Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Automated labeling in document images
Abstract: The National Library of Medicine (NLM) is developing an automated system to produce bibliographic records for its MEDLINER database. This system, named Medical Article Record System (MARS), employs document image analysis and understanding techniques and optical character recognition (OCR). This paper describes a key module in MARS called the Automated Labeling (AL) module, which labels all zones of interest (title, author, affiliation, and abstract) automatically. The AL algorithm is based on 120 rules that are derived from an analysis of journal page layouts and features extracted from OCR output. Experiments carried out on more than 11,000 articles in over 1,000 biomedical journals show the accuracy of this rule-based algorithm to exceed 96%.
Extracted statement — Logical Labels: abstract
Research field: Science
Title: Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data
Abstract: Abstract Background Genomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequently in unaffected individuals as polymorphisms. Affymetrix GeneChip whole genome sampling analysis (WGSA) combined with 100 K single nucleotide polymorphism (SNP) genotyping arrays is one of several microarray-based approaches that are now being used to detect such structural genomic changes. The popularity of this technology and its associated open source data format have resulted in the development of an increasing number of software packages for the analysis of copy number changes using these SNP arrays. Results We evaluated four publicly available software packages for high throughput copy number analysis using synthetic and empirical 100 K SNP array data sets, the latter obtained from 107 mental retardation (MR) patients and their unaffected parents and siblings. We evaluated the software with regards to overall suitability for high-throughput 100 K SNP array data analysis, as well as effectiveness of normalization, scaling with various reference sets and feature extraction, as well as true and false positive rates of genomic copy number variant (CNV) detection. Conclusion We observed considerable variation among the numbers and types of candidate CNVs detected by different analysis approaches, and found that multiple programs were needed to find all real aberrations in our test set. The frequency of false positive deletions was substantial, but could be greatly reduced by using the SNP genotype information to confirm loss of heterozygosity.
Extracted statement — Vendor: Affymetrix
Research field: Science
Title: Accuracy of CNV Detection from GWAS Data
Abstract: Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites—Birdsuite, Partek, HelixTree, and PennCNV-Affy—in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two “gold standards,” the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a “gold standard” for detection of CNVs remains to be established.
Extracted statement — Vendor: Affymetrix
Research field: Science
Title: TASC: topology adaptive spatial clustering for sensor networks
Abstract: The ability to extract topological regularity out of large randomly deployed sensor networks holds the promise to maximally leverage correlation for data aggregation and also to assist with sensor localization and hierarchy creation. This paper focuses on extracting such regular structures from physical topology through the development of a distributed clustering scheme. The topology adaptive spatial clustering (TASC) algorithm presented here is a distributed algorithm that partitions the network into a set of locally isotropic, non-overlapping clusters without prior knowledge of the number of clusters, cluster size and node coordinates. This is achieved by deriving a set of weights that encode distance measurements, connectivity and density information within the locality of each node. The derived weights form the terrain for holding a coordinated leader election in which each node selects the node closer to the center of mass of its neighborhood to become its leader. The clustering algorithm also employs a dynamic density reachability criterion that groups nodes according to their neighborhood's density properties. Our simulation results show that the proposed algorithm can trace locally isotropic structures in non-isotropic network and cluster the network with respect to local density attributes. We also found out that TASC exhibits consistent behavior in the presence of moderate measurement noise levels
Extracted statement — ole: Aggregation
Research field: Science
Title: Distributed Clustering-Based Aggregation Algorithm for Spatial Correlated Sensor Networks
Abstract: In wireless sensor networks, it is already noted that nearby sensor nodes monitoring an environmental feature typically register similar values. This kind of data redundancy due to the spatial correlation between sensor observations inspires the research of in-network data aggregation. In this paper, an α -local spatial clustering algorithm for sensor networks is proposed. By measuring the spatial correlation between data sampled by different sensors, the algorithm constructs a dominating set as the sensor network backbone used to realize the data aggregation based on the information description/summarization performance of the dominators. In order to evaluate the performance of the algorithm a pattern recognition scenario over environmental data is presented. The evaluation shows that the resulting network achieved by our algorithm can provide environmental information at higher accuracy compared to other algorithms.
Extracted statement — ole: Aggregation
Research field: Science
Title: Load-balanced clustering algorithm with distributed selforganization for wireless sensor networks
Abstract: Wireless sensor networks (WSNs) are composed of a large number of inexpensive power-constrained wireless sensor nodes, which detect and monitor physical parameters around them through self-organization. Utilizing clustering algorithms to form a hierarchical network topology is a common method of implementing network management and data aggregation in WSNs. Assuming that the residual energy of nodes follows the random distribution, we propose a load-balanced clustering algorithm for WSNs on the basis of their distance and density distribution, making it essentially different from the previous clustering algorithms. Simulated tests indicate that the new algorithm can build more balanceable clustering structure and enhance the network life cycle.
Extracted statement — ole: Aggregation
Research field: Science
Title: Kinetics of acetylcholinesterase immobilized on polyethylene tubing
Abstract: <jats:p> Acetylcholinesterase was covalently attached to the inner surface of polyethylene tubing. Initial oxidation generated surface carboxylic groups which, on reaction with thionyl chloride, produced acid chloride groups; these were caused to react with excess ethylenediamine. The amine groups on the surface were linked to glutaraldehyde, and acetylcholinesterase was then attached to the surface. Various kinetic tests showed the catalysis of the hydrolysis of acetylthiocholine iodide to be diffusion controlled. The apparent Michaelis constants were strongly dependent on flow rate and were much larger than the value for the free enzyme. Rate measurements over the temperature range 6–42 °C showed changes in activation energies consistent with diffusion control. </jats:p>
Extracted statement — Group that reacts
(with activated
matrix): amine
Research field: Science
Title: Decomposition of a Combined Inventory and Time Constrained Ship Routing Problem
Abstract: In contrast to vehicle routing problems, little work has been done in ship routing and scheduling, although large benefits may be expected from improving this scheduling process. We will present a real ship planning problem, which is a combined inventory management problem anda routing problem with time windows. A fleet of ships transports a single product (ammonia) between production and consumption harbors. The quantities loaded and discharged are determined by the production rates of the harbors, possible stock levels, and the actual ship visiting the harbor. We describe the real problem and the underlying mathematical model. To decompose this model, we discuss some model adjustments. Then, the problem can be solved by a DantzigÂ Wolfe decomposition approach including both ship routing subproblems and inventory management subproblems. The overall problem is solved by branch-and-bound. Our computational results indicate that the proposed method works for the real planning problem.
Extracted statement — Products: Ammonia
Research field: Science
Title: Software Cinema-Video-based Requirements Engineering
Abstract: The dialogue between end-user and developer presents several challenges in requirements development. One issue is the gap between the conceptual models of end-users and formal specification/analysis models of developers. This paper presents a novel technique for the video analysis of scenarios, relating the use of video-based requirements to process models of software development. It uses a knowledge model-an RDF graph-based on a semiotic interpretation of film language, which allows mapping conceptual into formal models. It can be queried with RDQL, a query language for RDF. The technique has been implemented with a tool which lets the analyst annotate objects as well as spatial or temporal relationships in the video, to represent the conceptual model. The video can be arranged in a scenario graph effectively representing a multi-path video. It can be viewed in linear time order to facilitate the review of individual scenarios by end-users. Each multi-path scene from the conceptual model is mapped to a UML use case in the formal model. A UML sequence diagram can also be generated from the annotations, which shows the direct mapping of film language to UML. This sequence diagram can be edited by the analyst, refining the conceptual model to reflect deeper understanding of the application domain. The use of the software cinema technique is demonstrated with several prototypical applications. One example is a loan application scenario for a financial services consulting firm which acted as an end-user
Extracted statement — Application : application
Research field: Science
Title: Fast Algorithms for Mining Association Rules
Abstract: We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving thii problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems. We also show how the best features of the two proposed algorithms can be combined into a hybrid algorithm, called AprioriHybrid. Scale-up experiments show that AprioriHybrid scales linearly with the number of transactions. AprioriHybrid also has excellent scale-up properties with respect to the transaction size and the number of items in the database.
Extracted statement — Algorithm name: AprioriHybrid
Research field: Science
Title: Relationship between sports drinks and dental erosion in 304 university athletes in Columbus
Abstract: Acidic soft drinks, including sports drinks, have been implicated in dental erosion with limited supporting data in scarce erosion studies worldwide. The purpose of this study was to determine the prevalence of dental erosion in a sample of athletes at a large Midwestern state university in the USA, and to evaluate whether regular consumption of sports drinks was associated with dental erosion. A cross-sectional, observational study was done using a convenience sample of 304 athletes, selected irrespective of sports drinks usage. The Lussi Index was used in a blinded clinical examination to grade the frequency and severity of erosion of all tooth surfaces excluding third molars and incisal surfaces of anterior teeth. A self-administered questionnaire was used to gather details on sports drink usage, lifestyle, health problems, dietary and oral health habits. Intraoral color slides were taken of all teeth with erosion. Sports drinks usage was found in 91.8% athletes and the total prevalence of erosion was 36.5%. Nonparametric tests and stepwise regression analysis using history variables showed no association between dental erosion and the use of sports drinks, quantity and frequency of consumption, years of usage and nonsport usage of sports drinks. The most significant predictor of erosion was found to be not belonging to the African race (p < 0.0001). The results of this study reveal no relationship between consumption of sports drinks and dental erosion.
Extracted statement — Study population: Athletes
Research field: Science
Title: Robust Facial Features Localization on Rotation Arbitrary Multi-View face in Complex Background
Abstract: Focused on facial features localization on multi-view face arbitrarily rotated in plane, a novel detection algorithm based improved SVM is proposed. First, the face is located by the rotation invariant multi-view (RIMV) face detector and its pose in plane is corrected by rotation. After the searching ranges of the facial features are determined, the crossing detection method which uses the brow-eye and nose-mouth features and the improved SVM detectors trained by large scale multi-view facial features examples is adopted to find the candidate eye, nose and mouth regions,. Based on the fact that the window region with higher value in the SVM discriminant function is relatively closer to the object, and the same object tends to be repeatedly detected by near windows, the candidate eyes, nose and mouth regions are filtered and merged to refine their location on the multi-view face. Experiments show that the algorithm has very good accuracy and robustness to the facial features localization with expression and arbitrary face pose in complex background.
Extracted statement — Challenges: Background
Research field: Science
Title: Falcon 2.0: An Entity and Relation Linking Tool over Wikidata
Abstract: The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from a natural language text, and possibly linking them to proper matches in Knowledge Graphs (KGs). Considering Wikidata as the background KG, there are still limited tools to link knowledge within the text to Wikidata. In this paper, we present Falcon 2.0, the first joint entity and relation linking tool over Wikidata. It receives a short natural language text in the English language and outputs a ranked list of entities and relations annotated with the proper candidates in Wikidata. The candidates are represented by their Internationalized Resource Identifier (IRI) in Wikidata. Falcon 2.0 resorts to the English language model for the recognition task (e.g., N-Gram tiling and N-Gram splitting), and then an optimization approach for the linking task. We have empirically studied the performance of Falcon 2.0 on Wikidata and concluded that it outperforms all the existing baselines. Falcon 2.0 is open source and can be reused by the community; all the required instructions of Falcon 2.0 are well-documented at our GitHub repository (https://github.com/SDM-TIB/falcon2.0). We also demonstrate an online API, which can be run without any technical expertise. Falcon 2.0 and its background knowledge bases are available as resources at https://labs.tib.eu/falcon/falcon2/.
Extracted statement — contains: Background
Research field: Science
Title: A synergistic chlorhexidine/chitosan combination for improved antiplaque strategies
Abstract: BACKGROUND The minor efficacy of chlorhexidine (CHX) on other cariogenic bacteria than mutans streptococci such as Streptococcus sanguinis may contribute to uneffective antiplaque strategies. METHODS AND RESULTS In addition to CHX (0.1%) as positive control and saline as negative control, two chitosan derivatives (0.2%) and their CHX combinations were applied to planktonic and attached sanguinis streptococci for 2 min. In a preclinical biofilm model, the bacteria suspended in human sterile saliva were allowed to attach to human enamel slides for 60 min under flow conditions mimicking human salivation. The efficacy of the test agents on streptococci was screened by the following parameters: vitality status, colony-forming units (CFU)/ml and cell density on enamel. The first combination reduced the bacterial vitality to approximately 0% and yielded a strong CFU reduction of 2-3 log(10) units, much stronger than CHX alone. Furthermore, the first chitosan derivative showed a significant decrease of the surface coverage with these treated streptococci after attachment to enamel. CONCLUSIONS Based on these results, a new CHX formulation would be beneficial unifying the bioadhesive properties of chitosan with the antibacterial activity of CHX synergistically resulting in a superior antiplaque effect than CHX alone.
Extracted statement — Advantages: Bioadhesive
Research field: Science
Title: Artificial neural networks to infer biomass and product concentration during the production of penicillin G acylase from Bacillus megaterium
Abstract: BACKGROUND: Production of microbial enzymes in bioreactors is a complex process including such phenomena as metabolic networks and mass transport resistances. The use of neural networks (NNs) to infer the state of bioreactors may be an interesting option that may handle the nonlinear dynamics of biomass growth and protein production. RESULTS: Feedforward multilayer perceptron (MLP) NNs were used for identification of the cultivation phase of Bacillus megaterium to produce the enzyme penicillin G acylase (EC. 3.5.1.11). The following variables were used as input to the net: run time and carbon dioxide concentration in the exhausted gas. The NN output associates a numerical value to the metabolic state of the cultivation, close to 0 during the lag phase, close to 1 during the exponential phase and approximately 2 for the stationary phase. This is a non-conventional approach for pattern recognition. During the exponential phase, another MLP was used to infer cellular concentration. Time, carbon dioxide concentration and stirrer speed form an integrated net input vector. Cellular concentrations provided by the NN were used in a hybrid approach to estimate product concentrations of the enzyme. The model employed a first-order approximation. CONCLUSION: Results showed that the algorithm was able to infer accurate values of cellular and product concentrations up to the end of the exponential growth phase, where an industrial run should stop. Copyright © 2008 Society of Chemical Industry
Extracted statement — Systems applied: Bioreactor
Research field: Science
Title: Accuracy of CNV Detection from GWAS Data
Abstract: Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites—Birdsuite, Partek, HelixTree, and PennCNV-Affy—in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two “gold standards,” the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a “gold standard” for detection of CNVs remains to be established.
Extracted statement — Algorithm: Birdsuite
Research field: Science
Title: Document image segmentation and text area ordering
Abstract: A system for document image segmentation and ordering text areas is described and applied to both Japanese and English complex printed page layouts. There is no need to make any assumption about the shape of blocks, hence the segmentation technique can handle not only skewed images without skew-correction but also documents where column are not rectangular. In this technique, on the bottom-up strategy, the connected components are extracted from the reduced image, and classified according to their local information. The connected components are merged into lines, and lines are merged into areas. Extracted text areas are classified as body, caption, header, and footer. A tree graph of the layout of body texts is made, and we get the order of texts by preorder traversal on the graph. The authors introduce the influence range of each node, a procedure for the title part, and extraction of the white horizontal separator. Making it possible to get good results on various documents. The total system is fast and compact.<<ETX>>
Extracted statement — Logical Labels: body