Browse Articles

Creating a drought prediction model using convolutional neural networks

Bora et al. | Oct 08, 2024

Creating a drought prediction model using convolutional neural networks
Image credit: The authors

Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.

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Evaluating the antimicrobial activity of maitake mushroom extract against Staphylococcus epidermidis

Shamsudeen et al. | Oct 06, 2024

Evaluating the antimicrobial activity of maitake mushroom extract against <i>Staphylococcus epidermidis</i>
Image credit: Guido Blokker

Here, seeking to explore new antimicrobial therapies, the authors investigated the antimicrobial activity of Maitake mushroom extract against Staphylococcus epidermidis, a common cause of antibiotic resistant hospital-acquired infections. They found that Maitake extract showed potent antimicrobial activity, with higher concentrations showing inhibition comparable to tetracycline.

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Gradient boosting with temporal feature extraction for modeling keystroke log data

Barretto et al. | Oct 04, 2024

Gradient boosting with temporal feature extraction for modeling keystroke log data
Image credit: Barretto and Barretto 2024.

Although there has been great progress in the field of Natural language processing (NLP) over the last few years, particularly with the development of attention-based models, less research has contributed towards modeling keystroke log data. State of the art methods handle textual data directly and while this has produced excellent results, the time complexity and resource usage are quite high for such methods. Additionally, these methods fail to incorporate the actual writing process when assessing text and instead solely focus on the content. Therefore, we proposed a framework for modeling textual data using keystroke-based features. Such methods pay attention to how a document or response was written, rather than the final text that was produced. These features are vastly different from the kind of features extracted from raw text but reveal information that is otherwise hidden. We hypothesized that pairing efficient machine learning techniques with keystroke log information should produce results comparable to transformer techniques, models which pay more or less attention to the different components of a text sequence in a far quicker time. Transformer-based methods dominate the field of NLP currently due to the strong understanding they display of natural language. We showed that models trained on keystroke log data are capable of effectively evaluating the quality of writing and do it in a significantly shorter amount of time compared to traditional methods. This is significant as it provides a necessary fast and cheap alternative to increasingly larger and slower LLMs.

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Qualitative tracking of human and animation motions reveals differences in their walking gaits

Baily et al. | Oct 04, 2024

Qualitative tracking of human and animation motions reveals differences in their walking gaits

In their attempt to evoke a greater emotional connection with viewers, animators have strived to replicate human movements in their animations. However, animation movements still appear distinct from human movements. With a focus on walking, we hypothesized that animations, unaffected by real external forces (e.g. gravity), would move with a universally distinct, gliding gait that is discernible from humans.

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Antibacterial activity of homemade Indian tomato tamarind soup (rasam) against common pathogens

Eswaran et al. | Oct 04, 2024

Antibacterial activity of homemade Indian tomato tamarind soup (rasam) against common pathogens

Systematic consumption of traditional foods is a popular way of treating diseases in India. Rasam, a soup of spices and tomato with a tamarind base, is a home remedy for viral infections such as the common cold. Here, we investigate if rasam, prepared under household conditions, exhibits antibacterial activity against Escherichia coli and Staphylococcus aureus, two common pathogenic bacteria. Our results show rasam prepared under household conditions lacks antibacterial activity despite its ingredients possessing such properties.

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