. Screening for lymphedema and accurate quantitative assessment of dermal backflow patterns on ICG represents a major shift in current clinical practice paradigms, putting an emphasis on early detection of lymphedema rather than palliative treatments and symptomatic relief. These findings set the stage for the development of a practical, universal, ICG-based quantification system for the staging of lymphedema, a significant advancement in the field of plastic surgery.

The material extrusion fused deposition modeling (FDM) technique has become a widely used technique that enables the production of complex parts for various applications. To overcome limitations of PLA material such as low impact toughness, commercially available materials such as UltiMaker Tough PLA were produced to improve the parent PLA material that can be widely applied in many engineering applications. In this study, 3D-printed parts (test specimens) considering six different printing parameters (i.e., layer height, wall thickness, infill density, build plate temperature, printing speed, and printing temperature) are experimentally investigated to understand their impact on the mechanical properties of Tough PLA material. Three different standardized tests of tensile, flexural, and compressive properties were conducted to determine the maximum force and Young’s modulus. These six properties were used as responses in a design of experiment, definitive screening design (DSD), to build six regression models. Analysis of variance (ANOVA) is performed to evaluate the effects of each of the six printing parameters on Tough PLA mechanical properties. It is shown that all regression models are statistically significant (p<0.05) with high values of adjusted and predicted R2. Conducted confirmation tests resulted in low relative errors between experimental and predicted data, indicating that the developed models are adequately accurate and reliable for the prediction of tensile, flexural, and compressive properties of Tough PLA material.

Attack graphs are a tool for analyzing security vulnerabilities that capture different and prospective attacks on a system. As a threat modeling tool, it shows possible paths that an attacker can exploit to achieve a particular goal. However, due to the large number of vulnerabilities that are published on a daily basis, they have the potential to rapidly expand in size. Consequently, this necessitates a significant amount of resources to generate attack graphs. In addition, generating composited attack models for complex systems such as self-adaptive or AI is very difficult due to their nature to continuously change. In this paper, we present a novel fragment-based attack graph generation approach that utilizes information from publicly available information security databases. Furthermore, we also propose a domain-specific language for attack modeling, which we employ in the proposed attack graph generation approach. Finally, we present a demonstrator example showcasing the attack generator's capability to replicate a verified attack chain, as previously confirmed by security experts.

Magnetic nanoparticles can be electrostatically assembled around sperm cells to form biohybrid micro robots. These biohybrid microrobots possess sufficient magnetic material to potentially allow for pulse-echo localization and wireless actuation. Alternatively, magnetic excitation of these nanoparticles can be used for localization based on Faraday's law of induction using a detection coil. Here, we investigate the influence of the electrostatic attraction between positively charged nanoparticles and negatively charged sperm cells on the activation of the nanoparticles during nonlinear differential magnetometry and wireless magnetic actuation. Activation of clusters of free nanoparticles and nanoparticles bound to the body of sperm cells is achieved by a combination of a high- frequency alternating field and a pulsating static field. The nonlinear response in both cases indicates that constraining the nanoparticles is likely to yield significant decreases in the magnetometry sensitivity. While the attachment of particles to the cells enables wireless actuation (rolling locomotion), the rate of change of the magnetization of the nanoparticles decreases one order of magnitude compared to free nanoparticles.

Technoeconomic, environmental and safety criteria generally affect the management of metallic and non-metallic mining operations. The first basic question that needs to be addressed when planning ore mining is which methods are adequate and what is the optimal mining technology? Due to the complex geologic framework of ore deposits, geological exploration has rendered synonymous the inherent uncertainties, vagueness, and inaccuracies. As a result, subjective evaluation by engineers and expert experience have become increasingly important. Given that the natural language used by miners and geologists is most suited for relaying knowledge and expressing opinions, the paper tests a fuzzy optimization methodology that uses linguistic variables. Consequently, extent analysis is applied to fuzzy AHP by means of triangular fuzzy numbers to arrive at a decision about the optimal mining technology. The entire procedure constitutes an integrated mine management system, which will contribute to sustainable production in the future. A case study to which the model was applied is presented in the paper.

This paper presents an effective approach to enable performance improvement in human-robot collaboration scenarios. The problem is tackled from the perspective of speed and separation monitoring principle, which stems from the recently instituted safety standard. The proposed approach attempts to seek for performance gains, measured by the speed-up of the production cycle, without compromising the safety constraints consistent with the standard. The approach is based on the notion of braking surface - an abstraction of the swept volume described by the manipulator during braking motion. We address two types of braking behavior: general and path-consistent. In both cases, the braking surface can be evaluated in a receding horizon manner. The robot velocity is continuously scaled such that, in case of a controlled stop, the corresponding volume spanned by the robot (braking surface) does not interfere with the surrounding obstacles. The approach is entirely kinematic and does not require the knowledge of the robot's dynamic model. Simulation study indicates that the pro-posed approach offers performance improvements compared to other state of the art methods. Moreover, the experiments demonstrate the real-time applicability of the method with the real robot in human-shared environment.

Pomegranate has shown a favorable effect on gingivitis/periodontitis, but the mechanisms involved are poorly understood. The aim of this study was to test the effect of pomegranate peel extract (PoPEx) on gingiva-derived mesenchymal stromal cells (GMSCs) under physiological and inflammatory conditions. GMSC lines from healthy (H) and periodontitis (P) gingiva (n = 3 of each) were established. The lines were treated with two non-toxic concentrations of PoPEX (low—10; high—40 µg/mL), with or without additional lipopolysaccharide (LPS) stimulation. Twenty-four genes in GMSCs involved in different functions were examined using real-time polymerase chain reaction (RT-PCR). PoPEx (mostly at higher concentrations) inhibited the basal expression of IL-6, MCP-1, GRO-α, RANTES, IP-10, HIF-1α, SDF-1, and HGF but increased the expression of IL-8, TLR3, TGF-β, TGF-β/LAP ratio, IDO-1, and IGFB4 genes in H-GMSCs. PoPEx increased IL-6, RANTES, MMP3, and BMP2 but inhibited TLR2 and GRO-α gene expression in P-GMSCs. LPS upregulated genes for proinflammatory cytokines and chemokines, tissue regeneration/repair (MMP3, IGFBP4, HGF), and immunomodulation (IP-10, RANTES, IDO-1, TLR3, COX-2), more strongly in P-GMSCs. PoPEx also potentiated most genes’ expression in LPS-stimulated P-GMSCs, including upregulation of osteoblastic genes (RUNX2, BMP2, COL1A1, and OPG), simultaneously inhibiting cell proliferation. In conclusion, the modulatory effects of PoPEx on gene expression in GMSCs are complex and dependent on applied concentrations, GMSC type, and LPS stimulation. Generally, the effect is more pronounced in inflammation-simulating conditions.

The implementation of disruptive technologies of Industry 4.0 is carried out in all segments of society, but we still do not fully understand the breadth and speed of its application. We are currently witnessing major changes in all industries, so that new business methods are emerging, as well as transformation of production systems, new form of consumption, delivery and transport. All this is happening due to the implementation of disruptive technological discoveries that include: the Internet of Things (IoT), advanced robotics, smart sensors, Big Data, analytics, cloud computing, 3D printing, machine learning, virtual and augmented reality (AR), artificial intelligence, and productive maintenance. Advanced robotics is one of the most important technologies in Industry 4.0. The robotic application in the automation of production processes, with the support of information technology, leads us to ‘’smart automation’’, i.e., ‘’smart factory’’. The changes are so profound that, from the perspective of human history, there has never been a time of greater promise or potential danger. New generation robots have many advantages compared to the firstgeneration industrial robots such as: they work alongside with workers, workers perform their tasks in a safe environment, robots take up less space, robots do not need to be separated by fences, robots are easy to manipulate and cheaper to implement. The paper analyzes the trend of implementation of collaborative and service robots for logistics, which make the automation of production processes more flexible. Robotic technology is the basic technology of Industry 4.0, because without its application, the implementation of Industry 4.0 would not be possible. The trend of application of new generation robots will have an increasing character in the future, because the goals of the fourth industrial revolution cannot be achieved without collaborative robots. In other words, the objective is to achieve a ‘’smart production process’’ or ‘’smart factory’’.

Since the introduction of the concept of Industry 4.0 until today, the world is facing a series of changes resulting from intensive scientific, technical and technological innovations. Research, innovation and development changes are aimed at improving production, business and everyday life through the application of basic technologies of Industry 4.0. In order for individuals, organizations, communities and states to be able to use the benefits of these improvements, it is necessary to rapidly adapt to all innovative trends: developing the necessary skills of individuals and groups for the adoption and use of these technologies, the implementation of technologies in companies, organizations and institutions, and the development of appropriate strategies that these processes would be managed and directed. In the developed world, these I 4.0 implementation processes are already reaching their maturity: educational programs are adapted to the needs of monitoring technical-technological changes, companies deal with solving challenges related to these processes after the implementation of Industry 4.0 technologies, and states and communities are working on devising further directions of development and a strategy that will further accelerate changes. In Bosnia and Herzegovina, the processes are somewhat slower: educational programs partially follow the needs of education for Industry 4.0, companies struggle with the challenges of adopting and implementing Industry 4.0 without adequate institutional support, and strategies related to exploiting the opportunities of Industry 4.0 have not been developed, both due to the lack of initiative, as well as due to administrative restrictions related to the complex political system of Bosnia and Herzegovina. Considering that, this paper presents the results of research on the representation of Industry 4.0 technologies in the economy and education of Sarajevo Canton. The sample on which the research was conducted included 105 companies and 239 respondents from the general population. The results show that the highest level of application of Industry 4.0 technologies exists in the part related to the advanced management of company resources using planning and management support systems, and in communications. These findings, as well as the results related to the established level of knowledge of Industry 4.0 technologies in the general population, speak in favor of the need for the urgent development of various educational programs that will accelerate the learning of Industry 4.0 among all members of the community, as well as the establishment of state programs to support the implementation of technologies in companies, so that the economy of the Canton and the country as a whole would not fall behind in relation to the world driven by the fourth industrial revolution.

Digital twins represent a new paradigm that brings fundamental changes to business and asset management. The proliferation of connected devices and sensors has generated vast amounts of data from physical assets and processes. Digital twins leverage this data to create a virtual counterpart that reflects the behavior, performance, and characteristics of their physical counterparts in real-time. The definition of digital twins encompasses a wide range of applications and contexts. This paper provides an overview of existing literature on digital twins, including their definition, key characteristics, and classification. Additionally, it highlights potential challenges and limitations associated with digital twins and identifies the technologies that enable their implementation. By understanding the fundamental concepts and technological advancements in the field of digital twins, organizations can harness their potential to enhance their business, optimize resources, and foster innovation. Numerous examples of digital twin applications in various industries are highlighted in this paper, with a particular focus on the elevator industry. Therefore, this paper serves as a comprehensive source of information for researchers, practitioners, and decision-makers who wish to explore the application of digital twins in different industries and domains.

The study determined antimicrobial activity using the Disc-diffusion method and extracts of three plants: garlic (Allium sativumL.), turmeric (Curcuma longaL.), and parsley (Petroselinum crispumL.) on Escherichia coli, Salmonella ssp. and Listeria monocytogenes. These pathogens have attracted the attention of numerous agencies and researchers,because of the negative impact on food and human health -and because of the impact of disease development on the economy. These studies are necessary and represent potential natural antimicrobial drugs, and due to the resistance of bacteria to known antibiotics, there is a constant increase in global consumer demand for natural ingredients. The tested plant extracts showed excellent antibacterial activity in all three replicates on Escherichia coliwith an average inhibition zone of 21,86 mm and were characterized as ***S -sensitive for the mentioned bacterium. With an average zone of inhibition of 19,052 mm, Curcuma longashowed the strongest effect on the tested bacterium Salmonella enteritidis, which tells us that this bacteria is very sensitive to the extract of the mentioned plant. The study identified zones of inhibition of very low values (˃ 8 mm) in all three tested extracts: Allium sativumL., Curcuma longaL. Petroselinum crispumL., and Listeria monocytogenes.KEYWORDS:Antimicrobial activity, extract, Disc-diffusion method