Copper has long been known as a metal with outstanding antimicrobial properties. Although ancient healers were not familiar with the mechanisms of its influence on microorganisms, they had empirically established its effectiveness in sterilizing drinking water, disinfecting wounds, treating skin diseases, various infections and other maladies. Recently, there has been renewed interest in investigating copper and its alloys as possible materials that can limit the spread of bacteria and viruses, given that humanity is often facing various local epidemics, and rarely pandemics, as ongoing Corona virus, SARS CoV-2, first detected in March 2020. This paper reviews the recent literature in the research field of antimicrobial properties of metallic copper, its alloys and other copper - based materials, with the aim to promote their future implementation on contact surfaces, primarily in hospitals and institutions with a high frequency of people where the probability of spreading infection is increased.

Lead-free solders have become a main focus of the electronic industry in recent years, because of the high toxicity of lead. Alloys based on the Sn-Bi system figure as potential replacements for Sn-Pb alloys in soldering due to favorable properties and low cost. One of the main advantages of these alloys are low melting temperatures, while additional advantages include good compatibility with substrates, low process temperature, high reliability, and potential applications in conjunction with reduced graphene oxide nanosheets as thermal interface materials. In this paper, characterization of microstructural and thermal properties as well as hardness measurements of seven alloys of different Sn-Bi compositions are performed. Structural properties of the samples were analyzed using optical microscopy and scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS). Thermal conductivity of the samples was investigated using the xenon-flash method, and phase transition temperatures were measured using the differential scanning calorimetry (DSC) analysis.

Obilježavanje 170 godina od smrti Petra II Petrovića Njegoša (1813–1851) prilika je da se utvrde dosadašnji dometi njegošologije, koji svjedoče o Njegoševom nepojmljivom umotvornom potencijalu, o kompleksnosti njegovog ukupnog prosvjetiteljskog djelovanja i o njegovoj pjesničkoj poziciji, ali i da se otvore novi horizonti i mogućnosti za ispitivanje do sada nedovoljno istraženih ili neopravdano zapostavljenih kodova Njegoševog poetskog opusa.

Abstract In this paper, we consider data driven control of Hammerstein systems. For such systems a common control structure is a transfer function followed by a static output nonlinearity that tries to cancel the input nonlinearity of the system, which is modeled as a polynomial or piece-wise linear function. The linear part of the controller is used to achieve desired disturbance rejection and tracking properties. To design a linear part of the controller, we propose a weighted average risk criterion with the risk being the average of the squared L2 tracking error. Here the average is with respect to the observations used in the controller and the weighting is with respect to how important it is to have good control for different impulse responses. This criterion corresponds to the average risk criterion leading to the Bayes estimator and we therefore call this approach Bayes control. By parametrizing the weighting function and estimating the corresponding hyperparameters we tune the weighting function to the information regarding the true impulse response contained in the data set available to the user for the control design. The numerical results show that the proposed methods result in stable controllers with performance comparable to the optimal controller, designed using the true input nonlinearity and true plant.