Sample preparation for nanoanalytical electron microscopy using the FIB lift-out method and low energy ion milling

Thinning specimens to electron transparency for electron microscopy analysis can be done by conventional (2 - 4 kV) argon ion milling or focused ion beam (FIB) lift-out techniques. Both these methods tend to leave ''mottling'' visible on thin specimen areas, and this is believed to be surface damage caused by ion implantation and amorphisation. A low energy (250 - 500 V) Argon ion polish has been shown to greatly improve specimen quality for crystalline silicon samples. Here we investigate the preparation of technologically important materials for nanoanalysis using conventional and lift-out methods followed by a low energy polish in a GentleMill™ low energy ion mill. We use a low energy, low angle (6 - 8°) ion beam to remove the surface damage from previous processing steps. We assess this method for the preparation of technologically important materials, such as steel, silicon and GaAs. For these materials the ability to create specimens from specific sites, and to be able to image and analyse these specimens with the full resolution and sensitivity of the STEM, allows a significant increase of the power and flexibility of nanoanalytical electron microscopy

Engagement in the digital age:Understanding “what works” for participatory technologies in environmental decision-making

Effective engagement is crucial for enhancing environmental decision-making processes, fostering more sustainable and equitable outcomes. However, the success of engagement is highly variable and context-dependent. While theoretical frameworks have been developed to explain outcome variance in engagement in environmental decision-making, they have not yet been tested in digital contexts, leaving their applicability to digital engagement processes unclear. More broadly, there are unanswered questions about the effectiveness of digital tools in achieving the goals of engagement, which have become increasingly pertinent amidst growing concerns about the potential of digital technologies for exacerbating exclusions, ethical issues, and systematically undermining democratic progress. This paper addresses this evidence gap by presenting findings from interviews with practitioners in UK public, private, and third sector organisations. Our results provide empirical insights into the technical, ethical, and inclusivity debates surrounding digital tools and their effectiveness in promoting accessible engagement, high-quality social interaction, place-based decision-making, and more trustworthy and credible outcomes. Our findings indicate that while current engagement theories are applicable to digital environments, the key explanatory factors acquire new dimensions in digital compared to in-person contexts. Drawing on the findings, this study contributes novel insights to expand current theory for explaining “what works” in engagement in environmental decisions, enhancing its relevance and applicability in the digital age. The paper concludes with evidence-led recommendations for environmental practitioners to improve engagement processes in digital and remote settings.</p

Engagement in the digital age:Understanding “what works” for participatory technologies in environmental decision-making

Effective engagement is crucial for enhancing environmental decision-making processes, fostering more sustainable and equitable outcomes. However, the success of engagement is highly variable and context-dependent. While theoretical frameworks have been developed to explain outcome variance in engagement in environmental decision-making, they have not yet been tested in digital contexts, leaving their applicability to digital engagement processes unclear. More broadly, there are unanswered questions about the effectiveness of digital tools in achieving the goals of engagement, which have become increasingly pertinent amidst growing concerns about the potential of digital technologies for exacerbating exclusions, ethical issues, and systematically undermining democratic progress. This paper addresses this evidence gap by presenting findings from interviews with practitioners in UK public, private, and third sector organisations. Our results provide empirical insights into the technical, ethical, and inclusivity debates surrounding digital tools and their effectiveness in promoting accessible engagement, high-quality social interaction, place-based decision-making, and more trustworthy and credible outcomes. Our findings indicate that while current engagement theories are applicable to digital environments, the key explanatory factors acquire new dimensions in digital compared to in-person contexts. Drawing on the findings, this study contributes novel insights to expand current theory for explaining “what works” in engagement in environmental decisions, enhancing its relevance and applicability in the digital age. The paper concludes with evidence-led recommendations for environmental practitioners to improve engagement processes in digital and remote settings.</p

Test of four colon cancer risk-scores in formalin fixed paraffin embedded microarray gene expression data.

BACKGROUND: Prognosis prediction for resected primary colon cancer is based on the T-stage Node Metastasis (TNM) staging system. We investigated if four well-documented gene expression risk scores can improve patient stratification. METHODS: Microarray-based versions of risk-scores were applied to a large independent cohort of 688 stage II/III tumors from the PETACC-3 trial. Prognostic value for relapse-free survival (RFS), survival after relapse (SAR), and overall survival (OS) was assessed by regression analysis. To assess improvement over a reference, prognostic model was assessed with the area under curve (AUC) of receiver operating characteristic (ROC) curves. All statistical tests were two-sided, except the AUC increase. RESULTS: All four risk scores (RSs) showed a statistically significant association (single-test, P &lt; .0167) with OS or RFS in univariate models, but with HRs below 1.38 per interquartile range. Three scores were predictors of shorter RFS, one of shorter SAR. Each RS could only marginally improve an RFS or OS model with the known factors T-stage, N-stage, and microsatellite instability (MSI) status (AUC gains &lt; 0.025 units). The pairwise interscore discordance was never high (maximal Spearman correlation = 0.563) A combined score showed a trend to higher prognostic value and higher AUC increase for OS (HR = 1.74, 95% confidence interval [CI] = 1.44 to 2.10, P &lt; .001, AUC from 0.6918 to 0.7321) and RFS (HR = 1.56, 95% CI = 1.33 to 1.84, P &lt; .001, AUC from 0.6723 to 0.6945) than any single score. CONCLUSIONS: The four tested gene expression-based risk scores provide prognostic information but contribute only marginally to improving models based on established risk factors. A combination of the risk scores might provide more robust information. Predictors of RFS and SAR might need to be different

Review Section : Nature/Nurture Revisited I

Biologically oriented approaches to the study of human conflict have thus far been limited largely to the study of aggression. A sample of the literature on this topic is reviewed, drawing upon four major approaches: comparative psychology, ethology (including some popularized accounts), evolutionary-based theories, and several areas of human physiology. More sophisticated relationships between so-called "innate" and "acquired" determinants of behavior are discussed, along with the proper relevance of animal behavior studies for human behavior. Unless contained in a comprehensive theory which includes social and psychological variables, biolog ically oriented theories (although often valid within their domain) offer at best severely limited and at worst highly misleading explanations of complex social conflicts. The review concludes with a list of several positive contributions of these biological approaches and suggests that social scientists must become more knowledgeable about them.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68270/2/10.1177_002200277401800206.pd

Editorial Statement About JCCAP’s 2023 Special Issue on Informant Discrepancies in Youth Mental Health Assessments: Observations, Guidelines, and Future Directions Grounded in 60 Years of Research

Issue 1 of the 2011 Volume of the Journal of Clinical Child and Adolescent Psychology (JCCAP) included a Special Section about the use of multi-informant approaches to measure child and adolescent (i.e., hereafter referred to collectively as “youth”) mental health (De Los Reyes, 2011). Researchers collect reports from multiple informants or sources (e.g., parent and peer, youth and teacher) to estimate a given youth’s mental health. The 2011 JCCAP Special Section focused on the most common outcome of these approaches, namely the significant discrepancies that arise when comparing estimates from any two informant’s reports (i.e., informant discrepancies). These discrepancies appear in assessments conducted across the lifespan (Achenbach, 2020). That said, JCCAP dedicated space to understanding informant discrepancies, because they have been a focus of scholarship in youth mental health for over 60 years (e.g., Achenbach et al., 1987; De Los Reyes & Kazdin, 2005; Glennon & Weisz, 1978; Kazdin et al., 1983; Kraemer et al., 2003; Lapouse & Monk, 1958; Quay et al., 1966; Richters, 1992; Rutter et al., 1970; van der Ende et al., 2012). Thus, we have a thorough understanding of the areas of research for which they reliably appear when clinically assessing youth. For instance, intervention researchers observe informant discrepancies in estimates of intervention effects within randomized controlled trials (e.g., Casey & Berman, 1985; Weisz et al., 2017). Service providers observe informant discrepancies when working with individual clients, most notably when making decisions about treatment planning (e.g., Hawley & Weisz, 2003; Hoffman & Chu, 2015). Scholars in developmental psychopathology observe these discrepancies when seeking to understand risk and protective factors linked to youth mental health concerns (e.g., Hawker & Boulton, 2000; Hou et al., 2020; Ivanova et al., 2022). Thus, the 2011 JCCAP Special Section posed a question: Might these informant discrepancies contain data relevant to understanding youth mental health? Suppose none of the work in youth mental health is immune from these discrepancies. In that case, the answer to this question strikes at the core of what we produce―from the interventions we develop and implement, to the developmental psychopathology research that informs intervention development