From Page to Program: A Study of Stakeholders in Multimodal First-Year Composition Curriculum and Program Design

Much of the writing we do today, whether for class, work, or personal engagement, relies on some form of media. Whether a computer to draft assignments, or smartphones to post on social media, technology has solidified its presence within our everyday writing experiences. Over the past two decades, as media has asserted its role in spaces outside of the classroom, its intersection with education, and composition classrooms specifically, has become more pronounced. These intersections have required that writing scholars, teachers, and writing program administrators (WPAs) remain attentive to the changing shape and modalities of composition. Responses to this include a wealth of research on the impact of changing composing technologies, as well as shared Outcomes Statements and position papers that offer guidelines for how administrators and teachers might incorporate multimodality into their writing curricula and classrooms. While these statements offer the language of objectives and outcomes, what they don’t support is the practical reality of making multimodality happen. What is a WPA to do? My dissertation is a qualitative study of first-year composition curriculum and writing program design at five public research universities that argues for targeted engagement with key stakeholders to develop inclusive, multimodal curricula. My findings suggest that there are three primary stakeholders that WPAs must engage to enact multimodal curricula: undergraduate students, first-year composition teachers, institutional administrators. I present a model for engaging with each level of stakeholder that is adaptable across institutional contexts based on my findings. This model illustrates how WPAs might embrace multimodal curricula to support writing instruction for the twenty-first century across various stakeholder levels. I analyze the factors that enable or inhibit multimodal curricular design, and argue for WPAs to consider how remediation assignments better position students for multimodal transfer; to assess if and how their training programs intentionally reflect their programmatic curricular goals; and lastly, to mobilize their institutional mission statements to access resources and support

Use of an Alarm Bundle to Reduce Alarm Fatigue in the ICU: A Quality Improvement Project

Significance and Background: In the critical care setting, frequent false alarms can lead to sensory overload and delayed reactions to alarms (aka, alarm fatigue). Patients are at risk because overtime staff may ignore or become desensitized to all alarm sounds, even true ones. Purpose: The purpose of this QI project is to establish alarm management protocol in a 14-bed ICU. The goals were to reduce alarm fatigue and create a safe environment for patients and clinical staff. Methods: The Model of Improvement (IHI, 2023) with cycles of the Plan-Do-Study-Act (PDSA) was used to implement an alarm bundle checklist that included daily skin cleansing with soap, water and change of ECG electrodes. The QI project occurred over 12 weeks. Outcome measures were to see a decrease in false alarms, track adherence to the alarm bundle checklist, and see improvement in nursing perception of alarm fatigue in the ICU. Outcome: A total 1,544 cardiac rhythms were recorded based on atrial, ventricular, and false rhythms. The occurrence of false alarms prior to the alarm bundle checklist (weeks 1-6) was 44.3% (2) with a 2.3% reduction after the implementation of the alarm bundle checklist (weeks 7-12) at 42% (1). The alarm bundle adherence showed \u3e90% completion rate except for last week of the study, which decreased to 86%. Responses (n=24) to the 11-question nursing survey showed \u3e10% improvement by week 12 except for the question that directly asked about the occurrence of nuisance alarms, which did not change from baseline to end of study. Discussion: There was a reduction in cardiac false alarm rhythms after using the alarm management protocol. Having more PSDA cycles may lead to larger reduction and improve sustainability of the alarm management protocol

A fundamental residue pitch perception bias for tone language speakers

A complex tone composed of only higher-order harmonics typically elicits a pitch percept equivalent to the tone's missing fundamental frequency (f0). When judging the direction of residue pitch change between two such tones, however, listeners may have completely opposite perceptual experiences depending on whether they are biased to perceive changes based on the overall spectrum or the missing f0 (harmonic spacing). Individual differences in residue pitch change judgments are reliable and have been associated with musical experience and functional neuroanatomy. Tone languages put greater pitch processing demands on their speakers than non-tone languages, and we investigated whether these lifelong differences in linguistic pitch processing affect listeners' bias for residue pitch. We asked native tone language speakers and native English speakers to perform a pitch judgment task for two tones with missing fundamental frequencies. Given tone pairs with ambiguous pitch changes, listeners were asked to judge the direction of pitch change, where the direction of their response indicated whether they attended to the overall spectrum (exhibiting a spectral bias) or the missing f0 (exhibiting a fundamental bias). We found that tone language speakers are significantly more likely to perceive pitch changes based on the missing f0 than English speakers. These results suggest that tone-language speakers' privileged experience with linguistic pitch fundamentally tunes their basic auditory processing

Statistical adjustment for a measure of healthy lifestyle doesn't yield the truth about hormone therapy

The Women's Health Initiative randomized clinical trial of hormone therapy found no benefit of hormones in preventive cardiovascular disease, a finding in striking contrast with a large body of observational research. Understanding whether better methodology and/or statistical adjustment might have prevented the erroneous conclusions of observational research is important. This is a re-analysis of data from a case-control study examining the relationship of postmenopausal hormone therapy and the risks of myocardial infarction (MI) and ischemic stroke in which we reported no overall increase or decrease in the risk of either event. Variables measuring health behavior/lifestyle that are not likely to be causally with the risks of MI and stroke (e.g., sunscreen use) were included in multivariate analysis along with traditional confounders (age, hypertension, diabetes, smoking, body mass index, ethnicity, education, prior coronary heart disease for MI and prior stroke/TIA for stroke) to determine whether adjustment for the health behavior/lifestyle variables could reproduce or bring the results closer to the findings in a large and definitive randomized clinical trial of hormone therapy, the Women's Health Initiative. For both MI and stroke, measures of health behavior/lifestyle were associated with odds ratios (ORs) less than 1.0. Adjustment for traditional cardiovascular disease confounders did not alter the magnitude of the ORs for MI or stroke. Addition of a subset of these variables selected using stepwise regression to the final MI or stroke models along with the traditional cardiovascular disease confounders moved the ORs for estrogen and estrogen/progestin use closer to values observed in the Women Health Initiative clinical trial, but did not reliably reproduce the clinical trial results for these two endpoints.Comment: Published in at http://dx.doi.org/10.1214/193940307000000437 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Populismo, institutiones locales y democracia (provincia de Buenos Aires, 1945-1958)

La imagen de un peronismo centralizador y autoritario, aún hoy hegemónica en las ciencias sociales, es en buena medida un legado de los argumentos “desperonizantes” de la “Revolución Libertadora”. Estas interpretaciones han sido construidas desde una perspectiva tocquevilliana, asociando a priori las ideas de descentralización, activación de la sociedad civil y democracia. En este artículo retomaremos aquellas investigaciones que consideran a los populismos como fuerzas inclusivas y democratizantes, repensando las relaciones entre peronismo clásico e instituciones locales, una dimensión que ha sido poco analizada. En concreto, indagaremos en los cambios y continuidades que sufrieron los municipios y los Consejos Escolares de la Provincia de Buenos Aires antes y después del peronismo.The image of a centralizing and authoritarian Peronism, that is still hegemonic in social sciences, is largely a legacy of the arguments “desperonizantes” of the “Revolución Libertadora”. These interpretations have been built since Tocqueville’s view, combining a priori ideas of decentralization, civil society’s activation and democracy. In this article we use those investigations that consider populism as inclusive and democratizing forces. This helps us to rethink the relationship between classical Peronism and local institutions, a dimension that has been little discussed. Specifically, we investigate the changes and continuities that have suffered the municipal government and local school boards in the province of Buenos Aires before and after Peronism.Fil: Ferreyra, Silvana Gabriela. Universidad Nacional de Mar del Plata. Facultad de Humanidades. Departamento de Historia. Centro de Estudios Históricos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Petitti, Eva Mara. Universidad Nacional de Mar del Plata. Facultad de Humanidades. Departamento de Historia. Centro de Estudios Históricos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Deep neural networks for grape bunch segmentation in natural images from a consumer-grade camera

AbstractPrecision agriculture relies on the availability of accurate knowledge of crop phenotypic traits at the sub-field level. While visual inspection by human experts has been traditionally adopted for phenotyping estimations, sensors mounted on field vehicles are becoming valuable tools to increase accuracy on a narrower scale and reduce execution time and labor costs, as well. In this respect, automated processing of sensor data for accurate and reliable fruit detection and characterization is a major research challenge, especially when data consist of low-quality natural images. This paper investigates the use of deep learning frameworks for automated segmentation of grape bunches in color images from a consumer-grade RGB-D camera, placed on-board an agricultural vehicle. A comparative study, based on the estimation of two image segmentation metrics, i.e. the segmentation accuracy and the well-known Intersection over Union (IoU), is presented to estimate the performance of four pre-trained network architectures, namely the AlexNet, the GoogLeNet, the VGG16, and the VGG19. Furthermore, a novel strategy aimed at improving the segmentation of bunch pixels is proposed. It is based on an optimal threshold selection of the bunch probability maps, as an alternative to the conventional minimization of cross-entropy loss of mutually exclusive classes. Results obtained in field tests show that the proposed strategy improves the mean segmentation accuracy of the four deep neural networks in a range between 2.10 and 8.04%. Besides, the comparative study of the four networks demonstrates that the best performance is achieved by the VGG19, which reaches a mean segmentation accuracy on the bunch class of 80.58%, with IoU values for the bunch class of 45.64%