The Yo-Yo tests are reliable for determining intermittent-exercise capacity and %HRpeak for soccer players and untrained 9- to 16-year-old girls. They also possess construct validity with better performances for soccer players compared with untrained age-matched girls, despite similar %HRpeak.

In order to reduce the curtailment of renewable generation in periods of low load, operators can limit the import net transfer capacity (NTC) of interconnections. This paper presents a probabilistic approach to support the operator in setting the maximum import NTC value in a way that the risk of curtailment remains below a pre-specified threshold. Main inputs are the probabilistic forecasts of wind power and solar PV generation, and special care is taken regarding the tails of the global margin distribution (all generation-all loads and pumping), since the accepted thresholds are generally very low. Two techniques are used for this purpose: interpolation with exponential functions and nonparametric estimation of extreme conditional quantiles using extreme value theory. The methodology is applied to five representative days, where situations ranging from high maximum NTC values to NTC=0 are addressed. Comparison of the two techniques for modeling tails is also comprised.

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Cloud computing is a service model that allows hosting and on demand distribution of computing resources all around the world, via Internet. Thus, cloud computing has become a successful paradigm that has been adopted and incorporated into virtually all major known IT companies (e.g., Google, Amazon, Microsoft). Based on this success, a large number of new companies were competitively created as providers of cloud computing services. This fact hindered the clients' ability to choose among those several cloud computing providers the most appropriate one to attend their requirements and computing needs. This work aims to specify a logical/mathematical multi-criteria scoring method able to select the most appropriate(s) cloud computing provider(s) to the user (customer), based on the analysis of performance indicator values desired by the customer and associated with every cloud computing provider that supports the demanded requirements. The method is a three stages algorithm that evaluates, scores, sorts and selects different cloud providers based on the utility of their performance indicators for each specific user of the method. An example of the method's usage is given in order to illustrate its operation.

Drug-induced liver injury (DILI) is an unpredictable and feared side effect of antituberculosis treatment (AT). The present study aimed to identify clinical and genetic variables associated with susceptibility to AT-associated hepatotoxicity in patients with pulmonary tuberculosis treated with a standard protocol. Of 233 patients enrolled, 90% prospectively, 103 developed liver injury: 37 with mild and 66 with severe phenotype (DILI). All patients with mild hepatitis had a RUCAM score ≥ 4 and all patients with DILI had a RUCAM score ≥ 6. Eight clinical variables and variants in six candidate genes were assessed. A logistic multivariate regression analysis identified four risk factors for AT-DILI: age ≥ 55 years (OR:3.67; 95% CI:1.82–7.41; p < 0.001), concomitant medication with other hepatotoxic drugs (OR:2.54; 95% CI:1.23–5.26; p = 0.012), NAT2 slow acetylator status (OR:2.46; 95% CI:1.25–4.84; p = 0.009), and carriers of p.Val444Ala variant for ABCB11 gene (OR:2.06; 95%CI:1.02–4.17; p = 0.044). The statistical model explains 24.9% of the susceptibility to AT-DILI, with an 8.9 times difference between patients in the highest and in the lowest quartiles of risk scores. This study sustains the complex architecture of AT-DILI. Prospective studies should evaluate the benefit of NAT2 and ABCB11 genotyping in AT personalization, particularly in patients over 55 years.

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