Miracle-dz/UniFAR-FTUs huggingface dataset:
Addressing the challenges of underspecification in web search

The World Wide Web contains information on a scale far beyond the capacity of manual organization methods. Web search engines help users sift through that information to find data of interest through keyword searches, while also driving a multi-billion dollar advertising industry on the Web. Searching through all of the data on the Web to find the most relevant content is an enormous task, often exacerbated by underspecification and ambiguity in the queries posed by users or the underlying data itself. Users frequently omit relevant context or submit multifaceted queries, authors rarely provide explicit keywords or categorizations, and content is often missing relevant keywords. Uncertainty leads to inherent difficulty for search engines to find the best information for a particular user and query. We investigate these problems and propose techniques to effectively satisfy the needs of users and advertisers when a search engine encounters such uncertainty. The main challenges we address consist of: (1) Discovering which queries or keywords may benefit from contextualization. We propose a framework for automatically identifying geo-localizable queries, establishing several features measurable from search query logs which enable traditional machine learning algorithms to classify queries with high accuracy. (2) Given an ambiguous query, determining the most likely user requirements for each of the possible subtopics and then selecting a diverse set of pages to satisfy the greatest number of users. We describe a model for user satisfaction with a returned set of pages and propose a greedy algorithm for diversifying search results tailored towards the requirements of informational queries, when users frequently require more than one relevant result. We demonstrate notable improvement over current ranking strategies. (3) Identifying the pertinent keywords from sparse or imprecise content. We study two approaches for generating keywords from the text content of videos and investigate related term mining approaches to overcome potential mismatches between these keywords and the keywords chosen by searchers or advertisers. We perform extensive evaluations to highlight under what conditions each method generates the most relevant keywords. This dissertation presents and evaluates methods and algorithms which may benefit search engines, their users, and their advertising partners for a significant fraction of search instances and exabytes of data.
Nonparametric Bayesian reward segmentation for skill discovery using inverse reinforcement learning

We present a method for segmenting a set of unstructured demonstration trajectories to discover reusable skills using inverse reinforcement learning (IRL). Each skill is characterised by a latent reward function which the demonstrator is assumed to be optimizing. The skill boundaries and the number of skills making up each demonstration are unknown. We use a Bayesian nonparametric approach to propose skill segmentations and maximum entropy inverse reinforcement learning to infer reward functions from the segments. This method produces a set of Markov Decision Processes (MDPs) that best describe the input trajectories. We evaluate this approach in a car driving domain and a simulated quadcopter obstacle course, showing that it is able to recover demonstrated skills more effectively than existing methods.
Annotations for HTML to VoiceXML Transcoding: Producing Voice WebPages with Usability in Mind

Web pages contain a large variety of information, but are largely designed for use by graphical web browsers. Mobile access to web-based information often requires presenting HTML web pages using channels that are limited in their graphical capabilities such as small-screens or audio-only interfaces. Content transcoding and annotations have been explored as methods for intelligently presenting HTML documents. Much of this work has focused on transcoding for small-screen devices such as are found on PDAs and cell phones. Here, we focus on the use of annotations and transcoding for presenting HTML content through a voice user interface instantiated in VoiceXML. This transcoded voice interface is designed with an assumption that it will not be used for extended web browsing by voice, but rather to quickly gain directed access to information on web pages. We have found repeated structures that are common in the presentation of data on web pages that are well suited for voice presentation and navigation. In this paper, we describe these structures and their use in an annotation system we have implemented that produces a VoiceXML interface to information originally embedded in HTML documents. We describe the transcoding process used to translate HTML into VoiceXML, including transcoding features we have designed to lead to highly usable VoiceXML code.
Low complexity stereo matching algorithm using adaptive sized square window

This paper presents an efficient stereo matching algorithm for hardware implementation. A low-complexity local window size decision rule is proposed in our processing scheme. The proper window size is adopted according to the local content characteristic. The matching computation cost is almost as low as the conventional fixed window size method. An efficient hardware architecture comprises unified window size processing elements is also developed. Experimental results reveal that the proposed design can achieve better quality than the related fixed window size method with the properties of low computation cost and hardware realizable flow.
Transient Energy and its Impact on Transmission Line Faults

Transmission and distribution lines are vital links between the generating unit and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high which has to be immediately taken care of in order to minimize damage caused by it. In this paper Discrete wavelet transform of voltage signals at the two ends of transmission lines have been analyzed. The transient energy of the detail information of level five is calculated for different fault conditions. It is observed that the variation of transient energy of healthy and faulted line can give important information which can be very useful in classifying and locating the fault. Keywords—Wavelet, Discrete wavelet transform, Multi resolution analysis, Transient energy
Simulation of the Aii amacrine cell of mammalian retina: Functional consequences of electrical coupling and regenerative membrane properties

Abstract The Aii amacrine cell of mammalian retina collects signals from several hundred rods and is hypothesized to transmit quantal “single-photon” signals at scotopic (starlight) intensities. One problem for this theory is that the quantal signal from one rod when summed with noise from neighboring rods would be lost if some mechanism did not exist for removing the noise. Several features of the Aii might together accomplish such a noise removal operation: The Aii is interconnected into a syncytial network by gap junctions, suggesting a noise-averaging function, and a quantal signal from one rod appears in five Aii cells due to anatomical divergence. Furthermore, the Aii contains voltage-gated Na+ and K+ channels and fires slow action potentials in vitro, suggesting that it could selectively amplify quantal photon signals embedded in uncorrelated noise. To test this hypothesis, we simulated a square array of AII somas (Rm = 25,000 Ohm-cm2) interconnected by gap junctions using a compartmental model. Simulated noisy inputs to the Aii produced noise (3.5 mV) uncorrelated between adjacent cells, and a gap junction conductance of 200 pS reduced the noise by a factor of 2.5, consistent with theory. Voltage-gated Na+ and K+ channels (Na+: 4 nS, K+: 0.4 nS) produced slow action potentials similar to those found in vitro in the presence of noise. For a narrow range of Na+ and coupling conductance, quantal photon events (-5–10 mV) were amplified nonlinearly by subthreshold regenerative events in the presence of noise. A lower coupling conductance produced spurious action potentials, and a greater conductance reduced amplification. Since the presence of noise in the weakly coupled circuit readily initiates action potentials that tend to spread throughout the AII network, we speculate that this tendency might be controlled in a negative feedback loop by up-modulating coupling or other synaptic conductances in response to spiking activity.
Locality enhanced spectral embedding and spatially smooth spectral regression for face recognition

This paper proposes two novel methods. First we propose Locality Enhanced Spectral Embedding(LESE) which can make a locality preserving mapping from the original nearest neighbor graph to the real line. It uses a regularized non-nearest penalty based on a non-nearest neighbor graph to enhance the locality of the mapping result. Second we make an efficient method for face recognition task. Previous methods consider a p1 × p2 image as a high dimensional vector in Rp1×p2 space and the pixels of each image are considered independent. It fails to consider that a face image is intrinsically a matrix, the pixels spatially close to each other may also be correlated. To explicitly model the spatial locality, we propose a novel Spatially Smooth Spectral Regression(SSR). It is a two stage framework for subspace learning, sequentially SSR uses the LESE to generate an eigenspace, and it solves a Laplacian smoothing penalty regularized regression to construct the projective function and learn a spatially smooth subspace. The subspace forms a good representation of the original face image. Experimental results on face recognition demonstrate the effectiveness of our proposed algorithm.
Engineering Blood and Lymphatic Microvascular Networks in Fibrin Matrices

Vascular network engineering is essential for nutrient delivery to tissue-engineered constructs and, consequently, their survival. In addition, the functionality of tissues also depends on tissue drainage and immune cell accessibility, which are the main functions of the lymphatic system. Engineering both the blood and lymphatic microvasculature would advance the survival and functionality of tissue-engineered constructs. The aim of this study was to isolate pure populations of lymphatic endothelial cells (LEC) and blood vascular endothelial cells (BEC) from human dermal microvascular endothelial cells and to study their network formation in our previously described coculture model with adipose-derived stromal cells (ASC) in fibrin scaffolds. We could follow the network development over a period of 4 weeks by fluorescently labeling the cells. We show that LEC and BEC form separate networks, which are morphologically distinguishable and sustainable over several weeks. In addition, lymphatic network development was dependent on vascular endothelial growth factor (VEGF)-C, resulting in denser networks with increasing VEGF-C concentration. Finally, we confirm the necessity of cell–cell contact between endothelial cells and ASC for the formation of both blood and lymphatic microvascular networks. This model represents a valuable platform for in vitro drug testing and for the future in vivo studies on lymphatic and blood microvascularization.
FRec: a novel framework of recommending users and communities in social media

In this paper, we propose a framework of recommending users and communities in social media. Given a user's profile, our framework is capable of recommending influential users and topic-cohesive interactive communities that are most relevant to the given user. In our framework, we present a generative topic model to discover user-oriented and community-oriented topics simultaneously, which enables us to capture the exact topic interests of users, as well as the focuses of communities. Extensive evaluation on a data set obtained from Twitter has demonstrated the effectiveness of our proposed framework compared with other probabilistic topic model based recommendation methods.
Acquisition of 3D surface temperature distribution of a car body

Thermal analysis using finite element modeling (FEM) is widely used in automotive industry nowadays. FEM can give simulation results at design stage. However, as FEM is a kind of simulations, it normally suffers from deviations with experimental results. Therefore, experimental measurement is necessary. To measure the 3D temperature distribution on a car body, we normally use a number of temperature sensors and then record the temperature values according to the positions of the sensors. It can provide the temperature values at different positions. Using this information, we can obtain the 3D temperature distribution on a car body. However, this method is time consuming and inconvenient, as we have to place a number of sensors on a car body, measure its corresponding positions as well as process the measured temperature values. In contrast, we firstly take a sequence of 2D thermal infrared images of the car body to have 2D temperature distribution and then reconstruct the 3D temperature distribution from the 2D images using computer vision method. It provides a more convenient method to acquire 3D temperature distribution compared to using a number of temperature sensors. The experimental results show the feasibility of our method.
Murine Cytomegalovirus Is Regulated by a Discrete Subset of Natural Killer Cells Reactive with Monoclonal Antibody to Ly49h

Antiviral roles of natural killer (NK) cell subsets were examined in C57BL/6 mice infected with murine cytomegalovirus (MCMV) and other viruses, including lymphocytic choriomeningitis virus (LCMV), vaccinia virus (VV), and mouse hepatitis virus (MHV). Each virus vigorously induced an NK cell infiltrate into the peritoneal cavity and liver, causing some redistributions of NK cell subsets defined by monoclonal antibody (mAb) directed against Ly49A, C/I, D, and G2. Striking results were seen with a mAb (1F8) reactive with the positively signaling molecule Ly49H, present in MCMV-resistant C57BL/6 mice. mAb 1F8 also stains Ly49 C and I, but exclusion of those reactivities with mAb 5E6, which recognizes Ly49 C and I, indicated that Ly49H+ cells infiltrated the peritoneal cavity and liver and were particularly effective at synthesizing interferon γ. Depletion of 1F8+ but not 5E6+ cells in vivo by mAb injections enhanced MCMV titers by 20-1,000-fold in the spleen and approximately fivefold in the liver. Titers of LCMV or VV were not enhanced. These anti-MCMV effects were attributed to prototypical NK1.1+CD3− NK cells and not to NK1.1+CD3+ “NK/T” cells. This is the first evidence that control of a virus infection in vivo is mediated by a distinct NK cell subset.
Influenza Virus Infection Induces Host Pyruvate Kinase M Which Interacts with Viral RNA-Dependent RNA Polymerase

Influenza virus RNA-dependent RNA polymerase (RdRp) is a heterotrimer of three viral proteins, PB1, PB2, and PA and is involved in both transcription and replication of the negative strand of the viral RNA (vRNA) genome. RdRp is multifunctional, possessing RNA polymerase, cap binding, and endonuclease activities. The enzyme synthesizes three different RNAs, complementary RNA (cRNA) and messenger RNA (mRNA) from vRNA, and vRNA from cRNA. To synthesize these three RNAs, RdRp requires conversion of its function by host factor. Here, we performed yeast two-hybrid screening to identify the relevant host factor, revealing that pyruvate kinase M2 (PKM2) interacted with the PA subunit of influenza virus RdRp. PKM2 is one of two enzymes (PKM1 and PKM2) produced by alternative splicing of the pyruvate kinase M (PKM) pre-mRNA. We determined the interacting regions in both PKM2 and PA, the expression level of PKM by western blotting at different time points after viral infection, and the effects of transfection of siRNA targeting PKM on influenza virus replication. The results demonstrated that the C-terminal region of PKM2 interacted with the C-terminus of the PA subunit, that the expression level of PKM2 increased with influenza virus infection time, and that this enzyme is essential for influenza virus multiplication. Moreover, isoelectric focusing of uninfected and influenza virus infected cell extracts, followed by gradient gel electrophoresis to separate the PKM1 and PKM2 isoforms and western blotting indicated that PKM2 became more acidic after influenza infection. The decreased pH of PKM2 may have been due to phosphorylation, and phosphorylated PKM2 is active as a pyruvate kinase and protein kinase; therefore, it is possible that PKM2 may transfer a phosphate group to PA and consequently transform the function of RdRp from transcriptase to replicase.
Shortfall Risk Minimisation vs . Symmetric ( Quadratic ) Hedging

The seller of a contingent claim H can always find a self-financing investment strategy that (super)hedges the claim H. When the seller wants to endow an initial capital x less than the one required to get perfect (super)hedging, the shortfall risk minimisation problem arises in a natural way. The aim is to find the strategy that minimises E{`([H(ST )−V x,φ T ])} (shortfall risk), where V x,φ t is the value at time t of the portfolio obtained according to the strategy φ and ` is a loss function (increasing on R+ and such that `(0) = 0) describing the attitude of investor towards taking risks. Another approach studied in the literature is that of quadratic hedging. Here, the investor wants to determine the initial capital x and the strategy φ to minimize E{(H(ST )− V x,φ T )}. This paper investigates a comparison between these two approaches. At first, the second problem is generalised to the case when an expression of the form E{`(H(ST )−V x,φ T )} is considered, with ` a suitable loss function: the resulting problem is called symmetric hedging problem. Then, we consider the case when the investor only wants to minimize the criterion w.r. t. the strategy φ, starting with a given initial capital x. This way, every triple (H, x, φ) defines two optimisation problems (shortfall risk minimization and symmetric hedging) which are compared.
My Partner’s Media Use: A Qualitative Study Exploring Perceptions of Problems with a Partner’s Media Use

ABSTRACT Media and technology use is widespread in American households, yet little is known about how it impacts romantic couples. The present study is an description of how romantic relationships were impacted by respondents’ perceptions of their partners’ media use. A sample of 98 respondents were asked to describe their frustration with their romantic partners’ media use. From the descriptions, four themes and five subthemes were identified, and these included the following conclusive themes that described an element of frustration: relationship impacts, appropriate media use, amount of media use, and distraction from the moment. Subthemes included media types, context of media use, value of media use, addiction, and virtual reality. Results showed mainly negative descriptions of media use with mentions of a few positive uses. The findings implicate further research on frustration over romantic partner’s media use.
Climbing stairs with EP-WAR2 biped robot

A second prototype of a biped walking robot, called EP-WAR2 (Electropneumatic WAlking Robot), has been designed and built at LARM (Laboratory of Robotics and Mechatronics) in Cassino. In addition to the performances of the previous prototype EP-WAR, EP-WAR2 is able to climb stairs because of a new actuation system. A suitable programming of the programmable logic controller has been based on several subroutines, which run different walking motions and specifically to climb stairs. Experimental tests prove the validity of the proposed low-cost design and programming technique.
Action selection based on localizability for active global localization of mobile robots

An actions selection mechanism for mobile robots is proposed to accelerate convergence of global localization without increasing computational complexity. In this mechanism, the localizability matrix of every pose is calculated off-line over the apriori probabilistic grid map, and during the phase of global localization with particle filtering, robot actions are selected actively according to maximization of localizability distinctness for all particles. Real robot and real world experiments are implemented for verifying the proposed approach. The experimental results show that the localizability matrix is able to represent the probability distribution of possible observations in the given map accurately, and the actions selection strategy improves the efficiency compared with standard global localization method.
Reciprocity and The Hyperlocal Journalist

Increased interest in hyperlocal news has led to growing evidence of its economic value, its ability to play traditional democratic roles associated with news, and its merits and deficiencies in comparison with the outputs of a declining established commercial news industry. Given many hyperlocal producers cite the desire to play a role in producing better communities, this paper breaks new ground in examining the social and cultural dimensions of hyperlocal journalism’s news-making, community-building, and place-making roles. We examine this emergent cultural form’s affinity with telling stories, and enabling conversations, about civic and political concerns, but also its affinity with, and celebration of, the banal everyday. Employing the novel theoretical concept of reciprocal journalism, we provide new evidence about the mutually reinforcing online, and offline, practices that underpin relationships between producers and the communities they inhabit and represent. Drawing on evidence from the most extensive multi-method study of UK hyperlocal news to date, it demonstrates the different kinds of direct and indirect reciprocal exchange practices common in community news, and shows how such work, often composed of journalistic and community-activist practices, can enable and foster relationships of sustained reciprocity which improve and strengthen both hyperlocal news and the communities it serves.