A decomposition result for a class of polling models

Boxma and Groenendijk have shown that the workload in polling models decomposes into two independent variables. This paper demonstrates a different type of decomposition that has an explicit multi-dimensional form. This decomposition does not apply to all polling models, but does, for example, apply to models with constant switch-over times and either exhaustive or gated service disciplines. For such models, we show that the population of customers present in the system (represented by a vector indicating the number of customers at each queue) at key time points breaks into two independent subpopulations: (1) the population of customers present in the related model with zero switch-over times; (2) another population, which is particularly easy to analyze. This result has a number of theoretical and applied implications.     

Importance of the choice of assumptions and models in the estimation of analytical quality specifications

The validity of any model depends on its ability to imagine the situation or problem to which it is applied. Further, the assumptions made in relation to the model are determining for the actual outcome. Within the field of clinical biochemistry a lot of models for analytical quality specifications, based on a variety of concepts and ’clinical settings’, have been proposed. A hierarchical structure for application of these approaches and models has been agreed on at several occasions in 1999. In this hierarchy, the highest rank is given to evaluation of analytical quality specifications based on ’clinical settings’/’clinical outcome’ models, followed by specifications based on biological variation and on ’clinicians opinions’. This contribution, deals with the problems of combining random and systematic errors and the implications of application of different models to a variety of clinical settings. Received: 1 June, 2002 Accepted: 17 July 2002 Presented at the European Conference on Quality in the Spotlight in Medical Laboratories, 7–9 October 2001, Antwerp, Belgium     

Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing

ABSTRACT

Existing data on structures and biological activities are limited and distributed unevenly across distinct molecular targets and chemical compounds. The question arises if these data represent an unbiased sample of the general population of chemical-biological interactions. To answer this question, we analyzed ChEMBL data for 87,583 molecules tested against 919 protein targets using supervised and unsupervised approaches. Hierarchical clustering of the Murcko frameworks generated using Chemistry Development Toolkit showed that the available data form a big diffuse cloud without apparent structure. In contrast hereto, PASS-based classifiers allowed prediction whether the compound had been tested against the particular molecular target, despite whether it was active or not. Thus, one may conclude that the selection of chemical compounds for testing against specific targets is biased, probably due to the influence of prior knowledge. We assessed the possibility to improve (Q)SAR predictions using this fact: PASS prediction of the interaction with the particular target for compounds predicted as tested against the target has significantly higher accuracy than for those predicted as untested (average ROC AUC are about 0.87 and 0.75, respectively). Thus, considering the existing bias in the data of the training set may increase the performance of virtual screening.     

Limit of detection estimator for second-order bilinear calibration

A new approach is developed for estimating the limit of detection in second-order bilinear calibration with the generalized rank annihilation method (GRAM). The proposed estimator is based on recently derived expressions for prediction variance and bias. It follows the latest IUPAC recommendations in the sense that it concisely accounts for the probabilities of committing both types I and II errors, i.e. false positive and false negative declarations, respectively. The estimator has been extensively validated with simulated data, yielding promising results.     

Optimal convergence properties of kernel density estimators without differentiability conditions

Let X ₁, X ₂, ..., X _n be independent observations from an (unknown) absolutely continuous univariate distribution with density f and let % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXafv3ySLgzGmvETj2BSbqefm0B1jxALjhiov2D% aebbfv3ySLgzGueE0jxyaibaiiYdd9qrFfea0dXdf9vqai-hEir8Ve% ea0de9qq-hbrpepeea0db9q8as0-LqLs-Jirpepeea0-as0Fb9pgea% 0lrP0xe9Fve9Fve9qapdbaqaaeGacaGaaiaabeqaamaabaabcaGcba% GabmOzayaajaGaaiikaiaadIhacaGGPaGaeyypa0Jaaiikaiaad6ga% caWGObGaaiykamaaCaaaleqabaGaeyOeI0IaaGymaaaakmaaqadaba% Gaam4saiaacUfadaWcgaqaaiaacIcacaWG4bGaeyOeI0Iaamiwamaa% BaaaleaacaWGPbaabeaakiaacMcaaeaacaWGObGaaiyxaaaaaSqaai% aadMgacqGH9aqpcaaIXaaabaGaamOBaaqdcqGHris5aaaa!5356!\[\hat f(x) = (nh)^{ - 1} \sum\nolimits_{i = 1}^n {K[{{(x - X_i )} \mathord{\left/ {\vphantom {{(x - X_i )} {h]}}} \right. \kern-\nulldelimiterspace} {h]}}} \] be a kernel estimator of f(x) at the point x, \s-<x<, with h=h _n (h _n O and nh _n , as n) the bandwidth and K a kernel function of order r. Optimal rates of convergence to zero for the bias and mean square error of such estimators have been studied and established by several authors under varying conditions on K and f. These conditions, however, have invariably included the assumption of existence of the r-th order derivative for f at the point x. It is shown in this paper that these rates of convergence remain valid without any differentiability assumptions on f at x. Instead some simple regularity conditions are imposed on the density f at the point of interest. Our methods are based on certain results in the theory of semi-groups of linear operators and the notions and relations of calculus of finite differences.This research was supported in part by grants from the Natural Sciences and Engineering Research Council of Canada and the University of Alberta Central Research Fund.     

浅埋偏压连拱隧道现场监测与结构受力分析研究

针对浅埋偏压连拱隧道结构受力的复杂性,结合石红高速大中山1#连拱隧道的实际情况,选择典型断面埋设监控量测设备对隧道施工过程中围岩变形和结构受力进行适时监测,并结合有限元分析软件MIDAS,对中隔墙空间受力特征进行研究.得出了支护结构在偏压作用下和施工扰动下的受力状态和变形特征.结果表明,在浅埋偏压条件下,减少支护结构受力的不均对于保证隧道结构稳定的重要性以及运用监控量测与数值模拟相互印证的方法可以更准确地分析隧道结构的稳定性,更好地指导施工.     

Female Faculty: Why So Few and Why Care?

Despite slow ongoing progress in increasing the representation of women in academia, women remain significantly under-represented at senior levels, in particular in the natural sciences and engineering. Not infrequently, this is downplayed by bringing forth arguments such as inherent biological differences between genders, that current policies are adequate to address the issue, or by deflecting this as being “not my problem” among other examples. In this piece we present scientific evidence that counters these claims, as well as a best-practice example, Genie, from Chalmers University of Technology, where one of the authors is currently employed. We also highlight particular challenges caused by the current COVID-19 pandemic. Finally, we conclude by proposing some possible solutions to the situation and emphasize that we need to all do our part, to ensure that the next generation of academics experience a more diverse, inclusive, and equitable working environment.     

Magnetic behavior of a nano-disk constrained in an antiferromagnetic substrate

In this work we report a numerical Monte Carlo study of the behavior of a magnetic nano-disk put over an antiferromagnetic substrate. Three approaches were considered for describe the substrate: (1) A stacked antiferromagnetic configuration, (2) an Ising like arrangement and (3) Heisenberg like spins. For the Heisenberg case we still have considered an easy-plane and an easy-axis symmetry of the substrate. The hysteresis loop for the nano-disk is obtained by considering the three cases. The signature of the vortex in the nano-disk appears as small jumps in the hysteresis curve. Exchange bias effects are observed since the substrate has an easy axis symmetry.     

Signatures of spin-glass freezing in Co/CoO nanospheres and nanodiscs

We present a study of the magnetic properties of Co nanoparticles having a combination of both spherical and disk shapes. The hcp Co nanospheres with an average diameter of 11 nm and nanodiscs of dimensions ∼2.5×15 nm² were prepared by thermal decomposition of di-cobalt octacarbonyl in the presence of an amine surfactant. The as-synthesized nanoparticles were oxidized to grow an antiferromagnetic layer. High resolution transmission electron microscopy showed the presence of a ferromagnet/antiferromagnet (Co/CoO) interface with a 2.2-nm thick CoO shell on the spherical nanoparticles and 0.5 nm thick on nanodiscs. We report the temperature and field dependent DC magnetization, frequency, field, and temperature dependent AC susceptibility, and the radio frequency transverse susceptibility. A low temperature paramagnetic behavior was observed in the DC magnetization at high fields and is assigned to defects in the CoO shell that are not coupled to the antiferromagnetic lattice. Our results support the existence of a low temperature frozen, disordered magnetic state, characterized by a strong exchange coupling between the structurally disordered, spin-glass CoO shell and Co core.