Production of the CMS Tracker End Cap sub-structures

The production and qualification of the 288 petals needed to build both CMS Tracker End Caps (TECs) is summarized. There will be first a description of a petal, integrating many components, the most important ones being the silicon modules. The organization of the production, involving 7 Institutes all over Europe, will then be explained. The petal assembly and testing procedure will be quickly described. The quality assurance put in place at each production step has resulted in a very high petal quality, as some overall plots will attest. Finally some details about part failures will be given

Analysis of inter-core cross-gain modulation in cladding pumped multi-core fiber amplifiers

We numerically investigate pump-induced gain variations in eight-core fi ber amplifi ers. We compare two fi bers with different erbium profi les by varying input power from -25 dBm to 0 dBm in one or four cores. Inter-core cross-gain modulation is < 0.6 dB

Modeling and characterization of cladding-pumped erbium-ytterbium co-doped fibers for amplification in communication systems

Cladding-pumped optical fiber amplifiers are of increased interest in the context of space-division multiplexing but are known to suffer from low power efficiency. In this context, ytterbium (Yb) co-doping can be an attractive solution to improve the performance of erbium (Er) doped fiber amplifiers. We present a detailed direct comparison between Er/Yb-co-doping and Er-doping using numerical simulations validated by experimental results. Two double-cladding fibers, one doped with Er only and the other one co-doped with Er and Yb, were designed, fabricated and characterized. Using the experimentally extracted parameters, we simulate multi-core fiber amplifiers and investigate the interest of Er/Yb-co-doping. We calculate the minimum gain of the amplifiers over a 35-nm spectral window considering various scenarios

Demonstration of an erbium-doped fiber with annular doping for low gain compression in cladding-pumped amplifiers

We present the design and characterization of a cladding-pumped amplifier with erbium doping located in an annular region near the core. This erbium-doped fiber is proposed to reduce gain saturation, leading to smaller gain compression when compared to uniform core doping. Through numerical simulations, we first compare the performance of three fibers with different erbium doping profiles in the core or the cladding. When the doped fibers are operated at the optimum length, results show that the smaller overlap of the signal mode field with the annular erbium doping region leads to higher gain and lower saturation of the amplifier. A single-core erbium-doped fiber with an annular doping and a D-shaped cladding was fabricated. Measurements demonstrate less than 4 dB of gain compression over the C-band for input power ranging from −40 dBm to 3 dBm. Small gain compression EDFAs are of interest for applications that require input channel reconfiguration. Higher gain and saturation output power are also key issues in cladding-pumped multi-core amplifiers

Status of the Micro Vertex Detector of the Compressed Baryonic Matter Experiment

The CBM experiment will investigate heavy-ion collisions at beam energies from 8 to 45 AGeV at the future accelerator facility FAIR. The goal of the experiment is to study the QCD phase diagram in the vincinity of the QCD critical point. To do so, CBM aims at measuring rare probes among them open charm. In order to identify those rare and short lived particles despite the rich combinatorial background generated in heavy ion collisions, a micro vertex detector (MVD) providing an unprecedented combination of high rate capability and radiation hardness, very light material budget and excellent granularity is required. In this work, we will discuss the concept of this detector and summarize the status of the R&D

A new molecular breast cancer subclass defined from a large scale real-time quantitative RT-PCR study

BACKGROUND: Current histo-pathological prognostic factors are not very helpful in predicting the clinical outcome of breast cancer due to the disease's heterogeneity. Molecular profiling using a large panel of genes could help to classify breast tumours and to define signatures which are predictive of their clinical behaviour. METHODS: To this aim, quantitative RT-PCR amplification was used to study the RNA expression levels of 47 genes in 199 primary breast tumours and 6 normal breast tissues. Genes were selected on the basis of their potential implication in hormonal sensitivity of breast tumours. Normalized RT-PCR data were analysed in an unsupervised manner by pairwise hierarchical clustering, and the statistical relevance of the defined subclasses was assessed by Chi2 analysis. The robustness of the selected subgroups was evaluated by classifying an external and independent set of tumours using these Chi2-defined molecular signatures. RESULTS: Hierarchical clustering of gene expression data allowed us to define a series of tumour subgroups that were either reminiscent of previously reported classifications, or represented putative new subtypes. The Chi2 analysis of these subgroups allowed us to define specific molecular signatures for some of them whose reliability was further demonstrated by using the validation data set. A new breast cancer subclass, called subgroup 7, that we defined in that way, was particularly interesting as it gathered tumours with specific bioclinical features including a low rate of recurrence during a 5 year follow-up. CONCLUSION: The analysis of the expression of 47 genes in 199 primary breast tumours allowed classifying them into a series of molecular subgroups. The subgroup 7, which has been highlighted by our study, was remarkable as it gathered tumours with specific bioclinical features including a low rate of recurrence. Although this finding should be confirmed by using a larger tumour cohort, it suggests that gene expression profiling using a minimal set of genes may allow the discovery of new subclasses of breast cancer that are characterized by specific molecular signatures and exhibit specific bioclinical features

Reception Test of Petals for the End Cap TEC+ of the CMS Silicon Strip Tracker

The silicon strip tracker of the CMS experiment has been completed and was inserted into the CMS detector in late 2007. The largest sub system of the tracker are its end caps, comprising two large end caps (TEC) each containing 3200 silicon strip modules. To ease construction, the end caps feature a modular design: groups of about 20 silicon modules are placed on sub-assemblies called petals and these self-contained elements are then mounted onto the TEC support structures. Each end cap consists of 144 such petals, which were built and fully qualified by several institutes across Europe. Fro

Integration of the End Cap TEC+ of the CMS Silicon Strip Tracker

The silicon strip tracker of the CMS experiment has been completed and inserted into the CMS detector in late 2007. The largest sub-system of the tracker is its end cap system, comprising two large end caps (TEC) each containing 3200 silicon strip modules. To ease construction, the end caps feature a modular design: groups of about 20 silicon modules are placed on sub-assemblies called petals and these self-contained elements are then mounted into the TEC support structures. Each end cap consists of 144 petals, and the insertion of these petals into the end cap structure is referred to as TEC integration. The two end caps were integrated independently in Aachen (TEC+) and at CERN (TEC--). This note deals with the integration of TEC+, describing procedures for end cap integration and for quality control during testing of integrated sections of the end cap and presenting results from the testing

The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

BACKGROUND: Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them.RESULTS:A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89 and the best AUC iP/R was 68. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing systems against manually generated annotations done by curators from the BioGRID and MINT databases. The highest AUC iP/R achieved by any run was 53, the best MCC score 0.55. In case of competitive systems with an acceptable recall (above 35) the macro-averaged precision ranged between 50 and 80, with a maximum F-Score of 55. CONCLUSIONS: The results of the ACT task of BioCreative III indicate that classification of large unbalanced article collections reflecting the real class imbalance is still challenging. Nevertheless, text-mining tools that report ranked lists of relevant articles for manual selection can potentially reduce the time needed to identify half of the relevant articles to less than 1/4 of the time when compared to unranked results. Detecting associations between full text articles and interaction detection method PSI-MI terms (IMT) is more difficult than might be anticipated. This is due to the variability of method term mentions, errors resulting from pre-processing of articles provided as PDF files, and the heterogeneity and different granularity of method term concepts encountered in the ontology. However, combining the sophisticated techniques developed by the participants with supporting evidence strings derived from the articles for human interpretation could result in practical modules for biological annotation workflows