nils-herrmann/clean_scirepeval huggingface dataset:
Self-Presentation and Deception Looks and Lies : The Role of Physical Attractiveness in Online Dating

This study examines the role of online daters’ physical attractiveness in their profile selfpresentation and, in particular, their use of deception. Sixty-nine online daters identified the deceptions in their online dating profiles and had their photograph taken in the lab. Independent judges rated the online daters’ physical attractiveness. Results show that the lower online daters’ attractiveness, the more likely they were to enhance their profile photographs and lie about their physical descriptors (height, weight, age). The association between attractiveness and deception did not extend to profile elements unrelated to their physical appearance (e.g., income, occupation), suggesting that their deceptions were limited and strategic. Results are discussed in terms of (a) evolutionary theories about the importance of physical attractiveness in the dating realm and (b) the technological affordances that allow online daters to engage in selective self-presentation.
A Comparative Study for Selecting the Best Unsupervised Learning Algorithm in E-Learning System

Clustering is one of the most important techniques of data mining. Clustering technique in data mining is an unsupervised machine learning algorithm that finds the groups of object such that objects in one group will be similar to one another and are dissimilar to the objects belonging to other clusters. Clustering is called unsupervised machine learning algorithm as groups are not predefined but defined by the data. So the most similar data are grouped into the clusters. In this paper, we compare five clustering algorithm namely Farthest first, MakeDensityBasedClusterer, Simple K-means, EM, Hierarchical clustering algorithm for recommending the course to the student based on student course selection & present the result. According to our simulation, we find that Simple K-means works better than other algorithms.
Correction to Construction of Panoramic Image Mosaics with Global and Local Alignment

An important element of this framework, which we exploit, is to perform the motion estimation between the current new input image and a warped (resampled) version of the mosaic. This allows us to estimate only incremental deformations of images (or equivalently, instantaneous motion), which greatly simplifies the computation of the gradients and Hessians required in our gradient descent algorithm (e.g., compare the Hessians computed below with those presented in Szeliski, 1996). Thus, to register two images I0(x) and I1(x′), where x′ is computed using some parametric motion model m, i.e., x′ = f(x; m), we first compute the warped image
Statistical Models for Frame-Semantic Parsing

We present a brief history and overview of statistical methods in frame-semantic parsing – the automatic analysis of text using the theory of frame semantics. We discuss how the FrameNet lexicon and frameannotated datasets have been used by statistical NLP researchers to build usable, state-of-the-art systems. We also focus on future directions in frame-semantic parsing research, and discuss NLP applications that could benefit from this line of work. 1 Frame-Semantic Parsing Frame-semantic parsing has been considered as the task of automatically finding semantically salient targets in text, disambiguating their semantic frame representing an event and scenario in discourse, and annotating arguments consisting of words or phrases in text with various frame elements (or roles). The FrameNet lexicon (Baker et al., 1998), an ontology inspired by the theory of frame semantics (Fillmore, 1982), serves as a repository of semantic frames and their roles. Figure 1 depicts a sentence with three evoked frames for the targets “million”, “created” and “pushed” with FrameNet frames and roles. Automatic analysis of text using framesemantic structures can be traced back to the pioneering work of Gildea and Jurafsky (2002). Although their experimental setup relied on a primitive version of FrameNet and only made use of “exemplars” or example usages of semantic frames (containing one target per sentence) as opposed to a “corpus” of sentences, it resulted in a flurry of work in the area of automatic semantic role labeling (Màrquez et al., 2008). However, the focus of semantic role labeling (SRL) research has mostly been on PropBank (Palmer et al., 2005) conventions, where verbal targets could evoke a “sense” frame, which is not shared across targets, making the frame disambiguation setup different from the representation in . Furthermore, it is fair to say that early research on PropBank focused primarily on argument structure prediction, and the interaction between frame and argument structure analysis has mostly been unaddressed (Màrquez et al., 2008). There are exceptions, where the verb frame has been taken into account during SRL (Meza-Ruiz and Riedel, 2009; Watanabe et al., 2010). Moreoever, the CoNLL 2008 and 2009 shared tasks also include the verb and noun frame identification task in their evaluations, although the overall goal was to predict semantic dependencies based on PropBank, and not full argument spans (Surdeanu et al., 2008;
On the Role and the Importance of Features for Background Modeling and Foreground Detection

Background modeling has emerged as a popular foreground det ection technique for various applications in video surveillance. Back ground modeling methods have become increasing efficient in robustly modeling the ba ckground and hence detecting moving objects in any visual scene. Although severa l background subtraction and foreground detection have been proposed recently, no tr aditional algorithm today still seem to be able to simultaneously address all the key ch allenges of illumination variation, dynamic camera motion, cluttered background an d occlusion. This limitation can be attributed to the lack of systematic investigati on concerning the role and importance of features within background modeling and fore ground detection. With the availability of a rather large set of invariant features , the challenge is in determining the best combination of features that would improve accu racy and robustness in T. Bouwmans Lab. MIA, Univ. La Rochelle, France Tel.: +05.46.45.72.02 E-mail: tbouwman@univ-lr.fr C. Silva Lab. MIA, Univ. La Rochelle, France E-mail: lolyne.pacheco@gmail.com C. Marghes Movidius E-mail: cristina.marghes@gmail.com M. Zitouni Visual Signal Analysis and Processing (VSAP) Research Cent er Department of Electrical and Computer Engineering, Khalif a University, U.A.E E-mail: mohammad.zitouni@kustar.ac.ae H. Bhaskar Visual Signal Analysis and Processing (VSAP) Research Cent er Department of Electrical and Computer Engineering, Khalif a University, U.A.E E-mail: harish.bhaskar@kustar.ac.ae C. Frelicot Lab. MIA, Univ. La Rochelle, France E-mail: cfrelicot@univ-lr.fr 2 Thierry Bouwmans et al. detection. The purpose of this study is to initiate a rigorou s and comprehensive survey of features used within background modeling and foregro und detection. Further, this paper presents a systematic experimental and statisti c l analysis of techniques that provide valuable insight on the trends in background mo eling and use it to draw meaningful recommendations for practitioners. In this pap er, a preliminary review of the key characteristics of features based on the types and si zes i provided in addition to investigating their intrinsic spectral, spatial and tem poral properties. Furthermore, improvements using statistical and fuzzy tools are examine d and techniques based on multiple features are benchmarked against reliability a nd selection criterion. Finally, a description of the different resources available s uch as datasets and codes is provided.
Stochastic Gradient Descent on Riemannian Manifolds

Stochastic gradient descent is a simple approach to find the local minima of a cost function whose evaluations are corrupted by noise. In this paper, we develop a procedure extending stochastic gradient descent algorithms to the case where the function is defined on a Riemannian manifold. We prove that, as in the Euclidian case, the gradient descent algorithm converges to a critical point of the cost function. The algorithm has numerous potential applications, and is illustrated here by four examples. In particular a novel gossip algorithm on the set of covariance matrices is derived and tested numerically.
The Combination of Trypan Blue and Brilliant Blue G-Assisted Vitrectomy for Macular Pucker: Histopathological Findings.

To report on the combined use of trypan blue (TB) and brilliant blue G (BBG) for staining the epiretinal membrane (ERM) and internal limiting membrane (ILM) during vitrectomy and to describe the histopathological findings.



10 surgical specimens were removed from 10 eyes with macular pucker during vitrectomy using a commercially available combination of TB and BBG for ERM and ILM staining and peeling. Specimens were evaluated using light and transmission electron microscopy.



In all cases the combination of TB and BBG was useful for identifying and delineating ERM and ILM. No complications related to the use of the dye were observed during or after surgery. Glial cells were present in all specimens. Hyalocytes were observed in 6 cases and myofibroblasts in 3 of them. In 7 cases native vitreous collagen fibrils were found on the ILM, while in 5 specimens newly formed collagen was present. No clinical evidence of toxicity was observed during the 3-month follow-up.



The combined use of TB and BBG appeared to be very useful intraoperatively to improve the visualization of ERM and ILM, thus facilitating their complete removal. Anatomical and histopathological findings demonstrated the safety and the efficacy of this vital dye.
Three-dimensional finite element analysis of the foot during standing--a material sensitivity study.

Information on the internal stresses/strains in the human foot and the pressure distribution at the plantar support interface under loading is useful in enhancing knowledge on the biomechanics of the ankle-foot complex. While techniques for plantar pressure measurements are well established, direct measurement of the internal stresses/strains is difficult. A three-dimensional (3D) finite element model of the human foot and ankle was developed using the actual geometry of the foot skeleton and soft tissues, which were obtained from 3D reconstruction of MR images. Except the phalanges that were fused, the interaction among the metatarsals, cuneiforms, cuboid, navicular, talus, calcaneus, tibia and fibula were defined as contact surfaces, which allow relative articulating movement. The plantar fascia and 72 major ligaments were simulated using tension-only truss elements by connecting the corresponding attachment points on the bone surfaces. The bony and ligamentous structures were embedded in a volume of soft tissues. The encapsulated soft tissue was defined as hyperelastic, while the bony and ligamentous structures were assumed to be linearly elastic. The effects of soft tissue stiffening on the stress distribution of the plantar surface and bony structures during balanced standing were investigated. Increases of soft tissue stiffness from 2 and up to 5 times the normal values were used to approximate the pathologically stiffened tissue behaviour with increasing stages of diabetic neuropathy. The results showed that a five-fold increase in soft tissue stiffness led to about 35% and 33% increase in the peak plantar pressure at the forefoot and rearfoot regions, respectively. This corresponded to about 47% decrease in the total contact area between the plantar foot and the horizontal support surface. Peak bone stress was found at the third metatarsal in all calculated cases with a minimal increase of about 7% with soft tissue stiffening.
An RF Energy Harvester System Using UHF Micropower CMOS Rectifier Based on a Diode Connected CMOS Transistor

This paper presents a new type diode connected MOS transistor to improve CMOS conventional rectifier's performance in RF energy harvester systems for wireless sensor networks in which the circuits are designed in 0.18  μm TSMC CMOS technology. The proposed diode connected MOS transistor uses a new bulk connection which leads to reduction in the threshold voltage and leakage current; therefore, it contributes to increment of the rectifier's output voltage, output current, and efficiency when it is well important in the conventional CMOS rectifiers. The design technique for the rectifiers is explained and a matching network has been proposed to increase the sensitivity of the proposed rectifier. Five-stage rectifier with a matching network is proposed based on the optimization. The simulation results shows 18.2% improvement in the efficiency of the rectifier circuit and increase in sensitivity of RF energy harvester circuit. All circuits are designed in 0.18 μm TSMC CMOS technology.
Pi-Pi contacts are an overlooked protein feature relevant to phase separation

Protein phase separation is implicated in formation of membraneless organelles, signaling puncta and the nuclear pore. Multivalent interactions of modular binding domains and their target motifs can drive phase separation. However, forces promoting the more common phase separation of intrinsically disordered regions are less understood, with suggested roles for multivalent cation-pi, pi-pi, and charge interactions and the hydrophobic effect. Known phase-separating proteins are enriched in pi-orbital containing residues and thus we analyzed pi-interactions in folded proteins. We found that pi-pi interactions involving non-aromatic groups are widespread, underestimated by force-fields used in structure calculations and correlated with solvation and lack of regular secondary structure, properties associated with disordered regions. We present a phase separation predictive algorithm based on pi interaction frequency, highlighting proteins involved in biomaterials and RNA processing.
Design of Low Noise Amplifier using BFP 540 and BFP 640

Amplifiers play a critical role in a Communication System. They are used to increase the voltage, current, and/or power of a signal, in both transmitters and receivers. LNA is used at the front end of the receivers. Important properties of amplifiers include gain, input and output impedances measured using Sparameters, noise figure, stability, bias networks, interface with other circuits (ports). When designing a linear narrow band amplifier, the goal is to produce a design that is well-matched at the design frequency and has a good gain and low noise at that frequency. The Sparameters are a function of bias condition, so the result using a set of S-parameters are only valid at the bias conditions at which the S-parameters were measured or simulated. In this Paper, using bilateral approach, LNA is designed using RF transistor BFP 540 and BFP 640 (product of Infineon Technology). The BFP 540 gives considerable gain with minimum noise figure whereas, BFP 640 gives higher gain but at the cost of high noise figure.
The aponeurotic expansion of the supraspinatus tendon: anatomy and prevalence in a series of 150 shoulder MRIs

To describe the aponeurotic expansion of the supraspinatus tendon with anatomic correlations and determine its prevalence in a series of patients imaged with MRI. In the first part of this HIPAA-compliant and IRB-approved study, we retrospectively reviewed 150 consecutive MRI studies of the shoulder obtained on a 1.5-T system. The aponeurotic expansion at the level of the bicipital groove was classified as: not visualized (type 0), flat-shaped (type 1), oval-shaped and less than 50 % the size of the adjacent long head of the biceps section (type 2A), or oval-shaped and more than 50 % the size of the adjacent long head of the biceps section (type 2B). In the second part of this study, we examined both shoulders of 25 cadavers with ultrasound. When aponeurotic expansion was seen at US, a dissection was performed to characterize its origin and termination. An aponeurotic expansion of the supraspinatus located anterior and lateral to the long head of the biceps in its groove was clearly demonstrated in 49 % of the shoulders with MRI. According to our classification, its shape was type 1 in 35 %, type 2A in 10 % and type 2B in 4 %. This structure was also identified in 28 of 50 cadaveric shoulders with ultrasound and confirmed at dissection in 10 cadavers (20 shoulders). This structure originated from the most anterior and superficial aspect of the supraspinatus tendon and inserted distally on the pectoralis major tendon. The aponeurotic expansion of the supraspinatus tendon can be identified with MRI or ultrasound in about half of the shoulders. It courses anteriorly and laterally to the long head of the biceps tendon, outside its synovial sheath.
Structure-function of the glucagon receptor family of G protein-coupled receptors: the glucagon, GIP, GLP-1, and GLP-2 receptors.

The glucagon-like peptides include glucagon, GLP-1, and GLP-2, and exert diverse actions on nutrient intake, gastrointestinal motility, islet hormone secretion, cell proliferation and apoptosis, nutrient absorption, and nutrient assimilation. GIP, a related member of the glucagon peptide superfamily, also regulates nutrient disposal via stimulation of insulin secretion. The actions of these peptides are mediated by distinct members of the glucagon receptor superfamily of G protein-coupled receptors. These receptors exhibit unique patterns of tissue-specific expression, exhibit considerable amino acid sequence identity, and share similar structural and functional properties with respect to ligand binding and signal transduction. This article provides an overview of the biology of these receptors with an emphasis on understanding the unique actions of glucagon-related peptides through studies of the biology of their cognate receptors.
Dynamic Approach for Data Scrubbing Process

It is very difficult to over-emphasize the benefits of accurate data. Errors in data are generally the most expensive aspect of data entry, costing the users even much more compared to the original data entry. Unfortunately, these costs are intangibles or difficult to measure. If errors are detected at an early stage then it requires little cost to remove the errors. Incorrect and misleading data lead to all sorts of unpleasant and unnecessary expenses. Unluckily, it would be very expensive to correct the errors after the data has been processed, particularly when the processed data has been converted into the knowledge for decision making. No doubt a stitch in time saves nine i.e. a timely effort will prevent more work at later stage. Moreover, time spent in processing errors can also have a significant cost. One of the major problems with automated data entry systems are errors. In this paper we discuss many well known techniques to minimize errors, different cleansing approaches and, suggest how we can improve accuracy rate. Framework available for data cleansing offer the fundamental services such as attribute selection, formation of tokens, selection of clustering algorithms, selection of eliminator functions etc.
An adaptive multilevel wavelet collocation method for elliptic problems

An adaptive multilevel wavelet collocation method for solving multi-dimensional elliptic problems with localized structures is described. The method is based on multi-dimensional second generation wavelets, and is an extension of the dynamically adaptive second generation wavelet collocation method for evolution problems [  (2003) 151]. Wavelet decomposition is used for grid adaptation and interpolation, while a hierarchical finite difference scheme, which takes advantage of wavelet multilevel decomposition, is used for derivative calculations. The multilevel structure of the wavelet approximation provides a natural way to obtain the solution on a near optimal grid. In order to accelerate the convergence of the solver, an iterative procedure analogous to the multigrid algorithm is developed. The overall computational complexity of the solver is O(N ), where N is the number of adapted grid points. The accuracy and computational efficiency of the method are demonstrated for the solution of twoand three-dimensional elliptic test problems.
Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support

A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends.
3D puppetry: a kinect-based interface for 3D animation

We present a system for producing 3D animations using physical objects (i.e., puppets) as input. Puppeteers can load 3D models of familiar rigid objects, including toys, into our system and use them as puppets for an animation. During a performance, the puppeteer physically manipulates these puppets in front of a Kinect depth sensor. Our system uses a combination of image-feature matching and 3D shape matching to identify and track the physical puppets. It then renders the corresponding 3D models into a virtual set. Our system operates in real time so that the puppeteer can immediately see the resulting animation and make adjustments on the fly. It also provides 6D virtual camera \\rev{and lighting} controls, which the puppeteer can adjust before, during, or after a performance. Finally our system supports layered animations to help puppeteers produce animations in which several characters move at the same time. We demonstrate the accessibility of our system with a variety of animations created by puppeteers with no prior animation experience.
Marenko-Pastur law for Kendall’s tau

We prove that Kendall’s Rank correlation matrix converges to the Marčenko Pastur law, under the assumption that observations are i.i.d random vectors X1, . . . , Xn with components that are independent and absolutely continuous with respect to the Lebesgue measure. This is the first result on the empirical spectral distribution of a multivariate U -statistic.
Predictive-State Decoders: Encoding the Future into Recurrent Networks

UC Berkeley, BAIR Lab Visiting Researcher with Sergey Levine June 2018 – Nov 2018 NEC Labs America Research Assistant with P. Vernaza, M. Chandraker May 2017 – Sept 2017 Uber Advanced Technologies Group Research Engineer with V. Ramakrishna, D. Bagnell June 2016 – Sept 2016 University of Tokyo I.I.S. Visiting Researcher with Ryo Yonetani, Yoichi Sato June 2015 – July 2015 National Robotics Engineering Center Research Programmer with Drew Bagnell June 2012 – Jan 2013 Carnegie Mellon University R.I. Research Intern with D. Dey, Drew Bagnell June 2011 – Aug 2011