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We propose performance profiles -- distribution functions for a performance metric -- as a tool for benchmarking and comparing optimization software. We show that performance profiles combine the best features of other tools for performance evaluation.

We examine the local convergence properties of pattern search methods, complementing the previously established global convergence properties for this class of algorithms. We show that the step-length control parameter which appears in the definition of pattern search algorithms provides a reliable asymptotic measure of first-order stationarity. This gives an analytical justification for a traditional stopping criterion for pattern search methods. Using this measure of first-order stationarity, we both revisit the global convergence properties of pattern search and analyze the behavior of pattern search in the neighborhood of an isolated local minimizer.

We examine the importance of optimality measures when benchmarking a set of solvers and show that the scale-invariance requirements we impose lead to a convergence test for nonlinearly constrained optimization solvers that uses a mixture of absolute and relative error measures. We demonstrate that this convergence test is well behaved at any point where the constraints satisfy the Mangasarian--Fromovitz constraint qualification and also avoids the explicit use of a complementarity measure. Computational experiments explore the impact of this convergence test on the benchmarking process with performance profiles.

The NEOS server provides access to a variety of optimization resources via the Internet. The new Kestrel interface to the server enables local modeling environments to request NEOS optimization services and retrieve the results for local visualization and analysis so that users have the same convenient access to remote NEOS solvers as to those installed locally. Kestrel agents have been implemented for the AMPL and GAMS modeling environments; these agents have been designed so that subproblems can be queued for execution and later retrieval of results, making possible a rudimentary form of parallel processing.

The NEOS Server 4.0 provides a general Internet-based client/server as a link between users and software applications. The administrative guide covers the fundamental principals behind the operation of the NEOS Server, installation and trouble-shooting of the Server software, and implementation details of potential interest to a NEOS Server administrator. The guide also discusses making new software applications available through the Server, including areas of concern to remote solver administrators such as maintaining security, providing usage instructions, and enforcing reasonable restrictions on jobs. The administrative guide is intended both as an introduction to the NEOS Server and as a reference for use when running the Server.

We propose performance profiles-distribution functions for a performance metric-as a tool for benchmarking and comparing optimization software. We show that performance profiles combine the best features of other tools for performance evaluation.

Fourer et al examine the development of modeling languages, the most widely established advance in software support for large-scale optimization. A modeling language is designed to let engineers and analysts describe mathematical models to a computer system in much the same way that they would describe models to other people. The advent of modeling languages for optimization has greatly reduced the difficulty of prototyping, testing, and maintaining realistically complex models. By allowing for interfaces to numerous optimization algorithm implementations--so-called \"solvers\"--modeling languages also have the potential to encourage comparisons between optimization methods.

Background Youth with type 1 diabetes (T1D) are encouraged to participate in physical activity (PA). Studies have identified fear of hypoglycemia (FOH) as a barrier to participating in PA. Objectives To examine (a) PA patterns in youth with T1D by age group and (b) the relationship between both parental and youth FOH and youth PA. Methods A cross‐sectional analysis from the SEARCH cohort study visit of youth ages 10 to 17 years with T1D (n = 1129) was conducted. Linear regression models estimated the association between self‐reported number of days of vigorous PA (VPA) and moderate PA (MPA) and both youth‐ and parent‐reported FOH. Multivariable models were adjusted for age, sex, race, duration of T1D, HbA1c, use of continuous glucose monitoring (CGM), recent severe hypoglycemia, primary insulin regimen, and BMI. Results Participants were 52% female, had mean (sd) age 14.4 (4.2) years, diabetes duration 7.5 years (1.8), HbA1c 9.2% (1.7). Older youth were less likely to engage in VPA (P < .01), or sports teams (P < .01), but more likely to engage in MPA (P < .01). Higher youth FOH (behavior subscale) was associated with increased levels of VPA (β (se) 0.30 (0.11), P = .01) but not significantly associated with MPA (P = .06). There was no statistically significant association between parental FOH and youth PA. Conclusions In SEARCH participants with T1D, VPA, and team sports participation declined with age, while MPA increased. We observed that higher scores on the youth FOH behavioral subscale were associated with increased VPA levels, suggesting that FOH may be less of a barrier to PA than previously thought.

The powerful interconnectedness of people and their pets means that the health and welfare of families and communities is entwined with the health and welfare of their pets. Because pets are not adequately considered in public health research and policy currently, the onus is disproportionately placed on the animal welfare field to solve community health problems associated with caring for pets. Response efforts may disproportionately affect vulnerable families who have fewer options for transportation and housing away from the disaster area.13,14 Planning that incorporates pet-inclusive evacuations increases the likelihood of pet owners' compliance; the Federal Emergency Management Agency's best practice guidelines already capture health and safety considerations, including for pets. [...]animal welfare organizations have expertise in designing shelters to increase safety and ensure legal compliance. The model shows the downstream effects on pets from social determinates related to human health, including environment, community, and economic stability.17 A comprehensive approach to community well-being, including public health research and policy planning for families, can help keep people and their pets together.17 Tendrils of intersection between public health and animal welfare are beginning to strengthen, primarily driven by the efforts of animal welfare organizations to draw in public health professionals. Animal welfare organizations are making connections to human health entities such as social workers, food banks, and One Health clinics, and are switching to harm reduction approaches that shiftanimal control from punitive to supportive models to ameliorate negative consequences.18 A few key actions could help the public health field begin to consciously address the intersection of human and pet health.

Research suggest prenatal vaccination against coronavirus disease-19 (COVID-19) is safe. However, previous studies utilized retrospectively collected data or examined late pregnancy vaccinations. We investigated the associations of COVID-19 vaccination throughout pregnancy with delivery and neonatal outcomes. We included 1,794 mother-neonate dyads enrolled in the Generation C Study with known prenatal COVID-19 vaccination status and complete covariate and outcome data. We used multivariable quantile regressions to estimate the effect of prenatal COVID-19 vaccination on birthweight, delivery gestational age, and blood loss at delivery; and Poisson generalized linear models for Caesarean delivery (CD) and Neonatal Intensive Care Unit (NICU) admission. Using the above methods, we estimated effects of trimester of vaccine initiation on these outcomes. In our sample, 13.7% (n = 250) received at least one prenatal dose of any COVID-19 vaccine. Vaccination was not associated with birthweight (β = 12.42 g [-90.5, 114.8]), gestational age (β = 0.2 days [-1.1, 1.5]), blood loss (β = -50.6 ml [-107.0, 5.8]), the risks of CD (RR = 0.8; [0.6, 1.1]) or NICU admission (RR = 0.9 [0.5, 1.7]). Trimester of vaccine initiation was also not associated with these outcomes. Our findings suggest that there is no associated risk between prenatal COVID-19 vaccination and adverse delivery and neonatal outcomes in a cohort sample from NYC.