Search Results (62)

This article presents an interpretable framework for customer segmentation and churn risk detection, integrating fuzzy clustering, explainable AI (XAI), and strategic scoring. The process begins with Fuzzy C-Means (FCM) applied to normalized RFM indicators (Recency, Frequency, Monetary), which were then mapped to a 2-tuple linguistic scale to enhance semantic interpretability. Cluster memberships and centroids were analyzed to identify distinct behavioral patterns. An XGBoost classifier was trained to validate the coherence of the fuzzy segments, while SHAP and LIME provided global and local explanations for the classification decisions. Following segmentation, an AHP-based strategic score was computed for each customer, using weights derived from pairwise comparisons reflecting organizational priorities. These scores were also translated into the 2-tuple domain, reinforcing interpretability. The model then identified customers at risk of disengagement, defined by a combination of low Recency, high Frequency and Monetary values, and a low AHP score. Based on Recency thresholds, customers are classified as Active, Latent, or Probable Churn. A second XGBoost model was applied to predict this risk level, with SHAP used to explain its predictive behavior. Overall, the proposed framework integrated fuzzy logic, semantic representation, and explainable AI to support actionable, transparent, and human-centered customer analytics. Full article

This study examines the evolution of public debt among the 27 EU member states using Graph Theory tools; the Threshold Weighted–Minimum Dominating Set (TW–MDS) and the k-core decomposition method, alongside a standard network quantitative metric, the density. By separating the data into three distinct periods, pre-crisis (2000–2007), European sovereign debt crisis (2008–2015), and post-crisis (2016–2023), we examine the potential synchronization of the debt ratios among EU countries through cross-correlations of the public debts. The findings reveal that public debt correlation was at its highest level during the 2008–2015 period, reflecting the universal impact of the crisis and the subsequent synchronized fiscal and monetary policy measures taken within EU. A significantly lower network density is observed in both the pre- and post-crisis periods. These results contribute to the overall debate on fiscal stability and policy coordination by showing how EU countries tend to align their fiscal behaviors during periods of crisis while behaving more independently during stable times. In addition, we yield a deeper insight into how economic shocks reorganize public debt interconnections within the crisis period. Finally, this analysis highlights to what extent European economic integration strengthens connections between the fiscal positions (through public debt) of the European Union member countries. Full article

This paper investigates Bitcoin’s resilience against the U.S. dollar—widely recognized as the global reserve currency—by applying a multi-method wavelet analysis framework to daily price data of Bitcoin, the USD strength index (DXY), the euro, and other assets ranging from August 2015 to June 2024. Quantitative measures—particularly the Frobenius norm of wavelet coherence and an exponential decay phase-weighting scheme—reveal that Bitcoin’s out-of-phase relationship with the dollar is lower and more sporadic than that of mainstream assets, indicating it is not tightly governed by dollar fluctuations. Even after controlling for the euro’s dominant influence in the DXY, BTC continues to show weaker coupling than mainstream assets—reinforcing the idea that it may serve as a partial hedge against dollar-driven volatility. These results support the hypothesis that Bitcoin may serve as a resilient store of value and hedge against dollar-driven market volatility, placing Bitcoin within the broader debate on global monetary frameworks. As global monetary conditions evolve, the resilience of Bitcoin (BTC) relative to the world’s leading reserve currency—the U.S. dollar—has significant implications for both investors and policymakers. Full article

The environmental impact of beef cattle production varies significantly across farming systems, influenced by factors like feed, management practices, and land use. By applying the LCA perspective with “from cradle to farm gate” boundaries and using the CAP’2ER^® tool, this study evaluates the carbon footprint of two farming models in Italy: a semi-extensive cow-calf beef production and an intensive farm for calf fattening. The carbon footprint was calculated using two functional units: kilograms of live meat gross production (LMGP), and a monetary unit. The first model showed a lower carbon footprint, with 13.4 kg CO₂eq/kg LMGP and 1.96 kg CO₂eq/EUR, compared to the second one 19.2 kg CO₂eq/kg LMGP and 5.20 kg CO₂eq/EUR. The use of monetary value as a functional unit is rarely explored in the literature, since most studies have focused on weight-based metrics, favoring intensive systems with longer lifecycles compared to extensive farming. Furthermore, contrary to findings in the literature for semi-extensive systems like adaptive multi-paddock grazing, the tool used for the calculation did not detect any carbon sequestration. These findings highlight the need for further investigation into diverse functional units to assess the environmental and economic performance of farming systems. Expanding this approach could inform policies and consumer decisions, promoting sustainable beef production aligned with climate goals and the European Green Deal agenda. Full article

The prevalence of overweight and obesity is increasing worldwide. Common comorbidities related to obesity, significantly polygenic disorders, cardiovascular disease, and heart conditions affect social and monetary systems. Over the past decade, research in drug discovery and development has opened new paths for alternative and conventional medicine. With a deeper comprehension of its underlying mechanisms, obesity is now recognized more as a chronic condition rather than merely a result of lifestyle choices. Nonetheless, addressing it solely through lifestyle changes is challenging due to the intricate nature of energy regulation dysfunction. The Federal Drug Administration (FDA) has approved six medications for the management of overweight and obesity. Seaweed are plants and algae that grow in oceans, rivers, and lakes. Studies have shown that seaweed has therapeutic potential in the management of body weight and obesity. Seaweed compounds such as carotenoids, xanthophyll, astaxanthin, fucoidans, and fucoxanthin have been demonstrated as potential bioactive components in the treatment of obesity. The abundance of natural seaweed bioactive compounds has been explored for their therapeutic potential for treating obesity worldwide. Keeping this view, this review covered the latest developments in the discovery of varied anti-obese seaweed and its bioactive components for the management of obesity. Full article

In the context of transportation development, the simultaneous emergence of automated vehicles (AVs) and human-driven vehicles (HDVs) can lead to varied traffic system performance. For the purpose of improving traffic systems, this paper proposes a traffic restriction scheme only for HDVs. We develop a variational inequality (VI) model to describe travel mode and route choices under this restriction scheme and design an algorithm to solve the model. The proposed model and algorithm are applied to a Sioux Falls network example to evaluate the effects of the traffic restriction scheme. Our findings indicate that the scheme improves overall social welfare, with a higher proportion of restricted travelers leading to greater social welfare as well as increased travel demand due to changes in capacity. However, some lower exogenous monetary factors lead to negative social welfare, as the presence of AVs may exacerbate road congestion. Additionally, advancements in technology are needed to adjust the weightings of travel time and congestion level estimates to further enhance social welfare. These results offer valuable insights for traffic demand management in traffic systems with a mix of AVs and HDVs. Full article

Rapid development of urbanization and intense human activities had a profound influence on the ecosystem service functions. As an integrated monetary index for the evaluation of final ecosystem services, the gross ecosystem product (GEP) is widely used in the quantification of ecosystem service value (ESV). This study initially assessed and analyzed the spatial distribution of the GEP at the county-level scale using multisource data spanning 2000, 2005, 2010, 2015, and 2020. Then, the spatial transfer characteristics of the GEP were measured. Finally, the study employed spatial panel econometric models and the geographically weighted regression (GWR) model to investigate the spatial effect of urbanization and ecological construction on the GEP. The results indicated that: (1) In 2020, the GEP in the Yangtze River Delta Region was RMB 15.24 trillion, and the GEP per unit area was RMB 42.58 million per square kilometer. It exhibited a cumulative decrease of RMB 298.72 billion from 2000 to 2020. (2) The spatial transfer efficiency of the GEP in urban agglomerations showed a clear decline trend. During the period of 2000–2020, over 96% of county-level units exhibited a decline with RMB 90,076,103.17/km², indicating a consistent downward trend from the central regions towards the periphery. (3) Based on the decomposition effects of the spatial Durbin mode, urbanization and the ecological construction indicator showed spatial spillover effects on the GEP, but their impact mechanisms varied substantially. Among them, the urbanization rate (UR), population density (PD), and the proportion of impervious land (ILP) had the largest negative effect on the GEP, and a 1% rise in ILP locally resulted in a 0.044% decline in the local GEP and a 0.078% rise in the GEP of neighboring units. And the area of ecological land had a positive effect on the GEP of both local and neighboring areas. Those conclusions can offer evidence in favor of encouraging ecologically responsible building practices and sustainable growth in urban agglomerations. Full article

The aim of the paper is to analyze changes and peculiarities of behavior of economic agents with bounded rationality in the New Keynesian model, in which imported equipment and technology are one of the factors of production, and households consume only domestic products. The formation of output gap and inflation expectations by agents is based on stationary values of these variables and on extrapolation of the latest available data on inflation and the output gap. The weight shares of agents applying these rules change endogenously. Histograms of the frequency distribution of the degree of buoyancy and the impulse responses of monetary policy shocks and technology shocks to the variables under study show that a less open economy tends to go through an economic cycle with a smaller amplitude than a more rigid economy. Analyses of the trade-offs between the volatility of inflation and the output gap at different parameter values in the Taylor rule show their non-linear nature (in contrast to standard models with rational expectations). An important result obtained in this analysis is that the rational expectations hypothesis is more consistent with a closed economy than with an open one. Full article

In recent years, application of bio-fertilizers (BFs) in intercropping systems has become known as one of the main sustainable and eco-friendly strategies for improving the quantity and quality of forage crops. In order to evaluate the forage quantity and quality of sorghum intercropped with soybean, a two-year field experiment was carried out as factorial based on a randomized complete blocks design (RCBD) with three replications. The first factor was different cropping patterns including soybean monocultures with densities of 40 and 50 plants m⁻² (G40 and G50), sorghum monocultures with densities of 10 and 15 plants m⁻² (S10 and S15) and intercropping of two plants with the mentioned densities. The second factor was non-application (control) and application of bio-fertilizers. The results demonstrated that the highest dry forage yield of sorghum (21.22 t ha⁻¹) was obtained in monoculture conditions with density of 15 plants m⁻² and inoculation with bio-fertilizer (S15+BF). The maximum crude protein (CP = 149.6 g kg⁻¹ DM), ash (113.2 g kg⁻¹ DM), water soluble carbohydrates (WSC = 251.16 g kg⁻¹ DM), dry matter intake (DMI = 26.83 g kg⁻¹ of body weight), digestible dry matter (DDM = 668.01 g kg⁻¹ DM), total digestible nutrients (TDN = 680.42 g kg⁻¹ DM), relative feed value (RFV = 142.98%) and net energy for lactation (NEL = 1.625 Mcal kg⁻¹) were observed in the intercropping of S10G50 inoculated with BF. Interestingly, application of bio-fertilizers enhanced the content of CP, ash, WSC, DMI, DDM, TDN, RFV and NEL by 7.5, 8, 11.7, 3.6, 2.3, 12.3, 5.9 and 3.5% when compared with the control (non-application of bio-fertilizers). In all intercropping patterns, the total land equivalent ratio (LER) value was greater than one, representing the advantage of these cropping patterns in comparison with sorghum monoculture. The highest total LER was recorded in the intercropping of S15G40 and S10G50 following application of BF. Additionally, the highest monetary advantage index (MAI) was calculated in the intercropping of S15G40+BF. Generally, it can be concluded that the intercropping of S10G50 along with bio-fertilizer inoculation could be suggested as an eco-friendly strategy for improving the forage quantity and quality under low-input conditions. Full article

The recent energy shortfall in Pakistan has prompted the need for the development of hydropower projects to cope with the energy and monetary crisis. Hydropower in the northern areas is available yet has not been explored too much. Focusing on the sustainable development goal (SDG) “Ensure access to affordable, reliable, sustainable and modern energy”, thirteen proposed sites were selected from upstream to downstream of the Hunza River for analysis. The head on all the proposed sites was determined by taking the elevation difference between the proposed turbine and the intake at all sites. The discharge on all proposed ungauged sites was determined using ArcGIS for watershed delineation and the area ratio method along with Soil Conservation Service–Curve Number (SCS-CN) by using gauged data of Hunza River provided by Water and Power Development Authority (WAPDA) Pakistan at Daniyor bridge Gilgit, Shimshal and the Passo tributaries of Hunza River. The Location Search Algorithm (LSA) approach used a multi-criteria decision-making tool (MDM) to make a decision matrix considering the location and constraint criteria and then normalizing the decision matrix using benefit and cost criteria, the relative weights were assigned to all criteria using a rank sum weighted method and the sites were ranked on the basis of the final score. The results revealed that Hunza River has a significant hydropower potential and based on the final score in the LSA approach, proposed site 13, site 4 and site 9 were concluded as the most promising sites among proposed alternatives. The proposed methodology could be an encouraging step for decision makers for future hydropower development in Pakistan. Full article

The aim of our paper is to construct a multidimensional financial inclusion (FI) index to measure the level of FI in 91 countries across different income groups. In order to address our research problem, we use the principal component analysis method. This approach addresses the criticism of the arbitrary selection of weights and reflects the degree of financial inclusion in depth. The data are drawn from the International Monetary Fund (IMF) Financial Access Survey (FAS), the World Development Indicators (World Bank) and the Global Findex Database during the period of 2004–2020. This paper is the first to consider so many indicators of financial inclusion (13 indicators), belonging to three different dimensions of FI, in order to take into account the maximum number of aspects related to this concept. In addition, unlike previous work, this paper considers both developing and developed countries, which makes it possible to identify differences between them. The proposed index has some advantages. First, it is robust, comparable across countries and has good predictive power in tracking household microeconomic indicators (accounts and savings). It is also well correlated with macroeconomic variables such as literacy rate, poverty, GINI index, real interest rate and employers. Second, our results clearly show that, as a country’s income level grows higher, its level of financial inclusion also grows higher. Full article

As global inflation escalates and geopolitical conflicts exacerbate, the world’s economy confronts an intensified degree of instability. In this volatile environment, blockchain currencies emerge as a potential bulwark, offering both value preservation and liquidity benefits. However, the conventional “mining” process introduces significant challenges, such as high energy consumption, data security risks, and detachment from the real economy, which potentially facilitate financial capital manipulation. This research endeavors to mitigate these issues, constructing an innovative blockchain cryptocurrency framework that integrates mining and distribution with intelligent big data. It also incorporates social contributions from individuals in domains such as health, knowledge, and ecological conservation. Consequently, the efficiency of cryptocurrency production and distribution correlates with the individual’s societal contribution. The more substantial the contribution, the higher the intrinsic value of the individual and the more efficient the access. Utilizing a comprehensive framework of mathematical modeling, computer numerical simulation, and fuzzy integrated evaluation, we propose a novel endogenous-value blockchain cryptocurrency system. We quantify and optimize variables such as individual intrinsic value, community efficiency, redistribution weights, and total monetary potential. We introduce an innovative method for accumulating time-decaying values such as knowledge contribution and establish an anti-cheating framework. Our results indicate that this pioneering approach can significantly enhance mining efficiency and optimize cryptocurrency distribution. This counters traditional criticisms of blockchain currencies and paves the way for a more sustainable, fair, and efficient model for future blockchain currency systems. Full article

The intercropping patterns of protected cultivations have been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry intercropping cultivated by clean tillage. We introduced 10 forages into wolfberry cultivation through land productivity and an interspecific competitiveness analysis, and we screened out the appropriate intercropping modes to provide a scientific basis for wolfberry green cultivation and pasture production. The results showed that the wolfberry–forage intercropping land equivalent ratio (LER) of greenhouse and field tests increased from 29% to 59% and from 62% to 170%, respectively, when compared with the monoculture weighted mean, showing significant yield advantages (p < 0.05), particularly in wolfberry–mangold, wolfberry–ryegrass, wolfberry–alfalfa, and wolfberry–clover. The aggressivity of interspecific competitiveness analysis showed that the forage introduction did not affect the dominant competitive position of wolfberry. In addition, wolfberry–forage intercropping could promote the monetary advantage index (MAI). Wolfberry–mangold, wolfberry–ryegrass, and wolfberry–alfalfa performed well, with MAI values of 827.63, 994.18, and 1918.57 for fruit and 2106.54, 1706.27, and 3103.13 for biomass, respectively. Finally, wolfberry–mangold, wolfberry–ryegrass, and wolfberry–alfalfa were screened out, which can form a new mode of wolfberry and forage production. Full article

Buildings and constructions are responsible for a great amount of global energy and energy-related carbon dioxide emissions. Because of these negative impacts, there is an increase in Life cycle assessment research in the construction sector to measure these effects and evaluate the sustainability performances. Life cycle assessment is a tool that can facilitate the decision-making process in the construction sector for material selection, or for the selection of the best environmentally friendly option in the building component level or building level. In this study, a comparative life cycle assessment analysis is conducted among 12 roof coverings of 1 square meter in the 60-year lifetime of a building. Impact categories that are available in environmental product declarations and included in this study are the global warming potential, ozone depletion potential, acidification potential, eutrophication potential, photochemical ozone creation potential, abiotic depletion potential of non-fossils and abiotic depletion potential of fossils resources. To facilitate the decision-making process, panel and monetary weightings are applied to convert environmental product declaration data of seven impact categories into one single-score. Monetary weightings applied in the study are in Euro ₂₀₁₉, differentiating itself from other comparative life cycle assessment studies. The single-score results are ranked and compared. R04 has the best performance for all panel weightings, while for monetary weightings, R03, R07 and R08 have the best performance for EPS, MMG and EVR, respectively. As a result, for 12 roof coverings, the weighted results could not address one single roof-covering material for numerous reasons. Among the weighting methods, panel weighting sets show more similarity in ranking results, while monetary-weighting sets results are more diverse. Full article

Wall plaster production induces significant environmental impacts during its entire life as it consumes a high amount of cement and natural resources. Therefore, in sustainable development, industrial wastes are partially replaced to produce cementitious material to reduce environmental impacts. This study aims to identify the optimal environmental benefits from the waste-based cementitious materials that are used to produce wall plaster. Thus, this study involved conducting a comprehensive review of the mechanical and sustainable performance of industrial waste-based cementitious materials focused on wall construction. Then, an experimental test was conducted to ensure the appropriate mix design to enable the required compressive strength. A comparative analysis of mortar showed that it contained 15% (by weight) of fly ash, blast furnace slag, bottom ash, recycled glass, ferronickel slag, expanded polystyrene and wood ash using life-cycle assessment. The results show that mortar containing fly ash has lower environmental impacts in almost all impact categories (i.e., human health, the ecosystem and natural resources). Endpoint damage assessment of mortar mixtures expresses resource extraction cost as the most affected impact criteria. The replacement of globally consumed cement with 15% fly ash can contribute to monetary savings of up to USD 87.74 billion. The assessment clarifies the advantage of incorporating waste products in cement mortar, which allows policymakers to interpret the analysis for decision making. This study also found that the production of industrial wastes for mortar mixes has a significant impact on the environment. Full article