nils-herrmann/clean_scirepeval huggingface dataset:
Log-Euclidean Kernels for Sparse Representation and Dictionary Learning

The symmetric positive definite (SPD) matrices have been widely used in image and vision problems. Recently there are growing interests in studying sparse representation (SR) of SPD matrices, motivated by the great success of SR for vector data. Though the space of SPD matrices is well-known to form a Lie group that is a Riemannian manifold, existing work fails to take full advantage of its geometric structure. This paper attempts to tackle this problem by proposing a kernel based method for SR and dictionary learning (DL) of SPD matrices. We disclose that the space of SPD matrices, with the operations of logarithmic multiplication and scalar logarithmic multiplication defined in the Log-Euclidean framework, is a complete inner product space. We can thus develop a broad family of kernels that satisfies Mercer's condition. These kernels characterize the geodesic distance and can be computed efficiently. We also consider the geometric structure in the DL process by updating atom matrices in the Riemannian space instead of in the Euclidean space. The proposed method is evaluated with various vision problems and shows notable performance gains over state-of-the-arts.
The self-paced VO2max test to assess maximal oxygen uptake in highly trained runners.

The novel self-paced maximal-oxygen-uptake (VO2max) test (SPV) may be a more suitable alternative to traditional maximal tests for elite athletes due to the ability to self-regulate pace. This study aimed to examine whether the SPV can be administered on a motorized treadmill.



Fourteen highly trained male distance runners performed a standard graded exercise test (GXT), an incline-based SPV (SPVincline), and a speed-based SPV (SPVspeed). The GXT included a plateau-verification stage. Both SPV protocols included 5×2-min stages (and a plateau-verification stage) and allowed for self-pacing based on fixed increments of rating of perceived exertion: 11, 13, 15, 17, and 20. The participants varied their speed and incline on the treadmill by moving between different marked zones in which the tester would then adjust the intensity.



There was no significant difference (P=.319, ES=0.21) in the VO2max achieved in the SPVspeed (67.6±3.6 mL·kg(-1)·min(-1), 95%CI=65.6-69.7 mL·kg(-1)·min(-1)) compared with that achieved in the GXT (68.6±6.0 mL·kg(-1)·min(-1), 95%CI=65.1-72.1 mL·kg(-1)·min(-1)). Participants achieved a significantly higher VO2max in the SPVincline (70.6±4.3 mL·kg(-1)·min(-1), 95%CI=68.1-73.0 mL·kg(-1)·min(-1)) than in either the GXT (P=.027, ES=0.39) or SPVspeed (P=.001, ES=0.76).



The SPVspeed protocol produces VO2max values similar to those obtained in the GXT and may represent a more appropriate and athlete-friendly test that is more oriented toward the variable speed found in competitive sport.
Scalable Clustering Algorithms with Balancing Constraints

Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., of approximately the same size or importance. In this paper, we propose a general framework for scalable, balanced clustering. The data clustering process is broken down into three steps: sampling of a small representative subset of the points, clustering of the sampled data, and populating the initial clusters with the remaining data followed by refinements. First, we show that a simple uniform sampling from the original data is sufficient to get a representative subset with high probability. While the proposed framework allows a large class of algorithms to be used for clustering the sampled set, we focus on some popular parametric algorithms for ease of exposition. We then present algorithms to populate and refine the clusters. The algorithm for populating the clusters is based on a generalization of the stable marriage problem, whereas the refinement algorithm is a constrained iterative relocation scheme. The complexity of the overall method is O(kN log N) for obtaining k balanced clusters from N data points, which compares favorably with other existing techniques for balanced clustering. In addition to providing balancing guarantees, the clustering performance obtained using the proposed framework is comparable to and often better than the corresponding unconstrained solution. Experimental results on several datasets, including high-dimensional (>20,000) ones, are provided to demonstrate the efficacy of the proposed framework.
Unexplained gastrointestinal symptoms and joint hypermobility: is connective tissue the missing link?

Unexplained gastrointestinal (GI) symptoms and joint hypermobility (JHM) are common in the general population, the latter described as benign joint hypermobility syndrome (BJHS) when associated with musculo-skeletal symptoms. Despite overlapping clinical features, the prevalence of JHM or BJHS in patients with functional gastrointestinal disorders has not been examined.  The incidence of JHM was evaluated in 129 new unselected tertiary referrals (97 female, age range 16-78 years) to a neurogastroenterology clinic using a validated 5-point questionnaire. A rheumatologist further evaluated 25 patients with JHM to determine the presence of BJHS. Groups with or without JHM were compared for presentation, symptoms and outcomes of relevant functional GI tests.  Sixty-three (49%) patients had evidence of generalized JHM. An unknown aetiology for GI symptoms was significantly more frequent in patients with JHM than in those without (P < 0.0001). The rheumatologist confirmed the clinical impression of JHM in 23 of 25 patients, 17 (68%) of whom were diagnosed with BJHS. Patients with co-existent BJHS and GI symptoms experienced abdominal pain (81%), bloating (57%), nausea (57%), reflux symptoms (48%), vomiting (43%), constipation (38%) and diarrhoea (14%). Twelve of 17 patients presenting with upper GI symptoms had delayed gastric emptying. One case is described in detail.  In a preliminary retrospective study, we have found a high incidence of JHM in patients referred to tertiary neurogastroenterology care with unexplained GI symptoms and in a proportion of these a diagnosis of BJHS is made. Symptoms and functional tests suggest GI dysmotility in a number of these patients. The possibility that a proportion of patients with unexplained GI symptoms and JHM may share a common pathophysiological disorder of connective tissue warrants further investigation.
Corruption – A selected and annotated bibliography

Acknowledgements A team of two researchers from Chr. Michelsen Institute (CMI) has prepared this annotated bibliography on "corruption": Inge Amundsen (political scientist). His research focus is comparative politics of democratisation, institutionalisation and reform, political parties, and state and civil society relations. Odd-Helge Fjeldstad (economist). His research focuses on corruption, public finance, tax reforms and fiscal decentralisation in developing countries. The team bears sole responsibility for the selection and presentation of the publications in this bibliography. We wish to acknowledge the advice offered to the team by Jens Andvig (Norwegian Institute for Foreign Affairs), and Mette Masst and Ragna Fidjestøl (NORAD). Special thanks to the CMI librarians for their invaluable assistance in providing us with a continuously expanding pile of literature. Inge Amundsen & Odd-Helge Fjeldstad Chr. Michelsen Institute, Bergen March 2000 Corruption A selected and annotated bibliography
Uncovering Crowdsourced Manipulation of Online Reviews

Online reviews are a cornerstone of consumer decision making. However, their authenticity and quality has proven hard to control, especially as polluters target these reviews toward promoting products or in degrading competitors. In a troubling direction, the widespread growth of crowdsourcing platforms like Mechanical Turk has created a large-scale, potentially difficult-to-detect workforce of malicious review writers. Hence, this paper tackles the challenge of uncovering crowdsourced manipulation of online reviews through a three-part effort: (i) First, we propose a novel sampling method for identifying products that have been targeted for manipulation and a seed set of deceptive reviewers who have been enlisted through crowdsourcing platforms. (ii) Second, we augment this base set of deceptive reviewers through a reviewer-reviewer graph clustering approach based on a Markov Random Field where we define individual potentials (of single reviewers) and pair potentials (between two reviewers). (iii) Finally, we embed the results of this probabilistic model into a classification framework for detecting crowd-manipulated reviews. We find that the proposed approach achieves up to 0.96 AUC, outperforming both traditional detection methods and a SimRank-based alternative clustering approach.
Texture Analysis: Representation and Matching

This paper describes a method for synthesizing images that match the texture appearanceof a given digitized sample. This synthesis is completely automatic and requires only the “target” texture as input. It allows generation of as much texture as desired so that any object can be covered. It can be used to produce solid textures for creating textured 3-d objects without the distortions inherent in texture mapping. It can also be used to synthesize texture mixtures, images that look a bit like each of several digitized samples. The approach is based on a model of human texture perception, and has potential to be a practically useful tool for graphics applications.
Identifying and Filtering Near-Duplicate Documents

The mathematical concept of document resemblance captures well the informal notion of syntactic similarity. The resemblance can be estimated using a fixed size “sketch” for each document. For a large collection of documents (say hundreds of millions) the size of this sketch is of the order of a few hundred bytes per document. However, for efficient large scale web indexing it is not necessary to determine the actual resemblance value: it suffices to determine whether newly encountered documents are duplicates or near-duplicates of documents already indexed. In other words, it suffices to determine whether the resemblance is above a certain threshold. In this talk we show how this determination can be made using a ”sample” of less than 50 bytes per document. The basic approach for computing resemblance has two aspects: first, resemblance is expressed as a set (of strings) intersection problem, and second, the relative size of intersections is evaluated by a process of random sampling that can be done independently for each document. The process of estimating the relative size of intersection of sets and the threshold test discussed above can be applied to arbitrary sets, and thus might be of independent interest. The algorithm for filtering near-duplicate documents discussed here has been successfully implemented and has been used for the last three years in the context of the AltaVista search engine.
Video Tracking Using Learned Hierarchical Features

In this paper, we propose an approach to learn hierarchical features for visual object tracking. First, we offline learn features robust to diverse motion patterns from auxiliary video sequences. The hierarchical features are learned via a two-layer convolutional neural network. Embedding the temporal slowness constraint in the stacked architecture makes the learned features robust to complicated motion transformations, which is important for visual object tracking. Then, given a target video sequence, we propose a domain adaptation module to online adapt the pre-learned features according to the specific target object. The adaptation is conducted in both layers of the deep feature learning module so as to include appearance information of the specific target object. As a result, the learned hierarchical features can be robust to both complicated motion transformations and appearance changes of target objects. We integrate our feature learning algorithm into three tracking methods. Experimental results demonstrate that significant improvement can be achieved using our learned hierarchical features, especially on video sequences with complicated motion transformations.
Traffic Estimation And Prediction Based On Real Time Floating Car Data

The knowledge of the actual current state of the road traffic and its short-term evolution for the entire road network is a basic component of ATIS (advanced traveler information systems) and ATMS (advanced traffic management system) applications. In this view the use of real-time floating-car data (FCD), based on traces of GPS positions, is emerging as a reliable and cost-effective way to gather accurate travel times/speeds in a road network and to improve short-term predictions of travel conditions. The purpose of this paper is to present a large-scale working application of FCD-system, developed and operated by OCTOTelematics, delivering real-time traffic speed information throughout the Italian motorway network and along some important arterial streets located in major Italian metropolitan areas. Traffic speed estimates are deduced at an interval of 3 minutes from GPS traces transmitted in real-time from a large number (and still growing) of privately owned cars (about 600.000) equipped with a specific device covering a range of insurance-related applications. This paper also proposes two algorithms, respectively based on artificial neural networks and pattern-matching, designed to on-line perform short-term (15 to 30 minutes) predictions of link travel speeds by using current and near-past link average speeds estimated by the OCTOTelematics FCD system. The Rome ring road (GRA-Grande Raccordo Anulare) was used for testing the feasibility of the two algorithms. Testing results showed that the proposed approaches for short-term predictions are very promising and effective.
Connective-Tissue Growth Factor (CTGF/CCN2) Induces Astrogenesis and Fibronectin Expression of Embryonic Neural Cells In Vitro

Connective-tissue growth factor (CTGF) is a modular secreted protein implicated in multiple cellular events such as chondrogenesis, skeletogenesis, angiogenesis and wound healing. CTGF contains four different structural modules. This modular organization is characteristic of members of the CCN family. The acronym was derived from the first three members discovered, cysteine-rich 61 (CYR61), CTGF and nephroblastoma overexpressed (NOV). CTGF is implicated as a mediator of important cell processes such as adhesion, migration, proliferation and differentiation. Extensive data have shown that CTGF interacts particularly with the TGFβ, WNT and MAPK signaling pathways. The capacity of CTGF to interact with different growth factors lends it an important role during early and late development, especially in the anterior region of the embryo. ctgf knockout mice have several cranio-facial defects, and the skeletal system is also greatly affected due to an impairment of the vascular-system development during chondrogenesis. This study, for the first time, indicated that CTGF is a potent inductor of gliogenesis during development. Our results showed that in vitro addition of recombinant CTGF protein to an embryonic mouse neural precursor cell culture increased the number of GFAP- and GFAP/Nestin-positive cells. Surprisingly, CTGF also increased the number of Sox2-positive cells. Moreover, this induction seemed not to involve cell proliferation. In addition, exogenous CTGF activated p44/42 but not p38 or JNK MAPK signaling, and increased the expression and deposition of the fibronectin extracellular matrix protein. Finally, CTGF was also able to induce GFAP as well as Nestin expression in a human malignant glioma stem cell line, suggesting a possible role in the differentiation process of gliomas. These results implicate ctgf as a key gene for astrogenesis during development, and suggest that its mechanism may involve activation of p44/42 MAPK signaling. Additionally, CTGF-induced differentiation of glioblastoma stem cells into a less-tumorigenic state could increase the chances of successful intervention, since differentiated cells are more vulnerable to cancer treatments.
Concurrency Control issues in Mobile Database

Mobile computing is a revolutionary technology, born as a result of remarkable advances in computer hardware and wireless communication. Mobile applications have become increasingly popular in recent years. Today, it is not uncommon to see people playing games or reading mails on handphones. With the rapid advances in mobile computing technology, there is an increasing demand for processing realtime transactions in a mobile environment. Hence there is a strong need for efficient transaction management, data access modes and data management, consistency control and other mobile data management issues. This survey paper will cover issues related to concurrency control in mobile database. This paper studies concurrency control problem in mobile database systems, we analyze the features of mobile database and concurrency control techniques. With the increasing number of mobile hosts there are many new solutions and algorithms for concurrency control being proposed and implemented. We wish that our paper has served as a survey of the important solutions in the fields of concurrency control in mobile database. Keywords-component; Distributed Real-time Databases, Mobile Real-time Databases, Concurrency Control, Data Similarity, and Transaction Scheduling.
Cluster-based patent retrieval

Through the recent NTCIR workshops, patent retrieval casts many challenging issues to information retrieval community. Unlike newspaper articles, patent documents are very long and well structured. These characteristics raise the necessity to reassess existing retrieval techniques that have been mainly developed for structure-less and short documents such as newspapers. This study investigates cluster-based retrieval in the context of invalidity search task of patent retrieval. Cluster-based retrieval assumes that clusters would provide additional evidence to match user’s information need. Thus far, cluster-based retrieval approaches have relied on automatically-created clusters. Fortunately, all patents have manuallyassigned cluster information, international patent classification codes. International patent classification is a standard taxonomy for classifying patents, and has currently about 69,000 nodes which are organized into a five-level hierarchical system. Thus, patent documents could provide the best test bed to develop and evaluate cluster-based retrieval techniques. Experiments using the NTCIR-4 patent collection showed that the cluster-based language model could be helpful to improving the cluster-less baseline language model.
Multi-objective performance optimization of a probabilistic similarity/dissimilarity-based broadcasting scheme for mobile ad hoc networks in disaster response scenarios

Communications among crewmembers in rescue teams and among victims are crucial to relieve the consequences and damages of a disaster situation. A common communication system for establishing real time communications between the elements (victims, crewmembers, people living in the vicinity of the disaster scenario, among others) involved in a disaster scenario is required. Ad hoc networks have been envisioned for years as a possible soluCommunicated by A. Castiglione. D. G. Reina · J. M. León-Coca · S. L. Toral · F. Barrero Electronic Engineering Department, University of Seville, Seville, Spain e-mail: dgutierrezreina@us.es J. M. León-Coca e-mail: jmleoncoca@us.es S. L. Toral e-mail: storal@us.es F. Barrero e-mail: fbarrero@esi.us.es E. Asimakopoulou · N. Bessis (B) School of Computing and Maths, University of Derby, Derby, UK e-mail: n.bessis@derby.ac.uk E. Asimakopoulou e-mail: eleana.asimakopoulou@gmail.com P. Norrington Institute for Research in Applicable Computing, University of Bedfordshire, Luton, UK e-mail: peter.norrington@beds.ac.uk N. Bessis Department of Computer Science and Technology, University of Bedfordshire, Bedfordshire, UK e-mail: nik.bessis@beds.ac.uk tion. They allow users to establish decentralized communications quickly and using common devices like mobile phones. Broadcasting is the main mechanism used to disseminate information in all-to-all fashion in ad hoc networks. The objective of this paper is to optimize a broadcasting scheme based on similarity/dissimilarity coefficient designed for disaster response scenarios through a multi-objective optimization problem in which several performance metrics such as reachability, number of retransmissions and delay are optimized simultaneously.
The combination of vitamin C and grape-seed polyphenols increases blood pressure: a randomized, double-blind, placebo-controlled trial.

There is growing evidence that oxidative stress contributes to the pathogenesis of hypertension and endothelial dysfunction. Thus, dietary antioxidants may beneficially influence blood pressure (BP) and endothelial function by reducing oxidative stress.



To determine if vitamin C and polyphenols, alone or in combination, can lower BP, improve endothelial function and reduce oxidative stress in hypertensive individuals.



A total of 69 treated hypertensive individuals with a mean 24-h ambulatory systolic blood pressure > or = 125 mmHg participated in a randomized, double-blind, placebo-controlled, factorial trial. Following a 3-week washout, participants received 500 mg/day vitamin C, 1000 mg/day grape-seed polyphenols, both vitamin C and polyphenols, or neither for 6 weeks. At baseline and post-intervention, 24-h ambulatory BP, ultrasound-assessed endothelium-dependent and -independent vasodilation of the brachial artery, and markers of oxidative damage, (plasma and urinary F2-isoprostanes, oxidized low-density lipoproteins and plasma tocopherols), were measured.



A significant interaction between grape-seed and vitamin C treatments for effects on BP was observed. Vitamin C alone reduced systolic BP versus placebo (-1.8 +/- 0.8 mmHg, P = 0.03), while polyphenols did not (-1.3 +/- 0.8 mmHg, P = 0.12). However, treatment with the combination of vitamin C and polyphenols increased systolic BP (4.8 +/- 0.9 mmHg versus placebo; 6.6 +/- 0.8 mmHg versus vitamin C; 6.1 +/- 0.9 mmHg versus polyphenols mmHg, each P < 0.0001) and diastolic BP (2.7 +/- 0.6 mmHg, P < 0.0001 versus placebo; 1.5 +/- 0.6 mmHg, P = 0.016 versus vitamin C; 3.2 +/- 0.7 mmHg, P < 0.0001 versus polyphenols). Endothelium-dependent and -independent vasodilation, and markers of oxidative damage were not significantly altered.



Although the mechanism remains to be elucidated, these results suggest caution for hypertensive subjects taking supplements containing combinations of vitamin C and polyphenols.