Notes

Any Computer-Based Technique to Design Non-Standard Proteins Most likely Capable to Avoid HOX-PBX1-Associated Cancer Conditions.
They also pinpoint the importance of China and Chile in the future evolution of the copper market.•Medical wastes will drastically increase due to Covid-19-outbreak.•Safe and sustainable waste management is a major concern.•Experience and lessons can be learned for medical waste management in China.The production and consumption of plastics, although inevitable in our modern life, are predominantly unsustainable and inefficient. Hence, the concept of a circular economy for plastics has been proposed as a sustainable approach to thrive both economy and our modern life. To implement a circular economy for plastics, an understanding of both individuals' and organizations' behaviors is needed since psychological effects often undermine technical solutions. We particularly focus on organizations' behaviors since commercial plastic waste has not been thoroughly investigated compared to household plastic waste. Using the Theory of Planned Behavior (TPB) and Partial Least Squares Structural Equation Modeling (PLS-SEM), we assess the determinants of intentions and behaviors of 637 organizations in Belgium towards a circular economy for plastics. Our PLS-SEM analysis support that attitudes, subjective norms, and perceived behavioral control of decision makers positively influence organizations' intentions to implement best practices of plastic recycling. Furthermore, organizations' intentions, perceived behavioral control, pressures, and enablers positively, whereas barriers negatively, influence organizations' behaviors. Our study shows that most organizations have positive intentions, yet they seem to be failing in implementing best practices of plastic recycling due to some critical barriers. To overcome this intention-behavior gap and to attain a circular economy for plastics, our study suggests some measures.This perspective calls for building greater understanding of the role that entrepreneurship plays in addressing the challenges to resource and waste management imposed by COVID-19. We contend that researchers and practitioners need to recognize that entrepreneurs are important change agents who can help in the transition to a more sustainable and circular economy. We present challenges as well as opportunities to address this gap with the goal to foster future research.The crisis brought upon by the COVID-19 pandemic has altered global waste generation dynamics and therefore has necessitated special attention. The unexpected fluctuations in waste composition and quantity also require a dynamic response from policymakers. This study highlights the challenges faced by the solid waste management sector during the pandemic and the underlying opportunities to fill existing loopholes in the system. The study presents specific cases for biomedical waste, plastic waste, and food waste management - all of which have been a major cause of concern during this crisis. Further, without active citizen participation and cooperation, commingled virus-laden biomedical waste with the regular solid waste stream pose significant negative health and safety issues to sanitation workers. Single-use plastic usage is set to bounce back due to growing concerns of hygiene, particularly from products used for personal protection and healthcare purposes. It is expected that household food waste generation may reduce due to increased conscious buying of more non-perishable items during lockdown and due to concerns of food shortage. However, there is a chance of increase in food waste from the broken supply chains such as food items getting stuck on road due to restriction in vehicle movements, lack of workers in the warehouse for handling the food products, etc. The study also stresses the need for building localized resilient supply chains to counter such situations during future pandemics. While offering innovative solutions to existing waste management challenges, the study also suggests some key recommendations to the policymakers to help handle probable future pandemics if any holistically.•New challenges in MSW management in Tehran after the COVID-19 pandemic was studied.•Over 5.5 millions of PPEs are being daily discarded in Tehran during COVID-19.•Hospital wastes are being disposed of without undergoing any treatment in Tehran.•Landfilling of MSW has increased by 34.7% after the outbreak of COVID-19.•Secondary contagion from improper management of MSW is probable in Tehran.•Effective governance and efficient coordination across multi-levels and multi-sectors are pivotal factors to ensure food supply during COVID-19.•Digital tools and innovative models provided valuable solutions to cope with the crisis in China, which can be further developed and contribute to the "New Normal".•The pandemic implies the necessity to strengthen urban-rural linkages and foster local food production for more resilient local food systems.In this study, a natural surfactant, saponin was isolated from soapnut (Sapindus Mukorossi). The extracted surfactant was characterized by Fourier-transform infrared spectroscopy (FTIR) analysis. The effectiveness of the isolated surfactant as EOR agent was evaluated from foam generation/stabilization properties, wettability alteration of the rock surfaces, as well as oil-water interfacial tension (IFT) reduction characteristics. The performance of the extracted saponin was compared with that of a commercial saponin and sodium dodecyl sulfate (SDS). The foaming properties of the saponin with carbon dioxide (CO2) was characterized using Teclis Foamscan instrument at room condition and 60 °C. The IFT and contact angles at room conditions and reservoir conditions were measured using KRŰSS Drop Shape Analyzer (DSA 25 and DSA 100) via pendant drop and sessile drop techniques respectively. Selleckchem PHI-101 The foamability of the saponin-stabilized foam was good at ambient condition and 60 °C. Moreover, the time taken for almost 100e of SiO2 nanoparticles (0.05 wt% and 0.1 wt%). The study suggests that the extracted saponin could be considered as supplementary alternative to conventional EOR surfactants.Biocidal functionalization in polyester fibers is a really tough challenge because of the lack of tethering groups. This study indicated supercritical carbon dioxide application using N-halamine would be an alternative solution for obtaining antibacterial function on the polyester surface. Firstly, N-(2-methyl-1-(4-methyl-2,5-dioxo-imidazolidin-4 yl)propan-2 yl)acrylamide was synthesized and applied to the polyester in supercritical carbon dioxide medium, at 120 °C, 30 MPa for different processing times. The addition of N-halamine on the surface significantly brought antibacterial activity against E. coli. The chlorine loadings showed that 6 -h exposure time was critical to obtain sufficient antibacterial activity. This treatment caused a reasonable and tolerable loss in color and mechanical properties. But, the durability to abrasion, stability, and rechargeability of oxidative chlorine, and the durability of N-halamine on the surface were remarkably good. Conclusively, it can be available to work on polyester surfaces with resource-efficient and eco-friendly supercritical carbon dioxide technique for getting more functionalization and modification.We present an early version of a Susceptible-Exposed-Infected-Recovered-Deceased (SEIRD) mathematical model based on partial differential equations coupled with a heterogeneous diffusion model. The model describes the spatio-temporal spread of the COVID-19 pandemic, and aims to capture dynamics also based on human habits and geographical features. To test the model, we compare the outputs generated by a finite-element solver with measured data over the Italian region of Lombardy, which has been heavily impacted by this crisis between February and April 2020. Our results show a strong qualitative agreement between the simulated forecast of the spatio-temporal COVID-19 spread in Lombardy and epidemiological data collected at the municipality level. Additional simulations exploring alternative scenarios for the relaxation of lockdown restrictions suggest that reopening strategies should account for local population densities and the specific dynamics of the contagion. Thus, we argue that data-driven simulations of our model could ultimately inform health authorities to design effective pandemic-arresting measures and anticipate the geographical allocation of crucial medical resources.This paper analyzes the drivers of cross-border bank lending to 49 Emerging Markets (EMs) during the period 1990Q1-2014Q4, by assessing the impact of monetary, financial and real sector shocks in both the US and the euro area. The literature has traditionally highlighted the influence of US monetary policy on driving cross-border bank flows, and more recently the importance of both US and Euro Area (EA) financial/banking sectors' related variables. Our contribution is the simultaneous analysis of the role of these US and EA drivers, as well as their interactions with real sector shocks. We corroborate the negative impact of US monetary policy tightening on cross-border lending to EMs, but we find that EA monetary policy seems to have an impact mostly on Emerging Europe, reflecting the fact that cross-border lending to most other EM regions is dollar denominated. We also find that real sector shocks in both the US and EA trigger an increase in cross-border lending, but less in EA when modeling the financial sector. Finally, for financial sector shocks, such as those associated with a decrease in bank leverage, our results indicate a broad-based overall contraction of cross-border lending if the shock originates in the US, and heterogenous effects across borrowing regions if the shock originates in the EA.The n-dimensional fuzzy logic (n-DFL) has been contributed to overcome the insufficiency of traditional fuzzy logic in modeling imperfect and imprecise information, coming from different opinions of many experts by considering the possibility to model not only ordered but also repeated membership degrees. Thus, n-DFL provides a consolidated logical strategy for applied technologies since the ordered evaluations provided by decision makers impact not only by selecting the best solutions for a decision making problem, but also by enabling their comparisons. In such context, this paper studies the n-dimensional fuzzy implications (n-DI) following distinct approaches (i) analytical studies, presenting the most desirable properties as neutrality, ordering, (contra-)symmetry, exchange and identity principles, discussing their interrelations and exemplifications; (ii) algebraic aspects mainly related to left- and right-continuity of representable n-dimensional fuzzy t-conorms; and (iii) generating n-DI from existing fuzzy implications. As the most relevant contribution, the prospective studies in the class of n-dimensional interval (S,N)-implications include results obtained from t-representable n-dimensional conorms and involutive n-dimensional fuzzy negations. And, these theoretical results are applied to model approximate reasoning of inference schemes, dealing with based-rule in n-dimensional interval fuzzy systems. A synthetic case-study illustrates the solution for a decision-making problem in medical diagnoses.
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