Unlocking green innovation and environmental performance: the mediated moderation of green absorptive capacity and green innovation climate.

This study extends the foundations of the natural resource-based view (NRBV) by introducing a mediation-moderation framework by analyzing the influence of green intellectual capital (GIC) on both green innovation performance (GIP) and environmental performance (EP) while simultaneously considering the mediating role of green absorptive capacity (GAC) and the moderating influence of the green innovation climate (GICL). The data for this study was gathered from a sample of 575 participants employed within small and medium enterprises' (SMEs') manufacturing firms. This dataset was utilized to evaluate the proposed model; this study uses the PLS-SEM approach to comprehensively examine the complex interactions among these variables. This model adds to the theoretical understanding of NRBV and enhances its practical applicability. The findings of this study reveal a positive relationship between GIC, GAC, GIP, and EP within organizations. Furthermore, our investigation reveals a positive correlation between a GICL and the relationships involving GIC, GAC, GIP, and EP. Importantly, this research introduces a novel perspective by clarifying the complex relations among these variables and highlighting the positive correlation between a GICL and the relationships involving GIC, GAC, GIP, and EP. This novel approach enhances the theoretical understanding of NRBV and its practical applicability in fostering GIP and EP within manufacturing SMEs operating in Pakistan.

Genomic and Epigenomic Features of Glioblastoma Multiforme and its Biomarkers.

Glioblastoma multiforme is a serious and life-threatening tumor of central nervous system, characterized by aggressive behavior, poor prognosis, and low survival rate. Despite of the availability of aggressive antitumor therapeutic regimen for glioblastoma (radiotherapy followed by chemotherapeutic dose), recovery rate, and patients' survival ratio is attributed to the lack of selectivity of therapeutic drugs and less advancement in cancer therapeutics over last decade. Moreover, tools employed in conventional diagnosis of glioblastoma are more invasive and painful, making the process excruciating for the patients. These challenges urge for the need of novel biomarkers for diagnosis, prognosis, and prediction purpose with less invasiveness and more patient compliance. This article will explore the genetic biomarkers isocitrate dehydrogenase mutation, MGMT mutations, and EGFR that can be deployed as an analytical tool in diagnosis of disease and prognosis of a therapeutic course. The review also highlights the importance of employing novel microRNAs as prognostic biomarkers. Recent clinical advancements to treat GBM and to prevent relapse of the disease are also discussed in this article in the hope of finding a robust and effective method to treat GBM.

Dynamic linkages among CO2 emissions, human development, financial development, and globalization: empirical evidence based on PMG long-run panel estimation.

This study investigates the impact of the human capital index, globalization, and financial development on carbon dioxide of grouping OECD countries using pool mean group estimation technique from 1990 to 2015. This study also applies the second-generation cross-sectional augmented Dickey-Fuller and cross-sectional Im, Pesaran, Shin panel (CIPS) unit root, and the latest (Westerlund 2008) cointegration tests for further investigations. The result shows that both the human development index and financial development stimulate environmental improvement by using PMG long-run panel estimation approach. Furthermore, the pairwise Dumitrescu-Hurlin panel causality results prove the two-way causal association between financial development and carbon emissions. The unidirectional causality running from globalization and human development index towards carbon emission is also supported. Based on the aforementioned results, we provide a set of recommendations for policy implication. Graphical abstract.

Determinants of carbon emissions in Pakistan's transport sector.

The transport infrastructure plays an imperative role in a country's progress. At the same time, it causes environmental degradation due to extensive use of fossil fuels. The transport system of Pakistan is largely dependent on nonrenewable energy sources (oil, coal, and gas), which are hazardous to environmental quality. This research uses an autoregressive distributive lag model (ARDL) to examine the impact of oil prices, energy intensity of road transport, economic growth, and population density on carbon dioxide (CO2) emissions of Pakistan's transport sector during the 1971-2014 period. The ARDL bounding test examines the cointegration and long-run relationships among the variables, and the directions of causal relationships are found through the Granger causality vector error correction model (VECM). The long-run results indicate that increases in oil prices and economic growth help to reduce the transport sector's CO2 emissions, while rising energy intensity, population concentration, and road infrastructure increase them, with population playing a dominant role. The findings of this study can help authorities in Pakistan to develop suitable energy policies for the transport sector. Among other recommendations, the study recommends investment in renewable energy projects and energy-efficient transport systems (e.g., light train, rapid transport system, and electric busses) and environmental taxes (subsidies) on the vehicles that use fossil fuels (renewable energy).