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In this article the authors look at sugar consumption and the relationship to productivity in the work/labor force.

The authors looked at potential downstream effects of raising the minimum wage. Specifically they focused on taxable wages, employment, and firm counts.

The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.

The challenge of accurately identifying shark species is crucial for biodiversity monitoring but is often hindered by time-consuming and labor-intensive manual methods. To address this, SharkNet, a CNN model based on AlexNet, achieved 93% accuracy in classifying shark species using a limited dataset of 1,400 images across 14 species. SharkNet offers a more efficient and reliable solution for marine biologists and conservationists in species identification and environmental monitoring.

The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.

The authors looked at the relationship between unemployment and minimum wage in Turkey (Türkiye). They found that there is a positive correlation between minimum wage and unemployment.

Female employment rates in South Korea are far below those of other countries that are members of the Organization for Economic Co-operation and Development. We assessed job satisfaction, job retention, and the underlying factors that impact these variables for both genders and various ages through a survey. Among 291 adult participants (161 women, 130 men) aged 20 to 59, working in various fields, 95% of responders were college graduates. These results suggest that even highly educated women feel more pressure from an innate sense of responsibility and societal perception to care for children than men.

Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.

Here, seeking to understand the correlation of 50 of the most important economic indicators with inflation, the authors used a rolling linear regression to identify indicators with the most significant correlation with the Month over Month Consumer Price Index Seasonally Adjusted (CPI). Ultimately the concluded that the average gasoline price, U.S. import price index, and 5-year market expected inflation had the most significant correlation with the CPI.