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The focus of this research is to examine the safe-haven properties of seven ethical and conventional asset classes using two sophisticated techniques: quantile coherence and Wavelet coherence. We analyze data ranging from October 3, 2011, to September 30, 2021, that encapsulates several global risk events. The results exhibit either positive or neutral associations between most assets and the Geopolitical Risk (GPR), indicating their safe haven capabilities against the GPR shocks. Notably, the coherence observed between the Economic Policy Uncertainty (EPU) and these assets reveals a positive correlation during bearish markets (monthly frequency) and normal and bullish markets (weekly frequency). Furthermore, only the S&P Green Bond (SPGRNB) as well as S&P Global Clean Energy (SPCE) indices demonstrate protective attributes against EPU shocks during COVID-19. Conversely, market volatility (VIX) was found to negatively impact all asset classes except SPGRNB, which indicates the non-idiosyncratic nature of VIX shocks. Consequently, investors and fund managers operating in ethical markets may consider optimizing their portfolios to shield their wealth amidst instances of extreme and enduring shocks.
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http://dx.doi.org/10.1016/j.heliyon.2024.e40980 | DOI Listing |
Angew Chem Int Ed Engl
September 2025
CFisUC, Department of Physics, University of Coimbra, 3004-516, Coimbra, Portugal.
With the goal of manipulating (bio)chemical processes, photoswitches emerge as important assets in molecular nanotechnology. To guide synthetic strategies toward increasingly more efficient systems, conformational dynamics studies performed with atomic rigor are in demand, particularly if this information can be extracted with control over the size of a perturbing solvation layer. Here, we use jet-cooled rotational spectroscopy and quantum chemistry calculations to unravel the structure and micro-hydration dynamics of a prototype photoswitch.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Zoology, University of British Columbia, Vancouver, British Columbia, Canada.
Computer vision has increasingly shown potential to improve data processing efficiency in ecological research. However, training computer vision models requires large amounts of high-quality, annotated training data. This poses a significant challenge for researchers looking to create bespoke computer vision models, as substantial human resources and biological replicates are often needed to adequately train these models.
View Article and Find Full Text PDFBMC Oral Health
August 2025
School of Business, University of Southern Queensland, Toowoomba, Australia.
Background: Dental health and care among children and adolescents are a major neglected area of public health, leading to both physical and mental health consequences in the long term. Several demographics, economic, and social factors influence dental service utilization, with Socio-Economic Status (SES) being a significant determinant. SES plays an important role in the utilization of dental services for children and adolescents.
View Article and Find Full Text PDFVaccines (Basel)
July 2025
Center for Oncology, Radiopharmaceuticals and Research, Biologic and Radiopharmaceutical Drugs Directorate, Health Products and Food Branch, Health Canada, Ottawa, ON K1A 0K9, Canada.
One concern in the yearly re-formulation of influenza vaccines is the time-consuming manufacturing of vaccine potency reagents, particularly for emergency responses. The continuous evaluation of modern techniques such as reversed-phase (RP) chromatography is an asset for streamlining this process. One challenge with RP methods, however, is the need to re-optimize methods for antigens that show poor separation, which can be highly dependent on analyst experience and available data.
View Article and Find Full Text PDFInt J Data Sci Anal
March 2024
Fidelity Investments, London, UK.
We introduce a novel framework to study the dynamics of news narratives, by leveraging GPT3.5 advanced text analysis capabilities and graph theory. In particular, we focus on a corpus of economic articles from The Wall Street Journal and dynamically extract the main topics of discussion over time, in a completely systematic and scalable fashion.
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