102 results
Tropical vegetation productivity and atmospheric methane over the last 40,000 years from model simulations and stalagmites in Sulawesi, Indonesia
- Claire E. Krause, Alena K. Kimbrough, Michael K. Gagan, Peter O. Hopcroft, Gavin B. Dunbar, Wahyoe S. Hantoro, John C. Hellstrom, Hai Cheng, R. Lawrence Edwards, Henri Wong, Bambang W. Suwargadi, Paul J. Valdes, Hamdi Rifai
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- Journal:
- Quaternary Research / Volume 118 / March 2024
- Published online by Cambridge University Press:
- 26 February 2024, pp. 126-141
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Recent research has shown the potential of speleothem δ13C to record a range of environmental processes. Here, we report on 230Th-dated stalagmite δ13C records for southwest Sulawesi, Indonesia, over the last 40,000 yr to investigate the relationship between tropical vegetation productivity and atmospheric methane concentrations. We demonstrate that the Sulawesi stalagmite δ13C record is driven by changes in vegetation productivity and soil respiration and explore the link between soil respiration and tropical methane emissions using HadCM3 and the Sheffield Dynamic Global Vegetation Model. The model indicates that changes in soil respiration are primarily driven by changes in temperature and CO2, in line with our interpretation of stalagmite δ13C. In turn, modelled methane emissions are driven by soil respiration, providing a mechanism that links methane to stalagmite δ13C. This relationship is particularly strong during the last glaciation, indicating a key role for the tropics in controlling atmospheric methane when emissions from high-latitude boreal wetlands were suppressed. With further investigation, the link between δ13C in stalagmites and tropical methane could provide a low-latitude proxy complementary to polar ice core records to improve our understanding of the glacial–interglacial methane budget.
Risk of bacterial bloodstream infection does not vary by central-line type during neutropenic periods in pediatric acute myeloid leukemia
- Caitlin W. Elgarten, William R. Otto, Luke Shenton, Madison T. Stein, Joseph Horowitz, Catherine Aftandilian, Staci D. Arnold, Kira O. Bona, Emi Caywood, Anderson B. Collier, M. Monica Gramatges, Meret Henry, Craig Lotterman, Kelly Maloney, Arunkumar J. Modi, Amir Mian, Rajen Mody, Elaine Morgan, Elizabeth A. Raetz, Anupam Verma, Naomi Winick, Jennifer J. Wilkes, Jennifer C. Yu, Richard Aplenc, Brian T. Fisher, Kelly D. Getz
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 44 / Issue 2 / February 2023
- Published online by Cambridge University Press:
- 25 April 2022, pp. 222-229
- Print publication:
- February 2023
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Background:
Bloodstream infections (BSIs) are a frequent cause of morbidity in patients with acute myeloid leukemia (AML), due in part to the presence of central venous access devices (CVADs) required to deliver therapy.
Objective:To determine the differential risk of bacterial BSI during neutropenia by CVAD type in pediatric patients with AML.
Methods:We performed a secondary analysis in a cohort of 560 pediatric patients (1,828 chemotherapy courses) receiving frontline AML chemotherapy at 17 US centers. The exposure was CVAD type at course start: tunneled externalized catheter (TEC), peripherally inserted central catheter (PICC), or totally implanted catheter (TIC). The primary outcome was course-specific incident bacterial BSI; secondary outcomes included mucosal barrier injury (MBI)-BSI and non-MBI BSI. Poisson regression was used to compute adjusted rate ratios comparing BSI occurrence during neutropenia by line type, controlling for demographic, clinical, and hospital-level characteristics.
Results:The rate of BSI did not differ by CVAD type: 11 BSIs per 1,000 neutropenic days for TECs, 13.7 for PICCs, and 10.7 for TICs. After adjustment, there was no statistically significant association between CVAD type and BSI: PICC incident rate ratio [IRR] = 1.00 (95% confidence interval [CI], 0.75–1.32) and TIC IRR = 0.83 (95% CI, 0.49–1.41) compared to TEC. When MBI and non-MBI were examined separately, results were similar.
Conclusions:In this large, multicenter cohort of pediatric AML patients, we found no difference in the rate of BSI during neutropenia by CVAD type. This may be due to a risk-profile for BSI that is unique to AML patients.
Optimizing red blood cell transfusion practices in the intensive care unit: a multi-phased health technology reassessment
- Lesley J.J. Soril, Tom W. Noseworthy, Derek R. Townsend, Sean M. Bagshaw, Henry T. Stelfox, David A. Zygun, Fiona M. Clement
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 38 / Issue 1 / 2022
- Published online by Cambridge University Press:
- 20 December 2021, e10
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Background
Health technology reassessment (HTR) is a process to manage existing health technologies to ensure ongoing optimal use. A model to guide HTR was developed; however, there is limited practical experience. This paper addresses this knowledge gap through the completion of a multi-phase HTR of red blood cell (RBC) transfusion practices in the intensive care unit (ICU).
ObjectiveThe HTR consisted of three phases and here we report on the final phase: the development, implementation, and evaluation of behavior change interventions aimed at addressing inappropriate RBC transfusions in an ICU.
MethodsThe interventions, comprised of group education and audit and feedback, were co-designed and implemented with clinical leaders. The intervention was evaluated through a controlled before-and-after pilot feasibility study. The primary outcome was the proportion of potentially inappropriate RBC transfusions (i.e., with a pre-transfusion hemoglobin of 70 g/L or more).
ResultsThere was marked variability in the monthly proportion of potentially inappropriate RBC transfusions. Relative to the pre-intervention phase, there was no significant difference in the proportion of potentially inappropriate RBC transfusions post-intervention. Lessons from this work include the importance of early and meaningful engagement of clinical leaders; tailoring the intervention modalities; and, efficient access to data through an electronic clinical information system.
ConclusionsIt was feasible to design, implement, and evaluate a tailored, multi-modal behavior change intervention in this small-scale pilot study. However, early evaluation of the intervention revealed no change in technology use leading to reflection on the important question of how the HTR model needs to be improved.
Nomenclature for Pediatric and Congenital Cardiac Care: Unification of Clinical and Administrative Nomenclature – The 2021 International Paediatric and Congenital Cardiac Code (IPCCC) and the Eleventh Revision of the International Classification of Diseases (ICD-11)
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- Jeffrey P. Jacobs, Rodney C. G. Franklin, Marie J. Béland, Diane E. Spicer, Steven D. Colan, Henry L. Walters III, Frédérique Bailliard, Lucile Houyel, James D. St. Louis, Leo Lopez, Vera D. Aiello, J. William Gaynor, Otto N. Krogmann, Hiromi Kurosawa, Bohdan J. Maruszewski, Giovanni Stellin, Paul Morris Weinberg, Marshall Lewis Jacobs, Jeffrey R. Boris, Meryl S. Cohen, Allen D. Everett, Jorge M. Giroud, Kristine J. Guleserian, Marina L. Hughes, Amy L. Juraszek, Stephen P. Seslar, Charles W. Shepard, Shubhika Srivastava, Andrew C. Cook, Adrian Crucean, Lazaro E. Hernandez, Rohit S. Loomba, Lindsay S. Rogers, Stephen P. Sanders, Jill J. Savla, Elif Seda Selamet Tierney, Justin T. Tretter, Lianyi Wang, Martin J. Elliott, Constantine Mavroudis, Christo I. Tchervenkov
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- Journal:
- Cardiology in the Young / Volume 31 / Issue 7 / July 2021
- Published online by Cambridge University Press:
- 29 July 2021, pp. 1057-1188
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Substantial progress has been made in the standardization of nomenclature for paediatric and congenital cardiac care. In 1936, Maude Abbott published her Atlas of Congenital Cardiac Disease, which was the first formal attempt to classify congenital heart disease. The International Paediatric and Congenital Cardiac Code (IPCCC) is now utilized worldwide and has most recently become the paediatric and congenital cardiac component of the Eleventh Revision of the International Classification of Diseases (ICD-11). The most recent publication of the IPCCC was in 2017. This manuscript provides an updated 2021 version of the IPCCC.
The International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD), in collaboration with the World Health Organization (WHO), developed the paediatric and congenital cardiac nomenclature that is now within the eleventh version of the International Classification of Diseases (ICD-11). This unification of IPCCC and ICD-11 is the IPCCC ICD-11 Nomenclature and is the first time that the clinical nomenclature for paediatric and congenital cardiac care and the administrative nomenclature for paediatric and congenital cardiac care are harmonized. The resultant congenital cardiac component of ICD-11 was increased from 29 congenital cardiac codes in ICD-9 and 73 congenital cardiac codes in ICD-10 to 318 codes submitted by ISNPCHD through 2018 for incorporation into ICD-11. After these 318 terms were incorporated into ICD-11 in 2018, the WHO ICD-11 team added an additional 49 terms, some of which are acceptable legacy terms from ICD-10, while others provide greater granularity than the ISNPCHD thought was originally acceptable. Thus, the total number of paediatric and congenital cardiac terms in ICD-11 is 367. In this manuscript, we describe and review the terminology, hierarchy, and definitions of the IPCCC ICD-11 Nomenclature. This article, therefore, presents a global system of nomenclature for paediatric and congenital cardiac care that unifies clinical and administrative nomenclature.
The members of ISNPCHD realize that the nomenclature published in this manuscript will continue to evolve. The version of the IPCCC that was published in 2017 has evolved and changed, and it is now replaced by this 2021 version. In the future, ISNPCHD will again publish updated versions of IPCCC, as IPCCC continues to evolve.
Influence of birth cohort on age of onset cluster analysis in bipolar I disorder
- M. Bauer, T. Glenn, M. Alda, O.A. Andreassen, E. Angelopoulos, R. Ardau, C. Baethge, R. Bauer, F. Bellivier, R.H. Belmaker, M. Berk, T.D. Bjella, L. Bossini, Y. Bersudsky, E.Y.W. Cheung, J. Conell, M. Del Zompo, S. Dodd, B. Etain, A. Fagiolini, M.A. Frye, K.N. Fountoulakis, J. Garneau-Fournier, A. Gonzalez-Pinto, H. Harima, S. Hassel, C. Henry, A. Iacovides, E.T. Isometsä, F. Kapczinski, S. Kliwicki, B. König, R. Krogh, M. Kunz, B. Lafer, E.R. Larsen, U. Lewitzka, C. Lopez-Jaramillo, G. MacQueen, M. Manchia, W. Marsh, M. Martinez-Cengotitabengoa, I. Melle, S. Monteith, G. Morken, R. Munoz, F.G. Nery, C. O’Donovan, Y. Osher, A. Pfennig, D. Quiroz, R. Ramesar, N. Rasgon, A. Reif, P. Ritter, J.K. Rybakowski, K. Sagduyu, A.M. Scippa, E. Severus, C. Simhandl, D.J. Stein, S. Strejilevich, A. Hatim Sulaiman, K. Suominen, H. Tagata, Y. Tatebayashi, C. Torrent, E. Vieta, B. Viswanath, M.J. Wanchoo, M. Zetin, P.C. Whybrow
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- Journal:
- European Psychiatry / Volume 30 / Issue 1 / January 2015
- Published online by Cambridge University Press:
- 15 April 2020, pp. 99-105
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Purpose:
Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
Methods:The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
Results:There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
Conclusion:These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.
EPA-0671 – Association Study Between Toll-Like Receptors 2 and 4 Single Nucleotide Polymorphisms and Bipolar Disorder
- J. Oliveira, B. Etain, W. Boukouaci, K. Amokrane, M. Bennabi, F. Bellivier, C. Henry, J. Kahn, D. Charron, R. Krishnamoorthy, M. Leboyer, R. Tamouza
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- European Psychiatry / Volume 29 / Issue S1 / 2014
- Published online by Cambridge University Press:
- 15 April 2020, p. 1
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Introduction:
Immune dysfunction is thought to play a critical role in the pathophysiology of bipolar disorder (BD). Better insight into the genetic control of innate immune responses is of importance due to possible interactions with environmental risk factors such as infectious agents, particularly early in life.
Objectives:Given the importance of Toll-like receptors (TLRs) in innate immunity, we analysed the association of selected genetic variants of TLR-2 and TLR-4, both major sensors of pathogenic infectious and non-infectious structures, with BD.
Aims:Explore possible implications of the innate arm of the immune response in BD.
Methods:Genomic DNAs from 572 BD patients and 202 controls were analyzed for the distribution of polymorphisms on the TLR-2 and TLR-4 loci using TaqMan®. Associations were examined using Chi-square test.
Results:We found that TLR-4 rs1927914 AA and rs11536891 TT genotypes were more frequent in BD patients than in controls (corrected p; pc = .02 and .02 respectively) particularly in early-onset BD (EOBD) patients (pc = .004 and .006) born during the summer season (pc = 02 and .002 respectively). We also found that TLR-2 rs3804099 TT and rs4696480 TT genotypes were significantly more prevalent in EOBD group as compared to the late-onset BD (LOBD) subset, the latter only after excluding patients with positive family history of psychiatric disorders (pc=0.024 and 0.002 respectively).
Conclusions:We report an association between BD and TLR-2 and TLR-4 genetic variants suggesting an important role for pathogens in disease development.
An ultra-wide bandwidth (704 to 4 032 MHz) receiver for the Parkes radio telescope
- George Hobbs, Richard N. Manchester, Alex Dunning, Andrew Jameson, Paul Roberts, Daniel George, J. A. Green, John Tuthill, Lawrence Toomey, Jane F. Kaczmarek, Stacy Mader, Malte Marquarding, Azeem Ahmed, Shaun W. Amy, Matthew Bailes, Ron Beresford, N. D. R. Bhat, Douglas C.-J. Bock, Michael Bourne, Mark Bowen, Michael Brothers, Andrew D. Cameron, Ettore Carretti, Nick Carter, Santy Castillo, Raji Chekkala, Wan Cheng, Yoon Chung, Daniel A. Craig, Shi Dai, Joanne Dawson, James Dempsey, Paul Doherty, Bin Dong, Philip Edwards, Tuohutinuer Ergesh, Xuyang Gao, JinLin Han, Douglas Hayman, Balthasar Indermuehle, Kanapathippillai Jeganathan, Simon Johnston, Henry Kanoniuk, Michael Kesteven, Michael Kramer, Mark Leach, Vince Mcintyre, Vanessa Moss, Stefan Osłowski, Chris Phillips, Nathan Pope, Brett Preisig, Daniel Price, Ken Reeves, Les Reilly, John Reynolds, Tim Robishaw, Peter Roush, Tim Ruckley, Elaine Sadler, John Sarkissian, Sean Severs, Ryan Shannon, Ken Smart, Malcolm Smith, Stephanie Smith, Charlotte Sobey, Lister Staveley-Smith, Anastasios Tzioumis, Willem van Straten, Nina Wang, Linqing Wen, Matthew Whiting
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- Journal:
- Publications of the Astronomical Society of Australia / Volume 37 / 2020
- Published online by Cambridge University Press:
- 08 April 2020, e012
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We describe an ultra-wide-bandwidth, low-frequency receiver recently installed on the Parkes radio telescope. The receiver system provides continuous frequency coverage from 704 to 4032 MHz. For much of the band ( ${\sim}60\%$ ), the system temperature is approximately 22 K and the receiver system remains in a linear regime even in the presence of strong mobile phone transmissions. We discuss the scientific and technical aspects of the new receiver, including its astronomical objectives, as well as the feed, receiver, digitiser, and signal processor design. We describe the pipeline routines that form the archive-ready data products and how those data files can be accessed from the archives. The system performance is quantified, including the system noise and linearity, beam shape, antenna efficiency, polarisation calibration, and timing stability.
Effect of Fall-Applied Residual Herbicides on Rice Growth and Yield
- Benjamin H. Lawrence, Jason A. Bond, Henry M. Edwards, Bobby R. Golden, Garret B. Montgomery, Thomas W. Eubank III, Timothy W. Walker
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- Journal:
- Weed Technology / Volume 32 / Issue 5 / October 2018
- Published online by Cambridge University Press:
- 20 August 2018, pp. 526-531
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Glyphosate-resistant (GR) Italian ryegrass is one of the most troublesome weeds in Mississippi row crop production. Fall-applied residual herbicide applications are recommended for control of GR Italian ryegrass. However, carryover of residual herbicides applied in fields for rice production can have a negative impact on rice performance. Field studies were conducted in Stoneville, MS, to determine the effects of fall-applied residual herbicides on rice growth and yield. Herbicide treatments included suggested use rates (1×) of clomazone at 840 g ai ha–1, pyroxasulfone 170 g ai ha–1, S-metolachlor 1,420 g ai ha–1, and trifluralin 1,680 g ai ha–1, and two times (2×) the suggested use rates in the fall before rice seeding. Pooled across application rate, pyroxasulfone, S-metolachlor, and trifluralin injured rice to an extent 28% to 36% greater than clomazone 14 d after emergence (DAE). Rice seedling density and height 14 DAE and rice maturity were negatively affected by all fall-applied herbicides except clomazone. Applications at 2× rates reduced rough rice yields in plots treated with pyroxasulfone, S-metolachlor, and trifluralin compared with clomazone. Pyroxasulfone applied at the 2× rate reduced rough rice yield 22% compared with the 1× rate. Rough rice yield was 90% or greater of the nontreated control in plots treated with either rate of S-metolachlor, and these were comparable with rough rice yields from plots treated with both rates of trifluralin and the 1× rate of pyroxasulfone. Early-season injury and reductions in seedling density and height 14 DAE, would preclude even 1× applications of pyroxasulfone, S-metolachlor, and trifluralin from being viable options for residual herbicide treatments targeting GR Italian ryegrass in the fall before rice seeding. Of the herbicides evaluated, only clomazone should be utilized as a fall-applied residual herbicide treatment targeting GR Italian ryegrass before seeding rice.
British Escherichia coli O157 in Cattle Study (BECS): to determine the prevalence of E. coli O157 in herds with cattle destined for the food chain
- M. K. HENRY, S. C. TONGUE, J. EVANS, C. WEBSTER, I. J. McKENDRICK, M. MORGAN, A. WILLETT, A. REEVES, R. W. HUMPHRY, D. L. GALLY, G. J. GUNN, M. E. CHASE-TOPPING
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- Journal:
- Epidemiology & Infection / Volume 145 / Issue 15 / November 2017
- Published online by Cambridge University Press:
- 19 September 2017, pp. 3168-3179
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Escherichia coli O157 are zoonotic bacteria for which cattle are an important reservoir. Prevalence estimates for E. coli O157 in British cattle for human consumption are over 10 years old. A new baseline is needed to inform current human health risk. The British E. coli O157 in Cattle Study (BECS) ran between September 2014 and November 2015 on 270 farms across Scotland and England & Wales. This is the first study to be conducted contemporaneously across Great Britain, thus enabling comparison between Scotland and England & Wales. Herd-level prevalence estimates for E. coli O157 did not differ significantly for Scotland (0·236, 95% CI 0·166–0·325) and England & Wales (0·213, 95% CI 0·156–0·283) (P = 0·65). The majority of isolates were verocytotoxin positive. A higher proportion of samples from Scotland were in the super-shedder category, though there was no difference between the surveys in the likelihood of a positive farm having at least one super-shedder sample. E. coli O157 continues to be common in British beef cattle, reaffirming public health policy that contact with cattle and their environments is a potential infection source.
Electron Microprobe Analysis of Glass Shards from Tephra Assigned to Set W, Mount St. Helens, Washington1
- Henry W. Smith, Rose Okazaki, Charles R. Knowles
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- Quaternary Research / Volume 7 / Issue 2 / March 1977
- Published online by Cambridge University Press:
- 20 January 2017, pp. 207-217
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We have extended the fallout areas for each of two members of tephra-set W, erupted from Mount St. Helens about 1500 ad , by several hundred kilometers beyond the limits mapped in 1975. We traced one member (We) east into Idaho, and the other (Wn) northeast into British Columbia. After using stratigraphic and petrographic observations to assign more than 100 tephra samples to set W, we found 26 of these, selected for chemical analysis, to be closely similar in content of Ca, Fe, and K in glass shards. But improved homogeneity was evident when the 26 sampling localities for tephra W were segregated geographically, east vs. northeast of the volcano. When Ca:Fe:K proportions were plotted on a ternary diagram, there was no overlap of the plotting areas for these two groups of tephra W samples. Without such data, tephra layers We and Wn are currently separable only from stratigraphic and geographic information. Partial glass analysis is also an aid, along with stratigraphic position and petrographic characteristics, in distinguishing tephra W from associated tephra layers. These include tephra layers T and Yn from Mount St. Helens, as well as older tephra layers from Mount Mazama and Glacier Peak.
Evaluation of Flufenacet plus Metribuzin Mixtures for Control of Italian Ryegrass in Winter Wheat
- Rebecca M. Koepke-Hill, Gregory R. Armel, Kevin W. Bradley, William A. Bailey, Henry P. Wilson, Thomas E. Hines
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- Journal:
- Weed Technology / Volume 25 / Issue 4 / December 2011
- Published online by Cambridge University Press:
- 20 January 2017, pp. 563-567
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Field studies were conducted to compare the effectiveness of PRE and POST applications of a prepackaged mixture of flufenacet plus metribuzin with that of diclofop for winter wheat tolerance and control of Italian ryegrass. Additional studies investigated the effectiveness of reduced rates of flufenacet plus metribuzin applied POST to Italian ryegrass when wheat was in the spike stage. All PRE and POST applications of flufenacet plus metribuzin produced similar or greater injury to wheat and more consistent control of Italian ryegrass than PRE or POST applications of diclofop. PRE applications of flufenacet plus metribuzin controlled Italian ryegrass 73 to 77%, whereas POST applications controlled Italian ryegrass 77 to 99%. PRE applications of diclofop controlled Italian ryegrass 57%; POST application controlled Italian ryegrass 78%. Wheat injury from flufenacet plus metribuzin applications varied with application rate, cultivar, and year of application.
Spectral reflectance curves to distinguish soybean from common cocklebur (Xanthium strumarium) and sicklepod (Cassia obtusifolia) grown with varying soil moisture
- W. Brien Henry, David R. Shaw, Kambham R. Reddy, Lori M. Bruce, Hrishikesh D. Tamhankar
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- Journal:
- Weed Science / Volume 52 / Issue 5 / October 2004
- Published online by Cambridge University Press:
- 20 January 2017, pp. 788-796
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Experiments were conducted to examine the use of spectral reflectance curves for discriminating between plant species across moisture levels. Weed species and soybean were grown at three moisture levels, and spectral reflectance data and leaf water potential were collected every other day after the imposition of moisture stress at 8 wk after planting. Moisture stress did not reduce the ability to discriminate between species. As moisture stress increased, it became easier to distinguish between species, regardless of analysis technique. Signature amplitudes of the top five bands, discrete wavelet transforms, and multiple indices were promising analysis techniques. Discriminant models created from data set of 1 yr and validated on additional data sets provided, on average, approximately 80% accurate classification among weeds and crop. This suggests that these models are relatively robust and could potentially be used across environmental conditions in field scenarios.
Electron Microprobe Data for Tephra Attributed to Glacier Peak, Washington1
- Henry W. Smith, Rose Okazaki, Charles R. Knowles
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- Quaternary Research / Volume 7 / Issue 2 / March 1977
- Published online by Cambridge University Press:
- 20 January 2017, pp. 197-206
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Reference samples of three prominent pumice units of Glacier Peak tephra collected east of the volcano within a distance of 100 km are similar petrographically to units described by earlier workers. Glass shards isolated from these samples were analyzed by electron microprobe to determine the content of Ca, Fe, and K. Resulting data, plus those published for two other references samples, provide a basis for attributing certain outlying tephra layers from 14 locations in eastern Washington, Idaho, Wyoming, and Montana to eruptions of Glacier Peak. Ten of the samples have properties of both Glacier Peak tephra and Mount St. Helens set J tephra, but proportions of Ca:Fe:K in glass shards indicate that 9 of the 10 outlying samples came from Glacier Peak, whereas one is assigned to Mount St. Helens set J. The remaining six outlying samples, all from southeastern Washington, contain cummingtonite phenocrysts and are chemically similar to some parts of Mount St. Helens tephra sets that are older than 12,000 BP.
Remote Sensing to Detect Herbicide Drift on Crops
- W. Brien Henry, David R. Shaw, Kambham R. Reddy, Lori M. Bruce, Hrishikesh D. Tamhankar
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- Journal:
- Weed Technology / Volume 18 / Issue 2 / June 2004
- Published online by Cambridge University Press:
- 20 January 2017, pp. 358-368
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Glyphosate and paraquat herbicide drift injury to crops may substantially reduce growth or yield. Determining the type and degree of injury is of importance to a producer. This research was conducted to determine whether remote sensing could be used to identify and quantify herbicide injury to crops. Soybean and corn plants were grown in 3.8-L pots to the five- to seven-leaf stage, at which time, applications of nonselective herbicides were made. Visual injury estimates were made, and hyperspectral reflectance data were recorded 1, 4, and 7 d after application (DAA). Several analysis techniques including multiple indices, signature amplitude (SA) with spectral bands as features, and wavelet analysis were used to distinguish between herbicide-treated and nontreated plants. Classification accuracy using SA analysis of paraquat injury on soybean was better than 75% for both 1/2- and 1/8× rates at 1, 4, and 7 DAA. Classification accuracy of paraquat injury on corn was better than 72% for the 1/2× rate at 1, 4, and 7 DAA. These data suggest that hyperspectral reflectance may be used to distinguish between healthy plants and injured plants to which herbicides have been applied; however, the classification accuracies remained at 75% or higher only when the higher rates of herbicide were applied. Applications of a 1/2× rate of glyphosate produced 55 to 81% soybean injury and 20 to 50% corn injury 4 and 7 DAA, respectively. However, using SA analysis, the moderately injured plants were indistinguishable from the uninjured controls, as represented by the low classification accuracies at the 1/8-, 1/32-, and 1/64× rates. The most promising technique for identifying drift injury was wavelet analysis, which successfully distinguished between corn plants treated with either the 1/8- or the 1/2× rates of paraquat compared with the nontreated corn plants better than 92% 1, 4, and 7 DAA. These analysis techniques, once tested and validated on field scale data, may help determine the extent and the degree of herbicide drift for making appropriate and, more importantly, timely management decisions.
Remote Sensing to Distinguish Soybean from Weeds After Herbicide Application
- W. Brien Henry, David R. Shaw, Kambham R. Reddy, Lori M. Bruce, Hrishikesh D. Tamhankar
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- Journal:
- Weed Technology / Volume 18 / Issue 3 / September 2004
- Published online by Cambridge University Press:
- 20 January 2017, pp. 594-604
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Two experiments, one focusing on preemergence (PRE) herbicides and the other on postemergence (POST) herbicides, were conducted and repeated in time to examine the utility of hyperspectral remote sensing data for discriminating common cocklebur, hemp sesbania, pitted morningglory, sicklepod, and soybean after PRE and POST herbicide application. Discriminant models were created from combinations of multiple indices. The model created from the second experimental run's data set and validated on the first experimental run's data provided an average of 97% correct classification of soybean and an overall average classification accuracy of 65% for all species. These data suggest that these models are relatively robust and could potentially be used across a wide range of herbicide applications in field scenarios. From the data set pooled across time and experiment types, a single discriminant model was created with multiple indices that discriminated soybean from weeds 88%, on average, regardless of herbicide, rate, or species. Signature amplitudes, an additional classification technique, produced variable results with respect to discriminating soybean from weeds after herbicide application and discriminating between controls and plants to which herbicides were applied; thus, this was not an adequate classification technique.
Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance
- Ming Li, Xiong-jian Luo, Mikael Landén, Sarah E. Bergen, Christina M. Hultman, Xiao Li, Wen Zhang, Yong-Gang Yao, Chen Zhang, Jiewei Liu, Manuel Mattheisen, Sven Cichon, Thomas W. Mühleisen, Franziska A. Degenhardt, Markus M. Nöthen, Thomas G. Schulze, Maria Grigoroiu-Serbanescu, Hao Li, Chris K. Fuller, Chunhui Chen, Qi Dong, Chuansheng Chen, Stéphane Jamain, Marion Leboyer, Frank Bellivier, Bruno Etain, Jean-Pierre Kahn, Chantal Henry, Martin Preisig, Zoltán Kutalik, Enrique Castelao, Adam Wright, Philip B. Mitchell, Janice M. Fullerton, Peter R. Schofield, Grant W. Montgomery, Sarah E. Medland, Scott D. Gordon, Nicholas G. Martin, MooDS Consortium, The Swedish Bipolar Study Group, Marcella Rietschel, Chunyu Liu, Joel E. Kleinman, Thomas M. Hyde, Daniel R. Weinberger, Bing Su
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- Journal:
- The British Journal of Psychiatry / Volume 208 / Issue 2 / February 2016
- Published online by Cambridge University Press:
- 02 January 2018, pp. 128-137
- Print publication:
- February 2016
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Background
Bipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.
AimsWe sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.
MethodTo detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.
ResultsIntegrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10–5). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10–8). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.
ConclusionsOur findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder.
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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. 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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
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- 05 August 2015
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- 27 April 2015, pp ix-xxx
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- By Cecil S. Ash, Paul Barach, Ulrike Buehner, M. Ross Bullock, Leonardo Canale, Henry G. Chou, Jeffrey A. Claridge, John J. Como, Armagan Dagal, Martin Dauber, James S. Davis, Shalini Dhir, François Donati, Roman Dudaryk, Richard P. Dutton, Talmage D. Egan, Yashar Eshraghi, John R. Fisgus, Jeff Gadsden, Sugantha Ganapathy, Mark A. Gerhardt, Inderjit Gill, Joseph F. Golob, Glenn P. Gravlee, Marcello Guglielmi, Jana Hambley, Peter Hebbard, Elena J. Holak, Khadil Hosein, Ken Johnson, Matthew A. Joy, George W. Kanellakos, Olga Kaslow, Arthur M. Lam, Vanetta Levesque, Jessica Anne Lovich-Sapola, M. Jocelyn Loy, Peter F. Mahoney, Donn Marciniak, Maureen McCunn, Craig C. McFarland, Maroun J. Mhanna, Timothy Moore, Cynthia Nguyen, Maxim Novikov, E. Orestes O’Brien, Ketan P. Parekh, Claire L. Park, Michael J. A. Parr, Elie Rizkala, Steven Roth, Alistair Royse, Colin Royse, Kasia Petelenz Rubin, David Ryan, Claire Sandstrom, Carl I. Schulman, Rishad Shaikh, Ranjita Sharma, Jeffrey H. Silverstein, Peter Slinger, Charles E. Smith, Christopher Smith, Paul Soeding, Rakesh V. Sondekoppam, P. David Soran, Eldar Søreide, Elizabeth A. Steele, Kristian Strand, Dennis M. Super, Kutaiba Tabbaa, Nicholas T. Tarmey, Joshua M. Tobin, Kalpana Tyagaraj, Heather A. Vallier, Sandra Werner, Earl Willis Weyers, William C. Wilson, Shoji Yokobori, Charles J. Yowler
- Edited by Charles E. Smith
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- Trauma Anesthesia
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- 05 April 2015
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- 09 April 2015, pp vii-x
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- By Agoston T. Agoston, Syed Z. Ali, Mahul B. Amin, Daniel A. Arber, Pedram Argani, Sylvia L. Asa, Rebecca N. Baergen, Zubair W. Baloch, Andrew M. Bellizzi, Kurt Benirschke, Allen Burke, Kenneth B. Calder, Karen L. Chang, Rebecca D. Chernock, Wang Cheung, Thomas V. Colby, Byron P. Croker, Ronald A. DeLellis, Edward F. DiCarlo, Ralph C. Eagle, Hormoz Ehya, Brett M. Elicker, Tarik M. Elsheikh, Robert E. Fechner, Linda D. Ferrell, Melina B. Flanagan, Douglas B. Flieder, Christopher S. Foster, Lillian Gaber, Karuna Garg, Kim R. Geisinger, Ryan M. Gill, Eric F. Glassy, David J. Glembocki, Zachary D. Goodman, Robert O. Greer, David J. Grignon, Gerardo E. Guiter, Kymberly A. Gyure, Ian S. Hagemann, Michael R. Henry, Jason L. Hornick, Ralph H. Hruban, Phyllis C. Huettner, Peter A. Humphrey, Olga B. Ioffe, Edward C. Klatt, Michael J. Klein, Ernest E. Lack, James N. Lampros, Lester J. Layfield, Robin D. LeGallo, Kevin O. Leslie, James S. Lewis, Virginia A. LiVolsi, Alberto M. Marchevsky, Anne Marie McNicol, Mitra Mehrad, Elizabeth Montgomery, Cesar A. Moran, Christopher A. Moskaluk, George J. Netto, G. Petur Nielsen, Robert D. Odze, Arthur S. Patchefsky, James W. Patterson, Elizabeth N. Pavlisko, John D. Pfeifer, Celeste N. Powers, Richard A. Prayson, Anja C. Roden, Victor L. Roggli, Andrew E. Rosenberg, Sherif Said, Margie A. Scott, Raja R. Seethala, Carlie S. Sigel, Jan F. Silverman, Bruce R. Smoller, Edward B. Stelow, Nora C. J. Sun, Mark W. Teague, Satish K. Tickoo, Thomas M. Ulbright, Paul E. Wakely, Jun Wang, Lawrence M. Weiss, Mark R. Wick, Howard H. Wu, Rhonda K. Yantiss, Charles Zaloudek, Yaxia Zhang, Xiaohui Sheila Zhao
- Edited by Mark R. Wick, University of Virginia, Virginia A. LiVolsi, University of Pennsylvania School of Medicine, John D. Pfeifer, Washington University School of Medicine, St Louis, Edward B. Stelow, University of Virginia, Paul E. Wakely, Jr
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- Silverberg's Principles and Practice of Surgical Pathology and Cytopathology
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- 13 March 2015
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- 26 March 2015, pp vii-x
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Land Use Implications of Expanding Biofuel Demand
- Michael R. Dicks, Jody Campiche, Daniel De La Torre Ugarte, Chad Hellwinckel, Henry L. Bryant, James W. Richardson
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- Journal of Agricultural and Applied Economics / Volume 41 / Issue 2 / August 2009
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- 26 January 2015, pp. 435-453
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The Renewable Fuel Standard mandates in the Energy Independence and Security Act of 2007 will require 36 billion gallons of ethanol to be produced in 2022. The mandates require that 16 of the 36 billion gallons must be produced from cellulosic feedstocks. The potential land use implications resulting from these mandates were examined using two methods, the POLYSYS model and a general equilibrium model. Results of the POLYSYS analysis indicated that 72.1 million tons of corn stover, 23.5 million tons of wheat straw, and 24.7 million acres would be used to produce 109 million tons of switchgrass in 2025 to meet the mandate. Results of the CGE analysis indicated that 10.9 billion bushels of corn grain, 71 million tons of corn stover, and 56,200 tons of switchgrass is needed to meet the mandate.