Catalog Data Research Articles

Sharpen data-driven prediction rules of individual large earthquakes with aid of Fourier and Gauss

Predicting individual large earthquakes (EQs)’ locations, magnitudes, and timing remains unreachable. The author’s prior study shows that individual large EQs have unique signatures obtained from multi-layered data transformations. Via spatio-temporal convolutions, decades-long EQ catalog data are transformed into pseudo-physics quantities (e.g., energy, power, vorticity, and Laplacian), which turn into surface-like information via Gauss curvatures. Using these new features, a rule-learning machine learning approach unravels promising prediction rules. This paper suggests further data transformation via Fourier transformation (FT). Results show that FT-based new feature can help sharpen the prediction rules. Feasibility tests of large EQs (Mge 6.5) over the past 40 years in the western U.S. show promise, shedding light on data-driven prediction of individual large EQs. The handshake among ML methods, Fourier, and Gauss may help answer the long-standing enigma of seismogenesis.

3DT-CM: A Low-complexity Cross-matching Algorithm for Large Astronomical Catalogues Using 3d-tree Approach

Location-based cross-matching is a preprocessing step in astronomy that aims to identify records belonging to the same celestial body based on the angular distance formula. The traditional approach involves comparing each record in one catalog with every record in the other catalog, resulting in a one-to-one comparison with high computational complexity. To reduce the computational time, index partitioning methods are used to divide the sky into regions and perform local cross-matching. In addition, cross-matching algorithms have been adopted on high-performance architectures to improve their efficiency. But the index partitioning methods and computation architectures only increase the degree of parallelism, and cannot decrease the complexity of pairwise-based cross-matching algorithm itself. A better algorithm is needed to further improve the performance of cross-matching algorithm. In this paper, we propose a 3d-tree-based cross-matching algorithm that converts the angular distance formula into an equivalent 3d Euclidean distance and uses 3d-tree method to reduce the overall computational complexity and to avoid boundary issues. Furthermore, we demonstrate the superiority of the 3d-tree approach over the 2d-tree method and implement it using a multi-threading technique during both the construction and querying phases. We have experimentally evaluated the proposed 3d-tree cross-matching algorithm using publicly available catalog data. The results show that our algorithm applied on two 32-core CPUs achieves equivalent performance than previous experiments conducted on a six-node CPU-GPU cluster.

Comparing Gardner-Knopoff, Gruenthal, and Uhrhammer Earthquake Declustering Methods in Aceh, Indonesia

The sudden release of energy from inside the earth, which generates seismic waves, causes earthquakes on the earth’s surface. Foreshock, mainshock, and aftershock are terms commonly used in this subject. These phrases refer to the three stages of an earthquake event—before the main event, the primary event, and after the main event. The earthquake data catalogue, however, typically does not distinguish between mainshock data and foreshocks/aftershocks. For seismic-related studies, justifying the mainshock is very crucial. There are several methods for separating the mainshock of earthquake data from the foreshocks/aftershocks. This study employs three declustering techniques, including Gardner-Knopoff (1974), Gruenthal, and Uhrhammer (1986). The present study collected and analyzed 3543 earthquake events from 1971 to 2021 for Aceh region. In order to determine which method provides the highest a-value and b-value outcomes for Aceh’s seismicity conditions, this study compares the aforementioned three approaches. The Uhrhammer method (1986) has an a-value of 5.82, a b-value of 1.05, 1893 main shock events, 305 clusters, and 3.3 percent of the total seismic moment generated at that location are the findings from this study. According to the Gruenthal method, the results had an a-value of 4.53, a b-value of 0.823, 776 mainshock events, 304 clusters, and released 1.3 percent of the total seismic moment at that location. a-value of 5.1, b-value of 0.929, 1097 main shock events, 319 clusters, and a release of 1.08 percent of the total seismic moment at that location were the results of the Gardner-Knopoff method (1974). For seismic hazard evaluation with the highest level of risk, the Uhrhammer (1986) technique is appropriate. The Gruenthal approach is suggested for more conservative cases.

Viscum album subsp. austriacum (Santalaceae R. Br.) in Volyn Polissia and Zhytomyr Polissia (Ukraine): current distribution, ecology and prediction of future spread

Background. One of the subspecies of the European mistletoe, the so called pine mistletoe (Viscum album subsp. austriacum (Wiesb.) Vollm.) is a hemiparasitic, evergreen, epiphytic phanerophyte that parazitizes predominantely on the Scots pine (Pinus sylvestris L.) in Ukraine. The pine trees infested with V. album subsp. austriacum lack moisture for transpiration and photosynthesis, which reduces their primary productivity, viability and health. The purpose of this study was: 1) to determine the current distribution of V. album subsp. austriacum in Volyn and Zhytomyr Polissia regions using GIS-technology; 2) study the main taxation parameters of pine stands infested with V. album subsp. austriacum; 3) predict the possible further spread of V. album subsp. austriacum in the studied Region. Materials and Methods. The grid mapping method based on GIS technology, with a grid size of 10×10 km and 20×20 km, was used to create the map of the species distribution. The spatial distribution of soil moisture in the forest soils of Drevlyanskyi Nature Reserve was determined using satellite images and data on soil moisture from the Earth Engine Data Catalog. The taxation parameters of the mistletoe-infested pine stand (i.e., participation of the Scots pine in the stand composition, area distribution of pine stands by age, relative completeness, stand quality class, trophotope, and hygrotope) were obtained from standard taxation descriptions. Results and Discussion. The study found that V. album subsp. austriacum is more widespread in Volyn Polissia than in Zhytomyr Polissya – 87 and 20 localities respectively. It was shown that the forest plantations colonized by V. album subsp. austriacum in Drevlyansky Nature Reserve are located in areas with the lowest moisture content, with a moisture reserve of 16–70 mm in the 0–100 cm soil layer, which corresponds to dry and fresh hygrotopes. Conclusions. V. album subsp. austriacum is more widely distributed in such nature reserves of the region as Shatskyi National Nature Park and Drevlianskyi Nature Reserve, and less so in Rivne, Cheremskyi, Polissia Nature Reserves and Pripyat-Stokhid National Nature Park. In the region under study, V. album subsp. austriacum mostly affects pure pine forests aged 80‒140 years, of medium completeness (0.5‒0.7), and relatively high and high stand quality classes – Ic–II, in fresh hygrotopes – 67.3 % of the area and in fairly infertile pine site type (trophotope B) – 51.5 %. Based on the distribution of forest site types in the region and their susceptibility to V. album subsp. austriacum, the possibility of its further intensive spread in the study region can be predicted.

A New Approach to 3D Digital Evaluation and Analysis In Geological Engineering

The initial geological analysis of hydropower projects is greatly complicated by the existence of complex geological conditions. To adapt advances in informatization and digitalization to the needs of the engineering survey industry and to conduct geological analysis more intuitively, in the present study the development of “GeoBIM”, a geological 3D design platform based on the DSI modeling engine and a “graphics + data” architecture is rerported. GeoBIM realized the integration of 3D information in the whole process of geological work, from field data collection, model design, and analysis to approval. Taking the siting and construction of a hydropower station as an example, the field data collection and cataloging APP (boreholes, caverns, slopes) and web-side exploration monitoring platform of GeoBIM were used to build a 3D geological fine visualization model. The principle of dissipated energy was used to analyze the quality of the rock mass, which showed the spatial distribution characteristics of local geological conditions and rock mass quality, improving the efficiency and intuitiveness of engineering rock mass quality classification. GeoBIM was compared with traditional 2D geological analysis methods and actual conditions to demonstrate the rationale and intuitive use of the 3D digital evaluation method in geological engineering. Bangladesh J. Bot. 52(2): 679-688, 2023 (June) Special

An investigation of linked data catalogue features in libraries, archives, and museums: a checklist approach

PurposeIn this study, the distinctive functional features of linked data (LD) catalogues were investigated to contrast with existing online public access catalogues (OPACs) and discovery systems using a checklist approach. The checklist was derived from a literature review and is composed of 10 items as follows: self-descriptive and dynamic content for resource description, linkage to external LD sources and online services, aggregation of knowledge contexts into knowledge graphs (KGs), URI-based link discovery, representation and query of LD relationships, URI-based serendipitous discovery, keyword recommendation, faceted limitation and browsing, visualization and openness of data.Design/methodology/approachTen functional features derived from the literature were checked against existing LD catalogues offered by libraries, archives and museums (LAMs). The LD catalogues were regarded as qualified subjects if they offered functional features that were distinct from current OPACs and discovery systems through URI-based enrichment and aggregation from various LD sources. In addition to individual organizations, LD union catalogues were also included. However, LD hubs, such as ISNI, OCLC WorldCat Entities, VIAF and Wikidata, were excluded. In total, six LD catalogues from LAMs were selected as subjects for examination.FindingsFirst, LD catalogues provide similar KG information through URI combination, and KGs also facilitate information serendipity, including social-document, intellectual, conceptual, spatial and temporal contexts and networks of corporate bodies, persons and families (CPFs). Second, LD catalogues have transformed the “seek first and browse later” paradigm into a “seek or browse” paradigm by refreshing the browsing function of traditional card catalogues with preview and new options to facilitate LD identification and discovery. Third, LD catalogues have refined keyword recommendation with the addition of the following fields: person’s title, CPF relationships, entity type and LD source. Lastly, a virtual union LD catalogue is offered.Research limitations/implicationsThe proposed checklist revealed the unique/improved functional features of LD catalogues, allowing further investigation and comparison. More cases from the fields of medicine, engineering science and so on will be required to make revisions to fine-tune the proposed checklist approach.Originality/valueTo the best of the author’s knowledge, this is the first study to propose a checklist of functional features for LD catalogues and examine what the results and features of LD catalogues have achieved and are supported by from ontologies across LAMs. The findings suggest that LD provides a viable alternative to catalogues. The proposed checklist and results pave the way for the future development of LD catalogues and next-generation catalogues and also provide a basis for the future study of LD catalogues from other fields to refine the proposed checklist.

General Physical Properties of Fermi Blazars

We study the general physical properties of Fermi blazars using the Fermi fourth source catalog data (4FGL-DR2). The quasi-simultaneous multiwavelength data of Fermi blazars are fitted by using the one-zone leptonic model to obtain some physical parameters, such as jet power, magnetic field, and Doppler factor. We study the distributions of the derived physical parameters as a function of black hole mass and accretion disk luminosity. The main results are as follows. (1) For a standard thin accretion disk, the jet kinetic power of most flat-spectrum radio quasars can be explained by the Blandford–Payne (BP) mechanism. However, the jet kinetic power of most BL Lacertae objects (BL Lacs) cannot be explained by either the Blandford–Znajek mechanism or the BP mechanism. The BL Lacs may have advection-dominated accretion flows surrounding their massive black holes. (2) After excluding the redshift, there is a moderately strong correlation between the jet kinetic power and jet radiation power and the accretion disk luminosity for Fermi blazars. These results confirm a close connection between jet and accretion. The jet kinetic power is slightly larger than the accretion disk luminosity for Fermi blazars. (3) There is a significant correlation between jet kinetic power and gamma-ray luminosity and radio luminosity for Fermi blazars, which suggests that gamma-ray luminosity and radio luminosity can be used to indicate the jet kinetic power.

Dynamics of Peri-Urban Land Use Structure in the Period 2000-2022 in Ilorin, Nigeria

Aim: To analyze the trend of peri-urban spatial growth structure between 2000 and 2022 in a rapidly urbanizing peri-urban area in Ilorin, Kwara State, Nigeria.
 Study Design: Longitudinal survey research.
 Place and Duration of Study: Eyenkorin, Kwara State 2022.
 Methodology: The spatial data was obtained from the Google Earth Engine Data Catalog, and machine learning algorithm was used to extract and classify three main land uses. Quantitative data was also simulated with the use of the Transitional Matrix that looked at the most likely path taken by the growth structure as it transitioned from one land use to another. The spatial growth structure was examined on a 12-year interval of 2000 – 2011; 2011 – 2022 and 2000 – 2022.
 Results: The study revealed that the present spatial structure of Eyenkorin (as at 2022) is majorly dominated by vegetation land/agricultural land Area 71.81 km2 (37.1%), followed by built-up land 79.77 km2 (33.4%) and bare land/ natural land 63.42 km2 (27.5%). The study revealed that the most dominant transition in the growth structure within the study time frame (2000 – 2022) is the built-up land which increased by 44.29 km2 (160.94%) and the most dominant loss is from vegetation land/agriculture land which decreased by 75.09 km2 (-48.49%).
 Conclusion: The findings of the study attests to the vulnerability of the non-built up land (agricultural land and bare land) that metamorphose into built-up land at the peripherals. In the next few years, it can be predicted that excessive unguided land development would have caught-up completely with the peripheral lands at the detriment of placing more need on the preservation of the environment. Government in developing countries should have a concrete development plan that actively controls the unhabitual expansion at the peripherals if sustainable land use and management will be achieved at the Peri-Urban.

Generative Adversarial Networks to incorporate the Training Image uncertainty in multiple-point statistics simulation

Multiple-point geostatistics (MPS) algorithms have been extensively used for geostatistical reservoir modeling. These techniques are known for building geostatistical simulations with curvilinear features, which are crucial for applications in flow simulation. One challenge in using MPS algorithms is obtaining a representative Training Image (TI). The result is that often one TI is used to condition the entire set of geostatistical simulations, and the TI uncertainty is disregarded. If the TI is uncertain, this uncertainty should be considered in the geostatistical simulations. Otherwise, the spatial uncertainty represented by the geostatistical simulations is underestimated. Incorporating the TI uncertainty requires building a data set or catalog of plausible TIs. In this context, we propose to use Generative Adversarial Networks (GANs) to build this catalog of TIs prior to the MPS simulation. Each TI generated by GAN is used to condition one realization built by the chosen MPS algorithm. The proposed workflow combines the strength of GAN to generate TIs with the strength of MPS algorithms to consider several sources of information to condition the simulations. A case study is shown, where the methodology is compared against the traditional MPS workflow, which uses a single TI. The results show that the proposed method successfully incorporated the TI uncertainty into the geostatistical workflow. The proposed method built numerical models with higher uncertainty and variability and, thus, provides a more realistic quantification of the space of uncertainty.

Data lake governance using IBM-Watson knowledge catalog

The strategic importance of data in decision-making is increasingly recognized, demanding efficient solutions such as data catalogs to ensure data governance and emphasize data interoperability, in accordance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. However, the usage of FAIR-compliant data catalogs lacks empirical studies due to its novelty. This study aims to promote the practical adoption of data catalogs as a means to manage the expanding data landscape. We differentiate our contribution by providing an empirical evaluation and comparison of IBM Watson Knowledge Catalog (IBM-WKC), a leading data cataloging solution, with two other prominent alternatives, Open-Metadata and Data-Galaxy, for extracting relevant information from data lakes containing heterogeneous data sources in their native formats. Our proposed methodology utilizes an innovative tool built on IBM-WKC for annotating collected documents. To evaluate our approach, we conducted experiments on a dataset of 100 documents sourced from scientific databases. Moreover, to assess our proposal, we compare the retrieved text to the appropriate interventions that use the original checklist. The results demonstrate the superiority of IBM-WKC over its competitors, showcasing its enhanced performance in addressing data cataloging challenges. Notably, the tested queries achieved an impressive accuracy, precision, and recall value of 96%. These findings highlight the reliability and alignment of IBM-WKC with the FAIR principles.

Zebrafish regulatory genomic resources for disease modelling and regeneration.

In the past decades, the zebrafish has become a disease model with increasing popularity owing to its advantages that include fast development, easy genetic manipulation, simplicity for imaging, and sharing conserved disease-associated genes and pathways with those of human. In parallel, studies of disease mechanisms are increasingly focusing on non-coding mutations, which require genome annotation maps of regulatory elements, such as enhancers and promoters. In line with this, genomic resources for zebrafish research are expanding, producing a variety of genomic data that help in defining regulatory elements and their conservation between zebrafish and humans. Here, we discuss recent developments in generating functional annotation maps for regulatory elements of the zebrafish genome and how this can be applied to human diseases. We highlight community-driven developments, such as DANIO-CODE, in generating a centralised and standardised catalogue of zebrafish genomics data and functional annotations; consider the advantages and limitations of current annotation maps; and offer considerations for interpreting and integrating existing maps with comparative genomics tools. We also discuss the need for developing standardised genomics protocols and bioinformatic pipelines and provide suggestions for the development of analysis and visualisation tools that will integrate various multiomic bulk sequencing data together with fast-expanding data on single-cell methods, such as single-cell assay for transposase-accessible chromatin with sequencing. Such integration tools are essential to exploit the multiomic chromatin characterisation offered by bulk genomics together with the cell-type resolution offered by emerging single-cell methods. Together, these advances will build an expansive toolkit for interrogating the mechanisms of human disease in zebrafish.

A Quick Look at the 3 GHz Radio Sky. II. Hunting for DRAGNs in the VLA Sky Survey

Active galactic nuclei (AGNs) can often be identified in radio images as two lobes, sometimes connected to a core by a radio jet. This multicomponent morphology unfortunately creates difficulties for source finders, leading to components that are (a) separate parts of a wider whole, and (b) offset from the multiwavelength cross identification of the host galaxy. In this work we define an algorithm, DRAGNhunter, for identifying double radio sources associated with AGNs (DRAGNs) from component catalog data in the first epoch Quick Look images of the high-resolution (≈3″ beam size) Very Large Array Sky Survey (VLASS). We use DRAGNhunter to construct a catalog of >17,000 DRAGNs in VLASS for which contamination from spurious sources is estimated at ≈11%. A “high-fidelity” sample consisting of 90% of our catalog is identified for which contamination is <3%. Host galaxies are found for ≈13,000 DRAGNs as well as for an additional 234,000 single-component radio sources. Using these data, we explore the properties of our DRAGNs, finding them to be typically consistent with Fanaroff–Riley class II sources and to allow us to report the discovery of 31 new giant radio galaxies identified using VLASS.

The Story of AWS Glue

AWS Glue is Amazon's serverless data integration cloud service that makes it simple and cost effective to extract, clean, enrich, load, and organize data. Originally launched in August 2017, AWS Glue began as an extract-transform-load (ETL) service designed to relieve developers and data engineers of the undifferentiated heavy lifting needed to load databases, data warehouses, and build data lakes on Amazon S3. Since then, it has evolved to serve a larger audience including ETL specialists and data scientists, and includes a broader suite of data integration capabilities. Today, hundreds of thousands of customers use AWS Glue every month. In this paper, we describe the use cases and challenges cloud customers face in preparing data for analytics and the tenets we chose to drive Glue's design. We chose early on to focus on ease-of-use, scale, and extensibility. At its core, Glue offers serverless Apache Spark and Python engines backed by a purpose-built resource manager for fast startup and auto-scaling. In Spark, it offers a new data structure --- DynamicFrames --- for manipulating messy schema-free semi-structured data such as event logs, a variety of transformations and tooling to simplify data preparation, and a new shuffle plugin to offload to cloud storage. It also includes a Hivemetastore compatible Data Catalog with Glue crawlers to build and manage metadata, e.g. for data lakes on Amazon S3. Finally, Glue Studio is its visual interface for authoring Spark and Python-based ETL jobs. We describe the innovations that differentiate AWS Glue and drive its popularity and how it has evolved over the years.

A Data Science Platform to Enable Time-domain Astronomy

SkyPortal is an open-source software package designed to discover interesting transients efficiently, manage follow-up, perform characterization, and visualize the results. By enabling fast access to archival and catalog data, crossmatching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, a SkyPortal-based platform has been operating at scale for >2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences across common front-end workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented application programming interface system. From back-end and front-end software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the reuse and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large language models to generate and surface source-level human-readable summaries automatically. With the imminent restart of the next generation of gravitational-wave detectors, SkyPortal now also includes dedicated multimessenger features addressing the requirements of rapid multimessenger follow-up: multitelescope management, team/group organizing interfaces, and crossmatching of multimessenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for newcomers to the field. This paper focuses on the detailed implementations, capabilities, and early science results that establish SkyPortal as a community software package ready to take on the data science challenges and opportunities presented by this next chapter in the multimessenger era.

New X-ray detections of magnetic period-bounce cataclysmic variables from XMM-Newton and SRG/eROSITA

Context. A great portion of the cataclysmic variable population, between 40% and 70%, is predicted to be made up of period-bouncers, systems with degenerate donors that have evolved past the period minimum. However, due to their intrinsic faintness, only a few of these systems have been observed and confidently identified so far. Aims. We have searched for X-ray emission as proof of accretion in order to confirm period-bounce cataclysmic variables. Methods. In this study, we used data from XMM-Newton and eROSITA on a pilot sample of three period-bounce candidates with a magnetic white dwarf, which are expected to exhibit stronger X-ray emission than non-magnetic systems due to more efficient conversion of matter accretion onto the white dwarf. Results. In a dedicated XMM-Newton observation of the period-bounce candidate SDSS J151415.65+074446.5 we discovered X-ray modulation at the binary orbital period confirming it as an accreting system. The X-ray light curve and the X-ray spectrum display characteristics of magnetic Polar-type systems, allowing us for the first time to determine the X-ray luminosity and mass accretion rate for this system. Catalog data from eROSITA on the Spektrum-Roentgen-Gamma satellite for V379 Vir and SDSS J125044.42+154957.4 enabled a first look into the X-ray behavior of period-bounce candidates with this new all-sky instrument. From the eROSITA measurements, the X-ray luminosity and mass accretion rate were determined for the first time for SDSS J125044.42+154957.4, and the earlier result for V379 Vir from XMM-Newton was confirmed. Conclusions. The three cataclysmic variables with a magnetic white dwarf and very low-mass donor studied in this work present evidence for X-ray emission at a similar level of LX [erg s−1] ≈ 1029, which, together with the detection of X-ray orbital modulation in two of them (i.e., V379 Vir and SDSS J151415.65+074446.5), unambiguously proves the presence of accretion in these systems. The detection of these period-bouncers at faint X-ray luminosity levels with the all-sky X-ray survey eROSITA offers new prospects for the identification of additional period-bouncers, providing impetus for theoretical studies of binary evolution.

Compilation of Regional Homogeneous Seismic Catalog for Identification of Tsunamigenic Zones in the Black Sea Region

Although tsunamis in the Black Sea are rare and less destructive, recently, their study has been the subject of interest due to the increasing concentration of population and infrastructure in low-lying coastal areas. This study aims to elucidate the spatial–temporal characteristics of earthquakes in the Black Sea region (27° E–42° E and 40° N–47° N) over a century to clarify the seismicity pattern further to be used for probabilistic seismic and tsunami hazard analysis. Significant volumes of seismic data from international and national databases were analyzed, and the results obtained from previous research were supplemented and expanded. Earthquakes over the period 1905–2022 from eight up-to-date seismic catalogs were used to compile a unified catalog after conversion to the moment magnitude scale Mw. The best-fit linear relationship between several magnitude scales and Mw was determined using the general orthogonal regression (GOR) and the least squares method (LSM). After the declustering procedure, the compiled catalog consists of 18,528 unique events. To assess the catalog data quality, the magnitude of completeness Mc was estimated for the entire catalog (1905–2022) and the so-called instrumental catalog (1977–2022). In addition, the spatial distribution of the completeness magnitude Mc and the recurrence b-plot slope in the Gutenberg–Richter distribution law were assessed using the goodness-of-fit and maximum likelihood methods from the instrumental catalog data. Finally, the most significant earthquakes within the Black Sea boundaries were estimated with their parameters and focal mechanisms. A possibility of the realization of strong quakes in the near future with tsunamigenic potential in the Black Sea region was concluded.

Revisiting Vrancea (Romania) Intermediate-Depth Seismicity: Some Statistical Characteristics and Seismic Quiescence Testing

Background: The intermediate-depth seismicity in the Vrancea region (Romania) is characterized by localized and persistent earthquake activity that culminates about two or three times in a century with the occurrence of a large event (M ≥ 6.5). Here we have revisited some important seismicity characteristics, using earthquake catalog data spanning two different time periods: 1960–1999 and 2005–2013. Methods: we have determined the b-value of the frequency-magnitude distribution of earthquakes, using a maximum likelihood procedure, and estimated the parameter β to quantify anomalous seismicity rate decreases and increases. Results: by using data from the first period, we have confirmed the existence of a decreased b-value in the deepest part of the seismogenic zone; by using data from the second period, we have statistically confirmed the seismic quiescence that preceded the occurrence of the 1977 M7.4 Vrancea earthquake. Conclusions: the decreased b-value has been interpreted either in terms of an increased lithostatic stress with depth or as an indicator of the depth range where the next major Vrancea earthquake may occur. The time variation of the seismicity parameter β may reveal anomalous seismic quiescence and increased earthquake rates that may precede the occurrence of large earthquakes.

The Translational Data Catalog - discoverable biomedical datasets

The discoverability of datasets resulting from the diverse range of translational and biomedical projects remains sporadic. It is especially difficult for datasets emerging from pre-competitive projects, often due to the legal constraints of data-sharing agreements, and the different priorities of the private and public sectors. The Translational Data Catalog is a single discovery point for the projects and datasets produced by a number of major research programmes funded by the European Commission. Funded by and rooted in a number of these European private-public partnership projects, the Data Catalog is built on FAIR-enabling community standards, and its mission is to ensure that datasets are findable and accessible by machines. Here we present its creation, content, value and adoption, as well as the next steps for sustainability within the ELIXIR ecosystem.

Business-Driven Data Recommender System: Design and Implementation

ABSTRACT Self-Service Business Intelligence (SSBI) increases decision-making reactivity of companies by facilitating the data use by non-IT experts. An important SSBI dimension is data querying where businesspeople create their own queries by reducing the technical complexity of formal languages like SQL. However, existing solutions ignore two other key challenges of data querying identified in the literature: the databases technical jargon and the data overload. In this paper, we propose, following the Design Science Research methodology, a framework (i.e. DatAssistant) to complement existing querying solutions with two new theoretical artifacts. The first bridges the semantic gap between technical databases and businesspeople via a business-aware ontology of the Data Warehouse mapped to the business Data Catalog. The second artifact filters data overload by mobilizing a hybrid recommender engine combining semantic systems and business rules. This paper then demonstrates the validity and applicability of the framework through its technical implementation in a real-world environment.

Study of the Long-term BVR c I c Photometric Variability of Eight PMS Stars in the Young Open Cluster Trumpler 37* *The Photometric Data will be Available in Electronic form Via CDS VizieR Online Data Catalogue.

This paper reports results from our long-term BV(RI) c photometric CCD observations of eight pre-main sequence stars collected from 2008 June to 2022 October. These stars are located in the young open cluster Trumpler 37, in the field of GM Cephei. The observational data indicate that all stars from our study exhibit variability in all-optical passbands, typical for young stars. In this paper, we describe and discuss the photometric behavior of the stars and the possible reasons for their variability. For two of the objects, we identified periodicity in their light variation.