Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning

Within a supervised classification framework, labeled data are used to learn classifier parameters. Prior to that, it is generally required to perform dimensionality reduction via feature extraction. These preprocessing steps have motivated numerous research works aiming at recovering latent variables in an unsupervised context. This paper proposes a unified framework to perform classification and low-level modeling jointly. The main objective is to use the estimated latent variables as features for classification and to incorporate simultaneously supervised information to help latent variable extraction. The proposed hierarchical Bayesian model is divided into three stages: a first low-level modeling stage to estimate latent variables, a second stage clustering these features into statistically homogeneous groups and a last classification stage exploiting the (possibly badly) labeled data. Performance of the model is assessed in the specific context of hyperspectral image interpretation, unifying two standard analysis techniques, namely unmixing and classification

Chalk cliff retreat in East Sussex and Kent 1870s to 2001

The retreat of chalk cliffs fringing the eastern English Channel contributes shingle to the beaches which helps to protect the cliffs and slow down erosion. Conversely, cliff retreat endangers settlements and infrastructure on the clifftop. Rates of retreat have been calculated by a variety of methods over the past century, but no attempt has been made to provide a complete coverage that allows for a true comparison of retreat rates over the entire coastline. Using historic maps and recent orthophotos, cliff retreat rates have been calculated for consecutive 50 m sections of chalk cliff along the English side of the entire eastern English Channel for a period of 125 years. The chalk cliffs of East Sussex erode at an average rate of 0.25 - 0.3 m y−1 while those in Kent at a rate of 0.1 m y−1

Polariton-assisted Singlet Fission in Acene Aggregates

Singlet fission is an important candidate to increase energy conversion efficiency in organic photovoltaics by providing a pathway to increase the quantum yield of excitons per photon absorbed in select materials. We investigate the dependence of exciton quantum yield for acenes in the strong light-matter interaction (polariton) regime, where the materials are embedded in optical microcavities. Starting from an open-quantum-systems approach, we build a kinetic model for time-evolution of species of interest in the presence of quenchers and show that polaritons can decrease or increase exciton quantum yields compared to the cavity-free case. In particular, we find that hexacene, a typically poor singlet-fission candidate, can feature a higher yield than cavity-free pentacene when assisted by polaritonic effects. Similarly, we show that pentacene yield can be increased when assisted by polariton states. Finally, we address how various relaxation processes between bright and dark states in lossy microcavities affect polariton photochemistry. Our results also provide insights on how to choose microcavities to enhance similarly related chemical processes.Comment: 12 pages, 4 figure

Comparison of convolutional neural networks for cloudy optical images reconstruction from single or multitemporal joint SAR and optical images

With the increasing availability of optical and synthetic aperture radar (SAR) images thanks to the Sentinel constellation, and the explosion of deep learning, new methods have emerged in recent years to tackle the reconstruction of optical images that are impacted by clouds. In this paper, we focus on the evaluation of convolutional neural networks that use jointly SAR and optical images to retrieve the missing contents in one single polluted optical image. We propose a simple framework that ease the creation of datasets for the training of deep nets targeting optical image reconstruction, and for the validation of machine learning based or deterministic approaches. These methods are quite different in terms of input images constraints, and comparing them is a problematic task not addressed in the literature. We show how space partitioning data structures help to query samples in terms of cloud coverage, relative acquisition date, pixel validity and relative proximity between SAR and optical images. We generate several datasets to compare the reconstructed images from networks that use a single pair of SAR and optical image, versus networks that use multiple pairs, and a traditional deterministic approach performing interpolation in temporal domain.Comment: 17 page

Modèle bayésien hiérarchique pour le démélange et la classification robuste d'images hyperspectrales

L’interprétation des images hyperspectrales demeure un problème complexe qui a été abordée sous différents paradigmes. En particulier, les techniques de classification supervisée et de démélange spectral sont deux familles de méthodes d’interprétation largement utilisées. Ces deux approches offrent des analyses complémentaires : le démélange spectral propose une modélisation basée sur une interprétation physique des images hyperspectrales, en supposant que chaque pixel est un mélange de spectres purs associés aux divers matériaux présents dans la scène, tandis que la classification supervisée cherche à identifier une classe unique par pixel en se basant sur un ensemble de classes sémantiques définies par l’utilisateur et sur un ensemble de données, labellisées par un expert, lui servant d’exemple. Si ces deux techniques ont été largement discutées dans la littérature, elles ont été rarement utilisées conjointement

Factorisation de matrices pour le démélange et la classification conjoints d'images hyperspectrales

La classification supervisée et le démélange spectral sont parmi les techniques les plus utilisées pour extraire l’information d’images hyperspectrales. Bien que ces deux méthodes sont couramment utilisées, elles n’ont que très rarement été envisagées conjointement. Au lieu d’utiliser ces méthodes de manière séquentielle, comme on le voit les travaux déjà réalisés [1], nous proposons ici d’introduire le concept de démélange et classification conjoints

Longitudinal trends in malaria testing rates in the face of elimination in eastern Myanmar: a 7-year observational study

Background: Providing at-risk communities with uninterrupted access to early diagnosis and treatment is a key component in reducing malaria transmission and achieving elimination. As programmes approach malaria elimination targets it is critical that each case is tested and treated early, which may present a challenge when the burden of malaria is reduced. In this paper we investigate whether malaria testing rates decline over time and assess the impacts of integrating malaria and non-malaria services on testing rates in the malaria elimination task force (METF) programme in the Kayin state of Myanmar. Methods: A retrospective analysis was conducted using weekly collected data on testing rates from a network of more than 1200 malaria posts during the period from 2014 to 2020. To determine whether monthly testing rates changed over the years of programme operations, and whether integrating malaria and non-malaria services impacted these testing rates, we fitted negative binomial mixed-effects regression models to aggregate monthly data, accounting for malaria seasonal variation. Results: In the first year of malaria post operation, testing rates declined, correlating with a decline in attendance by people from outside the malaria post catchment area, but then remained fairly constant (the Rate Ratio (RR) for 2nd versus 1st year open ranged from 0.68 to 0.84 across the four townships included in the analysis, the RR for 3rd to 6th year versus 1st year open were similar, ranging from 0.59–0.78). The implementation of a training programme, which was intended to expand the role of the malaria post workers, had minimal impact on testing rates up to 24 months after training was delivered (RR for integrated versus malaria-only services ranged from 1.00 to 1.07 across METF townships). Conclusion: Despite the decline in malaria incidence from 2014 to 2020, there has been no decline in the malaria testing rate in the METF programme after the establishment of the complete malaria post network in 2016. While the integration of malaria posts with other health services provides benefits to the population, our evaluation questions the necessity of integrated services in maintaining malaria testing rates in areas approaching elimination of malaria

Canada’s multiple voices diplomacy in climate change negotiations: a focus on Québec

Abstract: This article sheds light on the complexity of international climate change negotiations in a federal country, like Canada, where there is no clear attribution of full power over international negotiation concerning this issue. Climate change is a multi-level and multi-stakeholder issue, one that can only be tackled successfully if all actors, at all levels of government, are involved in the process. In recent years, Canadian provinces, especially Québec, have become intensely involved in climate change paradiplomacy. That situation has led to a Canadian paradox where the Government of Québec worked to respect the Kyoto Protocol and act accordingly, while Canada opted out of the Protocol in 2011

Space-time clustering of childhood malaria at the household level: a dynamic cohort in a Mali village

BACKGROUND: Spatial and temporal heterogeneities in the risk of malaria have led the WHO to recommend fine-scale stratification of the epidemiological situation, making it possible to set up actions and clinical or basic researches targeting high-risk zones. Before initiating such studies it is necessary to define local patterns of malaria transmission and infection (in time and in space) in order to facilitate selection of the appropriate study population and the intervention allocation. The aim of this study was to identify, spatially and temporally, high-risk zones of malaria, at the household level (resolution of 1 to 3 m). METHODS: This study took place in a Malian village with hyperendemic seasonal transmission as part of Mali-Tulane Tropical Medicine Research Center (NIAID/NIH). The study design was a dynamic cohort (22 surveys, from June 1996 to June 2001) on about 1300 children (<12 years) distributed between 173 households localized by GPS. We used the computed parasitological data to analyzed levels of Plasmodium falciparum, P. malariae and P. ovale infection and P. falciparum gametocyte carriage by means of time series and Kulldorff's scan statistic for space-time cluster detection. RESULTS: The time series analysis determined that malaria parasitemia (primarily P. falciparum) was persistently present throughout the population with the expected seasonal variability pattern and a downward temporal trend. We identified six high-risk clusters of P. falciparum infection, some of which persisted despite an overall tendency towards a decrease in risk. The first high-risk cluster of P. falciparum infection (rate ratio = 14.161) was detected from September 1996 to October 1996, in the north of the village. CONCLUSION: This study showed that, although infection proportions tended to decrease, high-risk zones persisted in the village particularly near temporal backwaters. Analysis of this heterogeneity at the household scale by GIS methods lead to target preventive actions more accurately on the high-risk zones identified. This mapping of malaria risk makes it possible to orient control programs, treating the high-risk zones identified as a matter of priority, and to improve the planning of intervention trials or research studies on malaria

Long-term Mortality in HIV-Positive Individuals Virally Suppressed for >3 Years With Incomplete CD4 Recovery

Virally suppressed HIV-positive individuals on combination antiretroviral therapy who do not achieve a CD4 count >200 cells/µL have substantially increased long-term mortality. The increased mortality was seen across different patient groups and for all causes of deat