Reviewerly/exHarmony huggingface dataset:
Bayesian solution to the monotone likelihood in the standard mixture cure model

An advantage of the standard mixture cure model over an usual survival model is how it accounts for the population heterogeneity. It allows a joint estimation for the distribution related to the susceptible and non‐susceptible subjects. The estimation algorithm may provide coefficients when the likelihood cannot be maximized. This phenomenon is known as Monotone Likelihood (ML), common in survival and logistic regressions. The ML tends to appear in situations with small sample size, many censored times, many binary or unbalanced covariates. Particularly, it occurs when all uncensored cases correspond to one level of a binary covariate. The existing frequentist solution is an adaptation of the Firth correction, originally proposed to reduce bias of maximum likelihood estimates. It prevents estimates by penalizing the likelihood, with the penalty interpreted as the Bayesian Jeffreys prior. In this paper, the penalized likelihood of the standard mixture cure model is considered with different penalties (Bayesian priors). A Monte Carlo simulation study indicates good inference results, especially for balanced data sets. Finally, a real application involving a melanoma data illustrates the approach.
Soil Data Harmonization to Create a Global Soil Data Platform

The management of our soils plays a crucial role in addressing some of our greatest challenges, such as food security and climate change. Working together across national borders is essential for securing the health and quality of our soil in the future. With multi-stakeholder processes, language and the use of language is very important since the capability of understanding each other is critical. Developing a common language facilitates learning together, trust-building, defining common viewpoints, resolving disagreements, and arriving at technically sound and practical solutions.&amp;#160;&amp;#160; This document represents the initial attempt to create a common soil domain ontology and data model to support the creation of a user-friendly infrastructure in accordance with FAIR (Findable, Accessible, Interoperable, and Reusable) data principles for uploading, managing, and providing comparable soil data at global scale. To meet these requirements, the review and application of accepted and widely used standards, conventions, and guidelines for the ingestion, organization, and sharing of soil data is necessary. The document should be regarded as a living document that evolves along with the progress of the project and in response to stakeholder feedback.&amp;#160;&amp;#160; This project began with the development of an ontology for the soil domain and the identification of representational terms. This was done by following a data-driven approach, which allowed the determination of relevant entities by making strategic decisions based on data analysis and organization, while facilitating a modular expansion of the knowledge base. Next, a standardized soil vocabulary was defined to facilitate data sharing and discovery.&amp;#160; Furthermore, soil analytical information is collected and modelled across a variety of data sources, as well as SI units and non-SI units accepted for use with the International System of Units. Finally, a list of relevant conversion factors, regressions, and pedotransfer functions was collected to facilitate data comparison across different data bases.&amp;#160;&amp;#160;
Assessing the soil baseline values of a geologically complex territory: the case study of Basilicata region.

The middle and lower reaches of the Basento river and the whole basin of the Cavone river, in Basilicata region (Italy), underwent to a geochemical prospecting involving soil and stream sediments. Specifically, 190 topsoils were collected within a depth range between 10-15 cm from the ground level and 10 bottom soils were sampled within the depth range between 80-100 cm.&amp;#160; Samples were analysed at the Life Analytics laboratory (Battipaglia, Italy), by ICP-MS following an aqua regia digestion, to determine the concentrations of 16 potentially toxic inorganic substances (As, Be, Cd, Co, Cr, CrIV, Cu, Hg, Ni, Pb, Sb, Se, Tl, V, Zn, SO4).&amp;#160;&amp;#160; The purpose of the study has been the definition of the upper background limits (UBLs) for the investigation area. An exploratory data analysis (EDA) was conducted on the dataset to outline the main data structural characteristics. Due to the huge number of samples below detection limits (BDL) for Cd, CrIV, Hg, Se, Tl, only As, Be, Co, Cr, Ni, Pb, Cu, V, Zn and SO4 were considered for the UBLs definition.&amp;#160; The estimate of the above-mentioned values has been conducted following a series of rigorous statistical tests in line with the "Guidelines for the determination of background values for soils and groundwater" released by the Italian National System for Environmental Protection (SNPA).&amp;#160;&amp;#160; In detail, after imputing the few BDL values found in the selected variables by means of K-nearest neighbors (k-NN) algorithm, topsoil and bottom soils data were considered as a whole. Indeed, the dataset was subdivided into 7 subsets according the geopedological units identified based on the local pedological and geological features.&amp;#160; The BoxCox algorithm was applied to the single subsets to normalize data distribution before any statistical treatment. Outliers were identified by mean of the Dixon&amp;#8217;s or Rosner&amp;#8217;s Outlier tests depending on the sample size, the observation of boxplots and Q-Q plots and the spatial location of some samples considered as hotspots. &amp;#160; For each variable and for each subset, two statical indices (i.e.:&amp;#160; 95th upper tolerance limit with 95% coverage (95UTL95) and the 95th upper prediction limit (UPL95)) were calculated. The more conservative among them was chosen as representative for the UBLs. Results showed that the UBLs found are much lower than the guideline values set by the Italian Environmental Law (Legislative Decree 152/2006). Our findings emphasized how the use of guideline values established at a national level is often inadequate to administrate a geologically and pedologically complex territory such as Italy, favoring the chance of running into a wrong identification of local environmental hazards. &amp;#160;
The International DORIS Service: almost 20 years old.

On 1 July 2023, the International DORIS Service (IDS) will celebrate the 20th anniversary of its creation under the umbrella of the International Association of Geodesy (IAG). The IDS was established to foster scientific research related to the French DORIS tracking system and to deliver scientific products, mostly related to the International Earth rotation and Reference systems Service (IERS). Since its start, the organization has continuously evolved, leading to additional and improved operational products.&amp;#160;IDS is now based on a reinforced structure with two Data Centers, six Analysis Centers, four Associated Analysis Center, a Combination Center, and several partner groups.The DORIS system recorded its first measurement on February 3rd, 1990, from the SPOT-2 remote sensing satellite. 32 years after, the system is at its best. DORIS has proven greatly valuable for geodesy and geophysics applications: measuring tectonic plate motions, determination of the rotation and the gravity parameters of the Earth, contributing to the international reference system, ... Technological and methodological improvements have allowed the improvement in the estimates of the positions of the DORIS tracking ground stations, the Earth rotation parameters and other geodetic variables such as the geocenter and the scale of the ITRF.&amp;#160;This year, a 9th satellite joins the current constellation of DORIS satellites. It is SWOT, launched on 16 December 2022. Never before have so many DORIS instruments been in operation simultaneously.This presentation addresses the recent achievements made by IDS and its components, and the future plans of the service.
The slip deficit rate, slow and fast earthquake at the Nankai subduction zone.

The Nankai subduction zone is considered as a region with a high seismic risk. Large earthquakes with magnitudes larger than 8 have occurred and will recur in the future. Additionally, several observations of slow earthquakes at the shallow and deep plate interface have continuously been being happening. Large and slow earthquakes originate from different types of frictional characteristics, mostly driven by an accumulation of interplate slip deficit. Here, we present results from geodetic observations to estimate the slip deficit rate at the Nankai subduction zone based on displacement rate data of the dense onshore GNSS array as well as that of the offshore GNSS-Acoustic stations during the period 2002 to 2016 (Nishimura et al. 2018). After removing co-seismic and post-seismic deformations due to earthquakes in other regions, we estimated the slip deficit rate at the plate interface by using a trans-dimensional reversible jump Markov chain Monte Carlo algorithm (Tomita et al. 2021). To obtain a smooth slip distribution without imposing smoothing constraints we used a Voronoi partitioning for slip parameters, in which the number of cells is automatically set during the inversion, based on the spatial resolution of data. In contrast to previous slip deficit inversions at the Nankai region, we included scaling weight factors for different types of data. The scaling factors were parameterized to be adjusted in the inversion procedure. Furthermore, we used elastic Green Functions estimated from a three-dimensional heterogeneous structure of the Nankai regions (Hori et al. 2021), instead of a homogeneous medium as previously done. We accomplished a new model of slip deficit rate for the Nankai subduction zone that complements previous models. Regions with high slip deficits agree with the rupture areas of historic large earthquakes. Lastly, the location of deep and shallow slow earthquakes agrees with estimated intermediate values of slip deficit. The slow earthquake region defines the transition between a locked and unlocked plate interface, while shallow slow earthquakes can also be generated by shallow heterogeneous patches or subsurface structures at the subducting plate.
Transfer Learning for LULC Classification on multi-modal data in the Amazon Basin

Mapping of Land use and land cover (LULC) changes over time requires automated processes and has been investigated using various machine learning algorithms and, more recently, deep learning models for semantic classification. New applications of these models to different satellite data and areas are regularly published. However, studies on the transfer of these models to other data and study areas are rather scarce. In a previous study [1], we used multi-modal and &amp;#8211;temporal Sentinel data for LULC classification using traditional and novel deep learning models. The data covered parts of the Amazon basin and was comprised of a twelve-month time series of radar imagery (Sentinel-1), combined with a singular multi-spectral image (Sentinel-2). All satellite images were captured throughout the year 2018. The label map (Collection 4) of the Amazon produced by the MapBiomas project [2] was used as training and test labels. Besides state-of-the-art models, we developed five variations of a deep learning model&amp;#8212;DeepForest&amp;#8212;which leverages on the multi-temporal and -modal aspect of the data. The best model variation (DF1c) reached an overall accuracy of 74.4% on the test data.Currently we are investigating the transferability of these models to more recent data of the same region. The new dataset was processed in the same way as in the previous study. It comprises a Sentinel-1 time-series and a single Sentinel-2 images from 2020, with an updated version of the label map of the MapBiomas project (Collection 6). This posed some challenges, as the classification scheme changed and is not fully backwards compatible with the one used to train the DeepForest models. A test dataset was chosen in the state of Mato Grosso, as the satellite scenes cover most classes used in the classification scheme. However, this data exhibits some class imbalance, as two of the eleven classes are dominating the scene. All five DeepForest variations reached accuracies higher than 79% and thus generalize well on the major LULC classes. For comparison and to further improve our models, we currently retrain the models on the new, larger data set (114,376 training image tiles compared to 18,074). Preliminary results will be shown during the session.&amp;#160;ReferencesCherif, E.; Hell, M.; Brandmeier, M. DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin. Remote Sensing 2022, 14, 5000, doi:10.3390/rs14195000. MapBiomas Brasil; Available online: https://mapbiomas.org/en
Data Producer and Data User Needs for Airborne and Field Earth Science Research Measurements

This presentation summarizes information on the needs of data producers and data users gathered from the combination of a March 2022 two-day on-line workshop and the nearly 30-year history of the NASA Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs). &amp;#160;The workshop included over 100 participants, primarily from the United States, with the first day focusing on the needs of data users and the second day focusing on the needs of data producers. &amp;#160;Based on both the workshop and the collective experience of the DAACs, both data producers and data users benefit substantially when there is an early partnership between the research project producing the data and the data archive which will publish the data. &amp;#160;The highly heterogenous nature of airborne and field research data presents &amp;#160;particular challenges for discovery, particularly in the context of systems that are optimized for discovery and delivery of on-orbit Earth science data. &amp;#160;The DAACs experience also demonstrates an evolution of best practices for working with this kind of data. &amp;#160;However, systems which have been in operation for decades often have technical debt, which can constrain the evolution of the research data infrastructure. &amp;#160;The migration of EOSDIS into a commercial cloud environment presents several interesting opportunities for addressing the data producer and data user needs identified by the workshop and experience of the DAACs. &amp;#160;
A model of forced folding controlled by syn-orogenic clastic deposits in a foreland fold and thrust belt. The case of the Jaca Basin, South Pyrenean Zone.

The nature and rate of syn-orogenic sedimentation play an important role in the tectono-stratigraphic evolution of foreland basins. Recent works have shown syn orogenic evaporites at the transition between underfilled and overfilled conditions in the Sivas basin (Turkey) have strongly influenced the subsequent structural and sedimentary evolution of the foreland fold and thrust belt (Legeay et al., 2020).In the western South Pyrenean Zone, the Jaca basin exhibits the classical stratigraphic succession of a pro-foreland basin systems. This was filled during Eocene-Oligocene with siliciclastic sediments derived from the erosion of the Pyrenees and deposited in a marine to continental environment. During Bartonian, a derivation in the sediment routing system and decreasing subsidence rate resulted in the deposition of a km-thick shale unit forming the transition between marine and continental conditions.The &amp;#8220;bed-to-bed&amp;#8221; mapping of the syn-orogenic units at the basin-scale using high-resolution DEM together with the reinterpreted seismic lines were used to build three cross-sections that highlight the structural style of the western South Pyrenean Zone. These illustrate the tectono-sedimentary evolution of a transitional shallow-marine to continental foreland basin.From end-Bartonian, the deposition of the Orosia-Cancias conglomerates in the north-eastern basin margin is coeval with the onset of the folding of the Basa anticline forward. During Priabonian, this were subsequently welded and forward-tilted coevally with the development of an imbricate in Hecho turbidites beneath, that can be linked to the emplacement of the Gavarnie thrust-sheet. At this time, the Orel alluvial fan was deposited westward at the termination of the Basa anticline and was associated with the growth of the second, shale-cored Atar&amp;#232;s anticline folding ahead. This was in turn welded during Rupelian at the time of deposition of the San Juan conglomerates at its western termination, coevally to the Botaya anticline folding downstream.The tectono-sedimentary evolution of the Jaca fold-and-thrust belt is thus resulting from complex interactions between the deformation of mobile shale and syn-orogenic alluvial sedimentation both at local and regional scale. This example highlights the influence of the syn-orogenic sedimentation and especially the deposition of a decoupling layer at the transition between marine and continental conditions during the evolution of foreland fold and thrust belts as well as thein mountain building processes.
Monitoring and Data Quality Issues of Mining Activites Around BRTR, Turkiye

Bogazici University-Kandilli Observatory and Earthquake Research Institute (KOERI) is operating IMS Primary Seismic Station (PS-43) under Belbasi Nuclear Tests Monitoring Center for the verification of compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT) since February 2000. PS-43 is composed of two seismic arrays (Ankara and Keskin). The medium-period array equipped with Guralp CMG-3TB instruments is located in the capital city of Ankara whereas the short-period array with Geotech 23900 sensors is located in Keskin. The data quality of the some of the array elements are degraded by the quarry blasts especially if there is an earthquake occurred at the same time with the explosion. There are more than 10 operational stone quarries spread across the city and there are more applications for new quarries each year. In this study, we show the importance of monitoring the quarry activities for the operation of the Turkish NDC. For this purpose, each blast is detected by automatically using cross-correlation and confirmed manually by the analyst.
geokube: A Python Package for Data Analysis and Visualization in Geoscience

geokube is a Python package for data analysis and visualisation in geoscience that&amp;#160; provides high level abstractions in terms of both Data Model, inspired by Climate Forecast and Unidata Common Data Models, and Application Programming Interface (API), inspired by xarray. Key features of geokube are the capabilities to: (i) perform georeferenced axis-based indexing on data structures and specialised geospatial operations according to different types of geo scientific datasets like structured grids, point observations, profiles etc. (e.g. extracting a bounding box or a multipolygon of variable values defined on a rotated pole grid), (ii) perform operations on the variables that are either instantaneous or defined over intervals, (iii) convert to/from xarray data structures and to read/write CF-compliant netCDF datasets.
Unsupervised Clustering applied on Raman spectra of dispersed carbonaceous material: a case history from the Paris Basin (France)

In the last decades, the use of Raman spectroscopy on dispersed carbonaceous material in rocks has become a promising tool for geothermometry and thermal maturity assessment. In diagenesis the main problem is linked to organofacies composition and the need of time-consuming optical classification (Henry et al., 2019, Sanders et al., 2022). In this work, three different methods of clustering analysis on Raman spectra were tested as a potential approach to recognize the three main organofacies (amorphous organic matter, translucid and opaque phytoclasts) that characterize a set of 27 organic-rich samples from the Lower Toarcian source rock interval (Schistes Carton) of the Paris Basin (France).Raman analyses were performed on concentrated organic matter obtained by acid attacks, with around 60 counts for each sample. Principal Component Analysis (PCA) was applied to reduce the dimensionality of each dataset on a 2-D score-plot. Unsupervised clustering was then performed by using three different clustering algorithms: k-means, Gaussian Mixture Models (GMM), and Density-Based Spatial Clustering for Applications with Noise (DBSCAN). The main task of these algorithms is to correctly assign the number of clusters, their size, orientation, and distribution in the score-plot that related to the heterogeneities in organofacies composition.Results show the best performances are achieved through the application of GMM clustering that can successfully determine cluster&amp;#8217;s geometry and optimal numbers with an accuracy mostly higher than 80% for the translucid phytoclasts group, that is the target for thermal maturity assessment.&amp;#160; This is a preliminary attempt showing promising application for unsupervised learning techniques coupled with Raman spectroscopy that could be applied in industrial routinely organic matter characterization or in the analysis of big dataset in both Earth and planetary sciences.&amp;#160;Henry, D. G., Jarvis, I., Gillmore, G., &amp; Stephenson, M., 2019. Raman spectroscopy as a tool to determine the thermal maturity of organic matter: Application to sedimentary, metamorphic and structural geology. Earth-Science Reviews 198, 102936.Sanders, M. M., Jubb, A. M., Hackley, P. C., &amp; Peters, K. E., 2022. Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock. Organic Geochemistry 165, 104371.
Intaking DKRZ ESM data collections

In this showcase, we present to you how Intake and its plugin Intake-ESM are utilized at DKRZ to provide highly FAIR data collections from different projects, stored on different types of storages in different formats.The Intake Plugin Intake-ESM allows users to not only find the data of interest, but also load them as analysis-ready-like Xarray datasets. We utilize this tool to provide users with access to many available data collections at our institution from only one single access point, the main DKRZ intake catalog at www.dkrz.de/s/intake. The functionality of this package works independently of data standards and formats and therefore enables full metadata-driven data access including data processing. Intake-esm catalogs increase the FAIRness of the data collections in all aspects but especially in terms of Accessibility and Interoperability.Started with a collection of DKRZ&amp;#8217;s CMIP6 Data Pool, DKRZ now hosts catalogs for more than 10PB of data on different local storages. The Intake-ESM package has been well integrated into ESM data provisioning workflows.Early sharing and making accessible: The co-developed inhouse ICON model generates an intake-esm catalog on each run. Uptake from other technologies: E.g., intake-esm catalogs serve as templates for the more advanced DKRZ STAC Catalogs.&amp;#160; Making accessible all storage types: tools used for writing data to the local institutional cloud allow users to create Intake-ESM catalogs for the written data. Data archiving: Catalogs for projects in the archive can be created from its metadata database. For future activities, we plan to make use of new functionalities like the support for kerchunked data and the derived variable registry.The DKRZ data management team develops and maintains local services around intake-esm for a positive user experience. In this showcase, we will present excerpts of seminars, workflows and integrations.