Miracle-dz/UniFAR-FTUs huggingface dataset:
MapReduce Based Personalized Locality Sensitive Hashing for Similarity Joins on Large Scale Data

Locality Sensitive Hashing (LSH) has been proposed as an efficient technique for similarity joins for high dimensional data. The efficiency and approximation rate of LSH depend on the number of generated false positive instances and false negative instances. In many domains, reducing the number of false positives is crucial. Furthermore, in some application scenarios, balancing false positives and false negatives is favored. To address these problems, in this paper we propose Personalized Locality Sensitive Hashing (PLSH), where a new banding scheme is embedded to tailor the number of false positives, false negatives, and the sum of both. PLSH is implemented in parallel using MapReduce framework to deal with similarity joins on large scale data. Experimental studies on real and simulated data verify the efficiency and effectiveness of our proposed PLSH technique, compared with state-of-the-art methods.
An expectation-maximization eigenvector clustering approach to direction of arrival estimation of multiple speech sources

This paper presents an eigenvector clustering approach for estimating the direction of arrival (DOA) of multiple speech signals using a microphone array. Existing clustering approaches usually only use low frequencies to avoid spatial aliasing. In this study, we propose a probabilistic eigenvector clustering approach to use all frequencies. In our work, time-frequency (TF) bins dominated by only one source are first detected using a combination of noise-floor tracking, onset detection and coherence test. For each selected TF bin, the largest eigenvector of its spatial covariance matrix is extracted for clustering. A mixture density model is introduced to model the distribution of the eigenvectors, where each component distribution corresponds to one source and is parameterized by the source DOA. To use eigenvectors of all frequencies, the steering vectors of all frequencies of the sources are used in the distribution function. The DOAs of the sources can be estimated by maximizing the likelihood of the eigenvectors using an expectation-maximization (EM) algorithm. Simulation and experimental results show that the proposed approach significantly improves the root-mean-square error (RMSE) for DOA estimation of multiple speech sources compared to the MUSIC algorithm implemented on the single-source dominated TF bins and our previous clustering approach.
National malaria vector control policy: an analysis of the decision to scale-up larviciding in Nigeria

Background: New vector control tools are needed to combat insecticide resistance and reduce malaria transmission. The World Health Organization (WHO) endorses larviciding as a supplementary vector control intervention using larvicides recommended by the WHO Pesticides Evaluation Scheme (WHOPES). The decision to scale-up larviciding in Nigeria provided an opportunity to investigate the factors influencing policy adoption and assess the role that actors and evidence play in the policymaking process, in order to draw lessons that help accelerate the uptake of new methods for vector control. Methods: A retrospective policy analysis was carried out using in-depth interviews with national level policy stakeholders to establish normative national vector control policy or strategy decision-making processes and compare these with the process that led to the decision to scale-up larviciding. The interviews were transcribed, then coded and analyzed using NVivo10. Data were coded according to pre-defined themes from an analytical policy framework developed a priori. Results: Stakeholders reported that the larviciding decision-making process deviated from the normative vector control decision-making process. National malaria policy is normally strongly influenced by WHO recommendations, but the potential of larviciding to contribute to national economic development objectives through larvicide production in Nigeria was cited as a key factor shaping the decision. The larviciding decision involved a restricted range of policy actors, and notably excluded actors that usually play advisory, consultative and evidence generation roles. Powerful actors limited the access of some actors to the policy processes and content. This may have limited the influence of scientific evidence in this policy decision. Conclusions: This study demonstrates that national vector control policy change can be facilitated by linking malaria control objectives to wider socioeconomic considerations and through engaging powerful policy champions to drive policy change and thereby accelerate access to new vector control tools.
Self-similar condensation of rotating magnetized self-gravitating isothermal filaments

Ordinary differential equations describing the self-similar collapse of a rotating, magnetized, self-gravitating and isothermal filament are derived. Explicit homologous solutions are studied with special emphasis on the bifurcation that occurs at the magnetosonic critical point. It is shown that there is a critical value for the toroidal magnetic field slope at the origin above which no bifurcation occurs, the solution remains homologous, and below which the density and the poloidal magnetic field tend to zero at large radius (envelope) whereas the toroidal magnetic field and azimuthal velocity relax towards a constant value. A series of spatial profiles of density, velocity and magnetic field, potentially useful for comparison with numerical or observational studies, is obtained numerically and discussed.
Region Trajectories for Video Semantic Concept Detection

Recently, with the advent of the convolutional neural network (CNN), many CNN-based object detection algorithms have been proposed and achieved encouraging results. In this paper, we introduce an algorithm based on region trajectories to establish the connections between object localizations in individual frames and video sequences. To detect object regions in the individual frames of a video, we enhance the region-based convolutional neural network (R-CNN), by incorporating EdgeBox with the Selective Search to generate candidate region proposals and combining the GoogLeNet with the AlexNet to improve the discriminability of the feature representations. The DeepMatching algorithm is employed in our proposed region trajectory method to track the points in the detected object regions. The experiments are conducted on the validation split of the TRECVID 2015 Localization dataset. As demonstrated by the experimental results, our proposed approach improves the object detection accuracy in both temporal and spatial measurements.
Do Orgasms Give Women Feedback about Mate Choice?

The current study represents a preliminary investigation of the extent to which female orgasm functions to promote good mate choices. Based on a survey of heterosexual female college students in committed relationships, how often women experienced orgasm as a result of sexual intercourse was related to their partner's family income, his self-confidence, and how attractive he was. Orgasm intensity was also related to how attracted they were to their partners, how many times they had sex per week, and ratings of sexual satisfaction. Those with partners who their friends rated as more attractive also tended to have more intense orgasms. Orgasm frequency was highly correlated (r = .82) with orgasm intensity, and orgasm intensity was a marginally better predictor of sexual satisfaction than orgasm frequency. Sexual satisfaction was related to how physically attracted women were to their partner and the breadth of his shoulders. Women who began having sexual intercourse at earlier ages had more sex partners, experienced more orgasms, and were more sexually satisfied with their partners. We also identified an ensemble of partner psychological traits (motivation, intelligence, focus, and determination) that predicted how often women initiated sexual intercourse. Their partner's sense of humor not only predicted his self-confidence and family income, but it also predicted women's propensity to initiate sex, how often they had sex, and it enhanced their orgasm frequency in comparison with other partners.
Modeling the Persuasive Effect of Search Engine Results

Search engines have become a fundamental tool for destination marketing organizations in that they offer the primary means for a destination to “be seen” by a very large audience. Recent research argues that the compact advertisements provided by search engines represent the “first impression” one may receive of a destination and therefore, they act as the gateway to destination website. As such, the compact text represented in search engine results provides an important foundation for promotional strategies to market destinations on the Internet. This study examines the persuasive effect of textual search results on travelers’ perceptions of the relevance of organic search results. A simulated travel planning exercise was conducted by asking respondents to rank order organic textual search results in terms of the degree of relevance to their planning task. The results of the analysis clearly indicate that certain linguistic elements of the search results have significantly higher persuasive power than others, and therefore, provide the building blocks for developing more effective communication strategies.
A photoionization model of the compact HII region G29.96-0.02

We present a detailed photoionization model of G29.96-0.02 (hereafter G29.96), one of the brightest Galactic Ultra Compact HII (UCHII) regions in the Galaxy. This source has been observed extensively at radio and infrared wavelengths. The most recent data include a complete ISO (SWS and LWS) spectrum, which displays a remarkable richness in atomic fine-structure lines. The number of observables is twice as great as the number available in previous studies. In addition, most atomic species are now observed in two ionization stages. The radio and infrared data on G29.96 are best reproduced using a nebular model with two density components: a diffuse (n(e) similar to 680 cm(-3)) extended (similar to1 pc) component surrounding a compact (similar to0.1 pc) dense (n(e) similar to 57 000 cm(-3)) core. The properties of the ionizing star were derived using state-of-the-art stellar atmosphere models. CoStar models yield an effective temperature of similar to30(+2)(-1) kK whereas more recent non-LTE line blanketed atmospheres with stellar winds indicate somewhat higher values, T-eff similar to 32-38 kK. This range in T-eff is compatible with all observational constraints, including near-infrared photometry and bolometric luminosity. The range 33-36 kK is also compatible with the spectral type O5-O8 determined by Watson & Hanson (1997) when recent downward revisions of the effective temperature scale of O stars are taken into account. The age of the ionizing star of G29.96 is found to be a few 10(6) yr, much older than the expected lifetime of UCHII regions. Accurate gas phase abundances are derived with the most robust results being Ne/S = 7.5 and N/O = 0.43 (1.3 and 3.5 times the solar values, respectively).
Back to Bentham? Explorations of experience utility

Two core meanings of "utility" are distinguished. "Decision utility" is the weight of an outcome in a decision. "Experienced utility" is hedonic quality, as in Bentham's usage. Experienced utility can be reported in real time (instant utility), or in retrospective evaluations of past episodes (remembered utility). Psychological research has documented systematic errors in retrospective evaluations, which can induce a preference for dominated options. We propose a formal normative theory of the total experienced utility of temporally extended outcomes. Measuring the experienced utility of outcomes permits tests of utility maximization and opens other Unes of empirical research.
Exploring the connection between L2 learning motivation and past learning narratives

Japanese secondary school students (N=524) were surveyed to assess the correlational relationship between present English learning motivation and past learning narratives. An additional aim of the study was to determine whether past narratives should be operationalized into research questionnaires that utilize Zoltan Dornyei’s (2005) future oriented L2 Motivational Self System (L2MSS). The results revealed a positive correlational relationship (r=.66) between past learning narratives and the motivational criterion measure, but the recommendation that past learning narrative question items should be incorporated into the present formulation of the L2MSS could not be corroborated with the data. Introduction An aspect of conducting research that is as essential as choosing a suitable population, pursuing appropriate data analysis, or even choosing a suitable theory, is the questions that the participants are asked. This is especially true for Likert scale questionnaires, where there is no room for elaboration. In such questionnaires, a number of questions are typically chosen to work in conjunction to capture the breadth of a concept or psychological state that is not directly measurable; this is referred to as the operationalization of the concept. While researching English learning motivation in Japanese secondary schools using Zoltan Dornyei’s (2005; 2009) L2 Motivational Self System (hereafter referred to as L2MSS), which focuses on imagined future possible selves and learners’ present learning experiences, I noticed what I perceived to be a gap between the theory and its operationalization with regards to learners’ past narratives (Cacali, 2014). Although it was not vital to the main thrust of the L2MSS research, five additional questions were inserted into my research instrument in order to explore the relationship between motivation and past learning narratives. The following
Forest Canopy Density Stratification: How Relevant is Biophysical Spectral Response Modelling Approach?

Abstract Monitoring of forest cover is an essential tool for sustainable management of natural resources. Woody green cover can better maintained and managed by identification of forest gaps and their subsequent refilling. Forest canopy density mapping is one of the tools used to identify such canopy openings and most useful parameter to consider in the planning and implementation of afforestation and reforestation program. The present study demonstrate the test‐assessment and practicability of forest canopy density mapping using satellite remote sensing data and biophysical spectral response modelling. Forest canopy density stratification through object oriented image analysis and conventional method of visual interpretation also have been compared with the Forest Canopy Density (FCD) Mapper semi expert system. In this study, forest canopy density is effectively stratified through linear multi‐parametric approach by utilizing advanced vegetation index, bare soil index, shadow index and thermal index. Isadata cluster analysis of forest canopy density map derived from FCD Mapper and conventional methods were shown similar results with respect to percent area of forest and non‐forest. The high percentage (10-30%) occurrence of bushy vegetation like Lantana Camera in ground canopy poses challenge in delineation of forest canopy density as its spectral reflectance is similar to that of the forest.
Econometric Computing with HC and HAC Covariance Matrix Estimators

Data described by econometric models typically contains autocorrelation and/or heteroskedasticity of unknown form and for inference in such models it is essential to use covariance matrix estimators that can consistently estimate the covariance of the model parameters. Hence, suitable heteroskedasticity consistent (HC) and heteroskedasticity and autocorrelation consistent (HAC) estimators have been receiving attention in the econometric literature over the last 20 years. To apply these estimators in practice, an implementation is needed that preferably translates the conceptual properties of the underlying theoretical frameworks into computational tools. In this paper, such an implementation in the package sandwich in the R system for statistical computing is described and it is shown how the suggested functions provide reusable components that build on readily existing functionality and how they can be integrated easily into new inferential procedures or applications. The toolbox contained in sandwich is extremely flexible and comprehensive, including specific functions for the most important HC and HAC estimators from the econometric literature. Several real-world data sets are used to illustrate how the functionality can be integrated into applications.
Galactosaminogalactan, a New Immunosuppressive Polysaccharide of Aspergillus fumigatus

A new polysaccharide secreted by the human opportunistic fungal pathogen Aspergillus fumigatus has been characterized. Carbohydrate analysis using specific chemical degradations, mass spectrometry, 1H and 13C nuclear magnetic resonance showed that this polysaccharide is a linear heterogeneous galactosaminogalactan composed of α1-4 linked galactose and α1-4 linked N-acetylgalactosamine residues where both monosacharides are randomly distributed and where the percentage of galactose per chain varied from 15 to 60%. This polysaccharide is antigenic and is recognized by a majority of the human population irrespectively of the occurrence of an Aspergillus infection. GalNAc oligosaccharides are an essential epitope of the galactosaminogalactan that explains the universal antibody reaction due to cross reactivity with other antigenic molecules containing GalNAc stretches such as the N-glycans of Campylobacter jejuni. The galactosaminogalactan has no protective effect during Aspergillus infections. Most importantly, the polysaccharide promotes fungal development in immunocompetent mice due to its immunosuppressive activity associated with disminished neutrophil infiltrates.
Being and Becoming Men of Character: Exploring Latino and Black Males’ Brotherhood and Masculinity Through Leadership in College

This article advances knowledge on the significance of engagement and leadership for five Latino and Black male student leaders at a Hispanic-serving institution. By exploring their experiences in a male-centered initiative, identity and masculinity emerged as salient frames to understand students’ engagement on campus. Individual and focus group interviews yielded that relationships and male peer-to-peer bonding built on students’ cultural wealth by providing unique opportunities for learning and self-growth. Implications are offered as well.
A NEAR-INFRARED VARIABILITY STUDY OF THE GALACTIC BLACK HOLE: A RED NOISE SOURCE WITH NO DETECTED PERIODICITY

We present the results of near-infrared (NIR; 2 and 3 μ) monitoring of Sgr A*-IR with 1 minute time sampling using the natural and laser guide star adaptive optics system at the Keck II telescope. Sgr A*-IR was observed continuously for up to 3 hr on each of seven nights, between 2005 July and 2007 August. Sgr A*-IR is detected at all times and is continuously variable, with a median observed 2 μ flux density of 0.192 mJy, corresponding to 16.3 mag at K′. These observations allow us to investigate Nyquist sampled periods ranging from about 2 minutes to 1 hr. Using Monte Carlo simulations, we find that the variability of Sgr A* in this data set is consistent with models based on correlated noise with power spectra having frequency-dependent power-law slopes between 2.0 and 3.0, consistent with those reported for active galactic nucleus light curves. Of particular interest are periods of ∼20 minutes, corresponding to a quasiperiodic signal claimed based upon previous NIR observations and interpreted as the orbit of a “hot spot” at or near the last stable orbit of a spinning black hole. We find no significant periodicity at any timescale probed in these new observations for periodic signals. This study is sensitive to periodic signals with amplitudes greater than 20% of the maximum amplitude of the underlying red noise component for light curves with a duration greater than ∼2 hr at a 98% confidence limit.
Property of Stocks and Wealth Effects on Consumption

Recent fluctuations of financial markets, especially, stock markets fluctuations, have revived the interest concerning the dynamics of real economic activity, namely, of private consumption. In this work, the role of stock market as a determinant of private consumption is analyzed, namely, by the consideration of wealth effects. It is also analyzed the potential differences of these effects originated by different categories of property of stocks (direct versus indirect property). Using a sample for the U. S. economy, in the period 1952:Q1 - 2001:Q4, several long-run relationships were estimated, suggesting that wealth effects associated to direct property are about 3.5 times superior to those associated to indirect property. Short-run dynamics is analyzed with the estimation of a single equation, suggesting that consumption contemporaneously answers to changes in income and in wealth and that the adjustment to long-run component is very slow, which constitutes an indicator that consumers gradually change their behaviors, possibly, due to habit formation. There is also evidence supporting the presence of the indirect channel of wealth effect.
The influence of knowledge networks on a firm’s innovative performance

Abstract This paper explores the concept of knowledge networks in order to disclose how firms are able to increase innovative performance as a result of network structure and network content, which concern how firms connect with network partners (network structure), what the essence of exchange is for firms to acquire knowledge in the network (knowledge heterogeneity), and why firms need to cooperate with others (knowledge cognition). By using a sample of 144 high-technology firms in Taiwan’s science parks to test the hypotheses, the results of this study show that, while network structures do impact on a firm’s innovative performance, access to heterogeneous knowledge and increasing a firm’s knowledge in terms of defining and recognizing novel knowledge should be considered, since both play critical roles in facilitating innovative performance. These findings suggest that knowledge flow through a firm’s relationships must be understood in terms of network structure and content.
Efficient 3D‐finite element formulation for thin mechanical and piezoelectric structures

It is the aim to compute efficiently the deformations of the mechanical structures that are excited or damped by piezoelectric actuators. They are treated as 3D structures to have much flexibility. Special design of the finite element concept is required since the structures are thin walled and locking effects have to be avoided. Although the computations are performed in the framework of 3D elasticity, we use ideas from modern plate elements and mixed methods. Copyright © 2007 John Wiley & Sons, Ltd.
Sharing good fortune: Effects of scarcity on small donation requests

Abstract Based on studies linking positive outcomes to subsequent helping, it was hypothesized that when individuals receive their choice of items when supply is constrained they will show heightened prosocial behavior. Participants either received a choice of candy when it was plentiful, a choice of candy under scarce conditions, or no option to choose between candies under scarce conditions. All were subsequently invited to keep previously acquired school supplies or to donate them back. As hypothesized, when participants received their choice of candy their donation rate was higher in the scarce, versus the non-scarce, condition. Those not receiving choice due to scarcity behaved similarly to those who received choice under the condition of plenty. Discussion focuses on applications to encourage helpfulness.