On Combining Wavelets Expansion and Sparse Linear Models for Regression on Metabolomic Data and Biomarker Selection

Wavelet thresholding of spectra has to be handled with care when the spectra are the predictors of a regression problem. Indeed, a blind thresholding of the signal followed by a regression method often leads to deteriorated predictions. The scope of this article is to show that sparse regression methods, applied in the wavelet domain, perform an automatic thresholding: the most relevant wavelet coefficients are selected to optimize the prediction of a given target of interest. This approach can be seen as a joint thresholding designed for a predictive purpose. The method is illustrated on a real world problem where metabolomic data are linked to poison ingestion. This example proves the usefulness of wavelet expansion and the good behavior of sparse and regularized methods. A comparison study is performed between the two-steps approach (wavelet thresholding and regression) and the one-step approach (selection of wavelet coefficients with a sparse regression). The comparison includes two types of wavelet bases, various thresholding methods, and various regression methods and is evaluated by calculating prediction performances. Information about the location of the most important features on the spectra was also obtained and used to identify the most relevant metabolites involved in the mice poisoning.     

CONTROL: the extractive ecology of corn monoculture

This article tells the history of the industrial and biotechnological development of large-scale corn agriculture, from a new materialist perspective. Addressing the large-scale economy of industrial food production as a form of more-than-human configuration, it demonstrates how corn has been made into a quintessential commodity and factor of production for a consumption-based economy. Set within discourses around the climate crisis, this account critically assesses the Anthropocene and its advocacy for human accountability in regards to the exploitation of nonhuman matters. I ask: who is the Anthropos? How does it/he/she meet with its domesticated subjects, or rather makes them into domesticable materials? Telling the history of corn monoculture from a new materialist standpoint exposes this industry’s distribution of agency, power and control across a diversity of human and nonhuman actors. This is at the centre of this article’s three sections: (1) an argument for inscribing extractivism within new materialist literature, (2) an account of the industrialization of corn monoculture, exposing the industry’s main mechanisms and economic endeavours, as well as its ramifications with a biopolitics of invasion and (3) the biotechnological development of the industry and its shifts from a biopolitics of vegetal matter to an informational extractivism and a necropolitics of killable life. Thus I argue that if the industry of corn monoculture belongs to a broader network of detrimental industries characteristic of the Anthropocene, the geological Anthropos is not to be understood as synonymous with the human species, but as a very restrictive ecology of humans and nonhumans, including corporate, industrial, technoscientific and extractive actors. As such, the article emphasizes the moral necessity of rupturing with the narrative of the Anthropocene, a discourse better suited for supporting existing mechanisms of domination and exploitation constitutive of the economy of climate change.     

Serious case reviews: The lived experience of Black children

Despite the many high‐profile Black child deaths in England, race as a factor remains a largely underexplored factor of serious case reviews (SCRs). Evidence from analysis of SCRs indicates that race receives limited attention, or is virtually absent. Given that the main function of SCRs is to provide opportunities for learning lessons to improve practice, the way in which issues of race and culture may influence child protection processes for Black children is therefore of critical importance. In this article, we employ content analysis to examine the extent that race and cultural factors are considered in SCRs involving Black children. It is argued that race is often an important factor influencing Black children's experiences of abuse and neglect, as well as their encounters in the child protection system. This article therefore poses two key questions: (a) What questions are asked about race, ethnicity, and culture in SCRs concerning Black children? (b) How did the SCRs extract lessons to be learnt for improving practice to safeguard Black children? By extending the analysis of race and ethnicity in SCRs, this article furthers our understandings of the needs of Black children in the child protection system.     

Cohort Measures of Internal Migration: Understanding Long-Term Trends

Internal migration intensities fluctuate over time, but both migration levels and trends show great diversity. The dynamics underpinning these trends remain poorly understood because they are analyzed almost exclusively by applying period measures to cross-sectional data. This article proposes 10 cohort measures that can be applied to both prospective and retrospective data to systematically examine long-term trends. To demonstrate their benefits, the proposed measures are applied to retrospective survey data for England that provide residential histories from birth to age 50 for cohorts born between 1918 and 1957. The analysis reveals stable lifetime migration for men but increased lifetime migration for women associated with earlier ages at moving in adulthood and a compression of intervals between consecutive moves. The proposed cohort measures provide a more comprehensive picture of migration behavior and should be used to complement period measures in exploring long-term trends. Increasing availability of retrospective and longitudinal survey data means that researchers can now apply the proposed measures to a wide range of countries.     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

A SIMULATION ANALYSIS OF THE JAPANESE JUST-IN-TIME TECHNIQUE (WITH KANBANS) FOR A MULTILINE,MULTISTAGE PRODUCTION SYSTEM

The Japanese “just-in-time with kanban” technique reduces in-process inventory to absolute minimal levels, in concert with the Japanese belief that inventory is an unnecessary evil. Due to the success of Japanese firms that employ this type of system, American firms would like to import this technique and emulate Japanese successes. But this Japanese success may be attributable not only to the just-in-time with kanban technique but also to the production environment in which the technique is employed. This paper simulates the just-in-time with kanban technique for a multiline, multistage production system in order to determine its adaptability to an American production environment that might include such characteristics as variable processing times, variable master production scheduling, and imbalances between production stages. The results have practical implications for those firms considering adoption of the Japanese technique.     

Time‐change models for asymmetric processes

Many records in environmental sciences exhibit asymmetric trajectories. The physical mechanisms behind these records may lead for example to sample paths with different characteristics at high and low levels (up–down asymmetries) or in the ascending and descending phases leading to time irreversibility (front–back asymmetries). Such features are important for many applications, and there is a need for simple and tractable models that can reproduce them. In this paper, we explore original time‐change models where the clock is a stochastic process that depends on the observed trajectory. The ergodicity of the proposed model is established under general conditions, and this result is used to develop nonparametric estimation procedures based on the joint distribution of the process and its derivative. The methodology is illustrated on meteorological and oceanographic data sets. We show that, combined with a marginal transformation, the proposed methodology is able to reproduce important characteristics of the data set such as marginal distributions, up‐crossing intensity, and up–down and front–back asymmetries.