成分和厚度的依赖

通过调整Mn的成分，系统地研究了Ni81Fe19/Ni100-xMnx双层膜的磁学性质，特别是交换偏置场(Hex)的变化.当Ni100-xMnx中Mn的原子百分比在534%到600%之间时，对于150nm的Ni81Fe19，得到了最大的交换偏置场175kA/m，同时由于Mn对Ni81Fe19层的扩散所造成的磁矩的降低小于20%；高角x射线衍射证明Ni100-xMnx的晶格常数随着Mn成分的改变而变化，Mn含量越多，其晶格常数越大；制备态Ni100-xMnx膜晶格常数与θ相NiMn膜晶格常数的接近程度与NiMn膜θ相形成的容易程度相对应.也研究了交换偏置场随着Ni１００-xMnx厚度的变化，第一次得到了当Ni100-xMnx中Mn的原子百分比为706%时，Ni81Fe19(150nm)/Ni100-xMnx(90nm)双层膜在经过240℃，5h退火后，可以有80kA/m的交换偏置场，此时铁磁层磁矩的大小几乎不变. 关键词： Ni81Fe19/Ni100-xMnx 交换偏置场     

江汉平原上空QTEC变化特征的统计分析

提出了一种观测台网用多接收机性能一致性的标定方法，并利用江汉平原GPS接收台网的观测数据，分析了该地区上空QTEC的日变化、季节变化、年变化和逐年变化的统计特征．标定结果表明，不同接收机之间的仪器偏差是从双频GPS卫星信标推算QTEC的主要误差来源之一，必须校正．统计分析证实，江汉平原上空QTEC的日变化特征同时受电离层和等离子层控制，其年变化以半年周期为主，峰值和谷值分别出现在两分点和两至点附近，QTEC值的逐年变化从太阳活动峰年到低年逐年下降，与以太阳黑子数为代表的太阳活动密切相关．     

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.     

具有HfN/HfO2栅结构的p型MOSFET中的负偏置-温度不稳定性研究

研究了HfN/HfO₂高K栅结构p型金属-氧化物-半导体(MOS)晶体管(MOSFET)中，负 偏置-温度应力引起的阈值电压不稳定性(NBTI)特征.HfN/HfO₂高K栅结构的等效 氧化层厚度(EOT)为1.3nm，内含原生缺陷密度较低.研究表明，由于所制备的HfN/HfO₂ 高K栅结构具有低的原生缺陷密度，因此在p-MOSFET器件中观察到的NBTI属HfN/HfO2高K栅结构的本征特征，而非工艺缺陷引起的；进一步研究表明，该HfN/HfO₂高K栅结构中观察到的NBTI与传统的SiO₂基栅介质p-MOSFET器件中观察 到的NBTI具有类似的特征，可以被所谓的反应-扩散(R-D)模型表征： HfN/HfO₂ 栅结构p-MOSFET器件的NBTI效应的起源可以归为衬底注入空穴诱导的界面反应机理，即在负 偏置和温度应力作用下，从Si衬底注入的空穴诱导了Si衬底界面Si-H键断裂这一化学反应的 发生，并由此产生了Si^＋陷阱在Si衬底界面的积累和H原子在介质层内部的扩散 ，这种Si^＋陷阱的界面积累和H原子的扩散导致了器件NBTI效应的发生. 关键词： 高K栅介质 负偏置-温度不稳定性(NBTI) 反应-扩散(R-D)模型     

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.     

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.