The aqueous extract of the Helichrysum italicum leaves (HI) is tested as a corrosion inhibitor of an iron in a simulated acid rain using potentiodynamic polarisation, cyclic voltammetry and electrochemical impedance spectroscopy. Results of all electrochemical methods indicate an increase of a corrosion inhibition efficiency of the iron with the HI extract concentration. Maximum inhibition efficiency (~ 50 %) is obtained at 2.0 g L–1 HI extract. The inhibitive action is assumed to occur via an adsorption of the HI extract on the iron surface. Results indicate that the adsorption process is spontaneous and follows the Freundlich adsorption isotherm. According to the calculated ΔG value (~ 15 kJ mol–1), the corrosion inhibition of the iron occurs predominantly via a physisorption of the HI extract. The concentration of iron ions released into a solution, measured by atomic absorption spectrometry, is in accordance with the electrochemical results.

both in the prenatal and postnatal period2. The syndrome is like a big puzzle whose parts need to be carefully assembled to get a whole picture.2 Good multidisciplinary approach, proper communication and collaboration with parents and all physician’s involved are required in the diagnostic process. All available resources and tools are needed to increase diagnostic precision in the prenatal diagnosis of fetal syndromes.4

Existing approaches to business process model-driven synthesis of data models are characterized by a direct synthesis of a target model based on source models represented by concrete notations, where the synthesis is supported by monolithic (semi)automatic transformation programs. This article presents an approach to automated two-phase business process model-driven synthesis of conceptual database models. It is based on the introduction of a domain specific language (DSL) as an intermediate layer between different source notations and the target notation, which splits the synthesis into two phases: (i) automatic extraction of specific concepts from the source model and their DSL-based representation, and (ii) automated generation of the target model based on the DSL-based representation of the extracted concepts. The proposed approach enables development of modular transformation tools for automatic synthesis of the target model based on business process models represented by different concrete notations. In this article we present an online generator, which implements the proposed approach. The generator is implemented as a web-based, service-oriented tool, which enables automatic generation of the initial conceptual database model represented by the UML class diagram, based on business models represented by two concrete notations.

New technologies are leading to changes in business models. Skills needed to perform most jobs are changing profoundly. Their acquisition and development are becoming crucial for the success and modernization of the labour market offering new forms of flexibility and security for job seekers, employees and employers. The era of automation necessitates the development of not only digital, but also social and emotional skills. Development of creativity, innovation, analytical and critical thinking, communication, negotiation and decision-making skills are gaining in importance. These skills, an integral part of entrepreneurship competence, are developed through entrepreneurship education. In today's world, this form of education is approached not only in the narrow sense, as a process of preparing for business creation, but also in a wider context, as a process of developing entrepreneurial mindset and skills and personal qualities that have universal application. There are several approaches, methods and models of entrepreneurship education. Serbia does not yet have a clearly defined strategy for developing this type of education. Aimed at providing recommendations for the selection of optimal solutions, an assessment study of the effects of the 'Student Company' method of entrepreneurship education, recognized globally as a model of good practice, was carried out within our education system. The research has shown that, according to the assessment of 175 teachers involved in the programme, the 'Student Company' method also gives excellent results in our country. This speaks in favour of its inclusion in all secondary schools in Serbia as an informal type of education.

Abstract. Current global mitigation ambition as under the Paris Agreement as reflected in the National Determined Contributions (NDCs) up to 2030 is insufficient to achieve the Agreement's 1.5 °C long term temperature limit. As governments are preparing new and updated NDCs for 2020, the question as to how much collective improvement is achieved is a pivotal one for the credibility of the international climate regime. The recent Special Report of the Intergovernmental Panel of Climate Change on Global Warming of 1.5 °C has assessed a wide range of scenarios that achieve the 1.5 °C limit. Those pathways are characterized by a substantial increase in near-term action and total greenhouse gas (GHG) emission levels about 50 % lower than what is implied by current NDCs. Here we assess the outcomes of different scenarios of NDC updating that fall short of achieving this 1.5 °C benchmark. We find that incremental improvements in reduction targets even if achieved globally, are insufficient to align collective ambition with the goals of the Paris Agreement. We provide estimates for global mean temperature increase by 2100 for different incremental NDC update scenarios and illustrate climate impacts under those scenarios including for extreme temperature, long-term sea level rise and economic damages for the most vulnerable countries. Under the assumption of maintaining ambition as reflected in current NDCs up to 2100 and beyond, we project a reduction in the Gross Domestic Product (GDP) in tropical countries of about 50–60 % compared to a no-climate change scenario and long-term sea-level rise of close to 2 m in 2300. About half of these impacts can be avoided by limiting warming to 1.5 °C, or below. Scenarios of more incremental NDC improvements do not lead to comparable reductions in climate impacts. An increase in 2030 of the aggregated NDC ambition of big emitters by 33 % does not deliver more than about half the potential reduction in climate impacts compared to limiting warming to 1.5 °C. Our results underscore that a transformational increase in 2030 ambition is required to achieve the goals of the Paris Agreement and avoid the worst impacts of climate change.