Two distinct classes of QTL determine rust resistance in sorghum

Background: Agriculture is facing enormous challenges to feed a growing population in the face of rapidly evolving pests and pathogens. The rusts, in particular, are a major pathogen of cereal crops with the potential to cause large reductions in yield. Improving stable disease resistance is an on-going major and challenging focus for many plant breeding programs, due to the rapidly evolving nature of the pathogen. Sorghum is a major summer cereal crop that is also a host for a rust pathogen which occurs in almost all sorghum growing areas of the world, causing direct and indirect yield losses in sorghum worldwide, however knowledge about its genetic control is still limited. In order to further investigate this issue, QTL and association mapping methods were implemented to study rust resistance in three bi-parental populations and an association mapping set of elite breeding lines in different environments. Results: In total, 64 significant or highly significant QTL and 21 suggestive rust resistance QTL were identified representing 55 unique genomic regions. Comparisons across populations within the current study and with rust QTL identified previously in both sorghum and maize revealed a high degree of correspondence in QTL location. Negative phenotypic correlations were observed between rust, maturity and height, indicating a trend for both early maturing and shorter genotypes to be more susceptible to rust. Conclusions: The significant amount of QTL co-location across traits, in addition to the consistency in the direction of QTL allele effects, has provided evidence to support pleiotropic QTL action across rust, height, maturity and stay-green, supporting the role of carbon stress in susceptibility to rust. Classical rust resistance QTL regions that did not co-locate with height, maturity or stay-green QTL were found to be significantly enriched for the defence-related NBS-encoding gene family, in contrast to the lack of defence-related gene enrichment in multi-trait effect rust resistance QTL. The distinction of disease resistance QTL hot-spots, enriched with defence-related gene families from QTL which impact on development and partitioning, provides plant breeders with knowledge which will allow for fast-tracking varieties with both durable pathogen resistance and appropriate adaptive traits

Dynamical SimRank search on time-varying networks

SimRank is an appealing pair-wise similarity measure based on graph structure. It iteratively follows the intuition that two nodes are assessed as similar if they are pointed to by similar nodes. Many real graphs are large, and links are constantly subject to minor changes. In this article, we study the efficient dynamical computation of all-pairs SimRanks on time-varying graphs. Existing methods for the dynamical SimRank computation [e.g., LTSF (Shao et al. in PVLDB 8(8):838–849, 2015) and READS (Zhang et al. in PVLDB 10(5):601–612, 2017)] mainly focus on top-k search with respect to a given query. For all-pairs dynamical SimRank search, Li et al.’s approach (Li et al. in EDBT, 2010) was proposed for this problem. It first factorizes the graph via a singular value decomposition (SVD) and then incrementally maintains such a factorization in response to link updates at the expense of exactness. As a result, all pairs of SimRanks are updated approximately, yielding (Formula presented.) time and (Formula presented.) memory in a graph with n nodes, where r is the target rank of the low-rank SVD. Our solution to the dynamical computation of SimRank comprises of five ingredients: (1) We first consider edge update that does not accompany new node insertions. We show that the SimRank update (Formula presented.) in response to every link update is expressible as a rank-one Sylvester matrix equation. This provides an incremental method requiring (Formula presented.) time and (Formula presented.) memory in the worst case to update (Formula presented.) pairs of similarities for K iterations. (2) To speed up the computation further, we propose a lossless pruning strategy that captures the “affected areas” of (Formula presented.) to eliminate unnecessary retrieval. This reduces the time of the incremental SimRank to (Formula presented.), where m is the number of edges in the old graph, and (Formula presented.) is the size of “affected areas” in (Formula presented.), and in practice, (Formula presented.). (3) We also consider edge updates that accompany node insertions, and categorize them into three cases, according to which end of the inserted edge is a new node. For each case, we devise an efficient incremental algorithm that can support new node insertions and accurately update the affected SimRanks. (4) We next study batch updates for dynamical SimRank computation, and design an efficient batch incremental method that handles “similar sink edges” simultaneously and eliminates redundant edge updates. (5) To achieve linear memory, we devise a memory-efficient strategy that dynamically updates all pairs of SimRanks column by column in just (Formula presented.) memory, without the need to store all (Formula presented.) pairs of old SimRank scores. Experimental studies on various datasets demonstrate that our solution substantially outperforms the existing incremental SimRank methods and is faster and more memory-efficient than its competitors on million-scale graphs

In-medium relativistic kinetic theory and nucleon-meson systems

Within the $\sigma-\omega$ model of coupled nucleon-meson systems, a generalized relativistic Lenard--Balescu--equation is presented resulting from a relativistic random phase approximation (RRPA). This provides a systematic derivation of relativistic transport equations in the frame of nonequilibrium Green's function technique including medium effects as well as flucuation effects. It contains all possible processes due to one meson exchange and special attention is kept to the off--shell character of the particles. As a new feature of many particle effects, processes are possible which can be interpreted as particle creation and annihilation due to in-medium one meson exchange. In-medium cross sections are obtained from the generalized derivation of collision integrals, which possess complete crossing symmetries.Comment: See nucl-th/9310032 for revised version which the authors incompetently resubmitted rather than correctly replacing thi

SimRank*: effective and scalable pairwise similarity search based on graph topology

Given a graph, how can we quantify similarity between two nodes in an effective and scalable way? SimRank is an attractive measure of pairwise similarity based on graph topologies. Its underpinning philosophy that “two nodes are similar if they are pointed to (have incoming edges) from similar nodes” can be regarded as an aggregation of similarities based on incoming paths. Despite its popularity in various applications (e.g., web search and social networks), SimRank has an undesirable trait, i.e., “zero-similarity”: it accommodates only the paths of equal length from a common “center” node, whereas a large portion of other paths are fully ignored. In this paper, we propose an effective and scalable similarity model, SimRank*, to remedy this problem. (1) We first provide a sufficient and necessary condition of the “zero-similarity” problem that exists in Jeh and Widom’s SimRank model, Li et al. ’s SimRank model, Random Walk with Restart (RWR), and ASCOS++. (2) We next present our treatment, SimRank*, which can resolve this issue while inheriting the merit of the simple SimRank philosophy. (3) We reduce the series form of SimRank* to a closed form, which looks simpler than SimRank but which enriches semantics without suffering from increased computational overhead. This leads to an iterative form of SimRank*, which requires O(Knm) time and O(n2) memory for computing all (n2) pairs of similarities on a graph of n nodes and m edges for K iterations. (4) To improve the computational time of SimRank* further, we leverage a novel clustering strategy via edge concentration. Due to its NP-hardness, we devise an efficient heuristic to speed up all-pairs SimRank* computation to O(Knm~) time, where m~ is generally much smaller than m. (5) To scale SimRank* on billion-edge graphs, we propose two memory-efficient single-source algorithms, i.e., ss-gSR* for geometric SimRank*, and ss-eSR* for exponential SimRank*, which can retrieve similarities between all n nodes and a given query on an as-needed basis. This significantly reduces the O(n2) memory of all-pairs search to either O(Kn+m~) for geometric SimRank*, or O(n+m~) for exponential SimRank*, without any loss of accuracy, where m~≪n2 . (6) We also compare SimRank* with another remedy of SimRank that adds self-loops on each node and demonstrate that SimRank* is more effective. (7) Using real and synthetic datasets, we empirically verify the richer semantics of SimRank*, and validate its high computational efficiency and scalability on large graphs with billions of edges

QCD Sum Rules for Σ\Sigma Hyperons in Nuclear Matter

Within finite-density QCD sum-rule approach we investigate the self-energies of $\Sigma$ hyperons propagating in nuclear matter from a correlator of $\Sigma$ interpolating fields evaluated in the nuclear matter ground state. We find that the Lorentz vector self-energy of the $\Sigma$ is similar to the nucleon vector self-energy. The magnitude of Lorentz scalar self-energy of the $\Sigma$ is also close to the corresponding value for nucleon; however, this prediction is sensitive to the strangeness content of the nucleon and to the assumed density dependence of certain four-quark condensate. The scalar and vector self-energies tend to cancel, but not completely. The implications for the couplings of $\Sigma$ to the scalar and vector mesons in nuclear matter and for the $\Sigma$ spin-orbit force in a finite nucleus are discussed.Comment: 20 pages in revtex, 6 figures available under request as ps files, UMD preprint #94--11

Modified Quark-Meson Coupling Model for Nuclear Matter

The quark-meson coupling model for nuclear matter, which describes nuclear matter as non-overlapping MIT bags bound by the self-consistent exchange of scalar and vector mesons, is modified by introducing medium modification of the bag constant. We model the density dependence of the bag constant in two different ways: one invokes a direct coupling of the bag constant to the scalar meson field, and the other relates the bag constant to the in-medium nucleon mass. Both models feature a decreasing bag constant with increasing density. We find that when the bag constant is significantly reduced in nuclear medium with respect to its free-space value, large canceling isoscalar Lorentz scalar and vector potentials for the nucleon in nuclear matter emerge naturally. Such potentials are comparable to those suggested by relativistic nuclear phenomenology and finite-density QCD sum rules. This suggests that the reduction of bag constant in nuclear medium may play an important role in low- and medium-energy nuclear physics.Comment: Part of the text is reordered, revised version to appear in Phys. Rev. C. 19 pages, ReVTeX, 4 figures embedde

Connected Vehicles: Solutions and Challenges

Abstract-Providing various wireless connectivities for vehicles enables the communication between vehicles and their internal and external environments. Such a connected vehicle solution is expected to be the next frontier for automotive revolution and the key to the evolution to next generation intelligent transportation systems (ITSs). Moreover, connected vehicles are also the building blocks of emerging Internet of Vehicles (IoV). Extensive research activities and numerous industrial initiatives have paved the way for the coming era of connected vehicles. In this paper, we focus on wireless technologies and potential challenges to provide vehicle-to-x connectivity. In particular, we discuss the challenges and review the state-of-the-art wireless solutions for vehicle-to-sensor, vehicleto-vehicle, vehicle-to-Internet, and vehicle-to-road infrastructure connectivities. We also identify future research issues for building connected vehicles

Effect of Aspect Ratio on Field Emission Properties of ZnO Nanorod Arrays

ZnO nanorod arrays are prepared on a silicon wafer through a multi-step hydrothermal process. The aspect ratios and densities of the ZnO nanorod arrays are controlled by adjusting the reaction times and concentrations of solution. The investigation of field emission properties of ZnO nanorod arrays revealed a strong dependency on the aspect ratio and their density. The aspect ratio and spacing of ZnO nanorod arrays are 39 and 167 nm (sample C), respectively, to exhibit the best field emission properties. The turn-on field and threshold field of the nanorod arrays are 3.83 V/μm and 5.65 V/μm, respectively. Importantly, the sample C shows a highest enhancement of factorβ, which is 2612. The result shows that an optimum density and aspect ratio of ZnO nanorod arrays have high efficiency of field emission