A numerical study of COVID-19 epidemic model with vaccination and diffusion.

The coronavirus infectious disease (or COVID-19) is a severe respiratory illness. Although the infection incidence decreased significantly, still it remains a major panic for human health and the global economy. The spatial movement of the population from one region to another remains one of the major causes of the spread of the infection. In the literature, most of the COVID-19 models have been constructed with only temporal effects. In this paper, a vaccinated spatio-temporal COVID-19 mathematical model is developed to study the impact of vaccines and other interventions on the disease dynamics in a spatially heterogeneous environment. Initially, some of the basic mathematical properties including existence, uniqueness, positivity, and boundedness of the diffusive vaccinated models are analyzed. The model equilibria and the basic reproductive number are presented. Further, based upon the uniform and non-uniform initial conditions, the spatio-temporal COVID-19 mathematical model is solved numerically using finite difference operator-splitting scheme. Furthermore, detailed simulation results are presented in order to visualize the impact of vaccination and other model key parameters with and without diffusion on the pandemic incidence. The obtained results reveal that the suggested intervention with diffusion has a significant impact on the disease dynamics and its control.

Continuous Glucose Monitoring in Hypoxic Environments Based on Water Splitting-Assisted Electrocatalysis

Conventional enzyme-based continuous glucose sensors in interstitial fluid usually rely on dissolved oxygen as the electron-transfer mediator to bring electrons from oxidase to electrode while generating hydrogen peroxide. This may lead to several problems. First, the sensor may provide biased detection results owing to fluctuation of oxygen in interstitial fluid. Second, the polymer coatings that regulate the glucose/oxygen ratio can affect the dynamic response of the sensor. Third, the glucose oxidation reaction continuously produces corrosive hydrogen peroxide, which may compromise the long-term stability of the sensor. Here, we introduce an oxygen-independent nonenzymatic glucose sensor based on water splitting-assisted electrocatalysis for continuous glucose monitoring. For the water splitting reaction (i.e., hydrogen evolution reaction), a negative pretreatment potential is applied to produce a localized alkaline condition at the surface of the working electrode for subsequent nonenzymatic electrocatalytic oxidation of glucose. The reaction process does not require the participation of oxygen;therefore, the problems caused by oxygen can be avoided. The nonenzymatic sensor exhibits acceptable sensitivity, reliability, and biocompatibility for continuous glucose monitoring in hypoxic environments, as shown by the in vitro and in vivo measurements. Therefore, we believe that it is a promising technique for continuous glucose monitoring, especially for clinically hypoxic patients.

Effective recycling of disposable medical face masks for sustainable green concrete via a new fiber hybridization technique.

Global public response to the COVID-19 (SARS-CoV-2) pandemic is highly focused on human health. However, conservationists have cautioned of unprecedented threats to the natural environment from a new type of non-biodegradable microplastic waste resulting from extensive use of disposable medical face masks (DMFMs). Thus, this waste must be recycled in an eco-friendly manner on an urgent basis. In this research, we developed a new environmentally friendly recycling technique using waste DMFMs in sustainable green concrete. More explicitly, a new fiber hybridization approach has been introduced in which two types of fibers namely DMFM fiber and basalt fiber (BF) were incorporated into fiber reinforced recycled aggregate concrete (FRAC). The volume fractions of DMFM fiber were 0%, 0.1%, and 0.2% and the volume fractions of BF were 0%, 0.25%, and 0.5%. In addition, two mineral admixtures (fly ash and ground granulated blast furnace slag) were also used. Test results indicated increase of approximately 12% in compressive strength, 26% in split tensile strength, and 60% in flexural strength of FRAC containing hybrid fibers and mineral admixtures. The density and ultra-sonic pulse velocity (UPV) of DMFM fiber- and BF-modified FRAC ranged from 2406-2433 kg/m3 and 4502-4541 m/s, respectively, which meets structural concrete requirements. The water absorption rate gradually increased with an increase in the volume fractions of fibers but remained within the allowable water absorption limit for construction materials. Lastly, the microstructure investigation indicated excellent concrete quality, improved interfacial transition zones (ITZs), and good compatibility of host concrete matrix with both DMFM fiber and BF that correlates well with the experimental results reported in this study.

Image Enhancement on Deep Learning Algorithm for COVID-19 Lung X-Ray Classification

The Novel Coronavirus Disease 2019 (COVID-19) is continuously a phenomenon that continues to study for its development throughout the world because of its international emergency status. The act of testing by clinical laboratory experts is a preventive effort to reduce the increase in cases. However, the number of experts is minimal compared to the cases. So, with deep learning, we need the best model for classifying lung disease variants that the world of health can utilize. This study applies several image enhancement techniques to the convolutional neural network algorithm ResNet50 architecture, which produces gamma correction as the best image improvement technique in this study with an accuracy of 0.986. These techniques also have a reasonably efficient time and a good loss value. © 2022 IEEE.

Shining light on ZnIn2S4 photocatalysts: Promotional effects of surface and heterostructure engineering toward artificial photosynthesis

The gradual depletion of fossil fuel reserves that contribute to ~85% of global energy production and release of toxic effluents urges the transformation toward renewable fuels. Thus, the sustainable utilization of sunlight for water splitting and CO2 reduction with heterogeneous photocatalysts has come to light. As a semiconductor photocatalyst, ZnIn2S4 has hit the limelight owing to its narrow bandgap and visible‐light‐responsive properties. However, the limitations of ZnIn2S4 include limited active sites, fast charge‐carrier recombination, and low photoconversion efficiency. Beginning from the fundamental photocatalytic mechanism, this review then provides in‐depth insights into several modification strategies of ZnIn2S4, extending from defect engineering, facet engineering, cocatalyst loading to junction engineering, enabling the synergistic construction of high‐performance ZnIn2S4‐based systems. Subsequently, the structure‐performance relation of ZnIn2S4‐based photocatalysts for hydrogen evolution (HER), overall water splitting (OWS), and CO2 reduction applications in the last 4 years will be discussed and concluded by the future perspectives of this frontier.

A computational fluid dynamics assessment of 3D printed ventilator splitters and restrictors for differential multi-patient ventilation.

BACKGROUND: The global pandemic of novel coronavirus (SARS-CoV-2) has led to global shortages of ventilators and accessories. One solution to this problem is to split ventilators between multiple patients, which poses the difficulty of treating two patients with dissimilar ventilation needs. A proposed solution to this problem is the use of 3D-printed flow splitters and restrictors. There is little data available on the reliability of such devices and how the use of different 3D printing methods might affect their performance. METHODS: We performed flow resistance measurements on 30 different 3D-printed restrictor designs produced using a range of fused deposition modelling and stereolithography printers and materials, from consumer grade printers using polylactic acid filament to professional printers using surgical resin. We compared their performance to novel computational fluid dynamics models driven by empirical ventilator flow rate data. This indicates the ideal performance of a part that matches the computer model. RESULTS: The 3D-printed restrictors varied considerably between printers and materials to a sufficient degree that would make them unsafe for clinical use without individual testing. This occurs because the interior surface of the restrictor is rough and has a reduced nominal average diameter when compared to the computer model. However, we have also shown that with careful calibration it is possible to tune the end-inspiratory (tidal) volume by titrating the inspiratory time on the ventilator. CONCLUSIONS: Computer simulations of differential multi patient ventilation indicate that the use of 3D-printed flow splitters is viable. However, in situ testing indicates that using 3D printers to produce flow restricting orifices is not recommended, as the flow resistance can deviate significantly from expected values depending on the type of printer used. TRIAL REGISTRATION: Not applicable.

Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail

Community retail is an important research issue in the field of fresh agriproduct e-commerce. This paper focuses on the problem of last-mile multi-temperature joint distribution (MTJD), which combines time coupling, order allocation, and vehicle scheduling. Firstly, according to the temperature of a refrigerated truck in multi-temperature zones, a split-order packing decision is proposed to integrate the different types of fresh agriproduct. Then, the order allocation strategy is incorporated into a comprehensive picking and distribution schedule, while taking into account the time-coupling of picking, distribution, and delivery time limit. To improve consumer satisfaction and reduce order fulfillment costs, an optimization model combining multi-item order allocation and vehicle scheduling is established, to determine the optimal order allocation scheme and distribution route. Finally, taking fresh agriproduct community retail in the Gulou District of Nanjing as an example, the effectiveness and feasibility of the model are illustrated. The numerical results of medium- to large-scale examples show that, compared with the variable neighborhood search algorithm (VNS) and genetic algorithm (GA), the mixed genetic algorithm (MGA) can save 29% of CPU time and 65% of iterations. This study considers the integrated optimization of multiple links, to provide scientific decision support for fresh agriproduct e-commerce enterprises.

COVID-19 and sheltering in place: The experiences of coercive control for college students returning home

After months of people sheltering in place, whether due to formal orders or to protect themselves from COVID-19, we have seen evidence of increases in Intimate Partner Violence (IPV). IPV, already a significant social justice issue worldwide, has been brought to the forefront during the pandemic, with many victims needing to be in confined spaces with their abusers. This chapter explores the experiences of sheltering in place for returning college students exposed to coercive control. It examines how coercive control, often intensified in post-separation abuse (PSA) and, where children are involved, parental alienation (PA), frequently manifests within families. Children have in the past been termed "secondary victims" of IPV, but this chapter will demonstrate how they should be considered primary victims of coercive control alongside their victimized parent. The particular challenges college students face during the COVID-19 pandemic when coercive control and PA are at issue will be delineated, and the many areas needing further research and exploration will be highlighted. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Design and Validation of Sample Splitting Protocol for Comparison of SARS-CoV-2 Quantification in Wastewater

Evaluations of analytical performance through interlaboratory comparisons and proficiency tests are underway globally for biomolecular-based methods [e.g., reverse-transcription quantitative polymerase chain reaction (RT-qPCR)] used in the surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater. These evaluations often rely on sharing a common reference wastewater sample that is split among participating laboratories. A known quantity of recovery surrogates can be introduced to the wastewater matrix by the coordinating laboratory as an exogenous control in a spike-and-recovery approach;however, split-sample comparisons are increasingly performed to evaluate in situ quantities of SARS-CoV-2 genetic signal native to the sample due to the lack of a universally accepted recovery surrogate of SARS-CoV-2. A reproducible procedure that minimizes the variability of SARS-CoV-2 genetic signal among split wastewater aliquots is therefore necessary to facilitate the method comparisons, especially when a large number of aliquots are required. Emerging literature has suggested that SARS-CoV-2 genetic signal in wastewater is linked to the solids fraction. Accordingly, a protocol that allows for equal distribution of solids content evenly among wastewater aliquots was also likely to facilitate even distribution of the SARS-CoV-2 genetic signal. Based on this premise, we reviewed existing sample splitting apparatus and approaches used for solids-based parameters in environmental samples. A portable batch reactor was designed, comprised of readily accessible materials and equipment. This design was validated through splitting of real wastewater samples collected from a municipal wastewater treatment facility serving a population with reported cases of COVID-19. This work applies well-established solid-liquid mixing theory and concepts that are likely unfamiliar to molecular microbiologists and laboratory analysts, providing (1) a prototype adaptable for a range of sample quantities, aliquot sizes, microbial targets, and water matrices;and (2) a pragmatic demonstration of critical considerations for design and validation of a reproducible and effective sample splitting protocol.

Impact of the COVID-19 pandemic on patients receiving intravitreal injections

We analyzed the economic benefits versus safety risks of sharing anti-vascular endothelial growth factor (VEGF) vials during the coronavirus disease (COVID-19) pandemic. This single-center retrospective study analyzed the data of patients with neovascular age-related macular degeneration (nAMD), proliferative diabetic retinopathy (PDR) and retinal vein occlusion (RVO) who received anti-VEGF between January 2016 and July 2021 at Renmin Hospital, Wuhan University, China. Costs were compared of the two protocols of intravitreal injections (IVIs) of ranibizumab, aflibercept and conbercept after (i) splitting the vial content for use in two patients and after (ii) disposal of the remaining vial content after use in a single patient, with the COVID-19 outbreak considered as the demarcation point. The incidence rates of post-injection endophthalmitis (PIE) preand post-outbreak were analyzed. The mean cost of a single IVI increased by 33.3%, from 3917.67±71.69 to 5222.67±84.98 Chinese Yuan during the pandemic. The incidences of IVI-related culture-positive PIE were 0.0134% (3 in 22448) and 0.0223% (1 in 4479), respectively, before and after the pandemic (P=0.6532). We conclude that vial sharing of IVIs in a large clinical institution is not associated with increased PIE risk and can significantly reduce the cost of therapy. © 2022

Survey Participation in the Time of Corona: An Empirical Analysis of the Effect of the COVID-19 Pandemic on Survey Participation in a Swiss Panel Study

The singular effect of a public shutdown in spring 2020—as a result of non-pharmaceutical official orders and arrangements in the course of the COVID-19 pandemic—on survey participation is investigated. The analysis is focused on panellists born around 1997 and living in German-speaking cantons of Switzerland. Utilising the techniques and procedures of event history analysis, the paradata of the fieldwork period are analysed in a dynamic micro–macro design. Several competing time-varying effects on the panellists’ survey participation and changes in the pandemic progress are controlled for, in addition to time-constant covariates, such as their education and social origin. Indeed, it becomes obvious that the public shutdown during the first wave of the pandemic improved the target persons’ propensity for survey participation. © 2022Author(s).

Strukturzerfall und der laute Ruf nach Halt

The lecture focuses on the observation, that the current societal turmoil is accompanied by uncertainty and splitting processes. Wars, climate change, COVID-19, political threats and the disintegration of societal structures distress collectively and increase individual powerlessness and feelings of minority. The reactive compensatory tendencies to regain power, order and ground are a natural countermovement, however they themselves imply the danger of a loss of capacity for a dialogue due to counter-splitting and disruptive radicality on the other hand. (English) [ FROM AUTHOR] Der Tagungsbeitrag fokussiert auf die Beobachtung, dass der gegenwärtig stattfindende gesellschaftliche Umbruch mit Verunsicherung und Spaltung einhergeht. Kriege, Klimawandel, politische Bedrohungen und der Zerfall bestehender gesellschaftlicher Strukturen beängstigen kollektiv und steigern individuelle Gefühle von Ohnmacht und Minderwertigkeit. Die reaktiven Kompensationsstrebungen zur Wiederherstellung von Macht, Ordnung und Halt sind eine natürliche Gegenbewegung, doch droht ihnen immer auch der Verlust der Dialogfähigkeit durch Gegenspaltung und disruptive Radikalität. (German) [ FROM AUTHOR] Copyright of Zeitschrift für Individualpsychologie is the property of Vandenhoeck & Ruprecht GmbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Face Mask Detection using MobileNetV2

To stem the COVID19 pandemic, great attention is needed to mitigate public health and the global economy which are negatively impacting. To overcome this, a technique is required to urge people put on the face mask. To contribute to the health of communities, this article aims to design a very precise and real-time analysis that can efficiently detect non-mask faces in public and thus, enforcing to wear mask. According to the World Health organization, the most effective way to fight the transmission of the corona virus is to wear medical masks. The detection of face mask in is done with the machine learning by using the series of stages involved through classification of images: MobileNetV2. The steps and stages used for developing the model square measure grouping the information, and pre-processing the data to remove noisy data, splitting the data, testing the model for the accuracy, and implementation of the model. The engineered model will sight those that square measure sporting a mask associated not sporting it at an accuracy of 95.85 percent. © 2022 IEEE.

When structures fall apart: The clarion call for support

The lecture focuses on the observation, that the current societal turmoil is accompanied by uncertainty and splitting processes. Wars, climate change, COVID-19, political threats and the disintegration of societal structures distress collectively and increase individual powerlessness and feelings of minority. The reactive compensatory tendencies to regain power, order and ground are a natural countermovement, however they themselves imply the danger of a loss of capacity for a dialogue due to counter-splitting and disruptive radicality on the other hand.

Impact of Stratum Composition Changes on the Accuracy of the Estimates in a Sample Survey

The study is devoted to measuring the impact of the element changes on the bias and variance of the estimator of the total in a sample business survey. Stratified simple random sampling is usually used in business surveys. Enterprises may join, split or change the stratum between sample selection and data collection. Assuming a model for enterprises joining and a model for the enterprises changing the stratum with some probability, expressions for the adjusted estimators of the total and the adjusted estimators of their variances are proposed. The influence of the enterprise changes on the variances of the estimators of the total is measured by the relative differences, i.e., by comparing them with the estimators, if there were no changes. The analytic results are illustrated with a simulation study using modified enterprise data. The simulation results demonstrate a large impact of the enterprise changes on the accuracy of the estimates, even in the case of the low probability of changes. The simulation results justify the need for adjustment of the enterprise changes between the sample selection and data collection, in order to improve the accuracy of results and the adjustment method available.

Nanoscale ZnO/α‐Fe2O3 Heterostructures: Toward Efficient and Low‐Cost Photoanodes for Water Splitting

Composite metal oxide semiconductors are promising candidates for photoelectrochemical water splitting (PEC WS) toward environmentally friendly hydrogen production. Among them, ZnO and α‐Fe2O3 hold great potential thanks to a series of benefits, including fast charge transport in single‐crystalline structures, large surface area and tunable shapes (ZnO), and energy bandgap falling in the visible spectral range (α‐Fe2O3). However, both materials present significant drawbacks, which hinder their successful application in high‐efficiency PEC WS: the wide bandgap of ZnO limits its absorption in the UV range, while the low charge carrier mobility results in heavy recombination losses in α‐Fe2O3 during charge collection. The synthesis of ZnO/hematite composites has recently proven to be an effective approach to improve the overall WS performances. In this review, the recent developments on the application of different morphologies (0D, 1D, 2D, and 3D structures) for PEC WS are illustrated, analyzing the role of the shape and morphology in boosting the functional properties, both in single systems and in composite nanostructures. Complex networks show higher photocatalytic efficiency than the single building blocks and, consequently, composite materials exhibit higher performances. Possible paths for the development of an effective lab‐to‐fab transition based on application of ZnO/α‐Fe2O3 composite structures are also suggested.

Data Embedding in SHVC Video Using Threshold-Controlled Block Splitting

With the increasing number of video applications, it is essential to resolve issues such as ineffective search of video content, tampered/forged video content, packet loss, to name a few. Data embedding is typically utilized as one of the solutions to address the aforementioned issues. One of the important requirements of data embedding is to maximize embedding capacity with minimal bit rate overhead while ensuring imperceptibility of the inserted data. However, embedding capacity varies depending on the video content and increasing the embedding capacity usually leads to video quality degradation. In this work, a threshold-controlled block splitting technique is proposed for embedding data into SHVC video. Specifically, the embedding capacity can be increased by coding the host video by using more small blocks, which can be achieved by tuning a threshold-controlled parameter in the rate distortion optimization process. Subsequently, the predictive syntax elements in both intra and inter-coded blocks are jointly utilized to embed data, which ensures that data can be embedded regardless of the prediction mode used in coding a block. Results suggest that the proposed method can achieve a trade-off between the increase in embedding capacity and bit rate overhead while maintaining video quality. In the best case scenario, the sequence PartyScene can embed 516.9 kbps with an average bit rate overhead of +7.0% for the Low Delay P configuration, while the same video can embed 1578.6 kbps with an average bit rate overhead of +2.9% for the All Intra configuration.

LCOS-SLM Based Intelligent Hybrid Algorithm for Beam Splitting

The iterative Fourier transform algorithm (IFTA) is widely used in various optical communication applications based on liquid crystal on silicon spatial light modulators. However, the traditional iterative method has many disadvantages, such as a poor effect, an inability to select an optimization direction, and the failure to consider zero padding or phase quantization. Moreover, after years of development, the emergence of various variant algorithms also makes it difficult for researchers to choose one. In this paper, a new intelligent hybrid algorithm that combines the IFTA and differential evolution algorithm is proposed in a novel way. The reliability of the proposed algorithm is verified by beam splitting, and the IFTA and symmetrical IFTA algorithms, for comparison, are introduced. The hybrid algorithm improves the defects above while considering the zero padding and phase quantization of a computer-generated hologram, which optimizes the directional optimization in the diffraction efficiency and the fidelity of the output beam and improves the results of these two algorithms. As a result, the engineers’ trouble in the selection of an algorithm has also been reduced.

Defense Mechanisms and Borderline Personality Organization Among COVID-19 Believers and Non-believers During Complete Lock-Down.

The aim of the current study was to investigate whether a specific social perception of the pandemic-believing or not in COVID-19-predicts borderline personality organizations and whether this relationship is mediated by more primitive maladaptive mechanisms-splitting, denial, and dissociation. The online study included 720 organization aged 25-45. Participants were diverse in terms of place of residence, being in a relationship, and education level. Approximately 30% of the general population reported not believing in the COVID-19 pandemic. Non-believers scored slightly higher on borderline symptoms and used more maladaptive defense mechanisms than believers. Individuals who deny COVID-19 are more likely to show characteristics of borderline personality organization. Splitting is an important mechanism in this relationship.

Use of capnography to verify emergency ventilator sharing in the COVID-19 era.

Exacerbation of COVID-19 pandemic may lead to acute shortage of ventilators, which may require shared use of ventilator as a lifesaving concept. Two model lungs were ventilated with one ventilator to i) test the adequacy of individual tidal volumes via capnography, ii) assess cross-breathing between lungs, and iii) offer a simulation-based algorithm for ensuring equal tidal volumes. Ventilation asymmetry was induced by placing rubber band around one model lung, and the uneven distribution of tidal volumes (VT) was counterbalanced by elevating airflow resistance (HR) contralaterally. VT, end-tidal CO2 concentration (ETCO2), and peak inspiratory pressure (Ppi) were measured. Unilateral LC reduced VT and elevated ETCO2 on the affected side. Under HR, VT and ETCO2 were re-equilibrated. In conclusion, capnography serves as simple, bedside method for controlling the adequacy of split ventilation in each patient. No collateral gas flow was observed between the two lungs with different time constants. Ventilator sharing may play a role in emergency situations.