2025年

Semisynthetic penicillin, Amoxicillin, is a broad-spectrum antibiotic that is widely used to treat bacterial infections in children suffering ear, nose, and throat infections, genitourinary tract infections, skin infections, and lower respiratory tract infections1. This antibiotic works against both gram-positive and gram-negative bacteria, such as Listeria monocytogenes, Haemophilus influenza, Streptococcus pneumonia , Streptococcus pyogene and Escherichia coli1,2. It shows antibacterial activity by inhibiting dd-transpeptidase, which maintains the integrity of the bacterial cell wall which results in bacterial cell death due to a fragile cell wall3. Nonadherence to medication was associated with 50% of drug-related hospitalizations in children4. In order to improve adherence and influence clinical outcome, it is important to acknowledge the importance of drug palatability to children4–6. The currently available liquid suspension form of this antibiotic is administered to patients through oral/GI routes. It is also available in capsules or tablets for adults7–9. In the gastrointestinal tract, the drug has to withstand variable pH conditions and enzymatic degradation , mucus and mucosal barriers to survive resulting in limiting drug bioavailability10,11. In addition to conventional drug delivery formulations, nanofibers can be used to deliver drugs orally, topically, and through buccal or transdermal routes12. Drug-loaded nanofibers offer many advantages as a delivery system, including their porous structure and their efficient delivery of various drugs and bioactive molecules including hydrophobic and hydrophilic drugs12–14. Considering that amoxicillin palatability can affect children patients’ compliance and due to the advantages of both nanofiber drug delivery system and drug delivery through buccal routes, hence, this project aims to prepare flavored electrospun nanofibers loaded with amoxicillin to mask the unpleasant taste of the drug for treating children with bacterial infection. Nanofibers loaded with amoxicillin can be applied between the child's gum and cheek, allowing the fibers to dissolve in mucus and penetrate directly into the bloodstream.

This paper presents a simplified but mostly accurate model for the acoustic mechanism of Seebeck sirens. We investigate the impact of key parameters, including the number and size of holes, as well as the angular speed of the disk, on the characteristics of the produced sound. The disk is fabricated using fused deposition modelling 3D printing, and we used a brushless motor, an air compressor, and a shotgun microphone to capture the generated sound. An order of magnitude analysis was conducted on the Navier-Stokes equation to formulate a simplified version. These simplifications allowed for a low computational intensity model relating volume flow rate to sound pressure level, which is used to predict the waveform of sound produced. Our findings reveal that the fundamental frequency of the sound can be precisely predicted by only the rotational frequency of the disk and the number of holes, a relationship validated experimentally. Notably, observed asymmetry in the waveform was attributed to skin drag effects, and this hypothesis was experimentally verified. Our model computes a solution in less than half a second on average: far less than the 21h 47min needed for a k−ω turbulent model to compute the same phenomenon. The research presents and verifies a simplified model of acoustic mechanics for the sound generated by rotating systems that require little computational resources, which can prove useful in situations where absolute precision is not required, in exchange for ease of computation. For more precise systems, this model serves as a foundation for quickly generating an initial design, paving the way for subsequent iterations using more comprehensive models. The developed model not only serves as a foundation for efficient preliminary designs but also contributes valuable insights into the intersection of fluid dynamics and sound production.

1.1 Short project summary My project involves the conceptualization and development of an innovative approach to modular self-assembling robotic systems. Through its ability to form any complex configuration, the system is highly adaptable to various scenarios and environments. Before delving deeper into the details of my project, I will provide an overview of my background and motivations. 1.2 Background Ever since I first watched the movie "Big Hero 6", I felt amazed by the applications of the so called “microbots”. From that point on, it made me always wonder what would be possible in the real world. When I did the research, I stumbled upon this field of modular robotics. Initially, I was unsure whether to embark on a project focused on electronics and robotics due to my background in programming. On the other side, this year gave me a chance to see the incredible performances of various projects at different science expos. Besides, I took part in the program of CANSAT LU and learned a lot during it, such as microchips, the control of miniature robotics, and the sensors of it. Finally, at school, I took the option Electronics where we dig into similar topics. With this accumulated knowledge and experience I felt confident enough to start this project.

Increasing energy needs alongside the urgent issues of chemical pollution has prompted the need for developing novel green energy sources. Nitrogen-based fertilizers are of fundamental importance for the ecosystem as their usage has increased eight times in the last fifty years [1]. On the other hand , increased use of nitrogenous fertilizers is followed by higher ammonia emissions, which are dangerous pollutants responsible for deterioration in biodiversity by means of eutrophication, acidification of soil and water, and climate change [2]. Ammonia has the2apacityy to bond with other pollutants including sulfur oxides and nitrogen oxides to create particles that cause smog, which is associated with lung disease. Ammonia also increases frost sensitivities and causes necrosis of many plant species [3.] Therefore, there is a need to properly manage the ammonia-rich nitrogen waste to decrease the environmental threat factors. Of the possible approaches suggested for ammonia waste treatment, the ammonia electro-oxidation reaction (eAOR) has various promising features for application in the energy sector. It is economically appealing because Ammonia can serve as an excellent hydrogen carrier due to its storage capabilities and existing transport infrastructure alongside having no net carbon emissions. Apart from this, it requires 95% less of the theoretical energy [4] to perform the process. But the reaction is kinetically slow [5], which has been a research obstacle during the development of (eAOR), due to factors ofmslow reaction rate and large catalytic overpotential that this process consumes an unnecessary amount of power [6]. Nickel-based catalysts are a promising solution to these problems, they are cheaper , more stable and easier to produce than electrocatalysts for water electrolysis which makes it highly energy efficient for widespread use on the industrial scale. N films deposited on the anodic side also allow the creation of N-containing products such as (NH42SO3) and nitrates, which can be converted into fertilizers or renewed into the nitrogen cycle to make the process more environmentally friendly while enhancing the (eAOR) process [7,8]. Compared to Pt and Ir which are the most used noble metals, they are less poisoned on the potentials less than 0.65V and are more stable [9,10]. However , noble metals are scarce, and their cost is high for industrial applications as well as the energy they waste during (eAOR) [11].

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.

When a leaf of a plant encounters stress, how does the plant convey the stress signal to other tissues and manage nutrient distribution? This field of study has been largely unexplored. However, the unique interconnected frond structure of Lemna trisulca, along with the use of a divided Petri dish, is very suitable for handling localized stress and investigating the mechanisms of intracellular signaling and nutrient distribution. Research has shown that when the mother leaf experiences localized stress, it releases healthy daughter leaves to minimize collateral damage to the daughter leaves. Conversely, when the daughter leaves face localized stress, the mother leaf chooses to retain them and continues supplying them with nutrients to support their survival. In-depth studies revealed that stressed daughter leaves accumulate Reactive Oxygen Species (ROS), triggering nutrient distribution by sending a distress signal to the mother leaf. This prompts the mother leaf to use Ca2+ as a signaling molecule to deliver nutrients to the daughter leaves. Selective detachment is regulated and triggered by the interaction between Ca2+ and ROS within the mother leaf. When the mother leaf undergoes stress, Ca2+ acts upstream to induce ROS accumulation at the nodes, sending a unidirectional detachment signal to the daughter leaves. This causes ROS accumulation at the daughter leaf nodes, inducing detachment and thereby reducing the collateral damage the daughter leaf could experience due to the mother leaves.

這是一份將近持續四年的研究，而這一年佩爾質數的出現，讓我們的討論「突飛猛進」。 佩爾方程式是形如𝑥2−𝑚𝑦2=1的方程式，其中𝑘不為完全平方數之正整數。我們定義廣義佩爾方程式是形如𝑥2−𝑚𝑦2=𝑛 的方程式。在過去的研究中，我們主要從𝑥2−𝑘𝑦2=𝑝 (𝑘,𝑝 皆為互質的奇質數) 的正整數解開始研究，接著延伸到 𝑥2−𝑘𝑦2=2𝑚𝑝1𝑛1𝑝2𝑛2⋯𝑝𝑗𝑛𝑗，進而得到了解的唯一分解性質。而本次的研究，延續之前的工作，對佩爾質數展開了討論。利用蜈蚣彘，我們成功地發現了一些佩爾質數，猜測出一些可能的結果並證明；同時我們對佩爾質數的生成結構做了相當程度的了解。作為結束，設法利用分析的方法解決的之前的問題，以及對方程式的不可約解，是否存在較低次方根解，給出了必要條件。

In this fast-paced digital economy, customers' judgment is based on their experience with a company’s products and services. Customer reviews become a vital source of information for companies because this information can be used to enhance their products, understand customer wants and needs, improve brand reputation, and provide a competitor’s advantage. A company can understand customer needs and wants by going through reviews. Customers are encouraged to leave not only their opinion but also their ideas for the development of the product or service. By understanding these reviews, a company can actively respond and engage with a reviewer or problem. Failure of companies who don't answer customer queries may negatively impact customer loyalty. Customers will feel neglected by these companies and will choose competing companies to handle their needs. Additionally, customers may speak negatively about a company that does not respond to reviews. The AI-based customer sentiment dashboard can help gain a company's competitive advantage by identifying weaknesses in themselves and others. Companies will be enabled to understand where they succeed and where improvement is needed compared to their competitors, leveraging businesses to address strengths and weaknesses before competitors do. Through AI-based customer sentiment dashboards, a company can analyze its competitor’s reviews and use that information as leverage to make improvements to its products and services. Customers are increasingly leaving reviews on popular apps like Google Play, Stamped.io, Yapto, and Judge.me, Loox, Qualaroo, and Yelp. The reviews are rich in customer sentiments offering valuable insights into user satisfaction and pointing out the areas for improvement that are crucial to every company no matter how big or small. Despite their value, manually processing these reviews is a challenging task due to the large volume of unstructured data. Manual processing is also vulnerable to bias and human error, leading to inaccurate information. Traditional methods such as surveys have been proven to be ineffective if the main focus is targeted feedback and have low responses compared to reviews. The advances in artificial intelligence like Natural Language Processing (NLP) help us interpret and analyze human language and generate outputs like predicting what type of sentiments are in reviews. This project proposes developing an AI-based sentiment analysis model to evaluate customer feedback on two widely used taxi applications. Natural Language Processing libraries, such as the Valence Aware Dictionary and Sentiment Reasoner (. The model aims to categorize customer reviews into positive, negative, and neutral sentiments.

The present research work aimed to assess the impact of biochar (BC) amendment (5%) and foliar supplementation of titanium (Ti) at a concentration of 50 mg L-1 TiO2 on the growth, chlorophyll content, and biochemical parameters of wheat (Triticum aestivum L). The results demonstrated significant improvements in several aspects of wheat physiology due to these treatments, both individually and in combination. Plant height, as well as fresh and dry weight of wheat, exhibited substantial increases when subjected to Ti and BC treatments, with the highest enhancements observed in plants treated with both Ti and BC. Furthermore, chlorophyll content, including chlorophyll a, chlorophyll b, total chlorophylls, and carotenoids, showed marked increases in response to individual Ti and BC treatments, with even greater improvements when both treatments were combined. In terms of biochemical parameters, the content of proline, sugars, and free amino acids significantly increased in plants grown in soils amended with BC. Additionally, foliar Ti treatment led to elevated levels of these biochemical constituents. The combined treatment of Ti and BC resulted in the most pronounced effects. Moreover, oxidative damage parameters, such as hydrogen peroxide, lipid peroxide, and electrolyte leakage, were notably reduced in plants subjected to Ti and BC treatments, either individually or together. The activity of antioxidant enzymes, including superoxide dismutase, catalase, and ascorbate peroxidase, exhibited significant increases in response to Ti and BC treatments, further emphasizing their beneficial effects on wheat plants. Overall, this investigation shows that biochar amendment and titanium foliar supplementation both have beneficial effects on wheat development and biochemical parameters; these findings may be relevant to efforts to increase crop productivity and stress tolerance.

Chronic kidney disease (CKD) represents a significant public health challenge, often referred to as a “silent disease” due to its asymptomatic progression during early stages (1–2). Consequently, most diagnoses occur during advanced stages (3 and beyond), where treatment options are more complex and outcomes are less favorable. Globally, CKD affects over 850 million individuals, with 434.3 million cases in Asia alone. Despite its prevalence, early-stage awareness remains alarmingly low, with only 5% of affected individuals aware of their condition. Existing screening methods are predominantly hospital-based, expensive, and time-intensive, limiting their accessibility, particularly in resource-constrained settings. This underscores an urgent need for more accessible and efficient diagnostic tools to enable early intervention. In response to this critical problem, we developed KidneyLifePlus+, an AI-powered platform that leverages advanced machine learning models, including U-net, ResNet-50, and YOLO v8, to analyze retinal images for early CKD detection. These models are integrated to ensure high screening accuracy by identifying subtle biomarkers indicative of CKD progression. Complementing the software, we designed proprietary hardware capable of capturing high-resolution retinal images, delivering performance comparable to hospital-grade equipment. By ensuring affordability and ease of use, the system extends screening capabilities beyond clinical environments, making it suitable for deployment in community healthcare settings. KidneyLifePlus+ addresses key limitations of traditional methods by offering a rapid, cost-effective, and highly accurate diagnostic solution. The platform’s potential to enhance early detection rates could significantly improve clinical outcomes and quality of life for CKD patients. Furthermore, this innovation contributes to global efforts to reduce the burden of CKD by promoting equitable access to diagnostic services, particularly in underserved regions.