東莨菪鹼 (Scopolamine) 是一種乙醯膽鹼受體的拮抗劑，如果服用過量的Scopolamine，可能產生記憶障礙的症狀，所以Scopolamine常作為讓實驗動物記憶能力下降的藥物。近年來全球人口老化速度快，像是阿茲海默症等疾病患者與日俱增，研究記憶的相關機制或能恢復記憶的治療方式成為重要課題。希望本研究能對Scopolamine的作用有更多了解，作為未來以此藥物當作前置實驗藥物的參考。斑馬魚 (Danio rerio) 是一種群居動物，牠們會依據對彼此的熟悉程度而調整未來的社交行為，所以能夠辨識並且記得曾經看過的魚對牠們十分重要。因此本研究選擇斑馬魚作為實驗動物，錄影觀察藥物對牠們記憶和社交行為的影響。 本研究將以斑馬魚的社交記憶 (Social recognition memory) 為主題，探討Scopolamine對斑馬魚學習與記憶能力的影響，以及受藥物影響後的社交行為改變。實驗藉由錄影觀察斑馬魚浸泡Scopolamine 溶液後的行為改變，包括電擊、社交偏好，群游，攻擊性實驗，推測Scopolamine有降低學習能力並在學會的情形下增強記憶的效果，而且能改變斑馬魚的部分社交行為。

探討經由抑制Hippo途徑，誘發受接觸性抑制之人類角膜內皮細胞(HCEC)增生及其機轉之研究。 研究過程 以攜帶YAP基因之質體轉染培養之受接觸性抑制之HCEC，或添加溶血磷脂酸(LPA)後，觀察HCEC之YAP蛋白核轉移、細胞分化及增生。再利用專一性激酶抑制劑探討可能之訊息途徑。 研究結果 轉染之YAP能顯著誘發HCEC細胞增生，同時保有其功能。LPA能誘發HCEC的YAP蛋白核轉移，進而增進HCEC細胞增生。而PI3K與ROCK抑制劑能顯著抑制HCEC的YAP蛋白核轉移及細胞增生。 結論 LPA能誘發YAP蛋白核轉移與受接觸性抑制之HCEC細胞增生，此現象應與PI3K及ROCK途徑之活化有關。 應用 此研究提供了一種創新的誘發細胞增生策略以用於移植或細胞療法。

近年來，螢光材料已經被廣泛用在染料敏化太陽能電池與有機發光二極體的敏化劑。然而，大多數的螢光材料皆含有鑭系元素以提供能階差供電子在基態與激發態間躍遷。在這個研究當中，即使不使用鑭矽元素，依然可以合成出具有高量子產率的光致發光材料。因為TPB(1,2,4,5–tetra(4-pyridyl)benzene)，有機胺類的一種，我可以不藉由鑭系元素而合成出各式各樣的螢光材料。本研究所合成的材料不僅較便宜，而且其放光光譜具有相當的變化性。因為這些化合物用有如此獨特的螢光特性，故這些材料具有作為感應材料的潛力。

Revealing fascinating and educating concepts in a field of astronomy usually requires expensive equipment. Therefore, most schools have very little practical equipment to teach astronomy. I wanted to investigate the Sun’s track using a simple apparatus that can be afforded by many schools instead of using an expensive one.

Ukraine as a whole, as well as Poltava Region in particular, have a problem with the state of atmospheric air pollution, because the vast majority of motor vehicles and industrial, energy, and mining enterprises are not equipped with proper cleaning filters. A clear confirmation of the ineffectiveness of Ukraine in matters of monitoring the condition and protection of the atmosphere, in comparison with European countries, was the scandal with the manipulation of exhausts of the Volkswagen concern (Dieselgate). Diesel engines use a catalyst with injection of a urea solution (AdBlue), or a catalytic converter built on the principle of accumulation of nitrogen oxides on a metal surface made of barium compounds . Synthetic urea in automotive catalysts transforms dangerous nitrogen oxides into harmless nitrogen and water . However, due to the software, during everyday use of the VW engines in question, this function remained disabled and the catalytic converter was simply removed. However, we see such cars, along with others, even more morally and technically outdated, on the roads of Ukraine every day. The practice of burning stubble in spring and autumn also leads to extreme consequences of air pollution. The morally outdated system of monitoring the state of the atmosphere, which has remained in Ukraine since Soviet times, is not able to show the real state of pollution, and the lack of proper control on the part of the state leads, in general, to the worsening of the situation every year. Environmental problems in the country in general, and in Poltava Oblast in particular, are the cause of the spread of cancer and high human mortality. Almost 80,000 people die of oncology in the country every year. According to 2020 data, the mortality of the population of Poltava Oblast from non-communicable diseases exceeds the average indicators for Ukraine: Ukraine – 1,597 people per 100,000 population, Poltava Oblast – 1,793 people per 100,000. Therefore, the relevance of the problem raised is extremely high, and it is necessary to start with monitoring air pollution and raising the problem at the national level, because most of the country's residents do not even know what kind of air they breathe at home and on the street.

研究探討透過強化學習讓機器學習各種人類上臂運動。延續「運用氣動肌肉缸模擬上臂肌肉控制之研究」，透過有限的動作組可以控制上臂肌肉，然而因應環境條件的多變，模擬人類透過學習產生多樣多變的反應，在仿生的領域中有其必要。比較強化學習中的Actor-Critic與 DDPG (Deep Deterministic Policy Gradient)兩種模式，我們透過 Gym 建構具動作與環境限制的簡易訓練環境。比較兩個模型的細節後，最後選用了 DDPG 為我們主要的強化學習方法。首先我們利用 Tensorflow 模擬學習模式並記錄模擬移動的學習過程。我們運用到仿生手臂的實體，藉由影像辨識取得手臂的狀態，回饋至學習模型。仿生手臂運用學習資料進行移動，接著我們觀測系統所學習的移動是否可完成指定動作或工作。在軟體模擬中，我們證實了藉由達成數次目標的學習後，DDPG 可完成較細緻的移動。而 DDPG 在仿生手臂上的實作，則需透過輸出動作給氣動仿生手臂系統，來控制仿生手臂移動至目標位置。在未來，機器人將不單單只是運用馬達來當作動力來源，也能運用氣動肌肉缸成為動力元件。並且，人形機器人將會做出更像真實人體的動作。

本研究在探討過原點且通過特定格子區域中格子點的直線數，利用縱向或橫向方式來計算。不論哪一種方式皆從正方形區域探討，得到其格子直線數與歐拉函數有關，特別是在橫向方式中增加上高斯符號與高斯符號協助計算，得到正方形、長方形、三角形及圓形區域的直線數及其上下界，及探討上下界的特定區域。此外，將原點移動到任意點，探討過任意點且通過特定格子區域中格子點的直線數，得到一些有趣的性質。 接下來，從正方形區域推廣至高維度的超立方體區域中的直線數，並推導出三個歐拉函數的推廣式，其中一種是約當囿互質函數，使用這些函數不僅能簡化計算，更能拓寬歐拉函數的視野。另外二種皆是利用幾何結構推導出來，其中一種是用第二類史特林數來表示。 最後我們使用此歐拉函數的推廣三式推導出高維度的超立方體、超長方體、單體 (即高維度中廣義三角形區域)及角錐柱中的格子直線數及其上下界，特別是利用橫向方式獲得公式的更為精簡。

The quick increasing energy consumption arouses the interest in the development of power storages. Electrochemical supercapacitor is one of clean and sustainable candidates of energy storage system, and porous carbons are the most potential candidate as electrode materials for electrochemical supercapacitor because of their large surface areas, high chemical and physical stability, good conductivity, as well as low cost. In this work, we synthesized the mesoporous carbons by using ZnO nanoparticles as sacrificing template via nano-casting synthetic process and natural porous carbon materials. The synthesized porous carbon has a mesoporous structure. Because the surface area and pore size of the synthesized mesoporous carbon are larger than that of the coconuts fiber-derived carbon, the CV plots show that the synthesized mesoporous carbon has a good rectangular shape and a much better performance than that of the coconuts fiber-derived carbon. We also develop an easy way to discriminate how well a supercapacitor works. We applied these porous carbon-based electrodes on both handmade as well as the commercial capacitors and measured their electrical performances. The handmade EDLC is less efficient than the commercial capacitor.

本研究共設計十二個實驗，探討垂直型風力發電機如何將各方吹來的風充分利用，首先設計能減少風力扇葉轉軸轉動摩擦力的軸承，接著製作導流罩以收集所有吹進來的風並提高 磁動生電的轉換效率。我們製作的風力發電機將來自四面八方的自然風有效利用，具積少成 多的集風特性，輸出電壓可達30V以上，並能針對鋰電池充電，發揮以時間換取空間的特殊功能，且因為體積小，非常適合於臺灣地狹人稠而且風力不強的環境。我們將自製的發電機實際應用在學校走廊、樓梯間以及樓頂進行發電，可以提供夜間照明，達到自給自足的綠色能源目標。

Double Parallelogram Lifting Mechanism (DPLM) is a compact and stable lifting mechanism with a large extension range widely adopted in robot designs. Rubber bands and springs are often installed on the DPLM to lighten the motors' load and maintain its height, yet the installation positions are often obtained through trial and error. This project aims at finding the optimal rubber band installation positions for DPLM using modeling and optimization techniques. A mathematical model which describes the forces and moments acting on all the linkages of DPLM was derived based on the conditions for the static equilibrium and verified with a 3D simulation software. A genetic algorithm (GA) was implemented to optimize rubber band installation positions, which managed to find solutions with the overall root-mean-square- error (RMSE) of the net moment less than 2 for 2 to 6 rubber bands. A further statistical analysis of 50000 random rubber band samples showed that installing rubber bands in triangles is the best solution with the overall lowest RMSE. A test was conducted with a prototype of the DPLM and the results were consistent with our model and optimization. This project derived and verified a mathematical model for the DPLM, and found the optimal way and positions to install rubber bands. The results of this project provides a theoretical basis for controlling DPLM with rubber bands, allowing it to be further adopted in industrial robots that require repetitive lifting and lowering such as inspection robots and aerial work platforms.