Setting the Tone: An Investigation of Skin Color Bias in Asia

For me, rhythm means having consistency. The piece highlights my own experience with the disruption of my daily rhythm due to COVID-19. The first half shows my routine and interactions prior to COVID-19 while the second half shows my experiences in the present day. Prior to the virus, I had a day to day routine that was filled with noise. Everyday moved quickly and I established a daily rhythm. However, when COVID-19 spread, it changed everything. I felt like I didn’t have a routine anymore because I wasn’t allowed to go anywhere. Time was moving much slower and worst of all, xenophobia was growing at a significant rate. As a Chinese Canadian, this was the first time I truly felt the weight of the color of my skin. COVID-19 changed the way that I consistently assumed that the color of my skin wasn’t something that strangers would significantly care about. However, as I got on a bus, I unintentionally scared a woman simply because of my skin color. From that point, I knew that xenophobia would affect the way people perceived me everyday. The woman was scared of the virus— which in turn was scared of me—and I was scared that she would thwart her anger towards me because I am Chinese. If looks could kill, then the woman and I ironically both feared each other. Now, due to COVID-19, I am adapting to a new routine. A routine where the color of skin rings louder than any other sound.

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Prevalence and Risk Factors of Hepatitis C Virus (HCV) in Tehsil Batkhela District Malakand, KPK, Pakistan

International Journal of Contemporary Research and Review ◽

10.15520/ijcrr/2018/9/06/525 ◽

2018 ◽

Vol 9 (06) ◽

pp. 20251-20256

Author(s):

Mudassir Khan ◽

Shahrukh Khan ◽

Shohra Haider ◽

Fazal Jalil ◽

Muhsin Jamal ◽

...

Keyword(s):

Risk Factors ◽

Hepatitis C Virus ◽

Hepatitis C ◽

Skin Color ◽

Significant Risk ◽

Rapid Test ◽

Prevalence Ratio ◽

Hcv Infection ◽

Hcv Rna ◽

Common Symptom

Background: Prevalence of Hepatitis C viral infection and its major risk factors has been found out in population of Batkhela, Khyber Pakhtunkhwa, Pakistan by taking number of volunteers from the interested area. HCV prevalence has not been researched in recent time here in this area, so that’s why we contributed. Materials and Methods: Ab rapid test cassette serum/plasma (USA) kit has been used for the mentioned purpose following by ELISA and finally PCR to find out active infection of virus. ICT positive individuals were reconfirmed by ELISA and then ELISA positive samples were carefully investigated by RT-PCR for Hepatitis C Virus. Results: The study population was of 770 volunteers belonging to the mentioned area of research, 453 males and 317 females. The overall prevalence was found to be 5.32% of HCV in Batkhela. This prevalence ratio was 3.12% in males and 2.20 % in females. 3rd generation ELISA was used to refine ICT positive samples which showed that 37 of the ICT positive samples had antibodies detected by ELISA. To find out active HCV infection, ELISA positive samples were refined by real time PCR which showed 2.98% of prevalence of active HCV infection in Batkhela based on HCV RNA in their blood. Principle Conclusion: Overall prevalence was found 5.32%, contaminated reused syringes and blades at Barbour’s shop, blood transfusion, surgical operations and unhygienic food in stalls etc were found significant risk factors for acquiring HCV infection. Body weakness and pale yellow skin color was common symptom in HCV positive volunteers. Safe sexual activities, blood screening before donation and sterilizing surgical equipment’s can protect us from Hepatitis C Virus.

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A Quantitative Analysis of Skin Color Using a Videomicroscope and a Computer.

Nishi Nihon Hifuka ◽

10.2336/nishinihonhifu.55.468 ◽

1993 ◽

Vol 55 (3) ◽

pp. 468-475 ◽

Cited By ~ 2

Author(s):

Hirotsugu TAKIWAKI ◽

Shiro SHIRAI ◽

Masahiro UTSUNOMIYA ◽

Yasumori WATANABE ◽

Yoshiyuki KANNO

Keyword(s):

Quantitative Analysis ◽

Skin Color

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Exploring the Facial Color Representative Regions Using the Humanae Images

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2020.64.6.060406 ◽

2020 ◽

Author(s):

Yuchun Yan ◽

Hayan Choi ◽

Hyeon-Jeong Suk

Keyword(s):

Image Analysis ◽

Future Study ◽

Skin Color ◽

Color Difference ◽

Facial Skin ◽

Female Images ◽

Gender And Race ◽

Facial Landmarks

It is difficult to describe facial skin color through a solid color as it varies from region to region. In this article, the authors utilized image analysis to identify the facial color representative region. A total of 1052 female images from Humanae project were selected as a solid color was generated for each image as their representative skin colors by the photographer. Using the open CV-based libraries, such as EOS of Surrey Face Models and DeepFace, 3448 facial landmarks together with gender and race information were detected. For an illustrative and intuitive analysis, they then re-defined 27 visually important sub-regions to cluster the landmarks. The 27 sub-region colors for each image were finally derived and recorded in L ∗ , a ∗ , and b ∗ . By estimating the color difference among representative color and 27 sub-regions, we discovered that sub-regions of below lips (low Labial) and central cheeks (upper Buccal) were the most representative regions across four major ethnicity groups. In future study, the methodology is expected to be applied for more image sources.

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