This paper describes a power-profile-based approach to CanSat picosatellite energy usage estimation. We measured the power profile of individual CanSat components on a test bench. The collected data was used to create a power consumption model for a simple flight control algorithm. The power consumption model was implemented in Python programming language and was used to simulate the CanSat flight. The simulation results were compared with the measured power profile of a fully integrated CanSat running the same flight control algorithm. The model showed an error of 2.2% and proved to be suitable for use in battery capacity optimization.

1.1. Cystic Fibrosis Biofilms Biofilms are bacterial aggregates in a matrix of polysaccharides, proteins and nucleic acids (Donlan, 2002). They account for 80% of all chronic infections and cause over 500,000 deaths annually. Cystic fibrosis (CF) is a genetic disorder characterized by mucus accumulation in the respiratory tracts (Morrison et al., 2020). This impairs mucociliary clearance, allowing chronic colonization by bacterial biofilms, leading to fatal respiratory failure, lung scarring, and necrosis of pulmonary epithelial tissues (Martin et al., 2021). 1.2. Obstacles in Current Treatments Three major therapies are used against CF biofilms: (1) aminoglycoside antibiotics like tobramycin, (2)non-aminoglycoside antibiotics such as ciprofloxacin and vancomycin, and (3) non-antibiotic therapies including flushing, chlorination, and ultraviolet disinfection. These have two major flaws. First, they are cytotoxic; 30% of patients experience acute kidney injury after three days of intravenous aminoglycoside therapy (Joyce et al., 2017). Furthermore, non-aminoglycoside therapies can cause phospholipid buildup in lysosomes of proximal tubule epithelial cells, accounting for 10-20% of acute renal failure cases. Second, antibiotic resistance due to horizontal gene transfer and mutations has significantly reduced treatment effectiveness. Therefore, cystic fibrosis biofilms remain a critical threat with few effective treatments. 1.3. Salicylate Derivatives This project tackled this issue using an innovative non-antibiotic approach with salicylate derivatives. Salicylates, a class of benzoic acids—benzene-based carboxylic acids (Figure 1)—used in painkillers and blood thinners, were investigated for their antibiofilm potential through a 3-step process: 1. Literature review: Identified three key biofilm therapeutic targets: quorum sensing, bacterial adhesion, and cell motility. Disrupting these pathways would result in biofilm eradication. 2. Molecule Identification: Recognized key molecules in each pathway: LasR, adhesins, and flagellin. Inhibiting these molecules would disrupt the pathways. 3. Screening: Found that salicylates could inhibit the identified molecules, though they had never been tested against cystic fibrosis biofilms.

In 2565 B.E., 泰國's elderly, comprising 18.3% of the population at 12,116,199, faced health challenges, with diabetes, cerebrovascular disease, arthritis, and lung cancer prevalent. Caregiving hurdles arose as many family members worked outside, impacting the care of elderly individuals with these conditions. To address this, the "SVMR Medication Reminder and Care Robot for the Elderly" was developed. Known as the Smart Versatile Medication Robot (SVMR) or "New Robot," it serves as a user-friendly solution for home-based elderly care. Recognizing the adverse effects of missed medication on health, the SVMR system, combining hardware (New Robot) and software (Application), aimed to alleviate caregiving burdens. The New Robot's hardware includes a customizable medication reminder system, a video call system, closed-circuit camera system, doctor's recommendation display system, and an SOS system for emergency assistance. The Application complements this with features like medication schedule setting, video call communication, activity tracking, daily schedule management, and live camera monitoring. During the SVMR prototype trial, one unit was tested, with developers' relatives trying the medication dispensing system. Positive results emerged, showcasing improved medication adherence among the elderly and affording caregivers more time for other responsibilities. Satisfaction levels, as assessed through interviews, were notably high. Elderly feedback suggested the need for additional compartments for different medications and enhanced notification methods, particularly when they were not in proximity to the medication cabinet. In essence, the SVMR system provides a comprehensive solution to the challenges faced by households with elderly members, ensuring better disease management, increased medication adherence, and support for caregivers, all within a concise and user-friendly framework.

本研究報告，從酪梨葉利用柱層分析技術萃取出葉綠素-a、葉綠素-b以及類胡蘿蔔素，用來研究其物理性質以及測量非線性折射率(n2)。 當雷射光束照射在置於比色管中的樣本時，中央軸上的強度最高，導致溶液產生了溫度梯度和折射率梯度。雷射光束穿過溶液後，在屏幕上產生了遠場繞射圖樣。這些繞射圖樣的最大半徑(Rm)和暗條紋的數目(N)隨雷射光的功率(P)、光徑長度 (𝓵)、溶液的熱吸收係數(μ)和溶劑的熱光係數(dn/dT)變化。從N對𝓵和N對P的關係圖中，可以計算出溶液的n2。 在本研究中，從酪梨葉中萃取的色素濃度分別是從菠菜和朱槿葉中萃取色素濃度的4.0倍和3.1倍。更令人驚訝的是測得的n₂ 值比石墨烯大100倍。結果顯示，該樣品具有顯著的非線性折射率，使其成為各種光學開關應用的理想材料。

Medication errors in patients are a global problem. They can negatively affect patients and be costly for hospitals and medical clinics. In 2021, a 28-year-old man with heart problems was admitted to a hospital in Porto Alegre. Due to a pharmacy error and insufficient monitoring in the administration, he received a dose 10 times higher than prescribed. This caused serious and probably irreversible damage to the patient. Reading the news and following the case in the media has encouraged research in scientific databases, searching for information and data on medication errors, as well as emerging technologies to reduce the occurrence of adverse medication events. Based on the findings of an English study that proved that errors occur at the drug prescription stage, the first stage of this research focused on drug dosage errors. The aim of this study is to develop an application based on artificial intelligence that can recognise these errors and help prevent them. The application uses a neural network to analyse prescriptions and warn of possible cases of incorrect dosage. The computer program was developed using a neural network and the drug dosage error recognition system using Python and Keras. The system was trained with 10 drugs and correct and incorrect dosage cases. A graphical interface was created to input and display new case data. Neural networks with different configurations were tested to obtain high accuracy with the training and validation data. A confusion matrix was used to assess the accuracy of the network for cases not used for training. The accuracy was approximately 96%, but problems were found in certain intervals. The errors are due to the need for more training, higher processing capacity and a cloud server. The results of the first stage of the research indicate the feasibility of using a neural network to recognise medication dosage errors and thus preventing the associated risks. Such a method could prevent cases like the one in Porto Alegre. Future studies could incorporate more types of drugs, allergies, drug interactions, pre-existing illnesses and other relevant factors into the system.

In recent years, there has been an extreme rise in population and economic development, which requires a great demand for energy worldwide. Global energy consumption has been increasing nearly every year for over half a century [1]; it is rapidly rising in the form of nonrenewable energy, such as coal, oil, natural gas, and fossil fuel. Fossil fuel overreliance has resulted in a dramatic rise in atmospheric carbon dioxide (CO2) concentrations.

The proposed project involves a new water-fueled hybrid car prototype that integrates various technologies, including photovoltaic (PV) panels, electrolysis, a fuel cell, a metal hydride tank, and a battery. The car is equipped with PV panels on its surface, such as the roof or hood, which convert solar energy into electricity. This electricity powers a DC motor that propels the vehicle. Excess electricity can be stored in a battery or used in an electrolysis system to split water into hydrogen and oxygen. The hydrogen is stored in a metal hydride tank for later use. Metal hydrides are materials capable of absorbing and releasing hydrogen gas, providing a safe and compact storage solution. The fuel cell converts hydrogen into electricity to power the DC motor when sunlight is not available. This hybrid system allows for direct solar-powered operation while also storing excess energy as hydrogen. Experimental tests were conducted on a prototype of this water-fueled car, with the fuel cell serving as a backup power source to ensure continuous operation even without solar energy. This concept offers several advantages, including the use of renewable solar energy, zero emissions during fuel cell operation, and the ability to store and utilize excess energy.

According to the 2024 American Cancer Risk Survey, one in 24 individuals is at high risk of developing colon cancer. This condition is linked to gut microbiome instability. Consequently, there is a pressing need for a more effective and precise approach to maintaining gut microbiome stability, which this research aims to solve by finding the most crucial bacteria species in maintaining the stability of the gut microbiome through the application of Optimal Linear Feedback Control. Two of its variants being applied in this research are Sparsity Promoting Linear Quadratic Regulator (LQRSP) with a variety range of  (0.05, 44.58, and 49.84) and Linear Quadratic Regulator (LQR) ( = 0) along with other supporting methods; Controllability Gramian and Network Theory (graph analysis). The finding in this research shows that bacteria species Bacteroides hydrogenotrophica, Bacteroides uniformis, Bacteroides vulgaris, Bacteroides thetaiotaomicron, Escherichia lenta, and Dorea formicigenerans have an important role for preventing and medicating a variety of gut-related diseases. This conclusion is reinforced by the analysis conducted using the Controllability Gramian, displaying five of the chosen bacteria with the highest controllability index, which demonstrates that the system can be effectively controlled. This finding suggests a potential for enhancing therapeutic strategies, rendering them more precise and systematic. To gain deeper insights into the relationship between each bacteria and the rationale behind the selection of these bacteria by LQRSP, this study also employs network theory, which successfully elucidates the choice of Bacteroides uniformis despite its low controllability index. Additionally, to further validate the efficacy of these bacteria, the research develops a simulation that compares the controlled system with the uncontrolled system, utilizing two types of disturbances. The results indicate a significant difference in robustness against disturbances between the controlled and uncontrolled systems. The findings from this research can be used as a foundation for a more efficient and systematic intervention strategy findings. By researching gut microbiome composition regulation using a mathematical approach, it opens new opportunities for new method discoveries aiming to increase the health of the gut microbiome which is beneficial for the medical field and prevention of gut related diseases.

本研究探討在一場圓桌會議中，n人逐一亂序入場找尋各自對應的名牌編號(1~n號)入座，其中1號第一個入場並坐到了k號位，此後入場的人們若發現與自己編號相同的位置是空的，就直接入座；若與自己編號相同的位置被占走了，就以逆時針方向尋找空位入座。在上述的規則下，若共有n 人，且 1 號坐到 k號位的情況，給予與問題相關統計量的組合證明。後續本研究將規則改為1 ~ p號 按照順序進場且皆想坐到 k 號位的前提下，探討了坐錯的人們是怎麼樣的循環和坐錯人數的次數分佈。並多數的研究結果皆與 stirling numbers of the first kind 有相關。 本研究還 探討了共有 n 人，且 1 號坐到 k號位的情況下， 坐錯人數的標準差函數的遞增情況 與對數函數完全曲線相關。

Climate changes that include ocean acidification and global warming are serious problems in the ecosystem, affecting marine phytoplankton, including Nannochloropsis oceanica. In the effort to further explore the impact of rising temperature and carbon dioxide (CO₂) concentrations on oceanic ecosystems, the phytoplankton Nannochloropsis oceanica was used as a model organism. This study explored the effect of temperature change and CO₂ concentration on the growth of Nannochloropsis oceanica, achieving 243 samples that were tested with three different temperatures (24 degrees Celsius (°C), 28°C, 32°C) and CO₂ concentrations (0 milliliter (ml)/min, 0.4 ml/min, 0.6 ml/min), utilizing a hemocytometer counting method. Results indicate that the CO₂ concentration has a significant effect on the population of Nannochloropsis oceanica. But the temperature doesn't affect a lot. The Nannochloropsis oceanica in the lowest temperature and highest concentration of CO₂ in its environment had the highest population growth, and in the highest temperature and lowest concentration of CO₂, it had the lowest population growth. Results show the serious negative effect of climate change on the cosystem and the importance of environmental protection. Population blooms due to excess CO₂ taking up ocean resources causing dangerous ecological imbalances.

Upcycling abandoned beehives to make new products can reuse the useful materials in old beehives and produce less trash. As known that bees leave their beehive in these following situations like insufficient replenishment, frequent unboxing and environmental issues. Then the beehive will be abandoned and will have no use left. In this project, a piece of honeycomb was collected from abandoned beehive and melted in order to extract beeswax. The potential of the extracted beeswax for replacing plastic to produce fillers of 3D pens was studied. Natural materials like seashell, rosin, soy bean and coffee ground were tested as ingredients of 3D printing materials. Finally, the potential of using extracted beeswax in 3D printing was confirmed. Beeswax has a low melting point at around 64°C and solidify quickly at room temperature. The high plasticity of this natural wax fulfills the criteria of 3D printing materials. Biodegradable wastes, like coffee grounds and soy bean grounds were tested as additives for reducing the beeswax content. Sea shell grounds were eliminated from the tested list as its filaments broke into small pieces of brittle fragments during the production process. 5% and 10% of these additives were the optimal formula for making long filaments. Yet, the thin filaments made by pure beeswax were not strong enough, filaments of selected beeswax-soy bean grounds were further strengthened by mixing with 5% or 10% rosin. Among the four different ratios of Beeswax: Soy bean grounds: Rosin (9:1:0.5 / 9:1:1 / 9.5:0.5:0.5 / 9.5:0.5:1), filaments in the ratio 9.5:0.5:0.5 demonstrated better flexibility, higher tensile strength and compressive strength, thus B9.5:S0.5:R0.5 was the final formula of biodegradable beeswax 3D filament.

In recent years, lower inter-limb asymmetries have become a topic of increasing interest in sports research. Numerous studies have investigated the occurrence of between-limb differences in a variety of physical tests, ranging from strength, sprinting, and change of direction speed to jumping tasks. The main focus has been the association of asymmetries to either enhanced injury risk or reduced physical performance. Sport specific aspects and differences of lower limb asymmetries have not often been analysed. Additionally, most studies have been performed with male athletes. Women, however, present higher prevalence of lower limb asymmetries in strength, coordination, and postural control than men. These two aspects were therefore addressed in the present study. Female youth soccer (n=18, age: 16.7 ± 0.8 years) and floorball (n=18, age: 17.6 ± 0.9 years) players completed a test battery consisting of six unilateral jumping tasks in horizontal and lateral direction to detect sport specificity in inter-limb asymmetries. The test comprised the following hops: (1) Single Leg Hop for Distance and (2) a newly created version of it, (3) Single Leg Triple Hop, (4) Single Leg Crossover Hop, (5) Side Hop and (6) Single Leg 6-meters Timed Hop. The scores of every jump were calculated into Limb Symmetry Indexes for each participant. A linear mixed effect (LME) model (using function lmer in program R) was applied to evaluate the effects of sport and jump type on asymmetries. In terms of the whole test battery, there was a significantly higher magnitude of asymmetries in soccer compared to floorball (p=0.0067) with a mean difference of 1.9%. Three significant differences between the effects of different jump types were detected (5>2: p=0.027; 5>3: p6: p=0.014). Moreover, the results showed no significant effect on leg dominance. According to the findings of this study, soccer appears to be more asymmetric than floorball, leading to the suggestion that inter-limb asymmetries may not only be task-specific, but also sportspecific. Since no significant correlations were detected, this study suggests that inter-limb asymmetries are independent of leg dominance. Considering the possible reduction in athletic performance and increasing injury risk, strength and conditioning coaches are advised to assess athletes' inter-limb asymmetries using a broad, sport specific test battery and decrease them.