21,963 research outputs found
An informational approach to the global optimization of expensive-to-evaluate functions
In many global optimization problems motivated by engineering applications,
the number of function evaluations is severely limited by time or cost. To
ensure that each evaluation contributes to the localization of good candidates
for the role of global minimizer, a sequential choice of evaluation points is
usually carried out. In particular, when Kriging is used to interpolate past
evaluations, the uncertainty associated with the lack of information on the
function can be expressed and used to compute a number of criteria accounting
for the interest of an additional evaluation at any given point. This paper
introduces minimizer entropy as a new Kriging-based criterion for the
sequential choice of points at which the function should be evaluated. Based on
\emph{stepwise uncertainty reduction}, it accounts for the informational gain
on the minimizer expected from a new evaluation. The criterion is approximated
using conditional simulations of the Gaussian process model behind Kriging, and
then inserted into an algorithm similar in spirit to the \emph{Efficient Global
Optimization} (EGO) algorithm. An empirical comparison is carried out between
our criterion and \emph{expected improvement}, one of the reference criteria in
the literature. Experimental results indicate major evaluation savings over
EGO. Finally, the method, which we call IAGO (for Informational Approach to
Global Optimization) is extended to robust optimization problems, where both
the factors to be tuned and the function evaluations are corrupted by noise.Comment: Accepted for publication in the Journal of Global Optimization (This
is the revised version, with additional details on computational problems,
and some grammatical changes
Analytical Solution of the Voter Model on Disordered Networks
We present a mathematical description of the voter model dynamics on
heterogeneous networks. When the average degree of the graph is
the system reaches complete order exponentially fast. For , a finite
system falls, before it fully orders, in a quasistationary state in which the
average density of active links (links between opposite-state nodes) in
surviving runs is constant and equal to , while an
infinite large system stays ad infinitum in a partially ordered stationary
active state. The mean life time of the quasistationary state is proportional
to the mean time to reach the fully ordered state , which scales as , where is the number of nodes of the
network, and is the second moment of the degree distribution. We find
good agreement between these analytical results and numerical simulations on
random networks with various degree distributions.Comment: 20 pages, 8 figure
The impact of the Covid-19 lockdown on the experiences and feeding practices of new mothers in the UK: Preliminary data from the COVID-19 New Mum Study
BACKGROUND: The COVID-19 New Mum Study is recording maternal experiences and infant feeding during the UK lockdown. This report from week 1 of the survey describes and compares the delivery and post-natal experiences of women who delivered before (BL) versus during (DL) the lockdown. METHODS: Women living in the UK aged ≥18 years with an infant ≤12 months of age completed an anonymous online survey (https://is.gd/covid19newmumstudy). Information/links are shared via websites, social media and existing contacts. RESULTS: From 27.5 to 20-3.6.20, 1365 women provided data (94% white, 95% married/with partner, 66% degree/higher qualification, 86% living in house; 1049 (77%) delivered BL and 316 (23%) DL. Delivery mode, skin-to-skin contact and breastfeeding initiation did not differ between groups. DL women had shorter hospital stays (p < 0.001). 39% reported changes to their birth plan. Reflecting younger infant age, 59% of DL infants were exclusively breast-fed/mixed fed versus 39% of BL (p < 0.05). 13% reported a change in feeding; often related to lack of breastfeeding support, especially with practical problems. Important sources of feeding support were the partner (60%), health professional (50%) and online groups (47%). 45% of DL women reported insufficient feeding support. Among BL women, 57% and 69% reported decreased feeding support and childcare, respectively. 40% BL/45% DL women reported insufficient support with their own health, 8%/9% contacted a mental health professional; 11% reported their mental health was affected. 9% highlighted lack of contact/support from family and distress that they had missed seeing the baby. CONCLUSION: Lockdown has impacted maternal experiences, resulting in distress for many women. Our findings suggest the need for better infant feeding support, especially 'face-to-face' support for practical issues; and recognising and supporting mothers who are struggling with mental health challenges or other aspects of their health. The effectiveness of online versus face-to-face contact is currently uncertain, and requires further evaluation
The Bak-Sneppen Model on Scale-Free Networks
We investigate by numerical simulations and analytical calculations the
Bak-Sneppen model for biological evolution in scale-free networks. By using
large scale numerical simulations, we study the avalanche size distribution and
the activity time behavior at nodes with different connectivities. We argue the
absence of a critical barrier and its associated critical behavior for infinite
size systems. These findings are supported by a single site mean-field analytic
treatment of the model.Comment: 5 pages and 3 eps figures. Final version appeared in Europhys. Let
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