Search results for: statistical databases

Authors: Jui-Teng Liao

Abstract:

The selected-response (SR) format has been commonly adopted to assess academic reading in both formal and informal testing (i.e., standardized assessment and classroom assessment) because of its strengths in content validity, construct validity, as well as scoring objectivity and efficiency. When developing a second language (L2) reading test, researchers indicate that the longer the test (e.g., more test items) is, the higher reliability and validity the test is likely to produce. However, previous studies have not provided specific guidelines regarding the optimal length of a test or the most suitable number of test items or reading passages. Additionally, reading tests often include different question types (e.g., factual, vocabulary, inferential) that require varying degrees of reading comprehension and cognitive processes. Therefore, it is important to investigate the impact of question types on the number of items in relation to the score reliability of L2 reading tests. Given the popularity of the SR question format and its impact on assessment results on teaching and learning, it is necessary to investigate the degree to which such a question format can reliably measure learners’ L2 reading comprehension. The present study, therefore, adopted the generalizability (G) theory to investigate the score reliability of the SR format in L2 reading tests focusing on how many test items a reading test should include. Specifically, this study aimed to investigate the interaction between question types and the number of items, providing insights into the appropriate item count for different types of questions. G theory is a comprehensive statistical framework used for estimating the score reliability of tests and validating their results. Data were collected from 108 English as a second language student who completed an English reading test comprising factual, vocabulary, and inferential questions in the SR format. The computer program mGENOVA was utilized to analyze the data using multivariate designs (i.e., scenarios). Based on the results of G theory analyses, the findings indicated that the number of test items had a critical impact on the score reliability of an L2 reading test. Furthermore, the findings revealed that different types of reading questions required varying numbers of test items for reliable assessment of learners’ L2 reading proficiency. Further implications for teaching practice and classroom-based assessments are discussed.

Keywords: second language reading assessment, validity and reliability, Generalizability theory, Academic reading, Question format

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Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

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Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

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Authors: Iman Farasat, Howard M. Salis

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The CRISPR/Cas9 system has revolutionized genome engineering by enabling site-directed and high-throughput genome editing, genome insertion, and gene knockdowns in several species, including bacteria, yeast, flies, worms, and human cell lines. This technology has the potential to enable human gene therapy to treat genetic diseases and cancer at the molecular level; however, the current CRISPR/Cas9 system suffers from seemingly sporadic off-target genome mutagenesis that prevents its use in gene therapy. A comprehensive mechanistic model that explains how the CRISPR/Cas9 functions would enable the rational design of the guide-RNAs responsible for target site selection while minimizing unexpected genome mutagenesis. Here, we present the first quantitative model of the CRISPR/Cas9 genome mutagenesis system that predicts how guide-RNA sequences (crRNAs) control target site selection and cleavage activity. We used statistical thermodynamics and law of mass action to develop a five-step biophysical model of cas9 cleavage, and examined it in vivo and in vitro. To predict a crRNA's binding specificities and cleavage rates, we then compiled a nearest neighbor (NN) energy model that accounts for all possible base pairings and mismatches between the crRNA and the possible genomic DNA sites. These calculations correctly predicted crRNA specificity across 5518 sites. Our analysis reveals that cas9 activity and specificity are anti-correlated, and, the trade-off between them is the determining factor in performing an RNA-mediated cleavage with minimal off-targets. To find an optimal solution, we first created a scheme of safe-design criteria for Cas9 target selection by systematic analysis of available high throughput measurements. We then used our biophysical model to determine the optimal Cas9 expression levels and timing that maximizes on-target cleavage and minimizes off-target activity. We successfully applied this approach in bacterial and mammalian cell lines to reduce off-target activity to near background mutagenesis level while maintaining high on-target cleavage rate.

Keywords: biophysical model, CRISPR, Cas9, genome editing

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Authors: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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Authors: Vasupradaa Manivannan, Santosh Maruthy

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Background/Aims: Preliminary evidence suggests that code-switching and code-mixing may act as one of the voluntary coping behavior to avoid the stuttering characteristics in children and adults; however, less is known about the types and patterns of code-mixing (CM) and code-switching (CS). Further, it is not known how it is different between children to adults who stutter. This study aimed to identify and compare the CM and CS patterns between Kannada-English bilingual children and adults who stutter. Method: A standard group comparison was made between five children who stutter (CWS) in the age range of 9-13 years and five adults who stutter (AWS) in the age range of 20-25 years. The participants who are proficient in Kannada (first language- L1) and English (second language- L2) were considered for the study. There were two tasks given to both the groups, a) General conversation (GC) with 10 random questions, b) Narration task (NAR) (Story / General Topic, for example., A Memorable Life Event) in three different conditions {Mono Kannada (MK), Mono English (ME), and Bilingual (BIL) Condition}. The children and adults were assessed online (via Zoom session) with a high-quality internet connection. The audio and video samples of the full assessment session were auto-recorded and manually transcribed. The recorded samples were analyzed for the percentage of dysfluencies using SSI-4 and CM, and CS exhibited in each participant using Matrix Language Frame (MLF) model parameters. The obtained data were analyzed using the Statistical Package for the Social Sciences (SPSS) software package (Version 20.0). Results: The mean, median, and standard deviation values were obtained for the percentage of dysfluencies (%SS) and frequency of CM and CS in Kannada-English bilingual children and adults who stutter for various parameters obtained through the MLF model. The inferential results indicated that %SS significantly varied between population (AWS vs CWS), languages (L1 vs L2), and tasks (GC vs NAR) but not across free (BIL) and bound (MK, ME) conditions. It was also found that the frequency of CM and CS patterns varies between CWS and AWS. The AWS had a lesser %SS but greater use of CS patterns than CWS, which is due to their excessive coping skills. The language mixing patterns were more observed in L1 than L2, and it was significant in most of the MLF parameters. However, there was a significantly higher (P<0.05) %SS in L2 than L1. The CS and CS patterns were more in conditions 1 and 3 than 2, which may be due to the higher proficiency of L2 than L1. Conclusion: The findings highlight the importance of assessing the CM and CS behaviors, their patterns, and the frequency of CM and CS between CWS and AWS on MLF parameters in two different tasks across three conditions. The results help us to understand CM and CS strategies in bilingual persons who stutter.

Keywords: bilinguals, code mixing, code switching, stuttering

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Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

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Authors: Marina Petrova

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Language policy issues related to the preservation and development of the native languages of the Russian peoples and the state languages of the national republics are increasingly becoming the focus of recent attention of educators and parents, public and national figures. Is it legal to teach the national language or the mother tongue as the state language? Due to that dispute language phobia moods easily evolve into xenophobia among the population. However, a civilized, intelligent multicultural personality can only be formed if the country develops bilingualism and multilingualism, and languages as a political tool help to find ‘keys’ to sufficiently closed national communities both within a poly-ethnic state and in internal relations of multilingual countries. The purpose of this study is to design and theoretically substantiate an efficient model of language education in the innovatively developing Republic of Sakha. 800 participants from different educational institutions of Yakutia worked at developing a multilingual model of education. This investigation is of considerable practical importance because researchers could build a methodical system designed to create conditions for the formation of a cultural language personality and the development of the multilingual communicative competence of Yakut youth, necessary for communication in native, Russian and foreign languages. The selected methodology of humane-personal and competence approaches is reliable and valid. Researchers used a variety of sources of information, including access to related scientific fields (philosophy of education, sociology, humane and social pedagogy, psychology, effective psychotherapy, methods of teaching Russian, psycholinguistics, socio-cultural education, ethnoculturology, ethnopsychology). Of special note is the application of theoretical and empirical research methods, a combination of academic analysis of the problem and experienced training, positive results of experimental work, representative series, correct processing and statistical reliability of the obtained data. It ensures the validity of the investigation’s findings as well as their broad introduction into practice of life-long language education.

Keywords: intercultural communication, language policy, multilingual and multicultural education, the Sakha Republic of Yakutia

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Sherelle Lou Sumera Icutan, Sheila P. Cayabyab, Mary Jane Laruan, Paulo V. Cenas, Agustina R. Tactay

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This study critically analyzed the recent theses and dissertations of the Basic Education Curriculum (BEC) teachers who finished their graduate programs in selected higher educational institutions in Region I and CAR to be able to come up with a unified result from the varied results of the analyzed research works. All theses and dissertations completed by the educators/teachers/school personnel in the secondary and elementary public and private schools in Region 1 and CAR from AY 2003–2004 to AY 2007–2008 were classified first–as to work or non-work related; second–as to the different aspects of the curriculum: implementation, content, instructional materials, assessment instruments, learning, teaching, and others; third–as to being eligible for meta-analysis or not. Only studies found eligible for meta-analysis were subjected to the procedure. Aside from documentary analysis, the statistical treatments used in meta-analysis include the standardized effect size, Pearson’s correlation (r), the chi-square test of homogeneity and the inverse of the Fisher transformation. This study found out that the BEC-teachers usually probe on work-related researchers with topics that are focused on the learning performances of the students and on factors related to teaching. The development of instructional materials and assessment of implemented programs are also equally explored. However, there are only few researches on content and assessment instrument. Research findings on the areas of learning and teaching are the only aspects that are meta-analyzable. The research findings across studies in Region I and CAR of BEC teachers that focused on similar variables correlated to teaching do not vary significantly. On the contrary, research findings across studies in Region I and CAR that focused on variables correlated to learning performance significantly vary. Within each region, variations on the findings of research works related to learning performance that considered similar variables still exist. The combined finding on the effect size or relationship of the variables that are correlated to learning performance are low which means that effect is small but definite while the combined findings on the relationship of the variables correlated to teaching are slight or almost negligible.

Keywords: meta-analysis, BEC teachers, work-related research,

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Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

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Authors: Ludmila A. Gavriliuc, Jerry McLarty, Heather E. Kleiner, J. Michael Mathis

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Abstract -- Background: The citrus coumarine Auraptene (Aur) is an effective chemopreventive agent, as manifested in many models of diseases and cancer. Nuclear factor erythroid 2-related factor (Nrf2) is an important regulator of genes induced by oxidative stress, such as glutathione S-transferases, heme oxygenase-1, and peroxiredoxin 1, by activating the antioxidant response element (ARE). Genetic and biochemical evidence has demonstrated that glutathione (GSH) and glutathione-dependent enzymes, glutathione reductase (GR), glutathione peroxidases (GPs), glutathione S-transferases (GSTs) are responsible for the control of intracellular reduction-oxidation status and participate in cellular adaptation to oxidative stress. The effect of Aur on the activity of GR, GPs (Se-GP and Se-iGP), and content of GSH in the liver, kidney, and spleen is insufficiently explored. Aim: Our goal was the examination of the Aur influence on the redox-system of GSH in Nrf2 wild type and Nrf2 knockout mice via activation of Nrf2 and ARE. Methods: Twenty female mice, 10 Nrf2 wild-type (WT) and 10 Nrf2 (-/-) knockout (KO), were bred and genotyped for our study. The activity of GR, Se-GP, Se-iGP, GST, G6PD, CytP450 reductase, catalase (Cat), and content of GSH were analyzed in the liver, kidney, and spleen using Spectrophotometry methods. The results of the specific activity of enzymes and the amount of GSH were analyzed with ANOVA and Spearman statistical methods. Results: Aur (200 mg/kg) treatment induced hepatic GST, GR, Se-GP activity and inhibited their activity in the spleen of mice, most likely via activation of the ARE through Nrf2. Activation in kidney Se-GP and G6PD by Aur is also controlled, apparently through Nrf2. Results of the non-parametric Spearman correlation analysis indicated the strong positive correlation between GR and G6PD only in the liver in WT control mice (r=+0.972; p < 0.005) and in the kidney KO control mice (r=+0.958; p < 0.005). The observed low content of GSH in the liver of KO mice indicated an increase in its participation in the neutralization of toxic substances with the absence of induction of GSH-dependent enzymes, such as GST, GR, Se-GP, and Se-iGP. Activation of CytP450 in kidney and spleen and Cat in the liver in KO mice probably revealed another regulatory mechanism for these enzymes. Conclusion: Thereby, obtained results testify that Aur can modulate the activity of genes and antioxidant enzymatic redox-system of GSH, responsible for the control of intracellular reduction-oxidation status.

Keywords: auraptene, glutathione, GST, Nrf2

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Oluwayemisi D. Ishola, Lekan Ajijola

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Nigeria faces a demographic challenge characterized by a burgeoning youth population and an escalating fertility rate. A notable decline in the use of modern contraceptives among adolescent girls and young women compounds the challenge. The youthful demographic stands at a critical juncture in the nation's pursuit to fulfill its pledge of achieving a 27% modern contraceptive rate by 2030, embodying the potential to translate this ambitious commitment into a tangible reality. This research undertook a multi-dimensional examination to scrutinize contraceptive ideational disparities among adolescents and young women in Nigeria, with a particular emphasis on ideational factors. The data underpinning this study were drawn from a cross-sectional household survey carried out in the Nigerian states of Edo, Ogun, Plateau, and Niger between October 2019 and January 2020. The survey encompassed 2,857 sexually active women aged 15-24 years. Employing an ideational framework focusing on behavior that accentuates psychosocial factors, the study dissected nine unique ideational variables into three principal domains: social, cognitive, and emotional. Multivariate logistics regression analyses were used to assess associations between ideational elements and contraceptive use within the total sample and specific age brackets (adolescents of 15-19 years and youth of 20-24 years). For this study, a p-value less than 0.05 was considered indicative of statistical significance. The study's results revealed significant associations between the ideational variables and contraceptive use in total sample and among adolescent and youth, ranging from p < .05 to p < .001. The influence of each domain's predictors on Family Planning (FP) manifested variations when assessed separately and across the different age groups. Notably, cognitive and emotional domains were found to be the strongest predictor of contraceptive use when compared with social domains in the general sample and among youth. This study’s findings highlight the complex interplay of social, cognitive, and emotional factors in contraceptive use among young individuals. Understanding these dynamics is crucial in developing effective strategies to overcome barriers and improve access to contraceptive services among young women in Nigeria.

Keywords: adolescents, contraception, ideation, youth

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Authors: Zena F. Mushtaq, Iqbal M. Abbas

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Background: Diabetes mellitus during pregnancy is one of the major medical and social problems with increasing prevalence in last decades and may lead to more vulnerable to dental problems and increased risk for periodontal diseases. Objectives: To assess oral hygiene behaviors among pregnant women with diabetes who attended primary health care centers and find out the relationship between oral hygiene behaviors and studied variables. Methodology: A cross sectional design was conducted from 7 July to 30 September 2014 on non probability (convenient sample) of 150 pregnant women with diabetes was selected from twelve Primary Health Care Centers at Baghdad city. Questionnaire format is tool for data collection which had designed and consisted of three main parts including: socio demographic, reproductive characteristics and items of oral hygiene behaviors among pregnant women with diabetes. Reliability of the questionnaire was determined through internal consistency of correlation coefficient (R= 0.940) and validity of content was determined through reviewing it by (12) experts in different specialties and was determined through pilot study. Descriptive and inferential statistics were used to analyze collected data. Result: Result of study revealed that (35.3%) of study sample was (35-39) years old with mean and SD is (X & SD = 33.57 ± 5.54) years, and (34.7%) of the study sample was graduated from primary school and less, half of the study sample was government employment and self employed, (42.7%) of the study sample had moderate socioeconomic status, the highest percentage (70.0%) of the study sample was nonsmokers, The result indicates that oral hygiene behaviors have moderate mean score in all items. There are no statistical significant association between oral hygiene domain and studied variables. Conclusions: All items related to health behavior concerning oral hygiene is in moderate mean of score, which may expose pregnant women with diabetes to high risk of periodontal diseases. Recommendations: Dental care provider should perform a dental examination at least every three months for each pregnant woman with diabetes, explanation of the effect of DM on periodontal health, oral hygiene instruction, oral prophylaxis, professional cleaning and treatment of periodontal diseases(scaling and root planing) when needed.

Keywords: diabetes, health behavior, pregnant women, oral hygiene

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Authors: S. M. Abdus Sattar

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Introduction: The objectives of the study are to assess different aspects of the tourism and hospitality industry, analyze its contributions to the Gross Domestic Product of Bangladesh, identify the importance of the tourism and hospitality industry, explore future prospects in the sectors, identify challenges and provide recommendations for the development of these industries. The study explores the significance of the tourism and hospitality industry in economic growth and defines its role. Tourism is one of the fastest-growing industries in the world today. Methodology: The study adopts statistical methods and utilizes both quantitative and qualitative research techniques. Data is collected through surveys, interviews, visitor registration, online platforms and analysis of various tourism-related records. The study focuses on marketing, management, attractions and services in the tourism and hospitality sectors. Result: The tourism and hospitality industry offers great opportunities for emerging economies and developing countries. The industry provides job creation, infrastructure development, cultural assets and environmental conservation, essential skills development, revenue generated, foreign exchange earned, economic growth and reduced poverty and inequality. Discussion: The study focuses on improving infrastructure and service quality in the tourism and hospitality industry to attract tourists. The industry significantly contributes to the Gross Domestic Product of Bangladesh. It highlights how the tourism and hospitality sectors can drive economic development, reduce poverty and promote cultural and environmental conservation. It also explores the challenges and future prospects in the tourism and hospitality sectors. Conclusion and Future Scope: The opportunities for tourism of Bangladesh are agricultural tourism, religious tourism, sports tourism, eco-tourism, educational tourism, rural tourism and cultural tourism. However, there is a lack of research and plans to explore the development of the industry. The tourism and hospitality industry offers numerous opportunities for growth and development. There are job opportunities for travel consultants, tour operators, event planners, hotel managers, travel writers, tourism development officers and airline executives in the future. The study recommends to development of tourism infrastructure, maintaining tourist destinations, railway stations, airports, rest houses, hotels and improving the quality of services.

Keywords: tourism, hospitality, employment, economic, development

Procedia PDF Downloads 30

Authors: Marko Jankovic, Aleksandra Knezevic, Maja Cupic, Dragana Vujic, Zeljko Zecevic, Borko Gobeljic, Marija Simic, Tanja Jovanovic

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The human cytomegalovirus (CMV) is a notorious pathogen in the pediatric transplant setting. Although studies on factors in complicity with CMV infection abound, the role of age, gender, allogeneic hematopoietic stem cell transplantation (alloHSCT) modality, and underlying disease as regards CMV infection and viral load in children are poorly explored. We examined the significance of various factors related to the risk of CMV infection and viral load in Serbian children and adolescents undergoing alloHSCT. This was a prospective single centre study of thirty two pediatric patients in receipt of alloHSCT for various malignant and non-malignant disorders. Screening for active viral infection was performed by regular weekly monitoring. The Real-Time PCR method was used for CMV DNA detection and quantitation. Statistical analysis was performed using the IBM SPSS Statistics v20 software. Chi-square test was used to evaluate categorical variables. Comparison between scalar and nominal data was done by Wilcoxon-Mann-Whitney test. Pearson correlation was applied for studying the association between patient age and viral load. CMV was detected in 23 (71.9%) patients. Infection occurred significantly more often (p=0.015) in patients with haploidentical donors. The opposite was noted for matched sibling grafts (p=0.006). The viral load was higher in females (p=0.041) and children in the aftermath of alloHSCT with malignant diseases (p=0.019). There was no significant relationship between the viral infection dynamics and overt medical consequences. This is the first study of risk factors for CMV infection in Serbian pediatric alloHSCT patients. Transplanted patients presented with a high incidence of CMV viremia. The HLA compatibility of donated graft is associated with the frequency of CMV positive events. Age, gender, underlying disease, and medically relevant events were not conducive to occurrences of viremia. Notably, substantial viral burdens were evidenced in females and patients with neoplastic diseases. Studies comprising larger populations are clearly needed to scrutinize current results.

Keywords: allogeneic hematopoietic stem cell transplantation, children, cytomegalovirus, risk factors, viral load

Procedia PDF Downloads 162

Authors: Frank Fan

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PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

Procedia PDF Downloads 62

Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

Procedia PDF Downloads 127

Authors: K. Alafogiannis, E. E. Houssos, E. Anagnostou, G. Kouvarakis, N. Mihalopoulos, A. Fotiadi

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The Mediterranean basin is an area where different aerosol types coexist, including urban/industrial, desert dust, biomass burning and marine particles. Particularly, mineral dust aerosols, mostly originated from North African deserts, significantly contribute to high aerosol loads above the Mediterranean. Dust transport, controlled by the variation of the atmospheric circulation throughout the year, results in a strong spatial and temporal variability of aerosol properties. In this study, the synoptic conditions which favor dust transport over the Eastern Mediterranean are thoroughly investigated. For this reason, three datasets are employed. Firstly, ground-based daily data of aerosol properties, namely Aerosol Optical Thickness (AOT), Ångström exponent (α440-870) and fine fraction from the FORTH-AERONET (Aerosol Robotic Network) station along with measurements of PM10 concentrations from Finokalia station, for the period 2003-2011, are used to identify days with high coarse aerosol load (episodes) over Crete. Then, geopotential height at 1000, 850 and 700 hPa levels obtained from the NCEP/NCAR Reanalysis Project, are utilized to depict the atmospheric circulation during the identified episodes. Additionally, air-mass back trajectories, calculated by HYSPLIT, are used to verify the origin of aerosols from neighbouring deserts. For the 227 identified dust episodes, the statistical methods of Factor and Cluster Analysis are applied on the corresponding atmospheric circulation data to reveal the main types of the synoptic conditions favouring dust transport towards Crete (Eastern Mediterranean). The 227 cases are classified into 11 distinct types (clusters). Dust episodes in Eastern Mediterranean, are found to be more frequent (52%) in spring with a secondary maximum in autumn. The main characteristic of the atmospheric circulation associated with dust episodes, is the presence of a low-pressure system at surface, either in southwestern Europe or western/central Mediterranean, which induces a southerly air flow favouring dust transport from African deserts. The exact position and the intensity of the low-pressure system vary notably among clusters. More rarely dust may originate from deserts of Arabian Peninsula.

Keywords: aerosols, atmospheric circulation, dust particles, Eastern Mediterranean

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Authors: Irene H. Maralit

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Warning labels have been found to inform smokers about the health hazards of smoking, encourage smokers to quit, and prevent nonsmokers from starting to smoke. Warning labels on tobacco products are an ideal way of communicating with smokers. Since the intervention is delivered at the time of smoking, nearly all smokers are exposed to warning labels and pack-a-day smokers could be exposed to the warnings more than 7,000 times per year. Given the reach and frequency of exposure, the proponents want to know the effect of warning labels on smoking behavior. Its aims to identify the profile of the smokers associated with its behavioral variables that best describe the users’ perception. The behavioral variables are AVOID, THINK RISK and FORGO. This research study aims to determine if there is significant relationship between the effect of warning labels on cigarette package on Consumer behavior when grouped according to profile variable. The researcher used quota sampling to gather representative data through purposive means to determine the accurate representation of data needed in the study. Furthermore, the data was gathered through the use of a self-constructed questionnaire. The statistical method used were Frequency count, Chi square, multi regression, weighted mean and ANOVA to determine the scale and percentage of the three variables. After the analysis of data, results shows that most of the respondents belongs to age range 22–28 years old with percentage of 25.3%, majority are male with a total number of 134 with percentage of 89.3% and single with total number of 79 and percentage of 52.7%, mostly are high school graduates with total number of 59 and percentage of 39.3, with regards to occupation, skilled workers have the highest frequency of 37 with 24.7%, Majority of the income of the respondents falls under the range of Php 5,001-Php10,000 with 50.7%. And also with regards to the number of sticks consumed per day falls under 6–10 got the highest frequency with 33.3%. The respondents THINK RISK factor got the highest composite mean which is 2.79 with verbal interpretation of agree. It is followed by FORGO with 2.78 composite mean and a verbal interpretation of agree and AVOID variable with composite mean of 2.77 with agree as its verbal interpretation. In terms of significant relationship on the effects of cigarette label to consumer behavior when grouped according to profile variable, sex and occupation found to be significant.

Keywords: consumer behavior, smokers, warning labels, think risk avoid forgo

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Authors: Abdelbaky Abouzeid

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The study aimed at determining the effect of using the active learning on achievement and attitudes toward studying the human rights course for the Bahrain Teachers College students and the extent to which any differences of statistical significance according to gender and section can exist. To achieve the objectives of the study, the researcher developed and implemented research tools such as academic achievement test and the scale of attitudes towards the study of the Human Rights Course. The scale of attitudes towards Human Rights was constructed of 40 items investigating four dimensions; the cognitive dimension, the behavioral dimension, the affective dimension, and course quality dimension. The researcher then applied some of the active learning strategies in teaching this course to all students of the first year of the Bahrain Teachers College (102 male and female students) after excluding two students who did not complete the course requirements. Students were divided into five groups. These strategies included interactive lecturing, presentations, role playing, group projects, simulation, brainstorming, concept maps and mind maps, reflection and think-pair-share. The course was introduced to students during the second semester of the academic year 2016-2017. The study findings revealed that the use of active learning strategies affected the achievement of students of Bahrain Teachers College in the Human Rights course. The results of the T-test showed statistically significant differences on the pre-test and post-test in favor of the post-test. No statistically significant differences in the achievement of students according to the section and gender were found. The results also indicated that the use of active learning strategies had a positive effect on students' attitudes towards the study of the Human Rights Course on all the scale’s items. The general average reached (4.26) and the percentage reached (85.19%). Regarding the effect of using active learning strategies on students’ attitudes towards all the four dimensions of the scale, the study concluded that the behavioral dimension came first; the quality of the course came second, the cognitive dimension came third and in the fourth place came the affective dimension. No statistically significant differences in the attitude towards studying the Human Rights Course for the students according to their sections or gender were found. Based on the findings of the study, the researchers suggested some recommendations that can contribute to the development of teaching Human Rights Course at the University of Bahrain.

Keywords: attitudes, academic achievement, human rights, behavioral dimension, cognitive dimension, affective dimension, quality of the course

Procedia PDF Downloads 199

Authors: H. S. Niroshani, W. M. Ediri Arachchi, R. Tudugala, U. J. M. A. L. Jayasinghe, U. M. U. J. Jayasekara, P. B. Hewavithana

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Mammography is used as a screening tool for early diagnosis of breast cancer. It is also useful in refining the diagnosis of breast cancer either by assessment or work up after a suspicious area in the breast has been detected. In order to detect breast cancer accurately and at the earliest possible stage, the image must have an optimum contrast to reveal mass densities and spiculated fibrous structures radiating from them. In addition, the spatial resolution must be adequate to reveal the suffusion of micro calcifications and their shape. The above factors can be optimized by implementing an effective QA programme to enhance the accurate diagnosis of mammographic imaging. Therefore, the radiographer’s knowledge on QA is greatly instrumental in routine mammographic practice. The aim of this study was to assess the radiographer’s knowledge on Quality Assurance and Quality Control programmes in relation to mammographic procedures. A cross-sectional study was carried out among all radiographers working in each mammography setting in Sri Lanka. Pre-tested, anonymous self-administered questionnaires were circulated among the study population and duly filled questionnaires returned within a period of three months were taken into the account. The data on demographical information, knowledge on QA programme and associated QC tests, overall knowledge on QA and QC programmes were obtained. Data analysis was performed using IBM SPSS statistical software (version 20.0). The total response rate was 59.6% and the average knowledge score was 54.15±11.29 SD out of 100. Knowledge was compared on the basis of education level, special training of mammography, and the years of working experience in a mammographic setting of the individuals. Out of 31 subjects, 64.5% (n=20) were graduate radiographers and 35.5% (n=11) were diploma holders while 83.9% (n=26) of radiographers have been specially trained for mammography and 16.1% (n=5) have not been attended for any special training for mammography. It is also noted that 58.1% (n=18) of individuals possessed their experience of less than one year and rest 41.9% (n=13) of them were greater than that. Further, the results found that there is a significant difference (P < 0.05) in the knowledge of QA and overall knowledge on QA and QC programme in the categories of education level and working experience. Also, results imply that there was a significant difference (P < 0.05) in the knowledge of QC test among the groups of trained and non-trained radiographers. This study reveals that education level, working experience and the training obtained particularly in the field of mammography have a significant impact on their knowledge on QA and QC in mammography.

Keywords: knowledge, mammography, quality assurance, quality control

Procedia PDF Downloads 332

Authors: Ernest Gyan Bediako, Petra Dancova, Tomas Vit

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Flow boiling heat transfer remains an important area of research due to its relevance in thermal management systems and other applications. Despite the enormous work done in the field of flow boiling heat transfer over the years to understand how flow parameters such as mass flux, heat flux, saturation conditions and tube geometries influence the characteristics of flow boiling heat transfer, there are still many contradictions and lack of agreement on the actual mechanisms controlling heat transfer and how flow parameters impact the heat transfer. This work thus seeks to experimentally investigate the heat transfer characteristics and flow patterns at low mass fluxes, low heat fluxes and low saturation pressure conditions which are of less attention in literature but prevalent in refrigeration, air-conditioning and heat pump applications. In this study, flow boiling experiment was conducted for R134a working fluid in a 5 mm internal diameter stainless steel horizontal smooth tube with mass flux ranging from 80- 100 kg/m2 s, heat fluxes ranging from 3.55kW/m2 - 25.23 kW/m2 and saturation pressure of 460 kPa. Vapor quality ranged from 0 to 1. A well-known flow pattern map created by Wojtan et al. was used to predict the flow patterns noticed during the study. The experimental results were correlated with well-known flow boiling heat transfer correlations in literature. The findings show that, heat transfer coefficient was influenced by both mass flux and heat fluxes. However, for an increasing heat flux, nucleate boiling was observed to be the dominant mechanism controlling the heat transfer especially at low vapor quality region. For an increasing mass flux, convective boiling was the dominant mechanism controlling the heat transfer especially in the high vapor quality region. Also, the study observed an unusual high heat transfer coefficient at low vapor qualities which could be due to periodic wetting of the walls of the tube due to slug flow pattern and stratified wavy flow patterns. The flow patterns predicted by Wojtan et al. flow pattern map were mixture of slug and stratified wavy, purely stratified wavy and dry out. Statistical assessment of the experimental data with various well-known correlations from literature showed that, none of the correlations reported in literature could predicted the experimental data with enough accuracy.

Keywords: flow boiling, heat transfer coefficient, mass flux, heat flux.

Procedia PDF Downloads 117

Authors: Shoaib Rasool

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Migration trends in rural areas of Gujrat are increasing day by day among illiterate people as they consider it as a source of attraction and charm of destination. It affects the life standard both positive and negative way to their families left behind in the context of poverty, socio-economic status and life standards. It also promotes material items and as well as social indicators of living, housing conditions, schooling of their children’s, health seeking behavior and to some extent their family environment. The nature of the present study is to analyze socio-economic conditions regarding life standard of emigrant families left behind in rural areas of Gujrat district, Pakistan. A survey design was used on 150 families selected from rural areas of Gujrat districts through purposive sampling technique. A well-structured questionnaire was administered by the researcher to explore the nature of the study and for further data collection process. The measurement tool was pretested on 20 families to check the workability and reliability before the actual data collection. Statistical tests were applied to draw results and conclusion. The preliminary findings of the study show that emigration has left deep social-economic impacts on life standards of rural families left behind in Gujrat. They improved their life status and living standard through remittances. Emigration is one of the major sources of development of economy of household and it also alleviate poverty at house household level as well as community and country level. The rationale behind migration varies individually and geographically. There are popular considered attractions in Pakistan includes securing high status, improvement in health condition, coping other, getting married then to acquire nationality, using the unfair means, opting educational visas etc. Emigrants are not only sending remittances but also returning with newly acquired skills and valuable knowledge to their country of origin because emigrants learn new methods of living and working. There are also women migrants who experience social downward mobility by engaging in jobs that are beneath their educational qualifications.

Keywords: emigration, life standard, families, left behind, rural area, Gujrat

Procedia PDF Downloads 444

Authors: Dalma Dojcsák, Csaba Váradi, Flóra Farkas, Tamás Farkas, János Papp, Béla Viskolcz

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Background: Appendicitis is a common acute inflammatory condition in both children and adults, but current laboratory markers such as C-reactive protein (CRP), white blood cell count (WBC), absolute neutrophil count (ANC), and red blood cell count (RNC) lack specificity in detecting appendicitis-related inflammation. N-glycosylation, an asparagine-linked glycosylation process, plays a vital role in cellular interactions, angiogenesis, immune response, and effector functions. Altered N-glycosylation impacts tumor growth and both acute and chronic inflammatory processes. IgG, the second most abundant glycoprotein in serum, shows altered glycosylation patterns during inflammation, suggesting that IgG glycan modifications may serve as potential biomarkers for appendicitis. Specifically, increased levels of agalactosylated IgG glycans are a known feature of various inflammatory conditions, potentially including appendicitis. Identifying pediatric appendicitis remains challenging due to the absence of specific biomarkers, which makes diagnosis reliant on clinical symptoms, imaging such as ultrasound, and nonspecific lab indicators (e.g., CRP, WBC, ANC). In this study, we analyzed the IgG derived N-glycome in pediatric patients with appendicitis compared with healthy controls. Methodology: The N-glycome was analyzed by high-performance liquid-chromatography combined with mass spectrometry. IgG was isolated from serum samples by Protein G column. The IgG derived glycans were released by enzymatic deglycosylation and fluorescent tags were attached to each glycan moiety, which made necessitates the sample clean-up for further reliable quantitation. Overall, 38 controls and 40 serum samples diagnosed with pediatric appendicitis were analyzed by HILIC-MS methods. Multivariate statistical tests were performed with area percentage under the peak data derived from the integrated peaks, which were obtained from the chromatograms. Conclusions: Our results represented the altered N-glycome of IgG in pediatric appendicitis is similar with other observations. The glycosylation pattern reported so far for IgG is characterized by decreased galactosylation and sialylation, and an increase in fucosylation.

Keywords: N-glycosylation, liquid chromatography, mass spectrometry, inflammation, appendicitis, immunoglobulin G

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Authors: K. Tunde Olagunju, C. Scott Allen, Freek Van Der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization are only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two (2) operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the hydrocarbon spectral slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven (7) different hydrocarbon oils (crude and refined oil) taken on ten (10) different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon-substrate combination, Sentinel-2, WorldView-3

Procedia PDF Downloads 216

Authors: Tekalign Gidi Kure

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This paper addresses a range of serious problems involving higher education in Ethiopia. In spite of increased enrollment in higher education, educational quality is deteriorating afterwards. Thus, this paper tried to assess the role of social infrastructure in education for economic development of the country and examined major critical problems in higher education of Ethiopia such as higher education finance, curriculum development, and instructor’s career development. Primarily the paper discusses the fundamental contributions of social infrastructure in higher education to economic development; namely development of human capital, improved health, life expectancy, increased productivity, and personal saving, then, the paper examines critically higher education in three regimes of Ethiopia (Emperor Regime, Derg Regime and EPDRF/current government). Thus, four main questions were raised during this research: "What are the antecedents of Ethiopia Higher Education System under three regimes?", " what are the current and emerging higher educational needs in Ethiopia economic development?", " what are the role of private sector in addressing the gaps in the higher education of the country and its adverse effect on quality issues? ", and "what improvements are needed in higher education system of Ethiopia?". Documents from Ministry of Education in Ethiopia, National Statistical Abstracts, and Reports from the World Bank and other recognized institutions were used in addition to recent empirical researches conducted in the country. In doing so, care had been taken to reduce prejudiced reports by involving different reports from multiple sources. The paper concludes that during emperor system higher education enrollment was among the very lowest in the world, therefore, the skilled human resource available to guide development were little, but the cost was very high. During the Derg regime where an ideological change in the system penetrated into higher education resulted with the lack of a large amount of resources to support higher education; the war inside and outside the country diverts resources from the sector. The main purpose of this paper is not only to discuss the problems and issues of higher education in the past, but it also investigates the influence that the current expansion of higher education has on the finance, staff, and other resources for the quality of education. The paper concludes that higher education in Ethiopia are financed by government, outdated curriculum and lagging behind the standard regarding qualified staff. Finally, it provided inevitable solutions if the country wants to gain well record in quality of education as well.

Keywords: social infrastructure, higher education, ethiopia, education quality

Procedia PDF Downloads 527

Authors: Emilia K. H. Danielsson-Waters, Malaz Elsaddig, Kevin Jones

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Unfortunately, it is well known that neonatal deaths are a common and potentially preventable occurrence across the world. Neonatal resuscitation is a simple and inexpensive intervention that can effectively reduce this rate, and can be taught and implemented globally. This project is a follow-on from one in 2012, which found that neonatal resuscitation simulation was valuable for education, but would be better improved by being delivered by local staff. Methods: This study involved auditing the neonatal admission and death records within a rural Ugandan hospital, alongside implementing a Train-The-Trainer teaching scheme to teach Neonatal Resuscitation. One local doctor was trained for simulating neonatal resuscitation, whom subsequently taught an additional 14 staff members in one-afternoon session. Participants were asked to complete questionnaires to assess their knowledge and confidence pre- and post-simulation, and a survey to identify barriers and drivers to simulation. Results: The results found that the neonatal mortality rate in this hospital was 25% between July 2016- July 2017, with birth asphyxia, prematurity and sepsis being the most common causes. Barriers to simulation that were identified predominantly included a lack of time, facilities and opportunity, yet all members stated simulation was beneficial for improving skills and confidence. The simulation session received incredibly positive qualitative feedback, and also a 0.58-point increase in knowledge (p=0.197) and 0.73-point increase in confidence (0.079). Conclusion: This research shows that it is possible to create a teaching scheme in a rural hospital, however, many barriers are in place for its sustainability, and a larger sample size with a more sensitive scale is required to achieve statistical significance. This is undeniably important, because teaching neonatal resuscitation can have a direct impact on neonatal mortality. Subsequently, recommendations include that efforts should be put in place to create a sustainable training scheme, for example, by employing a resuscitation officer. Moreover, neonatal resuscitation teaching should be conducted more frequently in hospitals, and conducted in a wider geographical context, including within the community, in order to achieve its full effect.

Keywords: neonatal resuscitation, sustainable medical education, train-the-trainer, Uganda

Procedia PDF Downloads 152

Authors: Japhet N. Mwambusi

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High tropical forests deforestation for solid wood furniture industry is among of climate change contributing agents. This pressure indirectly is caused by furniture joints failure due to poor gluing technology based on improper use of different glues to different wood species which lead to low quality and weak wood-glue joints. This study was carried in order to run performance tests of wood glues on different wood species used in wood workshops: Morogoro Tanzania whereby three popular wood species of C. lusitanica, T. glandis and E. maidenii were tested against five glues of Woodfix, Bullbond, Ponal, Fevicol and Coral found in the market. The findings were necessary on developing a guideline for proper glue selection for a particular wood species joining. Random sampling was employed to interview carpenters while conducting a survey on the background of carpenters like their education level and to determine factors that influence their glues choice. Monsanto Tensiometer was used to determine bonding strength of identified wood glues to different wood species in use under British Standard of testing wood shear strength (BS EN 205) procedures. Data obtained from interviewing carpenters were analyzed through Statistical Package of Social Science software (SPSS) to allow the comparison of different data while laboratory data were compiled, related and compared by the use of MS Excel worksheet software as well as Analysis of Variance (ANOVA). Results revealed that among all five wood glues tested in the laboratory to three different wood species, Coral performed much better with the average shear strength 4.18 N/mm², 3.23 N/mm² and 5.42 N/mm² for Cypress, Teak and Eucalyptus respectively. This displays that for a strong joint to be formed to all tree wood species for soft wood and hard wood, Coral has a first priority in use. The developed table of guideline from this research can be useful to carpenters on proper glue selection to a particular wood species so as to meet glue-bond strength. This will secure furniture market as well as reduce pressure to the forests for furniture production because of the strong existing furniture due to their strong joints. Indeed, this can be a good strategy on reducing climate change speed in tropics which result from high deforestation of trees for furniture production.

Keywords: climate change, deforestation, gluing technology, joint failure, wood-glue, wood species

Procedia PDF Downloads 241