The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.
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Understanding the Relationship Between Perception and Reality Related to Public Safety: A Case Study of Public Opinion on Local Law Enforcement in Andover, MA
A small town with low crime rates and relatively high education levels usually gives the perception of a safe and comfortable community. This study explored the connection between this perception, as defined by public opinion, and reality, as defined by US Census and FBI crime data.
Read More...Genetic underpinnings of the sex bias in autism spectrum disorder
Here, seeking to identify a possible explanation for the more frequent diagnosis of autism spectrum disorder (ASD) in males than females, they sought to investigate a potential sex bias in the expression of ASD-associated genes. Based on their analysis, they identified 17 ASD-associated candidate genes that showed stronger collective sex-dependent expression.
Read More...Contribution of environmental factors to genetic variation in the Pacific white-sided dolphin
Here the authors sought to understand the effects of different variables that may be tied to pollution and climate change on genetic variation of Pacific white-sided dolphins, a species that is currently threatened by water pollution. Based on environmental data collected alongside a genetic distance matrix, they found that ocean currents had the most significant impact on the genetic diversity of Pacific white-sided dolphins along the Japanese coast.
Read More...A Cloud-Enabled Communication Strategy for Wildfire Alerts
The traditional alert system in California consists of Wireless Emergency Alerts (WEAs), which lack location specificity, and sign-up-based technology which is limited by the number of sign ups. Those who do not have phones or have a silence option on their devices are most at risk from the current alert system. Here the authors developed cloud-enabled crisis connection for disaster alerts (CRISIS-CONNECT) to mitigate problems associated with the current alert system.
Read More...The impact of attending a more selective college on future income
Debates around legacy preferences, recruited athletes, and affirmative action in U.S. college admissions often focus on the belief that graduating from a more selective institution leads to higher future earnings. The study hypothesized a positive correlation between college selectivity and future income due to enhanced resources and opportunities.
Read More...Effects of Common Pesticides on Population Size, Motor Function, and Learning Capabilities in Drosophilia melanogaster
In this study, the authors examined the effects of commonly used pesticides (metolachlor, glyphosate, chlorpyrifos, and atrazine) on population size, motor function, and learning in Drosophila melanogaster.
Read More...Expressional correlations between SERPINA6 and pancreatic ductal adenocarcinoma-linked genes
Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, with early diagnosis and treatment challenges. When any of the genes KRAS, SMAD4, TP53, and BRCA2 are heavily mutated, they correlate with PDAC progression. Cellular stress, partly regulated by the gene SERPINA6, also correlates with PDAC progression. When SERPINA6 is highly expressed, corticosteroid-binding globulin inhibits the effect of the stress hormone cortisol. In this study, the authors explored whether there is an inverse correlation between the expression of SERPINA6 and PDAC-linked genes.
Read More...Uncovering mirror neurons’ molecular identity by single cell transcriptomics and microarray analysis
In this study, the authors use bioinformatic approaches to characterize the mirror neurons, which are active when performing and seeing certain actions. They also investigated whether mirror neuron impairment was connected to neural degenerative diseases and psychiatric disorders.
Read More...DNA-SEnet: A convolutional neural network for classifying DNA-asthma associations
In this study, the authors developed a model named DNA Sequence Embedding Network (DNA-SEnet) to classify DNA-asthma associations using their genomic patterns.
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