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This work examines the possibility of a rapid formation of glauconite in a relatively shallow platform environment (below fair-weather wave baseline). The materials studied here are uppermost Jurassic alternations of carbonate beds and marly interbeds, namely, the Assises de Croï Formation of the Boulonnais area (northernmost France). The carbonate beds yield field evidences of an early diagenetic origin and both beds and interbeds contain glauconite, questioning the duration of formation of the glauconite, relative to that of the diagenetic carbonate beds. Carbon and oxygen stable isotope composition of the carbonate beds confirm an early diagenetic growth. Contrasted grain-size distribution patterns of glauconite and quartz grain populations (isolated after acid digestion and magnetic separation) evidenced that glauconite formed after sediment deposition. Glauconite formation allegedly requires protracted episodes of ion capture from the water column, which is no longer possible when glauconite gets trapped within authigenic carbonates. Therefore, in-situ glauconite formation preceded carbonate authigenesis. Yet, the chemical composition of grains (Fe and K) typifies glauconite as highly evolved, meaning that its formation must have lasted over times, according to conventional views. Consequently, our results challenge these conventional views and confirm that glauconite can form in relatively shallow environments (which has been already brought to light previously) and it is concluded that early diagenetic glauconite can be markedly enriched in both K and Fe, which is an unprecedented result.

Glauconite is an authigenic mineral reputed to form during long-lasting contact between a nucleus (a pre-existing phyllosilicate) and seawater. This protracted contact makes it possible to subtract the ions necessary for the construction of the neoformed phyllosilicate, here, glauconite (a mineral very close to an illite, rich in K and Fe). As a result, glauconite is often associated with sediments deposited in a transgressive context with a strong slowdown in the rate of sedimentation and a relatively large water layer thickness. This is the case of the Cenomanian chalk of Boulonnais (north of France). Being chemically and physically resistant, glauconite is a mineral that is often reworked, like quartz grains. This is frequently the case of the Jurassic deposits of the Boulonnais, where glauconite, almost ubiquitous, either in traces or in significant proportions of the sediments, presents a grain size sorting attesting to its transport and reworking. However, these Jurassic deposits are shallow (shoreface, upper offshore), which supports the idea that the “glauconite factory” was itself in the shallow areas of the Boulonnais. The only identified Jurassic facies of the Boulonnais where glauconite is both relatively abundant, large in size and unsorted (non reworked) are oyster reefs that formed at the outlet of cold seeps linked to a late-Jurassic synsedimentary tectonic (Kimmeridgian, Tithonian). Our work makes it possible to hypothesize that isolated oyster reefs were environments combining the redox conditions and in contact with seawater favoring the authigenic formation of glauconite. The weakly reducing conditions necessary for the formation of glauconite here are attested by the contents of metallic trace elements sensitive to redox conditions (vanadium, germanium, arsenic, in this case). Our work thus adds a new element to the understanding of the mechanisms of formation of glauconite in shallow environments.

Background The therapeutic strategy for mycetoma relies heavily on the identification of the causative agents, which are either fungal or bacterial. While histopathological examination of surgical biopsies is currently the most used diagnostic tool, it requires well-trained pathologists, who are lacking in most rural areas where mycetoma is endemic. In this work we propose and evaluate a machine learning approach that semi-automatically analyses histopathological microscopic images of grains and provides a classification of the disease as eumycetoma or actinomycetoma. Methods The computational model is based on radiomics and partial least squares. It is assessed on a dataset that includes 890 individual grains collected from 168 patients originating from the Mycetoma Research Centre in Sudan. The dataset contained 94 eumycetoma cases and 74 actinomycetoma cases, with a distribution of the species among the two causative agents that is representative of the Sudanese distribution. Results The proposed model achieved identification of causative agents with an accuracy of 91.89%, which is comparable to the accuracy of experts from the domain. The method was found to be robust to a small error in the segmentation of the grain and to changes in the acquisition protocol. Among the radiomics features, the homogeneity of mycetoma grain textures was found to be the most discriminative feature for causative agent identification. Conclusion The results presented in this study support that this computational approach could greatly benefit rural areas with limited access to specialized clinical centres and also provide a second opinion for expert pathologists to implement the appropriate therapeutic strategy. [ABSTRACT FROM AUTHOR]

Though the morphological discrimination of the three pseudo-cryptic Ammonia species, A. aberdoveyensis, A. confertitesta and A. veneta, has been recently established, information on their ecology and habitats are still relatively scarce. This study aims to define distribution patterns of these species at eight sites scattered along the French coasts of the English Channel, over a total of 39 stations. These sites were classified into two habitats, either harbours (heavily modified sites) or less impacted (moderately influenced sites). The use of IndVal index (an index based on how a species is statistically specific to a habitat) clearly indicates that A. confertitesta is recorded preferentially in or close to harbours. Considering its non-indigenous species (NIS) status in Europe, we investigated its reported occurrences in Europe in the literature. It almost always showed a proximity to major European harbours. Sometimes, this species occurred relatively far away from these harbours, suggesting a secondary spread. Finally, this work interprets A. confertitesta being a NIS in the eastern English Channel with assumptions of being invasive regarding its dominance over the indigenous species A. aberdoveyensis and A. veneta. Complementary works such as retrospective core studies of fossil faunas are needed to quantitatively assess when and where A. confertitesta was introduced in Europe and potentially started to replace its congenerics A. veneta and A. aberdoveyensis. [ABSTRACT FROM AUTHOR]

In the last three decades, benthic foraminiferal ecology has been intensively investigated to improve the potential application of these marine organisms as proxies of the effects of climate change and other global change phenomena. It is still challenging to define the most important factors affecting foraminiferal communities and derived faunistic parameters. In this study, we examined the abiotic-biotic relationships of foraminiferal communities in the central-southern area of the Adriatic Sea using modern machine learning techniques. We combined gradient forest (Gf) and structural equation modeling (SEM) to test hypotheses about determinants of benthic foraminiferal assemblages. These approaches helped determine the relative effect of sizes of different environmental variables responsible for shaping living foraminiferal distributions. Four major faunal turnovers (at 13–28 m, 29–58 m, 59–215 m, and >215 m) were identified along a large bathymetric gradient (13–703 m water depth) that reflected the classical bathymetric distribution of benthic communities. Sand and organic matter (OM) contents were identified as the most relevant factors influencing the distribution of foraminifera either along the entire depth gradient or at selected bathymetric ranges. The SEM supported causal hypotheses that focused the factors that shaped assemblages at each bathymetric range, and the most notable causal relationships were direct effects of depth and indirect effects of the Gf-identified environmental parameters (i.e., sand, pollution load Index–PLI, organic matter–OM and total nitrogen–N) on foraminifera infauna and diversity. These results are relevant to understanding the basic ecology and conservation of foraminiferal communities. [ABSTRACT FROM AUTHOR]

We consider a model of a stationary population with random size given by a continuous-state branching process with immigration with a quadratic branching mechanism. We give an exact elementary simulation procedure for the genealogical tree of n individuals randomly chosen among the extant population at a given time. Then we prove the convergence of the renormalized total length of this genealogical tree as n goes to infinity; see also Pfaffelhuber, Wakolbinger and Weisshaupt (2011) in the context of a constant-size population. The limit appears already in Bi and Delmas (2016) but with a different approximation of the full genealogical tree. The proof is based on the ancestral process of the extant population at a fixed time, which was defined by Aldous and Popovic (2005) in the critical case. [ABSTRACT FROM AUTHOR]

We consider the Brownian tree introduced by Aldous and the associated Q-process which consists in an infinite spine on which are grafted independent Brownian trees. We present a reversal procedure on these trees that consists in looking at the tree downward from its top: the branching points becoming leaves and leaves becoming branching points. We prove that the distribution of this tree is invariant under this reversal procedure, which provides a better understanding of previous results from Bi and Delmas (2016). [ABSTRACT FROM AUTHOR]

The goal of this paper is the presentation of a post-processing method allowing to remove impulse noise in binary images, while preserving thin structures. We use a grain filter. We propose a method to automatically determine the required threshold using Galton-Watson processes. We present numerical results and a complete analysis on a synthetic image. We end the numerical section considering a specific application to granite samples crack detection: Here we deal with X-tomography images that have been binarized via preprocessing techniques and we want to remove residual impulse noise while keeping cracks and micro-cracks structure. [ABSTRACT FROM AUTHOR]

Representation of coalescent processes using pruning of trees has been used by Goldschmidt and Martin for the Bolthausen-Sznitman coalescent and by Abraham and Delmas for the β(3/2, 1/2)-coalescent. By considering a pruning procedure on stable Galton-Watson tree with n labeled leaves, we give a representation of the discrete β(1+α, 1-α)-coalescent, with α ∈ [1/2, 1) starting from the trivial partition of the n first integers. The construction can also be made directly on the stable continuum Lévy tree, with parameter 1/α, simultaneously for all n. This representation allows to use results on the asymptotic number of coalescence events to get the asymptotic number of cuts in stable Galton-Watson tree (with infinite variance for the offspring distribution) needed to isolate the root. Using convergence of the stable Galton-Watson tree conditioned to have infinitely many leaves, one can get the asymptotic distribution of blocks in the last coalescence event in the β(1 + α, 1 - α)-coalescent. [ABSTRACT FROM AUTHOR]

Considering a random binary tree with n labelled leaves, we use a pruning procedure on this tree in order to construct a β(3/2, ½)-coalescent process. We also use the continuous analogue of this construction, i.e. a pruning procedure on Aldous's continuum random tree, to construct a continuous state space process that has the same structure as the β-coalescent process up to some time change. These two constructions enable us to obtain results on the coalescent process, such as the asymptotics on the number of coalescent events or the law of the blocks involved in the last coalescent event. [ABSTRACT FROM AUTHOR]

We consider an initial population whose size evolves according to a continuous state branching process. Then we add to this process an immigration (with the same branching mechanism as the initial population), in such a way that the immigration rate is proportional to the whole population size. We prove this continuous state branching process with immigration proportional to its own size is itself a continuous state branching process. By considering the immigration as the apparition of a new type, this construction is a natural way to model neutral mutation. It also provides in some sense a dual construction of the particular pruning at nodes of continuous state branching process introduced by the authors in a previous paper. For a critical or sub-critical quadratic branching mechanism, it is possible to explicitly compute some quantities of interest. For example, we compute the Laplace transform of the size of the initial population conditionally on the non-extinction of the whole population with immigration. We also derive the probability of simultaneous extinction of the initial population and the whole population with immigration. [ABSTRACT FROM AUTHOR]

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Background: The therapeutic strategy for mycetoma relies heavily on the identification of the causative agents, which are either fungal or bacterial. While histopathological examination of surgical biopsies is currently the most used diagnostic tool, it requires well-trained pathologists, who are lacking in most rural areas where mycetoma is endemic. In this work we propose and evaluate a machine learning approach that semi-automatically analyses histopathological microscopic images of grains and provides a classification of the disease as eumycetoma or actinomycetoma., Methods: The computational model is based on radiomics and partial least squares. It is assessed on a dataset that includes 890 individual grains collected from 168 patients originating from the Mycetoma Research Centre in Sudan. The dataset contained 94 eumycetoma cases and 74 actinomycetoma cases, with a distribution of the species among the two causative agents that is representative of the Sudanese distribution., Results: The proposed model achieved identification of causative agents with an accuracy of 91.89%, which is comparable to the accuracy of experts from the domain. The method was found to be robust to a small error in the segmentation of the grain and to changes in the acquisition protocol. Among the radiomics features, the homogeneity of mycetoma grain textures was found to be the most discriminative feature for causative agent identification., Conclusion: The results presented in this study support that this computational approach could greatly benefit rural areas with limited access to specialized clinical centres and also provide a second opinion for expert pathologists to implement the appropriate therapeutic strategy., (© The Author(s) 2023. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)