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Country-level relationship of OTC medicine consumption and frequency of GP consultation

Hirai et al. | Dec 09, 2024

Country-level relationship of OTC medicine consumption and frequency of GP consultation

The discussion surrounding self-medication with non-prescription medicines has gained significance in healthcare and public health, particularly given the global increase in consumption of non-prescription drugs. This study aimed to examine the association between the frequency of general practitioner (GP) consultations and the proportion of economic resources spent on OTC medicine.

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Implications of various pure tones on Phaseolus vulgaris and Gaultheria shallon

Judit et al. | Jul 13, 2026

Implications of various pure tones on <i>Phaseolus vulgaris</i> and <i>Gaultheria shallon<i>

This study investigated how different sound frequencies (0, 1,000, 5,000, and 15,000 Hz) affect the growth of Phaseolus vulgaris and the transpiration rates of Gaultheria shallon. Although some differences in plant growth were observed, the authors found no consistent evidence that sound frequency enhanced overall growth or transpiration, highlighting the need for further research.

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Differences in Reliability and Predictability of Harvested Energy from Battery-less Intermittently Powered Systems

Sampath et al. | Apr 29, 2020

Differences in Reliability and Predictability of Harvested Energy from Battery-less Intermittently Powered Systems

Solar and radio frequency harvesters serve as a viable alternative energy source to batteries in many cases where the battery cannot be easily replaced. Using specifically designed circuit models, the authors quantify the reliability of different harvested energy sources to identify the most practical and efficient forms of renewable energy.

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Assigning Lightning Seasons to Different Regions in the United States

Hawkins et al. | Sep 07, 2020

Assigning Lightning Seasons to Different Regions in the United States

Climate change is predicted to increase the frequency of severe thunderstorm events in coming years. In this study, the authors hypothesized that (i) the majority of severe thunderstorm events will occur in the summer months in all states examined for all years analyzed, (ii) climate change will cause an unusual number of severe thunderstorm events in winter months in all states, (iii) thundersnow would be observed in Colorado, and (iv.) there would be no difference in the number of severe thunderstorm events between states in any given year examined. They classified lightning seasons in all states observed, with the most severe thunderstorm events occurring in May, June, July, and August. Colorado, New Jersey, Washington, and West Virginia were found to have severe thunderstorm events in the winter, which could be explained by increased winter storms due to climate change (1). Overall, they highlight the importance of quantifying when lightning seasons occur to avoid lightning-related injuries or death.

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Predicting baseball pitcher efficacy using physical pitch characteristics

Oberoi et al. | Jan 11, 2024

Predicting baseball pitcher efficacy using physical pitch characteristics
Image credit: Antoine Schibler

Here, the authors sought to develop a new metric to evaluate the efficacy of baseball pitchers using machine learning models. They found that the frequency of balls, was the most predictive feature for their walks/hits allowed per inning (WHIP) metric. While their machine learning models did not identify a defining trait, such as high velocity, spin rate, or types of pitches, they found that consistently pitching within the strike zone resulted in significantly lower WHIPs.

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