Genomic and Metabolomic Determinants of Neurological and Psychiatric Traits

This thesis aimed to identify genomic and metabolomic determinants of neurological and psychiatric disorders and their related endophenotypes by making use of various omics approaches. Novel insights into the pathophysiology of these disorders are provided by identifying novel genetic determinants underlying brain structures, cognitive ability, and neurodevelopmental disorders. Furthermore, a link between circulating metabolites and neurovascular pathology or gut microbiota is also highlighted

Measurement of Bone Mineral Density in Children with Cerebral Palsy from an Ethical Issue to a Diagnostic Necessity

© 2020 Jasmin S. Nurković et al. Introduction. Due to concerns about cumulative radiation exposure in the pediatric population, it is not standard practice to perform dual-energy X-ray absorptiometry (DXA) analysis in the diagnostic process of musculoskeletal disorders, such as cerebral palsy (CP). This study aimed to evaluate the bone mineral density (BMD) in children with CP and the ethical justification of applying DXA analysis in these children. Material and Methods. In this monocentric retrospective analysis, data were collected from children and adolescents with CP who were treated for a primary illness for three years. A clinical examination, which included a DXA analysis, recommended by the multidisciplinary team, was performed. After applying inclusion and exclusion criteria, 60 scans remained for statistical analysis. BMD and Z-scores for the lumbar spine (LS), and hip right and left femoral neck (RFN and LFN, respectively), and total hip (TH) were recorded. Results. The average age of children with CP when DXA analysis was first performed was about 7 years. The BMD (mean±SD) at LS (LS-BMD) of all patients was 0.612±0.12, at RFN 0.555±0.11, at LFN 0.572±0.1, and at TH (TH-BMD) 0.581±0.13. The values of the Z-score (mean±SD) at LS of all patients were-2.5±0.22, at RFN-2.2±0.21, at LFN-2.25 (SD=0.2), and at TH-2.3 (SD=0.23). There was no statistical significance between age and gender; however, BMI, walking ability, fracture history, and pattern of CP had a significant impact on BMD and Z-score values of these children. Conclusion. The results of our study clearly indicate that children with CP have a higher risk of low BMD, osteoporosis, and bone fractures, which makes it ethically justifiable to perform the DXA analysis in these children

Seroprevalence of Actinobacillus pleuropneumoniae in swine originated from commercial farms in Serbia

Porcine pleuropneumonia caused by Actinobacillus pleuropneumoniae (A.pleuropneumoniae) is one of the most important respiratory diseases of pigs and causes worldwide severe losses in pig farming. For A.pleuropneumoniae control and monitoring, the detection of ApxIV antibodies in the serum is the most frequently used serological method. The aim of this study was to investigate presence of antibodies against A. pleuropneumoniae in blood sera of gilts and sows using the ELISA test. Samples were taken from gilts and sows originating from four commercial swine farms in Serbia. For detection of ApxIV antibodies, commercial ELISA kit was used. A total of 453 blood sera samples of gilts (207) and sows (246) were examined. Antibodies against A. pleuropneumoniae were detected in 57 (12.58%) sera. Antibodies were present in 22 (10.62 %) sera of gilts and in 35(14.22%) sera of sows. Percentage of positive sera differed among the farms, ranging in gilts from 3.33-17.77 % and in sows from 8.95-22.64%. Serological methods is one of the most important procedures in the diagnosis of porcine pleuropneumonia particularly suitable for the control of animal health status in a large breeding

Flood impacts on road transportation using microscopic traffic modelling technique

The research presented in this paper proposes a novel methodology for modelling the impacts of floods on traffic. Often flooding is a complex combination of various causes (coastal, fluvial and pluvial). Further, transportation systems are very sensitive to external disturbances. There is insufficient knowledge on the interactions in these complex and dynamic systems. This paper proposes a methodology for integrating a flood model (MIKE Flood) and a traffic model (SUMO). Traffic on inundated roads will be interrupted or delayed according to the manner of flood propagation. As a consequence, some trips will be cancelled or rerouted and other trips will be indirectly affected. A comparison between the baseline and a flood scenario yields the impacts of that flood on traffic, estimated in terms of lost business hours, additional fuel consumption, and additional CO2 emissions. The outcome suggests that the proposed methodology can help to quantify the flood impact on transportation.Research on the PEARL (Preparing for Extreme And Rare events in coastaL regions) project is funded by the European Commission through Framework Programme 7, Grant Number 603663

Classical String in Curved Backgrounds

The Mathisson-Papapetrou method is originally used for derivation of the particle world line equation from the covariant conservation of its stress-energy tensor. We generalize this method to extended objects, such as a string. Without specifying the type of matter the string is made of, we obtain both the equations of motion and boundary conditions of the string. The world sheet equations turn out to be more general than the familiar minimal surface equations. In particular, they depend on the internal structure of the string. The relevant cases are classified by examining canonical forms of the effective 2-dimensional stress-energy tensor. The case of homogeneously distributed matter with the tension that equals its mass density is shown to define the familiar Nambu-Goto dynamics. The other three cases include physically relevant massive and massless strings, and unphysical tahyonic strings.Comment: 12 pages, REVTeX 4. Added a note and one referenc

Comparison Of 2D Numerical Schemes For Modelling Supercritical And Transcritical Flows Along Urban Floodplains

Urban floodplains usually have irregular geometry due to different obstacles, urban infrastructures and slope conditions. This may change the flow regime from subcritical to supercritical flow conditions, and vice versa. Implementation of the full momentum equation in 2D shallow water equations (SWEs) is not trivial in mixed flow conditions as subcritical and supercritical flows require different boundary conditions and hence different solution algorithms. Some models ignore the convective acceleration term (CAT) to simplify implementation of the momentum equation for mixed flow conditions. This work tried to investigate the effect of neglecting CATs by testing two 2D models which implement - full SWEs and completely reduced CAT. The models\u27 performances were then tested by setting up hypothetical case studies with changing flow regimes. Simulations results were compared to each other by setting the solutions of the method that solve the full equations as a reference. Findings of the numerical tests showed that, in the cases, results of the model which ignore CATs fully were very similar compared to solutions of the model which implement full SWEs. Hence, simplified models which ignore CATs may be used to model urban flood plains without significant loss of accuracy

Multi-Objective-Rehabilitation Of Urban Drainage Systems Within The Flood Risk Framework

Urban drainage systems are one of the most valuable public utilities in any community, which protects public health and the environment, nevertheless is one of the most overlooked infrastructures until considerable failures occurred. If there are not recurrent rehabilitation programs in place this vital infrastructure will decrease the level of service. This work presents an approach to find optimal rehabilitation measures based on the hydraulic performance of the system. To assess the performance of the urban drainage system a coupled 1D-2D model was developed. The model uses SWMM 5.0 for the 1D transport; to simulate the overland flow from the manholes when the capacity of the sewer pipes is exceeded a coupled 1D-2D non inertia model was used. The results are matrices composed of flood water depths and velocities values per each scenario of the flood event. These outputs are the main parameters to assess flood hazard. Furthermore, the vulnerability was assessed based on the socio-economic condition of the residents in the study area, located in a catchment area in Quito, Ecuador. The assessment of hazard and vulnerability were combined to estimate the flood risk damage. Several simulations were made for different flood events (10, 20, 50 and 100 year return period), obtaining Pareto sets per each event. However in order to have more realistic solutions the approach of expected annual flood risk cost were implemented to obtain integrated solutions for a number of flood events. Besides of these new solutions generated, the concept of cost-benefit analysis was applied to help in the identification of the most cost-effective solution. Keywords: Urban drainage systems, flood hazard, vulnerability, flood risk assessment, SWMM5, NSGAII, multi-objective-rehabilitation, genetic algorithms

Water quality and macrophytes in the Danube River: Artificial neural network modelling

This is the author accepted manuscript. The final version is available on from Elsevier via the DOI in this recordEcological assessment of large rivers such as the Danube is a challenging task. Eutrophication was reported as one of the main drivers that structure aquatic communities in the Danube basin. Due to their sedentary nature, relatively slow growth/ long life spans, and engineering role in aquatic ecosystems, macrophytes are widely used in the detection of nutrient enrichment. In this study, macrophyte presence-absence data within the 3 km long reaches obtained from the Joint Danube Survey (JDS3) were used to predict the water quality of the Danube river and its main tributaries. For each water quality variable (dissolved oxygen, nitrate-nitrogen, and orthophosphates), a multi-layer feed-forward artificial neural network model (ANN) was constructed using the macrophytes as explanatory variables. Despite the limited number of samples (123) along the wide trophic gradient of the Danube, the model showed good predictive performances for the main river channel. The highest discrepancy between observed and predicted water quality was obtained for the samples collected in the tributaries or downstream from the tributaries' mouth, where the model predicted better trophic conditions compared to measured ones. From 64 analysed macrophyte species, 28 were selected by sensitivity analysis as key water quality indicators (KIS) for at least one environmental variable. KIS mainly belonged to the eutrophic tolerant submerged or emerged species with broad ecological amplitude, which reflects the significance of the developed model for use on rivers subjected to nutrient pollution. However, the use of the developed predictive model is restricted to the river sections having a water velocity suitable for macrophytes growth. The developed ANN architecture represents the modelling approach which could be applied to other lotic systems and biological quality elements