Stability and singularities of relative hypersurfaces

We study relative hypersurfaces, and prove an instability condition for the fibres. This is the starting point for an investigation of the geometry of effective divisors on relative projective bundles.Preprin

Comparative genomic analysis of two Chilean Renibacterium salmoninarum isolates and the type strain ATCC 33209T

Indexación: Scopus.Two previously characterized Chilean isolates (H-2 and DJ2R), obtained from cage-cultured Atlantic salmon with clinical signs of bacterial kidney disease in southern Chile, were used (Bethke et al. 2016, 2017). The bacteria were routinely cultured in KDM-2 agar for 15–20 days at 15°C. For sequencing, genomic DNA of the two isolates was extracted using the InstaGene Purification Matrix (Bio-Rad) according to manufacturer instructions. The DJ2R genome was sequenced using an Illumina MiSeq platform with 2 ⨯ 250 paired-end reads by the AUSTRAL-omics Institute, hosted by the Universidad Austral de Chile (Valdivia, Chile). Using the same technology and parameters, H-2 genomic DNA was sequenced by the Central Support Service for Experimental Research (SCSIE, Spanish acronym) at the University of Valencia (Valencia, Spain).This work was supported by funding of the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT, Chile) [Grant Numbers FONDAP No. 15110027 and FONDECYT No. 1150695]. J.B. also acknowledges support received by CONICYT [Doctoral Scholarship No. 21140421].Renibacterium salmoninarum, a slow-growing facultative intracellular pathogen belonging to the high C+G content Actinobacteria phylum, is the causative agent of bacterial kidney disease, a progressive granulomatous infection affecting salmonids worldwide. This Gram-positive bacterium has existed in the Chilean salmonid industry for >30 years, but little or no information is available regarding the virulence mechanisms and genomic characteristics of Chilean isolates. In this study, the genomes of two Chilean isolates (H-2 and DJ2R)were sequenced, and a search was conducted for genes and proteins involved in virulence and pathogenicity, andwecompare with the type strain ATCC 33209T genome. The genome sizes of H-2 and DJ2R are 3,155,332 bp and 3,155,228 bp, respectively. They genomes presented six ribosomal RNA, 46 transcription RNA, and 25 noncodingRNA, and both had the same 56.27% G+C content described for the type strain ATCC 33209 T. A total of 3,522 and 3,527 coding sequences were found for H-2 and DJ2R, respectively. Meanwhile, the ATCC 33209T type strain had 3,519 coding sequences. The in silico genome analysis revealed a genes related to tricarboxylic acid cycle, glycolysis, iron transport and others metabolic pathway. Also, the data indicated that R salmoninarum may have a variety of possible virulence-factor and antibiotic-resistance strategies. Interestingly, many of genes had high identities with Mycobacterium species, a known pathogenic Actin obacteria bacterium. In summary, this study provides the first insights into and initial steps towards understanding the molecular basis of antibiotic resistance, virulence mechanisms and host/environment adaptation in twoChilean R. salmoninarum isolates that contain proteins of which were similar to those of Mycobacterium. Furthermore, important information is presented that could facilitate the development of preventive and treatment measures against R. salmoninarum in Chile and worldwide. © The Author(s) 2018.https://academic.oup.com/gbe/article/10/7/1816/504777

On the treatment of repeated observations in panel data: efficiency of mixed logit parameter estimates

Travel demand models are often estimated using cross-sectional data. Although the use of panel data has recently increased in many areas, there are still many aspects that have not been analyzed fully. Some examples of unexplored topics are: the optimal length of panel surveys and the resulting issue of how to model panel data correctly in the presence of repeated observations (for example, several trips per week, by people in a panel with waves every six months) and whether, and to what extent, this affects the efficiency of the estimated parameters and their capability to replicate the true situation. In this paper we analyse this issue and test the effect of including journeys made, with the same characteristics, several times in a week. A broad variety of models accounting for fixed parameters but also for random heterogeneity and correlation among individuals were estimated using each of real and synthetic data. The real data come from the Santiago Panel (2006-2008), while the synthetic data were appropriately generated to examine the same problem in a controlled experiment. Our results show that having more observations per individual increases the probability of capturing effects (different types of heterocedasticity), but having identical observations in a data panel reduces the capability to reproduce true phenomena. Consequently, the definition of panel survey duration requires us to consider the implicit level of routine that is present as represented in the proportion of identical observations

Inertia and shock effects on mode choice panel data: implications of the Transantiago implementation

The mode choice process, especially in the case of commuter trips, reflects the strong tendency people have to simplify the assessment of their options when confronted with successive well-known decisions. Thus, it is common to repeat the “habitual” choice over time involving a potentially important inertia element. However, while inertia effects increase the probability of maintaining the same choice in a stable situation, in a changing environment i.e. one that is disrupted by a radical or significant policy intervention, user behaviour may be affected by a specific response to abrupt changes. Shock effects of this kind could increase the probability of individuals leaving their habitual choices. Temporal effects have been commonly ignored in practical studies, as most demand models to date have been based on cross-sectional data. A few recent studies dealing with panel data have managed to incorporate inertia effects, but there are no studies that have included both inertia and shock effects. To address this, we started by building a data panel around the introduction of a new and radical policy for the conurbation of Santiago de Chile. The final aim was to develop mode choice models incorporating the effects of three main forces involved in the choice process: (1) the relative values of the modal attributes, (2) the inertia effect, and (3) the shock resulting from and abrupt policy intervention. This paper presents the formulation of an inertia-shock model and its application to each of simulated and real data. The results confirm that changing systems should be modelled respecting the presence of both inertia and shock effects, otherwise serious errors in model estimation may arise