全國中小學科展

2021年

「醛」面啟動-探討肉桂醛提升綠豆耐鹽能力之機制

濃厚氣味的中藥,吃了能讓人強健體魄,那植物服用後呢?研究發現,綠豆能感受肉桂粉中的氣味分子”肉桂醛”,並透過改變其生理與生長的發育來減緩其在鹽逆境下細胞死亡的程度,提高長期耐鹽能力。本研究顯示,熏完肉桂醛的綠豆能透過減少氣孔數、使澱粉代謝、增加根系來應對鹽逆境下的缺水問題,在生化研究方面,能透過在根部提前累積脯胺酸來應對滲透壓逆境。此外肉桂醛氣味能激發綠豆的抗氧化力,我們發現,肉桂醛能讓綠豆提前累積抗氧化物(脯胺酸、抗壞血酸),另能提高抗氧化酵素活性(POD、APX)來應對鹽逆境下的氧化傷害。本研究發現綠豆能感受肉桂醛氣味並提升其長期耐鹽能力,期待未來能將研究成果用於農業,減少逆境對農業帶來的損失。

以色彩區辨派典探討環狀誘導色彩錯覺中的同化與異化效果

色彩知覺是人類最重要的感官之一。由於形狀、亮度、空間頻率和色彩組成的不同,每個人對色彩的感知也有所差異。我們對此現象感到著迷,並決定進行一項研究,以識別和量化不同情況下的色彩誘導。 本研究選擇以環狀刺激作為主要圖像,以測量人類視覺色彩誘導。而本實驗主要利用紅色與綠色的誘導效果。實驗中,我們採用紅色及綠色基準做為目標環狀區域,並於其中添加可變性紅色目標,以測量受試者之視覺閾限。在色彩誘導的情況下,透過環狀刺激與測量所得之視覺閾限,我們可以識別並量化環狀刺激對色彩感知造成的影響。此外,我們也發現了環狀刺激中的單一環形如何影響人們對目標環狀區域的色彩感知。 我們利用實驗所得之結果,建立了一個預測並描述色彩錯覺與細胞反應相關性的模型,而此模型將會讓我們對人類視覺系統及神經間的側交互作用有更深一層的了解。

Predicting the Binding Affinity between Medicine and Estrogen Receptor Beta

Recent studies showed that the probability of Taiwanese females developing breast cancer has risen dramatically over the past 30 years. We are now facing younger and more breast cancer patients in Taiwan. What makes the matter even more severe, is the fact that patients that take cancer treating medicine will suffer from its serious side effects, some may even lose the ability to reproduce. We hope to develop a new system that can help doctors and researchers develop new medicine for treating breast cancer, the way medicine cures cancer tumors are by attaching onto the infected cells’ receptors. After collecting MACCS data (converted from SMILES), the dataset will be used for training the machine learning program. Due to the problem of insufficient training data, we used an ensemble method to generate our machine learning model. Among the three basic ensemble techniques, Max Voting, Averaging, and Weighted Averaging. we selected the max voting technique to perform the prediction for this research. We created two separate datasets, positive and negative, the two datasets will later be used as training data for the program. We weren’t sure of the ratio of positive and negative in the training data, therefore we compare 40 different ratios and evaluate the results. By comparing the accuracy of the models, we found out that when the ratio between positive data and negative data is 1:3000, the machine learning program will have the highest precision. After we created the final model through voting among the 1000 models generated, we evaluate the precision of the model through the following methods, AUC, precision, recall. The ultimate goal of this research is to assist doctors and researchers shorten the process of developing and testing new medicines.

以奈米錫奈米銦增益小分子團水製備及促進藥物傳輸效能探討

小分子團水(water cluster)的製備及應用一直是科學界的挑戰。本實驗利用熱蒸鍍法,加熱金屬塊材成原子蒸氣,在氬氣環境配合液態氮溫度下冷凝收集,成功製備了平均粒徑10nm金、20nm銀、54nm銦、71nm錫、14nm鎳奈米顆粒。將定量的奈米顆粒滲入去離子水中,以超聲波分散顆粒團聚,再以波長530奈米的綠光照射,讀取拉曼散射譜圖,判定來自小分子團水的振盪強度,探討5種奈米顆粒對形成小分子團水的功效。我們驚訝的發現奈米銦藉表面電漿共振(surface plasma resonance)及表面電子氧化還原功效,弱化水分子團簇成大分子團的功效為奈米金的16倍,奈米錫為12倍,也均高效於奈米銀及奈米鎳。以奈米銦及奈米錫增益小分子團水後,對將癌細胞藥物、養分帶入細胞的功效明顯提升。

同「鋅」協力 —— 以醇解法探討金屬鋅催化解聚 PET之反應

聚對苯二甲酸乙二酯 (PET) 是一種常見的合成高分子材料,其被應用的範圍相當廣泛,如產品包裝、手提袋等,然而隨著人類的過度使用,越來越多的 PET 產品被發現有回收不當的現象。 文獻指出,醇解法為一具有反應條件簡單、反應過程溫和及較不會產生多餘副產物的解聚 PET 方法,且醇解法能使用非均相觸媒,具有易於分離觸媒的優勢,具工業化潛力。本研究嘗試利用廢電池中的鋅作為催化劑用以解聚 PET 成單體對苯二甲酸乙二酯(BHET),並深入討論影響反應進行的因素與發展應用。利用廢電池中的鋅作為催化劑不但成本低廉,也更能符合本研究的核心「綠色化學」。 本研究已透過最適化條件搜尋,發現能在催化劑使用量為 0.2 克、反應時間 4 小時、反應溫度 180 度時,解聚 5 克的 PET,有最佳效果之 BHET 產率 75.8% 和 PET 轉化率 93.2%。根據最適化反應條件,並比較不同種的鋅化合物做為催化劑,發現廢電池中的鋅作為催化劑催化反應,具有較佳的轉化率與產率。

多邊形的剖分圖形數量之探討

從參考資料[1]可知,將凸n+2邊形利用n-1條不相交的對角線剖分成n個三角形的圖形數量即為卡特蘭數Cn。而我利用不相交的對角線把n+2邊形剖分成數個多邊形和三角形的組合,並從此類的剖分圖形與三角剖分圖形之關聯,進而由卡特蘭數的一般式推導出此類剖分圖形數量的一般式。在本研究中可得,若到把n+2邊形剖分成一個k+2邊形和多個三角形的圖形數量是(2n-k+1 n+1) ;把n+2邊形剖分成一個k+2邊形、一個m+2邊形和多個三角形的圖形數量,當m≠k,數量為n+2/2(2n-k-m+2 n+2) ,當m=k時,數量為n+2/2(2n-2k+2 n+2) ;把n+2邊形剖分成一個k1+2邊形、一個k2+2邊形、一個k3+2邊形、和n-k1-k2-k3 個三角形的剖分圖形,當k1,k2,k3兩兩相異時,數量為(n+2)(n+3)(2n-k1-k2-k3+3 n+3) ;把n+2邊形剖分成一個K1+2邊形、一個K2+2邊形、一個K3+2邊形、一個K4+2邊形和n-K1-k2-k3-k4個三角形的剖分圖形當k1,k2,k3,k4兩兩相異,數量為(n+2)(n+3)(n+4)(2n-k1-k2-k3-k4+4 n=4)。並猜測若k1,k2,...,ki兩兩相異時,把n+2邊形剖分成一個k1+2邊形、一個k2+2邊形、…、一個ki+2邊形、和n-Σkj 個三角形的剖分圖形數量為(n+i)!/(n+1)!(2n-Σkj+i n+i) 。

An Easy Method to Discuss Properties of Simplified Solid-state Tesla Coil

Wireless transmission products are widely used in our daily life. In this research, we focus on knowing how solid-state tesla coil works in different conditions and finding the best parameters through an easy way. In our work, a commercial electroscope was used as detector for measuring the strength of radio wave created by our simplified tesla coils. In fact, many factors would lead to experimental erorrs such as detectors, selected types of NPN BJT components, applied voltage and measuring position of height. Therefore, all of the factors were under control to make sure of accuracy and precision for our designed measuring method. In our experiment, graphics of radio wave distribution around tesla coils were drew by mathemetic software of GeoGebra. It shows the BJT types of 2n2222 had good performance for wireless transmisstion efficiency. To our surprised, we found the extended wires (called antenna) from the top of tesla coil also had an ability to transfer electromagnetic energy, and had good retention if the extended wires were within the length of main coil’s height. Finally, the shape’s and size’s effect was determined by our testing work. The result shows that pipe’s length, pipe’s diameter and turns ratio of two coils had great influence on tesla coil’s transmission efficiency. It was found that the tesla’s performance would be more efficient if wire was used to make the length twice rather than make the diameter twice. However, the turns ratio of secondary coil to primary coil would change while making the length twice. To avoid that, we fixed the length and decrease the turns of primary coil. At last, we found tesla coil must work at the turns of primary coil higher than two. Furthermore, the frequency of radio wave not only had less relationship with their length or diameter but also had less relationship with types of BJT In our study, our handmade tesla coil was succesfully applied for wireless charging and we find that the induced voltage decrease in propotion to cube root of distance between tesla coil and induced coil.

以新型CRISPR-Cas9技術優化粒線體基因剪輯

本研究開發一個新型的CRISPR-Cas9技術剪輯粒線體DNA,提供粒線體基因所造成疾病的一個有潛能之治療方式。在本研究中,我們將嵌入粒線體標的訊號序列後的 Cas9 蛋白質和 sgRNA 分子送入粒線體內,將 CRISPR-Cas9系統套用於粒線體中,並達成剪輯粒線體基因之目的。我們將 Cas9 蛋白質和 sgRNA 分子鑲嵌於同一質體上,有效導入CRISPR-Cas9系統於粒線體內,並觀察到剪輯之標的基因ND4含量下降了 32%,達到粒線體基因編輯之目標。雖然前人曾用ZFN (Zinc-finger Nuclease)和TALEN (Transcription Activator-like Effector Nucleases)成功編輯粒線體基因,但由於製作過程繁瑣和經費昂貴等種種原因,並未被廣泛使用。我們開發的新型CRISPR-Cas9粒線體基因剪輯系統將可以提供一個相對簡易且價格低廉的粒線體基因剪輯平台。

Consensus-based Machine Learning Model in the Scoring for Hepatic Steatosis Severity

研究目的:脂肪肝的盛行率在全世界的現代化國家都在增加。病理醫師在評估脂肪肝的嚴重等級時,常缺乏參考意見以減少差異。許多地區也缺乏病理醫師。本研究旨在建立一個有效評估脂肪肝嚴重程度的病理組織學人工智慧模型。研究過程:本研究經由臺中榮民總醫院人體研究倫理審查委員會審核通過,篩選後取得病理資料庫中適合的肝臟組織切片,由兩位病理醫師獨立為肝組織中脂肪堆積的程度評分。再以病理醫師討論後的共識答案為分級標準,來訓練人工智慧模型。研究結果:在100個樣本的獨立測試中,人工智慧模型和病理專科醫師的評分,有71%完全相同、27%差異只有一個等級、2%差異2個等級、而沒有2個等級以上的差異。結論及應用:我們已初步建立一個可以評估脂肪肝嚴重程度的人工智慧模型。這模型可為將來人工智慧的臨床應用,建立一個良好的基礎。

滾動體在旋轉圓盤上運動之軌跡探討(The motion of a rolling sphere on a rotating disk)

球體在旋轉平台上的運動分三階段:進動階段、螺線振盪階段、打滑階段。進動階段、螺線振盪階段為兩個運動模式的疊加:迴旋半徑漸增的螺旋線運動、向平台中心靠近的平移運動。當迴旋半徑漸增至滑動摩擦力的上限值,球進入打滑階段並向外甩出平台。 研究紀錄球體質心運動參數,並以接觸點準靜態理論計算及滑動-滾動摩擦模型進行數值分析,找出各種變因與運動參數間的關係。 結果發現滾動階段中鋼球作迴旋運動的頻率f球和平台旋轉頻率f盤和有正比關係,且比例值和球標準化轉動慣量δ正相關。由滾動階段過渡到滑動階段的最大迴旋半徑Rmax和f球2成反比、和δ呈負相關、和滑動摩擦係數μk成正比。滾動摩擦使球向平台中心靠近,也使迴旋半徑漸增。平台傾斜或呈錐狀時,球體的運動會向水平方向偏移。