scholarly journals Redefining Sociophonetic Competence: Mapping COG Differences in Phrase-Final Fricative Epithesis in L1 and L2 Speakers of French

Languages ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 59
Author(s):  
Amanda Dalola ◽  
Keiko Bridwell
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Multinomial Logistic Regression ◽  
Center Of Gravity ◽  
Final Position ◽  
Reading Task ◽  
Multiple Strategies ◽  
Low Profile ◽  
L1 And L2 ◽  
Measures Of Center

This article presents a study of measures of center of gravity (COG) in phrase-final fricative epithesis (PFFE) produced by L1 and L2 speakers of Continental French (CF). Participants completed a reading task targeting 98 tokens of /i,y,u/ in phrase-final position. COG measures were taken at the 25%, 50% and 75% marks, normalized and submitted to a mixed linear regression. Results revealed that L2 speakers showed higher COG values than L1 speakers in low PFFE-to-vowel ratios at the 25%, 50%, and 75% marks. COG measures were then categorized into six profile types on the basis of their frequencies at each timepoint: flat–low, flat–high, rising, falling, rising–falling, and falling–rising. Counts of COG profile were then submitted to multinomial logistic regression. Results revealed that although L1 speakers produced predominantly flat–low profile types at lower percent devoicings, L2 speakers preferred multiple strategies involving higher levels of articulatory energy (rising, falling, rise–fall). These results suggest that while L1 speakers realize PFFE differently with respect to phonological context, L2 speakers rely on its most common allophone, strong frication, in most contexts. As such, the findings of this study argue for an additional phonetic dimension in the construct of L2 sociophonetic competence.

scholarly journals Impact of change in household environment condition on morbidity in India: Evidence from longitudinal data

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247465
Author(s):  
N. Brahmanandam ◽  
R. Nagarajan
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Prime Minister ◽  
Multinomial Logistic Regression ◽  
Short Term ◽  
Clean Environment ◽  
Household Environment ◽  
Household Members ◽  
The Impact ◽  
Environment Condition

Background Household environment condition is an important predictor of morbidity of the household members. Without forming a healthy household environment, creating a healthy population is not possible. In this background, this study assesses the impact of change in household environment conditions on morbidity. Methods For the empirical analysis purpose of this study, we used two waves of longitudinal data from India Human Development Survey (2004–05, 2011–12). This study is based on 34131 re-contacted households in 2011–12 from the base year 2005. The bivariate and ANOVA tests were performed to assess any short-term morbidity (diarrhoea, fever and cough) with respect to change in household environment condition from 2005 to 2011. The multivariate linear regression was performed to assess the impact of change in household environment conditions on morbidity. The multinomial logistic regression was used to assess the impact of change in household environment condition on change in morbidity. Results The results from multivariate linear regression have shown that the share of household members fell sick due to any short-term morbidity (ASM) was significantly lower (β = –0.060, P<0.001) among the households who lived in clean environment condition in both the periods, 2004–05 and in 2011–12 as compared to those who were living in poor environment condition in both periods net of other socio-economic characteristics of the households. The share of household members fell sick due to any short-term morbidity has significantly declined (β = –0.051, P<0.001) among the household whose household environment condition has changed from poor in 2004–05 to clean environment in 2011–12 as compared to the households who have lived in poor environment condition in both periods in 2004–05 and 2011–12. The results of adjusted percentage from multinomial logistic regression have shown that the household members who fell sick with ASM was remained higher (4.9%; P<0.05) among the households whose environment condition was remained poor in both years in 2005 and 2011 as compared to the other households (2.7%) who remained in the better-off condition in both years in 2005 and 2011. Conclusion Considering the findings of the study, we suggest that ongoing government flagships programmes such as Swacch Bharat Mission (Clean India Mission), Pradhan Mantri Ujjwala Yojana (Prime Minister Clean Energy Scheme) and Pradhan Mantri Awas Yojana (Prime Minister Housing Scheme), and Jal Jeevan Mission (Improved Source of Drinking Water Scheme) should work in tandem to improve household environment conditions.

Role of Cross-training in Orthopaedic Injuries and Healthcare Burden in Masters Swimmers

2018 ◽  
Vol 40 (01) ◽  
pp. 52-56 ◽  
Author(s):  
Brett Baker ◽  
Stephanie Lapierre ◽  
Hirofumi Tanaka
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Healthcare Costs ◽  
Multinomial Logistic Regression ◽  
Linear Regression Analysis ◽  
Regression Analyses ◽  
Training Modality ◽  
Training History ◽  
Cross Training ◽  
Training Activities

AbstractWe determined whether the incidence of injuries would increase with advancing age and whether the participation in cross-training would be related to a decreased rate of injuries and healthcare costs in Masters swimmers. A total of 499 swimmers (55±14 years of age) belonging to US Masters Swimming completed a comprehensive questionnaire that included questions regarding their medical history as well as their training history. In average, swimmers had been training for 13±12 years, and 35, 40, and 47% participated in running, cycling, and dryland resistance training, respectively. According to the logistic regression, prevalence of injuries increased significantly but modestly with advancing age (p<0.05). Linear regression analysis showed that for every 1 month increase in the length of injury, healthcare costs increased by 7.4% (p<0.05). Linear regression and logistic regression analyses determined that overall volume of swimming training was not related to age or incidence of injuries, respectively. Multinomial logistic regression analyses using age and sex as predictors demonstrated that the odds of reporting a swim-related injury were significantly lower for individuals who participated in any number of cross-training activities compared with those who do not cross-train (p<0.05). Regular participation in any cross-training modality was inversely related to age (p<0.05). We concluded that the diversification of the overall training program by incorporating cross-training may be an important strategy to reduce sport-specific injuries among Masters athletes.

Public knowledge, perception and communication behavior surrounding COVID-19 in Malaysia

2020 ◽  
Author(s):  
Khayriyyah Mohd Hanafiah ◽  
Chang Da Wan
Keyword(s):  
Logistic Regression ◽  
Employment Status ◽  
Multinomial Logistic Regression ◽  
Movement Control ◽  
Education Level ◽  
Public Knowledge ◽  
Communication Behavior ◽  
Positive Communication ◽  
The Face ◽  
Control Order

The COVID-19 pandemic is the first to occur in an age of hyperconnectivity. This paper presents results from an online anonymous survey conducted in Malay, English, and Chinese, during the first week of the Movement Control Order in Malaysia (n=1075), which aimed to examine public knowledge, perception and communication behavior in the Malaysian society in the face of a sudden outbreak and social distancing measures. Although the level of public knowledge, risk perception and positive communication behavior surrounding COVID-19 was high, a majority of respondents reported receiving a lot of questionable information. Multinomial logistic regression further identified that responses to different items varied significantly across respondent survey language, gender, age, education level and employment status.

scholarly journals Reduced rank multinomial logistic regression in Markov chains with application to cognitive data

2021 ◽  
Author(s):  
Pei Wang ◽  
Erin L. Abner ◽  
David W. Fardo ◽  
Frederick A. Schmitt ◽  
Gregory A. Jicha ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Markov Chains ◽  
Multinomial Logistic Regression ◽  
Reduced Rank ◽  
Cognitive Data

Processing subject focus across two Spanish varieties

Probus ◽  
2020 ◽  
Vol 32 (1) ◽  
pp. 93-127
Author(s):  
Bradley Hoot ◽  
Tania Leal
Keyword(s):  
Language Processing ◽  
Sentence Processing ◽  
Word Order ◽  
Judgment Task ◽  
Spanish Speakers ◽  
Experimental Results ◽  
Final Position ◽  
Reading Task ◽  
New Information ◽  
Basic Facts

AbstractLinguists have keenly studied the realization of focus – the part of the sentence introducing new information – because it involves the interaction of different linguistic modules. Syntacticians have argued that Spanish uses word order for information-structural purposes, marking focused constituents via rightmost movement. However, recent studies have challenged this claim. To contribute sentence-processing evidence, we conducted a self-paced reading task and a judgment task with Mexican and Catalonian Spanish speakers. We found that movement to final position can signal focus in Spanish, in contrast to the aforementioned work. We contextualize our results within the literature, identifying three basic facts that theories of Spanish focus and theories of language processing should explain, and advance a fourth: that mismatches in information-structural expectations can induce processing delays. Finally, we propose that some differences in the existing experimental results may stem from methodological differences.

scholarly journals Association between Social Integration and Face Mask Use Behavior during the SARS-CoV-2 Pandemic in Japan: Results from U-CORONA Study

2021 ◽  
Vol 18 (9) ◽  
pp. 4717
Author(s):  
Nobutoshi Nawa ◽  
Yui Yamaoka ◽  
Yuna Koyama ◽  
Hisaaki Nishimura ◽  
Shiro Sonoda ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Social Network ◽  
Social Integration ◽  
Response Bias ◽  
Multinomial Logistic Regression ◽  
Face Mask ◽  
Neighborhood Association ◽  
Multinomial Logistic Regression Analysis ◽  
Use Behavior

Face mask use is a critical behavior to prevent the spread of SARS-CoV-2. We aimed to evaluate the association between social integration and face mask use during the COVID-19 pandemic in a random sample of households in Utsunomiya City, Greater Tokyo, Japan. Data included 645 adults in the Utsunomiya COVID-19 seROprevalence Neighborhood Association (U-CORONA) study, which was conducted after the first wave of the pandemic, between 14 June 2020 and 5 July 2020, in Utsunomiya City. Social integration before the pandemic was assessed by counting the number of social roles, based on the Cohen’s social network index. Face mask use before and during the pandemic was assessed by questionnaire, and participants were categorized into consistent mask users, new users, and current non-users. Multinomial logistic regression analysis was used to examine the association between lower social integration score and face mask use. To account for possible differential non-response bias, non-response weights were used. Of the 645 participants, 172 (26.7%) were consistent mask users and 460 (71.3%) were new users, while 13 (2.0%) were current non-users. Lower social integration level was positively associated with non-users (RRR: 1.76, 95% CI: 1.10, 2.82). Social integration may be important to promote face mask use.

scholarly journals Risk Scoring System of Mortality and Prediction Model of Hospital Stay for Critically Ill Patients Receiving Parenteral Nutrition

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 853
Author(s):  
Jee-Yun Kim ◽  
Jeong Yee ◽  
Tae-Im Park ◽  
So-Youn Shin ◽  
Man-Ho Ha ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Linear Regression ◽  
Parenteral Nutrition ◽  
Prediction Model ◽  
Scoring System ◽  
Prediction Equation ◽  
Icu Patients ◽  
Risk Scoring ◽  
Risk Scoring System

Predicting the clinical progression of intensive care unit (ICU) patients is crucial for survival and prognosis. Therefore, this retrospective study aimed to develop the risk scoring system of mortality and the prediction model of ICU length of stay (LOS) among patients admitted to the ICU. Data from ICU patients aged at least 18 years who received parenteral nutrition support for ≥50% of the daily calorie requirement from February 2014 to January 2018 were collected. In-hospital mortality and log-transformed LOS were analyzed by logistic regression and linear regression, respectively. For calculating risk scores, each coefficient was obtained based on regression model. Of 445 patients, 97 patients died in the ICU; the observed mortality rate was 21.8%. Using logistic regression analysis, APACHE II score (15–29: 1 point, 30 or higher: 2 points), qSOFA score ≥ 2 (2 points), serum albumin level < 3.4 g/dL (1 point), and infectious or respiratory disease (1 point) were incorporated into risk scoring system for mortality; patients with 0, 1, 2–4, and 5–6 points had approximately 10%, 20%, 40%, and 65% risk of death. For LOS, linear regression analysis showed the following prediction equation: log(LOS) = 0.01 × (APACHE II) + 0.04 × (total bilirubin) − 0.09 × (admission diagnosis of gastrointestinal disease or injury, poisoning, or other external cause) + 0.970. Our study provides the mortality risk score and LOS prediction equation. It could help clinicians to identify those at risk and optimize ICU management.

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