Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Assessment of copy number variation using the Illumina Infinium 1M SNP-array: A comparison of methodological approaches in the Spanish Bladder Cancer/EPICURO study
Abstract: High‐throughput single nucleotide polymorphism (SNP)‐array technologies allow to investigate copy number variants (CNVs) in genome‐wide scans and specific calling algorithms have been developed to determine CNV location and copy number. We report the results of a reliability analysis comparing data from 96 pairs of samples processed with CNVpartition, PennCNV, and QuantiSNP for Infinium Illumina Human 1Million probe chip data. We also performed a validity assessment with multiplex ligation‐dependent probe amplification (MLPA) as a reference standard. The number of CNVs per individual varied according to the calling algorithm. Higher numbers of CNVs were detected in saliva than in blood DNA samples regardless of the algorithm used. All algorithms presented low agreement with mean Kappa Index (KI) <66. PennCNV was the most reliable algorithm (KIw=98.96) when assessing the number of copies. The agreement observed in detecting CNV was higher in blood than in saliva samples. When comparing to MLPA, all algorithms identified poorly known copy aberrations (sensitivity = 0.19–0.28). In contrast, specificity was very high (0.97–0.99). Once a CNV was detected, the number of copies was truly assessed (sensitivity >0.62). Our results indicate that the current calling algorithms should be improved for high performance CNV analysis in genome‐wide scans. Further refinement is required to assess CNVs as risk factors in complex diseases.Hum Mutat 32:1–10, 2011. © 2011 Wiley‐Liss, Inc.
Extracted statement — Algorithm: and QuantiSNP
Research field: Science
Title: Facultative catadromy of the eel Anguilla japonica between freshwater and seawater habitats
Abstract: To confirm the occurrence of marine residents of the Japanese eel, Anguilla japonica, which have never entered freshwater ('sea eels'), we measured Sr and Ca concentrations by X-ray electron microprobe analysis of the otoliths of 69 yellow and silver eels, collected from 10 localities in seawater and freshwater habitats around Japan, and classified their migratory histories. Two-dimen- sional images of the Sr concentration in the otoliths showed that all specimens generally had a high Sr core at the center of their otolith, which corresponded to a period of their leptocephalus and early glass eel stages in the ocean, but there were a variety of different patterns of Sr concentration and concentric rings outside the central core. Line analysis of Sr/Ca ratios along the radius of each otolith showed peaks (ca 15 × 10 -3 ) between the core and out to about 150 µm (elver mark). The pattern change of the Sr/Ca ratio outside of 150 µm indicated 3 general categories of migratory history: 'river eels', 'estuarine eels' and 'sea eels'. These 3 categories corresponded to mean values of Sr/Ca ratios of ≥ 6.0 × 10 -3 for sea eels, which spent most of their life in the sea and did not enter freshwater, of 2.5 to 6.0 × 10 -3 for estuarine eels, which inhabited estuaries or switched between different habitats, and of <2.5 × 10 -3 for river eels, which entered and remained in freshwater river habitats after arrival in the estuary. The occurrence of sea eels was 20% of all specimens examined and that of river eels, 23%, while estuarine eels were the most prevalent (57%). The occurrence of sea eels was confirmed at 4 localities in Japanese coastal waters, including offshore islands, a small bay and an estuary. The finding of estuarine eels as an intermediate type, which appear to frequently move between different habitats, and their presence at almost all localities, suggested that A. japonica has a flexible pattern of migration, with an ability to adapt to various habitats and salinities. Thus, anguillid eel migrations into freshwater are clearly not an obligatory migratory pathway, and this form of diadromy should be defined as facultative catadromy, with the sea eel as one of several ecophenotypes. Furthermore, this study indicates that eels which utilize the marine environment to various degrees during their juve- nile growth phase may make a substantial contribution to the spawning stock each year.
Extracted statement — Species Order: Anguilla japonica
Research field: Science
Title: Use of otolith Sr:Ca ratios to study the riverine migratory behaviors of Japanese eel Anguilla japonica
Abstract: To understand the migratory behavior and habitat use of the Japanese eel Anguilla japonica in the Kaoping River, SW Taiwan, the temporal changes of strontium (Sr) and calcium (Ca) contents in otoliths of the eels in combination with age data were examined by wavelength dispersive X-ray spectrometry with an electron probe microanalyzer. Ages of the eel were determined by the annulus mark in their otolith. The pattern of the Sr:Ca ratios in the otoliths, before the elver stage, was similar among all specimens. Post-elver stage Sr:Ca ratios indicated that the eels experienced different salinity histories in their growth phase yellow stage. The mean (±SD) Sr:Ca ratios in otoliths beyond elver check of the 6 yellow eels from the freshwater middle reach were 1.8 ± 0.2 x 10 -3 with a maximum value of 3.73 x 10 -3 . Sr:Ca ratios of less than 4 x 10-3 were used to discriminate the freshwater from seawater resident eels. Eels from the lower reach of the river were classified into 3 types: (1) freshwater contingents, Sr:Ca ratio <4 x 10 -3 , constituted 14 % of the eels examined; (2) seawater contingent, Sr:Ca ratio 5.1 ± 1.1 x 10-3 (5%); and (3) estuarine contingent, Sr:Ca ratios ranged from 0 to 10 x 10 -3 , with migration between freshwater and seawater (81 %). The frequency distribution of the 3 contingents differed between yellow and silver eel stages (0.01 < p < 0.05 for each case) and changed with age of the eel, indicating that most of the eels stayed in the estuary for the first year then migrated to the freshwater until 6 yr old. The eel population in the river system was dominated by the estuarine contingent, probably because the estuarine environment was more stable and had a larger carrying capacity than the freshwater middle reach did, and also due to a preference for brackish water by the growth-phase, yellow eel.
Extracted statement — Species Order: Anguilla japonica
Research field: Science
Title: Migratory behaviour and habitat use by American eels Anguilla rostrata as revealed by otolith microchemistry
Abstract: The environmental history of American eels Anguilla rostrata from the East River, Nova Scotia, was investigated by electron microprobe analysis of the Sr:Ca ratio along transects of the eel otolith. The mean (±SD) Sr:Ca ratio in the otoliths of juvenile American eels was 5.42 × 10 -3 ± 1.22 × 10 -3 at the elver check and decreased to 2.38 × 10 -3 ± 0.99 × 10 -3 at the first annulus for eels that migrated directly into the river but increased to 7.28 × 10 -3 ± 1.09 × 10 -3 for eels that had remained in the estuary for 1 yr or more before entering the river. At the otolith edge, Sr:Ca ratios of 4.0 × 10 -3 or less indicated freshwater residence and ratios of 5.0 × 10 -3 or more indicated estuarine residence. Four distinct but interrelated behavioural groups were identified by the temporal changes in Sr:Ca ratios in their otoliths: (1) entrance into freshwater as an elver, (2) coastal or estuarine residence for 1y r or more before entering freshwater, and, after entering freshwater, (3) continuous freshwater res- idence until the silver eel stage and (4) freshwater residence for 1 yr or more before engaging in peri- odic, seasonal movements between estuary and freshwater until the silver eel stage. Small (< 70 mm total length), highly pigmented elvers that arrived early in the elver run were confirmed as slow growing age-1 juvenile eels. Juvenile eels that remained 1 yr or more in the estuary before entering the river contributed to the production of silver eels to a relatively greater extent than did elvers that entered the river during the year of continental arrival.
Extracted statement — Species Order: Anguilla rostrata
Research field: Science
Title: Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data
Abstract: MOTIVATION Array Comparative Genomic Hybridization (CGH) can reveal chromosomal aberrations in the genomic DNA. These amplifications and deletions at the DNA level are important in the pathogenesis of cancer and other diseases. While a large number of approaches have been proposed for analyzing the large array CGH datasets, the relative merits of these methods in practice are not clear. RESULTS We compare 11 different algorithms for analyzing array CGH data. These include both segment detection methods and smoothing methods, based on diverse techniques such as mixture models, Hidden Markov Models, maximum likelihood, regression, wavelets and genetic algorithms. We compute the Receiver Operating Characteristic (ROC) curves using simulated data to quantify sensitivity and specificity for various levels of signal-to-noise ratio and different sizes of abnormalities. We also characterize their performance on chromosomal regions of interest in a real dataset obtained from patients with Glioblastoma Multiforme. While comparisons of this type are difficult due to possibly sub-optimal choice of parameters in the methods, they nevertheless reveal general characteristics that are helpful to the biological investigator.
Extracted statement — Platform: array CGH
Research field: Science
Title: Composition estimations in a middle-vessel batch distillation column using artificial neural networks
Abstract: A virtual sensor that estimates product compositions in a middle-vessel batch distillation column has been developed. The sensor is based on a recurrent artificial neural network, and uses information available from secondary measurements (such as temperatures and flow rates). The criteria adopted for selecting the most suitable training data set and the benefits deriving from pre-processing these data by means of principal component analysis are demonstrated by simulation. The effects of sensor location, model initialization, and noisy temperature measurements on the performance of the soft sensor are also investigated. It is shown that the estimated compositions are in good agreement with the actual values.
Extracted statement — Systems applied: Batch distillation
Research field: Science
Title: Dynamic modeling and optimal control of batch reactors, based on structure approaching hybrid neural networks
Abstract: A novel Structure Approaching Hybrid Neural Network (SAHNN) approach to model batch reactors is presented. The Virtual Supervisor−Artificial Immune Algorithm method is utilized for the training of SAHNN, especially for the batch processes with partial unmeasurable state variables. SAHNN involves the use of approximate mechanistic equations to characterize unmeasured state variables. Since the main interest in batch process operation is on the end-of-batch product quality, an extended integral square error control index based on the SAHNN model is applied to track the desired temperature profile of a batch process. This approach introduces model mismatches and unmeasured disturbances into the optimal control strategy and provides a feedback channel for control. The performance of robustness and antidisturbances of the control system are then enhanced. The simulation result indicates that the SAHNN model and model-based optimal control strategy of the batch process are effective.
Extracted statement — Systems applied: Batch reactor
Research field: Science
Title: One-Day Bayesian Cloning of Type 1 Diabetes Subjects: Toward a Single-Day UVA/Padova Type 1 Diabetes Simulator
Abstract: Objective: The UVA/Padova Type 1 Diabetes (T1DM) Simulator has been shown to be representative of a T1DM population observed in a clinical trial, but has not yet been identified on T1DM data. Moreover, the current version of the simulator is “single meal” while making it “single-day centric,” i.e., by describing intraday variability, would be a step forward to create more realistic in silico scenarios. Here, we propose a Bayesian method for the identification of the model from plasma glucose and insulin concentrations only, by exploiting the prior model parameter distribution. Methods: The database consists of 47 T1DM subjects, who received dinner, breakfast, and lunch (respectively, 80, 50, and 60 CHO grams) in three 23-h occasions (one openand one closed-loop). The model is identified using the Bayesian Maximum a Posteriori technique, where the prior parameter distribution is that of the simulator. Diurnal variability of glucose absorption and insulin sensitivity is allowed. Results: The model well describes glucose traces (coefficient of determination R2 = 0.962 ± 0.027) and the posterior parameter distribution is similar to that included in the simulator. Absorption parameters at breakfast are significantly different from those at lunch and dinner, reflecting more rapid dynamics of glucose absorption. Insulin sensitivity varies in each individual but without a specific pattern. Conclusion: The incorporation of glucose absorption and insulin sensitivity diurnal variability into the simulator makes it more realistic. Significance: The proposed method, applied to the increasing number of longterm artificial pancreas studies, will allow to describe week/month variability, thus further refining the simulator.
Extracted statement — Method: Bayesian method
Research field: Science
Title: Leveraging online social networks and external data sources to predict personality
Abstract: Over the past decade, people have been expressing more and more of their personalities online. Online social networks such as Facebook.com capture much of individuals' personalities through their published interests, attributes and social interactions. Knowledge of an individual's personality can be of wide utility, either for social research, targeted marketing or a variety of other fields A key problem to predicting and utilizing personality information is the myriad of ways it is expressed across various people, locations and cultures. Similarly, a model predicting personality based on online data which cannot be extrapolated to "real world" situations is of limited utility for researchers. This paper presents initial work done on generating a probabilistic model of personality which uses representations of people's connections to other people, places, cultures, and ideas, as expressed through Face book. To this end, personality was predicted using a machine learning method known as a Bayesian Network. The model was trained using Face book data combined with external data sources to allow further inference. The results of this paper present one predictive model of personality that this project has produced. This model demonstrates the potential of this methodology in two ways: First, it is able to explain up to 56% of all variation in a personality trait from a sample of 615 individuals. Second it is able to clearly present how this variability is explained through findings such as how to determine how agreeable a man is based on his age, number of Face book wall posts, and his willingness to disclose his preference for music made by Lady Gaga.
Extracted statement — Machine learning algorithms: Bayesian Network
Research field: Science
Title: Citizens’ adaptive or avoiding behavioral response to an emergency message on their mobile phone
Abstract: Abstract Since November 2012, Dutch civil defense organizations employ NL-Alert, a cellular broadcast-based warning system to inform the public. Individuals receive a message on their mobile phone about the actual threat, as well as some advice how to deal with the situation at hand. This study reports on the behavioral effects of NL-Alert (n = 643). The current risk communication literature suggested underlying mechanisms as perceived threat, efficacy beliefs, social norms, information sufficiency, and perceived message quality. Results indicate that adaptive behavior and behavioral avoidance can be predicted by subsets of these determinants. Affective and social predictors appear to be more important in this context that socio-cognitive predictors. Implications for the use of cellular broadcast systems like NL-Alert as a warning tool in emergency situations are discussed.
Extracted statement — paper: Theory / Construct / Model: Behavioral Avoidance
Research field: Science
Title: Citizens' adaptive or avoiding behavioral response to an emergency message on their mobile phone
Abstract: Abstract Since November 2012, Dutch civil defense organizations employ NL-Alert, a cellular broadcast-based warning system to inform the public. Individuals receive a message on their mobile phone about the actual threat, as well as some advice how to deal with the situation at hand. This study reports on the behavioral effects of NL-Alert (n = 643). The current risk communication literature suggested underlying mechanisms as perceived threat, efficacy beliefs, social norms, information sufficiency, and perceived message quality. Results indicate that adaptive behavior and behavioral avoidance can be predicted by subsets of these determinants. Affective and social predictors appear to be more important in this context that socio-cognitive predictors. Implications for the use of cellular broadcast systems like NL-Alert as a warning tool in emergency situations are discussed.
Extracted statement — paper: Theory / Construct / Model: Behavioral Avoidance
Research field: Science
Title: An Integrated Model and Solution Approach for Fleet Sizing with Heterogeneous Assets
Abstract: This paper addresses a fleet-sizing problem in the context of the truck-rental industry. Specifically, trucks that vary in capacity and age are utilized over space and time to meet customer demand. Operational decisions (including demand allocation and empty truck repositioning) and tactical decisions (including asset procurements and sales) are explicitly examined in a linear programming model to determine the optimal fleet size and mix. The method uses a time-space network, common to fleet-management problems, but also includes capital cost decisions, wherein assets of different ages carry different costs, as is common to replacement analysis problems. A two-phase solution approach is developed to solve large-scale instances of the problem. Phase I allocates customer demand among assets through Benders decomposition with a demand-shifting algorithm assuring feasibility in each subproblem. Phase II uses the initial bounds and dual variables from Phase I and further improves the solution convergence without increasing computer memory requirements through the use of Lagrangian relaxation. Computational studies are presented to show the effectiveness of the approach for solving large problems within reasonable solution gaps.
Extracted statement — Method: Benders decomposition
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 — Application Domain: biomedical journals
Research field: Science
Title: Syntactic segmentation and labeling of digitized pages from technical journals
Abstract: A method for extracting alternating horizontal and vertical projection profiles are from nested sub-blocks of scanned page images of technical documents is discussed. The thresholded profile strings are parsed using the compiler utilities Lex and Yacc. The significant document components are demarcated and identified by the recursive application of block grammars. Backtracking for error recovery and branch and bound for maximum-area labeling are implemented with Unix Shell programs. Results of the segmentation and labeling process are stored in a labeled x-y tree. It is shown that families of technical documents that share the same layout conventions can be readily analyzed. Results from experiments in which more than 20 types of document entities were identified in sample pages from two journals are presented. >
Extracted statement — Key Idea: block grammar
Research field: Science
Title: Omya Hustadmarmor optimizes its supply chain for delivering calcium carbonate slurry to European paper manufacturers
Abstract: The Norwegian company Omya Hustadmarmor supplies calcium carbonate slurry to European paper manufacturers from a single processing plant, using chemical tank ships of various sizes to transport its products. Transportation costs are lower for large ships than for small ships, but their use increases planning complexity and creates problems in production. In 2001, the company faced overwhelming operational challenges and sought operations-research-based planning support. The CEO, Sturla Steinsvik, contacted More Research Molde, which conducted a project that led to the development of a decision-support system (DSS) for maritime inventory routing. The core of the DSS is an optimization model that is solved through a metaheuristic-based algorithm. The system helps planners to make stronger, faster decisions and has increased predictability and flexibility throughout the supply chain. It has saved production and transportation costs close to US$7 million a year. We project additional direct savings of nearly US$4 million a year as the company adds even larger ships to the fleet as a result of the project. In addition, the company has avoided investments of US$35 million by increasing capacity utilization. Finally, the project has had a positive environmental effect by reducing overall oil consumption by more than 10 percent.
Extracted statement — Products: Calcium carbonate slurry
Research field: Science
Title: Factors impacting the intention to use emergency
notification services in campus emergencies: an empirical investigation
Abstract: Research problem: This study investigates the factors influencing students' intentions to use emergency notification services to receive news about campus emergencies through short-message systems (SMS) and social network sites (SNS). Research questions: (1) What are the critical factors that influence students' intention to use SMS to receive emergency notifications? (2) What are the critical factors that influence students' intention to use SNS to receive emergency notifications? Literature review: By adapting Media Richness theory and prior research on emergency notifications, we propose that perceived media richness, perceived trust in information, perceived risk, perceived benefit, and perceived social influence impact the intention to use SMS and SNS to receive emergency notifications. Methodology: We conducted a quantitative, survey-based study that tested our model in five different scenarios, using logistic regression to test the research hypotheses with 574 students of a large research university in the northeastern US. Results and discussion: Results suggest that students' intention to use SNS is impacted by media richness, perceived benefit, and social influence, while students' intention to use SMS is influenced by trust and perceived benefit. Implications to emergency managers suggest how to more effectively manage and market the service through both channels. The results also suggest using SNS as an additional means of providing emergency notifications at academic institutions.
Extracted statement — Emergency Type: Campus emergencies