Vagal sensory afferent innervation corresponds to regulation of neurogenic inflammation in the airways. Capsaicin is mostly used for stimulation of sensory nerves that induce pain and inflammatory responses. It can specifically stimulate sensory afferent nerves, inducing neurogenic inflammation in the airways. According the past studies, we have found the right thoracic vagus nerve (RTVN) and right recurrent laryngeal nerve (RRLN); branches of right thoracic vagus trunk (RTVT) mediate different degree of neurogenic inflammation by intraenous injection of capsaicin (300 nmol/ml/kg). In order to investigate the innervation from the RTVN and RRLN of rat tracheobronchi and their involvement in plasma exudation, we injected 3 £gl of capsaicin (10 mg/ml) into RTVT and denervated the RRLN or RTVN and used India ink as tracer dye to label the leaky microvessels. Our observation indicated that injection of capsaicin into the RTVT coud induce obvious plasma exudation in trachea (area density of leaky blood vessels was about 22%), but plasma exudation was significantly decreased after denervation of RRLN. The left upper side of trachea was decreased by 77.6% and the right upper side decreased by 84.5%. This phenomenon was not caused by denervation of RTVN. The results suggest that vagal nerve innervation of upper trachea mostly came from the RLN. Otherwise, capsaicin injection into the RTVT also induced neurogenic inflammation in the larynx. Experimental denervation of both superior and recurrent laryngeal nerves resulted in a decrease of plasma extravasation by 84.98%. Denervation of either RTVN or RRLN also decreased the plasma extravasation in the larynx. The evidence suggest that sensory fibers in the superior laryngeal nerve, recurrent laryngeal nerve, and thoracic vagus nerve might come from the same population of vagal ganglion sensory neurons.

<p>Recurrent neural networks have been used for time-series prediction with good results. In this dissertation recurrent neural networks are compared with time-delayed feed forward networks, feed forward networks and linear regression models on a prediction task. The data used in all experiments is real-world sales data containing two kinds of segments: campaign segments and non-campaign segments. The task is to make predictions of sales under campaigns. It is evaluated if more accurate predictions can be made when only using the campaign segments of the data.</p><p>Throughout the entire project a knowledge discovery process, identified in the literature has been used to give a structured work-process. The results show that the recurrent network is not better than the other evaluated algorithms, in fact, the time-delayed feed forward neural network showed to give the best predictions. The results also show that more accurate predictions could be made when only using information from campaign segments.</p>

Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies missing covariates in recurrent event data, and discusses ways to include the survival outcomes in the imputation model. Some MI methods under consideration are the event indicator D combined with, respectively, the right-censored event times T, the logarithm of T and the cumulative baseline hazard H0(T). After imputation, we can then proceed to the complete data analysis. The Cox proportional hazards (PH) model and the PWP model are chosen as the analysis models, and the coefficient estimates are of substantive interest. A Monte Carlo simulation study is conducted to compare different MI methods, the relative bias and mean square error will be used in the evaluation process. Furthermore, an empirical study based on cardiovascular disease event data which contains missing values will be conducted. Overall, the results show that MI based on the Nelson-Aalen estimate of H0(T) is preferred in most circumstances.

Σήμερα η μελέτη των τεχνητών νευρωνικών δικτύων είναι ένα ώριμο επιστημονικό πεδίο. Τα πρώτα μοντέλα νευρωνικών δικτύων έκαναν την εμφάνιση τους την δεκαετία 1940 έως 1950, ξεκινώντας από το βασικό μοντέλο του νευρώνα του Mc Culloch-Pitls και τον πρώτο αλγόριθμο εκπαίδευσης ενός νευρώνα, τον γνωστό Perceptron του Frank Rosenblatt. Σήμερα υπάρχουν πληθώρα νευρωνικών μοντέλων που ακολουθούν διάφορα πρότυπα μάθησης όπως εκπαίδευση με εποπτεία (επίβλεψη) εκπαίδευση χωρίς εποπτεία κ.α. Η εργασία αυτή αποτελείται από 6 κεφάλαια ξεκινώντας από τις βασικές έννοιες των τεχνητών νευρωνικών δικτύων και συνεχίζοντας μέχρι την ανάλυση των ανατροφοδοτούμενων νευρωνικών δικτύων καθώς και την χρήση τους στον έλεγχο συστημάτων παρουσιάζοντας και διάφορες εφαρμογές τους. Στο πρώτο εισαγωγικό κεφάλαιο αναφέρουμε τις βασικές αρχές των τεχνητών νευρωνικών δικτύων και την αντιστοιχία τους με τον φυσικό νευρώνα του ανθρώπου. Παραθέτουμε επίσης μια σύντομη ιστορική αναδρομή Στην συνέχεια στο κεφάλαιο 2 ασχολούμαστε με τα ανατροφοδοτούμενα νευρωνικά δίκτυα. Δίνεται ένας ορισμός τον ανατροφοδοτούμενων νευρωνικών δικτύων (recurrent neural networks RNN) και αναφέρονται τα κυριότερα και δημοφιλέστερα είδη αυτών. Δίνοντας μια σύντομη ανάλυση της λειτουργίας τους. Το τρίτο κεφάλαιο ασχολείται με την εκπαίδευση των νευρωνικών δικτύων και τους διάφορους αλγόριθμους εκπαίδευσης. Ξεκινώντας από τον αλγόριθμο εκπαίδευσης του πιο απλού νευρωνικού δικτύου του Perceptron και καταλήγοντας στον αλγόριθμο Back-Propagation. Το τέταρτο κεφάλαιο αναφέρεται στον έλεγχο συστημάτων και την χρήση των νευρωνικών και ανατροφοδοτούμενων νευρωνικών δικτύων σε αυτόν. Αναλύονται οι διάφορες μοντελοποιήσεις καθώς και οι δομές ελέγχου (υπό επίβλεψη , αντίστροφος έλεγχος, προσαρμοστικός γραμμικός έλεγχος κ.α.) Στα δύο τελευταία κεφάλαια παραθέτουμε ένα παράδειγμα χρήσης ενός απλού ανατροφοδοτούμενου νευρωνικού δικτύου (simple recurrent network SRN) στον έλεγχο και τέλος εφαρμογές των νευρωνικών δικτύων σε διάφορους τομείς. / -

In this thesis we will consider divisibility properties of some recurrent sequences, Newman polynomials and computer calculations in those and related questions of number theory. / Čia nagrinėsime rekurenčiųjų sekų dalumo savybes, Niumano polinomus ir kompiuterių panaudojimąatliekant įvairius skaičiavimus, susijusius su minėtais skaičių teorijos klausimais.

Šioje disertacijoje bus nagrinėjamos rekurenčiųjų sekų dalumo savybės, Niumano polinomai ir kompiuterių panaudojimas atliekant įvairius matematinius skaiciavimus, susijusius su minėtais skaičių teorijos klausimais. / In this thesis we will consider divisibility properties of some recurrent sequences, Newman polynomials and computer calculations in those and related questions of number theory.

Recurrent data are widely encountered in many applications. This thesis work focuses on how the recurrent hospital admissions relate to the air pollutants. In particular, we consider the data for two major cities in Saskatchewan. The study period ranges from January 1, 2005 to December 30, 2011 and involves 20,284 patients aged 40 years and older. The hospital admission data is from the Canadian Institute for Health Information (CIHI). The air pollutants data is from the National Air Pollution Surveillance Program (NAPS) from Environment Canada. The data set has been approved by the Biomedical Research Ethics Board, University of Saskatchewan. The gaseous pollutants included in this study are carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), as well as particulate matter PM2:5 (tiny particles in the air that are 2:5 microns in width). In the data analysis, we applied three different existing models to all respiratory diseases and asthma, respectively. The three models are the Poisson process model (also called Andersen-Gill model), the Poisson process model with the number of previous events as a covariate and the Poisson process model with shared gamma distributed frailties (random effects). For all respiratory diseases, the Poisson process model with random effects provides the best t in comparison to the other two models. The model output suggests that the increased risk of hospital readmission is significantly associated with increased CO and O3. For asthma, the Poisson process model provides the best t in comparison to the other two models. We found that only CO and O3 have significant effects on recurrent hospital admissions due to asthma. We concluded this thesis with the discussion on the current and potential future work.

<p>The effectiveness of foreign aid in bringing economic and social development is mired in controversy. However, despite the controversial debates on its effectiveness, poor countries of the world have been receiving and using aid as a leverage to relieve themselves from development constraints they faced. Ethiopia is no exception amongst developing countries. Since the time it joined the World Bank group in 1945, foreign capital inflow has remained an important source of revenue for the government. This paper examines the fiscal impact of aid inflow into Ethiopia using time series data for the period 1975-2005. The empirical findings reveal that inflow of foreign aid influences public decision on revenue and expenditure patterns. The result shows that a larger proportion of aid is allocated to capital expenditure and that only a small proportion goes to recurrent expenditure. There is a strong positive association between aid inflow and capital expenditure. The finding also shows that, while a very weak negative association exists between aid and taxation effort, aid and borrowing are used as alternative source of finance.</p>

The aim of this study was to establish the factors associated with sports injuries among first division Rwandan female soccer players. Conclusion: Advocacy about the safety and improvement of Rwandan female soccer through workshops and trainings involving players, coaches and team owners need to be emphasised.

Fusarium graminearum, the causative agent of Fusarium head blight, is an economically important pathogen of wheat (Triticum aestivum). Breeding Fusarium head blight (FHB) resistant wheat requires knowledge of the underlying genetic control of FHB resistance. Genetic parameters for FHB resistance and five related traits were estimated in three populations at two locations and in two years. Moderate broad sense heritabilities for FHB severity and Fusarium damaged kernels (FDK) were observed. Incidence of FHB and the toxin deoxynivalenol (DON) accumulation had low to moderate broad sense heritabilities. Correlations between FDK and severity and FDK and DON were moderate to high in the three populations and do support indirect selection for FHB severity or DON based on FDK data alone, but it is important to be cautious in years with a high disease pressure when FHB resistance could be masked. A cycle of among-family and within-family selection cycle was conducted in 2003. Actual selection gain was higher than predicted gain based on variance components in 2003 in the within-family selection study. One population had also a strong response for low DON in the among-family selection study. The observed results suggest that selection for FHB resistant genotypes could be achieved with a recurrent selection scheme. Along with conventional breeding, molecular techniques are being used in breeding for FHB resistance. A first genotypic screening of the three populations showed Population 2 had the presence of a resistance allele form the resistant Chinese cultivar Sumai 3. Although Populations 1 and 3 did not have the resistance allele, the results suggest other sources of resistance might be present in these two populations.