Clustering Phenomenon Research Articles

The valuation of arithmetic Asian options with mean reversion and jump clustering

It is known that the prices of many commodities exhibit mean reversion and are subject to jumps. Particularly, there is mounting empirical evidence that suggests the existence of clustered jumps. In this paper, we consider the valuation problem of arithmetic Asian options under a Hawkes jump diffusion model which captures both the mean reversion and jump clustering phenomena. We compute option prices by means of characteristic functions and Fourier-cosine series expansion. Numerical studies justify the validity and efficiency of our pricing method, and demonstrate the nonnegligible effects of mean reversion and jump clustering on Asian option prices.

Neighborhood scale emerging from the clustering of residential redevelopment applications in the historic district of Macao

The residential building stock constitutes an integral component of densely built-up, historic districts while posing major challenges to urban renewal and conservation. With peninsular Macao being such a case in point, this study aimed to examine the potential interaction of residential redevelopment by analyzing permit application records from 2014 to 2021. First, the covariates of building attributes were collated, and a logistic regression model was fitted to account for the expected effects of building age, building type (single or multiple units), lot area, and the number of units or vacancies on application propensity. Whether a residential site was located within an urban conservation area, however, did not have a significant effect. Second, random-labeling simulations of the inhomogeneous K-function were conducted for the case–control spatial point dataset for the scenarios with and without covariates. The simulation results detected statistically significant clustering, and visual inspection of the simulation envelopes revealed a neighborhood scale. In exploring the determinants of the clustering phenomenon, reference was drawn from local media coverage, while both positivist and constructivist understandings of scale were mobilized to triangulate our findings, which together suggest a nascent coalition of small-scale residential redevelopment situated in the broader arena of planning policy-making and governance.

Associations between healthy lifestyle behavioral patterns and mental health problems: A latent class analysis of 161,744 Chinese young adults

BackgroundYouth mental health problems are a public health priority. Multiple healthy lifestyle behaviors may cluster into healthy lifestyle behavioral patterns (HLBPs) that increase mental health risks in adolescents and older adults, but little is known regarding young adults. This study aimed to explore the associations between cluster HLBPs and mental health problems in young adults. MethodsWe selected 161,744 young adults aged 20–39 as participants from the database of a Chinese general hospital health management center for the years 2015–2020. The latent class analysis was used to identify HLBPs. ResultsA total of 15.0 % of young adults have at least one mental health problem. Five clusters of HLBPs were identified, characterized as low-risk class (1.6 %), moderate-risk class 1 (12.0 %), moderate-risk class 2 (2.1 %), moderate-risk class 3 (56.8 %), and high-risk class (27.4 %). The odds ratios (ORs) for young adults with two mental health problems increased with the risk grade of HLBPs, while the ORs for young adults with one or three mental health problems ranged from high to low according to the risk grade of HLBPs: high-risk class, moderate-risk class 2, moderate-risk class 3, moderate-risk class 1. LimitationsCross-sectional design and no causal conclusions could be drawn. ConclusionYoung adults demonstrated a cluster phenomenon of healthy lifestyle behaviors and significant associations between HLBPs and mental health problems. Young adults with a higher risk grade for HLBPs were more likely to have mental health problems. Different HLBPs should be taken into account when implementing mental health interventions.

Liquid water transport phenomena in the porous transport layer of proton exchange membrane fuel cell based on lattice Boltzmann simulation

The porous transport layer (PTL) of proton exchange membrane fuel cell (PEMFC) plays an important role in water management. The liquid water transport behavior with real density ratio and viscosity ratio is discussed by establishing a multi-relaxation time (MRT) multiphase flow lattice Boltzmann model. The effects of temperature, wettability and microporous layer (MPL) thickness on the water transport process and water distribution are included. As the temperature increased from 278.15 K to 353.15 K, the water saturation in the PTL decreased from 0.501 to 0.219. The breaking phenomenon of water clusters are captured at temperatures of 328.15 K and 353.15 K. The hydrophobic structure has less water content under the ribs and the whole, which is beneficial to the reaction gas transport and the performance improvement of PEMFC. Adding MPL with a thickness of 25 µm can significantly improve water management. However, excessively thick MPL will drive water to flow under the ribs and reduce the permeability of the structure. Appropriate MPL thickness design is a feasible solution to improve water management.

Formation of casein and maltodextrin conjugates using shear and their effect on the stability of total nutrient emulsion based on homogenization

This study aimed to explore the desirable properties of casein and maltodextrin conjugates (PPCs) with simultaneously increased stability of total nutrient emulsion (TNE). Molecular interaction, stability, rheology and microstructure were analyzed. The results exhibited that the D[4,3] of PPCs increased by 169.34% at the shear time of 12 min and zeta-potential increased to 22.56 mV when the shear time was 4 min. The fluorescence spectrum and Raman spectrum analysis showed that the maximum emission wavelength of casein shifted from 347 nm to 336 nm, and the I760 value showed a decreasing trend (0.93–0.41), indicating that the molecular structure of casein stretches and opens under the influence of the shear force, and the hydrophobic groups inside casein are released into the polar environment. Furthermore, the stability index TSI decreases from 1.3 to 0.7, the change rate of backscattered light decreases to 0.6%, and the local particle concentration decreases, suggesting that the stability of the TNE enhanced with the increase of homogenization pressure in a suitable range. Meanwhile, the droplet particles are obviously smaller and there is no cluster phenomenon. After 28 days of storage, the homogeneous pressure of 80 MPa and 100 MPa makes the TNE have smaller TBARS values. This work provides a comprehensive explanation for preparing TNE based on shear and homogenization treatments.

Investigating the Identification and Spatial Distribution Characteristics of Camellia oleifera Plantations Using High-Resolution Imagery

Camellia oleifera is a vital economic crop of southern China. Accurate mapping and monitoring of Camellia oleifera plantations are essential for promoting sustainable operations within the Camellia oleifera industry. However, traditional remote sensing interpretation methods are no longer feasible for the large-scale extraction of plantation areas. This study proposes a novel deep learning-based method that utilizes GF-2 remote sensing imagery to achieve precise mapping and efficient monitoring of Camellia oleifera plantations. First, we conducted a comparative analysis of the performance of various semantic segmentation models using a self-compiled dataset of Camellia oleifera plantations. Subsequently, we proceeded to validate the prediction results obtained from the most effective deep-learning network model for Camellia oleifera plantations in Hengyang City. Finally, we incorporated DEM data to analyze the spatial distribution patterns. The findings indicate that the U-Net++ network model outperforms other semantic segmentation methods when applied to our self-generated dataset of Camellia oleifera plantations. It achieves a recall rate of 0.89, a precision rate of 0.92, and an mIOU of 0.83, demonstrating the effectiveness of the proposed method in identifying and monitoring Camellia oleifera plantations. By combining the predicted results with the data from DEM, we discovered that these plantations are typically situated at elevations ranging from 50 to 200 m, with slopes below 25°, and facing south or southeast. Moreover, a significant positive spatial correlation and clustering phenomenon are observed among the townships in Hengyang City. The method proposed in this study facilitates rapid and precise identification and monitoring of Camellia oleifera plantations, offering significant theoretical support and a scientific foundation for the management and ecological conservation of Camellia oleifera plantations.

JWST uncovers helium and water abundance variations in the bulge globular cluster NGC 6440

We used ultra-deep observations obtained with the NIRCam aboard the James Webb Space Telescope to explore the stellar population of NGC 6440: a typical massive, obscured, and contaminated globular cluster formed and orbiting within the Galactic bulge. Leveraging the exceptional capabilities of this camera, we sampled the cluster down to about five magnitudes below the main sequence turn-off in the (mF115W, mF115W − mF200W) colour–magnitude diagram. After carefully accounting for differential extinction and contamination by field interlopers, we find that the main sequence splits into two branches, each above and below the characteristic knee. By comparing the morphology of the colour–magnitude diagram with a suitable set of isochrones, we argue that the upper main sequence bi-modality is likely due to the presence of a He-enriched stellar population with a helium spread of ΔY = 0.04. The lower main sequence bi-modality can be attributed to variations in the abundance of water (i.e., oxygen) with Δ[O/Fe] ∼ −0.4. This is the first evidence of both helium and oxygen abundance variations in a globular cluster purely based on JWST observations. These results open the window for future in-depth investigations of the multiple population phenomenon in clusters located in the Galactic bulge, which were previously unfeasible with near-UV observations, due to prohibitive reddening and crowding conditions.

Evolution and coupled matching of ecosystem service supply and demand at different spatial scales in the Shandong Peninsula urban agglomeration, China

Ecosystem services are the environmental basis of human living and sustainable development, and the coupled matching of ecosystem service supply and demand (ESSD) plays an important role in socioeconomic and eco-environmental development. As one of the major regions supplying ecological products in China, the Shandong Peninsula urban agglomeration (SPUA) has unique geographical advantages and a strategic position. Based on high-resolution land-use and regional socioeconomic development data in SPUA, this study used value quantity assessment and an ecosystem service demand model to quantify ecosystem service supply (ESS) and ecosystem service demand (ESD) at both the city and county scale in 2000, 2010 and 2020. Meanwhile, the CA-Markov model was used to predict the potential land-use, the Moran index and Getis-Ord Gi* index were used to analyze spatial clusters of ESS and ESD, and a coupling coordination degree model and matching index were used to analyze the relationship between ESS and ESD. The results show that: (1) The most prominent land-use change in SPUA from 2000 to 2020 was the conversion of cropland to other land-use types; the process of land-use change was more intense from 2010 to 2020 than from 2000 to 2010; and the center of city activities might expand by 2030, which is related to the regional development plan. (2) The ESS was related to the regional natural conditions. Coastal regions or regions with abundant natural resources in SPUA had higher ESS, and the southwest region had lower ESS in SPUA. The ESS presented high–high clusters, low–low clusters and hot spots, and the cluster phenomena gradually diminished from 2000 to 2020. (3) The ESD was related to the regional location and economic development, with the southwest region of SPUA having a higher ESD than the northeast. The ESD presented low–low clusters, and Jinan and Qingdao had hot spots, which are the most developed cities in SPUA. (4) The study scale had impacts on coupled matching of ESSD. Coupled matching of ESSD was found to be unbalanced at the county scale from 2000 to 2020, but tended to be balanced at the city scale, which was related to resource management at different spatial scales. This study reveals the evolution and coupled matching of ESSD at different scales, which has important implications for the sustainable development of regional urban agglomerations.

Generator coordinate method for nuclear octupole excitations: Status and perspectives

Strong octupole correlations have been observed in the low-lying states of atomic nuclei across various mass regions. In this paper, we provide an overview of Beyond Mean-Field (BMF) studies of nuclear octupole collective motions with Generator Coordinate Method (GCM) in combination with quantum-number projections that are implemented to restore the broken symmetries in nuclear mean-field states. We highlight recent developments within this framework and their applications to excitation spectra and electromagnetic transition rates in octupole-shaped nuclei and hypernuclei. We discuss the novel phenomena of nucleon clustering in light nuclei. Additionally, we explore the phase transition from octupole vibrations to rotational motions as spin increases in heavy nuclei. Lastly, we examine the status and future prospects of studies on octupole deformation effects in nuclear Schiff moments. These studies, along with the upper limits of atomic Electric Dipole Moment (EDM), impose stringent constraints on beyond-standard-model time-reversal-violating nucleon–nucleon interactions.

Dynamics of price clustering in the Pakistan stock exchange

PurposeIn this paper, the authors study the phenomenon of price clustering in the Pakistan Stock Exchange (PSX), a market viewed as one of the best-performing stock markets in the world during 2014–2017. The authors study the effect of stock-level variables on price clustering and analyze the determinants of the cross-sectional patterns of price clustering in the PSX, in particular the causal link between price clustering and political instability.Design/methodology/approachThe authors' dataset comprises daily observations on 100 PSX stocks spanning from January 1, 2009 to June 30, 2019. The authors use multivariate regression and spectral analysis to shed light on the dynamics of stock price clustering in PSX.FindingsThe authors document abnormally high levels of stock price clustering, particularly on integer increments, in PSX. The nature of stock price clustering in PSX is consistent with the negotiation hypothesis of Harris (1991). The levels of stock price clustering on PSX are persistent and contain a cyclical component. Furthermore, the authors find that political uncertainty in Pakistan is a significant contributor to the high levels of price clustering on PSX. The authors' conclusions are robust to alternative econometric specifications and different measures of price clustering and political uncertainty.Practical implicationsThe authors' findings are of interest to investors and policymakers. Since price clustering decreases market quality and degrades the information content of stock prices, the authors' study shows that price efficiency in PSX has not improved despite major reforms over the last decade. One practical implication of the authors' results is that investors should be cautious while rebalancing portfolios around political events such as general elections because stock price clustering increases in the PSX during these periods. As a result, stock prices are likely to deviate from their intrinsic values.Originality/valueResearch on price clustering is limited to developed markets, and emerging/frontier markets have been largely overlooked. The phenomenon of price clustering in the PSX has yet to be studied, despite the relevance of the PSX for emerging/frontier market investors.

Shear-reversible clusters of HIV-1 in solution: stabilized by antibodies, dispersed by mucin.

The phenomenon of reversible clustering is expected to further nuance HIV immune stealth because virus surfaces can escape interaction with antibodies (Abs) by hiding temporarily within clusters. It is well known that mucin reduces HIV virulence, and the current perspective is that mucin aggregates HIV-1 to reduce infections. Our findings, however, suggest that mucin is dispersing HIV clusters. The study proposes a new paradigm for how HIV-1 may broadly evade Ab recognition with reversible clustering and why mucin effectively neutralizes HIV-1.

An Improved Visual SLAM Method with Adaptive Feature Extraction

The feature point method is the mainstream method to accomplish inter-frame estimation in visual Simultaneous Localization and Mapping (SLAM) methods, among which the Oriented FAST and Rotated BRIEF (ORB) feature-based method provides an equilibrium of accuracy as well as efficiency. However, the ORB algorithm is prone to clustering phenomena, and its unequal distribution of extracted feature points is not conducive to the subsequent camera tracking. To solve the above problems, this paper suggests an adaptive feature extraction algorithm that first constructs multiple-scale images using an adaptive Gaussian pyramid algorithm, calculates adaptive thresholds, and uses an adaptive meshing method for regional feature point detection to adapt to different scenes. The method uses Adaptive and Generic Accelerated Segment Test (AGAST) to speed up feature detection and the non-maximum suppression method to filter feature points. The feature points are then divided equally by a quadtree technique, and the orientation of those points is determined by an intensity centroid approach. Experiments were conducted on publicly available datasets, and the outcomes demonstrate the algorithm has good adaptivity and solves the problem of a large number of corner point clusters that may result from using manually set detection thresholds. The RMSE of the absolute trajectory error of SLAM applying this method on four sequences of TUM RGB-D datasets is decreased by 13.88% when compared with ORB-SLAM3. It is demonstrated that the algorithm provides high-quality feature points for subsequent image alignment, and the application to SLAM improves the reliability and accuracy of SLAM.

Atomic-scale imaging of ytterbium ions in lead halide perovskites.

Lanthanide-doped lead halide perovskites have demonstrated great potential for photoelectric applications. However, there is a long-standing controversy about the existence of lanthanide ions, e.g., whether the doping of Ln3+ is successful or not; the substituting sites of Ln3+ in lead halide perovskites are unclear. We directly identify the doped Yb3+ in CsPbCl3 perovskites by using the state-of-the-art transmission electron microscopy and three-dimensional atom probe tomography at atomic scale. Different from the previous assumptions and/or results, we evidence that Yb3+ simultaneously replace Pb2+ and occupy the lattice interstitial sites. Furthermore, we directly observe the cluster phenomenon of CsPbCl3 single crystal at near atomic scale. Density functional theory modeling further confirms and explains the mechanisms of our findings. Our findings thus provide an atomic-level understanding of the doping mechanism in perovskites and will stimulate a further thinking of the doping effect on the performance of perovskites.

Spatiotemporal interaction characteristics and transition mechanism of tourism environmental efficiency in China

High-quality development is the theme of China’s economic and social development in the new era, and it is also an objective need for tourism development in the 14th Five-Year Plan period. This study presents an investigation of China’s patterns of tourism environmental efficiency from the perspective of spatiotemporal interactions. A nested analytical framework of quantile regression and spatiotemporal leaps was used to explore the driving mechanism patterns of tourism environmental efficiency under different leap types. Based on various spatial analysis methods, we posit that the patterns of tourism environmental efficiency differ through spatial associations, dynamic evolutions, and transition mechanisms. Our results indicate that there is a dynamic convergence trend of the overall differences in tourism environmental efficiency in China from 2000 to 2020 where a significant clustering phenomenon is observed in space and the level of spatial clustering gradually tends to be stable. In terms of local spatial structures and the dependence directions of tourism environmental efficiency, China’s northwest and northeast regions are more volatile, while eastern coastal regions are relatively stable. Spatiotemporal leaps of tourism environmental efficiency show certain transfer inertia with strong spatial dependence or path-locked characteristics, among which most central and western regions always maintain high carbon emission attributes. These regions are the most limited in the synergy of tourism environmental efficiency. The spatiotemporal network patterns of tourism environmental efficiency are mainly based on positive correlations and show strong spatial integration. However, a few neighboring provinces still have a certain degree of spatiotemporal competition. Driving patterns of the spatiotemporal leaps in tourism environmental efficiency among regions differ greatly. The eastern coastal provinces are driven by population-urbanization constraint patterns, and the northwest, southwest, and northeast regions are driven by technology regulation patterns. From the southeast to the northwest, the leap in the environmental efficiency of China's tourism gradually shows a stepwise pattern of "congruent constraint-reverse development-congruent development.” Therefore, the government should not only consider these various driving/constraining factors but also combine different environmentally-efficient tourism clustering types and transition paths to emphasize differentiated environmental tourism measures. This can help avoid the closure of inter-provincial tourism policies through inter-regional synergy.

Isolable Tetragold(0) Clusters with Polarity-Tunable exo-Au-Au Bond via Intramolecular σ-Aromatization.

Intramolecular π-aromatization is a trait of many organic compounds that enhances the stability of their structures and polarizes related C-C π bonds. In contrast, rare study is focused on this phenomenon in metal clusters. Many existing homometallic clusters exhibit aromaticity, often characterized by nonpolar metal-metal bonds and a high degree of symmetry. However, synthesizing low-symmetric homometallic clusters with high-polar metal-metal bonds is challenging due to their limited thermodynamic stability. Herein, we report a facile strategy for the synthesis of [Au(μ2 -ER2 )]3 -AuPMe3 (E=Ge, Sn; R2 =1,1,4,4-tetrakis(trimethylsilyl)butane-1,4-diyl) clusters and reveal a novel stabilization mode, intramolecular σ-aromatization. Our electronic structure analyses show that these low-symmetric clusters possess a ten-electron σ-aromatic system, which is achieved via intramolecular σ-aromatization. Moreover, the strength of σ-aromaticity gives rise to a polarity-tunable exo-Au-Au bond.

Isolable Tetragold(0) Clusters with Polarity‐Tunable exo‐Au−Au Bond via Intramolecular σ‐Aromatization

AbstractIntramolecular π‐aromatization is a trait of many organic compounds that enhances the stability of their structures and polarizes related C−C π bonds. In contrast, rare study is focused on this phenomenon in metal clusters. Many existing homometallic clusters exhibit aromaticity, often characterized by nonpolar metal‐metal bonds and a high degree of symmetry. However, synthesizing low‐symmetric homometallic clusters with high‐polar metal‐metal bonds is challenging due to their limited thermodynamic stability. Herein, we report a facile strategy for the synthesis of [Au(μ2‐ER2)]3−AuPMe3 (E=Ge, Sn; R2=1,1,4,4‐tetrakis(trimethylsilyl)butane‐1,4‐diyl) clusters and reveal a novel stabilization mode, intramolecular σ‐aromatization. Our electronic structure analyses show that these low‐symmetric clusters possess a ten‐electron σ‐aromatic system, which is achieved via intramolecular σ‐aromatization. Moreover, the strength of σ‐aromaticity gives rise to a polarity‐tunable exo‐Au−Au bond.

Cluster synchronization for controlled nodes via the dynamics of edges in complex dynamical networks.

An appropriate dynamic coupling form between nodes and edges' state can effectively promote the emergence of desired network function (phenomenon), but the existing literatures have not conducted in-depth research on the coupling mechanism. This paper mainly focuses on the coupling auxiliary mechanism of dynamic edges for the emergence of cluster phenomenon of nodes, explores the essential relation between structure and function in complex dynamical networks (CDNs). Firstly, a novel model of CDNs has dynamic systems attached on not only nodes but also edges is proposed from the viewpoint of large-scale system. Secondly, a feedback nodes controller is synthesized associate with the designed linear and adaptive dynamics of edges. Via the appropriate dynamic behaviors of the edges system, the controlled nodes can realize cluster synchronized. Finally, the validity of the proposed approaches is verified by a given numerical example.

Human Crowds as Social Networks: Collective Dynamics of Consensus and Polarization

A ubiquitous type of collective behavior and decision-making is the coordinated motion of bird flocks, fish schools, and human crowds. Collective decisions to move in the same direction, turn right or left, or split into subgroups arise in a self-organized fashion from local interactions between individuals without central plans or designated leaders. Strikingly similar phenomena of consensus (collective motion), clustering (subgroup formation), and bipolarization (splitting into extreme groups) are also observed in opinion formation. As we developed models of crowd dynamics and analyzed crowd networks, we found ourselves going down the same path as models of opinion dynamics in social networks. In this article, we draw out the parallels between human crowds and social networks. We show that models of crowd dynamics and opinion dynamics have a similar mathematical form and generate analogous phenomena in multiagent simulations. We suggest that they can be unified by a common collective dynamics, which may be extended to other psychological collectives. Models of collective dynamics thus offer a means to account for collective behavior and collective decisions without appealing to a priori mental structures.

Genome-Wide Identification and Expression Profiling of B3 Transcription Factor Genes in Prunus armeniaca

The B3 superfamily, which belongs to the plant-specific transcription factors, is widely involved in multiple biological processes. In apricot (Prunus armeniaca), the classification, structure, and function of the B3 superfamily are not yet clear. In this study, a total of 75 B3 genes were identified from the apricot genome. The apricot B3 superfamily can be divided into five subfamilies, i.e., REM, ARF, ABI3, RAV, and HSI, and genes in the same subfamily have similar structures. The distribution of B3 genes on chromosomes presents a clustering phenomenon. Tandem duplication is the main mode of apricot B3 family expansion, and gene duplication mainly occurs in the REM and ARF subfamilies. Many B3 genes originated from a common ancestor of Arabidopsis and apricot before lineage divergence, and ancestor genes expanded fewer times in apricot than in Arabidopsis. Gene ontology analysis showed that apricot B3 genes were closely related to vernalization, flower development, and shoot system development. PaABI3-1 and PaABI3-2 might play a positive regulation role in the transcription of PaOleosin, which encodes a lipid body protein. This study lays a foundation for the further study of the B3 superfamily function in apricot, especially the specific functions of the ABI3 subfamily in apricot kernel oil storage.

New advances in circulating tumor cell‑mediated metastasis of breast cancer (Review).

Breast cancer stands as the most prevalent form of cancer affecting women, with metastasis serving as a leading cause of mortality among patients with breast cancer. Gaining a comprehensive understanding of the metastatic mechanism in breast cancer is essential for early detection and precision treatment of the disease. Circulating tumor cells (CTCs) play a vital role in this context, representing cancer cells that detach from tumor tissues and enter the bloodstream of cancer patients. These cells travel in the blood circulation as single cells or clusters. Recent research has shed light on the enhanced metastatic potential of CTC clusters compared to single CTCs, despite their limited occurrence. The aim of the present review was to explore recent findings on CTCs with a particular focus on the clustering phenomenon of CTCs observed in breast cancer. Additionally, the present review delved into the comparison between single CTCs and CTC clusters regarding their implications for the treatment and prognosis of patients diagnosed with metastatic breast cancer. By examining the role and mechanisms of CTCs in breast cancer metastasis, the present review provided an improved understanding of CTCs and their significance in early detection of breast cancer metastasis through peripheral blood analysis. Moreover, it contributed to the comprehension of cancer prognosis and prediction by highlighting the implications of CTCs in these aspects. Ultimately, the present study seeks to advance knowledge in the field and pave the way for improved approaches to breast cancer management.