Objective: To evaluate the diagnostic value of DWI in assessment of metastatic neck lymph node in a sample of Iranian patients with Head and Neck cancer. Methods: 25 patients with 80 neck lymph nodes were analyzed using 1.5 T MRI. DWI was performed with b values of 0 and 1,000 s/mm 2. Short axis diameter and ADC values (min, max and mean) were calculated for metastatic and non-metastatic neck LNs and results were compared with histopathological findings. The optimal ADC thresholds were analyzed using receiver coefficient characteristic (ROC) curves for discriminating between metastatic and benign neck lymph nodes. Result: Histopathological findings revealed that there are 45% (n=36) metastatic and 55% (n=44) non-metastatic neck LNs respectively. There was no statistically significant difference in short axis diameter between the two groups (p = 0.346). However, The ADC values of metastatic neck LNs were significantly lower than those of non-metastatic neck LNs (p < 0.001); 0.90 ± 0.10 × 10-3 mm 2 /s vs 1.06 ± 0.12 × 10-3 mm 2 /s (ADC mean), 0.78 ± 0.08 × 10-3 mm 2 /s vs 0.92 ± 0.20× 10-3 mm 2 /s (ADC min) and 1.02 ± 0.12 × 10-3 mm 2 /s vs 1.24 ± 0.15 × 10-3 mm 2 /s (ADC max). The optimal mean ADC threshold value was equal to 0.996 × 10-3 mm 2 /s for differentiating malignant from benign lymph nodes with sensitivity, specificity and accuracy of 80.56 %, 77.27 % and 71.59 % respectively. Conclusion: MR diffusion imaging and ADC values as a non-invasive technique can assess metastatic neck LNs in head and neck cancer with higher sensitivity, specificity and accuracy.
Polymerization of propylene was performed in a pilot fluidized bed reactor, resembling an industrial unit. In order to detect agglomeration in this reaction process, wall vibration signatures of the bed, which contains useful information about its hydrodynamics, were measured by an accelerometer. This approach is non-intrusive and can be easily applied in industry. Different methods employed to analyze the measured vibration signatures. Average cycle frequency of the signatures showed that agglomerates were formed and settled down in the reactor during the process. Plot of the power spectral density function of vibration signals showed that the peak corresponding to the dominant frequency generated by bubbles is located around 2,000 Hz. Energy of the signal among the three hydrodynamic structures in the bed (i. e., micro, meso and macro-scales) showed a decrease in share of macro-scale and a slight increase in share of micro and meso-scales due to the formation of agglomerates. The principal component analysis was performed to characterize the hydrodynamic changes occurred in bed due to formation of agglomerates during the polymerization reaction. Using the S-statistic test, changes in the hydrodynamics of the bed due to formation of agglomerates were detected about 20 minutes before defluidization.
A B S T R A C TThe main goal of this paper is to simulate the performance of Multiple Effect Desalination (MED) units in operation to predict the influence of variation of different input parameters on the amount of product, GOR value and thermodynamic condition of the unit during the operation. Therefore, for a given system with specified geometry, including thermocompressor, heat transfer area of the effects and condenser, mass and energy balance equations can be written and solved simultaneously in a set of nonlinear equations for different parts of the system. The results obtained by the simulation code are compared the experimental data obtained from an MED-TVC unit installed in Assaluyeh city in Kavian petrochemical company. There is a good agreement between the calculated results and the experimental data. Results show that the variation in the seawater temperature and the scaling amount around the tubes of the first effect have the most influence on variation in production rate.
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