nils-herrmann/clean_scirepeval huggingface dataset:
An ımproved clustering algorithm for text mining: multi-cluster spherical k-means

Thanks to advances in information and communication technologies, there is a prominent increase in the amount of information produced specifically in the form of text documents. In order to, effectively deal with this “information explosion” problem and utilize the huge amount of text databases, efficient and scalable tools and techniques are indispensable. In this study, text clustering which is one of the most important techniques of text mining that aims at extracting useful information by processing data in textual form is addressed. An improved variant of spherical K-Means (SKM) algorithm named multi-cluster SKM is developed for clustering high dimensional document collections with high performance and efficiency. Experiments were performed on several document data sets and it is shown that the new algorithm provides significant increase in clustering quality without causing considerable difference in CPU time usage when compared to SKM algorithm.
LEARNING DEEP RESNET BLOCKS SEQUENTIALLY

We prove a multiclass boosting theory for the ResNet architectures which simultaneously creates a new technique for multiclass boosting and provides a new algorithm for ResNet-style architectures. Our proposed training algorithm, BoostResNet, is particularly suitable in non-differentiable architectures. Our method only requires the relatively inexpensive sequential training of T “shallow ResNets”. We prove that the training error decays exponentially with the depth T if the weak module classifiers that we train perform slightly better than some weak baseline. In other words, we propose a weak learning condition and prove a boosting theory for ResNet under the weak learning condition. A generalization error bound based on margin theory is proved and suggests that ResNet could be resistant to overfitting using a network with l1 norm bounded weights.
A linear stability theory on time-invariant and time-dependent spatial domains with symmetry : the drop splash problem

This work is a combination of physical and analytical considerations of linear stability pictures on time-invariant and time-dependent spatial domains with symmetry. The discussion is offered in the context of the Rayleigh-Taylor instability (of a fluid interface accelerated in the direction of a heavier phase) applied to the drop splash problem, which provides a natural ground for developing stability theory on time-dependent spatial domains with O(2) symmetry. The peculiarity of the underlying linear model common in a number of other interfacial instabilities – linear oscillator ftt + a(k) f = 0 in the wavenumber k-space – allows one to establish a direct correspondence between stability pictures on time-invariant and time-dependent spatial domains. The stability analysis also leads to a notion of frustration in (linear) stability patterns.
Algorithm Selection for Classification Problems via Cluster-based Meta-features

Meta-features describe the characteristics of the datasets to facilitate algorithm selection. This paper proposes a new set of meta-features based on clustering the instances within datasets. We propose the use of a greedy clustering algorithm, and evaluate the meta-features generated based on the learning curves produced by the Random Forest algorithm. We also compared the utility of the proposed meta-features against preexisting meta-features described in the literature, and evaluated the applicability of these meta-features over a sample of UCI datasets. Our results show that these meta-features do indeed improve the performance when applied to the algorithm selection task.
Design and simulation of 10-bit SAR ADC for low power applications using 180nm technology

Analog-to-Digital converters plays vital role in medical and signal processing applications. Normally low power ADC's were required for long term and battery operated applications. SAR ADC is best suited for low power, medium resolution and moderate speed applications. This paper presents a 10-bit low power SAR ADC which is simulated in 180nm CMOS technology. Based on literature survey, low power consumption is attained by using Capacitive DAC. Capacitive DAC also incorporate Sample-and-Hold circuit in it. Dynamic latch comparator is used to increase in speed of operation and to get lower power consumption.
Error detection in content word combinations

This thesis addresses the task of error detection in the choice of content words focusing on adjective–noun and verb–object combinations. We show that error detection in content words is an under-explored area in research on learner language since (i) most previous approaches to error detection and correction have focused on other error types, and (ii) the approaches that have previously addressed errors in content words have not performed error detection proper. We show why this task is challenging for the existing algorithms and propose a novel approach to error detection in content words. We note that since content words express meaning, an error detection algorithm should take the semantic properties of the words into account. We use a compositional distribu-tional semantic framework in which we represent content words using their distributions in native English, while the meaning of the combinations is represented using models of com-positional semantics. We present a number of measures that describe different properties of the modelled representations and can reliably distinguish between the representations of the correct and incorrect content word combinations. Finally, we cast the task of error detection as a binary classification problem and implement a machine learning classifier that uses the output of the semantic measures as features. The results of our experiments confirm that an error detection algorithm that uses semantically motivated features achieves good accuracy and precision and outperforms the state-of-the-art approaches. We conclude that the features derived from the semantic representations encode important properties of the combinations that help distinguish the correct combinations from the incorrect ones. The approach presented in this work can naturally be extended to other types of content word combinations. Future research should also investigate how the error correction component for content word combinations could be implemented. 3 4 Acknowledgements First and foremost, I would like to express my profound gratitude to my supervisor, Ted Briscoe, for his constant support and encouragement throughout the course of my research. This work would not have been possible without his invaluable guidance and advice. I am immensely grateful to my examiners, Ann Copestake and Stephen Pulman, for providing their advice and constructive feedback on the final version of the dissertation. I am also thankful to my colleagues at the Natural Language and Information Processing research group for the insightful and inspiring discussions over these years. In particular, I would like to express my gratitude to would like to thank …
Minimal changes of serum creatinine predict prognosis in patients after cardiothoracic surgery: a prospective cohort study.

Acute renal failure increases risk of death after cardiac surgery. However, it is not known whether more subtle changes in renal function might have an impact on outcome. Thus, the association between small serum creatinine changes after surgery and mortality, independent of other established perioperative risk indicators, was analyzed. In a prospective cohort study in 4118 patients who underwent cardiac and thoracic aortic surgery, the effect of changes in serum creatinine within 48 h postoperatively on 30-d mortality was analyzed. Cox regression was used to correct for various established demographic preoperative risk indicators, intraoperative parameters, and postoperative complications. In the 2441 patients in whom serum creatinine decreased, early mortality was 2.6% in contrast to 8.9% in patients with increased postoperative serum creatinine values. Patients with large decreases (DeltaCrea <-0.3 mg/dl) showed a progressively increasing 30-d mortality (16 of 199 [8%]). Mortality was lowest (47 of 2195 [2.1%]) in patients in whom serum creatinine decreased to a maximum of -0.3 mg/dl; mortality increased to 6% in patients in whom serum creatinine remained unchanged or increased up to 0.5 mg/dl. Mortality (65 of 200 [32.5%]) was highest in patients in whom creatinine increased > or =0.5 mg/dl. For all groups, increases in mortality remained significant in multivariate analyses, including postoperative renal replacement therapy. After cardiac and thoracic aortic surgery, 30-d mortality was lowest in patients with a slight postoperative decrease in serum creatinine. Any even minimal increase or profound decrease of serum creatinine was associated with a substantial decrease in survival.
SPINE: SParse Interpretable Neural Embeddings

Prediction without justification has limited utility. Much of the success of neural models can be attributed to their ability to learn rich, dense and expressive representations. While these representations capture the underlying complexity and latent trends in the data, they are far from being interpretable. We propose a novel variant of denoising k-sparse autoencoders that generates highly efficient and interpretable distributed word representations (word embeddings), beginning with existing word representations from state-of-the-art methods like GloVe and word2vec. Through large scale human evaluation, we report that our resulting word embedddings are much more interpretable than the original GloVe and word2vec embeddings. Moreover, our embeddings outperform existing popular word embeddings on a diverse suite of benchmark downstream tasks.
Association between preterm brain injury and exposure to chorioamnionitis during fetal life

Preterm infants are susceptible to inflammation-induced white matter injury but the exposures that lead to this are uncertain. Histologic chorioamnionitis (HCA) reflects intrauterine inflammation, can trigger a fetal inflammatory response, and is closely associated with premature birth. In a cohort of 90 preterm infants with detailed placental histology and neonatal brain magnetic resonance imaging (MRI) data at term equivalent age, we used Tract-based Spatial Statistics (TBSS) to perform voxel-wise statistical comparison of fractional anisotropy (FA) data and computational morphometry analysis to compute the volumes of whole brain, tissue compartments and cerebrospinal fluid, to test the hypothesis that HCA is an independent antenatal risk factor for preterm brain injury. Twenty-six (29%) infants had HCA and this was associated with decreased FA in the genu, cingulum cingulate gyri, centrum semiovale, inferior longitudinal fasciculi, limbs of the internal capsule, external capsule and cerebellum (p < 0.05, corrected), independent of degree of prematurity, bronchopulmonary dysplasia and postnatal sepsis. This suggests that diffuse white matter injury begins in utero for a significant proportion of preterm infants, which focuses attention on the development of methods for detecting fetuses and placentas at risk as a means of reducing preterm brain injury.
Impact of exercise programs among helicopter pilots with transient LBP

Flight related low back pain (LBP) among helicopter pilots is frequent and may influence flight performance. Prolonged confined sitting during flights seems to weaken lumbar trunk (LT) muscles with associated secondary transient pain. Aim of the study was to investigate if structured training could improve muscular function and thus improve LBP related to flying.



39 helicopter pilots (35 men and 4 women), who reported flying related LBP on at least 1 of 3 missions last month, were allocated to two training programs over a 3-month period. Program A consisted of 10 exercises recommended for general LBP. Program B consisted of 4 exercises designed specifically to improve LT muscular endurance. The pilots were examined before and after the training using questionnaires for pain, function, quality of health and tests of LT muscular endurance as well as ultrasound measurements of the contractility of the lumbar multifidus muscle (LMM).



Approximately half of the participants performed the training per-protocol. Participants in this subset group had comparable baseline characteristics as the total study sample. Pre and post analysis of all pilots included, showed participants had marked improvement in endurance and contractility of the LMM following training. Similarly, participants had improvement in function and quality of health. Participants in program B had significant improvement in pain, function and quality of health.



This study indicates that participants who performed a three months exercise program had improved muscle endurance at the end of the program. The helicopter pilots also experienced improved function and quality of health.


 Registration date; February 5th, 2013, verified April 2016.
Aesthetic Depigmentation of Gingival Smoker's Melanosis Using Carbon Dioxide Lasers

Melanic pigmentation results from melanin produced by the melanocytes present in the basal layer of the oral epithelium. One of the most common causes of oral pigmentation is smoker melanosis, a condition associated with the melanocyte stimulation caused by cigarette smoke. This paper aims to illustrate the use of a carbon dioxide laser in the removal of the gingival melanic pigmentation for aesthetic reasons in a 27-year-old female patient with history of a smoking habit. The carbon dioxide laser vaporisation was performed on the gingival mucosa with effective and quick results and without any complications or significant symptoms after the treatment. We conclude that a carbon dioxide laser could be a useful, effective, and safe instrument to treat the aesthetic complications caused by oral smoker melanosis.
Effects of dose and formulation of carvacrol and thymol on bacteria and some functional traits of the gut in piglets after weaning.

Two trials were conducted to study the effects of dose and formulation of carvacrol and thymol on bacterial counts, metabolites and functional traits of the gut in weaned piglets. In the first experiment (Exp. I), 25 piglets (28 d, 6.59 +/- 0.48 kg BW) were allocated to five dietary treatments: a control diet, or the same diet supplemented with either carvacrol or thymol at doses of 500 and 2000 mg kg(-1). In the second experiment (Exp. II), 35 piglets (28 d, 7.99 +/- 0.73 kg BW) were assigned to seven dietary treatments: the same control diet as in Exp. I, or this diet supplemented with thymol in one of three formulations (on celite, on alphacel or microencapsulated) at doses of 500 and 2000 mg kg(-1). At 11/12 days post-weaning piglets were euthanised, and digesta from stomach, proximal and distal small intestine were sampled for bacteriological and biochemical analysis. Small intestinal tissue was sampled for histomorphological determinations. In none of the experiments or sections of the gut was the number of bacteria lowered by the carvacrol or thymol supplementation. In Exp. I, the villus/crypt ratio at the distal small intestine for the experimental diets (1.30-1.32) was higher than for the control diet (1.24) (p < 0.05). Thymol fed animals in Exp. II had a lower number of intra-epithelial lymphocytes at the proximal (p < 0.05) and at the distal (p < 0.1) small intestine as compared to control animals. Mean concentration of the active ingredient in the stomach and proximal small intestine for the 2000 mg kg(-1) carvacrol diet was 521 and 5 mg kg(-1) fresh digesta, respectively, and for the 2000 mg kg(-1) thymol diets it ranged between 475 and 647 and between 13 and 24 mg kg(-1) fresh digesta, respectively. Cumulative absorption in the proximal small intestine was higher than 90% for all treatments and was not affected by formulation type. These data suggest that carvacrol and thymol can improve gut health, but evidence for clear antimicrobial effects towards the major culturable bacteria of the pig foregut is limited.
Otherness in interior identity: a reflection about the Freudian concepts of unconscious, superego, and id.

Theoretical, psychoanalytical constructs referring to the unconscious, the superego, and id, enjoy an autonomy within the I. As such, this study contemplates the discussion of these foreign entities that inhabit the interior of the I, producing an effect of foreignness. In the first section, I will develop a reflection on the state of foreignness of the unconscious. I will begin with an analogy used by Freud, which addresses the thesis of universality of consciousness with the psychoanalytical thesis of the subconscience within the I. Affirmation of consciousness in the other may be used analogously for affirm the idea of another inhabiting our own being. I shall continue, seeking to understand how the process of unconscious repression produces the effect of foreignness. The idea of a moral censor present in the entity of the superego constitutes the theme of the second section. The superego follows the principle of otherness in its constitution and in its effects on the I. Finally, a reflection on the dimension of otherness in the Id seems urgent to me, as with this concept, Freud radicalized in the idea of the foreign as the origin of the subject.
Simulation of various natural phenomena based on computational fluid dynamics

Visual simulation of natural phenomena has become one of the most important research topics in computer graphics. Such phenomena include water, fire, smoke, clouds, and so on. Recent methods for the simulation of these phenomena utilize techniques developed in computational fluid dynamics. In this paper, the basic equations (Navier-Stokes equations) for simulating these phenomena are briefly described. These basic equations are used to simulate various natural phenomena. This paper then explains our applications of the equations for simulations of smoke, clouds, and aerodynamic sound.
Vertex Bisection is Hard, too

We settle an open problem mentioned in Diaz, Petit, and Serna: A survey of graph layout problems (ACM Computing Surveys 34:313–356, 2002). Of eight objectives considered in that survey, only the complexity status of minimum vertex bisection is listed as unknown. We show that both minimum and maximum vertex bisection are NP-hard, but polynomially solvable on special graph classes such as hypercubes and trees.  December 2005 Reviewed: April 2006  April 2007  February 2009 Final: February 2009  April 2009 Article type: Concise paper Communicated by: S. Albers E-mail addresses: Ulrik.Brandes@uni-konstanz.de (Ulrik Brandes) Daniel.Fleischer@uni-konstanz.de (Daniel Fleischer) 120 U. Brandes, D. Fleischer Vertex Bisection
Evaluating spoken dialogue systems according to de-facto standards: A case study

In the present paper, we investigate the validity and reliability of de-facto evaluation standards, defined for measuring or predicting the quality of the interaction with spoken dialogue systems. Two experiments have been carried out with a dialogue system for controlling domestic devices. During these experiments, subjective judgments of quality have been collected by two questionnaire methods (ITU-T Rec. P.851 and SASSI), and parameters describing the interaction have been logged and annotated. Both metrics served the derivation of prediction models according to the PARADISE approach. Although the limited database allows only tentative conclusions to be drawn, the results suggest that both questionnaire methods provide valid measurements of a large number of different quality aspects; most of the perceptive dimensions underlying the subjective judgments can also be measured with a high reliability. The extracted parameters mainly describe quality aspects which are directly linked to the system, environmental and task characteristics. Used as an input to prediction models, the parameters provide helpful information for system design and optimization, but not general predictions of system usability and acceptability.
DSets-DBSCAN: A Parameter-Free Clustering Algorithm

Clustering image pixels is an important image segmentation technique. While a large amount of clustering algorithms have been published and some of them generate impressive clustering results, their performance often depends heavily on user-specified parameters. This may be a problem in the practical tasks of data clustering and image segmentation. In order to remove the dependence of clustering results on user-specified parameters, we investigate the characteristics of existing clustering algorithms and present a parameter-free algorithm based on the DSets (dominant sets) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithms. First, we apply histogram equalization to the pairwise similarity matrix of input data and make DSets clustering results independent of user-specified parameters. Then, we extend the clusters from DSets with DBSCAN, where the input parameters are determined based on the clusters from DSets automatically. By merging the merits of DSets and DBSCAN, our algorithm is able to generate the clusters of arbitrary shapes without any parameter input. In both the data clustering and image segmentation experiments, our parameter-free algorithm performs better than or comparably with other algorithms with careful parameter tuning.
Kinetic analysis of the lower limbs during walking: what information can be gained from a three-dimensional model?

Kinetic analyses (joint moments, powers and work) of the lower limbs were performed during normal walking to determine what further information can be gained from a three-dimensional model over planar models. It was to be determined whether characteristic moment and power profiles exist in the frontal and transverse planes across subjects and how much work was performed in these planes. Kinetic profiles from nine subjects were derived using a three-dimensional inverse dynamics model of the lower limbs and power profiles were then calculated by a dot product of the angular velocities and joint moments resolved in a global reference system. Characteristic joint moment profiles across subjects were found for the hip, knee and ankle joints in all planes except for the ankle frontal moment. As expected, the major portion of work was performed in the plane of progression since the goal of locomotion is to support the body against gravity while generating movements which propel the body forward. However, the results also showed that substantial work was done in the frontal plane by the hip during walking (23% of the total work at that joint). The characteristic joint profiles suggest defined motor patterns and functional roles in the frontal and transverse planes. Kinetic analysis in three dimensions is necessary particularly if the hip joint is being examined as a substantial amount of work was done in the frontal plane of the hip to control the pelvis and trunk against gravitational forces.
Phishing through social bots on Twitter

This work investigates how social bots can phish employees of organizations, and thus endanger corporate network security. Current literature mostly focuses on traditional phishing methods (through e-mail, phone calls, and USB sticks). We address the serious organizational threats and security risks caused by phishing through online social media, specifically through Twitter. This paper first provides a review of current work. It then describes our experimental development, in which we created and deployed eight social bots on Twitter, each associated with one specific subject. For a period of four weeks, each bot published tweets about its subject and followed people with similar interests. In the final two weeks, our experiment showed that 437 unique users could have been phished, 33 of which visited our website through the network of an organization. Without revealing any sensitive or real data, the paper analyses some findings of this experiment and addresses further plans for research in this area.