Irum Shahzadi
58436813300
Publications - 13
Deep learning approach for automated hMPV classification
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
Human metapneumovirus (hMPV) is a significant cause of respiratory illness, particularly in children, elderly individuals, and immunocompromised patients. Despite its clinical relevance, hMPV poses diagnostic challenges due to its symptom similarity with other respiratory illnesses, such as influenza and respiratory syncytial virus (RSV), and the lack of specialized detection systems. Traditional diagnostic methods are often inadequate for providing rapid and accurate results, particularly in low-resource settings. This study proposes a novel deep learning framework, referred to as hMPV-Net, which leverages Convolutional Neural Networks (CNNs) to facilitate the precise detection and classification of hMPV infections. The CNN model is designed to perform binary classification by differentiating between hMPV-positive and hMPV-negative cases. To address the lack of real-world patient data, simulated image datasets were used for model training and evaluation, allowing the model to generalize to various clinical scenarios. A key challenge in developing this model is the imbalance within the dataset, where hMPV-positive cases are often underrepresented. To mitigate this, the framework incorporates advanced techniques such as data augmentation, weighted loss functions, and dropout regularization, which help to balance the dataset, improve model robustness, and enhance classification accuracy. These techniques are crucial in addressing issues such as overfitting and generalization, which are common when working with limited datasets in medical imaging tasks. The dataset used for model training and testing consists of 10,000 samples, with an equal distribution of hMPV-positive and hMPV-negative cases. Experimental results demonstrate that the hMPV-Net model achieves a high test accuracy of 91.8%, along with impressive test precision, recall, and F1-score values around 92%. These metrics indicate that the model performs exceptionally well in classifying both hMPV-positive and hMPV-negative cases. Furthermore, the model exhibits superior computational efficiency, requiring only 3.2 GFLOPs, which is significantly lower than other state-of-the-art models such as ResNet-50 and VGG-16. This reduction in computational cost makes the model suitable for deployment in resource-constrained healthcare environments, where computing power and infrastructure may be limited.
Open Access: Yes
From Agricultural and Forest Land Development to Urban Landscapes: Green Energy's Influence on Global Pollutant Emissions
Publication Name: Land Degradation and Development
Publication Date: 2025-08-15
Volume: 36
Issue: 13
Page Range: 4672-4690
Description:
There is a sharp inclination to use green energy sources such as solar, hydro, and nuclear energy to accomplish the COP29 targets and sustainability goals. The current study attempts to explore the role of green solar, hydro, and agriculture land use apropos global pollutant emissions. In doing so, the study examines the impacts of agricultural land use, forest area, and urbanization on global emissions. The study uses the global historical data from 1990Q1 to 2021Q4. The authors employ the diagnostic tests, autoregressive distributed lag models, and causality analysis for empirical analysis. The autoregressive distributed lag model's results mentioned that agricultural land and forestry also help improve environmental sustainability and urban landscape in the short and long run. In addition, the results find linear and nonlinear impacts of green solar and nuclear energy to mitigate the global carbon emission levels. The structural change policies of industrialization and urbanization remain the critical obstacles to attaining environmental sustainability. The on-hand research contributes to the ongoing challenges faced by global economies regarding green energy sources, agriculture land management and their criticality in attaining a sustainable environment by reducing carbon emissions. The research recommends further investments in green solar, agriculture land management, and incentivizing clean energy sources to achieve sustainable global development.
Open Access: Yes
DOI: 10.1002/ldr.5661
Do Land Resources, Agriculture Exports, and Agriculture Growth Induce Agriculture-Related Greenhouse Gas Emissions: Novel Findings in the Lens of COP–28
Publication Name: Land Degradation and Development
Publication Date: 2025-07-15
Volume: 36
Issue: 11
Page Range: 3858-3873
Description:
Globally, economies are highly concerned about the balance between climatic issues and attaining agricultural sustainability. However, empirical evidence regarding the nexus of agricultural sustainability, emissions, land use, and agricultural trade is scarce and requires appropriate policy-level attention. The current study examines the influence of land-use resources, agricultural exports, and foreign direct investment on agriculture-related greenhouse gas emissions in Brazil. Using various time series diagnostic measures on quarterly data from 1990Q1 to 2020Q4 reveals non-normality and a mixed order of stationarity in variables. The autoregressive distributed lag (ARDL) model and quantile ARDL approach are employed for comprehensive empirical analysis. The results assert that land resources and foreign investments are harmful to environmental sustainability, as they significantly enhance agricultural greenhouse gas emissions. Additionally, agricultural exports and green energy significantly contribute to emissions mitigation by tackling land-use and agricultural emissions in the short and long run. The results are robust across the ARDL and quantile regressions and pairwise granger causality. The study concludes that agricultural exports and land use are key factors inducing agricultural sustainability by inducing emissions. The study recommends increased spending on research and development, solar-based irrigation, and promotion of green energy projects. The study discusses novel findings and implications apropos land resources, foreign investments, agricultural exports, and emissions in the lens of COP 28.
Open Access: Yes
DOI: 10.1002/ldr.5604
How does intergenerational transmission affect green innovation? Evidence from Chinese family businesses
Publication Name: Structural Change and Economic Dynamics
Publication Date: 2025-06-01
Volume: 73
Issue: Unknown
Page Range: 158-169
Description:
Green innovation in family businesses is a significant yet underexplored area of research, particularly with regard to the influence of dynamic succession characteristics on intergenerational inheritance and its impact on innovation. This study, integrating the social-emotional wealth theory (SEW) and the agency theory, examines 505 Chinese listed family firms spanning from 2011 to 2020. Employing the Difference-in-Differences (DID) method, we investigate how intergenerational inheritance affects green innovation investment over time. Our findings reveal that initially, intergenerational transmission tends to inhibit green innovation investment in family businesses; however, this effect diminishes as the intergenerational process unfolds, indicative of the maturation of the second generation. Notably, we observe that a higher education level among second-generation heirs weakens the inhibitory effect of intergenerational inheritance on green innovation investment. This study addresses a gap in green innovation research by considering intergenerational transmission dynamics in family businesses, thus enhancing our understanding of innovation behaviors within this context. By synthesizing SEW and agency theory, this research offers novel insights into the varying impacts of intergenerational inheritance on firm innovation, shedding light on approaches to reconcile the willingness-ability paradox in family business innovation and promoting effective governance of succession processes.
Open Access: Yes
The impact of financial development and economic complexity on energy and carbon intensity: evidence of the top 10 complex countries
Publication Name: Energy Sources Part B Economics Planning and Policy
Publication Date: 2025-01-01
Volume: 20
Issue: 1
Page Range: Unknown
Description:
This paper explores the impact of economic complexity and financial development on energy efficiency through two indicators: energy intensity and carbon intensity, within the top 10 complex economies. Other control variables, such as economic growth, urbanization, and human capital, are also included in the models. Random and fixed-effects estimators with heteroskedasticity-consistent standard errors were used. Clustered random and fixed-effects estimators were considered to handle within-group (cluster) dependence. The study utilized the Driscoll-Kraay (DK) method to address non-spherical disturbances and ensure consistent standard errors and robustness against dependence. Feasible Generalized Least Squares (FGLS) considered entity-specific autocorrelation, and System Generalized Method of Moments (Sys-GMM) accommodated unobserved panel-level effects, were also employed. Our findings reveal that economic complexity is crucial in reducing carbon and energy intensity, highlighting the significance of fostering technological sectors to diversify and sophisticate the productive structure. However, the influence of financial development on these intensity measures remains ambiguous and necessitates further exploration. We propose policy implications aimed at boosting technological sectors, facilitating a green transition in the economy, and advancing the adoption of renewable energy technologies.
Open Access: Yes
Does import product diversification enhance energy demand in developed and developing economies? A policy-based analysis in the context of trade sustainability
Publication Name: Energy Sources Part B Economics Planning and Policy
Publication Date: 2025-01-01
Volume: 20
Issue: 1
Page Range: Unknown
Description:
Import product diversification is a major parameter in international trade. Import diversification contributes to economic growth and affects the environment due to its impact on energy consumption. In this article, we investigate the impact of import product diversification along with income, oil prices, natural resources, population, and foreign direct investment on energy demand, covering a composite sample of 102 developing and 36 developed economies over the period from 1995 to 2020. We also assess the impact of import diversification on energy demand considering all sub-samples. We find a significant long-run cointegration between total energy demand and import diversification for both developed and developing countries, confirmed by Pedroni cointegration tests. We further denote that import diversification together with other independent variables is stationary after the first differences in LLC unit root tests. Contrary to traditional methods, we apply panel quantile regression and conclude that import diversification, GDP, oil prices, foreign direct investment, natural resources, and population share long-run integration with total energy consumption for both developed and developing countries. The Dumitrescu and Hurlin short-run causality test confirms the existence of pair-wise bidirectional causality between all independent variables including import diversification, GDP, oil prices, natural resources, foreign investment, and population with energy demand. Our empirics conclude with important policy implications for sustainability.
Open Access: Yes
Is environmental information disclosure driving green energy development? Contextual evidence from Chinese city level data in the lens of sustainability
Publication Name: Renewable Energy
Publication Date: 2024-12-01
Volume: 237
Issue: Unknown
Page Range: Unknown
Description:
As an important supplement to mandatory environmental regulation, third-party participation in environmental regulation has become an important driving force for the comprehensive green transformation of economic and social development. Environmental information disclosure (EID) has become a widely used form of third-party participation ecological regulation, and the study of its impact on green energy development (GED) is receiving more and more academic attention. However, the research on this issue is still insufficient in academia. Based on resource-based theory and information processing theory, with IPE project of pollution information survey in China as an exogenous impact, this paper analyzes the causal impact of EID for GED using panel data of 285 Chinese cities from 2000 to 2020. The findings revealed that EID is a strong driver of GED in the long run, further amplified by the smart city pilot program. Besides, industrial structure transformation (IST), substantive green technological innovation (SGTI), non-substantive green technological innovation (NOSGTI), and green finance development (GFD) are important mediating mechanisms through which EID facilitates the GED. Concerning resource endowments of different regions and cities, the heterogeneity test asserted that the promotion effect of EID for GED is best in resource-based cities and old industrial parks. These results emphasize the importance of public participation in urban sustainable development and provide new ideas for promoting green growth.
Open Access: Yes
Do climate change policies, and environmental regulations affect the financial performance: policy-based analysis in context of green innovation
Publication Name: Environment Development and Sustainability
Publication Date: 2024-12-01
Volume: 26
Issue: 12
Page Range: 32137-32161
Description:
In these modern times, developed and developing economies use different means and strategies to attain economic growth and financial development. Still, environmental recovery instruments are not yet empirically explored in developed regions. The prime objective of this study is to unveil the nexus between electricity use, environmental policies, and financial development to report novel approaches through the lens of sustainable development. The present research examines the heterogeneous impacts of climate policies and ecological taxes on financial development. In doing so, the study has considered greener energy and institutional quality variables as policy factors for financial development. The authors employ the 29 OECD economies data from 1994 to 2020. This research gathered the data from authentic sources such as the OECD, the World Bank, and ICRG. The pre-estimation diagnostic (residual cross-section dependence, unit root, and cointegration) tests asserted cross-section dependence between countries, variables’ stationarity, and cointegration between the variables. Due to the asymmetrical behaviour of data shown by the Jarque and Bera (Int Stat Rev 55:163–172, 1987) test, this study uses non-parametric panel quantile regression. It asserts environmental policies and green electricity use have a substantial yet mixed influence on financial development. In contrast, trade openness and GDP are the significant factors of economic development in the region. Overall, Environmental taxes adversely affect financial development in developed countries across quantiles. This study suggests promoting and improving green investment, trade, and efficient environmental policies to encourage financial development in developed countries without affecting ecological quality.
Open Access: Yes
The dilemma of water, food, and greener energy nexus: A novel context of COP27 for G20 economies
Publication Name: Land Degradation and Development
Publication Date: 2024-05-30
Volume: 35
Issue: 9
Page Range: 2993-3006
Description:
In the contemporary world, achieving sustainable food production has become an urgent task for the international community and policymakers due to the rapidly growing social challenges of mankind. Sustainable food production practices aid countries in adapting to the challenges posed by climate change, thereby ensuring a better and more sustainable future for all. This study examines the impact of land use, energy efficiency (ENE), water productivity (WP), renewable energy consumption (REC), and gross domestic product (GDP) on sustainable food production in G20 nations over the period of 1998–2020. We use quantile regression approaches to capture potential heterogeneity across various food value-added distribution quantiles. The results show that arable land, WP, GDP, ENE, and REC are important factors affecting food value added in G20 nations. However, the nature of the relationship varies across different quantiles, suggesting heterogeneity in the relationships. The results show that ENE, renewable energies, and GDP are positively related to food production. However, arable land and WP are negatively related to food production. The findings can assist policymakers and stakeholders in making informed decisions to increase value added in the agricultural sector while promoting resilience and sustainability.
Open Access: Yes
DOI: 10.1002/ldr.5110
Nexus between climate change, agricultural output, fertilizer use, agriculture soil emissions: Novel implications in the context of environmental management
Publication Name: Journal of Cleaner Production
Publication Date: 2024-04-15
Volume: 450
Issue: Unknown
Page Range: Unknown
Description:
In evaluating the influence of greenhouse gases (GHGs) on climate change, the effectiveness of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) is intricately tied to their atmospheric turnover rates, which play a crucial role in their heat-trapping capacity. Understanding the dynamics of how these gases cycle through the atmosphere is essential for assessing their respective contributions to the greenhouse effect and, consequently, their impact on global warming and climate change. The prime objective of this research is to examine the role of climatic change, agriculture output, and fertilizer use on the agriculture soil's greenhouse gas emissions. In doing so, the present study has focused on the temperature of land, fertilizer consumption, crop and livestock production, and energy used in agriculture soils on the pollution level of agricultural soils. The study further delineates the intricate interdependencies between climate change factors and GHG emissions using novel econometric methodologies, specifically the PMG-ARDL, SC-ARDL, and Dumitrescu Hurlin Panel Causality frameworks. In doing so, we use a large panel dataset spanning 1990 to 2020. The estimations show that climate change, as measured by variations in terrestrial temperature, has a discernible and positive impact on GHG emissions over the short and long term. Energy consumption and livestock production positively correlate with GHG emissions, with the former having a more pronounced effect. The implications of fertilizer usage and overall crop yield become noticeably significant in the long term. It emphasizes the importance of using a diachronic perspective when assessing GHG emissions in the agricultural sector. It is also worth noting that agricultural land use appears to negatively impact GHG emissions, emphasizing the importance of implementing sustainable land management practices to mitigate adverse environmental consequences. The study also explores the causality between climate change, agricultural practices, and GHG emissions, revealing a bidirectional association between climatic change and soil emissions. Additionally, unidirectional causation is observed from fertilizer consumption and crop production to emissions, underscoring the importance of adopting sustainable agricultural practices to reduce emissions. The findings offer valuable insights for governments and researchers to create sustainability-related strategies for dealing with climate change issues, safeguarding natural resources, and ensuring a sustainable future for agriculture.
Open Access: Yes
From Over-Tourism to Under-Tourism via COVID-19: Lessons for Sustainable Tourism Management
Publication Name: Evaluation Review
Publication Date: 2024-02-01
Volume: 48
Issue: 1
Page Range: 177-210
Description:
With various strains of the novel coronavirus emerging during the last few years, there is a need to reinvent and manage the tourism industry by engaging various stakeholders. Industry and policymakers need to observe the shift and curate tourism-related products and offerings accordingly. In light of the increasing demand for innovations and future directions in the post-COVID-19 period, this article conducts a bibliometric analysis for sustainable tourism studies spanning the years 1990–2021. This paper presents an integrative review of tourism, environment and sustainable tourism to reveal geographical, contextual, and methodological directions for future research. The comprehensive analysis includes contributions on topics and methods, country collaborations, and thematic analysis. The findings are consistent with the Sustainable Development Goals of sustainable production and consumption (SDG-12), with a particular emphasis on sustainable tourism to promote local culture and create jobs (SDG-12.b) and on sustainable growth (SDG-13). The study’s findings can be used to inform future policies and directions; for example, the findings indicate that the hospitality industry is facing challenges that necessitate new regulations to address its socioeconomic and environmental impacts.
Open Access: Yes
Nexus Between Life Expectancy, Education, Governance, and Carbon Emissions: Contextual Evidence from Carbon Neutrality Dream of the USA
Publication Name: Journal of the Knowledge Economy
Publication Date: 2024-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
The purpose of this paper is to investigate the association between energy use, life expectancy, and governance related factors on the environmental quality of the USA. In this regard, the authors discuss the carbon neutrality target and sustainable development goals of the USA. For empirical analysis, the authors employ the US data for the period of 1996 to 2019. Using the Zivot-Andrews structural break unit root test, linear ARDL, and dynamic simulated ARDL, this study obtained the empirical results for diagnostic examination and long-run coefficients. The empirical findings explained how the education, life expectancy, and energy use induce the carbon emissions. Whereas, the instruments of governance have heterogenous impact on the environmental quality of the country. Based on the detailed empirical findings, the study draws the conclusions about the affirmative contributions to carbon emissions. The current research eventually suggests some energy related findings and implications to further reduce the environmental issues and to achieve neutrality targets of the USA.
Open Access: Yes
What do we learn from Nexus between trade diversification and structural change: informing the future about climate action and Sustainability
Publication Name: Environmental Science and Pollution Research
Publication Date: 2023-08-01
Volume: 30
Issue: 40
Page Range: 92162-92181
Description:
Economic complexity is considered key a driver of social change, structural change, and economic development. Economic complexity is mostly used to capture issues apropos product diversification of exports, trade, technological innovation, human knowledge, and skills. The current study has conducted a detailed bibliometric review of economic complexity, export quality, and trade diversification. In doing so, the authors used the literature up to 2021 to unveil economic complexity’s contextual information that witnessed structural change, social change, and trade indicators. The current study is the first integrative review to report the theoretical contribution, future research agendas, and thematic analysis of economic complexity, export quality, and export diversification. Our study, on the subject of economic complexity, export diversification, and import diversification in the period from 1966 to 2021, was carried out by systematically scanning 386 documents, and it is one of the pioneering studies in this field. In addition, economic diversity, development, and economic complexity; export diversification, import diversification, trade openness, and economic growth; energy, environmental Kuznets curve, and economic complexity; and sustainability and economic diversification are the four main research topics of the study. The findings are discussed apropos of economic complexity and exports, methodological aspects of economic complexity, and environmental issues nexus with economic complexity. The current study reports novel findings toward a path for achieving SDG-9 (industry and innovation) and SDG-13 (climate action). The biometric review enables researchers and policymakers to understand export quality, economic complexity, and the trade nexus and report future research directions for achieving sustainable growth in industries and innovation.
Open Access: Yes
