Genome Sequences and Structures of Two Biologically Distinct Strains of Grapevine leafroll - associated virus 2 and Sequence Analysis

Grapevine leafroll-associated virus 2 (GLRaV-2), a member of the genus Closterovirus within Closteroviridae, is implicated in several important diseases of grapevines including "leafroll”, "graft-incompatibility”, and "quick decline” worldwide. Several GLRaV-2 isolates have been detected from different grapevine genotypes. However, the genomes of these isolates were not sequenced or only partially sequenced. Consequently, the relationship of these viral isolates at the molecular level has not been determined. Here, we group the various GLRaV-2 isolates into four strains based on their coat protein gene sequences. We show that isolates "PN” (originated from Vitis vinifera cv. "Pinot noir”), "Sem” (from V. vinifera cv. "Semillon”) and "94/970” (from V. vinifera cv. "Muscat of Alexandria”) belong to the same strain, "93/955” (from hybrid "LN-33”) and "H4” (from V. rupestris "St. George”) each represents a distinct strain, while Grapevine rootstock stem lesion-associated viru

Change detection in SAR images based on the salient map guidance and an accelerated genetic algorithm

This paper proposes a change detection algorithm in synthetic aperture radar (SAR) images based on the salient image guidance and an accelerated genetic algorithm (S-aGA). The difference image is first generated by logarithm ratio operator based on the bi-temporal SAR images acquired in the same region. Then a saliency detection model is applied in the difference image to extract the salient regions containing the changed class pixels. The salient regions are further divided by fuzzy c-means (FCM) clustering algorithm into three categories: changed class (set of pixels with high gray values), unchanged class (set of pixels with low gray values) and undetermined class (set of pixels with middle gray value, which are difficult to classify). Finally, the proposed accelerated GA is applied to explore the reduced search space formed by the undetermined-class pixels according to an objective function considering neighborhood information. In S-aGA, an efficient mutation operator is designed by using the neighborhood information of undetermined-class pixels as the heuristic information to determine the mutation probability of each undetermined-class pixel adaptively, which accelerates the convergence of the GA significantly. The experimental results on two data sets demonstrate the efficiency of the proposed S-aGA. On the whole, S-aGA outperforms five other existing methods including the simple GA in terms of detection accuracy. In addition, S-aGA could obtain satisfying solution within limited generations, converging much faster than the simple GA

THE SHORT GRIT SCALE: A DIMENSIONALITY ANALYSIS

This study aimed to examine the internal structure, score reliability, scoring, and interpretation of the Short Grit Scale (Grit-S; Duckworth & Quinn, 2009) using a sample of engineering students (N = 610) from one large southeastern university located in the United States. Confirmatory factor analysis was used to compare four competing theoretical models: (a) a unidimensional model, (b) a two-factor model, (c) a second-order model, and (d) a bi-factor model. Given that researchers have used Grit-S as a single factor, a unidimensional model was examined. Two-factor and second-order models were considered based upon the work done by Duckworth, Peterson, Matthew, and Kelly (2007), and Duckworth and Quinn (2009). Finally, Reise, Morizot, and Hays (2007) have suggested a bi-factor model be considered when dealing with multidimensional scales given its ability to aid researches about the dimensionality and scoring of instruments consisting of heterogeneous item content. Findings from this study show that Grit-S was best represented by a bi-factor solution. Results indicate that the general grit factor possesses satisfactory score reliability and information, however, the results are not entirely clear or supportive of subscale scoring for either consistency of effort subscale or interest. The implications of these findings and future research are discussed

ASSESSING THE MODEL FIT OF MULTIDIMENSIONAL ITEM RESPONSE THEORY MODELS WITH POLYTOMOUS RESPONSES USING LIMITED-INFORMATION STATISTICS

Under item response theory, three types of limited information goodness-of-fit test statistics – M2, Mord, and C2 – have been proposed to assess model-data fit when data are sparse. However, the evaluation of the performance of these GOF statistics under multidimensional item response theory (MIRT) models with polytomous data is limited. The current study showed that M2 and C2 were well-calibrated under true model conditions and were powerful under misspecified model conditions. Mord were not well-calibrated when the number of response categories was more than three. RMSEA2 and RMSEAC2 are good tools to evaluate approximate fit. The second study aimed to evaluate the psychometric properties of the Religious Commitment Inventory-10 (RCI-10; Worthington et al., 2003) within the IRT framework and estimate C2 and its RMSEA to assess global model-fit. Results showed that the RCI-10 was best represented by a bifactor model. The scores from the RCI-10 could be scored as unidimensional notwithstanding the presence of multidimensionality. Two-factor correlational solution should not be used. Study two also showed that religious commitment is a risk factor of intimate partner violence, whereas spirituality was a protecting factor from the violence. More alcohol was related with more abusive behaviors. Implications of the two studies were discussed

PSR J1926-0652: A Pulsar with Interesting Emission Properties Discovered at FAST

We describe PSR J1926-0652, a pulsar recently discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Using sensitive single-pulse detections from FAST and long-term timing observations from the Parkes 64-m radio telescope, we probed phenomena on both long and short time scales. The FAST observations covered a wide frequency range from 270 to 800 MHz, enabling individual pulses to be studied in detail. The pulsar exhibits at least four profile components, short-term nulling lasting from 4 to 450 pulses, complex subpulse drifting behaviours and intermittency on scales of tens of minutes. While the average band spacing P3 is relatively constant across different bursts and components, significant variations in the separation of adjacent bands are seen, especially near the beginning and end of a burst. Band shapes and slopes are quite variable, especially for the trailing components and for the shorter bursts. We show that for each burst the last detectable pulse prior to emission ceasing has different properties compared to other pulses. These complexities pose challenges for the classic carousel-type models.Comment: 13pages with 12 figure

Matriks Jordan Dan Aplikasinya Pada Sistem Linier Waktu Diskrit

Matrix is diagonalizable (similar with matrix diagonal) if and only if the sum of geometric multiplicities of its eigenvalues is n.If we search for an upper triangular form that is nearly diagonal as possible but is still attainable by similarity for every matrix, especially the sum of geometric multiplicities of its eigenvalues is less than n, the result is the Jordan canonical form, which is denoted by , and . In this paper, will be described how to get matrix S(in order to get matrix ) by using generalized eigenvector. In addition, it will also describe the Jordan canonical form and its properties, and some observation and application on discrete time linear system

The development of inference machine model for vocation psychology based on rough set theory

Abstract In the paper the inference machine model for vocation psychology was build and developed by a rule-based rough set theory. At first, the rough set is used to optimize the rules for career psychological identification, by which the complexity of the neural network can be avoided. Second, the features used by the questionnaires are selected for input parameters of the classifier to incorporate more human like decision-making, whereas in other works, only a few of features or different characteristic options on the questionnaire, are used as deterministic parameters. A knowledge base of the behaviour characteristics and questionnaire analysis is developed from the feedbacks of some reputed career guides. These features are extracted from the carefully designed questionnaire. A rule -based rough set decision system is developed from these features to make an inference engine for career psychological identification

Loss of Asxl1 Alters Self-Renewal and Cell Fate of Bone Marrow Stromal Cell, Leading to Bohring-Opitz-like Syndrome in Mice

De novo ASXL1 mutations are found in patients with Bohring-Opitz syndrome, a disease with severe developmental defects and early childhood mortality. The underlying pathologic mechanisms remain largely unknown. Using Asxl1-targeted murine models, we found that Asxl1 global loss as well as conditional deletion in osteoblasts and their progenitors led to significant bone loss and a markedly decreased number of bone marrow stromal cells (BMSCs) compared with wild-type littermates. Asxl1(-/-) BMSCs displayed impaired self-renewal and skewed differentiation, away from osteoblasts and favoring adipocytes. RNA-sequencing analysis revealed altered expression of genes involved in cell proliferation, skeletal development, and morphogenesis. Furthermore, gene set enrichment analysis showed decreased expression of stem cell self-renewal gene signature, suggesting a role of Asxl1 in regulating the stemness of BMSCs. Importantly, re-introduction of Asxl1 normalized NANOG and OCT4 expression and restored the self-renewal capacity of Asxl1(-/-) BMSCs. Our study unveils a pivotal role of ASXL1 in the maintenance of BMSC functions and skeletal development