57 research outputs found
sj-docx-1-cat-10.1177_10760296231191123 - Supplemental material for Thromboprophylaxis in Hospitalized Non-Critically Ill Patients With Mild-to-Moderate COVID-19 Infection: A Systematic Review and Meta-Analysis
No full textSupplemental material, sj-docx-1-cat-10.1177_10760296231191123 for Thromboprophylaxis in Hospitalized Non-Critically Ill Patients With Mild-to-Moderate COVID-19 Infection: A Systematic Review
and Meta-Analysis by Awatif Hafiz, Hadeel Alkofide, Khalid Al Sulaiman, Hala Joharji, Sarah Aljohani, Khadijah A. Sarkhi, Reem Alharbi, Ghazwa B. Korayem, Mashael AlFaifi, Samiah Alsohimi and Ohoud Aljuhani in Clinical and Applied Thrombosis/Hemostasis</p
Mechanical Footstep power generator
No full textMechanical Footstep Power generator
By Author: Mohammed Aljohani
Abstract
Modern technology is focusing on newer and better sources of energy. Among the important areas are power generation methods since electricity has become part of our lives. Various researchers have conducted surveys to find out the feasibility of converting renewable kinetic energy into electricity. Some of the works done in the past emphasized the selection of suitable materials and power generation systems designs that appear complicated and expensive. To ensure there is cost efficiency and energy efficiency better power generation systems need to be embraced.
The footstep power generator is a system that utilizes the energy from people movement and transforms this movement into electricity. The system is efficient in the conversion of kinetic energy to electrical energy through placement of mechanical footstep power generator on the hind of footpaths. This project entails the conversion of the kinetic energy to electrical energy. The control mechanism carries the rack & pinion, D.C generator, battery and inverter control. The generator provides a simple and low-cost electricity production.
The mechanical footstep generator produces 1.56 kW for one down and up cycle without causing pollution which is an added advantage over other systems. Mechanical footstep power generator produces power on small scale therefore; the power generated applies to low power consuming gadgets. For instance, it can be used in lighting and running low power consuming devices.
Keywords: , ,
Hospitalization Endpoint in Clinical Trials of Outpatient Settings: using Anti-SARS-COV-2 Therapy as an Example
No full textAlhanouf Yousef Alnafisah,1 Ahmed Fawaz Alkhalidi,1 Hanin Aljohani,1 Manal Almutairi,1 Adel Alharf,2 Hadeel Alkofide3 1Efficacy and Safety Evaluation Department, Benefit and Risk Evaluation Directorate, Saudi Food and Drug Authority (SFDA), Riyadh, Saudi Arabia; 2Drug Sector, Saudi Food and Drug Authority (SFDA), Riyadh, Saudi Arabia; 3Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi ArabiaCorrespondence: Ahmed Fawaz Alkhalidi, Efficacy and Safety Evaluation Department, Benefit and Risk Evaluation Directorate, SFDA, Riyadh, 5163, Saudi Arabia, Tel +966555546169, Email [email protected]: In response to the COVID-19 pandemic, the World Health Organization (WHO) developed a set of outcome measures for trials primarily aimed at hospitalised patients. However, a gap exists in defining outcome standards for non-hospitalised patients. Therefore, this study aims to discuss hospitalisation as a primary outcome in outpatient trials and its potential pitfalls, specifically focusing on trials related to anti-SARS-COV-2 therapy.Methods: In this narrative review, researchers thoroughly searched MEDLINE and ClinicalTrials.gov from January 2020 to December 2022, targeting Phase III randomized controlled trials involving outpatients with mild-to-moderate COVID-19. The trials were specifically related to anti-SARS-COV-2 monoclonal antibodies or antiviral agents. The study collected essential data, including the type of intervention, comparator, primary objective, primary endpoint, and the use of estimands in the trial.Results: The search identified 12 trials that evaluated the efficacy of anti-SARS COV-2 therapies in a predefined population. Three studies used hospitalisation and death as primary endpoints in high-risk patients receiving monoclonal antibodies. Nine studies assessed the efficacy of several antiviral agents: four trials used hospitalisation and death as the main endpoints, while others used different measures such as virologic measures using the Reverse Transcription-Polymerase Chain Reaction test (RT-PCR), the eight-point WHO ordinal scale, symptom alleviation by Day 7 and time to clinical response.Conclusion: Choosing hospitalization as an endpoint may provide meaningful data such as the cost-effectiveness ratio of a drug. However, different hospital utilisation patterns and investigator decisions could bias clinical outcomes if no specific criteria are considered. Therefore, investigators should have clear criteria for determining variables that influence this measure.Keywords: COVID-19, outcome measures, non-hospitalized patients, monoclonal antibodies, antiviral agent
A study of the impact of tourism on the environment and Jeddah citizen's perceptions toward tourism in Jeddah, Saudi Arabia, 2018
No full textThis study examined the impact of tourism on the environment and Jeddah citizens perceptions toward tourism in Jeddah, Saudi Arabia. The sample consisted of citizens who reside in the city of Jeddah. The variables analyzed included the following: cleanliness of the city, crowding, access to facilities, availability of water, and the quality of air and sea. An explanatory research design was utilized to generate the study, and purposive sampling was employed to gather the analysis. A total of 115 participants participated in the study. The study results suggested that cleanliness of the city, crowding, access to facilities, availability of water, and the quality of air and sea affect the perception of Jeddah citizens toward tourism. Particularly, both crowding and quality of air and sea were significant predictors of perceptions toward tourism. KEY TERMS: Tourism in Jedda, tourism environmental impact, environmental factors, Jeddah citizen's Perceptions., Environmental Policy, Infrastructure, Social Policy, Social Work, Transportation, Urban Studies and Plannin
Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations
No full textMassive Open Online Courses (MOOCs) have become universal learning resources, and the COVID-19 pandemic is rendering these platforms even more necessary. In this paper, we seek to improve Learner Profiling (LP), i.e. estimating the demographic characteristics of learners in MOOC platforms. We have focused on examining models which show promise elsewhere, but were never examined in the LP area (deep learning models) based on effective textual representations. As LP characteristics, we predict here the employment status of learners. We compare sequential and parallel ensemble deep learning architectures based on Convolutional Neural Networks and Recurrent Neural Networks, obtaining an average high accuracy of 96.3% for our best method. Next, we predict the gender of learners based on syntactic knowledge from the text. We compare different tree-structured Long-Short-Term Memory models (as state-of-the-art candidates) and provide our novel version of a Bi-directional composition function for existing architectures. In addition, we evaluate 18 different combinations of word-level encoding and sentence-level encoding functions. Based on these results, we show that our Bi-directional model outperforms all other models and the highest accuracy result among our models is the one based on the combination of FeedForward Neural Network and the Stack-augmented Parser-Interpreter Neural Network (82.60% prediction accuracy). We argue that our prediction models recommended for both demographics characteristics examined in this study can achieve high accuracy. This is additionally also the first time a sound methodological approach toward improving accuracy for learner demographics classification on MOOCs was proposed
Predicting Learners' Demographics Characteristics: Deep Learning Ensemble Architecture for Learners' Characteristics Prediction in MOOCs
No full textAuthor Profiling (AP), which aims to predict an author's demographics characteristics automatically by using texts written by the author, is an important mechanism for many applications, as well as highly challenging. In this research, we analyse various previous machine learning models for AP, with respect to their potential for our research problem. Based on this, we propose a Deep Learning Architecture to predict the demographics characteristics of the learners in MOOCs, incorporating multi-feature representations and ensemble learning methods. Specifically, we employ a novel pipeline, combining the most successful deep learning classifiers, Convolution Neural Networks, Recurrent Neural Networks and Recursive Neural Networks, to learn from a text. Moreover, beside the state-of-the-art training involving character and word-level input, we additionally propose phrase-level input. With this approach, we aim at deepening our understanding of the writing style of learners, and thus, predict the author profile with high accuracy. In this paper, we propose the model and architecture, and report on initial tests of our model on a large dataset from the FutureLearn platform, to predict the demographics characteristics of the learners
Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification
No full textMassive Open Online Courses (MOOCs) have become universal learning resources, and the COVID-19 pandemic is rendering these platforms even more necessary. These platforms also bring incredible diversity of learners in terms of their traits. A research area called Author Profiling (AP in general; here, Learner Profiling (LP)), is to identify such traits about learners, which is vital in MOOCs for, e.g., preventing plagiarism, or eligibility for course certification. Identifying a learner’s trait in a MOOC is notoriously hard to do from textual content alone. We argue that to predict a learner’s academic level, we need to also be using other features stemming from MOOC platforms, such as derived from learners’ actions on the platform. In this study, we specifically examine time stamps, quizzes, and discussions. Our novel approach for the task achieves a high accuracy (90% in average) even with a simple shallow classifier, irrespective of data size, outperforming the state of the art
Orientalism in Children’s Literature: Representations of Egyptian and Jordanian Families in Elsa Marston’s Stories
No full textChildren’s literature plays a significant role in people’s lives. For children and young adults, a story is a discursive space where they find answers, solutions, and ideas. Contrastingly, to adult writers, it is a space dedicated to promoting ideological beliefs and values to young readers. Thus, this study attempts to investigate the problematic representation of Arab city and village families found in two children stories written by American author Elsa Marston (1933-2017). She classifies families into two opposing extremes; the civilized city families and the poor, conservative village families. Using Edward Said’s Orientalist discourse analysis, alongside David Spurr’s rhetorical trope of Classification, the researcher explores how and why Jordanian and Egyptian families are classified with disregard to cultural differences. The analysis reveals that Arab families, both Jordanian and Egyptian, are equally classified based on education, social class, and culture. City families are viewed as developed due to their interaction with the west, whereas village families are portrayed as ignorant and uncivilized for their lack of communication with the west. The analysis also detects the author’s negative attitude towards village families
Stacking interactions in indomethacin solid-state forms
No full textStacked structures with strong dispersion forces between stack neighbors often lead to anisotropic crystal growth and needlelike morphologies. The crystal structures of a new cocrystal and a molecular salt of indomethacin (IND) are reported: IND·MOA and IND·POBA·0.5H2O (MOA = p-methoxyaniline, POBA = 4-phenoxybenzylamine). In both structures, the IND and coformer molecules/ions are stacked and IND adopts the unusual conformation found in the α-polymorph of pure IND, resulting in a relatively short distance of about 3 Å between the methyl group and the C1′-atom of the chlorophenyl ring. While IND·MOA and IND·POBA·0.5H2O both crystallize as needles like α-IND, the weaker stacking interactions of the coformer in the IND·MOA cocrystal lead to shorter and thicker needles. Amorphous IND prepared by milling recrystallizes to the stable γ-polymorph without the metastable α-form being detected. When IND is milled in the presence of 2.5 wt % MOA, the amorphous phase converts to α-IND. The effect of small amounts of the coformer on the recrystallization route is attributed to a templating effect of the cocrystal formed during milling and/or the facilitation of the conversion to the α-phase conformation.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) and is cofunded under the European Regional Development Fund under Grant Number 12/RC/2275-P2. N.F. thanks the Irish Research Council for a Government of Ireland Postgraduate Scholarship (Project ID GOIPG/2023/4906). M.A. acknowledges the King Fahd University of Petroleum and Minerals (KFUPM) for providing facilities for this research. For the purpose of Open Access, the author has applied a CC BY public copyright license to any author accepted manuscript version arising from this submission.peer-reviewe
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