I first met Ulf Svante von Euler when he came to Belgrade, in 1968, to attend an international symposium on the occasion of the 50th anniversary of the Medical Faculty. I was at that time a graduate student at the Medical Faculty in Sarajevo, and a new researcher. I had finished medical school in Belgrade and had worked for two years as a physician in the northern part of Serbia. This article is protected by copyright. All rights reserved.

Amateurish and unprofessional handling of agricultural resources has lasting und unprecedented consequences for plant production, manifesting itself through the loss of soil quality, reduced crop yields, soil erosion, etc. The main focus of this research was to establish the characteristics of the agricultural soil within the municipality of Bužim, applying the FAO method AEZ (Agro-ecological Zoning), (FAO, 1978), and based on the achieved results, to assess the soil suitability for plum (Prunus domestica) cultivation. The assessment of the soil suitability has led to the conclusion that a significant part of land (classified S1 to N in quality), out of the total 13.026,27 ha of agricultural area belonging to the municipality of Bužim is well suited for fruit production. The following has been observed: areas with the best rated S1 class make up a total of 1.23% (159.52 ha), the S2 class takes up a total of 5.51% (717.24 ha), the S3 suitable class makes up a 2.29 % (298.24 ha) in total, and the largest area totaling 36.68 % (4.772.60 ha) is classified as N - meaning unsuitable soil. The main restraints imposed on intensive plum cultivation within the examined area are lack of nourishment, tilt, depth, rock-strewn soil and soil reaction.

Four new heteroleptic copper(II) complexes having chalcone or flavonol ligands and Schiff base (N-phenyl-5-chlorosalicylideneimine) as co-ligand were prepared, chemically and structurally characterized and investigated as functional biomimetic catecholase models. The complexes were prepared by the solution synthesis and crystal and molecular structures were determined by X-ray diffraction. Complexes were chemically characterized by elemental analysis, infrared and electronic absorption spectroscopy as well as by electrochemical measurements. Copper(II) chalcone complexes, with square-pyramidal CuO4N core, are binuclear, featuring phenolate oxygen from the Schiff base as a bridging atom, while copper(II) flavonol complexes are mononuclear, and reveal a square planar CuO3N coordination core. Catalytic activity of the complexes in 3, 5-di-tert-butylcatechol oxidation was confirmed by spectrophotometric and electrochemical measurements. Kinetic measurements revealed that the binuclear (chalcone-containing) complexes have enhanced catalytic activity as compared to the mononuclear Cu(II) flavonol complexes. Relatively high kcat values (300 – 750 h–1) confirmed their respectable biomimetic catecholase-like activity.

ABSTRACT Introduction:The anticonvulsant activity of cannabinoids attracted much attention in the last decade. Cannabinoids that are currently investigated with the intention of making them drugs for the treatment of epilepsy are cannabidiol, cannabidivarin, Δ9-tetrahydrocannabivarin, and Δ9-tetrahydrocannabinolic acid. Areas covered:In this review, the authors look at the results of preclinical and clinical studies with investigational cannabinoids. Relevant literature was searched for in MEDLINE, SCOPUS, EBSCO, GOOGLE SCHOLAR, and SCINDEX databases. Expert opinion: Preclinical studies confirmed anticonvulsant activity of cannabidiol and cannabidivarin in a variety of epilepsy models. While the results of clinical trials with cannabidivarin are still awaited, cannabidiol showed clear therapeutic benefit and good safety in patients with therapy-resistant seizures associated with Dravet syndrome and in patients with Lennox–Gastaut syndrome who have drop seizures. However, the full therapeutic potential of cannabinoids in treatment-resistant epilepsy needs to be investigated in the near future.

This paper explores how the functional safety of industrial deployments can be improved through emerging Industrie 4.0 approaches. We discuss how new sources of data, that are becoming accessible through advancing digitalization, can be used for this purpose, and how principles from predictive maintenance systems can be applied to industrial fail-safe applications: based on data from the industrial components themselves and from their environment as well as on metadata about interactions between these systems and people, we propose to create a model-based monitoring and controlling system that focuses on preserving the functional safety of the installation as a whole. We expect such a Predictive Fail-Safe system to mitigate or even prevent unsafe consequences of failures even in highly dynamic “smart factories”, thereby reducing or preventing harm to other equipment, the environment, and the involved people.

Today's systems are being built to connect to public or semi-public networks, are able to communicate with other systems, e.g., in the context of Internet-of-Things (IoT), involve multiple stakeholders, have dynamic system reconfigurations, and operate in increasingly unpredictable environments. In such complex systems, assuring safety and security in a continuous and joint effort is a major challenge, not the least due to the increasing number of attack surfaces arising from the increased connectivity. In this paper we present an approach that aims to bridge the gap between safety and security engineering. The potential of the approach is illustrated on the example of E-gas system, discussing the cases when unintentional faults as well as malicious attacks are taken into consideration when assuring safety of the described system.

In context of safety-critical Systems of Systems (SoS) that are built as a collection of several systems capable of fulfilling their own function as well as the overall SoS function, increase production efficiency and decrease human effort in such systems, one has to be able to guarantee critical properties such as safety and security. It is not sufficient to analyze and guarantee these critical properties isolated one from another, but one has to be able to provide joint analysis and guarantees on safety and security. This paper is our initial effort towards building a common safety and security assurance approach for complex SoS, where we start from identification and analysis of attack models and connecting them to the already identified functional safety requirements. In this way we will be able to assess system assets and vulnerabilities, and identify ways how an attacker could exploit them. We aim to connect attack modeling process to safety process by aligning mitigation strategies with safety requirements.

Two-dimensional (2D) materials have tremendous potential for next-generation nano- and opto-electronics [1], [2]. However, heat dissipation and its removal from hot spots in the monolayer remains a critical concern to the design of 2D-based devices [2], [3]. Thermal currents flowing in a atomic layer can either dissipate through source/drain contacts, as in a transistor configuration, or through a supporting substrate via van der Waals (vdW) coupling to it. When a 2D mateiral is supported by a substrate, the interfacial area formed between it and the substrate is often far larger than the lateral source/drain contact area. Thus, it is suspected that the majority of waste heat is removed across the 2D-substrate interface and then via the substrate. Therefore, it is imperative that the thermal boundary conductance (TBC) between the 2D layer and substrate be well characterized for reliable 2D device performance. Herein we tackle the question of selecting the best substrate for each 2D material from the point of view of heat dissipation.

: Autonomous cooperative driving systems require the integration of research activities in the field of embedded systems, robotics, communication, control and artificial intelligence in order to create a secure and intelligent autonomous drivers behaviour patterns in the traffic. Beside autonomous vehicle management, an important research focus is on the cooperation behaviour management. In this paper, we propose hybrid automaton modelling to emulate flexible vehicle Platoon and vehicles cooperation interactions. We introduce novel coding function for Platoon cooperation behaviour profile generation in time, which depends of vehicles number in Platoon and behaviour types. As the behaviour prediction of transportation systems, one of the primarily used methods of artificial intelligence in Intelligent Transport Systems, we propose an approach towards NARX neural network prediction of Platoon cooperation behaviour profile. With incorporation of Platoon manoeuvres dynamic prediction, which is capable of analysing traffic behaviour, this approach would be useful for secure implementation of real autonomous vehicles cooperation.

A company follows the concept of corporate social responsibility (CSR) when, in addition to its basic economic functions, it fulfi lls other functions to achieve greater social goals. Corporate social responsibility is an imperative in the modern world of business while in theory, it is still the subject of discussions. Nevertheless, within diff erent theories, there is a certain consensus specifi cally related to the understanding of the importance of stakeholders and the existence of diff erent levels of CSR. Th e main aim of this paper is to explore and analyze employee perceptions of CSR activities in Bosnia and Herzegovina. Th is paper will present a survey of the perception of 100 corporate representatives related to CSR, with an analysis of the infl uence of sociodemographic factors and job characteristics on their attitudes. In addition, the paper off ers the conclusion, with a number of recommendations for improving the current state of CSR in Bosnia and Herzegovina.