Development of a spatial decision support system requires integration of various spatial data sets coming from different information systems of possibly more than one organization. The spatial decision support system development for spatial planning and environmental protection is discussed and spatial data integration is described. The heterogeneity of information systems from which spatial data come is reflected through their purpose. Utility and real estate cadaster systems imply services to citizens as part of spatial data infrastructure in the Federation of Bosnia and Herzegovina. The spatial planning information system is intended for registration of environmental changes and spatial decision making. Utility cadaster information system development is described along with important aspects on how to satisfy both functional cadastral services and spatial planning experts needs to analyze information related to land use and network supply systems. Particular attention is given to spatial data transformation for utility cadaster database development in accordance with a prescribed data model.

Biodiversity of diatoms and applicability of diatom indices in biomonitoring based on littoral epiphytic samples of Lake Modrac were investigated. Diatoms were taken mostly from Phragmites australis stems in 2017, during which physical and chemical parameters of the water were measured. A total of 85 diatom taxa were identified. Gomphonema (13 spp.), Navicula (11 spp.), and Nitzschia (8 spp.) were the most abundant genera. Obtained values of trophic indices (TID, TvD, and TDIL) pointed to meso- to eutrophic status for most localities, while values of the IBD, EPI, ?D, and IPS indices indicated good ecological status, except for localities at the mouth of 2 main tributaries which had moderate or poor ecological status. Based on the hierarchical group average clustering and nonmetric multidimensional scaling, 4 groups were identified, mainly related to the sampling period, with higher spatial variation in species composition during summer. Since environmental legislation in Bosnia and Herzegovina still does not provide detailed instructions on using diatoms in biological assessment, results of this study can be useful for the development of biomonitoring tools for lakes in Bosnia and Herzegovina.

Routing process should encompass finding the best route through the network according to different criteria, with respect to the principle of load balancing, dynamic adaptation to current network conditions, special treatment of traffic based on QoS levels, as well as minimum energy consumption through energy-aware routing. The emergence of the IoT paradigm, 5G networks, increased number of real-time and mobile applications, as well as the increasingly complex requirements in terms of QoS, have put a grave task ahead of the researchers and the industry. Adaptive and efficient management of current network and traffic, and basis for making the networks resistant and ready for the inevitable changes in the foreseeable future, must be ensured. The idea of software-defined networks has offered a new architecture that seeks to overcome the disadvantages of classical network architectures. This approach has enabled direct programmability of the network, faster and simpler introduction of innovations, greater granularity of routing criteria, implementation of consistent and comprehensive policies, real-time response to changes, etc. This paper is a state-of-the-art overview of SDN traffic routing benefits in different network environments, as well as open issues and challenges to be addressed in future research.

Aim of this paper is to explore latency in reconvergence after link failure when using BGP-LS/PCEP as southbound protocols in IP/MPLS network with centralized controller. Controller in network is PCE element in charge of Traffic Engineering management. Scenario in this paper describes an IP/MPLS network with four routers, fours links and four tunnels passing through multiple links. In case of a link failure, affected tunnels must be rerouted to alternative links evenly distributing traffic across the links. Therefore, it is necessary to have a central controller that will have a complete knowledge of the network in order to evenly and efficiently redistribute traffic. Our IP/MPLS network contains multi-vendor devices and do not support OpenFlow protocol hence as a southbound protocols standardized BGP-LS and PCEP are used. BGP in general is designed as a very slow protocol. Additional, BGP-LS has to wait for the internal routing protocol on the routers to update the Traffic Engineering Database before the BGP-LS signals change event to its peers. Therefore, we will explore some possibilities of reducing the latency in reconvergence after link failure.

Digital analysis and biomedical image processing has become important part within modern medicine and biology. Digital pathology is just one of many medicine areas that is being upgraded by constant biomedical engineering research and development. It is very important that some of disciplines as nucleus detection, image segmentation or classification become more and more effective, with minimum human intervention on these processes, and maximum accuracy and precision. Improved optimization of nucleus segmentation methods parameters based on two levels of voting processes is presented in this paper. First level includes hybrid nucleus segmentation based on 7 segmentation algorithms: OTSU, Adaptive Fuzzy-c means, Adaptive K-means, KGB (Kernel Graph Cut), APC (Affinity Propagation Clustering), Multi Modal and SRM (Statistical region merging) based on optimization of algorithms parameters along with implemented first level voting structure. Second level voting structure includes segmentation results obtained in the first level of voting structure in combination with 3rd party segmentation tools: ImageJ/Fiji and MIB (Microscopy Image Browser). A definite segmented image of a nucleus could serve as a generic ground truth image because it is formed as a result of a consensus based on several different methods of segmentation and different parameter settings, which guarantees better objectivity of the results. In addition, this approach can be used with great scalability on 3D-stack image datasets.

It is suggested that IL-23/IL-17 axis and single nucleotide polymorphisms (SNPs) of IL23R may have crucial role in pathogenesis of Crohn’s disease (CD). Thus, we sought to assess the IL23R SNPs contribution to susceptibility and phenotype of CD. We recruited 117 CD subjects and 117 controls from Poland and 30 CD subjects and 30 controls from Bosnia and Herzegovina (B&H). Two common IL23R SNPs: rs1004819, rs7517847 were genotyped using TaqMan SNP assays. In the Polish population it was found that allele rs1004819: A increases the risk of CD, while allele rs7517847: A is protective against disease development. In Poles the co-carriage of two IL23R risk genotypes was associated with increased risk of CD. A significantly increased risk of CD early onset was observed in Poles carrying at least one rs7517847: G allele. It was also found that IL23R SNPs may be associated with structuring/penetrating CD behavior, as alleles rs1004819: A and rs7517847: G were significantly less frequent in patients without complications, from Poland and B&H, respectively. Allele rs1004819: A was also significantly more frequent in Poles with penetrating CD. These results confirm IL23R SNPs contribution to CD susceptibility in the Polish population and suggest their impact on early age of onset and more severe disease course.

Background: Despite multistep efforts, many asthma patients remain symptomatic. Anti-inflammatory activities of curcumin are shown. Aim of the study was to analyse the impact of curcumin add-on therapy on inflammatory parameters, lung function, disease control and quality of life in asthma patients. Subjects and methods: Three-months lasting study was done on 150 non-smokers with asthma, that were treated with stable, moderate dose of inhaled glucocorticoids (IGK) and divided into three groups (n=50 each): curcumin group (receiving curcumin 500 mg per os twice daily), placebo group (receiving placebo tablets) and control (non-intervention) group. Sputum eosinophils (sEo), blood eosinophils (bEo), high sensitive C-reactive protein (hsCRP), predicted forced expiratory volume in first second (FEV1%), Asthma Control Test (ACT) and mini Asthma Quality of Life Questionnaire (mAQLQ) were compared before and after study, as well as between groups. Results: Before study, all followed parameters were similar between groups. After study, FEV1%, ACT and AQLQ were improved in all groups, but these improvements were more prominent in curcumin group than in placebo and control. Additionally curcumin group only showed improvement in sEo, bEo and hsCRP. Furthermore, curcumin group showed more frequent clinically significant improvement in ACT score (change>3) and in mAQLQ score (change≥0.5) when compared to placebo and control. On the other side, after study FEV1%, ACT, mAQLQ, hsCRP, sEo and bEo were similarly distributed among placebo and control group. Conclusion: This is the first placebo controlled and single-blind study to suggest that add-on therapy with curcumin could improve lung function, disease control and quality of life in moderate partially controlled asthma. Future studies may benefit from a larger sample size, longer study duration, double blind design, different dose of curcumin and/or improvements in oral bioavailability.

In this paper, we introduce a transfer learning approach for our novel hybrid brain-computer interface in which electroencephalography and functional transcranial Doppler ultrasound are used simultaneously to record brain electrical activity and cerebral blood velocity respectively due to flickering mental rotation and word generation tasks. We reduced each trial into a scalar score using Regularized Discriminant Analysis (RDA). For each individual, class conditional probabilistic distribution of each mental task was estimated using RDA scores of the trials corresponding to that mental task. Similarities between class conditional distributions across individuals were measured using Kullback-Leibler divergence, Bhattacharyya, and Hellinger distances. Classification task was performed using Quadratic Discriminant Analysis (QDA), Linear Discriminant Analysis (LDA), and Support Vector Machines (SVM). We demonstrate that transfer learning can reduce calibration requirements up to %87.5. Moreover, it was found that QDA provides the most significant performance improvement compared to the case when no transfer learning is employed.

BACKGROUND Recently, hybrid brain-computer interfaces (BCIs) combining more than one modality have been investigated with the aim of boosting the performance of the existing single-modal BCIs in terms of accuracy and information transfer rate (ITR). Previously, we introduced a novel hybrid BCI in which EEG and fTCD modalities are used simultaneously to measure electrical brain activity and cerebral blood velocity during motor imagery (MI) tasks. NEW METHOD In this paper, we used multi-scale analysis and common spatial pattern algorithm to extract EEG and fTCD features. Moreover, we proposed probabilistic fusion of EEG and fTCD evidences instead of concatenating EEG and fTCD feature vectors corresponding to each trial. A Bayesian approach was proposed to fuse EEG and fTCD evidences under 3 different assumptions. RESULTS Experimental results showed that 93.85%, 93.71%, and 100% average accuracies and 19.89, 26.55, and 40.83 bits/min average ITRs were achieved for right MI vs baseline, left MI versus baseline, and right MI versus left MI respectively. COMPARISON WITH EXISTING METHODS These performance measures outperformed the results we obtained before in our preliminary study in which average accuracies of 88.33%, 89.48%, and 82.38% and average ITRs of 4.17, 5.45, and 10.57 bits/min were achieved for right MI versus baseline, left MI versus baseline, and right MI versus left MI respectively. Moreover, in terms of both accuracy and speed, the EEG- fTCD BCI with the proposed analysis techniques outperformed all EEG- fNIRS studies in comparison. CONCLUSIONS The proposed system is a more accurate and faster alternative to EEG-fNIRS systems.

Abstract Fractures of particle assemblies happen frequently in dense gas-solid systems leading to a notable heterogeneity in the particle configuration, especially in case of cohesive powders and non-spherical particle interlocking. In this work, we investigate the influence of such heterogeneities on the hydrodynamic drag by studying the idealized case of a random arrangement of spheres with a channel-like void region. More specifically, we introduce this heterogeneity to a homogeneous particle arrangement by shifting apart two bulk regions, such that a void channel divides particle bulk. Single-relaxation-time lattice Boltzmann simulations were performed to resolve fluid flow through such arrested particle configurations and calculate the corresponding gas-particle momentum exchange and pressure drop. The calculated drag forces acting on the solids for random sphere arrangement are in good agreement with previously reported results of Hill et al. (2001b), Tenneti et al. (2011), and Tang et al. (2015). However, the overall momentum exchange obtained for configurations containing a heterogeneity is significantly lower. Obviously, the channel allows for a by-passing of a considerable amount of the flow leading to a reduced overall pressure drop and thereby underestimating the minimum fluidization velocity in a fluidized bed. Based on these direct numerical simulations, we examine the overall pressure drop dependence on the characteristic length scale (i.e. width) of the channel-like heterogeneity L c , the superficial Reynolds number (30  ⩽  Re  ⩽  300), and the solid volume fraction in the dense (i.e. bulk) region (0.4  ⩽ ϕ p ⩽  0.55). The width of the channel is varied within the order of magnitude of particle diameter D p (1 ⩽ L c / D p ⩽ 4.36 ), decreasing an overall solid volume fraction (0.25  ⩽ ϕ ⩽  0.55). In addition to the numerical simulations, we derive (semi)-analytic correlations for the dense bulk region as well as for the channel. As the simulations range from laminar to transitional flow, providing a single pressure drop correlation is very challenging. Therefore, we estimate the channel pressure drop with the appropriate correlations selected according to calculated superficial Reynolds number. For laminar flow, we achieved a good agreement between a combined (i.e. bulk and channel) analytical prediction of overall pressure drop and our resolved numerical simulation. In the transitional regime, the pressure drop values are more difficult to predict, with the better agreement as we approach the turbulent regime. We believe that this work can act as a basis for the development of future drag laws accounting for channel-like sub-grid heterogeneities.