Miracle-dz/UniFAR-FTUs huggingface dataset:
The differences between latent topics in abstracts and citation contexts of citing papers

Although it is commonly expected that the citation context of a reference is likely to provide more detailed and direct information about the nature of a citation, few studies in the literature have specifically addressed the extent to which the information in different parts of a scientific publication differs. Do abstracts tend to use conceptually broader terms than sentences in a citation context in the body of a publication? In this article, we propose a method to analyze and compare latent topics in scientific publications, in particular, from abstracts of papers that cited a target reference and from sentences that cited the target reference. We conducted an experiment and applied topical modeling techniques to full‐text papers in eight biomedicine journals. Topics derived from the two sources are compared in terms of their similarities and broad‐narrow relationships defined based on information entropy. The results show that abstracts and citation contexts are characterized by distinct sets of topics with moderate overlaps. Furthermore, the results confirm that topics from abstracts of citing papers have broader terms than topics from citation contexts formed by citing sentences. The method and the findings could be used to enhance and extend the current methodologies for research evaluation and citation evaluation.
An improved DV-Hop localization algorithm in wireless sensor networks

Localization as a fundamental issue has a challenge in wireless sensor networks (WSNs). Many approaches have been proposed to solve the inaccurate node localization. Among range-free algorithms, DV-Hop (Distance Vector-hop) is a well-known localization algorithm that utilizes of hop-distance estimation to locate sensor nodes. This has lead positioning accuracy is limited. In this paper, an improved DV-HOP algorithm based on the hop-size correction and localization optimization is put forward. Firstly, based on difference of actual and estimated distance between reference nodes an effective hop-size is calculated for whole network; secondly, a correction value is added to the hops between unknown nodes and reference nodes while received signal strength indicator (RSSI) value is used to correct the distance of single hop. Finally, the Levenberg-Marquardt algorithm is applied to estimate an optimize position for each sensors. In evaluation step, various factors that affect the localization accuracy of the DV-Hop are investigated. Simulation results show that the proposed algorithm has been significantly improved compared to the basic DV-Hop and some existing improved algorithms.
Toward a Global Consensus on Outcome Measures for Clinical Trials in Tinnitus: Report From the First International Meeting of the COMiT Initiative, November 14, 2014, Amsterdam, The Netherlands

In Europe alone, over 70 million people experience tinnitus; for seven million people, it creates a debilitating condition. Despite its enormous socioeconomic relevance, progress in successfully treating the condition is somewhat limited. The European Union has approved funding to create a pan-European tinnitus research collaboration network (2014–2018). The goal of one working group is to establish an international standard for outcome measurements in clinical trials of tinnitus. Importantly, this would enhance tinnitus research by informing sample-size calculations, enabling meta-analyses, and facilitating the identification of tinnitus subtypes, ultimately leading to improved treatments. The first meeting followed a workshop on “Agreed Standards for Measurement: An International Perspective” with invited talks on clinimetrics and existing international initiatives to define core sets for outcome measurements in hearing loss (International classification of functioning, disability, and health core sets for hearing loss) and eczema (Harmonizing outcome measures for eczema). Both initiatives have taken an approach that clearly distinguishes the specification of what to measure from that of how to measure it. Meeting delegates agreed on taking a step-wise roadmap for which the first output would be a consensus on what outcome domains are essential for all trials. The working group seeks to embrace inclusivity and brings together clinicians, tinnitus researchers, experts on clinical research methodology, statisticians, and representatives of the health industry. People who experience tinnitus are another important participant group. This meeting report is a call to those stakeholders across the globe to actively participate in the initiative.
Privacy Preserving PageRank Algorithm By Using Secure Multi-Party Computation

In this work, we study the problem of privacy preserving computation on PageRank algorithm. The idea is to enforce the secure multi party computation of the algorithm iteratively using homomorphic encryption based on Paillier scheme. In the proposed PageRank computation, a user encrypt its own graph data using asymmetric encryption method, sends the data set into different parties in a privacy-preserving manner. Each party computes its own encrypted entity, but learns nothing about the data at other parties.
A comparison of two methods for building astronomical image mosaics on a grid

This paper compares two methods for running an application composed of a set of modules on a grid. The set of modules (collectively called Montage) generates large astronomical image mosaics by composing multiple small images. The workflow that describes a particular run of Montage can be expressed as a directed acyclic graph (DAG), or as a short sequence of parallel (MPI) and sequential programs. In the first case, Pegasus can be used to run the workflow. In the second case, a short shell script that calls each program can be run. In this paper, we discuss the Montage modules, the workflow run for a sample job, and the two methods of actually running the workflow. We examine the run time for each method and compare the portions that differ between the two methods.
On the capacity of relay-assisted wireless MIMO channels

We study the impact of multiple amplify-and-forward relays on the capacity of wireless MIMO channels. For wireless networks with one source/destination pair (equipped with multiple antennas) and several single-antenna amplify-and-forward relays we determine the compound (over two time slots) channel matrix of the relay-assisted MIMO channel. We derive the asymptotic eigenvalues of the compound channel matrix by letting the number of transmit and receive antennas go to infinity (large-array limit). Then the asymptotic ergodic capacity of the amplify-and-forward transmission scheme is determined for Rayleigh and Rice fading. The results serve as tight approximation for a finite number of transmit and receive antennas and are accurate in the large-array limit.
An OPS Hand Tracking Algorithm Based on Optical Flow

In this paper, a real-time technique for segmenting a hand, determining hand's locations is described. The algorithm consists of two steps; the first is to location the hand area in noise condition and segment the part of hand. Then seek for angles of the fingers and location of fingertip with a novel factor determination in special OPS (Optical Parameter Sequence). It keeps the advantages of optical flow and overcome the complex computation cost and recognizes the fingerspell correctly. According to the traditional technique, the algorithm has a good performance.
Are the Jets Accelerated from the Disk Coronas in Some Active Galactic Nuclei?

We use a sample of radio-loud active galactic nuclei (AGNs) with estimated central black hole masses to explore AGN jet-formation mechanisms. The jet power of AGNs is estimated from their extended radio luminosity. We find that the jets in several AGNs of this sample are too powerful to be extracted from the standard thin accretion disks or rapidly spinning black holes surrounded by standard thin disks. If advection-dominated accretion flows (ADAFs) are present in these AGNs, their bright optical continuum luminosity cannot be produced by pure ADAFs because of their low accretion rates and low radiation efficiency, unless the ADAFs transit to standard thin disks at some radii Rtr. If this is the case, we find that dimensionless accretion rates = /Edd as high as ≥0.05, and a transition from ADAFs to standard thin disks at rather small radii, ~20GMbh/c2, are required to explain their bright optical continuum emission. We propose that the disk-corona structure is present in at least some AGNs in this sample. The plasmas in the corona are very hot, and the pressure scale height of the corona Hc ~ R. Powerful jets with Qjet ~ Lbol (bolometric luminosity) can form via the large-scale magnetic fields created by dynamo processes in the disk corona of some AGNs. The maximal jet power extractable from the corona, Q ≤ 0.6Lc (Lc is the corona luminosity), is expected in this jet-formation scenario. The statistical results for the sample of AGNs are consistent with the predictions of this scenario. Finally, the possibility that the jet is driven from a super-Keplerian rotating hot layer located between the corona and the cold disk is discussed. We find that, in principle, this layer could also produce a powerful jet with Qjet ~ Lbol.
Towards image-based modeling for ambient sensing

The practical deployment of pervasive health monitoring requires a close integration of body sensor networks (BSNs) with intelligent ambient sensing. To this end, vision sensors with low cost and minimal power consumption provide an attractive means of activity tracking and capturing early signs of disease progression through changes in gait and posture. The purpose of this paper is to present an image-based modeling technique for generating a subject-specific simulation environment that allows systematic development of novel vision algorithms that can be implemented by low power video sensors with distributed processing and known ground-truth
Risk Factors for Upper Extremity Musculoskeletal Disorders Among Office Workers in Qom Province, Iran

Background The identification of the risk factors for musculoskeletal disorders (MSDs) is the first step in designing effective preventive interventions. Objectives To investigate the association between individual, organizational, physical, and psychological factors and upper extremity MSDs (i.e., shoulder, elbow and hand/wrist). Materials and Methods In this cross-sectional study, the study population was comprised of office workers from Qom Province, Iran. Of the 1630 Iranian office workers who were selected via a random multistage cluster sampling method, 1488 completed a comprehensive data collection form designed to investigate the individual, organizational, physical, and psychological factors related to MSDs (response rate: 91.3%). Results The predictors of shoulder MSDs in the past 12 months were uncomfortable sitting posture (β = 0.42, P = 0.04), limited rest breaks (β=0.73, P = 0.012), and no access to adjustable desks (β = 0.43, P = 0.018). Working on a computer for more than five hours (β = 0.61, P = 0.004) and an uncomfortable sitting posture (β = 0.79, P = 0.001) predicted hand/wrist symptoms. Conclusions Various risk factors in the workplace may contribute to MSDs in different upper extremities. Preventive interventions should hence include ergonomic and office equipment modifications.
A Causal Role for Brain-Derived Neurotrophic Factor in the Homeostatic Regulation of Sleep

Slow-wave activity (SWA), the EEG power between 0.5 and 4 Hz during non-rapid eye movement (NREM) sleep, is one of the best characterized markers of sleep need, because it increases as a function of preceding waking duration and decreases during sleep, but the underlying mechanisms remain unknown. We hypothesized that SWA is high at sleep onset because it reflects the occurrence, during the previous waking period, of widespread synaptic potentiation in cortical and subcortical areas. Consistent with this hypothesis, we recently showed that the more rats explore, the stronger is the cortical expression of BDNF during wakefulness, and the larger is the increase in SWA during the subsequent sleep period. There is compelling evidence that BDNF plays a causal role in synaptic potentiation, and exogenous application of BDNF in vivo is sufficient to induce long-term increases in synaptic strength. We therefore performed cortical unilateral microinjections of BDNF in awake rats and measured SWA during the subsequent sleep period. SWA during NREM sleep was higher in the injected hemisphere relative to the contralateral one. The effect was reversible within 2 h, and did not occur during wakefulness or rapid eye movement sleep. Asymmetries in NREM SWA did not occur after vehicle injections. Furthermore, microinjections, during wakefulness, of a polyclonal anti-BDNF antibody or K252a, an inhibitor of BDNF TrkB receptors, led to a local SWA decrease during the following sleep period. These effects were also reversible and specific for NREM sleep. These results show a causal link between BDNF expression during wakefulness and subsequent sleep regulation.
Exploiting user feedback for online filtering in event-based systems

Modern large-scale internet applications, like the ubiquitous social networks, represent today a fundamental source of information for millions of users. The larger is the user base, the more difficult it is to control the quality of data that is spread from producers to consumers. This can easily hamper the usability of such systems as the amount of low quality data received by consumers grows uncontrolled. In this paper we propose a novel solution to automatically filter new data injected in event-based systems with the aim of delivering to consumers only content they are actually interested in. Filtering is executed at run-time by first profiling both producers and consumers, and then matching their profiles as new data is produced.
Chromatin assembly in yeast cell-free extracts.

A simple method for preparing chromatin assembly extracts has not been available for budding yeast. Here I describe such a method in detail. The assembly extract, a crude 100,000g supernatant, is prepared from cells disrupted in a manual or motorized grinder while they are frozen. The core histones and all soluble protein factors required for chromatin assembly under physiological conditions are present in the extract. Assembly is sensitive to mutation of lysine residues in the amino-terminal tail of histone H4 whose acetylation is associated with nucleosome deposition in vivo. The reaction is ATP dependent, and assembly-driven DNA supercoiling occurs with the same efficiency as in extracts from mammalian somatic cells. This simple system offers a unique opportunity to analyze chromatin metabolism by a combined biochemical and genetic approach that is not feasible for any other model organism.
Share more, drive less: Millennials value perception and behavioral intent in using collaborative consumption services

This paper aims to investigate how the cognitive value perceptions and affective attitudes of Millennial consumers are related to behavioral intent in the context of collaborative consumption and how such relationships may be moderated. ,Two scenario-based online studies were conducted with young consumers concerning several collaborative consumption services. ,Using structural equation modeling, the authors found that specific dimensions of value perceptions (utilitarian, hedonic and symbolic) have differing effects on young consumers’ attitude and empathy toward collaborative consumption services. The analysis shows no moderating effects for perceived consumer effectiveness (Study 1 and Study 2) but a significant moderating effect for consumer innovativeness (Study 2). ,This research identifies important factors for the attitudinal and behavioral outcome of young consumers, an important consumer group for the emerging trend of collaborative consumption. Also, the role of empathy and two personal traits offer insights. ,Substantively, the findings guide marketers in the sharing economy in elevating their strategic tactics and effective approaches to reach this important consumer group. ,Given the paucity of research on consumer groups in this context, the current research breaks new ground by investigating value perceptions and empathy as drivers of positive reactions and moderating factors within the collaborative economy.
Testing Aspect-Oriented Programs with UML Design Models

The new constructs in aspect-oriented programming bring new types of programming faults with respect to crosscutting concerns, such as incorrect pointcuts and advice. This paper presents a UML-based approach to testing whether or not an aspect-oriented program conforms to its expected crosscutting behavior. We explore aspect-oriented UML design models to derive tests for exercising interactions between aspects and classes. Each aspect-oriented model consists of class diagrams, aspect diagrams, and sequence diagrams. For a method under test, we weave the sequence diagrams of the advice on the method into the method's sequence diagram. Based on the woven sequence diagram and class/aspect diagrams, we then generate an AOF (Aspect-Object Flow) tree by applying coverage criteria such as condition coverage, polymorphic coverage, and loop coverage to woven sequence diagrams. In the AOF tree, each path from the root to a leaf is an abstract message sequence, indicating a template of test cases. A concrete test case is obtained by creating objects that satisfy the collective constraints in the template. Our empirical study shows that the model-based testing approach is capable of revealing several types of aspect-specific faults, including incorrect advice type, incorrect (weaker or stronger) pointcut strengths, and incorrect aspect precedence.
Adaptive shared tree multicast in mobile wireless networks

Shared tree multicast is a well established concept used in several multicast protocols for wireline networks (e.g. core base tree, PIM sparse mode etc). In this paper, we extend the shared tree concept to wireless, mobile, multihop networks for applications ranging from ad hoc networking to disaster recovery and battlefield. The main challenge in wireless, mobile networks is the rapidly changing environment. We address this issue in our design by: (a) using "soft state"; (b) assigning different roles to nodes depending on their mobility (two level mobility model); (c) proposing an adaptive scheme which combines shared tree and source tree benefits. A detailed wireless simulation model is used to evaluate the proposed schemes and compare them with source based tree (as opposed to shared tree) multicast. The results show that shared tree protocols have low overhead and are very robust to mobility.
Mean curvature flow with obstacles: existence, uniqueness and regularity of solutions

We show short time existence and uniqueness of $\C^{1,1}$ solutions to the mean curvature flow with obstacles, when the obstacles are of class $\C^{1,1}$. If the initial interface is a periodic graph we show long time existence of the evolution and convergence to a minimal constrained hypersurface.
Learning for User Adaptive Systems: Likely Pitfalls and Daring Rescue

Adaptive user interfaces adapt themselves to the user by reasoning about the user and refining their internal model of the user’s needs. In machine learning, artificial systems learn how to perform better through experience. By observing examples from a sample, the learning algorithm tries to induce a hypothesis which approximates the target function. It seems obvious, that machine learning exactly offers what is desperately needed in intelligent adaptive behavior. But when trying to adapt by learning, one will sooner or later encounter one or more well–known problems, some of which have been discussed in [Webb et al., 2001]. We propose a framework for describing user modeling problems, identify several reasons for inherent noise and discuss few promising approaches which tackle these problems.
Social norms and optimal incentives in firms

This paper deals with the interplay between economic incen- tives and social norms inrms. We outline a simple model of team production and provide preliminary results on linear incentive schemes in the presence of a social norm that may cause multiple equilibria. The e®ect of the social norm on the optimal bonus rate is discussed, as well as the e®ectiveness of temporary changes in the bonus rate as a means to move arm from a bad to a good equilibrium.
To Watch or Not to Watch: Video Summarization with Explicit Duplicate Elimination

Video summarization is the process in which we extract key frames to form a storyboard representing the content of a video sequence. When asked to select images representing a video sequence, users attempt to find images related to the subject of the video. For the computer, such semantic analysis is a very hard problem. Still, it is possible to objectively identify the individual scenes from a sequence to extract a single key frame summarizing each scene. We propose a recursive method that broadly identifies shots in the sequence and cluster them in possible scenes via global image features. Shot boundary are usually blurry and faded and are removed along with the neighboring frames from the summary construction. A key frame is selected to represent each cluster before recursively analyzing its content. The key frames included in the hierarchical representation are analyzed for redundancy using local SURF features \cite{surf}. Key points enable the recognition of similar scene elements in the key frames, efficiently eliminating redundant information. The whole method is interactive: the user select the number of key frames to extract and the recursion depths to explore. The flexibility gained from the hierarchical representation allows the user to explore the key frames with a variable level of detail in an intuitive manner.
Efficiently Combining Contour and Texture Cues for Object Recognition

This paper proposes an efficient fusion of contour and texture cues for image categorization and object detection. Our work confirms and strengthens recent results that combining complementary feature types improves performance. We obtain a similar improvement in accuracy and additionally an improvement in efficiency. We use a boosting algorithm to learn models that use contour and texture features. Our main contributions are (i) the use of dense generic texture features to complement contour fragments, and (ii) a simple feature selection mechanism that includes the computational costs of features in order to learn a run-time efficient model. Our evaluation on 17 challenging and varied object classes confirms that the synergy of the two feature types performs significantly better than either alone, and that computational efficiency is substantially improved using our feature selection mechanism. An investigation of the boosted features shows a fascinating emergent property: the absence of certain textures often contributes towards object detection. Comparison with recent work shows that performance is state of the art.