Regulation of genes involved in carnitine homeostasis by PPARa across different species (rat, mouse, pig, cattle, chicken, and human)

Recent studies in rodents convincingly demonstrated that PPAR-alpha is a key regulator of genes involved in carnitine homeostasis, which serves as a reasonable explanation for the phenomenon that energy deprivation and fibrate treatment, both of which cause activation of hepatic PPAR-alpha, causes a strong increase of hepatic carnitine concentration in rats. The present paper aimed to comprehensively analyse available data from genetic and animal studies with mice, rats, pigs, cows, and laying hens and from human studies in order to compare the regulation of genes involved in carnitine homeostasis by PPAR-alpha across different species. Overall, our comparative analysis indicates that the role of PPAR-alpha as a regulator of carnitine homeostasis is well conserved across different species. However, despite demonstrating a well-conserved role of PPAR-alpha as a key regulator of carnitine homeostasis in general, our comprehensive analysis shows that this assumption particularly applies to the regulation by PPAR-alpha of carnitine uptake which is obviously highly conserved across species, whereas regulation by PPAR-alpha of carnitine biosynthesis appears less well conserved across species

Towards a Model for Research Portal Acceptance and Usage

Research portals have been suggested as both a knowledge management tool and a collaboration technology for research communities. This paper proposes a research model designed to understand the acceptance und usage of such portals. The model is based on UTAUT which we augment to include research portal-specific technology, individual and situational characteristics. Our model incorporates theories originating from the fields of knowledge management and collaboration technology. This paper thus answers the call for developing more technology-specific acceptance theories. It contributes to both research and practice, because it represents a first step towards developing research portals that are more widely used than they currently are

Strong-Field Bloch Electron Interferometry for Band Structure Retrieval

When Bloch electrons in a solid are exposed to a strong optical field, they are coherently driven in their respective bands where they acquire a quantum phase as the imprint of the band shape. If an electron approaches an avoided crossing formed by two bands, it may be split by undergoing a Landau-Zener transition. We here employ subsequent Landau-Zener transitions to realize strong-field Bloch electron interferometry (SFBEI), allowing us to reveal band structure information. In particular, we measure the Fermi velocity (band slope) of graphene in the vicinity of the K points as (1.07$\pm$0.04) nm fs$^{-1}$. We expect SFBEI for band structure retrieval to apply to a wide range of material systems and experimental conditions, making it suitable for studying transient changes in band structure with femtosecond temporal resolution at ambient conditions

Evaluating Groupware for Creative Group Processes – The Case Study of CreativeFlow

The creative potential of teams plays a crucial role in generating the competitive advantage of organizations. We introduce an architecture supporting creative group processes in the context of business processes. Based on the theoretical concept of Pockets of Creativity (Seidel et al. 2010), the architecture aims to balance freedom for creative group work and constraints set by the processes in its environment. The architecture is implemented in the prototype CreativeFlow, integrating a groupware component and a workflow component. The prototype is evaluated in a case study in a TV production company. Free participation in group tasks and support for the structuring of ideas were deemed appropriate for the support of creative group processes. Process structure is mainly imposed by project deadlines that require user notification, also outside the workflow component. Process orientation is a promising approach to increase the efficiency of the creative value creation

Accelerated gradient methods for total-variation-based CT image reconstruction

Total-variation (TV)-based Computed Tomography (CT) image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is very well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is much more demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large-scale systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits slow convergence. In the present work we consider the use of two accelerated gradient-based methods, GPBB and UPN, for reducing the number of gradient method iterations needed to achieve a high-accuracy TV solution in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the gradient method.Comment: 4 pages, 2 figure

Towards Usability Guidelines for Mobile Websites and Applications

The market for mobile devices is growing rapidly nowadays. Constant technolog-ical improvements provide great opportunities for the creation of mobile applica-tions. For the success of a mobile application or website, one of the main con-cerns, besides security issues, is usability. Poor usability decreases user produc-tivity and consequently causes loss of users. In order to avoid these problems, usability aspects have to be considered already during the design phase of the ap-plication, e.g. by following predefined usability guidelines. Although usability guidelines for web development are already in place since the 1990s, structured and evaluated usability guidelines for mobile applications can rarely be found in scientific literature. Thus, in this paper we introduce a catalogue of usability guidelines for mobile applications and websites, and subsequently demonstrate their usage by applying them in two case studies: the development of a mobile application and a mobile website

Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios

This work introduces an evaluation benchmark for depth estimation and completion using high-resolution depth measurements with angular resolution of up to 25" (arcsecond), akin to a 50 megapixel camera with per-pixel depth available. Existing datasets, such as the KITTI benchmark, provide only sparse reference measurements with an order of magnitude lower angular resolution - these sparse measurements are treated as ground truth by existing depth estimation methods. We propose an evaluation methodology in four characteristic automotive scenarios recorded in varying weather conditions (day, night, fog, rain). As a result, our benchmark allows us to evaluate the robustness of depth sensing methods in adverse weather and different driving conditions. Using the proposed evaluation data, we demonstrate that current stereo approaches provide significantly more stable depth estimates than monocular methods and lidar completion in adverse weather. Data and code are available at https://github.com/gruberto/PixelAccurateDepthBenchmark.git.Comment: 3DV 201

Risikoabschätzung bei suizidalen Patienten: Geht das überhaupt?

Eine Risikoabschätzung ist im Kontext suizidalen Erlebens und Verhaltens nicht sicher möglich. Aktuelle Metaanalysen zeigen, dass weder Einzelvariablen noch Risikoscores, das klinische Urteil oder die Orientierung an einem Theoriemodell eine zufriedenstellende Vorhersage suizidalen Verhaltens erlauben. Es stellt sich die Frage, wie in der klinischen Praxis mit dem Wissen um die mangelnde Präzision der Risikoabschätzung umgegangen werden sollte. Der vorliegende Artikel skizziert zunächst die aktuelle Befundlage und reflektiert im Anschluss die Bedeutung dieser Befunde für die praktische Arbeit: Die Risikoabschätzung sollte als kollaborativer Prozess verstanden werden, in dem der Therapeut anerkennt, dass er kein ausreichendes Expertenwissen hinsichtlich des Gefährdungspotentials eines Patienten besitz