Quality of life in long-term survivors of early stage endometrial cancer

Introduction. Endometrial cancer (EC) is the most common gynaecological malignancy in developed countries. Effective treatment of the early stage of the disease is achieved by surgery alone. An increasing number of patients with EC become long-term survivors; therefore, the purpose of this study was to investigate the quality-of-life (QOL) of EC survivors. Materials and Method. A total of 328 survivors who had completed cancer treatment more than 3 years ago, and had previously completed questionnaires concerning QOL – European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and depression – Beck Depression Inventory-II (BDI-II). Patients were grouped into those with surgery alone or surgery with adjuvant radiotherapy. Responses were compared with 284 healthy women who were seen for standard gynaecologic screening examinations. Results. According to the presented results, the QOL of women with EC after surgical treatment was equal to that of healthy women in the control group. Treatment with adjuvant radiotherapy influenced the QOL, with the exception of emotional functioning (p=0.028). No statistically significant differences were found in scores on the BDI-II between groups for the cognitive-affective factor, the somatic factor, or the total sum score. Conclusions. The quality of life in EC survivors approximates that of healthy controls after 3 years post-surgical treatment. Patients treated for early stage EC should be informed about the anticipated good prognosis and the low risk of psychosocial and physical long-term effects. Cancer survivors who are treated by surgery and adjuvant radiotherapy may be especially at risk for emotional functioning problems

Trajectory optimization using learning from demonstration with meta-heuristic grey wolf algorithm

Nowadays, most robotic systems perform their tasks in an environment that is generally known. Thus, robot’s trajectory can be planned in advance depending on a given task. However, as a part of modern manufacturing systems which are faced with the requirements to produce high product variety, mobile robots should be flexible to adapt to changing and diverse environments and needs. In such scenarios, a modification of the task or a change in the environment, forces the operator to modify robot’s trajectory. Such modification is usually expensive and time-consuming, as experienced engineers must be involved to program robot’s movements. The current paper presents a solution to this problem by simplifying the process of teaching the robot a new trajectory. The proposed method generates a trajectory based on an initial raw demonstration of its shape. The new trajectory is generated in such a way that the errors between the actual and target end positions and orientations of the robot are minimized. To minimize those errors, the grey wolf optimization (GWO) algorithm is applied. The proposed approach is demonstrated for a two-wheeled mobile robot. Simulation and experimental results confirm high accuracy of generated trajectories

Trajectory optimization using learning from demonstration with meta-heuristic grey wolf algorithm

Nowadays, most robotic systems perform their tasks in an environment that is generally known. Thus, robot’s trajectory can be planned in advance depending on a given task. However, as a part of modern manufacturing systems which are faced with the requirements to produce high product variety, mobile robots should be flexible to adapt to changing and diverse environments and needs. In such scenarios, a modification of the task or a change in the environment, forces the operator to modify robot’s trajectory. Such modification is usually expensive and time-consuming, as experienced engineers must be involved to program robot’s movements. The current paper presents a solution to this problem by simplifying the process of teaching the robot a new trajectory. The proposed method generates a trajectory based on an initial raw demonstration of its shape. The new trajectory is generated in such a way that the errors between the actual and target end positions and orientations of the robot are minimized. To minimize those errors, the grey wolf optimization (GWO) algorithm is applied. The proposed approach is demonstrated for a two-wheeled mobile robot. Simulation and experimental results confirm high accuracy of generated trajectories

The Dynamics Of Time Series Of Real Estate Prices

The presented research aims to contribute to the concerns regarding the evolutionary dynamics of the real estate market, seen as an open system flowing from one equilibrium state into another. In such quasi-stable states, real estate markets are thought to change only slightly with elapsed time, but occasionally, a sudden jump, during which the markets undergo changes of structural origin, might occur as well. Hence, the paper contains an analysis of the dynamics of time series of housing prices in order to distinguish between processes of different time scales. Research was performed assuming a priori distributions of the variables, and using the autocorrelation function together with the partial autocorrelation function for detailed data analysis

Multiscale surface texture and fractal analysis of straight bevel gears finished by PECH and PECF process

The present work was conducted to provide insights for an in-depth understanding of the straight bevel gears finished by pulsed-electrochemical-honing (PECH) and pulsed-electrochemical-finishing (PECF), using multi-scale surface texture and fractal analysis in order to give manufacturers a competitive edge when improving their tools. Unfinished bevel gears and bevel gears finished by PECF and PECH were analyzed on their surface texture characteristics and material properties. Surface characteristics of 20MnCr5 alloy steel gears were evaluated by computing four locations on regions of each sample. Field emission scanning electron microscopy (FESEM) was applied for surface material characterization. It was found that it can be discriminated between the PECF and PECH-finished bevel gears surface regions of samples and unfinished samples, using area-scale analysis and surface texture characteristics. The surface micro-morphology results can be applied in studies about improving the lifetime of tools and for mathematical modeling of lubrication processes between tool and workpiece

Quality of life in long-term survivors of early stage endometrial cancer

Introduction. Endometrial cancer (EC) is the most common gynaecological malignancy in developed countries. Effective treatment of the early stage of the disease is achieved by surgery alone. An increasing number of patients with EC become long-term survivors; therefore, the purpose of this study was to investigate the quality-of-life (QOL) of EC survivors. Materials and Method. A total of 328 survivors who had completed cancer treatment more than 3 years ago, and had previously completed questionnaires concerning QOL – European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and depression – Beck Depression Inventory-II (BDI-II). Patients were grouped into those with surgery alone or surgery with adjuvant radiotherapy. Responses were compared with 284 healthy women who were seen for standard gynaecologic screening examinations. Results. According to the presented results, the QOL of women with EC after surgical treatment was equal to that of healthy women in the control group. Treatment with adjuvant radiotherapy influenced the QOL, with the exception of emotional functioning (p=0.028). No statistically significant differences were found in scores on the BDI-II between groups for the cognitive-affective factor, the somatic factor, or the total sum score. Conclusions. The quality of life in EC survivors approximates that of healthy controls after 3 years post-surgical treatment. Patients treated for early stage EC should be informed about the anticipated good prognosis and the low risk of psychosocial and physical long-term effects. Cancer survivors who are treated by surgery and adjuvant radiotherapy may be especially at risk for emotional functioning problems

Mechanical properties and fractal analysis of the surface texture of sputtered hydroxyapatite coatings

This aim of this work is to establish a relationship between the surface morphology and mechanical properties of hydroxyapatite coatings prepared using RF magnetron sputtering at temperatures in the range from 400 to 800 degrees C. The topography of the samples was scanned using atomic force microscopy, and the obtained 3D maps were analyzed using fractal methods to derive the spatial characteristics of the surfaces. X-ray photoelectron spectroscopy revealed the strong influence of the deposition temperature on the Ca/P ratio in the growing films. The coatings deposited at 600-800 degrees C exhibited a Ca/P ratio between 1.63 and 1.69, close to the stoichiometric hydroxyapatite (Ca/P = 1.67), which is crucial for proper osseointegration. Fourier-transform infrared spectroscopy showed that the intensity of phosphate absorption bands increased with increasing substrate temperature. Each sample exhibited well defined and sharp hydroxyapatite band at 566 cm(-1), although more pronounced for the coatings deposited above 500 degrees C. Both the hardness and elastic modulus of the coated samples decrease with increasing deposition temperature. The surface morphology strongly depends on the deposition temperature. The sample deposited at 400 degrees C exhibits circular cavities dug in an otherwise flat surface. At higher deposition temperatures, these cavities increase in size and start to overlap each other so that at 500 degrees C the surface is composed of closely packed peaks and ridges. At that point, the characteristics of the surface turns from the dominance of cavities to grains of similar size, and develops in a similar manner at higher temperatures. (C) 2016 Elsevier B.V. All rights reserved

Surface micromorphology characterization of PDI8-CN2 thin films on H-Si by AFM analysis

A nanoscale investigation of three-dimensional (3-D) surface micromorphology of archetypical N, N0- bis (n-etyl) x:y, dicyanoperylene- 3, 4:9, 10 bis (dicarboximide) (PDI8-CN2) thin films on H-Si substrates, which are applicable in n-type semiconducting compounds, has been performed by using fractal analysis. In addition, surface texture characteristics of the PDI8-CN2 thin films have been characterized by using atomic force microscopy (AFM) operated in tapping-mode in the air. These analyses revealed that all samples can be described well as fractal structures at nanometer scale and their three dimensional surface texture could be implemented in both graphical models and computer simulations