148 research outputs found
Collaborating with youths as coteachers in literacy learning
The authors featured in this department column share instructional practices that support transformative literacy teaching and disrupt “struggling reader” and “struggling writer” labels.This work was supported by a Boston University Consortium grant and a Boston University School of Education Faculty Research Award. (Boston University Consortium; Boston University School of Education Faculty Research Award)Accepted manuscrip
Positioning adolescents in literacy teaching and learning
Secondary literacy instruction often happens to adolescents rather than with them. To disrupt this trend, we collaborated with 12th-grade “literacy mentors” to reimagine literacy teaching and learning with 10th-grade mentees in a public high school classroom. We used positioning theory as an analytic tool to (a) understand how mentors positioned themselves and how we positioned them and (b) examine the literacy practices that enabled and constrained the mentor position. We found that our positioning of mentors as collaborators was taken up in different and sometimes unexpected ways as a result of the multiple positions available to them and institutional-level factors that shaped what literacy practices were and were not negotiable. We argue that future collaborations with youth must account for the rights and duties of all members of a classroom community, including how those rights and duties intersect, merge, or come into conflict within and across practices.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a Faculty Research Award from the School of Education at Boston University. (Faculty Research Award from the School of Education at Boston University)Accepted manuscrip
Experimental Observations of Group Synchrony in a System of Chaotic Optoelectronic Oscillators
We experimentally demonstrate group synchrony in a network of four nonlinear
optoelectronic oscillators with time-delayed coupling. We divide the nodes into
two groups of two each, by giving each group different parameters and by
enabling only inter-group coupling. When coupled in this fashion, the two
groups display different dynamics, with no isochronal synchrony between them,
but the nodes in a single group are isochronally synchronized, even though
there is no intra-group coupling. We compare experimental behavior with
theoretical and numerical results
Complex Dynamics and Synchronization of Delayed-Feedback Nonlinear Oscillators
We describe a flexible and modular delayed-feedback nonlinear oscillator that
is capable of generating a wide range of dynamical behaviours, from periodic
oscillations to high-dimensional chaos. The oscillator uses electrooptic
modulation and fibre-optic transmission, with feedback and filtering
implemented through real-time digital-signal processing. We consider two such
oscillators that are coupled to one another, and we identify the conditions
under which they will synchronize. By examining the rates of divergence or
convergence between two coupled oscillators, we quantify the maximum Lyapunov
exponents or transverse Lyapunov exponents of the system, and we present an
experimental method to determine these rates that does not require a
mathematical model of the system. Finally, we demonstrate a new adaptive
control method that keeps two oscillators synchronized even when the coupling
between them is changing unpredictably.Comment: 24 pages, 13 figures. To appear in Phil. Trans. R. Soc. A (special
theme issue to accompany 2009 International Workshop on Delayed Complex
Systems
Underuse and Overuse of Colonoscopy for Repeat Screening and Surveillance in the Veterans Health Administration
Regular screening with colonoscopy lowers colorectal cancer incidence and mortality. We aimed to determine patterns of repeat and surveillance colonoscopy and identify factors associated with over- and underuse of colonoscopy
Post-Acute Sequelae of Covid-19 and Longitudinal antibody Levels in a Community-Based Cohort
BACKGROUND: Coronavirus disease 2019 (COVID-19) infection invokes variable immune responses and poses a risk of post-acute sequelae SARS-CoV-2 infection (PASC) symptoms; however, most data on natural history are derived from patients with severe infection. Further data are needed among patients with mild infection, who comprise most cases.
METHODS: The Dallas Fort-Worth (DFW) COVID-19 Prevalence Study included 21,597 community-dwelling adults (ages 18-89) who underwent COVID-19 PCR and anti-nucleocapsid antibody testing between July 2020 and March 2021. We invited participants with positive COVID-19 results (cases) and a subset with negative results (controls), matched on age, sex, race/ethnicity, and ZIP code, to complete a follow-up questionnaire for PASC symptoms and repeat anti-nucleocapsid testing, and anti-spike antibody testing between July and December 2021.
RESULTS: Of 3,917 adults invited to participate, 2260 (57.7%) completed the questionnaire- 1150 cases and 1110 controls. Persistent symptoms were reported in 21.1% of cases, with the most common being shortness of breath, fatigue, and loss of taste or smell. Among 292 cases with asymptomatic infection, \u3e15% reported new fatigue and 8-10% reported new loss of taste/smell, myalgias, or headache. Median anti-nucleocapsid levels in cases decreased from 3.5U to 0.7U over a median follow-up of 8.6 months. Anti-spike antibody levels at 6-7 months post-vaccination in cases were similar to that of controls.
CONCLUSIONS: More than 1 in 5 patients with COVID-19 infection, including those with mild infection, reported persistent symptoms during follow-up. Both nucleocapsid and spike protein antibody levels decreased within six months following a COVID-19 infection and vaccination
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Publisher Correction: An engineered human Fc domain that behaves like a pH-toggle switch for ultra-long circulation persistence.
An amendment to this paper has been published and can be accessed via a link at the top of the paper
Semantic text mining support for lignocellulose research
Biofuels produced from biomass are considered to be promising sustainable alternatives to fossil fuels. The conversion of lignocellulose into fermentable sugars for biofuels production requires the use of enzyme cocktails that can efficiently and economically hydrolyze lignocellulosic biomass. As many fungi naturally break down lignocellulose, the identification and characterization of the enzymes involved is a key challenge in the research and development of biomass-derived products and fuels. One approach to meeting this challenge is to mine the rapidly-expanding repertoire of microbial genomes for enzymes with the appropriate catalytic properties.
Semantic technologies, including natural language processing, ontologies, semantic Web services and Web-based collaboration tools, promise to support users in handling complex data, thereby facilitating knowledge-intensive tasks. An ongoing challenge is to select the appropriate technologies and combine them in a coherent system that brings measurable improvements to the users. We present our ongoing development of a semantic infrastructure in support of genomics-based lignocellulose research. Part of this effort is the automated curation of knowledge from information on fungal enzymes that is available in the literature and genome resources.
Working closely with fungal biology researchers who manually curate the existing literature, we developed ontological natural language processing pipelines integrated in a Web-based interface to assist them in two main tasks: mining the literature for relevant knowledge, and at the same time providing rich and semantically linked information
Population-Based Correlates of Covid-19 infection: an analysis From the Dfw Covid-19 Prevalence Study
BACKGROUND: COVID-19 has resulted in over 1 million deaths in the U.S. as of June 2022, with continued surges after vaccine availability. Information on related attitudes and behaviors are needed to inform public health strategies. We aimed to estimate the prevalence of COVID-19, risk factors of infection, and related attitudes and behaviors in a racially, ethnically, and socioeconomically diverse urban population.
METHODS: The DFW COVID-19 Prevalence Study Protocol 1 was conducted from July 2020 to March 2021 on a randomly selected sample of adults aged 18-89 years, living in Dallas or Tarrant Counties, Texas. Participants were asked to complete a 15-minute questionnaire and COVID-19 PCR and antibody testing. COVID-19 prevalence estimates were calculated with survey-weighted data.
RESULTS: Of 2969 adults who completed the questionnaire (7.4% weighted response), 1772 (53.9% weighted) completed COVID-19 testing. Overall, 11.5% of adults had evidence of COVID-19 infection, with a higher prevalence among Hispanic and non-Hispanic Black persons, essential workers, those in low-income neighborhoods, and those with lower education attainment compared to their counterparts. We observed differences in attitudes and behaviors by race and ethnicity, with non-Hispanic White persons being less likely to believe in the importance of mask wearing, and racial and ethnic minorities more likely to attend social gatherings.
CONCLUSION: Over 10% of an urban population was infected with COVID-19 early during the pandemic. Differences in attitudes and behaviors likely contribute to sociodemographic disparities in COVID-19 prevalence
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