Automatic classification of farms and traders in the pig production chain

The trade in live pigs is an essential risk factor in the spread of animal diseases. Traders play a key role in the trade network, as they are logistics hubs and responsible for large animal movements. In order to implement targeted control measures in case of a disease outbreak, it is hence strongly advisable to use information about the holding type in the pig production chain. However, in many datasets the types of the producing farms or the fact whether the agent is a trader are unknown. In this paper we introduce two indices that can be used to identify the position of a producing farm in the pig production chain and more importantly, identify traders. This was realized partially through a novel dynamic programming algorithm. Analyzing the pig trade network in Germany from 2005 to 2007, we demonstrate that our algorithm is very sensitive in detecting traders. Since the methodology can easily be applied to trade networks in other countries with similar infrastructure and legislation, we anticipate its use for augmenting the datasets in further network analyses and targeting control measures. For further usage, we have developed an R package which can be found in the supplementary material to this manuscript

Effectiveness and cost-effectiveness of four different strategies for SARS-CoV-2 surveillance in the general population (CoV-Surv Study): study protocol for a two-factorial randomized controlled multi-arm trial with cluster sampling

Background: To achieve higher effectiveness in population-based SARS-CoV-2 surveillance and to reliably predict the course of an outbreak, screening, and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic. Methods: This trial implements a two-factorial, randomized, controlled, multi-arm, prospective, interventional, single-blinded design with cluster sampling and four study arms, each representing a different SARS-CoV-2 testing and surveillance strategy based on individuals' self-collection of saliva samples which are then sent to and analyzed by a laboratory. The targeted sample size for the trial is 10,000 saliva samples equally allocated to the four study arms (2500 participants per arm). Strategies differ with respect to tested population groups (individuals vs. all household members) and testing approach (without vs. with pre-screening survey). The trial is complemented by an economic evaluation and qualitative assessment of user experiences. Primary outcomes include costs per completely screened person, costs per positive case, positive detection rate, and precision of positive detection rate. Discussion: Systems for active surveillance of the general population will gain more importance in the context of pandemics and related disease prevention efforts. The pandemic parameters derived from such active surveillance with routine population monitoring therefore not only enable a prospective assessment of the short-term course of a pandemic, but also a more targeted and thus more effective use of local and short-term countermeasures. Trial registration: ClinicalTrials.gov DRKS00023271. Registered November 30, 2020, with the German Clinical Trials Register (Deutsches Register Klinischer Studien

The Open Anchoring Quest Dataset: Anchored Estimates from 96 Studies on Anchoring Effects

People’s estimates are biased toward previously considered numbers (anchoring). We have aggregated all available data from anchoring studies that included at least two anchors into one large dataset. Data were standardized to comprise one estimate per row, coded according to a wide range of variables, and are available for download and analyses online (https://metaanalyses.shinyapps.io/OpAQ/). Because the dataset includes both original and meta-data it allows for fine-grained analyses (e.g., correlations of estimates for different tasks) but also for meta-analyses (e.g., effect sizes for anchoring effects)

Bayesian Changepoint Analysis

In this thesis, we elaborate upon Bayesian changepoint analysis, whereby our focus is on three big topics: approximate sampling via MCMC, exact inference and uncertainty quantification. Besides, modeling matters are discussed in an ongoing fashion. Our findings are underpinned through several changepoint examples with a focus on a well-log drilling data.In dieser Arbeit arbeiten wir an der Bayes'schen Changepointanalyse, wobei unser Fokus auf drei großen Themen liegt: approximatives Sampling via MCMC, exakte Inferenz und Quantifizierung von Unsicherheit. Außerdem werden Modellierungsfragen fortlaufend diskutiert. Unsere Ergebnisse werden durch mehrere Changepoint Beispiele untermauert, wobei der Schwerpunkt auf einem Bohrkern Datensatz liegt

Challenges of Interdisciplinary Cooperation - Adapting service blueprinting to product engineering

Designing processing machines or industrial products has become more and more complex. To handle the increasing complexity, many different stakeholders from various domains work together in interdisciplinary project teams. The present paper explores how blueprints can be applied to interdisciplinary product engineering processes including various disciplines with different motives and wishes. The aim of the presented blueprint variation is to chart the engineering design process using the example of a sales department in order to uncover operational weaknesses and highlight possible improvements. Opportunities and limitations of the presented adaptation are discussed

State-of-the-Art of Education on Solar Energy in Urban Planning

This report focuses on education in order to strengthen the knowledge and competence of relevant stakeholders in solar energy in urban planning. The core of this study is to create substantial links between research and education as well as between research and practice. Knowledge gaps in current education were investigated, reasons for these gaps were identified and solutions and strategies are proposed to overcome these shortcomings