Marginal models for the association structure of hierarchical binary responses

Clustered binary responses are often found in ecological studies. Data analysis may include modeling the marginal probability response. However, when the association is the main scientific focus, modeling the correlation structure between pairs of responses is the key part of the analysis. Second-order generalized estimating equations (GEE) are established in the literature. Some of them are more efficient in computational terms, especially facing large clusters. Alternating logistic regression (ALR) and orthogonalized residual (ORTH) GEE methods are presented and compared in this paper. Simulation results show a slightly superiority of ALR over ORTH. Marginal probabilities and odds ratios are also estimated and compared in a real ecological study involving a three-level hierarchical clustering. ALR and ORTH models are useful for modeling complex association structure with large cluster sizes.     

Generalized minimum aberration mixed-level orthogonal arrays: A general approach based on sequential integer quadratically constrained quadratic programming

Orthogonal fractional factorial designs and in particular orthogonal arrays (OAs) are frequently used in many fields of application, including medicine, engineering, and agriculture. In this article, we present a methodology and an algorithm to find an OA, of given size and strength, which satisfies the generalized minimum aberration criterion. The methodology is based on the joint use of polynomial counting functions, complex coding of levels, and algorithms for quadratic optimization and puts no restriction on the number of levels of each factor.     

抗日战争时期工厂内迁及其对大后方工业的影响

抗日战争爆发后 ,国民政府被迫组织了沿江沿海国营和部分民营工厂迁往我国西南等内地。工厂内迁促进了大后方工业的发展 ,为大后方迅速建立起新的工业基础 ,改变了过去不合理的工业局面。虽然这是在特殊的历史背景下的战时政治经济的产物 ,在很大程度上受制于战争的进展和时局的转换 ,但它却使西部地区的工业在战时短短的数年便走完了平时需要数十年乃至百余年才能走完的历程 ,并为嗣后西部地区工业的发展创设了一些条件和留下了一定的基础。抗日战争时期 ,国民政府主动或被动所采取的有关政策而形成的发展西部地区工业经济的模式 ,至今仍有鉴借意义     

A Comparative Study of Segregation Patterns in Belgium,Denmark, the Netherlands and Sweden: Neighbourhood Concentration and Representation of Non-European Migrants

In this paper, we use geo-coded, individual-level register data on four European countries to compute comparative measures of segregation that are independent of existing geographical sub-divisions. The focus is on non-European migrants, for whom aggregates of egocentric neighbourhoods (with different population counts) are used to assess small-scale, medium-scale, and large-scale segregation patterns. At the smallest scale level, corresponding to neighbourhoods with 200 persons, patterns of over- and under-representation are strikingly similar. At larger-scale levels, Belgium stands out as having relatively strong over- and under-representation. More than 55% of the Belgian population lives in large-scale neighbourhoods with moderate under- or over-representation of non-European migrants. In the other countries, the corresponding figures are between 30 and 40%. Possible explanations for the variation across countries are differences in housing policies and refugee placement policies. Sweden has the largest and Denmark the smallest non-European migrant population, in relative terms. Thus, in both migrant-dense and native-born-dense areas, Swedish neighbourhoods have a higher concentration and Denmark a lower concentration of non-European migrants than the other countries. For large-scale, migrant-dense neighbourhoods, however, levels of concentration are similar in Belgium, the Netherlands, and Sweden. Thus, to the extent that such concentrations contribute to spatial inequalities, these countries are facing similar policy challenges.     

Territorial Impact Assessment for European regions: A methodological proposal and an application to EU transport policy

The need to engage European research and institutions in the new field of Territorial Impact Assessment, from both a methodological and a procedural perspective, was stated some years ago by the European Spatial Development Perspective (ESDP). The necessity of multidimensional evaluation of the likely impact of policies and programmes on the territory – understood as the dimension on which all the other relevant dimensions (economic, social, environmental and cultural) converge and with which they integrate – emerged as a natural consequence of the importance of spatial aspects in the future development of the Union and of widespread preoccupations about certain emerging spatial trends.A proposal for a TIA methodology combining logical consistency vis-à-vis the Union's present institutional and policy guidelines with operational viability is being developed and applied to Trans-European Networks policy of the EU. Territorial impact is linked to an innovative definition of the objective of “territorial cohesion” of the Treaties in terms of territorial efficiency, quality and identity.Utilising sectoral impact studies developed inside the ESPON programme and developing territorial indicators for impact, vulnerability and desirability (territorial utility functions), a multicriteria model (TEQUILA) is implemented on priority projects as defined by the Commission, and results mapped and described for the 1360 NUTS-3 regions of the Union.     

Healthcare 4.0: trends,challenges and research directions

Abstract

This paper aims at examining the trends, challenges and theoretical gaps in the implementation of Healthcare 4.0 (H4.0) based on a scoping review of the literature. For that, we searched journal articles in four widely known databases and screened the retrieved articles to obtain a publications’ portfolio. Our findings indicate that, despite the recency of the subject, research in H4.0 has been conducted in an interdisciplinary way with a diversified set of applications and functionalities. In terms of its implementation, H4.0 has been more commonly found in hospitals’ information flows, especially the ones related to healthcare treatments. The identified implementation trends, however, neglect a more holistic approach for H4.0, which originated three main research directions for this topic. Although identified as a trending topic in the area of healthcare operations management, literature on H4.0 may be viewed as randomly conceived, lacking academic alignment and practical orientation based on a grounded theory, which we aim at providing with the present study.     

Psychophysical conditions and hormonal secretion in nurses on a rapidly rotating shift schedule and exposed to bright light during night work

The psychophysical conditions of 15 young female nurses, working in a rapidly-rotating shift system (2-2-2-2), modified according to some psychophysiological criteria, and exposed to short period (4 × 20 min) of bright light (2350 Lux) during their night duty, were studied in order to evaluate their adaptation to night work and to test a possible positive effect on it of bright light. Subjective evaluations of work load and psychophysical conditions, performance measures, hormonal excretion (cortisol, 6-sulphatoxymelatonin and catecholamines), oral temperature and activity-sleep logs were taken during the shiftwork cycle, comprising one morning, one afternoon and two consecutive nights under normal and bright light. The results showed that this rapidly-rotating shift system had little effect upon the normal circadian rhythms of the body. Moreover, the lengthening of the night shift to 10 h can be considered to be acceptable, provided that work load is reduced and there are sufficient rest pauses available. On the other hand, the reduction to 7 h of the length of the day shifts and delayed start of the morning shift to 07:00 h appeared to be convenient both in relation to the work load and sleep duration. Some positive effects of bright light upon psychophysical conditions and performance efficiency were noted, while hormonal excretion and body temperature did not show any effect of bright light; in particular, melatonin excretion was not suppressed appreciably by the bright light used.     

A general algorithm to fit constrained DEDICOM models

The DEDICOM model is a model to analyze square tables describing asymmetric relationships among n entities. Its importance in the asymmetric multidimensional scaling literature is due to the fact that several authors showed a large class of models to be simply a constrained version of DEDICOM. A typical example is the Generalized GIPSCAL proposed by Kiers & Takane. In this paper we present a new algorithm capable to fit, in the least squares sense, any DEDICOM constrained model.