Anogenital distance and variability in semen parameters

López-Espín, J.J. (Center of Operations Research, Miguel Hernandez University, Elche); Pérez-Palazón, C. (Gynaecological Center of Reproduction and Genetics and Division of Preventive Medicine and Public Health, University of Murcia School of Medicine); Maldonado-Cárceles, A.B. (Division of Preventive Medicine and Public Health, University of Murcia School of Medicine and Department of Preventive Medicine, Reina Sofia University General Hospital, Murcia); Ramón-Arias, J.D. (Gynaecological Center of Reproduction and Genetics, Murcia); Mendiola, J. (Division of Preventive Medicine and Public Health, University of Murcia School of Medicine and CIBER of Epidemiology and Public Health (CIBERESP), ISCIII, Madrid); Torres-Cantero, A.M. (Division of Preventive Medicine and Public Health, University of Murcia School of Medicine, Department of Preventive Medicine, Reina Sofia University General Hospital, CIBER of Epidemiology and Public Health (CIBERESP), ISCIII, Madrid and Regional Campus of Excellence Mare Nostrum, University of Murcia).

Abstract: The purpose of this study was to analyze whether the anogenital distance (AGD) was associated with variability in semen parameters. Semen parameters analyzed following the WHO guidelines and sperm DNA fragmentation were evaluated in 160 semen samples obtained over a period of a year from 16 healthy male volunteers. Two types of AGD measurements from the anus to the rear base of the scrotum (AGDAS) and to the cephalic insertion of the penis (AGDAP) were taken in each individual. The association between AGDs and semen parameters were studied using three statistical tools: a) general coefficient of variation (CV) and intra-individual coefficient of variation (CVi), b) general linear models for repeated measures, and c) mixed model fixed effects panel data. Men with shortened AGDAP have significantly greater intra-individual variability in sperm concentration, total sperm count, and normal sperm morphology. Conversely, greater total sperm motility was observed in men with long AGDAS. Shortened AGDAS was associated with less intra-individual variability of total sperm motility (progressive and non-progressive). AGD measurements were associated with the variability in semen parameters. AGD may be useful to determine intra-individual variability in semen parameters. Abbreviations: AGD: anogenital distance; AGDAP: anogenital distance from the anus to the cephalic insertion of the penis; AGDAS: anogenital distance from the anus to the rear base of the scrotum; AIC: Akaike information criteria; BMI: body mass index; CV: general coefficient of variation; CVi: intra-individual coefficient of variation; GLM: generalized linear model; PR+NP: total sperm motility. © 2017 Taylor & Francis.

Two-Step Linear Least-Squares Method for Photovoltaic Single-Diode Model Parameters Extraction

Toledo, F.J (Universidad Miguel Hernández); Blanes, J.M.M. ( Universidad Miguel Hernández); Galiano, V. (Universidad Miguel Hernández).

Publisher in Institute of Electrical and Electronics Engineers Inc.

Abstract: In this paper a new method to calculate the five parameters of the single-diode model of a photovoltaic cell or panel is presented. This new method takes into account the intrinsic properties of the model equation and the technique of linear least-squares fitting, so, the computational complexity and costs are very low. Moreover, the proposed method, named Two-Step Linear Least-Squares (TSLLS) method, is able to work absolutely blindly with any kind of I-V curve. It does not need initial guesses at all and, consequently, it is not necessary to know previously any information of any parameter. The proposed method provides the parameters of the single-diode model just using the coordinates of N points (N$\geq$5) of the I-V curve. The results provided by this method in a first stage have the same order of accuracy of the best documented methods in the field of parameters extraction, but, furthermore, in a second stage the best accuracy documented until now is obtained in two important case studies usually used in the literature as well as in a large-scale I-V curve repository with more than one million of curves. IEEE

Two-step benchmarking: Setting more realistically achievable targets in DEA

Ramón, N. (Universidad Miguel Herández); Ruíz, J.L. (Universidad Miguel Hernández); Sirvent, I. (Universidad Miguel Hernández).


Abstract: The models that set the closest targets have made an important contribution to DEA as tool for the best-practice benchmarking of decision making units (DMUs). These models may help defining plans for improvement that require less effort from the DMUs. However, in practice we often find cases of poor performance, for which closest targets are still unattainable. For those DMUs, we propose a two-step benchmarking procedure within the spirit of context-dependent DEA and that of the models that minimize the distance to the DEA efficient frontier. This procedure allows to setting more realistically achievable targets in the short term. In addition, it may offer different alternatives for planning improvements directed towards DEA efficient targets, which can be seen as representing improvements in a long term perspective. Thus, the sequential approach provides managers with a decision-support tool for the design of continuous improvement strategies based on actionable targets, by learning from better practices of others as an expert system. To illustrate, we examine an example which is concerned with the research performance of public Spanish universities. © 2017 Elsevier Ltd

A novel characterisation-based algorithm to discover new knowledge from classification datasets without use of support

Lazcorreta Puigmartí, E. (Universidad Miguel Hernández); Botella, F. (Universidad Miguel Hernández); Fernández-Caballero, A (Universidad Castilla- La Mancha)

Abstract: This paper introduces a novel proposal to discover the best associative classification rules through studying the influence of the attributes used in robust catalogues. Notice that a catalogue is defined as a dataset free of duplicate records. Moreover, a robust catalogue is obtained when incomplete records and those with uncertainty are eliminated from a catalogue. Therefore, a robust catalogue is a collection of association rules with 100% confidence and unitary support. In this paper we demonstrate that robust catalogues contain the same association rules as the datasets from which they were obtained, but can be managed in memory without eliminating any data from the analysis. In fact, the experiments performed show that all robust catalogues contained in a classification dataset are easily obtained, providing millions of associative classification rules with 100% confidence to the expert researcher in data mining. © 2017 Elsevier Ltd

A note on measuring group performance over time with pseudo-panels

Aparicio, J.(Miguel Hernandez University of Elche); Santin, D. (Complutense University of Madrid).

Abstract: Aparicio, Crespo-Cebada, Pedraja-Chaparro, and Santin (2017) recently extended the Camanho and Dyson (2006) Malmquist-type index (CDMI) for determining group performance in cross-sectional studies to panel or pseudo-panel databases. In that paper, it was shown that the pseudo-panel Malmquist index (PPMI) can be easily interpreted as the ratio of aggregated productivity changes in two groups of decision making units over time, if and only if a new difficult-to-interpret term, the so called ‘divergence component’ (DC), is equal to one. The aim of this paper is twofold. First, based upon considering a baseline group technology, we define a new base-group base-period PPMI where the DC always vanishes. Second, when more than two groups are analyzed, we show that under this framework the new base-group base-period PPMI, the new base-group CDMI and the components of both indexes satisfy the circular relation. Both results will make it easier for practitioners applying the two indexes in different economic sectors, regardless of how many groups are being compared.

Derivation and validation model for hospital hypoglycemia

Ena, J.(Hospital Marina Baixa); Gaviria, A.Z.(Hospital de Fuenlabrada); Romero Sánchez, M. (Hospital de Fuenlabrada); Carretero Gómez, J. (Hospital de Zafra, Badajoz); Carrasco Sánchez, F.J. (Hospital Juan Ramón Jiménez); Segura Heras, J.V. (Universidad Miguel Hernández); Porto Pérez, A.B. (Complexo Hospitalario Universitario de A Coruña); Vázquez Rodríguez, P. (Complexo Hospitalario Universitario de A Coruña); González Bezerra, C.(Hospital San Juan de Dios); Gómez Huelgas, R. (Hospital Regional Universitario).

Background An objective and simple prognostic model for hospitalized patients with hypoglycemia could be helpful in guiding initial intensity of treatment. Methods We carried out a derivation rule for hypoglycemia using data from a nationwide retrospective cohort study of patients with diabetes or hyperglycemia carried out in 2014 (n = 839 patients). The rule for hypoglycemia was validated using a second data set from a nationwide retrospective cohort study carried out in 2016 (n = 561 patients). We derived our prediction rule using logistic regression with hypoglycemia (glucose less than 70 mg/dL) as the primary outcome. Results The incidence of hypoglycemia in the derivation cohort was 10.3%. Patient’s characteristics independently associated with hypoglycemia included episodes of hypoglycemia during the previous three months (odds ratio [OR]: 6.29, 95% confidence interval [95%CI]: 3.37–11.79, p < 0.001) estimated glomerular filtration rate lower than 30 mL/min/1.73 m2 (OR: 2.32, 95%CI: 1.23–4.35, p = 0.009), daily insulin dose greater than 0.3 units per Kg (OR: 1.74, 95%CI: 1.06–2.85, p = 0.028), and days of hospitalization (OR: 1.03, 95%CI: 1.01–1.04, p = 0.001). The model showed an area under the curve (AUC): 0.72 (95%CI: 0.66–0.78, p < 0.001). The AUC in the validation cohort was: 0.71 (95%CI: 0.63–0.79, p < 0.001). Conclusions The rule showed fair accuracy to predict hypoglycemia. Implementation of the rule into computer systems could be used in guiding initial insulin therapy. © 2017 European Federation of Internal Medicine.