DETERMINATION OF CELL TYPE AND HAEMOCYTE MORPHOMETRIC CHARACTERISTICS OF WESTERN AUSTRALIA FRESHWATER CRAYFISH (Cherax cainii) AT DIFFERENT TEMPERATURES IN VITRO

The purpose of this study was to identify and morphologically characterize the hemocyte cell types of freshwater crayfish, Cherax cainii. In addition to morphological observations using a light microscope (LM) and electron transmission microscope (TEM), a flow cytometer (FCM) is also used. Three main types of haemocyte of C. cainii were identified by LM, TEM, and FCM. Determination of haemocyte by LM based on the number, size of cytoplasmic granules and the ratio of N:C. These cells are Hyaline (HC), Small Granule (SGC), and Large Granule (LGC) cells. Three types of haemocyte were also observed by TEM based on cell and nucleus size, granule diameter, number of cytoplasmic granules per cell and N:C. Haemocyte population was successfully detected with FCM based on forward scatter (FSC) signals, versus side scattering signals/side scatter (SSC), with plot data via scatter parameter gating. Three cluster formations were observed, which were temporarily classified as SGC, LGC, and HC regions. Morphometric analysis was performed with TEM on C. cainii haemocyte to measure various cellular features. Some morphological features vary between types of haemocyte and are also affected by temperature. Total hemocyte count (THC) and differential hemocyte count (DHC) are calculated using FCM. THC increases with higher temperatures, from 1,9 x 106 /ml at 20 °C to 4.9 x 106 /ml at 30 °C. The most abundant hemocyte at all temperatures is HC, followed by SGC and LGC.

A Maintenance Strategy for Heat Transfer Equipment Subject to Fouling: A Probabilistic Approach

Fouling of heat transfer surfaces introduces a major uncertainty into the design and operation of heat transfer equipment. After a brief discussion on impact of fouling, we present and discuss a stochastic approach to the analysis of fouling models. In view of the performance indicator (U/Uc) of the heat exchangers, a maintenance strategy for planned maintenance schedules is presented. Various scenarios of reliability based maintenance strategy are introduced. The strategy is explained in terms of the scatter parameter (α) of the time-to-fouling distribution corresponding to a critical level of fouling, and the risk factor (p) representing the probability of tubes being fouled to a critical level after which a cleaning cycle is needed. In addition, the cost implications of the above mentioned strategy are explained and their impact on heat exchanger maintenance is highlighted.