Foreign Surrogate Motherhood: mater semper certa erat

This Article compares the conflicting approaches to resolve the questions surrounding surrogate motherhood in a domestic context and then addresses some of its transnational implications, especially the recognition of foreign surrogacy judgments. It argues that not every case of foreign surrogacy involves the circumvention of the forum's prohibition of surrogacy and that courts need to take this into account when applying the public policy exception. It further argues that the adoption of the child by the commissioning parents should be seen as an alternative and adequate solution to the limping legal parenthood that would otherwise arise from the non-recognition of a surrogacy judgment.

Physical activity intensity and surrogate markers for cardiovascular health in adolescents

We examined the impact of physical activity (PA) on surrogate markers of cardiovascular health in adolescents. 52 healthy students (28 females, mean age 14.5 ± 0.7 years) were investigated. Microvascular endothelial function was assessed by peripheral arterial tonometry to determine reactive hyperemic index (RHI). Vagal activity was measured using 24 h analysis of heart rate variability [root mean square of successive normal-to-normal intervals (rMSSD)]. Exercise testing was performed to determine peak oxygen uptake ([Formula: see text]) and maximum power output. PA was assessed by accelerometry. Linear regression models were performed and adjusted for age, sex, skinfolds, and pubertal status. The cohort was dichotomized into two equally sized activity groups (low vs. high) based on the daily time spent in moderate-to-vigorous PA (MVPA, 3,000-5,200 counts(.)min(-1), model 1) and vigorous PA (VPA, >5,200 counts(.)min(-1), model 2). MVPA was an independent predictor for rMSSD (β = 0.448, P = 0.010), and VPA was associated with maximum power output (β = 0.248, P = 0.016). In model 1, the high MVPA group exhibited a higher vagal tone (rMSSD 49.2 ± 13.6 vs. 38.1 ± 11.7 ms, P = 0.006) and a lower systolic blood pressure (107.3 ± 9.9 vs. 112.9 ± 8.1 mmHg, P = 0.046). In model 2, the high VPA group had higher maximum power output values (3.9 ± 0.5 vs. 3.4 ± 0.5 W kg(-1), P = 0.012). In both models, no significant differences were observed for RHI and [Formula: see text]. In conclusion, in healthy adolescents, PA was associated with beneficial intensity-dependent effects on vagal tone, systolic blood pressure, and exercise capacity, but not on microvascular endothelial function.

Genuine cross-correlations: Which surrogate based measure reproduces analytical results best?

The analysis of short segments of noise-contaminated, multivariate real world data constitutes a challenge. In this paper we compare several techniques of analysis, which are supposed to correctly extract the amount of genuine cross-correlations from a multivariate data set. In order to test for the quality of their performance we derive time series from a linear test model, which allows the analytical derivation of genuine correlations. We compare the numerical estimates of the four measures with the analytical results for different correlation pattern. In the bivariate case all but one measure performs similarly well. However, in the multivariate case measures based on the eigenvalues of the equal-time cross-correlation matrix do not extract exclusively information about the amount of genuine correlations, but they rather reflect the spatial organization of the correlation pattern. This may lead to failures when interpreting the numerical results as illustrated by an application to three electroencephalographic recordings of three patients suffering from pharmacoresistent epilepsy.

Taking Root in the Silicon Forest: High-technology Firms as Surrogate Universities in Portland, Oregon

Most case studies of successful high-technology industry regions highlight the role of research universities in fostering regional economic development. The Portland, Oregon, region managed to root a thriving high-tech industry in the absence of this critical factor. In this article, I present a case study of the evolution of Portland's high-tech industry and propose that high-tech firms can act as surrogate universities that attract and develop labor, create knowledge, and function as incubators for startups. I conclude that planners working to develop high-tech industries in regions without major research universities should attract R&D-intensive firms, maintain information on key busineses and entrepreneurial ventures, support an innovation milieu, and set realistic goals.

SOMS: SurrOgate MultiStart algorithm for use with nonlinear programming for global optimization

SOMS is a general surrogate-based multistart algorithm, which is used in combination with any local optimizer to find global optima for computationally expensive functions with multiple local minima. SOMS differs from previous multistart methods in that a surrogate approximation is used by the multistart algorithm to help reduce the number of function evaluations necessary to identify the most promising points from which to start each nonlinear programming local search. SOMS’s numerical results are compared with four well-known methods, namely, Multi-Level Single Linkage (MLSL), MATLAB’s MultiStart, MATLAB’s GlobalSearch, and GLOBAL. In addition, we propose a class of wavy test functions that mimic the wavy nature of objective functions arising in many black-box simulations. Extensive comparisons of algorithms on the wavy testfunctions and on earlier standard global-optimization test functions are done for a total of 19 different test problems. The numerical results indicate that SOMS performs favorably in comparison to alternative methods and does especially well on wavy functions when the number of function evaluations allowed is limited.

SOP: Parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centers from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.