Stability of SARS-CoV-2 on the Army Combat Uniform and Recommendations for Cleaning.

SARS-CoV-2 is the virus responsible for the disease that is known as COVID-19. While there have been numerous studies detailing the survival rates of SARS-CoV-2 on various materials, there are currently no published data regarding whether this virus is stable on standard military uniforms. Consequently, there are no standard operating procedures for washing uniforms once exposed to the virus. This study aimed to determine whether SARS-CoV-2 could be removed from Army combat uniform material by washing with a commercially available detergent and tap water. Washing the fabric with detergent followed by a rinse step with tap water effectively removes detectable viral particles. Importantly, it was found that washing with hot water alone was not effective. Therefore, it is recommended that military personnel wash their uniforms with detergent and water as soon as possible after exposure to SARS-CoV-2; hot water should not be used as a substitute for detergent.

Vaccine Supply Forecasting and Optimization using Deterministic and Probabilistic Approaches

When the pandemic was at its peak, it was a quite difficult task for the government to schedule vaccine supply in various districts of a state. This task became further difficult when vaccines were required to be supplied to various Covid Vaccination Centers (CVCs) at a granular level. This is because there was no data regarding the trend being acquired at each CVC and the population distribution is non-uniform across the district. This led to the arousal of an ambiguous situation for a certain period and hence mismanagement. Now that we have sufficient data across each CVC, we can work on a time series analysis of vaccine requirements in which we can essentially forecast the number of administered doses and optimize the wastage at all atomic CVC levels. © 2023 IEEE.

Uniform consistency for local fitting of time series non-parametric regression allowing for discrete-valued response

Local linear kernel fitting is a popular nonparametric technique for modelling nonlinear time series data. Investigations into it, although extensively made for continuousvalued case, are still rare for the time series that are discrete-valued. In this paper, we propose and develop the uniform consistency of local linear maximum likelihood (LLML) fitting for time series regression allowing response to be discrete-valued under β-mixing dependence condition. Specifically, the uniform consistency of LLML estimators is established under time series conditional exponential family distributions with aid of a beta-mixing empirical process through local estimating equations. The rate of convergence is also provided under mild conditions. Performances of the proposed method are demonstrated by a Monte-Carlo simulation study and an application to COVID-19 data. There is a huge potential for the developed theory contributing to further development of discrete-valued response semiparametric time series models © 2022 American Psychological Association

Towards robust and accurate estimates of the incubation time distribution, with focus on upper tail probabilities and SARS-CoV-2 infection.

Quarantine length for individuals who have been at risk for infection with SARS-CoV-2 has been based on estimates of the incubation time distribution. The time of infection is often not known exactly, yielding data with an interval censored time origin. We give a detailed account of the data structure, likelihood formulation and assumptions usually made in the literature: (i) the risk of infection is assumed constant on the exposure window and (ii) the incubation time follows a specific parametric distribution. The impact of these assumptions remains unclear, especially for the right tail of the distribution which informs quarantine policy. We quantified bias in percentiles by means of simulation studies that mimic reality as close as possible. If assumption (i) is not correct, then median and upper percentiles are affected similarly, whereas misspecification of the parametric approach (ii) mainly affects upper percentiles. The latter may yield considerable bias. We suggest a semiparametric method that provides more robust estimates without the need of a parametric choice. Additionally, we used a simulation study to evaluate a method that has been suggested if all infection times are left censored. It assumes that the width of the interval from infection to latest possible exposure follows a uniform distribution. This assumption gave biased results in the exponential phase of an outbreak. Our application to open source data suggests that focus should be on the level of information in the observations, as expressed by the width of exposure windows, rather than the number of observations.

Simulation of COVID-19 Ultraviolet Disinfection Using Coupled Ray Tracing and CFD

Ultraviolet Germicidal Irradiance (UVGI) is the effective technique of inactivating disease-causing bacteria, mould spores, fungi, and viruses using ultraviolet radiation. In this study, we seek to quantify the efficacy and COVID-19 infection risk reduction achieved by UVGI in the upper unoccupied zone of a room so that we may specify the type and placement of UVGI emitters optimally. We present a computational fluid dynamics (CFD) based approach to model disinfection of aerosolized pathogens in a non-uniform ultraviolet field with mixing driven by air exchange and temperature gradients. We validate our CFD against simple calculation methods for UVGI effectiveness in well mixed spaces, and we integrate it with the Wells-Riley model of airborne infection risk to assess the relative benefit of UVGI with and against other measures. We demonstrate an order of magnitude reduction in infection risk as a result of applying UVGI, as well as the ability to quantify infection risk in non-well-mixed settings where simplified calculations methods do not apply. © International Building Performance Simulation Association, 2022

Nonmarital relationships: Introduction

In the United States today, adults live in a variety of nonmarital relationships and situations, ranging from committed partners who cohabit, to people who cohabit with differing levels of commitment,1 to committed partners who live apart. The COVID-19 pandemic has affected all of these relationship forms differently. The coming years will reveal the extent to which these impacts will alter the social and legal landscape around nonmarital relationships. These relationships have produced a range of responses in both existing law and law reform efforts. Meanwhile, scholars from various disciplines are studying nonmarital relationships, including polyamorous arrangements and other communities of choice. The Uniform Law Commission has developed a new proposal for uniformity in this area that addresses property rights and equitable claims, but not the many other legal rights and obligations that might accrue. Although the resolution of property disputes between nonmarital partners remains a critical concern, scholars have become interested in exploring the availability of other types of legal rights and the impact of demographic variations that the law has previously overlooked or oversimplified. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Comprehensive analysis of the novel omicron receptor AXL in cancers.

The SARS-CoV-2 is constantly mutating, and the new coronavirus such as Omicron has spread to many countries around the world. Anexelekto (AXL) is a transmembrane protein with biological functions such as promoting cell growth, migration, aggregation, metastasis and adhesion, and plays an important role in cancers and coronavirus disease 2019 (COVID-19). Unlike angiotensin-converting enzyme 2 (ACE2), AXL was highly expressed in respiratory system cells. In this study, we verified the AXL expression in cancer and normal tissues and found AXL expression was strongly correlated with cancer prognosis, tumor mutation burden (TMB), the microsatellite instability (MSI) in most tumor types. Immune infiltration analysis also demonstrated that there was an inextricable link between AXL expression and immune scores in cancer patients, especially in BLCA, BRCA and CESC. The NK-cells, plasmacytoid dendritic cells, myeloid dendritic cells, as one of the important components of the tumor microenvironment, were highly expressed AXL. In addition, AXL-related tumor neoantigens were identified and might provide the novel potential targets for tumor vaccines or SARS-Cov-2 vaccines research in cancer patients.

In-situ fabrication of 3D interior hotspots templated with a protein@Au core-shell structure for label-free and on-site SERS detection of viral diseases

Nanoscale plasmonic hotspots play a critical role in the enhancement of molecular Raman signals, enabling the sensitive and reliable trace analysis of biomedical molecules via surface-enhanced Raman spectroscopy (SERS). However, effective and label-free SERS diagnoses in practical fields remain challenging because of clinical samples' random adsorption and size mismatch with the nanoscale hotspots. Herein, we suggest a novel SERS strategy for interior hotspots templated with protein@Au core-shell nanostructures prepared via electrochemical one-pot Au deposition. The cytochrome c and lysates of SARS-CoV-2 (SLs) embedded in the interior hotspots were successfully functionalized to confine the electric fields and generate their optical fingerprint signals, respectively. Highly linear quantitative sensitivity was observed with the limit-of-detection value of 10-1 PFU/ mL. The feasibility of detecting the targets in a bodily fluidic environment was also confirmed using the proposed templates with SLs in human saliva and nasopharyngeal swabs. These interior hotspots templated with the target analytes are highly desirable for early and on-site SERS diagnoses of infectious diseases without any labeling processes.

Preparation of Nylon-6 micro-nanofiber composite membranes with 3D uniform gradient structure for high-efficiency air filtration of ultrafine particles

[Display omitted] • Nylon-6 micro-nanofiber composite membranes had uniform space gradient structure. • Composite membranes had good filtration performance against ultrafine particles. • The masks had stable protection performance and comfortable wearing experience. Compared of traditional melt-blown nonwoven materials, micro-nanofiber composite membranes with uniform spatial gradient structure will be the development trend of high efficiency and low resistance filtration materials, especially against ultrafine particles with kinetic diameter less than 0.25 (PM 0.25). Herein, Nylon-6 micro-nanofiber composite membranes (Nylon-6 FCMs) with three-dimensional (3D) uniform gradient structure were prepared by air jet spinning under the help of PEO. The fluffy 3D gradient structure possessed a uniform gradual pore gradient from large to small, ensuring the PM 0.25 were captured by exact grading under high gas flow due to the form of special "trumpet-like" gas passage inside the membranes. The structure of Nylon-6 FCMs could be controlled and exhibited high tensile strength, good moisture permeability, excellent filtration performance. Among them, the FCM-1 with a uniform gradual pore gradient could achieve the optimal filtering performance with filtration efficiency (99.99 %) and pressure drop (144 Pa). The mask prepared using this Nylon-6 FCMs also displayed good protective effect with comparable air permeability (221.84 mm·s−1) and moisture permeability (181.84 g·m−2·h−1) compared of commercial melt-blown masks. Most importantly, this mask prepared still could maintain good filtration performance even in high temperature and high humidity environment, providing users more comfortable wearing experience and stable protection performance, especially under the current COVID-19 outbreak. [ FROM AUTHOR]

An extended approach for the generalized powered uniform distribution.

A new uniform distribution model, generalized powered uniform distribution (GPUD), which is based on incorporating the parameter k into the probability density function (pdf) associated with the power of random variable values and includes a powered mean operator, is introduced in this paper. From this new model, the shape properties of the pdf as well as the higher-order moments, the moment generating function, the model that simulates the GPUD and other important statistics can be derived. This approach allows the generalization of the distribution presented by Jayakumar and Sankaran (2016) through the new GPUD ( J - S ) distribution. Two sets of real data related to COVID-19 and bladder cancer were tested to demonstrate the proposed model's potential. The maximum likelihood method was used to calculate the parameter estimators by applying the maxLik package in R. The results showed that this new model is more flexible and useful than other comparable models.

Implementation and characterisation of a sterilisation module consisting of novel 265 nm UVC LED packages

To efficiently fight against the COVID-19 pandemic, a sterilisation module using 265 nm UVC LED packages was developed. In this paper, the performance of the sterilisation module in terms of irradiance uniformity, junction temperature increase and sterilisation efficiency were characterised. The irradiance uniformity fluctuation across the four corners and the centre point in a 130 mm × 130 mm area was below 10%, exhibiting good uniformity. Uniform irradiance was important to achieve consistent sterilisation, which was the primary difference between the UVC LED package developed and commercial UVC LED packages. Key to achieving uniform irradiance was the structure, consisting of a stacked silicon reflector and a secondary optical lens designed by ray tracing simulation. The junction temperature increase of the 265 nm UVC LED package driving at 200 mA was only 28°C, sufficiently low to exhibit better reliability and performance. A 99.99% sterilisation efficiency on E. coli bacteria was achieved within one minute with UV dosage of 2.7 mJ/cm2 at 200 mA driving current. From the results, the novel 265 nm UVC LED package was a time-efficient solution for disinfection purposes. © 2021 The Hong Kong Institution of Engineers.

Design COVID-19 Ontology: A Healthcare and Safety Perspective

The COVID-19 pandemic has flooded a vast amount of information into the world. To help control this situation, good utilization of the overflow in data is required. However, data come in different forms, posing numerous challenges in subsequent processing. Therefore, a uniform knowledge representation of COVID-19 information is needed, and ontology can play a role. The ontology will model patient healthcare-related data, ranging from symptoms to side effects and medical conditions, and the necessary precautions, especially for healthcare workers, to obtain protection from the COVID-19 virus. We followed Sánchez’s methodology to build the vocabularies, which include current ontology concepts, W3C standards RDF, OWL and SWRL. This work shows promising results that can be applied by different organizations. © 2022, The Author(s).

Uniform Persistence and Global Attractivity in a Delayed Virus Dynamic Model with Apoptosis and Both Virus-to-Cell and Cell-to-Cell Infections

In this paper, we study the global dynamics of a delayed virus dynamics model with apoptosis and both virus-to-cell and cell-to-cell infections. When the basic reproduction number R0>1, we obtain the uniform persistence of the model, and give some explicit expressions of the ultimate upper and lower bounds of any positive solution of the model. In addition, by constructing the appropriate Lyapunov functionals, we obtain some sufficient conditions for the global attractivity of the disease-free equilibrium and the chronic infection equilibrium of the model. Our results extend existing related works.

Expert Decision Support System for Donor Identification Using Multi-Agent System

Convalescent Plasma (CP) therapy is an efficient method in the treatment of COVID-19 patients who either have a weak immune system or who are early in their illness. The notable setback for the implementation of the CP therapy lies in understanding the availability and spatial distribution of plasma donors. A multi-agent-based expert system is proposed in this paper to identify a suitable plasma donor in a short span and also in an efficient manner. Moreover, the issues with blood banks are twofold in connection with uneven intra-state and interstate distribution and lacuna of necessary facilities like the Component Blood Separation Units (CBSU) and Apheresis. The proposed expert system would remove the barriers of non-uniform distribution of blood banks and facilities across the country, and will provide a suitable solution to overcome the pandemic using multi-agent systems if implemented systematically. © 2021 IEEE.

Event-Driven Malicious URL Extractor

Cyber-attacks are attacks that are commonly carried out in order to obtain sensitive information or disrupt internet-based services. Recent occurrences, both internationally and locally, have shown an influx of these attacks expanding rapidly through the use of malicious URLs (Uniform Resource Locators). Traditional measures, including such blacklisting malicious URLs, make it extremely difficult to respond to such attacks in a timely and efficient manner. Most existing solutions remain restricted in terms of scalability and proactive user safeguarding in situations when freshly formed URLs are correlated with a recent event, such as Covid-19 related frauds. The proposed solution is presented with the primary aim of addressing traditional system limitations and offering an interface for users to protect themselves by detecting phishing/malicious URLs in real time. In this research, we will examine extracting user-input event-related keywords and leveraging NLP (Natural Language Processing) algorithms to match them with the accompanying URL (Uniform Resource Locator) token data to determine whether the URLs are malicious or benign. © 2021 IEEE.

Enhanced viral inactivation by combined ultraviolet light and heat

Viral sensitivity to high temperature and ultraviolet (UV) irradiation has been extensively studied. However, there is still little attention paid to study the joint effect of these two physical factors. Since the outbreak of the COVID-19 pandemic has necessitated the advances of disinfection techniques, rapid and effective viral inactivation by combining heat and UV light is worth investigating. This work focuses on developing such a device combining UV light-emitting diode light sources and a heater. Moreover, two UV bands have been studied in this work, namely 280 nm ultraviolet-C (UVC) and 365 nm ultraviolet-A (UVA. A) control system is developed to accurately control both the heating temperature of the device and the irradiance of the dual-spectral UV light sources. The performance of the device is verified by a series of experimental measurements. More importantly, the disinfection effect of the device has been verified by the experiments based on non-pathogenic carrier virus commonly used in the laboratory. The disinfection doses of the 280 nm UVC and 365 nm UVA light sources under the high temperature synergy have been examined. The experimental results show that when combined with a heating temperature of 60 C-circle, the cumulative UV radiation doses required for sufficient viral inactivation can be greatly reduced.

Optimal Design of a Parallel Manipulator for Aliquoting of Biomaterials Considering Workspace and Singularity Zones

This article presents the concept of a robotic system for aliquoting of biomaterial, consisting of a serial manipulator in combination with a parallel Delta-like robot. The paper describes a mathematical formulation for approximating the geometric constraints of the parallel robot as a set of solutions to a system of nonlinear inequalities. The analysis of the workspace is carried out, taking into account singularity zones, using a method based on the analysis of the Jacobian matrix of the mechanism and the interference of links. An optimal design procedure is proposed for the dimensional synthesis based on a criterion for maximizing the volume of the workspace, taking into account the ambiguity of the solution of the inverse kinematics. Simulation results are reported and discussed to propose a suitable design solution.

Standardizing States of Emergency: Fragmented Legitimacy of Model Public Health Lawmaking

The promulgation of model laws—exemplary statutes that states can voluntarily choose to adopt—is a prominent strategy that reformers in public health agencies, the legal academy, and non governmental organizations use to improve US public health law and make it more uniform. This article applies the science and technology studies literature on standardization to the process of model lawmaking to analyze how developers negotiate between alternative forms of expertise and utilize different drafting processes to secure the techno-political legitimacy of their model statutes. Drawing on archival records and interviews with thirty-four experts involved in the development of four model public health laws produced between 1999 and 2007, I show how developers work to satisfy multiple, and, at times, competing, audiences. I observe that developers leveraged forms of legal expertise to secure their model laws’ technical legitimacy and emphasized their objectivity, representativeness, and flexibility to promote their political legitimacy. Comparing the four model laws across several indicia of legitimacy, I find that the developers experienced varying degrees of success. This study contributes to the socio legal scholarship on model laws by revealing how they are able to achieve legitimacy, albeit fragmented, even in the context of scientific uncertainty.

A review of different ventilation modes on thermal comfort, air quality and virus spread control.

In the era of Corona Virus Disease 2019 (COVID-19), inappropriate indoor ventilation may turn out to be the culprit of microbial contamination in enclosed spaces and deteriorate the environment. To collaboratively improve the thermal comfort, air quality and virus spread control effect, it was essential to have an overall understanding of different ventilation modes. Hence, this study reviewed the latest scientific literature on indoor ventilation modes and manuals of various countries, identified characteristics of different ventilation modes and evaluated effects in different application occasions, wherefore to further propose their main limitations and solutions in the epidemic era. For thermal comfort, various non-uniform ventilation modes could decrease the floor-to-ceiling temperature difference, draft rate or PPD by 60%, 80% or 33% respectively, or increase the PMV by 45%. Unsteady ventilation modes (including intermittent ventilation and pulsating ventilation) could lower PPD values by 12%-37.8%. While for air quality and virus spread control, non-uniform ventilation modes could lower the mean age of air or contaminants concentration by 28.3%-47% or 15%-47% respectively, increase the air change efficiency, contaminant removal effectiveness or protection efficiency by 6.6%-10.4%, 22.6% or 14%-50% respectively. Unsteady ventilation mode (pulsating ventilation) could reduce the peak pollutant concentration and exposure time to undesirable concentrations by 31% and 48% respectively. Non-uniform modes and unsteady modes presented better performance in thermal comfort, air quality and virus spread control, whereas relevant performance evaluation indexes were still imperfect and the application scenarios were also limited.

Health care worker knowledge and attitudes towards uniform laundering during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic raised concerns towards domestic laundering of healthcare worker (HCW) uniforms; this is common practice in countries such as the United Kingdom (UK) and United States. Previous research suggested 4-32% of nurses did not adhere to laundry policies, which could be an infection control risk. This study aimed to investigate the knowledge and attitudes of UK healthcare workers towards domestic laundering of uniforms during the COVID-19 pandemic. METHODS: Online and paper questionnaires were distributed to HCWs and nursing students who regularly wear uniforms. Differences in knowledge between HCWs were analyzed by Chi-squared tests and attitudes were examined using exploratory factor analysis. RESULTS: About 86% of participants (n = 1099 of 1277) laundered their uniforms domestically. Respondents were confident in laundering their uniforms appropriately (71%), however 17% failed to launder at the recommended temperature (60°C). Most participants (68%) would prefer their employer launder their uniforms, with mixed negative emotions towards domestic laundering. Limited provision of uniforms and changing and/or storage facilities were a barrier to following guidelines. CONCLUSION: Most HCWs domestically launder their uniforms, despite a preference for professional laundering. One-fifth of HCWs deviated from the UK National Health Service uniform guidelines; onsite changing facilities were the most significant barrier towards adherence.