The analysis of the incidence of cervical carcinomas based on the material from Histopathological Laboratory located in Zawiercie District Hospital

Objectives: The aim of the study was to analyze the incidence of malignant cervical carcinomas found in the material from Histopathological Laboratory in Zawiercie District Hospital. Material and methods: The examined materials included histopathological results concerning segments and scrapings from gynecological procedures and the results of the segments, collected during gynecological operations performed in the years 2000-2005, in which malignant neoplasms of uterine cervix had been diagnosed. The data concerning the neoplasms were analysed, taking into account the following parameters: the number of neoplasms found in relation to the total number of diagnostic procedures performed, patients’ age, histological type of the neoplasm and the degree of clinical progression based on FIGO classification. Results: In the examined material, there were 50 cases of cervical carcinomas, with the highest incidence in patients aged between 50-59. The most common morphological type was squamous carcinoma and the majority of cervical carcinomas was characterized by the Io of disease clinical progression – 38 cases, also 4 preinvasive carcinomas were found and 8 cancers of the IIo of progression, according to FIGO classification. Conclusion: A considerable decrease of cervical carcinomas incidence, observed in the study period and the number of neoplasms found in an early progression stage are the effect of conducted screening examinations, due to which precancerous conditions are diagnosed and treated

Poisoning deaths in Poland : types and frequencies reported in Łódź, Kraków, Sosnowiec, Gdańsk, Wrocław and Poznań during 2009-2013

Objectives: The aim of this study has been to assess the characteristics of acute poisoning deaths in Poland over a period of time 2009–2013. Material and Methods: The analysis was based on the data obtained from the patient records stored in toxicology departments in 6 cities – Łódź, Kraków, Sosnowiec, Gdańsk, Wrocław and Poznań. Toxicological analyses were routinely performed in blood and/or urine. Major toxic substances were classified to one of the following categories: pharmaceuticals, alcohol group poisonings (ethanol and other alcohols), gases, solvents, drugs of abuse, pesticides, metals, mushrooms, others. Cases were analyzed according to the following criteria: year, age and gender of analyzed patients, toxic substance category and type of poisoning. The recorded fatal poisonings were classified according to the International Classification of Diseases. Results: The record of 261 deaths were retrospectively reviewed. There were 187 males (71.64%) and 74 females (28.36%) and the male to female ratio was 2.52. Alcohol group poisonings were more frequently responsible for deaths in men compared to all poisonings, 91.1% vs. 71.6%, respectively (p < 0.05), and pharmaceutical agents were more frequently responsible for deaths in women, 47.4% vs. 28.4%, (p < 0.05). Methanol was the most common agent in the alcohol group poisonings, accounting for 43.75% (N = 49), followed by ethylene glycol, 39.29% (N = 44), and ethanol, 16.96% (N = 19). Conclusions: Epidemiological profile data from investigation of poisoning deaths in Poland may be very useful for the development of preventive programs. Int J Occup Med Environ Health 2017;30(6):897–90

Assessment of the possibility of using data mining methods to predict sorption isotherms of selected organic compounds on activated carbon

The paper analyses the use of four data mining methods (Support Vector Machines. Cascade Neural Networks. Random Forests and Boosted Trees) to predict sorption on activated carbons. The input data for statistical models included the activated carbon parameters, organic substances and equilibrium concentrations in the solution. The assessment of the predictive abilities of the developed models was made with the use of mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE). The computations proved that methods of data mining considered in the study can be applied to predict sorption of selected organic compounds 011 activated carbon. The lowest values of sorption prediction errors were obtained with the Cascade Neural Networks method (MAE = 1.23 g/g; MAPE = 7.90% and RMSE = 1.81 g/g), while the highest error values were produced by the Boosted Trees method (MAE=14.31 g/g; MAPE = 39.43% and RMSE = 27.76 g/g)

Assessment of the possibility of using data mining methods to predict sorption isotherms of selected organic compounds on activated carbon

The paper analyses the use of four data mining methods (Support Vector Machines. Cascade Neural Networks. Random Forests and Boosted Trees) to predict sorption on activated carbons. The input data for statistical models included the activated carbon parameters, organic substances and equilibrium concentrations in the solution. The assessment of the predictive abilities of the developed models was made with the use of mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE). The computations proved that methods of data mining considered in the study can be applied to predict sorption of selected organic compounds 011 activated carbon. The lowest values of sorption prediction errors were obtained with the Cascade Neural Networks method (MAE = 1.23 g/g; MAPE = 7.90% and RMSE = 1.81 g/g), while the highest error values were produced by the Boosted Trees method (MAE=14.31 g/g; MAPE = 39.43% and RMSE = 27.76 g/g)

Modeling and Optimization of Pollutants Removal during Simultaneous Adsorption onto Activated Carbon with Advanced Oxidation in Aqueous Environment

The paper presents the results of studies on the modeling and optimization of organic pollutant removal from an aqueous solution in the course of simultaneous adsorption onto activated carbons with varied physical characteristics and oxidation using H2O2. The methodology for determining the models used for predicting the sorption and catalytic parameters in the process was presented. The analysis of the influence of the sorption and catalytic parameters of activated carbons as well as the oxidizer dose on the removal dynamics of organic dyes-phenol red and crystal violet-was carried out based on the designated empirical models. The obtained results confirm the influence of specific surface area (S) of the activated carbon and oxidizer dose on the values of the reaction rate constants related to the removal of pollutants from the solution in a simultaneous process. It was observed that the lower the specific surface area of carbon (S), the greater the influence of the oxidizer on the removal of pollutants from the solution. The proposed model, used for optimization of parameters in a simultaneous process, enables to analyze the effect of selected sorbents as well as the type and dose of the applied oxidizer on the pollutant removal efficiency. The practical application of models will enable to optimize the selection of a sorbent and oxidizer used simultaneously for a given group of pollutants and thus reduce the process costs