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  • Albrechtsen Dillon posted an update 7 hours, 15 minutes ago

    The abuse of illicit drugs usually associated with dramatic crimes may cause significant problems for the whole society. Wastewater-based epidemiology (WBE) has been demonstrated to be a novel and cost-effective way to evaluate the abuse of illicit drugs at the community level, and has been used as a routine method for monitoring and played a significant role for combating the crimes in some countries, e.g. China. The method can also provide temporal and spatial variation of drugs of abuse. The detection methods mainly remain on the conventional liquid chromatography coupled with mass spectrometry, which is extremely sensitive and selective, however needs advanced facility and well-trained personals, thus limit it in the lab. As an alternative, sensors have emerged to be a powerful analytical tool for a wide spectrum of analytes, in particular aptamer sensors (aptasensors) have attracted increasing attention and could act as an efficient tool in this field due to the excellent characteristics of selectivity, sensitivity, low cost, miniaturization, easy-to-use, and automation. In this review, we will briefly introduce the context, specific assessment process and applications of WBE and the recent progress of illicit drug aptasensors, in particular focusing on optical and electrochemical sensors. We then highlight several recent aptasensors for illicit drugs in new technology integration and discuss the feasibility of these aptasensor for WBE. We will summarize the challenges and propose our insights and opportunity on aptasensor for WBE to evaluate community-wide drug use trends and public health.Many natural compounds, found mainly in plants, are associated with the treatment of various diseases. The search for natural therapeutic agents includes compounds with antiviral and anti-inflammatory activities. Among the many steps involved in bioprospection, extraction is the first and most critical step for obtaining bioactive compounds. One of the main advantages of using compressed fluids extraction is the high quality of the final product obtained due to the use of green solvents, while the selectivity towards target compounds can be tuned by adjusting the process parameters, especially pressure, temperature and solvent characteristics. In this review, a discussion is provided on the power of compressed fluids, such as supercritical fluid extraction (SFE), pressurized liquid extraction (PLE) and subcritical water extraction (SWE) to obtain antiviral and anti-inflammatory compounds from natural sources. In addition, an adequate knowledge about the identity and quantity of the compounds present in the extract is essential to correlate biological activity with chemical composition. AD80 manufacturer Phytochemical profiling tools used for identification and quantification of these bioactive natural compound are also discussed. It can be anticipated that after the current SARS-COV-2 pandemic, the search of new natural compounds with antiviral and anti-inflammatory activity will be a hot research topic, so, this review provides an overview on the technologies currently used that could help this research.We challenge the assumption in the literature of constant housing supply elasticities across housing expansions. Using a time-varying parameter (TVP)-VAR model on monthly US data since the early 1990s, we find that the response of housing supply to an expansionary monetary policy shock relative to the response of house prices has declined substantially since the Great Financial Crisis (GFC). Our findings are consistent with research suggesting that land-use regulation has tightened. Absent major reversions in regulation, our results point to a post-COVID-19 housing recovery characterised by a sluggish response of housebuilding to demand, but a relatively stronger response of house prices.We compare risk-neutral densities from equity index options across several countries during the early phase of the COVID-19 pandemic. The initial reaction in all analyzed markets was late, abrupt and simultaneous. Only a few weeks later, densities started to differ across markets.The recent spread of COVID-19 has led to the worst economic crisis since the 1930s. To boost demand after the crisis, direct monetary transfers to households are being discussed. Using novel microdata from the Eurosystem Household Finance and Consumption Survey (HFCS), we study how much of such a transfer households would actually spend. We do so by exploiting the unique opportunity that the new wave of the survey included an experimental question to calculate the marginal propensity to consume from hypothetical windfall gains. Our results show that households on average spend between about 33% (the Netherlands) and 57% (Lithuania) of such a transfer. In all countries, answers are clustered at spending nothing, spending 50% and spending everything. Marginal propensities to consume decrease with income but are not as clearly related to wealth.This short note constructs Mobility Zones to facilitate the discussion on the geographic extent of individual mobility restrictions to control the spread of Covid-19. Mobility Zones are disjoint sets of counties where a given level of individual mobility directly or indirectly connects all counties within each set. I compute Mobility Zones for the United States and each state using smartphone-based mobility data between counties. The average area and population of Mobility Zones have sharply shrunk around the onset of the epidemic. Pre-Covid-19 Mobility Zones may be useful in calibrating quantitative studies of targeted restriction policies, or for policymakers deciding on the adoption of specific mobility measures. Two examples suggest the use of Mobility Zones to inform within-state differences and cross-state coordination in mobility restriction policies.We estimate a VAR with world-level variables to simulate the effects of the Covid-19 outbreak-related uncertainty shock. We find a peak (cumulative over one year) negative response of world output of 1.6% (14%).Controlling for the polarity and subjectivity of social media data based on the development of the COVID-19 outbreak, we analyse the relationships between the largest cryptocurrencies and such time-varying realisation as to the scale of the economic shock centralised within the rapidly-escalating pandemic. We find evidence of significant growth in both returns and volumes traded, indicating that large cryptocurrencies acted as a store of value during this period of exceptional financial market stress. Further, cryptocurrency returns are found to be significantly influenced by negative sentiment relating to COVID-19. While not only providing diversification benefits for investors, results suggest that these digital assets acted as a safe-haven similar to that of precious metals during historiccrises.

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