Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Gene Expression in Bugula Neritina during Symbiotic Association with "Candidatus Endobugula Sertula"

The colonial marine bryozoan, Bugula neritina, harbors an uncultured endosymbiont, “Candidatus Endobugula sertula” throughout its life stages. The bacterial symbiont has been proposed to be a source of complex polyketide metabolites, the bryostatins, that chemically defend B. neritina larvae from predation. Within a bryozoan colony, significantly higher amounts of bryostatins are found in ovicell-bearing zooids where the developing larvae are brooded, as compared to ovicell-free zooids. It is hypothesized that signaling between B. neritina and “Ca. Endobugula sertula” may be involved in the regulation of bryostatin production in different zooids, as well as in maintenance of the symbiosis. In this study, suppression subtractive hybridization (SSH) was used to identify differentially expressed host genes during this association. The identified genes suggest that the host plays a role in the distribution and localization of bacterial symbionts in different host zooids, possibly to regulate levels of bryostatin production in the zooids. INDEX WORDS: Symbiosis, Bugula neritina, Bryostatins, Differential gene expression DIFFERENTIAL GENE EXPRESSION IN BUGULA NERITINA DURING SYMBIOTIC ASSOCIATION WITH “CANDIDATUS ENDOBUGULA SERTULA”
Modeling Censored Data Using Mixture Regression Models with an Application to Cattle Production Yields

This research develops a mixture regression model that is shown to have advantages over the classical Tobit model in model fit and predictive tests when data are generated from a two step process. Additionally, the model is shown to allow for flexibility in distributional assumptions while nesting the classic Tobit model. A simulated data set is utilized to assess the potential loss in efficiency from model misspecification, assuming the Tobit and a zero-inflated log-normal distribution, which is derived from the generalized mixture model. Results from simulations key on the finding that the proposed zero-inflated log-normal model clearly outperforms the Tobit model when data are generated from a two step process. When data are generated from a Tobit model, forecasts are more accurate when utilizing the Tobit model. However, the Tobit model will be shown to be a special case of the generalized mixture model. The empirical model is then applied to evaluating mortality rates in commercial cattle feedlots, both independently and as part of a system including other performance and health factors. This particular application is hypothesized to be more appropriate for the proposed model due to the high degree of censoring and skewed nature of mortality rates. The zero-inflated log-normal model clearly models and predicts with more accuracy that the tobit model.
Development of an orthotopic model of human metastatic prostate cancer in the NOD-SCIDγ mouse (Mus musculus) anterior prostate

Prostate cancer is one of the most prevalent oncological diseases in males worldwide, and the mortalities resulting from this type of cancer are mainly due to metastasis. The most common models for the study of metastasis are transgenic and immunocompromised mice, which enable the study of the metastatic process in a controlled way by the injection of prostate cancer cells into the mice. In the present study, NOD-SCIDγ mice were injected orthotopically with PC3 cells in the anterior prostate in order to establish a metastatic model. The results demonstrated the development and growth of a primary tumor that preceded the formation of micrometastases in the lung, liver and pancreas, followed by macrometastases in the liver. This model adequately represents the dynamics of the metastatic process, and may be useful for novel therapeutic assays and post-surgical relapse studies.
In Vivo JNK Activation in Pancreatic β-Cells Leads to Glucose Intolerance Caused by Insulin Resistance in Pancreas

Insulin resistance is a key condition in the development of type 2 diabetes. It is well established that exacerbated Jun NH2-terminal kinase (JNK) activity is involved in promoting insulin resistance in peripheral insulin-target tissues; however, this involvement is less documented in pancreatic β-cells. Using a transgenic mouse model, here we show that JNK activation in β-cells led to glucose intolerance as a result of impaired capacity to increase insulinemia in response to hyperglycemia. Pancreatic islets from these mice showed no obvious morphostructural abnormalities or decreased insulin content. In contrast, these islets failed to secrete insulin in response to glucose or insulin but were competent in succinate-, ketoisocaproate-, 3-isobutyl-1-methylxanthine (IBMX-), KCl-, and tolbutamide-induced insulin secretion. At the molecular level, JNK activation in β-cells inhibited insulin-induced Akt phosphorylation, pancreatic and duodenal homeobox 1 nucleocytoplasmic shuttling, and transcription of insulin-target genes. Remarkably, rosiglitazone restored insulin secretion in response to hyperglycemia in mice and insulin-induced insulin secretion and signaling in isolated islets. In conclusion, the mere activation of JNK suffices to induce insulin resistance in pancreatic β-cells by inhibition of insulin signaling in these cells, but it is not sufficient to elicit β-cell death. In addition, we provide the first evidence that thiazolidinediones exert insulin-sensitizing action directly on pancreatic β-cells.
THE ROLE OF LANGUAGE-ANALYTIC ABILITY IN CHILDREN’S INSTRUCTED SECOND LANGUAGE LEARNING

Abstract Language-analytic ability, or the ability to treat language as an object of analysis and arrive at linguistic generalizations, is at the core of the constructs of language learning aptitude and metalinguistic awareness, which are implicated in our ability to learn explicitly. In the context of child second language (L2) learning, it has been argued that children learn primarily implicitly and that the most important component of aptitude may be memory ability. However, no empirical research to date has investigated the relationship and development of aptitude and metalinguistic awareness longitudinally as well as examined their predictive power for children’s L2 achievement in the classroom. In a study with English-speaking learners aged 8–9 (N = 111), we found that although aptitude and metalinguistic awareness were (still) dynamic, they significantly predicted children’s achievement in L2 French. Moreover, language-analytic ability proved to be the component with the strongest predictive power. This finding suggests that it may not be level of cognitive maturity alone that determines children’s approach to L2 learning; experiencing explicit, form-focused instruction may foster the role of language-analytic ability even in children as young as 8–9 years.
Underdiagnosis of childhood asthma: A comparison of survey estimates to clinical evaluation

ObjectivesDiagnostic patterns play a role in asthma prevalence estimates and could have implications for disease management. We sought to determine the extent to which questionnaire-derived estimates of childhood asthma reflect the disease’s true occurrence.Materials and MethodsChildren aged 6–12 years from Katowice, Poland, were recruited from a cross-sectional survey (N = 1822) via primary schools. Students were categorized into three mutually exclusive groups based on survey responses: “Asthma” (previously diagnosed asthma); “Respiratory symptoms” (no previous diagnosis of asthma and one or more respiratory symptoms during last year), “No respiratory symptoms” (no previous diagnosis of asthma or respiratory symptoms). A sample of children from each group (total N = 456) completed clinical testing to determine asthma presence according to GINA recommendations.ResultsBased on the survey, 5.4% of children were classified with asthma, 27.9% with respiratory symptoms, and 66.7% with no respiratory symptoms or asthma. All previously known 41 cases of asthma were confirmed. New diagnoses of asthma were made in 21 (10.9%) and 8 (3.6%) of subjects from the “Respiratory symptoms” (N = 192) and “No respiratory symptoms” (N = 223) groups, respectively. The overall prevalence of childhood asthma, incorporating the results of clinical examination, was 10.8% (95% CI: 9.4–12.2), compared to the questionnaire-derived figure of 5.4% (95% CI: 4.4–6.5%) and affected females more than males.ConclusionsAsthma prevalence was underestimated in this population possibly resulting from under-presentation or under-diagnosis. This could have potential implications for proper management and well-being of children. Questionnaire estimates of prevalence should be considered carefully in the context of regional diagnostic patterns.
Comparative assessment of predictions in ungauged basins – Part 3: Runoff signatures in Austria

Abstract. This is the third of a three-part paper series through which we assess the performance of runoff predictions in ungauged basins in a comparative way. Whereas the two previous papers by Parajka et al. (2013) and Salinas et al. (2013) assess the regionalisation performance of hydrographs and hydrological extremes on the basis of a comprehensive literature review of thousands of case studies around the world, in this paper we jointly assess prediction performance of a range of runoff signatures for a consistent and rich dataset. Daily runoff time series are predicted for 213 catchments in Austria by a regionalised rainfall–runoff model and by Top-kriging, a geostatistical estimation method that accounts for the river network hierarchy. From the runoff time-series, six runoff signatures are extracted: annual runoff, seasonal runoff, flow duration curves, low flows, high flows and runoff hydrographs. The predictive performance is assessed in terms of the bias, error spread and proportion of unexplained spatial variance of statistical measures of these signatures in cross-validation (blind testing) mode. Results of the comparative assessment show that, in Austria, the predictive performance increases with catchment area for both methods and for most signatures, it tends to increase with elevation for the regionalised rainfall–runoff model, while the dependence on climate characteristics is weaker. Annual and seasonal runoff can be predicted more accurately than all other signatures. The spatial variability of high flows in ungauged basins is the most difficult to estimate followed by the low flows. It also turns out that in this data-rich study in Austria, the geostatistical approach (Top-kriging) generally outperforms the regionalised rainfall–runoff model.
Wellbeing in adults who had a brush with death

Objectives: A Near-Death-Experience can be a lifechanging event initiating deep posttraumatic growth. Yet people can initially be left struggling with the internal changes and feel alienated from their life and social network. This study investigated whether Near-Death-Experiences also have an impact on people’s happiness, and if so, how long it lasts, and what kind of support they receive in making sense of the event. Method: Six semi-structured interviews were conducted with people who had a Near-Death-Experience and the data was subjected to Interpretative Phenomenological Analysis. Results: Five master-themes emerged: Sense of self, Attitude toward life and death, Effects of Near-Death-Experience, Relationship with others, and Experience of happiness. Conclusion: Almost all participants reported feeling less apprehensive towards death and simultaneously found a greater ability to embrace and appreciate life. Some gained new and profound internal insights that manifested in a renewed sense of self, stronger and more pronounced feelings of life purpose, and could reflect on the Near-Death-Experience as a precious gift. The majority of participants experienced a greater degree of happiness that gradually grew over time. This was largely located internally, which freed them from ‘the hedonic treadmill’ of pursuing it in the outside world. Stigma and a lack of awareness still represent a hurdle for connecting with others and accessing support. Clinical and research implications were discussed.
Neighborhood Danger, Parental Monitoring, Harsh Parenting, and Child Aggression in Nine Countries

Exposure to neighborhood danger during childhood has negative effects that permeate multiple dimensions of childhood. The current study examined whether mothers’, fathers’, and children's perceptions of neighborhood danger are related to child aggression, whether parental monitoring moderates this relation, and whether harsh parenting mediates this relation. Interviews were conducted with a sample of 1,293 children (age M = 10.68, SD = .66; 51% girls) and their mothers (n = 1,282) and fathers (n = 1,075) in nine countries (China, Colombia, Italy, Jordan, Kenya, the Philippines, Sweden, Thailand, and the United States). Perceptions of greater neighborhood danger were associated with more child aggression in all nine countries according to mothers’ and fathers’ reports and in five of the nine countries according to children's reports. Parental monitoring did not moderate the relation between perception of neighborhood danger and child aggression. The mediating role of harsh parenting was inconsistent across countries and reporters. Implications for further research are discussed, and include examination of more specific aspects of parental monitoring as well as more objective measures of neighborhood danger.
Visualization, analysis and structural pattern infusion of DBLP co-authorship network using Gephi

DBLP (Digital Bibliography & Library Project) has the huge collection (around 3.4 million) of journal articles with its meta data, papers published in various national and international conferences, and other number of online publications in the field of computer science. Research data on DBLP increases enormously which arises many research problems in the domain of bibliography data network analysis such as citation index and co-authorship etc. For this purpose, many researchers' work is available on Data visualization, Data Mining, Data Analysis and prediction of the same. Here in this research paper, we are showing results of visualizing and analyzing DBLP Co-authorship network with the help of Gephi tool. We use DBLP dataset which is an undirected graph and contains 17280 nodes and 58539 edges. In this Graph nodes are taken as author and edges connect two nodes/authors according to their association in considered research papers' dataset. There will be more than one edge in between two nodes if both the researcher co-authored more than one paper. Attention has been devoted towards statistic based analysis with some varying measuring factors such as connected nodes, clustering coefficient, page rank, Average path length and Graph density. We apply Force Atlas2 for community generation and thereafter graph represent co-authorship network communities. We discuss and detail about collect, analyze and visualize co-authorship data which is further used for understanding the academic collaboration and finding the research communities for specific knowledge domain. Even we discuss about analysis of individual researcher and their community in the past through repetitive co-published work.
Dimension-Preserving Reductions from LWE to LWR

The Learning with Rounding ( LWR ) problem was ﬁrst introduced by Banerjee, Peikert, and Rosen (Eurocrypt 2012) as a de-randomized form of the standard Learning with Errors ( LWE ) problem. The original motivation of LWR was as a building block for constructing eﬃcient, low-depth pseudorandom functions on lattices. It has since been used to construct reusable computational extractors, lossy trapdoor functions, and deterministic encryption. In this work we show two (incomparable) dimension-preserving reductions from LWE to LWR in the case of a polynomial-size modulus . Prior works either required a superpolynomial modulus q , or lost at least a factor log( q ) in the dimension of the reduction. A direct consequence of our improved reductions is an improvement in parameters (i.e. security and eﬃciency) for each of the known applications of poly-modulus LWR . Our results directly generalize to the ring setting. Indeed, our formal analysis is performed over “module lattices,” as deﬁned by Langlois and Stehl´e (DCC 2015), which generalize both the general lattice setting of LWE and the ideal lattice setting of RLWE as the single notion M – LWE . We hope that taking this broader perspective will lead to further insights of independent interest.
POPULATION DYNAMICS OF MOTTLED SCULPIN (PISCES) IN A VARIABLE ENVIRONMENT: INFORMATION THEORETIC APPROACHES

We used strong inference with Akaike's Information Criterion (AIC) to assess the processes capable of explaining long-term (1984-1995) variation in the per capita rate of change of mottled sculpin (Cottus bairdi) populations in the Coweeta Creek drainage (USA). We sampled two fourth- and one fifth-order sites (BCA (uppermost), BCB, and CC (lowermost)) along a downstream gradient, and the study encompassed extensive flow variation. Physical habitat availability varied significantly both within and among the sites. Sculpin densities in all sites were highly stable (coefficients of variation 5 0.23-0.41) and sampling variability was low (coefficients of variation 5 0.11-0.15). Population sta- bility was positively associated with habitat stability, and the only significant correlations of population parameters among sites involved juveniles. Sculpin densities were signifi- cantly higher in BCB than in CC. The data suggest that, despite their proximity, the dynamics of populations within the sites are being determined by small-scale (i.e., 30-50 m) rather than broad-scale spatial processes. Both AIC and Dennis and Taper analyses indicated that simple density dependence had the greatest ability to explain variation in r for all life-history classes in all sites (AIC, seven of nine cases; Dennis and Taper, nine of nine cases). Multiprocess models had little explanatory power. When adults were removed from two sites, juvenile sculpin shifted into microhabitats formerly occupied by adults. No shifts occurred in control sites. Consequently, it is likely that the patterns of density dependence observed in all three sites were a consequence of intraspecific competition for space. Our findings argue for a multitiered approach to the study of population variation, one that encompasses long-term monitoring, spatial variation, and experimental testing of potential mechanisms.
Feline Leukemia Virus DNA Vaccine Efficacy Is Enhanced by Coadministration with Interleukin-12 (IL-12) and IL-18 Expression Vectors

ABSTRACT The expectation that cell-mediated immunity is important in the control of feline leukemia virus (FeLV) infection led us to test a DNA vaccine administered alone or with cytokines that favored the development of a Th1 immune response. The vaccine consisted of two plasmids, one expressing the gag/pol genes and the other expressing the env gene of FeLV-A/Glasgow-1. The genetic adjuvants were plasmids encoding the feline cytokines interleukin-12 (IL-12), IL-18, or gamma interferon (IFN-γ). Kittens were immunized by three intramuscular inoculations of the FeLV DNA vaccine alone or in combination with plasmids expressing IFN-γ, IL-12, or both IL-12 and IL-18. Control kittens were inoculated with empty plasmid. Following immunization, anti-FeLV antibodies were not detected in any kitten. Three weeks after the final immunization, the kittens were challenged by the intraperitoneal inoculation of FeLV-A/Glasgow-1 and were then monitored for a further 15 weeks for the presence of virus in plasma and, at the end of the trial, for latent virus in bone marrow. The vaccine consisting of FeLV DNA with the IL-12 and IL-18 genes conferred significant immunity, protecting completely against transient and persistent viremia, and in five of six kittens protecting against latent infection. None of the other vaccines provided significant protection.
Queueing Systems 0 (2000) ?{? Modeling and Analysis of Power-tail Distributions via Classical Teletraac Methods Starobinski and Sidi / Modeling and Analysis of Power-tail Distributions

We propose a new methodology for modeling and analyzing power-tail distributions , such as the Pareto distribution, in communication networks. The basis of our approach is a tting algorithm which approximates a power-tail distribution by a hy-perexponential distribution. This algorithm possesses several key properties. First, the approximation can be achieved within any desired degree of accuracy. Second, the tted hyperexponential distribution depends only on a few parameters. Third, only a small number of exponentials are required in order to obtain an accurate approximation over many time scales. Once equipped with a tted hyperexponential distribution, we have an integrated framework for analyzing queueing systems with power-tail distributions. We consider the GI=G=1 queue with Pareto distributed service time and show how our approach allows to derive both quantitative numerical results and asymptotic closed-form results. This derivation shows that classical teletraac methods can be employed for the analysis of power-tail distributions.
A robust speed-invariant gait recognition system for walker and runner identification

In real-world scenarios, walking/running speed is one of the most common covariate factors that can affect the performance of gait recognition systems. By assuming the effect caused by the speed changes (from the query walker-s/runners) are intra-class variations that the training data (i.e., gallery) fails to capture, overfitting to the less representative training data may be the main problem that degrades the performance. In this work, we employ a general model based on random subspace method to solve this problem. More specifically, for query gaits in unknown speeds, we try to reduce the generalization errors by combining a large number of weak classifiers. We evaluate our method on two benchmark databases, i.e., Infrared CASIA-C dataset and Treadmill OU-ISIR-A dataset. For the cross-speed walking/running gait recognition experiments, nearly perfect results are achieved, significantly higher than other state-of-the-art algorithms. We also study the unknown- speed nrunner identification solely using the walking gait gallery, and the encouraging experimental results suggest the effectiveness of our method in such cross-mode gait recognition tasks.