Distributed Lag Linear and Non-Linear Models in R: The Package dlnm

Distributed lag non-linear models (DLNMs) represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data. This methodology rests on the definition of a crossbasis , a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm, which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper offers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.

Reducing and meta-analysing estimates from distributed lag non-linear models.

BACKGROUND: The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for investigating simultaneously non-linear and lagged relationships, and multivariate meta-analysis, a methodology to pool estimates of multi-parameter associations. However, the application of both methods in two-stage analyses is prevented by the high-dimensional definition of DLNMs. METHODS: In this contribution we propose a method to synthesize DLNMs to simpler summaries, expressed by a reduced set of parameters of one-dimensional functions, which are compatible with current multivariate meta-analytical techniques. The methodology and modelling framework are implemented in R through the packages dlnm and mvmeta. RESULTS: As an illustrative application, the method is adopted for the two-stage time series analysis of temperature-mortality associations using data from 10 regions in England and Wales. R code and data are available as supplementary online material. DISCUSSION AND CONCLUSIONS: The methodology proposed here extends the use of DLNMs in two-stage analyses, obtaining meta-analytical estimates of easily interpretable summaries from complex non-linear and delayed associations. The approach relaxes the assumptions and avoids simplifications required by simpler modelling approaches

Distributed Lag Linear and Non-Linear Models in R: The Package dlnm.

: Distributed lag non-linear models (DLNMs) represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data. This methodology rests on the definition of a crossbasis, a bi-dimensional functional space expressed by the combination of two sets of basis functions, which specify the relationships in the dimensions of predictor and lags, respectively. This framework is implemented in the R package dlnm, which provides functions to perform the broad range of models within the DLNM family and then to help interpret the results, with an emphasis on graphical representation. This paper offers an overview of the capabilities of the package, describing the conceptual and practical steps to specify and interpret DLNMs with an example of application to real data.<br/

Experimental analysis of radiation induced corrosion of copper canisters designed for KBS-3, a final repository for spent nuclear fuel

Radiation induced corrosion of copper is a crucial process that occurr on the copper surface of KBS -3 canisters. This work presents an experimental analysis of the consequences of corrosion induced by gamma radiation and H2O2 exposure. The materials investigated are : copper powder, copper (I) and (II) oxides powder and copper cube samples cut from a KBS-3 canister wallopenEmbargo per motivi editorial

Modeling exposure-lag-response associations with distributed lag non-linear models.

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure-lag-response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others

Cervical esophagotomy for removal of an ingested clam shell: a very uncommon foreign body ingestion

OBJECTIVE: To report the removal of an ingested clam shell that was firmly impacted in the esophagus. CLINICAL PRESENTATION AND INTERVENTION: A 77-year-old man presented at our hospital with acute dysphagia after eating a seafood risotto. An urgent dedicated examination (noncontrast helical multislice computed tomography scan of the neck and flexible esophagoscopy) detected a clam shell lodged in the upper esophagus. After several unsuccessful endoscopic attempts, a lifesaving cervical esophagotomy was performed and the foreign body was retrieved. CONCLUSION: This patient who ingested clam shell recovered well following the retrieval of the foreign body by performing a lifesaving cervical esophagotomy

Activity monitoring and behaviour analysis using RGB-depth sensors and wearable devices for ambient assisted living applications

Nei paesi sviluppati, la percentuale delle persone anziane è in costante crescita. Questa condizione è dovuta ai risultati raggiunti nel capo medico e nel miglioramento della qualità della vita. Con l'avanzare dell'età, le persone sono più soggette a malattie correlate con l'invecchiamento. Esse sono classificabili in tre gruppi: fisiche, sensoriali e mentali. Come diretta conseguenza dell'aumento della popolazione anziana ci sarà quindi una crescita dei costi nel sistema sanitario, che dovrà essere affrontata dalla UE nei prossimi anni. Una possibile soluzione a questa sfida è l'utilizzo della tecnologia. Questo concetto è chiamato Ambient Assisted living (AAL) e copre diverse aree quali ad esempio il supporto alla mobilità, la cura delle persone, la privacy, la sicurezza e le interazioni sociali. In questa tesi differenti sensori saranno utilizzati per mostrare, attraverso diverse applicazioni, le potenzialità della tecnologia nel contesto dell'AAL. In particolare verranno utilizzate le telecamere RGB-profondità e sensori indossabili. La prima applicazione sfrutta una telecamera di profondità per monitorare la distanza sensore-persona al fine di individuare possibili cadute. Un'implementazione alternativa usa l'informazione di profondità sincronizzata con l'accelerazione fornita da un dispositivo indossabile per classificare le attività realizzate dalla persona in due gruppi: Activity Daily Living e cadute. Al fine di valutare il fattore di rischio caduta negli anziani, la seconda applicazione usa la stessa configurazione descritta in precedenza per misurare i parametri cinematici del corpo durante un test clinico chiamato Timed Up and Go. Infine, la terza applicazione monitora i movimenti della persona durante il pasto per valutare se il soggetto sta seguendo una dieta corretta. L'informazione di profondità viene sfruttata per riconoscere particolari azioni mentre quella RGB per classificare oggetti di interesse come bicchieri o piatti presenti sul tavolo.Nowadays, in the developed countries, the percentage of the elderly is growing. This situation is a consequence of improvements in people's quality life and developments in the medical field. Because of ageing, people have higher probability to be affected by age-related diseases classified in three main groups physical, perceptual and mental. Therefore, the direct consequence is a growing of healthcare system costs and a not negligible financial sustainability issue which the EU will have to face in the next years. One possible solution to tackle this challenge is exploiting the advantages provided by the technology. This paradigm is called Ambient Assisted Living (AAL) and concerns different areas, such as mobility support, health and care, privacy and security, social environment and communication. In this thesis, two different type of sensors will be used to show the potentialities of the technology in the AAL scenario. RGB-Depth cameras and wearable devices will be studied to design affordable solutions. The first one is a fall detection system that uses the distance information between the target and the camera to monitor people inside the covered area. The application will trigger an alarm when recognizes a fall. An alternative implementation of the same solution synchronizes the information provided by a depth camera and a wearable device to classify the activities performed by the user in two groups: Activity Daily Living and fall. In order to assess the fall risk in the elderly, the second proposed application uses the previous sensors configuration to measure kinematic parameters of the body during a specific assessment test called Timed Up and Go. Finally, the third application monitor's the user's movements during an intake activity. Especially, the drinking gesture can be recognized by the system using the depth information to track the hand movements whereas the RGB stream is exploited to classify important objects placed on a table

Analysis of the Spectral Energy Distributions of Fermi bright blazars

Blazars are a small fraction of all extragalactic sources but, unlike other objects, they are strong emitters across the entire electromagnetic spectrum. In this study we have conducted a detailed investigation of the broad-band spectral properties of the gamma-ray selected blazars of the Fermi-LAT Bright AGN Sample (LBAS). By combining the accurately estimated Fermi gamma-ray spectra with Swift, radio, NIR-Optical and hard-X/gamma-ray data, collected within three months of the LBAS data taking period, we were able to assemble high-quality and quasi-simultaneous Spectral Energy Distributions (SED) for 48 LBAS blazars.Comment: 6 pages, 8 figures, "2009 Fermi Symposium", "eConf Proceedings C091122