The role of actions in auditory object discrimination.

Action representations can interact with object recognition processes. For example, so-called mirror neurons respond both when performing an action and when seeing or hearing such actions. Investigations of auditory object processing have largely focused on categorical discrimination, which begins within the initial 100 ms post-stimulus onset and subsequently engages distinct cortical networks. Whether action representations themselves contribute to auditory object recognition and the precise kinds of actions recruiting the auditory-visual mirror neuron system remain poorly understood. We applied electrical neuroimaging analyses to auditory evoked potentials (AEPs) in response to sounds of man-made objects that were further subdivided between sounds conveying a socio-functional context and typically cuing a responsive action by the listener (e.g. a ringing telephone) and those that are not linked to such a context and do not typically elicit responsive actions (e.g. notes on a piano). This distinction was validated psychophysically by a separate cohort of listeners. Beginning approximately 300 ms, responses to such context-related sounds significantly differed from context-free sounds both in the strength and topography of the electric field. This latency is >200 ms subsequent to general categorical discrimination. Additionally, such topographic differences indicate that sounds of different action sub-types engage distinct configurations of intracranial generators. Statistical analysis of source estimations identified differential activity within premotor and inferior (pre)frontal regions (Brodmann's areas (BA) 6, BA8, and BA45/46/47) in response to sounds of actions typically cuing a responsive action. We discuss our results in terms of a spatio-temporal model of auditory object processing and the interplay between semantic and action representations.

Iowa Prison Population Forecast FY 2004-2014

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2005-2015

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2006-2016

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2007-2017

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2008-2018

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2009-2019

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2010-2020

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Iowa Prison Population Forecast FY 2011-2021

CJJP takes a look at the forecast of inmates population in the state of Iowa in a ten year period. Information was produced by Division of Criminal and Juvenile Justice Planning. This report was made possible partially through funding from the U.S. Department of Justice, Bureau of Justice Statistics and its program for State Statistical Analysis Centers. Points of view or opinions expressed in this report are those of the Division of Criminal and Juvenile Justice Planning (CJJP), and do not necessarily reflect official positions of the U.S. Department of Justice.

Ultrastructural changes of the internal limiting membrane removed during indocyanine green assisted peeling versus conventional surgery for idiopathic macular epiretinal membrane.

PURPOSE: To evaluate the histologic features of cellular retinal fragments on the internal limiting membrane (ILM) removed during idiopathic macular epiretinal membrane (MEM) peeling surgery with and without the aid of indocyanine green (ICG) diluted in 5% glucose. METHODS: ILM specimens removed from 88 eyes during idiopathic MEM surgery between 1995 and 2003 were reviewed retrospectively. Histologic analysis focused on the presence and characteristics of retinal fragments on the retinal surface of the ILM. Statistical analysis compared the results between group I (conventional surgery) and group II (ICG-assisted peeling). RESULTS: Seventy-one eyes underwent MEM surgery without the aid of ICG (group I) and seventeen underwent MEM ICG-assisted surgery (group II). The amount of Müller cell debris on the retinal surface of the ILM was more significant in the group I than in the group II (40.8 vs. 11.8; P = 0.024). Large fragments of Müller cells were more frequently observed in the group I (no ICG) than in the group II (ICG) (63.4 vs. 23.5%; P = 0.003). CONCLUSIONS: The use of ICG diluted with 5% glucose in ILM removal during MEM surgery was associated with less retinal debris attached to the retinal face of the ILM compared with surgery in which ICG was not used.

Evaluating Roadway Subsurface Drainage Practices, 2013

The bearing capacity and service life of a pavement is affected adversely by the presence of undrained water in the pavement layers. In cold winter climates like in Iowa, this problem is magnified further by the risk of frost damage when water is present. Therefore, well-performing subsurface drainage systems form an important aspect of pavement design by the Iowa Department of Transportation (DOT). However, controversial findings are also reported in the literature regarding the benefits of subsurface drainage. The goal of this research was not to investigate whether subdrains are needed in Iowa pavements, but to conduct an extensive performance review of primary interstate pavement subdrains in Iowa, determine the cause of the problem if there are drains that are not functioning properly, and investigate the effect of poor subdrain performance due to improper design, construction, and maintenance on pavement surface distresses, if any. An extensive literature review was performed covering national-level and state-level research studies mainly focusing on the effects of subsurface drainage on performance of asphalt and concrete pavements. Several studies concerning the effects of a recycled portland cement concrete (RPCC) subbase on PCC pavement drainage systems were also reviewed. A detailed forensic test plan was developed in consultation with the project technical advisory committee (TAC) for inspecting and evaluating the Iowa pavement subdrains. Field investigations were conducted on 64 selected (jointed plain concrete pavement/JPCP and hot-mix asphalt/HMA) pavement sites during the fall season of 2012 and were mainly focused on the drainage outlet conditions. Statistical analysis was conducted on the compiled data from field investigations to further investigate the effect of drainage on pavement performance. Most Iowa subsurface drainage system outlet blockage is due to tufa, sediment, and soil. Although higher blockage rates reduce the flow rate of water inside outlet pipes, it does not always stop water flowing from inside the outlet pipe to outside the outlet pipe unless the outlet is completely blocked. Few pavement surface distresses were observed near blocked subsurface drainage outlet spots. More shoulder distresses (shoulder drop or cracking) were observed near blocked drainage outlet spots compared to open ones. Both field observations and limited performance analysis indicate that drainage outlet conditions do not have a significant effect on pavement performance. The use of RPCC subbase in PCC pavements results in tufa formation, a primary cause of drainage outlet blockage in JPCP. Several useful recommendations to potentially improve Iowa subdrain performance, which warrant detailed field investigations, were made

Evaluating Roadway Subsurface Drainage Practices: Tech Transfer Summary, 2013.

The bearing capacity and service life of a pavement is affected adversely by the presence of undrained water in the pavement layers. In cold winter climates like in Iowa, this problem is magnified further by the risk of frost damage when water is present. Therefore, well-performing subsurface drainage systems form an important aspect of pavement design by the Iowa Department of Transportation (DOT). However, controversial findings are also reported in the literature regarding the benefits of subsurface drainage. The goal of this research was not to investigate whether subdrains are needed in Iowa pavements, but to conduct an extensive performance review of primary interstate pavement subdrains in Iowa, determine the cause of the problem if there are drains that are not functioning properly, and investigate the effect of poor subdrain performance due to improper design, construction, and maintenance on pavement surface distresses, if any. An extensive literature review was performed covering national-level and state-level research studies mainly focusing on the effects of subsurface drainage on performance of asphalt and concrete pavements. Several studies concerning the effects of a recycled portland cement concrete (RPCC) subbase on PCC pavement drainage systems were also reviewed. A detailed forensic test plan was developed in consultation with the project technical advisory committee (TAC) for inspecting and evaluating the Iowa pavement subdrains. Field investigations were conducted on 64 selected (jointed plain concrete pavement/JPCP and hot-mix asphalt/HMA) pavement sites during the fall season of 2012 and were mainly focused on the drainage outlet conditions. Statistical analysis was conducted on the compiled data from field investigations to further investigate the effect of drainage on pavement performance. Most Iowa subsurface drainage system outlet blockage is due to tufa, sediment, and soil. Although higher blockage rates reduce the flow rate of water inside outlet pipes, it does not always stop water flowing from inside the outlet pipe to outside the outlet pipe unless the outlet is completely blocked. Few pavement surface distresses were observed near blocked subsurface drainage outlet spots. More shoulder distresses (shoulder drop or cracking) were observed near blocked drainage outlet spots compared to open ones. Both field observations and limited performance analysis indicate that drainage outlet conditions do not have a significant effect on pavement performance. The use of RPCC subbase in PCC pavements results in tufa formation, a primary cause of drainage outlet blockage in JPCP. Several useful recommendations to potentially improve Iowa subdrain performance, which warrant detailed field investigations, were made.

Evaluation of Bias in the Hamburg Wheel Tracking Device, RB00-010, 2013

As the list of states adopting the HWTD continues to grow, there is a need to evaluate how results are utilized. AASHTO T 324 does not standardize the analysis and reporting of test results. Furthermore, processing and reporting of the results among manufacturers is not uniform. This is partly due to the variation among agency reporting requirements. Some include only the midpoint rut depth, while others include the average across the entire length of the wheel track. To eliminate bias in reporting, statistical analysis was performed on over 150 test runs on gyratory specimens. Measurement location was found to be a source of significant variation in the HWTD. This is likely due to the nonuniform wheel speed across the specimen, geometry of the specimen, and air void profile. Eliminating this source of bias when reporting results is feasible though is dependent upon the average rut depth at the final pass. When reporting rut depth at the final pass, it is suggested for poor performing samples to average measurement locations near the interface of the adjoining gyratory specimens. This is necessary due to the wheel lipping on the mold. For all other samples it is reasonable to only eliminate the 3 locations furthest from the gear house. For multi‐wheel units, wheel side was also found to be significant for poor and good performing samples. After eliminating the suggested measurements from the analysis, the wheel was no longer a significant source of variation.

Human papilloma virus type and recurrence rate after surgical clearance of anal condylomata acuminata.

BACKGROUND: Anal condylomata acuminata (ACA) are caused by human papilloma virus (HPV) infection which is transmitted by close physical and sexual contact. The result of surgical treatment of ACA has an overall success rate of 71% to 93%, with a recurrence rate between 4% and 29%. The aim of this study was to assess a possible association between HPV type and ACA recurrence after surgical treatment. METHODS: We performed a retrospective analysis of 140 consecutive patients who underwent surgery for ACA from January 1990 to December 2005 at our tertiary University Hospital. We confirmed ACA by histopathological analysis and determined the HPV typing using the polymerase chain reaction. Patients gave consent for HPV testing and completed a questionnaire. We looked at the association of ACA, HPV typing, and HIV disease. We used chi, the Monte Carlo simulation, and Wilcoxon tests for statistical analysis. RESULTS: Among the 140 patients (123 M/17 F), HPV 6 and 11 were the most frequently encountered viruses (51% and 28%, respectively). Recurrence occurred in 35 (25%) patients. HPV 11 was present in 19 (41%) of these recurrences, which is statistically significant, when compared with other HPVs. There was no significant difference between recurrence rates in the 33 (24%) HIV-positive and the HIV-negative patients. CONCLUSIONS: HPV 11 is associated with higher recurrence rate of ACA. This makes routine clinical HPV typing questionable. Follow-up is required to identify recurrence and to treat it early, especially if HPV 11 has been identified.

TAMANHO AMOSTRAL ENVOLVENDO MÚLTIPLOS CARACTERES: UMA APLICAÇÃO À DIGESTIBILIDADE EM BOVINOS

O objetivo deste trabalho foi estimar o tamanho amostral mínimo (n) para comparar tratamentos em experimentos de consumo e de digestibilidade com bovinos, envolvendo múltiplos caracteres. Foram utilizados dados de digestibilidade de 72 novilhas com média de 18 meses de idade e 250 kg de peso. O experimento foi realizado na Embrapa-Centro de Pesquisa de Pecuária do Sudeste, São Carlos, SP, de 1988 a 1989, em delineamento inteiramente casualizado, com nove tratamentos organizados em esquema fatorial 3 x 3 (três grupos genéticos: Canchim, ½ Canchim + ½ Nelore e Nelore, e três níveis de proteína bruta: 6, 10 e 13%, com oito repetições cada, sendo a unidade experimental a novilha). Foram analisados consumo de ração (g/kg0,75) por quilograma de peso metabólico, energia digestível, nitrogênio retido (NR), NR (mg/kg0,75) e digestibilidades da matéria seca, proteína bruta, fibra em detergente neutro e fibra em detergente ácido. O valor mínimo de n, que permite detectar diferenças significativas (delta) entre vetores de médias de tratamentos, foi obtido por meio de um programa SAS (Statistical Analysis System), considerando modelo de distribuição normal t-variada, média zero e matriz de covariância sigma, estatística T² de Hotelling, distribuição F com parâmetro de não centralidade (d²D), erros do tipo I (alfa), poder do teste (1 beta) e delta. O valor de n variou de 6 a 47, sendo mais influenciado por alteração nos valores de delta, do que nos valores de alfa e poder do teste.