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Zhang, Yongzhong, Hexiao Huang, Jie Du et Yan Ma. « RFDPC : Density Peaks Clustering Algorithm Based on Resultant Force ». Mathematical Problems in Engineering 2022 (29 juin 2022) : 1–19. http://dx.doi.org/10.1155/2022/9143727.
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Density peaks clustering (DPC) is an efficient and effective algorithm due to its outstanding performance in discovering clusters with varying densities. However, the quality of this method is highly dependent on the cutoff distance. To improve the performance of DPC, the gravitation-based clustering (GDPC) algorithm is proposed. However, it cannot identify the clusters of varying densities. We developed a novel density peaks clustering algorithm based on the magnitude and direction of the resultant force acting on a data point (RFDPC). RFDPC is based on the idea that the resultant forces acting on the data points in the same cluster are more likely to point towards the cluster center. The cluster centers are selected based on the force directional factor and distance in the decision graph. Experimental results indicate superior performance of the proposed algorithm in detecting clusters of different densities, irregular shapes, and numbers of clusters.
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Dr Bhadresh R. Pandya, Bhumika S. Arora, Dr Vijay Chavda,. « PxEBCA : Proximity Expansion Based Clustering Algorithm ». Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no 5 (11 avril 2021) : 852–56. http://dx.doi.org/10.17762/turcomat.v12i5.1494.
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Cluster analysis is one of the main techniques for analysing data. It is a technique for detecting groups of objects which are similar without specifying any criteria for the grouping. The matter of detecting clusters is challenging when the clusters are of varied size, density and shape. DBSCAN can find arbitrary shaped clusters along with outliers but it cannot handle different density. This paper presents a new method for detecting density based clusters which works on datasets having varied density. In this paper we propose PxEBCA that discovers clusters with arbitrary shape and also with varying density.Experimental evaluation of the effectiveness and efficiency of PEBCA was done using synthetic data. The results of experiments demonstrated that PxEBCA is significantly more effective in discovering clusters of arbitrary shapes with varying densities.
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Xie, Yiqun, Xiaowei Jia, Shashi Shekhar, Han Bao et Xun Zhou. « Significant DBSCAN+ : Statistically Robust Density-based Clustering ». ACM Transactions on Intelligent Systems and Technology 12, no 5 (31 octobre 2021) : 1–26. http://dx.doi.org/10.1145/3474842.
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Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with varying geometric shapes and densities, under the constraint that the clusters are statistically significant. The problem is challenging, because many societal applications and domain science studies have low tolerance for spurious results, and clusters may have arbitrary shapes and varying densities. As a classical topic in data mining and learning, a myriad of techniques have been developed to detect clusters with both varying shapes and densities (e.g., density-based, hierarchical, spectral, or deep clustering methods). However, the vast majority of these techniques do not consider statistical rigor and are susceptible to detecting spurious clusters formed as a result of natural randomness. On the other hand, scan statistic approaches explicitly control the rate of spurious results, but they typically assume a single “hotspot” of over-density and many rely on further assumptions such as a tessellated input space. To unite the strengths of both lines of work, we propose a statistically robust formulation of a multi-scale DBSCAN, namely Significant DBSCAN+, to identify significant clusters that are density connected. As we will show, incorporation of statistical rigor is a powerful mechanism that allows the new Significant DBSCAN+ to outperform state-of-the-art clustering techniques in various scenarios. We also propose computational enhancements to speed-up the proposed approach. Experiment results show that Significant DBSCAN+ can simultaneously improve the success rate of true cluster detection (e.g., 10–20% increases in absolute F1 scores) and substantially reduce the rate of spurious results (e.g., from thousands/hundreds of spurious detections to none or just a few across 100 datasets), and the acceleration methods can improve the efficiency for both clustered and non-clustered data.
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Sarkar, Anish. « Finite clusters in high density Boolean models with balls of varying sizes ». Advances in Applied Probability 30, no 4 (décembre 1998) : 929–47. http://dx.doi.org/10.1239/aap/1035228201.
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In this paper we study finite clusters in a high density Boolean model with balls of two distinct sizes. Alexander (1993) studied the geometric structures of finite clusters in a high density Boolean model with balls of fixed size and showed that the only possible structure admitted by such events is that all Poisson points comprising the cluster are packed tightly inside a small sphere. When the balls are of varying sizes, the event that the cluster consists of k1 big balls and k2 small balls (both k1, k2 ≥ 1) occurs only when the centres of all big balls are compressed in a small sphere and the centres of the small balls are distributed uniformly inside the region formed by the big balls in such a way that the small balls are totally contained inside the big balls. We also show that it is most likely that a finite cluster in a high density Boolean model with varying ball sizes is made up only of small balls.
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Sarkar, Anish. « Finite clusters in high density Boolean models with balls of varying sizes ». Advances in Applied Probability 30, no 04 (décembre 1998) : 929–47. http://dx.doi.org/10.1017/s0001867800008739.
Texte intégralRésumé :
In this paper we study finite clusters in a high density Boolean model with balls of two distinct sizes. Alexander (1993) studied the geometric structures of finite clusters in a high density Boolean model with balls of fixed size and showed that the only possible structure admitted by such events is that all Poisson points comprising the cluster are packed tightly inside a small sphere. When the balls are of varying sizes, the event that the cluster consists of k 1 big balls and k 2 small balls (both k 1, k 2 ≥ 1) occurs only when the centres of all big balls are compressed in a small sphere and the centres of the small balls are distributed uniformly inside the region formed by the big balls in such a way that the small balls are totally contained inside the big balls. We also show that it is most likely that a finite cluster in a high density Boolean model with varying ball sizes is made up only of small balls.
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Tan, Lu, et Joanna Crowe Curran. « Comparison of Turbulent Flows over Clusters of Varying Density ». Journal of Hydraulic Engineering 138, no 12 (décembre 2012) : 1031–44. http://dx.doi.org/10.1061/(asce)hy.1943-7900.0000635.
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Shen, Xiaoqi, Wenzhong Shi, Zhewei Liu, Anshu Zhang, Lukang Wang et Fanxin Zeng. « Extracting Human Activity Areas from Large-Scale Spatial Data with Varying Densities ». ISPRS International Journal of Geo-Information 11, no 7 (13 juillet 2022) : 397. http://dx.doi.org/10.3390/ijgi11070397.
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Human activity area extraction, a popular research topic, refers to mining meaningful location clusters from raw activity data. However, varying densities of large-scale spatial data create a challenge for existing extraction methods. This research proposes a novel area extraction framework (ELV) aimed at tackling the challenge by using clustering with an adaptive distance parameter and a re-segmentation strategy with noise recovery. Firstly, a distance parameter was adaptively calculated to cluster high-density points, which can reduce the uncertainty introduced by human subjective factors. Secondly, the remaining points were assigned according to the spatial characteristics of the clustered points for a more reasonable judgment of noise points. Then, to face the varying density problem, a re-segmentation strategy was designed to segment the appropriate clusters into low- and high-density clusters. Lastly, the noise points produced in the re-segmentation step were recovered to reduce unnecessary noise. Compared with other algorithms, ELV showed better performance on real-life datasets and reached 0.42 on the Silhouette coefficient (SC) indicator, with an improvement of more than 16.67%. ELV ensures reliable clustering results, especially when the density differences of the activity points are large, and can be valuable in some applications, such as location prediction and recommendation.
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Pearce, Francesca A., Scott T. Kay, David J. Barnes, Richard G. Bower et Matthieu Schaller. « Hydrostatic mass estimates of massive galaxy clusters : a study with varying hydrodynamics flavours and non-thermal pressure support ». Monthly Notices of the Royal Astronomical Society 491, no 2 (24 octobre 2019) : 1622–42. http://dx.doi.org/10.1093/mnras/stz3003.
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ABSTRACT We use a set of 45 simulated clusters with a wide mass range (8 × 1013 < M500 [M⊙] < 2 × 1015) to investigate the effect of varying hydrodynamics flavours on cluster mass estimates. The cluster zooms were simulated using the same cosmological models as the BAHAMAS and C-EAGLE projects, leading to differences in both the hydrodynamics solvers and the subgrid physics but still producing clusters that broadly match observations. At the same mass resolution as BAHAMAS, for the most massive clusters (M500 > 1015 M⊙), we find that changes in the smoothed particle hydrodynamics (SPH) method produce the greatest differences in the final halo, while the subgrid models dominate at lower mass. By calculating the mass of all of the clusters using different permutations of the pressure, temperature, and density profiles, created with either the true simulated data or mock spectroscopic data, we find that the spectroscopic temperature causes a bias in the hydrostatic mass estimates that increases with the mass of the cluster, regardless of the SPH flavour used. For the most massive clusters, the estimated mass of the cluster using spectroscopic density and temperature profiles is found to be as low as 50 per cent of the true mass compared to ∼90 per cent for low-mass clusters. When including a correction for non-thermal pressure, the spectroscopic hydrostatic mass estimates are less biased on average and the mass dependence of the bias is reduced, although the scatter in the measurements does increase.
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Zhu, Ye, Kai Ming Ting et Mark J. Carman. « Density-ratio based clustering for discovering clusters with varying densities ». Pattern Recognition 60 (décembre 2016) : 983–97. http://dx.doi.org/10.1016/j.patcog.2016.07.007.
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Haghi, Hosein, Ghasem Safaei, Akram H. Zonoozi et Pavel Kroupa. « Dynamical evolution of star clusters with top-heavy IMF ». Proceedings of the International Astronomical Union 14, S351 (mai 2019) : 447–50. http://dx.doi.org/10.1017/s174392131900704x.
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AbstractSeveral observational and theoretical studies suggest that the initial mass function (IMF) slope for massive stars in globular clusters (GCs) depends on the initial cloud density and metallicity, such that the IMF becomes increasingly top-heavy with decreasing metallicity and increasing the gas density of the forming object. Using N-body simulations of GCs starting with a top-heavy IMF and undergo early gas expulsion within a Milky Way-like potential, we show how such a cluster would evolve. By varying the degree of top-heaviness, we calculate the dissolution time and the minimum cluster mass needed for the cluster to survive after 12 Gyr of evolution.
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Kroupa, Pavel. « The systematically varying stellar IMF ». Proceedings of the International Astronomical Union 14, S351 (mai 2019) : 117–21. http://dx.doi.org/10.1017/s1743921319007749.
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AbstractSome ultra-compact dwarf galaxies have large dynamical mass to light (M / L) ratios and also appear to contain an overabundance of LMXB sources, and some Milky Way globular clusters have a low concentration and appear to have a deficit of low-mass stars. These observations can be explained if the stellar IMF becomes increasingly top-heavy with decreasing metallicity and increasing gas density of the forming object. The thus constrained stellar IMF then accounts for the observed trend of metallicity and M / L ratio found amongst M31 globular star clusters. It also accounts for the overall shift of the observationally deduced galaxy-wide IMF from top-light to top-heavy with increasing star formation rate amongst galaxies. If the IMF varies similarly to deduced here, then extremely young very massive star-burst clusters observed at a high redshift would appear quasar-like (Jerabkova et al. 2017).
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Wang, Jing, Daniel K. Schreiber, Nathan Bailey, Peter Hosemann et Mychailo B. Toloczko. « The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data ». Microscopy and Microanalysis 25, no 2 (8 mars 2019) : 338–48. http://dx.doi.org/10.1017/s1431927618015386.
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AbstractAtom probe tomography (APT) is a powerful technique to characterize buried three-dimensional nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure–property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the density-based spatial clustering of applications with noise algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the nonuniformity of the atomic density in the APT reconstruction itself (e.g., crystallographic poles and other field evaporation artifacts). This clustering method relies heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we utilize a well-known cluster analysis algorithm, called ordering points to identify the clustering structures, and an automatic cluster extraction algorithm to analyze clusters of varying atomic density in APT data. This approach requires only one free parameter, and other inputs can be estimated or bounded based on physical parameters, such as the lattice parameter and solute concentration. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen.
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Altaf, Saud, Muhammad Waseem Waseem et Laila Kazmi. « IDCUP Algorithm to Classifying Arbitrary Shapes and Densities for Center-based Clustering Performance Analysis ». Interdisciplinary Journal of Information, Knowledge, and Management 15 (2020) : 091–108. http://dx.doi.org/10.28945/4541.
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Aim/Purpose: The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background: Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested. Methodology: A density-based approach on traditional center-based clustering is introduced that assigns a weight to each cluster. The weights are then utilized in calculating the distances from data vectors to centroids by multiplying the distance by the centroid weight. Contribution: In this paper, we have examined different density-based clustering methods for data sets with nested clusters of varying density. Two such data sets were used to evaluate some of the commonly cited algorithms found in the literature. Nested clusters were found to be challenging for the existing algorithms. In utmost cases, the targeted algorithms either did not detect the largest clusters or simply divided large clusters into non-overlapping regions. But, it may be possible to detect all clusters by doing multiple runs of the algorithm with different inputs and then combining the results. This work considered three challenges of clustering methods. Findings: As a result, a center with a low weight will attract objects from further away than a centroid with higher weight. This allows dense clusters inside larger clusters to be recognized. The methods are tested experimentally using the K-means, DBSCAN, TURN*, and IDCUP algorithms. The experimental results with different data sets showed that IDCUP is more robust and produces better clusters than DBSCAN, TURN*, and K-means. Finally, we compare K-means, DBSCAN, TURN*, and to deal with arbitrary shapes problems at different datasets. IDCUP shows better scalability compared to TURN*. Future Research: As future recommendations of this research, we are concerned with the exploration of further available challenges of the knowledge discovery process in clustering along with complex data sets with more time. A hybrid approach based on density-based and model-based clustering algorithms needs to compare to achieve maximum performance accuracy and avoid the arbitrary shapes related problems including optimization. It is anticipated that the comparable kind of the future suggested process will attain improved performance with analogous precision in identification of clustering shapes.
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Benkrima, Yamina, Djamel Belfennache, Radhia Yekhlef, Mohammed Elbar Soudani, Abdelkader Souiga et Yahia Achour. « Physicochemical Characteristics for Fen (n = 2–10) Cluster by Density Functional Theory ». East European Journal of Physics, no 2 (2 juin 2023) : 150–56. http://dx.doi.org/10.26565/2312-4334-2023-2-14.
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The In this work, we present a theoretical study on the equilibrium geometry and the energetic, electronic and magnetic properties of Fen (n = 2–10) based on the use of density functional theory (DFT). The results are obtained using Both Generalized Gradient Approximation according to the scheme described by Perdew-Burke-Ernzerhof (GGA-PBE). More stable structures obtained compared to other isomers have not been previously found. It is shown by the results calculated as the calculated fragmentation energy, and the second-order energy difference that Fen (n = 7,8,9) clusters are more stable than the other cluster sizes. The calculated magnetic properties of the most stable clusters display varying magnetic torque between values 3.00 μB and 3.35 μB, except for the Fe10 cluster, which takes the upper value 3.38 μB. These results are very important for experimental experts who are active in designing new nanocatalysis systems in the physical and chemical fields.
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Ma, Dongling, Baoze Liu, Qingji Huang et Qian Zhang. « Evolution Characteristics and Causes—An Analysis of Urban Catering Cluster Spatial Structure ». ISPRS International Journal of Geo-Information 12, no 8 (28 juillet 2023) : 302. http://dx.doi.org/10.3390/ijgi12080302.
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Studying the development characteristics of the urban catering industry holds significant importance for understanding the spatial patterns of cities. In this manuscript, according to the characteristics of the distribution of catering points and based on catering point of interest (POI) data of 106 cities in China in 2016 and 2022, we propose the Natural Nearest Neighbor Single Branch Model (NNSBM) to identify catering points by adaptive clustering, which improves the efficiency of identifying catering clusters. Subsequently, a catering spatial structure division model is constructed to classify the spatial structure of catering clusters into 3 major categories and 17 subcategories, and the evolution pattern of urban catering clusters is analyzed. In addition, based on the population density raster data, a bivariate spatial autocorrelation model is employed to analyze the complex relationship between the distribution of urban catering clusters and population density, revealing the distinctive characteristics of urban catering cluster evolution. The results showed that (1) In the initial stage of catering cluster formation, catering activities tend to gather first in a specific area of the city, giving rise to the main catering cluster. However, as the catering industry progresses, the phenomenon of “central fading” occurs within the main catering cluster. (2) The overall trend of the catering spatial structure of most cities showed an evolution toward low primacy–high concentration (Lp-Hc), and cities at different stages of catering capacity exhibited different evolution characteristics of catering clusters. (3) The influence of population density on catering distribution was staged, with a varying impact on cities with different types of catering spatial structures.
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Allaf, A. W., R. A. Hallett, S. P. Balm et H. W. Kroto. « HYDROGENATION OF CARBON CLUSTERS ». International Journal of Modern Physics B 06, no 23n24 (décembre 1992) : 3595–602. http://dx.doi.org/10.1142/s0217979292001663.
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Carbon clusters are produced by laser vaporisation of the surface of a rotating/translating graphite disc into a high density pulse of helium. The present study illustrates the effects of mixing varying amounts of hydrogen into the helium carrier gas on the carbon nucleation products with particular reference to the behaviour of the small to medium sized clusters ranging from C 10– C 40 with the aim of verifying the existence of small fullerenes (even clusters, C n, 20<n<32).
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KHALENKOV, A. M., N. G. BORISENKO, V. N. KONDRASHOV, Yu A. MERKULIEV, J. LIMPOUCH et V. G. PIMENOV. « Experience of micro-heterogeneous target fabrication to study energy transport in plasma near critical density ». Laser and Particle Beams 24, no 2 (juin 2006) : 283–90. http://dx.doi.org/10.1017/s0263034606060435.
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The experience of target fabrication with low-density and cluster heterogeneity is presented. Cluster plasma research is strongly dependent on target fabrication development and target structure characterization. Ten more target parameters should be measured for experiment interpreting in case of micro-heterogeneous plasma. Foam and foil targets, high-Z doped also, are produced and irradiated on the existing laser facilities. The density of 4.5 mg/cc cellulose triacetate in the form of regular three-dimensional polymer networks are achieved which is as low as plasma critical density for the third harmonic of iodine laser light. The possibilities of varying important target parameters, methods of their monitoring are discussed. Experiments with underdense foam targets with or without clusters irradiated on Prague Asterix Laser System (PALS) laser facility are analyzed preliminary for target optimization. Under-critical foams of varying structure (closed-cell foam or three-dimensional networks) and densities are reported for plasma experiments. Thermal and radiation transport in such targets are considered.
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Jiang, Jianhua, Wei Zhou, Limin Wang, Xin Tao et Keqin Li. « HaloDPC : An Improved Recognition Method on Halo Node for Density Peak Clustering Algorithm ». International Journal of Pattern Recognition and Artificial Intelligence 33, no 08 (25 juin 2019) : 1950012. http://dx.doi.org/10.1142/s0218001419500125.
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The density peaks clustering (DPC) is known as an excellent approach to detect some complicated-shaped clusters with high-dimensionality. However, it is not able to detect outliers, hub nodes and boundary nodes, or form low-density clusters. Therefore, halo is adopted to improve the performance of DPC in processing low-density nodes. This paper explores the potential reasons for adopting halos instead of low-density nodes, and proposes an improved recognition method on Halo node for Density Peak Clustering algorithm (HaloDPC). The proposed HaloDPC has improved the ability to deal with varying densities, irregular shapes, the number of clusters, outlier and hub node detection. This paper presents the advantages of the HaloDPC algorithm on several test cases.
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Liu, Yong Li. « Study on Information Technology with MADS — A New Data Clustering Algorithm Based on Ant Colony Optimization ». Advanced Materials Research 859 (décembre 2013) : 572–76. http://dx.doi.org/10.4028/www.scientific.net/amr.859.572.
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In the field of information technology, data clustering algorithms are widely used. In this paper, we proposed a new data clustering algorithm, named MADS, It is based on ant colony Optimization. MADS can automatically find clusters, depending on a few parameters that are not directly related to the data set. In addition, there are some existence technique was also utilized in our method, such as the density concept and cluster validity index (DB-index). The experiment results verified that MADS is able to discover clusters with varying shapes and is effective when applied to image segmentation.
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Wagner, Jenny, Jori Liesenborgs et David Eichler. « Multiply imaged time-varying sources behind galaxy clusters ». Astronomy & ; Astrophysics 621 (janvier 2019) : A91. http://dx.doi.org/10.1051/0004-6361/201833530.
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With upcoming (continuum) surveys of high-resolution radio telescopes, detection rates of fast radio bursts (FRBs) might approach 105 per sky per day by future extremely large observatories, such as the possible extension of the Square Kilometer Array (SKA) to a phase-2 array. Depending on the redshift distribution of FRBs and using the repeating FRB121102 as a model, we calculate a detection rate of multiply imaged FRBs with their multiply imaged hosts caused by the distribution of galaxy-cluster-scale gravitational lenses of the order of 10−4 per square degree per year for a minimum total flux of the host of 10 μJy at 1.4 GHz for SKA phase 2. Our comparison of estimated detection rates for quasars (QSOs), supernovae (SNe), gamma ray bursts (GRBs), and FRBs shows that multiple images of FRBs could be more numerous than those of GRBs and SNe and as numerous as multiple images of QSOs. Time delays between the multiple images of an FRB break degeneracies in model-based and model-independent lens reconstructions as other time-varying sources do, yet without a microlensing bias, as FRBs are more point-like and have shorter duration times. We estimate the relative imprecision of FRB time-delay measurements to be 10−10 for time delays on the order of 100 days for galaxy-cluster-scale lenses, yielding more precise (local) lens properties than time delays from the other time-varying sources. Using the lens modelling software Grale, we show the increase in accuracy and precision of the reconstructed scaled surface mass density map of a simulated cluster-scale lens when adding time delays for one set of multiple images to the set of observational constraints.
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Moskalenko, Olga L., Irina E. Kasparova et Roman A. Yaskevich. « ASSESSMENT OF THE EFFECT OF DIFFERENT CLUSTERS OF THE METABOLIC SYNDROME ON THE EXPRESSION OF DEPRESSIVE DISORDERS ». Russian Journal of Education and Psychology 14, no 5 (31 octobre 2023) : 177–95. http://dx.doi.org/10.12731/2658-4034-2023-14-5-177-195.
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The purpose of the study. To study the influence of various metabolic syndrome clusters on the severity of depressive disorders according to the CES-D scale.
Materials and methods. 136 male patients were examined, including 60 with metabolic syndrome. Metabolic syndrome was diagnosed based on the criteria of clinical recommendations of the All-Russian Scientific Society of Cardiology in 2009. The severity of depression was assessed using the Center for Epidemiological Studies Depression Scale - CES-D.
Results. It was found that among the surveyed men with metabolic syndrome, depressive disorders of varying severity on the CES-D scale were found in 40% of the surveyed, while among men with MS, the number of people with severe depression on the CES-D scale was higher. Among persons with a four-component metabolic syndrome cluster, patients with severe depression were more common (57,1%). In men with depression on the CES-D scale of varying severity, a three-component cluster of metabolic syndromes was more common, consisting of abdominal obesity, arterial hypertension, and an elevated level of low-density lipoprotein cholesterol.
Conclusion. The combination of abdominal obesity, arterial hypertension, and lipid disorders characterized by high levels of low-density lipoprotein was the most common metabolic syndrome cluster among men with depressive disorders of varying severity on the CES-D scale.
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de Mello, Matheus, Rogelio Díaz-Méndez et Alejandro Mendoza-Coto. « Ultrasoft Classical Systems at Zero Temperature ». Entropy 25, no 2 (15 février 2023) : 356. http://dx.doi.org/10.3390/e25020356.
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At low temperatures, classical ultrasoft particle systems develop interesting phases via the self-assembly of particle clusters. In this study, we reach analytical expressions for the energy and the density interval of the coexistence regions for general ultrasoft pairwise potentials at zero temperatures. We use an expansion in the inverse of the number of particles per cluster for an accurate determination of the different quantities of interest. Differently from previous works, we study the ground state of such models, in two and three dimensions, considering an integer cluster occupancy number. The resulting expressions were successfully tested in the small and large density regimes for the Generalized Exponential Model α, varying the value of the exponent.
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Anibal, James, Alexandre G. Day, Erol Bahadiroglu, Liam O’Neil, Long Phan, Alec Peltekian, Amir Erez, Mariana Kaplan, Grégoire Altan-Bonnet et Pankaj Mehta. « HAL-X : Scalable hierarchical clustering for rapid and tunable single-cell analysis ». PLOS Computational Biology 18, no 10 (3 octobre 2022) : e1010349. http://dx.doi.org/10.1371/journal.pcbi.1010349.
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Data clustering plays a significant role in biomedical sciences, particularly in single-cell data analysis. Researchers use clustering algorithms to group individual cells into populations that can be evaluated across different levels of disease progression, drug response, and other clinical statuses. In many cases, multiple sets of clusters must be generated to assess varying levels of cluster specificity. For example, there are many subtypes of leukocytes (e.g. T cells), whose individual preponderance and phenotype must be assessed for statistical/functional significance. In this report, we introduce a novel hierarchical density clustering algorithm (HAL-x) that uses supervised linkage methods to build a cluster hierarchy on raw single-cell data. With this new approach, HAL-x can quickly predict multiple sets of labels for immense datasets, achieving a considerable improvement in computational efficiency on large datasets compared to existing methods. We also show that cell clusters generated by HAL-x yield near-perfect F1-scores when classifying different clinical statuses based on single-cell profiles. Our hierarchical density clustering algorithm achieves high accuracy in single cell classification in a scalable, tunable and rapid manner.
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Zivkov, V., et S. Ninkovic. « Generalized Schuster law and King’s formula ». Serbian Astronomical Journal, no 157 (1998) : 7–11. http://dx.doi.org/10.2298/saj9857007z.
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By varying a particular form of the generalized Schuster density law (the exponent in the denominator equal to 3/2) the authors look for a suitable substitution for King?s density formula usually applied to star clusters and dwarf galaxies. The authors find expressions yielding almost identical density values as King?s formula, but from the mathematical point of view significantly more simple for use.
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Gonçalves, Inês G., et Jose Manuel Garcia-Aznar. « Extracellular matrix density regulates the formation of tumour spheroids through cell migration ». PLOS Computational Biology 17, no 2 (26 février 2021) : e1008764. http://dx.doi.org/10.1371/journal.pcbi.1008764.
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In this work, we show how the mechanical properties of the cellular microenvironment modulate the growth of tumour spheroids. Based on the composition of the extracellular matrix, its stiffness and architecture can significantly vary, subsequently influencing cell movement and tumour growth. However, it is still unclear exactly how both of these processes are regulated by the matrix composition. Here, we present a centre-based computational model that describes how collagen density, which modulates the steric hindrance properties of the matrix, governs individual cell migration and, consequently, leads to the formation of multicellular clusters of varying size. The model was calibrated using previously published experimental data, replicating a set of experiments in which cells were seeded in collagen matrices of different collagen densities, hence producing distinct mechanical properties. At an initial stage, we tracked individual cell trajectories and speeds. Subsequently, the formation of multicellular clusters was also analysed by quantifying their size. Overall, the results showed that our model could accurately replicate what was previously seen experimentally. Specifically, we showed that cells seeded in matrices with low collagen density tended to migrate more. Accordingly, cells strayed away from their original cluster and thus promoted the formation of small structures. In contrast, we also showed that high collagen densities hindered cell migration and produced multicellular clusters with increased volume. In conclusion, this model not only establishes a relation between matrix density and individual cell migration but also showcases how migration, or its inhibition, modulates tumour growth.
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Adhikari, Kapil, et Asok K. Ray. « An Ab initio Study on the Convergence of Electronic Properties of SiC Nanotubes ». Himalayan Physics 3 (1 janvier 2013) : 69–73. http://dx.doi.org/10.3126/hj.v3i0.7309.
Texte intégralRésumé :
Ab initio calculations of the electronic structures of silicon carbide (SiC) nanotubes represented by clusters are presented. The nanotube clusters of chiralities (3,3) and (5,5) are studied using the hybrid density functional B3LYP (Becke’s 3-parameter and the Lee-Yang-Parr exchange-correlation) and LANL2DZ (Los Alamos National Laboratory double ?) and 3-21G* basis sets. Evolution of electronic properties of silicon carbide (SiC) nanotubes (3, 3) and (5,5) with their length is discussed. The results suggest that the electronic properties of nanotubes change for short tubes of unit cells with lengths varying from 1 to 5. However, the properties do not seem to change significantly after this. Therefore, an infinite silicon carbide (SiC) nanotube can be approximated by a nanotube cluster of 5 unit cells.The Himalayan PhysicsVol. 3, No. 3, July 2012Page : 69-73
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Bi, Honguang, P. Mészáros et A. Mészáros. « X-Ray Background Fluctuations from Discrete Sources with a Varying Density Contrast ». Symposium - International Astronomical Union 139 (1990) : 416–17. http://dx.doi.org/10.1017/s007418090024117x.
Texte intégralRésumé :
In two previous publications (Mészáros and Mészáros 1988 “Paper I”; Bagoly, Mészáros, and Mészáros 1988 “Paper II”), we have studied the fluctuations of the X-ray background (XRB) expected if the XRB is produced by discrete sources distributed as galaxies. The distribution of matter was assumed to follow the large-scale structure in the form of spherical clusters (superclusters) or spherical voids. In Paper I the density contrast of XRB sources inside and outside structures was taken to be a step function of constant height, whereas in Paper II we introduced arbitrary density contrasts (independent of redshift) and allowed for a redshift evolution of the luminosity of the sources. This led to predicted angular fluctuations of the XRB, which, when we compared them with the HEAO–1 observational limit (Shafer 1983), allowed us to set limits on the type and density of structures.
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Einasto, J., I. Suhhonenko, L. J. Liivamägi et M. Einasto. « Extended percolation analysis of the cosmic web ». Astronomy & ; Astrophysics 616 (août 2018) : A141. http://dx.doi.org/10.1051/0004-6361/201833011.
Texte intégralRésumé :
Aims. We develop an extended percolation method to allow the comparison of geometrical properties of the real cosmic web with the simulated dark matter (DM) web for an ensemble of over- and under-density systems. Methods. We scanned density fields of DM model and Sloan Digital Sky Survey (SDSS) observational samples and found connected over- and under-density regions in a large range of threshold densities. Lengths, filling factors, and numbers of largest clusters and voids as functions of the threshold density were used as percolation functions. Results. We find that percolation functions of DM models of varying box sizes are very similar to each other. This stability suggests that properties of the cosmic web, as found in the present paper, can be applied to the cosmic web as a whole. Percolation functions depend strongly on the smoothing length. At smoothing length 1 h−1 Mpc the percolation threshold density for clusters is log PC = 0.718 ± 0.014, and for voids such density is log PV = −0.816 ± 0.015; this is very different from percolation thresholds for random samples, which are log P0 = 0.00 ± 0.02. Conclusions. The extended percolation analysis is a versatile method to study various geometrical properties of the cosmic web in a wide range of parameters. Percolation functions of the SDSS sample are very different from percolation functions of DM model samples. The SDSS sample has only one large percolating void that fills almost the whole volume. The SDSS sample contains numerous small isolated clusters at low threshold densities, instead of one single percolating DM cluster. These differences are due to the tenuous DM web, which is present in model samples but absent in real observational samples.
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Junkel-Vives, G. C., J. Abdallah, F. Blasco, C. Stenz, F. Salin, A. Ya Faenov, A. I. Magunov et al. « High resolution X-ray spectroscopy investigations of fs laser irradiated Ar clusters by varying cluster size and laser flux density ». Journal of Quantitative Spectroscopy and Radiative Transfer 71, no 2-6 (octobre 2001) : 417–30. http://dx.doi.org/10.1016/s0022-4073(01)00086-3.
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Meester, V., et D. J. Kraft. « Complex patchy colloids shaped from deformable seed particles through capillary interactions ». Soft Matter 14, no 7 (2018) : 1162–70. http://dx.doi.org/10.1039/c7sm02020a.
Texte intégralRésumé :
We investigate the mechanisms underlying the reconfiguration of random aggregates of spheres through capillary interactions, the so-called “colloidal recycling” method, for fabricating a wide variety of patchy particles. We explore the influence of capillary forces on clusters of deformable seed particles by systematically varying the crosslink density of the spherical seeds.
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Lake, William, Smadar Naoz, Yeou S. Chiou, Blakesley Burkhart, Federico Marinacci, Mark Vogelsberger et Kyle Kremer. « The Supersonic Project : SIGOs, A Proposed Progenitor to Globular Clusters, and Their Connections to Gravitational-wave Anisotropies ». Astrophysical Journal 922, no 1 (1 novembre 2021) : 86. http://dx.doi.org/10.3847/1538-4357/ac20d0.
Texte intégralRésumé :
Abstract Supersonically induced gas objects (SIGOs), are structures with little to no dark-matter component predicted to exist in regions of the universe with large relative velocities between baryons and dark matter at the time of recombination. They have been suggested to be the progenitors of present-day globular clusters. Using simulations, SIGOs have been studied on small scales (around 2 Mpc) where these relative velocities are coherent. However, it is challenging to study SIGOs using simulations on large scales due to the varying relative velocities at scales larger than a few Mpc. Here, we study SIGO abundances semi-analytically: using perturbation theory, we predict the number density of SIGOs analytically, and compare these results to small-box numerical simulations. We use the agreement between the numerical and analytic calculations to extrapolate the large-scale variation of SIGO abundances over different stream velocities. As a result, we predict similar large-scale variations of objects with high gas densities before reionization that could possibly be observed by JWST. If indeed SIGOs are progenitors of globular clusters, then we expect a similar variation of globular cluster abundances over large scales. Significantly, we find that the expected number density of SIGOs is consistent with observed globular cluster number densities. As a proof-of-concept, and because globular clusters were proposed to be natural formation sites for gravitational wave sources from binary black-hole mergers, we show that SIGOs should imprint an anisotropy on the gravitational wave signal on the sky, consistent with their distribution.
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Nino, Daniel F., Daniel Djayakarsana et Joshua N. Milstein. « FOCAL3D : A 3-dimensional clustering package for single-molecule localization microscopy ». PLOS Computational Biology 16, no 12 (8 décembre 2020) : e1008479. http://dx.doi.org/10.1371/journal.pcbi.1008479.
Texte intégralRésumé :
Single-molecule localization microscopy (SMLM) is a powerful tool for studying intracellular structure and macromolecular organization at the nanoscale. The increasingly massive pointillistic data sets generated by SMLM require the development of new and highly efficient quantification tools. Here we present FOCAL3D, an accurate, flexible and exceedingly fast (scaling linearly with the number of localizations) density-based algorithm for quantifying spatial clustering in large 3D SMLM data sets. Unlike DBSCAN, which is perhaps the most commonly employed density-based clustering algorithm, an optimum set of parameters for FOCAL3D may be objectively determined. We initially validate the performance of FOCAL3D on simulated datasets at varying noise levels and for a range of cluster sizes. These simulated datasets are used to illustrate the parametric insensitivity of the algorithm, in contrast to DBSCAN, and clustering metrics such as the F1 and Silhouette score indicate that FOCAL3D is highly accurate, even in the presence of significant background noise and mixed populations of variable sized clusters, once optimized. We then apply FOCAL3D to 3D astigmatic dSTORM images of the nuclear pore complex (NPC) in human osteosaracoma cells, illustrating both the validity of the parameter optimization and the ability of the algorithm to accurately cluster complex, heterogeneous 3D clusters in a biological dataset. FOCAL3D is provided as an open source software package written in Python.
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Majid, Abdul, Sidra Arif, Tariq M. Younes, Mohammad Alkhedher et Sayed M. ElDin. « DFT Study of Heteronuclear (TMFeO3)x Molecular Clusters (Where TM = Sc, Ti, Fe and x = 2, 4, 8) for Photocatalytic and Photovoltaic Applications ». Energies 15, no 19 (2 octobre 2022) : 7253. http://dx.doi.org/10.3390/en15197253.
Texte intégralRésumé :
The computational modeling of metal oxide clusters for photovoltaic application is carried out by using density functional theory. The structural and electronic properties of heteronuclear (TMFeO3)x molecular clusters (where x = 2, 4, 8 and TM = Sc, Ti, Fe) are investigated in detail. The physical parameters such as energy gap, formation energy, binding energy, and stability are determined. The computed values and trends in electronegativity (χ), chemical potential (μ), hardness (η) and softness (S), positions of highest occupied molecular orbitals (HOMO) and lowest unoccupied molecular orbitals (LUMO), and HOMO-LUMO gap with varying cluster sizes are discussed. The iso-surface plots with relaxed structure related to the frontier MOs are described to shed light on the charge transfer mechanism. In the entire series of the studied clusters, the computed gap of (Fe2O3)8 was found minimal and thus suitable for red light absorption, whereas (TiFeO3)2 exhibited a maximum gap which shows potential for blue light absorption. The clusters exhibiting different values of the gap are found suitable to absorb the solar radiation. HOMO and LUMO position with their energy differences in the clusters are found compatible for applications in photocatalytic and photovoltaic applications. The observed trend in the computed parameters points to the potential of the simulated materials for application in a TiO2-based semiconducting photoanode to harvest sunlight.
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Schiavi, R., R. Capuzzo-Dolcetta, I. Y. Georgiev, M. Arca-Sedda et A. Mastrobuono-Battisti. « Are we observing an NSC in course of formation in the NGC 4654 galaxy ? » Monthly Notices of the Royal Astronomical Society 503, no 1 (18 février 2021) : 594–602. http://dx.doi.org/10.1093/mnras/stab458.
Texte intégralRésumé :
ABSTRACT We use direct N-body simulations to explore some possible scenarios for the future evolution of two massive clusters observed towards the centre of NGC 4654, a spiral galaxy with mass similar to that of the Milky Way. Using archival HST data, we obtain the photometric masses of the two clusters, M = 3 × 105 M⊙ and M = 1.7 × 106 M⊙, their half-light radii, Reff ∼ 4 pc and Reff ∼ 6 pc, and their projected distances from the photometric centre of the galaxy (both <22 pc). The knowledge of the structure and separation of these two clusters (∼24 pc) provides a unique view for studying the dynamics of a galactic central zone hosting massive clusters. Varying some of the unknown cluster orbital parameters, we carry out several N-body simulations showing that the future evolution of these clusters will inevitably result in their merger. We find that, mainly depending on the shape of their relative orbit, they will merge into the galactic centre in less than 82 Myr. In addition to the tidal interaction, a proper consideration of the dynamical friction braking would shorten the merging times up to few Myr. We also investigate the possibility to form a massive nuclear star cluster (NSC) in the centre of the galaxy by this process. Our analysis suggests that for low-eccentricity orbits, and relatively long merger times, the final merged cluster is spherical in shape, with an effective radius of few parsecs and a mass within the effective radius of the order of $10^5\, \mathrm{M_{\odot }}$. Because the central density of such a cluster is higher than that of the host galaxy, it is likely that this merger remnant could be the likely embryo of a future NSC.
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Montejano-Carrizales, Juan M., Faustino Aguilera-Granja et Ricardo A. Guirado-López. « Stability, Electronic Properties, and Structural Isomerism in Small Copper Clusters ». MRS Proceedings 1479 (2012) : 15–20. http://dx.doi.org/10.1557/opl.2012.1591.
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ABSTRACTWe present extensive pseudopotential density functional theory calculations dedicated to analyze the stability, electronic properties, and structural isomerism in Cu6 clusters. We consider structures of different symmetries and charge states. Our total energy calculations reveal a strong competition between two- and three-dimensional atomic arrays, the later being mostly energetically preferred for the anionic structures. The bond lengths and electronic spectra strongly depend on the local atomic environment, a result that is expected to strongly influence the catalytic activity of our clusters. Using the nudged elastic band method we analyze the interconversion processes between different Cu6 isomers. Complex atomic relaxations are obtained when we study the transition between different cluster structures; however relatively small energy barriers of approximately 0.3 eV accompany the atomic displacements. Interestingly, we obtain that by considering positively charged Cu6+ systems we reduce further the energy barriers opposing the interconversion process. The previous results could imply that, under a range of experimental conditions, it should be possible to observe different Cu6cluster structures in varying proportions.
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Stern, Nicola. « Early Hominin Activity Traces at FxJj43, a One and a Half Million Year Old Locality in the Koobi Fora Formation, in Northern Kenya : a Field Report ». Proceedings of the Prehistoric Society 70 (2004) : 233–58. http://dx.doi.org/10.1017/s0079497x00001183.
Texte intégralRésumé :
FxJj43 is one of a series of Early Stone Age archaeological sites preserved in the Okote Member of the Koobi Fora Formation, in northern Kenya. It is the focus of a new research project that aims to explore the impact of time-averaging on the composition and characteristics of Early Stone Age archaeological assemblages. FxJj43 lends itself particularly well to this exercise because, unlike other sites in the Okote Member, it preserves a laterally extensive set of interlocking landforms. These include part of a sandy river channel, its southern bank, levee, and adjacent floodplain.Chipped stone artefacts and broken-up animal bones occur in clusters of varying size and density all the way along the 200 m long strip of outcrops containing the remnants of these landforms. Small-scale excavations aimed at investigating the characteristics of archaeological assemblages preserved in different palaeotopographic settings, and in clusters of varying size and density, suggest the existence of archaeological occurrences representing different amounts of overprinting. This underscores the long-term research potential of this locality for exploring the relationship between the material remains of individual behavioural events and agglomerations of debris resulting from many, often unrelated sets of activities.
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Boudane, Fatima, et Ali Berrichi. « Multi-Objective Artificial Bee Colony Algorithm for Parameter-Free Neighborhood-Based Clustering ». International Journal of Swarm Intelligence Research 12, no 4 (octobre 2021) : 186–204. http://dx.doi.org/10.4018/ijsir.2021100110.
Texte intégralRésumé :
Although various clustering algorithms have been proposed, most of them cannot handle arbitrarily shaped clusters with varying density and depend on the user-defined parameters which are hard to set. In this paper, to address these issues, the authors propose an automatic neighborhood-based clustering approach using an extended multi-objective artificial bee colony (NBC-MOABC) algorithm. In this approach, the ABC algorithm is used as a parameter tuning tool for the NBC algorithm. NBC-MOABC is parameter-free and uses a density-based solution encoding scheme. Furthermore, solution search equations of the standard ABC are modified in NBC-MOABC, and a mutation operator is used to better explore the search space. For evaluation, two objectives, based on density concepts, have been defined to replace the conventional validity indices, which may fail in the case of arbitrarily shaped clusters. Experimental results demonstrate the superiority of the proposed approach over seven clustering methods.
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Renedo-Mirambell, Martí, et Argimiro Arratia. « Identifying bias in network clustering quality metrics ». PeerJ Computer Science 9 (17 août 2023) : e1523. http://dx.doi.org/10.7717/peerj-cs.1523.
Texte intégralRésumé :
We study potential biases of popular network clustering quality metrics, such as those based on the dichotomy between internal and external connectivity. We propose a method that uses both stochastic and preferential attachment block models construction to generate networks with preset community structures, and Poisson or scale-free degree distribution, to which quality metrics will be applied. These models also allow us to generate multi-level structures of varying strength, which will show if metrics favour partitions into a larger or smaller number of clusters. Additionally, we propose another quality metric, the density ratio. We observed that most of the studied metrics tend to favour partitions into a smaller number of big clusters, even when their relative internal and external connectivity are the same. The metrics found to be less biased are modularity and density ratio.
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Hirai, Yutaka, Michiko S. Fujii et Takayuki R. Saitoh. « SIRIUS project. I. Star formation models for star-by-star simulations of star clusters and galaxy formation ». Publications of the Astronomical Society of Japan 73, no 4 (20 mai 2021) : 1036–56. http://dx.doi.org/10.1093/pasj/psab038.
Texte intégralRésumé :
Abstract Most stars are formed as star clusters in galaxies, which then disperse into galactic disks. Upcoming exascale supercomputational facilities will enable simulations of galaxies and their formation by resolving individual stars (star-by-star simulations). This will substantially advance our understanding of star formation in galaxies, star cluster formation, and assembly histories of galaxies. In previous galaxy simulations, a simple stellar population approximation was used. It is, however, difficult to improve the mass resolution with this approximation. Therefore, a model for forming individual stars that can be used in simulations of galaxies must be established. In this first paper of a series from the SIRIUS (SImulations Resolving IndividUal Stars) project, we demonstrate a stochastic star formation model for star-by-star simulations. An assumed stellar initial mass function (IMF) is randomly assigned to newly formed stars in this model. We introduce a maximum search radius to assemble the mass from surrounding gas particles to form star particles. In this study, we perform a series of N-body/smoothed particle hydrodynamics simulations of star cluster formations from turbulent molecular clouds and ultra-faint dwarf galaxies as test cases. The IMF can be correctly sampled if a maximum search radius that is larger than the value estimated from the threshold density for star formation is adopted. In small clouds, the formation of massive stars is highly stochastic because of the small number of stars. We confirm that the star formation efficiency and threshold density do not strongly affect the results. We find that our model can naturally reproduce the relationship between the most massive stars and the total stellar mass of star clusters. Herein, we demonstrate that our models can be applied to simulations varying from star clusters to galaxies for a wide range of resolutions.
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Hess, Sibylle, Wouter Duivesteijn, Philipp Honysz et Katharina Morik. « The SpectACl of Nonconvex Clustering : A Spectral Approach to Density-Based Clustering ». Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 juillet 2019) : 3788–95. http://dx.doi.org/10.1609/aaai.v33i01.33013788.
Texte intégralRésumé :
When it comes to clustering nonconvex shapes, two paradigms are used to find the most suitable clustering: minimum cut and maximum density. The most popular algorithms incorporating these paradigms are Spectral Clustering and DBSCAN. Both paradigms have their pros and cons. While minimum cut clusterings are sensitive to noise, density-based clusterings have trouble handling clusters with varying densities. In this paper, we propose SPECTACL: a method combining the advantages of both approaches, while solving the two mentioned drawbacks. Our method is easy to implement, such as Spectral Clustering, and theoretically founded to optimize a proposed density criterion of clusterings. Through experiments on synthetic and real-world data, we demonstrate that our approach provides robust and reliable clusterings.
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Ocko, Samuel A., et L. Mahadevan. « Collective thermoregulation in bee clusters ». Journal of The Royal Society Interface 11, no 91 (6 février 2014) : 20131033. http://dx.doi.org/10.1098/rsif.2013.1033.
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Swarming is an essential part of honeybee behaviour, wherein thousands of bees cling onto each other to form a dense cluster that may be exposed to the environment for several days. This cluster has the ability to maintain its core temperature actively without a central controller. We suggest that the swarm cluster is akin to an active porous structure whose functional requirement is to adjust to outside conditions by varying its porosity to control its core temperature. Using a continuum model that takes the form of a set of advection–diffusion equations for heat transfer in a mobile porous medium, we show that the equalization of an effective ‘behavioural pressure’, which propagates information about the ambient temperature through variations in density, leads to effective thermoregulation. Our model extends and generalizes previous models by focusing the question of mechanism on the form and role of the behavioural pressure, and allows us to explain the vertical asymmetry of the cluster (as a consequence of buoyancy-driven flows), the ability of the cluster to overpack at low ambient temperatures without breaking up at high ambient temperatures, and the relative insensitivity to large variations in the ambient temperature. Our theory also makes testable hypotheses for the response of the cluster to external temperature inhomogeneities and suggests strategies for biomimetic thermoregulation.
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Pfeffer, Joel, Nate Bastian, J. M. Diederik Kruijssen, Marta Reina-Campos, Robert A. Crain et Christopher Usher. « Young star cluster populations in the E-MOSAICS simulations ». Monthly Notices of the Royal Astronomical Society 490, no 2 (3 octobre 2019) : 1714–33. http://dx.doi.org/10.1093/mnras/stz2721.
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ABSTRACT We present an analysis of young star clusters (YSCs) that form in the E-MOSAICS cosmological, hydrodynamical simulations of galaxies and their star cluster populations. Through comparisons with observed YSC populations, this work aims to test models for YSC formation and obtain an insight into the formation processes at work in part of the local galaxy population. We find that the models used in E-MOSAICS for the cluster formation efficiency and high-mass truncation of the initial cluster mass function ($M_\rm {c,\ast }$) both quantitatively reproduce the observed values of cluster populations in nearby galaxies. At higher redshifts (z ≥ 2, near the peak of globular cluster formation) we find that, at a constant star formation rate (SFR) surface density, $M_\rm {c,\ast }$ is larger than at z = 0 by a factor of four due to the higher gas fractions in the simulated high-redshift galaxies. Similar processes should be at work in local galaxies, offering a new way to test the models. We find that cluster age distributions may be sensitive to variations in the cluster formation rate (but not SFR) with time, which may significantly affect their use in tests of cluster mass-loss. By comparing simulations with different implementations of cluster formation physics, we find that (even partially) environmentally independent cluster formation is inconsistent with the brightest cluster-SFR and specific luminosity-$\Sigma _\rm {SFR}$ relations, whereas these observables are reproduced by the fiducial, environmentally varying model. This shows that models in which a constant fraction of stars form in clusters are inconsistent with observations.
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An, Ji-Young. « Clustering and Determinant Analysis of Corporate Environmental Management Attitudes : Unsupervised Learning Techniques ». Korea International Trade Research Institute 19, no 4 (31 août 2023) : 211–28. http://dx.doi.org/10.16980/jitc.19.4.202308.211.
Texte intégralRésumé :
Purpose - The main objective of this study is to cluster companies based on environmental management attitudes using various indicators, and analyze differences in activities among the clusters to gain insights into environmental management performance.
Design/Methodology/Approach - The study encompasses panel data from 12 countries, 22 industry sectors, and 3,402 companies from 2013 to 2022. This study uses both machine learning methodology and conventional econometric methodology. The primary methodology involves using an unsupervised learning technique, K-means clustering, to categorize environmental management attitudes. Subsequently, Kernel Density estimation and Multinomial Logistic Regression were employed to conduct comparative analyses of environmental performance indicators within each cluster and identify the determinants shaping environmental management attitudes.
Findings - The research revealed the existence of five distinct clusters of companies with varying environmental management attitudes. Through Multinomial Logistics Regression, it identified that variables such as greenhouse gas emissions, energy consumption, total assets, return on assets, and other significantly influence environmental management attitudes.
Research Implications - By uncovering common characteristics and determinants within major countries and industries, this study offers valuable insights in promoting domestic environmental management in the context of rapidly changing international trade and investment environments. The findings provide policy implications and suggestions for fostering proactive environmental management practices among domestic companies.
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Wang, Long, Michiko S. Fujii et Ataru Tanikawa. « Impact of initial mass functions on the dynamical channel of gravitational wave sources ». Monthly Notices of the Royal Astronomical Society 504, no 4 (23 avril 2021) : 5778–87. http://dx.doi.org/10.1093/mnras/stab1157.
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ABSTRACT Dynamically formed black hole (BH) binaries (BBHs) are important sources of gravitational waves (GWs). Globular clusters (GCs) provide a major environment to produce such BBHs, but the total mass of the known GCs is small compared to that in the Galaxy; thus, the fraction of BBHs formed in GCs is also small. However, this assumes that GCs contain a canonical initial mass function (IMF) similar to that of field stars. This might not be true because several studies suggest that extreme dense and metal-poor environment can result in top-heavy IMFs, where GCs may originate. Although GCs with top-heavy IMFs were easily disrupted or have become dark clusters, the contribution to the GW sources can be significant. Using a high-performance and accurate N-body code, petar, we investigate the effect of varying IMFs by carrying out four star-by-star simulations of dense GCs with the initial mass of 5 × 105 M⊙ and the half-mass radius of 2 pc. We find that the BBH merger rate does not monotonically correlate with the slope of IMFs. Due to a rapid expansion, top-heavy IMFs lead to less efficient formation of merging BBHs. The formation rate continuously decreases as the cluster expands because of the dynamical heating caused by BHs. However, in star clusters with a top-heavier IMF, the total number of BHs is larger, and therefore, the final contribution to merging BBHs can still be more than that from clusters with the standard IMF, if the initial cluster mass and density are higher than those used in our model.
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Du, Mingjing, et Fuyu Wu. « Grid-Based Clustering Using Boundary Detection ». Entropy 24, no 11 (4 novembre 2022) : 1606. http://dx.doi.org/10.3390/e24111606.
Texte intégralRésumé :
Clustering can be divided into five categories: partitioning, hierarchical, model-based, density-based, and grid-based algorithms. Among them, grid-based clustering is highly efficient in handling spatial data. However, the traditional grid-based clustering algorithms still face many problems: (1) Parameter tuning: density thresholds are difficult to adjust; (2) Data challenge: clusters with overlapping regions and varying densities are not well handled. We propose a new grid-based clustering algorithm named GCBD that can solve the above problems. Firstly, the density estimation of nodes is defined using the standard grid structure. Secondly, GCBD uses an iterative boundary detection strategy to distinguish core nodes from boundary nodes. Finally, two clustering strategies are combined to group core nodes and assign boundary nodes. Experiments on 18 datasets demonstrate that the proposed algorithm outperforms 6 grid-based competitors.
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Maheshwari, G., G. Brown, D. A. Lauffenburger, A. Wells et L. G. Griffith. « Cell adhesion and motility depend on nanoscale RGD clustering ». Journal of Cell Science 113, no 10 (15 mai 2000) : 1677–86. http://dx.doi.org/10.1242/jcs.113.10.1677.
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Integrin adhesion receptors play a crucial role in regulating interactions between cells and extracellular matrix (ECM). Integrin activation initiates multiple intracellular signaling pathways and results in regulation of cell functions such as motility, proliferation and differentiation. Two key observations regarding the biophysical nature of integrin-mediated cell-matrix interactions motivated the present study: (1) cell motility can be regulated by modulating the magnitude of cell-substratum adhesion, by varying cell integrin expression level, integrin-ECM binding affinity or substratum ECM surface density; and (2) integrin clustering enables assembly of multiple cytoplasmic regulatory and structural proteins at sites of aggregated integrin cytoplasmic domains, activating certain intracellular signalling pathways. Here, using a minimal integrin adhesion ligand, YGRGD, we test the hypothesis that ligand clustering can affect cell migration in a manner related to its modulation of cell-substratum adhesion. We employ a synthetic polymer-linking method, which allows us to independently and systematically vary both the average surface density and the local (approx. 50 nm scale) spatial distribution of the YGRGD peptide, against a background otherwise inert with respect to cell adhesion. In this system, the ligand was presented in three alternative spatial distributions: singly, in clusters with an average of five ligands per cluster, or in clusters with an average of nine ligands per cluster; for each of these spatial distributions, a range of average ligand densities (1,000-200,000 ligands/micrometer(2)) were examined. Cluster spacing was adjusted in order to present equivalent average ligand densities independently of cluster size. The murine NR6 fibroblast cell line was used as a model because its migration behavior on ECM in the presence and absence of growth factors has been well-characterized and it expresses integrins known to interact with the YGRGD peptide. Using time-lapse videomicroscopy and analysis of individual cell movement paths, we find that NR6 cells can migrate on substrata where adhesion is mediated solely by the YGRGD peptide. As previously observed for migration of NR6 cells on fibronectin, migration speed on YGRGD is a function of the average surface ligand density. Strikingly, clustering of ligand significantly reduced the average ligand density required to support cell migration. In fact, non-clustered integrin ligands support cell attachment but neither full spreading nor haptokinetic or chemokinetic motility. In addition, by quantifying the strength of cell-substratum adhesion, we find that the variation of cell speed with spatial presentation of YGRGD is mediated via its effect on cell adhesion. These effects on motility and adhesion are also observed in the presence of epidermal growth factor (EGF), a known motility-regulating growth factor. Variation in YGRGD presentation also affects the organization of actin filaments within the cell, with a greater number of cells exhibiting stress fibers at higher cluster sizes of YGRGD. Our observations demonstrate that cell motility may be regulated by varying ligand spatial presentation at the nanoscale level, and suggest that integrin clustering is required to support cell locomotion.
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Sun, Xiao, Tongda Zhang, Yueting Chai et Yi Liu. « Localized Ambient Solidity Separation Algorithm Based Computer User Segmentation ». Computational Intelligence and Neuroscience 2015 (2015) : 1–16. http://dx.doi.org/10.1155/2015/829201.
Texte intégralRésumé :
Most of popular clustering methods typically have some strong assumptions of the dataset. For example, thek-means implicitly assumes that all clusters come from spherical Gaussian distributions which have different means but the same covariance. However, when dealing with datasets that have diverse distribution shapes or high dimensionality, these assumptions might not be valid anymore. In order to overcome this weakness, we proposed a new clustering algorithm named localized ambient solidity separation (LASS) algorithm, using a new isolation criterion called centroid distance. Compared with other density based isolation criteria, our proposed centroid distance isolation criterion addresses the problem caused by high dimensionality and varying density. The experiment on a designed two-dimensional benchmark dataset shows that our proposed LASS algorithm not only inherits the advantage of the original dissimilarity increments clustering method to separate naturally isolated clusters but also can identify the clusters which are adjacent, overlapping, and under background noise. Finally, we compared our LASS algorithm with the dissimilarity increments clustering method on a massive computer user dataset with over two million records that contains demographic and behaviors information. The results show that LASS algorithm works extremely well on this computer user dataset and can gain more knowledge from it.
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Unver, Mustafa, et Nihal Erginel. « Clustering applications of IFDBSCAN algorithm with comparative analysis ». Journal of Intelligent & ; Fuzzy Systems 39, no 5 (19 novembre 2020) : 6099–108. http://dx.doi.org/10.3233/jifs-189082.
Texte intégralRésumé :
Density Based Spatial Clustering of Application with Noise (DBSCAN) is one of the mostly preferred algorithm among density based clustering approaches in unsupervised machine learning, which uses epsilon neighborhood construction strategy in order to discover arbitrary shaped clusters. DBSCAN separates dense regions from low density regions and simultaneously assigns points that lie alone as outliers to unearth the hidden cluster patterns in the datasets. DBSCAN identifies dense regions by means of core point definition, detection of which are strictly dependent on input parameter definitions: ε is distance of the neighborhood or radius of hypersphere and MinPts is minimum density constraint inside ε radius hypersphere. Contrarily to classical DBSCAN’s crisp core point definition, intuitionistic fuzzy core point definition is proposed in our preliminary work to make DBSCAN algorithm capable of detecting different patterns of density by two different combinations of input parameters, particularly is a necessity for the density varying large datasets in multidimensional feature space. In this study, preliminarily proposed DBSCAN extension is studied: IFDBSCAN. The proposed extension is tested by computational experiments on several machine learning repository real-time datasets. Results show that, IFDBSCAN is superior to classical DBSCAN with respect to external & internal performance indices such as purity index, adjusted rand index, Fowlkes-Mallows score, silhouette coefficient, Calinski-Harabasz index and with respect to clustering structure results without increasing computational time so much, along with the possibility of trying two different density patterns on the same run and trying intermediary density values for the users by manipulating α margin.
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Gao, Xinyu, Guanjun Gao, Zhihui Li, Xiwu Li, Lizhen Yan, Yongan Zhang et Baiqing Xiong. « Effects of Different Heating and Cooling Rates during Solution Treatment on Microstructure and Properties of AA7050 Alloy Wires ». Materials 17, no 2 (8 janvier 2024) : 310. http://dx.doi.org/10.3390/ma17020310.
Texte intégralRésumé :
In the present study, the effects of varying heating and cooling rates during the solution treatment process on the microstructure and properties of AA7050 alloy wires were investigated using tensile tests, metallographic microscopy, electron backscattered diffraction, and transmission electron microscopy. It was found that the recrystallized grain size of the alloy, subjected to method of rapid heating, exhibited a smaller and more uniform distribution in comparison to method of slow heating. The low density of η′ strengthening phases after the artificial aging treatment was formed using air cooling method. Meanwhile, by using the water quenching method sufficient solute atoms and more nucleation sites were provided resulting in a large number of η′ strengthening phases being formed. In addition, the alloy processed using the water quenching method displayed higher strength than that treated using the air cooling method for the T6 and T73 states. Furthermore, coarse precipitates formed and less clusters were observed in the matrix, while high density nanoscale clusters and no continuous precipitation are formed when using the water quenching method.
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Southwell, C., et K. Weaver. « Evaluation of analystical procedures for density estimation from line-transect data : data grouping, data truncation and the unit of analysis ». Wildlife Research 20, no 4 (1993) : 433. http://dx.doi.org/10.1071/wr9930433.
Texte intégralRésumé :
We examined three aspects of line-transect analytical procedures: data grouping, data truncation and the use of individuals or clusters as the analytical unit. Bias and precision of density estimation in relation to various levels of these factors were assessed for 4 types of line-transect estimator (simple parametric, generalised parametric, non-parametric and quasi-strip) using line-transect survey data from macropod populations of known density. The effect of data grouping on bias and precision varied between estimators. Bias was stable across all grouping levels tested for the simple parametric estimator, and stable across aU but the coarsest grouping level for the generalised parametric and non-parametric estimators, but varied substantially across the range of levels tested for the quasi-strip estimator. Precision improved as the number of grouping levels increased for all estimators tested, but the extent of improvement varied between estimators, and for the estimator most affected, improvement was marginal beyond intermediate grouping levels. Density estimates were generally more accurate and precise when analysed in ungrouped form than in grouped form. No effects of truncation on bias or precision were detected. Varying the analytical unit did not affect bias, but precision was significantly lower for cluster analysis than individual analysis for all estimators.