Geostatistical analysis for spatial distribution of anemia (Hb level) among women of reproductive age and determinant factors

The study was designed to assess the geostatistical spatial distribution of anemia and determinant factors among the women of reproductive age group (RAG) in Gilgit district, Pakistan. The Hb levels for 15-25 RAG, 26-35 RAG, and 36-45 group showed 10.22 g/dL, 10.41 g/dL, and 9.90 g/dL levels, respectively, while the Hb level showed a nugget/sill ratio of 0.21 inferring strong for the 15-25 group, weak for the 26-36, and moderate for 36-45 spatial dependence. Furthermore, 15-25 RAG showed 8% severe and 33.34% sufficient cases and 26-35 showed 12% severe and 29.33% sufficient results in their Hb level, whereas 36-45 had 9.34% severe and 29.33% sufficient.

Determinants of environmental quality in India: evidence using the bootstrapped ARDL model with structural breaks

This current study examines the impact of renewable energy consumption, agriculture, and globalization on carbon emissions in India over the period from 1980 to 2018. For long-run estimates, we apply Gregory-Hansen's co-integration test, bootstrap ARDL approaches, fully modified ordinary least squares, and dynamic OLS. The empirical results of long-run estimates indicate that a 1% increase in renewable energy consumption, agriculture, and economic globalization will increase carbon emissions by 0.764%, 1.675%, and 0.517%, respectively. Moreover, this study confirms the detrimental effect of these variables on carbon dioxide emissions. Economic globalization coefficients indicate that the scale effect is valid in India. The 2002 economic crisis slowed down the country's growth rate, which reduced the ecological pollution. Several policy recommendations are derived from the empirical findings.

Natural Resources Depletion, Financial Risk, and Human Well-Being: What is the Role of Green Innovation and Economic Globalization?

Human well-being is the top priority of all nations in the twenty-first century. However, depletion of natural resources and financial risk can negatively impact human well-being, which in turn can make it difficult to realize human well-being. Also, green innovation and economic globalization may play a significant role in human well-being. In this context, this study assesses the impacts of natural resources, financial risk, green innovation, and economic globalization on human well-being in emerging countries from 1990 to 2018. The empirical results from the Common Correlated Effects Mean Group estimator unveiled that natural resources and financial risk negatively affect the human well-being of emerging nations. Furthermore, the results show that green innovation and economic globalization positively contribute to human well-being. These findings are also verified using alternative methods. In addition, natural resources, financial risk, and economic globalization Granger cause human well-being but not the other way round. Furthermore, bidirectional causality exists between green innovation and human well-being. Considering these novel findings, sustainable utilization of natural resources and controlling financial risk are necessary strategies for realizing human well-being. More resources should be allocated for green innovation, and government should encourage economic globalization to attain sustainable development in emerging countries.

Graphical Abstract

Effect of environmental taxes on environmental innovation and carbon intensity in China: an empirical investigation

Environmental taxes are deemed to be an important carbon mitigating factor and also encourage the producers to adopt environmentally friendly technologies. Therefore, the main objective of the analysis is to evaluate the environmental taxes on environmental innovations and carbon intensity in China. The novel quantile autoregressive distributed lag (QARDL) is applied to investigate the model empirically. From the results, we confer that the short and long run estimated coefficients of environmental taxes are positive and significant at most quantiles in the environmental innovation model, implying that the higher the rate of environmental taxes, the higher the rate of environment-related innovations. However, the estimates of environmental taxes are significant and negative in both short and long run at more than half quantiles in the carbon emissions model, suggesting the positive role of environmental taxes in reducing carbon emissions. In general, our findings imply that an increase in environment-related taxes helps reduce carbon intensity and promote environmental innovation in China. The study suggests that policymakers in China should promote environmental innovation and expand the environmental tax base to achieve the objective of carbon neutrality.

Pipeline Leakage Detection Using Acoustic Emission and Machine Learning Algorithms

Pipelines play a significant role in liquid and gas resource distribution. Pipeline leaks, however, result in severe consequences, such as wasted resources, risks to community health, distribution downtime, and economic loss. An efficient autonomous leakage detection system is clearly required. The recent leak diagnosis capability of acoustic emission (AE) technology has been well demonstrated. This article proposes a machine learning-based platform for leakage detection for various pinhole-sized leaks using the AE sensor channel information. Statistical measures, such as kurtosis, skewness, mean value, mean square, root mean square (RMS), peak value, standard deviation, entropy, and frequency spectrum features, were extracted from the AE signal as features to train the machine learning models. An adaptive threshold-based sliding window approach was used to retain the properties of both bursts and continuous-type emissions. First, we collected three AE sensor datasets and extracted 11 time domain and 14 frequency domain features for a one-second window for each AE sensor data category. The measurements and their associated statistics were transformed into feature vectors. Subsequently, these feature data were utilized for training and evaluating supervised machine learning models to detect leaks and pinhole-sized leaks. Several widely known classifiers, such as neural networks, decision trees, random forests, and k-nearest neighbors, were evaluated using the four datasets regarding water and gas leakages at different pressures and pinhole leak sizes. We achieved an exceptional overall classification accuracy of 99%, providing reliable and effective results that are suitable for the implementation of the proposed platform.

Global human obesity and global social index: Relationship and clustering

Introduction

Obesity, a complex, multifactorial disease, is considered a global disease burden widely affecting the quality of life across different populations. Factors involved in obesity involve genetics, behavior and socioeconomic and environmental origins, each contributing to the risk of debilitating morbidity and mortality. However, the trends across the world vary due to various globalization parameters.

Methods

This article tends to identify the global social indicators, compiled into a global index, and develop a correlation between the global social index created by using the human development index, social and political globalization, the global happiness index, and the quality of infrastructure, institutions, and individuals using the internet factors and its effect on global obesity.

Results and Discussion

Our results identified a positive correlation between medium human development levels with obesity compared to low and very high human development levels. Economic stability due to rapid industrialization has increased the buying capacity and changed the global food system, which seems to be the major driver of the rise of global obesity.

Conclusion

The results decipher that global social indicators and overall social index have positively affected global obesity, which will help policymakers and governmental organizations monitor the obesity patterns across their regions by a significant contribution from globally influenced social factors.

Transport infrastructure, economic growth, and transport CO2 emissions nexus: Does green energy consumption in the transport sector matter?

Attaining Sustainable Development Goals (SDGs) is important to control the adverse impacts of climate change and achieve sustainable development. Among the 17 SDGs, target 13 emphasizes enhancing urgent actions to combat climate-related changes. This target is also dependent on target 7, which advocates enhancing access to cheap alternative sustainable energy. To accomplish these targets, it is vital to curb the transport CO₂ emissions (TCO₂) which increased by approximately 80% from 1990 to 2019. Thus, this study assesses the role of transport renewable energy consumption (TRN) in TCO₂ by taking into consideration transport fossil fuel consumption (TTF) and road infrastructure (RF) from 1970 to 2019 for the United States (US) with the intention to suggest some suitable mitigation policies. Also, this study assessed the presence of transport environmental Kuznets curve (EKC) to assess the direction of transport-induced growth. The study used the Bayer-Hanck cointegration test which utilizes four different cointegration techniques to decide cointegration along with the Gradual Shift causality test which considers structural shift and fractional integration in time series data. The long-run findings of the Dynamic Ordinary Least Squares (DOLS) test, which counters endogeneity and serial correlation, revealed that the transport renewable energy use mitigates as well as Granger causes TCO₂. However, transport fossil fuel usage and road infrastructure enhance TCO₂. Surprisingly, the transport EKC is invalid in the case of the US, and increased growth levels are harmful to the environment. The association between TCO₂ and economic growth is similar to a U-shaped curve. The Spectral Causality test revealed the growth hypothesis regarding transport fossil fuel use and economic growth connection, which suggests that policymakers should be cautious while decreasing the usage of transport fossil fuels because it may hamper economic progress. These findings call for revisiting growth strategies and increasing green energy utilization in the transport sector to mitigate transport emissions.

Green growth and environmental quality in top polluted economies: the evolving role of financial institutions and markets

An efficient financial system is crucial for the attainment of green growth and superior environmental quality. Therefore, our focus in this analysis is to estimate the effect of financial institutions and markets on green growth and environmental quality in highly polluted economies from 1991 to 2019. Estimates of the variables are collected with the help of the ARDL bounds testing approach. Findings of the ARDL model imply that a financial institution's efficiency helps improve green growth in the USA, China, and Japan in the long-run. However, the efficiency of the financial markets causes the green economy to grow in the long run in China and Russia only. On the other side, in the CO₂ model, the long-run estimated coefficients of a financial institution's efficiency are negatively significant in Japan and China only, implying that a financial institution's efficiency significantly reduces CO₂ emissions. Similarly, the long-run estimates of financial markets are significantly negative in the context of China and Japan only in CO₂ emissions.

How do economic and financial factors influence green logistics? A comparative analysis of E7 and G7 nations

Logistics is an important sector that supports every sector of the economy, and thus, the development of nations is impossible without efficient logistics. Alongside this, the logistics sector generates various kinds of emissions that degrade the quality of the environment. Developed countries are striving to introduce green logistics to avoid environmental damages caused by transportation. Also, developing countries will start focusing on developing green logistics sooner or later. Keeping this in view, a comparative panel study on the group of seven (G7) and Emerging Seven (E7) nations is conducted to study the impacts of various economic and financial variables on green logistics. The data from 1996 to 2018 is analyzed using some reliable methods that produce efficient and consistent results during heterogeneity and cross-sectional dependence. The findings disclosed that cointegration is present in E7 and G7 panels. For E7 countries, the results disclosed that research and development (R&D), FDI, portfolio investment, and trade openness reduce green logistics. However, in the G7, R&D, FDI, portfolio investment, and trade increase green logistics. The empirical analysis did not show any meaningful impact of financial development and economic growth on green logistics in both groups of nations. Lastly, based on the comparative analysis, various policies are suggested for E7 to catch up with the G7 regarding logistics development. Also, policies for G7 are suggested to boost green logistics.

The nexus between environmental strategy and environmental performance: analyzing the roles of green product innovation and mechanistic/organic organizational structure

The relationship between environmental strategy and environmental performance has been extensively analyzed in the environmental management literature. However, this relationship is spurious due to the inconsistence outcomes, lack of intervening mechanism, and scarcity of appropriate context. This study undertakes these considerations by exploring the underlying moderation-mediation mechanism through which proactive corporate environmental strategy affects corporate environmental performance. The hypotheses of the study were empirically tested on the data gathered from 147 ISO 14001:2015 certified firms in Pakistan. The data was statistically validated and then tested with Bootstrapping method using Preacher and Hayes Process Macros. The findings of the study revealed that a proactive corporate environmental strategy predicts corporate environmental performance through green product innovation. Moreover, the moderation hypothesis of the organizational structure variable in the nexus between proactive corporate environmental strategy and green product innovation was not supported in the full sample, whereas the split sample based on organizational size indicated moderation effects in the small firm's sample. The findings of the study carry important implications for firms related to corporate environmental strategy and green product innovation strategy.

A Case Report on Biliary Ascariasis

Biliary Ascariasis occurs when Ascaris lumbricoides worms invade the biliary system. It may cause biliary obstruction, cholangitis, cholecystitis, or acute pancreatitis. We report a case of a 37-year-old female patient who presented with a history of upper abdominal pain, nausea, vomiting, and weight loss for two weeks. Ultrasound showed dilated common bile duct with linear tubular echogenic structure in the common bile duct and bowel loops. Endoscopic Retrograde Cholangio pancreatography (ERCP) revealed large adult worms confirming the diagnosis of Ascariasis.

Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique

Promotors are those genomic regions on the upstream of genes, which are bound by RNA polymerase for starting gene transcription. Because it is the most critical element of gene expression, the recognition of promoters is crucial to understand the regulation of gene expression. This study aimed to develop a machine learning-based model to predict promotors in Agrobacterium tumefaciens (A. tumefaciens) strain C58. In the model, promotor sequences were encoded by three different kinds of feature descriptors, namely, accumulated nucleotide frequency, k-mer nucleotide composition, and binary encodings. The obtained features were optimized by using correlation and the mRMR-based algorithm. These optimized features were inputted into a random forest (RF) classifier to discriminate promotor sequences from non-promotor sequences in A. tumefaciens strain C58. The examination of 10-fold cross-validation showed that the proposed model could yield an overall accuracy of 0.837. This model will provide help for the study of promoters in A. tumefaciens C58 strain.

Environmental degradation, renewable energy, and economic growth nexus: Assessing the role of financial and political risks?

Sustainable development goal (SDG), which focuses on affordable and sustainable energy, provides a practical solution to realize sustainable growth. In addition, this target can encourage the realization of SDG 13 (climate action). However, factors like political and financial risk can impact climate actions and renewable energy. Therefore, this research extends the debate on the ecological footprint (EF) mitigation and achievement of SDGs by evaluating the renewable energy, political risk, financial risk, and EF nexus in an Environment Kuznets Curve (EKC) framework from 1986 to 2018. Panel data for the Association of Southeast Asian Nations (ASEAN) is estimated using second-generation approaches. The CuP-FM test results indicated that the EKC is present in ASEAN in the context of renewable energy, financial risk, and political risk. Furthermore, the findings revealed that controlling political and financial risks is a useful mitigation strategy because EF decreases as these risks are reduced. Notably, a decrease in EF has been linked to the use of renewable energy. These results are verified by using CO2 emissions as an alternative proxy for environmental degradation. Moreover, both financial and political risk Granger cause renewable energy and economic growth indicating that controlling financial and political risk is necessary for sustainable development.

Do heavy-duty and passenger vehicle emissions standards reduce per capita emissions of oxides of nitrogen? Evidence from Europe

Oxides of nitrogen are among the most dangerous emissions to human health and to the environment. In European nations, road transportation contributes to approximately 40% of emissions of oxides of nitrogen with the dominant share coming from passenger and freight transport. To help mitigate emissions of oxides of nitrogen, the European Union (EU) has implemented vehicular emissions standards. This paper studies the effect of EU vehicular emissions standards on per capita emissions of oxides of nitrogen in European nations during the period 2000 to 2017, both for on-road vehicular emissions and at the economy level. To do this, pollution is modelled as a byproduct of economic production. After controlling for economic growth, historical per capita levels of emissions of oxides of nitrogen, and a series of geographic and technological factors, it is determined that the vehicular emissions standards put in place by the EU decrease per capita levels of emissions of oxides of nitrogen. More precisely, reducing the heavy duty emissions standard by 1 g/kWh leads to as much as a 7% reduction in per capita on-road emissions of oxides of nitrogen. Reducing the passenger vehicle emissions standards for both diesel and gasoline engines enhances this effect, resulting in an even greater reduction in per capita emissions of oxides of nitrogen. These results further suggest that any rebound effect taking place is outweighed by the reduction in emissions of oxides of nitrogen from lowering emissions standards.

Exploring renewable energy, financial development, environmental quality, and economic growth nexus: new evidence from composite indices for environmental quality and financial development

The association between trade, financial development, consumption of renewable energy, environmental quality, foreign direct investment, and economic growth is important for sustainable growth and environmental strategies. Hence, this research unveils this association in selected low- and high-income economies from 1996 to 2020. Unlike most of the previous literature, this study uses a composite environmental quality index, a composite financial development index, and a composite trade share measure to better represent environmental quality, financial development, and trade openness, respectively. The Continuously Updated Fully Modified and Continuously Updated Bias Corrected estimators along with the Dumitrescu Hurlin causality method are utilized to scrutinize the nature of the linkage between the modeled variables. The long-run estimation provided that consumption of renewable energy and environmental quality augment economic growth in high-income nations, while both these variables do not contribute to the economic growth in low-income countries. Financial development upsurges economic growth in high- as well as low-income nations. Interestingly, trade openness boosts economic growth in high-income countries, while in low-income countries, it obstructs economic growth. In causal linkage, the conservation hypothesis for low-income countries and the feedback hypothesis for high-income countries are confirmed in the context of consumption of renewable energy and economic growth association. The supply-leading hypothesis for low-income countries and the feedback hypothesis for high-income countries are supported regarding the financial development-economic growth nexus. Moreover, one-way causality from growth to environmental quality and bidirectional causality between environmental quality and economic growth for low- and high-income countries are established, respectively. Lastly, exhaustive environmental and economic policies are directed.

A path towards carbon mitigation amidst economic policy uncertainty in BRICS: an advanced panel analysis

Continuing economic progress with less environmental damage and achieving a sustainable environment require switching from fossil fuels to green energy. However, alleviating environmental damage of growth has become a major challenge for BRICS where economic progress amidst rising urbanization pollutes the environment. In this context, the fight against climate change and actions towards environmental sustainability are greatly affected by rising economic policy uncertainty. Hence, this study assesses the role of green energy, urbanization, and economic growth in CO2 emissions in the presence of economic policy uncertainty in BRICS (excluding South Africa) from 1997 to 2020. The study used the cross-sectionally augmented auto-regressive distributive lag technique for revealing the short- and long-run effects of the analyzed variables on environmental quality. The empirical evidence suggested that the environmental Kuznets curve exists according to the recent framework of Narayan and Narayan Energy Policy 38:661-666, (2010) because even though economic growth increases CO2 emissions, its long-run effect is less than the short-run effect. Economic policy uncertainty boosts CO2 not only in the short-run but also in the long-run, evidencing that a sustainable environment requires decreasing the levels of policy uncertainty. For BRICS, switching towards green energy is a vital option to decrease environmental deterioration owing to the negative connection between green energy and CO2. The findings indicated that rapid urbanization is among the causes of high CO2. Furthermore, economic policy uncertainty influences both green energy and economic growth levels. Finally, policies are recommended to mitigate environmental deterioration.

Economic growth, technology, and CO2 emissions in BRICS: Investigating the non-linear impacts of economic complexity

Upgrading economic structures and producing less pollution-intensive goods are indispensable for achieving Sustainable Development Goals (SDGs) in BRICS (Brazil, Russia, India, China, and South Africa) that produce 41% of global CO₂ emissions. Economic complexity (ECC), which measures the sophistication of productivity and economic structure, has important environmental repercussions. Theoretically, the environmental impacts of economic complexity at higher levels and lower levels of complexity vary from each other. However, the majority of previous studies have overlooked these theoretical underpinnings while assessing the environmental repercussions of economic complexity. In addition, technological competencies are necessary to boost the economic complexity levels. Accordingly, this study uncovers the non-linear effects of economic complexity on CO₂ emissions including technology, population density, and economic growth in a STIRPAT model. To this end, the panel data from 1992 to 2018 is analyzed using the Continuously Updated Fully Modified method (CuP-FM) in the context of BRICS. The long-run results uncovered that CO₂ emissions intensify at a lower level of economic complexity. On the flip side, a higher level of economic complexity is beneficial in mitigating CO₂ in BRICS. Hence, the economic complexity and CO₂ connections follow an inverted U-shaped curve. The results also disclosed that expanding the level of technology lessens CO₂ and stimulates the quality of the environment. Further, population density and economic growth are evidenced to intensify CO₂. Moreover, economic complexity and technology Granger cause CO₂. Lastly, strategies are directed in the context of Sustainable Development Goals 9 and 13 to control CO₂ emissions by upgrading technology and products complexity.

COVID-19-Induced Seizures: A Meta-Analysis of Case Series and Retrospective Cohorts

The adverse events and complications of coronavirus disease 2019 (COVID-19) continue to challenge the medical profession despite the worldwide vaccination against the severe acute respiratory coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. Other than typical respiratory manifestations, COVID-19 also presents a wide range of neurological manifestations. This article underlines the pooled incidence of COVID-19-induced seizures in patients with epilepsy and without epilepsy. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols, we conducted a bibliographical search, and an initial search revealed 1,375 articles. In total, 21 articles were included in the final analysis by following the inclusion criteria. A total of 11,526 patients from 21 published articles that met the predetermined search criteria were included. The median age of the patients was 61.9 years, of whom 51.5% were males. A total of 255 patients presented with seizures as the first manifestation of COVID-19 with a prevalence of 2.2% (95% confidence interval = 0.05-0.24, p < 0.01) (I² = 97%), of which 71 patients had previously been diagnosed with epilepsy. Among patients with epilepsy, 49 patients had seizures as an initial presentation of SARA-CoV-2 with an incidence of 72% (0.54-0.85, p = 0.1) (I² = 34). Although the incidence of COVID-19-induced seizures is not high compared to other neurological manifestations, seizure incidence in epileptic patients with COVID-19 is remarkably high. New-onset seizures in any patient should be considered a presentation of COVID-19 in the absence of other causative factors.

876 Veriset Haemostatic Patch, Indications, Benefits and Complications: A Systematic Review

Aim

Achieving haemostasis intraoperatively is important for minimising blood loss, complications, and operation time. Suturing, cauterisation, fibrin glues and patches are used for this purpose. We explore Veriset, a patch consisting of polyethylene glycol and oxidised cellulose, to determine and compare its safety and effectiveness.

Method

Medline, Embase, Web of Science, Scopus, Cinahl and Cochrane databases were searched. Data points collected were Study/subject characteristics/demographics, surgery/specialty, time to haemostasis, proportion of haemostasis achieved, intraoperative adverse events, post operative complications, follow up time, and biochemical/histological analysis. Risk of Bias was assessed by Newcastle-Ottawa Scale

Results

Six studies were included; four human trials (3 RCTs, 1 case series) and two animal trials.

The human trials combined had 250 patients, with 147 using Veriset. In two RCTs, Veriset showed faster time to haemostasis and higher proportion of haemostasis achieved vs suturing and Tachosil haemostatic patch. In all three RCTs, no significant differences in adverse events and complications were seen between Veriset and suturing/Tachosil. Vascular, nephrectomy and hepatic surgery were investigated.

In the animal studies, the pig trial showed similar effectiveness and safety as the human trials. The rat study compared novel experimental patches to Veriset, and showed similar effectiveness to Veriset, at reduced costs.

Conclusions

Although current literature is scarce, Veriset is more effective than alternatives for haemostasis, with similar safety, although there are now other experimental patches that could have better health economic implications. Further clinical trials would be necessary to determine the breadth of applicable surgical fields for Veriset.

541 Pre-Operative Assessment of Patients Undergoing Elective TURBT or Rigid Cystoscopy + Bladder Biopsy: Is a Group & Save Clinically Required?

Aim

Method

Results

Conclusions

Modeling for Insights: Does Fiscal Decentralization Impede Ecological Footprint?

In recent years, the debate on environmental issues has become a hot topic. Fiscal decentralization is believed to be a crucial driver of environmental sustainability. However, the discussion on the effect of fiscal decentralization (FD) on environmental sustainability has not reached a unanimous conclusion. In this study, we inspect the effect of fiscal decentralization, economic development, technological innovation, economic globalization, and energy use on environmental quality in eight Asia-Pacific Economic Cooperation (APEC) member countries. In addition, we analyze the mechanisms through which fiscal decentralization influences the ecological footprint (EF) through the channels of technological innovation and economic growth. Using the STIRPAT framework, this study employed the CS-ARDL method for short-run and long-run analyses that deal with slope heterogeneity and cross-sectional dependence. The empirical results show that fiscal decentralization and technological innovation mitigate ecological footprint, while economic development, energy consumption, and urbanization negatively affect environmental quality. However, economic globalization is not related to the EF in the sample economies. The results further reveal that FD enhances environmental quality through the channel of technological innovation, while it does not affect the EF through the channel of economic growth. Finally, it is recommended to make a reasoned division between the rights and responsibilities of local government and central government in environmental pollution management, and optimize the environmental system. At the same time, policymakers should encourage technological innovation to reduce the adverse impacts of economic development and energy consumption on the environment.