Search Results (135)

Urban freshwater ecosystems are exposed to multiple anthropogenic pressures, but their effects on macroinvertebrate communities may vary depending on waterbody type and surrounding land use structure. This study analysed macroinvertebrate communities in three waterbody types of the Belgrade functional urban area. Land use was classified into agricultural, artificial, and semi-natural areas, and evaluated using LUI and HHI indices. A total of 187 macroinvertebrate taxa were recorded, indicating high diversity despite the urban setting. Community composition differed among waterbody types, with non-wadeable rivers characterised by a high proportion of Oligochaeta, wadeable rivers by a greater contribution of insects, and canals by the dominance of crustaceans. Land use further influenced community structure: semi-natural areas were associated with a higher proportion of crustaceans, artificial areas with Chironomidae, and agricultural areas with Oligochaeta. Alpha diversity was highest in wadeable rivers, while beta diversity showed that compositional differences were driven by species turnover. SPEAR indices indicated stress-related differences among waterbody types. CCA showed that community variation was associated with conductivity, temperature, oxygen saturation, pH, BOD, TOC, AOX, and phosphate. Overall, macroinvertebrate communities in the Belgrade urban area are shaped by the combined effects of waterbody type, land use structure, and local environmental conditions. Full article

Human Activity Recognition (HAR) based on Channel State Information (CSI) has attracted considerable attention as a privacy-preserving sensing paradigm. However, CSI-based HAR faces several challenges, including environmental noise, long-range temporal dependencies, and the anisotropic structure of CSI tensors. To address these challenges, this paper presents Wi-CSNet, a lightweight CSI-oriented framework that integrates Discrete Wavelet Transform (DWT) preprocessing, asymmetric-stride convolutions, and a Cross-Scanning State Space Duality (CS-SSD) block derived from Mamba2. DWT preprocessing compresses temporal signals while preserving motion-related trends and reducing input dimensionality. Asymmetric-stride convolutions balance feature scales across heterogeneous CSI dimensions, while the lightweight CS-SSD module captures global dependencies with only a 0.63% parameter overhead. Extensive experiments demonstrate that Wi-CSNet achieves accuracies of 97.81% on HHI, 99.92% on UT-HAR, and 100% on NTU-HAR. These results confirm the effectiveness and robustness of Wi-CSNet for fine-grained CSI-based activity recognition in complex environments. Full article

Background/Objectives: Pneumonia is a leading cause of hospitalization among children in the United States, with a disproportionate burden in certain racial, socioeconomic, and clinical subgroups. The 13-valent pneumococcal conjugate vaccine (PCV13), introduced in 2010, significantly reduced pneumococcal disease overall, but its effect on disparities in all-cause hospitalized pneumonia (AC-hPNA) remains unclear. This study evaluated changes in AC-hPNA rates by age, race, comorbidity profile, and household income (HHI) before and after PCV13 implementation. Methods: A retrospective cohort study using Optum’s de-identified Clinformatics^® DataMart (2007–2019) included children < 18 years. Rates (per 100,000 person-years) and incidence rate ratios were calculated for four periods: pre-PCV13 (2008–2009), peri-PCV13 (2010–2012), post-PCV13#1 (2013–2016), and post-PCV13#2 (2017–2019). Analyses were stratified by age group and, within each, by race, comorbidity profile (low, at-risk), and HHI. Results: Among 10.1 million children, AC-hPNA rates declined by 51–57% from pre-PCV13 to post-PCV13#2 across all age groups, with the largest reductions in children aged <2 years. Declines occurred across all race, comorbidity, and HHI subgroups; however, rates remained several-fold higher among at-risk children. Persistent disparities were observed among Black children < 2 years, children aged 2–5 years with HHI < $50,000, and children aged 6–17 years with HHI of $50,000–$99,999. Conclusions: Substantial reductions in rates of pediatric AC-hPNA were observed in the period subsequent to the introduction of routine PCV13, yet residual disparities persist among children with comorbidities and select racial and income groups. Targeted strategies are needed to address these gaps. Full article

This paper analyses the short-run dynamic relationship between monetary policy and banking market structure in Colombia during a period of post-pandemic inflation and aggressive policy tightening. Using monthly credit portfolio data for 2017–2024, we compute several concentration indicators (the Herfindahl–Hirschman Index (HHI), CRk ratios, and a dominance index) and employ three complementary identification strategies to evaluate the causal effect of monetary policy innovations on banking concentration. First, a structural VAR model identified through sign restrictions finds that contractionary shocks are associated with a short-run increase in banking concentration (median peak response: +0.60 HHI points at h = 3; 90% credible set: [+0.12, +1.16]), contrasting with the negative short-run response obtained under recursive reduced-form identification. Second, an extended VAR including credit portfolio growth as a mechanism variable confirms that contractionary shocks compress aggregate lending but do not generate robust, persistent changes in concentration. Third, local projections with regime-interaction terms formally test the nonlinear mechanisms discussed in the literature and find evidence of state-dependent transmission: the concentration response is larger in the low-inflation regime and attenuates during high-inflation episodes. All estimated effects are transitory and horizon-sensitive, reinforcing a cautious interpretation. The paper contributes new evidence from an emerging economy on the structural consequences of monetary policy and highlights the importance of identification assumptions in determining the direction of this effect. Full article

Economic diversification has become a central policy objective for resource-dependent economies seeking to reduce vulnerability to external shocks. In the case of Saudi Arabia, diversification has gained particular importance within the framework of Vision 2030, which aims to broaden the productive base beyond the oil sector. This study examines the long-run relationship among globalization, economic globalization, government consumption spending, and economic diversification in Saudi Arabia from 1970 to 2022, utilizing the Herfindahl–Hirschman Index (HHI) as a measure of sectoral concentration. The analysis employs the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine both short-run and long-run relationships among the variables. To ensure robustness, the long-run ARDL estimates are cross-validated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR). The results indicate that government spending is significantly associated with greater economic diversification, as reflected by its negative and significant association with the HHI. Domestic credit to the private sector is also positively associated with economic diversification, while foreign direct investment exhibits a weak positive association with diversification. In contrast, both overall globalization and economic globalization are associated with higher sectoral concentration, suggesting that the benefits of global integration for diversification are not automatic. These findings highlight the importance of complementary domestic policies, including support for SMEs, expanded private-sector financing, and innovation-driven investment, to strengthen the relationship between globalization and sustainable economic diversification in Saudi Arabia. Full article

The study aims to identify and analyze the structural distribution of artificial intelligence-based solution (AIBS) application areas in modern enterprises, with particular emphasis on assessing the degree of concentration of reported AI application domains and their potential contribution to sustainable organizational development. The empirical study was conducted in 2025 using a questionnaire survey administered to 325 enterprises. Respondents were allowed to indicate multiple AI application areas, resulting in 668 valid AI application indications. Descriptive statistics, Pareto analysis, and the Herfindahl–Hirschman Index (HHI) were applied to examine the concentration of reported AI application areas. The results indicate that AI applications are unevenly distributed across organizational functions, with the highest concentration occurring in business and management, education, media and marketing, and information technology and cybersecurity. The calculated HHI value of 0.1639 indicates a moderate concentration of AI application areas, suggesting that organizations prioritize selected domains where AI can generate the greatest organizational and strategic value. From the perspective of sustainable development, the findings indicate that AI deployment supports more efficient resource allocation, organizational adaptability, data-driven decision-making, and digital transformation, which constitute important foundations of sustainable enterprise development. The HHI was used exclusively as a structural measure of concentration and does not assess the level, maturity, intensity, or quality of AI implementation within enterprises. Although the findings relate only to the analyzed sample, the study contributes to the literature by introducing a concentration-based analytical perspective on AI application areas and provides practical guidance for organizations seeking to implement AI in ways that support long-term sustainable development. Full article

Background: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) and GLP-1/glucose-dependent insulinotropic polypeptide (GIP) dual agonists have revolutionized the treatment of type 2 diabetes and obesity. The rapid growth in public interest, off-label use, and the emergence of counterfeit drugs underscores the need for timely monitoring of information demand. Objective: The objective of this study is to quantitatively characterize the temporal dynamics, market concentration, seasonality, and semantic structure of Russian-language search queries regarding GLP-1RAs and GLP-1/GIP dual agonists and to assess their correlation with pharmaceutical demand. Materials and Methods: This was a retrospective study of Yandex.Wordstat data from March 2018 to March 2026 (covering 97 months, 27 INNs and brand names). Time series analysis (trends, structural breaks, Seasonal-Trend decomposition based on Loess (STL decomposition)), calculation of the Herfindahl–Hirschman Index (HHI), and semantic analysis of 4562 unique formulations (bigrams, trigrams, Term Frequency–Inverse Document Frequency (TF-IDF), thematic classification, morphological normalization) were performed. Validation was conducted using DSM Group pharmacy sales data. Results: A total of 46.05 million queries were analyzed. Interest in semaglutide increased 215-fold, with the structural break point identified in January 2021. The HHI decreased from 0.311 (indicating a highly concentrated market) to 0.141 (indicating a competitive market). The share of diabetes-related queries did not exceed 0.46%, while the share of weight-loss-related queries reached 13.91%, and the share of commercial-component queries reached 41.1%. Four semantic signatures were identified: brand-dominant (Ozempic), instruction-targeted (Saxenda), dose-commercial (Tirzetta), and instruction-commercial (Trulicity). No statistically significant seasonality was confirmed after adjustment for multiple comparisons. The correlation between search interest and pharmacy sales was the strongest for Tirzetta (r = 0.976; n = 8; p < 0.001) and remained significant after trend removal (first differences: r = 0.819; p = 0.024). Conclusions: Yandex.Wordstat data provide a valuable supplementary source for digital pharmacoepidemiology. A systematic discrepancy was found between registered indications and actual information demand, a finding that has significant implications for pharmacovigilance and healthcare planning. Full article

Climate change is intensifying hydrological extremes, yet most frameworks assess drought and flood hazards independently, limiting integrated risk management. This study proposes a two-dimensional analytical framework to characterize the drought-flood continuum, moving beyond single-index approaches. We introduce the Hydro-Hazard Index (HHI) as a directionality metric (HHI = Flood Severity − Drought Severity) to classify the dominant hazard type, and the Total Severity Index (TSI = Flood Severity + Drought Severity) as a complementary metric to quantify overall hazard magnitude. Analyzing multi-temporal data from 115 hexagonal units (2018–2024), we employed dynamic features (trends, changes, volatility) and four machine learning models to classify areas as “flood-prone” based on validated flood records. Our results show HHI values ranging from −2.44 to 8.81, with 20.9% of areas classified as Flood-Dominated (mean HHI = 4.58) and 79.1% as Normal (mean HHI = 0.76). Crucially, the two-dimensional analysis revealed that areas with identical HHI values can have vastly different TSI values, under scoring the importance of our dual-index approach. Random Forest achieved the highest performance in predicting flood-prone status (Accuracy = 0.913, AUC = 0.967, Recall = 1.00), with flood_volatility as the most important predictor (24.2%). Spatial autocorrelation confirmed strong clustering of high-risk areas (Moran’s I = 0.716, p < 0.001). By analyzing flood and drought as distinct but interacting dimensions, this framework provides a more robust and nuanced tool for integrated risk assessment. While acknowledging limitations related to data availability and the need for further independent validation, the proposed framework supports sustainable water resource management and climate adaptation planning under increasing hydrological uncertainty. Full article

Background/Objectives: Food system assessments in Sub-Saharan Africa have predominantly focused on caloric availability, often overlooking the structural and nutritional quality of the food supply. This study examines what drives and constrains food system transformation in Sub-Saharan Africa under different development pathways, using long-term changes in caloric availability, adjusted protein density, the balance between animal and plant proteins, and the diversification of animal protein sources as the empirical basis for this assessment. Methods: The analysis is based on data from the Food and Agriculture Organization of the United Nations for the period 1961–2023, covering Nigeria, the Republic of the Congo, the Democratic Republic of the Congo, Kenya, South Africa and Ethiopia. A longitudinal approach was applied where data were available, complemented by a recent comparative analysis (2010–2023). Derived indicators include total protein supply, adjusted protein density, the share of animal and plant proteins and the Herfindahl–Hirschman index (HHI) to assess the diversification of animal protein sources. Results: Findings show that increases in caloric availability are not consistently associated with improvements in adjusted protein density or nutritional quality. Significant differences are observed across countries in protein supply levels, structural composition, and diversification patterns. Results reveal heterogeneous trajectories of food systems, from diversified to structurally constrained or highly concentrated systems. Conclusions: Beyond caloric availability, the structure and quality of the food supply are essential for assessing food system performance. Quantitative gains alone do not ensure improved nutritional or sustainable outcomes. The study highlights the importance of considering protein supply structure, diversification and nutritional efficiency in the context of SDG 2 (Zero Hunger) and broader food system transformation. Full article

The article examines the level of concentration in the ESG bond market in Central and Eastern European (CEE) countries over the period 2020–2025. The aim of the study is to assess the structure of this market in terms of value, volume, product composition, and sectoral distribution. The analysis employs the Herfindahl–Hirschman Index (HHI), which enables the measurement of concentration levels across the respective dimensions. The data are sourced from the Environmental Finance Data database. The results indicate that the ESG bond market in the CEE region is characterized by a high degree of geographical concentration, with the dominance of a limited number of countries, namely Poland, the Czech Republic (Czechia), and Hungary. At the same time, a very strong product concentration persists. Green bonds play a predominant role, while other types of instruments remain of limited significance. A high level of concentration is also observed in the structure of issuers and economic sectors. Despite an increase in both the value and number of issuances, no clear diversification of the market has occurred. The findings suggest that the development of the ESG bond market in CEE countries is uneven and is concentrated around a limited number of participants and market segments. Full article

Biliary tract cancers (BTCs), including cholangiocarcinoma and gallbladder cancers, are characterized by their rarity, poor prognosis, limited treatment options, and significant psychosocial burden among affected individuals. Hope and loneliness are known to play significant roles in shaping cancer-related experiences and outcomes; however, their trajectories in the context of rare cancers remain unexplored. The Canadian Cholangiocarcinoma Collaborative (C3) was founded to enhance access to treatment, research, and support for individuals affected by BTC in Canada. This mixed-methods study aimed to measure hope and loneliness among patients and caregivers over time and to gain a deeper understanding of their experiences. A total of 92 patients and 44 informal caregivers, self-, peer-, or physician-referred, consented to participate in this study. Participants completed electronic self-reported measures of hope (Hope Herth Index (HHI), 12 items) and loneliness (UCLA Loneliness scale, 20 items) upon joining C3 (baseline, T0), following the first informational session with a C3 research navigator (T1), and after two to three months (T2). A subsample (n = 14) also participated in two online focus groups. At baseline, participants reported relatively high levels of hope (patients: M = 39.8, SD = 4.9; caregivers: M = 38.9, SD = 4.68), with the HHI ranging from 12 to 48, where higher scores indicate higher hope. They also reported low-to-moderate levels of loneliness (patients: M = 32.13, SD = 9.63; caregivers: M = 36.69, SD = 12.37), with the scale ranging from 20 to 80, where low loneliness: 20–34; moderate: 35–49; moderately high: 50–64; and high: 65–80. At T1, a significant decrease in hope (mean difference [MD] = −1.38, 95% CI [−2.64, −0.11], p = 0.029) and a significant increase in loneliness (MD = 1.75, 95% CI [0.27, 3.23], p = 0.016) were found among patients, with no further significant changes from T1 to T2. Among caregivers, no significant changes were observed from baseline to T1; however, at T2, there was a significant decrease in hope (MD = −2.01, 95% CI [−3.61, −0.40], p = 0.010) and a significant increase in loneliness (MD = 4.54, 95% CI [1.31, 7.77], p = 0.004). No significant differences in hope or loneliness were found between participants who engaged in C3 activities and those who did not. Dyadic analysis revealed significant correlations between patients’ and caregivers’ hope and loneliness at baseline and at T2. Despite the significant changes, findings indicate consistently high levels of hope and low-to-moderate levels of loneliness over time. Focus group analyses further contextualize quantitative findings by highlighting patients’ and caregivers’ experiences in greater depth. The results serve to inform current and future initiatives aimed at providing timely, personalized psychosocial support to patients and caregivers affected by BTC. Full article

Background: While previous research has examined individual aspects of hearing loss, such as perceived hearing handicap, functional hearing ability, or hearing device outcomes, these domains are rarely evaluated together within the same cohort. We aimed to address this gap by providing a multidimensional assessment of hearing-related outcomes and comparing measures of perceived hearing handicap, psychosocial adjustment to hearing loss, functional hearing ability, and device-related benefit between hearing aid, cochlear implant, and bimodal device users. Methods: Cross-sectional data were collected from 749 adults aged ≥40 years using hearing aids (n = 467), cochlear implants (n = 150), or bimodal devices (n = 132), during 2022–2024. Measures of hearing handicap (Hearing Handicap Inventory for the Elderly Screening, HHIE-S), psychosocial responses to hearing loss (Attitudes towards Loss of Hearing Questionnaire, ALHQ), real-world hearing ability (Speech, Spatial and Qualities of Hearing Scale, SSQ), and outcomes of hearing device use (International Outcome Inventory for Hearing Devices, IOI-HD) were collected. Results: After multivariate adjustment, hearing aid users versus bimodal and cochlear implant users had significantly higher ALHQ scores in the domain of negative associations (suggestive of negative attitudes or stigma attached to hearing aid use): 2.22 (0.05) versus 1.92 (0.09) (p = 0.0067) and 1.90 (0.09) (p = 0.0145), respectively. Hearing aid users had significantly higher SSQ spatial scores (better sound localization and spatial perception) compared to bimodal device users (5.13 versus 4.45, p = 0.0254). Total IOI-HD scores were significantly lower in hearing aid users (reflective of irregular, inconsistent daily usage of the device) compared to cochlear implant users (p < 0.0001) and bimodal device users (p = 0.0007). HHIE-S scores were not significantly different between device user groups after multivariate adjustment. Conclusions: This multidimensional approach provides new insight into the heterogeneity of hearing experiences and may help inform more person-centered models of hearing care. Full article

Viticulture is a globally significant economic activity; however, the scientific literature lacks in-depth, long-term studies integrating historical trends with future market concentration projections. This study fills this gap by analyzing global grape production dynamics and market structure over a 63-year period (1961–2023). The detection of structural breaks and the forecasting of yield trajectories using AutoRegressive Integrated Moving Average with Exogenous Variables (ARIMAX) models are crucial for the strategic planning of agricultural resources and enhancing viticultural resilience. Results indicate that while the global population increased 2.58-fold (1961–2023), grape production rose only 1.69-fold, leading to a decline in per capita availability. Although traditional leaders remain dominant, the combined share of the top five producers fell from 60% to 51.8%. The market concentration analysis Herfindahl-Hirschman Index (HHI) = 0.092; the Concentration Ratio (CR₅) = 53.65%) for 2024–2030 suggests a monopolistic competition structure. The arithmetic mean of annual global production for the 2024–2030 period is projected to reach 79.42 million tons. China is expected to lead (23.11%), followed by Italy, the United States, France, and Spain. These findings highlight the necessity of precision viticulture and modern technology to stabilize yields and enhance competitiveness in high-value horticultural markets. Full article

This study examines the relationship between corporate concentration and labour market conditions in Hungary’s food industry over the period 1993–2022. Using industry-level panel data for the four most highly concentrated subsectors, cereals, food processing, oils and fats, and sugar and confectionery, corporate concentration is measured using the Herfindahl–Hirschman Index (HHI), and a two-way fixed-effects panel regression model is employed to assess its association with wage structures, working-time arrangements, and employment composition. The results reveal a statistically significant negative relationship between corporate concentration and both gross monthly earnings and base hourly wages. A 1000-point increase in the HHI is associated with an approximately 10 percent decline in base wages. Higher concentration is also positively associated with greater reliance on part-time employment and increased overtime intensity, alongside a significant reduction in paid leave provision. Importantly, when variables capturing working-time arrangements and employment structure are incorporated into the earnings model, the direct effect of concentration becomes statistically insignificant. This pattern likely reflects the fact that these variables are directly embedded in the determination of gross monthly earnings, suggesting that the effect of concentration operates indirectly through adjustments in working time and employment composition rather than through a purely independent channel. This finding suggests that the impact of concentration on wages operates partly through structural adjustments in compensation systems and increased labour flexibility. Overall, the evidence indicates that corporate concentration in Hungary’s food manufacturing sector does not necessarily reduce nominal earnings but instead reshapes their composition. The role of base wages weakens, while regular bonuses emerge as the primary mechanism of income adjustment, increasing managerial discretion and income volatility. These findings contribute to the literature on labour market monopsony in transition economies and underscore the importance of integrating labour market considerations into competition policy frameworks. Full article

This paper measures China’s role as an “external market provider” by quantifying, for 168 source countries during 2001–2022, the share of each country’s exports absorbed by China and decomposing that share into extensive (product coverage), quantity, and price margins using the Hummels–Klenow framework. To characterize destination-market concentration, we construct an HHI-based network diversification indicator from export-destination shares and interpret it from a complementary information-theoretic perspective, where higher concentration corresponds to lower diversification and stronger dependence. We document the dynamics of China’s market-provision role and estimate an extended gravity-type model with country- and year-fixed effects. The results show that China’s external market-provider role expanded markedly after WTO accession, with growth driven mainly by the quantity margin and, after 2018, increasingly supported by the price margin. Economic proximity and similarity in global value-chain position are associated with stronger China-absorption shares, while greater destination concentration relative to China is associated with lower China-absorption shares. Free trade agreements are linked to stronger, more extensive, and larger margins. Robustness checks based on lagged covariates, additional controls, higher-dimensional fixed effects, Tobit estimation, and winsorization support the main findings. Overall, the paper provides a replicable framework for measuring destination-market pull and shows how China’s import-side role varies across products, regions, and development groups, while using the information-theoretic perspective as a supplementary interpretation of diversification patterns rather than as a separate empirical tool. Full article