不同热条件下记忆对皮肤组织生物热反应的影响研究。

IF 1.3 4区 生物学 Q3 BIOLOGY
Rakhi Tiwari, Abhinav Singhal, Rajneesh Kumar, Pappu Kumar, Suniti Ghangas
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引用次数: 0

摘要

激光、聚焦超声、微波和射频等用于皮肤组织热疗法的新技术的进步,增加了医疗中许多具有挑战性的情况。在不同的热冲击和谐波加热条件下,建立了一种基于双相滞后记忆导数的精细生物传热模型。采用拉普拉斯变换方法来感知解析结果。采用拉普拉斯逆变换技术对位移、应变和温度随应力在时域上的分布进行了定量计算。利用计算结果分别分析了两种热条件下记忆相关导数核函数的分量和时滞参数对研究场(温度、位移、应变和应力)的影响。研究发现,插入记忆效应是一个统一的模型,因此,该模型可以更好地预测热处理过程的温度场数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Investigation of memory influences on bio-heat responses of skin tissue due to various thermal conditions.

Investigation of memory influences on bio-heat responses of skin tissue due to various thermal conditions.

Advancement of new technologies such as laser, focused ultrasound, microwave and radio frequency for thermal therapy of skin tissue has increased numerous challenging situations in medical treatment. In this article, a new meticulous bio-heat transfer model based on memory-dependent derivative with dual-phase-lag has been developed under different thermal conditions such as thermal shock and harmonic-type heating. Laplace transform method is acquired to perceive the analytical consequences. Quantitative results are evaluated for displacement, strain and temperature along with stress distributions in time domain by adopting the technique of inverse Laplace transform. Impacts of the constituents of memory-dependent derivatives-kernel functions along with time-delay parameter are analysed on the studied fields (temperature, displacement, strain and stress) for both thermal conditions separately using computational results. It has been found that the insertion of the memory effect proves itself a unified model, and therefore, this model can better predict temperature field data for thermal treatment processes.

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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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