Structural sensitivity analysis of flexible multibody systems modeled with the floating frame of reference approach using the adjoint variable method

For the efficient analysis and optimization of flexible multibody systems, gradient information is often required. Next to simple and easy-to-implement finite difference approaches, analytical methods, such as the adjoint variable method, have been developed and are now well established for the sensitivity analysis in multibody dynamics. They allow the computation of exact gradients and require normally less computational effort for large-scale problems. In the current work, we apply the adjoint variable method to flexible multibody systems with kinematic loops, which are modeled using the floating frame of reference formulation. Thereby, in order to solve ordinary differential equations only, the equations of motion are brought into minimal form using coordinate partitioning, and the constraint equations at position and velocity level are incorporated in the adjoint dynamics. For testing and illustrative purposes, the procedure is applied to compute the structural gradient for a flexible piston rod of a slider–crank mechanism.     

The shape of feature code: an analysis of twenty C-preprocessor-based systems

Feature annotations (e.g., code fragments guarded by #ifdef C-preprocessor directives) control code extensions related to features. Feature annotations have long been said to be undesirable. When maintaining features that control many annotations, there is a high risk of ripple effects. Also, excessive use of feature annotations leads to code clutter, hinder program comprehension and harden maintenance. To prevent such problems, developers should monitor the use of feature annotations, for example, by setting acceptable thresholds. Interestingly, little is known about how to extract thresholds in practice, and which values are representative for feature-related metrics. To address this issue, we analyze the statistical distribution of three feature-related metrics collected from a corpus of 20 well-known and long-lived C-preprocessor-based systems from different domains. We consider three metrics: scattering degree of feature constants, tangling degree of feature expressions, and nesting depth of preprocessor annotations. Our findings show that feature scattering is highly skewed; in 14 systems (70 %), the scattering distributions match a power law, making averages and standard deviations unreliable limits. Regarding tangling and nesting, the values tend to follow a uniform distribution; although outliers exist, they have little impact on the mean, suggesting that central statistics measures are reliable thresholds for tangling and nesting. Following our findings, we then propose thresholds from our benchmark data, as a basis for further investigations.     

Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures

The term urban heat island describes the phenomenon of altered temperatures in urban areas compared to their rural hinterlands. A surface urban heat island encompasses the patterns of land surface temperatures in urban areas. The classical indicator to describe a surface urban heat island is the difference between urban and rural surface temperatures. However, several other indicators for this purpose have been suggested in the literature. In this study, we compared the eleven different indicators for quantifying surface urban heat islands that were most frequently used in recent publications on remote sensing-based urban heat island assessments. The dataset used here consists of 263 European cities with monthly mean temperatures from MODIS data products for July 2002, January 2003 and July 2003. We found that (i) the indicators individually reveal diurnal and seasonal patterns but show rather low correlations over time, and (ii) for single points in time, the different indicators show only weak correlations, although they are supposed to quantify the same phenomenon. Differentiating cities according to thermal climate zones increased the relationships between the indicators. Thus, we can identify temporal aspects and indicator selection as important factors determining the estimation of urban heat islands. We conclude that research should take into account the differences and instabilities of the indicators chosen for quantifying surface urban heat islands and should use several indicators in parallel for describing the surface urban heat island of a city.     

On the implication problem for cardinality constraints and functional dependencies

In database design, integrity constraints are used to express database semantics. They specify the way by that the elements of a database are associated to each other. The implication problem asks whether a given set of constraints entails further constraints. In this paper, we study the finite implication problem for cardinality constraints. Our main result is a complete characterization of closed sets of cardinality constraints. Similar results are obtained for constraint sets containing cardinality constraints, but also key and functional dependencies. Moreover, we construct Armstrong databases for these constraint sets, which are of special interest for example-based deduction in database design.     

PIN OLEDs — Improved structures and materials to enhance device lifetime

Abstract— Currently, three issues are identified that decide upon the commercial success of organic light‐emitting diodes (OLEDs), both in display and lighting applications: power efficiency, lifetime, and price competitiveness. PIN OLEDs are widely seen as the preferred way to maximize power efficiency. Here, it is reported that this concept also delivers the world longest lifetimes. For a highly efficient deep‐red PIN OLED, a half‐lifetime of 25,000 hours for a starting brightness of 10,000 cd/m² and a minimal voltage increase over lifetime is reported. This value corresponds to more than 1 × 10⁶ hours at 1000 cd/m² using an exponent of n = 1.7, which was measured by driving the OLEDs at different starting luminances. Because there is no initial luminance drop, these PIN OLEDs also exhibit a very high 80% lifetime (>300,000 hours at 1000 cd/m²). New record lifetime values for blue and green will be reported as well. Additionally, further topics that have impact on the production yield and cost such as the newly developed air‐stable organic n‐doping material NDN‐26 and top‐emitting structures will be discussed.     

Gene expression changes in a transgenic mouse model overexpressing human wildtype and mutant torsinA

Primary torsion dystonia is an autosomal-dominantly inherited, neurodevelopmental movement disorder caused by a GAG deletion (ΔGAG) in the DYT1 gene, encoding torsinA. This mutation is responsible for approximately 70% of cases of early-onset primary torsion dystonia. The function of wildtype torsinA is still unknown, and it is unsolved how the deletion in the DYT1 gene contributes to the development of the disease. To better understand the molecular processes involved in torsinA pathology, we used genome-wide oligonucleotide microarrays to characterize gene expression patterns in the striatum of mouse models overexpressing the human wildtype and mutant torsinA. By this approach we were able to detect gene expression changes that seem to be specific for torsinA pathology. We found an impact of torsinA, independent from genotype, on vesicle trafficking, exocytosis, and neurotransmitter release in our mouse model. In addition, we were able to identify several new pathways and processes involved in the development of the nervous system that are affected by wildtype and mutant torsinA. Furthermore, we have striking evidence from our gene expression data that glutamate receptor mediated synaptic plasticity in the striatum is the affected underlying cellular process for impaired motor learning in human ΔGAG torsinA transgenic mice.     

Proteomic expression profiling of thyroid neoplasms

Thyroid cancer is the most common endocrine neoplasm with multiple histologic subtypes, each associated with different treatments and outcomes. Differentiating benign neoplasms such as follicular adenomas from malignant entities such as follicular carcinomas and papillary carcinoma can be challenging. To define the proteomic profile of different thyroid tumors, we screened an antibody array of 330 features against five thyroid neoplasms: follicular adenoma, follicular carcinoma, papillary carcinoma, anaplastic carcinoma, and medullary carcinoma as well as normal thyroid epithelium. Eight candidate biomarkers; c-erbB-2, Stat5a, Annexin IV, IL-11, RARα, FGF7, Caspase 9, and phospho-c-myc were identified as differentially expressed on the antibody array, and validated with immunohistochemistry on tissue microarrays, with a total of 144 samples of the same variety of thyroid neoplasms. Analysis revealed c-erbB-2, Annexin IV, and Stat5a have potential clinical utility to differentiate follicular adenoma, follicular carcinoma, and papillary carcinoma from each other. By using an antibody array as a discovery platform and a tissue microarray as a first step in validation on a large number of specimens, we have identified new markers that have potential utility in the diagnosis of thyroid neoplasms.     

Access control in feature-oriented programming

In feature-oriented programming (FOP) a programmer decomposes a program in terms of features. Ideally, features are implemented modularly so that they can be developed in isolation. Access control mechanisms in the form of access or visibility modifiers are an important ingredient to attain feature modularity as they allow programmers to hide and expose internal details of a module’s implementation. But developers of contemporary feature-oriented languages have not considered access control mechanisms so far. The absence of a well-defined access control model for FOP breaks encapsulation of feature code and leads to unexpected program behaviors and inadvertent type errors. We raise awareness of this problem, propose three feature-oriented access modifiers, and present a corresponding access modifier model. We offer an implementation of the model on the basis of a fully-fledged feature-oriented compiler. Finally, by analyzing ten feature-oriented programs, we explore the potential of feature-oriented modifiers in FOP.     

Initializing Wiener–Hammerstein models based on partitioning of the best linear approximation

This paper describes a new algorithm for initializing and estimating Wiener–Hammerstein models which consist of two linear parts with a static nonlinearity in between. The algorithm makes use of the best linear model of the system, which is a consistent estimate of the systems dynamics for Gaussian excitations. The linear model is split in all possible ways into two sub-models. For all possible splits, a Wiener–Hammerstein model is initialized which means that a nonlinearity is introduced in between the two sub-models. The linear parameters of this nonlinearity can be estimated using least-squares. All initialized models can then be ranked depending on the fit. Typically, one is only interested in the best one, for which all parameters are fitted using prediction error minimization.The paper explains the algorithm in detail and consistency of the initialization is proven. Computational aspects are investigated, showing that in most realistic cases, the number of splits of the initial linear model remains low enough to make the algorithm useful. The algorithm is illustrated on an example where it is shown that the initialization is a tool to avoid many local minima.