Today’s modelling approaches in Systems Medicine are increasingly multiscale, containing two or more submodels, where each operates on different temporal and/or spatial scales. In addition, as these models become increasingly sophisticated, they tend to be run as multiscale computing applications using computational infrastructures such as clusters, supercomputers, grids or clouds. Constructing, validating and deploying such applications is far from trivial, and communities in different scientific disciplines have chosen very diverse approaches to address these challenges. Within this paper we reflect on the use of Multiscale Computing within the context of Systems Medicine. Multiscale Computing is widely applied within this area, and instead of summarizing the field as a whole we will highlight a set of challenges that we believe are of key relevance to the Systems Medicine community.

Ovaj rad daje osvrt na stanje standardizacije u oblasti informacijske i bibliotečke djelatnosti u Bosni i Hercegovini, kroz rad dva tehnička komiteta Instituta za standardizaciju BiH. Informatizacija društva, kakva je opisana u strateškim dokumentima iz prethodne decenije, realizirana je ne zahvaljujući, nego uprkos podršci države. Složena politička i teška socijalna situacija u BiH nisu bile prepreka da po broju korisnika interneta budemo iznad svjetskog prosjeka. Na primjeru akademskih i istraživačkih mreža pokazano je da ipak zaostajemo u brzinama pristupa internetu, koje su među najnižim u regiji. IT industrija, kao perspektivna privredna grana, sama čini napore i vrši pritisak na državu da se učini više na razvoju ove djelatnosti, prvenstveno u sektoru obrazovanja. Na kraju rada dat je kritički osvrt na pojam Big Data i njegovu primjenu u naučnim podacima, koji čine usko specijalizirani dio bibliotečke djelatnosti, te ulogu standardizacije u toj oblasti.

Background: This cost-of-illness (COI) study provides deep insight in direct and indirect costs of multiple sclerosis (MS) in Bosnia and Herzegovina (BH). Aim: Objective of this study was to analyze the costs and quality of life (QoL) of patients with MS in BH. Patients and methods: We applied the same methodology already used in study conducted across nine European countries. Sixty-two patients participated with EDSS score not higher than 6.5. Costs are collected using a questionnaire quality of life was measured by EQ-5D and MSQOL-54 questionnaires. Results: Mean age of respondents was 39.8 The mean utility measured by EQ-5D-3L was 0.68 at the beginning and 0.63 at the end of the study. QoL measured by MSQoL-54 showed improvement at the end of the trial. Costs are presented from the societal and payer perspective. Cost of MS in Bosnia and Herzegovina annually amount 124.8 million BAM. Cost driver where indirect and DMDs costs, with significant differences among subgroups. Conclusions: This study provides an in-depth analysis of MS costs in BH providing data for health policies development and information for future cost-effectiveness evaluations of new therapeutic options as well as for comparison of MS costs with other countries.

UDK: 630*23:582.475(234.422 Bjelašnica) This document includes research in regeneration of fir in differently structured stands of beech and fir forests (with spruce) on mountain Bjelašnica near Sarajevo. Analysis of fir regeneration in differently structured stands was done by comparison of numbers of units of young fir, per growth category, and by total number of young fir at canopy density degree of 0.7 (0.60 – 0.79) and 0.9 (0.80 – 1.00), and by mixture ratio – share of fir (spruce) 0.7 (60 – 79 %) and 0.9 (80 – 100 %). Comparisons were done between virgin forest stands of beech and fir (with spruce) on ‘Ravnavala’, than, two-storied stand where we recorded transition of tree species (beech is dominant in upper growth, while fir is mainly dominant in young growth) on location ‘Medvjeđalokva’ and stands of typical uneven aged production forest of beech and fir (with spruce) in direct vicinity of virgin forest stand. Data gathering was done using total measurement method on permanent experimental plots of 1ha in virgin forest stand and two-storied stand on location ‘Medvjeđalokva’ and on circular plots in diameter of 12.62 m. Positions of circular experimental plots were determined by systematic sample in form of grid on intersections of Gauss-Krueger system, in intervals of 100 meters. Grid is laid in three transects of 27 plots each that is spread across forest compartments number: 111, 113, 114 and 115 of Management unit „Igman“, location ‘Ravnavala’. We have placed two experimental square plots of 1ha; one in virgin forest reservation ‘Ravnavala’ for preservation of assortment, status without human impact (compartment 106, MU „Igman“), and the other in management forest of this area “Medvjeđalokva” (compartment 117, MU „Igman”) for specific structure of assortment. Square 1ha plots were divided by grid of squares 10 x 10 m into 100 small plots.

In this paper we present a novel approach for real-time anomaly detection in the flexible production, an emerging area in the manufacturing, esp. in the context of Industry4.0. It is based on an advanced usage of Complex Event Processing combined with the massive data analytics, which enables learning of the clusters, which represent normal/usual and unusual/anomalous behaviour. The main innovation is in the combination of the model-based and data- driven approaches, which enables a continuous anomaly detection. The approach has been implemented using the D2Lab (Data Diagnostics Laboratory) framework for big data processing. The results have been tested in an industry case study, enabling efficient anomaly detection in the shoe manufacturing.

In this paper we present a novel approach for the process improvement based on the data-driven modelling. The idea is that by performing Big data analytics on the past process data we can model what is (statistically analyzed) usual/normal for a selected period and check the variations from that model in the real-time (as Six Sigma requires). Additionally, these data-driven models can support the root- cause analysis that should provide insights what can be eliminated as a waste in the process (as Lean requires). However, due to the above mentioned variety and volume of data, the analytics must be a) robust – dealing with differences efficiently and b) scalable - realized in an extremely parallel way. We propose a novel method for process control that uses big data analytics approaches to deal with the multidimensionality and the large size of the process space. In order to realize this idea we develop a new concept of self- aware digital twins which are able to reason about own behaviour and react if needed. Indeed, we revolutionize the concept of digital twins by extending their "virtual replica" (of physical objects) nature into "digital self-awareness" of physical objects (assets, systems), leading to the new generation of digital twins, so called self-aware DTs, which can "reasons" about the behaviour of an object (and not only mimic it) and actively participate in its improvement. We present the outcomes from the case study related to 3D laser cutting process.

The aim of our work was an implementation of potentiometric determination of copper in samples of the genus Veronica (family Plantaginaceae). Genus Veronica herbs are widely used in e.g. cosmetic, traditional medicine and food industry. The copper content was potentiometrically analysed in 25 herbal samples of genus Veronica and 12 of their hydrolats. The analysed samples were herbal samples of Veronicas harvested mainly in three Croatian regions – Dalmatia, Lika and Slavonia as well as randomly selected samples of theirs hydrolats. Veronicas’ samples were digested in a microwave oven by using nitric acid and hydrogen peroxide mixture. The potentiometric determination was performed by using commercially available CuISE for Cu2+, by using potentiometric methods previously developed in our laboratory.

Mljet (Latin: Melita) is eighth island in Croatia by size, one of the largest south Dalmatian islands and Dubrovnik archipelago’s largest island. Due to its beauty and living standard, the island of Mljet has a rich but insufficiently explored history. The remains of a Roman palace in Polače, according to which the place got its Slavicized name, bear witness of a strong Roman influence and the period of progress of the island of Mljet. The palace in Polače is certainly the most important Roman-period monument on the island. It was built as a villa rustica. Together with Diocletian’s Palace in Split, it represents the largest Roman monument on the entire territory of Dalmatia. The port in Polače is quite hidden and as such offered protection to ships and served as dilivery port for agricultural produce from the entire Roman empire. In the Roman period, this palace served as a headquarters of island’s governor, military, administration and clergy. All previous research suggest that this settlement  was inhabited from 1st to 11th century with all the features of an ancient and early  medieval town. Using previously analyzed sources and available literature, the paper tries to point out the importance and position of the island during the Roman  period. Particular attention was paid to the analysis of two legal acts - the charter of the German army chief and the barbarian king of Italy Odoacer, from the second  half of the 5th century and the fragment of the testament of an unknown testator  from the mid VI century, within which, in the period of a century, is mentioned the  same amount of yield (earnings) from the island of Mljet.

Approximate entropy (ApEn) and sample entropy (SampEn) have been previously used to quantify the regularity in centre of pressure (COP) time-series in different experimental groups and/or conditions. ApEn and SampEn are very sensitive to their input parameters: m (subseries length), r (tolerance) and N (data length). Yet, the effects of changing those parameters have been scarcely investigated in the analysis of COP time-series. This study aimed to investigate the effects of changing parameters m, r and N on ApEn and SampEn values in COP time-series, as well as the ability of these entropy measures to discriminate between groups. A public dataset of COP time-series was used. ApEn and SampEn were calculated for m = {2, 3, 4, 5}, r = {0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5} and N = {600, 1200} (30 and 60 s, respectively). Subjects were stratified in young adults (age < 60, n = 85), and older adults (age ≥ 60) with (n = 18) and without (n = 56) falls in the last year. The effects of changing parameters m, r and N on ApEn and SampEn were investigated with a three-way ANOVA. The ability of ApEn and SampEn to discriminate between groups was investigated with a mixed ANOVA (within-subject factors: m, r and N; between-subject factor: group). Specific combinations of m, r and N producing significant differences between groups were identified using the Tukey’s honest significant difference procedure. A significant three-way interaction between m, r and N confirmed the sensitivity of ApEn and SampEn to the input parameters. SampEn showed a higher consistency and ability to discriminate between groups than ApEn. Significant differences between groups were mostly observed in longer (N = 1200) COP time-series in the anterior-posterior direction. Those differences were observed for specific combinations of m and r, highlighting the importance of an adequate selection of input parameters. Future studies should favour SampEn over ApEn and longer time-series (≥ 60 s) over shorter ones (e.g. 30 s). The use of parameter combinations such as SampEn (m = {4, 5}, r = {0.25, 0.3, 0.35}) is recommended.