Shifts In Structure Research Articles

Supply Chain Plasticity: A Responsive Network Capability to Ensure Resilience

ABSTRACTIn the face of supply chain disruptions, firms are expected to swiftly recover and resume operations. Traditional strategies focus on restoring operations to pre‐disruption states while largely maintaining the existing supply network structure. Recent cases, however, highlight a different approach: supply chain plasticity, wherein firms undergo significant structural shifts in supply network design as a response to disruptions with the goal to improve performance. Drawing on the foundations of supply chain responsiveness and network theory, we investigate how (and if) firms redesign their supply chains against a backdrop of increased disruptions and the implications supply chain plasticity has on resilience. Rooted in network theory, this study not only theoretically compares, contrasts, and connects prior concepts with supply chain plasticity but also empirically investigates whether firms exhibit a plastic response by modifying their supply chain network structures—specifically focusing on structural holes, centrality, and clustering network dimensions. Furthermore, we hypothesize that network plasticity impacts firm performance in the form of time to recover from a disruption. The findings demonstrate that the existence and significance of network plasticity in shaping firm responses to disruptions are indeed present and can be beneficial. We also provide evidence that supply chain plasticity is an efficacious strategy to enhance resilience and recovery performance amidst heightened disruption frequency. As firms increasingly face dynamic and complex environments, understanding and leveraging network plasticity will be vital for sustaining competitive advantage and achieving long‐term success.

Трансформация структуры государственного долга по составу кредиторов в странах Центральной Азии и Южного Кавказа

The rapid growth of public debt in developing countries in recent years and the increasing risks associated with this process emphasize the importance of research in this area. The article examines one of the key aspects of public debt management — the structure of creditors’ debt portfolio. The object of the study is the public debt of four countries of Central Asia and three countries of the South Caucasus. The states of this region are important foreign economic partners of Russia, their contribution to mutual trade and realization of joint projects is growing. Their role in the global and regional economy is also expanding, including participation in major transport and logistics projects designed to increase the connectivity of Eurasia. The study is based on the data of international organizations on the total volume of public debt, debt to individual external creditors and the dynamics of macroeconomic indicators. The article examines changes in the structure of the main groups of creditors for each country over three long-term periods and analyzes similarities and differences in the observed structural shifts. It also decomposes the indicator of public debt dynamics and estimates the contribution of the economic growth factor and the effects of changes in countries’ debt to certain groups of creditors. The study identified the following key trends in public debt structural changes: 1) the declining role of bilateral loans from developed and developing countries since the 2000s; 2) the continued strong influence of debt raised from international financial organizations and development banks in most countries throughout the period under study; 3) in a number of countries, a gradual increase in market sources of debt financing (domestic and Eurobonds); the increasing role of loans from China — in the Kyrgyz Republic and the Republic of Tajikistan, etc. The study identifies reasons for these structural changes, and concludes with a discussion of the risks associated with the observed shifts in the structure of public debt.

Long-Term Elasticity of Environmental Demand: Environmental Protection Expenditures in Sweden, 1972–2020

This study uses reconstructions of historical Environmental Protection Expenditure Accounts (EPEA) in Sweden from 1970–2020 to present a time series approach that analyses the demand for environmental services. The paper’s aim is to analyse environmental adaptation as a historical, economic and environmental process and to explore structural shifts suggestive of an overall periodisation of environmental demand. The article contributes to a deeper understanding of demand-side factors in environmental adaptation as part of contemporary economic history. The investigation also provides evidence that the income elasticity of environmental demand was slightly higher than 1.0 and largely stable over time, and even though we were able to detect trend breaks, there is insufficient evidence for major structural breaks suggesting sharp shifts in societal environmental preferences. Policies requiring sharply rising environmental expenditures should consider this level of historical stability. This article was published open access under a CC BY licence: https://creativecommons.org/licences/by/4.0 .

Infodemic, Ignorance, or Imagination? The Problem of Misinformation in Health Emergencies

Abstract In understanding and responding to the problem of misinformation during global health emergencies, health experts and organizations such as the WHO have relied on the concept of the “infodemic,” or the idea that there is such an overabundance of information that ascertaining trustworthy sources and reliable guidance is difficult. Is this the best way to understand the problem of misinformation, however? A large and multidisciplinary literature has argued that such an approach misses the important role of individual psychological factors and societal “mega-trends” such as hyperpolarization, structural shifts in the media, and public mistrust in elites. This article argues that such contributions are important in understanding the multifaceted problem of misinformation but may miss another, equally important component: the politics of emergency. Specifically, the prominent role of speculation during moments of emergency—the need to respond to “what ifs” rather than just “what is”—provides a conducive context for misinformation, facilitating its production and spread while also problematizing efforts to correct it. The article illuminates this relationship through a discourse analysis of prominent misinformation claims during the US responses to Ebola in 2014 and COVID-19 in 2020.

Predictive Patterns and Market Efficiency: A Deep Learning Approach to Financial Time Series Forecasting

This study explores market efficiency and behavior by integrating key theories such as the Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH), Informational Efficiency and Random Walk theory. Using LSTM enhanced by optimizers like Stochastic Gradient Descent (SGD), Adam, AdaGrad, and RMSprop, we analyze market inefficiencies in the Standard and Poor’s (SPX) index over a 22-year period. Our results reveal “pockets in time” that challenge EMH predictions, particularly with the AdaGrad optimizer at a size of the hidden layer (HS) of 64. Beyond forecasting, we apply the Dominguez–Lobato (DL) and General Spectral (GS) tests as part of the Martingale Difference Hypothesis to assess statistical inefficiencies and deviations from the Random Walk model. By emphasizing “informational efficiency”, we examine how quickly new information is reflected in stock prices. We argue that market inefficiencies are transient phenomena influenced by structural shifts and information flow, challenging the notion that forecasting alone can refute EMH. Additionally, we compare LSTM with ARIMA with Exponential Smoothing, and LightGBM to highlight the strengths and limitations of these models in financial forecasting. The LSTM model excels at capturing temporal dependencies, while LightGBM demonstrates its effectiveness in detecting non-linear relationships. Our comprehensive approach offers a nuanced understanding of market dynamics and inefficiencies.

Evaluating the Impact of Chinese FDI in the Energy Sector on Green GDP Growth: A Spatial Econometric Analysis of MENA Countries

This study analyzes the impact of Chinese foreign direct investment (FDI) in the energy sector on the green GDP (GGDP) growth of seven Middle East and North Africa (MENA) countries based on data from 2009 to 2019. Using panel regression analysis, the study focuses on the effects of FDI, economic development level, population size, energy consumption structure, environmental regulation intensity, government fiscal expenditure, and the KOF Economic Globalization Index on GGDP growth. By comparing fixed-effects and random-effects models and applying the Hausman test to select the most appropriate model, the research indicates that the random-effects model is the most suitable. The results show that FDI, economic development level, and population size have significant positive effects on GGDP, while shifts in energy consumption structure also promote sustainable economic growth. In contrast, environmental regulation intensity and the globalization index have no significant impact on GGDP, suggesting that GGDP growth in MENA countries relies more on internal economic policies and the efficiency of resource allocation.

Contribution of Economic Development to The Development of The Mamminasata Region

Mamminasata (Makassar, Maros, Gowa, Takalar) is one of the urban or metropolitan areas in Eastern Indonesia. Mamminasata as a strategic area with economic interests has an important role in the development of its city and surrounding areas. Meanwhile, the dynamic development of the city causes demands for space needs to increase, especially the need for residential land. The objectives of this study are to 1) know economic development in the Mamminasata district/city in 2001-2021 2) know the development of built-up land in the Mamminasata district/city in 2001-2021 and 3) know the influence and contribution of economic growth to the development of the Mamminasata region. The research location is Makassar City, Maros Regency, Gowa Regency and Takalar Regency. This type of research is descriptive quantitative qualitative. The required data is collected through literature studies in the form of secondary data, namely Gross Regional Domestic Product (GRDP) at constant prices 2010, and google earth images 2001-2021. The analysis used in the research is literature study analysis, qualitative quantitative descriptive, basic statistics, LQ-DLQ, Shift Share, and multiple linear regression analysis. The result of this study is that during 2001-2021 the real income of the Mamminasata Region continued to increase. With the highest growth rate in Gowa Regency. Makassar City only has one leading sector, Maros Regency has two leading sectors, Gowa Regency has three leading sectors, and Takalar Regency has two leading sectors. Only Kabupaten Maros experienced a shift in economic structure from the tertiary sector to the primary sector in 2021 due to a significant economic decline. Spatially, sub-districts that are adjacent or directly adjacent to Makassar City have the most significant built-up land growth with developments following the main road network pattern. Based on the results of multiple linear regression analysis, it shows that there is no significant influence between the independent variables on the dependent variable either jointly or partially individually. Then the t-test was conducted again between tertiary variables and built-up land and showed a significant influence with a contribution of 33% to built-up land.

Between Tradition and Modernity: The Sociospatial Dynamics of Japanese Residential Architecture from Pre-War to Present

This research examines the evolution of Japanese residential architecture throughout the 20th century, focusing on the transformation of house plans in response to changing societal needs. This study specifically examines how traditional spatial configurations adapted to urbanization, modernisation, and shifts in the family structure. By analysing house plans across three distinct periods—the pre-war and post-Kanto earthquake period, the post-war period, and the post-oil shock period to the present—this research illustrates the transition from detached houses to modern collective housing. Utilising a space syntax methodology, this research quantitatively analyses threshold spaces, circulation, and family gathering spaces to understand their social and architectural implications. Historical analyses are paired with a network analysis of selected house plans, highlighting the persistent significance of traditional elements such as the doma (vestibule) and the en-gawa (verandah) in contemporary designs. The findings demonstrate a significant reduction in the size and complexity of living spaces over time, reflecting broader trends towards efficiency and modernisation in public housing. This research contributes to architectural scholarship by providing a detailed account of how Japanese customary spaces have been reconfigured to accommodate evolving lifestyles, offering insights into the balance between tradition and modern living.

The Role of Renewable Energy, Technological Innovation, and Human Capital on Environmental Quality in Türkiye: Testing the LCC Hypothesis with Smooth Structural Shifts

Newly industrializing economies are ardently striving for rapid development, aspiring to emulate the affluence of Western nations. However, amidst this relentless economic dynamism, the world grapples with an escalating climate change crisis. Therefore, it becomes imperative to identify the factors contributing to improving developing nations' environmental quality while concurrently advancing their sustainable development objectives. In this regard, the present study aims to dissect the environmental implications of renewable energy consumption, technological innovation, and human capital and examine the "Load Capacity Curve" (LCC) hypothesis in Türkiye through an extension of the STIRPAT model. To achieve this objective, the research operates a novel econometric methodology, namely the "augmented autoregressive distributed lag" (A-ARDL) approach with Fourier terms, to analyze yearly data from 1980 to 2019. The empirical findings substantiate the validation of the LCC hypothesis in Türkiye, both in the short and long term. Furthermore, the results unveil that renewable energy consumption and human capital significantly bolster ecological welfare over the long term, whereas technological innovation exhibits no discernible impact on the environment. Additionally, the outcomes display that population growth positively impacts the environment in the short term; nevertheless, over the long term, it becomes detrimental to environmental quality.

Differential Effects of Sulfur Fertilization on Soil Microbial Communities and Maize Yield Enhancement

Sulfur (S) is an essential nutrient for plant growth, influencing not only crop yields but also the composition and function of soil microbial communities. However, the differential effects of S fertilization on abundant and rare taxa in agricultural soils remain poorly understood. This study investigates the impact of different S fertilizer types on maize yield and the structure and stability of soil microbial communities, with a particular focus on abundant and rare taxa. S fertilization led to significant increases maize yield on two typical soils (black soil and sandy soil) (5.3–24.3%) and altered soil properties, including reducing pH (0.04–0.20) and increasing the available sulfur (AS) content (3.8–8.0 mg kg−1), with ammonium sulfate having a more pronounced effect than elemental sulfur. Microbial analysis revealed distinct impacts on the diversity and community structure of both abundant and rare taxa. Elemental sulfur reduced the alpha diversity of abundant taxa more than ammonium sulfate, while NMDS indicated significant shifts in community structures, particularly among abundant taxa. Network analysis showed that S fertilization decreased the complexity of microbial interactions among rare taxa, with ammonium sulfate leading to simpler networks and elemental sulfur resulting in higher modularity. SEM highlighted that the diversity of rare taxa played a crucial role in influencing maize yield, alongside direct effects from soil properties such as AS and SAR (aryl sulfatase). Functional predictions demonstrated that amino acid metabolism and xenobiotic biodegradation and metabolism pathways were enriched in rare taxa, suggesting significant implications for soil health and crop productivity. This study provides new insights into the roles of abundant and rare bacterial taxa under S fertilization, emphasizing their importance in optimizing fertilization strategies for enhanced crop yield in specific soil types.

Analysis of the development of organic crop production in Latin America

The paper is devoted to the study of the process of development of organic production as a global trend in agriculture. The objects of the research are the countries of Latin America, as territories that are promising in terms of large-scale and rapidly developing organic agriculture for export and domestic consumption — Uruguay, Paraguay, Brazil, Argentina, Chile, Mexico, Dominican Republic. The countries have large land funds and favorable agroclimatic conditions in most of their territories. In the work, based on the application of methods of time series alignment and the graphical method, trends in demand for the purchase and subsequent use of pesticides, the prevalence of malnutrition in Latin America and in the world, as well as prospects for the development of organic crop production by such an indicatosr as the total area of organic lands and number of producers are identified. The simple linear regression model constructed by the authors made it possible to establish the relationship between the volumes of greenhouse gas emissions and the average annual temperature, which made it possible to establish the need to reduce the use of synthetic fertilizers and pesticides to achieve sustainable development goals. Calculation of the linear and quadratic coefficients of structural shifts, as well as the index of differences, made it possible to identify structural changes in priority groups of crops for growing organic crops.

Assessing shifts in soil fungal community structure during the conversion of tropical semi-evergreen forest: implications for land use management

Assessing shifts in soil fungal community structure during the conversion of tropical semi-evergreen forest: implications for land use management

Disclosing the key role of Fe/As/Cu in community co-occurrence and microbial recruitment in metallurgical ruins

Mining activities have led to the persistent presence of substantial heavy metals at metallurgical sites. However, the impact of long-term and complex heavy metal pollution in metallurgical ruins on the structure and spatial shift of microbiome remains unclear. In this study, we focused on various types of metallurgical sites to uncover the occurrence of heavy metals in abandoned mines and the response patterns of microbial communities. The results indicate that mining activities have caused severe exceedances of multiple heavy metals, with AsBio, CuBio, and FeBio being the primary factors affecting community structure and function. Co-occurrence network analyses suggest that several genera, including Ellin6515, Cupriavidus, Acidobacteria genus RB41, Vicinamibacteraceae, Blastococcus, and Sphingomonas, may play significant roles in the synergistic metabolism of communities responding to Fe-Cu-As stress. Although random dispersal contributed to community migration, null models emphasized that variable selection predominates in the spatial turnover of community composition. Additionally, metagenomic prediction (PICRUSt2) identified key genes involved in stress and detoxification strategies of heavy metals. The composite heavy metal stress strengthened the relationship between network structure and the potential function of the community, along with critical ecosystem functions. Our findings demonstrated that microbial interactions were crucial for ecosystem management and the ecological consequences of heavy metal pollution remediation.

Rapid Quantification of Protein Secondary Structure Composition from a Single Unassigned 1D 13C Nuclear Magnetic Resonance Spectrum.

The function of a protein is predicated upon its three-dimensional fold. Representing its complex structure as a series of repeating secondary structural elements is one of the most useful ways by which we study, characterize, and visualize a protein. Consequently, experimental methods that quantify the secondary structure content allow us to connect a protein's structure to its function. Here, we introduce an automated gradient descent-based method we refer to as secondary-structure distribution by NMR that allows for rapid quantification of the protein secondary structure composition of a protein from a single, 1D 13C NMR spectrum without chemical shift assignments. The analysis of nearly 900 proteins with known structure and chemical shifts demonstrates the capabilities of our approach. We show that these results rival alternative techniques such as FT-IR and circular dichroism that are commonly used to estimate secondary structure compositions. The resulting method requires only the primary sequence of the protein and its referenced 13C NMR spectrum. Each residue is modeled in an ensemble of secondary structures with percentage contributions from random coil, α-helix, and β-sheet secondary structures obtained by minimizing the difference between a simulated and experimental 1D 13C NMR spectrum. The capabilities of the method are demonstrated as applied to samples at natural abundance or enriched in 13C, acquired by either solution or solid-state NMR, and even on low magnetic field benchtop NMR spectrometers. This approach allows for rapid characterization of protein secondary structure across traditionally challenging to characterize states including liquid-liquid phase-separated, membrane-bound, or aggregated states.

Invasive mussels reduce community bioturbation but do not affect oxygen penetration or nutrient fluxes in organic‐poor Great Lakes sediments

Abstract Invasive zebra and quagga (dreissenid) mussels have disrupted nutrient cycling and benthic macrofauna communities in the Laurentian Great Lakes and other invaded ecosystems. Dreissenids are now the dominant benthic macroinvertebrate in the Great Lakes, replacing the formerly dominant native bioturbating amphipod Diporeia spp. Dreissenids and Diporeia interact with their environment in fundamentally different ways, and the consequences of this functional shift in benthic community structure on benthic–pelagic coupling are not well understood, particularly in unproductive offshore lake regions. To determine how functional biology and benthic community structure impact sediment mixing and biogeochemistry in low particulate organic matter (POM) lake regions, we conducted a 6‐week sediment microcosm experiment with dreissenids, Diporeia and oligochaete worms—the second most common Great Lakes benthic macroinvertebrate. We found that sediment mixing rate and depth varied significantly among the taxa. Diporeia mixed sediment the deepest and strongest, followed by oligochaetes, while dreissenids did not appreciably mix sediment. Despite these differences, we found no significant variations among treatments in sediment oxygen penetration depth, sediment respiration (oxygen uptake) or nutrient dynamics. Our results suggest that dreissenids mix sediment less than native Great Lakes taxa, but that differential mixing rates may not measurably affect nutrient and oxygen dynamics in low‐POM sediments. Therefore, mussel effects in these areas may be manifested more through direct mechanisms rather than via altered sediment geochemistry.

Climate Warming and Mismanagement Drive the Shift of Fish Communities in the Wadi El-Rayan Arid Lakes

The Wadi El-Rayan lakes are important aquatic environments located at the border of the great North African Sahara. Quantifying the temporal changes in these lakes due to natural and/or anthropogenic stressors is critical when assessing potential impacts on aquatic ecosystem health and the sustainability of fisheries. To detect the changes in fish communities and their drivers, the landing composition of the Wadi El-Rayan lakes over the past 30 years was quantitatively analyzed. The areas of the lakes dramatically decreased from 110 km2 in 1991 to 73 km2 in 2019. The loss of the lake area was attributed to climate warming, where the evaporation rate exceeded the volume of recharge and the recharge decreased due to an increase in agriculture and aquaculture. The total landing significantly increased in the past three decades due to an increase in the fishing effort (number of licensed boats). Nile tilapia, mullet, and grass carp dominated the landings. The pelagic-to-demersal ratio indicated a shift in the fish community composition towards demersal species. This shift was attributed to an increase in the eutrophication level. The fish communities of the landing data were clustered into four distinct groups. These clusters were significantly differentiated (p < 0.001) in both a PERMANOVA test and a PCA plot. There was a gradual replacement of the dominant species among these clusters. The most recent cluster (2018–2019) was characterized by rare species dominating the community. This shift in species composition suggests that target taxa may have been overexploited. The total landing also decreased, which may have been a result of climate warming. Furthermore, the presence of alien and warm-water species significantly increased. The fish community structure and composition shift could be attributed to anthropogenic (mismanagement) and natural climatic changes (warming).

Intraday quantile coherence between oil and European sectors during the Russia-Ukraine war

ABSTRACT This study examines the interconnectedness between crude oil and European sectors during the Russia-Ukraine conflict. Using a quantile coherence approach, we investigate the intraday dynamics of market interactions at different quantiles and frequencies. The findings reveal that in the short-term, oil emerges as a robust hedge for 12 sectors in stable market conditions, transitioning to a weaker hedge during bullish and bearish market conditions. Furthermore, the long-term analysis shows a stronger coherence between oil and stock sector indices. The medium-term and long-term analyses reveal shifts in dependence structures, with oil acting as a safe haven in bullish markets for specific sectors. These findings provide valuable insights for investors and policymakers in managing risks amid geopolitical events, contributing to the existing literature on oil-European sector dynamics.

Seasonal dynamics of environmental heterogeneity augment microbial interactions by regulating community structure in different trophic lakes

Understanding how environmental heterogeneity drives microbial communities in lakes is essential for developing effective strategies to manage and restore aquatic ecosystems. However, the mechanisms by which environmental heterogeneity influences microbial community structure, network patterns, and interactions remain largely unexplored. To bridge this gap, we collected 84 water samples from four typical lakes in China (Fuxian, Tianmu, Taihu, and Xingyun) representing a range of trophic levels, across wet and dry seasons. We assessed environmental heterogeneity using 14 water quality parameters, analyzed community structure with Jaccard and Bray-Curtis dissimilarity indices, and developed a comprehensive index to elucidate microbial network complexity. Our study reveals three key findings: (1) Environmental heterogeneity was significantly greater in dry season compared to wet season across all lakes (P < 0.05). (2) Increased environmental heterogeneity led to higher bacterioplankton community dissimilarity, with greater β-diversity observed in dry season (P < 0.05). (3) Shifts in community structure due to increased environmental heterogeneity further enhanced microbial interactions, as evidenced by more complex and interconnected co-occurrence networks in the dry season. In summary, our study demonstrates that environmental heterogeneity significantly impacts bacterioplankton community structure and subsequently enhances microbial interactions. These findings underscore the importance of considering environmental heterogeneity in lake ecosystem management, as it plays a crucial role in regulating microbial community dynamics and interactions.

Mode of application of sulfonated graphene modulated bioavailable heavy metal contents and microbial community composition in long-term heavy metal contaminated soil

Nanomaterials are increasingly recognized for their potential in soil remediation. However, their impact on soil microbial communities in contaminated soil remains poorly understood. In this study, we investigated the dynamic effects of sulfonated graphene (SG) following one-time or repeated applications on heavy metal availability and soil microbial communities in long-term heavy metal-contaminated soil over 180 days. Our findings revealed that one-time SG application at 30 mg kg−1 significantly increased the bioavailable cadmium (Cd) and copper (Cu) contents by approximately 30 %–40 % after 2 and 180 days. Repeated SG applications, however, displayed no significant influence on heavy metal availability. One-time SG application, coupled with the increased available Cd, induced significant enrichment of some specific functional bacterial genera involved in glycan biosynthesis metabolism and biosynthesis of other secondary metabolites, thereby decreasing the available contents of heavy metals after 90 days. However, the shifts in bacterial community structure and function were subsequently partially recovered after 180 days. Conversely, repeated SG treatments led to minimal alterations after 90 days while leading to similar shifts in the bacterial community at 60 mg kg−1 after 180 days. The fungal community structure remained largely unaltered across all SG treatments. Intriguingly, SG treatments substantially stimulated fungal biomass, with the stimulation degree dependent on SG dosage. These results provide valuable insights for developing phytoremediation strategies, suggesting tailored SG applications during specific growth phases to optimize remediation efficiency.

Changes in cross-boundary coalescence effects induce the unsynchronized states shift of microbial structure and microbial-mediated nitrogen-cycle pathways in coupled-ecosystem

Understanding the coalescence of materials and microorganisms across pre-configured functional zones in coupled ecosystems is crucial for refining ecological restoration strategies. Deciphering how this coalescence triggers changes in state and functionality is key. However, the emergence of alternative states due to coalescence impacts could lead to abrupt ecological changes near boundaries, with unknown implications. This study focused on a typical coupled ecosystem, constructed wetland (CW), to investigate the impact of coalescence on shifts in aquatic microbial community states. A quantitative method and hierarchical linear models with Bayesian inference were used. Results showed a gradual increase in coalescence from inlet to outlet, with upstream points significantly influencing downstream points (54.13%, 62.35%, 84.03% for each pond). Alternative stable states were found in microbial-mediated nitrogen cycle pathways, leading to a transition from robust denitrification to diminished ammonification and denitrification states. This shift correlated strongly with community cohesion and nitrogen concentration. The observed change in state shift lagged 5% of the total CW length compared to the change in functional states. This research highlights the potential for targeted manipulation of microbial assemblages in CWs for ecological management and restoration.