Validation of a rapid and sensitive SARS-CoV-2 screening system developed for pandemic-scale infection surveillance

Without any realistic prospect of comprehensive global vaccine coverage and lasting immunity, control of pandemics such as COVID-19 will require implementation of large scale, rapid identification and isolation of infectious individuals to limit further transmission. Here, we describe an automated, high-throughput testing instrument, designed for population-scale testing for SARS-CoV-2 RNA within 25 minutes from inactivated saliva to result, and capable of reporting 3,840 results per hour. This integrated screening platform incorporates continuous flow loading of samples at random intervals to cost-effectively adjust for fluctuations in testing demand. Protecting vulnerable populations during global pandemics requires rapid and sensitive infection surveillance of asymptomatic carriers. This Sentinel surveillance system offers a feasible and scalable approach to complement vaccination, to curb the spread of COVID-19 variants and future pandemics to save lives.

UNIFORM INFERENCE IN A GENERALIZED INTERVAL ARITHMETIC CENTER AND RANGE LINEAR MODEL

Via generalized interval arithmetic, we propose a Generalized Interval Arithmetic Center and Range (GIA-CR) model for random intervals, where parameters in the model satisfy linear inequality constraints. We construct a constrained estimator of the parameter vector and develop asymptotically uniformly valid tests for linear equality constraints on the parameters in the model. We conduct a simulation study to examine the finite sample performance of our estimator and tests. Furthermore, we propose a coefficient of determination for the GIA-CR model. As a separate contribution, we establish the asymptotic distribution of the constrained estimator in Blanco-Fernández (2015, Multiple Set Arithmetic-Based Linear Regression Models for Interval-Valued Variables) in which the parameters satisfy an increasing number of random inequality constraints.

Measuring Mind Wandering During Online Lectures Assessed With EEG

Mind wandering can inhibit learning in multimedia classrooms, such as when watching online lectures. One explanation for this effect is that periods of mind wandering cause learners’ attention to be redirected from the learning material toward task-unrelated thoughts. The present study explored the relationship between mind wandering and online education using electroencephalography (EEG). Participants were asked to attend to a 75 minute educational video lecture, while task-irrelevant auditory tones played at random intervals. The tones were of two distinct pitches, with one occurring frequently (80%) and the other infrequently (20%). Participants were prompted at pseudo-random intervals during the lecture to report their degree of experienced mind wandering. EEG spectral power and event-related potentials (ERP) were compared between states of high and low degrees of self-reported mind wandering. Participants also performed pre/post quizzes based on the lecture material. Results revealed significantly higher delta, theta and alpha band activity during mind wandering, as well as a decreased P2 ERP amplitude. Further, learning scores (improvement on quizzes pre to post) were lower among participants who reported higher degrees of mind wandering throughout the video. The results are consistent with a view that mind wandering during e-learning is characterized by a shift in attention away from the external world and toward internal thoughts, which may be a cause of reduced learning.

A hierarchical clustering method for random intervals based on a similarity measure

A new clustering method for random intervals that are measured in the same units over the same group of individuals is provided. It takes into account the similarity degree between the expected values of the random intervals that can be analyzed by means of a two-sample similarity bootstrap test. Thus, the expectations of each pair of random intervals are compared through that test and a p-value matrix is finally obtained. The suggested clustering algorithm considers such a matrix where each p-value can be seen at the same time as a kind of similarity between the random intervals. The algorithm is iterative and includes an objective stopping criterion that leads to statistically similar clusters that are different from each other. Some simulations to show the empirical performance of the proposal are developed and the approach is applied to two real-life situations.

Impact of Relationship and Communication Variables on Ambulatory Blood Pressure in Advanced Cancer Caregivers

Background Cancer impacts both patients and their family caregivers. Evidence suggests that caregiving stress, including the strain of taking on a new role, can elevate the risk of numerous health conditions, including high blood pressure (BP). However, the caregiver’s psychosocial experiences, including their interpersonal relationship with the patient, may buffer some of the negative physiological consequences of caregiving. Purpose To examine the influence of psychosocial contextual variables on caregiver ambulatory BP. Methods Participants were 81 spouse–caregivers of patients with advanced gastrointestinal or thoracic cancer. For an entire day at home with the patient, caregivers wore an ambulatory BP monitor that took readings at random intervals. Immediately after each BP reading, caregivers reported on physical circumstances (e.g., posture, activity) and psychosocial experiences since the last BP measurement, including affect, caregiver and patient disclosure, and role perceptions (i.e., feeling more like a spouse vs. caregiver). Multilevel modeling was used to examine concurrent and lagged effects of psychosocial variables on systolic and diastolic BP, controlling for momentary posture, activity, negative affect, and time. Results Feeling more like a caregiver (vs. spouse) was associated with lower systolic BP at the same time point. Patient disclosure to the caregiver since the previous BP reading was associated with higher diastolic BP. No lagged effects were statistically significant. Conclusions Caregivers’ psychosocial experiences can have immediate physiological effects. Future research should examine possible cognitive and behavioral mechanisms of these effects, as well as longer-term effects of caregiver role perceptions and patient disclosure on caregiver psychological and physical health.

Exploration of Human-Mediated Interruption Strategies via Spoken Information Removal

Previous research from our laboratory which examined the impact of interruptions on performance in a collaborative communication task, found that interruptions from a synthetic agent, occurring either at fixed or random intervals, had a more deleterious effect on task performance than when interruption timing was determined by a human participant monitoring the communication task (Peters, Romigh, Bradley, & Raj, 2017). These results suggest that interruption times initiated by the human interrupters were more appropriate than the machine-generated ones; however, post-hoc analyses revealed no relation between interruption timing and language information prior to the human interruptions. Given these conflicting results and the demonstrated role of language information in other communication interactions, we aim to identify which spoken language components most motivate human interruption decisions, utilizing methods borrowed from the turn-taking literature (De Ruiter, Mitterer, & Enfield, 2006). Results indicate that listeners leverage prosodic and lexical information in making interruption decisions.

Combination of AM and FM screening as security printed feature

Protection of goods and packaging from counterfeiting and copying, tracking their movement requires improvement of existing labeling and security methods and the development of new ones. Making changes to the image at the prepress stage is the cheapest and easiest way of protection compared to using special printing techniques, special substrates, and inks or additional tags such as RFID. In the article, we suggest a new method to create security printed features, identify them in prints, and confirm the authenticity of the image. The method uses a combination of regular (AM) and stochastic (FM) screening in one image. There are two ways of separating images for AM and FM screening. First is to choose several random intervals in shadows of image tonal distribution and in accordance with values in these intervals original image is separated into two. The second is to separate by structure, for example, use FM screening on edges or textures. We tried Canny edge detector and local binary patterns. By using random values as the parameters, it is possible to generate unique print runs or even individual prints using digital printing. And large variability in the areas of separation gives reason to consider that the suggested method is reliable. Fourier analysis in the suggested method allows not only to detect the presence of security printed features but also to confirm the authenticity of the image on a print. Authentication is implemented by obtaining a digital image of the print by scanning or photographing and comparing the spectral composition of the original image and the digital image of the print. An expert survey showed that after our method presence of a combination of AM and FM screening in images on prints is barely visible. As a result, this method can be used to protect packaging labels with images from copying.