尼泊尔加德满都谷地居民主要指纹纹型与性别、血型的关系研究

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Sushma Paudel, Sushmita Paudel, Samikshya Kafle
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引用次数: 0

摘要

指纹是独特的生物特征标识,反映了复杂的遗传和环境/生理影响。除了具有法医意义外,它们还可以提供对血型和性别等生理特征的见解,这有助于法医分析缩小搜索范围。本探索性研究旨在确定指纹模式、性别和血型在尼泊尔加德满都一个特定区域队列中的潜在关联。本初步研究包括喜玛拉雅怀特豪斯国际学院290名学生(男144名,女146名)。指纹图案(环状、螺旋和拱形)被分析并与参与者的ABO-Rh血型进行比较。统计分析,包括卡方检验,用于确定关联和趋势。环状指纹是最常见的指纹模式(57.14%),其次是螺旋(35%)和拱形(7.86%)。B+ve血型在加德满都的研究人群中最为普遍(33.1%)。性别与指纹图谱有显著的相关性。性别分析显示,环在雌性中占主导地位,而雄性则显示出更高的螺旋频率。ABO血型与指纹图谱无显著相关性,而指纹图谱与Rh因子有显著相关性(p = 0.0496)。环型在Rh阳性(Rh+ve)个体中更为普遍,而螺旋型在Rh阴性(Rh−ve)个体中更为常见。此外,研究人员还观察到,特定手指更频繁地拥有不同的指纹模式。双手食指以弓状多见,小指和左手中指以环状多见。以双手无名指和右拇指为最常见者。这一发现强化了全球血型和指纹分布模式,Rh+ve个体代表大多数,环状指纹是最主要的指纹模式。性别差异的趋势表明了基因的微妙相互作用,女性的环状结构频率更高,而男性的环状结构频率更高。同样,一些血型的人更有可能表现出一组特定的指纹模式。这项研究清楚地显示了性别差异和遗传因素对指纹模式的影响,特别是Rh因素。这些发现促进了皮肤纹学领域的发展,并对法医学和人口遗传学产生了影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Dermatoglyphic Study of Primary Fingerprints Pattern in Relation to Gender and Blood Group Among Residents of Kathmandu Valley, Nepal

A Dermatoglyphic Study of Primary Fingerprints Pattern in Relation to Gender and Blood Group Among Residents of Kathmandu Valley, Nepal

A Dermatoglyphic Study of Primary Fingerprints Pattern in Relation to Gender and Blood Group Among Residents of Kathmandu Valley, Nepal

A Dermatoglyphic Study of Primary Fingerprints Pattern in Relation to Gender and Blood Group Among Residents of Kathmandu Valley, Nepal

A Dermatoglyphic Study of Primary Fingerprints Pattern in Relation to Gender and Blood Group Among Residents of Kathmandu Valley, Nepal

Fingerprints are unique biometric identifiers that reflect intricate genetic and environmental/physiological influences. Beyond their forensic significance, they can offer insights into physiological traits like blood groups and gender, which can help in forensic analysis to narrow down the search. This exploratory study aims to identify potential associations between fingerprint patterns, gender, and blood groups within a defined regional cohort in Kathmandu, Nepal. This preliminary study included 290 students (144 males and 146 females) from Himalayan Whitehouse International College (HWIC). Fingerprint patterns (loops, whorls, and arches) were analyzed and compared with participants’ ABO-Rh blood groups. Statistical analyses, including chi-square tests, were used to determine associations and trends. Loops emerged as the most common fingerprint pattern (57.14%), followed by whorls (35%), and arches (7.86%). Blood group B+ve was the most prevalent (33.1%) among the study population in Kathmandu. The significant association between gender and fingerprint pattern was observed. The gender analysis revealed that loops were predominant in females, while males showed a higher frequency of whorls. While no significant relationship was observed between ABO blood groups and fingerprint patterns, a strong association was found between fingerprint patterns and Rh factor (p = 0.0496). Loops were more prevalent among Rh-positive (Rh+ve) individuals, while whorls were more common among Rh-negative (Rh−ve) individuals. Additionally, specific fingers were observed to have distinct fingerprint patterns more frequently. Arches were most prevalent in the index finger of both hands, loops were most abundant in both pinky finger, and left middle finger. Whorls were most frequently observed in ring finger of both hands and right thumb. The findings reinforce global patterns of blood group and fingerprint distribution, where Rh+ve individuals represent the majority and loops are most dominant fingerprint pattern. The gender-specific trends suggest the nuanced interplay of genetics, with females displaying a higher frequency of loops and males showing more whorls. Similarly, some blood group are more likely to exhibit a specific set of fingerprint patterns. This research clearly shows the gender-based differences and influence of genetic factors on fingerprint patterns, particularly the Rh factor. These findings contribute to the growing field of dermatoglyphics, with implications for forensic science, and population genetics.

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来源期刊
IET Biometrics
IET Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
0.00%
发文量
46
审稿时长
33 weeks
期刊介绍: The field of biometric recognition - automated recognition of individuals based on their behavioural and biological characteristics - has now reached a level of maturity where viable practical applications are both possible and increasingly available. The biometrics field is characterised especially by its interdisciplinarity since, while focused primarily around a strong technological base, effective system design and implementation often requires a broad range of skills encompassing, for example, human factors, data security and database technologies, psychological and physiological awareness, and so on. Also, the technology focus itself embraces diversity, since the engineering of effective biometric systems requires integration of image analysis, pattern recognition, sensor technology, database engineering, security design and many other strands of understanding. The scope of the journal is intentionally relatively wide. While focusing on core technological issues, it is recognised that these may be inherently diverse and in many cases may cross traditional disciplinary boundaries. The scope of the journal will therefore include any topics where it can be shown that a paper can increase our understanding of biometric systems, signal future developments and applications for biometrics, or promote greater practical uptake for relevant technologies: Development and enhancement of individual biometric modalities including the established and traditional modalities (e.g. face, fingerprint, iris, signature and handwriting recognition) and also newer or emerging modalities (gait, ear-shape, neurological patterns, etc.) Multibiometrics, theoretical and practical issues, implementation of practical systems, multiclassifier and multimodal approaches Soft biometrics and information fusion for identification, verification and trait prediction Human factors and the human-computer interface issues for biometric systems, exception handling strategies Template construction and template management, ageing factors and their impact on biometric systems Usability and user-oriented design, psychological and physiological principles and system integration Sensors and sensor technologies for biometric processing Database technologies to support biometric systems Implementation of biometric systems, security engineering implications, smartcard and associated technologies in implementation, implementation platforms, system design and performance evaluation Trust and privacy issues, security of biometric systems and supporting technological solutions, biometric template protection Biometric cryptosystems, security and biometrics-linked encryption Links with forensic processing and cross-disciplinary commonalities Core underpinning technologies (e.g. image analysis, pattern recognition, computer vision, signal processing, etc.), where the specific relevance to biometric processing can be demonstrated Applications and application-led considerations Position papers on technology or on the industrial context of biometric system development Adoption and promotion of standards in biometrics, improving technology acceptance, deployment and interoperability, avoiding cross-cultural and cross-sector restrictions Relevant ethical and social issues
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