Highly Exposed ?NH2 Edge on Fragmented g-C3N4 Framework with Integrated Molybdenum Atoms for Catalytic CO2 Cycloaddition: DFT and Techno-Economic Assessment

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN),  NH₂ rich edges, and maximum utilization of isolated atomic Mo for propylene carbonate (PC) production through CO₂ cycloaddition of propylene oxide (PO). Various operational parameters are optimized, for example, temperature (130 °C), pressure (20 bar), catalyst (Mo₂GCN), and catalyst mass (0.1 g). Under optimal conditions, 2% Mo-doped GCN (Mo₂GCN) has the highest catalytic performance, especially the turnover frequency (TOF) obtained, 36.4 h⁻¹ is higher than most reported studies. DFT simulations prove the catalytic performance of Mo₂GCN significantly decreases the activation energy barrier for PO ring-opening from 50–60 to 4.903 kcal mol⁻¹. Coexistence of Lewis acid/base group improves the CO₂ cycloaddition performance by the formation of coordination bond between electron-deficient Mo atom with O atom of PO, while  NH₂ surface group disrupts the stability of CO₂ bond by donating electrons into its low-level empty orbital. Steady-state process simulation of the industrial-scale consumes 4.4 ton h⁻¹ of CO₂ with PC production of 10.2 ton h⁻¹. Techno-economic assessment profit from Mo₂GCN is estimated to be 60.39 million USD year⁻¹ at a catalyst loss rate of 0.01 wt% h⁻¹.     

Multifractal signatures of infectious diseases

Incidence of infection time-series data for the childhood diseases measles, chicken pox, rubella and whooping cough are described in the language of multifractals. We explore the potential of using the wavelet transform maximum modulus (WTMM) method to characterize the multiscale structure of the observed time series and of simulated data generated by the stochastic susceptible-exposed-infectious-recovered (SEIR) epidemic model. The singularity spectra of the observed time series suggest that each disease is characterized by a unique multifractal signature, which distinguishes that particular disease from the others. The wavelet scaling functions confirm that the time series of measles, rubella and whooping cough are clearly multifractal, while chicken pox has a more monofractal structure in time. The stochastic SEIR epidemic model is unable to reproduce the qualitative singularity structure of the reported incidence data: it is too smooth and does not appear to have a multifractal singularity structure. The precise reasons for the failure of the SEIR epidemic model to reproduce the correct multiscale structure of the reported incidence data remain unclear.     

Estimating epidemic coupling between populations from the time to invasion

Identifying the mechanisms by which diseases spread among populations is important for understanding and forecasting patterns of epidemics and pandemics. Estimating transmission coupling among populations is challenging because transmission events are difficult to observe in practice, and connectivity among populations is often obscured by local disease dynamics. We consider the common situation in which an epidemic is seeded in one population and later spreads to a second population. We present a method for estimating transmission coupling between the two populations, assuming they can be modelled as susceptible–infected–removed (SIR) systems. We show that the strength of coupling between the two populations can be estimated from the time taken for the disease to invade the second population. Confidence in the estimate is low if only a single invasion event has been observed, but is substantially improved if numerous independent invasion events are observed. Our analysis of this simplest, idealized scenario represents a first step toward developing and verifying methods for estimating epidemic coupling among populations in an ever-more-connected global human population.     

Nitrate Capture Investigation in Plasma-Activated Water and Its Antifungal Effect on Cryptococcus pseudolongus Cells

This research investigated the capture of nitrate by magnesium ions in plasma-activated water (PAW) and its antifungal effect on the cell viability of the newly emerged mushroom pathogen Cryptococcus pseudolongus. Optical emission spectra of the plasma jet exhibited several emission bands attributable to plasma-generated reactive oxygen and nitrogen species. The plasma was injected directly into deionized water (DW) with and without an immersed magnesium block. Plasma treatment of DW produced acidic PAW. However, plasma-activated magnesium water (PA-Mg-W) tended to be neutralized due to the reduction in plasma-generated hydrogen ions by electrons released from the zero-valent magnesium. Optical absorption and Raman spectra confirmed that nitrate ions were the dominant reactive species in the PAW and PA-Mg-W. Nitrate had a concentration-dependent antifungal effect on the tested fungal cells. We observed that the free nitrate content could be controlled to be lower in the PA-Mg-W than in the PAW due to the formation of nitrate salts by the magnesium ions. Although both the PAW and PA-Mg-W had antifungal effects on C. pseudolongus, their effectiveness differed, with cell viability higher in the PA-Mg-W than in the PAW. This study demonstrates that the antifungal effect of PAW could be manipulated using nitrate capture. The wide use of plasma therapy for problematic fungus control is challenging because fungi have rigid cell wall structures in different fungal groups.     

Population dynamic interference among childhood diseases

Epidemiologists usually study the interaction between a host population and one parasitic infection. However, different parasite species effectively compete, in an ecological sense, for the same finite group of susceptible hosts, so there may be an indirect effect on the population dynamics of one disease due to epidemics of another. In human populations, recovery from any serious infection is normally preceded by a period of convalescence, during which infected individuals stay at home and are effectively shielded from exposure to other infectious diseases. We present a model for the dynamics of two infectious diseases, incorporating a temporary removal of susceptibles. We use this model to explore population-level consequences of a temporary insusceptibility in childhood diseases, the dynamics of which are partly driven by differences in contact rates in and out of school terms. Significant population dynamic interference is predicted and cannot be dismissed in the limited case-study data available for measles and whooping cough in England before the vaccination era.     

A systematic review of the literature on plastic pollution in the Laurentian Great Lakes and its effects on freshwater biota

Plastic pollution is ubiquitous in freshwater systems worldwide, and the Laurentian Great Lakes are no exception. We conducted a systematic review to synthesize the current state of the literature on plastic pollution, including macroplastics (>5 mm) and microplastics (<5 mm), in the Great Lakes. Thirty-four publications were used in our systematic review. We found ubiquitous contamination of microplastics in surface water, with maximum abundances exceeding those in ocean gyres. There are also high levels of plastic contamination reported across benthic sediments and shorelines of the Great Lakes. Citizen science data reveals macroplastic across Great Lakes shorelines, with more than three million pieces of plastic litter recorded over a span of three years. We completed a second systematic review of plastic pollution and its impact on freshwater ecosystems in general to inform how plastic in the Great Lakes may impact wildlife. Among studies published in the literature, we found 390 tested effects, 234 (60%) of which were detected and 156 (40%) of which were not; almost all of the freshwater effects (>98%) were tested on microplastics. Based on a subset of these papers, we found that the shape and size of a particle likely affects whether an effect is detected, e.g., more effects are detected for smaller particles. Finally, we identify gaps in scientific knowledge that need to be addressed and discuss how the state of the science can inform management strategies.     

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.     

Parameterizing state–space models for infectious disease dynamics by generalized profiling: measles in Ontario

Parameter estimation for infectious disease models is important for basic understanding (e.g. to identify major transmission pathways), for forecasting emerging epidemics, and for designing control measures. Differential equation models are often used, but statistical inference for differential equations suffers from numerical challenges and poor agreement between observational data and deterministic models. Accounting for these departures via stochastic model terms requires full specification of the probabilistic dynamics, and computationally demanding estimation methods. Here, we demonstrate the utility of an alternative approach, generalized profiling, which provides robustness to violations of a deterministic model without needing to specify a complete probabilistic model. We introduce novel means for estimating the robustness parameters and for statistical inference in this framework. The methods are applied to a model for pre-vaccination measles incidence in Ontario, and we demonstrate the statistical validity of our inference through extensive simulation. The results confirm that school term versus summer drives seasonality of transmission, but we find no effects of short school breaks and the estimated basic reproductive ratio ℛ₀ greatly exceeds previous estimates. The approach applies naturally to any system for which candidate differential equations are available, and avoids many challenges that have limited Monte Carlo inference for state–space models.     

Hygrothermal analysis of woven-fabric composite plates

The elastic properties of glass/epoxy woven-fabric composites under hygrothermal loading were predicted by using three analytical models originally developed for the prediction of room-temperature elastic properties of woven-fabric composites. In this analysis, the dry and wet bulk resin properties tested at similar temperatures as the composites were used to predict the overall elastic properties of glass/epoxy plates. It is assumed that the fibres are not affected by both temperature and moisture. It was found that the predicted elastic properties of both satinweave and unidirectional fabric composites are in good agreement with experimental values.