Aim: Nosocomial infections (NIs) represent a major public health problem in developed, and even more in developing countries. Based on the origin of the pathogen, NIs are divided into endogenous caused by microorganisms of the patient’s microflora, and exogenous caused by pathogens from the patient’s environment or by the same microorganism isolated elsewhere from patient’s body. The main aim of this research was to determine the frequency, etiology and types of NIs at the Clinic for Surgery of the University Clinical Center Tuzla. Material and Methods: 5.039 patients were prospectively followed for the development of endogenous and exogenous NIs (January-December 2015). The definition of NI was performed using standardized the National Healthcare Safety Network (NHSN) criteria. Results: Based on continuous epidemiological surveillance, the incidence of NI was 3.51%; with a total of 177 registered infections, 24 endogenous and 153 exogenous. The most common NIs were urinary tract infections (UTIs) (14.29% endogenous and 85.71% exogenous) and surgical site infections (SSIs) (16.67% endogenous and 83.33% exogenous), p<0.001. Gram-negative bacteria were predominant (76.84%) over Gram-positive bacteria (23.16%). Gram-positive bacteria mainly caused bacteremia, while Gram-negative bacteria were most commonly isolated from UTIs and SSIs. The most common Gram-negative bacteria were Klebsiella pneumoniae (24.86%) and Pseudomonas aeruginosa (22.6%), and among Gram-positive, Staphylococcus aureus (10.73%) and coagulase-negative staphylococci (7.91%). Conclusion: Epidemiological surveillance is considered a key link in the program for the prevention and control of NIs. The most important, and the ultimate goal and purpose of conducting epidemiological surveillance are to reduce and eliminate the risk factors, which can lead to a reduction in NI incidence rate. Determining the endemic rates of NIs provides an objective understanding of the overall NI status in an institution as well as existing risk factors for the occurrence of these infections.

Abstract In this chapter, we present a new method of steganography using decomposition of Catalan numbers. The proposed steganographic method consists of two segments: the first segment refers to the process of embedding data and generation of a complex stego key, whereas the second segment refers to the process of extracting a hidden message based on the generated stego key. Both segments consist of several phases. The proposed method provides that the data carrier retains its original shape. At the end of the chapter, security testing and steganalysis of the proposed method are conducted. Implementation in Java programming language successfully proves the work of the proposed method.

The goal of psychometric scaling is the quantification of perceptual experiences, understanding the relationship between an external stimulus, the internal representation and the response. In this paper, we propose a probabilistic framework to fuse the outcome of different psychophysical experimental protocols, namely rating and pairwise comparisons experiments. Such a method can be used for merging existing datasets of subjective nature and for experiments in which both measurements are collected. We analyze and compare the outcomes of both types of experimental protocols in terms of time and accuracy in a set of simulations and experiments with benchmark and real-world image quality assessment datasets, showing the necessity of scaling and the advantages of each protocol and mixing. Although most of our examples focus on image quality assessment, our findings generalize to any other subjective quality-of-experience task.

Abstract The fluctuating production of renewable energy constraints the operation of Power-to-X processes such that steady-state conditions are unattainable without energy storage. It seems eminent to establish operation strategies considering significant disturbances along the process and to determine those scenarios where the operation becomes unfeasible. In this work, an industrial methanol Lurgi-type reactor, embedded in a Power-to-Jet process (Figure 1), is evaluated under fluctuating feed conditions. The simulated scenarios consist of step functions up to 20 % (w/w) increments in the feed flowrate as consequence of the fluctuating power input on the electrolysis stage. A one-dimensional dynamic model for a multi-tubular fixed bed reactor is implemented, considering both the gas and catalyst phase. The mathematical model is solved numerically using orthogonal collocation at the spatial domain and backward differences at the time domain. The system shows rapid response to disturbances, reaching steady state conditions in 1.5 minutes. Furthermore, it is evidenced that the feasible region to increase the production of methanol is narrowed down by rises of carbon dioxide feed flowrate up to 5 % (w/w).

Abstract To comply with the outcomes of the Climate Change Conference in Paris (COP 21), the ever-growing greenhouse gas (GHG) emissions has to be drastically reduced. With the soaring growth rates of GHG emissions in the aviation sector, the need for a near zero-net greenhouse emission alternative is essential. The novel concept of the Power-to-Jet pathway directly utilizes renewable electricity, carbon dioxide and water to synthesize a sustainable kerosene fuel that chemically resembles the one produced from fossil sources, having ‘Drop-in’ capability allowing the use and distribution within existing architectures. In the Power-to-Jet process, hydrogen is produced via water electrolysis. Captured CO2 (from rich point sources) then reacts with hydrogen to produce the intermediate methanol, before being upgraded to the final synthetic jet fuel along with by-products (Schmidt et al., 2012). With fluctuating electricity inputs due to the variability in photovoltaic and wind power generation, the process units within the Power-to-Jet process have to be adjusted at each time-instant to satisfy the production constraints. To find the best operating strategy for these fluctuating conditions, dynamic models are needed. In this work, we will propose a model that describes the dynamic behaviour of the carbon capture section in the Power-to-Jet process. Several dynamic scenarios can be introduced for the carbon capture rate by altering the lean solvent concentration, flue gas flow rates and re-boiler duty. The dynamic information obtained from the simulations (such as: Open loop gain, time constants and dead time) can be used to device an appropriate control scheme under varying electricity inputs, while satisfying all operational constraints.

Objective – The aim of the paper is to present a rare and complex congenital heart defect (CHD), congenitally corrected transposition of the great arteries of the heart (ccTGA) with associated anomalies, including ventricular septal defect (VSD), valvular and subvalvular pulmonary stenosis, dysplasia of the tricuspid valve, and atrial septal defect (ASD) with first-degree atrioventricular block, which was diagnosed, monitored and successfully treated with heart surgery in an infant. Case Report – A female infant was born with 3350 grams in weight, 50 cm in length, oxygen saturation of 98%, and heart rate of 170 beats per minute. The antenatal and perinatal period was normal. CHD was verified by ultrasound at the age of 3 days. Angiotensin-converting-enzyme inhibitors (ACE inhibitors) and diuretics were introduced in therapy after one month. Cardiac surgery (Senning-Rastelli procedure with placement of an 18-mm Contegra conduit) was performed at the age of 9 months. After the operation, the infant was stable on therapy with diuretics, antiaggregants, beta blockers, and antianemic therapy with vitamin D in prophylaxis. Conclusion – ccTGA with associated anomalies is a rare, life-threatening, congenital heart disease. After birth it demands correct diagnosis, adequate follow-up, and cardiac surgery in infancy.

Abstract A synthesis of an industrial utility system considering cogeneration options together with heat exchanger network synthesis has been developed. It consists of boilers at different temperature and pressure levels, steam turbines, condensers, cooling tower, deaerator and a heat exchanger network system, connecting the utility system with the process heat and electricity requirements. A mixed-integer nonlinear programming (MINLP) model was used for synthesis. A sensitivity analysis has been performed considering the price ratio of natural gas to electricity, while also estimating primary energy consumption and GHG emissions. The results indicate that the cogeneration is economically viable at different ratios of natural gas and electricity price. In addition, the sensitivity analysis shows the relationship between cogeneration and electricity purchase for obtaining the minimal primary energy consumption and consequently to reduce GHG emissions.