85 research outputs found
Investigating physiological glucose excursions before, during, and after Ramadan in adults without diabetes mellitus
Get PDFAIM: The study aimed to investigate physiological effects of Ramadan fasting on continuously monitored glucose levels in relation to Ramadan in young non-diabetic adults.METHODS: Continuous glucose monitoring was employed to measure interstitial glucose for several days 1-2weeks before Ramadan, in the middle of Ramadan, and 4-6weeks after Ramadan to assess glucose exposure and glucose variability.RESULTS: A total of 34,182 accurate glucose sensor readings and 438 capillary blood glucose values [mean absolute difference median (interquartile range) 8.5 (6.9-11.1)%] were obtained from 18 non-diabetic adults [13 females; aged 24 (21-27) years; baseline body mass index 23.9 (20.6-28.9) kg/m2]. The continuous glucose monitoring profiles showed an increase in the hyperglycemic (above 140mg/dL) area under the curve after Ramadan compared to both before (P=0.004) and during Ramadan (P=0.003), along with an increased glucose variability after Ramadan (P=0.014). Both the area under the interstitial glucose concentration curve for the entire day and the average glucose were positively associated with body mass index during (P=0.004 and P=0.005, respectively) and after Ramadan (P=0.013 and P=0.01, respectively). Atypical continuous glucose patterns were recognized in 11% of subjects, distinguished by a prolonged increased glucose exposure, particularly in response to a meal.CONCLUSION: The time-point 4-6weeks after Ramadan was distinguished by greater glucose exposure and wider glucose variability that may reflect ongoing changes in insulin sensitivity in response to altering lifestyle patterns in non-diabetic young adults across the spectrum of body weight.</p
Predetermined Anti-Diabetic Drug Regimen Adjustments during Ramadan Fasting: An Observational Study of Safety
No full textBackgroundMany Muslim type 2 diabetes mellitus (T2DM) patients choose to fast the month of Ramadan despite the possible adverse health effects brought about by the change in dietary habits, among other things. Clinical data regarding the safety of multi-drug regimens during fasting are particularly scarce. The aim of the study was to evaluate the safety of a drug protocol devised by the authors to accommodate Ramadan's dietary changes, involving dose adjustments of four anti-diabetic drug regimens in T2DM patients fasting Ramadan.MethodsIn this prospective, observational, open-label study, 301 T2DM patients who wished to fast Ramadan were followed during Ramadan and the preceding month. The incidence of hypoglycemia, diabetic ketoacidosis (DKA) and non-ketotic hyperosmolar state (NKHS) was monitored. Patients were classified into four groups: A group (those taking metformin, sulfonylurea and insulin [n=33]); B group (metformin and sulfonylurea [n=89]); C group (metformin and insulin [n=96]); and D group (premixed 70/30, glargine or regular insulin [n=82]). During Ramadan, drug doses were adjusted as percentages of their pre-Ramadan values: 75% for sulfonylureas, 75% for glargine, 75% for premixed insulin 70/30 in two doses, and 75% for regular insulin. Metformin was adjusted to a twice-daily regimen.ResultsNo cases of DKA or NKHS were reported. Hypoglycemia occurred at a lower rate than pre-Ramadan values in groups C, and D; and a similar rate in groups A, and B.ConclusionThe data suggested that using the above protocol to adjust the doses of anti-diabetic drugs is safe in T2DM patients in regards to hypoglycemia, DKA, and NKHS
Multilingual dataset of COVID tweets for relation-level metaphor analysis TCMeta 1.0
No full textTCMeta is a dataset of noun phrase constructions from COVID-related tweets, annotated for relation-level metaphor.
It contains 2,138 Slovene and 2,221 English instances in tab-separated tabular format .tsv, where each line presents a unique phrase under consideration, extracted from a COVID-related tweet. The primary annotations include the COVID metaphor label (whether the phrase expresses a metaphor relating to COVID), but also additional ones for idioms, metaphors not relating to COVID, or metaphors not evident on the relation-level.
The complete user tweet could not be published due to the ToS of the then Twitter platform. We recommend retrieving the text of the tweets via their IDs using the Hydrator tool [https://github.com/docnow/hydrator] or similar.
The dataset is further described in:
Brglez, M., Zayed, O. & Buitelaar, P. TCMeta: a multilingual dataset of COVID tweets for relation-level metaphor analysis. Lang Resources & Evaluation 59, 437–475 (2025). https://doi.org/10.1007/s10579-024-09725-z.
@article{brglez2025tcmeta,
title={{TCMeta}: a multilingual dataset of {COVID} tweets for relation-level metaphor analysis},
author={Brglez, Mojca and Zayed, Omnia and Buitelaar, Paul},
journal={Language Resources and Evaluation},
pages={437--475},
volume={59},
year={2025},
publisher={Springer},
doi = {10.1007/s10579-024-09725-z}
Cooperation without consensus: national discussions and local implementation in general education reform, 1930–1960
Get PDFThis study explores the general education movement of 1930-1960—a movement devoted to revising the content, and methods, of reforming the first two years of postsecondary study for undergraduates. It begins by noting that much of the extant literature focuses on the curricular statements produced by Harvard, Columbia, and the University of Chicago as well as their assumed influence upon other institutions of higher learning—including historically black colleges and universities, women’s colleges, religiously affiliated colleges, land grants, and community colleges—during this time period. This study complicates this reading of the movement by arguing that the curricular statements of Harvard, Columbia, and the University of Chicago were unable to achieve curricular reform on their respective campuses and were deemed to be unacceptable by institutions across the nation. The study asks, then, if the curricular theories of these prestigious universities were unable to create and/or sustain a fixed body of curricular content on their own campuses, is it likely that they influenced the curriculums of other institutions across the country? And more important, if the curricular structures in place at these institutions were constantly evolving—driven by faculty and student concerns, local context, the politics of curricular compromise, and not representing a linear, top-down method of reform—what method of reform did these universities and other institutions of higher learning look to, for achieving tangible and sustainable mechanisms of reform?
This study then offers a new way of seeing curricular reform in the general education movement by relying on the lenses provided by an exploration of three cooperative studies of general education—or studies funded by philanthropic groups in which a number of institutions and their representatives cooperate with each other and educational researchers to spur reform of their own curricular measures. The three cooperative studies of general education focused on are the Eight-Year Study (1930-1942); the Cooperative Study in General Education (1938-1947), and the California Study of General Education in the Junior College (1948-1952).
Using insights from an extensive exploration of the cooperative studies, this study argues that reform in the general education movement operated in a “matrix of influence” that involved educational research, philanthropy, and (both inter- and intra-) institutional “cooperation without consensus,” rather than a top-down channeling of reform from prestigious institutions. Further, this led to a cyclical and iterative interplay between national discussions and local implementation that changed both the content of general education and the methods of its constant reform. These processes shaped the way people talked about, implemented, and executed general education measures on their campuses. Through these processes, words became ideas, and ideas eventually became curricular structures implemented at the most basic levels. These reforms were almost always sensitive to local context and were often advertised to the public as being politically, economically, socially, and culturally expedient and relevant.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-12-01The student, Kevin Zayed, accepted the attached license on 2016-11-29 at 11:18.The student, Kevin Zayed, submitted this Dissertation for approval on 2016-11-29 at 11:24.This Dissertation was approved for publication on 2016-11-30 at 13:30.DSpace SAF Submission Ingestion Package generated from Vireo submission #10348 on 2017-02-28 at 14:42:27Made available in DSpace on 2017-03-01T17:01:44Z (GMT). No. of bitstreams: 3
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Breathable Cities: Dynamic Machine Learning Modelling Approaches for Advanced Air Pollution Control
Get PDFData Availability Statement: The data that support the findings of this study are available from the corresponding author, M.A., upon reasonable request.first_pageDownload PDFsettingsOrder Article Reprints
Open AccessArticle
Breathable Cities: Dynamic Machine Learning Modelling Approaches for Advanced Air Pollution Control
by Roba Zayed andMaysam Abbod *ORCID
Department of Electronic and Electrical Engineering, Brunel University London, London UB8 3PH, UK
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(13), 5581; https://doi.org/10.3390/app14135581
Submission received: 20 May 2024 / Revised: 19 June 2024 / Accepted: 24 June 2024 / Published: 27 June 2024
(This article belongs to the Special Issue Air Quality Prediction Based on Machine Learning Algorithms II)
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Abstract
This paper discusses air quality index (AQI) representation using a fuzzy logic framework to cover the blurry areas of AQI where indices are in between ranges of values. After studying several standards for air quality prediction (AQP), this research suggested the use of fuzzy logic as an extended method to cover some limitations found in several standards, in which the fuzzy logic represents a more dynamic way to support cross-country comparisons as well. This research expanded upon the United States Environmental Protection Agency (USEPA) standards to address their acknowledged limitations by constructing a fuzzy air quality levels prediction (FAQLP) model, which categorizes air quality into corresponding ranges (actual levels) and classifies new fuzzy levels (predicted levels), using a fuzzy logic model (to enforce more realistic predictions). This model can solve the issue of values at or near boundaries when there is uncertainty about air quality levels. The study aims to incorporate a comparative study of two urban settings providing dynamic machine-learning modeling approaches for advanced air pollution control. The DNN–Markov model is presented in this paper as the selected hybrid model for AQI prediction, and the adaptive neuro-fuzzy inference system (ANFIS) was used to represent AQI. This work presents a novel air quality index framework that consists of a DNN–Markov model for accurate hourly predictions and air quality level representations using ANFIS.This research received no external funding. The APC was funded by Brunel University London
Restoration of Blurred and Noisy Images Using Inverse Filtering and Adaptive Threshold Method
Get PDFA restoration scheme for images that are corrupted with both blur and impulsive noise is proposed in this paper to reconstruct an image with minimum degradation. The restoration scheme consists of two stages in sequence where the first stage is applied to the blurred image and the second stage is applied to de-blurred image that has been subject to noise through electronic transmission. The first stage uses frequency domain filtering while the second utilizes spatial filtering to reduce the indicated blur and noise, respectively. In particular, truncated inverse filtering is used for reducing the blur and an adaptive algorithm with an estimated threshold is used for minimizing the noise. Simulation of the introduced method uses several performance measuring indices such as mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results of these simulations show great performance of the proposed method in terms of reducing the blur and noise significantly while keeping details and sharpness of the image edges
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