LLukas22/scidocs huggingface dataset:
Active cleaning of label noise

Mislabeled examples in the training data can severely affect the performance of supervised classifiers. In this paper, we present an approach to remove any mislabeled examples in the dataset by selecting suspicious examples as targets for inspection. We show that the large margin and soft margin principles used in support vector machines (SVM) have the characteristic of capturing the mislabeled examples as support vectors. Experimental results on two character recognition datasets show that one-class and two-class SVMs are able to capture around 85% and 99% of label noise examples, respectively, as their support vectors. We propose another new method that iteratively builds two-class SVM classifiers on the non-support vector examples from the training data followed by an expert manually verifying the support vectors based on their classification score to identify any mislabeled examples. We show that this method reduces the number of examples to be reviewed, as well as providing parameter independence of this method, through experimental results on four data sets. So, by (re-)examining the labels of the selective support vectors, most noise can be removed. This can be quite advantageous when rapidly building a labeled data set. & 2015 Elsevier Ltd. All rights reserved.
Bilateral Choanal Atresia with Tessier Type 3 Facial Cleft: A Rare Association

Five-day-old male neonate born to non-consanguineous parents by normal vaginal delivery was presented with deformity of lip, face and eyelid on the right side, and cyanosis. The cyanosis had improved soon after endotracheal intubation. Examination revealed deformity of upper lip, upper jaw and lower eyelid of right eye; this type of craniofacial cleft is called as Tessier type 3 (Fig. 1). There was associated bilateral choanal atresia. The baby accidently self-extubated himself after 2 days, but could maintain thereafter with oxygen administration through hood. We plan to manage choanal atresia endoscopically at least on one side first before undertaking the reconstruction of the facial cleft part.
Association of Versican Turnover with All-Cause Mortality in Patients on Haemodialysis

OBJECTIVE
Cardiovascular diseases are among the most common causes of mortality in renal failure patients undergoing haemodialysis. A high turnover rate of the proteoglycan versican, represented by the increased presence of its fragmentation products in plasma, has previously been associated with cardiovascular diseases. The objective of the study was to investigate the association of versican turnover assessed in plasma with survival in haemodialysis patients.


METHODS
A specific matrix metalloproteinase-generated neo-epitope fragment of versican (VCANM) was measured in plasma of 364 haemodialysis patients with a 5-years follow-up, using a robust competitive enzyme-linked immunosorbent assays. Association between VCANM plasma concentration and survival was assessed by Kaplan-Meier analysis and adjusted Cox model.


RESULTS
Haemodialysis patients with plasma VCANM concentrations in the lowest quartile had increased risk of death (odds ratio, as compared to the highest quartile: 7.1, p<0.001), with a reduced survival of 152 days compared to 1295 days for patients with plasma VCANM in the highest quartile. Multivariate analysis showed that low VCANM (p<0.001) and older age (p<0.001) predicted death in haemodialysis patients.


CONCLUSIONS
Low concentrations of the versican fragment VCANM in plasma were associated with higher risk of death among haemodialysis patients. A possible protective role for the examined versican fragment is suggested.
A two-step system for direct bank telemarketing outcome classification

Intell Sys Acc Fin Mgmt. 2017;24:49–55. Summary A two‐step system is presented to improve prediction of telemarketing outcomes and to help the marketing management team effectively manage customer relationships in the banking industry. In the first step, several neural networks are trained with different categories of information to make initial predictions. In the second step, all initial predictions are combined by a single neural network to make a final prediction. Particle swarm optimization is employed to optimize the initial weights of each neural network in the ensemble system. Empirical results indicate that the two‐ step system presented performs better than all its individual components. In addition, the two‐ step system outperforms a baseline one where all categories of marketing information are used to train a single neural network. As a neural networks ensemble model, the proposed two‐step system is robust to noisy and nonlinear data, easy to interpret, suitable for large and heterogeneous marketing databases, fast and easy to implement.
Soziale Ungleichheit des Rauchverhaltens in Deutschland

Anhand von Daten des Bundes-Gesundheitssurveys 1998 wird der Einfluss alternativer Indikatoren sozialer Ungleichheit auf das Rauchverhalten der 18- bis 79-jährigen Bevölkerung in Deutschland untersucht. Danach rauchen die Angehörigen sozial benachteiligter Bevölkerungsgruppen nicht nur häufiger, ihnen fällt es offenbar auch schwerer, das Rauchen wieder aufzugeben. Besonders deutlich kommt dies im mittleren Lebensalter zum Ausdruck, während im höheren Alter nur noch schwache Unterschiede beobachtet werden können. Multivariate Analysen weisen bei Männern wie Frauen vor allem die Schulbildung als Determinante des Rauchverhaltens aus. Der Einfluss des Einkommens und der beruflichen Stellung ist vergleichsweise gering. Die Ergebnisse sprechen dafür, dass die im Gesundheitsstatus und in der Lebenserwartung zutage tretende Chancenungleichheit zu einem Teil auf unterschiedliche Rauchgewohnheiten zurückzuführen ist, und unterstreichen damit die Notwendigkeit zielgruppenspezifischer Interventionen der Tabakprävention und Tabakkontrollpolitik. Data of the National Health Survey 1998 are used to analyze the impact of alternative indicators of social inequality on smoking of the 18- to 79-year-old population in Germany. The members of socially disadvantaged groups not only smoke more frequently, they show also lower rates in smoking cessation. This is most obvious in middle age while only small differences can be observed at older ages. Multivariate analyses evidence primarily education as a determinant of smoking among men and women. The effects of income and occupational status are fairly small. The results point out that health inequalities can partly be explained by different smoking habits and, therefore, underline the necessity of a differentiated and group-specific tobacco prevention and tobacco control policy.
Online travel reviews as persuasive communication : The effects of content type , source , and certi fi cation logos on consumer behavior

We use an online travel context to test three aspects of communication
A transformable wheel robot with a passive leg

In this paper, we present a novel wheeled robot that transforms from a circled configuration to a spoke-like legged configuration. Wheeled mobile robots are able to quickly and efficiently move on flat surfaces. However they may sink into a terrain with dynamic surface such as snow, sand, dirt, moss, and small gravel. The transformable wheel robot presented in this paper is able to overcome obstacles and navigate these dynamics surfaces, yet can still move quickly over flat ground. The wheel is comprised of five spokes or legs, four of which are actively driven by a motor via four slider-crank linkages. The last one is designed be passive in order to significantly decrease the actuation force of the transformer mechanism. Analysis shows that the maximum driving force required to actuate the passive leg design is 1/187.5 times that of the active leg design. Experiments demonstrate that the passive leg design allows the mobile robot to open the transformation mechanism with a maximum external loading of 1.809 times the original robot weight. The diameter of the legged configuration wheel is 1.576 times that of the circled configuration.
On Organizational Becoming: Rethinking Organizational Change

Traditional approaches to organizational change have been dominated by assumptions privileging stability, routine, and order. As a result, organizational change has been reified and treated as exceptional rather than natural. In this paper, we set out to offer an account of organizational change on its own terms—to treat change as the normal condition of organizational life. The central question we address is as follows: What must organization(s) be like if change is constitutive of reality? Wishing to highlight the pervasiveness of change in organizations, we talk about organizational becoming. Change, we argue, is the reweaving of actors’ webs of beliefs and habits of action to accommodate new experiences obtained through interactions. Insofar as this is an ongoing process, that is to the extent actors try to make sense of and act coherently in the world, change is inherent in human action, and organizations are sites of continuously evolving human action. In this view, organization is a secondary accomplishment, in a double sense. Firstly, organization is the attempt to order the intrinsic flux of human action, to channel it towards certain ends by generalizing and institutionalizing particular cognitive representations. Secondly, organization is a pattern that is constituted, shaped, and emerging from change. Organization aims at stemming change but, in the process of doing so, it is generated by it. These claims are illustrated by drawing on the work of several organizational ethnographers. The implications of this view for theory and practice are outlined. (Continuous Change; Routines; Process; Improvization; Reflexivity; Emergence; Interaction; Experience) The point is that usually we look at change but we do not see it. We speak of change, but we do not think about it. We say that change exists, that everything changes, that change is the very law of things: Yes, we say it and we repeat it; but those are only words, and we reason and philosophize as though change did not exist. In order to think change and see it, there is a whole veil of prejudices to brush aside, some of them artificial, created by philosophical speculation, the others natural
A research agenda for highly effective human-computer interaction: useful, usable, and universal

Foreword: The ACM SIGCHI (Association for Computing Machinery Special Interest Group in Computer Human Interaction) community conducted a deliberative process involving a high-visibility committee, a day-long workshop at CHI99 (Pittsburgh, PA, May 15, 1999) and a collaborative authoring process. This interim report is offered to produce further discussion and input leading to endorsement by the SIGCHI Executive Committee and then other professional societies. The scope of this research agenda included advanced information and communications technology research that could yield benefits over the next two to five years.
Novel metaphor comprehension: Semantic neighbourhood density interacts with concreteness.

Previous research suggests that metaphor comprehension is affected both by the concreteness of the topic and vehicle and their semantic neighbours (Kintsch, 2000; Xu, 2010). However, studies have yet to manipulate these 2 variables simultaneously. To that end, we composed novel metaphors manipulated on topic concreteness and semantic neighbourhood density (SND) of topic and vehicle. In Experiment 1, participants rated the metaphors on the suitability (e.g. sensibility) of their topic-vehicle pairings. Topic concreteness interacted with SND such that participants rated metaphors from sparse semantic spaces to be more sensible than those from dense semantic spaces and preferred abstract topics over concrete topics only for metaphors from dense semantic spaces. In Experiments 2 and 3, we used presentation deadlines and found that topic concreteness and SND affect the online processing stages associated with metaphor comprehension. We discuss how the results are aligned with established psycholinguistic models of metaphor comprehension.
REVIEW OF SOME PROCESSES FOR CERAMIC‐TO‐METAL JOINING

Abstract Various methods are discussed for the joining of ceramics to metals and vice versa. State‐of‐the‐art techniques including refractory metallizations and active metal brazing are detailed from both a processing and applications standpoint. Various approaches to forming ceramic/metal joints or thin film coatings have been developed over the years to address the need to combine the properties of both types of materials for both electrical and structural applications. These methods address not only physical and chemical compatibility concerns but also the need for bonds between dissimilar materials to survive the rigors of use generated by such inevitable mismatches as can be found in expansion, elastic, reactive and thermal cycling behavior.
2-2013 Only if it is Convenient : Understanding How Convenience Influences Self-Service Technology Evaluation

Self-service technologies (SSTs) can help firms reduce labor costs while providing more channel options, but customers must be convinced of their value before foregoing a full service alternative. To understand how customers evaluate an SST, the authors conducted three studies to analyze the importance of convenience in the evaluation process along with exploring what constructs ultimately influence customers’ need for human interaction with an SST. Surveying both users’ experiences with an SST and also nonusers’ perceptions of an SST, a comprehensive analysis was undertaken to assess the perceived benefits of using an SST. In Study 1, the authors found that convenience had a strong positive effect on the perceived accuracy, speed, and exploration intentions of an SST. Building on these results, Studies 2 and 3 reveal that SST users have a lower need for interaction when they are satisfied with an SST, while nonusers’ trust perceptions had the greatest influence on the need for human interaction during an SST transaction. The authors discovered that user satisfaction can be enhanced by focusing on the speed and accuracy of an SST, whereas nonusers’ perceptions of accuracy and exploration increased the trust placed in an SST.
Hierarchical Implicit Models and Likelihood-Free Variational Inference

Implicit probabilistic models are a flexible class of models defined by a simulation process for data. They form the basis for theories which encompass our understanding of the physical world. Despite this fundamental nature, the use of implicit models remains limited due to challenges in specifying complex latent structure in them, and in performing inferences in such models with large data sets. In this paper, we first introduce hierarchical implicit models (HIMs). HIMs combine the idea of implicit densities with hierarchical Bayesian modeling, thereby defining models via simulators of data with rich hidden structure. Next, we develop likelihood-free variational inference (LFVI), a scalable variational inference algorithm for HIMs. Key to LFVI is specifying a variational family that is also implicit. This matches the model’s flexibility and allows for accurate approximation of the posterior. We demonstrate diverse applications: a large-scale physical simulator for predator-prey populations in ecology; a Bayesian generative adversarial network for discrete data; and a deep implicit model for text generation.
Using institutional theory and dynamic simulation to understand complex e-Government phenomena

Available online 17 May 2011
Three-body wear potential of dental yttrium-stabilized zirconia ceramic after grinding, polishing, and glazing treatments.

STATEMENT OF PROBLEM
Zirconia complete-coverage crowns are being widely used as restorations because of their improved esthetic characteristics. Data about the enamel wear potential of this ceramic after chair side adjustments are sparse.


PURPOSE
The purpose of this study was to investigate the 3-body wear of enamel opposing 3 types of ceramic (dense sintered yttrium-stabilized zirconia; Crystal Zirconia; DLMS) (Z), a lithium disilicate (IPS e-max CAD; Ivoclar Vivadent) (E), and a conventional low-fusing feldspathic porcelain (VitaVMK-Master; Vita Zahnfabrik) (P), treated to impart a rough, smooth, or glazed surface.


MATERIAL AND METHODS
Twenty-four specimens of each of the zirconia and the lithium disilicate ceramic were sectioned from computer-aided design and computer-aided manufacturing blocks into rectangular plates (15×12×2 mm). Twenty-four specimens of the feldspathic porcelain were formed into disks (12 mm diameter) from powders compressed in a silicone mold. All specimens (n=72) were prepared according to the manufacturers' recommendations. Specimens of each ceramic group were placed into 1 of 3 groups: group R, rough surface finish; group S, smooth surface finish; and group G, glazed surface finish. A total of 9 groups with 8 specimens each were placed in a 3-body wear simulator, with standardized enamel specimens (n=72) acting as the substrate. The wear of the enamel specimens was evaluated after 50,000 cycles. The data were analyzed with 2-way ANOVA and the Tukey HSD multiple comparison test (α=.05).


RESULTS
The data showed that the smooth zirconia group (ZS) was associated with the least amount of enamel wear (1.26 ±0.55 mm(2)). The most antagonistic enamel wear was associated with the glazed groups ZG (5.58 ±0.66 mm(2)), EG (3.29 ±1.29 mm(2)), and PG (4.2 ±1.27 mm(2)).


CONCLUSIONS
The degree of enamel wear associated with monolithic zirconia was similar to conventional feldspathic porcelain. Smoothly polished ceramic surfaces resulted in less wear of antagonistic enamel than glazing.
Alpha-synuclein: Pathology, mitochondrial dysfunction and neuroinflammation in Parkinson’s disease

Parkinson's disease (PD) is a complex, chronic and progressive neurodegenerative disease. While the etiology of PD is likely multifactorial, the protein α-synuclein is a central component to the pathogenesis of the disease. However, the mechanism by which α-synuclein causes toxicity and contributes to neuronal death remains unclear. Mitochondrial dysfunction is also widely considered to play a major role in the underlying mechanisms contributing to neurodegeneration in PD. This review discusses evidence for the neuropathological role for α-synuclein in the dysfunction of dopamine neurons in PD. We also discuss insights into the structure, localization, and cellular roles for α-synuclein that may influence its aggregation properties, ultimately impacting its pathogenicity, role in lysosomal dysfunction and activation of the neuroimmune response. We further highlight recent evidence linking α-synuclein and mitochondrial dysfunction in neurodegeneration. Identifying the underlying mechanisms responsible for this bi-directional relationship between α-synuclein and mitochondrial dysfunction may provide new insights into the pathophysiology of PD.
ART 2 - an unsupervised neural network for PD pattern recognition and classification

This paper introduces a method of classifying partial discharges of unknown origin. The innovative trend of using Artificial Neural Network (ANN) towards classification of Partial Discharge (PD) patterns is cogent and discernible. The Adaptive Resonance Theory (ART), a type of neural network which is suitable for PD pattern recognition is explained here. To ensure the suitability and reliability of chosen network for PD pattern recognition, the network is tested with the well known Iris plant database and alphabet character for recognition & classification. Further more the network is trained with various combinations off–q–n distributions of PD patterns and tested. It is shown that the ART 2 network is able to classify the PD patterns. The paper ends with analyzing the efficacy of multifarious features selected in the measurement space. Also the validation of input features is done using ‘Hold-One-Out’ method and partial set training technique q 2005 Elsevier Ltd. All rights reserved.
AMS 4.0: consensus prediction of post-translational modifications in protein sequences

We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The source code and precompiled binaries of brainstorming tool are available at http://code.google.com/p/automotifserver/ under Apache 2.0 licensing.
Indian Currency Note Denomination Recognition in Color Images

It has been estimated that every five seconds, a person in the world goes blind. These visually impaired people have a reduced perception of the world around them and thus face a lot of difficulty in carrying out their day to day tasks. Even their problems go unnoticed from the sight of the normal people. The Indian currency notes have a size difference of just ten mm between two consecutive denominations and make it highly unlikely for a blind person to determine it correctly. Also, the new one rupee coin has the same shape and size as was of the old fifty paisa coin while both are in circulation and hence have become undistinguishable now. These problems make visually impaired people unable to do everyday transactions easily. As a part of currency recognition system for visually impaired, we have already developed an efficient currency note localization algorithm that localizes currency notes in color images. This paper uses the localized regions of the image and feeds it into the recognition module for determination of the denomination of currency note. We here present the developed technique to recognize the denomination of the Indian currency note from the color image and the results obtained, thereafter.