Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Path Integral Inspired Query Sequence Suggestion for User Search Task Simplification

Query suggestion algorithms, which aim to suggest a set of similar but independent queries to users, have been widely studied to simplify user searches. However, in many cases, the users will accomplish their search tasks through a sequence of search behaviors instead of by one single query, which may make the classical query suggestion algorithms fail to satisfy end users in terms of task completion. In this paper, we propose a quantum path integral inspired algorithm for personalized user search behavior prediction, through which we can provide sequential query suggestions to assist the users complete their search tasks step by step. In detail, we consider the sequential search behavior of a user as a trajectory of a particle that moves in a query space. The query space is represented by a graph with each node is a query, which is named as query-path graph. Inspired by the quantum theorems, each edge in query-path graph is represented by both amplitude and phase respectively. Using this graph, we modify the quantum path integral algorithm to predict a user’s follow-up trajectory based on her behavioral history in this graph. We empirically show that the proposed algorithm can well predict the user search behavior and outperform classical query suggestion algorithms for user search task completion using the search log of a commercial search engine.
Optimization-Based Search for Nordsieck Methods of High Order with Quadratic Stability Polynomials

We describe the search for explicit general linear methods in Nordsieck form for which the stability function has only two nonzero roots. This search is based on state-of-the-art optimization software. Examples of methods found in this way are given for order p = 5, p = 6, and p = 7.
VOICES FROM THE GRASSROOTS: A PUBLIC HEALTH FRAMEWORK FOR CONDUCTING COMMUNITY-BASED PARTICIPATORY RESEARCH IN POST- KATRINA NEW ORLEANS

This paper explores the perspectives of grassroots organizers currently engaged in community work in Post-Katrina New Orleans to suggest a framework for Community-Based Participatory Research (CBPR). Engaging grassroots organizers in CBPR projects can prove an invaluable resource as they have longstanding relationships with community members and a proven commitment to the communities they serve. To gain entree necessary for carrying out CBPR in partnership with grassroots organizers in this context, researchers must foster genuine relationships that serve to empower community members and are not predicated on university obtained degrees or paternalistic ideas of community engagement. Specific to Post-Katrina New Orleans, grassroots organizers have a great deal of insight to share on the state of the city's recovery, why this work is important to the city's devastated communities, and how researchers interested in engaging their communities can be most effective. The framework presented is based on the principles of CBPR and enhanced with special considerations raised during interviews with grassroots community organizers in Post-Katrina New Orleans. This thesis is significant to public health because it serves not only to strengthen Community-Based Participatory Research in the city of New Orleans, but it could set a precedent for the field of Public Health related to their role in post-disaster recovery in any community for years to come.
Visual exploration of big spatio-temporal movement data

We propose a methodology for exploring groups of human objects and analyzing the movement behaviors of the groups within a specific given space. Movement datasets are generally too big to analyze. We have to use aggravation methods to reduce the datasets into groups. After exploring groups, we obtain an integrated solution with three visualization modules: Collision Detection View for visualizing the detailed information of each group, Force Direct Map for the community structure, and Hotspot View for finding which location in the given space is the most popular. Finally, we use millions of movement records to evaluate our method.
When ‘go’ and ‘nogo’ are equally frequent: ERP components and cortical tomography

In human electrophysiology, a considerable corpus of studies using event‐related potentials have investigated inhibitory processes by employing the ‘go–nogo’ paradigm, which requires responding to one type of event while withholding the response to another type of event. Two event‐related potential waveform features (N2 and P3) have been associated with larger amplitude in nogo trials than in go trials. Traditionally, these differences were thought to reflect response inhibition. Recently, the source localization of N2 to the anterior cingulate cortex, as well as the colocalization of N2 with error‐related negativity, has been interpreted in terms of conflict monitoring. In order to isolate the contribution of inhibitory processes, we matched the frequency of the go and nogo events, thus minimizing differences in response conflict between event types. A data‐driven analytical procedure contrasted go with nogo events across the entire event‐related potential segment and found that N2 reliably differentiated between the two conditions while P3 did not. Tomographical analyses of the N2 difference observed in conditions of equal go and nogo trial frequency localized N2 to the right ventral and dorsolateral prefrontal cortex. Because a growing body of evidence implicates these brain regions in inhibitory processes, we conclude that N2 does, at least in part, reflect inhibition.
Fast and accurate moving object extraction technique for MPEG-4 object-based video coding

A fast and robust video segmentation technique is proposed to generate a coding optimized binary object mask in this work. The algorithm exploits the color information in the L*u*v* space, and combines it with the motion information to separate moving objects from the background. A non-parametric gradient- based iterative color clustering algorithm, called the mean shift algorithm, is first employed to provide robust homogeneous color regions according to dominant colors. Next, moving regions are identified by a motion detection method, which is developed based on the frame intensity difference to circumvent the motion estimation complexity for the whole frame. Only moving regions are analyzed by a region-based affine motion model, and tracked to increase the temporal and spatial consistency of extracted objects. The final shape is optimized for MPEG-4 coding efficiency by using a variable bandwidth region boundary. The shape coding efficiency can be improved up to 30% with negligible loss of perceptual quality. The proposed system is evaluated for several typical MPEG-4 test sequences. It provides consistent and accurate object boundaries throughout the entire test sequences.
A Model of E-Correspondence with Error Correction

In this paper, we presented a model of e-correspondence with error correction for Internet communication. It is the model of a real-life secure e-correspondence system for any organization. In this model a sender can send a secret message even to a unacquainted person in an anonymous way. The users of this model are assumed to be may or may not be the members of a closed organization.
The Galaxy Cluster Luminosity-Temperature Relationship and Iron Abundances: A Measure of Formation History?

Both the X-ray luminosity-temperature (L-T) relationship and the iron abundance distribution of galaxy clusters show intrinsic dispersion. Using a large set of galaxy clusters with measured iron abundances, we find a correlation between abundance and the relative deviation of a cluster from the mean L-T relationship. We argue that these observations can be explained by taking into account the range of cluster formation epochs expected in a hierarchical universe. The known relationship of cooling flow mass deposition rate to luminosity and temperature is also consistent with this explanation. From the observed cluster population, we estimate that the oldest clusters formed at z ≳ 2. We propose that the iron abundance of a galaxy cluster can provide a parameterization of its age and dynamical history.
Locality preserving verification for image search

Establishing correct correspondences between two images has a wide range of applications, such as 2D and 3D registration, structure from motion, and image retrieval. In this paper, we propose a new matching method based on spatial constraints. The proposed method has linear time complexity, and is efficient when applying it to image retrieval. The main assumption behind our method is that, the local geometric structure among a feature point and its neighbors, is not easily affected by both geometric and photometric transformations, and thus should be preserved in their corresponding images. We model this local geometric structure by linear coefficients that reconstruct the point from its neighbors. The method is flexible, as it can not only estimate the number of correct matches between two images efficiently, but also determine the correctness of each match accurately. Furthermore, it is simple and easy to be implemented. When applying the proposed method on re-ranking images in an image search engine, it outperforms the-state-of-the-art techniques.
An optimized unitary beamforming technique for MIMO broadcast channels

This paper addresses the problem of linear beamforming design in MIMO broadcast channels. An iterative optimization method for unitary beamforming is proposed, based on successive optimization of Givens rotations. Under the assumption of perfect channel state information at the transmitter (CSIT) and for practical average signal-to-noise ratios (SNR), the proposed technique provides higher sum rates than zero-forcing (ZF) beamforming while performing close to minimum-mean- squared-error (MMSE) beamforming when the number of transmit antennas equals the number of scheduled users. Moreover, it is shown to achieve linear sum-rate growth with the number of transmit antennas. Interestingly, the proposed unitary beamforming approach proves to be very robust to channel estimation errors. In the simulated scenarios, it provides better sum rates than ZF beamforming and even MMSE beamforming as the variance of the estimation error increases. When combined with simple vector quantization techniques for CSIT feedback in systems with multiuser scheduling, the proposed technique proves to be well suited for limited feedback scenarios with practical number of users, exhibiting performance gains over existing techniques.
On Computer Simulation Models of RSW Process

Due to its high complicacy and transitoriness and closeness, resistance spot welding (RSW), which is widely employed as a major sheet metal joining technology in automotive industry, has attracted specific attentions for computer simulations since last century. In this paper, four major RSW numerical models, namely thermal model, electro-thermal model, electro-thermo-mechanical model and electro-thermal model with fluid flow field, are introduced and investigated thoroughly. Especially, a newly available multi-physics coupling model is discussed and compared with previous models. Suggestions for future research directions are also proposed at the end.
A Survey of Collective Movement of Mobile Robots

Collective movement of mobile robots is the problem of how to control a group of robots making them move as a group, in a cohesive way, towards a common direction. Collective movement serves not only to move a group of robots from one point to another, but to perform more complex tasks such as using the group of robots as a moving sensor array, collective mapping and searching tasks. In this article, a survey of collective movement of mobile robots is done, including a classification and characterization of its different types, a review of the most important architectures and a list of its promising applications.
Essays on corporate governance and investor disagreement

This thesis consists of two essays examining the roles of corporate governance and investor disagreement, respectively, in the performance and stock market valuations of firms. In the first chapter, I demonstrate that the relationship between corporate governance and firm performance varies with industry performance cycles. Firms with strong shareholder rights capture higher profits than poorly-governed firms in the same industry during highly profitable periods for the industry, but both groups have similar profits during weaker industry conditions. Analyst forecasts indicate that the pattern is expected, suggesting that the higher valuations of well-governed firms are due to this higher expected productivity in good times. Consistent with such expectations and with an updating of valuations as anticipated industry conditions change, positive abnormal stock returns to good governance are concentrated in periods of high industry returns, and are at least partially reversed during industry downturns. My results provide an alternative to learning and static risk theories in explaining the apparent abnormal returns to governance and their disappearance after 2001. In Chapter 2, I consider the impact of heterogeneous shareholder beliefs on stock prices, focusing on the context of corporate spin-offs and mergers. I extend theoretical work by Miller (1977) and Jarrow (1980) to show that when investors disagree about the prospects of different businesses and at least some of them are restricted from short-selling, the market price of an unseparable bundle of two enterprises will often be lower from the sum of the prices at which they would trade as standalone entities. Empirically, I construct a novel measure of observed disagreement that is informed by the theory and is less open to alternative interpretations than existing disagreement proxies. Consistent with the theory, I find that higher disagreement about the two components being either separated or joined is related to a positive return in the case of spin-offs and a negative return in stock mergers. Importantly, since I focus on returns on the ex date of these transactions, on which no new business information is released, these findings are unrelated to the expected business impact of the transactions.
Ztitch: a mobile phone application for 3D scene creation, navigation, and sharing

Modern smartphones provide an excellent platform for creating 3D scenes from photos. While there already exists many mobile applications that can stitch a set of photos to create a single, panoramic landscape photo, this paper proposes the creation of panoramic scenes where multiple photos are projected in a 3D space using the pinhole camera model, so that a realistic perspective of the scene is maintained. Our application allows users to automatically create a panoramic 3D scene in real-time using the live images from the phone's camera, and to manually fine-tune each photo's position via the touchscreen if the default position is inaccurate. The application enables scenes to be easily shared to other users, and was developed using the Silverlight framework so that it can run across multiple platforms.
Finite Group Discretization of Yang–Mills and Einstein Actions

Abstract Discrete versions of the Yang–Mills and Einstein actions are proposed for any finite group. These actions are invariant respectively under local gauge transformations and under the analogues of Lorentz and general coordinate transformations. The case Z n × Z n ×···× Z n is treated in some detail, recovering the Wilson action for Yang–Mills theories and a new discretized action for gravity.
Stock Market Interactions Driven by Large Declines

Abstract: This paper seeks to explore the relationship among the large declines in China’s stock market and stock markets in the United States, the United Kingdom, Japan, and Hong Kong, and to forecast future large declines in China’s stock market. We apply mutually exciting marked Hawkes processes—where the occurrences of large declines are regarded as events whose magnitudes follow generalized Pareto distributions—to study the interaction between the different stock markets. We find that these interactions are asymmetric. The occurrences of large declines in the Chinese stock market will stimulate declines in the United States and the United Kingdom, and especially in Japan’s and Hong Kong’s stock markets. However, only large declines in Hong Kong’s market have a substantial influence on the occurrence of big declines in China’s market. Finally, we try to predict the time of occurrence of the next major decline in China’s stock market using information from our empirical results.
Expression of the Receptor Tyrosine Kinase EphB2 on Dendritic Cells Is Modulated by Toll-Like Receptor Ligation but Is Not Required for T Cell Activation

The Eph receptor tyrosine kinases interact with their ephrin ligands on adjacent cells to facilitate contact-dependent cell communication. Ephrin B ligands are expressed on T cells and have been suggested to act as co-stimulatory molecules during T cell activation. There are no detailed reports of the expression and modulation of EphB receptors on dendritic cells, the main antigen presenting cells that interact with T cells. Here we show that mouse splenic dendritic cells (DC) and bone-marrow derived DCs (BMDC) express EphB2, a member of the EphB family. EphB2 expression is modulated by ligation of TLR4 and TLR9 and also by interaction with ephrin B ligands. Co-localization of EphB2 with MHC-II is also consistent with a potential role in T cell activation. However, BMDCs derived from EphB2 deficient mice were able to present antigen in the context of MHC-II and produce T cell activating cytokines to the same extent as intact DCs. Collectively our data suggest that EphB2 may contribute to DC responses, but that EphB2 is not required for T cell activation. This result may have arisen because DCs express other members of the EphB receptor family, EphB3, EphB4 and EphB6, all of which can interact with ephrin B ligands, or because EphB2 may be playing a role in another aspect of DC biology such as migration.
Acoustic noise concerns in functional magnetic resonance imaging

Magnetic resonance (MR) acoustic scanner noise may negatively affect the performance of functional magnetic resonance imaging (fMRI), a problem that worsens at the higher field strengths proposed to enhance fMRI. We present an overview of the current knowledge on the effects of confounding acoustic MR noise in fMRI experiments. The principles and effectiveness of various methods to reduce acoustic noise in fMRI are discussed, practical considerations are addressed and recommendations are made. Hum. Brain Mapping 20:123–141, 2003. © 2003 Wiley‐Liss, Inc.
Classification of Mammogram Images for Detection of Breast Cancer

Breast cancer is the most commonly observed cancer in women both in the developing and the developed countries of the world. The survival rate in it has improved over the past few years with the development of effective diagnostic techniques and improvements in treatment methodologies. About 1 in 8 U.S. women (about 12%) will develop invasive breast cancer over the course of lifetime. In 2014, an estimated 232,670, new cases of invasive breast cancer were expected to be diagnosed in women, along-with 62,570 new cases of non-invasive (in situ) breast cancer. By using mammogram image classification.
Glycosylation of the flagellin of the polar flagellum of Azospirillum brasilense, a Gram-negative nitrogen-fixing bacterium

Summary: The glycosylation of the flagellin of the polar flagellum of Azospirillum brasilense Sp7 is demonstrated in several ways: (1) by a decrease in apparent M r after chemical deglycosylation; (2) by sugar staining after SDS-PAGE; (3) by use of a sugar-specific monoclonal antibody in immunogold labelling coupled with transmission electron microscopy. In addition, two mutant flagellins are described; they differ in glycan composition when compared with the wild-type. The glycosylation of a bacterial flagellin is unusual and has to be taken into account in the proposed model for the assembly of the flagellar filament.
Career Transitions in Sport: International Perspectives

Theory and Research on Career Transitions in Sport Theoretical Perspectives on Career Transition in Sport Self-Identity Issues in Sport Career Termination Causes and Consequences of Sport Career Termination Career Transition Interventions Athlete Lifestyle Programs Practical Considerations in Implementing Sport Career Transition Programs Transferable Skills for Career Change Intervention Strategies for Athletes in Transition The Role of the Sport Organisation in the Career Transition Process Special Populations Transitions in Youth Sport: A Developmental Perspective on Parental Involvement Sport Transitions Among Athletes with Disabilities Career Transitions Among Dancers Within-Career Transitions of the Athlete-Coach-Parent Triad The End of an Era: The Case of Forced Transition Involving Boston University Football.
' s personal copy Sex differences in cannabinoid receptor-1 ( CB 1 ) pharmacology in mice selectively bred for high voluntary wheel-running behavior

a r t i c l e i n f o The endocannabinoid system (ECS) is involved in regulation of various physiological functions, including locomotion, antinociception, emotional states, and motivated behaviors. The ECS has been implicated in regulation of voluntary wheel running in mice via actions at the cannabinoid receptor-1 (CB1). Previously, we showed that four replicate lines of mice bred for high levels of voluntary wheel running (high-runner or HR lines) sex-specifically (females only) decreased running in response to antagonism of the CB1 receptor, as compared with four unselected Control lines. Here, we administered a CB1 receptor agonist, WIN 55,212-2 (WIN). We predicted that if CB1 activation is involved in the regulation of voluntary wheel running, then HR mice would show a greater response to CB1 agonism. Following our previous protocols, mice from generation 53 were acclimated to running wheels for 24 days, then received, in random order, either an intra-peritoneal injection of vehicle or a low (0.5 mg/kg), medium (1 mg/kg) or high dosage (3 mg/kg) of WIN. Each mouse received an injection and then experienced two nights without injections, for a total period of 12 days. Response to WIN was quantified as wheel revolutions, time spent running, and average running speed in the 10–120 min immediately following injection. Injection decreased wheel revolutions in all mice, but male HR mice decreased their running to a greater degree relative to Controls in response to the high dose of WIN over the entire period analyzed, whereas HR females showed a differential response relative to Controls only in the latter 70–120 min post-injection. These results, in conjunction with our previous study, show that (a) aspects of endocannabinoid signaling have diverged in four lines of mice bred for high levels of voluntary exercise and (b) male and female HR mice differ from one another in CB1 signaling as it relates to wheel running. Understanding the control of voluntary behavior is one of the greatest challenges for neurobiology. In particular, knowledge of how the brain motivates imperative, yet potentially costly behaviors – such as voluntary exercise – is of great relevance to an increasingly inactive human population (Garland et al., 2011a). The literature reflects an almost endless array of approaches to study the neurobiology of exercise; we have chosen to use a long-term selection experiment that targets high levels of voluntary wheel running in mice (Garland et al., 2011b; Rhodes et al., 2005; …