Potential synergy of microplastics and nitrogen enrichment on plant holobionts in wetland ecosystems.

Wetland ecosystems are global hotspots for environmental contaminants, including microplastics (MPs) and nutrients such as nitrogen (N) and phosphorus (P). While MP and nutrient effects on host plants and their associated microbial communities at the individual level have been studied, their synergistic effects on a plant holobiont (i.e., a plant host plus its microbiota, such as bacteria and fungi) in wetland ecosystems are nearly unknown. As an ecological entity, plant holobionts play pivotal roles in biological nitrogen fixation, promote plant resilience and defense chemistry against pathogens, and enhance biogeochemical processes. We summarize evidence based on recent literature to elaborate on the potential synergy of MPs and nutrient enrichment on plant holobionts in wetland ecosystems. We provide a conceptual framework to explain the interplay of MPs, nutrients, and plant holobionts and discuss major pathways of MPs and nutrients into the wetland milieu. Moreover, we highlight the ecological consequences of loss of plant holobionts in wetland ecosystems and conclude with recommendations for pending questions that warrant urgent research. We found that nutrient enrichment promotes the recruitment of MPs-degraded microorganisms and accelerates microbially mediated degradation of MPs, modifying their distribution and toxicity impacts on plant holobionts in wetland ecosystems. Moreover, a loss of wetland plant holobionts via long-term MP-nutrient interactions may likely exacerbate the disruption of wetland ecosystems' capacity to offer nature-based solutions for climate change mitigation through soil organic C sequestration. In conclusion, MP and nutrient enrichment interactions represent a severe ecological risk that can disorganize plant holobionts and their taxonomic roles, leading to dysbiosis (i.e., the disintegration of a stable plant microbiome) and diminishing wetland ecosystems' integrity and multifunctionality.

Investigating the impact of ICT on transport-based CO2 emissions: empirical evidence from a quantile cointegration regression analysis.

In the global initiative to leverage information and communication technologies (ICT) for reducing emissions, sub-Saharan Africa (SSA), a region of unique significance, has exhibited a delay in adopting ICT. This study aims to investigate the intricate relationship between ICT and carbon dioxide (CO2) emissions from transport in SSA. Employing the panel quantile autoregressive distributed lag (PQARDL) technique, the study analyzes panel data from 24 SSA nations spanning from 2000 to 2021. The results indicate that internet usage and fixed telephone subscriptions have a mitigating effect on CO2 emissions from transport across all quantiles in both the short and long run. However, mobile phone subscriptions contribute to CO2 emissions from transport across all quantiles. Additionally, the middle-income groups demonstrate negative relationships between ICT variables and emissions from transport, while the low-income group exhibits significant positive associations. These findings imply that ICT plays a pivotal role in mitigating transport-based emissions and reveal pronounced disparities in ICT adoption across various income groups within SSA, highlighting overarching underdevelopment in ICT infrastructure. Robustness checks employing a two-step system generalized method of moment (GMM) model reinforce our findings. The study provides policy recommendations, including the promotion of ICT infrastructure development, implementation of smart transportation solutions, and fostering public-private partnerships to address these challenges, shedding light on the path toward a greener and more sustainable transport ecosystem in SSA.

Numerical and experimental characterization of splitter blade impact on pump as turbine performance.

Several rivers and streams are available in Africa and Asian regions with great potentials not applicable for constructing large hydropower dams but feasible for small and mini hydro generation. This study strive for investigating the impact of splitter blade on pump as turbine performance considering different speed and flow rates. Two specific centrifugal pump models one with six blades without splitter and another with four blades and four splitters were used for the study. The inlet diameter and outlet diameters of both impellers were 104 mm/116 mm, and 160 mm respectively at a designed flow rate Q = 12.5 m3/h, head H = 16 m, rotational speed n = 1450 rpm and efficiency of 56%, outlet impeller width of 0.006 m, a blade outlet angle of 30° was used for the study. CFD simulations were conducted with the use of k-ε turbulence model. The influence of splitter blade position on the performance of pump as turbine in the selected specific pumps with and without splitter blades has been investigated both experimentally and numerically at three different flow rates and rotational speed. The simulated data were in good agreement with the experimental results, the maximum deviation error between the CFD and test for each model are 5.6%, 2.6%, for the head and efficiency; 7.5% and 3.6% at different flow conditions.

Predicting the carbon dioxide emission of China using a novel augmented hypo-variance brain storm optimisation and the impulse response function.

For the past decade, the level of carbon dioxide emission in most cities in China is on the ascendancy. Yet, better prediction of environmental pollution is at the fringes of recent studies. Several erstwhile researchers have attempted predicting pollution whilst utilising approaches including the ordinary linear regressions, multivariate regressions, autoregressive integrated moving average (ARIMA), evolutionary and some conventional swarm intelligence. These conventional approaches, however, lead but to imprecise predictions owing to the inherent parameter problems characterised in those approaches. Consequently, there is the need for a better prediction of the key antecedents that affect air pollution whilst using robust techniques. This current study, therefore predicts the carbon emissions levels of China into the next decade, in response to changes in key economic variables: energy consumption, economic growth, trade, and urbanisation. This is to aid in monitoring and implementing of tailored policies and transformations in China and in similar developing and emerging economies. Our findings revealed a steadily rise in emissions as the economy grows during the initial years but decline in the ensuing forecasted period. The findings of the impulse response function, revealed that in the next decade, urbanisation, and trade (import and export) will be the major contributors of carbon dioxide emission. The proposed Brainstorm optimisation algorithms prediction model was verified and validated with actual data. Our study revealed that the Brainstorm Optimisation algorithm predicts better with less prediction error even under uncertainty information.

Cytokine concentrations direct endothelial function in pregnancy and preeclampsia.

Endothelial dysfunction is a prominent feature of preeclampsia, a hypertensive disorder of pregnancy, and contributes to multiple symptoms characteristic of the syndrome. A myriad of growth factors and cytokines are dysregulated in preeclampsia as compared to normal pregnancy, however, a complete appreciation of the effect of changing concentrations of these factors on endothelial function is lacking. In this study, we evaluate the effect of a variety of growth factors and cytokines on Ca2+ signaling and monolayer integrity. We report that VEGF165, TNFα, EGF, and IL-1ß either improve or inhibit Ca2+ signaling depending on dose, whereas TNFα and IL-1ß reduce monolayer integrity and bFGF increases monolayer integrity. Additionally, to model the effects of combinations of growth factors and cytokines, we screened for Ca2+ signaling changes in response to 16 dose combinations of VEGF165 and TNFα together. This revealed an optimal combination capable of supporting pregnancy-adapted Ca2+ signaling, and that changes in either VEGF165 or TNFα dose would result in a shift toward suppressed function. This study shows in detail how growth factor or cytokine concentration effects endothelial cell function. Such data can be used to model how changing growth factor and cytokine levels in normal pregnancy may contribute to healthy endothelial function and in preeclampsia may promote endothelial dysfunction. The results of VEGF165 and TNFα combination treatments suggest that more complex growth factor and cytokine combination modeling may be important in order to more accurately understand the effects of circulating factors on the endothelial function.

Green Innovation Practices and Its Impacts on Environmental and Organizational Performance.

This study aims to investigate the impact of stakeholders' views on the practices of green innovation (GI), consequent effect on environmental and organizational performance (OP), and moderating influence of innovation orientation. A quantitative method was employed for the sample size of 515 responses. To accumulate the data from the respondents, convenient random sampling was used. Data were collected from manufacturing and services firms through a field survey by using a closed-ended questionnaire based in the Punjab province of Pakistan. The analysis was done using the structural equation model of the partial least square analysis method. Our findings proved a positive and significant link between stakeholders' views on GI practices. A significant association has been found between GI practices and environmental and OP. The moderating effect was found to be negative but statistically significant. This research offers numerous contributions and provides decision-making insinuations.