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Emerging economies are mostly plague by a massive consumption of non-renewable energy amidst an ever inceasing urbanization rate with little or no attention to the quality of the environmental. As such, this paper investigates the relationship between renewable energy, urbanization, economic growth, trade openness, and ecological footprint in CIVETS countries, namely, Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa. The study employs augmented mean group estimator, panel cointegration, and causality tests. The findings reveal that renewable energy improves environmental quality, and trade is not particularly harmful to the environment. However, non-renewable energy consumption and urbanization are the chief contributors to environmental degradation in the CIVETS countries. Economic expansion mitigates environmental deterioration in Colombia, South Africa, and Turkey, but contributes to pollution in Egypt, Indonesia, and Vietnam. Finally, the causality test suggests that urbanization drives environmental degradation. Policy directions are discussed.

Social entrepreneurship has been recognized as a tool to attain sustainable development. This paper highlights the role of social entrepreneurship in triggering social change and attaining sustainable development. The paper contributes significantly to the existing literature by conducting a systematic review of extant works. To this end, we analyzed and reviewed 173 research papers from the Web of Science database. The results are presented in the form of descriptive findings and thematic discussion. The paper concludes by setting up the agenda for future researchers in the field.

COVID-19 pandemic has brought significant and multiple challenges for SMEs. While SMEs have traditionally faced financial and non-financial crises, the pandemic has brought about additional uncertainties on how to maintain business continuity. The purpose of this paper is to examine how SMEs can mitigate against COVID-19-related crisis by examining the impacts that the pandemic has had on them through a review of 34 articles. The thematic analysis from the literature covered three overarching and inter-related challenges including (i) cost and finance-related challenges, (ii) disruption of activities, and (iii) existential difficulties. The paper’s value lies in addressing the gap between the espoused literature’s claim of the beneficial impact of new technological advancements and SMEs’ ability to survive in the context of the COVID-19 pandemic. The additional value of this paper is a framework of recommendations to help enhance SMEs’ resilience and responsiveness in the context of COVID-19. These recommendations include collaboration, openness, taking advantage of opportunities/victory, and durability.

Understanding structure–function relationships in the brain after stroke is reliant not only on the accurate anatomical delineation of the focal ischemic lesion, but also on previous infarcts, remote changes and the presence of white matter hyperintensities. The robust definition of primary stroke boundaries and secondary brain lesions will have significant impact on investigation of brain–behavior relationships and lesion volume correlations with clinical measures after stroke. Here we present an automated approach to identify chronic ischemic infarcts in addition to other white matter pathologies, that may be used to aid the development of post-stroke management strategies. Our approach uses Bayesian–Markov Random Field (MRF) classification to segment probable lesion volumes present on fluid attenuated inversion recovery (FLAIR) MRI. Thereafter, a random forest classification of the information from multimodal (T1-weighted, T2-weighted, FLAIR, and apparent diffusion coefficient (ADC)) MRI images and other context-aware features (within the probable lesion areas) was used to extract areas with high likelihood of being classified as lesions. The final segmentation of the lesion was obtained by thresholding the random forest probabilistic maps. The accuracy of the automated lesion delineation method was assessed in a total of 36 patients (24 male, 12 female, mean age: 64.57±14.23yrs) at 3months after stroke onset and compared with manually segmented lesion volumes by an expert. Accuracy assessment of the automated lesion identification method was performed using the commonly used evaluation metrics. The mean sensitivity of segmentation was measured to be 0.53±0.13 with a mean positive predictive value of 0.75±0.18. The mean lesion volume difference was observed to be 32.32%±21.643% with a high Pearson's correlation of r=0.76 (p<0.0001). The lesion overlap accuracy was measured in terms of Dice similarity coefficient with a mean of 0.60±0.12, while the contour accuracy was observed with a mean surface distance of 3.06mm±3.17mm. The results signify that our method was successful in identifying most of the lesion areas in FLAIR with a low false positive rate. [Display omitted] •Segmentation of chronic ischemic and other lesions impacting poststroke depression.•Hierarchical segmentation of the probable lesion from FLAIR using Bayesian-MRF.•Random-forest (RF) probabilistic classification on probable lesion class.•Context-rich features used in RF include multimodal MRI and lesion likelihood.

The e-commerce sector has experienced significant growth in the past two decades, outpacing other economic sectors and contributing to sustainable consumption, increased labour productivity, competitiveness, consumer incomes, and GDP growth. This trend is expected to continue, making e-commerce a key driver of sustainable economic growth in Europe. This study aims to explore the relationship between a nation’s innovation level and its population’s inclination towards online shopping in various EU member states. It hypothesizes that higher innovation levels within a country lead to a greater tendency for online purchases. This study conducts a thorough analysis of the interplay between European economies’ innovation levels and the e-commerce market’s evolution. A composite innovation index was created using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology, and panel data models were utilized to examine the dependencies, with data from Eurostat and the Global Innovation Index. The focus is on the period from 2019 to 2021, which was marked by unique market dynamics and the impact of the COVID-19 pandemic. The findings confirm the significant role of innovation in driving e-commerce expansion within the context of sustainable consumption, supporting the main hypothesis. This research also highlights the pandemic’s positive effect on the e-commerce sector. The pandemic-induced changes in consumer behaviour, particularly due to social isolation and crises in certain economic sectors, have emphasized the importance of online shopping. Notably, the most active online shoppers are identified in the 25 to 54 age group, revealing a key demographic trend.

\"Sustainable investment\"-includes a variety of asset classes selected while caring for the causes of environmental, social, and governance (ESG). It is an investment strategy that seeks to combine social and/ or environmental benefits with financial returns, thus linking investor's social, ethical, ecological and economic concerns Under certain conditions, these indices also help to attract foreign capital, seeking international participation in the local capital markets. The purpose of this paper is to study whether the sustainable investment alternatives offer better financial returns than the conventional indices from both developed and emerging markets. With an intent to maintain consistency, this paper comparatively analyzes the financial returns of the Thomson Reuters/S-Network global indices, namely the developed markets (excluding US) ESG index-TRESGDX, emerging markets ESG index-TRESGEX, US large-cap ESG index-TRESGUS, Europe ESG index-TRESGEU, and those of the usual markets, namely MSCI world index (MSCI W), MSCI All Country World Equity index (MSCI ACWI), MSCI USA index (MSCI USA), and MSCI Europe Australasia Far East index (MSCI EAFE), MSCI Emerging Markets index (MSCI EM) and MSCI Europe index (MSCI EU). The study also focusses on the inter-linkages between these indices. Daily closing prices of all the benchmark indices are taken for the five-year period of January 2013-December 2017. Line charts and unit-root tests are applied to check the stationary nature of the series; Granger's causality model, auto-regressive conditional heteroskedasticity (ARCH)-GARCH type modelling is performed to find out the linkages between the markets under study followed by the Johansen's cointegration test and the Vector Error Correction Model to test the volatility spillover between the sustainable indices and the conventional indices. The study finds that the sustainable indices and the conventional indices are integrated and there is a flow of information between the two investment avenues. The results indicate that there is no significant difference in the performance between sustainable indices and the traditional conventional indices, being a good substitute to the latter. Hence, the financial/investment managers can obtain more insights regarding investment decisions, and the study further suggests that their portfolios should consider both the indices with the perspective of diversifying the risk and hedging, and reap benefits of the same. Additionally, corporate executives shall use it to benchmark their own performance against peers and track news as well.

Relaxation processes over the static permittivity frequency region present in poly(propylene glycol) [PPG] of average molecular weights M n  = 425 and 725 have been investigated in the temperature range (285–320 K) and frequency range (1 Hz–1 MHz) using broadband dielectric spectroscopy. The data have been compared in the form of complex dielectric permittivity (ε*), electric modulus (M*), conductance (σ*), and impedance (Z*) spectra of PPG. From the comparative analysis of the spectra of all the complex quantities, the temperature-dependent relaxation processes caused by the presence of electrode polarization and ionic conduction effects were explored. The temperature dependence of various dielectric parameters such as dc conductivity (σ dc ), relaxation time due to electrode polarization (τ EP ), conductivity relaxation time (τ σ ), and their activation energies have been critically examined. It was observed that the dependence of dc conductivity (σ dc ) on the viscosity (η) or structural relaxation time (τ α ) of both PPGs satisfies the Stokes–Einstein–Nernst/Stokes–Einstein–Debye quite well. This behavior is similar to those reported in lithium percolate (LiClO 4 ) electrolyte solutions in PPG solvents. This demonstrates that the electrical conduction behavior of unknown ions impurities existing in pure PPG and extremely low known concentration added ions in pure PPG is the same. Graphical abstract

Intracellular Wolbachia bacteria manipulate arthropod reproduction to promote their own inheritance. The most prevalent mechanism, cytoplasmic incompatibility (CI), traces to a Wolbachia deubiquitylase, CidB, and CidA. CidB has properties of a toxin, while CidA binds CidB and rescues embryonic viability. CidB is also toxic to yeast where we identified both host effects and high-copy suppressors of toxicity. The strongest suppressor was karyopherin-α, a nuclear-import receptor; this required nuclear localization-signal binding. A protein-interaction screen of Drosophila extracts using a substrate-trapping catalytic mutant, CidB*, also identified karyopherin-α; the P32 protamine-histone exchange factor bound as well. When CidB* bound CidA, these host protein interactions disappeared. These associations would place CidB at the zygotic male pronucleus where CI defects first manifest. Overexpression of karyopherin-α, P32, or CidA in female flies suppressed CI. We propose that CidB targets nuclear-protein import and protamine-histone exchange and that CidA rescues embryos by restricting CidB access to its targets.

In this study, we revisit prominent equity market anomalies documented for India, namely size, value, volume and momentum. Using data for NSE 500 companies, we test for the persistence of these anomalies for a recent period from July 2005 to June 2016 employing one-factor capital asset pricing model (CAPM) and three-factor Fama–French model as asset pricing benchmarks. We test for the robustness of these anomalies by (a) forming both quintile and decile portfolios and (b) forming univariate and variety of bivariate-sorted portfolios. Corner portfolios based on deciles provide greater return differentials compared to quintile portfolios. Bivariate-sorted portfolios do not seem to outperform univariate-sorted portfolios. The value and momentum anomalies are explained by risk models which is contrary to prior evidence. Size and volume anomalies continue to provide significant returns but seem to have faded substantially over time when compared with the past results. The findings about weakening prominent Indian equity market anomalies shall pose a challenge for portfolio managers who may have to look for other sources of extra-normal profits. Indian market also seems to be informationally more efficient which is in line with recent financial market reforms and growing emphasis on financial inclusion and corporate governance.

We examine prominent market anomalies and evaluate the efficacy of alternative asset pricing models under different financial integration settings. A financial integration index is developed for classifying 25 sample markets into high-, medium- and low integration groups. Size is found to be the strongest anomaly in world markets, followed by value and liquidity. Value and profitability effects are larger for low-integrated markets. Highly integrated markets experience short-term momentum while many low-integrated markets exhibit mild reversals. Fama and French five-factor model outperforms capita l asset pricing model (CAPM) and Fama and French three-factor model in explaining returns. International factors augment the role of local factors for more integrated markets. Our study has implications for global investors to design anomaly based investment strategies.