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To model the fibre stress utilization in modified ring spun yarns, we developed an analytical formula from the experimental data. The development of empirical formulae is carried out by using two different techniques, i.e., Cubic Spline and Artificial Neural Network methods. The experimental data of stress-strain curves of fibre and yarn has a large variation. To cope this variability, we used the smoothing spline technique to find the best-fit curve with respect to a reasonable smoothness. The best nonlinear smooth fitting can be used to extrapolate the experimental data beyond the breaking point. The modified ring spun yarns (compact, SIRO and SIRO-compact) with 20/1, 30/1 and 40/1 English count, produced from viscose staple fibre, were used to predict fibre stress utilization up to the yarn break by extrapolating the mean stress-strain curves of fibre and yarn by using the artificial neural network. Moreover, a new distribution function of fibre distribution in yarn has been proposed and successfully implemented for the prediction of fibre stress utilization in yarn. The new formulation helps to compute the fibre stress utilization in the yarn analytically. The validation of the proposed methodology is presented by comparing the numerical results with the experimental data. The predicted fibre stress utilization was in good agreement with the experimental fibre stress utilization for all types of modified ring spun yarns. It has been observed that SIRO-compact yarn exhibits improved fibre stress utilization as compared to SIRO and compact yarns. Moreover, the new distribution functions Gamma and Gaussian distribution were introduced in parallel with the Dirac delta function. In previous similar studies on ring, rotor and air-jet spun yarns, the proposed model can only predict the fibre stress utilization before the breakage point whereas the modified model, in this study, can predict the fibre stress utilization up to the breaking point. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is prioritized at the G20 Conference in 2023. This transition is essential for reducing carbon emissions, and environmental experts have stressed the urgency of identifying the factors fueling this energy transition. This paper examines the effects of the transition to renewable energy and environmental technology innovations on achieving the G20 nations' carbon-neutrality goals between 1995 and 2020. In addition to analyzing the contribution of non-renewable energy sources, financial development, the labor force, and economic growth have been analyzed, all the selected variables are found to have a long-term cointegration relationship. Given the asymmetrical nature of the data distribution, the study employs an advanced moment quantile regression method. The outcome identifies non-renewable energy, financial development, and labor force as significant contributors to consumption-driven CO2 emissions throughout all quantiles. On the other hand, the development of renewable energy transition and advancements in environment-related technology innovations and economic growth led to a significant reduction in emission levels. The bootstrapped quantile regression provides additional confirmation of the reliability of these results. In addition, the panel causality analysis reveals both bidirectional and unidirectional causal connections among CO2 emissions and the other evaluated factors. These findings suggest that environmentally friendly strategies, green technological advancements and renewable energy are crucial for carbon mitigation. [ABSTRACT FROM AUTHOR]

Objective: To explore the presence of drug dependence and Epilepsy in patients with PTC (Post Truamatic Contusions) balanced cautiously. Study Design: Proposed Reviewed Research study. Setting: Hayatabad Medical Complex, Peshawar. Period: July 2020 to December 2020. Methods: About 90% of patients aged between fifteen to sixtyfive years old identified with cerebral lesion and balanced cautiously were applied. Follow up sessions was provided to patients for 12to 18 months. Results: Among the enrolled patients, 23% established early PTS (Post Traumatic Seizures) and approximately established late PTS (Post Traumatic Seizures) from mild to moderate level of cerebral lesion. Patients having early signs of Post traumatic Seizure, about 6% utilized AEDs (Anti-epileptic Drugs) for about 3 months throughout the treatment period and about 7% of patients along with late Post Traumatic Seizures utilized AEDs. Moreover, approximately 8 percent patients established late post traumatic Seizure without considering any early signs of condition. Research findings indicated that only 3% of patients with early and late PTS actually required AEDs for at least 6 months. Although, about 44 percent of patients were utilizing Anti-epileptic drugs to control seizures. Sensible usage of Anti-epileptic drugs is familiar in our region, contributing to enhanced danger of medicine opposition and acquiring financial pressure on low-paid people in well-established state. Additionally, extreme usage of anti-epileptic and prophylactic drugs doesn't impact the occurrence of PTE (Post Traumatic Epilepsy). Conclusion: The presence of late and early post-traumatic epilepsy observed within our study is contrast to that explored in another research. Sensible production of AEDs is occured in our state, that increases the danger of medicine opposition and attain financial issues for economically destruct people in well-established states. Extreme usage of AEDs and prophylactic drugs doesn't have an important influence on stopping PTE. [ABSTRACT FROM AUTHOR]

The computational study of fixed-point problems in distance spaces is an active and important research area. The purpose of this paper is to construct a new iterative scheme in the setting of Banach space for approximating solutions of fixed-point problems. We first prove the strong convergence of the scheme for a general class of contractions under some appropriate assumptions on the domain and a parameter involved in our scheme. We then study the qualitative aspects of our scheme, such as the stability and order of convergence for the scheme. Some nonlinear problems are then considered and solved numerically by our new iterative scheme. The numerical simulations and graphical visualizations prove the high accuracy and stability of the new fixed-point scheme. Eventually, we solve a 2D nonlinear Volterra Integral Equation (VIE) via the application of our main outcome. Our results improve many related results in fixed-point iteration theory. [ABSTRACT FROM AUTHOR]

Urban land serves as the medium for urban economic and residential activity. The degree of intensive and efficient use of urban land and the coordinated growth of the economy and society are significantly impacted by utilization efficiency. Northwest China's temperature, geography, water, and soil characteristics make less of the region suited for urban development. Thus, it is imperative to investigate Northwest China's urban land use efficiency (ULUE). This study applies the efficiency loss model to highlight the discrepancy between the optimal and actual values of each input-output variable of the ULUE, and uses the Super-SBM model to compute the ULUE of 39 cities. Additionally, the internal driving elements of the ULUE are examined using the Global Malmquist-Luenberger (GML) index. This study discovered that Northwest China had a low ULUE, with a modest upward trend seen between 2004 and 2018. The overall shape of the region was similar to an 'N' curve, with high efficiency values concentrated in the southeast of the region in 2018. When considering the agglomeration impact of urban agglomeration, these results are dependable. Moreover, the efficiency loss model discovered that pollution and wasteful resource usage were the main reasons behind the drop in ULUE in Northwest China. Finally, the GML index and its constituents revealed that the main force behind ULUE's growth in Northwest China is technological developments. This research provides important policy implications for reducing the gap between eastern and western regions, supporting high-quality development in northwest China, and protecting and intensively using urban land. [ABSTRACT FROM AUTHOR]

Understanding the eigenvalue distribution of sequence Toeplitz matrices has advanced significantly in recent years. Notable contributors include Bogoya, Grudsky, Böttcher, and Maximenko, who have derived precise asymptotic expansions for these eigenvalues under certain conditions related to the generating function as the matrix size increases. Building on this foundation, the Stefano Serra-Capizzano conjectured that, under certain assumptions about Ω and Φ, a similar expansion may hold for the eigenvalues of a sequence of preconditioned Toeplitz matrices T-1n (Φ)Tn(Ω), given a monotonic ratio r=Ω/Φ. In contrast to current eigenvalue solvers, this work presents a novel method for efficiently calculating the eigenvalues of a sequence of large preconditioned banded symmetric Toeplitz matrices (PBST). Our algorithm uses a higher-order spline fitting extrapolation technique to gather spectral data from a smaller sequence of PBST matrices in order to forecast the spectrum of bigger matrices. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018. Design/methodology/approach: Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis. Findings: The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam. Research limitations/implications: This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production. Originality/value: To the best of the authors' knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation. [ABSTRACT FROM AUTHOR]

This study refines a single-layer Feed-Forward Neural Network (FFNN) for the treatment of textile dye wastewater, concentrating on percentage decolorization (%DEC) and percentage chemical oxygen demand (%COD) reduction. The optimized neural network configuration comprises four input and one output neuron, fine-tuned based on the mean squared error (MSE). The training phase demonstrates a consistent MSE decline, reaching its lowest at epoch 209 for %DEC and epoch 34 for %COD, with corresponding MSEs of 1.799 × 10-5 and 1.4 × 10-3, respectively. The maximum absolute errors for %DEC and %COD were found to be 4.0787 and 2.4486, while the mean absolute errors were 0.4821 and 0.7256, respectively. In contrast to second-degree polynomial regression, the FFNN model exhibits enhanced predictive accuracy, as indicated by higher R² values of 0.99363 for %DEC and 0.99716 for %COD, and reduced error metrics. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore what are the determinant influencing factors of the dilemma faced by state‐owned enterprises (SOEs) in implementing innovation‐driven development strategy (IDDS), to propose a suitable localized theory. It also suggests specific actions to break the post‐effects dilemma with the support of this theory. Based on the innovation‐driven survey data of provincial SOEs in Gansu Province, this study adopts grounded theory to conduct exploratory research. This paper constructs a behavior process model of "pre‐motivation, innovation path, and post‐effects dilemma" to drive SOE's innovation and expounds on the incidence relation among the three. The results show that the external administrative force and institutional mechanism drive have both indirect and direct impacts on the innovation path choice of SOEs. The endogenous drive is distorted by external administrative force and institutional mechanism drive, leading to the limited innovation path choice and post‐effects dilemma. This paper puts forward the theory of "Attribute Imbalance–Weakened Autonomy–Sluggish Innovation" and explains why it is sometimes difficult to implement the IDDS of SOEs. However, there are some regional limitations in the application scenarios of the theory. Whether it has broader implications need to further explore. Future theoretical testing should be conducted with a sample of SOEs in developed market regions. It is possible to study the differences in the degree of government intervention in SOEs, the ways of intervention, and the impact of these differences on SOEs' balancing dual attribute conflicts. [ABSTRACT FROM AUTHOR]

Suppose C is any nonempty subset of a Banach space X. A mapping T : C → C is said to satisfy condition (Bγ,μ) if there exists μ ∈ [0, 1] and μ ∈ [0, 1/2 ] with 2μ ≤ γ such that for each two elements x, y ∈ C, γ||x - Tx|| ≤ ||x - y|| + μ||y - Ty|| implies ||Tx - Ty|| ≤ (1 - γ)||x - y|| + μ(||x - Ty|| + ||y - Tx||). In this research, we suggest some convergence results for these mappings under a up-to-date iterative process in a Banach space setting. Our results are new and improve some known results of the literature. [ABSTRACT FROM AUTHOR]

The main aim of this analysis is to determine the contribution of exports of communication technology, goods and services, food, and manufacturing exports and foreign investments to economic growth in Pakistan by utilizing time series data from 1976 to 2019. NARDL (non-linear autoregressive distributed lag) technique is utilized to encounter the linkages of variables via positive and negative shocks both in the long run and in the short run. The examined result of the short run indicates that the export of communication technology has a productive and adversative linkage to economic progress during positive and negative shocks. On the other side, exports of goods and services and food exports have a negative relationship with economic growth. Similarly, foreign investment exposed the constructive and negative linkage to economic growth during positive and negative shocks. Furthermore, manufacturing exports exposed an adversative and productive association to economic development in Pakistan. Moving toward the long-run analysis's results which show communication technology has constructive and adversative linkages to economic growth. Exports of goods and services and food exports also uncovered the adversative association to economic development in Pakistan. The foreign investment positive and negative shocks show adversative and productive linkages to economic growth. Furthermore, the variable manufacturing exports exposed a negative relation with economic growth in Pakistan in both positive and negative shocks. Based on the examined results, it is recommended that government policy experts must adopt new steps to boost exports to support the country's economic growth. [ABSTRACT FROM AUTHOR]

Climate change represents a grave challenge to the global economy, environment, and societal well-being, jeopardizing their long-term sustainability. In response to this urgent issue, the study emphasizes the significance of environmental policy and energy transitions as fundamental factors in addressing the climate change crisis. The research draws upon data from OECD countries spanning the period between 1990 and 2020, utilizing robust econometric techniques to assess data properties. The study utilizes a comprehensive CS-ARDL model, incorporating multiple control variables like non-renewable energy GDP, foreign direct investment (FDI), and research and development (R&D). The results show that environmental policy and energy transitions are effective in reducing climate change impacts in the form of CO2 emissions. The non-environmental factors like GDP and FDI are positively associated and thereby accelerate climate change processes, whereas R&D promotes environmental protection by reducing CO2 emissions. Based on these findings, the study advocates for the implementation of rigorous policy measures by OECD economies to strengthen and enforce environmental policies to ensure compliance and foster sustainable practices across sectors. The study also suggests that OECD must promote energy transitions by investing in renewable energy sources at the mass level (micro and macro) and phasing out reliance on non-renewable energy. [ABSTRACT FROM AUTHOR]

Climate change issues present substantial obstacles to the global community's stability and humanity's overall welfare. Reducing carbon emissions is crucial in attaining environmental sustainability and addressing the consequences of SDG 13 (climate actions). The G7 nations, representing some of the largest economies globally and significantly contributing to global carbon emissions, have achieved certain advancements in mitigating their carbon footprint. Nevertheless, the attainment of carbon neutrality continues to pose a substantial obstacle. This study examines the mechanisms leading to environmental sustainability in G7 economies, explicitly emphasizing the contribution of research and development (R&D) toward attaining carbon neutrality. The present study utilizes G7 data from 1990 to 2020 to conduct an empirical analysis employing a cross-sectional autoregressive distributed lag (CSARDL) panel model. The primary objective of this investigation is to examine the influence of R&D expenditure (R&DE) on carbon emissions metric ton (CO2Mt). Furthermore, this study investigates the current state of the EKC in the economies of the G7 nations, as well as the influence of renewable energy (RE) and non-renewable energy (NRE) on CO2Mt. The results suggest that R&DE is critical in mitigating CO2Mt and attaining carbon neutrality. The study also validates the EKC implies a negative and non-linear relationship between growth and CO2Mt. Moreover, renewable and non-renewable energy validate their respective negative and positive effects on CO2Mt. The findings of our study offer valuable insights for policymakers in the G7 nations, aiding them in developing effective regulatory measures for achieving carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Employees' negative outcomes have continued to be the logical position emphasized by service-oriented organizations that 'the customer is always right' and organizational policies that require employees to make customers happy, even in situations involving a customer's uncivil behavior. The current study builds and evaluates a research model that analyzes the associations among customer incivility, employees' emotional exhaustion, employees' intentions to quit the workplace, and employees' satisfaction at the workplace using the conservation of resources theory. Employees from four- and five-star hotels in Pakistan. The data shows that customers' incivility boosts employees' emotional exhaustion and employees' intentions to quit the workplace, but intentions have no effect on employees' satisfaction at the workplace when using structural equation modeling. The results show that employees' emotional exhaustion slightly mediates customers' incivility influence on employees' intentions to quit the workplace while totally mediating customers' incivility effect on employees' satisfaction at the workplace. The findings' implications, limitations, and future directions are examined. [ABSTRACT FROM AUTHOR]

The main purpose of this work is to connect the recently introduced iterative approximation scheme known as K F -iterative scheme with the class of generalized (α , β) -nonexpansive mappings. We consider the setting of a Banach space to prove our weak and strong convergence results. Once again, we prove that the class of (α , β) -nonexpansive mapping includes properly the classes of Suzuki nonexpansive, generalized α -nonexpansive and as well Reich–Suzuki type nonexpansive mappings by providing a numerical example. Eventually, we prove that K F -iterative scheme of this example is essentially more efficient than the other well-known iterative scheme of the literature. The presented work is new and extends some other well-known results in the iterations theory. [ABSTRACT FROM AUTHOR]

Public demand for environmental protection and environmental governance has a profound impact on enterprises' innovation behavior. Based on the panel data of 30 provinces in China from 2001 to 2018, this study uses a unit root to co-integration approach and the Panel Data Vector Autoregression model to empirically test the two-way dynamic relationship among green technology innovation, public environmental demands, and government environmental governance. The results show that both public environmental demands and environmental governance stimulate enterprises' green technology innovation; the estimated coefficient of government environmental governance and public environmental demands is 0.6681 and 0.0337, respectively. The incentive effect of environmental governance was more significant than that of public demands. Public environmental demands and green technology innovation have a bidirectional link, while environmental governance and green technology innovation share a two-way causality; meanwhile, environmental governance and public environmental demands share a unidirectional causal link. This study uses Impulse Response Function and Variance Decomposition to validate the outcomes, which shows that environmental governance's positive effect is more direct, while the effect of public demand has a time-lag impact, and the relationship among the three main variables is stable after the tenth period. The largest contribution to green technology innovation is environmental governance, with an explanation degree of 22.01%, followed by institutional quality (13.30%), and then public environmental demands (4.8%). These conclusions are not only significant for China to deal with the relationship among the public, government, and enterprises in the process of environmental governance, but also a valuable reference for other countries. [ABSTRACT FROM AUTHOR]

This study analysed data from a panel consisting of 32 O.E.C.D. member countries for the years 1996–2020. This research explores the nexus between CO2 emissions, G.D.P. per capita, renewable energy supply, the development of patents, and gross fixed capital formation in the context of 32 O.E.C.D. countries. Also, the panel quantile regression technique is being used to investigate potential variations in heterogeneity and asymmetry. The empirical evidence shows that technological innovation negatively impacts CO2 emissions; however, the impact varies greatly between quantiles. This research also explores the potential for heterogeneity and asymmetry in the moderating effect of technological innovation with regards to economic growth and renewable energy. The investigation, which relied on the use of panel quantile regression, revealed that technological innovation exerts a wide variety of moderating effects. In conclusion, the study provided policy recommendations. [ABSTRACT FROM AUTHOR]

This work proposes a new scheme under the umbrella of iteration methods to compute the sign of an invertible matrix. To this target, a review of the exiting solvers of the same type is given and then a new scheme is derived based on a multi-step Newton-type nonlinear equation solver. It is shown that the new method and its reciprocal converge globally with wider convergence radii in contrast to their competitors of the same order from the general Padé schemes. After investigation on the theoretical parts, numerical experiments based on complex matrices of various sizes are furnished to reveal the superiority of the proposed solver in terms of elapsed CPU time. [ABSTRACT FROM AUTHOR]

The study used an asymmetric ARDL model to analyse the asymmetric (positive and negative shocks) impact of foreign direct investment, personal remittances, total reserves, gross savings, and information and communication technology on economic growth in Pakistan from 1976 to 2019. The short-run and long-run results of the asymmetric autoregressive distributed lag approach show that total reserves have a negative and non-significant influence on Pakistan's economic growth. Similarly, the results of asymmetric ARDL show that positive shocks in personal remittances have a positive and significant influence on Pakistan's economic growth, but negative shocks have a negative and non-significant impact in both the long-run and short-run. The findings of the gross savings show that a positive shock has a favourable and non-significant impact on economic growth in both the long-run and short-run. The investigated outcomes of foreign direct investment show that positive shocks have a detrimental and considerable impact on the economy of Pakistan in both the long-run and short-run. Furthermore, information and communication technology has a negative impact on economic growth in both the long-run and short-run. The government of Pakistan may adopt better policies to build the country's infrastructure by employing foreign investment more effectively. [ABSTRACT FROM AUTHOR]

Government investment in environmental protection (Govin) plays a key role in stimulating private green investment (Prinv) to preserve the ecological environment with economic profits. To examine the effect of Govin on Prinv, this study uses data from 2010 to 2020 on green A-listed companies in China and estimates a dynamic panel model by using both the difference generalized method of moments and system generalized method of moments. The results indicate that Govin has a crowding-in effect on Prinv, and this conclusion is confirmed by several robustness tests. Furthermore, we identify revenues as a potential mechanism variable to explain how Govin affects Prinv. In addition, this study finds regional and enterprise ownership differences in the crowding in effect of Chinese Govin. Finally, based on these outcomes, the study suggests that the government should rationally and dynamically adjust the contents of public environmental investment and optimise its structure to effectively promote the development of green, low-carbon, and circular economies. [ABSTRACT FROM AUTHOR]

The stable growth of an economy is based on the coordination between environmental protection and economic development. Environmental regulation may affect energy efficiency because of its function of correcting energy consumption externalities. This paper uses the SBM model and Tobit model to explore the impact on and pathways of environmental regulations of energy efficiency in 30 provincial-level administrative regions in China and explains temporal and regional heterogeneity. The findings suggested that the environmental regulation in all provinces is continuously strengthened and the energy efficiency in eastern China is relatively higher. There is a positive effect of environmental regulation on energy efficiency and there is a temporal and spatial heterogeneity. Environmental regulation affects energy efficiency through green technology innovation, industrial structure upgrading, energy structure transformation and other transmission paths, and its influence mechanism on energy efficiency also has regional heterogeneity. The policy suggestions are: further enhance the intensity of environmental regulation, refine supporting safeguards and implement differentiated environmental regulation measures. [ABSTRACT FROM AUTHOR]

This study investigates the effects of military expenditure, final consumption expenditure, gross national expenditure, net income, broad money, and total reserves on Pakistan's economic growth. The nonlinear autoregressive distributed lag (NARDL) and robust regressions methods are used to examine the relationship among variables. The outcomes revealed that total reserves positively impacted the economic growth during positive and negative short- and long-run shocks. Final consumption expenditure and gross national expenditure negatively influenced the economic growth. Similarly, military expenditure and net income positively and negatively impacted the economic growth, while broad money has adverse and positive relation to economic growth. The results of the robust least squares and stepwise least squares approaches showed that all variables except military expenditure and reserves have positive impact on economic development. This study suggests that government should carefully monitor defence-related investment to maintain economic development. [ABSTRACT FROM AUTHOR]

This study employed fixed effects (FE) models, difference-in-differences (DID) methods, and mediating effect (ME) models to explore the total effect, structural effect, heterogeneous characteristics, and impact mechanism of digital inclusive finance (DIF) on green technology innovation (GTI) from 2011 to 2020. We derived the following results. First, DIF can significantly improve the level of GTI, and the positive role of internet digital inclusive finance is greater than that of traditional banks, but the three dimensions of the DIF index have different impacts on such innovation. Second, the impact of DIF on GTI has a "siphon effect," which is significantly promoted in regions with stronger economic power and inhibited in those with weaker economic power. Finally, there is an influence mechanism of "digital inclusive finance → financing constraints → green technology innovation." Our findings provide evidence to establish a lasting effect mechanism for DIF to promote GTI, and they have important reference value for other countries to develop DIF. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the durability of metallic coating for firefighter protective clothing when subjected to different washing cycles. Firefighter clothing ensemble consists of three layers, i.e. outer shell, moisture barrier, and thermal liner. The exposed surface of the outer shell was coated with silver particles through the physical vapor deposition process also called Magnetron sputtering. Afterwards, these specimens were exposed to radiant heat transmission machine at 30 kW/m2 and 40 kW/m2, respectively. It was found that specimens coated with silver particles showed improved thermal protective performance as compared to uncoated specimens. Later on, silver-coated specimens undergo five cycles of washing and their thermal protective performance in terms of transmitted heat flux density Qc (kW/m2) and radiant heat transmission index (RHTI 24 and RHTI 12) was measured. It was found that after five washing cycles, there was a negligible decline in thermal protective performance when exposed to 40 kW/m2. Afterwards, bending moment and water vapor resistance properties were measured before and after five washing cycles. It was inferred that there was no considerable difference in bending moment and water vapor resistance after different washing cycles, which confirmed stability of silver coating layers. However, when silver-coated outer shells were evaluated for abrasion resistance, there was a substantial decline in thermal protective performance on exposure to 40 kW/m2 after one hundred to five hundred cycles of abrasion. [ABSTRACT FROM AUTHOR]

Promoting the green development of resource-based cities is an essential way to achieve sustainable regional economic development. Based on 2009–2019 panel data of the Yellow River Basin cities, this study adopts the super-directional distance function model to measure the green development efficiency of these selected cities. Furthermore, based on the Malmquist-Luenberger index, this paper focuses on the dynamic change trend of green development efficiency and internal driving factors. Furthermore, the Tobit model is used to specifically explore the influencing factors affecting the green development of cities. The findings suggested that the green development efficiency of selected cities falls in the middle to high range and that the efficiency varies among all cities in the Yellow River Basin. Likewise, technical efficiency improvements and technological progress drive development efficiency, and the former contributes more to green development. However, financial development, energy structure adjustments, and environmental regulation can strongly contribute to the green development of cities, and each influencing factor has obvious temporal and regional differences. This paper proposes appropriate policy suggestions to promote the coordinated development of the economic development and environmental protection of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

China seems ambitious to achieve a "carbon emissions peak" before 2030 and "carbon neutrality" before 2060. To deal with this emissions mitigation plan, technology innovations are regarded as a crucial factor. However, considering its rebound effect (CO2 emissions driving effect) through economic growth, technology innovations might not prove a promising contributor to CO2 reduction. Therefore, there is a need to investigate further the nexus between technology innovations and CO2 emissions for conclusive debate. Based on the data of 215 cities in China, this paper uses mediating effects model to investigate the direct and indirect impacts (through economic growth and industrial structure transformation) of technology innovations on CO2 emissions from a microeconomic perspective. The main results suggest that technology innovations generally increase CO2 emissions in China both directly and indirectly. The impact of technology innovations and economic growth on CO2 emissions indicated the EKC characteristics. Furthermore, the contributions of technology innovations to CO2 emissions are distinguished in different regions. Thus, there is an urgent need for China to promote innovations in "clean technology" and to transform industrial structure to the tertiary industry to achieve the targets of carbon neutrality and emissions peaking. [ABSTRACT FROM AUTHOR]

We consider the class of generalized α-nonexpansive mappings in a setting of Banach spaces. We prove existence of fixed point and convergence results for these mappings under the K∗-iterative process. The weak convergence is obtained with the help of Opial's property while strong convergence results are obtained under various assumptions. Finally, we construct two numerical examples and connect our K∗-iterative process with them. An application to solve a fractional differential equation (FDE) is also provided. It has been eventually shown that the K∗- iterative process of this example gives more accurate numerical results corresponding to some other iterative processes of the literature. The main outcome is new and improves some known results of the literature. [ABSTRACT FROM AUTHOR]

Among all other leading challenges of this century, climate change affects people's livelihoods, particularly those residing in rural areas. This study is the first attempt to assess the Long-run (LR) and Short-run (SR) impacts of climatic factors, namely CO2 emissions, temperature, and precipitation on maize production in Nepal from 1983 to 2016, with the incorporation of cultivated area, fertilizers use, and credit supply as important input factors of maize production. To analyze the time-series dataset, we applied the Autoregressive distributed lag (ARDL), Vector error correction model (VECM), Impulse response function (IRF), and Variance decomposition (VD) methodologies. The results reveal that CO2 emissions and temperature decreased maize production in the short- and long-run while precipitation improved maize production in both cases. Also, cultivated area and fertilizers use significantly contributed to maize production in both periods. The results of the VECM causality indicate that rainfall and cultivated area have two-way causal associations with maize production. The CO2 emissions and credit represent unidirectional causality with maize production in the short-run. Besides, all variables share a significant long-run connection. Finally, the IRF and VD outcomes suggested that the effects of climatic and non-climatic factors are consistent on maize production. The policies recommend that better environmental quality is crucial for sustainable maize production in Nepal. [ABSTRACT FROM AUTHOR]

This paper examines the impact of climate variables and financial development on agricultural value-added and cereal production in selected Southeast Asian economies from 1970 to 2016. The current research applies second-generation advanced techniques to accomplish robust and reliable outcomes. The findings from the FM-OLS estimation disclose that climatic factors, for instance, CO2e and average temperature, impact both agricultural value-added and cereal production negatively, and financial development has an inverted U-shaped influence on both agricultural value-added and cereal production. Meanwhile, other important factors, including cropped area, income level, and rural labor force, significantly improve agricultural value-added and cereal production. Furthermore, the FM-OLS estimator's D-H panel causality test outcomes are reliable. The findings of our study reveal that both the short- and long-run risks of climatic changes to the agricultural sector pose a large-scale threat to food security in Southeast Asian economies. As a result, a robust and stable financial development in terms of governance of climate change finance in the agriculture sector must be achieved to enhance farmers' ability to adapt to current and future climate change adverse impacts. [ABSTRACT FROM AUTHOR]

This study is the first effort to assess the long-term effects of change in climate on crop production in South Asian countries from 1991 to 2016 by employing the second-generation methods robust to cross-sectional dependence and slope heterogeneity. Using panel data with the panel dynamic least squares (PD-LS) method and several co-integration approaches, this study confirmed a long-term co-integration among considered variables. The long-run estimates revealed that climatic variables, including temperature and CO2 emissions, negatively affected crop production, suggesting that a 1% increase in temperature and CO2 emissions reduces crop production by 1.93% and 0.32%, respectively. Conversely, precipitation positively affects crop production in the long-run, indicating that a 1% surge in precipitation increases crop production by 0.52%. Moreover, non-climatic variables including cultivated area, income level, and financial development positively affected crop production in the long-run. Furthermore, a 1% surge in cultivated area, income level, and financial development enhances crop production by 0.29%, 0.13%, and 0.04%, respectively. The outcomes of the Dumitrescu-Hurlin causality test confirmed that the causal link among all variables is significant, and outcomes verify the previous findings. This study suggests that urgent attention should be given to various adaptation strategies, such as credit supply, cropped area expansion, irrigation infrastructure enhancement, and the introduction of improved kinds of major food crops to enhance agricultural productivity. Besides, agricultural extension authorities should provide information about climate change to farming communities to deal with the adverse impacts of sudden climate changes on productivity. [ABSTRACT FROM AUTHOR]

The economic growth of developing countries has been associated with their exports, and the existing research suggests that exchange rates significantly influence the exports. This study used panel data to investigate the potential nexus of gross domestic product (GDP), exports and exchange rates in Asian countries over the period of 1981–2016. The results portray that nexus between exchange rate and exports holds true for Export-led Growth (ELG) and Growth-led Exports (GLE) hypotheses. This study used the Wald test under Vector Error Correction Model (VECM) with all necessary specifications tests to identify the possible nexus of variables, and applied the fixed effects model along with control variables. The results imply that an undervalued currency enhances exports and has a significant impact on economic growth. Additionally, the results of Fully Modified Ordinary Least Squares (FMOLS) model with financial crises dummy suggested that the estimations are robust. Keeping in view the aforementioned findings, a timely and balanced policy can play a pivotal role in improving the long term nexus of exchange rates, exports and economic growth. [ABSTRACT FROM AUTHOR]

This research work aims at modeling the sewing thread consumption for stitch class 301 through image analysis by using Fourier series. A mathematical model was developed by using the geometry of stitch class 301 for calculating sewing thread consumption. The modeling of stitch class 301 was conducted by changing the stitch density and thickness of the stitched fabric. The stitch density was adjusted by varying the stitch length (2, 3 and 4 mm) and the thickness of stitched fabric (2, 3 and 4 plies of fabric).The interlacement of sewing thread between the needle and bobbin was used for the measurement of arc length of one stitch. The total consumption of sewing thread was determined by multiplying the arc length by 4. The developed model was verified by using nine different stitched samples for comparing the predicted and measured values of sewing thread consumption. This model predicted the sewing thread consumption with 95% accuracy. Error percentages were also calculated for determining the major influencing factors that affected the sewing thread consumption. The proposed model can effectively be employed in garment industries for determining sewing thread consumption. [ABSTRACT FROM AUTHOR]

This study is the first attempt to examine the effects of changing climate and financial development on rice cultivation in the context of agrarian economy like Thailand from 1969 to 2016. The current study also uses other important variables, such as cultivated area, organic fertilizers usage, and rural labor to determine the long-term connection amid variables. In this study, we applied several econometric techniques, for instance the autoregressive distributive lag–error correction model (ARDL–ECM), vector error correction model (VECM), impulse response functions (IMFs), and variance decomposition (VARD) method to estimate the most reliable and robust outcomes. The empirical results showed that in the long- and short-run, there is a reduction in rice cultivation as temperature increase. The carbon dioxide (CO2) positively affects rice cultivation in the long-run, while this association is negative in the short-run. The findings further revealed that in the long- and short-run, domestic credit provided by the financial sector significantly positive improved rice cultivation, while domestic credit to private sector by banks negatively affects rice cultivation. The important input factors, including cultivated area, organic fertilizers usage, and rural labor significantly positive contributed toward rice cultivation in the long- and short-run. The calculated long-run causal connection of all the studied variables with rice cultivation is validated. The estimated short-run causal relationship is unidirectional among temperature, CO2 emissions, financial development, rural labor, and rice cultivation. In addition, our outcomes are robust and also verified by IMFs and VARD method. The study offers some important policy suggestions to increase rice production with the help of sound and well-developed financial systems and climate controls. [ABSTRACT FROM AUTHOR]

Population growth, food shortages, and low levels of human development have been longstanding issues confronting many African countries. Agricultural productivity remains a critical goal for mitigating these challenges and ensuring overall economic development. Total factor productivity (TFP) is a crucial metric for determining a sector's overall growth. However, due to a lack of comprehensive assessments of the trends and determinants of TFP growth in African agriculture, there are disagreements. Within the context of inclusive human development, the impact of agricultural productivity is frequently misrepresented in the current literature. This paper estimated TFP growth and assessed its impact on human development in Africa. Due to technological improvement, TFP increased moderately at a 5.4% growth rate across African countries over the period (2001–2019). Empirical evidence indicates that TFP growth enhances human development in the long run, but the effect varies according to levels of human development (HDI) and the nature of growth over time. For instance, higher levels of human development tend to mitigate the impact of TFP. Further analysis revealed that technical efficiency improvement is critical for enhancing food safety and human development. Policy recommendations for improving TFP for food security and human development in Africa are provided. Further investigation into agricultural TFP's impact beyond the poverty measure in Africa is encouraged. [ABSTRACT FROM AUTHOR]

Agriculture plays an integral part in facilitating socioeconomic development in Nepal. However, it is also associated with environmental concerns which need to be controlled for the sake of ensuring environmental and agricultural sustainability in tandem. Against this backdrop, this current study aims to check whether shocks to the levels of agricultural productivity, land utilization for crop production, and fertilizer consumption influence the carbon dioxide emission figures of Nepal over the 1965-2018 period. The long-run associations between these variables are confirmed from the cointegration analysis. Besides, the outcomes from the asymmetric non-linear autoregressive distributed lag regression analysis show that crop productivity does not influence the emission levels in Nepal. However, a decline in the land area used for crop production purposes is evidenced to trigger higher emissions of carbon dioxide both in the short- and long run. On the other hand, higher fertilizer consumption is found to boost the short- and long-run carbon dioxide emission levels in Nepal. Accordingly, considering the objective of reducing agriculture-based emissions, this study recommends the Nepalese government to adopt policies that can enhance the productivity of low energy-intensive crop production, stimulate green agriculture and non-agriculture activities, and minimize the use of chemical fertilizers in arable lands. [ABSTRACT FROM AUTHOR]

Isatin-core-containing ligands were synthesized by reacting an equimolar ratio of isatin with ethanolamine and anthranilic acid, respectively. The ligands were characterized by using FT‐IR, UV–Vis, 1H-NMR, ESIMS and elemental analysis. The synthesized ligands were further complexed with transition metal ions in a 1:2 molar ratio. Metal complexes were also characterized by physical, analytical and spectral methods in addition to molar conductance and magnetic moment measurements. The DFT calculations at B3LYP/6–311 + + G(d,p) level were accomplished for comparative study of isatin-based compounds. A good agreement among experimental UV–Vis, FT-IR and corresponding DFT results was found, which confirmed the purity of the studied compounds. The antimicrobial profile of all the compounds was evaluated by testing their antibacterial activity against two species of Gram-positive bacteria (Staphylococcus aureus, Streptococcus pyogenes) and two species of Gram-negative bacteria (Pseudomonas syringae, Escherichia coli) and antifungal activity against three species of fungi (Aspergillus niger, Rhizopus stolonifer and Trichoderma spirale) using the disk diffusion method. Moreover, the compounds were also investigated for antioxidant activity using phosphomolybdate and DPPH assays. The ligands revealed moderate activity against targets, which increased further upon complexation with different metal ions due to the chelation process. In addition, ANOVA and Tukey test for the experimental results of biological activities for all the prepared compounds supported the significant difference in all preclinical treatments' performance. The results showed that the isatin metal-based compounds are potent for being active as antimicrobial and antioxidant prototypes. [ABSTRACT FROM AUTHOR]

Since the open economy macroeconomic indicators such as the balance of trade and exchange rate interact with the economic and environmental indicators, it is worthy of delving into their interactive linkages. This study investigates the long-run and short-run dynamic interactive links among the balance of trade, aggregate economic output, real exchange rate, and carbon dioxide (CO2) emissions in Pakistan. Bayer and Hanck's combined cointegration and the auto-regressive distributed lag method are applied on annual time-series data from 1970 through 2018. The key findings are: (1) Balance of trade and real exchange rate imparted the CO2 emissions mitigation influence in both the long run and the short run. In contrast, the aggregate economic output exhibited the CO2 emissions driving influence in the long run and short run. (2) Balance of trade and real exchange rate induced enhancing and impeding influence on aggregate economic output, respectively, in the short run. However, they exposed the aggregate economic output strengthening influence in the long run. Besides, CO2 emissions produced a neutral influence on the aggregate economic output in the short run, whereas it put forward the aggregate economic output hampering influence in the long run. (3) Aggregate economic output revealed a balance of trade improvement influence for both the long run and short run. Nevertheless, the real exchange rate showed the balance of trade deterioration (improvement) influence in the short run (long run), confirming the J-curve hypothesis in Pakistan. Furthermore, (a) a bidirectional causality existed between CO2 emissions and aggregate economic output, and balance of trade and aggregate economic output. (b) A unidirectional causality existed from real exchange rate to balance of trade and aggregate economic output, and from the balance of trade and real exchange rate to CO2 emissions. The diversification of exports and energy mix is recommended to improve the balance of trade, economic aggregates, and environmental sustainability. [ABSTRACT FROM AUTHOR]

In the current study, the effects of fluidic parameters with entropy generation properties on velocity, temperature, and entropy numbers of non‐Newtonian fluid flowing through the porous channel are investigated. The complex system of fluid equations is handled with analytically and numerically. The first‐order perturbation expansion is employed on both velocity and temperature to obtain the approximate analytical solution. A comparison of the analytical solution is made with numerical results that are obtained by discretizing the system of boundary value problems. The pseudo‐spectral collocation method was used for the discretization, and the Newton method was to get the solutions to the complex differential equations. In the Newton method, the finite difference approximation of Jacobian is utilized. The pseudo‐spectral solutions are in good agreement with the analytical findings. The order of accuracy in temperature and velocity profiles is of order 10−6 which will be compared in the future with the experimental results of given non‐Newtonian fluid. [ABSTRACT FROM AUTHOR]

Governments worldwide have introduced various tax mechanisms to foster enterprise innovation, which in turn affect enterprise performance. To promote the innovation level of domestic enterprises, China has adopted an innovation-driven strategy policy. Based on China's manufacturing company data from 2007 to 2017, this article constructs a mediating effect model to study the direct effect of tax incentives and government subsidies on enterprise performance and the mediating effect of innovation on enterprise performance. We use RIF regression to investigate the difference between the effect of industrial subsidies on promoting technological innovation and enterprise performance. The study finds that tax incentives and government subsidies encourage enterprise performance through innovation, with the mediating effect accounting for about 34.5% and 16.8%, respectively. Industrial subsidies play a more obvious role in improving the innovation performance of high-tech enterprises. There is no significant difference in tax incentives on the performance of large enterprises and small and medium-sized enterprises. Moreover, government subsidies play an essential role in promoting the performance of large enterprises. Furthermore, with the increase in quantile, the impact of tax incentives and government subsidies on innovation is getting more extensive and more significant. Innovation has an increasing effect on enterprise performance, the effects of tax incentives on enterprise performance are becoming less and smaller, and the nexus of government subsidies and enterprise performance is generally unchanged. Therefore, implementing appropriate tax incentives and government subsidies for enterprise innovation is essential for improving enterprise performance, especially for high-tech enterprises. Enterprise size should not be used as a criterion for the government to implement tax incentives, although government subsidies tend to support large enterprises. [ABSTRACT FROM AUTHOR]

This paper reviews the long-term impact of public investments on irrigation and agricultural research and development along with other control variables, including physical capital, irrigated area, fertilizer consumption, level of mechanization, and CO2 emissions on China's agricultural output from 1986 to 2017. This study applied various econometric methods such as the ARDL bound-testing approach and Johansen co-integration procedure to determine the long-term co-integrating connection amid the variables. The empirical outcomes from the ARDL bound-testing method confirm a long-term co-integrating connection among the variables. The long-run results demonstrated that public investment in agricultural research and development and irrigation have a substantial positive effect on agricultural productivity. Furthermore, results revealed that physical capital and fertilizer consumption also have a significant positive effect on agricultural output; however, CO2 emissions have a substantial negative effect on agricultural production. These findings therefore suggest that the policy makers of China should initiate more effective policies to increase irrigation and agricultural research and development investments. Increasing irrigation and agricultural research and development investments will enhance agricultural productivity by ensuring food security in the country. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the impacts of climate change (CC), measured average annual rainfall, average annual temperature and carbon dioxide (CO2e) on cereal production (CPD) in Bangladesh by using the annual dataset from 1988–2014, with the incorporation of cereal cropped area (CCA), financial development (FD), energy consumption (EC) and rural labor force as important determinants of CPD. Design/methodology/approach: This study used an auto-regressive distributive lag (ARDL) model and several econometric approaches to validate the long- and short-term cointegration and the causality directions, respectively, of the scrutinized variables. Findings: Results of the bounds testing approach confirmed the stable long-term connections among the underlying variables. The estimates of the ARDL model indicated that rainfall improves CPD in the short-and long-term. However, CO2e has a significantly negative impact on CPD both in the short-and long-term. Results further showed that temperature has an adverse effect on CPD in the short-term. Among other determinants, CCA, FD and EC have significantly positive impacts on CPD in both cases. The outcomes of Granger causality indicated that a significant two-way causal association is running from all variables to CPD except temperature and rainfall. The connection between CPD and temperature is unidirectional, showing that CPD is influenced by temperature. All other variables also have a valid and significant causal link among each other. Additionally, the findings of variance decomposition suggest that results are robust, and all these factors have a significant influence on CPD in Bangladesh. Research limitations/implications: These findings have important policy implications for Bangladesh and other developing countries. For instance, introduce improved cereal crop varieties, increase CCA and familiarizes agricultural credits through formal institutions on relaxed conditions and on low-interest rates could reduce the CPD's vulnerability to climate shocks. Originality/value: To the best of the authors' knowledge, this study is the first attempt to examine the short- and long-term impacts of CC on CPD in Bangladesh over 1988–2014. The authors used various econometrics techniques, including the ARDL approach, the Granger causality test based on the vector error correction model framework and the variance decomposition method. [ABSTRACT FROM AUTHOR]

The underpinned study examines the effects of climatic and non-climatic factors on Indian agriculture, cereal production, and yield using the country-level time series data of 1965–2015. With the autoregressive distributed lag (ARDL) bounds testing approach, the long-term equilibrium association among the variables has been explored. The results reveal that climatic factors like CO2 emissions and temperature adversely affect agricultural output, while rainfall positively affects it. Likewise, non-climatic factors, including energy used, financial development, and labor force, affect agricultural production positively in the long run. The estimated long-run results further demonstrate that CO2 emissions and rainfall positively affect both cereal production and yield, while temperature adversely affects them. The results exhibit that the cereal cropped area, energy used, financial development, and labor force significantly and positively impact the long-run cereal production and yield. Finally, pairwise Granger causality test confirmed that both climatic and non-climatic factors are significantly influencing agriculture and cereal production in India. Based on these results, policymakers and governmental institutions should formulate coherent adaptation measures and mitigation policies to tackle the adverse climate change effects on agriculture and its production of cereals. [ABSTRACT FROM AUTHOR]

Introduction: Intestinal perforation is the serious complication of intestinal tuberculosis with high morbidity & mortality. Objectives: To determine the frequency of intestinal tuberculosis in patients of intestinal perforation presenting in Surgical Emergency, Bahawal Victoria Hospital, Bahawalpur. Study design: Descriptive, cross-sectional. Study duration: 1st November 2020 to 31st October 2021. Settings: Department of Surgery, Bahawal Victoria Hospital, Bahawalpur Material & Methods: A total of 106 patients with intestinal perforation of age 20-50 years and both genders were included. Patients with clinical features of duodenal perforation, intestinal perforation due to malignancy and traumatic perforation were excluded. Laparotomy was performed in all selected patients and tissue was sent to laboratory for histopathology. Clinical & laboratory findings of all patients were entered in pre-designed proforma in term of intestinal tuberculosis. Results: Mean age was 36.90±8.16 years. Majority of the patients 58(54.72%) were between 36 to 50 years of age. Out of the 106 patients, 69(65.09%) were male and 37(34.91%) were females with male to female ratio of 1.9:1. Frequency of intestinal tuberculosis in patients of intestinal perforation was found in 19 (17.92%) patients, whereas there was no intestinal tuberculosis in 87 (82.08%) patients. Conclusion: The study concluded that frequency of intestinal tuberculosis in patients of intestinal perforation is quite high in this region. [ABSTRACT FROM AUTHOR]

Pesticides are the leading defence against pests, but their unsafe use reciprocates the pesticide residues in highly susceptible food and is becoming a serious risk for human health. In this study, mint extract and riboflavin were tested as photosensitisers in combination with light irradiation of different frequencies, employed for various time intervals to improve the photo-degradation of deltamethrin (DM) and lambda cyhalothrin (λ-CHT) in cauliflower. Different source of light was studied, either in ultraviolet range (UV-C, 254 nm or UV-A, 320–380 nm) or sunlight simulator (> 380–800 nm). The degradation of the pesticides varied depending on the type of photosensitiser and light source. Photo-degradation of the DM and λ-CHT was enhanced by applying the mint extracts and riboflavin and a more significant degradation was achieved with UV-C than with either UV-A or sunlight, reaching a maximum decrement of the concentration by 67–76%. The light treatments did not significantly affect the in-vitro antioxidant activity of the natural antioxidants in cauliflower. A calculated dietary risk assessment revealed that obvious dietary health hazards of DM and λ-CHT pesticides when sprayed on cauliflower for pest control. The use of green chemical photosensitisers (mint extract and riboflavin) in combination with UV light irradiation represents a novel, sustainable, and safe approach to pesticide reduction in produce. [ABSTRACT FROM AUTHOR]

Since the development of the service sector and renewable energy reduce fossil-based energy consumption which mitigates CO2 emissions and this nexus provides a better understanding of the environmental sustainability. Considering the substantially increasing contribution of service sector and tremendous potential for renewable energy in ASEAN5 countries, leaning forward from ASEAN's energy and growth nexus, this study examines the impact of service sector contribution and renewable energy on the environmental quality of ASEAN5 using annual data from 1990 to 2018. The results of the fully modified ordinary least squared, dynamic ordinary least squared, and canonical co-integrating regressions depicted that the service sectors of Thailand, the Philippines, and Singapore augment CO2 emissions; however, the service sectors of Malaysia and Indonesia could reduce CO2 emissions. The increasing share of renewable energy can enhance environmental quality, but its magnitude varies in ASEAN5 economies; non-renewable energy, population, and economic development deteriorate the environment. Our results confirm the existence of environmental Kuznets curve in all the ASEAN5; the Gregory-Hansen test confirmed that results are robust. Finally, the Granger causality designated that economic development and non-renewable energy have a significant causal relationship with CO2 emission of ASEAN5 countries. These findings suggest that the ASEAN5 economies need to optimize their economic structure for promoting sustainable development in the long run. Graphical abstract [ABSTRACT FROM AUTHOR]

This paper numerically simulates the nanofluid flow over a thermally expanding Riga plate. Buongiorno model for nanofluid is employed to investigate the contribution of Brownian motion and thermophoretic force on the nanoflow. Magnetohydrodynamics (MHD) of viscous nanofluid through a porous medium is characterized with the help of Darcy–Forchheimer's model. In addition, the simultaneous effects of activation energy and chemical reaction have been incorporated. Moreover, highly nonlinear coupled differential equations are formulated which highlight the influence of viscous dissipation and heat generation. A numerical solution is achieved with the help of the Range–Kutta fourth-order (RK4) method combined with the shooting technique. Finally, the role of emerging parameters is studied via performing the numerical simulation which reveals that the momentum boundary layer of nanofluid shrinks due to the porous medium. Whereas, thermal boundary layer expands for all variables, except for the Prandtl number. Finally, mass transfer rated suffers due to Schmidt number. [ABSTRACT FROM AUTHOR]