Multiple Fano Resonances in Plasmonic Waveguide Based Cavity and Detection of Pathogenic Virus

A technique is implemented for the generation of multiple Fano-resonances in a plasmonic waveguide based rectangular cavity. A rectangular cavity provides four Fano peaks which can further be increased to nine by inserting the metallic bars in it. The trapped surface plasmon polaritons by metallic bars cause the generation of multiple Fano peaks over the wavelength range of 450 nm - 1300 nm. The obtained response is validated through Fano profile and Fano shape parameter is calculated for each resonance peak. The performance of the proposed device is numerically studied as refractive index sensor and method for analyzing the detection of pathogenic virus like SARS-Cov-2 is reported. Out of nine Fano peaks, the best values of sensing performance indices are obtained with full-width, half-maxima of 1.7 nm, quality factor of 405, sensitivity of 1145.71 nm/RIU and figure of merit of 393.25 RIU-1. IEEE

Charting well-being over adulthood into pandemic times: a longitudinal perspective

The purpose of this study is to investigate how well-being changes over the adult life course from early adulthood in 1998 through to the COVID-19 pandemic in 2021. We identify diverse well-being trajectories over time in a cohort of British Columbians and explore the extent to which changes in well-being associated with the pandemic varied for individuals in these different trajectory groups. Specifically, we ask: what was the effect of the pandemic on the well-being of individuals with different prior well-being trajectories over adulthood and how were these effects related to personal, educational and employment factors? To address this question, we model well-being trajectories over a large span of adulthood from the age of 28 to 51 years old. We find a diversity of distinct patterns in well-being changes over adulthood. The majority experience high well-being over time, while almost one in five experiences either chronically low or drastically decreased well-being in mid-adulthood, which coincides with the pandemic. Notably, those who have completed post-secondary education are less likely to report low well-being trajectories. Those with the lowest well-being over time also report the largest negative effects of the pandemic, which illustrates the compounding effects of the pandemic on existing inequalities.

The Construction of Intelligent Homework System in Schools under the Concept of Wisdom Education

The mega-scale online education conducted nationwide during the COVID-19 epidemic has enabled online learning to move from individualized participation to full participation, practicing and advancing the development of wisdom education to a large extent. In the post-epidemic era, a new educational order that integrates online and offline learning is gradually taking shape, and online learning has become a new norm from emergency. The popularization and promotion of online education has been the general trend. The "double reduction"policy has led to a trust dilemma, a communication dilemma, a cooperation dilemma and an organizational dilemma in the practice of home-school-society collaborative parenting, and an unprecedented challenge for school education and teachers teaching. This study proposes an intelligent operating system based on big data and adaptive learning traction model, rooted in rich pedagogical theories, to solve the above-mentioned challenges in online education by virtue of "wisdom". © 2023 IEEE.

Exploring COVID-19 transmission patterns and key factors during epidemics caused by three major strains in Asia.

The COVID-19 epidemic has lasted for more than two years since the outbreak in late 2019. An urgent and challenging question is how to systematically evaluate epidemic developments in different countries, during different periods, and to determine which measures that could be implemented are key for successful epidemic prevention. In this study, SBD distance-based K-shape clustering and hierarchical clustering methods were used to analyse epidemics in Asian countries. For the hierarchical clustering, epidemic time series were divided into three periods (epidemics induced by the Original/Alpha, Delta and Omicron variants separately). Standard deviations, the Hurst index, mortality rates, peak value of confirmed cases per capita, average growth rates, and the control efficiency of each period were used to characterize the epidemics. In addition, the total numbers of cases in the different countries were analysed by correlation and regression in relation to 15 variables that could have impacts on COVID-19. Finally, some suggestions on prevention and control measures for each category of country are given. We found that the total numbers of cases per million of a population, total deaths per million and mortality rates were highly correlated with the proportion of people aged over 65 years, the prevalence of multiple diseases, and the national GDP. We also found significant associations between case numbers and vaccination rates, health expenditures, and stringency of control measures. Vaccinations have played a positive role in COVID-19, with a gradual decline in mortality rates in later periods, and are still playing protective roles against the Delta and Omicron strains. The stringency of control measures taken by a government is not an indicator of the appropriateness of a country's response to the outbreak, and a higher index does not necessarily mean more effective measures; a combination of factors such as national vaccination rates, the country's economic foundation and the availability of medical equipment is also needed. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

A review of metal nanoparticle-based surface-enhanced Raman scattering substrates for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection Special Collection: Distinguished Australian Researchers

Monitoring an infectious disease early using highly sensitive and non-invasive techniques is critical for human health. Interestingly, the development of surface-enhanced Raman scattering (SERS) for biological detection ideally fits these medical requirements and is rapidly growing as a powerful diagnostic tool. SERS can enhance the Raman signal of the target molecule by more than 10(6) after the adsorption of the molecule on the plasmonic nanostructured surface. This review provides an overview of the use of gold and silver nanoparticles in SERS substrate designs, followed by the development of these SERS substrates in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection.

Learning torus PCA-based classification for multiscale RNA correction with application to SARS-CoV-2

Three-dimensional RNA structures frequently contain atomic clashes. Usually, corrections approximate the biophysical chemistry, which is computationally intensive and often does not correct all clashes. We propose fast, data-driven reconstructions from clash-free benchmark data with two-scale shape analysis: microscopic (suites) dihedral backbone angles, mesoscopic sugar ring centre landmarks. Our analysis relates concentrated mesoscopic scale neighbourhoods to microscopic scale clusters, correcting within-suite-backbone-to-backbone clashes exploiting angular shape and size-and-shape Frechet means. Validation shows that learned classes highly correspond with literature clusters and reconstructions are well within physical resolution. We illustrate the power of our method using cutting-edge SARS-CoV-2 RNA.

Psychoanalytic exploration of society: Possibilities and limits of psychoanalytical social research

The psychoanalytic exploration of social phenomena goes back as far as Freud's writings on cultural theory. In this article we aim at delineating how critical scholars following Freud sought to make psychoanalysis fruitful for social analyses and, based on this, develop contours of psychoanalytically oriented social research. This school of thought does not simply "apply" psychoanalytic knowledge but traces the social production of psychological conflicts. Moreover, we introduce Alfred Lorenzer's methodology and method of in-depth hermeneutic cultural analysis and from this theoretical perspective provide insights into recent research on the coronavirus disease 2019 (COVID-19) protests. (PsycInfo Database Record (c) 2023 APA, all rights reserved) (German) Die psychoanalytische Erkundung gesellschaftlicher Phanomene beginnt bereits mit Freuds kulturtheoretischen Schriften. In diesem Artikel zeichnen wir nach, wie an Freud anschliesende kritische Denker:innen die Psychoanalyse fur Gesellschaftsanalysen produktiv zu machen suchten, und entwickeln davon ausgehend Konturen einer psychoanalytisch orientierten Sozialforschung, die nicht nur psychoanalytische Erkenntnisse anwendet", sondern der gesellschaftlichen Hervorbringung innerpsychischer Konflikte nachspurt. Wir gehen dann auf Alfred Lorenzers Methodologie und Methode der Tiefenhermeneutischen Kulturanalyse ein und geben aus dieser theoretischen Perspektive einen Einblick in aktuelle Forschungen zu den Coronaprotesten. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Acting Egoistically in a Crisis: How Emotions Shape Data Donations

The spread of COVID-19 has affected all of us, be it financially, socially, or even physically. It has caused uncertainty and anxiety, which has put people into a "hot" mental state. Referred to as an empathy gap, people are assumed to make emotion-driven decisions in "hot" states compared to "cold" states, which contrasts with the normative assumption of rational decision-making in privacy research. Based on an experimental survey study among 445 participants, we investigate whether people's mental state interacts with individuals' information disclosure decision-making. We measure our research model in the context of actual health data donation, which constitutes a critical surveillance factor in the COVID-19 crisis. Thereby, we contribute to research by (1) investigating data donation behavior amid a crisis and (2) helping to explain further nuances of privacy decision-making and the importance of trust as a context-dependent driver of data donation. © 2022 IEEE Computer Society. All rights reserved.

Relationship between Vitamin D and Immunity in Older People with COVID-19.

Vitamin D is a group of lipophilic hormones with pleiotropic actions. It has been traditionally related to bone metabolism, although several studies in the last decade have suggested its role in sarcopenia, cardiovascular and neurological diseases, insulin-resistance and diabetes, malignancies, and autoimmune diseases and infections. In the pandemic era, by considering the response of the different branches of the immune system to SARS-CoV-2 infection, our aims are both to analyse, among the pleiotropic effects of vitamin D, how its strong multimodal modulatory effect on the immune system is able to affect the pathophysiology of COVID-19 disease and to emphasise a possible relationship between the well-known circannual fluctuations in blood levels of this hormone and the epidemiological trend of this infection, particularly in the elderly population. The biologically active form of vitamin D, or calcitriol, can influence both the innate and the adaptive arm of the immune response. Calcifediol levels have been found to be inversely correlated with upper respiratory tract infections in several studies, and this activity seems to be related to its role in the innate immunity. Cathelicidin is one of the main underlying mechanisms since this peptide increases the phagocytic and germicidal activity acting as chemoattractant for neutrophils and monocytes, and representing the first barrier in the respiratory epithelium to pathogenic invasion. Furthermore, vitamin D exerts a predominantly inhibitory action on the adaptive immune response, and it influences either cell-mediated or humoral immunity through suppression of B cells proliferation, immunoglobulins production or plasma cells differentiation. This role is played by promoting the shift from a type 1 to a type 2 immune response. In particular, the suppression of Th1 response is due to the inhibition of T cells proliferation, pro-inflammatory cytokines production (e.g., INF-γ, TNF-α, IL-2, IL-17) and macrophage activation. Finally, T cells also play a fundamental role in viral infectious diseases. CD4 T cells provide support to B cells antibodies production and coordinate the activity of the other immunological cells; moreover, CD8 T lymphocytes remove infected cells and reduce viral load. For all these reasons, calcifediol could have a protective role in the lung damage produced by COVID-19 by both modulating the sensitivity of tissue to angiotensin II and promoting overexpression of ACE-2. Promising results for the potential effectiveness of vitamin D supplementation in reducing the severity of COVID-19 disease was demonstrated in a pilot clinical trial of 76 hospitalised patients with SARS-CoV-2 infection where oral calcifediol administration reduced the need for ICU treatment. These interesting results need to be confirmed in larger studies with available information on vitamin D serum levels.

An Efficient Mobile Application for Identification of Immunity Boosting Medicinal Plants using Shape Descriptor Algorithm.

In the Covid-19 pandemic situation, the world is looking for immunity-boosting techniques for fighting against coronavirus. Every plant is medicine in one or another way, but Ayurveda explains the uses of plant-based medicines and immunity boosters for specific requirements of the human body. To help Ayurveda, botanists are trying to identify more species of medicinal immunity-boosting plants by evaluating the characteristics of the leaf. For a normal person, detecting immunity-boosting plants is a difficult task. Deep learning networks provide highly accurate results in image processing. In the medicinal plant analysis, many leaves are like each other. So, the direct analysis of leaf images using the deep learning network causes many issues for medicinal plant identification. Hence, keeping the requirement of a method at large to help all human beings, the proposed leaf shape descriptor with the deep learning-based mobile application is developed for the identification of immunity-boosting medicinal plants using a smartphone. SDAMPI algorithm explained numerical descriptor generation for closed shapes. This mobile application achieved 96%accuracy for the 64 × 64 sized images.

Shape Memory Respirator Mask for Airborne Viruses.

The emergence of COVID-19 has spurred demand for facemasks and prompted many studies aiming to develop masks that provide maximum protection. Filtration capacity and fit define the level of protection a mask can provide, and the fit is in large part determined by face shape and size. Due to differences in face dimensions and shapes, a mask of one size will not be likely to fit all faces. In this work, we examined shape memory polymers (SMPs) for producing facemasks that are able to alter their shape and size to fit every face. Polymer blends with and without additives or compatibilizers were melt-extruded, and their morphology, melting and crystallization behavior, mechanical properties, and shape memory (SM) behavior were characterized. All the blends had phase-separated morphology. The mechanical properties of the SMPs were modified by altering the content of polymers and compatibilizers or additives in the blends. The reversible and fixing phases are determined by the melting transitions. SM behavior is caused by physical interaction at the interface between the two phases in the blend and the crystallization of the reversible phase. The optimal SM blend and printing material for the mask was determined to be a polylactic acid (PLA)/polycaprolactone (PCL) blend with 30% PCL. A 3D-printed respirator mask was manufactured and fitted to several faces after being thermally activated at 65°C. The mask had excellent SM and could be molded and remolded to fit a variety of facial shapes and sizes. The mask also exhibited self-healing and healed from surface scratches.

Coronavirus peplomer charge heterogeneity

Recent advancements in viral hydrodynamics afford the calculation of the transport properties of particle suspensions from first principles, namely, from the detailed particle shapes. For coronavirus suspensions, for example, the shape can be approximated by beading (i) the spherical capsid and (ii) the radially protruding peplomers. The general rigid bead-rod theory allows us to assign Stokesian hydrodynamics to each bead. Thus, viral hydrodynamics yields the suspension rotational diffusivity, but not without first arriving at a configuration for the cationic peplomers. Prior work considered identical peplomers charged identically. However, a recent pioneering experiment uncovers remarkable peplomer size and charge heterogeneities. In this work, we use energy minimization to arrange the spikes, charged heterogeneously to obtain the coronavirus spike configuration required for its viral hydrodynamics. For this, we use the measured charge heterogeneity. We consider 20 000 randomly generated possibilities for cationic peplomers with formal charges ranging from 30 to 55. We find the configurations from energy minimization of all of these possibilities to be nearly spherically symmetric, all slightly oblate, and we report the corresponding breadth of the dimensionless rotational diffusivity, the transport property around which coronavirus cell attachment revolves. © 2023 Author(s).

Establishment of an in vitro assay to detect antibody-mediated procoagulant platelet formation on a single cell level in real time

Introduction Procoagulant platelets (PLTs), a subpopulation of PLTs that is characterized by increased externalization of phosphatidylserine (PS), are increasingly identified to promote a prothrombotic environment in different diseases. Recently we observed that procoagulant PLT formation can be induced via engagement of immune receptor Fc-gamma-RIIA by COVID-19, VITT and HIT patient immunoglobulin subclass G (IgG) antibodies (Abs). Here, Fc-gamma- RIIA engagement by patient Abs resulted in significant formation of procoagulant PLTs and loss of mitochondrial potential that was associated with high thrombin formation as well as increased thrombus formation. In the cur- rent study, we aim to establish a PLT adhesion assay that allows investigation of PLT mitochondria during procoagulant PLT formation. Method PLTs were spread on human serum albumin, fibrinogen or collagen precoated glass slides. Adhesion and subsequent shape change of PLTs as well as procoagulant PLT formation were investigated in real time using immune fluorescence microscopy. For the detection of PLT shape change, mitochondrial dynamics and PS externalization, PLTs were double stained with MitoTracker green, a mitochondrial dye that binds to free thiol groups of cysteine residues in the mitochondrial membrane, and Annexin-V, respectively. For the visualization of mitochondrial release from PLTs intracellular compartment, a monoclonal Ab that binds to a subunit of the translocase of the outer membrane (TOM) complex on the mitochondrial membrane, namely TOM22, was used. Results During the observation period, a subgroup of PLTs that was spread on collagen became procoagulant as determined by an increased binding of Annexin- V on the PLT surface. Contrary, these changes were nearly absent in PLTs that adhered to fibrinogen (percentage [ %] of Annexin-V positive cells: 19.80 +/- 3.42 % vs. 1.92 +/- 0.62 %, p value 0.0357). Interestingly, procoagulant PLT formation was associated with a significant loss of MitoTracker green signal in PLTs while it remained constant in non-procoagulant PLTs attached on both extracellular matrix coatings. Loss of MitoTracker green signal was associated with translocation of mitochondrial proteins from intracellular to extracellular, as a higher count of TOM22 Ab-positive labelled structures, most likely extracellular mitochondria were detected on collagen but not on fibrinogen coated glass slides. Conclusion Our findings indicate, that the formation of procoagulant PLTs is associated with dramatic changes of the mitochondrial integrity in PLTs. Further attempts, that investigate the potential pathophysiological role of PLT mitochondrial release in Ab-mediated prothrombotic disorders may contribute to a further understanding of the role of PLT mitochondria in these complex diseases.

Shape-based Evaluation of Epidemic Forecasts

Infectious disease forecasting for ongoing epidemics has been traditionally performed, communicated, and evaluated as numerical targets - 1, 2, 3, and 4 week ahead cases, deaths, and hospitalizations. While there is great value in predicting these numerical targets to assess the burden of the disease, we argue that there is also value in communicating the future trend (description of the shape) of the epidemic - for instance, if the cases will remain flat o r a s urge i s expected. To ensure what is being communicated is useful we need to be able to evaluate how well the predicted shape matches with the ground truth shape. Instead of treating this as a classification problem ( one out of n shapes), we define a transformation of the numerical forecasts into a "shapelet"-space representation. In this representation, each dimension corresponds to the similarity of the shape with one of the shapes of interest (a shapelet). We prove that this representation satisfies the property that two shapes that one would consider similar are mapped close to each other, and vice versa. We demonstrate that our representation is able to reasonably capture the trends in COVID-19 cases and deaths time-series. With this representation, we define an evaluation measure and a measure of agreement among multiple models. We also define the shapelet-space ensemble of multiple models as the mean of their shapelet-space representations. We show that this ensemble is able to accurately predict the shape of the future trend for COVID-19 cases and trends. We also show that the agreement between models can provide a good indicator of the reliability of the forecast. © 2022 IEEE.

Design and Performance Analysis of Compact Coronavirus-Shaped Microstrip Patch Antenna for Wireless Applications †

The paper proposes a compact-sized coronavirus-shaped Microstrip Patch Antenna (MPA) for wireless communication. A 15-20 GHz band of frequency is employed to analyze the effect of the shape on antenna's performance and characteristics. A low-cost FR4 dielectric substrate is used in the design and implementation of the coronavirus-shaped antenna, with suitable dimensions. The proposed antenna has six patterns depending upon the band of frequencies, and the same have been analyzed. The results show that the realized gain is better than -15 dB when using frequencies around 17 GHz, and total efficiency is about 70%. CST microwave software is used for designing and analysis.

Exploring the impact of the COVID-19 pandemic on perceptual disturbances and dysfunctional eating attitudes and behaviors: A review of the literature.

From the outbreak of the novel coronavirus 2019 (COVID-19) a new physical and social distancing environment has changed our lives and, more particularly, the way of perceiving oneself, as well as eating attitudes and behaviors. An increasing number of studies have highlighted a risky scenario in terms of negative perceptions of one's body as well as disordered eating and eating disorder patterns in both clinical and general population. With regard to this postulate, this literature review posits two main concepts-perceptual disturbances and dysfunctional eating attitudes and behaviors-in the general and (sub-)clinical populations, to provide an understanding of these phenomena during the COVID-19 pandemic. The main objective of this article is to provide a comprehensive and critical review of published scientific literature about perceptual disturbances (i.e., negative body image, body image disturbances, low body esteem) and dysfunctional eating attitudes and behaviors, including disordered eating (e.g., restrictive eating, binge-eating episodes, overeating, emotional eating) and eating disorders features in community (i.e., general population) and clinical and sub-clinical samples worldwide during the COVID-19 pandemic. The PubMed, ScienceDirect, Ebsco, and Google Scholar databases were searched. The initial search produced 42 references. Scientific publications from March 2020 to April 2022 were included, and among the works compiled, only published research articles have been retained. Purely theoretical papers were also excluded. The final selection consisted of 21 studies, covering both community, clinical (i.e., eating disorder population), and sub-clinical samples. The details of the results are discussed taking into consideration the potential impact of changes in the way we perceive ourselves and interact with others (e.g., the popularity of videoconferencing and the over-use of social network sites due to social isolation) as well as changes in eating attitudes and behaviors, physical activity and exercise (e.g., as an emotional response to the insecurity generated by the pandemic context), in community and (sub-)clinical samples. The discussion sheds light on two outcomes: (1) a summary of findings with methodological considerations; (2) an intervention continuum to deal with the consequences of the COVID-19 pandemic; (3) and a final conclusion.

Influence of letter shape on readers' emotional experience, reading fluency, and text comprehension and memorisation.

Introduction: The amount of educational material delivered to pupils and students through digital screens is increasing. This method of delivering educational materials has become even more prevalent during the COVID-19 pandemic. To be as effective as possible, educational material must be properly designed not only in terms of content, but also in terms of form, e.g., the typeface. The present study investigated the effect of letter shape on readers' feelings of pleasantness during reading, reading fluency, and text comprehension and memorisation. Methods: To find out whether age influences the effects of typeface shape on reading measures, we divided the participants into a group of less experienced readers (children) and more experienced readers (adults). Both groups read texts in eight different typefaces: four of them were round or in rounded shape, and four were angular or in pointed shape. With an eye-tracker, the reading speed and the number of regressive saccades were recorded as measures of reading fluency and changes in pupil size as an indicator of emotional response. After reading each text, the participants rated the pleasantness of the typeface, and their comprehension and memorisation of texts were checked by asking two questions about the text content. Results: We found that compared to angular letters or letters in pointed shape, round letters or letters in round shape created more pleasant feelings for readers and lead to a faster reading speed. Children, as expected, read more slowly due to less reading experiences, but, interestingly, had a similar number of regressive saccades and did not comprehend or remember the text worse than university students. Discussion: We concluded that softer typefaces of rounder shapes should be used in educational materials, as they make the reading process easier and thus support the learning process better for both younger and adult readers. The results of our study also showed that a comparison of findings of different studies may depend on the differences among the used letter shapes.

The 5'UTR of HCoV-OC43 adopts a topologically constrained structure to intrinsically repress translation.

The emergence of SARS-CoV-2, which is responsible for the COVID-19 pandemic, has highlighted the need for rapid characterization of viral mechanisms associated with cellular pathogenesis. Viral UTRs represent conserved genomic elements that contribute to such mechanisms. Structural details of most CoV UTRs are not available, however. Experimental approaches are needed to allow for the facile generation of high-quality viral RNA tertiary structural models, which can facilitate comparative mechanistic efforts. By integrating experimental and computational techniques, we herein report the efficient characterization of conserved RNA structures within the 5'UTR of the HCoV-OC43 genome, a lab-tractable model coronavirus. We provide evidence that the 5'UTR folds into a structure with well-defined stem-loops (SLs) as determined by chemical probing and direct detection of hydrogen bonds by NMR. We combine experimental base-pair restraints with global structural information from SAXS to generate a 3D model that reveals that SL1-4 adopts a topologically constrained structure wherein SLs 3 and 4 coaxially stack. Coaxial stacking is mediated by short linker nucleotides and allows SLs 1 to 2 to sample different cojoint orientations by pivoting about the SL3,4 helical axis. To evaluate the functional relevance of the SL3,4 coaxial helix, we engineered luciferase reporter constructs harboring the HCoV-OC43 5'UTR with mutations designed to abrogate coaxial stacking. Our results reveal that the SL3,4 helix intrinsically represses translation efficiency since the destabilizing mutations correlate with increased luciferase expression relative to wildtype without affecting reporter mRNA levels, thus highlighting how the 5'UTR structure contributes to the viral mechanism.

Dual-Polarized COVID-19 Microstrip Antenna Array for 5G Applications

This paper presents a novel unique single-layer dual-polarized microstrip patch antenna array with a COVID-19 shape designed for building a Base Station (BS) for sub-6 GHz applications at the resonant frequency 3.16 GHz. Furthermore, it is easy to fabricate and compact, which makes it suitable for 5G applications. Firstly, a single-element fractal shape antenna with a gain of 3 dB is discussed. Secondly, an 8-element 2x4 antenna array is designed with a gain of 8 dB. The antenna is fabricated using an FR4-epoxy double-sided copper board with a thickness of 1.6 mm. It is optimized by performing parametric studies of the dimensions using the finite element method (FEM) software program HFSS. The printed prototype measurements including S-parameters, polarization, and radiation pattern show a good agreement with simulation results. © 2022 IEEE.

Intelligent Surface-Enhanced Raman Scattering Sensor System for Virus Identification

COVID-19 has devastated the entire world for the past couple of years. Timely and efficient detection and identification of a virus are crucial in preventing the wider virus spread. By using intelligent sensors based on Surface-Enhanced Raman Scattering (SERS), it is possible to detect and identify virus automatically. In this study, we successfully applied the XGBoost Algorithm (Supervised Machine Learning) to classify the type of the virus using the SERS sensor data. The supervised approach has a limitation when a new type of virus arises, whose shape is different from the previously known samples. To tackle this problem, we investigated the unsupervised learning approaches that can cluster the virus data into different groups without labeled data. The unsupervised approach presented in this paper is called k-Shape Clustering. This technique compares the cross-correlation between different samples and then clusters them into similar or different groups. If a subvariant of a virus emerges, it would be clustered into the existing virus groups;if a new type of virus is found, it would be clustered into a new group. Both of the approaches have shown very promising results based on extensive evaluations. © 2022 IEEE.