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Adherence to and completion of tuberculosis (TB) treatment remain problematic in many high-burden countries. 99DOTS is a low-cost digital adherence technology that could increase TB treatment completion. We conducted a pragmatic stepped-wedge cluster-randomized trial including all adults treated for drug-susceptible pulmonary TB at 18 health facilities across Uganda over 8 months (1 December 2018-31 July 2019). Facilities were randomized to switch from routine (control period) to 99DOTS-based (intervention period) TB treatment supervision in consecutive months. Patients were allocated to the control or intervention period based on which facility they attended and their treatment start date. Health facility staff and patients were not blinded to the intervention. The primary outcome was TB treatment completion. Due to the pragmatic nature of the trial, the primary analysis was done according to intention-to-treat (ITT) and per protocol (PP) principles. This trial is registered with the Pan African Clinical Trials Registry (PACTR201808609844917). Of 1,913 eligible patients at the 18 health facilities (1,022 and 891 during the control and intervention periods, respectively), 38.0% were women, mean (SD) age was 39.4 (14.4) years, 46.8% were HIV-infected, and most (91.4%) had newly diagnosed TB. In total, 463 (52.0%) patients were enrolled on 99DOTS during the intervention period. In the ITT analysis, the odds of treatment success were similar in the intervention and control periods (adjusted odds ratio [aOR] 1.04, 95% CI 0.68-1.58, p = 0.87). The odds of treatment success did not increase in the intervention period for either men (aOR 1.24, 95% CI 0.73-2.10) or women (aOR 0.67, 95% CI 0.35-1.29), or for either patients with HIV infection (aOR 1.51, 95% CI 0.81-2.85) or without HIV infection (aOR 0.78, 95% CI 0.46-1.32). In the PP analysis, the 99DOTS-based intervention increased the odds of treatment success (aOR 2.89, 95% CI 1.57-5.33, p = 0.001). The odds of completing the intensive phase of treatment and the odds of not being lost to follow-up were similarly improved in PP but not ITT analyses. Study limitations include the likelihood of selection bias in the PP analysis, inability to verify medication dosing in either arm, and incomplete implementation of some components of the intervention. 99DOTS-based treatment supervision did not improve treatment outcomes in the overall study population. However, similar treatment outcomes were achieved during the control and intervention periods, and those patients enrolled on 99DOTS achieved high treatment completion. 99DOTS-based treatment supervision could be a viable alternative to directly observed therapy for a substantial proportion of patients with TB. Pan-African Clinical Trials Registry (PACTR201808609844917).

\"We encounter digital data processing on a range of platforms and in a multitude of contexts today: in the predictive algorithms of the financial sector, in drones, insurance, and risk management, in smart cities, biometrics, medicine, and more. This fascinating book explores the historical context of the current data-driven paradigm and explains how elusive yet crucial statistical concepts such as outliers, aggregates, and patterns form how we sense and make sense of data. From the 16th century's embodied measurements of the foot, through the blurred facial features of L'Homme Moyen, to the image aggregates of today's security systems, the examples collected in this book illustrate the central role of aesthetics throughout the history of statistical knowledge production. Taking its point of departure in analyses and discussions of contemporary artistic experiments by Rossella Biscotti, Stéphanie Solinas, and Adam Broomberg and Oliver Chanarin, the book broadens our understanding of the structures of knowledge and methods in statistical computation beyond optimistic narratives of calculative power. Venturing out into the tails of the distributions--to the systemically overlooked and excluded--this book challenges us to embrace an alternative view of room of modern data processing\"-- Provided by publisher.

For gait classification, hoof-on and hoof-off events are fundamental locomotion characteristics of interest. These events can be measured with inertial measurement units (IMUs) which measure the acceleration and angular velocity in three directions. The aim of this study was to present two algorithms for automatic detection of hoof-events from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. Seven Warmblood horses were equipped with two wireless IMUs, which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted on a lead over a force plate for internal validation. The agreement between the algorithms for the acceleration and angular velocity signals with the force plate was evaluated by Bland Altman analysis and linear mixed model analysis. These analyses were performed for both hoof-on and hoof-off detection and for both algorithms separately. For the hoof-on detection, the angular velocity algorithm was the most accurate with an accuracy between 2.39 and 12.22 ms and a precision of around 13.80 ms, depending on gait and hoof. For hoof-off detection, the acceleration algorithm was the most accurate with an accuracy of 3.20 ms and precision of 6.39 ms, independent of gait and hoof. These algorithms look highly promising for gait classification purposes although the applicability of these algorithms should be investigated under different circumstances, such as different surfaces and different hoof trimming conditions.

Objectives Eye tracking has been used in medical radiology to understand observers' gaze patterns during radiological diagnosis. This study examines the visual identification ability of junior hospital dental officers (JHDOs) and dental surgery assistants (DSAs) in radiographic and nonradiographic images using eye tracking technology and examines if there is a correlation. Material and methods Nine JHDOs and nine DSAs examined six radiographic images and 16 nonradiographic images using eye tracking. The areas of interest (AOIs) of the radiographic images were rated as easy, medium, and hard, and the nonradiographic images were categorized as pattern recognition, face recognition, and image comparison. The participants were required to identify and locate the AOIs. Data analysis of the two domains, entire slide and AOI, was conducted by evaluating the eye tracking metrics (ETM) and the performance outcomes. ETM consisted of six parameters, and performance outcomes consisted of four parameters. Results No significant differences were observed for ETMs for JHDOs and DSAs for both radiographic and nonradiographic images. The JHDOs showed significantly higher percentage in identifying AOIs than DSAs for all the radiographic images (72.7% vs. 36.4%, p = .004) and for the easy categorization of radiographic AOIs (85.7% vs. 42.9%, p = .012). JHDOs with higher correct identification percentage in face recognition had a shorter dwell time in AOIs. Conclusions Although no significant relation was observed between radiographic and nonradiographic images, there were some evidence that visual recognition skills may impact certain attributes of the visual search pattern in radiographic images.

This book covers a variety of problems, and offers solutions to some, in: Statistical state and parameter estimation in nonlinear stochastic dynamical system in both the classical and quantum scenarios Propagation of electromagnetic waves in a plasma as described by the Boltzmann Kinetic Transport Equation Classical and Quantum General Relativity It will be of use to Engineering undergraduate students interested in analysing the motion of robots subject to random perturbation, and also to research scientists working in Quantum Filtering.

Theories of scientific and technological change view discovery and invention as endogenous processes 1 , 2 , wherein previous accumulated knowledge enables future progress by allowing researchers to, in Newton’s words, ‘stand on the shoulders of giants’ 3 , 4 , 5 , 6 – 7 . Recent decades have witnessed exponential growth in the volume of new scientific and technological knowledge, thereby creating conditions that should be ripe for major advances 8 , 9 . Yet contrary to this view, studies suggest that progress is slowing in several major fields 10 , 11 . Here, we analyse these claims at scale across six decades, using data on 45 million papers and 3.9 million patents from six large-scale datasets, together with a new quantitative metric—the CD index 12 —that characterizes how papers and patents change networks of citations in science and technology. We find that papers and patents are increasingly less likely to break with the past in ways that push science and technology in new directions. This pattern holds universally across fields and is robust across multiple different citation- and text-based metrics 1 , 13 , 14 , 15 , 16 – 17 . Subsequently, we link this decline in disruptiveness to a narrowing in the use of previous knowledge, allowing us to reconcile the patterns we observe with the ‘shoulders of giants’ view. We find that the observed declines are unlikely to be driven by changes in the quality of published science, citation practices or field-specific factors. Overall, our results suggest that slowing rates of disruption may reflect a fundamental shift in the nature of science and technology. A decline in disruptive science and technology over time is reported, representing a substantive shift in science and technology, which is attributed in part to the reliance on a narrower set of existing knowledge.

\"Obtaining reliable models from given data is becoming increasingly important in a wide range of different applications fields including the prediction of energy consumption, complex networks, environmental modelling, biomedicine, bioinformatics, finance, process modelling, image and signal processing, brain-computer interfaces, and others. In data-driven modelling approaches one has witnessed considerable progress in the understanding of estimating flexible nonlinear models, learning and generalization aspects, optimization methods, and structured modelling. One area of high impact both in theory and applications is kernel methods and support vector machines. Optimization problems, learning, and representations of models are key ingredients in these methods. On the other hand, considerable progress has also been made on regularization of parametric models, including methods for compressed sensing and sparsity, where convex optimization plays an important role. At the international workshop ROKS 2013 Leuven, 1 July 8-10, 2013, researchers from diverse fields were meeting on the theory and applications of regularization, optimization, kernels, and support vector machines. At this occasion the present book has been edited as a follow-up to this event, with a variety of invited contributions from presenters and scientific committee members. It is a collection of recent progress and advanced contributions on these topics, addressing methods including ...\"-- Provided by publisher.

Objective To calculate the global warming potential, in carbon dioxide (CO2) equivalent emissions, from a sample of pragmatic randomised controlled trials.Design Retrospective analysis.Data source Internal data held by NIHR Evaluation, Trials and Studies Coordinating Centre.Studies included All eligible pragmatic randomised controlled trials funded by the NIHR Health Technology Assessment programme during 2002 and 2003.Main outcome measure CO2 equivalents for trial activities calculated with standard conversion factors.Results 12 pragmatic randomised controlled trials involving more than 4800 participants and a wide range of technologies were included. The average CO2 emission generated by the trials was 78.4 (range 42.1-112.7) tonnes. This is equivalent to that produced in one year by approximately nine people in the United Kingdom. Commuting to work by the trial team generated the most emissions (average 21 (11.5-35.0) tonnes per trial), followed by study centres’ fuel use (18 (9.3-32.2) tonnes per trial), trial team related travel (15 (2.0-29.0) tonnes per trial), and participant related travel (13 (0-46.7) tonnes per trial).Conclusions CO2 emissions from pragmatic randomised controlled trials are generated in areas where steps could be taken to reduce them. A large proportion of the CO2 emissions come from travel related to various aspects of a trial. The results of this research are likely to underestimate the total CO2 emissions associated with the trials studied, because of the sources of information available. Further research is needed to explore the additional CO2 emissions generated by clinical trials, over and above those generated by routine care. The results from this project will feed into NIHR guidelines that will advise researchers on how to reduce CO2 emissions.