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OBJECTIVES: Universal mask wearing due to COVID-19 has introduced barriers to clear communication. In hearing impaired individuals this can impact informed surgical consent. For cochlear implant candidates, who do not rely on sign language, real-time transcription with a stenographer (CART) is the gold-standard in assistive technologies. If CART is not available, speech to text (STT) applications have been advertised as solutions, but their transcription accuracy with or without an N95 mask is not well-established. Herein, we sought to investigate the transcription accuracy of three STT solutions for iPhone and compare their performance to the CART service at our institution. METHODS: Three native English speakers and three non-native English speakers read two passages (a cochlear implant consent and the non-medical 'Rainbow passage') with and without an N95 mask. Error rates from the comparison of the transcript (from either the STT app or CART) with the original passage were calculated. RESULTS: The CART service had the lowest error rate of all testing conditions (4.79-7.14%). Ava 24/7 (15.0 ± 9.49%) and the iPhone dictation (15.6 ± 6.65%) had significantly lower average error rates than the Live Transcribe (37.7 ± 20.3%) (P < 0.0001) application. Neither the presence of an N95 nor the type of passage had a statistically significant impact on the error rate. CONCLUSION: CART should be used to augment communication with patients who are hard of hearing. If CART is not available, a STT application such as Ava 24/7 or the native iPhone dictation application may be considered, even in the context of medical terminology.
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Human-beings are suffering from the rapid spread of COVID-19 throughout the world. In order to quickly identify, quarantine and cure the infected people, and to stop further infections, it is crucial to expose those origins who have been infected but are asymptomatic. However, this task is not easy, especially when the rigid security and privacy constraints on health records are taken into consideration. In this paper, we develop a new method to solve this problem. In the outbreak of a disease like COVID-19, the proposed method can find hidden infected people (or communities) through volunteered share of health data by some mobile users. Such volunteers only reveal whether they are healthy or infected e.g. through they mobile apps. This approach minimises health data disclosure and preserves privacy for the others. There are three steps in the proposed method. First, we borrow the idea from traditional epidemiology and design a novel algorithm to estimate the number of infection origins based on a Susceptible-Infected model. Second, we introduce the concept of 'heavy centre' to locate those origins. The probability of each node being infected will then be derived by building a spreading model based on the origins. To evaluate our method, we conduct a series of experiments on various networks with different structures. We examine the performance in estimating the number of origins as well as their origins. The results show that the proposed method yields higher accuracies than the existing methods, even when the fraction of volunteers is small. © 2001-2012 IEEE.
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A growing aspect of e-government is healthcare-related. Although preventative e-health services provided by governments like proximity tracing applications (PTAs) can bring important benefits, their adoption is lagging behind expectations. Researchers and policymakers need a better understanding of the factors that influence their adoption. The paper draws from the Unified Theory of Acceptance and Use of Technology (UTAUT) model and extends it by including privacy concerns as an explanatory factor regarding the intention to use PTAs. The study empirically evaluates the impact of privacy concerns together with two of its antecedents – trust in government and trust in technology – on the intention to use a PTA. Data from 762 adult respondents from Slovenia and Germany were collected and analysed using partial least squares structural equation modelling (PLS-SEM). The main findings are: (1) even in the unique context of a PTA the universal predictors of UTAUT have a significant impact;(2) privacy concerns have a direct impact on intention to use;and (3) trust in government and trust in technology both have a significant impact on privacy concerns. The theoretical implications are important for technology adoption research on e-health services provided by the government generally and PTAs in particular. © 2022 Elsevier Inc.
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The annual ACSM's Health & Fitness Journal® worldwide survey to determine industry trends by health and fitness professionals is now in its 17th consecutive year. The COVID-19 pandemic certainly made an impact on the 2021 survey and continued for 2022, but for 2023, some current trends are emerging whereas others are weakening because of the world's recovery from the isolation caused by COVID-19. The #1 trend for 2023, as it was for 2022, is wearable technology. Home exercise gyms was #2 for 2022 but has dropped to #13 for 2023. Fitness programs for older adults will make a comeback in 2023, breaking the top 10 at #4. Functional fitness training, a popular form of exercise for the older adult, is the #5 trend for 2023. Apply It!: From this article, the reader should understand the following concepts: • Explain the differences between a fitness fad and a fitness trend • Use the worldwide fitness trends in the commercial, corporate, clinical (including medical fitness), and community health and fitness industry to further promote physical activity • Study expert opinions about identified fitness trends for 2023
ABSTRACT
Music listening choices are considered to be a factor capable of measuring people's emotions. Thanks to the explosion of streaming music applications in recent years, it is possible to describe listening trends of the global population based on emotional features. In this paper we have analysed the most popular songs from 52 countries on Spotify through their features of danceability, positivity and intensity. This analysis allows exploring how these song features reflect mood trends along with other contextual factors that may affect the population's listening behaviour, such as the weather or the influence of the COVID-19 pandemic. Finally, we have proposed a multivariate time series model to predict the preferred type of music in those countries based on their previous music listening patterns and the contextual factors. The results show some relevant behavioural changes in these patterns due to the effect of the pandemic. Furthermore, the resulting prediction model enables forecasting the type of music listened to in three different groups of countries in the next 4 months with an error around 1%. These results may help to better understand streaming music consumption in businesses related to the music and marketing industry. © 2022 Elsevier B.V.
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In recent years, the significance of biosensors has increased rapidly due to the growing demand for rapid detection of various biomarkers with high selectivity and sensitivity. Among different biosensors, Graphene Field Effect Transistor (Gr-FET) based biosensors has emerged as a promising device and exhibited wide range of application prospects. Gr-FET biosensors are ideal for ultra-sensitive immunological diagnosis applications as it can sense surrounding changes on their surface with low noise. Recently Gr-FET based biosensors have gained profound research interest among scientific community because of its ability in detection of SARS-CoV-2 (corona virus-2). This review article highlights the sensing performance and characteristics of different Gr-FET biosensors like DNA sensor, RNA sensor, glucose sensor, lactose sensor, protein sensor, pH sensor, various bacteria and virus detecting sensors etc.This article also critically reviews the recent progress in Gr-FET based SARS- CoV-2 covid-19 virus detection bio-sensors. © 2022 Elsevier Ltd
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Nowadays, the entire world is struggling to adapt and survive the global pandemic. Moreover, most countries had a hard time keeping up with the new mutations of COVID-19. Therefore, taking preventive measures to control the spreading of the virus, including lockdowns, curfews, social distancing, masks, vaccines, is not enough to stop the virus. However, using the new technologies to adapt the prevention measures and enhance the existing ones will be more efficient. Most countries have already developed their non-pharmaceutical interventions measures (NPIs), mainly contacts tracing solutions at the pandemic beginning. Using those mobile applications, the authorities were able to reduce the spreading of the virus. Nevertheless, the virus is evolving, mutating, and becoming more and more dangerous to survive. Therefore, these mobile applications have become less effective in facing the constant changes of the pandemic situation. To that end, the need for enhancing and evolving contact tracing became more urgent. The goal here is to control the spread of the new variants and keep up with the rapid changes happening around the world. In this paper, we will present a detailed view of the new solution built to take contact tracing to a new level, empowered by the Bluetooth Low Energy technology for communication, advanced encryption method for security and data privacy, as well as secured storage and data management to have a system capable of slowing the COVID-19 variants from spreading and save lives. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The COVID-19 pandemic is also an infodemic, which has brought scientists closer to the popular media, highlighting the need for training in public communication of science and technology. A virtual magazine environment based on this scenario was simulated during a science communication course attended by first-year undergraduate chemistry students, who assumed the role of science journalists. The instructor, in the role of editor, organized a special issue on chemistry and COVID-19 and structured the activities into science communication classes, agenda building, interviews with nonexperts, writing popular science texts, peer reviews, and online publishing. Fifty-eight popular science texts were produced on different topics of chemistry related to the pandemic. The activity contributed to improving communication, information literacy, and media and technology learning, which are among the 21st century skills for science education. © 2022 American Chemical Society and Division of Chemical Education, Inc.
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Each zone could be very well investigated and ability packages, social and financial affects, and limitations to mass rehabilitation are discussed in greater detail. It describes in element the demanding situations and opportunities for IoE framework solutions inside the post-COVID-19 generation. The COVID-19 epidemic has furnished a far-wanted check of IoE-stimulated frameworks and answers. IoE solutions together with a ways flung fitness monitoring and phone tracking have supplied the guide of authorities to successfully manage to unfold the corona contamination. The principle contribution of this compare paper is the in-intensity analysis and segmentation of vicinity-unique IoE technology, which have the potential to be remarkable applications inside the new present day. So far, privacy worries and the protection of IoE applications are thoroughly analyzed with rising standards, and the code for multitasking practices is likewise being mentioned. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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In this study, we explore the use of echelon analysis and its software named EcheScan for spatial lattice data. EcheScan is developed as a web application via an internet browser in R language and Shiny server for echelon analysis. The technique of echelon is proposed to analyze the topological structure for spatial lattice data. The echelon tree provides a dendrogram representation. Regional features, such as hierarchical spatial data structure and hotspots clusters, are shown in an echelon dendrogram. In addition, we introduce the conception of echelon with the values and neighbors for lattice data. We also explain the use of EcheScan for one- and two-dimensional regular lattice data. Furthermore, coronavirus disease 2019 death data corresponding to 50 US states are illustrated using EcheScan as an example of geospatial lattice data. This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data Analysis Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification Data: Types and Structure > Image and Spatial Data. © 2022 The Authors. WIREs Computational Statistics published by Wiley Periodicals LLC.
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Global challenges such as the COVID-19 pandemic highlight the need for visionary innovations in chemical education. We recently deigned a new learning environment called "ZuKon 2030”, which addresses sustainability from a chemical perspective while simultaneously introducing students to the sustainable development goals (SDGs) of the United Nations Agenda 2030. It integrates modern and innovative learning strategies by creating a format that can be used in either face-to-face or distance learning settings. In addition to the modules designed as exit games embedded in the overarching narrative of a fictional science conference, the Future Conference, paper materials enriched with Augmented Reality are used in order to allow students to complete the modules independently. In this paper, we present the basic concept of the learning environment and concretely show the implementation of the concept. We use the module "The Mystery of Coral Death” as an example, and we report our results and experiences with the entire learning environment. In the preliminary study, the students rated the hybrid learning environment mostly positively in the areas of thematic content, realization of the learning environment, digital content, and game elements. © 2022 The Authors. Published by American Chemical Society and Division of Chemical Education, Inc.
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The article presents the discussion on preparing a renewed health plan and absolve to change poor habits. Topics include pandemic accelerated many trends in the health and fitness industry and taught many lessons;and walking, running, hiking, biking, swimming, racquet sports, and seasonal sports being readily accessible.
ABSTRACT
Semiconducting single-walled carbon nanotubes (SWCNTs) with tailored corona phases (CPs), or surface-adsorbed molecules, have emerged as a promising interface for sensing applications. The adsorption of an analyte can be specifically transduced as a modulation of their band-gap near-infrared (nIR) photoluminescence (PL). One such CP ideal for this purpose is single-stranded DNA (ssDNA), where subsequent sequence-dependent hybridization can result in PL emission wavelength shifts. Due to ssDNA adsorption to the SWCNT surface, the resultant noncanonical hybridization and its effect on SWCNT photophysical properties are not well understood. In this work, we study 20- and 21-mer DNA and RNA hybridization on the complementary ssDNA-SWCNT CP in the context of nucleic acid sensing for SARS-CoV-2 sequences as model analytes. We found that the van't Hoff transition enthalpy of hybridization on SWCNT CP was −11.9 kJ mol-1, much lower than that of hybridization in solution (−707 kJ mol-1). We used SWCNT solvatochromism to calculate the solvent-exposed surface area to indicate successful hybridization. We found that having a 30-mer anchor region in addition to the complementary region significantly improved PL response sensitivity and selectivity, with a (GT)15 anchor preferred for RNA targets. Coincubation of ssDNA-SWCNTs with an analyte at 37 °C resulted in faster hybridization kinetics without sacrificing specificity. Other methods aimed to improve CP rearrangement kinetics such as bath sonication and surfactant additions were ineffective. We also determined that the target sequence choice is important as secondary structure formation in the target is negatively correlated with hybridization. Best-performing CPs showed detection limits of 11 and 13 nM for DNA and RNA targets, respectively. Finally, we simulated sensing conditions using the saliva environment, showing sensor compatibility in biofluids. In total, this work elucidates key design features and processing to enable sequence-specific hybridization on ssDNA-SWCNT CPs. © 2022 American Chemical Society.
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The digitalization of human work has been an ever-evolving process. Student's and employee's attendance systems are automated by using fingerprint biometrics. Specifically covid situation has created the need for touchless attendance system. Many institutions have already implemented a face detection-based attendance system. However, the major problem in designing face-recognising biometric applications is the scalability and accuracy in time to differentiate between multiple faces from a single clip/image. This paper used the OpenFace model for face recognition and developed a multi-face recognition model. The Torch and Python deployment module of deep neural network-based face recognition was used, and it was predicated accurately in time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Internet of Things (IoT) has gained popularity since last recent years and applied in wide variety of applications including education, homes, offices and healthcare industry. IoT field changing the healthcare system by considering factors like economy, technology and social by which patients can be diagnose, treat or monitored in effective way. The world is facing current global challenge which can severe the respiratory syndrome Covid-19 which leads to serious health issues and even huge mortality. There are more than 31 cr. of people around the world suffering from Covid-19 with more than 5 cr. of mortality, when this paper was written. Since the pandemic started, several researchers put their efforts to use technologies to save world from effects of this virus. IoT plays a major role during this pandemic. IoT-enabled devices or applications helps to reduce the chances of virus spread of Covid-19 by early diagnose, monitoring of patients during active or recovery phase. This paper discusses the role of IoT during Covid-19 and how IoT implementation in healthcare helps in the phases of diagnosis, isolation and recovery. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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COVID-19 is one of the greatest pandemics that threaten individuals, especially the elders. It was first reported in Wuhan, China in 2019. It was discovered recently that COVID-19 disease can be detected using three main protocols. The first protocol is based on Polymerase Chain reaction (PCR), while the second protocol is based on lung chest (ultrasound, X-ray, and CT-Scan), and the final protocol is based on the ECG image reports. This review aims to present a survey on the methodologies and algorithms applied for the detection of COVID disease using electrocardiogram (ECG). In this study, various papers were presented for determining how the COVID can be diagnosed using ECG image reports relying on symptoms and changes in the ECG peaks and intervals. In addition to this, other studies are presented on techniques applied to the ECG reports for the detection of COVID. Also, the main limitations and future works are illustrated. It can be concluded that COVID can be detected with high accuracy using ECG reports and it is even more efficient than other protocols. Finally, based on the performance of the studies it can be shown that the ECG image report is close to an acceptable level in the detection of COVID disease. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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This research examined the determinants of e-satisfaction, continuance intention, and e-loyalty regarding the use of mobile payment applications (MPAs). It developed and validated the electronic technology continuance model (e-TCM) integrating a psychological factor (perceived threats), e-satisfaction, circumstantial factor (perceived anxiety), and the dimensions of quality. Using a questionnaire, data was collected from 455 respondents and analyzed using structural equation modeling. The influences of information quality, service quality, system quality, perceived usefulness, and confirmation on both e-satisfaction and continuance intention are found positive. However, perceived threats and perceived anxiety do not influence e-satisfaction but influence continuance intention. Moreover, e-satisfaction positively impacts continuance intention and e-loyalty;and continuance intention positively impacts e-loyalty. This research evidences the roles of perceived threat, e-satisfaction, perceived anxiety, and the dimensions of quality on customers' e-satisfaction, continuance intention and e-loyalty, using the integrated framework comprising the health belief model, expectation–confirmation model, and information systems success model. The findings of this research can guide MPA services providers, online businesses, industry analysts, suburban consumers, and respective government authorities when MPA usage is concerned during any unprecedented crisis such as the COVID-19 pandemic. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.
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COVID-19, which was first spread in China in 2019 and consequently spread worldwide, is caused by the SARS-CoV-2. Today, various carbon-based nanomaterials such as graphene, graphene oxide, carbon dots, and carbon nanotubes have been explored for the specific detection and targeted inhibition/inactivation of SARS-CoV-2 due to their great surface chemical structures, easy to-functionalization, biocompatibility, and low toxicity. According to exclusive inherent properties, carbon-based nanomaterials are promising candidates for targeted antiviral drug delivery and the inhibitory effects against pathogenic viruses based on photothermal effects or reactive oxygen species (ROS) formation. These high-stability nanomaterials exhibited unique physicochemical properties, providing efficient nanoplatforms for optical and electrochemical sensing and diagnostic applications with high sensitivity and selectivity. Up to now, these materials have been used for the fabrication of diagnostic kits, different types of personal protective equipment (PPE) such as anti-viral masks, vaccines, self-cleaning surfaces, and other subjects. This review article explores the most recent developments in carbon-based nanomaterials' diagnostic and therapeutic potential towards SARS-CoV-2 detection and inhibition, different mechanisms, challenges and benefits of the carbon-based nanomaterials.