Effects of Post-harvest Pre-cooling Processes and Cyclical Heat Treatment on the Physico-chemical Properties of "Red Haven Peaches" and "Shahmiveh Pears" During Cold Storage

Rosana G. Moreira, Editor-in-Chief; Texas A&M UniversityThis is a paper from International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 6 (2004): A. Kalbasi-Ashtari. Effects of Post-harvest Pre-cooling Processes and Cyclical Heat Treatment on the Physico-chemical Properties of "Red Haven Peaches" and "Shahmiveh Pears" During Cold Storage. (July 2004)

Purification and partial characterization of serum immunoglobulin from Persian sturgeon (Acipenser persicus)

In this study, immunoglobulins from serum of Persian sturgeon (Acipenser persicus) were purified and partially characterized. Immunoglobulins were purified from the pooled sera by a combination of salt precipitation, Ion-exchange chromatography and gel filtration methods. DEAE sepharosefast flow and sepharose CL-6B columns were used for Ion exchange-chromatography, and gel filtration, respectively. The purity, molecular weight and molecular distribution of the immunoglobulin preparations was determined by gel electrophoresis (SDS-P AGE) in reducing and non-reducing situations. In gel filtrated immunoglobulins two distinct peaks, high molecular weight (HMW Ig) and low molecular weight (LMW Ig) were obtained. Both HMW Ig and LMW Ig had identical heavy and light chains of 72-75 KDa and 27-29 KDa, respectively, in reducing SDS-P AGE. HMW Ig contained a group of bands, including two major bands in non-reducing SDS-PAGE, In contrast LMW Ig contain more than half of the total immunoglobulin, was 190 KDa. In ion exchange chromatography, immunoglobulins were eluted in three peaks. The first was exclusively monomer and others were mixture of monomer and polymers. This is the first report on persian sturgeon immunoglobulins. Results of this investigation showed that persian sturgeon immunoglobulins was not homogenous in respect of molecular distribution, PI and the type of light chain. The presence of more than one genes for light and\or heavy chains or post transcriptional and\or post modifications may be responsible for these variations

Induction of tetraploidy in rainbow trout (Oncorhynchus mykiss) by heat shock

This study has been conducted for determination of optimum time and duration of thermal shock on tetraploidy induction in Rainbow trout. This study was carried out by induction of 28°C thermal shock in different times after fertilization (49.5, 54.0, 58.5, 63.0, 67.5, 72.0, 76.5 and 81,0°C/hour and different duration (8, 10 and 12 min). Nuclear erythrocytes, cellular area and volume measurement were determined among blood smears of fingerling and statistic analysis showed that, induction of tetraploidy was conducted between 0-75% on various treatment, but highest tetraploidy yield (8.4%) was achieved by thermal shock on 28°C within 12 minutes, 74 degree-hour after fertilization. Moreover, tetra ploidy diagnostic was also approved by determination of nucleolus number in fishes. In this respect tetraploid and diploid fishes have 3-4 and 1-2 nucleolus, respectively

Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data

Resource demand estimation is essential for the application of analyical models, such as queueing networks, to real-world systems. In this paper, we investigate maximum likelihood (ML) estimators for service demands in closed queueing networks with load-independent and load-dependent service times. Stemming from a characterization of necessary conditions for ML estimation, we propose new estimators that infer demands from queue-length measurements, which are inexpensive metrics to collect in real systems. One advantage of focusing on queue-length data compared to response times or utilizations is that confidence intervals can be rigorously derived from the equilibrium distribution of the queueing network model. Our estimators and their confidence intervals are validated against simulation and real system measurements for a multi-tier application

An investigation on the micropyle number in the ova of the strugeon species in Caspian Sea

The micropyle number in the ova of sturgeon species from the South Caspian Sea was investigated. The study was conducted on female broodfishes of three species of sturgeon (Persian sturgeon Acipenser persicus, Stetates sturgeon A. stellatus and great sturgeon Huso huso) included 44 Persian sturgeon, 13 stellate sturgeon and 8 great sturgeon specimens. Fifty eggs were randomly collected from each broodfish and the micropyle number of totally 3250 eggs was determined. Out of 44 Persian sturgeon used, 14 specimens were collected from the south-east Caspian region (Golestan Province, Shaid Marjani Center) and 30 were from the south-west Caspian region (Guilan Province, Shahid Dr. Beheshti Center). The stellate sturgeon specimens were taken from the south-west and the great sturgeon specimens from the south-east Caspian region. The obtained result showed that the mean micropyle number in Persian sturgeon caught from the south-east Caspian region was 8 whereas in those caught from the south-west region was 9. There was no significant difference (p>0.95) in the micropyle number of Persian sturgeon collected from the south-east and south-west regions. The mean micropyle number determined for stellate and great sturgeon was 5. The outer diameter of the micropyle in the Persian, stellate, and great sturgeon were 22 μm, 17 μm and 19 μm respectively

Comparison of digestive enzyme activity in the stomach, pyloric caeca and intestine in diploid and triploid female of rainbow trout (Oncorhynchus mykiss)

The effects of chromosome manipulation on the digestive enzyme activity in the rainbow trout were studied. The enzymes included Pepsin, Trypsin, Chymotrypsin, cileimylase, Lipase and Alkaline Phosphatase which were assessed in diploid and triploid female of rainbow trout. Pepsin activity in the stomach of the assessed fish showed no significant difference between the diploid and triploid fish (P>0.05). The measurement of Trypsin and Chymotrypsin activity in the intestine and pyloric caeca revealed no significant difference in the treated and untreated fish (P>0.05). The activity of a-Amylase, Lipase and Alkaline Phosphatase showed no significant difference in the intestine and pyloric caeca of the diploid and triploid fish (P>0.05).The results indicated that chromosome manipulation in rainbow trout had no effects on digestive enzyme activity

Learning Queuing Networks by Recurrent Neural Networks

It is well known that building analytical performance models in practice is difficult because it requires a considerable degree of proficiency in the underlying mathematics. In this paper, we propose a machine-learning approach to derive performance models from data. We focus on queuing networks, and crucially exploit a deterministic approximation of their average dynamics in terms of a compact system of ordinary differential equations. We encode these equations into a recurrent neural network whose weights can be directly related to model parameters. This allows for an interpretable structure of the neural network, which can be trained from system measurements to yield a white-box parameterized model that can be used for prediction purposes such as what-if analyses and capacity planning. Using synthetic models as well as a real case study of a load-balancing system, we show the effectiveness of our technique in yielding models with high predictive power

Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data

Resource demand estimation is essential for the application of analyical models, such as queueing networks, to real-world systems. In this paper, we investigate maximum likelihood (ML) estimators for service demands in closed queueing networks with load-independent and load-dependent service times. Stemming from a characterization of necessary conditions for ML estimation, we propose new estimators that infer demands from queue-length measurements, which are inexpensive metrics to collect in real systems. One advantage of focusing on queue-length data compared to response times or utilizations is that confidence intervals can be rigorously derived from the equilibrium distribution of the queueing network model. Our estimators and their confidence intervals are validated against simulation and real system measurements for a multi-tier application