Best practices for digitally constructing endocranial casts: examples from birds and their dinosaurian relatives.

<p>ORFEUS (Observatories and Research Facilities for European Seismology) is a non-profit foundation that promotes seismology in the Euro-Mediterranean area through the collection, archival and distribution of seismic waveform data, metadata and closely related products. The data and services are collected or developed at national level by more than 60 contributing Institutions in Pan-Europe and further developed, integrated, standardized, homogenized and promoted through ORFEUS. Among the goals of ORFEUS are: (a) the development and coordination of waveform data products; (b) the coordination of a European data distribution system, and the support for seismic networks in archiving and exchanging digital seismic waveform data; (c) the encouragement of the adoption of best practices for seismic network operation, data quality control and data management; (d) the promotion of open access to seismic waveform data, products and services for the broader Earth science community.  These goals are achieved through the development and maintenance of services targeted to a broad community of seismological data users, ranging from earth scientists to earthquake engineering practitioners. Two Service Management Committees (SMCs) are consolidated within ORFEUS devoted to managing, operating and developing (with the support of one or more Infrastructure Development Groups): (i) the European Integrated waveform Data Archive (EIDA; https://www.orfeus-eu.org/data/eida/); and (ii) the European Strong-Motion databases (SM; https://www.orfeus-eu.org/data/strong/). A new SMC is being formed to represent the community of European mobile pools. Products and services for computational seismologists are also considered for integration in the ORFEUS domain. ORFEUS services currently provide access to the waveforms acquired by ~ 10,000 stations in Pan-Europe, including dense temporary experiments, with strong emphasis on open, high-quality data. Contributing to ORFEUS data archives means long-term archival, state-of-the-art quality control, improved access and increased  usage. Access to data and products is ensured through state-of-the-art information and communications technologies, with strong emphasis on federated web services that considerably improve seamless user access to data gathered and/or distributed by ORFEUS institutions. The web services also facilitate the automation of downstream products. Particular attention is paid to adopting clear policies and licences, and acknowledging the crucial role played by data providers / owners, who are part of the ORFEUS community. There are significant efforts by ORFEUS participating Institutions to enhance the existing services to tackle the challenges posed by the Big Data Era, with emphasis on data quality, improved user experience, and implementation of strategies for scalability, high-volume data access and archival. ORFEUS data and services are assessed and improved through the technical and scientific feedback of a User Advisory Group (UAG), comprised of European Earth scientists with expertise encompassing a broad range of disciplines. All ORFEUS services are developed in coordination with EPOS and are largely integrated in the EPOS Data Access Portal. ORFEUS is one of the founding Parties and fundamental pillars of EPOS Seismology. This contribution presents the current products and services of ORFEUS and introduces the planned key future activities. We aim at stimulating Community feedback about the current and planned ORFEUS strategies.</p>

The use of digital phenotyping continues to expand across all fields of health. By collecting quantitative data in real-time using devices such as smartphones or smartwatches, researchers and clinicians can develop a profile of a wide range of conditions. Smartphones contain sensors that collect data, such as GPS or accelerometer data, which can inform secondary metrics such as time spent at home, location entropy, or even sleep duration. These metrics, when used as digital biomarkers, are not only used to investigate the relationship between behavior and health symptoms but can also be used to support personalized and preventative care. Successful phenotyping requires consistent long-term collection of relevant and high-quality data. In this paper, we present the potential of newly available, for approved research, opt-in SensorKit sensors on iOS devices in improving the accuracy of digital phenotyping. We collected opt-in sensor data over 1 week from a single person with depression using the open-source mindLAMP app developed by the Division of Digital Psychiatry at Beth Israel Deaconess Medical Center. Five sensors from SensorKit were included. The names of the sensors, as listed in official documentation, include the following: phone usage, messages usage, visits, device usage, and ambient light. We compared data from these five new sensors from SensorKit to our current digital phenotyping data collection sensors to assess similarity and differences in both raw and processed data. We present sample data from all five of these new sensors. We also present sample data from current digital phenotyping sources and compare these data to SensorKit sensors when applicable. SensorKit offers great potential for health research. Many SensorKit sensors improve upon previously accessible features and produce data that appears clinically relevant. SensorKit sensors will likely play a substantial role in digital phenotyping. However, using these data requires advanced health app infrastructure and the ability to securely store high-frequency data.

High-speed wireless communication is required to carrying out high-quality data. It can be realized by increasing data capacity with enlarging operational bandwidth. As we know, light has very large operational bandwidth with a drawback of large propagation loss in free-pace (air). Therefore, high-speed communication can be realized using light with short coverage area. Light has wide spectrum include visible light region. The visible light is used as a lamp for lighting in a room. The lamp with laser emitting diode (LED) is widely used due to its characteristics of low electric power consumption with bright light. Visible light for communication is promising for smart home. In here, we report our research activity to realize and demonstrate visible light communication with low-cost optoelectronic devices such as laser diodes and photo detectors. Demonstration of the short range visible light communication to carry out digital data is reported.

Large data sets covering large areas and time spans and composed of many different independent sources raise the question of the obtained degree of harmonization. The present study is an analysis of the harmonization with respect to the moment magnitude M w within the earthquake catalogue for central, northern, and northwestern Europe (CENEC). The CENEC earthquake catalogue (Grunthal et al., J Seismol, 2009) contains parameters for over 8,000 events in the time period 1000–2004 with magnitude M w ≥ 3.5. Only about 2% of the data used for CENEC have original M w magnitudes derived directly from digital data. Some of the local catalogues and data files providing data give M w, but calculated by the respective agency from other magnitude measures or intensity. About 60% of the local data give strength measures other than M w, and these have to be transformed by us using available formulae or new regressions based on original M w data. Although all events are thus unified to M w magnitude, inhomogeneity in the M w obtained from over 40 local catalogues and data files and 50 special studies is inevitable. Two different approaches have been followed to investigate the compatibility of the different M w sets throughout CENEC. The first harmonization check is performed using M w from moment tensor solutions from SMTS and Pondrelli et al. (Phys Earth Planet Inter 130:71–101, 2002; Phys Earth Planet Inter 164:90–112, 2007). The method to derive the SMTS is described, e.g., by Braunmiller et al. (Tectonophysics 356:5–22, 2002) and Bernardi et al. (Geophys J Int 157:703–716, 2004), and the data are available in greater extent since 1997. One check is made against the M w given in national catalogues and another against the M w derived by applying different empirical relations developed for CENEC. The second harmonization check concerns the vast majority of data in CENEC related to earthquakes prior to 1997 or where no moment tensor based M w exists. In this case, an empirical relation for the M w dependence on epicentral intensity (I 0) and focal depth (h) was derived for 41 master events, i.e., earthquakes, located all over central Europe, with high-quality data. To include also the data lacking h, the corresponding depth-independent relation for these 41 events was also derived. These equations are compared with the different sets of data from which CENEC has been composed, and the goodness of fit is demonstrated for each set. The vast majority of the events are very well or reasonably consistent with the respective relation so that the data can be said to be harmonized with respect to M w, but there are exceptions, which are discussed in detail.

ORFEUS (Observatories and Research Facilities for European Seismology, http://orfeus-eu.org/) is a non-profit foundation that promotes seismology in the Euro-Mediterranean area and beyond through the collection, archival and distribution of seismic waveform data, metadata, and associated services and products. The data and services are collected or developed at national level by more than 60 contributing Institutions. They are further developed, integrated, standardised, homogenised and promoted through ORFEUS. Among the goals of ORFEUS are: (a) the development and coordination of waveform data products; (b) the coordination of a European data distribution system, and the support for seismic networks in managing digital seismic waveform data; (c) the encouragement of the adoption of best practices for seismic network operation, data quality control and data management; (d) the promotion of open access to seismic waveform data, products and services for the broader solid Earth science community. These goals are achieved through the development and maintenance of data services targeted to a broad community of seismological data users, ranging from earth scientists to earthquake engineering practitioners. Three Service Management Committees (SMCs) are consolidated within ORFEUS, devoted to managing, operating and developing (with the support of one or more Infrastructure Development Groups): (i) the European Integrated waveform Data Archive (EIDA; https://www.orfeus-eu.org/data/eida/); (ii) the European Strong-Motion databases (SM; https://www.orfeus-eu.org/data/strong/); the European mobile instrument pools (https://orfeus-eu.org/data/mobile/). Products and services for computational seismologists are also considered for integration in the ORFEUS domain. ORFEUS services currently provide access to the waveforms acquired by ~ 24,000 stations, including dense temporary experiments (e.g. AdriaArray; https://orfeus.readthedocs.io/en/latest/adria_array_main.html), with strong emphasis on open, high-quality data. Contributing to ORFEUS data archives means benefitting from long-term archival, state-of-the-art quality control, improved access, increased usage, and community participation. Access to data and products is ensured through state-of-the-art information and communication technologies, with strong emphasis on federated web services that considerably improve seamless user access to data gathered and/or distributed by the various ORFEUS institutions. Web services also facilitate the automation of downstream products. Particular attention is paid to adopting clear policies and licenses, and acknowledging the crucial role played by data providers, who are part of the ORFEUS community. There are significant efforts by ORFEUS participating institutions to enhance the existing services to tackle the challenges posed by Big Data, with emphasis on data quality, improved user experience, and implementation of strategies (e.g. Cloud) for scalability, high-volume data access and archival. ORFEUS actively encourages interoperability and integration of multidisciplinary datasets in seismological and Earth Science workflows. ORFEUS data and services are assessed and improved through the technical and scientific feedback of a User Advisory Group (UAG), which comprises selected European Earth scientists with expertise on a broad range of disciplines. All ORFEUS services are developed in coordination with EPOS and are largely integrated in the EPOS Data Access Portal (https://www.ics-c.epos-eu.org/). ORFEUS is one of the founding Parties and a fundamental pillar of EPOS Thematic Core Service (TCS) for Seismology. ORFEUS and its community are actively involved in EC projects (http://www.orfeus-eu.org/organization/projects/), notably Geo-INQUIRE (https://www.geo-inquire.eu/) and DT-GEO (https://dtgeo.eu/) in 2024.

BackgroundDigital phenotyping provides passive monitoring of behavioural health but faces implementation challenges in translating complex multimodal data into actionable clinical insights. Digital navigators, healthcare staff who interpret patient data and relay findings to clinicians, provide a solution, but workforce limitations restrict scalability.ObjectiveThis study provides one of the first systematic evaluation of large language model performance in interpreting simulated psychiatric digital phenotyping data, establishing baseline accuracy metrics for this emerging application.MethodsWe evaluated GPT-4o and GPT-3.5-turbo across over 153 test cases covering various clinical scenarios, timeframes and data quality levels using simulated test datasets currently employed in training human digital navigators. Performance was assessed on the model’s capacity to identify clinical patterns relative to human digital navigation experts.FindingsGPT-4o demonstrated 52% accuracy (95% CI 46.5% to 57.6%) in identifying clinical patterns based on standard test cases, significantly outperforming GPT-3.5-turbo (12%, 95% CI 8.4% to 15.6%). When analysing GPT-4o’s performance across different scenarios, strongest results were observed for worsening depression (100%) and worsening anxiety (83%) patterns while weakest performance was seen for increased home time with improving symptoms (6%). Accuracy declined with decreasing data quality (69% for high-quality data vs 39% for low-quality data) and shorter timeframes (60% for 3-month data vs 43% for 3-week data).ConclusionsGPT-4o’s 52% accuracy in zero-shot interpretation of psychiatric digital phenotyping data establishes a meaningful baseline, though performance gaps and occasional hallucinations confirm human oversight in digital navigation tasks remains essential. The significant performance variations across models, data quality levels and clinical scenarios highlight the need for careful implementation.Clinical implicationsLarge language models could serve as assistive tools that augment human digital navigators, potentially addressing workforce limitations while maintaining necessary clinical oversight in psychiatric digital phenotyping applications.

A new national standard for digital multimedia broadcasting (DMB) has been launched in Korea to provide high-quality digital audio, video, and data broadcasting services to fixed, mobile, and portable receivers. We have developed a low-power portable terrestrial DMB (T-DMB) receiver, which can decode not only T-DMB video services but also various data services. In particular, it can simultaneously decode DMB video and data services in the same ensemble.

A traffic simulation of Kobe-city was carried out. In order to simulate an actual traffic flow, a road network was constructed utilizing a high-quality digital map data, and an origin-destination information of vehicles was estimated by a geographical population distribution data. The result obtained in this way was incompatible with the traffic census data due to the differences between the simulation and actual traffic, such as routing, OD information and so on. In order to improve the reproducibility of the traffic flow, the parameter search whose adjustable parameter was the speed limit of the road was conducted. This adjustment showed that reproducibility improves. Further improvement of the reproducibility needs to reconsideration of the routing algorithm.

Accurate prediction of drone motion within structured urban air corridors is essential for ensuring safe and efficient operations in Urban Air Mobility (UAM) systems. Although real-world Remote Identification (Remote ID) regulations require drones to broadcast critical flight information such as velocity, access to large-scale, high-quality broadcast data remains limited. To address this, this study leverages a Digital Twin (DT) framework to augment Remote ID spatio-temporal broadcasts, emulating the sensing environment of dense urban airspace. Using Remote ID data, we propose BiDGCNLLM, a hybrid prediction framework that integrates a Bidirectional Graph Convolutional Network (BiGCN) with Dynamic Edge Weighting and a reprogrammed Large Language Model (LLM, Qwen2.5–0.5B) to capture spatial dependencies and temporal patterns in drone speed trajectories. The model forecasts near-future speed variations in surrounding drones, supporting proactive conflict avoidance in constrained air corridors. Results from the AirSUMO co-simulation platform and a DT replica of the Cranfield University campus show that BiDGCNLLM outperforms state-of-the-art time series models in short-term velocity prediction. Compared to Transformer-LSTM, BiDGCNLLM marginally improves the R2 by 11.59%. This study introduces the integration of LLMs into dynamic graph-based drone prediction. It shows the potential of Remote ID broadcasts to enable scalable, real-time airspace safety solutions in UAM.

Seismic anisotropy near source region in subduction zones around Japan

3D city models are nowadays used in very different applications. Due to this, the commercial exchange and, thus, the demand for high quality data becomes more and more important. We describe a quality model that defines common parameters used for spatial quality measurement, especially when dealing with 3D city models. Therefore, we explore different representations of city models: the reality, the user's idea and the digital data set. A welldefined mathematical formalism which addresses the different quality parameters is presented. This formalism also helps to create algorithms for measurement and improvement of spatial data quality. The aim is to be able to define uniformed criteria which can be easily transformed into software. The implemented prototype serves as base for the evaluation in which we provide examples based on actual data sets using typical quality requirements.

This reference is for an abstract only. A full paper was not submitted for this conference. Abstract: The poster introduces a new style of rock-atlas which comprehensively documents the petrographic and petrophysical properties of reservoir rocks from a Giant Mid-Cretaceous carbonate reservoir in Oman. The atlas integrates diverse datasets from sedimentologists, petrophysicists and reservoir engineers in a specially designed one page per sample format to allow comprehensive and easy access to rock data. It provides an overview in digital format of available high quality data for easy visual screening and sits at the top of a digital data base which contains the individual data categories. This giant carbonate reservoir in northern Oman has been producing for over 40 years under primary depletion and secondary development schemes. While cores were taken from some 30 wells over the years, overall coverage and recovery did not provide an adequate data base for a comprehensive and quantitative evaluation of the porosity and permeability system. Consequently, an extensive coring campaign was executed in the years 2003 to 2005 which resulted in excellent overall recovery of above 90% (1810 meters of new cores were taken with about 1700 meters of core recovered). For the first time, not only complete coverage of all Natih formation stratigraphic intervals was achieved, but the availability of cores from multiple wells also provided lateral and some up-dip/down-dip control. This effort has generated extensive geological and petrophysical data and subsequent studies have revealed a multi-scale heterogeneity system. The starting point for analyzing the porosity and permeability system from cores was to systematically cut three plugs per meter of core for routine porosity/permeability and MICP measurements. This resulted in over 5100 routine core samples. Using the results of a subsequent core description and facies analysis a representative subset of 510 plugs was selected for further analysis using petrographic thin sections. Nearly all of these thin sections were subjected to additional porosity quantification using modal analysis (point counting of mineral components and porosity on thin sections) and digital image analysis. After a review of thin sections, MICP data and CT-scans, a further subset with permeability greater than 1mD was selected for special core analysis (SCAL). Porosity and permeability data derived from conventional core analysis on plugs, modal analysis (MA), image analysis (IA) and mercury injection capillary pressure (MICP) measurements are recorded for each sample. Substantial differences in porosity and permeability values have been observed from the different techniques used. Samples provide a representative, descriptive and numerical data set of depositional facies, facies associations and rock types covering the stratigraphy and lateral variations recognized from core descriptions. At this point, the data set has been reduced from an initial starting point of about 5100 potential measurements to some 231 representative samples. These were submitted to a comprehensive SCAL analysis program (relative permeability and capillary pressure by centrifuge for oil-water and gas-oil, wettability (Amott), wettability (USBM), overburden stress, saturation exponent "n", cementation exponent "m" and NMR). Results from the extensive SCAL program were received from the vendor and incorporated in this atlas. However, failure during SCAL experiments (sample collapse and/or erratic data) reduced the number of samples with quality controlled and reliable SCAL data further to 166. While a reduction from a starting point of 5100 plug samples down to 166 samples might sound excessive, it is actually an unusually large and high quality data set not commonly available in carbonate reservoirs. The atlas combines the following data on to one single A3 size page format for each sample: sample source data with facies and rock type information, thin section description, thin section photomicrograph, CT-scan, porosity and permeability values from different measuring techniques, porosity-permeability cross-plot, MICP plots, modal analysis data, SCAL plots, SCAL QC status and SCAL numerical data. By integrating data from different sources into one comprehensive document, this atlas has provided subsurface engineers with an easily accessible reference document which increases understanding of the reservoir properties and heterogeneity and safeguards an expensive data set for future use. Example from 1 sample is provided below.

Abstract. There are many methods to express topographical features of ground surface. In which, contour map has been the traditional method and along with development of digital data, surface model such as shaded relief map has been using for ground surface expression. Recently, data acquisition has been developed very much quick, demanding more advanced visualization method to express ground surface so as to effectively use the high quality data. In this study, the authors using the Red Relief Image Map (RRIM, Chiba et al., 2008) to express ground surface visualization for a variety of map scales. The authors used 30 m mesh data of SRTM to show the topographical features of western Mongolian and micro-topographical features of ground surface in tectonically active regions of Japan. The results show that, compared to traditional and other similar methods, the RRIM can express ground surface more precisely and 3-dimensionally, suggested its advanced usage for many fields of topographical visualization.

BackgroundPrior studies indicate that older members of LGBTQ+ communities have specific health provision and health information needs related to coping with COVID-19, its long-term effects, and the social and economic impact of the pandemic. This study addresses the issue of a lack of timely, complete, and high-quality data about this population’s healthcare and healthcare information needs and behaviors. Recognizing also that this is a diverse population made up of multiple communities and identities with different concerns and experiences, this research seeks to develop and refine a method that can provide additional nuanced data and insights that can support improved and more closely targeted health interventions and online information provision.MethodsWe use computational discourse analysis, which is based on NLP algorithms, to build and analyze a digital corpus of online search results containing rich, wide-ranging content such as quotes and anecdotes from older members of LGBTQ+ communities as well as practitioners, advice, and recommendations from policymakers and healthcare experts, and research outcomes. In our analysis, we develop and apply an innovative disparities and resilience (D&R) framework to identify external and internal perspectives and understand better disparities and resilience as they pertain to this population.ResultsResults of this initial study support previous research that LGBTQ+ elders experience aggravated health and related social-economic disparities in comparison to the general population of older people. We also find that LGBTQ+ elders leverage individual toughness and community closeness, and quickly adapt mentally and technologically, despite inadequate social infrastructure for sharing health information and elders’ often low social economic status. The methods used therefore are able to surface distinctive resilience in the face of distinctive disparities.ConclusionsOur study provides evidence that methodological innovation in gathering and analyzing digital data relating to overlooked, disparately affected, and socially and economically marginalized intersectional communities such as LGBTQ+ elders can result in increased external and self-knowledge of these populations. Specifically, it demonstrates the potential of computational discourse analysis to surface hidden and emerging issues and trends relating to a multi-faceted population that has important concerns about public exposure in highly timely and automated ways. It also points to the potential benefits of triangulating data gathered through this approach with data gathered through more traditional mechanisms such as surveys and interviews.Trial registrationNot Applicable.

California Digital Library (CDL) and Dryad recently announced a partnership to address researcher needs and to “move the needle” on digital data adoption throughout the scholarly research community by working together to understand and respond to researcher needs for high-quality scientific data publishing infrastructures.