Nearest-neighbor Distance Research Articles

Exploring the relationship between seasonal variations of land surface temperature and urban morphological factors in complex urban areas.

The urban heat island effect is an increasingly serious problem in urban areas. Previous studies suggest that spatial variation in the urban land surface temperature (LST) is determined by interactions among urban morphological factors, but few studies have explored the main factors that affect the LST in different seasons in complex urban areas, especially at a fine scale. By considering the central Chinese city of Jinan as an example, we selected 19 parameters related to the architectural morphological factors, ecological basis factors, and humanistic factors and explored their effects on the LST in different seasons. A correlation model was used to identify the key factors and to analyze the main impact thresholds in different seasons. In the four seasons, the 19 factors all had significant correlations with LST. In particular, architectural morphological factors comprising the average building height and high building ratio had significant negative correlations with the LST in the four seasons. The architectural morphological factors comprising the floor area ratio, spatial concentration degree, building volume density, and urban surface pattern index comprising the mean nearest neighbor distance to green land, as well as humanistic factors comprising the point of interest density, nighttime light intensity, and human activity intensity of land surface had significant positive correlations with LST in the summer and autumn. Ecological basis factors made the main contributions to the LST in the spring, summer, and winter, whereas humanistic factors contributed the most in the autumn. The contributions of architectural morphological factors were relatively low in the four seasons. The dominant factors differed in each season but their thresholds had similar characteristics. The results obtained in this study deepen our understanding of the relationships between urban morphology and the urban heat island effect, and provide practical suggestions for improving the urban thermal environment through reasonable building planning and management.

Statistical and clustering analysis of microseismicity from a Saskatchewan potash mine

Microseismicity is expected in potash mining due to the associated rock-mass response. This phenomenon is known, but not fully understood. To assess the safety and efficiency of mining operations, producers must quantitatively discern between normal and abnormal seismic activity. In this work, statistical aspects and clustering of microseismicity from a Saskatchewan, Canada, potash mine are analyzed and quantified. Specifically, the frequency-magnitude statistics display a rich behavior that deviates from the standard Gutenberg-Richter scaling for small magnitudes. To model the magnitude distribution, we consider two additional models, i.e., the tapered Pareto distribution and a mixture of the tapered Pareto and Pareto distributions to fit the bi-modal catalog data. To study the clustering aspects of the observed microseismicity, the nearest-neighbor distance (NND) method is applied. This allowed the identification of potential cluster characteristics in time, space, and magnitude domains. The implemented modeling approaches and obtained results will be used to further advance strategies and protocols for the safe and efficient operation of potash mines.

Sociogenesis in unbounded space: modelling self-organised cohesive collective motion

Maintaining cohesion between randomly moving agents in unbounded space is an essential functionality for many real-world applications requiring distributed multi-agent systems. We develop a bio-inspired collective movement model in 1D unbounded space to ensure such functionality. Using an internal agent belief to estimate the mesoscopic state of the system, agent motion is coupled to a dynamically self-generated social ranking variable. This coupling between social information and individual movement is exploited to induce spatial self-sorting and produces an adaptive, group-relative coordinate system that stabilises random motion in unbounded space. We investigate the state-space of the model in terms of its key control parameters and find two separate regimes for the system to attain dynamical cohesive states, including a Partial Sensing regime in which the system self-selects nearest-neighbour distances so as to ensure a near-constant mean number of sensed neighbours. Overall, our approach constitutes a novel theoretical development in models of collective movement, as it considers agents who make decisions based on internal representations of their social environment that explicitly take into account spatial variation in a dynamic internal variable.

Dynamic Structural Transformations in a Series of Zero-Strain Lithium-Ion Battery Materials: Almost Simultaneous Operando X-ray Diffraction and X-ray Absorption Spectroscopy on Li2ZnTi3O8 and Related Compounds

A series of Li4/3-2x/3ZnxTi5/3-x/3O4 (LZTO) with 0 ≤ x ≤ 0.5 have received considerable interest as a negative electrode material for long-cycle-life lithium-ion batteries. However, their dynamic structural transformations under operating conditions have remained unknown, making an in-depth understanding essential for further improving the electrochemical performance. We, thus, performed almost simultaneous operando X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) studies on x = 0.125, 0.375, and 0.5. The x = 0.5 sample, Li2ZnTi3O8, indicated differences in the cubic lattice parameter between the discharge and charge reactions (δacs), corresponding to the reversible movement of Zn2+ ions between the tetrahedral and octahedral sites. δac was also observed for x = 0.125 and 0.375, although the capacity region exhibiting δac decreased with a decrease in x. For all of the samples, there is no significant difference in the nearest-neighbor distance of the Ti-O bond (dTi-O) between the discharge and charge reactions. We also demonstrated different structural transformations between the micro- (XRD) and atomic (XAS) scales. In the case for x = 0.5, for instance, the maximum microscale change in ac was within +0.29(3)%, whereas at the atomic scale, dTi-O changed by up to +4.8(3)%. Combined with our previous results for ex situ XRD and operando XRD/XAS measurements on other x compositions, the whole structural nature of LZTO, such as correspondence between ac and dTi-O, origins for voltage hysteresis, and zero-strain reaction mechanisms, has been unveiled.

DNA barcoding of Chinese snakes reveals hidden diversity and conservation needs.

DNA barcoding has greatly facilitated studies of taxonomy, biodiversity, biological conservation, and ecology. Here, we establish a reliable DNA barcoding library for Chinese snakes, unveiling hidden diversity with implications for taxonomy, and provide a standardized tool for conservation management. Our comprehensive study includes 1638 cytochrome c oxidase subunit I (COI) sequences from Chinese snakes that correspond to 17 families, 65 genera, 228 named species (80.6% of named species) and 36 candidate species. A barcode gap analysis reveals gaps, where all nearest neighbour distances exceed maximum intraspecific distances, in 217 named species and all candidate species. Three species-delimitation methods (ABGD, sGMYC, and sPTP) recover 320 operational taxonomic units (OTUs), of which 192 OTUs correspond to named and candidate species. Twenty-eight other named species share OTUs, such as Azemiops feae and A. kharini, Gloydius halys, G. shedaoensis, and G. intermedius, and Bungarus multicinctus and B. candidus, representing inconsistencies most probably caused by imperfect taxonomy, recent and rapid speciation, weak taxonomic signal, introgressive hybridization, and/or inadequate phylogenetic signal. In contrast, 43 species and candidate species assign to two or more OTUs due to having large intraspecific distances. If most OTUs detected in this study reflect valid species, including the 36 candidate species, then 30% more species would exist than are currently recognized. Several OTU divergences associate with known biogeographic barriers, such as the Taiwan Strait. In addition to facilitating future studies, this reliable and relatively comprehensive reference database will play an important role in the future monitoring, conservation, and management of Chinese snakes.

Mean nearest-neighbor distance in random 2D binary mixtures

The two-dimensional, mean nearest-neighbor distances, in random sequential addition hard disc computer-generated patterns with mixtures of two circle diameters, have been studied. The mean nearest-neighbor distance at a given area fraction is a quadratic polynomial function of the circle diameter standard deviation. Deviations from the uniform case may be either positive or negative, with large deviations (10–25%) at large circle diameter standard deviations. Nearest-neighbor distance distributions for binary mixture patterns may be well fit by skewed normal distributions.

Efficient generation of random fiber distributions in fiber reinforced composites

This paper proposes a new algorithm to generate representative volume elements (RVEs) with random fiber distribution in fiber reinforced composites (FRC). The proposed algorithm is straightforward and easy to implement based on judging the maximum and minimum distances between a new fiber and existing fibers. The generation results demonstrate that the maximum fiber volume fraction gradually increases and oscillates violently before reaching 78.54% as the fiber radius rises. Moreover, with the increase of RVE size, the maximum fiber volume fraction changes gently when the fiber radius does not exceed 6.5 μm, but it changes dramatically at other fiber radii. Then, the fiber distributions of the generated RVEs are evaluated using the nearest neighbor distance, Ripley’s K function, and pair distribution function. The evaluation results indicate that the fiber distributions present randomness. Lastly, the effective elastic properties of the Carbon/Epoxy unidirectional FRC are predicted using the RVEs generated by the proposed algorithm, the RVEs generated by regularization, and the Mori–Tanaka method. It is found that the prediction using the RVEs generated by the proposed algorithm is more accurate than the regularization, compared with the Mori–Tanaka and experiment results. The proposed algorithm contributes to microstructure modeling in computational micromechanics.

Monte Carlo modeling of hepatic steatosis based on stereology and spatial distribution of fat droplets

Background and ObjectiveTo model hepatic steatosis in adult humans with non-alcoholic fatty liver disease based on stereology and spatial distribution of fat droplets from liver biopsy specimens. MethodsHistological analysis was performed on 30 adult human liver biopsy specimens with varying degrees of steatosis. Morphological features of fat droplets were characterized by gamma distribution function (GDF) in both two-dimensional (2D) and three-dimensional (3D) spaces from three aspects: 1) size distribution indicating non-uniformity of fat droplets in radius; 2) nearest neighbor distance distribution indicating heterogeneous accumulation (i.e., clustering) of fat droplets; 3) regional anisotropy indicating inter-regional variability in fat fraction (FF). To generalize the morphological description of hepatic steatosis to different FFs, correlation analysis was performed among the estimated GDF parameters and FFs for all specimens. Finally, Monte Carlo modeling of hepatic steatosis was developed to simulate fat droplet distribution in tissue. ResultsMorphological features, including size and nearest neighbor distance in 2D and 3D spaces as well as regional anisotropy, statistically captured the distribution of fat droplets by the GDF fit (R2 > 0.54). The estimated GDF parameters (i.e., scale and shape parameters) and FFs were well correlated, with R2 > 0.55. In addition, simulated 3D liver morphological models demonstrated similar sections to real histological samples both visually and quantitatively. ConclusionsThe morphology of hepatic steatosis is well characterized by stereology and spatial distribution of fat droplets. Simulated models demonstrate similar appearances to real histological samples. Furthermore, the model may help understand MRI signal behavior in the presence of liver steatosis.

Disordered Heterogeneous Universe: Galaxy Distribution and Clustering across Length Scales

The studies of disordered heterogeneous media and galaxy cosmology share a common goal: analyzing the disordered distribution of particles and/or building blocks at microscales to predict physical properties of the medium at macroscales, whether it be a liquid, colloidal suspension, composite material, galaxy cluster, or entire Universe. The theory of disordered heterogeneous media provides an array of theoretical and computational techniques to characterize a wide class of complex material microstructures. In this work, we apply them to describe the disordered distributions of galaxies obtained from recent suites of dark matter simulations. We focus on the determination of lower-order correlation functions, void and particle nearest-neighbor functions, certain cluster statistics, pair-connectedness functions, percolation properties, and a scalar order metric to quantify the degree of order. Compared to analogous homogeneous Poisson and typical disordered systems, the cosmological simulations exhibit enhanced large-scale clustering and longer tails in the void and particle nearest-neighbor functions, due to the presence of quasi-long-range correlations imprinted by early Universe physics, with a minimum particle separation far below the mean nearest-neighbor distance. On large scales, the system appears hyperuniform, as a result of primordial density fluctuations, while on the smallest scales, the system becomes almost antihyperuniform, as evidenced by its number variance. Additionally, via a finite-scaling analysis, we compute the percolation threshold of the galaxy catalogs, finding this to be significantly lower than for Poisson realizations (at reduced density ηc=0.25 in our fiducial analysis compared to ηc=0.34), with strong dependence on the mean density; this is consistent with the observation that the galaxy distribution contains voids of up to 50% larger radius. However, the two sets of simulations appear to share the same fractal dimension on scales much larger than the average intergalaxy separation, implying that they lie in the same universality class. We also show that the distribution of galaxies is a highly correlated disordered system (relative to the uncorrelated Poisson distribution), as measured by the τ order metric. Finally, we consider the ability of large-scale clustering statistics to constrain cosmological parameters, such as the Universe’s expansion rate, using simulation-based inference. Both the nearest-neighbor distribution and pair-connectedness function (which includes contributions from correlation functions of all order) are found to considerably tighten bounds on the amplitude of quantum-mechanical fluctuations from inflation at a level equivalent to observing 25 times more galaxies. The pair-connectedness function in particular provides a useful alternative to the standard three-particle correlation, since it contains similar large-scale information to the three-point function, can be computed highly efficiently, and can be straightforwardly extended to small scales (though likely requires simulation-based modeling). This work provides the first application of such techniques to cosmology, providing both a novel system to test heterogeneous media descriptors and a tranche of new tools for cosmological analyses. A range of extensions are possible, including implementation on observational data; this will require further study on various observational effects, necessitating high-resolution simulations.6 MoreReceived 16 July 2022Revised 2 January 2023Accepted 10 January 2023DOI:https://doi.org/10.1103/PhysRevX.13.011038Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasLarge scale structure of the UniverseGravitation, Cosmology & AstrophysicsInterdisciplinary Physics

DNA barcoding of the genus Alburnoides Jeitteles, 1861 (Actinopterygii, Cyprinidae) from Anatolia, Turkey

The present study investigated the ability of DNA barcoding to reliably identify the endemic freshwater species in Turkey, known as biodiversity hotspots. The barcode region (652 bp) of the mitochondrial cytochrome c oxidase subunit I (COI) was used to barcode 153 individuals from 13 morphologically identified species of the genus Alburnoides. Based on the Kimura two-parameter (K2P) evolution model, the average interspecific distance (0.0595) was 31-fold higher than the average intraspecific distance (0.0019). There was a clear-cut barcode gap (0.0158–0.0187) between maximum intraspecific distance (A. tzanevi and A. velioglui) and minimum nearest-neighbour distance (A. freyhofi and A. kurui) for Anatolian Alburnoides species and a common genetic threshold of 0.0158 sequence divergence was defined for species delimitation. The multiple species delimitation methods (ABGD, ASAP, GMYC and bPTP) revealed a total of 11 molecular operational taxonomic units (MOTUs) for 13 morphospecies. Neighbour-joining (NJ), Maximum Likelihood (ML) and Bayesian Inference (BI) tree analysis indicated that all haplotypes were clustered into two major clades, which corresponded to eleven Alburnoides species clusters, with strong bootstrap support. Furthermore, all the specimens clustered in concurrence with the morpho-taxonomic status of the species, except for two species (A. coskuncelebii and A. emineae) that were morphologically differentiated, but showed overlap in variation for COI-based DNA barcode data with other species. Overall, present results identified that COI-based DNA barcoding is effective for species identification and cataloguing of genus Alburnoides in Turkey.

A possible signature of the influence of tidal perturbations in dwarf galaxy scaling relations

ABSTRACT Dwarf galaxies are excellent cosmological probes, because their shallow potential wells make them very sensitive to the key processes that drive galaxy evolution, including baryonic feedback, tidal interactions, and ram pressure stripping. However, some of the key parameters of dwarf galaxies, which help trace the effects of these processes, are still debated, including the relationship between their sizes and masses. We re-examine the Fornax Cluster dwarf population from the point of view of isomass-radius–stellar mass relations (IRSMRs) using the Fornax Deep Survey Dwarf galaxy Catalogue, with the centrally located (among dwarfs) $3.63 \mathcal {M}_{\odot }$ pc−2 isodensity radius defining our fiducial relation. This relation is a powerful diagnostic tool for identifying dwarfs with unusual structure, as dwarf galaxies’ remarkable monotonicity in light profile shapes, as a function of stellar mass, reduces the relation’s scatter tremendously. By examining how different dwarf properties (colour, 10th nearest neighbour distance, etc.) correlate with distance from our fiducial relation, we find a significant population of structural outliers with comparatively lower central mass surface density and larger half-light-radii, residing in locally denser regions in the cluster, albeit with similar red colours. We propose that these faint, extended outliers likely formed through tidal disturbances, which make the dwarfs more diffuse, but with little mass-loss. Comparing these outliers with ultra-diffuse galaxies (UDGs), we find that the term UDG lacks discriminatory power; UDGs in the Fornax Cluster lie both on and off of IRSMRs defined at small radii, while IRSMR outliers with masses below $\sim 10^{7.5} \mathcal {M}_{\odot }$ are excluded from the UDG classification due to their small effective radii.

Increased water temperature and turbidity act independently to alter social behavior in guppies (Poecilia reticulata).

Changes in environmental conditions can shift the costs and benefits of aggregation or interfere with the sensory perception of near neighbors. This affects group cohesion with potential impacts on the benefits of collective behavior such as reduced predation risk. Organisms are rarely exposed to one stressor in isolation, yet there are only a few studies exploring the interactions between multiple stressors and their effects on social behavior. Here, we tested the effects of increased water temperature and turbidity on refuge use and three measures of aggregation in guppies (Poecilia reticulata), increasing temperature and turbidity in isolation or in combination. When stressors were elevated in isolation, the distribution of fish within the arena as measured by the index of dispersion became more aggregated at higher temperatures but less aggregated when turbidity was increased. Another measure of cohesion at the global scale, the mean inter-individual distance, also indicated that fish were less aggregated in turbid water. This is likely due to turbidity acting as a visual constraint, as there was no evidence of a change in risk perception as refuge use was not affected by turbidity. Fish decreased refuge use and were closer to their nearest neighbor at higher temperatures. However, the nearest neighbor distance was not affected by turbidity, suggesting that local-scale interactions can be robust to the moderate increase in turbidity used here (5 NTU) compared with other studies that show a decline in shoal cohesion at higher turbidity (>100 NTU). We did not observe any significant interaction terms between the two stressors, indicating no synergistic or antagonistic effects. Our study suggests that the effects of environmental stressors on social behavior may be unpredictable and dependent on the metric used to measure cohesion, highlighting the need for mechanistic studies to link behavior to the physiology and sensory effects of environmental stressors.

Local stability and long distance reliability of tongue ultrasound spline metrics

Tongue ultrasound data arecommonly analyzed by using different metrics. In this study, we evaluate the local stability and long distance reliability of Average Nearest Neighbour Distance (Zharkova and Hewlett, 2009), Median Point-by-Point Distance (Palo, 2020), Procrustes analysis and Modified Curvature Index (Dawson et al., 2015). A metric which has good local stability should map a time-series of splines to a smooth scalar (or vector) time-series and not be very sensitive to small errors in the splining. Similarly, a metric with good long distance reliability should differentiate dissimilar tongue contours—such as different phoneme targets—reliably and without small splining errors significantly affecting the results. We test the metrics with simulated data generated from actual spline data. First, we select keyframes at phoneme target positions. Second, we vary the sampling frequency artificially by interpolating the splines between the keyframes. Third, we vary the level of splining noise by adding small perturbations to the splines at varying magnitudes and frequencies. Based on the simulation results, we will calculate the distributions of each of the metrics as conditioned by sampling frequency and noise level. The code and simulation data will be publicly available.

Influence of Cr-content on the local atomic structure of Fe–Cr alloy, a study using EXAFS

High Cr ferritic/martensitic steels are considered one of the most promising structural materials for advanced nuclear power plants. Therefore, understanding properties' evolution under operation conditions is of primary importance. Neutron scattering data and more recent ab initio calculations reveal that magnetism controls the transition from the local short-range ordering of the Cr clustering inside the alloy. The transition coincides with the change in the alloy heat of formation, which shifts from a small area with negative values to a region of positive values at around 10% Cr. This work aims to investigate the effect of Cr composition on the local atomic environment of Fe–Cr alloys. This work employed EXAFS to probe the local environment of Fe–Cr alloys as a function of Cr composition. The results show the anomaly (softening) of the nearest neighbor distance around Cr atom in the 10%Cr. Furthermore, the local atomic disorder around Cr absorbing atoms is larger than Fe atoms.

Natural Flexible and Responsive 2D Photonic Materials with Micro-Sandwich Structure

Here, we report a two-dimensional (2D) amorphous photonic structure (APS) discovered in the central layer of the periostracum of the mussel Perna canaliculus, based on field emission scanning electron microscopy, X-ray diffractometer, attenuated total reflection Fourier transform infrared spectroscopy, and fiber optic spectrometry combined with the image processing technology and pair correlation function analysis. This APS contains ~29% in volume of protein fibers embedded in a protein matrix. These fibers, with diameters of 103 ± 17 nm, are densely arranged and unevenly crimped. In addition, they are locally parallel with each other and exhibit short-range order with a nearest-neighbor distance of 189 nm. Interestingly, the APS is humidity-responsive with a vivid green structural color (~530 nm) in the wet state, which disappears in the dry state. Moreover, the APS is sandwiched by two dense layers in the periostracum, which is flexible in wet and can spontaneously or artificially deform into various shapes. We hope this APS may provide new inspirations for the design and synthesis of 2D amorphous photonic materials.

Antigen footprint governs activation of the B cell receptor

Antigen binding by B cell receptors (BCR) on cognate B cells elicits a response that eventually leads to production of antibodies. However, it is unclear what the distribution of BCRs is on the naïve B cell and how antigen binding triggers the first step in BCR signaling. Using DNA-PAINT super-resolution microscopy, we find that most BCRs are present as monomers, dimers, or loosely associated clusters on resting B cells, with a nearest-neighbor inter-Fab distance of 20–30 nm. We leverage a Holliday junction nanoscaffold to engineer monodisperse model antigens with precision-controlled affinity and valency, and find that the antigen exerts agonistic effects on the BCR as a function of increasing affinity and avidity. Monovalent macromolecular antigens can activate the BCR at high concentrations, whereas micromolecular antigens cannot, demonstrating that antigen binding does not directly drive activation. Based on this, we propose a BCR activation model determined by the antigen footprint.

Thermodynamic and elastic properties of tungsten and tungsten silicide

We present thermodynamic and elastic theory for BCC metal and binary interstitial alloy established by the statistical moment method (SMM) and perform numerical calculations for the silicon concentration, pressure and temperature dependences of nearest neighbor distance, volume, thermal expansion coefficient, heat capacities at constant volume and at constant pressure, Debye temperature, Gruneisen parameter, isothermal elastic modulus, bulk modulus, shearing modulus, elastic constants and longitudinal wave velocity for W and WSi under temperature up to 3600 K, pressure up to 100 GPa and silicon atom concentration up to 5%. The SMM numerical calculations for W are compared with experiments and other calculations. The SMM calculated results for WSi are predictive, orienting experimental results in the future.

Structure-based developmental toxicity and ASD-phenotypes of bisphenol A analogues in embryonic zebrafish

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has become more prevalent in recent years. Environmental endocrine disruptor bisphenol A (BPA) has been linked to ASD. BPA analogues (BPs) are structure-modified substitutes widely used as safer alternatives in consumer products, yet few studies have explored the developmental neurotoxicity (DNT) of BPA analogues. In the present study, we used the larval zebrafish model to assess the DNT effects of BPA and its analogues. Our results showed that many BPA analogues are more toxic than BPA in the embryonic zebrafish assay regarding teratogenic effect and mortality, which may partially due to differences in lipophilicity and/or different substitutes of structural function groups such as CF3, benzene, or cyclohexane. At sublethal concentrations, zebrafish embryos exposed to BPA or BPs also displayed reduced prosocial behavior in later larval development, evidenced by increased nearest neighbor distance (NND) and the interindividual distance (IID) in shoaling, which appears to be structurally independent. An in-depth analysis of BPA, bisphenol F (BPF), and bisphenol S (BPS) revealed macrocephaly and ASD-like behavioral deficits resulting from exposures to sublethal concentrations of these chemicals. The ASD-like behavioral deficits were characterized by hyperactivity, increased anxiety-like behavior, and decreased social contact. Mechanistically, accelerated neurogenesis that manifested by increased cell proliferation, the proportion of newborn mature neurons, and the number of neural stem cells in proliferation, as well as upregulated genes related to the K+ channels, may have contributed to the observed ASD-like morphological and behavioral alterations. Our findings indicate that BPF and BPS may also pose significant risks to ASD development in humans and highlight the importance of a comprehensive assessment of DNT effects for all BPA analogues in the future.

The Evolution Characteristics and Driving Mechanism of Urban Construction Land in Hong Kong since 1972

As an important spatial carrier of Hong Kong’s economic development, construction land provides a critical site for Hong Kong’s economic and social activities. The development of construction land directly affects the sustainable development of the city. Therefore, analysing the spatial and temporal evolution and driving mechanism of construction land in Hong Kong is of great significance in promoting sustainable urban development. This study aimed to evaluate the evolutionary characteristics and driving mechanism of construction land of Hong Kong in the period 1972–2020. Here, we extract construction land data from 1972 based on the historical map of Hong Kong. Then, we apply ArcGIS Pro and Fragstats software to calculate the rate of land expansion, land intensity, change in the centre of gravity, and landscape pattern index of construction land in Hong Kong from 1972–2020. Analysis shows the following: (1) The expansion of construction land in Hong Kong generally showed the characteristics of “rapid at first and then slowing down”, with 2010 as the peak of the 1970–2020 timeframe. (2) The sources of construction land transfer mainly came from cultivated land, sea areas, and forest land, which were mainly distributed in the New Territories. (3) The centre of gravity of construction land in Hong Kong showed the spatial characteristics of “slowly shifting to the northwest” during the study period, indicating that Hong Kong’s polycentric urban structure has been continuously strengthened. (4) The Spiltting index showed a tortuous upward trend, and the index of Mean Euclidean nearest neighbour distance showed a steady downward trend, which indicated that the landscape connectivity of city construction land steadily increased while the degree of fragmentation gradually increased. (5) The driving factors behind the expansion of Hong Kong construction land comes from population, economic, and traffic factors; the support factors come from location and policy factors; the elasticity factors mainly come from reclamation projects; the resistance factors mainly come from the restrictions of environmental protection departments, NGOs, and relevant laws on land reclamation.

Dimensional crossover in the nearest-neighbor statistics of random points in a quasi-low-dimensional system

In this work, we study the effects of geometric confinement on the point statistics in a quasi-low-dimensional system. Specifically, we focus on the nearest-neighbor statistics. Accordingly, we have performed comprehensive numerical simulations of binomial point process on quasi-one-dimensional rectangle strips for different values of the confinement ratio defined as the ratio of the strip width to the mean nearest-neighbor distance. We found that the nearest-neighbor distance distributions (NNDDs) conform to an extreme value Weibull distribution with the shape parameter depending on the confinement ratio, while the process intensity remains constant. This finding reveals the reduction of effective spatial degrees of freedom in a quasi-low-dimensional system under the geometric confinement. The scale dependence of the number of effective spatial degrees of freedom is found to obey the crossover ansatz. We stress that the functional form of the crossover ansatz is determined by the nature of the studied point process. Accordingly, different physical processes in the quasi-low-dimensional system obey different crossover ansatzes. The relevance of these results for quasi-low-dimensional systems is briefly highlighted.