Profitable mixed capacitated arc routing and related problems

Mixed Capacitated Arc Routing Problems (MCARP) aim to identify a set of vehicle trips that, starting and ending at a depot node, serve a given number of links, regarding the vehicles capacity, and minimizing a cost function. If both profits and costs on arcs are considered, the Profitable Mixed Capacitated Arc Routing Problem (PMCARP) may be defined. We present compact flow based models for the PMCARP, where two types of services are tackled, mandatory and optional. Adaptations of the models to fit into some other related problems are also proposed. The models are evaluated, according to their bounds quality as well as the CPU times, over large sets of test instances. New instances have been created from benchmark ones in order to solve variants that have been introduced here for the first time. Results show the new models performance within CPLEX and compare, whenever available, the proposed models against other resolution methods.info:eu-repo/semantics/publishedVersio

Correlation between impact factor and public availability of published research data in information science & library science journals

Trabajo presentado a la 15th International Society of Scientometrics and Informetrics Conference, celebrada en Estambúl (Turquia) del 29 de junio al 4 de julio de 2015.Scientists continuously generate research data but only a few part of them are published. If these data were accessible and reusable, researchers could examine them and generate new knowledge. Currently, the barriers to data sharing are phased out and public research organizations are demanding ever more insistently that publications resulting from publicly funded projects and data that support them should be published in open (Savage & Vickers, 2009). The purpose of this work is: a) to analyse policies concerning open availability of raw research data in journals in the Information Science & Library Science (ISLS); and b) to determine whether there is a correlation between the impact factor and policies of these journals concerning storage and reuse of scientific data.This work has benefited from assistance by the National R+D+I of the Ministry of Economy and Competitiveness of the Spanish Government (CSO2012-39632-C02-01) and Prometeo Program for excellent research groups of Generalitat Valenciana (GVPROMETEO2013-041).Peer Reviewe

Impact of a Web-Based Exercise and Nutritional Education Intervention in Patients Who Are Obese With Hypertension: Randomized Wait-List Controlled Trial

Background: Internet-based interventions are a promising strategy for promoting healthy lifestyle behaviors. These have a tremendous potential for delivering electronic health interventions in scalable and cost-effective ways. There is strong evidence that the use of these programs can lead to weight loss and can lower patients’ average blood pressure (BP) levels. So far, few studies have investigated the effects of internet-based programs on patients who are obese with hypertension (HTN). Objective: The aim of this study is to investigate the short- and long-term efficacy, in terms of body composition and BP parameters, of a self-administered internet-based intervention involving different modules and learning techniques aimed at promoting lifestyle changes (both physical activity and healthy eating) in patients who are obese with HTN. Methods: A randomized wait-list controlled trial design was used. We recruited 105 adults with HTN who were overweight or obese and randomly assigned them to either a 3-month internet-based intervention group (n=55) or the wait-list control group (n=50). We assessed BMI (primary outcome), body fat mass (BFM), systolic (S)BP and diastolic (D)BP, blood glucose and insulin levels, physical activity levels, and functional capacity for aerobic exercise at Time 0 (preintervention) and Time 1 (postintervention). All the patients in the wait-list control group subsequently received the intervention, and a secondary within-group analysis, which also included these participants, was conducted at Time 2 (12-month follow-up). Results: A 2-way mixed analysis of covariance showed a significant decrease in BMI, BFM, and blood glucose at 3 months in the internet-based intervention group; the effect size for the BMI and BFM parameters was moderate to large, and there was also a borderline significant trend for DBP and insulin. These results were either maintained or improved upon at Time 2 and showed significant changes for BMI (mean difference −0.4, 95% CI −0.1 to −0.6; P=.005), BFM (mean difference −2.4, 95% CI −1.1 to −3.6; P<.001), DBP (mean difference −1.8, 95% CI −0.2 to −3.3; P=.03), and blood glucose (mean difference −2, 95% CI 0 to −4; P=.04). Conclusions: Implementation of our self-administered internet-based intervention, which involved different learning techniques aimed to promote lifestyle changes, resulted in positive short- and long-term health benefits in patients who are obese with HTN

Correlation between impact factor and public availability of published research data in Information Science and Library Science journals

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-016-1868-7[EN] Scientists continuously generate research data but only a few of them are published. If these data were accessible and reusable, researchers could examine them and generate new knowledge. Our purpose is to determine whether there is a relationship between the impact factor and the policies concerning open availability of raw research data in journals of Information Science and Library Science (ISLS) subject category from the Web of Science database. We reviewed the policies related to public availability of papers and data sharing in the 85 journals included in the ISLS category of the Journal Citation Reports in 2012. The relationship between public availability of published data and impact factor of journals is analysed through different statistical tests. The variable "statement of complementary material" was accepted in 50 % of the journals; 65 % of the journals support "reuse"; 67 % of the journals specified "storage in thematic or institutional repositories"; the "publication of the manuscript in a website" was accepted in 69 % of the journals. We have found a 50 % of journals that include the possibility to deposit data as supplementary material, and more than 60 % accept reuse, storage in repositories and publication in websites. There is a clear positive relationship between being a top journal in impact factor ranking of JCR and having an open policy.This work has benefited from assistance by the National R+D+I of the Ministry of Economy and Competitiveness of the Spanish Government (CSO2012-39632-C02).Aleixandre-Benavent, R.; Moreno-Solano, L.; Ferrer Sapena, A.; Sánchez Pérez, EA. (2016). Correlation between impact factor and public availability of published research data in Information Science and Library Science journals. Scientometrics. 107(1):1-13. https://doi.org/10.1007/s11192-016-1868-7S1131071Aleixandre-Benavent, R., Vidal-Infer, A., Alonso-Arroyo, A., Valderrama-Zurián, J. C., Bueno-Cañigral, F., & Ferrer-Sapena, A. (2014). Public availability of published research data in substance abuse journals. International Journal of Drug Policy, 25, 1143–1146.Alsheikh-Ali, A. A., Qureshi, W., Al-Mallah, M. H., & Ioannidis, J. P. A. (2011). Public availability of published research data in high-impact journals. PLoS One, 6(9), e24357.Anderson, B. J., & Merry, A. F. (2009). Data sharing for pharmacokinetic studies. Paediatr Anaesthes, 19(10), 1005–1010.Blahous, B., Gorraiz, J., Gumpenberger, C., Lehner, O., Stein, B., & Ulrych, U. (2015). Research data policies in scientific journals—An empirical study. Zeitschrift fur Bibliothekswesen und Bibliographie, 62(1), 12–24.Borrego, A., & Garcia, F. (2013). Provision of supplementary materials in Library and Information Science scholarly journals. Aslib Proceedings, 65(5), 503–514.Cech, T. R. (2003). Sharing publication-related data and materials: responsibilities of authorship in the life sciences. www.nap.edu/books/0309088593/html . Accessed 24 November 2015CODATA. (2015). http://www.codata.org . Accessed 21 February 2015Conradie, P., & Choenni, S. (2014). On the barriers for local government releasing open data. Government Information Quarterly, 31, S10–S17.De Castro, P., Calzolari, A., Napolitani, F., Maria Rossi, A., Mabile, L., Cambon-Thomsen, A., & Bravo, E. (2013). Open data sharing in the context of bioresources. Acta Informatica Medica, 21(4), 291–292.Digital Curation Centre (DCC). (2015). http://www.dcc.ac.uk . Accessed 4 March 2015European Commission. (2015). Guidelines on open access to scientific publications and research data in Horizon 2020. European Commission, 2013. http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-pilot-guide_en.pdf . Accessed 15 March 2015Fear, K. (2015). Building outreach on assessment: Researcher compliance with journal policies for data sharing. Bulletin of the Association for Information Science and Technology, 41(6), 18–21.González, L. M., Saorín, T., Ferrer, A., Aleixandre-Benavent, R., & Peset, F. (2013). Gestión de datos de investigación: infraestructuras para su difusión. Professional Information, 22, 414–423.Jones, R. B., Reeves, D., & Martinez, C. S. (2012). Overview of electronic data sharing: Why, how, and impact. Current Oncology Reports, 14(6), 486–493.Kaye, J. (2012). The tension between data sharing and the protection of privacy ingenomics research. Annual Review of Genomics and Human Genetics, 13, 415–431.Leonelli, S., Smirnoff, N., Moore, J., Cook, C., & Bastow, R. (2013). Making open data work for plant scientists. Journal of Experimental Botany, 64(14), 4109–41017.National Institutes of Health (NIH). (2015). Data sharing policy. http://grants.nih.gov/grants/policy/data_sharing/index.htm . Accessed 3 March 2015National Science Foundation (NSF). (2014). Dissemination and sharing of research results. NSF Data Sharing Policy. http://www.nsf.gov/bfa/dias/policy/dmp.jsp . Accessed 21 November 2014Nelson, B. (2009). Data sharing: Empty archives. Nature, 461(7261), 160–163.Open Knowledge Foundation. (2015). https://okfn.org/ . Accessed 3 March 2015Pisani, E., & AbouZahr, C. (2010). Sharing health data: Good intentions are not enough. Bulletin of the World Health Organization, 88(6), 462–466.Piwowar, H. A., Day, R. S., & Fridsma, D. B. (2007). Sharing detailed research data is associated with increased citation rate. PLoS One, 2(3), e308.Piwowar, H. A., & Chapman, W.W. (2008). A review of journal policies for sharing research data. http://precedings.nature.com/documents/1700/version/1.hdl:10101/npre.2008.1700.1 . Accessed 11 December 2015Piwowar, H. A., & Todd, J. (2013). Data reuse and the open data citation advantage. PeerJ, 1, e175.Registry of Research Data Repositories (re3data). (2015). http://www.re3data.org/2014/03/re3data-org-from-funding-to-growing/ . Accessed 5 March 2015Savage, C. J., & Vickers, A. J. (2009). Empirical study of data saharing by authors publishing in PLOS journals. PLoS One, 4(9), e7078.Sayogo, D. S., & Pardo, T. A. (2013). Exploring the determinants of scientific data sharing: Understanding the motivation to publish research data. Government Information Quarterly, 30, S19–S31.Spencer, H. (2015). Thoughts on the sharing of data and research materials and the role of journal policies. http://web.stanford.edu/~vcs/Nov21/hilary_spencer_rdcscsJan2010.pdf . Accessed 11 December 2015Sturges, P., Bamkin, M., Anders, J., & Hussain, A. (2014). Journals and their policies on research data sharing. https://jordproject.wordpress.com/reportsand-article/journals-and-their-policies-on-research-data-sharing/ . Accessed 24 November 2015Tenenbaum, J. D., Sansone, S. A., & Haendel, M. (2007). A sea of standards for omics data: sink or swim? Journal of the American Medical Informatics Association, 21(2), 200–203.Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., et al. (2011). Data sharing by scientists: Practices and perceptions. PLoS One, 6(6), e21101.The Royal Society Publishing. (2015). http://royalsocietypublishing.org/data-sharing . Accessed 15 March 2015Toronto International Data Release Workshop Authors. (2009). Prepublication data sharing. Nature, 461(7261), 168–170.Van Noorden, R. (2013). Data-sharing: Everything on display. Nature, 500, 243–245.Wellcome Trust. (2015). Data sharing. http://www.wellcome.ac.uk/About-us/Policy/Spotlight-issues/Data-sharing/ . Accessed 21 January 201

The lack of stability of the impact factor of the mathematical journals

Trabajo presentado a la 15th International Society of Scientometrics and Informetrics Conference, celebrada en Estambúl (Turquia) del 29 de junio al 4 de julio de 2015.Although the 2-year Thomson-Reuters Impact Factor (IF) has become a usual tool for measuring the scientific productivity of all fields of the natural sciences (see Aleixandre-Benavent, Valderrama Zurián, & González Alcaide, 2007), its behavior in the particular case of the journals of pure mathematics (the area MATHEMATICS in the thematic directory of Thomson-Reuters) is far from being stable when its values in consecutive years are considered. If we consider the changes of the values of the IF of a given journal in the last decade, it can be easily seen that the variation of the values is surprisingly high if we compare with other disciplines. Mathematical journals seem to have the worst behavior regarding the time stability both of the IF and the position in the IF list.This work has benefited from assistance by the National R+D+I of the Ministry of Economy and Competitiveness of the Spanish Government (CSO2012-39632-C02-01) and Prometeo Program for excellent research groups of Generalitat Valenciana (GVPROMETEO2013-041).Peer reviewe

Citations to arXiv Preprints by Indexed Journals and their Impact on Research Evaluation

[EN] This article shows an approach to the study of two fundamental aspects of the prepublication of scientific manuscripts in specialized repositories (arXiv). The first refers to the size of the interaction of ¿standard papers¿ in journals appearing in the Web of Science (WoS) ¿ now Clarivate Analytics ¿ and ¿non-standard papers¿ (manuscripts appearing in arXiv). Specifically, we analyze the citations found in the WoS to articles in arXiv. The second aspect is how publication in arXiv affects the citation count of authors. The question is whether or not prepublishing in arXiv benefits authors from the point of view of increasing their citations, or rather produces a dispersion, which would diminish the relevance of their publications in evaluation processes. Data have been collected from arXiv, the websites of the journals, Google Scholar, and WoS following a specific ad hoc procedure. The number of citations in journal articles published in WoS to preprints in arXiv is not large. We show that citation counts from regular papers and preprints using different sources (arXiv, the journal¿s website, WoS) give completely different results. This suggests a rather scattered picture of citations that could distort the citation count of a given article against the author¿s interest. However, the number of WoS references to arXiv preprints is small, minimizing this potential negative effect.The work of the first, second, and third author was supported by Ministerio de Economía, Industria y Competitividad, Spain, under Research Grant CSO2015-65594-C2-1R Y 2R (MINECO/FEDER, UE). The work of the fourth author was supported by Ministerio de Economía, Industria y Competitividad, Spain, and FEDER, under Research Grant MTM2016-77054-C2-1-P. The authors would also like to thank the referees for their useful comments and references, which helped them to improve the work, especially in Section 5.Ferrer-Sapena, A.; Aleixandre-Benavent, R.; Peset Mancebo, MF.; Sánchez Pérez, EA. (2018). Citations to arXiv Preprints by Indexed Journals and their Impact on Research Evaluation. Journal of Information Science Theory and Practice (Online). 6(4):14-24. https://doi.org/10.1633/JISTaP.2018.6.4.2S14246

The Impact Factor as a measuring tool of the prestige of the journals in research assessment in mathematics

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Research evaluation following peer review. The version of record Antonia Ferrer-Sapena, Enrique A. Sánchez-Pérez, Fernanda Peset, Luis-Millán González, Rafael Aleixandre-Benavent; The Impact Factor as a measuring tool of the prestige of the journals in research assessment in mathematics. Res Eval 2016; 25 (3): 306-314 is available online at: https://doi.org/10.1093/reseval/rvv041The (2-year) Impact Factor of Thomson-Reuters (IF) has become the fundamental tool for analysing the scientific production of academic researchers in a lot of countries. In this article we show that this index and the ordering criterion obtained by using it are highly unstable in the case of mathematics, to the extent that sometimes no reliability can be assigned to its use. We explain the reasons of this behaviour by the specific properties of the mathematical journals and publications, attending mainly the point of view of the researchers in pure mathematics. Using the Journal Citation Report list of journals as a source of information, we analyse the stability in the position of the mathematical journals-the so-called rank-normalized impact factor-compared with journals in applied physics and microbiology during the period 2002-12. Due to the lack of stability of the position of the journals of mathematics in these lists, we propose a 'cumulative index' that fits better the characteristics of mathematical journals. The computation of this index uses the values of the IF of the journals in previous years, providing in this way a more stable indicator.This work was supported by the Ministerio de Economia y Competitividad (Spain) [CS02012-39632-C02 to A.F.S, F.P., R.A.B.] and [MTM2012-36740-C02-02 to E.A.S.P.].Ferrer Sapena, A.; Sánchez Pérez, EA.; Peset Mancebo, MF.; Gonzalez, L.; Aleixandre-Benavent, R. (2016). The Impact Factor as a measuring tool of the prestige of the journals in research assessment in mathematics. Research Evaluation. 25(3):306-314. https://doi.org/10.1093/reseval/rvv041S30631425

Profitable mixed capacitated arc routing and related problems

Mixed Capacitated Arc Routing Problems (MCARP) aim to identify a set of vehicle trips that, starting and ending at a depot node, serve a given number of links, regarding the vehicles capacity, and minimizing a cost function. If both profits and costs on arcs are considered, the Profitable Mixed Capacitated Arc Routing Problem (PMCARP) may be defined. We present compact flow based models for the PMCARP, where two types of services are tackled, mandatory and optional. Adaptations of the models to fit into some other related problems are also proposed. The models are evaluated, according to their bounds quality as well as the CPU times, over large sets of test instances. New instances have been created from benchmark ones in order to solve variants that have been introduced here for the first time. Results show the new models performance within CPLEX and compare, whenever available, the proposed models against other resolution methodsinfo:eu-repo/semantics/publishedVersio

Cómo analizar el impacto de los datos de investigación con métricas: modelos y servicios

This article is a summary of the different pathways to publish research data, of metrics for evaluating publishing and reuse, and of the existing services for measuring the reuse of research data. It is not yet possible to accurately analyze the metrics for open research data and this is one of the reasons why, in general, researchers do not include them in the assessment of their work. In order to further the use of these tools, it is necessary to increase the number of studies about these evaluation metrics

New Heuristic Algorithms for the Windy Rural Postman Problem

[EN] In this paper we deal with the windy rural postman problem. This problem generalizes several important arc routing problems and has interesting real-life applications. Here, we present several heuristics whose study has lead to the design of a scatter search algorithm for the windy rural postman problem. Extensive computational experiments over different sets of instances, with sizes up to 988 nodes and 3952 edges, are also presented. (c) 2004 Elsevier Ltd. All rights reserved.Benavent, E.; Corberán, A.; Piñana, E.; Plana. I.; Sanchís Llopis, JM. (2005). New Heuristic Algorithms for the Windy Rural Postman Problem. Computers & Operations Research. 32(12):3111-3128. doi:10.1016/j.cor.2004.04.007S31113128321