nils-herrmann/clean_scirepeval huggingface dataset:
Beyond nodes and edges: multiresolution algorithms for network data

Networks are a fundamental tool for understanding and modeling complex systems in physics, biology, neuroscience, engineering, and social science. Many networks are known to exhibit rich, lower-order connectivity patterns that can be captured at the level of individual nodes and edges. However, higher-order organization of complex networks -- at the level of small network subgraphs -- remains largely unknown. Here, we develop a generalized framework for clustering networks on the basis of higher-order connectivity patterns. This framework provides mathematical guarantees on the optimality of obtained clusters and scales to networks with billions of edges. The framework reveals higher-order organization in a number of networks, including information propagation units in neuronal networks and hub structure in transportation networks. Results show that networks exhibit rich higher-order organizational structures that are exposed by clustering based on higher-order connectivity patterns.
 Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low-dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node's network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state-of-the-art techniques on multi-label classification and link prediction in several real-world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks.
Money Laundering and Technology Enabled Crime: a cultural analysis

Over the past decade or so, aided by information and communication technologies, money laundering has seen a sharp increase. While traditionally money laundering was associated with drug cartels and warlords, increasingly the focus has shifted towards white-collar crime and terrorist financing. It is therefore important to understand why money laundering (and hence white-collar crime) comes into being and sustains over a period of time. This paper, while exploring the antecedents of technology enabled white-collar crime, undertakes a cultural analysis of the Silk Road case. The cultural analysis helps in understanding patterns of behavior associated with technology enabled white-collar crimes.
Stabilizing Integrators for Real-Time Physics

We present a new time integration method featuring excellent stability and energy conservation properties, making it particularly suitable for real-time physics. The commonly used backward Euler method is stable but introduces artificial damping. Methods such as implicit midpoint do not suffer from artificial damping but are unstable in many common simulation scenarios. We propose an algorithm that blends between the implicit midpoint and forward/backward Euler integrators such that the resulting simulation is stable while introducing only minimal artificial damping. We achieve this by tracking the total energy of the simulated system, taking into account energy-changing events: damping and forcing. To facilitate real-time simulations, we propose a local/global solver, similar to Projective Dynamics, as an alternative to Newton’s method. Compared to the original Projective Dynamics, which is derived from backward Euler, our final method introduces much less numerical damping at the cost of minimal computing overhead. Stability guarantees of our method are derived from the stability of backward Euler, whose stability is a widely accepted empirical fact. However, to our knowledge, theoretical guarantees have so far only been proven for linear ODEs. We provide preliminary theoretical results proving the stability of backward Euler also for certain cases of nonlinear potential functions.
Seroprevalence of Newcastle Disease , Chicken Infectious Anemia and Avian Influenza in Indigenous Chickens in Grenada , West Indies

This study was conducted to determine the seroprevalence of antibodies against Newcastle disease virus (NDV), Chicken infectious anemia virus (CIAV) and Avian influenza virus (AIV) in indigenous chickens in Grenada, West Indies. Indigenous chickens are kept for eggs and meat for either domestic consumption or local sale. These birds are usually kept in the backyard of the house with little or no shelter. The mean size of the flock per household was 14 birds (range 5-40 birds). Blood was collected from 368 birds from all the six parishes of Grenada and serum samples were tested for antibodies against NDV, CIAV and AIV using commercial enzyme-linked immunosorbent assay (ELISA) kits. The seroprevalence of antibodies against NDV, CIA and AI was 66.3% (95% CI; 61.5% to 71.1%), 59.5% (95% CI; 54.4% to 64.5%) and 10.3% (95% CI; 7.2% to 13.4%), respectively. Since indigenous chickens in Grenada are not vaccinated against poultry pathogens, these results indicate exposure of chickens to NDV, AIV and CIAV Indigenous chickens are thus among the risk factors acting as vectors of pathogens that can threaten commercial poultry and other avian species in Grenada
Robust Neural-Network-Based Classification of Premature Ventricular Contractions Using Wavelet Transform and Timing Interval Features

Automatic electrocardiogram (ECG) beat classification is essential to timely diagnosis of dangerous heart conditions. Specifically, accurate detection of premature ventricular contractions (PVCs) is imperative to prepare for the possible onset of life-threatening arrhythmias. Although many groups have developed highly accurate algorithms for detecting PVC beats, results have generally been limited to relatively small data sets. Additionally, many of the highest classification accuracies (>90%) have been achieved in experiments where training and testing sets overlapped significantly. Expanding the overall data set greatly reduces overall accuracy due to significant variation in ECG morphology among different patients. As a result, we believe that morphological information must be coupled with timing information, which is more constant among patients, in order to achieve high classification accuracy for larger data sets. With this approach, we combined wavelet-transformed ECG waves with timing information as our feature set for classification. We used select waveforms of 18 files of the MIT/BIH arrhythmia database, which provides an annotated collection of normal and arrhythmic beats, for training our neural-network classifier. We then tested the classifier on these 18 training files as well as 22 other files from the database. The accuracy was 95.16% over 93,281 beats from all 40 files, and 96.82% over the 22 files outside the training set in differentiating normal, PVC, and other beats
Benchmarking Semiconductor Manufacturing

We are studying the manufacturing performance of semiconductor wafer fabrication plants in the US, Asia, and Europe. There are great similarities in production equipment, manufacturing processes, and products produced at semiconductor fabs around the world. However, detailed comparisons over multi-year intervals show that important quantitative indicators of productivity, including defect density (yield), major equipment production rates, wafer throughput time, and effective new process introduction to manufacturing, vary by factors of 3 to as much as 5 across an international sample of 28 fabs. We conduct on-site observations, and interviews with manufacturing personnel at all levels from operator to general manager, to better understand reasons for the observed wide variations in performance. We have identified important factors in the areas of information systems, organizational practices, process and technology improvements, and production control that correlate strongly with high productivity. Optimum manufacturing strategy is different for commodity products, high-value proprietary products, and foundry business.
Data Mining for Student Outcome Prediction on Moodle: a systematic mapping

Virtual learning environments facilitate online learning, generating and storing large amounts of data during the learning/teaching process. This stored data enables extraction of valuable information using data mining. In this article, we present a systematic mapping, containing 42 papers, where data mining techniques are applied to predict students performance using Moodle data. Results show that decision trees are the most used classification approach. Furthermore, students interactions in forums are the main Moodle attribute analyzed by researchers.
Autotropism in fungal spores and hyphae

A tropism is a growth movement exhibited by part of an organism in response to a unidirectional stimulus. When the stimulus is due to the same organism which displays the tropism, or to a neighbouring organism of the same species, the oriented growth which occurs is an autotropism. For the purpose of this review autotropic responses are divided into two main groups. One group arises from interactions of neighbouring spores and affects the point of emergence and initial direction of growth of each germ-tube; the other group arises from interactions of neighbouring somatic hyphae and can result in the orientated growth of hyphae to give the characteristic growth pattern of a fungal colony grown on a solid medium. In the simplest sense there is an interaction of two spores or two hyphae but these responses may be modified by the size or density of the population to which the spores or hyphae belong and also by other environmental conditions. In the broadest sense autotropism can be investigated between neighbouring spore suspensions (or hyphal populations) of the same species. Many autotropic responses in fungi have been attributed to the production of labile metabolites to which germ-tubes and mature hyphae react in a negative chemotropic manner. Whilst such metabolites may play a major part in tropic responses between two spores which are in contact or slightly separated it is intended to point out that there is
Safe surgical technique: cement-augmented pedicle screw instrumentation and balloon-guided kyphoplasty for a lumbar burst fracture in a 97-year-old patient

During the last few years, an increasing number of unstable thoracolumbar fractures, especially in elderly patients, has been treated by dorsal instrumentation combined with a balloon kyphoplasty. This combination provides additional stabilization to the anterior spinal column without any need for a second ventral approach.



We report the case of a 97-year-old male patient with a lumbar burst fracture (type A3-1.1 according to the AO Classification) who presented prolonged neurological deficits of the lower limbs - grade C according to the modified Frankel/ASIA score. After a posterior realignment of the fractured vertebra with an internal screw fixation and after an augmentation with non-absorbable cement in combination with a balloon kyphoplasty, the patient regained his mobility without any neurological restrictions.



Especially in older patients, the presented technique of PMMA-augmented pedicle screw instrumentation combined with balloon-assisted kyphoplasty could be an option to address unstable vertebral fractures in "a minor-invasive way". The standard procedure of a two-step dorsoventral approach could be reduced to a one-step procedure.
Indexing compressed text

We design two compressed data structures for the full-text indexing problem that support efficient substring searches using roughly the space required for storing the text in compressed form.Our first compressed data structure retrieves the <i>occ</i> occurrences of a pattern <i>P</i>[1,<i>p</i>] within a text <i>T</i>[1,<i>n</i>] in <i>O</i>(<i>p</i> + <i>occ</i> log<sup>1+ε</sup> <i>n</i>) time for any chosen ε, 0<ε<1. This data structure uses at most 5<i>n</i><i>H</i><inf><i>k</i></inf>(<i>T</i>) + <i>o</i>(<i>n</i>) bits of storage, where <i>H</i><inf><i>k</i></inf>(<i>T</i>) is the <i>k</i>th order empirical entropy of <i>T</i>. The space usage is Θ(<i>n</i>) bits in the worst case and <i>o</i>(<i>n</i>) bits for compressible texts. This data structure exploits the relationship between suffix arrays and the Burrows--Wheeler Transform, and can be regarded as a <i>compressed suffix array</i>.Our second compressed data structure achieves <i>O</i>(<i>p</i>+<i>occ</i>) query time using <i>O</i>(<i>n</i><i>H</i><inf><i>k</i></inf>(<i>T</i>)log<sup>ε</sup> <i>n</i>) + <i>o</i>(<i>n</i>) bits of storage for any chosen ε, 0<ε<1. Therefore, it provides optimal <i>output-sensitive</i> query time using <i>o</i>(<i>n</i>log <i>n</i>) bits in the worst case. This second data structure builds upon the first one and exploits the interplay between two compressors: the Burrows--Wheeler Transform and the <i>LZ78</i> algorithm.
Catheter-directed therapy for the treatment of massive pulmonary embolism: systematic review and meta-analysis of modern techniques.

Systemic thrombolysis for the treatment of acute pulmonary embolism (PE) carries an estimated 20% risk of major hemorrhage, including a 3%-5% risk of hemorrhagic stroke. The authors used evidence-based methods to evaluate the safety and effectiveness of modern catheter-directed therapy (CDT) as an alternative treatment for massive PE.



The systematic review was initiated by electronic literature searches (MEDLINE, EMBASE) for studies published from January 1990 through September 2008. Inclusion criteria were applied to select patients with acute massive PE treated with modern CDT. Modern techniques were defined as the use of low-profile devices (< or =10 F), mechanical fragmentation and/or aspiration of emboli including rheolytic thrombectomy, and intraclot thrombolytic injection if a local drug was infused. Relevant non-English language articles were translated into English. Paired reviewers assessed study quality and abstracted data. Meta-analysis was performed by using random effects models to calculate pooled estimates for complications and clinical success rates across studies. Clinical success was defined as stabilization of hemodynamics, resolution of hypoxia, and survival to hospital discharge.



Five hundred ninety-four patients from 35 studies (six prospective, 29 retrospective) met the criteria for inclusion. The pooled clinical success rate from CDT was 86.5% (95% confidence interval [CI]: 82.1%, 90.2%). Pooled risks of minor and major procedural complications were 7.9% (95% CI: 5.0%, 11.3%) and 2.4% (95% CI: 1.9%, 4.3%), respectively. Data on the use of systemic thrombolysis before CDT were available in 571 patients; 546 of those patients (95%) were treated with CDT as the first adjunct to heparin without previous intravenous thrombolysis.



Modern CDT is a relatively safe and effective treatment for acute massive PE. At experienced centers, CDT should be considered as a first-line treatment for patients with massive PE.
Integrated Speech Enhancement Method Based on Weighted Prediction Error and DNN for Dereverberation and Denoising

Both reverberation and additive noises degrade the speech quality and intelligibility. the weighted prediction error (WPE) performs well on dereverberation but with limitations. First, The WPE doesn’t consider the influence of the additive noise which degrades the performance of dereverberation. Second, it relies on a time-consuming iterative process, and there is no guarantee or a widely accepted criterion on its convergence. In this paper, we integrate deep neural network (DNN) into WPE for dereverberation and denoising. DNN is used to suppress the background noise to meet the noise-free assumption of WPE. Meanwhile, DNN is applied to directly predict spectral variance of the target speech to make the WPE work without iteration. The experimental results show that the proposed method has a significant improvement in speech quality and runs fast.
Psoriatic arthritis and nail changes: exploring the relationship.

Psoriatic arthritis (PsA) has a diverse range of clinical manifestations, both articular and extra-articular. Although the association of PsA with skin changes is well established, the relationship of PsA with psoriatic nail changes remains relatively unexplored.



This report reviews the current literature surrounding the association of PsA with nail changes. A review of the literature was completed using PubMed, MEDLINE, and EMBASE in September 2013, encompassing years 1964-2012.



A total of 21 articles were reviewed. On average, 66% [standard deviation (SD) 17.7] of PsA patients had nail changes. The type of nail changes and their associations varied widely between studies.



Studies of nail changes in PsA are highly variable with a wide range of results. Given the variability of results that were observed in this review, our recommendations are that further large studies on nail changes in patients with PsA should be conducted.
Patterns of nail matrix and bed of longitudinal melanonychia by intraoperative dermatoscopy.

The dermatoscopic examination of the nail plate has been recently introduced for the evaluation of pigmented nail lesions. There is, however, no evidence that this technique improves diagnostic accuracy of in situ melanoma.



To establish and validate patterns for intraoperative dermatoscopy of the nail matrix.



Intraoperative nail matrix dermatoscopy was performed in 100 consecutive bands of longitudinal melanonychia that were excised and submitted to histopathologic examination.



We identified 4 dermatoscopic patterns: regular gray pattern (hypermelanosis), regular brown pattern (benign melanocytic hyperplasia), regular brown pattern with globules or blotch (melanocytic nevi), and irregular pattern (melanoma).



Nail matrix dermatoscopy is an invasive procedure that can not routinely be performed in all cases of melanonychia.



The patterns described present high sensitivity and specificity for intraoperative differential diagnosis of pigmented nail lesions.
Neonatal Schwartz-Jampel syndrome: a common autosomal recessive syndrome in the United Arab Emirates.

Schwartz-Jampel syndrome (SJS) is a heterogeneous autosomal recessive syndrome of myotonia and bone dysplasia. Two types have been recognised: the classical type with late infantile or childhood manifestation and a rarer form with neonatal manifestation. We report five families with a total of 11 children affected with severe neonatal SJS. All presented after birth with skeletal abnormalities and feeding difficulties. Five had the typical pursed appearance of the mouth. Nine died from respiratory complications (five in the neonatal period and four before 2 years of age). One (4 months old) remains hospitalised since birth requiring continuous oxygen supplementation and one (5 months old) requires nasogastric tube feeding and has repeated attacks of aspiration. Only seven of the 17 previously reported neonatal SJS cases had a similar course to the patients in this report. We suggest that within neonatal SJS there is a subgroup which manifests severe respiratory and feeding problems and has a poor prognosis. This report brings the total number of children with neonatal SJS reported from the UAE to 14. This represents the largest review of this syndrome to date from one centre and indicates that this syndrome is fairly common in the population of the UAE.
Dynamic Effective Resistances and Approximate Schur Complement on Separable Graphs

We consider the problem of dynamically maintaining (approximate) all-pairs effective resistances in separable graphs, which are those that admit an n-separator theorem for some c < 1. We give a fully dynamic algorithm that maintains (1 + ε)-approximations of the allpairs effective resistances of an n-vertex graph G undergoing edge insertions and deletions with Õ( √ n/ε) worst-case update time and Õ( √ n/ε) worst-case query time, if G is guaranteed to be √ n-separable (i.e., it is taken from a class satisfying a √ n-separator theorem) and its separator can be computed in Õ(n) time. Our algorithm is built upon a dynamic algorithm for maintaining approximate Schur complement that approximately preserves pairwise effective resistances among a set of terminals for separable graphs, which might be of independent interest. We complement our result by proving that for any two fixed vertices s and t, no incremental or decremental algorithm can maintain the s − t effective resistance for √n-separable graphs with worst-case update time O(n) and query time O(n) for any δ > 0, unless the Online Matrix Vector Multiplication (OMv) conjecture is false. We further show that for general graphs, no incremental or decremental algorithm can maintain the s− t effective resistance problem with worst-case update time O(n) and querytime O(n) for any δ > 0, unless the OMv conjecture is false. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 340506. University of Vienna, Faculty of Computer Science, Vienna, Austria. E-mail: gramoz.goranci@univie.ac.at. University of Vienna, Faculty of Computer Science, Vienna, Austria. E-mail: monika.henzinger@univie.ac.at. Department of Computer Science, University of Sheffield, Sheffield, UK.  p.peng@sheffield.ac.uk. Work done in part while at the Faculty of Computer Science, University of Vienna, Austria.
Prevention of Diabetes Self-Management Program (PREDIAS): Effects on Weight, Metabolic Risk Factors, and Behavioral Outcomes

To evaluate the efficacy of the group program PREDIAS for diabetes prevention.



PREDIAS consists of 12 lessons and aims at lifestyle modification. The control group received written information about diabetes prevention. In this study, a total of 182 persons with an elevated diabetes risk participated (aged 56.3 +/- 10.1 years, 43% female, and BMI 31.5 +/- 5.3 kg/m(2)).



After 12 months, weight loss was significantly higher (P = 0.001) in PREDIAS than in the control group (-3.8 +/- 5.2 vs. -1.4 +/- 4.09 kg). There were also significant effects (P = 0.001) on fasting glucose (control group 1.8 +/- 13.1 mg/dl vs. PREDIAS -4.3 +/- 11.3 mg/dl), duration of physical activity per week (control group 17.9 +/- 63.8 min vs. PREDIAS 46.6 +/- 95.5 min; P = 0.03), and eating behavior.



PREDIAS significantly modified lifestyle factors associated with an elevated diabetes risk.
Two-Stage Data Augmentation for Low-Resourced Speech Recognition

Low resourced languages suffer from limited training data and resources. Data augmentation is a common approach to increasing the amount of training data. Additional data is synthesized by manipulating the original data with a variety of methods. Unlike most previous work that focuses on a single technique, we combine multiple, complementary augmentation approaches. The first stage adds noise and perturbs the speed of additional copies of the original audio. The data is further augmented in a second stage, where a novel fMLLR-based augmentation is applied to bottleneck features to further improve performance. A reduction in word error rate is demonstrated on four languages from the IARPA Babel program. We present an analysis exploring why these techniques are beneficial.