Bad smells in design and design patterns

International audienceTo give a consistent and more valuable property on models, model-driven processes should be able to reuse the expert knowledge generally expressed in terms of patterns. We focus our work on the design stage and on the systematically use of design patterns. Choose a good design pattern and ensure the correct integration of the chosen pattern are non trivial for a designer who wants to use them. To help designers, we propose design inspection in order to detect “bad smells in design” and models reworking through use of design patterns. The automatic detection and the explanation of the misconceptions are performed thanks to spoiled patterns. A “spoiled pattern” is a pattern which allows to instantiate inadequate solutions for a given problem: requirements are respected, but architecture is improvable

1 Sharing Bad Practices in Design to Improve the Use of Patterns

To ensure the use of good analysis and design practices and an easier maintenance of software, analysts and designers may use patterns. To help them, we propose models inspection in order to detect instantiations of “spoiled pattern ” and models reworking through the use of the design patterns. As a design pattern allows the instantiation of the best known solution for a given problem, a “spoiled pattern ” allows the instantiation of alternative solutions for the same problem: requirements are respected, but architecture is improvable. We have collected a set of alternative solutions and deduced the corresponding spoiled patterns. We have defined a first catalog of these improvable practices from several experiments with students. To overcome the limits imposed by this method (restricted public, limited problems and tiresome validation process), we would like to open this problematic to the expert community. Therefore, we propose a collaborative website sharing bad practices in object oriented design to improve the use of patterns

Interferometric lensless imaging: rank-one projections of image frequencies with speckle illuminations

Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging technique that enables potential endoscopic observations of biological samples at cellular scale. In this work, we show that this technique is tantamount to collecting multiple symmetric rank-one projections (SROP) of an interferometric matrix--a matrix encoding the spectral content of the sample image. In this model, each SROP is induced by the complex sketching vector shaping the incident light wavefront with a spatial light modulator (SLM), while the projected interferometric matrix collects up to $O(Q^2)$ image frequencies for a $Q$-core MCF. While this scheme subsumes previous sensing modalities, such as raster scanning (RS) imaging with beamformed illumination, we demonstrate that collecting the measurements of $M$ random SLM configurations--and thus acquiring $M$ SROPs--allows us to estimate an image of interest if $M$ and $Q$ scale log-linearly with the image sparsity level This demonstration is achieved both theoretically, with a specific restricted isometry analysis of the sensing scheme, and with extensive Monte Carlo experiments. On a practical side, we perform a single calibration of the sensing system robust to certain deviations to the theoretical model and independent of the sketching vectors used during the imaging phase. Experimental results made on an actual MCF system demonstrate the effectiveness of this imaging procedure on a benchmark image.Comment: 13 pages, keywords: lensless imaging, rank-one projections, interferometric matrix, inverse problem, computational imaging, single-pixe

Un Framework de traçabilité pour des transformations à caractère impératif

National audienceCet article s’inscrit dans le cadre de l’ingénierie dirigée par les mo- dèles et apporte une contribution au problème de la traçabilité des artefacts de modélisation durant une chaîne de transformations écrites dans un langage impé- ratif. L’approche que nous proposons nécessite peu d’interventions de l’utilisa- teur. Nous introduisons un métamodèle générique des traces qui permet entre autres d’apporter une dimension multi-échelles aux traces grâce à l’applica- tion du patron de conception composite. Le principe de notre approche est de surveiller certaines catégories d’opérations intéressantes pour la génération de traces pertinentes. Ces catégories sont définies à l’aide du type des objets mani- pulés par les opérations. Une fois les catégories définies, la trace est générée par du code dédié qui est injecté automatiquement dans la transformation, autour des opérations caractérisées par les catégories définies. Un prototype a été réa- lisé pour les transformations de modèles écrites en Java, sur le framework EMF. L’injection du code dédié à la traçabilité est réalisée à l’aide de la programmation par aspects

Hair cortisol concentration in finishing pigs on commercial farms: variability between pigs, batches, and farms

Hair cortisol is a stress indicator and could be used to assess the pigs’ exposure to stressors in the weeks/months prior to non-invasive hair sampling. The main aim of this study was to describe the hair cortisol concentration (HCC) variability between individuals within a batch, between farms and between batches within a farm. The secondary aim was to determine how the number of sampled pigs influences the characterization of HCC within a batch. Twenty farrow-to-finish pig farms were recruited considering the diversity of their management practices and health status (data collected). Hair was sampled in two separate batches, 8 months apart. The necks of 24 finishing pigs were clipped per batch the week prior to slaughter. To describe the variability in HCC, an analysis of the variance model was run with three explanatory variables (batch, farm and their interaction). To identify farm clusters, a principal component analysis followed by a hierarchical clustering was carried out with four active variables (means and standard deviations of the two batches per farm) and 17 supplementary variables (management practices, herd health data). We determined how the number of sampled pigs influenced the characterization of HCC within a batch by selecting subsamples of the results. HCC ranged from 0.4 to 121.6 pg/mg, with a mean of 25.9 ± 16.2 pg/mg. The variability in HCC was mainly explained by differences between pigs (57%), then between farms (24%), between batches within the same farm (16%) and between batches (3%). Three clusters of farms were identified: low homogeneous concentrations (n = 3 farms), heterogeneous concentrations with either higher (n = 7) or lower (n = 10) HCC in batch 2 than in batch 1. The diversity of management practices and health statuses allowed to discuss hypotheses explaining the HCC variations observed. We highlighted the need to sample more than 24 pigs to characterize HCC in a pig batch. HCC differences between batches on six farms suggest sampling pigs in more than one batch to describe the HCC at the farm level. HCC variations described here confirm the need to study its links with exposure of pigs to stressors

Using Dynamic Stochastic Modelling to Estimate Population Risk Factors in Infectious Disease: The Example of FIV in 15 Cat Populations

BACKGROUND:In natural cat populations, Feline Immunodeficiency Virus (FIV) is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. METHODOLOGY/PRINCIPAL FINDINGS:To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively) on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. CONCLUSION:Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease

Prions in Milk from Ewes Incubating Natural Scrapie

Since prion infectivity had never been reported in milk, dairy products originating from transmissible spongiform encephalopathy (TSE)-affected ruminant flocks currently enter unrestricted into the animal and human food chain. However, a recently published study brought the first evidence of the presence of prions in mammary secretions from scrapie-affected ewes. Here we report the detection of consistent levels of infectivity in colostrum and milk from sheep incubating natural scrapie, several months prior to clinical onset. Additionally, abnormal PrP was detected, by immunohistochemistry and PET blot, in lacteal ducts and mammary acini. This PrPSc accumulation was detected only in ewes harbouring mammary ectopic lymphoid follicles that developed consequent to Maedi lentivirus infection. However, bioassay revealed that prion infectivity was present in milk and colostrum, not only from ewes with such lympho-proliferative chronic mastitis, but also from those displaying lesion-free mammary glands. In milk and colostrum, infectivity could be recovered in the cellular, cream, and casein-whey fractions. In our samples, using a Tg 338 mouse model, the highest per ml infectious titre measured was found to be equivalent to that contained in 6 µg of a posterior brain stem from a terminally scrapie-affected ewe. These findings indicate that both colostrum and milk from small ruminants incubating TSE could contribute to the animal TSE transmission process, either directly or through the presence of milk-derived material in animal feedstuffs. It also raises some concern with regard to the risk to humans of TSE exposure associated with milk products from ovine and other TSE-susceptible dairy species

Combinations of single-top-quark production cross-section measurements and vertical bar f(LV)V(tb)vertical bar determinations at root s=7 and 8 TeV with the ATLAS and CMS experiments

This paper presents the combinations of single-top-quark production cross-section measurements by the ATLAS and CMS Collaborations, using data from LHC proton-proton collisions at = 7 and 8 TeV corresponding to integrated luminosities of 1.17 to 5.1 fb(-1) at = 7 TeV and 12.2 to 20.3 fb(-1) at = 8 TeV. These combinations are performed per centre-of-mass energy and for each production mode: t-channel, tW, and s-channel. The combined t-channel cross-sections are 67.5 +/- 5.7 pb and 87.7 +/- 5.8 pb at = 7 and 8 TeV respectively. The combined tW cross-sections are 16.3 +/- 4.1 pb and 23.1 +/- 3.6 pb at = 7 and 8 TeV respectively. For the s-channel cross-section, the combination yields 4.9 +/- 1.4 pb at = 8 TeV. The square of the magnitude of the CKM matrix element V-tb multiplied by a form factor f(LV) is determined for each production mode and centre-of-mass energy, using the ratio of the measured cross-section to its theoretical prediction. It is assumed that the top-quark-related CKM matrix elements obey the relation |V-td|, |V-ts| << |V-tb|. All the |f(LV)V(tb)|(2) determinations, extracted from individual ratios at = 7 and 8 TeV, are combined, resulting in |f(LV)V(tb)| = 1.02 +/- 0.04 (meas.) +/- 0.02 (theo.). All combined measurements are consistent with their corresponding Standard Model predictions.Peer reviewe