A Superconducting RF Cavity for Bunch Compression of the High Intensity SPS Proton Beam at Transfer to LHC

The bunch length of the high-intensity proton beam ejected from the CERN SPS into LHC must be reduced to fit into the 400MHz LHC buckets. This will be done using a new 400MHz superconducting RF system in the SPS. Above transition bunch compression is obtained with a cavity tuned slightly below the bunch frequency, thus giving a very high capacitive impedeance. Such a system would however be extremely critical and very unstable without strong RF feedback. To keep the required RF power at an acceptable level during the ramp, the beam, which occupies only a third of the SPS, is accelerated in a variable harmonic mode to place the beam spectrum substantially above the cavity bandwidth. On the flat top, when the beam spectrum is moved towards the cavity resonance, the phase and amplitude of the reference voltage, including its modulation at the revolution frequency are programmed to keep the required RF power to a minimum. This scheme is described in detail together with the prototype 400MHz superconducting cavity already installed in the SPS. Initial tests with beam will also be reported

The LHC superconducting cavities

The LHC RF system, which must handle high intensity (0.5 A d.c.) beams, makes use of superconducting single-cell cavities, best suited to minimizing the effects of periodic transient beam loading. There will be eight cavities per beam, each capable of delivering 2 MV (5 MV/m accelerating field) at 400 MHz. The cavities themselves are now being manufactured by industry, using niobium-on-copper technology which gives full satisfaction at LEP. A cavity unit includes a helium tank (4.5 K operating temperature) built around a cavity cell, RF and HOM couplers and a mechanical tuner, all housed in a modular cryostat. Four-unit modules are ultimately foreseen for the LHC (two per beam), while at present a prototype version with two complete units is being extensively tested. In addition to a detailed description of the cavity and its ancillary equipment, the first test results of the prototype will be reported

Optimising ‘cash flows’:Converting corporate finance to hard currency

Following recent works that have underlined the increasing search for liquidity in economic exchange, this article studies how illiquid forms of money are converted into liquid forms by corporate finance actors. In the name of ‘shareholder value’, the various forms of value generated by companies (such as ‘trade credit’) tend to be increasingly transformed into liquid forms of money that are easily distributable to shareholders (‘cash flows’). Describing this phenomenon as an example of what anthropologists of money call ‘conversion’, this paper highlights how such a conversion process was necessary for the historical development of ‘shareholder value’ policies in corporate finance. Considering documentary sources and interviews with consultants, auditors, and private equity fund managers involved in ‘cash flow’ optimisation practices, this paper details this conversion phenomenon and shows how it has relied on the historical elaboration of specific metrological, technical, legal, and moral norms

Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

Taenia solium porcine cysticercosis in Madagascar: Comparison of immuno-diagnostic techniques and estimation of the prevalence in pork carcasses traded in Antananarivo city

Taenia solium cysticercosis was reported in official veterinary and medical statistics to be highly prevalent in pigs and humans in Madagascar, but few estimates are available for pigs. This study aimed to estimate the seroprevalence of porcine cysticercosis among pigs slaughtered in Antananarivo abattoirs. Firstly, the diagnostic performance of two antigen-ELISA techniques (B158B60 Ag-ELISA and HP10 Ag-ELISA) and an immunoblotting method were compared with meat inspection procedures on a sample of pigs suspected to be infected with (group 1; n = 250) or free of (group 2; n = 250) T. solium based on direct veterinary inspection in Madagascar. Sensitivity and specificity of the antigen ELISAs were then estimated using a Bayesian approach for detection of porcine cysticercosis in the absence of a gold standard. Then, a third set of pig sera (group 3, n = 250) was randomly collected in Antananarivo slaughterhouses and tested to estimate the overall prevalence of T. solium contamination in pork meat traded in Antananarivo. The antigen ELISAs showed a high sensitivity (>84%), but the B158B60 Ag-ELISA appeared to be more specific than the HP10 Ag-ELISA (model 1: 95% vs 74%; model 2: 87% vs 71%). The overall prevalence of porcine cysticercosis in Antananarivo slaughterhouses was estimated at 2.3% (95% credibility interval [95%CrI]: 0.09–9.1%) to 2.6% (95%CrI: 0.1–10.3%) depending on the model and priors used. Since the sample used in this study is not representative of the national pig population, village-based surveys and longitudinal monitoring at slaughter are needed to better estimate the overall prevalence, geographical patterns and main risk factors for T. solium contamination, in order to improve control policies. (Résumé d'auteur

Looking beyond forest cover: an analysis of landscape-scale predictors of forest degradation in the Brazilian Amazon.

While forest degradation rates and extent exceed deforestation in the Brazilian Amazon, less attention is given to the factors controlling its spatial distribution. No quantified correlation exists between changes of forest structure due to anthropogenic disturbances and dynamics of land use and cover change occurring at broader spatial levels. This study examines the influence of multi-scale landscape structure factors (i.e. spatial composition, configuration and dynamic of land use/cover) on primary forest's aboveground biomass (AGB), spanning from low to highly degraded, in Paragominas municipality (Pará state). We used random forest models to identify the most important landscape predictors of degradation and clustering methods to analyze their distribution and interactions. We found that 58% of the variance of AGB could be explained by metrics reflecting land use practices and agricultural dynamics around primary forest patches and that their spatial patterns were not randomly distributed. Forest degradation is mainly driven by fragmentation effects resulting from old deforestation and colonization events linked with cropland expansion (e.g. soybean and maize) coupled with high accessibility to market. To a lesser extent, degradation is driven by recent and ongoing (1985?2015) deforestation and fragmentation in slash-and-burn agricultural areas, characterized by heterogeneous mosaics of pastures and fallow lands combined with high use of fire. Our findings highlight the potential of landscape-level framework and remotely sensed land cover data for a thorough understanding of the distribution of forest degradation across human-modified landscapes. Addressing these spatial determinants by looking at agricultural dynamics beyond forest cover is necessary to improve forest management which has major implications for biodiversity, carbon and other ecosystem services