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.     

Beyond Contact? Policy approaches to work with families of looked after children in four European countries

In England, placement within the looked after system is not viewed as a desirable long‐term solution for most children, and policy has prioritised continued contact with parents, and swift return home, wherever possible. This review examines policy approaches to work with families of looked after children in England and in three other European countries: Denmark, France and the Netherlands, aiming to identify areas for shared learning in relation to this challenging area of policy and practice. The research highlights relationships between care populations and policy understandings of the purpose of work with families, including understandings of children's and/or parents’ rights.     

Toddlers Help Anonymously

Young children are extremely motivated to help others, but it is not clear whether they do so in anonymous situations without social recognition. In two studies, we found that 18‐month‐old toddlers provided help equally in situations where an adult recipient was present and in situations where an adult recipient was not present. We included several control conditions to rule out that toddlers were simply unaware of their anonymity or were merely motivated to restore the physical order of things. Together, these findings suggest that early in ontogeny children are motivated to help others in need regardless of whether they can immediately be recognized for their prosocial intentions.     

Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria

This work presents a study about the smoothness attained by the methods more frequently used to choose the smoothing parameter in the context of splines: Cross Validation, Generalized Cross Validation, and corrected Akaike and Bayesian Information Criteria, implemented with Penalized Least Squares. It is concluded that the amount of smoothness strongly depends on the length of the series and on the type of underlying trend, while the presence of seasonality even though statistically significant is less relevant. The intrinsic variability of the series is not statistically significant and its effect is taken into account only through the smoothing parameter.     

Bayesian and Robust Bayesian analysis under a general class of balanced loss functions

For estimating an unknown parameter θ, we introduce and motivate the use of balanced loss functions of the form L_{r, w, d0}(q, d)=wr(d₀, d)+ (1-w) r(q, d){L_{\rho, \omega, \delta_0}(\theta, \delta)=\omega \rho(\delta_0, \delta)+ (1-\omega) \rho(\theta, \delta)}, as well as the weighted version q(q) L_{r, w, d0}(q, d){q(\theta) L_{\rho, \omega, \delta_0}(\theta, \delta)}, where ρ(θ, δ) is an arbitrary loss function, δ ₀ is a chosen a priori “target” estimator of q, w ? [0,1){\theta, \omega \in[0,1)}, and q(·) is a positive weight function. we develop Bayesian estimators under L_{r, w, d0}{L_{\rho, \omega, \delta_0}} with ω > 0 by relating such estimators to Bayesian solutions under L_{r, w, d0}{L_{\rho, \omega, \delta_0}} with ω = 0. Illustrations are given for various choices of ρ, such as absolute value, entropy, linex, and squared error type losses. Finally, under various robust Bayesian analysis criteria including posterior regret gamma-minimaxity, conditional gamma-minimaxity, and most stable, we establish explicit connections between optimal actions derived under balanced and unbalanced losses.     

Community Wise: The Development of an Anti-Oppression Model to Promote Individual and Community Health

Communities with histories of oppression have shown great resilience, yet few health interventions focus on structural oppression as a contributor to health problems in these communities. This article describes the development and active ingredients of Community Wise, a unique behavioral health intervention designed to reduce substance use frequency, related health risk behaviors, and recidivism among individuals with a history of incarceration and substance abuse residing in distressed and predominantly African American communities. Community Wise, developed through the collaborative efforts of a board of service providers, researchers, consumers, and government officials, is a 12-week group intervention that aims to address behavioral health problems by raising critical consciousness in distressed communities.     

Building a Values‐Informed Mental Model for New Orleans Climate Risk Management

Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals’ values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a “Values‐informed Mental Model” research approach, or ViMM, to elicit individuals’ values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans’ unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision‐support processes and may encourage adoption of CRM strategies more in line with stakeholders’ values.     

Adult Sexual Outcomes of Child Sexual Abuse Vary According to Relationship Status

This study tested a moderation model in which the association between child sexual abuse severity and negative sexual outcomes (i.e., sexual avoidance and compulsivity) differed as a function of relationships status (i.e., single, cohabiting, and married individuals). A sample of 1,033 adults completed self‐report questionnaires online, and 21.5% reported childhood sexual abuse. Path analyses indicated that child sexual abuse severity was associated with higher sexual compulsivity in single individuals, both higher sexual avoidance and compulsivity in cohabiting individuals, and higher sexual avoidance in married individuals. The moderation model was invariant across men and women. These results suggest that the time course of negative sexual outcomes associated with child sexual abuse may follow distinct patterns of expression according to relationship status.     

Sport and disability: Pistorius does not fit with the categories

Oscar Pistorius presents a major issue to sports organisations, as exposed in the media. First and foremost, media wrongly perceive him as the first disabled athlete to participate in the Olympic Games. Second, they openly question the legitimacy of his participation mainly based on the inequity introduced by his prosthetic legs. Content analysis, in English and French, of written press, International Association of Athletics Federations (IAAF) and Court of Arbitration for Sport (CAS) texts, from 2004 to 2012, confirms that Pistorius presents a new puzzle to sports organizations. This is partly because they are not able to determine whether his performances are a result of his body strength or if they are biased by his artificial limbs. Furthermore, when he is competing against able-bodied athletes, sports organizsations put him in a ‘monstrous’ position. Similarly, while categorising him as an ‘athlete’ they do not grant him the characteristic feature of this category: certified comparability of performances to ultimately establish ranks.