Relative Local Density Research Articles

Acquisitions, spatial heterogeneity and economic impacts in Central European non-metro-politan regions

ABSTRACT This paper aims to make a conceptual and empirical contribution to our understanding of the effects of extra-regional assets and knowledge inflow, through mergers and acquisitions (M&A), in different types of regions. We revealed that the M&A market is not geographically homogeneous, and regions differ in all aspects of the M&A market: relative position, local density and foreign attractiveness, the same as in the M&A intensity. This heterogeneity is not random but follows a spatial pattern and differences in economic fundamentals of regions, but at the same time, there is no linear relationship between economic performance and M&A performance. The regional M&A market characteristics can explain differences in the impacts of M&A transactions on the economy, especially in the exit rate of companies after acquisition and in the change of employment. The impacts of M&A on the regional economy generally do not differ by sector of the acquired company. However, some patterns show that the negative effects are more present after acquisitions of firms in tradeable sectors in the less developed regions, whereas in the stronger regions, the most vulnerable sectors belong to the part of the economy which offers mundane, but occasionally purchased (and thus substitutable) goods.

Non-iterative border-peeling clustering algorithm based on swap strategy

Border-Peeling algorithm is a recently proposed density based clustering algorithm. The method of peeling off border points by continuous iteration and calculating the density influence value by using the Gaussian kernel distance makes the algorithm more complex. At the same time, there is a risk of excessive peeling of small clusters on unbalanced datasets, which leads to a large number of noise misidentification. In order to reduce the time consumption and improve the clustering performance on unbalanced datasets, this paper proposes a non-iterative border-peeling clustering algorithm. First, the potential core points are determined by the centroids of k-nearest neighbor. Secondly, the points with lower local relative density in the core points and the points with higher relative density in the border points are exchanged to complete the distinction between the core points and the border points. Then basic DBSCAN method is used to cluster core points and noise points. Finally, the associations between the border points and the core points are based on the number of reverse nearest neighbors of the border points in the core points. Our method has achieved competitive results on 10 synthetic datasets and 8 UCI real-world datasets.

Relative Local Electron Density Tuning in Metal-Covalent Organic Frameworks for Boosting CO2 Photoreduction.

The high electron density and efficient charge carrier separation are two important factors to affect photocatalytic activity, especially for the CO2 photoreduction reaction. However, the systematic studies on the structure-functional relationship regarding the above two factors based on precisely structure model are rarely reported. Herein, as a proof-of-concept, we developed a new strategy on the evaluation of local electron density by controlling the relative electron-deficient (ED) and electron-rich (ER) intensity of monomer at a molecular level based on three rational-designed vinylene-linked sp2 carbon-covalent organic frameworks (COFs). As expected, the as-prepared vinylene-linked sp2 carbon-conjugated metal-covalent organic framework (MCOFs) (VL-MCOF-1) with molecular junction exhibited excellent activities for CO2-to-HCOOH conversion (283.41 μmol g-1 h-1) and high selectivity of 97.1%, much higher than the VL-MCOF-2 and g-C34N6-COF, which is due to the synergistic effect of the multi-electronic metal clusters (Cu3(PyCA)3) (PyCA = pyrazolate-4-carboxaldehyde) as strong ER roles and cyanopyridine units as ED roles and active sites, as well as the boosted photo-induced charge separation efficiency of vinyl connection and increased light utilization ability. These results not only provide a strategy for regulating the electron-density distribution of photocatalysts at the molecular level but also offers profound insights for metal clusters-based COFs to effective CO2 conversion.

Relative Local Electron Density Tuning in Metal‐Covalent Organic Frameworks for Boosting CO2Photoreduction

AbstractThe high local electron density and efficient charge carrier separation are two important factors to affect photocatalytic activity, especially for the CO2photoreduction reaction. However, the systematic studies on the structure‐functional relationship regarding the above two factors based on precisely structure model are rarely reported. Herein, as a proof‐of‐concept, we developed a new strategy on the evaluation of local electron density by controlling the relative electron‐deficient (ED) and electron‐rich (ER) intensity of monomer at a molecular level based on three rational‐designed vinylene‐linked sp2carbon‐covalent organic frameworks (COFs). As expected, the as‐prepared vinylene‐linked sp2carbon‐conjugated metal‐covalent organic framework (MCOFs) (VL‐MCOF‐1) with molecular junction exhibited excellent activities for CO2‐to‐HCOOH conversion (283.41 μmol g−1 h−1) and high selectivity of 97.1 %, much higher than the VL‐MCOF‐2 and g‐C34N6‐COF, which is due to the synergistic effect of the multi‐electronic metal clusters (Cu3(PyCA)3) (PyCA=pyrazolate‐4‐carboxaldehyde) as strong ER roles and cyanopyridine units as ED roles and active sites, as well as the boosted photo‐induced charge separation efficiency of vinyl connection and increased light utilization ability. These results not only provide a strategy for regulating the electron‐density distribution of photocatalysts at the molecular level but also offers profound insights for metal clusters‐based COFs to effective CO2conversion.

Disentangling the “many-eyes”, “dilution effect”, “selfish herd”, and “distracted prey” hypotheses in shaping alert and flight initiation distance in a colonial seabird

Group living is thought to have important antipredator benefits for animals, owing to the mechanisms of shared vigilance (“many-eyes” hypothesis), risk dilution (“dilution effect” hypothesis), and relative safety in the center of the group (“selfish herd” hypothesis). However, it can also incur costs since social stimuli, such as conspecific aggression, may distract individuals from anti-predator behavior (“distracted prey” hypothesis). We simultaneously evaluated how these four different hypotheses shape anti-predator behaviors of breeding king penguins (Aptenodytes patagonicus), which aggregate into large colonies, experience frequent aggressive social interactions, and are regularly exposed to predation by giant petrels (Macronectes sp.) and brown skuas (Catharacta loonbergi) when breeding on land. We approached 200 incubating penguins at four different periods of the breeding season across a range of overall increasing colony densities. We measured the distance at which focal birds detected the approaching threat (alert distance: AD), whether birds decided to flee or not, and the distance of flight initiation (flight initiation distance: FID, viz. the bird attempting to walk away with its egg on its feet). We quantified relative local neighbor density, centrality within the colony (rank), and the number of aggressions the focal bird emitted towards neighbors during the approach. We found that birds engaged in aggressive conflicts with neighbors were less likely to flee, and that increasing relative local neighbor density at low and medium overall colony density resulted in a decrease in bird AD, both supporting the “distracted prey” hypothesis. However, at maximal overall colony density, increasing relative local neighbor density resulted in longer AD, supporting the “many-eyes” hypothesis. We found no support for the “dilution effect” and “selfish herd” hypotheses, and no effects of any hypothesis on FID.

A sleep scheduling algorithm of redundant nodes in power communication sensor networks based on relative local density

In order to overcome the problems of low network coverage and short network node survival time in the traditional node sleep scheduling algorithm, a redundant node sleep scheduling algorithm based on relative local density is proposed in this paper. The composition of power communication sensor network is analysed, and the energy receiving model of redundant nodes in power communication sensor network is constructed. The sleep scheduling of network redundant nodes is realised according to the relative local density redundant node sleep algorithm. The results show that when the number of nodes is 120, the network performance of this method is 5.18 and the network coverage can reach 99.93%. At the same time, the survival time of sensor nodes under this method is longer, this method can prolong the network life cycle, and the sleep scheduling effect of redundant nodes is better.

A sleep scheduling algorithm of redundant nodes in power communication sensor networks based on relative local density

A sleep scheduling algorithm of redundant nodes in power communication sensor networks based on relative local density

Mechanism of thermal gradients in spark plasma sintering of titanium and the resultant graded microstructure: A novel strategy of incorporating master sintering curve into finite element modeling

Spark plasma sintering (SPS) is an efficient consolidation process for metals and ceramics because of its high heating rates, lower sintering temperatures and shorter holding time than other sintering processes. To understand and utilize the thermal gradients that occur in SPS, the present work developed a strategy to incorporate master sintering curve (MSC) into a thermal-electric (TE) finite element modeling (FEM) to enable continuous nodal-specific simulation of the evolution of thermal and electrical properties of the powder compact with respect to both relative density and temperature during SPS. This combined model is proposed as an alternative to the thermal-electric-mechanical fully coupled model that is more computationally expensive and difficult to parameterize experimentally. Pure Ti was selected as the material for experimental verification because of its technological importance for aerospace and defense applications. While lab-scale Ti samples were sintered for construction and validation of MSC, a scaled-up Ti sample with diameter of 70 mm was made via SPS, and its microstructure were characterized to verify the accuracy of the MSC - TE FEM combined model. Both modeling and experimental results showed that the local relative density of the pure Ti decreased as the location moved radially from center to surface. The location-specific relative densities predicted by the combined model were within ±1.5% deviation from the experimental results, which verified the ability and accuracy of the MSC-TE FEM combined model to guide experimental design and parameter selection for control and utilization of gradients in SPS to achieve graded microstructure. • SPS of pure Ti has an apparent sintering activation energy of of 156.5 kJ/mol • Master sintering curve is incorporated into FEM for improved prediction of gradients • The accuracy of MSC-FEM combined model is experimentally validated • Deviation between the experimental and simulated results are <1.5%

Increased relative density and characteristic melt pool Signals at the edge in PBF-LB/M

Limited process control can cause metallurgical defect formation and inhomogeneous relative density in laser powder bed fusion manufactured parts. This study shows that process monitoring, based on optical melt-pool signal analysis is capable of tracing relative density variations: Unsupervised machine learning, applied to cluster multiple-slice monitoring data, reveals characteristic patterns in this noisy time-series signal, which can be co-registered with geometrical positions in the build part. For cylindrical 15–5 PH stainless steel specimens, manufactured under constant process parameters and post-analyzed by µ-computer tomography, correlations between such patterns and an increased local relative density at the edge have been observed. Finite element method (FEM) modeling of thermal histories at exemplary positions close to the edge suggest pre-heating effects caused by neighboring laser scan trajectories as possible reasons for the increased melt pool intensity at the edge. • Increased relative density at the edge of PBF-LB/M specimens observed in µ-CT scans. • Multi-layer data analysis reveals increased melt pool monitoring signal at the edge. • Unsupervised time series clustering identifies interpretable patterns in melt pool data. • FEM modeling of thermal histories suggests preheating as common cause in observed edge effects.

A new multi-scale topology optimization framework for optimal combinations of macro-layouts and local gradings of TPMS-based lattice structures

In this work, optimal combinations of macro-layouts and local gradings of triply periodic minimal surface (TPMS)-based lattice structures are obtained by using multi-scale topology optimization. A new innovative framework is proposed by using two density variables in each finite element. The first variable is the local relative lattice density and it sets the effective orthotropic elastic properties of the element, which in turn are obtained by using numerical homogenization of representative volume elements of the particular TPMS-based lattice structure of interest. The second variable is a standard topology optimization macro density variable, which defines if the element should be treated as a void or contain the graded lattice structure by letting this variable be governed by the rational approximation of material properties (RAMP) model. By using such density variables for all elements, the compliance is minimized by separately constraining the volume of lattice structure and the volume of macro-layout by using two independent constraints. For benchmarks in 3 D, it is demonstrated that the stiffness is increased significantly by including local grading of the lattice structure compared to using a constant lattice density. It is also demonstrated how ultra-lightweight designs can be generated using the multi-scale formulation, and how the optimal multi-scale solutions easily can be realized to printable stl-files by using implicit based geometry modeling. Finally, the new multi-scale topology optimization framework is utilized to generate an optimal design combination of macro-layout and local grading of frame-based Gyroid structure for the established GE-bracket benchmark.

Programmed Plastic Deformation in Mathematically-Designed Architected Cellular Materials

The ability to control the exhibited plastic deformation behavior of cellular materials under certain loading conditions can be harnessed to design more reliable and structurally efficient damage-tolerant materials for crashworthiness and protective equipment applications. In this work, a mathematically-based design approach is proposed to program the deformation behavior of cellular materials with minimal surface-based topologies and ductile constituent material by employing the concept of functional grading to control the local relative density of unit cells. To demonstrate the applicability of this design tactic, two examples are presented. Rhombic, and double arrow deformation profiles were programmed as the desired deformation patterns. Grayscale images were used to map the relative density distribution of the cellular material. 316L stainless steel metallic samples were fabricated using the powder bed fusion additive manufacturing technique. Results of compressive tests showed that the designed materials followed the desired programmed deformation behavior. Results of mechanical testing also showed that samples with programmed deformation exhibited higher plateau stress and toughness values as compared to their uniform counterparts while no effect on Young’s modulus was observed. Plateau stress values increased by 8.6% and 13.4% and toughness values increased by 5.6% and 11.2% for the graded-rhombic and graded-arrow patterns, respectively. Results of numerical simulations predicted the exact deformation behavior that was programmed in the samples and that were obtained experimentally.

The Struggle of Ash—Insights from Long-Term Survey in Latvia

The dieback of common ash (Fraxinus excelsior L.) has dramatically decreased the abundance of the species in Europe; however, tolerance of trees varies regionally. The tolerance of trees is considered to be a result of synergy of genetic and environmental factors, suggesting an uneven future potential of populations. This also implies that wide extrapolations would be biased and local information is needed. Survival of ash during 2005–2020, as well as stand- and tree-level variables affecting them was assessed based on four surveys of 15 permanent sampling plots from an eastern Baltic region (Latvia) using an additive model. Although at the beginning of dieback a relatively low mortality rate was observed, it increased during the 2015–2020 period, which was caused by dying of the most tolerant trees, though single trees have survived. In the studied stands, ash has been gradually replaced by other local tree species, though some recruitment of ash was locally observed, implying formation of mixed broadleaved stands with slight ash admixture. The survival of trees was related to tree height and position within a stand (relative height and local density), though the relationships were nonlinear, indicating presence of critical conditions. Regarding temporal changes, survival rapidly dropped during the first 16 years, stabilizing at a relatively low level. Although low recruitment of ash still implies plummeting economic importance of the species, the observed responses of survival, as well as the recruitment, imply potential to locally improve the survival of ash via management (tending), hopefully providing time for natural resistance to develop.

Local relative density fluctuation in the early stage of a sintered glass sphere compact determined by X-ray computed tomography

The relative density of a sintered glass-powder compact varies at the local level due to its heterogeneous nature, which makes its characterization essential. In this work, high-resolution X-ray computed tomography (XCT) was used to quantitatively characterize the local relative density fluctuation of a sintered glass compact in its initial stage. The degree of heterogeneity of the microstructure was calculated taking into account the coarseness parameter. With a basis of 23,500 particles scanned in the representative volume element (RVE), the local environment was subdivided into three different groups of particles, represented by a cubic cell with a volume equivalent to that of approximately 600, 80 and 10 spherical particles with a diameter of 80 μm. Independent of the particle group analysed, we found that the maximum of the local relative density distributions, which could be described by a normal distribution function, always occurs around the relative density of the RVE. However, the fluctuation of the data showed a considerable change regarding the width, which increases as the volume of the analysed group of particles decreases, suggesting that particle packing is more heterogeneous on a small scale. In particular, we observed that the heterogeneity of the microstructure for the RVE under consideration becomes pronounced for groups of approximately 10 to 80 particles.

Simulation and Physical Experiment Study on Powder Metallurgy Preparation of Silicon Composite Powder

The compaction and sintering processes of multi-component silicon powders, including single-action die compaction, uniaxial hot pressing and bidirectional hot compaction, were numerically performed by FEM (finite element method) modelling. The relationships of initial packing structure, compaction method, pressing pressure and sintering temperature between overall relative densities of multi-component silicon components were systematically discussed and studied. Meanwhile, various macro- and microscopic properties of silicon composite powders were carefully characterized, such as overall and local relative density, local stress distributions and void filling behaviour. The results show that fully compacted silicon composite targets with low internal stress can be obtained by using uniaxial hot pressing or bidirectional hot compaction method. And the physical experiments were carried out to verify the accuracy of the simulation results.

Overlapping Community Detection Method Based on Network Representation Learning and Density Peaks

At present, the research on complex social networks has attracted extensive attention from scholars, and community detection is an important research direction in the study of network structure. Network data is often high-dimensional and very large, which makes it very difficult to process. Therefore, it is of great significance for community detection to represent network structure with low-dimensional vector. And many real world social networks contain overlapping communities. In this paper, we propose an overlapping community detection method based on network representation learning and density peaks, called NRLDP. First, it uses network representation learning technology to represent the unweighted network or weighted network with low-dimensional vectors. Then, it applies the density peaks clustering algorithm to overlapping community detection, uses cosine similarity to calculate the distance between nodes, and improves the local density calculation method. Finally, it selects the core node according to the relative distance and local density, and allocates the remaining nodes to achieve overlapping community detection of unweighted network or weighted network. Compared with relevant community detection methods on real world social networks and synthetic networks of LFR Benchmark, the results of the experiment show that our proposed approach is effective and accurate.

Density-Sensitive Implicit Functions Using Sub-Voxel Sampling in Additive Manufacturing

In the context of lattice-based design and manufacturing, the problem of physical realization of density maps into lattices of a particular family is central. Density maps are prescribed by design optimization algorithms, which seek to fulfill structural demands on a workpiece, while saving material. These density maps cannot be directly manufactured since local graded densities cannot be achieved using the bulk solid material. Because of this reason, existing topology optimization approaches bias the local voxel relative density to either 0 (void) or 1 (filled). Additive manufacturing opens possibilities to produce graded density individuals belonging to different lattice families. However, voxel-level sampled boundary representations of the individuals produce rough and possibly disconnected shells. In response to this limitation, this article uses sub-voxel sampling (largely unexploited in the literature) to generate lattices of graded densities. This sub-voxel sampling eliminates the risk of shell disconnections and renders better surface continuity. The manuscript devises a function to produce Schwarz cells that materialize a given relative density. This article illustrates a correlation of continuity against stress concentration by simulating C 0 and C 1 inter-lattice continuity. The implemented algorithm produces implicit functions and thus lattice designs which are suitable for metal additive manufacturing and able to achieve the target material savings. The resulting workpieces, produced by outsource manufacturers, are presented. Additional work is required in the modeling of the mechanical response (stress/strain/deformation) and response of large lattice sets (with arbitrary geometry and topology) under working loads.

Design of Lattice Structures Using Local Relative Density Mapping Method

In order to solve the problem of substantial computational resources of lattice structure during optimization, a local relative density mapping (LRDM) method is proposed. The proposed method uses solid isotropic microstructures with penalization to optimize a model at the macroscopic scale. The local relative density information is obtained from the topology optimization result. The contour lines of an optimized model are extracted using a density contour approach, and the triangular mesh is generated using a mesh generator. A local mapping relationship between the elements’ relative density and the struts’ relative cross-sectional area is established to automatically determine the diameter of each individual strut in the lattice structures. The proposed LRDM method can be applied to local finite element meshes and local density elements, but it is also suitable for global ones. In addition, some cases are considered in order to test the effectiveness of the LRDM method. The results show that the solution time of the LRDM is lower than the RDM method by approximately 50%. The proposed method provides instructions for the design of more complex lattice structures.

Accumulated Relative Density Outlier Detection For Large Scale Traffic Data

Outlier detection (OD) has been popularly developed in many fields such as medical diagnosis, network intrusion detection, fraud detection and military surveillance. This paper presents an accumulated relative density (ARD) OD method to identify outliers which possess relatively low or high local density. Previously, many density-based OD methods, such as local outlier factor (LOF) and Local Correlation Integral (LOCI), are applied to detect outliers which have low relative density in the data set. Relative local density (RLD) is measured and then compared with each other by statistics to label abnormities. In the proposed ARD method, a big circle centered at every data point is formed first. This big circle covers some data points with its radius. Then, for each encapsulated point inside this big circle, a small circle centered at itself is defined. Afterward, the ratio of number of covered data points inside the small circle of that particular point to the average number of data points in all small circles is defined as the RLD. After RLDs of all data points are calculated, a point whose RLD deviates greatly from the mean of all RLDs will be labeled as an outlier, otherwise as inliers. This ARD method was evaluated by a real world traffic data set which was originally represented as spatial-temporal (ST) traffic flow signals. The ST signals were processed by a principal component analysis (PCA) to reduce its dimension into two-dimensional 2D data points. An average 95% detection success rate (DSR) of OD can be achieved by this method.

Variable Density Cellular Structure Design Method Base on Local Relative Density Mapping

Variable Density Cellular Structure Design Method Base on Local Relative Density Mapping

Density functional theory study of water-gas shift reaction on TM@Cu12 core-shell nanoclusters

The mechanism of water-gas shift reaction on the transition metal of Co, Ni, Cu (from the 3d row), Rh, Pd, Ag (from the 4d row), Ir, Pt, and Au (from the 5d row) @Cu12 bimetallic clusters have been studied using density functional theory (DFT) calculations. Three reaction mechanisms including redox, carboxyl, and formate mechanisms, which are equal to CO* + O* → CO2 (g), CO* + OH* → COOH* → CO2 (g) + H*, and CO* + H* + O* → CHO* + O* → HCOO** → CO2 (g) + H*, respectively, have been studied. The result revealed that the WGSR prefer to follow the carboxyl mechanism on the TM@Cu12 surfaces. The rate-controlling step of WGS reaction is H2O dissociation into OH and H or COOH decomposition into CO and OH. The transition metal additive in Cu cluster could enhance the activity of water dissociation, which is beneficial for WGS reaction. Especially, doping Ni has the largest promotion effect in reducing the active barrier, the reason is electronic effect. The calculation indicates that Ni@Cu12 is thus the promising candidates for improved WGSR catalysts. In addition, The TOF values are studied to estimate effectively activity of the TM@Cu12 cluster. To get insight into conclusion, reaction mechanism and structure of cluster was elucidated by the relative energy profiles and detailed electronic local density of states (LDOS).