Adaptive ML-CFAR detection for correlated chi-square targets of all fluctuation models in correlated clutter and multiple target situations

Purpose The aims of this study were to characterize hearing symptoms, habits, and sound pressure levels (SPLs) of personal audio system (PAS) used by young adults; estimate the risk of developing hearing loss and assess whether instructions given to users led to behavioral changes; and propose recommendations for PAS users. Method A cross-sectional study was performed in 50 subjects with normal hearing. Procedures included questionnaire and measurement of PAS SPLs (real ear and manikin) through the users' own headphones and devices while they listened to four songs. After 1 year, 30 subjects answered questions about their usage habits. For the statistical analysis, one-way analysis of variance, Tukey's post hoc test, Lin and Spearman coefficients, the chi-square test, and logistic regression were used. Results Most subjects listened to music every day, usually in noisy environments. Sixty percent of the subjects reported hearing symptoms after using a PAS. Substantial variability in the equivalent music listening level (Leq) was noted ( M = 84.7 dBA; min = 65.1 dBA, max = 97.5 dBA). A significant difference was found only in the 4-kHz band when comparing the real-ear and manikin techniques. Based on the Leq, 38% of the individuals exceeded the maximum daily time allowance. Comparison of the subjects according to the maximum allowed daily exposure time revealed a higher number of hearing complaints from people with greater exposure. After 1 year, 43% of the subjects reduced their usage time, and 70% reduced the volume. A volume not exceeding 80% was recommended, and at this volume, the maximum usage time should be 160 min. Conclusions The habit of listening to music at high intensities on a daily basis seems to cause hearing symptoms, even in individuals with normal hearing. The real-ear and manikin techniques produced similar results. Providing instructions on this topic combined with measuring PAS SPLs may be an appropriate strategy for raising the awareness of people who are at risk. Supplemental Material https://doi.org/10.23641/asha.12431435

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On Computing Critical Points for a Bivariate Chi-Square Random Variable

Communications in Statistics - Simulation and Computation ◽

10.1080/03610917308548265 ◽

1973 ◽

Vol 2 (3) ◽

pp. 221-224

Author(s):

Richard Gunst

Keyword(s):

Critical Points ◽

Random Variable ◽

Chi Square

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Suicide Risk Among College Student

Crisis ◽

10.1027/0227-5910/a000340 ◽

2015 ◽

Vol 36 (6) ◽

pp. 416-423 ◽

Cited By ~ 11

Author(s):

Richard Shadick ◽

Faedra Backus Dagirmanjian ◽

Baptiste Barbot

Keyword(s):

Sexual Minority ◽

Students Of Color ◽

Structural Equation ◽

Suicide Risk ◽

Equation Modeling ◽

First Year ◽

Chi Square ◽

First Year College ◽

Marginalized Groups ◽

First Year College Students

Abstract. Background: Research on young adults in the general population has identified a relationship between sexual minority identification and risk for suicide. Differential rates of suicidal ideation and attempts have also been found across racial and ethnic groups. Aims: This study examined risk for suicide among university students, based on membership in one or more marginalized groups (sexual minority and racial minority identification). Method: Data were collected from first-year college students (N = 4,345) at an urban university. Structural equation modeling was employed to model a suicidality construct, based on which a "risk for suicide" category system was derived. Chi-square and logistic regression analyses were then conducted to estimate the relationship between the background variables of interest and suicide risk. Results: Students who identified as lesbian, gay, or bisexual (LGB) were associated with higher suicide risk than their heterosexual peers. Students of color were slightly less at risk than their heterosexual peers. However, LGB students of color were associated with elevated suicide risk relative to heterosexual peers. Conclusion: Results indicate that belonging to multiple marginalized groups may increase one's risk for suicide, though these effects are not simply additive. Findings highlight the complexity of the intersection between marginalized identities and suicidality.

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