Sentence examples for index farm from inspiring English sources

In both part-time employment scenarios, relative risk of exposure was significantly higher for farms that had a different integrator affiliation than the index farm compared to farms within the same integrator group as the index farm (p<0.05).

Farms outside the integrator group of the index farm faced minimal risk at 2 days of infectiousness of the index farm (<1%) and upwards of 4% risk of exposure by 15 days of infectiousness [mean = 4.4 (3.6.06.0)].

Risk estimates in the part-time worker scenarios assume that the index farm also engages in the given employment practice.

Assuming a 2-day period of viral survival on a vehicle, a second farm affiliated with the same integrator group as the index farm would likely face an exposure risk of more than 3% with a 2 day period of infectiousness at the index farm [mean  = 3.6 (95% CI: 2.4, 4.9)] (Table 3).

If 7 days of viral survival on a vehicle is assumed (which might occur as a result of manure on tires, for example [46], [47]), farms within the same integrator group as the index farm may face an exposure risk greater than 6% at 2 days of infectiousness of the index farm [mean  = 6.4 (4.2, 8.6)].

In all scenarios, however, the effect of being within the same integrator group as the index farm contributed to a greater relative increase in risk than did changes to the model parameters of duration of infectiousness at the index farm duration of viral survival on a vehicle.

However, this species is only found on offshore islands, has limited dispersal, and does not overlap with the index farms.

Therefore, influenza A (H5N1) introduced into poultry markets in 2002 likely was amplified within them and transmitted back to a few index farms, initiating each genotype-specific outbreak.

The plasmid spread to unrelated E. coli isolates within an index cattle farm and persisted within the environment.

Likewise, an ecological analysis in South Korea found strong association of pesticide self-poisoning mortality rates with an index of farming activities and population [ 12].

In particular, it is tested on twelve UCI classification datasets, a facial recognition problem, three real world prediction problems (2 chaotic time series of geomagnetic activity indices and wind farm power generation data), two synthetic case studies with constant and nonconstant noise variance as well as k-selector and linear programming problems.