In film, anxiety and depressive disorders are often depicted inaccurately. When viewers are exposed to these inaccurate portrayals, they collect misinformation about the disorders, as well as people who live with them, leading to stigma. This study used a mixed-method descriptive approach to analyze 16 teenagers’ attitudes towards people with anxiety and depression. Results found that while participants understood how these portrayals create stigma, they did not attribute this to misinformation. These results can be used to help both the film industry and the movie-going public better understand the effects of inaccurate storytelling and the extent to which it informs public perception
This paper presents findings on Carcharhinus leucas (bull shark) and Carcharhinus amblyrhynchos (grey reef shark) aggression towards humans at Beqa Adventure Divers in Shark Reef Marine Reserve, Fiji. We hypothesized that grey reef sharks would receive more prods than bull sharks because grey reef sharks are typically more aggressive than bull sharks. The results supported our hypothesis, as an individual grey reef shark received 2.44 prods on average per feed, while a bull shark had an average of 0.61. These findings are meaningful not only to the world’s general understanding of shark aggression, but also to human protection against grey reef sharks as well as public education on bull sharks and the conservation of the species.
The mountain chain of the Western Ghats on the Indian peninsula, a UNESCO World Heritage site, is home to about 200 frog species, 89 of which are endemic. Distinctive to each frog species, their vocalizations can be used for species recognition. Manually surveying frogs at night during the rain in elephant and big cat forests is difficult, so being able to autonomously record ambient soundscapes and identify species is essential. An effective machine learning (ML) species classifier requires substantial training data from this area. The goal of this study was to assess data augmentation techniques on a dataset of frog vocalizations from this region, which has a minimal number of audio recordings per species. Consequently, enhancing an ML model’s performance with limited data is necessary. We analyzed the effects of four data augmentation techniques (Time Shifting, Noise Injection, Spectral Augmentation, and Test-Time Augmentation) individually and their combined effect on the frog vocalization data and the public environmental sounds dataset (ESC-50). The effect of combined data augmentation techniques improved the model's relative accuracy as the size of the dataset decreased. The combination of all four techniques improved the ML model’s classification accuracy on the frog calls dataset by 94%. This study established a data augmentation approach to maximize the classification accuracy with sparse data of frog call recordings, thereby creating a possibility to build a real-world automated field frog species identifier system. Such a system can significantly help in the conservation of frog species in this vital biodiversity hotspot.
The death of George Floyd has shed light on the disproportionate level of policing affecting non-Whites in the United States of America. To explore whether non-Whites were disproportionately targetted by New York City's "Stop and Frisk" policy, the authors analyze publicly available data on the practice between 2003-2019. Their results suggest African Americans were indeed more likely to be stopped by the police until 2012, after which there was some improvement.
Algorithmic trading has been increasingly used by Americans. In this work, we tested whether including the opening, closing, and highest prices in three supervised learning models affected their performance. Indeed, we found that including all three prices decreased the error of the prediction significantly.
The authors looked at how a student's own background influence their attitude towards integration of diverse cultures and ethnicities. While overall students viewed other groups positively, the authors found that groups still indicated they felt judged by their peers.
Overwatering and underwatering grass are widespread issues with environmental and financial consequences. This study developed an accessible method to assess grass water use efficiency (WUE) combining smartphone imaging with open access color unmixing analysis. The method can be applied in automated irrigation systems or apps, providing grass WUE assessment for regular consumer use.
With low-temperature transportation being critical for the progress of research and medical services by preserving biological samples and vaccines, the optimization of cold storage materials is more critical now than ever. The exclusive use of dry ice has its limitations. Notably, it proves insufficient for cold storage during long-range transportation necessary for the delivery of specimens to rural areas. In this article, the authors have proposed a new means of cold storage through the combination of dry ice and ethanol. Upon thorough analysis, the authors have determined their new method as considerably better than the use of pure dry ice across many characteristics, including cold storage capacity, longevity of material, and financial and environmental feasibility.
