Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic query wefinement using lexical affinities with maximal information gain

This work describes an automatic query refinement technique, which focuses on improving precision of the top ranked documents. The terms used for refinement are lexical affinities (LAs), pairs of closely related words which contain exactly one of the original query terms. Adding these terms to the query is equivalent to re-ranking search results, thus, precision is improved while recall is preserved. We describe a novel method that selects the most "informative" LAs for refinement, namely, those LAs that best separate relevant documents from irrelevant documents in the set of results. The information gain of candidate LAs is determined using unsupervised estimation that is based on the scoring function of the search engine. This method is thus fully automatic and its quality depends on the quality of the scoring function. Experiments we conducted with TREC data clearly show a significant improvement in the precision of the top ranked documents.
The Lived Experience of Companion-animal Loss: A Systematic Review of Qualitative Studies

Abstract The aim of this systematic review was to evaluate qualitative studies of the lived experience of companion-animal loss and grief. Six electronic databases (PsycINFO, CINAHL Plus, Ovid MEDLINE, ProQuest, Scopus, and Web of Science) were searched for English language, peer-reviewed articles from 1970 to July 2015. Only primary empirical studies using a qualitative method with textual data describing a direct ongoing relationship with, and subsequent loss of, a companion animal were included. A narrative synthesis was conducted on 11 eligible studies using inductive open coding techniques. Analysis revealed that pets were often labeled as family, and strong emotional connections between animals and humans were reported in some studies, whereas in other studies findings were inconsistent. Loss experience was predominantly with prototypical animals (cats, dogs); two studies involved other animals (horse, fish). Grief was described in five studies, with participants’ experience ranging from low to overwhelming. Prolonged grief was associated with self-disenfranchisement, whereas subjective healing was associated with remembrance, in which the animal remained as a memory in a “new” normal. Clinical implications are discussed.
A New Scheme of Neural Network and DCT-Domain Based Digital Watermarking

Digital Watermarking is one of the data hiding technique, has been popular in today multimedia era to prevent and control copyright protection. In this paper, a new blind scheme of digital watermarking is proposed by combining block based DCT domain approach and Neural Network. DCT domain based is used in watermark embedding to achieve better imperceptibility and Neural Network is applied in watermark extraction to improve watermark retrieval performance and achieve more robustness. By combining DCT transform based and Neural Network, the proposed scheme is intended to improve digital watermarking performance. Experimental results will be show and proof the better performances on different images and more robustness against on various attacks. Keywords—Digital watermarking, Discrete Cosine Transform (DCT) domain, Neural Network.
Energy-Efficient GPS-Based Positioning in the Android Operating System

We present our ongoing collaborative work on EnDroid, an energy-efficient GPS-based positioning system for the Android Operating System. EnDroid is based on the EnTracked positioning system, developed at the University of Aarhus, Denmark. We describe the current prototypical state of our implementation and present our experiences and conclusions from preliminarily evaluating EnDroid on the Google Nexus One Smartphone. Although the preliminary results seem to support the approach, there are still several open questions, both at the application interface, as well as at the hardware management level.
DEKANT: a static analysis tool that learns to detect web application vulnerabilities

The state of web security remains troubling as web applications continue to be favorite targets of hackers. Static analysis tools are important mechanisms for programmers to deal with this problem as they search for vulnerabilities automatically in the application source code, allowing programmers to remove them. However, developing these tools requires explicitly coding knowledge about how to discover each kind of vulnerability. This paper presents a new approach in which static analysis tools learn to detect vulnerabilities automatically using machine learning. The approach uses a sequence model to learn to characterize vulnerabilities based on a set of annotated source code slices. This model takes into consideration the order in which the code elements appear and are executed in the slices. The model created can then be used as a static analysis tool to discover and identify vulnerabilities in source code. The approach was implemented in the DEKANT tool and evaluated experimentally with a set of open source PHP applications and WordPress plugins, finding 16 zero-day vulnerabilities.
Effects of screening on the Hofstadter butterfly.

We study, within the Hartree approximation, the effects of the electron-electron interaction on the energy spectrum of a two-dimensional electron gas in a perpendicular homogeneous magnetic field and a lateral superlattice potential with square symmetry. Due to the strong screening effects, the bandwidth of the Landau bands oscillates strongly with their filling. For short enough periods and strong enough modulation of the superlattice potential, the miniband structure of the Landau bands can be resolved in the thermodynamic density of states.
QoE Prediction for Enriched Assessment of Individual Video Viewing Experience

Most automatic Quality of Experience (QoE) assessment models have so far aimed at predicting the QoE of a video as experienced by an average user, and solely based on perceptual characteristics of the video being viewed. The importance of other characteristics, such as those related to the video content being watched, or those related to an individual user have been largely neglected. This is suboptimal in view of the fact that video viewing experience is individual and multifaceted, considering the perceived quality (related to coding or network-induced artifacts), but also other -- more hedonic - aspects, like enjoyment. In this paper, we propose an expanded model which aims to assess QoE of a given video, not only in terms of perceived quality but also of enjoyment, as experienced by a specific user. To do so, we feed the model not only with information extracted from the video (related to both perceived quality and content), but also with individual user characteristics, such as interest, personality and gender. We assess our expanded QoE model based on two publicly available QoE datasets, namely i_QoE and CP-QAE-I. The results show that combining various types of characteristics enables better QoE prediction performance as compared to only considering perceptual characteristics of the video, both when targeting perceived quality and enjoyment.
The putative P-gp inhibitor telmisartan does not affect the transcellular permeability and cellular uptake of the calcium channel antagonist verapamil in the P-glycoprotein expressing cell line MDCK II MDR1

Verapamil is used in high doses for the treatment of cluster headache. Verapamil has been described as a P‐glycoprotein (P‐gp, ABCB1) substrate. We wished to evaluate in vitro whether co administration of a P‐gp inhibitor with verapamil could be a feasible strategy for increasing CNS uptake of verapamil. Fluxes of radiolabelled verapamil across MDCK II MDR1 monolayers were measured in the absence and presence of the putative P‐gp inhibitor telmisartan (a clinically approved drug compound). Verapamil displayed a vectorial basolateral‐to‐apical transepithelial efflux across the MDCK II MDR1 monolayers with a permeability of 5.7 × 10−5 cm sec−1 compared to an apical to basolateral permeability of 1.3 × 10−5 cm sec‐1. The efflux could be inhibited with the P‐gp inhibitor zosuquidar. Zosuquidar (0.4 μmol/L) reduced the efflux ratio (PB‐A/PA‐B) for verapamil 4.6–1.6. The presence of telmisartan, however, only caused a slight reduction in P‐gp‐mediated verapamil transport to an efflux ratio of 3.4. Overall, the results of the present in vitro approach indicate, that clinical use of telmisartan as a P‐gp inhibitor may not be an effective strategy for increasing brain uptake of verapamil by co‐administration with telmisartan.
Predictions for Cosmological Infrared Surveys from Space with the Multiband Imaging Photometer for SIRTF

We make predictions for the cosmological surveys to be conducted by the Multiband Imaging Photometer for SIRTF (MIPS) at 24, 70, and 160 μm for the Guaranteed Time Observer and the Legacy programs, using the latest knowledge of the instrument. In addition to the detector noise and the cirrus confusion noise, we discuss in detail the derivation of the confusion noise due to extragalactic sources, which depends strongly on the shape of the source counts at a given wavelength and on the telescope and detector pixel sizes. We show that it is wise in general to compare the classical photometric criterion, used for decades, and the so-called source density criterion to predict the confusion levels. We obtain, using the model of Lagache, Dole, and Puget, limiting fluxes of 50 μJy, 3.2 mJy, and 36 mJy at 24, 70, and 160 μm, respectively. After taking into account other known sources of noise that will limit the surveys' sensitivities, we compute the redshift distributions of the detected sources at each wavelength and show that they extend up to z ~ 2.7 at 24 μm and up to z ~ 2.5 at 70 and 160 μm, leading to the resolution of at most 69%, 54%, and 24% of the cosmic infrared background (CIB) at 24, 70, and 160 μm, respectively. We estimate which galaxy populations will be used to derive the luminosity function evolution with redshift. We also give the redshift distributions of the unresolved sources in the far-IR range, which dominates the fluctuations of the CIB, and a predicted power spectrum showing the feasibility of fluctuations (due to both Poissonian and clustered source distributions) measurements. The main conclusion is that MIPS (and SIRTF in general) cosmological surveys will greatly improve our understanding of galaxy evolution by giving data with unprecedented accuracy in the mid-IR and far-IR range.
Vulnerabilities of ad hoc network routing protocols to MAC misbehavior

In a mobile ad hoc network (MANET), adversaries could compromise network functionality by attacking the physical layer, the MAC layer, or the network layer. Significant research efforts have been made towards increasing the survivability of MANET either by developing secure routing algorithms or by improving the robustness of MAC layer protocol in the presence of selfish or compromised nodes. In addition, some recent studies have focused on quantifying the resiliency of MANET against MAC layer misbehaviors; however little work has been done on quantifying the impact of these misbehaviors on the performance of ad hoc routing protocols. In this paper, we review some of MANET link layer vulnerabilities, we study their impacts on network layer performance and compare the performance of two prominent on-demand routing protocols (AODV and DSR). We show that simple attacks on the link layer could propagate to the upper network layer and disrupt the routing mechanism, therefore causing devastating effects on the overall network performance. Although several secure ad hoc routing protocols have been proposed, none of them are resilient to MAC misbehaviors.
Web Person Name Disambiguation by Relevance Weighting of Extended Feature Sets

This paper describes our approach to the Person Name Disambiguation clustering task in the Third Web People Search Evaluation Campaign(WePS3). The method focuses on two aspects: the extended feature sets, and feature relevance weighting. Bag-of-words and named entities are most commonly used features in many existing web entity disambiguation algorithms and we further extend this basic feature set with Wikipedia concepts. Then two feature weighting models are employed. One is the feature relevance to the target person name(or “query name”), and the other is the feature relevance to the text content. Similarity score is calculated according to the feature weights for clustering documents of the same person. Experiments show that the system based on our approach has generated the best results among all the WePS-3’s submissions.
OUTBREEDING DEPRESSION, BUT NO INBREEDING DEPRESSION IN HAPLODIPLOID AMBROSIA BEETLES WITH REGULAR SIBLING MATING

Abstract In sexual reproduction the genetic similarity or dissimilarity between mates strongly affects offspring fitness. When mating partners are too closely related, increased homozygosity generally causes inbreeding depression, whereas crossing between too distantly related individuals may disrupt local adaptations or coadaptations within the genome and result in outbreeding depression. The optimal degree of inbreeding or outbreeding depends on population structure. A long history of inbreeding is expected to reduce inbreeding depression due to purging of deleterious alleles, and to promote outbreeding depression because of increased genetic variation between lineages. Ambrosia beetles (Xyleborini) are bark beetles with haplodiploid sex determination, strong local mate competition due to regular sibling mating within the natal chamber, and heavily biased sex ratios. We experimentally mated females of Xylosandrus germanus to brothers and unrelated males and measured offspring fitness. Inbred matings did not produce offspring with reduced fitness in any of the examined life-history traits. In contrast, outcrossed offspring suffered from reduced hatching rates. Reduction in inbreeding depression is usually attributed to purging of deleterious alleles, and the absence of inbreeding depression in X. germanus may represent the highest degree of purging of all examined species so far. Outbreeding depression within the same population has previously only been reported from plants. The causes and consequences of our findings are discussed with respect to mating strategies, sex ratios, and speciation in this unusual system.
Human capital: Migration and rural population change

The movement of labor out of agriculture is a universal concomitant of economic modernization and growth. Traditional migration models overlook many potential interactions between migration and development. Given imperfect markets characterizing most migrant-sending areas, migration and remittances can have far-reaching impacts, both positive and negative, on incomes and production in agricultural households. Linkages through product and factor markets transmit impacts of migration from migrant-sending households to others inside and outside the rural economy. Recent theoretical and empirical studies reveal the complexity of migration determinants and impacts in rural economies, and they point to new arenas for policy intervention.
Source Traffic Modeling of Wireless Applications

Summary Data applications are expected to play an increasingly important role in the next generation mobile communication services. To plan these networks, detailed models of data users with diverse applications are required. The purpose of this study is to provide practically usable traffic models for data users in wireless networks, e.g. GPRS. We start with a discussion of well-known models in the literature, where the focus is on their applicability in mobile networks. A practical model of mobile HTTP users, based on an extrapolation of WWW users in current wire-line networks, is presented; this model is expected to be accurate enough to be used in simulation studies for network planning purposes. Finally, models for other emerging data applications are also taken into account.
Adaptive scale fixing for multiscale texture segmentation

This paper addresses two challenging issues in unsupervised multiscale texture segmentation: determining adequate spatial and feature resolutions for different regions of the image, and utilizing information across different scales/resolutions. The center of a homogeneous texture is analyzed using coarse spatial resolution, and its border is detected using fine spatial resolution so as to locate the boundary accurately. The extraction of texture features is achieved via a multiresolution pyramid. The feature values are integrated across scales/resolutions adaptively. The number of textures is determined automatically using the variance ratio criterion. Experimental results on synthetic and real images demonstrate the improvement in performance of the proposed multiscale scheme over single scale approaches.
Just-in-time Adaptive Classifiers in Non-Stationary Conditions

In real world applications ageing effects, process drifts, soft and hard faults may affect the data generation mechanism and, as a consequence, data coming from it. Intelligent measurement systems developed for such processes (e.g., industrial quality assessment and control, environmental monitoring) require adaptive techniques which, by tracking the system evolution, allow the intelligent system for keeping acceptable performance. Here we focus on adaptive classifiers embedded in intelligent measurement systems designed to cope with non-stationary environments, yet well performing in stationary conditions. The novelty of the approach resides in the possibility to update in a just-in-time fashion, i.e., only when it is really needed, the knowledge base of the classifier. A large experimental campaign shows the effectiveness of the proposed design.
Projected Crop Production under Regional Climate Change Using Scenario Data and Modeling: Sensitivity to Chosen Sowing Date and Cultivar

A sensitivity analysis of the responses of crops to the chosen production adaptation options under regional climate change was conducted in this study. Projections of winter wheat production for different sowing dates and cultivars were estimated for a major economic and agricultural province of China from 2021 to 2080 using the World Food Study model (WOFOST) under representative concentration pathways (RCPs) scenarios. A modeling chain was established and a correction method was proposed to reduce the bias of the resulting model-simulated climate data. The results indicated that adjusting the sowing dates and cultivars could mitigate the influences of climate change on winter wheat production in Jinagsu. The yield gains were projected from the chosen sowing date and cultivar. The following actions are recommended to ensure high and stable yields under future climate changes: (i) advance the latest sowing date in some areas of northern Jiangsu; and (ii) use heat-tolerant or heat-tolerant and drought-resistant varieties in most areas of Jiangsu rather than the currently used cultivar. Fewer of the common negative effects of using a single climate model occurred when using the sensitivity analysis because our bias correction method was effective for scenario data and because the WOFOST performed well for Jiangsu after calibration.
Limitations of short range Mexican hat connection for driving target selection in a 2D neural field: activity suppression and deviation from input stimuli

Dynamic Neural Field models (DNF) often use a kernel of connection with short range excitation and long range inhibition. This organization has been suggested as a model for brain structures or for artificial systems involved in winner-take-all processes such as saliency localization, perceptual decision or target/action selection. A good example of such a DNF is the superior colliculus (SC), a key structure for eye movements. Recent results suggest that the superficial layers of the SC (SCs) exhibit relatively short range inhibition with a longer time constant than excitation. The aim of the present study was to further examine the properties of a DNF with such an inhibition pattern in the context of target selection. First we tested the effects of stimulus size and shape on when and where self-maintained clusters of firing neurons appeared, using three variants of the model. In each model variant, small stimuli led to rapid formation of a spiking cluster, a range of medium sizes led to the suppression of any activity on the network and hence to no target selection, while larger sizes led to delayed selection of multiple loci. Second, we tested the model with two stimuli separated by a varying distance. Again single, none, or multiple spiking clusters could occur, depending on distance and relative stimulus strength. For short distances, activity attracted toward the strongest stimulus, reminiscent of well-known behavioral data for saccadic eye movements, while for larger distances repulsion away from the second stimulus occurred. All these properties predicted by the model suggest that the SCs, or any other neural structure thought to implement a short range MH, is an imperfect winner-take-all system. Although, those properties call for systematic testing, the discussion gathers neurophysiological and behavioral data suggesting that such properties are indeed present in target selection for saccadic eye movements.
Sentiment Classification Approaches – A Review

With the outbreak of web 2.0, several types of social media such as blogs, discussion forums, review websites and community websites that can be useful for determine the public; sentiment and opinion, towards products and services. Recent surveys impart that online reviews have greater economic impact compared to claric media. The major task of opinion mining or sentiment analysis is used to find the subjective information from the user defined opinions. The expressed opinions may be positive, negative or neutral. Machine learning techniques are widely used for sentiment classification. In this paper, we look insight into the various machine learning techniques for sentiment classification and research challenges exist in this field.
Engagement and Disaffection in the Classroom: Part of a Larger Motivational Dynamic?

A study of 805 4th through 7th graders used a model of motivational development to guide the investigation of the internal dynamics of 4 indicators of behavioral and emotional engagement and disaffection and the facilitative effects of teacher support and 3 student self-perceptions (competence, autonomy, and relatedness) on changes in these indicators over the school year. In terms of internal dynamics, emotional components of engagement contributed significantly to changes in their behavioral counterparts; feedback from behavior to changes in emotion were not as consistent. Teacher support and students' self-perceptions (especially autonomy) contributed to changes in behavioral components: Each predicted increases in engagement and decreases in disaffection. Tests of process models revealed that the effects of teacher context were mediated by children's self-perceptions. Taken together, these findings suggest a clear distinction between indicators and facilitators of engagement and begin to articulate the dynamics between emotion and behavior that take place inside engagement and the motivational dynamics that take place outside of engagement, involving the social context, self-systems, and engagement itself.
Internally generated 21.6-GHz millimeter wave based on brillouin fiber laser

An all-optically generated millimeter wave carrier at 21.67 GHz is experimentally achieved. This frequency is realized when two consecutively generated laser wavelength are heterodyned on the 60 GHz high-speed photodiode. The mixing between the Brillouin pump and the second-order Stokes wavelengths is spaced by 1.7 nm. This spacing, which is doubled from inherently generated Stokes shift, is accomplished through the isolated circulation of the first order Stokes wave in the double Brillouin Stokes shifter built with 25-km single mode fiber. The generated millimeter carrier is measured at 21.68 GHz, and its carrier phase noise and threshold power are −58.67 dBc/Hz and 19 mw of Brillouin pump power respectively.