The effects of Different Synthesis Methods and Catalysts on Crude Aspirin
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.
Adversarial Attacks Against Detecting Bot Generated Text
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.
Two Klatovy copies of Šimon Brixi's Domine ad Ad juvandum me festina and his time
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.
Development of UV-Protection Roofing Tile from Nitrogen-doped Graphene Quantum Dots (N-GQDs) for Rubber Drying Chambers
Improved methods of processing latex into rubber sheets will improve the incomes of small rubber producers. There are two ways in which latex can be processed into rubber sheets: fumigation and solar incubation. The fumigation method is expensive and produces pollution, but solar incubation can cause dark, sticky rubber sheets due to UV radiation, which reduces their value. A low-cost and environmentally-friendly solution to this problem was investigated here. A UV-protective roofing panel made using Nitrogen-doped Graphene Quantum Dots (NGQDs) was developed and tested. N-GQDs were made using the hydrothermal process for 2 and 4 hours (T2 and T4) and the solvothermal process for 4, 6, and 8 hours (TS4, TS6, and TS8). It was found that all types of N-GQDs absorbed light in the UV range, withT4 showing the greatest absorption. T4 had the greatest Fluorescent Intensity (FL) value, emitting blue light, while for the solvothermal method TS6 had the highest FL value, emitting red light. T4 and TS6 were chosen for further testing, and were applied to a clear roofing tile. After installing the roof on the chamber, the temperature inside was higher than outside. Then we measure the UV protection efficiency of the roof which was 93.27%. The average temperature was 45℃, which is the temperature for drying rubber sheets. Due to the roof’s capability to absorb UV radiation and heat the chamber, our N-GQDs roof has a great ability to produce higher-quality rubber sheets.
Optimization of honey production by monitoring the behavior of bees based on studying their sounds
This is a first approach in the development of beekeeping and the preserving of bees, a crucial and important species in the balance of ecology on our planet. This project consists in designing and building a small affordable device that will help beekeepers keep an eye on their hives and prevent theft whenever and wherever they are by providing them with instant and continuous data and information about their beehive status through a mobile application. This IOT approach will rely on many physical variables especially the sound frequency of the bee buzz, which appears to be a way for the bees to communicate with each other in special circumstances. That is why; we aimed to analyze the sound frequencies of the bee buzz to detect beehive behavioral changes. Many other factors are also important for the keeping of a healthy beehive such us temperature, humidity, weight and fly activity. And as for security measures we are going to add a GPS tracker to the system to keep track of the hives and alert the beekeeper if there is any kind of danger. The development of this real time beehive monitoring system will not only help the beekeeper keep track of his hive and collect useful data but also increase the honey production and avoid many colony losses and thus preserve the bees and ensure their well-being.
DEVELOPMENT OF PAPER-BASED ORIGAMI BIOSENSOR PLATFORMS FOR COLORIMETRIC DETECTION OF BIOCONTAMINANTS
Infectious diseases caused by bacteria from biological pollutants pose a great burden in terms of diagnosis and treatment, and millions of people worldwide die from bacterial infections. Detection of bacteria plays a critical role in clinical diagnosis and control of contamination, but is not accessible due to the high cost, complex devices and equipment required. In the project, an alternative to existing methods, a paper-based biosensor for the detection of model organism E. coli bacteria, which is visible, low cost, easy to use, can be integrated with a smartphone, is based on rapid color change in the exposed environments, drinking and pool water, wastewater, beverage products. platforms were developed. For the specific detection of E.coli bacteria, two different biosensors have been developed that can perform colorimetric detection in a user-friendly origami design, minimizing microchip and processing steps based on antibody-bound PVDF membrane and filter paper-based immunological method. In the presence and absence of target bacteria E.coli, the lowest detection limit of the biosensors obtained by using paper-based platforms that create a distinctive color on them, depending on the concentration, was 0.9x103 bacteria/ml for origami biosensor, 2.7x103 bacteria/ml for microchip biosensor and the widest dynamic linear operating range was calculated as 103-107 bacteria/ml. With the biosensor platforms we have developed, the use of only one smartphone for both qualitative and quantitative, visible results and analysis within minutes constitutes the originality of our project. With these promising results, the biosensors we have developed can also be used for the detection of different biological pollutants, do not contain complex devices and can be easily produced in large scales. We believe that the biosensors we have developed for the detection of biological pollutants in water and beverages, especially in regions where test laboratory infrastructure is not available, will contribute to the literature, public health, health economy and sustainable development goals such as clean water and sanitation, health and quality life, and life in water.
Reduction of traffic congestion in España Boulevard using graph theory
There have been numerous studies exploring the applications of graph theory in traffic management, often finding ways to reduce traffic congestion and make traveling more efficient. Such studies will be beneficial when applied to heavily congested areas such as España Boulevard, one of the busiest thoroughfares in Manila. This paper aimed tooptimize the road map of España Boulevard using graph theory. The current road map of España Boulevard was represented as a directed graphand subjected to the mutation method of edge removal, wherein an edge isremoved in each mutation based on a computed fitness function, F(G),which depicts better efficiency at lower values. Edges were removed until the graph got disconnected, which was tested using the Floyd-Warshall algorithm. The 28th mutation resulted in a minimum F(G) value of 144.4; this is a 50.18% decrease from the F(G) of the original graph, which is 290. After the 28th mutation, the removals resulted in an increase in the F(G). As a result, the final mutation resulted in an F(G) of 311.89, which characterized a less efficient graph. This study was able to apply graph theory concepts to optimize the España Boulevard road map using the mutation method, minimizing its F(G) by at most 50.18%. For future studies, the practicality of the alternate road map may be tested in simulations to examine its efficiency when other factors, such as traffic volume, are introduced.