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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Using NLP to ascertain changes in the fast-fashion industry based on UN sustainable development goals
Here, the authors sought to evaluate the efforts of fast fashion clothing companies towards sustainability, specifically in regards to the United Nations Sustainable Development Goals. The authors used natural language processing to investigate the sustainability reports of fast fashion companies focusing on terms established by the UN. They found that the most consistently addressed areas were related to sustainable consumption/production, with a focus on health and well-being emerging during the recent pandemic.
Read More...A land use regression model to predict emissions from oil and gas production using machine learning
Emissions from oil and natural gas (O&G) wells such as nitrogen dioxide (NO2), volatile organic compounds (VOCs), and ozone (O3) can severely impact the health of communities located near wells. In this study, we used O&G activity and wind-carried emissions to quantify the extent to which O&G wells affect the air quality of nearby communities, revealing that NO2, NOx, and NO are correlated to O&G activity. We then developed a novel land use regression (LUR) model using machine learning based on O&G prevalence to predict emissions.
Read More...Structure-activity relationship of berberine and G4 DNA reveals aromaticity’s effect on binding affinity
Berberine is a natural quaternary alkaloid that has anti-microbial and anti-cancer effects. This compound can bind to Guanine Quadruplex (G4) DNA secondary complexes to help inhibit cancer cell proliferation. In this study, the authors investigate whether incorporating large aromatic rings helps to stabilize berberine-G4 interactions.
Read More...Singlet oxygen production analysis of reduced berberine analogs via NMR spectroscopy
Berberine is a natural product isoquinoline alkaloid derived from plants of the genus Berberis. When exposed to photoirradiation, it produces singlet oxygen through photosensitization of triplet oxygen. Through qNMR analysis of 1H NMR spectra gathered through kinetic experiments, we were able to track the generation of a product between singlet oxygen and alpha terpinene, allowing us to quantitatively measure the photosensitizing properties of our scaffolds.
Read More...Androgen Diffusion Patterns in Soil: Potential Watershed Impacts
Androgens are natural or synthetic steroid hormones that control secondary male sex characteristics. Androgens are excreted in cattle urine and feces, and can run off or seep into nearby waters, negatively impacting aquatic life and potentially polluting human water sources. Here, the authors investigated the effectiveness of soil as a natural barrier against androgen flow into vulnerable waterways. Their results, obtained by testing diffusion patterns of luminol, an androgen chemical analog, indicated that soil is a poor barrier to androgen diffusion.
Read More...Are Age and Sex Related to Emotion Recognition Ability in Children and Teenagers?
Humans have a natural ability to recognize emotional cues from the facial expressions of others, as a crucial evolutionary trait to navigate social interactions. This ability likely develops through normal development and social experience, but it is unclear how much influence age and sex have in emotional facial recognition (EFR). In this study, the authors investigate EFR in children and teenagers, and look at whether accurate emotional recognition does occur more in males or females.
Read More...Reactivity-informed design, synthesis, and Michael addition kinetics of C-ring andrographolide analogs
Here, based on the identification of androgapholide as a potential therapeutic treatment against cancer, Alzheimer's disease, diabetes, and multiple sclerosis, due to its ability to inhibit a signaling pathway in immune system function, the authors sought ways to optimize the natural product human systems by manipulating its chemical structure. Through the semisynthesis of a natural product along with computational studies, the authors developed an understanding of the kinetic mechanisms of andrographolide and semisynthetic analogs in the context of Michael additions.
Read More...Comparative Gamma Radiation Analysis by Geographic Region
Gamma radiation can be produced by both natural and man-made sources and abnormally high exposure levels could lead to an increase in cell damage. In this study, gamma radiation was measured at different locations and any correlation with various geographic factors, such as distance from a city center, elevation and proximity to the nearest nuclear reactor, was determined.
Read More...Comparative singlet oxygen photosensitizer efficiency of berberine, rose bengal, and methylene blue by time course nuclear magnetic resonance (NMR) monitoring of a photochemical 4+2 cycloaddition endoperoxide formation
Berberine, a natural product alkaloid, has been shown to exert biological activity via in situ production of singlet oxygen when photo irradiated. Berberine utilizes singlet oxygen in its putative mechanism of action, wherein it forms an activated complex with DNA and photosensitizes triplet oxygen to singlet oxygen to specifically oxidize guanine residues, thereby halting cell replication and leading to cell death. This has potential application in photodynamic therapy, alongside other such compounds which also act as photosensitizers and produce singlet oxygen in situ. The quantification of singlet oxygen in various photosensitizers, including berberine, is essential for determining their photosensitizer efficiencies. We postulated that the singlet oxygen produced by photoirradiation of berberine would be superior in terms of singlet oxygen production to the aforementioned photosensitizers when irradiated with UV light, but inferior under visible light conditions, due to its strong absorbance of UV wavelengths.
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