508 research outputs found

    Advances in Big Data Analytics: Algorithmic Stability and Data Cleansing

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    Analysis of what has come to be called “big data” presents a number of challenges as data continues to grow in size, complexity and heterogeneity. To help addresses these challenges, we study a pair of foundational issues in algorithmic stability (robustness and tuning), with application to clustering in high-throughput computational biology, and an issue in data cleansing (outlier detection), with application to pre-processing in streaming meteorological measurement. These issues highlight major ongoing research aspects of modern big data analytics. First, a new metric, robustness, is proposed in the setting of biological data clustering to measure an algorithm’s tendency to maintain output coherence over a range of parameter settings. It is well known that different algorithms tend to produce different clusters, and that the choice of algorithm is often driven by factors such as data size and type, similarity measure(s) employed, and the sort of clusters desired. Even within the context of a single algorithm, clusters often vary drastically depending on parameter settings. Empirical comparisons performed over a variety of algorithms and settings show highly differential performance on transcriptomic data and demonstrate that many popular methods actually perform poorly. Second, tuning strategies are studied for maximizing biological fidelity when using the well-known paraclique algorithm. Three initialization strategies are compared, using ontological enrichment as a proxy for cluster quality. Although extant paraclique codes begin by simply employing the first maximum clique found, results indicate that by generating all maximum cliques and then choosing one of highest average edge weight, one can produce a small but statistically significant expected improvement in overall cluster quality. Third, a novel outlier detection method is described that helps cleanse data by combining Pearson correlation coefficients, K-means clustering, and Singular Spectrum Analysis in a coherent framework that detects instrument failures and extreme weather events in Atmospheric Radiation Measurement sensor data. The framework is tested and found to produce more accurate results than do traditional approaches that rely on a hand-annotated database

    A Distributed Coordinated Control Scheme for Morphing Wings with Sampled Communication

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    AbstractTo investigate the control of morphing wings by means of interacting effectors, this article proposes a distributed coordinated control scheme with sampled communication on the basis of a simple morphing wing model, established with arrayed agents. The control scheme can change the shape of airfoil into an expected one and keep it smooth during morphing. As the interconnection of communication network and the agents would make the behavior of the morphing wing system complicated, a diagrammatic stability analysis method is put forward to ensure the system stability. Two simulations are carried out on the morphing wing system by using MATLAB. The results stand witness to the feasibility of the distributed coordinated control scheme and the effectiveness of the diagrammatic stability analysis method

    Excessive recreational computer use and food consumption behaviour among adolescents

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    INTRODUCTION: Using the 2005 California Health Interview Survey (CHIS) data, we explore the association between excessive recreational computer use and specific food consumption behavior among California's adolescents aged 12-17. METHOD: The adolescent component of CHIS 2005 measured the respondents' average number of hours spent on viewing TV on a weekday, the average number of hours spent on viewing TV on a weekend day, the average number of hours spent on playing with a computer on a weekday, and the average number of hours spent on playing with computers on a weekend day. We recode these four continuous variables into four variables of "excessive media use," and define more than three hours of using a medium per day as "excessive." These four variables are then used in logistic regressions to predict different food consumption behaviors on the previous day: having fast food, eating sugary food more than once, drinking sugary drinks more than once, and eating more than five servings of fruits and vegetables. We use the following variables as covariates in the logistic regressions: age, gender, race/ethnicity, parental education, household poverty status, whether born in the U.S., and whether living with two parents. RESULTS: Having fast food on the previous day is associated with excessive weekday TV viewing (O.R.=1.38, p<0.01). Having sugary food more than once is associated with excessive weekend TV viewing (O.R.=1.50, p<0.001). Having sugary drinks more than once is associated with excessive weekday TV viewing (O.R.=1.41, p<0.01), excessive weekday recreational computer use (O.R.=1.38, p<0.05), and excessive weekend TV viewing (O.R.=1.43, p<0.001). Finally, having more than five servings of fruits and vegetables on the previous day is negatively associated with all four media use variables: excessive weekday TV viewing (O.R.=0.64, p<0.001), excessive weekday recreational computer use (O.R.=0.68, p<0.01), excessive weekend TV viewing (O.R.=0.80, p<0.05), and excessive weekend recreational computer use (O.R.=0.78, p<0.05). CONCLUSION: Excessive recreational computer use independently predicts undesirable eating behaviors that could lead to overweight and obesity. Preventive measures ranging from parental/youth counseling to content regulations might be addressing the potential undesirable influence from excessive computer use on eating behaviors among children and adolescents

    Microscopic evidence for strong periodic lattice distortion in 2D charge-density wave systems

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    In the quasi-2D electron systems of the layered transition metal dichalcogenides (TMD) there is still a controversy about the nature of the transitions to charge-density wave (CDW) phases, i.e. whether they are described by a Peierls-type mechanism or by a lattice-driven model. By performing scanning tunneling microscopy (STM) experiments on the canonical TMD-CDW systems, we have imaged the electronic modulation and the lattice distortion separately in 2H-TaS2_2, TaSe2_2, and NbSe2_2. Across the three materials, we found dominant lattice contributions instead of the electronic modulation expected from Peierls transitions, in contrast to the CDW states that show the hallmark of contrast inversion between filled and empty states. Our results imply that the periodic lattice distortion (PLD) plays a vital role in the formation of CDW phases in the TMDs and illustrate the importance of taking into account the more complicated lattice degree of freedom when studying correlated electron systems

    Energy efficiency and environmental degradation nexus: evidence from the Quantile-on-Quantile regression technique

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    The world is facing enormous challenge of climate change and global warming due to increased emission level. In order to overcome such challenges, economies are adopting energy efficient techniques to control the carbon emissions and improves environmental sustainability. This study analyses the influencing factors of environmental quality from a global perspective throughout the last three decades. In this regard, advanced time series approaches are used to identify the association between factors such as economic growth, energy efficiency (E.N.E.F.), and carbon emissions – covering global data over the period 1990Q4–2020Q4. From the time series methods, this study observed the stationarity of all variables at first difference. The empirical outcomes also validates the long-run equilibrium relationship between the variables. Due to asymmetric distribution of the variables, this study uses the novel Quantile-on-Quantile (Q.Q.) regression approach, which reveals that increasing economic growth harms environmental quality by increasing the carbon emissions level. However, E.N.E.F. is a prominent factor of environmental sustainability, that reduces the level of carbon emissions in the atmosphere. Employing the pairwise Granger causality test, this study observed the unidirectional causality from economic growth to carbon emissions, while a two-way causal nexus is found between economic growth – E.N.E.F. and E.N.E.F. – carbon emissions. Based on the empirical results, this study suggests that economic growth should be regulated in a sense that it contribute towards the improvement of E.N.E.F., which ultimately leads to reduce the emissions level and promote environmental sustainability

    Physical origin of color changes in lutetium hydride under pressure

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    Recently, near-ambient superconductivity was claimed in nitrogen-doped lutetium hydride (LuH3δ_{3-\delta}Nϵ_{\epsilon}) . Unfortunately, all follow-up research still cannot find superconductivity signs in successfully synthesized lutetium dihydride (LuH2_2) and N-doped LuH2±x_{2\pm x}Ny_y. However, a similar intriguing observation was the pressure-induced color changes (from blue to pink and subsequent red). The physical understanding of its origin and the correlation between the color, crystal structure, and chemical composition of Lu-H-N is still lacking. In this work, we theoretically study the optical properties of LuH2_2, LuH3_3, and some potential N-doped compounds using the first-principles calculations by considering both interband and intraband contributions. Our results show that LuH2_2 has an optical reflectivity peak around blue light up to 10 GPa. Under higher pressure, the reflectivity of red light gradually becomes dominant. This evolution is driven by changes in the direct band gap and the Fermi velocity of free electrons under pressure. In contrast, LuH3_3 exhibits gray and no color change up to 50 GPa. Furthermore, we considered different types of N-doped LuH2_2 and LuH3_3. We find that N-doped LuH2_2 with the substitution of a hydrogen atom at the tetrahedral position maintains the color change when the N-doping concentration is low. As the doping level increases, this trend becomes less obvious. While other N-doped structures do not show significant color change. Our results can clarify the origin of the experimental observed blue-to-red color change in lutetium hydride and also provide a further understanding of the potential N-doped lutetium dihydride
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