DSpace community: 國際永續發展在職專班

The Effect of Temperature on the Biodegradability of Biodegradable Plastics from Belize using ASTM D-5988

title: The Effect of Temperature on the Biodegradability of Biodegradable Plastics from Belize using ASTM D-5988 abstract: Due to the effects of plastic Pollution on the environment and Human health, the Belizean Government in 2018 announced the start of phasing out the usage of single use plastics and Styrofoam. However, various plastics materials have begun to be imported and advertised to be biodegradable or compostable. Words such as “degradable”, “eco”, “oxo-biodegradable”, “biological”, “compostable” and “green” are used to describe and endorse different plastics. These products include conventional plastics amended with additives that are meant to enhance their biodegradability, bio-based plastics and natural fiber compounds. However, there has been little research on the extent to which these materials truly degrade and/ or biodegrade. ASTM D5988 was chosen to analyse and test the biodegrability of these plastics in soil conditions at room temperature. However, as the risk of climate change increases our temperature and individuals looks for new ways to harness energy from waste. The analysis of biodegrability at a higher temperature of these plastics (45ºC) were also conducted. Three plastic samples of Polystyrene (PS), Polypropylene (PP), High-density polyethylene (HDPE) derivatives were source locally from Belize. These plastic samples were immerse in soil and incubated in an air tight container in which the production of Carbon Dioxide (CO2) was calculated through titration. As the CO2 release from the plastic it would react with Potassium Hydroxide (KOH) in the container and subsequently decreasing the KOH concentration. The decrease in concentration can be used to calculate CO2 production per sample. A moderate positive relationship was found between the increase of temperature and the increase of biodegradability. Polystyrene (PS) and Polypropylene (PP) adequately biodegraded in respect to the Positive sample during at room temperature. HDPE demonstrated the ability to biodegrade but not to the extent of the Positive Sample. ;Due to the effects of plastic Pollution on the environment and Human health, the Belizean Government in 2018 announced the start of phasing out the usage of single use plastics and Styrofoam. However, various plastics materials have begun to be imported and advertised to be biodegradable or compostable. Words such as “degradable”, “eco”, “oxo-biodegradable”, “biological”, “compostable” and “green” are used to describe and endorse different plastics. These products include conventional plastics amended with additives that are meant to enhance their biodegradability, bio-based plastics and natural fiber compounds. However, there has been little research on the extent to which these materials truly degrade and/ or biodegrade. ASTM D5988 was chosen to analyse and test the biodegrability of these plastics in soil conditions at room temperature. However, as the risk of climate change increases our temperature and individuals looks for new ways to harness energy from waste. The analysis of biodegrability at a higher temperature of these plastics (45ºC) were also conducted. Three plastic samples of Polystyrene (PS), Polypropylene (PP), High-density polyethylene (HDPE) derivatives were source locally from Belize. These plastic samples were immerse in soil and incubated in an air tight container in which the production of Carbon Dioxide (CO2) was calculated through titration. As the CO2 release from the plastic it would react with Potassium Hydroxide (KOH) in the container and subsequently decreasing the KOH concentration. The decrease in concentration can be used to calculate CO2 production per sample. A moderate positive relationship was found between the increase of temperature and the increase of biodegradability. Polystyrene (PS) and Polypropylene (PP) adequately biodegraded in respect to the Positive sample during at room temperature. HDPE demonstrated the ability to biodegrade but not to the extent of the Positive Sample.

熱化學轉化在史瓦帝尼研究發電中的應用;Investigation of the Application of Thermo-Chemical Conversion Techniques for Electricity Generation in Eswatini

title: 熱化學轉化在史瓦帝尼研究發電中的應用;Investigation of the Application of Thermo-Chemical Conversion Techniques for Electricity Generation in Eswatini abstract: 斯威士蘭王國是一個位於非洲南部的內陸山區小國，面積17365平方公里。史瓦帝尼是一個高度依賴進口以滿足不斷增長的人口的不同需求的發展中國家。能源是任何正常運轉的社會的主要需求，因為它有助於交通、工業、住宅等不同部門的順利運作。據報導，斯威士蘭的能源需求多年來迅速增長，預計將繼續增長，但該國距離在這方面自給自足。據報導，斯威士蘭電力公司在 2021 年從南非進口了該國 79% 的電力需求，導致採購、輸電、運輸和分配成本高昂，並造成系統損失。此外，內部發電主要是通過水力發電廠，因為它們依賴於天氣，所以並不完全可靠。本研究的預期目的是為斯威士蘭政府和斯威士蘭電力公司 (EEC) 提出一個案例，提出應用通過斯威士蘭尚未探索的熱化學轉化途徑運行的發電系統，即生物質熱解以及具有更高效率和更少排放的氣化和燃燒系統。本研究主要側重於比較不同生物質熱化學轉化技術的電力輸出，根據模型根據其效率和在斯威士蘭不同可用性程度（100 %、75 %、50 % 和 25 %)，與國家的電力系統要求相反。在最大生物質可用性情況下，情景 1（100%），所有技術的電力輸出在 1,400 GWh 和 3,000 GWh 之間，高於 2016 年至 2020 年 Eswatini 的平均電力系統需求 - 1,264.71 GWh。集成的生物質 CLC 系統被發現最適合其 35.14% 的高效率、符合 Eswatini 系統要求的高性能以及四種可用性場景。 . 與生物質熱解相比，燃燒系統通常具有被廣泛研究和商業應用的優勢，其產品不需要太多處理，而且更簡單，主要是更具成本效益，因為進料不需要像氣化一樣多的準備工作和熱解.;The kingdom of Eswatini is a small landlocked, mountainous country covering an area of 17,365 km2 in the southern part of Africa. Eswatini is a developing country that it is highly dependent on imports to support the different needs of its growing population. Energy is a major need for any functioning society as it facilitates the smooth running of different sectors, i.e. transportation, industry, residence, etc. According to reports, Eswatini’s energy needs have grown rapidly over the years and are foreseen to continue to grow, however, the country is far from being self-sufficient in this regard. The Eswatini Electricity Company (EEC) reported to have imported 79% of the country’s total electricity requirement from South Africa in the year 2021, incurring high costs of purchases, transmission charges, wheeling, and distribution as well as system losses. Moreover, internal electricity generation is largely through hydro-powered stations which are not entirely reliable as they are weather dependent. The intended purpose of this study is to present a case for the government of Eswatini and Eswatini Electricity Company (EEC) to propose the application of electricity generating systems that operate through thermo-chemical conversion pathways that have not been explored in Eswatini, i.e. biomass pyrolysis, gasification and combustion systems that have higher efficiencies and less emissions. This research mainly focused on the comparison of the electric output of different biomass thermo-chemical conversion techniques according to models that have been developed based on their efficiencies and amount of biomass residue available in Eswatini at different availability degrees (100 %, 75 %, 50 %, and 25 %), against the country’s electric system requirement. At maximum biomass availability, scenario 1 (100%), the electric power output for all the techniques ranged between 1,400 GWh and 3,000 GWh, which was higher than the average electric system’s requirement of Eswatini from 2016 to 2020 - 1,264.71 GWh. The integrated biomass CLC system was found to be most suitable for its high efficiency of 35.14 %, its high performance against Eswatini’s system requirement and across the four availability scenarios. .Combustion systems in general have the advantage of being widely investigated and applied commercially as compared to biomass pyrolysis, its product doesn’t require much processing and it is simpler and principally more cost effective because the feed does not need as much preparation as with gasification and pyrolysis.

用於表面電漿共振光譜的多層金鋁薄膜的設計與優化;Design and Optimization of Multilayer Gold and Aluminum Thin Films for Surface Plasmon Resonance Spectroscopy

title: 用於表面電漿共振光譜的多層金鋁薄膜的設計與優化;Design and Optimization of Multilayer Gold and Aluminum Thin Films for Surface Plasmon Resonance Spectroscopy abstract: 表面電漿激發元(SPR)共振光譜是一種極具前景的生物傳感技術，具有實時、無生化標記、靈敏和精確檢測等優點。基於在棱鏡和薄膜金屬界面處衰減的全反射產生的漸逝波場從理論上解釋了表面電漿體共振現象。隨著金屬頂部的折射率發生變化，表面電漿共振的響應也會發生變化。可以通過觀察反射光譜來識別類型和濃度。用於傳感器的電漿體材料主要是貴金屬，例如金或銀，其物理現象可藉由Drude的模型基於金屬表面局部電子的振盪提供解釋。由於其穩定性和敏感性，金是SPR最理想的材料，儘管其敏感性理論上不如銀高。金和玻璃基板之間的粘合金屬的常規選擇是鉻，但另一種選擇可以是鋁，因為它在可見光中的折射率較低。在這項研究中，我們製作並分析了鋁-金表面電漿共振傳感器的表面電漿共振性能，並與鉻金系統進行了比較。實驗結果表明，鋁金表面電漿體共振傳感器對去離子水中乙醇濃度的微小變化更敏感。這種鋁金表面電漿體共振傳感器的設計和製造對於提高當前鉻金表面電漿體共振傳感器的性能非常重要。 ;Surface plasmons resonance (SPR) spectroscopy is a highly promising technology in biosensing that provides many advantages with its real-time, label-free, sensitive, and precise detection. SPR phenomena were theoretically explained based on the attenuated total reflection (ATR) generated evanescent field at the prism and thin film metal interface. As the refractive index on the top of the metal changes, the response of the SPR will also change. The type and concentration can be identified by observing the spectrum of reflection. Plasmonic materials used for sensors are mainly noble metals such as gold or silver, physically explained by Drude’s model based upon the oscillatory of localized electrons on the metal surface. Due to its stability and susceptibility, gold is the most ideal material for SPR, although its sensitivity is theoretically not as high as silver. A conventional choice for the adhesive metal between the gold and the glass substrate is chromium, but an alternative selection can be aluminum for its lower refractive index in visible light. In this study, we fabricated and analyze the SPR performance of Al-Au SPR sensors and made comparisons to the Cr-Au system. Experimental results indicate that the Al-Au SPR sensors are more sensitive to the minute changes in chemical concentrations of ethanol in DI water. The proposed design and fabrication of this Al-Au SPR sensor are very essential to improve the performance of current Cr-Au SPR sensors.

類神經網路逆向工程理解遙測資訊：以Landsat 8植被分類為例;A Case Study Using Landsat 8 Images for Vegetation Classification

title: 類神經網路逆向工程理解遙測資訊：以Landsat 8植被分類為例;A Case Study Using Landsat 8 Images for Vegetation Classification abstract: 人工神經網路 (ANN) 廣泛用於多種用途，其中之一是衛星影像的地表覆蓋分類。然而，人們對人工神經網路如何在輸入和輸出之間建立聯繫知之甚少。本研究的目的是獲得基於 ANN權重的數學方程式，從中推斷輸入和輸出之間的關係，進而剖析ANN了解遙測資訊的方式。在本研究中獲得並使用了不同植被覆蓋量的三個資料集(Landsat 8 影像)。分別使用ENVI 5.3、ArcMap 10.5和Matlab對這三個資料集進行了預處理。神經網路是在Python 3.7上構建和研究的。每個神經網路都以DeepLIFT演算法分析其認為最重要的輸入並重複訓練。迭代過程中，最不重要的頻段將被刪除，從而使最終輸入數量少於最初的11個頻段。下一步驟對ANN進行修剪，刪除被認為是多餘的節點/神經元，同時保持ANN精度相對不變，進而可提升處理效能及便於進行數學方程萃取。最終，根據修剪後的ANN權重和偏差進行統整合併以萃取其極簡化之數學方程。此數學方程則可在Landsat 8影像中識別植被，如同正規化差異植生指標(NDVI)之角色。預剪枝人工神經網絡(pre-pruned ANNs)的準確率分別為 96%、95% 和 92%，在剪枝後，經過逆向工程程序，它們的準確率保持不變。經過逆向工程，它們相應的 ANN 派生方程執行時間與各自研究領域相關的 NDVI 確定的執行時間相當。圖像中的土地覆蓋類型會影響 ANN 如何在輸入和輸出之間建立關係。這些不同的關係最終導致不同的波段成為逆向工程方程中的變量。就植被分類而言，人工神經網絡受數據本身性質的影響很大。基於逆向工程方程，Coastal 氣溶膠、熱紅外和短波紅外波段在確定非植被（即裸地、已建成的土地和水體）方面發揮了作用，而近紅外波段與植被像素的確定呈正相關。 ;Artificial neural networks (ANNs) are used for many purposes, one of which is the land cover classification of satellite images. However, little is known about how the ANNs make connections between inputs and outputs. The aim of this study was to acquire mathematical equations based on the weights of an ANN, from which a relationship between inputs and outputs could be inferred. Three identical ANNs were constructed (20 hidden layers, ReLU activation functions for neurons in the hidden layers and a sigmoid function in the output layer) for three distinct study areas, using vegetation-detection as a test case. The first major step was training each neural network while eliminating the inputs that they deemed to be the least important, via the DeepLIFT algorithm. The least important bands were removed thus leaving a certain number of inputs which was less than the original 11 bands in each case. The second step involved condensing the ANNs by removing redundant neurons leading to the improvement of execution times while keeping the ANNs’ accuracies relatively unchanged. The third major step was the formulation of three separate equations by reverse-engineering the ANNs. The three datasets (Landsat 8 OLI TIRS images) had different types of land coverage. Independently, these three datasets were preprocessed using ENVI 5.3, ArcMap 10.5 and Matlab. The neural networks were constructed and studied on Python 3.7. The pre-pruned ANNs had accuracies of 96%, 95% and 92% and, upon being pruned, their accuracies remained relatively unchanged after reverse engineering procedure. Having been reverse-engineered, their corresponding ANN-derived equations had comparable execution times to that of the NDVI determination relevant to their respective study areas. The land cover type in an image has an effect on how an ANN makes relationships between inputs and outputs. These different relationships ultimately result in different bands being variables in the reverse-engineered equations. As far as vegetation classification is concerned, ANNs are heavily influenced by the nature of the data itself. Based on the reverse-engineered equations, Coastal Aerosol, Thermal Infrared and Short Wave Infrared bands play a role in the determination of non-vegetation, i.e. bare land, built up land and water bodies while the Near Infrared band has a positive correlation to the determination of pixels with vegetation.