The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been recognized as inflammatory markers and used as prognostic makers in various cancers. The present study sought to investigate the prognostic role of NLR and PLR in Chinese patients with glioma. Clinical data, including NLR, PLR and overall survival (OS), were collected from 112 patients who underwent surgery to treat primary glioma. Kaplan-Meier survival analysis as well as uni- and multivariate Cox r...

We study time-harmonic Maxwell's equations in meta-materials that use either perfect conductors or high-contrast materials. Based on known effective equations for perfectly conducting inclusions, we calculate the transmission and reflection coefficients for four different geometries. For high-contrast materials and essentially two-dimensional geometries, we analyze parallel electric and parallel magnetic fields and discuss their potential to exhibit transmission through a sample of meta-mate...

We introduce a set of new Value-at-Risk independence backtests by establishing a connection between the independence property of Value-at-Risk forecasts and the extremal index, a general measure of extremal clustering of stationary sequences. We introduce a sequence of relative excess returns whose extremal index has to be estimated. We compare our backtest to both popular and recent competitors using Monte-Carlo simulations and find considerable power in many scenarios. In an applied s...

One way to reduce emissions from the consumption of electricity is switching to green electricity suppliers. This paper identifies the determinants of adopting green electricity and the effect on electricity consumption, using panel data on more than 9,000 households. To control for potential self-selection into green electricity tariffs, an endogenous dummy treatment effects model is estimated. The results suggest that wealthier and better-educated households are more likely to adopt gr...

Industrielle Betreibermodelle sind in den vergangenen Jahren in den Fokus des praktischen und wissenschaftlichen Diskurses gerückt, da mit ihnen umfassende Potenziale für Anbieter und Nachfrager realisiert werden können. Gleichzeitig konnten in übergeordneten Forschungsgebieten bereits vielfältige Erkenntnisse zum Vertrieb komplexer Produkt- Dienstleistungsbündel und industrieller Problemlösungen generiert werden. Allerdings sind industrielle Betreibermodelle hochgradig individuelle Geschäfts...

In dieser Arbeit wird eine Messung der CP-Asymmetrien Sf und S-f in B0→D^∓ π^±-Zerfällen präsentiert. Der analysierte Datensatz enthält dabei Ereignisse aus Proton-Proton-Kollisionen bei Schwerpunktsenergien von 7 und 8 TeV, die in den Jahren 2011 und 2012 vom LHCb-Detektor aufgenommen wurden und entspricht einer integrierten Luminosität von 3 fb-1. Die CP-Asymmetrien sind gemessen als Sf=0.058±0.020(stat.)±0.011(syst.), S-f =0.038±0.020(stat.)±0.007(syst.). Diese Ergebnisse sind präzise...

Green and open spaces are important components of green infrastructure. They offer a range of different ecosystem services society benefits from. Due to ongoing urbanisation and densification processes many urban and peri-urban green and open spaces disappear or degrade in quantity and quality, with negative impact on their ecosystems. The decline of the ecological functions of nature and landscape also weakens their social and economic merits, which are especially important for society. Henc...

In many technical fields, high-strength steels like AISI 4140 are commonly used for highly dynamically loaded parts. Increasing demands on weight, performance and efficiency of the automotive industry lead to increasing demands on material properties. For surface conditioning, optimised machining processes are capable of improving the fatigue performance without increasing the production cost significantly. This paper compares the influence of three different sulphur contents and three d...

Feature selection is an important task in machine learning, reducing dimensionality of learning problems by selecting few relevant features without losing too much information. Focusing on smaller sets of features, we can learn simpler models from data that are easier to understand and to apply. In fact, simpler models are more robust to input noise and outliers, often leading to better prediction performance than the models trained in higher dimensions with all features. We implement several...

We present our ongoing collaborative work on EnDroid, an energy-efficient GPS-based positioning system for the Android Operating System. EnDroid is based on the EnTracked positioning system, developed at the University of Aarhus, Denmark. We describe the current prototypical state of our implementation and present our experiences and conclusions from preliminarily evaluating EnDroid on the Google Nexus One Smartphone. Although the preliminary results seem to sup- port the approach, there are...

This Report describes the technical background and usage of the GraphMod plug-in for RapidMiner. The plug-in enables RapidMiner to load factor graphs and interpret Label and Attributes which are contained in an Example as assignments to random variables. A set of examples which belong to the same Batch is treated as assignment to a whole factor graph. New operators allow the estimation of factor weights, the computation of the single-node marginal probability functions and the computation of ...

Empirical analysis of statistical algorithms often demands time-consuming experiments which are best performed on high performance computing clusters. We present two R packages which greatly simplify working in batch computing environments. The package BatchJobs implements the basic objects and procedures to control a batch cluster within R. It is structured around cluster versions of the well-known higher order functions Map, Reduce and Filter from functional programming. An important featur...

Optimization in general means selecting a best choice out of various alternatives, which reduces the cost or disadvantage of an objective. Optimization problems are very popular in the fields such as economics, finance, logistics, etc. Optimization is a science of its own and machine learning or data mining is a diverse growing field which applies techniques from various other areas to find useful insights from data. Many of the machine learning problems can be modelled and solved as optimiza...