CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: PCR stutter</title> <meta name="description" content="Search results for: PCR stutter"> <meta name="keywords" content="PCR stutter"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="PCR stutter" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="PCR stutter"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 10</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: PCR stutter</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10</span> Dopamine and Serotonin Levels in Blood Samples of Jordanian Children Who Stutter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mazin%20Alqhazo">Mazin Alqhazo</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayat%20Bani%20Rashaid"> Ayat Bani Rashaid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study examines the levels of dopamine and serotonin in blood samples of children who stutter compared with normal fluent speakers. Blood specimens from 50 children who stutter (6 females, 44 males) and 50 normal children matched age and gender were collected for the purpose of the current study. The concentrations of dopamine and serotonin were measured using the 1100 series high-performance liquid chromatography coupled with ultraviolet detector instrument (HPLC-UV). It was revealed that dopamine level in the blood samples of stuttering group and fluent group was not significant (P = 0.769), whereas the level of serotonin was significantly higher in the blood samples of stuttering group than the blood samples of fluent normal group (P = 0.015). It is concluded that serotonin blockers could be used in future studies to evaluate its role as a medication for the treatment of stuttering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dopamine" title="dopamine">dopamine</a>, <a href="https://publications.waset.org/abstracts/search?q=serotonin" title=" serotonin"> serotonin</a>, <a href="https://publications.waset.org/abstracts/search?q=stuttering" title=" stuttering"> stuttering</a>, <a href="https://publications.waset.org/abstracts/search?q=fluent%20speakers" title=" fluent speakers"> fluent speakers</a> </p> <a href="https://publications.waset.org/abstracts/112649/dopamine-and-serotonin-levels-in-blood-samples-of-jordanian-children-who-stutter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112649.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">160</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9</span> Code Mixing and Code-Switching Patterns in Kannada-English Bilingual Children and Adults Who Stutter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vasupradaa%20Manivannan">Vasupradaa Manivannan</a>, <a href="https://publications.waset.org/abstracts/search?q=Santosh%20Maruthy"> Santosh Maruthy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> 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. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bilinguals" title="bilinguals">bilinguals</a>, <a href="https://publications.waset.org/abstracts/search?q=code%20mixing" title=" code mixing"> code mixing</a>, <a href="https://publications.waset.org/abstracts/search?q=code%20switching" title=" code switching"> code switching</a>, <a href="https://publications.waset.org/abstracts/search?q=stuttering" title=" stuttering"> stuttering</a> </p> <a href="https://publications.waset.org/abstracts/145457/code-mixing-and-code-switching-patterns-in-kannada-english-bilingual-children-and-adults-who-stutter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> An Infinite Mixture Model for Modelling Stutter Ratio in Forensic Data Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20C.%20S.%20Sampath%20Fernando">M. A. C. S. Sampath Fernando</a>, <a href="https://publications.waset.org/abstracts/search?q=James%20M.%20Curran"> James M. Curran</a>, <a href="https://publications.waset.org/abstracts/search?q=Renate%20Meyer"> Renate Meyer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chinese%20restaurant%20process" title="Chinese restaurant process">Chinese restaurant process</a>, <a href="https://publications.waset.org/abstracts/search?q=Dirichlet%20prior" title=" Dirichlet prior"> Dirichlet prior</a>, <a href="https://publications.waset.org/abstracts/search?q=infinite%20mixture%20model" title=" infinite mixture model"> infinite mixture model</a>, <a href="https://publications.waset.org/abstracts/search?q=PCR%20stutter" title=" PCR stutter"> PCR stutter</a> </p> <a href="https://publications.waset.org/abstracts/57612/an-infinite-mixture-model-for-modelling-stutter-ratio-in-forensic-data-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57612.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">330</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> Stuttering Persistence in Children: Effectiveness of the Psicodizione Method in a Small Italian Cohort</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Corinna%20Zeli">Corinna Zeli</a>, <a href="https://publications.waset.org/abstracts/search?q=Silvia%20Calati"> Silvia Calati</a>, <a href="https://publications.waset.org/abstracts/search?q=Marco%20Simeoni"> Marco Simeoni</a>, <a href="https://publications.waset.org/abstracts/search?q=Chiara%20Comastri"> Chiara Comastri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Developmental stuttering affects about 10% of preschool children; although the high percentage of natural recovery, a quarter of them will become an adult who stutters. An effective early intervention should help those children with high persistence risk for the future. The Psicodizione method for early stuttering is an Italian behavior indirect treatment for preschool children who stutter in which method parents act as good guides for communication, modeling their own fluency. In this study, we give a preliminary measure to evaluate the long-term effectiveness of Psicodizione method on stuttering preschool children with a high persistence risk. Among all Italian children treated with the Psicodizione method between 2018 and 2019, we selected 8 kids with at least 3 high risk persistence factors from the Illinois Prediction Criteria proposed by Yairi and Seery. The factors chosen for the selection were: one parent who stutters (1pt mother; 1.5pt father), male gender, ≥ 4 years old at onset; ≥ 12 months from onset of symptoms before treatment. For this study, the families were contacted after an average period of time of 14,7 months (range 3 - 26 months). Parental reports were gathered with a standard online questionnaire in order to obtain data reflecting fluency from a wide range of the children’s life situations. The minimum worthwhile outcome was set at "mild evidence" in a 5 point Likert scale (1 mild evidence- 5 high severity evidence). A second group of 6 children, among those treated with the Piscodizione method, was selected as high potential for spontaneous remission (low persistence risk). The children in this group had to fulfill all the following criteria: female gender, symptoms for less than 12 months (before treatment), age of onset <4 years old, none of the parents with persistent stuttering. At the time of this follow-up, the children were aged 6–9 years, with a mean of 15 months post-treatment. Among the children in the high persistence risk group, 2 (25%) hadn’t had stutter anymore, and 3 (37,5%) had mild stutter based on parental reports. In the low persistency risk group, the children were aged 4–6 years, with a mean of 14 months post-treatment, and 5 (84%) hadn’t had stutter anymore (for the past 16 months on average).62,5% of children at high risk of persistence after Psicodizione treatment showed mild evidence of stutter at most. 75% of parents confirmed a better fluency than before the treatment. The low persistence risk group seemed to be representative of spontaneous recovery. This study’s design could help to better evaluate the success of the proposed interventions for stuttering preschool children and provides a preliminary measure of the effectiveness of the Psicodizione method on high persistence risk children. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=early%20treatment" title="early treatment">early treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=fluency" title=" fluency"> fluency</a>, <a href="https://publications.waset.org/abstracts/search?q=preschool%20children" title=" preschool children"> preschool children</a>, <a href="https://publications.waset.org/abstracts/search?q=stuttering" title=" stuttering"> stuttering</a> </p> <a href="https://publications.waset.org/abstracts/134307/stuttering-persistence-in-children-effectiveness-of-the-psicodizione-method-in-a-small-italian-cohort" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134307.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">218</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> Analysis of Linguistic Disfluencies in Bilingual Children’s Discourse</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sheena%20Christabel%20Pravin">Sheena Christabel Pravin</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Palanivelan"> M. Palanivelan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bi-lingual" title="bi-lingual">bi-lingual</a>, <a href="https://publications.waset.org/abstracts/search?q=children%20who%20stutter" title=" children who stutter"> children who stutter</a>, <a href="https://publications.waset.org/abstracts/search?q=children%20with%20language%20impairment" title=" children with language impairment"> children with language impairment</a>, <a href="https://publications.waset.org/abstracts/search?q=hidden%20markov%20models" title=" hidden markov models"> hidden markov models</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-layer%20perceptron" title=" multi-layer perceptron"> multi-layer perceptron</a>, <a href="https://publications.waset.org/abstracts/search?q=linguistic%20disfluencies" title=" linguistic disfluencies"> linguistic disfluencies</a>, <a href="https://publications.waset.org/abstracts/search?q=stuttering%20disfluencies" title=" stuttering disfluencies"> stuttering disfluencies</a> </p> <a href="https://publications.waset.org/abstracts/87075/analysis-of-linguistic-disfluencies-in-bilingual-childrens-discourse" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87075.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">217</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> Phonological Encoding and Working Memory in Kannada Speaking Adults Who Stutter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nirmal%20Sugathan">Nirmal Sugathan</a>, <a href="https://publications.waset.org/abstracts/search?q=Santosh%20Maruthy"> Santosh Maruthy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: A considerable number of studies have evidenced that phonological encoding (PE) and working memory (WM) skills operate differently in adults who stutter (AWS). In order to tap these skills, several paradigms have been employed such as phonological priming, phoneme monitoring, and nonword repetition tasks. This study, however, utilizes a word jumble paradigm to assess both PE and WM using different modalities and this may give a better understanding of phonological processing deficits in AWS. Aim: The present study investigated PE and WM abilities in conjunction with lexical access in AWS using jumbled words. The study also aimed at investigating the effect of increase in cognitive load on phonological processing in AWS by comparing the speech reaction time (SRT) and accuracy scores across various syllable lengths. Method: Participants were 11 AWS (Age range=19-26) and 11 adults who do not stutter (AWNS) (Age range=19-26) matched for age, gender and handedness. Stimuli: Ninety 3-, 4-, and 5-syllable jumbled words (JWs) (n=30 per syllable length category) constructed from Kannada words served as stimuli for jumbled word paradigm. In order to generate jumbled words (JWs), the syllables in the real words were randomly transpositioned. Procedures: To assess PE, the JWs were presently visually using DMDX software and for WM task, JWs were presented through auditory mode through headphones. The participants were asked to silently manipulate the jumbled words to form a Kannada real word and verbally respond once. The responses for both tasks were audio recorded using record function in DMDX software and the recorded responses were analyzed using PRAAT software to calculate the SRT. Results: SRT: Mann-Whitney test results demonstrated that AWS performed significantly slower on both tasks (p < 0.001) as indicated by increased SRT. Also, AWS presented with increased SRT on both the tasks in all syllable length conditions (p < 0.001). Effect of syllable length: Wilcoxon signed rank test was carried out revealed that, on task assessing PE, the SRT of 4syllable JWs were significantly higher in both AWS (Z= -2.93, p=.003) and AWNS (Z= -2.41, p=.003) when compared to 3-syllable words. However, the findings for 4- and 5-syllable words were not significant. Task Accuracy: The accuracy scores were calculated for three syllable length conditions for both PE and PM tasks and were compared across the groups using Mann-Whitney test. The results indicated that the accuracy scores of AWS were significantly below that of AWNS in all the three syllable conditions for both the tasks (p < 0.001). Conclusion: The above findings suggest that PE and WM skills are compromised in AWS as indicated by increased SRT. Also, AWS were progressively less accurate in descrambling JWs of increasing syllable length and this may be interpreted as, rather than existing as a uniform deficiency, PE and WM deficits emerge when the cognitive load is increased. AWNS exhibited increased SRT and increased accuracy for JWs of longer syllable length whereas AWS was not benefited from increasing the reaction time, thus AWS had to compromise for both SRT and accuracy while solving JWs of longer syllable length. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adults%20who%20stutter" title="adults who stutter">adults who stutter</a>, <a href="https://publications.waset.org/abstracts/search?q=phonological%20ability" title=" phonological ability"> phonological ability</a>, <a href="https://publications.waset.org/abstracts/search?q=working%20memory" title=" working memory"> working memory</a>, <a href="https://publications.waset.org/abstracts/search?q=encoding" title=" encoding"> encoding</a>, <a href="https://publications.waset.org/abstracts/search?q=jumbled%20words" title=" jumbled words"> jumbled words</a> </p> <a href="https://publications.waset.org/abstracts/99180/phonological-encoding-and-working-memory-in-kannada-speaking-adults-who-stutter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99180.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">240</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Emotional and Physiological Reaction While Listening the Speech of Adults Who Stutter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xharavina%20V.">Xharavina V.</a>, <a href="https://publications.waset.org/abstracts/search?q=Gallopeni%20F."> Gallopeni F.</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmeti%20K."> Ahmeti K.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stuttered speech is filled with intermittent sound prolongations and/or rapid part word repetitions. Oftentimes, these aberrant acoustic behaviors are associated with intermittent physical tension and struggle behaviors such as head jerks, arm jerks, finger tapping, excessive eye-blinks, etc. Additionally, the jarring nature of acoustic and physical manifestations that often accompanies moderate-severe stuttering may induce negative emotional responses in listeners, which alters communication between the person who stutters and their listeners. However, researches for the influence of negative emotions in the communication and for physical reaction are limited. Therefore, to compare psycho-physiological responses of fluent adults, while listening the speech of adults who speak fluency and adults who stutter, are necessary. This study comprises the experimental method, with total of 104 participants (average age-20 years old, SD=2.1), divided into 3 groups. All participants self-reported no impairments in speech, language, or hearing. Exploring the responses of the participants, there were used two records speeches; a voice who speaks fluently and the voice who stutters. Heartbeats and the pulse were measured by the digital blood pressure monitor called 'Tensoval', as a physiological response to the fluent and stuttering sample. Meanwhile, the emotional responses of participants were measured by the self-reporting questionnaire (Steenbarger, 2001). Results showed an increase in heartbeats during the stuttering speech compared with the fluent sample (p < 0.5). The listeners also self-reported themselves as more alive, unhappy, nervous, repulsive, sad, tense, distracted and upset when listening the stuttering words versus the words of the fluent adult (where it was reported to experience positive emotions). These data support the notions that speech with stuttering can bring a psycho-physical reaction to the listeners. Speech pathologists should be aware that listeners show intolerable physiological reactions to stuttering that remain visible over time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emotional" title="emotional">emotional</a>, <a href="https://publications.waset.org/abstracts/search?q=physiological" title=" physiological"> physiological</a>, <a href="https://publications.waset.org/abstracts/search?q=stuttering" title=" stuttering"> stuttering</a>, <a href="https://publications.waset.org/abstracts/search?q=fluent%20speech" title=" fluent speech"> fluent speech</a> </p> <a href="https://publications.waset.org/abstracts/99557/emotional-and-physiological-reaction-while-listening-the-speech-of-adults-who-stutter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99557.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Cross Cultural Adaptation and Content Validation of the Assessment Instrument Preschooler Awareness of Stuttering Survey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Catarina%20Belchior">Catarina Belchior</a>, <a href="https://publications.waset.org/abstracts/search?q=Catarina%20Martins"> Catarina Martins</a>, <a href="https://publications.waset.org/abstracts/search?q=Sara%20Mendes"> Sara Mendes</a>, <a href="https://publications.waset.org/abstracts/search?q=Ana%20Rita%20S.%20Valente"> Ana Rita S. Valente</a>, <a href="https://publications.waset.org/abstracts/search?q=Elsa%20Marta%20Soares"> Elsa Marta Soares</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: The negative feelings and attitudes that a person who stutters can develop are extremely relevant when considering assessment and intervention in Speech and Language Therapy. This relates to the fact that the person who stutters can experience feelings such as shame, fear and negative beliefs when communicating. Considering the complexity and importance of integrating diverse aspects in stuttering intervention, it is central to identify those emotions as early as possible. Therefore, this research aimed to achieve the translation, adaptation to European Portuguese and to analyze the content validation of the Preschooler Awareness Stuttering Survey (Abbiati, Guitar & Hutchins, 2015), an instrument that allows the assessment of the impact of stuttering on preschool children who stutter considering feelings and attitudes. Methodology: Cross-sectional descriptive qualitative research. The following methodological procedures were followed: translation, back-translation, panel of experts and pilot study. This abstract describes the results of the first three phases of this process. The translation was accomplished by two Speech Language Therapists (SLT). Both professionals have more than five years of experience and are users of English language. One of them has a broad experience in the field of stuttering. Back-translation was conducted by two bilingual individuals without experience in health or any knowledge about the instrument. The panel of experts was composed by 3 different SLT, experts in the field of stuttering. Results and Discussion: In the translation and back-translation process it was possible to verify differences in semantic and idiomatic equivalences of several concepts and expressions, as well as the need to include new information to enhance the understanding of the application of the instrument. The meeting between the two translators and the researchers allowed the achievement of a consensus version that was used in back-translation. Considering adaptation and content validation, the main change made by the experts was the conceptual equivalence of the questions and answers of the instrument's sheets. Considering that in the translated consensus version the questions began with various nouns such as 'is' or 'the cow' and that the answers did not contain the adverb 'much' as in the original instrument, the panel agreed that it would be more appropriate if the questions all started with 'how' and that all the answers should present the adverb 'much'. This decision was made to ensure that the translate instrument would be similar to the original and so that the results obtained could be comparable between the original and the translated instrument. There was also elaborated one semantic equivalence between concepts. The panel of experts found that all other items and specificities of the instrument were adequate, concluding the adequacy of the instrument considering its objectives and its intended target population. Conclusion: This research aspires to diversify the existing validated resources in this scope, adding a new instrument that allows the assessment of preschool children who stutter. Consequently, it is hoped that this instrument will provide a real and reliable assessment that can lead to an appropriate therapeutic intervention according to the characteristics and needs of each child. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stuttering" title="stuttering">stuttering</a>, <a href="https://publications.waset.org/abstracts/search?q=assessment" title=" assessment"> assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=feelings%20and%20attitudes" title=" feelings and attitudes"> feelings and attitudes</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20language%20therapy" title=" speech language therapy"> speech language therapy</a> </p> <a href="https://publications.waset.org/abstracts/107708/cross-cultural-adaptation-and-content-validation-of-the-assessment-instrument-preschooler-awareness-of-stuttering-survey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107708.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">149</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Performance and Limitations of Likelihood Based Information Criteria and Leave-One-Out Cross-Validation Approximation Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20C.%20S.%20Sampath%20Fernando">M. A. C. S. Sampath Fernando</a>, <a href="https://publications.waset.org/abstracts/search?q=James%20M.%20Curran"> James M. Curran</a>, <a href="https://publications.waset.org/abstracts/search?q=Renate%20Meyer"> Renate Meyer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cross-validation" title="cross-validation">cross-validation</a>, <a href="https://publications.waset.org/abstracts/search?q=importance%20sampling" title=" importance sampling"> importance sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20criteria" title=" information criteria"> information criteria</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20accuracy" title=" predictive accuracy"> predictive accuracy</a> </p> <a href="https://publications.waset.org/abstracts/57619/performance-and-limitations-of-likelihood-based-information-criteria-and-leave-one-out-cross-validation-approximation-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57619.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">392</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Translation and Adaptation of the Assessment Instrument “Kiddycat” for European Portuguese</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elsa%20Marta%20Soares">Elsa Marta Soares</a>, <a href="https://publications.waset.org/abstracts/search?q=Ana%20Rita%20Valente"> Ana Rita Valente</a>, <a href="https://publications.waset.org/abstracts/search?q=Cristiana%20Rodrigues"> Cristiana Rodrigues</a>, <a href="https://publications.waset.org/abstracts/search?q=Filipa%20Gon%C3%A7alves"> Filipa Gonçalves </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The assessment of feelings and attitudes of preschool children in relation to stuttering is crucial. Negative experiences can lead to anxiety, worry or frustration. To avoid the worsening of attitudes and feelings related to stuttering, it is important the early detection in order to intervene as soon as possible through an individualized intervention plan. Then it is important to have Portuguese instruments that allow this assessment. Aims: The aim of the present study is to realize the translation and adaptation of the Communication Attitude Test for Children in Preschool Age and Kindergarten (KiddyCat) for EP. Methodology: For the translation and adaptation process, a methodological study was carried out with the following steps: translation, back translation, assessment by a committee of experts and pre-test. This abstract describes the results of the first two phases of this process. The translation was accomplished by two bilingual individuals without experience in health and any knowledge about the instrument. One of them was an English teacher and the other one a Translator. The back-translation was conducted by two Senior Class Teachers that live in United Kingdom without any knowledge in health and about the instrument. Results and Discussion: In translation there were differences in semantic equivalences of various expressions and concepts. A discussion between the two translators, mediated by the researchers, allowed to achieve the consensus version of the translated instrument. Taking into account the original version of KiddyCAT the results demonstrated that back-translation versions were similar to the original version of this assessment instrument. Although the back-translators used different words, they were synonymous, maintaining semantic and idiomatic equivalences of the instrument’s items. Conclusion: This project contributes with an important resource that can be used in the assessment of feelings and attitudes of preschool children who stutter. This was the first phase of the research; expert panel and pretest are being developed. Therefore, it is expected that this instrument contributes to an holistic therapeutic intervention, taking into account the individual characteristics of each child. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assessment" title="assessment">assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=feelings%20and%20attitudes" title=" feelings and attitudes"> feelings and attitudes</a>, <a href="https://publications.waset.org/abstracts/search?q=preschool%20children" title=" preschool children"> preschool children</a>, <a href="https://publications.waset.org/abstracts/search?q=stuttering" title=" stuttering "> stuttering </a> </p> <a href="https://publications.waset.org/abstracts/121633/translation-and-adaptation-of-the-assessment-instrument-kiddycat-for-european-portuguese" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/121633.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>