In this article, the authors investigate the RNA expression differences between groups of chronic cocaine abusers and drug-free subjects.
Read More...TNF signaling pathway upregulation as a potential pharmaceutical target for cocaine-addicted individuals
In this article, the authors investigate the RNA expression differences between groups of chronic cocaine abusers and drug-free subjects.
Read More...Solving a new NP-Complete problem that resembles image pattern recognition using deep learning
In this study, the authors tested the ability and accuracy of a neural net to identify patterns in complex number matrices.
Read More...Environmentally-friendly graphene conductive ink using graphene powder, polystyrene, and waste oil
In this article, the authors propose an effective, environmentally-friendly method of producing conductive ink using expired waste oil, polystyrene, and graphene.
Read More...Population Forecasting by Population Growth Models based on MATLAB Simulation
In this work, the authors investigate the accuracy with which two different population growth models can predict population growth over time. They apply the Malthusian law or Logistic law to US population from 1951 until 2019. To assess how closely the growth model fits actual population data, a least-squared curve fit was applied and revealed that the Logistic law of population growth resulted in smaller sum of squared residuals. These findings are important for ensuring optimal population growth models are implemented to data as population forecasting affects a country's economic and social structure.
Read More...Zinc-related Treatments Combined with Chloroquine and Gemcitabine for Treating Pancreatic Cancer
Pancreatic cancer is one of the deadliest cancers, with a 10% 5-year survival rate. The authors studied various dosages of TPEN and zinc in combination with Chloroquine and Gemcitabine as treatments to reduce cell proliferation. Results showed that when combined with Chloroquine and Gemcitabine, zinc and TPEN both significantly lowered cell proliferation compared to Gemcitabine, suggesting a synergistic effect that resulted in a more cytotoxic treatment. Further research and clinical trials on this topic are needed to determine whether this could be a viable treatment for pancreatic cancer.
Read More...Reimagize – a digital card-based roleplaying game to improve adolescent girls’ body image
Reimagize, a role-playing with decision-making, was conjured, implementing social psychological concepts like counter-stereotyping and perspective-taking. As the game works implicitly to influence body image, it even counters image issues beyond personal body dissatisfaction. This study explored whether a digital role-playing card game, incorporating some of the most common prejudices of body image (like size prejudice, prejudices from the media, etc.) as identified by a digital survey/questionnaire completed by Indian girls aged 11-21, could counter these issues and reduce personal body dissatisfaction.
Read More...Using explainable artificial intelligence to identify patient-specific breast cancer subtypes
Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.
Read More...Understanding investors behaviors during the COVID-19 outbreak using Twitter sentiment analysis
The authors examine a relationship between tweet sentiment and stock market behavior during the early weeks of the COVID-19 pandemic.
Read More...Artificial Intelligence Networks Towards Learning Without Forgetting
In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.
Read More...Floor level estimation using MEMS pressure sensors
The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.
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