Spread Analysis of the Sustainability-Linked Bonds Tied to an Issuer’s Greenhouse Gases Emissions Reduction Target

Sustainability-Linked Bonds (SLBs) are a new type of general corporate purpose bond in which payments are tied to an issuer’s sustainability key performance indicators (KPIs) with respect to the environmental, social, and governance (ESG) criteria. The structure is complementary to green bonds. The Tesco SLBs are linked to the firm’s ability to cut its greenhouse gas emissions by 60%. The priority is to reduce its reliance on nonrenewable grid electricity, which contributed 65% of Tesco’s global carbon emissions footprint. Tesco accounts for 1% of electricity demand in the UK. Failure to meet the goals will result in a coupon step-up by 25 basis points on the last three coupons. The aim of our study is to investigate the presence of, how we call it ‘ESG spread’, marked by negative yield difference between SLB and regular bonds. It is something similar to ‘greenium’, that is, a premium paid by bondholders for green bonds when compared to nongreen bonds. We compare the bid and ask yields of SLBs with the interpolated yields, calculated for the yields of Tesco and Carrefour notes. Then, we look into the SLB yields in coupon step-up scenario to answer the question if the issuer’s failure to keep up with KPIs results in changing of ESG spread from negative to positive.

Pulse-Height and 2-D Charge-Spread Single-Pixels Studies on a LuYAP:Ce Scintillation Array

The present work deals with a 10 × 10 array of (Lu0.7Y0.3)AP:Ce 2 × 2 × 10 mm3 pixels, manufactured by Crytur (Cz), that has been utilized in a previous paper. The crystal-array has been coupled to an 8 × 8 anodes H10966 model Hamamatsu (Jp) Position-Sensitive Photo Multiplier Tube (PSPMT) connected to electronics for single events scintillation read-out. The response of such a detector has been studied under Co-57, or Ba-133, or Cs-137 gamma-ray emissions, as well as with Lu-176 self-activity only. The present work is aimed at characterizing the individual crystal-pixels’ single-event responses in terms of pulse-height and of spreads of the 2-D charge-distributions. In particular, the charge-spread characterization pointed out several defects in the crystal-array assembly, not detected by usual pulse-height studies. The diagnostic method based on charge-spread analysis seems also well suited for scintillation array characterizations for gamma-ray detectors studies, as well as for quality controls of such pixelated devices during the lifetime of systems in the field of radionuclide medical imaging (SPECT and PET). The method is also appropriate for other applications where gamma-ray spectroscopy is required, like nuclear physics, astrophysics, astroparticle physics, homeland security, and non-proliferation.

Ranking Effectiveness of COVID-19 Tests Using Fuzzy Bipolar Soft Expert Sets

The theory of fuzzy bipolar soft sets is an efficient extension of soft sets for depicting the bipolarity of uncertain fuzzy soft information; however, it is limited to a single expert. The present research article introduces the theory of an innovative hybrid model called the fuzzy bipolar soft expert sets, as a natural extension of two existing models (including fuzzy soft expert sets and fuzzy bipolar soft sets). The proposed model is highly suitable for describing the bipolarity of fuzzy soft information having multiple expert opinions. Some fundamental properties of the developed hybrid model are discussed, including subset, complement, union, intersection, AND operation, and OR operation. The proposed concepts are explained with detailed examples. Moreover, to demonstrate the applicability of our initiated model, an application of the proposed hybrid model is presented along with the developed algorithm to tackle the real-world group decision-making situation, that is, ranking effectiveness of tests in spread analysis of COVID-19. Finally, a comparative analysis of the developed model with some existing mathematical tools such as fuzzy soft expert sets and fuzzy bipolar soft sets is provided to show the cogency and reliability of the initiated model.

Covid-19 Spread Analysis

Covid-19 Spread Analysis is a stand-alone application developed in python which will help us to analyse the covid-19 cases all over the world. In this python project, we will implement a live dashboard for COVID 19 spread analysis. This dashboard will provide much insightful visualization for the study of corona virus spread. It will consist of a world map on which circles of the top 15 regions having the largest corona cases of will be displayed. There will be a table in the left panel showing the total active cases till date in the respective region. In the right panel, there will be a world map which will represent the impact of the virus using a red circle. More the number of cases in the region on the map, the bigger are the red circle in that region. Also, the user can see a detailed graph of state wise covid-19 cases of our country. This graph will show the active, confirmed, recovered and death cases. User can see all this information date wise as well as month wise. The graph will be updated every day so that user can clearly analyse the covid-19 spread. The project aims to understand various useful features of this tool and to present different concepts of data science applied within the application along with its importance in managing the ongoing pandemic. . It gives the readers an insight in to covid-19 spread is happening with the help of the entire data.

Common concerns, barriers to care, and the lived experience of individuals with hepatitis B: a qualitative study

Background An estimated between 257 and 292 million people live with chronic HBV globally. While much is known about the causes, and epidemiology of HBV, little is understood about the quality of life and impact of HBV on those living with the infection. Methods A random sample of HBV-related email queries sent to the Hepatitis B Foundation, a U.S.-based non-profit organization, over a 12-month period in 2018–2019 were retrieved, tabulated, and analyzed qualitatively to highlight information needs and explore the experiences of people living with HBV and their families and loved ones. Codebook development was informed by the literature and through line-by-line reading of a sub-sample of queries. Data analysis was facilitated by NVivo12 software. Data were coded independently by two members of the research team and intercoder reliability was assessed to assure coding accuracy throughout the coding phase. Results A total of 338 queries from people around the globe were identified and analyzed. The analysis revealed three thematic groups: 1) health-specific challenges associated with diagnosis and treatment, 2) emotional needs related to experiences with HBV stigma, discrimination, fear, social isolation, and distress and 3) informational needs related to HBV prevention and transmission, and interpretation of laboratory tests. Conclusions People living with HBV are in need of information to manage their disease and prevent its spread. Analysis of queries uncovered significant misconceptions about HBV transmission and treatment. Additionally, the emotional and psychological impact of an HBV diagnosis on those living with the infection is significant. There is a clear need for patient and community education to expand knowledge and awareness of HBV globally to achieve 2030 WHO HBV elimination goals.

Complex Network Modelling of Origin–Destination Commuting Flows for the COVID-19 Epidemic Spread Analysis in Italian Lombardy Region

Currently the whole world is affected by the COVID-19 disease. Italy was the first country to be seriously affected in Europe, where the first COVID-19 outbreak was localized in the Lombardy region. The further spreading of the cases led to the lockdown of the most affected regions in northern Italy and then the entire country. In this work we investigated an epidemic spread scenario in the Lombardy region by using the origin–destination matrix with information about the commuting flows among 1450 urban areas within the region. We performed a large-scale simulation-based modeling of the epidemic spread over the networks related to three main motivations, i.e., work, study and occasional transfers to quantify the potential contribution of each category of travellers to the spread of the epidemic process. Our findings outline that the three networks are characterised by different weight dynamic growth rates and that the network “work” has a critical role in the diffusion phenomenon showing the greatest contribution to the epidemic spread.