MODELING OF FLOW AND TEMPERATURE FIELD IN AN ECONOMIZER

This article deals with the economizer as one of the main parts of a boiler. Economizers and air heaters perform a key function in providing high overall boiler thermal efficiency by recovering the low level energy from the flue gas before it is exhausted to the atmosphere. The most common and reliable economizer design is the bare-tube, in-line, cross-flow type. To reduce capital costs, most boiler manufacturers build economizers with a variety of designs to enhance the controlling gas-side heat transfer rate. From this point of view it creates a lack for an investigation and modeling of these parts

Immunohistochemical visualization of pro-inflammatory cytokines and enzymes in ovarian tumors

Epithelial ovarian cancer represents one of the most deadly gynaecological neoplasms in developed countries and is a highly heterogeneous disease. Epidemiological studies show that anti-inflammatory drugs reduce the incidence and mortality of several types of cancer, indicating the potential role of pro-inflammatory factors in carcinogenesis. The expression of pro-inflammatory factors in various cancer types, including ovarian cancer, was assessed in many studies, yielding in consistent results, often due to the histological heterogeneity of various cancers. The aim of the study was to investigate the expression of IL-1, IL-6, TGF-β, TNF-α, COX-2,iNOS, and NF-kB in serous and mucinous ovarian cancers. Ninety cases of ovarian tumors classified into mucous and serous type (45 patients in each group) were selected. Each group was classified into subgroups according to the three stages of tumor differentiation, i.e. into (i) benign, (ii) borderline and (iii) malignant tumors. The presence of proteins of interest in paraffin sections was analysed by immunohistochemistry. The expression of most of the studied factors depended on the histological tumor subtype and the degree of malignancy. Expression of NF-κB appears to be related to the level of the neoplastic differentiation only in the group of serous tumors, while the presence of IL-6 in the mucinous tumor subtype was observed only in the case of benign lesions. Expression of IL-1, TNF-α and COX-2 increased with the stage of the disease in both serous and mucinous tumors. The highest level of TGF-β expression was observed in serous borderline tumors. The different levels of iNOS immunoreactivity between the groups of serous and mucinous tumors were observed only in borderline tumors. The results of our study may be helpful in designing therapeutic strategies depending on the type of ovarian cancer

Unsupervised Analysis of Classical Biomedical Markers: Robustness and Medical Relevance of Patient Clustering Using Bioinformatics Tools

Motivation: It has been proposed that clustering clinical markers, such as blood test results, can be used to stratify patients. However, the robustness of clusters formed with this approach to data pre-processing and clustering algorithm choices has not been evaluated, nor has clustering reproducibility. Here, we made use of the NHANES survey to compare clusters generated with various combinations of pre-processing and clustering algorithms, and tested their reproducibility in two separate samples. Method: Values of 44 biomarkers and 19 health/life style traits were extracted from the National Health and Nutrition Examination Survey (NHANES). The 1999–2002 survey was used for training, while data from the 2003–2006 survey was tested as a validation set. Twelve combinations of pre-processing and clustering algorithms were applied to the training set. The quality of the resulting clusters was evaluated both by considering their properties and by comparative enrichment analysis. Cluster assignments were projected to the validation set (using an artificial neural network) and enrichment in health/life style traits in the resulting clusters was compared to the clusters generated from the original training set. Results: The clusters obtained with different pre-processing and clustering combinations differed both in terms of cluster quality measures and in terms of reproducibility of enrichment with health/life style properties. Z-score normalization, for example, dramatically improved cluster quality and enrichments, as compared to unprocessed data, regardless of the clustering algorithm used. Clustering diabetes patients revealed a group of patients enriched with retinopathies. This coul

Analysis of a Micro-CHP Unit with in-series SOFC Stacks Fed by Biogas

AbstractThis paper presents results of a recent evaluation of a conceptual micro-CHP units in two alternative configurations. Parallel and in-series connections of two identical commercial electrolyte-supported SOFC stacks were under evaluation. In order to achieve high overall fuel utilization in the system enabling high electrical efficiency, both concepts were analyzed with respect to operational regimes typical for SOFC stacks. Numerical analysis included several possible configurations of complete a system with fuel processor, SOFC stacks and BoP components. Evaluation of the in-series connection was performed using experimental setup with a commercial SOFC stack to reproduce operating conditions obtained from the model. Validation of the concept was necessary to qualitatively and quantitatively determine possibility of operating second stack on lean fuel originating from the anodic compartments of the first stack. Results of the comparative analysis presented in this paper were used to aid in defining optimal outline of a micro-CHP power system. Predictions of the models were in agreement with preliminary experiments, proving the concept of in-series stacks configuration viable. Electrical efficiency increases for the system with two in-series stacks, and value of 46%LHV can be achieved in the micro-CHP system with SOFC

Radiometric Correction with Topography Influence of Multispectral Imagery Obtained from Unmanned Aerial Vehicles

This article aims to present the methods of the radiometric correction of multispectral images—a short review of the existing techniques. The role of radiometric correction is essential to many applications, especially in precision farming, forestry, and climate analysis. Moreover, this paper presents a new relative approach, which considers the angle of inclination of the terrain and the angle of incidence of electromagnetic radiation on the imaged objects when obtaining the baseline data. This method was developed for data obtained from low altitudes—for imagery data acquired by sensors mounted on UAV platforms. The paper analyses the effect of the correction on the spectral information, i.e., the compatibility of the spectral reflection characteristics obtained from the image with the spectral reflection characteristics obtained in the field. The developed method of correction for multispectral data obtained from low altitudes allows for the mapping of spectral reflection characteristics to an extent that allows for the classification of terrestrial coverage with an accuracy of over 95%. In addition, it is possible to distinguish objects that are very similar in terms of spectral reflection characteristics. This research presents a new method of correction of each spectral channel obtained by the multispectral camera, increasing the accuracy of the results obtained, e.g., based on SAM coefficients or correlations, but also when distinguishing land cover types during classification. The results are characterized by high accuracy (over 94% in classification)

Pre-Processing of Panchromatic Images to Improve Object Detection in Pansharpened Images

In recent years, many techniques of fusion of multi-sensors satellite images have been developed. This article focuses on examining and improvement the usability of pansharpened images for object detection, especially when fusing data with a high GSD ratio. A methodology to improve an interpretative ability of pansharpening results is based on pre-processing of the panchromatic image using Logarithmic-Laplace filtration. The proposed approach was used to examine several different pansharpening methods and data sets with different spatial resolution ratios, i.e., from 1:4 to 1:60. The obtained results showed that the proposed approach significantly improves an object detection of fused images, especially for imagery data with a high-resolution ratio. The interpretative ability was assessed using qualitative method (based on image segmentation) and quantitative method (using an indicator based on the Speeded Up Robust Features (SURF) detector). In the case of combining data acquired with the same sensor the interpretative potential had improved by a dozen or so per cent. However, for data with a high resolution ratio, the improvement was several dozen, or even several hundred per cents, in the case of images blurred after pansharpening by the classic method (with original panchromatic image). Image segmentation showed that it is possible to recognize narrow objects that were originally blurred and difficult to identify. In addition, for panchromatic images acquired by WorldView-2, the proposed approach improved not only object detection but also the spectral quality of the fused image

Quality Assessment of the Bidirectional Reflectance Distribution Function for NIR Imagery Sequences from UAV

Imaging from low altitudes is nowadays commonly used in remote sensing and photogrammetry. More and more often, in addition to acquiring images in the visible range, images in other spectral ranges, e.g., near infrared (NIR), are also recorded. During low-altitude photogrammetric studies, small-format images of large coverage along and across the flight route are acquired that provide information about the imaged objects. The novelty presented in this research is the use of the modified method of the dark-object subtraction technique correction with a modified Walthall’s model for correction of images obtained from a low altitude. The basic versions of these models have often been used to radiometric correction of satellite imagery and classic aerial images. However, with the increasing popularity of imaging from low altitude (in particular in the NIR range), it has also become necessary to perform radiometric correction for this type of images. The radiometric correction of images acquired from low altitudes is important from the point of view of eliminating disturbances which might reduce the capabilities of image interpretation. The radiometric correction of images acquired from low altitudes should take into account the influence of the atmosphere but also the geometry of illumination, which is described by the bidirectional reflectance distribution function (BRDF). This paper presents a method of radiometric correction for unmanned aerial vehicle (UAV) NIR images. The study presents a method of low-altitude image acquisition and a fusion of the method of the dark-object subtraction technique correction with a modified Walthall’s model. The proposed solution performs the radiometric correction of images acquired in the NIR range with the root mean square error (RMSE) value not exceeding 10% with respect to the original images. The obtained results confirm that the proposed method will provide effective compensation of radiometric disturbances in UAV images