Risk factors for equine fractures in Thoroughbred flat racing in North America

The aim of this paper is to identify risk factors associated with equine fractures in flat horse racing of Thoroughbreds in North America. Equine fractures were defined as any fracture sustained by a horse during a race. This was a cohort study that made use of all starts from the racecourses reporting injuries. The analysis was based on 2,201,152 racing starts that represent 91% of all official racing starts in the USA and Canada from 1 st January 2009–31 st December 2014. Approximately 3,990,000 workout starts made by the 171,523 Thoroughbreds that raced during that period were also included in the analysis. During this period the incidence of equine fractures was 2 per 1000 starts. The final multivariable logistic regression models identified risk factors significantly associated (p < 0.05) with equine fracture. For example, horses were found to have a 32% higher chance of sustaining a fracture when racing on a dirt surface compared to a synthetic surface; a 35% higher chance if they had sustained a previous injury during racing and a 47% higher chance was also found for stallions compared to mares and geldings. Furthermore, logistic regression models based on data available only from the period 2009–2013 were used to predict the probability of a Thoroughbred sustaining a fracture for 2014. The 5% of starts that had the highest score in our predictive models for 2014 were found to have 2.4 times (95% CI: 1.9–2.9) higher fracture prevalence than the mean fracture prevalence of 2014. The results of this study can be used to identify horses at higher risk on entering a race and could help inform the design and implementation of preventive measures aimed at minimising the number of Thoroughbreds sustaining fractures during racing in North America

An investigation of equine injuries in Thoroughbred flat racing in North America

The aim of this research work was to investigate and quantify the risk of fatal and fracture injury for Thoroughbreds participating in flat racing in the US and Canada so that horses at particular risk can be identified and the risk of fatal injury reduced. Risk factors associated with fatalities and fractures were identified and predictive models for both fatalities and fractures were developed and their performance was evaluated. Our analysis was based on 188,269 Thoroughbreds that raced on 89 racecourses reporting injuries to the Equine Injury Database (EID) in the US and Canada from 1st January 2009 to 31st December 2015. This included 2,493,957 race starts and 4,592,162 exercise starts. The race starts reported to the EID represented the starts for 90.0% of all official Thoroughbred racing events in the United States and Canada during the 7-year observation period. The annual average risk of fatal and fracture equine injuries for the period 2009 - 2015 was estimated and a description of the different injury types that resulted in fatalities and fractures was given, based on the cases recorded in the EID. Possible risk factors were pre-screened using univariable logistic regression models; risk factors with an association indicated by p < 0.20 were then included in a stepwise logistic regression selection process. A forward bidirectional elimination approach using Akaike's Information Criterion was utilised for the stepwise selection. We identified more than 20 risk factors that were found to be significantly associated with fatal injury (p < 0.05) and more than 20 risk factors associated with fracture injury, across the final multi-variable models. The risk factors identified are related to the horse’s previous racing history, the trainer, the race, the horse's expected performance and the horse's racing history. Five different algorithms were used to develop predictive models based on the data available from the period 2009 - 2014 for both fatal and fracture injuries. Firstly, we used Multivariable Logistic Regression, commonly used in risk factor analysis. Secondly, Improved Balanced Random Forests were developed, a machine learning algorithm based on a modification of the random forests algorithm. Because fatal injuries are extremely rare events, less than 2 instances per 1000 starts on average, balanced samples were used to develop the Random Forest model to deal with the class-imbalance problem. Furthermore, we trained an Artificial Neural Network with a single layer and two networks with deep architecture, a Deep Belief Network and a Stacked Denoising Autoencoder. As artificial neural networks and deep learning models have been successfully used to solve complex problems in a diverse field of domains we wanted to explore the possibility of using them to successfully predict equine injuries. The performance of each classifier was evaluated by calculating the Area Under the Receiver Operating Characteristic Curve (AUC), using the data available from 2015 for validation. AUC results ranged from 0.62 to 0.64 for the best performing algorithm and similar predictive results were obtained from the wide array of different models created. This is the first study to make use of the extensive information contained in the EID to identify risk factors associated with equine fatal and fracture injuries in the US and Canada for this period. To our knowledge, this is the largest retrospective observational study investigating the risk of equine fatal and fracture injuries during flat racing in the literature. This is also the first study to train logistic regression and machine learning models to predict equine injuries using such an extensive amount of data and a full year of horse racing events for prediction and evaluation. We believe the results could help identify horses at high risk of (fatal) injury on entering a race and inform the design and implementation of preventive measures aimed at minimising the number of Thoroughbreds sustaining fatal injuries during racing in North America

Mathematical Studies of Photochemical Air Pollution

In Part I a new, comprehensive model for a chemically reacting plume, is presented, that accounts for the effects of incomplete turbulent macro- and micro- mixing on chemical reactions between plume and ambient constituents. This "Turbulent Reacting Plume Model" (TRPM) is modular in nature, allowing for the use of different levels of approximation of the phenomena involved. The core of the model consists of the evolution equations for reaction progress variables appropriate for evolving, spatially varying systems ("local phenomenal extent of reaction"). These equations estimate the interaction of mixing and chemical reaction and require input parameters characterizing internal plume behavior, such as relative dispersion and fine scale plume segregation. The model addresses deficiencies in previous reactive plume models. Calculations performed with the TRPM are compared with the experimental data of P.J.H. Builtjes for the reaction between NO in a point source plume and ambient O3, taking place in a wind tunnel simulating a neutral atmospheric boundary layer. The comparison shows the TRPM capable of quantitatively predicting the retardation imposed on the evolution of nonlinear plume chemistry by incomplete mixing. Part IA (Chapters 1 to 3) contains a detailed description of the TRPM structure and comparisons of calculations with measurements, as well as a literature survey of reactive plume models. Part IB (Chapters 4 to 7) contains studies on the turbulent dispersion and reaction phenomena and plume dynamics, thus exposing in detail the underlying concepts and methods relevant to turbulent reactive plume modeling. New formulations for describing in-plume phenomena, such as the "Localized Production of Fluctuations Model" for the calculation of the plume concentration variance are included here. Part II (Chapter 8) presents a collection of distribution-based statistical methods that are appropriate for characterizing extreme events in air pollution studies. Applications to the evaluation of air quality standards, formulation of rollback calculations, and to the use of plume models are included here.</p

Investigating the Potential of the Inter-IXP Multigraph for the Provisioning of Guaranteed End-to-End Services

In this work, we propose utilizing the rich connectivity between IXPs and ISPs for inter-domain path stitching, supervised by centralized QoS brokers. In this context, we highlight a novel abstraction of the Internet topology, i.e., the inter-IXP multigraph composed of IXPs and paths crossing the domains of their shared member ISPs. This can potentially serve as a dense Internet-wide substrate for provisioning guaranteed end-to-end (e2e) services with high path diversity and global IPv4 address space reach. We thus map the IXP multigraph, evaluate its potential, and introduce a rich algorithmic framework for path stitching on such graph structures.Comment: Proceedings of ACM SIGMETRICS '15, pages 429-430, 1/1/2015. arXiv admin note: text overlap with arXiv:1611.0264

Cache as a service:leveraging SDN to efficiently and transparently support Video-on-Demand on the last mile

High quality online video streaming, both live and on-demand, has become an essential part of consumers’ every-day lives. The popularity of video streaming as placed a heavy burden on the network infrastructure that now has to transfer an enormous amount of data very quickly to the end-user. To further exacerbate the situation, the Video-on-Demand (VoD) distribution paradigm uses a unicast independent flow for each user request. This results in multiple duplicate flows carrying the same video assets many times end-to-end. We present OpenCache: a highly configurable, efficient and transparent in-network caching service that aims to improve the VoD distribution efficiency by caching video assets as close to the end-user as possible. OpenCache leverages Software Defined Networking to benefit last mile environments by improving network utilisation and increasing the Quality of Experience for the end-user. Our evaluation on a pan-European OpenFlow testbed uses adaptive video streaming and demonstrates that with the use of OpenCache, the external link utilisation is reduced by 100%. Furthermore the streaming application receives better quality video and observes higher throughput, lower latency and shorter start up and buffering times

5G networks with IoT and analysis of two economic sectors

Αντικείμενο της παρούσας εργασία είναι μια παρουσίαση εφαρμογών των δικτύων κινητής επικοινωνίας 5ης γενιάς σε συνδυασμό με την τεχνολογία του Διαδικτύου των Πραγμάτων στον τομέα του πολιτισμού και της αυτόνομης οδήγησης. Για τις ανάγκες της παρούσης βιβλιογραφικής μελέτης πραγματοποιήθηκε εκτεταμένη αναζήτηση εργασιών και επιστημονικών δημοσιεύσεων στον τομέα των δύο αυτών τεχνολογιών της εποχής μας με ιδιαίτερη έμφαση στις δημοσιεύσεις των τελευταίων δύο ετών. Στα κεφάλαια 1 και 2 παρουδικτύων 5ης γενιάς σε συνδυασμό με το Διαδικτύου των Πραγμάτων στον τομέα του πολιτισμού και των έξυπνων δικτύων ηλεκτρικών ενέργειας . Στο κεφάλαιο 4 παρουσιάζεται συνοσιάζεται μια κατά το δυνατόν περιεκτική παρουσίαση των δικτύων κινητής επικοινωνίας 5ης γενιάς και του Διαδικτύου των Πραγμάτων δίνοντας έμφαση σε μια όσο γίνεται κατανοητή και περιγραφική παρουσίαση των δύο αυτών τεχνολογιών. Στο κεφάλαιο 3 παρουσιάζονται μερικές από τις τελευταίες εφαρμογές των πτικά η τεχνολογία της αυτόνομης οδήγησης καθώς και κάποια απτά παραδείγματα της βιομηχανίας αυτοκινήτων που εφαρμόζει ήδη αυτή την τεχνολογία.The purpose of this study is to present the applications of 5th generation mobile communication networks (known as 5G) in combination with Internet of Things technology in the field of culture and autonomous driving. For the purposes of this bibliographic study, an extensive research was made for papers and scientific publications in the field of the two technologies of our time, with particular emphasis on the publications of the last two years. Chapters 1 and 2 present a more comprehensive presentation of 5G and IoT, with a focus on a as much as possible comprehensible and descriptive presentation of these two technologies. Chapter 3 presents some of the latest applications of 5G networks in conjunction with IoT in the field of culture and smart electricity grids. Chapter 4 gives a brief overview of autonomous driving technology as well as some specific examples of the automotive industry already applying this technology

Preliminary diagnostic reference levels for endoscopic retrograde cholangio-pancreatography in Greece

The main objective of this study was to determine the preliminary Diagnostic Reference Levels (DRLs) in terms of Kerma Area Product (KAP) and fluoroscopy time (Tf) during Endoscopic Retrograde Cholangio-Pancreatography (ERCP) procedures. Additionally, an investigation was conducted to explore the statistical relation between KAP and Tf. Data from a set of 200 randomly selected patients treated in 4 large hospitals in Greece (50 patients per hospital) were analyzed in order to obtain preliminary DRLs for KAP and Tf during therapeutic ERCP procedures. Non-parametric statistic tests were performed in order to determine a statistically significant relation between KAP and Tf. The resulting third quartiles for KAP and Tf for hospitals (A, B, C and D) were found as followed: KAPA = 10.7 Gy cm^2, TfA = 4.9 min; KAPB = 7.5 Gy cm^2, TfB = 5.0 min; KAPC = 19.0 Gy cm^2, TfC = 7.3 min; KAPD = 52.4 Gy cm^2, TfD = 15.8 min. The third quartiles, calculated for the total 200 cases sample, are: KAP = 18.8 Gy cm^2 and Tf = 8.2 min. For 3 out of 4 hospitals and for the total sample, p-values of statistical indices (correlation of KAP and Tf) are less than 0.001, while for the Hospital A p-values are ranging from 0.07 to 0.08. Using curve fitting, we finally determine that the relation of Tf and KAP is deriving from a power equation (KAP = Tf^1.282) with R^2 = 0.85. The suggested Preliminary DRLs (deriving from the third quartiles of the total sample) for Greece are: KAP = 19 Gy cm^2 and Tf = 8 min, while the relation between KAP and Tf is efficiently described by a power equatio