Production of pions, kaons and protons in pp collisions at s=900\sqrt{s}=900 GeV with ALICE at the LHC

The production of $\pi^+$, $\pi^-$, $K^+$, $K^-$, p, and pbar at mid-rapidity has been measured in proton-proton collisions at $\sqrt{s} = 900$ GeV with the ALICE detector. Particle identification is performed using the specific energy loss in the inner tracking silicon detector and the time projection chamber. In addition, time-of-flight information is used to identify hadrons at higher momenta. Finally, the distinctive kink topology of the weak decay of charged kaons is used for an alternative measurement of the kaon transverse momentum ($p_{\rm T}$) spectra. Since these various particle identification tools give the best separation capabilities over different momentum ranges, the results are combined to extract spectra from $p_{\rm T}$ = 100 MeV/$c$ to 2.5 GeV/$c$. The measured spectra are further compared with QCD-inspired models which yield a poor description. The total yields and the mean $p_{\rm T}$ are compared with previous measurements, and the trends as a function of collision energy are discussed.Comment: 24 pages, 18 captioned figures, 5 tables, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/388

Assessment of the control measures of the category A diseases of Animal Health Law: peste des petits ruminants

EFSA received a mandate from the European Commission to assess the effectiveness of some of the control measures against diseases included in the Category A list according to Regulation (EU) 2016/429 on transmissible animal diseases (‘Animal Health Law’). This opinion belongs to a series of opinions where these control measures will be assessed, with this opinion covering the assessment of control measures for peste des petits ruminants (PPR). In this opinion, EFSA and the AHAW Panel of experts review the effectiveness of: (i) clinical and laboratory sampling procedures, (ii) monitoring period and (iii) the minimum radii of the protection and surveillance zones, and the minimum length of time the measures should be applied in these zones. The general methodology used for this series of opinions has been published elsewhere; nonetheless, the transmission kernels used for the assessment of the minimum radii of the protection and surveillance zones are shown. Several scenarios for which these control measures had to be assessed were designed and agreed prior to the start of the assessment. The monitoring period of 21 days was assessed as effective, except for the first affected establishments detected, where 33 days is recommended. It was concluded that beyond the protection (3 km) and the surveillance zones (10 km) only 9.6% (95% CI: 3.1–25.8%) and 2.3% (95% CI: 1–5.5%) of the infections from an affected establishment may occur, respectively. This may be considered sufficient to contain the disease spread (95% probability of containing transmission corresponds to 5.3 km). Recommendations provided for each of the scenarios assessed aim to support the European Commission in the drafting of further pieces of legislation, as well as for plausible ad-hoc requests in relation to PPR

Assessment of the control measures of the category A diseases of Animal Health Law: Classical Swine Fever

EFSA received a mandate from the European Commission to assess the effectiveness of some of the control measures against diseases included in the Category A list according to Regulation (EU) 2016/429 on transmissible animal diseases (‘Animal Health Law’). This opinion belongs to a series of opinions where these control measures will be assessed, with this opinion covering the assessment of control measures for Classical swine fever (CSF). In this opinion, EFSA and the AHAW Panel of experts review the effectiveness of: (i) clinical and laboratory sampling procedures, (ii) monitoring period and (iii) the minimum radii of the protection and surveillance zones, and the minimum length of time the measures should be applied in these zones. The general methodology used for this series of opinions has been published elsewhere; nonetheless, details of the model used for answering these questions are presented in this opinion as well as the transmission kernels used for the assessment of the minimum radius of the protection and surveillance zones. Several scenarios for which these control measures had to be assessed were designed and agreed prior to the start of the assessment. Here, several recommendations are given on how to increase the effectiveness of some of the sampling procedures. Based on the average length of the period between virus introduction and the reporting of a CSF suspicion, the monitoring period was assessed as non-effective. In a similar way, it was recommended that the length of the measures in the protection and surveillance zones were increased from 15 to 25 days in the protection zone and from 30 to 40 days in the surveillance zone. Finally, the analysis of existing Kernels for CSF suggested that the radius of the protection and the surveillance zones comprise 99% of the infections from an affected establishment if transmission occurred. Recommendations provided for each of the scenarios assessed aim to support the European Commission in the drafting of further pieces of legislation, as well as for plausible ad hoc requests in relation to CSF

Assessment of animal diseases caused by bacteria resistant to antimicrobials: Poultry

open25siIn this opinion, the antimicrobial-resistant bacteria responsible for transmissible diseases that constitute a threat to poultry health have been assessed. The assessment has been performed following a methodology based on information collected by an extensive literature review and expert judgement. Details of the methodology used for this assessment are explained in a separate opinion. A global state of play is provided for: Avibacterium (Haemophilus) paragallinarum, Bordetella avium, Clostridium perfringens, Enterococcus faecalis and Enterococcus cecorum, Erysipelothrix rhusiopathiae, Escherichia coli, Gallibacterium spp., Mycoplasma synoviae, Ornithobacterium rhinotracheale, Pasteurella multocida, Riemerella anatipestifer and Staphylococcus aureus. Among those bacteria, EFSA identified Escherichia coli, Enterococcus faecalis and Enterococcus cecorum with ≥ 66% certainty as being the most relevant antimicrobial resistant bacteria in the EU based on the available evidence. The animal health impact of these most relevant bacteria, and their eligibility for being listed and categorised within the Animal Health Law Framework, will be assessed in separate scientific opinions.mixedNielsen S.S.; Bicout D.J.; Calistri P.; Canali E.; Drewe J.A.; Garin-Bastuji B.; Gonzales Rojas J.L.; Gortazar Schmidt C.; Herskin M.; Michel V.; Miranda Chueca M.A.; Padalino B.; Pasquali P.; Roberts H.C.; Spoolder H.; Stahl K.; Velarde A.; Viltrop A.; Winckler C.; Dewulf J.; Guardabassi L.; Hilbert F.; Mader R.; Baldinelli F.; Alvarez J.Nielsen S.S.; Bicout D.J.; Calistri P.; Canali E.; Drewe J.A.; Garin-Bastuji B.; Gonzales Rojas J.L.; Gortazar Schmidt C.; Herskin M.; Michel V.; Miranda Chueca M.A.; Padalino B.; Pasquali P.; Roberts H.C.; Spoolder H.; Stahl K.; Velarde A.; Viltrop A.; Winckler C.; Dewulf J.; Guardabassi L.; Hilbert F.; Mader R.; Baldinelli F.; Alvarez J

The t-stability number of a random graph

Given a graph G = (V,E), a vertex subset S is called t-stable (or t-dependent) if the subgraph G[S] induced on S has maximum degree at most t. The t-stability number of G is the maximum order of a t-stable set in G. We investigate the typical values that this parameter takes on a random graph on n vertices and edge probability equal to p. For any fixed 0 < p < 1 and fixed non-negative integer t, we show that, with probability tending to 1 as n grows, the t-stability number takes on at most two values which we identify as functions of t, p and n. The main tool we use is an asymptotic expression for the expected number of t-stable sets of order k. We derive this expression by performing a precise count of the number of graphs on k vertices that have maximum degree at most k. Using the above results, we also obtain asymptotic bounds on the t-improper chromatic number of a random graph (this is the generalisation of the chromatic number, where we partition of the vertex set of the graph into t-stable sets).Comment: 25 pages; v2 has 30 pages and is identical to the journal version apart from formatting and a minor amendment to Lemma 8 (and its proof on p. 21