Response assessment in the treatment of glioblastoma (GB) based on MR-imaging is still challenging, in particular for immunotherapeutic strategies. Several assessment tools have been proposed. In this post-hoc analysis we compared response assessment criteria (MacDonald, RANO, mRANO, Vol.-mRANO, iRANO) in newly diagnosed GB patients treated with tumor lysate-charged autologous dendritic cells (Audencel) and determined the differences in prediction of progression free survival (PFS) and overall survival (OS). 76 patients with newly diagnosed GB enrolled in a multicenter randomized phase II trial receiving standard of care (SOC, n= 40) or SOC + Audencel vaccine (n= 36) were included. Tumor volumes were calculated by semiautomatic segmentation. To detect differences in PFS among the assessment criteria Kruskal-Wallis-test, for correlation analysis Spearman test was used. There was a significant difference in median PFS based on the different assessments (mRANO 8.55 months [9.10-14.03], Vol.-mRANO 8.61 months [9.72-14.92] compared to MacDonald 4.04 months [5.21-8.75] and RANO 4.16 months [5.28-8.61]. For the vaccination arm only, median PFS by iRANO was 5.95 months [5.70-11.54]). There was no difference in PFS between SOC and SOC + Audencel using the different response criteria. The best correlation between PFS and OS was detected for mRANO (r= 0.65, p< 0.001) and Vol.-mRANO (r= 0.69, p< 0.001). At an 8-month landmark, the impact of progressive disease on median OS was best shown for mRANO (13.70 months [13.13-18.98], and Vol.-mRANO 12.03 months [12.51-17.94]) compared to MacDonald 17.97 months [15.45-20.92], RANO 17.97 months [15.92-20.95] and iRANO 17.34 months [14.99-22.73]. When comparing different response assessments in GB patients treated with dendritic cell-based immunotherapy the best correlation between PFS and OS was observed for mRANO and Vol.-mRANO. Overall, no difference in PFS and OS was seen between the two treatment arms. iRANO was not superior for predicting OS in patients treated with Audencel.

Introduction Although extracorporeal shock wave lithotripsy (ESWL) is minimally invasive and highly efficient for the management of kidney stones, adverse effects have been described. Available indicators of renal function exhibit insufficient sensitivity in acute renal injury (AKI). We aimed to evaluate the severity of the kidney tissue response to ESWL injury by measuring the urinary neutrophil gelatinase-associated lipocalin (uNGAL), which can indicate AKI in its early phase. Material and methods The prospective, controlled study included 62 patients with nephrolithiasis undergoing single ESWL treatment. uNGAL level was measured before the procedure, and 6 h and 12 h after. Results The median uNGAL level increased by 126.0%, 6 h after ESWL (p <0.001). The growth rate continued and 12 h after was higher by 583.7%, compared to the pre-treatment level (p <0.001). The median value of estimated glomerular filtration rate (eGFR) dropped by 15.3% 12 h after the treatment (p <0.001). It increased by 5.0% in the period 7 days to 3 months after (p <0.001) and after 3 months it was lower by 10.1% compared to pre-ESWL values (p <0.001). uNGAL level after 12 h was significantly negatively associated with eGFR, 12 h, 7 days and 3 months after the ESWL. The sensitivity of uNGAL 12 h after ESWL was 60.6%; its specificity was 75.0%, with a positive predictive value of 74.0% and negative predictive value of 61.7%. Conclusions uNGAL appears to be a useful biomarker for the assessment and prediction of AKI. It was noticed that uNGAL had the highest predictive value 12 h after the ESWL treatment.

An adaptive control is a control, which by pre-setting the parameters of the controller, enables the control of processes whose parameters are time-varying or are initially uncertain. The possibilities and benefits of adaptive control are versatile and can be best demonstrated by applying the system while driving a car, or maintaining the optimal speed and distance between cars, which is shown in this paper. As the car’s weight decreases while driving due to fuel consumption, the control algorithm has to be adapted to the changed driving conditions. Accordingly, an adaptive control system using the Matlab software package, and an adaptive cruise control system (ACC) was created in this paper, which is based on a predictive model. After evaluating the developed model of adaptive car motion control, the output parameters such as speed, acceleration, and distance between the two vehicles were analyzed. In this paper a PID controller is used to reduce oscillations in the system. First, the P controller was used to reduce the rise time of the significant values, then the PI controller improved the rise time, and finally the PID controller achieved overshoot reduction performance without affecting the dynamic response system. The obtained results confirm the justified expectations for the possibility of adaptive car control utilization as one of the possible solutions to the increasing traffic incidents, as well as a measure to improve the reduction of these incidents.

Wood is one of the most important construction materials in Europe and its use in building applications has increased in the recent decades. To enable even more extensive and reliable use of wood, this article aimed to determine the effect of thermal modification on mechanical properties of fir wood (lat. Abies sp.), linden wood (lat. Tilia sp.), and beech wood (lat. Fagus sp.). The thermal modification was conducted in a laboratory oven at five different temperatures of 170, 180, 195, 210, 220 °C and processed with a different maximum duration of the process of 78, 120, 180, 240, 276 minutes. Mechanical properties of treated wood have shown statistically insignificant fluctuations at lower temperatures compared to control samples. On the other hand, raising the temperature to 210 °C significantly affected the strength of all the species. The results revealed that thermal modification at high temperatures and longer exposure causes a decrease in the maximum force of the three wood species.

In the production of expanded polystyrene, the standards are very high in terms of thermal, fire, dimensional, and mechanical characteristics, because each of the characteristics is a condition for achieving quality that allows competitiveness in the market. To ensure high-quality products, it is necessary to achieve optimal performance and product quality through carefully adjusted input parameters of production. Since the production of expanded polystyrene is specific in several ways, an experimental study was conducted in which the basic parameters affecting product quality were detected and through which a series of experiments were performed to prove product quality. Experimental research for this work was conducted on three types of expanded polystyrene samples whose purpose is to insulate floors exposed to pressure. The samples were made of the same material of different densities and aging times for which the pressure stress at a deformation of 10% was tested. After the experimental phase, the modeling of the output parameters was performed. Modeling involved the development of a model that describes a given problem and the obtained modeled values were analyzed and compared with the experimental one. The modeling method used genetic programming using the GPdotNET software package. The goal of modeling with the GpdotNET tool is to obtain a realistic model that would give the value of the compression stress at a deformation of 10% as an output variable in materials made of expanded polystyrene.

Optical time-domain reflectometer (OTDR) enables simple identification and localization of a plethora of refractive and reflective events on a fiber link, including splices, connectors and breaks, and measuring insertion/return loss. Specifically, large enough OTDR dynamic range (DR) and thus high signal-to-noise-ratio (SNR) enable clear far-end visibility of longer fibers. We point out here that, under such conditions, the optical bit-error-rate (BER) floor is dominantly determined by reflective events that introduce significant return loss. This complements the OTDR legacy tests by appropriate optical BER floor estimation in the field. As high SNR implies inter-symbol interference as dominating error generating mechanism, we could apply the classical time-dispersion channel model for the optical BER floor determined by the root-mean-square (rms) delay spread of the actual fiber channel power-delay profile. However, as the high-SNR condition is not always fulfilled mostly due to insufficient DR, we propose here inserting a low-noise optical preamplifier as the OTDR front-end to reduce noise floor and amplify the backscattered signal. In order to verify the model for the exemplar test situation, we measured BER on the same fiber link to find very good matching between the measured BER floor values and the ones predicted from the OTDR trace.

The paper presents a diagnosis of the condition of the stadium FK Velež “Rođeni” in Mostar, which was built in period 2006-2008 and represents an important facility for the citizens of Mostar. The steps in diagnosing the condition of an existing structure are explained, including a collection of existing documentation, an inspection of the structure, test and calculations, and assessment and decision on further action. Drawings of the stadium were given, visual inspection of the stadium was performed and calculations of the current and future layout of the structure. The calculations were performed in software Tower 8 and with respect to European norms EN0, EN1, EN2, EN3 and EN8. A visual inspection revealed a large number of damages to the stadium, which were classified into specific groups. The mechanisms of destruction and classification were performed using EN 1504.

Goal of this research was to develop and manufacture planetary gearbox prototype using rapid prototyping technology (additive manufacturing). Developed prototype was used to visually analyse the design of the planetary gearbox. Also, it was used to improve and innovate education of students on several courses at Mechanical Design study program at Faculty of Mechanical Engineering. It is shown that low cost rapid prototyping technology can be used to manufacture prototypes of complex machines and machine elements. Prototypes manufactured using this technology have same functionality like the real one. Main limitation is the fact that they cannot sustain real world loads and stresses. This paper shows opportunities which low cost rapid prototyping technology is offering in improvement and innovation of education process at engineering schools and faculties. All complex and heavy machines can be manufactured using this type of technology and on that way more precisely presented to the students.

The development of teleoperation systems, robots, or any physical part of the system can be costly and if something goes wrong it can lead to development overdue. Precisely for these reasons, engineers and scientists today resort to the development of simulated systems before the construction of a real system. Robot Operating System (ROS) is one of the most popular solutions for robot development, manipulation, and simulation. In this paper, we present a web application for remote control of a ROS robot. The robot is controlled via a web application that is used as a virtual Joystick. Also, in this paper, an experimental work analysis of the projected system is performed. Further research possibilities include upgrading the presented web interface, adding certain motion autonomy sensors, or integrating some path planning algorithms.

Nowadays, automatic systems are using in more spheres of industry, and in this way, human intervention is avoided and used as minimally as possible. In the chicken poultry industry, the use of mother hens is transferring to automatic egg incubating systems. Such systems are helpful for the farmers to incubate the eggs automatically without the need for human intervention. These systems work by keeping the physical quantities, temperature and humidity, at the optimal level. In that way, the fetuses inside eggs are growing without the presence of the mother hen. The egg incubating systems not only improve poultry production considerably but also help in the regularity of income making, enabling the farmers to be able to get transition into possible rural entrepreneurship. This paper describes the design and implementation of a fuzzy control system for egg incubating based on IoT technology. The microcontroller is programmed to work as a fuzzy logic control system for controlling microclimate conditions in the egg incubator to keep the conditions for different eggs type optimal. Informations from the temperature and humidity sensors are sent wirelessly to the cloud. Also, the implemented egg incubating system enables automatic tracking of the remaining days until hatching chickens. In this way, remote monitoring, from any location, of microclimatic conditions inside the egg incubator is enabled. For the experimental work analysis of the implemented egg incubating system, the egg incubator is made. Based on the results of the experimental work analysis can be seen that the egg incubating system works well and that it helps with improving poultry production.

With the development of modern technology, smartphones have become a necessity for most people. Among other uses, mobile phones are increasingly being used in smart home systems. In smart homes, mobile phones are used to remotely control and monitor various systems such as simply turning on/off lights and household appliances, various monitoring systems, etc. Nowadays, sending coded messages or pressing application buttons is increasingly being avoided in process of developing smart systems. More and more frequently is used voice commands. The system which uses voice commands for remote control and monitoring smart home is described in this paper. In the implemented system, the user is able, using specific voice commands to remotely control the operation of various appliances in his home. An Android application was designed to control the implemented system. Using the designed Android application, the user controls the desired home devices with specific voice commands. Also, on the designed Android application are buttons that the user can use, in case the user’s voice is not recognized in the implemented system. For experimental work analysis, the model of the home is made with lights and different home appliances inside. The results of the experimental work analysis of the implemented system show this system is very simple to use and very efficient. Also, the latest technology for remote control and monitor smart systems is applied in the proposed smart home system.

The paper analyzes the cardiovascular parameters of patients with heart disease. The aim of this study was to predict death in a patient with cardiovascular disease based on 12 parameters, using Random Forest and Logistic Regression algorithms. Parameters were tuned for both algorithms to determine the best settings. The most significant factors in the process predicted were found using the FEATURE SELECTION method of both algorithms. By comparative analysis of the obtained results, the highest accuracy of 90% was obtained using the Random Forest Algorithm.

The Canadian Fire Weather Index system [1] has been used worldwide by many countries as classic approach in fire prediction. It represents system that account for the effects of fuel moisture and weather conditions on fire behaviour. It numerical outputs are based on calculation of four meteorological elements: air temperature, relative humidity, wind speed and precipitation in last 24h. In this paper meteorological data in combination with Canadian Fire Weather Index system (CFWI) components is used as input to predict fire occurrence using logistic regression model. As logistic regression is a supervised machine learning method it’s based on user input in the form of dataset. Dataset is collected using NASA GES DISC Giovanni web-based application in the form of daily area-averaged time series in period of 31.7.2010 to 31.7.2020, it’s analysed and pre-processed before it is used as input for logit model. CFWI components values are not imported but calculated in run-time based on pre-processed meteorological data. As a result of this research windows application was developed to assist fire managers and all those involved in studying the fire behaviour.