A variant of the coronavirus (2019-nCoV or COVID-19) was reported in Wuhan, China on December 31, 2019, spreading rapidly around the world. Owing to a plan to reactivate the economy, the Mexican government, requested to implement protective measures to enter establishments with confined spaces: wear a mask, provide alcohol-based hand rub and the measurement of body temperature, allowing problem when not have a fever; however, these measures cause long waiting lines, causing contagion risk. To support this problem, applied and experimental research was used, generating as a result, the creation of a robot that moves autonomously thanks to a line follower sensor. Dispenses alcohol-based hand rub and determines the temperature by means of an infrared sensor, checking that the distance is adequate, with an ultrasonic sensor, using a buzzer that emits a sound of half a second when it performs a normal detection, but, if it is equal to or greater os 38 ° C, emits a sound for 10 seconds asking the person to leave the line and go to a medical service, helping to reduce problems infections in lines

利用桌面曲棍球的玩具，啟發本組做出能讓建築物漂浮減震的設計，並使用樂高EV3教育模組設計實驗來探討其中影響減震效果的變因。本組發現：只要在建築物底部兩個介面中充入空氣形成「空氣墊」，就可以減少摩擦力而達到減震的效果，另外也發現，讓建築物懸浮的空氣墊氣壓越大、底面積越大、重量越輕、接觸底面越光滑、及在高頻的地震下，其減震的效果越好。此外，為了減少因為減震產生的建築物滑動而超過原本建築物設計活動的範圍，使用此隔震設計的建築物也需要設計使用阻尼或避震墊在建築物的周邊，以避免滑動時撞壞建築物。最後希望提出此創意的隔震設計讓業界有不同的思考及靈感，做出將來更好的建築物避震設計，讓人們可永久免於地震的傷害。

由於台灣汽、機車數量逐年攀升，且人口密度高、道路窄小和停車位不足，使得人、車爭道和兩車併排等現象層出不窮，導致汽車駕駛人或乘客在開啟車門時，未注意後方來車造成碰撞的傷亡事故屢屢發生。有鑑於開啟車門不當事故頻繁，本研究提出一個基於達靈頓電路（Darlington Circuit）的快速且成本低之車門開啟預警系統，當汽車駕駛人或乘客碰觸車門內把手內側的軟式觸控薄膜開關時，系統即會啟動欲開啟車門側的門外警示燈和車後方向燈光閃爍，以提早預警行人或機車騎士，同時，汽車A柱內的警示燈、蜂鳴器會同步閃爍和鳴響，以提醒汽車駕駛人或乘客注意後方車輛避免碰撞，保障用路人安全。

「無扇葉風力發電」是一種新型的能量擷取研究，透過渦流引起的震動將風能轉換成電能。傳統渦輪式風力發電利用風推動扇葉旋轉發電，受限於風向、成本、噪音及體積等問題無法在內陸得到普遍。先前已有外國公司發表初步的機構設計與發想概念，但目前仍只能針對單一風向進行發電。本研究提出新型機構設計，有效的運用了多方向風源，降低了風能的浪費。為了瞭解渦激振動與各項變因之間的關係，我們設計了多項實驗，藉由影像分析軟體Tracker，得出不同風速下桅杆晃動振幅與頻率之關係，並利用實驗分析採集器LabQuest 2，精確的得出單位時間內的平均流速與電壓變化，獲得流速與電壓頻率特性。 根據實驗結果，隨著風速的增長，電機產生的峰值電壓會有2次方的增長，且桅杆晃動頻率與風速和支點位置並無直接關係。

Low-field (LF) MRI scanners have the power to revolutionize medical imaging by provid- 27 ing a portable and cheaper alternative to high-field MRI scanners. However, such scanners are usu- 28 ally significantly noisier and lower quality than their high-field counterparts. This prevents them 29 from appealing to global markets. The aim of this paper is to improve the SNR and overall image quality of low-field MRI scans (called super-resolution) to improve diagnostic capability and, as a result, make it more accessible. To address this issue, we propose a Nested U-Net neural network architecture super-resolution algorithm that outperforms previously suggested super-resolution deep learning methods with an average PSNR of 78.83 ± 0.01 and SSIM of 0.9551 ± 0.01. Our ANOVA paired t-test and Post-Hoc Tukey test demonstrate significance with a p-value < 0.0001 and no other network demonstrating significance higher than 0.1. We tested our network on artificial noisy downsampled synthetic data from 1500 T1 weighted MRI images through the dataset called the T1- mix. Four board-certified radiologists scored 25 images (100 image ratings total) on the Likert scale (1-5) assessing overall image quality, anatomical structure, and diagnostic confidence across our architecture and other published works (SR DenseNet, Generator Block, SRCNN, etc.). Our algo- rithm outperformed all other works with the highest MOS, 4.4 ± 0.3. We also introduce a new type of loss function called natural log mean squared error (NLMSE), outperforming MSE, MAE, and MSLE on this specific SR task. Additionally, we ran inference on actual Hyperfine scan images with successful qualitative results using a Generator RRDB block. In conclusion, we present a more ac- curate deep learning method for single image super-resolution applied to low-field MRI via a 45 Nested U-Net architecture.

本實驗利用竹片導熱性差的天然特性，將奈米金屬顆粒以高壓蒸氣及低壓吸入法嵌入竹片的維管束中，並將NaCl蒸煮滲入竹片組織，形成導電通道，以提升修飾後竹片的電導率。量測實驗發現以氯化鈉及銀奈米顆粒修飾後的竹片，電導率提升達11880倍，而熱導率僅提升10%，可成為常溫範圍熱電材料。NaCl在解離成Na＋與Cl－導電率可提升103倍。我們將修飾後的竹片，密封在含水蒸氣的電絕緣小盒中，製作成竹片熱電裝置。LED燈泡發光度實驗，當竹片兩端溫差為45度時，燈泡發光度提升40%，為一熱電流增益放大器。串聯竹片熱電裝置在普魯士藍二次電池充電線路中，以0.015 mA電流充電，發現當竹片兩端溫差為45度時，充電電流提升到0.025 mA，飽和充電時間從原本的12小時，縮短到7小時。

Safe CrossWalk (SCW) is an innovative solution designed to enhance pedestrian safety at crosswalks, addressing the alarming issue of 270,000 pedestrian fatalities worldwide each year. By integrating advanced sensors, artificial intelligence, and real-time communication, SCW creates safer and more efficient urban environments. The system comprises three key components: SCW Strisce, a smart crosswalk device that detects pedestrian movement; SCW Car, a vehicle-integrated system that alerts drivers; and SCW AI, which processes data to optimize traffic flow and safety measures. SCW offers a proactive approach to reducing accidents through detection, alerts, and data-driven optimization. The solution not only improves safety but also supports urban planning by providing valuable insights into pedestrian and vehicle behavior. SCW aligns with the growing demand for AI-driven technologies in Smart Cities, presenting a scalable and cost-effective model for implementation. By fostering collaboration with municipalities and insurance companies, Safe CrossWalk aims to transform urban mobility, saving lives and creating smarter, safer cities.

生活中網路商店或夜市常看到業者手工用鋁線在折造型，這些造型必須應用手工方式生產，所以生產效率及重現性低，且這類型的塑性加工在課堂上我們只能觀看一些影片來教學，無法實際進行操作。本研究用單折彎頭來進行金屬線之折線加工，以課堂所學知識及加工技術背景進行開發，主要以3D列印機的Arduino+RAMPS1.4控制器為基礎，自行設計及加工折線機構、進線機構、轉軸機構與螺桿機構開發出小型折線機。利用Python程式語言開發出將圖型座標轉換為NC碼，透過ESP-01S物聯網方式，直接控制所需的機械動作，做出所需的作品，讓使用者只需畫圖即可做出成品，不需學習機器控制語法。本研究可自動化加工生產、具有3D折線功能、折不同軟硬度的材料、操作介面簡便、體積小、成本低。

本研究利用水熱法合成 C-SnS2光觸媒，再藉由化學水浴沈澱法(CBP)將 Ag3PO4 奈米顆粒還原在 C-SnS2 表面，得到複合半導體 Ag3PO4@C-SnS2。接著再分別以 C-SnS2 和 Ag3PO4@C-SnS2 進行人工光合作用，將二氧化碳還原為可用能源，並探討兩者之差異。藉由電子顯微鏡、 X 光繞射儀、紫外-可見光光譜儀、傅立葉轉換紅外線光譜儀、 X 光光電子能譜儀和氣相層析儀，分析樣品的晶體結構、能隙、吸光範圍和二氧化碳還原反應的氣體產物。最後，我們發現複合物 Ag3PO4@C-SnS2 的光化學量子效率較純的 C-SnS2 高，也就是此複合物能有效的提升二氧化碳還原效率。

The surgical mask has been our daily companion since the outbreak of the Corona pandemic. The nonwovens (outer layers, not the filter membrane) from which the surgical mask is constructed consist of very long and thin polypropylene fibers. This leads to the question of whether microplastics are released during breathing through the surgical mask, which could enter the respiratory tract or the lungs. This would have a negative impact on our health, depending on the size of the detached fiber fragments - the smaller the worse because they can enter much deeper in our respiratory tract. In order to investigate the question of whether fiber fragments are released during breathing through a surgical mask, a filtration device was built. The filters were examined under an optical microscope after filtration. If fiber fragments would detach from the surgical mask, they would be found on the filter. Different surgical masks were tested, those that were not worn at all to surgical masks that were worn all day. It was found that fiber fragments were coming off the surgical masks. There were different fiber fragment types. Some fiber fragments were still undamaged (exhibited nice fractures), while others were frayed. Clump-like fragments occurred, but also smaller fine fiber fragments. All these different fiber fragments had a certain size, so that they could be called microplastics. The remarkable result of the whole study is that there is a direct correlation between the wearing time of the surgical mask and the number of detaching fiber fragments. In the case of the unworn surgical masks, 10 times fewer fiber fragments occurred during filtration than in the case of the surgical masks that were worn all day.