Scientific literature analysis of Judo in Web of Science

Although judo is a sport with great tradition that is practised worldwide, the state of the art and scientific advanc- es have not been analysed from a bibliometric point of view up to now. The aim of the present article is the status of the scientific production, collaboration, and impact of scientific pa- pers on judo, as well as the most active research groups working on this topic. Our analysis was based on documents retrieved from the Science Citation Index and Social Science Citation Index. Bibliometric analysis and network construction were performed using Histcite and Bibexcel software. As a result, 383 original papers and scientific reviews were retrieved from 162 journals in 78 Web of Science® cate- gories. Archives of Budo had the highest number of articles (56), and International Journal of Sports Medicine had the highest number of citations (192). More than half of the articles were within the area of sports science. The co- authorship network (threshold ≥3 articles) enabled us to identify 6 clusters of authors written in partnership. The citation network was formed mainly by 14 authors. Although research on judo is still at an early stage and has a lower profile than other sports, its development has potential interest to many scientific fields and sports in general. Judo research is mainly published in journals cov- ering sport science and sport medicine topics; the latter being the most cited ones. The co-authorship networks tended to be centralized, with a single lead author, while citation networks between authors were usually directed towards other areas of research.Peset Mancebo, MF.; Ferrer Sapena, A.; Villamón Herrera, M.; González Moreno, LM.; Toca Herrera, J.; Aleixandre Benavent, R. (2013). Scientific literature analysis of Judo in Web of Science. Archives of Budo. 9(2):81-91. http://hdl.handle.net/10251/43595S81919

Mapping QTLs associated with fruit quality traits in peach Prunus persica (L.) Batsch using SNP maps

[EN] Fruit quality is an essential criterion used to select new cultivars in peach breeding programs and is determined based on a combination of organoleptic and nutritional traits. The aim of this study was to identify quantitative trait loci (QTLs) for fruit quality traits in an F-1 nectarine population derived from 'Venus' and 'Big Top' cultivars. The progeny were evaluated over 4 years for agronomical and biochemical characteristics and genotyped using simple sequence repeat (SSR) markers and 'IPSC 9K peach SNP array v1'. Two genetic maps were constructed using 411 markers. The 'Venus' map spanned 259 cM on nine linkage groups (LGs) with 104 markers. The 'Big Top' map spanned 464 cM on 10 LGs with 122 markers. Single or Multiple QTL models mapping was applied separately for each year and all years combined. A total of 54 QTLs mapped over 12 LGs belonged to seven peach chromosomes. Most of the QTLs were consistent over the 4 years of study and were validated with the multi-year analysis. QTLs for total phenolic, flavonoid, and anthocyanin contents were reported for the first time in peach. LG 4 in 'Venus' and LG 5 in 'Big Top' showed the highest numbers of QTLs. This work represents the first study in an F-1 nectarine family to identify peach genomic regions that control fruit quality traits using 'IPSC 9K SNP array v1' and provides useful information for marker-assisted breeding to produce peaches with better antioxidant content and healthy attributes.We are grateful to C.H. Crisosto (University of California, Davis) for providing SSR markers (UCDCH15 and BINEPPCU6377). We thank E. Sierra and S. Segura for the technical assistance and plant management in the field and N. Ksouri for the bioinformatic assistance. We are grateful to A. Casas and E. Igartua for the assistance and support with the statistical analysis using JoinMap (R) 4 software. This study was funded by the Spanish Ministry of Economy and Competitiveness (MINECO) grants AGL-2008-00283, AGL2011-24576, and AGL2014-52063-R and was co-funded by the FEDER and the Regional Government of Aragon (A44) with European Social Fund. W. Abidi was supported by a JAE-Pre fellowship from the Consejo Superior de Investigaciones Cientificas (CSIC), which enabled him to visit the University of California, Davis, and the IBMCP, Valencia, Spain. J.L. Zeballos received a master fellow funded by the Spanish Agency for International Cooperation and Development (AECID).Zeballos, JL.; Adibi, W.; Giménez Millán, R.; Monforte Gilabert, AJ.; Moreno, MA.; Gogorcena, Y. (2016). Mapping QTLs associated with fruit quality traits in peach Prunus persica (L.) Batsch using SNP maps. 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Impact of COVID-19 on the self-reported physical activity of people with complete thoracic spinal cord injury full-time manual wheelchair users

Coronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Activitat física; Lesió medul·larCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Actividad física; Lesión de la médula espinalCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Physical activity; Spinal cord injuryContext The emergence of COVID-19 caused a new public health crisis, leading to major changes in daily life routines, often including physical activity (PA) levels. The main goal of this study was to analyze the differences in self-reported physical activity of people with complete spinal cord injuries between the time prior to the COVID-19 lockdown and the lockdown period itself. Methods A sample of 20 participants with complete thoracic spinal cord injuries completed the Physical Activity Scale for Individuals with Physical Disabilities before and during the COVID-19 lockdown. Results The results showed differences between the pre-lockdown and lockdown measurements in total self-reported PA (z=−3.92; P<0.001; d=1.28), recreational PA (z=−3.92; P<0.001; d=1.18) and occupational PA (z=−2.03; P=0.042; d=0.55). Nevertheless, no differences were found in housework PA between the two time periods. Furthermore, the results showed differences in total minutes (z=−3.92; P<0.001; d=1.75), minutes spent on recreational activities (z=−3.82; P<0.001; d=1.56) and minutes spent on occupational activities (z=−2.032; P=0.042; d=0.55) of moderate/vigorous intensity. Conclusions Individuals with thoracic spinal cord injuries who were full-time manual wheelchair users displayed lower levels of PA during the pandemic than in the pre-pandemic period. The results suggest that the prohibition and restrictions on carrying out recreational and/or occupational activities are the main reasons for this inactivity. Physical activity promotion strategies should be implemented within this population to lessen the effects of this physical inactivity stemming from the COVID-19 pandemic.This work was supported by the Fundació la Marató de la TV3 under [grant number 201720-10]

Social inequalities in a population based colorectal cancer screening programme in the Basque Country

Background: While it is known that a variety of factors (biological, behavioural and interventional) play a major role in the health of individuals and populations, the importance of the role of social determinants is less clear. The effect of social inequality on population-based screening for colorectal cancer (CRC) could limit the value of such programmes. The present study aims to determine whether such inequalities exist. Methods: Data was obtained from the population-based screening programme administered in the Autonomous Community of the Basque Country, Spain, with a target population aged 50 to 69, first invited to participate between 2009 and 2011. The magnitude of inequality was analysed using the odds ratio (taking the least disadvantaged socioeconomic quintile as the reference population), the population attributable risk and the relative index of inequality, based on the regression, which is the ratio of the rates in the most and least disadvantaged socioeconomic groups. Results: The target population comprised 242,394 people, with the test kit successfully sent to 95.1 % (230,510). The overall response rate was 64.3 % (67.1 in women and 61.4 % men). Among women, the highest participation was in the third quintile (71.5 %) and the lowest in the first - the least disadvantaged (65.7 %). The lowest and highest rates of people with identified lesions were in the second and fourth quintiles (14.7/1000 and 17.0/1000 respectively). Among men, the response rate was lowest in the fifth - most disadvantaged - quintile (60.2 %). The highest rate of identified lesions was in the fifth quintile; 38 % higher than the first (55.7/1000 compared to 41.0/1000). Conclusions: Sex and socioeconomic group influence the rate of participation in the CRC programme and the rate of lesions found in the participants. Any public health programme is morally and ethically obliged to strive for equity and effectiveness. Improving participation of men and socially disadvantaged groups should be taken in account

Graph-based Global Robot Localization Informing Situational Graphs with Architectural Graphs

peer reviewedIn this paper, we propose a solution for legged robot localization using architectural plans. Our specific contributions towards this goal are several. Firstly, we develop a method for converting the plan of a building into what we denote as an architectural graph (A-Graph). When the robot starts moving in an environment, we assume it has no knowledge about it, and it estimates an online situational graph representation (S-Graph) of its surroundings. We develop a novel graph-to-graph matching method, in order to relate the S-Graph estimated online from the robot sensors and the A-Graph extracted from the building plans. Note the challenge in this, as the S-Graph may show a partial view of the full A-Graph, their nodes are heterogeneous and their reference frames are different. After the matching, both graphs are aligned and merged, resulting in what we denote as an informed Situational Graph (iS-Graph), with which we achieve global robot localization and exploitation of prior knowledge from the building plans. Our experiments show that our pipeline shows a higher robustness and a significantly lower pose error than several LiDAR localization baselines.Robotic Situational Awareness By Understanding And Reasonin

Graph-based Global Robot Simultaneous Localization and Mapping using Architectural Plans

peer reviewedIn this paper, we propose a solution for graph-based global robot simultaneous localization and mapping (SLAM) using architectural plans. Before the start of the robot operation, the previously available architectural plan of the building is converted into our proposed architectural graph (A-Graph). When the robot starts its operation, it uses its onboard LIDAR and odometry to carry out an online SLAM relying on our situational graph (S-Graph), which includes both, a representation of the environment with multiple levels of abstractions, such as walls or rooms, and their relationships, as well as the robot poses with their associated keyframes. Our novel graph-to-graph matching method is used to relate the aforementioned S-Graph and A-Graph, which are aligned and merged, resulting in our novel informed Situational Graph (iS-Graph). Our iS-Graph not only provides graph-based global robot localization, but it extends the graph-based SLAM capabilities of the S-Graph by incorporating into it the prior knowledge of the environment existing in the architectural planRobotic Situational Awareness By Understanding And Reasonin

The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis

[EN] The spread of the SARS-CoV-2 virus has transformed many aspects of people's daily life, including sports. Social networks have been flooded on these issues. The present study aims to analyze the tweets produced relating to sports and COVID-19. From the end of January to the beginning of May 2020, over 4,000,000 tweets on this subject were downloaded through the Twitter search API. Once the duplicates, replicas, and retweets were removed, 119,253 original tweets were analyzed. A quantitative-qualitative content analysis was used to study the selected tweets. Posts dynamics regarding sport and exercise evolved according to the COVID-19 pandemic and subsequent lockdown, shifting from considering sport as a healthy bastion to an activity exposed to disease like any other. Most media professional sporting events received great attention on Twitter, while grassroots and women's sport were relegated to a residual role. The analysis of the 30 topics identified focused on the social, sporting, economic and health impact of the pandemic on the sport. Sporting cancellations, leisure time and socialization disruptions, club bankruptcies, sports training and athletes' uncertain career development were the main concerns. Although general health measures appeared in the tweets analyzed, those addressed to sports practice were relatively scarce. Finally, this study shows the importance of Twitter as a means of conveying social attitudes towards sports and COVID-19 and its potential to generate alternative responses in future stages of the pandemic.González, L.; Devis-Devis, J.; Pellicer-Chenoll, M.; Pans, M.; Pardo-Ibáñez, A.; García-Massó, X.; Peset Mancebo, MF.... (2021). The Impact of COVID-19 on Sport in Twitter: A Quantitative and Qualitative Content Analysis. International Journal of Environmental research and Public Health (Online). 18(9):1-20. https://doi.org/10.3390/ijerph18094554S12018

Better Situational Graphs by Inferring High-level Semantic-Relational Concepts

Recent works on SLAM extend their pose graphs with higher-level semantic concepts exploiting relationships between them, to provide, not only a richer representation of the situation/environment but also to improve the accuracy of its estimation. Concretely, our previous work, Situational Graphs (S-Graphs), a pioneer in jointly leveraging semantic relationships in the factor optimization process, relies on semantic entities such as wall surfaces and rooms, whose relationship is mathematically defined. Nevertheless, excerpting these high-level concepts relying exclusively on the lower-level factor-graph remains a challenge and it is currently done with ad-hoc algorithms, which limits its capability to include new semantic-relational concepts. To overcome this limitation, in this work, we propose a Graph Neural Network (GNN) for learning high-level semantic-relational concepts that can be inferred from the low-level factor graph. We have demonstrated that we can infer room entities and their relationship to the mapped wall surfaces, more accurately and more computationally efficient than the baseline algorithm. Additionally, to demonstrate the versatility of our method, we provide a new semantic concept, i.e. wall, and its relationship with its wall surfaces. Our proposed method has been integrated into S-Graphs+, and it has been validated in both simulated and real datasets. A docker container with our software will be made available to the scientific community

Comparison of visual and optical quality of monofocal versus multifocal intraocular lenses

Postprint (author's final draft

Mechanochemical Synthesis of Visible Light Sensitive Titanium Dioxide Photocatalyst

Phase transition of anatase nanoparticles into the phases TiO2-II and rutile under grinding was studied. The addition of ammonium carbamate to the reaction mixture inhibits the phase conversion and the cold welding of particles. The UV-visible absorption spectrum showed narrowing the band gap width after grinding with an ammonium carbamate additive resulting in shift of the light absorption of the ground sample towards the visible region. By EPR, intensive formation of OH• radical at irradiation of the sample with both UV (λ > 300 nm) and visible (λ > 435 nm) light was observed. High photocatalytic activity of the ground sample in visible light region was demonstrated also by measurement of kinetics of the photocatalytic decomposition of 4-chlorophenol