45,386 research outputs found
Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders
We propose an approach to estimate the effect of multiple simultaneous
interventions in the presence of hidden confounders. To overcome the problem of
hidden confounding, we consider the setting where we have access to not only
the observational data but also sets of single-variable interventions in which
each of the treatment variables is intervened on separately. We prove
identifiability under the assumption that the data is generated from a
nonlinear continuous structural causal model with additive Gaussian noise. In
addition, we propose a simple parameter estimation method by pooling all the
data from different regimes and jointly maximizing the combined likelihood. We
also conduct comprehensive experiments to verify the identifiability result as
well as to compare the performance of our approach against a baseline on both
synthetic and real-world data.Comment: Accepted to The Conference on Uncertainty in Artificial Intelligence
(UAI) 202
Systems approaches and algorithms for discovery of combinatorial therapies
Effective therapy of complex diseases requires control of highly non-linear
complex networks that remain incompletely characterized. In particular, drug
intervention can be seen as control of signaling in cellular networks.
Identification of control parameters presents an extreme challenge due to the
combinatorial explosion of control possibilities in combination therapy and to
the incomplete knowledge of the systems biology of cells. In this review paper
we describe the main current and proposed approaches to the design of
combinatorial therapies, including the empirical methods used now by clinicians
and alternative approaches suggested recently by several authors. New
approaches for designing combinations arising from systems biology are
described. We discuss in special detail the design of algorithms that identify
optimal control parameters in cellular networks based on a quantitative
characterization of control landscapes, maximizing utilization of incomplete
knowledge of the state and structure of intracellular networks. The use of new
technology for high-throughput measurements is key to these new approaches to
combination therapy and essential for the characterization of control
landscapes and implementation of the algorithms. Combinatorial optimization in
medical therapy is also compared with the combinatorial optimization of
engineering and materials science and similarities and differences are
delineated.Comment: 25 page
Systematic techniques for assisting recruitment to trials (START): study protocol for embedded, randomized controlled trials
BACKGROUND: Randomized controlled trials play a central role in evidence-based practice, but recruitment of participants, and retention of them once in the trial, is challenging. Moreover, there is a dearth of evidence that research teams can use to inform the development of their recruitment and retention strategies. As with other healthcare initiatives, the fairest test of the effectiveness of a recruitment strategy is a trial comparing alternatives, which for recruitment would mean embedding a recruitment trial within an ongoing host trial. Systematic reviews indicate that such studies are rare. Embedded trials are largely delivered in an ad hoc way, with interventions almost always developed in isolation and tested in the context of a single host trial, limiting their ability to contribute to a body of evidence with regard to a single recruitment intervention and to researchers working in different contexts. METHODS/DESIGN: The Systematic Techniques for Assisting Recruitment to Trials (START) program is funded by the United Kingdom Medical Research Council (MRC) Methodology Research Programme to support the routine adoption of embedded trials to test standardized recruitment interventions across ongoing host trials. To achieve this aim, the program involves three interrelated work packages: (1) methodology - to develop guidelines for the design, analysis and reporting of embedded recruitment studies; (2) interventions - to develop effective and useful recruitment interventions; and (3) implementation - to recruit host trials and test interventions through embedded studies. DISCUSSION: Successful completion of the START program will provide a model for a platform for the wider trials community to use to evaluate recruitment interventions or, potentially, other types of intervention linked to trial conduct. It will also increase the evidence base for two types of recruitment intervention. TRIAL REGISTRATION: The START protocol covers the methodology for embedded trials. Each embedded trial is registered separately or as a substudy of the host trial
Dynamic investigation on the Mirandola bell tower in post-earthquake scenarios
After the seismic events of the 20th and 29th of May 2012 in Emilia (Italy), most of the monumental and historic buildings of the area were severely damaged. In a few structures, partial collapse mechanisms were observed (e.g. façade tilting, out-of-plane overturning of panels…). This paper presents the case-study of the bell tower of the Santa Maria Maggiore cathedral, located in Mirandola (Italy). The dynamic response of the structure was evaluated through operational modal analysis using ambient vibrations, a consolidated non-destructive procedure that estimates the dynamic parameters of the bell-tower. The dynamic tests were carried out in pre-intervention and post-intervention conditions in order to understand the sensitivity of dynamic measurements to safety interventions. Furthermore, a comparative study is made with similar cases of undamaged masonry towers up to the 6th mode. Finally, an investigation on the state of connections and of the building itself is carried out via FE model updating
Control of stochastic and induced switching in biophysical networks
Noise caused by fluctuations at the molecular level is a fundamental part of
intracellular processes. While the response of biological systems to noise has
been studied extensively, there has been limited understanding of how to
exploit it to induce a desired cell state. Here we present a scalable,
quantitative method based on the Freidlin-Wentzell action to predict and
control noise-induced switching between different states in genetic networks
that, conveniently, can also control transitions between stable states in the
absence of noise. We apply this methodology to models of cell differentiation
and show how predicted manipulations of tunable factors can induce lineage
changes, and further utilize it to identify new candidate strategies for cancer
therapy in a cell death pathway model. This framework offers a systems approach
to identifying the key factors for rationally manipulating biophysical
dynamics, and should also find use in controlling other classes of noisy
complex networks.Comment: A ready-to-use code package implementing the method described here is
available from the authors upon reques
Eat, Sleep, Console for Neonatal Abstinence Syndrome Babies
Neonatal Abstinence Syndrome (NAS) is a complex disorder that manifests with neurologic, gastrointestinal, and musculoskeletal disturbances and is most often associated with opioid withdrawal. In the US, 6 out of 1,000 babies are born to mothers who used opioids during their pregnancy. These babies go on to develop NAS. Androscoggin County, where Central Maine Medical Center is located, has an even higher rate of babies with NAS: 100 out of 1,000. Most institutions use the Finnegan Neonatal Abstinence Scoring System (FNASS) to guide pharmacologic treatment. This system assigns a score based on 21 clinical signs of withdrawal with a score ≥8 indicating a need for pharmacologic treatment. This system has never been validated nor has its score cutoffs been tested which may lead to over or under treatment of babies experiencing NAS. Eat, Sleep, Console is a novel approach which has shown to decrease average length of stay, pharmacologic treatment, and healthcare costs.https://scholarworks.uvm.edu/fmclerk/1503/thumbnail.jp
Life Monza: project description and actions’ updating
The introduction of Low Emission Zones, urban areas subject to road traffic restrictions in order to ensure compliance with the air pollutants limit values set by the European Directive on ambient air quality (2008/50/EC), is a common and well-established action in the administrative government of cities. The impacts on air quality improvement are widely analysed, whereas the effects and benefits concerning the noise have not been addressed in a comprehensive manner. As a consequence, the definition, the criteria for the analysis and the management methods of a Noise Low Emission Zone are not clearly expressed and shared yet. The LIFE MONZA project (Methodologies fOr Noise low emission Zones introduction And management - LIFE15 ENV/IT/000586) addresses these issues. The first objective of the project, co-funded by the European Commission, is to introduce an easy-replicable method for the identification and the management of the Noise Low Emission Zone, an urban area subject to traffic restrictions, whose impacts and benefits regarding noise issues will be analyzed and tested in the pilot area of the city of Monza, located in Northern Italy. Background conditions, structure, objectives of the project and actions’ progress will be discussed in this article
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Sustainable assessment of structures and materials using ground penetrating radar (GPR)
Ground penetrating radar (GPR) is a non-destructive, non-invasive device that can be used to investigate materials in buildings, structures and the ground. Its use relies on recording the reflections of radar waves that are transmitted into materials. This paper provides an overview of GPR, a brief explanation of its principles of operation and application, suggests areas where its use may be appropriate in the context of buildings and structures, and includes some case studies from engineering investigations conducted by the author to highlight examples of the information it can provide. The technical information that GPR can commonly provide includes material depths and thicknesses, locations of excessive moisture or deterioration, and the location of steelwork within construction materials. Whilst reducing uncertainty in data obtained from building and structural investigations, other advantages compared to alternative intrusive investigations include less time and costs for investigations, less disruption to users of the building / structure, and less material required for subsequent repair and maintenance work. This paper also highlights, however, some limitations of the technique which should be considered in order to optimise the success of GPR investigations, such as the necessity for specialist knowledge in operation and data interpretation, and the limited GPR signal penetration within certain materials. Overall, the potential for use of GPR in the determination of material and structural properties in the built environment is highlighted
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