51 results
3 Stricker Learning Span criterion validity: remote self-administration of a computer adaptive word list memory test shows similar ability to differentiate PET-defined biomarker groups as in-person Rey Auditory Verbal Learning Test performance in cognitively unimpaired individuals on the Alzheimer’s continuum
- Nikki H. Stricker, John L. Stricker, Aimee J. Karstens, Jay S. Patel, Teresa J. Christianson, Winnie Z. Fan, Sabrina M. Albertson, Ryan D. Frank, Mary M. Machulda, Walter K. Kremers, Julie A. Fields, Jonathan Graff-Radford, Clifford R. Jack, Jr, David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 407-408
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Objective:
The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.
Participants and Methods:Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).
Results:Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.
Conclusions:Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.
65 Mayo Test Drive raw composite criterion validity: a brief remote self-administered digital cognitive composite shows similar ability to differentiate PET-defined biomarker groups as a global composite from a person-administered neuropsychological battery in cognitively unimpaired individuals on the Alzheimer’s continuum
- Nikki H. Stricker, Aimee J. Karstens, Teresa J. Christianson, John L. Stricker, Winnie Z. Fan, Sabrina M. Albertson, Ryan D. Frank, Mary M. Machulda, Walter K. Kremers, Jason Hassenstab, Julie A. Fields, Jonathan Graff-Radford, Clifford R. Jack, Jr., David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 371-372
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Objective:
Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based multi-device (smartphone, tablet, personal computer) platform optimized for remote self-administered cognitive assessment that includes a computer-adaptive word list memory test (Stricker Learning Span; SLS; Stricker et al., 2022; Stricker et al., in press) and a measure of processing speed (Symbols Test: Wilks et al., 2021). Study aims were to determine criterion validity of MTD by comparing the ability of the MTD raw composite and in-person administered cognitive measures to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.
Participants and Methods:Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11, range=37-94; mean education=16, SD=2, range=6-20; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) or with no evidence of AD pathology (A-T-, n=181). Primary outcome variables were MTD raw composite (SLS sum of trials + an accuracy-weighted Symbols response time measure), Global-z (average of 9 in-person neuropsychological measures) and an in-person screening measure (Kokmen Short Test of Mental Status, STMS; which is like the MMSE). Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).
Results:Remotely administered MTD raw composite showed comparable to slightly larger effect sizes compared to Global-z. Unadjusted effect sizes for MTD raw composite for differentiating A+ vs. A- and A+T+ vs. A-T- groups, respectively, were -0.57 and -0.84 and effect sizes for Global-z were -0.54 and -0.73 (all p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but MTD raw composite remained significant for A+T+ vs A-T- (adjusted effect size -0.35, p=.007); Global-z did not reach significance for A+T+ vs A-T- (adjusted effect size -0.19, p=.08). Neither composite reached significance for adjusted analyses for the A+ vs A- comparison (MTD raw composite adjusted effect size= -.22, p=.06; Global-z adjusted effect size= -.08, p=.47). Results were the same for an alternative MTD composite using traditional z-score averaging methods, but the raw score method is preferred for comparability to other screening measures. The STMS screening measure did not differentiate biomarker groups in any analyses (unadjusted and adjusted p’s>.05; d’s -0.23 to 0.05).
Conclusions:Remotely administered MTD raw composite shows at least similar ability to separate biomarker-defined groups in CU individuals as a Global-z for person-administered measures within a neuropsychological battery, providing evidence of criterion validity. Both the MTD raw composite and Global-z showed greater ability to separate biomarker positive from negative CU groups compared to a typical screening measure (STMS) that was unable to differentiate these groups. MTD may be useful as a screening measure to aid early detection of Alzheimer’s pathological changes.
65 Verbal and Visual-Spatial Abilities Differ by Ethnicity in a Referred Pediatric Sample
- Gary P. Rempe, Patricia Lyke, Jennifer G. Walter, John H. King
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 741-742
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Objective:
To compare performances of matched groups derived from caregiver-reported ethnicity on measures of verbal comprehension and visual-spatial abilities, and to identify factors potentially related to differences.
Participants and Methods:Participants included 159 English speaking children from 615 years of age who were referred for neuropsychological evaluation at a clinic in the southwestern region of the United States. Participants were matched across four groups based on caregiver-reported ethnicity, including American Indian (n = 41), Hispanic (n= 41), White (n = 41), and Other (i.e., Black, Asian; n = 36) categories. Propensity score matching was used to derive samples, with participants matched on age, caregiver-reported sex assigned at birth, and the full-scale intelligence quotient on the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V).
Results:Using a dependent variable derived from subtracting the WISC-V Verbal Comprehension Index from the Visual-Spatial Index, significant differences across groups were found via a factorial analysis of variance model (p = .02, eta squared = .06). Achieved power was .82. Post-hoc analysis indicated significantly greater differences between verbal comprehension and visual-spatial abilities amongst participants of American Indian (mean difference = -6.61 standard score points) and Hispanic (mean difference = -6.66 standard score points) ethnicity relative to participants of White ethnicity (mean difference = 2.17 standard score points; p < .01). Differences did not relate to participant age or assigned sex.
Conclusions:Greater differences between visual and verbal intellectual abilities were found amongst Hispanic and American Indian participants relative to White participants. Hispanic and American children tended to perform higher on visual spatial rather than verbal tasks, while the pattern was reversed for White children. Findings are congruent with previous research conducted using older versions of the WISC and continue to highlight potential issues related to the external validity of this measure in certain populations. This study contributes to the existing literature by replicating previous findings with the most recent iteration of the WISC in a referred sample. Current results continue to suggest that the WISC-V Verbal Comprehension Index may function more as a measure of English language ability rather than verbal intellectual ability. Given these findings, it is important that weaknesses in verbal comprehension amongst children of Hispanic or American Indian ethnicity be interpreted in this context when identified in clinical and research settings. Discrepancies between ethnic groups may relate broadly to cultural and systemic factors (e.g., differing patient/examiner characteristics, inequalities in access to education/intervention and healthcare, bilingualism/exposure to the English language).
Differing impact of the COVID-19 pandemic on youth mental health: combined population and clinical study
- Lu Qi, Zuo Zhang, Lauren Robinson, Marina Bobou, Chantal Gourlan, Jeanne Winterer, Rebecca Adams, Kofoworola Agunbiade, Yuning Zhang, Sinead King, Nilakshi Vaidya, Eric Artiges, Tobias Banaschewski, Arun L. W. Bokde, M. John Broulidakis, Rüdiger Brühl, Herta Flor, Juliane H. Fröhner, Hugh Garavan, Antoine Grigis, Andreas Heinz, Sarah Hohmann, Marie-Laure Paillère Martinot, Sabina Millenet, Frauke Nees, Betteke Maria van Noort, Dimitri Papadopoulos Orfanos, Luise Poustka, Julia Sinclair, Michael N. Smolka, Robert Whelan, Argyris Stringaris, Henrik Walter, Jean-Luc Martinot, Gunter Schumann, Ulrike Schmidt, Sylvane Desrivières, IMAGEN Consortium, ESTRA Consortium and STRATIFY Consortium
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- Journal:
- BJPsych Open / Volume 9 / Issue 6 / November 2023
- Published online by Cambridge University Press:
- 20 November 2023, e217
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Background
Identifying youths most at risk to COVID-19-related mental illness is essential for the development of effective targeted interventions.
AimsTo compare trajectories of mental health throughout the pandemic in youth with and without prior mental illness and identify those most at risk of COVID-19-related mental illness.
MethodData were collected from individuals aged 18–26 years (N = 669) from two existing cohorts: IMAGEN, a population-based cohort; and ESTRA/STRATIFY, clinical cohorts of individuals with pre-existing diagnoses of mental disorders. Repeated COVID-19 surveys and standardised mental health assessments were used to compare trajectories of mental health symptoms from before the pandemic through to the second lockdown.
ResultsMental health trajectories differed significantly between cohorts. In the population cohort, depression and eating disorder symptoms increased by 33.9% (95% CI 31.78–36.57) and 15.6% (95% CI 15.39–15.68) during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously (a 15.2% decrease) during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease.
ConclusionsHealthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic. Targeted mental health interventions considering prior diagnostic risk may be warranted to help young people cope with the challenges of psychosocial stress and reduce the associated healthcare burden.
Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test
- Nikki H. Stricker, John L. Stricker, Ryan D. Frank, Winnie Z. Fan, Teresa J. Christianson, Jay S. Patel, Aimee J. Karstens, Walter K. Kremers, Mary M. Machulda, Julie A. Fields, Jonathan Graff-Radford, Clifford R. Jack, Jr., David S. Knopman, Michelle M. Mielke, Ronald C. Petersen
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- Journal:
- Journal of the International Neuropsychological Society / Volume 30 / Issue 2 / February 2024
- Published online by Cambridge University Press:
- 30 June 2023, pp. 138-151
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Objective:
The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey’s Auditory Verbal Learning Test (AVLT).
Method:Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A−T−, n = 195). Analyses were repeated among CU participants only.
Results:The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p’s > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A− vs A+) to large (A−T− vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups.
Conclusions:Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.
Brain morphometric features predict medication response in youth with bipolar disorder: a prospective randomized clinical trial
- Du Lei, Kun Qin, Wenbin Li, Walter H. L. Pinaya, Maxwell J. Tallman, L. Rodrigo Patino, Jeffrey R. Strawn, David Fleck, Christina C. Klein, Su Lui, Qiyong Gong, Caleb M. Adler, Andrea Mechelli, John A. Sweeney, Melissa P. DelBello
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- Journal:
- Psychological Medicine / Volume 53 / Issue 9 / July 2023
- Published online by Cambridge University Press:
- 08 April 2022, pp. 4083-4093
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Background
Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.
MethodsA total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.
ResultsPre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.
ConclusionsThese findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.
Worth the Wait: Delayed Recall after 1 Week Predicts Cognitive and Medial Temporal Lobe Trajectories in Older Adults
- Cutter A. Lindbergh, Nicole Walker, Renaud La Joie, Sophia Weiner-Light, Adam M. Staffaroni, Kaitlin B. Casaletto, Fanny Elahi, Samantha M. Walters, Michelle You, Devyn Cotter, Breton Asken, Alexandra C. Apple, Elena Tsoy, John Neuhaus, Corrina Fonseca, Amy Wolf, Yann Cobigo, Howie Rosen, Joel H. Kramer, the Hillblom Aging Network
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- Journal of the International Neuropsychological Society / Volume 27 / Issue 4 / April 2021
- Published online by Cambridge University Press:
- 14 October 2020, pp. 382-388
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Objective: We evaluated whether memory recall following an extended (1 week) delay predicts cognitive and brain structural trajectories in older adultsMethod:
Clinically normal older adults (52–92 years old) were followed longitudinally for up to 8 years after completing a memory paradigm at baseline [Story Recall Test (SRT)] that assessed delayed recall at 30 min and 1 week. Subsets of the cohort underwent neuroimaging (N = 134, mean age = 75) and neuropsychological testing (N = 178–207, mean ages = 74–76) at annual study visits occurring approximately 15–18 months apart. Mixed-effects regression models evaluated if baseline SRT performance predicted longitudinal changes in gray matter volumes and cognitive composite scores, controlling for demographics.
Results:Worse SRT 1-week recall was associated with more precipitous rates of longitudinal decline in medial temporal lobe volumes (p = .037), episodic memory (p = .003), and executive functioning (p = .011), but not occipital lobe or total gray matter volumes (demonstrating neuroanatomical specificity; p > .58). By contrast, SRT 30-min recall was only associated with longitudinal decline in executive functioning (p = .044).
Conclusions:Memory paradigms that capture longer-term recall may be particularly sensitive to age-related medial temporal lobe changes and neurodegenerative disease trajectories. (JINS, 2020, xx, xx-xx)
Pollination of the Australian cycad Cycas ophiolitica (Cycadaceae): the limited role of wind pollination in a cycad with beetle pollinator mutualists, and its ecological significance
- John A. Hall, Gimme H. Walter
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- Journal of Tropical Ecology / Volume 34 / Issue 2 / March 2018
- Published online by Cambridge University Press:
- 17 April 2018, pp. 121-134
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Cycads in the Zamiaceae are well known for their host-specific insect pollination mutualisms. Pollination of Cycas in the sister family Cycadaceae is less well-documented, with beetle pollination possibly coexisting with a limited potential for wind pollination, a hypothesis we tested for C. ophiolitica in Central Queensland, Australia. Cones were associated with three species of beetle: an undescribed weevil (Curculionidae), Hapalips sp. (Erotylidae) and Ulomoides sp. (Tenebrionidae). Pollination-vector exclusion experiments compared the pollination success (quantified as % ovules pollinated per cone) of control cones against bagged or netted cones that excluded wind or insects respectively (n = 10 for all treatments). Insects do pollinate C. ophiolitica in the absence of wind, the median (first quartile-third quartile) pollination success of control plants being 83.7% (60.8–87.2%) while bagged cones, from which wind, but not insects, were excluded, pollinated at 52.9% (19.5–74.8%). For netted cones, (excluding insects but not wind), pollination fell to 12.6% (10.9–45.9%). Airborne pollen (as quantified by capture on a series of adhesive pollen traps) decreased rapidly with distance from male cones, potentially becoming ineffective for wind pollination at ~5 m. Airborne pollen load in the vicinity of female cones, and distance of females from neighbouring males, suggests wind pollination may occur sporadically, but only at high spatial densities. Although Cycas appears to be primarily insect pollinated, this limited potential for ambophily may be significant given the history of dispersal and pollinator host shifts among these cycads.
18 - Insights Gained on the Great Recession's Effects
- from Part VI - Conclusion
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- By John Bynner, Emeritus Professor of Social Sciences in Education at the London Institute of Education, Glen H. Elder, Odum Distinguished Research Professor of Sociology at University of North Carolina at Chapel Hill, Walter R. Heinz, Emeritus Professor of Sociology and Psychology at the University of Bremen, Germany, Ingrid Schoon, Professor of Human Development and Social Policy at the University College London Institute of Education
- Edited by Ingrid Schoon, University College London, John Bynner, University College London
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- Book:
- Young People's Development and the Great Recession
- Published online:
- 20 October 2017
- Print publication:
- 02 November 2017, pp 447-478
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Summary
What Have We Learned?
What have we learned about the changing nature of youth transitions and the effect of the Great Recession on them? In this final chapter we draw conclusions and seek further insights from the evidence presented. First we give a brief overview, taking the discussion back to the initial questions about the recession effects to which the preceding chapters were directed. Second, we discuss the evidence in the light of key themes of contemporary youth research and draw out their intersection with life course theory. We then consider the theoretical and policy insights to be gained from the evidence reported. Our discussion focuses on young people in the USA, the UK, and Germany, but also takes into account developments across a range of industrialized countries.
Overview
What was the impact of the Great Recession on young people making the transition to independent adulthood? The overall conclusion to be drawn is that the Great Recession was a significant but not principal influence on young people's changing life course post-2007. Better to characterize it as a major economic shock that intensified the impact of preexisting economic and social processes on young people's lives. Originating principally in Western countries in the period of technological transformation and de-industrialization of the late 1970s, as the contributors to the book show, these effects presented new obstacles to entering and sustaining employment within the adult labor market. There were also wider repercussions for functioning in the family and other life domains. Although the short-term effects may have been modest, they might be followed by more serious outcomes and long-term scarring effects. There could also be lagged effects (i.e., a delay between the exposure and onset of adjustment problems) and therefore continued monitoring of life chances for young people is necessary.
The recession effects varied with each successive cohort embarking on the transition to independent adulthood, i.e., they differed for different age groups, for different countries, and between different sections of the youth population. Younger cohorts, aged 15–18 when the effects of the Great Recession began to be felt, faced heightened difficulties in gaining entry to jobs or to the vocational education and training (VET) routes that previously ensured access to them.
Assessment of two nondestructive assays for detecting glyphosate resistance in horseweed (Conyza canadensis)
- Clifford H. Koger, Dale L. Shaner, W. Brien Henry, Talia Nadler-Hassar, Walter E. Thomas, John W. Wilcut
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- Journal:
- Weed Science / Volume 53 / Issue 5 / October 2005
- Published online by Cambridge University Press:
- 20 January 2017, pp. 559-566
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Two rapid, nondestructive assays were developed and tested for their potential in differentiating glyphosate-resistant from glyphosate-susceptible biotypes of horseweed. In one assay, leaves of glyphosate-resistant and -susceptible corn, cotton, and soybean plants as well as glyphosate-resistant and -susceptible horseweed plants were dipped in solutions of 0, 300, 600, and 1200 mg ae L−1 glyphosate for 3 d and subsequent injury was evaluated. In the second assay, plant sensitivity to glyphosate was evaluated in vivo by incubating excised leaf disc tissue from the same plants used in the first assay in 0.7, 1.3, 2.6, 5.3, 10.6, 21.1, 42.3, and 84.5 mg ae L−1 glyphosate solutions for 16 h and measuring shikimate levels with a spectrophotometer. The leaf-dip assay differentiated between glyphosate-resistant and -susceptible crops and horseweed biotypes. The 600 mg L−1 rate of glyphosate was more consistent in differentiating resistant and susceptible plants compared with the 300 and 1,200 mg L−1 rates. The in vivo assay detected significant differences between susceptible and glyphosate-resistant plants of all species. Shikimate accumulated in a glyphosate dose-dependent manner in leaf discs from susceptible crops, but shikimate did not accumulate in leaf discs from resistant crops and levels were similar to nontreated leaf discs. Shikimate accumulated at high (≥ 21.1 mg ae L−1) concentrations of glyphosate in leaf discs from all horseweed biotypes. Shikimate accumulated at low glyphosate concentrations (≤ 10.6 mg L−1) in leaf discs from susceptible horseweed biotypes but not in resistant biotypes. Both assays were able to differentiate resistant from susceptible biotypes of horseweed and might have utility for screening other weed populations for resistance to glyphosate.
Absorption and Translocation of Glyphosate and Sucrose in Glyphosate-Resistant Cotton
- Walter E. Thomas, Wesley J. Everman, Ian C. Burke, Clifford H. Koger, John W. Wilcut
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- Journal:
- Weed Technology / Volume 21 / Issue 2 / June 2007
- Published online by Cambridge University Press:
- 20 January 2017, pp. 459-464
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Studies were conducted to evaluate absorption and translocation of 14C-glyphosate in glyphosate-resistant (GR) cotton. Both commercial GR cotton events [glyphosate-resistant event 1, marketed as Roundup Ready®, released 1997 (GRE1), and glyphosate-resistant event 2, marketed as Roundup Ready Flex®, released 2006 (GRE2)] were evaluated at the four-leaf and eight-leaf growth stages. Plants were harvested at 1, 3, 5, and 7 d after treatment (DAT). Glyphosate absorption, as a percentage of applied, increased over time with 29 and 36% absorption at 7 DAT in four-leaf GRE1 and GRE2 cotton, respectively. In eight-leaf cotton, glyphosate absorption (33% at 7 DAT) was not different between events. Glyphosate translocation patterns were not different between events or harvest timings and exhibited a source–sink relation. Observed translocation differences between cotton growth stages were probably due to reduced glyphosate export from the treated leaf of eight-leaf cotton. An additional study compared absorption and translocation of 14C-glyphosate and 14C-sucrose in 5- and 10-leaf GRE2 cotton. Averaged over trials, 14C compounds, and growth stages, cotton absorbed 28% of the applied dose at 14 DAT. On the basis of the percentage of 14C exported out of the treated leaf, glyphosate and sucrose translocation patterns were similar, indicating that glyphosate may be used as a photoassimilate model in GRE2 cotton.
Assessment of two nondestructive assays for detecting glyphosate resistance in horseweed (Conyza canadensis)
- Clifford H. Koger, Dale L. Shaner, W. Brien Henry, Talia Nadler-Hassar, Walter E. Thomas, John W. Wilcut
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- Journal:
- Weed Science / Volume 53 / Issue 4 / August 2005
- Published online by Cambridge University Press:
- 20 January 2017, pp. 438-445
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Two rapid, nondestructive assays were developed and tested for their potential in differentiating glyphosate-resistant from glyphosate-susceptible biotypes of horseweed. In one assay, leaves of glyphosate-resistant and -susceptible corn, cotton, and soybean plants, as well as glyphosate-resistant and -susceptible horseweed plants, were dipped in solutions of 0, 300, 600, and 1,200 mg ae L−1 glyphosate for 3 d, and subsequent injury was evaluated. In the second assay, plant sensitivity to glyphosate was evaluated in vivo by incubating excised leaf disc tissue from the same plants used in the first assay in 0.7, 1.3, 2.6, 5.3, 10.6, 21.1, 42.3, and 84.5 mg ae L−1 glyphosate solutions for 16 h and measuring shikimate levels with a spectrophotometer. The leaf dip assay differentiated between glyphosate-resistant and -susceptible crops and horseweed biotypes. The 600 mg L−1 rate of glyphosate was more consistent in differentiating resistant and susceptible plants compared with the 300 and 1,200 mg L−1 rates. The in vivo assay detected significant differences between susceptible and glyphosate-resistant plants of all species. Shikimate accumulated in a glyphosate dose–dependent manner in leaf discs from susceptible crops, but shikimate did not accumulate in leaf discs from resistant crops, and levels were similar to nontreated leaf discs. Shikimate accumulated at high (≥ 21.1 mg ae L−1) concentrations of glyphosate in leaf discs from all horseweed biotypes. Shikimate accumulated at low glyphosate concentrations (≤ 10.6 mg L−1) in leaf discs from susceptible horseweed biotypes but not in resistant biotypes. Both assays were able to differentiate resistant from susceptible biotypes of horseweed and could have utility for screening other weed populations for resistance to glyphosate.
Control of Common Sunflower (Helianthus annuus) in Artillery Range Trials at Ft. Riley, Kansas
- Walter H. Fick, Wayne A. Geyer, John Barbur
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- Journal:
- Weed Technology / Volume 23 / Issue 4 / December 2009
- Published online by Cambridge University Press:
- 20 January 2017, pp. 540-543
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Military bases in the United States were mandated to reduce the amount of pesticide used to 50% of 1993 levels by 2000. Historically, 2,4-D was applied to control common sunflower, which establishes itself in disturbed soils and obstructs gunners' views of targets. A 25-ha lowland field in Camp Forsyth was selected to compare efficacy of alternative herbicides with that of 2,4-D low-volatile ester (LVE), with the goal of reducing the amount of herbicide applied by at least half. Site vegetation was mostly native tallgrass prairie dominated by warm-season C4 grasses (e.g., big bluestem, Indiangrass, little bluestem, and switchgrass) and including less abundant C3 species in the Asteraceae, Fabaceae, Brassicaceae, and other families. Initially, the site had a high population of common sunflower. All herbicide treatments from 3 yr of field trials were highly and equally effective at reducing common sunflower, decreasing stem density by 83 to100%. Treatments that offer substantial reductions in the amount of herbicide applied are chlorimuron (0.01 kg ae/ha), dicamba + 2,4-D amine (0.07 kg ae/ha + 0.20 kg ae/ha), clopyralid + 2,4-D amine (0.06 kg ae/ha + 0.28 kg ae/ha), 2,4-D LVE (0.56 kg ae/ha), and metsulfuron + 2,4-D amine (0.002 kg ai/ha + 0.28 kg ae/ha). Use of these herbicides at Ft. Riley would reduce total active ingredient applied by 73 to 99% and lower chemical costs for this particular use by as much as 88%.
CMP Challenges for Advanced Technology Nodes beyond Si
- John H Zhang, Stan Tsai, Charan Surisetty, Jody Fronheiser, Shariq Siddiqui, Steven Bentley, Raghuveer Patlolla, Donald F. Canaperi, Walter Kleemeier, Cathy Labelle
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- Journal:
- MRS Advances / Volume 2 / Issue 51 / 2017
- Published online by Cambridge University Press:
- 09 May 2017, pp. 2891-2902
- Print publication:
- 2017
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As the scaling of the device dimensions in CMOS devices runs into physical limitations, new materials beyond Si with high electron and hole mobilities such as Ge, SiGe, and III-V materials are introduced. Challenges of CMP for these materials are reviewed in this paper. First we discussed the challenge of the new integration schemes to CMP. Loading effects can result in different growth rates for varying feature sizes, which results in a critical dimension dependent overburden. This makes it more difficult to meet the targets of the CMP process with respect to oxide loss and Ge/SiGe/III-V dishing. Secondly we discuss the challenge for the reduction of the defects during CMP for these new materials. Finally the challenge that is relevant especially for the introduction of III-V materials is studied. During the polishing of III-V materials, toxic gases as well as III-V containing liquid waste will be created. The chemical mechanism of the waste control is discussed.
CMP Challenges for Advanced Technology Nodes
- John H Zhang, Haigou Huang, Andrew M. Greene, Ruilong Xie, Soon-Cheon Seo, Pietro Montanini, Wei-Tsu Tseng, Stan Tsai, Matthew Malley, Qiang Fang, Raghuveer Patlolla, Dinesh Koli, Dechao Guo, Donald F. Canaperi, Charan Surisetty, Jean E Wynne, Walter Kleemeier, Cathy Labelle
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- Journal:
- MRS Advances / Volume 2 / Issue 44 / 2017
- Published online by Cambridge University Press:
- 16 May 2017, pp. 2361-2372
- Print publication:
- 2017
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The CMP challenges for advanced technology nodes are discussed. Global and local uniformity challenges and their cumulative effects are presented. Uniformity improvements for advanced node integration were achieved through slurry, pad and platen optimization, innovative integration schemes, the reduction of incoming variation and the reduction of cumulative effects. We discuss reduction of typical CMP defect types. Defects resulting from simple mechanisms (foreign material, polish residues) and those resulting from chemical and physical interactions (corrosion, chemical attack, scratches, physical migration) and strategies for control are studied. Defectivity reduction measures include new post-CMP clean chemicals, new slurries and pads and reduction of incoming defectivity. Finally we discuss an observed tradeoff between good defectivity and good uniformity.
Contributors
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- By Mitchell Aboulafia, Frederick Adams, Marilyn McCord Adams, Robert M. Adams, Laird Addis, James W. Allard, David Allison, William P. Alston, Karl Ameriks, C. Anthony Anderson, David Leech Anderson, Lanier Anderson, Roger Ariew, David Armstrong, Denis G. Arnold, E. J. Ashworth, Margaret Atherton, Robin Attfield, Bruce Aune, Edward Wilson Averill, Jody Azzouni, Kent Bach, Andrew Bailey, Lynne Rudder Baker, Thomas R. Baldwin, Jon Barwise, George Bealer, William Bechtel, Lawrence C. Becker, Mark A. Bedau, Ernst Behler, José A. Benardete, Ermanno Bencivenga, Jan Berg, Michael Bergmann, Robert L. Bernasconi, Sven Bernecker, Bernard Berofsky, Rod Bertolet, Charles J. Beyer, Christian Beyer, Joseph Bien, Joseph Bien, Peg Birmingham, Ivan Boh, James Bohman, Daniel Bonevac, Laurence BonJour, William J. Bouwsma, Raymond D. Bradley, Myles Brand, Richard B. Brandt, Michael E. Bratman, Stephen E. Braude, Daniel Breazeale, Angela Breitenbach, Jason Bridges, David O. Brink, Gordon G. Brittan, Justin Broackes, Dan W. Brock, Aaron Bronfman, Jeffrey E. Brower, Bartosz Brozek, Anthony Brueckner, Jeffrey Bub, Lara Buchak, Otavio Bueno, Ann E. Bumpus, Robert W. Burch, John Burgess, Arthur W. Burks, Panayot Butchvarov, Robert E. Butts, Marina Bykova, Patrick Byrne, David Carr, Noël Carroll, Edward S. Casey, Victor Caston, Victor Caston, Albert Casullo, Robert L. Causey, Alan K. L. Chan, Ruth Chang, Deen K. Chatterjee, Andrew Chignell, Roderick M. Chisholm, Kelly J. Clark, E. J. Coffman, Robin Collins, Brian P. Copenhaver, John Corcoran, John Cottingham, Roger Crisp, Frederick J. Crosson, Antonio S. Cua, Phillip D. Cummins, Martin Curd, Adam Cureton, Andrew Cutrofello, Stephen Darwall, Paul Sheldon Davies, Wayne A. Davis, Timothy Joseph Day, Claudio de Almeida, Mario De Caro, Mario De Caro, John Deigh, C. F. Delaney, Daniel C. Dennett, Michael R. DePaul, Michael Detlefsen, Daniel Trent Devereux, Philip E. Devine, John M. Dillon, Martin C. Dillon, Robert DiSalle, Mary Domski, Alan Donagan, Paul Draper, Fred Dretske, Mircea Dumitru, Wilhelm Dupré, Gerald Dworkin, John Earman, Ellery Eells, Catherine Z. Elgin, Berent Enç, Ronald P. Endicott, Edward Erwin, John Etchemendy, C. Stephen Evans, Susan L. Feagin, Solomon Feferman, Richard Feldman, Arthur Fine, Maurice A. Finocchiaro, William FitzPatrick, Richard E. Flathman, Gvozden Flego, Richard Foley, Graeme Forbes, Rainer Forst, Malcolm R. Forster, Daniel Fouke, Patrick Francken, Samuel Freeman, Elizabeth Fricker, Miranda Fricker, Michael Friedman, Michael Fuerstein, Richard A. Fumerton, Alan Gabbey, Pieranna Garavaso, Daniel Garber, Jorge L. A. Garcia, Robert K. Garcia, Don Garrett, Philip Gasper, Gerald Gaus, Berys Gaut, Bernard Gert, Roger F. Gibson, Cody Gilmore, Carl Ginet, Alan H. Goldman, Alvin I. Goldman, Alfonso Gömez-Lobo, Lenn E. Goodman, Robert M. Gordon, Stefan Gosepath, Jorge J. E. Gracia, Daniel W. Graham, George A. Graham, Peter J. Graham, Richard E. Grandy, I. Grattan-Guinness, John Greco, Philip T. Grier, Nicholas Griffin, Nicholas Griffin, David A. Griffiths, Paul J. Griffiths, Stephen R. Grimm, Charles L. Griswold, Charles B. Guignon, Pete A. Y. Gunter, Dimitri Gutas, Gary Gutting, Paul Guyer, Kwame Gyekye, Oscar A. Haac, Raul Hakli, Raul Hakli, Michael Hallett, Edward C. Halper, Jean Hampton, R. James Hankinson, K. R. Hanley, Russell Hardin, Robert M. Harnish, William Harper, David Harrah, Kevin Hart, Ali Hasan, William Hasker, John Haugeland, Roger Hausheer, William Heald, Peter Heath, Richard Heck, John F. Heil, Vincent F. Hendricks, Stephen Hetherington, Francis Heylighen, Kathleen Marie Higgins, Risto Hilpinen, Harold T. Hodes, Joshua Hoffman, Alan Holland, Robert L. Holmes, Richard Holton, Brad W. Hooker, Terence E. Horgan, Tamara Horowitz, Paul Horwich, Vittorio Hösle, Paul Hoβfeld, Daniel Howard-Snyder, Frances Howard-Snyder, Anne Hudson, Deal W. Hudson, Carl A. Huffman, David L. Hull, Patricia Huntington, Thomas Hurka, Paul Hurley, Rosalind Hursthouse, Guillermo Hurtado, Ronald E. Hustwit, Sarah Hutton, Jonathan Jenkins Ichikawa, Harry A. Ide, David Ingram, Philip J. Ivanhoe, Alfred L. Ivry, Frank Jackson, Dale Jacquette, Joseph Jedwab, Richard Jeffrey, David Alan Johnson, Edward Johnson, Mark D. Jordan, Richard Joyce, Hwa Yol Jung, Robert Hillary Kane, Tomis Kapitan, Jacquelyn Ann K. Kegley, James A. Keller, Ralph Kennedy, Sergei Khoruzhii, Jaegwon Kim, Yersu Kim, Nathan L. King, Patricia Kitcher, Peter D. Klein, E. D. Klemke, Virginia Klenk, George L. Kline, Christian Klotz, Simo Knuuttila, Joseph J. Kockelmans, Konstantin Kolenda, Sebastian Tomasz Kołodziejczyk, Isaac Kramnick, Richard Kraut, Fred Kroon, Manfred Kuehn, Steven T. Kuhn, Henry E. Kyburg, John Lachs, Jennifer Lackey, Stephen E. Lahey, Andrea Lavazza, Thomas H. Leahey, Joo Heung Lee, Keith Lehrer, Dorothy Leland, Noah M. Lemos, Ernest LePore, Sarah-Jane Leslie, Isaac Levi, Andrew Levine, Alan E. Lewis, Daniel E. Little, Shu-hsien Liu, Shu-hsien Liu, Alan K. L. Chan, Brian Loar, Lawrence B. Lombard, John Longeway, Dominic McIver Lopes, Michael J. Loux, E. J. Lowe, Steven Luper, Eugene C. Luschei, William G. Lycan, David Lyons, David Macarthur, Danielle Macbeth, Scott MacDonald, Jacob L. Mackey, Louis H. Mackey, Penelope Mackie, Edward H. Madden, Penelope Maddy, G. B. Madison, Bernd Magnus, Pekka Mäkelä, Rudolf A. Makkreel, David Manley, William E. Mann (W.E.M.), Vladimir Marchenkov, Peter Markie, Jean-Pierre Marquis, Ausonio Marras, Mike W. Martin, A. P. Martinich, William L. McBride, David McCabe, Storrs McCall, Hugh J. McCann, Robert N. McCauley, John J. McDermott, Sarah McGrath, Ralph McInerny, Daniel J. McKaughan, Thomas McKay, Michael McKinsey, Brian P. McLaughlin, Ernan McMullin, Anthonie Meijers, Jack W. Meiland, William Jason Melanson, Alfred R. Mele, Joseph R. Mendola, Christopher Menzel, Michael J. Meyer, Christian B. Miller, David W. Miller, Peter Millican, Robert N. Minor, Phillip Mitsis, James A. Montmarquet, Michael S. Moore, Tim Moore, Benjamin Morison, Donald R. Morrison, Stephen J. Morse, Paul K. Moser, Alexander P. D. Mourelatos, Ian Mueller, James Bernard Murphy, Mark C. Murphy, Steven Nadler, Jan Narveson, Alan Nelson, Jerome Neu, Samuel Newlands, Kai Nielsen, Ilkka Niiniluoto, Carlos G. Noreña, Calvin G. Normore, David Fate Norton, Nikolaj Nottelmann, Donald Nute, David S. Oderberg, Steve Odin, Michael O’Rourke, Willard G. Oxtoby, Heinz Paetzold, George S. Pappas, Anthony J. Parel, Lydia Patton, R. P. Peerenboom, Francis Jeffry Pelletier, Adriaan T. Peperzak, Derk Pereboom, Jaroslav Peregrin, Glen Pettigrove, Philip Pettit, Edmund L. Pincoffs, Andrew Pinsent, Robert B. Pippin, Alvin Plantinga, Louis P. Pojman, Richard H. Popkin, John F. Post, Carl J. Posy, William J. Prior, Richard Purtill, Michael Quante, Philip L. Quinn, Philip L. Quinn, Elizabeth S. Radcliffe, Diana Raffman, Gerard Raulet, Stephen L. Read, Andrews Reath, Andrew Reisner, Nicholas Rescher, Henry S. Richardson, Robert C. Richardson, Thomas Ricketts, Wayne D. Riggs, Mark Roberts, Robert C. Roberts, Luke Robinson, Alexander Rosenberg, Gary Rosenkranz, Bernice Glatzer Rosenthal, Adina L. Roskies, William L. Rowe, T. M. Rudavsky, Michael Ruse, Bruce Russell, Lilly-Marlene Russow, Dan Ryder, R. M. Sainsbury, Joseph Salerno, Nathan Salmon, Wesley C. Salmon, Constantine Sandis, David H. Sanford, Marco Santambrogio, David Sapire, Ruth A. Saunders, Geoffrey Sayre-McCord, Charles Sayward, James P. Scanlan, Richard Schacht, Tamar Schapiro, Frederick F. Schmitt, Jerome B. Schneewind, Calvin O. Schrag, Alan D. Schrift, George F. Schumm, Jean-Loup Seban, David N. Sedley, Kenneth Seeskin, Krister Segerberg, Charlene Haddock Seigfried, Dennis M. Senchuk, James F. Sennett, William Lad Sessions, Stewart Shapiro, Tommie Shelby, Donald W. Sherburne, Christopher Shields, Roger A. Shiner, Sydney Shoemaker, Robert K. Shope, Kwong-loi Shun, Wilfried Sieg, A. John Simmons, Robert L. Simon, Marcus G. Singer, Georgette Sinkler, Walter Sinnott-Armstrong, Matti T. Sintonen, Lawrence Sklar, Brian Skyrms, Robert C. Sleigh, Michael Anthony Slote, Hans Sluga, Barry Smith, Michael Smith, Robin Smith, Robert Sokolowski, Robert C. Solomon, Marta Soniewicka, Philip Soper, Ernest Sosa, Nicholas Southwood, Paul Vincent Spade, T. L. S. Sprigge, Eric O. Springsted, George J. Stack, Rebecca Stangl, Jason Stanley, Florian Steinberger, Sören Stenlund, Christopher Stephens, James P. Sterba, Josef Stern, Matthias Steup, M. A. Stewart, Leopold Stubenberg, Edith Dudley Sulla, Frederick Suppe, Jere Paul Surber, David George Sussman, Sigrún Svavarsdóttir, Zeno G. Swijtink, Richard Swinburne, Charles C. Taliaferro, Robert B. Talisse, John Tasioulas, Paul Teller, Larry S. Temkin, Mark Textor, H. S. Thayer, Peter Thielke, Alan Thomas, Amie L. Thomasson, Katherine Thomson-Jones, Joshua C. Thurow, Vzalerie Tiberius, Terrence N. Tice, Paul Tidman, Mark C. Timmons, William Tolhurst, James E. Tomberlin, Rosemarie Tong, Lawrence Torcello, Kelly Trogdon, J. D. Trout, Robert E. Tully, Raimo Tuomela, John Turri, Martin M. Tweedale, Thomas Uebel, Jennifer Uleman, James Van Cleve, Harry van der Linden, Peter van Inwagen, Bryan W. Van Norden, René van Woudenberg, Donald Phillip Verene, Samantha Vice, Thomas Vinci, Donald Wayne Viney, Barbara Von Eckardt, Peter B. M. Vranas, Steven J. Wagner, William J. Wainwright, Paul E. Walker, Robert E. Wall, Craig Walton, Douglas Walton, Eric Watkins, Richard A. Watson, Michael V. Wedin, Rudolph H. Weingartner, Paul Weirich, Paul J. Weithman, Carl Wellman, Howard Wettstein, Samuel C. Wheeler, Stephen A. White, Jennifer Whiting, Edward R. Wierenga, Michael Williams, Fred Wilson, W. Kent Wilson, Kenneth P. Winkler, John F. Wippel, Jan Woleński, Allan B. Wolter, Nicholas P. Wolterstorff, Rega Wood, W. Jay Wood, Paul Woodruff, Alison Wylie, Gideon Yaffe, Takashi Yagisawa, Yutaka Yamamoto, Keith E. Yandell, Xiaomei Yang, Dean Zimmerman, Günter Zoller, Catherine Zuckert, Michael Zuckert, Jack A. Zupko (J.A.Z.)
- Edited by Robert Audi, University of Notre Dame, Indiana
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- The Cambridge Dictionary of Philosophy
- Published online:
- 05 August 2015
- Print publication:
- 27 April 2015, pp ix-xxx
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- By Rony A. Adam, Gloria Bachmann, Nichole M. Barker, Randall B. Barnes, John Bennett, Inbar Ben-Shachar, Jonathan S. Berek, Sarah L. Berga, Monica W. Best, Eric J. Bieber, Frank M. Biro, Shan Biscette, Anita K. Blanchard, Candace Brown, Ronald T. Burkman, Joseph Buscema, John E. Buster, Michael Byas-Smith, Sandra Ann Carson, Judy C. Chang, Annie N. Y. Cheung, Mindy S. Christianson, Karishma Circelli, Daniel L. Clarke-Pearson, Larry J. Copeland, Bryan D. Cowan, Navneet Dhillon, Michael P. Diamond, Conception Diaz-Arrastia, Nicole M. Donnellan, Michael L. Eisenberg, Eric Eisenhauer, Sebastian Faro, J. Stuart Ferriss, Lisa C. Flowers, Susan J. Freeman, Leda Gattoc, Claudine Marie Gayle, Timothy M. Geiger, Jennifer S. Gell, Alan N. Gordon, Victoria L. Green, Jon K. Hathaway, Enrique Hernandez, S. Paige Hertweck, Randall S. Hines, Ira R. Horowitz, Fred M. Howard, William W. Hurd, Fidan Israfilbayli, Denise J. Jamieson, Carolyn R. Jaslow, Erika B. Johnston-MacAnanny, Rohna M. Kearney, Namita Khanna, Caroline C. King, Jeremy A. King, Ira J. Kodner, Tamara Kolev, Athena P. Kourtis, S. Robert Kovac, Ertug Kovanci, William H. Kutteh, Eduardo Lara-Torre, Pallavi Latthe, Herschel W. Lawson, Ronald L. Levine, Frank W. Ling, Larry I. Lipshultz, Steven D. McCarus, Robert McLellan, Shruti Malik, Suketu M. Mansuria, Mohamed K. Mehasseb, Pamela J. Murray, Saloney Nazeer, Farr R. Nezhat, Hextan Y. S. Ngan, Gina M. Northington, Peggy A. Norton, Ruth M. O'Regan, Kristiina Parviainen, Resad P. Pasic, Tanja Pejovic, K. Ulrich Petry, Nancy A. Phillips, Ashish Pradhan, Elizabeth E. Puscheck, Suneetha Rachaneni, Devon M. Ramaeker, David B. Redwine, Robert L. Reid, Carla P. Roberts, Walter Romano, Peter G. Rose, Robert L. Rosenfield, Shon P. Rowan, Mack T. Ruffin, Janice M. Rymer, Evis Sala, Ritu Salani, Joseph S. Sanfilippo, Mahmood I. Shafi, Roger P. Smith, Meredith L. Snook, Thomas E. Snyder, Mary D. Stephenson, Thomas G. Stovall, Richard L. Sweet, Philip M. Toozs-Hobson, Togas Tulandi, Elizabeth R. Unger, Denise S. Uyar, Marion S. Verp, Rahi Victory, Tamara J. Vokes, Michelle J. Washington, Katharine O'Connell White, Paul E. Wise, Frank M. Wittmaack, Miya P. Yamamoto, Christine Yu, Howard A. Zacur
- Edited by Eric J. Bieber, Joseph S. Sanfilippo, University of Pittsburgh, Ira R. Horowitz, Emory University, Atlanta, Mahmood I. Shafi
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- Clinical Gynecology
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- 05 April 2015
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- 23 April 2015, pp viii-xiv
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- By Federica Agosta, Alberto Albanese, Timothy J. Amrhein, A. M. Barrett, Walter S. Bartynski, Felix Benninger, Thomas Brandt, Andrew G. Burke, Michelle Cameron, Elisa Canu, Louis R. Caplan, Christine M. Carr, Daniel J. A. Connolly, Firouz Daneshgari, John DeLuca, Marianne de Visser, Marianne Dieterich, Antonio E. Elia, Joseph H. Feinberg, Massimo Filippi, Lauren C. Frey, Gaëtan Garraux, Andrea Ginestroni, Peter J. Goadsby, Bronwyn E. Hamilton, Simon J. Hickman, Holly E. Hinson, Jon P. Jennings, Jan Kassubek, Horacio Kaufmann, David M. Kaylie, Joanna Kitley, Vladimir S. Kostic, C. T. Paul Krediet, Megan C. Leary, Farooq H. Maniyar, Ken R. Maravilla, Mario Mascalchi, Rajarshi Mazumder, Priyesh Mehta, Jacqueline A. Palace, Raj M. Paspulati, Christopher A. Potter, Angelo Quattrini, Louis P. Riccelli, Nilo Riva, Maria A. Rocca, Mirabelle B. Sajisevi, Richard Salazar-Montero, Nicholas D. Schiff, Jack H. Simon, Israel Steiner, Carl D. Stevens, Bart P. van de Warrenburg, Judith van Gaalen, William J. Weiner, Jane L. Weissman, Jay Yao, G. Bryan Young
- Edited by Massimo Filippi, Jack H. Simon
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- Imaging Acute Neurologic Disease
- Published online:
- 05 October 2014
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- 11 September 2014, pp vi-viii
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- By Lenard A. Adler, Pinky Agarwal, Rehan Ahmed, Jagga Rao Alluri, Fawaz Al-Mufti, Samuel Alperin, Michael Amoashiy, Michael Andary, David J. Anschel, Padmaja Aradhya, Vandana Aspen, Esther Baldinger, Jee Bang, George D. Baquis, John J. Barry, Jason J. S. Barton, Julius Bazan, Amanda R. Bedford, Marlene Behrmann, Lourdes Bello-Espinosa, Ajay Berdia, Alan R. Berger, Mark Beyer, Don C. Bienfang, Kevin M. Biglan, Thomas M. Boes, Paul W. Brazis, Jonathan L. Brisman, Jeffrey A. Brown, Scott E. Brown, Ryan R. Byrne, Rina Caprarella, Casey A. Chamberlain, Wan-Tsu W. Chang, Grace M. Charles, Jasvinder Chawla, David Clark, Todd J. Cohen, Joe Colombo, Howard Crystal, Vladimir Dadashev, Sarita B. Dave, Jean Robert Desrouleaux, Richard L. Doty, Robert Duarte, Jeffrey S. Durmer, Christyn M. Edmundson, Eric R. Eggenberger, Steven Ender, Noam Epstein, Alberto J. Espay, Alan B. Ettinger, Niloofar (Nelly) Faghani, Amtul Farheen, Edward Firouztale, Rod Foroozan, Anne L. Foundas, David Elliot Friedman, Deborah I. Friedman, Steven J. Frucht, Oded Gerber, Tal Gilboa, Martin Gizzi, Teneille G. Gofton, Louis J. Goodrich, Malcolm H. Gottesman, Varda Gross-Tsur, Deepak Grover, David A. Gudis, John J. Halperin, Maxim D. Hammer, Andrew R. Harrison, L. Anne Hayman, Galen V. Henderson, Steven Herskovitz, Caitlin Hoffman, Laryssa A. Huryn, Andres M. Kanner, Gary P. Kaplan, Bashar Katirji, Kenneth R. Kaufman, Annie Killoran, Nina Kirz, Gad E. Klein, Danielle G. Koby, Christopher P. Kogut, W. Curt LaFrance, Patrick J.M. Lavin, Susan W. Law, James L. Levenson, Richard B. Lipton, Glenn Lopate, Daniel J. Luciano, Reema Maindiratta, Robert M. Mallery, Georgios Manousakis, Alan Mazurek, Luis J. Mejico, Dragana Micic, Ali Mokhtarzadeh, Walter J. Molofsky, Heather E. Moss, Mark L. Moster, Manpreet Multani, Siddhartha Nadkarni, George C. Newman, Rolla Nuoman, Paul A. Nyquist, Gaia Donata Oggioni, Odi Oguh, Denis Ostrovskiy, Kristina Y. Pao, Juwen Park, Anastas F. Pass, Victoria S. Pelak, Jeffrey Peterson, John Pile-Spellman, Misha L. Pless, Gregory M. Pontone, Aparna M. Prabhu, Michael T. Pulley, Philip Ragone, Prajwal Rajappa, Venkat Ramani, Sindhu Ramchandren, Ritesh A. Ramdhani, Ramses Ribot, Heidi D. Riney, Diana Rojas-Soto, Michael Ronthal, Daniel M. Rosenbaum, David B. Rosenfield, Durga Roy, Michael J. Ruckenstein, Max C. Rudansky, Eva Sahay, Friedhelm Sandbrink, Jade S. Schiffman, Angela Scicutella, Maroun T. Semaan, Robert C. Sergott, Aashit K. Shah, David M. Shaw, Amit M. Shelat, Claire A. Sheldon, Anant M. Shenoy, Yelizaveta Sher, Jessica A. Shields, Tanya Simuni, Rajpaul Singh, Eric E. Smouha, David Solomon, Mehri Songhorian, Steven A. Sparr, Egilius L. H. Spierings, Eve G. Spratt, Beth Stein, S.H. Subramony, Rosa Ana Tang, Cara Tannenbaum, Hakan Tekeli, Amanda J. Thompson, Michael J. Thorpy, Matthew J. Thurtell, Pedro J. Torrico, Ira M. Turner, Scott Uretsky, Ruth H. Walker, Deborah M. Weisbrot, Michael A. Williams, Jacques Winter, Randall J. Wright, Jay Elliot Yasen, Shicong Ye, G. Bryan Young, Huiying Yu, Ryan J. Zehnder
- Edited by Alan B. Ettinger, Albert Einstein College of Medicine, New York, Deborah M. Weisbrot, State University of New York, Stony Brook
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- Neurologic Differential Diagnosis
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- 05 June 2014
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- 17 April 2014, pp xi-xx
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- By E. Jennifer Ashworth, J. L. Berggren, Charles Burnett, Joan Cadden, Bruce S. Eastwood, Edward Grant, Danielle Jacquart, Elaheh Kheirandish, Tomomi Kinukawa, Walter Roy Laird, Y. Tzvi Langermann, David C. Lindberg, Stephen C. McCcluskey, A. George Molland, Robert G. Morrison, William R. Newman, John North, Vivian Nutton, George Ovitt, Katharine Park, F. Jamil Ragep, Karen Meier Reeds, Emilie Savage-Smith, Michael H. Shank, Katherine H. Tachau, Anne Tihon, David Woodward
- David C. Lindberg, Michael H. Shank
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- The Cambridge History of Science
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- 05 September 2013
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- 07 October 2013, pp xvii-xxii
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