Possible Utilization of Distillery Waste in the Carbonization Process.

This paper characterizes the carbonization process in terms of the utilization of distillery waste in a laboratory-scale reactor. Due to the increase in market prices of wood and environmental protection laws, biomass waste, including distillery waste, is a potential source for biochar production. An experimental investigation of the carbonization process was carried out for different mixtures of distillery waste and oak sawdust. The obtained results showed that due to the European Standard, biochar from distillery waste could be used for the production of charcoal briquettes for barbecue applications. In addition, biochar from carbonization samples with 66, 50, and 33% distillery waste meet the standards defined by the International Biochar Initiative for HMs content. The analysis of the dynamics of the heating rate showed that adding wood to distillery waste significantly shortens the carbonization process, but this reduces the number of bio-oils produced and its calorific value.

Comparative Analysis of Pelletized and Unpelletized Sunflower Husks Combustion Process in a Batch-Type Reactor.

This paper describes characteristics of the combustion of sunflower husk (SH), sunflower husk pellets (SHP), and, for comparison, hardwood pellets (HP). The experiments were carried out using a laboratory-scale combustion reactor. A proximate analysis showed that the material may constitute an alternative fuel, with a relatively high heating value (HHV) of 18 MJ/kg. For SHP, both the maximum combustion temperatures (TMAX = 1110 °C) and the kinetic parameters (temperature front velocity vt = 7.9 mm/min, combustion front velocity vc = 8 mm/min, mass loss rate vm = 14.7 g/min) of the process were very similar to those obtained for good-quality hardwood pellets (TMAX = 1090 °C, vt = 5.4 mm/min, vc = 5.2 mm/min, vm = 13.2 g/min) and generally very different form SH (TMAX = 840 °C, vt = 20.7 mm/min, vc = 19 mm/min, vm = 13.1 g/min). The analysis of ash from SH and SHP combustion showed that it has good physicochemical properties (ash melting point temperatures >1500 °C) and is safe for the environment. Furthermore, the research showed that the pelletization of SH transformed a difficult fuel into a high-quality substitute for hardwood pellets, giving a similar fuel consumption density (Fout = 0.083 kg/s·m2 for SHP and 0.077 kg/s·m2 for HP) and power output density (Pρ = MW/m2 for SHP and 1.5 MW/m2 for HP).

Carbonization of corncobs for the preparation of barbecue charcoal and combustion characteristics of corncob char.

The paper examines the process of carbonization of waste from corncobs at carbonization temperatures within a range of 300-700 °C in a laboratory-scale reactor. These studies are important because of reductions in wood resources for the preparation of barbecue charcoal due to environmental protection laws and legislative processes in many countries aimed at the protection of forest resources. The results presented here include the physical and chemical properties of char as a function of carbonization temperatures as well as the characteristics of the heating rate of a fixed bed of corncobs and within a single corncob particle. The combustion characteristics of the char were determined using thermogravimetric analysis. The results show that the volatile matter yield of the char decreased, whereas the fixed carbon yield and higher heating value (HHV) increased, along with higher carbonization temperatures. TGA analysis shows that the ignition and burnout temperature of the char increased, with a simultaneous decrease in the value of the S index, along with increased carbonization temperatures. The results show that carbonization temperatures of 500 °C and above meet the standards for the production of barbecue charcoal.

Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network.

Background: Toward the goal of predicting individual long-term cancer survival to guide treatment decisions, this study evaluated the ability of a probabilistic neural network (PNN), an established model used for decision-making in research and clinical settings, to predict the 10-year overall survival in patients with cervical cancer who underwent primary surgical treatment. Patients and Method: The input dataset was derived from 102 patients with cervical cancer FIGO stage IA2-IIB treated by radical hysterectomy. We identified 4 demographic parameters, 13 tumor-related parameters, and 6 selected perioperative variables for each patient and performed computer simulations with DTREG software. The predictive ability of the model was determined on the basis of its error, sensitivity, and specificity, as well as area under the receiver operating characteristic curve. The results of the PNN predictive model were compared with those of logistic regression analysis and a single decision tree as reference models. Results: The PNN model had very high predictive ability, with a sensitivity of 0.949, a specificity of 0.679, and an error rate of 12.5%. The PNN's area under the receiver operating characteristic curve was high, 0.809, a value greater than those for both logistic regression analysis and the single decision tree. Conclusion: The PNN model effectively and reliably predicted 10-year overall survival in women with operable cervical cancer, and may therefore serve as a tool for decision-making process in cancer treatment.

The influence of temperature on the physicochemical properties of products of pyrolysis of leather-tannery waste.

The present paper examines the pyrolysis of waste from leather tanneries at 300-500 °C. These studies are important because of difficulties in the utilisation of this type of waste as well as its energy potential as fuel. The pyrolysis of tannery waste and data from the relevant literature showed that thermal degradation can be explained using tanned collagen as a reference. Moreover, the experimental results indicated that this process is highly non-linear, due to various mechanisms of heat transport which cause temperature differences in a laboratory pyrolysis reactor. Thermogravimetric analysis has shown that the greater part of mass loss is observed between 80 and 500 °C and that the most significant mass release occurs at 325 °C. Moreover, the proportions of CO2 and CO decrease along with increasing temperatures. The paper presents characteristics of the composition of solid, liquid, and gaseous products of leather-waste pyrolysis at various temperatures. The maximum heating value of gaseous products at 500 °C was 9.54 MJ/Nm3. An increase from 300 to 500 °C results in the dominant position of condensation polymerisation; the maximum value of the liquid phase yield is reached at 400 °C (42%). HHV analysis of the resulting char showed a maximum value of 21.18 MJ/kg at 450 °C. The results of oxidised component analysis showed that the major oxidised component of char was chromium oxide (Cr2O3), with a content of approximately 8.5% at all pyrolysis temperatures.

Experimental tests of co-combustion of pelletized leather tannery wastes and hardwood pellets.

This study examines the possibility of using pelletized leather tannery wastes (LTW) in the co-combustion process with hardwood pellets (HP). The experiments were carried out in a small-scale combustion reactor and were followed by thermogravimetric analysis (TGA) of fuels in the nitrogen and air atmosphere. The experimental investigation has indicated that the leather tannery wastes can be an interesting fuel with a relatively high heating value (HHV), at the level of 16 MJ/kg, and the volatile content of about 68%. Thermal decomposition of the leather tannery sample occurs at temperatures ranging between 220 and 420 °C, with the maximum of intensity at 320 °C. The experimental results indicated that the averaged maximum temperatures obtained during the combustion reached similar values for all samples, which indicates that doping wood pellets with leather waste pellets does not have a significant impact on the temperature characteristics of the combustion process. However, decreasing the amount of hardwood pellets in the mixture reduces the bulk density of the fuel bed and the combustion front velocity. The emission of nitrogen oxides for combusting blends is twice as high as for combustion of pure HP, which is related to higher nitrogen content in leather waste as well as higher ash content.

Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

BACKGROUND: Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. METHODS: The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. RESULTS: The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. CONCLUSIONS: The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

Thermal and chemical effects of turkey feathers pyrolysis.

This study examines the thermal and chemical effects of the pyrolysis of turkey feathers. Research of feathers pyrolysis is important because of their increasing production and difficulties of their utilization. The experiments were carried out by means of thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and two pyrolytic reactors. The experimental investigation indicated that the feather material liquefies at temperatures between 210 and 240°C. This liquefaction together with the agglomeration of various dispersed and porous elements of the feathers into larger droplets leads to the volume reduction. Moreover, this work presents characteristics of the composition of the solid, liquid and gaseous products of turkey feathers pyrolysis at different temperatures. The higher heating value (HHV) of gaseous products in temperature 900°C equals 19.28 MJ/Nm(3) making the gases suitable for use as a fuel. The thermochemical conversion of turkey feathers leads to the formation of poisonous compounds such as hydrogen cyanide (HCN) in the liquid (0.13%) and gaseous (88 mg/Nm(3)) products. The phenomenon of liquefaction of feathers is important because it can lead to rapid degradation of the walls of reactors, and the formation of deposits.

Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients.

The aim of this article was to compare gene expression programming (GEP) method with three types of neural networks in the prediction of adverse events of radical hysterectomy in cervical cancer patients. One-hundred and seven patients treated by radical hysterectomy were analyzed. Each record representing a single patient consisted of 10 parameters. The occurrence and lack of perioperative complications imposed a two-class classification problem. In the simulations, GEP algorithm was compared to a multilayer perceptron (MLP), a radial basis function network neural, and a probabilistic neural network. The generalization ability of the models was assessed on the basis of their accuracy, the sensitivity, the specificity, and the area under the receiver operating characteristic curve (AUROC). The GEP classifier provided best results in the prediction of the adverse events with the accuracy of 71.96 %. Comparable but slightly worse outcomes were obtained using MLP, i.e., 71.87 %. For each of measured indices: accuracy, sensitivity, specificity, and the AUROC, the standard deviation was the smallest for the models generated by GEP classifier.

Hardware implementation of fuzzy Petri net as a controller.

The paper presents a new approach to fuzzy Petri net (FPN) and its hardware implementation. The authors' motivation is as follows. Complex industrial processes can be often decomposed into many parallelly working subprocesses, which can, in turn, be modeled using Petri nets. If all the process variables (or events) are assumed to be two-valued signals, then it is possible to obtain a hardware or software control device, which works according to the algorithm described by conventional Petri net. However, the values of real signals are contained in some bounded interval and can be interpreted as events which are not only true or false, but rather true in some degree from the interval [0, 1]. Such a natural interpretation from multivalued logic (fuzzy logic) point of view, concerns sensor outputs, control signals, time expiration, etc. It leads to the idea of FPN as a controller, which one can rather simply obtain, and which would be able to process both analog, and binary signals. In the paper both graphical, and algebraic representations of the proposed FPN are given. The conditions under which transitions can be fired are described. The algebraic description of the net and a theorem which enables computation of new marking in the net, based on current marking, are formulated. Hardware implementation of the FPN, which uses fuzzy JK flip-flops and fuzzy gates, are proposed. An example illustrating usefulness of the proposed FPN for control algorithm description and its synthesis as a controller device for the concrete production process are presented.