The usage of power system multi-model forecasting aided state estimation for cyber attack detection

THE PURPOSE. Smart electrical grids involve extensive use of information infrastructure. Such an aggregate cyber-physical system can be subject to cyber attacks. One of the ways to counter cyberattacks is state estimation. State Estimation is used to identify the present power system operating state and eliminating metering errors and corrupted data. In particular, when a real measurement is replaced by a false one by a malefactor or a failure in the functioning of communication channels occurs, it is possible to detect false data and restore them. However, there is a class of cyberattacks, so-called False Data Injection Attack, aimed at distorting the results of the state estimation. The aim of the research was to develop a state estimation algorithm, which is able to work in the presence of cyber-attack with high accuracy.METHODS. The authors propose a Multi-Model Forecasting-Aided State Estimation method based on multi-model discrete tracking parameter estimation by the Kalman filter. The multimodal state estimator consisted of three single state estimators, which produced single estimates using different forecasting models. In this paper only linear forecasting models were considered, such as autoregression model, vector autoregression model and Holt’s exponen tial smoothing. When we obtained the multi-model estimate as the weighted sum of the single-model estimates. Cyberattack detection was implemented through innovative and residual analysis. The analysis of the proposed algorithm performance was carried out by simulation modeling using the example of a IEEE 30-bus system in Matlab.RESULTS. The paper describes an false data injection cyber attack and its specific impact on power system state estimation. A Multi - Model Forecasting-Aided State Estimation algorithm has been developed, which allows detecting cyber attacks and recovering corrupted data. Simulation of the algorithm has been carried out and its efficiency has been proved.CONCLUSION. The results showed the cyber attack detection rate of 100%. The Multi-Model Forecasting-Aided State Estimation is an protective measure against the impact of cyber attacks on power system.

The new frontline: exploring the links between moral distress, moral resilience and mental health in healthcare workers during the COVID-19 pandemic

Background Global health crises, such as the COVID-19 pandemic, confront healthcare workers (HCW) with increased exposure to potentially morally distressing events. The pandemic has provided an opportunity to explore the links between moral distress, moral resilience, and emergence of mental health symptoms in HCWs. Methods A total of 962 Canadian healthcare workers (88.4% female, 44.6 + 12.8 years old) completed an online survey during the first COVID-19 wave in Canada (between April 3rd and September 3rd, 2020). Respondents completed a series of validated scales assessing moral distress, perceived stress, anxiety, and depression symptoms, and moral resilience. Respondents were grouped based on exposure to patients who tested positive for COVID-19. In addition to descriptive statistics and analyses of covariance, multiple linear regression was used to evaluate if moral resilience moderates the association between exposure to morally distressing events and moral distress. Factors associated with moral resilience were also assessed. Findings Respondents working with patients with COVID-19 showed significantly more severe moral distress, anxiety, and depression symptoms (F > 5.5, p < .020), and a higher proportion screened positive for mental disorders (Chi-squared > 9.1, p = .002), compared to healthcare workers who were not. Moral resilience moderated the relationship between exposure to potentially morally distressing events and moral distress (p < .001); compared to those with higher moral resilience, the subgroup with the lowest moral resilience had a steeper cross-sectional worsening in moral distress as the frequency of potentially morally distressing events increased. Moral resilience also correlated with lower stress, anxiety, and depression symptoms (r > .27, p < .001). Factors independently associated with stronger moral resilience included: being male, older age, no mental disorder diagnosis, sleeping more, and higher support from employers and colleagues (B [0.02, |-0.26|]. Interpretation Elevated moral distress and mental health symptoms in healthcare workers facing a global crisis such as the COVID-19 pandemic call for the development of interventions promoting moral resilience as a protective measure against moral adversities.

Intranasal inhibitor blocks Omicron and other variants of SARS-CoV-2

The emergence of the SARS-CoV-2 Omicron variant capable of escaping neutralizing antibodies emphasizes the need for prophylactic strategies to complement vaccination in fighting the COVID-19 pandemic. Nasal epithelium is rich in the ACE2 receptor and important for SARS-CoV-2 transmission by supporting early viral replication before seeding to the lung. Intranasal administration of SARS-CoV-2 neutralizing antibodies or antibody fragments has shown encouraging potential as a protective measure in animal models. However, there remains a need for SARS-CoV-2 blocking agents that are more economical to produce in large scale, while less vulnerable to mutational variation in the neutralization epitopes of the viral Spike glycoprotein. Here we describe TriSb92, a highly manufacturable trimeric human nephrocystin SH3 domain-derived antibody mimetic targeted against a conserved region in the receptor-binding domain of the Spike. TriSb92 potently neutralizes SARS-CoV-2 and its variants of concern, including Delta and Omicron. Intranasal administration of a modest dose of TriSb92 (5 or 50 micrograms) as early as eight hours before the challenge with SARS-CoV-2 B.1.351 efficiently protected mice from infection. The target epitope of TriSb92 was defined by cryo-EM, which revealed triggering of a conformational shift in the Spike trimer rather than competition for ACE2 binding as the molecular basis of its strong inhibitory action. Our results highlight the potential of intranasal inhibitors in protecting susceptible individuals from SARS-CoV-2 infection, and describe a novel type of inhibitor that could be of use in addressing the challenge posed by the Omicron variant.

Intranasal inhibitor blocks omicron and other variants of SARS-CoV-2

The emergence of the SARS-CoV-2 Omicron variant capable of escaping neutralizing antibodies emphasizes the need for prophylactic strategies to complement vaccination in fighting the COVID-19 pandemic. Nasal epithelium is rich in the ACE2 receptor and important for SARS-CoV-2 transmission by supporting early viral replication before seeding to the lung1. Intranasal administration of SARS-CoV-2 neutralizing antibodies or antibody fragments has shown encouraging potential as a protective measure in animal models2-5. However, there remains a need for SARS-CoV-2 blocking agents that are more economical to produce in large scale, while less vulnerable to mutational variation in the neutralization epitopes of the viral Spike glycoprotein. Here we describe TriSb92, a highly manufacturable trimeric human nephrocystin SH3 domain-derived antibody mimetic targeted against a conserved region in the receptor-binding domain of the Spike. TriSb92 potently neutralizes SARS-CoV-2 and its variants of concern, including Delta and Omicron. Intranasal administration of a modest dose of TriSb92 (5 or 50 micrograms) as early as eight hours before the challenge with SARS-CoV-2 B.1.351 efficiently protected mice from infection. The target epitope of TriSb92 was defined by cryo-EM, which revealed triggering of a conformational shift in the Spike trimer rather than competition for ACE2 binding as the molecular basis of its strong inhibitory action. Our results highlight the potential of intranasal inhibitors in protecting susceptible individuals from SARS-CoV-2 infection, and describe a novel type of inhibitor that could be of use in addressing the challenge posed by the Omicron variant.

Knowledge, Perception and Attitude of the Undergraduate Healthcare Students Relative to COVID-19 Infection at a Teaching Institute of Karachi

Coronavirus disease 2019 (COVID-19) has been declared a pandemic by the World Health Organization. Efforts are being made all over the world to raise awareness in order to prevent the disease from spreading. The purpose of this study was to assess undergraduate healthcare students' attitudes, perceptions, and knowledge of COVID-19 disease. We conducted a cross- sectional survey in which a questionnaire with 12 questions was transformed online on Google forms and distributed online to healthcare students. Data was collected between May and June of 2021. The convenience sampling technique was used, resulting in a sample size of 926 people. A total of 926 individual questionnaires were evaluated. The findings revealed that the majority of participants learned about COVID-19 through social media and electronic media, which was the most common source of information. The majority of participants stated that older and middle-aged people are more likely to be affected. The protective measure against symptomatic and asymptomatic COVID 19 is N95 and surgical masks, as well as sanitization. Half of the participants believe that COVID 19 is a bioweapon, and that it affects all religious groups equally. In general, undergraduate healthcare students had a fair understanding of the disease and a favorable attitude toward preventive measures. The government and the public are taking effective measures to combat disease spread; however, there is still a need for additional awareness campaigns and knowledge of safe interventions to combat disease spread.

Exploring the Prevalence of Protective Measure Adoption in Mosques during the COVID-19 Pandemic in Indonesia

Muslims worship together more frequently than members of other religions. They pray in congregation at the mosque five times a day, causing the mosque to become a central hub for COVID-19 transmission. Therefore, the adoption of protective measures as a method of mitigating the COVID-19 pandemic in mosques is vital. This study aims to account for the implementation status of protective measures in mosques in Surakarta City, Indonesia, during the COVID-19 pandemic. A cross-sectional survey was conducted using a structured questionnaire sent to mosque caretakers as research participants. The mosques were chosen using a simple random sampling technique for a total sample of 247 mosques in Surakarta City. Participants were asked how often they implement the following protective measures in mosques, as recommended by the Majelis Ulama Indonesia: checking body temperature before entering the mosque, prayer distancing, carrying own prayer mat, wearing a mask when praying and no handshaking after prayer. The prevalence of the adoption of protective measures was revealed to be amongst 44.6% to 92.6%, with the lowest prevalence in checking body temperature before entering the mosque. Overall, only 33.7% of mosques implemented all protective measures. In mosques affiliated with Nahdlatul Ulama and the small mosques, the prevalence of protective measures was lower than in mosques affiliated with Muhammadiyah and the large mosques, respectively, suggesting that it is crucial to develop targeted health messages for these groups. Finally, as religious communities remain active in congregational worship during the outbreak, the contradictions between medical and religious practices must be addressed in society for believers to adopt public health policies and for policymakers to comprehend the importance of religious observances.

Self-presentation and gender on social media: an exploration of the expression of “authentic selves”

Purpose In response to calls for more research on gender(s) in digital contexts, this paper aims to ask, how do individuals engage in self-presentation of their gender identities on social media? Design/methodology/approach Using a multi-method qualitative approach, this research explores the narratives of 17 Millennials as they negotiate their online gender expressions with a particular focus on the image-based social platforms, Facebook and Instagram. Specifically, in-depth interviews, a collage technique and visual data from informants’ social media pages were analyzed to identify emergent themes. Findings Drawing on the theoretical work of Goffman’s (1971) self-presentation and Butler’s (1999) gender performance, this research highlights a pervading discourse of authenticity or the desire for Millennial social media users to craft and perform a perceived “authentic self” online. This often entails both expressions of gender fluidly and gender policing. Further, four strategies emerge in the data which reveal how individuals negotiate and navigate their gendered self-presentation online, either in an agentic manner or as a protective measure. Originality/value While much research exists on online self-presentation, gender(s) has been under-researched in a digital context. Existing studies examine the content of social media pages (e.g. Facebook profiles or women’s Instagram pages) as it relates to gender, but largely do not explore the lived experiences and narratives of individuals as they negotiate their gendered expressions. In addition, the use of visual data through the collage technique adds valuable insight into how gender is experienced and performed. Findings reveal that while Millennials are often touted as a gender-fluid generation, tensions still exist in online gendered expressions.

Myths Surrounding Covid-19 Vaccine Candidates: A Guide to Fight Back

The Covid-19 pandemic has propelled public health officials into the socio-political sphere due to the need for constantly updated information on behalf of the public. However, many individuals choose to acquire health information/guidance from indirect sources, including social media, news organizations, and general word of mouth. As a result, myths and false narratives about various essential health topics, including vaccine characteristics and protective measures, can circulate un-verified between millions of individuals with little recourse. These can further widen the “gap” between public knowledge and current research, resulting in lower vaccine uptake (vaccine hesitancy) and protective measure adherence. Such actions have profound implications as nations attempt to achieve herd immunity and end the pandemic once and for all. Thus, it is vital that public health officials, health providers, researchers, and the general public be able to differentiate common Covid-19 myths from facts and be prepared to approach such interactions via sound reasoning and research-based evidence. This chapter will serve as a guide to accomplish just that.

Reinforcing customer journey through artificial intelligence: a review and research agenda

Purpose This study defines a three-angled research plan to intensify the knowledge and development undergoing in the retail sector. It proposes a theoretical framework of the customer journey to explain the customers' intent to adopt artificial intelligence (AI) and machine learning (ML) as a protective measure for interaction between the customer and the brand.Design/methodology/approach This study presents a research agenda from three-dimensional online search, ML and AI algorithms. This paper enhances the readers' understanding by reviewing the literature present in utilizing AI in the customer journey and presenting a theoretical framework.Findings Using AI tools like Chatbots, Recommenders, Virtual Assistance and Interactive Voice Recognition (IVR) helps create improved brand awareness, better customer relationships marketing and personalized product modification.Originality/value This study intends to identify a research plan based on investigating customer journey trends in today's changing times with AI incorporation. The research provides a novel model framework of the customer journey by directing customers into different stages and providing different touchpoints in each stage, all supported with AI and ML.

Synergetic measures needed to control infection waves and contain SARS-CoV-2 transmission

The public and scientific discourse on how to mitigate the COVID-19 pandemic is often focused on the impact of individual protective measures, in particular on immunization by vaccination. In view of changing virus variants and conditions, however, it seems not clear if vaccination or any other single protective measure alone may suffice to contain the transmission of SARS-CoV-2. Here, we investigate the effectiveness and synergies of vaccination and different non-pharmaceutical interventions such as universal masking (surgical, N95/FFP2), distancing & ventilation, contact reduction, and testing & isolation as a function of compliance in the population. We find that it would be difficult to contain SARS-CoV-2 transmission by any individual measure as currently available under realistic conditions. Instead, we show how multiple synergetic measures can be and have to be combined to decrease and keep the effective reproduction number (Re) below unity, even for virus variants with increased basic reproduction number (R0). We suggest that the presented approach and results can be used to design and communicate efficient strategies for mitigating the COVID-19 pandemic, depending on R0 as well as the efficacy and compliance achieved with each protective measure. At vaccination rates around 70%, the combination and synergies of universal masking, distancing & ventilation, and testing & isolation with moderate compliances around 30% appear well suited to keep Re below 1 and prevent or suppress infection waves. Higher compliance or additional measures like contact reductions (confinement/lockdown) are required to effectively and swiftly break intense waves of infection. For schools, we find that the transmission of SARS-CoV-2 can be contained by 2-3 tests per week combined with distancing & ventilation and masking.