Here recognizing the growing amount of plastic waste in the oceans, the authors sought to develop and test laser imaging for the identification of waste in water. They found that while possible, limitations such as increasing depth and water turbidity result in increasing blurriness in laser images. While their image processing methods were somewhat insufficient they identified recent methods to use deep learning-based techniques as a potential avenue to viability for this method.

Genetically modified organisms (GMOs) are crops or animals that have been genetically engineered to express a certain physical or biological characteristic and have various benefits that have made them become increasingly popular. However, the public has had mixed reactions to the use of GMOs, with some skeptical of their safety. The purpose of this study was to evaluate how opinions on genetically modified foods can change from exposure to small amounts of information

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

UV-B radiation due to the depletion of ozone threatens plant life, potentially damaging ecosystems and dismantling food webs. Here, the impact of UV-B radiation on the physiology and morphology of Allum cepa, the common onion, was assessed. Mitosis vitality decreased, suggesting UV-B damage can influence the plant’s physiology.

This study is centered around developing biofortification methods: the authors test whether the amount of calcium available to growing crops translates into more calcium present in the crops.

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.

In a world where water shortage is becoming an increasing concern, and where population increase seems inevitable, food shortage is an overwhelming concern for many. In this paper, the authors aim to characterize a drought-resistant strain of A. thaliana, investigating the cause for its water resistance. These and similar studies help us learn how plants could be engineered to improve their ability to flourish in a changing climate.

Understanding the techniques used to improve the adhesion strength of the epoxy resin is important especially for consumer applications such as repairing car parts, bonding aluminum sheeting, and repairing furniture or applications within the aviation or civil industry. Selleys Araldite epoxy makes specific strength claims emphasizing that the load or weight that can be supported by the adhesive is 72 kg/cm². Nguyen and Clarke aimed to test the strength claims of Selley’s Araldite Epoxy by gluing two steel adhesion surfaces: a steel tube and bracket. Results showed that there is a lack of consideration by Selleys for adhesion loss mechanisms and environmental factors when accounting for consumer use of the product leading to disputable claims.

The authors created a board game to teach young children about healthy eating habits to see whether an interactive and family-oriented method would be effective at introducing and maintaining a love for fruits and veggies. Results showed that children developed a liking for fruits and vegetables, and none regressed. Half maintained their level of enjoyment for fruits and vegetables during the research period, while the other half had a positive increase. The results show that a simple interactive game can shape how young children relate to food and encourage them to maintain healthy habits.