本研究結合奈米合成技術與生物醫學， 利用表沒食子兒茶素沒食子酸酯 (Epigallocatechin gallate, EGCG) 作為載體 調控摻雜Cu2+/Cu3+與 Fe2+/Fe3+之含量 並以π-π交互作用力附載缺氧性抗癌藥物替拉扎明 (Tirapazamine, TPZ) 成功製備出多功能金屬多酚配位奈米顆粒簡稱為EFeCuTPZ。 材料經紫外-可見光譜 (UV-vis)，、動態光散射 (DLS) 及掃描式電子顯微鏡 (SEM) 確認其粒徑大小、形貌學與穩定性。利用808 nm和671 nm雷射分析其光熱轉換效率 評估光熱療法效果，。在腫瘤微酸性環境下， EFeCuTPZ可利用高濃度之H2O2行芬頓反應 (Fenton Reaction) 產生高活性之氫氧自由基 (•OH)， 展現化學動力療法 (Chemo dynamic-therapy, CDT)，。同時， 藉由材料中的Cu²⁺與腫瘤環境中的穀胱甘肽 (Glutathione, GSH)反應減少高活性物質 (Reactive oxygen species, ROS) 的消耗 增強CDT之療效。酸性條件下 TPZ顯著釋放 有助於腫瘤治療。 另外， 細胞實驗顯示EFeCuTPZ具有高生物相容性與治療效果， 成功開發出具CDT，、CT及PTT功能之奈米複合材料 為醫學新興藥物材料提供可能性。

Carbon dioxide (CO2) is an important greenhouse gas that helps trap heat in our atmosphere; without it, our planet would be inhospitably cold [1]. It is the fourth most abundant gas in the Earth's atmosphere. It is a byproduct of normal cell function when breathed out of the body, and produced when fossil fuels and organic wood compounds are burned [2]. However, an increase in CO2 concentration in the atmosphere can contribute to climate change and ocean acidification, and exposure to high levels of CO2 can produce a variety of health effects [3]. Human progress and economic innovation have led to increased emissions, causing climate change and affecting all living creatures. Current levels are 36.8 Gt CO2 in 2023 and are expected to reach 54-56 Gt CO2 by 2030 [4]. Figure 1 displays the current atmospheric CO2 measurements at Mauna Loa Observatory without seasonal variations [5].

鈣及攜鈣蛋白調節酶(CaMKII)存在於大部分細胞中，研究顯示其在多種癌細胞中過度表現。苯基磺醯胺衍生物為CaMKII抑制劑的常見結構，而吲哚與靛紅是常見藥物結構，因此本研究參考文獻[1]，並擴展臨床尚未解決問題，優化此兩類衍生物以製成抗癌藥物。第一系列以苯基磺醯胺為主架構，改良文獻[1]中抑制效果最佳的化合物1，第二系列則修改吲哚與靛紅的取代基，設計出多種候選分子。初步利用分子模擬分析軟體(Discovery Studio)模擬蛋白質與藥物分子結合，考量結合能、結合方位、藥物取得及合成難易度，選定有潛力的WACY與CYWA系列結構進行合成。本實驗使用創新的步驟合成，簡易、高效率且符合綠色化學，再經核磁共振與高解析度質譜儀驗證得出高純度產物。最後根據生物檢測發現WACY-2對乳癌細胞毒性高和對於一般乳腺細胞和乳癌細胞的選擇性都較市售抑制劑KN-93佳，而WACY-6對CaMKII抑制效果為WACY系列最佳；CYWA-2, 3, 6, 7對乳癌細胞的毒性和對CaMKII抑制效果又優於KN-93與WACY系列許多。本研究成功製備出符合理論計算預期且抑制蛋白質的效果較KN-93佳的化合物，未來極具潛力作為抗乳癌的標靶藥物。

Stroke is a very common disease, almost a national disease. In terms of stroke frequency, 匈牙利 ranks second in the world. Every year, 40-50 thousand people become paralyzed or permanently injured as a result of cerebrovascular disorders. This number is three to four times higher than in developed countries. Almost every Hungarian family is affected! Of course, saving the life of someone who has a stroke is the most important thing, but rehabilitation is also very important, since only with the help of a physiotherapist will the patient be able to live a full life.

The equation of an ellipse and quadratic residues are well-known concepts in elementary geometry and number theory, respectively. While the properties of ellipse equations in Euclidean space have been extensively studied, many characteristics of quadratic residues, such as consecutive quadratic residues, have also been explored in past research. In this study, we discovered the characteristic polynomial of the equation of an ellipse over finite fields Fp, a single-variable polynomial that shares the same roots as the ellipse. Furthermore, by examining the parallels between the equation of an ellipse and the pairs of residues and nonresidues, we derived a characteristic polynomial for this concept and demonstrated its connection to the Catalan number, a significant sequence in combinatorics. This research was conducted through the following steps. First, the power sums of the roots of the ellipse in Fp were calculated using the Legendre symbol and Euler’s criterion. Next, the characteristic polynomial of the ellipse was determined using Newton’s identity, generating functions, and Vieta’s theorem. Finally, leveraging the equivalence between the equation of the ellipse and the pairs of residues and nonresidues, we established the main results connecting these two concepts with Catalan numbers.

On average, the agricultural sector uses 70% of water withdrawals worldwide to produce crops1 and contributes to the eutrophication of lakes by using nutrients that are leached from the soils into lakes and reservoirs2. Vertical farming has great potential to remedy some of these issues. By growing plants vertically in controlled environments with artificial light and reusing the water, vertical farms use op to 99% less water3 and can produce up to 10 times the yield per square meter4 compared to traditional greenhouses. This improved efficiency comes at a cost; on average, vertical farms use more than 600% more energy per kilogramme of crop compared to traditional greenhouses5. 55% of this energy use is due to the use of artificial lighting6. Even though a lot of research is conducted on yield optimisation of crops in vertical farming, few research articles focus on the growth efficiency of crops to reduce the energy use in vertical farms. Only a few previous studies have tested photoperiods under 10 h·d-1. This study focuses on reducing the energy costs of light use in vertical farms by finding the photoperiod with highest energy use efficiency for the leafy vegetable arugula (eruca sativa). Energy use efficiency is defined as fresh mass per unit of electricity input (measured in kWh). In this study, arugula plants were exposed to LED growth light, with photoperiods ranging from 0 h·d-1 to 24 h·d-1 (0 h·d-1, 4 h·d-1, 7 h·d-1, 9 h·d-1, 12 h·d-1, 14 h·d-1, 16 h·d-1 and 24 h·d-1) and a PPFD of 800 μmol·m-2·s-1. The photoperiod 7 h·d-1 had the highest energy use efficiency of all photoperiods and, if used in vertical farms, this could account for approximately a 10 percent decrease in energy per kilogramme used in vertical farms (a 4 kWh decrease), with the planting density of 1400 plants per m2. This could amount to a yearly energy saving of 4,000,000 kWh per vertical farm (based on the yearly harvest of the vertical farm Nordic Harvest). This could help make vertical farming a more sustainable plant production for the future and in turn, help farming protect our water resources instead of consuming and polluting.

The following issues associated with soil affected by wildfires were identified: First, there was a significant decline in the populations of anaerobic and aerobic soil bacteria, which play a critical role in the decomposition and cycling of organic matter. This decline resulted in reduced water retention capacity and porosity of the soil, leading to poor moisture retention and increased evaporation compared to unaffected soil. Moreover, the organic matter content in the soil was significantly depleted, inhibiting plant growth. Additionally, there was a notable proliferation of methane-producing bacteria, which contribute to the greenhouse effect. It was further observed that fire-damaged soils exhibit limited natural recovery, even over prolonged periods. .An investigation into the underlying causes of these problems revealed that actinomycetes, the primary microorganisms responsible for producing watersoluble aromatic compounds in soil, are particularly sensitive to heat compared to other bacterial species. Research demonstrated that the population and diversity of actinomycetes are significantly diminished in soils exposed to wildfires. To mitigate these issues, water-soluble aromatic compounds produced by actinomycetes were extracted and introduced into wildfire-affected soil. This intervention promoted the restoration of actinomycetes populations, enabling their normal growth in the affected soil. Consequently, various wildfire-induced soil problems were effectively resolved. These outcomes were confirmed through the study...Key Words: Actinomycetes, anaerobic and aerobic soil bacteria, methane-producing bacteria, wildfires, water-soluble aromatic compounds.

Previous research observed increased TNTs formation between hypoxic and normoxic neuroblastoma cells, aiding hypoxic cell survival. CHGA was identified as a potential factor in this process. This study compared CHGA expression and whether CHGA exists in TNTs in five cell lines, with SH-SY5Y showing the highest levels, followed by SK-N-BE(2)C, while the other three showed lower expression. Future studies will focus on the impact of CHGA on cell survival and its mechanisms.

Current research shows Northern Guam to be composed of porous limestone bedrock which allow groundwater to flow out. One large discharge point has already been identified last year in north-western Guam at Ayuyu Cave. However, little is known about Tumon Bay which is known to comprise karst watersheds which should allow for SGD. This project has examined invisible groundwater discharge using a salinity meter and was able to detect two areas of concentrated freshwater discharges in Tumon Bay, with a few minor ones scattered throughout the bay. These seeps were found to have consistently lower salinity while pH varied, and hosted more marine life than other high salinity areas. Further unique coral growth in Tumon Bay’s inner lagoon was associated with these two freshwater discharges with the pH levels further segregating the types of coral species found during on-site observation. Two coral communities, staghorn Acropora and massive Porites, were found adjacent to the surveyed groundwater seeps. It’s inferred that lower wave energy in eastern Tumon Bay allows for greater plankton and other microbial growth leading to more heterotrophic coral growth, favoring Porites corals, while Western Tumon Bay has higher wave energy which leads to the growth of more autotrophic corals, such as the Acropora found in the first area surveyed. This is the first study to document the presence, location, and consequences of invisible freshwater discharges across the billion-dollar bay. This study gauges the effects of SGD on inner shore habitats, also providing a coral cover assessment across Tumon Bay using transects and quadrats. These discoveries allow for strategic coral planting, designated areas needing government protection, and show areas of appealing inner lagoon coral growth for tourism.

This report presents a novel AI-driven tool for aiding musical composition through the generation of chord progressions. Data acquisition and analysis are discussed, uncovering intriguing patterns in chord progressions across diverse musical genres and periods. We developed a range of deep learning models, from basic recurrent networks to sophisticated Transformer architectures, including conditional and style-based Transformers for improved controllability. Human evaluation indicates that, within the context of our specific data processing methods, the chord sequences generated by the more advanced models are practically indistinguishable from real sequences. The models are then integrated into a userfriendly open-source web application, making advanced music composition tools accessible to a broader audience.