From crisis to resilience: strengthening climate action in OECD countries through environmental policy and energy transition.

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.

Research and development for a carbon-neutral future and the status of EKC in G7 economies: evidence from CSARDL approach.

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.

How does the development of digital inclusive finance in China affect green technology innovation? A theoretical mechanism study and empirical analysis.

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.

The dynamic change trends and internal driving factors of green development efficiency: robust evidence from resource-based Yellow River Basin cities.

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.

Determination of affected brain regions at various stages of Alzheimer's disease.

The objective of study was to explore those brain areas that were affected at each stage during the progression of Alzheimer's disease (AD). Six affected brain areas were explored at mild cognitive impairment, four at first stage and six at each of second and third stage of Alzheimer's disease. The common brain regions among these stages were cuneus, precuneus, calcarine cortex, middle frontal gyrus, superior frontal gyrus, and frontal superior medial gyrus. The fMRI data at the resting state of 18 AD patients who were converted from MCI to stage 3 of Alzheimer's were taken from ADNI public source database. Among these patients, there were ten males and eight females. Independent component analysis was used to explore affected brain regions and an algorithm based on deep learning convolutional neural network was proposed for binary classification among the stages of Alzheimer's disease. The proposed CNN model delivered 94.6 % accuracy for separating stage 1 of Alzheimer's disease from mild cognitive impairment. 96.7 % accuracy was acquired to distinguish stage 2 of Alzheimer's disease from mild cognitive impairment, and stage 3 of Alzheimer's disease was separated from mild cognitive impairment with an accuracy of 97.8 %.

Technology innovations impact on carbon emission in Chinese cities: exploring the mediating role of economic growth and industrial structure transformation.

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.

The role of climatic changes and financial development to the ASEAN agricultural output: a novel long-run evidence for sustainable production.

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.

Exploring Tourism Efficiency and Its Drivers to Understand the Backwardness of the Tourism Industry in Gansu, China.

Gansu Province is rich in tourism resources, and it is the hometown of the "copper galloping horse", which is the logo of China's tourism. However, the scale and revenues of tourism in Gansu province are still at a low level. This paper first evaluated the tourism efficiency of 14 cities and prefectures of Gansu Province in China from 2011 to 2019 using the super-slack-based measure (Super-SBM) and then investigated the internal driving mechanism of the efficiency change through the Global Malmquist-Luenberger (GML) index and its decomposition, and finally analyzed the external influencing elements of tourist efficiency by the Tobit model. The results revealed that the tourism efficiency of Gansu Province had increased rapidly during the study period, especially after 2016, the rising range increased. From 2011 to 2019, the cumulative changes in GML index, technological change (TC), and efficiency change (EC) of tourism efficiency in Gansu Province were 5.053, 4.145 and 1.160, respectively, indicating that the improvement of tourism efficiency in Gansu province is mainly due to technological progress. The regression results of the Tobit model show that the status of the tourism industry, trade openness, information level, and technological innovation level can significantly promote tourism efficiency in the province. At the same time, upgrading the industrial structure and the improvement of greening coverage inhibit tourism efficiency. However, the impact of the economic development level on the tourism efficiency of Gansu Province is not apparent. According to the research results, this paper puts forward corresponding suggestions to promote the development of tourism in Gansu Province. This study is crucial for hospitality, tourism, and policy sectors to understand the underlying factors and promote the healthy development of the tourism industry in Gansu Province.

Multinodular goitre surgery complications and directly observed surgeons' skills: A prospective double-blind observational cohort study.

OBJECTIVE: To study multinodular goitre patients' surgery by direct observation of surgical technique, and to compare complications with surgeons' skills and experience, for improved training of future thyroid surgeons. METHODS: Based on positivist epistemology and analytical observational design, this prospective double-blind study of a cohort of multinodular goitre patients operated upon by variedly experienced surgeons, was conducted at Bahawal Victoria Hospital Bahawalpur and Nishtar Medical University Hospital Multan, Pakistan, from December 2016 to April 2019. Patients were admitted through outpatient department and operated upon in routine operation lists. The surgeons were specialists/senior registrars, assistant professors, associate professors and professors. The patients were divided into two virtual groups: the one operated upon by surgeons with >3 years of post-fellowship experience and the other operated upon by surgeons with <3 years of post-fellowship experience. Surgeries were directly observed and differences in surgical technique and complications were recorded for respective groups. Data was analysed using SPSS 20. RESULTS: Of the 134 patients, there were 73(54.5%) in group 1 and 61(45.5%) in group 2. Overall, there were 119(88.8%) females and 15(11.2%) males. The overall mean age was 37.17±13.41 years (range: 14-80 years). Of the 25 surgeons, 13(52%) were in group 1 and 12(48%) in group 2. Group 1 had fewer complications compared to group 2, which on certain parameters was statistically significant (p<0.05). CONCLUSIONS: Surgeons' experience and technique were found to have significant relationship with the rate of complications. Direct observation of surgeries is significant for real life evaluation and training of junior surgeons.

The asymmetric effects of crops productivity, agricultural land utilization, and fertilizer consumption on carbon emissions: revisiting the carbonization-agricultural activity nexus in Nepal.

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.

Does financial development mitigate the effects of climate variability on rice cultivation? Empirical evidence from agrarian economy.

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.

Modeling the impact of climatic and non-climatic factors on cereal production: evidence from Indian agricultural sector.

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.

Lapachol-Induced Upregulation of Sirt1/Sirt3 is linked with Improved Skin Wound Healing in Alloxan-induced Diabetic Mice.

Timely repair of damaged skin is very important to maintain the integrity and homeostasis of skin, but the wound healing process is compromised in diabetic patients due to several extrinsic and intrinsic factors thus lead to leg amputation and death eventually. Sirtuins, a family of seven conserved proteins are known to be associated with pathophysiological processes of the skin. The most important among them are sirt1and sirt3 involved in cell regeneration and cell survival. Naphthoquinone derivatives have a wide range of therapeutic properties, but the potential diabetic wound healing activity of lapachol has not been identified yet. The present study thus aimed to investigate the wound healing effects of lapachol in a diabetic mouse model. Diabetic wounded mice were divided into 3 groups; vehicle, lapachol 0.05%, and lapachol 0.1%. Skin samples collected from diabetic wounded mice on different time points after treatment for 10 consecutive days were subjected to downstream analysis by western blot, ELISA and histology. Lapachol treatment was found to enhance the expression of sirt1/sirt3 and other proteins involved in cell migration and blood vessel formation. The tissue development rate was increased by lapachol treatment with better collagen deposition. Interestingly, lapachol treatment also gave rise to a high concentration of growth factors resulting in speedy and timely recovery of injured skin. In summary, our findings suggest that lapachol promotes efficient wound healing in a diabetic mouse model by increasing the expression of sirt1 and sirt3 and other proteins related to wound repair and skin regeneration including α-PAK, RAC1/CDC42, VEGF and growth factors viz PDGF and VEGF. This research work finds a novel potential activator of sirtuins in the form of lapachol and depicts the role of activated sirtuins in diabetic wound healing.

Green photosensitisers for the degradation of selected pesticides of high risk in most susceptible food: A safer approach.

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.

Investigating the myth of smokeless industry: environmental sustainability in the ASEAN countries and the role of service sector and renewable energy.

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.

Towards long-term sustainable environment: does agriculture and renewable energy consumption matter?

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO2 emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO2 emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO2 emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section.

PERCEPTRON: an open-source GPU-accelerated proteoform identification pipeline for top-down proteomics.

PERCEPTRON is a next-generation freely available web-based proteoform identification and characterization platform for top-down proteomics (TDP). PERCEPTRON search pipeline brings together algorithms for (i) intact protein mass tuning, (ii) de novo sequence tags-based filtering, (iii) characterization of terminal as well as post-translational modifications, (iv) identification of truncated proteoforms, (v) in silico spectral comparison, and (vi) weight-based candidate protein scoring. High-throughput performance is achieved through the execution of optimized code via multiple threads in parallel, on graphics processing units (GPUs) using NVidia Compute Unified Device Architecture (CUDA) framework. An intuitive graphical web interface allows for setting up of search parameters as well as for visualization of results. The accuracy and performance of the tool have been validated on several TDP datasets and against available TDP software. Specifically, results obtained from searching two published TDP datasets demonstrate that PERCEPTRON outperforms all other tools by up to 135% in terms of reported proteins and 10-fold in terms of runtime. In conclusion, the proposed tool significantly enhances the state-of-the-art in TDP search software and is publicly available at https://perceptron.lums.edu.pk. Users can also create in-house deployments of the tool by building code available on the GitHub repository (http://github.com/BIRL/Perceptron).

Addressing the long- and short-run effects of climate change on major food crops production in Turkey.

This study assessed the long-run (LR) and short-run (SR) impacts of climatic and non-climatic factors, i.e., CO2 emissions (CO2e), average level of temperature (ALT), average level of precipitation (ALP), area harvested of wheat and rice crops (AHW and (AHR), domestic credit (DCR), and agricultural labor (ALB) on wheat and rice production (WP and RP) in Turkey by using annual time series data ranging from 1980 to 2016 and by employing several econometric techniques. The autoregressive distributed lag-bounds (ARDL) approach and the Johansen and Juselius cointegration (JJC) test confirmed a valid long-term connection among underlying variables. The estimation results from the ARDL model reveal that climatic factors such as CO2 emissions and temperature adversely affected wheat production in the long run as well as in the short run, whereas precipitation positively improved wheat production in both periods. Further results indicate that non-climatic factors like area harvested of wheat and domestic credit positively and significantly enhanced wheat production in the long run and short run. Similarly, CO2 emissions also adversely affected rice production in both periods, while temperature and precipitation positively contributed towards rice production in both cases. In addition, area harvested of rice positively and significantly boosted rice production in the long run as well as in the short run, while domestic credit negatively influenced rice production in the long run but in the short run positively improved rice production. Additionally, the outcomes of the VECM Granger Causality for both rice and wheat production confirm that both climatic and non-climatic variables have a strong influence on the production of both crops. This study found that climate change has a deleterious influence on both wheat and rice production; therefore, the study suggests that temperature-resistant varieties of both crops should be developed and introduced by agricultural research institutions. In addition to this, up-to-date information is more needed related to climate change, and in the farming communities, it should be provided by agricultural extension workers.

Trends in antimicrobial resistance amongst pathogens isolated from blood and cerebrospinal fluid cultures in Pakistan (2011-2015): A retrospective cross-sectional study.

While antimicrobial resistance (AMR) continues to be a major public health problem in Pakistan, data regarding trends of resistance among pathogenic bacteria remains scarce, with few studies presenting long-term trends in AMR. This study was therefore designed to analyze long-term AMR trends at a national level in Pakistan. We report here results of a comprehensive analysis of resistance, among pathogens isolated from blood and cerebrospinal fluid (CSF), between 2011 and 2015. Susceptibility data was obtained from a local laboratory with collection points all across Pakistan (Chughtai Laboratory). Resistance proportions to most commonly used antimicrobials were calculated for each pathogen over a period of five years. While Acinetobacter species demonstrated highest resistance rates to all tested antimicrobials, a sharp increase in carbapenem resistance was the most noticeable (50%-95%) between 2011-2015. Our results also highlight the presence of third and fourth generation cephalosporins resistance in Salmonella enterica serovar Typhi in Pakistan. Interestingly, where rise in AMR was being observed in some major invasive pathogens, decreasing resistance trends were observed in Staphylococcus aureus, against commonly used antimicrobials. Overall pathogens isolated from blood and CSF between 2011-2015, showed an increase in resistance towards commonly used antimicrobials.