Global Factors Research Articles

Shifts in mycorrhizal types of fungi and plants in response to fertilisation, warming and herbivory in a tundra grassland.

Climate warming is severely affecting high-latitude regions. In the Arctic tundra, it may lead to enhanced soil nutrient availability and interact with simultaneous changes in grazing pressure. It is presently unknown how these concurrently occurring global change drivers affect the root-associated fungal communities, particularly mycorrhizal fungi, and whether changes coincide with shifts in plant mycorrhizal types. We investigated changes in root-associated fungal communities and mycorrhizal types of the plant community in a 10-yr factorial experiment with warming, fertilisation and grazing exclusion in a Finnish tundra grassland. The strongest determinant of the root-associated fungal community was fertilisation, which consistently increased potential plant pathogen abundance and had contrasting effects on the different mycorrhizal fungal types, contingent on other treatments. Plant mycorrhizal types went through pronounced shifts, with warming favouring ecto- and ericoid mycorrhiza but not under fertilisation and grazing exclusion. Combination of all treatments resulted in dominance by arbuscular mycorrhizal plants. However, shifts in plant mycorrhizal types vs fungi were mostly but not always aligned in their magnitude and direction. Our results show that our ability to predict shifts in symbiotic and antagonistic fungal communities depend on simultaneous consideration of multiple global change factors that jointly alter plant and fungal communities.

On bursty star formation during cosmological reionization - how does it influence the baryon mass content of dark matter halos?

Abstract The baryon mass content (i.e. stellar and gas mass) of dark matter halos in the early Universe depends on both global factors - e.g. ionizing ultraviolet (UV) radiation background - and local factors - e.g. star formation efficiency and assembly history. We use a lightweight semi-analytical model to investigate how both local and global factors impact the halo baryon mass content at redshifts of z ≥ 5. Our model incorporates a time delay between when stars form and when they produce feedback of 0 ≤ td/Myr ≤ 30, which can drive bursts of star formation, and a mass and redshift dependent UV background, which captures the influence of cosmological reionization on gas accretion onto halos. We use statistically representative halo assembly histories and assume that the cosmological gas accretion rate is proportional to the halo mass accretion rate. Delayed (td>0) feedback leads to oscillations in gas mass with cosmic time, behaviour that cannot be captured with instantaneous feedback (td=0). Highly efficient star formation drives stronger oscillations, while strong feedback impacts when oscillations occur; in contrast, inefficient star formation and weak feedback produce similar long-term behaviour to that observed in instantaneous feedback models. If the delayed feedback timescale is too long, a halo retains its gas reservoir but the feedback suppresses star formation. Our model predicts that lower mass systems (halo masses mh ≤ 107M⊙) at z ≤ 10 should be strongly gas deficient (mg → 0), whereas higher mass systems retain their gas reservoirs because they are sufficiently massive to continue accreting gas through cosmological reionization. Interestingly, in higher mass halos, the median m⋆/(m⋆ + mg) ≃ 0.01 – 0.05, but is a factor of 3-5 smaller when feedback is delayed. Our model does not include seed supermassive black hole feedback, which is necessary to explain massive quenched galaxies in the early Universe.

The association between addiction profile and early maladaptive schemas among individuals with opioid use disorder

ABSTRACT Background and objective Opioid use disorder (OUD) is a global problem and factors that play a role in its development and treatment outcomes need to be examined. We aimed to compare early maladaptive schemas (EMS) in individuals with OUD with a control group and to investigate the effects of these variables on the addiction profile. Methods Eighty-one participants with a diagnosis of OUD and 81 control participants were included in the study. The sociodemographic data form and Young Schema Inventory Short Form-3 were used as data collection tools for both groups. In addition, the Addiction Profile Index (API) was applied to the OUD group. Results A statistically significant difference was identified in 11 of the 14 schema domains. We found a statistically significant positive correlation in the API total scores of OUD patients with the areas of failure, social isolation/insecurity, and nesting/addiction schemas. Conclusions OUD patients were characterized with more prominent maladaptive schemas compared to the control group. When evaluating individuals with OUD, it would be beneficial to determine the dominant schema areas and consider them in designing treatment programs. In addition, new methods should be developed to examine the effects of schemas on complex events such as dependency.

Estimating potentially preventable ambient PM2.5-attributable adult deaths by improving air quality in Nepal

Air pollution is an important global environmental health risk factor, with many Asian countries experiencing alarming levels in recent decades. Nepal, a South Asian country, has been facing severe degradation in air quality in recent years, where data are scarce on the health impact of air pollution, especially at sub-national levels. In this study, we investigated ambient fine particulate matter (PM2.5)-attributable adult (≥25 years) premature mortality in Nepal, analyzed its long-term trend, and estimated potentially preventable adult mortality under different improved air quality scenarios defined using the World Health Organization's (WHO) interim targets (IT) and the air quality goal (AQG). Leveraging an open-source high-resolution PM2.5 dataset and an age-specific population dataset, we employed the Global Exposure Mortality Model to estimate mean and 95% confidence intervals of PM2.5-attributable adult mortality using Monte Carlo simulations. We estimated the country-level NCD + LRI (non-communicable diseases and lower respiratory infections) adult deaths attributable to PM2.5 exposure as 48881 (95% CI: 37175−61470), and the PM2.5-attributable NCD + LRI adult mortality rate as 267 (95% CI: 203−335) per 100000 in 2019. The adult mortality burden consistently increased during 2000–2019. Moreover, improving air quality to the WHO ITs and AQG could prevent an estimated 9690 (95% CI: 7698−11812) to 39419 (95% CI: 30311−49277) premature adult deaths across the country in 2019. Our findings suggest that the adult mortality burden due to air pollution in Nepal is substantial, which offers an opportunity to prevent a considerable number of premature adult deaths by mitigating air pollution in the country.

Fisheries Impact Pathway: Making Global and Regionalised Impacts on Marine Ecosystem Quality Accessible in Life Cycle Impact Assessment

Overexploitation in wild-capture fisheries is a principal driver of marine biodiversity loss. Currently, efforts are underway to improve the representation of marine damage indicators in Life Cycle Impact Assessment (LCIA) methods. The recently operationalised fisheries impact pathway has introduced fishing impacts on the marine system into the LCIA framework, and the current work seeks to further develop this complex pathway. In total, 5000+ Characterisation Factors for exploited marine organisms have been re-computed with updated fisheries production data (2018), exploring temporal effects on dynamic, biotic resource impacts. An estimation of discarded unwanted by-catch is incorporated into the characterisation. Regional to global scaling factors are tested for the representation of species-specific vulnerability. The temporal and spatial variations in impacts reflect the dynamic nature of real-world fisheries trends, global average impacts increased by 41% (2015–2018). Discarding as an additive, regional estimate increases impacts, most notably for lower impacted stocks. The retention of species-specific detail relating to species distributions is of particular relevance to fisheries when computing global-scale impacts. Updating CFs improves the relevance of the fisheries impact assessment, and continued periodic re-computation is recommended to maintain relevance with real-world trends. Data availability remains a challenge to large-scale marine impact assessment and the continued development of this emergent impact pathway is expected.

Impact of Global and Domestic Factors on Indian Government Bond Yields

Impact of Global and Domestic Factors on Indian Government Bond Yields

Exploring the Relationship between Solar Panel Adoption and Socio-Economic Factors: A Case Study of Urban Households in Developing Countries

This article will discuss the results of research on how the use of solar panels as an alternative energy source is related to social and economic factors, especially in urban areas in developing countries. This study will analyze factors such as education level, income, and people's perceptions of alternative energy to identify correlations between solar panel use and socio-economic variables. It is hoped that this article can provide new insights for public policy in promoting the use of renewable energy and creating a more inclusive society. This research can be categorized as quantitative. The research method used is the associative research method. The data analysis method used is correlation analysis. The sampling technique used is purposive sampling. The results of the study show that there are different characteristics of the relationship between the use of solar panels and socio-economic variables. Research on the relationship between global solar panel use and factors such as the number of prosumers, total kwh exports, GRDP, total investment, total load, home charging ev, distance to the capital city, air quality, and per capita expenditure has very important uses for stakeholders, especially in terms of sustainable energy development and reducing negative impacts on the environment. Policymakers can use the results of this research to formulate more appropriate policies to promote the use of solar energy and drive the shift to renewable energy sources.

Assessing the Asymmetric Relationship between Global Economic Factors and Cryptocurrency: A Comparison between Normal Times and COVID-19 Times using the NARDL Model

Stock markets, commodity markets, and cryptocurrency markets, have all been negatively affected with the onset of this pandemic covid-19, and the effects are far more intense than that any previous outbreaks. This paper not only aims at understanding the interaction of global economic factors with the digital currency bitcoin, but it also sheds light on the impact Covid-19 had on the relationship between bitcoin and global economic factors. In line with the objective of this study, the researcher determines the asymmetric relationship between global economic factors’ price, specifically gold price, crude oil price, stock index S & P price, and bitcoin price during the unprecedented times of Covid-19 using the Non-linear autoregressive distributed lags (NARDL model). Data was analysed for the period March 2014 to March 2021, employing descriptive statistics, unit roots testing, and NARDL model, aided by the statistical package EViews version 11.The findings reveal the presence of a statistically significant and asymmetric relationship between global economic factors and cryptocurrency during the covid-19 times, whilst before the strike of the pandemic, global economic factors were not significant to cryptocurrency as the results are insignificant. Howbeit, the overall model showcases mixed results since the significance of the asymmetric effect for the overall model is due to the significance of the asymmetric effect during covid-19. The relevant authorities as well as central banks are recommended to work closely together to enforce effective economic policies to mitigate the dreadful effects of the covid-19 pandemic without instilling uncertainty among investors thus gearing towards market recovery.

Litter decomposition rate response to multiple global change factors: a meta-analysis

Anthropogenic global change fundamentally impacts ecosystem biogeochemical cycling. Although litter decomposition is a crucial component of carbon (C) cycling, its response to diverse global change factors (GCFs) remains uncertain. In this research, we synthesized 1706 observations from 260 peer-reviewed publications to elucidate the effects of GCFs on litter decomposition rate (k) and the contribution of different variables to them. Overall, nitrogen (N) addition and drought significantly decreased k (-3.3 and -17.7%, respectively), phosphorus (P) addition, warming, and increased precipitation significantly increased k (6.7, 8.2, and 11.6%, respectively), while elevated CO2 had an insignificant effect on k (-0.6%). Combined GCFs had no significant effect on k except for warming*drought, and all combined factors mainly exhibited antagonistic interactions. Further analysis showed that k responses to GCFs were influenced by initial litter quality (C, N, C:N, P, cellulose, lignin, and vegetation types), soil properties (soil organic C, soil total N, soil total P, soil respiration and microbial biomass C), environmental factors (latitude, longitude, annual mean temperature, annual mean precipitation, ecosystem type, and climate type), and experimental methods (experiment type, richness, treatment method, fertilizer form, fertilizer rate, and experimental duration). Initial litter quality predominantly governed the k response to N addition (53.5%), while soil properties were more significant in regulating the P addition response (44.8%). Environmental factors largely determined k responses to warming, drought, and increased precipitation (50.6, 54.7, 46.9%). Moreover, the experimental methodology also played an important role in regulating k responses to GCFs, which explained 8.6, 23.6, 31.1, 23.7, and 29.7% of the variation of the responses of k to N addition, P addition, warming, drought, and increased precipitation. This meta-analysis offers improved global-scale nutrient cycling predictions under climate change and underscores the need for long-term, multi-factor, methodologically standardized experiments to accurately predict the influence of GCFs on litter decomposition.

ANALYZING TRENDS AND FACTORS INFLUENCING THE INDIAN STOCK MARKET”

ANALYZING TRENDS AND FACTORS INFLUENCING THE INDIAN STOCK MARKET”

The effects of foreign investor composition on Colombia's sovereign debt flows

Assessing the composition of sovereign debt holders is important because investors' behavior varies according to distinctive components, including shareholders' preferences, regulatory constraints, and profitability mandates. To study this issue, we examine the determinants of offshore investments of mutual funds and pension funds, which concentrate Colombia's outstanding sovereign debt. Our results indicate that mutual funds exhibit considerable sensitivity to shocks in global factors, such as the Federal Funds Rate, sovereign risk, and the composition of financial indices. This contrasts with findings among pension funds, for which we detected a lower sensitivity to these factors, underlining the differences in foreign investor behavior that can impact sovereign debt flows within emerging markets.

Tail risk intersection between tech-tokens and tech-stocks

This study investigates the interconnectedness of upside and downside tail risks between tech-industry tokens and equities, focusing on uncertainties and portfolio implications. We estimate tail-risk measures at various quantiles using the conditional autoregressive value-at-risk method and investigate selected assets' static and dynamic connectedness using a time-varying parameter-vector autoregression approach. The findings reveal a moderate level of time-varying tail-risk interconnectedness. Furthermore, we examine the role of global uncertainty factors in tail-risk contagion and identify the factors driving connectedness. Moreover, this study analyzes portfolio implications, offering insights into effective risk management strategies and the potential benefits of diversification. These findings have significant implications for investors, regulators, and policymakers in risk management in the technology industry.

The Intuitive Eating Scale-3: Development and psychometric evaluation

Intuitive eating has been found to protect against disordered eating and preserve well-being. Yet, there are methodological (length), conceptual (inconsideration of medical, value-based, and access-related reasons for food consumption), and psychometric (item wording) concerns with its most common measure, the Intuitive Eating Scale-2 (IES-2). To address these concerns, we developed the IES-3 and investigated its psychometric properties with U.S. community adults. Across three online studies, we evaluated the IES-3's factorial validity using exploratory factor analysis (EFA; Study 1; N = 957; Mage = 36.30), as well as confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), bifactor-CFA, and bifactor-ESEM (Study 2; N = 1152; Mage = 40.95), and cross-validated the optimal model (Study 3; N = 884; Mage = 38.54). We examined measurement invariance across samples and time, differential item functioning (age, body mass index [BMI], gender), composite reliability, and validity. Study 1 revealed a 12-item, 4-factor structure (unconditional permission to eat, eating for physical reasons, reliance on hunger and satiety cues, body-food choice congruence). In Study 2, a bifactor-ESEM model with a global intuitive eating factor and four specific factors best fit the data, which was temporally stable across three weeks. This model also had good fit in Study 3 and, across Studies 2 and 3, and was fully invariant and lacked measurement bias in terms of age, gender, and BMI. Associations between latent IES-3 factors and age, gender, and BMI were invariant across Studies 2 and 3. Composite reliability and validity (relationships with disordered eating, embodiment, body image, well-being, and distress; negligible relationship with impression management) of the retained model were also supported. The 12-item IES-3 demonstrates strong psychometric properties in U.S. community adults. Research is now needed using the IES-3 in other cultural contexts and social identity groups.

Evolution of rates, patterns, and driving forces of green eco-spaces in a subtropical hilly region

Monitoring ecological resource change in mountainous and hilly areas (MHAs) is vital for theoretical and practical advancements of ecological resource utilization and management in complex ecosystems. The factors driving structural and functional changes in green eco-spaces (GES) in these areas are complex and uncertain, with notable spatial scale effects. However, analyzing the multi-scale driving mechanisms of ecological and socioeconomic factors at a fine spatiotemporal scale presents significant challenges. To address these challenges, we analyzed dynamic changes in GES and eco-socio-economic development in Shanghang County, a typical mountainous region in southern China. We used multiple linear regression and multi-scale geographically weighted regression model to identify key factors driving GES changes and their multi-scale effects at both global and local levels. Over the past two decades, the GES area in the study area has exhibited a consistent pattern of decline, characterized by phases of gradual decline (2000–2005), sharp decline (2005–2009), slow decline (2009–2019). Key global factors driving GES changes included elevation (ELE), slope (SLOPE), population density (PD), distance to settlements (SETTLE), and distance to administrative centers (ADMIN). These factors exhibited significant spatial heterogeneity and multi-scale effects on GES changes. Specifically, SETTLE, PD, SLOPE, and ELE consistently drove GES changes at the local level, while ADMIN only showed significant localized effects during 2005–2009. The synergy between SETTLE and SLOPE had a considerable impact on GES changes, increasing over time, whereas ELE and PD demonstrated a consistent trade-off effect. These findings provide detailed spatiotemporal insights into the driving mechanisms of natural ecological resources, offering crucial guidance for environmental management, land source management, regional economic development, and biodiversity conservation in Shanghang and analogous subtropical hilly regions worldwide.

Analysing the Factors Behind Exchange Rate Fluctuations in India

Abstract: The study gives an overview of the various determinants of the exchange rate movements in India. Out of the multiple factors affecting the Rupee-Dollar value the impact of Interest rate differential, Trade deficit of India, Foreign Net investment inflows to India, Oil prices, and Gold prices (in the short term) on the exchange rate has been studied using Regression analysis and correlation and the role they played by the above mentioned variables in determining the exchange rate during the Global Financial Crisis of 2008-2010 and during the Covid-19 Period from 2020-2023. Exchange rate fluctuations play a crucial role in shaping the economy of a country, and India is no exception. The exchange rate of the Indian rupee against major world currencies is subject to constant fluctuations, influenced by a multitude of domestic and global factors. These fluctuations have significant implications for various stakeholders, including businesses, consumers, investors, and policymakers. Several factors contribute to the exchange rate fluctuations in India. One of the primary factors is the demand and supply dynamics of foreign exchange. Factors such as trade balance, foreign direct investments, portfolio investments, remittances impact the demand for and supply of foreign currency, Crude oil prices, Gold prices, and thereby affecting the exchange rate. In addition, macroeconomic variables like inflation, interest rates, and economic growth also play a crucial role in determining exchange rate movements. For instance, a high inflation rate in India compared to trading partner countries can lead to a depreciation of the rupee. Global economic conditions and geopolitical events are other significant factors influencing exchange rate fluctuations in India. Economic developments in major trading partners, changes in global commodity prices, and geopolitical tensions can all impact investor sentiment and capital flows, leading to fluctuations in the exchange rate. For example, uncertainties related to Brexit or trade tensions between major economies can trigger volatility in currency markets. Monetary policy decisions by the Reserve Bank of India (RBI) also play a crucial role in influencing exchange rates. Interest rate changes, open market operations, and forex interventions by the central bank can impact the value of the rupee visa-vis other currencies. The RBI often intervenes in the foreign exchange market to stabilize the rupee or prevent extreme volatility. Apart from these factors, market speculation, investor sentiment, and technological advancements in the financial markets can also contribute to exchange rate fluctuations. High-frequency trading, algorithmic trading, and the use of complex financial instruments by market participants can amplify exchange rate movements and increase volatility

CO2 enrichment accelerates alpine plant growth via increasing water-use efficiency

Phenological changes in global vegetation are often attributed to climate warming. However, climate warming and elevated atmospheric CO2 concentration (eCO2) are two co-occurring global change factors, and how eCO2 would affect vegetation phenology has received less attention. The partial pressure of atmospheric CO2 on the Tibetan Plateau (TP) is lower than that in regions of lower altitudes. Consequently, the growth and phenology of alpine plants in this region could be more sensitive to eCO2, but this hypothesis is not yet supported by empirical evidence. Here we explored the effect of eCO2 on plant phenology (including phenophases of green-up, budding, and flowering) through a 5-year field manipulation experiment in a high-altitude (4600 m above sea level) alpine grassland on the TP. Our results showed that eCO2 significantly advanced the spring phenology of an early-flowering species (Kobresia pygmaea), while it had no impact on the phenology of two mid-flowering species (Potentilla saundersiana and Potentilla cuneata). Compared to other low-altitude regions, plant phenology on the TP underwent greater alterations under eCO2, which supports our hypothesis that the growth of high-altitude plants is more sensitive to eCO2. Furthermore, we found that eCO2 significantly reduced the overlapping of flowering between contrasting plant species, mainly due to the phenological advancement of the K. pygmaea induced by eCO2. The observed advancement of the spring phenology in K. pygmaea under eCO2 was associated with increasing ecosystem water-use efficiency (WUE), thereby advancing its subsequent phenological development, such as budding and flowering. Our findings provide experimental evidence that atmospheric CO2 enrichment can accelerate plant growth processes in high-altitude regions, and suggest that large-scale model simulations should consider the effects of elevated atmospheric CO2 concentration on plant growth and phenology.

Brain on Fire: How Brain Infection and Neuroinflammation Drive Worldwide Epilepsy Burden

Roughly 80% of the global burden of epilepsy resides in low- and middle-income countries (LMICs; WHO, 2022). Despite numerous new therapies for the treatment of epilepsy, the number of patients who remain resistant to available medications is unchanged. Additionally, no therapy has yet been clinically proven to prevent or attenuate the development of epilepsy in at-risk individuals. Unfortunately, access to next generation therapies in LMICs is low, the stigma associated with epilepsy remains high, and access to adequate resources is unchanged. Thus, the global epilepsy burden disproportionately falls on LMICs such that strategies to conscientiously integrate global epilepsy risk factors into preclinical research may meaningfully advance 21st century epilepsy therapies. Brain infections are one of the main risk factors for epilepsy in resource-poor settings. Further, both infection- and autoimmune-associated encephalitis contribute to worldwide epilepsy risk and remain relatively understudied. For example, clinical SARS CoV-2 infection can induce rare instances of encephalopathy and acute seizures. Among viruses known to cause acute brain infection, enteroviruses increase risk for encephalitis-induced epilepsy, but are not associated with risk for other neurodevelopmental disorders (eg, autism spectrum or attentional deficit hyperactivity disorders). Naturally occurring models of viral infection-induced epilepsy therefore provide an exquisite opportunity to uncover novel contributors to epileptogenesis. Moreover, the convergent neuroinflammatory pathways that are associated with viral infection-induced encephalitis and autoimmune encephalitis reflect an untapped therapeutic opportunity to meaningfully reduce the global burden of epilepsy. This review summarizes the latest advances in translational research integrating encephalitis-induced seizure and epilepsy models, in tandem with progress in clinical diagnosis of inflammation and virally mediated epilepsy. This improved awareness of the shared biological underpinnings of epileptogenesis following brain infection or autoimmune encephalitis is anticipated to beneficially impact the global burden of epilepsy.

Micro, Small, and Medium Enterprises’ Cross-Border Business Strategies

This paper explores the operational strategies of cross-border micro, small, and medium enterprises (MSMEs). Against the backdrop of globalization and digitalization, cross-border trade has become one of the important pathways for many MSMEs to achieve growth and competitive advantage. Firstly, the paper outlines the concept and characteristics of cross-border MSMEs, as well as the analysis of their operational environment in the context of globalization, including political, economic, social, technological, environmental, and legal factors. Secondly, the paper proposes operational strategies for cross-border MSMEs, including international market selection and positioning, cross-border marketing strategies, supply chain management, cross-border financial management, and cross-border risk management. Finally, the paper summarizes the importance of effectively implementing these strategies for cross-border MSMEs to seize international market opportunities, reduce operational risks, and enhance competitiveness and profitability.

Damping prediction of highly dissipative meta-structures through a wave finite element methodology

Aiming at accurately predicting the global Damping Loss Factor (DLF) for Highly Dissipative Structures (HDS), the current study uses the Wave Finite Element (WFE) methodology. It starts by deriving the forced responses of a Unit Cell (UC) representative of the periodic meta-structure. Then it computes the DLF of the wave via the power balance. The Bloch expansion is employed. The response to a point force applied to the periodic structure is decomposed in the Brillouin zone, allowing the prediction via integration over the wavespace. The global DLF is derived based on the Power Input Method (PIM). The accuracy of the methodology is demonstrated through several cases from simple panels to complex meta-structures. For HDS, results of General Laminated Model (GLM) is exploited for wave DLF and PIM based on Finite Element Method (FEM) data is provided as reference approach for global DLF. The study discusses the influence of bending waves on the DLF estimation for HDS. A final case study with a meta-structure is also offered. The later consists of a doubly periodic coated sphere in a host rubber, it demonstrates the importance of Bloch modes.

Dynamic linkage between environmental segments of stock markets: the role of global risk factors

ABSTRACT This study evaluates the links between representative indices of companies with high environmental performance and the propensity of such indices to economic and financial shocks. Five indices, representing environmental segments and four global macroeconomic and financial variables, were analyzed over a thirteen-year period, which included various crisis moments, such as the sovereign debt crisis, the COVID-19 pandemic and the onset of the Russia/Ukraine conflict. Using dynamic and nonlinear models, our research reveals statistically significant and consistent relationships between the variables under investigation, particularly during periods of global financial and pandemic crises. The analysis revealed that the VIXCLS is the most influential global risk factor, with certain risk factors being influenced by environmental segments, particularly Alternative Energy. This influence can create conditions conducive to contagion risk and diminish the benefits of portfolio diversification. This study contributes to a deeper understanding of the connection between environmental investments and their vulnerability to significant global events and risks.