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Background Data papers have emerged as a powerful instrument for open data publishing, obtaining credit, and establishing priority for datasets generated in scientific experiments. Academic publishing improves data and metadata quality through peer review and increases the impact of datasets by enhancing their visibility, accessibility, and reusability. Objective We aimed to establish a new type of article structure and template for omics studies: the omics data paper. To improve data interoperability and further incentivize researchers to publish well-described datasets, we created a prototype workflow for streamlined import of genomics metadata from the European Nucleotide Archive directly into a data paper manuscript. Methods An omics data paper template was designed by defining key article sections that encourage the description of omics datasets and methodologies. A metadata import workflow, based on REpresentational State Transfer services and Xpath, was prototyped to extract information from the European Nucleotide Archive, ArrayExpress, and BioSamples databases. Findings The template and workflow for automatic import of standard-compliant metadata into an omics data paper manuscript provide a mechanism for enhancing existing metadata through publishing. Conclusion The omics data paper structure and workflow for import of genomics metadata will help to bring genomic and other omics datasets into the spotlight. Promoting enhanced metadata descriptions and enforcing manuscript peer review and data auditing of the underlying datasets brings additional quality to datasets. We hope that streamlined metadata reuse for scholarly publishing encourages authors to create enhanced metadata descriptions in the form of data papers to improve both the quality of their metadata and its findability and accessibility. [ABSTRACT FROM AUTHOR]

The emergence of massive datasets exploring the multiple levels of molecular biology has made their analysis and knowledge transfer more complex. Flexible tools to manage big biological datasets could be of great help for standardizing the usage of developed data visualizations and integration methods. Business intelligence (BI) tools have been used in many fields as exploratory tools. They have numerous connectors to link numerous data repositories with a unified graphic interface, offering an overview of data and facilitating interpretation for decision makers. BI tools could be a flexible and user-friendly way of handling molecular biological data with interactive visualizations. However, it is rather uncommon to see such tools used for the exploration of massive and complex datasets in biological fields. We believe that two main obstacles could be the reason. Firstly, we posit that the way to import data into BI tools are not compatible with biological databases. Secondly, BI tools may not be adapted to certain particularities of complex biological data, namely, the size, the variability of datasets and the availability of specialized visualizations. This paper highlights the use of five BI tools (Elastic Kibana, Siren Investigate, Microsoft Power BI, Salesforce Tableau and Apache Superset) onto which the massive data management repository engine called Elasticsearch is compatible. Four case studies will be discussed in which these BI tools were applied on biological datasets with different characteristics. We conclude that the performance of the tools depends on the complexity of the biological questions and the size of the datasets. [ABSTRACT FROM AUTHOR]

According to Menger's theorem, connectivity and edge connectivity are closely related to node-disjoint paths and edge-disjoint paths, respectively. Node- and edge-disjoint paths can keep the effective transmission of information and confidentiality. Therefore, node-disjoint paths and edge-disjoint paths are two important parameters to measure the reliability of a network. For a faulty node (resp. edge) set |$S\subset V$| (resp. |$S\subset E$|⁠), a connected graph |$G=(V,E)$| is |$S$| -strongly Menger-node-connected (resp. Menger-edge-connected) if any two distinct nodes |$x$| and |$y$| in |$G-S$| are connected by |$\min \{\deg _{G-S}(x),\deg _{G-S}(y)\}$| internally node-disjoint (resp. edge-disjoint) paths in |$G-S$|⁠ , where |$\deg _{G-S}(x)$| and |$\deg _{G-S}(y)$| are the degrees of |$x$| and |$y$| in |$G-S$|⁠ , respectively. And most of the previous studies are based on networks that are triangle-free. In this paper, we consider the strongly Menger (edge) connectedness of a class of |$r$| -dimensional recursive networks RNCG |$G_{r}$| with triangles. Moreover, we show that |$G_{r}$| is |$(rl-l-1)$| -strongly Menger-node-connected. And then we show that |$G_{r}$| is |$[k+(r-1)l-2]$| -strongly Menger-edge-connected of order 1 and |$[2k+2(r-1)l-6]$| -strongly Menger-edge-connected of order 2. Since the class of |$r$| -dimensional recursive networks RNCG |$G_{r}$| includes not only data center networks DCell and generalized DCell but also interconnection network dragonfly, etc. all the results are appropriate for these networks. [ABSTRACT FROM AUTHOR]

This study aims to review the open science (OS) policy documents, identify their subject areas, and distinguish the topics of OS support policies in seven European countries, providing a platform for practical cooperation between countries in science popularization. With a qualitative–inductive approach, all pertinent policy documents in OS were collected through documentary study, and thematic analysis was conducted to identify OS policies for each country. Finally, forty-six policy documents extracted up to December 2020 were thematically analyzed through a qualitative–inductive case study. All selected countries had developed OS policies, and these supportive policies were generally related to the three dimensions of 'open input, open process, and open output'. In 'open input', recommendations for the performance of research data repositories, as well as management criteria, are considered. Most countries adopted 'open output' protectionist policies. Multiple policies in the 'open process' indicate the need for an appropriate OS platform. [ABSTRACT FROM AUTHOR]

Motivation The scale of omics research presents many obstacles to full sharing and access to analysis results. Current publication models impose limits on the number of pages and figures, requiring careful preparation and selection of content. At the same time, depositing data in open repositories significantly shifts the burden of access and reproduction to readers, who may include people who are not programmers or analysts. Results We introduce shinyExprPortal, an R package that implements omics web portals with minimal coding effort. The portals allow exploration of transcriptomic or proteomic expression data and phenotypes, showcasing results of various types of analysis including differential expression, co-expression and pathways analysis. The integration with bioinformatics workflows enables researchers to focus on their results and share findings using interactive and publication-quality plots. Availability and implementation The shinyExprPortal package is available to download and install from CRAN and https://github.com/C4TB/shinyExprPortal. [ABSTRACT FROM AUTHOR]

Knowledge of the neutron spectra of reference fields is very important for calibration purposes. This paper presents new calculations of the neutron spectra and dosimetric parameters of a D2O moderated 252Cf source assembly used to produce a neutron reference field at the Physikalisch-Technische Bundeanstalt (PTB), based on recent 252Cf fission neutron spectrum data and conversion coefficients for operational radiation protection units recommended by the International Commission on Radiological Protection (ICRP) report 57. Neutron fluence and dose calculations were carried out using a detailed simulation model of the source assembly implemented using MCNP6 and the cross-section data library ENDF/B-VIII.0. The PTB moderator was compared with the International Organization for Standardization, ISO 8529 model and to previous calculations done at PTB. The results show differences to the previous calculations performed at PTB of the order of 5% and a slight discrepancy with the ISO 8529 moderator model regarding the values of the operational quantities. [ABSTRACT FROM AUTHOR]

The Ocean provides benefits of free cooling for cloud computing platforms. However, the use of the ocean for hosting cloud platforms needs to consider three challenges. The first challenge is identifying suitable underwater locations for siting underwater data centres. The second is designing a low-cost method for acquiring underwater data centres. The third is designing a mechanism ensuring that the use of the ocean for hosting data centres is scalable. This paper proposes the intelligent marine compute locator (IMCL) to identify suitable locations for siting underwater data centres. The proposed IMCL determines the specific heat capacity of different ocean locations at multiple epochs. In addition, the conversion of end-of-life vessels into artificial reefs that host open-source disaggregated hardware computing payload is proposed to reduce acquisition costs. The use of disaggregated architecture enables multiple cloud service providers to use limited ocean locations. The formulated metrics are the power usage effectiveness (PUE) and ocean space utilization (OSU). Simulations show that the use of disaggregated design architecture instead of non-disaggregated architecture (existing mechanism) enhances the PUE and OSU by 4.4 and 16.4% on average, respectively. [ABSTRACT FROM AUTHOR]

The peptide-like molecule cyanoformamide (NCCONH2) is the cyano (CN) derivative of formamide (NH2CHO). It is known to play a role in the synthesis of nucleic acid precursors under prebiotic conditions. In this paper, we present a tentative detection of NCCONH2 in the interstellar medium with the Atacama Large Millimeter/submillimeter Array (ALMA) archive data. 10 unblended lines of NCCONH2 were seen around 3σ noise levels toward Sagittarius B2(N1E), a position that is slightly offset from the continuum peak. The column density of NCCONH2 was estimated to be 2.4 × 1015 cm−2, and the fractional abundance of NCCONH2 toward Sgr B2(N1E) was 6.9 × 10−10. The abundance ratio between NCCONH2 and NH2CHO is estimated to be ∼0.01. We also searched for other peptide-like molecules toward Sgr B2(N1E). The abundances of NH2CHO, CH3NCO and CH3NHCHO toward Sgr B2(N1E) were about 1/10 of those toward Sgr B2(N1S), while the abundance of CH3CONH2 was only 1/20 of that toward Sgr B2(N1S). [ABSTRACT FROM AUTHOR]

In coreless filament winding, resin-impregnated fibre filaments are wound around anchor points without an additional mould. The final geometry of the produced part results from the interaction of fibres in space and is initially undetermined. Therefore, the success of large-scale coreless wound fibre composite structures for architectural applications relies on the reciprocal collaboration of simulation, fabrication, quality evaluation, and data integration domains. The correlation of data from those domains enables the optimization of the design towards ideal performance and material efficiency. This paper elaborates on a computational co-design framework to enable new modes of collaboration for coreless wound fibre-polymer composite structures. It introduces the use of a shared object model acting as a central data repository that facilitates interdisciplinary data exchange and the investigation of correlations between domains. The application of the developed computational co-design framework is demonstrated in a case study in which the data are successfully mapped, linked, and analysed across the different fields of expertise. The results showcase the framework's potential to gain a deeper understanding of large-scale coreless wound filament structures and their fabrication and geometrical implications for design optimization. [ABSTRACT FROM AUTHOR]

Motivation Probabilistic Identification of bacterial essential genes using transposon-directed insertion-site sequencing (TraDIS) data based on Tn5 libraries has received relatively little attention in the literature; most methods are designed for mariner transposon insertions. Analysis of Tn5 transposon-based genomic data is challenging due to the high insertion density and genomic resolution. We present a novel probabilistic Bayesian approach for classifying bacterial essential genes using transposon insertion density derived from transposon insertion sequencing data. We implement a Markov chain Monte Carlo sampling procedure to estimate the posterior probability that any given gene is essential. We implement a Bayesian decision theory approach to selecting essential genes. We assess the effectiveness of our approach via analysis of both simulated data and three previously published Escherichia coli , Salmonella Typhimurium and Staphylococcus aureus datasets. These three bacteria have relatively well characterized essential genes which allows us to test our classification procedure using receiver operating characteristic curves and area under the curves. We compare the classification performance with that of Bio-Tradis, a standard tool for bacterial gene classification. Results Our method is able to classify genes in the three datasets with areas under the curves between 0.967 and 0.983. Our simulated synthetic datasets show that both the number of insertions and the extent to which insertions are tolerated in the distal regions of essential genes are both important in determining classification accuracy. Importantly our method gives the user the option of classifying essential genes based on the user-supplied costs of false discovery and false non-discovery. Availability and implementation An R package that implements the method presented in this paper is available for download from https://github.com/Kevin-walters/insdens. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

This paper argues that frequently updated data on the nature of residential moves and the circumstances of movers in the United Kingdom are insufficient for many research purposes. Accordingly, we develop previous research reported in this Journal to re‐purpose consumer and administrative data in order to develop annual estimates of residential mobility between all UK neighbourhoods. We use a unique digital corpus of linked individual and household‐level consumer registers compiled by the UK Consumer Data Research Centre, comprising over 143 million unique address records pertaining to the entire UK adult population over the period 1997–2016. We describe how records pertaining to individuals vacating a property can be assigned to their most probable residential destination, based on novel methods of matching names, assessing household composition, and using information on the date and probable distance of residential moves. We believe that the results of this analysis contribute highly granular, frequently updated estimates of residential moves that can be used to chart population‐wide outcomes of residential mobility and migration behaviour, as well as the socio‐spatial characteristics of the sedentary population. [ABSTRACT FROM AUTHOR]

Detection of free precession is very important for analysing the internal structure of neutron stars. So far, because of the interference of the accretion process, no feasible method has been proposed to detect the precession of accreting neutron stars in both theory and observations. Based on the analysis of archive data from Chandra and the Neutron Star Interior Composition ExploreR (NICER) of the ultra-compact X-ray binary system 4U 1820–30, we find that the energy spectra have a stable sinusoidal bi-directional oscillation period near 1000 s, no matter which state the X-ray binary system is in. After we fit the energy spectra and carry out Fourier decomposition of the fitting parameters, we find that this period is more steadily emitted from the neutron star. We discuss the possible origin of this period and conclude that the period is most likely the free precession period of the neutron star in 4U 1820–30. Its nutation can result in the seesaw-like periodical bi-directional oscillation we find in this paper. [ABSTRACT FROM AUTHOR]

This paper investigates a novel micro-channel flat separated loop heat pipe system for cooling the information technology equipment in the data centres through theoretical and experimental analysis and by assessing the impact of the inlet water temperature on system performance. A computer model is developed to simulate the steady-state performance of the micro-channel flat separated loop heat pipe system. After comparing the experimental and modelling results, the new and conventional system under the same working conditions, the model is validated yielding high accuracy in predicting the performance of the micro-channel flat separated loop heat pipe system with recorded error being limited to 2.16–8.97%. The new system has better performance than the conventional system. Under the operating conditions of heat load intensity of 1,000 W/m2, water flow rate of 0.28 m3/h, refrigerant filling rate of 30%, ambient air temperature of 26°C, and evaporator and condenser height difference of 0.8 m, the performance of the system has been explored at inlet temperature from 15 to 24°C with increments of 3°C. The system's averaged heat transfer efficiency was found to decrease with the increase in inlet temperature. This research provides valuable insight into the data centre information technology equipment cooling, which is of great significance for energy saving and environmentally friendly operation of data centres. [ABSTRACT FROM AUTHOR]

With the continuous development of space and sensor technologies during the last 40 years, ocean remote sensing has entered into the big-data era with typical five-V (volume, variety, value, velocity and veracity) characteristics. Ocean remote-sensing data archives reach several tens of petabytes and massive satellite data are acquired worldwide daily. To precisely, efficiently and intelligently mine the useful information submerged in such ocean remote-sensing data sets is a big challenge. Deep learning—a powerful technology recently emerging in the machine-learning field—has demonstrated its more significant superiority over traditional physical- or statistical-based algorithms for image-information extraction in many industrial-field applications and starts to draw interest in ocean remote-sensing applications. In this review paper, we first systematically reviewed two deep-learning frameworks that carry out ocean remote-sensing-image classifications and then presented eight typical applications in ocean internal-wave/eddy/oil-spill/coastal-inundation/sea-ice/green-algae/ship/coral-reef mapping from different types of ocean remote-sensing imagery to show how effective these deep-learning frameworks are. Researchers can also readily modify these existing frameworks for information mining of other kinds of remote-sensing imagery. [ABSTRACT FROM AUTHOR]

Recording a stellar occultation is one powerful method that gives direct information about the physical properties of the occulting Solar system object. In order to obtain reliable and accurate results, simultaneous observations from different locations across-track of the projected path are of great importance. However, organizing all the observing stations, aggregating, and analysing the data is time-consuming and not that easy. We have developed a web portal named Occultation Portal (OP) to manage all those occultation observation campaigns from a central server. With this portal, the instrumental and observational information of all observers participating in a stellar occultation campaign and the concerned data are archived systematically in a standard format. The researchers can then visualize the archived data on an event basis. The investigators can also extract the light curve for each data set with the added reduction pipeline to the portal base. This paper describes in detail the portal structure and the developed features. [ABSTRACT FROM AUTHOR]

Regional seismic networks may and in some cases need to be used to monitor teleseismic or network-outside events. For detecting and localizing teleseismic events automatically and reliably in this case, in this paper we present a novel progressive association algorithm for teleseismic signals recorded by a regional seismic network. The algorithm takes triangle station arrays as the starting point to search for P waves of teleseismic events progressively by that, as detections from different stations actually are from the same teleseismic event, their arrival times should be linearly related to the average slowness vector with which the signal propagates across the network, and the slowness of direct teleseismic P wave basically is different from other major seismic phases. We have tested this algorithm using data recorded by Xinjiang Seismic Network of China (XJSN) for 16 d. The results show that the algorithm can effectively and reliably detect and localize earthquakes outside of the network. For the period of the test data, as all mb 4.0+ events with c < 30° and all mb 4.5+ events with c < 60° referring to the International Data Center-Reviewed Event Bulletin (IDC REB) were detected, where c is the epicentral distance relative to the network's geographical centre, the rate of false events only accounted for 2.4 per cent, suggesting that the new association algorithm has good application prospect for situations when regional seismic networks need to be used to monitor teleseismic events. [ABSTRACT FROM AUTHOR]

Virtualization is an important enabling technology for many large data centers and cloud computing environments, and virtual machine (VM) migration plays a key role in the load balancing among the hosts of the data center. However, the existing load balancing schemes based on VM migration have serious influence on the fault-tolerant level of the services in the data center, and thus the reliability of the services cannot be guaranteed. In this paper, a novel guaranteeing fault-tolerant requirement load balancing scheme (GFTLBS) is proposed. GFTLBS migrates the VMs to balance the load without violating the fault-tolerant requirement of all services. The simulation results show that the scheme can guarantee the fault-tolerant requirements of all services while keeping the load balance. [ABSTRACT FROM AUTHOR]

With the rapid development of cloud computing, many large-scale data centers are being built to provide increasingly popular online application services. This leads to the proposal of data center networks (DCNs) supporting millions of servers with high-network capacity by using only commodity switches. The k-dimensional DCell with n-port switches and tk,n servers, Dk,n, has been proposed as a model for a large-scale DCN with a server-centric structure. In this paper, we study the diagnosability and the g-good-neighbor conditional diagnosability of Dk,n. We prove that: (i) Dk,n is (n + k - 1)-diagnosable under the precise diagnosis strategy and (2k + n - 2)/(2k + n - 2)- diagnosable under the pessimistic diagnosis strategy; (ii) the g-good-neighbor conditional diagnosabilities of Dk,n under the PMC model and the MM* model are both (g + 1)k + n - 1 (resp. (n + k - g)tg-n+1,n - 1) with 0 ≤ g ≤ n - 1 (resp. n ≤ g ≤ n + k - 2), which is almost (g + 1) (resp. tg-n+1,n) times of the traditional diagnosability. These results provide a quantitative evaluation for a large-scale DCN's reliability and availability. [ABSTRACT FROM AUTHOR]

The article titled "Erratum: Doppler confirmation of TESS planet candidate TOI1408.01: grazing transit and likely eccentric orbit" was published in the Monthly Notices of the Royal Astronomical Society: Letters in 2023. The authors of the paper discovered that there were multiple duplicated transit lightcurves in their analysis due to a mistake. They reanalyzed the correct dataset and found that there were mostly insignificant changes to the results, with the orbital period being the most notable change. The corrected table is provided in the article. [Extracted from the article]

Open Science has gained momentum over the past decade, and embracing that, GigaScience , from its launch a decade ago has aimed at pushing scientific publishing beyond just making articles open access toward making the entire research process open and available as an embedded part of the publishing process. Before the journal's launch in July 2012, the editors aimed to make publishing more than a narrative presentation of work already done into a fully open process. Major milestones include creating our own data repository, embracing FAIR principles, promoting and integrating preprints, and working with other platforms to contribute to a 21st century publishing infrastructure. Almost 10 years after GigaScience 's launch, UNESCO published its Open Science Recommendations. With these in mind, looking back, we are happy to have contributed in various ways to UNESCO's aim to "foster a culture of Open Science and aligning incentives for Open Science" from the very beginning, and, more, to use those recommendations to guide our path into the future: to truly embrace the full spectrum of information, tools, and access to Open Science for all participants in scientific endeavours. [ABSTRACT FROM AUTHOR]

This paper is the first to systematically analyze the characteristics of voter turnout in Korea's democratic national elections, which began with the country's transition from authoritarian to democratic rule in 1987. The paper attempts to find out who voted, and why, in the national elections held between 1992 and 2002. The present inquiry uses survey data collected by the Korean Social Science Data Center. Major findings suggest that Koreans were affected more by socioeconomic, attitudinal, regional, and election year factors in their decision to vote than by the state of the economy or institutional factors. Furthermore, the findings indicate that Korean voter turnout, which has been marked by several years of decline, will likely continue declining. [ABSTRACT FROM AUTHOR]

In this paper, we present results from a radio–optical study of the galaxy populations of the galaxy clusters Abell 1300 and MACS J1931.8−2634, a merger and a relaxed system respectively both located at z ∼ 0.3, aimed at finding evidence of merger-induced radio emission. Radio observations are taken at 1.28 GHz with the MeerKAT interferometer during its early-stage commissioning phase, and combined with archive optical data. We generated catalogues containing 107 and 162 radio sources in the A 1300 and MACS J1931.8−2634 cluster fields, respectively, above a 0.2 mJy threshold and within a 30 arcmin radius from the cluster centre (corresponding to 8.1 and 8.8 Mpc, respectively). By cross-correlating the radio and optical catalogues, and including spectroscopic information, nine and six sources were found to be cluster members and used to construct the radio luminosity functions, respectively, for both clusters. The comparison of the radio source catalogues between the two cluster fields leads to a marginal difference, with a 2σ statistical significance. We derived the radio luminosity function at 1.28 GHz in both clusters, in the power range of |$22.81 \lt \rm {log~\mathit{ P}_{1.28~GHz}~(W\,Hz^{-1})} \lt 25.95$|⁠ , and obtained that in A 1300 the radio luminosity function averaged over the full radio power interval is only 3.3 ± 1.9 times higher than the MACS J1931.8−2634 one, suggesting no statistical difference in their probability to host nuclear radio emission. We conclude that, at least for the two clusters studied here, the role of cluster mergers in affecting the statistical properties of the radio galaxy population is negligible. [ABSTRACT FROM AUTHOR]

Background: Many bioinformatics tools use reference data, such as genome assemblies or sequence databanks. Galaxy offers multiple ways to give access to this data through its web interface. However, the process of adding new reference data was customarily manual and time consuming, even more so when this data needed to be indexed in a variety of formats (e.g. Blast, Bowtie, BWA, or 2bit). BioMAJ is a widely used and stable software that is designed to automate the download and transformation of data from various sources. This data can be used directly from the command line, in more complex systems, such as Mobyle, or by using a REST API. Findings: To ease the process of giving access to reference data in Galaxy, we have developed the BioMAJ2Galaxy module, which enables the gap between BioMAJ and Galaxy to be bridged. With this module, it is now possible to configure BioMAJ to automatically download some reference data, to then convert and/or index it in various formats, and then make this data available in a Galaxy server using data libraries or data managers. Conclusions: The developments presented in this paper allow us to integrate the reference data in Galaxy in an automatic, reliable, and diskspace-saving way. The code is freely available on the GenOuest GitHub account (https://github.com/genouest/biomaj2galaxy). [ABSTRACT FROM AUTHOR]

Background: Many bioinformatics tools use reference data, such as genome assemblies or sequence databanks. Galaxy offers multiple ways to give access to this data through its web interface. However, the process of adding new reference data was customarily manual and time consuming, even more so when this data needed to be indexed in a variety of formats (e.g. Blast, Bowtie, BWA, or 2bit). BioMAJ is a widely used and stable software that is designed to automate the download and transformation of data from various sources. This data can be used directly from the command line, in more complex systems, such as Mobyle, or by using a REST API. Findings: To ease the process of giving access to reference data in Galaxy, we have developed the BioMAJ2Galaxy module, which enables the gap between BioMAJ and Galaxy to be bridged. With this module, it is now possible to configure BioMAJ to automatically download some reference data, to then convert and/or index it in various formats, and then make this data available in a Galaxy server using data libraries or data managers. Conclusions: The developments presented in this paper allow us to integrate the reference data in Galaxy in an automatic, reliable, and diskspace-saving way. The code is freely available on the GenOuest GitHub account (https://github.com/genouest/biomaj2galaxy). [ABSTRACT FROM AUTHOR]

Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. In this paper we address the generation of covariance data in the resonance region done with the computer code SAMMY. SAMMY is used in the evaluation of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on the generalised least-squares formalism (Bayesian theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, it provides the resonance parameter covariances. For resonance parameter evaluations where there are no resonance parameter covariance data available, the alternative is to use an approach called the 'retroactive' resonance parameter covariance generation. In this paper, we describe the application of the retroactive covariance generation approach for the gadolinium isotopes. [ABSTRACT FROM AUTHOR]

In this paper, we analyse how to extract the physical properties from the GALANTE photometry of a stellar sample. We propose a direct comparison between the observational colours (photometric bands normalized to the 515 nm central wavelength) and the synthetic colours derived from different stellar libraries. We use the reduced χ2 as the figure of merit for selecting the best fitting between both colour sets. The synthetic colours of the Next Generation Spectral Library (NGSL) provide a valuable sample for testing the uncertainty and precision of the stellar parameters derived from observational data. Reddening, as an extrinsic stellar physical parameter becomes a crucial variable for accounting for the errors and bias in the derived estimates: the higher the reddenings, the larger the errors and uncertainties in the derived parameters. NGSL colours also enable us to compare different theoretical stellar libraries for the same set of physical parameters, where we see how different catalogues of models can provide very different solutions in a, sometimes, non-linear way. This peculiar behaviour makes us to be cautious with the derived physical parameters obtained from GALANTE photometry without previous detailed knowledge of the theoretical libraries used to this end. In addition, we carry out the experiment of deriving physical stellar parameters from some theoretical libraries, using some other libraries as observational data. In particular, we use the Kurucz and Coelho libraries, as input observational data, to derive stellar parameters from Coelho + TLUSTY and Kurucz + TLUSTY stellar libraries, respectively, for different photometric errors and colour excesses. [ABSTRACT FROM AUTHOR]

MEGARA (Multi Espectrógrafo en GTC de Alta Resolución para Astronomía) is an optical (3650–9750 Å), fibre-fed, medium-high spectral resolution (R = 6000, 12 000 and 20 000) instrument for the Gran Telescopio CANARIAS (GTC) 10.4-m telescope, commissioned in the summer of 2017, and currently in operation. The scientific exploitation of MEGARA requires a stellar spectra library to interpret galaxy data and to estimate the contribution of the stellar populations. In this paper, we introduce the MEGARA-GTC spectral library, detailing the rationale behind the building of this catalogue. We present the spectra of 97 stars (21 individual stars and 56 members of the globular cluster M15, which are both subsamples taken during the commissioning runs, and 20 stars from our ongoing GTC Open-Time programme). The spectra have R  = 20 000 in the HR-R and HR-I set-ups, centred at 6563 and 8633 Å, respectively. We describe the procedures to reduce and analyse the data. Then, we determine the best-fitting theoretical models to each spectrum through a χ2 minimization technique, to derive the stellar physical parameters, and we discuss the results. We have also measured some absorption lines and indices. Finally, we introduce our project to complete the library and the data base in order to make the spectra available to the community. [ABSTRACT FROM AUTHOR]

We present the first release of GTC OSIRIS broad-band data archive. This is an effort conducted in the framework of the Spanish Virtual Observatory to help optimize science from the Gran Telescopio Canarias Archive. Data Release 1 includes 6788 broad-band images in the Sloan griz filters obtained between 2009 April and 2014 January and the associated catalogue with roughly 6.23 million detections of more than 630 000 unique sources. The catalogue contains standard PSF and Kron aperture photometry with a mean accuracy better than 0.09 and 0.15 mag, respectively. The relative astrometric residuals are always better than 30 mas and better than 15 mas in most cases. The absolute astrometric uncertainty of the catalogue is of 0.12 arcsec. In this paper we describe the procedure followed to build the image archive and the associated catalogue, as well as the quality tests carried out for validation. To illustrate some of the scientific potential of the catalogue, we also provide two examples of its scientific exploitation: discovery and identification of asteroids and cool dwarfs. [ABSTRACT FROM AUTHOR]

Virtual machine (VM) migration has recently emerged as a potential tool to improve the performance, cost and fault tolerance of data centers. However, migrating VMs requires more hardware resources to reserve target slots during the migration. A large number of simultaneous migrations can exhaust the physical resources of a data center. Consequently, the system may deny new service requests. In this paper, we introduce an efficient strategy to limit the number of target slots used for the migration process with the aim of maintaining high data center availability. In particular, the number of target slots is determined by the tradeoff between the waiting time of the queued migration processes and the probability that the system rejects new user requests due to the lack of available resources. We also propose a method to reduce the waiting time of the migration process by adding a sufficient number of slots during the migration process. Accordingly, a data center can use fewer resources while still guaranteeing the quality of the service. The efficiency of our proposed method is demonstrated by the experimental results. [ABSTRACT FROM AUTHOR]

This work describes a novel approach for the reduction of energy consumption in data centres (DCs) that will yield benefits both in terms of running costs and its environmental impact. The method is based on the introduction of collaborative interactions and flexibility clauses in contracts between all the DC ecosystem entities. The included entities are all the actors along the energy production–consumption chain, from the energy provider to the Information Technology customer. The collaborative approach also integrates the interaction between federated DCs. In this paper, we find a detailed description of the architecture that enables interaction between the DC ecosystem parties, which is designed to be progressively deployed, allowing traditional and ‘greened’ services to coexist, and without modification of the existing DC automation and framework systems. [ABSTRACT FROM AUTHOR]

The swift adoption of cloud services is accelerating the deployment of data centers. These data centers are consuming a large amount of energy, which is expected to grow dramatically under the existing technological trends. Therefore, research efforts are in great need to architect green data centers with better energy efficiency. The most prominent approach is the consolidation enabled by virtualization. However, little effort has been paid to the potential overhead in energy usage and the throughput reduction for virtualized servers. Clear understanding of energy usage on virtualized servers lays out a solid foundation for green data-center architecture. This paper investigates how virtualization affects the energy usage in servers under different task loads, aiming to understand a fundamental trade-off between the energy saving from consolidation and the detrimental effects from virtualization. We adopt an empirical approach to measure the server energy usage with different configurations, including a benchmark case and two alternative hypervisors. Based on the collected data, we report a few findings on the impact of virtualization on server energy usage and their implications to green data-center architecture. We envision that these technical insights would bring tremendous value propositions to green data-center architecture and operations. [ABSTRACT FROM AUTHOR]

PDS 110 is a young disc-hosting star in the Orion OB1A association. Two dimming events of similar depth and duration were seen in 2008 (WASP) and 2011 (KELT), consistent with an object in a closed periodic orbit. In this paper, we present data from a ground-based observing campaign designed to measure the star both photometrically and spectroscopically during the time of predicted eclipse in 2017 September. Despite high-quality photometry, the predicted eclipse did not occur, although coherent structure is present suggesting variable amounts of stellar flux or dust obscuration. We also searched for radial velocity (RV) oscillations caused by any hypothetical companion and can rule out close binaries to 0.1 M s. A search of Sonneberg plate archive data also enabled us to extend the photometric baseline of this star back more than 50 yr, and similarly does not re-detect any deep eclipses. Taken together, they suggest that the eclipses seen in WASP and KELT photometry were due to aperiodic events. It would seem that PDS 110 undergoes stochastic dimmings that are shallower and of shorter duration than those of UX Ori variables, but may have a similar mechanism. [ABSTRACT FROM AUTHOR]

Although there is great interest in reducing energy consumption for all areas of human activity, many of the proposed approaches such as the smart home or the smart grid are actually prone to an increase in the use of Information and Communication Technologies (ICT) which itself is a big consumer of energy. It is remarkable that ICT's carbon imprint is of the order of 2% of the world total, comparable to the carbon imprint of air travel. Thus, it is imperative to address energy savings in ICT and, in particular, in data centres and networks. This paper follows up on our previous work that seeks novel ways to reduce the energy consumption in packet networks which constitute the backbone of the Internet and of the information society as a whole. Here we discuss the use of routing control as a means to reduce energy consumption while remaining aware of QoS considerations, and propose a method that uses a queueing theoretic analysis and optimization technique to distribute traffic so as to reduce a cost function that comprises both energy and QoS. A method using G-networks is developed to incorporate both the effect of user traffic and the overhead in QoS and energy consumption introduced by the control traffic that will be needed to carry out the re-routing decisions. For an N-node network, we show that this approach results in an algorithm which has O(N3) time complexity. Because this approach may be too costly in computational overhead and delays, we also propose another approach that uses load balancing and which would be much simpler to implement. [ABSTRACT FROM AUTHOR]

Key Features Recently updated and expanded, the World Health Organization (WHO) Health Inequality Data Repository is a large repository for datasets of disaggregated data, covering a diversity of topics, dimensions of inequality and populations. To our knowledge, it is the largest global data repository of disaggregated health data and provides access to disaggregated data for all SDG indicators, where these data are available. Additional searching and consultation were undertaken to identify other sources of data, focusing first on global datasets (containing data from any/all countries), and then on regional and continental datasets (containing data from multiple countries). Data resource basics Disaggregated health data are a central requirement for health inequality monitoring, which is the process of quantifying and assessing health inequalities in a defined population. [Extracted from the article]

The article introduces a statistical methodology called hierarchical vintage sparse PCA (Hvsp) that is used to analyze networks and identify factors and communities with hierarchical structures. Hvsp combines hierarchical clustering and sparse PCA to explore the hierarchical organization of networks, offering interpretability and computational advantages. The article provides examples and comparisons of Hvsp with other methods, demonstrating its effectiveness in community detection. The authors also apply Hvsp to a statistics citation network to cluster related communities based on research interests, supported by visualizations and tables. The article includes a Github repository with codes and data for further exploration. The authors declare no conflicts of interest. [Extracted from the article]

Digital specimens collected by community members are a largely untapped source of entomological data. By mining and curating data from photo observations uploaded to online community data repositories, researchers can utilize this wealth of information to address questions about predator–prey interactions, phenotypic variation within species, plant–pollinator interactions, and a host of other topics. We mined data from photo observations on the community science website iNaturalist to investigate patterns in host plant availability and affiliation by 2 species of soldier beetles, Chauliognathus marginatus (F.) and Chauliognathus pensylvanicus (De Geer). Chauliognathus marginatus was observed with white flowers more than expected based on their potential availability, while C. pensylvanicus was observed with yellow flowers over all other flower colors and more than expected based on their potential availability. Communities of flowers available to, and observed with, C. marginatus and C. pensylvanicus differed significantly at the family and genus levels. To our knowledge, this is the first study to utilize a dataset mined and curated from community science photo observations to address species-specific behavior and ecology questions. With appropriate study design and analytical methods, these types of data could prove invaluable in future investigations of a variety of entomological and ecological questions. [ABSTRACT FROM AUTHOR]

A detailed palaeointensity study was performed using the modified Thellier method on 18 Quaternary and Neogene volcanic units, ages ranging from 0.08 to 5.98 Ma, in Central Anatolia, Turkey. Robust data, which were estimated from 12 lava units in the study area, significantly increase the database of palaeomagnetic data, directions and absolute palaeointensity for the Anatolian region covering the time window back to ∼6 Ma. Previous studies sensitively dated the samples, except for one site dated in this study. The palaeointensity (VDM) value from the upper Miocene site estimated as 48.6 ± 9.2 μT (10.1 × 1022 ± 1.9 Am2) fits well into the Neogene VDM range in the data archives. For Pliocene samples with an age of 4.7 Ma, the palaeointensity was calculated to be 21.0 ± 4.7 μT. For these samples, an inclination of +42.9° was determined, and together with the results of low palaeointensity and normal polarity, this corresponds to the Nunivak or Sidufjall subchrons. These are normal polarity chrons within the Gilbert Chron which predominantly has reversed polarity. Palaeodirectional data and field strength with age between 0.08 and 2.57 Ma clearly showed the Brunhes and Matuyama Chrons in the Pleistocene. Three new data with 25.0 ± 7.9 μT (age 1.84 Ma), 59.7 ± 8.2 μT (age 2.15 Ma) and 79.6 ± 19.3 μT (age 2.57 Ma) from the early Pleistocene period significantly contribute to global data archives, which lack palaeointensity data from similar latitude range. The average VDM values for nine Pleistocene sites were calculated to be 51.5 ± 16.4 μT (10.3 × 1022 ± 3.7 Am2). According to the comparison of our data with the palaeointensity database, field model record and previous studies of the Pleistocene, significantly high field strength obtained from Central Anatolia, located in the Northern Hemisphere, could have occurred due to asymmetry between the Northern and Southern Hemispheres during the Pleistocene. [ABSTRACT FROM AUTHOR]

Recent advances in genome sequencing have led to an increase in the number of sequenced genomes. However, the presence of repetitive sequences complicates the assembly of plant genomes. The LTR assembly index (LAI) has recently been widely used to assess the quality of genome assembly, as a higher LAI is associated with a higher quality of assembly. Here, we assessed the quality of assembled genomes of 1664 plant and algal genomes using LAI and reported the results as data repository called PlantLAI (https://bioinformatics.um6p.ma/PlantLAI). A number of 55 117 586 pseudomolecules/scaffolds with a total length of 988.11 gigabase-pairs were examined using the LAI workflow. A total of 46 583 551 accurate LTR-RTs were discovered, including 2 263 188 Copia , 2 933 052 Gypsy , and 1 387 311 unknown superfamilies. Consequently, only 1136 plant genomes are suitable for LAI calculation, with values ranging from 0 to 31.59. Based on the quality classification system, 476 diploid genomes were classified as draft, 472 as reference, and 135 as gold genomes. We also provide a free webtool to calculate the LAI of newly assembled genomes and the ability to save the result in the repository. The data repository is designed to fill in the gaps in the reported LAI of existing genomes, while the webtool is designed to help researchers calculate the LAI of their newly sequenced genomes. [ABSTRACT FROM AUTHOR]

With more and more businesses and organizations outsourcing their IT services to distributed clouds for cost savings, historical and operational data generated by the services have been growing exponentially. The generated data that are referred to as big data, stored at different geographic datacenters, now become an invaluable asset to these businesses and organizations, as they can make use of the data through analysis to identify business advantages and make strategic decisions. Big data analytics thus has been emerged as a main research topic in cloud computing. To efficiently evaluate a big data analytic query in a distributed cloud consisting of multiple datacenters at different geographic locations interconnected by the Internet, it poses great challenges: (i) the source data of the query typically are located at different datacenters; and (ii) the resource demands of the query may be beyond the supplies of any single datacenter at that moment. In this paper, we formulate an online query evaluation problem for big data analytic queries in distributed clouds, with an objective to maximize the query acceptance ratio while minimizing the accumulative query evaluation cost, for which we first propose a novel metric to model the usages of different resources in the distributed cloud, by incorporating the capacities and workloads of different datacenters and links, as well as resource demands of different queries. We then devise efficient online algorithms for query evaluations under both unsplittable and splittable source data assumptions. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms. Experimental results demonstrate that the proposed algorithms are promising, and outperform other heuristics at 95% confidence intervals. [ABSTRACT FROM AUTHOR]

With the emergence of high-throughput technologies, computational screening based on gene expression profiles has become one of the most effective methods for drug discovery. More importantly, profile-based approaches remarkably enhance novel drug–disease pair discovery without relying on drug- or disease-specific prior knowledge, which has been widely used in modern medicine. However, profile-based systematic screening of active ingredients of traditional Chinese medicine (TCM) has been scarcely performed due to inadequate pharmacotranscriptomic data. Here, we develop the largest-to-date online TCM active ingredients-based pharmacotranscriptomic platform integrated traditional Chinese medicine (ITCM) for the effective screening of active ingredients. First, we performed unified high-throughput experiments and constructed the largest data repository of 496 representative active ingredients, which was five times larger than the previous one built by our team. The transcriptome-based multi-scale analysis was also performed to elucidate their mechanism. Then, we developed six state-of-art signature search methods to screen active ingredients and determine the optimal signature size for all methods. Moreover, we integrated them into a screening strategy, TCM-Query, to identify the potential active ingredients for the special disease. In addition, we also comprehensively collected the TCM-related resource by literature mining. Finally, we applied ITCM to an active ingredient bavachinin, and two diseases, including prostate cancer and COVID-19, to demonstrate the power of drug discovery. ITCM was aimed to comprehensively explore the active ingredients of TCM and boost studies of pharmacological action and drug discovery. ITCM is available at http://itcm.biotcm.net. [ABSTRACT FROM AUTHOR]

The power of next-generation sequencing has resulted in an explosive growth in the number of projects aiming to understand the metagenomic diversity of complex microbial environments. The interdisciplinary nature of this microbiome research community, along with the absence of reporting standards for microbiome data and samples, poses a significant challenge for follow-up studies. Commonly used names of metagenomes and metatranscriptomes in public databases currently lack the essential information necessary to accurately describe and classify the underlying samples, which makes a comparative analysis difficult to conduct and often results in misclassified sequences in data repositories. The Genomes OnLine Database (GOLD) (https:// gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute has been at the forefront of addressing this challenge by developing a standardized nomenclature system for naming microbiome samples. GOLD, currently in its twenty-fifth anniversary, continues to enrich the research community with hundreds of thousands of metagenomes and metatranscriptomes with well-curated and easy-to-understand names. Through this manuscript, we describe the overall naming process that can be easily adopted by researchers worldwide. Additionally, we propose the use of this naming system as a best practice for the scientific community to facilitate better interoperability and reusability of microbiome data. [ABSTRACT FROM AUTHOR]

Background Machine learning (ML) technologies, especially deep learning (DL), have gained increasing attention in predictive mass spectrometry (MS) for enhancing the data-processing pipeline from raw data analysis to end-user predictions and rescoring. ML models need large-scale datasets for training and repurposing, which can be obtained from a range of public data repositories. However, applying ML to public MS datasets on larger scales is challenging, as they vary widely in terms of data acquisition methods, biological systems, and experimental designs. Results We aim to facilitate ML efforts in MS data by conducting a systematic analysis of the potential sources of variability in public MS repositories. We also examine how these factors affect ML performance and perform a comprehensive transfer learning to evaluate the benefits of current best practice methods in the field for transfer learning. Conclusions Our findings show significantly higher levels of homogeneity within a project than between projects, which indicates that it is important to construct datasets most closely resembling future test cases, as transferability is severely limited for unseen datasets. We also found that transfer learning, although it did increase model performance, did not increase model performance compared to a non-pretrained model. [ABSTRACT FROM AUTHOR]

Background Biomedical research often involves contextual integration of multimodal and multiomic data in search of mechanisms for improved diagnosis, treatment, and monitoring. Researchers need to access information from diverse sources, comprising data in various and sometimes incongruent formats. The downstream processing of the data to decipher mechanisms by reconstructing networks and developing quantitative models warrants considerable effort. Results MetGENE is a knowledge-based, gene-centric data aggregator that hierarchically retrieves information about the gene(s), their related pathway(s), reaction(s), metabolite(s), and metabolomic studies from standard data repositories under one dashboard to enable ease of access through centralization of relevant information. We note that MetGENE focuses only on those genes that encode for proteins directly associated with metabolites. All other gene–metabolite associations are beyond the current scope of MetGENE. Further, the information can be contextualized by filtering by species, anatomy (tissue), and condition (disease or phenotype). Conclusions MetGENE is an open-source tool that aggregates metabolite information for a given gene(s) and presents them in different computable formats (e.g. JSON) for further integration with other omics studies. MetGENE is available at https://bdcw.org/MetGENE/index.php. [ABSTRACT FROM AUTHOR]

As thousands of 2019 Corona virus disease (Covid-19) clinical trials are continuously getting added to various registries these days, good practices on data sharing and transparency have become one of the prime topics of discussion than ever before. Although trial registration is considered a crucial step, there is a lack of integration between registration and published literature. Trial outcomes are a matter of public interest, but sponsor compliances are not adequate with the recommended guidelines. Although the global recognition of data transparency increases day by day, there is still a long journey to travel. It is high time that scholarly publishing stakeholders should put in a collaborative effort to check author compliance. In this article, we aimed to comprehend and discuss the imperative roles of various scholarly publishing stakeholders in improving clinical trial transparency during this pandemic situation and highlight the changing paradigm towards the pressing need for reporting clinical trial data more effectively. [ABSTRACT FROM AUTHOR]

The National Institutes of Health (NIH) implemented a new Data Management and Sharing Policy on January 25, 2023. This policy replaces the 2003 document and affirms the NIH's support for open science and data sharing. Almost all proposals for research that will produce scientific data are now required to include a Data Management and Sharing Plan, which lays out how the research team will collect and preserve data to ensure long-term discoverability and access. Researchers must approach their projects with data sharing in mind, to the extent that is ethically, legally, and technically possible. [ABSTRACT FROM AUTHOR]

Background Influenza has long burdened the Military Health System (MHS). This study assesses the impact of repeated annual vaccination on influenza vaccine effectiveness (VE). Methods This retrospective, case control study using the test-negative design utilized data extracted from the MHS Data Repository (MDR). Cases had a positive influenza test and controls sought care for an influenza-like illness within 2 weeks of a case, had no positive influenza tests, and were matched by sex, race, age, and location. Vaccine effectiveness was assessed using conditional logistic regression separately for those who received inactivated and live attenuated influenza vaccines (LAIV). Results A total of 6860 cases and controls were identified in the MDR, among whom 53% were vaccinated in all 3 seasons. Among those who received inactivated influenza vaccine during the current season, VE ranged from 26% to 37% (2012/13 [A(H3N2)]: VE 26%, 95% confidence interval [CI] = 1%–45%; 2013/14 [A(H1N1)pdm09]: VE 37%, 95% CI = 18%–52%; 2014/15 [A(H3N2)]: VE 31%, 95% CI = 17%–42%). The VE ranged from 25% to 49% for those only vaccinated this season (2012/13 [A(H3N2)]: VE 38%, 95% CI = −3% to 63%; 2013/14 [A(H1N1)pdm09]: VE 49%, 95% CI = 11%–71%; 2014/15 [A(H3N2)]: VE 25%, 95% CI = −7% to 48%). The VE was more variable in those who received LAIV in the current season. No statistically significant differences in VE were observed between those frequently vaccinated and those vaccinated only during the current season. Conclusions These results underscore the value of annual influenza vaccinations for preventing infection while highlighting the need for continued improvements in influenza vaccine effectiveness. [ABSTRACT FROM AUTHOR]

This article studies the contents of the Architectural Biennial of Quito's (BAQ) archive from its first edition in 1978 to its eighth in 1992, using technological tools and producing bipartite networks that make visible the inter- and intra-relationships of the archive's data through quantitative and qualitative analysis. By using these methods and means, the results firstly show how the BAQ articulated discussions of modern architecture in Ecuador, and secondly, the extent of local and international exchanges implicated in the professional scope throughout the BAQ. The study of this archive allows one to understand the most important relationships in the architectural productions and communications at the hands of BAQ as a platform for circulating ideas. [ABSTRACT FROM AUTHOR]

Tracing the closure of oceans with irregular margins and the formation of an orocline are crucial for understanding plate reconstruction and continental assembly. The eastern Central Asian Orogenic Belt, where the Mongol-Okhotsk orocline is situated, is one of the world's largest magmatic provinces. Using a large data set of U-Pb zircon ages, we updated the timing of many published igneous rocks, which allowed us to recognize tightly 'folded' linear Carboniferous-Jurassic magmatic belts that wrap around the Mongol-Okhotsk suture and their migrations both sutureward and suture-parallel. The new successive magmatic belts reveal a rollback, scissor-like (or zipper-like) closure of the Mongol-Okhotsk Ocean that was fundamentally controlled by coeval subduction rollback and rotation of the Siberian and Mongolian-Erguna blocks. This study also demonstrates the complex mechanisms and processes of the closure of an ocean with irregular margins and the formation of a consequent orocline. [ABSTRACT FROM AUTHOR]

Radiation dose management systems (DMS) are currently used to help improve radiation protection in medical imaging and interventions. This study presents our experience using a homemade DMS called DOLQA (Dose On-Line for Quality Assurance). Our DMS is connected to 14 X-ray systems in a university hospital linked to the central data repository of a large network of 16 public hospitals in the Autonomous Community of Madrid, with 6.7 million inhabitants. The system allows us to manage individual patient dose data and groups of procedures with the same clinical indications, and compare them with diagnostic reference levels (DRLs). The system can also help to prioritise optimisation actions. This study includes results of imaging examinations from 2020, with 37,601 procedures and 286,471 radiation events included in the radiation dose structured reports (RDSR), for computed tomography (CT), interventional procedures, positron emission tomography-CT (PET-CT) and mammography. The benefits of the system include: automatic registration and management of patient doses, creation of dose reports for patients, information on recurrent examinations, high dose alerts, and help to define optimisation actions. The system requires the support of medical physicists and implication of radiologists and radiographers. DMSs must undergo periodic quality controls and audit reports must be drawn up and submitted to the hospital's quality committee. The drawbacks of DMSs include the need for continuous external support (medical physics experts, radiologists, radiographers, technical services of imaging equipment and hospital informatics services) and the need to include data on clinical indication for the imaging procedures. DMS perform automatic management of radiation doses, produces patient dose reports, and registers high dose alerts to suggest optimisation actions. Benefits and limitations are derived from the practical experience in a large university hospital. [ABSTRACT FROM AUTHOR]