研究生: |
蔡秉叡 Tsai, Ping-Jui |
---|---|
論文名稱: |
1.水橋現象及相關效應之探討 2.利用統計方法分析SHR以及WKY老鼠 1.New Phenomenon and Evidence in Project of Water Bridge 2.Defining States of Mental Disorder via Statistical Methods on SHR and WKY |
指導教授: |
洪在明
Hong, Tzay-Ming |
口試委員: |
周亞謙
Chou, Ya-Chang 張家靖 Chang, Chia-Ching 徐鏞元 Hsu, Yung-Yuan |
學位類別: |
碩士 Master |
系所名稱: |
理學院 - 物理學系 Department of Physics |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 69 |
中文關鍵詞: | 水橋 、決策樹 、病理分析 、老鼠 、電偶極 、電容 |
外文關鍵詞: | capacitance, decision tree, electric dipole, mental disorder, rat, water bridge |
相關次數: | 點閱:2 下載:0 |
分享至: |
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摘要
此篇論文探討水橋(water thread or water bridge)現象,攸關無雜質的去離子水,在高電壓下的物理現象。此現象是William Armstrong在1893年首次發現的,實驗裝置是在兩個燒杯口,距離不為零的情況,串聯600伏特直流電壓,正極端的去離子水會主動噴出水柱(cone jet),在燒杯間搭建起一條抵抗重力的水橋。雖然已經有許多有關水橋現象的實驗與理論,我們希望藉由特殊的實驗設計來間接證實及探討其完整的物理意義,這包括以下兩個面向:
首先是垂涎現象,它是指當我們使用注射幫浦(syringe pump),將水滴落降在水橋上。如果這個撞擊超過水橋的支撐能耐,會出現一連串的排水現象,將多餘的水排出水橋;當水橋漸漸恢復原狀,取而代之的是具有再現性的滴水現象,透過每秒1000張的高速攝影機,可以清晰看見不同電壓造成的不同垂涎長度以及隨後的抬升行為,我們暱稱其為垂涎現象。
其次是當我們把電壓移除或是將燒杯距離加大,導致水橋斷裂,會發現在水橋中間產生一個帶電水團,這個現象有助於了解,在燒杯口是否有累積電荷?換言之,可否將這兩個燒杯視為一等效電容?我們使用高速攝影機以及外加電場來測量水團的帶電量,並改變燒杯口的幾何形狀,來驗證等效電容這個假設模型,能否正確地預測實驗上觀測到的水團電性。
結合物理、生醫及統計領域的第二主題,專注在提出並探討一個新的方法論,俾
使科學家在神經網路特性中,能找出一套可以兼具定性及定量的數值,來定義不同的
老鼠病理狀態。之後,再藉由這個狀態,使用統計方法來找出一套能夠篩選多個狀態
以及病理的機制,在狀態分類上,分為生理和外在作用-生理狀態計有WKY(一般情
形)及SHR(過動症情形)兩種,在外在作用的情況,我們選用麻醉劑,以IOS(麻醉劑)濃度的量值來區分高與低麻醉,藉此分類不同型態的實驗鼠,並加以分析。
Abstrct
Up to now, Although scientist offer many theories trying to solve, but all theories are all incomplete, in this post, we will show two and more experiments and theory to make complete - Capacitance effect, Saliva phenomenon and film.
In the past two decades neuroscience has offered many popular methods for the analysis mental disorder, such as seed-based analysis, ICA, and graph methods. They are widely used in the study of brain network. We offered a new procedure that can simplify the analysis and has a high ROC index over 9. This method is based on graph methods to build a connectivity network, which is characterized by degrees in this paper and measures the number of effective links for each voxel. When the degree is ranked from low to high, the network equation can be fit by the power-law distribution. It has been proposed that human behavior can be differentiated by distinct and yet robust exponents of the power law. Using the mentally disordered SHR and WKY rats as our samples, We used chi-square distribution and decision tree to analyze the statistical properties of this power law and identify its different math traits. This is more concise, precise, and useful than the majority of conventional approaches.
Keywords: Capacitance; Decision Tree; Electric Dipole; Mental Disorder; Rat; Water Bridge.
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