A Population Dynamics Model for Prawn Aquaculture

Abstract

We have used a stochastic population model to simulate the prawn size distribution in the grow‐out ponds as a function of time. The model allows for growth and mortality parameters which are dependent on size class and pond biomass. We have written a computer program based on this model in which the user inputs a stocking number, a stocking size distribution, a stocking schedule, the harvest size classes, and a harvest schedule. The computer then computes the number of prawns and the prawn size distribution in the pond at specified time increments and a quarterly production economics summary. We compare simulated growth and harvest data generated by the program to actual growth and harvest data from Hawaii and Florida. We also use the program to evaluate the effects of stocking number, stocking schedule and stocking size on annual yields from a prawn grow‐out pond.

Using Prospective Risk Analysis Tools to Improve Safety in Pharmacy Settings: A Systematic Review and Critical Appraisal

“…All analyses conducted in inpatient setting used FMEA. [18][19][20][21][22][23][24][25][26][27] The majority of them did not assess dispensing separately, but as part of the entire medication use process. Only 2 studies were undertaken to specifically assess dispensing as an individual process.…”

“…[23][24][25] Only 2 analyses evaluated the dispensing of all medication categories. 20,26 The studies included in this review identified various failure modes throughout the dispensing process, most commonly related to the transcription, [18][19][20][22][23][24][25] selection, 18,20,21,26,27 preparation, 18,19,23,25 and validation 19,20,24,25 phases (Table 2). Accordingly, the reviewed publications propose numerous general and stage-specific corrective actions, out of which the introduction of computerized prescribing and electronic transmission of prescriptions to the pharmacy, 19,22,25 use of bar code technology in the picking and packing phase, 27 direct label printing from the server (i.e., prescription), 19,25 as well as automation of compounding 25 proved to be the most effective ones (Table 3).…”

“…In most FMEA studies, brainstorming was the only data source used for specifying potential failure modes as well as for quantifying the related risks. 18,19,21,22,[24][25][26] Only a few research teams used factual data on the incidence and types of medication errors in addition to brainstorming. 20,23,27 The study using ST-PRA also considered data from published literature to complement expert opinion for defining potential failure modes in an abbreviated FMEA (Table 5).…”