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Analyzing resilience in a sample population as a novel qualifier for triage in psychological first aid

Ramesh et al. | Apr 18, 2023

Analyzing resilience in a sample population as a novel qualifier for triage in psychological first aid
Image credit: Mat Napo

While serving as an immediate address for psychological safety and stability, psychological first aid (PFA) currently lacks the incorporation of triage. Without triage, patients cannot be prioritized in correspondence to condition severity that is often called for within emergency conditions. To disentangle the relevance of a potential triage system to PFA, the authors of this paper have developed a method to quantify resilience - a prominent predictor of the capability to recover from a disaster. With this resilience index, they have quantified resilience of differing age, race, and sex demographics to better inform the practice of PFA and potential demographic prioritization via a triage system.

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Indoor near-field target detection characteristics under radio and radar joint operation at 2.4 GHz ISM band

Koh et al. | Apr 29, 2022

Indoor near-field target detection characteristics under radio and radar joint operation at 2.4 GHz ISM band

In our modern age, the burgeoning use of radios and radars has resulted in competition for electromagnetic spectrum resources. With recent research highlighting solutions to radio and radar mutual interference, there is a desperate need for a cost-effective configuration that permits a radar-radio joint system. In this study, the authors have set out to determine the feasibility of using single-tone continuous-wave radars in a radar-joint system. With this system, they aim to facilitate cost-effective near-field target detection by way of the popularized 2.4-GHz industrial, scientific, and medical (ISM) band.

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An improved video fingerprinting attack on users of the Tor network

Srikanth et al. | Mar 31, 2022

An improved video fingerprinting attack on users of the Tor network

The Tor network allows individuals to secure their online identities by encrypting their traffic, however it is vulnerable to fingerprinting attacks that threaten users' online privacy. In this paper, the authors develop a new video fingerprinting model to explore how well video streaming can be fingerprinted in Tor. They found that their model could distinguish which one of 50 videos a user was hypothetically watching on the Tor network with 85% accuracy, demonstrating that video fingerprinting is a serious threat to the privacy of Tor users.

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Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques

Chatterjee et al. | Oct 25, 2021

Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques

Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.

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