Node Arc Research Articles

Survival analysis of recurrent breast cancer patients using mix Bayesian network

IntroductionBreast cancer (BC) is the most common cancer among women. Iranians have an 11% BC recurrence rate, which lowers their survival rates. Few studies have investigated cancer recurrence survival rates. This study's major purpose is to use a mixed Bayesian network (BN) to analyze recurrent patients' survival. Material and methodsThis study aimed to evaluate the pathobiological features, age, gender, final status, and survival time of the patients. Bayesian imputation was used for missing data. The performance of BN was optimized through the utilization of a blacklist and prior probability. After structural and parametric learning, posterior conditional probabilities and mean survival periods for the node arcs were predicted. The hold-out technique based on the posterior classification error was used to investigate the model's validation. ResultsThe study included 220 cancer recurrence patients. These patients averaged 47 years old. The BN with a blacklist and prior probability has a higher network score than other networks. The hold-out technique verified structural learning. The Directed Acyclic Graph showed a statistically significant relationship between cancer biomarkers (ER, PR, and HER2 receptors), cancer stage, and tumor grade and patient survival duration. Patient death was also significantly associated with education, ER, PR, HER2, and tumor grade. The BN reports that HER2 negative, ER positive, and PR positive patients had a higher survival rate. ConclusionSurvival and death of relapsed patients depend on biomarkers. Based on the findings, patient survival can be predicted with their features.

Band structure, superconductivity, and polytypism in AuSn4

The orthorhombic compound AuSn4 is compositionally similar to the Dirac node arc semimetal PtSn$_4$. AuSn$_4$ is, contrary to PtSn$_4$, superconducting with a critical temperature of T$_c$ = 2.35 K. Recent measurements present indications for quasi two-dimensional superconducting behavior in AuSn$_4$. Here we present measurements of the superconducting density of states and the band structure of AuSn$_4$ through Scanning Tunneling Microscopy (STM) and Angular Resolved Photoemission Spectroscopy (ARPES). The superconducting gap values in different portions of the Fermi surface are spread around {\Delta}0 = 0.4 meV, which is close to but somewhat larger than $\Delta =$ 1.76kBT$_c$ expected from BCS theory. We observe superconducting features in the tunneling conductance at the surface up to temperatures about 20% larger than bulk Tc. The band structure calculated with Density Functional Theory (DFT) follows well the results of ARPES. The crystal structure presents two possible stackings of Sn layers, giving two nearly degenerate polytypes. This makes AuSn$_4$ a rather unique case with a three dimensional electronic band structure but properties ressembling those of low dimensional layered compounds.

Multiple surface resonance electronic spin states in the strong topological metal Zr2Te2P

Nonzero spin polarization occurs in nonmagnetic materials induced by spin-orbital coupling when inversion symmetry is broken. Understanding the origin of spin polarization is essential for finding effective methods of manipulating the electron spin. Recently, nontrivial Dirac node arcs with a novel spin texture have been reported in a tetradymite family ${M}_{2}{\text{Te}}_{2}X$ (with $M=\text{Ti}$, Zr, or Hf and $X=\text{P}$ or As) and have potential applications in spintronics. Here, combining spin- and angle-resolved photoemission spectroscopy and first-principles calculations, we have unambiguously distinguished the spin-polarized topological surface states from the bulk continuum states in ${\text{Zr}}_{2}{\text{Te}}_{2}\text{P}$, and report that surface resonance Rashba-type spin splittings and spin-momentum-layer locked bulk states exist along with the Dirac node arcs in reciprocal space in adjacent energy ranges. Our work shows the importance of resonance and hybridization between surface and bulk states to their electronic spin textures and provides a platform for developing spintronics devices.

Layer-locked spin states revealed in the centrosymmetric nodal-line semimetal HfSiS

The spin-polarized bulk states in the centrosymmetric nodal-line semimetal HfSiS were observed by spin- and angle-resolved photoelectron spectroscopy. Combining with density functional theory calculations and the tight-binding model, the layer-locked spin states' nature of the observed $\mathrm{\ensuremath{\Lambda}}$-shaped bulk bands was revealed and the tight-binding model shows the importance of the next-nearest-neighbor term of spin-orbit coupling in the spin reversal of the bands along the $\overline{\mathrm{\ensuremath{\Gamma}}}\text{\ensuremath{-}}\overline{\mathit{M}}$ direction. Furthermore, the topological essence of attractive Dirac node arc states was confirmed.

Efficient Electrochemical Water Splitting with PdSn4 Dirac Nodal Arc Semimetal

Recently, several researchers have claimed the existence of superior catalytic activity associated with topological materials belonging to the class of Dirac/Weyl semimetals, owing to the high electron conductivity and charge carrier mobility in these topological materials. By means of X-ray photoelectron spectroscopy, electrocatalytic tests, and density functional theory, we have investigated the chemical reactivity (chemisorption of ambient gases), ambient stability, and catalytic properties of PdSn4, a topological semimetal showing Dirac node arcs. We find a Tafel slope of 83 mV in the hydrogen evolution reaction (HER) dec–1 with an overpotential of 50 mV, with performances resembling those of pure Pd, regardless of its limited amount in the alloy, with a subsequent reduction in the cost of raw materials by ∼80%. Remarkably, the PdSn4-based electrode shows superior robustness to CO compared to pure Pd and Pt and high stability in water media, although the PdSn4 surface is prone to oxidation with the formation of a sub-nanometric SnO2 skin. Moreover, we also assessed the significance of the role of topological electronic states in the observed catalytic properties. Actually, the peculiar atomic structure of oxidized PdSn4 enables the migration of hydrogen atoms through the Sn–O layer with a barrier comparable with the energy cost of the Heyrovsky step of HER over Pt(111) in acidic media (0.1 eV). On the other hand, the topological properties play a minor role, if existing, contrarily to the recent reports overestimating their contribution in catalytic properties.

Experimental Observation and Spin Texture of Dirac Node Arcs in Tetradymite Topological Metals.

We report the observation of a nontrivial spin texture in Dirac node arcs, i.e., novel topological objects formed when Dirac cones of massless particles extend along an open one-dimensional line in momentum space. We find that such states are present in all the compounds of the tetradymite M_{2}Te_{2}X family (M=Ti, Zr, or Hf and X=P or As) regardless of the weak or strong character of the topological invariant. The Dirac node arcs in tetradymites are thus the simplest possible textbook example of a type-I Dirac system with a single spin-polarized node arc.

Evidence for a large Rashba splitting in PtPb4 from angle-resolved photoemission spectroscopy

We studied the electronic structure of PtPb$_{4}$ using laser angle-resolved photoemission spectroscopy(ARPES) and density functional theory(DFT) calculations. This material is closely related to PtSn$_{4}$, which exhibits exotic topological properties such as Dirac node arcs. Fermi surface(FS) of PtPb$_{4}$ consists of two electron pockets at the center of the Brillouin zone(BZ) and several hole pockets around the zone boundaries. Our ARPES data reveals significant Rashba splitting at the $\Gamma$ point in agreement with DFT calculations. The presence of Rashba splitting may render this material of potential interest for spintronic applications.

The giant planar Hall effect and anisotropic magnetoresistance in Dirac node arcs semimetal PtSn4

Topological semimetals (TSMs) present intriguing quantum states and have attracted much attention in recent years because of exhibiting various anomalous magneto-transport phenomena. Theoretical prediction shows that some novel phenomena, such as negative magnetoresistance (MR) and the planar Hall effect (PHE), originate from the chiral anomaly in TSMs. In this work, high-field (33 T) Shubnikov–de Haas (SdH) oscillations are obtained to reveal the topology of PtSn4. Giant PHE and anisotropic magnetoresistance (AMR) are observed in Dirac node arcs of semimetal PtSn4. First, a non-zero transverse voltage can be acquired while tilting the in-plane magnetic field. Moreover, the amplitude of PHE sharply increases at T* ∼ 50 K with decreasing temperature, which is suggested to be related to the Fermi surface reconstruction observed in PtSn4. Subsequently, the field-dependent amplitudes of the PHE show an abnormal behavior around 50 K, which is thought to stem from the complex correlation between the chiral charge and electric one in PtSn4 driving the system into different coupling states due to the complicated band structure. On the other hand, the relative AMR is negative and up to −98% at 8.5 T. Our work proves that the PHE measurements are a convincing transport fingerprint feature to confirm the chiral anomaly in TSMs.

Catalytic activity of PtSn4: Insights from surface-science spectroscopies

Bulk PtSn4 has recently attracted the interest of the scientific community for the presence of electronic states exhibiting Dirac node arcs, enabling possible applications in nanoelectronics. Here, by means of surface-science experiments and density functional theory, we assess its suitability for catalysis by studying the chemical reactivity of the (0 1 0)-oriented PtSn4 surface toward CO, H2O, O2 molecules at room temperature and, moreover, its stability in air. We demonstrate that the catalytic activity of PtSn4 is determined by the composition of the outermost atomic layer. Specifically, we find that the surface termination for PtSn4 crystals cleaved in vacuum is an atomic Sn layer, which is totally free from any CO poisoning. In oxygen-rich environment, as well as in ambient atmosphere, the surface termination is a SnOx skin including SnO and SnO2 in comparable amount. However, valence-band states, including those forming Dirac node arcs, are only slightly affected by surface modifications. The astonishingly beneficial influence of surface oxidation on catalytic activity has been demonstrated by electrocatalytic tests evidencing a reduction of the Tafel slope, from 442 down to 86 mV dec−1, whose origin has been explained by our theoretical model. The use of surface-science tools to tune the chemical reactivity of PtSn4 opens the way toward its effective use in catalysis, especially for hydrogen evolution reaction and oxygen evolution reaction.

Moving object removal and surface mesh mapping for path planning on 3D terrain

ABSTRACT This paper proposes a method of moving object removal and map building for path planning on 3D terrain. Our method introduces a map representation named surface mesh maps, which is built from 3D LIDAR points using graph-based SLAM with moving object removal and polygon mesh reconstruction. We need moving object removal since moving objects, such as pedestrians, are included in raw maps built by SLAM in dynamic environments. For path planning, it is desirable that only stationary (static) objects remain in the maps. Occupancy voxel filtering can be used to remove moving objects. Stationary objects have high occupancy probability, and moving objects have low occupancy probability. However, due to shallow incidence of the LIDAR beams in 3D space, it is difficult to determine the correct probability of occupancy. Hence, we improve moving object removal using a new inverse measurement model with incident angles and a two-pass scheme to properly calculate the occupancy probability. In addition, we propose a path planning method using a graph search and the graph structures of the surface mesh maps. Path costs are given to the nodes and the arcs of the graph since path planning on 3D terrain requires an appropriate cost calculation. We introduce node costs and arc costs based on slopes, roughness, height differences, and travel distances. Path planning is performed by a graph search using the costs and graph pruning using collision detection and mesh boundary detection. The main contribution of our method is to combine SLAM with moving object removal and a graph search for path planning on large-scale 3D terrain. We conducted experiments by traveling over 5 km in outdoor dynamic environments. The results showed that the proposed method is capable of moving object removal and surface mesh mapping for path planning on 3D terrain.

Survivable multi-commodity network flow design: case of node capacities and arc failure

This paper is focused on the design of a survivable network with node capacities and flow restrictions. The goal is to design a survivable network at minimum cost so that feasible flows exist at the time of multiple simultaneous failure arcs (failure scenario). To solve this problem Benders' decomposition (BD) was initially proposed and, then, a new strategy was presented to obtain specific failure scenarios. We computationally demonstrated that BD using this strategy could obtain the optimal solution faster. This strategy reduced iterations more greatly than the BD approach. Using this strategy, the length CPU time required for solving the problem was reduced by 30% on average.

Origin of the extremely large magnetoresistance in topological semimetal PtSn4

$\mathrm{PtS}{\mathrm{n}}_{4}$ with extremely large magnetoresistance (XMR), a fascinating topological material platform, hosts a novel topological structure and Dirac node arcs, in which the Dirac nodes form closed loops in the momentum space. Here we performed the angular dependent magnetoresistivity (AMR), Hall effect, heat capacity measurements, and first-principles calculations to study the electronic properties of topological semimetal $\mathrm{PtS}{\mathrm{n}}_{4}$. There are some interesting observations on $\mathrm{PtS}{\mathrm{n}}_{4}$. (1) In the different experimental probes, we observed the anomalies around $T\ensuremath{\sim}55\phantom{\rule{0.16em}{0ex}}\mathrm{K}$. Significant changes of the transport results and the heat capacity have been observed, indicating successive Fermi surface reconstruction induced by the temperature. It means there is Lifshitz transition (LT) induced by the temperature in $\mathrm{PtS}{\mathrm{n}}_{4}$. (2) The perfect compensation between the electron and hole has been found around $T\ensuremath{\sim}30\phantom{\rule{0.16em}{0ex}}\mathrm{K}$, where the XMR appears, which is confirmed by the Hall effect measurements and the first-principles calculations. The XMR effect in $\mathrm{PtS}{\mathrm{n}}_{4}$ is suggested to originate from the combination of the electron-hole compensation and a particular orbital texture on the electron pocket. Meanwhile, we also found that LT seems to serve as a knob for the novel topological properties in two-dimensional (2D) topological semimetals (TSMs).

Topological nature of the node-arc semimetal PtSn4 probed by de Haas-van Alphen quantum oscillations

Dirac node arc semimetal state is a new topological quantum state which is proposed to exist in PtSn4 (Wu et al 2016 Dirac node arcs in PtSn4 Nat. Phys. 12 667–71). We present a systematic de Haas-van Alphen quantum oscillation study on this compound. Two intriguing oscillation branches, i.e. F1 and F2, are detected in the fast Fourier transformation spectra, both of which are characterized to possess tiny effective mass and ultrahigh quantum mobility. And the F2 branch exhibits an angle-dependent nontrivial Berry phase. The features are consistent with the existence of the node arc semimetal state and shed new light on its complicated Fermi surfaces and topological nature.

Enhanced electron correlations in the binary stannide PdSn4 : A homologue of the Dirac nodal arc semimetal PtSn4

The advent of nodal-line semi-metals, i.e. systems in which the conduction and valence bands cross each other along a closed trajectory (line or loop) inside the Brillouin zone, has opened up a new arena for the exploration of topological condensed matter in which, due to a vanishing density of states near the Fermi level, electron correlation effects may also play an important role. In spite of this conceptual richness however, material realization of nodal-line (loop) fermions is rare, with PbTaSe2, ZrSiS and PtSn4 the only promising known candidates. Here we report the synthesis and physical properties of a new compound PdSn4 that is isostructural with PtSn4 yet possesses quasiparticles with significantly enhanced effective masses. In addition, PdSn4 displays an unusual polar angular magnetoresistance which at a certain field orientation, varies linearly with field up to 55 Tesla. Our study suggests that, in association with its homologue PtSn4 whose low-lying excitations were recently claimed to possess Dirac node arcs, PdSn4 may be a promising candidate in the search for novel topological states with enhanced correlation effects.

Connectivity concepts in fuzzy incidence graphs

Connectivity concepts in fuzzy incidence graphs are discussed in this article. Fuzzy incidence graphs are important in interconnection networks with influenced flows. Thus it is of primary importance to analyze their connectivity properties. The existence of a strong path between any node arc pair of a fuzzy incidence graph is established. Cut pairs and fuzzy incidence trees are characterized using the concept of strong pairs. Several other structural properties of fuzzy incidence graphs are also obtained.

Large linear magnetoresistance in a transition-metal stannide β-RhSn4

Materials exhibiting large magnetoresistance may not only be of fundamental research interest, but also can lead to wide-ranging applications in magnetic sensors and switches. Here we demonstrate a large linear-in-field magnetoresistance, Δρ/ρ reaching as high as ∼600% at 2 K under a 9 T field, in the tetragonal phase of a transition-metal stannide β-RhSn4. Detailed analyses show that its magnetic responses are overall inconsistent with the classical model based on the multiple electron scattering by mobility fluctuations in an inhomogenous conductor, but rather in line with the quantum effects due to the presence of Dirac-like dispersions in the electronic structure. Our results may help guiding the future quest for quantum magnetoresistive materials into the family of stannides, similar to the role played by PtSn4 with topological node arcs.

Dirac node arcs in PtSn4

In topological quantum materials the conduction and valence bands are connected at points (Dirac/Weyl semimetals) or along lines (Line Node semimetals) in the momentum space. Numbers of studies demonstrated that several materials are indeed Dirac/Weyl semimetals. However, there is still no experimental confirmation of materials with line nodes, in which the Dirac nodes form closed loops in the momentum space. Here we report the discovery of a novel topological structure - Dirac node arcs - in the ultrahigh magnetoresistive material PtSn4 using laser-based angle-resolved photoemission spectroscopy (ARPES) data and density functional theory (DFT) calculations. Unlike the closed loops of line nodes, the Dirac node arc structure resembles the Dirac dispersion in graphene that is extended along one dimension in momentum space and confined by band gaps on either end. We propose that this reported Dirac node arc structure is a novel topological state that provides a novel platform for studying the exotic properties of Dirac Fermions.

ON TOTALLY WEIGHTED INTERCONNECTION NETWORKS

In a network, each arc is assigned a weight. The weight of a path or a cycle is defined as the minimum weight of its arcs. The maximum of weights of all paths between two nodes is defined as the strength of connectedness between the nodes. In network applications, the reduction in the strength of connectedness is more relevant than the total disconnection of the graph. A graph is totally weighted if both node set and arc set are weighted. A precisely weighted graph is a totally weighted complete graph with weight functions σ : V → ℜ+ and μ : E → ℜ+ such that μ(x,y) = σ(x) ∧ σ(y) for any pair of nodes x,y of G where ∧ represents the minimum. Different types of arcs and the existence of partial bridges in precisely weighted complete graphs are studied. The minimum and maximum strong degrees of such a graph are also obtained. Also the concept of node strength sequence is introduced and relations between node strength sequence and strong degrees are obtained.

Branch Exchange in Electrical Distribution Systems

This paper presents a branch exchange (BE) algorithm to solve network reconfiguration problems. The proposed technique involves a matrix manipulation approach, which has been devised by analysing the node–arc incidence matrix of the distribution network. A set of observations made on the network matrix permits the successful implementation of the BE technique by matrix manipulation. The approach presented here is simple and produces rapid results. Moreover, it can be implemented on large networks and can be used either as an exhaustive BE or as a heuristic BE. This method has been applied to 33 bus and 70 bus electrical distribution systems for the purpose of network reconfiguration for minimizing real power losses.

Redundant modeling in permutation weighted constraint satisfaction problems

In classical constraint satisfaction, redundant modeling has been shown effective in increasing constraint propagation and reducing search space for many problem instances. In this paper, we investigate, for the first time, how to benefit the same from redundant modeling in weighted constraint satisfaction problems (WCSPs), a common soft constraint framework for modeling optimization and over-constrained problems. Our work focuses on a popular and special class of problems, namely, permutation problems. First, we show how to automatically generate a redundant permutation WCSP model from an existing permutation WCSP using generalized model induction. We then uncover why naively combining mutually redundant permutation WCSPs by posting channeling constraints as hard constraints and relying on the standard node consistency (NC*) and arc consistency (AC*) algorithms would miss pruning opportunities, which are available even in a single model. Based on these observations, we suggest two approaches to handle the combined WCSP models. In our first approach, we propose $m\text {-NC}_{\text c}^*$ and $m\text {-AC}_{\text c}^*$ and their associated algorithms for effectively enforcing node and arc consistencies in a combined model with m sub-models. The two notions are strictly stronger than NC* and AC* respectively. While the first approach specifically refines NC* and AC* so as to apply to combined models, in our second approach, we propose a parameterized local consistency LB(m,?). The consistency can be instantiated with any local consistency ? for single models and applied to a combined model with m sub-models. We also provide a simple algorithm to enforce LB(m,?). With the two suggested approaches, we demonstrate their applicabilities on several permutation problems in the experiments. Prototype implementations of our proposed algorithms confirm that applying $2\text {-NC}_{\text c}^*,\;2\text {-AC}_{\text c}^*$ , and LB(2,?) on combined models allow far more constraint propagation than applying the state-of-the-art AC*, FDAC*, and EDAC* algorithms on single models of hard benchmark problems.