Magma Design Automation: Component placement on chips; the "holey cheese" problem.

The costs of the fabrication of a chip is partly determined by the wire length needed by the transistors to respect the wiring scheme. The transistors have to be placed without overlap into a prescribed configuration of blockades, i.e. parts of the chipthat are beforehand excluded from positioning by for example some other functional component, and holes, i.e. the remaining free area on the chip. A method to minimize the wire length when the free area is a simply connected domain has already been implemented by Magma, but the placement problem becomes much more complex when the free area is not a simply connected domain anymore, forming a ``holey cheese''. One of the approaches of the problem in this case is to first cluster the transistors into so-called macro's in such a way that closely interconnected transistors stay together, and that the macro's can be fit into the holes. One way to carry out the clustering is to use a graph clustering algorithm, the so-called Markov Cluster algorithm. Another way is to combine the placement method of Magma on a rectangular area of the same size as the total size of the holes, and a min cut-max flow algorithm to divide that rectangle into more or less rectangular macro's in such a way that as little wires as possible are cut. It is now possible to formulate the Quadratic Assignment Problem that remains after clustering the original problem to one with 100 up to 1000 macros. There exists a lot of literature on finding the global minimum of the costs, but nowadays computational possibilities are still too restrictive to find an optimal solution within a reasonable amount of time and computational memory. however, we believe it is possible to find a solution that leads to a acceptable local minimum of the costs

Ten years after the Dutch public health campaign on folic acid: the continuing challenge

BACKGROUND: Folic acid use in the periconceptional period reduces the risk of neural tube defects (NTDs). However, applying this knowledge in daily practice is not an easy task. We report here the current level of folic acid use in the Netherlands and discuss the figures within the framework of a national governmental campaign held in 1995 promoting the use of folic acid and the professional interventions undertaken since then. METHODS: We carried out six studies in the northern Netherlands during 1995, 1996, 1998, 2000, 2003 and 2005, respectively. The same methodology in the same health professionals' practices was followed in all studies. Pregnant women attending their first or second antenatal visit were asked to fill in a questionnaire aimed at assessing their awareness and use of folic acid. RESULTS: In 2005, most of the pregnant women used folic acid "at some time in their pregnancy", and 51% used it for the entire advised period. Prior knowledge on the protective affect of folic acid and on the period of use was strongly related to the level of education. The use of folic acid in a previous pregnancy [odds ratio (OR) 3.9, 95% confidence interval (95% CI) 1.6-9.9], the use of an oral contraceptive (OR 2.1, 95% CI 1.1-4.1) and parity (OR 0.08, 95% CI 0.01-0.5) significantly predicted the current correct use. The most recent figures revealed that there is still a large gap between more highly and less educated women in terms of taking folic acid in the advised period: 63 versus 31%, respectively. DISCUSSION: The aim of the Dutch Ministry of Health is to have 70% of Dutch women wanting to become pregnant use folic acid supplements in the advised period by 2010. While this level has almost been reached among more highly educated women (63%), it will take a great deal more effort, money and creativity to achieve the necessary increase from the current level of 31% among women with a lower educational background

Roses are unselfish: a greenhouse growth model to predict harvest rates.

We consider the question of how rose production in a greenhouse can be optimised. Based on realistic assumptions, a rose growth model is derived that can be used to predict the rose harvest. The model is made up of two constituent parts: (i) a local model that calculates the photosynthetic rate per area of leaf and (ii) a global model of the greenhouse that transforms the photosynthesis of the leaves into an increase in mass of the rose crop. The growth rate of the rose stems depends not only on the time-dependent ambient conditions within the greenhouse, which include temperature, relative humidity, CO$_2$ concentration and light intensity, but also on the location and age distribution of the leaves and the form of the underlying rose bush supporting the crop

Theory of asymmetric non-additive binary hard-sphere mixtures

We show that the formal procedure of integrating out the degrees of freedom of the small spheres in a binary hard-sphere mixture works equally well for non-additive as it does for additive mixtures. For highly asymmetric mixtures (small size ratios) the resulting effective Hamiltonian of the one-component fluid of big spheres, which consists of an infinite number of many-body interactions, should be accurately approximated by truncating after the term describing the effective pair interaction. Using a density functional treatment developed originally for additive hard-sphere mixtures we determine the zero, one, and two-body contribution to the effective Hamiltonian. We demonstrate that even small degrees of positive or negative non-additivity have significant effect on the shape of the depletion potential. The second virial coefficient $B_2$, corresponding to the effective pair interaction between two big spheres, is found to be a sensitive measure of the effects of non-additivity. The variation of $B_2$ with the density of the small spheres shows significantly different behavior for additive, slightly positive and slightly negative non-additive mixtures. We discuss the possible repercussions of these results for the phase behavior of binary hard-sphere mixtures and suggest that measurements of $B_2$ might provide a means of determining the degree of non-additivity in real colloidal mixtures

Newer long-acting insulin prescriptions for patients with type 2 diabetes: prevalence and practice variation in a retrospective cohort study

Background Little is known about prescription patterns of expensive non-recommended newer long-acting insulins (glargine 300 U/mL and degludec) for patients with type 2 diabetes mellitus (T2DM). Aim To identify practice variation in, and practice and patient-related characteristics associated with, the prescription of newer long-acting insulins to patients with T2DM in primary care. Design and setting A retrospective cohort study in Dutch general practices (Nivel Primary Care Database). Method A first prescription for intermediate or long-acting insulins in 2018 was identified in patients aged ≥40 years using other T2DM drugs. Per practice, the median percentage and interquartile range (IQR) of patients with newer insulin prescriptions were calculated. Multilevel logistic regression models were constructed to calculate intraclass correlation coefficients (ICCs) and quantify the association of patient and practice characteristics with prescriptions for newer insulins (odds ratios [ORs] and 95% confidence intervals [CIs]). Results In total, 7757 patients with prescriptions for intermediate or long-acting insulins from 282 general practices were identified. A median percentage of 21.2% (IQR 12.5-36.4%) of all patients prescribed intermediate or long-acting insulins per practice received a prescription for newer insulins. After multilevel modelling, the ICC decreased from 20% to 19%. Female sex (OR 0.77, 95% CI = 0.69 to 0.87), age ≥86 years compared with 40-55 years (OR 0.22, 95% CI = 0.15 to 0.34), prescriptions for metformin (OR 0.66, 95% CI = 0.53 to 0.82), sulfonylurea (OR 0.58, 95% CI = 0.51 to 0.66), or other newer T2DM drugs (OR 3.10, 95% CI = 2.63 to 3.66), and dispensing practices (OR 1.78, 95% CI = 1.03 to 3.10) were associated with the prescription of newer insulins. Conclusion The inter-practice variation in the prescription of newer insulins is large and could only be partially explained by patient- and practicerelated differences. This indicates substantial opportunities for improvement

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations

Meta-analysis of genome-wide association studies of anxiety disorders.

Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat-response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case-control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10(-8)); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10(-9)). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.Molecular Psychiatry advance online publication, 12 January 2016; doi:10.1038/mp.2015.197

Emericella quadrilineata as Cause of Invasive Aspergillosis

This opportunistic fungus is frequently misidentified because of its morphologic similarity to E. nidulans

Genetic risk profiles for depression and anxiety in adult and elderly cohorts

The first generation of genome-wide association studies (GWA studies) for psychiatric disorders has led to new insights regarding the genetic architecture of these disorders. We now start to realize that a larger number of genes, each with a small contribution, are likely to explain the heritability of psychiatric diseases. The contribution of a large number of genes to complex traits can be analyzed with genome-wide profiling. In a discovery sample, a genetic risk profile for depression was defined based on a GWA study of 1738 adult cases and 1802 controls. The genetic risk scores were tested in two population-based samples of elderly participants. The genetic risk profiles were evaluated for depression and anxiety in the Rotterdam Study cohort and the Erasmus Rucphen Family (ERF) study. The genetic risk scores were significantly associated with different measures of depression and explained up to ∼0.7% of the variance in depression in Rotterdam Study and up to ∼1% in ERF study. The genetic score for depression was also significantly associated with anxiety explaining up to 2.1% in Rotterdam study. These findings suggest the presence of many genetic loci of small effect that influence both depression and anxiety. Remarkably, the predictive value of these profiles was as large in the sample of elderly participants as in the middle-aged samples