Search Results (15)

This work deals with questions of enhancing the scalability and security of linear chain Bitcoin by introducing a D-BTC (Domino Bitcoin) protocol, supported by a simply connected two-dimensional structure. The paper seeks to answer the question: can the linear topology of Bitcoin be replaced by a richer geometric structure that simultaneously (i) enlarges the number of valid positions where parallel mining can occur, and (ii) strengthens the asymptotic decay of the double-spend reversal probability? In the D-BTC protocol, the blocks, called B-dominoes (Bitcoin dominoes) are organized as a finite connected region subset of ${\mathbb{Z}}^2$ without holes, also called a lattice. Simple connectivity plays a central role in D-BTC and to mine a (valid) B-domino, a miner has to compute four PoW (Proof of Work), corresponding to cardinal directions, allowing them to add it to the frontier of the lattice, under the constraint that the new lattice is simply connected. We introduce a new deterministic consensus based on maximization of the lattice surface. By using a simple version of the isoperimetric inequality, we see that the frontier size grows as $\Omega \left(\sqrt{n}\right)$, where n is the lattice size. Following the Nakamoto’s heuristic, and under the honest majority assumption, a double-spending attack is successful with probability decaying exponentially in $k^2$, where k is the minimum Manhattan distance of the concerned B-domino from the lattice frontier. Additionally, we set up implementations and experiments to demonstrate the practical viability of the protocol with authentic gossip-based message propagation and complete Merkle tree verification. Full article

This study deciphers the impacts of urban forests and green spaces (UFGSs) on housing prices through a systematic review of 180 peer-reviewed articles (440 empirical cases) to delineate how various UFGS attributes drive housing price changes, focusing on the direction, intensity, and contextual dependency of these impacts. We identified specific UFGS attributes (e.g., proximity, size, type, quality, accessibility, landscape patterns) and the methodologies assessing their price impacts, primarily hedonic pricing models. Our findings confirm a consistent, albeit highly variable, positive premium from urban forests and related green infrastructure on housing prices. Key drivers include not only proximity and size, but also crucial qualitative attributes like perceived UFGS quality (e.g., tree canopy coverage, wooded park maintenance), which often show stronger or more consistent effects than simple quantitative measures. The analysis also highlights that negative impacts can arise from poorly managed urban forests or certain disamenity-prone green typologies. Significant spatio-temporal heterogeneity is evident, with price effects varying by urban context (e.g., density, development stage) and over time. Socio-economic factors, particularly manifesting as “green gentrification”, which can exacerbate inequalities by disproportionately benefiting higher-income groups, critically moderate these relationships. Furthermore, prevalent non-linear effects (e.g., distance-decay patterns, threshold effects for UFGS size) and complex interactions between different UFGS attributes underscore the nuanced nature of the UFGS–price nexus. This review provides a structured understanding of urban forest and green space capitalization drivers, emphasizing the need for nuanced, evidence-based urban forestry planning and green space management that considers UFGS quality, diversity, and equitable distribution for sustainable urban development. Full article

Given the energy-intensive operations and considerable carbon emissions of offshore oil and gas platforms (OOGPs) in deep-sea regions, adopting floating offshore wind farms (FOWFs) as power sources offers substantial benefits. However, the expenses associated with dynamic submarine cables constitute a substantial portion of the capital expenditure (CAPEX) for this hybrid system, highlighting the crucial need for optimization in the power collection system design. In this study, we present a mixed-integer quadratic programming (MIQP) model designed to reduce both the costs of investment and power losses associated with dynamic submarine cables, taking into account the influence of the wake effect in local wind conditions. Due to the complexity of this problem, we employ the Benders’ decomposition method to reformulate it into a master problem and a slave problem. Additionally, two valid inequalities are specifically incorporated into the master problem to accelerate the solution process. These constraints are derived from a heuristic combination of various cable connection configurations and a greedy-based spanning tree structure. Through multiple case studies, we first demonstrate the accuracy and rapid convergence of our method. Furthermore, we reveal that as the wind farm grows in size, the influence of the wake effect becomes increasingly pronounced. Full article

Vegetation in residential areas plays a crucial role in biodiverse and sustainable cities as it enhances biological diversity, environmental quality, and the human well-being of city residents. However, the distribution of vegetation among these areas is often unequal, leading to disparities in access to its benefits. To promote a more biodiverse and environmentally just city, we investigated how woody plants (trees, shrubs and vines) vary with socioeconomic level in residential streetscapes of Santiago de Chile. Across the city, we sampled woody plants in 120 plots (11 m radius) located in residential streetscapes of three socioeconomic levels: low, medium, and high. A total of 557 woody plants were identified and measured. Of these, only 9.7% corresponded to native species, whereas 90.3% were introduced species. Wealthier residential areas had higher species richness and abundance of woody plants, as well as plants with greater structural size (revealed by height and crown area). In addition, we found that the composition of woody plants differed among socioeconomic levels: Liquidambar styraciflua, Platanus x hispanica, and Pittosporum tobira were more abundant in high socioeconomic areas; Prunus cerasifera, Citrus limon, and Ailanthus altissima were more abundant in medium socioeconomic areas; Robinia pseudoacacia, Acer negundo, and Schinus areira were more abundant in low socioeconomic areas. Our research highlights that woody plant diversity, abundance, structure, and composition vary with socioeconomic level in residential streetscapes. Key insights for reducing these inequalities and achieve a more environmentally just city include: (a) governance and equity-based investment; (b) prioritizing local native species; (c) promoting the use of non-tree woody plants; and (d) empowering communities through capacity building and stewardship. Full article

Enhancing forest biodiversity and carbon sinks in the face of climate change is a high priority on the global agenda. The aim of our study was to explore the feasibility and potential of enhancing biodiversity and stand biomass productivity, which are strongly linked to forest ecosystem functioning and services in temperate forests. Based on data from the 5th to 7th National Forest Inventory of South Korea, 1760 natural forest plots (0.16 ha) were used, of which 344 plots belonged to conifer stands, 711 plots belonged to broadleaved stands, and 705 plots belonged to mixed stands. Forest succession-related factor (i.e., stand age), and abiotic (i.e., climatic and topographic conditions, and soil properties) and biotic drivers (i.e., species diversity, functional trait diversity, functional trait identity, and stand structural diversity) were jointly included as independent variables in an integrated model to explain variations in stand biomass productivity. In order to reveal the key drivers and relationships that regulate stand biomass productivity across forest stand types, we applied a multi-model averaging approach and piecewise structural equation modelling (pSEM). As a key finding, across all forest stand types, forest stand age-induced tree size inequality (i.e., DBH STD) in all forest stand types commonly increased stand biomass productivity, showing strong positive standardized effects (β > 0.5, p < 0.001). We also found that the functional trait identities controlling stand biomass productivity within each forest stand type differed according to their functional traits of dominant species, and that these mechanisms were controlled directly or indirectly by environmental conditions. Our research suggests that appropriate forest management plans should be developed in accordance with environmental gradients to simultaneously promote biodiversity and stand biomass productivity in different forest stand types. Full article

This paper presents a heuristic methodology for the optimal expansion of unbalanced three-phase distribution systems in rural areas, simultaneously addressing feeder routing and conductor sizing to minimize the total annualized cost—defined as the sum of investments in conductors and operational energy losses. The planning strategy explores two radial topological models: the Minimum Spanning Tree (MST) and the Steiner Tree (ST). The latter incorporates auxiliary nodes to reduce the total line length. For each topology, an initial conductor sizing is performed based on three-phase power flow calculations using Broyden’s method, capturing the unbalanced nature of the rural networks. These initial solutions are refined via four metaheuristic algorithms—the Chu–Beasley Genetic Algorithm (CBGA), Particle Swarm Optimization (PSO), the Sine–Cosine Algorithm (SCA), and the Grey Wolf Optimizer (GWO)—under a master–slave optimization framework. Numerical experiments on 15-, 25- and 50-node rural test systems show that the ST combined with GWO consistently achieves the lowest total costs—reducing expenditures by up to 70.63% compared to MST configurations—and exhibits superior robustness across all performance metrics, including best-, average-, and worst-case solutions, as well as standard deviation. Beyond its technical contributions, the proposed methodology supports the United Nations Sustainable Development Goals by promoting universal energy access (SDG 7), fostering cost-effective rural infrastructure (SDG 9), and contributing to reductions in urban–rural inequalities in electricity access (SDG 10). All simulations were implemented in MATLAB 2024a, demonstrating the practical viability and scalability of the method for planning rural distribution networks under unbalanced load conditions. Full article

The concept of energy burden (EB) continues to gain prominence in energy and associated policy research as energy prices rise and electricity and heating options diversify. This research offers a deeper understanding of EB dynamics and how EB can be addressed more effectively by discerning the interplay between regional environmental, social, and economic factors. Using decision trees (DTs), a powerful machine learning technique, we explore the multifaceted dynamics that shape EB across the United States (U.S.) by examining how factors like housing quality, demographic variations, access to energy sources, and regional economic conditions interact, creating distinct EB profiles across communities. Following a comprehensive review of existing literature and DT analysis, we map the results to identify the most significant factors influencing EB. We find that no single variable has a determinant effect on EB levels. While there is no uniform regional pattern, regions with higher population density exhibit a stronger correlation between EB and socioeconomic and other demographic factors such as educational attainment levels and racial segregation. Our findings underscore the significance of regional ecologies in shaping EB, revealing how localized environmental and economic contexts amplify or mitigate systemic inequities. Specifically, our analysis reveals significant regional disparities, highlighting the need for localized policies and interventions. We find that a one-size-fits-all approach is insufficient and that targeted, place-based strategies are necessary to address the specific needs of different communities. Policy interventions should prioritize energy democracy, address systemic inequities, and ensure universal energy access through participatory planning, financial assistance, and targeted initiatives such as housing rehabilitation, energy efficiency improvements, and incentives for underrepresented communities. Full article

The size–growth relationship (SGR) quantifies growth partitioning among different sized trees in a stand and helps to elucidate stand growth dynamics during stand development. SGR strongly correlates with stand density, stand age, and drought severity. This study focused on larch (Larix principis-rupprechtii (Mayr)) forests with different stand ages (17–19 years, 20–29 years, 30–39 years, and 40–46 years) and stand densities (300–1400 trees·ha⁻¹ and 1400–3300 trees·ha⁻¹) as the research subjects. Employing a linear mixed model, we aimed to quantify the effects of stand density, stand age, and drought index on SGR. The results revealed that the Gini coefficient had a significant variation between high-density and low-density larch stands (p < 0.01). Stand age, stand density, and drought index exerted varying degrees of influence on the growth dominance coefficient (GD) and SGR of larch forests. In stands aged less than 39 years, a pronounced growth advantage of large trees over small trees was evident (typically SGR > 1 and GD > 0), indicating a positive growth dominance stage where large trees dominated. Compared to high-density stands, low-density stands exhibited a notably greater positive growth dominance. After 40 years, the growth stage transitioned to a relatively symmetric stage (SGR approximately equal to 1), with a discernible shift towards a reverse growth dominance stage (GD < 0). Compared to stand density and stand age, the drought index had a more influential effect on SGR. As drought severity increased, SGR increased, amplifying the growth advantage of large trees over small ones. The findings underscored the significance of adjusting stand density and optimizing tree size structure to enhance larch resilience against the warming and drying effects. Full article

Benefits of cultural ecosystem services (CESs) of urban green spaces (UGSs) for human health and general well-being have been widely recognized. Optimizing the landscape structure of green vegetation and improving CES are essential to reduce environmental inequality, and detecting the determinant landscape features that influence CES at multi-scale is the first step. Using partial least squares structural equation modeling (PLS-SEM), we evaluated multiscale effects of vegetation landscape structure of UGS on residents’ perceptions of CES in 40 residential communities in Zhengzhou city, China. According to our results, at the micro-scale level in a single residential community, public activity spaces within green spaces, particularly large size of open spaces, was the most critical factor affecting residents’ perceptions of recreational services, which provided a multifunctional landscape, with opportunities for multiple recreational leisure activities and entertainment. Then, the percentage of vegetation coverage in green spaces, and large vegetation patches that can significantly improve residents’ perceptions of CES and were identified in the natural landscape. At the ecosystem level and species community level, although vegetation structure contributed little to the level of CES, an open vegetation structure with a large area of grass cover was particularly beneficial to increase aesthetic services, and both richness of flowers and ornamental trees improved residents’ spiritual perception. However, our findings suggest that improving the management of green space vegetation is the most effective and direct way of improving CES and resolving environmental inequities between residential communities with different vegetation coverage and infrastructure, and we suggest that future research should explore residents’ subjective perceptions of both vegetation and landscape structure of UGS at larger spatial scale. Full article

Forest aboveground biomass (AGB) plays an important role in regulating the global carbon cycle and is thus an essential component of ecosystem functioning. In the relationships between biodiversity and ecosystem functioning (BEF), studies have shown that many biotic factors (e.g., species, functional traits, and large trees) and abiotic factors have significant impacts on AGB. However, the relative strength of these affecting factors remains unclear. In this study, we analyzed woody plants (diameter at breast height [DBH] ≥ 1 cm) within a 1.6 ha plot in an old-growth subtropical natural forest in southern China. We used structural equation models to test the effects of tree diversity (species, phylogenetic, functional, and size inequality), functional composition, large trees, and environmental factors (topography, soil nutrients, and understory light) on AGB. Our results indicated that size inequality, the community-weighted mean of maximum DBH (CWM_MDBH), and large trees had significant, positive effects on AGB (p < 0.001), while lower soil phosphorus content was found to promote an increase in AGB. Furthermore, large trees, which were mostly composed of dominant tree species, were the main driver of AGB, and the effect of functional composition (e.g., CWM_MDBH) on AGB was substantially reduced by large trees. We argue that the selection effect plays a key role in regulating BEF relationships in subtropical natural forests and conclude that retaining large-diameter trees and dominant species, along with sustaining a complex stand structure, are key measures for improving productivity. Full article

Variability of a microsite contributes to the size hierarchy in tree populations. Tree size symmetry varies with the available growth resources. However, competition hierarchy may not cause size symmetry in tree populations. The identification of mechanisms that determine size hierarchy has ecological significance in the management of a forest stand. Therefore, this study investigated the tree size structure of the Teak stand in the Hilltop and Valley-Bottom stands of the Omo Forest Reserve. A ten-year-old Teak plantation was delineated into Hilltop and Valley-Bottom stands based on topography. Five (30 m × 30 m) sample plots were systematically demarcated on 1 km transects in each stand. Tree stems with diameter at breast height (dbh) ≥ 10 cm were enumerated. Diameter at breast height and total height were measured using Girth tape and Spiegel Relaskop. Stem size inequality, diversity and stand attributes of both stands were evaluated for diameter and height. Data collected were analyzed using descriptive, correlation, regression analysis and t-test at α_0.05. Mean dbh and height in the Valley-Bottom stand (11.30 ± 4.82 cm dbh and 7.26 ± 3.21 m) were not significantly different from the Hilltop stand (10.19 ± 4.62 cm dbh and 7.12 ± 3.88 m). Stem density in the Hilltop stand (1431.0 stems/ha) was higher than in Valley-Bottom stand (1248.0 stems/ha). All distributions expressed unimodality, except the diameter distribution of the Valley-Bottom stand, which expressed bimodality. The inequality was strongly correlated with the diversity indices in dbh and height distributions in the Hilltop and Valley-Bottom stands, respectively. The same mechanism was responsible for the dbh and height structures of the Hilltop and Valley-Bottom stands, respectively. However, different mechanisms were responsible for the dbh and height structures of the Valley-Bottom and Hilltop stands, respectively. Full article

Tree size diversity is an indicator of biodiversity values of a forest. Microsite conditions of a forest determine the survival and growth of trees. However, the contribution of variable habitats to tree size hierarchy and segregation is poorly understood. Tree size variation in a population is caused by different competition mechanisms. Therefore, the size distribution and spatial pattern of trees can identify the process governing resource utilisation in the forest. The objective of the study was to investigate the tree stem structural diversity in the Elephant Camp natural forest in the Omo Forest Reserve. Three and four 0.09 ha sample plots were established in Riparian (RF) and Old-growth forests (OF) in the Elephant Camp natural forest, respectively. The tree stems (Dbh ≥ 5cm) were identified to the species level and enumerated within each plot, and the stem density was computed. The diameter at breast height (Dbh) was measured with diameter tape. Species diversity was assessed using Shannon–Weiner (H’) and Simpson indices (1-D’), while size inequality was assessed using the Gini coefficient (GC), coefficient of variation (CV), H’ and I-D’. The performance of single two- and three-parameter Weibull models was evaluated using Kolmogorov–Smirnov (K-S) chi-square (χ²), root-mean-square error (RMSE), bias and the coefficient of determination (R²). Data were analysed using descriptive statistics. A total of 27 and 24 tree species were identified in RF and OF, respectively. The stem density of RF was significantly higher than that of OF. The values of species diversity (H’, 1-D’) and evenness (E’) were higher in OF than in RF, while richness (Margalef and number of species) was higher in RF than in OF. The Dbh was 38.30 ± 21.4 and 42.87 ± 19.2 cm in Riparian and Old-growth forests, respectively. Size-density distributions of both forests were positively skewed and expressed exponential pattern. The forest types of the Elephant Camp natural forest comprise the same size-density frequency shape but a different proportion of tree sizes and structural diversities. Full article

This paper is focused on the derivation of data-processing and majorization inequalities for f-divergences, and their applications in information theory and statistics. For the accessibility of the material, the main results are first introduced without proofs, followed by exemplifications of the theorems with further related analytical results, interpretations, and information-theoretic applications. One application refers to the performance analysis of list decoding with either fixed or variable list sizes; some earlier bounds on the list decoding error probability are reproduced in a unified way, and new bounds are obtained and exemplified numerically. Another application is related to a study of the quality of approximating a probability mass function, induced by the leaves of a Tunstall tree, by an equiprobable distribution. The compression rates of finite-length Tunstall codes are further analyzed for asserting their closeness to the Shannon entropy of a memoryless and stationary discrete source. Almost all the analysis is relegated to the appendices, which form the major part of this manuscript. Full article

This study presents a new metric for quantifying structural complexity using the diversity of tree damage types in forests that have experienced wind disturbance. Structural complexity studies of forests have to date not incorporated any protocol to address the variety of structural damage types experienced by trees in wind disturbances. This study describes and demonstrates such a protocol. Damage diversity, defined as the richness and evenness of types of tree damage, is calculated analogously to species diversity using two common indices, and termed a ‘Shannon Damage Heterogeneity Index’ (Sh-DHI) and an inverse Simpson Damage Heterogeneity Index (iSi-DHI). The two versions of the DHI are presented for >400 plots across 18 distinct wind disturbed forests of eastern North America. Relationships between DHI and pre-disturbance forest species diversity and size variability, as well as wind disturbance severity, calculated as the fraction of basal area downed in a wind disturbance event, are examined. DHIs are only weakly related to pre-disturbance tree species diversity, but are significantly positively related to pre-disturbance tree size inequality (size diversity). Damage diversity exhibits a robust curvilinear relationship to severity; both versions of the DHI show peaks at intermediate levels of wind disturbance severity, suggesting that in turn structural complexity may also peak at intermediate levels of severity. Full article

Inter-tree competition is considered one of the most important ecological processes of forest development. However, its importance in structuring the spatial patterns of plant communities remains controversial. We collected observational data from two plots in a natural Mongolian Scots pine forest to study the contribution of competition to tree growth, mortality, and size inequality. We used the nearest neighbour method to determine the presence of competition, and unmarked and marked spatial point pattern analyses to test the density-dependent mortality effects and the spatial autocorrelation of tree size. We identified significant positive correlations between tree canopy diameter and nearest neighbour distance in both plots, which were more evident in the denser plot. The pair correlation functions of both plots indicated regular distribution patterns of living trees, and trees living in more crowded environments were more likely to die. However, the mark differentiation characteristics showed weak evidence of a negative spatial autocorrelation in tree size, particularly in the high-density plot. The high mortality rate of suppressed trees and weak asymmetric competition may have accounted for the lack of dissimilarity in tree size. This study showed that inter-tree competition is an important determinant of the development of Mongolian Scots pine forests.
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