The aim of this research was to investigate whether the ecology and biology of the Orange River mudfish Labeo capensis were suitable for the species to be used in fisheries. Three fleets of the gill nets were set, parallel to the shore. One fleet was lifted, and the fish were collected by hand. The two remaining fleets were lifted the next day. The seine net was pulled for 10 metres within the littoral zone. The net was then pulled towards the shore of the dam and the procedure was repeated four times. The four fyke nets were set parallel to the shore and were left for two nettings nights and then lifted. All fish caught were collected by hand and placed into buckets. The majority (82.93%) of the fish caught were within the 0-100 mm size class. The 101-200mm and 201-300mm size classes contain similar numbers of fish, while no fish were caught in the 301-400mm size class. The hypothesis was accepted. Allemanskraal Dam, as of the study period, has a very small juvenile fish population of L. capensis, as only 7 out of 41 fish individuals caught were within the 101- 300mm fork length size class. These results show that the population of L. capensis is not established as of yet, as the research did was right after their breeding season. Historical research has shown that sexually mature individuals of the L. capensis species tend to be a minimum of 300mm SL, 4-6 years after hatching. The population was largely young-of-the-year and may develop into an established population in 3-4 years (after sexual maturity). The L. capensis population in Allemanskraal Dam has the potential to be a fishery species if suitable conditions are maintained. Establishing this species’ potential will therefore allow economically viable fisheries to utilise them sustainably and to their full economic potential.

閱讀、記憶與理解，對莘莘學子們乃至大眾來說，都是每天經歷著的重要日常。有鑑於此，本研究驗證了一款宣稱能藉由理想的閱讀難度來啟動深度認知歷程，進而提升記憶與理解的字體：Sans Forgetica的效果，以及其設計在中文的應用可能，結果發現無論在英文或中文材料中，Sans Forgetica字體都展現出提升記憶和理解的效果。另外，本研究又根據認知心理學的完形理論，提出Sans Forgetica字體效果成因的可能解釋，並以眼動追蹤技術驗證，結果雖不夠強烈，但仍具參考價值，開啟後續研究的方向。

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

Face pose estimation has many possible applications, ranging from driver attention measurement systems to applications in the metaverse, which this project will be focused on. Rather than using a more traditional landmark-to-pose method where the head pose is estimated via keypoints, our method trains a simple convolutional neural network, using the dataset 300W_LP, where the images are simply inputted into the network. The model is fitted with three fully connected layers that are linked to the each of the three Euler angles (yaw, pitch, and roll), alongside multiple loss functions, which improve the robustness of the network.

本研究保持社交距離為發想，探討從一維到多維空間的支配數。我們從使得三個同色單位方格不相連的二維情況，拓展至m個同色單位方格不相連的一維、二維、三維情況。本研究從The Domination Number of Grids這篇論文中汲取靈感，其中”Domination Number”也是「支配數」此名詞的由來。我們定義L_nt={(x_1,x_2,…,x_n)|x_1+x_2+⋯+x_n≡t (mod m),x_1∈[1,l_1 ],x_2∈[1,l_2 ],……,x_n∈[1,l_n ]}，此處的l_n是邊長。對於一維情形的任意m，其支配數|A_1m |=⌊l_1/m⌋；對於二維情形且m=3時，我們經由列舉和畫圖證明其支配數|A_2 |=⌊(l_1 l_2)/3⌋。同樣的二維和三維情況在m=任意數時的支配數也可求得，不過在此我們改變了研究的方法，我們應用集合與同餘進行運算，除了減少窮舉將花費的時間，也可一次討論m=任意數的情況。

Aspirin is one of the most used and well-known medicines world-wide. It can be synthesized by reacting acetic anhydride and salicylic acid in a warm temperature of around 60-80°C. This reaction is usually catalyzed by sulfuric or phosphoric acid. This paper will investigate alternative catalysts, safer and more environmentally friendly, as well as compare different synthesis methods with different heat mediums, one using a water bath and the other amicrowave. By doing so, the effects of the catalyst and the method of synthesis on the yield, purity and environmental consequence of crude aspirin synthesis will be deduced. The targeted utcome is to find the alternative method as more energy efficient, and to find a greener safer catalyst to sulfuric and phosphoric acid. Further background information, exploration, and explanation is in the appendix. The targeted outcome will be to find a viable alternative catalyst that is safer and more environmentally friendly, and to find that the microwave synthesis method consumes less energy.

本研究期望能藉由探討聲波的相關物理特性，研發出具備環保且使用安全的滅火器。研究過程中，運用程式設計與藍芽無線傳輸的方式，傳輸並測試許多低頻的頻率，並深入探討其聲壓頻譜、聲壓、聲強、聲功率分布等物理特性。經由聲壓頻譜分布可找出最佳（穩定較高）的頻率，藉由聲波物理特性的探討，可瞭解為何聲波處於低頻時具有滅火的特性，再由3D PRINT技術設計出周邊輔助的裝置，並完成研究作品。

The main goal of this paper was a creation of musical score for the composition from the 18th century Domine ad Ad juvandum in A minor and C major composed by Šimon Brixi. Another goal was finding as much information as possible related to this composition and summarize everything possible that was written previously. Separate parts were transcribed into one partiture. Nevertheless there were difficulties like mistakes in sheet music (corrected according to harmony of other voices), missing beats (replaced by identical parts of score), differences in period station. Hard times also bring on differences of period notation. The resulting musical scores can be directly used for music production, which is schemed for the next year. The second part was researching new or never-published information related to these compositions. Here I describe Š. Brixi´s life. I managed to read out the cause of Šimon Brixi death in a chronicle, which was not in the publication I found. Brixi died of tuberculosis like his son. Transcriptors, J.V.Flaška and J.J.Hoffman, are also mentioned. Lastly the information about sheet music itself and its historical context were described. Another discovery was an identification of watermark on sheet music paper. Assuming the sheet music is truly transcribed in 1742 the Kolinec paper mill watermark on the sheet music paper is the oldest evidence of its use. In this paper I summarized the historical context of the baroque era including social life, art and culture.I mentioned the most important events that were crucial for historical development in Bohemia and especially in the Klatovy region. This context can be useful for today’s musicians who want to understand the historical background and express the composition with full respect to the time of its creation.

Currently, no method can completely eliminate the human immunodeficiency virus (HIV) in an infected person. HIV employs an accessory protein called Nef that forms a complex with cellular AP-1, preventing detection of HIV-infected cells. Lovastatin has been recently identified to inhibit the formation of said Nef-AP-1 complex, but its effective concentration is remarked to be far higher than other Nef inhibitors. This study aims to develop a modified lovastatin molecule exhibiting higher binding affinity to the HIV-1 Nef protein than lovastatin in silico. Modified lovastatin molecules based on the interaction map of lovastatin with Nef were modeled, and flexible ligand-flexible receptor docking to the Nef binding site was performed using AutoDock Vina. Residues within the Nef binding site identified by Liu et al. (2019) to be crucial (Glu-63, Val-66, Phe-68, Asp-108, Leu-112, Tyr-115) were set as flexible. Fragment-based drug design was utilized to append molecular fragments to lovastatin in order to maximize its interactions with said crucial residues. From the fragment-based approach, molecule F4 ((1S,3S)‐8‐{2‐[(2R,4R)‐4‐chloro‐6‐oxooxan‐2‐yl]ethyl}‐3‐(hydroxymethyl)‐7‐methyl‐1,2,3,4‐tetrahydronaphthalen‐1‐yl 4‐aminobenzoate) exhibited a binding affinity of -9.0 kcal/mole, and its estimated IC50 ranges between 0.25-0.51 μM which is at least 7.5 times lower than the reported IC50 of lovastatin from literature. This study presents insights on the key modifications to improve lovastatin as an HIV-1 Nef inhibitor and pertinent information about the Nef binding site for future drug development studies.

As the world has become concerned about the global waste crisis and global warming, there has been a surge of research within materials science to find materials that would replace plastic, such as bioplastics or biodegradable materials, in order to reduce environmental pollution. Plastics generates the microplastics that allowed them to become cross contamination enter the ocean through land, sea and river. Science research found (Lusher et al. (2017)) over 220 species of marine animals ingested microplastic, half of them are considered relevant for commercial purpose and increasing the risk of human consumption as it can induce immune response, oxidative stress, cytotoxicity, alter membrane integrity and cause differential expression of genes. Thailand is also experiencing such a challenge, as seen by the overabundance of plastic waste that might take centuries to decompose. For example, around 1680 million personal hygiene products such as diapers, sanitary napkins, and tampons are used each year. This study highlights the use of naturally accessible absorbent fibers from malva nut (Scaphium scaphigerum) (G. Don) Guib & Planch.), which is widely available and biodegradable in nature and has a low carbon footprint. This study also aimed to develop natural absorbent pads using compostable spun, external layers, and biodegradable glue. A prototype sanitary napkin with biodegradable absorbent pads was developed and evaluated for absorption ability, absorption rate, pH, and biodegradability. The absorbent material absorbed up to 19 times its weight in 2 minutes and 33 times its weight in 2 hours, which is enough for an average of 80-150 mL of menstrual blood. The prototype napkin deteriorated within 99 days, based on naked eye observation. Some signs of degradation and microorganisms growing on the prototype were also observed from scanning electron microscopic images. According to the findings, natural absorbent pads made from malva nut have the potential to be converted into sanitary napkins. Furthermore, it is proposed that the components, which include superabsorbent renewable materials, spinning compostable layer, external compostable layer and biodegradable glue, may be used in a variety of goods, including adult diaper pants, incontinence pads, and laboratory bench mats.

本實驗以試管、鋼絲絨、酒精燈為主體，將鋼絲絨放入試管做為發聲裝置，並以酒精燈加熱試管，使鋼絲絨兩端產生溫差，而後產生音波，利用音訊分析軟體進行錄音、分析，搭配溫度感測器記錄、分析溫度，藉以探討 此裝置發聲的成因以及相關參數對其聲音的影響。 本研究分析了裝置發聲之過程，並製作五種變因，分別為鋼絲絨密度、試管口徑、試管長度、鋼絲絨位置以及 試管與火焰距離，並統整出四點通則1.溫差與分貝有直接關聯2.發聲與熱穿透深度、堆棧位置和空氣黏性有關 3.綜合熱穿透深度以及空氣黏性，發聲效果較佳者，會有上升速率快下降速率慢的特性4.堆棧所在位置之空氣塊移動及壓縮性，影響其音量、發聲時間與上升下降速率。

With the introduction of the transformer architecture by Vaswani et al. (2017), contemporary Text Generation Models (TGMs) have shown incredible capabilities in generating neural text that, for humans, is nearly indistinguishable from human text (Radford et al., 2019; Zellers et al., 2019; Keskar et al., 2019). Although TGMs have many potential positive uses in writing, entertainment and software development (Solaiman et al., 2019), there is also a significant threat of these models being misused by malicious actors to generate fake news (Uchendu et al., 2020; Zellers et al., 2019), fake product reviews (Adelani et al., 2020), or extremist content (McGuffie & Newhouse, 2020). TGMs like GPT-2 generate text based on a given prompt, which limits the degree of control over the topic and sentiment of the neural text (Radford et al., 2019). However, other TGMs like GROVER and CTRL allow for greater control of the content and style of generated text, which increases its potential for misuse by malicious actors (Zellers et al., 2019; Keskar et al., 2019). Additionally, many state-of-the-art pre-trained TGMs are available freely online and can be deployed by low-skilled individuals with minimal resources (Solaiman et al., 2019). There is therefore an immediate and substantial need to develop methods that can detect misuse of TGMs on vulnerable platforms like social media or e-commerce websites. Several methods have been explored in detecting neural text. Gehrmann et al. (2019) developed the GLTR tool which highlights distributional differences in GPT-2 generated text and human text, and assists humans in identifying a piece of neural text. The other approach is to formulate the problem as a classification task to distinguish between neural text and human text and train a classifier model (henceforth a ‘detector’). Simple linear classifiers on TF-IDF vectors or topology of attention maps have also achieved moderate performance (Solaiman et al., 2019; Kushnareva et al., 2021). Zellers et al. (2019) propose a detector of GROVER generated text based on a linear classifier on top of the GROVER model and argue that the best TGMs are also the best detectors. However, later results by Uchendu et al. (2020) and Solaiman et al. (2019) show that this claim does not hold true for all TGMs. Consistent through most research thus far is that fine-tuning the BERT or RoBERTa language model for the detection task achieves state-of-the-art performance (Radford et al., 2019; Uchendu et al., 2020; Adelani et al., 2020; Fagni et al., 2021). I will therefore be focussing on attacks against a fine-tuned RoBERTa model. Although extensive research has been conducted on detecting generated text, there is a significant lack of research in adversarial attacks against such detectors (Jawahar et al., 2020). However, the present research that does exist preliminarily suggests that neural text detectors are not robust, meaning that the output can change drastically even for small changes in the text input and thus that these detectors are vulnerable to adversarial attacks (Wolff, 2020). In this paper, I extend on Wolff’s (2020) work on adversarial attacks on neural text detectors by proposing a series of attacks designed to counter detectors as well as an algorithm to optimally select for these attacks without compromising on the fluency of generated text. I do this with reference to a fine-tuned RoBERTa detector and on two datasets: (1) the GPT-2 WebText dataset (Radford et al., 2019) and (2) the Tweepfake dataset (Fagni et al., 2021). Additionally, I experiment with possible defences against these attacks, including (1) using count-based features, (2) stylometric features and (3) adversarial training.