Stochastic Modelling of Pilling Degree Changes During the Pilling Process of Wool Fabrics

As a fabric surface defect, pilling gives clothes an unpleasant appearance and is often characterized with small, complex clusters of fibers attaching to the surface of the garment caused by the fiber migration from yams to the fabric surface as the fabric rubs against itself, another fabric, or even the skin. In this study, a Markov chain model was built based on the pilling propensity of wool fabrics, evaluated with a scale ranging from 1 (severe pilling) to 5 (non-pilling). These degrees were defined as the state space of Markov chain. The numerical values of the transition probability matrix related to the pilling degrees were obtained by maximum likelihood estimation (MLE). Based on the matrix, it was intended to model the changes in the pilling process of woven wool fabrics. Furthermore, given that the fabric will eventually be in state 1, 2 or 3, accepted as unpleasant appearance; the conditional mean first passage times for any transient state to enter any recurrent state for the first time were determined

Strontium (II) Biosorption Studies on Starch-Functionalized Magnetic Nanobiocomposites Using Full Factorial Design Method

The purpose of this research was to fabricate starch based magnetic nanobiocomposites using two different starch types (corn and wheat) and to examine the effects of some experimental parameters (such as starch concentration, NaOH concentration and aging time of nanoparticles) that play a role in the synthesis products. The characterization of the starch-based magnetic-nanobiocomposite materials were realized with several techniques. In the previous study, MW_S3 and MC_S3 from starch stabilized magnetite nanobiocomposites were selected for further studies with smaller particle size and large surface areas, as a result of calculations based on XRD results and BET surface area. The usability of starch-based magnetic-nanobiocomposite materials, which can provide rapid separation with their magnetic properties and are not toxic, in removing Sr(II) ions from aqueous solutions has been investigated. The parameters affecting the biosorption were investigated using a full factorial experimental design. In the biosorption study, pH, temperature, initial Sr(II) concentration and contact time were determined as four independent variables. The regression coefficients were found using the least squares method and the response surface graphs were created according to the polynomial equation obtained from the full factorial experimental design. ANOVA (analysis of variance) analysis within the 95% confidence interval of the model applied for the full factorial experimental design was examined and the compatibility of the model with the experimental findings was examine. It is seen that the biosorption of Sr(II) on MW_S3 and MC_S3 nanobiocomposites increases with increasing concentration in the range of 25-75 ppm. As a result of the regression analysis, it was observed that pH was statistically significant (p < 0.05) and had an increasing effect for MW_S3. Evaluating the results obtained, it was found that the combined effects of the parameters on the biosorption of Sr(II) on MW_S3 adsorbent were not significant, but the combined effects of concentration and time were only significant on the adsorption of Sr(II) on MC_S3 adsorbent. From the solution of the equation obtained in the full factorial experimental design, it has been determined that the optimum biosorption conditions for MW_S3 adsorbent are; pH is 7, temperature is 34.87 degrees C, initial Sr(II) concentration is 75 mg/L and contact time is 30 min. Optimum adsorption conditions for MC_S3 adsorbent were determined to be pH is 8, temperature is 34.46 degrees C, initial Sr(II) concentration is 74.83 mg/L and contact time is 59.54 min. The composition and chemical state of the magnetic nanobiocomposites were investigated by XPS analysis after Sr(II) biosorption. For the purpose of determine the adsorption model, the relevant parameters were calculated using Langmuir, Freundlich and Dubinin-Radushkevich isotherms. Gibbs free energy change, enthalpy and entropy values, which are the values of adsorption thermodynamics, were calculated.Ege University Scientific Research Project Unit Project [FYL-2020-22227]This study was financially supported by Ege University Scientific Research Project Unit Project No. FYL-2020-22227

The value of frozen section evaluation in the management of borderline ovarian tumors

WOS: 000299473200007PubMed ID: 22269402Purpose: To evaluate the accuracy of a frozen section and to analyze the factors affecting frozen section results in cases of borderline ovarian tumors (BOTs). Materials and Methods: The files and pathological reports of 82 cases diagnosed with BOT at our clinic, between January 1994 and June 2009, have been retrospectively evaluated. The frozen section results were compared to the permanent paraffin section results. Accuracy, overdiagnosis, and underdiagnosis rates were estimated. The factors affecting the diagnosis were also evaluated using logistic regression analysis. Results: The mean age was 40.16 14.01 years. Of the patients, 47.6 had serous and 42.7 had mucinous histology. About 90 of the cases were in stage I. The rate of correct diagnosis with frozen section was 69.5. The rates of overdiagnosis and underdiagnosis were 1.2 and 29.3; respectively. The factors affecting the diagnosis were determined as, the dimension of the ovarian mass (P = 0.005), presence of a solid component (P = 0.000), preoperative CA 125 value (P = 0.016), and intraoperative rupture of the ovarian cyst (P = 0.049). Conclusion: In the frozen section evaluation of BOTs, the underdiagnosis that restricts the diagnostic performance of the method seems to be a major problem. A more careful approach is therefore needed, while choosing a proper surgical technique during laparotomy for ovarian masses. In order to reduce the false diagnosis and surgical morbidity, the frozen section analysis should be applied by experienced pathologists and the possible predictive factors affecting a false diagnosis should carefully be taken into consideration

The value of frozen section evaluation in the management of borderline ovarian tumors

Purpose: To evaluate the accuracy of a frozen section and to analyze the factors affecting frozen section results in cases of borderline ovarian tumors (BOTs). Materials and Methods: The files and pathological reports of 82 cases diagnosed with BOT at our clinic, between January 1994 and June 2009, have been retrospectively evaluated. The frozen section results were compared to the permanent paraffin section results. Accuracy, overdiagnosis, and underdiagnosis rates were estimated. The factors affecting the diagnosis were also evaluated using logistic regression analysis. Results: The mean age was 40.16 ± 14.01 years. Of the patients, 47.6% had serous and 42.7% had mucinous histology. About 90% of the cases were in stage I. The rate of correct diagnosis with frozen section was 69.5%. The rates of overdiagnosis and underdiagnosis were 1.2 and 29.3%; respectively. The factors affecting the diagnosis were determined as, the dimension of the ovarian mass (P = 0.005), presence of a solid component (P = 0.000), preoperative CA 125 value (P = 0.016), and intraoperative rupture of the ovarian cyst (P = 0.049). Conclusion: In the frozen section evaluation of BOTs, the underdiagnosis that restricts the diagnostic performance of the method seems to be a major problem. A more careful approach is therefore needed, while choosing a proper surgical technique during laparotomy for ovarian masses. In order to reduce the false diagnosis and surgical morbidity, the frozen section analysis should be applied by experienced pathologists and the possible predictive factors affecting a false diagnosis should carefully be taken into consideration

Second primary cancers following borderline ovarian tumors

WOS: 000290536100034PubMed ID: 20628749Several studies have reported an increased risk of second primary cancers subsequent to invasive epithelial ovarian cancer. However, there is no adequate data regarding such risk in borderline ovarian tumors (BOTs). The aim of this study was to evaluate the risk of subsequent second primary cancers among women with BOTs. BOT patients treated in our center between December 1985 and April 2009 were retrospectively screened for developing second primary cancer during follow-up period. There were 96 women diagnosed with BOT. Mean age at the time of diagnosis was 47 +/- A 14.3, ranging from 19 to 79. Eighty-eight (91.6%) patients had stage I disease, two patients (2.1%) had stage II and six (6.2%) had stage III. Twenty-five (26.0%) patients received platinum-based adjuvant chemotherapy. Mean follow-up time was 96.5 +/- A 442 months (range: 9-280 months). There were ten (10.4%) recurrences. Only one patient developed second primary cancer. Second primary cancer observed in this case was basal cell carsinoma of the eyelid, which was diagnosed 2 years after primary disease. There were no patients with common women's cancers such as breast and colorectal cancers. These findings do not suggest increased risk of subsequent cancers in patients with BOT. However, population-based studies are needed for evaluating exact risk of developing second primary malignancies in women with BOTs