden geriatrischen Assessments von über 400 Patienten, die an dieser Klinik 2014 und 2015 routinemäßig bei allen stationären Patienten, die 65 Jahre oder älter waren, vor Einleitung einer spezifischen Therapie erhoben wurden, wurde gezeigt, dass die Entscheidung einer geriatrisch-onkologischen Konferenz entscheidend von der Klassifizierung allein aufgrund des Assessments, aber auch von der persönlichen Einschätzung des Behandlers abweicht. Es wurde ein statistisches Modell erstellt, welches anhand der Assessmentdaten die Klassifizierung von Patienten in einer geriatrischonkologischen Konferenz vorhersagt. Bis zur weiteren prospektiven Validierung und Bewertung der denkbaren Entscheidungsstrategien ist eine geriatrisch-onkologische Konferenz am besten geeignet, die Therapiefähigkeit geriatrisch-onkologischer Patienten zu beurteilen, da sie alle verfügbaren Informationen berücksichtigen und damit die maximale Patientensicherheit gewährleisten kann.Background A comprehensive geriatric assessment (CGA) is recommended before treating elderly cancer patients. However, it is not proven that additional information from the CGA will change our treatment decision. Methods 421 cancer patients, 65 years or older, were judged by their treating oncologist regarding fitness for chemotherapy. Accompanying a CGA was performed and each patient was discussed in a multidisciplinary board (MB) including a geriatrician. The differences between the judgements of the treating oncologist, the MB, and a classification based solely on the CGA were examined. Additionally, a statistical model of the decision-making process within the MB, based on the findings of the CGA was established and evaluated. Results Treating oncologist and MB judged 12% and 15% of the patients as frail, 41% and 38% as vulnerable, 46% and 47% as fit. 83% of congruence was observed. Based on the proposal of Balducci, 55% of the patients were classified as frail, 30% as vulnerable and 15% as fit. 34% of congruence with treating oncologist judgement was observed. In the 2-stage logistic model the activities of daily living and the mini mental state examination (MMSE) discriminated between frail and vulnerable or fit. Tinetti test, age, Charlson comorbidity index, living alone, MMSE and mini nutritional assessment discriminated between vulnerable and fit. The statistical models were able to differentiate with an accuracy of 95% between frail and vulnerable or fit and 83% between vulnerable and fit. Conclusions To our experience, the judgement of an experienced oncologist is well comparable with the judgement of a MB. Nevertheless, for some patients discussion of CGA data in the MB may essentially change treatment decisions. A logistic regression model of the decision making process within the MB may replace the elaborate team discussion, if a conference is not feasible

Erarbeitung eines Vorschlags einer einheitlichen, sektoren- und berufsgruppenübergreifenden Basisdokumentation für die Kinder-, Jugend-, und Familienpsychosomatik – Entwicklung und Evaluation eines Instrumentariums zur Qualitätssicherung aus multidisziplinärer Perspektive unter besonderer Berücksichtigung der Erfassung sozialer Dimension psychischer Erkrankung

Hintergrund: In Psychiatrie, Psychosomatik, Psychotherapie und komplementärer medizinischer Fachgebiete (P-Fächern), werden Basisdokumentationen (BaDo‘s) als Instrumente für die Qualitätssicherung (QS) eingesetzt. Mit der Psy-BaDo-PTM konnte sich für die psychosomatische Behandlung erwachsener Patienten eine einrichtungs-, sektoren- und berufsgruppenübergreifende BaDo etablieren. Ein vergleichbares Instrument für die Kinder-, Jugend- und Familienpsychosomatik fehlt bislang. Zielstellung: Das Ziel der vorliegenden Arbeit bestand in der Entwicklung eines Vorschlags für eine einrichtungs-, sektoren- und berufsgruppenübergreifende BaDo für die Kinder-, Jugend- und Familienpsychosomatik. Aufgrund der Relevanz für die Therapieevaluation wurden die psychometrischen Eigenschaften des SDQ und KINDL-R evaluiert. Das Potential der entwickelten BaDo, die soziale Dimension psychischer Erkrankung und sozialtherapeutische Interventionen zu erfassen, wurde untersucht. Methode: Nach einer systematischen Literaturrecherche wurden in einer qualitativen Dokumentenanalyse Schnittmengen zwischen BaDo’s für Kinder und Jugendliche sowie Erwachsene herausgearbeitet. Kinder- und jugendspezifische Aspekte wurden identifiziert. Aufgrund deskriptiv-statistischer Analysen und konzeptueller Überlegungen wurde ein Merkmalkatalogs für die Kinder-, Jugend- und Familienpsychosomatik zusammengestellt. Die Evaluation der psychometrischen Eigenschaften der deutschsprachigen SDQ und KINDL-R Versionen erfolgte durch eine metaanalytische Aggregation vorliegender Befunde. Eine Bewertung wurde auf Grundlage eines Kriterienkatalogs des Deutschen Kollegiums für Psychosomatische Medizin (DKPM) vorgenommen. Die Untersuchung der faktoriellen Struktur und der Known Groups Validität des Kid-KINDL erfolgte durch Sekundäranalyse eines Datensatzes 8- bis 11-jähriger psychisch kranker Kinder, die sich zum Erhebungszeitpunkt in psychosomatischer Krankenhausbehandlung befanden. Auf Grundlage einer theoretischen Ableitung psycho-sozialer Kontextfaktoren wurden BaDo-Items identifiziert, über die eine Kontextualisierung psychischer Erkrankung vorgenommen und sozialtherapeutische Interventionen ausgewertet werden können. Ergebnisse: Es konnte eine BaDo für die Kinder- und Jugendpsychosomatik erarbeitet werden. Eine Kinder- und Jugendspezifikation wurde durch die Erfassung biographischer und familienanamnestischer Daten erzielt. Die Erhebung soziodemographischer Merkmale wurde konzeptuell angepasst. Trotz einiger Limitationen sprach die zusammenfassende Bewertung nach DKPM-Kriterien für den Einsatz des SDQ und KINDL-R in der QS. In der Evaluation des Kid-KINDL zeigte ein Modell mit Item-Doppelladungen krankheitsassoziierter Items auf den HRQoL-Dimensionen und zwei mit den HRQoL Faktoren unkorrelierten Psychopathologie-Faktoren im Vergleich den besten Modell-Fit. Die Psy-BaDo-PTM-KiJu ermöglicht eine relativ breite Erfassung psycho-sozialer Kontextfakten. Die Evaluation sozialtherapeutischer Interventionen erscheint aus Perspektive Klinischer Sozialarbeit allerdings unzureichend. Diskussion: Aktuell wird die Psy-BaDo-PTM-KiJu in der Praxis erprobt. Auf Grundlage dieser Erfahrungen sollte die BaDo überarbeitet werden. Perspektivisch wäre die Konsentierung des Merkmalkatalogs durch Berufs- und Fachverbände wünschenswert. Mit dem SDQ und dem KINDL-R konnten zwei international weit verbreitete Instrumente in die BaDo integriert werden. Allerdings zeigte die Untersuchung auch, dass es an systematischen Überblicksarbeiten zu psychometrischen Eigenschaften generischer psychodiagnostischer Instrumente für Kinder und Jugendliche fehlt. In der Untersuchung des Kid-KINDL ergaben sich deutliche Hinweise darauf, dass aufgrund von Item-Doppelladungen einige HRQoL-Dimensionen durch das Instrument nicht valide erfasst werden. Trotz dieser Limitationen erscheint der Kid-KINDL für die Erfassung der HRQoL-Dimensionen Selbstwert, Familie und Freunde geeignet. Es konnte gezeigt werden, dass BaDo-Daten für die Analyse psycho-sozialer Faktoren durchaus interessant sind. Eine adäquate Berücksichtigung sozialtherapeutischer Leistungen in BaDo‘s würde dabei helfen, das multi-disziplinäre psychosomatische Behandlungsspektrum in der QS abzubilden

Improving students' performance via case-based e-learning

BackgroundThe integration of interdisciplinary clinical reasoning and decision-making into the medical curriculum is imperative. Novel, high-quality e-learning environments, encompassing virtual clinical and hands-on training, are essential. Consequently, we evaluated the efficacy of a case-based e-learning approach.MethodThe impact of a case-based interdisciplinary e-learning environment with an integrated question/feedback system on medical students' academic performance was examined in a cross-sectional sample of different study years, longitudinally matched per academic year. Differences between the groups were analyzed through an unpaired t-test.ResultsThe exam results of students who participated in the e-learning course (n = 296) were compared with those of all students at the university (n = 5,800). A statistically significant (p-value < 0.01) improvement in students' final examination grades was observed through intensive training on the offered platform.ConclusionsOur analyses demonstrated the positive influence of a case-based e-learning approach within the Viennese medical curriculum

Risk factors of screw misplacement by using intraoperative computed tomography image-guided navigation: a series of 1471 screws [Abstract]

Background: The aim of this study was to identify potential risk factors for screw misplacement after using an intraoperative computed tomography (iCT) guided navigation for Screw insertion. Methods: A retrospective analysis of all patients following iCT navigated spinal pedicle screw placement between October 2015 and March 2022 was performed. Navigated drilling of the pedicle was followed by screw placement (with and without via K-wire). Screw position was checked by a further iCT scan . Screw position was assesed according to the Gertzbein-Robbins classification and the rates of screws actually revised intraoperatively were calculated. Results: 256 consecutive patients were identified (50,39% male, 49,61% female). A total of 1471 Screws were implanted. Median age was 67 years. The all-over revision rate was 4,49%. Screws were placed in all spinal regions. Degenerative spine disease was the most common diagnosis (43,44%). No significant differences in revision rates were found for gender and age. Lumbar spine (6,25%), thoracic spine (5,86%), tumor (6,40%) and infection (7,98%) diagnosis were associated with highest revision rate. We also found significantly increased revision rates for overweight (BMI 25 to 30) and obesity (BMI > 30) at 4,17% and 7,38%. Conclusions: The all-over revision rate was 4,49%. The highest revision rates were observed for tumor (6,40 %), infection patients (7,98 %), lumbar spine (6,25 %) and thoracic spine (5,86 %). Overweight and obesity also seems to be a significant risk factor for screw misplacement (BMI30: 7,38%). None of the patients suffered from any neurovascular damage. No secondary operation to revise the misplaced screws was required

WHAT WE NEED FOR ENCODING OF MEMORY AND EMOTIONAL RECONSOLIDATION

Background: It is known that an interactive design and good participants’ involvement strengthens the motivation to engage in learning processes. Previous research suggests attitude-behaviour consistency with relevance of subjective meaning and interest in learning. This observational study aims to measure the attitude of medical students. Methods: The connotative meaning and perception of e-learning were explored. A semantic differential scale was given to all students (N=328) of a case-based blended-learning (CBBL) course, 296 medical students were included in this study. Results: The online-survey completion rate was 100%. An exploratory principal components analysis with varimax rotation was performed. Five components could be extracted that explained 47.21% of the total variance. The five components are best described by the following adjectives taken from the item pool: “soft, emotional, playful”, “clear and organised”, “vigorous and serious”, “vivid and outgoing”, “economical and introverted”. An additional qualitative analysis revealed relevant positive connotations ascribed to e-learning by the students: freedom in time and space for learning, interdisciplinary approach and communication, playfulness and clear, structured procedure. Conclusion: Our study demonstrated that a specific set of aspects is essential for students to feel comfortable and affectcognitively engaged to learn and gain the best exam grades

Inflation Forecasting in Turbulent Times

Recently, many countries were hit by a series of macroeconomic shocks, most notably as a consequence of the COVID-19 pandemic and Russia's invasion in Ukraine, raising inflation rates to multi-decade highs and suspending well-documented macroeconomic relationships. To capture these tail events, we propose a mixed-frequency Bayesian vector autoregressive (BVAR) model with t-distributed innovations or with stochastic volatility. While inflation, industrial production, oil and gas prices are available at monthly frequencies, real gross domestic product (GDP) is observed at a quarterly frequency. Thus, we apply a mixed-frequency framework using the forward-filtering-backward-sampling algorithm to generate monthly real GDP growth rates. We forecast inflation in those euro area countries which extensively import energy from Russia and therefore have been heavily exposed to the recent oil and gas price shocks. To measure the forecast performance of our mixed-frequency BVAR model, we compare these inflation forecasts with those generated by a battery of competing inflation forecasting models. The proposed BVAR models dominate the competition for all countries in terms of the log predictive density score

Numerical Investigation of the Effects of Post-Combustion due to Fuel Outflow in Bleed Engine Cycles of a Retro Propulsion-Assisted Launch Vehicle

Reusable launch vehicles (RLV) have the potential to be a resource- and cost-efficient alternative to conventional space transport systems. Several first stages of RLVs are in the maturing process and the European long term strategy aims towards the development and characterization of RLV relevant technologies for their next generation of launchers. We are basing our studies on the EU funded Retro Propulsion Assisted Landing Technologies (RETALT) project, which was formed with the goal of investigating Vertical Take-off Vertical Landing (VTVL) launch vehicles. In this paper, the first stage of the VTVL Two Stage to Orbit (TSTO) RETALT1 configuration will be used for the assessment of thermal loads during the flight trajectory. The mission plan for the first stage of the RETALT1-vehicle is to return either to the launch pad or a drone ship via a re-entry burn and a retro propulsion maneuver. During this retro propulsion phase high thermal loads are acting on the rocket structure and especially the landing legs, the base plate and the aerodynamic control surfaces. These thermal loads due to the main engine exhaust of the RLV have been characterized in previous studies by Laureti et al. Only little research has been devoted to the topic of post combustion due to the outflow of gas generators and air vents of cryogenic fuel tanks in VTVL-configurations in general. Owing to these secondary exhaust jets, unburned hydrogen is ejected near the high temperature outflow of the main engines, which could lead to a significant post combustion with the surrounding atmospheric oxygen and deviating thermal loads along the vital parts of the rocket structure. In order to provide an assessment of the additional influence of the post combustion and thermal loads, Computational Fluid Dynamics (CFD) simulations are carried out using the DLR-TAU code with the Reynolds Averaged Navier Stokes (RANS) method. As the post-combustion of the nozzle- and gasgenerator-outflow is to be observed, a reduced Jachimowsky mechanism for a species mixture of the liquid hydrogen, liquid oxygen combustion mixture and ambient air is applied as chemistry model. In this publication the validity of the computational mesh by means of a GCI-study and the influence of the turbulence modeling with different approaches is to be investigated. With these results first observations of the flow field characteristics and the thermal loads acting on the RLV will be done in order to identify the simulation parameters, including crucial points along the flight trajectory for investigations of the heat flux distribution across the surface structures of the vehicle