Impact of automobile exhaust on biochemical and genomorphic characteristics of Mimusops elengi L. growing along roadsides of Lahore city, Pakistan.

Automobile exhaust releases different types of pollutants that are at great risk to the air quality of the environment and incidental distress to the nature of roadside plants. Mimusops elengi L. is an evergreen medicinal tree cultivated along the roadside of Lahore City. This research aimed to investigate physiological, morphological and genomorphic characteristics of M. elengi under the influence of air pollution from vehicles. Healthy and mature leaves were collected from trees on Canal Bank and Mall roads of Lahore as the experimental sites and control sites were 20 km away from the experimental site. Different physiochemical, morphological, air pollution tolerance index (APTI) and molecular analysis for the detection of DNA damage were performed through comet assay. The results demonstrated the mean accumulated Cd, Pb, Cu and Ni heavy metal contents on the leaves were higher than the control plants (1.27, 3.22, 1.32 and 1.46 µg mg-1). APTI of trees was 9.04. Trees in these roads significantly (p < 0.01) had a lower leaf area, petiole length and leaf dry matter content in comparison to control site. Increased comet tail showed that DNA damage was higher for roadside trees than trees in the control area. For tolerance of air pollution, it necessary to check the APTI value for the M. elengi at the polluted road side of Lahore city. For long-term screening, the source and type of pollutants and consistent monitoring of various responses given by the trees should be known.

Understanding rural women's preferences for telephone call engagement with primary health care providers in Nigeria: a discrete choice experiment.

BACKGROUND: The COVID-19 pandemic has accelerated the use of mobile phones to provide primary health care services and maintain continuity of care. This study aims to understand rural women's preferences for telephone call engagement with primary health care providers in Nigeria. METHODS: A discrete choice experiment was conducted alongside an action research project that empowered primary health care workers to develop and implement a telephone call intervention to assess and enhance experiences with facility childbirth care. Between January and March 2022, 30 providers from 10 primary health care facilities implemented the choice experiment among rural women who had institutional childbirth to elicit service user preferences for telephone call engagement. The women were asked to express their preferred scenario for telephone call engagement with their primary health care providers. Generalised linear mixed models were used to estimate women's preferences. RESULTS: Data for 460 women were available for the discrete choice experiment. The study showed that rural women have preferences for telephone call engagement with primary health care providers. Specifically, women preferred engaging with female to male callers (ß=1.665 (95% CI 1.41, 1.93), SE=0.13, p<0.001), preferred call duration under 15 min (ß=1.287 (95% CI 0.61, 1.96), SE=0.34, p<0.001) and preferred being notified before the telephone engagement (warm calling) (ß=1.828 (95% CI 1.10, 2.56), SE=0.37, p<0.001). Phone credit incentive was also a statistically significant predictor of women's preferences for engagement. However, neither the availability of scheduling options, the period of the day or the day of the week predicts women's preferences. CONCLUSIONS: The study highlights the importance of understanding rural women's preferences for telephone call engagement with healthcare providers in low-income and middle-income countries. These findings can inform the development of mobile phone-based interventions and improve acceptability and broader adoption.

Intravesical mitomycin C efficacy in acidic and alkaline urinary pH: impact on recurrence-free survival rate after TURBT.

Background: Urinary bladder tumor recurrence following transurethral resection of bladder tumor (TURBT) is a common issue. This study aims to determine how urine alkalinization affects bladder tumor recurrence after surgery. Materials and methods: Sixty patients receiving mitomycin C (MMC) therapy after TURBT were divided into two groups based on mean pH values. Twenty-six patients were in group A, whose urine pH was below 5.5. However, there were 34 patients in group B, and their urine pH was higher than 5.5. Both groups of patients were given intravesical MMC once weekly for 6 weeks following TURBT. A cystoscopy was performed as a follow-up at 3, 6, and 12 months. Urine pH and the recurrence-free survival rate were compared using Kaplan-Meier survival analysis and the COX proportional hazard model. Results: The mean time to tumor recurrence in group A (intravesical MMC in acidic urine) and group B (intravesical MMC in alkaline urine) was 12.48 versus 16.84 months, respectively. Alkaline urine pH was identified as an independent predictor of preventing the recurrence of superficial bladder tumors by univariate COX regression analysis. Age, sex, and mean tumor size did not affect the likelihood of tumor recurrence. However, smoking had an association with increased tumor recurrence. Conclusion: Tumor recurrence post-TURBT is delayed in patients with alkaline urine pH. Smoking is an independent risk factor for bladder tumors.

Green growth strategies in Asia: unleashing the heterogeneous asymmetry of ICT capital, financial fragility, environmental policy stringency, and education.

Financial fragility, ICT capital, environmental policy stringency, and education are the main factors that have also gained popularity regarding their impact on green growth. This study examines the impact of financial fragility, ICT capital, environmental policy stringency, and education on green growth. For analyzing the short- and long-run estimates, we have applied the panel QARDL model. The results of the panel QARDL model highlight that the estimates of non-performing bank loans and bank costs are negatively significant in both the short and long run, implying that financial fragility hurts green growth in the short and long run. Similarly, the estimated coefficients of the internet (mobile) and education estimates are positively significant in the short and long run, confirming that ICT capital and education are causing green growth, while environmental policy stringency promotes green growth only in the long run. Regarding the asymmetric effects of all the factors on green growth, the Wald test only confirms asymmetric effects in the long run. The study offers several significant recommendations for sustainable green development policies.

How do energy technology innovation, financial inclusion, and digital trade help to achieve carbon neutrality targets?

The ultimate goal of carbon neutrality objectives is to bring greenhouse gas emissions down to a point where they are no longer a factor in escalating climate change and global warming. Adopting sustainable habits, technologies, and investments may be facilitated and accelerated by energy technology innovation, digitalization trade, and financial inclusion, which can substantially influence reaching carbon neutrality objectives. However, none of the past studies have examined the role of energy technology innovation, financial inclusion, and digital trade on the carbon neutrality targets in top polluted economies. To fill this vacuum, this study aims to investigate the effect of energy technology innovation, financial inclusion, and digital trade on carbon neutrality in the top 40 polluted economies across Asia, America, and Europe from 2004-2021. Two renowned econometric techniques are used for empirical analysis, including Two Stage Least Square (2SLS) and Generalized Method of Moments (GMM). The estimates of energy innovation, ICT trade, digital financial inclusion, foreign direct investment, and research and development spending highlight the adverse influence on carbon emissions in global, Asian, American, and European samples. Conversely, the per capita income and foreign direct investment cause carbon emissions to increase in Asia, America, and Europe. Thus, policy experts in top polluted economies should target an integrated policy with a central focus on energy innovation, digital trade, and financial inclusiveness to achieve carbon neutrality.

Green growth as a determinant of ecological footprint: Do ICT diffusion, environmental innovation, and natural resources matter?

The nexus between green growth and ecological footprint is associated with crucial environmental implications. But this domain is not examined sufficiently and provides ambiguous findings. Furthermore, these studies have not addressed the role of natural resources, environmental innovation, and ICT in influencing ecological footprint. Our study analyzes the impact of green growth, ICT, environmental innovation, and natural resources on the ecological footprint ofemerging-7 and developed-7 economies. We employed CS-ARDL methodology to draw the long-run and short-run estimates of the said relationships. The obtained findings show that green growth, ICT, and environmental innovation reduce the ecological footprint in emerging economies in the long run. However, natural resources enhance the ecological footprint in emerging economies in the long run. Green growth, ICT, natural resources, and environmental innovation reduce the ecological footprint in the long run in developed economies. Based on these outcomes, the study recommends important policy suggestions.

Education and its impact on renewable energy demand, carbon intensity, and green growth: do digital financial inclusion and environmental policy stringency matter in China.

Various targets need to be accomplished before the dream of sustainable development comes true. Among these targets, increasing renewable energy demand, reducing carbon intensity, and achieving green growth are the most noticeable. Therefore, the present study focuses on capturing digital financial inclusion's impact on renewable energy demand, carbon intensity, and green growth in the presence of ICT trade and environmental policy stringency in China. To empirically estimate the model, we have applied ARDL covering the time span from 1995 to 2020. The results state that the estimated coefficients attached to education, ATMS, and environmental policy stringency are positively significant in the renewable energy and green growth model and negatively significant in the carbon intensity model. From these results, we confer that education, digital financial inclusion, and environmental policy stringency are good for increasing renewable energy demand, reducing carbon intensity, and achieving green growth in China. In the short run, some of the estimates are negative; hence, we conclude that the results are inconclusive. The results recommend some imperative policy suggestions.

Financial deepening, financial innovation, and education as new determinants of green growth in China.

To address the issue of global warming, the agreed solution is to reduce GHG emissions. The plausible solution to reduce GHG emissions is to follow a green growth strategy that refers to the complete decoupling of economic growth from its environmental impact through the sustainable utilization of natural resources. Consistent with this view, this study investigates the impact of financial deepening, financial innovation, and education on green growth in China from 1996 to 2020. The empirical analysis of the model is conducted through quantile ARDL. The long-run estimated coefficients of financial institution deepening are positively significant across most quantiles, whereas the estimated coefficients of financial market deepening are positively significant in almost half quantiles. These results imply that the financial deepening of both financial markets and institutions can positively contribute to green growth. However, the estimates of financial innovations are significant and positive in higher quantiles, implying that financial innovation only contributes to the green when the rate of financial innovation is too high. The estimates of education are positively significant at higher quantiles. Our study highlights various policy suggestions that are aimed at instigating sustainable green growth in China.

Optimization of Wire Electric Discharge Machining (WEDM) Process Parameters for AISI 1045 Medium Carbon Steel Using Taguchi Design of Experiments.

With the growth of the manufacturing industry, the demand for alloy materials with high hardness, toughness, and impact strength has increased. Since products from such alloy materials are extremely difficult to manufacture with high accuracy and reduced surface roughness using traditional machining techniques, wire electric discharge machining can be used to machine such complex parts with more precision. In this case-study-based research, machining factors such as current, pulse-on time, and voltage are studied to determine their effects on the material removal rate for AISI 1045 medium carbon steel. The Taguchi L9 orthogonal array is used in the design of experiments for optimization. Statistical techniques such as analysis of variance and signal-to-noise ratio are used to identify the control parameters that matter most in bringing about optimal results. Based on the results, the current is the most crucial control variable in this investigation. Moreover, the maximum material removal rate obtained was 0.7112 mm3/min with the obtained optimized values of current (I) = 16 A, voltage (V) = 50 V, and pulse-on time (Ton) = 100 µs.

Clean energy consumption and CO2 emissions: does China reduce some pollution burdens through environmental regulation?

Environmental regulations are considered a prerequisite for environmental performance. However, very limited studies have explored the asymmetric relationship between clean energy consumption, environmental regulation, and CO2 emissions. This study scrutinizes the asymmetry phenomenon in environmental regulation-clean energy consumption and environmental quality nexus in China by using the time series nonlinear ARDL approach by covering the period 1993-2019. The result reveals that the impact of environmental regulation on clean energy consumption and CO2 emissions is asymmetric. A positive change in environmental regulation has a positive effect on clean energy consumption but a negative impact on CO2 emissions in the long run. While a negative change in environmental regulation has insignificant effects on clean energy consumption and CO2 emissions in the long run. The study suggests that China should need to revisit environmental regulation policies that could help in improving environmental quality.

Energy efficiency and green innovation and its asymmetric impact on CO2 emission in China: a new perspective.

Green innovation undoubtedly plays a significant role in generating employment opportunities, improving green economic activity, and increasing environmental sustainability. This study scrutinizes the effect of energy efficiency and green innovation on CO2 emissions for China using nonlinear autoregressive distributed lag (NARDL) from 1991 to 2019. Findings show that energy efficiency and green innovation contribute to reducing CO2 emissions in China. Energy efficiency and green innovation are also important nonlinear determinants of CO2 emissions. An increase in energy efficiency and green innovation lowers CO2 emissions, while a fall in energy efficiency and green innovation increases CO2 emissions in China in the long run. Some policy measures are suggested to attain carbon neutrality.

The asymmetric effect of technology shocks on CO2 emissions: a panel analysis of BRICS economies.

Technological innovation positively contributes to economic development in BRICS countries; their environmental consequences cannot be ignored. Thus, it is imperious to explore the impact of technological shocks on environmental quality. We used ARDL and NARDL models to draw empirical consensus on the data set from 1990 to 2019 for BRICS economies. The results of ARDL model reveal that technological shocks positively affect carbon emissions in the long-run and short-run. The findings of NARDL model reveal that positive shocks in technology positively affect carbon emissions in the long-run and short-run, implying that an increase in technological development triggers an increase in carbon emissions. However, the negative shocks in technology have a negative impact on carbon emissions in the long-run, inferring that a reduction in technological development leads to a decrease in carbon emissions. The negative shock in technology has no significant impact on carbon emissions in the short-run. The findings emphasize the importance of environmental friendly technology to achieving sustainable development goals.

The trade-off between economic performance and environmental quality: does financial inclusion matter for emerging Asian economies?

This study examines the role of financial inclusion on the environment-economic performance in the top five Asian emerging economies. The data used for empirical investigation covers the time period from 1995 to 2019. Financial inclusion is measured through bank branches, bank credit, and insurance premiums. To check long-run associations, the panel ARDL approach has been employed for empirical analysis. The empirical evidence confirms the significant associations between financial inclusion-GDP nexus and financial inclusion-CO2 nexus. The findings show that bank branches and bank credit have a significantly positive impact on economic growth and CO2 emissions in the long run. However, insurance premium has no impact on economic growth but it exerts a significant negative impact on carbon emissions in the long run. Furthermore, energy consumption is highly sensitive to economic growth and carbon emissions. The study delivers imperative points for pollution eradication and attaining sustained economic growth. There is a need for government-level efforts to align the targets of financial inclusion with economic growth and environmental policies.

Re-evaluating the asymmetric conventional energy and renewable energy consumption-economic growth nexus for Pakistan.

To understand the nexus between economic growth and energy sources, in this study, we have selected Pakistan and collected data over the period 1980-2016. The neoclassical production function of Pakistan is augmented with conventional and renewable energy, capital, and labor. Conversely, the conventional and renewable models are being constructed by using GDP as an independent variable. This paper applied linear and nonlinear ARDL models to see whether the influence of conventional and renewable energy consumption on GDP per capita of Pakistan is symmetric or asymmetric and vice versa. Furthermore, the asymmetric causal effects between the energy variables and economic growth are also discussed. From the findings of the study, we deduce the long-run asymmetric effects of renewable energy on the economic growth of Pakistan. Similarly, the asymmetric effects of GDP, in the long run, are confirmed in both energy models. The symmetric and asymmetric causality results have recommended growth and conservation hypothesis. The findings propose that renewable energy is a significant factor in boosting the economic growth of Pakistan and a decline in the use of renewable energy could actually stem the economic growth of Pakistan.

The shadow economy in South Asia: dynamic effects on clean energy consumption and environmental pollution.

This study explores the symmetric and asymmetric effects of the shadow economy on clean energy and air pollution of South Asian countries over the period 1991-2019. The short-run ARDL findings for the clean energy model suggest that shadow economy increases clean energy consumption in Pakistan and Sri Lanka, whereas this effect is negative for India and insignificant for other countries. The long-run results indicate the adverse impact only for India and the effects of tax revenue on clean energy are positively significant in Sri Lanka while negatively signiicant in Nepal and Bangladesh. Institutional quality significantly increases clean energy in Pakistan, India, and Nepal. However, in the case of Pakistan and Nepal, institutional quality deteriorated the environmental quality. The results for the pollution model confer that shadow economy increases emissions in Pakistan, decreases in Bangladesh and Nepal, and has no effect in India and Sri Lanka. The nonlinear ARDL results reveal that the positive components of the shadow economy significantly increase clean energy consumption only in Pakistan; however, the negative components of the shadow economy are negatively significant in all countries except Sri Lanka and Nepal. However, the negative component of the informal sector of the economy reduces CO2 emissions in India and increases CO2 emissions in Bangladesh and Nepal. The results offer important policy implications for achieving clean energy and better environmental quality in South Asian countries.

Renewable energy and non-renewable energy consumption: assessing the asymmetric role of monetary policy uncertainty in energy consumption.

Previous infant literature has assessed the symmetric impact of monetary policy uncertainty on a few macro variables. Our study has considered asymmetric monetary policy uncertainty impacts on energy consumption. Our key concern in this study is to regulate whether US monetary policy uncertainty has an asymmetric impact on energy consumption. We employ the symmetric and asymmetric autoregressive distributed lag (ARDL) estimation methods, and we found that monetary policy uncertainty has short- and long-run negative effects on renewable energy consumption in the linear model, while decreased monetary policy uncertainty has a significant negative influence on renewable energy consumption in the USA in the non-linear model. However, in the short and long run, the measure of monetary policy uncertainty has an insignificant impact on non-renewable energy consumption, while increased monetary policy uncertainty in the USA has negative effects and decreased monetary policy uncertainty has positive effects on non-renewable energy consumption in the short and long run in the non-linear model. The effects are asymmetric in direction and magnitude. The study results call for vital changes in renewable and non-renewable energy policies to accommodate monetary policy uncertainties.