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When demands exceed capacities, suppliers allocate available supply to customers based on customer importance and advance demand information. The accuracy of advance demand information interacts with the length of customer order lead times and influences overall customer service levels. In this paper, we analyse industrial contract portfolios with customer-specific terms in order to derive insights for contract portfolio management and the design of demand fulfilment processes. For this purpose, we develop a framework for analysis of contract portfolios capturing the dynamics of industrial planning processes. The framework is applied to portfolios from the semiconductor sector. Our numerical analysis shows that, in order to improve service levels, demand fulfilment processes and contract portfolio management must especially take into account the length of order lead times and the accuracy of advance demand information. Even though suppliers often prefer long order lead times, our analysis shows that demand fulfilment performance is not primarily determined by the absolute length of the order lead times but by the presence of a negative correlation with the accuracy of advance demand information in the entire contract portfolio. Consequently, these factors require increased attention in the management of contract portfolios and in the negotiation of individual contracts.

High demand uncertainties, long production lead times, and short product life cycles cause high risks for supply chain planning in the semiconductor industry. These affect all industries producing goods containing semiconductors. We present a robust supply chain planning framework for revenue management that consists of stable and flexible solutions for demand steering and dynamic pricing, extending current industry practice in several aspects. We introduce the concept of availabilities and capabilities, as well as various planning processes and process enablers. Based on our framework, we also highlight directions for future research.

We propose a data-driven allocation planning approach, which is designed for use in advanced planning systems as they are widely used in industrial environments. The approach exploits increasingly available data on individual customers and products by allocating supply on a highly granular level at high planning frequencies. It counteracts rationing gaming by customers, which we assume to be the reason for demand forecast biases. We create an incentive for truthful forecasting by not only allocating supply based on customer profitability but also based on forecast bias. In the long term, this approach gives access to a profit potential and an on-time service level increase. In the short term, however, setting such an incentive does not only have a positive impact on service levels but also leads to a decline in profits. Our methodology quantifies this trade off providing decision support for determining the extent to which the forecast bias should affect the allocation. In a numerical study based on the semiconductor industry, we demonstrate that the approach has a large long-term profit potential while having limited effect on short-term profits for significant service level incentives. The analysis further shows that the allocation efficiency increases with the granularity level and the predictive quality of the available data.

Accurate order promising is a key requirement for customer satisfaction. Nevertheless, practitioners struggle with the reliability of the delivery dates they promise to customers. Consequently, the costs of demand fulfilment soar due to intensified communication, emergency processes in logistics and acquisition of costly external production resources. We identify and formalise product and process flexibilities in supply chains that can be exploited in production planning. Product flexibility is the possibility to produce several kinds of products from one predecessor product. Process flexibility is the possibility to use one production process to manufacture several products. In order to increase the accuracy and robustness of delivery dates, we develop an order promising methodology able to deal with demand mix uncertainty and heterogeneous customer order lead times. The approach anticipates changes in production plans made possible by product and process flexibilities. In a numerical study based on a ca...

In personalized medicine, SNPs are used to identify specific diseases of a patient. However, for many SNPs, no information about the pathogenicity is available. Current programs try to predict the effect of a SNP on the function of a protein, but give no possibility for visual interpretation. We have developed SNPViz, a program that first finds 3D structures of affected proteins and then highlights the affected amino acid in the 3D structure. This can give researchers and doctors more information about the probable pathogenicity of the SNP. In the future, we plan to add also further information, such as whether the position of the SNP is in a binding domain, or is involved in a protein-protein interaction.

Spinal cord transections in mammalian animal models lead to loss of motor function. In this study, we show that functional recovery from complete transection of the adult mouse spinal cord can in fact occur without any intervention if dural injury along with displacement of the ends of the cut cord and fibroblastic infiltration is minimized. Underlying this function is the expression of GAP-43 in axonal growth cones, axonal extension and bridging of the injury site indicated by biocytin retrograde tracing and neuronal remodeling of both the white matter and the gray matter. Such studies suggest a new murine model for the study of spinal cord regeneration.

Article 88 (1) (a) of Directive 2001/83/EC must be interpreted as meaning that it does not prohibit the dissemination on a website, by a pharmaceutical undertaking, of information relating to medicinal products available on medical prescription only, where that information is accessible on the website only to someone who seeks to obtain it and that dissemination consists solely in the faithful reproduction of the packaging of the medicinal product, in accordance with Article 62 of Directive 2001/83, and in the literal and complete reproduction of the package leaflet or the summary of the product's characteristics, which have been approved by the authorities with competence in relation to medicinal products (official headnote).

Case-based approaches predict the behaviour of dynamic systems by analysing a given experimental setting in the context of others. To select similar cases and to control adaptation of cases, they employ general knowledge. If that is neither available nor inductively derivable, the knowledge implicit in cases can be utilized for a case-based ranking and adaptation of similar cases. We introduce the system OASES and its application to medical experimental studies to demonstrate this approach.

Understanding disease-related metabolite interactions is a key issue in computational biology. We apply a modified Bayesian Optimization Algorithm to targeted metabolomics data from plasma samples of insulin-sensitive and -resistant subjects both suffering from non-alcoholic fatty liver disease. In addition to improving the classification accuracy by selecting relevant features, we extract the information that led to their selection and reconstruct networks from detected feature dependencies. We compare the influence of a variety of classifiers and different scoring metrics and examine whether the reconstructed networks represent physiological metabolite interconnections. We find that the presented method is capable of significantly improving the classification accuracy of otherwise hardly classifiable metabolomics data and that the detected metabolite dependencies can be mapped to physiological pathways, which in turn were affirmed by literature from the domain.

We have shown recently that downregulation of the androgen receptor (AR), one of the key players in prostate tumor cells, with short antisense oligodeoxynucleotides (ODNs) results in inhibition of prostate tumor growth. Particularly with regard to an application of these antisense drugs in vivo, we now investigated the usefulness of microbubble-enhanced ultrasound to deliver these ODNs into prostate cancer cells. Our short antisense AR ODNs were loaded onto the lipid surface of cationic gas-filled microbubbles by ion charge binding, and delivered into the cells by bursting the loaded microbubbles with ultrasound. In vitro experiments were initially performed to show that this kind of delivery system works in principle. In fact, transfection of prostate tumor cells with antisense AR ODNs using microbubble-enhanced ultrasound resulted in 49% transfected cells, associated with a decrease in AR expression compared to untreated controls. In vivo, uptake of a digoxigenin-labelled ODN was found in prostate tumour xenografts in nude mice following intratumoral or intravenous injection of loaded microbubbles and subsequent exposure of the tumour to ultrasound, respectively. Our results show that ultrasound seems to be the driving force of this delivery system. Uptake of the ODN was also observed in tumors after treatment with ultrasound alone, with only minor differences compared to the combined use of microbubbles and ultrasound.

This study reports an anatomical investigation of the angular branch of the thoracodorsal artery, which can be used in reconstructive surgery to serve as a pedicle for gaining osseous material from the scapula. The study was performed on 135 samples and topography and morphometry of the vessel were investigated. It was found that this artery has five main types of origin. It courses in the fascial gliding layer between the serratus muscle, and the teres major and subscapular muscle to the inferior angle of the scapula. There it provides the bone with blood through periostal branches as part of the arterial rete on the costal and dorsal side of the scapula. The mean length of the angular branch and the thoracodorsal artery together was 148 mm, and when also adding the subscapular artery the overall length became 167 mm. It was found that the length of a pedicle consisting of the angular branch and the thoracodorsal artery is determined by the difference in origin of the vessels with minor influences of the body size. The internal diameters of unfilled fixated vessels measured 3.06 mm for the subscapular, 1.77 mm for the circumflex scapular, 1.30 mm for the thoracodorsal and 0.64 mm for the angular branch. The exact knowledge of the microanatomy in this area is necessary to be able to use the osseous free flap more selectively and have less traumatization in the donor area.

Case oriented tutoring gives students the possibility to practice their acquired theoretical knowledge in the context of concrete cases. Accordingly, tutoring systems for individualized learning have to take the skills of students at applying their knowledge to problem solving into account. This paper describes a case-based methodology for planning tutoring processes depending on the skills of individual users. We develop methods for retrieving tutoring plans of users with similar skills and present adaptation techniques for improving these plans based on the student's behavior during the corresponding tutoring process. The developed methodology is based on the notion that a student has to perform threads of associations in the process of problem solving.

Case-based approaches are employed within a multitude of application areas one of which is the prediction of dynamic behaviour. Given a situation the possible development after a time span shall be determined. If only a small set of heterogenously structured cases describing observations at a variety of time points is given to start with, as it is the case when experimental medical studies shall be analysed, it becomes necessary to analyse and evaluate the temporal horizon from case to case differently, and treat time as a first class variable. This is the strategy OASES (Our Approach to Simulation based on Experimental Studies) employs. For this purpose, OASES utilises knowledge implicit in cases for matching and adaptation. Whether different time points do match in the current situation or how different time points of observation might effect the development, is decided based on cases which time is an explicit part of. Keywords: Case-Based Reasoning; Case-Based Similarity Ranking; Case-Based Adaptation; Prediction; Experimental Studies