Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Neighborhood Formation Approaches for Collaborative Filtering

E-commerce, buying and selling of products by electronic means, has become popular due to the emergence of World Wide Web. One of the vital components of e-commerce systems is recommender systems (RSs). The RS is employed as a part of e-commerce system to help users in finding products of their interest from a huge number of available products. The Collaborative filtering (CF) approach is one of the popular approaches employed to build recommender systems. The neighborhood formation is one of the key steps in collaborative filtering and influences the performance of recommender systems. In this thesis, we have made an effort to improve the performance of recommender systems by proposing two improved neighborhood formation methods. At first, we have extended the notion of lower-bound similarity to improve the performance of neighborhood formation in CF-based recommender system. For neighborhood formation, k-nearest neighbor (kNN) approach is followed to find k neighbors of a target user. Given a fixed k value, the approach finds k nearest neighbors using different similarity methods. We identified the following issue with the kNN approach. Due to fixed value of k, the users who have rated few products may get less-similar neighbors and the users who have rated more products may miss the genuine neighbors. In the literature, the notion of lower-bound similarity has been proposed as an alternative to the popular k-means approach to improve the clustering performance in which the clusters are extracted by fixing the similarity threshold. By extending the notion of lower-bound similarity, we have proposed a neighborhood formation approach by fixing the similarity threshold instead of k. With this approach, it was proposed that it is possible to get appropriate number of neighbors of a target user. The experimental results on real-world dataset, show that the proposed approach improves the performance over the existing kNN-CF approach. In addition, we have proposed a category-based approach to improve the neighborhood formation in collaborative filtering approach. It can be noted that in kNN-based CF approach, the similarity values of the product ratings between two users are computed by considering the product ratings of each user as one unit. It was observed that the products rated by a user consist of several sub-groups based on different categories. In this situation, if we compare the product ratings of two users, they may not be similar at the user-level. However, they may be similar if the comparison made at the category-level. The basic idea is that there is an opportunity to find the genuine neighbors if we find the neighbors at the category-level. In the proposed approach, ratings given by a user are divided into different sub-groups based on the categories of products. We consider that the ratings of each sub-group are given by a virtual user. For a target user, the recommendations of the corresponding virtual user are computed
Parental Vaccine Safety Concerns in 2009

OBJECTIVE: Vaccine safety concerns can diminish parents' willingness to vaccinate their children. The objective of this study was to characterize the current prevalence of parental vaccine refusal and specific vaccine safety concerns and to determine whether such concerns were more common in specific population groups. METHODS: In January 2009, as part of a larger study of parents and nonparents, 2521 online surveys were sent to a nationally representative sample of parents of children who were aged ≤17 years. The main outcome measures were parental opinions on vaccine safety and whether the parent had ever refused a vaccine that a doctor recommended for his or her child. RESULTS: The response rate was 62%. Most parents agreed that vaccines protect their child(ren) from diseases; however, more than half of the respondents also expressed concerns regarding serious adverse effects. Overall, 11.5% of the parents had refused at least 1 recommended vaccine. Women were more likely to be concerned about serious adverse effects, to believe that some vaccines cause autism, and to have ever refused a vaccine for their child(ren). Hispanic parents were more likely than white or black parents to report that they generally follow their doctor's recommendations about vaccines for their children and less likely to have ever refused a vaccine. Hispanic parents were also more likely to be concerned about serious adverse effects of vaccines and to believe that some vaccines cause autism. CONCLUSIONS: Although parents overwhelmingly share the belief that vaccines are a good way to protect their children from disease, these same parents express concerns regarding the potential adverse effects and especially seem to question the safety of newer vaccines. Although information is available to address many vaccine safety concerns, such information is not reaching many parents in an effective or convincing manner.
The 11 March 2011 Tohoku tsunami wavefront mapping across offshore Southern California

The 11 March 2011 (Mw = 9.0) Tohoku tsunami was recorded by a temporary array of seafloor pressure gauges deployed off the coast of Southern California, demonstrating how dense array data can illustrate and empirically validate predictions of linear tsunami wave propagation characteristics. A noise cross‐correlation method was used to first correct for the pressure gauge instrument phase response. Phase and group travel times were then measured for the first arrival in the pressure gauge tsunami waveforms filtered in narrow bands around 30 periods between 200 and 3000 s. For each period, phase velocities were estimated across the pressure gauge array based on the phase travel time gradient using eikonal tomography. Clear correlation was observed between the phase velocity and long‐wavelength bathymetry variations where fast and slow velocities occurred for deep and shallow water regions, respectively. In particular, velocity gradients are pronounced at the Patton Escarpment and near island plateaus due to the abrupt bathymetry change. In the deep open ocean area, clear phase velocity dispersion is observed. Comparison with numerically calculated tsunami waveforms validates the approach and provides an independent measure of the finite‐frequency effect on phase velocities at long periods.
G Protein-Activated (GIRK) Current in Rat Ventricular Myocytes is Masked by Constitutive Inward Rectifier Current (IK1)

Inwardly-rectifying K<sup>+</sup> channel subunits are not homogenously expressed in different cardiac tissues. In ventricular myocytes (VM) the background current-voltage relation is dominated by I<sub>K1</sub>, carried by channels composed of Kir2.x subunits, which is less important in atrial myocytes (AM). On the other hand in AM a large G protein gated current carried by Kir3.1/3.4 complexes can be activated by stimulation of muscarinic M<sub>2</sub> receptors (I<sub>K(ACh)</sub>), which is assumed to be marginal in VM. Recent evidence suggests that total current carried by cardiac inward-rectifiers (I<sub>K(ATP)</sub>, I<sub>K(ACh)</sub>, I<sub>K1</sub>) in both, AM and VM is limited, due to K<sup>+</sup> accumulation/depletion. This lead us to hypothesize that in conventional whole celI recordings I<sub>K(ACh)</sub> in VM is underestimated as a consequence of constitutive I<sub>K1</sub>. In that case a reduction in density of I<sub>K1</sub> should be paralleled by an increase in density of I<sub>K(ACh)</sub>. Three different experimental strategies have been used to test for this hypothesis: (i) Adenovirus-driven expression of a dominant-negative mutant of Kir2.1, one of the subunits supposed to form I<sub>K1</sub> channels, in VM caused a reduction in I<sub>K1</sub>-density by about 80 %. In those cells I<sub>K(ACh)</sub> was increased about 4 fold. (ii) A comparable increase in I<sub>K(ACh)</sub> was observed upon reduction of I<sub>K1</sub> caused by adenovirus-mediated RNA interference. (iii) Ba<sup>2+</sup> in a concentration of 2 µM blocks I<sub>K1</sub> in VM by about 60 % without affecting atrial I<sub>K(ACh)</sub>. The reduction in I<sub>K1</sub> by 2 µM Ba<sup>2+</sup> is paralleled by a reversible increase in I<sub>K(ACh)</sub> by about 100%. These data demonstrate that the increase in K<sup>+</sup> conductance underlying ventricular I<sub>K(ACh)</sub> is largely underestimated, suggesting that it might be of greater physiological relevance than previously thought.
An Integrated System for Modeling, Animating and Rendering Hair

There are basically four problems to solve in order to produce realistic animated synthetic actors with hair: hair modeling and creation, hair motion, collision detection and hair rendering. This paper describes a complete methodology to solve these basic four problems. We present how hair styles may be designed with our Hair Styler module. Then we survey the animation model and emphasize a method of collision processing. Finally, we explain how hair may be rendered using an extension of a standard ray‐tracing program. We also show applications of our synthetic actors with various hair styles and different styles of mustaches and beards.
The Gay Family in the Ad: Consumer Responses to Non-traditional Families in Marketing Communications

This paper investigates consumer responses to gay families portrayed in advertising, drawing on critical visual analysis, reader response analysis and queer theory. Twenty-five consumers were interviewed about a selection of family oriented ads. Several themes emerged from the interviews, including straightening up – reading apparently gay images as heterosexual, or straight, despite rather overt gay signals. This important interpretive phenomenon seems to "interfere" with processing of apparently gay imagery, revealing interesting interpretive strategies. Findings are discussed within the advertising as representation research tradition, and illuminate interpretive strategies that consumers use when confronted with culturally sensitive images in advertising.
A Riemannian geometry for low-rank matrix completion

We propose a new Riemannian geometry for fixed-rank matrices that is specifically tailored to the low-rank matrix completion problem. Exploiting the degree of freedom of a quotient space, we tune the metric on our search space to the particular least square cost function. At one level, it illustrates in a novel way how to exploit the versatile framework of optimization on quotient manifold. At another level, our algorithm can be considered as an improved version of LMaFit, the state-of-the-art Gauss-Seidel algorithm. We develop necessary tools needed to perform both first-order and second-order optimization. In particular, we propose gradient descent schemes (steepest descent and conjugate gradient) and trust-region algorithms. We also show that, thanks to the simplicity of the cost function, it is numerically cheap to perform an exact linesearch given a search direction, which makes our algorithms competitive with the state-of-the-art on standard low-rank matrix completion instances.
The brainstem reticular formation is a small-world, not scale-free, network

Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called ‘small-world’ and ‘scale-free’ networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain—the medial reticular formation (RF) of the brainstem—and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement.
Iron abundances derived from RR Lyrae light curves and low-dispersion spectroscopy

With the aid of the All Sky Automated Survey (ASAS) database on the Galactic field, we compare the iron abun- dances of fundamental mode RR Lyrae stars derived from the Fourier parameters with those obtained from low-dispersion spectroscopy. We show from a set of 79 stars, distinct from the original calibrating sample of the Fourier method and selected without quality control, that almost all discrepant estimates are the results of some defects or peculiarities either in the photom- etry or in the spectroscopy. Omitting objects deviating by more than 0.4 dex, the remaining subsample of 64 stars yields Fourier abundances that fit the spectroscopic ones with σ = 0.20 dex. Other, more stringent selection criteria and different Fourier decompositions lead to smaller subsamples and concomitant better agreement, down to σ = 0.16 dex. Except perhaps for two variables among the 163 stars, comprised of the ASAS variables and those of the original calibrating set of the Fourier method, all discrepant values can be accounted for by observational noise and insufficient data coverage. We suggest that the agreement can be further improved when new, more accurate spectroscopic data become available for a test with the best photometric data. As a by-product of this analysis, we also compute revised periods and select Blazhko variables.
Crowd++: unsupervised speaker count with smartphones

Smartphones are excellent mobile sensing platforms, with the microphone in particular being exercised in several audio inference applications. We take smartphone audio inference a step further and demonstrate for the first time that it's possible to accurately estimate the number of people talking in a certain place -- with an average error distance of 1.5 speakers -- through unsupervised machine learning analysis on audio segments captured by the smartphones. Inference occurs transparently to the user and no human intervention is needed to derive the classification model. Our results are based on the design, implementation, and evaluation of a system called Crowd++, involving 120 participants in 10 very different environments. We show that no dedicated external hardware or cumbersome supervised learning approaches are needed but only off-the-shelf smartphones used in a transparent manner. We believe our findings have profound implications in many research fields, including social sensing and personal wellbeing assessment.
The Presence of a Weapon Shrinks the Functional Field of View

Summary This study examined whether the functional field of view shrinks by the presence of a weapon or the increase of emotional arousal. In Experiment 1, participants viewed two types of pictures depicting scenes involving weapons or control objects and were asked to identify digits presented at the periphery when the pictures disappeared. The results showed that the presence of a weapon impaired identification of the peripheral digits, even when the pictures were equal with respect to emotional arousal level. In Experiment 2, participants viewed emotionally arousing pictures or neutral pictures, neither of which included weapons, and they were asked to identify digits presented at the periphery when the pictures disappeared. The results revealed that the increased emotional arousal did not impair identification of the peripheral digits. These results indicate that the functional field of view shrinks because of the presence of a weapon but not because of increased emotional arousal.Copyright © 2015 John Wiley & Sons, Ltd.
Patriarchy/Matriarchy versus Blood Quantum Cultural Significance as Evidenced in Hawaii Land Commission Grants

During the land division of 1848 (Great Mahele), both Hawaiians and non-Hawaiians were given the ability to make a formal claim to land in the Hawaiian Islands, 1 seemingly regardless of gender. While the West was a predominantly patriarchal society at this time, lineage purity and ‘godliness’ were the markers of Hawaiian society. While many scholars have pointed to the Mahele as a major turning point in the land distribution system (that is, land was taken from the Hawaiian people and ‘redistributed’ to non-Hawaiians), it may have also been an unusual opportunity for gendered resource distribution: namely formal, governmentally- recognized land ownership by women. Hawaiian society, while predominantly classbased within a patriarchal system, did allow females positions of power.
A senone based confidence measure for speech recognition

This paper describes three experiments in using fra me level observation probabilities as the basis for wo rd confidence annotation in an HMM speech recognition system. One experiment is at the word level, one us es word classes, and the other uses phone classes. In each experiment we categorize hypotheses into correct an d incorrect categories by aligning a best recognition hypothesis with the known transcript. The confidenc e of error prediction for each class is a measure of the resolvability between the correct and incorrect histograms.
A hybrid algorithm for multiple parameters estimation with UCA of electromagnetic vector sensors

In order to avoid the multi-dimensional spectrum peak search for multiple parameters estimation, a hybrid algorithm with uniform circular array (UCA) of electromagnetic vector sensors based on the beamspace transformation is proposed. In the beamspace, the azimuth angle can be split from other parameters and can be estimated without using spectral peak search. Then, the elevation estimation can be obtained with the estimated azimuth angle via a one-dimensional spectrum peak search. Finally, the polarized parameters are obtained based on the estimated azimuth and elevation angle via the engine decomposition with the modulus constraint. Its computation complexity is superior to the one of the tradition MUSIC and the existing reduced-dimensional algorithm.
A CONTROL OF CHANNEL RATE FOR REAL-TIME VBR VIDEO TRANSMISSION

Recent studies on the Constant Bit Rate and Variable Bit Rate transmissions have mainly focused on the frame by frame encoder rate control based on the quantization parameter. With the existing approaches it is difficult to guarantee a consistent video quality. Also, the rate control overhead is too high for the real-time video sources. In this paper, a channel rate allocation scheme based on the control period is proposed to transmit a real-time video, in which the control period is defined by a pre-specified number of frames or group of pictures. At each control period, video traffic information is collected to determine the channel rate at the next control period. The channel rate is allocated to satisfy various channel rate constraints such that the buffer occupancy at the decoder is maintained at a target level. If the allocated channel rate approaches the level at which the negotiated traffic descriptions may be violated, the encoder rate is decreased through adjusting quantization parameters in the MPEG encoder. In the experimental results, the video quality and the overflow and underflow probabilities at the buffer are compared at different control periods. Experiments show that the video quality and the utilization of network bandwidth resources can be optimized through the suitable selection of the control period. Index Terms – ATM networks, VBR video transmission, control of channel rate, control period.
A General Recommendation Model for Heterogeneous Networks

Heterogeneous networks refer to the networks comprising multiple types of entities as well as their interaction relationships. They arise in a great variety of domains, for example, event-based social networks Meetup and Plancast, and DBLP. Recommendation is a useful task in these heterogeneous network systems. Although many recommendation algorithms are proposed for heterogeneous data, none of them is able to explicitly model the influence strength between different types of entities, which is useful not only for achieving higher recommendation accuracy but also better understanding the role of each entity type in recommendation problems. Moreover, many of those algorithms are designed for a particular task, and hence it is challenging to apply them in other problems. In this paper, we propose a graph-based model, called HeteRS, which can solve general recommendation problems on heterogeneous networks. Our method models the rich information with a heterogeneous graph and considers the recommendation problem as a query-dependent node proximity problem. To address the challenging issue of weighting the influences between different types of entities, we propose a learning scheme to set the influence weights between different types of entities in recommendation. Experimental results on real-world datasets demonstrate that our proposed method significantly outperforms the baseline methods in our experiments for all the recommendation tasks, and the learned influence weights help understanding user behaviors.
Quantitative conservation biology : theory and practice of population viability analysis

Preface - What Is PVA, and How Can It Be Used in Conservation Decision-making? - The Causes and Quantification of Population Vulnerability - Count-based PVA: Density-independent Models - Count-based PVA: Incorporating Density Dependence, Demographic Stochasticity, Correlated Environments, Catastrophes and Bonanzas - Accounting for Observation Error in Count-based PVAs - Demographic PVAs: Using Demographic Data to Build Stochastic Projection Matrix Models - Demographic PVAs: Using Projection Matrices to Assess Population Growth and Viability - Demographic PVAs Based on Vital Rates: Removing Sampling Variation and Incorporating Large Variance, Correlated Environments, Demographic Stochasticity, and Density Dependence into Matrix Models - Using Demographic PVA Models in Management: Sensitivity and Elasticity Analysis - Multi-site PVAs: The Interaction of Dispersal and Environmental Correlation - Multi-site PVAs: Methods of Analysis for Spatially Complex Populations - Critiques and Cautions: When to Perform (and When Not to Perform) a PVA - References
An algebra for pattern matching, time-aware aggregates and partitions on relational data streams

Many interesting applications of continuous-query processing are concerned with pattern matching or complex temporal aggregation of events. Real-world queries that rely on these operations are difficult to implement in current stream-processing systems. The reason seems to be a gap between two types of existing query languages: Some languages (e. g. CQL) offer a small set of simple operators that can be combined in order to create complex queries. While these languages provide sound and comprehensible semantics, they lack the expressiveness required for many real-world applications. Other approaches (e. g. Aurora) provide powerful operators but lack semantic strictness, which is required for reasoning about query results. Such reasoning is a prerequisite for safe query optimization. We try to bridge this gap by integrating operators for pattern matching and time-aware aggregates into a general-purpose stream model featuring stream partitioning. These operators can answer several questions that we have found to be relevant in a real-world object-tracking scenario. Moreover, they are formally defined, allowing expressive and efficient queries to be written in CQL-like languages, while remaining understandable and easy to use.