A second derivative SQP method: theoretical issues

Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second derivative information may often be calculated, there is little practical theory that justifies exact-Hessian SQP methods. In particular, the resulting quadratic programming (QP) subproblems are often nonconvex, and thus finding their global solutions may be computationally nonviable. This paper presents a second-derivative SQP method based on quadratic subproblems that are either convex, and thus may be solved efficiently, or need not be solved globally. Additionally, an explicit descent-constraint is imposed on certain QP subproblems, which “guides” the iterates through areas in which nonconvexity is a concern. Global convergence of the resulting algorithm is established

A second derivative SQP method: local convergence

In [19], we gave global convergence results for a second-derivative SQP method for minimizing the exact ℓ1-merit function for a fixed value of the penalty parameter. To establish this result, we used the properties of the so-called Cauchy step, which was itself computed from the so-called predictor step. In addition, we allowed for the computation of a variety of (optional) SQP steps that were intended to improve the efficiency of the algorithm. \ud \ud Although we established global convergence of the algorithm, we did not discuss certain aspects that are critical when developing software capable of solving general optimization problems. In particular, we must have strategies for updating the penalty parameter and better techniques for defining the positive-definite matrix Bk used in computing the predictor step. In this paper we address both of these issues. We consider two techniques for defining the positive-definite matrix Bk—a simple diagonal approximation and a more sophisticated limited-memory BFGS update. We also analyze a strategy for updating the penalty paramter based on approximately minimizing the ℓ1-penalty function over a sequence of increasing values of the penalty parameter.\ud \ud Algorithms based on exact penalty functions have certain desirable properties. To be practical, however, these algorithms must be guaranteed to avoid the so-called Maratos effect. We show that a nonmonotone varient of our algorithm avoids this phenomenon and, therefore, results in asymptotically superlinear local convergence; this is verified by preliminary numerical results on the Hock and Shittkowski test set

Fetal liver blood flow distribution: role in human developmental strategy to prioritize fat deposition versus brain development

Among primates, human neonates have the largest brains but also the highest proportion of body fat. If placental nutrient supply is limited, the fetus faces a dilemma: should resources be allocated to brain growth, or to fat deposition for use as a potential postnatal energy reserve? We hypothesised that resolving this dilemma operates at the level of umbilical blood distribution entering the fetal liver. In 381 uncomplicated pregnancies in third trimester, we measured blood flow perfusing the fetal liver, or bypassing it via the ductus venosus to supply the brain and heart using ultrasound techniques. Across the range of fetal growth and independent of the mother's adiposity and parity, greater liver blood flow was associated with greater offspring fat mass measured by dual-energy X-ray absorptiometry, both in the infant at birth (r = 0.43, P<0.001) and at age 4 years (r = 0.16, P = 0.02). In contrast, smaller placentas less able to meet fetal demand for essential nutrients were associated with a brain-sparing flow pattern (r = 0.17, p = 0.02). This flow pattern was also associated with a higher degree of shunting through ductus venosus (P = 0.04). We propose that humans evolved a developmental strategy to prioritize nutrient allocation for prenatal fat deposition when the supply of conditionally essential nutrients requiring hepatic inter-conversion is limited, switching resource allocation to favour the brain if the supply of essential nutrients is limited. Facilitated placental transfer mechanisms for glucose and other nutrients evolved in environments less affluent than those now prevalent in developed populations, and we propose that in circumstances of maternal adiposity and nutrient excess these mechanisms now also lead to prenatal fat deposition. Prenatal developmental influences play important roles in the human propensity to deposit fa

Perceptions of trends in Seychelles artisanal trap fisheries: comparing catch monitoring, underwater visual census and fishers' knowledge

Fisheries scientists and managers are increasingly engaging with fishers' knowledge (FK) to provide novel information and improve the legitimacy of fisheries governance. Disputes between the perceptions of fishers and scientists can generate conflicts for governance, but can also be a source of new perspectives or understandings. This paper compares artisanal trap fishers' reported current catch rates with landings data and underwater visual census (UVC). Fishers' reports of contemporary 'normal' catch per day tended to be higher than recent median landings records. However, fishers' reports of 'normal' catch per trap were not significantly different from the median CPUE calculated from landings data, and reports of 'good' and 'poor' catch rates were indicative of variability observed in landings data. FK, landings and UVC data all gave different perspectives of trends over a ten-year period. Fishers' perceptions indicated greater declines than statistical models fitted to landings data, while UVC evidence for trends varied between sites and according to the fish assemblage considered. Divergence in trend perceptions may have resulted from differences in the spatial, temporal or taxonomic focus of each dataset. Fishers may have experienced and understood behavioural changes and increased fishing power, which may have obscured declines from landings data. Various psychological factors affect memory and recall, and may have affected these memory-based estimates of trends, while different assumptions underlying the analysis of both interview data and conventional scientific data could also have led to qualitatively different trend perceptions. Differing perspectives from these three data sources illustrate both the potential for 'cognitive conflicts' between stakeholders who do not rely on the same data sources, as well as the importance of multiple information sources to understand dynamics of fisheries. Collaborative investigation of such divergence may facilitate learning and improve fisheries governance

Interventions to reduce suicides at suicide hotspots: a systematic review

Background: 'Suicide hotspots' include tall structures (for example, bridges and cliffs), railway tracks, and isolated locations (for example, rural car parks) which offer direct means for suicide or seclusion that prevents intervention. Methods. We searched Medline for studies that could inform the following question: 'What interventions are available to reduce suicides at hotspots, and are they effective?'. Results: There are four main approaches: (a) restricting access to means (through installation of physical barriers); (b) encouraging help-seeking (by placement of signs and telephones); (c) increasing the likelihood of intervention by a third party (through surveillance and staff training); and (d) encouraging responsible media reporting of suicide (through guidelines for journalists). There is relatively strong evidence that reducing access to means can avert suicides at hotspots without substitution effects. The evidence is weaker for the other approaches, although they show promise. Conclusions: More well-designed intervention studies are needed to strengthen this evidence base. © 2013 Cox et al.; licensee BioMed Central Ltd.published_or_final_versio

Meta-analysis of honey bee neurogenomic response links deformed wing virus type A to precocious behavioral maturation

Crop pollination by the western honey bee Apis mellifera is vital to agriculture but threatened by alarmingly high levels of colony mortality, especially in Europe and North America. Colony loss is due, in part, to the high viral loads of Deformed wing virus (DWV), transmitted by the ectoparasitic mite Varroa destructor, especially throughout the overwintering period of a honey bee colony. Covert DWV infection is commonplace and has been causally linked to precocious foraging, which itself has been linked to colony loss. Taking advantage of four brain transcriptome studies that unexpectedly revealed evidence of covert DWV-A infection, we set out to explore whether this effect is due to DWV-A mimicking naturally occurring changes in brain gene expression that are associated with behavioral maturation. Consistent with this hypothesis, we found that brain gene expression profiles of DWV-A infected bees resembled those of foragers, even in individuals that were much younger than typical foragers. In addition, brain transcriptional regulatory network analysis revealed a positive association between DWV-A infection and transcription factors previously associated with honey bee foraging behavior. Surprisingly, single-cell RNA-Sequencing implicated glia, not neurons, in this effect; there are relatively few glial cells in the insect brain and they are rarely associated with behavioral plasticity. Covert DWV-A infection also has been linked to impaired learning, which together with precocious foraging can lead to increased occurrence of infected bees from one colony mistakenly entering another colony, especially under crowded modern apiary conditions. These findings provide new insights into the mechanisms by which DWV-A affects honey bee health and colony survival

A Pilot Study Of Group Mindfulness‐Based Cognitive Therapy (Mbct) For Combat Veterans With Posttraumatic Stress Disorder (Ptsd)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98769/1/da22104.pd