SARS-CoV-2 air and surface contamination on a COVID-19 ward and at home

SARS-CoV-2 has been detected both in air and on surfaces, but questions remain about the patient-specific and environmental factors affecting virus transmission to the environment. Additionally, more detailed information on viral findings in air is needed. This cross-sectional study presents results from 259 air and 252 surface samples from the surroundings of 23 hospitalized and eight home-treated COVID-19 patients between July 2020 and March 2021 and compares the results between the measured environments and patient factors. The proportions of PCR-positive air and surface samples showed statistical similarity in hospital and in the home. In four cases, positive environmental samples were detected even after the patients had developed a neutralizing IgG response. SARS-CoV-2 RNA was detected in the following particle sizes: 0.65–4.7 µm, >7 µm, >10 µm, and <100 µm. Appropriate infection control against airborne and surface transmission routes is needed in both environments, even after antibody production has begun.

Quantification of Similar Neurodegeneration Across Geriatric Concussions and Alzheimer’s Disease

Geriatric mild traumatic brain injury (mTBI) is a risk factor for Alzheimer’s disease (AD), but few studies have studied how the neuroanatomic effects of these conditions can converge onto similar brain structure trajectories. Here we use magnetic resonance imaging to investigate similarities between mTBI and AD across both white and gray matter (WM and GM, respectively) using measures like fractional anisotropy (FA, a surrogate measure of WM integrity) and cortical thickness. We identify statistically significant similarities in neurodegeneration across mTBI (N = 33; age µ = 63 years (y), σ = 11 y) and AD (N = 66; age µ = 76 y, σ = 9 y) by testing for statistical equivalences of mean FA and cortical thickness. Both WM and GM are found to exhibit significant similarities in how mean FA and cortical thickness decrease, respectively, across mTBI and AD. For WM, the broadest spatial extent of statistical similarity between conditions, quantified as percentages of structures’ volumes, is found within the superior fronto-occipital fasciculus (left (L): 91%, p &lt; 0.05; right (R): 95%, p &lt; 0.05), and in the crura of the fornix (L: 65%, p &lt; 0.05; R: 80%, p &lt; 0.05). Across mTBI and AD, cortical thinning trajectories are most similar in the superior precentral sulcus (L: 91%, p &lt; 0.05; R: 100%, p &lt; 0.05), and anterior lateral sulcus (L: 75%, p &lt; 0.05; R: 86%, p &lt; 0.05). Future studies should leverage such findings to identify AD risk factors in mTBI patients.

Statistical Similarity of Mortality and Recovery Ratios for Covid-19 Patients based on Gender and Age

Background: Studying the behavior of patients infected to Covid-19 is an essential issue for health authorities during the global pandemic, so the aim of this study is to investigate the statistical similarity between the recovery and mortality ratios based on the patients’ age and gender. To this purpose, the well-known statistical testing method of Kolmogorov-Smirnov has been utilized to investigate the similarity of distribution functions for mortality and recovery rates for patients infected to Covid-19. Results: Data for 1015 patients resulted in dead, recovery, and transferred have been collected and analyzed. The age is cross-classified by gender where the rates’ cumulative distribution functions are independently calculated and depicted for females and males. The results revealed there is no significant difference between the distribution functions of mortality and recovery rates by gender but there is by age. Conclusion: The research results would support the health authorities to manage the admission and discharging procedures of the Covid-19 patients where the hospitality services are traditionally provided differently by gender. Doi: 10.28991/HIJ-2021-02-04-05 Full Text: PDF

Distribution-Based Similarity Measures Applied to Laboratory Results Matching

The use of international laboratory terminologies inside hospital information systems is required to conduct data reuse analyses through inter-hospital databases. While most terminology matching techniques performing semantic interoperability are language-based, another strategy is to use distribution matching that performs terms matching based on the statistical similarity. In this work, our objective is to design and assess a structured framework to perform distribution matching on concepts described by continuous variables. We propose a framework that combines distribution matching and machine learning techniques. Using a training sample consisting of correct and incorrect correspondences between different terminologies, a match probability score is built. For each term, best candidates are returned and sorted in decreasing order using the probability given by the model. Searching 101 terms from Lille University Hospital among the same list of concepts in MIMIC-III, the model returned the correct match in the top 5 candidates for 96 of them (95%). Using this open-source framework with a top-k suggestions system could make the expert validation of terminologies alignment easier.

SARS-CoV-2 air and surface contamination on a COVID-19 ward and at home

SARS-CoV-2 has been detected both in air and on surfaces, but questions remain about the patient-specific and environmental factors affecting virus transmission to the environment. Additionally, more detailed information on viral findings in air is needed. This cross-sectional study presents results from 259 air and 252 surface samples from the surroundings of 23 hospitalized and eight home-treated COVID-19 patients between July 2020 and March 2021 and compares the results between the measured environments and patient factors. The proportions of PCR-positive air and surface samples showed statistical similarity in hospital and in the home. In four cases, positive environmental samples were detected even after the patients had developed a neutralizing IgG response. SARS-CoV-2 RNA was detected in the following particle sizes: 0.65–4.7 μm, >7 μm, >10 μm, and <100 μm. Appropriate infection control against airborne and surface transmission routes is needed in both environments, even after antibody production has begun.

Use of audiovisual media to enhance patients' knowledge regarding the oral adverse effects of oncology treatment

Objective: the present study aimed to evaluate the efficacy of didactic alternatives, namely the audiovisualmedia, in conveying information regarding the oral adverse effects of oncology treatment in cancer patients.Methods: cancer patients were randomly divided into two groups: control group (n = 40) and audiovisualgroup (n = 36). The control group received verbal information regarding the oral side effects of cancer treatment.Conversely, the audiovisual group received the same verbal information, along with an illustrativeaudiovisual media presentation. Additionally, questionnaires on the subject were administered before andafter the intervention by the dental team. Results: the current study employed Fisher’s exact test for statisticalanalysis, and the results showed statistical similarity between the two groups (P > 0.05). Both educational approaches achieved the intended objective. Conclusion: a well-conducted dialogue can create adequate awareness among cancer patients and improve adaptation. Optionally, the use of innovative techniques, such as audiovisual resources, was observed to be an accessible and efficient alternative that can also be used in patient education. Therefore, educational videos can be used to improve patients understanding, adherence to therapeutic regimens, and quality of life and contribute to a better prognosis.

Energy constraints on brain network formation

Energy constraints are a fundamental limitation of the brain, which is physically embedded in a restricted space. The collective dynamics of neurons through connections enable the brain to achieve rich functionality, but building connections and maintaining activity come at a high cost. The effects of reducing these costs can be found in the characteristic structures of the brain network. Nevertheless, the mechanism by which energy constraints affect the organization and formation of the neuronal network in the brain is unclear. Here, it is shown that a simple model based on cost minimization can reproduce structures characteristic of the brain network. With reference to the behavior of neurons in real brains, the cost function was introduced in an activity-dependent form correlating the activity cost and the wiring cost as a simple ratio. Cost reduction of this ratio resulted in strengthening connections, especially at highly activated nodes, and induced the formation of large clusters. Regarding these network features, statistical similarity was confirmed by comparison to connectome datasets from various real brains. The findings indicate that these networks share an efficient structure maintained with low costs, both for activity and for wiring. These results imply the crucial role of energy constraints in regulating the network activity and structure of the brain.

Devnagari Handwritten Characters Image Super-Resolution based on Enhanced SRGAN

The difficulty in machine learning-based image super-resolution is to generate high-frequency component in an image without introducing any artifacts. In this paper, Devnagari handwritten characters image using a generative adversarial network with a classifier is generated in high-resolution which is also classifiable. The generator architecture is modified by removing all batch normalization layers in generator architecture with a residual in residual dense block. Batch normalization is removed because it produces unwanted artifacts in the generated images. A Devnagari handwritten characters classifier is built using CNN. The classifier is used in the network to calculate the content loss. The adversarial loss is obtained from the GAN architecture and both of the losses are added to obtain total loss. Generated HR images is validated using six different evaluation metrics among which MSE, PSNR determines pixel-wise difference and SSIM compares images perceptually. Similarly, FID is used to measure the statistical similarity between the batch of generated images and its original batch. Finally, the Gradient similarity is used to assess the quality of the generated image. From the experimental results, we obtain MSE, PSNR and SSIM as 0.0507, 12.95(dB) and 0.8172 respectively. Similarly, the FID value obtained was 27.5 with the classification accuracy of image data of 98%. The gradient similarity between the generated image and the ground truth obtained was 0.9124.

Olfactory Metamers or Analogous Multicomponent Odors?

A recent paper used predictive modeling to guide the creation of olfactory metamers, odors that smell identical yet do not share physicochemical features. This reanalysis of their validation performed on human subjects shows that the results do not meet the threshold for statistical similarity.

A Study of The Effect of Black Swan Events on Stock Markets – and Developing a Model for Predicting and Responding to them

Black Swan events are rare and seemingly random in nature. In the famous paper by Nassim Nicholas Taleb, it is posited that Black Swan events cannot be reliably predicted, and it is instead important to be prepared for them at all times (Musgrave, 2009). This study aims to understand various Black Swan events in recent history from the point of view of equity markets, and performs a comparative study between different events across time and geography in order to understand if there are any standard early indicators. In this study, a total of seven global events have been observed within the selected period from FY 1997 to FY 2019. All events have been considered from the standpoint of their impact on S&P 500 index. Apart from assessing the sensitivity factor, the impact of each event was observed for any statistical similarity through a One-Way ANOVA test of their normalised values.