Book reviews

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45784/1/11153_2004_Article_BF00140614.pd

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal organic frameworks (MOFs). At present, we have libraries of over ten thousand synthesized materials and millions of in-silico predicted materials. The fact that we have so many materials opens many exciting avenues to tailor make a material that is optimal for a given application. However, from an experimental and computational point of view we simply have too many materials to screen using brute-force techniques. In this review, we show that having so many materials allows us to use big-data methods as a powerful technique to study these materials and to discover complex correlations. The first part of the review gives an introduction to the principles of big-data science. We emphasize the importance of data collection, methods to augment small data sets, how to select appropriate training sets. An important part of this review are the different approaches that are used to represent these materials in feature space. The review also includes a general overview of the different ML techniques, but as most applications in porous materials use supervised ML our review is focused on the different approaches for supervised ML. In particular, we review the different method to optimize the ML process and how to quantify the performance of the different methods. In the second part, we review how the different approaches of ML have been applied to porous materials. In particular, we discuss applications in the field of gas storage and separation, the stability of these materials, their electronic properties, and their synthesis. The range of topics illustrates the large variety of topics that can be studied with big-data science. Given the increasing interest of the scientific community in ML, we expect this list to rapidly expand in the coming years.Comment: Editorial changes (typos fixed, minor adjustments to figures

Early childhood adversities and trajectories of psychiatric problems in adoptees: Evidence for long lasting effects

The aim of the present study is to investigate whether early childhood adversities determine the longitudinal course of psychiatric problems from childhood to adulthood; in particular if the impact of early maltreatment on psychopathology decreases as time passes. A sample of 1,984 international adoptees was followed (955 males and 1029 females; adopted at the mean age of 29 months). Parents provided information about abuse, neglect and numbe

A Widespread Chromosomal Inversion Polymorphism Contributes to a Major Life-History Transition, Local Adaptation, and Reproductive Isolation

A set of experiments demonstrates the involvement of a chromosomal inversion in the adaptive transition between annual and perennial ecotypes of the yellow monkeyflower, Mimulus guttatu

Chemical diversity in a metal-organic framework revealed by fluorescence lifetime imaging

The presence and variation of chemical functionality and defects in crystalline materials, such as metal–organic frameworks (MOFs), have tremendous impact on their properties. Finding a means of identifying and characterizing this chemical diversity is an important ongoing challenge. This task is complicated by the characteristic problem of bulk measurements only giving a statistical average over an entire sample, leaving uncharacterized any diversity that might exist between crystallites or even within individual crystals. Here we show that by using fluorescence imaging and lifetime analysis, both the spatial arrangement of functionalities and the level of defects within a multivariable MOF crystal can be determined for the bulk as well as for the individual constituent crystals. We apply these methods to UiO-67, to study the incorporation of functional groups and their consequences on the structural features. We believe that the potential of the techniques presented here in uncovering chemical diversity in what is generally assumed to be homogeneous systems can provide a new level of understanding of materials properties

Patterns of risk and protective factors in the intergenerational cycle of maltreatment

his study investigates the continuation and discontinuation of the intergenerational transmission of child maltreatment within the first 13 months of the child’s life. Differences in risk factors and parenting styles between families who initiate (Initiators), maintain (Maintainers) or break (Cycle Breakers) the intergenerational cycle of child maltreatment are explored in comparison to control families (Controls). One hundred and three Health Visitors were trained to assess risk factors and parenting styles of 4,351 families, at both 4–6 weeks and 3–5 months after birth. Maintainers, Initiators and Cycle Breakers had a significantly higher prevalence for the majority of risk factors and poor parenting styles than Controls. Protective factors of financial solvency and social support distinguished Cycle Breakers from Maintainers and Initiators. Therefore, it is the presence of protective factors that distinguish Cycle Breakers from families who were referred to Child Protection professionals in the first year after birth. A conceptual, hierarchical model that considers history of abuse, risk and protective factors, in turn, is proposed to assess families for the potential of child maltreatment

A study protocol for applying the co-creating knowledge translation framework to a population health study

BACKGROUND: Population health research can generate significant outcomes for communities, while Knowledge Translation (KT) aims to expressly maximize the outcomes of knowledge producing activity. Yet the two approaches are seldom explicitly combined as part of the research process. A population health study in Port Lincoln, South Australia offered the opportunity to develop and apply the co-KT Framework to the entire research process. This is a new framework to facilitate knowledge formation collaboratively between researchers and communities throughout a research to intervention implementation process. DESIGN: This study employs a five step framework (the co-KT Framework) that is formulated from engaged scholarship and action research principles. By following the steps a knowledge base will be cumulatively co-created with the study population that is useful to the research aims. Step 1 is the initiating of contact between the researcher and the study contexts, and the framing of the research issue, achieved through a systematic data collection tool. Step 2 refines the research issue and the knowledge base by building into it context specific details and conducting knowledge exchange events. Step 3 involves interpreting and analysing the knowledge base, and integrating evidence to inform intervention development. In Step 4 the intervention will be piloted and evaluated. Step 5 is the completion of the research process where outcomes for improvement will be instituted as regular practice with the facilitation of the community. In summary, the model uses an iterative knowledge construction mechanism that is complemented by external evidence to design interventions to address health priorities within the community. DISCUSSION: This is a systematic approach that operationalises the translational cycle using a framework for KT practice. It begins with the local context as its foundation for knowledge creation and ends with the development of contextually applicable interventions. It will be of interest to those involved in KT research, participatory action research, population health research and health care systems studies. The co-KT Framework is a method for embedding the principles of KT into all stages of a community-based research process, in which research questions are framed by emergent data from each previous stage.Kathryn Powell, Alison Kitson, Elizabeth Hoon, Jonathan Newbury, Anne Wilson and Justin Beilb

How does community context influence coalitions in the formation stage? a multiple case study based on the Community Coalition Action Theory

<p>Abstract</p> <p>Background</p> <p>Community coalitions are rooted in complex and dynamic community systems. Despite recognition that environmental factors affect coalition behavior, few studies have examined how community context impacts coalition formation. Using the Community Coalition Action theory as an organizing framework, the current study employs multiple case study methodology to examine how five domains of community context affect coalitions in the formation stage of coalition development. Domains are history of collaboration, geography, community demographics and economic conditions, community politics and history, and community norms and values.</p> <p>Methods</p> <p>Data were from 8 sites that participated in an evaluation of a healthy cities and communities initiative in California. Twenty-three focus groups were conducted with coalition members, and 76 semi-structured interviews were conducted with local coordinators and coalition leaders. Cross-site analyses were conducted to identify the ways contextual domains influenced selection of the lead agency, coalition membership, staffing and leadership, and coalition processes and structures.</p> <p>Results</p> <p>History of collaboration influenced all four coalition factors examined, from lead agency selection to coalition structure. Geography influenced coalition formation largely through membership and staffing, whereas the demographic and economic makeup of the community had an impact on coalition membership, staffing, and infrastructure for coalition processes. The influence of community politics, history, norms and values was most noticeable on coalition membership.</p> <p>Conclusions</p> <p>Findings contribute to an ecologic and theory-based understanding of the range of ways community context influences coalitions in their formative stage.</p

A typology of practice narratives during the implementation of a preventive, community intervention trial

<p>Abstract</p> <p>Background</p> <p>Traditional methods of process evaluation encompass what components were delivered, but rarely uncover how practitioners position themselves and act relative to an intervention being tested. This could be crucial for expanding our understanding of implementation and its contribution to intervention effectiveness.</p> <p>Methods</p> <p>We undertook a narrative analysis of in-depth, unstructured field diaries kept by nine community development practitioners for two years. The practitioners were responsible for implementing a multi-component, preventive, community-level intervention for mothers of new babies in eight communities, as part of a cluster randomised community intervention trial. We constructed a narrative typology of approaches to practice, drawing on the phenomenology of Alfred Schutz and Max Weber's Ideal Type theory.</p> <p>Results</p> <p>Five types of practice emerged, from a highly 'technology-based' type that was faithful to intervention specifications, through to a 'romantic' type that held relationships to be central to daily operations, with intact relationships being the final arbiter of intervention success. The five types also differed in terms of how others involved in the intervention were characterized, the narrative form (<it>e.g</it>., tragedy, satire) and where and how transformative change in communities was best created. This meant that different types traded-off or managed the priorities of the intervention differently, according to the deeply held values of their type.</p> <p>Conclusions</p> <p>The data set constructed for this analysis is unique. It revealed that practitioners not only exercise their agency within interventions, they do so systematically, that is, according to a pattern. The typology is the first of its kind and, if verified through replication, may have value for anticipating intervention dynamics and explaining implementation variation in community interventions.</p