The human gut microbiome is influenced by numerous factors including commonly used drugs, but it has also been shown that the gut microbiome by itself influences drug responses and efficacy. We studied the relations between commonly used drugs and microbial changes considering factors like polypharmacy and multi-morbidity. We performed metagenomics sequencing of 1883 faecal samples from three cohorts: 1) a population-based cohort, 2) patients with inflammatory bowel diseases and 3) patients with irritable bowel syndrome. Differences between drug users and non-users were analysed per cohort, followed by a meta-analysis. 17 of 41 drugs were associated with changes in microbial features. For example, metformin users showed enrichment of Escherichia-coli -derived metabolic pathways and methanogenic pathways were increased in oral steroid users in patients with IBD. Due the importance of the gut microbiome in health and the widespread use of drugs, we here provide evidence for extensive changes in taxonomy, metabolic activity and resistome in relation to commonly used drugs. This research paves the way to further mechanistic studies for drug response and side effects and has implications on future microbiome studies, underlining the need for correcting for multiple drug use in both general population and in GI disease cohorts.

The popularity of railway transportation has been on the rise over the past decades, as it has been able to provide safe, reliable, and highly available service. The main challenge within this domain is to reduce the costs of preventive maintenance and improve operational efficiency. To tackle these challenges, one needs to investigate and provide new approaches to enable quick and timely data collection, transfer, and storage aiming at easier and faster analysis whenever needed. In this thesis, we aim at enabling the monitoring and analysis of collected signal data from a train propulsion system. The main idea is to monitor and analyze collected signal data gathered during the regular operation of the propulsion control unit or data recorded during the regular train tests in the real-time simulator. To do so, we have implemented a solution to enable train signal data collection and its storage into a .txt and .CSV file to be further analyzed in the edge node and in the future connected to the cloud for further analysis purposes. In our analysis, we focus on identifying signal anomalies and predicting potential failures using MathWorks tools. Two machine learning techniques, unsupervised and supervised learning, are implemented. Additionally, in this thesis, we have investigated ways of how data can be efficiently managed. We have also reviewed existing edge computing solutions and anomaly detection approaches using a survey as a suitable method to identify relevant works within the state of the art.

Assessment of historical buildings presents specific engineering task, considering the ways they were built and the materials, which were used. Many of them belong to cultural heritage and merit special care and protection. This concerns also the historical buildings in Bosnia and Herzegovina. The country is situated in seismic active region of South-East Europe and the majority of the historical buildings were made of stone-masonry. In the case of stronger earthquake motion such buildings could suffer heavy damages. The damages are sometimes cumulated through many years and many causes. Substantial damages were caused by recent war disaster, as well. The aim is to preserve and reveal their aesthetic and historical values and to use original materials and original way of construction, if possible. In most cases seismic assessment procedures result in the requirements for the strengthening or retrofit of the old masonry building structures. Design and construction procedures of repair and strengthening of two medieval stone masonry buildings are presented. Equilibrium between aesthetical and structural demands is discussed.

Introduction. Decreased salivary flow is frequently associated with numerous diseases such as diabetes mellitus and may lead to numerous oral diseases. The aim of this study was to compare salivary flow rate and oral health status in type 2 diabetics and healthy controls. Material and methods. The study involved 90 patients, divided into the three groups: 30 with well controlled (HbA1c<9%), 30 will poorly controlled (HbA1c?9%) diabetes and 30 healthy subjects. The following clinical parameters were determined: decayed, missing and filled teeth (DMFT); plaque index (PI), sulcus bleeding index (SBI), probing pocket depth (PPD) and clinical attachment level (CAL). Culture of Candida spp. specimens were obtained from tongue dorsum and inoculated into Sabouraud Dextrose Agar. Saliva was collected using ?a spit technique?. Results. Highest mean of unstimulated salivary flow was in healthy subjects; however significant difference between groups was not observed. Stimulated salivary flow results indicate significant reduction in diabetics as well as significant relation between metabolic control and salivary flow. Unstimulated and stimulated salivary flows were negatively and significantly correlated with periodontal parameters and DMFT. Conclusion. The present findings indicate that decreased salivary flow rate could have a significant impact on oral health status in type 2 diabetics.