International volunteers’ serving as teachers in rural indigenous schools in Ecuador: Challenges and opportunities for culturally relevant teaching

This ethnographic study is situated in the complexities and dilemmas of international aid education (IAE), the volunteer sector and cross-cultural learning and teaching. It examines the challenges and opportunities faced by three international volunteers (IVs) teaching in Indigenous communities in rural Ecuador. Through onsite observations and interviews, along with discussions with principal participants (IVs), and secondary participants (three local teachers and the volunteer program director), we present a narrative of the IVs experiences, pedagogical approaches and the factors which affect culturally relevant teaching (CRT) practices. This illustration serves as a platform for a cross-comparative analysis of key themes and issues related to CRT and anti-colonial education in the sphere of IAE. The paper concludes by identifying the implications of IAE may have on the local education and Indigenous knowledges and highlights issues and concerns that must be addressed so that anti-colonial CRT can occur within international cross-cultural contexts

Detection of gravitational waves in circular particle accelerators II. Response analysis and parameter estimation using synthetic data

We simulate the response of a Storage Ring Gravitational-wave Observatory (SRGO) to astrophysical gravitational waves (GWs), numerically obtaining its sensitivity curve, parameter degeneracies, and optimal choices of some controllable experiment parameters. We also generate synthetic noisy GW data and use Markov Chain Monte Carlo (MCMC) methods to perform parameter estimation of the source properties. With this, we show that a single SRGO could potentially localize the GW source in the sky using Earth's rotation. Then, we study the source sky localization area, mass and distance estimation errors as functions of noise, data sampling rate, and observing time. Finally, we discuss, along with its implications, the capacity of an SRGO to detect and constrain the parameters of millihertz (mHz) GW events.Comment: This manuscript is the sequel to Phys. Rev. D 102, 122006 (2020) or arXiv:2012.00529. This manuscript will be submitted for review and publication to Physical Review D (PRD). 21 pages, 10 figure

T cell immunity as a tool for studying epigenetic regulation of cellular differentiation

Cellular differentiation is regulated by the strict spatial and temporal control of gene expression. This is achieved, in part, by regulating changes in histone post-translational modifications (PTMs) and DNA methylation that in-turn, impact transcriptional activity. Further, histone PTMs and DNA methylation are often propagated faithfully at cell division (termed epigenetic propagation), and thus contribute to maintaining cellular identity in the absence of signals driving differentiation. Cardinal features of adaptive T cell immunity include the ability to differentiate in response to infection, resulting in acquisition of immune functions required for pathogen clearance; and the ability to maintain this functional capacity in the long-term, allowing more rapid and effective pathogen elimination following re-infection. These characteristics underpin vaccination strategies by effectively establishing a long-lived T cell population that contributes to an immunologically protective state (termed immunological memory). As we discuss in this review, epigenetic mechanisms provide attractive and powerful explanations for key aspects of T cell-mediated immunity - most obviously and notably, immunological memory, because of the capacity of epigenetic circuits to perpetuate cellular identities in the absence of the initial signals that drive differentiation. Indeed, T cell responses to infection are an ideal model system for studying how epigenetic factors shape cellular differentiation and development generally. This review will examine how epigenetic mechanisms regulate T cell function and differentiation, and how these model systems are providing general insights into the epigenetic regulation of gene transcription during cellular differentiation

ReoptSMART: A Learning Query Plan Cache

The task of query optimization in modern relational database systems is important but can be computationally expensive. Parametric query optimization(PQO) has as its goal the prediction of optimal query execution plans based on historical results, without consulting the query optimizer. We develop machine learning techniques that can accurately model the output of a query optimizer. Our algorithms handle non-linear boundaries in plan space and achieve high prediction accuracy even when a limited amount of data is available for training. We use both predicted and actual query execution times for learning, and are the first to demonstrate a total net win of a PQO method over a state-of-the-art query optimizer for some workloads. ReoptSMART realizes savings not only in optimization time, but also in query execution time, for an over-all improvement by more than an order of magnitude in some cases

Recognition of Famous Names Predicts Cognitive Decline in Healthy Elders

Objective: The ability to recognize familiar people is impaired in both Mild Cognitive Impairment (MCI) and Alzheimer’s Dementia (AD). In addition, both groups often demonstrate a time-limited temporal gradient (TG) in which well known people from decades earlier are better recalled than those learned recently. In this study, we examined the TG in cognitively intact elders for remote famous names (1950–1965) compared to more recent famous names (1995–2005). We hypothesized that the TG pattern on a famous name recognition task (FNRT) would predict future cognitive decline, and also show a significant correlation with hippocampal volume. Method: Seventy-eight healthy elders (ages 65–90) with age-appropriate cognitive functioning at baseline were administered a FNRT. Follow-up testing 18 months later produced two groups: Declining (≥ 1 SD reduction on at least one of three measures) and Stable (\u3c 1 SD). Results: The Declining group (N = 27) recognized fewer recent famous names than the Stable group (N = 51), although recognition for remote names was comparable. Baseline MRI volumes for both the left and right hippocampi were significantly smaller in the Declining group than the Stable group. Smaller baseline hippocampal volume was also significantly correlated with poorer performance for recent, but not remote famous names. Logistic regression analyses indicated that baseline TG performance was a significant predictor of group status (Declining vs. Stable) independent of chronological age and APOE ε4 inheritance. Conclusions: The TG for famous name recognition may serve as an early preclinical cognitive marker of cognitive decline in healthy older individual

Are We at Risk of Losing the Current Generation of Climate Researchers to Data Science?

Climate model output has progressively increased in size over the past decades and is expected to continue to rise in the future. Consequently, the research time expended by Early Career Researchers (ECRs) on data-intensive activities is displacing the time spent in fostering novel scientific ideas and expanding the frontiers of climate sciences. Here, we highlight an urgent need for a better balance between data-intensive and foundational climate science activities, more open-ended research opportunities that reinforce the scientific freedom of the ECRs, and strong coordinated action to provide infrastructure and resources to the ECRs working in under-resourced environments

Gradient Representations and Affine Structures in AE(n)

We study the indefinite Kac-Moody algebras AE(n), arising in the reduction of Einstein's theory from (n+1) space-time dimensions to one (time) dimension, and their distinguished maximal regular subalgebras sl(n) and affine A_{n-2}^{(1)}. The interplay between these two subalgebras is used, for n=3, to determine the commutation relations of the `gradient generators' within AE(3). The low level truncation of the geodesic sigma-model over the coset space AE(n)/K(AE(n)) is shown to map to a suitably truncated version of the SL(n)/SO(n) non-linear sigma-model resulting from the reduction Einstein's equations in (n+1) dimensions to (1+1) dimensions. A further truncation to diagonal solutions can be exploited to define a one-to-one correspondence between such solutions, and null geodesic trajectories on the infinite-dimensional coset space H/K(H), where H is the (extended) Heisenberg group, and K(H) its maximal compact subgroup. We clarify the relation between H and the corresponding subgroup of the Geroch group.Comment: 43 page

Non-inhibitory levels of oxygen during cultivation increase freeze-drying stress tolerance in Limosilactobacillus reuteri DSM 17938

The physiological effects of oxygen on Limosilactobacillus reuteri DSM 17938 during cultivation and the ensuing properties of the freeze-dried probiotic product was investigated. On-line flow cytometry and k-means clustering gating was used to follow growth and viability in real time during cultivation. The bacterium tolerated aeration at 500 ml/min, with a growth rate of 0.74 ± 0.13 h-1 which demonstrated that low levels of oxygen did not influence the growth kinetics of the bacterium. Modulation of the redox metabolism was, however, seen already at non-inhibitory oxygen levels by 1.5-fold higher production of acetate and 1.5-fold lower ethanol production. A significantly higher survival rate in the freeze-dried product was observed for cells cultivated in presence of oxygen compared to absence of oxygen (61.8 ± 2.4 % vs 11.5 ± 4.3 %), coinciding with a higher degree of unsaturated fatty acids (UFA:SFA ratio of 10 for air sparged vs 3.59 for N2 sparged conditions.). Oxygen also resulted in improved bile tolerance and boosted 5’nucleotidase activity (370 U/L vs 240 U/L in N2 sparged conditions) but lower tolerance to acidic conditions compared bacteria grown under complete anaerobic conditions which survived up to 90 min of exposure at pH 2. Overall, our results indicate the controlled supply of oxygen during production may be used as means for probiotic activity optimisation of L. reuteri DSM 17938

Expert Review of the MyCoast Application

Final Project for INST490: Integrated Capstone for Information Science (Spring 2021). University of Maryland, College Park.The MyCoast app is a mobile and web-based application used by the Maryland Department of Natural Resources to document and analyze pictures and data of flooding caused by precipitation and coastal events. The data it collects is used for various purposes, including visualizing impacts of flood events, as well as enhancing awareness of flood events among Maryland residents. This project’s goal was to create an expert review of the MyCoast application. Initially, the goal was to create wireframes and a new schema for the app. After discussion, the goal shifted to interviewing people with different backgrounds (who work in sector, peers, etc.) and creating a list of recommendations from our findings. This report reviews the MyCoast application and end-user feedback on app functionality and user experience, makes recommendations for improvements to the app and recommendations for improvements to end-user documentation to improve the user experience and data quality.Maryland Department of Natural Resource