Common Neighbor Research Articles

Factors affecting the structure, phase transition and crystallization process of AlNi nanoparticles

Understanding the relationship between the molecular structure and processing conditions of nanomaterials is crucial to able predict their final properties. This paper investigates the effect of some processing conditions dealing with heating speed; atomic numbers, atom at temperature; annealing time (t) on the phase transition and crystallization processes of an AlNi nanoparticles by using molecular dynamics (MD) method embedded with Sutton-Chen (SC) interaction potential and free boundary conditions. Quantitively structural characteristics, phase transition and crystallization process are analyzed through radial distribution function (RDF), the total energy of the system (Etot), size (D) and Common Neighborhood Analysis (CNA) methods. The different structural unit numbers of materials such as Face Centered Cubic (FCC), Hexagonal Close-Packed (HCP), Body-Centered Cubic (BCC), Amorphous (Amor) are observed with variation of inlet parameters. Besides, by using different mathematical models, various molecular parameters are determined and a relationship between size of nanoparticle (D), total energy of the system (Etot) with atomic number (N) was also established by which D ∼ N−1/3 and Etot ∼ N−1.

Simulation on the Factors Affecting the Crystallization Process of FeNi Alloy by Molecular Dynamics.

This paper investigates the crystallization process of FeNi alloys with different impurity concentrations of Ni(x) [x = 10% (Fe90Ni10), 20% (Fe80Ni20), 30% (Fe70Ni30), 40% (Fe60Ni40), and 50% (Fe50Ni50)] at temperature (T) = 300 K and Fe70Ni30 at heating rates of 4 × 1012, 4 × 1013, and 4 × 1014 K/s at different temperatures, T = 300, 400, 500, 600, 700, 900, 1100, and 1300 K. Molecular dynamics models with the Sutton–Chen embedded interaction potential and recirculating boundary conditions are used to calculate the molecular parameters of alloys, such as radial distribution function, total energy of the system (Etot), size (l), and crystallization temperature (through the relationship between Etot and T). The common neighborhood analysis method is used to confirm the theoretical results of crystallization for Fe–Fe, Fe–Ni, and Ni–Ni. The annealing process did not have an effect on the crystallization process of FeNi alloys. The effect of Ni content, heating rate, and annealing time on structural unit numbers, such as face-centered cubic, hexagonal close-packed, blocked cubic center, and amorphous, and the crystallization process of FeNi alloys is also investigated.

Determining phase transition using potential energy distribution and surface energy of Pd nanoparticles

Molecular dynamics simulation is employed to understand the thermodynamic behavior of cuboctahedron (cub) and icosahedron (ico) nanoparticles with 2–20 number of shells (55–28,741 atoms). The embedded atom method was used to describe the interatomic potential. Conventional melting criteria such as potential energy and specific heat capacity (Cp) caloric curves as well as structure analysis by radial distribution function (G(r)) and common neighbor analysis (CNA) were utilized simultaneously to provide a comprehensive picture of the melting process. It is shown that the potential energy distribution and surface energy (γp) proposed here are holding several advantages over previous criteria. In particular, potential energy distribution can distinguish between interior and surface atoms and even corner, edge and plane atoms at the surface. While G(r) and CNA are not surface sensitive methods and cannot distinguish between surface melting and an allotropic transition. It is also shown that allotropic change appears more clearly in Cp and γp rather than potential energy. However, determining accurate Cp requires enough sampling to be averaged. Finally, a few issues in the current methods for determining γp were discussed and a simple method based on available models was proposed which, independent of estimation of the surface area, predicts the correct temperature and size-dependent trend in agreement with Guggenheim-Katayama and Tolman’s models, respectively.

A seed-extended algorithm for detecting protein complexes based on density and modularity with topological structure and GO annotations

BackgroundThe detection of protein complexes is of great significance for researching mechanisms underlying complex diseases and developing new drugs. Thus, various computational algorithms have been proposed for protein complex detection. However, most of these methods are based on only topological information and are sensitive to the reliability of interactions. As a result, their performance is affected by false-positive interactions in PPINs. Moreover, these methods consider only density and modularity and ignore protein complexes with various densities and modularities.ResultsTo address these challenges, we propose an algorithm to exploit protein complexes in PPINs by a Seed-Extended algorithm based on Density and Modularity with Topological structure and GO annotations, named SE-DMTG to improve the accuracy of protein complex detection. First, we use common neighbors and GO annotations to construct a weighted PPIN. Second, we define a new seed selection strategy to select seed nodes. Third, we design a new fitness function to detect protein complexes with various densities and modularities. We compare the performance of SE-DMTG with that of thirteen state-of-the-art algorithms on several real datasets.ConclusionThe experimental results show that SE-DMTG not only outperforms some classical algorithms in yeast PPINs in terms of the F-measure and Jaccard but also achieves an ideal performance in terms of functional enrichment. Furthermore, we apply SE-DMTG to PPINs of several other species and demonstrate the outstanding accuracy and matching ratio in detecting protein complexes compared with other algorithms.

Research on mechanism of nanoscale cutting with arc trajectory for monocrystalline silicon based on molecular dynamics simulation

Movement trajectory of diamond tool during an ultra-precision cutting may be nonlinear due to external vibrations. Hence, we investigate nanoscale cutting of monocrystalline silicon using molecular dynamics simulation when the diamond tool trajectory contains an arc segment. Surface morphology, atomic displacement, radial distribution function, coordination values, common neighbor analysis, temperature variation and distribution of von Mises stress and hydrostatic stress are studied by changing the arc radius of tool path. An optimal surface integrity for the workpieces is obtained when the arc radius is 30 Å. Displacement vector analysis shows that the atoms at the initial position between the diamond tool and the workpiece have relatively large displacement. Furthermore, cutting distance has great influence on radial distribution function and atomic coordination values. Dislocation analysis indicates that the subsurface of workpiece with the arc radius of 30 Å is the smoothest, while temperature analysis reveals that only the maximum temperature of this workpiece exceeds 1000 K. Finally, the stress analysis indicates that the average hydrostatic stress decreases before increasing with the arc radius. For comparison, the average von Mises stress increases gradually. In addition, peak value of the two average stresses resides at the middle and the end of the arc, respectively. The curve trajectory of the tool results in the concentration of the hydrostatic stress and the von Mises stress in the local region of workpiece subsurface.

Effect of different crystal orientations on the surface integrity during nanogrinding of monocrystalline nickel

During nanofabrication, the processing of different crystal faces along the surface of a workpiece varies because of size effects. The burr height and subsurface damage during nanogrinding of different crystal orientations in monocrystalline nickel are simulated by molecular dynamics in this study. The burr height and depth of the subsurface deformation layer are calculated quantitatively by atomic displacement, common neighbor analysis and dislocation analysis techniques. Among the directions considered in this paper, the burr height is the smallest when grinding in the (110)[110] direction, and the depth of the subsurface deformation layer is small when grinding along the (111) plane. This study demonstrates the effect of different slip paths on burr height and provides a reference for the actual processing of face-centered cubic crystals.

A molecular dynamics study on cooling rate effect on atomic structure of solidified silver nanoparticles

The atomic structures and solidification point of silver nanoparticles (SNPs) are studied in a series of molecular dynamics simulations based on the empirical embedded atom methods (EAM). The solidification point is calculated from the extracted potential energy during the cooling process, whereas the atomic structures are analyzed using the common neighbor (CN) method. The results indicate that the structures of the solidified SNPs are very sensitive to both the applied cooling rate and the particle size. We find the critical cooling rate where a glassy structure is observed. Below the critical rate, polycrystalline nanoparticles are formed, where the percentage of the close-packed structures, i.e., FCC and HCP, decreases with increasing cooling rate. Moreover, the proportion of those structures is always larger with a bigger particle size for an identical applied cooling rate. The findings in this study provide useful information for many practical applications where the nanostructure strongly affects thermal management and operational efficiency.

The Republic of Belarus in the Common Neighborhood of the Russian Federation and the European Union

The Republic of Belarus in the Common Neighborhood of the Russian Federation and the European Union

Probabilistic diagnosis of clustered faults for hypercube-based multiprocessor system

As the sizes of multiprocessor systems grow, chances of processors becoming faulty increase, making it an important issue to diagnose faulty nodes in the system. Different models have been proposed and studied. One proposed by Huang et al. employed a probabilistic fault model to determine the status of a cluster of nodes in rectangular grid structures [8]. Later, Tang et al. extended the diagnosis algorithm to more general, regular topologies, in which any pair of adjacent nodes has no common neighbors [25]. In a recent work by Lu et al., the algorithm was further extended to regular topologies where any pair of adjacent nodes has a certain number of common neighbors [18]. In this paper, we extend the threshold to apply the probabilistic diagnosis algorithm for hypercube-based multiprocessor system, and carry out an analysis on the algorithm's effectiveness. The analysis shows a very high rate of correct diagnosis, both for an individual node and for nodes as a whole. Although the analysis is done for a particular regular network (the hypercube), the outcome can serve as a useful reference, and can shed light on the effectiveness of the probabilistic diagnosis for a large group of triangle-free multiprocessor systems.

On the role of Cu-Zr amorphous intergranular films on crack growth retardation in nanocrystalline Cu during monotonic and cyclic loading conditions

In the present study, molecular dynamics simulation was used to investigate the influence of amorphous intergranular films (AIF) and its thickness on possible crack retardation in nanocrystalline Cu under tensile and cyclic loading conditions. Structural analyses were carried out based on different methods such as centro-symmetry parameter, common neighbor analysis, and atomic strain. Results showed that specimens with AIF thickness as small as 0.5 nm can restrict the propagation of both perpendicular and parallel cracks during uniaxial tensile deformation. By increasing the AIF thickness, the crack propagation was found to be further retarded due to crack tip blunting. Atomic strain analysis also revealed that thicker AIF localized the strain distribution more strongly thus inhibiting the nucleation of multiple intergranular cracks and subsequent rapid fracture. In case of cyclic loading, the strain was accumulated through the formation of twins/stacking faults when the AIF thickness was 0.5 and 1 nm, which can interact with the AIF and eventually cause the nucleation of voids/cracks. However, increasing the AIF thickness to 2 nm can restrict such mechanism as the strain was mostly accommodated by the amorphous phase.

Detection of Fake Accounts in Social Networks Based on One Class Classification

Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity measures somethings such as common neighbors, common neighbors graph edges, cosine, and the Jaccard similarity coefficient are calculated based on adjacency matrix of the corresponding graph of the social network. In the next step, in order to reduce the complexity of data, Principal Component Analysis is applied to each computed similarity matrix to provide a set of informative features. then, a set of highly informative eigenvectors are selected using elbow-method. Extracted features are employed to train a One Class Classification (OCC) algorithm. Finally, this trained model is employed to identify fake accounts. As our experimental results indicate the promising performance of the proposed method a detection accuracy and false negative rates are 99.6% and 0%, respectively. We conclude that bringing similarity measures and One Class Classification algorithms into play, rather than the multi-class algorithms, provide better results.

Influence of Stress on Creep Behavior of Ni60Zr40 Glass-Reinforced Ni Nanocomposite Investigated by Atomistic Simulations

In this present study, molecular dynamics simulations of creep deformation at 1200 K temperature and different stresses have been performed to study the influence of stress on the creep behavior of Ni60Zr40 glass-reinforced nanocrystalline (NC) Ni nanocomposite using embedded atom method potential. Adaptive common neighbor analysis, centro-symmetry parameter estimation, Voronoi polyhedra, atomic trajectory and radial distribution functions are implemented to present structural evolution during creep process, thereby providing an insight into the underlying mechanism. The specimen is observed to undergo substantial amorphization with the progress of creep deformation owing to stress-induced diffusion of Zr atoms to NC Ni through the Ni60Zr40 glass–NC Ni interface and thickening of grain boundaries, which eventually causes a negative creep phenomenon at the later stage of tertiary creep regime. Calculated stress exponent for Ni60Zr40 glass-reinforced nanocrystalline (NC) Ni nanocomposite is equal to 0.64.

Molecular dynamics factors affecting on the structure, phase transition of Al bulk

In this work, we study the effect of atomic number (N) at temperature (T), T = 300 K; effect of T to Al5324 bulk; effect of annealing time (t) to Al5324 bulk at crystallization temperature (Tg), effect of Tg = 600 K on structure, phase transition of Al bulk by Molecular Dynamics (MD) method with embedded Sutton-Chen (SC) potential and recirculating boundary conditions. The results were analyzed through Radial Distribution Function (RDF), total energy of the system (Etot), size (l), Common Neighborhood Analysis (CNA) method, crystallization temperature (Tg) (via relationship between Etot, T). The obtained results show that the size (l) of Al bulk is always proportional with atomic number (N) according to the formula l ∼ N−1/3 and the total energy of the system (Etot) always proportional to the number of atoms (N) according to the formula Etot ∼ N−1. In particular, Al bulk always exists in three types of structures, including: Face Centred Cubic (FCC), Hexagonal Close-Packed (HCP), and Amorphous (Amor) structure. When atomic number (N) is increased, the temperature (T) decreases and the tempering time (t) increases then the number units of FCC, HCP increases, Amor decreases leads to change structure and phase transition of Al bulk.

Caregiver Perceptions of Environmental Facilitators and Barriers to Healthy Eating and Active Living During Summer: Findings from the Project SWEAT Study (P04-143-19)

ObjectivesTo determine caregiver perceptions of neighborhood-level environmental barriers and facilitators to healthy eating and active living (HEAL) among children living in low-income, urban neighborhoods during the summer. MethodsThe current study was a part of a prospective observational study - Project SWEAT - which investigated determinants of unhealthy weight gain during the summer months in economically disadvantaged school-age children. Caregivers with students in grades preK–5th attending 2 Columbus, OH elementary schools were recruited. Participants completed a demographic survey. To explore neighborhood-level environmental barriers and facilitators to HEAL, participants engaged in a modified HEAL MAPPS (Healthy Eating Active Living Mapping Attributes using Participatory Photographic Surveys) protocol, which included 5 phases: 1) orientation; 2) photographing and geotagging facilitators and barriers to HEAL on daily routes using a Garmin Oregon 650 device; 3) in-depth interview (IDI) discussing images and routes taken; 4) focus group per school site; and 5) culminating local community stakeholder meeting. ResultsTen families enrolled; 9 families completed photographing, geotagging and IDIs; 5 families participated in focus groups. A majority (77.8%, n = 7) of caregivers were African-American, female (88.9%, n = 8), and low-income (55.6%, n = 5). Preliminary analyses of photograph and IDI themes include: 1) walkway infrastructure crucial for healthy eating and active living; 2) scarce accessibility to healthy, affordable foods; 3) multiple abandoned properties; and 4) unsafe activity near common neighborhood routes. ConclusionsResults from this pilot indicate caregivers perceive both environmental barriers and facilitators to healthy eating and active living during the summer. Additional research should be conducted to confirm findings from this study and compare findings to different settings (e.g., rural and suburban). Funding SourcesUSDA North Central Nutrition Education Center for Excellence.

Formula omitted]-colouring [formula omitted]-free graphs in subexponential time

A graph is called Pt-free if it does not contain the path on t vertices as an induced subgraph. Let H be a multigraph with the property that any two distinct vertices share at most one common neighbour. We show that the generating function for (list) graph homomorphisms from G to H can be calculated in subexponential time 2Otnlog(n) for n=|V(G)| in the class of Pt-free graphs G. As a corollary, we show that the number of 3-colourings of a Pt-free graph G can be found in subexponential time. On the other hand, no subexponential time algorithm exists for 4-colourability of Pt-free graphs assuming the Exponential Time Hypothesis. Along the way, we prove that Pt-free graphs have pathwidth that is linear in their maximum degree.

Link prediction via linear optimization

Link prediction is an elemental challenge in network science, which has already found applications in guiding laboratorial experiments, digging out drug targets, recommending online friends, probing network evolution mechanisms, and so on. With a simple assumption that the likelihood of the existence of a link between two nodes can be unfolded by a linear summation of neighboring nodes’ contributions, we obtain the analytical solution of the optimal likelihood matrix, which shows remarkably better performance in predicting missing links than the state-of-the-art algorithms for not only simple networks, but also weighted and directed networks. To our surprise, even some degenerated local similarity indices from the solution outperform well-known local indices, which largely refines our knowledge, for example, the number of 3-hop paths between two nodes more accurately predicts missing links than the number of 2-hop paths (i.e., the number of common neighbors), while in previous methods, longer paths are always considered to be less important than shorter paths.

Beyond bond links in complex networks:Local bridges, global bridges and silk links

Many network researchers use intuitive or basic definitions when discussing the importance of strong and weak links and their roles. Others use an approach best described as “if not strong, then weak” to determine the strengths and weaknesses of individual links, thus deemphasizing hierarchical network structures that allow links to express different strength levels. Here we describe our proposal for a hierarchical edge type analysis (HETA) algorithm for determining link types at multiple network hierarchy levels based on the common neighbor concept plus statistical factors such as bond links, kth-layer local bridges, global bridges, and silk links—all generated during long-term network development and evolution processes. Two sets of networks were used to validate our proposed algorithm, one consisting of 16 networks employed in multiple past studies, and one consisting of two types of one-dimensional small-world networks expressing different random rewiring or shortcut addition probabilities. Two applications with potential for developmental contributions are demonstrated: a network fingerprint analysis framework, and a hierarchical network community partition method.

Distributed Model Predictive Control for Cooperative and Flexible Vehicle Platooning

This paper investigates the cooperative and flexible vehicle platooning problem in automated highway systems. We formulate the platoon into a dynamically decoupled system and address the flexible platooning problem using distributed model predictive control (DMPC) techniques. A two-step noniterative DMPC strategy is proposed that sequentially solves local components of a constrained optimal control problem over two batches of vehicle clusters based on intervehicle communication. By introducing the clustering procedure, the proposed DMPC scheme only requires compatibility constraints of common neighbors of two adjacent vehicle clusters. With the two-step DMPC scheme, stability of the overall closed-loop system is guaranteed by a series of linear matrix inequalities that can be efficiently solved in practical applications. Collision-free properties are addressed using coupled state constraints together with terminal sets during a cooperation procedure. Simulations of flexible platooning are conducted for both joining and leaving events to show the effectiveness of the two-step DMPC scheme.

Atomistic study on shape memory properties of Ni\u2013Al alloys

The shape memory properties of Ni–Al alloy are investigated using molecular dynamics simulation. The phase transformation behaviors for various Ni composition ratios are studied under quasistatic cooling and heating process. Various loadings, i.e., uniaxial, shear, and biaxial, are applied on a 68% Ni–Al alloy till plasticity takes place. The atomic configurations are inspected and analyzed using a common neighbor parameter. The shape recovery capability of the plastically deformed alloy is examined after heating above the phase transformation temperature. It is found that there would be shape recovery if the twinning plane reorientation or moving was the major yielding mechanism. For those loadings in which stacking faults or dislocations nucleate, the deformed model would not restore to its original shape after heating and the corresponding maximum shear stress is noticeably higher. There is no direct dependence between the yield strain and the shape recovery capability. Our findings could provide a possible explanation for the functional fatigue of the polycrystalline shape memory alloy.

Community detection in facebook activity networks and presenting a new multilayer label propagation algorithm for community detection

The emergence of online social networks has revolutionized millions of web users’ behavior so that their interactions with each other produce huge amounts of data on different activities. Community detection, herein, is one of the most important tasks. The very recent trend is to detect meaningful communities based on users’ interactions or the activity network. However, in many of such studies, authors consider the basic network model while almost ignoring the model of the interactions in the multi-layer network. In this research, an experimental study is done to compare community detection in Facebook friendship network to that of activity network, considering different activities in Facebook OSN such as sharing. Then, a new community detection evaluation metric based on homophily is proposed. Eventually, a new method of community detection based on different activities in Facebook social network is presented. In this method, we generalized three familiar similarity methods, Jaccard, Common Neighbors and Adamic-Adar for multi-layered network model.