2025年

Energy has had an enormous impact on the development of technology and is a main factor in humans’ advancement towards an evolved society. Nevertheless, nonrenewable energy resources – which are the most effective in everyday application - have led to changes in the climate, environment, human health, and the world in general [1], which has encouraged researchers to switch to the use of renewable energy sources. Solar Cells are one of the most effective resources that rely on renewable energy. They come in a variety of types, operation methods, and efficiency as shown in Figure 1, including Dye-Sensitized Solar Cells (DSSC), which, inspired by photosynthesis in plants, uses photo-sensitive dye to capture sunlight and generate electricity. DSSCs were proved to have generated a great deal of interest and are one of the most promising solar cells among third-generation PV technologies, due to their low cost, simple preparation, good performance, and environmental friendliness compared to conventional photovoltaic devices [3]. However, their efficiency is quite insufficient for everyday use. Previous studies proved that Tandem DSSCs – which are two dye-sensitized cells stacked on top of each other – are able to enhance cell performance. The light absorption range of a tandem cell is increased because the bottom cell behind the top one absorbs and uses the incident light that was not absorbed by it [4]. It operates as shown in Figure 2, where the light photons excite the electrons of the dye molecules. The electrons are then transported to the FTO (conductive glass) by the semiconductor, which is used in the figure as TiO2 nanoparticles. The electrons pass through the circuit to perform the work, then move to the counter electrode (shown as Platinum). They are then transported by the electrolyte (I-/I3-) back to the dye molecules, and the process is repeated.

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.

In this paper, I investigated the motion of a nonlinear coupled oscillator system consisting of two leaf springs secured to a non-magnetic base with magnets attached to the upper ends such they repel and are free to move. My results showed that the system exhibits the beats phenomenon, and interestingly that the frequencies show a dependence on initial conditions. I hence hypothesized this sensitivity is due to two sources of nonlinearities: geometric nonlinearity during large deflections of the leaf springs and the nonlinearity in the magnetic force. To test this hypothesis, a nonlinear mathematical model was developed, accounting for nonlinear beam effects up to third order and fully solving the nonlinear magnetic force using a current cylinder model, accounting for the tilting of the magnets. An approximate linear model was also developed for comparison. The theoretical models were validated experimentally by investigating the dynamic motion of the springs through time, as well as how the modal frequencies in the system depend on the initial displacement, the length of the spring, and the distance between the springs. The more accurate nonlinear model I derived shows good agreement with experimental results while the linear theory does not, highlighting the importance of nonlinearities in this system. An improved understanding of these nonlinear systems could lead to advancements in design and efficiency, and safety in various applications such as energy harvesting.

This thesis presents the design and construction of a small-scale humanoid robot, covering all aspects from 3D modeling to electronics design and programming. The robot is built entirely from custom 3D-printed components, with a new servomotor developed specifically to meet the project’s requirements. During the robot’s development, custom electronics were also designed, leading to a modular platform that enables easy interaction with diverse modules like servomotors and inertial measurement unit (IMU) modules. This modular approach allows these components to be programmed and controlled with minimal adjustments, as well as making development of potential future modules straightforward. The robot is operated via a computer application that includes a graphical user interface for displaying real-time data from the robot.

One of the main factors that contribute to fire incidents and the excessive heat people feel during a heat wave is the building materials used, and one such material that possesses durable and heat-resistant properties is sandwich panels. A possible structure that can be used to model sandwich panels is honeycomb structures; however, further research has yet to be conducted on its applications as a heat-resistant urban construction material. This study aims to design a three-dimensional model of a honeycomb sandwich panel and simulate its performance under different thermal and structural stressors. A 3D model of the honeycomb sandwich panel was generated using Autodesk Fusion 360. Then, multiple versions of the panel were generated with varying heat-resistant core materials—namely, aluminum, nickel, nickel-copper alloy 400, and copper—along with polystyrene as the core material for the control model. The following properties of every panel were assessed using finite element analysis (FEA): static deformation, stress distribution, strain distribution, total heat flux, and thermal gradient. Results showed that when subjected to varying structural loads (2 kN, 5 kN, 7 kN), the nickel-core panel demonstrated the best results in terms of static deformation and strain distribution due to its relatively lower deformation and elongation values, respectively. Meanwhile, under the same structural loads, the aluminum-core panel performed better than other core materials in terms of stress distribution due to it having the relatively highest difference between its simulated von Mises stress and its yield strength. The honeycomb sandwich panels have also shown to possess heat-resistivity when subjected to a thermal load of 90°C, with polystyrene being the most promising material overall in terms of heat-resistance due to its relatively lower heat flux and thermal gradient. The results from this study would contribute to future research on honeycomb sandwich panels and may be used in real-life applications.

Due to their pollination services, honeybees are one of the most ecologically vital animals, being singlehandedly responsible for nearly 80% of global agricultural pollination [1]. However, in recent years, they have experienced large declines in populations, and as a survey reported roughly 50% of beekeepers in the US lost their honeybee colonies [2]. These losses are experienced globally due to a combination of many factors, including but not limited to habitat loss, pesticides, climate change, and other invasive species [3, 4]. One of the biggest factors attributed to the decline of honeybee colonies is the usage of pesticides, specifically neonicotinoids [3-6]. Neonicotinoid compounds have been used globally since their introduction in the early 1990s [4]. Studies have shown that neonicotinoids can have both sublethal and lethal effects on honeybees, depending on the dosages that they are exposed to, as neonicotinoids bind to nervous system receptors of honeybees [7]. These effects can range from behavior changes to altered motor functions [7-9]. Among the reported effects, one of the more significant ones is the effect of neonicotinoids on honeybee learning and memory [10, 11]. Additionally, there is a lack of availability for methods of monitoring of honeybee hives, essentially meaning that the only methods to track honeybee health are through obtrusive physical methods of inspection. This paper aims to develop a novel AI-based honeybee health assessment system, able to monitor beehives using the following functions: continuous temperature and humidity monitoring both inside and outside the hive, as well as video and audio recording to assess honeybee health as well as population. In addition, this system can be used for honeybee-related studies such as nutrition effects and evaluation on health, learning, and memory. To do this, four types of nutrition have been studied and their effects have been analyzed by a deep learning approach.

Carbon capture and storage technology (CCS) has tremendous potential to enable the use of fossil fuels while reducing the emissions of CO₂ into the atmosphere, and, consequently, combating climate change. CCS faces several challenges such as energy consumption, cost, low practical applications and environmental friendliness. In this work, a new approach to carbon capture that is not energy intensive is proposed.

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.

本研究記錄人類進行「剪刀石頭布」遊戲時的決策行為，也設計T型迷宮建立鼠婦之負趨光行為作為動物模式，探討行為偏好與決策依賴性等特性。我們發現「出石頭」的機率較高，且時間間隔縮短後，「出剪刀」的機率增加而「出石頭」的機率減少，並會展現負相關的決策經驗依賴性，其中「慢出組」更為明顯，代表出拳間隔縮短而減少意識作用，負相關的決策經驗依賴性即會減弱。另一方面，鼠婦在負趨光性刺激剛消失後，仍呈現負趨光性的選擇方向，具有習慣性。鼠婦在選擇行走方向多次後，會呈現與前次選擇的正向相關性。在負趨光性的環境刺激後，上述的現象會先消失，而後再現。若負趨光性刺激方向轉換，則原先的趨光行為消失，應是因方向選擇的習慣性干擾了負趨光性的選擇。

Fungal infections, particularly those caused by resistant strains like Candida auris and Candida glabrata, pose a significant threat to global health. The widespread use of azole antifungals, such as fluconazole, has driven the emergence of multidrug-resistant strains, undermining the efficacy of existing treatments. These challenges necessitate the development of novel antifungal agents with enhanced activity and reduced resistance profiles. To address resistance mechanisms, we designed and synthesized hybrid molecules combining triazole and thiazolidine-2,4-dione (TZD) pharmacophores. This strategy leverages dual mechanisms of action: inhibiting fungal CYP51, a key enzyme in ergosterol biosynthesis, and disrupting fungal cell wall integrity. The structural versatility of hybrid molecules allows for targeted modifications to enhance antifungal potency, binding specificity, and pharmacokinetics. Using a stepwise synthetic approach, triazole-containing piperazine derivatives were first prepared and coupled with TZD-based carboxylic acids via optimized condensation reactions. The structures of the synthesized compounds were confirmed through advanced spectroscopic methods, including 1D/2D NMR and high-resolution mass spectrometry. The antifungal activity of these hybrids was evaluated in vitro against clinical and reference strains of Candida spp. and Aspergillus fumigatus. Among the synthesized compounds, 6a demonstrated notable activity against Candida parapsilosis (MIC 0.06 μg/mL), comparable to voriconazole. Compound 4b exhibited moderate activity against C. parapsilosis (MIC 1–2 μg/mL) and A. fumigatus (MIC 8 μg/mL). However, most compounds showed limited efficacy against highly resistant strains such as C. albicans 8R and C. krusei. This study highlights the potential of hybrid triazole-TZD molecules in overcoming resistance and improving antifungal efficacy. While promising, further optimization is required to broaden the spectrum of activity and enhance efficacy against multidrug-resistant pathogens. These findings contribute to the growing field of antifungal drug development, emphasizing hybrid approaches as a viable solution for combating fungal resistance.